Deflated Sharpe Ratio

Reporting the best Sharpe ratio from N trials is misleading. The Deflated Sharpe Ratio corrects for the number of trials, non-normal returns, and sample size to test whether observed performance reflects genuine skill.

The Problem

If you test 100 strategy variants and report the best Sharpe, you are performing selection bias. Under the null of zero skill, the expected maximum Sharpe across N trials grows with sqrt(2 * log(N)), measured in units of the spread of Sharpes across those trials: at 100 trials the best result is about 2.5 spreads above zero before any alpha exists. Without correction, most "discovered" strategies are artifacts that fail out of sample.

The Pattern

WRONG

import numpy as np