Bayesian estimation of GARCH model by hybrid Monte Carlo

Details Bayesian estimation of GARCH model by hybrid Monte Carlo Bayesian estimation of GARCH model by hybrid Monte Carlo

2007-02-27

arxiv.org/abs/physics/0702240v1

Proceedings of the 9th Joint Conference on Information Sciences 2006, CIEF-214

Physics

Computational Physics

The 9th Joint Conference on Information Sciences (JCIS), October 8-11, 2006

Scientific paper

10.2991/jcis.2006.159

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.

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