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The out-of-sample forecasts of nonlinear long-memory models of the real exchange rate

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  • Sang-Kuck Chung

    (Department of Economics and International Trade, INJE University, Korea)

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    Abstract

    We consider a new time series model that can describe long memory and nonlinearity simultaneously and can be used to assess an extensive evaluation of the out-of-sample forecasting performance of the nonlinear long-memory model. Upon fitting it to the real exchange rate, we find that a parsimonious version of the model captures the salient features of the data rather well. We then use this nonlinear long-memory model to forecast dynamically out-of-sample over the sample period for OECD countries. Overall, we find clear evidence that favours the nonlinear long-memory model over any other estimated models. Copyright © 2006 John Wiley & Sons, Ltd.

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    Article provided by John Wiley & Sons, Ltd. in its journal International Journal of Finance & Economics.

    Volume (Year): 11 (2006)
    Issue (Month): 4 ()
    Pages: 355-370

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    Handle: RePEc:ijf:ijfiec:v:11:y:2006:i:4:p:355-370

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    Cited by:
    1. Boutahar, Mohamed & Mootamri, Imène & Péguin-Feissolle, Anne, 2009. "A fractionally integrated exponential STAR model applied to the US real effective exchange rate," Economic Modelling, Elsevier, vol. 26(2), pages 335-341, March.

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