January 5, 2017 Software Open Access

David Ardia; Lennart F. Hoogerheide

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    "description": "<p>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.</p>", 
    "license": {
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    "title": "bayesGARCH: Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations in R", 
    "journal": {
      "volume": "2", 
      "issue": "2", 
      "pages": "41-47", 
      "title": "The R Journal"
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    "version": "v2.0.4", 
    "references": [
      "David Ardia. Financial Risk Management with Bayesian Estimation of GARCH Models: Theory and Applications, volume 612 of Lecture Notes in Economics and Mathematical Systems. Springer-Verlag, Berlin, Germany, 2008. doi: 10.1007/978-3-540-78657-3", 
      "David Ardia and Lennart F. Hoogerheide. Bayesian estimation of the GARCH(1,1) model with Student-t innovations. The R Journal, 2(2):41-47, 2010. URL http://journal.r-project.org/"
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      "GARCH", 
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    "publication_date": "2017-01-05", 
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        "affiliation": "University of Neuch\u00e2tel", 
        "name": "David Ardia"
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        "affiliation": "Vrije Universiteit Amsterdam", 
        "name": "Lennart F. Hoogerheide"
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