Nonparametric estimation of 100(1 − p)% expected shortfall: p → 0 as sample size is increased

DOI10.1080/03610918.2016.1152370zbMath1462.62209OpenAlexW2506935376MaRDI QIDQ4563411

Santanu Dutta, Suparna Biswas

Publication date: 1 June 2018

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2016.1152370

zbMATH Keywords

nonparametric estimationexpected shortfall

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Nonparametric estimation (62G05) Statistics of extreme values; tail inference (62G32)

Related Items (1)

The expected-based value-at-risk and expected shortfall using quantile and expectile with application to electricity market data

Cites Work

• Extreme quantile estimation for dependent data, with applications to finance
• Estimating conditional tail expectation with actuarial applications in view
• Coherent Measures of Risk
• Estimation methods for expected shortfall
• Bandwith selection for the smoothing of distribution functions
• Nonparametric Estimation and Sensitivity Analysis of Expected Shortfall
• Empirical properties of asset returns: stylized facts and statistical issues
• COMPARATIVE ANALYSES OF EXPECTED SHORTFALL AND VALUE-AT-RISK(Special Issue on Theory, Methodology and Applications in Financial Engneering)

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