基于改进灰聚类的房地产企业财务评价模型研究

发布时间：2018-08-05 17:06

【摘要】：2007年8月，由房地产企业危机引起的美国次级抵押贷款金融风暴席卷美国、欧盟和日本等世界主要金融市场，同时对我国的金融市场也造成了一定冲击。不够规范化的房地产企业和不完善的金融体系，使得财务风险成为我国众多房地产企业持续发展亟需解决的现实问题。据不完全统计，我国房地产企业的资产负债率平均为65%左右，有些甚至超过100%。如何识别、评价和防范企业财务风险，在危机来临之前尽早地发现财务风险信号，从而最大程度地保证企业资金的安全成为社会各界密切关注的重点。国内外学者利用各种评价方法如杜邦体系、EVA体系、模糊数学和神经网络等对房地产企业财务状况进行评价。财务评价模型可使管理者提早发现财务危机的信号，有助于资本投入者对房地产企业目前的财务状况和经营成果进行综合评价，有助于债权人保证资金的安全性及收益性。首先，梳理国内外房地产企业财务评价模型、灰色系统理论及灰色综合评价方法的相关文献，系统地、全面地总结相关研究的动态及特点。其次对房地产企业的现状、特点，面临的财务风险及成因分析，引出建立评价模型的重要性。再次，设计房地产企业财务评价指标体系。最后，，在灰类和白化权函数的基础上，对聚类系数稍加改进来构建灰聚类评价模型。选取房地产企业中具有代表性70家上市公司2012年财务数据作为研究样本，利用聚类评价模型来评价其财务状况，以验证该模型的合理性和有效性，并给出防范房地产企业财务风险的建议。
[Abstract]:In August 2007, the American subprime mortgage financial crisis, caused by the real estate crisis, swept the world's major financial markets, such as the United States, the EU and Japan, and also caused a certain impact on the financial markets of our country. The unstandardized real estate enterprises and imperfect financial systems made the financial risks become a large number of real estate in China. According to the incomplete statistics, the average asset liability rate of the real estate enterprises in China is about 65%. Some even more than 100%. recognize, evaluate and prevent the financial risks of the enterprises, and find the financial risk signals as soon as possible before the crisis, so as to ensure the security of the enterprise capital to the maximum extent. The domestic and foreign scholars have used various evaluation methods such as DuPont system, EVA system, fuzzy mathematics and neural network to evaluate the financial situation of real estate enterprises. The financial evaluation model can make the managers find the signal of financial crisis early, and help the capital input to the real estate enterprise's current finance. Comprehensive evaluation of the state and business results will help creditors to ensure the safety and profitability of funds.
First, combing the financial evaluation model of real estate enterprises at home and abroad, the relevant literature of grey system theory and grey comprehensive evaluation method, systematically and comprehensively summarizing the dynamic and characteristics of the related research. Secondly, the present situation, characteristics, financial risk and cause analysis of real estate enterprises, lead to the importance of establishing the evaluation model. Finally, on the basis of the grey class and the whitening weight function, the grey clustering evaluation model is built on the basis of the grey class and the whitening weight function. The financial data of the 70 representative listed companies in the real estate enterprises in 2012 are selected as the research samples, and the financial situation is evaluated by the cluster evaluation model. The rationality and validity of the model are verified, and suggestions for preventing financial risks of real estate enterprises are given.
【学位授予单位】：哈尔滨理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F275;F299.233.4;F224

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