(Non-)robustness of maximum likelihood estimators for operational risk severity distributions

DOI10.1080/14697680903159240zbMath1201.91091OpenAlexW2131582885MaRDI QIDQ3063853

Sonja Huber

Publication date: 15 December 2010

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/14697680903159240

zbMATH Keywords

risk measuresstatistical methodsrisk managementdownside riskvalue at risknon-Gaussian distributionsextreme value statistical applications

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05)

Related Items

Bayesian estimation of truncated data with applications to operational risk measurement

Uses Software

• ROptEst

Cites Work

• A robust estimator for the tail index of Pareto-type distributions
• A simple general approach to inference about the tail of a distribution
• Robust estimation of extremes
• Parameter Estimation for a Generalized Gamma Distribution
• Robust Statistics
• Robust Estimation of a Location Parameter
• Robust Statistics
• Robust inference with GMM estimators
• Robust estimation of tail parameters for two-parameter Pareto and exponential models via generalized quantile statistics

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