本文選題：KMV模型 + COPULA函數(shù)　； 參考：《北京郵電大學(xué)》2013年博士論文

【摘要】：信用風(fēng)險(xiǎn)由交易對(duì)手違約所造成的既有損失,是金融市場(chǎng)中最古老、最重要的風(fēng)險(xiǎn)形式之一,也是中國現(xiàn)代商業(yè)銀行面臨的主要風(fēng)險(xiǎn)。通常上認(rèn)為,貸款是其最主要、最明顯的風(fēng)險(xiǎn)來源。實(shí)際上,它卻廣泛的存在于銀行的所有業(yè)務(wù)之中,包括交易賬戶、表內(nèi)外業(yè)務(wù)等。隨著金融市場(chǎng)的不斷發(fā)展,在創(chuàng)新、利用金融衍生工具進(jìn)行避險(xiǎn)的同時(shí),也會(huì)引發(fā)商業(yè)銀行的信用風(fēng)險(xiǎn),如承兌、金融期貨、債券、承諾和擔(dān)保等。作為商業(yè)銀行經(jīng)營活動(dòng)中最主要的風(fēng)險(xiǎn)之一,信用風(fēng)險(xiǎn)直接影響著現(xiàn)代社會(huì)經(jīng)濟(jì)生活的各個(gè)方面,也影響著一個(gè)國家的宏觀經(jīng)濟(jì)決策和經(jīng)濟(jì)發(fā)展,甚至影響到整個(gè)全球經(jīng)濟(jì)的穩(wěn)定與協(xié)調(diào)發(fā)展。商業(yè)銀行作為信用風(fēng)險(xiǎn)的承載體,其信用風(fēng)險(xiǎn)管理體系的完善與否直接關(guān)系到商業(yè)銀行的經(jīng)營能否成功。 中國大型商業(yè)銀行于2010年底開始實(shí)施新巴塞爾資本協(xié)議。作為巴塞爾委員會(huì)的成員之一,嚴(yán)格執(zhí)行新巴塞爾協(xié)議,有助于提高抵御金融危機(jī)的能力,也是中國銀行業(yè)融入金融全球化,參與國際競(jìng)爭(zhēng)的必然要求。在巴塞爾新資本協(xié)議逐步全球化實(shí)施的今天,信用風(fēng)險(xiǎn)管理作為銀行業(yè)自身管理的重要組成部分,將成為中國銀行業(yè)資本管理中的重中之重。 本論文的研究工作主要是基于KMV模型在商業(yè)銀行信用風(fēng)險(xiǎn)管理中的測(cè)算研究完成的。本文在分析KMV模型的基本思想、理論架構(gòu)、模型計(jì)量步驟的基礎(chǔ)上,討論KMV模型的在實(shí)際應(yīng)用中的測(cè)算情況以及研究KMV模型在中國的適用性,并利用KMV模型定量分析的研究方法,對(duì)上市公司ST公司和非ST公司的違約率進(jìn)行測(cè)算,同時(shí)結(jié)合Copula函數(shù)討論聯(lián)合違約概率,找出了較為符合中國國情的結(jié)合了Copula函數(shù)的KMV模型,最后,對(duì)KMV模型在中國銀行業(yè)中的風(fēng)險(xiǎn)測(cè)算和應(yīng)用提出改進(jìn)措施。本文相關(guān)研究成果主要概括為三點(diǎn)： 第一,本文以KMV模型作為切入點(diǎn),從對(duì)KMV模型的理論基礎(chǔ)、參數(shù)設(shè)計(jì)、計(jì)算方法等基本點(diǎn)著手進(jìn)行了詳盡的討論,把KMV模型從紛繁復(fù)雜的理論框架中梳理出來,討論KMV模型在測(cè)度中國商業(yè)銀行信用風(fēng)險(xiǎn)時(shí)的實(shí)際測(cè)算過程,與過程中的局限性和改進(jìn)方法,形成了較為規(guī)范、具體和實(shí)用性的研究成果,為中國商業(yè)銀行提高現(xiàn)有的風(fēng)險(xiǎn)管理水平,逐步引入國際上先進(jìn)的風(fēng)險(xiǎn)管理方法提供了具有實(shí)際意義的參考。 第二,由于組合信用風(fēng)險(xiǎn)的”厚尾”特征,為了提高商業(yè)銀行中組合信用風(fēng)險(xiǎn)測(cè)算的準(zhǔn)確率,本文構(gòu)建了結(jié)合Copula函數(shù)的KMV模型。針對(duì)KMV模型的不足,將不同的Copula函數(shù)與KMV模型相結(jié)合,并采用”平方歐式距離”的方法進(jìn)行模型評(píng)價(jià)。 第三,利用中國上市公司ST公司與非ST公司的相關(guān)數(shù)據(jù)進(jìn)行測(cè)算,說明KMV模型能夠較好的測(cè)度我國上市公司的信用風(fēng)險(xiǎn)狀況。針對(duì)KMV模型自身的局限性,利用中國資本市場(chǎng)上市公司相關(guān)數(shù)據(jù),通過結(jié)合了copula函數(shù)后改進(jìn)了的KMV模型測(cè)算聯(lián)合違約概率,并通過“距離法”評(píng)價(jià)模型,找出最符合實(shí)際情況的改進(jìn)后的KMV模型,使KMV模型更適用于測(cè)算中國商業(yè)銀行組合信用風(fēng)險(xiǎn)。
[Abstract]:It is one of the oldest and most important forms of risk in the financial market. It is also the main risk faced by modern commercial banks in China. Generally speaking, loan is the most important and most obvious source of risk. In fact, it exists widely in all the business of the bank. With the continuous development of the financial market, the credit risks of commercial banks, such as acceptance, financial futures, bonds, commitments and guarantees, are also caused by the continuous development of financial markets and the use of financial derivatives to avoid risks, such as acceptance, financial futures, bonds, commitments and guarantees. As one of the most important risks in commercial banks' business activities, credit risk affects directly All aspects of the modern social and economic life also affect the macroeconomic decision-making and economic development of a country, and even the stability and coordinated development of the whole global economy. As the carrier of credit risk, the perfection of the credit risk management system of commercial banks is directly related to the success of commercial banks' operation.
China's large commercial banks began to implement the new Basel capital agreement at the end of 2010. As one of the members of the Basel Committee, the strict implementation of the new Basel agreement will help to improve the ability to resist the financial crisis. It is also the inevitable requirement for China's banking industry to integrate into the financial globalization and participate in international competition. In Basel new capital agreement gradually Today, with the implementation of globalization, credit risk management, as an important part of the banking industry's own management, will become the top priority in the capital management of China's banking industry.
The research work of this paper is based on the calculation of the KMV model in the credit risk management of commercial banks. Based on the analysis of the basic ideas, the theoretical framework and the steps of the model measurement of the KMV model, this paper discusses the calculation of the KMV model in the practical application and the applicability of the KMV model in China, and uses KMV The method of model quantitative analysis is used to calculate the default rate of ST and non ST companies in listed companies, and to discuss the joint default probability combined with Copula function, and find out the KMV model which is in line with the national conditions of China and combine the Copula function. Finally, the improvement measures are put forward to the risk calculation and application of the KMV model in the Chinese banking industry. The relevant research results of this paper are summarized as three points.
First, this paper takes the KMV model as a breakthrough point, discusses the basic points of the theoretical basis, parameter design and calculation method of the KMV model, and combs the KMV model from the complicated and complicated theoretical framework, and discusses the actual calculation process of the KMV model in measuring the credit risk of the commercial bank of China, and the limitation in the process. It has formed a more standardized, specific and practical research result, which provides a practical reference for Chinese commercial banks to improve the existing risk management level and gradually introduce advanced international risk management methods.
Second, due to the "thick tail" feature of combined credit risk, in order to improve the accuracy of the combined credit risk calculation in commercial banks, this paper constructs a KMV model combining the Copula function. Aiming at the shortage of the KMV model, the different Copula functions are combined with the KMV model, and the model is evaluated with the "square Euclidean distance" method.
Third, using the related data of ST company of Chinese listed company and non ST company, it shows that the KMV model can measure the credit risk status of the listed companies in China better. According to the limitations of the KMV model itself, it uses the related data of the listed companies in China capital market, and calculates the improved KMV model by combining the copula function. The joint default probability is combined with the "distance method" evaluation model to find the improved KMV model which is most consistent with the actual situation, so that the KMV model is more suitable for the calculation of the combined credit risk of China's commercial banks.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2013
【分類號(hào)】：F224;F832.33

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