基于波動約束性度量的中美港股市交叉相關(guān)性研究
[Abstract]:In this paper, the multi-fractal elimination trend cross-correlation analysis (MF-DCCA) method is used to study the stock markets in mainland China, the United States and Hong Kong in different volatility constraints. In this paper, a multi-fractal elimination trend cross-correlation analysis (VC-MF-DCCA) based on volatility constraint metric is proposed to study the volatility conduction between the mainland of China, the United States and Hong Kong stock markets. The empirical results show that stock market volatility is related to important events in financial markets. Hong Kong's stock market, based on the Hang Seng index (HSI), is more influential than the mainland stock market, which is based on the Shanghai index. Mainland Chinese stocks with the Shanghai index as a sample are more influential than U.S. stocks with the Dow Jones Industrial average (DJIA) as a sample. The Hong Kong stock market and the mainland Chinese stock market are the most conductive. Hong Kong's stock market was the most influential in the sharp range of volatility between 1991 and 2014. In this paper, the split autoregressive moving average method is used to verify the validity of multifractal trend elimination cross correlation analysis (VC-MF-DCCA) based on volatility constraint measure. In this paper, the multifractal elimination trend cross correlation analysis (VC-MF-DCCA) based on volatility constraint metric, the cross correlation analysis (VC-DCCA) method based on volatility constraint metric and the empirical analysis method are presented. The cross-correlation analysis method of multifractal elimination trend based on modal decomposition (EMD) is compared. It is found that the multi-fractal elimination trend cross-correlation analysis method based on volatility constraint measure is more accurate and can be intuitively associated with specific major events in the stock market.
【學(xué)位授予單位】:南京信息工程大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2017
【分類號】:F831.51
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