本文選題：個(gè)人住房貸款 + 違約風(fēng)險(xiǎn)　； 參考：《青島科技大學(xué)》2017年碩士論文

【摘要】：當(dāng)前,我國房地產(chǎn)市場日益繁榮,特別是近兩年來,房地產(chǎn)行業(yè)又迎來了新一輪的熱潮,樓市的火爆帶來了商業(yè)銀行個(gè)人住房貸款巨大的增量。個(gè)人住房貸款總量高速積累,房價(jià)飛漲、投機(jī)炒房等現(xiàn)象層出不窮,未來的房地產(chǎn)市場價(jià)格中蘊(yùn)藏的諸多不確定因素,都使商業(yè)銀行個(gè)人住房貸款業(yè)務(wù)風(fēng)險(xiǎn)形成更大可能。本文通過研究大量的文獻(xiàn),以HH銀行個(gè)人住房貸款業(yè)務(wù)風(fēng)險(xiǎn)管理為題進(jìn)行研究,以理性違約與被動(dòng)違約理論、信息不對(duì)稱理論、全面風(fēng)險(xiǎn)管理理論等理論為基礎(chǔ),運(yùn)用了文獻(xiàn)分析法、案例分析法和實(shí)證分析等方法,重點(diǎn)對(duì)HH銀行個(gè)人住房貸款業(yè)務(wù)風(fēng)險(xiǎn)管理的現(xiàn)狀及其存在的風(fēng)險(xiǎn)和問題進(jìn)行剖析。在實(shí)證分析部分,從借款人特征、貸款特征、房產(chǎn)特征和外部經(jīng)濟(jì)特征四個(gè)維度構(gòu)架了分析框架,結(jié)合HH銀行的個(gè)人住房貸款業(yè)務(wù)的相關(guān)數(shù)據(jù)情況,選取借款人性別、年齡、戶籍所在地、婚姻狀況、職業(yè)、學(xué)歷、家庭月收入、月還款額、月還款收入比、貸款金額、貸款期限、貸款價(jià)值比、還款方式、房產(chǎn)價(jià)值、住房面積、單位面積房價(jià)和房價(jià)指數(shù)等17個(gè)影響因素作為變量,在對(duì)變量進(jìn)行量化和描述性分析的基礎(chǔ)上,運(yùn)用因子分析法對(duì)各個(gè)變量進(jìn)行“降維”處理,最終提取出了7個(gè)公共因子,采用二分類Logistic回歸分析法,構(gòu)建回歸模型,并給予模型進(jìn)行了回歸分析,從而發(fā)現(xiàn)家庭財(cái)務(wù)負(fù)擔(dān)因子、貸款因子、職業(yè)學(xué)歷和房價(jià)指數(shù)因子對(duì)于貸款風(fēng)險(xiǎn)影響顯著,戶籍因子、婚姻年齡和性別因子對(duì)貸款風(fēng)險(xiǎn)也有一定程度影響,但是,影響程度較前幾個(gè)因子小一些,通過分析各個(gè)變量因子對(duì)個(gè)人住房貸款業(yè)務(wù)風(fēng)險(xiǎn)的影響程度和作用方向,發(fā)現(xiàn)各個(gè)因子之間既相互區(qū)別,但之間也存在著關(guān)聯(lián),但是風(fēng)險(xiǎn)的產(chǎn)生都不是單一因素造成的,而是多個(gè)因子的共同影響,最終導(dǎo)致風(fēng)險(xiǎn)發(fā)生的可能性。因此,銀行在個(gè)人貸款業(yè)務(wù)方面應(yīng)該充分綜合考慮多方面的影響因素,重點(diǎn)關(guān)注家庭財(cái)務(wù)負(fù)擔(dān)、貸款金額期限等重要影響因素的動(dòng)態(tài)變化,更加準(zhǔn)確、充分的考慮各個(gè)影響因素,從而提高信貸的質(zhì)量,改善不良貸款的情況,在此基礎(chǔ)上提出對(duì)策和建議。
[Abstract]:At present, the real estate market of our country is booming day by day, especially in the past two years, the real estate industry has ushered in a new round of upsurge, the boom of the real estate market has brought the huge increment of the commercial bank personal housing loan. The rapid accumulation of personal housing loans, the soaring house prices, speculation and other phenomena emerge in endlessly. Many uncertain factors in the future real estate market price, make commercial banks personal housing loan business risk formation more likely. This paper studies the risk management of personal housing loan business in HH bank, based on the theories of rational default and passive default, information asymmetry theory, comprehensive risk management theory and so on. By using the methods of literature analysis, case analysis and empirical analysis, this paper analyzes the present situation, risks and problems of HH bank's personal housing loan business risk management. In the empirical analysis part, from the borrower characteristics, loan characteristics, real estate characteristics and external economic characteristics of the four dimensions of the analysis framework, combined with the HH bank personal housing loan business related data, select the borrower gender, age, Place of domicile, marital status, occupation, education, monthly family income, monthly repayment amount, monthly repayment income ratio, loan amount, loan term, loan value ratio, repayment method, real estate value, housing area, On the basis of quantitative and descriptive analysis of the variables, 17 influencing factors, such as unit area house price and house price index, are used to reduce the dimension of each variable, and 7 common factors are extracted. By using two-classification Logistic regression analysis method, the regression model is constructed, and the regression analysis is carried out to find that the factors of family financial burden, loan, professional education and house price index have significant influence on loan risk, household registration factor, and household registration factor. The age of marriage and gender also have some influence on the risk of loan, but the degree of influence is smaller than that of the previous factors. By analyzing the influence degree and direction of each variable factor on the risk of individual housing loan business, It is found that each factor is different from each other, but there is also a correlation between them. However, the risk is not caused by a single factor, but by the co-influence of multiple factors, which leads to the possibility of risk occurring. Therefore, banks should fully and synthetically consider various influencing factors in their personal loan business, focusing on the dynamic changes of important influencing factors, such as family financial burden, loan period, etc., and be more accurate. In order to improve the quality of credit and improve the situation of non-performing loans, the countermeasures and suggestions are put forward.
【學(xué)位授予單位】：青島科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F832.479

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 張平;;開春去庫存 入秋限購令 銀行如何應(yīng)對(duì)新風(fēng)險(xiǎn)[J];杭州金融研修學(xué)院學(xué)報(bào);2016年12期

2 高恒;;“十二五”中國城鎮(zhèn)住房市場發(fā)展情況回顧[J];住宅與房地產(chǎn);2016年27期

3 陳端永;;新常態(tài)下青島房地產(chǎn)市場現(xiàn)狀分析與思考[J];中國統(tǒng)計(jì);2016年04期

4 ;中國房地產(chǎn)市場2015總結(jié)與2016趨勢展望[J];中外建筑;2016年02期

5 于洋;;二孩來了,地產(chǎn)如何“接生”?[J];商周刊;2015年24期

6 謝婷;;解析個(gè)人住房貸款違約現(xiàn)象[J];經(jīng)濟(jì)研究導(dǎo)刊;2015年06期

7 章彰;;基于風(fēng)險(xiǎn)預(yù)測的風(fēng)險(xiǎn)管理模式創(chuàng)新——個(gè)人住房按揭貸款視角[J];銀行家;2015年01期

8 李宇嘉;;論個(gè)人住房貸款發(fā)展的困境、原因及化解[J];中國房地產(chǎn);2013年22期

9 徐遙君;;淺析我國商業(yè)銀行個(gè)人住房貸款的違約風(fēng)險(xiǎn)[J];對(duì)外經(jīng)貿(mào);2013年03期

10 曾悅;;基于新政策下的商業(yè)銀行房貸業(yè)務(wù)風(fēng)險(xiǎn)控制分析[J];現(xiàn)代商業(yè);2012年12期

相關(guān)碩士學(xué)位論文 前5條

1 田建國;商業(yè)銀行個(gè)人住房貸款風(fēng)險(xiǎn)管理研究[D];山東大學(xué);2015年

2 梁詩杰;商業(yè)銀行個(gè)人住房貸款業(yè)務(wù)的風(fēng)險(xiǎn)防范研究[D];廈門大學(xué);2014年

3 楊艷竹;商業(yè)銀行個(gè)人住房貸款風(fēng)險(xiǎn)研究[D];首都經(jīng)濟(jì)貿(mào)易大學(xué);2014年

4 劉暢;我國商業(yè)銀行個(gè)人住房貸款風(fēng)險(xiǎn)防控研究[D];西南財(cái)經(jīng)大學(xué);2014年

5 暢曉菊;我國個(gè)人住房貸款擔(dān)保體系的構(gòu)建與管理研究[D];西安建筑科技大學(xué);2004年

，

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