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

  • Ardia, David

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.

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File URL: http://mpra.ub.uni-muenchen.de/17414/1/MPRA_paper_17414.pdf
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File URL: http://mpra.ub.uni-muenchen.de/27853/3/MPRA_paper_27853.pdf
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File URL: http://mpra.ub.uni-muenchen.de/30122/2/MPRA_paper_30122.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 17414.

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Date of creation: 20 Sep 2009
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Handle: RePEc:pra:mprapa:17414
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  1. 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.
  2. Ardia, David, 2009. "Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations in R," MPRA Paper 17414, University Library of Munich, Germany.
  3. 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.
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