Dynamic hedge fund portfolio construction: A semi-parametric approach

Richard Harris and Murat Mazibaş

Journal of Banking & Finance, 2013, vol. 37, issue 1, 139-149

Abstract: In this article, we evaluate alternative optimization frameworks for constructing portfolios of hedge funds. We compare the standard mean–variance optimization model with models based on CVaR, CDaR and Omega, for both conservative and aggressive hedge fund investment strategies. In order to implement the CVaR, CDaR and Omega optimization models, we propose a semi-parametric methodology, which is based on extreme value theory, copula and Monte Carlo simulation. We compare the semi-parametric approach with the standard, non-parametric approach, used to compute CVaR, CDaR and Omega, and the benchmark parametric approach, based on both static and dynamic mean–variance optimization. We report two main findings. The first is that the CVaR, CDaR and Omega models offer a significant improvement in terms of risk-adjusted portfolio performance over the parametric mean–variance model. The second is that semi-parametric estimation of the CVaR, CDaR and Omega models offers a very substantial improvement over non-parametric estimation. Our results are robust to the choice of target return, risk limit and estimation sample size.

Keywords: Funds of hedge funds; Portfolio optimization; Copula; Extreme value theory; Monte Carlo simulation (search for similar items in EconPapers)
JEL-codes: C14 C15 C61 G11 G12 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:37:y:2013:i:1:p:139-149

DOI: 10.1016/j.jbankfin.2012.08.017

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