Forecasting performance of exponential smooth transition autoregressive exchange rate models

A. Z. Baharumshah and Liew, Venus Khim Sen (2006) Forecasting performance of exponential smooth transition autoregressive exchange rate models. Open Economies Review, 17 (2). pp. 235-251. ISSN 0923-7992

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Abstract

This paper compares the forecasting performance of the Smooth Transition Autoregressive (STAR) model with the conventional linear Autoregressive (AR) and Simple Random Walk (SRW) models. The empirical analysis was conducted using quarterly data for the yen-based currencies of six major East Asian countries. We discovered strong evidence on nonlinear mean reversion in deviation from purchasing power parity (PPP). The results suggest that both the STAR and AR models outperform or at least match the performance of the SRW model. The results also show that the STAR model outperforms the AR model, its linear competitor in a 14-quarter forecast horizon. This finding is consistent with the emerging line of research that emphasizes the importance of allowing nonlinearity in the adjustment of exchange rate.

Item Type:	Article
Keyword:	Autoregressive, Smooth transition autoregressive, Nonlinear time series, Forecasting accuracy
Subjects:	H Social Sciences > HG Finance > HG1-9999 Finance > HG3810-4000 Foreign exchange. International finance. International monetary system
Department:	SCHOOL > Labuan School of Informatics Science
Depositing User:	ADMIN ADMIN
Date Deposited:	04 Oct 2011 17:37
Last Modified:	30 Jun 2021 23:16
URI:	https://eprints.ums.edu.my/id/eprint/1110

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