本文關(guān)鍵詞：基于Copula方法在開放式基金投資組合風險管理中的應用研究　出處：《湖南大學》2012年碩士論文　論文類型：學位論文

  更多相關(guān)文章： 開放式基金 時變Copula函數(shù) VaR 投資組合

【摘要】：針對傳統(tǒng)的相關(guān)系數(shù)矩陣并不能很好的描述金融資產(chǎn)間的非線性相依結(jié)構(gòu)，本文將時變Copula函數(shù)與GARCH模型相結(jié)合，建立Copula-GARCH模型研究開放式基金投資組合的風險和相依結(jié)構(gòu)。該模型可以有效規(guī)避由于傳統(tǒng)線性相依結(jié)構(gòu)假定所帶來的模型設定誤差，同時還考慮了相依性的動態(tài)性變化，以便于更好的刻畫資產(chǎn)間相依結(jié)構(gòu)的時變性特征。 本文首先對開放式基金的概念以及內(nèi)涵進行闡述，同時比較已有的度量市場收益風險的方法。其次應用自相關(guān)檢驗對開放式基金凈值收益時間序列進行檢驗，以判別開放式基金收益時間序列是否存在高階序列相關(guān)性。并應用ARCH-LM檢驗對該時間序列進行檢驗，判別是否具有高階ARCH效應，并以此為依據(jù)，選擇適當?shù)腉ARCH類模型對開放式基金收益的邊緣分布進行描述。為了表示所假定的分布能對開放式基金收益時間序列的分布特征進行較好的刻畫，應用K-S檢驗以及A-D檢驗對開放式基金收益序列邊緣分布模型的擬合優(yōu)度進行檢驗。再次，運用不同的時變Copula函數(shù)對開放式基金資產(chǎn)間的相依性關(guān)系進行描述。最后，將蒙特卡羅模擬技術(shù)與時變Copula函數(shù)相結(jié)合，對開放式基金組合風險進行VaR測度，以反映開放式基金投資組合風險變化情況與其資產(chǎn)在不同風險情況下可能損失的概率。我們選取了有代表性的三支開放式基金作為研究對象，，發(fā)現(xiàn)時變Clayton Copula-AR(p)-GARCH模型所估計的VaR值更為準確，并且能夠在各個置信水平下較全面地覆蓋最大損失風險，從而達到控制風險的目的。 本文的創(chuàng)新主要體現(xiàn)在：所構(gòu)建的模型能有效地避免金融時間序列所普遍存在的尖峰厚尾以及有偏性特征所造成的模型設定誤差；本文通過擬合優(yōu)度檢驗確定最優(yōu)Copula類型，以確保實證結(jié)果的穩(wěn)健性以及準確性。
[Abstract]:Because the traditional correlation coefficient matrix can not well describe the nonlinear dependent structure between financial assets, this paper combines the time-varying Copula function with the GARCH model. Copula-GARCH model is established to study the risk and dependent structure of open-end fund portfolio. This model can effectively avoid the model setting error caused by the traditional linear dependent structure assumption. At the same time, the dynamic variation of dependency is considered in order to better describe the time-varying characteristics of the dependent structure of assets. This paper first describes the concept and connotation of open-end funds, and compares the existing methods to measure the market return risk. Secondly, we use autocorrelation test to test the time series of net income of open-end funds. In order to determine whether the open-end fund income time series has higher order sequence correlation, and use ARCH-LM test to test the time series, judge whether there is high order ARCH effect. And based on it. Select appropriate GARCH model to describe the marginal distribution of open-end fund income. In order to express the assumed distribution of open-end fund income time series distribution characteristics can be well described. K-S test and A-D test are used to test the goodness of fit of the edge distribution model of open-end fund income series. Third. Different time-varying Copula functions are used to describe the relationship between open-end fund assets. Finally, Monte Carlo simulation technology and time-varying Copula function are combined. The risk of open-end fund portfolio is measured by VaR. In order to reflect the risk change of open-end fund portfolio and the probability of possible loss of its assets under different risk conditions, we select three representative open-end funds as the research object. It is found that the estimated VaR value of the time-varying Clayton Copula-AR(p)-GARCH model is more accurate and can cover the maximum loss risk more comprehensively at various confidence levels. In order to achieve the purpose of risk control. The innovations of this paper are as follows: the model constructed can effectively avoid the model setting error caused by the ubiquitous peak and thick tail of financial time series and the bias characteristic; In order to ensure the robustness and accuracy of empirical results, the optimal Copula type is determined by goodness of fit test in this paper.
【學位授予單位】：湖南大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：F224;F830.59

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