Stocks Trading Using RL
Rather than learning new methods to solve toy reinforcement learning (RL) problems in this chapter, we will try to utilize our deep Q-network (DQN) knowledge to deal with the much more practical problem of financial trading. I can’t promise that the code will make you super rich on the stock market or Forex, because my goal is much less ambitious: to demonstrate how to go beyond the Atari games and apply RL to a different practical domain.
In this chapter, we will:
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Implement our own OpenAI Gym environment to simulate the stock market
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Apply the DQN method that you learned in Chapter 6 and Chapter 8 to train an agent to trade stocks to maximize profit
