Research on Bitcoin Price Prediction Based on ARIMA-LSTM Hybrid Modeling

Abstract

Currently, there are relatively few studies on Bitcoin price prediction, and accurate prediction of Bitcoin price is the focus of economic policy makers as well as investors. In this paper, we combine the methods of traditional time series model (ARIMA) and deep learning model (LSTM) to analyze the price prediction of bitcoin historical data. The empirical results show that the single LSTM model has the best prediction effect in the three prediction intervals of short-term, medium-term, and long-term. The ARIMA-LSTM hybrid model has a little improvement compared to the ARIMA model, which is chosen in this paper under the assumption that the relationship between the linear and nonlinear parts is additive, which will make the prediction effect worse. This problem will be avoided if the nonlinear combination is used for modeling, making the prediction better.