Cryptocurrency Price Prediction Using Linear Regression and Long Short-Term Memory (LSTM)

Abstract

Abstract: Predicting future events is difficult, particularly with regards to cryptocurrency, where the media, influential people and governments have a sharp and vital impact on worth. Cryptocurrency market analysis is a method through which the realworld data of the cryptocurrency market is used to predict where it will go next. If foretold accurately, it helps investors to invest when the value is low (purchasing in bulk when the price is dipping) and sell once it's high so as to gain a profit. This research provides two machine learning algorithms which are Long Short-Term Memory (LSTM) and Linear Regression for predicting the values of six different types of crypto currencies such as Bitcoin (BTC), Dash coin (DASH), Lite coin (LTC), Dogecoin (DOGE), Ethereum (ETH), and Monero (XMR). The accuracy of the models is analyzed using mean squared error.