Fast gradient descent method for Mean-CVaR optimization

Garud Iyengar () and Alfred Ma ()

Annals of Operations Research, 2013, vol. 205, issue 1, 203-212

Abstract: We propose an iterative gradient descent algorithm for solving scenario-based Mean-CVaR portfolio selection problem. The algorithm is fast and does not require any LP solver. It also has efficiency advantage over the LP approach for large scenario size. Copyright Springer Science+Business Media New York 2013

Keywords: Conditional value-at-risk; Portfolio optimization (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (11)

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DOI: 10.1007/s10479-012-1245-8

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