Skip to content

QUICK_START.md

Latest commit

 

History

History
118 lines (88 loc) · 3.17 KB

QUICK_START.md

File metadata and controls

118 lines (88 loc) · 3.17 KB
Raw

🚀 Quick Start Guide

Getting Started with the Investment Strategy Backtester

Option 1: Web Interface (Recommended for Beginners)

  1. Navigate to the Backtesting directory:

    cd Backtesting

  2. Install dependencies (if not already installed):

    pip install -r requirements.txt

  3. Launch the web interface:

    streamlit run app.py

  4. Open your browser and go to http://localhost:8501

  5. Start backtesting:

    • Choose a strategy from the sidebar
    • Select an asset (stock/ETF)
    • Configure parameters
    • Click "Run Backtest"

Option 2: Command Line Interface (For Advanced Users)

  1. List available strategies:

    python3 cli.py --list-strategies

  2. Run a backtest:

    python3 cli.py --strategy rsi --symbol ^GSPC --start 2020-01-01 --end 2023-01-01

  3. Get help:

    python3 cli.py --help

Option 3: Examples

Run the example script to see the system in action:

python3 -m Backtesting.example

🎯 Available Strategies

1. RSI Strategy

  • Best for: Value investing, contrarian approaches
  • Logic: Invests when RSI is oversold (below threshold)
  • Parameters: RSI period, RSI threshold

2. Moving Average Crossover

  • Best for: Trend following, momentum strategies
  • Logic: Invests when fast MA crosses above slow MA
  • Parameters: Fast period, slow period

3. Bollinger Bands Strategy

  • Best for: Mean reversion, volatility-based strategies
  • Logic: Invests when price touches lower band
  • Parameters: BB period, standard deviation

4. Dollar Cost Averaging

  • Best for: Baseline comparison, conservative investing
  • Logic: Invests fixed amounts at regular intervals
  • Parameters: None (uses investment settings)

📊 Popular Assets

The system includes pre-configured popular assets:

  • ^GSPC: S&P 500 Index
  • SPY: SPDR S&P 500 ETF
  • QQQ: Invesco QQQ Trust
  • AAPL: Apple Inc.
  • MSFT: Microsoft Corporation
  • And many more...

💡 Tips for Beginners

  1. Start with DCA: Use Dollar Cost Averaging as a baseline
  2. Use longer periods: 5+ years for more reliable results
  3. Compare strategies: Test different approaches on the same asset
  4. Focus on metrics: Pay attention to Sharpe ratio and maximum drawdown
  5. Experiment: Try different parameters to see their impact

🔧 Troubleshooting

Common Issues

  1. Import errors: Make sure you're in the Backtesting directory
  2. Missing dependencies: Run pip install -r requirements.txt
  3. Data errors: Some tickers may have limited historical data
  4. Rate limits: Yahoo Finance may limit requests during high traffic

Getting Help

  • Check the main README.md for detailed documentation
  • Look at example.py for usage examples
  • Use the CLI help: python3 cli.py --help

🎉 Success!

Once you see the web interface running, you can:

  • ✅ Choose from 4 different investment strategies
  • ✅ Test on 20+ popular stocks and ETFs
  • ✅ Compare strategy performance
  • ✅ Analyze comprehensive metrics
  • ✅ Learn about different investment approaches

Happy backtesting! 📈