Comparison of Distance Measurement in Time Series Clustering for Predicting Bitcoin Prices
Ui-Jun Baek, Shin Mu-gon, Min-Seong Lee, Boseon Kim, Jee- Tae Park, Myung‐Sup Kim · 2020
Since the development of Bitcoin, the first blockchain-based cryptocurrency, many cryptocurrencies have formed and have traded in markets. The integrity and anonymity of cryptocurrency was enough to raise its value and its price gained worldwide attention. Therefore, many studies are being carried out to predict the price of cryptocurrency for make a profit. We cluster time series through K-Medoids algorithm and train and evaluate each cluster with predictive models. We also examine the predictive performance in Bitcoin price according to the various distance measurement of clustering.