Journal of Statistics: Advances in Theory and ApplicationsAuthor's: Anupam Dutta
Pages: [27] - [37]
Received Date: August 19, 2014
Submitted by:
The objective of this paper is to investigate the properties of GARCH (1,1) model and to perform inference using a Bayesian approach. In doing so, the Markov Chain Monte Carlo (MCMC) approach is used for estimating the parameters of GARCH (1,1) and the t-GARCH (1,1) models. We examine the U.S.-Japan and the U.S.-U.K. exchange rate series. The empirical analysis reveals that the MCMC approach is found to be effective for each return series.
stochastic volatility, Bayesian approach, Markov Chain Monte Carlo (MCMC).
