btester - Trading Strategy Backtesting Framework

btester is a Python framework optimized for running backtests on multiple assets and supports full portfolio backtesting. It provides tools for backtesting trading strategies based on historical market data. The framework includes classes for managing financial positions, completed trades, and a flexible abstract base class for implementing custom trading strategies.

Installation

You can install btester using pip. Simply run the following command:

pip install btester

Usage

1. Define your custom trading strategy by creating a class that inherits from the Strategy abstract class.

2. Implement the required methods in your custom strategy: init for initialization and next for the core strategy logic.

3. Instantiate the Backtest class with your custom strategy, historical market data, and other parameters.

4. Run the backtest using the run method, which returns a Result object containing backtest results.

Example Usage

# Example usage of the btester
from btester import Strategy, Backtest
import pandas as pd

# Define a custom strategy by inheriting from the abstract Strategy class
class MyStrategy(Strategy):
    def init(self):
        # Custom initialization logic for the strategy
        pass

    def next(self, i: int, record: Dict[Hashable, Any]):
        # Custom strategy logic for each time step
        pass

# Load historical market data
data = pd.read_csv('historical_data.csv', parse_dates=['Date'])
data.set_index('Date', inplace=True)

# Initialize and run the backtest
backtest = Backtest(strategy=MyStrategy, data=data, cash=10000, commission=0.01)
result = backtest.run()

# Access backtest results
returns_series = result.returns
completed_trades = result.trades
remaining_positions = result.open_positions

Examples

Check out the examples in the examples directory for additional use cases and demonstrations. The examples cover various scenarios and strategies to help you understand the versatility of the btester.

• Example 1: Multiple Assets Breakout Strategy
• Example 2: Multiple Assets Moving Average Crossover Strategy
• Example 3: Single Asset Breakout Strategy
• Example 4: Single Asset Moving Average Crossover Strategy

Feel free to explore and adapt these examples to suit your specific needs and trading strategies.