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

Adam Artur Krzemienowski , Sylwia Szymczyk


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.
Author Adam Artur Krzemienowski IAiIS
Adam Artur Krzemienowski,,
- The Institute of Control and Computation Engineering
, Sylwia Szymczyk IAiIS
Sylwia Szymczyk,,
- The Institute of Control and Computation Engineering
Journal seriesAnnals of Operations Research, ISSN 0254-5330
Issue year2016
Publication size in sheets0.85
Keywords in EnglishMultivariate risk measures Quantile risk measures Portfolio optimization Column generation algorithm
URL http://link.springer.com/article/10.1007%2Fs10479-014-1625-3
projectThe Multivariate Conditional Value-at-Risk as a Measure of Risk. Project leader: Krzemienowski Adam Artur, , Phone: 7640, start date 04-05-2011, end date 03-06-2012, 505/G/1031/0036, Completed
WEiTI Projekty finansowane przez MNiSW
Languageen angielski
Krzemienowski Szymczak AOR16.pdf (file archived - login or check accessibility on faculty) Krzemienowski Szymczak AOR16.pdf 516.06 KB
Score (nominal)30
ScoreMinisterial score = 30.0, 27-03-2017, ArticleFromJournal
Ministerial score (2013-2016) = 30.0, 27-03-2017, ArticleFromJournal
Publication indicators WoS Impact Factor: 2016 = 1.709 (2) - 2016=1.918 (5)
Citation count*8 (2018-02-17)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.