非负不同分布负相伴随机变量下的精细大偏差

研究非负,不同分布,负相伴随机变量的精细大偏差问题.在相对较弱的条件下,重点解决非随机和的精细大偏差的下限问题,得到相对应的随机和的一致渐近结论.同时,对复合更新风险模型进行深入的讨论,在一定的条件之下将其简化为一般的更新风险模型,并将所得相关的精细大偏差的结论应用到更为实际的复合更新风险模型中,验证其理论与实际价值.除此之外,本文的研究还表明,随机变量间的这种相依关系对精细大偏差的最终结果的影响并不大.     

重尾平稳序列的大偏差

本文给出了一类重尾的随机变量序列{Xn,n≥1}的部分和Sn=∑i=1 n Xi与随机和S(t)=∑i=1^N(t) Xi的大偏差结果其中{N(t),t≥)}是一族非负整值的随机变量，{Xn,n≥1}是非负的平稳过程，并且与{N(t),t≥0}独立。本文将独立同分布情形的结果掖到了平稳相依的情形。     

非负不同分布负相协随机变量下的精细大偏差（英文）

本文研究非负,不同分布,负相协随机变量的精细大偏差问题.在相对较弱的条件下,重点解决了非随机和的精细大偏差的下限问题,得到相对应的随机和的一致渐近结论.同时,对复合更新风险模型进行了深入的讨论,在一定的条件之下将其简化为一般的更新模型,并将所得相关的精细大偏差的结论应用到更为实际的复合更新风险模型中,验证了其理论与实际价值.除此之外,本文的研究还表明,随机变量间的这种相依关系对精细大偏差的最终结果的影响并不大.     

一类时间相依复合更新风险模型损失过程的尾概率渐近估计

考虑一类复合相依更新风险模型,一次事故引发多次索赔.假设索赔次数与索赔时刻相依,同一事故引起的索赔额是宽上限相依(widely upper orthant dependent)且服从重尾分布.得到该风险模型损失过程的精细大偏差和有限时破产概率的渐近估计.     

重尾相依随机变量的随机加权和尾概率的渐近估计（英文）

令{X_k;k≥1}为一列实值随机变量,{θ_k;k≥1}为另一列与之独立的随机变量序列.假设{X_k;k≥1}为两两广义负象限相依且服从重尾分布,在{θ_k;k≥1}独立和相依条件下,本文得到了一些渐近估计.     

独立重尾随机变量随机和的大偏差估计

本文研究了一类独立重尾随机变量随机和S（t)∧=∑k=1^N(t)Xk,t≥0的大偏差概率，其中{N(t),t≥0}是一放大晨负整数值随机变量；{Xn,n≥1}是非负，独立随机变量序列，并与{N(t),t≥０}独立。本文的结果将{Xn,n≥１}为独立同分布情形推广到了独立不同分布情形。     

风险模型中重尾随机变量和的若干大偏差结果

进一步研究随机变量部分和与随机和的大偏差,其中S(n)=∑ni=1Xi,S(t)=∑N(t)i=1Xi(t>0).{Xn,n≥1}是一个独立同分布的随机变量(未必是非负的)序列具有共同的分布F(定义于R上)和有限期望μ=EX1.{N(t),t≥0}是一个非负的整数值的随机变量的更新计数过程且与{Xn,n≥1}相互独立.本文在假定F∈C条件下,进一步推广并改进了由Klüppelberg等和Kaiw等人给出的一些大偏差结果.这些结果可应用到某些金融保险方面的一些特定的问题中去.     

广义负相依重尾随机变量和及其最大值尾概率的渐近性

假设X_1,X_2…,X_n是一列具有广义负相依结构的随机变量(r.v.s.),分别具有分布F_1,F_2,...,F_n.假设S_n:=X_1+X_2+…+X_n.本文分别在三类重尾分布族下得到了如下量之间的渐近关系:P(S_nx),P(max{X_1,X_2,…,x_n}x), P(max{S_1, S_2,…,S_n} X)和(?)P(X_k x).在此基础上,本文还探讨了随机加权和最大值尾概率的渐近性质,并运用蒙特卡洛(CMC)数值模拟验证了其有效性.最后,本文将得到的主要结果应用到了一个带有保险风险与金融风险的离散时间风险模型,得到了有限时间破产概率的渐近性.     

一类带有宽负相依索赔额的新风险模型损失过程的精细大偏差

本文研究一类基于保单进入过程的风险模型,客户在其保期内可索赔多次.假设每个顾客的索赔额是宽负相依的且服从重尾分布,不同顾客之间的索赔额是相互独立的.本文得到了损失过程的大偏差.     

D族END的随机变量和的精确大偏差

研究了非随机和的S_n=∑_i=1ⁿ X_i,n≥1的精确大偏差的问题,这里{X_i,i≥1}是服从控制变化尾分布族（D族）的非负的、END的随机变量,但不必是同分布的.在给定的一些假设条件下,得到了非随机和的渐近关系,推广了相应的独立同分布情形下的结论.     

Precise large deviations for generalized dependent compound renewal risk model with consistent variation

We investigate the precise large deviations of random sums of negatively dependent random variables with consistently varying tails. We find out the asymptotic behavior of precise large deviations of random sums is insensitive to the negative dependence. We also consider the generalized dependent compound renewal risk model with consistent variation, which including premium process and claim process, and obtain the asymptotic behavior of the tail probabilities of the claim surplus process.     

On the discrete-time compound renewal risk model with dependence

In this paper, we study the discrete-time renewal risk model with dependence between the claim amount random variable and the interclaim time random variable. We consider several dependence structures between the claim amount random variable and the interclaim time random variable. Recursive formulas are derived for the probability mass function and the moments of the total claim amount over a fixed period of time. In the context of ruin theory, explicit expressions for the expected penalty (Gerber-Shiu) function are derived for special cases. We also discuss how the discrete-time compound renewal risk model with dependence can be used to approximate the corresponding continuous time compound renewal risk model with dependence. Numerical examples are provided to illustrate different topics discussed in the paper.     

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??In this paper, precise large deviations of nonnegative, non-identical distributions and negatively associated random variables are investigated. Under certain conditions, the lower bound of the precise large deviations for the non-random sum is solved and the uniformly asymptotic results for the corresponding random sum are obtained. At the same time, we deeply discussed the compound renewal risk model, in which we found that the compound renewal risk model can be equivalent to renewal risk model under certain conditions. The relative research results of precise large deviations are applied to the more practical compound renewal risk model, and the theoretical and practical values are verified. In addition, this paper also shows that the impact of this dependency relationship between random variables to precise large deviations of the final result is not significant.     

宽象限相依随机变量部分和的中偏差及其在保险中的应用

研究了控制变换尾分布的宽象限相依实值随机变量部分和的中偏差.相应于所得到的理论结果,进一步给出了在相依保险风险模型中的两个应用;一是在基于顾客到达过程的保险风险模型中,保险公司盈余的渐近估计;二是在复合更新风险模型中,有限时和无限时破产概率的一致渐近估计.     

On a risk model with random incomes and dependence between claim sizes and claim intervals

In this paper, we construct a risk model with a dependence setting where there exists a specific structure among the time between two claim occurrences, premium sizes and claim sizes. Given that the premium size is exponentially distributed, both the Laplace transforms and defective renewal equations for the expected discounted penalty functions are obtained. Exact representations for the solutions of the defective renewal equations are derived through an associated compound geometric distribution. When the claims are subexponentially distributed, the asymptotic formulae for ruin probabilities are obtained. Finally, when the individual premium sizes have rational Laplace transforms, the Laplace transforms for the expected discounted penalty functions are obtained.     

On a Generalization from Ruin to Default in a Lévy Insurance Risk Model

In a variety of insurance risk models, ruin-related quantities in the class of expected discounted penalty function (EDPF) were known to satisfy defective renewal equations that lead to explicit solutions. Recent development in the ruin literature has shown that similar defective renewal equations exist for a more general class of quantities than that of EDPF. This paper further extends the analysis of this new class of functions in the context of a spectrally negative Lévy risk model. In particular, we present an operator-based approach as an alternative analytical tool in comparison with fluctuation theoretic methods used for similar quantities in the current literature. The paper also identifies a sufficient and necessary condition under which the classical results from defective renewal equation and those from fluctuation theory are interchangeable. As a by-product, we present a series representation of scale function as well as potential measure in terms of compound geometric distribution.     

Asymptotic aspects of the Gerber-Shiu function in the renewal risk model using Wiener-Hopf factorization and convolution equivalence

We study the asymptotic behavior of the Gerber-Shiu expected discounted penalty function in the renewal risk model. Under the assumption that the claim-size distribution has a convolution-equivalent density function, which allows both heavy-tailed and light-tailed cases, we establish some asymptotic formulas for the Gerber-Shiu function with a fairly general penalty function. These formulas become completely transparent in the compound Poisson risk model or for certain choices of the penalty function in the renewal risk model. A by-product of this work is an extension of the Wiener-Hopf factorization to include the times of ascending and descending ladders in the continuous-time renewal risk model.     

Ruin probabilities in the discrete time renewal risk model

In this paper, we study the discrete time renewal risk model, an extension to Gerber’s compound binomial model. Under the framework of this extension, we study the aggregate claim amount process and both finite-time and infinite-time ruin probabilities. For completeness, we derive an upper bound and an asymptotic expression for the infinite-time ruin probabilities in this risk model. Also, we demonstrate that the proposed extension can be used to approximate the continuous time renewal risk model (also known as the Sparre Andersen risk model) as Gerber’s compound binomial model has been proposed as a discrete-time version of the classical compound Poisson risk model. This allows us to derive both numerical upper and lower bounds for the infinite-time ruin probabilities defined in the continuous time risk model from their equivalents under the discrete time renewal risk model. Finally, the numerical algorithm proposed to compute infinite-time ruin probabilities in the discrete time renewal risk model is also applied in some of its extensions.     

Asymptotics for solutions of a defective renewal equation with applications

In this paper, we derive non-exponential asymptotic forms for solutions of defective renewal equations. These include as special cases asymptotics for compound geometric distribution and the convolution of a compound geometric distribution with a distribution function. As applications of these results, we study the Gerber-Shiu discounted penalty function in the classical risk model and the reliability of a two-unit cold standby system in reliability theory.      

A Perturbed Risk Model with Dependence Based on a Generalized Farlie-Gumbel-Morgenstern Copula

In this paper, we consider a perturbed compound Poisson risk model with dependence, where the dependence structure for the claim size and the inter-claim time is modeled by a generalized Farlie-Gumbel-Morgenstern copula. The integro equations, the Laplace transforms and the defective renewal equations for the Gerber-Shiu functions are obtained. For exponential claims, some explicit expressions are obtained, and some numerical examples for the ruin probabilities are also provided.