基于靜態(tài)與動態(tài)CoVaR方法銀行系統(tǒng)性風險研究
發(fā)布時間：2019-05-16 01:58
【摘要】：近年來我國金融市場發(fā)展跌宕起伏,接二連三發(fā)生多起風險事件,2013年的"錢荒","債災",2015年年中和2016年初的股災,這一次次金融風險事件的背后無不揭示著我國金融體系的脆弱性,一次次危機的背后也都不同程度的存在銀行系統(tǒng)性風險,銀行體系與資本市場和社會經(jīng)濟聯(lián)系最為緊密,因此對銀行系統(tǒng)性風險的測度方法和傳導效應研究意義重大。本文首先對系統(tǒng)性風險管理理論發(fā)展歷程和最新進展進行研究,重點探討了風險管理主流工具風險價值VaR模型及其衍生出來的CoVaR模型,之后選用更新、更全面的風險度量工具——CoVaR模型對我國商業(yè)銀行系統(tǒng)性風險及其溢出效應進行研究,以我國16個主要上市銀行和申萬二級銀行指數(shù)作為樣本,運用分位數(shù)回歸技術分別構建了商業(yè)銀行與系統(tǒng)間的靜態(tài)CoVaR模型和動態(tài)CoVaR模型,對商業(yè)銀行系統(tǒng)性風險及其溢出效應進行綜合分析�；陟o態(tài)CoVaR分析銀行風險時,測算了各銀行自身風險及其與銀行業(yè)整體之間的雙向風險溢出效應,并應用聚類分析方法,從風險數(shù)據(jù)的角度對銀行進行分類研究。結果表明單一的運用VaR模型可能會導致銀行業(yè)整體的風險水平被低估,CoVaR方法在風險價值的基礎上綜合考慮風險的溢出效應,是一種更為全面的風險管理工具。從測算結果來看,各銀行的無條件風險與其對銀行整體的風險溢出并沒有明顯的相關關系,我國大部分銀行的風險水平高于銀行整體,大型國有商業(yè)銀行自身風險和對系統(tǒng)的溢出效應相對較小,大多數(shù)股份制銀行波動較大,對系統(tǒng)風險溢出較高。銀行風險與其受到銀行系統(tǒng)的溢出有一定的正相關關系,即銀行的自身風險越高也越容易受到銀行業(yè)系統(tǒng)風險的影響�；趧討B(tài)CoVaR分析銀行風險時,借助資產(chǎn)定價模型的原理,引入了更加符合我國金融市場特征的宏觀變量,構建了比較有效的動態(tài)CoVaR模型。通過測算結果發(fā)現(xiàn),國有銀行自身風險比較低,表現(xiàn)相對穩(wěn)定,但一旦陷入危機對將對銀行板塊形成較強的風險溢出效應。股份制銀行自身風險比較高,對系統(tǒng)的風險溢出效應在中等水平。一般情況下,城市商業(yè)銀行的風險價值中等,但系統(tǒng)陷入危機時風險上升最快,容易受到系統(tǒng)的影響,對系統(tǒng)的風險溢出效應比股份制銀行大。最后,根據(jù)理論研究和實證分析的結果,分別對降低銀行自身風險和加強銀行系統(tǒng)性風險監(jiān)管提出了建議。
[Abstract]:In recent years, the development of China's financial market has experienced ups and downs, with a number of risk events one after another, the "money shortage" in 2013, the "debt disaster", and the stock market disasters in mid-2015 and early 2016. Behind this financial risk event, the fragility of China's financial system is revealed, and there are systemic risks of banks to varying degrees behind the crisis, and the banking system is most closely related to the capital market and social economy. Therefore, it is of great significance to study the measurement method and conduction effect of bank systemic risk. In this paper, the development course and latest progress of systemic risk management theory are studied, and the risk value VaR model of the mainstream tool of risk management and its derived CoVaR model are discussed in detail, and then the update is selected. The CoVaR model, a more comprehensive risk measurement tool, studies the systemic risk and spillover effects of commercial banks in China, and takes the index of 16 major listed banks and Shenwan secondary banks as samples. The static CoVaR model and dynamic CoVaR model between commercial bank and system are constructed by using quantile regression technique, and the systemic risk and spillover effect of commercial bank are comprehensively analyzed. When analyzing the bank risk based on static CoVaR, this paper calculates the risk of each bank and its two-way risk spillover effect with the banking industry as a whole, and applies the cluster analysis method to classify the bank from the point of view of risk data. The results show that the single use of VaR model may lead to the underestimation of the overall risk level of the banking industry. CoVaR method is a more comprehensive risk management tool, which considers the spillover effect of risk comprehensively on the basis of risk value. From the measured results, there is no obvious correlation between the unconditional risk of each bank and its risk spillover to the bank as a whole. The risk level of most banks in our country is higher than that of the bank as a whole. The risk of large state-owned commercial banks and the spillover effect to the system are relatively small, most of the joint-stock banks fluctuate greatly, and the spillover to the system risk is higher. There is a positive correlation between bank risk and the spillover of the banking system, that is, the higher the risk of the bank itself, the more vulnerable it is to the risk of the banking system. Based on the dynamic CoVaR analysis of bank risk, with the help of the principle of asset pricing model, the macro variables which are more in line with the characteristics of China's financial market are introduced, and a more effective dynamic CoVaR model is constructed. Through the calculation results, it is found that the risk of state-owned banks is relatively low and relatively stable, but once they fall into the crisis, they will have a strong risk spillover effect on the banking sector. The risk of joint-stock banks is relatively high, and the risk spillover effect on the system is at the medium level. In general, the risk value of city commercial banks is medium, but when the system falls into crisis, the risk rises the fastest and is vulnerable to the influence of the system, and the risk spillover effect on the system is greater than that of joint-stock banks. Finally, according to the results of theoretical research and empirical analysis, some suggestions are put forward to reduce the risk of banks and strengthen the supervision of systemic risk of banks.
【學位授予單位】：南京大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F224;F832.33
，
本文編號：2477934
[Abstract]:In recent years, the development of China's financial market has experienced ups and downs, with a number of risk events one after another, the "money shortage" in 2013, the "debt disaster", and the stock market disasters in mid-2015 and early 2016. Behind this financial risk event, the fragility of China's financial system is revealed, and there are systemic risks of banks to varying degrees behind the crisis, and the banking system is most closely related to the capital market and social economy. Therefore, it is of great significance to study the measurement method and conduction effect of bank systemic risk. In this paper, the development course and latest progress of systemic risk management theory are studied, and the risk value VaR model of the mainstream tool of risk management and its derived CoVaR model are discussed in detail, and then the update is selected. The CoVaR model, a more comprehensive risk measurement tool, studies the systemic risk and spillover effects of commercial banks in China, and takes the index of 16 major listed banks and Shenwan secondary banks as samples. The static CoVaR model and dynamic CoVaR model between commercial bank and system are constructed by using quantile regression technique, and the systemic risk and spillover effect of commercial bank are comprehensively analyzed. When analyzing the bank risk based on static CoVaR, this paper calculates the risk of each bank and its two-way risk spillover effect with the banking industry as a whole, and applies the cluster analysis method to classify the bank from the point of view of risk data. The results show that the single use of VaR model may lead to the underestimation of the overall risk level of the banking industry. CoVaR method is a more comprehensive risk management tool, which considers the spillover effect of risk comprehensively on the basis of risk value. From the measured results, there is no obvious correlation between the unconditional risk of each bank and its risk spillover to the bank as a whole. The risk level of most banks in our country is higher than that of the bank as a whole. The risk of large state-owned commercial banks and the spillover effect to the system are relatively small, most of the joint-stock banks fluctuate greatly, and the spillover to the system risk is higher. There is a positive correlation between bank risk and the spillover of the banking system, that is, the higher the risk of the bank itself, the more vulnerable it is to the risk of the banking system. Based on the dynamic CoVaR analysis of bank risk, with the help of the principle of asset pricing model, the macro variables which are more in line with the characteristics of China's financial market are introduced, and a more effective dynamic CoVaR model is constructed. Through the calculation results, it is found that the risk of state-owned banks is relatively low and relatively stable, but once they fall into the crisis, they will have a strong risk spillover effect on the banking sector. The risk of joint-stock banks is relatively high, and the risk spillover effect on the system is at the medium level. In general, the risk value of city commercial banks is medium, but when the system falls into crisis, the risk rises the fastest and is vulnerable to the influence of the system, and the risk spillover effect on the system is greater than that of joint-stock banks. Finally, according to the results of theoretical research and empirical analysis, some suggestions are put forward to reduce the risk of banks and strengthen the supervision of systemic risk of banks.
【學位授予單位】：南京大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F224;F832.33
，
本文編號：2477934
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