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A New Algorithm Based on Copulas for VaR Valuation with Empirical Calculations
Company: Theoretical Computer Science
Company Url: Click here to open
Year Of Publication: 2007
Month Of Publication: June
Resource Link: Click here to open
Pages: 190-197
Download Count: 0
View Count: 1300
Comment Num: 0
Language: English
Source: article
Who Can Read: Free
Date: 10-6-2013
Publisher: Administrator
Summary
This paper concerns the application of copula functions in VaR valuation. The copula function is used to model the dependence structure of multivariate assets. After the introduction of the traditional Monte Carlo simulation method and the pure copula method we present a new algorithm based on mixture copula functions and the dependence measure, Spearman's rho. This new method is used to simulate daily returns of two stock market indices in China, Shanghai Stock Composite Index and Shenzhen Stock Composite Index, and then empirically calculate six risk measures including VaR and conditional VaR. The results are compared with those derived from the traditional Monte Carlo method and the pure copula method. From the comparison we show that the dependence structure between asset returns plays a more important role in valuating risk measures comparing with the form of marginal distributions. ? 2007 Elsevier Ltd. All rights reserved.
(volume 378, number 2)
Author(s)
Li, Ping Sign in to follow this author
Cheng, Gang Sign in to follow this author
Shi, Peng Sign in to follow this author
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