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Execution uncertainty of dark pools and portfolio balance

Author

Listed:
  • Zhu, Jianchang
  • Sun, Xuchu
  • Li, Tangrong

Abstract

Execution uncertainty can disrupt portfolio balance; for example, dark pool orders for some assets in the portfolio are executed while others are not. To alleviate this problem, we consider a conditional dark pool order in a discrete model of the optimal portfolio execution strategy. Conditional dark pool orders allow an investor to submit a portfolio that will be executed only if the condition that all assets in the portfolio are executable is met. Additionally, dark pools are trading systems established for large transactions. We provide new insight into the puzzle of small average dark pool order size through portfolio balance.

Suggested Citation

  • Zhu, Jianchang & Sun, Xuchu & Li, Tangrong, 2024. "Execution uncertainty of dark pools and portfolio balance," Finance Research Letters, Elsevier, vol. 63(C).
  • Handle: RePEc:eee:finlet:v:63:y:2024:i:c:s1544612324003064
    DOI: 10.1016/j.frl.2024.105276
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    References listed on IDEAS

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    1. Samuel Antill & Darrell Duffie, 2021. "Augmenting Markets with Mechanisms [Optimal Execution of Portfolio Transactions]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(4), pages 1665-1719.
    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. Linlin Ye, 2016. "Understanding the Impacts of Dark Pools on Price Discovery," Papers 1612.08486, arXiv.org.
    4. Nicole Bäuerle & Ulrich Rieder, 2009. "MDP algorithms for portfolio optimization problems in pure jump markets," Finance and Stochastics, Springer, vol. 13(4), pages 591-611, September.
    5. Obizhaeva, Anna A. & Wang, Jiang, 2013. "Optimal trading strategy and supply/demand dynamics," Journal of Financial Markets, Elsevier, vol. 16(1), pages 1-32.
    6. Chen, Yuanyuan & Gao, Xuefeng & Li, Duan, 2018. "Optimal order execution using hidden orders," Journal of Economic Dynamics and Control, Elsevier, vol. 94(C), pages 89-116.
    7. Gerry Tsoukalas & Jiang Wang & Kay Giesecke, 2019. "Dynamic Portfolio Execution," Management Science, INFORMS, vol. 67(5), pages 2015-2040, May.
    8. Peter Kratz & Torsten Schöneborn, 2018. "Optimal Liquidation And Adverse Selection In Dark Pools," Mathematical Finance, Wiley Blackwell, vol. 28(1), pages 177-210, January.
    9. Peter Kratz & Torsten Schöneborn, 2015. "Portfolio Liquidation In Dark Pools In Continuous Time," Mathematical Finance, Wiley Blackwell, vol. 25(3), pages 496-544, July.
    10. Bertsimas, Dimitris & Lo, Andrew W., 1998. "Optimal control of execution costs," Journal of Financial Markets, Elsevier, vol. 1(1), pages 1-50, April.
    11. Peter Kratz & Torsten Sch�neborn, 2014. "Optimal liquidation in dark pools," Quantitative Finance, Taylor & Francis Journals, vol. 14(9), pages 1519-1539, September.
    12. Florian Klöck & Alexander Schied & Yuemeng Sun, 2017. "Price manipulation in a market impact model with dark pool," Applied Mathematical Finance, Taylor & Francis Journals, vol. 24(5), pages 417-450, September.
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    More about this item

    Keywords

    Optimal execution; Dark pool; Portfolio management;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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