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1、学校代码10125 专业代码 025600 硕士学位论文题目 收益法中企业净现金流量值的组合预测研究姓 名 申华芳 专 业 资产评估 研究方向 企业价值评估 所属学院 管理科学与工程学院指导教师 苗敬毅 二一六年三月十日93 / 99University Code 10125 Major CodeShanxi University of Finance & EconomicsThesis for Masters DegreeTitle Research on the combination forecasting of net cash flow value of enterprises in
2、 the income approachNameShen HuafangMajorAsset Valuation Research OrientationBusiness ValuationSchool School of Management Science and EngineeringTutorMiao jingyiMarch. 10 , 2016学位论文原创性声明本人郑重声明：所呈交的学位论文，是本人在导师的指导下，独立进行研究工作所取得的成果。除文中已经注明引用的内容外，本论文不包含任何其他个人或集体已经发表或撰写过的作品成果。对本文的研究所做出重要贡献的个人和集体，均已在文中以明确
3、方式标明。本人完全意识到本声明的法律结果由本人承担。学位论文作者签名：日期：年月日学位论文版权使用授权书本学位论文作者完全了解学校有关保管、使用学位论文的规定，同意学校保留并向国家有关部门或机构送交论文的复印件和电子版，允许论文被查阅和借阅。本人授权山西财经大学可以将本学位论文的全部或部分内容编入有关数据库进行检索，可以采用影印、缩印或扫描等复制手段保存和汇编本学位论文。本学位论文属于保密，不保密。在年解密后适用本授权书。（请在以上方框内打“”）学位论文作者签名：指导教师签名：日期：年月日日期：年月日摘要虽然应用收益法对企业价值的评估起源于西方资本主义国家，我国资本市场不断的发展和完善，收益法
4、对我国的很多企业进行价值评估越来越重要。收益法在我国市场的应用也因特定的经济环境和参数预测的偏差而遇到一些阻力，对收益法的应用的完善，是非常必要和紧迫的。我国资本市场的发展速度越来越快，同时收益法的评估体系也不断完善，因此收益法对企业的评估与发展提供了非常好的条件。选择运用收益法评估企业的整体价值时，最重要的是对预期收益、收益年限、折现率这三个参数的预测，本文的研究主要针对的是数据“灰化”的前提下对企业收益的预测。本文首先理论阐述了收益法在企业价值评估中的重要地位，并从收益法原理角度阐述了企业在整体价值评估中选取企业净现金流量作为企业的预期收益指标。本文还从理论方面研究了多元线性回归在企业净现
5、金流量预测中的不足之处，分别探讨了灰色预测模型、支持向量机回归和组合预测在数据“灰化”的情形下对企业净现金流量预测的合理性。本文创新性的提出了在企业净现金的预测过程中采用GM（2,1）模型与支持向量机回归组合预测的方法对企业的净现金流量进行预测。这种预测方法不仅可以解决数据贫乏下的预测误差，同时还可以通过两种方法的综合运用消除单项预测方法所带来的系统误差。本文以东风汽车为例，选取企业年度报告中的相关数据，分别运用多元线性回归和组合预测的方法对该企业的净现金流量进行预测，年度报告的数据量有限，多元回归的方法只有在基于大数据背景下的预测精度才会高，因此在本文在案例数据贫乏的条件下引入的GM（2,1
6、）模型和支持向量机模型所得出的预测结果均比多元线性回归的预测精度要高，将两种模型组合预测剔除个别因素的影响之后的预测精度也比多元线性回归的精度要高，因此，将该种数据贫乏条件下的预测方法引入到评估过程中存在一定的合理性。本文主要采用了查阅文献法和统计分析法，通过查阅文献来了解学者在相关领域的研究与观点，进而确定论文的选题与创新点，在具体分析案例时，选择多元回归分析方法、GM(2,1)模型、支持向量机回归与组合预测。关键词：企业价值评估，收益法，企业净现金流量，组合预测ABSTRACTAlthough income method was applied to assessment of enter
7、prise value originated from the western capitalist countries, but with the constant improvement of Chinas capital market and the development, income method application in our country enterprise value evaluation is becoming more and more widely. Income method for specific application in our country m
8、arket economy environment and the parameter prediction deviation and met some resistance, the improvement of the application of income approach, it is quite necessary and urgent. The constant improvement of Chinas capital market also provides the assessment of enterprise value by applying the method
9、 of income more favorable conditions.Option evaluation of the enterprise overall value by applying the method of income, the most important thing is that the expected income, income fixed number of year, the discount rate the three parameters of prediction, this paper studies focused on the data und
10、er the premise of grey for corporate earnings forecasts. This paper firstly made a theory of income approach in the important position of enterprise value assessment, and elaborated the enterprise from the Angle of income method principle in the overall evaluation to select indicators for enterprise
11、 net cash flow as the expected return. This article also studied from the aspects of the theory of multiple linear regression in the enterprise net cash flow forecast deficiency, respectively discusses the grey forecasting model, support vector machine (SVM) regression and combination forecast in th
12、e case of the grey data to the enterprise the rationality of the net cash flow forecast.In this paper, the innovative put forward in the process of enterprise net cash forecast USES GM (2, 1) model and support vector machine (SVM) regression combination forecast method to forecast the enterprises ne
13、t cash flow. This forecasting method can not only solve the data under the poor prediction error, at the same time also can be eliminated by two methods of the integrated use of a single prediction method of system error. With dongfeng motor as an example, this paper select relevant data in the annu
14、al report of the enterprise, respectively using the method of multivariate linear regression and combination forecast forecast net cash flow of the enterprise, the data of the annual report of the quantity is limited, the multivariate regression method only based on the background of big data accura
15、cy is high, so in this paper in the case of poor data under the condition of introducing GM (2, 1) model and support vector machine (SVM) model of forecasting results are higher than the prediction precision of multiple linear regression, the two kinds of combination forecast model after eliminating the influence of individual factors of forecasting precision is higher than the precision of the multiple linear regression, therefore, to this kind of poor data under the condition of prediction method is introduced into the
