Backtesting

Backtesting is a term used in modeling to refer to testing a predictive model on historical data. Backtesting is a type of retrodiction, and a special type of cross-validation applied to previous time period(s). In quantitative finance, backtesting is an important step before deploying algorithmic strategies in live markets. == Financial analysis== In economics and finance, backtesting seeks to estimate the performance of a strategy or model if it had been employed during a past period. This requires simulating past conditions with sufficient detail, which means that backtesting is limited by the need for detailed historical data, the inability to model strategies that would affect historic prices, and 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. Historically, backtesting was only performed by large institutions and professional money managers due to the expense of obtaining and using detailed datasets. However, backtesting 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. Basel financial regulations require large financial institutions to backtest certain risk models. For a Value at Risk 1-day at 99% backtested 250 days in a row, the test is considered green (0-95%), orange (95-99.99%) or red (99.99-100%) depending on the following table: For a Value at Risk 10-day at 99% backtested 250 days in a row, the test is considered green (0-95%), orange (95-99.99%) or red (99.99-100%) depending on the following table: ==See also== ==References==

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