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A one-step approach for determining the optimal aggregate capital reserve and allocation

Author

Listed:
  • Cai, Jun
  • Jia, Huameng
  • Wang, Ying

Abstract

In this paper, we introduce a new method for determining the optimal aggregate capital reserve and the corresponding optimal allocation through a one-step approach, allowing for the simultaneous consideration of aggregate and individual risks. In our one-step approach, both the aggregate capital and the allocation scheme are optimized to minimize an expected loss or cost function that accounts for these risks. Our findings provide insights into decision-makers’ attitudes toward commonly used capital requirement criteria and allocation principles, including VaR and CTE capital criteria, as well as VaR-based and CTE-based haircut allocation principles, and the CTE additive allocation principle. We also offer quantitative arguments explaining why the aggregate capital requirement and the corresponding allocation are optimal and specify the conditions under which they achieve optimality. Notably, our one-step optimal capital criteria can yield required reserves that meet the safety and budget requirements discussed in. Additionally, we provide numerical examples to illustrate our new approaches and compare them with standard methods commonly used in practice.

Suggested Citation

  • Cai, Jun & Jia, Huameng & Wang, Ying, 2026. "A one-step approach for determining the optimal aggregate capital reserve and allocation," Insurance: Mathematics and Economics, Elsevier, vol. 126(C).
  • Handle: RePEc:eee:insuma:v:126:y:2026:i:c:s0167668725001301
    DOI: 10.1016/j.insmatheco.2025.103183
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    References listed on IDEAS

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    1. Belles-Sampera, Jaume & Guillén, Montserrat & Santolino, Miguel, 2014. "GlueVaR risk measures in capital allocation applications," Insurance: Mathematics and Economics, Elsevier, vol. 58(C), pages 132-137.
    2. Jan Dhaene & Andreas Tsanakas & Emiliano A. Valdez & Steven Vanduffel, 2012. "Optimal Capital Allocation Principles," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 79(1), pages 1-28, March.
    3. Tiantian Mao & Jun Cai, 2018. "Risk measures based on behavioural economics theory," Finance and Stochastics, Springer, vol. 22(2), pages 367-393, April.
    4. Arthur Chiragiev & Zinoviy Landsman, 2007. "Multivariate Pareto portfolios: TCE-based capital allocation and divided differences," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2007(4), pages 261-280.
    5. Xu, Maochao & Hu, Taizhong, 2012. "Stochastic comparisons of capital allocations with applications," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 293-298.
    6. Zhou, Ming & Dhaene, Jan & Yao, Jing, 2018. "An approximation method for risk aggregations and capital allocation rules based on additive risk factor models," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 92-100.
    7. Cai, Jun & Wang, Ying, 2021. "Optimal capital allocation principles considering capital shortfall and surplus risks in a hierarchical corporate structure," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 329-349.
    8. Jan Dhaene & Mark Goovaerts & Rob Kaas, 2003. "Economic Capital Allocation Derived from Risk Measures," North American Actuarial Journal, Taylor & Francis Journals, vol. 7(2), pages 44-56.
    9. Cai, Jun & Wang, Ying & Mao, Tiantian, 2017. "Tail subadditivity of distortion risk measures and multivariate tail distortion risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 105-116.
    10. Zaks, Yaniv & Tsanakas, Andreas, 2014. "Optimal capital allocation in a hierarchical corporate structure," Insurance: Mathematics and Economics, Elsevier, vol. 56(C), pages 48-55.
    11. Landsman, Zinoviy & Makov, Udi & Shushi, Tomer, 2016. "Multivariate tail conditional expectation for elliptical distributions," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 216-223.
    12. Chen, Die & Mao, Tiantian & Pan, Xiaoqing & Hu, Taizhong, 2012. "Extreme value behavior of aggregate dependent risks," Insurance: Mathematics and Economics, Elsevier, vol. 50(1), pages 99-108.
    13. Shushi, Tomer & Yao, Jing, 2020. "Multivariate risk measures based on conditional expectation and systemic risk for Exponential Dispersion Models," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 178-186.
    14. Embrechts, Paul & Neslehová, Johanna & Wüthrich, Mario V., 2009. "Additivity properties for Value-at-Risk under Archimedean dependence and heavy-tailedness," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 164-169, April.
    15. Furman, Edward & Zitikis, Ricardas, 2008. "Weighted risk capital allocations," Insurance: Mathematics and Economics, Elsevier, vol. 43(2), pages 263-269, October.
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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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