Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 221, Issue 2, Pages 397-406Publisher
ELSEVIER
DOI: 10.1016/j.ejor.2012.03.012
Keywords
Risk management; Asymmetric distributions; Partitioned value-at-risk; Portfolio optimization; Robust risk measures
Funding
- Singapore-MIT Alliance
- NUS [R-314-000-068-122]
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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. (C) 2012 Elsevier B.V. All rights reserved.
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