本文選題：金融不良貸款 + 巴塞爾新資本協(xié)議�。� 參考：《北京交通大學》2012年博士論文

【摘要】：金融體系中,不良貸款的產(chǎn)生一直對金融機構(gòu)構(gòu)成著嚴重威脅,甚至是一個國家的經(jīng)濟。設(shè)立資產(chǎn)管理公司處置不良貸款是世界各國一項通行且行之有效的做法。源于我國銀行金融機構(gòu)經(jīng)營模式,如何防范金融不良貸款的發(fā)生及發(fā)生后的損失管理問題研究成為是我國金融體系最核心的研究內(nèi)容之一。 特別是在我國開展實施巴塞爾Ⅱ新資本協(xié)議的今天,深入研究不良貸款的處置和損失問題對我國銀行信用風險管理水平的提升及開發(fā)銀行內(nèi)部評級系統(tǒng)中的核心參數(shù)—違約損失率LGD都具有重大的現(xiàn)實意義。 由于我國特殊的金融發(fā)展歷程,我國銀行業(yè)的違約不良貸款在2006年前基本劃撥或出售給了四大資產(chǎn)管理公司。在新的金融環(huán)境下,根據(jù)國務(wù)院及財政部對資產(chǎn)管理公司新的發(fā)展定位,我國四大資產(chǎn)管理公司將不會結(jié)業(yè)清算,回歸母體行,而是仍將以不良貸款處置為主業(yè)發(fā)展金融控股集團。因此,在未來可預見的時間內(nèi),資產(chǎn)管理公司仍將是我國金融不良貸款處置管理的主要力量。一方面,由于歷史軌跡的改變,我國金融資產(chǎn)管理公司亟需通過對歷史數(shù)據(jù)的采集、整理和挖掘,探索一條提升不良貸款處置管理水平的新途徑；另一方面,由于我國金融不良貸款對銀行金融機構(gòu)的重大影響,研究不良貸款的特征及回收率估計模式,對我國新資本協(xié)議的實施不可或缺。 違約損失數(shù)據(jù)庫的建設(shè)在我國一直是個空白,利用大規(guī)模歷史數(shù)據(jù)及其挖掘成果進行不良貸款處置管理的國內(nèi)外研究和實證也很少。同時,與銀行業(yè)、學術(shù)界和各信用評級機構(gòu)所關(guān)注違約率的研究相比,由于數(shù)據(jù)缺乏、影響因素眾多和形成原因復雜多樣等問題,對違約損失率(LGD)國外學者也是從90年代中后期才開始關(guān)注,而國內(nèi)的研究起步更晚,大部分還處于定性的描述,成熟的定量研究及模型開發(fā)幾乎還是空白。由于信用環(huán)境和經(jīng)營模式的差異,符合中國國情違約損失數(shù)據(jù)庫的開發(fā)、數(shù)據(jù)的挖掘利用、違約損失率模型的開發(fā)研究都是我國金融業(yè)和學界亟需填補和完善的研究空白。由于違約損失率和回收率的互補關(guān)系,本文將交互使用這兩個概念。 本文嘗試從資產(chǎn)管理公司的視角出發(fā),結(jié)合新資本協(xié)議對金融風險管理的要求,通過建立我國大型的金融不良貸款損失數(shù)據(jù)庫,在海量的不良貸款回收數(shù)據(jù)的基礎(chǔ)上,總結(jié)歸納了我國不良貸款的特征和適合我國國情的違約損失率模型開發(fā)方法,并形成系統(tǒng)軟件進行了實證。開拓性地研究了一套利用數(shù)據(jù)、挖掘成果、IT技術(shù)來整體提升資產(chǎn)管理公司不良貸款處置和損失管理的方法。具體結(jié)構(gòu)如下： 第二章綜述和總結(jié)了不良貸款發(fā)生及處置清收的國內(nèi)外模式及處置方法； 第三章對不良貸款處置核心定價問題開展了理論研究。從金融資產(chǎn)定價理論出發(fā),探討了信用風險定價問題和圍繞信用資產(chǎn)違約損失率計量的各種方法。追根溯源實現(xiàn)了不良貸款違約損失定價問題從理論到實踐的全面梳理和研究； 第四章在全面設(shè)計我國金融不良貸款數(shù)據(jù)庫和數(shù)據(jù)準備的基礎(chǔ)上,本文分析了影響我國不良貸款回收率水平的主要因素：宏觀因素、行業(yè)地區(qū)因素、債務(wù)人因素、債項因素等； 第五章總結(jié)了適合我國國情的不良貸款定價模型框架和回收率估計模型并對主要模型變量的貢獻度進行了分析； 第六章以資產(chǎn)管理公司為例,給出了在實際研究成果基礎(chǔ)上所構(gòu)建的我國第一個基于計算機技術(shù)的、從數(shù)據(jù)管理到過程風險管理到處置定價管理的實際管理框架。其中包括數(shù)據(jù)采集和數(shù)據(jù)處理,不良貸款處置方式的選擇、不良貸款的定價及風險監(jiān)測。應(yīng)用實踐表明,本研究的成果,不僅大大提高了資產(chǎn)管理公司的工作效率,而且也提高了不良貸款的回收率。 第七章總結(jié)了全文的研究成果,并結(jié)合我國國情給出相應(yīng)的政策建議。 本文的創(chuàng)新點在于： (1)通過中國的海量不良貸款違約損失數(shù)據(jù),實證總結(jié)了影響我國不良貸款回收率的基本因素：宏觀經(jīng)濟因素、行業(yè)地區(qū)因素、債務(wù)人因素和債項因素。影響因素的得出為中國不良貸款的定價模型建設(shè)奠定了理論基礎(chǔ)； (2)總結(jié)了適合我國國情的不良貸款回收率的建模方法應(yīng)根據(jù)我國不良貸款的違約損失率U型分布的特征,通過先判別后回歸的方式來進行回收率的計量工作,同時為提高模型實用性,應(yīng)采取單戶模型和打包模型結(jié)合的方式。同時模型建設(shè)中應(yīng)該使用分布模型來更好的認識我國不良貸款的分布特征和影響因素； (3)研究總結(jié)了我國金融不良貸款違約損失數(shù)據(jù)庫基本設(shè)計要素,包括：業(yè)務(wù)變量的內(nèi)容,業(yè)務(wù)邏輯結(jié)構(gòu),數(shù)據(jù)采集清洗的有效機制。提出了我國金融環(huán)境下建立違約損失數(shù)據(jù)共享機制的必要性和重要意義,為今后我國金融不良貸款定價、管理及風險研究工作奠定了良好的研究基礎(chǔ)； (4)通過實證研究,提出只有通過基礎(chǔ)違約損失數(shù)據(jù)庫的建設(shè),在進行大量的數(shù)據(jù)特征和損失率影響因素挖掘的前提下,構(gòu)建適合中國國情的模型才能有效的實現(xiàn)金融不良貸款的處置管理。同時為我國金融不良貸款處置管理及風險控制在整體決策層面上提供了實際案例和參考模式。
[Abstract]:In the financial system, the production of non-performing loans has been a serious threat to the financial institutions and even the economy of a country. Setting up a Asset Management Co to dispose of bad loans is a common and effective practice in the world. It is based on the management mode of the banking institutions in China and how to prevent the occurrence and occurrence of the financial non-performing loans. The research on loss management has become one of the core research contents of China's financial system.
Especially in the implementation of the implementation of the new Basel II capital agreement in China, it is of great practical significance to study the problem of the disposal and loss of non-performing loans for the improvement of the bank credit risk management level and the core parameter of the internal rating system of the bank - the default loss rate LGD.
Because of our country's special financial development course, the non-performing loan of the banking industry of our country basically allocated or sold to four Asset Management Co before 2006. Under the new financial environment, according to the new development orientation of the Asset Management Co, the State Council and the Ministry of finance will not settle the liquidation and return to the parent of the four Asset Management Co. Therefore, in the foreseeable future, Asset Management Co will still be the main force for the management of our financial non-performing loans in the foreseeable future. On the one hand, because of the change of the historical track, the financial Asset Management Co of our country needs to collect and collate the historical data. And explore a new way to improve the management level of non-performing loans. On the other hand, the study of the characteristics of non-performing loans and the estimation model of the recovery rate due to the significant impact of our non-performing loans on bank financial institutions can not be or lack of the implementation of the new capital agreement in China.
The construction of the default loss database has been a blank in our country. There are few domestic and international research and empirical research on the management of non-performing loans with large-scale historical data and their mining results. At the same time, compared with the research of the banking, academic and credit rating agencies, there are many factors affecting the default rate due to the lack of data. There are many problems in the formation of complex reasons. The foreign scholars of the default loss rate (LGD) have begun to pay attention to the late 90s, while the domestic research started later, most of them are still in the qualitative description. The mature quantitative research and model development are almost still blank. Due to the difference of the credit environment and management mode, it conforms to the breach of China's national conditions. The development of the loss database, the data mining and utilization, the development and research of the default loss rate model are all the research gaps that the financial industry and the academic community need to fill and perfect. The two concepts will be used in this paper because of the complementary relationship between the loss rate of default and the recovery rate.
From the perspective of the Asset Management Co, this paper tries to combine the requirements of the new capital agreement to the management of financial risk, and through the establishment of a large database for the loss of financial non-performing loans in China, and on the basis of a large amount of data on the recovery of non-performing loans, sums up the characteristics of the non-performing loans in China and the loss rate model suitable for the national conditions of our country. The method of development and the formation of system software have been demonstrated. A set of methods to improve the disposal and loss management of non-performing loans of Asset Management Co by using data, mining results and IT technology is explored. The concrete structure is as follows:
The second chapter summarizes and summarizes the domestic and international modes and disposal methods of the occurrence and disposal of non-performing loans.
The third chapter carries out a theoretical study on the core pricing of non-performing loans. Starting from the theory of financial asset pricing, this paper discusses the pricing of credit risk and the various methods of measuring the rate of default loss around the credit assets.
The fourth chapter, based on the comprehensive design of the database and data preparation of our country's non-performing loans, analyzes the main factors that affect the recovery of non-performing loans in China, such as macro factors, industry regional factors, debtor factors and debt factors.
The fifth chapter summarizes the pricing model framework and the rate of return model of the non-performing loans suitable for China's national conditions, and analyzes the contribution of the main model variables.
The sixth chapter, taking the Asset Management Co as an example, gives the actual management framework of China's first computer technology based on the actual research results, from data management to process risk management to disposal pricing management, including data collection and data processing, the choice of non-performing loans, and the determination of non-performing loans. Price and risk monitoring. Application practice shows that the results of this study not only greatly improve the efficiency of the Asset Management Co, but also improve the recovery rate of non-performing loans.
The seventh chapter summarizes the research results and gives corresponding policy recommendations in light of China's national conditions.
The innovation of this article lies in:
(1) through the data of large amount of non-performing loans in China, this paper empirically summarizes the basic factors that affect the recovery rate of non-performing loans in China: macroeconomic factors, industry regional factors, debtor factors and debt factors.
(2) the modeling method for the recovery rate of non-performing loans suitable for the national conditions of our country should be based on the characteristics of the U distribution of the default loss rate of the non-performing loans in China. The recovery rate should be measured by the first discriminant and post regression method. At the same time, in order to improve the practicability of the model, the single household model and the packaging model should be combined. The distribution model should be used to better understand the distribution characteristics and influencing factors of non-performing loans in China.
(3) the study summarizes the basic design elements of the default loss database of our country's NPLs, including the content of the business variables, the business logic structure, the effective mechanism of the data collection and cleaning, and puts forward the necessity and significance of establishing the data sharing mechanism of default loss under the financial environment of our country, and the pricing of our country's financial non-performing loans in the future. Management and risk research has laid a good foundation for research.
(4) through the empirical study, it is proposed that only through the construction of the database for the loss of basic breach of contract, under the premise that a large number of data features and the factors affecting the loss rate are excavated, a model suitable for China's national conditions can be constructed to effectively realize the disposal and management of the financial non-performing loans. At the same time, the management and risk control of the non-performing loans of China's financial system and the risk control are also proposed. It provides practical cases and reference models at the overall decision-making level.

【學位授予單位】：北京交通大學
【學位級別】：博士
【學位授予年份】：2012
【分類號】：F832.4;F224

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