Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
418170 | Computational Statistics & Data Analysis | 2007 | 10 Pages |
Abstract
A goodness of fit test for copulas based on Rosenblatt's transformation is investigated. This test performs well if the marginal distribution functions are known and are used in the test statistic. If the marginal distribution functions are unknown and are replaced by their empirical estimates, then the test's properties change significantly. This is shown in detail by simulation for special cases. A bootstrap version of the test is suggested and it is shown by simulation that it performs well. An empirical application of this test to daily returns of German assets reveals that a Gaussian copula is unsuitable to describe their dependence structure. A tνtν-copula with low degrees of freedom such as ν=4ν=4 or 5 fits the data in some cases.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Jadran Dobrić, Friedrich Schmid,