本文選題：信用評(píng)級(jí)　切入點(diǎn)：信息敏感性　出處：《大連理工大學(xué)》2016年博士論文

【摘要】：作為國(guó)民經(jīng)濟(jì)和社會(huì)發(fā)展重要組成部分的小企業(yè),信用評(píng)級(jí)的結(jié)果直接影響其融資的渠道、可能性及成本。甚至,信用評(píng)級(jí)結(jié)果會(huì)影響小企業(yè)購(gòu)銷(xiāo)合同的簽訂、招投標(biāo)的參加及政府采購(gòu)的爭(zhēng)取等諸多方面。特別是多年以來(lái)小企業(yè)貸款貴和貸款難的問(wèn)題始終都未得到有效解決。這一問(wèn)題的解決固然復(fù)雜困難,但鑒于目前許多商業(yè)銀行等金融機(jī)構(gòu)已將對(duì)貸款企業(yè)客戶的信用評(píng)級(jí)結(jié)果納入到信貸審批程序之中,顯然若能科學(xué)合理地對(duì)小企業(yè)進(jìn)行信用評(píng)級(jí)必將有助于貸款貴和貸款難問(wèn)題的解決。此外,信用評(píng)級(jí)也事關(guān)著國(guó)家金融體系的安全。因此,開(kāi)展小企業(yè)信用評(píng)級(jí)的研究至關(guān)重要。小企業(yè)信用評(píng)級(jí)的本質(zhì)在于其信用風(fēng)險(xiǎn)的評(píng)價(jià)。為了通俗形象地反映企業(yè)信用風(fēng)險(xiǎn)的相對(duì)大小,通常會(huì)將企業(yè)的信用風(fēng)險(xiǎn)進(jìn)行等級(jí)劃分。而信用評(píng)級(jí)指標(biāo)體系和信用評(píng)級(jí)指標(biāo)的賦權(quán)是信用風(fēng)險(xiǎn)評(píng)價(jià)的基礎(chǔ)。其中,信用評(píng)級(jí)指標(biāo)體系是通過(guò)信用評(píng)級(jí)指標(biāo)篩選,即通過(guò)剔除信用風(fēng)險(xiǎn)識(shí)別能力弱和反映信息重疊程度高的信用評(píng)級(jí)海選指標(biāo)實(shí)現(xiàn)的；信用評(píng)級(jí)指標(biāo)賦權(quán)是指確定信用評(píng)級(jí)指標(biāo)的權(quán)重。本文主要聚焦于小企業(yè)信用風(fēng)險(xiǎn)的評(píng)級(jí)及其合理性的檢驗(yàn),主要工作如下：(1)為了選取信用風(fēng)險(xiǎn)識(shí)別能力大的信用評(píng)級(jí)指標(biāo),提出了一種基于信用風(fēng)險(xiǎn)識(shí)別能力的信用評(píng)級(jí)指標(biāo)遴選方法。首先,將信用評(píng)級(jí)指標(biāo)的取值分為違約與非違約兩組,根據(jù)一個(gè)信用評(píng)級(jí)指標(biāo)取值的組間變異與組內(nèi)變異的相對(duì)差距越大,該信用評(píng)級(jí)指標(biāo)對(duì)違約與否的影響越顯著,該信用評(píng)級(jí)指標(biāo)越應(yīng)予以保留的F檢驗(yàn)思路,剔除對(duì)信用違約與否影響不顯著的少量信用評(píng)級(jí)指標(biāo),以保證保留下來(lái)的信用評(píng)級(jí)指標(biāo)皆對(duì)信用違約狀態(tài)有一定的影響。之后,通過(guò)主成分占待篩信用評(píng)級(jí)指標(biāo)集信息、的比例與每個(gè)被保留的主成分對(duì)信用評(píng)級(jí)指標(biāo)偏導(dǎo)數(shù)的乘積的和,表示待篩信用評(píng)級(jí)指標(biāo)集信息受該指標(biāo)大小變化影響的敏感程度,稱(chēng)之為指標(biāo)的信息、敏感性。在此基礎(chǔ)上,根據(jù)信用評(píng)級(jí)指標(biāo)的信息敏感性越大,該指標(biāo)解釋待篩信用評(píng)級(jí)指標(biāo)集蘊(yùn)含的信用風(fēng)險(xiǎn)信息的能力越大,該指標(biāo)識(shí)別信用違約綜合風(fēng)險(xiǎn)的能力也越大,該指標(biāo)越應(yīng)予以保留的信息敏感性思路,進(jìn)一步地剔除信用違約綜合風(fēng)險(xiǎn)識(shí)別能力弱的信用評(píng)級(jí)指標(biāo)。該方法克服了現(xiàn)有研究?jī)H依賴(lài)信用評(píng)級(jí)指標(biāo)對(duì)違約與否的影響選取信用風(fēng)險(xiǎn)識(shí)別能力大的指標(biāo)的不足,也克服了現(xiàn)有主成分降維方法遴選指標(biāo)時(shí)僅依據(jù)指標(biāo)的單個(gè)因子載荷無(wú)法合理篩選指標(biāo)的不足。(2)為了降低信用評(píng)級(jí)指標(biāo)彼此之間的信息重疊程度,提出了一種基于信息重疊雙重剔除的信用評(píng)級(jí)指標(biāo)遴選方法。首先,該方法通過(guò)一組信用評(píng)級(jí)指標(biāo)的病態(tài)指數(shù)確定一組信用評(píng)級(jí)指標(biāo)整體的信息重疊程度,并以一個(gè)評(píng)級(jí)指標(biāo)被剔除后該組信用評(píng)級(jí)指標(biāo)病態(tài)指數(shù)減少的幅度確定該指標(biāo)與指標(biāo)集內(nèi)其余指標(biāo)間的信息重疊程度,簡(jiǎn)稱(chēng)為該信用評(píng)級(jí)指標(biāo)的信息重疊程度。通過(guò)剔除信息重疊程度高的指標(biāo),實(shí)現(xiàn)信用評(píng)級(jí)指標(biāo)間整體信息重疊程度的快速降低。之后,為了避免指標(biāo)體系整體信息重疊程度低而部分指標(biāo)間信息重疊高,進(jìn)一步地剔除相關(guān)程度高的任兩個(gè)指標(biāo)中信息敏感性小的指標(biāo)。該方法克服了現(xiàn)有研究?jī)H僅考慮兩兩指標(biāo)間的信息重疊的降低而不考慮評(píng)級(jí)指標(biāo)間整體信息重疊程度的不足。(3)為了確定小企業(yè)信用評(píng)級(jí)指標(biāo)的權(quán)重,提出了一種基于雙重信用違約風(fēng)險(xiǎn)識(shí)別的信用評(píng)級(jí)指標(biāo)賦權(quán)方法。首先,該方法根據(jù)信用評(píng)級(jí)指標(biāo)識(shí)別信用違約與否提供的信息量(信息增益)越大,該信用評(píng)級(jí)指標(biāo)識(shí)別違約與否的能力越大,該指標(biāo)的權(quán)重理應(yīng)越大的信息增益賦權(quán)思路,實(shí)現(xiàn)信用評(píng)級(jí)指標(biāo)的第一重賦權(quán)。之后,鑒于信息敏感性能夠反映信用評(píng)級(jí)指標(biāo)識(shí)別信用違約綜合風(fēng)險(xiǎn)能力的大小,根據(jù)信用評(píng)級(jí)指標(biāo)的信息敏感性越大、該信用評(píng)級(jí)指標(biāo)信用違約綜合風(fēng)險(xiǎn)識(shí)別的能力也越大、該指標(biāo)的權(quán)重理應(yīng)也越大的信息敏感性賦權(quán)思路,實(shí)現(xiàn)信用評(píng)級(jí)指標(biāo)的第二重賦權(quán)。第一重賦權(quán)雖然利用了違約與否所蘊(yùn)含的信用風(fēng)險(xiǎn)的價(jià)值,但違約與否畢竟不能精細(xì)地刻畫(huà)信用風(fēng)險(xiǎn)。第二重賦權(quán)雖然體現(xiàn)了信用評(píng)級(jí)指標(biāo)識(shí)別信用違約綜合風(fēng)險(xiǎn)的能力,但卻沒(méi)有有效利用違約與否這個(gè)寶貴的反映信用風(fēng)險(xiǎn)的指標(biāo)。有鑒于此,最后通過(guò)乘法集成歸一法對(duì)上述兩種賦權(quán)方法確定的信用評(píng)級(jí)指標(biāo)的權(quán)重進(jìn)行了綜合,實(shí)現(xiàn)了兩種賦權(quán)方法的取長(zhǎng)補(bǔ)短,克服了現(xiàn)有研究在對(duì)信用評(píng)級(jí)指標(biāo)賦權(quán)時(shí)僅考慮對(duì)違約狀態(tài)的影響程度或不考慮對(duì)違約狀態(tài)的影響程度的不足。同時(shí),基于信用評(píng)級(jí)指標(biāo)的遴選和賦權(quán)確定了小企業(yè)的信用綜合得分,并據(jù)此劃分了不同信用等級(jí)對(duì)應(yīng)信用得分區(qū)間,進(jìn)而實(shí)現(xiàn)了小企業(yè)信用等級(jí)的確定。(4)為了檢驗(yàn)小企業(yè)信用評(píng)級(jí)指標(biāo)體系的合理性,根據(jù)指標(biāo)體系對(duì)違約與否判別的準(zhǔn)確率越高,指標(biāo)體系整體上識(shí)別基本信用風(fēng)險(xiǎn)的能力越大的思路,提出了基于貝葉斯判別的信用評(píng)級(jí)指標(biāo)體系合理性檢驗(yàn)?zāi)Ｐ?克服了現(xiàn)有研究完全不考慮指標(biāo)在單位及量綱上的差異及錯(cuò)誤使用多重決定系數(shù)的不足。此外,為了檢驗(yàn)小企業(yè)信用評(píng)級(jí)指標(biāo)賦權(quán)的合理性,根據(jù)全部樣本企業(yè)間信用綜合得分與實(shí)際違約損失率間的不一致,提出了基于信用非一致性比率的信用評(píng)級(jí)指標(biāo)賦權(quán)合理性檢驗(yàn)方法,克服了現(xiàn)有研究缺乏此類(lèi)客觀檢驗(yàn)方法的不足。并在實(shí)證研究中,從對(duì)違約狀態(tài)判別的準(zhǔn)確率和信息重疊程度兩個(gè)不同角度,將本文構(gòu)建的小企業(yè)信用評(píng)級(jí)指標(biāo)體系與現(xiàn)有研究的兩套小企業(yè)信用評(píng)級(jí)指標(biāo)體系進(jìn)行了定量對(duì)比,進(jìn)一步驗(yàn)證了利用本文方法構(gòu)建信用評(píng)級(jí)指標(biāo)體系的合理性。
[Abstract]:As an important part of the national economic and social development of small enterprises, credit rating results directly affect its financing channels, and the possibility of cost. Even, the credit rating results will affect the purchase contract is signed for small businesses, and to participate in the bidding and government procurement bidding for many years. Especially for small business loans and expensive loan difficult problem has not been solved effectively. To solve this problem is difficult, but because of the many commercial banks and other financial institutions have credit rating results of the loan business customers into the credit approval process, obviously if reasonably on the small business credit rating will help loan and your loan is difficult to solve the problem. In addition, the credit rating is also a matter of national security of the financial system. Therefore, it is important to study development of small enterprise credit rating of small enterprises. The essence of the credit rating industry is to evaluate the credit risk. In order to reflect the relative size of the popular image of enterprise credit risk, usually will rank the credit risk of the enterprise. And the weighted index system of credit rating and credit rating is the basis of credit risk evaluation. The credit rating index system by credit rating index selection, through the recognition of credit risk elimination ability and weak implementation of the credit rating index reflects the high degree of overlap of audition information; credit rating index weight refers to the weight to determine the credit rating index. This paper mainly focused on small business credit risk rating and the rationality of the test, the main work is as follows: (1) to the credit rating index the selection of the credit risk recognition ability, puts forward a selection method of credit risk recognition ability of the credit rating index. Based on the first letter With the value of rating for breach and non breach two groups, according to the relative gap between a credit rating index value of the variance between groups and within group variation is bigger, the credit rating index for breach of contract and whether the influence is more significant, the credit rating index should be retained more F test ideas, excluding significant the effect of credit default and not a credit rating index, to ensure that the retained credit rating index have a certain influence on the credit default. Then, by principal components accounted for the screen credit rating index set of product information, and the proportion of each component is reserved for the credit rating index and partial derivative said to be more sensitive, screen credit rating index set information by the index size change, called index information sensitivity. On this basis, according to the information sensitivity of credit rating index is the index. The ability to explain the credit risk information to screen the credit rating index set contains a larger capacity of the identification index of credit default risk is more comprehensive, more sensitive information ideas of the index should be retained, further eliminate credit default risk recognition ability of the comprehensive credit rating index. This method overcomes the shortcomings of existing research only rely on the lack of credit rating index of default or not the influence of selection of large index of credit risk identification ability, and overcomes the problem of principal components method selection index only based on the deficiency of single factor load index cannot reasonable screening index. (2) in order to reduce the degree of information overlap between each of the credit rating index, is proposed a method of selecting information overlapping of the credit rating index based on double elimination. Firstly, the method to determine a set of credit through a set of credit rating index morbid index The overall rating index information overlap degree, and with a rating index were eliminated after the group credit rating index index to reduce the magnitude of morbid information to determine the degree of overlap index and other indexes between the index set, referred to as information overlap degree of the credit rating index. Through eliminating a high degree of overlap of information index, fast to reduce the implementation of credit rating index between the overall information overlap degree. Then, in order to avoid the whole information index system of low degree of overlap and part of the overlapped information index is high, further eliminating a high degree of correlation as the two indicators in the information sensitivity index. The existing small studies considered only 22 index information overlap between the reduced and not considering the lack of information between the overall rating index of the degree of overlap to overcome this method. (3) to determine the weight of the credit rating index of small enterprises, propose a method based on double Credit default risk recognition credit rating index weighting method. First, according to the credit rating index of credit default or identification information (information gain) greater recognition ability of the credit rating index of default or not is greater, the weight of the index should be more information gain weighting ideas, realization of credit the first heavy weight rating index. Then, in view of information sensitivity can reflect the credit rating index of credit default risk identification capability, according to the information sensitivity of credit rating index is bigger, the credit rating index of credit default risk identification is greater, the weight of the index should be more information sensitivity weighting ideas the credit rating index, the second weighting. The first weighting although use default or not contained in the value of credit risk, but the default or not after all Not fine description of credit risk. The second weighting reflects the credit rating index of credit default risk recognition ability, but there is no effective use of this valuable default or not reflect the credit risk indicators. In view of this, the integrated weight multiplication normalization method for the two kinds of weighting method to determine the credit rating index of overall, realized two kinds of weighting methods complement each other, to overcome the existing research on the weight of the credit rating index when only considering the influence degree of the default state or not considering the insufficient degree of influence on the default state. At the same time, the credit rating index selection and weight to determine the comprehensive score based on small business credit, and accordingly division of the different credit rating corresponds to the credit score interval, thus confirming the credit rating of small enterprises. (4) in order to test the small enterprise credit rating means The rationality of index system, according to the index system of breach of contract and the accuracy of the discriminant is higher, the overall index system of thinking ability to identify the basic credit risk more, proposed Bayesian credit rating index system to verify the rationality of model based on the existing research, to overcome the lack of index without considering the differences in unit and dimension the use of multiple coefficient of determination and error. In addition, in order to test the rationality of weighted credit rating index of small enterprises, according to the comprehensive score of all samples between the enterprise and the actual credit default loss rate is not consistent between the proposed reasonable test method of weighting non consistency ratio of credit based on credit rating index, overcomes the shortcomings of the existing lack of such the objective test method. And in the empirical study, from the default state estimation accuracy and information overlap of two different angles, the The small business credit rating index system is quantitatively compared with the existing two sets of small business credit rating index system, further validates the rationality of using this method to build credit rating index system.

【學(xué)位授予單位】：大連理工大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：F276.3;F832.4
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本文編號(hào)：1696743