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Multivariate bitcoin price volatility forecasting: an optimized decomposition pattern learning model

delete2026-08-17
delete0
PRE
AI
S
Shiva Pourmand
H
Hesam Omranpour *
A
Asal Aghaz
DOI：10.1016/j.irfa.2026.105345delete
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摘要

摘要

En 中文
• 通过集成EMD/VMD分解开发了一种比特币预测的多变量框架。• 对时间窗口和特征进行进化优化，提高了预测效果，并揭示了波动市场中关键模式。• 使用随机森林实现了高精度的短期比特币价格预测（MAPE = 0.01166 ± 0.00105）。• 将比特币波动率预测重新表述为二分类问题，并实现了95.47%的预测准确率。• 通过在多种交易成本情景下的四年回测，证明了其经济有效性和稳健性。
Keyword:
Bitcoin
Multivariate
Multistep
EMD/VMD
Volatility patterns

期刊

International Review of Financial Analysis 封面图
International Review of Financial Analysis
IF:
9.8
论文数:
4.2K
被引数:
1.9W

机构

A
amirkabir university of technology
学者数:
1.1K
论文数: 581
被引数: 0
B
babol noshirvani university of technology
学者数:
3.2K
论文数: 3.1K
被引数: 3
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