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Stochastics
An International Journal of Probability and Stochastic Processes
Volume 89, 2017 - Issue 6-7: Proceedings of the Hammamet Conference, 19-23 October 2015
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Articles

Asymptotic optimal tracking: feedback strategies

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Pages 943-966 | Received 27 Apr 2016, Accepted 18 Jan 2017, Published online: 16 Feb 2017
 

Abstract

This is a companion paper to [Cai, Rosenbaum and Tankov, Asymptotic lower bounds for optimal tracking: a linear programming approach, Arxiv: 1510.04295]. We consider a class of strategies of feedback form for the problem of tracking and study their performance under the asymptotic framework of the above reference. The strategies depend only on the current state of the system and keep the deviation from the target inside a time-varying domain. Although the dynamics of the target is non-Markovian, it turns out that such strategies are asympototically optimal for a large list of examples.

Notes

No potential conflict of interest was reported by the authors.

1 We thank Emmanuel Gobet for pointing out this reference.

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