Template-Type: ReDIF-Paper 1.0
Series: Tinbergen Institute Discussion Papers
Creation-Date: 2014-03-17
Number: 14-037/III
Author-Name: Manabu Asai
Author-Workplace-Name: Soka University, Japan
Author-Name: Michael McAleer
Author-Workplace-Name: National Tsing Hua University, Taiwan,  Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Complutense University of Madrid, Spain
Title: Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance
Abstract: Modelling covariance structures is known to suffer from the curse of dimensionality. In order to avoid this problem for forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures that accommodates asymmetry and long memory. Using the basic structure of the fMSV model, the authors extend the dynamic correlation MSV model, the conditional/stochastic Wishart autoregressive models, the matrix-exponential MSV model, and the Cholesky MSV model. Empirical results for 7 financial asset returns for US stock returns indicate that the new fMSV models outperform existing dynamic conditional correlation models for forecasting future covariances. Among the new fMSV models, the Cholesky MSV model with long memory and asymmetry shows stable and better forecasting performance for one-day, five-day and ten-day horizons in the periods before, during and after the global financial crisis.
Classification-JEL: C32, C53, C58, G17
Keywords: Dimension reduction; Factor Model; Multivariate Stochastic Volatility; Leverage Effects; Long Memory; Realized Volatility
File-Url: https://papers.tinbergen.nl/14037.pdf
File-Format: application/pdf
File-Size: 322292 bytes
Handle: RePEc:tin:wpaper:20140037