Stock Crash Risk Prediction With Implied Volatility Index: A Comparison of Tree-Based and Transformer-Based Models
Stock price crash prediction is important for both risk management and investment decisions. We build machine learning models that predict whether individual stocks will experience a maximum drawdown over 40% within 60 trading days. The dataset covers 2,812 Korean listed stocks from 2015 to 2024. We...
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| Principais autores: | , |
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| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
IEEE
2026-01-01
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| Serija: | IEEE Access |
| Teme: | |
| Online dostop: | https://ieeexplore.ieee.org/document/11359683/ |
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