April 2006
We generalize the factor stochastic volatility (FSV) model of Pitt and Shephard (1999) and Aguilar and West (2000) in two important directions. First, we make the FSV model more flexible and able to capture more general time-varying variance-covariance structures by letting the matrix of factor loadings to be time dependent. Secondly, we entertain FSV model with jumps in the common factors volatilities through So, Lam and Li's (1998) Markov switching stochastic volatility model. Novel Markov Chain Monte Carlo algorithm is derived for both class of models. We apply our methodology to two illustrative situations: daily exchange rate returns (Aguilar and West, 2000) and Latin American stock returns (Lopes and Migon, 2002).
Keywords: Bayesian inference, factor analysis, variance decomposition, dynamic models, Markov switching.
The manuscript is available in PostScript and PDF formats.