基于顺序统计量的几何分在特征的进一步结果

用顺序统计量来刻划几何分布的特征已有不少结果，但仍有问题有待解决．本文在文［１］的基础上，针对Ａｒｎｏｌｄ［２］所提问题进行了进一步研究，得到了一些进一步的结果．这些结果同时给出了几何分布的基于顺序统计量的特征．     

对数正态分布场合的BAYES分析和大样本的后验分布

本文绘出了对数正态分布场合中的两参数μ，σ2均未知时的Bayes分析，并给出相应的例子．讨论了大样本的后验分布，推广了[2]中的结果．     

由圈长分布确定的偶图

阶为n的图G的圈长分布是序列(C1，C2，…，Cn)，其中ci是图G中长为i的圈数．本文得到如下结果：设A∈_E(Kn,r)，|A|≤1，且n≤r≤min{n 6，2n-3)，则G=Kn,r，r-A是由它的圈长分布确定的．     

LOgistic响应分布中刻度参数的中、小样本推断

在火炸药产品的敏感性推断中，对响应分布的标准差给出较精确的推断，是基础性工作之一．为此，本文基于Logistic响应分布，在二元响应数据下，应用鞍点近似方法构造了刻度参数的近似置信区间，并进行了模拟研究．最后，本文将该方法应用于QD-8电雷管．模拟结果和实例分析表明，在中、小样本情形，本文方法对刻度参数的推断结果较为精确，显著改进了现行的基于渐近正态性的方法．     

高阶微分方程允许解的存在性

本文主要目的是利用值分布理论研究复高阶微分方程(Ω(z,w)/w^k0(w’)^k1…(w^(n)^kn)^m=aw^p ∑j=0^s bj(z)w^j,(p≥m）亚纯允许解的存在性问题．证明了一个在适当的条件下，该微分方程的亚纯解一定不是允许解的结果．实例表明该文的结果是最佳的．     

伯努利数和二项分布及超几何分布的快速计算

本文利用伯努利数建立了二项分布值和超几何分布值的快速计算公式，这些公式计算的结果精确度高，而且非常便于计算机编程．     

多元极值分布参数的最大似然估计与分步估计

本文考虑多元极值分布的参数估计，给出了分步估计渐近协差阵的近似表示，并对维数P=2，5及相关参数α=0．001，0．01；0．1（0．2），0．9；0．99，0．999的各种组合，计算了分步估计关于最大似然估计的渐近效率，分析了各种参数及维数对渐近效率的影响．分步估计是一种合理、简单而且有较强实用意义的估计方法．     

整函数和亚纯函数多项式的导数

本文考虑整函数和亚纯函数多项式的导数的值分布问题，得到了类似Ｔｕｍｒａ－Ｃｌｕｎｉｅ定理的一些结果，它们包含了文［１，４，５］中的结果作为特殊情况．     

退化矩阵Liouville,Beta,Dirichlet分布

该文引进和讨论了退化矩阵Liouville分布，由此导出退化矩阵Beta分布、退化矩阵Dirichlet分布．推广了文献［1］关于退化Wishart分布和秩为1的退化矩阵Beta分布的结果。     

也谈洛特卡分布的参数估计

本文分析了论文〔１〕参数估计的结果与过程，并给出估计洛特卡分布参数的一种方法．     

Recursions for multivariate compound phase variables

We show how to generalize the result given in [Eisele, K.-Th., 2006. Recursions for compound phase distributions. Insurance: Math. Econom. 38, 149-156] to the multivariate case, i.e. we find a Panjer-like recursion principle for the distribution of a multivariate compound phase variable. Recursion formulas and procedures for the bivariate case are given in detail. We give a possible application for agricultural risks and calculate concrete examples via a VB-program.     

Univariate and multivariate versions of the negative binomial-inverse Gaussian distributions with applications

In this paper we propose a new compound negative binomial distribution by mixing the p negative binomial parameter with an inverse Gaussian distribution and where we consider the reparameterization p=exp(−λ). This new formulation provides a tractable model with attractive properties which make it suitable for application not only in the insurance setting but also in other fields where overdispersion is observed. Basic properties of the new distribution are studied. A recurrence for the probabilities of the new distribution and an integral equation for the probability density function of the compound version, when the claim severities are absolutely continuous, are derived. A multivariate version of the new distribution is proposed. For this multivariate version, we provide marginal distributions, the means vector, the covariance matrix and a simple formula for computing multivariate probabilities. Estimation methods are discussed. Finally, examples of application for both univariate and bivariate cases are given.     

Jump diffusion processes and their applications in insurance and finance

For insurance risks, jump processes such as homogeneous/non-homogeneous compound Poisson processes and compound Cox processes have been used to model aggregate losses. If we consider the economic assumption of a positive interest to aggregate losses, Lévy processes have proven to be useful. Also in financial modelling, it has been observed that diffusion models are not robust enough to capture the appearance of jumps in underlying asset prices and interest rates. As a result, jump diffusion processes, which are, simply speaking, combinations of compound Poisson processes with Brownian motion, have gained popularity for modelling in insurance and finance. In this paper, considering a jump diffusion process, we obtain the explicit expression of the joint Laplace transform of the distribution of a jump diffusion process and its integrated process, assuming that jump size follows the mixture of two exponential distributions, which is a special case of phase-type distributions. Based on this Laplace transform, we derive the moments of the aggregate accumulated claim amounts of insurance risk. For a financial application, we concern non-defaultable zero-coupon bond pricing. We also provide several numerical examples for the moments of aggregate accumulated claims and default-free zero-coupon bond prices.     

Copula理论在复合期权定价中的应用

本文使用风险中性评价方法分三部分计算了复合期权的价值,针对需要计算联合分布的第二部分,通过选取边缘分布为GARCH模型的二元正态Copula模型进行推理验证,结果求得的联合分布与使用风险中性评价方法的计算结果一致.进一步计算得到了时间相依的复合期权的价值,并且给出了使用Bayes时序诊断法和Z检验来诊断期权定价时其出现价格大的波动时的局部拐点的方法.     

关于Erlang分布的一个注记

利用递推的方法得到了尺度参数不同的两个相互独立的Erlang分布的卷积的表达形式.作为应用得到了Beta分布的Laplace变换的表达式.     

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.     

复合泊松过程及其在保险风险中的若干应用

本文利用齐次泊松过程的可加性,研究了复合泊松过程的可加性及其性质。作为应用,讨论了单个理赔额服从指数分布的复合泊松风险模型在第n次索赔时发生负盈余的概率。     

A compound of the generalized negative binomial distribution with the generalized beta distribution

This paper presents a compound of the generalized negative binomial distribution with the generalized beta distribution. In the introductory part of the paper, we provide a chronological overview of recent developments in the compounding of distributions, including the Polish results. Then, in addition to presenting the probability function of the compound generalized negative binomial-generalized beta distribution, we present special cases as well as factorial and crude moments of some compound distributions.     

On positive definite quadratic forms in correlatedt variables

Summary In this paper we extend Ruben's [4] result for quadratic forms in normal variables. He represented the distribution function of the quadratic form in normal variables as an infinite mixture of chi-square distribution functions. In the central case, we show that the distribution function of a quadratic form int-variables can be represented as a mixture of beta distribution functions. In the noncentral case, the distribution function presented is an infinite series in beta distribution functions. An application to quadratic discrimination is given.     

复合泊松过程的可加性

对复合泊松分布可加性的研究在许多的文献中都可以看到,本文首先应用特征函数的方法证明了复合泊松分布的可加性.以此为基础,结合对随机过程相关性质的讨论,证明了复合泊松过程也具有与复合泊松分布可加性相似的,某种意义上的可加性性质.