Assessing the Efficient Market Hypothesis for Cryptocurrencies with High-Frequency Data using Time Series Classification

Published in In Proceedings of the 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022), 2022

Recommended citation: Rafael Ayllón-Gavilán, David Guijo-Rubio, Pedro Antonio Gutiérrez, César Hervás-Martínez, "Assessing the Efficient Market Hypothesis for Cryptocurrencies with High-Frequency Data using Time Series Classification." In Proceedings of the 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022), Lecture Notes in Networks and Systems, Vol. 531, 2022, Salamanca, Spain, pp.146--155. http://doi.org/10.1007/978-3-031-18050-7_14