Out-of-sample Comparison of Copula Specifications in Multivariate Density Forecasts

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… (More)

Topics

6 Figures and Tables

Statistics

0102030201520162017
Citations per Year

Citation Velocity: 7

Averaging 7 citations per year over the last 3 years.

Learn more about how we calculate this metric in our FAQ.

Cite this paper

@inproceedings{Diks2008OutofsampleCO, title={Out-of-sample Comparison of Copula Specifications in Multivariate Density Forecasts}, author={Cees Diks and Valentyn Panchenko and Dick van Dijk}, year={2008} }