本文選題：Copula模型 + 變結(jié)構(gòu)Copula模型　； 參考：《浙江財(cái)經(jīng)大學(xué)》2017年碩士論文

【摘要】：Copula模型因?qū)⒙?lián)合分布與它們各自的邊緣分布連接在一起,被人們稱為連接函數(shù),雖然起源較晚,但由于具有優(yōu)良的特質(zhì),迅速在國(guó)內(nèi)外得到了廣泛的關(guān)注和快速的發(fā)展,并應(yīng)用于金融、醫(yī)學(xué)、質(zhì)量工程等若干領(lǐng)域.特別在國(guó)際化與多元化發(fā)展影響下的金融市場(chǎng),Copula模型克服了傳統(tǒng)相關(guān)性工具的缺點(diǎn),更好地描述了金融市場(chǎng)內(nèi)外間呈現(xiàn)出的非線性、非對(duì)稱和尾部相關(guān)特征.Copula模型的出現(xiàn)為研究相依性的學(xué)者也提供了特別的貢獻(xiàn),從而也促使了Copula模型的理論發(fā)展和實(shí)際應(yīng)用.從形式上,由最初的二元Copula函數(shù)到多元Copula函數(shù),由單一Copula模型到混合Copula模型,從靜態(tài)Copula模型到動(dòng)態(tài)Copula模型.從研究?jī)?nèi)容,包含模型選擇、參數(shù)估計(jì)和擬合優(yōu)度檢驗(yàn)等,以及研究方法的參數(shù)估計(jì)方法,非參數(shù)估計(jì)方法和貝葉斯估計(jì)方法等方面都有了快速的發(fā)展.目前,關(guān)于Copula模型的理論研究主要集中在靜態(tài)Copula模型、半?yún)?shù)及參數(shù)方法上.而動(dòng)態(tài)Copula模型考慮了金融變量的波動(dòng)傳染機(jī)制,因此動(dòng)態(tài)Copula模型可更好地刻畫(huà)金融市場(chǎng)內(nèi)外間的變結(jié)構(gòu)相關(guān)關(guān)系.動(dòng)態(tài)Copula模型可分為變結(jié)構(gòu)Copula模型和時(shí)變Copula模型.本文基于非參數(shù)方法對(duì)變結(jié)構(gòu)Copula模型進(jìn)行變點(diǎn)檢測(cè)分析研究.經(jīng)驗(yàn)似然非參數(shù)方法由Owen(1988)提出,由于其優(yōu)良性質(zhì),被廣泛應(yīng)用于各個(gè)學(xué)科及領(lǐng)域.本文在一定的假設(shè)條件與約束條件下,構(gòu)造了檢測(cè)Copula模型中的變結(jié)構(gòu)點(diǎn)的經(jīng)驗(yàn)似然比檢驗(yàn)統(tǒng)計(jì)量,且給出了相應(yīng)的漸近分布特征與大樣本性質(zhì)的證明,最后,通過(guò)相應(yīng)的隨機(jī)模擬和一個(gè)實(shí)證分析對(duì)本文提出的非參數(shù)經(jīng)驗(yàn)似然方法進(jìn)行驗(yàn)證.本文的主要研究?jī)?nèi)容可以歸納為以下幾點(diǎn):1.歸納總結(jié)變結(jié)構(gòu)Copula模型的研究現(xiàn)狀、背景及研究意義,提出本文的研究方法及研究?jī)?nèi)容.2.采用經(jīng)驗(yàn)似然方法檢測(cè)Copula模型中存在單一變結(jié)構(gòu)點(diǎn),構(gòu)造相應(yīng)的檢驗(yàn)統(tǒng)計(jì)量,給出漸近分布和大樣本性質(zhì)的證明,最后進(jìn)行了隨機(jī)模擬與實(shí)例說(shuō)明該方法的合理性與可行性.3.采用經(jīng)驗(yàn)似然方法研究Copula模型中存在多個(gè)變結(jié)構(gòu)點(diǎn)的情況,構(gòu)造相應(yīng)的檢驗(yàn)統(tǒng)計(jì)量,給出漸近分布和大樣本性質(zhì)的證明,最后進(jìn)行了隨機(jī)模擬與實(shí)例分析來(lái)說(shuō)明該方法的適用性與可行性.4.對(duì)論文進(jìn)行總結(jié)概括,提出了論文中存在的優(yōu)缺點(diǎn),并對(duì)未來(lái)變結(jié)構(gòu)Copula模型研究的發(fā)展方向進(jìn)行了展望.
[Abstract]:The Copula model is called join function because it connects the joint distribution with their respective edge distribution. Although the origin is late, because of its excellent characteristics, it has been widely concerned and developed rapidly at home and abroad. And applied to finance, medicine, quality engineering and other fields. Especially under the influence of internationalization and diversification, the Copula model of financial markets overcomes the shortcomings of traditional correlation tools and better describes the nonlinearity in and out of financial markets. The emergence of asymmetric and tail-dependent characteristics. Copula model also provides a special contribution to the study of dependence of scholars, which also promotes the theoretical development and practical application of Copula model. Formally, from the initial binary Copula function to the multivariate Copula function, from the single Copula model to the hybrid Copula model, from the static Copula model to the dynamic Copula model. The research contents, including model selection, parameter estimation and goodness of fit test, as well as parameter estimation methods, non-parametric estimation methods and Bayesian estimation methods, have been developed rapidly. At present, the theoretical research on Copula model is mainly focused on static Copula model, semi-parameter and parametric method. The dynamic Copula model considers the volatility contagion mechanism of the financial variables, so the dynamic Copula model can better describe the variable structure correlation between the financial market and the outside. The dynamic Copula model can be divided into variable structure Copula model and time-varying Copula model. In this paper, the variable point detection of variable structure Copula model is studied based on nonparametric method. Empirical likelihood nonparametric method was proposed by Owenn 1988. It is widely used in various disciplines and fields because of its excellent properties. In this paper, under certain assumptions and constraints, empirical likelihood ratio test statistics for detecting variable structure points in Copula model are constructed, and the corresponding asymptotic distribution characteristics and properties of large samples are proved. The non-parametric empirical likelihood method proposed in this paper is verified by the corresponding stochastic simulation and an empirical analysis. The main contents of this paper can be summarized as follows: 1. The research status, background and significance of variable structure Copula model are summarized, and the research methods and contents of this paper are put forward. The empirical likelihood method is used to detect the existence of a single variable structure point in the Copula model. The corresponding test statistics are constructed, and the asymptotic distribution and the properties of large samples are proved. Finally, a stochastic simulation and an example are carried out to illustrate the rationality and feasibility of the method. The empirical likelihood method is used to study the existence of multiple variable structure points in the Copula model. The corresponding test statistics are constructed, and the asymptotic distribution and the properties of large samples are proved. Finally, random simulation and example analysis are carried out to illustrate the applicability and feasibility of the method. In this paper, the advantages and disadvantages of this paper are summarized, and the future research direction of variable structure Copula model is prospected.
【學(xué)位授予單位】：浙江財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F224;F831.5

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