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Hybrid data decomposition-based deep learning for Bitcoin prediction and algorithm trading
Li,Yuze1; Jiang,Shangrong2; Li,Xuerong1; Wang,Shouyang2
2022-04-02
发表期刊Financial Innovation
卷号8期号:1
摘要AbstractIn recent years, Bitcoin has received substantial attention as potentially high-earning investment. However, its volatile price movement exhibits great financial risks. Therefore, how to accurately predict and capture changing trends in the Bitcoin market is of substantial importance to investors and policy makers. However, empirical works in the Bitcoin forecasting and trading support systems are at an early stage. To fill this void, this study proposes a novel data decomposition-based hybrid bidirectional deep-learning model in forecasting the daily price change in the Bitcoin market and conducting algorithmic trading on the market. Two primary steps are involved in our methodology framework, namely, data decomposition for inner factors extraction and bidirectional deep learning for forecasting the Bitcoin price. Results demonstrate that the proposed model outperforms other benchmark models, including econometric models, machine-learning models, and deep-learning models. Furthermore, the proposed model achieved higher investment returns than all benchmark models and the buy-and-hold strategy in a trading simulation. The robustness of the model is verified through multiple forecasting periods and testing intervals.
关键词Bitcoin price Variational mode decomposition Deep learning Price forecasting Algorithmic trading
DOI10.1186/s40854-022-00336-7
语种英语
WOS记录号BMC:10.1186/s40854-022-00336-7
出版者Springer Berlin Heidelberg
引用统计
文献类型期刊论文
条目标识符http://ir.amss.ac.cn/handle/2S8OKBNM/60078
专题中国科学院数学与系统科学研究院
通讯作者Li,Xuerong
作者单位1.Chinese Academy of Sciences; Academy of Mathematics and Systems Science
2.University of Chinese Academy of Sciences; School of Economics and Management
推荐引用方式
GB/T 7714
Li,Yuze,Jiang,Shangrong,Li,Xuerong,et al. Hybrid data decomposition-based deep learning for Bitcoin prediction and algorithm trading[J]. Financial Innovation,2022,8(1).
APA Li,Yuze,Jiang,Shangrong,Li,Xuerong,&Wang,Shouyang.(2022).Hybrid data decomposition-based deep learning for Bitcoin prediction and algorithm trading.Financial Innovation,8(1).
MLA Li,Yuze,et al."Hybrid data decomposition-based deep learning for Bitcoin prediction and algorithm trading".Financial Innovation 8.1(2022).
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