Dynamic Ridge Polynomial Neural Networks in Exchange Rates Time Series Forecasting

  • Rozaida Ghazali
  • Abir Jaafar Hussain
  • Dhiya Al-Jumeily
  • Madjid Merabti
Conference paper

DOI: 10.1007/978-3-540-71629-7_15

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4432)
Cite this paper as:
Ghazali R., Hussain A.J., Al-Jumeily D., Merabti M. (2007) Dynamic Ridge Polynomial Neural Networks in Exchange Rates Time Series Forecasting. In: Beliczynski B., Dzielinski A., Iwanowski M., Ribeiro B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4432. Springer, Berlin, Heidelberg

Abstract

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.

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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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