Cryptocurrency Price Prediction Using LSTM and GRU Networks

Abstract

cryptocurrencies are increasingly used by investors as assets, mainly for short term. Therefore, in the financial sector, prediction is important and can be done using Deep Learning techniques. This paper presents results on the prediction of three cryptocurrencies that see high volumes but are discussed in very few papers. In this paper we used LSTM (Long Short-Term Memory) models and also GRU (Gated Recurrent Unit). These are applied to three important cryptocurrencies, namely DOGECoin, Ripple (XRP) and OMG Network. The results presented prove that LSTM and GRU can be successful in predicting the daily closing values for these cryptocurrencies.