A Dynamic Component Model for Forecasting High-Dimensional Realized Covariance Matrices

Econometrics and Statistics, 1, 40-61, 2017

24 Pages Posted: 9 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 3, 2016

Abstract

The Multiplicative MIDAS Realized DCC (MMReDCC) model simultaneously accounts for short and long term dynamics in the conditional (co)volatilities of asset returns, in line with the empirical evidence suggesting that their level is changing over time as a function of economic conditions.

Herein the applicability of the model is improved along two directions.

First, by proposing an algorithm that relies on the maximization of an iteratively re-computed moment-based profile likelihood function and keeps estimation feasible in large dimensions by mitigating the incidental parameter problem.

Second, by illustrating a conditional bootstrap procedure to generate multi-step ahead predictions from the model. In an empirical application on a dataset of forty-six equities, the MMReDCC model is found to statistically outperform the selected benchmarks in terms of in-sample fit as well as in terms of out-of-sample covariance predictions. The latter are mostly significant in periods of high market volatility.

Keywords: Realized covariance, dynamic component models, multi-step forecasting, iterative algorithm

JEL Classification: C13, C32, C58

Suggested Citation

Bauwens, Luc and Braione, Manuela and Storti, Giuseppe, A Dynamic Component Model for Forecasting High-Dimensional Realized Covariance Matrices (November 3, 2016). Econometrics and Statistics, 1, 40-61, 2017, Available at SSRN: https://ssrn.com/abstract=2965413

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

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