具扩散项的停止-损失再保问题的破产概率

本文在具有扩散项的假定下,研究了原保险公司、再保险公司的破产问题.在索赔随机变量为指数情形,得到了免赔额与破产概率之间的关系,并且得到了如下的结果:1.随机风险模型生存概率的表达公式,从而得到了由扰动导致的破产概率的表达公式.2.分别得到了两类保险公司破产概率的表达公式.所得结果不仅推广了文献[1]的结果,而且使用的方法具有一定的独立价值.     

具扩散项的带免赔额的Erlang(2)问题的破产概率

本文从具有扩散项的模型出发,最终在个体理赔额服从Erlang(2)分布情形下利用解高阶微分-差分方程和鞅的办法得到了与免赔额d有关的原、再保的相应破产概率ψ(u)以及调节系数的表达公式。所得结果不仅仅直接的推广了文献[7]的相关结论,尤其在再保险的场合下研究该模型的文献还不多见,而且在保险资金可以入市的经济背景下也是具有现实意义的。     

索赔次数为复合Poisson-Geometric过程下破产概率的显式表达

本文研究索赔次数为复合Poisson-Geometric过程下的风险模型;当个体索赔额服从相位(Phase-Type)分布时,得到了破产概率的显式表达式及数值结果。     

破产概率的大偏差上界

本文建立如下风险模型:Un=M+Sn-Yn(初始资金M,保费收入Sn是复合泊松过程,打折索赔过程Yn)。应用大偏差原理,讨论了离散时间风险模型在有限时间t内的破产概率上界估计。     

重尾索赔条件下现代风险模型的破产概率估计:多险种混合情形

破产概率是非寿险保险风险理论的核心问题。与经典的Cramér-Lundberg模型相比, 由Li Zehui等建立的现代风险模型更为准确地描述了非寿险保险运营的主要特征, 对现实保险业务具有较好的解释力。本文基于现代风险模型, 考虑保险公司多个险种混合经营这一更为现实的情形, 在索赔额服从正则尾分布条件下获得了破产概率的渐近等价估计。我们发现, 在具有大额索赔特征的多个险种混合的条件下, 公司面临的极端索赔风险将由索赔额分布尾部最厚的那些险种决定, 而索赔额分布尾部相对较薄的那些险种的影响作用将被淹没。该结论的有效性可用MATLAB数值模拟得到理想的验证。本文结果是对风险模型研究的重要推广, 也为多险种混合情形下保险公司的风险控制与初始保证金界定提供了依据。     

破产风险的测定与控制

破产风险同一般意义上的风险具有明显的差异,其研究对象涉及企业、个人等组成的社会群体,影响因素具有定性、定量相结合的特征.本文在文[1]基础上,做了如下改进工作采用定性识别与模型定量计算相结合的方式,研究了破产风险的识别、衡量和控制.采用基于参数分布和模糊识别方法对破产风险进行分类,提出破产概率推断方法,建立了企业寿命分布函数,最后给出破产风险控制的规划模型及仿真计算的案例.     

二元风险模型下的保险公司最优投资策略

本文考虑了二元风险模型下保险公司的投资问题.假设保险公司的两个子公司分别在风险市场上投资,且投资策略都属于常数族,利用鞅方法得到了破产概率的指数型上界,给控制保险公司的风险提供了可能.并且得到了最优的常数投资策略,该策略可以使破产概率的上界最小.最后给出了具体的算例阐述了本文的结果.     

二维GPSJ分布类及其在保险中的应用

本文给出的二维GPSJ分布类(即GPSJ2)在保险领域应用范围较广,如由机动车辆保险由财产损失索赔次数和人身伤亡索赔次数所组成的模型、超额再保险中的由自留保单数和分出报单数所组成的二维模型等。本文在GPSJ1类基础上研究二维GPSJ类,本文给出了此分布类的定义、背景意义、概率计算的递推公式,同时还对各参数的最大似然估计值的求解过程进行了分析。本文最后将这一模型应用于一组机动车辆赔付次数数据,考虑了由财产损失索赔次数、人身伤亡索赔次数组成的二维模型,拟合效果令人满意。     

最小化破产概率的最优投资

本文研究基于最小化破产概率准则的最优投资问题.不同于Merton问题中消费是内生决策变量,本文假设投资者单位时间内必须消费不少于一个固定数量的财富,因而投资者有可能最终破产.在三类不同存贷约束条件下,通过求解模型相对应的Hamilton-Jacobi-Bellmen (HJB)方程,都获得了最优投资策略及最优值函数(破...     

公司债务与内生破产的实物期权方法分析

本文利用实物期权方法在风险中性概率测试下研究公司的债务与内生破产问题。将公司破产与接管理解为股东和债权人持有的期权,在得到写在公司资产上的各种相机权益的价值后,本文详细讨论风险债务的债权人在公司破产时选择破产清算或破产营运时公司债务水平与破产决策之间的关系,分析了不同杠杆水平的公司破产决策问题,发现公司债务对公司的破产决策具有重要影响。杠杆公司股东策略违约的破产时间与公司价值最大化的时间通常不一致,破产导致公司价值损失;而且由于杠杆融资,公司破产时间与纯股本公司破产时间不一致,破产带来效率损失。本文的分析对我国公司债务与破产政策的研究具有一定借鉴意义。     

超效率DEA模型的区间扩展

将一种改进的DEA模型-超效率DEA(SE-DEA)模型[1]拓展到区间投入产出情形,得到区间SE-DEA模型。定义了一种反映决策者满意度的区间数序关系。当决策者给定一满意度水平,将区间SE-DEA中的区间不等式约束转化为确定型约束。研究了该满意度水平的另一层含义,即决策者对除被评价决策单元外的其它决策单元的偏好程度,据此将区间SE-DEA中的区间等式约束和区间目标函数转化为确定型。最终将区间SE-DEA转化为某一满意度水平下的确定型SE-DEA,并进行求解。最后将文中方法应用于天津市某4家科研所的效率预测问题之中。     

信息非对称条件下的质量预防决策分析

研究了不同信息条件下供应链的质量预防问题,在文献[1,2]建立的有关质量签约问题的优化模型基础上,把供应商作为委托人和购买商作为代理人建立了供应链的质量预防决策委托代理模型。其中,质量预防水平和供应商要求购买商的前向支付是供应商的决策变量,质量评价水平是购买商的决策变量。本文重点研究了了非对称信息下供应链的质量预防和前向支付问题,考虑了购买商质量评价信息隐匿情况,运用极大值原理推导了供应商的质量预防和前向支付的最优解。最后结合一个农机公司拖拉机销售问题进行了仿真计算和分析,对比了不同信息环境下的决策结果。     

基于偏尾分布的证券价格行为特征分析方法

在偏尾分布^[2-3]的基础上,本文首次给出了证券价格行为指标、极限价格、均衡价格、重心价格等基本特征的概念及解析表达式,尤其是给出了极限价格和重心价格的计算方法,前者有助于判断价格运行趋势在不同显著水平下的反转位置,后者有助于判断市场当前的价格重心是否合乎理性。     

动态全参数自调整BP神经网络模型的改进

针对BP网络存在的缺点,有多种改进方法。本文在文献[14]的基础上,从算法和网络结构设计方面又进行了综合改进,这不仅加快了网络的收敛速度,而且优化了网络的拓扑结构,从而增强了BP神经网络的适应能力。将新改进的BP网络应用于我国能源消费预测,取得了令人满意的效果。     

金融网络的模型和优化

金融网络就是经济系统中资金循环,文献[1-8]研究了金融网络的模型。本文则在文献[1-8]金融网络模型的基础之上,建立了资产、负债、适度规模和价格的改进模型。这一改进模型考虑了所有经济部门的金融工具的风险、金融网络的经济资源约束、资产和负债的会计帐户约束等问题。模型的改进适用于应用。文章采用了进化规划算法,并依此进行仿真实验。     

A Comparative Analysis of PRA and Intelligent Adversary Methods for Counterterrorism Risk Management

In counterterrorism risk management decisions, the analyst can choose to represent terrorist decisions as defender uncertainties or as attacker decisions. We perform a comparative analysis of probabilistic risk analysis (PRA) methods including event trees, influence diagrams, Bayesian networks, decision trees, game theory, and combined methods on the same illustrative examples (container screening for radiological materials) to get insights into the significant differences in assumptions and results. A key tenent of PRA and decision analysis is the use of subjective probability to assess the likelihood of possible outcomes. For each technique, we compare the assumptions, probability assessment requirements, risk levels, and potential insights for risk managers. We find that assessing the distribution of potential attacker decisions is a complex judgment task, particularly considering the adaptation of the attacker to defender decisions. Intelligent adversary risk analysis and adversarial risk analysis are extensions of decision analysis and sequential game theory that help to decompose such judgments. These techniques explicitly show the adaptation of the attacker and the resulting shift in risk based on defender decisions.     

Assessing the export trade risk of bluetongue virus serotypes 4 and 8 in France

Bluetongue (BT) causes an economic loss of $3 billion every year in the world. After two serious occurrences of BT (bluetongue virus [BTV] occurrence in 2006 and 2015), France has been controlling for decades, but it has not been eradicated. As the largest live cattle export market in the world, France is also one of the major exporters of breeding animals and genetic materials in the world. The biosafety of its exported cattle and products has always been a concern. The scenario tree quantitative model was used to analyze the risk of BTV release from French exported live cattle and bovine semen. The results showed that with the increase in vaccination coverage rates, the risk decreased. If the vaccine coverage is 0%, the areas with the highest average risk probability of BTV-4 and BTV-8 release from exported live cattle were Haute-Savoie and Puy-de-Dôme, and the risk was 2.96 × 10^–4 and 4.25 × 10^–4, respectively. When the vaccine coverage was 90%, the risk probability of BTV-4 and BTV-8 release from exported live cattle was 2.96 × 10^–5 and 4.24 × 10^–5, respectively. The average probability of BTV-8 release from bovine semen was 1.09 × 10^–10. Sensitivity analysis showed that the probability of false negative polymerase chain reaction (PCR) test and the probability of BT infection in the bull breeding station had an impact on the model. The identification of high-risk areas and the discovery of key control measures provide a reference for decision makers to assess the risk of French exports of live cattle and bovine semen.     

APPROXIMATIONS FOR THE GI/G/m QUEUE

Queueing models can usefully represent production systems experiencing congestion due to irregular flows, but exact analyses of these queueing models can be difficult. Thus it is natural to seek relatively simple approximations that are suitably accurate for engineering purposes. Here approximations for a basic queueing model are developed and evaluated. The model is the GI/G/m queue, which has m identical servers in parallel, unlimited waiting room, and the first-come first-served queue discipline, with service and interarrival times coming from independent sequences of independent and identically distributed random variables with general distributions. The approximations depend on the general interarrival-time and service-time distributions only through their first two moments. The main focus is on the expected waiting time and the probability of having to wait before beginning service, but approximations are also developed for other congestion measures, including the entire distributions of waiting time, queue-length and number in system. These relatively simple approximations are useful supplements to algorithms for computing the exact values that have been developed in recent years. The simple approximations can serve as starting points for developing approximations for more complicated systems for which exact solutions are not yet available. These approximations are especially useful for incorporating GI/G/m models in larger models, such as queueing networks, wherein the approximations can be components of rapid modeling tools.