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Theory and Methods

Tail Index Regression

&
Pages 1233-1240 | Received 01 Aug 2008, Published online: 01 Jan 2012

Keep up to date with the latest research on this topic with citation updates for this article.

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Yuya Sasaki & Yulong Wang. (2022) Fixed-k Inference for Conditional Extremal Quantiles. Journal of Business & Economic Statistics 40:2, pages 829-837.
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Rui Li, Chenlei Leng & Jinhong You. (2022) Semiparametric Tail Index Regression. Journal of Business & Economic Statistics 40:1, pages 82-95.
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Deyuan Li & Huixia Judy Wang. (2019) Extreme Quantile Estimation for Autoregressive Models. Journal of Business & Economic Statistics 37:4, pages 661-670.
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Yaolan Ma, Yuexiang Jiang & Wei Huang. (2019) Tail index varying coefficient model. Communications in Statistics - Theory and Methods 48:2, pages 235-256.
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Yuri Goegebeur, Armelle Guillou & Michael Osmann. (2017) A local moment type estimator for an extreme quantile in regression with random covariates. Communications in Statistics - Theory and Methods 46:1, pages 319-343.
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Tong Siu Tung Wong & Wai Keung Li. (2015) Extreme values identification in regression using a peaks-over-threshold approach. Journal of Applied Statistics 42:3, pages 566-576.
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Yuri Goegebeur, Armelle Guillou & Antoine Schorgen. (2014) Nonparametric regression estimation of conditional tails: the random covariate case. Statistics 48:4, pages 732-755.
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Huixia Judy Wang & Deyuan Li. (2013) Estimation of Extreme Conditional Quantiles Through Power Transformation. Journal of the American Statistical Association 108:503, pages 1062-1074.
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Huixia Judy Wang, Deyuan Li & Xuming He. (2012) Estimation of High Conditional Quantiles for Heavy-Tailed Distributions. Journal of the American Statistical Association 107:500, pages 1453-1464.
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Yuri Goegebeur & Tertius De Wet. (2012) Local Estimation of the Second-Order Parameter in Extreme Value Statistics and Local Unbiased Estimation of the Tail Index. Communications in Statistics - Theory and Methods 41:19, pages 3575-3607.
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Jasper Velthoen, Clément Dombry, Juan-Juan Cai & Sebastian Engelke. (2023) Gradient boosting for extreme quantile regression. Extremes 26:4, pages 639-667.
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João Nicolau, Paulo M.M. Rodrigues & Marian Z. Stoykov. (2023) Tail index estimation in the presence of covariates: Stock returns’ tail risk dynamics. Journal of Econometrics 235:2, pages 2266-2284.
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João Nicolau, Pedro Raposo & Paulo M. M. Rodrigues. (2022) Measuring wage inequality under right censoring. Economic Inquiry 61:2, pages 377-401.
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Arthur Maillart & Christian Y. Robert. (2023) Tail index partition-based rules extraction with application to tornado damage insurance. ASTIN Bulletin, pages 1-27.
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Fengyang He, Huixia Judy Wang & Yuejin Zhou. (2022) Extremal quantile autoregression for heavy-tailed time series. Computational Statistics & Data Analysis 176, pages 107563.
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Miguel de Carvalho, Alina Kumukova & Gonçalo dos Reis. (2022) Regression-type analysis for multivariate extreme values. Extremes 25:4, pages 595-622.
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Ikjin Lee, Ungki Lee, Palaniappan Ramu, Deepanshu Yadav, Gamze Bayrak & Erdem Acar. (2022) Small failure probability: principles, progress and perspectives. Structural and Multidisciplinary Optimization 65:11.
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Kumushoy Abduraimova. (2022) Contagion and tail risk in complex financial networks. Journal of Banking & Finance 143, pages 106560.
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Léo R. Belzile & Anthony C. Davison. (2022) Improved inference on risk measures for univariate extremes. The Annals of Applied Statistics 16:3.
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Hengxin Cui, Ken Seng Tan, Fan Yang & Chen Zhou. (2022) Asymptotic analysis of portfolio diversification. Insurance: Mathematics and Economics 106, pages 302-325.
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M. de Carvalho, S. Pereira, P. Pereira & P. de Zea Bermudez. (2021) An Extreme Value Bayesian Lasso for the Conditional Left and Right Tails. Journal of Agricultural, Biological and Environmental Statistics 27:2, pages 222-239.
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Yaolan Ma & Bo Wei. (2022) Efficient estimation of partially linear tail index models using B‐splines. Australian & New Zealand Journal of Statistics 64:1, pages 27-44.
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Jiaxi Wang, Yanxi Hou, Xingchi Li & Tiandong Wang. (2022) EVIboost for the Estimation of Extreme Value Index Under Heterogeneous Extremes. Journal of Data Science, pages 1-20.
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Jie Hu, Yu Chen & Keqi Tan. (2021) ESTIMATION OF HIGH CONDITIONAL TAIL RISK BASED ON EXPECTILE REGRESSION. ASTIN Bulletin 51:2, pages 539-570.
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Wuyi Ye, Kunliang Jiang & Xiaoquan Liu. (2021) Financial contagion and the TIR-MIDAS model. Finance Research Letters 39, pages 101589.
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Goedele Dierckx, Yuri Goegebeur & Armelle Guillou. (2019) Local Robust Estimation of Pareto-Type Tails with Random Right Censoring. Sankhya A 83:1, pages 70-108.
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L. Mhalla, M. Carvalho & V. Chavez‐Demoulin. (2019) Regression‐type models for extremal dependence. Scandinavian Journal of Statistics 46:4, pages 1141-1167.
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Yuri Goegebeur, Armelle Guillou & Jing Qin. (2019) Bias-corrected estimation for conditional Pareto-type distributions with random right censoring. Extremes 22:3, pages 459-498.
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Yaolan Ma, Yuexiang Jiang & Wei Huang. (2018) Empirical likelihood based inference for conditional Pareto-type tail index. Statistics & Probability Letters 134, pages 114-121.
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Laurent Gardes. (2017) Tail dimension reduction for extreme quantile estimation. Extremes 21:1, pages 57-95.
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Paul Kinsvater & Roland Fried. (2016) Conditional heavy-tail behavior with applications to precipitation and river flow extremes. Stochastic Environmental Research and Risk Assessment 31:5, pages 1155-1169.
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Tertius de Wet, Yuri Goegebeur, Armelle Guillou & Michael Osmann. (2015) Kernel regression with Weibull-type tails. Annals of the Institute of Statistical Mathematics 68:5, pages 1135-1162.
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Gilles Stupfler. (2016) Estimating the conditional extreme-value index under random right-censoring. Journal of Multivariate Analysis 144, pages 1-24.
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Laurent Gardes. (2015) A general estimator for the extreme value index: applications to conditional and heteroscedastic extremes. Extremes 18:3, pages 479-510.
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Yuri Goegebeur, Armelle Guillou & Gilles Stupfler. (2015) Uniform asymptotic properties of a nonparametric regression estimator of conditional tails. Annales de l'Institut Henri Poincaré, Probabilités et Statistiques 51:3.
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Luke B. SmithBrian J. ReichAmy H. HerringPeter H. LangloisMontserrat Fuentes. (2015) Multilevel quantile function modeling with application to birth outcomes. Biometrics 71:2, pages 508-519.
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Yuri Goegebeur, Armelle Guillou & Théo Rietsch. (2014) Robust conditional Weibull-type estimation. Annals of the Institute of Statistical Mathematics 67:3, pages 479-514.
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Jonathan El Methni, Laurent Gardes & Stéphane Girard. (2014) Non-parametric Estimation of Extreme Risk Measures from Conditional Heavy-tailed Distributions. Scandinavian Journal of Statistics 41:4, pages 988-1012.
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Enrico Biffis & Erik Chavez. (2014) Tail Risk in Commercial Property Insurance. Risks 2:4, pages 393-410.
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Yuri Goegebeur, Armelle Guillou & Michael Osmann. (2014) A local moment type estimator for the extreme value index in regression with random covariates. Canadian Journal of Statistics 42:3, pages 487-507.
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Goedele Dierckx, Yuri Goegebeur & Armelle Guillou. (2014) Local robust and asymptotically unbiased estimation of conditional Pareto-type tails. TEST 23:2, pages 330-355.
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Laurent Gardes & Gilles Stupfler. (2013) Estimation of the conditional tail index using a smoothed local Hill estimator. Extremes 17:1, pages 45-75.
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Qingzhao Zhang, Deyuan Li & Hansheng Wang. (2013) A note on tail dependence regression. Journal of Multivariate Analysis 120, pages 163-172.
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Gilles Stupfler. (2013) A moment estimator for the conditional extreme-value index. Electronic Journal of Statistics 7:none.
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John H. J. Einmahl, Fan Yang & Chen Zhou. (2018) Testing the Multivariate Regular Variation Model. SSRN Electronic Journal.
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Enrico Biffis & Erik Chavez. (2014) Tail Risk in Commercial Property Insurance. SSRN Electronic Journal.
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