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The amazing power of dimensional analysis: Quantifying market impact

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  • Mathias Pohl
  • Alexander Ristig
  • Walter Schachermayer
  • Ludovic Tangpi

Abstract

This note complements the inspiring work on dimensional analysis and market microstructure by Kyle and Obizhaeva [18]. Following closely these authors, our main result shows by a similar argument as usually applied in physics the following remarkable fact. If the market impact of a meta-order only depends on four well-defined and financially meaningful variables, then -- up to a constant -- there is only one possible form of this dependence. In particular, the market impact is proportional to the square-root of the size of the meta-order. This theorem can be regarded as a special case of a more general result of Kyle and Obizhaeva. These authors consider five variables which might have an influence on the size of the market impact. In this case one finds a richer variety of possible functional relations which we precisely characterize. We also discuss the analogies to classical arguments from physics, such as the period of a pendulum.

Suggested Citation

  • Mathias Pohl & Alexander Ristig & Walter Schachermayer & Ludovic Tangpi, 2017. "The amazing power of dimensional analysis: Quantifying market impact," Papers 1702.05434, arXiv.org, revised Sep 2017.
    • Handle: RePEc:arx:papers:1702.05434
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    References listed on IDEAS

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    1. Albert S. Kyle & Anna Obizhaeva, 2016. "Market Microstructure Invariance: A Dynamic Equilibrium Model," Working Papers w0228, Center for Economic and Financial Research (CEFIR).
    2. Xavier Gabaix & Parameswaran Gopikrishnan & Vasiliki Plerou & H. Eugene Stanley, 2006. "Institutional Investors and Stock Market Volatility," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(2), pages 461-504.
    3. Nataliya Bershova & Dmitry Rakhlin, 2013. "The non-linear market impact of large trades: evidence from buy-side order flow," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1759-1778, November.
    4. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    5. 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.
    6. Esteban Moro & Javier Vicente & Luis G. Moyano & Austin Gerig & J. Doyne Farmer & Gabriella Vaglica & Fabrizio Lillo & Rosario N. Mantegna, 2009. "Market impact and trading profile of large trading orders in stock markets," Papers 0908.0202, arXiv.org.
    7. Bence Toth & Yves Lemperiere & Cyril Deremble & Joachim de Lataillade & Julien Kockelkoren & Jean-Philippe Bouchaud, 2011. "Anomalous price impact and the critical nature of liquidity in financial markets," Papers 1105.1694, arXiv.org, revised Nov 2011.
    8. Iacopo Mastromatteo & Bence Toth & Jean-Philippe Bouchaud, 2013. "Agent-based models for latent liquidity and concave price impact," Papers 1311.6262, arXiv.org, revised Dec 2014.
    9. Albert S. Kyle & Anna Obizhaeva, 2016. "Market Microstructure Invariance: A Dynamic Equilibrium Model," Working Papers w0228, New Economic School (NES).
    10. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    11. Foucault, Thierry & Pagano, Marco & Roell, Ailsa, 2013. "Market Liquidity: Theory, Evidence, and Policy," OUP Catalogue, Oxford University Press, number 9780199936243.
    12. J. Donier & J. Bonart & I. Mastromatteo & J.-P. Bouchaud, 2015. "A fully consistent, minimal model for non-linear market impact," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1109-1121, July.
    13. Jonathan Donier & Julius Bonart & Iacopo Mastromatteo & Jean-Philippe Bouchaud, 2014. "A fully consistent, minimal model for non-linear market impact," Papers 1412.0141, arXiv.org, revised Mar 2015.
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    Citations

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    Cited by:

    1. Sergey Nadtochiy, 2022. "A simple microstructural explanation of the concavity of price impact," Mathematical Finance, Wiley Blackwell, vol. 32(1), pages 78-113, January.
    2. Sergey Nadtochiy, 2020. "A simple microstructural explanation of the concavity of price impact," Papers 2001.01860, arXiv.org, revised Dec 2020.
    3. Dilip B. Madan & Wim Schoutens & King Wang, 2020. "Bilateral multiple gamma returns: Their risks and rewards," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 7(01), pages 1-27, March.
    4. 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.
    5. Thierry Roncalli & Amina Cherief & Fatma Karray-Meziou & Margaux Regnault, 2021. "Liquidity Stress Testing in Asset Management -- Part 2. Modeling the Asset Liquidity Risk," Papers 2105.08377, arXiv.org.
    6. Mathias Pohl & Alexander Ristig & Walter Schachermayer & Ludovic Tangpi, 2018. "Theoretical and empirical analysis of trading activity," Papers 1803.04892, arXiv.org, revised Oct 2018.
    7. Tathagata Banerjee & Zachary Feinstein, 2019. "Price mediated contagion through capital ratio requirements with VWAP liquidation prices," Papers 1910.12130, arXiv.org, revised Feb 2021.
    8. Banerjee, Tathagata & Feinstein, Zachary, 2021. "Price mediated contagion through capital ratio requirements with VWAP liquidation prices," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1147-1160.
    9. Paul Jusselin & Mathieu Rosenbaum, 2018. "No-arbitrage implies power-law market impact and rough volatility," Papers 1805.07134, arXiv.org.

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