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Convex duality in stochastic programming and mathematical finance

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  • Teemu Pennanen

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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  • Teemu Pennanen, 2010. "Convex duality in stochastic programming and mathematical finance," Papers 1006.4083, arXiv.org.
    • Handle: RePEc:arx:papers:1006.4083
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    File URL: http://arxiv.org/pdf/1006.4083
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