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Zero Variance and Hamiltonian Monte Carlo Methods in GARCH Models

10/20/2017

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by Rafael S. Paixão, et al.

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In this paper, we develop Bayesian Hamiltonian Monte Carlo methods for inference in asymmetric GARCH models under different distributions for the error term. We implemented Zero-variance and Hamiltonian Monte Carlo schemes for parameter estimation to try and reduce the standard errors of the estimates thus obtaing more efficient results at the price of a small extra computational cost.

Rafael S. Paixão
1 publication
Ricardo S. Ehlers
4 publications

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