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基于logistic回歸的違約概率模型的建立及分析

發(fā)布時(shí)間:2018-07-15 09:41
【摘要】:由于我國(guó)銀行的商業(yè)化改革剛剛起步,法律、法規(guī)、數(shù)據(jù)和管理方法等還很不完善,這些都是產(chǎn)生金融風(fēng)險(xiǎn)的因素,其中信用風(fēng)險(xiǎn)是我國(guó)商業(yè)銀行面臨的最主要風(fēng)險(xiǎn).我國(guó)加入WTO后,金融市場(chǎng)進(jìn)一步對(duì)外開放,當(dāng)前我國(guó)商業(yè)銀行面臨的主要任務(wù)是如何采取積極有效地措施與國(guó)際銀行業(yè)接軌,這些任務(wù)首當(dāng)其沖的是如何管理信用風(fēng)險(xiǎn).《新巴塞爾協(xié)議》的實(shí)施要求銀行建立完整的內(nèi)部信用評(píng)級(jí)體系,對(duì)客戶進(jìn)行信用評(píng)級(jí),量化貸款客戶的信用風(fēng)險(xiǎn).本文通過(guò)建立違約概率模型來(lái)預(yù)測(cè)客戶違約情況,進(jìn)一步加強(qiáng)商業(yè)銀行信用風(fēng)險(xiǎn)的管理. 本文中的違約概率模型是基于Logistic回歸分析。首先,采用逐步向后選擇法進(jìn)行模型指標(biāo)的篩選。其次,通過(guò)Logistic回歸得到違約概率模型.最后,我們利用Kolmogorov-Smirnov檢驗(yàn)(簡(jiǎn)稱K-S檢驗(yàn))與ROC曲線來(lái)檢驗(yàn)?zāi)P蛥^(qū)分違約客戶的能力和準(zhǔn)確度,最后確定違約概率模型.并且通過(guò)某商業(yè)銀行的真實(shí)數(shù)據(jù)來(lái)對(duì)我們所建立的模型進(jìn)行實(shí)證分析研究,得出結(jié)論.
[Abstract]:As the commercial reform of Chinese banks has just started, the laws, regulations, data and management methods are still very imperfect, these are the factors that produce financial risks, among which the credit risk is the most important risk faced by commercial banks in our country. After China's entry into WTO, the financial market is further opened to the outside world. At present, the main task facing our commercial banks is how to take active and effective measures to connect with the international banking industry. The implementation of Basel II requires banks to establish a complete internal credit rating system, credit rating for customers, and quantify the credit risk of loan customers. In this paper, the default probability model is established to predict the customer default and further strengthen the credit risk management of commercial banks. The probability model of default in this paper is based on Logistic regression analysis. First, the stepwise backward selection method is used to screen the model indexes. Secondly, the probability model of default is obtained by logistic regression. Finally, we use Kolmogorov-Smirnov test (K-S test for short) and ROC curve to test the model to distinguish the ability and accuracy of default customers, and finally determine the default probability model. And through the real data of a commercial bank to make an empirical analysis of our model, draw a conclusion.
【學(xué)位授予單位】:山東大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2012
【分類號(hào)】:F224;F832.33

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 宋冬梅;沈友娣;;運(yùn)用Logistic模型評(píng)價(jià)上市公司信用風(fēng)險(xiǎn)[J];財(cái)會(huì)月刊;2008年05期

2 甄士龍;黎艷;;用Logistic模型估計(jì)企業(yè)的違約概率[J];廣西金融研究;2008年11期

3 馬永波;晏國(guó)祥;;內(nèi)部評(píng)級(jí)違約概率度量模型的演進(jìn)與啟示[J];石家莊經(jīng)濟(jì)學(xué)院學(xué)報(bào);2006年02期

4 蔡海燕;;商業(yè)銀行信用風(fēng)險(xiǎn)管理模型應(yīng)用探討[J];經(jīng)濟(jì)師;2008年07期

5 林林;徐翔宇;;信用風(fēng)險(xiǎn)模型綜述及對(duì)我國(guó)借鑒[J];金融經(jīng)濟(jì);2009年02期

6 張燃;用Logit模型預(yù)測(cè)銀行客戶的違約概率[J];金融教學(xué)與研究;2005年04期

7 李越;;現(xiàn)代信用風(fēng)險(xiǎn)度量方法與模型述評(píng)[J];遼寧經(jīng)濟(jì);2008年04期

8 趙中華;劉梅;;商業(yè)銀行信用風(fēng)險(xiǎn)的VAR度量分析[J];商場(chǎng)現(xiàn)代化;2008年13期

9 柏藝益;;Logistic模型在評(píng)價(jià)上市公司信用風(fēng)險(xiǎn)中的應(yīng)用研究[J];時(shí)代經(jīng)貿(mào)(中旬刊);2008年S6期

10 管七海,馮宗憲;信用違約概率測(cè)度研究:文獻(xiàn)綜述與比較[J];世界經(jīng)濟(jì);2004年11期

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