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

Cees Diks (), Valentyn Panchenko and Dick van Dijk ()

No 2008-23, Discussion Papers from School of Economics, The University of New South Wales

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 nonnested. 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.

Keywords: Copula-based density forecast; semiparametric statistics; out-of-sample forecast evaluation; Kullback-Leibler Information Criterion; empirical copula (search for similar items in EconPapers)
JEL-codes: C12 C14 C32 C52 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-for
Date: 2008-10
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Related works:
Journal Article: Out-of-sample comparison of copula specifications in multivariate density forecasts (2010) Downloads
Working Paper: Out-of-sample comparison of copula specifications in multivariate density forecasts (2010) Downloads
Working Paper: Out-of-sample comparison of copula specifications in multivariate density forecasts (2008) Downloads
Working Paper: Out-of-sample Comparison of Copula Specifications in Multivariate Density Forecasts (2008) Downloads
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