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Journals / Business and Economics Research Journal / 2019 / Cilt: 10 - Sayı: 5

Measuring Systemic Risks in the Turkish Banking Sector

Serkan ŞENGÜL
ENSAR YILMAZ
Pages
1071–1084
DOI
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AI Summary & Key Takeaways

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

Secondly, both systemic risk measures (MES and ΔCoVaR) are analyzed to determine the relationships between some variables associated with bank characteristics (e.g., VaR, size and leverage ratio) and banks' systemic risk contributions, via simple panel data regression methods.

📌 3 Key Takeaways

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Objective & Hypothesis:This paper focused on measuring the systemic risks in Turkey’s banking sector by using two major measures that have been proposed in the literature as conditional value at risk (CoVaR) and marginal expected shortfall (MES).
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Key Findings & Data:In order to compute the contribution of banking sector to systemic risks, the MES and ΔCoVaR measures are estimated for the six Turkish banks, which are listed, on the Borsa Istanbul (BIST) during 2000–2016 period by using Engle’s dynamic conditional correlation model.
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Conclusion & Impact:Secondly, both systemic risk measures (MES and ΔCoVaR) are analyzed to determine the relationships between some variables associated with bank characteristics (e.g., VaR, size and leverage ratio) and banks' systemic risk contributions, via simple panel data regression methods.
🔬Design:Modeling & Simulation
📍Scope:2000–2016 Verileri
⚙️Variables:Domain Parameters

Özet

This paper focused on measuring the systemic risks in Turkey’s banking sector by using two major measures that have been proposed in the literature as conditional value at risk (CoVaR) and marginal expected shortfall (MES). In order to compute the contribution of banking sector to systemic risks, the MES and ΔCoVaR measures are estimated for the six Turkish banks, which are listed, on the Borsa Istanbul (BIST) during 2000–2016 period by using Engle’s dynamic conditional correlation model. The preliminary results of this study show that although the measures provide different rankings for the systemic risk contributions, they turn out to be qualitatively very similar in explaining the cross-sectional differences in systemic risk contributions. Secondly, both systemic risk measures (MES and ΔCoVaR) are analyzed to determine the relationships between some variables associated with bank characteristics (e.g., VaR, size and leverage ratio) and banks' systemic risk contributions, via simple panel data regression methods.

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Cite This Article

ŞENGÜL, S., YILMAZ, E. (2019). Measuring Systemic Risks in the Turkish Banking Sector. Business and Economics Research Journal, Cilt: 10 - Sayı: 5, 1071–1084. https://ajindex.com/articles/148200

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