Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/94323 
Year of Publication: 
1996
Series/Report no.: 
Working Paper No. 1996-19
Publisher: 
Rutgers University, Department of Economics, New Brunswick, NJ
Abstract: 
We compare small-sample properties of Bayes estimation and maximum likelihood estimation (MLE) of ARMA-GARCH models. Our Monte Carlo experiments indicate that in small sample, the Bayes estimator beats the MLE. We also develop a Bayes method of testing strict stationarity and ergodicity of the conditional variance in the GARCH(1,1) process, near epoch depencenve (NED), and finiteness of unconditional moments of the GARCH(1,1) process by using a Markov chain Monte Carlo (MCMC) mehtod. We apply this method to test these properties in the ARMA-GARCH models of weekly foreign exchange rates.
Subjects: 
GARCH
Markov Chain Monte Carlo (MCMC)
Near Epoch Dependence (NED)
JEL: 
C11
C22
Document Type: 
Working Paper

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