Abstract
We propose a Bayesian procedure to estimate a switching regression in which the number of switching points (i.e. join points) is not known. We apply the Bayesian procedure to a regression model for the yen-dollar exchange rate using monthly data from January 1973 to June 1992. We identify three join points in January 1978, September 1988, and March 1990. We compare the post-sample forecast performances of our switching regression model to those of other regression models. The post-sample forecasts show that the Bayesian switching model performs better than the other models.
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Tsurumi, H., Chen, C.L. Estimating unknown join points: Determination of the yen-dollar exchange rate. Financial Engineering and the Japanese Markets 1, 55–66 (1994). https://doi.org/10.1007/BF02425209
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DOI: https://doi.org/10.1007/BF02425209