MCMC methods for comparing stochastic volatility and GARCH models
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- PREMINGER, Arie & HAFNER, Christian, 2006. "Deciding between GARCH and stochastic volatility via strong decision rules," CORE Discussion Papers 2006042, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Bildirici, Melike & Ersin, Özgür, 2012. "Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models," MPRA Paper 40330, University Library of Munich, Germany, revised May 2012.
- Arie Preminger & Christian M. Hafner, 2006. "Deciding Between Garch And Stochastic Volatility Via Strong Decision Rules," Working Papers 0603, Ben-Gurion University of the Negev, Department of Economics.
- Tsiaplias, Sarantis, 2008. "Factor estimation using MCMC-based Kalman filter methods," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 344-353, December.
- Brent Hudson & Richard Gerlach, 2008. "A Bayesian approach to relaxing parameter restrictions in multivariate GARCH models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(3), pages 606-627, November.
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