Using artificial neural network and a statistical method for the estimation of Euro/Turkish Lira exchange rate
Oktay Taş, Emir Yakak, Umut Uğurlu · Pressacademia · 2018
Purpose-The aim of this study is to estimate the movement of the Euro/Turkish lira currency with a statistical method and artificial neural networks methods and to compare the performance of these two methods.Methodology-In the study, two different forecasting methods were used to estimate the dollar exchange rate.In both models, the Euro/Turkish lira daily rate for the last 10 years was used and the daily dollar rate for the last 1 year was estimated.Findings-The mean absolute errors found by artificial neural networks method are about 2% less than those found by the statistical method.Since estimates are made using the "rolling window" method for each of the 365 days, it can be said that the results obtained are "robust".Conclusion-It has been observed that the Artificial Neural Networks model yields more successful results than the statistical model, although both models used in the research can forecast the dollar exchange rate with a certain success.In future studies it may be possible to increase the estimation performance by adding the exogenous variables to the model.