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Optimal allocations with distortion risk measures and mixed risk attitudes

Author

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  • Mario Ghossoub
  • Qinghua Ren
  • Ruodu Wang

Abstract

We study Pareto-optimal risk sharing in economies with heterogeneous attitudes toward risk, where agents' preferences are modeled by distortion risk measures. Building on comonotonic and counter-monotonic improvement results, we show that agents with similar attitudes optimally share risks comonotonically (risk-averse) or counter-monotonically (risk-seeking). We show how the general $n$-agent problem can be reduced to a two-agent formulation between representative risk-averse and risk-seeking agents, characterized by the infimal convolution of their distortion risk measures. Within this two-agent framework, we establish necessary and sufficient conditions for the existence of optimal allocations, and we identify when the infimal convolution yields an unbounded value. When existence fails, we analyze the problem under nonnegative allocation constraints, and we characterize optima explicitly, under piecewise-linear distortion functions and Bernoulli-type risks. Our findings suggest that the optimal allocation structure is governed by the relative strength of risk aversion versus risk seeking behavior, as intuition would suggest.

Suggested Citation

  • Mario Ghossoub & Qinghua Ren & Ruodu Wang, 2025. "Optimal allocations with distortion risk measures and mixed risk attitudes," Papers 2510.18236, arXiv.org.
  • Handle: RePEc:arx:papers:2510.18236
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    References listed on IDEAS

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    1. Dhaene, Jan & Denuit, Michel, 1999. "The safest dependence structure among risks," Insurance: Mathematics and Economics, Elsevier, vol. 25(1), pages 11-21, September.
    2. Jean-Gabriel Lauzier & Liyuan Lin & Ruodu Wang, 2024. "Risk Sharing, Measuring Variability, and Distortion Riskmetrics," Monash Econometrics and Business Statistics Working Papers 18/24, Monash University, Department of Econometrics and Business Statistics.
    3. Dhaene, J. & Denuit, M. & Goovaerts, M. J. & Kaas, R. & Vyncke, D., 2002. "The concept of comonotonicity in actuarial science and finance: theory," Insurance: Mathematics and Economics, Elsevier, vol. 31(1), pages 3-33, August.
    4. Ruodu Wang & Yunran Wei & Gordon E. Willmot, 2020. "Characterization, Robustness, and Aggregation of Signed Choquet Integrals," Mathematics of Operations Research, INFORMS, vol. 45(3), pages 993-1015, August.
    5. Herings, P.J.J. & Zhan, Yang, 2022. "Competitive Equilibria in Incomplete Markets with Risk Loving Preferences," Other publications TiSEM a8d79048-2351-4e73-97ce-9, Tilburg University, School of Economics and Management.
    6. Paul Embrechts & Haiyan Liu & Tiantian Mao & Ruodu Wang, 2017. "Quantile-Based Risk Sharing with Heterogeneous Beliefs," Swiss Finance Institute Research Paper Series 17-65, Swiss Finance Institute, revised Jan 2018.
    7. Aloisio Araujo & Alain Chateauneuf & Juan Pablo Gama & Rodrigo Novinski, 2018. "General Equilibrium With Uncertainty Loving Preferences," Econometrica, Econometric Society, vol. 86(5), pages 1859-1871, September.
    8. 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.
    9. Dhaene, J. & Denuit, M. & Goovaerts, M. J. & Kaas, R. & Vyncke, D., 2002. "The concept of comonotonicity in actuarial science and finance: applications," Insurance: Mathematics and Economics, Elsevier, vol. 31(2), pages 133-161, October.
    10. Mario Ghossoub & Qinghua Ren & Ruodu Wang, 2024. "Counter-monotonic Risk Sharing with Heterogeneous Distortion Risk Measures," Papers 2412.00655, arXiv.org.
    11. Beatrice Acciaio, 2007. "Optimal risk sharing with non-monotone monetary functionals," Finance and Stochastics, Springer, vol. 11(2), pages 267-289, April.
    12. Aloisio Araujo & Jean-Marc Bonnisseau & Alain Chateauneuf & Rodrigo Novinski, 2017. "Optimal sharing with an infinite number of commodities in the presence of optimistic and pessimistic agents," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 63(1), pages 131-157, January.
    13. Pauline Barrieu & Nicole El Karoui, 2005. "Inf-convolution of risk measures and optimal risk transfer," Finance and Stochastics, Springer, vol. 9(2), pages 269-298, April.
    14. 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.
    15. Tsanakas, Andreas, 2009. "To split or not to split: Capital allocation with convex risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 268-277, April.
    16. Paul Embrechts & Bin Wang & Ruodu Wang, 2015. "Aggregation-robustness and model uncertainty of regulatory risk measures," Finance and Stochastics, Springer, vol. 19(4), pages 763-790, October.
    17. Wang, Ruodu & Wei, Yunran, 2020. "Characterizing optimal allocations in quantile-based risk sharing," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 288-300.
    18. repec:dau:papers:123456789/361 is not listed on IDEAS
    19. Barrieu, Pauline & El Karoui, Nicole, 2005. "Inf-convolution of risk measures and optimal risk transfer," LSE Research Online Documents on Economics 2829, London School of Economics and Political Science, LSE Library.
    20. David Heath & Hyejin Ku, 2004. "Pareto Equilibria with coherent measures of risk," Mathematical Finance, Wiley Blackwell, vol. 14(2), pages 163-172, April.
    21. Jean-Gabriel Lauzier & Liyuan Lin & Peter Wakker & Ruodu Wang, 2024. "Optimal risk sharing, equilibria, and welfare with empirically realistic risk attitudes," Papers 2401.03328, arXiv.org, revised Oct 2025.
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