Forecasting TRY/USD Exchange Rate with Various Artificial Neural Network Models Cover Image

Forecasting TRY/USD Exchange Rate with Various Artificial Neural Network Models
Forecasting TRY/USD Exchange Rate with Various Artificial Neural Network Models

Author(s): Cagatay Bal, Serdar Demir
Subject(s): ICT Information and Communications Technologies
Published by: UIKTEN - Association for Information Communication Technology Education and Science
Keywords: Activations functions; artificial neural networks; Exchange rates; Forecasting; Learning algorithms; Performance measures; TRY/USD

Summary/Abstract: Exchange rate forecasting is one of the most common subjects among the forecasting problem field. Researchers and academicians from many different disciplines proposed various approaches for better exchange rate forecasting. In recent years, for solving the stated forecasting problem artificial neural networks have become successful tool to obtain solutions. Many different artificial neural networks have been used, developed and still developing for even better and trustable forecasts. In this study, TRY/USD exchange rate forecasting is modeled with different learning algorithms, activations functions and performance measures. Various Artificial Neural Network (ANN) models for better forecasting were investigated, compared and the obtained forecasting results interpreted respectively. The results of the application show that Variable Learning Rate Backpropagation learning algorithm with tan-sigmoid activation function has the best performance for TRY/USD exchange rate forecasting.

  • Issue Year: 6/2017
  • Issue No: 1
  • Page Range: 11-16
  • Page Count: 6
  • Language: English