本文選題：生存分析 + Cox比例風險模型�。� 參考：《山東大學》2014年碩士論文

【摘要】：信用風險作為銀行業(yè)的主要風險之一,表現(xiàn)形式越來越多樣化,影響也逐漸擴大,不僅會給金融行業(yè)帶來巨大的沖擊還會影響整個社會的穩(wěn)定,因此,其危害性也得到了越來越多的重視。為了有效的管理信用風險,商業(yè)銀行也加快了信用風險研究的步伐。 發(fā)達國家的信用風險管理起步早,發(fā)展較成熟,逐漸實現(xiàn)定性向定量的發(fā)展。而我國的商業(yè)銀行信用風險管理還處于定性分析的階段,缺乏成熟的定量分析模型和技術。然而,隨著金融行業(yè)的不斷發(fā)展,傳統(tǒng)的信用風險的評級方法和傳統(tǒng)的信用風險模型已經很難適應發(fā)展需要,因此準確合理的度量商業(yè)銀行的信用風險對商業(yè)銀行的信用風險管理尤其重要。 目前研究信用風險的模型較多,應用較早有Logit模型、研究單一信用風險的KMV模型及測度組合信用風險的Credit Risk+等模型,這些模型在一定條件和假設下取得了較好的結果。然而Credit Risk+等模型需要企業(yè)信用評級的數(shù)據,而我國缺乏企業(yè)信用評級的歷史數(shù)據,所以這些模型不太適用我國的金融市場。隨著生存分析理論的發(fā)展和應用的不斷推廣,基于生存分析的Cox比例風險模型在信用風險度量研究中顯示出一定的優(yōu)越性,Cox比例風險模型不需要信用評級數(shù)據,而是研究對生存時間有影響的財務數(shù)據,因此可以用來分析國內企業(yè)的財務狀況。本文嘗試進行Cox比例風險模型的實證研究。 本文基于現(xiàn)有的信用風險研究結果,首先,介紹了生存分析的基本理論并分析生存分析在信用風險度量中的作用。其次,詳細介紹了基于生存分析的Cox比例風險模型,并給出了模型參數(shù)和非參部分的估計方法。最后,基于實際數(shù)據建立Cox比例風險模型,進而得到上市公司的違約概率,并對模型結果進行分析,根據模型結果我們可以分析增加上市公司財務風險的因素(即危險因素)和減少上市公司風險的因素(即保護因素)。通過分析模型的時點預測能力及準確性,判斷模型可行,商業(yè)銀行可以根據模型結果判斷自身面臨的信用風險情況。本文通過CAP曲線、ROC曲線及KS檢驗驗證了模型的有效性和穩(wěn)定性,為模型在實際中的應用提供了基礎。
[Abstract]:As one of the main risks of the banking industry, credit risk is becoming more and more diversified and its influence is gradually expanding. It will not only bring huge impact to the financial industry but also affect the stability of the whole society. Therefore, its harmfulness has also been paid more and more attention. In order to manage credit risk, commercial banks also accelerate their credit The pace of risk research.
The credit risk management in developed countries is early, mature and gradually realized to the qualitative and quantitative development. The credit risk management of commercial banks in China is still in the stage of qualitative analysis, lack of mature quantitative analysis model and technology. However, with the continuous development of the financial industry, the traditional credit risk rating method and tradition The credit risk model has been difficult to adapt to the development needs, so the accurate and reasonable measure of the credit risk of commercial banks is particularly important for the credit risk management of commercial banks.
At present, there are many models to study credit risk, the Logit model is used earlier, the KMV model of single credit risk and the Credit Risk+ model of measuring combination credit risk are studied. These models have obtained good results under certain conditions and assumptions. However, Credit Risk+ and other models need the data of enterprise credit rating, but China is short of enterprise. The historical data of the industry credit rating, so these models are not very suitable for China's financial market. With the development and application of survival analysis theory, the Cox proportional risk model based on survival analysis shows some advantages in the research of credit risk measurement. Cox does not need credit rating data, but it does not need the credit rating data. The financial data that affect the survival time can be used to analyze the financial situation of domestic enterprises. This paper attempts to conduct an empirical study on the Cox proportional hazards model.
Based on the existing research results of credit risk, this paper first introduces the basic theory of survival analysis and analyzes the role of survival analysis in credit risk measurement. Secondly, the Cox proportional risk model based on survival analysis is introduced in detail, and the model parameters and non parametric estimation methods are given. Finally, based on the actual data, the Cox is established. According to the results of the model, we can analyze the factors of increasing the financial risk of the listed companies (i.e., the risk factors) and the factors to reduce the risk of the listed companies (that is the protection factor). It is feasible that commercial banks can judge their credit risk according to the results of the model. In this paper, the validity and stability of the model are verified by CAP curve, ROC curve and KS test, which provides a basis for the application of the model in practice.

【學位授予單位】：山東大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：F832.33;O213

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本文編號：1853670