Performances of non-linear smooth transition autoregressive and linear autoregressive models in forecasting the Ringgit-Yen rate

This study compares the performance of Smooth Transition Autoregressive (STAR) non-linear model and the conventional linear Autoregressive (AR) time series model in forecasting the Ringgit-Yen rate. Based on standard linearity test procedure, we find empirical evidence that the adjustment of the Ringgit-Yen rate towards its long-run Purchasing Power Parity equilibrium follows a non-linearity path. In terms of forecasting ability, results of this study suggest that both the STAR and AR models exceed or match the performance of SRW model based mean absolute forecast error (MAFE) mean absolute percentage forecast error (MAPFE) and mean square forecast error (RMSFE). The results also show that the STAR model outperforms the AR model, its linear competitor. Our finding is consistent with the emerging line of research that emphasized the importance of allowing non-linearity in the adjustment of exchange rate toward its long run equilibrium.

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