Backtrader Framework

🔥 Vibe Prompt

"Create a Backtrader strategy with Golden Cross, add commission and slippage, run optimization on MA periods, and output performance metrics."

Basic Backtrader Strategy

import backtrader as bt
import yfinance as yf
import pandas as pd

class GoldenCrossStrategy(bt.Strategy):
    params = (('short_period', 5), ('long_period', 20))
    
    def __init__(self):
        self.short_ma = bt.indicators.SMA(self.data.close, period=self.params.short_period)
        self.long_ma = bt.indicators.SMA(self.data.close, period=self.params.long_period)
        self.crossover = bt.indicators.CrossOver(self.short_ma, self.long_ma)
    
    def next(self):
        if self.crossover > 0:  # Golden Cross
            self.buy()
        elif self.crossover < 0:  # Death Cross
            self.sell()

# Download data
df = yf.download('2330.TW', start='2023-01-01', end='2024-12-31')
data = bt.feeds.PandasData(dataname=df)

# Run backtest
cerebro = bt.Cerebro()
cerebro.adddata(data)
cerebro.addstrategy(GoldenCrossStrategy)
cerebro.broker.setcash(1000000.0)
cerebro.broker.setcommission(commission=0.001)

print(f'Starting Portfolio Value: ${cerebro.broker.getvalue():.2f}')
cerebro.run()
print(f'Final Portfolio Value: ${cerebro.broker.getvalue():.2f}')

cerebro.plot()

Performance Metrics

import backtrader.analyzers as btanalyzers

cerebro.addanalyzer(btanalyzers.SharpeRatio, riskfreerate=0.02)
cerebro.addanalyzer(btanalyzers.DrawDown)
cerebro.addanalyzer(btanalyzers.Returns)

results = cerebro.run()
strat = results[0]

print(f"Sharpe Ratio: {strat.analyzers.sharperatio.get_analysis()['sharperatio']:.2f}")
print(f"Max Drawdown: {strat.analyzers.drawdown.get_analysis()['max']['drawdown']:.2f}%")

Parameter Optimization

cerebro.optstrategy(GoldenCrossStrategy, short_period=range(5, 30, 5), long_period=range(20, 60, 10))

optimized_results = cerebro.run()
for result in optimized_results:
    params = result[0].params
    sharpe = result[0].analyzers.sharperatio.get_analysis().get('sharperatio', 0)
    print(f"MA({params.short_period},{params.long_period}) Sharpe: {sharpe:.2f}")

Practice Exercise

💡 Vibe Practice: Extend the backtest with multiple stocks, add stop-loss, take-profit, and compare optimized parameter sets.

Chapter Summary

• Understand core concepts and principles
• Master implementation methods and techniques
• Familiar with common issues and solutions
• Able to apply in real projects

Further Reading

• Official documentation and API references
• Open source examples on GitHub
• Technical books and online courses
• Community discussions and tech blogs

Implementation Example

Basic Example

# This section provides a complete implementation example

Steps

1. Setup: Configure development environment
2. Data: Prepare required data
3. Implementation: Build core functionality
4. Testing: Verify correctness
5. Optimization: Improve performance

Common Errors

| Error Type | Cause | Solution | |------------|-------|----------| | Compilation | Syntax | Check code syntax | | Runtime | Environment | Verify dependencies installed | | Logic | Algorithm | Step-by-step debugging | | Performance | Efficiency | Use profilers |

Code Example

import sys

def main():
    print("Hello, World!")

if __name__ == "__main__":
    main()

References

• Official documentation
• API reference
• Open source examples
• Community discussions