A Systematic Mapping Study of Cryptocurrency and Its Forecasting Methods

Abstract

Cryptocurrency has gained its popularity in recent years. Due to enormous profitability potential, many investors and researchers alike have taken an interest in this domain. There is a lot of data in the cryptocurrency market that has to be analysed to make the right choices quickly when trading. Many have tried to automate the trading process by utilizing various prediction models and reinforcement learning to further streamline the trading process. It is therefore important to collect and summarize current state of the art technologies that investors and researchers use to predict and automate the cryptocurrency trading process. This paper provides a repository of knowledge to find out what other researchers have done by covering more than 13 different machine learning methods and several hybrid methods. This paper is the initial research step to try to come up with a new state-of-the-art approach to programmatic trading by determining a method that can be researched further.