On-line portfolio selection is an important and challenging question in computational finance and attracts increasing attention in the machine learning and data mining fields. Previously an on-line portfolio selection strategy called On-Line Moving Average Reversion (OLMAR) (Li et al., 2012)...

Portfolio selection has attracted increasing attention in machine learning and AI communities recently. Portfolio selection using on-line learning method has been extensively investigated previously. Literature about portfolio selection using recurrent reinforcement learning (RRL) is relatively...

This paper studies the mean-variance portfolio selection under the assumption that the market state is modulated by a hidden Markov chain which is unobservable to investors. We employ a game-theoretic formulation to address the time-inconsistency arising in mean-variance analysis for portfolio...