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A short-term cryptocurrency price movement prediction using centrality measures
Author(s)
Date Issued
2020
ISBN
9781728190129
9781728190136
ISSN
2375-9259
2375-9232
Citation
Ho, K. H., Chiu, W. H., & Li, C. (2020). A short-term cryptocurrency price movement prediction using centrality measures. In Fatta, G. D., Sheng, V. S., Cuzzocrea, A., Zaniolo, C., & Wu, X. (Eds.). Conference proceeding of 20th international conference on data mining workshops, ICDM workshops 2020. 20th International Conference on Data Mining Workshops, ICDM Workshops 2020, Sorrento, Italy (pp. 369-376). IEEE.
Type
Conference Paper
Abstract
We conduct a network analysis with centrality measures, using historical daily close prices of top 120 cryptocurrencies between 2013 and 2020, to study and understand the dynamic evolution and characteristics of the cryptocurrency market. Our study has three primary findings: (1) the overall cross-return correlation among the cryptocurrencies is weakening from 2013 to 2016 and then strengthening thereafter; (2) cryptocurrencies that are primarily used for transaction payment, notably BTC, dominate the market until mid-2016, followed by those developed for applications using blockchain as the underlying technology, particularly data storage and recording such as MAID and FCT, between mid-2016 and mid-2017. Since then, ETH, alongside with its strongly correlated cryptocurrencies have replaced BTC to become the benchmark cryptocurrencies. Furthermore, during the outbreak of COVID-19, QTUM and BNB have intermittently replaced ETH to take the leading positions due to their active community engagement during the pandemic; (3) centrality measures are useful features in improving the prediction accuracy of the short-term cryptocurrency price movement.
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