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Sensitivity of multiperiod optimization problems in adapted Wasserstein distance (2208.05656v2)

Published 11 Aug 2022 in math.OC, math.PR, and q-fin.MF

Abstract: We analyze the effect of small changes in the underlying probabilistic model on the value of multi-period stochastic optimization problems and optimal stopping problems. We work in finite discrete time and measure these changes with the adapted Wasserstein distance. We prove explicit first-order approximations for both problems. Expected utility maximization is discussed as a special case.

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