Inâsample overfitting is a drawback of any backtestâbased investment strategy. It is thus of paramount importance to have an understanding of why and how the inâsample overfitting occurs. In this article we propose a simple framework that allows one to model and quantify inâsample PnL overfitting. This allows us to compute the factor appropriate for discounting PnLs of inâsample investment strategies.