本文選題：商業(yè)銀行　切入點：信用風(fēng)險　出處：《湖南大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：宏觀壓力測試作為宏觀審慎管理的重要組成部分，可用于評估宏觀經(jīng)濟(jì)沖擊下金融機(jī)構(gòu)的極端損失，目前已受到全球金融機(jī)構(gòu)和監(jiān)管當(dāng)局的高度重視。目前國內(nèi)對于宏觀壓力測試應(yīng)用研究才剛剛起步。信用風(fēng)險是我國商業(yè)銀行面臨的最主要的風(fēng)險。已有對信用風(fēng)險宏觀壓力測試的研究側(cè)重于評估宏觀經(jīng)濟(jì)沖擊對商業(yè)銀行信用風(fēng)險影響的大小，并未就商業(yè)銀行產(chǎn)生這種變化的差異性的根源進(jìn)行探討。商業(yè)銀行貸款結(jié)構(gòu)是影響信用風(fēng)險的重要因素，如果不考慮結(jié)構(gòu)差異，將不能準(zhǔn)確反映系統(tǒng)性風(fēng)險變化。因此，本文從貸款結(jié)構(gòu)差異的視角對我國商業(yè)銀行進(jìn)行信用風(fēng)險宏觀壓力測試，旨在為商業(yè)銀行進(jìn)行科學(xué)信貸決策、有效防范極端情景下的信用風(fēng)險提供參考。 本文構(gòu)建了基于貸款結(jié)構(gòu)差異的商業(yè)銀行信用風(fēng)險宏觀壓力測試框架，選取2011年不良貸款率最高和最低的兩家國有銀行和兩家股份制商業(yè)銀行作為研究對象。首先，，選取GDP、CPI、一年期貸款基準(zhǔn)利、第三產(chǎn)業(yè)生產(chǎn)總值占比和國房景氣指數(shù)五個宏觀經(jīng)濟(jì)變量，構(gòu)建VAR宏觀經(jīng)濟(jì)情景模型，模擬宏觀經(jīng)濟(jì)因子的內(nèi)在作用機(jī)制。其次，分析銀行貸款結(jié)構(gòu)特征，利用KMV模型測算基于貸款結(jié)構(gòu)差異的銀行違約率作為信用風(fēng)險承壓指標(biāo)，構(gòu)建各銀行的宏觀壓力傳導(dǎo)模型。再次，考慮宏觀因子之間相互作用，對GDP增長大幅下降以及利率大幅上升兩種極端情景下各商業(yè)銀行信用風(fēng)險進(jìn)行壓力測試，并從行業(yè)貸款結(jié)構(gòu)差異和貸款期限結(jié)構(gòu)差異的角度對壓力測試結(jié)果進(jìn)行分析。 實證結(jié)果表明，GDP和利率大幅波動對我國各家商業(yè)銀行信用風(fēng)險的沖擊都很大，在這兩個宏觀經(jīng)濟(jì)因子不同程度的沖擊下違約率均出現(xiàn)了大幅度地增加。其中，在GDP增長率大幅放緩的過程中，制造業(yè)、建筑業(yè)、批發(fā)零售業(yè)、房地產(chǎn)行業(yè)和信息技術(shù)業(yè)這五個行業(yè)貸款總占比越高的商業(yè)銀行，違約率越高。在利率大幅上升的過程中，中長期貸款占比越高的商業(yè)銀行，違約率也越高。最后，本文就加強(qiáng)系統(tǒng)性信用風(fēng)險的管理提出了相關(guān)建議。
[Abstract]:As an important component of macro-prudential management, macro-stress tests can be used to assess the extreme losses of financial institutions under macroeconomic shocks. At present, the global financial institutions and regulatory authorities have attached great importance to it. At present, the research on the application of macro stress testing in China has just started. Credit risk is the most important risk faced by commercial banks in China. The study of risk macro stress test focuses on assessing the impact of macroeconomic shocks on the credit risk of commercial banks. This paper does not discuss the root cause of the difference of the commercial bank. The loan structure of the commercial bank is an important factor affecting the credit risk. If the structural difference is not considered, it will not accurately reflect the change of the systemic risk. From the perspective of loan structure difference, this paper tests the credit risk of Chinese commercial banks in order to provide a reference for commercial banks to make scientific credit decisions and effectively guard against the credit risk in extreme situations. In this paper, the macro stress test framework of credit risk of commercial banks based on the difference of loan structure is constructed, and two state-owned banks and two joint-stock commercial banks with the highest and lowest non-performing loan ratio in 2011 are selected as the research objects. This paper selects five macroeconomic variables, such as VAR CPI, one-year loan benchmark interest, the proportion of tertiary industry GDP and the national housing boom index, to construct the VAR macroeconomic scenario model to simulate the internal mechanism of macroeconomic factors. Secondly, This paper analyzes the characteristics of bank loan structure, uses KMV model to calculate the default rate of bank based on the difference of loan structure as the credit risk bearing index, and constructs the macro pressure conduction model of each bank. Thirdly, considering the interaction between macro factors, The credit risk of commercial banks is tested under the two extreme scenarios of sharp decline in GDP growth and sharp rise in interest rate. The stress test results are analyzed from the perspective of industry loan structure difference and loan maturity structure difference. The empirical results show that the large fluctuations of GDP and interest rate have a great impact on the credit risk of commercial banks in China, and the default rate has increased greatly under the impact of these two macroeconomic factors. In the midst of a sharp slowdown in GDP growth, the higher the share of loans in the manufacturing, construction, wholesale and retail sectors, the real estate sector and the information technology sector, the higher the default rate. The higher the ratio of long-term loans to commercial banks, the higher the default rate. Finally, this paper puts forward some suggestions on how to strengthen the management of systemic credit risk.
【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F832.4;F224

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 盛斌;石靜雅;;厚尾事件度量和壓力測試在我國商業(yè)銀行的應(yīng)用研究[J];財經(jīng)問題研究;2010年02期

2 李江;劉麗平;;中國商業(yè)銀行體系信用風(fēng)險評估——基于宏觀壓力測試的研究[J];當(dāng)代經(jīng)濟(jì)科學(xué);2008年06期

3 湯婷婷;方兆本;;商業(yè)銀行信用風(fēng)險與宏觀經(jīng)濟(jì)——基于壓力測試的研究[J];當(dāng)代經(jīng)濟(jì)科學(xué);2011年04期

4 高同裕;陳元富;;宏觀壓力測試及其在我國應(yīng)用面臨的問題[J];南方金融;2006年07期

5 黃彥琳;鄧可欣;彭建剛;;我國銀行業(yè)信用風(fēng)險宏觀壓力測試研究[J];海南金融;2011年04期

6 巴曙松;朱元倩;;壓力測試在銀行風(fēng)險管理中的應(yīng)用[J];經(jīng)濟(jì)學(xué)家;2010年02期

7 楊曉奇;吳棟;;基于向量誤差修正模型的商業(yè)銀行宏觀壓力測試模型研究[J];金融理論與實踐;2010年08期

8 黃t

本文編號：1599978