A regression model for crypto-currency price

Abstract

The aim of the paper is to fit a regression model which can be used commonly for the four important crypto currencies: Bitcoin, Litecoin, Ethereum and Ripple to predict the prices. The data has information over the past six years regarding price, transaction volume, transaction count, exchange volume, generated coins etc of these currencies. Understanding the dynamics of crypto currency market can help to a certain extent to take wise investment decisions. Among the variables under consideration the study revealed that transaction volume can be used as an influencing variable to fit a quadratic regression model and predict the prices of the crypto currencies.