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Price Impact Without Averaging

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Listed:
  • Claudio Bellani
  • Damiano Brigo
  • Mikko S. Pakkanen
  • Leandro Sánchez-Betancourt

Abstract

We present a method to estimate price impact in order-driven markets that does not require averaging over executions or scenarios. Given order book data associated with one single execution of a sell metaorder, we estimate its contribution to price decrease during the trade. We do so by modelling the limit order book using a state-dependent Hawkes process, and by defining the price impact profile of the execution as a function of the compensator of the state-dependent Hawkes process. We apply our method to a dataset from NASDAQ, and we conclude that the scheduling of sell child orders has a bigger impact on price than their sizes.

Suggested Citation

  • Claudio Bellani & Damiano Brigo & Mikko S. Pakkanen & Leandro Sánchez-Betancourt, 2023. "Price Impact Without Averaging," Applied Mathematical Finance, Taylor & Francis Journals, vol. 30(4), pages 175-206, July.
    • Handle: RePEc:taf:apmtfi:v:30:y:2023:i:4:p:175-206
    DOI: 10.1080/1350486X.2024.2303078
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