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论文编号：	10165
作者编号：	2120162717
上传时间：	2018/6/11 7:24:00
中文题目：	加强金融监管背景下房地产企业财务风险评估研究
英文题目：	Research on Financial Risk Assessment of Real Estate Enterprises under the Background of Tightening Financial Supervision
指导老师：	齐岳
中文关键字：	房地产；财务风险；风险评估；因子分析；回归模型
英文关键字：	Real Estate Enterprises；Financial Risk；Risk Assessment；Factor Analysis；Logistic Model
中文摘要：	据统计，2017年我国房地产与建筑行业生产总值在我国国民生产总值中占比高达13%，且我国国民生产总值的年同比增长率未来10年均能保持在5%左右，同时我国城镇化水平仍处于中期阶段。因此房地产行业作为国家支柱型产业，在经济增长和城镇化进程的双重刺激下，仍有较大发展空间。经过十几年的发展，我国房地产行业已开始进入周期性拐点，房地产泡沫水平以及居民的负债率均处于历史高位。此外，受全球收紧货币政策，降低金融杠杆，避免系统性金融风险的影响，中国金融监管部门在2017年加强了对房地产行业的金融监管，尤其是要求银行的表内表外资产都要回归于表内，严禁委外业务、信托、理财产品等资金流向房地产业。政府及相关机构表示，2018年对房地产金融的监管将更加严格，标准更高。综上，本文认为在经济周期以及金融监管的双重压力下，研究房地产企业的财务风险对于房地产企业本身以及相关投资者均至关重要，具有一定的实践意义。 本文在广泛阅读国内外关于房地产企业财务风险评估文献的基础上，以我国在港股上市的房地产企业为研究对象，采取定性及定量相结合的研究方式，试图构建适用于港股上市房地产企业的财务风险评估模型。首先，本文解释了选择港股上市房地产行业作为研究对象的研究背景以及在金融监管加强的趋势下进行房地产企业财务风险评估的重要性。梳理国内外相关研究文献，在财务风险、财务风险评估模型以及房地产财务风险研究理论的基础上，结合金融监管背景，提出房地产企业存在的主要财务风险类型以及影响因素。其次，构建财务风险评估模型。通过借鉴国内外学者研究成果，结合金融监管加强背景以及港股房地产行业特性，最终选取代表盈利、筹资、投资、营运水平的16个传统财务指标以及反映房地产企业现金流量、股票市场表现以及规模的7个方面共计23个财务指标构建了财务风险评估指标体系。并综合采用主营业务收入增长率、净利润收益率、总资产周转率、速动比率以及净利润五个判断指标筛选出32家存在财务风险的企业。最后，构建基于因子分析的Z值与Logistic回归模型进行实证分析。利用SPSS.22软件对93家房地产企业2014-2016年的23个财务指标进行正态性检验以及显著性检验，然后通过因子分析提取出9个公共因子。在因子分析的基础上构建Z值模型和Logistic 回归评估模型，模型均取得较高的预测精度。通过对两模型进行综合比较。 本文得出结论即在对港股上市房地产企业进行财务风险评估时，基于因子分析的Logistic 回归模型比Z值模型预测精度更高，Logistic 回归评估模型的最佳阈值为0.4，研究结果具有一定实践意义。
英文摘要：	According to statistics, China's real estate and construction industry's gross domestic product accounted for 13% of China's gross national product in 2017, the year-on-year growth rate of China's gross national product can maintain at around 5% over the next 10 years. The level of urbanization is still in the middle stage. Therefore, as a national pillar industry, the real estate industry still has ample room for development under the dual stimulus of economic growth and urbanization. After more than ten years of development, China's real estate industry has begun to enter a cyclical inflection point, and the real estate bubble level and the debt ratio of residents are all at historically high levels. In addition, under the background of global tightening of monetary policy and avoiding the effects of systemic financial risks, China's financial regulatory authorities strengthened financial supervision of the real estate industry in 2017, in particular, required the return of both on- and off-balance sheet assets of banks. In the table, it is strictly prohibited that funds such as outsourcing operations, trusts, and wealth management products flow to the real estate industry. The government and relevant agencies stated that the supervision of real estate finance in 2018 will be more stringent and the standards will be higher. In summary, this article believes that studying the real estate company's financial risk under the dual pressure of economic cycle and financial supervision is very important for the real estate company itself and the relevant investors, and has certain practical significance. This article is based on extensive reading of domestic and international literature on financial risk assessment of real estate companies, taking China’s real estate companies listed on Hong Kong stocks as the research object, adopting a combination of qualitative and quantitative research methods, and trying to construct the financial risks evaluation model for Hong Kong shares listed real estate companies. First of all, this article explains the research background of selecting the Hong Kong stocks listed real estate industry as the research object and the importance of real estate company financial risk assessment under the trend of strengthening financial supervision. Combine domestic and foreign relevant research literature, based on financial risk, financial risk assessment model and real estate financial risk research theory, combined with the background of financial supervision, put forward the main types of financial risks and influencing factors of real estate companies. Secondly, building a financial risk assessment model. Through learning from the research results of domestic and foreign scholars, combining financial supervision and strengthening the background and the characteristics of Hong Kong stocks real estate industry, we finally selected 16 traditional financial indicators representing earnings, financing, investment, and operating levels, and reflected the cash flow of real estate companies, the performance of the stock market, and the size of 7 Two financial indicators, a total of 23 financial indicators built a financial risk assessment index system. In addition, 32 companies with financial risks were screened out using the five indicators of main business revenue growth rate, net profit yield, total asset turnover rate, quick ratio and net profit.Finally, building Z-value and Logistic regression model based on factor analysis. Using SPSS.22 software, the 23 financial indicators of 93 real estate enterprises from 2014 to 2016 were tested for normality and significance, and then 9 common factors were extracted by factor analysis. Based on factor analysis, Z-value model and a Logistic regression model were constructed. The models achieved high prediction accuracy. Through the comparison of the two models, this paper concludes that when assessing the financial risk of Hong Kong shares listed real estate companies, the Logistic regression model based on factor analysis is more accurate than the Z-value model, and the optimal threshold of the Logistic regression model is 0.4, the results of the study have a certain practical significance.
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