Backtrader Event-Driven: Simulating Slippage
What if your trading strategy looks profitable in a backtest but fails immediately once you go live? This gap often stems from ignoring backtrader's abi...
What if your trading strategy looks profitable in a backtest but fails immediately once you go live? This gap often stems from ignoring backtrader's ability to simulate real-world execution friction like slippage and latency. Slippage is the difference between the expected price of a trade and the actual price at which it executes. It occurs due to market volatility, liquidity gaps, or order book depth. Latency simulation is the modeling of time delays between signal generation and order execution. Together, these factors define the realism of an event-driven backtest. Without these models, your backtest assumes perfect fills at exact prices, creating a false sense of security. In practice, even a 0.1% slippage can turn a winning strategy into a losing one over hundreds of trades. Event-driven simulation processes market data chronologically, handling one tick or bar at a time to mimic real-time trading. Unlike vectorized backtesters that calculate results in bulk, this approach respects the sequence of events. Backtrader is a pure Python event-driven framework that iterates through each timestep. It processes strategy logic, orders, and portfolio updates sequentially.