基于大数据的发电上市公司盈利能力评价与预测研究

发布时间：2018-05-21 08:23

本文选题：大数据 + 盈利能力　；参考：《华北电力大学(北京)》2017年硕士论文

【摘要】：发电行业作为国民经济增长的基石行业,在经济社会发展中起着至关重要的作用。2015年9号文的颁布及新电力改革配套政策措施的实施,标志着电力行业市场化进程的进一步推进。在电力市场引入竞争机制之后,发电企业面临着前所未有的发展机遇及挑战。在面对市场化的未来环境中,发电企业将要参与市场竞争,而企业盈利能力的高低正是占有市场的关键,如何提高发电企业盈利能力水平成为亟待突破的发展要求。因此客观评价电力企业的盈利能力,基于过去预测未来,为电力企业管理决策提供有力的依据就显得尤为重要。本文以发电企业为研究对象,应用相关数学模型,对发电上市公司盈利能力做出评价与预测,以期为企业提供其盈利能力综合指标计算并追根溯源分析其影响因素,从而达到指导管理层决策的作用。本文首先通过阅读大量文献资料,从电力行业、盈利能力评价、盈利能力预测三个角度总结了国内外的发展动态及研究现状,在此基础上确定了论文的基本思路与框架。其次,通过对盈利能力内涵的学习及评价与预测理论的研究,梳理了本文应用模型的理论与方法。再次,论文以实证分析为主要内容,分析了发电上市公司的发展现状,选取了9个具有代表性且对盈利能力影响较大的量化指标,构建了发电上市公司盈利能力评价指标体系。再次,搜集和处理了60家发电上市公司2011-2016年度与季度的指标数据,并分别从横向和纵向角度探讨了其总体发展趋势及子行业、资金规模和资本结构三个分类下的盈利指标特殊表现。由于简单的财务分析并不能体现对企业盈利能力综合能力水平,本文在对数据有了初步分析之后,选用60家发电上市公司2011-2015年年度数据进行综合评估。针对指标较多且为面板数据的特点,选择了因子分析与逼近理想值法相结合的评价模型,用以确定各上市公司2011-2015年期间内盈利能力指标得分和次序排名,并依据评价结果具体分析和总结不同子行业的盈利能力表现,针对具体子行业提出盈利能力建议。由于市场环境的变化,发电上市公司也面临着前所未有的障碍。总结过去的目的是为了指导未来。本文以盈利能力综合指标为预测对象,结合自回归模型与支持向量机模型进行盈利能力短期预测,并基于因子分析的评价结果给出一家公司的预测算例以证实其预测模型的可行性。在模型的运用上,具体分析了企业盈利影响因素变动后对预测指标可能产生的影响,以期分析企业未来可能发生的变化并以此为基础提出相关的应对建议,为企业管理层决策提供方法与思路。
[Abstract]:As the cornerstone of national economic growth, power generation industry plays a vital role in economic and social development. Marks the electric power industry marketization advancement further advancement. After the introduction of competition mechanism in the electricity market, power generation enterprises are facing unprecedented opportunities and challenges. In the face of the future market environment, power generation enterprises will participate in market competition, and the profitability of enterprises is the key to occupy the market. How to improve the profitability of power generation enterprises has become an urgent need for development. Therefore, it is very important to objectively evaluate the profitability of electric power enterprises and forecast the future based on the past. This paper takes the power generation enterprise as the research object, applies the correlation mathematics model, makes the appraisal and the forecast to the power generation listed company's profit ability, in order to provide the enterprise with its profit ability comprehensive index calculation and trace back to the source analysis its influence factor. In order to guide the management decision-making role. Firstly, through reading a lot of literature, this paper summarizes the development trend and research status of power industry, profitability evaluation and profitability prediction, and then determines the basic ideas and framework of the paper. Secondly, through the study of the connotation of profitability and the research of evaluation and prediction theory, this paper combs the theory and method of applying the model. Thirdly, the paper takes empirical analysis as the main content, analyzes the current situation of power generation listed companies, selects nine representative quantitative indicators which have a greater impact on profitability, and constructs the evaluation index system of power generation listed companies' profitability. Thirdly, we collect and process the index data of 60 listed power generation companies in 2011-2016, and discuss their overall development trend and sub-industries from the horizontal and vertical angles, respectively. Capital size and capital structure under the three categories of profit indicators special performance. Because the simple financial analysis can not reflect the comprehensive ability level of the enterprise profitability, this paper selects 60 listed power generation companies to make a comprehensive evaluation of the annual data from 2011-2015 after a preliminary analysis of the data. In view of the characteristics of more indicators and panel data, the evaluation model combining factor analysis and approximation ideal value method is selected to determine the score and order of profitability index of each listed company in the period 2011-2015. According to the evaluation results, the paper analyzes and summarizes the performance of profitability of different sub-industries, and puts forward suggestions on profitability of specific sub-industries. Due to the change of market environment, listed power generation companies are also facing unprecedented obstacles. The purpose of summing up the past is to guide the future. This paper takes the comprehensive index of profitability as the prediction object, combines the autoregressive model and the support vector machine model to predict the profitability in the short term. Based on the evaluation results of factor analysis, a forecasting example of a company is given to verify the feasibility of its forecasting model. In the application of the model, the paper analyzes the influence of the influence factors on the forecast index, in order to analyze the possible changes in the future and put forward some relevant suggestions. Provides the method and the thought for the enterprise management decision-making.
【学位授予单位】：华北电力大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F426.61;F406.7

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