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Nonlinear time series and neural-network models of exchange rates between the US dollar and major currencies

Author

Listed:
  • Allen, D.E.
  • McAleer, M.J.
  • Peiris, S.
  • Singh, A.K.

Abstract

This paper features an analysis of major currency exchange rate movements in relation to the US dollar, as constituted in US dollar terms. Euro, British pound, Chinese yuan, and Japanese yen are modelled using a variety of non- linear models, including smooth transition regression models, logistic smooth transition regressions models, threshold autoregressive models, nonlinear autoregressive models, and additive nonlinear autoregressive models, plus Neural Network models. The results suggest that there is no dominating class of time series models, and the different currency pairs relationships with the US dollar are captured best by neural net regression models, over the ten year sample of daily exchange rate returns data, from August 2005 to August 2015.

Suggested Citation

  • Allen, D.E. & McAleer, M.J. & Peiris, S. & Singh, A.K., 2015. "Nonlinear time series and neural-network models of exchange rates between the US dollar and major currencies," Econometric Institute Research Papers EI2015-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Handle: RePEc:ems:eureir:79217
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    References listed on IDEAS

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    More about this item

    Keywords

    non linear models; time series; non-parametric; smooth-transition regression models; neural networks; GMDH shell;

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F3 - International Economics - - International Finance
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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