Döviz Kurları Öngörüsünde Parasal Model ve Arima Modelleri: Türkiye Örneği

Bu çalışma ile döviz kuru öngörüsü için geliştirilen, yapısal modellerden parasal yaklaşım modeli ile yapısal modellere rakip olan zaman serisi analizi yöntemlerinden ARIMA modeli kullanılarak Türkiye için döviz kuru öngörüsü yapılması ve bu iki yöntemin öngörü güçlerinin karşılaştırılması amaçlanmıştır. Bunu gerçekleştirmek için 1980-2001 dönemi için Türkiye’nin en fazla ticaret yaptığı beş ülke (A.B.D., Almanya, İngiltere, Fransa, İtalya) ile Türk lirasına ilişkin reel döviz kurunun aylık verileri kullanılarak parasal yaklaşım modeli ve zaman serisi modellerine dayanan döviz kuru öngörüleri tahmin edilmiştir. Bu iki modelin öngörü güçlerinin karşılaştırması sonucunda parasal modeldeki değişkenlerin döviz kurunu açıklamada etkisi olduğu görülmesine karşın, ARIMA modelinin Parasal modele göre öngörü gücünün daha iyi olduğu sonucuna varılmıştır

Anahtar Kelimeler:

Döviz Kuru, Parasal Model, ARIMA Modeli, Öngörü

In this study by using the monetary approach which is a structural model and a rival to the structural models the ARIMA model which is one of the time series analyzing method that was developed to forecasting the foreign exchange has been aimed to compare the forecasting powers of the two methods and the foreign exchange rate forecasting of Turkey. In order to realize this, for the period of 1980-2001, the monthly real foreign exchange rate datas have been used related to the Turkish Liras and the five countries which Turkey has the most trade with. (U.S.A, Germany, England, France, Italy). The datas belong to variables have been got from the data bases of the International Financial Statistics (IFS) and the OECD Main Economic Indicators. As the series monthly, they have been used in the analysis after being purified from the seasonal effect and taking their natural logarithm. In all of the analysis, it was utilized from the Econometric Views packet program. As comparing the forecasting powers of the two models, firstly utilized from the error terms statistics. Also to learn which model is better the regression coefficient of the forecasting values directed ex post and the real values have been tested by investigating. At the end of the all analysis that has been done, it has been concluded that the ARIMA model’s forecasting power is better according to the monetary model.

Keywords:

Exchange Rate, Monetary Model, ARIMA Model, Forecasting,

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