本文選題：房地產(chǎn)　切入點(diǎn)：公司債券　出處：《華東師范大學(xué)》2013年碩士論文

【摘要】：經(jīng)過6年的發(fā)展,公司債券漸漸成為越來(lái)越多經(jīng)營(yíng)者降低融資成本的外部融資工具,也成為了越來(lái)越多投資者追捧的對(duì)象。因而公司債券的風(fēng)險(xiǎn)補(bǔ)償,即信用利差成為了發(fā)行人和投資者進(jìn)行投融資時(shí)最為關(guān)注的問題。 本文選取了房地產(chǎn)市場(chǎng)公司債券作為研究對(duì)象,基于對(duì)時(shí)間序列分析的方法,通過分析我國(guó)公司債券的宏微觀影響因子,提供了一種建立了二級(jí)市場(chǎng)上房地產(chǎn)行業(yè)公司債券信用利差預(yù)測(cè)模型的方法。首先,從債券自身因素、宏觀經(jīng)濟(jì)因素和企業(yè)財(cái)務(wù)因素三個(gè)層面來(lái)考慮信用利差的影響因素。其次,利用聚類分析的方法從納入考慮的眾多影響因子中選取了7個(gè)宏微觀因子,建立信用利差預(yù)測(cè)模型,這是本文的重點(diǎn)。這一步中,采用多項(xiàng)式擬合的方法調(diào)整了財(cái)務(wù)數(shù)據(jù)頻率,利用逐步回歸的方法排除非顯著影響因子,建立信用利差與顯著影響因子之間的協(xié)整關(guān)系后建立殘差的ARMA模型對(duì)協(xié)整關(guān)系進(jìn)行修正,得到了第一類信用利差預(yù)測(cè)模型。接著又將非顯著因子引入到模型中,統(tǒng)一了行業(yè)中所有債券信用利差影響因子,建立了第二類信用利差預(yù)測(cè)模型。經(jīng)過對(duì)比,兩類模型在預(yù)測(cè)效果上的差別非常細(xì)微,但第二類模型在實(shí)務(wù)操作中有更高的便利性和可比性。最后,本文將第二類模型與已有的信用利差模型進(jìn)行對(duì)比,論證了本文第二類模型的合理性和優(yōu)勢(shì)。 通過上述研究過程,本文得到了如下研究結(jié)論：對(duì)房地產(chǎn)行業(yè)公司債券信用利差產(chǎn)生影響的微觀因子有剩余到期期限、總資產(chǎn)、凈利潤(rùn)和經(jīng)營(yíng)活動(dòng)現(xiàn)金凈流量,宏觀因素有股票市場(chǎng)收益率、利率期限結(jié)構(gòu)斜率和工業(yè)增加值。對(duì)不同債券信用利差產(chǎn)生顯著影響的因子是不一樣的,但引入非顯著因子并不會(huì)影響模型的預(yù)測(cè)效果。相反,引入非顯著因子可以提高實(shí)務(wù)操作中的便利性和可比性。
[Abstract]:After six years of development, corporate bonds have gradually become an external financing tool for more and more operators to reduce their financing costs, and become more and more popular among investors. That is, credit spreads have become the most concerned issue when issuers and investors invest and finance. This paper selects corporate bonds in real estate market as the research object, based on the method of time series analysis, through the analysis of the macro and micro factors of corporate bonds in China. This paper provides a method for predicting the credit spreads of real estate companies in the secondary market. The influence factors of credit spreads are considered from three aspects of macroeconomic factors and enterprise financial factors. Secondly, seven macro and micro factors are selected from the many factors taken into account by cluster analysis, and a credit spread prediction model is established. This is the focus of this paper. In this step, the frequency of financial data is adjusted by polynomial fitting method, and the non-significant influence factors are excluded by the method of stepwise regression. After establishing the cointegration relationship between credit interest difference and significant influence factor, the ARMA model of residual error is established to modify the co-integration relation, and the first kind of credit interest rate prediction model is obtained. Then, the non-significant factor is introduced into the model. Unifies the influence factors of all bond credit spreads in the industry, and establishes the second kind of credit spread forecasting model. After comparison, the difference between the two kinds of models in the forecasting effect is very small. But the second type model is more convenient and comparable in practical operation. Finally, this paper compares the second type model with the existing credit spread model, and proves the rationality and advantage of the second type model. Through the above research process, this paper obtains the following conclusions: the micro factors that affect the credit spreads of real estate companies are the remaining maturity period, total assets, net profit and net cash flow of operating activities. Macro factors include stock market yield, interest rate term structure slope and industrial added value. The factors that have significant influence on different bond credit spreads are different, but the introduction of non-significant factors will not affect the forecasting effect of the model. The introduction of non-significant factors can improve convenience and comparability in practical operations.
【學(xué)位授予單位】：華東師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F224;F299.23;F832.51

【參考文獻(xiàn)】

相關(guān)期刊論文 前3條

1 孫克;;企業(yè)債信用價(jià)差動(dòng)態(tài)過程的影響因素研究[J];證券市場(chǎng)導(dǎo)報(bào);2010年07期

2 李嵐;楊長(zhǎng)志;;基于面板數(shù)據(jù)的中期票據(jù)信用利差研究[J];證券市場(chǎng)導(dǎo)報(bào);2010年08期

3 程文衛(wèi);;通貨膨脹對(duì)固定收益證券到期收益率和信用利差的影響:基于中國(guó)的實(shí)證研究[J];中央財(cái)經(jīng)大學(xué)學(xué)報(bào);2009年07期

，

本文編號(hào)：1697189