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Forecast evaluation of nonlinear models: the case of long-span real exchange rates

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Forecast evaluation of nonlinear models: the case of long-span real exchange rates. / Pavlidis, Efthymios; Paya, Ivan; Peel, David.
In: Journal of Forecasting, Vol. 31, No. 7, 2012, p. 580-595.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Pavlidis, E, Paya, I & Peel, D 2012, 'Forecast evaluation of nonlinear models: the case of long-span real exchange rates', Journal of Forecasting, vol. 31, no. 7, pp. 580-595. https://doi.org/10.1002/for.1247

APA

Pavlidis, E., Paya, I., & Peel, D. (2012). Forecast evaluation of nonlinear models: the case of long-span real exchange rates. Journal of Forecasting, 31(7), 580-595. https://doi.org/10.1002/for.1247

Vancouver

Pavlidis E, Paya I, Peel D. Forecast evaluation of nonlinear models: the case of long-span real exchange rates. Journal of Forecasting. 2012;31(7):580-595. Epub 2011 Sept 19. doi: 10.1002/for.1247

Author

Pavlidis, Efthymios ; Paya, Ivan ; Peel, David. / Forecast evaluation of nonlinear models : the case of long-span real exchange rates. In: Journal of Forecasting. 2012 ; Vol. 31, No. 7. pp. 580-595.

Bibtex

@article{31642702c89848a480bccd5a8344b23c,
title = "Forecast evaluation of nonlinear models: the case of long-span real exchange rates",
abstract = "This paper deals with the nonlinear modeling and forecasting of the dollar–sterling and franc–sterling real exchange rates using long spans of data. Our contribution is threefold. First, we provide significant evidence of smooth transition dynamics in the series by employing a battery of recently developed in-sample statistical tests. Second, we investigate the small-sample properties of several evaluation measures for comparing recursive forecasts when one of the competing models is nonlinear. Finally, we run a forecasting race for the post-Bretton Woods era between the nonlinear real exchange rate model, the random walk, and the linear autoregressive model. The nonlinear model outperforms all rival models in the dollar–sterling case but cannot beat the linear autoregressive in the franc–sterling. ",
keywords = "real exchange rate, nonlinearity , robust linearity tests , forecast evaluation , bootstrapping",
author = "Efthymios Pavlidis and Ivan Paya and David Peel",
year = "2012",
doi = "10.1002/for.1247",
language = "English",
volume = "31",
pages = "580--595",
journal = "Journal of Forecasting",
issn = "0277-6693",
publisher = "John Wiley and Sons Ltd",
number = "7",

}

RIS

TY - JOUR

T1 - Forecast evaluation of nonlinear models

T2 - the case of long-span real exchange rates

AU - Pavlidis, Efthymios

AU - Paya, Ivan

AU - Peel, David

PY - 2012

Y1 - 2012

N2 - This paper deals with the nonlinear modeling and forecasting of the dollar–sterling and franc–sterling real exchange rates using long spans of data. Our contribution is threefold. First, we provide significant evidence of smooth transition dynamics in the series by employing a battery of recently developed in-sample statistical tests. Second, we investigate the small-sample properties of several evaluation measures for comparing recursive forecasts when one of the competing models is nonlinear. Finally, we run a forecasting race for the post-Bretton Woods era between the nonlinear real exchange rate model, the random walk, and the linear autoregressive model. The nonlinear model outperforms all rival models in the dollar–sterling case but cannot beat the linear autoregressive in the franc–sterling.

AB - This paper deals with the nonlinear modeling and forecasting of the dollar–sterling and franc–sterling real exchange rates using long spans of data. Our contribution is threefold. First, we provide significant evidence of smooth transition dynamics in the series by employing a battery of recently developed in-sample statistical tests. Second, we investigate the small-sample properties of several evaluation measures for comparing recursive forecasts when one of the competing models is nonlinear. Finally, we run a forecasting race for the post-Bretton Woods era between the nonlinear real exchange rate model, the random walk, and the linear autoregressive model. The nonlinear model outperforms all rival models in the dollar–sterling case but cannot beat the linear autoregressive in the franc–sterling.

KW - real exchange rate

KW - nonlinearity

KW - robust linearity tests

KW - forecast evaluation

KW - bootstrapping

U2 - 10.1002/for.1247

DO - 10.1002/for.1247

M3 - Journal article

VL - 31

SP - 580

EP - 595

JO - Journal of Forecasting

JF - Journal of Forecasting

SN - 0277-6693

IS - 7

ER -