Wavelet-Based Multiscale Research On Chinese Stock Markets Volatility

With the development of Chinese stock markets speeding up, the impact on the whole national economy which the volatility of stock markets have must increases as the time goes on. Though there are a great number of references before in analyzing the volatility of Chinese stock markets , they are all based on one single time scale. But the result only using one single time scale is always one-sided. Only when we analyze the volatility of Chinese stock markets based on multi time scale can we obtain all-sided and right analyzing result.Wavelet method is a natural analyzing tool for us studying the multiscale properties of the stock market volatility. Generally speaking, wavelet method is the complement and generalization of spectral analyzing method, which is familiar to us. It is a kind of time-scale(time- frequency) analyzing method of signal, and has the ability of characterizing the local character of signal in time and frequency domain.So, it is especially suitable for analyzing nonstationary time series. In addition, wavelet transform can reduce the correlation of long memory process. So, wavelet method is also fit for analyzing long memory time series and can estimate long memory parameter. In analyzing the volatility of financial markets, it is wavelet method that makes the researchers describe the long-memory property of the volatility of financial markets and the correlation of various financial markets in different time scale.Therefore, based on wavelet method, firstly, this thesis analyzes the multiscale and time varying long-memory property of the volatility of Chinese stock market. This thesis finds that there are evident multiscale phenomena in the long memory of the volatility of Chinese stock markets, and furthmore, there is a significant difference in the intraday and interday long memory parameter of the volatility of Chinese stock market using the technology of dummy variable.Secondly, by the wavelet correlation and cross-correlation, this thesis analyzes the multiscale property of the volatility-transmission of Shenzhen and Shanghai stock market and found that, the contemporary and lead-lag volatility-transmission relationship of Shenzhen and Shanghai Stock market becomes much stronger as the timescale becomes much bigger, so there is a better result in the smaller timescale if we want to invest dispersively using the portfolio.