Matrix-State Particle Filter for Wishart Stochastic Volatility Processes
Author | : Roberto Casarin |
Publisher | : |
Total Pages | : 0 |
Release | : 2010 |
ISBN-10 | : OCLC:1376544196 |
ISBN-13 | : |
Rating | : 4/5 ( Downloads) |
Download or read book Matrix-State Particle Filter for Wishart Stochastic Volatility Processes written by Roberto Casarin and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work deals with multivariate stochastic volatility models, which account for a time-varying variance-covariance structure of the observable variables. We focus on a special class of models recently proposed in the literature and assume that the covariance matrix is a latent variable which follows an autoregressive Wishart process. We review two alternative stochastic representations of the Wishart process and propose Markov-Switching Wishart processes to capture different regimes in the volatility level. We apply a full Bayesian inference approach, which relies upon Sequential Monte Carlo (SMC) for matrix-valued distributions and allows us to sequentially estimate both the parameters and the latent variables.