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The short-term predictability pockets in China

Author

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  • Dong, Dairui
  • Hua, Xia
  • Wang, Binxu

Abstract

Previous studies by Farmer et al. (2023, 2024) identified local pockets of predictability in the U.S. market using a non-parametric method: the FST algorithm. We applied this algorithm to China's A-share market, which is characterized by a large proportion of retail investors and pronounced behavioral biases. To adapt to China's unique context, we incorporated three sentiment-driven variables while retaining the original ones. Our findings confirm the presence of predictability pockets in China, with IPO first-day returns and realized variance demonstrating significant predictive power. Although the original FST algorithm requires localized adjustments, we confirm the existence of these predictability pockets in China's stock market. Overall, our research indicates potential for practical trading strategies based on the FST algorithm in retail-dominated markets.

Suggested Citation

  • Dong, Dairui & Hua, Xia & Wang, Binxu, 2025. "The short-term predictability pockets in China," Pacific-Basin Finance Journal, Elsevier, vol. 91(C).
    • Handle: RePEc:eee:pacfin:v:91:y:2025:i:c:s0927538x24003718
    DOI: 10.1016/j.pacfin.2024.102619
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