Bayesian Analysis of a Doubly Truncated ARMA-GARCH Model

Elena Goldman, Lubin School of Business, Pace University
Hiroki Tsurumi, Department of Economics, Rutgers University

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.

Recommended Citation

Elena Goldman and Hiroki Tsurumi (2005) "Bayesian Analysis of a Doubly Truncated ARMA-GARCH Model", Studies in Nonlinear Dynamics & Econometrics: Vol. 9: No. 2, Article 5.
http://www.bepress.com/snde/vol9/iss2/art5

Related Files

goldman_datacode.zip (18 kB)
Data and code

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