3 by vivekys | 0 comments on Hacker News.
Recently I published my experiments on using deep reinforcement learning for portfolio allocation. Few open problem I struggled and still don't have an answer are 1. For the problem specifically like stock market, how one can decide when to stop the training of RL agent ? i.e. What is the metric that can determine agent has been trained ? 2. How can one determine the deployed agent is now deviating from the trained data distribution so that it can be retrained ? I appreciate any comments/suggestions or any mistake I might have made. Here are the links https://ift.tt/2KyprHa https://ift.tt/2O0sgTB https://ift.tt/35jeelt https://ift.tt/37huzZY https://ift.tt/2CXwq8a
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