《上市公司财务数据多维联机分析设计硕士学位》由会员分享，可在线阅读，更多相关《上市公司财务数据多维联机分析设计硕士学位（102页珍藏版）》请在金锄头文库上搜索。
1、精选资料摘 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
2、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
3、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
4、”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
5、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可修改编辑ABSTACTStatistics is a
6、practical subject. It concerns the collecting, processing and analyzing of the related data, gives presumptions and predictions to its 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.
7、In addition, as we all known its 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 transacti
8、on 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
9、 stocks intrinsic value at first, then to the trend of its price. So, applying the theory and method of statistics to the elementary analysis of stocks investment is significant for the dissertation in the stock investments. The industry analysis or the company analysis is based on the financial dat
10、a, 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（MOL
11、DA）. 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 include
12、s 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
13、 aspect is little, deficient and not on-line at present. The MOLDA technology is able 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
14、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 th
15、e 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,
16、 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 methodthe improved analytic hierarchy process （IAHP）, and subjective methodthe primary component a
