This note presents the R package bayesGARCH which provides functions for the Bayesian estimation of the parsimonious and effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids the tedious task of tuning an MCMC sampling algorithm. The usage of the package is shown in an empirical application to exchange rate log-returns.
fGarch, rgarch, tseries, bayesGARCH, coda, foreach
Finance, Bayesian, TimeSeries, Econometrics, Environmetrics, gR, HighPerformanceComputing
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For attribution, please cite this work as
Ardia & Hoogerheide, "The R Journal: Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations", The R Journal, 2010
BibTeX citation
@article{RJ-2010-014,
author = {Ardia, David and Hoogerheide, Lennart F.},
title = {The R Journal: Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations},
journal = {The R Journal},
year = {2010},
note = {https://doi.org/10.32614/RJ-2010-014},
doi = {10.32614/RJ-2010-014},
volume = {2},
issue = {2},
issn = {2073-4859},
pages = {41-47}
}