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Extreme risk in portfolio selection: model comparison and analysis

Delava, Walter
(2024)

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Delava_52561900_2024.pdf
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Details

Supervisors
Lassance, Nathan
Faculty
Louvain School of Management
Degree label
Master [120] : ingénieur de gestion, à finalité spécialisée
Abstract
This master’s thesis applies Extreme Value Theory (EVT) to risk management in financial markets, comparing traditional Value-at-Risk (VaR) models with EVT-based models. Using major stock indices such as BEL20, CAC40, S&P500, and MSCI World, the analysis examines the models' ability to predict extreme losses. Findings indicate that EVT models are more robust in identifying extreme events and estimating maximum losses. The results support the use of diverse financial data and multiple quantitative approaches for more accurate risk predictions. This study highlights the practical implications of EVT in enhancing financial risk management.

Citations

  • APA

Delava, W. (2024). Extreme risk in portfolio selection: model comparison and analysis. https://dial-mem.test.bib.ucl.ac.be/handle/2078.2/38982