A New Criterion for Environmental Risk Management of Multiplication Processes

This paper aims to propose ERT （Expected Reaching Time）, a new risk adverse evaluation criterion of finite multiplication processes, and to examine its properties in relation to the dominance criterion. The ERT means the expected time that takes for an objective valiable to reach a target value. To deal with the environmental risk involved in the process, the expectation maximizing strategy may be the most well known. However, for many cases the dominance strategy rather than the expectation maximizing strategy is adopted and works very well. In this paper we first prove rigorously that minimization of the ERT is equivalent to the dominance criterion in the infinite period. Then we demonstrate by simulation that the ERT gives almost equal evaluation as the dominance criterion even for the finite multiplications, after showing that it is approximately proportional to the logarithm of the target value.     

Novel method for the evaluation of data quality based on fuzzy control

One of the goals of data collection is preparing for decision-making, so high quality requirement must be satisfied. Rational evaluation of data quality is an effective way to identify data problem in time, and the quality of data after this evaluation is satisfactory with the requirement of decision maker. A fuzzy neural network based research method of data quality evaluation is proposed. First, the criteria for the evaluation of data quality are selected to construct the fuzzy sets of evaluating grades, and then by using the learning ability of NN, the objective evaluation of membership is carried out, which can be used for the effective evaluation of data quality. This research has been used in the platform of ＇data report of national compulsory education outlay guarantee＇ from the Chinese Ministry of Education. This method can be used for the effective evaluation of data quality worldwide, and the data quality situation can be found out more completely, objectively, and in better time by using the method.     

A Credit Risk Evaluation Approach to Neural Network Training by Means of Financial Ratios

In recent years artificial neural networks are used to recognize the risk category of investigated companies. The research is based on data from 81 listed enterprises that applied for credit in domestic regional banks operating in China. The backpropagation algorithm-the multilayer feedforward network structure is described. Each firm is described by 9 diagnostic variables and potential borrowers are classified into four classes. The efficiency of classification is evaluated in terms of classification errors calculated from the actual classification made by the credit officers. The results of the experiments show that LevenbergMarque training error is smallest among 4 learning algorithms and its performance is better, and application of artificial neural networks and classification functions can support the creditworthiness evaluation of borrowers.     

Evaluation matrix with the speed feature based on double inspiriting control lines

Methods of the comprehensive evaluation have been studied for many years. However, the change speed of evaluated objects was rarely considered by the existing evaluation methods. An evaluation matrix is proposed to remedy this deficiency. Firstly, the change speed state （CSS） of the evaluated objects is analyzed based on double inspiriting control lines （DICLs）, and a matrix of the CSS is constructed. Then, 72 elements in the matrix are analyzed, and formulas describing each CSS are given. The efficiency of the proposed evaluation matrix is proved when the CSS merges with the change speed trend （CST） in the dynamic comprehensive evaluation. Finally, a computing example shows that the proposed evaluation matrix is feasible in the dynamic comprehensive evaluation with the speed feature.     

Estimation of chain reaction bankruptcy structure by chance discovery method — With time order method and directed KeyGraph

Chain reaction bankruptcy is regarded as common phenomenon and its effect is to be taken into account when credit risk portfolio is analyzed. But consideration and modeling of its effect leave much room for improvement. That is mainly because method for grasping relations among companies with limited data is underdeveloped. In this article, chance discovery method is applied to estimate industrial relations that are to include companies＇ relations that transmit chain reaction of bankruptcy. Time order method and directed KeyGraph are newly introduced to distinguish and express the time order among defaults that is essential information for the analysis of chain reaction bankruptcy. The steps for the data analysis are introduced and result of example analysis with default data in Kyushu, Japan, 2005 is presented. The structure estimated by the new method is compared with the structure of actual account receivable holders of bankrupted companies for evaluation.     

Multiple-Attribute and Multilevel Synthetic Evaluation Model and Its Application

On the basis of analyzing the flaws of present multiple-attribute and multilevel evaluation methods, concerning the problem of characteristics of the multiple-attribute and multilevel system s appraisal and the particular emphasis on the respective attributes in the evaluation process, as well as its relevance to the environment, an optimal attribute system is proposed, and the multiplicative analytic hierarchy process (MAHP) is used to obtain subjective weight coefficients and the objective weight coefficient evaluating method is given. The deviation between the index value of each level and the values of the same index of other levels are formulated, and an optimal model is gained, thus establishing the weight coefficients of the whole optimal attribute system. Furthermore, the detailed implementation procedure of this method is introduced. Besides, favorable results have been gained by applying the model to the practical problems of economic evaluation.     

ESTIMATION OF CHAIN REACTION BANKRUPTCY STRUCTURE BY CHANCE DISCOVERY METHO—WITH TIME ORDER METHOD AND DIRECTED KEYGRAPH

Chain reaction bankruptcy is regarded as common phenomenon and its effect is to be taken into account when credit risk portfolio is analyzed.But consideration and modeling of its effect leave much room for improvement.That is mainly because method for grasping relations among companies with limited data is underdeveloped.In this article,chance discovery method is applied to estimate industrial relations that are to include companies' relations that transmit chain reaction of bankruptcy. Time order method and directed KeyGraph are newly introduced to distinguish and express the time order among defaults that is essential information for the analysis of chain reaction bankruptcy.The steps for the data analysis are introduced and result of example analysis with default data in Kyushu, Japan,2005 is presented.The structure estimated by the new method is compared with the structure of actual account receivable holders of bankrupted companies for evaluation.     

Review on the Progress for Mutual Fund Performance Dynamic Evaluation Theory

The progress of performance dynamic evaluation theory for mutual fund from different points is summarized. The theories include conditional performance evaluation model, stochastic discount factors model, dynamic selecting and timing ability, portfolio change measure and so on. Meanwhile, this paper also summarized the progress of Performance Persistence and Survlvorshlp Bias. Then the analysis of the development tendency for the performance evaluation of portfolio is made.     

Optimal Investment with Noise Trading Risk

This paper investigates the optimal dynamic investment for an investor who maximizes constant absolute risk aversion （CARA） utility in a discrete-time market with a riskfree bond and a risky stock. The risky stock is assumed to present both the dividend risk and the price risk. With our assumptions, the dividend risk is equivalent to fundamental risk, and the price risk is equivalent to the noise trading risk. The analytical expression for the optimal investment strategy is obtained by dynamic programming. The main result in this paper highlights the importance of differentiating between noise trading risk and fundamental risk for the optimal dynamic investment.     

Production planning problem with pricing under random yield: CVaR criterion

In this paper, we address a basic production planning problem with price dependent demand and stochastic yield of production. We use price and target quantity as decision variables to lower the risk of low yield. The value of risk control becomes more important especially for products with short life cycle. This is because, the profit implications of low yield might be unbearable in the short run. We apply Conditional Value at Risk （CVaR） to model the, risk. CVaR measure is a coherent risk measure and thereby having nice conceptual and mathematical underpinnings. It is also widely used in practice. We consider the problem under general demand function and general distribution function of yield and find sufficient conditions under which the problem has a unique local maximum. We also both analytically and numerically analyze the impact of parameter change on the optimal solution. Among our results, we analytically show that with increasing risk aversion, the optimal price increases. This relation is opposite to that of in Newsvendor problem where the uncertainty lies in demand side.     

基于改进风险矩阵方法的武器装备采办风险评估

在时国外广泛采用的风险矩阵评估方法进行全面分析和系统总结的基础上,针对风险矩阵方法的不足,结合我国武器装备采办风险评估的客观实际和需要,对其进行了适应性改进.运用改进的风险矩阵方法,以某型号的采办为例示范性地进行了风险评估,从而为制定科学合理的武器装备采办风险管理决策提供决策依据.     

基于证据理论的软件开发风险评估方法

通过将软件开发过程分解为分析、设计、实施阶段,根据决策者对每一阶段的技术风险、费用风险、进度风险的确信度,给出了一种基于Dempster-Shfer证据组合理论的风险评估方法.从而,将软件开发过程中影响风险的多种不确定性定性指标转化为确定的定量指标进行评价.最后通过实例说明了该方法的有效性.     

审计评价Agent系统结构模型与优化

审计评价的Agent系统问题,就是行为审计博弈方的最优对策问题,即审计服务双方对其收益最大化的管理与优化.因此,风险因素在审计收益管理中有着重要影响,当把风险因素引入审计评价系统,并设定评价为Agent模式后,审计资产所有者风险份额的相对控制会从外部推动审计服务与评价效能的提升,内部会启动提高审计资产所有者效率的动力机制,从而提高了评价系统活力.通过审计评价系统的Agent模型与优化调控审计绩效评价管理方向,有助于促进审计绩效的持续改善,更好地促进审计服务创新发展.     

绿色食品生产经营中的风险及其管理

分析了绿色食品生产经营中的主要风险———自然风险、技术风险、服务风险、市场风险、管理风险,找出了各类风险的风险因素;建立了风险综合评价指标体系,给出了风险评价方法和模型;从损失补偿、完善市场体系、加强服务、加强立法执法、提高从业人员素质等方面探讨了风险管理策略。表1,参16。     

基于多元联系数集对分析的航空维修风险态势评估

为提高航空维修风险评估的有效性,引入多元联系数集对分析理论,将评估系统中的确定与不确定因素作为一个整体进行处理。在考虑专家权重的基础上,运用不确定层次分析法确定各评估指标的权重区间,并通过三元联系数的联系度表达式将权重区间转化为权重精确值。对三元联系数的不确定项进行拓展得到五元联系数表达式,以此为基础建立风险的同异反评估模型。根据由该模型计算出的集对势结果对系统风险态势进行评判,并利用各阶偏联系数对风险发展趋势进行分析,实现静态和动态评估的有效结合。以某航空公司维修基地为实例,计算和分析结果表明了该方法在系统风险评估及趋势分析中的可行性与有效性。     

基于产品市场生命周期的产品创新项目风险估计方法

产品创新是企业在现代市场环境下经济增长的主要方式,但产品创新项目具有很高的风险性和不确定性,产品创新项目的风险评估与管理己成为学术界和企业界所关注的重要研究课题.产品创新项目风险估计是产品创新项目风险评估的基础,是产品创新项目风险控制和管理的前提与关键.本文拟从产品市场生命周期特点出发,研究具有企业产品创新特色的、个性化的产品创新项目风险估计方法.     

基于多分类离散选择模型的农产品安全风险评估研究

针对农产品安全风险评估问题,提出了一种基于多分类离散选择模型的风险评估方法。在建立农产品安全风险评估指标体系的基础上,建立有序多分类Logistic模型,给出了风险判别分析计算步骤。结合山东省出口蔬菜备案基地评价数据进行了实证研究。表3,参7。     

城市轨道交通投融资风险评价方法

利用模糊评判理论和层次分析法相结合,构建了城市轨道交通项目投融资风险评价指标体系和评价模型,并以长沙市地铁2号线一期工程为例,全面介绍了模糊层次分析法在城市轨道交通投融资风险评价中的应用,为轨道交通投融资风险控制提供参考依据。     

基于模糊证据推理的系统风险分析与评价

针对系统风险分析与评价中面临的模糊不确定风险信息建模问题,以及风险因素信息融合问题,在模糊集理论与证据理论研究的基础上,采用模糊证据推理技术, 提出了基于模糊证据推理的系统风险分析与评价方法的具体算法与处理操作流程.首先通过故障模式及影响分析进行风险识别,采用模糊信度结构模型建立风险不确定性的统一描述框架, 然后通过数据预处理算法、模糊证据推理信息融合算法以及模糊风险排序方法完成风险评价结果计算; 文末以某航天发射场火箭推进剂加注系统风险分析为例,验证了方法的可行性与有效性.该方法定量化分析系统部件的风险程度,为后续风险应对措施的制定提供辅助决策支持.     

考虑风险偏好的项目投资风险属性数学决策模型研究

在分析传统属性数学评价模型存在的缺陷基础上,把投资者风险偏好分为喜好风险型、厌恶风险型和一般风险型等三类,引入风险偏好系数这一变量,构建了具有风险偏好的项目投资风险属性数学决策模型。