Bayesian Analysis of a Doubly Truncated ARMA-GARCH Model

Goldman Elena () and Tsurumi Hiroki ()
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Goldman Elena: Lubin School of Business, Pace University
Tsurumi Hiroki: Department of Economics, Rutgers University

Studies in Nonlinear Dynamics & Econometrics, 2005, vol. 9, issue 2, 38

Abstract: We develop a new Markov Chain Monte Carlo procedure for a time series regression model truncated by upper and lower bounds. The regression error term is assumed to follow an ARMA--GARCH process. We use a convergence diagnostics with a simultaneous test of mean and covariance stationarity and discuss model selection criteria. Using MCMC procedure we test the purchasing power parity theory for the Japanese yen controlled to fluctuate in a narrow band and find that the theory is supported if double truncation is incorporated in estimation.

Date: 2005
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DOI: 10.2202/1558-3708.1166

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