Value-at-risk forecasting- based on textual information and a hybrid deep learning-based approach
The recent rise in deep learning and natural language processing (NLP) applications has notably improved productivity across different fields. This research aims to refine Value-at-Risk (VaR) model accuracy by leveraging text mining and deep learning. It first uses NLP to analyze online news sentime...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
Elsevier
2025
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| Online Access: | http://psasir.upm.edu.my/id/eprint/120553/1/120553.pdf http://psasir.upm.edu.my/id/eprint/120553/ https://linkinghub.elsevier.com/retrieve/pii/S1059056025005660 |
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