This paper is devoted to the important yet unexplored subject of crowding effects on market impact, that we call ‘co-impact’. Our analysis is based on a large database of metaorders by institutional investors in the U.S. equity market. We find that the market chiefly reacts to the net order flow of ongoing metaorders, without individually distinguishing them. The joint co-impact of multiple contemporaneous metaorders depends on the total number of metaorders and their mutual sign correlation. Using a simple heuristic model calibrated on data, we reproduce very well the different regimes of the empirical market impact curves as a function of volume fraction φ: square-root for large φ, linear for intermediate φ, and a finite intercept I0 when φ→0. The value of I0 grows with the sign correlation coefficient. Our study sheds light on an apparent paradox: How can a non-linear impact law survive in the presence of a large number of simultaneously executed metaorders?

Bucci, F., Mastromatteo, I., Eisler, Z., Lillo, F., Bouchaud, J., Lehalle, C. (2020). Co-impact: crowding effects in institutional trading activity. QUANTITATIVE FINANCE, 20(2), 193-205 [10.1080/14697688.2019.1660398].

Co-impact: crowding effects in institutional trading activity

Lillo, F.;
2020

Abstract

This paper is devoted to the important yet unexplored subject of crowding effects on market impact, that we call ‘co-impact’. Our analysis is based on a large database of metaorders by institutional investors in the U.S. equity market. We find that the market chiefly reacts to the net order flow of ongoing metaorders, without individually distinguishing them. The joint co-impact of multiple contemporaneous metaorders depends on the total number of metaorders and their mutual sign correlation. Using a simple heuristic model calibrated on data, we reproduce very well the different regimes of the empirical market impact curves as a function of volume fraction φ: square-root for large φ, linear for intermediate φ, and a finite intercept I0 when φ→0. The value of I0 grows with the sign correlation coefficient. Our study sheds light on an apparent paradox: How can a non-linear impact law survive in the presence of a large number of simultaneously executed metaorders?
2020
Bucci, F., Mastromatteo, I., Eisler, Z., Lillo, F., Bouchaud, J., Lehalle, C. (2020). Co-impact: crowding effects in institutional trading activity. QUANTITATIVE FINANCE, 20(2), 193-205 [10.1080/14697688.2019.1660398].
Bucci, F.; Mastromatteo, I.; Eisler, Z.; Lillo, F.; Bouchaud, J.-P.; Lehalle, C.-A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/720766
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