Fast estimation of multivariate stochastic volatility
| dc.creator | Triantafyllopoulos, Kostas | |
| dc.creator | Montana, Giovanni | |
| dc.date | 2007-08-31 | |
| dc.date | 2007-11-29 | |
| dc.date.accessioned | 2026-07-07T12:05:23Z | |
| dc.date.available | 2026-07-07T12:05:23Z | |
| dc.description | In this paper we develop a Bayesian procedure for estimating multivariate stochastic volatility (MSV) using state space models. A multiplicative model based on inverted Wishart and multivariate singular beta distributions is proposed for the evolution of the volatility, and a flexible sequential volatility updating is employed. Being computationally fast, the resulting estimation procedure is particularly suitable for on-line forecasting. Three performance measures are discussed in the context of model selection: the log-likelihood criterion, the mean of standardized one-step forecast errors, and sequential Bayes factors. Finally, the proposed methods are applied to a data set comprising eight exchange rates vis-a-vis the US dollar. | |
| dc.description | 15 pages, 4 figures | |
| dc.identifier | https://arxiv.org/abs/0708.4376 | |
| dc.identifier | http://arxiv.org/abs/0708.4376 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/208362 | |
| dc.subject | Statistical Finance | |
| dc.subject | Applications | |
| dc.subject | Methodology | |
| dc.title | Fast estimation of multivariate stochastic volatility | |
| dc.type | text |