基于MF-DCCA模型的中美股票市场互相关分析与多重分形分析
Cross-correlation and multifractality analysis of the Chinese and American stock markets based on the MF-DCCA model.
作者信息
Chen Yijun, Zhang Jun-Hao, Lu Lei, Xie Zi-Miao
机构信息
College of Finance, Guizhou University of Commerce, Avenida 26, 550014, Guiyang, PR China.
School of Business, Macau University of Science and Technology, Avenida Wailong, Taipa, 999078, Macao, PR China.
出版信息
Heliyon. 2024 Aug 22;10(17):e36537. doi: 10.1016/j.heliyon.2024.e36537. eCollection 2024 Sep 15.
OBJECTIVE
To compare the multifractal features and factors of the Chinese and American stock markets and their correlation, complexity and uncertainty.
METHODS
The paper analyzes the CSI 300 and S&P 500 indices from March 2018 to March 2023 using the MF-DCCA model and removes the long-term memory and nonlinear effects by random reshuffling and phase processing methods.
RESULTS
The paper shows that (1) CSI 300 and S&P 500 have multifractal features, with different long-term memory, complexity and irregularity at different scales; (2) The markets are fractal movements influenced by investors' irrationality and expectations, not efficient markets; (3) Long-term memory and nonlinear effects cause the multifractal features. The paper offers a new perspective and method for the market investors and regulators.
目的
比较中美股票市场的多重分形特征、影响因素及其相关性、复杂性和不确定性。
方法
本文运用多重分形去趋势波动分析（MF-DCCA）模型，对2018年3月至2023年3月的沪深300指数和标准普尔500指数进行分析，并通过随机重排和相位处理方法消除长期记忆和非线性效应。
结果
研究表明：（1）沪深300指数和标准普尔500指数具有多重分形特征，在不同尺度上具有不同的长期记忆、复杂性和不规则性；（2）市场是受投资者非理性和预期影响的分形运动，而非有效市场；（3）长期记忆和非线性效应导致了多重分形特征。本文为市场投资者和监管者提供了新的视角和方法。
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