基于DEA模型的中国上市公司定向增发融资效率研究

发布时间：2018-06-21 21:33

本文选题：定向增发 + 主成分分析　；参考：《东北财经大学》2016年硕士论文

【摘要】：自2006年5月8日我国证监会颁布《上市公司证券发行管理办法》以来,定向增发以其发行门槛低,限制条件少以及审批程序简单,融资成本低等优势迅速成为上市公司股权再融资的主要手段。继2013年IPO暂停引发一轮"定增热"后,2014至2015年国企改革以及企业间并购重组又引发新一轮热潮。据wind资讯统计,2014和2015年进行定向增发的企业分别有477和930家,在定向增发融资规模上2014年募集资金规模达到6907.552亿元,2015年首次募集资金规模突破万亿大关高达12327.8273亿元。笔者对2013至2015年我国定向增发情况进行统计后发现,定向增发存在明显的行业差别;募集资金总额前四位的行业分别是制造业、房地产业、金融业和水利、环境和公共设施管理业,占2013至2015年定向增发募集资金总额的46.76%、8.33%、7.46%、6.88%,在进行定向增发的行业中,制造业上市公司数量占实施定向增发上市公司数的60.91%。不论在融资规模还是公司数量上制造业都占有绝对优势,因此本文以制造业为例就定向增发融资效率进行研究。本文通过梳理已有文献发现,学者们对评价定向增发融资效率的角度多从宣告效应、长期超额累积收益率以及经营业绩三方面研究,评价定向增发融资效率的方法大多采用事件研究法以及多元回归法。但我国证券市场目前处于弱有效市场阶段,股票市场并不能完全反映企业的经营业绩,并且企业在定向增发时可能会有盈余管理等行为最终导致事件研究法采取的衡量指标累积超额收益率偏低,因此,仅以事件研究法作为定增融资效率的研究方法具有片面性。而多元回归分析通过构建多元线性回归方程对企业的长期累计超额收益率或者定增前后几年公司财务指标的变化判断企业再融资效率的高低,同时可以判断影响融资效率高低的因素和程度。但多元回归分析法的前提是所选用的影响融资效率的因素与评价融资效率的指标具有线性关系,显然,现实中很难证明二者之间一定具有线性关系。由于衡量定向增发融资效率所采用的评价指标以及方法各有差别,目前暂时没有得出一致的结论。本文借鉴已有学者的研究,提出一种基于主成分分析以及DEA模型的评价方法衡量定向增发融资效率。本文选取2010-2012年宣告定向增发预案并成功实施的制造业A股上市公司为样本,选取定向增发折扣率、定向增发前一年度资产负债率、定向增发相对规模,公司规模以及Tobin'Q值5个输入指标,长期累积超额收益率、每股收益以及反映公司盈利能力、成长能力、运营能力、偿债能力和现金流状况的13个财务指标作为输出指标,其中财务指标取定向增发当年、定向增发后一年、定向增发后两年的平均值。首先本文运用主成分分析将上述15个输出指标归纳为具有一定经济含义的7个主成分,然后利用DEA模型对研究样本进行相对效率评价以及排序,最后对无效样本进行分析与改进。本文的结论以及创新主要有:(1)我国制造业上市公司依然没有跳出定向增发融资效率低下的困境,仅有20.14%的样本为DEA有效,49.64%的样本为技术有效以及78.78%的样本处于规模收益递减阶段;(2)DEA模型的最优性,DEA模型利用所有样本的输入输出数据建立生产可能集,然后从所选的同类的样本单元中找到处于相对最优的样本,对每个决策单元进行效率排序,对于无效的样本可以根据样本集分析无效原因,提出改进意见;(3)遵循市场指标以及财务指标相结合的原则全面评价上市公司定向增发融资效率,克服研究指标单一的不足,同时采用财务指标三年的平均值,避免某年指标值异常的影响;(4)利用主成分分析法将输出指标归纳为具有明确经济含义的7个主成分,避免人为主观赋权的缺陷。
[Abstract]:Since the May 8, 2006 China Securities Regulatory Commission promulgated the management method of securities issuance of listed companies, the directional addition has been the main means of refinancing the shares of listed companies with its low issuing threshold, less restrictive conditions, simple examination and approval procedures and low financing cost. After the IPO suspension in 2013, a round of "heat increase" was initiated, 2014 to 2015 The reform of state-owned enterprises and the merger and reorganization of enterprises have led to a new round of upsurge. According to wind information statistics, there were 477 and 930 companies in 2014 and 2015, respectively. In 2014, the scale of fund raising was 690 billion 755 million 200 thousand yuan, and the first raised fund in 2015 was up to 1 trillion and 232 billion 782 million 730 thousand yuan. According to the statistics of China's directional issuance from 2013 to 2015, it was found that there were obvious industrial differences in the directional increase. The top four sectors of the total fund raising were manufacturing, real estate, financial and water conservancy, environment and public facilities management, which accounted for 46.76%, 8.33%, 7.46%, 6.88% of the total amount of funds raised from 2013 to 2015. In the industry that carries out the directional addition, the number of the listed companies in the manufacturing sector accounts for the absolute advantage of the number of targeted additional listed companies, regardless of the size of the financing or the number of Companies in the company. Therefore, this paper takes the manufacturing industry as an example to study the financing efficiency of the 60.91%.. The angle of evaluating directional increase financing efficiency is mainly from three aspects: declaration effect, long-term excess cumulative yield and operating performance. Most of the methods to evaluate the efficiency of directional increase financing are event research and multiple regression. However, the stock market in China is currently in a weak and effective market stage, and the stock market can not fully reflect the enterprise. The business performance of the industry, and the enterprises may have earnings management in the direction of the directional addition, will eventually lead to the low cumulative excess rate of return on the measure index adopted by the event research method. Therefore, only the study method of the event study method is one-sided as the research method of increasing the financing efficiency. And the multi regression analysis is used to construct the multiple linear regression equation. At the same time, the factors and degree of influencing the efficiency of financing are judged by the long-term cumulative excess rate of return or the changes in the financial index of the company in the years before and after the increase. But the precondition of the multiple regression analysis is that the factors that affect the efficiency of financing and the index of the efficiency of the evaluation of financing have been selected. It is obvious that it is difficult to prove that there is a linear relationship between the two in reality. Because of the difference between the evaluation indexes and methods used to measure the financing efficiency of the directional increase, there is no consensus conclusion for the time being. In this paper, a writer based on the principal component analysis and the DEA model is proposed for reference. The method is to measure the efficiency of directional increase financing. In this paper, we selected the A shares listed companies of the manufacturing industry, which announced the directional addition plan for 2010-2012 years and successfully carried out the listed companies of the manufacturing industry, to select the directional increase discount rate, to add the assets and liabilities rate of the previous year, to increase the relative scale, the size of the company and the value of the Tobin'Q value, and to accumulate the excess returns for a long time. Rate, earnings per share, and the 13 financial indicators that reflect the company's profitability, growth capacity, operational ability, debt service and cash flow status as the output indicators, in which the financial indicators are added to the same year, the orientation after the increase in the year, the average of the following two years after the increase of orientation. The first first article uses the principal component analysis to make the above 15 output indicators It is summed up as 7 principal components with certain economic meaning, and then the DEA model is used to evaluate and sort the relative efficiency of the research samples. Finally, the invalid samples are analyzed and improved. The conclusions and innovations of this paper are as follows: (1) the listed companies in our country still have not jumped out of the predicament of the low efficiency of targeted additional financing, only 20 The sample of.14% is valid for DEA, 49.64% of samples are efficient and 78.78% of the samples are in the stage of decline in scale of return; (2) the optimality of the DEA model, the DEA model uses the input and output data of all the samples to establish the production possible set, and then finds the relatively optimal sample from the selected sample unit, for each decision list. In order to sort the efficiency, the invalid sample can be analyzed according to the reason of the invalid analysis. (3) follow the principle of combining the market index and financial index to comprehensively evaluate the financing efficiency of the listed company, overcome the shortage of the single research index, and use the average value of the financial index for three years to avoid a certain year. The effect of abnormal index value; (4) using the principal component analysis method to sum up the output index into 7 principal components with clear economic meaning and avoid the defects of subjective empowerment.
【学位授予单位】：东北财经大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：F832.51;F224

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