注资后股息的最优梯度调整

IF 1.4 3区 数学 Q2 MATHEMATICS, APPLIED Mathematics of Operations Research Pub Date : 2024-08-13 DOI:10.1287/moor.2023.0102
Wenyuan Wang, Ran Xu, Kaixin Yan
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引用次数: 0

摘要

在本文中,我们研究了带有注资和梯级约束的最优股息问题,其股息支付率是不递减的。引入注资是为了消除破产的可能性。在 Cramér-Lundberg 风险模型下,该问题被表述为一个二维随机控制问题。通过应用粘性理论,我们证明了价值函数是相关汉密尔顿-雅各比-贝尔曼方程的唯一粘性解。为了获得分析结果,我们进一步研究了具有有限棘轮约束的问题,即股息率只有有限个可用值。我们证明,一般棘轮约束下的价值函数可以任意接近有限棘轮约束下的价值函数。最后,我们推导出了采用注资阈值型有限棘轮股利策略时的价值函数表达式,并证明了这种策略在某些凹性条件下的最优性。本文最后提供了各种情况下的数值示例。R. Xu 得到了国家自然科学基金[12201506 和 12371468]、江苏省高等学校自然科学基金[21KJB110024]和西安交通大学-利物浦大学科研发展基金[RDF-20-01-02]的资助。
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Optimal Ratcheting of Dividends with Capital Injection
In this paper, we investigate the optimal dividend problem with capital injection and ratcheting constraint with nondecreasing dividend payout rate. Capital injections are introduced in order to eliminate the possibility of bankruptcy. Under the Cramér–Lundberg risk model, the problem is formulated as a two-dimensional stochastic control problem. By applying the viscosity theory, we show that the value function is the unique viscosity solution to the associated Hamilton–Jacobi–Bellman equation. In order to obtain analytical results, we further study the problem with finite ratcheting constraint, where the dividend rate takes only a finite number of available values. We show that the value function under general ratcheting can be approximated arbitrarily closely by the one with finite ratcheting. Finally, we derive the expressions of value function when the threshold-type finite ratcheting dividend strategy with capital injection is applied, and we show the optimality of such a strategy under certain conditions of concavity. Numerical examples under various scenarios are provided at the end.Funding W. Wang was supported by the National Natural Science Foundation of China [Grants 12171405, 12271066, and 11661074] and the Fundamental Research Funds for the Central Universities of China [Grant 20720220044]. R. Xu was supported by the National Natural Science Foundation of China [Grants 12201506 and 12371468], the Natural Science Foundation of the Jiangsu Higher Education Institutions of China [Grant 21KJB110024], and Xi’an Jiaotong-Liverpool University Research Development Funding [Grant RDF-20-01-02].
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来源期刊
Mathematics of Operations Research
Mathematics of Operations Research 管理科学-应用数学
CiteScore
3.40
自引率
5.90%
发文量
178
审稿时长
15.0 months
期刊介绍: Mathematics of Operations Research is an international journal of the Institute for Operations Research and the Management Sciences (INFORMS). The journal invites articles concerned with the mathematical and computational foundations in the areas of continuous, discrete, and stochastic optimization; mathematical programming; dynamic programming; stochastic processes; stochastic models; simulation methodology; control and adaptation; networks; game theory; and decision theory. Also sought are contributions to learning theory and machine learning that have special relevance to decision making, operations research, and management science. The emphasis is on originality, quality, and importance; correctness alone is not sufficient. Significant developments in operations research and management science not having substantial mathematical interest should be directed to other journals such as Management Science or Operations Research.
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