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基于GMDH-Monte Carlo模擬的個人住房貸款風(fēng)險度量研究

發(fā)布時間:2018-05-02 16:56

  本文選題:個人住房貸款風(fēng)險 + GMDH; 參考:《中南大學(xué)》2013年碩士論文


【摘要】:隨著1998年我國福利分房制度的逐步取消,以及鼓勵城鎮(zhèn)住房建設(shè)和消費,各大商業(yè)銀行紛紛開展了個人住房抵押貸款業(yè)務(wù),截至到2011年末全國個人住房貸款余額達(dá)到了7.93萬億元,是1998年底的85倍,而此期間我國的商業(yè)銀行貸款總量僅增加了6倍多。個人住房貸款業(yè)務(wù)在給商業(yè)銀行帶來了豐厚利潤回報的同時,風(fēng)險也逐漸暴露出來。尤其近幾年宏觀經(jīng)濟(jì)的波動導(dǎo)致房地產(chǎn)市場劇烈的波動,在很大程度上影響到銀行個人住房貸款業(yè)務(wù),因此很有必要從宏觀層面上對我國的個人住房貸款風(fēng)險進(jìn)行定量的分析研究。 區(qū)別于以往的從宏觀層面上僅對我國的個人住房抵押貸款風(fēng)險提出預(yù)警及防范措施的研究方法,本文從個人住房貸款余額增長是否過快的角度定量分析我國個人住房抵押貸款風(fēng)險。在研究過程中,把在金融領(lǐng)域應(yīng)用廣泛的蒙特卡洛模擬方法應(yīng)用于實證研究,首先根據(jù)我國1997-2011之間的宏觀經(jīng)濟(jì)數(shù)據(jù)以及個人住房貸款余額利用GMDH方法獲得宏觀經(jīng)濟(jì)變量和個人住房抵押貸款余額之間的關(guān)系函數(shù);然后,利用Crystal Ball軟件進(jìn)行蒙特卡洛模擬,得出個人住房抵押貸款余額在2012-2015年分布統(tǒng)計結(jié)果;最后利用VaR的計算思想和國際經(jīng)驗警戒區(qū)間,從短期和長期兩方面度量了我國的個人住房貸款風(fēng)險。實證結(jié)果表明,用VaR方法得出我國2012年個人住房貸款的風(fēng)險在99%的置信度下出現(xiàn)緩解,但隨著置信度的下降,風(fēng)險逐漸擴(kuò)大;參照國際上經(jīng)驗警戒區(qū)間,即個人住房貸款同總貸款余額比值的警戒區(qū)間為18%-20%,發(fā)現(xiàn)若按照當(dāng)前的增長速度,當(dāng)置信度為99%時,我國在未來2-3年內(nèi)將進(jìn)入這一警戒區(qū)間,甚至可能超過最高警戒線。在此基礎(chǔ)上,進(jìn)行了壓力試驗,發(fā)現(xiàn)人均可支配收入增幅的大幅下降將會增加個人住房貸款的風(fēng)險。根據(jù)本文的研究結(jié)果,提出了相關(guān)的政策和措施建議。
[Abstract]:With the gradual abolition of welfare housing allocation system in China in 1998 and the encouragement of urban housing construction and consumption, various major commercial banks have launched individual housing mortgage loan business one after another. By the end of 2011, the balance of personal housing loans in China had reached 7.93 trillion yuan, 85 times of that at the end of 1998, but the total amount of commercial bank loans in China only increased by more than six times during this period. Personal housing loan business has brought huge profit return to commercial banks, and the risks have been exposed gradually. In particular, the macroeconomic fluctuations in recent years have led to violent fluctuations in the real estate market, which to a large extent have affected the individual housing loan business of banks. Therefore, it is necessary to carry out quantitative analysis and research on the risk of personal housing loan in China from the macro level. Different from the previous research methods that only put forward early warning and preventive measures to the risk of personal housing mortgage loan in China from the macro level, This paper quantitatively analyzes the risk of personal housing mortgage loan in China from the point of view of whether the balance of personal housing loan increases too fast. In the course of the research, the Monte Carlo simulation method, which is widely used in the field of finance, is applied to the empirical research. Firstly, according to the macroeconomic data between 1997 and 2011 and the balance of personal housing loan, the relationship function between the macroeconomic variables and the balance of individual housing mortgage loan is obtained by using GMDH method. Then, Monte Carlo simulation is carried out by using Crystal Ball software. The statistical results of the distribution of personal housing mortgage balance in 2012-2015 are obtained, and the risk of personal housing loan in China is measured in the short and long term by using VaR's calculation idea and the warning range of international experience. The empirical results show that the risk of personal housing loan in China in 2012 is mitigated at 99% of the confidence level, but with the decrease of the confidence level, the risk gradually expands. That is, the warning range of the ratio of personal housing loan to total loan balance is 18-20. It is found that if the current growth rate is followed, when the confidence level is 99, China will enter this warning range in the next 2-3 years, and may even exceed the highest warning line. On this basis, a stress test was conducted and found that a sharp decline in per capita disposable income would increase the risk of personal housing loans. According to the research results of this paper, the relevant policies and measures are proposed.
【學(xué)位授予單位】:中南大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2013
【分類號】:F832.479;F224

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