American Options in incomplete Markets: Upper and lower Snell Envelopes and robust partial Hedging

This thesis studies American options in an incomplete financial market and in continuous time. It is composed of two parts. In the first part we study a stochastic optimization problem in which a robust convex loss functional is minimized in a space of stochastic integrals. This problem arises when the seller of an American option aims to control the shortfall risk by using a partial hedge. We quantify the shortfall risk through a robust loss functional motivated by an extension of classical expected utility theory due to Gilboa and Schmeidler. In a general semimartingale model we prove the existence of an optimal strategy. Under additional compactness assumptions we show how the robust problem can be reduced to a non-robust optimization problem with respect to a worst-case probability measure. In the second part, we study the notions of the upper and the lower Snell envelope associated to an American option. We construct the envelopes for stable families of equivalent probability measures, the family of local martingale measures being an important special case. We then formulate two robust optimal stopping problems. The stopping problem related to the upper Snell envelope is motivated by the problem of monitoring the risk associated to the buyer’s choice of an exercise time, where the risk is specified by a coherent risk measure. The stopping problem related to the lower Snell envelope is motivated by a robust extension of classical expected utility theory due to Gilboa and Schmeidler. Using martingale methods we show how to construct optimal solutions in continuous time and for a finite horizon.