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

See all articles by Luc Bauwens

Luc Bauwens

Université catholique de Louvain

Manuela Braione

SOSE

Giuseppe Storti

University of Salerno - Department of Economics

Date Written: November 19, 2014

Abstract

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

Bauwens, Luc and Braione, Manuela and Storti, Giuseppe, Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices (November 19, 2014). Annales d'Economie et de Statistique, 123-124,103-134, December, 2016, Available at SSRN: https://ssrn.com/abstract=2965458

Luc Bauwens (Contact Author)

Université catholique de Louvain ( email )

CORE
34 Voie du Roman Pays
B-1348 Louvain-la-Neuve, b-1348
Belgium
32 10 474321 (Phone)
32 10 474301 (Fax)

Manuela Braione

SOSE ( email )

Via Mentore Maggini
Rome, 00143
Italy
00143 (Fax)

Giuseppe Storti

University of Salerno - Department of Economics ( email )

Via John Paul II, 132
Fisciano (SA), 84084
Italy

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
29
Abstract Views
305
PlumX Metrics