Tail Index Regression

By Hansheng Wang, Chih-Ling Tsai. 2009

132 citations recorded by the source corpus.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/2f8a79c983b41217b411917329019a7d094348c3

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Citations in the corpus

Modelling Time Series Extremes (2012, methodology): “When covariates are recorded simultaneously with the variable of interest, estimators of the tail index that depend on the covariates have been suggested by Beirlant & Goegebeur (2003), Wang & Tsai (2009) and Gardes et al. (2011).”
Estimation of High Conditional Quantiles for Heavy-Tailed Distributions (2012, methodology): “Results from our approach can provide a guideline for choosing appropriate link functions for the tail index regression (TIR) such as in Wang and Tsai (2009).”
Estimation of Extreme Conditional Quantiles Through Power Transformation (2013, methodology): “One class of work models extremes by fitting a fully parametric model, such as generalized extreme value distribution or generalized Pareto distribution (GPD), where the location, shape and scale parameters are allowed to depend on covariates either parametrically or nonparametrically (Davison and R”
Estimation of the conditional tail index using a smoothed local Hill estimator (2014, methodology): “One can cite the works of Wang and Tsai [17], based on a maximum likelihood approach, and Daouia et al.”
Nonparametric regression estimation of conditional tails: the random covariate case (2014, background): “Wang and Tsai [15] considered maximum likelihood estimation within the Hall subclass of the Pareto-type models,[16] where the tail index is related to the covariates through a log link function.”
Non‐parametric Estimation of Extreme Risk Measures from Conditional Heavy‐tailed Distributions (2014, background): “…to the estimation of the RCTM: R̂CTM W a;n.ˇnjx/ D R̂CTMa;n.˛njx/ ˛n ˇn a O n.x/ ; where a is a fixed value, 0 < ˇn < ˛n and O n.x/ is an estimator of the conditional tail index .x/ (Gardes & Girard, 2008; Gardes et al., 2012; Gardes & Stupfler, 2013; Goegebeur & de Wet, 2012; Wang & Tsai, 2009).”