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.
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Yang, L., Liu, XY., Li, X., Li, Y. (2019). Price Prediction of Cryptocurrency: An Empirical Study. In: Qiu, M. (eds) Smart Blockchain. SmartBlock 2019. Lecture Notes in Computer Science(), vol 11911. Springer, Cham. https://doi.org/10.1007/978-3-030-34083-4_13
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DOI: https://doi.org/10.1007/978-3-030-34083-4_13
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