基于變結(jié)構(gòu)Copula模型的國內(nèi)外股市波動溢出效應(yīng)研究
本文選題:變結(jié)構(gòu)Copula + Granger因果檢驗。 參考:《華南理工大學(xué)》2013年碩士論文
【摘要】:在經(jīng)濟全球化及金融市場一體化的背景下,金融危機的爆發(fā)加劇了風(fēng)險在全球金融市場之間的傳遞,這種風(fēng)險在不同金融市場之間傳遞的現(xiàn)象即表現(xiàn)為金融市場間的波動溢出效應(yīng)。雖然目前已有不少關(guān)于波動溢出效應(yīng)的研究,但仍然存在諸多缺陷。因此,本文在對傳統(tǒng)波動溢出效應(yīng)研究方法進行梳理的基礎(chǔ)上,提出了一種新的研究方法——EMD分解技術(shù)與變結(jié)構(gòu)Copula模型相結(jié)合。并通過實證分析驗證了該研究方法應(yīng)用于研究不同股票市場之間的波動溢出效應(yīng)的有效性。 本文的核心工作可概括如下:首先采用EMD技術(shù)分解并合成了具有不同經(jīng)濟含義的股票收益率新序列;然后,結(jié)合Granger因果檢驗方法分別對不同地區(qū)股票市場的高低頻序列進行波動傳遞的方向分析;最后,,以股票收益率的高頻序列作為波動溢出效應(yīng)的研究對象,建立變結(jié)構(gòu)Copula模型,通過檢驗Copula函數(shù)的相關(guān)系數(shù)研究分析了發(fā)生波動溢出時的強度大小。 基于上述方法,以2006年1月4日—2010年12月30日期間的道-瓊斯指數(shù)(DJI)、英國金融時報指數(shù)(FTSE)、日經(jīng)225指數(shù)(NIK)、恒生指數(shù)(HSI)、滬深300指數(shù)(HS300)每日的收盤價為原始數(shù)據(jù),對不同股票市場之間的波動溢出效應(yīng)進行了深入的分析。研究結(jié)果表明:(1)除了日本與中國大陸地區(qū)的股票市場,其余股市間均存在一定程度的波動溢出。其中,英美兩國股市、日本與中國香港地區(qū)股市之間均存在長期的波動溢出效應(yīng),并且美國股票市場領(lǐng)跑全球金融市場;(2)英美兩國股市由短期內(nèi)信息雙向流動轉(zhuǎn)變?yōu)閱蜗蛐畔⒘鲃,日本股市與中國股市之間由最初不存在顯著的信息流動轉(zhuǎn)變?yōu)殡p向信息流動,其余地區(qū)的股市隨著交易周期的加長,由單向信息流動轉(zhuǎn)為雙向信息流動。發(fā)達(dá)國家的股價變化往往領(lǐng)先于發(fā)展中國家的股價變動。
[Abstract]:In the context of economic globalization and financial market integration, the outbreak of the financial crisis has intensified the transmission of risk among the global financial markets. The phenomenon of risk transmission between different financial markets is the volatility spillover effect between financial markets. Although there are many researches on volatility spillover effect, there are still many defects. Therefore, on the basis of combing the traditional research methods of volatility spillover effect, a new research method, EMD decomposition technique and variable structure Copula model, is proposed in this paper. The validity of this method is verified by empirical analysis in the study of volatility spillover effects between different stock markets. The core work of this paper can be summarized as follows: firstly, we use EMD technology to decompose and synthesize a new series of stock returns with different economic meanings. Combined with Granger causality test method, the direction of volatility transmission of high and low frequency series of stock market in different regions is analyzed respectively. Finally, the variable structure Copula model is established by taking the high frequency series of stock yield as the research object of volatility spillover effect. By testing the correlation coefficient of Copula function, the intensity of volatility spillover is analyzed. Based on the above method, the daily closing prices of the Dow Jones Index (DJI), the Financial Times Index (FTSE), the Nikkei 225 Index (Nikkei), the Hang Seng Index (HSI) and the Shanghai and Shenzhen Index (HS300) for the period from 4 January 2006 to 30 December 2010 are taken as the original data. The volatility spillover effect between different stock markets is analyzed. The results show that there is a certain degree of volatility spillover between the stock markets of Japan and mainland China. Among them, there is a long-term volatility spillover effect between the stock markets of the United States and the United States, the stock markets of Japan and Hong Kong of China. Moreover, the US stock market leads the global financial market.) the stock markets of the United States and the United States have changed from two-way information flow to one-way information flow in the short term, and the information flow between the Japanese stock market and the Chinese stock market has changed from no significant information flow at first to a two-way information flow. The stock market in other regions changed from one-way information flow to two-way information flow with the increase of trading cycle. Stock prices in developed countries tend to move ahead of those in developing countries.
【學(xué)位授予單位】:華南理工大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2013
【分類號】:F831.5;F224
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