Dynamic programming in convex stochastic optimization

Teemu Pennanen; Ari-Pekka Perkkiö

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arXiv · 2203.17107

Dynamic programming in convex stochastic optimization

Teemu Pennanen·Ari-Pekka Perkkiö

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Abstract

This paper studies the dynamic programming principle for general convex stochastic optimization problems introduced by Rockafellar and Wets in [30]. We extend the applicability of the theory by relaxing compactness and boundedness assumptions. In the context of financial mathematics, the relaxed assumption are satisfied under the well-known no-arbitrage condition and the reasonable asymptotic elasticity condition of the utility function. Besides financial mathematics, we obtain several new results in linear and nonlinear stochastic programming and stochastic optimal control.

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Teemu Pennanen, Ari-Pekka Perkkiö. 2022-03-31. Dynamic programming in convex stochastic optimization. https://arxiv.org/abs/2203.17107

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