本文關(guān)鍵詞：基于時(shí)變混合Copula模型的市場(chǎng)間極端風(fēng)險(xiǎn)溢出度量　出處：《浙江工商大學(xué)》2012年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： Copula CoVaR 極端風(fēng)險(xiǎn)溢出 返回測(cè)試

【摘要】：2007年美國(guó)次貸危機(jī)爆發(fā)并迅速蔓延至其它金融市場(chǎng),最終導(dǎo)致了一場(chǎng)席卷全球的金融危機(jī)。這一事實(shí)充分表明全球金融市場(chǎng)并不是相互孤立的,隨著經(jīng)濟(jì)全球化和金融一體化的迅猛發(fā)展,全球金融市場(chǎng)之間的相互依存性日益增加,金融風(fēng)險(xiǎn)的表現(xiàn)形式也日趨復(fù)雜化和多樣化,在這樣的形勢(shì)中缺乏對(duì)極端條件下金融市場(chǎng)之間風(fēng)險(xiǎn)溢出的考量,可能會(huì)在很大程度上低估金融市場(chǎng)的風(fēng)險(xiǎn)水平,造成災(zāi)難性的后果。如何有效地度量金融市場(chǎng)之間的極端風(fēng)險(xiǎn)溢出水平成為了時(shí)下風(fēng)險(xiǎn)管理機(jī)構(gòu)和金融監(jiān)管當(dāng)局亟須解決的問題。 隨著金融創(chuàng)新的飛速發(fā)展,尤其是近年來,金融風(fēng)險(xiǎn)原有的一些分析方法如基于線性相關(guān)的分析方法等已經(jīng)不再能夠適應(yīng)這一要求,而一種新的,可以用于研究非線性、非對(duì)稱相依關(guān)系的Copula方法,在國(guó)際上被迅速應(yīng)用到金融市場(chǎng)研究的各個(gè)領(lǐng)域,成為資產(chǎn)定價(jià)、金融風(fēng)險(xiǎn)監(jiān)管、管理與防范以及保險(xiǎn)定價(jià)的有效工具。本文嘗試性地提出了一種時(shí)變混合Copula模型,這種模型能夠在分布的不同區(qū)域分別選擇不同種類的時(shí)變Copula函數(shù)對(duì)金融變量進(jìn)行描述。模型使用時(shí)變Gumbel Copula函數(shù)對(duì)聯(lián)合分布上尾部的相依關(guān)系進(jìn)行描述,使用時(shí)變Rotated Gumbel Copula函數(shù)對(duì)聯(lián)合分布下尾部的相依關(guān)系進(jìn)行刻畫,在分布的其他區(qū)域則使用時(shí)變混合Copula函數(shù)來捕捉相依關(guān)系的變化。這種模型不僅克服了單—Copula函數(shù)只適于描述分布特定區(qū)域相依性的缺陷,相較于混合Copula函數(shù),這種模型在不同時(shí)期的相依參數(shù)還具有時(shí)變性,特別適用于研究非常時(shí)期的金融變量建模問題。時(shí)變混合Copula模型不僅能夠捕捉變量之間相依關(guān)系的變化,還可以捕捉到相依模式的變化,特別是在非常時(shí)期,更加適用于對(duì)金融變量聯(lián)合分布建模。本文基于時(shí)變混合Copula模型,提出了一種新的、針對(duì)極端風(fēng)險(xiǎn)溢出指標(biāo)CoVaR進(jìn)行估計(jì)的方法,并使用這種方法對(duì)美國(guó)股票市場(chǎng)、中國(guó)大陸股票市場(chǎng)、英國(guó)股票市場(chǎng)以及香港股票市場(chǎng)之間的極端風(fēng)險(xiǎn)溢出效應(yīng)做了實(shí)證分析研究。最后通過返回測(cè)試檢驗(yàn)表明：基于Normal Copula、Time-Varying Normal Copula、Gumbel Copula、Time-Varying Gumbel Copula以及混合(Mixed) Copula模型計(jì)算得到的市場(chǎng)間極端風(fēng)險(xiǎn)溢出指標(biāo)CoVaR均不能通過檢驗(yàn),均在不同程度上低估了市場(chǎng)間的風(fēng)險(xiǎn)溢出效應(yīng),不能作為CoVaR計(jì)算的有效工具。而基于時(shí)變混合Copula的模型明顯優(yōu)于其它模型,使用該模型計(jì)算得到的金融市場(chǎng)間極端風(fēng)險(xiǎn)溢出指標(biāo)CoVaR全部通過了檢驗(yàn),因此證實(shí)了本文提出的時(shí)變混合Copula模型在度量金融市場(chǎng)間極端風(fēng)險(xiǎn)溢出方面具有顯著的優(yōu)越性,可以將其作為度量金融市場(chǎng)間極端風(fēng)險(xiǎn)溢出水平的有效工具。
[Abstract]:In 2007, the subprime mortgage crisis in the United States broke out and spread to other financial markets, which eventually led to a financial crisis sweeping the whole world. This fact fully shows that the global financial markets are not isolated from each other. With the rapid development of economic globalization and financial integration, the interdependence of global financial markets is increasing, and the manifestations of financial risks are becoming more and more complicated and diversified. In such a situation, the lack of consideration of risk spillover between financial markets under extreme conditions may greatly underestimate the risk level of financial markets. How to effectively measure the level of extreme risk spillover between financial markets has become an urgent problem to be solved by risk management institutions and financial regulatory authorities. With the rapid development of financial innovation, especially in recent years, some of the original financial risk analysis methods, such as linear correlation analysis methods can no longer adapt to this requirement, and a new. The Copula method, which can be used to study the nonlinear and asymmetric dependency, has been rapidly applied to various fields of financial market research, such as asset pricing and financial risk supervision. This paper presents a time-varying mixed Copula model. The model can select different kinds of time-varying Copula functions to describe the financial variables in different regions of the distribution. The model uses time-varying Gumbel. The Copula function describes the tail dependency on the joint distribution. The time-varying Rotated Gumbel Copula function is used to characterize the tail dependency under joint distribution. In other regions of the distribution, the time-varying mixed Copula function is used to capture the variation of dependency. This model not only overcomes the defect that the single-Copula function is only suitable for describing the dependence of a particular region of the distribution. . Compared with the mixed Copula function, the dependent parameters of this model are time-varying in different periods. The time-varying mixed Copula model can not only capture the changes of the dependent relationships between variables, but also capture the changes of dependent patterns. Especially in the unusual period, it is more suitable for modeling the joint distribution of financial variables. Based on the time-varying mixed Copula model, a new model is proposed in this paper. The method of estimating the extreme risk spillover index (CoVaR), and using this method in the US stock market, the Chinese mainland stock market. The extreme risk spillover effect between the UK stock market and Hong Kong stock market is analyzed empirically. Finally, the result of return test shows that: based on Normal Copula. Time-Varying Normal Copula,Gumbel Copula. Time-Varying Gumbel Copula and mixed. The Copula model calculated the inter-market extreme risk spillover index CoVaR can not pass the test. The risk spillover effect between markets is underestimated to some extent, and can not be used as an effective tool for CoVaR calculation. However, the model based on time-varying mixed Copula is obviously superior to other models. Using this model to calculate the financial market risk spillover index CoVaR all passed the test. Therefore, it is proved that the time-varying mixed Copula model proposed in this paper has significant advantages in measuring the extreme risk spillover between financial markets. It can be used as an effective tool to measure the level of extreme risk spillover between financial markets.
【學(xué)位授予單位】：浙江工商大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F830.91;F224

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