Convex duality in stochastic programming and mathematical finance

Details Convex duality in stochastic programming and mathematical finance Convex duality in stochastic programming and mathematical finance

2010-06-21

arxiv.org/abs/1006.4083v1

Economy

Quantitative Finance

Computational Finance

Scientific paper

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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