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Optimal execution with stochastic delay

Author

Listed:
  • Álvaro Cartea

    (University of Oxford
    Oxford-Man Institute of Quantitative Finance)

  • Leandro Sánchez-Betancourt

    (King’s College London)

Abstract

We show how traders use marketable limit orders (MLOs) to liquidate a position over a trading window when there is latency in the marketplace. MLOs are liquidity-taking orders that specify a price limit and are for immediate execution only; however, if the price limit of the MLO precludes it from being filled, the exchange cancels the order. We frame our model as an impulse control problem with stochastic latency where the trader controls the times and the price limits of the MLOs sent to the exchange. We show that impatient liquidity takers submit MLOs that may walk the book (capped by the limit price) to increase the probability of filling the trades. On the other hand, patient liquidity takers use speculative MLOs that are only filled if there has been an advantageous move in prices over the latency period. Patient traders who are fast do not use their speed to hit the quotes they observe, or to finish the execution programme early; they use speed to complete the execution programme with as many speculative MLOs as possible. We use foreign exchange data to implement the random-latency-optimal strategy and to compare it with four benchmarks. For patient traders, the random-latency-optimal strategy outperforms the benchmarks by an amount that is greater than the transaction costs paid by liquidity takers in foreign exchange markets. Around news announcements, the value of the outperformance is between two and ten times the value of the transaction costs. The superiority of the strategy is due to both the speculative MLOs that are filled and the price protection of the MLOs.

Suggested Citation

  • Álvaro Cartea & Leandro Sánchez-Betancourt, 2023. "Optimal execution with stochastic delay," Finance and Stochastics, Springer, vol. 27(1), pages 1-47, January.
  • Handle: RePEc:spr:finsto:v:27:y:2023:i:1:d:10.1007_s00780-022-00491-w
    DOI: 10.1007/s00780-022-00491-w
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    References listed on IDEAS

    as
    1. �lvaro Cartea & Sebastian Jaimungal, 2015. "Optimal execution with limit and market orders," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1279-1291, August.
    2. Olivier Gu'eant & Charles-Albert Lehalle & Joaquin Fernandez Tapia, 2011. "Optimal Portfolio Liquidation with Limit Orders," Papers 1106.3279, arXiv.org, revised Jul 2012.
    3. Fabien Guilbaud & Huyên Pham, 2013. "Optimal high-frequency trading with limit and market orders," Quantitative Finance, Taylor & Francis Journals, vol. 13(1), pages 79-94, January.
    4. 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.
    5. 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.
    6. Weston Barger & Matthew Lorig, 2019. "Optimal Liquidation Under Stochastic Price Impact," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(02), pages 1-28, March.
    7. Xuefeng Gao & Yunhan Wang, 2020. "Optimal market making in the presence of latency," Quantitative Finance, Taylor & Francis Journals, vol. 20(9), pages 1495-1512, September.
    8. Xuefeng Gao & Yunhan Wang, 2018. "Optimal Market Making in the Presence of Latency," Papers 1806.05849, arXiv.org, revised Mar 2020.
    9. 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.
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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Yan Dolinsky, 2023. "Delayed Semi-static Hedging in the Continuous Time Bachelier Model," Papers 2311.17270, arXiv.org, revised Dec 2023.
    2. 'Alvaro Cartea & Gerardo Duran-Martin & Leandro S'anchez-Betancourt, 2023. "Detecting Toxic Flow," Papers 2312.05827, arXiv.org.
    3. Yan Dolinsky & Or Zuk, 2023. "Explicit Computations for Delayed Semistatic Hedging," Papers 2308.10550, arXiv.org.

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    More about this item

    Keywords

    Algorithmic trading; High-frequency trading; Stochastic delay; Latency;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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