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Tl/Euro And Leu/Euro Exchange Rates Forecasting With Artificial Neural Network

Author

Listed:
  • Cagdas Hakan ALADAG

    (Hacettepe University, Faculty of Science, Department of Statistics, Beytepe, 06800, Ankara,Turkey)

  • Miruna MAZURENCU MARINESCU

    (The Bucharest University of Economic Studies, Department of Statistics and Econometrics, Bucharest, Romania)

Abstract

Forecasting is a popular research topic that is getting more and more attention from researchers and practitioners in various fields. It is a wellknown fact thatexchange rate forecasting is an important and challenging task for both academic researchers and business practitioners. Therefore, various approaches have been suggested in the literature for exchange rate forecasting. The forecasting techniques range from Box-Jenkins models to artificial networks. Artificial neural networks have also been successfully applied to various time series forecasting problems since they can model both linear and non-linear parts of time series. In addition, artificial neural networks method does not require assumptions such as those of other commonly used conventional methods. In this study, artificial neural networks are utilized to forecast TL/EUR and LEU/EUR exchange rates. In order to reach high forecasting accuracy level, different artificial neural networks models are examined and the obtained best results are compared to those produced by Box-Jenkins models

Suggested Citation

  • Cagdas Hakan ALADAG & Miruna MAZURENCU MARINESCU, 2013. "Tl/Euro And Leu/Euro Exchange Rates Forecasting With Artificial Neural Network," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 2(2), pages 1-6, DECEMBER.
    • Handle: RePEc:aes:jsesro:v:2:y:2013:i:2:p:1-6
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    References listed on IDEAS

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    1. Cem Kadilar & Muammer Simsek & Cagdas Hakan Aladag, 2009. "Forecasting The Exchange Rate Series With Ann: The Case Of Turkey," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 9(1), pages 17-29, May.
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    Cited by:

    1. Jying-Nan Wang & Jiangze Du & Chonghui Jiang & Kin-Keung Lai, 2019. "Chinese Currency Exchange Rates Forecasting with EMD-Based Neural Network," Complexity, Hindawi, vol. 2019, pages 1-15, October.

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    More about this item

    Keywords

    Artificial neural networks; Box-Jenkins models; Exchange rates; Forecasting; Time series.;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

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