Estimating the distortion parameter of the proportional-hazard premium for heavy-tailed losses
From MaRDI portal
Publication:654807
DOI10.1016/J.INSMATHECO.2011.05.001zbMath1229.91155OpenAlexW2021440908MaRDI QIDQ654807
Ričardas Zitikis, Abdelhakim Necir, Brahim Brahimi, Djamel Meraghni
Publication date: 21 December 2011
Published in: Insurance Mathematics \& Economics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.insmatheco.2011.05.001
heavy tailextreme valuedistortion risk measuredistortion parameterproportional-hazard premiumproportional-hazard transformrisk aversion index
Related Items (6)
ESTIMATION OF RISK MEASURES FROM HEAVY TAILED DISTRIBUTIONS ⋮ Generalized PELVE and applications to risk measures ⋮ Statistical foundations for assessing the difference between the classical and weighted-Gini betas ⋮ On the interplay between distortion, mean value and Haezendonck-Goovaerts risk measures ⋮ Estimating the distortion parameter of the proportional hazards premium for heavy-tailed losses under Lévy-stable regime ⋮ Weighted allocations, their concomitant-based estimators, and asymptotics
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- \(L\)-functions, processes, and statistics in measuring economic inequality and actuarial risks
- Estimating the conditional tail expectation in the case of heavy-tailed losses
- Estimating L-functionals for heavy-tailed distributions and application
- Empirical estimation of the proportional hazard premium for heavy-tailed claim amounts
- On the estimation of the extreme-value index and large quantile estimation
- Weighted premium calculation principles
- Estimating conditional tail expectation with actuarial applications in view
- Reiss and Thomas' automatic selection of the number of extremes
- Weighted risk capital allocations
- Laws of large numbers for sums of extreme values
- A simple general approach to inference about the tail of a distribution
- Optimal choice of sample fraction in extreme-value estimation
- Selecting the optimal sample fraction in univariate extreme value estimation
- A synthesis of risk measures for capital adequacy
- Risk measures, distortion parameters, and their empirical estimation
- Asymptotically best linear unbiased tail estimators under a second-order regular variation condition
- On univariate extreme value statistics and the estimation of reinsurance premiums
- Coherent Measures of Risk
- Statistical estimate of the proportional hazard premium of loss
- Limit theorems for the ratio of the empirical distribution function to the true distribution function
- Estimation of Parameters and Larger Quantiles Based on the k Largest Observations
- Applying the Proportional Hazard Premium Calculation Principle
- Empirical Estimation of Risk Measures and Related Quantities
- Using a bootstrap method to choose the sample fraction in tail index estimation
- Estimating the mean of a heavy tailed distribution
- Confidence intervals for the tail index
This page was built for publication: Estimating the distortion parameter of the proportional-hazard premium for heavy-tailed losses