【摘要】：金融危機(jī)頻發(fā),金融機(jī)構(gòu)面臨的風(fēng)險(xiǎn)日益增多,現(xiàn)有的風(fēng)險(xiǎn)度量方法存在不足,金融風(fēng)險(xiǎn)分布形態(tài)各異,現(xiàn)有的相關(guān)性度量方法無法描述復(fù)雜金融市場的相關(guān)模式等等,基于以上這些原因,需要一種既能靈活的構(gòu)造多元風(fēng)險(xiǎn)分布、又能反映變量間的相關(guān)模式的技術(shù)出現(xiàn)。Copula函數(shù)就是這樣一種新的、更加穩(wěn)健的、靈活的相關(guān)性分析技術(shù)。它是一個(gè)函數(shù),它主要用來描述隨機(jī)變量之間的相關(guān)性。最早提出Copula理論的是Sklar(1959),他指出連續(xù)的k(k2)元聯(lián)合分布函數(shù)能分解為一個(gè)Copula函數(shù)和k個(gè)邊際分布兩部分信息,其中Copula函數(shù)描述了隨機(jī)變量間的相關(guān)模式。這樣可以選取代表不同相關(guān)模式的Copula函數(shù)形式來描述金融市場的相關(guān)模式,并結(jié)合數(shù)據(jù)的邊際分布形式,利用Sklar定理構(gòu)造出能充分反映數(shù)據(jù)特征的聯(lián)合分布形式,最后再根據(jù)分布形態(tài)得到風(fēng)險(xiǎn)度量指標(biāo)。所以本文從應(yīng)用的角度全面系統(tǒng)地探討了Copula函數(shù)在各種金融風(fēng)險(xiǎn)度量中的應(yīng)用。 在全球金融危機(jī)頻發(fā)的情況下,各國金融機(jī)構(gòu)必須采取措施防范各種風(fēng)險(xiǎn),以保障金融安全。要保障金融安全,首先需要了解在金融活動(dòng)中可能會(huì)出現(xiàn)哪些風(fēng)險(xiǎn),以便有針對性地防范和化解風(fēng)險(xiǎn)。根據(jù)金融風(fēng)險(xiǎn)的性質(zhì)和來源不同,金融風(fēng)險(xiǎn)主要面臨四種風(fēng)險(xiǎn)：市場風(fēng)險(xiǎn)、信用風(fēng)險(xiǎn)、操作風(fēng)險(xiǎn)和整體風(fēng)險(xiǎn)。 Copula理論在實(shí)際應(yīng)用中有許多優(yōu)點(diǎn)。Copula函數(shù)是很好的描述相關(guān)結(jié)構(gòu)的工具,可以非常好地度量金融市場的各種復(fù)雜相關(guān)模式和相關(guān)程度。所以本文從應(yīng)用的角度全面系統(tǒng)地探討了Copula函數(shù)在各種金融風(fēng)險(xiǎn)度量中的應(yīng)用。 文章第一章主要介紹了選題背景、研究意義及國內(nèi)外研究現(xiàn)狀。文章第二部分主要介紹了Copula理論,包括其定義、性質(zhì)、種類等。文章第三章主要介紹了copula理論在金融風(fēng)險(xiǎn)度量中的應(yīng)用。包括copula理論在金融風(fēng)險(xiǎn)度兩種的優(yōu)勢及應(yīng)用方式。文章第四章介紹了基于copula方法的組合信用風(fēng)險(xiǎn)度量模型,第五章介紹了基于copula方法的投資組合風(fēng)險(xiǎn)測量模型,在此基礎(chǔ)上,文章第六章則是基于copula方法的投資組合風(fēng)險(xiǎn)測量的實(shí)證研究。 文章歸納整理了國內(nèi)外關(guān)于Copula函數(shù)在主要金融風(fēng)險(xiǎn)中的研究現(xiàn)狀,指出Copula函數(shù)的應(yīng)用價(jià)值。在詳細(xì)總結(jié)Copula函數(shù)的基本理論和特點(diǎn)基礎(chǔ)上,對由Copula函數(shù)導(dǎo)出的相關(guān)性度量指標(biāo)進(jìn)行深入的分析。文章研究的重點(diǎn)是Copula函數(shù)在金融風(fēng)險(xiǎn)、信用風(fēng)險(xiǎn)度量和投資組合風(fēng)險(xiǎn)測量模型的應(yīng)用。
[Abstract]:With the frequent occurrence of financial crises, the risks faced by financial institutions are increasing day by day, the existing risk measurement methods are insufficient, the financial risk distribution is different, the existing correlation measurement methods can not describe the related models of complex financial markets, and so on. For these reasons, a new, more robust and flexible correlation analysis technique is needed to construct the multivariate risk distribution and reflect the correlation pattern between variables. The Copula function is such a new, more robust and flexible correlation analysis technique. It is a function that describes the correlation between random variables. Sklar (1959) was the first to put forward the Copula theory. He pointed out that the continuous joint distribution function of k (k2) can be decomposed into two parts: a Copula function and k marginal distribution, in which the Copula function describes the correlation model between random variables. In this way, we can select the Copula function which represents different related patterns to describe the related patterns of the financial market, and combine the marginal distribution form of the data, and use the Sklar theorem to construct the joint distribution form, which can fully reflect the characteristics of the data. Finally, the risk measurement index is obtained according to the distribution form. Therefore, this paper discusses the application of Copula function in various financial risk measurement from the perspective of application. Under the situation of frequent global financial crisis, financial institutions in various countries must take measures to prevent all kinds of risks in order to ensure financial security. In order to ensure financial security, it is necessary to know what risks may appear in financial activities, so as to prevent and defuse risks. According to the nature and source of financial risk, financial risk mainly faces four kinds of risks: market risk, credit risk, Operational risk and overall risk. Copula theory has many advantages in practical application. Copula function is a good tool to describe the related structure, and it can measure all kinds of complex correlation models and correlation degree of financial market very well. Therefore, this paper discusses the application of Copula function in various financial risk measurement from the perspective of application. The first chapter mainly introduces the background, research significance and domestic and foreign research status. The second part mainly introduces the theory of Copula, including its definition, properties, types and so on. Chapter three introduces the application of copula theory in financial risk measurement. Including the advantages and application of copula theory in financial risk. The fourth chapter introduces the portfolio credit risk measurement model based on copula method, and the fifth chapter introduces the portfolio risk measurement model based on copula method. Chapter 6 is an empirical study of portfolio risk measurement based on copula method. This paper summarizes the research status of Copula function in main financial risks at home and abroad, and points out the application value of Copula function. On the basis of summarizing the basic theory and characteristics of Copula function in detail, the correlation metric derived from Copula function is analyzed deeply. This paper focuses on the application of Copula function in financial risk, credit risk measurement and portfolio risk measurement.
【學(xué)位授予單位】：長江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F224;F830

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