Deflated Sharpe Ratio Calculator

Standard Sharpe ratio assumes returns are i.i.d. Gaussian, which they aren't. Lopez de Prado's deflated Sharpe (2014) corrects for skew, kurtosis, and the multiple-testing penalty when you ran N strategy variants. The deflated value is what would be left after the curve-fitting comes out in the wash.

All of them. The deflation factor depends on the total number of strategy variants tested, including the ones you discarded. Under-reporting trials shrinks the deflation and inflates the apparent Sharpe — that's exactly the bias the metric was designed to catch.

The deflated Sharpe the tool shows is your annualized Sharpe minus the expected maximum Sharpe from N trials — a Sharpe difference, not a z-score, so don't map fixed magnitudes to fixed confidences (that mapping depends on sample size). A positive value means your Sharpe beats what pure selection would produce. For the confidence read, use PSR (probability of skill), which the tool also reports: PSR ≥ 0.95 is the common publication bar.

Yes. A negative DSR means the deflation correction is so large that the strategy's Sharpe is statistically indistinguishable from zero, or worse, from a draw of pure random noise. Negative DSR is common when the trial count is high (50+) and the raw Sharpe is modest.

Be cautious below 100 observations. The deflation formula incorporates higher moments (skew, kurtosis), which need decent sample size to estimate well. This calculator takes skew and kurtosis as inputs you set — it does not estimate them from a trade log, so estimate them on at least 100 observations before trusting DSR, or use the Backtest Overfitting Score, which computes moments from an uploaded returns CSV.