Bayesian estimation of GARCH model by hybrid Monte Carlo
Computational Physics
2008-12-09 v1 Data Analysis, Statistics and Probability
Statistical Finance
Abstract
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.
Cite
@article{arxiv.physics/0702240,
title = {Bayesian estimation of GARCH model by hybrid Monte Carlo},
author = {Tetsuya Takaishi},
journal= {arXiv preprint arXiv:physics/0702240},
year = {2008}
}
Comments
The 9th Joint Conference on Information Sciences (JCIS), October 8-11, 2006