Dynamic benchmark targeting

Schlag, K. H. and Zapechelnyuk, A. (2017) Dynamic benchmark targeting. Journal of Economic Theory, 169, pp. 145-169. (doi: 10.1016/j.jet.2017.02.004)

137653.pdf - Accepted Version



We study decision making in complex discrete-time dynamic environments where Bayesian optimization is intractable. A decision maker is equipped with a finite set of benchmark strategies. She aims to perform similarly to or better than each of these benchmarks. Furthermore, she cannot commit to any decision rule, hence she must satisfy this goal at all times and after every history. We find such a rule for a sufficiently patient decision maker and show that it necessitates not to rely too much on observations from distant past. In this sense we find that it can be optimal to forget.

Item Type:Articles
Additional Information:Karl Schlag gratefully acknowledges financial support from the Department of Economics and Business of the Universitat Pompeu Fabra, Grant AL 12207, and from the Spanish Ministerio de Educacion y Ciencia, Grant MEC-SEJ2006-09993.
Glasgow Author(s) Enlighten ID:Zapechelnyuk, Professor Andriy
Authors: Schlag, K. H., and Zapechelnyuk, A.
College/School:College of Social Sciences > Adam Smith Business School
Journal Name:Journal of Economic Theory
ISSN (Online):1095-7235
Published Online:21 February 2017
Copyright Holders:Copyright © 2017 Elsevier
First Published:First published in Journal of Economic Theory 169: 145-169
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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