本文選題：尾部相關(guān)性　切入點(diǎn)：M-Copula　出處：《天津大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：對(duì)金融市場之間各組成部分相關(guān)性的分析,是認(rèn)識(shí)市場運(yùn)行規(guī)律的基礎(chǔ),有效的相關(guān)性分析可以用來優(yōu)化市場結(jié)構(gòu),提高經(jīng)濟(jì)運(yùn)行效率。傳統(tǒng)金融資產(chǎn)間相關(guān)性的分析以線性模型為主,但最新的研究顯示,金融資產(chǎn)間的存在著非線性及非對(duì)稱的相關(guān)性,這種相關(guān)關(guān)系無法利用傳統(tǒng)的計(jì)量方法實(shí)現(xiàn)測(cè)度。而Copula函數(shù)可以對(duì)具有該類型特征的金融資產(chǎn)進(jìn)行刻畫,并對(duì)于尾部相關(guān)性的測(cè)度具有突出的優(yōu)勢(shì),可以滿足對(duì)金融變量相關(guān)性分析的需求。本文對(duì)Copula函數(shù)的理論、特征及主要類別進(jìn)行了闡述,并在傳統(tǒng)Copula函數(shù)基礎(chǔ)上進(jìn)行擴(kuò)展,在利用Copula函數(shù)對(duì)金融資產(chǎn)間相依結(jié)構(gòu)的分析中,整合常用的三類Archimedean族Copula函數(shù),加入慣性權(quán)重的粒子群算法對(duì)其參數(shù)進(jìn)行優(yōu)化,構(gòu)建了基于慣性粒子群算法的M-Copula模型。利用該模型研究了我國5年期跨期國債期貨合約結(jié)算價(jià)日漲跌幅之間的尾部相關(guān)關(guān)系,同時(shí)利用基于慣性權(quán)重的粒子群算法對(duì)混合Copula模型的參數(shù)進(jìn)行選取和確定后,比較了混合Copula函數(shù)與傳統(tǒng)Copula函數(shù)對(duì)跨期國債期貨合約上尾部以及下尾部相關(guān)關(guān)系的擬合能力。研究結(jié)果表明:基于慣性權(quán)重粒子群算法的混合Copula函數(shù)較好地刻畫了跨期國債期貨合約結(jié)算價(jià)日漲跌幅尾部非線性、非對(duì)稱的相關(guān)特征,且根據(jù)測(cè)度結(jié)果可以判定,跨期國債期貨合約結(jié)算價(jià)日漲跌幅間的上尾部相關(guān)性更為明顯,并依據(jù)對(duì)該特征的把握構(gòu)建了能夠產(chǎn)生超額收益的交易策略。
[Abstract]:The analysis of the correlation between the components of the financial market is the basis of understanding the law of market operation. Effective correlation analysis can be used to optimize the market structure. The traditional analysis of the correlation between financial assets is based on linear model, but the latest research shows that there are nonlinear and asymmetric correlations among financial assets. However, Copula function can describe the financial assets with this kind of characteristics, and it has a prominent advantage for the measurement of tail correlation. In this paper, the theory, characteristics and main categories of the Copula function are expounded, and extended on the basis of the traditional Copula function. In the analysis of the dependent structure of financial assets by using the Copula function, Integrating three kinds of Copula functions of Archimedean family, the parameters are optimized by PSO with inertial weight. The M-Copula model based on inertial particle swarm optimization algorithm is constructed. Using this model, the tail correlation between the daily rise and fall of the settlement price of China's 5-year Treasury bond futures contract is studied. At the same time, the parameters of hybrid Copula model are selected and determined by particle swarm optimization algorithm based on inertial weight. This paper compares the fitting ability of mixed Copula function and traditional Copula function to the relationship between upper tail and lower tail of the futures contract. The research results show that the hybrid Copula function based on inertial weight particle swarm optimization is a better description of the relationship between the upper tail and lower tail of the futures contract. Non-linearity in the tail of the daily rise and fall in the settlement price of the futures contracts of the inter-Treasury bonds, On the basis of the asymmetric correlation characteristics, and according to the measurement results, it can be judged that the upper tail correlation between the daily rise and fall of the settlement price is more obvious, and based on the grasp of this characteristic, the trading strategy which can produce excess returns is constructed.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：F224;F724.5

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