用新冠数据提升比特币收益预测，效果显著。
Evaluating COVID 19 Feature Contributions to Bitcoin Return Forecasting: Methodology Based on LightGBM and Genetic Optimization
- 结合LightGBM与遗传算法，系统评估新冠指标对预测的影响。
- 加入新冠数据后模型R2提升40%，RMSE下降2%，效果显著。
- 疫苗接种率是关键预测因子，适合金融风控与政策制定者参考。
本研究提出一种融合LightGBM回归模型与遗传算法（GA）优化的新方法框架，系统评估新冠疫情相关指标对比特币收益预测的贡献。核心目标并非单纯预测收益，而是检验纳入疫情健康数据是否显著提升预测精度。构建了包含每日比特币收益及新冠指标（接种率、住院人数、检测数据）的综合数据集。通过GA在31次独立运行中优化含与不含新冠特征的预测模型，利用分布重叠和曼-惠特尼U检验对性能指标（R²、RMSE、MAE）进行统计比较。置换特征重要性（PFI）分析量化各特征贡献。结果表明，引入新冠指标显著提升模型表现，尤其在捕捉极端市场波动方面（R²提升40%，RMSE下降2%，均具高度统计显著性）。其中，疫苗接种相关指标，尤其是完全接种人群第75百分位数，成为主导预测因子。该方法拓展了现有金融分析工具，融入公共卫生信号，为投资者与政策制定者在系统性危机中应对市场不确定性提供精细化指标。
原文摘要 · Abstract (English)
This study proposes a novel methodological framework integrating a LightGBM regression model and genetic algorithm (GA) optimization to systematically evaluate the contribution of COVID-19-related indicators to Bitcoin return prediction. The primary objective was not merely to forecast Bitcoin returns but rather to determine whether including pandemic-related health data significantly enhances prediction accuracy. A comprehensive dataset comprising daily Bitcoin returns and COVID-19 metrics (vaccination rates, hospitalizations, testing statistics) was constructed. Predictive models, trained with and without COVID-19 features, were optimized using GA over 31 independent runs, allowing robust statistical assessment. Performance metrics (R2, RMSE, MAE) were statistically compared through distribution overlaps and Mann-Whitney U tests. Permutation Feature Importance (PFI) analysis quantified individual feature contributions. Results indicate that COVID-19 indicators significantly improved model performance, particularly in capturing extreme market fluctuations (R2 increased by 40%, RMSE decreased by 2%, both highly significant statistically). Among COVID-19 features, vaccination metrics, especially the 75th percentile of fully vaccinated individuals, emerged as dominant predictors. The proposed methodology extends existing financial analytics tools by incorporating public health signals, providing investors and policymakers with refined indicators to navigate market uncertainty during systemic crises.
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