Journal article
Properties and calculation of multivariate risk measures: MVaR and MCVaR
Annals of operations research, v 211(1), pp 225-254
01 Dec 2013
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
A recent paper by Pr,kopa (Ann. Oper. Res. 193(1):49-69, 2012) presented results in connection with Multivariate Value-at-Risk (MVaR) that has been known for some time under the name of p-quantile or p-Level Efficient Point (pLEP) and introduced a new multivariate risk measure, called Multivariate Conditional Value-at-Risk (MCVaR). The purpose of this paper is to further develop the theory and methodology of MVaR and MCVaR. This includes new methods to numerically calculate MCVaR, for both continuous and discrete distributions. Numerical examples with recent financial market data are presented.
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Details
- Title
- Properties and calculation of multivariate risk measures: MVaR and MCVaR
- Creators
- Jinwook Lee - Rutgers, The State University of New JerseyAndras Prekopa - Rutgers, The State University of New Jersey
- Publication Details
- Annals of operations research, v 211(1), pp 225-254
- Publisher
- Springer Nature
- Number of pages
- 30
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:000328197900013
- Scopus ID
- 2-s2.0-84890022836
- Other Identifier
- 991021879750304721
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- Web of Science research areas
- Operations Research & Management Science