Quantifying Backtest Overfitting in Alternative Beta Strategies

Avoiding Backtesting Overfitting by Covariance-Penalties: An Empirical Investigation of the Ordinary and Total Least Squares Cases

“…Our results suggest that Covariance-Penalties are a suitable procedure to avoid Backtesting Overfitting, and Total Least Squares provides superior performance when compared to Ordinary Least Squares.We can outline, chronologically, three distinct approaches in the literature to evaluate and deal with backtesting overfitting: Data Snooping, Overestimated Performance, and Cross-Validation Evaluation. The problem of overfitting cannot be understated, and innumerable references highlight the issues with phacking which has been an issue for considerable periods but making headlines more recently (see e.g., [35], [26], [7], [13]), and [24]) although it may not always be willful ([16]), and is pernicious in finance (see for instance, [44]).…”