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Optimal Asset Allocation for a Mean-Variance-CVaR Insurer under Regulatory Constraints
School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai, China
School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai, China
School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai, China
- 1 School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai, China
- 2 School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai, China
- 3 School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai, China
American Journal of Industrial and Business Management·Volume 09 (2019)·Pages 1568–1580·Published 18 July 2019·DOI10.4236/ajibm.2019.97103
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Abstract
In this paper, we introduce the mean-variance-CVaR criteria into the study of asset allocation for insurers. Considering that the financial market consists of one risk-free asset and multiple risky assets with regulatory constraints, an optimization problem is established for an insurer with underwriting business. Based on practical financial and insurance data, an empirical study is carried out. The results show that the mean-variance-CVaR model is able to provide more potential investment strategies for an insurer. The regulatory policy released by China Insurance Regulatory Commission plays a key role in controlling investment risk for Chinese insurers.
KeywordsMean-Variance-CVaR CriteriaOptimal Asset AllocationInsuranceRegulatory Constraints
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