Yanling Jiang, Gaozhao Guan, Beixin Fang
School of Mathematics and Statistics, Lanzhou University, Lanzhou, Gansu, 730000, China
With the deepening of the financial market’s reform and innovation, to better explain the market's stock price fluctuations, this article uses the traditional efficient market hypothesis to study further. This study is showed that the Shanghai Stock Exchange Index, the Shenzhen Stock Exchange Index, and the Nasdaq Index have the characteristics of "tip fat tail ", which indicates that the distribution is not normal. Based on the theory of multifractal spectrum, empirical analysis and comparison results of multifractal characteristics, three indexes are carried out to analyze the impact of the maturity of different financial markets on stock price fluctuations. Finally, the multifractal spectrum parameters and daily return rate as input variables, an average accuracy rate of 99.436%, are obtained for the Shanghai Composite Index forecast for the next 30 days, using a 5-layer neural network model. It has particular practical significance for controlling and managing financial risks.
Multifractal, MF-DFA, multifractal spectrum, neural network, financial market
Yanling Jiang, Gaozhao Guan, Beixin Fang. Research on Application of Multifractal Spectrum and Neural Network in Financial Market. Academic Journal of Business & Management (2021) Vol. 3, Issue 7: 102-106. https://doi.org/10.25236/AJBM.2021.030717.
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