Quotation Kastner, Gregor, Frühwirth-Schnatter, Sylvia, Lopes, Hedibert Freitas. 2013. Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models. 1st Vienna Workshop on High Dimensional Time Series in Macroeconomics and Finance, IHS Wien, Österreich, 02.05.-04.05.


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Abstract

Multivariate factor stochastic volatility models are increasingly used for the analysis of multivariate financial and economic time series because they can capture the volatility dynamics by a small number of latent factors. The main advantage of such a model is its parsimony, where all variances and covariances of a time series vector are governed by a low-dimensional common factor with the components following independent stochastic volatility models. For high dimensional problems of this kind, Bayesian MCMC estimation is a very efficient estimation method, however, it is associated with a considerable computational burden when the number of assets is moderate to large. To overcome this, we avoid the usual forward-filtering backward-sampling (FFBS) algorithm by sampling ``all without a loop'' (AWOL), consider various reparameterizations such as (partial) non-centering, and apply an ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation at an univariate level, which can be applied directly to heteroscedasticity estimation for latent variables such as factors. To show the effectiveness of our approach, we apply the model to a vector of daily exchange rate data.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Paper presented at an academic conference or symposium
Language English
Title Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models
Event 1st Vienna Workshop on High Dimensional Time Series in Macroeconomics and Finance
Year 2013
Date 02.05.-04.05.
Country Austria
Location IHS Wien
URL http://www.ihs.ac.at/conferences/timeseries/

Associations

People
Kastner, Gregor (Details)
Frühwirth-Schnatter, Sylvia (Details)
External
Lopes, Hedibert Freitas (The University of Chicago Booth School of Business, United States/USA)
Organization
Institute for Statistics and Mathematics IN (Details)
Research areas (ÖSTAT Classification 'Statistik Austria')
1105 Computer software (Details)
1162 Statistics (Details)
5323 Econometrics (Details)
5701 Applied statistics (Details)
5707 Time series analysis (Details)
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