From 5babdfcf937f7bd63dfc4cef7d4ebabc0087402f Mon Sep 17 00:00:00 2001
From: Brody <wacker.brody@gmail.com>
Date: Wed, 19 Feb 2020 20:50:54 -0500
Subject: [PATCH 1/3] adding ffm returns to selection dataframes

---
 .ipynb_checkpoints/ffmreturns-checkpoint      | 100 +++
 .../selection_criteria-checkpoint.ipynb       | 775 +++++++++++++-----
 .../selection_data-checkpoint.csv             |  93 ---
 ffmreturns.csv                                | 101 +++
 selection_criteria.ipynb                      | 775 +++++++++++++-----
 selection_data.csv                            | 186 ++---
 6 files changed, 1426 insertions(+), 604 deletions(-)
 create mode 100644 .ipynb_checkpoints/ffmreturns-checkpoint
 delete mode 100644 .ipynb_checkpoints/selection_data-checkpoint.csv
 create mode 100644 ffmreturns.csv

diff --git a/.ipynb_checkpoints/ffmreturns-checkpoint b/.ipynb_checkpoints/ffmreturns-checkpoint
new file mode 100644
index 0000000..5bced18
--- /dev/null
+++ b/.ipynb_checkpoints/ffmreturns-checkpoint
@@ -0,0 +1,100 @@
+ADBE,0.3297610282865694
+MSFT,0.3225006496044267
+CTAS,0.2859733002204454
+BBY,0.2640730920141721
+SNPS,0.25897876742285353
+FISV,0.24990297848444798
+UNH,0.24309382373184238
+FB,0.23878909384322328
+RMD,0.23631678016476249
+AAPL,0.23604932199955078
+MCO,0.23485811677381752
+BSX,0.23386062128084006
+BA,0.23323612695525472
+MTD,0.2328952696179387
+MSI,0.23146830458678086
+OKE,0.23014778207879386
+NEE,0.22798619050096225
+ACN,0.225818128420618
+TXN,0.22491230637789683
+TMO,0.22339609173340735
+GOOGL,0.21463984288683724
+DXC,0.21090615329816487
+NRG,0.20866969560486595
+CRM,0.20747020399236582
+CINF,0.19983786702761977
+RCL,0.19565944392066684
+AJG,0.19558301781587423
+RTN,0.19479613991497
+FMC,0.19386685693474592
+COST,0.1921299735178258
+NEM,0.18968579649834488
+TGT,0.1850698189348571
+ADP,0.18326947581738273
+AON,0.18316741852219454
+SBUX,0.17774496669754897
+HII,0.1723097618928521
+HLT,0.17104685108303183
+LNT,0.16624432746404136
+IT,0.16521374355769894
+PHM,0.16513204010023563
+CCI,0.16397523743042758
+AES,0.16265380753609693
+RJF,0.1550462998103735
+APD,0.15316088144652082
+AMGN,0.15174865810801244
+MRK,0.1470158610669735
+MGM,0.14633287861111777
+GWW,0.14375378284097465
+EFX,0.14091486053075086
+AXP,0.1322522270329868
+ALB,0.13220722861896406
+HOLX,0.12996771202046364
+FE,0.1299095587244921
+VFC,0.12911080366775834
+ETN,0.12899826119201457
+HSY,0.12508534205222416
+WMT,0.12505470711955646
+MDT,0.12421349008442331
+LKQ,0.12177166088583005
+CNP,0.12150168720845926
+PEP,0.11793526453693497
+COF,0.11610429860555255
+EIX,0.11470824011644254
+LUV,0.10783286161659233
+KO,0.10382014867597877
+LYB,0.1035124663018064
+GS,0.09991453877165773
+KMX,0.09928523351871378
+PPL,0.09823927431199717
+SYF,0.09183609795442904
+EQR,0.08949458007993966
+EXPE,0.0862855530385388
+GM,0.08449462028501559
+BMY,0.08317680705161642
+ORCL,0.0773501478844939
+INCY,0.07679309483980977
+GPC,0.07422802537055226
+IRM,0.07306073071186923
+FFIV,0.0649893956263632
+GIS,0.06314688753298886
+DISCK,0.06155249624087282
+HST,0.052833241856252385
+RL,0.0462670767467909
+FCX,0.03864626404421445
+NWS,0.025555928100843527
+FDX,0.024253909510178945
+ABC,0.018486985894230375
+HRB,0.0011037382541728281
+WBA,-0.00740543302934619
+BWA,-0.008936780754010469
+CVS,-0.010387316592991813
+MHK,-0.01639706077444565
+NBL,-0.0381337135963052
+KMI,-0.0385112142823507
+OXY,-0.042821393899740684
+COG,-0.050016632355008334
+SRCL,-0.08588067563687068
+M,-0.12659804983237255
+MYL,-0.13082884844793088
+AMG,-0.13879823286529672
diff --git a/.ipynb_checkpoints/selection_criteria-checkpoint.ipynb b/.ipynb_checkpoints/selection_criteria-checkpoint.ipynb
index 3f8e59f..2b53187 100644
--- a/.ipynb_checkpoints/selection_criteria-checkpoint.ipynb
+++ b/.ipynb_checkpoints/selection_criteria-checkpoint.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -127,7 +127,7 @@
        "[505 rows x 2 columns]"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -141,7 +141,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -240,7 +240,7 @@
        "[100 rows x 1 columns]"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -254,7 +254,120 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>FFM Returns</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Stock</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>ADBE</th>\n",
+       "      <td>0.329761</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>MSFT</th>\n",
+       "      <td>0.322501</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CTAS</th>\n",
+       "      <td>0.285973</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>BBY</th>\n",
+       "      <td>0.264073</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SNPS</th>\n",
+       "      <td>0.258979</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>COG</th>\n",
+       "      <td>-0.050017</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SRCL</th>\n",
+       "      <td>-0.085881</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>M</th>\n",
+       "      <td>-0.126598</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>MYL</th>\n",
+       "      <td>-0.130829</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AMG</th>\n",
+       "      <td>-0.138798</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>100 rows × 1 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       FFM Returns\n",
+       "Stock             \n",
+       "ADBE      0.329761\n",
+       "MSFT      0.322501\n",
+       "CTAS      0.285973\n",
+       "BBY       0.264073\n",
+       "SNPS      0.258979\n",
+       "...            ...\n",
+       "COG      -0.050017\n",
+       "SRCL     -0.085881\n",
+       "M        -0.126598\n",
+       "MYL      -0.130829\n",
+       "AMG      -0.138798\n",
+       "\n",
+       "[100 rows x 1 columns]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# importing sharpe ratio data\n",
+    "ffm_path = Path('ffmreturns.csv')\n",
+    "ffm_df = pd.read_csv(ffm_path, index_col = 'Stock')\n",
+    "ffm_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -405,7 +518,7 @@
        "[100 rows x 5 columns]"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -419,7 +532,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -447,6 +560,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -461,6 +575,7 @@
        "      <td>Accenture plc</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.113858</td>\n",
+       "      <td>0.225818</td>\n",
        "      <td>28.34</td>\n",
        "      <td>7.49</td>\n",
        "      <td>1.03</td>\n",
@@ -473,6 +588,7 @@
        "      <td>Adobe Systems Inc</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.616060</td>\n",
+       "      <td>0.329761</td>\n",
        "      <td>63.17</td>\n",
        "      <td>6.01</td>\n",
        "      <td>1.09</td>\n",
@@ -485,6 +601,7 @@
        "      <td>AES Corp</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>1.182641</td>\n",
+       "      <td>0.162654</td>\n",
        "      <td>27.44</td>\n",
        "      <td>0.76</td>\n",
        "      <td>1.05</td>\n",
@@ -497,6 +614,7 @@
        "      <td>Affiliated Managers Group Inc</td>\n",
        "      <td>Financials</td>\n",
        "      <td>1.097986</td>\n",
+       "      <td>-0.138798</td>\n",
        "      <td>267.18</td>\n",
        "      <td>0.31</td>\n",
        "      <td>1.69</td>\n",
@@ -509,6 +627,7 @@
        "      <td>Air Products &amp; Chemicals Inc</td>\n",
        "      <td>Materials</td>\n",
        "      <td>1.224824</td>\n",
+       "      <td>0.153161</td>\n",
        "      <td>30.09</td>\n",
        "      <td>8.51</td>\n",
        "      <td>0.86</td>\n",
@@ -526,6 +645,7 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
+       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>87</th>\n",
@@ -533,6 +653,7 @@
        "      <td>Thermo Fisher Scientific</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.957237</td>\n",
+       "      <td>0.223396</td>\n",
        "      <td>36.98</td>\n",
        "      <td>9.17</td>\n",
        "      <td>1.14</td>\n",
@@ -545,6 +666,7 @@
        "      <td>United Health Group Inc.</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.892893</td>\n",
+       "      <td>0.243094</td>\n",
        "      <td>20.86</td>\n",
        "      <td>14.33</td>\n",
        "      <td>0.69</td>\n",
@@ -557,6 +679,7 @@
        "      <td>V.F. Corp.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.323241</td>\n",
+       "      <td>0.129111</td>\n",
        "      <td>25.99</td>\n",
        "      <td>3.22</td>\n",
        "      <td>1.20</td>\n",
@@ -569,6 +692,7 @@
        "      <td>Wal-Mart Stores</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>1.271096</td>\n",
+       "      <td>0.125055</td>\n",
        "      <td>23.55</td>\n",
        "      <td>5.00</td>\n",
        "      <td>0.36</td>\n",
@@ -581,6 +705,7 @@
        "      <td>Walgreens Boots Alliance</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>2.224201</td>\n",
+       "      <td>-0.007405</td>\n",
        "      <td>13.00</td>\n",
        "      <td>4.07</td>\n",
        "      <td>0.92</td>\n",
@@ -589,7 +714,7 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>92 rows × 9 columns</p>\n",
+       "<p>92 rows × 10 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -606,33 +731,46 @@
        "90    WMT                Wal-Mart Stores        Consumer Staples   \n",
        "91    WBA       Walgreens Boots Alliance        Consumer Staples   \n",
        "\n",
-       "    sharpe ratio  P/E ratio    EPS  beta       mkt cap      shares  \n",
-       "0       1.113858      28.34   7.49  1.03  139515576338   656946000  \n",
-       "1       0.616060      63.17   6.01  1.09  185174936969   487726000  \n",
-       "2       1.182641      27.44   0.76  1.05   13895280692   663893000  \n",
-       "3       1.097986     267.18   0.31  1.69    4084648875    49272000  \n",
-       "4       1.224824      30.09   8.51  0.86   56495776935   220678000  \n",
-       "..           ...        ...    ...   ...           ...         ...  \n",
-       "87      0.957237      36.98   9.17  1.14  136012138268   400991000  \n",
-       "88      0.892893      20.86  14.33  0.69  283068652543   947415000  \n",
-       "89      1.323241      25.99   3.22  1.20   33022293377   394720000  \n",
-       "90      1.271096      23.55   5.00  0.36  334474559018  2837175000  \n",
-       "91      2.224201      13.00   4.07  0.92   46817805348   885862000  \n",
+       "    sharpe ratio  FFM returns  P/E ratio    EPS  beta       mkt cap  \\\n",
+       "0       1.113858     0.225818      28.34   7.49  1.03  139515576338   \n",
+       "1       0.616060     0.329761      63.17   6.01  1.09  185174936969   \n",
+       "2       1.182641     0.162654      27.44   0.76  1.05   13895280692   \n",
+       "3       1.097986    -0.138798     267.18   0.31  1.69    4084648875   \n",
+       "4       1.224824     0.153161      30.09   8.51  0.86   56495776935   \n",
+       "..           ...          ...        ...    ...   ...           ...   \n",
+       "87      0.957237     0.223396      36.98   9.17  1.14  136012138268   \n",
+       "88      0.892893     0.243094      20.86  14.33  0.69  283068652543   \n",
+       "89      1.323241     0.129111      25.99   3.22  1.20   33022293377   \n",
+       "90      1.271096     0.125055      23.55   5.00  0.36  334474559018   \n",
+       "91      2.224201    -0.007405      13.00   4.07  0.92   46817805348   \n",
+       "\n",
+       "        shares  \n",
+       "0    656946000  \n",
+       "1    487726000  \n",
+       "2    663893000  \n",
+       "3     49272000  \n",
+       "4    220678000  \n",
+       "..         ...  \n",
+       "87   400991000  \n",
+       "88   947415000  \n",
+       "89   394720000  \n",
+       "90  2837175000  \n",
+       "91   885862000  \n",
        "\n",
-       "[92 rows x 9 columns]"
+       "[92 rows x 10 columns]"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# concatenating the datasets and dropping nulls\n",
-    "merged_df = pd.concat([sp500_df,sharpe_df,stock_data_df], axis='columns', join='inner')\n",
+    "merged_df = pd.concat([sp500_df,sharpe_df,ffm_df,stock_data_df], axis='columns', join='inner')\n",
     "merged_df.dropna(inplace=True)\n",
     "merged_df.reset_index(inplace=True)\n",
-    "merged_df.columns = ['ticker','name','sector','sharpe ratio','P/E ratio','EPS','beta','mkt cap','shares']\n",
+    "merged_df.columns = ['ticker','name','sector','sharpe ratio','FFM returns','P/E ratio','EPS','beta','mkt cap','shares']\n",
     "merged_df"
    ]
   },
@@ -719,7 +857,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'FFM Returns')"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1800x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# plotting returns\n",
+    "merged_df.plot(x='ticker',y='FFM returns', kind='bar', figsize=(25,10))\n",
+    "plt.suptitle('FFM Returns in Investment Universe', fontsize=30)\n",
+    "plt.xlabel('Company Ticker',fontsize=20)\n",
+    "plt.ylabel('FFM Returns',fontsize=20)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -732,9 +906,60 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  after removing the cwd from sys.path.\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:8: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  \n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:12: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  if sys.path[0] == '':\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:16: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  app.launch_new_instance()\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:20: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:24: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:28: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:32: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:36: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:40: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n"
+     ]
+    }
+   ],
    "source": [
     "# creating datasets for each sector\n",
     "cd_mask = merged_df['sector'] == 'Consumer Discretionary'\n",
@@ -780,7 +1005,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -808,6 +1033,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -822,6 +1048,7 @@
        "      <td>Genuine Parts</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>2.924464</td>\n",
+       "      <td>0.074228</td>\n",
        "      <td>17.71</td>\n",
        "      <td>5.45</td>\n",
        "      <td>0.89</td>\n",
@@ -834,6 +1061,7 @@
        "      <td>Expedia Inc.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>2.407311</td>\n",
+       "      <td>0.086286</td>\n",
        "      <td>32.58</td>\n",
        "      <td>3.77</td>\n",
        "      <td>1.01</td>\n",
@@ -846,6 +1074,7 @@
        "      <td>Discovery Communications-C</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>2.309659</td>\n",
+       "      <td>0.061552</td>\n",
        "      <td>11.10</td>\n",
        "      <td>2.59</td>\n",
        "      <td>1.45</td>\n",
@@ -858,6 +1087,7 @@
        "      <td>LKQ Corporation</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>2.216066</td>\n",
+       "      <td>0.121772</td>\n",
        "      <td>23.73</td>\n",
        "      <td>1.40</td>\n",
        "      <td>1.30</td>\n",
@@ -870,6 +1100,7 @@
        "      <td>General Motors</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.903721</td>\n",
+       "      <td>0.084495</td>\n",
        "      <td>7.60</td>\n",
        "      <td>4.57</td>\n",
        "      <td>1.38</td>\n",
@@ -882,6 +1113,7 @@
        "      <td>Carmax Inc</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.703158</td>\n",
+       "      <td>0.099285</td>\n",
        "      <td>19.16</td>\n",
        "      <td>5.16</td>\n",
        "      <td>1.10</td>\n",
@@ -894,6 +1126,7 @@
        "      <td>Polo Ralph Lauren Corp.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.685028</td>\n",
+       "      <td>0.046267</td>\n",
        "      <td>14.16</td>\n",
        "      <td>8.61</td>\n",
        "      <td>0.90</td>\n",
@@ -906,6 +1139,7 @@
        "      <td>BorgWarner</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.682271</td>\n",
+       "      <td>-0.008937</td>\n",
        "      <td>9.20</td>\n",
        "      <td>3.71</td>\n",
        "      <td>1.91</td>\n",
@@ -918,6 +1152,7 @@
        "      <td>Starbucks Corp.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.388488</td>\n",
+       "      <td>0.177745</td>\n",
        "      <td>29.15</td>\n",
        "      <td>3.06</td>\n",
        "      <td>0.56</td>\n",
@@ -930,6 +1165,7 @@
        "      <td>Royal Caribbean Cruises Ltd</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.347063</td>\n",
+       "      <td>0.195659</td>\n",
        "      <td>12.55</td>\n",
        "      <td>9.02</td>\n",
        "      <td>1.44</td>\n",
@@ -942,6 +1178,7 @@
        "      <td>Target Corp.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.340882</td>\n",
+       "      <td>0.185070</td>\n",
        "      <td>18.64</td>\n",
        "      <td>6.26</td>\n",
        "      <td>0.56</td>\n",
@@ -954,6 +1191,7 @@
        "      <td>V.F. Corp.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.323241</td>\n",
+       "      <td>0.129111</td>\n",
        "      <td>25.99</td>\n",
        "      <td>3.22</td>\n",
        "      <td>1.20</td>\n",
@@ -966,6 +1204,7 @@
        "      <td>Mohawk Industries</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.255168</td>\n",
+       "      <td>-0.016397</td>\n",
        "      <td>13.40</td>\n",
        "      <td>10.30</td>\n",
        "      <td>1.36</td>\n",
@@ -978,6 +1217,7 @@
        "      <td>Pulte Homes Inc.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.125225</td>\n",
+       "      <td>0.165132</td>\n",
        "      <td>12.77</td>\n",
        "      <td>3.66</td>\n",
        "      <td>0.56</td>\n",
@@ -990,6 +1230,7 @@
        "      <td>Hilton Worldwide Holdings Inc</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.059899</td>\n",
+       "      <td>0.171047</td>\n",
        "      <td>37.27</td>\n",
        "      <td>3.04</td>\n",
        "      <td>1.14</td>\n",
@@ -1002,6 +1243,7 @@
        "      <td>Macy's Inc.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>0.826483</td>\n",
+       "      <td>-0.126598</td>\n",
        "      <td>5.39</td>\n",
        "      <td>3.09</td>\n",
        "      <td>0.66</td>\n",
@@ -1014,6 +1256,7 @@
        "      <td>Best Buy Co. Inc.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>0.823915</td>\n",
+       "      <td>0.264073</td>\n",
        "      <td>15.98</td>\n",
        "      <td>5.64</td>\n",
        "      <td>1.12</td>\n",
@@ -1044,27 +1287,46 @@
        "56      M                    Macy's Inc.  Consumer Discretionary   \n",
        "15    BBY              Best Buy Co. Inc.  Consumer Discretionary   \n",
        "\n",
-       "    sharpe ratio  P/E ratio    EPS  beta       mkt cap      shares  \n",
-       "44      2.924464      17.71   5.45  0.89   14016415887   145293000  \n",
-       "33      2.407311      32.58   3.77  1.01   17792025802   139363000  \n",
-       "30      2.309659      11.10   2.59  1.45   15392873644   360664000  \n",
-       "54      2.216066      23.73   1.40  1.30   10174538633   306462000  \n",
-       "43      1.903721       7.60   4.57  1.38   49672072361  1429002000  \n",
-       "22      1.703158      19.16   5.16  1.10   16144071451   163385000  \n",
-       "72      1.685028      14.16   8.61  0.90    8984857815    48862000  \n",
-       "17      1.682271       9.20   3.71  1.91    7048901814   206410000  \n",
-       "81      1.388488      29.15   3.06  0.56  104787934567  1173700000  \n",
-       "78      1.347063      12.55   9.02  1.44   23627921924   208801000  \n",
-       "84      1.340882      18.64   6.26  0.56   59100734918   506737000  \n",
-       "89      1.323241      25.99   3.22  1.20   33022293377   394720000  \n",
-       "61      1.255168      13.40  10.30  1.36    9882403253    71622000  \n",
-       "74      1.125225      12.77   3.66  0.56   12605132379   269975000  \n",
-       "47      1.059899      37.27   3.04  1.14   31415437971   277448000  \n",
-       "56      0.826483       5.39   3.09  0.66    5150446573   308965000  \n",
-       "15      0.823915      15.98   5.64  1.12   23344272933   258777000  "
+       "    sharpe ratio  FFM returns  P/E ratio    EPS  beta       mkt cap  \\\n",
+       "44      2.924464     0.074228      17.71   5.45  0.89   14016415887   \n",
+       "33      2.407311     0.086286      32.58   3.77  1.01   17792025802   \n",
+       "30      2.309659     0.061552      11.10   2.59  1.45   15392873644   \n",
+       "54      2.216066     0.121772      23.73   1.40  1.30   10174538633   \n",
+       "43      1.903721     0.084495       7.60   4.57  1.38   49672072361   \n",
+       "22      1.703158     0.099285      19.16   5.16  1.10   16144071451   \n",
+       "72      1.685028     0.046267      14.16   8.61  0.90    8984857815   \n",
+       "17      1.682271    -0.008937       9.20   3.71  1.91    7048901814   \n",
+       "81      1.388488     0.177745      29.15   3.06  0.56  104787934567   \n",
+       "78      1.347063     0.195659      12.55   9.02  1.44   23627921924   \n",
+       "84      1.340882     0.185070      18.64   6.26  0.56   59100734918   \n",
+       "89      1.323241     0.129111      25.99   3.22  1.20   33022293377   \n",
+       "61      1.255168    -0.016397      13.40  10.30  1.36    9882403253   \n",
+       "74      1.125225     0.165132      12.77   3.66  0.56   12605132379   \n",
+       "47      1.059899     0.171047      37.27   3.04  1.14   31415437971   \n",
+       "56      0.826483    -0.126598       5.39   3.09  0.66    5150446573   \n",
+       "15      0.823915     0.264073      15.98   5.64  1.12   23344272933   \n",
+       "\n",
+       "        shares  \n",
+       "44   145293000  \n",
+       "33   139363000  \n",
+       "30   360664000  \n",
+       "54   306462000  \n",
+       "43  1429002000  \n",
+       "22   163385000  \n",
+       "72    48862000  \n",
+       "17   206410000  \n",
+       "81  1173700000  \n",
+       "78   208801000  \n",
+       "84   506737000  \n",
+       "89   394720000  \n",
+       "61    71622000  \n",
+       "74   269975000  \n",
+       "47   277448000  \n",
+       "56   308965000  \n",
+       "15   258777000  "
       ]
      },
-     "execution_count": 49,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1077,7 +1339,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -1105,6 +1367,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -1119,6 +1382,7 @@
        "      <td>General Mills</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>2.641281</td>\n",
+       "      <td>0.063147</td>\n",
        "      <td>15.34</td>\n",
        "      <td>3.48</td>\n",
        "      <td>0.73</td>\n",
@@ -1131,6 +1395,7 @@
        "      <td>Walgreens Boots Alliance</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>2.224201</td>\n",
+       "      <td>-0.007405</td>\n",
        "      <td>13.00</td>\n",
        "      <td>4.07</td>\n",
        "      <td>0.92</td>\n",
@@ -1143,6 +1408,7 @@
        "      <td>Coca-Cola Company (The)</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>2.197158</td>\n",
+       "      <td>0.103820</td>\n",
        "      <td>28.99</td>\n",
        "      <td>2.07</td>\n",
        "      <td>0.41</td>\n",
@@ -1155,6 +1421,7 @@
        "      <td>PepsiCo Inc.</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>1.951250</td>\n",
+       "      <td>0.117935</td>\n",
        "      <td>28.31</td>\n",
        "      <td>5.19</td>\n",
        "      <td>0.53</td>\n",
@@ -1167,6 +1434,7 @@
        "      <td>CVS Health</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>1.707963</td>\n",
+       "      <td>-0.010387</td>\n",
        "      <td>14.05</td>\n",
        "      <td>5.08</td>\n",
        "      <td>0.93</td>\n",
@@ -1179,6 +1447,7 @@
        "      <td>The Hershey Company</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>1.469682</td>\n",
+       "      <td>0.125085</td>\n",
        "      <td>29.33</td>\n",
        "      <td>5.47</td>\n",
        "      <td>0.02</td>\n",
@@ -1191,6 +1460,7 @@
        "      <td>Wal-Mart Stores</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>1.271096</td>\n",
+       "      <td>0.125055</td>\n",
        "      <td>23.55</td>\n",
        "      <td>5.00</td>\n",
        "      <td>0.36</td>\n",
@@ -1203,6 +1473,7 @@
        "      <td>Costco Wholesale Corp.</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>1.060644</td>\n",
+       "      <td>0.192130</td>\n",
        "      <td>37.75</td>\n",
        "      <td>8.43</td>\n",
        "      <td>0.90</td>\n",
@@ -1224,18 +1495,18 @@
        "90    WMT           Wal-Mart Stores  Consumer Staples      1.271096   \n",
        "27   COST    Costco Wholesale Corp.  Consumer Staples      1.060644   \n",
        "\n",
-       "    P/E ratio   EPS  beta       mkt cap      shares  \n",
-       "42      15.34  3.48  0.73   32242795100   604817000  \n",
-       "91      13.00  4.07  0.92   46817805348   885862000  \n",
-       "26      28.99  2.07  0.41  256586003265  4280000000  \n",
-       "71      28.31  5.19  0.53  204968008309  1389545000  \n",
-       "29      14.05  5.08  0.93   92849804253  1300964000  \n",
-       "86      29.33  5.47  0.02   23779704176   148308000  \n",
-       "90      23.55  5.00  0.36  334474559018  2837175000  \n",
-       "27      37.75  8.43  0.90  140615987901   441758000  "
+       "    FFM returns  P/E ratio   EPS  beta       mkt cap      shares  \n",
+       "42     0.063147      15.34  3.48  0.73   32242795100   604817000  \n",
+       "91    -0.007405      13.00  4.07  0.92   46817805348   885862000  \n",
+       "26     0.103820      28.99  2.07  0.41  256586003265  4280000000  \n",
+       "71     0.117935      28.31  5.19  0.53  204968008309  1389545000  \n",
+       "29    -0.010387      14.05  5.08  0.93   92849804253  1300964000  \n",
+       "86     0.125085      29.33  5.47  0.02   23779704176   148308000  \n",
+       "90     0.125055      23.55  5.00  0.36  334474559018  2837175000  \n",
+       "27     0.192130      37.75  8.43  0.90  140615987901   441758000  "
       ]
      },
-     "execution_count": 40,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1248,7 +1519,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -1276,6 +1547,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -1290,6 +1562,7 @@
        "      <td>Occidental Petroleum</td>\n",
        "      <td>Energy</td>\n",
        "      <td>2.054771</td>\n",
+       "      <td>-0.042821</td>\n",
        "      <td>29.53</td>\n",
        "      <td>1.41</td>\n",
        "      <td>0.90</td>\n",
@@ -1302,6 +1575,7 @@
        "      <td>Cabot Oil &amp; Gas</td>\n",
        "      <td>Energy</td>\n",
        "      <td>1.952983</td>\n",
+       "      <td>-0.050017</td>\n",
        "      <td>7.80</td>\n",
        "      <td>1.90</td>\n",
        "      <td>0.47</td>\n",
@@ -1314,6 +1588,7 @@
        "      <td>Kinder Morgan</td>\n",
        "      <td>Energy</td>\n",
        "      <td>1.038470</td>\n",
+       "      <td>-0.038511</td>\n",
        "      <td>22.87</td>\n",
        "      <td>0.96</td>\n",
        "      <td>0.81</td>\n",
@@ -1326,6 +1601,7 @@
        "      <td>ONEOK</td>\n",
        "      <td>Energy</td>\n",
        "      <td>0.917326</td>\n",
+       "      <td>0.230148</td>\n",
        "      <td>25.56</td>\n",
        "      <td>3.01</td>\n",
        "      <td>1.11</td>\n",
@@ -1337,20 +1613,20 @@
        "</div>"
       ],
       "text/plain": [
-       "   ticker                  name  sector  sharpe ratio  P/E ratio   EPS  beta  \\\n",
-       "68    OXY  Occidental Petroleum  Energy      2.054771      29.53  1.41  0.90   \n",
-       "20    COG       Cabot Oil & Gas  Energy      1.952983       7.80  1.90  0.47   \n",
-       "53    KMI         Kinder Morgan  Energy      1.038470      22.87  0.96  0.81   \n",
-       "69    OKE                 ONEOK  Energy      0.917326      25.56  3.01  1.11   \n",
+       "   ticker                  name  sector  sharpe ratio  FFM returns  P/E ratio  \\\n",
+       "68    OXY  Occidental Petroleum  Energy      2.054771    -0.042821      29.53   \n",
+       "20    COG       Cabot Oil & Gas  Energy      1.952983    -0.050017       7.80   \n",
+       "53    KMI         Kinder Morgan  Energy      1.038470    -0.038511      22.87   \n",
+       "69    OKE                 ONEOK  Energy      0.917326     0.230148      25.56   \n",
        "\n",
-       "        mkt cap      shares  \n",
-       "68  37161985836   893317000  \n",
-       "20   6037284157   407925000  \n",
-       "53  49831386000  2265063000  \n",
-       "69  31799253894   413085000  "
+       "     EPS  beta      mkt cap      shares  \n",
+       "68  1.41  0.90  37161985836   893317000  \n",
+       "20  1.90  0.47   6037284157   407925000  \n",
+       "53  0.96  0.81  49831386000  2265063000  \n",
+       "69  3.01  1.11  31799253894   413085000  "
       ]
      },
-     "execution_count": 41,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1363,7 +1639,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -1391,6 +1667,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -1405,6 +1682,7 @@
        "      <td>Synchrony Financial</td>\n",
        "      <td>Financials</td>\n",
        "      <td>2.493336</td>\n",
+       "      <td>0.091836</td>\n",
        "      <td>6.07</td>\n",
        "      <td>5.56</td>\n",
        "      <td>1.21</td>\n",
@@ -1417,6 +1695,7 @@
        "      <td>Block H&amp;R</td>\n",
        "      <td>Financials</td>\n",
        "      <td>2.210675</td>\n",
+       "      <td>0.001104</td>\n",
        "      <td>11.75</td>\n",
        "      <td>1.90</td>\n",
        "      <td>0.23</td>\n",
@@ -1429,6 +1708,7 @@
        "      <td>Capital One Financial</td>\n",
        "      <td>Financials</td>\n",
        "      <td>2.034764</td>\n",
+       "      <td>0.116104</td>\n",
        "      <td>9.31</td>\n",
        "      <td>11.02</td>\n",
        "      <td>1.25</td>\n",
@@ -1441,6 +1721,7 @@
        "      <td>Goldman Sachs Group</td>\n",
        "      <td>Financials</td>\n",
        "      <td>1.828821</td>\n",
+       "      <td>0.099915</td>\n",
        "      <td>11.27</td>\n",
        "      <td>21.03</td>\n",
        "      <td>1.32</td>\n",
@@ -1453,6 +1734,7 @@
        "      <td>Raymond James Financial Inc.</td>\n",
        "      <td>Financials</td>\n",
        "      <td>1.281138</td>\n",
+       "      <td>0.155046</td>\n",
        "      <td>13.44</td>\n",
        "      <td>7.36</td>\n",
        "      <td>1.50</td>\n",
@@ -1465,6 +1747,7 @@
        "      <td>American Express Co</td>\n",
        "      <td>Financials</td>\n",
        "      <td>1.214408</td>\n",
+       "      <td>0.132252</td>\n",
        "      <td>17.01</td>\n",
        "      <td>7.99</td>\n",
        "      <td>0.99</td>\n",
@@ -1477,6 +1760,7 @@
        "      <td>Cincinnati Financial</td>\n",
        "      <td>Financials</td>\n",
        "      <td>1.121374</td>\n",
+       "      <td>0.199838</td>\n",
        "      <td>9.52</td>\n",
        "      <td>12.10</td>\n",
        "      <td>0.57</td>\n",
@@ -1489,6 +1773,7 @@
        "      <td>Aon plc</td>\n",
        "      <td>Financials</td>\n",
        "      <td>1.104319</td>\n",
+       "      <td>0.183167</td>\n",
        "      <td>37.00</td>\n",
        "      <td>6.37</td>\n",
        "      <td>0.83</td>\n",
@@ -1501,6 +1786,7 @@
        "      <td>Affiliated Managers Group Inc</td>\n",
        "      <td>Financials</td>\n",
        "      <td>1.097986</td>\n",
+       "      <td>-0.138798</td>\n",
        "      <td>267.18</td>\n",
        "      <td>0.31</td>\n",
        "      <td>1.69</td>\n",
@@ -1513,6 +1799,7 @@
        "      <td>Arthur J. Gallagher &amp; Co.</td>\n",
        "      <td>Financials</td>\n",
        "      <td>0.967112</td>\n",
+       "      <td>0.195583</td>\n",
        "      <td>31.03</td>\n",
        "      <td>3.52</td>\n",
        "      <td>0.76</td>\n",
@@ -1525,6 +1812,7 @@
        "      <td>Moody's Corp</td>\n",
        "      <td>Financials</td>\n",
        "      <td>0.927984</td>\n",
+       "      <td>0.234858</td>\n",
        "      <td>37.43</td>\n",
        "      <td>7.42</td>\n",
        "      <td>1.21</td>\n",
@@ -1536,34 +1824,34 @@
        "</div>"
       ],
       "text/plain": [
-       "   ticker                           name      sector  sharpe ratio  P/E ratio  \\\n",
-       "82    SYF            Synchrony Financial  Financials      2.493336       6.07   \n",
-       "16    HRB                      Block H&R  Financials      2.210675      11.75   \n",
-       "21    COF          Capital One Financial  Financials      2.034764       9.31   \n",
-       "45     GS            Goldman Sachs Group  Financials      1.828821      11.27   \n",
-       "75    RJF   Raymond James Financial Inc.  Financials      1.281138      13.44   \n",
-       "8     AXP            American Express Co  Financials      1.214408      17.01   \n",
-       "24   CINF           Cincinnati Financial  Financials      1.121374       9.52   \n",
-       "11    AON                        Aon plc  Financials      1.104319      37.00   \n",
-       "3     AMG  Affiliated Managers Group Inc  Financials      1.097986     267.18   \n",
-       "13    AJG      Arthur J. Gallagher & Co.  Financials      0.967112      31.03   \n",
-       "62    MCO                   Moody's Corp  Financials      0.927984      37.43   \n",
+       "   ticker                           name      sector  sharpe ratio  \\\n",
+       "82    SYF            Synchrony Financial  Financials      2.493336   \n",
+       "16    HRB                      Block H&R  Financials      2.210675   \n",
+       "21    COF          Capital One Financial  Financials      2.034764   \n",
+       "45     GS            Goldman Sachs Group  Financials      1.828821   \n",
+       "75    RJF   Raymond James Financial Inc.  Financials      1.281138   \n",
+       "8     AXP            American Express Co  Financials      1.214408   \n",
+       "24   CINF           Cincinnati Financial  Financials      1.121374   \n",
+       "11    AON                        Aon plc  Financials      1.104319   \n",
+       "3     AMG  Affiliated Managers Group Inc  Financials      1.097986   \n",
+       "13    AJG      Arthur J. Gallagher & Co.  Financials      0.967112   \n",
+       "62    MCO                   Moody's Corp  Financials      0.927984   \n",
        "\n",
-       "      EPS  beta       mkt cap     shares  \n",
-       "82   5.56  1.21   20704848750  613477000  \n",
-       "16   1.90  0.23    4369605316  195246000  \n",
-       "21  11.02  1.25   46865423721  456600000  \n",
-       "45  21.03  1.32   83946946608  354087000  \n",
-       "75   7.36  1.50   13782151374  139284000  \n",
-       "8    7.99  0.99  111178449600  808041000  \n",
-       "24  12.10  0.57   18822318390  163374000  \n",
-       "11   6.37  0.83   54701475530  234137000  \n",
-       "3    0.31  1.69    4084648875   49272000  \n",
-       "13   3.52  0.76   20549043209  188247000  \n",
-       "62   7.42  1.21   52148688479  187700000  "
+       "    FFM returns  P/E ratio    EPS  beta       mkt cap     shares  \n",
+       "82     0.091836       6.07   5.56  1.21   20704848750  613477000  \n",
+       "16     0.001104      11.75   1.90  0.23    4369605316  195246000  \n",
+       "21     0.116104       9.31  11.02  1.25   46865423721  456600000  \n",
+       "45     0.099915      11.27  21.03  1.32   83946946608  354087000  \n",
+       "75     0.155046      13.44   7.36  1.50   13782151374  139284000  \n",
+       "8      0.132252      17.01   7.99  0.99  111178449600  808041000  \n",
+       "24     0.199838       9.52  12.10  0.57   18822318390  163374000  \n",
+       "11     0.183167      37.00   6.37  0.83   54701475530  234137000  \n",
+       "3     -0.138798     267.18   0.31  1.69    4084648875   49272000  \n",
+       "13     0.195583      31.03   3.52  0.76   20549043209  188247000  \n",
+       "62     0.234858      37.43   7.42  1.21   52148688479  187700000  "
       ]
      },
-     "execution_count": 42,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1576,7 +1864,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -1604,6 +1892,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -1618,6 +1907,7 @@
        "      <td>AmerisourceBergen Corp</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>2.824204</td>\n",
+       "      <td>0.018487</td>\n",
        "      <td>30.62</td>\n",
        "      <td>3.08</td>\n",
        "      <td>1.01</td>\n",
@@ -1630,6 +1920,7 @@
        "      <td>Bristol-Myers Squibb</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>2.688515</td>\n",
+       "      <td>0.083177</td>\n",
        "      <td>33.05</td>\n",
        "      <td>2.01</td>\n",
        "      <td>0.76</td>\n",
@@ -1642,6 +1933,7 @@
        "      <td>Hologic</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>2.425412</td>\n",
+       "      <td>0.129968</td>\n",
        "      <td>173.01</td>\n",
        "      <td>0.31</td>\n",
        "      <td>0.85</td>\n",
@@ -1654,6 +1946,7 @@
        "      <td>Medtronic plc</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>1.917921</td>\n",
+       "      <td>0.124213</td>\n",
        "      <td>33.97</td>\n",
        "      <td>3.45</td>\n",
        "      <td>0.60</td>\n",
@@ -1666,6 +1959,7 @@
        "      <td>Amgen Inc</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>1.861649</td>\n",
+       "      <td>0.151749</td>\n",
        "      <td>17.36</td>\n",
        "      <td>12.88</td>\n",
        "      <td>1.12</td>\n",
@@ -1678,6 +1972,7 @@
        "      <td>Merck &amp; Co.</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>1.368058</td>\n",
+       "      <td>0.147016</td>\n",
        "      <td>21.52</td>\n",
        "      <td>3.84</td>\n",
        "      <td>0.57</td>\n",
@@ -1690,6 +1985,7 @@
        "      <td>Incyte</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>1.268258</td>\n",
+       "      <td>0.076793</td>\n",
        "      <td>38.21</td>\n",
        "      <td>2.05</td>\n",
        "      <td>1.06</td>\n",
@@ -1702,6 +1998,7 @@
        "      <td>Mettler Toledo</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.969242</td>\n",
+       "      <td>0.232895</td>\n",
        "      <td>33.97</td>\n",
        "      <td>22.47</td>\n",
        "      <td>1.39</td>\n",
@@ -1714,6 +2011,7 @@
        "      <td>Thermo Fisher Scientific</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.957237</td>\n",
+       "      <td>0.223396</td>\n",
        "      <td>36.98</td>\n",
        "      <td>9.17</td>\n",
        "      <td>1.14</td>\n",
@@ -1726,6 +2024,7 @@
        "      <td>Boston Scientific</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.933787</td>\n",
+       "      <td>0.233861</td>\n",
        "      <td>12.70</td>\n",
        "      <td>3.33</td>\n",
        "      <td>0.87</td>\n",
@@ -1738,6 +2037,7 @@
        "      <td>Mylan N.V.</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.893280</td>\n",
+       "      <td>-0.130829</td>\n",
        "      <td>239.58</td>\n",
        "      <td>0.09</td>\n",
        "      <td>1.72</td>\n",
@@ -1750,6 +2050,7 @@
        "      <td>United Health Group Inc.</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.892893</td>\n",
+       "      <td>0.243094</td>\n",
        "      <td>20.86</td>\n",
        "      <td>14.33</td>\n",
        "      <td>0.69</td>\n",
@@ -1762,6 +2063,7 @@
        "      <td>ResMed</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.834963</td>\n",
+       "      <td>0.236317</td>\n",
        "      <td>56.31</td>\n",
        "      <td>3.14</td>\n",
        "      <td>0.48</td>\n",
@@ -1773,38 +2075,38 @@
        "</div>"
       ],
       "text/plain": [
-       "   ticker                      name       sector  sharpe ratio  P/E ratio  \\\n",
-       "9     ABC    AmerisourceBergen Corp  Health Care      2.824204      30.62   \n",
-       "19    BMY      Bristol-Myers Squibb  Health Care      2.688515      33.05   \n",
-       "48   HOLX                   Hologic  Health Care      2.425412     173.01   \n",
-       "57    MDT             Medtronic plc  Health Care      1.917921      33.97   \n",
-       "10   AMGN                 Amgen Inc  Health Care      1.861649      17.36   \n",
-       "58    MRK               Merck & Co.  Health Care      1.368058      21.52   \n",
-       "51   INCY                    Incyte  Health Care      1.268258      38.21   \n",
-       "59    MTD            Mettler Toledo  Health Care      0.969242      33.97   \n",
-       "87    TMO  Thermo Fisher Scientific  Health Care      0.957237      36.98   \n",
-       "18    BSX         Boston Scientific  Health Care      0.933787      12.70   \n",
-       "64    MYL                Mylan N.V.  Health Care      0.893280     239.58   \n",
-       "88    UNH  United Health Group Inc.  Health Care      0.892893      20.86   \n",
-       "77    RMD                    ResMed  Health Care      0.834963      56.31   \n",
+       "   ticker                      name       sector  sharpe ratio  FFM returns  \\\n",
+       "9     ABC    AmerisourceBergen Corp  Health Care      2.824204     0.018487   \n",
+       "19    BMY      Bristol-Myers Squibb  Health Care      2.688515     0.083177   \n",
+       "48   HOLX                   Hologic  Health Care      2.425412     0.129968   \n",
+       "57    MDT             Medtronic plc  Health Care      1.917921     0.124213   \n",
+       "10   AMGN                 Amgen Inc  Health Care      1.861649     0.151749   \n",
+       "58    MRK               Merck & Co.  Health Care      1.368058     0.147016   \n",
+       "51   INCY                    Incyte  Health Care      1.268258     0.076793   \n",
+       "59    MTD            Mettler Toledo  Health Care      0.969242     0.232895   \n",
+       "87    TMO  Thermo Fisher Scientific  Health Care      0.957237     0.223396   \n",
+       "18    BSX         Boston Scientific  Health Care      0.933787     0.233861   \n",
+       "64    MYL                Mylan N.V.  Health Care      0.893280    -0.130829   \n",
+       "88    UNH  United Health Group Inc.  Health Care      0.892893     0.243094   \n",
+       "77    RMD                    ResMed  Health Care      0.834963     0.236317   \n",
        "\n",
-       "      EPS  beta       mkt cap      shares  \n",
-       "9    3.08  1.01   19427969245   205892000  \n",
-       "19   2.01  0.76  155607591281  2344185000  \n",
-       "48   0.31  0.85   13960272160   263302000  \n",
-       "57   3.45  0.60  157266553194  1340378000  \n",
-       "10  12.88  1.12  131810065840   589807000  \n",
-       "58   3.84  0.57  210425581484  2545984000  \n",
-       "51   2.05  1.06   17006076538   216776000  \n",
-       "59  22.47  1.39   18357249893    24053000  \n",
-       "87   9.17  1.14  136012138268   400991000  \n",
-       "18   3.33  0.87   58972695354  1393824000  \n",
-       "64   0.09  1.72   11303303743   516177000  \n",
-       "88  14.33  0.69  283068652543   947415000  \n",
-       "77   3.14  0.48   25539363082   144617000  "
+       "    P/E ratio    EPS  beta       mkt cap      shares  \n",
+       "9       30.62   3.08  1.01   19427969245   205892000  \n",
+       "19      33.05   2.01  0.76  155607591281  2344185000  \n",
+       "48     173.01   0.31  0.85   13960272160   263302000  \n",
+       "57      33.97   3.45  0.60  157266553194  1340378000  \n",
+       "10      17.36  12.88  1.12  131810065840   589807000  \n",
+       "58      21.52   3.84  0.57  210425581484  2545984000  \n",
+       "51      38.21   2.05  1.06   17006076538   216776000  \n",
+       "59      33.97  22.47  1.39   18357249893    24053000  \n",
+       "87      36.98   9.17  1.14  136012138268   400991000  \n",
+       "18      12.70   3.33  0.87   58972695354  1393824000  \n",
+       "64     239.58   0.09  1.72   11303303743   516177000  \n",
+       "88      20.86  14.33  0.69  283068652543   947415000  \n",
+       "77      56.31   3.14  0.48   25539363082   144617000  "
       ]
      },
-     "execution_count": 43,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1817,7 +2119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -1845,6 +2147,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -1859,6 +2162,7 @@
        "      <td>Southwest Airlines</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>1.726576</td>\n",
+       "      <td>0.107833</td>\n",
        "      <td>13.77</td>\n",
        "      <td>4.21</td>\n",
        "      <td>1.47</td>\n",
@@ -1871,6 +2175,7 @@
        "      <td>Eaton Corporation</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>1.604766</td>\n",
+       "      <td>0.128998</td>\n",
        "      <td>19.71</td>\n",
        "      <td>5.25</td>\n",
        "      <td>1.42</td>\n",
@@ -1883,6 +2188,7 @@
        "      <td>FedEx Corporation</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>1.509820</td>\n",
+       "      <td>0.024254</td>\n",
        "      <td>583.74</td>\n",
        "      <td>0.27</td>\n",
        "      <td>1.71</td>\n",
@@ -1895,6 +2201,7 @@
        "      <td>Grainger (W.W.) Inc.</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>1.358110</td>\n",
+       "      <td>0.143754</td>\n",
        "      <td>17.94</td>\n",
        "      <td>17.15</td>\n",
        "      <td>0.97</td>\n",
@@ -1907,6 +2214,7 @@
        "      <td>Raytheon Co.</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>1.158338</td>\n",
+       "      <td>0.194796</td>\n",
        "      <td>19.05</td>\n",
        "      <td>11.93</td>\n",
        "      <td>0.85</td>\n",
@@ -1919,6 +2227,7 @@
        "      <td>Huntington Ingalls Industries</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>1.154338</td>\n",
+       "      <td>0.172310</td>\n",
        "      <td>18.57</td>\n",
        "      <td>13.26</td>\n",
        "      <td>1.24</td>\n",
@@ -1931,6 +2240,7 @@
        "      <td>Cintas Corporation</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>0.703186</td>\n",
+       "      <td>0.285973</td>\n",
        "      <td>35.38</td>\n",
        "      <td>8.51</td>\n",
        "      <td>0.99</td>\n",
@@ -1951,17 +2261,17 @@
        "50    HII  Huntington Ingalls Industries  Industrials      1.154338   \n",
        "25   CTAS             Cintas Corporation  Industrials      0.703186   \n",
        "\n",
-       "    P/E ratio    EPS  beta      mkt cap     shares  \n",
-       "80      13.77   4.21  1.47  29987649751  517296000  \n",
-       "31      19.71   5.25  1.42  42807571261  413400000  \n",
-       "36     583.74   0.27  1.71  41418694505  261119000  \n",
-       "46      17.94  17.15  0.97  16517112872   53688000  \n",
-       "76      19.05  11.93  0.85  63256224340  278441000  \n",
-       "50      18.57  13.26  1.24  10035519873   40760000  \n",
-       "25      35.38   8.51  0.99  31216601386  103751000  "
+       "    FFM returns  P/E ratio    EPS  beta      mkt cap     shares  \n",
+       "80     0.107833      13.77   4.21  1.47  29987649751  517296000  \n",
+       "31     0.128998      19.71   5.25  1.42  42807571261  413400000  \n",
+       "36     0.024254     583.74   0.27  1.71  41418694505  261119000  \n",
+       "46     0.143754      17.94  17.15  0.97  16517112872   53688000  \n",
+       "76     0.194796      19.05  11.93  0.85  63256224340  278441000  \n",
+       "50     0.172310      18.57  13.26  1.24  10035519873   40760000  \n",
+       "25     0.285973      35.38   8.51  0.99  31216601386  103751000  "
       ]
      },
-     "execution_count": 44,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1974,7 +2284,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -2002,6 +2312,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -2016,6 +2327,7 @@
        "      <td>Oracle Corp.</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.949619</td>\n",
+       "      <td>0.077350</td>\n",
        "      <td>17.61</td>\n",
        "      <td>3.15</td>\n",
        "      <td>1.11</td>\n",
@@ -2028,6 +2340,7 @@
        "      <td>F5 Networks</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.701382</td>\n",
+       "      <td>0.064989</td>\n",
        "      <td>19.49</td>\n",
        "      <td>6.54</td>\n",
        "      <td>0.98</td>\n",
@@ -2040,6 +2353,7 @@
        "      <td>Gartner Inc</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.337328</td>\n",
+       "      <td>0.165214</td>\n",
        "      <td>59.34</td>\n",
        "      <td>2.57</td>\n",
        "      <td>1.21</td>\n",
@@ -2052,6 +2366,7 @@
        "      <td>Alphabet Inc Class A</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.198026</td>\n",
+       "      <td>0.214640</td>\n",
        "      <td>30.89</td>\n",
        "      <td>49.16</td>\n",
        "      <td>1.02</td>\n",
@@ -2064,6 +2379,7 @@
        "      <td>Accenture plc</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.113858</td>\n",
+       "      <td>0.225818</td>\n",
        "      <td>28.34</td>\n",
        "      <td>7.49</td>\n",
        "      <td>1.03</td>\n",
@@ -2076,6 +2392,7 @@
        "      <td>Facebook, Inc.</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.105767</td>\n",
+       "      <td>0.238789</td>\n",
        "      <td>33.32</td>\n",
        "      <td>6.43</td>\n",
        "      <td>1.05</td>\n",
@@ -2088,6 +2405,7 @@
        "      <td>Automatic Data Processing</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.004579</td>\n",
+       "      <td>0.183269</td>\n",
        "      <td>32.04</td>\n",
        "      <td>5.66</td>\n",
        "      <td>0.87</td>\n",
@@ -2100,6 +2418,7 @@
        "      <td>Fiserv Inc</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.948895</td>\n",
+       "      <td>0.249903</td>\n",
        "      <td>71.58</td>\n",
        "      <td>1.71</td>\n",
        "      <td>0.80</td>\n",
@@ -2112,6 +2431,7 @@
        "      <td>Apple Inc.</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.919063</td>\n",
+       "      <td>0.236049</td>\n",
        "      <td>25.66</td>\n",
        "      <td>12.66</td>\n",
        "      <td>1.29</td>\n",
@@ -2124,6 +2444,7 @@
        "      <td>Texas Instruments</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.886247</td>\n",
+       "      <td>0.224912</td>\n",
        "      <td>25.24</td>\n",
        "      <td>5.24</td>\n",
        "      <td>1.24</td>\n",
@@ -2136,6 +2457,7 @@
        "      <td>Salesforce.com</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.885841</td>\n",
+       "      <td>0.207470</td>\n",
        "      <td>200.68</td>\n",
        "      <td>0.95</td>\n",
        "      <td>1.19</td>\n",
@@ -2148,6 +2470,7 @@
        "      <td>Synopsys Inc.</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.801366</td>\n",
+       "      <td>0.258979</td>\n",
        "      <td>47.31</td>\n",
        "      <td>3.45</td>\n",
        "      <td>1.18</td>\n",
@@ -2160,6 +2483,7 @@
        "      <td>Motorola Solutions Inc.</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.785703</td>\n",
+       "      <td>0.231468</td>\n",
        "      <td>37.31</td>\n",
        "      <td>4.94</td>\n",
        "      <td>0.50</td>\n",
@@ -2172,6 +2496,7 @@
        "      <td>Microsoft Corp.</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.688151</td>\n",
+       "      <td>0.322501</td>\n",
        "      <td>32.28</td>\n",
        "      <td>5.74</td>\n",
        "      <td>1.15</td>\n",
@@ -2184,6 +2509,7 @@
        "      <td>Adobe Systems Inc</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.616060</td>\n",
+       "      <td>0.329761</td>\n",
        "      <td>63.17</td>\n",
        "      <td>6.01</td>\n",
        "      <td>1.09</td>\n",
@@ -2212,25 +2538,25 @@
        "60   MSFT            Microsoft Corp.  Information Technology      0.688151   \n",
        "1    ADBE          Adobe Systems Inc  Information Technology      0.616060   \n",
        "\n",
-       "    P/E ratio    EPS  beta        mkt cap      shares  \n",
-       "70      17.61   3.15  1.11   177928293945  3207649000  \n",
-       "34      19.49   6.54  0.98     7753118169    60804000  \n",
-       "41      59.34   2.57  1.21    13633532057    89453000  \n",
-       "7       30.89  49.16  1.02  1044236513876   299895000  \n",
-       "0       28.34   7.49  1.03   139515576338   656946000  \n",
-       "35      33.32   6.43  1.05   610509360122  2405746000  \n",
-       "14      32.04   5.66  0.87    78255412500   431754000  \n",
-       "38      71.58   1.71  0.80    83164756192   679895000  \n",
-       "12      25.66  12.66  1.29  1421812279411  4375480000  \n",
-       "85      25.24   5.24  1.24   123223956977   932032000  \n",
-       "79     200.68   0.95  1.19   168485647293   887000000  \n",
-       "83      47.31   3.45  1.18    24589893168   150535000  \n",
-       "63      37.31   4.94  0.50    31596072387   171336000  \n",
-       "60      32.28   5.74  1.15  1409780857873  7606047000  \n",
-       "1       63.17   6.01  1.09   185174936969   487726000  "
+       "    FFM returns  P/E ratio    EPS  beta        mkt cap      shares  \n",
+       "70     0.077350      17.61   3.15  1.11   177928293945  3207649000  \n",
+       "34     0.064989      19.49   6.54  0.98     7753118169    60804000  \n",
+       "41     0.165214      59.34   2.57  1.21    13633532057    89453000  \n",
+       "7      0.214640      30.89  49.16  1.02  1044236513876   299895000  \n",
+       "0      0.225818      28.34   7.49  1.03   139515576338   656946000  \n",
+       "35     0.238789      33.32   6.43  1.05   610509360122  2405746000  \n",
+       "14     0.183269      32.04   5.66  0.87    78255412500   431754000  \n",
+       "38     0.249903      71.58   1.71  0.80    83164756192   679895000  \n",
+       "12     0.236049      25.66  12.66  1.29  1421812279411  4375480000  \n",
+       "85     0.224912      25.24   5.24  1.24   123223956977   932032000  \n",
+       "79     0.207470     200.68   0.95  1.19   168485647293   887000000  \n",
+       "83     0.258979      47.31   3.45  1.18    24589893168   150535000  \n",
+       "63     0.231468      37.31   4.94  0.50    31596072387   171336000  \n",
+       "60     0.322501      32.28   5.74  1.15  1409780857873  7606047000  \n",
+       "1      0.329761      63.17   6.01  1.09   185174936969   487726000  "
       ]
      },
-     "execution_count": 45,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2243,7 +2569,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -2271,6 +2597,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -2285,6 +2612,7 @@
        "      <td>LyondellBasell</td>\n",
        "      <td>Materials</td>\n",
        "      <td>2.072393</td>\n",
+       "      <td>0.103512</td>\n",
        "      <td>8.65</td>\n",
        "      <td>9.55</td>\n",
        "      <td>1.45</td>\n",
@@ -2297,6 +2625,7 @@
        "      <td>Newmont Mining Corporation</td>\n",
        "      <td>Materials</td>\n",
        "      <td>1.248661</td>\n",
+       "      <td>0.189686</td>\n",
        "      <td>15.83</td>\n",
        "      <td>2.78</td>\n",
        "      <td>0.16</td>\n",
@@ -2309,6 +2638,7 @@
        "      <td>Air Products &amp; Chemicals Inc</td>\n",
        "      <td>Materials</td>\n",
        "      <td>1.224824</td>\n",
+       "      <td>0.153161</td>\n",
        "      <td>30.09</td>\n",
        "      <td>8.51</td>\n",
        "      <td>0.86</td>\n",
@@ -2321,6 +2651,7 @@
        "      <td>Freeport-McMoRan Inc.</td>\n",
        "      <td>Materials</td>\n",
        "      <td>1.031316</td>\n",
+       "      <td>0.038646</td>\n",
        "      <td>78.35</td>\n",
        "      <td>0.16</td>\n",
        "      <td>2.42</td>\n",
@@ -2333,6 +2664,7 @@
        "      <td>Albemarle Corp</td>\n",
        "      <td>Materials</td>\n",
        "      <td>0.990292</td>\n",
+       "      <td>0.132207</td>\n",
        "      <td>16.67</td>\n",
        "      <td>5.38</td>\n",
        "      <td>1.57</td>\n",
@@ -2345,6 +2677,7 @@
        "      <td>FMC Corporation</td>\n",
        "      <td>Materials</td>\n",
        "      <td>0.889526</td>\n",
+       "      <td>0.193867</td>\n",
        "      <td>27.41</td>\n",
        "      <td>3.85</td>\n",
        "      <td>1.54</td>\n",
@@ -2356,24 +2689,24 @@
        "</div>"
       ],
       "text/plain": [
-       "   ticker                          name     sector  sharpe ratio  P/E ratio  \\\n",
-       "55    LYB                LyondellBasell  Materials      2.072393       8.65   \n",
-       "65    NEM    Newmont Mining Corporation  Materials      1.248661      15.83   \n",
-       "4     APD  Air Products & Chemicals Inc  Materials      1.224824      30.09   \n",
-       "40    FCX         Freeport-McMoRan Inc.  Materials      1.031316      78.35   \n",
-       "5     ALB                Albemarle Corp  Materials      0.990292      16.67   \n",
-       "39    FMC               FMC Corporation  Materials      0.889526      27.41   \n",
+       "   ticker                          name     sector  sharpe ratio  FFM returns  \\\n",
+       "55    LYB                LyondellBasell  Materials      2.072393     0.103512   \n",
+       "65    NEM    Newmont Mining Corporation  Materials      1.248661     0.189686   \n",
+       "4     APD  Air Products & Chemicals Inc  Materials      1.224824     0.153161   \n",
+       "40    FCX         Freeport-McMoRan Inc.  Materials      1.031316     0.038646   \n",
+       "5     ALB                Albemarle Corp  Materials      0.990292     0.132207   \n",
+       "39    FMC               FMC Corporation  Materials      0.889526     0.193867   \n",
        "\n",
-       "     EPS  beta      mkt cap      shares  \n",
-       "55  9.55  1.45  27505799491   333000000  \n",
-       "65  2.78  0.16  36130286851   819839000  \n",
-       "4   8.51  0.86  56495776935   220678000  \n",
-       "40  0.16  2.42  17759187027  1450914000  \n",
-       "5   5.38  1.57   9504798055   106033000  \n",
-       "39  3.85  1.54  13670494208   129615000  "
+       "    P/E ratio   EPS  beta      mkt cap      shares  \n",
+       "55       8.65  9.55  1.45  27505799491   333000000  \n",
+       "65      15.83  2.78  0.16  36130286851   819839000  \n",
+       "4       30.09  8.51  0.86  56495776935   220678000  \n",
+       "40      78.35  0.16  2.42  17759187027  1450914000  \n",
+       "5       16.67  5.38  1.57   9504798055   106033000  \n",
+       "39      27.41  3.85  1.54  13670494208   129615000  "
       ]
      },
-     "execution_count": 46,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2386,7 +2719,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
@@ -2414,6 +2747,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -2428,6 +2762,7 @@
        "      <td>Host Hotels &amp; Resorts</td>\n",
        "      <td>Real Estate</td>\n",
        "      <td>2.308137</td>\n",
+       "      <td>0.052833</td>\n",
        "      <td>10.89</td>\n",
        "      <td>1.55</td>\n",
        "      <td>1.17</td>\n",
@@ -2440,6 +2775,7 @@
        "      <td>Iron Mountain Incorporated</td>\n",
        "      <td>Real Estate</td>\n",
        "      <td>2.233518</td>\n",
+       "      <td>0.073061</td>\n",
        "      <td>35.67</td>\n",
        "      <td>0.93</td>\n",
        "      <td>0.53</td>\n",
@@ -2452,6 +2788,7 @@
        "      <td>Equity Residential</td>\n",
        "      <td>Real Estate</td>\n",
        "      <td>2.158996</td>\n",
+       "      <td>0.089495</td>\n",
        "      <td>34.53</td>\n",
        "      <td>2.50</td>\n",
        "      <td>0.45</td>\n",
@@ -2464,6 +2801,7 @@
        "      <td>Crown Castle International Corp.</td>\n",
        "      <td>Real Estate</td>\n",
        "      <td>1.281977</td>\n",
+       "      <td>0.163975</td>\n",
        "      <td>83.64</td>\n",
        "      <td>1.98</td>\n",
        "      <td>0.30</td>\n",
@@ -2481,14 +2819,14 @@
        "32    EQR                Equity Residential  Real Estate      2.158996   \n",
        "28    CCI  Crown Castle International Corp.  Real Estate      1.281977   \n",
        "\n",
-       "    P/E ratio   EPS  beta      mkt cap     shares  \n",
-       "49      10.89  1.55  1.17  12127479870  717178000  \n",
-       "52      35.67  0.93  0.53   9521121824  287300000  \n",
-       "32      34.53  2.50  0.45  32134657027  371671000  \n",
-       "28      83.64  1.98  0.30  69005081855  415768000  "
+       "    FFM returns  P/E ratio   EPS  beta      mkt cap     shares  \n",
+       "49     0.052833      10.89  1.55  1.17  12127479870  717178000  \n",
+       "52     0.073061      35.67  0.93  0.53   9521121824  287300000  \n",
+       "32     0.089495      34.53  2.50  0.45  32134657027  371671000  \n",
+       "28     0.163975      83.64  1.98  0.30  69005081855  415768000  "
       ]
      },
-     "execution_count": 51,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2501,7 +2839,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -2529,6 +2867,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -2543,6 +2882,7 @@
        "      <td>PPL Corp.</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>2.755488</td>\n",
+       "      <td>0.098239</td>\n",
        "      <td>14.38</td>\n",
        "      <td>2.46</td>\n",
        "      <td>0.51</td>\n",
@@ -2555,6 +2895,7 @@
        "      <td>FirstEnergy Corp</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>1.510567</td>\n",
+       "      <td>0.129910</td>\n",
        "      <td>31.45</td>\n",
        "      <td>1.66</td>\n",
        "      <td>0.20</td>\n",
@@ -2567,6 +2908,7 @@
        "      <td>Alliant Energy Corp</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>1.366718</td>\n",
+       "      <td>0.166244</td>\n",
        "      <td>26.79</td>\n",
        "      <td>2.23</td>\n",
        "      <td>0.23</td>\n",
@@ -2579,6 +2921,7 @@
        "      <td>CenterPoint Energy</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>1.361230</td>\n",
+       "      <td>0.121502</td>\n",
        "      <td>21.58</td>\n",
        "      <td>1.26</td>\n",
        "      <td>0.44</td>\n",
@@ -2591,6 +2934,7 @@
        "      <td>AES Corp</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>1.182641</td>\n",
+       "      <td>0.162654</td>\n",
        "      <td>27.44</td>\n",
        "      <td>0.76</td>\n",
        "      <td>1.05</td>\n",
@@ -2603,6 +2947,7 @@
        "      <td>NextEra Energy</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>0.928683</td>\n",
+       "      <td>0.227986</td>\n",
        "      <td>34.73</td>\n",
        "      <td>8.02</td>\n",
        "      <td>0.15</td>\n",
@@ -2615,6 +2960,7 @@
        "      <td>NRG Energy</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>0.692217</td>\n",
+       "      <td>0.208670</td>\n",
        "      <td>10.31</td>\n",
        "      <td>3.89</td>\n",
        "      <td>0.71</td>\n",
@@ -2626,26 +2972,26 @@
        "</div>"
       ],
       "text/plain": [
-       "   ticker                 name     sector  sharpe ratio  P/E ratio   EPS  \\\n",
-       "73    PPL            PPL Corp.  Utilities      2.755488      14.38  2.46   \n",
-       "37     FE     FirstEnergy Corp  Utilities      1.510567      31.45  1.66   \n",
-       "6     LNT  Alliant Energy Corp  Utilities      1.366718      26.79  2.23   \n",
-       "23    CNP   CenterPoint Energy  Utilities      1.361230      21.58  1.26   \n",
-       "2     AES             AES Corp  Utilities      1.182641      27.44  0.76   \n",
-       "66    NEE       NextEra Energy  Utilities      0.928683      34.73  8.02   \n",
-       "67    NRG           NRG Energy  Utilities      0.692217      10.31  3.89   \n",
+       "   ticker                 name     sector  sharpe ratio  FFM returns  \\\n",
+       "73    PPL            PPL Corp.  Utilities      2.755488     0.098239   \n",
+       "37     FE     FirstEnergy Corp  Utilities      1.510567     0.129910   \n",
+       "6     LNT  Alliant Energy Corp  Utilities      1.366718     0.166244   \n",
+       "23    CNP   CenterPoint Energy  Utilities      1.361230     0.121502   \n",
+       "2     AES             AES Corp  Utilities      1.182641     0.162654   \n",
+       "66    NEE       NextEra Energy  Utilities      0.928683     0.227986   \n",
+       "67    NRG           NRG Energy  Utilities      0.692217     0.208670   \n",
        "\n",
-       "    beta       mkt cap     shares  \n",
-       "73  0.51   25573676437  723033000  \n",
-       "37  0.20   28241486749  540714000  \n",
-       "6   0.23   14358652779  244628000  \n",
-       "23  0.44   13650929559  502242000  \n",
-       "2   1.05   13895280692  663893000  \n",
-       "66  0.15  136133886150  488776000  \n",
-       "67  0.71   10078855985  251594000  "
+       "    P/E ratio   EPS  beta       mkt cap     shares  \n",
+       "73      14.38  2.46  0.51   25573676437  723033000  \n",
+       "37      31.45  1.66  0.20   28241486749  540714000  \n",
+       "6       26.79  2.23  0.23   14358652779  244628000  \n",
+       "23      21.58  1.26  0.44   13650929559  502242000  \n",
+       "2       27.44  0.76  1.05   13895280692  663893000  \n",
+       "66      34.73  8.02  0.15  136133886150  488776000  \n",
+       "67      10.31  3.89  0.71   10078855985  251594000  "
       ]
      },
-     "execution_count": 52,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2658,7 +3004,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -2686,6 +3032,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -2700,6 +3047,7 @@
        "      <td>Genuine Parts</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>2.924464</td>\n",
+       "      <td>0.074228</td>\n",
        "      <td>17.71</td>\n",
        "      <td>5.45</td>\n",
        "      <td>0.89</td>\n",
@@ -2712,6 +3060,7 @@
        "      <td>General Mills</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>2.641281</td>\n",
+       "      <td>0.063147</td>\n",
        "      <td>15.34</td>\n",
        "      <td>3.48</td>\n",
        "      <td>0.73</td>\n",
@@ -2724,6 +3073,7 @@
        "      <td>Cabot Oil &amp; Gas</td>\n",
        "      <td>Energy</td>\n",
        "      <td>1.952983</td>\n",
+       "      <td>-0.050017</td>\n",
        "      <td>7.80</td>\n",
        "      <td>1.90</td>\n",
        "      <td>0.47</td>\n",
@@ -2736,6 +3086,7 @@
        "      <td>Synchrony Financial</td>\n",
        "      <td>Financials</td>\n",
        "      <td>2.493336</td>\n",
+       "      <td>0.091836</td>\n",
        "      <td>6.07</td>\n",
        "      <td>5.56</td>\n",
        "      <td>1.21</td>\n",
@@ -2748,6 +3099,7 @@
        "      <td>Amgen Inc</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>1.861649</td>\n",
+       "      <td>0.151749</td>\n",
        "      <td>17.36</td>\n",
        "      <td>12.88</td>\n",
        "      <td>1.12</td>\n",
@@ -2760,6 +3112,7 @@
        "      <td>Southwest Airlines</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>1.726576</td>\n",
+       "      <td>0.107833</td>\n",
        "      <td>13.77</td>\n",
        "      <td>4.21</td>\n",
        "      <td>1.47</td>\n",
@@ -2772,6 +3125,7 @@
        "      <td>Alphabet Inc Class A</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.198026</td>\n",
+       "      <td>0.214640</td>\n",
        "      <td>30.89</td>\n",
        "      <td>49.16</td>\n",
        "      <td>1.02</td>\n",
@@ -2784,6 +3138,7 @@
        "      <td>LyondellBasell</td>\n",
        "      <td>Materials</td>\n",
        "      <td>2.072393</td>\n",
+       "      <td>0.103512</td>\n",
        "      <td>8.65</td>\n",
        "      <td>9.55</td>\n",
        "      <td>1.45</td>\n",
@@ -2796,6 +3151,7 @@
        "      <td>Host Hotels &amp; Resorts</td>\n",
        "      <td>Real Estate</td>\n",
        "      <td>2.308137</td>\n",
+       "      <td>0.052833</td>\n",
        "      <td>10.89</td>\n",
        "      <td>1.55</td>\n",
        "      <td>1.17</td>\n",
@@ -2808,6 +3164,7 @@
        "      <td>PPL Corp.</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>2.755488</td>\n",
+       "      <td>0.098239</td>\n",
        "      <td>14.38</td>\n",
        "      <td>2.46</td>\n",
        "      <td>0.51</td>\n",
@@ -2831,20 +3188,20 @@
        "8    HST  Host Hotels & Resorts             Real Estate      2.308137   \n",
        "9    PPL              PPL Corp.               Utilities      2.755488   \n",
        "\n",
-       "   P/E ratio    EPS  beta        mkt cap     shares  \n",
-       "0      17.71   5.45  0.89    14016415887  145293000  \n",
-       "1      15.34   3.48  0.73    32242795100  604817000  \n",
-       "2       7.80   1.90  0.47     6037284157  407925000  \n",
-       "3       6.07   5.56  1.21    20704848750  613477000  \n",
-       "4      17.36  12.88  1.12   131810065840  589807000  \n",
-       "5      13.77   4.21  1.47    29987649751  517296000  \n",
-       "6      30.89  49.16  1.02  1044236513876  299895000  \n",
-       "7       8.65   9.55  1.45    27505799491  333000000  \n",
-       "8      10.89   1.55  1.17    12127479870  717178000  \n",
-       "9      14.38   2.46  0.51    25573676437  723033000  "
+       "   FFM returns  P/E ratio    EPS  beta        mkt cap     shares  \n",
+       "0     0.074228      17.71   5.45  0.89    14016415887  145293000  \n",
+       "1     0.063147      15.34   3.48  0.73    32242795100  604817000  \n",
+       "2    -0.050017       7.80   1.90  0.47     6037284157  407925000  \n",
+       "3     0.091836       6.07   5.56  1.21    20704848750  613477000  \n",
+       "4     0.151749      17.36  12.88  1.12   131810065840  589807000  \n",
+       "5     0.107833      13.77   4.21  1.47    29987649751  517296000  \n",
+       "6     0.214640      30.89  49.16  1.02  1044236513876  299895000  \n",
+       "7     0.103512       8.65   9.55  1.45    27505799491  333000000  \n",
+       "8     0.052833      10.89   1.55  1.17    12127479870  717178000  \n",
+       "9     0.098239      14.38   2.46  0.51    25573676437  723033000  "
       ]
      },
-     "execution_count": 66,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/.ipynb_checkpoints/selection_data-checkpoint.csv b/.ipynb_checkpoints/selection_data-checkpoint.csv
deleted file mode 100644
index 1ca7832..0000000
--- a/.ipynb_checkpoints/selection_data-checkpoint.csv
+++ /dev/null
@@ -1,93 +0,0 @@
-ticker,name,sector,sharpe ratio,P/E ratio,EPS,beta,mkt cap,shares
-ACN,Accenture plc,Information Technology,1.113857669340631,28.34,7.49,1.03,139515576338,656946000
-ADBE,Adobe Systems Inc,Information Technology,0.6160597494509739,63.17,6.01,1.09,185174936969,487726000
-AES,AES Corp,Utilities,1.1826406099615412,27.44,0.76,1.05,13895280692,663893000
-AMG,Affiliated Managers Group Inc,Financials,1.0979859640832188,267.18,0.31,1.69,4084648875,49272000
-APD,Air Products & Chemicals Inc,Materials,1.2248244816385878,30.09,8.51,0.86,56495776935,220678000
-ALB,Albemarle Corp,Materials,0.9902917360691272,16.67,5.38,1.57,9504798055,106033000
-LNT,Alliant Energy Corp,Utilities,1.366717870072912,26.79,2.23,0.23,14358652779,244628000
-GOOGL,Alphabet Inc Class A,Information Technology,1.1980263475215909,30.89,49.16,1.02,1044236513876,299895000
-AXP,American Express Co,Financials,1.2144084830799449,17.01,7.99,0.99,111178449600,808041000
-ABC,AmerisourceBergen Corp,Health Care,2.824204459596733,30.62,3.08,1.01,19427969245,205892000
-AMGN,Amgen Inc,Health Care,1.8616491950461436,17.36,12.88,1.12,131810065840,589807000
-AON,Aon plc,Financials,1.1043185924986845,37.0,6.37,0.83,54701475530,234137000
-AAPL,Apple Inc.,Information Technology,0.9190627984536254,25.66,12.66,1.29,1421812279411,4375480000
-AJG,Arthur J. Gallagher & Co.,Financials,0.9671115946025484,31.03,3.52,0.76,20549043209,188247000
-ADP,Automatic Data Processing,Information Technology,1.0045789926171458,32.04,5.66,0.87,78255412500,431754000
-BBY,Best Buy Co. Inc.,Consumer Discretionary,0.8239151677600225,15.98,5.64,1.12,23344272933,258777000
-HRB,Block H&R,Financials,2.2106749521427664,11.75,1.9,0.23,4369605316,195246000
-BWA,BorgWarner,Consumer Discretionary,1.6822710938226986,9.2,3.71,1.91,7048901814,206410000
-BSX,Boston Scientific,Health Care,0.933786790381214,12.7,3.33,0.87,58972695354,1393824000
-BMY,Bristol-Myers Squibb,Health Care,2.6885152748619983,33.05,2.01,0.76,155607591281,2344185000
-COG,Cabot Oil & Gas,Energy,1.9529827367707384,7.8,1.9,0.47,6037284157,407925000
-COF,Capital One Financial,Financials,2.0347637955056546,9.31,11.02,1.25,46865423721,456600000
-KMX,Carmax Inc,Consumer Discretionary,1.703158159266752,19.16,5.16,1.1,16144071451,163385000
-CNP,CenterPoint Energy,Utilities,1.3612303069648497,21.58,1.26,0.44,13650929559,502242000
-CINF,Cincinnati Financial,Financials,1.121373755776759,9.52,12.1,0.57,18822318390,163374000
-CTAS,Cintas Corporation,Industrials,0.7031855337517299,35.38,8.51,0.99,31216601386,103751000
-KO,Coca-Cola Company (The),Consumer Staples,2.1971578395739524,28.99,2.07,0.41,256586003265,4280000000
-COST,Costco Wholesale Corp.,Consumer Staples,1.0606439166888946,37.75,8.43,0.9,140615987901,441758000
-CCI,Crown Castle International Corp.,Real Estate,1.28197687434905,83.64,1.98,0.3,69005081855,415768000
-CVS,CVS Health,Consumer Staples,1.7079627340498365,14.05,5.08,0.93,92849804253,1300964000
-DISCK,Discovery Communications-C,Consumer Discretionary,2.3096592718590108,11.1,2.59,1.45,15392873644,360664000
-ETN,Eaton Corporation,Industrials,1.6047656571399305,19.71,5.25,1.42,42807571261,413400000
-EQR,Equity Residential,Real Estate,2.1589960066234664,34.53,2.5,0.45,32134657027,371671000
-EXPE,Expedia Inc.,Consumer Discretionary,2.407311381193101,32.58,3.77,1.01,17792025802,139363000
-FFIV,F5 Networks,Information Technology,1.7013819459588144,19.49,6.54,0.98,7753118169,60804000
-FB,"Facebook, Inc.",Information Technology,1.1057666021536463,33.32,6.43,1.05,610509360122,2405746000
-FDX,FedEx Corporation,Industrials,1.5098202059987225,583.74,0.27,1.71,41418694505,261119000
-FE,FirstEnergy Corp,Utilities,1.510567029063732,31.45,1.66,0.2,28241486749,540714000
-FISV,Fiserv Inc,Information Technology,0.9488954080578804,71.58,1.71,0.8,83164756192,679895000
-FMC,FMC Corporation,Materials,0.8895256452785432,27.41,3.85,1.54,13670494208,129615000
-FCX,Freeport-McMoRan Inc.,Materials,1.0313162803944909,78.35,0.16,2.42,17759187027,1450914000
-IT,Gartner Inc,Information Technology,1.3373284476702674,59.34,2.57,1.21,13633532057,89453000
-GIS,General Mills,Consumer Staples,2.6412807761987938,15.34,3.48,0.73,32242795100,604817000
-GM,General Motors,Consumer Discretionary,1.9037211165069965,7.6,4.57,1.38,49672072361,1429002000
-GPC,Genuine Parts,Consumer Discretionary,2.9244641954801547,17.71,5.45,0.89,14016415887,145293000
-GS,Goldman Sachs Group,Financials,1.8288212830340496,11.27,21.03,1.32,83946946608,354087000
-GWW,Grainger (W.W.) Inc.,Industrials,1.3581101466189422,17.94,17.15,0.97,16517112872,53688000
-HLT,Hilton Worldwide Holdings Inc,Consumer Discretionary,1.0598993481607704,37.27,3.04,1.14,31415437971,277448000
-HOLX,Hologic,Health Care,2.425411589403344,173.01,0.31,0.85,13960272160,263302000
-HST,Host Hotels & Resorts,Real Estate,2.308137021714921,10.89,1.55,1.17,12127479870,717178000
-HII,Huntington Ingalls Industries,Industrials,1.1543380976790991,18.57,13.26,1.24,10035519873,40760000
-INCY,Incyte,Health Care,1.2682583277151145,38.21,2.05,1.06,17006076538,216776000
-IRM,Iron Mountain Incorporated,Real Estate,2.2335183274879347,35.67,0.93,0.53,9521121824,287300000
-KMI,Kinder Morgan,Energy,1.0384695673083184,22.87,0.96,0.81,49831386000,2265063000
-LKQ,LKQ Corporation,Consumer Discretionary,2.216065603315,23.73,1.4,1.3,10174538633,306462000
-LYB,LyondellBasell,Materials,2.072392824468477,8.65,9.55,1.45,27505799491,333000000
-M,Macy's Inc.,Consumer Discretionary,0.8264829931760201,5.39,3.09,0.66,5150446573,308965000
-MDT,Medtronic plc,Health Care,1.9179209088058464,33.97,3.45,0.6,157266553194,1340378000
-MRK,Merck & Co.,Health Care,1.3680581566358117,21.52,3.84,0.57,210425581484,2545984000
-MTD,Mettler Toledo,Health Care,0.9692418639176908,33.97,22.47,1.39,18357249893,24053000
-MSFT,Microsoft Corp.,Information Technology,0.6881506526553905,32.28,5.74,1.15,1409780857873,7606047000
-MHK,Mohawk Industries,Consumer Discretionary,1.2551682079723412,13.4,10.3,1.36,9882403253,71622000
-MCO,Moody's Corp,Financials,0.927983578033472,37.43,7.42,1.21,52148688479,187700000
-MSI,Motorola Solutions Inc.,Information Technology,0.7857028051967873,37.31,4.94,0.5,31596072387,171336000
-MYL,Mylan N.V.,Health Care,0.8932799452587622,239.58,0.09,1.72,11303303743,516177000
-NEM,Newmont Mining Corporation,Materials,1.2486611843780435,15.83,2.78,0.16,36130286851,819839000
-NEE,NextEra Energy,Utilities,0.9286832114176752,34.73,8.02,0.15,136133886150,488776000
-NRG,NRG Energy,Utilities,0.6922170062921974,10.31,3.89,0.71,10078855985,251594000
-OXY,Occidental Petroleum,Energy,2.054770999686784,29.53,1.41,0.9,37161985836,893317000
-OKE,ONEOK,Energy,0.9173258155980414,25.56,3.01,1.11,31799253894,413085000
-ORCL,Oracle Corp.,Information Technology,1.9496194449404018,17.61,3.15,1.11,177928293945,3207649000
-PEP,PepsiCo Inc.,Consumer Staples,1.9512497779197016,28.31,5.19,0.53,204968008309,1389545000
-RL,Polo Ralph Lauren Corp.,Consumer Discretionary,1.6850277667707554,14.16,8.61,0.9,8984857815,48862000
-PPL,PPL Corp.,Utilities,2.7554877393877537,14.38,2.46,0.51,25573676437,723033000
-PHM,Pulte Homes Inc.,Consumer Discretionary,1.1252252514376082,12.77,3.66,0.56,12605132379,269975000
-RJF,Raymond James Financial Inc.,Financials,1.2811378025870532,13.44,7.36,1.5,13782151374,139284000
-RTN,Raytheon Co.,Industrials,1.158337993905323,19.05,11.93,0.85,63256224340,278441000
-RMD,ResMed,Health Care,0.834963320137938,56.31,3.14,0.48,25539363082,144617000
-RCL,Royal Caribbean Cruises Ltd,Consumer Discretionary,1.3470625587214564,12.55,9.02,1.44,23627921924,208801000
-CRM,Salesforce.com,Information Technology,0.8858414532311987,200.68,0.95,1.19,168485647293,887000000
-LUV,Southwest Airlines,Industrials,1.7265757683369565,13.77,4.21,1.47,29987649751,517296000
-SBUX,Starbucks Corp.,Consumer Discretionary,1.3884881607519866,29.15,3.06,0.56,104787934567,1173700000
-SYF,Synchrony Financial,Financials,2.4933359586834767,6.07,5.56,1.21,20704848750,613477000
-SNPS,Synopsys Inc.,Information Technology,0.8013663430252196,47.31,3.45,1.18,24589893168,150535000
-TGT,Target Corp.,Consumer Discretionary,1.340881991913131,18.64,6.26,0.56,59100734918,506737000
-TXN,Texas Instruments,Information Technology,0.8862468117623082,25.24,5.24,1.24,123223956977,932032000
-HSY,The Hershey Company,Consumer Staples,1.4696819942330823,29.33,5.47,0.02,23779704176,148308000
-TMO,Thermo Fisher Scientific,Health Care,0.9572371356767688,36.98,9.17,1.14,136012138268,400991000
-UNH,United Health Group Inc.,Health Care,0.8928925321222835,20.86,14.33,0.69,283068652543,947415000
-VFC,V.F. Corp.,Consumer Discretionary,1.3232414086548459,25.99,3.22,1.2,33022293377,394720000
-WMT,Wal-Mart Stores,Consumer Staples,1.2710964130621618,23.55,5.0,0.36,334474559018,2837175000
-WBA,Walgreens Boots Alliance,Consumer Staples,2.224201311650672,13.0,4.07,0.92,46817805348,885862000
diff --git a/ffmreturns.csv b/ffmreturns.csv
new file mode 100644
index 0000000..1bf6314
--- /dev/null
+++ b/ffmreturns.csv
@@ -0,0 +1,101 @@
+Stock,FFM Returns
+ADBE,0.329761028
+MSFT,0.32250065
+CTAS,0.2859733
+BBY,0.264073092
+SNPS,0.258978767
+FISV,0.249902978
+UNH,0.243093824
+FB,0.238789094
+RMD,0.23631678
+AAPL,0.236049322
+MCO,0.234858117
+BSX,0.233860621
+BA,0.233236127
+MTD,0.23289527
+MSI,0.231468305
+OKE,0.230147782
+NEE,0.227986191
+ACN,0.225818128
+TXN,0.224912306
+TMO,0.223396092
+GOOGL,0.214639843
+DXC,0.210906153
+NRG,0.208669696
+CRM,0.207470204
+CINF,0.199837867
+RCL,0.195659444
+AJG,0.195583018
+RTN,0.19479614
+FMC,0.193866857
+COST,0.192129974
+NEM,0.189685796
+TGT,0.185069819
+ADP,0.183269476
+AON,0.183167419
+SBUX,0.177744967
+HII,0.172309762
+HLT,0.171046851
+LNT,0.166244327
+IT,0.165213744
+PHM,0.16513204
+CCI,0.163975237
+AES,0.162653808
+RJF,0.1550463
+APD,0.153160881
+AMGN,0.151748658
+MRK,0.147015861
+MGM,0.146332879
+GWW,0.143753783
+EFX,0.140914861
+AXP,0.132252227
+ALB,0.132207229
+HOLX,0.129967712
+FE,0.129909559
+VFC,0.129110804
+ETN,0.128998261
+HSY,0.125085342
+WMT,0.125054707
+MDT,0.12421349
+LKQ,0.121771661
+CNP,0.121501687
+PEP,0.117935265
+COF,0.116104299
+EIX,0.11470824
+LUV,0.107832862
+KO,0.103820149
+LYB,0.103512466
+GS,0.099914539
+KMX,0.099285234
+PPL,0.098239274
+SYF,0.091836098
+EQR,0.08949458
+EXPE,0.086285553
+GM,0.08449462
+BMY,0.083176807
+ORCL,0.077350148
+INCY,0.076793095
+GPC,0.074228025
+IRM,0.073060731
+FFIV,0.064989396
+GIS,0.063146888
+DISCK,0.061552496
+HST,0.052833242
+RL,0.046267077
+FCX,0.038646264
+NWS,0.025555928
+FDX,0.02425391
+ABC,0.018486986
+HRB,0.001103738
+WBA,-0.007405433
+BWA,-0.008936781
+CVS,-0.010387317
+MHK,-0.016397061
+NBL,-0.038133714
+KMI,-0.038511214
+OXY,-0.042821394
+COG,-0.050016632
+SRCL,-0.085880676
+M,-0.12659805
+MYL,-0.130828848
+AMG,-0.138798233
\ No newline at end of file
diff --git a/selection_criteria.ipynb b/selection_criteria.ipynb
index 3f8e59f..2b53187 100644
--- a/selection_criteria.ipynb
+++ b/selection_criteria.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -127,7 +127,7 @@
        "[505 rows x 2 columns]"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -141,7 +141,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -240,7 +240,7 @@
        "[100 rows x 1 columns]"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -254,7 +254,120 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>FFM Returns</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Stock</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>ADBE</th>\n",
+       "      <td>0.329761</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>MSFT</th>\n",
+       "      <td>0.322501</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CTAS</th>\n",
+       "      <td>0.285973</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>BBY</th>\n",
+       "      <td>0.264073</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SNPS</th>\n",
+       "      <td>0.258979</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>COG</th>\n",
+       "      <td>-0.050017</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SRCL</th>\n",
+       "      <td>-0.085881</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>M</th>\n",
+       "      <td>-0.126598</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>MYL</th>\n",
+       "      <td>-0.130829</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AMG</th>\n",
+       "      <td>-0.138798</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>100 rows × 1 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       FFM Returns\n",
+       "Stock             \n",
+       "ADBE      0.329761\n",
+       "MSFT      0.322501\n",
+       "CTAS      0.285973\n",
+       "BBY       0.264073\n",
+       "SNPS      0.258979\n",
+       "...            ...\n",
+       "COG      -0.050017\n",
+       "SRCL     -0.085881\n",
+       "M        -0.126598\n",
+       "MYL      -0.130829\n",
+       "AMG      -0.138798\n",
+       "\n",
+       "[100 rows x 1 columns]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# importing sharpe ratio data\n",
+    "ffm_path = Path('ffmreturns.csv')\n",
+    "ffm_df = pd.read_csv(ffm_path, index_col = 'Stock')\n",
+    "ffm_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -405,7 +518,7 @@
        "[100 rows x 5 columns]"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -419,7 +532,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -447,6 +560,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -461,6 +575,7 @@
        "      <td>Accenture plc</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.113858</td>\n",
+       "      <td>0.225818</td>\n",
        "      <td>28.34</td>\n",
        "      <td>7.49</td>\n",
        "      <td>1.03</td>\n",
@@ -473,6 +588,7 @@
        "      <td>Adobe Systems Inc</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.616060</td>\n",
+       "      <td>0.329761</td>\n",
        "      <td>63.17</td>\n",
        "      <td>6.01</td>\n",
        "      <td>1.09</td>\n",
@@ -485,6 +601,7 @@
        "      <td>AES Corp</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>1.182641</td>\n",
+       "      <td>0.162654</td>\n",
        "      <td>27.44</td>\n",
        "      <td>0.76</td>\n",
        "      <td>1.05</td>\n",
@@ -497,6 +614,7 @@
        "      <td>Affiliated Managers Group Inc</td>\n",
        "      <td>Financials</td>\n",
        "      <td>1.097986</td>\n",
+       "      <td>-0.138798</td>\n",
        "      <td>267.18</td>\n",
        "      <td>0.31</td>\n",
        "      <td>1.69</td>\n",
@@ -509,6 +627,7 @@
        "      <td>Air Products &amp; Chemicals Inc</td>\n",
        "      <td>Materials</td>\n",
        "      <td>1.224824</td>\n",
+       "      <td>0.153161</td>\n",
        "      <td>30.09</td>\n",
        "      <td>8.51</td>\n",
        "      <td>0.86</td>\n",
@@ -526,6 +645,7 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
+       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>87</th>\n",
@@ -533,6 +653,7 @@
        "      <td>Thermo Fisher Scientific</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.957237</td>\n",
+       "      <td>0.223396</td>\n",
        "      <td>36.98</td>\n",
        "      <td>9.17</td>\n",
        "      <td>1.14</td>\n",
@@ -545,6 +666,7 @@
        "      <td>United Health Group Inc.</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.892893</td>\n",
+       "      <td>0.243094</td>\n",
        "      <td>20.86</td>\n",
        "      <td>14.33</td>\n",
        "      <td>0.69</td>\n",
@@ -557,6 +679,7 @@
        "      <td>V.F. Corp.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.323241</td>\n",
+       "      <td>0.129111</td>\n",
        "      <td>25.99</td>\n",
        "      <td>3.22</td>\n",
        "      <td>1.20</td>\n",
@@ -569,6 +692,7 @@
        "      <td>Wal-Mart Stores</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>1.271096</td>\n",
+       "      <td>0.125055</td>\n",
        "      <td>23.55</td>\n",
        "      <td>5.00</td>\n",
        "      <td>0.36</td>\n",
@@ -581,6 +705,7 @@
        "      <td>Walgreens Boots Alliance</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>2.224201</td>\n",
+       "      <td>-0.007405</td>\n",
        "      <td>13.00</td>\n",
        "      <td>4.07</td>\n",
        "      <td>0.92</td>\n",
@@ -589,7 +714,7 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>92 rows × 9 columns</p>\n",
+       "<p>92 rows × 10 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -606,33 +731,46 @@
        "90    WMT                Wal-Mart Stores        Consumer Staples   \n",
        "91    WBA       Walgreens Boots Alliance        Consumer Staples   \n",
        "\n",
-       "    sharpe ratio  P/E ratio    EPS  beta       mkt cap      shares  \n",
-       "0       1.113858      28.34   7.49  1.03  139515576338   656946000  \n",
-       "1       0.616060      63.17   6.01  1.09  185174936969   487726000  \n",
-       "2       1.182641      27.44   0.76  1.05   13895280692   663893000  \n",
-       "3       1.097986     267.18   0.31  1.69    4084648875    49272000  \n",
-       "4       1.224824      30.09   8.51  0.86   56495776935   220678000  \n",
-       "..           ...        ...    ...   ...           ...         ...  \n",
-       "87      0.957237      36.98   9.17  1.14  136012138268   400991000  \n",
-       "88      0.892893      20.86  14.33  0.69  283068652543   947415000  \n",
-       "89      1.323241      25.99   3.22  1.20   33022293377   394720000  \n",
-       "90      1.271096      23.55   5.00  0.36  334474559018  2837175000  \n",
-       "91      2.224201      13.00   4.07  0.92   46817805348   885862000  \n",
+       "    sharpe ratio  FFM returns  P/E ratio    EPS  beta       mkt cap  \\\n",
+       "0       1.113858     0.225818      28.34   7.49  1.03  139515576338   \n",
+       "1       0.616060     0.329761      63.17   6.01  1.09  185174936969   \n",
+       "2       1.182641     0.162654      27.44   0.76  1.05   13895280692   \n",
+       "3       1.097986    -0.138798     267.18   0.31  1.69    4084648875   \n",
+       "4       1.224824     0.153161      30.09   8.51  0.86   56495776935   \n",
+       "..           ...          ...        ...    ...   ...           ...   \n",
+       "87      0.957237     0.223396      36.98   9.17  1.14  136012138268   \n",
+       "88      0.892893     0.243094      20.86  14.33  0.69  283068652543   \n",
+       "89      1.323241     0.129111      25.99   3.22  1.20   33022293377   \n",
+       "90      1.271096     0.125055      23.55   5.00  0.36  334474559018   \n",
+       "91      2.224201    -0.007405      13.00   4.07  0.92   46817805348   \n",
+       "\n",
+       "        shares  \n",
+       "0    656946000  \n",
+       "1    487726000  \n",
+       "2    663893000  \n",
+       "3     49272000  \n",
+       "4    220678000  \n",
+       "..         ...  \n",
+       "87   400991000  \n",
+       "88   947415000  \n",
+       "89   394720000  \n",
+       "90  2837175000  \n",
+       "91   885862000  \n",
        "\n",
-       "[92 rows x 9 columns]"
+       "[92 rows x 10 columns]"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# concatenating the datasets and dropping nulls\n",
-    "merged_df = pd.concat([sp500_df,sharpe_df,stock_data_df], axis='columns', join='inner')\n",
+    "merged_df = pd.concat([sp500_df,sharpe_df,ffm_df,stock_data_df], axis='columns', join='inner')\n",
     "merged_df.dropna(inplace=True)\n",
     "merged_df.reset_index(inplace=True)\n",
-    "merged_df.columns = ['ticker','name','sector','sharpe ratio','P/E ratio','EPS','beta','mkt cap','shares']\n",
+    "merged_df.columns = ['ticker','name','sector','sharpe ratio','FFM returns','P/E ratio','EPS','beta','mkt cap','shares']\n",
     "merged_df"
    ]
   },
@@ -719,7 +857,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'FFM Returns')"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1800x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# plotting returns\n",
+    "merged_df.plot(x='ticker',y='FFM returns', kind='bar', figsize=(25,10))\n",
+    "plt.suptitle('FFM Returns in Investment Universe', fontsize=30)\n",
+    "plt.xlabel('Company Ticker',fontsize=20)\n",
+    "plt.ylabel('FFM Returns',fontsize=20)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -732,9 +906,60 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  after removing the cwd from sys.path.\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:8: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  \n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:12: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  if sys.path[0] == '':\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:16: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  app.launch_new_instance()\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:20: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:24: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:28: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:32: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:36: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:40: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n"
+     ]
+    }
+   ],
    "source": [
     "# creating datasets for each sector\n",
     "cd_mask = merged_df['sector'] == 'Consumer Discretionary'\n",
@@ -780,7 +1005,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -808,6 +1033,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -822,6 +1048,7 @@
        "      <td>Genuine Parts</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>2.924464</td>\n",
+       "      <td>0.074228</td>\n",
        "      <td>17.71</td>\n",
        "      <td>5.45</td>\n",
        "      <td>0.89</td>\n",
@@ -834,6 +1061,7 @@
        "      <td>Expedia Inc.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>2.407311</td>\n",
+       "      <td>0.086286</td>\n",
        "      <td>32.58</td>\n",
        "      <td>3.77</td>\n",
        "      <td>1.01</td>\n",
@@ -846,6 +1074,7 @@
        "      <td>Discovery Communications-C</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>2.309659</td>\n",
+       "      <td>0.061552</td>\n",
        "      <td>11.10</td>\n",
        "      <td>2.59</td>\n",
        "      <td>1.45</td>\n",
@@ -858,6 +1087,7 @@
        "      <td>LKQ Corporation</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>2.216066</td>\n",
+       "      <td>0.121772</td>\n",
        "      <td>23.73</td>\n",
        "      <td>1.40</td>\n",
        "      <td>1.30</td>\n",
@@ -870,6 +1100,7 @@
        "      <td>General Motors</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.903721</td>\n",
+       "      <td>0.084495</td>\n",
        "      <td>7.60</td>\n",
        "      <td>4.57</td>\n",
        "      <td>1.38</td>\n",
@@ -882,6 +1113,7 @@
        "      <td>Carmax Inc</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.703158</td>\n",
+       "      <td>0.099285</td>\n",
        "      <td>19.16</td>\n",
        "      <td>5.16</td>\n",
        "      <td>1.10</td>\n",
@@ -894,6 +1126,7 @@
        "      <td>Polo Ralph Lauren Corp.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.685028</td>\n",
+       "      <td>0.046267</td>\n",
        "      <td>14.16</td>\n",
        "      <td>8.61</td>\n",
        "      <td>0.90</td>\n",
@@ -906,6 +1139,7 @@
        "      <td>BorgWarner</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.682271</td>\n",
+       "      <td>-0.008937</td>\n",
        "      <td>9.20</td>\n",
        "      <td>3.71</td>\n",
        "      <td>1.91</td>\n",
@@ -918,6 +1152,7 @@
        "      <td>Starbucks Corp.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.388488</td>\n",
+       "      <td>0.177745</td>\n",
        "      <td>29.15</td>\n",
        "      <td>3.06</td>\n",
        "      <td>0.56</td>\n",
@@ -930,6 +1165,7 @@
        "      <td>Royal Caribbean Cruises Ltd</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.347063</td>\n",
+       "      <td>0.195659</td>\n",
        "      <td>12.55</td>\n",
        "      <td>9.02</td>\n",
        "      <td>1.44</td>\n",
@@ -942,6 +1178,7 @@
        "      <td>Target Corp.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.340882</td>\n",
+       "      <td>0.185070</td>\n",
        "      <td>18.64</td>\n",
        "      <td>6.26</td>\n",
        "      <td>0.56</td>\n",
@@ -954,6 +1191,7 @@
        "      <td>V.F. Corp.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.323241</td>\n",
+       "      <td>0.129111</td>\n",
        "      <td>25.99</td>\n",
        "      <td>3.22</td>\n",
        "      <td>1.20</td>\n",
@@ -966,6 +1204,7 @@
        "      <td>Mohawk Industries</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.255168</td>\n",
+       "      <td>-0.016397</td>\n",
        "      <td>13.40</td>\n",
        "      <td>10.30</td>\n",
        "      <td>1.36</td>\n",
@@ -978,6 +1217,7 @@
        "      <td>Pulte Homes Inc.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.125225</td>\n",
+       "      <td>0.165132</td>\n",
        "      <td>12.77</td>\n",
        "      <td>3.66</td>\n",
        "      <td>0.56</td>\n",
@@ -990,6 +1230,7 @@
        "      <td>Hilton Worldwide Holdings Inc</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>1.059899</td>\n",
+       "      <td>0.171047</td>\n",
        "      <td>37.27</td>\n",
        "      <td>3.04</td>\n",
        "      <td>1.14</td>\n",
@@ -1002,6 +1243,7 @@
        "      <td>Macy's Inc.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>0.826483</td>\n",
+       "      <td>-0.126598</td>\n",
        "      <td>5.39</td>\n",
        "      <td>3.09</td>\n",
        "      <td>0.66</td>\n",
@@ -1014,6 +1256,7 @@
        "      <td>Best Buy Co. Inc.</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>0.823915</td>\n",
+       "      <td>0.264073</td>\n",
        "      <td>15.98</td>\n",
        "      <td>5.64</td>\n",
        "      <td>1.12</td>\n",
@@ -1044,27 +1287,46 @@
        "56      M                    Macy's Inc.  Consumer Discretionary   \n",
        "15    BBY              Best Buy Co. Inc.  Consumer Discretionary   \n",
        "\n",
-       "    sharpe ratio  P/E ratio    EPS  beta       mkt cap      shares  \n",
-       "44      2.924464      17.71   5.45  0.89   14016415887   145293000  \n",
-       "33      2.407311      32.58   3.77  1.01   17792025802   139363000  \n",
-       "30      2.309659      11.10   2.59  1.45   15392873644   360664000  \n",
-       "54      2.216066      23.73   1.40  1.30   10174538633   306462000  \n",
-       "43      1.903721       7.60   4.57  1.38   49672072361  1429002000  \n",
-       "22      1.703158      19.16   5.16  1.10   16144071451   163385000  \n",
-       "72      1.685028      14.16   8.61  0.90    8984857815    48862000  \n",
-       "17      1.682271       9.20   3.71  1.91    7048901814   206410000  \n",
-       "81      1.388488      29.15   3.06  0.56  104787934567  1173700000  \n",
-       "78      1.347063      12.55   9.02  1.44   23627921924   208801000  \n",
-       "84      1.340882      18.64   6.26  0.56   59100734918   506737000  \n",
-       "89      1.323241      25.99   3.22  1.20   33022293377   394720000  \n",
-       "61      1.255168      13.40  10.30  1.36    9882403253    71622000  \n",
-       "74      1.125225      12.77   3.66  0.56   12605132379   269975000  \n",
-       "47      1.059899      37.27   3.04  1.14   31415437971   277448000  \n",
-       "56      0.826483       5.39   3.09  0.66    5150446573   308965000  \n",
-       "15      0.823915      15.98   5.64  1.12   23344272933   258777000  "
+       "    sharpe ratio  FFM returns  P/E ratio    EPS  beta       mkt cap  \\\n",
+       "44      2.924464     0.074228      17.71   5.45  0.89   14016415887   \n",
+       "33      2.407311     0.086286      32.58   3.77  1.01   17792025802   \n",
+       "30      2.309659     0.061552      11.10   2.59  1.45   15392873644   \n",
+       "54      2.216066     0.121772      23.73   1.40  1.30   10174538633   \n",
+       "43      1.903721     0.084495       7.60   4.57  1.38   49672072361   \n",
+       "22      1.703158     0.099285      19.16   5.16  1.10   16144071451   \n",
+       "72      1.685028     0.046267      14.16   8.61  0.90    8984857815   \n",
+       "17      1.682271    -0.008937       9.20   3.71  1.91    7048901814   \n",
+       "81      1.388488     0.177745      29.15   3.06  0.56  104787934567   \n",
+       "78      1.347063     0.195659      12.55   9.02  1.44   23627921924   \n",
+       "84      1.340882     0.185070      18.64   6.26  0.56   59100734918   \n",
+       "89      1.323241     0.129111      25.99   3.22  1.20   33022293377   \n",
+       "61      1.255168    -0.016397      13.40  10.30  1.36    9882403253   \n",
+       "74      1.125225     0.165132      12.77   3.66  0.56   12605132379   \n",
+       "47      1.059899     0.171047      37.27   3.04  1.14   31415437971   \n",
+       "56      0.826483    -0.126598       5.39   3.09  0.66    5150446573   \n",
+       "15      0.823915     0.264073      15.98   5.64  1.12   23344272933   \n",
+       "\n",
+       "        shares  \n",
+       "44   145293000  \n",
+       "33   139363000  \n",
+       "30   360664000  \n",
+       "54   306462000  \n",
+       "43  1429002000  \n",
+       "22   163385000  \n",
+       "72    48862000  \n",
+       "17   206410000  \n",
+       "81  1173700000  \n",
+       "78   208801000  \n",
+       "84   506737000  \n",
+       "89   394720000  \n",
+       "61    71622000  \n",
+       "74   269975000  \n",
+       "47   277448000  \n",
+       "56   308965000  \n",
+       "15   258777000  "
       ]
      },
-     "execution_count": 49,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1077,7 +1339,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -1105,6 +1367,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -1119,6 +1382,7 @@
        "      <td>General Mills</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>2.641281</td>\n",
+       "      <td>0.063147</td>\n",
        "      <td>15.34</td>\n",
        "      <td>3.48</td>\n",
        "      <td>0.73</td>\n",
@@ -1131,6 +1395,7 @@
        "      <td>Walgreens Boots Alliance</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>2.224201</td>\n",
+       "      <td>-0.007405</td>\n",
        "      <td>13.00</td>\n",
        "      <td>4.07</td>\n",
        "      <td>0.92</td>\n",
@@ -1143,6 +1408,7 @@
        "      <td>Coca-Cola Company (The)</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>2.197158</td>\n",
+       "      <td>0.103820</td>\n",
        "      <td>28.99</td>\n",
        "      <td>2.07</td>\n",
        "      <td>0.41</td>\n",
@@ -1155,6 +1421,7 @@
        "      <td>PepsiCo Inc.</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>1.951250</td>\n",
+       "      <td>0.117935</td>\n",
        "      <td>28.31</td>\n",
        "      <td>5.19</td>\n",
        "      <td>0.53</td>\n",
@@ -1167,6 +1434,7 @@
        "      <td>CVS Health</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>1.707963</td>\n",
+       "      <td>-0.010387</td>\n",
        "      <td>14.05</td>\n",
        "      <td>5.08</td>\n",
        "      <td>0.93</td>\n",
@@ -1179,6 +1447,7 @@
        "      <td>The Hershey Company</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>1.469682</td>\n",
+       "      <td>0.125085</td>\n",
        "      <td>29.33</td>\n",
        "      <td>5.47</td>\n",
        "      <td>0.02</td>\n",
@@ -1191,6 +1460,7 @@
        "      <td>Wal-Mart Stores</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>1.271096</td>\n",
+       "      <td>0.125055</td>\n",
        "      <td>23.55</td>\n",
        "      <td>5.00</td>\n",
        "      <td>0.36</td>\n",
@@ -1203,6 +1473,7 @@
        "      <td>Costco Wholesale Corp.</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>1.060644</td>\n",
+       "      <td>0.192130</td>\n",
        "      <td>37.75</td>\n",
        "      <td>8.43</td>\n",
        "      <td>0.90</td>\n",
@@ -1224,18 +1495,18 @@
        "90    WMT           Wal-Mart Stores  Consumer Staples      1.271096   \n",
        "27   COST    Costco Wholesale Corp.  Consumer Staples      1.060644   \n",
        "\n",
-       "    P/E ratio   EPS  beta       mkt cap      shares  \n",
-       "42      15.34  3.48  0.73   32242795100   604817000  \n",
-       "91      13.00  4.07  0.92   46817805348   885862000  \n",
-       "26      28.99  2.07  0.41  256586003265  4280000000  \n",
-       "71      28.31  5.19  0.53  204968008309  1389545000  \n",
-       "29      14.05  5.08  0.93   92849804253  1300964000  \n",
-       "86      29.33  5.47  0.02   23779704176   148308000  \n",
-       "90      23.55  5.00  0.36  334474559018  2837175000  \n",
-       "27      37.75  8.43  0.90  140615987901   441758000  "
+       "    FFM returns  P/E ratio   EPS  beta       mkt cap      shares  \n",
+       "42     0.063147      15.34  3.48  0.73   32242795100   604817000  \n",
+       "91    -0.007405      13.00  4.07  0.92   46817805348   885862000  \n",
+       "26     0.103820      28.99  2.07  0.41  256586003265  4280000000  \n",
+       "71     0.117935      28.31  5.19  0.53  204968008309  1389545000  \n",
+       "29    -0.010387      14.05  5.08  0.93   92849804253  1300964000  \n",
+       "86     0.125085      29.33  5.47  0.02   23779704176   148308000  \n",
+       "90     0.125055      23.55  5.00  0.36  334474559018  2837175000  \n",
+       "27     0.192130      37.75  8.43  0.90  140615987901   441758000  "
       ]
      },
-     "execution_count": 40,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1248,7 +1519,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -1276,6 +1547,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -1290,6 +1562,7 @@
        "      <td>Occidental Petroleum</td>\n",
        "      <td>Energy</td>\n",
        "      <td>2.054771</td>\n",
+       "      <td>-0.042821</td>\n",
        "      <td>29.53</td>\n",
        "      <td>1.41</td>\n",
        "      <td>0.90</td>\n",
@@ -1302,6 +1575,7 @@
        "      <td>Cabot Oil &amp; Gas</td>\n",
        "      <td>Energy</td>\n",
        "      <td>1.952983</td>\n",
+       "      <td>-0.050017</td>\n",
        "      <td>7.80</td>\n",
        "      <td>1.90</td>\n",
        "      <td>0.47</td>\n",
@@ -1314,6 +1588,7 @@
        "      <td>Kinder Morgan</td>\n",
        "      <td>Energy</td>\n",
        "      <td>1.038470</td>\n",
+       "      <td>-0.038511</td>\n",
        "      <td>22.87</td>\n",
        "      <td>0.96</td>\n",
        "      <td>0.81</td>\n",
@@ -1326,6 +1601,7 @@
        "      <td>ONEOK</td>\n",
        "      <td>Energy</td>\n",
        "      <td>0.917326</td>\n",
+       "      <td>0.230148</td>\n",
        "      <td>25.56</td>\n",
        "      <td>3.01</td>\n",
        "      <td>1.11</td>\n",
@@ -1337,20 +1613,20 @@
        "</div>"
       ],
       "text/plain": [
-       "   ticker                  name  sector  sharpe ratio  P/E ratio   EPS  beta  \\\n",
-       "68    OXY  Occidental Petroleum  Energy      2.054771      29.53  1.41  0.90   \n",
-       "20    COG       Cabot Oil & Gas  Energy      1.952983       7.80  1.90  0.47   \n",
-       "53    KMI         Kinder Morgan  Energy      1.038470      22.87  0.96  0.81   \n",
-       "69    OKE                 ONEOK  Energy      0.917326      25.56  3.01  1.11   \n",
+       "   ticker                  name  sector  sharpe ratio  FFM returns  P/E ratio  \\\n",
+       "68    OXY  Occidental Petroleum  Energy      2.054771    -0.042821      29.53   \n",
+       "20    COG       Cabot Oil & Gas  Energy      1.952983    -0.050017       7.80   \n",
+       "53    KMI         Kinder Morgan  Energy      1.038470    -0.038511      22.87   \n",
+       "69    OKE                 ONEOK  Energy      0.917326     0.230148      25.56   \n",
        "\n",
-       "        mkt cap      shares  \n",
-       "68  37161985836   893317000  \n",
-       "20   6037284157   407925000  \n",
-       "53  49831386000  2265063000  \n",
-       "69  31799253894   413085000  "
+       "     EPS  beta      mkt cap      shares  \n",
+       "68  1.41  0.90  37161985836   893317000  \n",
+       "20  1.90  0.47   6037284157   407925000  \n",
+       "53  0.96  0.81  49831386000  2265063000  \n",
+       "69  3.01  1.11  31799253894   413085000  "
       ]
      },
-     "execution_count": 41,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1363,7 +1639,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -1391,6 +1667,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -1405,6 +1682,7 @@
        "      <td>Synchrony Financial</td>\n",
        "      <td>Financials</td>\n",
        "      <td>2.493336</td>\n",
+       "      <td>0.091836</td>\n",
        "      <td>6.07</td>\n",
        "      <td>5.56</td>\n",
        "      <td>1.21</td>\n",
@@ -1417,6 +1695,7 @@
        "      <td>Block H&amp;R</td>\n",
        "      <td>Financials</td>\n",
        "      <td>2.210675</td>\n",
+       "      <td>0.001104</td>\n",
        "      <td>11.75</td>\n",
        "      <td>1.90</td>\n",
        "      <td>0.23</td>\n",
@@ -1429,6 +1708,7 @@
        "      <td>Capital One Financial</td>\n",
        "      <td>Financials</td>\n",
        "      <td>2.034764</td>\n",
+       "      <td>0.116104</td>\n",
        "      <td>9.31</td>\n",
        "      <td>11.02</td>\n",
        "      <td>1.25</td>\n",
@@ -1441,6 +1721,7 @@
        "      <td>Goldman Sachs Group</td>\n",
        "      <td>Financials</td>\n",
        "      <td>1.828821</td>\n",
+       "      <td>0.099915</td>\n",
        "      <td>11.27</td>\n",
        "      <td>21.03</td>\n",
        "      <td>1.32</td>\n",
@@ -1453,6 +1734,7 @@
        "      <td>Raymond James Financial Inc.</td>\n",
        "      <td>Financials</td>\n",
        "      <td>1.281138</td>\n",
+       "      <td>0.155046</td>\n",
        "      <td>13.44</td>\n",
        "      <td>7.36</td>\n",
        "      <td>1.50</td>\n",
@@ -1465,6 +1747,7 @@
        "      <td>American Express Co</td>\n",
        "      <td>Financials</td>\n",
        "      <td>1.214408</td>\n",
+       "      <td>0.132252</td>\n",
        "      <td>17.01</td>\n",
        "      <td>7.99</td>\n",
        "      <td>0.99</td>\n",
@@ -1477,6 +1760,7 @@
        "      <td>Cincinnati Financial</td>\n",
        "      <td>Financials</td>\n",
        "      <td>1.121374</td>\n",
+       "      <td>0.199838</td>\n",
        "      <td>9.52</td>\n",
        "      <td>12.10</td>\n",
        "      <td>0.57</td>\n",
@@ -1489,6 +1773,7 @@
        "      <td>Aon plc</td>\n",
        "      <td>Financials</td>\n",
        "      <td>1.104319</td>\n",
+       "      <td>0.183167</td>\n",
        "      <td>37.00</td>\n",
        "      <td>6.37</td>\n",
        "      <td>0.83</td>\n",
@@ -1501,6 +1786,7 @@
        "      <td>Affiliated Managers Group Inc</td>\n",
        "      <td>Financials</td>\n",
        "      <td>1.097986</td>\n",
+       "      <td>-0.138798</td>\n",
        "      <td>267.18</td>\n",
        "      <td>0.31</td>\n",
        "      <td>1.69</td>\n",
@@ -1513,6 +1799,7 @@
        "      <td>Arthur J. Gallagher &amp; Co.</td>\n",
        "      <td>Financials</td>\n",
        "      <td>0.967112</td>\n",
+       "      <td>0.195583</td>\n",
        "      <td>31.03</td>\n",
        "      <td>3.52</td>\n",
        "      <td>0.76</td>\n",
@@ -1525,6 +1812,7 @@
        "      <td>Moody's Corp</td>\n",
        "      <td>Financials</td>\n",
        "      <td>0.927984</td>\n",
+       "      <td>0.234858</td>\n",
        "      <td>37.43</td>\n",
        "      <td>7.42</td>\n",
        "      <td>1.21</td>\n",
@@ -1536,34 +1824,34 @@
        "</div>"
       ],
       "text/plain": [
-       "   ticker                           name      sector  sharpe ratio  P/E ratio  \\\n",
-       "82    SYF            Synchrony Financial  Financials      2.493336       6.07   \n",
-       "16    HRB                      Block H&R  Financials      2.210675      11.75   \n",
-       "21    COF          Capital One Financial  Financials      2.034764       9.31   \n",
-       "45     GS            Goldman Sachs Group  Financials      1.828821      11.27   \n",
-       "75    RJF   Raymond James Financial Inc.  Financials      1.281138      13.44   \n",
-       "8     AXP            American Express Co  Financials      1.214408      17.01   \n",
-       "24   CINF           Cincinnati Financial  Financials      1.121374       9.52   \n",
-       "11    AON                        Aon plc  Financials      1.104319      37.00   \n",
-       "3     AMG  Affiliated Managers Group Inc  Financials      1.097986     267.18   \n",
-       "13    AJG      Arthur J. Gallagher & Co.  Financials      0.967112      31.03   \n",
-       "62    MCO                   Moody's Corp  Financials      0.927984      37.43   \n",
+       "   ticker                           name      sector  sharpe ratio  \\\n",
+       "82    SYF            Synchrony Financial  Financials      2.493336   \n",
+       "16    HRB                      Block H&R  Financials      2.210675   \n",
+       "21    COF          Capital One Financial  Financials      2.034764   \n",
+       "45     GS            Goldman Sachs Group  Financials      1.828821   \n",
+       "75    RJF   Raymond James Financial Inc.  Financials      1.281138   \n",
+       "8     AXP            American Express Co  Financials      1.214408   \n",
+       "24   CINF           Cincinnati Financial  Financials      1.121374   \n",
+       "11    AON                        Aon plc  Financials      1.104319   \n",
+       "3     AMG  Affiliated Managers Group Inc  Financials      1.097986   \n",
+       "13    AJG      Arthur J. Gallagher & Co.  Financials      0.967112   \n",
+       "62    MCO                   Moody's Corp  Financials      0.927984   \n",
        "\n",
-       "      EPS  beta       mkt cap     shares  \n",
-       "82   5.56  1.21   20704848750  613477000  \n",
-       "16   1.90  0.23    4369605316  195246000  \n",
-       "21  11.02  1.25   46865423721  456600000  \n",
-       "45  21.03  1.32   83946946608  354087000  \n",
-       "75   7.36  1.50   13782151374  139284000  \n",
-       "8    7.99  0.99  111178449600  808041000  \n",
-       "24  12.10  0.57   18822318390  163374000  \n",
-       "11   6.37  0.83   54701475530  234137000  \n",
-       "3    0.31  1.69    4084648875   49272000  \n",
-       "13   3.52  0.76   20549043209  188247000  \n",
-       "62   7.42  1.21   52148688479  187700000  "
+       "    FFM returns  P/E ratio    EPS  beta       mkt cap     shares  \n",
+       "82     0.091836       6.07   5.56  1.21   20704848750  613477000  \n",
+       "16     0.001104      11.75   1.90  0.23    4369605316  195246000  \n",
+       "21     0.116104       9.31  11.02  1.25   46865423721  456600000  \n",
+       "45     0.099915      11.27  21.03  1.32   83946946608  354087000  \n",
+       "75     0.155046      13.44   7.36  1.50   13782151374  139284000  \n",
+       "8      0.132252      17.01   7.99  0.99  111178449600  808041000  \n",
+       "24     0.199838       9.52  12.10  0.57   18822318390  163374000  \n",
+       "11     0.183167      37.00   6.37  0.83   54701475530  234137000  \n",
+       "3     -0.138798     267.18   0.31  1.69    4084648875   49272000  \n",
+       "13     0.195583      31.03   3.52  0.76   20549043209  188247000  \n",
+       "62     0.234858      37.43   7.42  1.21   52148688479  187700000  "
       ]
      },
-     "execution_count": 42,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1576,7 +1864,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -1604,6 +1892,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -1618,6 +1907,7 @@
        "      <td>AmerisourceBergen Corp</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>2.824204</td>\n",
+       "      <td>0.018487</td>\n",
        "      <td>30.62</td>\n",
        "      <td>3.08</td>\n",
        "      <td>1.01</td>\n",
@@ -1630,6 +1920,7 @@
        "      <td>Bristol-Myers Squibb</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>2.688515</td>\n",
+       "      <td>0.083177</td>\n",
        "      <td>33.05</td>\n",
        "      <td>2.01</td>\n",
        "      <td>0.76</td>\n",
@@ -1642,6 +1933,7 @@
        "      <td>Hologic</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>2.425412</td>\n",
+       "      <td>0.129968</td>\n",
        "      <td>173.01</td>\n",
        "      <td>0.31</td>\n",
        "      <td>0.85</td>\n",
@@ -1654,6 +1946,7 @@
        "      <td>Medtronic plc</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>1.917921</td>\n",
+       "      <td>0.124213</td>\n",
        "      <td>33.97</td>\n",
        "      <td>3.45</td>\n",
        "      <td>0.60</td>\n",
@@ -1666,6 +1959,7 @@
        "      <td>Amgen Inc</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>1.861649</td>\n",
+       "      <td>0.151749</td>\n",
        "      <td>17.36</td>\n",
        "      <td>12.88</td>\n",
        "      <td>1.12</td>\n",
@@ -1678,6 +1972,7 @@
        "      <td>Merck &amp; Co.</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>1.368058</td>\n",
+       "      <td>0.147016</td>\n",
        "      <td>21.52</td>\n",
        "      <td>3.84</td>\n",
        "      <td>0.57</td>\n",
@@ -1690,6 +1985,7 @@
        "      <td>Incyte</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>1.268258</td>\n",
+       "      <td>0.076793</td>\n",
        "      <td>38.21</td>\n",
        "      <td>2.05</td>\n",
        "      <td>1.06</td>\n",
@@ -1702,6 +1998,7 @@
        "      <td>Mettler Toledo</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.969242</td>\n",
+       "      <td>0.232895</td>\n",
        "      <td>33.97</td>\n",
        "      <td>22.47</td>\n",
        "      <td>1.39</td>\n",
@@ -1714,6 +2011,7 @@
        "      <td>Thermo Fisher Scientific</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.957237</td>\n",
+       "      <td>0.223396</td>\n",
        "      <td>36.98</td>\n",
        "      <td>9.17</td>\n",
        "      <td>1.14</td>\n",
@@ -1726,6 +2024,7 @@
        "      <td>Boston Scientific</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.933787</td>\n",
+       "      <td>0.233861</td>\n",
        "      <td>12.70</td>\n",
        "      <td>3.33</td>\n",
        "      <td>0.87</td>\n",
@@ -1738,6 +2037,7 @@
        "      <td>Mylan N.V.</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.893280</td>\n",
+       "      <td>-0.130829</td>\n",
        "      <td>239.58</td>\n",
        "      <td>0.09</td>\n",
        "      <td>1.72</td>\n",
@@ -1750,6 +2050,7 @@
        "      <td>United Health Group Inc.</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.892893</td>\n",
+       "      <td>0.243094</td>\n",
        "      <td>20.86</td>\n",
        "      <td>14.33</td>\n",
        "      <td>0.69</td>\n",
@@ -1762,6 +2063,7 @@
        "      <td>ResMed</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>0.834963</td>\n",
+       "      <td>0.236317</td>\n",
        "      <td>56.31</td>\n",
        "      <td>3.14</td>\n",
        "      <td>0.48</td>\n",
@@ -1773,38 +2075,38 @@
        "</div>"
       ],
       "text/plain": [
-       "   ticker                      name       sector  sharpe ratio  P/E ratio  \\\n",
-       "9     ABC    AmerisourceBergen Corp  Health Care      2.824204      30.62   \n",
-       "19    BMY      Bristol-Myers Squibb  Health Care      2.688515      33.05   \n",
-       "48   HOLX                   Hologic  Health Care      2.425412     173.01   \n",
-       "57    MDT             Medtronic plc  Health Care      1.917921      33.97   \n",
-       "10   AMGN                 Amgen Inc  Health Care      1.861649      17.36   \n",
-       "58    MRK               Merck & Co.  Health Care      1.368058      21.52   \n",
-       "51   INCY                    Incyte  Health Care      1.268258      38.21   \n",
-       "59    MTD            Mettler Toledo  Health Care      0.969242      33.97   \n",
-       "87    TMO  Thermo Fisher Scientific  Health Care      0.957237      36.98   \n",
-       "18    BSX         Boston Scientific  Health Care      0.933787      12.70   \n",
-       "64    MYL                Mylan N.V.  Health Care      0.893280     239.58   \n",
-       "88    UNH  United Health Group Inc.  Health Care      0.892893      20.86   \n",
-       "77    RMD                    ResMed  Health Care      0.834963      56.31   \n",
+       "   ticker                      name       sector  sharpe ratio  FFM returns  \\\n",
+       "9     ABC    AmerisourceBergen Corp  Health Care      2.824204     0.018487   \n",
+       "19    BMY      Bristol-Myers Squibb  Health Care      2.688515     0.083177   \n",
+       "48   HOLX                   Hologic  Health Care      2.425412     0.129968   \n",
+       "57    MDT             Medtronic plc  Health Care      1.917921     0.124213   \n",
+       "10   AMGN                 Amgen Inc  Health Care      1.861649     0.151749   \n",
+       "58    MRK               Merck & Co.  Health Care      1.368058     0.147016   \n",
+       "51   INCY                    Incyte  Health Care      1.268258     0.076793   \n",
+       "59    MTD            Mettler Toledo  Health Care      0.969242     0.232895   \n",
+       "87    TMO  Thermo Fisher Scientific  Health Care      0.957237     0.223396   \n",
+       "18    BSX         Boston Scientific  Health Care      0.933787     0.233861   \n",
+       "64    MYL                Mylan N.V.  Health Care      0.893280    -0.130829   \n",
+       "88    UNH  United Health Group Inc.  Health Care      0.892893     0.243094   \n",
+       "77    RMD                    ResMed  Health Care      0.834963     0.236317   \n",
        "\n",
-       "      EPS  beta       mkt cap      shares  \n",
-       "9    3.08  1.01   19427969245   205892000  \n",
-       "19   2.01  0.76  155607591281  2344185000  \n",
-       "48   0.31  0.85   13960272160   263302000  \n",
-       "57   3.45  0.60  157266553194  1340378000  \n",
-       "10  12.88  1.12  131810065840   589807000  \n",
-       "58   3.84  0.57  210425581484  2545984000  \n",
-       "51   2.05  1.06   17006076538   216776000  \n",
-       "59  22.47  1.39   18357249893    24053000  \n",
-       "87   9.17  1.14  136012138268   400991000  \n",
-       "18   3.33  0.87   58972695354  1393824000  \n",
-       "64   0.09  1.72   11303303743   516177000  \n",
-       "88  14.33  0.69  283068652543   947415000  \n",
-       "77   3.14  0.48   25539363082   144617000  "
+       "    P/E ratio    EPS  beta       mkt cap      shares  \n",
+       "9       30.62   3.08  1.01   19427969245   205892000  \n",
+       "19      33.05   2.01  0.76  155607591281  2344185000  \n",
+       "48     173.01   0.31  0.85   13960272160   263302000  \n",
+       "57      33.97   3.45  0.60  157266553194  1340378000  \n",
+       "10      17.36  12.88  1.12  131810065840   589807000  \n",
+       "58      21.52   3.84  0.57  210425581484  2545984000  \n",
+       "51      38.21   2.05  1.06   17006076538   216776000  \n",
+       "59      33.97  22.47  1.39   18357249893    24053000  \n",
+       "87      36.98   9.17  1.14  136012138268   400991000  \n",
+       "18      12.70   3.33  0.87   58972695354  1393824000  \n",
+       "64     239.58   0.09  1.72   11303303743   516177000  \n",
+       "88      20.86  14.33  0.69  283068652543   947415000  \n",
+       "77      56.31   3.14  0.48   25539363082   144617000  "
       ]
      },
-     "execution_count": 43,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1817,7 +2119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -1845,6 +2147,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -1859,6 +2162,7 @@
        "      <td>Southwest Airlines</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>1.726576</td>\n",
+       "      <td>0.107833</td>\n",
        "      <td>13.77</td>\n",
        "      <td>4.21</td>\n",
        "      <td>1.47</td>\n",
@@ -1871,6 +2175,7 @@
        "      <td>Eaton Corporation</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>1.604766</td>\n",
+       "      <td>0.128998</td>\n",
        "      <td>19.71</td>\n",
        "      <td>5.25</td>\n",
        "      <td>1.42</td>\n",
@@ -1883,6 +2188,7 @@
        "      <td>FedEx Corporation</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>1.509820</td>\n",
+       "      <td>0.024254</td>\n",
        "      <td>583.74</td>\n",
        "      <td>0.27</td>\n",
        "      <td>1.71</td>\n",
@@ -1895,6 +2201,7 @@
        "      <td>Grainger (W.W.) Inc.</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>1.358110</td>\n",
+       "      <td>0.143754</td>\n",
        "      <td>17.94</td>\n",
        "      <td>17.15</td>\n",
        "      <td>0.97</td>\n",
@@ -1907,6 +2214,7 @@
        "      <td>Raytheon Co.</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>1.158338</td>\n",
+       "      <td>0.194796</td>\n",
        "      <td>19.05</td>\n",
        "      <td>11.93</td>\n",
        "      <td>0.85</td>\n",
@@ -1919,6 +2227,7 @@
        "      <td>Huntington Ingalls Industries</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>1.154338</td>\n",
+       "      <td>0.172310</td>\n",
        "      <td>18.57</td>\n",
        "      <td>13.26</td>\n",
        "      <td>1.24</td>\n",
@@ -1931,6 +2240,7 @@
        "      <td>Cintas Corporation</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>0.703186</td>\n",
+       "      <td>0.285973</td>\n",
        "      <td>35.38</td>\n",
        "      <td>8.51</td>\n",
        "      <td>0.99</td>\n",
@@ -1951,17 +2261,17 @@
        "50    HII  Huntington Ingalls Industries  Industrials      1.154338   \n",
        "25   CTAS             Cintas Corporation  Industrials      0.703186   \n",
        "\n",
-       "    P/E ratio    EPS  beta      mkt cap     shares  \n",
-       "80      13.77   4.21  1.47  29987649751  517296000  \n",
-       "31      19.71   5.25  1.42  42807571261  413400000  \n",
-       "36     583.74   0.27  1.71  41418694505  261119000  \n",
-       "46      17.94  17.15  0.97  16517112872   53688000  \n",
-       "76      19.05  11.93  0.85  63256224340  278441000  \n",
-       "50      18.57  13.26  1.24  10035519873   40760000  \n",
-       "25      35.38   8.51  0.99  31216601386  103751000  "
+       "    FFM returns  P/E ratio    EPS  beta      mkt cap     shares  \n",
+       "80     0.107833      13.77   4.21  1.47  29987649751  517296000  \n",
+       "31     0.128998      19.71   5.25  1.42  42807571261  413400000  \n",
+       "36     0.024254     583.74   0.27  1.71  41418694505  261119000  \n",
+       "46     0.143754      17.94  17.15  0.97  16517112872   53688000  \n",
+       "76     0.194796      19.05  11.93  0.85  63256224340  278441000  \n",
+       "50     0.172310      18.57  13.26  1.24  10035519873   40760000  \n",
+       "25     0.285973      35.38   8.51  0.99  31216601386  103751000  "
       ]
      },
-     "execution_count": 44,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1974,7 +2284,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -2002,6 +2312,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -2016,6 +2327,7 @@
        "      <td>Oracle Corp.</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.949619</td>\n",
+       "      <td>0.077350</td>\n",
        "      <td>17.61</td>\n",
        "      <td>3.15</td>\n",
        "      <td>1.11</td>\n",
@@ -2028,6 +2340,7 @@
        "      <td>F5 Networks</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.701382</td>\n",
+       "      <td>0.064989</td>\n",
        "      <td>19.49</td>\n",
        "      <td>6.54</td>\n",
        "      <td>0.98</td>\n",
@@ -2040,6 +2353,7 @@
        "      <td>Gartner Inc</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.337328</td>\n",
+       "      <td>0.165214</td>\n",
        "      <td>59.34</td>\n",
        "      <td>2.57</td>\n",
        "      <td>1.21</td>\n",
@@ -2052,6 +2366,7 @@
        "      <td>Alphabet Inc Class A</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.198026</td>\n",
+       "      <td>0.214640</td>\n",
        "      <td>30.89</td>\n",
        "      <td>49.16</td>\n",
        "      <td>1.02</td>\n",
@@ -2064,6 +2379,7 @@
        "      <td>Accenture plc</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.113858</td>\n",
+       "      <td>0.225818</td>\n",
        "      <td>28.34</td>\n",
        "      <td>7.49</td>\n",
        "      <td>1.03</td>\n",
@@ -2076,6 +2392,7 @@
        "      <td>Facebook, Inc.</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.105767</td>\n",
+       "      <td>0.238789</td>\n",
        "      <td>33.32</td>\n",
        "      <td>6.43</td>\n",
        "      <td>1.05</td>\n",
@@ -2088,6 +2405,7 @@
        "      <td>Automatic Data Processing</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.004579</td>\n",
+       "      <td>0.183269</td>\n",
        "      <td>32.04</td>\n",
        "      <td>5.66</td>\n",
        "      <td>0.87</td>\n",
@@ -2100,6 +2418,7 @@
        "      <td>Fiserv Inc</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.948895</td>\n",
+       "      <td>0.249903</td>\n",
        "      <td>71.58</td>\n",
        "      <td>1.71</td>\n",
        "      <td>0.80</td>\n",
@@ -2112,6 +2431,7 @@
        "      <td>Apple Inc.</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.919063</td>\n",
+       "      <td>0.236049</td>\n",
        "      <td>25.66</td>\n",
        "      <td>12.66</td>\n",
        "      <td>1.29</td>\n",
@@ -2124,6 +2444,7 @@
        "      <td>Texas Instruments</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.886247</td>\n",
+       "      <td>0.224912</td>\n",
        "      <td>25.24</td>\n",
        "      <td>5.24</td>\n",
        "      <td>1.24</td>\n",
@@ -2136,6 +2457,7 @@
        "      <td>Salesforce.com</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.885841</td>\n",
+       "      <td>0.207470</td>\n",
        "      <td>200.68</td>\n",
        "      <td>0.95</td>\n",
        "      <td>1.19</td>\n",
@@ -2148,6 +2470,7 @@
        "      <td>Synopsys Inc.</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.801366</td>\n",
+       "      <td>0.258979</td>\n",
        "      <td>47.31</td>\n",
        "      <td>3.45</td>\n",
        "      <td>1.18</td>\n",
@@ -2160,6 +2483,7 @@
        "      <td>Motorola Solutions Inc.</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.785703</td>\n",
+       "      <td>0.231468</td>\n",
        "      <td>37.31</td>\n",
        "      <td>4.94</td>\n",
        "      <td>0.50</td>\n",
@@ -2172,6 +2496,7 @@
        "      <td>Microsoft Corp.</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.688151</td>\n",
+       "      <td>0.322501</td>\n",
        "      <td>32.28</td>\n",
        "      <td>5.74</td>\n",
        "      <td>1.15</td>\n",
@@ -2184,6 +2509,7 @@
        "      <td>Adobe Systems Inc</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>0.616060</td>\n",
+       "      <td>0.329761</td>\n",
        "      <td>63.17</td>\n",
        "      <td>6.01</td>\n",
        "      <td>1.09</td>\n",
@@ -2212,25 +2538,25 @@
        "60   MSFT            Microsoft Corp.  Information Technology      0.688151   \n",
        "1    ADBE          Adobe Systems Inc  Information Technology      0.616060   \n",
        "\n",
-       "    P/E ratio    EPS  beta        mkt cap      shares  \n",
-       "70      17.61   3.15  1.11   177928293945  3207649000  \n",
-       "34      19.49   6.54  0.98     7753118169    60804000  \n",
-       "41      59.34   2.57  1.21    13633532057    89453000  \n",
-       "7       30.89  49.16  1.02  1044236513876   299895000  \n",
-       "0       28.34   7.49  1.03   139515576338   656946000  \n",
-       "35      33.32   6.43  1.05   610509360122  2405746000  \n",
-       "14      32.04   5.66  0.87    78255412500   431754000  \n",
-       "38      71.58   1.71  0.80    83164756192   679895000  \n",
-       "12      25.66  12.66  1.29  1421812279411  4375480000  \n",
-       "85      25.24   5.24  1.24   123223956977   932032000  \n",
-       "79     200.68   0.95  1.19   168485647293   887000000  \n",
-       "83      47.31   3.45  1.18    24589893168   150535000  \n",
-       "63      37.31   4.94  0.50    31596072387   171336000  \n",
-       "60      32.28   5.74  1.15  1409780857873  7606047000  \n",
-       "1       63.17   6.01  1.09   185174936969   487726000  "
+       "    FFM returns  P/E ratio    EPS  beta        mkt cap      shares  \n",
+       "70     0.077350      17.61   3.15  1.11   177928293945  3207649000  \n",
+       "34     0.064989      19.49   6.54  0.98     7753118169    60804000  \n",
+       "41     0.165214      59.34   2.57  1.21    13633532057    89453000  \n",
+       "7      0.214640      30.89  49.16  1.02  1044236513876   299895000  \n",
+       "0      0.225818      28.34   7.49  1.03   139515576338   656946000  \n",
+       "35     0.238789      33.32   6.43  1.05   610509360122  2405746000  \n",
+       "14     0.183269      32.04   5.66  0.87    78255412500   431754000  \n",
+       "38     0.249903      71.58   1.71  0.80    83164756192   679895000  \n",
+       "12     0.236049      25.66  12.66  1.29  1421812279411  4375480000  \n",
+       "85     0.224912      25.24   5.24  1.24   123223956977   932032000  \n",
+       "79     0.207470     200.68   0.95  1.19   168485647293   887000000  \n",
+       "83     0.258979      47.31   3.45  1.18    24589893168   150535000  \n",
+       "63     0.231468      37.31   4.94  0.50    31596072387   171336000  \n",
+       "60     0.322501      32.28   5.74  1.15  1409780857873  7606047000  \n",
+       "1      0.329761      63.17   6.01  1.09   185174936969   487726000  "
       ]
      },
-     "execution_count": 45,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2243,7 +2569,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -2271,6 +2597,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -2285,6 +2612,7 @@
        "      <td>LyondellBasell</td>\n",
        "      <td>Materials</td>\n",
        "      <td>2.072393</td>\n",
+       "      <td>0.103512</td>\n",
        "      <td>8.65</td>\n",
        "      <td>9.55</td>\n",
        "      <td>1.45</td>\n",
@@ -2297,6 +2625,7 @@
        "      <td>Newmont Mining Corporation</td>\n",
        "      <td>Materials</td>\n",
        "      <td>1.248661</td>\n",
+       "      <td>0.189686</td>\n",
        "      <td>15.83</td>\n",
        "      <td>2.78</td>\n",
        "      <td>0.16</td>\n",
@@ -2309,6 +2638,7 @@
        "      <td>Air Products &amp; Chemicals Inc</td>\n",
        "      <td>Materials</td>\n",
        "      <td>1.224824</td>\n",
+       "      <td>0.153161</td>\n",
        "      <td>30.09</td>\n",
        "      <td>8.51</td>\n",
        "      <td>0.86</td>\n",
@@ -2321,6 +2651,7 @@
        "      <td>Freeport-McMoRan Inc.</td>\n",
        "      <td>Materials</td>\n",
        "      <td>1.031316</td>\n",
+       "      <td>0.038646</td>\n",
        "      <td>78.35</td>\n",
        "      <td>0.16</td>\n",
        "      <td>2.42</td>\n",
@@ -2333,6 +2664,7 @@
        "      <td>Albemarle Corp</td>\n",
        "      <td>Materials</td>\n",
        "      <td>0.990292</td>\n",
+       "      <td>0.132207</td>\n",
        "      <td>16.67</td>\n",
        "      <td>5.38</td>\n",
        "      <td>1.57</td>\n",
@@ -2345,6 +2677,7 @@
        "      <td>FMC Corporation</td>\n",
        "      <td>Materials</td>\n",
        "      <td>0.889526</td>\n",
+       "      <td>0.193867</td>\n",
        "      <td>27.41</td>\n",
        "      <td>3.85</td>\n",
        "      <td>1.54</td>\n",
@@ -2356,24 +2689,24 @@
        "</div>"
       ],
       "text/plain": [
-       "   ticker                          name     sector  sharpe ratio  P/E ratio  \\\n",
-       "55    LYB                LyondellBasell  Materials      2.072393       8.65   \n",
-       "65    NEM    Newmont Mining Corporation  Materials      1.248661      15.83   \n",
-       "4     APD  Air Products & Chemicals Inc  Materials      1.224824      30.09   \n",
-       "40    FCX         Freeport-McMoRan Inc.  Materials      1.031316      78.35   \n",
-       "5     ALB                Albemarle Corp  Materials      0.990292      16.67   \n",
-       "39    FMC               FMC Corporation  Materials      0.889526      27.41   \n",
+       "   ticker                          name     sector  sharpe ratio  FFM returns  \\\n",
+       "55    LYB                LyondellBasell  Materials      2.072393     0.103512   \n",
+       "65    NEM    Newmont Mining Corporation  Materials      1.248661     0.189686   \n",
+       "4     APD  Air Products & Chemicals Inc  Materials      1.224824     0.153161   \n",
+       "40    FCX         Freeport-McMoRan Inc.  Materials      1.031316     0.038646   \n",
+       "5     ALB                Albemarle Corp  Materials      0.990292     0.132207   \n",
+       "39    FMC               FMC Corporation  Materials      0.889526     0.193867   \n",
        "\n",
-       "     EPS  beta      mkt cap      shares  \n",
-       "55  9.55  1.45  27505799491   333000000  \n",
-       "65  2.78  0.16  36130286851   819839000  \n",
-       "4   8.51  0.86  56495776935   220678000  \n",
-       "40  0.16  2.42  17759187027  1450914000  \n",
-       "5   5.38  1.57   9504798055   106033000  \n",
-       "39  3.85  1.54  13670494208   129615000  "
+       "    P/E ratio   EPS  beta      mkt cap      shares  \n",
+       "55       8.65  9.55  1.45  27505799491   333000000  \n",
+       "65      15.83  2.78  0.16  36130286851   819839000  \n",
+       "4       30.09  8.51  0.86  56495776935   220678000  \n",
+       "40      78.35  0.16  2.42  17759187027  1450914000  \n",
+       "5       16.67  5.38  1.57   9504798055   106033000  \n",
+       "39      27.41  3.85  1.54  13670494208   129615000  "
       ]
      },
-     "execution_count": 46,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2386,7 +2719,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
@@ -2414,6 +2747,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -2428,6 +2762,7 @@
        "      <td>Host Hotels &amp; Resorts</td>\n",
        "      <td>Real Estate</td>\n",
        "      <td>2.308137</td>\n",
+       "      <td>0.052833</td>\n",
        "      <td>10.89</td>\n",
        "      <td>1.55</td>\n",
        "      <td>1.17</td>\n",
@@ -2440,6 +2775,7 @@
        "      <td>Iron Mountain Incorporated</td>\n",
        "      <td>Real Estate</td>\n",
        "      <td>2.233518</td>\n",
+       "      <td>0.073061</td>\n",
        "      <td>35.67</td>\n",
        "      <td>0.93</td>\n",
        "      <td>0.53</td>\n",
@@ -2452,6 +2788,7 @@
        "      <td>Equity Residential</td>\n",
        "      <td>Real Estate</td>\n",
        "      <td>2.158996</td>\n",
+       "      <td>0.089495</td>\n",
        "      <td>34.53</td>\n",
        "      <td>2.50</td>\n",
        "      <td>0.45</td>\n",
@@ -2464,6 +2801,7 @@
        "      <td>Crown Castle International Corp.</td>\n",
        "      <td>Real Estate</td>\n",
        "      <td>1.281977</td>\n",
+       "      <td>0.163975</td>\n",
        "      <td>83.64</td>\n",
        "      <td>1.98</td>\n",
        "      <td>0.30</td>\n",
@@ -2481,14 +2819,14 @@
        "32    EQR                Equity Residential  Real Estate      2.158996   \n",
        "28    CCI  Crown Castle International Corp.  Real Estate      1.281977   \n",
        "\n",
-       "    P/E ratio   EPS  beta      mkt cap     shares  \n",
-       "49      10.89  1.55  1.17  12127479870  717178000  \n",
-       "52      35.67  0.93  0.53   9521121824  287300000  \n",
-       "32      34.53  2.50  0.45  32134657027  371671000  \n",
-       "28      83.64  1.98  0.30  69005081855  415768000  "
+       "    FFM returns  P/E ratio   EPS  beta      mkt cap     shares  \n",
+       "49     0.052833      10.89  1.55  1.17  12127479870  717178000  \n",
+       "52     0.073061      35.67  0.93  0.53   9521121824  287300000  \n",
+       "32     0.089495      34.53  2.50  0.45  32134657027  371671000  \n",
+       "28     0.163975      83.64  1.98  0.30  69005081855  415768000  "
       ]
      },
-     "execution_count": 51,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2501,7 +2839,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -2529,6 +2867,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -2543,6 +2882,7 @@
        "      <td>PPL Corp.</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>2.755488</td>\n",
+       "      <td>0.098239</td>\n",
        "      <td>14.38</td>\n",
        "      <td>2.46</td>\n",
        "      <td>0.51</td>\n",
@@ -2555,6 +2895,7 @@
        "      <td>FirstEnergy Corp</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>1.510567</td>\n",
+       "      <td>0.129910</td>\n",
        "      <td>31.45</td>\n",
        "      <td>1.66</td>\n",
        "      <td>0.20</td>\n",
@@ -2567,6 +2908,7 @@
        "      <td>Alliant Energy Corp</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>1.366718</td>\n",
+       "      <td>0.166244</td>\n",
        "      <td>26.79</td>\n",
        "      <td>2.23</td>\n",
        "      <td>0.23</td>\n",
@@ -2579,6 +2921,7 @@
        "      <td>CenterPoint Energy</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>1.361230</td>\n",
+       "      <td>0.121502</td>\n",
        "      <td>21.58</td>\n",
        "      <td>1.26</td>\n",
        "      <td>0.44</td>\n",
@@ -2591,6 +2934,7 @@
        "      <td>AES Corp</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>1.182641</td>\n",
+       "      <td>0.162654</td>\n",
        "      <td>27.44</td>\n",
        "      <td>0.76</td>\n",
        "      <td>1.05</td>\n",
@@ -2603,6 +2947,7 @@
        "      <td>NextEra Energy</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>0.928683</td>\n",
+       "      <td>0.227986</td>\n",
        "      <td>34.73</td>\n",
        "      <td>8.02</td>\n",
        "      <td>0.15</td>\n",
@@ -2615,6 +2960,7 @@
        "      <td>NRG Energy</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>0.692217</td>\n",
+       "      <td>0.208670</td>\n",
        "      <td>10.31</td>\n",
        "      <td>3.89</td>\n",
        "      <td>0.71</td>\n",
@@ -2626,26 +2972,26 @@
        "</div>"
       ],
       "text/plain": [
-       "   ticker                 name     sector  sharpe ratio  P/E ratio   EPS  \\\n",
-       "73    PPL            PPL Corp.  Utilities      2.755488      14.38  2.46   \n",
-       "37     FE     FirstEnergy Corp  Utilities      1.510567      31.45  1.66   \n",
-       "6     LNT  Alliant Energy Corp  Utilities      1.366718      26.79  2.23   \n",
-       "23    CNP   CenterPoint Energy  Utilities      1.361230      21.58  1.26   \n",
-       "2     AES             AES Corp  Utilities      1.182641      27.44  0.76   \n",
-       "66    NEE       NextEra Energy  Utilities      0.928683      34.73  8.02   \n",
-       "67    NRG           NRG Energy  Utilities      0.692217      10.31  3.89   \n",
+       "   ticker                 name     sector  sharpe ratio  FFM returns  \\\n",
+       "73    PPL            PPL Corp.  Utilities      2.755488     0.098239   \n",
+       "37     FE     FirstEnergy Corp  Utilities      1.510567     0.129910   \n",
+       "6     LNT  Alliant Energy Corp  Utilities      1.366718     0.166244   \n",
+       "23    CNP   CenterPoint Energy  Utilities      1.361230     0.121502   \n",
+       "2     AES             AES Corp  Utilities      1.182641     0.162654   \n",
+       "66    NEE       NextEra Energy  Utilities      0.928683     0.227986   \n",
+       "67    NRG           NRG Energy  Utilities      0.692217     0.208670   \n",
        "\n",
-       "    beta       mkt cap     shares  \n",
-       "73  0.51   25573676437  723033000  \n",
-       "37  0.20   28241486749  540714000  \n",
-       "6   0.23   14358652779  244628000  \n",
-       "23  0.44   13650929559  502242000  \n",
-       "2   1.05   13895280692  663893000  \n",
-       "66  0.15  136133886150  488776000  \n",
-       "67  0.71   10078855985  251594000  "
+       "    P/E ratio   EPS  beta       mkt cap     shares  \n",
+       "73      14.38  2.46  0.51   25573676437  723033000  \n",
+       "37      31.45  1.66  0.20   28241486749  540714000  \n",
+       "6       26.79  2.23  0.23   14358652779  244628000  \n",
+       "23      21.58  1.26  0.44   13650929559  502242000  \n",
+       "2       27.44  0.76  1.05   13895280692  663893000  \n",
+       "66      34.73  8.02  0.15  136133886150  488776000  \n",
+       "67      10.31  3.89  0.71   10078855985  251594000  "
       ]
      },
-     "execution_count": 52,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2658,7 +3004,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -2686,6 +3032,7 @@
        "      <th>name</th>\n",
        "      <th>sector</th>\n",
        "      <th>sharpe ratio</th>\n",
+       "      <th>FFM returns</th>\n",
        "      <th>P/E ratio</th>\n",
        "      <th>EPS</th>\n",
        "      <th>beta</th>\n",
@@ -2700,6 +3047,7 @@
        "      <td>Genuine Parts</td>\n",
        "      <td>Consumer Discretionary</td>\n",
        "      <td>2.924464</td>\n",
+       "      <td>0.074228</td>\n",
        "      <td>17.71</td>\n",
        "      <td>5.45</td>\n",
        "      <td>0.89</td>\n",
@@ -2712,6 +3060,7 @@
        "      <td>General Mills</td>\n",
        "      <td>Consumer Staples</td>\n",
        "      <td>2.641281</td>\n",
+       "      <td>0.063147</td>\n",
        "      <td>15.34</td>\n",
        "      <td>3.48</td>\n",
        "      <td>0.73</td>\n",
@@ -2724,6 +3073,7 @@
        "      <td>Cabot Oil &amp; Gas</td>\n",
        "      <td>Energy</td>\n",
        "      <td>1.952983</td>\n",
+       "      <td>-0.050017</td>\n",
        "      <td>7.80</td>\n",
        "      <td>1.90</td>\n",
        "      <td>0.47</td>\n",
@@ -2736,6 +3086,7 @@
        "      <td>Synchrony Financial</td>\n",
        "      <td>Financials</td>\n",
        "      <td>2.493336</td>\n",
+       "      <td>0.091836</td>\n",
        "      <td>6.07</td>\n",
        "      <td>5.56</td>\n",
        "      <td>1.21</td>\n",
@@ -2748,6 +3099,7 @@
        "      <td>Amgen Inc</td>\n",
        "      <td>Health Care</td>\n",
        "      <td>1.861649</td>\n",
+       "      <td>0.151749</td>\n",
        "      <td>17.36</td>\n",
        "      <td>12.88</td>\n",
        "      <td>1.12</td>\n",
@@ -2760,6 +3112,7 @@
        "      <td>Southwest Airlines</td>\n",
        "      <td>Industrials</td>\n",
        "      <td>1.726576</td>\n",
+       "      <td>0.107833</td>\n",
        "      <td>13.77</td>\n",
        "      <td>4.21</td>\n",
        "      <td>1.47</td>\n",
@@ -2772,6 +3125,7 @@
        "      <td>Alphabet Inc Class A</td>\n",
        "      <td>Information Technology</td>\n",
        "      <td>1.198026</td>\n",
+       "      <td>0.214640</td>\n",
        "      <td>30.89</td>\n",
        "      <td>49.16</td>\n",
        "      <td>1.02</td>\n",
@@ -2784,6 +3138,7 @@
        "      <td>LyondellBasell</td>\n",
        "      <td>Materials</td>\n",
        "      <td>2.072393</td>\n",
+       "      <td>0.103512</td>\n",
        "      <td>8.65</td>\n",
        "      <td>9.55</td>\n",
        "      <td>1.45</td>\n",
@@ -2796,6 +3151,7 @@
        "      <td>Host Hotels &amp; Resorts</td>\n",
        "      <td>Real Estate</td>\n",
        "      <td>2.308137</td>\n",
+       "      <td>0.052833</td>\n",
        "      <td>10.89</td>\n",
        "      <td>1.55</td>\n",
        "      <td>1.17</td>\n",
@@ -2808,6 +3164,7 @@
        "      <td>PPL Corp.</td>\n",
        "      <td>Utilities</td>\n",
        "      <td>2.755488</td>\n",
+       "      <td>0.098239</td>\n",
        "      <td>14.38</td>\n",
        "      <td>2.46</td>\n",
        "      <td>0.51</td>\n",
@@ -2831,20 +3188,20 @@
        "8    HST  Host Hotels & Resorts             Real Estate      2.308137   \n",
        "9    PPL              PPL Corp.               Utilities      2.755488   \n",
        "\n",
-       "   P/E ratio    EPS  beta        mkt cap     shares  \n",
-       "0      17.71   5.45  0.89    14016415887  145293000  \n",
-       "1      15.34   3.48  0.73    32242795100  604817000  \n",
-       "2       7.80   1.90  0.47     6037284157  407925000  \n",
-       "3       6.07   5.56  1.21    20704848750  613477000  \n",
-       "4      17.36  12.88  1.12   131810065840  589807000  \n",
-       "5      13.77   4.21  1.47    29987649751  517296000  \n",
-       "6      30.89  49.16  1.02  1044236513876  299895000  \n",
-       "7       8.65   9.55  1.45    27505799491  333000000  \n",
-       "8      10.89   1.55  1.17    12127479870  717178000  \n",
-       "9      14.38   2.46  0.51    25573676437  723033000  "
+       "   FFM returns  P/E ratio    EPS  beta        mkt cap     shares  \n",
+       "0     0.074228      17.71   5.45  0.89    14016415887  145293000  \n",
+       "1     0.063147      15.34   3.48  0.73    32242795100  604817000  \n",
+       "2    -0.050017       7.80   1.90  0.47     6037284157  407925000  \n",
+       "3     0.091836       6.07   5.56  1.21    20704848750  613477000  \n",
+       "4     0.151749      17.36  12.88  1.12   131810065840  589807000  \n",
+       "5     0.107833      13.77   4.21  1.47    29987649751  517296000  \n",
+       "6     0.214640      30.89  49.16  1.02  1044236513876  299895000  \n",
+       "7     0.103512       8.65   9.55  1.45    27505799491  333000000  \n",
+       "8     0.052833      10.89   1.55  1.17    12127479870  717178000  \n",
+       "9     0.098239      14.38   2.46  0.51    25573676437  723033000  "
       ]
      },
-     "execution_count": 66,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/selection_data.csv b/selection_data.csv
index 1ca7832..78a1164 100644
--- a/selection_data.csv
+++ b/selection_data.csv
@@ -1,93 +1,93 @@
-ticker,name,sector,sharpe ratio,P/E ratio,EPS,beta,mkt cap,shares
-ACN,Accenture plc,Information Technology,1.113857669340631,28.34,7.49,1.03,139515576338,656946000
-ADBE,Adobe Systems Inc,Information Technology,0.6160597494509739,63.17,6.01,1.09,185174936969,487726000
-AES,AES Corp,Utilities,1.1826406099615412,27.44,0.76,1.05,13895280692,663893000
-AMG,Affiliated Managers Group Inc,Financials,1.0979859640832188,267.18,0.31,1.69,4084648875,49272000
-APD,Air Products & Chemicals Inc,Materials,1.2248244816385878,30.09,8.51,0.86,56495776935,220678000
-ALB,Albemarle Corp,Materials,0.9902917360691272,16.67,5.38,1.57,9504798055,106033000
-LNT,Alliant Energy Corp,Utilities,1.366717870072912,26.79,2.23,0.23,14358652779,244628000
-GOOGL,Alphabet Inc Class A,Information Technology,1.1980263475215909,30.89,49.16,1.02,1044236513876,299895000
-AXP,American Express Co,Financials,1.2144084830799449,17.01,7.99,0.99,111178449600,808041000
-ABC,AmerisourceBergen Corp,Health Care,2.824204459596733,30.62,3.08,1.01,19427969245,205892000
-AMGN,Amgen Inc,Health Care,1.8616491950461436,17.36,12.88,1.12,131810065840,589807000
-AON,Aon plc,Financials,1.1043185924986845,37.0,6.37,0.83,54701475530,234137000
-AAPL,Apple Inc.,Information Technology,0.9190627984536254,25.66,12.66,1.29,1421812279411,4375480000
-AJG,Arthur J. Gallagher & Co.,Financials,0.9671115946025484,31.03,3.52,0.76,20549043209,188247000
-ADP,Automatic Data Processing,Information Technology,1.0045789926171458,32.04,5.66,0.87,78255412500,431754000
-BBY,Best Buy Co. Inc.,Consumer Discretionary,0.8239151677600225,15.98,5.64,1.12,23344272933,258777000
-HRB,Block H&R,Financials,2.2106749521427664,11.75,1.9,0.23,4369605316,195246000
-BWA,BorgWarner,Consumer Discretionary,1.6822710938226986,9.2,3.71,1.91,7048901814,206410000
-BSX,Boston Scientific,Health Care,0.933786790381214,12.7,3.33,0.87,58972695354,1393824000
-BMY,Bristol-Myers Squibb,Health Care,2.6885152748619983,33.05,2.01,0.76,155607591281,2344185000
-COG,Cabot Oil & Gas,Energy,1.9529827367707384,7.8,1.9,0.47,6037284157,407925000
-COF,Capital One Financial,Financials,2.0347637955056546,9.31,11.02,1.25,46865423721,456600000
-KMX,Carmax Inc,Consumer Discretionary,1.703158159266752,19.16,5.16,1.1,16144071451,163385000
-CNP,CenterPoint Energy,Utilities,1.3612303069648497,21.58,1.26,0.44,13650929559,502242000
-CINF,Cincinnati Financial,Financials,1.121373755776759,9.52,12.1,0.57,18822318390,163374000
-CTAS,Cintas Corporation,Industrials,0.7031855337517299,35.38,8.51,0.99,31216601386,103751000
-KO,Coca-Cola Company (The),Consumer Staples,2.1971578395739524,28.99,2.07,0.41,256586003265,4280000000
-COST,Costco Wholesale Corp.,Consumer Staples,1.0606439166888946,37.75,8.43,0.9,140615987901,441758000
-CCI,Crown Castle International Corp.,Real Estate,1.28197687434905,83.64,1.98,0.3,69005081855,415768000
-CVS,CVS Health,Consumer Staples,1.7079627340498365,14.05,5.08,0.93,92849804253,1300964000
-DISCK,Discovery Communications-C,Consumer Discretionary,2.3096592718590108,11.1,2.59,1.45,15392873644,360664000
-ETN,Eaton Corporation,Industrials,1.6047656571399305,19.71,5.25,1.42,42807571261,413400000
-EQR,Equity Residential,Real Estate,2.1589960066234664,34.53,2.5,0.45,32134657027,371671000
-EXPE,Expedia Inc.,Consumer Discretionary,2.407311381193101,32.58,3.77,1.01,17792025802,139363000
-FFIV,F5 Networks,Information Technology,1.7013819459588144,19.49,6.54,0.98,7753118169,60804000
-FB,"Facebook, Inc.",Information Technology,1.1057666021536463,33.32,6.43,1.05,610509360122,2405746000
-FDX,FedEx Corporation,Industrials,1.5098202059987225,583.74,0.27,1.71,41418694505,261119000
-FE,FirstEnergy Corp,Utilities,1.510567029063732,31.45,1.66,0.2,28241486749,540714000
-FISV,Fiserv Inc,Information Technology,0.9488954080578804,71.58,1.71,0.8,83164756192,679895000
-FMC,FMC Corporation,Materials,0.8895256452785432,27.41,3.85,1.54,13670494208,129615000
-FCX,Freeport-McMoRan Inc.,Materials,1.0313162803944909,78.35,0.16,2.42,17759187027,1450914000
-IT,Gartner Inc,Information Technology,1.3373284476702674,59.34,2.57,1.21,13633532057,89453000
-GIS,General Mills,Consumer Staples,2.6412807761987938,15.34,3.48,0.73,32242795100,604817000
-GM,General Motors,Consumer Discretionary,1.9037211165069965,7.6,4.57,1.38,49672072361,1429002000
-GPC,Genuine Parts,Consumer Discretionary,2.9244641954801547,17.71,5.45,0.89,14016415887,145293000
-GS,Goldman Sachs Group,Financials,1.8288212830340496,11.27,21.03,1.32,83946946608,354087000
-GWW,Grainger (W.W.) Inc.,Industrials,1.3581101466189422,17.94,17.15,0.97,16517112872,53688000
-HLT,Hilton Worldwide Holdings Inc,Consumer Discretionary,1.0598993481607704,37.27,3.04,1.14,31415437971,277448000
-HOLX,Hologic,Health Care,2.425411589403344,173.01,0.31,0.85,13960272160,263302000
-HST,Host Hotels & Resorts,Real Estate,2.308137021714921,10.89,1.55,1.17,12127479870,717178000
-HII,Huntington Ingalls Industries,Industrials,1.1543380976790991,18.57,13.26,1.24,10035519873,40760000
-INCY,Incyte,Health Care,1.2682583277151145,38.21,2.05,1.06,17006076538,216776000
-IRM,Iron Mountain Incorporated,Real Estate,2.2335183274879347,35.67,0.93,0.53,9521121824,287300000
-KMI,Kinder Morgan,Energy,1.0384695673083184,22.87,0.96,0.81,49831386000,2265063000
-LKQ,LKQ Corporation,Consumer Discretionary,2.216065603315,23.73,1.4,1.3,10174538633,306462000
-LYB,LyondellBasell,Materials,2.072392824468477,8.65,9.55,1.45,27505799491,333000000
-M,Macy's Inc.,Consumer Discretionary,0.8264829931760201,5.39,3.09,0.66,5150446573,308965000
-MDT,Medtronic plc,Health Care,1.9179209088058464,33.97,3.45,0.6,157266553194,1340378000
-MRK,Merck & Co.,Health Care,1.3680581566358117,21.52,3.84,0.57,210425581484,2545984000
-MTD,Mettler Toledo,Health Care,0.9692418639176908,33.97,22.47,1.39,18357249893,24053000
-MSFT,Microsoft Corp.,Information Technology,0.6881506526553905,32.28,5.74,1.15,1409780857873,7606047000
-MHK,Mohawk Industries,Consumer Discretionary,1.2551682079723412,13.4,10.3,1.36,9882403253,71622000
-MCO,Moody's Corp,Financials,0.927983578033472,37.43,7.42,1.21,52148688479,187700000
-MSI,Motorola Solutions Inc.,Information Technology,0.7857028051967873,37.31,4.94,0.5,31596072387,171336000
-MYL,Mylan N.V.,Health Care,0.8932799452587622,239.58,0.09,1.72,11303303743,516177000
-NEM,Newmont Mining Corporation,Materials,1.2486611843780435,15.83,2.78,0.16,36130286851,819839000
-NEE,NextEra Energy,Utilities,0.9286832114176752,34.73,8.02,0.15,136133886150,488776000
-NRG,NRG Energy,Utilities,0.6922170062921974,10.31,3.89,0.71,10078855985,251594000
-OXY,Occidental Petroleum,Energy,2.054770999686784,29.53,1.41,0.9,37161985836,893317000
-OKE,ONEOK,Energy,0.9173258155980414,25.56,3.01,1.11,31799253894,413085000
-ORCL,Oracle Corp.,Information Technology,1.9496194449404018,17.61,3.15,1.11,177928293945,3207649000
-PEP,PepsiCo Inc.,Consumer Staples,1.9512497779197016,28.31,5.19,0.53,204968008309,1389545000
-RL,Polo Ralph Lauren Corp.,Consumer Discretionary,1.6850277667707554,14.16,8.61,0.9,8984857815,48862000
-PPL,PPL Corp.,Utilities,2.7554877393877537,14.38,2.46,0.51,25573676437,723033000
-PHM,Pulte Homes Inc.,Consumer Discretionary,1.1252252514376082,12.77,3.66,0.56,12605132379,269975000
-RJF,Raymond James Financial Inc.,Financials,1.2811378025870532,13.44,7.36,1.5,13782151374,139284000
-RTN,Raytheon Co.,Industrials,1.158337993905323,19.05,11.93,0.85,63256224340,278441000
-RMD,ResMed,Health Care,0.834963320137938,56.31,3.14,0.48,25539363082,144617000
-RCL,Royal Caribbean Cruises Ltd,Consumer Discretionary,1.3470625587214564,12.55,9.02,1.44,23627921924,208801000
-CRM,Salesforce.com,Information Technology,0.8858414532311987,200.68,0.95,1.19,168485647293,887000000
-LUV,Southwest Airlines,Industrials,1.7265757683369565,13.77,4.21,1.47,29987649751,517296000
-SBUX,Starbucks Corp.,Consumer Discretionary,1.3884881607519866,29.15,3.06,0.56,104787934567,1173700000
-SYF,Synchrony Financial,Financials,2.4933359586834767,6.07,5.56,1.21,20704848750,613477000
-SNPS,Synopsys Inc.,Information Technology,0.8013663430252196,47.31,3.45,1.18,24589893168,150535000
-TGT,Target Corp.,Consumer Discretionary,1.340881991913131,18.64,6.26,0.56,59100734918,506737000
-TXN,Texas Instruments,Information Technology,0.8862468117623082,25.24,5.24,1.24,123223956977,932032000
-HSY,The Hershey Company,Consumer Staples,1.4696819942330823,29.33,5.47,0.02,23779704176,148308000
-TMO,Thermo Fisher Scientific,Health Care,0.9572371356767688,36.98,9.17,1.14,136012138268,400991000
-UNH,United Health Group Inc.,Health Care,0.8928925321222835,20.86,14.33,0.69,283068652543,947415000
-VFC,V.F. Corp.,Consumer Discretionary,1.3232414086548459,25.99,3.22,1.2,33022293377,394720000
-WMT,Wal-Mart Stores,Consumer Staples,1.2710964130621618,23.55,5.0,0.36,334474559018,2837175000
-WBA,Walgreens Boots Alliance,Consumer Staples,2.224201311650672,13.0,4.07,0.92,46817805348,885862000
+ticker,name,sector,sharpe ratio,FFM returns,P/E ratio,EPS,beta,mkt cap,shares
+ACN,Accenture plc,Information Technology,1.113857669340631,0.225818128,28.34,7.49,1.03,139515576338,656946000
+ADBE,Adobe Systems Inc,Information Technology,0.6160597494509739,0.329761028,63.17,6.01,1.09,185174936969,487726000
+AES,AES Corp,Utilities,1.1826406099615412,0.162653808,27.44,0.76,1.05,13895280692,663893000
+AMG,Affiliated Managers Group Inc,Financials,1.0979859640832188,-0.13879823300000002,267.18,0.31,1.69,4084648875,49272000
+APD,Air Products & Chemicals Inc,Materials,1.2248244816385878,0.153160881,30.09,8.51,0.86,56495776935,220678000
+ALB,Albemarle Corp,Materials,0.9902917360691272,0.132207229,16.67,5.38,1.57,9504798055,106033000
+LNT,Alliant Energy Corp,Utilities,1.366717870072912,0.166244327,26.79,2.23,0.23,14358652779,244628000
+GOOGL,Alphabet Inc Class A,Information Technology,1.1980263475215909,0.214639843,30.89,49.16,1.02,1044236513876,299895000
+AXP,American Express Co,Financials,1.2144084830799449,0.132252227,17.01,7.99,0.99,111178449600,808041000
+ABC,AmerisourceBergen Corp,Health Care,2.824204459596733,0.018486986,30.62,3.08,1.01,19427969245,205892000
+AMGN,Amgen Inc,Health Care,1.8616491950461436,0.151748658,17.36,12.88,1.12,131810065840,589807000
+AON,Aon plc,Financials,1.1043185924986845,0.183167419,37.0,6.37,0.83,54701475530,234137000
+AAPL,Apple Inc.,Information Technology,0.9190627984536254,0.236049322,25.66,12.66,1.29,1421812279411,4375480000
+AJG,Arthur J. Gallagher & Co.,Financials,0.9671115946025484,0.195583018,31.03,3.52,0.76,20549043209,188247000
+ADP,Automatic Data Processing,Information Technology,1.0045789926171458,0.18326947600000001,32.04,5.66,0.87,78255412500,431754000
+BBY,Best Buy Co. Inc.,Consumer Discretionary,0.8239151677600225,0.264073092,15.98,5.64,1.12,23344272933,258777000
+HRB,Block H&R,Financials,2.2106749521427664,0.001103738,11.75,1.9,0.23,4369605316,195246000
+BWA,BorgWarner,Consumer Discretionary,1.6822710938226986,-0.008936781,9.2,3.71,1.91,7048901814,206410000
+BSX,Boston Scientific,Health Care,0.933786790381214,0.23386062100000002,12.7,3.33,0.87,58972695354,1393824000
+BMY,Bristol-Myers Squibb,Health Care,2.6885152748619983,0.083176807,33.05,2.01,0.76,155607591281,2344185000
+COG,Cabot Oil & Gas,Energy,1.9529827367707384,-0.050016632000000005,7.8,1.9,0.47,6037284157,407925000
+COF,Capital One Financial,Financials,2.0347637955056546,0.11610429900000001,9.31,11.02,1.25,46865423721,456600000
+KMX,Carmax Inc,Consumer Discretionary,1.703158159266752,0.099285234,19.16,5.16,1.1,16144071451,163385000
+CNP,CenterPoint Energy,Utilities,1.3612303069648497,0.121501687,21.58,1.26,0.44,13650929559,502242000
+CINF,Cincinnati Financial,Financials,1.121373755776759,0.199837867,9.52,12.1,0.57,18822318390,163374000
+CTAS,Cintas Corporation,Industrials,0.7031855337517299,0.2859733,35.38,8.51,0.99,31216601386,103751000
+KO,Coca-Cola Company (The),Consumer Staples,2.1971578395739524,0.103820149,28.99,2.07,0.41,256586003265,4280000000
+COST,Costco Wholesale Corp.,Consumer Staples,1.0606439166888946,0.19212997399999998,37.75,8.43,0.9,140615987901,441758000
+CCI,Crown Castle International Corp.,Real Estate,1.28197687434905,0.163975237,83.64,1.98,0.3,69005081855,415768000
+CVS,CVS Health,Consumer Staples,1.7079627340498365,-0.010387317,14.05,5.08,0.93,92849804253,1300964000
+DISCK,Discovery Communications-C,Consumer Discretionary,2.3096592718590108,0.061552496,11.1,2.59,1.45,15392873644,360664000
+ETN,Eaton Corporation,Industrials,1.6047656571399305,0.128998261,19.71,5.25,1.42,42807571261,413400000
+EQR,Equity Residential,Real Estate,2.1589960066234664,0.08949458,34.53,2.5,0.45,32134657027,371671000
+EXPE,Expedia Inc.,Consumer Discretionary,2.407311381193101,0.086285553,32.58,3.77,1.01,17792025802,139363000
+FFIV,F5 Networks,Information Technology,1.7013819459588144,0.06498939599999999,19.49,6.54,0.98,7753118169,60804000
+FB,"Facebook, Inc.",Information Technology,1.1057666021536463,0.23878909399999998,33.32,6.43,1.05,610509360122,2405746000
+FDX,FedEx Corporation,Industrials,1.5098202059987225,0.02425391,583.74,0.27,1.71,41418694505,261119000
+FE,FirstEnergy Corp,Utilities,1.510567029063732,0.129909559,31.45,1.66,0.2,28241486749,540714000
+FISV,Fiserv Inc,Information Technology,0.9488954080578804,0.249902978,71.58,1.71,0.8,83164756192,679895000
+FMC,FMC Corporation,Materials,0.8895256452785432,0.193866857,27.41,3.85,1.54,13670494208,129615000
+FCX,Freeport-McMoRan Inc.,Materials,1.0313162803944909,0.038646264,78.35,0.16,2.42,17759187027,1450914000
+IT,Gartner Inc,Information Technology,1.3373284476702674,0.165213744,59.34,2.57,1.21,13633532057,89453000
+GIS,General Mills,Consumer Staples,2.6412807761987938,0.063146888,15.34,3.48,0.73,32242795100,604817000
+GM,General Motors,Consumer Discretionary,1.9037211165069965,0.08449462,7.6,4.57,1.38,49672072361,1429002000
+GPC,Genuine Parts,Consumer Discretionary,2.9244641954801547,0.074228025,17.71,5.45,0.89,14016415887,145293000
+GS,Goldman Sachs Group,Financials,1.8288212830340496,0.09991453900000001,11.27,21.03,1.32,83946946608,354087000
+GWW,Grainger (W.W.) Inc.,Industrials,1.3581101466189422,0.143753783,17.94,17.15,0.97,16517112872,53688000
+HLT,Hilton Worldwide Holdings Inc,Consumer Discretionary,1.0598993481607704,0.17104685100000003,37.27,3.04,1.14,31415437971,277448000
+HOLX,Hologic,Health Care,2.425411589403344,0.12996771199999999,173.01,0.31,0.85,13960272160,263302000
+HST,Host Hotels & Resorts,Real Estate,2.308137021714921,0.052833242,10.89,1.55,1.17,12127479870,717178000
+HII,Huntington Ingalls Industries,Industrials,1.1543380976790991,0.172309762,18.57,13.26,1.24,10035519873,40760000
+INCY,Incyte,Health Care,1.2682583277151145,0.076793095,38.21,2.05,1.06,17006076538,216776000
+IRM,Iron Mountain Incorporated,Real Estate,2.2335183274879347,0.07306073099999999,35.67,0.93,0.53,9521121824,287300000
+KMI,Kinder Morgan,Energy,1.0384695673083184,-0.038511214,22.87,0.96,0.81,49831386000,2265063000
+LKQ,LKQ Corporation,Consumer Discretionary,2.216065603315,0.12177166099999999,23.73,1.4,1.3,10174538633,306462000
+LYB,LyondellBasell,Materials,2.072392824468477,0.103512466,8.65,9.55,1.45,27505799491,333000000
+M,Macy's Inc.,Consumer Discretionary,0.8264829931760201,-0.12659805,5.39,3.09,0.66,5150446573,308965000
+MDT,Medtronic plc,Health Care,1.9179209088058464,0.12421349,33.97,3.45,0.6,157266553194,1340378000
+MRK,Merck & Co.,Health Care,1.3680581566358117,0.147015861,21.52,3.84,0.57,210425581484,2545984000
+MTD,Mettler Toledo,Health Care,0.9692418639176908,0.23289527,33.97,22.47,1.39,18357249893,24053000
+MSFT,Microsoft Corp.,Information Technology,0.6881506526553905,0.32250065,32.28,5.74,1.15,1409780857873,7606047000
+MHK,Mohawk Industries,Consumer Discretionary,1.2551682079723412,-0.016397061,13.4,10.3,1.36,9882403253,71622000
+MCO,Moody's Corp,Financials,0.927983578033472,0.234858117,37.43,7.42,1.21,52148688479,187700000
+MSI,Motorola Solutions Inc.,Information Technology,0.7857028051967873,0.231468305,37.31,4.94,0.5,31596072387,171336000
+MYL,Mylan N.V.,Health Care,0.8932799452587622,-0.130828848,239.58,0.09,1.72,11303303743,516177000
+NEM,Newmont Mining Corporation,Materials,1.2486611843780435,0.18968579600000002,15.83,2.78,0.16,36130286851,819839000
+NEE,NextEra Energy,Utilities,0.9286832114176752,0.227986191,34.73,8.02,0.15,136133886150,488776000
+NRG,NRG Energy,Utilities,0.6922170062921974,0.20866969600000002,10.31,3.89,0.71,10078855985,251594000
+OXY,Occidental Petroleum,Energy,2.054770999686784,-0.042821394000000006,29.53,1.41,0.9,37161985836,893317000
+OKE,ONEOK,Energy,0.9173258155980414,0.230147782,25.56,3.01,1.11,31799253894,413085000
+ORCL,Oracle Corp.,Information Technology,1.9496194449404018,0.077350148,17.61,3.15,1.11,177928293945,3207649000
+PEP,PepsiCo Inc.,Consumer Staples,1.9512497779197016,0.117935265,28.31,5.19,0.53,204968008309,1389545000
+RL,Polo Ralph Lauren Corp.,Consumer Discretionary,1.6850277667707554,0.046267077000000004,14.16,8.61,0.9,8984857815,48862000
+PPL,PPL Corp.,Utilities,2.7554877393877537,0.098239274,14.38,2.46,0.51,25573676437,723033000
+PHM,Pulte Homes Inc.,Consumer Discretionary,1.1252252514376082,0.16513204,12.77,3.66,0.56,12605132379,269975000
+RJF,Raymond James Financial Inc.,Financials,1.2811378025870532,0.1550463,13.44,7.36,1.5,13782151374,139284000
+RTN,Raytheon Co.,Industrials,1.158337993905323,0.19479614,19.05,11.93,0.85,63256224340,278441000
+RMD,ResMed,Health Care,0.834963320137938,0.23631678,56.31,3.14,0.48,25539363082,144617000
+RCL,Royal Caribbean Cruises Ltd,Consumer Discretionary,1.3470625587214564,0.195659444,12.55,9.02,1.44,23627921924,208801000
+CRM,Salesforce.com,Information Technology,0.8858414532311987,0.207470204,200.68,0.95,1.19,168485647293,887000000
+LUV,Southwest Airlines,Industrials,1.7265757683369565,0.10783286199999999,13.77,4.21,1.47,29987649751,517296000
+SBUX,Starbucks Corp.,Consumer Discretionary,1.3884881607519866,0.177744967,29.15,3.06,0.56,104787934567,1173700000
+SYF,Synchrony Financial,Financials,2.4933359586834767,0.091836098,6.07,5.56,1.21,20704848750,613477000
+SNPS,Synopsys Inc.,Information Technology,0.8013663430252196,0.258978767,47.31,3.45,1.18,24589893168,150535000
+TGT,Target Corp.,Consumer Discretionary,1.340881991913131,0.185069819,18.64,6.26,0.56,59100734918,506737000
+TXN,Texas Instruments,Information Technology,0.8862468117623082,0.224912306,25.24,5.24,1.24,123223956977,932032000
+HSY,The Hershey Company,Consumer Staples,1.4696819942330823,0.125085342,29.33,5.47,0.02,23779704176,148308000
+TMO,Thermo Fisher Scientific,Health Care,0.9572371356767688,0.223396092,36.98,9.17,1.14,136012138268,400991000
+UNH,United Health Group Inc.,Health Care,0.8928925321222835,0.243093824,20.86,14.33,0.69,283068652543,947415000
+VFC,V.F. Corp.,Consumer Discretionary,1.3232414086548459,0.129110804,25.99,3.22,1.2,33022293377,394720000
+WMT,Wal-Mart Stores,Consumer Staples,1.2710964130621618,0.125054707,23.55,5.0,0.36,334474559018,2837175000
+WBA,Walgreens Boots Alliance,Consumer Staples,2.224201311650672,-0.007405433,13.0,4.07,0.92,46817805348,885862000

From 4544783aef0b4879c5bd947a3ffb39802935cd74 Mon Sep 17 00:00:00 2001
From: Brody <wacker.brody@gmail.com>
Date: Wed, 19 Feb 2020 20:58:14 -0500
Subject: [PATCH 2/3] creating portfolio csv file

---
 .ipynb_checkpoints/portfolio-checkpoint.csv   |  11 ++
 .../selection_criteria-checkpoint.ipynb       | 102 +++++++++---------
 portfolio.csv                                 |  11 ++
 selection_criteria.ipynb                      | 102 +++++++++---------
 4 files changed, 130 insertions(+), 96 deletions(-)
 create mode 100644 .ipynb_checkpoints/portfolio-checkpoint.csv
 create mode 100644 portfolio.csv

diff --git a/.ipynb_checkpoints/portfolio-checkpoint.csv b/.ipynb_checkpoints/portfolio-checkpoint.csv
new file mode 100644
index 0000000..c5b695a
--- /dev/null
+++ b/.ipynb_checkpoints/portfolio-checkpoint.csv
@@ -0,0 +1,11 @@
+ticker,name,sector,sharpe ratio,FFM returns,P/E ratio,EPS,beta,mkt cap,shares
+GPC,Genuine Parts,Consumer Discretionary,2.9244641954801547,0.074228025,17.71,5.45,0.89,14016415887,145293000
+GIS,General Mills,Consumer Staples,2.6412807761987938,0.063146888,15.34,3.48,0.73,32242795100,604817000
+COG,Cabot Oil & Gas,Energy,1.9529827367707384,-0.050016632000000005,7.8,1.9,0.47,6037284157,407925000
+SYF,Synchrony Financial,Financials,2.4933359586834767,0.091836098,6.07,5.56,1.21,20704848750,613477000
+AMGN,Amgen Inc,Health Care,1.8616491950461436,0.151748658,17.36,12.88,1.12,131810065840,589807000
+LUV,Southwest Airlines,Industrials,1.7265757683369565,0.10783286199999999,13.77,4.21,1.47,29987649751,517296000
+GOOGL,Alphabet Inc Class A,Information Technology,1.1980263475215909,0.214639843,30.89,49.16,1.02,1044236513876,299895000
+LYB,LyondellBasell,Materials,2.072392824468477,0.103512466,8.65,9.55,1.45,27505799491,333000000
+HST,Host Hotels & Resorts,Real Estate,2.308137021714921,0.052833242,10.89,1.55,1.17,12127479870,717178000
+PPL,PPL Corp.,Utilities,2.7554877393877537,0.098239274,14.38,2.46,0.51,25573676437,723033000
diff --git a/.ipynb_checkpoints/selection_criteria-checkpoint.ipynb b/.ipynb_checkpoints/selection_criteria-checkpoint.ipynb
index 2b53187..c335771 100644
--- a/.ipynb_checkpoints/selection_criteria-checkpoint.ipynb
+++ b/.ipynb_checkpoints/selection_criteria-checkpoint.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -127,7 +127,7 @@
        "[505 rows x 2 columns]"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -141,7 +141,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -240,7 +240,7 @@
        "[100 rows x 1 columns]"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -254,7 +254,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -353,7 +353,7 @@
        "[100 rows x 1 columns]"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -367,7 +367,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -518,7 +518,7 @@
        "[100 rows x 5 columns]"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -532,7 +532,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -760,7 +760,7 @@
        "[92 rows x 10 columns]"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -776,7 +776,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 112,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -785,7 +785,7 @@
        "Text(0, 0.5, 'Sharpe Ratio')"
       ]
      },
-     "execution_count": 112,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -816,7 +816,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 113,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -825,7 +825,7 @@
        "(0, 100)"
       ]
      },
-     "execution_count": 113,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -857,7 +857,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -866,7 +866,7 @@
        "Text(0, 0.5, 'FFM Returns')"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -893,7 +893,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -906,7 +906,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -1005,7 +1005,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -1326,7 +1326,7 @@
        "15   258777000  "
       ]
      },
-     "execution_count": 17,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1339,7 +1339,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -1506,7 +1506,7 @@
        "27     0.192130      37.75  8.43  0.90  140615987901   441758000  "
       ]
      },
-     "execution_count": 18,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1519,7 +1519,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -1626,7 +1626,7 @@
        "69  3.01  1.11  31799253894   413085000  "
       ]
      },
-     "execution_count": 19,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1639,7 +1639,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -1851,7 +1851,7 @@
        "62     0.234858      37.43   7.42  1.21   52148688479  187700000  "
       ]
      },
-     "execution_count": 20,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1864,7 +1864,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -2106,7 +2106,7 @@
        "77      56.31   3.14  0.48   25539363082   144617000  "
       ]
      },
-     "execution_count": 21,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2119,7 +2119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -2271,7 +2271,7 @@
        "25     0.285973      35.38   8.51  0.99  31216601386  103751000  "
       ]
      },
-     "execution_count": 22,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2284,7 +2284,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -2556,7 +2556,7 @@
        "1      0.329761      63.17   6.01  1.09   185174936969   487726000  "
       ]
      },
-     "execution_count": 23,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2569,7 +2569,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -2706,7 +2706,7 @@
        "39      27.41  3.85  1.54  13670494208   129615000  "
       ]
      },
-     "execution_count": 24,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2719,7 +2719,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -2826,7 +2826,7 @@
        "28     0.163975      83.64  1.98  0.30  69005081855  415768000  "
       ]
      },
-     "execution_count": 25,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2839,7 +2839,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -2991,7 +2991,7 @@
        "67      10.31  3.89  0.71   10078855985  251594000  "
       ]
      },
-     "execution_count": 26,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3004,7 +3004,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -3201,7 +3201,7 @@
        "9     0.098239      14.38   2.46  0.51    25573676437  723033000  "
       ]
      },
-     "execution_count": 27,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3217,7 +3217,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 111,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -3226,13 +3226,13 @@
        "Text(0, 0.5, 'Sharpe Ratio')"
       ]
      },
-     "execution_count": 111,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
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\n",
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\n",
       "text/plain": [
        "<Figure size 1800x720 with 1 Axes>"
       ]
@@ -3257,7 +3257,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 108,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
@@ -3266,7 +3266,7 @@
        "Text(0, 0.5, 'P/E Ratio')"
       ]
      },
-     "execution_count": 108,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -3297,10 +3297,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "# printing the dataset to csv \n",
+    "output = 'portfolio.csv'\n",
+    "\n",
+    "with open(output, 'w') as file:\n",
+    "    file.write(portfolio_df.to_csv(index=False))"
+   ]
   }
  ],
  "metadata": {
diff --git a/portfolio.csv b/portfolio.csv
new file mode 100644
index 0000000..c5b695a
--- /dev/null
+++ b/portfolio.csv
@@ -0,0 +1,11 @@
+ticker,name,sector,sharpe ratio,FFM returns,P/E ratio,EPS,beta,mkt cap,shares
+GPC,Genuine Parts,Consumer Discretionary,2.9244641954801547,0.074228025,17.71,5.45,0.89,14016415887,145293000
+GIS,General Mills,Consumer Staples,2.6412807761987938,0.063146888,15.34,3.48,0.73,32242795100,604817000
+COG,Cabot Oil & Gas,Energy,1.9529827367707384,-0.050016632000000005,7.8,1.9,0.47,6037284157,407925000
+SYF,Synchrony Financial,Financials,2.4933359586834767,0.091836098,6.07,5.56,1.21,20704848750,613477000
+AMGN,Amgen Inc,Health Care,1.8616491950461436,0.151748658,17.36,12.88,1.12,131810065840,589807000
+LUV,Southwest Airlines,Industrials,1.7265757683369565,0.10783286199999999,13.77,4.21,1.47,29987649751,517296000
+GOOGL,Alphabet Inc Class A,Information Technology,1.1980263475215909,0.214639843,30.89,49.16,1.02,1044236513876,299895000
+LYB,LyondellBasell,Materials,2.072392824468477,0.103512466,8.65,9.55,1.45,27505799491,333000000
+HST,Host Hotels & Resorts,Real Estate,2.308137021714921,0.052833242,10.89,1.55,1.17,12127479870,717178000
+PPL,PPL Corp.,Utilities,2.7554877393877537,0.098239274,14.38,2.46,0.51,25573676437,723033000
diff --git a/selection_criteria.ipynb b/selection_criteria.ipynb
index 2b53187..c335771 100644
--- a/selection_criteria.ipynb
+++ b/selection_criteria.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -127,7 +127,7 @@
        "[505 rows x 2 columns]"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -141,7 +141,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -240,7 +240,7 @@
        "[100 rows x 1 columns]"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -254,7 +254,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -353,7 +353,7 @@
        "[100 rows x 1 columns]"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -367,7 +367,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -518,7 +518,7 @@
        "[100 rows x 5 columns]"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -532,7 +532,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -760,7 +760,7 @@
        "[92 rows x 10 columns]"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -776,7 +776,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 112,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -785,7 +785,7 @@
        "Text(0, 0.5, 'Sharpe Ratio')"
       ]
      },
-     "execution_count": 112,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -816,7 +816,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 113,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -825,7 +825,7 @@
        "(0, 100)"
       ]
      },
-     "execution_count": 113,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -857,7 +857,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -866,7 +866,7 @@
        "Text(0, 0.5, 'FFM Returns')"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -893,7 +893,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -906,7 +906,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -1005,7 +1005,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -1326,7 +1326,7 @@
        "15   258777000  "
       ]
      },
-     "execution_count": 17,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1339,7 +1339,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -1506,7 +1506,7 @@
        "27     0.192130      37.75  8.43  0.90  140615987901   441758000  "
       ]
      },
-     "execution_count": 18,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1519,7 +1519,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -1626,7 +1626,7 @@
        "69  3.01  1.11  31799253894   413085000  "
       ]
      },
-     "execution_count": 19,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1639,7 +1639,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -1851,7 +1851,7 @@
        "62     0.234858      37.43   7.42  1.21   52148688479  187700000  "
       ]
      },
-     "execution_count": 20,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1864,7 +1864,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -2106,7 +2106,7 @@
        "77      56.31   3.14  0.48   25539363082   144617000  "
       ]
      },
-     "execution_count": 21,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2119,7 +2119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -2271,7 +2271,7 @@
        "25     0.285973      35.38   8.51  0.99  31216601386  103751000  "
       ]
      },
-     "execution_count": 22,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2284,7 +2284,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -2556,7 +2556,7 @@
        "1      0.329761      63.17   6.01  1.09   185174936969   487726000  "
       ]
      },
-     "execution_count": 23,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2569,7 +2569,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -2706,7 +2706,7 @@
        "39      27.41  3.85  1.54  13670494208   129615000  "
       ]
      },
-     "execution_count": 24,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2719,7 +2719,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -2826,7 +2826,7 @@
        "28     0.163975      83.64  1.98  0.30  69005081855  415768000  "
       ]
      },
-     "execution_count": 25,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2839,7 +2839,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -2991,7 +2991,7 @@
        "67      10.31  3.89  0.71   10078855985  251594000  "
       ]
      },
-     "execution_count": 26,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3004,7 +3004,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -3201,7 +3201,7 @@
        "9     0.098239      14.38   2.46  0.51    25573676437  723033000  "
       ]
      },
-     "execution_count": 27,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3217,7 +3217,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 111,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -3226,13 +3226,13 @@
        "Text(0, 0.5, 'Sharpe Ratio')"
       ]
      },
-     "execution_count": 111,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
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\n",
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\n",
       "text/plain": [
        "<Figure size 1800x720 with 1 Axes>"
       ]
@@ -3257,7 +3257,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 108,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
@@ -3266,7 +3266,7 @@
        "Text(0, 0.5, 'P/E Ratio')"
       ]
      },
-     "execution_count": 108,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -3297,10 +3297,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "# printing the dataset to csv \n",
+    "output = 'portfolio.csv'\n",
+    "\n",
+    "with open(output, 'w') as file:\n",
+    "    file.write(portfolio_df.to_csv(index=False))"
+   ]
   }
  ],
  "metadata": {

From a77fdf76cc50277ec39a0f02890cba6427869aa6 Mon Sep 17 00:00:00 2001
From: Brody <wacker.brody@gmail.com>
Date: Wed, 19 Feb 2020 21:50:09 -0500
Subject: [PATCH 3/3] cleaning some files

---
 .../monthly_data-checkpoint.csv               | 118 +--
 .ipynb_checkpoints/portfolio-checkpoint.csv   |   2 +-
 .ipynb_checkpoints/stock_data-checkpoint.csv  | 101 +++
 data_cleaning.ipynb                           | 700 ++++++++++++++----
 monthly_data.csv                              | 119 ++-
 portfolio.csv                                 |   2 +-
 selection_criteria.ipynb                      | 123 +--
 stock_picking.ipynb                           | 107 ---
 8 files changed, 835 insertions(+), 437 deletions(-)
 create mode 100644 .ipynb_checkpoints/stock_data-checkpoint.csv
 delete mode 100644 stock_picking.ipynb

diff --git a/.ipynb_checkpoints/monthly_data-checkpoint.csv b/.ipynb_checkpoints/monthly_data-checkpoint.csv
index 651a31d..375688e 100644
--- a/.ipynb_checkpoints/monthly_data-checkpoint.csv
+++ b/.ipynb_checkpoints/monthly_data-checkpoint.csv
@@ -1,59 +1,59 @@
-Date,DXC,BBY,AMG,CNP,WMT,MRK,NEM,VFC,MDT,HST,MTD,CCI,KMI,RMD,LUV,NWS,AMGN,APD,TGT,MYL,GPC,FCX,KO,DISCK,FISV,ACN,SRCL,IT,PHM,ALB,AAPL,EFX,FE,COST,GWW,M,CRM,LKQ,AON,PEP,RJF,ORCL,MHK,PPL,FMC,OKE,EQR,RCL,IRM,BA,ABC,GIS,SYF,BMY,ADBE,SNPS,BWA,MSI,COF,LYB,RTN,FFIV,HLT,CVS,NEE,KMX,INCY,MGM,AES,GM,FDX,ADP,HOLX,NRG,NBL,MSFT,COG,OXY,GOOGL,GS,HRB,AJG,CINF,TXN,ETN,EXPE,TMO,BSX,CTAS,WBA,UNH,HSY,FB,EIX,SBUX,MCO,HII,RL,LNT,AXP
-3/31/15,22.12887955,33.17991257,209.0900574,16.58027267,73.01541138,49.78084564,20.14196968,62.42157745,70.46037292,16.2150135,328.6499939,68.70916748,34.21094131,66.11945343,42.28531647,14.84605312,140.7632446,122.6047897,69.96856689,59.34999847,81.15415955,18.19032478,34.73751068,29.47999954,39.70000076,84.22186279,140.4299927,83.84999847,20.65921211,48.82647324,114.5078812,87.83695221,28.48910141,138.0237427,212.1398468,50.79764938,66.80999756,25.55999947,90.70262909,83.08290863,53.11358261,39.84144211,185.75,24.88516998,46.18547821,36.38588333,60.05521774,73.40809631,26.71063995,131.8426514,104.9794693,47.03043365,27.96347618,56.33089447,73.94000244,46.31999969,56.40074158,60.64439392,70.51819611,72.33731079,99.14241028,114.9400024,58.83329391,91.35561371,89.90338135,69.01000214,91.66000366,20.02988815,10.53318119,30.31094933,157.6053925,77.0472641,33.02999878,23.57284737,45.09856415,36.76264191,28.1772213,57.97121048,554.7000122,174.9113922,27.07629585,40.91389084,46.11833954,50.14593887,57.64738083,89.95684814,132.1265717,17.75,77.17124939,76.2355423,109.7141113,89.78566742,82.22000122,53.20843887,43.33609772,97.56402588,131.2903137,118.7339096,26.84617615,72.46104431
-4/30/15,21.84752274,30.42296982,220.139389,17.03519058,69.28697205,51.58223724,24.57673073,60.03445435,67.26213837,16.18287468,317.0100098,69.53327179,35.31919098,58.89770889,38.71540451,14.56540966,139.0549164,116.2427292,67.20631409,72.26000214,78.24552917,22.39833641,34.74606705,30.22999954,38.79999924,85.10553741,133.4299927,82.98000336,17.93624687,55.16541672,115.1704788,91.54878235,29.17978859,130.6819,223.4930878,50.57852936,72.81999969,27.06999969,91.08507538,82.64845276,52.87973022,40.41659546,173.5,25.15871429,47.84734344,36.73788834,56.96993256,61.04038239,25.25355911,125.9216461,105.5612946,46.34711075,28.70056725,55.97953415,76.05999756,46.88000107,55.20708466,54.34983063,72.33436584,85.28881073,94.37812042,122.0199966,57.5223465,88.19024658,87.20759583,68.11000061,97.16000366,20.14417648,10.8610611,28.33872223,161.5300598,76.05762482,33.74000168,23.75412941,46.77707672,43.97773743,32.27069855,63.60951233,548.7700195,182.774353,25.53124428,41.85906982,43.83319092,47.82565689,58.78262329,90.05240631,123.6092529,17.81999969,75.58300018,74.66005707,103.3236389,81.78668213,78.76999664,51.90526199,45.37706375,101.0605469,123.2714539,120.4584579,25.99754906,71.83956909
-5/31/15,21.84752274,30.42296982,220.139389,17.03519058,69.28697205,51.58223724,24.57673073,60.03445435,67.26213837,16.18287468,317.0100098,69.53327179,35.31919098,58.89770889,38.71540451,14.56540966,139.0549164,116.2427292,67.20631409,72.26000214,78.24552917,22.39833641,34.74606705,30.22999954,38.79999924,85.10553741,133.4299927,82.98000336,17.93624687,55.16541672,115.1704788,91.54878235,29.17978859,130.6819,223.4930878,50.57852936,72.81999969,27.06999969,91.08507538,82.64845276,52.87973022,40.41659546,173.5,25.15871429,47.84734344,36.73788834,56.96993256,61.04038239,25.25355911,125.9216461,105.5612946,46.34711075,28.70056725,55.97953415,76.05999756,46.88000107,55.20708466,54.34983063,72.33436584,85.28881073,94.37812042,122.0199966,57.5223465,88.19024658,87.20759583,68.11000061,97.16000366,20.14417648,10.8610611,28.33872223,161.5300598,76.05762482,33.74000168,23.75412941,46.77707672,43.97773743,32.27069855,63.60951233,548.7700195,182.774353,25.53124428,41.85906982,43.83319092,47.82565689,58.78262329,90.05240631,123.6092529,17.81999969,75.58300018,74.66005707,103.3236389,81.78668213,78.76999664,51.90526199,45.37706375,101.0605469,123.2714539,120.4584579,25.99754906,71.83956909
-6/30/15,22.40707016,28.82517815,212.8088837,15.65253353,63.36373138,49.67954254,21.6937809,58.08469391,67.2856369,16.09233093,341.4599915,67.5120697,31.56934929,52.18186951,31.64920044,13.32122231,135.855484,111.5814438,70.05734253,67.86000061,78.50126648,17.92252159,33.88396072,31.07999992,41.41500092,88.89923859,133.9100037,85.77999878,18.80583,51.31402206,115.9103012,91.96601105,26.71190453,123.3827133,213.9125366,53.07841492,69.62999725,30.25,94.35063934,81.69982147,55.89750671,37.34040833,190.8999939,23.67712975,42.54595184,30.15410233,54.543396,71.14515686,23.04073143,122.6440277,98.45967102,46.66536331,30.3406086,58.4478035,81.01000214,50.65000153,53.11985779,52.46259689,79.0872879,85.9503479,87.42689514,120.3499985,54.72171783,93.15530396,85.35237122,66.20999908,104.2099991,17.38209534,10.95191479,27.21938896,162.5431824,72.60791779,38.06000137,21.53305626,39.50669861,40.17753601,30.11268997,62.35045242,540.039978,194.8909302,25.19944954,41.71438217,43.8286438,45.44363022,57.72208405,104.668808,127.7692413,17.70000076,79.96956635,76.3181839,113.6344223,79.48459625,85.76999664,47.69550323,49.23071289,101.7887955,105.8185425,119.9401016,24.8152504,72.35973358
-7/31/15,22.33538055,28.54231644,202.3923492,15.90751171,64.30175018,51.45100784,15.94530678,64.20632935,71.18110657,15.7271452,337.6000061,68.86567688,28.88349342,53.64447784,34.62378693,13.34928608,156.2709503,116.2133408,70.24616241,55.99000168,77.9927063,11.34374332,35.48186874,30.29999924,43.43000031,94.71379089,140.9700012,88.56999969,19.3378067,50.32062149,112.09375,96.74001312,27.86901474,132.7373657,206.7354126,54.32925415,73.30000305,31.45999908,95.66407013,84.33444977,55.35335541,37.14490891,201.5899963,25.55715942,39.29933548,29.30657387,58.15008545,81.23512268,22.33464432,127.4624252,97.91338348,49.12409973,31.65815163,57.97966003,81.98999786,50.84000015,46.45650482,55.04273605,73.09077454,77.90498352,99.68015289,134.1399994,53.33132172,100.2128601,91.59513855,64.51000214,104.2799988,18.68694115,10.65503216,25.73306465,163.5161285,72.19159698,41.65999985,21.26855087,32.77375412,42.49809647,24.97615433,56.28135681,657.5,191.4185791,28.29308128,41.82902908,48.22198105,44.39523315,52.2774353,116.2412567,137.3893585,17.34000015,80.8298645,87.33569336,113.0755539,83.1174469,94.01000214,51.49707031,53.18790436,104.1175995,110.3486786,114.0772018,26.68710899,70.8142395
-8/31/15,21.16109085,32.47583389,181.500885,15.51362514,58.21995926,46.99180984,15.85243511,60.32513046,65.64208984,14.38814831,296.5499878,70.10998535,27.02408028,48.34326172,35.16722488,12.93767738,134.9404755,113.7832184,67.16710663,49.59000015,73.20529175,10.27212143,33.96169281,25.36000061,42.63499832,86.59363556,141.1399994,85.51000214,19.30980873,41.9740715,104.673584,92.98957062,26.51084518,128.293045,203.0179596,46.108284,69.36000061,29.98999977,88.70547485,81.34095001,49.71481705,34.49435043,196.9700012,24.89834785,34.25535583,27.92616081,55.38288879,79.70716095,21.06369019,116.2728958,92.88459015,47.90043259,30.35903358,52.52971268,78.56999969,46.93000031,40.90403366,59.30633926,70.59272003,71.55426788,93.71342468,121.4100037,49.38405228,91.24030304,86.34473419,61,116.1900024,19.4584198,9.989092827,24.0425663,143.6656647,69.97437286,38.81000137,18.87169456,31.08064079,39.86539078,22.61612892,58.53421783,647.8200073,176.651825,28.91350365,38.55714035,45.70651627,42.49435425,49.23986053,110.3117447,123.4466095,16.73999977,80.34771729,78.53221893,107.7664032,80.61513519,89.43000031,50.18411255,50.36998749,96.75738525,106.2142868,100.7565765,24.58720398,71.42871094
-9/30/15,21.11546135,33.01520538,166.4601593,15.03038788,58.31890106,43.47086716,14.94756603,57.0814476,61.11518478,12.9899168,284.7399902,67.01094055,23.08011436,47.43111801,36.45125198,12.08474064,122.9738388,104.7707443,67.98821259,40.25999832,73.23386383,9.354968071,34.95290375,24.29000092,43.30500031,90.25872803,139.3099976,83.93000031,17.6784687,41.22819138,102.3899918,92.30567932,25.97166634,132.4335938,195.3583984,40.62372208,69.43000031,28.36000061,84.12018585,83.18035889,46.73573303,33.59222794,181.7899933,26.76540756,27.60689545,24.97146225,58.84031296,81.17966461,23.44693184,116.5131226,88.19578552,47.36876678,28.83877182,52.62149811,82.22000122,46.18000031,38.9825592,62.87292862,65.84416199,69.8613739,99.835495,115.8000031,45.62505341,85.96549225,85.59015656,59.31999969,110.3300018,17.57258224,8.14943409,24.81786919,137.5727844,73.18412018,39.13000107,14.06851006,28.0758419,40.54324722,20.88671684,53.61166382,638.3699951,162.7519836,30.941082,36.72629547,47.39852142,43.98662949,44.26928329,112.8922958,120.5522079,16.40999985,81.06620789,75.40179443,108.5225601,82.7403717,89.90000153,54.487957,52.33102036,92.87046051,101.0913239,107.5599213,25.37684059,69.01732635
-10/31/15,21.11546135,33.01520538,166.4601593,15.03038788,58.31890106,43.47086716,14.94756603,57.0814476,61.11518478,12.9899168,284.7399902,67.01094055,23.08011436,47.43111801,36.45125198,12.08474064,122.9738388,104.7707443,67.98821259,40.25999832,73.23386383,9.354968071,34.95290375,24.29000092,43.30500031,90.25872803,139.3099976,83.93000031,17.6784687,41.22819138,102.3899918,92.30567932,25.97166634,132.4335938,195.3583984,40.62372208,69.43000031,28.36000061,84.12018585,83.18035889,46.73573303,33.59222794,181.7899933,26.76540756,27.60689545,24.97146225,58.84031296,81.17966461,23.44693184,116.5131226,88.19578552,47.36876678,28.83877182,52.62149811,82.22000122,46.18000031,38.9825592,62.87292862,65.84416199,69.8613739,99.835495,115.8000031,45.62505341,85.96549225,85.59015656,59.31999969,110.3300018,17.57258224,8.14943409,24.81786919,137.5727844,73.18412018,39.13000107,14.06851006,28.0758419,40.54324722,20.88671684,53.61166382,638.3699951,162.7519836,30.941082,36.72629547,47.39852142,43.98662949,44.26928329,112.8922958,120.5522079,16.40999985,81.06620789,75.40179443,108.5225601,82.7403717,89.90000153,54.487957,52.33102036,92.87046051,101.0913239,107.5599213,25.37684059,69.01732635
-11/30/15,25.58247566,28.26571274,172.5348511,14.32482719,52.92233276,46.6570282,17.12412262,54.14410019,68.78424835,13.63900089,342.7799988,72.99240875,20.02120972,55.73605347,43.96380997,13.63068295,143.9514618,112.4162445,63.15590668,51.29999924,80.07219696,7.927809238,37.41568375,29.57999992,48.11999893,99.54733276,120.7200012,93.30000305,18.2499485,50.07216263,110.2863541,106.1859512,26.3432579,148.2512512,183.2286835,30.93482208,79.69000244,29.48999977,90.2251358,88.3493576,55.30504227,36.38683319,190.7200012,27.70126152,34.98283768,23.28781319,62.52176285,84.38713837,21.3626194,130.2146912,91.90279388,49.52352142,29.32710266,59.56362534,91.45999908,50.08000183,40.13496017,65.99910736,71.6384964,80.96800232,114.0404587,103,46.24868774,84.12036896,88.98271942,57.29999924,114.2399979,21.65856552,8.391382217,29.92693901,151.4848785,78.55728149,40.34999847,11.84131908,34.29051208,50.12149811,18.00821495,61.26236725,762.8499756,178.5913391,31.35989952,38.92382813,53.8387413,51.96366501,50.68035507,118.3331757,136.4444275,18.28000069,87.58171082,76.5825882,105.4355316,78.26383209,104.2399979,51.28277969,56.70307922,97.85218048,123.9810486,113.0671692,26.35447693,66.95153046
-12/31/15,26.8158474,27.28581429,155.5276794,15.51644707,55.59673691,46.89155197,16.75507545,52.41654587,70.5765152,12.76554585,339.1300049,74.21672058,12.67358494,50.23448944,41.32410049,13.15936089,145.0505219,107.5554504,63.25173569,54.06999969,76.40296173,6.561280251,37.7141571,25.21999931,45.72999954,97.0219574,120.5999985,90.69999695,16.77791786,52.67303085,98.12966919,106.0621567,26.62859726,148.3247223,185.1016846,27.95503235,78.40000153,29.62999916,87.81570435,88.75508118,54.7746048,34.10857391,189.3899994,28.09038162,32.00911331,19.48024178,64.35243225,92.58094025,20.77049255,129.4447937,96.62651825,49.43778992,28.01875687,61.48082352,93.94000244,45.61000061,40.64264297,63.31148911,65.86252594,73.4305954,114.5001831,96.95999908,42.62368774,87.4104538,92.57375336,53.97000122,108.4499969,21.63951492,8.038590431,28.4125843,142.6022949,77.63143921,38.68999863,11.27607918,30.79319763,51.16359329,16.91796684,55.39425659,778.0100098,169.390152,28.6259613,36.73368073,52.93668747,49.00427628,45.34741592,119.4769897,140.0010834,18.44000053,87.06533813,77.61244202,110.5226898,80.94789124,104.6600037,51.56275558,55.44691086,95.21417999,120.1267395,101.9399948,27.34402084,64.99829102
-1/31/16,26.8158474,27.28581429,155.5276794,15.51644707,55.59673691,46.89155197,16.75507545,52.41654587,70.5765152,12.76554585,339.1300049,74.21672058,12.67358494,50.23448944,41.32410049,13.15936089,145.0505219,107.5554504,63.25173569,54.06999969,76.40296173,6.561280251,37.7141571,25.21999931,45.72999954,97.0219574,120.5999985,90.69999695,16.77791786,52.67303085,98.12966919,106.0621567,26.62859726,148.3247223,185.1016846,27.95503235,78.40000153,29.62999916,87.81570435,88.75508118,54.7746048,34.10857391,189.3899994,28.09038162,32.00911331,19.48024178,64.35243225,92.58094025,20.77049255,129.4447937,96.62651825,49.43778992,28.01875687,61.48082352,93.94000244,45.61000061,40.64264297,63.31148911,65.86252594,73.4305954,114.5001831,96.95999908,42.62368774,87.4104538,92.57375336,53.97000122,108.4499969,21.63951492,8.038590431,28.4125843,142.6022949,77.63143921,38.68999863,11.27607918,30.79319763,51.16359329,16.91796684,55.39425659,778.0100098,169.390152,28.6259613,36.73368073,52.93668747,49.00427628,45.34741592,119.4769897,140.0010834,18.44000053,87.06533813,77.61244202,110.5226898,80.94789124,104.6600037,51.56275558,55.44691086,95.21417999,120.1267395,101.9399948,27.34402084,64.99829102
-2/29/16,23.64028931,29.02422142,135.0158844,15.96675396,60.16782379,44.57450104,24.05690193,54.82475281,71.00775909,12.74058151,314.9100037,74.25964355,15.63035679,53.52879333,40.25884628,10.7556076,128.0188446,109.5063324,68.90608978,45.06999969,80.19243622,7.394765377,37.86341095,24.64999962,47.81499863,93.08538818,113.9300003,82.40000153,16.18476486,52.8705101,90.62934113,99.88147736,28.39893913,138.1640472,199.3565216,34.53222275,67.75,27.60000038,91.06692505,86.88972473,41.42346191,34.48358536,179.7299957,28.79820442,30.79026031,19.47673798,58.75245667,68.3791275,22.59300804,106.7801743,81.01863861,50.85251236,24.83082962,55.34971619,85.15000153,44.75,30.84708023,67.9731369,60.36500168,68.45993805,114.4909286,96.16999817,41.38879013,87.26416779,101.2899323,46.25999832,73.5,18.02975464,8.331839561,24.59471512,131.0114594,77.60396576,34.63000107,10.48128891,27.67160416,47.25836945,19.27131271,56.48165894,717.2199707,141.1472015,28.25642586,35.75567245,56.4884758,47.76208115,49.41682816,100.0703964,127.5061035,16.97999954,80.31430817,72.28131866,111.8943481,82.95213318,106.9199982,59.35683823,53.94156265,84.63775635,124.1136093,82.99313354,30.03297234,52.16990662
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-8/31/18,88.86766815,76.34365082,143.6633759,26.41962814,93.44718933,65.85691071,29.42657661,83.78227997,93.4256134,20.10204124,584.460022,108.068718,16.46951103,109.6061859,60.29633331,13.30342865,192.5683899,160.5797729,84.10103607,39.13000107,95.49878693,13.69413757,42.5006752,25.63999939,80.06999969,164.8144073,61.68999863,149.7599945,27.36355782,92.92978668,222.9515839,131.826828,35.45421982,229.8304138,344.0355835,33.01755142,152.6799927,34.52000046,143.5174408,107.0401382,90.79820251,47.36307144,191.5899963,27.48413277,72.09928131,60.98164749,64.77236176,118.1615982,32.41106033,333.529541,87.86965179,43.32273102,30.44654846,57.75475311,263.5100098,102.1399994,42.80514526,125.3749924,96.51681519,105.1502075,193.6302795,189.1199951,76.95734406,71.76994324,165.0478973,78.05000305,73.91000366,28.21082687,12.82623768,33.86655426,238.7618713,142.3084564,39.75999832,34.96694183,28.78144646,110.2171326,23.21758842,73.16490173,1231.800049,232.0666351,25.48573494,69.9587326,73.96214294,107.6231155,79.59928894,128.6785431,238.137619,35.56000137,208.9283447,66.1071701,262.2696533,97.6646347,175.7299957,62.19913483,51.94258118,175.6986084,239.5334015,128.2601318,40.9994278,103.7132568
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diff --git a/.ipynb_checkpoints/portfolio-checkpoint.csv b/.ipynb_checkpoints/portfolio-checkpoint.csv
index c5b695a..1f9f196 100644
--- a/.ipynb_checkpoints/portfolio-checkpoint.csv
+++ b/.ipynb_checkpoints/portfolio-checkpoint.csv
@@ -1,7 +1,7 @@
 ticker,name,sector,sharpe ratio,FFM returns,P/E ratio,EPS,beta,mkt cap,shares
 GPC,Genuine Parts,Consumer Discretionary,2.9244641954801547,0.074228025,17.71,5.45,0.89,14016415887,145293000
 GIS,General Mills,Consumer Staples,2.6412807761987938,0.063146888,15.34,3.48,0.73,32242795100,604817000
-COG,Cabot Oil & Gas,Energy,1.9529827367707384,-0.050016632000000005,7.8,1.9,0.47,6037284157,407925000
+OKE,ONEOK,Energy,0.9173258155980414,0.230147782,25.56,3.01,1.11,31799253894,413085000
 SYF,Synchrony Financial,Financials,2.4933359586834767,0.091836098,6.07,5.56,1.21,20704848750,613477000
 AMGN,Amgen Inc,Health Care,1.8616491950461436,0.151748658,17.36,12.88,1.12,131810065840,589807000
 LUV,Southwest Airlines,Industrials,1.7265757683369565,0.10783286199999999,13.77,4.21,1.47,29987649751,517296000
diff --git a/.ipynb_checkpoints/stock_data-checkpoint.csv b/.ipynb_checkpoints/stock_data-checkpoint.csv
new file mode 100644
index 0000000..de82bbf
--- /dev/null
+++ b/.ipynb_checkpoints/stock_data-checkpoint.csv
@@ -0,0 +1,101 @@
+Stock,pe,eps,beta,marketcap,shares
+DXC,#N/A,-6.26,#N/A,7819681142,253721000
+BBY,15.98,5.64,1.12,23344272933,258777000
+AMG,267.18,0.31,1.69,4084648875,49272000
+CNP,21.58,1.26,0.44,13650929559,502242000
+WMT,23.55,5.00,0.36,334474559018,2837175000
+MRK,21.52,3.84,0.57,210425581484,2545984000
+NEM,15.83,2.78,0.16,36130286851,819839000
+VFC,25.99,3.22,1.20,33022293377,394720000
+MDT,33.97,3.45,0.60,157266553194,1340378000
+HST,10.89,1.55,1.17,12127479870,717178000
+MTD,33.97,22.47,1.39,18357249893,24053000
+CCI,83.64,1.98,0.30,69005081855,415768000
+KMI,22.87,0.96,0.81,49831386000,2265063000
+RMD,56.31,3.14,0.48,25539363082,144617000
+LUV,13.77,4.21,1.47,29987649751,517296000
+NWS,#N/A,-0.31,1.45,8671670226,199630000
+AMGN,17.36,12.88,1.12,131810065840,589807000
+APD,30.09,8.51,0.86,56495776935,220678000
+TGT,18.64,6.26,0.56,59100734918,506737000
+MYL,239.58,0.09,1.72,11303303743,516177000
+GPC,17.71,5.45,0.89,14016415887,145293000
+FCX,78.35,0.16,2.42,17759187027,1450914000
+KO,28.99,2.07,0.41,256586003265,4280000000
+DISCK,11.10,2.59,1.45,15392873644,360664000
+FISV,71.58,1.71,0.80,83164756192,679895000
+ACN,28.34,7.49,1.03,139515576338,656946000
+SRCL,#N/A,-4.91,1.31,5875914401,91128000
+IT,59.34,2.57,1.21,13633532057,89453000
+PHM,12.77,3.66,0.56,12605132379,269975000
+ALB,16.67,5.38,1.57,9504798055,106033000
+AAPL,25.66,12.66,1.29,1421812279411,4375480000
+EFX,#N/A,-3.30,1.22,19750752813,121200000
+FE,31.45,1.66,0.20,28241486749,540714000
+COST,37.75,8.43,0.90,140615987901,441758000
+GWW,17.94,17.15,0.97,16517112872,53688000
+M,5.39,3.09,0.66,5150446573,308965000
+CRM,200.68,0.95,1.19,168485647293,887000000
+LKQ,23.73,1.40,1.30,10174538633,306462000
+AON,37.00,6.37,0.83,54701475530,234137000
+PEP,28.31,5.19,0.53,204968008309,1389545000
+RJF,13.44,7.36,1.50,13782151374,139284000
+ORCL,17.61,3.15,1.11,177928293945,3207649000
+MHK,13.40,10.30,1.36,9882403253,71622000
+PPL,14.38,2.46,0.51,25573676437,723033000
+FMC,27.41,3.85,1.54,13670494208,129615000
+OKE,25.56,3.01,1.11,31799253894,413085000
+EQR,34.53,2.50,0.45,32134657027,371671000
+RCL,12.55,9.02,1.44,23627921924,208801000
+IRM,35.67,0.93,0.53,9521121824,287300000
+BA,#N/A,-1.12,1.28,191747618980,563152000
+ABC,30.62,3.08,1.01,19427969245,205892000
+GIS,15.34,3.48,0.73,32242795100,604817000
+SYF,6.07,5.56,1.21,20704848750,613477000
+BMY,33.05,2.01,0.76,155607591281,2344185000
+ADBE,63.17,6.01,1.09,185174936969,487726000
+SNPS,47.31,3.45,1.18,24589893168,150535000
+BWA,9.20,3.71,1.91,7048901814,206410000
+MSI,37.31,4.94,0.50,31596072387,171336000
+COF,9.31,11.02,1.25,46865423721,456600000
+LYB,8.65,9.55,1.45,27505799491,333000000
+RTN,19.05,11.93,0.85,63256224340,278441000
+FFIV,19.49,6.54,0.98,7753118169,60804000
+HLT,37.27,3.04,1.14,31415437971,277448000
+CVS,14.05,5.08,0.93,92849804253,1300964000
+NEE,34.73,8.02,0.15,136133886150,488776000
+KMX,19.16,5.16,1.10,16144071451,163385000
+INCY,38.21,2.05,1.06,17006076538,216776000
+MGM,#N/A,0.00,1.50,15575639746,494151000
+AES,27.44,0.76,1.05,13895280692,663893000
+GM,7.60,4.57,1.38,49672072361,1429002000
+FDX,583.74,0.27,1.71,41418694505,261119000
+ADP,32.04,5.66,0.87,78255412500,431754000
+HOLX,173.01,0.31,0.85,13960272160,263302000
+NRG,10.31,3.89,0.71,10078855985,251594000
+NBL,#N/A,-3.16,1.55,9168232366,478509000
+MSFT,32.28,5.74,1.15,1409780857873,7606047000
+COG,7.80,1.90,0.47,6037284157,407925000
+OXY,29.53,1.41,0.90,37161985836,893317000
+GOOGL,30.89,49.16,1.02,1044236513876,299895000
+GS,11.27,21.03,1.32,83946946608,354087000
+HRB,11.75,1.90,0.23,4369605316,195246000
+AJG,31.03,3.52,0.76,20549043209,188247000
+CINF,9.52,12.10,0.57,18822318390,163374000
+TXN,25.24,5.24,1.24,123223956977,932032000
+ETN,19.71,5.25,1.42,42807571261,413400000
+EXPE,32.58,3.77,1.01,17792025802,139363000
+TMO,36.98,9.17,1.14,136012138268,400991000
+BSX,12.70,3.33,0.87,58972695354,1393824000
+CTAS,35.38,8.51,0.99,31216601386,103751000
+WBA,13.00,4.07,0.92,46817805348,885862000
+UNH,20.86,14.33,0.69,283068652543,947415000
+HSY,29.33,5.47,0.02,23779704176,148308000
+FB,33.32,6.43,1.05,610509360122,2405746000
+EIX,#N/A,-0.99,0.13,27662480921,358601000
+SBUX,29.15,3.06,0.56,104787934567,1173700000
+MCO,37.43,7.42,1.21,52148688479,187700000
+HII,18.57,13.26,1.24,10035519873,40760000
+RL,14.16,8.61,0.90,8984857815,48862000
+LNT,26.79,2.23,0.23,14358652779,244628000
+AXP,17.01,7.99,0.99,111178449600,808041000
\ No newline at end of file
diff --git a/data_cleaning.ipynb b/data_cleaning.ipynb
index 4994ae3..ab74772 100644
--- a/data_cleaning.ipynb
+++ b/data_cleaning.ipynb
@@ -2,9 +2,18 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/anaconda3/lib/python3.7/site-packages/pandas_datareader/compat/__init__.py:7: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
+      "  from pandas.util.testing import assert_frame_equal\n"
+     ]
+    }
+   ],
    "source": [
     "import pandas as pd\n",
     "from pathlib import Path\n",
@@ -20,7 +29,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -138,7 +147,7 @@
        "[505 rows x 3 columns]"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -151,7 +160,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -260,7 +269,7 @@
        "Utilities                       28    28"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -272,7 +281,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -281,7 +290,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -290,7 +299,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -328,115 +337,115 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "['GGP',\n",
-       " 'TPR',\n",
+       "['IBM',\n",
+       " 'ZION',\n",
+       " 'LRCX',\n",
+       " 'IVZ',\n",
+       " 'BWA',\n",
+       " 'MTB',\n",
        " 'MDLZ',\n",
-       " 'FE',\n",
-       " 'XYL',\n",
-       " 'URI',\n",
-       " 'LYB',\n",
-       " 'AMD',\n",
+       " 'ADP',\n",
+       " 'SLG',\n",
        " 'HPQ',\n",
-       " 'AMGN',\n",
-       " 'ECL',\n",
-       " 'KORS',\n",
-       " 'CMS',\n",
-       " 'UDR',\n",
-       " 'ALLE',\n",
-       " 'UPS',\n",
-       " 'HSY',\n",
-       " 'MKC',\n",
-       " 'LNT',\n",
-       " 'INTU',\n",
-       " 'ANSS',\n",
-       " 'PRU',\n",
-       " 'COL',\n",
-       " 'CLX',\n",
-       " 'PLD',\n",
-       " 'IP',\n",
-       " 'AYI',\n",
-       " 'UTX',\n",
-       " 'IFF',\n",
-       " 'PNW',\n",
-       " 'NWSA',\n",
-       " 'LEG',\n",
-       " 'STX',\n",
-       " 'MET',\n",
-       " 'LOW',\n",
-       " 'NWS',\n",
-       " 'ZTS',\n",
-       " 'SPGI',\n",
-       " 'GILD',\n",
-       " 'PBCT',\n",
-       " 'LUV',\n",
-       " 'EL',\n",
-       " 'NTAP',\n",
-       " 'TMO',\n",
-       " 'NOV',\n",
-       " 'RCL',\n",
-       " 'TWX',\n",
-       " 'LLY',\n",
-       " 'UNP',\n",
+       " 'MNST',\n",
+       " 'DAL',\n",
+       " 'URI',\n",
+       " 'KSU',\n",
+       " 'HRS',\n",
+       " 'TROW',\n",
+       " 'HES',\n",
+       " 'SRE',\n",
+       " 'DVN',\n",
+       " 'MPC',\n",
+       " 'FFIV',\n",
+       " 'MAC',\n",
+       " 'UNM',\n",
+       " 'HRL',\n",
+       " 'CCL',\n",
+       " 'SRCL',\n",
        " 'DWDP',\n",
-       " 'MTD',\n",
-       " 'ADI',\n",
-       " 'BMY',\n",
-       " 'AAP',\n",
-       " 'FIS',\n",
-       " 'PRGO',\n",
-       " 'MMC',\n",
-       " 'CNC',\n",
-       " 'CHRW',\n",
-       " 'NRG',\n",
-       " 'ABC',\n",
-       " 'ORLY',\n",
-       " 'UA',\n",
+       " 'PEP',\n",
+       " 'SYK',\n",
+       " 'IQV',\n",
+       " 'SBUX',\n",
+       " 'CMCSA',\n",
+       " 'YUM',\n",
        " 'AXP',\n",
+       " 'NCLH',\n",
+       " 'NBL',\n",
+       " 'CLX',\n",
+       " 'ABBV',\n",
+       " 'BLL',\n",
+       " 'HIG',\n",
+       " 'ETR',\n",
+       " 'PGR',\n",
+       " 'UNH',\n",
        " 'IDXX',\n",
-       " 'DLR',\n",
-       " 'APTV',\n",
-       " 'TAP',\n",
+       " 'TSS',\n",
+       " 'CINF',\n",
+       " 'JWN',\n",
+       " 'NEE',\n",
+       " 'CSCO',\n",
+       " 'HON',\n",
+       " 'BF.B',\n",
+       " 'AAP',\n",
+       " 'GRMN',\n",
+       " 'IFF',\n",
+       " 'EQIX',\n",
+       " 'XOM',\n",
+       " 'TSCO',\n",
        " 'KR',\n",
-       " 'DISCK',\n",
-       " 'HBAN',\n",
-       " 'CI',\n",
-       " 'CCL',\n",
-       " 'AGN',\n",
-       " 'GE',\n",
-       " 'GIS',\n",
-       " 'ILMN',\n",
-       " 'HRS',\n",
-       " 'BBT',\n",
-       " 'DUK',\n",
-       " 'NVDA',\n",
+       " 'EVHC',\n",
+       " 'XEC',\n",
        " 'FMC',\n",
-       " 'NTRS',\n",
+       " 'PAYX',\n",
+       " 'MAA',\n",
+       " 'ESS',\n",
        " 'COF',\n",
-       " 'SNI',\n",
-       " 'JNPR',\n",
-       " 'PCLN',\n",
-       " 'XRX',\n",
-       " 'MPC',\n",
-       " 'AJG',\n",
-       " 'VFC',\n",
-       " 'LMT',\n",
-       " 'CME',\n",
-       " 'FTI',\n",
+       " 'MCHP',\n",
+       " 'PFE',\n",
+       " 'ADSK',\n",
+       " 'WRK',\n",
+       " 'EXC',\n",
+       " 'APH',\n",
+       " 'GS',\n",
+       " 'CERN',\n",
+       " 'WBA',\n",
        " 'AMP',\n",
-       " 'WYNN',\n",
-       " 'CSCO',\n",
-       " 'UAL',\n",
-       " 'SRCL',\n",
-       " 'TIF']"
+       " 'CHTR',\n",
+       " 'LLY',\n",
+       " 'CHRW',\n",
+       " 'DFS',\n",
+       " 'WU',\n",
+       " 'MSI',\n",
+       " 'LB',\n",
+       " 'TRV',\n",
+       " 'PM',\n",
+       " 'DXC',\n",
+       " 'AMD',\n",
+       " 'QCOM',\n",
+       " 'PCLN',\n",
+       " 'DOV',\n",
+       " 'VAR',\n",
+       " 'PCAR',\n",
+       " 'EBAY',\n",
+       " 'VNO',\n",
+       " 'MCO',\n",
+       " 'ALK',\n",
+       " 'SBAC',\n",
+       " 'AGN',\n",
+       " 'DISCA',\n",
+       " 'FDX',\n",
+       " 'MGM']"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -448,7 +457,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -457,7 +466,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -473,7 +482,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -488,7 +497,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -503,7 +512,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -518,7 +527,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -533,7 +542,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -548,7 +557,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -563,7 +572,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -578,7 +587,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -593,9 +602,412 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>DXC</th>\n",
+       "      <th>BBY</th>\n",
+       "      <th>AMG</th>\n",
+       "      <th>CNP</th>\n",
+       "      <th>WMT</th>\n",
+       "      <th>MRK</th>\n",
+       "      <th>NEM</th>\n",
+       "      <th>VFC</th>\n",
+       "      <th>MDT</th>\n",
+       "      <th>HST</th>\n",
+       "      <th>...</th>\n",
+       "      <th>UNH</th>\n",
+       "      <th>HSY</th>\n",
+       "      <th>FB</th>\n",
+       "      <th>EIX</th>\n",
+       "      <th>SBUX</th>\n",
+       "      <th>MCO</th>\n",
+       "      <th>HII</th>\n",
+       "      <th>RL</th>\n",
+       "      <th>LNT</th>\n",
+       "      <th>AXP</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2015-01-02</th>\n",
+       "      <td>21.286510</td>\n",
+       "      <td>33.869621</td>\n",
+       "      <td>204.065598</td>\n",
+       "      <td>18.782833</td>\n",
+       "      <td>75.800331</td>\n",
+       "      <td>49.132111</td>\n",
+       "      <td>17.923134</td>\n",
+       "      <td>60.863708</td>\n",
+       "      <td>64.685036</td>\n",
+       "      <td>18.943111</td>\n",
+       "      <td>...</td>\n",
+       "      <td>93.161888</td>\n",
+       "      <td>91.816597</td>\n",
+       "      <td>78.449997</td>\n",
+       "      <td>55.423393</td>\n",
+       "      <td>37.132599</td>\n",
+       "      <td>89.816803</td>\n",
+       "      <td>104.540627</td>\n",
+       "      <td>164.706375</td>\n",
+       "      <td>28.115042</td>\n",
+       "      <td>85.741974</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-05</th>\n",
+       "      <td>20.855738</td>\n",
+       "      <td>32.996471</td>\n",
+       "      <td>196.666382</td>\n",
+       "      <td>18.186682</td>\n",
+       "      <td>75.579727</td>\n",
+       "      <td>49.862339</td>\n",
+       "      <td>18.034346</td>\n",
+       "      <td>60.352108</td>\n",
+       "      <td>64.415070</td>\n",
+       "      <td>18.791948</td>\n",
+       "      <td>...</td>\n",
+       "      <td>91.627373</td>\n",
+       "      <td>91.170326</td>\n",
+       "      <td>77.190002</td>\n",
+       "      <td>55.288025</td>\n",
+       "      <td>36.421303</td>\n",
+       "      <td>88.055870</td>\n",
+       "      <td>102.971252</td>\n",
+       "      <td>160.010773</td>\n",
+       "      <td>27.772594</td>\n",
+       "      <td>83.474472</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-06</th>\n",
+       "      <td>20.909586</td>\n",
+       "      <td>32.699589</td>\n",
+       "      <td>192.428558</td>\n",
+       "      <td>17.781296</td>\n",
+       "      <td>76.162109</td>\n",
+       "      <td>51.821095</td>\n",
+       "      <td>18.785009</td>\n",
+       "      <td>59.997307</td>\n",
+       "      <td>64.091087</td>\n",
+       "      <td>18.712391</td>\n",
+       "      <td>...</td>\n",
+       "      <td>91.442474</td>\n",
+       "      <td>91.471321</td>\n",
+       "      <td>76.150002</td>\n",
+       "      <td>55.499523</td>\n",
+       "      <td>36.124943</td>\n",
+       "      <td>87.128571</td>\n",
+       "      <td>106.754547</td>\n",
+       "      <td>156.889389</td>\n",
+       "      <td>27.683804</td>\n",
+       "      <td>81.695465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-07</th>\n",
+       "      <td>21.061031</td>\n",
+       "      <td>33.642605</td>\n",
+       "      <td>197.151260</td>\n",
+       "      <td>18.011810</td>\n",
+       "      <td>78.182854</td>\n",
+       "      <td>52.929340</td>\n",
+       "      <td>18.618195</td>\n",
+       "      <td>60.764694</td>\n",
+       "      <td>65.692909</td>\n",
+       "      <td>18.815811</td>\n",
+       "      <td>...</td>\n",
+       "      <td>92.376137</td>\n",
+       "      <td>93.082603</td>\n",
+       "      <td>76.150002</td>\n",
+       "      <td>56.430172</td>\n",
+       "      <td>37.014053</td>\n",
+       "      <td>88.458626</td>\n",
+       "      <td>106.567703</td>\n",
+       "      <td>160.820389</td>\n",
+       "      <td>28.140408</td>\n",
+       "      <td>83.479713</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-08</th>\n",
+       "      <td>21.299976</td>\n",
+       "      <td>34.149033</td>\n",
+       "      <td>199.158630</td>\n",
+       "      <td>18.441044</td>\n",
+       "      <td>79.833008</td>\n",
+       "      <td>53.994629</td>\n",
+       "      <td>18.516251</td>\n",
+       "      <td>62.134457</td>\n",
+       "      <td>67.267754</td>\n",
+       "      <td>19.014713</td>\n",
+       "      <td>...</td>\n",
+       "      <td>96.785576</td>\n",
+       "      <td>94.879814</td>\n",
+       "      <td>78.180000</td>\n",
+       "      <td>56.743195</td>\n",
+       "      <td>37.611340</td>\n",
+       "      <td>89.320381</td>\n",
+       "      <td>109.986694</td>\n",
+       "      <td>160.631485</td>\n",
+       "      <td>28.584330</td>\n",
+       "      <td>84.663033</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-06</th>\n",
+       "      <td>35.330002</td>\n",
+       "      <td>87.910004</td>\n",
+       "      <td>83.008774</td>\n",
+       "      <td>26.463535</td>\n",
+       "      <td>117.650002</td>\n",
+       "      <td>91.639999</td>\n",
+       "      <td>43.259998</td>\n",
+       "      <td>99.209999</td>\n",
+       "      <td>114.889999</td>\n",
+       "      <td>17.570000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>291.549988</td>\n",
+       "      <td>144.570007</td>\n",
+       "      <td>212.600006</td>\n",
+       "      <td>75.129997</td>\n",
+       "      <td>87.721161</td>\n",
+       "      <td>241.869995</td>\n",
+       "      <td>265.000000</td>\n",
+       "      <td>119.809998</td>\n",
+       "      <td>53.404282</td>\n",
+       "      <td>124.059998</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-07</th>\n",
+       "      <td>35.849998</td>\n",
+       "      <td>88.410004</td>\n",
+       "      <td>82.072395</td>\n",
+       "      <td>26.582251</td>\n",
+       "      <td>116.559998</td>\n",
+       "      <td>89.199997</td>\n",
+       "      <td>43.230000</td>\n",
+       "      <td>98.720001</td>\n",
+       "      <td>114.489998</td>\n",
+       "      <td>17.520000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>289.790009</td>\n",
+       "      <td>144.850006</td>\n",
+       "      <td>213.059998</td>\n",
+       "      <td>75.860001</td>\n",
+       "      <td>87.452415</td>\n",
+       "      <td>241.000000</td>\n",
+       "      <td>267.459991</td>\n",
+       "      <td>120.330002</td>\n",
+       "      <td>53.453960</td>\n",
+       "      <td>123.410004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-08</th>\n",
+       "      <td>36.459999</td>\n",
+       "      <td>88.650002</td>\n",
+       "      <td>82.211853</td>\n",
+       "      <td>26.354712</td>\n",
+       "      <td>116.160004</td>\n",
+       "      <td>88.599998</td>\n",
+       "      <td>42.080002</td>\n",
+       "      <td>97.040001</td>\n",
+       "      <td>116.500000</td>\n",
+       "      <td>17.639999</td>\n",
+       "      <td>...</td>\n",
+       "      <td>295.899994</td>\n",
+       "      <td>146.039993</td>\n",
+       "      <td>215.220001</td>\n",
+       "      <td>75.739998</td>\n",
+       "      <td>88.467682</td>\n",
+       "      <td>245.619995</td>\n",
+       "      <td>268.959991</td>\n",
+       "      <td>120.000000</td>\n",
+       "      <td>53.573189</td>\n",
+       "      <td>125.540001</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-09</th>\n",
+       "      <td>36.220001</td>\n",
+       "      <td>89.370003</td>\n",
+       "      <td>82.610313</td>\n",
+       "      <td>26.166748</td>\n",
+       "      <td>117.360001</td>\n",
+       "      <td>89.379997</td>\n",
+       "      <td>41.660000</td>\n",
+       "      <td>95.779999</td>\n",
+       "      <td>118.389999</td>\n",
+       "      <td>17.430000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>294.220001</td>\n",
+       "      <td>146.570007</td>\n",
+       "      <td>218.300003</td>\n",
+       "      <td>76.139999</td>\n",
+       "      <td>90.110031</td>\n",
+       "      <td>248.850006</td>\n",
+       "      <td>276.010010</td>\n",
+       "      <td>117.930000</td>\n",
+       "      <td>54.179264</td>\n",
+       "      <td>127.809998</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-10</th>\n",
+       "      <td>35.740002</td>\n",
+       "      <td>90.650002</td>\n",
+       "      <td>82.610313</td>\n",
+       "      <td>26.018353</td>\n",
+       "      <td>116.379997</td>\n",
+       "      <td>89.529999</td>\n",
+       "      <td>42.270000</td>\n",
+       "      <td>95.059998</td>\n",
+       "      <td>118.639999</td>\n",
+       "      <td>17.520000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>295.130005</td>\n",
+       "      <td>148.130005</td>\n",
+       "      <td>218.059998</td>\n",
+       "      <td>75.500000</td>\n",
+       "      <td>89.741745</td>\n",
+       "      <td>248.029999</td>\n",
+       "      <td>270.940002</td>\n",
+       "      <td>117.959999</td>\n",
+       "      <td>54.715794</td>\n",
+       "      <td>127.279999</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1265 rows × 100 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  DXC        BBY         AMG        CNP         WMT  \\\n",
+       "Date                                                                  \n",
+       "2015-01-02  21.286510  33.869621  204.065598  18.782833   75.800331   \n",
+       "2015-01-05  20.855738  32.996471  196.666382  18.186682   75.579727   \n",
+       "2015-01-06  20.909586  32.699589  192.428558  17.781296   76.162109   \n",
+       "2015-01-07  21.061031  33.642605  197.151260  18.011810   78.182854   \n",
+       "2015-01-08  21.299976  34.149033  199.158630  18.441044   79.833008   \n",
+       "...               ...        ...         ...        ...         ...   \n",
+       "2020-01-06  35.330002  87.910004   83.008774  26.463535  117.650002   \n",
+       "2020-01-07  35.849998  88.410004   82.072395  26.582251  116.559998   \n",
+       "2020-01-08  36.459999  88.650002   82.211853  26.354712  116.160004   \n",
+       "2020-01-09  36.220001  89.370003   82.610313  26.166748  117.360001   \n",
+       "2020-01-10  35.740002  90.650002   82.610313  26.018353  116.379997   \n",
+       "\n",
+       "                  MRK        NEM        VFC         MDT        HST  ...  \\\n",
+       "Date                                                                ...   \n",
+       "2015-01-02  49.132111  17.923134  60.863708   64.685036  18.943111  ...   \n",
+       "2015-01-05  49.862339  18.034346  60.352108   64.415070  18.791948  ...   \n",
+       "2015-01-06  51.821095  18.785009  59.997307   64.091087  18.712391  ...   \n",
+       "2015-01-07  52.929340  18.618195  60.764694   65.692909  18.815811  ...   \n",
+       "2015-01-08  53.994629  18.516251  62.134457   67.267754  19.014713  ...   \n",
+       "...               ...        ...        ...         ...        ...  ...   \n",
+       "2020-01-06  91.639999  43.259998  99.209999  114.889999  17.570000  ...   \n",
+       "2020-01-07  89.199997  43.230000  98.720001  114.489998  17.520000  ...   \n",
+       "2020-01-08  88.599998  42.080002  97.040001  116.500000  17.639999  ...   \n",
+       "2020-01-09  89.379997  41.660000  95.779999  118.389999  17.430000  ...   \n",
+       "2020-01-10  89.529999  42.270000  95.059998  118.639999  17.520000  ...   \n",
+       "\n",
+       "                   UNH         HSY          FB        EIX       SBUX  \\\n",
+       "Date                                                                   \n",
+       "2015-01-02   93.161888   91.816597   78.449997  55.423393  37.132599   \n",
+       "2015-01-05   91.627373   91.170326   77.190002  55.288025  36.421303   \n",
+       "2015-01-06   91.442474   91.471321   76.150002  55.499523  36.124943   \n",
+       "2015-01-07   92.376137   93.082603   76.150002  56.430172  37.014053   \n",
+       "2015-01-08   96.785576   94.879814   78.180000  56.743195  37.611340   \n",
+       "...                ...         ...         ...        ...        ...   \n",
+       "2020-01-06  291.549988  144.570007  212.600006  75.129997  87.721161   \n",
+       "2020-01-07  289.790009  144.850006  213.059998  75.860001  87.452415   \n",
+       "2020-01-08  295.899994  146.039993  215.220001  75.739998  88.467682   \n",
+       "2020-01-09  294.220001  146.570007  218.300003  76.139999  90.110031   \n",
+       "2020-01-10  295.130005  148.130005  218.059998  75.500000  89.741745   \n",
+       "\n",
+       "                   MCO         HII          RL        LNT         AXP  \n",
+       "Date                                                                   \n",
+       "2015-01-02   89.816803  104.540627  164.706375  28.115042   85.741974  \n",
+       "2015-01-05   88.055870  102.971252  160.010773  27.772594   83.474472  \n",
+       "2015-01-06   87.128571  106.754547  156.889389  27.683804   81.695465  \n",
+       "2015-01-07   88.458626  106.567703  160.820389  28.140408   83.479713  \n",
+       "2015-01-08   89.320381  109.986694  160.631485  28.584330   84.663033  \n",
+       "...                ...         ...         ...        ...         ...  \n",
+       "2020-01-06  241.869995  265.000000  119.809998  53.404282  124.059998  \n",
+       "2020-01-07  241.000000  267.459991  120.330002  53.453960  123.410004  \n",
+       "2020-01-08  245.619995  268.959991  120.000000  53.573189  125.540001  \n",
+       "2020-01-09  248.850006  276.010010  117.930000  54.179264  127.809998  \n",
+       "2020-01-10  248.029999  270.940002  117.959999  54.715794  127.279999  \n",
+       "\n",
+       "[1265 rows x 100 columns]"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "combined_df_1 = pd.concat([stocks_df1,stocks_df3,stocks_df4,stocks_df5,stocks_df6,stocks_df7,stocks_df8,stocks_df9], axis = 'columns', join='inner')\n",
     "#combined_df_1.reset_index(inplace = True)\n",
@@ -604,7 +1016,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -613,44 +1025,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "NameError",
-     "evalue": "name 'combined_monthly' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-2-05da0d445a5d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdaily_returns\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcombined_monthly\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpct_change\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m: name 'combined_monthly' is not defined"
-     ]
-    }
-   ],
-   "source": [
-    "daily_returns = combined_monthly.pct_change()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
-    "combined_monthly.to_clipboard()"
+    "daily_returns = combined_monthly.pct_change()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -670,7 +1054,7 @@
        "Length: 100, dtype: float64"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -681,12 +1065,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
     "combined_monthly.dropna(inplace = True)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# printing the dataset to csv \n",
+    "output = 'monthly_data.csv'\n",
+    "\n",
+    "with open(output, 'w') as file:\n",
+    "    file.write(combined_monthly.to_csv(index=False))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/monthly_data.csv b/monthly_data.csv
index 3177c1c..375688e 100644
--- a/monthly_data.csv
+++ b/monthly_data.csv
@@ -1,60 +1,59 @@
-Date,DXC,BBY,AMG,CNP,WMT,MRK,NEM,VFC,MDT,HST,MTD,CCI,KMI,RMD,LUV,NWS,AMGN,APD,TGT,MYL,GPC,FCX,KO,DISCK,FISV,ACN,SRCL,IT,PHM,ALB,AAPL,EFX,FE,COST,GWW,M,CRM,LKQ,AON,PEP,RJF,ORCL,MHK,PPL,FMC,OKE,EQR,RCL,IRM,BA,ABC,GIS,SYF,BMY,ADBE,SNPS,BWA,MSI,COF,LYB,RTN,FFIV,HLT,CVS,NEE,KMX,INCY,MGM,AES,GM,FDX,ADP,HOLX,NRG,NBL,MSFT,COG,OXY,GOOGL,GS,HRB,AJG,CINF,TXN,ETN,EXPE,TMO,BSX,CTAS,WBA,UNH,HSY,FB,EIX,SBUX,MCO,HII,RL,LNT,AXP
-2/27/2015,23.86782265,33.26713562,210.6866455,16.88897324,74.06195831,50.29189301,24.40104866,63.25667191,69.82347107,16.70748901,314.1700134,71.15853882,33.35688019,59.28459167,41.21752548,15.73475933,138.887619,125.8181381,65.50121307,57.33000183,83.13213348,20.76288414,36.78805923,30.51000023,39.03499985,80.93172455,134.9700012,83.11000061,20.8873291,51.99001694,118.2165375,87.91251373,28.42409897,133.887558,213.1294556,49.62020493,69.37999725,24.57999992,94.70365906,85.42989349,53.2719841,40.46008301,184.3500061,24.90868378,50.98762131,33.38389206,59.00678635,68.53813171,26.56648827,132.5190582,94.90358734,44.69554138,29.43766594,53.20431137,79.09999847,46.40999985,57.31464005,61.4779892,70.41978455,70.780159,98.10521698,118.1200027,56.15182877,91.93980408,89.39362335,67.11000061,85.84999847,20.69659615,10.63154316,29.91179276,168.3940277,79.46625519,32.38000107,22.44052124,43.55839539,39.64686203,27.67150116,61.27190018,562.6300049,176.6049194,28.65096474,40.80010986,45.27275848,51.55763626,59.7765007,87.50965881,127.7081833,16.89999962,78.92019653,74.79510498,105.040535,92.33921814,78.97000122,54.35739136,42.78238678,91.11618042,132.0232697,123.6062775,27.10185242,75.4275589
-3/31/2015,22.12887955,33.17991257,209.0900574,16.58027267,73.01541138,49.78084564,20.14196968,62.42157745,70.46037292,16.2150135,328.6499939,68.70916748,34.21094131,66.11945343,42.28531647,14.84605312,140.7632446,122.6047897,69.96856689,59.34999847,81.15415955,18.19032478,34.73751068,29.47999954,39.70000076,84.22186279,140.4299927,83.84999847,20.65921211,48.82647324,114.5078812,87.83695221,28.48910141,138.0237427,212.1398468,50.79764938,66.80999756,25.55999947,90.70262909,83.08290863,53.11358261,39.84144211,185.75,24.88516998,46.18547821,36.38588333,60.05521774,73.40809631,26.71063995,131.8426514,104.9794693,47.03043365,27.96347618,56.33089447,73.94000244,46.31999969,56.40074158,60.64439392,70.51819611,72.33731079,99.14241028,114.9400024,58.83329391,91.35561371,89.90338135,69.01000214,91.66000366,20.02988815,10.53318119,30.31094933,157.6053925,77.0472641,33.02999878,23.57284737,45.09856415,36.76264191,28.1772213,57.97121048,554.7000122,174.9113922,27.07629585,40.91389084,46.11833954,50.14593887,57.64738083,89.95684814,132.1265717,17.75,77.17124939,76.2355423,109.7141113,89.78566742,82.22000122,53.20843887,43.33609772,97.56402588,131.2903137,118.7339096,26.84617615,72.46104431
-4/30/2015,21.84752274,30.42296982,220.139389,17.03519058,69.28697205,51.58223724,24.57673073,60.03445435,67.26213837,16.18287468,317.0100098,69.53327179,35.31919098,58.89770889,38.71540451,14.56540966,139.0549164,116.2427292,67.20631409,72.26000214,78.24552917,22.39833641,34.74606705,30.22999954,38.79999924,85.10553741,133.4299927,82.98000336,17.93624687,55.16541672,115.1704788,91.54878235,29.17978859,130.6819,223.4930878,50.57852936,72.81999969,27.06999969,91.08507538,82.64845276,52.87973022,40.41659546,173.5,25.15871429,47.84734344,36.73788834,56.96993256,61.04038239,25.25355911,125.9216461,105.5612946,46.34711075,28.70056725,55.97953415,76.05999756,46.88000107,55.20708466,54.34983063,72.33436584,85.28881073,94.37812042,122.0199966,57.5223465,88.19024658,87.20759583,68.11000061,97.16000366,20.14417648,10.8610611,28.33872223,161.5300598,76.05762482,33.74000168,23.75412941,46.77707672,43.97773743,32.27069855,63.60951233,548.7700195,182.774353,25.53124428,41.85906982,43.83319092,47.82565689,58.78262329,90.05240631,123.6092529,17.81999969,75.58300018,74.66005707,103.3236389,81.78668213,78.76999664,51.90526199,45.37706375,101.0605469,123.2714539,120.4584579,25.99754906,71.83956909
-5/31/2015,21.84752274,30.42296982,220.139389,17.03519058,69.28697205,51.58223724,24.57673073,60.03445435,67.26213837,16.18287468,317.0100098,69.53327179,35.31919098,58.89770889,38.71540451,14.56540966,139.0549164,116.2427292,67.20631409,72.26000214,78.24552917,22.39833641,34.74606705,30.22999954,38.79999924,85.10553741,133.4299927,82.98000336,17.93624687,55.16541672,115.1704788,91.54878235,29.17978859,130.6819,223.4930878,50.57852936,72.81999969,27.06999969,91.08507538,82.64845276,52.87973022,40.41659546,173.5,25.15871429,47.84734344,36.73788834,56.96993256,61.04038239,25.25355911,125.9216461,105.5612946,46.34711075,28.70056725,55.97953415,76.05999756,46.88000107,55.20708466,54.34983063,72.33436584,85.28881073,94.37812042,122.0199966,57.5223465,88.19024658,87.20759583,68.11000061,97.16000366,20.14417648,10.8610611,28.33872223,161.5300598,76.05762482,33.74000168,23.75412941,46.77707672,43.97773743,32.27069855,63.60951233,548.7700195,182.774353,25.53124428,41.85906982,43.83319092,47.82565689,58.78262329,90.05240631,123.6092529,17.81999969,75.58300018,74.66005707,103.3236389,81.78668213,78.76999664,51.90526199,45.37706375,101.0605469,123.2714539,120.4584579,25.99754906,71.83956909
-6/30/2015,22.40707016,28.82517815,212.8088837,15.65253353,63.36373138,49.67954254,21.6937809,58.08469391,67.2856369,16.09233093,341.4599915,67.5120697,31.56934929,52.18186951,31.64920044,13.32122231,135.855484,111.5814438,70.05734253,67.86000061,78.50126648,17.92252159,33.88396072,31.07999992,41.41500092,88.89923859,133.9100037,85.77999878,18.80583,51.31402206,115.9103012,91.96601105,26.71190453,123.3827133,213.9125366,53.07841492,69.62999725,30.25,94.35063934,81.69982147,55.89750671,37.34040833,190.8999939,23.67712975,42.54595184,30.15410233,54.543396,71.14515686,23.04073143,122.6440277,98.45967102,46.66536331,30.3406086,58.4478035,81.01000214,50.65000153,53.11985779,52.46259689,79.0872879,85.9503479,87.42689514,120.3499985,54.72171783,93.15530396,85.35237122,66.20999908,104.2099991,17.38209534,10.95191479,27.21938896,162.5431824,72.60791779,38.06000137,21.53305626,39.50669861,40.17753601,30.11268997,62.35045242,540.039978,194.8909302,25.19944954,41.71438217,43.8286438,45.44363022,57.72208405,104.668808,127.7692413,17.70000076,79.96956635,76.3181839,113.6344223,79.48459625,85.76999664,47.69550323,49.23071289,101.7887955,105.8185425,119.9401016,24.8152504,72.35973358
-7/31/2015,22.33538055,28.54231644,202.3923492,15.90751171,64.30175018,51.45100784,15.94530678,64.20632935,71.18110657,15.7271452,337.6000061,68.86567688,28.88349342,53.64447784,34.62378693,13.34928608,156.2709503,116.2133408,70.24616241,55.99000168,77.9927063,11.34374332,35.48186874,30.29999924,43.43000031,94.71379089,140.9700012,88.56999969,19.3378067,50.32062149,112.09375,96.74001312,27.86901474,132.7373657,206.7354126,54.32925415,73.30000305,31.45999908,95.66407013,84.33444977,55.35335541,37.14490891,201.5899963,25.55715942,39.29933548,29.30657387,58.15008545,81.23512268,22.33464432,127.4624252,97.91338348,49.12409973,31.65815163,57.97966003,81.98999786,50.84000015,46.45650482,55.04273605,73.09077454,77.90498352,99.68015289,134.1399994,53.33132172,100.2128601,91.59513855,64.51000214,104.2799988,18.68694115,10.65503216,25.73306465,163.5161285,72.19159698,41.65999985,21.26855087,32.77375412,42.49809647,24.97615433,56.28135681,657.5,191.4185791,28.29308128,41.82902908,48.22198105,44.39523315,52.2774353,116.2412567,137.3893585,17.34000015,80.8298645,87.33569336,113.0755539,83.1174469,94.01000214,51.49707031,53.18790436,104.1175995,110.3486786,114.0772018,26.68710899,70.8142395
-8/31/2015,21.16109085,32.47583389,181.500885,15.51362514,58.21995926,46.99180984,15.85243511,60.32513046,65.64208984,14.38814831,296.5499878,70.10998535,27.02408028,48.34326172,35.16722488,12.93767738,134.9404755,113.7832184,67.16710663,49.59000015,73.20529175,10.27212143,33.96169281,25.36000061,42.63499832,86.59363556,141.1399994,85.51000214,19.30980873,41.9740715,104.673584,92.98957062,26.51084518,128.293045,203.0179596,46.108284,69.36000061,29.98999977,88.70547485,81.34095001,49.71481705,34.49435043,196.9700012,24.89834785,34.25535583,27.92616081,55.38288879,79.70716095,21.06369019,116.2728958,92.88459015,47.90043259,30.35903358,52.52971268,78.56999969,46.93000031,40.90403366,59.30633926,70.59272003,71.55426788,93.71342468,121.4100037,49.38405228,91.24030304,86.34473419,61,116.1900024,19.4584198,9.989092827,24.0425663,143.6656647,69.97437286,38.81000137,18.87169456,31.08064079,39.86539078,22.61612892,58.53421783,647.8200073,176.651825,28.91350365,38.55714035,45.70651627,42.49435425,49.23986053,110.3117447,123.4466095,16.73999977,80.34771729,78.53221893,107.7664032,80.61513519,89.43000031,50.18411255,50.36998749,96.75738525,106.2142868,100.7565765,24.58720398,71.42871094
-9/30/2015,21.11546135,33.01520538,166.4601593,15.03038788,58.31890106,43.47086716,14.94756603,57.0814476,61.11518478,12.9899168,284.7399902,67.01094055,23.08011436,47.43111801,36.45125198,12.08474064,122.9738388,104.7707443,67.98821259,40.25999832,73.23386383,9.354968071,34.95290375,24.29000092,43.30500031,90.25872803,139.3099976,83.93000031,17.6784687,41.22819138,102.3899918,92.30567932,25.97166634,132.4335938,195.3583984,40.62372208,69.43000031,28.36000061,84.12018585,83.18035889,46.73573303,33.59222794,181.7899933,26.76540756,27.60689545,24.97146225,58.84031296,81.17966461,23.44693184,116.5131226,88.19578552,47.36876678,28.83877182,52.62149811,82.22000122,46.18000031,38.9825592,62.87292862,65.84416199,69.8613739,99.835495,115.8000031,45.62505341,85.96549225,85.59015656,59.31999969,110.3300018,17.57258224,8.14943409,24.81786919,137.5727844,73.18412018,39.13000107,14.06851006,28.0758419,40.54324722,20.88671684,53.61166382,638.3699951,162.7519836,30.941082,36.72629547,47.39852142,43.98662949,44.26928329,112.8922958,120.5522079,16.40999985,81.06620789,75.40179443,108.5225601,82.7403717,89.90000153,54.487957,52.33102036,92.87046051,101.0913239,107.5599213,25.37684059,69.01732635
-10/31/2015,21.11546135,33.01520538,166.4601593,15.03038788,58.31890106,43.47086716,14.94756603,57.0814476,61.11518478,12.9899168,284.7399902,67.01094055,23.08011436,47.43111801,36.45125198,12.08474064,122.9738388,104.7707443,67.98821259,40.25999832,73.23386383,9.354968071,34.95290375,24.29000092,43.30500031,90.25872803,139.3099976,83.93000031,17.6784687,41.22819138,102.3899918,92.30567932,25.97166634,132.4335938,195.3583984,40.62372208,69.43000031,28.36000061,84.12018585,83.18035889,46.73573303,33.59222794,181.7899933,26.76540756,27.60689545,24.97146225,58.84031296,81.17966461,23.44693184,116.5131226,88.19578552,47.36876678,28.83877182,52.62149811,82.22000122,46.18000031,38.9825592,62.87292862,65.84416199,69.8613739,99.835495,115.8000031,45.62505341,85.96549225,85.59015656,59.31999969,110.3300018,17.57258224,8.14943409,24.81786919,137.5727844,73.18412018,39.13000107,14.06851006,28.0758419,40.54324722,20.88671684,53.61166382,638.3699951,162.7519836,30.941082,36.72629547,47.39852142,43.98662949,44.26928329,112.8922958,120.5522079,16.40999985,81.06620789,75.40179443,108.5225601,82.7403717,89.90000153,54.487957,52.33102036,92.87046051,101.0913239,107.5599213,25.37684059,69.01732635
-11/30/2015,25.58247566,28.26571274,172.5348511,14.32482719,52.92233276,46.6570282,17.12412262,54.14410019,68.78424835,13.63900089,342.7799988,72.99240875,20.02120972,55.73605347,43.96380997,13.63068295,143.9514618,112.4162445,63.15590668,51.29999924,80.07219696,7.927809238,37.41568375,29.57999992,48.11999893,99.54733276,120.7200012,93.30000305,18.2499485,50.07216263,110.2863541,106.1859512,26.3432579,148.2512512,183.2286835,30.93482208,79.69000244,29.48999977,90.2251358,88.3493576,55.30504227,36.38683319,190.7200012,27.70126152,34.98283768,23.28781319,62.52176285,84.38713837,21.3626194,130.2146912,91.90279388,49.52352142,29.32710266,59.56362534,91.45999908,50.08000183,40.13496017,65.99910736,71.6384964,80.96800232,114.0404587,103,46.24868774,84.12036896,88.98271942,57.29999924,114.2399979,21.65856552,8.391382217,29.92693901,151.4848785,78.55728149,40.34999847,11.84131908,34.29051208,50.12149811,18.00821495,61.26236725,762.8499756,178.5913391,31.35989952,38.92382813,53.8387413,51.96366501,50.68035507,118.3331757,136.4444275,18.28000069,87.58171082,76.5825882,105.4355316,78.26383209,104.2399979,51.28277969,56.70307922,97.85218048,123.9810486,113.0671692,26.35447693,66.95153046
-12/31/2015,26.8158474,27.28581429,155.5276794,15.51644707,55.59673691,46.89155197,16.75507545,52.41654587,70.5765152,12.76554585,339.1300049,74.21672058,12.67358494,50.23448944,41.32410049,13.15936089,145.0505219,107.5554504,63.25173569,54.06999969,76.40296173,6.561280251,37.7141571,25.21999931,45.72999954,97.0219574,120.5999985,90.69999695,16.77791786,52.67303085,98.12966919,106.0621567,26.62859726,148.3247223,185.1016846,27.95503235,78.40000153,29.62999916,87.81570435,88.75508118,54.7746048,34.10857391,189.3899994,28.09038162,32.00911331,19.48024178,64.35243225,92.58094025,20.77049255,129.4447937,96.62651825,49.43778992,28.01875687,61.48082352,93.94000244,45.61000061,40.64264297,63.31148911,65.86252594,73.4305954,114.5001831,96.95999908,42.62368774,87.4104538,92.57375336,53.97000122,108.4499969,21.63951492,8.038590431,28.4125843,142.6022949,77.63143921,38.68999863,11.27607918,30.79319763,51.16359329,16.91796684,55.39425659,778.0100098,169.390152,28.6259613,36.73368073,52.93668747,49.00427628,45.34741592,119.4769897,140.0010834,18.44000053,87.06533813,77.61244202,110.5226898,80.94789124,104.6600037,51.56275558,55.44691086,95.21417999,120.1267395,101.9399948,27.34402084,64.99829102
-1/31/2016,26.8158474,27.28581429,155.5276794,15.51644707,55.59673691,46.89155197,16.75507545,52.41654587,70.5765152,12.76554585,339.1300049,74.21672058,12.67358494,50.23448944,41.32410049,13.15936089,145.0505219,107.5554504,63.25173569,54.06999969,76.40296173,6.561280251,37.7141571,25.21999931,45.72999954,97.0219574,120.5999985,90.69999695,16.77791786,52.67303085,98.12966919,106.0621567,26.62859726,148.3247223,185.1016846,27.95503235,78.40000153,29.62999916,87.81570435,88.75508118,54.7746048,34.10857391,189.3899994,28.09038162,32.00911331,19.48024178,64.35243225,92.58094025,20.77049255,129.4447937,96.62651825,49.43778992,28.01875687,61.48082352,93.94000244,45.61000061,40.64264297,63.31148911,65.86252594,73.4305954,114.5001831,96.95999908,42.62368774,87.4104538,92.57375336,53.97000122,108.4499969,21.63951492,8.038590431,28.4125843,142.6022949,77.63143921,38.68999863,11.27607918,30.79319763,51.16359329,16.91796684,55.39425659,778.0100098,169.390152,28.6259613,36.73368073,52.93668747,49.00427628,45.34741592,119.4769897,140.0010834,18.44000053,87.06533813,77.61244202,110.5226898,80.94789124,104.6600037,51.56275558,55.44691086,95.21417999,120.1267395,101.9399948,27.34402084,64.99829102
-2/29/2016,23.64028931,29.02422142,135.0158844,15.96675396,60.16782379,44.57450104,24.05690193,54.82475281,71.00775909,12.74058151,314.9100037,74.25964355,15.63035679,53.52879333,40.25884628,10.7556076,128.0188446,109.5063324,68.90608978,45.06999969,80.19243622,7.394765377,37.86341095,24.64999962,47.81499863,93.08538818,113.9300003,82.40000153,16.18476486,52.8705101,90.62934113,99.88147736,28.39893913,138.1640472,199.3565216,34.53222275,67.75,27.60000038,91.06692505,86.88972473,41.42346191,34.48358536,179.7299957,28.79820442,30.79026031,19.47673798,58.75245667,68.3791275,22.59300804,106.7801743,81.01863861,50.85251236,24.83082962,55.34971619,85.15000153,44.75,30.84708023,67.9731369,60.36500168,68.45993805,114.4909286,96.16999817,41.38879013,87.26416779,101.2899323,46.25999832,73.5,18.02975464,8.331839561,24.59471512,131.0114594,77.60396576,34.63000107,10.48128891,27.67160416,47.25836945,19.27131271,56.48165894,717.2199707,141.1472015,28.25642586,35.75567245,56.4884758,47.76208115,49.41682816,100.0703964,127.5061035,16.97999954,80.31430817,72.28131866,111.8943481,82.95213318,106.9199982,59.35683823,53.94156265,84.63775635,124.1136093,82.99313354,30.03297234,52.16990662
-3/31/2016,28.21900368,29.31440926,158.0977173,17.92938423,62.57766342,47.38238907,24.77876854,54.85501099,69.16433716,14.06951427,344.7600098,75.03817749,15.43162918,54.38471985,43.07095337,12.59747505,134.9020081,119.8471756,72.2701416,46.34999847,89.01425171,10.02121544,41.0429306,27,51.29000092,107.1419525,126.1900024,89.34999847,17.70474052,60.42209244,102.1583557,109.186554,30.52016258,145.1168976,214.54953,35.52483749,73.83000183,31.93000031,99.82098389,91.67944336,45.17496109,38.35573196,190.8999939,31.66686821,33.1779747,24.23230553,66.75919342,75.53239441,26.50518227,114.6951752,80.95314789,54.74097443,26.40637016,57.43252563,93.80000305,48.43999863,36.24626923,70.42264557,63.65280914,73.04328918,113.363121,105.8499985,44.92702484,93.15543365,106.2458115,51.09999847,72.47000122,20.42038918,10.03221607,26.58650017,156.0183411,82.71674347,34.5,12.64949989,29.46322441,51.29874039,21.74125671,56.76677704,762.9000244,148.1795349,22.8677597,40.28694153,58.90444183,51.72572708,55.05603409,103.8729935,139.8965912,18.80999947,85.87961578,77.13423157,121.6012268,84.04732513,114.0999985,63.02928543,55.3223114,92.03401184,130.1720428,88.48091125,32.83075333,57.63282013
-4/30/2016,28.21900368,29.31440926,158.0977173,17.92938423,62.57766342,47.38238907,24.77876854,54.85501099,69.16433716,14.06951427,344.7600098,75.03817749,15.43162918,54.38471985,43.07095337,12.59747505,134.9020081,119.8471756,72.2701416,46.34999847,89.01425171,10.02121544,41.0429306,27,51.29000092,107.1419525,126.1900024,89.34999847,17.70474052,60.42209244,102.1583557,109.186554,30.52016258,145.1168976,214.54953,35.52483749,73.83000183,31.93000031,99.82098389,91.67944336,45.17496109,38.35573196,190.8999939,31.66686821,33.1779747,24.23230553,66.75919342,75.53239441,26.50518227,114.6951752,80.95314789,54.74097443,26.40637016,57.43252563,93.80000305,48.43999863,36.24626923,70.42264557,63.65280914,73.04328918,113.363121,105.8499985,44.92702484,93.15543365,106.2458115,51.09999847,72.47000122,20.42038918,10.03221607,26.58650017,156.0183411,82.71674347,34.5,12.64949989,29.46322441,51.29874039,21.74125671,56.76677704,762.9000244,148.1795349,22.8677597,40.28694153,58.90444183,51.72572708,55.05603409,103.8729935,139.8965912,18.80999947,85.87961578,77.13423157,121.6012268,84.04732513,114.0999985,63.02928543,55.3223114,92.03401184,130.1720428,88.48091125,32.83075333,57.63282013
-5/31/2016,40.56236267,29.07042313,168.9231415,19.53780556,65.14345551,50.38240814,30.21368217,52.78820038,74.21792603,12.97428036,375.3200073,78.77706146,15.7292099,55.83942795,40.84049606,11.73229122,143.0538025,118.6740723,60.87392044,43.34000015,86.82830811,10.73840046,39.45924377,26.77000046,52.66500092,111.5289612,97.98999786,101.6200027,17.75205803,74.19261932,94.1705246,120.4391556,28.14080238,137.4088593,211.0040894,26.75844383,83.70999908,33.06999969,104.7587891,90.50752258,53.20227432,37.83055878,196.6900024,32.05781937,39.02954102,35.6908226,61.58076477,71.50180817,28.71720505,114.9111176,70.45008087,54.64030457,28.74663734,64.46323395,99.47000122,51.66999817,32.24705887,64.44088745,67.64665985,70.17948151,120.5879288,110.1999969,41.52087784,86.97485352,108.6374741,53.65999985,84.41000366,21.76333427,9.520609856,26.45961571,158.1756897,80.99251556,34.40999985,15.95807457,33.62871552,49.57177734,22.96626472,62.58198547,748.8499756,151.1564941,18.48809242,43.77401733,62.27502823,54.93878937,54.73050308,107.4016953,149.954834,22.70999908,90.65122986,71.19725037,126.1011353,85.28876495,118.8099976,62.80130768,51.04299545,94.38925171,146.3107147,86.70687866,33.03248215,62.02415466
-6/30/2016,41.05993652,27.91133308,137.0407715,20.81257629,67.2050705,52.01252365,36.49472046,52.4128418,80.01849365,13.84389782,364.9200134,88.82920837,16.28600311,59.78203201,37.78734207,11.09528446,137.8007813,118.9839554,61.79437637,43.24000168,91.32702637,10.7965517,40.41267014,23.85000038,54.36500168,106.2042236,104.1200027,97.41000366,18.53202629,75.2456665,90.15322113,122.9967957,29.94194984,145.047287,209.9876251,27.39182091,79.41000366,31.70000076,104.7204514,95.48547363,46.97719574,38.51752853,189.7599945,31.70775032,38.23206329,39.15674973,61.755867,62.0409317,31.54996109,118.2996902,74.52786255,62.07306671,23.2921505,66.47731018,95.79000092,54.08000183,27.97335243,61.74634171,58.65974045,64.19316864,126.428093,113.8399963,45.01758194,86.33460999,117.9347687,49.02999878,79.98000336,21.55379486,10.71390438,24.24359512,145.8926849,85.22834015,34.59999847,14.60387993,33.74159622,47.86014938,24.66214371,63.29911804,703.5300293,140.8253479,20.09427261,43.45449829,67.96459198,56.79728317,53.04321289,102.6321487,146.1371765,23.37000084,93.83550262,76.59683228,133.8113403,104.2479172,114.2799988,68.52713776,53.11670303,89.67169952,160.2541199,82.84885406,35.39513779,57.59667587
-7/31/2016,41.05993652,27.91133308,137.0407715,20.81257629,67.2050705,52.01252365,36.49472046,52.4128418,80.01849365,13.84389782,364.9200134,88.82920837,16.28600311,59.78203201,37.78734207,11.09528446,137.8007813,118.9839554,61.79437637,43.24000168,91.32702637,10.7965517,40.41267014,23.85000038,54.36500168,106.2042236,104.1200027,97.41000366,18.53202629,75.2456665,90.15322113,122.9967957,29.94194984,145.047287,209.9876251,27.39182091,79.41000366,31.70000076,104.7204514,95.48547363,46.97719574,38.51752853,189.7599945,31.70775032,38.23206329,39.15674973,61.755867,62.0409317,31.54996109,118.2996902,74.52786255,62.07306671,23.2921505,66.47731018,95.79000092,54.08000183,27.97335243,61.74634171,58.65974045,64.19316864,126.428093,113.8399963,45.01758194,86.33460999,117.9347687,49.02999878,79.98000336,21.55379486,10.71390438,24.24359512,145.8926849,85.22834015,34.59999847,14.60387993,33.74159622,47.86014938,24.66214371,63.29911804,703.5300293,140.8253479,20.09427261,43.45449829,67.96459198,56.79728317,53.04321289,102.6321487,146.1371765,23.37000084,93.83550262,76.59683228,133.8113403,104.2479172,114.2799988,68.52713776,53.11670303,89.67169952,160.2541199,82.84885406,35.39513779,57.59667587
-8/31/2016,39.03852844,35.09895706,138.28685,19.70934486,66.20101166,56.68923569,35.6737709,52.89017105,80.65667725,15.218894,403.0700073,82.99660492,19.1271019,63.34947205,35.63851166,13.71936417,154.917038,130.3596497,62.61743927,42.36000061,92.74313354,9.972757339,38.71877289,24.81999969,51.52500153,107.8072662,85.98000336,91,20.31962204,75.87182617,100.597023,126.6702881,28.37888908,150.1140594,214.3417511,29.48634338,79.41999817,36.09000015,107.0727539,96.89611053,55.42928696,38.93312073,212.7799988,29.21312714,38.75217819,39.22070313,58.16062546,65.69962311,30.42516518,118.8942947,82.0292511,62.04834366,25.76175308,51.87129593,102.3099976,59.29000092,32.71327591,72.06080627,66.53179932,68.81220245,131.0212708,122.7300034,47.76190948,84.59563446,110.148735,58.95000076,81.09999847,22.75387383,10.45489597,27.34471893,158.5325928,83.31726837,38.41999817,11.82343674,32.52961731,54.07826233,23.61785889,64.37979889,789.8499756,161.2436829,18.92356682,45.45553589,69.97929382,63.38154602,59.62175751,105.5956955,150.5185242,23.81999969,112.367363,74.57977295,128.9308319,92.25603485,126.1200027,64.15982819,52.47117615,104.376976,157.9984589,95.79106903,34.08485794,62.16572952
-9/30/2016,43.32911301,35.0843811,140.8666229,20.37597466,66.83114624,56.75933838,36.67602921,48.0920105,80.47258759,13.46845341,419.8299866,83.3086853,20.24758911,61.54463196,37.58085251,13.61882305,151.9564362,126.7232437,61.2703476,38.11999893,91.19522858,10.52518368,38.03743362,26.30999947,49.73500061,114.528801,80.13999939,88.44999695,19.14117241,81.42966461,107.186554,129.2440338,28.68236351,141.2418976,208.9334717,30.51854706,71.33000183,35.45999908,108.1689682,98.72963715,55.66073227,37.10074997,200.3399963,29.35262489,40.06561661,42.98468781,58.12000656,69.71582031,30.09651947,120.9975662,76.19091797,55.96792984,25.91911888,48.73498154,108.5400009,59.34999847,33.46475983,71.77732086,66.74552155,70.3560791,127.2812576,124.6399994,45.8810463,80.60134125,111.4055939,53.34999847,94.29000092,24.79210281,11.13052273,27.54205894,168.3119354,82.30912781,38.83000183,10.94473553,33.71834564,54.21001816,24.73977852,61.68857574,804.0599976,153.4507904,20.43018532,46.79868317,68.88805389,63.96487427,58.87804413,112.9502258,157.474411,23.79999924,107.6722412,74.49660492,133.2867889,88.29392242,128.2700043,64.15998077,50.52088928,103.9832535,146.7586212,93.97859955,34.40819168,60.70592117
-10/31/2016,45.18808365,35.75518799,129.1456146,19.99880791,64.88513947,53.40343475,34.57572556,46.51324844,76.39307404,13.39060211,404.0799866,80.46128845,17.99130249,56.77608871,38.70180511,11.87576675,128.5904694,122.3386307,61.31494904,36.5,82.2436676,10.83531761,38.10933685,25.11000061,49.24000168,110.1032562,80.08999634,86.04000092,17.76576042,79.58181,107.651123,119.0547028,29.73150253,136.9447174,193.396347,30.05726814,75.16000366,32.27999878,106.8980942,97.30457306,57.48708344,36.42904282,184.3000031,29.15732956,38.86381912,41.02128601,55.7890625,71.50172424,27.04917717,130.8158875,66.32515717,54.71983719,26.4652729,46.33332062,107.5100021,59.31000137,34.09258652,68.29571533,68.7990799,69.38787842,128.4211121,138.2100067,45.22074509,76.54885101,116.5787811,49.93999863,86.97000122,24.92544746,10.29080868,27.39468384,167.9650726,81.24526215,36.00999832,10.40828323,32.52018356,56.39347458,20.02196121,61.68012619,809.9000244,169.5979919,20.27133179,44.3699646,64.6499176,64.57555389,57.1397438,125.0561981,145.5643311,22,102.0017624,76.4463501,134.553009,94.6296463,130.9900055,65.25225067,49.52241516,96.53117371,154.3538666,91.15385437,34.44485855,63.27884293
-11/30/2016,50.31686401,41.99465561,144.1765594,21.1663723,65.26509094,55.64979553,30.28176117,46.77066422,68.00120544,15.43206215,412.019989,73.8026123,19.55001831,58.73484039,45.04097366,11.44479275,132.1278687,132.4616852,69.49120331,36.61000061,87.3640213,14.87675571,36.57339096,26.44000053,52.31000137,113.1248322,72.97000122,102.8199997,18.01409912,83.61090088,105.3257675,110.2113495,27.42629433,139.4470978,215.5009308,34.76066971,72,32.83000183,110.0520706,91.53211975,68.78943634,38.10731506,197.4400024,28.41015053,46.51391602,46.5269165,54.21702576,75.3154068,26.46376801,140.4212189,73.901474,53.80165482,32.13860703,51.36619186,102.8099976,60.47999954,33.99877548,75.5129776,78.91217804,79.56262207,140.576004,140.75,50.23781967,69.98619843,105.6424942,57.79000092,102.2900009,27.34465218,10.01102448,29.93475914,184.6825714,89.60682678,38.27999878,11.10347271,36.09941483,57.09659576,21.25200462,60.36885071,775.8800049,209.3044434,19.55649757,46.66631317,70.09375,67.87578583,60.15810776,120.3059998,138.7133331,20.45999908,110.9993362,78.65519714,151.328476,89.81761932,118.4199982,61.0696373,54.3454361,96.87519836,171.5826569,97.20290375,32.51667786,68.63306427
-12/31/2016,50.31686401,41.99465561,144.1765594,21.1663723,65.26509094,55.64979553,30.28176117,46.77066422,68.00120544,15.43206215,412.019989,73.8026123,19.55001831,58.73484039,45.04097366,11.44479275,132.1278687,132.4616852,69.49120331,36.61000061,87.3640213,14.87675571,36.57339096,26.44000053,52.31000137,113.1248322,72.97000122,102.8199997,18.01409912,83.61090088,105.3257675,110.2113495,27.42629433,139.4470978,215.5009308,34.76066971,72,32.83000183,110.0520706,91.53211975,68.78943634,38.10731506,197.4400024,28.41015053,46.51391602,46.5269165,54.21702576,75.3154068,26.46376801,140.4212189,73.901474,53.80165482,32.13860703,51.36619186,102.8099976,60.47999954,33.99877548,75.5129776,78.91217804,79.56262207,140.576004,140.75,50.23781967,69.98619843,105.6424942,57.79000092,102.2900009,27.34465218,10.01102448,29.93475914,184.6825714,89.60682678,38.27999878,11.10347271,36.09941483,57.09659576,21.25200462,60.36885071,775.8800049,209.3044434,19.55649757,46.66631317,70.09375,67.87578583,60.15810776,120.3059998,138.7133331,20.45999908,110.9993362,78.65519714,151.328476,89.81761932,118.4199982,61.0696373,54.3454361,96.87519836,171.5826569,97.20290375,32.51667786,68.63306427
-1/31/2017,51.76005554,41.15646362,148.3237,23.25107193,62.28830719,56.80997849,33.91693497,44.52139664,71.22750092,15.83987904,426.6300049,78.51493073,19.78380775,64.5242691,50.65671921,12.11519718,143.6925964,128.9160156,58.01129913,38.04999924,88.48738861,16.13667488,37.67919922,27.70999908,53.71500015,107.8583832,77.13999939,99.36000061,20.6444397,88.53578186,115.6467743,112.9365387,26.57606697,152.3039856,236.0630951,24.56163406,79.09999847,31.90999985,109.0190353,94.89713287,71.87398529,38.18041992,215.8399963,29.9256382,50.02843094,47.20196152,55.34298325,87.5916214,29.17926407,152.4152222,82.70446014,55.5899086,33.31032562,45.03609085,113.3799973,62.88999939,38.99355316,76.38043213,82.0577774,82.16127777,136.2143402,134.0299988,56.23034668,72.16751099,114.419075,66.70999908,121.2099991,27.43036842,10.1086874,32.08224106,182.5875397,94.80780029,40.52999878,16.22460365,37.61301804,61.25614166,20.65573883,57.9573822,820.1900024,218.8777161,19.12864494,49.89171982,64.87891388,69.79423523,64.02030945,117.9202347,151.0269775,24.05999947,112.4618912,76.06522369,154.9415588,98.0242691,130.3200073,65.21118927,51.76738739,99.93087006,186.172348,82.62709045,34.37582016,73.07816315
-2/28/2017,57.0525589,40.79593277,163.688858,24.48130989,66.19882965,60.36575699,32.0098114,45.3602829,75.80923462,15.76974964,476.2200012,83.61039734,18.87166405,69.14595795,55.97320557,12.64194584,163.0138092,129.5709381,53.36123276,41.84999847,87.48193359,12.98687458,38.03269958,28.06999969,57.70000076,116.0327682,82.87999725,103.2099991,21.1627121,97.01282501,131.1177826,126.2543488,28.77135658,165.0375519,232.8710175,27.62144279,81.34999847,31.57999992,111.8726883,100.9322205,75.35593414,40.54111099,226.3600006,31.67788506,47.91619492,46.29406738,57.43758392,89.90232849,29.62754631,169.5391235,87.06121826,53.71260071,33.82304382,51.95273972,118.3399963,71.44000244,40.42866516,74.73377228,88.53755951,80.3730545,145.6537323,143.2700043,55.85925293,73.78834534,122.0803375,64.54000092,133.1000061,25.03973961,10.17937851,32.2837944,186.3240204,96.33803558,40.58000183,16.24422073,34.53142166,60.98883057,21.05962753,56.05882645,844.9299927,237.3832092,18.32641792,52.78345108,67.06664276,70.79206085,65.10572052,115.4472046,156.2696533,24.54999924,114.3022003,80.54946899,158.0767212,101.277916,135.5399933,71.34933472,53.55445862,108.1017761,209.7270355,74.12424469,36.04667282,76.59907532
-3/31/2017,57.56435394,45.77693558,159.7996521,24.7053299,67.76677704,58.65066528,30.85992241,47.94607925,75.8835144,16.53911209,478.9100037,85.33712769,19.25246048,69.08837128,52.15149307,13.03106785,151.507843,125.6656418,50.11070251,38.99000168,85.07972717,12.94810867,38.80730438,28.30999947,57.65499878,113.5510712,82.88999939,107.9899979,22.6919632,101.2743301,137.5018463,132.0687256,28.23017502,156.1979218,218.5959778,24.94151497,82.48999786,29.27000046,114.8133774,102.988121,73.36513519,42.46393204,229.4900055,32.46450424,58.04898834,47.48461914,57.11754608,92.23828888,29.54792976,166.3690033,84.19754791,52.50257492,32.01242828,49.81819916,130.1300049,72.12999725,40.04537201,82.06465149,81.74584198,81.06288147,144.094696,142.5700073,57.2413063,71.88365936,119.6294022,59.22000122,133.6699982,26.20895767,9.878947258,31.30388069,188.8106689,96.65044403,42.54999924,18.34341621,32.56822586,62.78093338,22.99249649,54.82999039,847.7999878,219.8325958,20.92129898,52.76478577,66.87716675,74.43238831,67.62245178,122.6446762,152.3695679,24.87000084,122.5641937,77.44424438,157.3515778,102.1191559,142.0500031,71.71392822,54.98583221,108.7521057,192.7294617,76.73387146,36.16537476,75.69015503
-4/30/2017,57.56435394,45.77693558,159.7996521,24.7053299,67.76677704,58.65066528,30.85992241,47.94607925,75.8835144,16.53911209,478.9100037,85.33712769,19.25246048,69.08837128,52.15149307,13.03106785,151.507843,125.6656418,50.11070251,38.99000168,85.07972717,12.94810867,38.80730438,28.30999947,57.65499878,113.5510712,82.88999939,107.9899979,22.6919632,101.2743301,137.5018463,132.0687256,28.23017502,156.1979218,218.5959778,24.94151497,82.48999786,29.27000046,114.8133774,102.988121,73.36513519,42.46393204,229.4900055,32.46450424,58.04898834,47.48461914,57.11754608,92.23828888,29.54792976,166.3690033,84.19754791,52.50257492,32.01242828,49.81819916,130.1300049,72.12999725,40.04537201,82.06465149,81.74584198,81.06288147,144.094696,142.5700073,57.2413063,71.88365936,119.6294022,59.22000122,133.6699982,26.20895767,9.878947258,31.30388069,188.8106689,96.65044403,42.54999924,18.34341621,32.56822586,62.78093338,22.99249649,54.82999039,847.7999878,219.8325958,20.92129898,52.76478577,66.87716675,74.43238831,67.62245178,122.6446762,152.3695679,24.87000084,122.5641937,77.44424438,157.3515778,102.1191559,142.0500031,71.71392822,54.98583221,108.7521057,192.7294617,76.73387146,36.16537476,75.69015503
-5/31/2017,64.66293335,55.31418228,150.1594543,25.88984489,74.39112854,60.09985352,31.97410774,46.92557907,79.3875885,15.94526386,582.8099976,91.842453,16.71330452,68.58335876,58.292099,13.22412014,144.390274,133.8117371,50.61867523,38.97999954,85.27306366,11.13575935,41.57794189,25.82999992,62.63999939,119.1219254,81.76999664,119.5999985,21.84402466,108.9053802,146.8152466,132.5030212,26.26697922,175.3650208,162.8821106,19.77481842,89.63999939,31.48999977,127.0150833,108.3397903,69.52658844,43.39255905,239.3000031,34.65253448,62.87041855,43.03678894,59.75217438,104.0381393,28.92665672,177.8513489,87.67950439,50.90235901,25.17303467,49.78287506,141.8600006,74.87000275,40.87490845,79.54237366,73.28446198,71.57785034,155.7824707,128.1300049,65.24133301,70.80685425,132.7400665,62.83000183,129.3300018,30.34117126,10.43006897,30.03791809,187.5432587,96.63156891,43.31000137,15.78115559,27.30019569,66.95646667,21.38242149,50.99638367,987.0900269,202.8477478,23.8817749,53.30702209,64.85059357,76.68833923,71.12150574,140.0377808,171.4058533,27.03000069,121.9249191,75.88620758,168.0680695,108.3399506,151.4600067,73.47953033,60.14825439,115.3621292,189.0442505,63.74119568,38.1640892,73.91620636
-6/30/2017,64.1709671,53.71529007,161.8813477,24.7767868,71.62749481,59.59332275,30.37112045,50.66065598,83.59810638,16.36746788,588.539978,91.36412811,17.06965828,75.11373138,60.38079453,13.65848923,160.1928711,133.7602386,47.9936676,38.81999969,86.03235626,11.63972855,41.34851456,25.20999908,61.16999817,118.3658829,76.31999969,123.5100021,23.72751617,101.4704971,138.4153748,133.1035614,26.19511223,155.4404907,170.6820679,19.88719368,86.59999847,32.95000076,128.9943695,107.0605087,77.38573456,47.93353653,241.6900024,33.90282822,61.09221268,45.18516541,60.88246155,103.1411057,28.92660332,187.4439392,90.31647491,49.70022202,27.9575386,51.41616821,141.4400024,72.93000031,40.73067474,83.01267242,78.715065,75.86604309,154.1456757,127.0599976,60.7067337,74.15226746,131.5106049,63.06000137,125.9100037,30.03153992,9.921067238,31.26831055,210.7697601,97.26435089,45.38000107,16.92101669,26.92908669,66.08404541,24.16724396,52.45650482,929.6799927,213.0640564,28.03755951,54.16327667,67.50137329,71.51937866,71.5351181,145.0732269,173.2222595,27.71999931,122.079895,73.34793091,178.6269684,100.9149017,150.9799957,70.92141724,55.13670349,118.5079193,179.7276459,69.86129761,36.96771622,80.9292984
-7/31/2017,65.55944061,54.66160965,181.3723145,25.50977707,75.70670319,59.39805984,34.85317993,54.6976738,79.50740051,16.7168541,573.0800171,91.72893524,18.31365776,74.39028931,53.93849182,14.18938446,162.3134918,132.9093628,52.01378632,38.99000168,78.77024841,14.16926289,42.26122665,23.12999916,64.25,123.2850342,77.08000183,128.3200073,23.62111473,111.334877,142.9420776,140.8716431,28.66550064,154.0603638,157.6443329,20.32361794,90.80000305,34.56000137,134.4151306,108.0987701,80.25080872,47.91282272,248.9900055,33.61344528,63.87710571,49.00545883,62.94484711,106.7670441,30.66927147,229.8238068,89.63812256,50.38389969,28.42631149,52.87147141,146.4900055,76.56999969,44.94221497,86.78338623,82.10681915,80.99030304,163.9683228,120.75,61.37416077,74.14284515,137.1040039,66.25,133.2899933,31.60558319,9.983578682,32.20824051,201.750473,112.8802032,44.20999908,24.22205544,27.50953674,69.69838715,23.96488953,54.2614212,945.5,216.3574829,27.66566086,55.62024689,70.97660065,76.11753082,71.92114258,152.3974762,174.2746582,26.62000084,130.6130981,75.55838776,184.7828827,98.97875214,169.25,71.36586761,51.04233932,128.1985168,198.988327,71.61256409,37.58872604,82.18945313
-8/31/2017,71.09661102,50.83885574,172.6427307,27.05493546,74.35429382,59.37945938,35.95025635,55.29575729,76.33544159,16.23308563,605.0900269,98.89723206,17.32760239,75.19146729,50.78245926,13.22412014,166.4608002,135.9200592,50.61351013,31.47999954,76.82254791,14.32432938,41.99386978,21.01000023,61.85499954,125.141655,71.88999939,120.5899963,24.97531319,111.777153,158.2367859,138.3743896,29.59819031,152.8271637,154.8954468,17.7735424,95.48999786,34.65000153,135.3782043,108.0337448,75.55287933,48.29666519,253.1199951,34.41146851,72.10636902,47.557724,62.10325241,117.5221176,33.18645477,228.5246887,77.0242691,48.21140289,29.01172638,56.19800186,155.1600037,80.41999817,44.76615143,84.33338165,76.20296478,81.43981171,173.7432098,119.3799973,63.29351044,71.74035645,142.1782074,67.15000153,137.4100037,31.63437462,9.965522766,32.70953751,207.9088287,101.0710144,38.59999847,24.50736809,22.69919586,72.06483459,24.67075729,52.30754471,955.2399902,215.5645142,24.25507545,55.1487999,71.59151459,77.46443176,66.49330139,144.7980957,185.8016663,27.54999924,130.7680664,76.71405029,191.6131439,99.21618652,171.9700012,73.21833038,52.10861969,130.9179688,207.1654816,83.1993103,39.63835144,83.02841187
-9/30/2017,71.09661102,50.83885574,172.6427307,27.05493546,74.35429382,59.37945938,35.95025635,55.29575729,76.33544159,16.23308563,605.0900269,98.89723206,17.32760239,75.19146729,50.78245926,13.22412014,166.4608002,135.9200592,50.61351013,31.47999954,76.82254791,14.32432938,41.99386978,21.01000023,61.85499954,125.141655,71.88999939,120.5899963,24.97531319,111.777153,158.2367859,138.3743896,29.59819031,152.8271637,154.8954468,17.7735424,95.48999786,34.65000153,135.3782043,108.0337448,75.55287933,48.29666519,253.1199951,34.41146851,72.10636902,47.557724,62.10325241,117.5221176,33.18645477,228.5246887,77.0242691,48.21140289,29.01172638,56.19800186,155.1600037,80.41999817,44.76615143,84.33338165,76.20296478,81.43981171,173.7432098,119.3799973,63.29351044,71.74035645,142.1782074,67.15000153,137.4100037,31.63437462,9.965522766,32.70953751,207.9088287,101.0710144,38.59999847,24.50736809,22.69919586,72.06483459,24.67075729,52.30754471,955.2399902,215.5645142,24.25507545,55.1487999,71.59151459,77.46443176,66.49330139,144.7980957,185.8016663,27.54999924,130.7680664,76.71405029,191.6131439,99.21618652,171.9700012,73.21833038,52.10861969,130.9179688,207.1654816,83.1993103,39.63835144,83.02841187
-10/31/2017,76.73799896,52.75645828,182.2280273,27.01839447,83.15450287,51.59529114,33.97257614,62.12649155,76.69396973,17.71422577,682.6300049,98.54898071,16.34732056,81.58827209,52.45767975,13.51619244,164.072998,150.9308472,54.79957962,35.70999908,82.4835434,13.54899216,42.72759247,17.80999947,64.71499634,137.5628357,70.84999847,125.3099976,29.34148979,135.8034363,163.0996704,105.4100571,29.93432617,157.0588074,188.3670197,16.32561493,102.3399963,37.68999863,139.8832092,102.8995056,81.99793243,49.03630066,261.7600098,33.27416611,77.82926941,47.65431595,62.68000412,117.4806595,34.14770508,245.9934692,73.85691833,47.44472504,30.73603249,57.64169312,175.1600037,86.51999664,50.85266113,87.12570953,88.23499298,94.00671387,172.7494507,121.2699966,71.11540222,63.98649979,146.4857941,75.09999847,113.25,30.18681908,9.703848839,39.26729584,219.5074768,110.9498749,37.84999847,24.62545204,26.61449623,80.170578,26.74677086,57.28759766,1033.040039,233.6197357,22.64927864,60.32078171,65.80818176,91.01629639,74.14705658,121.667099,192.594696,28.13999939,144.3572388,62.37838745,203.2869873,100.407692,180.0599976,73.51911163,52.08962631,139.1034698,225.4362183,85.13434601,40.41156769,92.46796417
-11/30/2017,80.61180115,56.17742538,194.3287201,27.65818787,92.60238647,51.76387787,34.75236511,65.07894897,78.2274704,17.9225235,629.210022,103.9973373,15.55296898,83.1233902,59.09037018,15.94716263,165.609375,154.3484039,56.17443848,36.52999878,86.91481781,13.49084377,42.88115311,18.07999992,65.72499847,143.0224304,66.30999756,120.8899994,33.12686157,129.4706116,166.4070129,111.2312164,31.36013031,180.3594971,212.1804199,20.71159744,104.3199997,39.41999817,136.7526093,109.5258255,85.4024353,47.26367188,282.6099854,32.48571777,79.12000275,46.21863556,62.26996994,117.5850754,34.89041519,265.3578796,81.79762268,51.68478394,33.9705658,59.07198334,181.4700012,90.37999725,53.87475967,90.56108093,88.46430969,95.0690918,183.2467041,134.1999969,76.46665192,71.52146912,150.2362976,68.91000366,98.98999786,32.85404205,9.76847744,39.36779404,224.9997711,109.2320938,41.72000122,27.23575211,25.20572662,81.5321579,28.00240326,62.54880142,1036.170044,239.3409576,23.96759224,63.07234955,70.55592346,91.58107758,72.60593414,119.853447,191.5315399,26.28000069,154.1626282,68.88350677,221.3899689,105.5282288,177.1799927,74.73292542,55.21111679,148.6798401,234.7096405,90.57958984,42.13976669,94.58798981
-12/31/2017,80.61180115,56.17742538,194.3287201,27.65818787,92.60238647,51.76387787,34.75236511,65.07894897,78.2274704,17.9225235,629.210022,103.9973373,15.55296898,83.1233902,59.09037018,15.94716263,165.609375,154.3484039,56.17443848,36.52999878,86.91481781,13.49084377,42.88115311,18.07999992,65.72499847,143.0224304,66.30999756,120.8899994,33.12686157,129.4706116,166.4070129,111.2312164,31.36013031,180.3594971,212.1804199,20.71159744,104.3199997,39.41999817,136.7526093,109.5258255,85.4024353,47.26367188,282.6099854,32.48571777,79.12000275,46.21863556,62.26996994,117.5850754,34.89041519,265.3578796,81.79762268,51.68478394,33.9705658,59.07198334,181.4700012,90.37999725,53.87475967,90.56108093,88.46430969,95.0690918,183.2467041,134.1999969,76.46665192,71.52146912,150.2362976,68.91000366,98.98999786,32.85404205,9.76847744,39.36779404,224.9997711,109.2320938,41.72000122,27.23575211,25.20572662,81.5321579,28.00240326,62.54880142,1036.170044,239.3409576,23.96759224,63.07234955,70.55592346,91.58107758,72.60593414,119.853447,191.5315399,26.28000069,154.1626282,68.88350677,221.3899689,105.5282288,177.1799927,74.73292542,55.21111679,148.6798401,234.7096405,90.57958984,42.13976669,94.58798981
-1/31/2018,83.65775299,69.23270416,195.2677307,25.9716053,102.0614777,55.96341324,38.13926315,72.87200928,82.27169037,18.98946953,675.2600098,104.7734604,16.3391304,98.10313416,59.33715439,16.96817017,175.4049072,160.3194427,70.54158783,42.84999847,97.99768066,18.89881325,44.58627701,23.86000061,70.41999817,155.2848206,75.36000061,138.7400055,30.97621727,107.8264694,162.1270142,121.7675781,30.22110558,190.5690918,258.5358582,22.91753769,113.9100037,42.02999878,139.0074158,113.0789261,93.48868561,49.89457321,281.0599976,28.55193138,76.70083618,53.09156418,57.86845398,127.3675766,30.37022781,339.721344,96.11846924,53.88762283,37.55787277,58.90442657,199.7599945,92.61000061,54.43595505,96.24207306,99.96468353,109.7654037,201.1551361,144.5399933,84.44259644,73.92952728,150.5975647,71.37000275,90.29000092,35.21377945,10.79417706,39.09902954,255.6882324,118.6279678,42.70000076,25.64981651,29.25014496,92.03245544,25.54202652,67.26081848,1182.219971,258.9123535,24.52197075,65.45802307,73.09475708,103.8059616,78.38415527,125.2444077,222.856308,27.95999908,164.9434204,71.25030518,229.7440948,104.9574585,186.8899994,58.04561615,54.24669266,158.4436035,230.6985321,109.3484802,37.45037079,96.56348419
-2/28/2018,86.17044067,68.64519501,185.5140076,25.19129372,86.17780304,51.21242142,35.96444702,66.97148132,76.52445984,16.97710037,616.2199707,102.2556229,14.72157764,93.07300568,56.4483757,15.94716263,174.5650482,153.1018677,71.30376434,40.31999969,86.48127747,18.02655983,40.49209976,22.97999954,71.69499969,155.5843658,62.66999817,113.4100037,27.31707573,97.04286194,173.1816559,110.1395569,30.03974342,187.1862488,252.0077515,25.97320938,116.25,39.47999954,137.1985931,103.1434021,89.91944885,49.0048027,239.8800049,25.66717529,65.90914917,50.80951309,52.8151741,120.7393036,27.27511787,348.951355,92.12787628,46.57239151,34.57458878,62.29191971,209.1300049,84.66999817,47.65047073,102.7156219,94.57852173,99.12227631,209.405838,148.5200043,79.65110779,63.63257599,145.671936,61.91999817,85.16000366,33.06906891,10.14988804,36.27792358,240.0340271,110.6541824,38.83000183,25.50189209,28.70171928,91.25797272,23.4191761,58.8543396,1103.920044,254.8318939,23.40397644,66.21495056,70.89905548,102.5565414,75.3316803,102.8978577,207.4131927,27.26000023,167.1074371,65.60394287,219.4396973,94.10584259,178.3200073,56.24473953,54.81933975,163.8600922,255.1419525,101.2461014,36.41400909,94.72742462
-3/31/2018,86.17044067,68.64519501,185.5140076,25.19129372,86.17780304,51.21242142,35.96444702,66.97148132,76.52445984,16.97710037,616.2199707,102.2556229,14.72157764,93.07300568,56.4483757,15.94716263,174.5650482,153.1018677,71.30376434,40.31999969,86.48127747,18.02655983,40.49209976,22.97999954,71.69499969,155.5843658,62.66999817,113.4100037,27.31707573,97.04286194,173.1816559,110.1395569,30.03974342,187.1862488,252.0077515,25.97320938,116.25,39.47999954,137.1985931,103.1434021,89.91944885,49.0048027,239.8800049,25.66717529,65.90914917,50.80951309,52.8151741,120.7393036,27.27511787,348.951355,92.12787628,46.57239151,34.57458878,62.29191971,209.1300049,84.66999817,47.65047073,102.7156219,94.57852173,99.12227631,209.405838,148.5200043,79.65110779,63.63257599,145.671936,61.91999817,85.16000366,33.06906891,10.14988804,36.27792358,240.0340271,110.6541824,38.83000183,25.50189209,28.70171928,91.25797272,23.4191761,58.8543396,1103.920044,254.8318939,23.40397644,66.21495056,70.89905548,102.5565414,75.3316803,102.8978577,207.4131927,27.26000023,167.1074371,65.60394287,219.4396973,94.10584259,178.3200073,56.24473953,54.81933975,163.8600922,255.1419525,101.2461014,36.41400909,94.72742462
-4/30/2018,86.78114319,72.98988342,161.5115967,23.58947945,85.1987381,56.09073639,37.12444305,73.11548615,77.19800568,18.08918381,559.9299927,94.60356903,14.55573368,92.45753479,51.66955185,15.89564037,165.7404022,155.6123047,68.64678192,38.75999832,83.82511902,14.78217983,40.84009171,22.21999931,70.86000061,147.3942108,58.70999908,121.2900009,29.63591194,93.99520111,160.6781769,109.5668716,31.96310234,193.3244781,271.0854492,27.79104233,120.9899979,31.02000046,139.6881714,95.58222961,87.29723358,44.35199738,209.8800049,26.46314812,67.12856293,55.04606628,58.49100113,103.6942215,29.95497513,321.3500977,87.69379425,40.73725128,31.51522636,49.36605835,221.6000061,85.51000214,47.51453781,106.7849808,87.51869965,97.74555206,198.0953064,163.0899963,77.87319183,66.10741425,156.9312439,62.5,61.93999863,30.45922279,11.55111313,34.21620941,241.3053436,113.9256668,38.79000092,30.59984779,32.55042267,91.01467133,23.17684364,70.14385223,1018.580017,230.9895782,25.77093315,67.45826721,67.33449554,96.00654602,70.6132431,112.9644928,209.3387146,28.71999931,166.7549133,63.28033447,230.1348572,88.05303192,172,61.40950394,55.27056503,159.2647705,236.8347931,105.5636902,40.78401184,96.29218292
-5/31/2018,77.56075287,65.09290314,156.3125153,24.5964241,79.99781799,56.71957779,36.78428268,73.37767029,83.16151428,20.00353241,550.7399902,97.67980194,15.3470068,100.799736,49.95798874,15.1130867,171.9398346,154.7685089,69.51217651,38.45999908,86.16941833,16.42464256,40.64160538,19.77000046,72.59999847,151.8199463,63.5,132.7400055,29.52853584,90.61192322,182.3896332,111.8112717,32.32515717,194.9502869,299.0720215,31.22579002,129.3300018,31.77000046,137.1389008,95.80191803,93.92111969,45.37170029,204.0399933,24.84443855,73.32531738,62.30389404,60.65207291,100.6176224,29.38129997,340.9617004,79.87129974,39.38679504,33.05672073,49.83007813,249.2799988,88.06999969,47.52250671,104.364006,91.17656708,103.6530075,202.5029907,173.1100006,79.86485291,60.01072693,158.750351,68.91999817,68.26999664,30.48830605,12.03240967,39.7667923,243.1795502,125.4455948,37.88999939,33.7881546,34.46646118,96.60909271,22.206604,76.44463348,1100,219.6971741,25.58452797,64.27591705,66.40595245,106.5639267,72.73117828,119.0503159,207.2687073,30.38999939,178.4561615,59.77771759,235.109436,86.85197449,191.7799988,58.2603035,54.69100952,167.9140167,215.9741364,129.3287354,39.33117676,95.85339355
-6/30/2018,77.56075287,65.09290314,156.3125153,24.5964241,79.99781799,56.71957779,36.78428268,73.37767029,83.16151428,20.00353241,550.7399902,97.67980194,15.3470068,100.799736,49.95798874,15.1130867,171.9398346,154.7685089,69.51217651,38.45999908,86.16941833,16.42464256,40.64160538,19.77000046,72.59999847,151.8199463,63.5,132.7400055,29.52853584,90.61192322,182.3896332,111.8112717,32.32515717,194.9502869,299.0720215,31.22579002,129.3300018,31.77000046,137.1389008,95.80191803,93.92111969,45.37170029,204.0399933,24.84443855,73.32531738,62.30389404,60.65207291,100.6176224,29.38129997,340.9617004,79.87129974,39.38679504,33.05672073,49.83007813,249.2799988,88.06999969,47.52250671,104.364006,91.17656708,103.6530075,202.5029907,173.1100006,79.86485291,60.01072693,158.750351,68.91999817,68.26999664,30.48830605,12.03240967,39.7667923,243.1795502,125.4455948,37.88999939,33.7881546,34.46646118,96.60909271,22.206604,76.44463348,1100,219.6971741,25.58452797,64.27591705,66.40595245,106.5639267,72.73117828,119.0503159,207.2687073,30.38999939,178.4561615,59.77771759,235.109436,86.85197449,191.7799988,58.2603035,54.69100952,167.9140167,215.9741364,129.3287354,39.33117676,95.85339355
-7/31/2018,82.67260742,71.99680328,157.048645,26.8085022,86.48177338,63.24529648,34.78462219,83.72770691,87.4369278,19.55117607,592.5100098,105.036026,16.54395103,103.7116623,57.05922318,14.96635818,188.1459503,158.5325928,76.94116211,37.31000137,93.06948853,16.08208084,44.46503448,24.54999924,75.48000336,155.3195801,69.86000061,135.4299927,27.89222717,91.64558411,185.7276459,123.1336899,33.27369308,215.0805969,335.4360962,35.89021301,137.1499939,33.52000046,141.1407928,109.8974686,89.38314819,46.48561096,188.3600006,26.58770943,75.83714294,64.38800049,62.55432892,108.6955566,31.52222824,344.9700623,79.56987762,43.36981201,27.62522125,56.03785324,244.6799927,89.43000031,44.83366013,118.4791565,91.48696899,103.2948303,192.2613525,171.3800049,77.83631897,61.86866379,161.5059662,74.68000031,66.54000092,30.52685928,12.6080761,35.61390305,240.641037,130.9043732,42.90999985,31.29141045,34.84298706,103.6856842,22.83830452,76.88406372,1227.219971,230.931015,23.69626999,69.19262695,72.95886993,106.5890198,78.9899826,131.6507721,233.5859833,33.61000061,200.2234039,64.78874969,247.381073,94.73270416,172.5800018,63.05078125,50.56047821,168.4554443,227.6779938,130.3558044,41.12384033,97.39141083
-8/31/2018,88.86766815,76.34365082,143.6633759,26.41962814,93.44718933,65.85691071,29.42657661,83.78227997,93.4256134,20.10204124,584.460022,108.068718,16.46951103,109.6061859,60.29633331,13.30342865,192.5683899,160.5797729,84.10103607,39.13000107,95.49878693,13.69413757,42.5006752,25.63999939,80.06999969,164.8144073,61.68999863,149.7599945,27.36355782,92.92978668,222.9515839,131.826828,35.45421982,229.8304138,344.0355835,33.01755142,152.6799927,34.52000046,143.5174408,107.0401382,90.79820251,47.36307144,191.5899963,27.48413277,72.09928131,60.98164749,64.77236176,118.1615982,32.41106033,333.529541,87.86965179,43.32273102,30.44654846,57.75475311,263.5100098,102.1399994,42.80514526,125.3749924,96.51681519,105.1502075,193.6302795,189.1199951,76.95734406,71.76994324,165.0478973,78.05000305,73.91000366,28.21082687,12.82623768,33.86655426,238.7618713,142.3084564,39.75999832,34.96694183,28.78144646,110.2171326,23.21758842,73.16490173,1231.800049,232.0666351,25.48573494,69.9587326,73.96214294,107.6231155,79.59928894,128.6785431,238.137619,35.56000137,208.9283447,66.1071701,262.2696533,97.6646347,175.7299957,62.19913483,51.94258118,175.6986084,239.5334015,128.2601318,40.9994278,103.7132568
-9/30/2018,88.86766815,76.34365082,143.6633759,26.41962814,93.44718933,65.85691071,29.42657661,83.78227997,93.4256134,20.10204124,584.460022,108.068718,16.46951103,109.6061859,60.29633331,13.30342865,192.5683899,160.5797729,84.10103607,39.13000107,95.49878693,13.69413757,42.5006752,25.63999939,80.06999969,164.8144073,61.68999863,149.7599945,27.36355782,92.92978668,222.9515839,131.826828,35.45421982,229.8304138,344.0355835,33.01755142,152.6799927,34.52000046,143.5174408,107.0401382,90.79820251,47.36307144,191.5899963,27.48413277,72.09928131,60.98164749,64.77236176,118.1615982,32.41106033,333.529541,87.86965179,43.32273102,30.44654846,57.75475311,263.5100098,102.1399994,42.80514526,125.3749924,96.51681519,105.1502075,193.6302795,189.1199951,76.95734406,71.76994324,165.0478973,78.05000305,73.91000366,28.21082687,12.82623768,33.86655426,238.7618713,142.3084564,39.75999832,34.96694183,28.78144646,110.2171326,23.21758842,73.16490173,1231.800049,232.0666351,25.48573494,69.9587326,73.96214294,107.6231155,79.59928894,128.6785431,238.137619,35.56000137,208.9283447,66.1071701,262.2696533,97.6646347,175.7299957,62.19913483,51.94258118,175.6986084,239.5334015,128.2601318,40.9994278,103.7132568
-10/31/2018,71.20167542,67.71237946,111.7720795,25.67808914,97.75592804,71.15911865,29.46146584,75.77589417,87.48067474,18.01394463,546.8200073,104.0286255,16.03157616,104.2050781,48.29608154,13.1498642,185.8027954,150.0291138,80.38137054,31.25,94.32457733,11.39800072,46.04534912,29.30999947,79.30000305,155.0569611,49.97000122,147.5200043,24.1348629,96.85569,214.3618469,99.81723022,35.359375,225.3941193,275.9222717,31.30067635,137.2400055,27.27000046,154.3775177,108.2820206,75.08502197,47.80827332,124.7300034,28.47160149,66.0219574,60.6948204,62.60270691,101.4963531,27.93366432,345.273468,85.94564056,41.70214081,27.76432991,48.51662445,245.7599945,89.52999878,38.54126358,120.2059784,86.98104858,83.97529602,170.6568756,175.2799988,70.56240845,69.52864838,167.3766327,67.91000366,64.81999969,26.07881927,14.01645374,34.74800873,216.2248688,140.3776093,38.99000168,35.78742599,24.06523895,104.8009644,23.60731125,62.0635376,1090.579956,219.9270477,25.24104691,72.17463684,76.38263702,89.65029907,68.6177597,123.679306,232.8717651,36.13999939,178.0840607,76.91613007,256.1850891,104.1063156,151.7899933,66.26256561,56.62664413,143.5829163,214.0682068,125.7415695,41.45168686,100.895607
-11/30/2018,61.63056564,62.336689,109.5584412,26.89323044,95.19213104,76.69832611,30.81448364,74.32219696,94.98987579,17.91025352,636.6599731,109.9217453,16.07867241,110.368988,53.71586227,13.20900822,202.1039276,156.3665771,68.76932526,33.86000061,99.9019928,11.68172741,48.85206604,27.93000031,79.12999725,161.8447876,48.06999969,153.1900024,26.05033302,94.02479553,175.519989,101.4195938,36.22901917,228.5485687,306.5484314,31.23678207,142.7599945,27.84000015,163.2044678,117.4934158,78.06139374,47.72996521,128.0599976,28.64955139,69.96230316,57.59646606,68.6644516,109.5788498,30.99988747,338.9502869,87.21595001,40.28350449,25.15579796,51.31972122,250.8899994,91.94000244,38.87537766,128.7290802,87.73880005,87.77568054,170.9493561,171.9700012,75.04936981,77.02993774,177.4191437,66.06999969,64.25,26.35251045,14.89128017,36.03955078,224.7231445,143.6317749,44.40999985,38.00251007,23.08711052,109.2742615,24.57961273,65.02466583,1109.650024,186.8381958,25.91748238,75.15876007,79.38394165,96.42984009,74.34799957,119.4163208,248.7188416,37.66999817,185.5765686,82.08174896,276.6809082,105.9295197,140.6100006,52.82670212,65.1864624,157.4632416,212.0005341,108.0750809,43.77598953,110.2652435
-12/31/2018,52.13723755,51.49493408,96.07069397,27.10445976,91.30091858,74.38368225,33.29081345,65.66993713,89.09342194,15.90275955,565.5800171,104.9457779,14.48681736,112.422554,45.85391617,11.38537693,188.9247284,156.6417542,64.04965973,27.39999962,93.14393616,10.08698559,45.89573288,23.07999992,73.48999786,138.7170563,36.68999863,127.8399963,25.6398468,75.51846313,155.0371094,91.99578094,35.96086884,201.3041992,275.624115,27.50611877,136.9700012,23.72999954,143.6823883,107.2965698,72.85274506,44.19622803,116.9599991,26.8926487,62.93343353,50.5832634,64.13746643,95.40375519,30.10253716,315.2367249,72.9906311,37.07491302,22.71574211,49.89897156,226.2400055,84.23999786,34.12154007,113.3263626,73.95378876,79.12448883,150.3629913,162.0299988,71.33366394,62.93019104,169.7154694,62.72999954,63.59000015,23.81758308,13.90109158,32.10009384,158.7968903,128.477829,41.09999847,39.15949631,18.24407196,100.0900574,21.83443451,57.46208191,1044.959961,163.675705,24.34381866,72.26158905,75.71707153,91.26309967,66.34693909,111.3688889,223.2017212,35.34000015,166.3731842,66.24124908,244.9770966,104.8340378,131.0899963,54.80021286,62.91978073,138.6254578,187.219574,100.9913101,40.7476387,93.61791992
-1/31/2019,62.87455368,57.60120773,103.4751434,29.68720818,93.92773438,72.45619965,32.77198792,77.48021698,86.57616425,17.22878456,638.1599731,113.0898666,17.23988152,93.96025085,55.99544525,12.74570751,181.5878296,160.8893433,70.74634552,29.95000076,96.8301239,11.43751717,46.65177917,26.64999962,82.93000031,151.0531464,44.08000183,135.8899994,27.43532562,79.1047821,163.5879974,105.7166061,37.54104233,212.0952148,288.3432922,24.29183769,151.9700012,26.21999931,154.8277893,109.4234695,79.17707062,49.3635788,128.7899933,29.7309494,67.90276337,61.04089737,70.50166321,117.1205826,34.55150604,376.9351196,81.79070282,42.82214355,29.08699989,47.76699829,247.8200073,93.34999847,40.171875,115.1685104,78.84555817,82.74960327,161.5507507,160.9499969,73.99626923,63.43881989,174.7536011,58.77999878,80.58999634,28.90312004,15.88963795,37.4453125,174.7819214,137.0221252,44.40000153,40.4851532,21.72561264,102.9083939,24.44232559,62.5173912,1125.890015,194.0103302,22.63581467,73.25188446,79.33568573,97.9757843,73.68123627,117.8938217,245.0242157,38.15000153,185.705307,70.05110168,265.706543,103.7776642,166.6900024,54.99327469,66.57382202,156.908905,203.0974731,113.3687515,43.24539566,101.2789459
-2/28/2019,64.58074188,66.93563843,108.3963699,29.20735931,97.0249939,79.13426971,32.78159332,80.41667175,88.64286804,18.70744514,680.9099731,114.7225571,18.2495079,101.5227051,55.28514862,13.12029171,185.8965149,177.3217926,71.02148438,26.38999939,105.5217514,12.67559719,43.94747162,27.25,84.69000244,158.7558289,44.58000183,142.3000031,26.63623619,89.45218658,170.9129181,108.1762924,39.41254044,216.7405396,298.8406372,22.89713478,163.6499939,27.70000076,169.9904633,113.2185822,81.22289276,51.23080826,136.1199951,30.53782272,76.15660095,61.08843231,71.59960175,115.5888901,32.89823914,432.2117615,82.10191345,45.41421127,31.7977562,49.98264313,262.5,101.6800003,40.05162048,140.9880676,82.18682098,81.36995697,182.8672943,168.1399994,82.7088623,55.967453,184.5125427,62.09999847,86.23000336,26.26217651,16.70399475,37.88674927,178.1580811,149.9463348,47.15000153,41.24715424,21.65394211,110.869133,24.11904144,61.92760086,1126.550049,193.5050812,23.17316628,79.13578796,84.91030884,102.9388046,77.0826416,121.9076538,258.8877258,40.11999893,204.6115875,69.43562317,238.1918488,108.9682541,161.4499969,57.8119545,69.0033493,171.875061,206.8148346,122.1832733,44.60684586,106.2492065
-3/31/2019,64.58074188,66.93563843,108.3963699,29.20735931,97.0249939,79.13426971,32.78159332,80.41667175,88.64286804,18.70744514,680.9099731,114.7225571,18.2495079,101.5227051,55.28514862,13.12029171,185.8965149,177.3217926,71.02148438,26.38999939,105.5217514,12.67559719,43.94747162,27.25,84.69000244,158.7558289,44.58000183,142.3000031,26.63623619,89.45218658,170.9129181,108.1762924,39.41254044,216.7405396,298.8406372,22.89713478,163.6499939,27.70000076,169.9904633,113.2185822,81.22289276,51.23080826,136.1199951,30.53782272,76.15660095,61.08843231,71.59960175,115.5888901,32.89823914,432.2117615,82.10191345,45.41421127,31.7977562,49.98264313,262.5,101.6800003,40.05162048,140.9880676,82.18682098,81.36995697,182.8672943,168.1399994,82.7088623,55.967453,184.5125427,62.09999847,86.23000336,26.26217651,16.70399475,37.88674927,178.1580811,149.9463348,47.15000153,41.24715424,21.65394211,110.869133,24.11904144,61.92760086,1126.550049,193.5050812,23.17316628,79.13578796,84.91030884,102.9388046,77.0826416,121.9076538,258.8877258,40.11999893,204.6115875,69.43562317,238.1918488,108.9682541,161.4499969,57.8119545,69.0033493,171.875061,206.8148346,122.1832733,44.60684586,106.2492065
-4/30/2019,64.65377808,72.8702774,109.6918564,30.0407486,101.3409424,77.14263916,30.71038818,87.46104431,87.46434021,18.54973602,745.2600098,122.6175995,19.16257858,103.5842819,53.65901947,12.40532207,175.3733521,202.6438141,75.69497681,26.98999977,100.1772308,12.1411314,47.96834946,28.76000023,87.23999786,181.1880493,58.38999939,158.9700012,31.16069984,73.86421967,198.0773621,124.8647766,40.65052795,243.2856445,276.5136414,22.09021187,165.3500061,30.10000038,178.9641571,125.3687286,90.44984436,54.619133,136.25,30.00906372,77.9799881,65.38808441,74.81989288,118.6846085,30.69937325,371.0384216,73.68473816,50.0744133,33.80644226,45.31880569,289.25,121.0800018,41.19566727,143.3308105,91.28263092,84.94169617,175.0396118,156.8999939,86.58055115,53.13334656,191.1177216,77.86000061,76.80000305,26.27099228,16.72996902,37.7490921,187.1891327,161.9160309,46.38000107,40.7723732,26.4539814,129.2467194,25.36319542,55.78352356,1198.959961,202.5753326,26.38136292,82.42818451,94.68153381,114.6651306,80.73804474,128.6903076,276.9239197,37.11999893,215.0501404,52.24984741,230.0688019,122.9191055,193.3999939,62.15393448,76.29064178,195.2060699,219.8216095,129.0839996,46.2790947,116.0171585
-5/31/2019,46.75449753,61.37320328,83.18334961,27.82862473,100.492363,77.63269043,32.71753693,80.55620575,91.17723083,17.46027565,723.0900269,126.7412415,19.23973083,113.4829254,47.09882736,11.57101631,164.4346924,200.4774475,79.36608887,16.79999924,96.62110901,9.576798439,48.03678894,25.63999939,85.86000061,176.6253662,46.38000107,151.3000031,30.70507813,62.29157257,173.4736023,120.2369461,40.24631119,238.0311127,257.9572144,19.30312729,151.4100037,25.64999962,178.8946228,125.3197708,81.56982422,49.94989777,135.5500031,28.61485863,72.44662476,61.23936462,74.96674347,119.4893265,28.96969986,337.5218201,77.13782501,48.09944916,32.99524689,44.28417206,270.8999939,116.4400024,35.15464401,148.3158569,84.81476593,71.48271942,171.993988,132.0800018,89.16183472,51.16942596,196.055191,78.27999878,78.62999725,24.48539352,15.44004154,32.3120575,152.4307861,157.7103119,44.00999832,33.71123886,21.01973343,122.8514862,24.59657288,47.15261078,1106.5,180.3350677,25.45059967,82.99990845,96.70943451,102.178093,73.25239563,114.2930222,266.4738159,38.40999985,219.6950073,48.53081894,238.6863861,130.636734,177.4700012,57.86543655,75.04615021,182.0457916,203.4109192,103.1357346,46.5044632,113.5232315
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diff --git a/portfolio.csv b/portfolio.csv
index c5b695a..1f9f196 100644
--- a/portfolio.csv
+++ b/portfolio.csv
@@ -1,7 +1,7 @@
 ticker,name,sector,sharpe ratio,FFM returns,P/E ratio,EPS,beta,mkt cap,shares
 GPC,Genuine Parts,Consumer Discretionary,2.9244641954801547,0.074228025,17.71,5.45,0.89,14016415887,145293000
 GIS,General Mills,Consumer Staples,2.6412807761987938,0.063146888,15.34,3.48,0.73,32242795100,604817000
-COG,Cabot Oil & Gas,Energy,1.9529827367707384,-0.050016632000000005,7.8,1.9,0.47,6037284157,407925000
+OKE,ONEOK,Energy,0.9173258155980414,0.230147782,25.56,3.01,1.11,31799253894,413085000
 SYF,Synchrony Financial,Financials,2.4933359586834767,0.091836098,6.07,5.56,1.21,20704848750,613477000
 AMGN,Amgen Inc,Health Care,1.8616491950461436,0.151748658,17.36,12.88,1.12,131810065840,589807000
 LUV,Southwest Airlines,Industrials,1.7265757683369565,0.10783286199999999,13.77,4.21,1.47,29987649751,517296000
diff --git a/selection_criteria.ipynb b/selection_criteria.ipynb
index c335771..e0f0924 100644
--- a/selection_criteria.ipynb
+++ b/selection_criteria.ipynb
@@ -2,20 +2,21 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
     "# importing libraries\n",
     "from pathlib import Path \n",
     "import pandas as pd\n",
+    "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
     "%matplotlib inline"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -127,7 +128,7 @@
        "[505 rows x 2 columns]"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -141,7 +142,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -240,7 +241,7 @@
        "[100 rows x 1 columns]"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -254,7 +255,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -353,7 +354,7 @@
        "[100 rows x 1 columns]"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -367,7 +368,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -518,7 +519,7 @@
        "[100 rows x 5 columns]"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -532,7 +533,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -760,7 +761,7 @@
        "[92 rows x 10 columns]"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -776,7 +777,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -785,7 +786,7 @@
        "Text(0, 0.5, 'Sharpe Ratio')"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -816,7 +817,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -825,7 +826,7 @@
        "(0, 100)"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -857,7 +858,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -866,7 +867,7 @@
        "Text(0, 0.5, 'FFM Returns')"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -893,7 +894,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -906,7 +907,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -1005,7 +1006,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -1326,7 +1327,7 @@
        "15   258777000  "
       ]
      },
-     "execution_count": 13,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1339,7 +1340,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -1506,7 +1507,7 @@
        "27     0.192130      37.75  8.43  0.90  140615987901   441758000  "
       ]
      },
-     "execution_count": 14,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1519,7 +1520,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -1626,7 +1627,7 @@
        "69  3.01  1.11  31799253894   413085000  "
       ]
      },
-     "execution_count": 15,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1634,12 +1635,12 @@
    "source": [
     "energy_df\n",
     "\n",
-    "# COG - decent sharpe, good p/e"
+    "# OKE - only one with positive returns"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -1851,7 +1852,7 @@
        "62     0.234858      37.43   7.42  1.21   52148688479  187700000  "
       ]
      },
-     "execution_count": 16,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1864,7 +1865,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -2106,7 +2107,7 @@
        "77      56.31   3.14  0.48   25539363082   144617000  "
       ]
      },
-     "execution_count": 17,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2119,7 +2120,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -2271,7 +2272,7 @@
        "25     0.285973      35.38   8.51  0.99  31216601386  103751000  "
       ]
      },
-     "execution_count": 18,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2284,7 +2285,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -2556,7 +2557,7 @@
        "1      0.329761      63.17   6.01  1.09   185174936969   487726000  "
       ]
      },
-     "execution_count": 19,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2569,7 +2570,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -2706,7 +2707,7 @@
        "39      27.41  3.85  1.54  13670494208   129615000  "
       ]
      },
-     "execution_count": 20,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2719,7 +2720,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -2826,7 +2827,7 @@
        "28     0.163975      83.64  1.98  0.30  69005081855  415768000  "
       ]
      },
-     "execution_count": 21,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2839,7 +2840,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -2991,7 +2992,7 @@
        "67      10.31  3.89  0.71   10078855985  251594000  "
       ]
      },
-     "execution_count": 22,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3004,7 +3005,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -3069,16 +3070,16 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>COG</td>\n",
-       "      <td>Cabot Oil &amp; Gas</td>\n",
+       "      <td>OKE</td>\n",
+       "      <td>ONEOK</td>\n",
        "      <td>Energy</td>\n",
-       "      <td>1.952983</td>\n",
-       "      <td>-0.050017</td>\n",
-       "      <td>7.80</td>\n",
-       "      <td>1.90</td>\n",
-       "      <td>0.47</td>\n",
-       "      <td>6037284157</td>\n",
-       "      <td>407925000</td>\n",
+       "      <td>0.917326</td>\n",
+       "      <td>0.230148</td>\n",
+       "      <td>25.56</td>\n",
+       "      <td>3.01</td>\n",
+       "      <td>1.11</td>\n",
+       "      <td>31799253894</td>\n",
+       "      <td>413085000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
@@ -3179,7 +3180,7 @@
        "  ticker                   name                  sector  sharpe ratio  \\\n",
        "0    GPC          Genuine Parts  Consumer Discretionary      2.924464   \n",
        "1    GIS          General Mills        Consumer Staples      2.641281   \n",
-       "2    COG        Cabot Oil & Gas                  Energy      1.952983   \n",
+       "2    OKE                  ONEOK                  Energy      0.917326   \n",
        "3    SYF    Synchrony Financial              Financials      2.493336   \n",
        "4   AMGN              Amgen Inc             Health Care      1.861649   \n",
        "5    LUV     Southwest Airlines             Industrials      1.726576   \n",
@@ -3191,7 +3192,7 @@
        "   FFM returns  P/E ratio    EPS  beta        mkt cap     shares  \n",
        "0     0.074228      17.71   5.45  0.89    14016415887  145293000  \n",
        "1     0.063147      15.34   3.48  0.73    32242795100  604817000  \n",
-       "2    -0.050017       7.80   1.90  0.47     6037284157  407925000  \n",
+       "2     0.230148      25.56   3.01  1.11    31799253894  413085000  \n",
        "3     0.091836       6.07   5.56  1.21    20704848750  613477000  \n",
        "4     0.151749      17.36  12.88  1.12   131810065840  589807000  \n",
        "5     0.107833      13.77   4.21  1.47    29987649751  517296000  \n",
@@ -3201,14 +3202,14 @@
        "9     0.098239      14.38   2.46  0.51    25573676437  723033000  "
       ]
      },
-     "execution_count": 23,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# creating portfolio of best pick from each sector\n",
-    "portfolio_df = merged_df.loc[[44,42,20,82,10,80,7,55,49,73]]\n",
+    "portfolio_df = merged_df.loc[[44,42,69,82,10,80,7,55,49,73]]\n",
     "portfolio_df.sort_values(by = 'sector', inplace=True)\n",
     "portfolio_df.reset_index(inplace=True)\n",
     "portfolio_df.drop(['index'], axis=1, inplace=True)\n",
@@ -3217,7 +3218,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -3226,13 +3227,13 @@
        "Text(0, 0.5, 'Sharpe Ratio')"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1800x720 with 1 Axes>"
       ]
@@ -3257,7 +3258,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
@@ -3266,13 +3267,13 @@
        "Text(0, 0.5, 'P/E Ratio')"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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\n",
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5qNOqO5eubACAFyff6gMA9KNa659KKZ9McmZagerEUsrEJNck+XtaPXEPTrJhe5e/JFkg0FvCcz9aSrkryZZJdi+lfCPJzzNvhurztdafLsFx55RS3pPkprQepPcfSXYtpXwvyYNptX84IK0HziWtvr3vbYfL/eErafWDfl2SLZL8vpRyXlozYAcn2SmtoHD59vhv1lp/0k+19FZHO5AHa61TFmO/lbr70qMHz9Rar1nMupbUOUk+nWT1tGZZf67WOrXT9v9KMrb9/oz2TObrksxIsnGS96U1+/q6tP4N11nIua7v9P6r7S8o/pBkdnvdX2qtd/e28Frr99qf6X5J1ktyeyllQpJfp/XXDq9J63d0lfYuVyf59nyHGZrWXxt8spRya1oz/+9J8kRaPbk3SfLuJOu2x0+qtd7S2xoBAF5KBNYAAP2s1npWewLy15KskGSf9mt+v02yV631sT48/fFptRdZLsmH268Oc7KE/z1Ya51SStk9yQ/Smhk+pv2a32NJ/r3WeuOSnKeXtcwupbwxrRncb0kyPN23KqlJTk9ydH/Vshje2v65uA9bXDvJxF6OnZFkjcU8/hKptT5VSjkjrR7WHbOs/73T9omllFMy799l7/arsxvb+yx05nGt9bZSyg/SCpjXSXLqfEPOS3LoYl7CgWl9kfP+JC9L8pH2a37fTzKumz7cHcslyXbtV0+uT6t2AAC6oSUIAMAyUGs9K62ZpKekFcg9kdbM44eSXJVkXJJtaq0P9PF5f5TWgw8vSauVwqyF77FYx74prRnin0zyy7R6ST+XVkj9qyTHJXllrfVnfXXOhdTyj1rrnmkF1pek1YJkVloh5L1Jzk6yba31E51bOQyEUsq2SdZvL76g24HM578yb/b+u0opm3XeWGv9jyR7pvXXBTPSulceTivAPSTJ2MXoK/7vST6a5Bdp3W+zFz584Wqtz9VaD07rrwLOT/LHtPpu/zOt35vvtOs7oNa6wO9QrfVPSUamNRP7u0l+l2RmWl8KPZXWPfi9JG+tte5Wa318aeoFAHgxKwt/SDcAANCXSiknpTUD+ckka/RjqxQAAHjBMcMaAACWrY7+1T8VVgMAQFcCawAAWEZKKf+SZHR78cXUDgQAAPqEliAAAAAAADSCGdYAAAAAADSCwBoAAAAAgEYQWAMAAAAA0AgCawAAAAAAGkFgDQAAAABAIwisAQAAAABoBIE1AAAAAACNILAGAAAAAKARBNYAAAAAADSCwBoAAAAAgEYQWAMAAAAA0AgCawAAAAAAGkFgDQAAAABAIwisAQAAAABoBIE1AAAAAACNILAGAAAAAKARBNYAAAAAADSCwBoAAAAAgEYQWAMAAAAA0AgCawAAAAAAGkFgDQAAAABAIwisAQAAAABoBIE1AAAAAACNILAGAAAAAKARBNYAAAAAADSCwBoAAAAAgEYQWAMAAAAA0AgCawAAAAAAGkFgDQAAAABAIwisAQAAAABoBIE1AAAAAACNILAGAAAAAKARBNYAAAAAADSCwBoAAAAAgEYQWAMAAAAA0AgCawAAAAAAGkFgDQAAAABAIwisAQAAAABoBIE1AAAAAACNILAGAAAAAKARBNYAAAAAADSCwBoAAAAAgEYQWAMAAAAA0AgCawAAAAAAGkFgDQAAAABAIwwe6AL6yhprrFFHjRo10GUAAAAAALAQU6ZMeazWOqK7bS+awHrUqFGZPHnyQJcBAAAAAMBClFIe6GmbliAAAAAAADSCwBoAAAAAgEYQWAMAAAAA0Agvmh7WAAAAAAD95bnnnsv06dMza9asgS7lBWPo0KFZf/31M2TIkF7vI7AGAAAAAFiE6dOnZ5VVVsmoUaNSShnochqv1poZM2Zk+vTp2XDDDXu9n5YgAAAAAACLMGvWrKy++urC6l4qpWT11Vdf7BnpAmsAAAAAgF4QVi+eJfm8BNYAAAAAAC8AgwYNyujRo7PFFltkv/32y9NPPz132wc/+MHcfPPNGTduXDbccMOMHj06o0ePzutf//olPt8TTzyRb3zjG3OXH3rooey7775LdQ2LUmqt/XqCZWXMmDF18uTJA10GAAAAAPAiNHXq1Gy66aZzl0eNv6pPjz/tS3sucszKK6+cJ598Mkly4IEHZtttt81RRx2VJBk9enSmTJmSQw45JG9961t7HSzPnj07gwd3/6jDadOm5a1vfWt+97vf9fIqFjT/55YkpZQptdYx3Y03wxoAAAAA4AVmp512yh//+MckrVB44403zqBBg3q174QJE7LffvvlbW97W/bYY488+eST+bd/+7dss8022XLLLXPFFVckScaPH58//elPGT16dI455phMmzYtW2yxRZJWT+/3v//92XLLLbP11ltn0qRJfXJd3UfnAAAAAAA00uzZs3PNNdfkTW96U5J0eZ8kxxxzTD7/+c8nSTbffPNcfPHFCxzjlltuyW9/+9sMHz48s2fPzsSJE/Pyl788jz32WLbffvvstdde+dKXvpTf/e53ueOOO5K0Zlx3OOuss5Ikd911V+65557sscceuffeezN06NClujaBNQAAAADAC8A///nPjB49OklrhvUhhxySJLn22mtzwQUXzB13yimnLLIlyO67757hw4cnSWqtOe644/LLX/4yyy23XB588MH89a9/Xej+N910Uw4//PAkySabbJKRI0fm3nvvzb/+678u8fUlAmsAAAAAgBeEFVdcce5s5w5PP/10nnjiiay77rqLdayVVlpp7vuLL744jz76aKZMmZIhQ4Zk1KhRmTVr1kL3769nI+phDQAAAADwAjVp0qSMHTt2qY4xc+bMrLnmmhkyZEgmTZqUBx54IEmyyiqr5B//+Ee3++y8885zW43ce++9+fOf/5xXv/rVS1VHIrAGAAAAAHjBmr9/ddLqYT169Oi5r2effXahxzjwwAMzefLkjBkzJhdffHE22WSTJMnqq6+eHXbYIVtssUWOOeaYLvt85CMfyZw5c7Lllltm//33z4QJE7LCCiss9fWU/pq6vayNGTOmTp48eaDLAAAAAABehKZOnZpNN910oMtYwDbbbJPf/OY3GTJkyECX0q3uPrdSypRa65juxuthDQAAAADwAnXbbbcNdAl9SksQAAAAAAAaQWANAAAAAEAjCKwBAAAAAHrhxfI8wGVlST4vgTUAAAAAwCIMHTo0M2bMEFr3Uq01M2bMyNChQxdrPw9dBAAAAABYhPXXXz/Tp0/Po48+OtClvGAMHTo066+//mLtI7AGAAAAAFiEIUOGZMMNNxzoMl70tAQBAAAAAKARzLAGAACgT40af9VAl9BI076050CXAACNZ4Y1AAAAAACNILAGAAAAAKARBNYAAAAAADSCwBoAAAAAgEYQWAMAAAAA0AgCawAAAAAAGkFgDQAAAABAIwisAQAAAABoBIE1AAAAAACNILAGAAAAAKARBjSwLqUMLaX8bynlzlLK3aWUk9rrNyyl/KaU8odSyvdLKcsPZJ0AAAAAAPS/gZ5h/UySXWutWyUZneRNpZTtk3w5yddrra9K8niSQwawRgAAAAAAloEBDaxry5PtxSHtV02ya5L/aa+/MMneA1AeAAAAAADL0EDPsE4pZVAp5Y4kjyS5LsmfkjxRa53dHjI9yXoDVR8AAAAAAMvGgAfWtdY5tdbRSdZPsl2STbsb1t2+pZQPlFIml1ImP/roo/1ZJgAAAAAA/WzAA+sOtdYnktyQZPskw0opg9ub1k/yUA/7fLvWOqbWOmbEiBHLplAAAAAAAPrFgAbWpZQRpZRh7fcrJtktydQkk5Ls2x72viRXDEyFAAAAAAAsK4MXPaRfrZPkwlLKoLTC8/+utf64lPL7JJeWUj6f5PYk5w1kkQAAAAAA9L8BDaxrrb9NsnU36+9Lq581AAAAAAAvEY3pYQ0AAAAAwEubwBoAAAAAgEYQWAMAAAAA0AgCawAAAAAAGkFgDQAAAABAIwisAQAAAABoBIE1AAAAAACNILAGAAAAAKARBNYAAAAAADSCwBoAAAAAgEYQWAMAAAAA0AgCawAAAAAAGkFgDQAAAABAIwisAQAAAABoBIE1AAAAAACNILAGAAAAAKARBNYAAAAAADSCwBoAAAAAgEYQWAMAAAAA0AgCawAAAAAAGkFgDQAAAABAIwisAQAAAABoBIE1AAAAAACNILAGAAAAAKARBNYAAAAAADSCwBoAAAAAgEYQWAMAAAAA0AgCawAAAAAAGkFgDQAAAABAIwisAQAAAABoBIE1AAAAAACNILAGAAAAAKARBNYAAAAAADSCwBoAAAAAgEYQWAMAAAAA0AgCawAAAAAAGkFgDQAAAABAIwisAQAAAABoBIE1AAAAAACNILAGAAAAAKARBNYAAAAAADSCwBoAAAAAgEYQWAMAAAAA0AgCawAAAAAAGkFgDQAAAABAIwisAQAAAABoBIE1AAAAAACNILCmR6NGjcqoUaOW+XnHjRuXUkqmTZu2zM/dX6ZNm5ZSSsaNGzfQpdBAEyZMSCklEyZMGOhSAAAAAAaUwPolopSSUspAl9EvOgLuUko++9nP9jjuwgsvnDvuDW94w7IrkLmBfefX4MGDs9Zaa2XPPffMNddc0+O+t956a0opOfXUU5PMC3cX9urtFy3dHWuFFVbIyJEjc+CBB+bOO+/si8vPDTfckFJKTjzxxD45HgAAAMCL1eCBLgD6yuDBg3P++efnM5/5TAYNGrTA9nPOOSeDBw/O7Nmzl3lt6623XqZOnZpVV111mZ+7SVZdddUceeSRSZJZs2blzjvvzNVXX52rr746p59+eo444ogF9pk4cWKSZO+99+6yfquttlpgXYdhw4YtVl2dj/X3v/89N998c773ve/lsssuy/XXX58ddthhsY63uPbZZ59sv/32WWeddfr1PAAAAABNJ7DmReOtb31rfvjDH+YnP/lJ9txzzy7bpk6dmptvvjn77LPP3AB0WRoyZEg22WSTZX7ephk2bNgCs4wvuOCCHHzwwTnuuONy6KGH5mUve1mX7RMnTsxWW22VV7ziFV3Wjx49us9mLHd3rA996EM5++yz8+lPfzqTJk3qk/P0ZNVVV33Jf5kBAAAAkGgJ8pJXa82ZZ56ZzTffPEOHDs16662Xj33sY5k5c+ZC97vkkksyduzYrLbaahk6dGg23XTTfP7zn88zzzyzwNgf/vCHec973pONN944K620UlZeeeVsu+22OeOMM/L888/32bUceOCBWXHFFXPOOecssK1j3aGHHtrtvjNnzswpp5ySXXfdNeuvv36WX375jBgxInvttVd+/etfLzD+iCOOSCklRx999ALbzjvvvJRSsvvuu8+9vp56WHe0M7n//vtz5plnZrPNNsvQoUMzatSonHzyyam1Jkl+8IMfZLvttstKK62UNddcMx/72Mcya9asLsdaVJ/sN7zhDQu0hencqmLy5Ml505velFVXXTWrrbZa3vnOd+Yvf/lLkuS+++7LAQcckBEjRmTFFVfM2LFj+6xdxrhx47LSSivlqaeeyt13391l2z333JN77rkn++yzT5+ca3EccsghSVotSeZ37733Zvz48RkzZkxGjBgxt43IBz7wgUyfPr3L2HHjxmXs2LFJkpNOOqlL+5EbbrghycJ7WE+ZMiXvfOc7s+aaa849z0c+8pE8/PDDfXvBAAAAAA1ghvVL3JFHHpkzzjgj66yzTj7wgQ9kyJAhueKKK/Kb3/wmzz77bJZffvkF9jnkkENy/vnnZ/3118873vGODBs2LL/+9a9zwgkn5Prrr891112XwYPn3Vrjx4/Pcsstl9e+9rVZb731MnPmzPz85z/Pxz/+8dx666357ne/2yfXMmzYsOy333753ve+l4cffnhue4Vnnnkm3/nOd7LLLrtk44037nbfqVOn5vjjj8/OO++cPffcM6uttlr+/Oc/58orr8w111yTH/3oR3nTm940d/xXv/rV/OpXv8rXv/717LrrrnNndP/+97/PEUcckbXWWisXXXRRlluud98JffKTn8wNN9yQt73tbdljjz1y5ZVX5vjjj8+zzz6b4cOHZ/z48dl7772z00475brrrstZZ52VOXPm5Jvf/OZSfmott9uPK2EAACAASURBVN56a7785S9nl112yWGHHZa77rorl19+ee66665ceeWV2XHHHbPJJpvkoIMOygMPPJDLL788u+++e+67776svPLKfVJDkgUC9csvvzxJ8o53vKPPztFbHV8WDBkyZIFtl19+eb71rW9l7Nixef3rX5/ll18+d999d84999z86Ec/yuTJk7PeeuslmdfK5MILL8wuu+zSpX/6onpt//jHP8473/nO1Fqz7777ZuTIkZkyZUq++c1v5oorrsjNN988IA9GBQAAAOgvAuuXsF/96lc544wzstFGG+V///d/M3z48CTJF77whYwdOzYPP/xwRo4c2WWfCRMm5Pzzz88+++yTiy++OCuuuOLcbSeeeGJOOumknHXWWfn4xz8+d/1VV12VjTbaqMtxnn/++bz//e/Pd77znXzsYx/La1/72j65psMOOyzf+c53MmHChBx77LFJWi0lZsyYkcMOO6zH/TbddNM89NBDWWONNbqsnz59erbbbrt84hOf6BJYL7/88rn00kuzzTbbZNy4cbnjjjsyfPjwvOtd78qsWbNyxRVXZK211up13VOmTMlvf/vbuSHniSeemFe+8pU55ZRT8rKXvSxTpkzJpptumqQVwG+99dY5//zzc9JJJ2XNNdfs9Xl6cvXVV+eiiy7KgQceOHddxxcTr3/963P00Ufn+OOPn7vtc5/7XD7zmc/kvPPO6/JvvSQuuOCCPPXUU1lppZWy+eabd9k2ceLEbLTRRtlyyy0X2O+OO+7osSXI9ttv3+Xfa0l0zMrfcccdF9j23ve+N5/4xCeywgordFn/05/+NG9+85vz+c9/fu6XCXvvvXeGDRuWCy+8MG94wxt63cbkySefzLhx4zJ79uzccMMN2WmnneZu+/KXv5zx48fnAx/4QH76058u4RUCAAAANI+WIC9hF1xwQZLk+OOPnxtWJ8nQoUPzxS9+sdt9Tj/99LkPN+wcVifJCSeckNVXXz0XX3xxl/Xzh9VJstxyy80NOq+99tqluo7Odtxxx2y66aY599xz586QPeecc+a2uOjJqquuukBYnSTrr79+9t1339xzzz3585//3GXbK1/5ynz729/OY489lne/+9356Ec/mrvvvjvHHntsdtttt8Wq+4QTTpgbViet2eJ77bVXnn766Xz4wx+eG1YnyQorrJD9998/zz77bKZOnbpY5+nJjjvu2CWsTpL3ve99SVqfzfjx47tsO+igg5K0QuPF8cQTT+TEE0/MiSeemPHjx+ctb3nL3NYbJ598cpd76i9/+UsmT57cYzuQO++8MyeddFK3r5/85CeLVVdH+H3iiSfmqKOOymte85qce+65WXfddfO1r31tgfHrrbfeAmF1kuyxxx7ZfPPN++SevuKKKzJjxozsv//+XcLqJDn66KMzatSoXHfddQvclwAAAAAvZGZYv4TddtttSZJddtllgW077bRTl7YeSfL000/nzjvvzBprrJHTTjut22OusMIKC4SoM2bMyCmnnJKrr7469913X5566qku2x988MGluYwFHHrooTn66KPz85//PCNHjsykSZNy+OGHZ+jQoQvd7+abb87pp5+eW265JY888kieffbZBercYIMNuqw74IADcv311+fcc8/NL3/5y+y444456aSTFrvmMWPGLLBu3XXXTZJsu+22C2zrCLfn75e8pBZ2/tGjR2fQoEF9cv6ZM2fO/XwGDRqU4cOH581vfnM+9rGP5S1veUuXsR0Px+wpsH7f+97Xbc/nJXHnnXcu0JN7gw02yI033rjAv3nSahdy8cUXZ8KECbnzzjvz+OOPZ86cOXO3d9dKZ3F1/H7uuuuuC2wbPHhwdt5550ybNi233357tzUCAAAAvBAJrF/COh6s2F3rikGDBmX11Vfvsu7xxx9PrTWPPvpor0PZJ554Iq95zWty//33Z7vttstBBx2U4cOHZ/DgwXniiSdy+umnd/ugxqVx0EEH5bjjjsu5556bkSNHpta60HYgSSsc3XfffTN06NDsvvvu2WijjbLSSitlueWWyw033JBf/OIXPda577775txzz02SHH744QuEu72x6qqrLrCu4wuDhW177rnnFvtcA3n+kSNHZtq0ab0aO3HixKy99tp53etet1jnWBId4XetNY888kjOO++8fPrTn87b3va23HLLLXnZy17WZfxRRx2V0047Leuss07e+MY3Zr311ps7O3zChAl54IEHlrqmjt/Pjl7s8+tY/8QTTyz1uQAAAACaQmD9EtYRRP71r3/NK17xii7b5syZkxkzZnRpU9Exfuutt547+3NRzj333Nx///357Gc/u0Dv3ltuuSWnn376UlxB99ZYY43ss88+mThxYl7+8pfnda97XbbYYouF7nPCCSdk+eWXz+TJk7u030iSD37wg/nFL37R7X6PPfZYDjnkkLmB5pFHHpmxY8dmxIgRfXMxi6HjAY+zZ8/udvsLKdicMWNGbrzxxhx22GELPIixP5VSstZaa+W4447L448/nq9+9av59Kc/nVNPPXXumEceeSRnnHFGtthii/zqV7/KKqus0uUYl1xySZ/U0vH79n//93/dbn/44Ye7jAMAAAB4MdDD+iVsm222SZJuw9gbb7xxgeBz5ZVXzuabb5677747f/vb33p1jj/+8Y9J0m3/6J5C4L5w2GGH5Zlnnsmjjz66yNnVSavOzTbbbIGw+vnnn89NN93U7T611owbNy4PPvhgTj/99Jx++ul5+OGHc9BBB83tn70srbbaaklavZ/n9/e//z333nvvsi5piV155ZWZM2dOj+1AloXPfOYzGTFiRM4888zcf//9c9ffd999ef7557PHHnssEFZPnz4999133wLH6ph137ltyKJsvfXWSZIbbrhhgW2zZ8+ee192/B4DAAAAvBgIrF/Cxo0blyT5whe+0CWAnjVrVo499thu9znqqKPy7LPP5uCDD+52xu7jjz/eZfb1qFGjkiwYut1+++09PtixL4wdOzZXXHFFJk6cmAMOOGCR40eNGpU//OEPeeihh+auq7XmpJNOyu9///tu9zn11FNz1VVX5V3velcOPfTQHHrooTnggAPyk5/8JKecckqfXUtvrbLKKtlkk01y8803d6l5zpw5Oeqoo/LPf/5zmde0pC6//PIMGzYsY8eOHbAaVllllXzqU5/Kc8891+WvAzru6ZtuuqlLAP3kk0/msMMO63aGe0d7ncV5QOLee++d4cOH55JLLsmvf/3rLttOO+203Hfffdltt930rwYAAABeVLQEeQnbYYcdcvjhh+e//uu/ssUWW2TffffNkCFDcsUVV2S11VbrtnfuwQcfnClTpuQb3/hGNtpoo7zxjW/MBhtskL/97W+5//7788tf/jLvf//7861vfStJq5/0KaeckiOPPDKTJk3Kq171qvzhD3/Ij3/847zjHe/I97///X65tlJK9tprr16P/8QnPpEPfehD2XrrrfPOd74zQ4YMmRv8vu1tb8uPfvSjLuNvvfXWHHvssdlwww3z7W9/e+76s88+O7feemuOP/747Lzzztl+++377Jp645hjjskhhxySHXbYIfvtt1+GDh2aSZMm5bnnnstWW221wIMFm+jJJ5/Mz372s7n3Y0/uuOOOBdrMdLawbb31kY98JF/72tdy0UUX5VOf+lQ222yzrL322jnggANy6aWXZvTo0dljjz0yc+bMXHfddRk6dGhGjx6dO+64o8txXv3qV2e99dbLpZdemuWXXz4bbLBBSil573vfm5EjR3Z77pVXXjnnn39+9ttvv+yyyy7Zb7/9ssEGG2TKlCn56U9/mrXXXjtnn332Ul8jAAAAQJMIrF/iTj/99Gy88cY566yzcvbZZ2f11VfPPvvsk5NPPjlbbbVVt/ucddZZefOb35xvfetb+dnPfpYnnngiw4cPzwYbbJBjjjkm73nPe+aOXXfddXPjjTdm/Pjxuemmm3Lttddmk002yTe+8Y3stttu/RZYL64PfvCDWWGFFXLaaaflwgsvzIorrpiddtopF1xwQS677LIugfXMmTOz//77J0kuvfTSLj2EX/7yl+fSSy/NDjvskAMOOCB33HFHhg0btsyu4+CDD06tNaeeemouvPDCrLbaann729+ek08+udu2LE10zTXXZNasWYtsB3LnnXcuNIDvi8B6xRVXzLHHHpsjjjgiJ5xwQi677LIkyXnnnZdXvOIV+f73v5+zzjorI0aMyF577ZX//M//7PZzHjRoUCZOnJjx48fnv//7v/OPf/wjtdbsuOOOPQbWSfL2t789N998c04++eRce+21mTlzZtZee+186EMfygknnJB11113qa8RAAAAoEnKQPTa7Q9jxoypkydPHugygKX07ne/Oz/84Q/z2GOPzX2YJQAALyyjxl810CU00rQv7TnQJQBAI5RSptRax3S3TQ9roDGeffbZXHXVVdljjz2E1QAAAAAvQVqCAI2x/PLLZ+bMmQNdBgAAAAADxAxrAAAAAAAaQWANAAAAAEAjCKwBAAAAAGgEgTUAAAAAAI3goYsALxCjxl810CU00rQv7TnQJQAAAAB9xAxrAAAAAAAaQWANAAAAAEAjCKwBAAAAAGgEgTUAAAAAAI0gsAYAAAAAoBEGNLAupfxLKWVSKWVqKeXuUsrH2+tPLKU8WEq5o/16y0DWCQAAAABA/xs8wOefneToWuttpZRVkkwppVzX3vb1WutXB7A2AAAAAACWoQENrGutDyd5uP3+H6WUqUnWW5JjPf30/8vtt7+hD6sDaJbx280Y6BIa6fbbTxnoEgCA+fjvlu757xYAWLTG9LAupYxKsnWS37RXfayU8ttSyvmllNV62OcDpZTJpZTJzz333DKqFAAAAACA/lBqrQNdQ0opKyf5RZIv1FovL6WsleSxJDXJ55KsU2s9eGHHGDNmTJ08eXL/FwswQEaNv2qgS2ikaV/ac6BLAADm479buue/WwCgpZQypdY6prttAz7DupQyJMllSS6utV6eJLXWv9Za59Ran09yTpLtBrJGAAAAAAD634AG1qWUkuS8JFNrrad2Wr9Op2H7JPndsq4NAAAAAIBla0AfuphkhyTvTXJXKeWO9rrjkvx7KWV0Wi1BpiX54MCUBwAAAADAsjKggXWt9aYkpZtNVy/rWgAAAAAAGFgD3sMaAAAAAAASgTUAAAAAAA0hsAYAAAAAoBEE1gAAAAAANILAGgAAAACARhBYAwAAAADQCAJrAAAAAAAaQWANAAAAAEAjCKwBAAAAAGgEgTUAAAAAAI0gsAYAAAAAoBEE1gAAAAAANILAGgAAAACARhBYAwAAAADQCAJrAAAAAAAaQWANAAAAAEAjCKwBAAAAAGgEgTUAAAAAAI0gsAYAAAAAoBEE1gAAAAAANILAGgAAAACARhBYAwAAAADQCAJrAAAAAAAaQWANAAAAAEAjCKwBAAAAAGgEgTUAAAAAAI0gsAYAAAAAoBEE1gAAAAAANILAGgAAAACARhBYAwAAAADQCAJrAAAAAAAaQWANAAAAAEAjCKwBAAAAAGgEgTUAAAAAAI0gsAYAAAAAoBEE1gAAAAAANILAGgAAAACARhBYAwAAAADQCAJrAAAAAAAaQWANAAAAAEAjCKwBAAAAAGgEgTUAAAAAAI0gsAYAAAAAoBEE1gAAAAAANILAGgAAAACARhBYAwAAAADQCAJrAAAAAAAaQWANAAAAAEAjCKwBAAAAAGgEgTUAAAAAAI0gsAYAAAAAoBEE1gAAAAAANILAGgAAAACARhBYAwAAAADQCAJrAAAAAAAaQWANAAAAAEAjCKwBAAAAAGgEgTUAAAAAAI0gsAYAAAAAoBEE1gAAAAAANILAGgAAAACARhBYAwAAAADQCAJrAAAAAAAaQWANAAAAAEAjCKwBAAAAAGgEgTUAAAAAAI0gsAYAAAAAoBEE1gAAAAAANILAGgAAAACARhBYAwAAAADQCAJrAAAAAAAaQWANAAAAAEAjCKwBAAAAAGgEgTUAAAAAAI0gsAYAAAAAoBEGNLAupfxLKWVSKWVqKeXuUsrH2+uHl1KuK6X8of1ztYGsEwAAAACA/jfQM6xnJzm61rppku2TfLSUslmS8Umur7W+Ksn17WUAAAAAAF7EBjSwrrU+XGu9rf3+H0mmJlkvyduTXNgedmGSvQemQgAAAAAAlpWBnmE9VyllVJKtk/wmyVq11oeTVqidZM0e9vlAKWVyKWXyo48+uqxKBQAAAACgHzQisC6lrJzksiRH1lr/3tv9aq3frrWOqbWOGTFiRP8VCAAAAABAvxvwwLqUMiStsPriWuvl7dV/LaWs096+TpJHBqo+AAAAAACWjQENrEspJcl5SabWWk/ttOnKJO9rv39fkiuWdW0AAAAAACxbgwf4/DskeW+Su0opd7TXHZfkS0n+u5RySJI/J9lvgOoDAAAAAGAZGdDAutZ6U5LSw+Z/W5a1AAAAAAAwsAa8hzUAAAAAACQCawAAAAAAGkJgDQAAAABAIwisAQAAAABoBIE1AAAAAACNILAGAAAAAKARBNYAAAAAADSCwBoAAAAAgEYQWAMAAAAA0AgCawAAAAAAGkFgDQAAAABAIwisAQAAAABoBIE1AAAAAACNILAGAAAAAKARBNYAAAAAADTC4CXZqZSyY5KtkwxLMjPJbbXWm/qyMAAAAAAAXloWK7AupWyT5KIkr+5YlaS2t/2/JAfVWif3aYUAAAAAALwk9DqwLqW8MsnPk7w8yU3t9w8nWSfJ2CQ7JbmulLJdrfUP/VArAAAAAAAvYoszw/qEJCsn2b/W+oP5tp1YStk3yaVJPp3kfX1UHwAAAAAALxGL89DF3ZL8sJuwOklSa/2fJFe0xwEAAAAAwGJZnMB6jST3LGLMPe1xAAAAAACwWBYnsH40yWaLGLNJkseWvBwAAAAAAF6qFiew/nmSvUopB3S3sZTyziRvT/KzvigM4P+zd+dhdpZ1mvjvbxIggbAqIKPSwb1dERHcRXHHHlzGVtsewHHa1qtxQMdfi84o2suI19gj6tjTrT0qOrbaKiBC0y6oKGqLgChoqygCKrJvYQsk+f7+qBOsJJWkilRy3qQ+n+uqK+dd6py7Uk9Ondz1nOcFAAAAYG6ZyUUX/yIThfQnqurPknwtyW+T3CvJQUmelGRpkr+a5YwAAAAAAMwB0y6su/vnVfWMJB9L8sTRRyep0Sk/TXJ4d1806ykBAAAAANjqzWSGdbr7e0l+v6qekGS/JDsnuTHJ97v7W5sgHwAAAAAAc8SMCutVuvvbSb49y1kAAAAAAJjDZnLRRQAAAAAA2GTWOcO6qt6WiTWqP9Dd1422p6O7+y9nJR0AAAAAAHPG+pYEeXsmCutPJ7lutD0dnURhDQAAAADAjKyvsH7a6M/L1tgGAAAAAIBZt87CurvPXN82AAAAAADMpvXNsF5NVR2W5Pzu/uF6znl4kv26+2OzEW5LteSY08YdYZAuOe6QcUcAAAAAAAZs3gzO/WiSF2zgnEOTfORupwEAAAAAYM6aSWE9HfMzcdFFAAAAAACYkdkurB+U5PpZvk8AAAAAAOaA9a5hXVUfXmPXC6pqyRSnzk+yd5InJ7GAMwAAAAAAM7ahiy4eMel2J9l39DGVTvLdJK/f+FgAAAAAAMw1Gyqs9xn9WUkuTnJ8kvdOcd6KJNd39y2zmA0AgE1syTHeHDeVS447ZNwRAABgTlpvYd3dl666XVXvSPK1yfsAAAAAAGC2bGiG9V26+x2bMggAAAAAAHPbtAvryapqfpJ7JtluquPdfdnGhAIAAAAAYO6ZUWFdVY9IclySp2UdZXUmLr54t4pwAAAAAADmrmkXy1X1kCTfHm1+OckfJPlBkiuT7JeJGddfS2J2NQAAAAAAMzZvBue+Nck2SZ7Q3YeO9p3U3c9Jsk+SjyR5aJK3zW5EAAAAAADmgpkU1gclObW7L5i0r5Kku29J8qdJrk/yl7OWDgAAAACAOWMmhfU9k1w0aXt5ku1XbXT38kwsCfKs2YkGAAAAAMBcMpPC+rokiydtX5Nk7zXOuSPJzhsbCgAAAACAuWcmhfUvkiyZtH1ukmdW1R5JUlU7JDk0yS9nLR0AAAAAAHPGTArrLyV52qiYTpK/S7Jbku9X1WeSXJDk95L8w+xGBAAAAABgLphJYf2hJK9KsihJuvu0JEePtl+cZI8k70ryvlnOCAAAAADAHLBguid292+TfHqNfe+rqg9k4oKMV3V3z3I+AAAAAADmiGkX1uvS3SuSXDkLWQAAAAAAmMNmsiTIBlXVs6rqu7N5nwAAAAAAzA3TnmFdVbslWd7dN01x7PFJ/keSp8xiNgAAAAAA5pANzrCuqhdX1S+SXJ3k+qo6v6oOHB3bo6o+m+SsJE9N8oMkh27KwAAAAAAAbJ3WO8O6qp6c5J+S1KTdj0xyelUdlOQLSe6b5EdJju3uEzdRTgAAAAAAtnIbmmF9dCbK6jcn2WP08bYkuyT5apI9kxyZ5FHKagAAAAAANsaG1rB+XJIzuvtdk/b9VVU9LclBSV7d3f93U4UDAAAAAGDu2NAM692TnDvF/nNGf35uduMAAAAAADBXbaiwXpDk1in235ok3X3DrCcCAAAAAGBO2lBhDQAAAAAAm8WG1rBOkiOq6qA19i1Jkqr66hTnd3cfvJG5AAAAAACYY6ZTWC8ZfUzloCn29d3MAgAAAADAHLahwvppmyUFAAAAAABz3noL6+4+c3MFAQAAAABgbnPRRQAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAzCgnEHgLlsyTGnjTvCIF1y3CHjjgAAAADAGMzqDOuq2qmq9p7N+wQAAAAAYG5Yb2FdVSuq6q1r7HtpVZ24jk95fZJfTvfBq+rDVXVVVV04ad/bq+o3VXX+6ON5070/AAAAAAC2XBuaYV2jj8kekuTQWXr8jyZ5zhT739Pd+44+/nmWHgsAAAAAgAEb60UXu/sbSa4bZwYAAAAAAIZhrIX1ehxZVT8cLRmy67jDAAAAAACw6Q2xsP4/Se6fZN8kv03yN+s6sapeXVXnVNU5V1999ebKBwAAAADAJjC4wrq7r+zuFd29MsmHkhywnnM/2N37d/f+u+++++YLCQAAAADArBtcYV1Ve03afGGSC8eVBQAAAACAzWfBNM45oqoOmrS9JEmq6qtTnLtkJg9eVZ9MclCSe1bVr5Mcm+Sgqto3SSe5JMmfzuQ+AQAAAADYMk2nsF6SqYvog9Zxfk/3wbv75VPs/r/T/XwAAAAAALYeGyqsn7ZZUgAAAAAAMOett7Du7jM3VxAAAAAAAOa29V50saqOr6qnVFVtrkAAAAAAAMxN6y2skxyZ5GtJrqyqf6iq51XVtpshFwAAAAAAc8yGCut/l+S1Sc5N8sdJvpDkmqr6VFW9tKp23NQBAQAAAACYGza0hvVVST6Y5INVtVOS5yd5YZLnJfnDJMuq6owkJyU5pbuv3sR5AQAAAADWackxp407wiBdctwh444wLRuaYX2X7r6pu/+xu1+SZPckL0jyqSQHJvlQksur6syqOqqqfm/TxAUAAAAAYGs17cJ6su5e1t2ndPcrk+yZ5OAkf5dknyTvSXJxVZ07ezEBAAAAANja3a3CerLuXtndX+vu13X33kkOSPKuJIs2Oh0AAAAAAHPGetewXqWq9k7y2CSd5Hvd/at1ndvd5yQ5J8lbZiUhAAAAAABzwgYL66p6d5Kjk9RoV1fVe7r7/9ukyQAAAAAAmFPWuyRIVf1Rkjdkoqz+SZKfjm6/oapevunjAQAAAAAwV2xoDetXJVme5Bnd/bDufmiSZydZOToGAAAAAACzYkOF9SOTnNzdX1u1o7u/kuTzSfbdlMEAAAAAAJhbNlRY75qJZUDW9JMku8x+HAAAAAAA5qoNFdbzktw5xf4787uLMAIAAAAAwEZbMI1zepOnAAAABm3JMaeNO8IgXXLcIeOOAACwVZlOYf32qnr7VAeqasUUu7u7p3O/AAAAAABwl+kUyzNd+sNSIQAAAAAAzNh6C+vu3tAa1wAAAAAAMCsU0gAAAAAADILCGgAAAACAQVBYAwAAAAAwCAprAAAAAAAGQWENAAAAAMAgKKwBAAAAABgEhTUAAAAAAIOgsAYAAAAAYBAU1gAAAAAADILCGgAAAACAQVBYAwAAAAAwCAprAAAAAAAGQWENAAAAAMAgKKwBAAAAABgEhTUAAAAAAIOgsAYAAAAAYBAU1gAAAAAADILCGgAAAACAQVBYAwAAAAAwCAprAAAAAAAGQWENAAAAAMAgKKwBAAAAABgEhTUAAAAAAIOgsAYAAAAAYBAU1gAAAAAADILCGgAAAACAQVBYAwAAAAAwCAprAAAAAAAGQWENAAAAAMAgKKwBAAAAABgEhTUAAAAAAIOgsAYAAAAAYBAU1gAAAAAADILCGgAAAACAQVBYAwAAAAAwCAprAAAAAAAGQWENAAAAAMAgKKwBAAAAABgEhTUAAAAAAIOgsAYAAAAAYBAU1gAAAAAADILCGgAAAACAQVBYAwAAAAAwCAprAAAAAAAGYcG4AzBcv/4//ylJcp/XfnizPu4RRxyRE044Ib/85S+zZMmSzfrYW6NxfR8BAABgNi055rRxRxikS447ZNwRYFaZYT1HXPqu5+fSdz1/3DE2iSOOOCJVtdrHDjvskIc//OE55phjcv3116/zcw855JDstttuWb58eZJkyZIla93Xmh8f/ehHp5VrzfuaN29edt555zzucY/L8ccfnzvvvHM2vvxc8Y/HbLXfWwAAAADmFjOs2Woceuih2XfffZMkV1xxRb7whS/kXe96Vz772c/m7LPPzm677bba+UuXLs0ZZ5yRl770pVmwYPV/CkcddVR22WWXKR9nRUyPvAAAIABJREFU1WNM16r7WrFiRS677LKceOKJef3rX58zzjgjedhrZnRfd8eeL/vrTf4YAAAAADAbFNZsNV7wghfkiCOOuGv73e9+dw488MD8+Mc/zvvf//4ce+yxq53/z//8z1m2bFle+MIXrnVfRx999KwtR7Lmfb31rW/Nvvvum1NPPTV77vjELNz7EbPyOOuyza57bdL7BwAAAIDZorCe47o7S887NTd///TcecNvM3/Rjtn+QY/PLk85bL2fd8uPz8zSH/xL7rzy4qxcfkcW7LxndnjYQdn5gBenFmyz2rm3/uw7ufWn38qDTnx9fvOb36Sq8uAHPziHH354jjzyyMybt2lWplm8eHEOP/zwvOlNb8rZZ5+91vETTzwx22+/fZ797Gdvksdflwc84AF56lOfOlGY//aitQrrmy/4Sm77+dm548pfZMUt1yfz5mfb3Zdk8aOfl8UPe9pd5y2/8cr85u9eddf25GVBtrvvw3OvPzouybrXsO7ld+amc07OLT8+M8uv/20yb1623WOf7LjfH2SH33/yrH/dAAAAALAhCus57vozPpil534h8xfvlh33fU4yb35uu+i7WXb5z5KVy5N5aw+Ra/75vbnlgi9n/o73zKIHPSHzFu6QOy7/aW785v/L7Zf+IHu+9K9S8+b/7jHOPCFVlQOf+9Tc+973zo033pivfvWrOeqoo/K9730vH//4xzfZ19fdSZKqWm3/smXLcvrpp+c5z3lOFi1atMkef4O55s9f69h1X/rbbHOP+2a7+z488xfvmpW3Lc1tvzgn1576N1l+7a+zy1P+Y5Jk3nY7ZOcnvjw3X3BGVtx0VXZ+4svvuo8FO++5/sdfcWeu/Ke3ZtmvLsyC3e6THfc7JCvvXJZbf/qtXHPKu3LHVRdn16cePotfMQAAAABsmMJ6Drv91/+Wped+IQt22Sv3Oux/Zf6iHZMk/ZTDcsUn35wVN1+X+Tvtsdrn3HzBV3LLBV/Oogc9Pvd8/hszb5vt7jp2w1mfyI3f+mSWnndqdtr/0Lv27/Efjs02u+6Vj0+6au3KlSvzyle+Mh/72Mdy5JFH5sADD5z1r+/mm2/OCSeckCRr3f9XvvKVLF26dMrlQJLk+OOPX+ca1sccc0wWLlx4t3P99Kc/zZlnnpkk2e4+D1vr+F7/6QNrLePRK+7MVZ85Njd+97NZ/OjnZsGO98y8hYuzy5NekdsvuyArbroquzzpFdPOcNPZJ2XZry7Mwvs9Jnu8+G13/YJhlye+PL/92Bty079+Jovuf0AW3uf37/bXCQAAAAAzpbCew2654MtJkp0f/4d3ldVJUgu2za5PPTxXfvIta33OTeecksybn3s+96jVyuok2fkJL8vS807LLT/++mqF9VRrKM+bNy9HHXVUPvaxj+WLX/zirBTWJ598ci655JIkyZVXXplTTjkll19+ee5///vnyCOPXO3ck046Kdtss02e//znT3FPyXvf+951Ps7RRx89o8J6Vfm96qKLn/vc53LrrbfmjW98Yz4z/wFrnT/V31fN3yY7Pvr5uf3SH+b2S3+QxQ8/eNqPP5WbL/hykspuT//Pq82Gn7/DLtn5CS/Ldf/yvtz8wy8qrAEAAADYrBTWc9gdV/4iSbLdFBf92+4+D0vmrb5cxco7b8+dV/0y87bfKTed8/kp77PmL8id1/56tX0rbrspN333xDzykW/OxRdfnFtuuWW147/5zW825su4y+c///l8/vMTuRYtWpQlS5bkFa94RY455pjsuuuuv8uzYkVOOeWUHHTQQeucRf3LX/5y1i66OFX5/fa3vz3HHntsPnPMaWsdW37TVbnxXz+X2y/9QVbcdHV6+bLVjq9Yeu1G5Vm57NYsv/63mb/4HtnmHvdd6/jC33tkkuSOKy/eqMcBAAAAgJlSWM9hK5fdmiSZv/3apW3Nm595k2ZdJ8nK229O0ll564258VufnN5j3H5zrjjh9Vl+45VZdMABOeyww7LbbrtlwYIFueGGG/Le9743y5Yt2/AdTcNHPvKRHHHEERs876yzzsrVV1+dF73oRbPyuBuyqvy+/fbbc/755+c1r3lN3vGOd+R+97tfkt1WO/fOG67IFR97Q1befnO2u89Ds2ifR2fettsn8+Zl+Y1X5ZYLz0ivuHOj8tz1fV+825THF4z2r1x2y5THAQAAAGBTUVjPYfO22z5JsuLWGzJv23utdqxXrsjK25Zm/uJ7TDp/hyTJtnveP3sdse4lMyZb+oMvZfmNV2bnJ7483z3rH1c79p3vfGe9S29sKieddFKqKoceeuiGT55FCxcuzOMe97icfvrpechDHpLXvva12eXwv82CHX/3d7z0eydl5W035R7POzqLH/GM1T7/lh+fmVsuPGOjc9z1fb/l+imPL7/5utXOAwAAAIDNZd44H7yqPlxVV1XVhZP27VZVX66qi0Z/7rq+++Du23bP+ydJll12wVrHlv36R8nKFavtm7ftomxzz71zxzWXZsVtS6f1GMtvuDxJsv2Dn7jWsVUXHtzcTj755DzucY/LXnutvVb05rDXXnvlLW95S2655ZbceNYnVjt25/W/TZJs/6AnrPV5t/9q7e9TktS8iX/Gvcb3a13mbbd9FuyyV1YsvTZ3Xrf2cizLLvthkt+NDwAAAADYXMZaWCf5aJLnrLHvmCRndPcDk5wx2mYT2GE0g/fG7/zTagV0L78j1595wpSfs9NjX5CsWJ5rT3/vaImQ1a24/eYsu+Lnd20v2HnPJMnta5Ti3//+9/POd75zo7+GmTr33HNz6aWX5oUvfOFmf+zJXve612XPPffMzReesVppvGDnPZKsXU7fdvG5ufkHX5ryvuYt3ClJsvymq6f9+Isf+cwkneu//pHViu4Vt96YG7796UnnAAAAAMDmM9YlQbr7G1W1ZI3dhyY5aHT7hCRfT/KmzRZqDll4n4dmx8f8QZae+4X89sN/NjELet783HbRdzNv4eIp1zhe/MhnZdkVv8jN3z8tv/n7P8nCffbLgp12z8rbl2b5DVfm9l9fmMWPeEa2u9eRSZIdHvb03PTdE3P9GR/Ki150VR74wAfmoosuyqmnnpoXvehF+fSnP71Zv+aTTjopSTZYWB9//PHrvCDjQQcdlIMOOmijcmy//fY55phj8vrXvz43nPWJ7P7v/zxJsuOjD8nNF3wlV598XLZ/8BOyYPE9csc1l+b2i8/L9g95Um79yTfXuq+FSx6VW396Vq4+6X9k0f33Ty3YNgt22iOLH/70dT7+Tge8MLddfE5uu+hf89uPvC6L7rd/evmy3PKTb2XlrTdkpwNfnIX3edhGfY0AAAAAMFNDXMN6z+7+bZJ092+rao9xB9qa7Xrwq7Ng13+XpeedlqXnn575i3bKogc+Prs+9bBc/uHXTfk593jWa7Pofo/JzeefntsvPT8rb78l8xYtzoKdds9OB7w4ix920F3nLtjxHtnzFe/KDWd+NGeddVa++MUv5iEPeUj+9m//Ns94xjPGUlg/4hGPyAMe8ID1nrehtbU3trBOkte85jV541v/Mrf+2zdzx+Nekm332Cfb7rFP9nzZO3PDNz+e239xTrpXZtvd98nuL3xL5i3cYcrCevEjn5XlN16VW//tG7npu59LVq7Idvd9+HoL65q/TfZ86V/lpu+dnFt+/PUsPe/UZN78bLv7Ptnx4D/JDg996kZ/fQAAAAAwU9Xd4w0wMcP61O5++Gj7hu7eZdLx67t7ynWsq+rVSV6dJHvvvfdjLr300k0feBqWHHPauCMM0iXHHTLWx//Zz36WBz/4wXnb296Wd7zjHWPNsoqxMrVxj5WhMl6mZrzAxvHcMjXPLWszVqZmrEzNeJma8QIbx3PL1Dy3rM1YmdqQxkpVndvd+091bNxrWE/lyqraK0lGf161rhO7+4PdvX9377/77rtvtoBsmaa7HAgAAAAAMB5DLKxPSXL46PbhST4/xixsRd70pjelu7PvvvuOOwoAAAAAMIWxFtZV9ckk30ny4Kr6dVW9KslxSZ5ZVRcleeZoGwAAAACArdxYL7rY3S9fx6GDN2sQAAAAAADGbohLggAAAAAAMAcprAEAAAAAGASFNQAAAAAAg6CwBgAAAABgEBTWAAAAAAAMgsIaAAAAAIBBUFgDAAAAADAICmsAAAAAAAZBYQ0AAAAAwCAorAEAAAAAGITq7nFnmBU77rNjP+bYx4w7RpLkXy++dtwRBulx97vHuCMMjrEyNWNlasbL1IwX2DieW6bmuWVtxsrUjJWpGS9TM15g43humZrnlrUZK1Mb0lg585Vnntvd+091zAxrAAAAAAAGYauZYb3//vv3OeecM+4YSZIlx5w27giDdMlxh4w7wuAYK1MzVqZmvEzNeIGN47llap5b1masTM1YmZrxMjXjBTaO55apeW5Zm7EytSGNlaoywxoAAAAAgGFTWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICwYdwAAAABgbnJhtKkN6cJoAJubGdYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgLxh0AAJhdS445bdwRBumS4w4ZdwQAAAA2wAxrAAAAAAAGQWENAAAAAMAgKKwBAAAAABgEhTUAAAAAAIOgsAYAAAAAYBAU1gAAAAAADILCGgAAAACAQVBYAwAAAAAwCAprAAAAAAAGQWENAAAAAMAgKKwBAAAAABgEhTUAAAAAAIOgsAYAAAAAYBAWjDvAulTVJUmWJlmRZHl37z/eRAAAAAAAbEqDLaxHntbd14w7BAAAAAAAm54lQQAAAAAAGIQhF9ad5EtVdW5VvXrcYQAAAAAA2LSGvCTIE7v78qraI8mXq+on3f2NySeMiuxXJ8nee+89jowAAAAAAMySwc6w7u7LR39eleSkJAdMcc4Hu3v/7t5/991339wRAQAAAACYRYMsrKtqh6racdXtJM9KcuF4UwEAAAAAsCkNdUmQPZOcVFXJRMZ/7O5/GW8kAAAAAAA2pUEW1t19cZJHjTsHAAAAAACbzyCXBAEAAAAAYO5RWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgKawAAAAAABkFhDQAAAADAICisAQAAAAAYBIU1AAAAAACDoLAGAAAAAGAQFNYAAAAAAAyCwhoAAAAAgEFQWAMAAAAAMAgKawAAAAAABmGwhXVVPaeqflpVP6+qY8adBwAAAACATWuQhXVVzU/ygSTPTfLQJC+vqoeONxUAAAAAAJvSIAvrJAck+Xl3X9zddyT5VJJDx5wJAAAAAIBNqLp73BnWUlX/Iclzuvs/j7b/Y5IDu/vINc57dZJXjzYfnOSnmzXoluGeSa4Zdwi2CMYKM2G8MF3GCjNhvDBdxgozYbwwXcYKM2G8MF3GytR+r7t3n+rAgs2dZJpqin1rNevd/cEkH9z0cbZcVXVOd+8/7hwMn7HCTBgvTJexwkwYL0yXscJMGC9Ml7HCTBgvTJexMnNDXRLk10nuO2n7PkkuH1MWAAAAAAA2g6EW1t9L8sCq2qeqtk3ysiSnjDkTAAAAAACb0CCXBOnu5VV1ZJIvJpmf5MPd/aMxx9pSWTKF6TJWmAnjhekyVpgJ44XpMlaYCeOF6TJWmAnjhekyVmZokBddBAAAAABg7hnqkiAAAAAAAMwxCmsAAAAAAAZBYQ0AAAAAwCAorLcSVbWwqnafYv8eVbVwHJkAAACGoKqOHncGAOY2P4umT2G99XhfkidPsf+ZSd6zmbOwhamqe1TVC6vqMePOwrBU1T9Nuv2uNY59afMnYsiq6kWTbu86zizA1qOq3lhV9x13DrZ4bxh3AIanqp5YVQ8b3X5RVR1fVa+rqm3HnY1hqaqPjjsDWwU/i6ZpwbgDMGue1N2vXnNnd3+iqt4yjkAMV1WdmuSY7r6wqvZKcl6Sc5Lcv6o+2N3HjzchA/LASbefmeRNk7bXelcHc95/T3Li6PYZSfYbYxYGrKq+lqTXcbi7++DNmYfBu3eSb1fVL5N8MslnuvuaMWdiy1PjDsCwVNX7k+yfZNuquiDJPZP8S5InJHlsksPGGI/heeS4A7BV8LNomhTWW4/1DXoz6VnTPt194ej2K5N8ubsPq6odk3wricKaVdZVKG3oGHNTreM2rOmNU+x7XJI/T3LVZs7CwHX366vqDUmekuRlSd5aVT/IRHl9UncvHWtAthRet7Cmpyd5eJKFSX6dZM/uXl5VH0jyw7EmY4i2r6pHZx2vcbv7vM2chy2Tn0XTpLDeelxVVQd099mTd1bVY5NcPaZMDNedk24fnORDSdLdS6tq5XgiMVCrXpjNS7Jo0ou0SrJorMkYokWTxsvCNV/UeyHPKt197qrbVfXUJG9Nsl2S13T36WMLxmB1dyc5M8mZVXVkkmckOS7J3yXZfpzZGI6qWpqpywCvW5jKstFzy21VdWl3L08mnm+q6s4NfC5zz72T/E2mLqw7E78Agck/i1aNlVU/l/wsmgGF9dbj/0vyT6N1lVb9J3D/TLyN6WXjCsVg/aqqXpeJmQT7ZeKtb6mqRUm2GWcwBueKJP9riturtmGy9Y0XL+RZTVU9OxNF9e1J/rq7vzbmSGwBquoRmXht+9Ik1yax9B136e4dx52BLcoeVfVfMlEirbqd0bal71jTz7vba1k2yM+i2VETv1Bka1BVeyT5s0y8rSlJfpTkf3e3t9aymtFY+YskeyX5QHd/abT/aUke093vHmc+hqOqtunuKWeYVNU+3f3LzZ2J4aqqnbr7pnHnYPiq6nuZKAP+Z5LvrHncbHwmq6oHZqKkfnmSFUk+leST3X3xWIMxeFV17yTzR5uXr5pBC0lSVX+5vuPd/dbNlYXhq6rvd/ejx52D4auqhUlek+QBmVhe6MN+/sycwnorMnrr9f2T/Ki7/23ceYAtX1WdnuTQ7r5jjf2PTHJKdy8ZSzAGqap+keS/dfenxp2FYauqr+d3b4+c/JbJZOLd2GYwcZequjgT61V/qrsvGHcehquq3pxkm+7+i9H2ZUluzMQ7CE/o7neOMx/DUlWP7e7vjTsHW4aqetaqiV6j7W0yMVnwNyYJMllVfToTy7B+M8lzk1za3UeNN9WWR2G9laiqtyX540wsB3Jgknd294fGm4qhqqovZD2L/Xf3v9+McRiwqvqrJI9P8gfdfeto30FJ/l+SV3b3l8cYj4Gpqt/LxEVbFyd5bXf/fMyRAJhDquq8JE/u7ltG29/v7kdX1fwkZ3b3k8abkCEZXbz1m0ne7OKtbEhV/V2S93f3j6pq50y8Q2xFkt2SvLG7PznWgAxGVV3Q3Y8Y3V6Q5Ozu3m/MsbY41rDeerw0yb7dfWtV3SMTaxIrrFmXqZb8mHwhAEiSdPd/r6r/luSLVfXcJM9O8p4kL+juc8abjqHp7kuTvLCqnpPkW6NlH1ZOOu6XYSSZWD4myZ7dfdFo+yX53UVovtjdV44tHIMzxYX0Osk1Sb6W5E3dfe1YgjFIq8rqkfeO9q0YXasFJtsvyeuTnFtVxyoc2YAnd/drRrdfmeRn3f2CqrpXktMz8U4gSCZmVydJunt5lYrl7lBYbz1uXzX7sbuvrap54w7EoO2S5D7d/YEkqaqzM7GWaCd50ziDMTzd/ddVdVsm3sFRSZ5u5izrUlUPTvLnmZix9IFMKqxhkncn+XaSi0bb78zEf/YWJXlCJtb9gyRTX7yoqnZNckSSv0vyks2dicFaPPn6G9390SSpqu2S7DTOYAxPd69I8u6q+uck36mq/5OJ1y01cbh3G2tAhmbyEonPTPKZJOnuKxSSrOFRVXVTfjcZcNGk7e5uP4+mwZIgW4mquiHJN1ZtJnnyaHvVPwiz2rhLVX0rycu6+1ej7fOTHJxkhyQf6e6Dx5mP4Zi0fEwleWKSnye5YtVxzy1MVlXHJfn3Sf5rd58+7jwMV1V9P8l+PXohOvlCRlV1lrftM11VdZ632bJKVf2PJPdKcuSkpcx2SPK/k1zR3W8eZz6Gp6oOT/LfM/FL9tV+0T4qtCFJUlVfS/I3SX6TiXf4PGRUVi9IcmF3P2SsAWErY4b11uPQNbbfHUs8sG7briqrR84avZ322tGLelhl1fIxi5J8KRMv4n+R5LaxJWLIHpHkGd19eZJU1WFJXpzk0iRv7+7rxhmOQVnQq8+a+I+Tbu+yucOwZRpd8Mr/Z5jsrUn+OsllVXVpJv4fdN8k/3d0DO5SVd/IxESMp6567QLr8adJ3peJX4od3d2rJvEcnOS0saVicKpqYSbeLfiAJD9M8uHuXj7eVFseM6y3ElV1aNazxEN3f2ac+RiWqvp5dz9gHcd+0d3339yZGKZRGfDXSf5Tkssy8R+/+yT5aJK3rHrLLSR3XezqGd19XVU9Jcmnkrwuyb5Jfr+7/8NYAzIYowtdPXvSf/ZW7b93ktO7+5HjScYQVdWLpti9ayau4XJWd//FZo7EwI3Wq171Wvfn3e0X7aylqp7T3f+yjmNHd/fxmzsTsOWrqk9nYh3rbyZ5bpJLu/uo8aba8iistxKWeGAmquoTSb7e3R9aY/+fJjmou18+nmQMTVW9J8niJG9YdfX00cXS3p3k1u4+epz5GJaqOr+79x3d/kCSq7v77Wseg6r64yRHJfmvSb4/2r1fJp5b3tfdHx9XNoanqj6yxq5Ocm0mXsuY1cZqqmqPJH+W5GGZGCs/TvKB7r5qrMHYolTVZd2997hzMBxV9f6sfgHg1XT3f9mMcRiwqrqgux8xur0gydmWL5s5b6HbeljigZl4fZKTq+qPkpw32veYJNslecHYUjFEz0/yoMlv3e/um6rqtUl+kkRhzWQLqmrB6C1vByd59eRjY8rEAHX3/6uqa5L8VSZKpSS5MMnbrH/Omrr7les6ZhYkk1XVE5P8YybeCfaxTLwzbL8kZ1fVK7r7W2OMx5bFspqs6ZxJt9+R5NhxBWHw7noXcncvd1HOu8cM662EJR64O6rq6fldUfCj7v7qOPMwPFX1s+5+0EyPMTdV1X9L8rwk1yTZO6OL6lXVA5Kc0N1PHGtAYKtjFiSTVdW/Jnltd39/jf37Jvn77j5wPMnY0nhuYX0mXywa1lRVK5LcsmozE9eDunV0u7t7p3Fl25KY7bT1+G5V/ck6lng4e0yZGLhRQa2kZn1+XFWHdffHJu8cvZ3/J2PKxEB1919X1RlJ9krypUkz8+dlYi1rSJJU1fvWd9zbapkB05aYbKc1y+ok6e7zq2rHcQRiuKpqaaZe4mFVwQTrYuYn69Td88edYWtghvVWYrRW28lJlmWKJR66+8pxZQO2XKMLoJ2Y5LYk52bixdljM/Ei/oXd/ZsxxgO2UFV1RyaWAPmnJJdnjdKxu08YRy62PGZBMllV/VuSJ3T39Wvs3y3Jt7v7IeNJBmxNquo8axLDpqWw3spY4gHYFCY9t1QmnlvOGHMkYAtWVfdI8pIkL02yPMmnk3xuzZIJkg3Pguxu7xolSVJVr07yJ0nemNUn8bwryYe7++/HlQ3Ysq3xs2j7TCzxkFjmATYJhTUAAGMzeifHy5O8IcmbuvvjY44EbMGq6vlJ/jyTJvEk+Z/d/YXxpQIAZkJhDQDAWFTVfpkoq5+ZiWWH/qa7fzzeVAAAwDjNG3cAAADmlqp6R1Wdm4lZ1Wcm2b+7X6WsBjZWVT23qs6sqmuq6urR7eeNOxcAMH1mWAMAsFlV1cokF2figq7J79aErCQru/tRYwkGbNGq6k+S/GkmlgQ5Z7R7/yTHJfmH7v7guLIBANOnsAYAYLOqqt9ImdbjAAALOElEQVSbaneS+yR5S3ebDQnMWFX9OMmTuvu6NfbfI8lZ3f3740kGAMyEK2oDALBZdfelq25X1b5J/ijJHyb5ZZLPjSsXsMWrNcvqJOnua6tqHHkAgLtBYQ0AwGZVVQ9K8rJMXHDx2iSfzkTR9LSxBgO2dDdV1aO6+weTd1bVo5IsHVMmAGCGLAkCAMBmNVrD+ptJXtXdPx/tu7i77zfeZMCWrKqelOQTST6S5NxMrI//2CSHJ/nj7j5rjPEAgGmaN+4AAADMOS9OckWSr1XVh6rq4EysYQ1wt40K6QMy8f/cI5K8MhPPLQcqqwFgy2GGNQAAY1FVOyR5QSaWBnl6khOSnNTdXxprMGCLVFWHJrlPd39gtH12kt0zMdP6z7v7s+PMBwBMj8IaAICxq6rdkrwkyUu7++njzgNsearqW0le1t2/Gm2fn4lfhi1O8pHuPnic+QCA6bEkCAAAY9fd13X33yurgY2w7aqyeuSs0XPLZUl2GFcoAGBmFNYAAABsDXadvNHdR07a3H0zZwEA7iaFNQAAAFuD71bVn6y5s6r+NMnZY8gDANwN1rAGAABgi1dVeyQ5OcmyJOeNdj8myXZJXtDdV44rGwAwfQprAAAAthpV9fQkDxtt/qi7vzrOPADAzCisAQAAAAAYBGtYAwAAAAAwCAprAAAAAAAGQWENAABsUFV9varu9nqCVXVQVXVVvX0WYwEAsJVRWAMAsFlU1UOq6v1VdWFV3VhVd1TV5VV1WlW9qqoWjjvjXDAqjWfyccS4MwMAMHcsGHcAAAC2flX1tiTHZmLCxL8mOSHJzUn2THJQkn9I8tok+48p4lzyjin2HZ1k5yTvTXLDGsfOH/15WJLtN2EuAABQWAMAsGlV1VsyUZL+KslLuvu7U5zz/CT/dXNnm4u6++1r7hvNot45yfHdfck6Pu+yTRoMAABiSRAAADahqlqS5O1J7kzyvKnK6iTp7lOTPGeKz//DqvrGaAmR26rqgqp6c1VtN8W5l4w+FlfVe6rqV6PPOb+qXjA6Z0FVvaWqLqqq26vqF1V15BT3ddd6y1X1+Kr6yijD0qr6YlWtNRO8qv5dVb2tqr5VVVdMWvLkH6vq96f6uxk9xkdHtz9VVdeMcp0zKvEnn/+a0flvW8ff9b2q6s6qumCq4xtrfWtYV9WzquoLVXVVVS0b/d1/vqqeMY37XVhVnx19bR+oqnmTjm0/+n6fX1W3VNXNVfWdqnr5FPcz+Xt2wGipmetG+5ZszNcOAMD/3979x3pd1XEcf75HlC0sDByolTFx/ZiNJKDcgCAXQWg6rbVaWSpL0nCJGuJEgRw2yygl+7GiLY3GkpKWE3KggpEpGS6brTQKf2SuBYkpKvDuj/P51scvny959X7vvbjnY2Pncj7nfD7ny4c/7l733PfpOwbWkiRJ6qbTgcHAqsy8b38DM/OZ+t8jYgmwEngbsAJYBgSwBFgbEYMbbjMYuAX4ILAauA44ClgVEcdX9zsbuI1ShmQIcE1EfLTDst5djX0G+AZwM3A8sDEiJrWNnQxcRCmpsQpYSil/8mHg7ogY0+EZRwJ3AW+u1rsSOAZYHRFTa+OuB54AZkXEoIb7nEH5Dcpvd3hOV0TEImAtpbTLWuAqYB3lvX3i/8w9hPK+TgHmZ+Y5mbm3ujYUuIPyvvcAyymlZA4FVkTE5R1uexywETioNufZF/8JJUmS1JcsCSJJkqRumli163oyKSKOA+ZTyohMyMzHqv75wE+BE4ALKWFm3eHAPcCUVgAeEdcBG4AfAw8Cx2TmjuraV4E/UILmlQ1LmQ7MycxltbWdBNwILI+It7QCVmA9MCIzd7Z9ljHAL4EvATManjEFWJiZi2pzVgBrqs94K0BmPll9lnOq+/y8Nj6AWcBTlNC7T0TENOBSYCswKTMfabv+hv3MPZLyA4DRwGmZeX3bkK8BxwLzMvPK2ryDKP/+F0fEDZm5pW3eNGB2ZvZpcC9JkqTe4Q5rSZIkddNhVftwD+edUbWXt8JqgMzcTal1vZcS0Db5fH23dmZupASqh1DCzx21a3+mhMnv6LBr+QHg2npHZq4GbqcErZNq/Y+3h9VV/72UMHtqh13hfwUub5uzFtgGTGgb+82qPautfxowCliZmf9qeEa3zKna89vDaoDMbHzvEfFO4FfAEcCM9rA6IoZRdmdvrofV1T13AfMou+0/3nD7LYbVkiRJBy53WEuSJKmbomobax/vx9iqXd9+ITP/GBEPA6MiYmg9gAZ2ZOaDDfd7lBLo/qbh2iPAIGBk9XXdxtoO6rrbgPdSdgDf3uqMiJnAbGAcMJx9v98eDvytrW9LZu5peMZDlPIW/5WZv4+IDcCMiHhjZj5UXfpM1X6r4T7d9B7Ku13TgzkTgbnATmByFei3G095JxkRCxuut4L/fWqDU8qrSJIk6QBlYC1JkqRuehR4K9CxNEQHr6va9nCXWv+bqnH1wLrT7uLdAB12H++u2qbdz3/vcL/Wru/WOomIc4GvA9spdZm3UUp0JHAyMAbY57BInr/+9nU1/UbktZR62bOAyyJiJPAhSvDd12HtUGB7Zj7dgznHAgcDmyjlWJoMq9rx1Z9OhjT0PdbQJ0mSpAOEgbUkSZK66Q7gfZSDCr/Xg3mtYHkkpe50u8PaxnXLiA79I+vPj4hXAIsoYenYzHxe0F7V5O4tP6EE6WdGxGL66bDFyg5gWES8ugeh9TLKwYmfBX4WESc3zG2916WZObeHa+rpbn5JkiQNINawliRJUjd9H3gOODUi3r6/gRFR333826qd0jBuNGXH9ta2ciDdMDEimr5nbq2rtc7hlN3GmxrC6iH8r8TJS5aZzwHfpdR/PpGy0/pJ4Ie99YweuJNS9mV6D+ZkZp5NOVRxGnBTRLymbcxdlDrlk9onS5Ik6eXNwFqSJEldk5l/ARYCr6QEk+OaxkXEdODmWtfyqr0kIg6tjRsEfIXyfWxPdmy/WEcDZ9c7IuIkSv3qB4CNVffjlPIf76oC6tbYwZQyIcN7eV3fAfZQdiuPAlY0HfjYB66p2qsi4oj2i019LZl5HnAFMBVYGxGvrV17nBLAj4uIBdUO9vZ7HxURo17qB5AkSdLAYkkQSZIkdVVmLqkCx8uAuyNiE7CZsit4BKUe89FVX2vOpoi4EvgCcF9E3AD8G5gBHEMpNfLlPlj+GkoYOwO4FxgNnALsAs5sHciYmXsj4mrgIuB3EbGaEtJPBV4P3Fp93Ssyc1tE3ESpXQ39Uw6EzPxFRHwRWADcHxE3Ug6LHEE5XPFO4NP7mX9xROyilFO5JSKmZ+b26vLnKP8vFgOfjIg7KKVQDqcctjge+BiwtRufTZIkSf3DHdaSJEnqusxcTAmal1EOKjwduBCYSalRPYsScNbnzKMEkn8CTgPOpXz/egnw/sx8tg+W/mtK+Y9XUQLUGcB6YHJmbmgbuwA4H3gaOIsSbG8GJlAOYOxtrV3omzPzni7c/wXJzEsp73ETcAJwAfAB4H7gBy9g/mLKDyYmAOsiYnjV/wRlJ/sc4B/AqcBcSvC/EziPcrilJEmSXkYi0zNJJEmSpLqImELZFb0oMxf272qaRcRCyq71WZnZF+VRJEmSpK5zh7UkSZJ0gImIg4HZwD+BH/XzciRJkqReYw1rSZIk6QARETOBscCJlDrRF2TmU/27KkmSJKn3GFhLkiRJB46PAJ+iHD54BbC0f5cjSZIk9S5rWEuSJEmSJEmSBgRrWEuSJEmSJEmSBgQDa0mSJEmSJEnSgGBgLUmSJEmSJEkaEAysJUmSJEmSJEkDgoG1JEmSJEmSJGlAMLCWJEmSJEmSJA0I/wFX22s9Z0LnLgAAAABJRU5ErkJggg==\n",
       "text/plain": [
        "<Figure size 1800x720 with 1 Axes>"
       ]
@@ -3297,7 +3298,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
diff --git a/stock_picking.ipynb b/stock_picking.ipynb
deleted file mode 100644
index a1b5b71..0000000
--- a/stock_picking.ipynb
+++ /dev/null
@@ -1,107 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "from pathlib import Path\n",
-    "import numpy as np\n",
-    "import seaborn as sns\n",
-    "import matplotlib.pyplot as plt"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "stock_csv_path = Path('monthly_data.csv')\n",
-    "monthly_df = pd.read_csv(stock_csv_path, index_col = 'Date')\n",
-    "returns = monthly_df.pct_change()\n",
-    "returns.dropna(inplace = True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0.5, 1, 'Correlation Matrix')"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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J24eP0xkRp7/BfWITNxEZAO8bY661/44EJ4zPM8b0IKIBYGH4LeB6h2ONMS/afUcCSDbGPGcLo34FYI4x5tHQMzFcfvachz8I2aat7K/3Sj7p+QmcDtihthQpmfS7V28Wh9PYSuhUOtrrK6fS6daEiVT/pFLA7lQpamY5xxI2HhXLYM1h+Xy1+zh1vfrvV3p9O1NkX5e2+ddhsaY6qK0rrcWRmSXgUhtXKsuk6xP3ee2ll7L11vZ8CRJ++8yXXttZTDFzJdArewIbjvK1UFVZEWw8KpXQyts87GZxYkVuOirPwiHy4bFIW8TBu2OvfOf1J6jUwcUzOYWstLL8ataU1LwpS3eEHFcjdR2nkOkXW4/VXavZK6mlS1IkT7uNW6kdledXSo2laCm+xl//lHF0VedaaZ978SXhtzdvylyEKb9KrYZyaqVEXbju8erXfvT6ah+Usaw4JGN1NeGWpsh7Ixnrghg1E8U0qBSy/e9DcvyoWNn3iF3dFFGfj+4jV7P4u5cASIolAGxS99pln0erPOvVyfIdqhXN6aeFekuNj/lDJJD6q/2+XaSs9OB3Mge4Fd6CZLl+gGncecGZbHGnAGhARNG23mBHhFYg+cQYc5vVF15JRBOtvxsAYEXnPwOwIKtJ28eZAzdp+/BxOiNwhvu4vwGXepoIrtP3EbgKdjoYY/YQ0WoAiRBqZyS4YskqY8z92Z3IsSDrxnwWss35sgGxsgHgxyS2TC5W5IWzNokvcU4SW4QVWlb1+iptl+1pYchLVQvL7SreuLLXDvRktlrC7ZJ2Vi5K/H5xsaG3OUX5BVGIxx2tLJu01ZLiVdRapGULhY8JO79iw1hZPUTUFbaa8wGmbRYrM1X5y4tZiykuXiw/jeJ2u06Li4sItUtq15fVze5FobWJIxpfiOCXYwEAjdRYdx4Xi29vKn+ujVrRRJUTi7vWKolDhEOhlk1C+iqr57Y/le87lRAWrvbNN7RxgIirB3h9jf4QuyIQz+NuFS/j13DWZ4XY8MVwYtrx+P6aKaSk7sofHjjvUt4vQtiQW47ISqpC4dBnVCaT98KhUmEZC3UI1TsqrT6/L1Xey3qxbBEHNLlvk6wUSlmS2oGgvEvlo0Lf9crq/JuPybXULm9995Hyme3H5F1oaM/f4CyJ11Cl0NjKWdHh39sTRUFwleRlVfAxgCutu+NsMFMyBERUGewuWaK67wWQaoy5K9xnfJyZcJO2Dx+nMyJy8XeqcMIWt83Jrgq2tqeG2aUvEV0AoA6AmzNUBJ8DoDUR1TbGhE0P0JT3lxpWww1VyqSjr3vjUJax9mc7S3vYFMnOGPOa0LTLvso0c1IWQmKMWAbViodaVN3V8Y9u2ee1I+ZxKnq7hmKRHj8iFmfxp/4v5Fjn1hZSTNp6zg7oXqe0HLOmyPJeUoPPe/SYZGpodKjPn0vaL9bMgWv6eu3zmrNFt/1Xocnf2keyJoIH+dEUOUeyYjR6deaskuBzQ72+nlWKe22X9JG0S6jbNUtL7AHH+PiBrtch9SmmN5eMESspUtyeaP3k9XzMxYu8vh8+Fn2Kc1uE+mjNVrFeUSqULNPhLLmvBw+Gxi5uaS9ZDxHOevtlpte3cqNkOpzb4WwAQCuV/aDROZFZvrVuvCjs9l+t7saD1wmBKuVP8TIGX2BL+477L0XyDI6dxF0kuigmWVaFDpc3KBvSp5FYUt5l85NyV3W8GgDQp6a818kpcn+OHuH37ZheHSbKSuWqBqxRc/iwvOuFokKns8ql5XvbpLS89wtXMBko9ln5Qe81VPSG3PX/unyX19e5rty36laioXUXyarJDxSEdMC8/mhMBvAc2E2SEZ9Y2de2AJ63jEqH2WBizjdEVD7MZ9NR3m+okjVzzUfBgJu0fWQPN2n5+OdxRlvcFm+DufVLbbXtEBhj5hLRewDuBPCA6v/M0uW/JaJ2xphMnZdO1e/n/g97fc4rqHOzddaI82drK3vIrZLbe1UZtsiP/yj5vBHKubV2H5uB+rf8xzVCF768o1is2MG+Y20ZHFSCUOX6cYZHm3XChktOFsumZAXO/V236aDXV/aYLFAWbuY8bO2XFk8fsHAliyCp1HF0mCeKcBNtHnPvaaLeN7HzjV7bHTf2JxEoulTRpCdM5VXLLeO/8vpWvyy5zzVKsEUVq3z5G7dLVknNKPbhR458w+s7OEFyd6OUv/yvpzhrIKGoEvH6P6HXf/U41xXuGZT7R+XlbpjfrIJjL3nuk5dLhkcp60+ttE48d1Pnit+2aTl+LyrFyntRPVGyGlLmsbDTV8vkmKJDCKzdz6uOvS/JIvRcRXNv9TBnFn350HteX/OK4sMv2pWVAuO7XoZPOg4AAHQJ/u5tn7hEFChvHsn/n/6XvHfp2G8WO5S6YdWacq+Cv3Bm0W+b5KvXtLyMZdMB/lxJ5YOm1h299jfD+XnqDKADSkHSrfk27JJ3ITpa/On1qvK9Lj59tte3toVY1N9t5Pf66rYiopXUrZ3Xdqu2v2evxa97ZCVyM/KGM93HDWPMZmPMSznY9T8ArieieN1pjHkdrF0y2frKffjwAXiTto/soSft/EAkKMd/pwonSnmPC9M3C8As234HXLLHbdsKwLlKRmb43MiMfT58+PBxqlAQLO4CxZwsFCZo4KjrgJBqAEn3c0FIQNwjAPChDS691FmcId9PlUDmQpvUr8kTq1XA8ehKIavEDGIP0Oaj//H6tM732aXTLTR43FsluFWlEAdZZibJkrJVlCxAHMHCpV9lxJ7jPK7CyuWg0wmPWVfIwWESJN12TJNSePsl6v5oFHM05sNi2Wjtbde+toSEMZKCoemAABD8mMX1k5QrKUUtrwvbdLA2iRLcPPTtz167vEstC4RPAaN6oQFWne63xqbWRVQ72+vT98K5aCKV+uK279732iXPYtdcQqS4LDQcGaRbifDpgGlLOBB9SL2rMTHKFVGuKgBgr0rLW75aAuH1YkIXptsyCVrLdhWQjZVnHDj3Urtd6PVfrRd3YDkbuD+sgpNNPntHHZfv2xZ1/8JZoUfUd+H71XL82tF8LSXflAIlf++Qd8x937evk+uv8aUQcKY35m9nRsp7XnEmE3B8+Mg13KTtw8fpjDPS4s6K7g5mQrqaVPUArAQXWPgWwF9gGvxmAHHgIsGPqnqUmcKVF9NWrIMWidL0dUes0el+OhDpLO0735PAz9CakjbWpklosst1tWX75mVicVV/ioOP7StKwYfSFcSyib1NAoHeWHs29NqpD90AABh+Z6eQ/QDgjvM5OLNv28Gw26vYtKiEeLE8Ul8SbfB6tqpJ3FMS3B3y+Yde+8hKTkfbuV4sG42GVlYgbZsI/FzTUKzrYpaM9MWnYuXXCUNQCVwp6YSF7pNAZRlF+T7vYw7krRv8iGxXBAsv6Kst+oA847Q/WDo2cK1sPitGxpKYyPdC66Zc31LIVDMXs0BR/EPven3FVfDtRyt+VSoyvMV/R6vQdEWNXfPXAwD6dJXg7k8z5L1MbMvpcJ0rSbpltf6i9/3LqFAV5CtVGmlw5iey4QAHHRuUlNXLiofkvjfsw2qi3VRqZ9V+EvybP4aFxpLUighNhNjVvz5TN3T63LFjKnXQQlPm+/1HygeufZHLxNGFl3p9HRtK6uOaQfwOpAuujhFNfJfG+efC8KufE0XEKfRd5xQnYnFnSnc3xowHMB4AiGg9gAuMMbvtvwfA0uDtvy8A8DkRXWCM+TPkLD58+PBxCpCfetwnCyfqKskR3T0rGGNmEtE4MMlmaFb7uiK+388Tv7Aj7mopVi0S5ejrmlSj0/2cP1tb2S+uFn95pU1sfeoyCrM2iEVaUVGPa17C9ROXfSZW4u7NMq4BF1gyiSU8AMDaH8V6rbuELdVPlPxoXzGO8c6c9QCAZOUXfUA2Y7b1jRdVAj5V1fa/bX/Np5/1+pYsEPq784F2aVcd4bDIRu3r7JMUuNGL5PPFlrLFU1YV/Z24XSR4VeKkV5hi7kEZa6XC8rmz7meL6vvNcq/bK3/vJkeZDoR/dVP38Vi1PTwnSfymB/byquXBbyUe8XlNsfLKW+u/TXcR1Hp3opCB+rXl+o1vqecnVRiBN3/jlNQuiqafoLb/bVM+47cJWWm/8vd3uOECAMCr/5ns9TV8MetaIxP/lvf2zgv6hmyfdMMzXvuW5hVCtn+8VvmdXxCp/L+sYFYRZVG3mSA+5g9XcJUgPdFpa9Vl7WsRL6NWMvPsOzD8/dfknJ9KGuuPu/heaSmIc0dIEttrVbgKYkwg/Ux7DvKGguAqOVE/fI7o7jnAHwDqhttARAOJaD4RzR+/dfcJHt7H6QS/mpCPgoAIUI7/ThVONB0wO7p7TpHpldsS9+MAIPjfwQYASv6RUYBQCh4A6aVYnUiUpq47Ug0gWSPal+2sbCC9PKXDKiXVemE1JXxTmS3lgyr6vlZloBz4mqthF1fKLFuSxApxv1zLlNSrtpvW2euKysQUcBaPjt4HLr7Eayd9akuGKQLPvANi8bkMhiar5AdS294uayGimpBmkpQV7Cqjt0mIDfmMRmDwkwhOYN97GZUho0MXC9bwM6gdLRXniybIqil6d9a2RqGyoYWltQjSPlvggWJlv1WKst28BGe6BmpW9fpKFpKK94GE6JAxa2ywzz35UCi1HgAa1WJ/8ncrpKZlFS0C1YlXb0M69cKDbdlRXy9GTqYzpxy2HM06qyRKWcxxF4SKcGlhqRWH5B1071tJ9ayiaojFvuUoZ8hoH3ZqmPsSp2R71yjpYSfaRqWEcr9GSSfvtM+qXVEldXFwr9d0xToSKWuRrdyiIFjceckqcXT39gByX42W0QSA79/+l8BN2j6yh5u0ffzzKADzdu6rvLsK70RUEUAfY8xLlu4+zBjTQ+23HkDzDMHJ5io4eT6AT8ABzKwn7zBV3rOrvJ5f0KXRMqsob/bwSoBKhvoPAcAcYEv2+INCw456+VOvnTpiAAAg8sl3vD5drTtc9ffD11/staMVFT2/sKa5+H1rzD/9dDNSrpIM+9gPv5ENx21+eaHCyAqpT9/mtSMfGJ2nsQRHDffagbs4jpC2UTgBUPIFWjwsr3D3QF9/6r0SR4n8b2jhEQ1HeXf53PkNxyXIz2sOTnnTawd63BR+pzxWeX8noXSOJ8UBSbtOyTyfF3XAzQByQnfX6EtEbQDEAFgHnvh9i9uHDx+nDSILgDpgrifu7Ojuqq9qhn+/A0WDzw2CbzGzatwDEpG+1RYN1QV8dWkx5z/TUqxaJMqxIHVuts4acf5sbWVr6/tRVXS11Eh2Xr9wmeR6aGZcbyv12XCFZCfowsLt1i0HIMVPAeDOXSL4dH8CF/EtrJxvj+5b77VfK8P5rNrHfef3b3vtx9sPAACMGNze63tlrAj7OH90p+Lio75IFSt+tiSPa9jGhV7fwxUkV6SizQqpr1h9K1UZthu3i+xq2gpO2x/bXlwB2mvb2BZYKKL8onWbSxziy9n83K9SxX41jt19DQAg6pX/eX2PFK/qtZ0P9sldUlR3RDHZflEx9qe27iQZPlOnim1xXg2Obby6RArS6mdxb1F+Vu0SJLbSY9NfXvtgLy5K99W8jV6fLjTQ+l0p2vDwJSzxemlJYd7+fVisd1fw+O54yUN/4aAc18G9HwBw8/WtvXbkf95PN2YAqKvkdt17UUyVJhv0xDVe+4Fh7wAAYlVWx0EVT3juwIaQ85dXMako4uN2Gv+Q1zf7xie89rR9nC3VpbhMOW3HSd2VF0vJ9+WQevdHHBE/+InAZ0768KHgJm0f2cNN2j6yx6HMIsUniNPf3vYnbh8+fPhIh4JQSCFXE7elu79gjLnH/nsYmL4+CsAaAKWMMYaIWgP4BUAlY8xmIkoA+7RLAWgB9o0Xtn+fWIXATDH/SQ7k1QgjJnNcBVd15XVXE1JXqtEa2k4kSlPXNalGp/s5aPfII/NF+3vMYg7e9VafKVtDEm1in5NalA6tuomLx1gq+Y3n1wjZDwBuq28rjRwJL9zUNI6X5fGxMv4119/jtftW4nGlHRARq9uHSaWRlNmLeZwtwlcSua4hCyulfShaIwPPEh30NGvxzFOkI+02cRV+EFMUZhK7u+rGSPCwYglxK1S/l4TFiWsAACAASURBVJfiU4dLVZRS62Tp6+j7mSEiJjQoeW31UiF9wSVSRX14S3muS/7m92XPcnGFaJ9ndDwfv3+N0GMCwJ1WCqBs6/DP8jurGd93hGiMf/9fEULbdj8HN2+tJ/e3eGWhpIerUTS0QWKYXkF19b2Z+6m4u9paDtKtdaVQSVlFn184h90uWjDs8HdzvfadDXVtFEYwGGr9NoiVd6H1lc289g8fstyEmTXD62v3mLjQao+dBAD4UT3/QCfZ3qMyf68KR+VvOuDpP23n3p1zFEBvIkr31toiCNsBuNnoXAAL7f8BoBWAecaYNADvAhhojGkMoAGAT+HjXwE3afvwcTqDcvF3qpCrdEAiSgbwJIA4Y8wIZ3EbY0Za+vpvxpg3iegzAJMANDPG3EVEj4KLAz9ORPsA1DHG7Mz8TOkRHDOcB3lYFSe0wT/q3MfrMsslbc1VXg/OU3ThHULTjmjFlTxSrUAUAERY6jogpBoqrizLJXPkWIvlXENGfAwAGDNWSnNR0zbSLsvBH5MiNPAIRW9P6c9kmZjRElCk4mLNuNQys1sISIGmUokkbS1bzGkfCHWYGjaWse7jdMTAAJF11WNxFj+Oyv2NaCAKBmm2Wkzae2Nk+zWS2khF2aIPvjxS+mrJ9eGYBCoDNzKXP/jfO2X7+SKuFWjJK4HgeAlSUUsRWTJLmKRrFkodShdkA0Q8KuLy6+UzKbISoEi2Pn+4VNIBO/wuHLLjj3Nq35Z5672+yle1l7Gea8fy8/cyZlUtyN0rM0dS9ALXyjt2/C6mVhV6Vn7Ejgy5UsafxM8gdpRUa0IRCRqnzZXjRjTmZ2T2y1fJ7FApq0WtpZ4kFmvyc3Lc+OdZ0MsckZVYoLHc6+Dndt/NUiEooKr5pC1nuV2qIKsLs16C2hH2WMEfJVDsqtgDQHASr6oCVuyKDya2pKcmuVcxp2vIqjCiGcsDpP2UPh02cPUDeZpTPytRLseTYp+920/J/H0iAdQxAK627g+NXyAWdnUA/wPgkoHPBeBElV8EsJKIviCiWzKrfKMp72/MWXwCw/RxusFN2j58nM44Iy1uS755DMBxAIchFnctAF+Baw+8YIzpRUQ/A+gMYCOAysaYZHucGgA6AbgSgDHGtM/qvKkPXWsA4LPR072+vlu4OLxOq9t4VOi0CQH2e+nK67om5OajnO6npViX7RDZVEdfv0alnbm0OCC9P7vqXVcAAIbc8orXd4mS0mxlK7qXmCEFARbUFCH/ZqvZSptUUayJnpslXe3tclwnUPta+2+TcX1UvlbI9t5jRBz/hRvZShp6ewevb8bbsnrYfpzvRa0i8ht63rplXntCIh//mlkiBfvhBVLd0N3r4pHia9yTKn7RSzfJtTjSx6eXSdZEtCoA0dTWX9y0Qyj5DepJvOD7xRyT6K3uj0bqU2y9Rf6frA7eKid1FmNsSuWVyyQdcmLD87126UIcJ2jaQKWJLpY4SBM7vjkbxIrtp94Rd65zVGrl2X+K4bH3IpakWrhKYi+xKvXxnJFMoPnofll9NSomx1qZJPflMvsdGFtWLN5bdoj4lcM7iXL9fbuJeFb0Wyxk9UZZ2a4LNaw7yislnbRx9f2yKh39xEQAQIx6fpou7tJA9fEvUN+3rXt5dXHehMe9vt0PihDaZFtLs5aSP2j7qrw3kwayeNbRDDIAV+3fmac5dVIuLO6eBcjiBjgYeSMA740yxqwCUBzAxQBcBGMBgOsBrHOTtt13jTHmNQAdADQiohOlzPsoQHCTtg8fpzOIcv53qnCiIlN7iehT8OT9tto0F1xIYYD69xNQQlRE1B3AVMOmfi1woYVMK7wDADVhj0sA00O2HVfmwBolAlUuin+Fj6tMDF153RVl0AUPtBTr2jAZHJpUo7NGnD/7kpJyKybvEb9hle2cNaHzVPRYHNYdCS9MtMaOJSqTF8WVeNqjjklNRRC/bNTzAACzX2RxFyQLkcOVNmtRKnxxACciFVFdij9oQayyVk63c6J4z/7cKX5th8C5l3oxB331B5Q41/KtvOqpXFQsv8IV5c4VWSrSsuFw6Ff2seoibAeUiNKfllTSr4RkYjjBMQC4ohw/q9hOUrqsxHKROi3ThDNQ1q4MH6JZb59VGXXMs9X26Irsd16rrqNxnGTVRHTk1dvVHa/AY/V4hVS6kBwrPjI0g2JDJtlGDrHKIo6qUy1kuxZn263eISfnquV6ES9koN3H+b4WU7OIE37SSFTFTL7ZKCuNOk5yeauQhr5eKavi9VborWUJWXGgjDy3jXbcx3Ip25EdqADkleSFJPQ8OL1P42cAlQC4yN1csL9bMy+uBfu4FwF4D8DVxpis5c18nBFIFyj2kSXcpO3jn0dELv5OFXJlcWu6uzFmB1hzRG9/FlyezP17PTL48I0xVyKXCHQZAAC4+OLJIdvaj5eAV7X7nvfacbF8acWfkkyKcv0kuu8K+OqyYl7BA4gUqxOIAoS6DmTIzY5h+875sgGxsgHglXV8jNfVuJs2KouMuEKXoPrpc699Q03+fYyPC28R97yapeMPrxYrLqKy+DLPLc+WcODmO7y+5l+IQE8x66NOy4SBdkUTa+UUEiv4gdZCsy5k72Xha/t5fbV/ER+yg8sYAYArb5jotYO7JcPl79lM9a/7lGStRLQTidpOpewzVJkQOusitoOV0Ve5xze0kDztY4dDrdMB1cT+qN7L5hnXljz71replVAt7h/4p+R5awyqz881MyOwyAtcOuycuSIi1vA/t3ptSmR/9SP71mPXBRzrL96sqrf96LbQxekNqhhIOPS8XKRcI24QH7HZxZbucMVP0IiuwO97ZIJ8zQM3CD39htf5+1iqoqy0dm4MHV+X64Rmn/y7xAPi+3XjY/YVvePzn5UMoTZWn6DGM5KtZb6Z5LUHXSzxrWM75B3KK850WVcfPnycJLhJ20f2yM9JGygYrpJcy7qeEoSRdf2yEmdg6IyFk4Vjd7DfUUuxarg8a23lhkNmErHBl+4FkD5HNl3u6/nCsnOYUkkKB2kRo/zCD1XlWi5UubknguBHshIK9Lsniz1zjv2dJU++2LQ5IduDz0k1vMCw0OrywRfF8tR52CeC7O5V2uJZXjuiUfs8nUsj3HdAF0Em64/O7PpOhuyqxrZ2rQAAibN/zbdjmt3CWKZS4VcKeZV1/bZU+RxPil12b832XETUBcwWDwB40xjzTIbtlcHExGJ2n/uNMVkWqMmTm4aIyhLRh0S0logWENFcIupFRO2JKImIFhLRn0T0iPpMCyKaTUQriegvInqTiLLmMZ9CuEnbR96RX5O2Dx8nE/mZVUJEATD3pSuAegD6EVFGC+9BAJ8aY5qAU6RfRTY44YmbiAjMjpxtjKlujGlmT+p+Bn+yA2kO4BoiakZEZcHEnPuMMXXAFPlvAcSHnsGHDx8+/nnkMwGnBYDVxpi1xphj4Hq9GStXGEgiVAKArcgGefFxXwjgmDHGi7kZYzYAeMVWxHF9KUS0AEANO+B3jTFz7TYDrhSfJYLTJgAANj4kBBe3PFxWX6jdO1WKWopNMTtXBQyTkyXItHQrp8Z16ikpbrryuqsJ2UHpUmuyjxaJinqZKe+aVKPT/VwgMjNtb9c/Uy2526sMjOlV+FwB9apo98iv1bkWZLVK8vtX+k25V1v6Myml/GVSj3zGy4qSbY8bo4ggesk/owqP6yK7tAaAGWp57WoTtuggRItNf8iSttYfQk8PTn8PALDjcSHIrNssVdgrluHFV4ULhIyUsmi9XMsW3rfeUhFLwnFJbQxO4+CWdo/MUc/NkZRarRWCkbu/ANCuC7ugCl0h7qm9T0iFnGhLrNq2Vgg4+l5Ns8fqcJXUGo98eoKMz1Zu+vIpee07K3GxmJfGAQC+aXqR19e6jgRPDxyQd9x9B76vIu+Nfl8dFtaS97LRZ3ItEWdzyqi+fh2fdoSqSJVO2OSrcV77284DAEhqLQAUVemK7r7o8xcuItsr2Pc17hFJGth4+0iv7b6vlSqJHnf8097iHTOasexDzdIqXRBAjRXhtdpzikAufNxENBDAQNU1ztbLdagAQJfO2gygJdJjJIDpRHQ7mBtzEbJBXlwl9cFV2rOEJde0ArAcLCq1IOtPeJ8Tyvv0n7P/gI/THm7S9uHjdEZuXCXGmHHGmObqb1zGw4U5RUYfej8A7xhjKgLoBuA9Ispybs63rBIiGgOgDYBjAIYDaEtEC8EFTp4xxiynXFCN0lV5nzTaAEDVqSJ/6WoyNlg0T39KmjZ1zZMUBVCyQi2vXcXWJEx96Aavr+4S+R1yoT9XDxKQSjWAEmaCiEQ56npmcEFIILz1rftMshAVOm0Ire6mRaI86/Go0KGDC3/w2pV+sLKZ0WKRd77nhdBj7hdqd/Cdp7y2q4aTtmZhSJ9GcK6ka9Z8Rizy4OQ3vHbgkpsBAOWqSHA1MVboMlQxVFq26C4haBS1qX/BcWJ5BQY+qnbmFDZzUKodtVHPzWFxXZH41fc3+CULH5kZUuez1GQRMUpbzmmiNSvL+DU622MZTclXKwI0bgEA6L1ZaqUGf1M1I59mkatuG8MHnIvp985+B7SVvam1GHPl+7JF3WSVvJepjw/y2s7iDvd+AfBEx9JWiaBaxFmtvHZmY3Rw72iTFb9LZza1QKv91j2kT5/fiYwBcq9xODnjR/KEfM4p2QzmtjhURKgr5EYAXQDAGDPX6jeVApCpEF9eLO7lALxvpzFmCJjC7pJKfzLGNDHGNFPulOUAmsHHvxJu0vbh43QG5eK/HOB3ALWIqBoRRYHjgBkJKRvBcyeI6CwARQDsQhbIi8X9A4CniOhWqzsCZCDkhMFoAL8R0dfGmHl2oNcAmGGM2Z7pp6LZyppzTmevq621orR/7y9V5zDa+l27K1LLuk0iIjUziQkcw+8USdFPlNSqo3Q/vn+916drQuqiB7FvsAtAi0Rp+roj1lT4WawF7c92lnZm6YKuZmIp5T+8fZdYXp/acQfUiqbXNKHfT6rFkgEd2wjdedyMv732EZsSemtzqVKvU+wm2uNftlq8XI+XkGM5H+ewVjL+6YrSffkWOZerrj79NRHPL6xWhdus4FXLcmKFJ1YXyvvyP5j40lL5qNNhJfdTu8u8rg/Ly0rL1VG8Z7fU9Hxe1S68uRUTi2IHSrX0BY3be+0mg9mvOvlyyZDR6XgP2fqVfSsIWavBciF2HX/3HQDAV1fI6qtZJdm34jSm179SWt6vhqoQQTpBqjVLAaQXPxu+R67L4VP1Xvd5bXjIdv1eJ6tCCLWjmfAVH5D37qIbRe732Ze/AyDUeCA9ecXVTf1G1YVdf0R89PXtdZ13m3yvP3leVjeuPqgjkAFAzTkzvfaj9nvRKDa9Fd9zb+ZTSU6QnwQcY0wqEd0GYBo41e9t6314DMB8Y8xkAPcAeIOIhoLdBgNMNnnaeanyboioJ4AXiehe8C9ECoD7svjMDiK6EsBzRFQG7EaZDeDzzD7j48yBm7R9+Didkd/0G5uTPTVD38OqvQLAeRk/lxUKLAEnO4QlFxxTvsaosDLgIXB+RACI/fjbLPbMHB59PU0yTSLqNpcdYtniojgpUZWZ9e0d8+u3vHag+40h27ODpvJTUc5aMLsVKWiccAS0ROrJhhuXG1NmCI5+wGtH9BfrN7vPnQwEv33Hazt5hnR+7UKh75rWbdFSAOGg/fUUL1lSwYmcORS4TCjhmuqPQNZ2mfNBU2xGaf38QdoSlj1wvnQA6Yp1oHA0MkK/g1SqUsj24GzJxgmoVVU65JGA83PZSjmeb87bsemU0Cx9yrsPHz58KBSAWsEFY+IOjuVVxdsPi5D/zTtYpP1z5VdeeVj8Z0WtL/ASVdR14WbJxFiawv7wO84X/947c9Z7beejfuGgZDTcn1DFa7sCvgBQ/uPx/PkWIoa0RkltOpGoGvMlOq5zZ11U3/mygfBZJ3HKv/ncASkn5fyhsQF546778iWv/XJ3tsgGXiS+zle/E7/zDivF2a+MWF46Q+Y/Jdmffe968XHfU17y50tb2c+OxSTfdmGyWFbuWQFA8AsmhX0wWPKsj6o84MpF2K8aFyF+1UbNRMrz67l83X2V31zj2BC2wqLGiGXm/M6A5Pfr53p3vAhmXWXvQeMbxJc7+TUpU3ZRM44DjP9lvdfnfLkAcEccH+vqMuKj1/74pG5sfX61SESqahUR7+I5k4Q0d38bLozbNkEsU/WIvawOd04AeDlZrstB+8CH3iEpwpGPcObasKLyXidEhuYrVFCyrv1vFuv53lEcp4hSTuFDykfuxqILKUSrCyhsZ8jeI6Uox6ePfOC1lx3i72BHVUii3QxJKdXPtYQa99BDskI5EZxK1b+cIq+U915EZIioruqrTURTiWi1pbt/aqnx7e2+F6t9p2iyjo8zG27S9pE93KTtI3uUCPNjkxcUhNJlebW4+wGYA05xGWnzD78GcLcx5isAIKILICmCmwGMAJc4yzHS/mYm1N4wxQeOKx+9fnxO3H/exn1obDMUUtW+pQrx3h/+sh5dq7HfMFkVSnBWxP0JVfBMElt5hZVlcVhZ1K6Iry4dposehJNjDcfOKhVGJB8QSztZFRzQcAUeohTDDZvXe0037IhoGUdiYTmXu+7Jew6gW3Gxmh1cdP+pKs3wwG+f2XPJ+F05sJ8PpKBWNIvjp4VwDIBAr8EIzuFcfP3ctBB+ohXX35wiGUJpKkNnbxihfo3j+zmXPUr1HVYWfWSYdXC0Wsm4kmvH1wrzc486Z8o+Pv4VZ5XBhOWhRR1irEX5xZ6DuLx0qO94/x72fbetVBxLLHs3KSjHN8s55/npsXdgxKCXAQAlIuVreiCYe+n6/eq9CW6T2Ea4L38xdS822EIGpfTEqMrbRdh7qb8XR8JIA9+8Y7W3amtUWJVGsxkm40a8h4HPM/mwTCF5R4OGt3+7LxnnxPPndGFk9w4mp5lMi4ycCHLDNzlVyItWSRw4EnojeOIGgKsAzHWTNgAYY2YaY9xacTGAJCLqiH8IjcsVzXK7m7Qzg5u0/w0IN2lruEk7M7hJOzO4SftMQLhJWyPcpK3hJu3M4CbtMwFu0s4MbtLODG7Szgz5OWkDBaOQQl7O3RPAt8aYvwHsJaKmyBml/QmwGlaW0JT3N1eE+u18+PDh42SAiHL8d8rGeKLpgET0NYBRxpjviOgOMK0zAGCDMealMPu3BzDMGNODiH4ET973AXjOGDMry5OFSQfcch5TezWp5WTg8PWeSx7R43Pl4QlBZhra4dKyskv3yy5dMK+YX0PEt5pboseJIm2R0O8jGl+Yp2M5pN4rBJmIq4WR6fSutbyA1jn3xqQEs/KqR/1aGSHL3LoztMp6cOp4GUu36/N0Lo1w34G0lUIvj3DEl+jwKykXcwj0Ghx2e15xoEd7AEDRKbNOyvEzRR7TARdWqJLjSbHJlg0FJx3QCkddCKABERnwhG0APArg/Bwc4kmwrzvrKqc+zijk16Ttw8fJBBWA2mUnGpy8DMAEY4xXbsNa0X8DeICIuhtjvrb9XQBs0R82xkwnoscBlM/JyRwJ5s3vJQXMpWCNLSvWTiG1dEmwgb4O9YXyvnClSHHuOc6/GVWKCF12dpLUMYyk9OcB0ltWTVVl7nNmcArTJ22EEKDH4mpChpNiBUQkSlOTr1Dpbi7dT1eZD5cueFExGVOv4SL5++4z7Fu+5gqxLOdMlhQ1R0M+V6WwaSv7aeujvH/1XK/vvzWljqCr4h2jXvh9qrJ6unRAu5J4+4anvT4dyOxUhentC5UPuGUVoYRPWsXBtSFhLFtAKsBEPjzW63tUpVm6NNGhivI+Rj3XejH8PrS+SGjyX0wVEacmpVioa/5ukU/QVrajz3dVFe+1BK0TgVq9TT6vzbvzLf175BMSD+hTVo61SqVZOimBp5UP+YE965ARTyp5gnsulzTOImP5HNoH7a4fAFbb9FqdItj3Qrkvo74NFZkqot4BJyug73+vcnIty5I40Nv3VSFQbX5apBqmr+fvazlVJb7bZ5JGOq4HM3FTM9jHt6fsRl5QAGKTJ+zj7gcgY6TpM3BwsgeA24loFRGtADAA4VWunoQUXfDxL4B2//jwcboiPyvgnCyckMVtjGkfpk+Hwbtk3A5gB4BZav/JyGEqZOGGbMWUnB1qZVWIkvQhTcBpGMvWZ9J+6dOZSoVt6lxCvGRCFFXWTLi0Jt0XHyvnTfuANbZ0qtkelbroqq/rMj+66IGTYw1k8iY4Yk26dD8FZ2nP2C/j71VChJlSLCkiIl40wDTpxaVVlSgRXnKzvrXC0hbO8vqKqrSxQnbYhdX4Iig0dTHQ/UYEv2cS1XaVYlcvRp5BqrXUNdkoQpE2KhUOX+neYdeMxQCAxIelr1oR+cy2Y7zSCs4X+YLShSQ10hF0jm6W1Zl+E6q24NXNJ58tDnt+t1Jbo56FrlN1yJJKSqrUzNUHFT2+FK8Q68XI9oC6fi0y5ZBdHnO1IvI1P7pBrNEiVoIhRj03/Q4741m/K0XOkaIUpewKuGwhOf6mo6Hez7PU891z+HjIduwVIbyjR+W92GnfkQqF5fhUXFbQLg0xLcx3NS+IOINdJT585Bpu0vbh43RGQcjjLhAiU/8rXtYAQK9BEtwK3MVC9HsulayP4k8IdTiiLgvWH7imr9eXMHW213ZZBakvia9VI3Ax09cDnYTBpqt1r7le/HLVHw7VmaamQg0OV/09nTj8HpahpHgRmYqoL2JhniCRItUE+gyR7aOsVKeysofcKizFMf97jBsrpaCArvxt9nAIgoqVlQEqgSKXFXLo6f94fdHXqsrzlrSy/xWhIyd0FH/60SXi4y5cnaUCzGGxMiMqiccscNez/JlBvb2+NT+L37bOHey7D9w8EuGQ9idXFNeC/+lcNFZClqqqgg1x4kNPG/dsumsCgMN/Cz095iJbqKCOWJ6BDkLZDs78hM/frIPXZzZKoYKZ3dkHr4sfpFzdzWsv/EV4A60/5HeTylWVsSqRpoi6PBZdiIFiJIPEHOGYjZki+ffbp4uUQcVfOBsl+J3QzKmsZCuZaSyOZnYrn7GyzqlXP27sVTntxURiItCqBwAg9YH+0nePFOg4eCP3Hz0g70Lpmb947eCC6QCAVdff7/XpYifBMf8n520qzzvQ4do8zbwralTP8aRYb83aUzLL58rHHY7ibvuHEtERIkpQfWErvdv+KfkzfB8FCW7S9pE93KTtIwdQk3Z+IIIox3+nCrmyuInoUwCJAL43xoxU/b8BOArgLWPMO7avPSRvOxbAIjDDMt715/S8qSOuNgDw4gvil3SC8bOqiuWzNEV+uR2L7zxVHGDaPCHyOJp1PeX3/Vv5uJOsr1VnROjoeN9KYt3WGsrW4QvDJCJeVgnzOCH4mgvEytYlplxpMVfwAAB6qtJXL9pMhXAi9QDwdjkW8UlRAj+D3xWO05DL2eE7+jbJ1JzygeT7OkGtc4vKvdDCSO8k8vH7/yyW29hWYhGX9bJKxA7YrSzWa7ZK8dbgQhZsermjrFJKq3vV2t6r9bukDFvrdlW99rczOc7RW5cGU0i5qisAIPZDsUJ1oQQnezB8nlzL+DZXeO1460NuX0sYtbNXiWhRy8q8Kvrwb4m336cyOVwGUHnll+2jxrqtHU8yf22UrJl0WSUPXem1X3/gXe4rLfGQv/bLfbksh1klWuSpT0NZVRX/kldyo6rI6qhxnLAUl6jvk8OQuyR89dKL/H0sWUie+45j4qN29+WtcnJ+F3sCgO3H+L3r/oLkka//jxRWnrCGLf3zispnOrwgmu6f3SF0kQ1KgmL44T15mlFX1qqR40mxzqo1p7fFnQnFHURUA0AcmFDTL9xnjTEpYEZljXDbffw74CZtH9nDTdo+soeetPMDBYE5mRtXSTiKO8CT9UcAfgJQx1a2SYcMld5zhHRV3heuzv4DPnz48JEPiAhQjv9OFXKTVdIPwCjb/tj++w+w9d3LGJNGRJ8DuByAK5kSrtJ7+5ycLF2V93EjDAAMvenckP2ani2/E23Pb+K10zZzIeXtv8rSsfc0CVIdHMaBjbinJG+s5tPP6gGEnGvEYBl62gEh6wQG8LGGbpDAktkvS+HAzXeEHKv8ZapSka2+rmtCajgdba3up+GINTrdTwcinYvkttE/en1jHpPgotnBwaWIW4aFPf61j13D+30n7oUB3SXgum0ZB1crdxdyR+pWSfEySexWiKjeEBs7sYdsSD+pGR08JEqAhWpwcEwUooFUpdR36auhYwy+OsJrF7l5QMj2O4fK8v7wAnYvaJr7ddeJj5Sq8Jmpmyweu/6f1GmMfvRxAMCwb/4Xch4AuKk708yjmsj9SVsnAcH4Mvys2w2WoDmU+h815vfilhvFWDm+TVIT693/UMg5hw3I2sd71QXiqihyiehxk628dPtN8i5unSVundYNmGwTPCQptRu++M1r32nPm3pA3DfhMOAe8Yomfy9SRolJfNw/7n/D62vST9yFD1l329FN4qrSQfnzX34fAFBqQNYVhHKLApBUkrOJOzOKOxG9D6AWgO/ssiEKwFrIxP1TbnzZPs5suEnbh4/TGWdMOiAR3QKgaRiKexqA6caYp1X/OgDtAVRDmCCkDlrmdJBm60oDAItbSjXoxiuZALGqqVhu327a77VdEOrWPo28vslTxAp1RIwht0jA7rcPJWA3z1oRmhr9ogpy3T5MfuUDt3G63bR6siJYkCyBneZWlrLzBkkLm6Yq4Lh+ffy71opl81w1Tm3UGto64PeDrRiviRJdVQqaqz5/8VAZ85CHxWJMtMHBriUkCNZCUd4nJLLl1X+bnFNXIXfBqd49JFA8Z5pQ9i9SqW+O+PLr5WI5H1ZU/j+t9X1DR6H/F64sKWYLPmX6eGZV3lOf4Wo/kfe/4vV9oqQEdltSh6bMa0r4nR34WqNvusbrBGLaZgAAIABJREFU2/mkpFaWbssJVV++K/R/HXx0gcILEqRqSys11uBHzwMAnhoy2uu7o7VUsEn4mldFuvJ6O1VZaIuqku4kFHTwVVevd/hFySu0/EwCeoEmnLKon2WkmrOqFuEAf1FV5b3V22Lxv3AZ1/0sqj6kSWougP67EixbqdJAL6jGAf5yrzzh9b3X/Vavfdy+Fv3ay/iib5Tn8sF1/L2LzkCYuXzfjjzNvOsa1M5xcLLasr9P6+BkZhT3qmH6v4AKXmaCDkS0Wf21zmZ/H2cANFvRh4/TFQUhHTBHrpIsKO4hau/GmLvVP2eF2T4LQGh55yyQNo8T8VeqdD3nTd25T/yjB1Slj2KWBhxUdGJdAeeATZ07slL0r7YdU5VWUkMp29tUqlPKbKE8x/dh6237cfm8rupSTFksDuEq4BxRn9HVyl1NSF2hR8OJROmqNI5UA0i6n/NlA2JlA3JdB8NUGOLtoVH7/WGq8Wz8TYSv9qeGfibQvItH5tmVyb1y9Ob1S7Z7fXXKCzFJP6NwMDt2hfStVjTrQ2Ho0brCzZqlfI/qLxCp1JUbRRAqdhmnlG4NQ+0GgIP2vcmsUk3ab7yq03UcN62XWqhFrfWu0+r2qPsf7g3YkslYHP48JN+BlrOnyQa7QtTyA2VUap8TmdKpjVi+yGvusp87YuQz+8JUKFp/RL6j+puwdmsyAKDcQVkpR6uU0jX2/OuXyXt7VqTEeVzK7q58JhH6lHcfPhS0LrcPH6crCoCL+5+buG1Q831jzLX235EAtgGYl62/+yBbJDWKhIogNWkr+Qcxc8Xii4vnX2YtihP7k/j/LrESpjvX7/P6urQTX2GTVaHSkJ2Ki98ytoWiTFsaci1Vj69FKSVCFcbKi1FiQWY/W5e3KrKQ2S3X4qqvp2ZicTs5Vi0Spenrjlijs0a6fiaZDs7S/p+SKhXCNnBWTOh9v6q6EFQSz+LMnuO75POdqxUL+YzW425bR1YUq9aJxdmkE/ujA6VE/pMSpcp7mSgZdzhE1Kwe0tdclb6q6qRvjdzL3qXEtx9vRccOzZMYQYPqMpa5tjp72xLhixP0q8Crg6p1wpfEi2jD1eNrTZIYQuUasqJIW86W/uOfPo6fbmGJgTZXSgbMTx+HFpi6pGR8SB8gsg6t1PWhhBpXYb4XF6trqVdPnsuKFfwdKFFUnn/gRqGZX/L8ZADpJYwPhXlHKxUWkanml0nM6fguzrwKnC8ZTj0v/dhrV/yGVx9VasuYk5+TeEPf+vzebdiUHHLOvMCfuNMjBZyVEm2MOQygIzLodPvw4YPhJm0f/zwKQiGFf0xkioiSwT7xP4wxE4loApiQ0zZbiztM6bLkyzsBAOL+Nz3/B6uwprnkldaYPz+LPbOHy/4AgAvXq0yLd1h4x+WDA0DqU5KvGvl/Y5AR+VlaLBxOdmm0vOLYHUJTj3r505DtZud6r01lqoZs18JKgY5Xh2zPDTa0bOG1q8z7LYs98xeL6rD16jKsACA4+gHZwfrZw5VuA0StUYtk5SeO38W56oVGfZJvxww+e5fXDgwfFX6nPJYu29b8rBxPionz/zyts0ryCx8DuJKIigA4G8DJLRjpw4cPH7nEGZNVkl8wxiwhoqrg9MKpWe1LRAMBDASAVzs1w82NqmP8azO97U78SRfg3XBUsgeK26ySXp1l+wRVgqqYLW3WsIT4rRftEV+Zy7TQebHPlhT/6XVKrKfUeC6T9f65fbw+nVN9RRP20Wore0YVsb5dnvNElW98mSpd5kpL6RJNI/YKI9TlDtdXvugeX4kvcELXgQCEAQkAHzwsFqfLGtG+7HCl0XSfLndV1wrll1QMwC0q+6Ovuhbnu/+8sTD4UlSGytnWH39AZVI0U3nOz33DvudH9q1HOKQ+yYJFkSPk+u+Kl89XsRkSOj//EV1ay8YT6neV9+b7z8Wvnmiv9dd98q7cskNywt196aVEyGovEr+0k6v95EtZJVUvIj7g1mMkDnHflSMBAP0rSLzgOxVHcO/m/yVInOepJGHvOuic8Nvu7+m1A7exNPJDxap6fS1VPMAVJtGFKC59SBifI+5lPRVdAETngT9qn5H+3nQpK+XxdqTw8TvMEUbuHxfI8afv42u9UOXEN7+jq9d+v7yUUdN6JSOOCNP0ROBnlYTHZADPgUk64SM4SE95T733itNfNNxHttABVx9Zw03aPrJH/otM5evhTgpOxcT9NoAkY8zSnOqW+PDhw8c/hTOG8p4vJyJKNsbEZehrjxzQ31Pv6WMAgHoqQmYyp5BRMalBRyr4RwmcKhR8bqjXFxgmFaJxmJe6adtkmWv2SaJ/RDWmCVMJKURvUiRtLe1DOZbZxiliEX1vks9Xl+AhCsny08NxIUWkWXp6RHkRA3LCUwBgDvLSz+xYL8dXIklmH6cT6pqQh8eO99oxT3NwSotEBW55LHRM2UAHLF/bqQKiSZw2ljZDaPTUTioTrel9ndeuPuIGblSVZW5ENblXVILdSsEpb8rxVU3CiJ6s460JSsEvpaI7LNnJzJNKKpH/Jzwxk8JkD7NFRJwiGrWXY73H2RxmmVwflZSFYeDOZ3h78l61XaVxHmRBJAqIe8HsF+3u5NsGAQDiP58h55wj5OPUD1k4qfCr8qyQpkgtEaFkLhwSQTMUFqExs5eF1tKWqqoykz732l5Q96iIRBndXrfMHkdVuCkkbp1AU5s0GiPuD3NA0mjdM0pbI1XuI2qIEFzwZVuxqrBKN1TvpdnB7sC090W+IHDPC7LduuBIf28AILZ4nmbevec2yPGkWOKXZadklv/HLO6Mk7btm4Uw7EofZya8SduHj9MYBcHiLhDMSWfxvNNdKmXcuJ0tJl1dY6Oi/sZZ6mzPKkJuWP2yCDv9ZcWMrmko5bRGL9rqtR2ddtRBqZrzcAUhDww8S4KTFT4YBwD4sM1lXt+yFBEDesAG1xK+/cnrm6EsZhecfFyJHT2kgo/3lGeCv6a0P6OCUP+tyVIvuvL6wLclLcxVq9FSrG8+KMI9jr6uSTU69dEF3LSVfWsZsZJdlfTOiqD0Y9I4r60DqU5kaXSXQQiHs2NDVycNq0twbup9XGVIC14FLvW0z3BsCD+DqDETvT4dfAz3XO8tKsG9y0uz9dj0VgmefjVK4ugdfmWhsld/lJWaroBzZyJblH1LixV63joRmTqWxGStt9V7WzNaLM7zPubV0TA1pguLiULEYRX0duJWd5cVEakX1HVRaX7vXu17gdd36yARVXO4o6QEYnXlJgf9Xt2qJGDv6nonACAqk4nuvwf4HR3bWr4Xukq9q9J+2cOyknaCaACwMIW/o+1UZaYLeg/w2v/XmFd18YH0yXF5Dk6eQp3tnOKfTgf08S+Gm7R9+DitEUE5/8sBiKgLEa0kotVEdH8m+1xBRCuIaDkRfZjdMfPV4iaiIICl9rjrAFxrjNlvUwCnGGMaWL/2l3Y7AOw2xlwU5nCCsmwVVywcWkhASzqWD2MtKGYzapSQX25ncRdrLKlixZaKsNHRMDT1ikpWVdPYqSinfiUoMamyhaRdqHQoJTkqzEM/FuacgNRkjMnkRUm0NR8L6c1K5MnVhHQFD4D0dQK945wVUrwIgKT7OV82IFY2IGJDpRU1utxhERZyCPS7B8eHsnVVLkpePU2Zdve9RCFVZV7dF22dhkNEyYSQvnox4pddoYoCOFRQz7VMKWvdVhOLuGikbI9uwv01VP1SjeL2vsZEhreJAjZfTr/LicVllUGJvLqpooSd9HtRJyFUn61C4ay/xsXVs6aE0PtTSX1ei4fVsYU79Ht1bLO8A06oLDOL26GKSif8U91/VxfWrFkT8hkAqGE/F6cs6ohqZ3ttl4ZYJ5MCIyeMfHSVEFEAXJ+gI4DNAH4nosnGmBVqn1oAHgBwnjFmX7gqYhmR3xb3YWNMY2NMAwB7AQzJZL+f7H6Ns520fZwxcJO2Dx+nM/K55mQLAKuNMWuNMcfAJMRLM+xzM4Axxph9AGCM2YlscDJ93HPB7Mg8Y9b9XHLsL1XiypVUiFQ3r1mcWNS163NEO0lVC4+Nlcu9tgRb8V98+ofXp/17bVTSv0P9GLGM5m0WKcoKL48EABRXllnnRLFsCl8bWkO5RQex6IJzWaxnWKtKIfsBQEcrpL/zeHhJU2eJF1aSmPtfeU9t535dWqy8Ki3m5Fi1SJSGI9borBHtz3aW9our5Zg9FLEJR7jMW6Gn30LaTvZ7pnx0ibdZ+yg7/pfJQp/cLQSaqpC49gYrERpaxI6x50c2ZMqqviJqpdLW+ks15f1C5Y/+2F7DOfeIzMACJQ0cM34OX0smq5/uthhFxYrhRaimWtnY3heLX3r8F0LwOdyZ35XzS8Vhv81PblxfMqfWrRZRNIcmcWGylgCYZN5XL+S+VP763jbLqlGcrGKa1RTi0ES7QktV37FAvFj859l7GaXeu3DSwNsVmer2q0RC4i0rmEUtpPTaxWXlyX330jcAgFlJUibwHKUw2dOKa+3IRuo318hfAk4FAJrAsBlAywz71AYAIvoZrHw70hiTpXj9SfFx2+VBBzDZJhzaEtEi+zcik318nGFwk7aP7LE/n0klPnIBohz/6aLm9m9gxqOFOUNGn2gkuARkezCr/E0iCpXXzPCB/EQ0ES0CV8ZZAOC7TPbLthalpryPblkHN9WugPWTQiU9dynh9k1H5Zd59yJ+8WuWFstv43bZnhTk7XWUBTFxu+RpO8r7OepcK5XfVlvfVIup6ntS53h9f+6UfWv/Mpsbna6Vsf4hBXBrPsMZJtOXSr6sCF0CC20BibSQ583YZzMlIkj8kwkdJWtl95/8460L+OrSYq7oQTgpVkDo6zo3W2eNOH+2trKn7JV73aMI90dUrofgRM7JXacmpmpFFFV+1EcA0pfLOpgsFtXxbDJs46uUCOnbrd6Rv46zj/XC6pJhs3CfjLWFfR9ad5bshn1fi1RBg3M4Z/unGZLVovH7QV7hHV0vz6K02t6wGN+L+dPl/pdS8YL6Q7p57XGPcZ51/ErJklin3kGX47RK9YlwLkBxnFGlaegXNU5ERixUZfYO/y0+7EOu2IgKFAWUdb84hT+nfdz6HXXSwHrFM/tLybBJcHGATfKDvnrCLK+9ylLunS8cAKikjH+RKqwSTk72REGBnNuzmuGdCTYD0EvpigC2htnnV2PMcQDriGgleCL/HZngpPi4wUW6o5C5jztbGGPGGWOaG2Oa31S7QvYf8HHaw03aPrKHm7R9ZI/8nLQBlnXN6V8O8DuAWkRUjYiiwGUdM3oiJgG4AACIqBTYdRJaPFSPMT+Zk5odSURNwNkjNcB+Hp1VkqtiwcHRwwwABG6QQqXLG3C+bP1lC8N/yOGYWBOICu8LPBGkrRfLwXzPbLTAjQ9n+RmdDhfod4/0T36D+y65OefnV74+XaDAIeUqEeOJ/ZB9hSZJYh6OWZob6MLMtf4IFfQH4PmzUUSsb824fPV3lviMqJeZlzoU4dh4zn8LAGmrJE4RqMNrpOAnwpYMXP9gyDGDr8u7FBj0eMj2tCWzvXbE2e2yHF/wt2/kWC26hmw/PEBe9ahLxaIO9Bocsm/qA/29duTTE7I+bxhZVtcHAIjmZxA4V2JhTkIYSC8jnFOY3bJSpFIVsx6fvcfh7m+6/aZLPCagVqXpcNjGX6LDF41IhzzKuiZ3b5njSTHu63nZnouIugEYBfZfv22MeZKIHgMw3xgzmTjK+TyALgCCAJ40xnyc+RFPYnDSGLOQiBaDf2HmAgjND/NxZuFISpab3aTtI/ykrZHdpP2vwuHwQfOThnxWBzTGTEUGNVRjzMOqbQDcbf9yhHyduDPS2o0xFwMAEV0KYI3tmwWf5u7Dh4/TFAWB8n7SRabskuBSAAOMMdn4NcLD/P2bAQCj3B4R1Tk0k/qY0J0jLhEtX7OBg0dmoVC3I0e+4bWDH3MqVOBKEaEKvqoSXOL4NyjQX6jjaStErMdMF2GgwF3P8ud/+VI+H5DfxEDL7iHXFG55mPr0bTLWB0bLvl/Y1LjSEpgJtOkl27/mdEkUkUCrmSlxYerDOtybB8m1VBwjYj4UycGfcC4XQORY035Urjn1LFzl8sBQcRWZ376X49cTF8vgc/gZjflA7jVVq6s+N4sb5cW9cvQTEUaKef0j25AUvtQHr/fakY+xOJUWgdLEobQ/2AWiafLp3E7W1aKX5MGpItgV6MbncgJIAEBlRaog+OFzfJxuon2eNultGctRvm8R3VXVHRX8o0osyxBcoCo7LfpVzn+DcvsQh6iC8yVzLNC8CzJCC3ZFtBG3DRXjlNjgvK9lKDPlWBFd+B1z3yUASJ0m44q8yl7j/j1ysgpyLwJNODyZtniW15f2tRIiK8GB5J+ekefb9qU7ZPvZLOVg/hCpiEAfCZs5t1Lg3vQVfqhCnTzNvCk9z83xpBg76ZczU2TKLgmydv76+FfATdo+fJzOoAKgVZIni5uIKoLpnPXAGSpTAAwH8yO8ACQRPQHOrLsEwDQAiQBcLs9qY8xlyAIpl7Q2ADBuhqRQuQomr5URsaRj6loaxbL1WTJG6LAHVQpakiUKaLr13IOSXlTG0oR1dRN9rrqqWky7wR0BAJ8qcoOmIVx5QxsAQOQTYrltbSukg3JvcrbFtx0lMNNt419ee0IiS6AeV9fnRLYA4I2yTObZrtLe7r9ejj/6Xa4QN6SfWL6/T5Eq5rsssUdXXi/5/c9e+zMr/NPzS8kK0SJRjr6uK9nodL/H96/32sFJr/NYrn7S62sYK+le1zRlGd2ZyySQWlPRvJfa1L1+W8On4x3o0R4AUHTKLK/P3R8A2G9TJ++e+LTX98U1Eqh0V3B+TRHcmrJS0ih71meCyOg/pM61rsbj3pFqqqpNl41yr2da6eGiqlrQ/IMSG7jxJq4C//7bklraXFVhX5kk76gTmdLX5ypDaWhBq7blhRjmAswvlpIKNY1Uut88+304mCrP9dGbJKg84QNeaRVWPmH9Drjvztiy8r1x30sAWH6IVx/X3SmrhL3TJOj9wTJOjy2p0iWvmfm+1x7fnlctB1LTZ5UMPbQnTzPvocva5HhSjJk4p2DVnLSR0M8BTDLG1AKnsMQBeDLDfiMAnAegpzHGBSivVpT3LCdtH2cO3KTtw8fpjHxOBzwpyIur5EIAR4wx4wHAGBMkoqFg8aiZAEBE9wDoBqCzMeZwpkfKBmSp6JFhggb63iWoxHlHD49UZ9XU3BRbAbtMlFjklbSIVJjfXP27XrGEEvs5nyvOR78s/sEDyvII7mZij77Z6zZLzcLEWPbXFqbwv6NOeOlYJqsjR3rQYkoRlSRVq3QU+/mDSjLgsMp9dcddtU4ISLqmnLOidMEDDbdq0dR1TapxCPQc5Pk7tZW9VEngOoJHXUXmSVPXnZ0pVLhiKAFH5/lG2SEG2vX2+pLTxN9exopbxVcWOeD41eLDXbGWpQ4qZiLs5M5UOiq88FH5BL6+VXtFikFb51SMSVD7jqsxK4szMsxckdl74aAJMOWqhJKs9Of3K8q6q3GaoASzqJhY7E78an9q1nnUulaqHr6r++p83QAQVF+8ova8evxmt3BXUu24i2Yi6HXCKADBybxM3PXB7EgPxpgDRLQRQE2wlV0HQDNjTHKGz35ARG5K/c4YMzwP4/BRQKCDVD58nLY4w4sFE8IbQK5/NYDiADoBmJhhn6uNMfMzfjDdQRTlfewrozDwhgEYOKh3yH79e9T32otnCtlor6Vxt35SMg7+ekqEhQpbGrcTrgeAs+4XL8+CNaFiPo2Vf676vZI14LJGmlZ81OtbvlVyT/+ezePS9mrFMiKIRdaHvE2JSGnSSWUrb5moLGqNTpbmnaosH5fpAgCt358JAChUQzI1/py83Gs7WdAmnaTKvIarvO7KigHpCx64FYETiAKEuq4R0ag9gm+MBCC+bCA9jXrYN+zbHz1URCOpmmQqVPlBMizCIbJHt5C+rhXEet6eZLNhVGmxUsrf3PkJLrMW0Vt8+L3/I2SpiKv4GisPkOwHDVcRvVix8M+q1secIbS+i7yXF94kxQ0Cw0cBAIYOH4XZ1fjdPqZiF+dUlWtx0PIL4dClnpCt4idO89pm53oAQHslqLbzuMQmBjfhZxSlYgxUVZ5FLSuxG61WsuFkGa7vIllD038QH3yPS6zQVjPxm383Ut6bs+33remDEtSOqCsiVWfZ6y5bNGup39wiN5T3U4W8TNzLAfTRHURUFMzLXwNgB4CrAXxPRHuMMTNzc/B0GgCHkvwq72cA3KTtI3u4SdvHKcAZ7ir5/v/Zu+7wKKovel42IYRA6J1A6NKkd6RIbwJiAxWxYUMEwS6KvaGigig2RMUG/kQEEUSKBZGOgIKU0HtNQgrZvN8f9725N9nZJJCgJM75Pj+HmdmZ2ZnZl/vuPfccAM8rpYZoracZRcCXAUwFcBoAtNZblFKXA/haKdVba732XE60s2ULAMBvQkr1alPnWryA2QWlhfh+OyOmo9fxKYtGcRTUrjxFGTvufJy/0B6Osmu5CPYXFH+J597HBrW9EokVsPsg5y0rR3EUdNGzgV1yFTvVDljXshxzk6UZbmFjELsngXPUUi93zT4yi5WC85XF7CTWSNtWEZ+5qStH17HrSb7TVypQZB8AThlZznQGvgLW9EBKsUqRKGtV4bt1nMM5l6wRmc+2kfbwV9lM95WB/G2/N5ZhgXMvQuKHpPFRuA8bN285yqyNgiY69K9mnnv5cH4vFo6ljsUWnzC3+QdxrX32U757036eUcn7WsJE76XEjEpiac+bAQAde7KN3rwpi53lLrv70/m71sTv5t0OF7WXuFOBRhDBxMcsvtnI4mXNG7JsWt3FxMtPEDWAltU5ov9lC33XSBFRtwxjzrsd3mTePdnlUuYs5N9orw7MMJlpROOu7szMrasuY7nbJfNo9jXnMWaS9O3NM91I847FJ6RibzLfl8Bf1tkhLzTgnPOcwLRpDgBwpVLqbwBbACQBeDjDfisA3AjgG6WUfWqfCFnXH+DhPwGnUchDlvh9gTvd0UMg5KCdK8hl67LzgRw14GitdwPo67JpMURbu9Z6Pjjw6ni25ylcmPKGPVwkKXvu+hOzoulvbI0aHDEWKEfLqcfjsfR74rt2fpjFUk/PI55y2cLh0IY10VHkiKOKUhS2v30rlF9KedWLmnFettQO7sxTLanjsH5djuIkuyGkPZsGWCSsjeVzHSYbrPLVAhkRANCwKX3vtCR3wfiWgilgjU63/cKdfa3bxwAAUv7cgRBjmRVemSP62hVMlJWUDFU1JuD4TY3ZcdL0mSjYgwSXpIGvtRaThgdSitXm60Mu6YfE4ZRDltxsyRqx+WwZZd87k+V8X+xSM+D6ID5f6IlxAZs7NGeGjd9IkcY99ASKzaaYoX43PqbMt6sqFEs3PMx5YWsk0GVgQ5w5GqihUTWaOi6TEs6g1KBAc6eqZWl2cWDNHlTsSumQNrWZwxNagURg29xQGonrqDZSqGc7Z3vSkkClz5ZtY5zltL+5dBRiujB71mJh2VJ9md+vSlHNo+lFfP4Q0Z/QJIV/DydO0mwv4hKWC24u3sd4w5KJKhsoAnXl3i2OQFmBMjyrbFKK9v37ifdQrjzNUIqMucPZ3j6VtW1s/UqV4e9qe1AqFAhDg64u78U5Ii9E3HnC5T0z2EE7GOygHQzanzmVyQ7aeQFZuVOHuHh2SqiqMZlut4P2ucIO2hcC7KAdDHbQDga3QVvCbdCWsIN2MNhB+0KAHbSDIV5QG90gVSXdYAftYJCkAzfk5qANIN+zSjx48OAh3yG/s0qglBoA6p6so7X+y7i5/wlgM6h2kQDgRq31ZrN/CwDjQZaAGsDPAEZorTP9kx1i/gK+u5yt2yxB64wg7H8rHGRq/k2FzDYtmAI3+ymeelUwBSnpkbc7hXNlEUfo4Ul1jVlLuYhStwhHCZXWU0v5wnXsol5QXEu3Ug8AAEKfmeqs27uXqe1RRrt64+r9zjppSjdnGTmEHBO0sDvE9q//plREtIioez/GxryzniCKVb83xzjrVo58zVneb6iRZQpwSqLNXazbPP47atl+7C0Wxpr7AAsnWed16wcJpHeqqW4KrYWmzQFOUyH1jxochcl6lqX72SIkkD49cr9xnknXgymmtv4p9L1CJjDFbPwipqBdZBzBrznO9/pz4flYwTTONKzGqablB045ywe+/gMAsOk0i2yxXBWw0DyLHjO4iFdC6FGHmkreyumc8tgh7tuVTWIAAFN/jnXWXX6I35WvhEPN3eb/0xbwrPKOT5guZ8WrvtjExdUby7GbT+Ez9B2mruL2/Q4lONWx4AjNKmJEM1Udca8//JXey0Jippcmrs+qy38Ry2nF4eX4vm828gW157FpRNwwLip/uoJ+7xVEM5N/IgulHTbUxTdnpOc8jMqpIm4eSJXk9E/LINDgK+27t5lW9oYAPoQpViqlygL4EsADWuvaAOoAmAcgG8roHvIFTp/Keh8PHv5t5IHi5DmLTCmlCoMi604AvtFaX2Qi7m+11vXNPvcBqKi1HmnkXdMJiGcbLjzuM6PJDTvs5cBGj6Dwi+KebcDwC1NWX+AExM1JJiNSHyCKUugLH7tutwYDJ/p1d1YV+55FhPxTiJLoG8YNPDKy8A1nQSTnnPezLGjoi58EbM8pUkZc5SwXeD1nNlrSrcb6IOYU0lXnrQSeiTkStLtZkMzKi0qc6M4FP/kskEqzLn0w1lmlKro3Jln4X+WZjG8UybrqoxzF6sPsGhNyUUaD73OH/7X76Zz3cBOZ/2chN9zGFMVDmE6oTSEcAJIfopi94LtCjjgX4f/tW7qOVtk2u8r6mPOmOsu+HkPdd8qhA07qnb2zPSiGvjknb4lMAegPYJ7WeguAY0opW26ubmh+20CODq+Y9fWRoUU+M0j35Cn3lReTAAAgAElEQVTvT83BZXq4UJBbg7YHD+cV+TzingNggtZ6gVJqBKhjchLSR9xXg3LcPZRSXwH4UGt99n/ec9A5qfdxflNVqJHJnv8wzggvzLDAlmU3n0UJqfsR0rBjtk4pjSJ8dz6TyZ5BPj+Lm46kEUGWn1vDpgp6Js1KpMRtlpDvqEv+0S36zsqTMzfh/56Tqr7uQwK3L2XFB1/73BPD1MdIcEmVqJDFnmdxzDhBcy3iTk/NLtL+otqPnGW4/R79L97jrPPdLd7LiHSGWtlHTiPuu/tmP+J+Y3beMVJQSpUEqQPWV0ppkAmmBvBmhl2/AWB/oRsBNAUZCHv4D8IO2h48XNAIyb+skisATNNaO2GXUmoJgIy2z+1gvCYBTATwu1JqjtZ6ufnMdQB+0FofQCawEU3iu/zDL/wlWSilPsPt5Kk7OK8Y1pJc4FGKBXb078Kuqy7xaNNWs5ta6nGu3oeVpQaT0Ke52y/lXm63lY0KiDQt20Ks6PRvXL2P7Extxulykd+LQSzKNLNsZud4363j+Lx3UZR25gSTbyI/YdMGa992+Id1zrqyb09wlhOfotx5wVuH8meev9tZ1gfJKCCkBgvq+wSrxN5j1ZCbL+w1AUBISWp2OrqEv3ORKhytOXZjDzd33N+t4QGQvlnJikTZ1nUgfVONZY2EPjreWSdz3Db6luvOjGRuUOJWYvtEDuAo3L+O7/uK2fQdGrXmKF46ooT3onz5gYl8fRV/We4spz5IZhjHlzMrpvQclvu1983XiFu7D07j7WXvu9lZTltCswa/MPgIq8H8ct/9dC+ShvV31hWc8jUyInUMu8D/OZefUYMNlLlMvIld4MOi+feSuJHz4RaFHn2Ar+8TYhZJCeHkVSxeVugjekelvSAEcyt5KzFMCo1nhlPqcxx9xy0jtkzByvx+hN8rzj+LHe3jFvG7X/yXPwKu+6yQjwfuQQCez7BuJohBUl0ptRZEB0wBcAsAaK0PKqWuATBeKVUGJF28FEQn9PBfQMHIrPfxAIAHbQ9ZQw7auYI8QAc872bBuQKXHLf/pZEAWAbz30Tan8Q9DqnTyn0Hw1zxv8qy474xrzrLOo7EfFSRksguLKMASB/J5xas5CfAbcapY29y1oU+9T6yC/8HTzvLIQMp+lJRpYPtnr1jiry5bFG2+exgrBOLtM3Mo3YMggX0cZ4EquLlMr0WOfsoMCmjgjGyrGecK2weX+bw9Sm2WUMqsahyMwd+NrAzZbe8/3lFTnPcowdmP8f98sy8k+P24OFcYAdtDx4uaOSBiNsbuD148OBBQkgSX6jI1sBtDH8Hg8zL00Bdvi8AKKy1bmb2aQZgvNa6o1KqI4g9sh1AQQCfaa2fUEoVAvAOSE5aATgBoIeLtVk6JBtt6Re/4ELi2GPUkvylaI7YlczNNJWNq0vnOjwll7rE1r+yTiFWqfv5JF/GKb9Odx4AeLx4jLN8fTWm6FV9m1IB7wk3bek8fVMLKt4UnbuUzyWE8tvtoILO9Arc2j1YuJiPLUbnTRTt/eNP7XSWnzDXZd1XAODadx90lifcQBSre0axm/bMN1lkaWsiTambFeFpfPed7Ew+sgipA044xIUteS+s16X0Bjwi2vOlI73eTcd9p2ZrZ530hLRuNVJDW6r72fb1J4SzuoQtRLoVLAGgrPEvlZ9/pBh/lw5GtbCtUNz732K+/nrGlWXeMRaZeuho4DtyeVlWqmz4F+dgj1xKrfhLtrCPZbiI8HqOo0LifSNZ+/zasqzEuDqOC9TW0d0+HwCYEBdYUJTP6pHrWzjLBV6l4t79xVkju6XQkV8RRymemhH8Xg0dzc00DzxFzT4FRICaIpIM9h2V97d/SW6U3pxIxx/0Baf6Vt/A/Xn/O0Kdtq2j+Dfa6zlO1711L9FTD6TwuwYAT6UEuledFfJDxK2Uag2gD4AmWutkpVQpAFZ5voxSqqfW2q2l8CetdR+lVCSAtUqpb0E2Zge11g3MsWsDcNcq9ZDvYAdtDx4uaOSHgRtAeQBHtNbJAKC1PgI4BaGXADwKwL0XnPZPUEqtAlDdHGun2Ja55qq9yJoxAIASoYHV42RRXJXO6tZ5Oi6O/y5Ib8FtSURLKi8kJU+JKOr4mfR/xYH0btUSKpT+jhUSEeefIgpISUwN+IybY/3+lMBzAuyy7vYZAIgyamb7U8R5hGO8dcNOXMVt4DIiPm31tIsJ53qBKmb2ohPYgeikmFFsOk338pIovpd/nQkUt1fRdZwmHukMXkCwr6wnZEFBybIa2gCLRAWDpfvJvWyUDQAHXe6xX7xDIcbXJTyaC8Xhiql91evQ+pSf3HVX4sz32incihrKc5mZnCQFFJRT85p1AQAFxLu0TxgFlC0Q+JPNirxWTKjdpSWJ52IkHqTL+5ZE3u4z75ucPabt46KtPWqYuNb4M4EyydWESNX6BKY2OizL1SydvE/QBe3vLUy896oVy+UeSKG2kVxvYMwDdMDsXOF8ANFKqS1KqTeVUh3EtmUAkpVSnYJ92DTrtAI14LwP4AGl1DKl1NNKqaBCurLl/Z2Vf2Xv23i4oCE7Lz14uGChVPb/+7cuMTt0QOMneQlIUOo2AA8CGApgDIAoAI8AeADuOe40AO9ord8yxyoMSpl0AeXNW2utM51Dp62YqwFAFeW88pHrySW79KJfnXW2BRhwp0Cl7WD5zpCq5LAimwN8o1/gz0dSXjH1ueHOutAxLzvL/vVLnOVFlxM1sbOkqJUIdOtxEyMCgHUXUUwmc6FZIW3ramc5pAY1xvhXciOHKsROIyhQMN1+QaE5WvL/wOJdvq4kaJVVm71/AYtdqWp1+bALmKrvMxKn/kUssetrLxwkjfiX9IT01b+Ej2XkWE8Oud5Zl06w6z1qslLtWBzMje4XjC7of5+uL2UpN9UUnCC9NunHmrZZOM3U5Xy9bRP3f/MOb2/CBhRpe6h2IYWX/FO52Unvphx16Nh0wrW8r3jG2EYBje/qkc6q09ezy334qFG0vUlXZ50UD/N1oBjMN/Au13MhkWo+adv5vQyp19Z938yQKEpYso3diK8F4/frY0YCNpnz+mkLuPHJN4SE2ORvAQBCLu6UMzrg2OuzTwd86qMLlw6otfbD2JEppf4AcIPY9qNS6ilQVC3xk9Y6QBbMFCK/AvCVUioNQC+QhreHfA6f0KX24OFChcoPrBJTQEzTWluaQyNQnrq+2O0ZkLZ9ph5DSqm2ADZprY8rpQoAqAvhTRkM+o/fAQAfj2IplCH76XK+q8xu2etFLtTmg2/ryBXzucuYiWHzwTe25Ir8VzVYhP5vk5d+5kSss05Wx+9ryUyHziuotXdGA84irYnnHOfQqjRTqLWWxRHnV+Hr7mYYHC+X4pbz0Uf4Vt5rWAMRIlcpr2tSGfqOpcP4hbtiGbc+f9CC5D1vuIH/tr7wzi/O8lGT7768FFf8LdMFYFaCZGLcH8Wt1xWNC/mlpTnKX3OcWSH2WQHcNPK/68Y66+LTWPzK1iGk87r0hLSmB/KYErZ9vcDNzE6Qz83ms4OxTu6qQjnsusM4Sv2xITe4NDM57mmreHZ392HOgdv7cllJjizb7bjVWU59lry03+/HUXIzURto+D2ZVaRtX4d7G5Kda/fiHJFKBs7APVQiyopV8nZZ/g3c8gg3C/n6DwMAjBHPsnQYv2M23y+NFAbczdLE9z9DskOSTRTv52D19Xi6lunVGzvrZJ2mhHnWnT7gZ/WFeC82nab61EDB0GnwDm9/qST9XlIyZA0eSTqGHCGfFCcLA3hDKVUMQCqArQCGAXBaxLTWc5VSh4N8XqI6gMmKKpshAOaAWuU9/AcgFfs8ZA47aHv4F5AfBm6t9SoAbVw2dcywX1OxvBgukbTWehqAszYWOvoW5bWS0wJTT2WErVE7McVpcDGJ5YQIFkKTchwRFo2iiG7ROrZSkhZJzUoESkp2KcaR0fotzBVt9RS1spcO489fVY4ZGtUGBJqltu9xkbNsi3a3tqocsB8ADC5jRJxSA9kpAFDXCF4lCFZN2pSXnOUiJlKXBrj3dGY7q23GZq1IEY5yJQaY8/s/4hrAlSK6LlOKvutnW/lvd4sigQyVkEaXAonE3JHcgzJh/Bp2f5qycAvHCqlU4bzuPKNUwY4I5eu2IlFtX+fNHYSjvI0ibS4b4CgbACbtJH51j/HfOOskD2XnTmKTSKaKxHUVqTaSmOzOEFo1j6Lka7tx/8G3PzJPvMKNtwMAHmpSETt2072qU4t1zPfsCWx5kNxoN0hLu0+e43rDkBH0PHuV4Ii+aT3ue5i3ln4bCSLKV4X5d3G1eQeKRPLxD8QFGgsXEb/LLuJ7LzU2dAjj53flbcxz+O5d6nvYEs9MlAanmNl0eVUWn1p3IHPz5rNCfhi4PXjINSTm4o8rn8MO2h6yRq4O2kCeoAPmiYE7MZGilw7lOdelT1LE2PAKZsnqZOZsh1w7lBZ+XeSsi47kvGhoWxJ3LzL2Q2ddu97MhPDViAFATBDLAGktooWjGzlS37s8FgDQpD5HK5HdhEVVLc5nW4RddSVf9w/EFIgcdm3AfgDQ6CZiVZzZvsd1e2tjppu8R+T2RHTesSZFlKrXIGddRPXaznK9VcSgOL3cvUZcryfNDvQGlstscgfzaVGVOkabj57E19Sdj5+2njtGQy4mhkWHGhzlFqnMEWXI5RRxtvhkjrNOzhSsiW8wazErxypFomQXpOVnS9aIzGfbSHvecWYy3F2V2UxRZlbSvYpg7QjUHULPSh864rq9XEmK/sPvYDZT9WWct90Qe9JZ7nADsVVU197OumrvBYp7tbmMu3Dl9077cjIAoHVtvv5lm8V1GSu/9ldxDlr1Z9ZJp4dJADRV5K3RnC3fmg6i34Aqw1KwNbZyF6lFy+r8fAs+zeJqLffQ7CqkiTC6aMgMoo7r6H3dv110Qv7FtZeYmyjfHgMgaWm2zbWyRi5H3EqpHgBeA/kWvKu1zqisave7AuTL21xrvdJtH4tz/tOilPIbi7INSqnZSqliSqkGZt1apdQxpdQOs/yDUipGKaWVUneLY0xUSg0912v4JyBpex5yBjtoe8gadtD2kDVyddAGKOLO7n9ZwFCpJwHoCSJjDFJK1XXZrwiAEQCWZ9zmeoln9YXSI9G4udcHcAzAXVrrP8y6RiD3m/vMv214dgjAPYZR4sGDBw8XHnJx4AbQAsBWrfV2rXUKgM8A9HPZ7ykALwJIctkWgNxKlSwDCUdlhcMAfgHxwN/JYl8Hx47Rd5kvWtIfKErTsy+mcbtsKVHkariaXF827+LW5GrlubCyfwE50BQXn/lwxlpnuWQYpQUuFxH33LmcSpC0pt6jiQEw5+XZzroSG791llsPNykc1njCsacn8nV/Q59b1aijs67ZZUwh+2YyNfYcFW3qvBX4n3E1kaXbvsKhZ+nfVHDr+TDrgZ/aw9PPzbvovtavxqkoiYVfEQWv6/BuzrrZE9iBJyqUik+r4vidOz6HBakGvs2Rtn8uOdl9u5kLmUW2suDS5S+MBgD8sIGLpw0Pf+8sLz9Az/O6IM7r1q1GamhLkSjbvn7FRk7fSLqfvcMyPfLGDk4v3F+3XMD1DRTn/3oiOTN1bcQNWPKu/rqXimtlXuHnvz2R71uXuvRez5/KdM22KznFt18UJ215e9ZMfm+vfJ2/t28Y/QYmPsiF3v7lxNWYZqdZ03lWXmkGN9v8cIIonWUEzfSGj6c6y98aamaEGMDi/PyOXvUG/f9TIe429OYbneWXllPq78m32JnqzBZOtcxdTnTCDQlciH5y6GhneYZ5bvb9s+iOHOIsUiVKqWEglp3FFK31FPHvigCkIPweACKPCiilGgOI1lp/q5Qag2wgx1l4MxXoDIqws4PnAYw2n8vsuE7L+8yETMUDPeQR2EHbg4cLGmfR8q61nqK1bib+m5LxaC5ncGIspVQIgFcBjHbZLyhyEnFHGIuyGACrACzIfHeC1nqHUup3ULt7ZvtNATAFAHZdXFsDQNvUQIpV+ximBEWVYrqez9DR2nTmiUDCctY8KVmnLABgyQKOZgZdUpU/XzSQzta2Op8roojwnGxDf/kbf85RXJnGwn6zZmBxMqIkU7DSNi6jz9/ZNWA/AOjStCJdvyiYSTQ2jTMxLbiRJKwJ90e13E8RdcQTTIELn8oRX+QGimyWreWCq4xayhvZVt89XFPp/BsXiSIaU3Gy0Afcel6/ecWA6/T14mirfz1uI9+0nSleIYMpeOmzn6Nwn6AWHvg6cz9B6wkpYaVYARaJkr+nZnW4UGrpflGCGmmjbAB4cRMV/54JQt3sbp5Bodb1XbdfNbARAODMYZ49tonh4l2aobzWK8/Fz8LduXEq5S2efVi0E++lLTgCgP99kvO9RvxGKtQKdB5qEc2yseX7MHU14mOK+iMF3c/Xg6eNHTZRE1J8PJ8zNDRwnLo4kumche9ymq7xQBhJJPjuGMc7r+Dv12UruVs1OsJ0QP/4h5zl3p2pKH94c3ZaSM4Cucsq2QMgWvy7EoB94t9FQM2Mi41wXzkA3yilLsusQJnjHDeAKiCZ1yCCB654FqRtcuHzbjx48PDfQu7muFcAqKmUqmpqe9dAZCe01ie11qW01jFa6xgAvwHIdNAGciHHrbU+qZQaAWCWUmqy1jpLfW2t9V9KqU0gne/fs9q/Ql9qRf/8FRbYsaSkP/ZwDvu3PzmX1spEaa0O8fbZG3h70VCKnEqFcjTx3hJuXba9PqPY5B1vrueIdEh1zoFG/kI56J93Mh1v+2bOgQ77kz5XWuSt92/nfWtUpmzlN1fybKnf6Fec5Q9+jQUAJIkGJPa6BlYeoejt85mcn3x0EDubT99CgvljvvvSWTfrw2XO8j5jQHGJS9MRAPx2nFJVF8fzNb8p7lV1k4uU8p4//cAzGc6sA/og5TAnrt7rrKsUzq9h5aEjAACb9nNE2qEjSwFsOk35YCaNpYd1X684iO+lND2wcqyPCpEo2b5uG2sk3U/ms22k/chv3Fou5aCm/ETfr8rvnNa84n52MT+0ij63djfT/pJEg8uA52hWMvVeLgG1f51Vk/8Qsqh2Lvm+eK8f8Yno+NZxAIDlj7P4V98yPCu1Mr1TxO+m3T6mz640NYsCIud773GeCU1ZS/etrMiB7xWyuZbkuENIyeq7WKjtlJlB913N4mzrb+FZ4ScH6R51Lc7XXKMZG0HMvoeS6KsyNP3k2IE1F+mAWutUpdRwAN+D6IDva603KqWeBLBSa53dFHM65EpxUmu9Rim1DvTX5KNsfuwZAGuy3MtDvoEdtD14uKCRyw04Wuu5AOZmWPdYkH07ZueYedbl/VQ/U1GedX71L/wThDP7yJcy2TNr/BjD9M1LYzdlsifgnzeVz9tjaMD2yWVYOOiOQ9sCtucUO1tyZFNleZaTokzh/50jRl+LnpnseRbHFBK5qMt1DOsonpXzuo7j2YOVYj1XZOUoLx3pfY0Dc/DnivgrieVT+Mv5zjopXayKE0NFFXN3qbeORCo6sAaTG1hZvQEAoNm2zOsSuY4curz7J47J9qDoGz7+wpV19eAhN5Bbg7YHD+cVnlZJ7sD/Ns0qPhnH4v5W1lMa7G5O5PR6iVCa7nQvzxXz7SeYlbHKyK6OaMXR0ru/c0v5ziTK+1ppSiC9lOk9DTiKKf8x5SM/aM2GALFJ3HJ+ez1isMgo+3sh62qNeccK+dGnhGzriMKUVy3k4xfq+ZMsUWvlYGVBf/gXzznLb15FUqK39OZzTpjNrBBrtzWoIrMbGmxibvALJYltc38s54XvKc9t0sWNFGjvEix2tEKY2t4lZgT+6cSLnzJysrNOCk5Zw+MSwmauajQfd+HfxKmWZsoSqQ+SwYKMsqVZrv2ur8S5P1crEmVb1wHmZgPMGrG5bMBdInaokCJttX2Ds3yyF3HaZ63hekmtCGYotfiK1bEebE/57h5CBOq4YFZlV9b1VSEXfPcYbp8PfZByxPeKzxcX+WqbMJA87htvY+nie18hIpmUdU0VM3h7j+XsMFJIE9vPDRzHBLNvn+Tf+EqTu+4kxN06LmYjhTEN2DQiWtRJRp3mPPw5QV34nIlzukKlVLxY7qWU+lspVVkpNc60tdcQ20eZdc2UUkWUUtusZZlSKkwp9YdSqqXbeTzkL9hB20PWsIO2h6whB+1cgc+X/f/+JeToGyulOgN4A0A3rfUuw0P8A1SkfNrsdgWATQCgtY5TSj0E6t3vBrI++1VrnWl/vuoyAADQaMKsgG19mjBfuPh6ro5XjCQebs2bWQzp2GtcH+hVgrZv3XICNWpRlNVDdJXFGxH35dXqo7n5K99ecLvLtuYoQv9MOdzmQvC+jDBScCsjdB7MdlraRE5XV+TZAc5wN921ZYjhEBqkaNLTiG9tO8GMg5CmnEutYF7sAo05x95paayzfMp0u8XUZj6zxIBoygErwVi4Wsi6Fgrl66pUiZgpybGBprG+wWOgTxCbp+qDTNcpLeR0ixWj51JKsB8KX8ZRXo8ZVNPQR5mVokryO3B8OUX3kq18uYh+rYmvtBaTpgdWjlWKRMkuSMvPlqwRCRtpTz3IrBFpDRXZlj4/uG19bP+SXvvISPEzLEKznufXfI3futLsIbosv1dHjwV2REsDDDdcKbjbqdv5ukM2rwAA9BXfv1IJfsdPnaLfwGnRDamieYZq34Figue930XW9fI6LEK1TageXmQ7deuzpV7TaK6H6F3EejmV6kcXIxSmN/JQcUdN/l7rD+Vik14eSJXkRGTqElDbem+ttayOfQ3Ti6+UqgbgJKjVHQCgtf4CQJpS6n4AtwN4CP8i7KAdDM3F1MxD5rCDdjDYQdsDnEE7GOyg7QHOoB0MuTpoA7nN4z4vONczh4PMgPtrrTNasJ8CsFspVR/AIACfZ/wwgJEAXgDwtNba1WdItrxPmTHbbRcPHjx4yH3kF5f3gA8pdRrAjwC2aa3vEevHAYgHsAvUH9AdrGMyxnYDKaVGArgfwJfy80HhQgf0v3Y/AMB3T47p9pnCzU39nI8VzCXdpkXCCiK7kLofspXcOdeGn/hcxiXdzeX+bKD3sViTqlAjkz3TI3Eoe0YX6EhmSr6hD5/1+SXS/uKIVR/i6b+vmRHCEq4qbvfVpqcAQFWqHbD9bJAV3S8dXfCU8RIVaadzhX0e6Z6FSLFl+b3t50Kyn6v1f83tRr7+t2e6b+qTpDke+tjbmR/z5//xMdsNyPa1BEVO6YDvj8s+HfCmcf/K6H2uEXcagKsANFdKuf0CZwO4HsAurfUpuUEpVQGkO9sCQC+l1NmPIB7yJOyg7cHDBY08EHGfc3FSa31aKdUHwE9KqYNa6/fEtkSl1AMAtrh89FUAz2qt9yil7gUwSSnVXmcS+lsnd0klam9cyBeJppZmTSo4y4XaE13tt9e42NHqsWuc5bT1RNE6vDLWWbdFFE4a1qQiUfEFLJwUN4CjqQUrmDrY9woSDorbwOsiKgnXj1eoECajbP+b7GyORtTscubDqfyZtzkKsRSyE0c5mpJNMbtbEynn9GmmQ+45wfvWNe3bRcpwEStiIIsFpf1ORaqQdkyB8w1k6Znk24nmmCLkA1JOciHUZ3iIc//g4nCDYlxQq/uMUL08RHlu+dwqFOXIsOZnbwIAlva82VlXVRTnrIhRxV9EjvgiJiXZxhtJBzxyKf/B8Bs3l1Iv8P23zusAe0JapxqApVgBFomyresAUOlXvhb7rGwREhBRNoDbo4iaN2n6o866hSMmOMu2UFurKb/L4VVYXgGR4l6YSPZkby7eFp2zhPc1vpw/12Tq5glBJ+yzm7Kcx7uyq03BysLHcRFdt3RRb9KMC8H6Q5JQUOJ36Y/n967oPJr12UYcAGh0C1/rTEOz7NuZKb3hJzlzeuIVcvv5SrT033qQZ3172tBzl+JyABD1w2rkCP8iWyS7yBGrRGt9zNjyLFVKHcmw7bOM+yulugKoDOA9s89spdStAIYA+DDj/h7yGQ55xUkPeQB5gMedJ1re9c4/NABs6HCZs842iGxt2sxZt2I/U7D+Ms04j97A0dhsYZRw2gj7DOzJTSmblsQ6y9uMuP1Ve3nSIJt9rn6EPSN9w6hBaKHIgW8XwjrNTfTZaDOLQH0l8qqXm7zj12Jd35ksMvXpgJEAgKIiEui7m2vCNnotKRztL/5zXcD29s+zyNWzd3KjR0UjrFRTNIJcsoMbdKaVp+9tm54A4P1ynFetZFzEpXP9yvl839qJY9kc6+qOfP/2J/O9skJVHcVz8ZViOt/K6TQ7kE0tEv53xtFnjMASAMwU99W+71eI5/pOWf4u1n1dekImCtMDZUT7F/0S66zrI56FvVetyjJdstZattbyz6Io+a7BTzvrxvfi72rb1+U1NRezl63C8dx+B3tOIP0zsthYnyPuOp/zdwmp1xYA8J54lqWFsUhx813DREqg+Qz2jHy3J+W4hfYZiglq6CDTJPW7iLhPCC/U1maGXPgtlvid04y7a22k30vcn7Bm7DH73VPEe0jNMIb1P3YgZznuT57Lfo772oe8lncP+RuyMObBwwWLPBBxn/PArZTyg5ptLPqDTBVmAdgOoBCAgwBe1Fp/az7zOoDDWuunzL8fAVBBa52plvfuvpS33HyS26jt3/C/BIeznGjk6G0acxL+5EaNZpU4citUiL66lB+V+b8q4YG2mJXFuoUvcg66/TpqZZc5+EaFOUfa4IU7Ao7VvQM38FgRpqZC0N7XkluTaxYkEdeTohFCwoYHW4V1WPVrewVsh2gjH9Ga25x3G2fxysKNW6JaQfresvpfQ0Tn5YtTjvqD/zFrpVRYYJ5QVartCButjEtw1lctyPf1UpMDnTdlsbOujWgM2pFEDR6yqUXi4DSS/q0gIu5wETEWNLMW/9RnnXXNojhH+u2PlEOVzuvSWsyaHkgpVtyguA8AACAASURBVAnbvp6uqUbA5rNllD1GWOK9YHLkVzWtgDWbqHW7anV+b0//FfgORIcHYaicoXu1VfxuEi5jJkgLI/5USXy+STV+B+b8RXK2kYKv3PxHbmKrW4iee7jYHu/yju4RM6oenfi9/24RtX/0/40lBboNYK7CQmOaMVvY4F1+Ddepyprf+25x/FxBHmjAyUnEbY0UHCilYgD8pLXuY/7dCMDXSqlErfVCAI8CWKuU+gQ0ntwCoDE8/CdgB20PWcMO2h7+BeSB4uQ557iVUvFa68IZ1nUE8bX7iHU3AeirtR5g/j0IRBUEgE+11lnqd78RWUoDwM09OFcZftedAAA9m9kDqgfnwH1tyUjZ/wrLf6qeLPWpysUAADZcwpFt3Zs68fZuxCcNuVgY3S7lc+1/kCVei5lIOaJ3R2ddSNer+FjlOcqw0EeYgZL6HEnHhj7OeWcVxe28aevJEk1vXMHfTxgF+MePooVS/JllT7B4futHyVRBdWA+teSk2xRGmmgntvKoAHPGU79lA+TQG24S349EqDZ0H+Ssq3eXiPj38qwn9Dkyrk19ZCh/vpiYadxHEWnSsP78mQqigf00RY+hL/L3k7Ct7D5hWuF/j81oUZPy/XrJD86qkGt5RnT4RopIN8RyvaRJLWZaWGuxYjfwvfQN4ebftLVGZrgIR64h1Tk2WVOTIsrGf/PsxDJRAOCBJSxeNWkeGTD4WvK99H/HNXxfP8rDy/dS6iukfED7hlVkVsqy6fwO2TqGf+F0Pmabvs5y6gv30kIi59VVi9Z8rgqGny5TC4k8k/J1ovcu6TbmZku2lOX3h4/i32g65pV5lrFPMg+86hcslaAPstAadjFzx3fj4znLcX/5SvZz3Ffem6d43IDxnDT//S+T/VaDDamhtf4UQHEAUdkZtD3kH9hB20PWsIO2h2xADNq5AhWS/f/+JfwTEXdjANO11nXMvysB+AmUKrlYa+0qNCBt7yf3ad301mYUbU95idrfpXnA5xVrOctbDZukkJCavElwT+euJ0rasVTOUXaP5ujou13HAQD7U7j6/ayQUH3ESK/eUbess67iTI5YPmlK/OhtQmL2zkbMyS296Fe6jsrMwOi1i1kJb5Sm6Pzuw/z9pOyo/VpS1lXKwdYtRHm/q2ayRdRb/UY5y7fd3NZZnvQucdQPCrupbsX5kXaMpYhsjDj/+FN8Xru+ilBna1iYOdkbEyg3LJ+VfxXnMz/qQ7Om42f4WTQVxsAWjRuxhO7Un2OdZXmPLM6M5qg/7GWSCJWypQXEe2HvoZRFvUaIZzW7jhlJ86eSca408Z2xjRmwo4/Q4CGfVX8h/tTGsGASrmH+/PRFzEm2jJ5LPmLrrrt6cFOxva7tSSzidNMB/ryV/pUyxBJW2vXue7o560LHchekvQe1BTPpiPiNWObRkBFsIz3mOZaicBvCpHSulJatEUE1jTSuvqDPu8yrX3ArSRIvi+NIv7Ng1rSdTDPU8dc+4aw7LagtTyQfz1nE/dVr2Y+4L78nz0Xc2UVjADK5+RqAcQC+APB4sA9J2/uMg7aE26At4TZoS7gN2hJug3Yw2EE7GOygHQx20A6GkCxeETtoB4PboC3hNmhLuA3aEm6DtoTboH2ucBu0JeygHQzyD58b3AZtCbdBW8Jt0JZwG7Ql3AbtYLCDdjDIQdMN8g+XG+ygHQxZDSJug7aE26At4TZoS8hBO1eQByLu80oHNO3sY0FFSCilegIoA2AaiHWyTin1gdY6cx8vDx48ePinkM9ZJcFwiVJqDWhgPgRghNZ6oVKqIIAJAK4w7e0JRtp1IoBLMzug6jkQANBh2pKAbU3KcmRTK44j7r2mAaZwF27Q6eHnwszGrRRdVx3Cp27w6hxnuW6hwL/i/UryuYpXFtS5ghQRNBSRQekwntIWbxoTcKzWtUsFrGsQyRGrjmNWwSVGB1y6wkgMNBrQPuGQY4uvANChNF33mf3cTty+GEfXR01aqN017iJaQ6xOeBqnVC4tximNFBPxNKrHRcQimwNFH31NuzmFwmbCUb6AoA6mnKFzhIfzukI9uSX78iwkPP1mei3nHteW5eLnPhfqWHeho16nFj1X1ZWL1m1XMmW0cHciIkrndQnrViM1tCVs+3rzYuyAI+l+thB5TWmmI352mKUGnm8XONPpVzJzOd2OYialCgmX95NE9+spHHZk5rSVoQmGhnFkmfALzx76lgg8rx+Bv5uBNfhd37SPZSXqVTTf+zDPhOMEndBG2s07VHXW+bpe6yy3ixof9Jw5Qh5gleREqyTgqWmtFwMoGrg3oLVOAlA7w7qvAHx1rtfgIW8hHbvDg4cLFfm5AeefhF5KTRWxQtjIShQdPcGR7abTnFetaKIFHc8R2gyR47bNA79O4ChbItGlwWKLaMSoJ9anLaPoSzYIFQnlv9rJ+0mkSN7sU6c48iu2n/K1soFHFeGmExtInwrSgPO3aYOWn6+XzPfqL+O1WfdBjuL2dr2Br9/8/6fPuDW70/N8/AWHKUq6WMh/Joq8Ym0zI9ixlWsEOxL5uVgynO/mxwBNZ9v8ONP5pFdmc9PgEifuT9ISnil9tYVyy3fDHWE1AiPS1cL/smwBegr+lfOcdafFs96zh96Xau+976zbv4ffoZS3vgcA/JHA95e9jNgTUjrVRIvtViRKtq7LppqWhu4ni5Ayyn7wZ87N29LiEdFGrhNYEEtF0kwjQTSW6TOiDmQadPYm87rOVZj6uH4fRfoFUvgB1R3DtYm9g0koK1wUX9xi1d928zV1vohnZfHxdF7fQD5mt0/59zhnzT4AQJU/DznrKtzPNFWLVaKICQDtA/Y4S/xHUyUePLhDu3cbevBwQeFfdLbJLrKkAyqlNICPtdbXm3+HAtgPYLnWuo9SqixI7S8alFqM1Vr3Ml2UfwKQAhWTAdhuh7pmmx/APK31g0EvwsVIYXNDysfWXpdDCccskDCYRW8ip7vnNV0F7V0wK5ozRf12822xFLHIzzgK9M94w1n2XREYX+5ty6yHdBKnuYS1tVnMR4pjnQvSNXh0HpzJnmdxTGOkAQAh1490llUJol46jTAAQhoFllD8n7OUqu/qkQHbzwbxVzLFzopESZyrAUVWsAYN0mXeP4FZF/oY1RlCn3wP/wZsk1XoM1Nz7ZjZMgPJqZHCvPeyTwfscfMFKzKVAKC+UipCa50IoCuAvWL7kwAWaK1fAxwmicW2jG3xAN42+8UC6KS1PgIP/wnk1qDtwcN5xVk4Av1byG6q5DsAvQHMAPlIfgrAqu6XB+CEGVrr9QGfziH8r1JL7OvPcB1zlOHOSnnUPxI4L1jGMBWurM+NMvP/cjyLsd80nVxTm3NuM7bw9r3G7ftFwV2WjRyj6rPzd8X3SOpySmNuTtiZxHnHm2rQOWSUvbAKGwl03klsyJdKMt/1vqPMDXbj6cpGi+dKUtW9hJDUvGU2y3e+2JNyiGOGsjTT6x9ylL43ma71MsGakTzuh4tSjvXZ/awpdm9ZNgqoaBpwGgse998ix33bQdGAY3LL7/ce7qyTQv31TO1BNme0FGax0xbQPZRNPRK2Vb7glK+ddZKnbO+QbA6R2/ube9DmMq5izJrJcsDtqlMO+H0h7v/IMW5Tt8eSzuvthaytNT2YtXqfs06KRLWfxgXcUb2o5VyyRmQ+20ba6azRRPRt8UwJZmU8cBubZdhOVvl+VY/gIeGQaYyKEQ1WN97D7/jIZ6mvorBgM8X7+blNNO+o5HFXFzxuK9Q18D02sph7KxdXlpiaVk/B+un4PhtQPNO0n7Ms36EnkgP7Mc4KeSBVkt0r/AzANYbSdzEAOTefBOA9pdQipdQjxprMorpoi5+US9fsIY9CFgQ9ZA47aHvIGim57SmQB6zLspPjjtdaF1ZKrQQN0jVBEbbT2q6UKgGgB4CeALoBqA8gEsC3Wuv6QY4bC6BZsFSJbHl/66mHmw675vJ0+UG3vPC5wL+ITeitKI5E6v3MGw0qbGSO4fb5dMd6ksX5pYGqtR6LXib+Hvo5soIvcGKUtpmZFiG1mwdudzELPhv4J7Jwkm/4c9m6pqDHymGOO+3vlc5ySE3i5WdlMKtP8exJCnZZnL6ehZsKfTQ3YLs+zgwkVZxb7uE3DAxh9ptl3jULA18J/5IvnWVfhysDtkvWSNo7z9B+I1nwTEbfk14hE2nfbYKGmcQiULb/4HzBPjf7zHLlmJu4+zikbhAP05zmuH/8JPs57kuvvWBz3BbfABgPoCOAknKD1voYgOkApiulvgUxclZlPMDZQGs9BcAUANBbV134Nj0esoSX484+3AZtD/8Q8hkd8H0AJ7XWfxgxKQCAUupSAL8Z8+AiAKoDcFe68eDBg4cLHfmpAUdrvQckEJURTQFMVEqlgnLm72qtVxg6YK4g7RMqtFmtZgAo2NI1A3P2OHUi083B0iPpEOXuHJMRqkgR1/UVrnZpGcgiFRFSuU6m27WcEmcTaVsFtdKl2Ucf44KaKh1YMNXxXBRShcU9iaApuf/XWfC16ZfxY1kiJFp8V8MF97W5LMjeBqmBgmMS4aNGZbo97cvJzrJvGKvQ+d836QnhsKOKl8n8WmR6xDivI1SILZ3hQq7V0I4IEnHbphqA6X4SNj0CAHfdSzrqb4lUiRZpG3WeUyX6gInfcpoqEVILabM47RY0VZJT5IeW90xa2xeb5ZcAvOSyTywo1x3suDHZvkoP+QLnMmh78PCPIw+kSvKEy/vhlvU0ALy1joV5xhoKlnSolhrc0cYfsnxJFkM6KNqQ96dQRFa/JEcdX+/hiLGAeXijhGTn5DIsu1pN0Jq6fEDqtB9dy1Ql6dPX/0pq+g6bwIVQ64QCsBvKF0KiVrrLW5rgCT93Hj5zIpaXDd2rakH+O3zVsI7O8geTFwEABnfie7Xud3bg+dNIBbQSFLZ6G9Y4y6+VpvMP/5x9Gt+8mqU4ixsRIqmuKdvYB+9jkSb/t+To/eEtTPsqKJ5bj7oUvX6zkel2PWtxcfGLTdT+HEzWNXUM5dFDx3Nk9njxGGe5mJEFkM/17bL8XC01T4qATVzFbQvXxBAdcPkBFn66Tnw/S327UlxzpV+56PxzVaIZFo/k90d6QvYeQg4zb7y91FknRaJk+3o7QzOUdD9JTbSQBcsXOjI1r+icJemuGQCqCT3uZafovZDv1XWd+R2d+D3pyMvnJyVWHzpK1yLv/6Bobqn/0vzeHn6e29h3vcuF4m92kNBaIfFbuvnnz5zlyW2JDFDElz61MeTkoZwVJ3/5KvvFybaX51s9bg8eAPCg7cHDhQylVLb/y+bxeiilNiultiqlAjrElVL3KqU2KaXWK6UWKqUCBXcyfia3HHCUUkNB9L7hSqlxAG4FcBhAAQBPGcsyKKWmAugA4CSAgiDfySeQCdZVjtEAECbkJev8Sp6BcYMGOusK1efIQnUmuqD+iVufVQ3RbhxJ4vSbxr7jrIqO5simcCeKkkMf5Nbz1Aeuc5aXfcER6cV1iGRToDznHwvU5igo5CZqIFKl+PqsjyTAeTvVsKmzTnompj4xDADg38/MyfC3uBnJevol7+TtUqTJOtoXvUnQ5uoIj+alJJyEEkLY6voHnGX/y8Qp9u/kKD2kqJAKLUqCkLMmcLTUpRE3KEVewS3hIf3Jq3LrpSybWq4K37ciM+haNjZkiuNFQzs6y4krqFkpciI/N5lv/6MuNeo22MRNMykj2P8zzcj9hghneV8NflafPEf3VbrUR4vGomoXEzUw9QTXEIrOY+pl6vMkT5C6nRthwh97wVme05rSRb3mcRv6SuG8nmyaUlrfxBTOdFKsQiTKvpupD3HEGvr4ZLEvRcynrrncWffAYp5p2GadMyOZxhrSls02jk+m6PbYMc7BV7taeE6aZiBZu0nbyd877FX6vPTULDyCvUp3PUatHZXF+VU7pmkmP0ayBssX8yyig5Ay8E8mt6Ck1Tw7BYDCc5bnKApOWzYr24NiSOt+mZ5LKeUDsAXUcb4HwAoAg6QHgVKqE0hC5LRS6g4AHbXWmXKLz2fE/appd+8H4G2llJRIvs9sawTgBqVUVdcjeMhXsIO2Bw8XNHLXAacFgK1a6+1a6xRQM2O6Yo/WepHW2ubLfgNQKctLPI8Rd7zWerzZdgDkL3nIRNzfaq1nKKWKgcyEW2mtDwWcxMKKTAl1OX2A/gq7OagHg//XWc5ydgtl2flM2p+/AQBC6rRy3a4PU3Vdn+SIWLqsu34mgV3GVWSgxLn/f2/ydQ0wspii+i71FmzThmQkpIOVgA3nekC6phnb4BIe6AeZ29CHYmlBXL+cqdhmlqQ7OCAp+C4/I+ceSL0Jl8Yh/0xu5PX1Hya2m/jCfyZwnbxO0QiDY1x7UYYBk65BqqZ41uegg2ENDwCkY6Ckuy/nADeRqixxvht4TnPtQJtnKRlK/qlcZ/ENpVZ5fTB9Xl9VbZSziHvF3OxH3M17ZRVxXwGgh9bauoBdD6Cl1np4kP0nAjigtX46s+PmRNY1Qim1Vvy7BKhJJ+OFNAHwd4aB+SWl1KMAagB4PdNB24MHDx7+SZwFq0R2eBtMMc2Dzi4uH3P9w6CUug5AM1AqOVPkZOBOlMp/NuIW20cppW4FUA3UDi9xn4m4CwNYqJRqo7VO56Qrb8ibvVri1iY1MekVzqHec5hydVPLc956y2mOkkqbHKW0TfpdCLrvT6G8ba8q/Nf8s+1sF3bcOFxLg1zp4H3HRczdrfw2MSTeKcvXsi2Jr+W+ZjTzKbmQTWfnV2Fucred5KVs2Rvy+wHuxrzyul4wIlOy+n7ndObuvj6IDBTuvoXzl5Pf49t9wNiFSSuqVsLg1rrIP3WQrUFHlGSX+mgjQtSwMJverolnBs8DRzki8i8nofzXe7NUrdSa6FiUorgEYW7Q9CLOvU81DA95fyQSb6JZUcTUb5119xfnWZk91wQhMiXvby9j49X+Kq4BzJrOLfctomnWMuVPZr08JRg+VoisrxCG6hTL9+14V7Jh++oPbqmvJESmurzPZhej+1MdS1qLSdMD6/IuRaLcXN4la2T4dVw7cBOpqleIc//2vSglxMtGPMizzlHjZgIACghWSap4lvYevyzOXyU8cMgZ8OZoZ3n+3dyrscSwbToU5Rx/t8+5XvCEYKtIY4/nz2Tem5ElzqIBR3Z4B8EepPfSqARgX8adlFJdADwCoIPWOjnj9ow43znu2gCuBjDNCFSlg9Y6HsQHb+eyjV3em9Q8j5fp4Z+CHbQ9ZA07aHvIGom57vKeqyJTKwDUVEpVVUoVAHANMmQmlFKNQXLXl2U3+3DeHXC01l8ppW4AcAOMFreFMWVoCeANt886+7WiCnvzIosDtpUJ469QIJJvpI2Y4xM4QmlSgXPFs2Mpuo4ZxBXvWq9wlLbpNLEPnigeg8ePxwIALirEkVFZIQfrM0L91g4NAI6kBnYeSri9a1ISU6KoiXiK+dz/ztYtRJFuqHiRVFn+I9/IsCL2LWZZWcmzLmPYOnXrBhoYA0DLIvR5nSwtwDhXa/nlS04m4t6mFQEAiVsCtcN8LXs7rIuGgqlxQtyrQ2coH92yOs+EQgpxJN+hRGD3qY7jDsKw6MAuxpZRfK4tiYFmwaUFW6mpMTxW/ZmJUmkGG0mU70PMn3b7FgUcBwCKm5lepRLu9YCClYnHPLhyCSyYT2yIJtX4u/ra9AUATDjUF5Or0IRWlqGktZiFlGJ1g+RmS9aIhYyyN57m+9PJGEIXFzZ8+hCPKzUjAnP/bkp9LYvwvfjlFL9Dzc16vZZljfal8O+1sZnBVRXG1L7W3DGbhhEAyDqtdZFcrL/kYsu71jpVKTUcwPcgZ7f3tdYblVJPAliptf4G1MBYGMCXhmK4S2udaWvwP2Vd9iRIgMpyuGyOuwCAhbiADYPtoO0ha9hBOxjsoO0BzqAdDHbQ9pA1cnXQBnK95V1rPRfA3AzrHhPLXc72mLnm8q61ngpgqlkel2HbKrDD+9BzPacHDx48nHfkgZb3PGEWnPAyNRXMOcZu21ZeZqcoAiaJ/EPdSJpmJSfxNHz3KS6YlTNu3ysnsUfgX4l8LFlwsbCuOQCw5mcuArX6iqh5O5K5plBQPPyIioE0PDn9tHS8Wi5TT4mdyamu67ea6b+85G7f8yRmfQJ979b1uVYQsy8u4PObNnF6QxIbN5vtvXZsgBtqm+uesYELbqdd0j6hD77heEEuf4nTUqli1zsbkw/HL1u4UNwkhQuVC47Qdct4VBXh9EHiRnouMqGyIo6fu88+l0R+l0JE4X/eWqL2dXqYW/J/EM02ER9TgXmlOCZ7wnDR6NQpd5GrdYuoqCqf/5y/OP1w3QtUND+Syt+5lSheWud1ALAlVetUEwzLxHvfdjK3jJe6klINtggJcHoEABadoPeyoigoXhrOaatjJsUli+JHXVKEi0RLf+diXGj96STd1w4V2HtFyi58Zlrij5xhamxNUSeJMqlD6XwFBDIhzhr5SR3Qg4ecQhr4evBwwSK/RNxKKT+AP8Sqz0AJ9d8BjNJaLzX7zQfwjtb6S+NwEwcgDcBBAEO01gfEevuneanWekRm5w8pSBGH9LZztolVUuzGZ6KoFCHMVDKUv26iWX9SyJfKKLlkWOBf3WKCFnVSNnXsIWqeLDjK4l2ooDM560SUYp1CigTJrVU0x5K0LAlbvEwWF6CPBBYH/aLwFCXOVcFEVCWiwgM+AwBVzf3Xx5gCFyUKpWHmtqWK+5ekA6PAkEaXwj+L6tNxIqIsKr5XgaIU8UmRrhMnOaKKKXj2sYYsop0y503bzgVHeUxLQ0wVM4Yyov09MpKOVSDIj9vue9pFFhfg4p38vPyuSDRRrnx/xLtYICXwvDEuFDsJKRIl29dtKVq+V3ImYCPtvXKmJ98bM2uVPxW332iZMPmu8HbnN3KC6Xvly/FvpcxBml3Ie6VKcXRuf4+5Pszmo4g7HWfbQil1J4B3TZPNFQC01vpLsUsnrfURpdSzAB4GMEKuz8mFe8h7sIO2Bw8XNPKAWXCOUiVa6+VKqV8BjAMwGCSk4oal4EH7rFGwGTV73Fe9bMC2a9tzc0XEwJ68YbdpUCnPf6FVa768xjOnmoUWzrp209g0oUD1QIbE7U+zyFTigmXOsu+eF+la5M5CeMd301hkROPZzNm3rfJdbnb3hhxyq6EsFnT3K7z6UspdF2zOzuSStnXXSMr67fzf7866VqLRAxupAdZ3M7ttS/Qba9rLw5g2dodo5knZQ3+DfaK67xN0P32ExKlC2vZGymP3AACeuIVF8FUxpmmqGGomahnGaZWIS7hlvE4W09hCjz4QsG7o6D7Octo+ysOH1OPrH3A3Z6lVYVNzb86tBTd8PNVZ9vWge3nvcc7BS9x4GzW9qWimY/q/fstZbtKM3quIh+5z1jX/URAOqlIT15CifE8SfuHaQt0xdwae857uAeskpBRreAMhEWHa12VTjXxvnHy2iLKHv8QerxPH9qeFeK4XIDRwSLn5jkudZVWM6z21f6SZpn8396MUvY7Fx+7sTTRPfZzllkOqc2PU9UYuWYqE5QbUOcgS/NPI7sCdsb39Oa21FZd+CMBuABO01luDfL4P0qdaFpn0CwB8qLV+NdtX7CHPwg7aHjxc0MgDOe5siUxlFJTKsK0/gDcBrNBa9xPrY8G57PUARmitT2Tl7i4+77S8Tx5wSdNbW9TFlKdnONvvOERC+jOE+cC6BM7hljJ5tcH12aH7u7/Y+Xt/CuXthtTjKH76Jo42bF7vFdEaLVve72nAxy0/5RUAwBsdr3fWHRGV/puMqH7V31l4aG5lbhnvtYsE6Z8ryZHDQ6JN3LZRh4gXSra8WyH9UiKXeMvsic7yhF530TUPZa7Iqx/85iwfNqyCy0SbthXpB4AHi9L3fn4//+0dWZbNjcqbXGXbKM5PrktgJsNdh9j0wLqzT72CI84UkZuvGUFRnvzpNG/E9/rDX+l7BzNSODN6EAAg7OVPnXWypd3eoRfF/bP3FwCuLk1yv00HsXrDNx/y7KqDMViYspajRPmsbPu5PQ4AtBVsnLgBnQEA03+NddbJxq02059zlkd3Ix0iKUWwVzSoDNlPBg7DRcv7RJeW9xfEezV6JEfnoWPfSnfNQPp6gGWN2Fw2ANw4ime1w5/6GgBQWNQ73Fregxk12DJCvw8fd9Z9fyNLNSw2rJY+4r1s+y4beDx7JS2nZRjDHk8+nqOR92zMyVWNpnnPSEEpFQngRQCXAiitlOqVYZdOWutGWushWuuzEhBI1/Leom5OLtPDBQI7aHvIGnbQ9vAvIHdb3s8LckoHfAzAF1rrv0yh8nOl1I9a66SsPng20AmUi4twqVifEqyREqI6fsr8OU9M5Ip4adEev9dE3DKKlW3gBV143JEu5wcAVZHyhpLPWkzc2VKVAmVZU1x63gsGeREspzzc5ZokyorvB8EAsQyZVNFuHCW+bJKm7WFBzu9wnwtxFCkr/Xa5gPj+bqwLX7sBjguO/C4nBMMkwhxDPov4Y3zdhYI8A4uQ6EAp4wLiI2Eu91A+6yKGNaLKcOt8hPhe8fEU8ZYNc8+D2mMVi3Tn5CtfoM1buCyGGUbDywvexH1dA/PZbu+AG5PD7ZoAd8Nqt54FgN/ndAQrkc+2kXZ8kN+gG5SYS1k2Eg6xLG4BweiQzCzn8yV59iWj+6zOe1bIR8XJjDnueQCmARgAoCEAaK3XKqW+B/AAgEwdbZA+x71eaz0k07095At41mXZh9ug7cEduTpoA3kix52tgVtrHazMWivDfiPEckyQY7muzwwqjKKX4y4dYkUF73S34Js6HNMCMgpnbm2o+cs/bcNBXGNy0LKDznbz3R9VxcmHxglur18sayPbKQOXw6Ib7dAuyhLJWCcqNPCWBguobRdiUhAVNBtRye+PYiwYdTAlkFMsj3XcXOvp3UW5hwAAIABJREFUNPcOPBv9Pl48BuN2rnTdBwB+OZmAiyMpX5vmIjns63ML/GsWAgAS/O7nsp9LFh+PKiussVzEqySSV1FuXjLnU8Sx4l3eISnudSCOeM41tnLeOk6+N+Zm7HW5pwBHge/tPIpeJjddT2z3G7nbwU0qYO76A+b84liJNLt86ZuXcN9lVAfwi3vp9kMMJk5mIQ18pbWYPZaMXKVIlO2CTBfRC9aI/ZwcOI+lBt5fKX52Rhzffn7GmLdxxSTqGE0S76CtM+1NjnPupT7JbB47q4v3a1dxq3NGPmKV5FtcI9y43SCLWP91ZDZoA3AG7WCwg/Z/Ab1KuNbyHdhBOxjsoP1fgB20gyGre5mrgzaA89DSk+v4zw/cHjx48JAOeSBVctaek0qpGJBnZH2xbhyAeAD1QU041bTWyUqpUiDN2ZjMPme9KYPCek4KxF9NtKbCn39/Vtd/tkjbutpZzsonMivsb890vPJLmY5n/SWlt6R0gQ+5mDXDLU716egsR327OEfX5Qbp/B024fNM9swa/re42cd3+1M5OpZzzN9YpEoV41lTyEUtafv30/ic3c9vCWVl9QbOcrNtfwRsT33yNmc59LHc6x5NfWQoHfOZqc46K58AAPoA0fF8l7DL+z+Jc/K0zA0UKpozOuCeP7NPB6xUJ+/RAYPAD8Cz8/YQgNwatD14OL9QZ/Hfv4PzkSqZAPKbfCfLPbOJnS2pLX3qFm6QsQYHb5cVLe+CxlM5nNqzK5fmMtXOwyzPaYtzkiq1XjSNWKrTzQe4GXRyGT5XfZHPbTN1HADg/asectaVF00LPW5oTetElL2m5sXOcuNN1JjzXWX2oey5609n2XpZHhOSmdLH0Xrv1RFOJpcP4ej+ww/IX1K2fq9+i/PNsUlUkIsO589Lz8mXSlIDxejfZzrr3m59hbNcxYhQHUjh4qi8r4P3/e0sp61bTN+p283OOinremMPakyas5A/00gUJ7+IpTboR46ld/Z2jmWiWxnZPmI8MwGgmhFcunkHk6SmizZqK/QlHXg+3cjUSpvH35HEzV43ubwjl9dhOmHZJdzAY6NzWcLbk8zH6tWbehYmz2QRLOmb+pvwTb1qL5kxyAaXUUeEF2dNaiJ6XHgz3tuam22KzqVZnfSElG41Vo5VikTJ9vU3JgbWLGQh0s3T8rEmLCUx728qNN/wLtu0Jbz1sbP8+QqSSpCF7ls+Y5f3jwZTA05ihuLsHfE5lEHKgnZ7IeB8RNy7APwM4HqXbdWVUmvtfwBuD3YQpdQwpdRKpdTK6cdyaP7p4YKAHbQ9eLiwkT8j7mD5H7n+WZAhZkZ32G0ZnOHHBT2JcE+2Oacbe/UP2K9lMa44b41PdJb3pFAU07g0O4RHRDDNZ+FWohUNeuEWPufYD/lCXbwJKwj5zNbXNHWWfW2p079TJXag/m4XC+PEr6DoUdophBcUlKMwavOOFVGcNVcAuPGoYbg7a2NAOcqNHxVGEL7RHJk0+ILalOMXsrff5kRhLmD+3+yKhq7H71GWGm+kwE+kaHP+08jF3j2Y28SXzgo0XQhp2BGpz1L7fcNIjuzk6z//R4pee3Xg2U2BMtz4M7zcfmSE3ickclICn1v/khyxr08w9zWC3xsZJXbpRgzXgk+zfM7Qm290lgvfdQOd866XA84D8H3ZtpuNKqQ0WqNbSITqRzHj6dGJv2vBt6m7tMZclkTYJEwvOl8UyIKqHlEgYJ3EoGg2mig8IjCLKZ3XpSekNT2QjVlSJMq2r8ummjMuNTMZZT+5eq+z/HCD8gAAvZgFxT75nfPh9nu1alTeWefrxLWXUPUoAKBepLsc8TkjDxQnz2XgPgqgeIZ1JQA4c1et9VYTUV8FDx4M7KDtwcMFjfw4cGut45VS+5VSnbXWC5VSJUBuQa8B6CR2fQaBEfc5YVN7knpceohtm+4w/19+gltwrUARANSqQFHWmk1M2K8bw5FbrQiKXre/+oWzbnkcR7lu4vSyHffH6SwY1bkp5VP3HePP1xb55iKDMkq4ABWjA1uP60kedDhHpOHmRZJ5VYkNwhrKIu5mZlIcMMJE5U8KB++qHIVt30f38Mxhvr/y2x804l11X2fJVNl6XdNERu99xhF9UZduttCHJzkMk42nOeIvJpqR+lxGpKOZX6931jURdlabj1OdgoVIAVWhhrOcvHV/wPWnm13Yy07iekcJ0VSy9AeaHbXcc4Oz7qXle5zlB8JI+veUi0UXwLn9i6oFyhwAwMyJZJXXqwXnfb9bxIJZvYZSHaJL5xqYb/L89SrysWzLPQDYuWRSkMYpiy/38OzvuscmOctVewwN2Le5yHFbazHZem6lWAEWiQoT41yqS8Rtc9kAR9kA8Owf9Kxea8QyBde24hz8d6soOn/751hn3X1n+FnacyVm8f3PHhf+wH2uOe4hAB41UfWPAJ7QWqeTa9NabwSw2u3DHv6bkLRAD5ljvijOeviHkQdEps6ax/1vwP/KCLrI4pyv9l09EgCQdAvHXmGXixy4iaJOvcTsguLzmRvtf5fkI9Wl/Pm0jyc7y6oUVfJ9d3Gu2L9wurOsF//Ap3qSNDj8P3/N59/H8pr2WtN9J2F66mtJMwr/y9xB5hv9Cu/7zjhaKCiMCq7n6NcR6j/GsrXHPvrOWS5x5zUAgNUPMtGnyZd8fMRR8dfX4cqA6wQAvZsYLmlzP3Xfvo3+ZqsWwmLYGlkAQD3Onf80jEx4293GkzNVgqN/NDUGCzs5Doibwuct+sFU+oyIsv0vss53yGDS+FCVavN2qUq4mpg9vhFcj/D/yAa61iwipAmzJ9LeYqlR3x3j6DOrOUftazeAj2WfVX3B+Rct7clT6F2JeIlld9N+Y8NqFcPXbXnYOMxdlr6BQsPE5On986bydpco2j+FZVNRWBh8DB5D24UzkV7LsyZlTXyFtZg0PfD1M783IRKFCDYD9vUn7oHUqJH5bNv+f89HPHud9D/+vdn3Pe0rNtWSPQVJt/F9L3DXKGc5pFXfnPG4D8Vmn8ddJuZfGb29zkkP/xjsoO0haziDtocsIQftXEF+zHF78ODBQ/7GhT9wn0vLuwbwsdb6evPvUAD7ASzXWvcx63oCeApAJOgufKu1HmO2DQNgcwKnANyrtf4505OalveTPdiTsei8n+gAl/GUe/0f3KBjC3IDRrGH3c7P+TRbDlJBrusXLznr/rz5UWd52ykqNPbbvdlZtyiGDR3aP8k0dd8Qarw52KG1s27OZk5bdKhEFKrqK7mws6NFc2fZOuNMr1DTWTdoPU8pP7uYpu1lwljjufPOTfy9TINScjJPyWuJKe+2ZkTTq9KDW7M/fu8nZ9k2LvXvx9vD3+Rmm1U1qFmo6VYuGH4tUhEWfcW93jptsbNcex2XOuy0/OirU3mdUK9b8DcVk6+6jB12wq7gZp+E1yjdk67NP5EL1KnPUdok9Mn3nHUrREv6PkMXlM/1U3HfrzQpHN+oZ5x1yfcN42sZPBgAsP4W7gJt/Dffl1nRdF+aRjNtrtKvy/m7zqHr+u52fu+6DeBmrAKvU7F8nmjGkuqE3QQ1ruicJQCA2dFMHey7+y9khHzXqsxgymtIKSoKfmdkAgBgn3DYaWWKwtJ5XXpCfv8YyQrIor0slPYx1yLlGSTdzxYiI4czRfGuAex7elVpOn/7m1nyIXQMq2P8cBG990V86Ut1LQ/sztnIe2R39gfFUtF5JlWSAKC+UipCa50I0iZxyJlKqfoAJgLobQwWQmEsyJRSfQDcBqCdcX9vAuBrpVQLrXXmcmke8jw8l3cPeQL5OFXyHYDeAGYAGATgUwA2HL4fwDNa678AQGudCvKkBMhk4T7rN6m1Xq2U+hDAXQCCUg5s0W7KCibvW9HLZet4vP/tFNPxGhhSfvwPHOUu2HXMWbZNBdtu58LNksPc6HDIaFRL2tn3x5lCVuttLkSWK0A0vm+Ep2Ws0MZulxr4B1zSuizkbqoU08U2nKZ9/ZrpfJ3F5+abNvBDQgP8wVVc8Jq2jehYY1P5mqQstW02qvQdR6HsgQ7MP073pclBbjNfk5DsLFc3Le8LXuOC6N+igcnG5r5+tyFtB0Wnn2zg4mCUoA5ebBpzlszjyLF9KhekPl1BERvLNiFdM03cMvoOstHgf0eY5mjv8WXHuKC26TQ/i+/epQJ2x3WDnHVzl3O+ucvWCXT9B08667gtCVhp9Lz1Li7oSU+eE6+8DyC9FOnCr1mYqlsXmlEsE9RU2wgDAHPWcHFwsPn/kpO8b18E4psdTIkd9tj9znLBiR+ZzzOdtHFhptR+ZmiEZQ7y/bPO6wB7Qkq64F7x3luBBdu6DqRvFrJ0vytE0d1G2QDwhfk96neZVNCxzgfOsqXH7khK/1tqiZziwh+4z5UO+BmAa5RSBQFcDGC52FYfwCrXT5GmfMZtK5Feax5A+pb3d1YGTv885D3YQduDhwsaISHZ/+9fwjlF3Frr9UamdRCAuTm8BgWXNnrZ8v5dqQp6/i87XL31torIrotof69fhyhmv23kKPjaS1hM58AOiiYOHmNCf4RoKmkfJT1UCD2K8/GX7ODI4+pjFNHKBqCWJThKqv783QHHio7mY1kpzjYV3Js2upqI66iImCXKGUGriqJp6O8bWbinbRRFNMm7OfIa1JHbrGM3kIhSlVpMt5S4tCidP+3jN5x18v5YQa7FJ3lGUlO2YSdS5BRSrir8cykvWlJ4NkpBqiaPUkvznMdYbGjdIhZOqlDA3cvROVblEgHrWkdxROe0bydzlDmwLN/3LUY2Yf92blrZkMDvWKMjtL1r8cD3AwA6FaP1LVpGu27/ytzr6/txDn/2HK5XxD5J6SQZZTfvUNVZrvIn13EsehaPDFgHAEijGZj0Ql2+mGdNHQvTvKRDUf4uVYvxvTpyhmYV0j9UH+f7It3XLRpGBs4upUiUbF+3jTWS7ifz2TbS/vKIaPnvw/nw8qOomeiiQrnc8p6PI26AtEjGg9IkEhsBNA3cHQCwyWVbE7PeQz6HHbQ9eLigkR8bcJRS8VrrwkqpSgAGaq1fU0p1BDBGa91HKXUxgK8A9NJab1FKhQAYqbV+RSl1GSiX3UNrfVQp1Qj0B6Cl1jpQPcji+H4NAP5F3J7u2miw4BO+zmhq0AgRFfOTvfivedQUyiX6JzF7wPfIa3ywOIqo01Yt4nUF+C+7rxuzShzRfukdWIYjC/0d5cN9dzBrJU3ItmIHyXP6enGbun8FG0SoCjRT0Cc42vI168H7/k65ZVVcGArUZMEn/0yKTHwDWSvEP/8jPn8oRbHx4990VhXuJBpIDJvFN5KZEDLtEVKVWBFpa5kJo0ry91fRzJBwPv8XZ9f0Ec7bhlxkrjuN76UqE8PXPdFI59ZgVot8F9I2/kLHqcdZev/HL/KxWnWhc/4qDDhimFWCUyY3/ddGvqaho/lY4+n8qlkLPv8VPKNKiyVxLb2Rv5+vN0vYOseRTTE1+P6oGF7WW9bQ57te66w7cz+/I77hdC1aSPCq8jF8LbOoYSzkiqG8vTTPBNK+Nsyb2hz9+1pfxtdomsRUqQrOOik0ZhvSpPO69IS0DV3+RVyjkCJRsO3rYULqQTCE/HMon+0TUfbtJZlB89Ypmj34P3wOEr7h43M2op48mP1BsWjZPMMqAQBorfeA9Ekyrl+vlBoJ4FOlVCFQGmSO2faNUqoigF8NrTAOwHWZDtoePPwHYQdtD/8GLvxUSZ5oeU995FoNALMmc5vxwD3EHnitNOetpTynzVdXK8hRcslCnB+dbwSrbhO53slC7Me6tEuzYClY36cy8xZqzKeI+qtGXZx1u0Sl+/a+VHuN+GC2s+77KhxZdd9J0fcTQvDeGkUAwFhjBFBA5ILHCiMBK94vhZ9uGMvCjDOfnQEA6FCDc9jfC7f0k8aZ++p6LP5fZjGL/39seM7XruA2/YfqdnWWfea+S/nUtUJi99aDLLua+hBFjNbcAUgvTFSnEEVfkT7Ogct39PAZyvNLowkJq0AY+jCLKU0SBhgHjDv7UydinXXWKAIALjfiWzE3dXfWffUM52B7d6Z7MVtoiVxtDA0A4N4ixE2+oybPfmqu5nr8njY0A1y7m1kpZUXevsnHPAMc34c46e2i3HPYbXdQpP1MCc6BuxlMyO9/26ieznLoQ9R2L987KdcUZWoXxQTr5/orOeJ+4ROqzcjnJ/Ph9lqmlmd5AvkbtZ+75jLm2f88j5lNljUiTUn6xPLs4vYo/t6dRW7+yuMHczbyxh3J/qBYpFTeirg9eDhb2EHbQ9awg7aHrCEH7dzBhR9x542B21TFdyUFcp8le2FVPHOL6xiR99Y9OBc67X/rAz735xrmgRcSrJXyShgdGJwWHX7hgrua9hNF0smia0zydFMM51e+XjVKiyjK5PUaBhGEL2EinpQgsyPLTU4T14cmLPi0M4lElEoN5a63iEe5UHjYHHfnbs4vcuwN7EyiKFcKO8lutdrmXh8UXXenXaQ2Q5+bBn2c7vepd9o46yWPu2wU3YPNx5j10b03d6y+OYMsxzhuTI+4RWT5VZwb8JwoG2BXKmkCLe/rugPEYCi3lKPkKCE7e9h0xK6K43dNZG0RbZg96w8JuWGxPaoUMThSBc97t7Aua7KLGDRj3rwHT95OnHG/YGWsEvxum8UP9l5YyGeVtJpnB5GGl58o3puOgmHyh+Hqy2HMV4Oj3DRNHb8lxPM7lhr43KW1mDQ9sHKsUmukyAIW0bL8bMkakflsOWAvPMH3xV0q7SyQy0VHpZSVvfYBeFdr/XyG7eEApoGIG0cBXK21js3smP8eEdHDfw520PaQNeyg7SFryEE7V5CLrBKllA/AJFCsURfAIKVU3Qy73QzguNa6BoBXAbyALOAN3B48ePCQDrnqOdkCwFat9XatdQqoebFfhn36AbAiMjMAdFYqi78KWus88R+AYf9v78zj7SiqPP49JiyBANHgwkRBAmL8ACIIM5A4qERBERHZEoZFEPcBAUGRiAygILKq4MCAoMgAAiKKjInRsEgAgRACScAlJMMyfBTEhUCAQPKbP071u3Xrdffr+94LuY/U7/O5n9vddWrrrq4+dbZambSrev1Dqa0ru/6h1NaVXf+KauvL9cPjMM2Kfp9K0vfGxSPF+YHAeQnNPOCN0flDwPq19a7sjndwg2atTNpVvf6h1NaVXf9QauvKrn9FtbVbfrjIPZ24z01o5pdM3KPrys2ikoyMjIwVh8eAOP7BG4HHq2hCNNX1gL9SgzxxZ2RkZKw43A28xcw2NrPVgcm4t3iM64Fid+q9gRsVWO8qDA1zQMeFK5l2Va+/E9pVvf5OaFf1+juh7aTMroCkl8zsMOCXuDngJZLmm9nJuOjneuBi4DIzW4Bz2pP7KndIeE5mZGRkZLSQRSUZGRkZQwx54s7IyMgYYsgTd0ZGRsYQw5CeuIPQvxP6PVdUWxrUvaaZvbbk+uvCFnDxtWPMrHwLlYxBR3g2Aw5xMZgIceyr0kZVpWWsGuhK5aSZnQ4slHRBcv0o4A2Sjg3nsyVtU1ZGRbmN6M2s9/5XEST9NdDdRMm2ay0y9ezpa2YXAtMk/SSpa3981/vPRtfOwc2CFuE7DF2jsMFySVtr+yNpdkS7k6Qbw/HGkhZFaXsWbTOzL/RR5tlRvumSdg7Hx0n6RlU+MzsAH3OXJdc/CTwr6YroWqM2JO1+taS/1eWLyh8G7Ixvv7cLcKukvaP02lCGkn4Y0fZ5X83sw8D9kh4O108A9gIeBo6I84T02cBnJd2ZXP8EMEXS2HD+RuDNkmaG8y8AxZ5iV0hakOTfCL/XfzGz7YF3AQ9Jui6hazS2Q8z9FyW9GM7fCuwKPJyO9ZC+Pr45+N+AS4Az8I3GHwKOLtrbF5NVVvaqhG6duB8AtpC0PLn+KnzwbxHOV9TEvQgftGXxAhS9NGVbtG2P73T/hKTt4j5JSoPLFGnzJW2eXDNgR9w06CPAffgkfp2kxRHdctzzqthcM26zJO0U0fb0P70XSdpyYA4wFXghvQ+STory3Stp67IyS/p5L7Bj3P5wfR3gZknvjK41akNdnyrasCO+QfqHgLvwIHtjJS1J6M4ty45vpD5G0vCIts/7amb3A9tLWmJmuwFn4x+NrYF9JO3SVpHZu/DgRHcBxwIbAf+JO2scJd/IBDO7Erhc0g3h/Pe42dxawDhJ+0dlfhU4GB/bPwLeB9yMb4x+n6QjI9pGY9vMfgMcKumPZrZpaO/leECluyQdl/RrOu4avg4wEfg+8HN88t5f0nsC3fephiR9vCb9lY+Xw+2z0x8wv0ka8BLwdMlvMfB0Sd4lwP0lv7n4B2EgbX438GvgVuCDJekP1uStTAvpw3Cu8F5gSZJ2FDAT32XoQGBkTTn3lh2XpL0DOA2fOC/GX3CrKHN22XEFbeU9TtOatqGuTyW0jwG3h/u0Tri2qMGzNeCAME6uAt7e6X3FJ8bi2iXAsX3dt/Dcv45zp48CO9fd/5K23JqkPQCsDowK78la4fpwYF5/xjYwNzr+GvDdcLx6nBbR3Bfd00eStDl9PYv881+3OuAsMbO3SPpjfNHM3gLEMRznKnB7DbEI55hq0aH4YRd8H83ngVMk3VSR7Qkz+2dJdyV1bUeLWy5ry5Y41z0Jj9U7JU6XdA5wjpltjHNwM8zsYeBUSXPSplcct52HfHOAL5vZ+FDuuWZ2rNxhIMZYM7sefxGL47h9u0enq5nZ2pKejWkCx716kq9pG0aY2da4vmbNcGxRObMj2muBPfB7uczMflZyH+J2Dcc51KOBO4G9Jf2+hLTJfTUzG4kzDxNx7rnAmpRjH7zf5+MfrklmNktBVFeRd2J0PDpJe14eoW6pmT2ksMqQO4ksTWibju24vzvhog8kLQ2rphTLQrrMLBX/9dB3Iq5bFdGtE/cJwFQz+zpQRLTfFjgOOLIyV99YqiBj7AOzqBE/4AMUM7sbeC0+WO8I13om/WTS+CJwtZn9gPY+HUTiKRU+UJPxl3YZvqzdWdLCqgZLWhQmohE4R7kZPvHFqJpkDdg4oSUoU7cGtsS51SdSGtpDVJ5Z1b6Ai4Efm9lnFQLFm9mbcZHAxWUZGrThT7jYIT2G6FkBSDrCfD/U9+L39gxgXTPbF/iFpJ7dD8zs34EjgBn45tZ146bJff0W/jyexldYs0I9WwO99lw1s1/jTMr7wrP9CnAYcLeZfVNS4UW42Mw2k/SH0MdC/zIOeCYpdlSQHVvodyFHNjw+Rlx/07F9v5mdCfwfsCkwPdBWKVCbjsF1euXM6EFXyrgBzGwLfLIrtqCeB5wpaW5EM0XSqR2UeZ6kPi1RzJWgewH/wCfN6+KXOqK7mRbHkcrEpUi+HOhfhytmij7Nx0M8PpHQLcTl2T+K+1vR1rG05OCPhvbeIOn5Etp315Ul6ZZAdwjOla6Jxwe+Om1jf2Fmn8E/wIUC7RngNEnnJ3SN2mBm60p6up9tWQ34AD6J7yxp/ShtOf6ReJJ2rtLwZ/v2iLbpfR2Dby50n4L+xsw2AFaT9EjSto8qURiG62/A34MDwvkHgO8ApwDFZPpOfGV2hKSpUd46uTGSDolob6bB2DazEfgHbgPcnfu+cH08sIl6K6Ib3auMenTlxG1mr1KimIzSRkn6ezj+Tl05kj5fkv+teAzdceHSg8BFZUvgSPzwEVz7XyZ+aIzAXW2Cy+nLd7stzzcaV1Q+IumeJG05Lqf/Gc7NtT1QtVuAbJhOEBX1LcfluQVtWubuEe3cND3CC7i1wDeKFzrKNxIff4vLMjZtg5k9BHxF0o8a9GsP4PaKD8AISc9F5xvVlRVz4HUfj+Kem9kBkv47XJsg6baI5jBJ5/XV/oj+KkmTovMtcKVhoeCeD5wuaV5Z/oZ1bC/ptwPI/yZgsqQzkutNx2DH7/aqhG6duJuaQi3FOfGr8VCJqeXBpUn+HYCfAP+FK/oMX4Z/EtizbKCa2eY4R3sg8CVJV0dp6wKvL2Tx5rbAxUZ4v5T054j2BFzBdQ+uxf+GpIsq+n8D8GVJ8wJHNhsX32wCXCjpWxHtidTIadVuARJbP1wraa+K+htzRX1McMPx1cWJkrbuRG7ZARe7ES6GGImPmQVVeczsx8AOuJz5NlxReZuk+SW0PWaOfSG5rzPUbgZaWJU0suhpWN8jkjYsuT4S54afLclW0AwDXq1gXmoese5g3FLlbf1tU8izPi25/Bh8pXpMQtN0DH4sOj0J+I84PX23VzmoCzSk6Q+3Lb0PuAh4DT653gFcQ3vA8dHAZ4CbgF8Bn8AHZVW5U4H3lFx/NzA1Oh+LLzXvxJfpewNrluS7EDg4Ol8AnAt8D7ggoZ1PS4s/Gri7pp2x5cwU4IfheB0GYP1CBxYYNWVMaEg3DDfvAjgp/C/HP0Kn4HqM/4h/A2kDLvL4M3ADHibzeuD6ivxvxk0Cz8M/pE/iMu7SezWQ+0rLqqSRRU/D+lJrjM/hK5Onwu9h4HMl+Sbj4r/HgVtwWf9jwHXANv1pUxiTBwHTgIXAWcBjgzkG+ztWX8m/rlROSpoZFCEn4UvtZ3Bb0ekJ3VPABcAFQX64HzDf3PLgsrRcXOZ2c0l9t5g7yBRYQLv4YUPgcxa2gVOLM9wO+HSUb7GkwwHMbGZSzfNqafGfshrPOCDezn4i/gFD0mJLNPUdLinrrB/iMocB++Jc0zQ5578b/hEZgX9IC9p1cbn9GHyy/BWuRDsGV8ZdLqnglrbBJ48P4RPmlcAMhbdzAG14Ky4quBVXdJaK2aJ78r/m3qojwq84jrGe1TiBqN0BpIlVSSOLngJWbdlkwGoR3fHAeJwhWRiujQW+bWavkfT1KO/xwDslLQjl34GLM3rJ0oGNLbEQamtwS1z2BG67fTwwU5LM7KNV+Wg4BmvyZNC9ViXQzBQK6Bnk+wHvx7nqe1KagFJ5akC8vDyZ1mC0PANGAAAJvklEQVQZmdDFg2h4MukcGB2nWvVNEg16cV4ou2KzuUfN7HCcG9oG52YKRdBqtCPua68lZYKtzOzpUOeIcFy0R5LWDecX4zty3AV8x9y8cAdcfPPTpMzLcDvjO/AVzxdx076PKNEHqDMzw0ZtMLPTgN1xr7up1MDMpoQyXgv8HvgtznV/StKyhHw9YDcod8LCRW4FXhfEQBYdE86LMAfjzJ1wimd/f0QztqSOs2q68rvo+EBgK0XKaEkLzS1l7sPtwAssVRAlSZptZosqJm3wVUhdGwpMwT/G5wNXmNlVfdA3HYMZNejKidsamkKZ2Un4y/Ugbk1xnKSXaop+UwWHajhnV+B7Cp5pJW2L7cCXm9kbJP0JQEEZFLj/lOtLd3Y+k8jGN0k7FP94vA+YpKCMxT3X2iwDFMn6zOxI1cj+JA2rSkuwLe5ksjxwpn8BNi36mWCspC1D/d8LtBuqQukY6JqYGTZtw5b4OHk8lH0QLVfyE5MP/UH46u0GXL59p6R/VDTzYTX3zruIlvlafAwuNgN4G71h+FZWU9IESe9tWDcqsSCS9Fy6OqP9owIwMj5Xu230M2pg4aGWH8FY/EP8U+CfzOxYXMb9h4S+0Rg0s8W03o+18gTfjq6cuHHvqx5OIHC155rZNTgXUIg1vorL1bYKv1ODOKOXyVbAF2vqnBUdzzCzXRRsjQuYm6gdj7vogtu4/tzMjsaVneAc8pkhLcYoXD7/3VDWXTg3JtyluQdyq4fPpA2UO0BUOfjA4C0plypY9Uh63sz+UDFpQyTWkbQscHFVliKpid++qjYzbNqGDXAHEczd2U8DDsc9Ly/E9RNF+8aZx6EZD7wH5/xH4pzp7ZLij2IZp10KRQrgGprYCuUduIx9X9wp7NqyPNYyH90cf7YP4O9GfM8eM7OJkmYkeSfS2z48/aik5zEW9dWnGEFMcwpwirnT2H746neTTsqJyst23DXoSquSGIE7Q1Iv70Jze+uZ+FL9xTRdzZxtyurcFfg2sKtaFiPH4S/bB2Nu3NyOdgotU6x5uF3y1KTM23B54qPhfA4uv14b+L7aLRF+Tr2lyO5l1/tjCVBRzhJczg9haR+do3Yb5mW0xEyGy4qXUMIZWWdmhlVtaPsom9kcSe8Ix98FnpR0YppW0sfhuL3zjrieYuOYGzSzLVRiThdk75MlXR5dO6Gsjla39DUz24yWU9VTuOv8MZJKrXLMbAJwBfADXBxmOFPwMVzpe1ug2xzXxcwMdMJ1LxNwcVUvi5kmMLMvSTo9HO8j6Zoo7VRJU8JxY+ubjMFDt3LchZnbYfiAfZWZvYRva39yRDYGn2DH4crE23EzrzsqZOGVyhZoTRySfmFmL+Dem3vgstvt8ABJf0vyTCPIoPvA6sWkHTBTrlx9yszWTmj78kDsQbSkHEyZ4VbA63GHnhgbkexQ3YH4BdyKoSnKRAtlGG5mw4OIbCJuo9+TFhOa2e44tz0B/9DOx8fM0eE/xiPhY12pdI1oy8zv1sZFXqPxGB6/w5WnH1YrAt5RNf06C9hD0r3RtZ+Z2XW4Oeu/hGsv4OZ8m4U+GfAbXEfQJkLpUJE9GTg9HB+HW3QVKJgVaMnwM15GdOXEHQb0BGA7hXCXQYZ2vpkdFeRqKNiImtuibou/lB8HLjKzv6t3NL4d8MnoStzUr3I5LGmGmR2MR0+7HZiYyhI7fBFenaTFHpzp4F+kBk4KoZwVsaQ8B7eXb1uxhNXPOTSI91KBTvrVdLV0JXCLedyL5/DJEfNIdan8+mD8WX4JuEcet6MKnShde5R45nFXjgAOwfUuRdpe+GR4k5lNC2l14ph1k0m7qGtOqKPAt/BndUlMZ2bbhrT4WXWiyLaK4/S8E+ubjEFCV4pKzMN/vl9JDOowcUxXEljKzNbDJ+UJ4X8UHoDqkIRuGG55sh/wdjyi3pXpcjLhYtfAxTDLSLhY68AByMwux0OXtjndmNmncVOu/aJrjZwUQvqauDx8U3zVcYnqFbR9wszmKYTOLUmbWygj+1FuJ/2KlVNtSfQWwWyPy7qnKzifBNHESLXHiymrZ33gKSUvQtzPMG5qla5Bdv4FYH/gUuDb6eos0K2NB7raD4+jcimuxJue0D0IjE/LCPXcLmlcOO/Xs7IoHG9FetMQwE/hopqqEMirdvjVFYSu5Ljx2A29Ng6Q9KR5fAkAzG2vN8fN/O7Euamzy16YkH8ZLtaYZmZr4C/PzWZ2sqRzI7qmXOwGuNniJDzE7FXAtRX1HwX81Mz+jfaYEmvgL3KM+CUoMxWLcSn+YbkVD2C/Oc7xDQRV0eqgt71zJ2jcr05WEirxeFVizQA9E/xpwF9x8cVlwPq4KO6gIPYq0InS9QxgT1wZuqVK4tpEZT2Li1kuD5PwPsCXCcGZIpwDTDezY2gfL98MaQX6+6z64tjqzPbiOjuxvskYLKgLvIDSHzVxnWmP/zwNtwb5AS7b3BLK40ZHedbAX7JrgLtxy5Qxg9DmMbj883HgwBq6nXCrh8OBnRr0sa8Y13E85OF90Tfsy5XAJ0uuHwpcNRjPdTDa2Y/6Z+G73uyDi0G2D9fH0dubcRnt8d1foiLWO276+VyRRh9x4Tto7264vLrwiPwNLiMf8LMarPuPy/fLPFn/FXd4e1mf8ary61ZRSWyp0JaEu57HXLfhXOb48NsC56juUMtjr6C9NKRPxSPv9TsIT1Ju7AB0D3CWpAcGUF7R/9hKA8rFBAOKe1FR/+txN+iltIegXR34qKpNA/sqt3G/VgQSC5QH1R6bo1Z00K3o5Fkl4qe1GIT7b2Y3AkdKuj+5vi0exqC/+pCMGnTlxN0fmO+9NwGfvHcDRksaldAsp/VBiDver4FrvR2ApmmA8uVO0Yk5Xj/Kfi9RCFqFfRWHKprKbbsB5lun1ZmEtkXHW1nPakXpQzLqMaQnbjP7PC3zrhcJpoDhf64qQsMOYv3LcQegIhxo7Am5XNJWK7L+jM7QB8fftpJb2bAhEh3PzBZI2rTTtIyBYahP3GfTCs3ZaxeRl6H+MueJHjdmSbu+zE3KeAWim8U45psV36je1lKH4ptTTCrPmTEQDOmJu5tgJW7M6iA4fkZGFbpNjBNjRelDMurRreaAQwIVbsymDgIEZWQMZcg3CxmfyNj/Z6jrQ7odmeMeAIKM+1Y8VnjhxrxQYYeejIz+YkVYgGS8cpA57oGhUzfmjIxGUI6Ol1GDzHEPApq6MWdkZGQMBvLEPciI3JgnSdppZbcnIyPjlYc8cWdkZGQMMdRtWJuRkZGR0YXIE3dGRkbGEEOeuDMyMjKGGPLEnZGRkTHEkCfujIyMjCGG/wdRgcoH+HekdQAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "correlations = monthly_df.corr()\n",
-    "sns.heatmap(correlations, cmap = 'Reds', vmax = 1, vmin = 0).set_title(\"Correlation Matrix\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "std_dev = returns.std()\n",
-    "monthly_std_dev = std_dev*(12**0.5)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.4"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}