A new non-parametric estimation of the expected shortfall for dependent financial losses

DOI10.1016/J.JSPI.2024.106151MaRDI QIDQ6556777

Mohammed Bouaddi, Khouzeima Moutanabbir

Publication date: 17 June 2024

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

zbMATH Keywords

kernel estimation\(\alpha\)-mixingvalue-at-risk (VaR)nonparametric smoothingexpected shortfall (ES)

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Bahadur representation of linear kernel quantile estimator of VaR under \(\alpha \)-mixing assumptions
• Quantifying market risk with value-at-risk or expected shortfall? -- Consequences for capital requirements and model risk
• Nonparametric kernel estimation of CVaR under \(\alpha\)-mixing sequences
• Can a regulatory risk measure induce profit-maximizing risk capital allocations? The case of conditional tail expectation
• Risk aggregation and capital allocation using a new generalized Archimedean copula
• Coherent measures of risk
• A CENTRAL LIMIT THEOREM AND A STRONG MIXING CONDITION
• Nonparametric Estimation and Sensitivity Analysis of Expected Shortfall
• Nonparametric estimation of 100(1 − p)% expected shortfall: p → 0 as sample size is increased

This page was built for publication: A new non-parametric estimation of the expected shortfall for dependent financial losses

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6556777)