Bayesian estimation of GARCH model by hybrid Monte Carlo

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The hybrid Monte Carlo (HMC) algorithm is used for Bayesian analysis of the generalized autoregressive conditional heteroscedasticity (GARCH) model. The HMC algorithm is one of Markov chain Monte Carlo (MCMC) algorithms and it updates all parameters at once. We demonstrate that how the HMC reproduces the GARCH parameters correctly. The algorithm is rather general and it can be applied to other models like stochastic volatility models.
The 9th Joint Conference on Information Sciences (JCIS), October 8-11, 2006

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Computational Physics, Data Analysis, Statistics and Probability, Statistical Finance

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http://salesiana.dossiersoluciones.com/handle/123456789/209911

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/physics/0702240
 http://arxiv.org/abs/physics/0702240
 Proceedings of the 9th Joint Conference on Information Sciences 2006, CIEF-214
 doi:10.2991/jcis.2006.159

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arXiv