IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2610.10053.html

On Bonart's interpretation of the Square-Root Impact Law

Author

Listed:
  • J. -P. Bouchaud
  • I. Mastromatteo
  • B. Toth

Abstract

The square-root impact law (SRIL), $I = Y\sigma\sqrt{Q/V}$, bundles two facts that a single mechanism must explain at once: a shape (impact proportional to square-root of traded volume $Q$) and an amplitude ($Y=O(1)$, independent of the participation rate $\varphi$). Bonart has recently proposed an elegant solution: if realized and counterfactual prices are both diffusive, information-neutral impact must have white increments and the SRIL follows without the wart. We reformulate and simplify his argument, and foreground the ingredient he himself regards as essential --- that the market whitens the stationary stream of each participant's metaorders, not any isolated one. The Lillo--Mike--Farmer model satisfies his premises, yet gives an isolated metaorder the super-square-root impact $\varphi^{(1-\gamma)/2}Q^{(1+\gamma)/2}$, $\gamma\in(0,1)$, because single metaorders (i.e. not part of a stream) are statistically invisible and thus priced mechanically. We then construct an explicit multi-agent propagator that realizes Bonart's whitening, and show it reproduces the clean SRIL precisely when the market can attribute trades to their issuer. But correct re-attribution of anonymous trades is a formidable task, which requires markets to behave as implausibly efficient signal processing machines. The stream hypothesis makes a sharp, falsifiable prediction --- isolated metaorders, well separated in time, should not obey the SRIL --- that does not seem agree with empirical data known to us. Independently, a volume-conservation argument singles out the square-root law and lays bare the step the diffusivity route must assume: diffusivity fixes the variance of impact --- an additive, stationary, age-blind quantity --- whereas the SRIL is a law for the mean impact, which marginally decays as $1/\sqrt{\text{age}}$ and therefore demands an origin of time.

Suggested Citation

  • J. -P. Bouchaud & I. Mastromatteo & B. Toth, 2026. "On Bonart's interpretation of the Square-Root Impact Law," Papers 2610.10053, arXiv.org.
  • Handle: RePEc:arx:papers:2610.10053
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2610.10053
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guillaume Maitrier & Gr'egoire Loeper & Jean-Philippe Bouchaud, 2025. "The Subtle Interplay between Square-root Impact, Order Imbalance & Volatility II: An Artificial Market Generator," Papers 2509.05065, arXiv.org.
    2. Jutta G. Kurth & Zoltan Eisler & Adam Rej & Jean-Philippe Bouchaud, 2026. "Is Trend Still Your Friend?: A Microstructural Account of the Demise of Short-Term Trend-Following," Papers 2607.01550, arXiv.org.
    3. Louis Saddier & Matteo Marsili, 2023. "A Bayesian theory of market impact," Papers 2303.08867, arXiv.org, revised May 2024.
    4. Julius F. Bonart, 2026. "Diffusive in plain sight: An inconspicuous law of market impact," Papers 2606.07059, arXiv.org, revised Oct 2026.
    5. Fr'ed'eric Bucci & Iacopo Mastromatteo & Michael Benzaquen & Jean-Philippe Bouchaud, 2019. "Impact is not just volatility," Papers 1905.04569, arXiv.org.
    6. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    7. Guillaume Maitrier & Grégoire Loeper & Kiyoshi Kanazawa & Jean-Philippe Bouchaud, 2026. "The ‘double’ square-root law: evidence for the mechanical origin of market impact using Tokyo stock exchange data," Quantitative Finance, Taylor & Francis Journals, vol. 26(4), pages 491-503, April.
    8. Michael Benzaquen & Jean-Philippe Bouchaud, 2018. "A fractional reaction–diffusion description of supply and demand," Post-Print hal-02323544, HAL.
    9. Frédéric Bucci & Iacopo Mastromatteo & Michael Benzaquen & Jean-Philippe Bouchaud, 2019. "Impact is not just volatility," Quantitative Finance, Taylor & Francis Journals, vol. 19(11), pages 1763-1766, November.
    10. C. Gomes & H. Waelbroeck, 2015. "Is market impact a measure of the information value of trades? Market response to liquidity vs. informed metaorders," Quantitative Finance, Taylor & Francis Journals, vol. 15(5), pages 773-793, May.
    11. Paul Jusselin & Mathieu Rosenbaum, 2020. "No‐arbitrage implies power‐law market impact and rough volatility," Mathematical Finance, Wiley Blackwell, vol. 30(4), pages 1309-1336, October.
    12. Frédéric Bucci & Iacopo Mastromatteo & Michael Benzaquen & Jean-Philippe Bouchaud, 2019. "Impact is not just volatility," Post-Print hal-02323182, HAL.
    13. F. Lillo & Szabolcs Mike & J. Doyne Farmer, 2004. "A theory for long-memory in supply and demand," Papers cond-mat/0412708, arXiv.org, revised Mar 2005.
    14. Michael Benzaquen & Jean-Philippe Bouchaud, 2018. "A fractional reaction–diffusion description of supply and demand," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 91(2), pages 1-7, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Julius F. Bonart, 2026. "Diffusive Market Impact: A Consistent Microfoundation," Papers 2610.11691, arXiv.org, revised Oct 2026.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guillaume Maitrier & Jean-Philippe Bouchaud, 2025. "The Subtle Interplay between Square-root Impact, Order Imbalance & Volatility: A Unifying Framework," Papers 2506.07711, arXiv.org, revised Mar 2026.
    2. Guillaume Maitrier & Gr'egoire Loeper & Kiyoshi Kanazawa & Jean-Philippe Bouchaud, 2025. "The "double" square-root law: Evidence for the mechanical origin of market impact using Tokyo Stock Exchange data," Papers 2502.16246, arXiv.org, revised Aug 2025.
    3. Guillaume Maitrier & Gr'egoire Loeper & Jean-Philippe Bouchaud, 2025. "Generating realistic metaorders from public data," Papers 2503.18199, arXiv.org, revised Apr 2025.
    4. Fabrizio Lillo, 2021. "Order flow and price formation," Papers 2105.00521, arXiv.org.
    5. Seungki Min & Costis Maglaras & Ciamac C. Moallemi, 2022. "Cross-Sectional Variation of Intraday Liquidity, Cross-Impact, and Their Effect on Portfolio Execution," Operations Research, INFORMS, vol. 70(2), pages 830-846, March.
    6. Jean-Philippe Bouchaud, 2021. "The Inelastic Market Hypothesis: A Microstructural Interpretation," Papers 2108.00242, arXiv.org, revised Jan 2022.
    7. Chanaka Edirisinghe & Jingnan Chen & Jaehwan Jeong, 2023. "Optimal Leveraged Portfolio Selection Under Quasi-Elastic Market Impact," Operations Research, INFORMS, vol. 71(5), pages 1558-1576, September.
    8. Julius F. Bonart, 2026. "Diffusive Market Impact: A Consistent Microfoundation," Papers 2610.11691, arXiv.org, revised Oct 2026.
    9. Claudio Bellani & Damiano Brigo & Mikko Pakkanen & Leandro Sanchez-Betancourt, 2021. "Non-average price impact in order-driven markets," Papers 2110.00771, arXiv.org, revised Jan 2022.
    10. Alejandro Rodriguez Dominguez & Miquel Noguer i Alonso, 2026. "Robustness or Crowding: Experimental Design for Trading Strategy Capacity," Papers 2608.08405, arXiv.org.
    11. Umut c{C}etin & Mingwei Lin & Giulia Livieri, 2026. "When large trades are not (automatically) news: liquidity tail risk and price discovery," Papers 2607.01198, arXiv.org, revised Jul 2026.
    12. Julius F. Bonart, 2026. "Diffusive in plain sight: An inconspicuous law of market impact," Papers 2606.07059, arXiv.org, revised Oct 2026.
    13. Jonathan Donier, 2012. "Market Impact with Autocorrelated Order Flow under Perfect Competition," Papers 1212.4770, arXiv.org.
    14. Thibault Jaisson, 2014. "Market impact as anticipation of the order flow imbalance," Papers 1402.1288, arXiv.org.
    15. J. Doyne Farmer & Austin Gerig & Fabrizio Lillo & Henri Waelbroeck, 2013. "How efficiency shapes market impact," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1743-1758, November.
    16. Yamamoto, Ryuichi, 2019. "Dynamic Predictor Selection And Order Splitting In A Limit Order Market," Macroeconomic Dynamics, Cambridge University Press, vol. 23(5), pages 1757-1792, July.
    17. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    18. Johann Lussange & Stefano Vrizzi & Sacha Bourgeois-Gironde & Stefano Palminteri & Boris Gutkin, 2023. "Stock Price Formation: Precepts from a Multi-Agent Reinforcement Learning Model," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1523-1544, April.
    19. Umut c{C}etin & Henri Waelbroeck, 2020. "Informed trading, limit order book and implementation shortfall: equilibrium and asymptotics," Papers 2003.04425, arXiv.org.
    20. Johann Lussange & Ivan Lazarevich & Sacha Bourgeois-Gironde & Stefano Palminteri & Boris Gutkin, 2021. "Modelling Stock Markets by Multi-agent Reinforcement Learning," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 113-147, January.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2610.10053. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: https://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.