本文選題：商業(yè)銀行　切入點：系統(tǒng)性風(fēng)險　出處：《山西財經(jīng)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：自從2006年11月,中國金融系統(tǒng)全面對外開放,中國金融業(yè)開始進入機遇與風(fēng)險并存的經(jīng)濟環(huán)境,銀行業(yè)作為金融業(yè)的中流砥柱,面臨新的挑戰(zhàn),不僅如此,由于美國次級房貸危機引發(fā)的金融風(fēng)暴使全球經(jīng)濟陷入了新一輪的金融危機,作為我國金融行業(yè)的重要組成部分,商業(yè)銀行難逃此次危機,這給我國商業(yè)銀行帶來不小的壓力。由于系統(tǒng)性風(fēng)險在此次金融危機中扮演的重要角色,有關(guān)系統(tǒng)性風(fēng)險的研究便成為國內(nèi)外學(xué)者研究的熱門課題。本文就我國商業(yè)銀行系統(tǒng)性風(fēng)險的度量問題展開研究,在介紹系統(tǒng)性風(fēng)險的概念和影響因素的基礎(chǔ)上,對我國商業(yè)銀行系統(tǒng)性風(fēng)險進行了定量分析,以期本文能夠為繼續(xù)研究商業(yè)銀行針對系統(tǒng)性風(fēng)險逆周期監(jiān)管的學(xué)者提供一定的思路、建議。本文主要采用或有權(quán)益分析法,將我國整個銀行體系中的所有2010年以前上市的銀行作為一個整體單位來研究,得到違約概率和違約距離等風(fēng)險指標(biāo),并結(jié)合這些指標(biāo)探討2007年第一季度至2016年第一季度我國商業(yè)銀行的系統(tǒng)性風(fēng)險發(fā)展水平,最后結(jié)合前期的度量研究對我國商業(yè)銀行防御系統(tǒng)性風(fēng)險提供建議。通過本文的量化研究,可以得到想要抵御系統(tǒng)性風(fēng)險,違約距離應(yīng)該維持在什么水平;違約概率為0.03時,說明有較大經(jīng)濟危機,會產(chǎn)生系統(tǒng)性風(fēng)險,對于我國商業(yè)銀行來說,應(yīng)將違約概率控制在0.01以內(nèi);預(yù)期損失凈現(xiàn)值反映商業(yè)銀行可以預(yù)計到的風(fēng)險損失值,通過本文分析可知,往往在風(fēng)險過后,商業(yè)銀行才增加預(yù)期損失凈現(xiàn)值,有悖于逆周期監(jiān)管的核心宗旨;目前我國政府針對我國經(jīng)濟的根本問題,采取了一系列措施,有助于我國整體金融的健康穩(wěn)定發(fā)展,一定程度上從根本上緩解了我國商業(yè)銀行所面臨的系統(tǒng)性風(fēng)險問題。本文的創(chuàng)新之處在于,首次利用CCA模型對能代表我國商業(yè)銀行整體水平的所有2010年以前上市的商業(yè)銀行作為一個部門所面臨的系統(tǒng)性風(fēng)險進行量化分析,突破以往僅對單個銀行的系統(tǒng)性風(fēng)險進行計量研究的局面;數(shù)據(jù)的處理上,對于前期未上市銀行股權(quán)市場價值不可得的情況,暫時選用賬面價值代替;本文采用MATLAB對CCA模型進行編程,在編程過程中,借鑒了KMV模型的編程模式,用該程序可以直接利用股權(quán)市場價值及其波動率和負(fù)債賬面價值算出資產(chǎn)市場價值及其波動率,進而得到違約距離、違約概率、預(yù)期損失凈現(xiàn)值等可以直接衡量風(fēng)險的指標(biāo)。
[Abstract]:Since November 2006, when China's financial system was fully opened to the outside world, China's financial industry has begun to enter an economic environment in which opportunities and risks coexist. As the mainstay of the financial industry, the banking industry is facing new challenges, not only that. As a result of the financial turmoil caused by the subprime mortgage crisis in the United States, the global economy has fallen into a new round of financial crisis. As an important part of our financial industry, commercial banks cannot escape the crisis. This has put a lot of pressure on commercial banks in China. Because of the important role that systemic risk plays in the financial crisis, The research on systemic risk has become a hot topic for scholars at home and abroad. This paper studies the measurement of systemic risk of commercial banks in China, based on the introduction of the concept of systemic risk and its influencing factors. The quantitative analysis of the systemic risk of commercial banks in China is carried out in the hope that this paper can provide some ideas for the scholars who continue to study the countercyclical supervision of systemic risks in commercial banks. All the banks listed before 2010 in the whole banking system of our country are studied as a whole unit, and the risk indicators such as default probability and default distance are obtained. Combined with these indicators, this paper discusses the development level of systemic risk of commercial banks in China from in the first quarter of 2007 to in the first quarter of 2016. Finally, combined with the previous measurement research, it provides suggestions for commercial banks to defend against systemic risk. Through the quantitative research in this paper, we can find out what level the distance of default should be maintained in order to resist systemic risk; when the probability of default is 0.03, It shows that there is a large economic crisis, there will be systemic risk, for our commercial banks, the probability of default should be controlled within 0.01; the NPV of expected losses reflects the expected risk loss value of commercial banks, through the analysis of this paper, we can know, Often after the risk, commercial banks increase the net present value of expected losses, which is contrary to the core purpose of counter-cyclical supervision. At present, our government has taken a series of measures to address the fundamental problems of our economy. It is helpful to the healthy and stable development of the whole finance of our country, and to some extent alleviates the systemic risk problem faced by the commercial banks of our country. The innovation of this paper lies in:. For the first time, the CCA model is used to quantify the systemic risks faced by all commercial banks listed before 2010, which represent the overall level of commercial banks in China. To break through the situation that the systematic risk of a single bank was only studied in the past, and to deal with the data, the unlisted bank stock market value was temporarily replaced by book value. In this paper, MATLAB is used to program the CCA model. In the process of programming, the programming mode of KMV model is used to calculate the market value of assets and its volatility directly by using the stock market value and its volatility and the book value of liabilities. Then, the distance of default, the probability of default, the net present value of expected loss and so on can be obtained to measure the risk directly.
【學(xué)位授予單位】：山西財經(jīng)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F832.33

【參考文獻】

相關(guān)期刊論文 前10條

1 中國人壽保險(集團)公司財務(wù)部課題組;繆建民;;我國壽險行業(yè)系統(tǒng)性風(fēng)險的評估、計量與防范[J];金融會計;2015年07期

2 吳恒煜;胡錫亮;呂江林;聶富強;;我國行業(yè)風(fēng)險的決定因素及傳遞機制研究——來自滬深300細(xì)分行業(yè)的經(jīng)驗證據(jù)[J];當(dāng)代經(jīng)濟科學(xué);2014年05期

3 范小云;方意;王道平;;我國銀行系統(tǒng)性風(fēng)險的動態(tài)特征及系統(tǒng)重要性銀行甄別——基于CCA與DAG相結(jié)合的分析[J];金融研究;2013年11期

4 吳恒煜;胡錫亮;呂江林;;我國銀行業(yè)系統(tǒng)性風(fēng)險研究——基于拓展的未定權(quán)益分析法[J];國際金融研究;2013年07期

5 巴曙松;居姍;朱元倩;;SCCA方法與系統(tǒng)性風(fēng)險度量[J];金融監(jiān)管研究;2013年03期

6 方意;趙勝民;王道平;;我國金融機構(gòu)系統(tǒng)性風(fēng)險測度——基于DGC-GARCH模型的研究[J];金融監(jiān)管研究;2012年11期

7 劉呂科;張定勝;鄒恒甫;;金融系統(tǒng)性風(fēng)險衡量研究最新進展述評[J];金融研究;2012年11期

8 宮曉琳;;宏觀金融風(fēng)險聯(lián)動綜合傳染機制[J];金融研究;2012年05期

9 宮曉琳;;未定權(quán)益分析方法與中國宏觀金融風(fēng)險的測度分析[J];經(jīng)濟研究;2012年03期

10 沈沛龍;樊歡;;基于可流動性資產(chǎn)負(fù)債表的我國政府債務(wù)風(fēng)險研究[J];經(jīng)濟研究;2012年02期

相關(guān)博士學(xué)位論文 前1條

1 孫潔;基于或有權(quán)益方法的中國上市商業(yè)銀行風(fēng)險研究[D];武漢大學(xué);2010年

相關(guān)碩士學(xué)位論文 前1條

1 賈祥蕊;我國銀行業(yè)系統(tǒng)性風(fēng)險分析[D];山東大學(xué);2013年

，

本文編號：1564049