The total duration of drawdowns is shown to be an efficient and robust estimator of Sharpe ratios , especially for heavy-tailed price returns. Because such type of data mechanically reduces the expected total drawdown duration with respect to Gaussian price returns , moment-based estimators are prone to overestimate true Sharpe ratios in leptokurtic market conditions and may further amplify large price returns when they are used by trend-followers .
The total duration of drawdowns is shown to be an efficient and robust estimator of Sharpe ratios . Its properties are distribution-dependent: the expected total drawdown duration is smaller for heavy-tailed returns than for Gaussian ones. As a consequence, in leptokurtic market conditions , the new estimator yields smaller Sharpe ratios than moment-based estimators, which implies that the standard estimator overestimates the information content of prices when the return distribution has heavy tails. Accordingly, using the standard estimator for taking trend-following decisions enhances large price fluctuations .
R
, especially for heavy-tailed price returns. Because such type of data mechanically reduces
. Its properties are distribution-dependent:
R
with respect to Gaussian price returns , moment-based estimators are prone to overestimate true Sharpe ratios
is smaller for heavy-tailed returns than for Gaussian ones. As a consequence,
R
and may further amplify large price returns when they are used by trend-followers
, the new estimator yields smaller Sharpe ratios than moment-based estimators, which implies that the standard estimator overestimates the information content of prices when the return distribution has heavy tails. Accordingly, using the standard estimator for taking trend-following decisions enhances large price fluctuations