Assessing the Forecastibility of ESTAR Model: Some Evidence from Ringgit/Yen Rate

Ahmad Zubaidi Baharumshah (), Venus Khim-Sen Liew () and Evan Lau ()

The Icfai Journal of Applied Economics, 2007, vol. VI, issue 1, pages 7-19

Abstract: This paper endeavors to contribute to the debate on the relevance of non-linear forecasts in the financial markets. To that end, this study forecasts the Yen-based Ringgit by using the Exponential Smooth Transition Autoregressive (ESTAR) model. When formally assessed for forecast accuracy, the results reveal that the ESTAR out-of-sample predictors statistically outperform both the linear AR and random walk models at standard significant levels. The hypothesis of equal forecasting accuracy between ESTAR model and the random walk model is formally rejected based on the Fisher sign test. This paper offers evidence on the ability to forecast exchange rates using non-linear methods and concludes that linear models are not always the optimal for forecasting exchange rate as there is some forecast accuracy that can be gained by considering the non-linearity inherent in the exchange rate.

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