IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1609.02395.html
   My bibliography  Save this paper

Dissecting cross-impact on stock markets: An empirical analysis

Author

Listed:
  • Michael Benzaquen
  • Iacopo Mastromatteo
  • Zoltan Eisler
  • Jean-Philippe Bouchaud

Abstract

The vast majority of market impact studies assess each product individually, and the interactions between the different order flows are disregarded. This strong approximation may lead to an underestimation of trading costs and possible contagion effects. Transactions in fact mediate a significant part of the correlation between different instruments. In turn, liquidity shares the sectorial structure of market correlations, which can be encoded as a set of eigenvalues and eigenvectors. We introduce a multivariate linear propagator model that successfully describes such a structure, and accounts for a significant fraction of the covariance of stock returns. We dissect the various dynamical mechanisms that contribute to the joint dynamics of assets. We also define two simplified models with substantially less parameters in order to reduce overfitting, and show that they have superior out-of-sample performance.

Suggested Citation

  • Michael Benzaquen & Iacopo Mastromatteo & Zoltan Eisler & Jean-Philippe Bouchaud, 2016. "Dissecting cross-impact on stock markets: An empirical analysis," Papers 1609.02395, arXiv.org, revised Nov 2016.
  • Handle: RePEc:arx:papers:1609.02395
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1609.02395
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jean-Philippe Bouchaud & J. Doyne Farmer & Fabrizio Lillo, 2008. "How markets slowly digest changes in supply and demand," Papers 0809.0822, arXiv.org.
    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. Iacopo Mastromatteo & Michael Benzaquen & Zoltan Eisler & Jean-Philippe Bouchaud, 2017. "Trading Lightly: Cross-Impact and Optimal Portfolio Execution," Papers 1702.03838, arXiv.org, revised Aug 2017.
    2. Seungki Min & Costis Maglaras & Ciamac C. Moallemi, 2018. "Cross-Sectional Variation of Intraday Liquidity, Cross-Impact, and their Effect on Portfolio Execution," Papers 1811.05524, arXiv.org.
    3. Shanshan Wang, 2017. "Trading strategies for stock pairs regarding to the cross-impact cost," Papers 1701.03098, arXiv.org, revised Jul 2017.

    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. Juan C. Henao-Londono & Sebastian M. Krause & Thomas Guhr, 2021. "Price response functions and spread impact in correlated financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(4), pages 1-20, April.
    2. B. Tóth & F. Lillo & J. D. Farmer, 2010. "Segmentation algorithm for non-stationary compound Poisson processes," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 78(2), pages 235-243, November.
    3. Thibault Jaisson, 2014. "Market impact as anticipation of the order flow imbalance," Papers 1402.1288, arXiv.org.
    4. Michael Benzaquen & Jean-Philippe Bouchaud, 2017. "A fractional reaction-diffusion description of supply and demand," Papers 1704.02638, arXiv.org, revised Aug 2017.
    5. Rama Cont & Adrien De Larrard, 2011. "Price dynamics in a Markovian limit order market," Papers 1104.4596, arXiv.org.
    6. repec:hal:wpaper:hal-00777941 is not listed on IDEAS
    7. Jonathan A. Ch'avez-Casillas & Jos'e E. Figueroa-L'opez, 2014. "One-level limit order book models with memory and variable spread," Papers 1407.5684, arXiv.org, revised Mar 2016.
    8. M. Cristelli & V. Alfi & L. Pietronero & A. Zaccaria, 2010. "Liquidity crisis, granularity of the order book and price fluctuations," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 73(1), pages 41-49, January.
    9. Alexander Lykov & Stepan Muzychka & Kirill Vaninsky, 2016. "Investor'S Sentiment In Multi-Agent Model Of The Continuous Double Auction," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(06), pages 1-29, September.
    10. Ban Zheng & Eric Moulines & Fr'ed'eric Abergel, 2012. "Price Jump Prediction in Limit Order Book," Papers 1204.1381, arXiv.org.
    11. Aaron Wheeler & Jeffrey D. Varner, 2023. "Scalable Agent-Based Modeling for Complex Financial Market Simulations," Papers 2312.14903, arXiv.org, revised Jan 2024.
    12. Enzo Busseti & Fabrizio Lillo, 2012. "Calibration of optimal execution of financial transactions in the presence of transient market impact," Papers 1206.0682, arXiv.org.
    13. Michael Benzaquen & Jean-Philippe Bouchaud, 2018. "A fractional reaction–diffusion description of supply and demand," Post-Print hal-02323544, HAL.
    14. B. Tóth & Z. Eisler & F. Lillo & J. Kockelkoren & J.-P. Bouchaud & J.D. Farmer, 2012. "How does the market react to your order flow?," Quantitative Finance, Taylor & Francis Journals, vol. 12(7), pages 1015-1024, May.
    15. Lublóy, Ágnes & Gyarmati, Ákos & Váradi, Kata, 2012. "Virtuális árhatás a Budapesti Értéktőzsdén [Virtual price effects on the Budapest stock exchange]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(5), pages 508-539.
    16. Chen, Jingnan & Feng, Liming & Peng, Jiming, 2015. "Optimal deleveraging with nonlinear temporary price impact," European Journal of Operational Research, Elsevier, vol. 244(1), pages 240-247.
    17. Jakob Albers & Mihai Cucuringu & Sam Howison & Alexander Y. Shestopaloff, 2021. "Fragmentation, Price Formation, and Cross-Impact in Bitcoin Markets," Papers 2108.09750, arXiv.org.
    18. Stephan Grimm & Thomas Guhr, 2018. "How spread changes affect the order book: Comparing the price responses of order deletions and placements to trades," Papers 1812.09067, arXiv.org.
    19. Ban Zheng & Eric Moulines & Frédéric Abergel, 2013. "Price jump prediction in a limit order book," Post-Print hal-00684716, HAL.
    20. Chávez-Casillas, Jonathan A. & Figueroa-López, José E., 2017. "A one-level limit order book model with memory and variable spread," Stochastic Processes and their Applications, Elsevier, vol. 127(8), pages 2447-2481.
    21. F. Caccioli & M. Marsili & P. Vivo, 2009. "Eroding market stability by proliferation of financial instruments," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(4), pages 467-479, October.

    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:1609.02395. 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: http://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.