We refine the discretization of G-expectation by Y. Dolinsky, M.Nutz, and M. Soner (Stochastic Processes and their Applications, 122 (2012), 664-675), in order to obtain a discretization of sublinear expectation where the martingale laws are defined on a finite lattice rather than the whole set...

We refine the discretization of G-expectation by Y. Dolinsky, M. Nutz, and M. Soner (Stochastic Processes and their Applications, 122 (2012), 664-675), in order to obtain a discretization of sublinear expectation where the martingale laws are defined on a finite lattice rather than the whole set...

We refine the discretization of G-expectation by Y. Dolinsky, M.Nutz, and M. Soner (Stochastic Processes and their Applications, 122 (2012), 664-675), in order to obtain a discretization of sublinear expectation where the martingale laws are defined on a finite lattice rather than the whole set...

Abstract We apply a suitable modification of the functional delta method to statistical functionals that arise from law-invariant coherent risk measures. To this end we establish differentiability of the statistical functional in a relaxed Hadamard sense, namely with respect to a suitably chosen...

We introduce a notion of volatility uncertainty in discrete time and define the corresponding analogue of Peng’s G-expectation. In the continuous-time limit, the resulting sublinear expectation converges weakly to the G-expectation. This can be seen as a Donsker-type result for the G-Brownian...

We introduce a notion of volatility uncertainty in discrete time and define the corresponding analogue of Peng’s G-expectation. In the continuous-time limit, the resulting sublinear expectation converges weakly to the G-expectation. This can be seen as a Donsker-type result for the G-Brownian...