How Well the Ringgit-Yen Rate Fits the Non-linear Smooth Transition Autoregressive and Linear Autoregressive Models

Liew, Venus Khim-Sen and Ahmad Zubaidi, Baharumshah (2002) How Well the Ringgit-Yen Rate Fits the Non-linear Smooth Transition Autoregressive and Linear Autoregressive Models. Pertanika Journal of Social Science and Humanities, 10 (2). pp. 1-15. ISSN 0128-7702

[img]
Preview
PDF
How Well the Ringgit-Yen Rate Fits (abstract).pdf

Download (15kB) | Preview

Abstract

This study compares the forecasting performance between Smooth Transition Autoregressive (STAR) non-linear model and the conventional linear Autoregressive (AR) time series model using the simple random walk (SRW) model as the standard reference model. To accomplish this objective, quarterly frequency exchange rate data, which is well known for its non-linear adjustment towards purchasing power parity equilibrium path is employed. The empirical results 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 outperform the AR model, its linear competitor. This is consistent with the emerging line of research that emphasised the importance of allowing non-linearity in the adjustment of exchange rate toward its long run equilibrium.

Item Type: E-Article
Uncontrolled Keywords: Autoregressive, Smooth Transition Autoregressive, non-linear time series, forecasting accuracy, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak
Subjects: H Social Sciences > HB Economic Theory
Divisions: Academic Faculties, Institutes and Centres > Faculty of Economics and Business
Depositing User: ROSSAZANA AB RAHIM
Date Deposited: 27 Nov 2017 06:21
Last Modified: 27 Nov 2017 06:21
URI: http://ir.unimas.my/id/eprint/18597

Actions (For repository members only: login required)

View Item View Item