Autoregressive Integrated Moving Average Model based Prediction of Bitcoin Close Price

Abstract

Analysis of any digital currency is performed for identifying and quantifying uncertainties, estimating their impact on results with real-time market value. Cryptocurrency, as an encrypted form of currencies which is used for shopping, investment, money transfer and in other purpose now days. Most popular use of Bitcoins are investment because its price was unexpectedly high in past few years (data shown in content of paper). In this paper prediction of Bitcoin close price by using the ARIMA model has been performed. The ARIMA model is found suitable for the prediction of bitcoin prices because this model is used for prediction of time series data. The forecast of future values is provided based on seasonality and trend present in the price data. In terms of visualizations, results are manifest by using R programming language. The obtained results are then compared with actual prices and percent mean error is calculated. The present mean error is found here less than 6% for most of the values.