Journal
QUANTITATIVE FINANCE
Volume 9, Issue 7, Pages 869-885Publisher
ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/14697680902852746
Keywords
Portfolio selection; Downside risk; Lower-partial moment; Robust optimization
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Funding
- National Science Foundation of China [70401009, 70518001]
- Research Grants Council, Hong Kong [N_CUHK445/05]
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We investigate a robust version of the portfolio selection problem under a risk measure based on the lower-partial moment (LPM), where uncertainty exists in the underlying distribution. We demonstrate that the problem formulations for robust portfolio selection based on the worst-case LPMs of degree 0, 1 and 2 under various structures of uncertainty can be cast as mathematically tractable optimization problems, such as linear programs, second-order cone programs or semidefinite programs. We perform extensive numerical studies using real market data to reveal important properties of several aspects of robust portfolio selection. We can conclude from our results that robustness does not necessarily imply a conservative policy and is indeed indispensable and valuable in portfolio selection.
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