Multivariate bilateral gamma, copulas, CoSkews and CoKurtosis

被引:2
|
作者
Madan, Dilip B. [1 ]
Wang, King [2 ]
机构
[1] Univ Maryland, Robert H Smith Sch Business, College Pk, MD 20742 USA
[2] Morgan Stanley, Derivat Prod Strats, 1585 Broadway,5th Floor, New York, NY 10036 USA
关键词
Multivariate variance gamma; tail probabilities; bivariate characteristic function estimation; MODELS;
D O I
10.1142/S2424786321500328
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
Correlation graphs are introduced to delineate the levels observed in data and models for return and squared return correlations. A sample of 2048 representative pairs of equity assets is selected from a possible collection of 381, 501 pairs by quantization. Five copulas are estimated and simulated on these pairs of returns, the Gaussian, t-copula, Clayton, Gumbel and Frank. Additionally, the multivariate bilateral gamma (MBG) model that introduces dependence via common time changes is also fit and simulated. Results of fit statistics on returns, CoSkew and CoKurtosis pairs are reported. The general ordering of the models is MBG, t-copula, followed by the Gaussian, Frank, Gumbel and Clayton copulas.
引用
收藏
页数:20
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