Multivariate Stochastic Volatility Models: Bayesian Estimation and Model Comparison
AbstractIn this paper we show that fully likelihood-based estimation and comparison of multivariate stochastic volatility (SV) models can be easily performed via a freely available Bayesian software called WinBUGS. Moreover, we introduce to the literature several new specifications that are natural extensions to certain existing models, one of which allows for time-varying correlation coefficients. Ideas are illustrated by fitting, to a bivariate time series data of weekly exchange rates, nine multivariate SV models, including the specifications with Granger causality in volatility, time-varying correlations, heavy-tailed error distributions, additive factor structure, and multiplicative factor structure. Empirical results suggest that the best specifications are those that allow for time-varying correlation coefficients.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Taylor and Francis Journals in its journal Econometric Reviews.
Volume (Year): 25 (2006)
Issue (Month): 2-3 ()
Contact details of provider:
Web page: http://taylorandfrancis.metapress.com/link.asp?target=journal&id=107830
Other versions of this item:
- Jun Yu & Renate Meyer, 2004. "Multivariate Stochastic Volatility Models: Bayesian Estimation and Model Comparison," Working Papers 23-2004, Singapore Management University, School of Economics.
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Gianni Amisano & Roberto Casarin, 2008. "Particle Filters for Markov-Switching Stochastic-Correlation Models," Working Papers 0814, University of Brescia, Department of Economics.
- Huang, Shirley J. & Yu, Jun, 2010.
"Bayesian analysis of structural credit risk models with microstructure noises,"
Journal of Economic Dynamics and Control,
Elsevier, vol. 34(11), pages 2259-2272, November.
- Shirley J. Huang & Jun Yu, 2009. "Bayesian Analysis of Structural Credit Risk Models with Microstructure Noises," Finance Working Papers 23054, East Asian Bureau of Economic Research.
- Shirley J. Huang & Jun Yu, . "Bayesian Analysis of Structural Credit Risk Models with Microstructure Noises," Working Papers CoFie-07-2008, Sim Kee Boon Institute for Financial Economics.
- Christian M. Hafner & Hans Manner, 2012.
"Dynamic stochastic copula models: estimation, inference and applications,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 27(2), pages 269-295, 03.
- Hafner, Christian M. & Manner, Hans, 2008. "Dynamic stochastic copula models: Estimation, inference and applications," Research Memoranda 043, Maastricht : METEOR, Maastricht Research School of Economics of Technology and Organization.
- Beum-Jo Park, 2011. "Forecasting Volatility in Financial Markets Using a Bivariate Stochastic Volatility Model with Surprising Information," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 37-58, September.
- Roberto Casarin & Domenico sartore, 2008.
"Matrix-State Particle Filter for Wishart Stochastic Volatility Processes,"
0816, University of Brescia, Department of Economics.
- Roberto Casarin & Domenico Sartore, 2007. "Matrix-State Particle Filter for Wishart Stochastic Volatility Processes," Working Papers 2007_30, Department of Economics, University of Venice "Ca' Foscari".
- Manner, Hans & Segers, Johan, 2011. "Tails of correlation mixtures of elliptical copulas," Insurance: Mathematics and Economics, Elsevier, vol. 48(1), pages 153-160, January.
- Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
- Johansson, Anders C., 2010.
"Asian sovereign debt and country risk,"
Pacific-Basin Finance Journal,
Elsevier, vol. 18(4), pages 335-350, September.
- K. Triantafyllopoulos, 2008. "Multivariate stochastic volatility with Bayesian dynamic linear models," Papers 0802.0214, arXiv.org.
- Jiří Witzany, 2011.
"Estimating Correlated Jumps and Stochastic Volatilities,"
Working Papers IES
2011/35, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2011.
- Jiří Witzany, 2013. "Estimating Correlated Jumps and Stochastic Volatilities," Prague Economic Papers, University of Economics, Prague, vol. 2013(2), pages 251-283.
- Mustafa Hakan Eratalay, 2012. "Estimation of Multivariate Stochastic Volatility Models: A Comparative Monte Carlo Study," EUSP Deparment of Economics Working Paper Series Ec-04/12, European University at St. Petersburg, Department of Economics.
- Charles S. Bos & Phillip Gould, 2007. "Dynamic Correlations and Optimal Hedge Ratios," Tinbergen Institute Discussion Papers 07-025/4, Tinbergen Institute.
- Manner, Hans, 2011. "Tails of correlation mixtures of elliptical copulas," Open Access publications from UniversitÃ© catholique de Louvain info:hdl:2078.1/114367, Université catholique de Louvain.
- Almeida, Carlos & Czado, Claudia, 2012. "Efficient Bayesian inference for stochastic time-varying copula models," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1511-1527.
- Hans J. Skaug & Jun Yu, 2009.
"Automated Likelihood Based Inference for Stochastic Volatility Models,"
15-2009, Singapore Management University, School of Economics.
- Jun Yu, 2007. "Automated Likelihood Based Inference for Stochastic Volatility Models," Working Papers 01-2007, Sim Kee Boon Institute for Financial Economics.
- Hans J. Skaug & Jun Yu, 2007. "Automated Likelihood Based Inference for Stochastic Volatility Models," Working Papers CoFie-01-2007, Sim Kee Boon Institute for Financial Economics.
- Agata Kliber, 2011. "Sovereign CDS Instruments in Central Europe – Linkages and Interdependence," Dynamic Econometric Models, Wydawnictwo Naukowe Uniwersytetu Mikolaja Kopernika, vol. 11, pages 111-128.
- Asai, Manabu & McAleer, Michael, 2009. "The structure of dynamic correlations in multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 150(2), pages 182-192, June.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.