Bayesian estimation of GARCH model with an adaptive proposal density
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.
|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|
|Contact details of provider:|| Web page: http://arxiv.org/ |
When requesting a correction, please mention this item's handle: RePEc:arx:papers:1012.5986. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (arXiv administrators)
If references are entirely missing, you can add them using this form.