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Research Article | Open Access

A non-zero-sum reinsurance-investment game informed by alpha-maximin ambiguity-averse preferences

Yating Chen1Mi Chen1Xiang Hu2( )
School of Mathematics and Statistics & Key Laboratory of Analytical Mathematics and Applications (Ministry of Education) & Fujian Provincial Key Laboratory of Statistics and Artificial Intelligence, Fujian Normal University, Fuzhou 350117, China
School of Finance, Zhongnan University of Economics and Law, Nanhu Road, Wuhan 430073, China
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Abstract

This paper investigates the optimal reinsurance and investment problem with delay in the framework of the non-zero-sum stochastic differential game, where the game is considered between two insurers characterized by similar ambiguity-averse preferences. Both insurers maximize their respective α-maxmin mean-variance criterion in the market. The criterion is time-inconsistent and we derive the equilibrium reinsurance-investment strategies and value functions by the extended HJB equations. Finally, some numerical examples and sensitivity analysis are presented to demonstrate the effects of model parameters on the equilibrium strategy. We find the delay factor and the various attitudes of decision-makers toward ambiguity have a great influence on the final strategy. Moreover, the insurer's investment behavior will be more aggressive the more intense its competition with other insurers and the greater its ambiguity-seeking.

CLC number: 62P05, 91B30

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AIMS Mathematics
Pages 6649-6673

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Cite this article:
Chen Y, Chen M, Hu X. A non-zero-sum reinsurance-investment game informed by alpha-maximin ambiguity-averse preferences. AIMS Mathematics, 2026, 11(3): 6649-6673. https://doi.org/10.3934/math.2026275

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Received: 01 December 2025
Revised: 03 February 2026
Accepted: 27 February 2026
Published: 15 March 2026
©2026 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)