Backtrader Alerts System

A proof of concept that integrates the backtrader library with a modern web frontend. The goal was to build an intuitive UI with Streamlit and Plotly that puts trading tools—including backtesting, live alerts, and market data visualization—into a single, web application.

Features

• Multiple Data Sources: Support for Yahoo Finance (stocks/crypto) and Binance (crypto)
• All Backtrader Indicators: Support for 30+ indicators including RSI, CCI, Bollinger Bands, MACD, SMA, EMA, and more
• Multi-Timeframe Analysis: Analyze multiple timeframes simultaneously (5m, 15m, 30m, 1h, 2h, 4h, 1d)
• Flexible Strategies:
  • Simple Indicator Strategy: Single indicator with customizable entry/exit conditions
  • RSI Crossover Strategy: Classic oversold/overbought strategy
  • Multi-Indicator Strategy: Combine multiple indicators with complex conditions
  • Multi-Timeframe Strategy: Cross-timeframe analysis and alerts
• Telegram Alerts: Real-time trade notifications via Telegram
• Streamlit GUI: Interactive web interface for backtesting and analysis
• CLI Support: Command-line interface for automated workflows
• Comprehensive Results: Detailed trade history, performance metrics, and visualizations

Installation

1. Clone the repository:

git clone https://github.com/yourusername/backtraderalerts.git
cd backtraderalerts

2. Install dependencies:

pip install -r requirements.txt

3. Configure settings (optional):

cp config/config.yaml.example config/config.yaml
# Edit config/config.yaml with your settings

Quick Start

GUI Mode (Recommended)

Launch the Streamlit interface:

python main.py --mode gui

Or directly:

streamlit run src/gui/streamlit_app.py

CLI Mode

Run a backtest from the command line:

python main.py --mode backtest --symbol BTC-USD --interval 1d --start-date 2023-01-01

Configuration

Telegram Setup

1. Create a Telegram bot:

   • Message @BotFather on Telegram
   • Use /newbot command
   • Save the bot token

2. Get your chat ID:

   • Message your bot
   • Visit: https://api.telegram.org/bot<YOUR_BOT_TOKEN>/getUpdates
   • Find your chat ID in the response

3. Add to configuration:

   • In GUI: Enter in the sidebar
   • In config file: Update telegram section

Available Indicators

The system supports all major Backtrader indicators organized by category:

Momentum Indicators:

• RSI, CCI, Stochastic, Williams %R, ROC

Trend Indicators:

• SMA, EMA, WMA, DEMA, TEMA, ADX, MACD, Ichimoku

Volatility Indicators:

• Bollinger Bands, ATR, Standard Deviation, Keltner Channel, Donchian Channel

Volume Indicators:

• OBV, A/D, MFI, Chaikin Money Flow

Other Indicators:

• Parabolic SAR, Pivot Points, ZigZag

Strategy Types

1. Simple Indicator Strategy: Use any single indicator with customizable entry/exit rules
2. RSI Crossover Strategy: Classic RSI oversold/overbought strategy
3. Multi-Indicator Strategy: Combine multiple indicators with complex conditions (AND/OR logic, crossovers)
4. Multi-Timeframe Strategy: Analyze multiple timeframes simultaneously with conditions like:
   • "Buy when 1h close > SMA(200) AND 4h RSI < 30"
   • "Sell when daily close crosses below EMA(50)"
   • "Alert when 4h price crosses above $50,000"

Project Structure

backtraderalerts/
├── src/
│   ├── data/            # Data fetching modules
│   ├── strategies/      # Trading strategies
│   ├── alerts/          # Alert dispatchers
│   ├── engine/          # Backtrader engine
│   ├── gui/             # Streamlit interface
│   └── config/          # Configuration management
├── config/              # Configuration files
├── logs/                # Log files
├── main.py              # Main entry point
├── requirements.txt     # Python dependencies
└── README.md            # This file

Usage Examples

GUI Workflow

1. Configure Settings:

   • Open sidebar
   • Enter Telegram credentials (optional)
   • Set trading parameters

2. Run Backtest:

   • Select symbol and date range
   • Configure strategy parameters
   • Click "Run Backtest"

3. Analyze Results:

   • View portfolio performance chart
   • Check buy/sell signals on price chart
   • Review trade history table
   • Download results as CSV

CLI Examples

Basic backtest:

python main.py --mode backtest --symbol AAPL --interval 1d

With custom parameters:

python main.py --mode backtest \
    --symbol BTC-USD \
    --interval 4h \
    --start-date 2023-06-01 \
    --end-date 2023-12-31 \
    --rsi-period 21 \
    --rsi-oversold 25 \
    --rsi-overbought 75

Using config file:

python main.py --mode backtest --config my_config.yaml --symbol ETH-USD

Extending the System

Adding New Strategies

1. Create a new file in src/strategies/
2. Inherit from backtrader.Strategy
3. Implement __init__, next, and optional logging methods
4. Update GUI to include new strategy option

Example:

class MyStrategy(bt.Strategy):
    params = (
        ('param1', 10),
        ('param2', 20),
    )
    
    def __init__(self):
        # Initialize indicators
        pass
    
    def next(self):
        # Trading logic
        pass

Adding New Data Sources

1. Update DataFetcher class in src/data/fetcher.py
2. Add new source to fetch_data method
3. Update configuration options

Troubleshooting

Common Issues

1. "No module named 'backtrader'"

   • Run: pip install -r requirements.txt

2. Telegram alerts not working

   • Verify bot token and chat ID
   • Check internet connection
   • Ensure bot has messaged you first

3. Data fetch errors

   • Check symbol format (e.g., BTC-USD for Yahoo Finance)
   • Verify date range is valid
   • Check internet connection

## Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Acknowledgments

- [Backtrader](https://www.backtrader.com/) - Python backtesting library
- [Streamlit](https://streamlit.io/) - Web app framework
- [yfinance](https://github.com/ranaroussi/yfinance) - Yahoo Finance data
- [python-telegram-bot](https://python-telegram-bot.org/) - Telegram bot API