Dynamic Ridge Polynomial Neural Networks in Exchange Rates Time Series Forecasting

  • Rozaida Ghazali
  • Abir Jaafar Hussain
  • Dhiya Al-Jumeily
  • Madjid Merabti
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4432)


This paper proposed a novel dynamic system which utilizes Ridge Polynomial Neural Networks for the prediction of the exchange rate time series. We performed a set of simulations covering three uni-variate exchange rate signals which are; the JP/EU, JP/UK, and JP/US time series. The forecasting performance of the novel Dynamic Ridge Polynomial Neural Network is compared with the performance of the Multilayer Perceptron and the feedforward Ridge Polynomial Neural Network. The simulation results indicated that the proposed network demonstrated advantages in capturing noisy movement in the exchange rate signals with a higher profit return.


Exchange Rate Forecast Horizon Normalize Mean Square Error Time Series Forecast Annualize Return 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Rozaida Ghazali
    • 1
  • Abir Jaafar Hussain
    • 1
  • Dhiya Al-Jumeily
    • 1
  • Madjid Merabti
    • 1
  1. 1.School of Computing & Mathematical Sciences, Liverpool John Moores University, L3 3AF LiverpoolEngland

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