Orlicz-Lorentz premia and distortion Haezendonck-Goovaerts risk measures
About
In financial and actuarial research, distortion and Haezendonck-Goovaerts risk measures are attractive due to their strong properties. They have so far been treated separately. In this paper, following a suggestion by Goovaerts, Linders, Van Weert, and Tank, we introduce and study a new class of risk measure that encompasses the distortion and Haezendonck-Goovaerts risk measures, aptly called the distortion Haezendonck-Goovaerts risk measures. They will be defined on a larger space than the space of bounded risks. We provide situations where these new risk measures are coherent, and explore their risk theoretic properties.
Aline Goulard, Karl Grosse-Erdmann• 2025
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Multimodal Reward Modeling | Multimodal RewardBench | Accuracy88.79 | 30 | |
| Reward Modeling | VL-RewardBench | Accuracy86.45 | 13 | |
| Reward Modeling | VisionArena Battle | Accuracy76.66 | 13 | |
| Reward Modeling | WildVision-Battle | Accuracy73.42 | 13 | |
| Reward Modeling | MLLM-as-a-Judge (MaaJ) | Accuracy66.6 | 13 | |
| Reward Modeling | Aggregated Benchmarks Macro | Average Score (excl. MM-RB, VL-RB)72.23 | 12 |
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