skfolio.measures.deflated_sharpe_ratio#

skfolio.measures.deflated_sharpe_ratio(returns, trial_sharpe_ratios, risk_free_rate=0.0)[source]#

Compute the Deflated Sharpe Ratio (DSR).

The DSR estimates the probability that the true Sharpe ratio of a strategy selected as the best of several trials is greater than zero, once the number and dispersion of those trials and the non-normality of the selected returns are accounted for. It is the Probabilistic Sharpe Ratio benchmarked against the expected maximum Sharpe ratio of the search:

\[DSR = PSR\left(SR_0\right)\]

with \(SR_0\) computed by expected_max_sharpe_ratio using trial_sharpe_ratio_mean=0.0. The selected strategy meets a 95% confidence requirement when \(DSR \geq 0.95\).

Parameters:

returnsndarray of shape (n_observations,) or (n_observations, n_assets): Return series of the selected trial. For a 2D-array, each column is assessed against the same benchmark derived from trial_sharpe_ratios.
trial_sharpe_ratiosndarray of shape (n_trials,): Sharpe ratios of every trial evaluated by the search, not only the selected one, since their count and dispersion set the benchmark. They must use the same risk-free rate as returns.
risk_free_ratefloat, default=0.0: Risk-free rate used to compute the excess mean of returns.

Returns:

valuefloat or ndarray of shape (n_assets,): Estimated probability that the true Sharpe ratio of the selected trial is greater than zero after accounting for selection across trials. If returns is a 1D-array, the result is a float. If returns is a 2D-array, the result is a ndarray of shape (n_assets,).

Raises:

ValueError: If trial_sharpe_ratios is not a 1D-array, is empty after dropping NaNs, or contains infinite values.