Exploring a Hybrid Algorithm for Price Volatility Prediction of Bitcoin

Authors

Zikang Li, School of Information Technology and Management, University of International Business and Economics, Beijing, 100029, ChinaFollow
Xusen Cheng, School of Information, Renmin University of China, Beijing, 100872, ChinaFollow
Ying Bao, School of Information Technology and Management, University of International Business and Economics, Beijing, 100029, China

Abstract

In recent years, the Bitcoin investment market has become increasingly popular. We collected existing literature on Bitcoin and found that predictions about the role of Bitcoin in investment portfolios and the volatility of Bitcoin price as well as return have become advanced research topics. This study shows our current work on the prediction of Bitcoin price volatility and proposes an idea for predicting the price volatility. We have designed an experiment that compares different combinations of machine learning algorithms with GARCH-type models, intending to compare the effects of these models in the prediction of Bitcoin time series and finally implement an optimized algorithm.

Recommended Citation

Li, Zikang; Cheng, Xusen; and Bao, Ying, "Exploring a Hybrid Algorithm for Price Volatility Prediction of Bitcoin" (2020). WHICEB 2020 Proceedings. 4.
https://aisel.aisnet.org/whiceb2020/4