Semi-parametric estimation of multivariate extreme expectiles
From MaRDI portal
Publication:2034472
DOI10.1016/j.jmva.2021.104758zbMath1467.62084OpenAlexW3153065051WikidataQ115162987 ScholiaQ115162987MaRDI QIDQ2034472
Nicholas Beck, Elena Di Bernardino, Mélina Mailhot
Publication date: 22 June 2021
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmva.2021.104758
Estimation in multivariate analysis (62H12) Extreme value theory; extremal stochastic processes (60G70) Statistics of extreme values; tail inference (62G32) Methods of quasi-Newton type (90C53) Large deviations (60F10)
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Making and Evaluating Point Forecasts
- Asymmetric Least Squares Estimation and Testing
- An introduction to recent advances in high/infinite dimensional statistics
- Vector-valued tail value-at-risk and capital allocation
- On multivariate extensions of value-at-risk
- Bivariate lower and upper orthant value-at-risk
- Multivariate extensions of expectiles risk measures
- A directional multivariate value at risk
- Extreme geometric quantiles in a multivariate regular variation framework
- On the limited memory BFGS method for large scale optimization
- Functional nonparametric estimation of conditional extreme quantiles
- A simple general approach to inference about the tail of a distribution
- An estimator of the stable tail dependence function based on the empirical beta copula
- Estimation of conditional extreme risk measures from heavy-tailed elliptical random vectors
- Extreme M-quantiles as risk measures: from \(L^{1}\) to \(L^{p}\) optimization
- Extremes for multivariate expectiles
- Weak convergence and empirical processes. With applications to statistics
- Generalized quantiles as risk measures
- Global convergence of BFGS and PRP methods under a modified weak Wolfe-Powell line search
- Nonparametric estimation of the conditional tail copula
- Impact of dependence on some multivariate risk indicators
- On kernel smoothing for extremal quantile regression
- Design-based estimation for geometric quantiles with application to outlier detection
- Dynamic coherent risk measures
- Bounds for functions of multivariate risks
- On the Global Convergence of the BFGS Method for Nonconvex Unconstrained Optimization Problems
- Coherent Measures of Risk
- COHERENCE AND ELICITABILITY
- Non-parametric Estimation of Tail Dependence
- Almost sure convergence of the Hill estimator
- Estimation of Parameters and Larger Quantiles Based on the k Largest Observations
- Asymptotic Statistics
- Multivariate geometric expectiles
- Estimation of Tail Risk Based on Extreme Expectiles
- A consistent estimator to the orthant-based tail value-at-risk
- On elicitable risk measures
- A Limited Memory Algorithm for Bound Constrained Optimization
- COMONOTONIC MEASURES OF MULTIVARIATE RISKS
- Copulas checker-type approximations: Application to quantiles estimation of sums of dependent random variables
- MULTIVARIATE GEOMETRIC TAIL- AND RANGE-VALUE-AT-RISK
- ASYMPTOTIC EXPANSIONS OF GENERALIZED QUANTILES AND EXPECTILES FOR EXTREME RISKS
- Estimation of the Marginal Expected Shortfall: the Mean When a Related Variable is Extreme
- Plug-in estimation of level sets in a non-compact setting with applications in multivariate risk theory
- A modified BFGS method and its global convergence in nonconvex minimization
This page was built for publication: Semi-parametric estimation of multivariate extreme expectiles