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CDS and equity markets’ volatility linkages: lessons from the EMU crisis

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Abstract

We investigate the means and volatility feedback loop hypotheses in terms of the informational flow among credit distress conditions, equity market expectations and investor sentiment to identify the transmission channels among sovereign CDS, equity and volatility markets. We examine core (Germany, France) and periphery (Portugal, Italy, Ireland, Spain, Greece) EMU countries for the 2009–2014 period. Our findings support the volatility feedback loop hypothesis among markets. Specifically, the major transmitters of shocks (volatility) were both the core and periphery sovereigns, while investor sentiment was the main receiver of volatility. Further, we found that, before the EMU debt crisis (2008–2009), the information flow started from the equity towards the CDS market but turned bidirectionally, post-debt crisis (2010–2014). Finally, geopolitics as a measure of macroeconomic risk, was found to respond more to sovereign risk than to bank risk in the EMU, and to the core sovereign/bank risk than to the periphery.

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Notes

  1. Since we use geopolitics as a macroeconomic uncertainty index we also built on to the limited literature strand on the channel of (policy or macroeconomic) uncertainty and CDS: eg. Wisniewski and Lambe (2015) argue that CDS spreads react to shocks in policy risk; Wang et al. (2019) associate positively the Economic Policy Uncertainty index to CDS.

  2. The EUROSTOXX50 Index is constructed from blue chip companies of sector leaders in the Eurozone: Austria, Belgium, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal and Spain. The EUROSTOXX 50 Volatility Index (VSTOXX) index exhibits the implied volatility given by the prices of the options with corresponding maturity, on the EUROSTOXX 50 Index.

  3. Since we use this framework as an additional measure of the cross-propagation mechanism we include the time-varying aspect, i.e., dynamic variance decompositions coming from VARs with rolling windows (250 days) and generalized variance decompositions as in Diebold and Yilmaz (2012). Since we utilize the factorization based on the ordering of variables: sovereign, equity, volatility markets we do need to apply the Diebold and Yilmaz (2012) generalized variance decomposition scheme based on Cholesky.

  4. Selection bias is expected given data availability for bank institutions and thus we use a representative sample of 3 per country.

  5. We employ two versions for periphery CDS portfolios for both sovereign and bank risk level; one involving Greek CDS series and the second one excludes them, given that Greece is considered the ground zero country for the Eurozone’s debt crisis. Essentially, we allow for a sensitivity analysis for the pool of periphery CDS portfolios. In the analysis we implemented the second case. All CDS data are scaled /100.

  6. The results are available upon request.

  7. We have also performed additional tests such as autoregressions and cross-correlations to validate the lead-lag relationships. In all cases, a 2- to 3-month lead was detected for the sentiment and GPR indicators followed by index changes. We found similar relationships for the cycle components. Hence, we can state that these indicators move in cycles and precede movements in equity indices (such as the RSTOCK).

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Authors and Affiliations

  1. Department of Business Administration, Athens University of Economics and Business, 76 Patission Street, 10434, Athens, Greece

    Theodoros Bratis & Georgios P. Kouretas

  2. Department of Finance, School of Economics and Business, The American College of Greece, 6 Gravias Street, 15342, Athens, Greece

    Nikiforos T. Laopodis

  3. IPAG Business School, 184 Boulevard Saint-Germain, 75006, Paris, France

    Georgios P. Kouretas

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  1. Theodoros Bratis
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  2. Nikiforos T. Laopodis
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  3. Georgios P. Kouretas
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Correspondence to Georgios P. Kouretas.

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The paper has benefited from helpful comments and discussions by seminar participants at Athens University of Economics and Business, Audencia Nantes School of Management, IPAG Business School, Imperial University London. We thank Angelos Antzoulatos, Manthos Delis, Dimitris Georgoutsos, Iftekhar Hasan, Alexandros Kontonikas and George Tavlas for many helpful comments and discussions. All remaining errors are our own.

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Appendix

See Tables 6, 7, 8.

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Bratis, T., Laopodis, N.T. & Kouretas, G.P. CDS and equity markets’ volatility linkages: lessons from the EMU crisis. Rev Quant Finan Acc 60, 1259–1281 (2023). https://doi.org/10.1007/s11156-023-01126-7

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