NONPARAMETRIC ESTIMATION OF CONDITIONAL VALUE-AT-RISK AND EXPECTED SHORTFALL BASED ON EXTREME VALUE THEORY

DOI10.1017/S0266466616000517zbMath1441.62240arXiv1612.08099MaRDI QIDQ4599616

Feng Yao, Carlos Martins-Filho, Maximo Torero

Publication date: 4 January 2018

Published in: Econometric Theory (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1612.08099

Mathematics Subject Classification ID

Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70) Nonparametric estimation (62G05) Statistics of extreme values; tail inference (62G32)

Related Items

SIMULTANEOUS CONFIDENCE BANDS FOR CONDITIONAL VALUE-AT-RISK AND EXPECTED SHORTFALL, An Extensive Comparison of Some Well‐Established Value at Risk Methods, Uncertainty Comparison Between Value-at-Risk and Expected Shortfall, Bayesian bandwidth estimation for local linear fitting in nonparametric regression models, Quantile Estimation of Regression Models with GARCH-X Errors, A data-driven framework for consistent financial valuation and risk measurement, Improving precipitation forecasts using extreme quantile regression, Econometric modeling of risk measures: a selective review of the recent literature, Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models, The functional \(k\mathrm{NN}\) estimator of the conditional expectile: uniform consistency in number of neighbors

Uses Software

• QRM

Cites Work

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