本文關鍵詞：基于尾部變結(jié)構(gòu)Copula模型的股市波動溢出效應研究　出處：《浙江工商大學》2013年碩士論文　論文類型：學位論文

  更多相關文章： Copula 尾部變結(jié)構(gòu) 相依結(jié)構(gòu) 波動溢出效應

【摘要】：隨著中國經(jīng)濟的快速發(fā)展和市場的逐步開放,中國股市受到世界主要股市的傳染和影響日益加深。近年來,由于金融市場波動的日益劇烈與金融危機的頻發(fā),各國金融市場之間的波動溢出效應研究越來越受到國內(nèi)外學者的密切關注。以往傳統(tǒng)的相關關系度量方法只能度量變量間的線性相關關系,越來越不能適應人們對于相關性度量的需要,因此,本文引入可以度量非線性相關關系的度量工具一Copula函數(shù)來建立非線性相關性模型。 以往相關研究較多的是運用單一Copula函數(shù),并不能全面地描述金融變量間的相依結(jié)構(gòu)。但是,相對單一Copula函數(shù),混合Copula函數(shù)可以包含不同類型的Copula,能夠更加靈活地度量變量之間的相依性。基于此,本文通過線性組合方式構(gòu)建一個具有尾部變結(jié)構(gòu)的混合Copula模型。該混合Copula函數(shù)不僅能度量變量之間的上尾和下尾相關關系,還能同時度量變量間的相依程度和相依模式。同時,本文另一創(chuàng)新之處是考慮了混合Copula模型權重參數(shù)的時變性,而Copula函數(shù)參數(shù)是不變的,權重參數(shù)的時變性能夠更靈活地捕捉到變量之間相依模式的動態(tài)性。 本文在數(shù)據(jù)上選取2000年1月至2013年1月上證綜指、香港恒生指數(shù)、美國標普500指數(shù)和日經(jīng)225指數(shù),研究中國股市與這些股市之間相依性的變化以及是否存在風險溢出效應的特征。首先使用AR(1)-GARCH(1,1)-t模型來模擬指數(shù)收益率序列的邊際分布,然后使用靜態(tài)formal Copula, Gumbel Copula,Clayton Copula, SJC Copula函數(shù)和本文構(gòu)建的具有尾部變結(jié)構(gòu)特征的時變混合Copula函數(shù)來對中國大陸股市與國際主要股市間的風險傳染及相依特征進行建模,并對實證結(jié)果進行分析。實證結(jié)果表明,十多年來,在中國資本市場逐步對外開放進程中,上證指數(shù)與國際主要指數(shù)之間的聯(lián)動性并不強,上證綜指對國際主要股市的影響力還較弱。不過,雖然中國股市與其他四個股市間的尾部相依程度較低,但是當市場在面對極端情況時,例如2008年的次貸危機,仍然有同時發(fā)生大起或大落的可能,這在一定程度上反映了大的金融危機爆發(fā)時對全球股市的影響,特別是由美國引起的金融危機。
[Abstract]:With the rapid development of China gradually open economy and market, the stock market has been the world's major stock markets Chinese infectious and influence is growing. In recent years, due to the frequent fluctuations in the financial market is becoming increasingly fierce and the financial crisis, the volatility spillover effect between financial markets research pay more and more attention of scholars at home and abroad. The past relationship the traditional measurement method can only measure the linear relationship between the variables, increasingly unable to meet the needs of the people for, so we introduce the correlation metric, a measure tool can measure the nonlinear relationship between the Copula function to establish the nonlinear correlation model.
The more research is the use of a single Copula function, and can not fully describe the dependence structure of financial variables. However, relative to a single Copula function, mixed Copula function can contain different types of Copula, can be more flexible to measure the dependency between variables. Based on this, this paper constructs a hybrid Copula model with variable tail structure by linear combination method. The mixed Copula function can not only measure the variables between the upper and lower tail correlation, but also measure the dependence between variables and dependent mode. At the same time, this is another innovation of the modified hybrid Copula model weight parameters, and the parameters of Copula function is constant. Time-varying weight parameters can be more flexible to capture the dynamic dependencies between variables of the model.
In this paper, from January 2000 to January 2013 the Shanghai Composite Index in the data selection, the Hongkong Hang Seng Index, the S & P 500 and the Nikkei 225 index, the stock market and the characteristics between China stock dependent changes and the existence of Risk Spillover effect. The first use of AR (1) -GARCH (1,1) -t model to simulate the marginal distribution of index returns sequence, and then use the static formal Copula, Gumbel Copula, Clayton Copula, SJC Copula function and the tail has the characteristics of variable structure and time-varying mixed Copula function on the mainland stock market and the model dependent characteristics and risk contagion between Chinese main international stock markets, and analyzed the results of empirical analysis. The empirical results show that, more than 10 in China years, the capital market gradually in the process of opening up, the linkage between the Shanghai index and international index is not strong, the Shanghai Composite Index of major international The influence of the stock market is still relatively weak. However, although the stock market and the other four Chinese tail stock market's dependence degree is low, but when the market in the face of extreme conditions, such as the 2008 subprime crisis, there are still large or occur at the same time big potential, impact on the global stock market to a certain extent reflects the outbreak of the financial crisis, especially the United States caused by the financial crisis.

【學位授予單位】：浙江工商大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：F832.51;F224

【參考文獻】

相關期刊論文 前10條

1 田光;張瑞鋒;;基于Copula的股票市場波動溢出分析[J];財經(jīng)理論與實踐;2011年06期

2 韋艷華,張世英;金融市場的相關性分析——Copula-GARCH模型及其應用[J];系統(tǒng)工程;2004年04期

3 韋艷華;齊樹天;;亞洲新興市場金融危機傳染問題研究——基于Copula理論的檢驗方法[J];國際金融研究;2008年09期

4 黃在鑫;覃正;;中美主要金融市場相關結(jié)構(gòu)及風險傳導路徑研究——基于Copula理論與方法[J];國際金融研究;2012年05期

5 劉平;杜曉蓉;;對金融危機風險傳染效應的比較研究——基于靜態(tài)與動態(tài)copula函數(shù)的分析[J];經(jīng)濟經(jīng)緯;2011年03期

6 趙留彥,王一鳴;A、B股之間的信息流動與波動溢出[J];金融研究;2003年10期

7 孫清;蔡則祥;;基于COPULA函數(shù)的信貸資產(chǎn)風險估計模型[J];南京社會科學;2007年07期

8 韋艷華,張世英,孟利鋒;Copula理論在金融上的應用[J];西北農(nóng)林科技大學學報(社會科學版);2003年05期

9 李勇;李傳樂;;風險傳染效應在牛市、熊市中的異化現(xiàn)象——來自A+H雙重上市公司的證據(jù)[J];金融發(fā)展研究;2008年11期

10 孫彬;楊朝軍;于靜;;基于copula函數(shù)的國際證券市場傳染效應實證分析[J];上海交通大學學報;2009年04期

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