On the Multi-Periodic Threshold Strategy for the Spectrally Negative Lévy Risk Model
As a crucial modeling tool for stochastic financial markets, the Lévy risk model effectively characterizes the evolution of risks during enterprise operations. Through dynamic evaluation and quantitative analysis of risk indicators under specific dividend- distribution strategies, this model can provide theoretical foundations for optimizing corporate capital allocation. Addressing the inadequate adaptability of traditional single-period threshold strategies in time-varying market environments, this paper proposes a dividend strategy based on multiperiod dynamic threshold adjustments. By implementing periodic modifications of threshold parameters, this strategy enhances the risk model’s dynamic responsiveness to market fluctuations and temporal variations. Within the framework of the spectrally negative Lévy risk model, this paper constructs a stochastic control model for multiperiod threshold dividend strategies. We derive the integro-differential equations for the expected present value of aggregate dividend payments before ruin and the Gerber–Shiu function, respectively. Combining the methodologies of the discounted increment density, the operator introduced by Dickson and Hipp, and the inverse Laplace transforms, we derive the explicit solutions to these integro-differential equations. Finally, numerical simulations of the related results are conducted using given examples, thereby demonstrating the feasibility of the analytical method proposed in this paper.
Authors
- Yu Zhao (ORCID: https://orcid.org/0000-0003-4198-6251)
- Zhang Liu (ORCID: https://orcid.org/0000-0002-1693-0646)
- Steve Shen
Institutions
- Jiangxi Agricultural University (CN)
Publication Details
- Journal
- Risks
- Published
- 2025-08-22
- DOI
- https://doi.org/10.3390/risks13090162
- Primary Topic
- Probability and Risk Models
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Jiangxi Province