Forecasting The Exchange Rate Series With Ann: The Case Of Turkey
AbstractAs it is possible to model both linear and nonlinear structures in time series by using Artificial Neural Network (ANN), it is suitable to apply this method to the chaotic series having nonlinear component. Therefore, in this study, we propose to employ ANN method for high volatility Turkish TL/US dollar exchange rate series and the results show that ANN method has the best forecasting accuracy with respect to time series models, such as seasonal ARIMA and ARCH models. The suggestions about the details of the usage of ANN method are also made for the exchange rate of Turkey.
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Bibliographic InfoArticle provided by Department of Econometrics, Faculty of Economics, Istanbul University in its journal Istanbul University Econometrics and Statistics e-Journal.
Volume (Year): 9 (2009)
Issue (Month): 1 (May)
Activation function; ARIMA; ARCH; Artificial neural network; Chaotic series; Exchange rate; Forecasting; Time series;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- F31 - International Economics - - International Finance - - - Foreign Exchange
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
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