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영어

In recent years, the Chinese market has entered a new opening up era. In the background of financial deepening and liberalization, financial innovation is a new profit growth point for financial institutions. As the capitalization-weighted stock market index, which is designed to replicate the performance of top 300 stocks traded in the Shanghai and Shenzhen stock exchanges, CSI 300 Index will also become the standard product or reference for more financial multiple derivatives. The existing research on the anti-manipulation and stability of CSI 300 index mainly focuses on the influence of the stock weight on the index, which often ignores the impact of the weight share price change on the stock index. In actual transactions, it is easier to exert influence on the index by manipulating the prices of the heavyweight. Therefore, it is important to study the correlation between the index and weight stocks, especially tail dependence. This paper uses the Copula function instead of a simple linear correlation function because there is no specific hypothesis on the distribution state of the data sequence when describing the relationship between two financial variables. It is a good solution to the problem that the relevance of financial variables cannot be depicted by the general linear functions in excessive volatility period. After comparing different forms of the Copula function, this paper selects the t-Copula function as the research tool and constructs the tail correlation measure. Then, the stock price time series sample is selected from the top ten weight shares of CSI 300 index from January 2015 to December 2016, including China Ping An (601318), China Merchants Bank (600036), CITIC Securities (601998), Minsheng Bank (600016) and Vanke A (000002). The AR (n) -XARCH model is used to deal with the autocorrelation and the ARCH effect of CSI 300 index and the time series of the daily returns of the five weight shares, whose resulting sequence is transformed by the probability integral. From the obtained correlation coefficient, it can see that the correlation between the CSI 300 index and the five weight stocks is relatively high. In view of this, this paper provides some suggestions:1) the weight share selection mechanism of the stock index should be optimized; 2) CSI 300 index should be strengthen supervised to reduce the manipulated volatility, which further promote the stable operation of the financial market.