Decision making in the presence of randomness is an important problem, particularly in finance. Often, decision makers base their choices on the values of `risk measures' or `nonlinear expectations'; it is important to understand how these decisions evolve through time. In this paper, we consider how these decisions are affected by the use of a moving horizon, and the possible inconsistencies that this creates. By giving a formal treatment of time consistency without Bellman's equations, we show that there is a new sense in which these decisions can be seen as consistent.
We consider portfolio selection when decisions based on a dynamic risk measure are affected by the use of a moving horizon, and the possible inconsistencies that this creates. By giving a formal treatment of time consistency which is independent of Bellman's equations, we show that there is a new sense in which these decisions can be seen as consistent.
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Decision making in the presence of randomness is an important problem, particularly in finance. Often, decision makers base their choices on the values of `risk measures' or `nonlinear expectations'; it is important to understand how these decisions evolve through time. In this paper, we consider how these decisions
We consider portfolio selection when decisions based on a dynamic risk measure
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which is independent of