Acquiring trading strategy in financial market using Reinforcement Learning

Abstract

Machine learning is attracting attention due to the success of AI image recognition and game AI represented by AlphaGo. Also, due to its high accuracy, it is being applied to various fields. In particular, the application of reinforcement learning has become active due to the success of autonomous driving technology and game AI. Currently, research on strategy acquisition in financial market transactions using machine learning is also active. In this research, we aim to acquire trading rules by using reinforcement learning in foreign exchange margin trading (FX).