TensorFlow 2 Reinforcement Learning Cookbook by Praveen Palanisamy

Author:Praveen Palanisamy
Language: eng
Format: epub, mobi
Publisher: Packt Publishing Pvt Ltd
Published: 2021-01-15T00:00:00+00:00

Now, it's time for you to get one of the agents you built as part of the previous chapter to train and test this real data-backed stock market trading environment. For now, let's test the environment with a simple, random agent:if __name__ == "__main__":

env = StockTradingVisualContinuousEnv()

obs = env.reset()

for _ in range(600):

action = env.action_space.sample()

next_obs, reward, done, _ = env.step(action)

env.render()

How it works…

To simulate a stock market, a real stock market data stream must be used. An offline file-based stream is utilized as an alternative to a web-based API, which would require internet connectivity and potentially a user account to fetch market data. The file stream contains the market data in a standard format: Date, Open, High, Low, Close, Adj-Close, and Volume.

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