IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1908.03281.html
   My bibliography  Save this paper

Latency and Liquidity Risk

Author

Listed:
  • 'Alvaro Cartea
  • Sebastian Jaimungal
  • Leandro S'anchez-Betancourt

Abstract

Latency (i.e., time delay) in electronic markets affects the efficacy of liquidity taking strategies. During the time liquidity takers process information and send marketable limit orders (MLOs) to the exchange, the limit order book (LOB) might undergo updates, so there is no guarantee that MLOs are filled. We develop a latency-optimal trading strategy that improves the marksmanship of liquidity takers. The interaction between the LOB and MLOs is modelled as a marked point process. Each MLO specifies a price limit so the order can receive worse prices and quantities than those the liquidity taker targets if the updates in the LOB are against the interest of the trader. In our model, the liquidity taker balances the tradeoff between missing trades and the costs of walking the book. We employ techniques of variational analysis to obtain the optimal price limit of each MLO the agent sends. The price limit of a MLO is characterized as the solution to a new class of forward-backward stochastic differential equations (FBSDEs) driven by random measures. We prove the existence and uniqueness of the solution to the FBSDE and numerically solve it to illustrate the performance of the latency-optimal strategies.

Suggested Citation

  • 'Alvaro Cartea & Sebastian Jaimungal & Leandro S'anchez-Betancourt, 2019. "Latency and Liquidity Risk," Papers 1908.03281, arXiv.org.
  • Handle: RePEc:arx:papers:1908.03281
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1908.03281
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Charles-Albert Lehalle & Sophie Laruelle (ed.), 2013. "Market Microstructure in Practice," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8967, December.
    2. Ciamac C. Moallemi & Mehmet Sağlam, 2013. "OR Forum---The Cost of Latency in High-Frequency Trading," Operations Research, INFORMS, vol. 61(5), pages 1070-1086, October.
    3. Edward Hoyle, 2010. "Information-based models for finance and insurance," Papers 1010.0829, arXiv.org.
    4. 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.
    5. Alvaro Cartea & Sebastian Jaimungal & Jamie Walton, 2018. "Foreign Exchange Markets with Last Look," Papers 1806.04460, arXiv.org.
    6. Duffie, Darrel & Lions, Pierre-Louis, 1992. "PDE solutions of stochastic differential utility," Journal of Mathematical Economics, Elsevier, vol. 21(6), pages 577-606.
    7. Philippe Casgrain & Sebastian Jaimungal, 2018. "Mean-Field Games with Differing Beliefs for Algorithmic Trading," Papers 1810.06101, arXiv.org, revised Dec 2019.
    8. Duffie, Darrell & Epstein, Larry G, 1992. "Stochastic Differential Utility," Econometrica, Econometric Society, vol. 60(2), pages 353-394, March.
    9. Sasha Stoikov & Rolf Waeber, 2016. "Reducing transaction costs with low-latency trading algorithms," Quantitative Finance, Taylor & Francis Journals, vol. 16(9), pages 1445-1451, September.
    10. Duffie, Darrell & Epstein, Larry G, 1992. "Asset Pricing with Stochastic Differential Utility," The Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 411-436.
    Full references (including those not matched with items on IDEAS)

    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. Fahrenwaldt, Matthias Albrecht & Jensen, Ninna Reitzel & Steffensen, Mogens, 2020. "Nonrecursive separation of risk and time preferences," Journal of Mathematical Economics, Elsevier, vol. 90(C), pages 95-108.
    2. Dirk Becherer & Wilfried Kuissi-Kamdem & Olivier Menoukeu-Pamen, 2023. "Optimal consumption with labor income and borrowing constraints for recursive preferences," Working Papers hal-04017143, HAL.
    3. Dominika Czyz & Karolina Safarzynska, 2023. "Catastrophic Damages and the Optimal Carbon Tax Under Loss Aversion," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 85(2), pages 303-340, June.
    4. Aït-Sahalia, Yacine & Matthys, Felix, 2019. "Robust consumption and portfolio policies when asset prices can jump," Journal of Economic Theory, Elsevier, vol. 179(C), pages 1-56.
    5. Huang, Jianhui & Wang, Guangchen & Wu, Zhen, 2010. "Optimal premium policy of an insurance firm: Full and partial information," Insurance: Mathematics and Economics, Elsevier, vol. 47(2), pages 208-215, October.
    6. Chabakauri, Georgy, 2010. "Asset pricing with heterogeneous investors and portfolio constraints," LSE Research Online Documents on Economics 43142, London School of Economics and Political Science, LSE Library.
    7. Riedel, Frank, 2002. "Generic Determinancy of Equilibria with Local Substitution," Department of Economics, Working Paper Series qt43j2n5f5, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    8. Li, Hanwu & Riedel, Frank & Yang, Shuzhen, 2024. "Optimal consumption for recursive preferences with local substitution — the case of certainty," Journal of Mathematical Economics, Elsevier, vol. 110(C).
    9. Marc Arnold & Dirk Hackbarth & Tatjana Xenia Puhan, 2018. "Financing Asset Sales and Business Cycles [Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries]," Review of Finance, European Finance Association, vol. 22(1), pages 243-277.
    10. Miyoshi, Yoshiyuki & Toda, Alexis Akira, 2017. "Growth effects of annuities and government transfers in perpetual youth models," Journal of Mathematical Economics, Elsevier, vol. 72(C), pages 1-6.
    11. Ruan, Xinfeng, 2021. "Ambiguity, long-run risks, and asset prices in continuous time," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 115-126.
    12. Andrew Ang & Dimitris Papanikolaou & Mark M. Westerfield, 2014. "Portfolio Choice with Illiquid Assets," Management Science, INFORMS, vol. 60(11), pages 2737-2761, November.
    13. Frederick Ploeg, 2021. "Carbon pricing under uncertainty," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 28(5), pages 1122-1142, October.
    14. Shi, Huihong & Mu, Congming & Yang, Jinqiang & Huang, Wenli, 2021. "A Sino-US comparative analysis of the hi-tech entrepreneurial model," Economic Modelling, Elsevier, vol. 94(C), pages 953-966.
    15. Camelia Minoiu & Andrés Schneider & Min Wei, 2023. "Why Does the Yield Curve Predict GDP Growth? The Role of Banks," FRB Atlanta Working Paper 2023-14, Federal Reserve Bank of Atlanta.
    16. Zixin Feng & Dejian Tian, 2021. "Optimal consumption and portfolio selection with Epstein-Zin utility under general constraints," Papers 2111.09032, arXiv.org, revised May 2023.
    17. Emmanuelle Augeraud-Véron & Giorgio Fabbri & Katheline Schubert, 2019. "The Value of Biodiversity as an Insurance Device," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(4), pages 1068-1081.
    18. Joshua Lanier & Bin Miao & John K.-H. Quah & Songfa Zhong, 2024. "Intertemporal Consumption with Risk: A Revealed Preference Analysis," The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1319-1333, September.
    19. Kraft, Holger & Weiss, Farina, 2019. "Consumption-portfolio choice with preferences for cash," Journal of Economic Dynamics and Control, Elsevier, vol. 98(C), pages 40-59.
    20. Knut K. Aase, 2016. "Recursive utility using the stochastic maximum principle," Quantitative Economics, Econometric Society, vol. 7(3), pages 859-887, November.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:1908.03281. 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.