本文選題：債務(wù)抵押債券 + KMV模型　； 參考：《湖南大學(xué)》2014年碩士論文

【摘要】：債務(wù)抵押債券（CDO）是一種基于信用資產(chǎn)池現(xiàn)金流為支撐，以分券的方式發(fā)行的結(jié)構(gòu)性衍生金融產(chǎn)品。由于其復(fù)雜的內(nèi)在結(jié)構(gòu)和交易流程，使得對(duì)其進(jìn)行定價(jià)尤為困難。 本文基于國(guó)內(nèi)二級(jí)市場(chǎng)流動(dòng)性嚴(yán)重不足，市場(chǎng)缺乏信用違約數(shù)據(jù)的現(xiàn)狀，以及國(guó)內(nèi)市場(chǎng)所發(fā)行的CDO普遍存在資產(chǎn)評(píng)級(jí)高、集中度高等特點(diǎn)。運(yùn)用KMV模型，利用國(guó)內(nèi)市場(chǎng)數(shù)據(jù)估算出資產(chǎn)池中各資產(chǎn)的違約概率。針對(duì)違約事件導(dǎo)致資產(chǎn)價(jià)值發(fā)生跳躍的情形，在模型中引入“跳躍”過(guò)程進(jìn)行描述。然后，針對(duì)信用資產(chǎn)收益序列的“尖峰厚尾”的特征，信用資產(chǎn)的相關(guān)結(jié)構(gòu)是動(dòng)態(tài)的，非線(xiàn)性相關(guān)的。本文引入Gaussian Copula和Student-t Copula函數(shù)估算出各債務(wù)人相互的違約相關(guān)結(jié)構(gòu)。最后，利用無(wú)套利定價(jià)原理求解出各分券的收益面和損失面，并運(yùn)用Monte Carlo模擬估算出各個(gè)分券的合理信用價(jià)差。 實(shí)證結(jié)果顯示，針對(duì)資產(chǎn)的突變過(guò)程，通過(guò)在模型中引入“跳躍”過(guò)程加以刻畫(huà)，運(yùn)用KMV模型估算“債務(wù)人”的違約概率是有效的。并且，在高級(jí)券層的定價(jià)精度優(yōu)于次級(jí)券層。其次，，引入Copula函數(shù)能夠很好的擬合信用資產(chǎn)的尾部非線(xiàn)性風(fēng)險(xiǎn)特征，并且Student-t Copula函數(shù)相對(duì)于Gaussian Copula函數(shù)的模擬結(jié)果更優(yōu)，平均能縮小3-5個(gè)bps。最后，本文發(fā)現(xiàn)KMV模型中，運(yùn)用虛擬“債務(wù)人”進(jìn)行分類(lèi)，會(huì)提高資產(chǎn)的信用，進(jìn)而使得次級(jí)券層的定價(jià)誤差加大。
[Abstract]:CDO is a kind of structured derivative financial product based on the cash flow of credit asset pool. Because of its complex internal structure and transaction process, it is particularly difficult to price it. This paper is based on the lack of liquidity in domestic secondary market, the lack of credit default data in the market, and the high asset rating and high concentration of CDO issued in domestic market. The default probability of each asset in the asset pool is estimated by using KMV model and domestic market data. In view of the situation that the default event leads to the jump of asset value, the "jump" process is introduced into the model. Then, the correlation structure of credit assets is dynamic and nonlinear. In this paper, Gaussian Copula and Student-t Copula functions are introduced to estimate the relative structure of each debtor's default. Finally, the yield and loss surfaces of each coupon are calculated by using the no-arbitrage pricing principle, and the reasonable credit spread of each coupon is estimated by Monte Carlo simulation. The empirical results show that it is effective to use KMV model to estimate the default probability of "debtor" by introducing "jump" process to describe the sudden change process of assets. Moreover, the pricing accuracy in the premium bond layer is better than that in the secondary bond layer. Secondly, the Copula function can fit the tail nonlinear risk characteristics of the credit assets well, and the Student-t Copula function is better than the Gaussian Copula function, and it can reduce 3-5 bps on average. Finally, this paper finds that in the KMV model, the use of virtual "debtor" to classify assets will improve the credit of assets, and then make the pricing error of sub-securities layer increase.
【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：F832.51

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本文編號(hào)：1886275