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Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads

Author

Listed:
  • Rutger-Jan Lange

    (VU University Amsterdam, Erasmus University Rotterdam, the Netherlands)

  • Andre Lucas

    (VU University Amsterdam, the Netherlands)

  • Arjen H. Siegmann

    (VU University Amsterdam, the Netherlands)

Abstract

We compute joint sovereign default probabilities as coincident systemic risk indicators. Instead of commonly used CDS spreads, we use government bond yield data which provide a longer data history. We show that for the more recent sample period 2008--2015, joint default probabilities based on CDS and bond yield data yield similar results. For the period 1987-2008, only the bond yield data can be used to shed light on European sovereign systemic stress. We also show that simple averages of rolling pairwise correlations do not always yield intuitive systemic risk indicators.

Suggested Citation

  • Rutger-Jan Lange & Andre Lucas & Arjen H. Siegmann, 2016. "Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads," Tinbergen Institute Discussion Papers 16-064/IV, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20160064
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    References listed on IDEAS

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    8. Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2016. "Spillover dynamics for systemic risk measurement using spatial financial time series models," Journal of Econometrics, Elsevier, vol. 195(2), pages 211-223.
    9. André Lucas & Bernd Schwaab & Xin Zhang, 2014. "Conditional Euro Area Sovereign Default Risk," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 271-284, April.
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    12. Jun Pan & Kenneth J. Singleton, 2008. "Default and Recovery Implicit in the Term Structure of Sovereign CDS Spreads," Journal of Finance, American Finance Association, vol. 63(5), pages 2345-2384, October.
    13. Lucas, André & Zhang, Xin, 2016. "Score-driven exponentially weighted moving averages and Value-at-Risk forecasting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 293-302.
    14. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
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    Cited by:

    1. Hoang Nguyen & Audron.e Virbickait.e & M. Concepci'on Aus'in & Pedro Galeano, 2024. "Structured factor copulas for modeling the systemic risk of European and United States banks," Papers 2401.03443, arXiv.org.
    2. Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," International Journal of Forecasting, Elsevier, vol. 35(1), pages 25-44.
    3. Lumengo Bonga-Bonga & Mathias mandla Manguzvane, 2020. "Assessing the extent of contagion of sovereign credit risk among BRICS countries," Economics Bulletin, AccessEcon, vol. 40(2), pages 1017-1032.
    4. J. W. Muteba Mwamba & Mathias Manguzvane, 2020. "Contagion risk in african sovereign debt markets: A spatial econometrics approach," International Finance, Wiley Blackwell, vol. 23(3), pages 506-536, December.

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    More about this item

    Keywords

    systemic risk; conditional default; credit default swaps; bond yields;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • 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

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