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Solvency II, or how to sweep the downside risk under the carpet

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  • Weber, Stefan

Abstract

Under Solvency II the computation of capital requirements is based on value at risk (V@R). V@R is a quantile-based risk measure and neglects extreme risks in the tail. V@R belongs to the family of distortion risk measures. A serious deficiency of V@R is that firms can hide their total downside risk in corporate networks, unless a consolidated solvency balance sheet is required for each economic scenario. In this case, they can largely reduce their total capital requirements via appropriate transfer agreements within a network structure consisting of sufficiently many entities and thereby circumvent capital regulation. We prove several versions of such a result for general distortion risk measures of V@R-type, explicitly construct suitable allocations of the network portfolio, and finally demonstrate how these findings can be extended beyond distortion risk measures. We also discuss why consolidation requirements cannot completely eliminate this problem. Capital regulation should thus be based on coherent or convex risk measures like average value at risk or expectiles.

Suggested Citation

  • Weber, Stefan, 2018. "Solvency II, or how to sweep the downside risk under the carpet," Insurance: Mathematics and Economics, Elsevier, vol. 82(C), pages 191-200.
    • Handle: RePEc:eee:insuma:v:82:y:2018:i:c:p:191-200
    DOI: 10.1016/j.insmatheco.2017.11.010
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    References listed on IDEAS

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    1. Philipp Keller, 2007. "Group Diversification," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 32(3), pages 382-392, July.
    2. Wang, Shaun, 1996. "Premium Calculation by Transforming the Layer Premium Density," ASTIN Bulletin, Cambridge University Press, vol. 26(1), pages 71-92, May.
    3. Volker Krätschmer & Alexander Schied & Henryk Zähle, 2014. "Comparative and qualitative robustness for law-invariant risk measures," Finance and Stochastics, Springer, vol. 18(2), pages 271-295, April.
    4. E. Jouini & W. Schachermayer & N. Touzi, 2008. "Optimal Risk Sharing For Law Invariant Monetary Utility Functions," Mathematical Finance, Wiley Blackwell, vol. 18(2), pages 269-292, April.
    5. Rama Cont & Romain Deguest & Giacomo Scandolo, 2010. "Robustness and sensitivity analysis of risk measurement procedures," Post-Print hal-00413729, HAL.
    6. Andreas Haier & Ilya Molchanov & Michael Schmutz, 2015. "Intragroup transfers, intragroup diversification and their risk assessment," Papers 1511.06320, arXiv.org, revised Nov 2016.
    7. Andreas Haier & Ilya Molchanov & Michael Schmutz, 2016. "Intragroup transfers, intragroup diversification and their risk assessment," Annals of Finance, Springer, vol. 12(3), pages 363-392, December.
    8. Volker Kratschmer & Alexander Schied & Henryk Zahle, 2012. "Comparative and qualitative robustness for law-invariant risk measures," Papers 1204.2458, arXiv.org, revised Jan 2014.
    9. Rama Cont & Romain Deguest & Giacomo Scandolo, 2010. "Robustness and sensitivity analysis of risk measurement procedures," Quantitative Finance, Taylor & Francis Journals, vol. 10(6), pages 593-606.
    10. Cui, Wei & Yang, Jingping & Wu, Lan, 2013. "Optimal reinsurance minimizing the distortion risk measure under general reinsurance premium principles," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 74-85.
    11. repec:dau:papers:123456789/361 is not listed on IDEAS
    12. Ruodu Wang, 2016. "Regulatory arbitrage of risk measures," Quantitative Finance, Taylor & Francis Journals, vol. 16(3), pages 337-347, March.
    13. Hans Föllmer & Stefan Weber, 2015. "The Axiomatic Approach to Risk Measures for Capital Determination," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 301-337, December.
    14. Christiansen, Marcus C. & Niemeyer, Andreas, 2014. "Fundamental Definition Of The Solvency Capital Requirement In Solvency Ii," ASTIN Bulletin, Cambridge University Press, vol. 44(3), pages 501-533, September.
    15. Paul Embrechts & Haiyan Liu & Ruodu Wang, 2017. "Quantile-Based Risk Sharing," Swiss Finance Institute Research Paper Series 17-54, Swiss Finance Institute.
    16. Damir Filipović & Michael Kupper, 2008. "Optimal Capital And Risk Transfers For Group Diversification," Mathematical Finance, Wiley Blackwell, vol. 18(1), pages 55-76, January.
    17. Song, Yongsheng & Yan, Jia-An, 2009. "Risk measures with comonotonic subadditivity or convexity and respecting stochastic orders," Insurance: Mathematics and Economics, Elsevier, vol. 45(3), pages 459-465, December.
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