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  本文關(guān)鍵詞：危機傳染背景下資產(chǎn)組合風險模型測試精度比較研究　出處：《西南交通大學》2013年博士論文　論文類型：學位論文

  更多相關(guān)文章： 極值理論 時變Copula函數(shù) 因果關(guān)系效應 風險價值 預期損失

【摘要】：從1929年的美國股市大崩潰開始,國際金融市場歷經(jīng)了數(shù)次危機傳染。而美國次貸危機更因在短時間內(nèi)便震撼國際金融市場,演變成全球性的經(jīng)濟危機且影響深遠,而成為金融危機傳染的代表性事件。國際金融市場危機傳染的頻繁發(fā)生,使得投資者面臨著巨大的風險,同時也對金融風險管理提出了更高的要求。 金融風險管理的基礎(chǔ)與核心在于如何正確地度量風險,由于在金融實務中,投資者往往對資產(chǎn)組合進行投資而非單一資產(chǎn),因而對于資產(chǎn)組合風險的度量更具現(xiàn)實意義。同單一資產(chǎn)的風險評估相比,投資組合的風險評價更為復雜,因為在組合風險的計量過程中,不僅需要考慮組合中單一資產(chǎn)收益的波動率模型,還必須考慮到組合中各個資產(chǎn)間的相依關(guān)系。然而金融資產(chǎn)間的相關(guān)性錯綜復雜,所以如何正確地選擇和運用風險度量工具就成為組合風險評價中最重要的一個環(huán)節(jié)。 本文以美國SP500指數(shù)、日本日經(jīng)225指數(shù)、中國上證綜指和香港恒生指數(shù)作為研究對象,將四類時變Copula-EVT模型作為核心研究方法,以美國次貸危機為代表的金融危機傳染作為一條貫穿始終的研究主線,層層推進四個關(guān)鍵問題： ·危機傳染是否顯著地影響了股市間尾部極值風險傳導的強度? ·股市間風險傳導的方向是否發(fā)生明顯的變化? ·危機爆發(fā)后,對于二元資產(chǎn)組合及多元資產(chǎn)組合的多頭頭寸與空頭頭寸,各類風險模型假定下的VaR風險價值模型和ES預期損失模型的測度精度是否顯著改變?其變化狀況是否有所不同? ·哪些因素將影響到VaR模型和ES模型的預測準確度?其影響的結(jié)果怎樣? 為此,本文在各股指收益的標準殘差序列的基礎(chǔ)上,結(jié)合EVT極值理論,構(gòu)建邊緣分布,分別運用四類時變Copula函數(shù)構(gòu)建各個資產(chǎn)組合的聯(lián)合分布,采用擬合效果相對較好的時變t Copula-GJR-EVT模型,得到危機爆發(fā)前后股市間的極值動態(tài)相依系數(shù)；通過時變SJC-Copula-EVT模型獲得股市間的上尾和下尾極值相關(guān)系數(shù)。運用格蘭杰因果檢驗的方法,分析了金融危機傳染對于股市間風險傳導方向產(chǎn)生的影響。實證研究結(jié)果表明,危機的爆發(fā),對于股市間極值風險傳遞的強度和風險傳導的方向產(chǎn)生了很大的影響。次貸危機發(fā)生以后,國際股市間極值風險傳染的程度普遍增強,其時變特征也非常明顯。從股市風險傳導的方向上看：次貸危機爆發(fā)以前,股指間的風險主要匯集于紐約股市,而三大亞洲股市,即中國滬市、香港股市和東京股市間不存在風險傳導關(guān)系。次貸危機爆發(fā)后,股市間風險傳導的途徑和方向發(fā)生了明顯的變化：不僅美國紐約股市與其他股市間形成了雙向風險傳導關(guān)系,亞洲股市間也顯現(xiàn)出密切而復雜的風險傳導格局,中國股市與國際股市的極值風險關(guān)聯(lián)度顯著增強。 這些鮮明的特點,無疑將影響到投資組合風險模型的測度準確度。在此背景下,本文將四個股指收益進行組合,構(gòu)造了二元資產(chǎn)組合及多元資產(chǎn)組合,基于四類時變Copula-EVT模型和DCC-GARCH模型,分別針對多頭頭寸和空頭頭寸,建立了VaR模型和ES模型,并運用Backtesting方法進行后驗分析,對比研究了危機以后各類風險模型測度精度的變化狀況。實證結(jié)果表明：第一,次貸危機爆發(fā)后,金融市場間極值風險正向相關(guān)的程度顯著增強,分散化投資的作用在一定程度上被削弱,資產(chǎn)組合VaR風險價值模型的測度精度有所降低；然而在某些狀況下,預期損失ES模型的測度精度卻在危機后有一定程度的提高。第二,無論是VaR模型還是ES模型,基于時變Copula-EVT構(gòu)建的風險模型,其測度精度在總體上高于DCC-GARCH風險模型。第三,邊緣分布模型的選擇,對于時變Copula-EVT風險模型的測度效果具有重要影響。第四,由不同類型的時變Copula函數(shù)構(gòu)造的風險模型,對于資產(chǎn)組合風險的預測準確度有所不同。綜合來看,危機爆發(fā)以后,時變SJC-Copula-EVT-VaR模型與時變tCopula-EVT-ES模型的測度精度均相對較高,這進一步表明,次貸危機對于資產(chǎn)組合風險模型的測度效果產(chǎn)生了巨大沖擊,善于刻畫變量間非對稱性、厚尾性相依特征的模型顯現(xiàn)出較強的測度優(yōu)勢。盡管如此,對于資產(chǎn)組合的風險測度,仍需根據(jù)資產(chǎn)組合的分布特征以及科學的對比研究來靈活地選擇合適的風險模型。 在經(jīng)濟全球化的今天,無論是從時間還是空間的角度,金融危機傳染都日趨嚴重。美國次貸危機爆發(fā)以來,金融市場的運行環(huán)境更加錯綜復雜,金融風險極容易在各個市場之間相互傳染。在金融危機頻發(fā)的背景下進行投資組合,應特別注意防范組合投資風險。對于資產(chǎn)組合的風險評估,應嘗試構(gòu)建多個風險模型,選擇測度準確度相對較高的模型進行風險評估,并將VaR模型與ES模型結(jié)合使用。此外,對投資組合的風險評估還應立足于動態(tài)的角度,因為尾部極值風險傳導具有時變特性,所以在使用靜態(tài)類風險評估方法時必須謹慎,以防錯誤評估資產(chǎn)組合的風險,同時,必須及時有效地采取相應的止損措施,以防范極端金融事件導致股市同時暴跌而對組合資產(chǎn)造成巨額虧損。
[Abstract]:From the beginning of 1929, the U.S. stock market collapse, the international financial market has experienced several crisis. While the U.S. subprime mortgage crisis because it shocked the international financial market in a short period of time, evolved into a global economic crisis and a far-reaching influence, and become the representative of financial crisis incidents. The frequent crisis of international financial market contagion, the investors face a huge risk, but also put forward higher requirements on financial risk management.
The basis and core of financial risk management is how to correctly measure the risk, because in the field of finance, investors tend to portfolio investment rather than a single asset and portfolio risk measurement for more practical significance. The risk assessment with single assets compared to the risk evaluation of portfolio is more complicated, because the measurement in the process of portfolio risk, not only need to consider a single asset return portfolio volatility in the model must also take into account the dependence between the individual asset portfolio. However, the correlation between financial assets complicated, so how to correctly select and use of risk measurement tools has become one of the most important link in the evaluation of portfolio risk.
In this paper, the SP500 index, Japan's Nikkei 225 index, Chinese Shanghai Composite Index and Hongkong's Hang Seng Index as the research object, the four time varying Copula-EVT model as the core research method, sub loan crisis in the United States as the representative of the financial crisis as a main line through all the four key problems on promoting layers:
Does the crisis contagion significantly affect the intensity of the tail extremum risk transmission between the stock markets?
Is there a significant change in the direction of risk conduction between stock markets?
After the outbreak of the crisis, did the measurement accuracy of VaR risk value model and ES expected loss model change significantly under the assumption of all kinds of risk models for two asset portfolios and multiple asset portfolios' multi position and short positions? Are there any differences in their accuracy?
What factors will affect the prediction accuracy of the VaR model and the ES model? What is the result of its impact?
Therefore, based on the standard error sequence of the stock index on the EVT combined with the extreme value theory, constructing marginal distribution and joint distribution using the four class construction of each portfolio Copula function, the fitting result of time-varying t Copula-GJR-EVT model, obtained before and after the stock market crisis between the extreme dynamic dependence coefficient; through time varying SJC-Copula-EVT model to obtain the stock market between the upper and lower tail extreme correlation coefficient. By using the method of Grainger causality test, analysis of the financial crisis contagion effect on stock market risk conduction direction. The empirical results show that the outbreak of the crisis, the strength and the extreme risk transfer between stock market risk conduction in the direction of the great the effects of the subprime mortgage crisis. Later, the international stock market risk contagion degree is enhanced, the time variation characteristics are also very obvious. From the stock market risk conduction direction: before the outbreak of the subprime crisis, the risk of the stock index mainly collects in the New York stock market, and the three major Asian stock markets, namely Chinese Shanghai, no risk conduction relationship between Hongkong stock market and Tokyo stock market. After the outbreak of the subprime crisis, change ways and direction of stock market risk conduction not only the New York stock market and other markets are formed between the two-way relationship between risk conduction, Asian stock markets also showed the risk conduction pattern close and complex, China stock market and international stock market related extreme risk is significantly increased.
These distinctive features, will undoubtedly affect the measure accuracy of portfolio risk model. In this context, the four stock index returns are combined to construct two yuan asset portfolio and multi asset portfolio, four time varying Copula-EVT model and DCC-GARCH model based on the address of the long and short positions, the establishment of VaR model and ES model, and analyzed the test by using the Backtesting method, a comparative study of the changes of all kinds of crisis risk model measurement accuracy. The empirical results show that: first, after the outbreak of the subprime crisis, a positive extreme risk related financial city significantly enhanced, diversification of investment effect is weakened to a certain extent, measure the accuracy of portfolio VaR risk value model is reduced; however, in some cases, measurement accuracy of ES model is the expected loss in the wake of the crisis to a certain extent Increase. Second, either VaR model or ES model, based on time-varying risk model of construction of Copula-EVT, the measurement accuracy is generally higher than that in the DCC-GARCH risk model. Third, the marginal distribution model, measurement model for the time-varying Copula-EVT risk model has important influence. Fourth, the risk from different types of time-varying model the Copula function is constructed, the prediction accuracy for portfolio risk is different. In general, after the crisis, the time-varying measurement accuracy of SJC-Copula-EVT-VaR model and time-varying tCopula-EVT-ES model are relatively high, this further indicates that the subprime crisis has had a huge impact on the effect of portfolio risk measure model, good asymmetric variables of heavy tailed dependent feature model shows strong advantage measure. Even so, the risk measure of portfolio assets, according to the needs The distribution characteristics of the combination and the scientific comparison study to choose the appropriate risk model flexibly.
In the economic globalization today, whether it is from the angle of time and space, the contagion of financial crisis are becoming more serious. Since the outbreak of the subprime crisis, the operating environment of financial market more perplexing, financial contagion in interaction between various markets easily. Investment portfolio in the financial crisis under the background of frequent, should pay special attention to prevent the combination investment risk. Risk assessment for the portfolio, we should try to construct a multi risk model, selection of measurement accuracy higher relative risk assessment model, and the combination of VaR model and ES model. In addition, the risk assessment of the portfolio also should be based on the dynamic perspective, because sometimes the varying characteristics with tail extreme risk conduction, so in assessing the risk of using a static class method must be careful to prevent error risk, portfolio assessment at the same time, must be timely and effectively take corresponding The stop damage measures to prevent the stock market plunge at the same time to prevent the extreme financial incidents caused huge losses to the portfolio.

【學位授予單位】：西南交通大學
【學位級別】：博士
【學位授予年份】：2013
【分類號】：F224;F830.91

【參考文獻】

相關(guān)期刊論文 前10條

1 馬興杰;;有偏分布下的VaR估計方法研究[J];北京理工大學學報(社會科學版);2008年05期

2 楊湘豫;崔迎媛;;基于Copula-GARCH-EVT的中國開放式基金投資組合風險度量[J];財經(jīng)理論與實踐;2009年05期

3 曾健,陳俊芳;Copula函數(shù)在風險管理中的應用研究——以上證A股與B股的相關(guān)結(jié)構(gòu)分析為例[J];當代財經(jīng);2005年02期

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

5 李悅;程希駿;;上證指數(shù)和恒生指數(shù)的copula尾部相關(guān)性分析[J];系統(tǒng)工程;2006年05期

6 羅付巖;鄧光明;;基于時變Copula的VaR估計[J];系統(tǒng)工程;2007年08期

7 楊湘豫;夏宇;;基于Copula方法的開放式基金投資組合的VaR研究[J];系統(tǒng)工程;2008年12期

8 楊湘豫;周再立;;基于Copula-TARCH的開放式基金投資組合風險的實證分析[J];系統(tǒng)工程;2011年06期

9 黃騰飛;李幫義;熊季霞;;中國期貨市場的混沌性檢驗[J];系統(tǒng)工程;2012年01期

10 張志波,齊中英;基于VAR模型的金融危機傳染效應檢驗方法與實證分析[J];管理工程學報;2005年03期

相關(guān)博士學位論文 前10條

1 陳麗娟;中國開放式基金組合的市場風險度量[D];東華大學;2011年

2 劉瓊芳;基于Copula理論的金融時間序列相依性研究[D];重慶大學;2010年

3 解鳳敏;經(jīng)濟全球化下中國金融危機壓力預警研究[D];中國礦業(yè)大學;2011年

4 王魯非;金融市場風險的尾部估計和極值度量[D];吉林大學;2011年

5 牟曉云;金融危機對中日韓三國經(jīng)濟的影響及政府的對策效應研究[D];吉林大學;2011年

6 林宇;動態(tài)極值VaR測試的準確性及VaR因果關(guān)系研究[D];西南交通大學;2008年

7 任仙玲;基于Copula理論的金融市場相依結(jié)構(gòu)研究[D];天津大學;2008年

8 劉晶;極值統(tǒng)計理論及其在金融風險管理中的應用[D];天津大學;2008年

9 趙麗琴;基于Copula函數(shù)的金融風險度量研究[D];廈門大學;2009年

10 易文德;基于COPULA理論的金融風險相依結(jié)構(gòu)模型及應用研究[D];西南交通大學;2010年

，

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