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Comparing Accuracy Performance of ELM, ARMA and ARMA-GARCH Model In Predicting Exchange Rate Return

Author

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  • Nimet Melis Esenyel
  • Melda Akın

Abstract

GARCH type models and artificial intelligence models are frequently used in the modeling of financial time series returns. In this study, the performance of ARMA and ARMA-GARCH models was compared with ELM. Four error measurement criteria were used in the performance comparison. According to the findings, ELM models of Euro and GBP exchange rates returns are superior to the ARMA and ARMA-GARCH models. According to this result, it can be said that ELM, one of the artificial intelligence-based methods, is more suitable for estimating the exchange rate returns during the period covered.

Suggested Citation

  • Nimet Melis Esenyel & Melda Akın, 2017. "Comparing Accuracy Performance of ELM, ARMA and ARMA-GARCH Model In Predicting Exchange Rate Return," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 5(1), pages 1-14, June.
    • Handle: RePEc:anm:alpnmr:v:5:y:2017:i:1:p:1-14
    DOI: http://dx.doi.org/10.17093/alphanumeric.298658
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    More about this item

    Keywords

    ARMA; ARMA-GARCH; Artificial Neural Networks; Extreme Learning Machine;
    All these keywords.

    JEL classification:

    • 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

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