【作者】 于楠；

【导师】 冯嘉礼；

【作者基本信息】 上海海事大学 ， 计算机应用技术， 2004， 硕士

【摘要】 企业综合实力是指企业在较长时期內的市场竞争能力，不仅包括现在的生存状态，也包括将来的发展前景。作为理性的投资者，正确认识和评价企业披露的信息是有必要的。目前我国上市公司会计年报中包括了一些财务指标和经营业绩指标，对考察一个企业的经营现状提供了有用的信息，但不足以准确全面地分析其经营成果、机制创新和发展潜力。 本项目试图建立更为一般性的企业综合实力评价体系，满足投资者和管理者的需要。通过定性和定量的综合的分析，可以区分企业的综合实力等级及其在同行业中所处的位置。本项目对股票分析也提出了一个解决方法。股票信息瞬息万变，从大量的股票数据中找到真正有用的信息是金融领域的一个难题。目前市面上主要通过各种参数指标的组合去描绘股市变化的规律，然而，现实情况是，人们用自己熟悉的某些参数，如：MACD、KDJ等进行的指标分析，大多都不准确。要么提前、要么滞后。至于某些人煞费苦心试图寻找的所谓“万能指标”，至今仍不知在何处。 一般认为，股票价格及其变化趋势反映的是上市公司的综合实力，怎样根据股票价格及其变化趋势，去理智地分析、评估一家上市公司的综合实力，并对该公司的“好”或“坏”作出一个准确的判断，对投资能否赢利来说是很重要的。 因为综合实力是反映上市公司“好”或“坏”的重要属性，股票价格及其变化趋势是反映综合实力(这一属性)的量特征，而“强”或“弱”则是反映综合实力(这一属性)本质的两个质特征，因此，从属性论的观点看，股票分析和决策的整个过程，就是一个事物属性的量——质特征转化过程。 基于这样一种认识，本文利用属性论方法提出的的定性映射及其转化程度函数(Conversion Degree Function，mDWCDF)η_i(x，α_i，β_i，ξ_i)既能解决属性量—转化差异，又能确定不同属性间的权重的特点，设计了一个财务分析系统，并给出了层次分析—微变因子调控算法和均分斜率趋势分析算法两个算法，给出了财务分析中的主指标权重确定和主指标预测的一种新的分析方法。定性映射及其转化程度函数在财务分析中的应用 1.层次分析一微变因子调控算法 设嘿为专家关于财务主指标的基权值的向量空间，Z二(t，，八，t。)。衅为使用层次分析法(AHP法)得到的第i位专家关于财务主指标的基权值向量，其次，对向量空间嘿中的向量进行统计平均，得到统计平均后的基权值向量E=(e，，A，e，)o然后取调控因子向量入沮一(△lrl，AA，Am气)其中八E(一1，1)，将向量E与向量入沂相加，使得权值向量变为E一协+八rl，AA，氏+么八)，最后通过数据调整向量△贝的值，当向量△趋于无穷小时就得到一个包含k(k>l)条向量的切线丛，则该切线丛内的向量可认为是主指标权值的较优解。 2.均分斜率趋势分析法 首先假设财务主指标的走势曲线为:P(x)一bl十bzx+·+气广一‘(脚<n)，采用多项式数据拟合，求出:b‘，i二l，A，m。其次，将拟合方程根据属性论方法中的模式—向量转换特性转换为向量。然后构造一个人工神经元网络，然后根据定性基准的w_内积变换与人工神经元的关系由该人工神经元网络得到一个定性基准的w_内积变换，将向量输入进行学习，得到训练范例，然后将己有的向量输入到该定性基准的w_内积变换中，得到匹配的向量。我们由该匹配的向量可得到预测点t+1点处的值与拟合点t点处的值的大小关系。最后利用差分方程来求得预测点t+l点处的值。因此可对当前财务主指标曲线的走势进行预测。更多还原

【Abstract】 The company comprehensive competence which is the market competent ability in a long-term period includes not only survival situation now but also the future aspect. As a rational investor, recognizing and assessing successfully the information of the company is essential. In current the accounting reporters of the companies in our nation include some financial indexes and achievement indexes which provide useful information to assess the situation of the company but not enough information to analysis comprehensive achievements and innovation and latent capacity.Our project tries to establish an ordinary assessing system about company comprehensive competence to satisfy the need of investors and administrators. Through comprehensive analysis of attributive from quantity to quality, we can distinguish the level the company in. And our project provides a solution of certificate of stock analysis. The information of certificate of stock is so various that it is difficult to find the real useful information even to the economists. The main approach currently depicting the currentness of the certificate of the stock is the association of the parameters. But many people have found that to analysis with the facility of associating-parameters of MACD, KDJ , etc. is inaccurate which may be advanced or lagged. And it is not unrealistical to search a universal index sign.Because the stock is the reflection of the integrated competence,it is important for a successful investment how to analysis and assess a company’scomprehensive competence according to the stock price and the change currency and then give a accurate determination about the company.Because the comprehensive competence is the major index depicting the qulity of a company and the price and change currency of stock is the quantity character of the comprehensive ability, according to which the "good" or "bad" is the quality character of the comprehensive competence, the stock analysis and decision is a quantity-quality changing process.Our project use The Qualitative Mapping model and which induced m_Dimension Weight Conversion Degree Function which could resolve the conversion difference from quantity to quality of attributive in the Attribute Theory and could certify the weights of different attributes to design a financial system and give two algorithms: one is Layerevel Analysis-Gradualchange Factor Controlling and the other is Equipartition Slope Controlling. So we can use these methods to give a new analysis way to certify the main weight in a financial analysis and to predict the main weight.the algorithm of Layerevel Analysis-Gradualchange Factor ControllingFirstly, we hypothesise that Mnm is the vectorial space of fundamental weight about the financial main index signs, and T: = (t} ,A ,tm)M"m is No. i fundamental weight vector which we get through the method of Layerevel Analysis (AHP).Secondly, we make a statistical average of all the vectors in the Mm ,andhence get the statistic fundamental vector 7 = (e} ,A ,em).Lastly, we take a Controlling factor’s vector { =(Ai,’A Ar}’ A e 1, 1) .We add the vector E and the vector ,then make vector turn into =Ari’AA ’6m+Amrm)-We can injustify the value of AR ’ wnen vector isdiminished, and get a clump of tangents which number is k(k>1). We can say that above tangents are better solutions.the algorithm of Equipartition Slope ControllingFirstly, we assume that the curvature depicting fianancial currency is:we adopt the method ofpolynome-data-fitting and hence obtain the consequence which is bj,j=1,...,m .Secondly,we turn the fitting equation into vector according to the model-vector conveying character in the The Qualitative Mapping.And we construct a manul nerve net.then we can get a m_Dimension Weight Conversion Degree Function from the net according to the relations between the m_Dimension Weight Conversion Degree Function and the manul nerve net. We input the vector and obtain the train model, finaly we obtain the fitting vector. So we can use the fitt更多还原