SOVEREIGN CREDIT DEFAULT SWAP (CDS) SPREADS CHANGES IN VARIOUS ECONOMIC CONJUNCTURES: EVIDENCE FROM TURKEY BY MACHINE LEARNING ALGORITHMS

Year 2022, , 354 - 374, 22.03.2022

Mustafa Tevfik Kartal , Serpil Kılıç Depren , Özer Depren

https://doi.org/10.11611/yead.1076897

Cited By: 1

Abstract

The study aims to define the sources of Turkey’s sovereign CDS spread changes to develop policies that stabilize CDS spreads since they have a volatile and increasing trend, especially in the last two years. In this context, monthly data of 13 factors related to international, macroeconomic, and market between 2011/1 and 2019/12 are used by dividing the dataset into three periods as the full period (2011-2019), the stability period (2011-2017), and the macroeconomic turbulent period (2018-2019) and performing 4 different machine learning algorithms. The empirical results prove that (i) Treasury bond interest rate should be lower than 8% in the stability period and gold prices should be lower than TL 5.500 in the macroeconomic turbulent period to have low-level CDS spreads; (ii) NPL volume has no significant effect on in any period examined; (iii) the significance of factors on sovereign CDS spreads vary over the periods.

Keywords

Sovereign CDS Spreads, Machine Learning Algorithms, eXtreme Gradient Boosting, Turkey

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