Guardado en:
| Autores principales: | , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2603.12767 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866915859068354560 |
|---|---|
| author | Nistor, Mihaela-Adriana Popescu, Ionel |
| author_facet | Nistor, Mihaela-Adriana Popescu, Ionel |
| contents | In this paper we introduce a generalization of classical risk measures in which the risk is represented by a step function taking two values, corresponding to two endogenously determined market regimes. This extends the traditional framework where risk measures map random variables to single real numbers. For the quadratic loss function, we study the optimization problem of determining the optimal regime threshold and corresponding values. In the case of log-concave distributions we give conditions for the uniqueness of the regime changing. We treat the case of one dimension and also of multi-dimensions for elliptic distributions.
We demonstrate the necessity of convexity through counterexamples. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_12767 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A property of log-concave and weakly-symmetric distributions for two step approximations of random variables Nistor, Mihaela-Adriana Popescu, Ionel Probability Risk Management In this paper we introduce a generalization of classical risk measures in which the risk is represented by a step function taking two values, corresponding to two endogenously determined market regimes. This extends the traditional framework where risk measures map random variables to single real numbers. For the quadratic loss function, we study the optimization problem of determining the optimal regime threshold and corresponding values. In the case of log-concave distributions we give conditions for the uniqueness of the regime changing. We treat the case of one dimension and also of multi-dimensions for elliptic distributions. We demonstrate the necessity of convexity through counterexamples. |
| title | A property of log-concave and weakly-symmetric distributions for two step approximations of random variables |
| topic | Probability Risk Management |
| url | https://arxiv.org/abs/2603.12767 |