About this document
Machine Learning for Stock Crash Risk by Stanislav Se is a document available to read on EtoBox.
This research introduces a machine learning-based measure for assessing stock price crash risk using the Minimum Covariance Determinant (MCD) methodology, which predicts crash risk through regression analysis. The study finds a significant correlation between stock price crash risk and firm-specific investor sentiment, indicating that higher sentiment levels increase the likelihood of crashes. The proposed model outperforms traditional measures, demonstrating its robustness and adaptability to varying marke
- Author
- Stanislav Se
- Language
- EN