Ensemble Boosting Trees for Volatility Forecasting
The study finds ensemble boosting tree models, particularly CatBoost and LightGBM, more effective than traditional models in predicting China's crude oil futures volatility, with macroeconomic and HAR-type variables impacting forecasts differently.
Featured in No. 49 on 15 May 2024 · on release day
- Released
- 15 May 2024
- First featured
- No. 49 · 15 May 2024
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- Not yet, as far as Semantic Scholar knows
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- Identifier
- RePEc:eee:reveco:v:92:y:2024:i:c:p:1595-1615
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