本文關(guān)鍵詞：基于t-Copula-EGARCH模型的滬深股市風(fēng)險(xiǎn)值的研究　出處：《西南財(cái)經(jīng)大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： VaR t-Copula EGARCH模型 事后檢驗(yàn)

【摘要】：隨著金融衍生產(chǎn)品與信息技術(shù)的發(fā)展,全球金融市場(chǎng)的交易量規(guī)模越來越大。然而金融市場(chǎng)的欣欣向榮,也潛藏著巨大的風(fēng)險(xiǎn),如2007年的美國次貸危機(jī)、2009年底發(fā)生的希臘債務(wù)危機(jī)等。金融危機(jī)爆發(fā)給投資者帶來了巨大的損失,因此如何有效的計(jì)算金融資產(chǎn)的風(fēng)險(xiǎn)價(jià)值成為各個(gè)金融機(jī)構(gòu)面臨的很重要的問題。通常,我們計(jì)算金融資產(chǎn)的風(fēng)險(xiǎn)值有三類主要方法：敏感性分析法、歷史收益模擬法、蒙特卡洛模擬方法等。單個(gè)金融資產(chǎn)的VaR易于計(jì)算,而多個(gè)金融資產(chǎn)的聯(lián)合分布下VaR的計(jì)算比較困難。以往,我們通常假定多個(gè)金融資產(chǎn)服從線性相關(guān)性,然后計(jì)算出風(fēng)險(xiǎn)值。然而多個(gè)金融資產(chǎn)之間并不服從線性相關(guān)性,因此本文引入Copula理論來描述多個(gè)金融資產(chǎn)的相關(guān)性。在實(shí)證部分,我們先對(duì)滬深股市2008年1月15號(hào)到2012年8月20號(hào)這1200對(duì)數(shù)據(jù)進(jìn)行時(shí)間序列分析發(fā)現(xiàn)EGARCH模型可以較好的描述滬深股市的波動(dòng)性特征與杠桿性,然后采用歐式平方距離法選取出t-Copula函數(shù)來描述滬深股市的相依性,最后分別用傳統(tǒng)的蒙特卡洛模擬方法、t-Copula-GARCH模型、t-Copula-EGARCH模型分別來建模,對(duì)求得的VaR進(jìn)行比較。并對(duì)各個(gè)結(jié)果進(jìn)行事后檢驗(yàn)發(fā)現(xiàn)t-Copula-EGARCH在這幾種方法求出的VaR最符合實(shí)際情況。
[Abstract]:With the development of financial derivatives and information technology, the trading volume of the global financial market is becoming larger and larger. However, the prosperity of the financial market has hidden huge risks, such as the subprime mortgage crisis in 2007 in the United States. In end of 2009, the Greek debt crisis occurred. The financial crisis brought huge losses to investors. Therefore, how to effectively calculate the risk value of financial assets has become a very important problem faced by various financial institutions. Generally, there are three main methods to calculate the risk value of financial assets: sensitivity analysis. Historical income simulation method, Monte Carlo simulation method and so on. The VaR of a single financial asset is easy to calculate, but the calculation of VaR under the joint distribution of multiple financial assets is more difficult. We usually assume that multiple financial assets are dependent on linear correlation and then calculate the value of risk. However, multiple financial assets are not subject to linear correlation. Therefore, this paper introduces Copula theory to describe the correlation of multiple financial assets. From January 15th 2008 to August 20th 2012, we analyze the time series of Shanghai and Shenzhen stock market, and find that EGARCH model can describe the volatility of Shanghai and Shenzhen stock market. Characteristics and leverage. Then using the Euclidean square distance method to select t-Copula function to describe the dependence of Shanghai and Shenzhen stock market. Finally, the traditional Monte Carlo simulation method is used to simulate the t-Copula-GARCH model. The t-Copula-EGARCH model is modeled separately. The VaR obtained is compared and the VaR obtained by t-Copula-EGARCH is found to be the most suitable for the actual situation.
【學(xué)位授予單位】：西南財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F832.51;F224

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本文編號(hào)：1410058