As human beings, we learn from experiences. We have not become so charming by accident. Years of positive compliments as well as negative criticism, have all helped shape us into who we are today. We learn how to ride a bike by trying out different muscle movements until it just clicks. When you perform actions, you are sometimes rewarded immediately. This is all about Reinforcement learning (RL).
This chapter is all about designing a machine learning system driven by criticisms and rewards. We will see how to apply RL algorithms for a predictive model on real-life datasets.
From the trading point of view, an option is a contract that gives its owner the right to buy (call option) or sell (put option) a financial asset (underlying) at a fixed price (the strike price) at or before a fixed date (the expiry date).
We will see how to develop a real-life application for such options trading using an RL algorithm called QLearning...