An improved model accuracy for forecasting risk measures: application of ensemble methods
Author:
Affiliation:
1. Department of Statistics, University of Botswana, Gaborone, Botswana
2. School of Economics and Econometrics, University of Johannesburg, Johannesburg, South Africa
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/15140326.2024.2395775
Reference74 articles.
1. CARL and His POT: Measuring Risks in Commodity Markets
2. Coherent Measures of Risk
3. Atsin J. A. & Ocran M. (2015). Calendar effects and market anomalies on the Johannesburg stock exchange. https://mpra.ub.uni-muenchen.de/87448/
4. Barrera D. Crépey S. Gobet E. Nguyen H.-D. & Saadeddine B. (2022). Learning value-at-risk and expected shortfall. arXiv preprint arXiv:.06476. https://arxiv.org/abs/2209.06476
5. BCBS. (2014). Basel II: Fundamental review of the trading book: A revised market risk framework. Retrieved December 31 2023 from www.bis.org/publ/bcbs265.pdf
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