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. ...
