Bowley solution of a mean-variance game in insurance

被引:16
|
作者
Li, Danping [1 ]
Young, Virginia R. [2 ]
机构
[1] East China Normal Univ, Sch Stat, Key Lab Adv Theory & Applicat Stat & Data Sci MOE, Shanghai 200062, Peoples R China
[2] Univ Michigan, Dept Math, Ann Arbor, MI 48109 USA
来源
基金
中国国家自然科学基金;
关键词
Bowley solution; Stackelberg equilibrium; Equilibrium insurance strategy; Mean-variance premium principle; Mean-variance payoff functional; OPTIMAL REINSURANCE; EQUILIBRIUM; TREATIES;
D O I
10.1016/j.insmatheco.2021.01.009
中图分类号
F [经济];
学科分类号
02 ;
摘要
In this paper, we compute the Bowley solution of a one-period, mean-variance Stackelberg game in insurance, in which a buyer and a seller of insurance are the two players, and they act in a certain order. First, the seller offers the buyer any (reasonable) indemnity policy in exchange for a premium computed according to the mean-variance premium principle. Then, the buyer chooses an indemnity policy, given that premium rule. To optimize the choices of the two players, we work backwards. Specifically, given any pair of parameters for the mean-variance premium principle, we compute the optimal insurance indemnity to maximize a mean-variance functional of the buyer's terminal wealth. Then, we compute the parameters of the mean-variance premium principle to maximize the seller's expected terminal wealth, given the foreknowledge of what the buyer will choose when offered that premium principle. This pair of optimal choices, namely, the optimal indemnity and the optimal parameters of the premium principle, constitute a Bowley solution of this Stackelberg game. We illustrate our results via numerical examples. (C) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页码:35 / 43
页数:9
相关论文
共 50 条
  • [31] On the nature of mean-variance spanning
    Cheung, C. Sherman
    Kwan, Clarence C. Y.
    Mountain, Dean C.
    FINANCE RESEARCH LETTERS, 2009, 6 (02) : 106 - 113
  • [32] A Mean-Variance Optimization Algorithm
    Erlich, Istvan
    Venayagamoorthy, Ganesh K.
    Worawat, Nakawiro
    2010 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2010,
  • [33] Revisiting mean-variance optimization
    Uysal, E
    Trainer, FH
    Reiss, J
    JOURNAL OF PORTFOLIO MANAGEMENT, 2001, 27 (04): : 71 - +
  • [34] A mean-variance acreage model
    Fang, Ming
    Perng, Cherng-tiao
    APPLICABLE ANALYSIS, 2022, 101 (04) : 1211 - 1224
  • [35] On robust mean-variance portfolios
    Pinar, Mustafa C.
    OPTIMIZATION, 2016, 65 (05) : 1039 - 1048
  • [36] A Generalisation of the Mean-Variance Analysis
    Zakamouline, Valeri
    Koekebakker, Steen
    EUROPEAN FINANCIAL MANAGEMENT, 2009, 15 (05) : 934 - 970
  • [37] Tests of Mean-Variance Spanning
    Kan, Raymond
    Zhou, GuoFu
    ANNALS OF ECONOMICS AND FINANCE, 2012, 13 (01): : 139 - 187
  • [38] MEAN-VARIANCE PORTFOLIO THEORY
    DEDEK, O
    POLITICKA EKONOMIE, 1992, 40 (04) : 525 - 549
  • [39] Minimum Norm Solution of the Markowitz Mean-variance Portfolio Optimization Model
    Moosaei, Hossein
    Hladik, Milan
    38TH INTERNATIONAL CONFERENCE ON MATHEMATICAL METHODS IN ECONOMICS (MME 2020), 2020, : 383 - 388
  • [40] Beyond Mean-Variance Markowitz Portfolio Selection: A Comparison of Mean-Variance-Skewness-Kurtosis Model and Robust Mean-Variance Model
    Gubu, La
    Rashif, Muhamad
    ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, 2024, 58 (01): : 298 - 313