The probability of ruin in finite time

The Sparre Andersen model in the collective risk theory is investigated. We obtain the rate of convergence for the ruin probability after thenth payoff in the case where claim sizes are heavy tailed (say, subexponential). Institute of Mathematics and Informatics, Akademijos 4, 2600 Vilnius, Lithuania. Published in Lietuvos Matematikos Rinkinys, Vol. 39, No. 3, pp. 304–309, July–September, 1999.     

A series for infinite time ruin probabilities

This paper presents a series method for calculating the infinite time ruin function. The terms of the series involve convolutions related to the claim size distribution. Approximations to the series are presented, with their error analyses. Three detailed examples are given, two of which involve the inverse Gaussian distribution. A discussion of that distribution is made, including the maximum likelihood estimators of its parameters. The relevance of the Poisson model for numbers of claims stochastic process is considered. Evidence from two very large studies is presented to support that model, at least for some portfolios.     

常息力更新场合有限时间破产概率对负相依索赔额的不敏感性

设索赔来到过程为具有常数利息力度的更新风险模型.在索赔额分布为负相依的次指数分布假定下,建立了有限时间破产概率的一个渐近等价公式.所得结果显示,在独立同分布索赔额情形,有限时间破产概率的有关渐近等价公式,在负相依场合依然成立.这表明有限时间破产概率对于索赔额的负相依结构是不敏感的.     

Nonparametric estimation of ruin probabilities given a random sample of claims

In this paper the well-known insurance ruin problem is reconsidered. The ruin probability is estimated in the case of an unknown claims density, assuming a sample of claims is given. An important step in the construction of the estimator is the application of a regularized version of the inverse of the Laplace transform. A rate of convergence in probability for the integrated squared error (ISE) is derived and a simulation study is included.      

Asymptotic behaviour of the finite-time ruin probability under subexponential claim sizes

The paper deals with the Sparre Andersen risk model. We study the tail behaviour of the finite-time ruin probability, Ψ(x,t), in the case of subexponential claim sizes as initial risk reserve x tends to infinity. The asymptotic formula holds uniformly for t in a corresponding region and reestablishes a formula of Tang [Tang, Q., 2004a. Asymptotics for the finite time ruin probability in the renewal model with consistent variation. Stochastic Models 20, 281–297] obtained for the class of claim distributions having consistent variation.     

On the moments of the time to ruin in dependent Sparre Andersen models with emphasis on Coxian interclaim times

The structural properties of the moments of the time to ruin are studied in dependent Sparre Andersen models. The moments of the time to ruin may be viewed as generalized versions of the Gerber–Shiu function. It is shown that structural properties of the Gerber–Shiu function hold also for the moments of the time to ruin. In particular, the moments continue to satisfy defective renewal equations. These properties are discussed in detail in the model of Willmot and Woo (2012), which has Coxian interclaim times and arbitrary time-dependent claim sizes. Structural quantities needed to determine the moments of the time to ruin are specified under this model. Numerical examples illustrating the methodology are presented.     

Sparre Andersen风险模型的破产问题(英)

本文主要研究了一类Sparre Andersen模型,其索赔时间间隔的分布为指数分布与Erlang(n) 分布的混合.得到了当初始资金u趋于无穷大时,破产概率ψ(u)的确切表达式和渐近表达式.     

再保险与有限时间破产概率

研究保险公司用超额索赔再保险最小化其有限时间破产概率的问题,用鞅方法得到有限时间破产概率的上界以及保险公司的最优再保险自留额.     

Tail equivalence relationships for ruin probabilities in several risk models

This paper is a further investigation into the ruin probability ψ(x) in several risk models, where x is the initial surplus. Under the assumption that the claim sizes are heavy‐tailed, we get some tail equivalence relationships of ψ(x). Copyright © 2005 John Wiley & Sons, Ltd.     

A note on the convexity of ruin probabilities

Conditions for the convexity of compound geometric tails and compound geometric convolution tails are established. The results are then applied to analyze the convexity of the ruin probability and the Laplace transform of the time to ruin in the classical compound Poisson risk model with and without diffusion. An application to an optimization problem is given.     

Large-deviation probabilities for maxima of sums of subexponential random variables with application to finite-time ruin probabilities

We establish an asymptotic relation for the large-deviation probabilities of the maxima of sums of subexponential random variables centered by multiples of order statistics of i.i.d.standard uniform random variables.This extends a corresponding result of Korshunov.As an application,we generalize a result of Tang,the uniform asymptotic estimate for the finite-time ruin probability,to the whole strongly subexponential class.     

Sparre Andersen模型中破产概率的边界

研究在Andersen Spaxre模型中,当破产概率的初始边界已知的时候,根据更新方程和更新方程中函数的单调性来改进破产概率的边界,并进一步改进了严重损失函数G（x,y）的边界．     

时间赢余过程的构造及其破产理论

本文提出了一种研究风险模型的新思路，并构造了一个时间孕余过程，从另外一个新的侧面给出了破产概率的定义，并在此方面做了初步的探讨。     

Approximation for Ruin Probability in the Sparre Andersen Model with Interest

We consider the Sparre Andersen model modified by the inclusion of interest on the surplus.Approximation for the ultimate ruin probability is derived by rounding.And upper bound and lower bound arealso derived by rounding-down and rounding-up respectively.According to the upper bound and lower bound,we can easily obtain the error estimation of the approximation.Applications of the results to the compoundPoisson model are given.     

带常利率和相依结构更新风险模型的破产概率

研究了一类具有常利率及相依结构的Sparre Andersen模型,模型中假设理赔间隔时间决定下一次理赔额的分布情况.对一般分布情形,利用推广后的调节系数方程与递归更新技巧,得到了此模型的最终破产概率上界的估计.最后以理赔额和理赔间隔时间都服从指数分布的情况下的实例分析来说明该模型的有效性.     

Regularization and error estimate of infinite‐time ruin probabilities for Cramer‐Lundberg model

In this article, we consider the problem of finding the ultimate ruin probability in the classical risk mode. Using Laplace transform inversion and Fourier transform, we obtain ultimate ruin probability of an insurance company. First, we show that this problem is ill‐posed in the sense of Hadamard. Then, we apply the Tikhonov and truncation methods for establishing the approximate function for the ultimate ruin probability. Furthermore, convergence of the method, together with some examples, will be given. Finally, we present a numerical example to show efficiency of the method.     

Asymptotics for the ruin probabilities of a two‐dimensional renewal risk model with heavy‐tailed claims

In this paper, we consider two dependent classes of insurance business with heavy‐tailed claims. The dependence comes from the assumption that claim arrivals of the two classes are governed by a common renewal counting process. We study two types of ruin in the two‐dimensional framework. For each type of ruin, we establish an asymptotic formula for the finite‐time ruin probability. These formulae possess a certain uniformity feature in the time horizon. Copyright © 2010 John Wiley & Sons, Ltd.     

Asymptotic behaviour of the finite‐time ruin probability in renewal risk models

In this paper we study the tail behaviour of the probability of ruin within finite time t, as initial risk reserve x tends to infinity, for the renewal risk model with strongly subexponential claim sizes. The asymptotic formula holds uniformly for t∈[f(x), ∞), where f(x) is an infinitely increasing function, and substantially extends the result of Tang (Stoch. Models 2004; 20 :281–297) obtained for the class of claim distributions with consistently varying tails. Two examples illustrate the result. Copyright © 2008 John Wiley & Sons, Ltd.     

Bayesian estimation of regression parameters in elliptical measurement error models

The main object of this paper is to discuss the Bayes estimation of the regression coefficients in the elliptically distributed simple regression model with measurement errors. The posterior distribution for the line parameters is obtained in a closed form, considering the following: the ratio of the error variances is known, informative prior distribution for the error variance, and non-informative prior distributions for the regression coefficients and for the incidental parameters. We proved that the posterior distribution of the regression coefficients has at most two real modes. Situations with a single mode are more likely than those with two modes, especially in large samples. The precision of the modal estimators is studied by deriving the Hessian matrix, which although complicated can be computed numerically. The posterior mean is estimated by using the Gibbs sampling algorithm and approximations by normal distributions. The results are applied to a real data set and connections with results in the literature are reported.