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Cross-Sectional Variation of Intraday Liquidity, Cross-Impact, and Their Effect on Portfolio Execution

Author

Listed:
  • Seungki Min

    (Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea)

  • Costis Maglaras

    (Graduate School of Business, Columbia University, New York, New York 10027)

  • Ciamac C. Moallemi

    (Graduate School of Business, Columbia University, New York, New York 10027)

Abstract

An analysis of intraday volumes for the S&P 500 constituent stocks illustrates that (i) volume surprises (i.e., deviations from forecasted trading volumes) are correlated across stocks and that (ii) this correlation increases during the last few hours of the trading session. These observations can be attributed partly to the prevalence of portfolio trading activity that is implicit in the growth of passive (systematic) investment strategies and partly to the increased trading intensity of such strategies toward the end of the trading session. In this paper, we investigate the consequences of such portfolio liquidity on price impact and portfolio execution. We derive a linear cross-asset market impact from a stylized model that explicitly captures the fact that a certain fraction of natural liquidity providers trade only portfolios of stocks whenever they choose to execute. We find that because of cross-impact and its intraday variation, it is optimal for a risk-neutral cost-minimizing liquidator to execute a portfolio of orders in a coupled manner, as opposed to the separable volume-weighted average price execution schedule that is often assumed. The optimal schedule couples the execution on the individual stocks so as to take advantage of increased portfolio liquidity toward the end of the day. A worst case analysis shows that the potential cost reduction from this optimized execution schedule over the separable approach can be as high as 15% for plausible model parameters. Finally, we discuss how to estimate cross-sectional price impact if one had a data set of realized portfolio transaction records by exploiting the low-rank structure of its coefficient matrix suggested by our analysis.

Suggested Citation

  • 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.
    • Handle: RePEc:inm:oropre:v:70:y:2022:i:2:p:830-846
    DOI: 10.1287/opre.2021.2201
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    1. Aur'elien Alfonsi & Antje Fruth & Alexander Schied, 2007. "Optimal execution strategies in limit order books with general shape functions," Papers 0708.1756, arXiv.org, revised Feb 2010.
    2. M. Schneider & F. Lillo, 2019. "Cross-impact and no-dynamic-arbitrage," Quantitative Finance, Taylor & Francis Journals, vol. 19(1), pages 137-154, January.
    3. David B. Brown & Bruce Ian Carlin & Miguel Sousa Lobo, 2010. "Optimal Portfolio Liquidation with Distress Risk," Management Science, INFORMS, vol. 56(11), pages 1997-2014, November.
    4. 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.
    5. Lo, Andrew W & Wang, Jiang, 2000. "Trading Volume: Definitions, Data Analysis, and Implications of Portfolio Theory," The Review of Financial Studies, Society for Financial Studies, vol. 13(2), pages 257-300.
    6. 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.
    7. Aurelien Alfonsi & Antje Fruth & Alexander Schied, 2010. "Optimal execution strategies in limit order books with general shape functions," Quantitative Finance, Taylor & Francis Journals, vol. 10(2), pages 143-157.
    8. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    9. Karolyi, G. Andrew & Lee, Kuan-Hui & van Dijk, Mathijs A., 2012. "Understanding commonality in liquidity around the world," Journal of Financial Economics, Elsevier, vol. 105(1), pages 82-112.
    10. Gerry Tsoukalas & Jiang Wang & Kay Giesecke, 2019. "Dynamic Portfolio Execution," Management Science, INFORMS, vol. 67(5), pages 2015-2040, May.
    11. 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.
    12. Mehdi Tomas & Iacopo Mastromatteo & Michael Benzaquen, 2020. "How to build a cross-impact model from first principles: Theoretical requirements and empirical results," Working Papers hal-02567489, HAL.
    13. Gur Huberman & Werner Stanzl, 2005. "Optimal Liquidity Trading," Review of Finance, Springer, vol. 9(2), pages 165-200, June.
    14. Gianbiagio Curato & Jim Gatheral & Fabrizio Lillo, 2017. "Optimal execution with non-linear transient market impact," Quantitative Finance, Taylor & Francis Journals, vol. 17(1), pages 41-54, January.
    15. Jim Gatheral, 2010. "No-dynamic-arbitrage and market impact," Quantitative Finance, Taylor & Francis Journals, vol. 10(7), pages 749-759.
    16. Ioanid Rosu, 2009. "A Dynamic Model of the Limit Order Book," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4601-4641, November.
    17. Itzhak Ben-David & Francesco A. Franzoni & Rabih Moussawi, 2016. "Exchange Traded Funds (ETFs)," Swiss Finance Institute Research Paper Series 16-64, Swiss Finance Institute.
    18. Obizhaeva, Anna A. & Wang, Jiang, 2013. "Optimal trading strategy and supply/demand dynamics," Journal of Financial Markets, Elsevier, vol. 16(1), pages 1-32.
    19. Fr'ed'eric Bucci & Iacopo Mastromatteo & Michael Benzaquen & Jean-Philippe Bouchaud, 2019. "Impact is not just volatility," Papers 1905.04569, arXiv.org.
    20. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    21. Bertsimas, Dimitris & Lo, Andrew W., 1998. "Optimal control of execution costs," Journal of Financial Markets, Elsevier, vol. 1(1), pages 1-50, April.
    22. Ioanid Rosu, 2009. "A Dynamic Model of the Limit Order Book," Post-Print hal-00515873, HAL.
    23. Robert Almgren, 2003. "Optimal execution with nonlinear impact functions and trading-enhanced risk," Applied Mathematical Finance, Taylor & Francis Journals, vol. 10(1), pages 1-18.
    24. Frédéric Bucci & Iacopo Mastromatteo & Michael Benzaquen & Jean-Philippe Bouchaud, 2019. "Impact is not just volatility," Post-Print hal-02323182, HAL.
    25. 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.
    26. Jennings, Robert H & Starks, Laura T & Fellingham, John C, 1981. "An Equilibrium Model of Asset Trading with Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 36(1), pages 143-161, March.
    27. 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.
    28. Bence Toth & Zoltan Eisler & Jean-Philippe Bouchaud, 2017. "The short-term price impact of trades is universal," Papers 1702.08029, arXiv.org, revised Jan 2018.
    29. 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.
    30. Gur Huberman & Werner Stanzl, 2004. "Price Manipulation and Quasi-Arbitrage," Econometrica, Econometric Society, vol. 72(4), pages 1247-1275, July.
    31. Andrew Koch & Stefan Ruenzi & Laura Starks, 2016. "Editor's Choice Commonality in Liquidity: A Demand-Side Explanation," The Review of Financial Studies, Society for Financial Studies, vol. 29(8), pages 1943-1974.
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    Cited by:

    1. Natascha Hey & Iacopo Mastromatteo & Johannes Muhle-Karbe & Kevin Webster, 2025. "Trading with Concave Price Impact and Impact Decay—Theory and Evidence," Operations Research, INFORMS, vol. 73(3), pages 1230-1247, May.
    2. Chapkovski, Philipp & Cordoni, Francesco & Giannetti, Caterina & Lillo, Fabrizio, 2025. "Cross−impact and price bubbles in hybrid financial markets," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 118(C).
    3. Johannes Muhle-Karbe & Zexin Wang & Kevin Webster, 2024. "Stochastic Liquidity as a Proxy for Nonlinear Price Impact," Operations Research, INFORMS, vol. 72(2), pages 444-458, March.
    4. Mihai Cucuringu & Kang Li & Chao Zhang, 2025. "Forecasting Intraday Volume in Equity Markets with Machine Learning," Papers 2505.08180, arXiv.org.
    5. Masamitsu Ohnishi & Makoto Shimoshimizu, 2022. "Optimal Pair–Trade Execution with Generalized Cross–Impact," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(2), pages 253-289, June.

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