Beating the Random Walk in Central and Eastern Europe by Survey Forecasts
This paper investigates the forecasting ability of survey data on exchange rate expectations with multiple forecast horizons. The survey forecasts are on the exchange rates of five Central and Eastern European currencies: Czech Koruna, Hungarian Forint, Polish Zloty, Romanian Leu and Slovakian Koruna. First, different term-structure models are fitted on the survey forecasts. Then, the forecasting performances of the fitted forecasts are compared. The fitted forecasts for the 5 months horizon and beyond are proved to be significantly better than the random walk on the pooled data of the five currencies. The best performing term-structure model is the one that assumes an exponential relationship between the forecast and the forecast horizon, and has time-varying parameters.
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