Reinforcement Learning in Online Stock Trading Systems
نویسندگان
چکیده
Applications of Machine Learning (ML) to stock market analysis include Portfolio Optimization, Investment Strategy Determination, and Market Risk Analysis. This paper focuses on the problem of Investment Strategy Determination through the use of reinforcement learning techniques. Four techniques, two based on Recurrent Reinforcement Learning (RLL) and two based on Q-learning, were utilized. Q-learning produced results that consistently beat Buy and Hold strategies on several technology stocks, whereas the RRL methods were often inconsistent and require further investigation.
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