基于多元统计分析的商业银行绩效评价研究

本文以国内13家商业银行的2008年效率指标体系数据为样本,运用因子分析法,找出影响商业银行效率状况的因子,计算各样本的因子得分;根据银行效率综合评分公式,计算各样本银行的综合评价得分;根据各样本的因子得分,用聚类分析的方法将商业银行运营状况进行分类。结合分类结果及综合评分对各样本银行评价结果为:股份制商业银行的经营绩效综合评价得分较高,而国有商业银行的经营绩效综合评价得分较低;国有商业银行除在偿债能力因子平均得分上与股份制商业银行差距不大外,在发展能力因子、盈利能力因子及经营效率因子上平均得分均较大地低于股份制商业银行。     

柴油机另部件磨耗状态与润滑油光谱分析结果的多元判别

本文利用润滑油中磨耗金属的光谱分析结果,提出了适合国情的判断内燃机车柴油机另部件磨耗状态的多元判别法.对判别的特征因子进行了选择,对其分辨能力进行了定量估计.证明了润滑油中铁含量的变化速率是主要特征因子.报告了马氏距离判别法的判别函数及判别效果,对明显的非正常磨耗准确率达88.0%,正常磨耗和少量非正常磨耗准确率达95.5%.此外,还报告了两种简易判别法.最后,讨论了实际应用效果和今后展望.     

A spherical representation of a correlation matrix

It is common practice to perform a principal component analysis (PCA) on a correlation matrix to represent graphically the relations among numerous variables. In such a situation, the variables may be considered as points on the unit hypersphere of an Euclidean space, and PCA provides a sort of best fit of these points within a subspace. Taking into account their particular position, this paper suggests to represent the variables on an optimal three-dimensional unit sphere.

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Résumé Il est classique d'utiliser une analyse en composantes principales pour représenter graphiquement une matrice de corrélation. Dans une telle situation, les variables peuvent être considérées comme des points sur l'hypersphère unité d'un espace Euclidien, et l'analyse en composantes principales permet d'obtenir une bonne approximation de ces points à l'aide d'un sous-espace Euclidien. Prenant en compte une telle situation géométrique, le présent article suggère de représenter les variables sur une sphère tri-dimensionelle optimale.

     

The Time and Cost Prediction of Tunnel Boring Machine in Tunnelling

0Introduction Thetimeandcostprediction,whicharegettingonslow ly,arealwaysthekeyfactorthatdeterminewhethertheassistantdecision makingsystemisutility.Soitisnecessarytoresearchonthetimeandcostneededinaspecialprojectand theirprobabilitydistributing,whichcouldbeusedasacredi blebasisforsigningacontractandasatooltooptimizecon structionplanandtoreducecost.SystemofOkubo[1]hasthreephases:①Checktheenvironmentsothatitissuitable forthefundamentalrequirementsinwhichtunnelboringma chine(TBM)isused;②Estim…     

求解多元函数总体极小谷峰法的验证与测试

本文介绍了对求多元函数总体极小谷峰法的基本思路,简述了算法的收敛和复杂性,并用多个典型函数进行了验证和测试.计算结果表明,相比其它算法,谷峰法简单,实用,运算速度快,对目标函数要求低,易推广应用.     

FORECASTING NIKKEI 225 INDEX WITH SUPPORT VECTOR MACHINE

Support Vector Machine (SVM) is a very specific type of learning algorithms characterized by the capacity control of the decision function, the use of the kernel functions and the sparsity of the solution. In this paper, we investigate the predictability of financial movement direction with SVM by forecasting the weekly movement direction of NIKKEI 225 index. To evaluate the forecasting ability of SVM, we compare the perfor-mance with those of Linear Discriminant Analysis, Quadratic Discriminant Analysis and Elman Backpropagation Neural Networks. The experiment results show that SVM outperforms other classification methods. Furthermore, we propose a combining model by integrating SVM with other classification methods. The combining model performs the best among the forecasting methods.     

Volatility forecasting for risk management

Recent research has suggested that forecast evaluation on the basis of standard statistical loss functions could prefer models which are sub‐optimal when used in a practical setting. This paper explores a number of statistical models for predicting the daily volatility of several key UK financial time series. The out‐of‐sample forecasting performance of various linear and GARCH‐type models of volatility are compared with forecasts derived from a multivariate approach. The forecasts are evaluated using traditional metrics, such as mean squared error, and also by how adequately they perform in a modern risk management setting. We find that the relative accuracies of the various methods are highly sensitive to the measure used to evaluate them. Such results have implications for any econometric time series forecasts which are subsequently employed in financial decision making. Copyright © 2002 John Wiley & Sons, Ltd.     

基于多元GARCH模型的可转换债券市场与股票市场的波动关系研究

可转换债券作为一种混合型的金融衍生品,已经成为金融市场中重要的组成成分,并且其市场与股票市场之间又是互相影响的,它们的共同发展对金融市场的繁荣和企业竞争力的提高方面起到了积极的推动作用.因此,对可转债市场与股票市场之间关系的实证研究具有一定的理论与现实意义.基于上证指数(000001)与上证转债指数(000139),运用BEKK形式的多元GARCH模型来实证研究可转债市场与股票市场之间的波动关系及其溢出效应.实证结果发现,这两个市场之间有正相关的关系,并且存在双向的波动溢出效应.     

基于多元线性回归模型和灰色关联分析的江苏省粮食产量预测

针对江苏省近年来粮食产量波动的现状,采用灰色关联模型对2000~2009年江苏省粮食产量进行分析.结果发现,播种面积、化肥施用量、年均气温、年均降水以及农药施用量等5个因素是粮食产量波动的主导因素.然后在灰关联分析的基础上建立多元线性回归方程对2010~2012年江苏省粮食产量进行预测与验证,结果表明预测效果良好.最后,针对现状提出了相关建议.     

用SPSS研究耀州瓷和南宋官瓷原料来源关系

选取陕西耀州瓷和杭州郊坛下南宋官瓷样品,用中子活化分析(NAA)测得各个样品中29种元素的含量,用多元统计分析(SPSS)中的主成分因子分析法对样品进行分类、研究,从而揭示出耀州瓷胎和南宋官瓷胎的原料产地彼此独立,各自有着较为集中、稳定的原料来源;耀州瓷釉和南宋官瓷釉的釉料配方明显不同,历代耀州青瓷釉的配方相近,但不同釉色的耀州瓷釉却有着迥然相异的原料配方.