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Bayesian Vector Autoregressions with Non-Gaussian Shocks

Listed author(s):
  • Ching-Wai (Jeremy) Chiu

    (Bank of England)

  • Haroon Mumtaz

    ()

    (Queen Mary University of London)

  • Gabor Pinter

    (Bank of England)

This paper proposes a Bayesian Vector Autoregression where the orthogonalised shocks are assumed to be non-Gaussian. A Gibbs sampling algorithm is provided to approximate the poste-rior distribution of the model parameters. An application to a model of the yield curve suggests that there is ample evidence against the assumption of normal shocks. The proposed model provides notable improvements both in terms of in-sample Öt and out of sample forecasting.

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File URL: http://econ.qmul.ac.uk/research/cremfi/2016/DP5.pdf
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Paper provided by CReMFi, School of Economics and Finance, QMUL in its series CReMFi Discussion Papers with number 5.

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Date of creation: Jul 2016
Handle: RePEc:qmm:wpaper:5
Contact details of provider: Web page: http://www.econ.qmul.ac.uk

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  28. Ching-Wai (Jeremy) Chiu & Haroon Mumtaz & Gabor Pinter, 2014. "Fat-tails in VAR Models," Working Papers 714, Queen Mary University of London, School of Economics and Finance.
  29. Bianchi, Francesco & Mumtaz, Haroon & Surico, Paolo, 2009. "The great moderation of the term structure of UK interest rates," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 856-871, September.
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