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Portfolio diversification in the sovereign credit swap markets

  • Analytical Models for Financial Modeling and Risk Management
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Abstract

We develop models for portfolio diversification in the sovereign credit default swaps (CDS) markets and show that, despite literature findings that sovereign CDS spreads are affected by global factors, there is sufficient idiosyncratic risk to be diversified. However, we identify regime switching in the times series of CDS spreads and spread returns, and the optimal diversified strategies can be regime dependent. The developed models trade off the CVaR risk measure against expected return, consistently with the statistical properties of spreads. We consider three investment strategies suited for different CDS market participants: for investors with long positions, speculators that hold uncovered long and short positions, and hedgers with covered long and short exposures. We use the models to illustrate that diversification pays in the CDS market. The models are also tested for active portfolio management in Eurozone core and periphery, and Central, Eastern and South-Eastern Europe countries, and the optimized portfolio results outperform the broad S&P/ISDA Eurozone Developed Nation Sovereign CDS index. The paper concludes by identifying open questions in developing integrated enterprise-wide risk management models using CDS.

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Notes

  1. See REUTERS SUMMIT-Investors overpaying for yield after years of low rates, Thu. Nov. 20, 2014, http://www.reuters.com/article/investment-yearend-yield-idUSL2N0T82YH20141120.

  2. The GAUSS code is available from Zhongjun Qu as “GAUSS code: Estimating and Testing Structural Changes in Multivariate Regressions” at http://people.bu.edu/qu/code.htm.

  3. \(\alpha \in (0,1]\) and all numerical experiments in this paper are carried out for \(\alpha =0.95\).

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Acknowledgements

Stavros Zenios is holder of a Marie Sklodowska-Curie fellowship funded from the European Union Horizon 2020 research and innovation programme under Grant Agreement No. 655092. The authors benefited from the comments of two anonymous referees and participants at the Macro seminars at the Finance Department of the Wharton School.

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Authors and Affiliations

  1. Department of Economics, Management and Statistics, University of Palermo, Palermo, IT, Italy

    Andrea Consiglio

  2. Department of Accounting and Finance, University of Cyprus, Nicosia, CY, Cyprus

    Somayyeh Lotfi & Stavros A. Zenios

  3. Norwegian School of Economics, Bergen, Norway

    Stavros A. Zenios

  4. Wharton Financial Institutions Center, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA

    Stavros A. Zenios

Authors
  1. Andrea Consiglio
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  2. Somayyeh Lotfi
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  3. Stavros A. Zenios
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Corresponding author

Correspondence to Stavros A. Zenios.

Appendices

Appendix A: Regime switching in the CDS spread levels of CESEE and Baltic countries

See Figs. 10 and 11.

Fig. 10
figure 10

Regime switching appears synchronized for these CESEE countries. a Bulgaria, b Croatia, c Czech Republic, d Hungary, e Poland, f Romania, g Slovakia, h Slovenia

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Fig. 11
figure 11

Regime switching appears idiosyncratic for the Baltic countries. a Estonia, b Latvia, c Lithuania

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Appendix B: CDS spread moments of all country groups under different regimes

See Tables 3, 4, 5, 6 and 7.

Table 3 CDS spread return moment estimates during each regime for eurozone core and periphery countries
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Table 4 CDS spread return moment estimates during each regime for CESEE countries
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Table 5 CDS spread return moment estimates during each regime for the Baltic countries
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Table 6 CDS spread return statistics for eurozone core and periphery countries under the common regimes
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Table 7 CDS spread return statistics for CESEE and Baltic countries under the common regimes
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Appendix C: Efficient frontiers under different regimes

See Figs. 12 and 13.

Fig. 12
figure 12

The relative position of efficient frontiers for each country group using strategy L is regime dependent. a Regime I. Turbulent, b Regime II. Crisis, c Regime III. Post crisis

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Fig. 13
figure 13

The relative position of efficient frontiers for each country group using strategy LS is regime dependent. a Regime I. Turbulent, b Regime II. Crisis, c Regime III. Post crisis

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Consiglio, A., Lotfi, S. & Zenios, S.A. Portfolio diversification in the sovereign credit swap markets. Ann Oper Res 266, 5–33 (2018). https://doi.org/10.1007/s10479-017-2565-5

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  • DOI: https://doi.org/10.1007/s10479-017-2565-5

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