Discretionary stopping of stochastic differential equations with generalised drift

Mihail Zervos, Neofytos Rodosthenous, Pui Chan Lon, Thomas Bernhardt

Research output: Contribution to journalArticlepeer-review


We consider the problem of optimally stopping a general one-dimensional stochastic differential equation (SDE) with generalised drift over an infinite time horizon. First, we derive a complete characterisation of the solution to this problem in terms of variational inequalities. In particular, we prove that the problem’s value function is the difference of two convex functions and satisfies an appropriate variational inequality in the sense of distributions. We also establish a verification theorem that is the strongest one possible because it involves only the optimal stopping problem’s data. Next, we derive the complete explicit solution to the problem that arises when the state process is a skew geometric Brownian motion and the reward function is the one of a financial call option. In this case, we show that the optimal stopping strategy can take several qualitatively different forms, depending on parameter values. Furthermore, the explicit solution to this special case shows that the so-called “principle of smooth fit” does not hold in general for optimal stopping problems involving solutions to SDEs with generalised drift.
Original languageEnglish
Pages (from-to)1-39
Number of pages39
JournalElectronic Journal of Probability
Publication statusPublished - 5 Dec 2019


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