Abstract
This papers examines the joint dynamics of a system of asset returns. I describe and implement a multivariate factor stochastic volatility (MVFSV) model. I follow closely the work of Doz and Renault (2006), with two important changes. First, I design a sequential testing procedure to determine the dimensions of the appropriate factor structure needed to accommodate the conditional heteroscedasticity among a system of returns. Second, I employ a form of Tikhonov Regularization in order to overcome a near singularity among the moment conditions used for estimation. Simulation studies suggest that the MVFSV model is able to recover accurately the latent factors that drive the conditional volatility of returns. Moreover, the model estimates can be used to construct conditionally homoscedastic portfolios as linear combinations of the conditionally heteroscedastic assets. An empirical application to portfolios representing the twelve sectors of the U.S. economy
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
