Abstract #301240

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JSM 2003 Abstract #301240
Activity Number: 123
Type: Contributed
Date/Time: Monday, August 4, 2003 : 10:30 AM to 12:20 PM
Sponsor: Business & Economics Statistics Section
Abstract - #301240
Title: A Multivariate Stochastic Volatility Model with Long Memory
Author(s): Giovanni Petris*+
Companies: University of Arkansas
Address: Dept. of Mathematical Sciences, Fayetteville, AR, 72701,
Keywords: stochastic volatility ; long memory ; Bayesian analysis
Abstract:

We present a Bayesian approach to estimation and prediction for a multivariate long memory stochastic volatility model. In order to keep model complexity to an acceptable level, we use a factor model for the observations as the first stage of a model hyerarchy, modeling then the factors as long memory stochastic volatility processes. Assuming that the multivariate observations depend on a low-dimensional vector of factors is highly plausible in many applications, including the analysis of financial markets returns. The hyerarchical model allows for an efficient evaluation of posterior distributions of parameters and latent factors and volatilities, via Markov chain Monte Carlo simulations.

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