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Does trade clustering reduce trading costs? Evidence from periodicity in algorithmic trading

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  • Dmitriy Muravyev
  • Joerg Picard

Abstract

We study how trading activity affects liquidity and volatility by introducing two periodicities in trading activity. First, trades and quote updates are much more frequent within the first 100 ms of a second than during its remainder. Second, trading activity often spikes at intervals of exactly one second. For these two periodicities, higher trade and quote intensities lead to higher volatility, but they do not significantly affect stock liquidity. These periodicities are likely caused by algorithms that trade predictably by repeating instructions in loops with round start times and time increments. Such predictable behavior may provide an example of behavioral biases in trading algorithms.

Suggested Citation

  • Dmitriy Muravyev & Joerg Picard, 2022. "Does trade clustering reduce trading costs? Evidence from periodicity in algorithmic trading," Financial Management, Financial Management Association International, vol. 51(4), pages 1201-1229, December.
    • Handle: RePEc:bla:finmgt:v:51:y:2022:i:4:p:1201-1229
    DOI: 10.1111/fima.12405
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    Cited by:

    1. 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.

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