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

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.

Automated summary

This study validates the power-law distribution in stock trading activity and identifies the lead-lag effect based on 10 years of trading data. It designs investment strategies utilizing this effect, which significantly improve the performance of basic alpha-factor strategies.