基于GARCH-VaR模型对房地产上市公司的财务风险研究
发布时间：2018-10-09 11:02
【摘要】：自2007年次贷危机爆发以后,迫使各国开始重视风险管理的研究。经过“金融风暴”的爆发,财务风险无处不在,企业必须时刻注意识别和防范风险。本文尝试着对目前发展的财务风险管理系统提出适合企业的财务风险预警系统。目前我国房地产行业发展迅猛,社会及政府部门对其发展态势给予了高度关注。在经济形势严峻的情况下,防范房地产上市公司内部财务风险就显得尤为重要。 本文针对新形势的发展状态下,提出了预测房地产上市公司财务风险的方法。本文针对房地产行业龙头公司—M房地产上市公司进行了研究分析,进而通过M房地产上市公司的研究方法,推广到所有房地产上市公司的研究中,并分析了共36家房地产上市公司的财务风险值。本文选取了五大类财务指标,包括：每股指标、盈利能力、成长能力、营运能力、偿债及资本结构共22个财务指标进行研究,选取时间为2002年3月31日至2013年3月31日期间的季度财务数据共45个季度数据。本文利用熵权法来进行测算权重,从而算出了综合测评财务指标序列,再对该序列进行时间序列分析的相关检验,主要检验包括：单位根检验、自相关性检验、ARCH-LM检验等。综合测评财务指标序列通过了单位根检验,但存在着3阶的自相关性,同时还检验出其存在着高阶ARCH效应,因此对其建立GARCH模型,模型检验后发现消除了之前存在的ARCH效应,结论是模型通过检验,可以利用GARCH模型来分析。本文通过GARCH模型来计算风险VaR值,从而得到综合测评财务指标值计算出相应的财务风险值。为了分析财务风险值,采用自回归模型(VAR模型)来预测下一期的风险值,预测阶数为5阶,预测模型的拟合优度达到71.4%,效果较好。另一方面,本文通过建立房地产上市公司财务风险转移概率矩阵进一步度量所有房地产上市公司的风险转移概率,从而能够更加有效地控制风险。 本文通过建立的预测模型,能够合理的分析出下一期的财务风险值,从而可以达到防范风险,预测风险的目的,能够提前为房地产上市公司的风险防范采取适当措施,从而能够为房地产行业提供更加有效的规避方法。本文已建立起适合企业自身发展的财务风险管理体系,但同时也要不断完善财务风险管理的系统,使预测效果达到更佳。
[Abstract]:Since the subprime mortgage crisis broke out in 2007, countries began to attach importance to risk management research. After the outbreak of "financial storm", financial risks are everywhere, enterprises must always pay attention to identify and guard against risks. This paper attempts to put forward a financial risk early warning system suitable for enterprises to develop the current financial risk management system. At present, the real estate industry is developing rapidly in our country, and the society and government departments pay close attention to it. In the severe economic situation, it is particularly important to guard against the internal financial risks of listed real estate companies. In view of the development of the new situation, this paper puts forward a method to predict the financial risk of real estate listed companies. This article has carried on the research analysis to the real estate industry leading company -M real estate listed company, then through the M real estate listed company's research method, popularized to all the real estate listed company's research, And analyzed a total of 36 real estate listed companies financial risk value. This paper selects five kinds of financial indicators, including: per share index, profitability, growth capacity, operating capacity, debt service and capital structure of a total of 22 financial indicators to study. A total of 45 quarterly financial data were selected from March 31, 2002 to March 31, 2013. In this paper, entropy weight method is used to calculate the financial index sequence of comprehensive evaluation, and then the correlation test of time series analysis of this series is carried out. The main tests include unit root test, autocorrelation test and ARCH-LM test. The financial index sequence of comprehensive evaluation has passed the unit root test, but there is a third order autocorrelation, and at the same time, the existence of high order ARCH effect is also tested. Therefore, the GARCH model is established, and the former ARCH effect is eliminated after the model test. The conclusion is that GARCH model can be used to analyze the model. In this paper, the risk VaR value is calculated by GARCH model, and the corresponding financial risk value is calculated by synthetically evaluating the financial index value. In order to analyze the financial risk value, the autoregressive model (VAR model) is used to predict the risk value in the next period. The prediction order is 5 order, and the goodness of fit of the prediction model is 71.4. The effect is good. On the other hand, this paper further measures the risk transfer probability of all listed real estate companies by establishing the financial risk transfer probability matrix of real estate listed companies, so as to control the risk more effectively. Through the prediction model, this paper can reasonably analyze the value of financial risk in the next period, so as to achieve the purpose of risk prevention, forecast risk, and take appropriate measures for the risk prevention of listed real estate companies in advance. Thus, the real estate industry can provide a more effective way to circumvent. This paper has established a financial risk management system suitable for the enterprise's own development, but at the same time, it is necessary to continuously improve the financial risk management system so as to achieve a better forecast effect.
【学位授予单位】：内蒙古工业大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F299.233.42
本文编号：2259094
[Abstract]:Since the subprime mortgage crisis broke out in 2007, countries began to attach importance to risk management research. After the outbreak of "financial storm", financial risks are everywhere, enterprises must always pay attention to identify and guard against risks. This paper attempts to put forward a financial risk early warning system suitable for enterprises to develop the current financial risk management system. At present, the real estate industry is developing rapidly in our country, and the society and government departments pay close attention to it. In the severe economic situation, it is particularly important to guard against the internal financial risks of listed real estate companies. In view of the development of the new situation, this paper puts forward a method to predict the financial risk of real estate listed companies. This article has carried on the research analysis to the real estate industry leading company -M real estate listed company, then through the M real estate listed company's research method, popularized to all the real estate listed company's research, And analyzed a total of 36 real estate listed companies financial risk value. This paper selects five kinds of financial indicators, including: per share index, profitability, growth capacity, operating capacity, debt service and capital structure of a total of 22 financial indicators to study. A total of 45 quarterly financial data were selected from March 31, 2002 to March 31, 2013. In this paper, entropy weight method is used to calculate the financial index sequence of comprehensive evaluation, and then the correlation test of time series analysis of this series is carried out. The main tests include unit root test, autocorrelation test and ARCH-LM test. The financial index sequence of comprehensive evaluation has passed the unit root test, but there is a third order autocorrelation, and at the same time, the existence of high order ARCH effect is also tested. Therefore, the GARCH model is established, and the former ARCH effect is eliminated after the model test. The conclusion is that GARCH model can be used to analyze the model. In this paper, the risk VaR value is calculated by GARCH model, and the corresponding financial risk value is calculated by synthetically evaluating the financial index value. In order to analyze the financial risk value, the autoregressive model (VAR model) is used to predict the risk value in the next period. The prediction order is 5 order, and the goodness of fit of the prediction model is 71.4. The effect is good. On the other hand, this paper further measures the risk transfer probability of all listed real estate companies by establishing the financial risk transfer probability matrix of real estate listed companies, so as to control the risk more effectively. Through the prediction model, this paper can reasonably analyze the value of financial risk in the next period, so as to achieve the purpose of risk prevention, forecast risk, and take appropriate measures for the risk prevention of listed real estate companies in advance. Thus, the real estate industry can provide a more effective way to circumvent. This paper has established a financial risk management system suitable for the enterprise's own development, but at the same time, it is necessary to continuously improve the financial risk management system so as to achieve a better forecast effect.
【学位授予单位】：内蒙古工业大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F299.233.42
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