相关随机利率下的双二项模型的破产概率

研究带有相关随机利率的双二项风险模型,得到了破产概率的积分表达式,并利用鞅分析的方法得到了破产概率的经典Lundberg上界,另外给出了一个破产概率的比经典Lundberg上界更精确的上界.     

一类相依索赔离散风险模型研究

研究了一类相依索赔的离散风险模型,得到了利率为0时模型的最终破产概率所满足的积分方程,以及破产持续n期的概率所满足的表达式.进而,得到了利率不为0时该模型的最终破产概率所满足的积分方程,并利用鞅论技巧导出了最终破产概率的一个Lundberg型上界,最后运用Matlab软件随机模拟破产概率并与Lundberg型上界作比较.     

具有相依结构离散时间模型破产概率的上界

研究两类具有相依结构的离散时间风险模型的破产概率问题.其中,索赔和利率过程假设为2个不同的自回归移动平均模型.利用更新递归技巧,首先得到了该模型下破产概率所满足的递归方程.然后,根据该递归方程得到了破产概率的上界估计.最后对两类风险模型的破产概率的上界进行了比较.     

马氏利率下相关险种的离散风险建模和破产概率

在随机利率服从有限齐次Markov链下,建立相关险种离散风险模型,采用递推方法得到了有限时间破产概率的递推等式和最终破产概率的积分等式;给出了有限时间破产概率和最终破产概率的上界,导出了破产时刻余额分布的计算等式.     

Markov链利率下再保险模型的破产概率上界

研究了如何确定离散时间情况下再保险模型破产概率上界的问题.为了降低自身的破产风险,保险公司常常对部分乃至全部资产进行再保险.假定索赔间隔时间和索赔额具有一阶自回归结构,假定利率过程为取值于可数状态空间的Markov链.建立了其比例再保险模型,分别用递归更新技巧和鞅方法得到模型的破产概率上界.该破产概率上界作为评估再保险公司偿付能力和风险控制能力的重要指标,对于它的研究成果能为再保险人做出重大决策提供重要的依据,具有较为重要的理论和现实意义.     

一类推广负风险和模型的破产概率

本文研究了带干扰的两险种负风险和模型的破产问题.利用无穷小方法,给出了该风险模型破产概率所满足的微分-积分方程,并推导出破产概率满足的Lundberg型不等式.最后指出了当索赔服从负指数分布时破产概率的上界,推广了经典风险模型的结果.     

投资收益下的两类双二项风险模型的破产概率及比较

本文讨论了含投资因素的双二项风险模型,得到了破产概率表达式,并对几类相关的双二项风险模型的调节系数及破产概率上界进行了比较.     

寿险中的破产理论及应用

本文研究了求解寿险中破产概率的简洁方法 ,得到寿险破产模型 ,设计了求解寿险中的破产概率的一种算法 ,并得到寿险破产概率的一个上界。     

保费收取过程是随机过程的双险种风险模型

研究保费收取过程是一个随机过程的双险种风险模型,得出了Lundberg上界、最终破产概率、不破产所满足的微积分方程、索赔服从指数分布的不破产概率、有限时间不破产所满足的微积分方程.     

保费随机收取的广义二元复合非齐次Poisson风险模型

研究了一类双险种风险模型,其中索赔到达计数过程和保费到达计数过程均为非齐次Po isson过程,用鞅方法得到了有限时间破产概率的一个上界,并给出了当两个险种的个体索赔均服从指数分布时,有限时间破产概率的上界估计.     

Strict upper and lower bounds of quantities in linear second-order systems

This paper aims to present a model verification technique for general numerical computations of linear second-order systems. Strict upper and lower bounds on quantities of interest are eventually obtained. The model verification technique consists of two major steps. The first is the representation of the error in quantities of interest through an adjoint correction; the second is the application of the strict upper bound derived for the time-discretization error. Moreover, the bounds on quantities of interest are further improved through an optimization procedure. Academic examples are studied to verify the proposed bounds and to explore the potential application of these bounds to adaptive time-stepping.     

带干扰的常利率超额再保险Poisson风险模型的最优自留额

本文推广了Centeno[1],何树红[2],张茂军[3]的模型,研究带干扰的常利率超额再保险风险模型。首先用鞅方法求得其调节函数,进而证明Lundberg不等式,给出有限时间破产概率上界,并讨论最优自留额的确定。     

Bounds for the expectation of linear combinations of order statistics with application to pert networks

The bounds derived by Arnold and Groeneveld [l] for the expectation of linear combinations of order statistics are slightly extended, and this allows us to deduce directly as particular cases the upper bounds obtained by Aven [2] for the expectation of the maximum of a number of random variables. These latter bounds are then used to construct simple explicit upper bounds for the mean completion time in Pert networks     

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本文考虑了常利力下带干扰的双复合Poisson风险过程, 借助微分和伊藤公式, 分别获得了无限时和有限时生存概率的积分微分方程. 当保费服从指数分布时, 得到了无限时生存概率的微分方程.     

New upper solution bounds of the discrete algebraic Riccati matrix equation

In this note, we present upper matrix bounds for the solution of the discrete algebraic Riccati equation (DARE). Using the matrix bound of Theorem 2.2, we then give several eigenvalue upper bounds for the solution of the DARE and make comparisons with existing results. The advantage of our results over existing upper bounds is that the new upper bounds of Theorem 2.2 and Corollary 2.1 are always calculated if the stabilizing solution of the DARE exists, whilst all existing upper matrix bounds might not be calculated because they have been derived under stronger conditions. Finally, we give numerical examples to demonstrate the effectiveness of the derived results.     

Comparisons of weak regular splittings and multisplitting methods

Summary Comparison results for weak regular splittings of monotone matrices are derived. As an application we get upper and lower bounds for the convergence rate of iterative procedures based on multisplittings. This yields a very simple proof of results of Neumann-Plemmons on upper bounds, and establishes lower bounds, which has in special cases been conjectured by these authors.Dedicated to the memory of Peter Henrici     

On Upper Bounds for Minimum Distance and Covering Radius of Non-binary Codes

We consider upper bounds on two fundamental parameters of a code; minimum distance and covering radius. New upper bounds on the covering radius of non-binary linear codes are derived by generalizing a method due to S. Litsyn and A. Tietäväinen lt:newu and combining it with a new upper bound on the asymptotic information rate of non-binary codes. The upper bound on the information rate is an application of a shortening method of a code and is an analogue of the Shannon-Gallager-Berlekamp straight line bound on error probability. These results improve on the best presently known asymptotic upper bounds on minimum distance and covering radius of non-binary codes in certain intervals.     

Bounds for the variance of Mann-Whitney statistic

Summary Lower and upper bounds for the variance of Mann-Whitney statistic have been obtained by Birnbaum and Klose recently. The main problem in their paper reduces to that of obtaining bounds of an integral of a convex function of a cumulative distribution function satisfying certain side restrictions. Using the methods and results of Rustagi and Harris, bounds for such an integral are obtained and bounds for the variance of the Mann-Whitney statistic are derived therefrom.     

Recursive lower and dual upper bounds for Bermudan-style options

Although Bermudan options are routinely priced by simulation and least-squares methods using lower and dual upper bounds, the latter are hardly optimized. In this paper, we optimize recursive upper bounds, which are more tractable than the original/nonrecursive ones, and derive two new results: (1) An upper bound based on (a martingale that depends on) stopping times is independent of the next-stage exercise decision and hence cannot be optimized. Instead, we optimize the recursive lower bound, and use its optimal recursive policy to evaluate the upper bound as well. (2) Less time-intensive upper bounds that are based on a continuation-value function only need this function in the continuation region, where this continuation value is less nonlinear and easier to fit (than in the entire support). In the numerical exercise, both upper bounds improve over state-of-the-art methods (including standard least-squares and pathwise optimization). Specifically, the very small gap between the lower and the upper bounds derived in (1) implies the recursive policy and the associated martingale are near optimal, so that these two specific lower/upper bounds are hard to improve, yet the upper bound is tighter than the lower bound.