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滬港證券市場收益的跳躍溢出與波動溢出研究

發(fā)布時間:2018-05-02 21:01

  本文選題:證券市場 + 跳躍溢出; 參考:《湖南大學(xué)》2014年碩士論文


【摘要】:證券市場間的跳躍溢出與波動溢出現(xiàn)象是近來金融學(xué)家研究的熱點(diǎn)問題之一。隨著經(jīng)濟(jì)全球化、金融自由化的日益深入,這種現(xiàn)象廣泛地發(fā)生在世界各主要證券市場之間,顯現(xiàn)著越來越重大的影響力。上海和香港證券市場是中國最重要的證券市場之一,對于這兩個市場間的跳躍溢出與波動溢出進(jìn)行研究不僅可以幫助我們理清滬港兩市之間以怎樣的方式連接、跳躍和波動的信息又是通過什么樣的機(jī)制在市場間傳播的,還有利于兩地金融監(jiān)管當(dāng)局及時調(diào)整監(jiān)管策略,投資者投資構(gòu)建合理的資產(chǎn)組合以規(guī)避風(fēng)險。 本文首先整理了國內(nèi)外相關(guān)領(lǐng)域的文獻(xiàn)并進(jìn)行了評述,在對跳躍與波動等相關(guān)概念進(jìn)行界定并指出現(xiàn)有研究的不足后,提出了自己的研究思路并簡要介紹了基于MCMC算法的SVCJ模型及其估計(jì)方法、跳躍溢出指標(biāo)的定義、波動溢出測度模型等實(shí)證工具。選取上證綜指與恒指收益,,在對其進(jìn)行基本統(tǒng)計(jì)分析后,使用SVCJ模型估計(jì)了兩市收益的參數(shù)、跳躍項(xiàng)與波動率,并在此基礎(chǔ)上利用條件跳躍溢出概率、跳躍溢出頻度、強(qiáng)度、平均跳躍溢出大小等指標(biāo)定量分析了滬港間的跳躍溢出,通過建立誤差修正模型、Granger因果檢驗(yàn)、廣義脈沖響應(yīng)函數(shù)測度了兩地間的波動溢出,最終得出了以下主要結(jié)論:(1)香港證券市場的波動較小,且跳躍的幅度與頻度都不大;而上海市場的波動較大,跳躍的幅度與頻率也較高。(2)在跳躍溢出信息的到達(dá)方面,香港證券市場的反應(yīng)更加靈敏迅速,上海證券市場則相對較慢。(3)在長期內(nèi),兩個市場的波動存在均衡關(guān)系,并且滬市的波動對港市波動的影響較強(qiáng),港市的波動對滬市波動的影響較弱,同時兩者的影響時效都很長。(4)在短期內(nèi),兩地的波動對各自的影響存在滯后一日或兩日效應(yīng),受自身影響較大,受對方的影響較弱。最后,在對全文作出總結(jié)后提出了相關(guān)政策建議以及本研究的不足和對未來研究的展望。
[Abstract]:The phenomenon of jump spillover and volatility spillover between securities markets is one of the hot issues recently studied by financiers. With the globalization of economy and the deepening of financial liberalization, this phenomenon widely occurs among the major securities markets in the world, showing more and more important influence. Shanghai and Hong Kong stock markets are one of the most important securities markets in China. The study of jump spillover and volatility spillover between these two markets can not only help us to understand how the Shanghai and Hong Kong stock markets are connected. What kind of mechanism is used to spread the information of jump and fluctuation among the markets, and it is also helpful for the financial regulatory authorities in both places to adjust the supervision strategy in time, and for investors to invest and construct a reasonable portfolio to avoid risks. In this paper, firstly, the literature of related fields at home and abroad is summarized and reviewed. After defining the relevant concepts, such as jump and fluctuation, and pointing out the shortcomings of the existing research, In this paper, the author puts forward his own research idea and briefly introduces the SVCJ model based on MCMC algorithm and its estimation method, the definition of jump spillover index, the volatility spillover measure model and other empirical tools. After analyzing the return of Shanghai Composite Index and Hang Seng Index, the paper uses SVCJ model to estimate the parameters, jump items and volatility of the two markets, and then uses conditional jump spillover probability, jump overflow frequency and intensity. The average jump spillover is quantitatively analyzed. By establishing the error correction model and Granger causality test, the generalized impulse response function is used to measure the volatility spillover between Shanghai and Hong Kong. Finally, the following main conclusions are drawn: (1) the volatility of the Hong Kong stock market is relatively small, and the amplitude and frequency of the jump are small; while the volatility of the Shanghai market is large, and the jump amplitude and frequency are also higher. 2) in terms of the arrival of the jump spillover information, The response of the Hong Kong stock market is more sensitive and rapid, while the Shanghai stock market is relatively slow.) in the long run, there is a balanced relationship between the volatility of the two markets, and the volatility of the Shanghai stock market has a stronger impact on the volatility of the Hong Kong market. The effect of the fluctuation of Hong Kong market on the fluctuation of Shanghai stock market is weak, and the effect of both of them is very long. In the short term, the effect of the fluctuation in both places is delayed by one day or two days, which is influenced by oneself and weak by the other side. Finally, after summarizing the full text, the paper puts forward some relevant policy suggestions and the shortcomings of this study and prospects for future research.
【學(xué)位授予單位】:湖南大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2014
【分類號】:F224;F832.51

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 王春峰;孫永亮;房振明;李曄;;訂單流不平衡對股票價格的沖擊效應(yīng)實(shí)證研究[J];北京理工大學(xué)學(xué)報(社會科學(xué)版);2007年02期

2 曾志堅(jiān);徐迪;左楠;;金融危機(jī)對證券市場波動溢出的影響研究[J];財經(jīng)理論與實(shí)踐;2011年06期

3 田光;張瑞鋒;;基于Copula的股票市場波動溢出分析[J];財經(jīng)理論與實(shí)踐;2011年06期

4 劉慶富;朱W

本文編號:1835483


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