Developing a Stock Price Predictive Model
An emerging area for applying is the stock market trading, where a trader acts like a reinforcement agent since buying and selling (that is, action) particular stock changes the state of the trader by generating profit or loss, that is, reward. The following figure shows some of the most active stocks on July 15, 2017 (for an example):
Now, we want to develop an intelligent agent that will predict stock prices such that a trader will buy at a low price and sell at a high price. However, this type of prediction is not so easy and is dependent on several parameters such as the current number of stocks, recent historical prices, and most importantly, on the available budget to be invested for buying and selling.
The states in this situation are a vector containing information about the current budget, current number of stocks, and a recent history of stock prices (the last 200 stock prices). So each state is a 202...