Back to Search
Start Over
Multivariate Tail Moments for Log-Elliptical Dependence Structures as Measures of Risks
- Source :
- Symmetry, Vol 13, Iss 559, p 559 (2021), Symmetry, Volume 13, Issue 4
- Publication Year :
- 2021
- Publisher :
- MDPI AG, 2021.
-
Abstract
- The class of log-elliptical distributions is well used and studied in risk measurement and actuarial science. The reason is that risks are often skewed and positive when they describe pure risks, i.e., risks in which there is no possibility of profit. In practice, risk managers confront a system of mutually dependent risks, not only one risk. Thus, it is important to measure risks while capturing their dependence structure. In this short paper, we compute the multivariate risk measures, multivariate tail conditional expectation, and multivariate tail covariance measure for the family of log-elliptical distributions, which captures the dependence structure of the risks while focusing on the tail of their distributions, i.e., on extreme loss events. We then study our result and examine special cases, as well as the optimal portfolio selection using such measures. Finally, we show how the given multivariate tail moments can also be computed for log-skew elliptical models based on similar approaches given for the log-elliptical case.
- Subjects :
- Multivariate statistics
tail conditional expectation
Physics and Astronomy (miscellaneous)
log-skew-elliptical distributions
General Mathematics
Short paper
Structure (category theory)
Conditional expectation
01 natural sciences
Measure (mathematics)
010104 statistics & probability
log-elliptical distributions
0502 economics and business
Computer Science (miscellaneous)
Econometrics
multivariate tail covariance
0101 mathematics
Mathematics
050208 finance
lcsh:Mathematics
05 social sciences
Covariance
lcsh:QA1-939
Chemistry (miscellaneous)
Portfolio
multivariate tail conditional expectation
Subjects
Details
- Language :
- English
- ISSN :
- 20738994
- Volume :
- 13
- Issue :
- 559
- Database :
- OpenAIRE
- Journal :
- Symmetry
- Accession number :
- edsair.doi.dedup.....3e8cca15d79b8213dfeb6df70c9df5c7