software . 2017

bayesGARCH: Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations in R

David Ardia; Lennart F. Hoogerheide;
Open Access
  • Published: 05 Jan 2017
  • Publisher: Zenodo
Abstract
The package bayesGARCH implements in R (R Core Team, 2016) the Bayesian estimation procedure described in Ardia (2008, chapter 5) for the GARCH(1,1) model with Student-t innovations. The approach consists of a Metropolis-Hastings (MH) algorithm where the proposal distributions are constructed from auxiliary ARMA processes on the squared observations. This methodology avoids the time-consuming and difficult task, especially for non-experts, of choosing and tuning a sampling algorithm. We refer the user to Ardia (2008) and Ardia and Hoogerheide (2010) for illustrations. The latest version of the package is available at https://github.com/ArdiaD/bayesGARCH.
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Subjects
free text keywords: GARCH, Bayesian, MCMC, R software
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ZENODO
Software . 2017
Providers: ZENODO
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