我国房地产公司系统违约风险动态监测

发布时间：2018-04-21 13:18

本文选题：系统性未定权益分析 + 系统违约风险　；参考：《河北大学》2017年硕士论文

【摘要】：美国次贷危机的爆发引发全球经济危机,对国际金融秩序造成严重的破坏与冲击,系统性风险就是造成此次危机的主要原因之一。危机爆发以后,各国及学术界意识到加强金融监管及防范系统性风险的重要性。近年来,随着我国房地产业的快速发展,房地产业已成为我国国民经济的支柱产业,而作为房地产行业供给主体的房地产公司,近年来发生诸多违约事件,违约现象的产生为我国防范房地产公司系统违约风险敲响了警钟。研究房地产公司系统违约风险对于把控房地产行业风险水平,促进房地产市场健康发展具有重要意义。本文以2002年第一季度到2016年第二季度为研究区间,采用扩展系统未定权益分析法度量了我国65家上市房地产公司系统违约风险,第一步基于未定权益分析法测算了我国样本房地产公司15年间每日违约距离、违约概率及违约损失。在测算结果中发现房地产公司违约概率在2002年至2016年间总体呈两阶段的先上升后下降的趋势,并于2008年及2015年达到最高点,即违约风险较高,通过观察虽然每家房地产公司违约概率较小,但在短期内有快速上升的趋势;第二步由于房地产业具有金融特性,因此具有一定的相依性,考虑房地产公司间联合违约现象,根据多元极值理论和多元Copula测算了房地产公司联合违约概率及期望损失,通过观察联合违约概率的走势同单家房地产公司的违约概率走势基本一致,且联合违约概率较高;第三步将测算的期望损失降序排列,可以识别绿地控股、银亿股份、光明地产等十家重要房地产公司,这些重要房地产公司的期望损失占比高达90%。随着房地产业的快速发展,房地产市场风险显现,近几年房地产公司违约事件频发,违约风险增加,经过测度房地产公司联合违约概率较大,系统违约风险较高。最后本文有针对性的提出了相关防控对策:第一,规范房地产公司融资结构,降低系统违约风险;第二,加强房地产金融监管,防范系统违约风险;第三,建立房地产公司系统违约风险预警机制,识别系统重要机构。
[Abstract]:The outbreak of the subprime mortgage crisis in the United States triggered the global economic crisis, causing serious damage and impact to the international financial order. Systemic risk is one of the main causes of the crisis. After the crisis broke out, countries and academia realized the importance of strengthening financial supervision and preventing systemic risks. In recent years, with the rapid development of China's real estate industry, the real estate industry has become the pillar industry of our national economy. The occurrence of breach of contract has sounded the alarm for our country to guard against the risk of real estate company system default. It is of great significance to study the system default risk of real estate companies to control the real estate industry risk level and promote the healthy development of real estate market. Taking the first quarter of 2002 to the second quarter of 2016 as the study interval, this paper uses the extended system undetermined equity analysis method to measure the systemic default risk of 65 listed real estate companies in China. The first step is to calculate the daily default distance, default probability and default loss of the sample real estate companies in our country for 15 years based on the undetermined equity analysis method. The results show that the probability of default of real estate companies rose first and then decreased in two stages from 2002 to 2016, and reached the highest point in 2008 and 2015, that is, the risk of default is higher. Although the probability of default of every real estate company is small, it has a tendency of rising rapidly in the short term. The second step is considering the phenomenon of joint default among real estate companies because the real estate industry has financial characteristics, so it has certain dependence. According to the theory of multivariate extreme value and multiple Copula, the joint default probability and expected loss of real estate company are calculated. The trend of joint default probability is basically consistent with that of single real estate company, and the joint default probability is higher. In the third step, ten major real estate companies, such as Greenbelt Holdings, Silver billion shares and Guangming Real Estate, can be identified in descending order of the estimated expected losses, which account for as much as 90 percent of the expected losses of these important real estate companies. With the rapid development of the real estate industry, the real estate market risk appears. In recent years, the real estate company defaults frequently, the default risk increases, after the measure the real estate company joint default probability is bigger, the system default risk is higher. Finally, this paper puts forward the relevant countermeasures: first, standardize the financing structure of real estate companies, reduce the risk of system default; second, strengthen the real estate financial supervision to prevent the risk of system default; third, Establish the system default risk warning mechanism of real estate companies, identify the important institutions of the system.
【学位授予单位】：河北大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F299.233.4

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