Document Type : Research Article
Department of Computer Science, Shaqra University, Shaqraa, Saudi Arabia
The increasing volatility in pricing and growing potential for profit in digital currency have made predicting the price of cryptocurrency a very attractive research topic. Several studies have already been conducted using various machine-learning models to predict crypto currency prices. This study presented in this paper applied a classic Autoregressive Integrated Moving Average(ARIMA) model to predict the prices of the three major cryptocurrencies âAT Bitcoin, XRP and Ethereum âAT using daily, weekly and monthly time series. The results demonstrated that ARIMA outperforms most other methods in predicting cryptocurrency prices on a daily time series basis in terms of mean absolute error (MAE), mean squared error (MSE) and root mean squared error(RMSE).
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