Title
Multidimensional Portfolio Risk Measurement: A Mixed Copula Approach
Abstract
It is an increasingly challenging task to explore the risk measurement for multidimensional portfolios with nonlinear correlative assets. A risk measurement scheme based on the mixed copula theory is proposed in this paper, where the mixed copula is constructed by the linear combination of three single Archimedean copulas, embodying greater flexibility than single copula in connecting different types of marginal distributions. In the scenario, ARMA-EGARCH model with t innovation is employed to fit marginal distributions, and the parameter values of the mixed copulas are inferred by maximum likelihood estimation (MLE) method, and interior point algorithm is used to calculate the extreme values of the MLE, VaR and CVaR, corresponding to the optimal portfolio with the minimum risk. Finally, an empirical study on five international stock market indexes in Europe is performed to verify the feasibility and effectiveness of the scheme.
Year
DOI
Venue
2020
10.1504/IJCSM.2020.111708
INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS
Keywords
DocType
Volume
ARMA-EGARCH, CVaR, mixed copula, risk measurement
Journal
12
Issue
ISSN
Citations 
3
1752-5055
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
wenli cai121.28
Na Liu200.34
Yu-Xuan Wu300.34
Xiang-Dong Liu400.34