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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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    File URL: http://eaf.ku.edu.tr/sites/eaf.ku.edu.tr/files/erf_wp_1515.pdf
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    References listed on IDEAS

    as
    1. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    2. FrancisX. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    3. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    4. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    5. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    6. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    7. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2015. "Estimating Global Bank Network Connectedness," Koç University-TUSIAD Economic Research Forum Working Papers 1512, Koc University-TUSIAD Economic Research Forum.
    8. Jens Hilscher & Yves Nosbusch, 2010. "Determinants of Sovereign Risk: Macroeconomic Fundamentals and the Pricing of Sovereign Debt," Review of Finance, European Finance Association, vol. 14(2), pages 235-262.
    9. Alter, Adrian & Beyer, Andreas, 2014. "The dynamics of spillover effects during the European sovereign debt turmoil," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 134-153.
    10. Wang, Ping & Moore, Tomoe, 2012. "The integration of the credit default swap markets during the US subprime crisis: Dynamic correlation analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(1), pages 1-15.
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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. 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.
    4. 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.
    5. Antonakakis, Nikolaos & Gabauer, David, 2017. "Refined Measures of Dynamic Connectedness based on TVP-VAR," MPRA Paper 78282, University Library of Munich, Germany.

    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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