Portfolio optimization with a copula-based extension of conditional value-at-risk
Adam Artur Krzemienowski , Sylwia Szymczyk
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.Author | |||||
Journal series | Annals of Operations Research, ISSN 0254-5330, (A 30 pkt) | ||||
Issue year | 2016 | ||||
Vol | 237 | ||||
No | 1 | ||||
Pages | 219-236 | ||||
Publication size in sheets | 0.85 | ||||
Keywords in English | Multivariate risk measures Quantile risk measures Portfolio optimization Column generation algorithm | ||||
ASJC Classification | ; | ||||
DOI | DOI:10.1007/s10479-014-1625-3 | ||||
URL | http://link.springer.com/article/10.1007%2Fs10479-014-1625-3 | ||||
Project | The 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 | ||||
Language | en angielski | ||||
License | Journal (articles only); author's original; ; after publication | ||||
File |
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Score (nominal) | 30 | ||||
Score | = 30.0, 12-05-2019, ArticleFromJournal = 30.0, 12-05-2019, ArticleFromJournal | ||||
Publication indicators | = 8; : 2016 = 1.287; : 2016 = 1.709 (2) - 2016=1.918 (5) | ||||
Citation count* | 14 (2019-11-18) |
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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