BVAR论文：基于因果关系的金融市场间传导性研究.doc

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1、 BVAR论文：基于因果关系的金融市场间传导性研究【中文摘要】全球经济的迅猛发展,对于中国的经济既是机遇又是挑战,利益与风险并存,如何在获得利益的同时,规避风险就显得极为重要,而要规避风险弄清什么样的事件会导致风险,尽早防范此类事件就变成了未雨绸缪的关键,而在股市的下跌时期,尤其是极端下跌时期,传导性会变的复杂和强烈,一些没有传导关系或者是传导关系比较弱的金融市场会产生传导关系,而且这些传导关系是危机在金融市场间传导的载体,随着金融市场间经济的联系,使得风险随着金融市场迅速传播,而且在范围和程度上都会有所加强,由此可见,金融市场间的传导关系是未雨绸缪的关键,这也表明了研究金融市场间的传导关系的

2、重要性。金融市场间的传导会导致风险的传导,甚至会引起大规模经济危机,1992-1993年的欧洲金融货币体系危机,1997年的亚洲金融危机,1998年俄罗斯经济危机以及2007年美国次贷危机的爆发就是很好的例子。然而1997年的亚洲金融危机,对于中国经济的影响并不大,为什么呢?究其原因就是当时中国的金融市场与其他国家的金融市场间的传导性很弱或者基本上不存在,然而随着中国加入WTO以及中国经济的国际化的不断深入,中国金融市场以前形成的“孤岛”将不复存在,那么他的庇佑作用也随之消失,因此,应该更加关注中国金融市场自身或者与其他金融市场间的传导关系,这样保证中国金融市场平稳健康发展的“预防针”才能做好

3、,才能使中国金融市场在全球经济日新月异的今天和未来立于不败之地。本文不仅运用BVAR计量模型通过Granger因果关系研究沪深股市和新加坡股市之间,中外新兴金融市场和成熟金融市场间以及基于股市指数极差的传导性,也通过脉冲响应函数进一步验证了因果关系的结论；而且也实证分析了上涨和下跌过程中沪深股市及新加坡股市之间,中外股市之间以及香港和沪深股市之间传导性的变化特征。实证结果表明：对于沪深股市及新加坡股市,在整个样本期,沪深股市互相传导,新加坡股市与深圳股市互相传导,新加坡股市对上海股市单向传导；沪深股市及新加坡股市三者问在下跌时期的传导关系比上涨时期更为复杂；对于中外股市,在整个样本期香港股市与

4、新加坡股市互相传导,日本股市与韩国股市互相传导,美国股市对其他股市单向传导,中国沪市对韩国股市单向传导,中国沪市对新加坡股市单向传导,中国沪市对香港股市单向传导；下跌时期六个股市间的传导关系都比上涨时期更加的错综复杂,而且应用脉冲响应函数验证了Granger因果关系的结论；对于沪深股市及香港股市,在整个样本期和上涨时期都是深圳股市对香港股市单向传导,下跌时期深圳股市对上海股市和香港股市都是单向传导,香港股市对上海股市单向传导,同样也可以看出下跌时期的传导性要比上涨时期更加的强烈。【英文摘要】The rapid development of the global economy, which i

5、s not only a opportunity for Chinas economic but also a challenge for it, benefits and risks are exited at one time. It is extremely important for us how to benefit and to avoid risks at the same time, if you want to avoid the risk of events, to know what is necessary will lead to the risk becomes p

6、roactive key for as soon as possible to prevent such incidents, the stock markets in decline Period, especially in the extreme down period, the conductivity becomes complex and intense, some financial markets which had no relationship or a weak conductivity between them will become had conductive re

7、lationship, and these relationships are the carrier of financial market crisis, as the economic contacts between the financial markets, making the risk of rapid spread of the financial markets, and in the scope and extent, it will be strengthened, This shows that the conductivity between financial m

8、arkets is the key to avoid the risk, which explains the important of the researching conductivity among financial markets. Conductivity between financial markets will lead to the risk of transmission, and may even cause a large-scale economic crisis,1992-1993 crisis in the European financial and mon

9、etary system, the 1997 Asian financial crisis, the Russian economic crisis of 1998 and the 2007 outbreak of the U.S. subprime mortgage crisis are typical examples. However, the 1997 Asian financial crisis, the Chinese economy is no more influence, why? The reason is that the conductivity of Chinas f

10、inancial markets and other countries is weak or nearly non-existent in 1997, but with Chinas accession to WTO and Chinese economy continued to deepen for the internationalization of the economy, Chinas financial market “islands” which formed before will cease to exist, then the blessing of his role

11、will disappear, therefore, we should be more concerned about Chinas financial market itself or with other financial markets relationship between the conduction, so that Chinas financial markets to ensure a smooth healthy development of the “vaccination”, which make Chinas financial market to be invi

12、ncible in the rapidly changing global economy today and the future.This paper not only by the use of BVAR econometric model of Granger causality between stock markets Shanghai, Shenzhen and Singapore stock markets and Chinese and foreign financial markets in emerging and mature financial markets and

13、 the stock price based on very poor conductivity, but also by the impulse response function to further verify the causal relationship conclusion; But also empirical analysis of the changes of the conductive features process between up and down which between the Shanghai, Shenzhen and Singapore stock

14、 markets, as well as between Chinese and foreign stock markets as well as between Shanghai, Shenzhen and Hong Kong stock markets. The empirical results show that:for Shanghai, Shenzhen and Singapore stock markets, in the entire sample period, Shanghai and Shenzhen stock mutual conduction, the Singap

15、ore stock market and Shenzhen stock mutual conduction, the Singapore stock market on the Shanghai stock market unidirectional conduction; and Singapore stock markets, Shanghai and Shenzhen stock markets conduction in down period than rise period is more complicated; For Chinese and foreign stock mar

16、kets, in the whole sample period the Hong Kong stock market and Singapore stock market with each other conduction, Japan stock market and South Korea stock market mutual conduction, the U.S. stock market one-way transfer to other markets, Shanghai stock market One-way transfer the South Korea stock

17、market and Shanghai stock market on one-way transmission of Singapore stock market and Shanghai stock market one-way transmission of Hong Kong stock market; the conductivity relationship of the six stock markets in down period more complex than rise, and the application of the impulse response funct

18、ion to verify the conclusions of the Granger causality; for the Shanghai, Shenzhen stock markets and the Hong Kong stock market,in the period of the entire sample period and rise period the Shenzhen stock market are one-way transfer of Hong Kong stock market, during the down period Shenzhen stock ma

19、rket to shanghai and Hong Kong stock markets are One-way transmission, which can also be seen that the conductivity during the down period is more complex than rise period.【关键词】BVAR 成熟金融市场 新兴金融市场 Granger-Causality 传导性 脉冲响应函数 股市指数日极差【英文关键词】BVAR developed financial market emerging financial markets Gr

20、anger-causality conductivity the impulse response function very poor of stock index【目录】基于因果关系的金融市场间传导性研究摘要4-6Abstract6-8第1章 序言11-211.1 选题的依据11-161.2 选题的目的和意义16-171.3 国内外的研究现状17-191.4 本文的研究内容19-21第2章 研究方法21-252.1 数据样本212.1.1 数据的选取212.1.2 样本的处理212.2 模型的选取21-252.2.1 单位根检验的模型21-222.2.2 因果关系检验的模型22-242.2.3 脉冲响应函数模型24-25第3章 沪深股市及新加坡股市的传导性25-353.1 数据段选取253.2 实证检验25-333.3 结论33-35第4章 中外股市的传导性35-474.1 数据段选取354.2 实证检验35-464.2.1 因果检验实证35-434.2.2 脉冲响应实证43-464.3 结论46-47第5章 基于股市指数极差的传导性47-525.1 数据段选取475.2 实证检验47-515.3 结论51-52结论52-54致谢54-55参考文献55-57攻读学位期间取得学术成果57