保单个数为几何分布的总索赔额分布函数的实用界值

本文根据单个保单索赔额分布函数F(x)的一些特殊性质,研究了开放个别风险模型在保单个数N为几何分布下,总索赔额分布函数Fs(x)=∑(1-p)PnF(n)(x)的界值问题,得到一些实用的、便于数值计算的n=0界值结果,具有重要的应用价值.     

未决赔款准备金的分布函数及其界值研究

根据保单组合的损失赔付额分布函数的性质,应用排队模型的分析方法,本文研究了未决赔款准备金分布函数.得到针对未来某一时间段内保险公司所需计提的未决赔款准备金分布函数的上界和下界,而且给出的计算实例表明所得到的未决赔款准备金分布函数的上界和下界是十分有效的.     

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。     

Erlang风险模型有限时间的破产概率

Erlang风险模型广泛应用于排队论、控制论以及金融风险过程.本文在索赔来到(claim-arrival)为Erlang过程,索赔额服从帕雷托分布以及具有常数利息力度的假设下,得到了有限时间内破产概率的渐近表达公式.该结果实质性地推广了Kluppelberg and Stadtmuller[1]和Tang[2]的结果:前者考虑了无穷时间的破产概率,而后者考虑的过程局限为泊松的.由破产模型与排队模型之间的联系可知,本文的结果在管理科学中有许多应用.     

免赔额和NCD赔付条件下保险索赔次数的分布

本文分析了免赔额及NCD赔付条件对索赔次数分布的影响,通过比较风险事件与索赔事件的差异引出了一类同质集合保单索赔次数的分布(PG分布);给出了PG分布的性质及参数估计方法。通过两个保险实例展示了数据拟合效果。     

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.     

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。     

展望理论的权重函数与证券收益率分布

证券收益率的概率受到投资者主观判断概率的影响,从而形成“尖峰厚尾”等形态特征。在展望理论的权重函数的基础上,建立了收益率分布主观概率模型,对收益率分布的“厚尾分布”、中部形态及整体形态特征进行了理论推导。并利用深圳证券市场的441支股票的实际收益率分布的概率形态进行了实证分析,实证检验的结果与提出的模型所推导的特征性质得到了一致的吻合。     

基于Z值模型的企业财务预警系统构建

本文选取重庆长安汽车股份有限公司进行实证分析,通过对其09年半年报财务指标的截取及分析,建立Z值模型对长安公司存在的系统风险进行分析,并提出运用z分析法对我国上市公司进行财务分析时需要注意的问题。     

基于权值的多阶段风险值证券组合问题研究

风险值问题一直是金融领域中研究风险管理的一个重要课题,在金融经济中有着重要广泛的应用.本文在已有的条件风险值的基础上建立了一种新的多阶段CVaR模型.我们给出了多阶段下基于权值的α-CVaR损失值的概念及相应的多阶段CVaR模型,我们证明了它等价于求解一个非线性规划问题.这对于求解多阶段风险值问题具有重要作用.     

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。     

基于债权终止的可违约债券定价

已有实证结果表明流动性风险及其与违约风险的相关性是影响可违约债券收益率的重要因素,然而目前的研究还不能建立一种计算简便且同时包含流动性风险以及风险相关尤其是尾部相关性的定价模型。本文将流动性风险与违约风险都描述为债权终止事件驱动型的风险,从而可以利用与违约时间类似的出售时间来刻画流动性风险过程。基于债权终止事件的发生时间,本文拓展了简约模型以考虑流动性风险及风险相关性。与以往的研究相比,基于债权终止时间的模型具备诸多优势:模型简便适合大规模计算、允许时变流动性风险、包含尾部相关等较为丰富的风险相关性结构。数值算例表明,本文的模型能更好地刻画流动性风险溢价以及风险的尾部相关性对债券收益率曲线上下尾端的影响。     

The Use of Individual and Societal Risk Criteria Within the Dutch Flood Safety Policy—Nationwide Estimates of Societal Risk and Policy Applications

The Dutch government is in the process of revising its flood safety policy. The current safety standards for flood defenses in the Netherlands are largely based on the outcomes of cost‐benefit analyses. Loss of life has not been considered separately in the choice for current standards. This article presents the results of a research project that evaluated the potential roles of two risk metrics, individual and societal risk, to support decision making about new flood safety standards. These risk metrics are already used in the Dutch major hazards policy for the evaluation of risks to the public. Individual risk concerns the annual probability of death of a person. Societal risk concerns the probability of an event with many fatalities. Technical aspects of the use of individual and societal risk metrics in flood risk assessments as well as policy implications are discussed. Preliminary estimates of nationwide levels of societal risk are presented. Societal risk levels appear relatively high in the southwestern part of the country where densely populated dike rings are threatened by a combination of river and coastal floods. It was found that cumulation, the simultaneous flooding of multiple dike rings during a single flood event, has significant impact on the national level of societal risk. Options for the application of the individual and societal risk in the new flood safety policy are presented and discussed.     

On The Method of Discrete Probability Distributions in Risk and Reliability Calculations–Application to Seismic Risk Assessment

If the point of view is adopted that in calculations of real-world phenomena we almost invariably have significant uncertainty in the numerical values of our parameters, then, in these calculations, numerical quantities should be replaced by probability distributions and mathematical operations between these quantities should be replaced by analogous operations between probability distributions. Also, practical calculations one way or another always require discretization or truncation. Combining these two thoughts leads to a numerical approach to probabilistic calculations having great simplicity, power, and elegance. The philosophy and technique of this approach is described, some pitfalls are pointed out, and an application to seismic risk assessment is outlined.     

Mental Models in Risk Assessment: Informing People About Drugs

One way to communicate about the risks of drugs is through the use of package inserts. The problems associated with this medium of informing patients have been investigated by several researchers who found that people require information about drugs they are using, including extensive risk information, and that they are willing to take this information into account in their usage of drugs. But empirical results also show that people easily misinterpret the information given. A conceptual framework is proposed that might be used for better understanding the cognitive processes involved in such a type of risk assessment and communication. It is based on the idea that people develop, through experience, a mental model of how a drug works, which effects it might produce, that contraindications have to be considered, etc. This mental model is "run" when a specific package insert has been read and a specific question arises such as, for example, whether certain symptoms can be explained as normal or whether they require special attention and action. We argue that the mental model approach offers a useful perspective for examining how people understand package inserts, and consequently for improving their content and design. The approach promises to be equally useful for other aspects of risk analysis that are dependent upon human judgment and decision making, e.g., threat diagnosis and human reliability analysis.     

The Use of PBPK Models to Inform Human Health Risk Assessment: Case Study on Perchlorate and Radioiodide Human Lifestage Models

Physiologically‐based pharmacokinetic (PBPK) models are often submitted to or selected by agencies, such as the U.S. Environmental Protection Agency (U.S. EPA) and Agency for Toxic Substances and Disease Registry, for consideration for application in human health risk assessment (HHRA). Recently, U.S. EPA evaluated the human PBPK models for perchlorate and radioiodide for their ability to estimate the relative sensitivity of perchlorate inhibition on thyroidal radioiodide uptake for various population groups and lifestages. The most well‐defined mode of action of the environmental contaminant, perchlorate, is competitive inhibition of thyroidal iodide uptake by the sodium‐iodide symporter (NIS). In this analysis, a six‐step framework for PBPK model evaluation was followed, and with a few modifications, the models were determined to be suitable for use in HHRA to evaluate relative sensitivity among human lifestages. Relative sensitivity to perchlorate was determined by comparing the PBPK model predicted percent inhibition of thyroidal radioactive iodide uptake (RAIU) by perchlorate for different lifestages. A limited sensitivity analysis indicated that model parameters describing urinary excretion of perchlorate and iodide were particularly important in prediction of RAIU inhibition; therefore, a range of biologically plausible values available in the peer‐reviewed literature was evaluated. Using the updated PBPK models, the greatest sensitivity to RAIU inhibition was predicted to be the near‐term fetus (gestation week 40) compared to the average adult and other lifestages; however, when exposure factors were taken into account, newborns were found to be populations that need further evaluation and consideration in a risk assessment for perchlorate.     

Uncertainty and Variability Analysis in Multiplicative Risk Models

Currently, there is a trend away from the use of single (often conservative) estimates of risk to summarize the results of risk analyses in favor of stochastic methods which provide a more complete characterization of risk. The use of such stochastic methods leads to a distribution of possible values of risk, taking into account both uncertainty and variability in all of the factors affecting risk. In this article, we propose a general framework for the analysis of uncertainty and variability for use in the commonly encountered case of multiplicative risk models, in which risk may be expressed as a product of two or more risk factors. Our analytical methods facilitate the evaluation of overall uncertainty and variability in risk assessment, as well as the contributions of individual risk factors to both uncertainty and variability which is cumbersome using Monte Carlo methods. The use of these methods is illustrated in the analysis of potential cancer risks due to the ingestion of radon in drinking water.