Döviz Kuru Getirisinin Tahmininde ELM, ARMA ve ARMA-GARCH Modellerinin Doğruluk Performansının Karşılaştırılması

Finansal zaman serilerinin getirilerinin modellenmesinde GARCH tipi modeller ve yapay zeka modelleri sıklıkla kullanılmaktadır. Bu çalışmada ARMA ve ARMA-GARCH modellerinin performansı, yapay zeka tekniklerinden ELM ile karşılaştırılmıştır. Performans karşılaştırmada dört adet hata ölçüm kriterinden yararlanılmıştır. Elde edilen bulgulara göre Euro ve GBP döviz kurlarının ELM modellerinin, ARMA ve ARMA-GARCH modellerine kıyasla daha üstün olduğu görülmüştür. Bu sonuca göre ele alınan dönem içerisinde, döviz kuru getirilerinin tahmininde ELM’ nin daha uygun olduğu söylenebilir

Anahtar Kelimeler:

ARMA, Yapay Sinir Ağları, ELM (Hızlı Öğrenen Makina), ARMA-GARCH

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

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.

Keywords:

ARMA, Artificial Neural Networks, Extreme Learning Machine, ARMA-GARCH,

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