The Reinforcement Learning Kelly Strategy
Abstract
The full Kelly portfolio strategy's deficiency in the face of estimation errors in practice can be mitigated by fractional or shrinkage Kelly strategies. This paper provides an alternative, the RL Kelly strategy, based on a reinforcement learning (RL) framework. RL algorithms are developed for the practical implementation of the RL Kelly strategy. Extensive simulation studies are conducted, and the results confirm the superior performance of the RL Kelly strategies.
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Cite this version of the work
Ruihong Jiang, David Saunders, Chengguo Weng
(2022).
The Reinforcement Learning Kelly Strategy. UWSpace.
http://hdl.handle.net/10012/20094
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