本文選題：證券業(yè) + 系統(tǒng)性風險　； 參考：《廈門大學》2014年碩士論文

【摘要】：2007年美國次貸危機引發(fā)全球性的金融危機,系統(tǒng)性風險在世界范圍內(nèi)快速傳播,各國的經(jīng)濟、金融發(fā)展受到了巨大的影響,各金融機構(gòu)以及各國監(jiān)管部門開始將系統(tǒng)性風險的預警和防范作為風險管理的一個重點。此次危機雖然已經(jīng)接近尾聲,但是關(guān)于系統(tǒng)性風險的測度和防范將成為金融業(yè)永恒的主題。 本文通過回顧關(guān)于系統(tǒng)性風險度量方法的相關(guān)理論和實證研究,引出了本文研究所使用的CoVaR方法。通過詳細介紹該方法的原理和實際操作,以我國11家上市證券公司為研究對象,對我國證券業(yè)的系統(tǒng)性風險進行實證分析。本文使用分位數(shù)回歸方法求解VaR和CoVaR,計算我國證券業(yè)以及各證券公司的風險價值和各公司與行業(yè)之間的相互風險溢出效應(yīng),得到可以量化的風險值和風險溢出率。 實證結(jié)果表明,使用VaR方法可能會低估證券公司以及證券業(yè)的風險水平,尤其是極端事件發(fā)生的時候；而CoVaR方法能夠較為全面的捕捉各機構(gòu)處于極端狀況時對行業(yè)整體風險值的影響,以及行業(yè)處于極端狀況時對各機構(gòu)的風險值的影響,因此相對于傳統(tǒng)風險度量方法而言,CoVaR是比較全面和有效的方法。實證結(jié)果還表明,各證券公司對證券業(yè)的風險溢出效應(yīng)與其資產(chǎn)或者市值規(guī)模并沒有必然的關(guān)系。自身風險水平較低的證券公司對行業(yè)的風險溢出效應(yīng)較低,而行業(yè)對這些證券公司的風險溢出效應(yīng)則較高。使用CoVaR方法可以度量各證券公司對行業(yè)的風險溢出效應(yīng)大小以及各個證券公司受到行業(yè)風險爆發(fā)的影響大小,但是這并不能代表公司對行業(yè)收益水平的影響力,事實上,這二者之間并不沖突。文章最后針對實證分析的結(jié)論,對我國證券公司的風險防范和監(jiān)管部門的監(jiān)管提出政策建議。
[Abstract]:In 2007, the subprime mortgage crisis in the United States triggered a global financial crisis, systemic risk spread rapidly around the world, and the economic and financial development of various countries was greatly affected. Financial institutions and national regulators have begun to place systemic risk warning and prevention as a focus of risk management. Although the crisis has come to an end, the measurement and prevention of systemic risk will become the eternal theme of the financial industry. By reviewing the relevant theoretical and empirical research on systematic risk measurement, this paper leads to the CoVaR method used in this paper. By introducing the principle and practice of this method in detail, taking 11 listed securities companies in China as the research object, this paper makes an empirical analysis on the systemic risk of the securities industry in China. In this paper, the quantile regression method is used to solve VaR and CoVaR, and the risk value and mutual risk spillover effect between companies and industries are calculated, and the quantifiable risk value and risk spillover rate are obtained. The empirical results show that the VaR method may underestimate the risk level of securities firms and securities industry, especially when extreme events occur. The CoVaR method can comprehensively capture the impact of the institutions in extreme conditions on the overall risk value of the industry and the impact of the industry in the extreme situation on the risk value of each organization. Therefore, CoVaR is more comprehensive and effective than the traditional risk measurement method. The empirical results also show that the risk spillover effect of securities firms to the securities industry is not necessarily related to their assets or the scale of market value. The securities companies with lower risk level have lower risk spillover effect on the industry, while the risk spillover effect of the industry on these securities companies is higher. The CoVaR method can measure the risk spillover effect of each securities company to the industry and the impact of the industry risk explosion on each securities company, but this does not represent the influence of the company on the industry income level, in fact, the risk spillover effect of each securities company on the industry can be measured. There is no conflict between the two. Finally, based on the conclusion of empirical analysis, the paper puts forward some policy suggestions on the risk prevention and supervision of securities companies in China.
【學位授予單位】：廈門大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：F224;F832.39

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