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Web of Proceedings - Francis Academic Press
Web of Proceedings - Francis Academic Press

The utilization of four models for the prediction of ETH's realized fluctuations

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DOI: 10.25236/iceesr.2024.045


Meiyu Song, Yueqi Yu, Yile Zhang, Zizhen Wang

Corresponding Author

Meiyu Song


Model predictions are very important for the cryptocurrency market, and accurate model predictions are important for the application of blockchain in the market and to improve the socio-economic benefits. In order to predict the realized fluctuation of cryptocurrency more accurately, based on the four models of BASELINE MODEL, RANDOM WALK, GARCH, NEURAL NETWORK, combining the current situation at home and abroad and the advantages in big data processing, by comparing the metrics of RMSE and RMSPE, we conclude that the optimal model for the realized fluctuation is random walk.[1]


ETH, GARCH, neural network, forecasting