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Smart money in China's A-share market: Evidence from big data

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  • Chen, Zhenhua
  • Liu, Zhenya
  • Teka, Hanen
  • Zhang, Yifan

Abstract

In this study, we propose a bar-level tracker of smart money trades by detecting the trading aggressiveness of informed traders. Accordingly, we define monthly smart money measures to identify the direction of informed trades. By using the 1-min transaction data in China’s A-share market from 1999 to 2019, we find a negative cross-sectional relationship between the smart money measures and stock future returns. We construct smart money strategies based on the fuzzy c-means (FCM) clustering algorithm, wherein the optimal strategy produces an annual Sharpe ratio of 1.169. Our findings indicate that the FCM-based portfolio formation could outperform the conventional sorting-based strategies. This study may be useful for research on smart money trades and the analysis of cross-sectional variation in returns.

Suggested Citation

  • Chen, Zhenhua & Liu, Zhenya & Teka, Hanen & Zhang, Yifan, 2022. "Smart money in China's A-share market: Evidence from big data," Research in International Business and Finance, Elsevier, vol. 61(C).
    • Handle: RePEc:eee:riibaf:v:61:y:2022:i:c:s0275531922000514
    DOI: 10.1016/j.ribaf.2022.101663
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    More about this item

    Keywords

    China’s A-share; Smart money; Trading aggressiveness; Fuzzy c-means clustering;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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