基于MCMC稳态模拟的贝叶斯经验费率厘定信用模型

B黨lmann-Straub model is one of the most famous applications of the Bayesian method for the experience rate making.However,by the traditional B黨lmann-Straub model one cannot get the unbiased posterior estimation of the parameters when there is not sufficient prior information for the structural parameters;What's more,the difficult of computing high dimension numeration limits the application of Bayesian method.This paper introduces the Markov chain Monte Carlo simulaton method based on the Gibbs sampling after analyzing the structure of the B黨lmann-Straub model and sets up the Bayesian credibility model for estimating the predictive risk premium.Also by using the results of the numeration analysis,this paper proves that from this model one can get the posterior distributions of the parameters dynamically and the posterior estimation of the censoring parameters in the situation that exists unknown parameters,as well as improve the precision of the numeration,which can be helpful to find the heterogeneity of the premium.     

现代信用风险度量模型的实证比较与适用性分析

本文通过实证比较分析发现,现代信用风险度量模型对银行贷款的违约率、贷款损失和损失率的预测结果的差异性较大;但信用监测模型和信用风险附加法所预测的经济资本配置比例不仅符合巴塞尔协议对银行贷款经济资本的要求,也略大于实际应该配置的比例,实证表明了它们对度量我国商业银行贷款组合的信用风险具有较好的适用性.此外,本文也充分验证了借款人信用等级的不同,银行贷款经济资本配置的比例会有显著性的差异.     

Toward Improved Communication about Wildland Fire: Mental Models Research to Identify Information Needs for Natural Resource Management

The management of natural- and human-induced wildland fires is an intricate process that must balance two considerations: that of fire as a necessary natural disturbance and that of the risks that fire poses. Reconciling tradeoffs between these risks and benefits is contingent upon informed, directed, and two-way communication between wildland fire managers and stakeholders. In an effort to aid with the design of such a communication effort, this study used mental models research to determine the unique wildland fire information and decision-making needs of stakeholders living at the wildland-urban interface of a fire-prone area. While the analysis revealed many similarities in how stakeholders conceptualized the risks and benefits of wildland fire, many misconceptions and important gaps in understanding on the part of both expert and nonexpert respondents were identified.     

Markov (Set) chains application to predict mortality rates using extended Milevsky–Promislov generalized mortality models

The mortality rates ( μx,t) measure the frequency of deaths in a fixed: population and time interval. The ability to model and forecast μx,t allows determining, among others, fundamental characteristics of life expectancy tables, e.g. used to determine the amount of premium in life insurance, adequate to the risk of death. The article proposes a new method of modelling and forecasting μx,t, using the class of stochastic Milevsky–Promislov switch models with excitations. The excitations are modelled by second, fourth and sixth order polynomials of outputs from the non-Gaussian Linear Scalar Filter (nGLSF) model and taking into account the Markov (Set) chain. The Markov (Set) chain state space is defined based on even orders of the nGLSF polynomial. The model order determines the theoretical values of the death rates. The obtained results usually provide a more precise forecast of the mortality rates than the commonly used Lee–Carter model.     

Estimation of the parameters of symmetric stable ARMA and ARMA–GARCH models

In this article, we first propose the modified Hannan–Rissanen Method for estimating the parameters of autoregressive moving average (ARMA) process with symmetric stable noise and symmetric stable generalized autoregressive conditional heteroskedastic (GARCH) noise. Next, we propose the modified empirical characteristic function method for the estimation of GARCH parameters with symmetric stable noise. Further, we show the efficiency, accuracy and simplicity of our methods with Monte-Carlo simulation. Finally, we apply our proposed methods to model the financial data.     

外语教师队伍建设要重视造就学者型教师

外语教师队伍建设要从改变教师的传统教育理念,加强专业理论知识学习,提高教师的反思意识,研究教师的发展模式等方面入手,引导培养青年教师向学者型教师发展。     

中国股票市场的信息反应曲线和股票价格波动的非对称性

股票价格波动对于市场信息的反应过程具有非对称性。通过利用多种非对称性GARCH 模型,描述和检验了沪市股票日收益率序列的条件波动性,并通过对股票市场信息影响曲线的分析,发现沪市股票价格波动中存在显著的非对称性反应。这说明股市波动对于不同的政策干预和信息冲击具有不同程度的反应,“利好消息”对股市的刺激作用仍然需要其他市场干预的配合才能发挥出来。     

股票市场的极值风险测度及后验分析研究

通过对上证综指和世界股市若干重要指数的实证研究发现,无论是在成熟资本市场还是新兴资本市场当中,极值理论(EVT)及其工具都能更加准确地刻画实际市场的极端波动和风险状况.详细说明了不同收益分布假定下风险价值(VaR)的计算方法及其后验分析(Back-testing)过程,证明了与非条件和条件正态分布以及条件t分布等主流金融理论的收益分布假定相比,条件EVT分布在测度极端市场风险时所表现出的优越性,同时说明了在不同概率水平下各种收益分布假定的精确度和适用范围.     

部分中间产出作为最终产品的两阶段合作效率

网络DEA模型研究多个进程和多个子系统的复杂系统的效率度量.针对中间产出无法为第2阶段完全消耗的情形,传统DEA模型对系统效率的评价偏高,已有网络DEA模型则对系统效率的评价偏低.本文提出部分中间产出作为最终产品,进入流通渠道的两阶段效率模型,用来测度两阶段生产过程的真实效率.采用乘积形式描述两阶段合作的特征,给出不同...     

区域电力市场结构、所有权结构对发电企业效率影响的实证研究

以我国电力产业放松规制的实践为背景,基于产业组织理论构建了区域电力市场结构、所有权结构对发电企业效率影响的综合模型。以1999~2006年电力行业上市公司的统计数据为样本,采用分层线性模型回归方法对市场结构和所有权结构对发电企业效率的影响效果和影响路径进行了研究。实证结果表明:电力行业市场集中度下降有利于我国电力企业效率提升;电力行业国有所有权比重下降有利于企业效率的提升;电力行业企业数量和国有所有权比重对企业效率存在负向交互影响作用,但不显著。