一类索赔为复合Poisson-Geometric过程双险种风险模型的破产概率

对索赔为复合Poisson-Geometric过程的双险种风险模型进行研究,给出了当初始资本为0及索赔额为指数分布下破产概率的具体表达式,并利用鞅方法得到了最终破产概率满足的Lundberg不等式和一般公式.     

一类推广的复合Poisson-Geometric风险模型破产概率

本文主要研究了一类推广的复合Poisson-Geometric风险模型.利用鞅方法和微分方法,获得破产概率公式和破产概率的积分方程,并给出了保单价和索赔额服从指数分布时破产概率的显式表达式.     

带干扰的索赔次数为复合Poisson-Geometric过程的负风险和模型

引进带干扰的索赔次数为复合Poisson-Geometric过程的负风险和模型,给出该模型的破产概率所满足的积分-微分方程及解析式.     

复合Poisson-Geometric风险模型Gerber-Shiu折现惩罚函数

本文研究赔付为复合Poisson-Geometric过程的风险模型,首先得到了Gerber-Shiu折现惩罚期望函数所满足的更新方程,然后在此基础上推导出了破产概率和破产即刻前赢余分布等所满足的更新方程,再运用Laplace方法得出了破产概率的Pollazek-Khinchin公式,最后根据Pollazek-Khinchin公式,直接得出了当索赔分布服从指数分布的情形下破产概率的显示表达式.     

索赔相关的Poisson-Geometric风险模型研究

研究了保费到达为复合Poisson-Geometric过程的索赔相关风险模型,通过模型转化得到了破产概率的表达式及其上界.进一步地,将模型推广为带干扰的情形,得到了相应的结果.     

索赔次数为复合Poisson-Geometric过程下的破产概率和最优投资和再保险策略

本文对索赔次数为复合Poisson-Geometric过程的风险模型,在保险公司的盈余可以投资于风险资产,以及索赔购买比例再保险的策略下,研究使得破产概率最小的最优投资和再保险策略.通过求解相应的Hamilton-Jacobi-Bellman方程,得到使得破产概率最小的最优投资和比例再保险策略,以及最小破产概率的显示表达式.     

索赔次数为复合Poisson-Geometric过程的双险种风险模型

对索赔次数为复合Poisson-Geometric过程的双险种风险模型进行研究,给出了生存概率所满足的积分方程、指数分布下的具体表达式及有限时间内的积分—微分方程,并利用鞅方法得到了最终破产概率的Lundberg不等式和一般公式.     

改进后的复合Poisson-Geometric风险模型Gerber-Shiu折现惩罚函数

在考虑到因保费收入和通货膨胀等随机干扰的影响,以及将多余资本用于投资来提高赔付能力的基础上,文章对复合Poisson-Geometric风险模型做进一步推广,建立以保费收入服从复合Poisson过程,理赔量服从复合Poisson-Geometric过程的带投资的干扰风险模型,针对该风险模型,应用全期望公式,推导了Gerber-Shiu折现惩罚函数满足的更新方程,进而得到了在破产时盈余惩罚期望,破产赤字和破产概率满足的更新方程.并以保费额和索赔额均服从指数分布为例,给出破产概率满足的微分方程.以及通过数值例子,分析了初始准备金额,投资金额及保费额等对保险公司最终破产概率的影响.结论为经营者或决策者对各种金融或保险风险进行定量分析和预测提供了理论依据.     

索赔次数为复合Poisson-Geometric过程的常利率风险模型的罚金函数

讨论了常利率下索赔次数为复合Poisson-Geometric过程的风险模型的罚金函数,得到了罚金函数的期望所满足的积分方程,并由所得到的积分方程推出了破产概率所满足的积分方程,初始盈余为0时,得到了罚金函数的期望及破产概率的精确解.     

马氏风险过程

研究了一般马氏风险过程,它是经典风险过程的拓广.具有大额索赔的风险过程用此马氏风险模型来描述是适合的.在此模型中,索赔到达过程由一点过程来描述,该点过程是一马氏跳过程从0到t时间段内的跳跃次数.主要研究了此风险模型的破产概率,得到了破产概率满足的积分方程,并应用本文引入的广更新方法,得到了破产概率的收敛速度上界.     

Analysis of the Gerber-Shiu function and dividend barrier problems for a risk process with two classes of claims

In this paper we consider a risk model with two independent classes of insurance risks. We assume that the two independent claim counting processes are, respectively, the Poisson and the generalized Erlang(2) process. We prove that the Gerber-Shiu function satisfies some defective renewal equations. Exact representations for the solutions of these equations are derived through an associated compound geometric distribution and an analytic expression for this quantity is given when the claim severities have rationally distributed Laplace transforms. Further, the same risk model is considered in the presence of a constant dividend barrier. A system of integro-differential equations with certain boundary conditions for the Gerber-Shiu function is derived and solved. Using systems of integro-differential equations for the moment-generating function as well as for the arbitrary moments of the discounted sum of the dividend payments until ruin, a matrix version of the dividends-penalty is derived. An extension to a risk model when the two independent claim counting processes are Poisson and generalized Erlang(ν), respectively, is considered, generalizing the aforementioned results.     

A modified insurance risk process with uncertainty

An insurance risk process is traditionally considered by describing the claim process via a renewal reward process and assuming the total premium to be proportional to the time with a constant ratio. It is usually modeled as a stochastic process such as the compound Poisson process, and historical data are collected and employed to estimate the corresponding parameters of probability distributions. However, there exists the case of lack of data such as for a new insurance product. An alternative way is to estimate the parameters based on experts’ subjective belief and information. Therefore, it is necessary to employ the uncertain process to model the insurance risk process. In this paper, we propose a modified insurance risk process in which both the claim process and the premium process are assumed to be renewal reward processes with uncertain factors. Then we give the inverse uncertainty distribution of the modified process at each time. On this basis, we derive the ruin index which has an explicit expression based on given uncertainty distributions.     

A micro-level claim count model with overdispersion and reporting delays

The accurate estimation of outstanding liabilities of an insurance company is an essential task. This is to meet regulatory requirements, but also to achieve efficient internal capital management. Over the recent years, there has been increasing interest in the utilisation of insurance data at a more granular level, and to model claims using stochastic processes. So far, this so-called ‘micro-level reserving’ approach has mainly focused on the Poisson process.In this paper, we propose and apply a Cox process approach to model the arrival process and reporting pattern of insurance claims. This allows for over-dispersion and serial dependency in claim counts, which are typical features in real data. We explicitly consider risk exposure and reporting delays, and show how to use our model to predict the numbers of Incurred-But-Not-Reported (IBNR) claims. The model is calibrated and illustrated using real data from the AUSI data set.     

A new uncertain insurance model with variational lower limit

Uncertainty theory provides a new tool to deal with uncertainty. The paper employs it to propose a new uncertain insurance model with variational lower limit, and gives a ruin index and uncertainty distribution for the uncertain insurance risk process that claim process is a renewal reward process. The model extends and improves uncertain insurance model presented by Liu. Finally, it also provides examples to illustrate the effectiveness of the model.     

广义负相依一般风险模型中有限时破产概率的估计及数值模拟

本文研究了一类带利率的重尾相依风险模型, 其中索赔额是一列上广义负相依随机变量, 索赔到达过程是一般的非负整值过程, 并且独立于索赔额序列, 保费收入过程是一个一般的非负非降随机过程. 我们考虑了两种情况, 其一是索赔额、索赔到达过程及保费收入过程相互独立, 其二是累积折现保费收入总量的尾概率可以被索赔额的尾概率高阶控制, 得到了保险公司有限时破产概率的渐近估计,并且给出了相应的数值模拟, 验证了理论结果的合理性.     

Bayesian modelling of financial guarantee insurance

In this paper we model the claim process of financial guarantee insurance, and predict the pure premium and the required amount of risk capital. The data used are from the financial guarantee system of the Finnish statutory pension scheme. The losses in financial guarantee insurance may be devastating during an economic depression (i.e., deep recession). This indicates that the economic business cycle, and in particular depressions, must be taken into account in modelling the claim amounts in financial guarantee insurance. A Markov regime-switching model is used to predict the frequency and severity of future depression periods. The claim amounts are predicted using a transfer function model where the predicted growth rate of the real GNP is an explanatory variable. The pure premium and initial risk reserve are evaluated on the basis of the predictive distribution of claim amounts. Bayesian methods are applied throughout the modelling process. For example, estimation is based on posterior simulation with the Gibbs sampler, and model adequacy is assessed by posterior predictive checking. Simulation results show that the required amount of risk capital is high, even though depressions are an infrequent phenomenon.     

带干扰风险的破产模型的研究

本文对古典风险模型中保险公司按单位时间常数率收到保险费的假设做了改进,将每次收到的保险费的次数看作是复合泊松过程,将每次收到的保费和每次的理陪额均看作是服从指数分布的随机变量,并引入带干扰风险的扰动项,从而对古典风险模型进行推广,且给出了相应的破产概率上界,分析了破产概率的上界与准备金,索赔额,净保费和扰动方差之间的关系。     

带干扰风险的破产模型的研究

本文对古典风险模型中保险公司按单位时间常数率收到保险费的假设做了改进,将每次收到的保险费的次数看作是复合泊松过程,将每次收到的保费和每次的理陪额均看作是服从指数分布的随机变量,并引入带干扰风险的扰动项,从而对古典风险模型进行推广,且给出了相应的破产概率上界,分析了破产概率的上界与准备金,索赔额,净保费和扰动方差之间的关系.     

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。     

Survival probability and ruin probability of a risk model

In this paper, a new risk model is studied in which the rate of premium income is regarded as a random variable, the arrival of insurance policies is a Poisson process and the process of claim occurring is p-thinning process. The integral representations of the survival probability are gotten. The explicit formula of the survival probability on the infinite interval is obtained in the special casc cxponential distribution.The Lundberg inequality and the common formula of the ruin probability are gotten in terms of some techniques from martingale theory.