Distributions and Copulas for Integrated Risk Management
| Autor: | Peter F. Christoffersen |
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| Rok vydání: | 2012 |
| Předmět: | |
| DOI: | 10.1016/b978-0-12-374448-7.00009-9 |
| Popis: | Multivariate risk models require assumptions about the multivariate distribution of return shocks. The multivariate normal distribution is the most convenient model but it does not allow for enough extreme dependence in most risk management applications. One can use the threshold correlation to measure extreme dependence in observed asset returns and in the available multivariate distributions. The multivariate symmetric t and in particular the asymmetric t distribution provides the larger threshold correlations that one requires, but in high dimension the asymmetric t is cumbersome to estimate. In addition, a copula model allows to link together a wide range of marginal distributions. The normal and t copulas are fairly flexible and are applicable in high dimensions. Copulas are also well suited for integrated risk management where the risk models from individual business units must be linked together to provide a sensible aggregate measure of risk for the organization as a whole. |
| Databáze: | OpenAIRE |
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