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Journals / Yönetim ve Ekonomi Araştırmaları Dergisi / 2026 / Cilt: 20 Sayı: 1

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

Mustafa Tevfik Kartal(Borsa İstanbul)0000-0001-8038-8241
Serpil Kılıç Depren(YILDIZ TECHNICAL UNIVERSITY)0000-0003-4737-7131
Özer Depren(Yapı Kredi Bank)0000-0001-8948-5742
Pages
354–374
Publication Date
2022-03-22
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

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.

📌 3 Key Takeaways

🎯
Objective & Hypothesis: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.
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Key Findings & Data: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.
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Conclusion & Impact: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.
🔬Design:Modeling & Simulation
📍Scope:2011 Verileri
⚙️Variables:Sovereign CDS Spreads · Machine Learning Algorithms · eXtreme Gradient Boosting

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.

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Cite This Article

Kartal, M. T., Depren, S. K., Depren, Ö. (2022). SOVEREIGN CREDIT DEFAULT SWAP (CDS) SPREADS CHANGES IN VARIOUS ECONOMIC CONJUNCTURES: EVIDENCE FROM TURKEY BY MACHINE LEARNING ALGORITHMS. Yönetim ve Ekonomi Araştırmaları Dergisi, Cilt: 20 Sayı: 1, 354–374. https://doi.org/10.11611/yead.1076897

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