Deep Learning-Based Cryptocurrency Price Prediction: A Comparative Analysis

Abstract

In recent years, cryptocurrencies have gained a lot of popularity in the financial markets and now, in addition to investing on them, it is possible to use them as a common currency to meet daily needs. Given the complex nature of financial markets and their reliance on different parameters to determine stocks' and assets' prices, the ability to predict prices is important for investment decisions, especially with respect to cryptocurrencies. To this end, Deep Learning (DL)-based algorithms can be viable solutions, owing to their use as time series forecasting tools. In this paper, we investigate the applicability of DL algorithms to forecast the prices of three cryptocurrencies, namely Bitcoin, Ethereum, and Ripple. We evaluate the performance of the proposed approach, in terms of short-term and long-term prediction accuracy (considering proper error metrics).