Trade-time clustering

Jeffrey R. Black (), Pankaj K. Jain () and Wei Sun ()
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Jeffrey R. Black: University of Memphis
Pankaj K. Jain: University of Memphis
Wei Sun: Saginaw Valley State University

Review of Quantitative Finance and Accounting, 2023, vol. 60, issue 3, No 11, 1209-1242

Abstract: 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.

Keywords: Trade-time clustering; Trade concentration; High frequency trading; Trading cost (search for similar items in EconPapers)
JEL-codes: G10 G12 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11156-023-01125-8

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