Time Series Forecasting of Cryptocurrency Prices Using Machine Learning Algorithms Michael Siek*, Gilbertus Priastian
Business Information Systems
School of Information Systems
Faculty of Computing and Media
Bina Nusantara University
Jakarta, Indonesia 11480
Abstract
The creation of digital exchanges and marketplaces can provide a safe trading platform for cryptocurrencies. The fluctuation of cryptocurrency prices offers some gains in cryptocurrency trading and investment. This paper aims at analyzing technical aspects of cryptocurrency prices by analyzing and forecasting the time series of cryptocurrency prices using the principles of statistical time series analysis and machine learning algorithms. The implementation of Facebook prophet time series forecasting model can supply the demands of reliable cryptocurrency forecasts for the traders or investors in better decision making and improved trading strategy.
Keywords: Dynamics of currency prices, advanced time series forecasting, data-driven modelling
