Why do regime-switching models forecast so badly?

✍ Scribed by Robert Dacco; Steve Satchell

• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 196 KB
• Volume: 18
• Category: Article
• ISSN: 0277-6693
• DOI: 10.1002/(sici)1099-131x(199901)18:1<1::aid-for685>3.0.co;2-b

✦ Synopsis

Most non-linear techniques give good in-sample ®ts to exchange rate data but are usually outperformed by random walks or random walks with drift when used for out-of-sample forecasting. In the case of regime-switching models it is possible to understand why forecasts based on the true model can have higher mean squared error than those of a random walk or random walk with drift. In this paper we provide some analytical results for the case of a simple switching model, the segmented trend model. It requires only a small misclassi®cation, when forecasting which regime the world will be in, to lose any advantage from knowing the correct model speci®cation.

To illustrate this we discuss some results for the DM/dollar exchange rate. We conjecture that the forecasting result is more general and describes limitations to the use of switching models for forecasting. This result has two implications. First, it questions the leading role of the random walk hypothesis for the spot exchange rate. Second, it suggests that the mean square error is not an appropriate way to evaluate forecast performance for non-linear models.