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摘要翻译：
本文发展了寻找最优股利支付和再保险政策的数值方法。本文提出了广义奇异控制的盈余和贴现收益函数，其中盈余由一个同时受正则和奇异控制的制度转换过程来建模。为了逼近值函数和最优控制，利用马尔可夫链逼近技术构造了一个具有两个分量的离散时间受控马尔可夫链。给出了剩余过程和值函数逼近序列收敛性的证明。给出了比例再保险和超额损失再保险的实例，说明了数值方法的适用性。
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英文标题：
《Numerical Solutions of Optimal Risk Control and Dividend Optimization
Policies under A Generalized Singular Control Formulation》
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作者：
Zhuo Jin, George Yin, and Chao Zhu
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最新提交年份：
2011
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分类信息：
一级分类：Quantitative Finance 数量金融学
二级分类：Computational Finance 计算金融学
分类描述：Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法，包括蒙特卡罗，偏微分方程，格子和其他数值方法，并应用于金融建模
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一级分类：Mathematics 数学
二级分类：Optimization and Control 优化与控制
分类描述：Operations research, linear programming, control theory, systems theory, optimal control, game theory
运筹学，线性规划，控制论，系统论，最优控制，博弈论
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一级分类：Mathematics 数学
二级分类：Probability 概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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一级分类：Quantitative Finance 数量金融学
二级分类：Risk Management 风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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英文摘要：
This paper develops numerical methods for finding optimal dividend pay-out and reinsurance policies. A generalized singular control formulation of surplus and discounted payoff function are introduced, where the surplus is modeled by a regime-switching process subject to both regular and singular controls. To approximate the value function and optimal controls, Markov chain approximation techniques are used to construct a discrete-time controlled Markov chain with two components. The proofs of the convergence of the approximation sequence to the surplus process and the value function are given. Examples of proportional and excess-of-loss reinsurance are presented to illustrate the applicability of the numerical methods.
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PDF链接：
https://arxiv.org/pdf/1111.2584
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