Backtesting

Backtesting is jargon used in financial industries to refer to testing a trading strategy or predictive model using existing historic data. Backtesting is a special type of cross-validation applied to time series data.

Backtesting seeks to estimate the performance of a strategy if it had been employed during a past period. This requires simulating past conditions with sufficient detail, making one limitation of backtesting the need for detailed historical data. A second limitation is the inability to model strategies that would affect historic prices. Finally, backtesting, like other modeling, is limited by potential overfitting. That is, it is often possible to find a strategy that would have worked well in the past, but will not work well in the future. Despite these limitations, backtesting provides information not available when models and strategies are tested on synthetic data.

Backtesting has historically been performed by large institutions and professional money managers due to the expense of obtaining and using detailed datasets. However, backtrading is increasingly used on a wider basis, and independent web-based backtesting platforms have emerged. Although the technique is widely used, it is prone to weaknesses.^[1]

See also

• Retrodiction
• Forecasting
• Hindcast
• Algorithmic trading
• Program trading
• Statistical arbitrage

References