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Correlation and Dependence in Risk Management: Properties and Pitfalls
Company: ETH Zurich
Company Url: Click here to open
Year Of Publication: 1999
Month Of Publication: July
Pages: 37
Download Count: 3520
View Count: 21162
Comment Num: 0
Language: EN
Source:
Who Can Read: Free
Date: 9-14-2002
Publisher: Administrator
Summary
Modern risk management calls for an understanding of stochastic dependence going beyond simple linear correlation. This paper deals with the static (non-time-dependent) case and emphasizes the copula representation of dependence for a random vector. Linear correlation is a natural dependence measure for multivariate normally and, more generally, elliptically distributed risks but other dependence concepts like comonotonicity and rank correlation should also be understood by the risk management practitioner. Using counterexamples the falsity of some commonly held views on correlation is demonstrated; in general, these fallacies arise from the naive assumption that dependence properties of the elliptical world also hold in the non-elliptical world. In particular, the problem of finding multivariate models which are consistent with prespecified marginal distributions and correlations is addressed. Pitfalls are highlighted and simulation algorithms avoiding these problems are constructed.
Author(s)
Embrechts, Paul Sign in to follow this author
McNeil, Alexander Sign in to follow this author
Straumann, Daniel Sign in to follow this author
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