Nonlinear expectile regression with application to value-at-risk and expected shortfall estimation

DOI10.1016/J.CSDA.2015.07.011zbMath1468.62101OpenAlexW1193828462MaRDI QIDQ1660129

Sangyeol Lee, Minjo Kim

Publication date: 15 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2015.07.011

zbMATH Keywords

consistencyasymptotic normalityvalue-at-riskexpected shortfallexpectile regressionasymmetric least squares regression

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05) Applications of statistics to actuarial sciences and financial mathematics (62P05)

Related Items (22)

Monitoring parameter change for time series models with application to location-Scale heteroscedastic models ⋮ Robust estimation and shrinkage in ultrahigh dimensional expectile regression with heavy tails and variance heterogeneity ⋮ On expectile-assisted inverse regression estimation for sufficient dimension reduction ⋮ A new GEE method to account for heteroscedasticity using asymmetric least-square regressions ⋮ Test for conditional quantile change in GARCH models ⋮ A continuous threshold expectile model ⋮ A class of distortion measures generated from expectile and its estimation ⋮ Risk measurement for conditionally heteroscedastic location-scale time series models with ASTD and AEPD innovations ⋮ Data-driven and distribution-free estimation of tailed-related risks for GARCH models using composite asymmetric least squares regression ⋮ Asymmetric influence measure for high dimensional regression ⋮ On entropy-based goodness-of-fit test for asymmetric Student-t and exponential power distributions ⋮ Conditional quantile change test for time series based on support vector regression ⋮ Parametric expectile regression and its application for premium calculation ⋮ Expectile trace regression via low-rank and group sparsity regularization ⋮ Test for conditional quantile change in general conditional heteroscedastic time series models ⋮ Data driven value-at-risk forecasting using a SVR-GARCH-KDE hybrid ⋮ Learning rates for kernel-based expectile regression ⋮ On entropy goodness-of-fit test based on integrated distribution function ⋮ Bootstrap entropy test for general location-scale time series models with heteroscedasticity ⋮ Test for tail index constancy of GARCH innovations based on conditional volatility ⋮ Dynamic large financial networks \textit{via} conditional expected shortfalls ⋮ An elastic-net penalized expectile regression with applications

Uses Software

• CAViaR
• QRM

Cites Work

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• Asymmetric Least Squares Estimation and Testing
• Quasi-maximum-likelihood estimation in conditionally heteroscedastic time series: a stochastic recurrence equations approach
• Generalized method of moments specification testing
• Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes
• Coherent Measures of Risk
• Stability of nonlinear AR-GARCH models
• On the Estimation of Production Frontiers: Maximum Likelihood Estimation of the Parameters of a Discontinuous Density Function
• Bayesian Forecasting for Financial Risk Management, Pre and Post the Global Financial Crisis
• Regression Analysis when the Dependent Variable Is Truncated Normal
• MIXING AND MOMENT PROPERTIES OF VARIOUS GARCH AND STOCHASTIC VOLATILITY MODELS
• Quantile Regression Estimator for GARCH Models

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