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A new modular neural network approach for exchange rate prediction

Author

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  • Ebtesam Zargany
  • Abbas Ahmadi

Abstract

A novel approach using modular neural networks to forecast exchange rates based on harmonic patterns in Forex market is introduced. The proposed approach employs three algorithms to predict price, validate its prediction and update the system. The model is trained by historical data using major currencies in Forex market. The proposed system's predictions were evaluated by comparing its results with a non-modular neural network. Results showed that the infrastructure market data consist of significant accurate relations that a single network cannot detect these relations and separate trained networks in specific tasks are needed. Comparison of modular and non-modular systems showed that modular neural network outperforms the other one.

Suggested Citation

  • Ebtesam Zargany & Abbas Ahmadi, 2015. "A new modular neural network approach for exchange rate prediction," International Journal of Electronic Finance, Inderscience Enterprises Ltd, vol. 8(2/3/4), pages 97-123.
    • Handle: RePEc:ids:ijelfi:v:8:y:2015:i:2/3/4:p:97-123
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