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Accelerated Share Repurchase: pricing and execution strategy

Author

Listed:
  • Olivier Guéant

    (LJLL - Laboratoire Jacques-Louis Lions - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique)

  • Jiang Pu
  • Royer Guillaume

    (CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique - X - École polytechnique - CNRS - Centre National de la Recherche Scientifique)

Abstract

In this article, we consider a specific optimal execution problem associated to accelerated share repurchase contracts. When firms want to repurchase their own shares, they often enter such a contract with a bank. The bank buys the shares for the firm and is paid the average market price over the execution period, the length of the period being decided upon by the bank during the buying process. Mathematically, the problem is new and related to both option pricing (Asian and Bermudan options) and optimal execution. We provide a model, along with associated numerical methods, to determine the optimal stopping time and the optimal buying strategy of the bank.

Suggested Citation

  • Olivier Guéant & Jiang Pu & Royer Guillaume, 2015. "Accelerated Share Repurchase: pricing and execution strategy," Post-Print hal-01393126, HAL.
    • Handle: RePEc:hal:journl:hal-01393126
    DOI: 10.1142/S0219024915500193
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    Cited by:

    1. Olivier Gu'eant & Iuliia Manziuk & Jiang Pu, 2019. "Accelerated Share Repurchase and other buyback programs: what neural networks can bring," Papers 1907.09753, arXiv.org, revised Nov 2019.
    2. Olivier Guéant & Iuliia Manziuk & Jiang Pu, 2020. "Accelerated Share Repurchase and other buyback programs: what neural networks can bring," Working Papers hal-02987889, HAL.
    3. Olivier Guéant & Jiang Pu, 2015. "Option pricing and hedging with execution costs and market impact," Post-Print hal-01393124, HAL.
    4. Olivier Guéant & Iuliia Manziuk & Jiang Pu, 2020. "Accelerated Share Repurchase and other buyback programs: what neural networks can bring," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-02987889, HAL.
    5. Mohamed Hamdouche & Pierre Henry-Labordere & Huyen Pham, 2023. "Policy gradient learning methods for stochastic control with exit time and applications to share repurchase pricing," Papers 2302.07320, arXiv.org.
    6. Alexis Bismuth & Olivier Gu'eant & Jiang Pu, 2016. "Portfolio choice, portfolio liquidation, and portfolio transition under drift uncertainty," Papers 1611.07843, arXiv.org, revised Mar 2019.
    7. David Evangelista & Yuri Saporito & Yuri Thamsten, 2022. "Price formation in financial markets: a game-theoretic perspective," Papers 2202.11416, arXiv.org.
    8. Olivier Guéant, 2016. "The Financial Mathematics of Market Liquidity: From Optimal Execution to Market Making," Post-Print hal-01393136, HAL.

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