Luc Feron

  School of Business and Economics | Bachelor Econometrics and Operations Research

"An optimal stopping problem with partial observations"

Luc's elevator pitch
This paper studies a discrete-time optimal stopping problem over an infinite horizon. The problem is built on top of a simple Markov chain which has parametrized transition probabilities. The decision-maker makes partial observations and his actions have non-deterministic results. In this paper I present and prove 14 theorems which result in four main findings: the optimal strategy, value of the game, performance of memoryless strategies and the value of information. This paper’s contributions are mainly theoretical; however, it also paves the way toward solving the problem on more complex Markov chains which may have practical applications in security pricing.