Stochastic Non‐Zero Differential Game Between Two Insurers Under CEV (E‐CEV) Model

This paper considers a stochastic non‐zero‐sum differential game between two competitive insurers. Both insurers are allowed to invest in one risk‐free asset and one risky asset, whose price dynamics follow the constant elasticity of variance (CEV) model, specifically the extended CEV (E‐CEV) model. At the same time, they are permitted to purchase proportional reinsurance to control the risks associated with individual claims. The goal of each insurer is to determine optimal strategies that maximize the expected utility of terminal wealth relative to that of their competitor. The Nash equilibrium reinsurance and investment strategies are explicitly derived using stochastic control theory techniques. Finally, we numerically examine the effect of model parameters on optimal investment and reinsurance strategies.

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Publication Details

Journal
Journal of Mathematics
Published
2025-01-01
DOI
https://doi.org/10.1155/jom/6936093
Primary Topic
Insurance and Financial Risk Management
Type
article
Field-Weighted Citation Impact
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article

Stochastic Non‐Zero Differential Game Between Two Insurers Under CEV (E‐CEV) Model

Winfrida Felix Mwigilwa
Journal of Mathematics
Insurance and Financial Risk Management
article

Stochastic Non‐Zero Differential Game Between Two Insurers Under CEV (E‐CEV) Model

Winfrida Felix Mwigilwa
article en

Abstract

This paper considers a stochastic non‐zero‐sum differential game between two competitive insurers. Both insurers are allowed to invest in one risk‐free asset and one risky asset, whose price dynamics follow the constant elasticity of variance (CEV) model, specifically the extended CEV (E‐CEV) model. At the same time, they are permitted to purchase proportional reinsurance to control the risks associated with individual claims. The goal of each insurer is to determine optimal strategies that maximize the expected utility of terminal wealth relative to that of their competitor. The Nash equilibrium reinsurance and investment strategies are explicitly derived using stochastic control theory techniques. Finally, we numerically examine the effect of model parameters on optimal investment and reinsurance strategies.

Journal of MathematicsVol. 2025(1)
Ardhi University (TZ)
Openalex Percentile: Top 84%
Insurance and Financial Risk Management
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