Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations in R
This paper presents the R package bayesGARCH which provides functions for the Bayesian estimation of the parsimonious but effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids the time-consuming and difficult task of tuning a sampling algorithm. The usage of the package is shown in an empirical application to exchange rate log-returns.
|Date of creation:||20 Sep 2009|
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Web page: https://mpra.ub.uni-muenchen.de
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- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
- Deschamps, Philippe J., 2004.
"A flexible prior distribution for Markov switching autoregressions with Student-t errors,"
DQE Working Papers
2, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland, revised 12 Nov 2011.
- Deschamps, Philippe J., 2006. "A flexible prior distribution for Markov switching autoregressions with Student-t errors," Journal of Econometrics, Elsevier, vol. 133(1), pages 153-190, July.
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