Long-Term and Short-Term Integrated Learning-Based Price Forecasting for Virtual Currency

As the blockchain and digital economy are becoming mature, a growing number of investors enter the virtual money market. How to exploit the available data to predict the changing trend of the virtual currency has been a focus. On account of the SVR model, this paper proposes a virtual currency price forecasting model with long-term and short-term integrated learning, taking advantage of extensive virtual currency price data to demonstrate the proposed model. The simulation experiment confirm that the accuracy of the SVR model is indeed increased on the virtual currency price forecasting issue.