Reinforcement Learning and Its Applications in Finance

Abstract

Reinforcement learning (RL) models, a practical application drawn upon deep neural networks, are among the models examined in to identify its applicability to solve various problems related to financial areas including stock markets, portfolio management, forex markets, bankruptcy and insolvency, financial crisis, and cryptocurrency. A comprehensive introductory text focusing on financial applications of RL is rare if not difficult to find. This essay is aimed at presenting a short yet concise one-stop-resource that covers: (a) few important basics of RL, (b) types of problems it can address, (c) how it works, (d) its strength and limitations especially when compared to other approaches, (e) scopes within which the use of RL is recommended, and (f) examples of its applications in finance. Getting this writing to be comprehensive and effective in practice is a much more ambitious attempt, but it does highlight what it makes to work in practice.  sample/object of research, research instruments, and research results