多重分形谱与神经网络在金融市场中的应用研究

Ya-Ping Jiang, Gaozhao Guan, Beixin Fang
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引用次数: 0

摘要

随着金融市场改革创新的不断深入,为了更好地解释市场的股价波动,本文采用传统的有效市场假说进行进一步的研究。本研究表明,上证指数、深证指数和纳斯达克指数具有“尖胖尾”的特征,即分布不正态。基于多重分形谱理论、实证分析和多重分形特征比较结果,采用三个指标分析不同金融市场成熟度对股价波动的影响。最后,利用5层神经网络模型,以多重分形谱参数和日收益率为输入变量,对未来30天上证综合指数进行预测,平均准确率达到99.436%。这对金融风险的控制和管理具有特殊的现实意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Application of Multifractal Spectrum and Neural Network in Financial Market
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.
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