ARMA-GARCH Yaklaşımıyla USD/TRY Döviz Kurunun Modellenmesi ve Tahmini

Abstract

Döviz kuru fiyatlarının doğru bir şekilde tahmin edilmesi, yatırımcıların döviz kuru yatırımlarından maksimum kazanç elde etmelerine ve döviz kurları ile iş yapan firmaların bu tahminlere göre ticaretlerini yönetmelerine yardımcı olur. Bu nedenle döviz kuru fiyatlarının tahmini, hem yatırımcılar hem de döviz kurlarıyla iş yapan şirketler için çok önemlidir. Bu çalışmada, döviz kuru fiyatlarını modellemek için çeşitli GARCH (Genelleştirilmiş Otoregresif Koşullu Değişken Varyans) modelleri ile birleştirilmiş ARMA (Otoregresif Hareketli Ortalama) modelleri uygulanmıştır. Bu amaçla, volatilitenin döviz kuru fiyatları üzerindeki etkisini belirlemek için hataların hem simetrik hem de çarpık olarak dağıldığı ARMA-GARCH (M) modelleri ve ARMA-GARCH modelleri incelenmiştir. Uyum iyiliği ve tahmin doğruluğu performans kriterlerine göre belirlenen en uygun modelin, ilk olarak asimetrik ve doğrusal olmayan yapıları modelleyebilen ARMA-NAGARCH modeli ve ikinci olarak ise ARMA-GJRGARCH modeli olduğu sonucuna varılmıştır. Bununla birlikte ARMA-GARCH (M) modellerinin performansı, ARMA-GARCH modellerine göre daha düşük olması nedeniyle volatilitenin döviz kuru fiyatlarına etkisi zayıf bulunmuştur.

Keywords

• ARIMA
• GARCH Modelleri
• Döviz Kuru
• Öngörü
• Model Değerlendirme

Modeling and Forecasting of USD/TRY Exchange Rate Using ARMA-GARCH Approach

Abstract

Accurately predicting the exchange rate prices helps investors to obtain maximum profit from their exchange rate investments as well as to help firms conducting business with exchange rates to manage their trading based on these predictions. Therefore, the prediction of exchange rate prices is crucial for both investors and companies engaged in exchange rates. In this study, ARMA (Autoregressive Moving Average) models combined with various GARCH (Generalized Autoregressive Conditional Heteroscedasticity) models are applied to model exchange rate prices. For this purpose, ARMA-GARCH (M) models are investigated in order to determine the effect of volatility on exchange rate prices as well as ARMA-GARCH models in which the errors are distributed both symmetrically and skewed. It is concluded that the best fitted model which is determined based on the goodness of fit and estimation accuracy performance criteria, is firstly ARMA-NAGARCH model which can model asymmetric and non-linear structures and secondly ARMA-GJRGARCH model. However, since the performance of ARMA-GARCH (M) models is lower than ARMA-GARCH models, the effect of volatility on exchange rate prices is found to be weak.

Keywords

• ARIMA
• GARCH Models
• Exchange Rates
• Forecasting
• Model Evaluation

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