Strategic Asset Allocation and Market Timing: A Reinforcement Learning Approach

We apply the recurrent reinforcement learning method of Moody et al. (1998) in the context of the strategic asset allocation computed for sample data from the United States, the United Kingdom, and Germany. It is found that the optimal asset allocation deviates substantially from the fixed-mix rule. The investor actively times the market and he is able to outperform it consistently with respect to risk adjusted returns over the almost two decades we analyze.