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Forecasting Performance of Exponential Smooth Transition Autoregressive Exchange Rate Models

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  • Ahmad Baharumshah

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  • Venus Liew

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. Copyright Springer Science + Business Media, LLC 2006

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  • Ahmad Baharumshah & Venus Liew, 2006. "Forecasting Performance of Exponential Smooth Transition Autoregressive Exchange Rate Models," Open Economies Review, Springer, vol. 17(2), pages 235-251, April.
  • Handle: RePEc:kap:openec:v:17:y:2006:i:2:p:235-251
    DOI: 10.1007/s11079-006-6812-7
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    Cited by:

    1. Pede, Valerien O. & Florax, Raymond J.G.M. & Lambert, Dayton M., 2014. "Spatial econometric STAR models: Lagrange multiplier tests, Monte Carlo simulations and an empirical application," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 118-128.
    2. Liew, Venus Khim-Sen & Baharumshah, Ahmad Zubaidi & Habibullah, Muzafar Shah & Midi, Habshah, 2008. "Monetary exchange rate model: supportive evidence from nonlinear testing procedures," MPRA Paper 7293, University Library of Munich, Germany.
    3. Hu, Junjuan & Chen, Zhenlong, 2016. "A unit root test against globally stationary ESTAR models when local condition is non-stationary," Economics Letters, Elsevier, vol. 146(C), pages 89-94.
    4. Christian Grisse & Thomas Nitschka, 2016. "Exchange Rate Returns and External Adjustment: Evidence from Switzerland," Open Economies Review, Springer, vol. 27(2), pages 317-339, April.
    5. Pede, Valerien O. & Florax, Raymond J.G.M. & Holt, Matthew T., 2008. "Modeling Non-Linear Spatial Dynamics: A Family of Spatial STAR Models and an Application to U.S. Economic Growth," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6518, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Liew Khim Sen & Ahmad Zubaidi Baharumshah & Choo Wei Chong & Habshah Midi, 2003. "A Non-parametric Bootstrap Simulation Study in ESTAR (1) Model," GE, Growth, Math methods 0307005, EconWPA.
    7. Chan, Tze-Haw & Lye, Chun Teck & Hooy, Chee-Wooi, 2010. "Forecasting Malaysian Exchange Rate: Do Artificial Neural Networks Work?," MPRA Paper 26326, University Library of Munich, Germany.
    8. Rangan Gupta & Anandamayee Majumdar & Mark E. Wohar, 2017. "The Role of Current Account Balance in Forecasting the US Equity Premium: Evidence From a Quantile Predictive Regression Approach," Open Economies Review, Springer, vol. 28(1), pages 47-59, February.
    9. Venus Khim-Sen Liew & Zhuo Qiao & Wing-keung Wong, 2010. "Linearity and stationarity of G7 government bond returns," Economics Bulletin, AccessEcon, vol. 30(4), pages 2642-2655.

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