| During the30-year’s reforming and opening up process, China has accelerated its economic globalization. In particular, after the entry to WTO in2001, China has caught a golden age of economic development. However, as a member of the global economy integration, China has not escaped the adverse impact of the sub-prime mortgage crisis, which has influenced the economy of the whole world since2007, just like the butterfly effect. Likewise, as the barometer of political economy, China’s stock market has been linking with other stock markets in the world more and more closely. Due to the sub-prime mortgage crisis, every stock market has fallen in varying degrees, showing a strong correlation. The dynamic linkage between the world and China’s stock market, the biggest emerging market and second biggest stock market in the world, has caught the eyes of regulatory authorities, experts and investors over the world.With the background of economic globalization and financial liberalization, we need to find out what is the linkage between China’s stock market and other major stock markets, whether the linkage will change as time goes by, and what is the time track of the linkage. To a further step, what have formed the time-varying pattern? To speed up China’s financial liberalization, the government has implemented a series of financial reforms, such as the implementation of the QFII and QDII systems, the split share structure reform of the RMB exchange rate, and the launch of Growth Enterprise Market and stock index futures. What effects did these reforms have on the linkage between China and international stock markets? The financial crisis in2007has led to the economic recession in some developed countries, and resulted in the slowdown of world economy. Meanwhile China’s economy is also faced with serious challenges. We need to think about whether the contagion effect of the financial crisis has appeared in China’s stock market. Researching into these problems can be theoretically and practically meaningful to recognize the dynamic features of Chinese stocks.The issues mentioned above involve two core aspects:first, how can we measure the correlation between stock markets scientifically and reasonably. Because the time series data of yield rate often shows non-normality, volatility clustering and the features of steep-peak and heavy tails, and the correlation between financial markets or financial assets appears to be asymmetric, the existed measure method which is based multivariate normal distribution assumption is not applicable. Besides, the correlation between markets will change due to the adjustment of policy and the variation of the market environment. Thus the issue is very inconclusive and complicated. It is also insufficient to use Copula model with fixed time-varying pattern. This paper presents a nonparametric model of time-varying Copula to test the linkage between China and international stock markets. Second, how can we study the linkage mechanism between Chinese and foreign stock markets with econometrics method? This paper has discussed the factors comprehensively by using the parameter linear models and semi-parametric partly linear models.The studies and main conclusions are as follows:First, based on the review and assessment of existed measure methods, this paper presents nonparametric model of time-varying Copula to test the linkage between China and international stock markets. This article regards Copula parameters as a nonparametric function of time and proposes empirical distribution function and the local maximum likelihood method to estimate the time-varying parameters in Copula function. The method for obtaining the optimal bandwidth through maximum pseudo likelihood function and a statistical test on whether the copula parameter is time-varying are also introduced.; we have completed the selection of time-varying Copula model through goodness of fit and maximize the likelihood function of copula and we have justified the large sample properties of the parameter’s estimator in Copula function, including consistency and asymptotic normality. By designing lots of Monte Carlo Stimulations, we have finally proved that our method is feasible and robust. Second, this paper estimated the dynamic linkage between China and the world’s major stock markets based on time-varying Copula nonparametric model. And further we analyzed whether there was a significant change and causes between China and the United States and between China and Hong Kong before and after major events.This paper selected the weekly return of China, the United States, France, Germany, Japan, and Hong Kong from1997to2010to model the dynamic correlation structure by applying the time-varying Copula nonparametric models. The study found that the dynamic correlation structure between them have obvious locality and variability. Throughout the sample period, the linkage between Shanghai and the Hang Seng was the greatest, followed by the Shanghai and the Nikkei225, however, the correlations with the European and American stock markets are low. Further study found that the correlation between China and Hong Kong significantly increase after following events:China’s accession to WTO, China launched QFII, China’s share reform and Chinese CSI300Stock Index Futures. That is, the linkage between China and Hong Kong’s stock markets strengthened with the acceleration of China’s financial liberalization. However, the dynamic linkage between China and the U.S. stock markets significantly strengthened only in the period before and after the introduction of Chinese CSI300Stock Index Futures. The linkage was not significantly different before and after China’s accession to WTO. the QFII launch and the share reform.Third, this paper discussed the factors impacting the linkage between China and international stock markets comprehensively, especially the variable of China’s financial liberalization, as well as the source of data.According to current literature, we have built the Chinese financial liberalization index quarterly from1982to2010. From the results of the index, China has been improving the degree of financial liberalization, and in2010, the degree obtained66.65%, but China is still part of financial repression compared to the full realization of the requirements of the financial market, such as China’s capital account is not completely open yet.Fourth, this paper has comprehensively studied the internal mechanism of the time-varying linkage between China and the U.S. and between China and Hong Kong, based on the parametric and semi-parametric partly linear regression models.We select China’s financial liberalization, foreign trade dependence, GDP growth rates, differences in inflation rates, interest rate differences, the interaction of the dummy variable in U.S. financial crisis and China’s financial liberalization, as well as the dummy variables in and after U.S. financial crisis as explanatory variables. The study found semi-parametric partly linear model is more robust and consistent with theoretical expectations.The results show that the improvement of CFLI promotes the linkage between China and Hong Kong’s stock markets, but reduces the linkage between China and the U.S. stock markets. In addition, there is the financial crisis contagion effect between the U.S. and China, while there is not between the mainland and Hong Kong. The contagion effect intensifies between mainland and Hong Kong while weakens that between China and the U.S. as the acceleration of CFLI. but in the post-financial crisis period, as the foreign trade dependence increased, the linkage of them has a very significant increase, especially that between China and Hong Kong. When the macroeconomic indicators (GDP growth rates differences, differences in inflation rates, interest rate differences) are small, the linkage between mainland and Hong Kong stock markets did not change significantly, while they increased to a certain extent, the linkage declined, which is consistent with theoretical expectations. However, we can’t draw the same conclusion to the Sino-US stock markets.The innovative points of this paper are as the following:First, we have come up with the non-parameter time-varying Copula model and applied it to measure the correlation between stock markets. In the paper, we have presented the complete statistical inference theory, including the estimator of the time-varying parameter, the selection of smoothing parameter, the hypothesis testing of whether the parameter is time-varying and the lager sample properties of time-varying parameters. We have also designed a lot of Monte Carole Stimulations to testify this model’s feasibility, robustness and superiority. This model not only can be used to measure the correlation between stock markets, but also can be helpful in the dynamic modeling of the correlation structure of financial markets or financial assets, serving to portfolio, risk management and the pricing of derivatives.Second, we have changed the method of selecting time-varying Copula model. Since most literatures are focusing on how to choose Copula model in certain situations, and we lack the information on how to select a time-varying Copula model, then we have introduced a method:using statistical fitting test and maximizing the likelihood function to elect a model.Third, we have researched into the linkage mechanism between China and the U.S., as well as that between mainland China and Hong Kong, by applying econometrics methods. On one hand, the range of explanatory variables is wider than previous researches. Furthermore, we have constructed the data from1982to2010of financial liberalization index. On the other hand, this paper has provided a more reasonable model. According to our research, parametric liner model has its limitations. Thus we have designed semi-parametric partly linear regression models to study the intrinsic motivation of co-movement. |
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