Use Cross-Validation to Reduce Backtest Parameter Selection Bias

Summary

The document considers how to select strategy parameters after ranking many combinations on an in-sample period and then checking the strongest performers on an out-of-sample period. Its answer warns that repeatedly selecting the top-performing percentage can introduce sampling bias, especially when many parameter settings have similar results. Ranking the same candidates across successive periods does not by itself remove that selection effect.

The suggested approach is to use traditional cross-validation within the training data: randomly select samples for calibration and validation, then evaluate the calibrated parameters on a separate out-of-sample period. The response characterizes top-percent selection as poorly stratified, but does not specify a cross-validation scheme, how to handle time dependence in financial data, or how to choose among parameters after validation. It is brief guidance rather than a full walk-forward protocol or an empirical comparison of selection methods.

Key ideas

• Repeatedly selecting the best-ranked parameter percentage can create sampling bias.
• Use cross-validation within the training data to calibrate and validate candidate parameters.
• Reserve a separate out-of-sample period for evaluation after parameter calibration.
• The answer does not detail a time-series-specific validation design or a final parameter selection rule.

Tags

# Is there an equation that gives you the optimal spread width or strike prices when opening a vertical options spread?


# Is there an equation that gives you the optimal spread width or strike prices when opening a vertical options spread?












On a specific leg, when going to open a spread is there an equation that can tell me at what strike price I should sell at and what strike price I should buy at?

I look at this options calculator website and see if I but at just the right strike price below the current underlying price, and sell at the just the right strike price above the current underlying price I can find a sweet spot where I can usually get some good numbers if I stay above the underlying price at the time I open the position. It's easier to show than explain.

I can't always get predictions like this from all options chains. Sometimes the prices of the options and, I think, the option's volatility seems to effect the type of 'action' you can get on price movements of a spread.

My question again, is there an equation or code in Python that can tell one which are the best two options to, one buy, and second, to sell for the most profit?

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.