Distributionally robust inference for extreme Value-at-Risk
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DOI: 10.1016/j.insmatheco.2020.03.003
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"Getting the right tail right: Modeling tails of health expenditure distributions,"
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- Martin Karlsson & Yulong Wang & Nicolas R. Ziebarth, 2023. "Getting the Right Tail Right: Modeling Tails of Health Expenditure Distributions," NBER Working Papers 31444, National Bureau of Economic Research, Inc.
- Karlsson, Martin & Wang, Yulong & Ziebarth, Nicolas R., 2023. "Getting the Right Tail Right: Modeling tails of health expenditure distributions," ZEW Discussion Papers 23-045, ZEW - Leibniz Centre for European Economic Research.
- Patrick Kuiper & Ali Hasan & Wenhao Yang & Yuting Ng & Hoda Bidkhori & Jose Blanchet & Vahid Tarokh, 2024. "Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions," Papers 2408.00131, arXiv.org.
- Chia-Sheng Tu & Chung-Yuen Yang & Ming-Tang Tsai, 2020. "An Optimal Phase Arrangement of Distribution Transformers under Risk Assessment," Energies, MDPI, vol. 13(21), pages 1-16, November.
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Keywords
Value-at-Risk; Extreme Value-at-Risk; Distributionally robust; Regular variation; Tawn–Molchanov; Linear semi-infinite programming; Extremal coefficients;All these keywords.
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