A representation for filtration-consistent nonlinear expectations and its application
S Zheng, S Li - Communications in Statistics-Simulation and …, 2022 - Taylor & Francis
S Zheng, S Li
Communications in Statistics-Simulation and Computation, 2022•Taylor & FrancisIn this paper, we consider filtration-consistent nonlinear expectations which satisfy a general
domination condition. We show that filtration-consistent nonlinear expectations can be
represented by g-expectations defined by the solutions of backward stochastic differential
equations, whose generators are independent of y and uniformly continuous in z. As an
application, we establish a concentration inequality for time-consistent risk measures.
domination condition. We show that filtration-consistent nonlinear expectations can be
represented by g-expectations defined by the solutions of backward stochastic differential
equations, whose generators are independent of y and uniformly continuous in z. As an
application, we establish a concentration inequality for time-consistent risk measures.
Abstract
In this paper, we consider filtration-consistent nonlinear expectations which satisfy a general domination condition. We show that filtration-consistent nonlinear expectations can be represented by g-expectations defined by the solutions of backward stochastic differential equations, whose generators are independent of y and uniformly continuous in z. As an application, we establish a concentration inequality for time-consistent risk measures.
Taylor & Francis OnlineShowing the best result for this search. See all results