📉 Trading-Bot

A professional-grade C++ trading bot for backtesting and simulating trading strategies on Nifty 50 index data with comprehensive risk management and performance analytics.

🚀 Features

Core Functionality

• Market Data Handler: Robust CSV parsing with validation and error handling
• Advanced Trading Strategy: Moving Average Crossover with RSI filter and risk controls
• Risk Management:
  • Dynamic position sizing based on account balance
  • Maximum exposure limits
  • Stop-loss and take-profit orders
• Broker Simulator:
  • Realistic order execution
  • Portfolio tracking with unrealized P/L
  • Average entry price calculation for multiple buys
• Comprehensive Trade Logging:
  • Detailed trade history with reasons
  • Advanced performance metrics (Sharpe Ratio, Max Drawdown, Profit Factor)
  • CSV export for analysis
• Dual Mode Operation:
  • Backtest on historical data
  • Live simulation with synthetic market data

Performance Metrics

• Total/Winning/Losing trades
• Win rate percentage
• Average win/loss amounts
• Largest win/loss
• Profit factor (gross profit / gross loss)
• Maximum drawdown percentage
• Sharpe ratio (risk-adjusted returns)

📁 Project Structure

nifty50-trading-bot/
├── bot/                       # Source files
│   ├── main.cpp              # Main entry point with TradingEngine
│   ├── Config.cpp/h          # Configuration management with validation
│   ├── MarketDataHandler.cpp/h   # CSV data loading and live data generation
│   ├── Strategy.cpp/h        # Trading strategy with MA crossover and RSI
│   ├── RiskManager.cpp/h     # Position sizing and risk controls
│   ├── BrokerSimulator.cpp/h # Order execution and portfolio management
│   ├── TradeLogger.cpp/h     # Trade logging and statistics
│   └── Types.h               # Common data structures and enums
├── data/
│   └── nifty50_data.csv      # Historical OHLCV data
├── logs/                      # Generated log files
│   ├── trades.csv            # Backtest trade log
│   └── live_trades.csv       # Live simulation trade log
├── config.txt                 # Configuration file
├── README.md
└── .gitignore

🛠️ Build & Run

Prerequisites

• C++17 compatible compiler (g++, clang, MSVC)
• Standard C++ library with threading support

Quick Start - Direct Compilation

Windows (PowerShell/CMD):

cd bot
g++ -std=c++17 -O2 *.cpp -o trading_bot.exe
.\trading_bot.exe              # Run backtest (default)
.\trading_bot.exe --live       # Run live simulation

Linux / macOS:

cd bot
g++ -std=c++17 -O2 *.cpp -o trading_bot
./trading_bot                  # Run backtest (default)
./trading_bot --live           # Run live simulation

Command Line Options

./trading_bot                  # Use mode from config.txt
./trading_bot --backtest       # Force backtest mode
./trading_bot --live           # Force live simulation mode
./trading_bot --config custom.txt  # Use custom config file

Build Optimization Flags

For production use, compile with optimizations:

g++ -std=c++17 -O3 -march=native -DNDEBUG *.cpp -o trading_bot

⚙️ Configuration

Edit config.txt to customize trading parameters:

Capital Management

initial_balance=100000        # Starting capital in INR
risk_percentage=10.0          # Capital allocation per trade (%)
max_exposure=80.0             # Max portfolio exposure (%)
stop_loss_percentage=5.0      # Stop loss threshold (%)
take_profit_percentage=15.0   # Take profit target (%)

Strategy Parameters

short_ma_period=20           # Short-term MA period (days)
long_ma_period=50            # Long-term MA period (days)
rsi_period=14                # RSI calculation period (days)

Mode Selection

mode=backtest                # backtest or live

Live Simulation Settings

live_iterations=100          # Number of ticks to simulate
live_history_size=200        # Historical data points for context
live_delay_ms=500           # Delay between ticks (ms)

📊 Data Format

CSV file must have the following format:

Date,Open,High,Low,Close,Volume
2024-01-01,21727.75,21834.35,21680.85,21741.90,154000000
2024-01-02,21751.35,21755.60,21555.65,21665.80,263710000

Data Requirements:

• Header row required
• Date format: YYYY-MM-DD (or any consistent format)
• Prices: Decimal numbers
• Volume: Integer
• OHLC validation: High ≥ Low, High ≥ Open, High ≥ Close, Low ≤ Open, Low ≤ Close

📈 Trading Strategy

Moving Average Crossover with RSI Filter

BUY Signal:

• Short MA crosses above Long MA (Golden Cross)
• RSI < 70 (not overbought)
• No existing position

SELL Signal:

• Short MA crosses below Long MA (Death Cross)
• RSI > 30 (not oversold)
• Has existing position

Risk Management Exits:

• Stop Loss: Position closed if loss exceeds configured percentage
• Take Profit: Position closed if profit reaches target percentage

HOLD:

• No crossover detected
• RSI in extreme zones
• Exposure limits reached

🎯 Key Improvements Over Original

1. Fixed Critical Issues

• ✅ Corrected risk management calculation (was allocating 40% per trade!)
• ✅ Fixed look-ahead bias in backtesting
• ✅ Improved CSV parsing with proper error handling
• ✅ Fixed position management edge cases

2. Enhanced Features

• ✅ Stop-loss and take-profit orders
• ✅ Better crossover detection (handles exact crosses)
• ✅ Detailed trade reasons in logs
• ✅ Unrealized P/L tracking for open positions
• ✅ Advanced performance metrics (Sharpe, Drawdown, Profit Factor)

3. Code Quality

• ✅ Comprehensive error handling with try-catch blocks
• ✅ Configuration validation
• ✅ Unified TradingEngine class (DRY principle)
• ✅ Better data validation
• ✅ Improved random number generation for live simulation

4. User Experience

• ✅ Detailed progress reporting
• ✅ Clear trade execution logs with reasons
• ✅ Professional summary statistics
• ✅ Better configuration with comments
• ✅ Command-line argument support

📝 Output Examples

Trade Execution

[2024-03-18] SELL executed: 2 shares @ INR 22055.70 | Total: INR 44111.40 | 
P/L: INR 568.00 (1.30%) | Balance: INR 100568.00 | 
Reason: Death Cross detected (MA20=21890.50 < MA50=21920.30, RSI=62.50)

Statistics Summary

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**Disclaimer**: This software is for educational and research purposes only. It should not be used for actual trading without proper testing, risk assessment, and professional financial advice.