本文關(guān)鍵詞：我國資產(chǎn)支持證券劣后級風(fēng)險分析　出處：《云南財經(jīng)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 資產(chǎn)證券化 劣后級證券 信用風(fēng)險

【摘要】：自2013年我國重啟信貸資產(chǎn)證券化,發(fā)行規(guī)模不斷擴(kuò)大,市場朝著規(guī)范化和常態(tài)化的方向發(fā)展。與此同時,劣后級資產(chǎn)支持證券的投資者群體仍有待擴(kuò)大,二級市場的流動性亟待改善。導(dǎo)致這一問題的原因之一即是劣后級資產(chǎn)支持證券的信息披露不足,缺乏風(fēng)險評級,難以進(jìn)行風(fēng)險評估和定價。而國內(nèi)現(xiàn)有的研究大多著眼于將資產(chǎn)支持證券作為一個整體進(jìn)行風(fēng)險分析,或止步于分析信用風(fēng)險對優(yōu)先級證券的影響,未充分考慮資產(chǎn)支持證券中各個層級間的巨大風(fēng)險差異,忽略了劣后級資產(chǎn)支持證券,故通過對劣后級部分風(fēng)險的分析,可以彌補(bǔ)過往研究的遺漏之處,為資產(chǎn)證券化的理論與實踐提供參考。首先進(jìn)行定性分析,對資產(chǎn)支持證券的風(fēng)險形式做了梳理,并重點論述了不同層級證券在遭遇不同形式風(fēng)險時的差異。依次論述了宏觀經(jīng)濟(jì)與市場風(fēng)險、信用風(fēng)險、操作風(fēng)險,其中信用風(fēng)險是資產(chǎn)支持證券的主要風(fēng)險來源。然后進(jìn)行量化分析,先使用定量指標(biāo)分析,通過比較同一類型資產(chǎn)支持證券的風(fēng)險指標(biāo),對風(fēng)險狀況進(jìn)行評估。再使用在險價值模型(VAR Model)的歷史模擬法對風(fēng)險進(jìn)行了分析,從而求出劣后級證券在一定置信水平下可能承受的最大損失,將這一指標(biāo)同定量指標(biāo)相結(jié)合,對其風(fēng)險水平形成一個基本的判斷。此后,運用多元回歸模型對定量指標(biāo)的有效性進(jìn)行了檢驗,在歐美學(xué)者研究的基礎(chǔ)上,對模型中的解釋變量作出了一定的調(diào)整,以適應(yīng)我國的實際情況。考慮我國當(dāng)前金融業(yè)發(fā)展?fàn)顩r,違約風(fēng)險為當(dāng)前主要的風(fēng)險來源,銀行業(yè)仍占主導(dǎo)地位,且商業(yè)銀行對資產(chǎn)證券化的需求較大,市場潛力大。選取2014年-2016年間數(shù)據(jù),對信貸資產(chǎn)支持證券(劣后級)的違約風(fēng)險進(jìn)行了多元回歸分析。結(jié)果表明資產(chǎn)的違約率、分散度、期限、違約回收率、發(fā)起機(jī)構(gòu)可以作為劣后級證券的風(fēng)險指標(biāo)。最后,結(jié)合定性分析和定量分析的結(jié)論,提出應(yīng)加強(qiáng)信息披露,改善二級市場流動性,有針對性的提升監(jiān)管力度等建議。
[Abstract]:Since 2013, the credit asset securitization has been restarted in China, the issuing scale is expanding and the market is developing towards standardization and normalization. At the same time, the investor group of inferior asset backed securities still needs to be expanded. The liquidity of the secondary market needs to be improved urgently. One of the reasons for this problem is that the information disclosure of the inferior asset-backed securities is insufficient and the risk rating is lacking. It is difficult to carry out risk assessment and pricing. However, most of the existing domestic studies focus on risk analysis of asset-backed securities as a whole, or stop at analyzing the impact of credit risk on priority securities. The great risk difference among different levels of asset-backed securities is not fully considered, and the inferior backclass asset-backed securities are neglected. Therefore, through the analysis of the partial risk of inferior post-grade securities, we can make up for the omissions of previous studies. It provides a reference for the theory and practice of asset securitization. Firstly, qualitative analysis is carried out to sort out the risk forms of asset-backed securities. And discussed the different levels of securities in the face of different forms of risk, in turn discussed the macroeconomic and market risk, credit risk, operational risk. Credit risk is the main risk source of asset-backed securities. The risk condition is evaluated and the risk is analyzed by using the historical simulation method of VAR Model. In order to find out the maximum loss that the inferior security may bear under a certain confidence level, combine this index with the quantitative index, form a basic judgment to its risk level. The validity of quantitative indexes is tested by using multivariate regression model. Based on the research of European and American scholars, the explanatory variables in the model are adjusted to a certain extent. In order to adapt to the actual situation of our country, considering the current development of the financial industry in China, default risk is the main risk source at present, the banking industry is still dominant, and commercial banks have a large demand for asset securitization. The data from 2014 to 2016 are used to analyze the default risk of credit asset-backed securities. The results show that the default rate, dispersion and maturity of the assets. Default recovery rate, the initiator can be used as a risk indicator of inferior securities. Finally, combined with qualitative analysis and quantitative analysis of the conclusion, we should strengthen information disclosure, improve the liquidity of the secondary market. Targeted measures to enhance supervision and other recommendations.
【學(xué)位授予單位】：云南財經(jīng)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F832.51

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