联系我们

论文查询结果	返回搜索

论文编号：	1679
作者编号：	031808
上传时间：	2010/5/20 11:11:46
中文题目：	上市公司财务困境预警的实证研究
英文题目：	Listed companies Financial distress Empirical research Logistic regression
指导老师：	张晓农
中文关键字：	上市公司 财务困境 实证研究 逻辑回归
英文关键字：	Listed companies Financial distress Empirical research Logistic regression
中文摘要：	上市公司财务困境预警的研究在国外尤其是在资本市场发达的国家是一个被广泛关注的研究课题。作为经济和财务预警系统研究的重要组成部分，它不仅具有较高学术价值，而且有着巨大的社会应用价值。随着经济理论的发展和研究方法的改进，这一研究不断深化，而实务界对这一研究成果的强烈需求，推动了学术界的研究进程。处于迅速成长过程中的中国社会主义市场经济，更加迫切地需要完善经济预测方法，建立经济预警系统。出于对这一问题的浓厚兴趣和对其应用价值的特别关注，本文在对国内外经典文献回顾和总结的基础上，运用中国资本市场的数据，构造适用于我国上市公司的财务困境预警模型，希望能为我国上市公司财务困境预警理论与实证研究的发展和应用做出应有贡献。 本文采用实证分析方法：首先选取了1998年至2005年8年中因“财务状况异常”而被特别处理(ST)的40家A股上市公司作为研究样本，并按照行业、规模和年份配对的标准选择同样数目的财务状况良好的上市公司构成控制样本。其次，通过t检验对选取的25个备择变量进行研究，从中选出若干差异显著的财务指标。再次，采用Logistic回归方法，分别得出ST前一年、ST前两年、ST前三年的财务困境预警模型。Logistic回归模型是一种非线性的概率模型，具有较强的适用性，从实证结果看，三个模型的判断准确率分别是93.75%、86.25%和75%，表明本文提出的预警模型有较强的判别分类能力，可用于外推预测。最后，文章对如何预控企业财务困境提出了建设性的对策研究。 本文的实证研究与以前我国上市公司财务困境预警的实证研究有所不同：第一，样本新，时间跨度长；第二，备择变量的选取能反映企业多方面的财务状况，T检验时采用前一年、前两年和前三年的数据资料，三年都通过检验的备择变量才可作为模型变量用来构建回归模型（一般研究只采用2年的数据资料）；第三，本文用（t-1），（t-2），（t-3）年的数据和变量分别进行预测，进而为企业及时改善状况赢得更多时间。
英文摘要：	Empirical research on financial distress prediction is one of the most important research subjects in many foreign countries especially in the developed capital market countries. As an important part of economic and financial prediction system, the research has not only high academic value but also enormous practical value. With the development of economic theory and improvement of research methods, the research is furthering on, at the same time, the strong requirement from practitioners also push the research forward. With the rapid development of Market Economy, We must try our best to perfect economic prediction methods and construct prediction system. Due to the great interests to the topic and special concern about the value of its application, in this paper, we try to construct several financial distress prediction models of Chinese listed firms based on the review of previous empirical results and a thorough understanding Of Chinese condition and hope to devote to the development and application of the theoretical and empirical research on financial distress prediction of Chinese listed companies. Firstly, based on the summary of previous research methods and results, forty A Publicly listed firms, which are special treated(ST) during the year 1998 to 2005, are selected as samples. And according to the matching criterion of the relevant industry, size and year, the equal quantity firms whose financial situation is good are selected as control samples. Then twenty-five independent variables are studied by T test. Furthermore, some financial ratios, which are great different between the two groups for the years before the financial distress, are picked out to establish the “t- 1 year”, “t- 2 year” and “t- 3 year” model to forecast the financial distress by the method of Logistic regression. Logistic regression model is a kind of non-linear probability model, it is not strict to distribution of the data, have not used the complicated mathematics methods either, according to the empirical results, we can conclude that the accuracy of the “t- 1 year”, “t- 2 year” and “t- 3 year” model was differently 95 percent, 82.5 percent and 76.25 percent, indicating that it has the great ability to differentiate and can applied to deducing Prediction. Finally, the paper puts forward the constructive measures about how to prevent and control the corporate financial distress. The empirical study of this paper is different from the previous study: firstly, the samples selected in this paper are new, long-period and the amount are large; secondly, we have chosen various financial variables; thirdly, the “t- 1 year”, “t- 2 year” and “t- 3 year” model win more time for the enterprise improve management condition.
查看全文：	预览  下载(下载需要进行登录)