Optimal Claiming on Vehicle Insurance

Insurance companies charge reduced premiums to motorists who go through a period of one or more years without making a claim. When an accident occurs the insured frequently finds himself with the option of either making a claim and reverting to a higher premium or paying for the repair himself. Most motorists operate an informal system of "no-claim limits", whereby they only claim for repairs which exceed a certain cost.In this paper it is shown how, under reasonable assumptions regarding the rate of accidents and the distribution of repair costs, optimal no-claim limits can be determined. These minimise the long run average cost of premiums and repairs and show significant savings over the case where all claims are made. The effect of an "excess clause", whereby the insured agrees to pay a first amount of any claim is also studied, and rules for determining whether it is profitable to accept such a clause are presented in the form of a graph.     

Optimal Claiming in an Automobile Insurance System with Bonus-Malus Structure

A motorist involved in an accident will have to decide whether to claim from his insurance company or not when he is at fault. An optimal decision rule can only be determined in the light of future developments and future decisions, since the consequences of claiming or not claiming are felt in the subsequent year's premiums. In this paper, optimal no-claim limits are determined for a common Dutch type of insurance policy with bonus-malus structures, using generalized Markovian programming. The computational results are given for various values of the expected number of accidents per year.     

Vehicle Scheduling Revisited

Several published results for vehicle scheduling algorithms are based on rounded inter-customer distances. This gives overall distances which vary somewhat from actual distances (presented here), and there appears to be a downward bias. Care should be taken in comparing results based on rounded inter-customer distances with those based on real distances.     

保险公司的最优投资策略选择

保险公司传统的投资模型只允许保险公司在保费收取与赔付之间的时滞范围内投资,即投资期间不收取保费也不允许任何赔付发生。本文研究的模型克服了传统模型的不足,投资期间可以收取保费也可以接受索赔。模型在保证保险公司实现目标收益的条件下,使得公司面临的风险最小。另外在模型中引进一个安全投资比例,即保险公司以此比例的财富用于风险投资是相对安全的。通过求解模型,得到保险公司的最优投资策略和风险最小情况下用于投资的财富的比率,并讨论了保费、索赔对投资的影响;另外还得到保险公司投资组合的有效边界,并讨论了有效边界的动态性质;最后用实际数据对保险公司如何选择安全投资比例、如何分配投资资金进行了模拟。     

Optimal Cross Hedging of Insurance Derivatives

Abstract

We consider insurance derivatives depending on an external physical risk process, for example, a temperature in a low dimensional climate model. We assume that this process is correlated with a tradable financial asset. We derive optimal strategies for exponential utility from terminal wealth, determine the indifference prices of the derivatives, and interpret them in terms of diversification pressure. Moreover, we check the optimal investment strategies for standard admissibility criteria. Finally, we compare the static risk connected with an insurance derivative to the reduced risk due to a dynamic investment into the correlated asset. We show that dynamic hedging reduces the risk aversion in terms of entropic risk measures by a factor related to the correlation.     

人寿保险中的最优缴费模型

精算数学中 ,将自然保费制转化为现今的均衡保费制 ,精算师并未考虑投保人的最优缴费策略 .本文采用最优化方法对定期寿险保单的缴费方式进行了分析 .得出 ,当精算师计算保费的利息与“银行储蓄利率”相等时 ,均衡收缴保费是保险人的最优策略 ,否则应分别采用递增或递减缴费策略 .     

Optimal Tracking for an Insurance Model

Abstract

In this article, we assume that we have a number of candidate insurance models for describing a risk process. Suppose that in each model the risk process is a function of the states of some Markov chains. Based on observing the history of the premiums and claims processes we propose dynamics whose solutions indicate the likelihoods of each candidate model.     

中国汽车保险的最优索赔策略

在大多数国家,汽车保险中使用的无索赔奖励系统(BMS)只考虑了索赔次数,而我国2006年7月开始实施的A、B、C三个车险条款中的C条款是与索赔额有关的BMS,所以需要对现有的最优索赔策略模型进行推广。本文应用马尔科夫最优化原理推广了汽车保险的最优索赔策略模型,并对我国现行的三个车险条款的最优索赔策略问题进行了实证研究。     

具有违约风险的人寿保险的最优定价

本文探讨具有违约风险的人寿保险的最优定价.我们从Black-Scholes的期权定价模型出发,考虑风险管理和准备金的要求,根据一次支付和均衡支付这两种不同的假设分别建立两个优化模型,并且借助于优化技术获得最优解.数量化分析结果表明,两个模型的最优价格对于利息率参数以及非索赔成本的变化都不敏感.这说明这两个模型是稳定的,而且是实用的.     

Optimal Feedback Control for Linear Systems with Input Delays Revisited

The design problem of optimal feedback control for linear systems with input delays is very important in many engineering applications. Usually, the linear systems with input delays are firstly converted into linear systems without delays, and then all the design procedures are based on the delay-free linear systems. In this way, the feedback controllers are not designed in terms of the original states. This paper presents some new closed-form formula in terms of the original states for the delayed optimal feedback control of linear systems with input delays. We firstly reveal the essential role of the input delay in the optimal control design of the linear system with a single input delay: the input delay postpones the action of the optimal control only. Based on this fact, we calculate the delayed optimal control and find that the optimal state can be represented by a simple closed-form formula, so that the delayed optimal feedback control can be obtained in a simple way. We show that the delayed feedback gain matrix can be “smaller” than that for the controlled system with zero input delay, which implies that the input delay can be considered as a positive factor. In addition, we give a general formula for the delayed optimal feedback control of time-variant linear systems with multiple input delays. To show the effectiveness and advantages of the main results, we present five illustrative examples with detailed numerical simulation and comparison.     

政府对科技保险的最优财政补贴规模研究

运用机制设计理论建立信息激励模型,在完全信息、不完全信息、不完全信息加入可调整项三种情形下,对科技保险进行险种划分,得到在不同信息激励影响下的政府对保险公司的最优补贴规模.运用期望收益理论,针对科技研发成功或不成功、科技企业投保或不投保的情形,建立政府补贴投保企业的最优补贴规模模型,得出政府对投保企业补贴规模的限制范围.     

保险公司的最优投资和再保险策略

在保险公司既可以做证券(股票和债券)投资,同时又采取比例再保险策略的情况下,通过对经典的Cramér-Lundberg保险公司盈余过程模型的连续扩散近似,利用动态规划原理分别得出了在破产概率最小和终值期望效用最大两种目标函数下,保险公司的最优投资和最优再保策略的显式解和对应的目标函数值.对两种目标函数下的最优策略做了比较研究.     

基于破产理论的我国极端洪水保险风险组合随机优化模型

极端洪水给人类造成了巨大损失,极端洪水保险是分散极端洪水风险的一种有效手段.基于政府、市场和公众合作的极端洪水保险模式是适合我国国情的.在此模式下,建立政府有效参与的保险公司和保险区域风险组合随机优化模型,保证极端洪水保险的有效供给和需求,为合理厘定保险费率提供理论基础.随机优化模型中充分考虑了保险公司的破产概率、稳定性经营和保险区域的灾后恢复能力.最后给出了此模型的收敛性定理.     

跳—扩散过程下带实业项目的保险最优决策

为了考虑一类带有实业项目投资的保险最优投资策略问题,假定保险公司盈余服从跳-扩散过程,在最小化保险公司破产概率准则下,使用动态规划原理建立了线性消费率下保险资金最优投资选择模型,通过求解HJB方程得到了最优投资决策和最小破产概率的解析式解,最后分析了线性消费、索赔强度、索赔额以及实业项目投资额对最小化破产概率和最优投资策略的影响.     

双险种最优再保险策略

本文对双险种风险模型,在一险种采取比例再保险,另一险种采取超出损失再保险策略下,得到调节系数与再保险自留水平之间的函数关系式,在理赔额为指数分布和Erlang(2)分布的条件下,得到最优比例再保险和超出损失再保险的自留水平,以及调节系数最大值。     

车灯线光源的优化设计

通过运用光学成像原理和空间解析几何上向量和平面的一些知识,将立体中的几何问题转化为平面几何问题来解决,对车灯线光源进行优化设计,建立模型.通过数学软件计算线光源长度,使线光源的功率最小.对得到的线光源长度,在有标尺的坐标系中画出测试屏上反射光的亮区,最后本文讨论该设计规范的合理性.     

车险费率厘定精算技术的研究与应用评述

精算技术为中国车险市场费率改革提供必要支持,可以确保费率厘定的科学性与合理性。首先,本文系统梳理了车险分类风险费率厘定精算统计模型的发展历程,并回顾参数估计方法。其次,论述了车险个体风险费率厘定的精算模型与方法,并重点评述了信度理论与奖惩系统的研究。进而,归纳出车险费率厘定精算统计模型的研究热点与发展方向。最后,指明现有研究对中国车险费率厘定精算方法的启示,并提出相关建议。     

Optimal Exercise Strategies for Operational Risk Insurance via Multiple Stopping Times

In this paper we demonstrate how to develop analytic closed form solutions to optimal multiple stopping time problems arising in the setting in which the value function acts on a compound process that is modified by the actions taken at the stopping times. This class of problem is particularly relevant in insurance and risk management settings and we demonstrate this on an important application domain based on insurance strategies in Operational Risk management for financial institutions. In this area of risk management the most prevalent class of loss process models is the Loss Distribution Approach (LDA) framework which involves modelling annual losses via a compound process. Given an LDA model framework, we consider Operational Risk insurance products that mitigate the risk for such loss processes and may reduce capital requirements. In particular, we consider insurance products that grant the policy holder the right to insure k of its annual Operational losses in a horizon of T years. We consider two insurance product structures and two general model settings, the first are families of relevant LDA loss models that we can obtain closed form optimal stopping rules for under each generic insurance mitigation structure and then secondly classes of LDA models for which we can develop closed form approximations of the optimal stopping rules. In particular, for losses following a compound Poisson process with jump size given by an Inverse-Gaussian distribution and two generic types of insurance mitigation, we are able to derive analytic expressions for the loss process modified by the insurance application, as well as closed form solutions for the optimal multiple stopping rules in discrete time (annually). When the combination of insurance mitigation and jump size distribution does not lead to tractable stopping rules we develop a principled class of closed form approximations to the optimal decision rule. These approximations are developed based on a class of orthogonal Askey polynomial series basis expansion representations of the annual loss compound process distribution and functions of this annual loss.     

Optimal Reinsurance and Dividend Strategies Under the Markov-Modulated Insurance Risk Model

In this article, we consider the optimal reinsurance and dividend strategy for an insurer. We model the surplus process of the insurer by the classical compound Poisson risk model modulated by an observable continuous-time Markov chain. The object of the insurer is to select the reinsurance and dividend strategy that maximizes the expected total discounted dividend payments until ruin. We give the definition of viscosity solution in the presence of regime switching. The optimal value function is characterized as the unique viscosity solution of the associated Hamilton–Jacobi–Bellman equation and a verification theorem is also obtained.