diff --git a/Dockerfile.prod b/Dockerfile.prod
index 9790e7e..02144dd 100644
--- a/Dockerfile.prod
+++ b/Dockerfile.prod
@@ -31,6 +31,7 @@ RUN az storage blob download-batch \
     --source mlruns \
     --destination /app/mlruns/ || echo "No mlruns/ in storage yet, skipping"
 EXPOSE 8000 8501
+
 COPY docker/entrypoint.sh /entrypoint.sh
 RUN chmod +x /entrypoint.sh
-CMD ["/entrypoint.sh"]
\ No newline at end of file
+CMD ["/bin/bash", "/entrypoint.sh"]
\ No newline at end of file
diff --git a/mlflow.db b/mlflow.db
index 2f0cdf7..492b80e 100644
Binary files a/mlflow.db and b/mlflow.db differ
diff --git a/models/artifacts/backtest_results.json b/models/artifacts/backtest_results.json
index 9ee9f3f..0e85b0a 100644
--- a/models/artifacts/backtest_results.json
+++ b/models/artifacts/backtest_results.json
@@ -2,85 +2,85 @@
   "logistic_regression": {
     "model_name": "logistic_regression",
     "initial_capital": 500000.0,
-    "final_capital": 493204.1575020498,
-    "total_trades": 136738,
+    "final_capital": 492705.5220935263,
+    "total_trades": 136657,
     "metrics": {
-      "total_return_pct": -0.7007231456740204,
-      "sharpe_ratio": 0.009860509042075846,
-      "win_rate": 0.49995612046395294,
-      "profit_factor": 0.9927246230177307
+      "total_return_pct": -0.8011159236488097,
+      "sharpe_ratio": 0.0027096238618928097,
+      "win_rate": 0.49990121252478836,
+      "profit_factor": 0.9921891798679353
     }
   },
   "decision_tree": {
     "model_name": "decision_tree",
     "initial_capital": 500000.0,
-    "final_capital": 578881.831804675,
-    "total_trades": 131809,
+    "final_capital": 535574.7952353342,
+    "total_trades": 139347,
     "metrics": {
-      "total_return_pct": 15.009130022201145,
-      "sharpe_ratio": 1.106539644244743,
-      "win_rate": 0.5029929670963288,
-      "profit_factor": 1.0827461283809072
+      "total_return_pct": 6.638419192753875,
+      "sharpe_ratio": 0.4680495126617511,
+      "win_rate": 0.5132295636073974,
+      "profit_factor": 1.0388947831273074
     }
   },
   "adaboost": {
     "model_name": "adaboost",
     "initial_capital": 500000.0,
-    "final_capital": 527884.436830822,
-    "total_trades": 138862,
+    "final_capital": 497490.2428801132,
+    "total_trades": 139963,
     "metrics": {
-      "total_return_pct": 6.16692067536555,
-      "sharpe_ratio": 0.5479899310298146,
-      "win_rate": 0.5121199464216273,
-      "profit_factor": 1.0302239065896193
+      "total_return_pct": -0.12140197236132355,
+      "sharpe_ratio": 0.03631951202318103,
+      "win_rate": 0.5066767645734944,
+      "profit_factor": 0.9972326441488291
     }
   },
   "random_forest": {
     "model_name": "random_forest",
     "initial_capital": 500000.0,
-    "final_capital": 535141.0293030565,
-    "total_trades": 137898,
+    "final_capital": 567910.5106008762,
+    "total_trades": 137675,
     "metrics": {
-      "total_return_pct": 6.959293080633122,
-      "sharpe_ratio": 0.5176854615114458,
-      "win_rate": 0.5085715528869165,
-      "profit_factor": 1.0360523930337522
+      "total_return_pct": 14.323199716288414,
+      "sharpe_ratio": 1.029771534052213,
+      "win_rate": 0.5054512438714364,
+      "profit_factor": 1.06602984774183
     }
   },
   "lightgbm": {
     "model_name": "lightgbm",
     "initial_capital": 500000.0,
-    "final_capital": 502976.41332192585,
-    "total_trades": 133002,
+    "final_capital": 504583.0645151714,
+    "total_trades": 133377,
     "metrics": {
-      "total_return_pct": 1.2614237556337615,
-      "sharpe_ratio": 0.14759871549408887,
-      "win_rate": 0.49972932737853565,
-      "profit_factor": 1.0030046186448662
+      "total_return_pct": 1.6038144528949472,
+      "sharpe_ratio": 0.17137856645149313,
+      "win_rate": 0.5027628451682075,
+      "profit_factor": 1.0046778475452267
     }
   },
   "voting_classifier": {
     "model_name": "voting_classifier",
     "initial_capital": 500000.0,
-    "final_capital": 511678.2427597648,
-    "total_trades": 135828,
+    "final_capital": 508977.30249215994,
+    "total_trades": 136029,
     "metrics": {
-      "total_return_pct": 3.0150256782757623,
-      "sharpe_ratio": 0.2756268746125455,
-      "win_rate": 0.5035338810849015,
-      "profit_factor": 1.0119298707075866
+      "total_return_pct": 2.4780097080419727,
+      "sharpe_ratio": 0.24514815714230245,
+      "win_rate": 0.5021943850208411,
+      "profit_factor": 1.0091277291482916
     }
   },
   "naive_buy_baseline": {
     "model_name": "naive_buy_baseline",
     "initial_capital": 500000.0,
-    "final_capital": 583926.7224497921,
+    "final_capital": 583902.3325100574,
     "total_trades": 151524,
     "metrics": {
-      "total_return_pct": 17.606993973683593,
-      "sharpe_ratio": 0.9842788949006163,
-      "win_rate": 0.5174163828832397,
-      "profit_factor": 1.0829189840007805
+      "total_return_pct": 17.602081666393786,
+      "sharpe_ratio": 0.9840903604306787,
+      "win_rate": 0.5174097832686572,
+      "profit_factor": 1.0828999784672162
     }
   }
 }
\ No newline at end of file
diff --git a/models/artifacts/best_model.json b/models/artifacts/best_model.json
index 0fa5eee..60b8681 100644
--- a/models/artifacts/best_model.json
+++ b/models/artifacts/best_model.json
@@ -1,10 +1,10 @@
 {
   "model_name": "lightgbm",
   "model_path": "models/lightgbm.pkl",
-  "test_f1_macro": 0.0,
-  "test_accuracy": 0.0,
-  "test_precision_macro": 0.0,
-  "test_recall_macro": 0.0,
-  "test_mcc": 0.1183,
-  "selected_at": "2026-05-04T15:21:09.345798+00:00Z"
+  "test_f1_macro": 0.4073584602583696,
+  "test_accuracy": 0.417024663986895,
+  "test_precision_macro": 0.43576849537949297,
+  "test_recall_macro": 0.417024663986895,
+  "test_mcc": 0.10451422641901091,
+  "selected_at": "2026-05-04T21:13:44.737894+00:00Z"
 }
\ No newline at end of file
diff --git a/models/artifacts/confusion_matrix_adaboost.csv b/models/artifacts/confusion_matrix_adaboost.csv
index ee0df42..c693be7 100644
--- a/models/artifacts/confusion_matrix_adaboost.csv
+++ b/models/artifacts/confusion_matrix_adaboost.csv
@@ -1,4 +1,4 @@
 ,Pred Hold,Pred Buy,Pred Sell
-Hold,46820,3038,12092
-Buy,28556,5761,5404
-Sell,37832,2923,9577
+Hold,45241,3032,13678
+Buy,28304,5669,5747
+Sell,36772,2938,10622
diff --git a/models/artifacts/confusion_matrix_decision_tree.csv b/models/artifacts/confusion_matrix_decision_tree.csv
index 1b81e94..77a7b33 100644
--- a/models/artifacts/confusion_matrix_decision_tree.csv
+++ b/models/artifacts/confusion_matrix_decision_tree.csv
@@ -1,4 +1,4 @@
 ,Pred Hold,Pred Buy,Pred Sell
-Hold,34039,5565,22346
-Buy,21613,7929,10179
-Sell,26686,5034,18612
+Hold,33257,3765,24929
+Buy,21340,5300,13080
+Sell,26159,3149,21024
diff --git a/models/artifacts/confusion_matrix_lightgbm.csv b/models/artifacts/confusion_matrix_lightgbm.csv
index 0139c4d..43ec5b0 100644
--- a/models/artifacts/confusion_matrix_lightgbm.csv
+++ b/models/artifacts/confusion_matrix_lightgbm.csv
@@ -1,4 +1,4 @@
 ,Pred Hold,Pred Buy,Pred Sell
-Hold,27783,5582,28585
-Buy,13376,9794,16551
-Sell,19146,3892,27294
+Hold,26473,5541,29937
+Buy,13067,8926,17727
+Sell,18492,3850,27990
diff --git a/models/artifacts/confusion_matrix_logistic_regression.csv b/models/artifacts/confusion_matrix_logistic_regression.csv
index ab8f887..4ff8dce 100644
--- a/models/artifacts/confusion_matrix_logistic_regression.csv
+++ b/models/artifacts/confusion_matrix_logistic_regression.csv
@@ -1,4 +1,4 @@
 ,Pred Hold,Pred Buy,Pred Sell
-Hold,29952,4493,27505
-Buy,17248,8002,14471
-Sell,23531,2611,24190
+Hold,37905,4572,19474
+Buy,22756,7745,9219
+Sell,30309,2657,17366
diff --git a/models/artifacts/confusion_matrix_random_forest.csv b/models/artifacts/confusion_matrix_random_forest.csv
index e68d473..7aba26c 100644
--- a/models/artifacts/confusion_matrix_random_forest.csv
+++ b/models/artifacts/confusion_matrix_random_forest.csv
@@ -1,4 +1,4 @@
 ,Pred Hold,Pred Buy,Pred Sell
-Hold,39225,4054,18671
-Buy,21213,7325,11183
-Sell,29766,2836,17730
+Hold,34209,4077,23665
+Buy,17679,7300,14741
+Sell,24995,2680,22657
diff --git a/models/artifacts/confusion_matrix_voting_classifier.csv b/models/artifacts/confusion_matrix_voting_classifier.csv
index 9b0629f..1f43bb4 100644
--- a/models/artifacts/confusion_matrix_voting_classifier.csv
+++ b/models/artifacts/confusion_matrix_voting_classifier.csv
@@ -1,4 +1,4 @@
 ,Pred Hold,Pred Buy,Pred Sell
-Hold,31878,4486,25586
-Buy,16279,8415,15027
-Sell,22826,3114,24392
+Hold,29621,4591,27739
+Buy,14984,7937,16799
+Sell,20986,3146,26200
diff --git a/models/artifacts/model_comparison.csv b/models/artifacts/model_comparison.csv
index fb81058..92addb6 100644
--- a/models/artifacts/model_comparison.csv
+++ b/models/artifacts/model_comparison.csv
@@ -1,7 +1,7 @@
-model,train_accuracy,test_accuracy,cv_accuracy,overfit_gap,train_time_s
-logistic_regression,0.4483937946341601,0.40883014697175035,0.3877766233304916,0.03956364766240977,1360.18
-decision_tree,0.4823761149694377,0.39855396639517904,0.3804392227905655,0.08382214857425868,13.56
-adaboost,0.4685643972379895,0.4089551453270352,0.3916595623756749,0.059609251910954286,4792.6
-random_forest,0.5800421927579644,0.4231457480822621,0.39460562304631996,0.15689644467570235,683.38
-lightgbm,0.6146572379561654,0.42779042381021304,0.4080615942028986,0.1868668141459524,479.19
-voting_classifier,0.6056908606223682,0.4261654451915106,,0.1795254154308576,1994.97
+Model,Train Acc,Test Acc,Overfit Gap,Weighted F1,MCC,Signal Precision (B),Hold Recall (B)
+logistic_regression,0.4393,0.4146,0.0248,0.3954,0.0749,0.4471,0.6119
+decision_tree,0.4798,0.392,0.0878,0.3706,0.0426,0.395,0.5368
+adaboost,0.4664,0.4048,0.0616,0.3593,0.0444,0.4203,0.7303
+random_forest,0.5792,0.4221,0.157,0.4065,0.0958,0.4452,0.5522
+lightgbm,0.5989,0.417,0.1818,0.4074,0.1045,0.4286,0.4273
+voting_classifier,0.5931,0.4195,0.1736,0.4075,0.1008,0.4384,0.4781
diff --git a/models/artifacts/training_results.json b/models/artifacts/training_results.json
index 29fd040..fa12da1 100644
--- a/models/artifacts/training_results.json
+++ b/models/artifacts/training_results.json
@@ -1,15 +1,15 @@
 {
-  "generated_at": "2026-05-03T16:58:59.199060+00:00",
+  "generated_at": "2026-05-04T21:02:49.210784+00:00",
   "models": {
     "logistic_regression": {
       "best_params": {
         "C": 0.1,
         "l1_ratio": 0.1
       },
-      "cv_accuracy": 0.3877766233304916,
-      "train_accuracy": 0.4483937946341601,
-      "test_accuracy": 0.40883014697175035,
-      "train_time_s": 1360.18,
+      "cv_accuracy": 0.3884759519749929,
+      "train_accuracy": 0.43933157502131287,
+      "test_accuracy": 0.4145707650506898,
+      "train_time_s": 97.81,
       "artifact_path": "models/logistic_regression.pkl"
     },
     "decision_tree": {
@@ -17,10 +17,10 @@
         "max_depth": 8,
         "min_samples_leaf": 200
       },
-      "cv_accuracy": 0.3804392227905655,
-      "train_accuracy": 0.4823761149694377,
-      "test_accuracy": 0.39855396639517904,
-      "train_time_s": 13.56,
+      "cv_accuracy": 0.4016943734015345,
+      "train_accuracy": 0.4797877371057119,
+      "test_accuracy": 0.39197252685802253,
+      "train_time_s": 3.23,
       "artifact_path": "models/decision_tree.pkl"
     },
     "adaboost": {
@@ -28,10 +28,10 @@
         "learning_rate": 0.1,
         "n_estimators": 200
       },
-      "cv_accuracy": 0.3916595623756749,
-      "train_accuracy": 0.4685643972379895,
-      "test_accuracy": 0.4089551453270352,
-      "train_time_s": 4792.6,
+      "cv_accuracy": 0.39465668513782326,
+      "train_accuracy": 0.4663806079497016,
+      "test_accuracy": 0.4048077998460557,
+      "train_time_s": 754.96,
       "artifact_path": "models/adaboost.pkl"
     },
     "random_forest": {
@@ -40,10 +40,10 @@
         "max_samples": 0.7,
         "min_samples_leaf": 100
       },
-      "cv_accuracy": 0.39460562304631996,
-      "train_accuracy": 0.5800421927579644,
-      "test_accuracy": 0.4231457480822621,
-      "train_time_s": 683.38,
+      "cv_accuracy": 0.3956046639670361,
+      "train_accuracy": 0.5791756580349531,
+      "test_accuracy": 0.4221364052025289,
+      "train_time_s": 204.96,
       "artifact_path": "models/random_forest.pkl"
     },
     "lightgbm": {
@@ -54,10 +54,10 @@
         "num_leaves": 48,
         "reg_lambda": 1.0
       },
-      "cv_accuracy": 0.4080615942028986,
-      "train_accuracy": 0.6146572379561654,
-      "test_accuracy": 0.42779042381021304,
-      "train_time_s": 479.19,
+      "cv_accuracy": 0.3952450092355783,
+      "train_accuracy": 0.5988517689684569,
+      "test_accuracy": 0.417024663986895,
+      "train_time_s": 1833.6,
       "artifact_path": "models/lightgbm.pkl"
     },
     "voting_classifier": {
@@ -70,9 +70,9 @@
         "voting": "soft"
       },
       "cv_accuracy": null,
-      "train_accuracy": 0.6056908606223682,
-      "test_accuracy": 0.4261654451915106,
-      "train_time_s": 1994.97,
+      "train_accuracy": 0.5930540014919011,
+      "test_accuracy": 0.41945224765300687,
+      "train_time_s": 469.87,
       "artifact_path": "models/voting_classifier.pkl"
     }
   }