本文選題：保障性商品房 + Logistic模型��； 參考：《天津科技大學(xué)》2012年碩士論文

【摘要】：我國城市人口激增引起住房需求的膨脹,而目前住房方面的支出超出了普通收入家庭的支付能力。國家制定了一系列政策建立保障房,以滿足人民居者有其屋的基本需求。然而資金的缺乏成為制約保障性住房建設(shè)的瓶頸問題。本文研究集社會保障福利性和貨幣支付商品性于一身的保障性商品房融資問題。 本文通過對住房抵押貸款證券化(MBS)的分析,考慮是否可以將其作為一種金融創(chuàng)新工具,應(yīng)用于我國保障性商品房建設(shè)融資中。我們看到,剛剛稍有平息的美國金融危機(jī)即由MBS的過度發(fā)放引起,本文通過對次貸危機(jī)的深刻認(rèn)識,分析在我國保障性商品房中應(yīng)用可能與美國存在的異同,發(fā)現(xiàn)我國保障性商品房的售賣對象也是低收入人群,但與美國看似同,實(shí)為反。我國保障性商品房就是讓中低收入者買得起房,為此,國家制定了一系列政策,包括劃撥土地、調(diào)低地價(jià),免收城市基礎(chǔ)設(shè)施配套費(fèi)等各種行政事業(yè)性收費(fèi)和政府性基金,實(shí)行稅收優(yōu)惠政策,對于保障房的房地產(chǎn)建設(shè),也給予政策傾斜和保護(hù)。這就從根本上降低了這種“政策性”住房的建設(shè)成本。而房屋本身的低價(jià)也會大大降低投資風(fēng)險(xiǎn)。 本文的創(chuàng)新點(diǎn)除了提出MBS在保障性商品房中的應(yīng)用,還體現(xiàn)于提取出適用于我國保障性商品房的理論�；贛BS研究的兩方面——提前償付研究與定價(jià)研究,以提前償付為重點(diǎn),建立了兩個模型。 在提前償還預(yù)測模型中,通過研究影響國內(nèi)外提前償付率因素,找到符合我國保障性商品房的因素,采用Logistic模型分析方法,同時(shí)選用一家商業(yè)銀行的數(shù)據(jù),對所選樣本進(jìn)行分析和預(yù)測,得到影響該樣本發(fā)生提前還款的因素主要有貸款金額、借款人婚姻狀況和貸款利率變化。 在個人貸款實(shí)際清償年限預(yù)測模型中,構(gòu)建了以“收入—儲蓄”為主因素的個人提前還款案例,通過ARMA模型預(yù)測未來人均GDP及人均收入,再結(jié)合前人的文獻(xiàn)給出天津某類經(jīng)濟(jì)適用房貸款人的各項(xiàng)參數(shù),最終得到個人提前還款的預(yù)期時(shí)間。 模型求解中用到R程序、Eviews、SPSS等數(shù)學(xué)統(tǒng)計(jì)分析軟件。
[Abstract]:The explosion of urban population in China has caused the housing demand to swell, but the current housing expenditure is beyond the ability of the ordinary income families to pay.The state formulated a series of policies to establish indemnificatory apartment to meet the basic needs of the people's home ownership.However, the lack of funds has become the bottleneck of the construction of affordable housing.This paper studies the financing of affordable commercial housing with social security welfare and currency payment commodity.Based on the analysis of mortgage securitization (MBS), this paper considers whether it can be used as a financial innovation tool to finance the construction of affordable commercial housing in China.We can see that the US financial crisis, which has just subsided a little bit, is caused by the excessive issuance of MBS. Through the deep understanding of the subprime mortgage crisis, this paper analyzes the similarities and differences that may exist between the US and our country in the application of affordable commercial housing.It is found that the sale of affordable commercial housing in our country is also low-income people, but it seems to be the same as the United States.Affordable commercial housing in our country is to make housing affordable for low- and middle-income people. For this reason, the state has formulated a series of policies, including the allocation of land, the reduction of land prices, the exemption of all kinds of administrative fees and government funds, such as supporting fees for urban infrastructure facilities.The implementation of preferential tax policies, indemnificatory apartment's real estate construction, but also to give policy tilt and protection.This fundamentally reduces the construction cost of this kind of "policy" housing.And the low price of the house itself will greatly reduce the investment risk.The innovation of this paper is not only to put forward the application of MBS in the affordable commercial housing, but also to extract the theory suitable for our country's indemnificatory commercial housing.Based on two aspects of MBS research, prepayment and pricing, two models are established, focusing on prepayment.In the forecasting model of early repayment, by studying the factors affecting the early repayment rate at home and abroad, finding out the factors that accord with the guarantee commercial housing in our country, adopting the Logistic model analysis method, choosing the data of a commercial bank at the same time.Through the analysis and prediction of the selected sample, it is found that the factors influencing the prepayment of the sample are the loan amount, the borrower's marital status and the change of the loan interest rate.In the prediction model of the actual repayment years of personal loans, a case of individual prepayment with "income-savings" as the main factor is constructed, and the ARMA model is used to predict the per capita GDP and per capita income in the future.Combined with previous literatures, the parameters of some comfortable housing lenders in Tianjin are given, and the expected time of individual prepayment is finally obtained.The mathematical statistical analysis software, such as Eviewsl SPSS, is used in solving the model.
【學(xué)位授予單位】：天津科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：F299.23;F832.45

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