Cross-correlation and multifractality analysis of the Chinese and American stock markets based on the MF-DCCA model

Abstract

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.

Keywords

• Chinese and American stock markets
• Multifractal characteristics
• Long-term memory
• Nonlinearity
• MF-DCCA model