Portfolio optimization with a copula-based extension of conditional value-at-risk

Adam Krzemienowski () and Sylwia Szymczyk

Annals of Operations Research, 2016, vol. 237, issue 1, 219-236

Abstract: The paper presents a copula-based extension of Conditional Value-at-Risk and its application to portfolio optimization. Copula-based conditional value-at-risk (CCVaR) is a scalar risk measure for multivariate risks modeled by multivariate random variables. It is assumed that the univariate risk components are perfect substitutes, i.e., they are expressed in the same units. CCVaR is a quantile risk measure that allows one to emphasize the consequences of more pessimistic scenarios. By changing the level of a quantile, the measure permits to parameterize prudent attitudes toward risk ranging from the extreme risk aversion to the risk neutrality. In terms of definition, CCVaR is slightly different from popular and well-researched CVaR. Nevertheless, this small difference allows one to efficiently solve CCVaR portfolio optimization problems based on the full information carried by a multivariate random variable by employing column generation algorithm. Copyright The Author(s) 2016

Keywords: Multivariate risk measures; Quantile risk measures; Portfolio optimization; Column generation algorithm (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (16)

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DOI: 10.1007/s10479-014-1625-3

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