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Trade-time clustering

Author

Listed:
  • Jeffrey R. Black

    (University of Memphis)

  • Pankaj K. Jain

    (University of Memphis)

  • Wei Sun

    (Saginaw Valley State University)

Abstract

We introduce an intraday measure of trade-time clustering which estimates periodic grouping of trades, integrating volume and trade duration. This measure consistently detects informed trading superior to volume and duration. We find that in stable markets, both lagged information flow and liquidity are positively associated with trade-time clustering, while in volatile markets only lagged liquidity is. Trade-time clustering is positively associated with contemporaneous price impact, price volatility, and market efficiency, suggesting that trade clustering contributes to price discovery. Following increased trade-time clustering, we observe more aggressive orders from informed traders, but less high-frequency trading in stable markets.

Suggested Citation

  • Jeffrey R. Black & Pankaj K. Jain & Wei Sun, 2023. "Trade-time clustering," Review of Quantitative Finance and Accounting, Springer, vol. 60(3), pages 1209-1242, April.
    • Handle: RePEc:kap:rqfnac:v:60:y:2023:i:3:d:10.1007_s11156-023-01125-8
    DOI: 10.1007/s11156-023-01125-8
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    More about this item

    Keywords

    Trade-time clustering; Trade concentration; High frequency trading; Trading cost;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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