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Title: On dynamic programming principle for stochastic control under expectation constraints
Authors: Chow, YL
Yu, X 
Zhou, C
Issue Date: Jun-2020
Source: Journal of optimization theory and applications, June 2020, v. 185, no. 3, p. 803-818
Abstract: This paper studies the dynamic programming principle using the measurable selection method for stochastic control of continuous processes. The novelty of this work is to incorporate intermediate expectation constraints on the canonical space at each time t. Motivated by some financial applications, we show that several types of dynamic trading constraints can be reformulated into expectation constraints on paths of controlled state processes. Our results can therefore be employed to recover the dynamic programming principle for these optimal investment problems under dynamic constraints, possibly path-dependent, in a non-Markovian framework.
Keywords: Dynamic programming principle
Dynamic trading constraints
Intermediate expectation constraints
Measurable selection
Publisher: Springer
Journal: Journal of optimization theory and applications 
ISSN: 0022-3239
EISSN: 1573-2878
DOI: 10.1007/s10957-020-01673-2
Rights: © Springer Science+Business Media, LLC, part of Springer Nature 2020
This is a post-peer-review, pre-copyedit version of an article published in Journal of Optimization Theory and Applications. The final authenticated version is available online at:
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