Conditionally fitted Sharpe performance with an application to hedge fund rating

Darolles, Serge; Gouriéroux, Christian

doi:10.1016/j.jbankfin.2009.08.025

Cited by 25 publications

(14 citation statements)

References 44 publications

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“…Sharpe [28] extended the work of Markowitz [43] showing a simplified model of the relationships between assets, offering evidence on costs as well as the advantage of using the model for practical applications [45]. In Sharpe's model, returns between the assets are not correlated with each other, but with a single index representing returns of the entire market.…”

Section: Portfolio Selectionmentioning

confidence: 99%

Entropic Data Envelopment Analysis: A Diversification Approach for Portfolio Optimization

Rotela

Rocha

Áquila

et al. 2017

Entropy

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Abstract:Recently, different methods have been proposed for portfolio optimization and decision making on investment issues. This article aims to present a new method for portfolio formation based on Data Envelopment Analysis (DEA) and Entropy function. This new portfolio optimization method applies DEA in association with a model resulting from the insertion of the Entropy function directly into the optimization procedure. First, the DEA model was applied to perform a pre-selection of the assets. Then, assets given as efficient were submitted to the proposed model, resulting from the insertion of the Entropy function into the simplified Sharpe's portfolio optimization model. As a result, an improved asset participation was provided in the portfolio. In the DEA model, several variables were evaluated and a low value of beta was achieved, guaranteeing greater robustness to the portfolio. Entropy function has provided not only greater diversity but also more feasible asset allocation. Additionally, the proposed method has obtained a better portfolio performance, measured by the Sharpe Ratio, in relation to the comparative methods.

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Section: Portfolio Selectionmentioning

confidence: 99%

Entropic Data Envelopment Analysis: A Diversification Approach for Portfolio Optimization

Rotela

Rocha

Áquila

et al. 2017

Entropy

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“…Another major concern is the non-Gaussian nature of stock returns due to dynamic trading strategies (for instance, hedge funds are a case in point: see Darolles and Gourieroux (2010)). Problematic here is the underestimation of risk in performance appraisal.…”

Section: Traditional Performance Measuresmentioning

confidence: 99%

Portfolio performance gauging in discrete time using a Luenberger productivity indicator

Brandouy

Briec

Kerstens

et al. 2010

Journal of Banking & Finance

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a b s t r a c tThis paper proposes a pragmatic, discrete time indicator to gauge the performance of portfolios over time.Integrating the shortage function (Luenberger, 1995) into a Luenberger portfolio productivity indicator (Chambers, 2002), this study estimates the changes in the relative positions of portfolios with respect to the traditional Markowitz mean-variance efficient frontier, as well as the eventual shifts of this frontier over time. Based on the analysis of local changes relative to these mean-variance and higher moment (in casu, mean-variance-skewness and mean-variance-skewness-kurtosis) frontiers, this methodology allows to neatly separate between on the one hand performance changes due to portfolio strategies and on the other hand performance changes due to the market evolution. This methodology is empirically illustrated using a mimicking portfolio approach French, 1996, 1997) using US monthly data from

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“…ii) Second, one can consider conditional performance measures instead of unconditional measures [see e.g. Darolles and Gourieroux (2008) for conditional Sharpe performances and Gourieroux and Jasiak (2008) for the definition of conditional L-Moments]. These extensions are clearly out of the scope of the present paper.…”

Section: Estimation Of L-performancementioning

confidence: 99%

L-performance with an application to hedge funds

Darolles

Gouriéroux

Jasiak

2009

Journal of Empirical Finance

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International audienceThis paper introduces a new parametric fund performance measure, called the L-performance. The L-performance is an alternative to the Sharpe performance, which is commonly used in practice despite its inability to account for skewness and heavy tails of unconditional return distributions. The L-performance improves upon the Sharpe measure in this respect. Technically, it resembles the Sharpe measure in that it is defined as a ratio of the first- and second-order moments, which are the trimmed L-moments instead of the conventional (power) moments. The trimming parameters allow for focusing the L-performance on specific risk levels of interest, according to financial risk criteria. For illustration, a set of L-performances is computed for a variety of hedge funds. The empirical study shows the use of L-performance for fund ranking and return smoothing (manipulation) control

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Conditionally fitted Sharpe performance with an application to hedge fund rating

Cited by 25 publications

References 44 publications

Entropic Data Envelopment Analysis: A Diversification Approach for Portfolio Optimization

Entropic Data Envelopment Analysis: A Diversification Approach for Portfolio Optimization

Portfolio performance gauging in discrete time using a Luenberger productivity indicator

L-performance with an application to hedge funds

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