Not logged in.
Quick Search - Contribution
Contribution Details
| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Law-Invariant Functionals that Collapse to the Mean: Beyond Convexity |
| Organization Unit | |
| Authors |
|
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
|
| Journal Title | Mathematics and Financial Economics |
| Publisher | Springer |
| Geographical Reach | international |
| ISSN | 1862-9679 |
| Volume | 16 |
| Number | 3 |
| Page Range | 447 - 480 |
| Date | 2022 |
| Abstract Text | We establish general "collapse to the mean" principles that provide conditions under which a law-invariant functional reduces to an expectation. In the convex setting, we retrieve and sharpen known results from the literature. However, our results also apply beyond the convex setting. We illustrate this by providing a complete account of the "collapse to the mean" for quasiconvex functionals. In the special cases of consistent risk measures and Choquet integrals, we can even dispense with quasiconvexity. In addition, we relate the "collapse to the mean" to the study of solutions of a broad class of optimisation problems with law-invariant objectives that appear in mathematical finance, insurance, and economics. We show that the corresponding quantile formulations studied in the literature are sometimes illegitimate and require further analysis. |
| Free access at | Official URL |
| Official URL | https://link.springer.com/article/10.1007/s11579-022-00313-9 |
| Digital Object Identifier | 10.1007/s11579-022-00313-9 |
| Other Identification Number | merlin-id:22591 |
| PDF File |
Download from ZORA
|
| Export |
BibTeX
EP3 XML (ZORA)
|