本文選題：Copula-VaR　切入點(diǎn)：金融風(fēng)險(xiǎn)管理　出處：《華中科技大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：近年來，伴隨著信息技術(shù)的發(fā)展，全球化進(jìn)程的腳步也越來越快，經(jīng)濟(jì)全球化使得各個(gè)國家和各個(gè)市場之間的聯(lián)系更為緊密，單一市場波動(dòng)所帶來的影響能夠輕而易舉地跨越市場、跨越國界，對處在全球一體化下的其他國家和市場產(chǎn)生不同程度的影響。而股票市場作為支持一國經(jīng)濟(jì)發(fā)展并控制國家經(jīng)濟(jì)命脈的最重要的資本市場，其重要性不言而喻。因此，研究股票市場的風(fēng)險(xiǎn)并以此來防范其對國家經(jīng)濟(jì)建設(shè)可能帶來的不利影響就顯得尤為重要。 理論部分首先介紹了金融風(fēng)險(xiǎn)的定義和分類，其中VaR因其容易理解、易于操作且能夠量化風(fēng)險(xiǎn)等諸多特點(diǎn)現(xiàn)已成為風(fēng)險(xiǎn)監(jiān)管機(jī)構(gòu)主流的風(fēng)險(xiǎn)測度方法，即便VaR方法有著這些優(yōu)點(diǎn)，但與此同時(shí)其也有不足的地方，于是在此基礎(chǔ)上提出了Copula-VaR方法來對股票市場進(jìn)行風(fēng)險(xiǎn)分析。其次對Copula函數(shù)的性質(zhì)和不同類型Copula函數(shù)的特征進(jìn)行了詳細(xì)的介紹，因?yàn)镃opula在測度資產(chǎn)組合的風(fēng)險(xiǎn)時(shí)是不需要資產(chǎn)收益率服從正態(tài)分布的假設(shè)前提，而且其在結(jié)構(gòu)上能較好的擬合資產(chǎn)之間的聯(lián)合分布，并且也能消除單純的VaR因不能解決資產(chǎn)之間的非線性相關(guān)性所引起的不合理測度風(fēng)險(xiǎn)等特點(diǎn)，因此Copula-VaR方法能得到更加精確的投資組合VaR值。 實(shí)證部分選擇我國股票市場的上海綜合指數(shù)和深圳成分指數(shù)進(jìn)行研究分析。根據(jù)樣本數(shù)據(jù)聯(lián)合密度函數(shù)所具有的特征，本文選用的是具有尾部對稱特征的二元t-Copula函數(shù)作為上證指數(shù)和深成指數(shù)的聯(lián)合分布函數(shù)，利用Copula函數(shù)對其各自變量的求偏導(dǎo)后服從0-1均勻分布的特點(diǎn)，用蒙特卡洛模擬法求出了在不同置信水平下的VaR。最后，變動(dòng)投資組合中上證指數(shù)和深成指數(shù)的比例就得到了一組VaR值并將得到的結(jié)果繪制成曲線，隨著模擬次數(shù)的增加，得到了近似直線的投資比例和組合的VaR值，直線的斜率即是單位上證指數(shù)百分比變動(dòng)所引起的組合VaR值變化，也就是全文的結(jié)論。 文章中所用到的Copula方法是最近發(fā)展起來的一種更加精確的用來測度相關(guān)性的方法，不僅適用于股票市場，對于其他資本市場同樣適用，，另外，這種方法還可以解決多變量相關(guān)性的問題。
[Abstract]:In recent years, with the development of information technology, the pace of globalization has become faster and faster. Economic globalization has made countries and markets more closely linked. The impact of single market volatility can easily cross markets, across borders, The importance of the stock market as the most important capital market to support a country's economic development and control the lifeblood of a country's economy is self-evident. It is very important to study the risk of stock market and prevent its possible adverse effects on national economic construction. The theoretical part first introduces the definition and classification of financial risk. VaR has become the mainstream risk measurement method for risk regulators because of its easy understanding, easy operation and the ability to quantify risk. Even if the VaR method has these advantages, at the same time it has its shortcomings, On this basis, Copula-VaR method is proposed to analyze the risk of stock market. Secondly, the properties of Copula functions and the characteristics of different types of Copula functions are introduced in detail. Because Copula does not need to assume the return of assets from normal distribution when measuring the risk of portfolio, and it can fit the joint distribution of assets better in structure. And it can also eliminate the characteristics of VaR which can not solve the nonlinear correlation between assets caused by the unreasonable risk measurement, so Copula-VaR method can get more accurate portfolio VaR value. In the empirical part, the Shanghai Composite Index and the Shenzhen component Index of China's stock market are selected for research and analysis. According to the characteristics of the sample data associated with the density function, In this paper, the binary t-Copula function with tail symmetry is chosen as the joint distribution function of Shanghai Stock Exchange Index and Deep Index, and the Copula function is used to obtain the partial derivative of their variables from 0-1 uniform distribution. At last, the ratio of Shanghai Stock Exchange Index to Deep Index in the variable portfolio is obtained by Monte Carlo simulation method. Finally, a set of VaR values are obtained and the obtained results are drawn into curves. With the increase of simulation times, The investment ratio and the VaR value of the portfolio are obtained. The slope of the straight line is the change of the VaR value caused by the percentage change of the stock index, which is the conclusion of the whole paper. The Copula method used in this paper is a more accurate method for measuring correlation, which is developed recently. It is applicable not only to the stock market, but also to other capital markets. This method can also solve the problem of multivariate correlation.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F224;F832.51

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