JSM 2005 - Toronto

Abstract #303582

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Activity Number: 181
Type: Topic Contributed
Date/Time: Monday, August 8, 2005 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #303582
Title: Time-varying Covariances: A Cholesky Decomposition Approach
Author(s): Hedibert F. Lopes*+ and Robert McCulloch and Ruey Tsay
Companies: The University of Chicago and The University of Chicago and The University of Chicago
Address: 5807 South Woodlawn Avenue, Chicago, IL, 60637, United States
Keywords: Multivariate stochastic volatility ; Markov chain Monte Carlo ; Portfolio selection ; Factor analysis ; Data reduction ; Sequential Monte Carlo
Abstract:

In this paper, we introduce a new class of time-varying multivariate stochastic volatility models that rely upon the Cholesky decomposition of the vector of time series covariance matrices at each given time period. Our model structure encompasses and/or generalizes several of the existing factor-like stochastic volatility models recently proposed in the financial econometrics literature. We compare our model with competing ones by posterior predictive assessment and portfolio cumulative gains in emerging and developed economy stock markets.

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Revised March 2005