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  Atıf Sayısı 1
 Görüntüleme 86
 İndirme 42
Ulke Kredi Notlarini Etkileyen Faktorlerin Cesitli Siniflandirma Analizleri Ile İncelenmesi
2019
Dergi:  
Ekoist: Journal of Econometrics and Statistics
Yazar:  
Özet:

Credit ratings are alphabetical indicators of credit risk provided by international rating agencies such as Standard and Poor’s, Moody’s, and Fitch. Since credit ratings are an assessment of a government’s ability to repay the public debt on time, investors, lenders, and market participants can make investment decisions in line with published reports. Therefore, the scores given are very important. In this study, the factors handled by Moody’s as sovereign ratings were determined using Logistic Regression Analysis and Artificial Neural Networks for the data of 85 countries for 2017 and the countries were divided into classes according to investment grade. As a result of the analysis, per capita GDP, inflation, general government primary balance / GDP, government debt, external payments, official forex reserves were found to be statistically significant. The correct classification rate of the logistic regression model was found to be 90%, whereas the correct classification rate of the artificial neural network model was found to be 88%. In August 2018, Moody’s downgraded Turkey’s credit rating from ‘’Ba2’’ to ‘’Ba3’’ and in June 2019 to B1 so the rating outlook dropped from stable to negative. Similarly, the analysis concluded that Turkey had been placed onto the list of non-investable countries.

Anahtar Kelimeler:

Review Of Factors Affecting Country Credit Ratings With Various Classification Analyses
2019
Yazar:  
Özet:

Credit ratings are alphabetical indicators of credit risk provided by international rating agencies such as Standard and Poor's, Moody's, and Fitch. Since credit ratings are an assessment of a government’s ability to repay the public debt on time, investors, lenders, and market participants can make investment decisions in line with published reports. Therefore, the scores given are very important. In this study, the factors handled by Moody's as sovereign ratings were determined using Logistic Regression Analysis and Artificial Neural Networks for the data of 85 countries for 2017 and the countries were divided into classes according to investment grade. As a result of the analysis, per capita GDP, inflation, general government primary balance / GDP, government debt, external payments, official forex reserves were found to be statistically significant. The correct classification rate of the logistic regression model was found to be 90%, while the correct classification rate of the artificial neural network model was found to be 88%. In August 2018, Moody's lowered Turkey's credit rating from 'Ba2' to 'Ba3' and in June 2019 to B1 so the rating outlook dropped from stable to negative. Similarly, the analysis concluded that Turkey had been placed onto the list of non-investable countries.

Anahtar Kelimeler:

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Ekoist: Journal of Econometrics and Statistics

Alan :   Sosyal, Beşeri ve İdari Bilimler

Dergi Türü :   Ulusal

Metrikler
Makale : 215
Atıf : 1.517
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