本文選題：商業(yè)銀行 + 信用風險　； 參考：《西南財經(jīng)大學》2013年碩士論文

【摘要】：上世紀七十年代由于金融自由化發(fā)展和金融管制放松,使各金融機構的業(yè)務迅速發(fā)展,趨利性的金融衍生產(chǎn)品迅速出現(xiàn)。金融業(yè)的相關風險不斷暴露,不斷引發(fā)金融危機,如亞洲金融危機、歐洲貨幣危機、美國次貸危機。尤其是美國次貸危機,被前美聯(lián)儲主席格林斯潘認為是“百年一遇”的全球性金融風暴。有多方面原因?qū)е略摻鹑谖C的出現(xiàn),但究其根源,主要是信用風險管理方面的失控。 這些由于金融創(chuàng)新而爆發(fā)的金融危機使世界經(jīng)濟不斷遭到巨大的影響。為此,國際金融界各監(jiān)管部門對風險監(jiān)管提高了重視。國際銀行監(jiān)管機構于2010年9月出臺的《巴塞爾新資本協(xié)議》,對銀行風險的控制更加關注,提出的資本和流動性監(jiān)管標準比以前更加嚴格。 從國內(nèi)目前的研究現(xiàn)狀來看,我國銀行業(yè)信用評級體系只可達到基本的內(nèi)部評級法的要求,但是與高級內(nèi)部評級法的規(guī)定還相差較遠,遠達不到規(guī)定的要求。我國商業(yè)銀行成立較晚,銀行業(yè)監(jiān)管方面不完善,信用風險管理水平落后,技術不發(fā)達,體系不健全,沒有更好的方法量化信用風險的大小。 因此,借鑒并研究學習國際銀行業(yè)信用風險管理的相關先進技術對我國銀行業(yè)抗風險能力的提高和信用風險管理的加強具有重要意義,在將來的國際競爭中處于有利地位。結合我國國有商業(yè)銀行的具體情況以及面對當前上市公司非交易性金融信貸資產(chǎn),應用CreditMetrics模型進行研究和計算,對于我國銀行業(yè)的信用風險水平度量具有重大意義。 本文以CreditMetrics模型的實證分析與應用為導向,先后分析我國商業(yè)銀行信用風險方面的現(xiàn)狀、存在的問題和對我國銀行業(yè)在信用風險管理方面實踐的簡要回顧基礎上,圍繞商業(yè)銀行如何利用信用風險的模型方法去度量其面對的非交易性金融資產(chǎn)信貸組合,如針對銀行貸款和非公開性私募債券的價值和風險進行度量和分析。最后提出在我國如何更好的加強社會各層面的信用風險管理,以至于減少商業(yè)銀行及其他金融結構等信用風險,并對此提出一些政策和建議。 文章主要采用實證分析和數(shù)理模型分析的研究方法。主要基于金融學、信用風險管理、數(shù)理金融學等方面的相關理論知識和模型工具。通過對我國商業(yè)銀行信用風險管理現(xiàn)狀的分析,利用CreditMetrics模型及其他相關數(shù)理模型輔助工具,如蒙特卡洛模擬方法、Cholesky分解方法、Nelson-Siegel方法以及VaR方法和ES方法。在假設的非交易性金融信貸資產(chǎn)組合頭寸的信息下,來實證分析如果信貸質(zhì)量發(fā)生變化而導致2013年信用評級變化的信用風險水平,并結合目前我國當前各層面存在的信用風險管理問題提出相應的建議。 在信用風險度量的實證部分,基于我國十二家上市公司相關數(shù)據(jù)組成的信貸資產(chǎn)組合,應用CreditMetrics模型進行該信貸資產(chǎn)組合的信用風險水平度量。但是,由于貸款不能公開交易信息,無法準確獲得貸款市值及其一年內(nèi)貸款價值的波動大小。對此,可以通過利用該債務公司的一些其他公開信息來估計其貸款市值。這些需要搜集的信息包括：選取的12家債務公司2012年的歷史股價,債務公司主體長期信用等級及其資產(chǎn)回收率,信用風險轉(zhuǎn)移矩陣和債券市場上的各信用評級的公司債券信息。 CreditMetrics模型最先由J.P.摩根同其他合伙人于1997年提出,用于計量貸款組合信用風險的新型內(nèi)控模型,考慮資產(chǎn)價值隨經(jīng)濟的時間變動和信用等級的變化引起的資產(chǎn)總價值變動。該模型基本思想是通過收集該債務公司的其他公開信息,并基于債務公司在一定期限內(nèi)(通常是1年)的某個市場風險因子的變動情況,研究下一年因受違約事件或債務公司信用質(zhì)量導致的信用等級轉(zhuǎn)移、降級、升級,從而影響資產(chǎn)組合的價值,以此計量該資產(chǎn)組合在第2年期末的市場價值。進一步根據(jù)期末損失分布,求出一定置信水平下信貸資產(chǎn)組合可能發(fā)生的最大價值損失。 CreditMetrics模型對于信貸組合信用風險的度量應用需要一些理論假設條件,這些假設包括：信貸資產(chǎn)的股票收益率呈標準正態(tài)分布,并服從標準的幾何布朗運動。不良貸款回收率與違約率不相關。非交易性金融資產(chǎn)組合中各筆貸款頭寸在研究期間保持不變。 論文具體研究了以下幾個問題： 第一,我國商業(yè)銀行信用風險的現(xiàn)狀和存在的問題,并簡要回顧了我國已經(jīng)對此做出的管理實踐。 由于我國銀行業(yè)還沒有建立起先進的信用風險資料的歷史數(shù)據(jù)庫,數(shù)據(jù)庫存在問題,導致信用風險的計量難度較大。商業(yè)銀行在長期經(jīng)營中也暴露出大量信用風險,僅從財務報表中就可以體現(xiàn)出商業(yè)銀行的不良貸款數(shù)額巨大而且在急劇上升,貸款呆帳準備金比率較低,資產(chǎn)負債比例偏高,貸款量略大。在商業(yè)銀行的業(yè)務中,經(jīng)營監(jiān)管各環(huán)節(jié)仍能反應出信用風險管理的缺失。 鑒于國際銀行業(yè)頻繁的發(fā)生動蕩并出現(xiàn)危機,國際監(jiān)管機構不斷發(fā)布并出臺一些法律法規(guī),以此約束并規(guī)范銀行業(yè)的信用風險以及內(nèi)部控制。按照《巴塞爾新資本規(guī)定》的要求,我國一些商業(yè)銀行開始進行內(nèi)部控制制度建設。在我國,中小企業(yè)作為特殊群體,近些年迅速發(fā)展。在促進我國經(jīng)濟繁榮以及多元化發(fā)展的過程中,對中小企業(yè)發(fā)展的風險管理也采取了一系列的保護方法。 第二,基于CreditMetrics模型的信用風險度量實證分析與研究過程。 在信用風險度量的實證部分,在我國上市公司和資本市場中選取數(shù)據(jù),建立了信貸風險組合的度量框架。通過計算債務公司的歷史(2012年)股價收益率,利用蒙特卡洛方法模擬出與上年相關水平一致的收益率。利用穆迪公司發(fā)布的信用風險轉(zhuǎn)移矩陣,計算出由于信用評級變化對應的不同收益率臨界值。通過Nelson-Siegel方法計算資本市場不同信用級別的債券收益率,從而得到2013年底信貸資產(chǎn)評級變化后的資產(chǎn)價值。再經(jīng)過搜集債務公司主體長期信用等級和對應的資產(chǎn)回收率,計算VaR值和ES值來度量信用風險水平。 實證結果認為CreditMetrics模型對于研究我國信貸資產(chǎn)組合的信用風險水平的度量可行,但是仍然需要進一步改進。 第三,結合當前我國各層面存在的信用風險管理問題提出相應的建議。 評級機構應盡快建立信用風險數(shù)據(jù)庫,積極研究發(fā)明適合我國的內(nèi)部評級模型和體系,建立全面可靠的信用風險數(shù)據(jù)庫,并統(tǒng)計出適合國內(nèi)使用的風險轉(zhuǎn)移矩陣、資本回收率和債券遠期貼現(xiàn)率等。 本文采用國際權威并流行的度量信用風險水平的CreditMetrics模型,由于歷史數(shù)據(jù)的搜集需要較強的數(shù)據(jù)庫支持,因此這種模型目前在我國只被少數(shù)大型銀行使用,還未在國內(nèi)廣泛推廣。筆者為此度量方法做嘗試,并驗證易于計算并可行。本文可能存在的創(chuàng)新內(nèi)容有： 第一,文章對于信貸資產(chǎn)組合之間的相關系數(shù)用Cholesky方法分解,將每對債務公司之間的相關特征用Cholesky分解矩陣來表示。利用該分解矩陣將第一年債務公司之間的相關特征轉(zhuǎn)移到模擬的第二年(2013年)債務公司收益率的時間序列中,從而對模擬的2013年信貸資產(chǎn)的收益率進行調(diào)整。相關性水平利用該上市公司的股價收益率相關性代替資產(chǎn)總價值的相關性,與經(jīng)濟變動密切相聯(lián)系,時刻反應經(jīng)濟的市場變動,具有較強的時效性。 第二,在計算不同信用評級的信貸資產(chǎn)遠期利率水平時,沒有采用傳統(tǒng)方法的零息票國庫券利率去貼現(xiàn)信貸資產(chǎn)的現(xiàn)金流,而是采用Nelson-Siegel模型,這樣可以針對不同信用評級的信貸資產(chǎn)分別計算其價值。為了使本文研究國內(nèi)信貸資產(chǎn)更有針對性,所以樣本數(shù)據(jù)選取的國內(nèi)各信用評級的公司債券,以此來計算國內(nèi)公司一年后變換到其他評級的價值。 第三,在計算信用風險水平時,本文不僅采用了VaR值的計算,還計算了ES值�？紤]了所有信貸資產(chǎn)損失超過VaR值的小概率事件,對超過VaR值的所有信貸資產(chǎn)的損失值同樣重視。 在運用CreditMetrics實證研究過程中發(fā)現(xiàn),該模型度量風險的精確性高度依賴于信用評級轉(zhuǎn)移矩陣和資本市場的債券遠期利率的準確性,所以評級機構應盡快建立相關數(shù)據(jù)庫并對此進行統(tǒng)計計算。 計算結果有可能低估了《巴塞爾新資本協(xié)議》中經(jīng)濟資本的8%要求,因為度量過程中的置信水平選取較低,而且債券的到期日都在三年以上,而本文只研究了債券信貸資產(chǎn)發(fā)行一年后的信用風險水平。而且本文認為CreditMetrics模型的損失分布函數(shù)有可能存在一個厚尾分布,今后可以基于此進一步考慮CreditMetrics模型的實證計算。 本文的CreditMetrics模型使用股價市值,計算結果具有客觀性和前瞻預期性,貸款信息緊跟市場變動而變動。而且不僅考慮了貸款違約的風險,也考慮了信貸資產(chǎn)質(zhì)量變化的風險。不僅可以用來度量信貸組合的信用風險,也可度量單一貸款的信用風險。在度量信用風險時,不僅利用VaR值來表示,而且還用ES值對VaR值進行補充。指出銀行業(yè)的信用風險是我國商業(yè)銀行面臨的主要風險之一,當前我國國內(nèi)銀行業(yè)要依據(jù)《巴塞爾新資本協(xié)議》的要求,完善我國銀行業(yè)的體制改革,制定前瞻性的銀行發(fā)展策略,從而引導銀行的改革與建設。
[Abstract]:Since the development of financial liberalization and the relaxation of financial regulation in the 1970s and the 1970s , the rapid development of the business of financial institutions and the rapid emergence of financial derivatives . The risks associated with the financial industry have been continuously exposed to the global financial crisis , such as the Asian financial crisis , the European monetary crisis and the US subprime crisis . Especially in the US subprime crisis , the former Federal Reserve Chairman , Greenspan , is regarded as a global financial storm of " one hundred years . " However , it is the root cause of the financial crisis , which is mainly the control of credit risk management .

The financial crisis triggered by financial innovation has caused the world ' s economy to continue to suffer . For this reason , regulators in the international financial sector have given greater attention to risk regulation . The Basel 2 Basel Capital Accord , issued in September 2010 , is more concerned about the control of banks ' risks , and the proposed standards of capital and liquidity supervision are more stringent than before .

In view of the present research situation in China , the credit rating system of China ' s banking industry can only meet the requirement of the basic internal rating method , but it is far from the requirement of the advanced internal rating method , but it can ' t meet the requirement . The bank ' s banking supervision is not perfect , the credit risk management level is backward , the technology is not developed , the system is not perfect , and the credit risk is not quantified .

Therefore , it is of great significance to learn from and study the relevant advanced technology of credit risk management in China ' s banking industry . It is of great significance to strengthen the anti - risk ability and credit risk management in China ' s banking industry in the future .

Based on the empirical analysis and application of the Credit Metrics model , this paper analyzes the current situation and existing problems of the credit risk of commercial banks in China , and measures and analyzes the value and risk of the bank loans and non - public private equity bonds . Finally , it puts forward some policies and suggestions on how to strengthen the credit risk management at all levels in our country so as to reduce the credit risk of commercial banks and other financial structures .

Based on the analysis of the current situation of credit risk management in China ' s commercial banks , this paper makes an empirical analysis on the credit risk level of credit rating change in 2013 based on the analysis of the current situation of credit risk management in China ' s commercial banks , such as Monte Carlo simulation method , cholesky decomposition method , Nelson - Siegel method , VaR method and ES method .

In the empirical part of the credit risk measure , based on the credit assets combination of twelve listed companies in our country , the credit risk level measure of the credit asset portfolio is made based on the Credit Metrics model . However , due to the fact that the loan cannot disclose the transaction information , it is impossible to accurately obtain the loan market value and the fluctuation size of the loan value within one year . The information that needs to be collected includes the historical stock price of the 12 debt companies selected in 2012 , the long - term credit rating of the debt company principal and its asset recovery rate , the credit risk transfer matrix and the corporate bond information of each credit rating on the bond market .

Credit Metrics Model is first proposed by J . P . Morgan and other partners in 1997 . It is used to measure the credit risk of loan portfolio . The basic idea of this model is to study the value of the asset portfolio at the end of the second year by collecting other public information of the debt company and based on the change of the credit rating caused by the credit quality of the debt company .

The Credit Metrics model requires some theoretical assumptions for the measurement of credit portfolio credit risk . These assumptions include : the stock yield of credit assets is standard normal distribution and follows the standard geometric Brownian motion . The non - performing loan recovery rate is not related to the default rate .

In this paper , the following problems are studied :

First , the present situation and existing problems of credit risk in commercial banks in China are briefly reviewed , and the management practice has been briefly reviewed .

Because China ' s banking has not established the advanced historical database of credit risk information , there is a problem in the database , which leads to the great difficulty of credit risk measurement . In the long run , commercial banks also exposed a large amount of credit risk . Only from the financial statements , the amount of non - performing loans of commercial banks is huge and the loan amount is slightly larger . In the business of commercial banks , the management and supervision links can still reflect the lack of credit risk management .

In view of the frequent turbulence and crisis in the international banking industry , the international regulatory agencies have issued and issued some laws and regulations to restrict and regulate the credit risk and internal control of the banking industry . In accordance with the requirements of the Basel 2 new capital requirement , some commercial banks in China have started the internal control system construction . In our country , small and medium - sized enterprises are developing rapidly in recent years . In the process of promoting the economic prosperity and diversification of our country , the risk management of the development of small and medium - sized enterprises has also taken a series of protection methods .

Secondly , based on the Credit Metrics model , the empirical analysis and research process of credit risk measurement .

In the empirical part of credit risk measurement , the data is selected in China ' s listed company and capital market , and the measure frame of credit risk combination is established . By calculating the yield of stock price in the history of the debt company ( 2012 ) , the yield of different yield corresponding to the previous year is simulated by Monte Carlo method . By means of the credit risk transfer matrix issued by Moody ' s Company , the asset value after the credit rating change has been calculated . Through the collection of the long - term credit rating and the corresponding asset recovery rate of the debt company , the VaR and ES value are calculated to measure the credit risk level .

The empirical results show that the Credit Metrics model is feasible to study the credit risk level of our country ' s credit portfolio , but we still need to improve further .

Thirdly , the paper puts forward some suggestions on the management of credit risk in all aspects of our country .

The rating agencies should establish the credit risk database as soon as possible , actively study the internal rating models and systems suitable for our country , establish a fully reliable credit risk database , and calculate the risk transfer matrix , capital recovery rate and long - term discount rate suitable for domestic use .

In this paper , based on the Credit Metrics model of the international authoritative and popular measure credit risk level , since the collection of historical data requires stronger database support , this model is only used by a small number of large banks in our country , and has not been widely promoted in China . The author attempts to do this and verifies that it is easy to calculate and feasible . The possible innovations in this paper are as follows :

First , the correlation coefficient between the credit asset portfolio is decomposed by the cholesky decomposition matrix , and the correlation between each pair of debt companies is represented by the cholesky decomposition matrix . By using the decomposition matrix , the correlation characteristics between the first year debt companies are transferred to the simulated second year ( 2013 ) debt company yield time series , so as to adjust the yield of the simulated 2013 credit assets .

Secondly , when calculating the forward interest rate level of credit assets with different credit rating , we do not adopt the traditional method ' s zero coupon treasury bond interest rate to discount the cash flow of the credit assets , but adopt the Nelson - Siegel model so that the value of the credit assets with different credit rating can be calculated respectively . In order to make the research study domestic credit assets more targeted , the domestic credit rating of the sample data is selected as the corporate bond of each credit rating , so as to calculate the value of the domestic company after one year after conversion to other ratings .

Thirdly , when calculating credit risk level , this paper not only adopts VaR calculation , but also calculates ES value . Considering the small probability event that all credit asset losses exceed VaR value , the loss value of all credit assets that exceed VaR value is also paid .

It is found that the accuracy of the model measure risk depends on the accuracy of the long - term interest rate of the credit rating transfer matrix and the capital market , so the rating agency should establish the relevant database as soon as possible and calculate the risk .

It is possible to underestimate the 8 % requirement of economic capital in Basel 2 Capital Accord , because the confidence level in the measurement process is lower , and the maturity of the bond is more than three years , and the credit risk level after one year of the issuance of the bond credit asset is studied .

The credit risk is one of the main risks faced by commercial banks in China . It is pointed out that the credit risk of banking is one of the main risks faced by commercial banks in China .

【學位授予單位】：西南財經(jīng)大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：F832.4;F224

【參考文獻】

相關期刊論文 前10條

1 潘蔚琳,王可;信用風險計量模型的分析與借鑒[J];北方經(jīng)貿(mào);2002年08期

2 陳忠陽;信用風險量化管理模型發(fā)展探析[J];國際金融研究;2000年10期

3 程鵬,吳沖鋒,李為冰;信用風險度量和管理方法研究[J];管理工程學報;2002年01期

4 朱小宗;張宗益;耿華丹;吳俊;;現(xiàn)代信用風險度量模型的實證比較與適用性分析[J];管理工程學報;2006年01期

5 董穎穎,柯孔林;信用計量技術及其在我國的應用分析[J];華東經(jīng)濟管理;2002年06期

6 石良平 ,趙然 ,靳潔;論商業(yè)銀行信用風險的量化管理[J];上海經(jīng)濟研究;2003年04期

7 葉慶祥,景乃權,徐凌峰;基于資本市場理論的上市公司信用風險度量研究[J];經(jīng)濟學家;2005年02期

8 吳世農(nóng),盧賢義;我國上市公司財務困境的預測模型研究[J];經(jīng)濟研究;2001年06期

9 楊蘊石,徐樅巍;高級內(nèi)部信用風險度量模型方法的比較[J];科技導報;2004年07期

10 陳靜;上市公司財務惡化預測的實證分析[J];會計研究;1999年04期

，

本文編號：1795831