Detecting the lead–lag effect in stock markets: definition, patterns, and investment strategies

Yongli Li (), Tianchen Wang (), Baiqing Sun () and Chao Liu ()
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Yongli Li: Harbin Institute of Technology
Tianchen Wang: Harbin Institute of Technology
Baiqing Sun: Harbin Institute of Technology
Chao Liu: Harbin Institute of Technology

Financial Innovation, 2022, vol. 8, issue 1, 1-36

Abstract: Abstract Human activities widely exhibit a power-law distribution. Considering stock trading as a typical human activity in the financial domain, the first aim of this paper is to validate whether the well-known power-law distribution can be observed in this activity. Interestingly, this paper determines that the number of accumulated lead–lag days between stock pairs meets the power-law distribution in both the U.S. and Chinese stock markets based on 10 years of trading data. Based on this finding this paper adopts the power-law distribution to formally define the lead–lag effect, detect stock pairs with the lead–lag effect, and then design a pure lead–lag investment strategy as well as enhancement investment strategies by integrating the lead–lag strategy into classic alpha-factor strategies. Tests conducted on 20 different alpha-factor strategies demonstrate that both perform better than the selected benchmark strategy and that the lead–lag strategy provides useful signals that significantly improve the performance of basic alpha-factor strategies. Our results therefore indicate that the lead–lag effect may provide effective information for designing more profitable investment strategies.

Keywords: Power-law distribution; Lead–lag effect; Stock market; Complex network; Investment strategy (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1186/s40854-022-00356-3

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