Abstract
In this paper, we continue to study random convex analysis. First, we introduce the notion of an --pre--barreled module. Then, we develop the theory of random duality under the framework of a random locally convex module endowed with the locally --convex topology in order to establish a characterization for a random locally convex module to be --pre--barreled, in particular we prove that the model space employed in the module approach to conditional risk measures is --pre--barreled, which forms the most difficult part of this paper. Finally, we prove the continuity and subdifferentiability theorems for a proper lower semicontinuous --convex function on an --pre--barreled random locally convex module. So the principal results of this paper may be well suited to the study of continuity and subdifferentiability for --convex conditional risk measures.
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