Exploring a Hybrid Algorithm for Price Volatility Prediction of Bitcoin

被引：0
|
作者：
Li, Zikang [1 ]
Cheng, Xusen [2 ]
Bao, Ying [1 ]
机构：
[1] Univ Int Business & Econ, Sch Informat Technol & Management, Beijing 100029, Peoples R China
[2] Renmin Univ China, Sch Informat, Beijing 100872, Peoples R China
来源：
PROCEEDINGS OF NINETEENTH WUHAN INTERNATIONAL CONFERENCE ON E-BUSINESS | 2020年
关键词：
Bitcoin; GARCH; volatility prediction; machine learning;
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
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.
引用
收藏
页码：12 / 19
页数：8
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