Analysis of hedge fund performance

Capocci, Daniel; Hübner, Georges

doi:10.1016/j.jempfin.2002.12.002

Cited by 267 publications

(190 citation statements)

References 69 publications

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“…The results of the applications are compared 11 The CISDM hedge fund database has been subject of many academic studies. For the properties of this database, see, e.g., (Edwards and Caglayan 2001;Kouwenberg 2003;Capocci and Hübner 2004). 12 Altogether we analyzed 450 hedge funds.…”

Section: Data and Proceduresmentioning

confidence: 99%

Performance measurement of hedge funds using data envelopment analysis

Eling

2006

Fin Mkts Portfolio Mgmt

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Data envelopment analysis (DEA) is a nonparametric method from the area of operations research that measures the relationship of produced outputs to assigned inputs and determines an efficiency score. This efficiency score can be interpreted as a performance measure in investment analysis. Recent literature contains intensive discussion of using DEA to measure the performance of hedge funds, as this approach yields some advantages compared to classic performance measures. This paper extends the current discussion in three aspects. First, we present different DEA models and analyze their suitability for hedge fund performance measurement. Second, we systematize possible inputs and outputs for DEA and again examine their suitability for hedge fund performance measurement. Third, two rules are developed to select inputs and outputs in DEA of hedge funds. Using this framework, we find a completely new ranking of hedge funds compared to classic performance measures and compared to previously proposed DEA applications. Thus, we propose that classic performance measures should be supplemented with DEA based on the suggested rules to fully capture hedge fund risk and return characteristics.

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Section: Data and Proceduresmentioning

confidence: 99%

Performance measurement of hedge funds using data envelopment analysis

Eling

2006

Fin Mkts Portfolio Mgmt

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“…A few years later, Capocci and Hubner (2004) examined hedge funds' behaviour from 1984 to 2000 (HFR, MAR) using various asset pricing models. Those included an extended form of Carhart's (1997) model, combined with the Fama and French (1998) and Agarwal and Naik (2000) models plus one more factor that takes into consideration the fact that hedge funds may invest in Emerging Markets.…”

Section: Linear Factor Modelsmentioning

confidence: 99%

“…Sharpe, 1992;Capocci and Hubner, 2004) that examined hedge fund performance under a linear framework. However, linear models are more suitable for traditional mixed funds (investing in equity and bonds).…”

Section: Linear Factor Modelsmentioning

confidence: 99%

Recent advances in explaining hedge fund returns: Implicit factors and exposures

Stafylas

Anderson

Uddin

2017

Global Finance Journal

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We survey articles covering how hedge funds returns are explained, using largely nonlinear multifactor models that examine the non-linear pay-offs and exposures of hedge funds. We provide an integrated view of the implicit factor and statistical factor models that are largely able to explain the hedge fund return-generating process. We present their evolution through time by discussing pioneering studies that made a significant contribution to knowledge, and also recent innovative studies that examine hedge funds exposures using advanced econometric methods. This is the first review that analyzes very recent studies that explain a large part of hedge fund variation. We conclude by presenting some gaps for future research. Recent Advances in Explaining Hedge Fund Returns: Implicit Factors and Exposures AbstractWe survey articles covering how hedge funds returns are explained, using largely nonlinear multifactor models that examine the non-linear pay-offs and exposures of hedge funds. We provide an integrated view of the implicit factor and statistical factor models that are largely able to explain the hedge fund return-generating process. We present their evolution through time by discussing pioneering studies that made a significant contribution to knowledge, and also recent innovative studies that examine hedge funds exposures using advanced econometric methods. This is the first review that analyzes very recent studies that explain a large part of hedge fund variation. We conclude by presenting some gaps for future research.Keywords: hedge fund performance; implicit factors; statistical factors; linear and non-linear multi-factor models; alpha and beta returns 1

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“…We start the implementation with the fourfactor model proposed by Carhart, 32 supposedly achieving better significance levels than the Fama and French 31 specification for hedge fund returns (see Agarwal and Naik and 9 Capocci and Hübner 33 ). This market model is taken as the benchmark of a correctly specified model.…”

Section: Risk Factorsmentioning

confidence: 99%

“…This specification typically achieves significance levels that can easily be improved with style-based indexes. Among them, Capocci and Hübner 33 show that an additional factor accounting for the emerging bond market investment strategy triggers a major shift in the explanatory power of the hedge fund return regressions. Consequently, we choose this particular asset-based index as the fifth independent variable.…”

Section: Risk Factorsmentioning

confidence: 99%

Hedge fund return specification with errors-in-variables

Coën

Hübner²,

Desfleurs³

2010

J Deriv Hedge Funds

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In linear models for hedge fund returns, errors-in-variables may significantly alter the measurement of factor loadings and the estimation of abnormal performance. The higher moment estimator (HME) introduced by Dagenais and Dagenais (1997) effectively deals with these issues. Results on individual funds show that the HME specification does not uncover systematic performance biases, but can modify estimated alphas in most cases and identifies relative persistence for directional funds in bearish market conditions. www.palgrave-journals.com/jdhf/ Overall, the risk premia calculated with HME remain relatively stable when compared to ordinary least squares specifications.

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Analysis of hedge fund performance

Cited by 267 publications

References 69 publications

Performance measurement of hedge funds using data envelopment analysis

Performance measurement of hedge funds using data envelopment analysis

Recent advances in explaining hedge fund returns: Implicit factors and exposures

Hedge fund return specification with errors-in-variables

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