Multifractal detrended fluctuation analysis on high-frequency SZSE in Chinese stock market

Abstract

We use multifractal detrended fluctuation analysis (MF-DFA) method to investigate the multifractal behavior of Shenzhen Component Index (SZSE) 5-minute high-frequency stock data from 2017.6.15 - 2018.4.11. We determine generalized Hurst exponent and singularity spectrum and find that these fluctuations have multifractal nature. In order to maintain the long-term memory of the stock , all 9696 data are divided into 6 units. According to the multifractal spectrum, the main parameters of the six units are obtained. Comparing the MF-DFA results for the original SZSE high-frequency time series with those for shuffled series, we conclude that the origin of multifractality is due to both the broadness of probability density function and long-range correlation. The generalized Hurst exponent obviously depend on the order of fluctuation function and change with it. The curve of scaling function clearly departs from a straight line, i.e. it shows clearly nonlinear property, and the multifractal spectrum displays the commonly observed bell shape. This will provide an important and theoretical foundation for researching the forecasting of finance markets.