Summary
the 2014 International Symposium on Nonlinear Theory and its Applications
2014
Session Number:B1L-B
Session:
Number:B1L-B1
Evaluating Copula-Based Multivariate Density Forecasts in Selected Regions of Support
Cees Diks, Valentyn Panchenko, Oleg Sokolinskiy, Dick van Dijk,
pp.220-220
Publication Date:2014/9/14
Online ISSN:2188-5079
Summary:
We propose a testing framework for comparing the predictive accuracy of copulabased multivariate density forecasts, focusing on a specific part of the joint distribution. The test is based on the Kullback-Leibler Information Criterion, using out-of-sample conditional likelihood and censored likelihood to restrict the evaluation of the forecasts to the region of interest. Monte Carlo simulation results show that the proposed tests have satisfactory size and power properties in small samples. In an empirical application to daily exchange rate returns we find evidence that the dependence structure varies with the sign and magnitude of returns, such that different parametric copula models achieve superior forecasting performance in different regions of the support. Our empirical analysis emphasises the importance of allowing for lower and upper tail dependence for accurate forecasting of common extreme movements of the different currencies.