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hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorBenhamou, Éric
hal.structure.identifier
dc.contributor.authorSaltiel, David
hal.structure.identifier
dc.contributor.authorGuez, Beatrice
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dc.contributor.authorParis, Nicolas
HAL ID: 8249
ORCID: 0000-0002-7155-9261
dc.date.accessioned2020-11-12T10:48:26Z
dc.date.available2020-11-12T10:48:26Z
dc.date.issued2020
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/21203
dc.language.isoenen
dc.subjectSharpe ratioen
dc.subjectStudent distributionen
dc.subjectcompounding effect on Sharpeen
dc.subjectWald testen
dc.subjectT-testen
dc.subjectChi square testen
dc.subject.ddc332en
dc.subject.classificationjelC.C1.C12en
dc.subject.classificationjelG.G1.G11en
dc.titleTesting Sharpe ratio: luck or skill ?en
dc.typeDocument de travail / Working paper
dc.description.abstractenSharpe ratio (sometimes also referred to as information ratio) is widely used in asset management to compare and benchmark funds and asset managers. It computes the ratio of the (excess) net return over the strategy standard deviation. However, the elements to compute the Sharpe ratio, namely, the expected returns and the volatilities are unknown numbers and need to be estimated statistically. This means that the Sharpe ratio used by funds is likely to be error prone because of statistical estimation errors. In this paper, we provide various tests to measure the quality of the Sharpe ratios. By quality, we are aiming at measuring whether a manager was indeed lucky of skillful. The test assesses this through the statistical significance of the Sharpe ratio. We not only look at the traditional Sharpe ratio but also compute a modified Sharpe insensitive to used Capital. We provide various statistical tests that can be used to precisely quantify the fact that the Sharpe is statistically significant. We illustrate in particular the number of trades for a given Sharpe level that provides statistical significance as well as the impact of auto-correlation by providing reference tables that provides the minimum required Sharpe ratio for a given time period and correlation. We also provide for a Sharpe ratio of 0.5, 1.0, 1.5 and 2.0 the skill percentage given the auto-correlation level.en
dc.publisher.cityParisen
dc.relation.ispartofseriestitlePreprint Lamsadeen
dc.identifier.urlsitehttps://hal.archives-ouvertes.fr/hal-02886500en
dc.subject.ddclabelEconomie financièreen
dc.description.ssrncandidatenonen
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.date.updated2020-11-12T10:36:05Z
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