Proceedings of the 2nd International Conference on Information, Control and Automation, ICICA 2022, December 2-4, 2022, Chongqing, China

Research Article

Research on the Price Prediction of Bitcoin and Gold Based on Random Forest Model

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  • @INPROCEEDINGS{10.4108/eai.2-12-2022.2327931,
        author={Jingben  Lu and Yawei  Song and Qianhui  Li and Junrong  Tang and Yuke  Hou},
        title={Research on the Price Prediction of Bitcoin and Gold Based on Random Forest Model},
        proceedings={Proceedings of the 2nd International Conference on Information, Control and Automation, ICICA 2022, December 2-4, 2022, Chongqing, China},
        publisher={EAI},
        proceedings_a={ICICA},
        year={2023},
        month={3},
        keywords={bitcoin; gold price; random forest; investment},
        doi={10.4108/eai.2-12-2022.2327931}
    }
    
  • Jingben Lu
    Yawei Song
    Qianhui Li
    Junrong Tang
    Yuke Hou
    Year: 2023
    Research on the Price Prediction of Bitcoin and Gold Based on Random Forest Model
    ICICA
    EAI
    DOI: 10.4108/eai.2-12-2022.2327931
Jingben Lu1, Yawei Song1, Qianhui Li2, Junrong Tang1, Yuke Hou1,*
  • 1: Guangxi Normal University
  • 2: North China University of Technology
*Contact email: hyk20000827@qq.com

Abstract

In recent years, machine learning has achieved good results in the field of asset prices. Compared with traditional data analysis and technical analysis, using machine learning methods can show unique advantages in various aspects. In this paper, we combine the correlation between bull and bear markets and bitcoin and gold prices in the market, and apply a random forest model to predict them. The results of the study show that the random forest has high explanations and the accuracy of the model predictions are above 0.9, indicating that the model is a good fit for bitcoin and gold price predictions; bitcoin price is volatile and not suitable as a long-term investment, and it is suitable for gold at the beginning of each year.