Year: 2025
Type: article
Abstract: This paper innovatively investigated the optimal investment and reinsurance problem with the objective of minimizing the probability of insolvency in a framework that simultaneously considers the ambiguity aversion perspective and inflation risk. Different from traditional research, this study assumed that insurance companies can not only purchase proportional reinsurance to minimize claims risk but also invest in the financial market, and examined the impact of inflation on the prices of risky assets through discounting. In particular, we incorporated the inflation effect into the pricing of risky assets and proposed a new investment model that takes inflation into account. The surplus process of an insurance company was modeled using a diffusion approximation model, and the financial market consisted of risk-free assets and risky assets, in which the price of risky assets was described by the constant elasticity of variance (CEV) model, which has an advantage in capturing market volatility compared to traditional models. Through the Radon-Nikodym derivative and Girsanov's theorem, we derived the wealth process of an insurance company from the perspective of ambiguity aversion. Based on the principle of dynamic programming, the HJB equation of the optimization problem was established, and the analytical solutions of the robust optimal investment and reinsurance strategies were obtained. Finally, the sensitivity of the model parameters to the theoretical results was analyzed through numerical simulation experiments, which provides quantitative guidance for insurance company's investment and reinsurance decisions in complex economic environments.
Source: AIMS Mathematics
DOI: 10.3934/math.2025642
Authors: Chen Wang, Hongmin Xiao
Institution: Northwest Normal University
Language: English
Topic: Probability and Risk Models
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,200
Awards: 随机动态死亡率模型的统计性质及应用研究, G732207954
OpenAlex ID: W4411537993
