Forecasting performance of exponential smooth transition autoregressive exchange rate models
Baharumshah, Ahmad Zubaidi 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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Official URL: http://dx.doi.org/10.1007/s11079-006-6812-7
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. © Springer Science + Business Media, LLC 2006.
|Keyword:||Autoregressive; Forecasting accuracy; Nonlinear time series; Smooth transition autoregressive|
|Subject:||Purchasing power parity|
|Subject:||Foreign exchange rates|
|Faculty or Institute:||Faculty of Economics and Management|
|Deposited By:||Azwana Abdul Rahman|
|Deposited On:||25 Oct 2011 15:41|
|Last Modified:||25 Oct 2011 15:41|
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