PREDICTING USD/ TL EXCHANGE RATE IN TURKEY: THE LONG-SHORT TERM MEMORY APPROACH

Authors : Ayten YAĞMUR, Zeynep KARAÇOR, Fatih MANGIR, Abdulrazak Bawa YUSSİF

Pages : 935-949

Doi:10.30798/makuiibf.1097568

View : 135 | Download : 205

Publication Date : 2023-08-02

Article Type : Research Paper

Abstract :The prediction of the exchange rate time series has been quite challenging but is an essential process. This is as a result of the inherent noise and the volatile behavior in these series. Time series analysis models such as ARIMA have been used for this purpose. However, these models are limited due to the fact that they are not able to explain the non-linearity as well as the stochastic properties of foreign exchange rates. In order to perform a more accurate exchange rate prediction, deep-learning methods have been employed withremarkable rates of success. In this paper, we apply the Long-Short Term Memory Neural Network to predict the USD/TL exchange rate in Turkey. The result from this paper indicates that the Long-Short Term Memory Neural Network deep learning method gives higher prediction accuracy compared to the Auto Regressive Integrated Moving Average and the Multilayer Perception Neural Network models.
Keywords : Tahmin, Döviz Kuru, Zaman Serileri, ARIMA, LSTM, MLP