publication . Preprint . 2016

Online Learning of Commission Avoidant Portfolio Ensembles

Uziel, Guy; El-Yaniv, Ran;
Open Access English
  • Published: 03 May 2016
Abstract
We present a novel online ensemble learning strategy for portfolio selection. The new strategy controls and exploits any set of commission-oblivious portfolio selection algorithms. The strategy handles transaction costs using a novel commission avoidance mechanism. We prove a logarithmic regret bound for our strategy with respect to optimal mixtures of the base algorithms. Numerical examples validate the viability of our method and show significant improvement over the state-of-the-art.
Subjects
free text keywords: Computer Science - Artificial Intelligence, Computer Science - Learning
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