Quotation Kastner, Gregor, Frühwirth-Schnatter, Sylvia, Lopes, Hedibert Freitas. 2015. Dynamic covariance estimation using sparse Bayesian factor stochastic volatility models. In Proceedings of the 30th International Workshop on Statistical Modelling, Volume 2, Hrsg. Herwig Friedl, Helga Wagner, S. 139-142. Linz: None.


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Abstract

We address the "curse of dimensionality" arising in time-varying covariance estimation by modeling the underlying volatility dynamics of a time series vector through a lower dimensional collection of latent dynamic factors. Furthermore, we apply a Normal-Gamma shrinkage prior to the elements of the factor loadings matrix, thereby increasing parsimony even more. Estimation is carried out via MCMC in order to obtain draws from the high-dimensional posterior and predictive distributions. To guarantee efficiency of the samplers, we utilize several ancillarity-sufficiency interweaving strategies (ASIS) for sampling the factor loadings. Estimation and forecasting performance is evaluated for simulated and real-world data.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Contribution to conference proceedings
Language English
Title Dynamic covariance estimation using sparse Bayesian factor stochastic volatility models
Title of whole publication Proceedings of the 30th International Workshop on Statistical Modelling, Volume 2
Editor Herwig Friedl, Helga Wagner
Page from 139
Page to 142
Location Linz
Year 2015
URL http://ifas.jku.at/iwsm2015/

Associations

People
Kastner, Gregor (Details)
Frühwirth-Schnatter, Sylvia (Details)
External
Lopes, Hedibert Freitas (Insper, Brazil)
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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