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The effect of green energy, global environmental indexes, and stock markets in predicting oil price crashes: Evidence from explainable machine learning
This study aims to predict oil prices during the 2019 novel coronavirus (COVID-19) pandemic by looking into green energy resources, global environmental indexes (ESG), and stock markets. The study employs advanced machine learning, such as the LightGBM, CatBoost, XGBoost, Random Forest (RF), and neu...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier Ltd.
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8437676/ https://www.ncbi.nlm.nih.gov/pubmed/34392096 http://dx.doi.org/10.1016/j.jenvman.2021.113511 |