A Rank-based Approach to Cross-Sectional Analysis

Abstract : Sharpe-like ratios have been traditionally used to measure the performances of portfolio managers. However, they are known to suffer major drawbacks. Among them, two are intricate : (1) they are relative to a peer's performance and (2) the best score is generally assumed to correspond to a "good" portfolio allocation, with no guarantee on the goodness of this allocation. Last but no least (3) these measures suffer significant estimation errors leading to the inability to distinguish two managers' performances. In this paper, we propose a cross-sectional measure of portfolio performance dealing with these three issues. First, we define the score of a portfolio over a single period as the percentage of investable portfolios outperformed by this portfolio. This score quantifies the goodness of the allocation remedying drawbacks (1) and (2). The new information brought by the cross-sectionality of this score is then discussed through applications. Secondly, we build a performance index, as the average cross-section score over successive periods, whose estimation partially answers drawback (3). In order to assess its informativeness and using empirical data, we compare its forecasts with those of the Sharpe and Sortino ratios. The results show that our measure is the most robust and informative. It validates the utility of such cross-sectional performance measure.
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https://halshs.archives-ouvertes.fr/halshs-00646073
Contributeur : Dominique Guégan <>
Soumis le : mardi 29 novembre 2011 - 10:29:28
Dernière modification le : vendredi 26 juillet 2019 - 11:58:03

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  • HAL Id : halshs-00646073, version 1

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Dominique Guegan, Monica Billio, Ludovic Calès. A Rank-based Approach to Cross-Sectional Analysis. European Journal of Operational Research, Elsevier, 2015, A paraître. ⟨halshs-00646073⟩

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