De Angelis, T and Peskir, G (Cover date: June 2020) Global C¹ regularity of the value function in optimal stopping problems. Annals of Applied Probability, 30 (3). pp. 1007-1031. ISSN 1050-5164
Abstract
We show that if either the process is strong Feller and the boundary point is probabilistically regular for the stopping set, or the process is strong Markov and the boundary point is probabilistically regular for the interior of the stopping set, then the boundary point is Green regular for the stopping set. Combining this implication with the existence of a continuously differentiable flow of the process we show that the value function is continuously differentiable at the optimal stopping boundary whenever the gain function is so. The derived fact holds both in the parabolic and elliptic case of the boundary value problem under the sole hypothesis of probabilistic regularity of the optimal stopping boundary, thus improving upon known analytic results in the PDE literature, and establishing the fact for the first time in the case of integro-differential equations. The method of proof is purely probabilistic and conceptually simple. Examples of application include the first known probabilistic proof of the fact that the time derivative of the value function in the American put problem is continuous across the optimal stopping boundary.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © Institute of Mathematical Statistics, 2020. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Optimal stopping problem; strong Markov/Feller process; free boundary problem; regularity of the value function; regularity of a boundary point; regularity of a stochastic flow; smooth fit |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/R021201/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Sep 2019 14:28 |
Last Modified: | 05 Jun 2021 19:07 |
Status: | Published |
Publisher: | Institute of Mathematical Statistics |
Identification Number: | 10.1214/19-AAP1517 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:150282 |