本文選題：風(fēng)險(xiǎn)度量分析　切入點(diǎn)：隨機(jī)波動(dòng)模型　出處：《湖南大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：基于Copula的金融資產(chǎn)投資組合風(fēng)險(xiǎn)測(cè)度的應(yīng)用研究是金融風(fēng)險(xiǎn)管理的前沿性課題.隨著經(jīng)濟(jì)全球化的加快，國內(nèi)的金融市場(chǎng)也變得日益復(fù)雜和多樣化，金融市場(chǎng)風(fēng)險(xiǎn)度量的相關(guān)模式呈現(xiàn)出非正態(tài)、非對(duì)稱和尾部相關(guān)等特性，Copula函數(shù)相較于以往基于正態(tài)分布假設(shè)的分析方法，對(duì)金融風(fēng)險(xiǎn)進(jìn)行相關(guān)性分析有其特有的優(yōu)勢(shì).本文將Copula理論結(jié)合描述邊緣分布的隨機(jī)波動(dòng)模型，對(duì)中國兩大能源股票板塊的相關(guān)性進(jìn)行分析，構(gòu)建t-Copula-SV-t模型，然后結(jié)合風(fēng)險(xiǎn)度量理論計(jì)算風(fēng)險(xiǎn)值來觀察股票的風(fēng)險(xiǎn). 本文在理論上，首先介紹了隨機(jī)波動(dòng)模型以及Copula理論在國內(nèi)外金融領(lǐng)域中的研究現(xiàn)狀，并簡(jiǎn)要介紹了貝葉斯計(jì)量工具的應(yīng)用.然后分章節(jié)對(duì)Copula函數(shù)、隨機(jī)波動(dòng)模型的相關(guān)內(nèi)容作了詳細(xì)的闡述，包括模型的介紹、分類、參數(shù)估計(jì)以及檢驗(yàn)等方面.接著介紹了風(fēng)險(xiǎn)值的概念以及不同條件下的計(jì)算方法，為后面的風(fēng)險(xiǎn)度量做好理論準(zhǔn)備. 在實(shí)證方面，本文選取上證能源股票和深證能源股票作為研究樣本，首先分析數(shù)據(jù)的基本統(tǒng)計(jì)特征，然后運(yùn)用隨機(jī)波動(dòng)模型對(duì)變量建立邊緣分布，并通過檢驗(yàn)比較并選擇出最適合的SV-t模型；接著以選擇的SV-t模型為邊緣分布，建立不同類型的Copula模型，通過Copula密度函數(shù)圖及理論評(píng)價(jià)均可看出t-Copula模型是幾類模型中擬合效果最好的，在Copula模型的基礎(chǔ)上計(jì)算組合的風(fēng)險(xiǎn)值. 最后本文對(duì)Copula理論在中國金融市場(chǎng)相關(guān)性研究以及風(fēng)險(xiǎn)度量分析中的應(yīng)用進(jìn)行總結(jié)，并提出了有待我們進(jìn)一步研究的問題和展望.
[Abstract]:The research on the risk measurement of financial asset portfolio based on Copula is a leading subject of financial risk management. With the acceleration of economic globalization, the domestic financial market is becoming more and more complex and diversified. The related patterns of financial market risk measurement show the characteristics of non-normal, asymmetric and tail correlation. Compared with the previous analysis methods based on the normal distribution hypothesis, the Copula function is analyzed. This paper combines the Copula theory with the stochastic volatility model to describe the marginal distribution, analyzes the correlation between the two energy stocks in China, and constructs the t-Copula-SV-t model. Then combining the risk measurement theory to calculate the risk value to observe the stock risk. In theory, this paper first introduces the stochastic volatility model and the research status of Copula theory in the field of finance at home and abroad, and briefly introduces the application of Bayesian econometric tools. The related contents of the stochastic volatility model are described in detail, including the introduction, classification, parameter estimation and test of the model. Then, the concept of the risk value and the calculation methods under different conditions are introduced. Prepare for the following risk measurement. In the empirical aspect, this paper selects the energy stocks of Shanghai Stock Exchange and Shenzhen Stock Exchange as the research samples, analyzes the basic statistical characteristics of the data, and then uses the stochastic volatility model to establish the marginal distribution of the variables. The most suitable SV-t model is compared and selected by testing, and then different types of Copula models are established with the selected SV-t model as the edge distribution. Through the Copula density function diagram and the theoretical evaluation, it can be seen that t-Copula model is the best fit among several kinds of models. The risk value of combination is calculated on the basis of Copula model. Finally, this paper summarizes the application of Copula theory in the study of the correlation of Chinese financial market and the risk measurement analysis, and puts forward some problems and prospects for our further study.
【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F832.51;F224

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 余立凡;何海鷹;;基于半?yún)?shù)Copula的信用風(fēng)險(xiǎn)實(shí)證分析[J];福建金融;2010年10期

2 劉樂平;張美英;李姣嬌;;基于WinBUGS軟件的貝葉斯計(jì)量經(jīng)濟(jì)學(xué)[J];東華理工學(xué)院學(xué)報(bào)(社會(huì)科學(xué)版);2007年02期

3 周竟東;謝赤;歐輝生;趙亦軍;;權(quán)證收益率波動(dòng)的度量:基于GARCH和SV模型的比較[J];系統(tǒng)工程;2010年04期

4 黃珍;苑慧玲;倪麗云;;基于Copula函數(shù)和蒙特卡洛模擬方法的權(quán)證定價(jià)[J];科技和產(chǎn)業(yè);2012年11期

5 周孝華;李強(qiáng);張保帥;;基于Copula-ASV-GPD的我國多元外匯儲(chǔ)幣組合的風(fēng)險(xiǎn)度量[J];系統(tǒng)工程;2012年11期

6 魯志軍;姚德權(quán);;基于Copula-VaR的金融資產(chǎn)組合風(fēng)險(xiǎn)測(cè)度研究[J];財(cái)經(jīng)理論與實(shí)踐;2012年06期

7 劉平;杜曉蓉;;對(duì)金融危機(jī)風(fēng)險(xiǎn)傳染效應(yīng)的比較研究——基于靜態(tài)與動(dòng)態(tài)copula函數(shù)的分析[J];經(jīng)濟(jì)經(jīng)緯;2011年03期

8 劉樂平,袁衛(wèi);現(xiàn)代貝葉斯分析與現(xiàn)代統(tǒng)計(jì)推斷[J];經(jīng)濟(jì)理論與經(jīng)濟(jì)管理;2004年06期

9 孫志賓;張榮幸;;連接函數(shù)(Copula)在行業(yè)投資中的應(yīng)用[J];經(jīng)濟(jì)師;2010年08期

10 李堪;白雪晶;;Copula理論在金融市場(chǎng)分析應(yīng)用中的理論探析[J];金融理論與教學(xué);2011年02期

相關(guān)博士學(xué)位論文 前1條

1 戰(zhàn)雪麗;基于Copula理論的多金融資產(chǎn)定價(jià)與風(fēng)險(xiǎn)測(cè)度[D];天津大學(xué);2007年

，

本文編號(hào)：1588036