On the elicitability of range value at risk
| Autor: | Tobias Fissler, Johanna F. Ziegel |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
101029 Mathematische Statistik
Statistics and Probability 101018 Statistik 101018 Statistics Risk measure Rank (computer programming) Truncated mean 401117 Viticulture 101029 Mathematical statistics 101007 Financial mathematics 62C99 62G35 62P05 91G70 [MSC 2010] Term (time) Expected shortfall Range (mathematics) 510 Mathematics 101007 Finanzmathematik Modeling and Simulation Backtesting consistency expected shortfall point forecasts scoring functions trimmed mean Econometrics Statistics Probability and Uncertainty Robustness (economics) Value at risk 401117 Weinbau Mathematics |
| Zdroj: | Fissler, Tobias; Ziegel, Johanna F. (2021). On the elicitability of Range Value at Risk. Statistics & risk modeling, 38(1-2), pp. 25-46. De Gruyter 10.1515/strm-2020-0037 |
| ISSN: | 2196-7040 2193-1402 |
| DOI: | 10.1515/strm-2020-0037 |
| Popis: | The debate of which quantitative risk measure to choose in practice has mainly focused on the dichotomy between value at risk (VaR) and expected shortfall (ES). Range value at risk (RVaR) is a natural interpolation between VaR and ES, constituting a tradeoff between the sensitivity of ES and the robustness of VaR, turning it into a practically relevant risk measure on its own. Hence, there is a need to statistically assess, compare and rank the predictive performance of different RVaR models, tasks subsumed under the term “comparative backtesting” in finance. This is best done in terms of strictly consistent loss or scoring functions, i.e., functions which are minimized in expectation by the correct risk measure forecast. Much like ES, RVaR does not admit strictly consistent scoring functions, i.e., it is not elicitable. Mitigating this negative result, we show that a triplet of RVaR with two VaR-components is elicitable. We characterize all strictly consistent scoring functions for this triplet. Additional properties of these scoring functions are examined, including the diagnostic tool of Murphy diagrams. The results are illustrated with a simulation study, and we put our approach in perspective with respect to the classical approach of trimmed least squares regression. |
| Databáze: | OpenAIRE |
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