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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.21556 |
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| _version_ | 1866912731110572032 |
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| author | Bonollo, Michele Grasselli, Martino Mori, Gianmarco Oz, Havva Nilsu |
| author_facet | Bonollo, Michele Grasselli, Martino Mori, Gianmarco Oz, Havva Nilsu |
| contents | Despite decades of research in risk management, most of the literature has focused on scalar risk measures (like e.g. Value-at-Risk and Expected Shortfall). While such scalar measures provide compact and tractable summaries, they provide a poor informative value as they miss the intrinsic multivariate nature of risk.To contribute to a paradigmatic enhancement, and building on recent theoretical work by Faugeras and Pagés (2024), we propose a novel multivariate representation of risk that better reflects the structure of potential portfolio losses, while maintaining desirable properties of interpretability and analytical coherence. The proposed framework extends the classical frequency-severity approach and provides a more comprehensive characterization of extreme events. Several empirical applications based on real-world data demonstrate the feasibility, robustness and practical relevance of the methodology, suggesting its potential for both regulatory and managerial applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_21556 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Informative Risk Measures in the Banking Industry: A Proposal based on the Magnitude-Propensity Approach Bonollo, Michele Grasselli, Martino Mori, Gianmarco Oz, Havva Nilsu Risk Management Computational Finance Despite decades of research in risk management, most of the literature has focused on scalar risk measures (like e.g. Value-at-Risk and Expected Shortfall). While such scalar measures provide compact and tractable summaries, they provide a poor informative value as they miss the intrinsic multivariate nature of risk.To contribute to a paradigmatic enhancement, and building on recent theoretical work by Faugeras and Pagés (2024), we propose a novel multivariate representation of risk that better reflects the structure of potential portfolio losses, while maintaining desirable properties of interpretability and analytical coherence. The proposed framework extends the classical frequency-severity approach and provides a more comprehensive characterization of extreme events. Several empirical applications based on real-world data demonstrate the feasibility, robustness and practical relevance of the methodology, suggesting its potential for both regulatory and managerial applications. |
| title | Informative Risk Measures in the Banking Industry: A Proposal based on the Magnitude-Propensity Approach |
| topic | Risk Management Computational Finance |
| url | https://arxiv.org/abs/2511.21556 |