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Order-Flow Filtration and Directional Association with Short-Horizon Returns

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  • Aditya Nittur Anantha
  • Shashi Jain
  • Prithwish Maiti

Abstract

Electronic markets generate dense order flow with many transient orders, which degrade directional signals derived from the limit order book (LOB). We study whether simple structural filters on order lifetime, modification count, and modification timing sharpen the association between order book imbalance (OBI) and short-horizon returns in BankNifty index futures, where unfiltered OBI is already known to be a strong short-horizon directional indicator. The efficacy of each filter is evaluated using a three-step diagnostic ladder: contemporaneous correlations, linear association between discretised regimes, and Hawkes event-time excitation between OBI and return regimes. Our results indicate that filtration of the aggregate order flow produces only modest changes relative to the unfiltered benchmark. By contrast, when filters are applied on the parent orders of executed trades, the resulting OBI series exhibits systematically stronger directional association. Motivated by recent regulatory initiatives to curb noisy order flow, we treat the association between OBI and short-horizon returns as a policy-relevant diagnostic of market quality. We then compare unfiltered and filtered OBI series, using tick-by-tick data from the National Stock Exchange of India, to infer how structural filters on the order flow affect OBI-return dynamics in an emerging market setting.

Suggested Citation

  • Aditya Nittur Anantha & Shashi Jain & Prithwish Maiti, 2025. "Order-Flow Filtration and Directional Association with Short-Horizon Returns," Papers 2507.22712, arXiv.org, revised Dec 2025.
  • Handle: RePEc:arx:papers:2507.22712
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    References listed on IDEAS

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    1. Hamza Bodor & Laurent Carlier, 2024. "A Novel Approach to Queue-Reactive Models: The Importance of Order Sizes," Papers 2405.18594, arXiv.org.
    2. Stephen J. Hardiman & Nicolas Bercot & Jean-Philippe Bouchaud, 2013. "Critical reflexivity in financial markets: a Hawkes process analysis," Papers 1302.1405, arXiv.org, revised Jun 2013.
    3. Petter N. Kolm & Jeremy Turiel & Nicholas Westray, 2023. "Deep order flow imbalance: Extracting alpha at multiple horizons from the limit order book," Mathematical Finance, Wiley Blackwell, vol. 33(4), pages 1044-1081, October.
    4. Rama Cont & Arseniy Kukanov & Sasha Stoikov, 2014. "The Price Impact of Order Book Events," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 47-88.
    5. Weibing Huang & Charles-Albert Lehalle & Mathieu Rosenbaum, 2015. "Simulating and Analyzing Order Book Data: The Queue-Reactive Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 107-122, March.
    6. Bowsher, Clive G., 2007. "Modelling security market events in continuous time: Intensity based, multivariate point process models," Journal of Econometrics, Elsevier, vol. 141(2), pages 876-912, December.
    7. Stephen Hardiman & Nicolas Bercot & Jean-Philippe Bouchaud, 2013. "Critical reflexivity in financial markets: a Hawkes process analysis," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(10), pages 1-9, October.
    8. Sobin Joseph & Shashi Jain, 2023. "A neural network based model for multi-dimensional nonlinear Hawkes processes," Papers 2303.03073, arXiv.org.
    9. Isao Yagi & Mahiro Hoshino & Takanobu Mizuta & Ning Cai, 2023. "Impact of High-Frequency Trading with an Order Book Imbalance Strategy on Agent-Based Stock Markets," Complexity, Hindawi, vol. 2023, pages 1-12, February.
    10. V. Filimonov & D. Sornette, 2015. "Apparent criticality and calibration issues in the Hawkes self-excited point process model: application to high-frequency financial data," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1293-1314, August.
    11. Marcello Rambaldi & Emmanuel Bacry & Fabrizio Lillo, 2017. "The role of volume in order book dynamics: a multivariate Hawkes process analysis," Quantitative Finance, Taylor & Francis Journals, vol. 17(7), pages 999-1020, July.
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