E3S Web of Conferences (Jan 2020)

Bitcoin price prediction using ARIMA and LSTM

  • Hua Yiqing

DOI
https://doi.org/10.1051/e3sconf/202021801050
Journal volume & issue
Vol. 218
p. 01050

Abstract

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The goal of this paper is to compare the accuracy of bitcoin price in USD prediction based on two different model, Long Short term Memory (LSTM) network and ARIMA model. Real-time price data is collected by Pycurl from Bitfine. LSTM model is implemented by Keras and TensorFlow. ARIMA model used in this paper is mainly to present a classical comparison of time series forecasting, as expected, it could make efficient prediction limited in short-time interval, and the outcome depends on the time period. The LSTM could reach a better performance, with extra, indispensable time for model training, especially via CPU.