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Modified Gaussian Pseudo-Copula: Applications in Insurance and Finance
Company: Insurance: Mathematics and Economics
Company Url: Click here to open
Year Of Publication: 2013
Month Of Publication: May
Resource Link: Click here to open
Pages: 10
Download Count: 0
View Count: 1113
Comment Num: 0
Language: English
Source: article
Who Can Read: Free
Date: 6-11-2013
Publisher: Administrator
Summary
The Gaussian copula is by far the most popular copula for modeling the association in finance and insurance risk problems. However, one major drawback of Gaussian copula is that it intrinsically lacks the flexibility of modeling the tail dependence, which real life data often exhibit. In this paper, we present the Modified Gaussian copula, a pseudo-copula model that allows for both tail dependence and elliptical dependence structure. To improve model flexibility, the Gaussian copula is modified such that each correlation coefficient is not only an unknown parameter (to be modeled), but also a function of random variables. We present the characteristics of the Modified Gaussian pseudo-copula, and show that our modification enables the copula to capture the tail dependence adequately. The proposed modified Gaussian pseudo-copula is assessed by estimating the association on a real life insurance data and a finance data set. Furthermore, a comprehensive simulation study comparing goodness-of-fit test statistics is carried out. Both experiment results demonstrate that our Modified Gaussian pseudo-copula fits data (with or without tail de
Author(s)
Fang, Yi Sign in to follow this author
Madsen, Lisa Sign in to follow this author
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