ASYMPTOTIC EXPANSIONS OF GENERALIZED QUANTILES AND EXPECTILES FOR EXTREME RISKS

DOI10.1017/S0269964815000017zbMath1373.62216MaRDI QIDQ5358042

Taizhong Hu, Tiantian Mao, Kai Wang Ng

Publication date: 19 September 2017

Published in: Probability in the Engineering and Informational Sciences (Search for Journal in Brave)

Mathematics Subject Classification ID

Statistics of extreme values; tail inference (62G32)

Related Items (9)

Statistical inference for extreme extremile in heavy-tailed heteroscedastic regression model ⋮ Asymptotic properties of generalized shortfall risk measures for heavy-tailed risks ⋮ Extreme M-quantiles as risk measures: from \(L^{1}\) to \(L^{p}\) optimization ⋮ ExpectHill estimation, extreme risk and heavy tails ⋮ Risk concentration based on expectiles for extreme risks under FGM copula ⋮ Dual representation of expectile-based expected shortfall and its properties ⋮ Tail expectile process and risk assessment ⋮ Semi-parametric estimation of multivariate extreme expectiles ⋮ Relative bound and asymptotic comparison of expectile with respect to expected shortfall

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