Hands-On Machine Learning for Algorithmic Trading

Strategy backtesting

The incorporation of an investment idea into an algorithmic strategy requires extensive testing with a scientific approach that attempts to reject the idea based on its performance in alternative out-of-sample market scenarios. Testing may involve simulated data to capture scenarios deemed possible but not reflected in historic data.

A strategy-backtesting engine needs to simulate the execution of a strategy realistically to achieve unbiased performance and risk estimates. In addition to the potential biases introduced by the data or a flawed use of statistics, the backtest engine needs to accurately represent the practical aspects of trade-signal evaluation, order placement, and execution in line with market conditions. ...