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Bayesian Analysis of a Doubly Truncated ARMA-GARCH Model

Author

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  • Goldman Elena

    (Lubin School of Business, Pace University)

  • Tsurumi Hiroki

    (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.

Suggested Citation

  • Goldman Elena & Tsurumi Hiroki, 2005. "Bayesian Analysis of a Doubly Truncated ARMA-GARCH Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-38, June.
    • Handle: RePEc:bpj:sndecm:v:9:y:2005:i:2:n:5
    DOI: 10.2202/1558-3708.1166
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    Cited by:

    1. Elena Goldman, 2006. "Testing efficiency of the ruble-sterling foreign-exchange market under the gold standard," Empirical Economics, Springer, vol. 31(2), pages 449-477, June.
    2. Terence D.Agbeyegbe & Elena Goldman, 2005. "Estimation of threshold time series models using efficient jump MCMC," Economics Working Paper Archive at Hunter College 406, Hunter College Department of Economics, revised 2005.

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