Chapter 5: Reinforcement Learning in the Real World â Building Stock/Share Trading Agents
Software-based deep reinforcement learning (deep RL) agents have tremendous potential when it comes to executing trading strategies tirelessly and flawlessly without limitations based on memory capacity, speed, efficiency, and emotional disturbances that a human trader is prone to facing. Profitable trading in the stock market involves carefully executing buy/sell trades with stock symbols/tickers while taking into account several market factors such as trading conditions and macro and micro market conditions, in addition to social, political, and company-specific changes. Deep RL agents have a lot of potential when it comes to solving challenging problems ...
Get TensorFlow 2 Reinforcement Learning Cookbook now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
