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Change analysis of a dynamic copula for measuring dependence in multivariate financial data

Content Provider	Scilit
Author	Guégan, D. Zhang, J.
Copyright Year	2010
Description	Journal: Quantitative Finance This paper proposes a new approach to measure dependencies in multivariate financial data. Data in finance and insurance often cover a long time period. Therefore, the economic factors may induce some changes within the dependence structure. Recently, two methods have been proposed using copulas to analyse such changes. The first approach investigates changes within the parameters of the copula. The second determines the sequence of copulas using moving windows. In this paper we take into account the non-stationarity of the data and analyse the impact of (1) time-varying parameters for a copula family, and (2) the sequence of copulas, on the computations of the VaR and ES measures. We propose tests based on conditional copulas and the goodness-of-fit to decide the type of change, and further give the corresponding change analysis. We illustrate our approach using the Standard & Poor 500 and Nasdaq indices in order to compute risk measures using the two previous methods.
Related Links	https://halshs.archives-ouvertes.fr/halshs-00368334/file/guegan-_zhang_QF09.pdf
Ending Page	430
Page Count	10
Starting Page	421
ISSN	14697688
e-ISSN	14697696
DOI	10.1080/14697680902933041
Journal	Quantitative Finance
Issue Number	4
Volume Number	10
Language	English
Publisher	Informa UK Limited
Publisher Date	2010-04-01
Access Restriction	Open
Subject Keyword	Journal: Quantitative Finance Applied Mathematics Statistics and Probability Financial Markets Mathematical Models Statistical Methods Stochastic Processes Risk Management Financial Time Series Extreme Value Theory Extreme Risk and Insurance
Content Type	Text
Subject	Finance

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