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Convex duality in stochastic programming and mathematical finance

2010/06/21 by Pennanen, Teemu
#46A20 #52A07 #52A41 #90C15 #91B25 #Computational Finance (q-fin.CP) #FOS: Economics and business #FOS: Mathematics #Optimization and Control (math.OC)

paper · doi:10.48550/arxiv.1006.4083

Abstract

This paper proposes a general duality framework for the problem of minimizing a convex integral functional over a space of stochastic processes adapted to a given filtration. The framework unifies many well-known duality frameworks from operations research and mathematical finance. The unification allows the extension of some useful techniques from these two fields to a much wider class of problems. In particular, combining certain finite-dimensional techniques from convex analysis with measure theoretic techniques from mathematical finance, we are able to close the duality gap in some situations where traditional topological arguments fail.

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