基于聚类分析的申贷信用等级评价方法

 为了解决申贷信用等级评价问题,介绍了解决银行申请贷款信用等级评价中聚类分析采用的基本概念及术语,提出了2种聚类算法包括基于信贷数据的聚类算法δ-kmeans;基于高维信贷数据的聚类算法ASC,并通过实验对其性能进行比较分析,实验表明:①δ-kmeans算法在信贷风险的控制上取得较好效果;②相比传统k-means和Coweb算法,ASC算法在聚类高维信贷数据上更加有效.利用k-means算法对银行信贷数据的聚类动力学关系进行分析.最后,给出了聚类分析算法在银行信贷领域应用的的难点.     

用约化方法对可展期的企业债券定价

可展期的企业债券是指企业在债券到期日有权根据当时的利率水平决定是否以同样的收益率将债券到期日延长,它可使企业规避利率风险,但是延展期内投资人要承担企业破产的风险,为此,必须给债券投资人以补偿.文中用约化模型处理企业违约风险,在随机利率下,用偏微分方程的方法给出了可展期的企业债券定价的公式,并讨论了它与普通企业债券在收益率上的差异.     

信用攸关的利率互换的定价

在约化方法的框架下,针对实务界出现的一种新型信用衍生产品--信用攸关的利率互换(credit contingentinterest rate swap,CCIRS),以偏微分方程(partial differentialequation,PDE)为方法,利用对冲原理建立了定价模型.之后分别利用显式和隐式差分对模型进行数...     

酉矩阵的一个新判定

把矩阵体积的概念推广到复数域上,并利用复矩阵体积的性质给出酉矩阵的一个新判定.     

Jordan标准形定理的一个矩阵证明

运用矩阵的初等运算重新证明了Jordan标准形定理.     

浅议我国银团贷款发展的制约因素及对策

分析了银团贷款的特点和优势,概述了我国银团贷款发展现状及制约因素,阐述了大力推进我国银团贷款发展的对策建议。     

浅谈阜新煤田东梁区辉绿岩活动对煤层气含量的影响

东梁区岩浆岩为第三纪喜山期产物,岩性为辉绿岩,呈高角度岩墙侵入。共组合25条辉绿岩墙,其中20条分布在煤层可采范围内。辉绿岩体以多种形式侵入到煤、岩层中,由于辉绿岩的侵入,引起局部煤层的热变质,受辉绿岩侵入体的烘烤作用,煤的变质程度增加,煤阶增高,煤层气含量增加。辉绿岩侵入体的烘烤作用使煤的煤层气最大吸附量增加,但煤变成天然焦后,储层煤层气含量降至很低甚至不含煤层气。     

专业运动员职级制度设计构想——我国专业运动员职级制度研究之三

国家高度重视运动员保障工作,各省市政府也都在进行制度创新和政策研究。本文在调查研究的基础上,结合竞技体育工作的规律、特征,借鉴其他职业领域职级制度的政策、经验,构建了专业运动员职级框架。     

Business failure prediction using decision trees

Accurate business failure prediction models would be extremely valuable to many industry sectors, particularly financial investment and lending. The potential value of such models is emphasised by the extremely costly failure of high‐profile companies in the recent past. Consequently, a significant interest has been generated in business failure prediction within academia as well as in the finance industry. Statistical business failure prediction models attempt to predict the failure or success of a business. Discriminant and logit analyses have traditionally been the most popular approaches, but there are also a range of promising non‐parametric techniques that can alternatively be applied. In this paper, the relatively new technique of decision trees is applied to business failure prediction. The numerical results suggest that decision trees could be superior predictors of business failure as compared to discriminant analysis. Copyright © 2009 John Wiley & Sons, Ltd.     

Retail default prediction by using sequential minimal optimization technique

This paper employed sequential minimal optimization (SMO) to develop default prediction model in the US retail market. Principal components analysis is used for variable reduction purposes. Four standard credit scoring techniques—naïve Bayes, logistic regression, recursive partitioning and artificial neural network—are compared to SMO, using a sample of 195 healthy firms and 51 distressed firms over five time periods between 1994 and 2002. The five techniques perform well in predicting default particularly one year before financial distress. Furthermore, the prediction still remains sound even 5 years before default. No single methodology has the absolute best classification ability, as the model performance varies in terms of different time periods and variable groups. External influences have greater impacts on the naïve Bayes than other techniques. In terms of similarity with Moody's ranking, SMO excelled over other techniques in most of the time periods. Copyright © 2008 John Wiley & Sons, Ltd.