Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices
Annales d'Economie et de Statistique, 123-124,103-134, December, 2016
33 Pages Posted: 10 May 2017
Date Written: November 19, 2014
Novel model specifications that include a time-varying long run component in the dynamics of realized covariance matrices are proposed. The adopted modeling framework allows the secular component to enter the model structure either in an additive fashion or as a multiplicative factor, and to be specified parametrically, using a MIDAS filter, or non-parametrically. Estimation is performed by maximizing a Wishart quasi-likelihood function. The one-step ahead forecasting performance of the models is assessed by means of three approaches: the Model Confidence Set, (global) minimum variance portfolios and Value-at-Risk. The results provide evidence in favor of the hypothesis that the proposed models outperform benchmarks incorporating a constant long run component, both in and out-of-sample.
Keywords: realized covariance, component dynamic models, MIDAS, minimum variance portfolio, Model Confidence Set, Value-at-Risk
JEL Classification: C13, C32, C58
Suggested Citation: Suggested Citation