Portfolio value-at-risk optimization for asymmetrically distributed asset returns

Joel Weiqiang Goh, Kian Guan Lim, Melvyn Sim and Weina Zhang

European Journal of Operational Research, 2012, vol. 221, issue 2, 397-406

Abstract: We propose a new approach to portfolio optimization by separating asset return distributions into positive and negative half-spaces. The approach minimizes a newly-defined Partitioned Value-at-Risk (PVaR) risk measure by using half-space statistical information. Using simulated data, the PVaR approach always generates better risk-return tradeoffs in the optimal portfolios when compared to traditional Markowitz mean–variance approach. When using real financial data, our approach also outperforms the Markowitz approach in the risk-return tradeoff. Given that the PVaR measure is also a robust risk measure, our new approach can be very useful for optimal portfolio allocations when asset return distributions are asymmetrical.

Keywords: Risk management; Asymmetric distributions; Partitioned value-at-risk; Portfolio optimization; Robust risk measures (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (27)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:221:y:2012:i:2:p:397-406

DOI: 10.1016/j.ejor.2012.03.012

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