本文選題：房地產(chǎn)開發(fā)貸款　切入點(diǎn)：商業(yè)銀行　出處：《湖南大學(xué)》2013年碩士論文

【摘要】：隨著房地產(chǎn)業(yè)的高速發(fā)展，房地產(chǎn)信貸占銀行總信貸的比重不斷上升，銀行房地產(chǎn)開發(fā)信貸面臨著越來越大的潛在風(fēng)險。房地產(chǎn)業(yè)是典型的資金密集型行業(yè)，其開發(fā)和經(jīng)營的資金大部分來源于金融機(jī)構(gòu)，發(fā)展嚴(yán)重依賴于商業(yè)銀行的貸款，這使得房地產(chǎn)業(yè)的風(fēng)險高度集中于銀行體系。而目前我國商業(yè)銀行對房地產(chǎn)貸款信用風(fēng)險的準(zhǔn)確度量和有效管理的滯后，也在無形中增加了商業(yè)銀行的經(jīng)營風(fēng)險，本文主要研究在借鑒西方發(fā)達(dá)的信用風(fēng)險度量技術(shù)的基礎(chǔ)上，對如何優(yōu)化我國商業(yè)銀行計量房地產(chǎn)開發(fā)信貸資產(chǎn)風(fēng)險的做出了探究，并為進(jìn)一步加強(qiáng)我國房地產(chǎn)開發(fā)貸款信用度量及風(fēng)險管控提出相應(yīng)對策。 國際信用風(fēng)險管理領(lǐng)域逐漸發(fā)展出了一套完整的風(fēng)險度量體系，這對于我國商業(yè)銀行信用風(fēng)險的量化管理具有一定的借鑒意義，，本文系統(tǒng)性地闡述了目前在國際上應(yīng)用較為廣泛的，同時具有較大影響力的KMV模型、Credit Metrics、CreditRisk+等信用風(fēng)險度量模型的理論基礎(chǔ)、度量方式以及在中國經(jīng)濟(jì)高速發(fā)展的大形勢之下的適用性。選取了在現(xiàn)階段較為適合我國經(jīng)濟(jì)發(fā)展?fàn)顩r的KMV模型為代表，運(yùn)用實(shí)證的方法驗(yàn)證了現(xiàn)代信用風(fēng)險度量方法在中國房地產(chǎn)開發(fā)市場的適用性，實(shí)證結(jié)果表明違約距離能從整體上區(qū)分房地產(chǎn)開發(fā)行業(yè)中的ST類公司與非ST類公司，能較好的反映出我國房地產(chǎn)業(yè)上市公司的信用變化狀況，適合我國商業(yè)銀行用來提高評估房地產(chǎn)開發(fā)信貸資金風(fēng)險即房地產(chǎn)公司償債能力的水平。但是本文也發(fā)現(xiàn)，可能是由于中國股市的非有效性和違約數(shù)據(jù)的缺乏問題，現(xiàn)代信用風(fēng)險度量模型對于我國商業(yè)銀行識別信用風(fēng)險的能力是有限的，因此還需要不斷夯實(shí)房地產(chǎn)信用風(fēng)險的度量基礎(chǔ)，提高商業(yè)銀行精準(zhǔn)度量水平，并結(jié)合我國的實(shí)際情況進(jìn)行模型的修正和完善。
[Abstract]:With the rapid development of the real estate industry, the proportion of the real estate credit to the total bank credit is increasing, and the bank real estate development credit is facing more and more potential risks. The real estate industry is a typical capital-intensive industry. Most of the funds for its development and operation came from financial institutions, and development was heavily dependent on loans from commercial banks. This makes the risk of the real estate industry highly concentrated in the banking system. However, at present, the commercial banks in our country lag behind in the accuracy and effective management of the credit risk of real estate loans, which also increases the operational risk of the commercial banks invisibly. On the basis of the developed credit risk measurement technology in the west, this paper probes into how to optimize the commercial banks in our country to measure the risk of credit assets in real estate development. And put forward the corresponding countermeasures for further strengthening the credit degree and risk control of the real estate development loan in our country. The international credit risk management field has gradually developed a set of complete risk measurement system, which has certain reference significance for the quantitative management of the commercial bank credit risk in our country. This paper systematically expounds the theoretical basis of credit risk measurement model such as Credit Metrics CreditRisk, which is widely used in the world and has great influence. The method of measurement and its applicability under the situation of rapid economic development in China. The KMV model, which is more suitable for China's economic development at the present stage, is selected as the representative. The applicability of modern credit risk measurement method in Chinese real estate development market is verified by the empirical method. The empirical results show that the default distance can distinguish St companies from non-St companies in real estate development industry as a whole. It can better reflect the credit changes of listed companies in real estate industry in China, and it is suitable for commercial banks to improve the level of assessing the risk of real estate development credit funds, that is, the ability of real estate companies to repay their debts. Due to the non-validity of Chinese stock market and the lack of default data, the modern credit risk measurement model is limited to the ability of Chinese commercial banks to identify credit risk. Therefore, it is necessary to strengthen the measurement foundation of real estate credit risk, to improve the level of accurate measurement of commercial banks, and to modify and improve the model according to the actual situation of our country.
【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】：F832.45

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 儲小俊;基于期權(quán)定價理論的風(fēng)險投資決策[J];商業(yè)研究;2005年08期

2 張玲,曾維火;基于Z值模型的我國上市公司信用評級研究[J];財經(jīng)研究;2004年06期

3 于立勇,詹捷輝;基于Logistic回歸分析的違約概率預(yù)測研究[J];財經(jīng)研究;2004年09期

4 肖杰;杜子平;;Credit Metrics模型下組合信用風(fēng)險應(yīng)用與改進(jìn)研究[J];財會通訊;2010年14期

5 張雪寧;我國發(fā)展房地產(chǎn)信托投資基金的可行性分析[J];中國房地產(chǎn);2004年06期

6 李建華;韓崗;韓曉普;;基于Credit Portfolio View的信用風(fēng)險度量模型研究[J];工業(yè)技術(shù)經(jīng)濟(jì);2008年03期

7 王建紅,陳松,鄭志明;住房抵押貸款的理性違約及其風(fēng)險的規(guī)避[J];重慶建筑大學(xué)學(xué)報;2002年05期

8 章忠志,符林,唐煥文;基于人工神經(jīng)網(wǎng)絡(luò)的商業(yè)銀行信用風(fēng)險模型[J];經(jīng)濟(jì)數(shù)學(xué);2003年03期

9 陳學(xué)會;房地產(chǎn)業(yè)要素供給規(guī)制問題探析[J];經(jīng)濟(jì)問題;2004年09期

10 劉明興,羅俊偉;泡沫經(jīng)濟(jì)與金融危機(jī)[J];經(jīng)濟(jì)學(xué)家;2000年04期

相關(guān)博士學(xué)位論文 前1條

1 劉迎春;我國商業(yè)銀行信用風(fēng)險度量和管理研究[D];東北財經(jīng)大學(xué);2011年

本文編號：1668862