Multifractal characteristics and return predictability in the Chinese stock markets

Xin-Lan Fu, Xing-Lu Gao, Zheng Shan, Yin-Jie Ma (), Zhi-Qiang Jiang () and Wei-Xing Zhou
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Xin-Lan Fu: East China University of Science and Technology
Xing-Lu Gao: East China University of Science and Technology
Zheng Shan: East China University of Science and Technology
Yin-Jie Ma: East China University of Science and Technology
Zhi-Qiang Jiang: East China University of Science and Technology

Annals of Operations Research, 2025, vol. 352, issue 3, No 5, 415-440

Abstract: Abstract By employing the Multifractal detrended fluctuation (MFDFA) analysis methods, the multifractal nature is revealed in the high-frequency data of two typical indexes, the Shanghai Stock Exchange Composite 180 Index (SH180) and the Shenzhen Stock Exchange Composite Index (SZCI). It is found that there is a statistically significant relationship between excess returns and multifractal characteristics, which can be applied to forecast the returns. The in-sample and out-of-sample tests on the return predictability of multifractal characteristics indicate that the multifractal spectral width is a significant return predictor. Additional tests on the S &P 500 index, the exchange rate between Bitcoin and US dollar, four Chinese commodity futures, and the SH180 and SZCI in different sub-periods reveal that the predicting ability of multifractality is robust to the asset type and sample period. The underlying explanation is that multifractal characteristic width contains the information of market volatility and downside tail risk. Our results shed new lights on the application of multifractal nature in asset pricing.

Keywords: Multifractal characteristics; Multifractal detrended fluctuation analysis; Return predictability (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10479-023-05281-x

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