Revolutionizing agricultural stock volatility forecasting: a comparative study of machine learning and HAR-RV models
This study investigates the realized volatility of the Shanghai Agricultural Stock Index (March 2017–May 2021), focusing on predictive accuracy. By incorporating three primary influencing factors, it evaluates the performance of traditional HAR-RV and LSTM models, demonstrating improved forecasting...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Journal of Applied Economics |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/15140326.2025.2454081 |
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