Out-of-sample comparison of copula specifications in multivariate density forecasts

Cees Diks (), Dick van Dijk and Valentyn Panchenko

No 08-10, CeNDEF Working Papers from Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance

Abstract: We introduce a statistical test for comparing the predictive accuracy of competing copula specifications in multivariate density forecasts, based on the Kullback-Leibler Information Criterion (KLIC). The test is valid under general conditions: in particular it allows for parameter estimation uncertainty and for the copulas to be nested or non-nested. Monte Carlo simulations demonstrate that the proposed test has satisfactory size and power properties in finite samples. Applying the test to daily exchange rate returns of several major currencies against the US dollar we find that the Student's t copula is favored over Gaussian, Gumbel and Clayton copulas. This suggests that these exchange rate returns are characterized by symmetric tail dependence.

Date: 2008
New Economics Papers: this item is included in nep-ecm and nep-for
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Related works:
Journal Article: Out-of-sample comparison of copula specifications in multivariate density forecasts (2010)
Working Paper: Out-of-sample comparison of copula specifications in multivariate density forecasts (2010)
Working Paper: Out-of-sample comparison of copula specifications in multivariate density forecasts (2008)
Working Paper: Out-of-sample Comparison of Copula Specifications in Multivariate Density Forecasts (2008)
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