Step-by-step guide
Our solution uses an actor-critic reinforcement learning model, along with an infused time series, to help us predict the best action, based on the stock prices. The possible actions are as follows:
- Hold: This means that based on the price and projected profit, the trader should hold a stock
- Sell: This means that based on the price and projected profit, the trader should sell a stock
- Buy: This means that based on the price and projected profit, the trader should buy a stock
The actor-critic network is a family of reinforcement learning methods premised on two interacting network models. These models have two components: the actor and the critic. In our case, the network models that we will use will be neural networks. We will use the Keras package, which you have already learned about, to create the neural networks. The reward function that we are looking to improve is the profit.
The actor takes in the state of the environment, then returns the best action, or a policy that...
