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

  更多相關(guān)文章： 開放式基金 時(shí)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(shí)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(fēng)險(xiǎn)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(shè)定誤差，同時(shí)還考慮了相依性的動(dòng)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(shí)變性特征。 本文首先對開放式基金的概念以及內(nèi)涵進(jìn)行闡述，同時(shí)比較已有的度量市場收益風(fēng)險(xiǎn)的方法。其次應(yīng)用自相關(guān)檢驗(yàn)對開放式基金凈值收益時(shí)間序列進(jìn)行檢驗(yàn)，以判別開放式基金收益時(shí)間序列是否存在高階序列相關(guān)性。并應(yīng)用ARCH-LM檢驗(yàn)對該時(shí)間序列進(jìn)行檢驗(yàn)，判別是否具有高階ARCH效應(yīng)，并以此為依據(jù)，選擇適當(dāng)?shù)腉ARCH類模型對開放式基金收益的邊緣分布進(jìn)行描述。為了表示所假定的分布能對開放式基金收益時(shí)間序列的分布特征進(jìn)行較好的刻畫，應(yīng)用K-S檢驗(yàn)以及A-D檢驗(yàn)對開放式基金收益序列邊緣分布模型的擬合優(yōu)度進(jìn)行檢驗(yàn)。再次，運(yùn)用不同的時(shí)變Copula函數(shù)對開放式基金資產(chǎn)間的相依性關(guān)系進(jìn)行描述。最后，將蒙特卡羅模擬技術(shù)與時(shí)變Copula函數(shù)相結(jié)合，對開放式基金組合風(fēng)險(xiǎn)進(jìn)行VaR測度，以反映開放式基金投資組合風(fēng)險(xiǎn)變化情況與其資產(chǎn)在不同風(fēng)險(xiǎn)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(shí)變Clayton Copula-AR(p)-GARCH模型所估計(jì)的VaR值更為準(zhǔn)確，并且能夠在各個(gè)置信水平下較全面地覆蓋最大損失風(fēng)險(xiǎn)，從而達(dá)到控制風(fēng)險(xiǎn)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(shí)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(shè)定誤差；本文通過擬合優(yōu)度檢驗(yàn)確定最優(yōu)Copula類型，以確保實(shí)證結(jié)果的穩(wěn)健性以及準(zhǔn)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(xué)位授予單位】：湖南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F224;F830.59

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