Backtests on model-driven strategies leak more than usual

Evaluating a strategy over a window that falls inside the training corpus of the model driving it produces results that mean very little. Almost every published backtest of this kind has the problem.

Honest evaluation needs a genuine holdout after the training cutoff, which limits you to short windows and modest claims.