What it shows: the more strategies you try on the same data, the higher the best backtested Sharpe ratio climbs — purely from luck. Each simulated strategy's returns are drawn from a zero-mean normal distribution, so there is no real edge anywhere. The benchmark line is the expected maximum Sharpe under pure chance (Bailey & López de Prado, 2014). It's the intuition behind the backtesting guide and signal validation: a backtest Sharpe is only meaningful once you discount it for how many things you tested.
All returns are synthetic random noise — nothing here is a performance figure or investment advice. Related tools: Information Coefficient Calculator · Signal Decay Calculator.
Run the experiment
Every strategy below has zero real edge — its "returns" are pure random noise. We build many of them, compute each one's in-sample annualized Sharpe ratio, and keep the best — exactly what happens when you grid-search parameters or test many ideas on one dataset.
60 return observations per strategy