Zero Variance and Hamiltonian Monte Carlo Methods in GARCH Models
Computation
2017-10-24 v1
Abstract
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.
Cite
@article{arxiv.1710.07693,
title = {Zero Variance and Hamiltonian Monte Carlo Methods in GARCH Models},
author = {Rafael S. Paixão and Ricardo S. Ehlers},
journal= {arXiv preprint arXiv:1710.07693},
year = {2017}
}