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Price Prediction of Cryptocurrency: An Empirical Study

  • Liuqing Yang
  • Xiao-Yang LiuEmail author
  • Xinyi Li
  • Yinchuan Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11911)

Abstract

Cryptocurrency has high volatility in market price since its inception. Existing works have explored different models to predict cryptocurrency prices. However, the accuracy is not satisfactory. In this paper, we conduct empirical study on the price forecasting. Firstly, we quantify the entropy and the conditional entropy of cryptocurrencies and stocks, respectively, and find that cryptocurrencies are more difficult to predict than stocks. Secondly, we evaluate various perspectives, including Twitter volume, Twitter sentiment and CNN-LSTM price prediction. Empirical results demonstrated the randomness in price validity, thus no single method is robust enough for cryptocurrency price prediction.

Keywords

Cryptocurrency Block chain Price prediction LSTM 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Liuqing Yang
    • 1
  • Xiao-Yang Liu
    • 1
    Email author
  • Xinyi Li
    • 1
  • Yinchuan Li
    • 1
    • 2
  1. 1.Columbia UniversityNew YorkUSA
  2. 2.Beijing Institute of TechnologyBeijingChina

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