FORECAST OF CDS PREMIUM WITH ANFIS METHOD: THE CASE OF TURKEY

Year 2021, , 1175 - 1197, 31.12.2021

Busra Kutlu Karabıyık

https://doi.org/10.17130/ijmeb.816813

Abstract

CDS premium expresses the risk levels and investability of countries. Investors who can correctly forecast the CDS premium can transfer their funds to reliable countries and correct sources. This study was forecasted by Turkey's CDS premium ANFIS method. Exchange rate, credit rating, interest rate, stock price, stock volatility and stock return were selected as input variables for the study. A daily data set covering the period 2015-2020 was used for the study. As a result of the input selection with the ANFIS method, the most effective input variables in estimating the CDS premium are; exchange rate, stock price and interest rate. After training the model, in order to test the consistency of the ANFIS model, CDS estimation was made with the test data set shown to the model for the first time, and it was observed that the ANFIS model CDS predictive values were very close to the actual CDS values. Finally, ANFIS prediction model and multiple linear regression analysis results were compared to evaluate the predictive performance of ANFIS model. It is concluded that the ANFIS prediction model has a better prediction performance.

Keywords

Multiple Linear Regression, Root Mean Square Error, CDS, ANFIS

ANFIS METODU İLE CDS PRİMİ TAHMİNLEMESİ: TÜRKİYE ÖRNEĞİ

Abstract

CDS primi ülkelerin risk derecelerini ve yatırım yapılabilirliklerini ifade etmektedir. CDS primini doğru tahmin edebilen yatırımcılar fonlarını güvenilir ülkelere ve doğru kaynaklara aktarabilmektedirler. Bu çalışmada Türkiye’nin CDS primi ANFIS metodu ile tahmin edilmiştir. Çalışmanın girdi değişkenleri olarak döviz kuru, kredi notu, faiz oranı, hisse senedi fiyatı, hisse senedi volatilitesi ve hisse senedi getirisi seçilmiştir. Çalışma için 2015-2020 dönemini kapsayan günlük bir veri seti kullanılmıştır. ANFIS metodu ile girdi seçimi neticesinde CDS priminin tahmin edilmesinde en etkili girdi değişkenlerin; döviz kuru, hisse senedi fiyatı ve faiz oranı oldukları tespit edilmiştir. Model eğitildikten sonra, ANFIS modelinin tutarlılığının sınanması için modele ilk defa gösterilen test veri seti ile CDS tahminlemesi yapılmış ve ANFIS modeli CDS tahmin değerlerinin gerçek CDS değerlerine oldukça yakın olduğu görülmüştür. Son olarak, ANFIS modelinin tahmin performansının değerlendirilmesi için ANFIS tahmin modeli ve çoklu doğrusal regresyon analizi sonuçları karşılaştırılmıştır. ANFIS tahmin modelinin daha iyi bir tahmin performansına sahip olduğu sonucunda ulaşılmıştır.

Keywords

Çoklu Doğrusal Regresyon, CDS, ANFIS, Ortalama Hata Karekökü

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