本文關(guān)鍵詞： 風險價值 TGARCH模型 POT模型 Copula函數(shù)　出處：《中央民族大學》2012年碩士論文　論文類型：學位論文

【摘要】：金融時間序列具有尖峰厚尾性、自相關(guān)性、波動集簇性和波動非對稱性等特征,所以本文基于極值理論和GARCH理論,利用TGARCH-POT模型分別建立了上證指數(shù)和深圳成指的邊緣分布函數(shù)。 在經(jīng)濟全球化的背景下,金融市場不是封閉和孤立的,不同市場之間,或者不同資產(chǎn)之間,往往存在相互影響和波動的相關(guān)關(guān)系。描述兩個市場相關(guān)結(jié)構(gòu)的傳統(tǒng)做法是選取t-Copula函數(shù),但t-Copula函數(shù)具有對稱性,對于變量間的非對稱尾部相關(guān)并不適合。在阿基米德Copula函數(shù)中,Gumbel Copula和Clayton Copula函數(shù)的密度函數(shù)都具有非對稱性,能夠很好的描述市場間的尾部相關(guān)性。因此本文考慮從Gumbel Copula和Clayton Copula函數(shù)中選取一個適當?shù)腃opula函數(shù)來描述滬深股市的相關(guān)結(jié)構(gòu)。 我們選取上證指數(shù)和深圳成指2002年至2011年10年的數(shù)據(jù)做實證分析,運用Copula蒙特卡洛模擬計算出來的VaR與真實值比較得到2010年和2011年的不同置信水平下的失效天數(shù)。從中可以看到,(1) TGARCH-POT-Copula相比GARCH-t-Copula有效,這說明了利用極值理論中的POT模型改進了邊緣分布,而GARCH-t-Copula顯然低估了風險。(2)在201O年和2011年,TGARCH-POT-Gumbel Copula相比TGARCH-POT-Clayton Copula有效,主要原因可能是經(jīng)過08年金融危機后,經(jīng)濟開始復蘇,投資者信心開始增強,所以Gumbel Coupla函數(shù)比較適合描述這兩個市場在這期間的相關(guān)結(jié)構(gòu)。
[Abstract]:Financial time series have the characteristics of sharp peak and thick tail, autocorrelation, volatility cluster and volatility asymmetry. Therefore, based on the extreme value theory and GARCH theory, the TGARCH-POT model is used to establish the edge distribution function of Shanghai stock index and Shenzhen index respectively. In the context of economic globalization, financial markets are not closed and isolated, between different markets, or between different assets. The traditional way to describe the structure of two markets is to choose t-Copula function, but t-Copula function has symmetry. It is not suitable for asymmetric tail correlation between variables. In Archimedes Copula function, the density functions of Gumbel Copula and Clayton Copula are both asymmetric. Therefore, this paper considers choosing an appropriate Copula function from the Gumbel Copula and Clayton Copula functions to describe the relevant structure of Shanghai and Shenzhen stock markets. We choose the data of Shanghai Stock Exchange Index and Shenzhen Cheng Index from 2002 to 2011 for empirical analysis. By comparing the VaR calculated by Copula Monte Carlo simulation with the real value, the failure days of 2010 and 2011 at different confidence levels are obtained. It can be seen that TGARCH-POT-Copula is more effective than GARCH-t-Copula. This shows that the marginal distribution is improved by using the POT model in extreme value theory, while GARCH-t-Copula obviously underestimated the risk.) in 2010 and 2011, TGARCH-POT-Gumbel Copula was more efficient than TGARCH-POT-Clayton Copula, probably because the economy began to recover after the 2008 financial crisis. Investor confidence is beginning to grow, so the Gumbel Coupla function is more appropriate to describe the structure of the two markets during this period.
【學位授予單位】：中央民族大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：F224;F832.51

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本文編號：1503489