外文翻譯--基于灰色關(guān)聯(lián)分析商業(yè)銀行信貸風(fēng)險管理

1、<p><b>　　中文3028字</b></p><p>　　畢業(yè)論文外文文獻(xiàn)翻譯</p><p>　　基于灰色關(guān)聯(lián)分析商業(yè)銀行信貸風(fēng)險管理</p><p><b>　　1 介紹</b></p><p>　　作為中國金融體系的重要組成部分,商業(yè)銀行的操作的魯棒性一直是金融監(jiān)管的核心,這是

2、關(guān)于整個金融系統(tǒng)的關(guān)鍵,國民經(jīng)濟(jì)的健康發(fā)展。目前,我國商業(yè)銀行的大部分收入來自存貸款利率之間的區(qū)別。所以貸款的質(zhì)量直接影響著銀行的操作導(dǎo)致流行的信用風(fēng)險的研究在理論和實踐上。等問題在銀行信貸資產(chǎn)質(zhì)量低,大量的不良貸款逐漸擠壓與金融市場環(huán)境的日益復(fù)雜和衍生金融工具的不斷發(fā)展。信用風(fēng)險對商業(yè)銀行吸引了越來越多的關(guān)注,必須正確理解。它不僅具有實際意義的加強(qiáng)國內(nèi)商業(yè)銀行的風(fēng)險管理,但也有助于建設(shè)一個健全的和強(qiáng)大的金融監(jiān)管體系,并最終導(dǎo)致日出發(fā)展

3、道路。與此同時,信用風(fēng)險的分析提供了一個參考實現(xiàn)不同的信貸和降低商業(yè)銀行的信用風(fēng)險,爭取有利的商業(yè)銀行的存款準(zhǔn)備金率,以追求更好的發(fā)展條件下的中央銀行實施不同的存款準(zhǔn)備金率。</p><p>　　對信用風(fēng)險的研究,國內(nèi)外學(xué)者主要集中在測量信貸與違約概率,違約風(fēng)險的信用評級和專家判斷。違約概率是債務(wù)人不能償還債務(wù)的可能性預(yù)期(默認(rèn))?，F(xiàn)有個人信貸資產(chǎn)違約概率模型主要包括默頓模型(默頓,1973);KMV模型的KMV

4、公司(KMV,1993 - 1997);物流模式;麥肯錫公司的信貸組合視圖模型(威爾遜,1997)；瑞士銀行模型,摩根大通和強(qiáng)度模型的信用度量模型(JP摩根,1997)。信用評級是由五個評價指標(biāo)包括資本充足率、資產(chǎn)質(zhì)量、管理、收益和流動性。駱駝評級體系是一套標(biāo)準(zhǔn)化和制度化的索引使用的綜合評級系統(tǒng)目前全國性銀行的貨幣監(jiān)理署管理員直接在業(yè)務(wù)和商業(yè)銀行和其他金融機(jī)構(gòu)的信貸條件。專家判斷方法的情況下使用上述模型需要的數(shù)據(jù)缺失的情況下,信用評級和

5、違約等數(shù)據(jù)。這種方法主要是集中在信用風(fēng)險評估從定性的角度。</p><p>　　國內(nèi)學(xué)者所做的風(fēng)險評估研究。例如,總結(jié)了信用風(fēng)險評估理論,提出了相關(guān)的理論基礎(chǔ)和基本做法。這些模型和方法主要是用來衡量風(fēng)險的大小,然后得出資產(chǎn)組合的形式,以避免或減少信用風(fēng)險的發(fā)生。在考慮具體的影響因素,研究低的數(shù)量。方舟子和曾慶紅(2004)建立了信用風(fēng)險評價函數(shù)使用多元統(tǒng)計方法對借款企業(yè)的財務(wù)數(shù)據(jù),以提高企業(yè)的信用風(fēng)險評估的科學(xué)性

6、。白朱所做的研究信用風(fēng)險影響因素,得出結(jié)論企業(yè)金融和宏觀經(jīng)濟(jì)、地區(qū)和行業(yè)指數(shù),對信貸風(fēng)險在一定程度上產(chǎn)生影響?？罩玫幕A(chǔ)上深入研究影響因素,本文研究了影響因素的減值貸款分析通過發(fā)生率不同行業(yè)使用灰色關(guān)聯(lián)度分析方法識別方法。它增加了宏觀經(jīng)濟(jì)因素,得出結(jié)論:信貸資產(chǎn)的比例所擁有的銀行對信用風(fēng)險的影響,并提供行業(yè)判斷執(zhí)行不同的信貸。根據(jù)實證分析結(jié)果,分析了銀行信用風(fēng)險的出現(xiàn)將從宏觀的角度,提供了客觀依據(jù)一些宏觀經(jīng)濟(jì)現(xiàn)象的存在。</p&g

7、t;<p>　　本文的結(jié)構(gòu)如下:第二部分提出了發(fā)病率識別方法與時間序列相關(guān)銀行信用風(fēng)險根據(jù)行業(yè)和宏觀經(jīng)濟(jì)因素。第三部分展示了實證研究和分析歷史數(shù)據(jù)的交通銀行理論模型,認(rèn)為商業(yè)銀行信用風(fēng)險管理建議根據(jù)這項研究的結(jié)果;第四部分是調(diào)查的結(jié)論。</p><p><b>　　2發(fā)生率識別方法</b></p><p>　　信用風(fēng)險是借款人或交易對手不能履行合同規(guī)定的

8、義務(wù)(如維修)由于信貸質(zhì)量變化,導(dǎo)致銀行損失。本文選擇減值貸款比率指的是信用風(fēng)險大小的指標(biāo)。減值貸款的銀行包括現(xiàn)有的不良貸款和部分可能是未來的不良貸款。減值貸款的比例直接影響銀行信貸的風(fēng)險。如果減值貸款比率高,商業(yè)銀行信貸風(fēng)險相對大;如果減值貸款比率較低,商業(yè)銀行信貸風(fēng)險也相對較小。</p><p>　　屬性的銀行貸款的行業(yè)和宏觀經(jīng)濟(jì)因素對銀行信貸風(fēng)險的影響,本文選擇灰色系統(tǒng)理論的灰色關(guān)聯(lián)分析方法來研究建立發(fā)生率

9、識別方法?；疑P(guān)聯(lián)度分析方法主要研究的發(fā)展趨勢和發(fā)展因素的內(nèi)部系統(tǒng),廣泛應(yīng)用于社會系統(tǒng)、經(jīng)濟(jì)系統(tǒng)、農(nóng)業(yè)系統(tǒng)、生態(tài)系統(tǒng)、教育系統(tǒng)。盡管總是使用回歸分析方法來研究解釋變量和變量之間的關(guān)系也廣泛應(yīng)用于復(fù)雜的客觀經(jīng)濟(jì)變革現(xiàn)象,適用于灰色關(guān)聯(lián)分析無論有多少數(shù)量的樣品相比,回歸分析和方差分析。計算也非常小,非常方便、定量和定性分析結(jié)果的偏差不會出現(xiàn)。根據(jù)現(xiàn)有數(shù)據(jù)灰度值的大型商業(yè)銀行的發(fā)展和一些人為的因素,這種方法似乎尤其適用。減值貸款比率多年了的行

10、為反應(yīng)系統(tǒng)的數(shù)據(jù)序列和不同行業(yè)的銀行貸款比例發(fā)生率相關(guān)因素序列建立模型行業(yè)占比和銀行不良貸款比率,然后影響因素上的探索性研究信用風(fēng)險將會完成。與此同時,宏觀經(jīng)濟(jì)因素將虛擬變量來測量相對貸款比率的變化通過使用絕對發(fā)生率識別方法對宏觀經(jīng)濟(jì)和減值貸款。發(fā)病率識別模型的過程如下。</p><p><b>　　定義7</b></p><p>　　基于上面的發(fā)病率識別方法,我們可

11、以計算灰色關(guān)聯(lián)度對行業(yè)與減值貸款比率因素和宏觀經(jīng)濟(jì)因素。根據(jù)絕對程度的灰色關(guān)聯(lián)度?m1,我們可以判斷宏觀經(jīng)濟(jì)因素會影響商業(yè)銀行明顯的減值貸款比率。因此,我們可以發(fā)現(xiàn)水平,宏觀經(jīng)濟(jì)因素影響商業(yè)銀行的信貸風(fēng)險。</p><p>　　根據(jù)結(jié)果的方法,不同的行業(yè)和宏觀經(jīng)濟(jì)因素如何影響不良貸款比率可以分析。</p><p>　　具體來說,影響商業(yè)銀行信用風(fēng)險的行業(yè)主要將通過灰色關(guān)聯(lián)的發(fā)現(xiàn)不同行業(yè)之間

12、的貸款規(guī)模和減值貸款比率,這樣我們可以提供定量參考商業(yè)銀行信貸。宏觀經(jīng)濟(jì)因素的影響,商業(yè)銀行信貸風(fēng)險將灰色系統(tǒng)理論的角度。</p><p>　　風(fēng)險控制系統(tǒng),從行業(yè)的角度,行業(yè)風(fēng)險因素可以根據(jù)灰色關(guān)聯(lián)度確定不同行業(yè)因素和不良資產(chǎn)貸款所示:方程14根據(jù)不同行業(yè)的行業(yè)風(fēng)險因素,實際的風(fēng)險和預(yù)期的風(fēng)險之間的偏差可以設(shè)置為：15個方程根據(jù)公式(10),行業(yè)關(guān)聯(lián)度越大,風(fēng)險越小偏差。在真正的貸款過程中,影響越大的行業(yè)信貸風(fēng)

13、險,管理部門應(yīng)該更多的關(guān)注。償還能力是需要特別指出。風(fēng)險的控制下,該行業(yè)風(fēng)險大相關(guān)性相對小范圍也符合實際情況。</p><p>　　因此,根據(jù)判斷行業(yè)信貸風(fēng)險的角度,行業(yè)因素的風(fēng)險判斷的結(jié)果可以擴(kuò)展到風(fēng)險控制。從行業(yè)因素、允許偏差的風(fēng)險控制可以定義,添加新的影響因素,使風(fēng)險控制更加完美,更加合理。</p><p>　　風(fēng)險控制是風(fēng)險管理的重要過程之一,所以我們可以控制的風(fēng)險信用風(fēng)險的行業(yè)因

14、素根據(jù)灰色關(guān)聯(lián)系數(shù)不同的行業(yè)因素造成的信用風(fēng)險。以及常見的控制系統(tǒng)的對象,控制過程的控制系統(tǒng)結(jié)構(gòu)如圖1所示。風(fēng)險控制制度的目的是確保在一定范圍控制風(fēng)險。對應(yīng)于灰色控制理論,以確保風(fēng)險控制的逐步穩(wěn)定。</p><p><b>　　2實證分析</b></p><p>　　根據(jù)第二部分的結(jié)果,我們得出這樣的結(jié)論:宏觀經(jīng)濟(jì)影響的減值貸款與實際情況一致。在現(xiàn)實生活中,良好的宏觀

15、經(jīng)濟(jì)環(huán)境可以減少減值貸款。穩(wěn)定的宏觀經(jīng)濟(jì)環(huán)境,如宏觀經(jīng)濟(jì)政策的擴(kuò)張或整個經(jīng)濟(jì)社會的發(fā)展將促進(jìn)企業(yè)經(jīng)營,提高企業(yè)的管理。的條件下不存在債務(wù)危機(jī)和生存危機(jī),企業(yè)將償還貸款和減值貸款比率最終將減少。關(guān)于上面的五個行業(yè)因素,制造業(yè)的貸款比例,權(quán)力、批發(fā)和零售和房地產(chǎn)業(yè)有各種對減值貸款比率的影響。電力行業(yè)最低限度影響商業(yè)銀行的信貸風(fēng)險。在田間小路的過程中,違約風(fēng)險最小而銀行為電力行業(yè)提供貸款。權(quán)力作為社會經(jīng)濟(jì)發(fā)展的一個基本能源是由國家控制,因此違

16、約風(fēng)險遠(yuǎn)低于其他行業(yè)。運(yùn)輸以及批發(fā)和零售貿(mào)易屬于高風(fēng)險信貸行業(yè)。這些行業(yè)的貸款必須嚴(yán)格對待,綜合考慮不同的公司在這些行業(yè)的實際情況是不容忽視的,所以我們有理由確定貸款和貸款的數(shù)量。特別是房地產(chǎn)業(yè)的相關(guān)程度最大的五個行業(yè)和對不良資產(chǎn)的影響是最大的。近年來,房地產(chǎn)業(yè)發(fā)展在全國各地商業(yè)銀行的主要力量。土地代理商尋求發(fā)展機(jī)遇無處不在,到處都建了房子。房地產(chǎn)市場面臨的高價格和高泡沫,更多的買家正在尋找更好的機(jī)會或者沒有那么多錢買,房地產(chǎn)業(yè)的資金流

17、動困難。銀行將風(fēng)險</p><p>　　Commercial bank credit risk management based on grey incidence analysis</p><p>　　1 Introduction</p><p>　　As an important component of China's financial system

18、, commercial bank's operation robustness is always the core of financial supervision, which is the key concerning the whole financial system and the sound development of the national economy. At present, the majority

19、 of incomes of our country commercial banks come from the difference between deposit and loan rates. So the quality of loans has a direct impact on the operations of banks which result in popular research into the credit

20、 risk on th</p><p>　　On the study of credit risk, domestic and foreign scholars mostly focused on the measurement of the credit default risk with default probability, the credit rating and expert judgment. T

21、he default probability is the possibility expected that the debtor cannot repay debts (default) on time. Existing individual credit asset default probability models mainly include Merton model (Merton, 1973); KMV model o

22、f KMV company (KMV, 1993-1997); Logistic model; Credit portfolio View model of McKinsey compan</p><p>　　Domestic scholars have done research on risk assessment as well. For instance, Liu (2010) has summarize

23、d credit risk assessment theory and put forward relevant theoretical basis and basic practices. These models and methods are mostly used to measure the size of the risk and then conclude the form of the asset portfolio t

24、o avoid or reduce the occurrence of credit risk. On considering concrete influent factors, the amount of research done is low. Fang and Zeng (2004) have built the credit risk ev</p><p>　　The structure of thi

25、s paper is as follows: the second part puts forward the incidence identification method with time series related to the bank credit risk according to industry and macroeconomic factors. The third part shows empirical res

26、earch and analysis on the historical data with the Bank of Communications of the theoretical model and concludes that the commercial bank credit risk management advises according to the results of this study; the fourth

27、part is the conclusion of investigation.</p><p>　　2 The incidence identification method</p><p>　　Credit risk is that the borrower or the counterparty is unable to perform a contract with the obl

28、igation prescribed (such as servicing) due to credit quality changes and causes a loss to the bank. This paper selects impairment loan ratio referring to the index of credit risk size. The impairment loan of the bank inc

29、ludes the existing non-performing loans and the portion which is likely to be non-performing loans in the future. The proportion of the impairment loans influence the bank credit risk</p><p>　　For the attrib

30、ute of the industry and macroeconomic factor of bank loans towards the bank credit risk influence, this article chooses the grey incidence analysis method of grey system theory to study establishing the incidence identif

31、ication method. The grey incidence analysis method mainly researches the development trend and development factors of the internal system, which is widely used in the social system, economic system, agricultural system,

32、ecosystem and education system. Although regre</p><p>　　Definition 7</p><p>　　Based on the incidence identification method above, we can compute the grey incidence degree with respect to the ind

33、ustry factor and macroeconomic factor with the impairment loan ratio. According to the absolute degree of grey incidence ? m1, we can judge whether the macroeconomic factor can influence the impairment loan ratio of comm

34、ercial bank obviously. Accordingly, we can find the level that macroeconomic factor influence the commercial bank's credit risk.</p><p>　　According to the results of the method, how the different industr

35、y and macroeconomic factors influence the impaired loan ratio can be analyzed.</p><p>　　Specifically, the industry affecting commercial bank credit risk largely will be found out through the degree of grey i

36、ncidence between the different industries loan scale and the impairment loan ratio, so that we can provide quantitative reference for commercial bank credit. Macroeconomic factor's influence to the commercial bank cr

37、edit risk will be demonstrated from the angle of the grey system theory.</p><p>　　In the risk control system, from the angle of industry, the industry risk factors can be determined according to grey correla

38、tion degree of different industries factors and bad assets loans which shown below: Equation 14 According to the industry risk factors of different industries, the deviation between actual risk and the expected risk can

39、be set as: Equation 15 According to formula (10), the greater the industry correlation is, the smaller the risk deviation is. In the real lending process, </p><p>　　Therefore, according to the judgment of cr

40、edit risk at the industry angle, the result of the risk judgment of industry factor can be extended to the risk control. From the industry factor, the allowed deviation of risk control can be defined so as to add new inf

41、luent factors and make the risk control to be more perfect and more reasonable.</p><p>　　The risk control is one of the important processes of risk management, so we can control the risk from the industry fa

42、ctor of credit risk according to grey incidence coefficient result of different industry factors with the credit risk. As well as the common control system's object, the control process has a control system structure

43、 as shown in Figure 1. The purpose of risk control system is to ensure the risk is in certain limits under controlling. Corresponding to the grey control theory, that</p><p>　　2. Empirical analysis</p>

44、<p>　　According to the result of the second part, we conclude that the macro economy affects the impairment loan which is consistent with the actual situation. In real life, a good macroeconomic circumstance can r

45、educe the impairment loan. The steady macroeconomic circumstance, such as the expansion of macroeconomic policies or the whole development of economics in society will promote the enterprise operation and improve the man