Multivariate Conditional Copula-GARCD-JSU Model and its Application

Abstract:

Generalized autoregressive conditional density model provides a useful tool for simulating the probability density function of financial asset return. It is essential for describing the dynamic character of financial asset return comprehensively. Copula function can be used to combine some marginal distributions together. Based on Copula function, multivariate conditional Copula-GARCD-JSU model, a new model, is proposed in the paper. Fortunately, the famous “dimension disaster” in multivariate GARCD model can be overcome by the new model. Furthermore, the estimation and test method for the model are discussed in detail. In empirical analysis, the new model can not only be applied to describe the dynamic character of individual market, but also to simulate the dynamic relation between them.

• Periodical: Advanced Materials Research (Volumes 452-453)
• Pages: 997-1001
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.452-453.997
• Online since: January 2012
• Authors: Cui Xia Jiang, Qi Fa Xu, Shi Ying Zhang
• Keywords: Conditional Copula Function, GARCD Model, JSU Distribution

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