Price Impact Without Averaging

Claudio Bellani, Damiano Brigo, Mikko S. Pakkanen and Leandro Sánchez-Betancourt

Applied Mathematical Finance, 2023, vol. 30, issue 4, 175-206

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.

Date: 2023
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DOI: 10.1080/1350486X.2024.2303078

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