Bayesian CV@R/super-quantile regression

DOI10.1080/02664763.2018.1450363OpenAlexW2794003188MaRDI QIDQ5036539

Mike G. Tsionas, Marwan Izzeldin

Publication date: 23 February 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://eprints.lancs.ac.uk/id/eprint/124204/1/SuperQuantile_Regression.pdf

zbMATH Keywords

Bayesian analysisrisk measuresparticle filteringCV@Rsuper-quantile regression

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• CAViaR

Cites Work

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• Nonparametric estimation of conditional VaR and expected shortfall
• Asymptotically efficient estimation of the conditional expected shortfall
• Superquantile regression with applications to buffered reliability, uncertainty quantification, and conditional value-at-risk
• Central limit theorem for sequential Monte Carlo methods and its application to Bayesian inference
• Following a Moving Target—Monte Carlo Inference for Dynamic Bayesian Models
• Conditional Value-at-Risk and Average Value-at-Risk: Estimation and Asymptotics
• Risk Tuning with Generalized Linear Regression
• On estimating the conditional expected shortfall
• The Bayesian Lasso
• Asymptotic consistency of risk functionals
• Regression Quantiles
• Bayesian quantile inference
• A sequential particle filter method for static models
• Nonparametric Estimation and Sensitivity Analysis of Expected Shortfall
• Adaptive Sequential Posterior Simulators for Massively Parallel Computing Environments
• Gibbs sampling methods for Bayesian quantile regression

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