Dynamic benchmark targeting
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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.
Schlag , K H & Zapechelnyuk , A 2017 , ' Dynamic benchmark targeting ' , Journal of Economic Theory , vol. 169 , pp. 145-169 . https://doi.org/10.1016/j.jet.2017.02.004
Journal of Economic Theory
© 2017 Elsevier Inc. All rights reserved. This work has been made available online in accordance with the publisher’s policies. This is the author created accepted version manuscript following peer review and as such may differ slightly from the final published version. The final published version of this work is available at: https://doi.org/10.1016/j.jet.2017.02.004
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