Random G-expectations

Abstract

We construct a time-consistent sublinear expectation in the setting of volatility uncertainty. This mapping extends Peng's G-expectation by allowing the range of the volatility uncertainty to be stochastic. Our construction is purely probabilistic and based on an optimal control formulation with path-dependent control sets.

Published in at http://dx.doi.org/10.1214/12-AAP885 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)

References in corpus (2)

• A theoretical framework for the pricing of contingent claims in the presence of model uncertainty
• Nonlinear Expectations and Stochastic Calculus under Uncertainty

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