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Bayesian estimation of GARCH model with an adaptive proposal density

Listed author(s):
  • Tetsuya Takaishi
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    A Bayesian estimation of a GARCH model is performed for US Dollar/Japanese Yen exchange rate by the Metropolis-Hastings algorithm with a proposal density given by the adaptive construction scheme. In the adaptive construction scheme the proposal density is assumed to take a form of a multivariate Student's t-distribution and its parameters are evaluated by using the sampled data and updated adaptively during Markov Chain Monte Carlo simulations. We find that the autocorrelation times between the data sampled by the adaptive construction scheme are considerably reduced. We conclude that the adaptive construction scheme works efficiently for the Bayesian inference of the GARCH model.

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    Paper provided by in its series Papers with number 1012.5986.

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    Date of creation: Dec 2010
    Date of revision: Dec 2010
    Publication status: Published in New Advances in Intelligent Decision Technologies, SCI 199, (2009) pp. 635-643
    Handle: RePEc:arx:papers:1012.5986
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