Some Studies on Stochastic Optimization based Quantitative Risk Management
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866917178041696256 |
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| author | Hu, Zhaolin |
| author_facet | Hu, Zhaolin |
| contents | Risk management often plays an important role in decision making under uncertainty. In quantitative risk management, assessing and optimizing risk metrics requires efficient computing techniques and reliable theoretical guarantees. In this paper, we introduce several topics on quantitative risk management and review some of the recent studies and advancements on the topics. We consider several risk metrics and study decision models that involve the metrics, with a main focus on the related computing techniques and theoretical properties. We show that stochastic optimization, as a powerful tool, can be leveraged to effectively address these problems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_24736 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Some Studies on Stochastic Optimization based Quantitative Risk Management Hu, Zhaolin Optimization and Control Risk management often plays an important role in decision making under uncertainty. In quantitative risk management, assessing and optimizing risk metrics requires efficient computing techniques and reliable theoretical guarantees. In this paper, we introduce several topics on quantitative risk management and review some of the recent studies and advancements on the topics. We consider several risk metrics and study decision models that involve the metrics, with a main focus on the related computing techniques and theoretical properties. We show that stochastic optimization, as a powerful tool, can be leveraged to effectively address these problems. |
| title | Some Studies on Stochastic Optimization based Quantitative Risk Management |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2512.24736 |