Accelerated share repurchase and other buyback programs: what neural networks can bring
Iuliia Manziuk and
Additional contact information
Olivier Guéant: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique
Iuliia Manziuk: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique
Jiang Pu: Institut europlace de finance
Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL
When firms want to buy back their own shares, they have a choice between several alternatives. If they often carry out open market repurchase, they also increasingly rely on banks through complex buyback contracts involving option components, e.g. accelerated share repurchase contracts, VWAP-minus profit-sharing contracts, etc. The entanglement between the execution problem and the option hedging problem makes the management of these contracts a difficult task that should not boil down to simple Greek-based risk hedging, contrary to what happens with classical books of options. In this paper, we propose a machine learning method to optimally manage several types of buyback contract. In particular, we recover strategies similar to those obtained in the literature with partial differential equation and recombinant tree methods and show that our new method, which does not suffer from the curse of dimensionality, enables to address types of contract that could not be addressed with grid or tree methods.
Keywords: ASR contracts; Optimal stopping; Stochastic optimal control; deep learning; Recurrent neural networks; Reinforcement learning (search for similar items in EconPapers)
Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-03252518
References: Add references at CitEc
Citations: Track citations by RSS feed
Published in Quantitative Finance, Taylor & Francis (Routledge), 2020, 20 (8), pp.1389-1404. ⟨10.1080/14697688.2020.1729397⟩
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:hal:cesptp:hal-03252518
Access Statistics for this paper
More papers in Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL
Bibliographic data for series maintained by CCSD ().