發(fā)布時(shí)間：2018-01-30 08:07

  本文關(guān)鍵詞： 商業(yè)銀行 房地產(chǎn)信貸 違約率 信貸風(fēng)險(xiǎn) 防范　出處：《山西財(cái)經(jīng)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：信貸資產(chǎn)占了銀行總資產(chǎn)的很大一部分比例,而這卻使得銀行內(nèi)部積聚了大量的風(fēng)險(xiǎn),所以信貸風(fēng)險(xiǎn)的管理不容忽視。而近年來(lái),隨著“互聯(lián)網(wǎng)+金融”的快速發(fā)展,我國(guó)整個(gè)金融環(huán)境發(fā)生了較大的變化,商業(yè)銀行的信貸風(fēng)險(xiǎn)程度也不可避免地日益增加。再加上,我國(guó)商業(yè)銀行與房地產(chǎn)市場(chǎng)密切相關(guān),而房地產(chǎn)市場(chǎng)資金較密集且鏈條較長(zhǎng),因而房地產(chǎn)市場(chǎng)的微小變化直接影響到銀行信貸的風(fēng)險(xiǎn)程度。所以,研究商業(yè)銀行房地產(chǎn)信貸風(fēng)險(xiǎn)的有效管理并及時(shí)予以防范有著比較重要的意義。本文基于CPV模型,從上市銀行的角度出發(fā),從理論和實(shí)證兩個(gè)角度對(duì)銀行房地產(chǎn)信貸風(fēng)險(xiǎn)的管理以及防范進(jìn)行了研究。理論方面,一是闡述了上市銀行房地產(chǎn)信貸風(fēng)險(xiǎn)的理論內(nèi)容。具體介紹了房地產(chǎn)信貸風(fēng)險(xiǎn)的特點(diǎn)、成因以及現(xiàn)狀和問(wèn)題;二是總結(jié)了商業(yè)銀行信貸風(fēng)險(xiǎn)度量的理論方法。在回顧信貸度量方法定性到定量質(zhì)的進(jìn)步的基礎(chǔ)上,對(duì)比分析了KMV、CR+、CM以及CPV模型這四種現(xiàn)代風(fēng)險(xiǎn)度量方法,得出了利用CPV模型進(jìn)行信貸風(fēng)險(xiǎn)度量的結(jié)論,為下文的實(shí)證模型奠定了理論基礎(chǔ)。實(shí)證方面,一是選擇變量�；贑PV模型的假設(shè),宏觀經(jīng)濟(jì)系數(shù)選取了宏觀景氣一致指數(shù)、國(guó)房景氣指數(shù)以及中長(zhǎng)期利率三個(gè)變量,違約率用房地產(chǎn)不良貸款率來(lái)代替;二是建立模型。構(gòu)建了我國(guó)上市銀行信貸風(fēng)險(xiǎn)違約率與宏觀經(jīng)濟(jì)系數(shù)之間相關(guān)關(guān)系的模型。通過(guò)研究我國(guó)17家上市銀行2009年-2016年各個(gè)季度的公開(kāi)數(shù)據(jù),選擇運(yùn)用STATA軟件進(jìn)行面板回歸模型分析。實(shí)證結(jié)果表明:中長(zhǎng)期利率MLTIR和國(guó)房景氣指數(shù)CERCI與違約率DP呈現(xiàn)正相關(guān),而宏觀經(jīng)濟(jì)景氣指數(shù)MECI與違約率DP呈現(xiàn)負(fù)相關(guān)的關(guān)系。因此,本文以理論和實(shí)證分析為前提條件,從宏、微觀不同的角度來(lái)予以防范。宏觀方面,商業(yè)銀行應(yīng)該以風(fēng)險(xiǎn)最小化為原則,堅(jiān)持審慎經(jīng)營(yíng)管理,同時(shí)遵循市場(chǎng)規(guī)律,適度調(diào)整信貸結(jié)構(gòu)。微觀方面,商業(yè)銀行不僅應(yīng)該加強(qiáng)房產(chǎn)貸款審核機(jī)制,杜絕盲目放貸,而且要進(jìn)行業(yè)務(wù)創(chuàng)新,分散房地產(chǎn)貸款,更要嚴(yán)格進(jìn)行壓力測(cè)試,完善信貸風(fēng)險(xiǎn)管理體系。
[Abstract]:Credit assets account for a large proportion of the total assets of banks, but this makes banks accumulate a large number of risks, so the management of credit risk can not be ignored. And in recent years. With the rapid development of Internet finance, great changes have taken place in the whole financial environment of our country, and the degree of credit risk of commercial banks is inevitably increasing day by day. Commercial banks in China are closely related to the real estate market, and the real estate market is more capital intensive and longer chain, so the small changes in the real estate market directly affect the risk degree of bank credit. It is very important to study the effective management of real estate credit risk in commercial banks and to prevent it in time. Based on the CPV model, this paper starts from the perspective of listed banks. This paper studies the management and prevention of bank real estate credit risk from both theoretical and empirical perspectives. The first is to elaborate the theoretical content of real estate credit risk of listed banks. The characteristics, causes, current situation and problems of real estate credit risk are introduced in detail. The second is to summarize the theoretical methods of credit risk measurement of commercial banks. On the basis of reviewing the qualitative and qualitative progress of credit measurement methods, this paper compares and analyzes KMV / CR. CM and CPV model, four modern risk measurement methods, draw the conclusion that using CPV model to measure credit risk, which lays a theoretical foundation for the following empirical model. Based on the hypothesis of CPV model, the macroeconomic coefficient is divided into three variables: macroeconomic consensus index, national housing boom index and medium and long-term interest rate, and default rate is replaced by non-performing loan rate of real estate. The second is to establish a model. The relationship between credit risk default rate and macroeconomic coefficient of listed banks in China is established. Through the study of 17 listed banks in China from 2009 to 2016 in each quarter of the public. Open the data. The empirical results show that the long-term interest rate (MLTIR) and the national housing boom index (CERCI) are positively correlated with the default rate (DP). The macroeconomic boom index (MECI) is negatively correlated with default rate (DP). Therefore, this paper takes the theoretical and empirical analysis as the prerequisite to prevent it from macro and micro perspectives. Commercial banks should take the risk minimization as the principle, adhere to the prudent management, at the same time follow the law of the market, adjust the credit structure appropriately. Microscopically, commercial banks should not only strengthen the real estate loan audit mechanism. Put an end to blind lending, but also to carry out business innovation, dispersion of real estate loans, but also to strictly carry out stress testing, improve the credit risk management system.
【學(xué)位授予單位】：山西財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F299.23;F832.4

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