Trading Strategy Backtesting Framework

A comprehensive Python framework for backtesting various trading strategies using historical market data. Built with the backtesting library and featuring a command-line interface for easy strategy testing and parameter optimization.

Features

• 🔄 Multiple built-in trading strategies (SMA, RSI, MACD, FVG, ChatGPT)
• 📊 Interactive plots and performance metrics
• ⚙️ Parameter optimization capabilities
• 🎯 Flexible data loading (symbols, date ranges, intervals)
• 🖥️ Command-line interface for easy execution
• 📈 Support for stocks, ETFs, and cryptocurrencies via Yahoo Finance

Setup

1. Create and activate virtual environment

python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

2. Install dependencies

pip install -r requirements.txt

3. (Optional) Set up OpenAI API for ChatGPT strategy

export OPENAI_API_KEY='your-api-key-here'

Quick Start

List available strategies

python src/main.py --list-strategies

Run a basic backtest

python src/main.py --strategy sma --symbol AAPL --period 1y

Custom parameters example

python src/main.py --strategy rsi --symbol TSLA --period 6mo --rsi-period 21 --rsi-overbought 75

Available Strategies

Strategy	Key	Description
Simple Moving Average	sma, smacross	Classic SMA crossover strategy
RSI	rsi	Relative Strength Index overbought/oversold
SMA + MACD	smamacd, sma_macd	Combined SMA and MACD signals
Fair Value Gap	fvg, fairvaluegap	Price gap trading strategy
ChatGPT	chatgpt	AI-powered trading decisions (requires OpenAI API)

Command Line Arguments

Basic Usage

python src/main.py --strategy STRATEGY --symbol SYMBOL [OPTIONS]

Core Arguments

Argument	Description	Example
--strategy, -s	Strategy to use	--strategy sma
--symbol	Stock/crypto symbol	--symbol AAPL
--list-strategies	Show all available strategies

Data Parameters

Argument	Description	Example
--period	Time period	--period 1y, --period 6mo
--interval	Data interval	--interval 1d, --interval 1h
--start	Start date (YYYY-MM-DD)	--start 2023-01-01
--end	End date (YYYY-MM-DD)	--end 2023-12-31

Backtest Parameters

Argument	Description	Default	Example
--cash	Initial cash amount	100000	--cash 50000
--commission	Commission rate	0.002 (0.2%)	--commission 0.001
--exclusive-orders	Use exclusive orders	True

Analysis Options

Argument	Description	Example
--optimize	Run parameter optimization (strategy-specific)	--optimize
--plot	Show backtest plot (default)	--plot
--no-plot	Disable plotting	--no-plot
--plot-volume	Include volume in plots	--plot-volume

Strategy-Specific Parameters

SMA Strategy

Argument	Description	Default
--n1	Short period	10
--n2	Long period	20

RSI Strategy

Argument	Description	Default
--rsi-period	RSI calculation period	14
--rsi-overbought	Overbought threshold	70
--rsi-oversold	Oversold threshold	30

SMA MACD Strategy

Argument	Description	Default
--sma-period	SMA period	10
--macd-fast	MACD fast period	12
--macd-slow	MACD slow period	26
--macd-signal	MACD signal period	9

Usage Examples

Basic Examples

# Simple SMA strategy on Apple stock
python src/main.py --strategy sma --symbol AAPL

# RSI strategy on Tesla with custom parameters
python src/main.py --strategy rsi --symbol TSLA --rsi-period 21 --rsi-overbought 75

# Bitcoin trading with FVG strategy
python src/main.py --strategy fvg --symbol BTC-USD --period 1y

Advanced Examples

# Optimize strategy parameters (each strategy defines its own optimization ranges)
python src/main.py --strategy sma --symbol SPY --period 2y --optimize
python src/main.py --strategy rsi --symbol AAPL --period 1y --optimize
python src/main.py --strategy fvg --symbol BTC-USD --period 6mo --optimize

# High-frequency trading simulation
python src/main.py --strategy sma --symbol AAPL --period 5d --interval 5m --cash 10000

# Custom date range with specific commission
python src/main.py --strategy rsi --symbol MSFT --start 2023-01-01 --end 2023-12-31 --commission 0.001

# Multiple parameter customization
python src/main.py --strategy smamacd --symbol QQQ --period 1y --sma-period 20 --macd-fast 10 --macd-slow 30

ChatGPT Strategy (Requires OpenAI API)

# Set API key first
export OPENAI_API_KEY='your-api-key-here'

# Run ChatGPT strategy
python src/main.py --strategy chatgpt --symbol AAPL --period 3mo

# Bitcoin example with higher cash for expensive asset
python src/main.py --strategy chatgpt --symbol BTC-USD --start 2024-01-01 --cash 1000000

Performance Metrics

The framework provides comprehensive performance metrics including:

• Returns: Strategy vs Buy & Hold comparison
• Risk Metrics: Sharpe Ratio, Sortino Ratio, Maximum Drawdown
• Trade Analysis: Win Rate, Average Trade, Profit Factor
• Timing: Exposure Time, Trade Duration
• Visualization: Equity curves, drawdown plots, trade markers

Adding Custom Strategies

1. Create your strategy file in src/strategies/
2. Inherit from backtesting.Strategy
3. Add import and registry entry in src/strategies/__init__.py
4. (Optional) Add CLI parameters in src/main.py

Example:

# src/strategies/my_strategy.py
from backtesting import Strategy

class MyStrategy(Strategy):
    param1 = 10
    
    def init(self):
        # Initialize indicators
        pass
    
    def next(self):
        # Trading logic
        pass

Troubleshooting

Common Issues

1. "Module not found" errors: Ensure virtual environment is activated
2. "No data loaded": Check symbol name and date ranges
3. ChatGPT API errors: Verify API key is set and has credits
4. Plot not showing: Use --plot flag or check display settings

Getting Help

python src/main.py --help

Dependencies

• backtesting - Core backtesting engine
• yfinance - Market data provider
• pandas - Data manipulation
• numpy - Numerical computing
• talib - Technical analysis (for MACD strategy)
• openai - ChatGPT integration (optional)

License

Open source - feel free to modify and extend for your trading research!