Journal of Financial Econometrics Advance Access originally published online on September 15, 2009
Journal of Financial Econometrics 2009 7(4):481-503; doi:10.1093/jjfinec/nbp016
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A Latent Factor Model of Multivariate Conditional Heteroscedasticity
University of North Carolina at Chapel Hill
Address correspondence to Mike Aguilar, 06A Gardner Hall, CB#3305, UNC-Chapel Hill, Chapel Hill, NC 27599, or e-mail: maguilar{at}email.unc.edu.
JEL Classification: C12, C13, C14, C32, C51, G12
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Abstract |
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This paper examines the joint dynamics of a system of asset returns by describing and implementing a factor multivariate stochastic volatility (factor MSV) model. The foundation for the model discussed here is the work of Doz and Renault (2006). Despite its attractive design, that model has not been adopted widely in the literature, most likely due to the difficulty encountered in its implementation. The main contribution of this paper is to illustrate that this factor MSV model can be implemented easily and with only a few modifications. Specifically, I develop a sequential testing procedure that can account simultaneously for a series of nested hypotheses and structure properly the moment conditions used for estimation. A simulation study suggests that the factor MSV model and estimation strategy presented here is able to recover accurately the number of, and dynamics for, the latent factors that drive the conditional volatility of returns.
KEYWORDS: common features, conditional factor models, generalized method of moments, multivariate conditional heteroscedasticity, stochastic volatility
The author is grateful to Eric Renault for guidance, as well as to Eric Ghysels, Denis Pelletier, the editors and two anonymous referees formany helpful comments.
Received January 15, 2008; revised August 3, 2009; accepted August 4, 2009