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Sonderforschungsbereich 386: Statistische Analyse diskreter Strukturen, Universität München (LMU) >
Discussion papers, SFB 386, LMU München >
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http://hdl.handle.net/10419/31135
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| Title: | | Copula structure analysis based on robust and extreme dependence measures  |
| Authors: | | Klüppelberg, Claudia Kuhn, Gabriel |
| Issue Date: | | 2006 |
| Series/Report no.: | | Discussion paper // Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München 507 |
| Abstract: | | In this paper we extend the standard approach of correlation structure analysis in order to reduce the dimension of highdimensional statistical data. The classical assumption of a linear model for the distribution of a random vector is replaced by the weaker assumption of a model for the copula. For elliptical copulae a 'correlation-like' structure remains but different margins and non-existence of moments are possible. Moreover, elliptical copulae allow also for a 'copula structure analysis' of dependence in extremes. After introducing the new concepts and deriving some theoretical results we observe in a simulation study the performance of the estimators: the theoretical asymptotic behavior of the statistics can be observed even for a sample of only 100 observations. Finally, we test our method on real financial data and explain differences between our copula based approach and the classical approach. Our new method yields a considerable dimension reduction also in non-linear models. |
| Subjects: | | copula structure analysis correlation structure analysis covariance structure analysis dimension reduction elliptical copula factor analysis Kendall's tau tail copula tail dependence |
| Persistent Identifier of the first edition: | | urn:nbn:de:bvb:19-epub-1871-2 |
| Document Type: | | Working Paper |
| Appears in Collections: | | Discussion papers, SFB 386, LMU München
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