發(fā)布時(shí)間：2018-08-26 21:33

【摘要】：本文對(duì)深圳股票市場的收益與風(fēng)險(xiǎn)進(jìn)行研究．選取深圳股票市場中具有代表性的六支股票作為研究對(duì)象，通過建立多元混合Copula-GARCH模型來分析股票收益的相關(guān)性以及對(duì)VaR進(jìn)行計(jì)算．本文主要內(nèi)容有： 第一章闡述了選題的背景和研究意義，并進(jìn)行了相關(guān)的文獻(xiàn)綜述． 第二章對(duì)Copula函數(shù)概念、性質(zhì)及分類進(jìn)行了簡要概述，為建立Copula函數(shù)模型提供概念上的準(zhǔn)備． 第三章首先給出了Copula函數(shù)模型的一般構(gòu)建方法，包括邊際分布和Copula函數(shù)的選取、參數(shù)估計(jì)及其檢驗(yàn)方法，其次給出幾種重要的相關(guān)性測度，包括Copula函數(shù)的Kendall秩相關(guān)系數(shù)與尾部相關(guān)系數(shù)． 第四章是實(shí)證研究．選取深圳股票市場中2011年6月30日至2012年6月30日六支股票的收盤價(jià)格為指標(biāo)變量，并對(duì)其數(shù)據(jù)進(jìn)行預(yù)處理得到這六支股票收益率序列，在對(duì)數(shù)據(jù)進(jìn)行基本統(tǒng)計(jì)分析的基礎(chǔ)上，分別建立了這六支股票的GARCH-t模型來刻畫相應(yīng)的邊際分布，為了分析六支股票兩兩間的相關(guān)關(guān)系，考慮到其中有15種不同組合的兩兩相關(guān)，為避免贅述，本文僅以深發(fā)展A與萬科A為例對(duì)其Copula函數(shù)的建模進(jìn)行詳細(xì)的論證．具體過程如下：在同一個(gè)邊際分布GARCH-t模型下分別選取四種不同的阿基米德Copula函數(shù)建立了多元Copula-GARCH模型并進(jìn)行了參數(shù)估計(jì)與檢驗(yàn)，根據(jù)χ2擬合優(yōu)度檢驗(yàn)的結(jié)果最終選擇多元M-Copula-GARCH模型(4.9)來刻畫這兩支股票的相關(guān)性結(jié)構(gòu)，據(jù)此模型不僅可以分別刻畫這兩支股票各自的運(yùn)行規(guī)律，而且還可以得出以下相關(guān)性結(jié)論：深發(fā)展A股和萬科A股收益率之間存在較強(qiáng)的正相關(guān)關(guān)系，兩者的收益率之間存在顯著的非對(duì)稱的尾部相關(guān)關(guān)系，Kendall秩相關(guān)系數(shù)為0.7123，上尾部相關(guān)系數(shù)為0.5363，下尾相關(guān)系數(shù)為0.2757．而且由于模型給出了兩支股票的聯(lián)合分布，，從而可以掌握其協(xié)同運(yùn)行規(guī)律．而對(duì)于其它14種股票組合的兩兩相關(guān)性討論完全類似于深發(fā)展A與萬科A的Copula函數(shù)模型的建模過程，為節(jié)省篇幅同時(shí)考慮到第五章的需要，本文僅列出了這些組合的秩相關(guān)系數(shù)的結(jié)果． 第五章根據(jù)第四章的建模方法與結(jié)果，利用一步向前預(yù)測法計(jì)算了單支股票收益率的1天持有期VaR，并進(jìn)一步對(duì)六支股票的整體VaR進(jìn)行計(jì)算，從而得到了深圳股票市場風(fēng)險(xiǎn)的一種度量．
[Abstract]:This paper studies the income and risk of Shenzhen stock market. Six representative stocks in Shenzhen stock market are selected as the research objects. The correlation of stock returns and the calculation of VaR are analyzed by establishing a multivariate mixed Copula-GARCH model. The main contents of this paper are as follows: the first chapter describes the background and significance of the topic. In the second chapter, the concept, properties and classification of Copula function are briefly summarized. In the third chapter, the general construction methods of Copula function model are given, including marginal distribution, selection of Copula function, parameter estimation and test method. Secondly, several important correlation measures are given. The Kendall rank correlation coefficient and tail correlation coefficient of Copula function are included. Chapter four is an empirical study. The closing prices of six stocks in Shenzhen Stock Market from June 30, 2011 to June 30, 2012 are selected as index variables. On the basis of the basic statistical analysis of the data, the GARCH-t model of the six stocks is established to depict the corresponding marginal distribution. In order to analyze the correlation between two and two stocks, and considering that there are 15 different combinations, in order to avoid repetition, In this paper, only the deep development A and Vanke A are taken as examples to demonstrate in detail the modeling of their Copula functions. The concrete process is as follows: four different Archimedes Copula functions are selected under the same marginal distribution GARCH-t model to establish the multivariate. The Copula-GARCH model is used to estimate and test the parameters. According to the results of 蠂 2 goodness of fit test, the multivariate M-Copula-GARCH model (4. 9) is chosen to describe the correlation structure of these two stocks. Furthermore, we can draw the following conclusions: there is a strong positive correlation between the returns of A shares and Vanke A shares. There is a significant asymmetric tail correlation between the two rates of return. The Kendall rank correlation coefficient is 0.7123, the upper tail correlation coefficient is 0.5363, and the lower tail correlation coefficient is 0.2757. Moreover, the joint distribution of the two stocks is given in the model. In order to save space and take into account the need of chapter 5, the discussion on the correlation of 14 other stock combinations is completely similar to the modeling process of the Copula function model of the further development of A and Vanke A. In this paper, only the results of rank correlation coefficients of these combinations are listed. The one-step forward prediction method is used to calculate the one-day holding period VaR, of a single stock return, and the overall VaR of six stocks is further calculated, thus a measure of the risk of Shenzhen stock market is obtained.
【學(xué)位授予單位】：南京財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F832.51

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本文編號(hào)：2206225