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How Connected is the Global Sovereign Credit Risk Network?

Author

Listed:
  • Gorkem Bostanci

    (University of Pennsylvania)

  • Kamil Yilmaz

    () (Koc University)

Abstract

We apply the Diebold-Yilmaz connectedness index methodology on sovereign credit default swaps (SCDSs) to estimate the network structure of global sovereign credit risk. In particular, using the elastic net estimation method, we separately estimate networks of daily SCDS returns and volatilities for 38 countries between 2009 and 2014. Our results reveal striking differences between the network structures of returns and volatilities. In SCDS return networks, developing and developed countries stand apart in two big clusters. In the case of the SCDS volatility networks, however, we observe regional clusters among emerging market countries along with the developed-country cluster. We also show that global factors are more important than domestic factors in the determination of SCDS returns and volatilities. Finally, emerging market countries are the key generators of connectedness of sovereign credit risk shocks while severely problematic countries as well as developed countries play relatively smaller roles.

Suggested Citation

  • Gorkem Bostanci & Kamil Yilmaz, 2015. "How Connected is the Global Sovereign Credit Risk Network?," Koç University-TUSIAD Economic Research Forum Working Papers 1515, Koc University-TUSIAD Economic Research Forum.
  • Handle: RePEc:koc:wpaper:1515
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Vergote, Olivier, 2016. "Credit risk spillover between financials and sovereigns in the euro area during 2007-2015," Working Paper Series 1898, European Central Bank.
    2. Debarsy, Nicolas & Dossougoin, Cyrille & Ertur, Cem & Gnabo, Jean-Yves, 2018. "Measuring sovereign risk spillovers and assessing the role of transmission channels: A spatial econometrics approach," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 21-45.
    3. Lee, Hahn Shik & Lee, Woo Suk, 2019. "Cross-regional connectedness in the Korean housing market," Journal of Housing Economics, Elsevier, vol. 46(C).
    4. Andrew Castro & Neville Francis, 2018. "What Economic Factors Underlie Connectedness in Corporate Credit Default Swaps: News vs. Macroeconomic Factors?," 2018 Meeting Papers 586, Society for Economic Dynamics.
    5. Greenwood-Nimmo, Matthew & Huang, Jingong & Nguyen, Viet Hoang, 2019. "Financial sector bailouts, sovereign bailouts, and the transfer of credit risk," Journal of Financial Markets, Elsevier, vol. 42(C), pages 121-142.
    6. Neharika Sobti, 2018. "Domestic intermarket linkages: measuring dynamic return and volatility connectedness among Indian financial markets," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 45(4), pages 325-344, December.
    7. Ferhat Camlica & Didem Gunes & Etkin Ozen, 2017. "A Financial Connectedness Analysis for Turkey," Working Papers 1719, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    8. Mardi Dungey & John Harvey & Pierre Siklos & Vladimir Volkov, 2017. "Signed spillover effects building on historical decompositions," CAMA Working Papers 2017-52, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Antonakakis, Nikolaos & Gabauer, David, 2017. "Refined Measures of Dynamic Connectedness based on TVP-VAR," MPRA Paper 78282, University Library of Munich, Germany.
    10. Zhang, Weiping & Zhuang, Xintian & Lu, Yang, 2020. "Spatial spillover effects and risk contagion around G20 stock markets based on volatility network," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).

    More about this item

    Keywords

    Sovereign Credit Default Swaps; Sovereign Credit Risk; Systemic risk; Connectedness; Network Estimation; Lasso; Elastic Net; Vector Autoregression; Variance Decomposition.;

    JEL classification:

    • F34 - International Economics - - International Finance - - - International Lending and Debt Problems
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration

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