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上市公司财务数据多维联机分析设计硕士学位论文.doc
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上市公司财务数据多维联机分析设计硕士学位论文.doc
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上海海运学院硕士论文 上市公司财务数据多维联机分析设计
1
摘 要
统计学是一门应用性很强的学科,它是研究如何有效地收集、整理、分析数据,
并对所考察的问题作出推断或预测,甚至为制定决策和采取行动提供依据和建议的一
门学科。凡是有大量数据出现的地方,都用到了统计学。另外,众所周知的是复杂的
数据处理需要计算机来辅助完成。
证券投资也毫不例外地用到了统计学的理论和方法,但是统计学在证券投资领域
主要应用在证券投资技术分析上,而较少涉及基本分析。技术分析是研究股票的短期
买卖行为,即何时买进、何时卖出;基本面分析则主要致力于研究股票的内在价值,
它的研究范围包括宏观、中观和微观三个层面。宏观因素对具体的证券投资决策影响
很小,作为一个理性的投资者,首要关注的是基本面的行业和公司分析,其次才是宏
观层面分析和技术分析。行业分析和公司分析的数据源都是上市公司的财务数据,包
括财务报表和报表附注。
上 市 公 司 财 务 数 据 多 维 联 机 分 析 ( Multi-dimensional On-Line Financial Data
Analysis, MOLFDA)以上市公司财务数据为分析对象,综合应用计算机数据处理技
术、统计分析方法,用多维联机数据分析(Multi-dimensional On-Line Data Analysis,
MOLDA)作为技术支持,不仅可以实现基本面的行业分析和公司分析,还可以对上
市公司从地区、市场(深、沪)等多个角度进行分析。
全文由 “引言”、“正文”和“结论” 三部分组成;其中,“正文”部分由第一
章至第四章构成,它们是论文的主体部分。
“引言”部分,在现实需求和研究现状分析的基础上,指出上市公司财务数据分
析是理性证券投资者的现实需求,而目前提供的相关信息存在量少、分析方法不够完
善 、 大 量 的 数 据 缺 乏 合 理 的 联 机 组 织 等 问 题 , 最 后 提 出 多 维 联 机 数 据 分 析
(Multi-dimensional On-Line Data Analysis, MOLDA)技术是实现上市公司财务数据
多维联机分析的理想技术。
第一章:多维联机数据分析(MOLDA)技术。阐述与 MOLDA 相关的基本概念、
特点和结构。指出“多维联机数据分析设计”的重要性,它包括“多维业务空间设计”
和“方法库设计”
第二章:MOLFDA 多维业务空间的设计。介绍了业务空间设计的基本理论,设
计了上市公司财务数据分析的业务空间——设计了“度量”和“维”;并构建了多维
数据立方体。
第三章:MOLFDA 方法库的设计(一)。设计了总量分析、相对数分析、财务比
上海海运学院硕士论文 上市公司财务数据多维联机分析设计
2
率基本分析等较简单的计算分析方法。主要用了大量表格进行详细地说明。
第四章:MOLFDA 方法库设计(二)。设计了财务分析中较复杂的分析方法——
财务比率综合分析方法。首先,指出财务比率综合分析的核心问题是确定财务比率的
加权权重系数;接着,从综合评价分析方法的基本理论着手,对基本理论进行了较全
面的阐述;然后,以港口业上市公司为研究对象,分别用“主观”、“客观”赋权法这
两类常用的确定权重系数的方法对其进行了综合评价;最后,比较分析“主观”、“客
观”赋权法的优劣,提出了集成赋权的综合评价方法,对集成赋权综合评价分析的结
果进行了一致性检验,得出集成赋权综合评价比任何单一的赋权综合评价更合理的结
论。
在“多维业务空间”和“分析方法库”设计好之后,计算机人员能够非常轻松的
开发实现上市公司财务数据多维联机分析系统。相信本文的研究对于普及上市公司财
务分析知识、倡导理性证券投资、促进证券市场的良性发展有着重大的理论和现实意
义。
关键字:多维联机数据分析(MOLDA)、上市公司财务分析、
业务空间设计、分析方法设计、集成多指标综合评价
上海海运学院硕士论文 上市公司财务数据多维联机分析设计
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ABSTACT
Statistics is a practical subject. It concerns the collecting, processing and
analyzing of the related data, gives presumptions and predictions to it’s objects,
and provides suggestions to decision-makers. Actually, where there is a great deal
of data, there esists a chance for the utilized the field of statistics. In addition, as we
all known it’s feasible to process the data by computer.
Therefore, statistics can be unexceptionally utilized in the field of stock
investmen. However, statistics is more often used in technical analysis than in
elementary analysis. Technical analysis deals with short-run transaction of stocks
while elementary analysis concerns the evaluation of certain stocks; elementary
analysis focus on the intrinsic value the stock, as a result, its concerns are the
macro economy, the middle economy and the micro economy and so on. A rational
stock investor should pay his attention to the stock’s intrinsic value at first, then to
the trend of its price. So, applying the theory and method of statistics to the
elementary analysis of stock’s investment is significant for the dissertation in the
stock investments. The industry analysis or the company analysis is based on the
financial data, which contain the financial report and their notes of the listed
companies.
The multi-dimensional on-line financial data analysis(MOLFDA) are based
the financial data, applying the data process technology by computer and statistics
methods, backed up the multi-dimensional on-line data analysis(MOLDA). It can
realize the elementary analysis, such as industry analysis and the company
analysis; furthermre it can analysis the financial data from the area dimension and
the market dimension, even any tow or all of them.
This paper contains three parts: preface, text and conclusion. The text includes
four chapters; they are the mains of the whole paper.
In the preface part, based on the realistic requirements and the status quo of
the study. It fingers out the financial data analysis of the listed companies is the
realistic requirement of the stock investors. But the information concerning this
aspect is little, deficient and not on-line at present. The MOLDA technology is able
上海海运学院硕士论文 上市公司财务数据多维联机分析设计
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to improve these problems.
Chapter one, the multi-dimensional on-line data analysis technology. Mainly
introduces the concept, the characteristics and its construction. Point out the
design of the multi-dimensional on-line data analysis is important. It includes the
design of the “business space” and the design of the “analysis methods”.
Chapter tow, the design of the “business space” of the MOLFDA. At first
introduces the theory and the concepts, then it projects the “business space” of the
MOLFDA, projects the measures and the dimensions; at last build the
multi-dimensional data clubes.
Chapter three, the design ( one ) of “analysis methods” of the MOLFDA.
Through a great deal of tables it explains some simple analysis methods, such as
the inventory analysis, simple contrary analysis and so on.
Chapter four, the design ( tow ) of “analysis methods” of the MOLFDA. It
mainly projects the comprehend evaluation of the multi-index for the financial
analysis. The core of the comprehend evaluation is the determination of the
weighting coefficients. After explaining the based theory overall, it determines the
weighting coefficients by objective method——the improved analytic hierarchy
process ( IAHP ) , and subjective method——the primary component analysis
(PCA), respectively. The comprhend evaluation for the companies of the harbor
is studied in this chapter. Therefore, determining the weighting coefficients by
single method, either objiective method or subjective method is not perfect. The
integration method of determining weighting coefficients in the comprehend
evaluation which based on the IAHP and the PCA method has been pointed out in
this chapter. At last, the comprehend evaluation result by the integration method
accords to that of the single method, by F test statistic. The result by using
integration method has showed much more reasonable than any of the result by
single method.
After the disgning the “business space” and “analysis method”, the
programmers can develop and realize the multi-dimensional on-line financial data
analysis system easily. The study of this paper will help generalize the knowledge
of financial analysis, initate rational investment in China’s stock market, and
therefore will demonstrate its great theoretical and pratical value for the
上海海运学院硕士论文 上市公司财务数据多维联机分析设计
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development of China’s stock market.
Jin Congli(Industrial Economics)
Directed by Professor Xiao Zhaoyuan
KEY WORDS: multi-dimension on-line data analysis,
financial analysis of the listed company,
the design of “business space”,
the design of “analysis methods”,
the multi-index integration comprehend evaluation
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