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Random $G$-expectations
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.