Maximum Empirical Likelihood Estimation of the Spectral Measure of an Extreme Value Distribution
Author
Abstract
Suggested Citation
Download full text from publisher
Other versions of this item:
- Einmahl, J.H.J. & Segers, J.J.J., 2009. "Maximum empirical likelihood estimation of the spectral measure of an extreme-value distribution," Other publications TiSEM ffef2e15-c4a8-471f-b730-1, Tilburg University, School of Economics and Management.
- Einmahl, J.H.J. & Segers, J.J.J., 2008. "Maximum Empirical Likelihood Estimation of the Spectral Measure of an Extreme Value Distribution," Other publications TiSEM e9340b9a-fe69-4e77-8594-8, Tilburg University, School of Economics and Management.
References listed on IDEAS
- Einmahl, J.H.J. & Krajina, A. & Segers, J.J.J., 2007.
"A Method of Moments Estimator of Tail Dependence,"
Other publications TiSEM
6ee60ab8-3c01-4bd9-aa5e-7, Tilburg University, School of Economics and Management.
- Einmahl, J.H.J. & Krajina, A. & Segers, J.J.J., 2007. "A Method of Moments Estimator of Tail Dependence," Discussion Paper 2007-80, Tilburg University, Center for Economic Research.
- Einmahl, J.H.J. & Krajina, A. & Segers, J.J.J., 2008. "A method of moments estimator of tail dependence," Other publications TiSEM 448fd556-b3e0-4fb0-bcb7-8, Tilburg University, School of Economics and Management.
- Drees, Holger & Huang, Xin, 1998. "Best Attainable Rates of Convergence for Estimators of the Stable Tail Dependence Function," Journal of Multivariate Analysis, Elsevier, vol. 64(1), pages 25-47, January.
- Einmahl, John H.J. & de Haan, Laurens & Sinha, Ashoke Kumar, 1997.
"Estimating the spectral measure of an extreme value distribution,"
Stochastic Processes and their Applications, Elsevier, vol. 70(2), pages 143-171, October.
- J Einmahl, .H. & de Haan, L. & Sinha, A., 1997. "Estimating the spectral measure of an extreme value distribution," Other publications TiSEM ac22e123-1e5d-448a-981e-a, Tilburg University, School of Economics and Management.
- Einmahl, John H. J., 1997.
"Poisson and Gaussian approximation of weighted local empirical processes,"
Stochastic Processes and their Applications, Elsevier, vol. 70(1), pages 31-58, October.
- Einmahl, J.H.J., 1997. "Poisson and Gaussian approximation of weighted local empirical processes," Other publications TiSEM 07d934b9-2bd4-474a-bf32-f, Tilburg University, School of Economics and Management.
- Einmahl, J.H.J. & de Haan, L.F.M. & Piterbarg, V.I., 2001. "Nonparametric estimation of the spectral measure of an extreme value distribution," Other publications TiSEM c3485b9b-a0bd-456f-9baa-0, Tilburg University, School of Economics and Management.
- de Haan, Laurens & Neves, Cláudia & Peng, Liang, 2008. "Parametric tail copula estimation and model testing," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1260-1275, July.
- Edward Frees & Emiliano Valdez, 1998. "Understanding Relationships Using Copulas," North American Actuarial Journal, Taylor & Francis Journals, vol. 2(1), pages 1-25.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Holger Drees, 2012. "Extreme value analysis of actuarial risks: estimation and model validation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(2), pages 225-264, June.
- Gudendorf, Gordon & Segers, Johan, 2011. "Nonparametric estimation of an extreme-value copula in arbitrary dimensions," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 37-47, January.
- Deyuan Li & Liang Peng & Yongcheng Qi, 2011. "Empirical likelihood confidence intervals for the endpoint of a distribution function," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(2), pages 353-366, August.
- Lehtomaa, Jaakko & Resnick, Sidney I., 2020. "Asymptotic independence and support detection techniques for heavy-tailed multivariate data," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 262-277.
- Sabourin, Anne & Naveau, Philippe, 2014. "Bayesian Dirichlet mixture model for multivariate extremes: A re-parametrization," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 542-567.
- Khader Khadraoui & Pierre Ribereau, 2019. "Bayesian Inference with M-splines on Spectral Measure of Bivariate Extremes," Methodology and Computing in Applied Probability, Springer, vol. 21(3), pages 765-788, September.
- Padoan, Simone A., 2011. "Multivariate extreme models based on underlying skew-t and skew-normal distributions," Journal of Multivariate Analysis, Elsevier, vol. 102(5), pages 977-991, May.
- Sabourin, Anne, 2015. "Semi-parametric modeling of excesses above high multivariate thresholds with censored data," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 126-146.
- de Carvalho, Miguel & Oumow, Boris & Segers, Johan & WarchoÅ‚, MichaÅ‚, 2012. "A Euclidean likelihood estimator for bivariate tail dependence," LIDAM Discussion Papers ISBA 2012013, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Cui, Hengxin & Tan, Ken Seng & Yang, Fan & Zhou, Chen, 2022. "Asymptotic analysis of portfolio diversification," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 302-325.
- Goix, Nicolas & Sabourin, Anne & Clémençon, Stephan, 2017. "Sparse representation of multivariate extremes with applications to anomaly detection," Journal of Multivariate Analysis, Elsevier, vol. 161(C), pages 12-31.
- Einmahl, J.H.J. & de Haan, L.F.M. & Krajina, A., 2009.
"Estimating Extreme Bivariate Quantile Regions,"
Discussion Paper
2009-29, Tilburg University, Center for Economic Research.
- Einmahl, J.H.J. & de Haan, L.F.M. & Krajina, A., 2009. "Estimating Extreme Bivariate Quantile Regions," Other publications TiSEM 007ce0a9-dd94-4301-ad62-1, Tilburg University, School of Economics and Management.
- M. Ghil & Pascal Yiou & Stéphane Hallegatte & B. D. Malamud & P. Naveau & A. Soloviev & P. Friederichs & V. Keilis-Borok & D. Kondrashov & V. Kossobokov & O. Mestre & C. Nicolis & H. W. Rust & P. Sheb, 2011. "Extreme events: dynamics, statistics and prediction," Post-Print hal-00716514, HAL.
- Shi, Xiaojun & Tang, Qihe & Yuan, Zhongyi, 2017. "A limit distribution of credit portfolio losses with low default probabilities," Insurance: Mathematics and Economics, Elsevier, vol. 73(C), pages 156-167.
- Hu, Shuang & Peng, Zuoxiang & Segers, Johan, 2022. "Modelling multivariate extreme value distributions via Markov trees," LIDAM Discussion Papers ISBA 2022021, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Bücher, Axel & Volgushev, Stanislav & Zou, Nan, 2019. "On second order conditions in the multivariate block maxima and peak over threshold method," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 604-619.
- Kiriliouk, Anna & Segers, Johan & Warchol, Michal, 2014. "Nonparametric estimation of extremal dependence," LIDAM Discussion Papers ISBA 2014044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Einmahl, J.H.J. & Krajina, A. & Segers, J., 2011.
"An M-Estimator for Tail Dependence in Arbitrary Dimensions,"
Discussion Paper
2011-013, Tilburg University, Center for Economic Research.
- Einmahl, John H. J. & Krajina, Andrea & Segers, Johan, 2012. "An M-estimator for tail dependence in arbitrary dimensions," LIDAM Reprints ISBA 2012035, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Einmahl, J.H.J. & Krajina, A. & Segers, J., 2012. "An M-estimator for tail dependence in arbitrary dimensions," Other publications TiSEM 7d447c58-3e8f-4387-b36b-e, Tilburg University, School of Economics and Management.
- EINMAHL, John H.J. & KRAJINA, Andrea & Segers, Johan, 2011. "An M-Estimator For Tail Dependence In Arbitrary Dimensions," LIDAM Discussion Papers ISBA 2011005, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Einmahl, J.H.J. & Krajina, A. & Segers, J., 2011. "An M-Estimator for Tail Dependence in Arbitrary Dimensions," Other publications TiSEM 27508aa0-9825-4d9e-b1f4-1, Tilburg University, School of Economics and Management.
- Krajina, A., 2010. "An M-estimator of multivariate tail dependence," Other publications TiSEM 66518e07-db9a-4446-81be-c, Tilburg University, School of Economics and Management.
- Einmahl, J.H.J. & de Haan, L.F.M. & Piterbarg, V.I., 2001. "Nonparametric estimation of the spectral measure of an extreme value distribution," Other publications TiSEM c3485b9b-a0bd-456f-9baa-0, Tilburg University, School of Economics and Management.
- Di Bernardino, Elena & Maume-Deschamps, Véronique & Prieur, Clémentine, 2013. "Estimating a bivariate tail: A copula based approach," Journal of Multivariate Analysis, Elsevier, vol. 119(C), pages 81-100.
- Kiriliouk, Anna & Lee, Jeongjin & Segers, Johan, 2023. "X-Vine Models for Multivariate Extremes," LIDAM Discussion Papers ISBA 2023038, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Khader Khadraoui & Pierre Ribereau, 2019. "Bayesian Inference with M-splines on Spectral Measure of Bivariate Extremes," Methodology and Computing in Applied Probability, Springer, vol. 21(3), pages 765-788, September.
- Bücher Axel, 2014. "A note on nonparametric estimation of bivariate tail dependence," Statistics & Risk Modeling, De Gruyter, vol. 31(2), pages 151-162, June.
- Hu, Shuang & Peng, Zuoxiang & Segers, Johan, 2022. "Modelling multivariate extreme value distributions via Markov trees," LIDAM Discussion Papers ISBA 2022021, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Zhang, Dabao & Wells, Martin T. & Peng, Liang, 2008. "Nonparametric estimation of the dependence function for a multivariate extreme value distribution," Journal of Multivariate Analysis, Elsevier, vol. 99(4), pages 577-588, April.
- Estate Khmaladze & Wolfgang Weil, 2008. "Local empirical processes near boundaries of convex bodies," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(4), pages 813-842, December.
- John H. J. Einmahl & Anna Kiriliouk & Andrea Krajina & Johan Segers, 2016.
"An M-estimator of spatial tail dependence,"
Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 275-298, January.
- Einmahl, J.H.J. & Kiriliouk, A. & Krajina, A. & Segers, J., 2014. "An M-estimator of Spatial Tail Dependence," Other publications TiSEM 2d5c1a3b-a5f6-4329-8df2-f, Tilburg University, School of Economics and Management.
- Einmahl, John & Kiriliouk, Anna & Krajina, Andrea & Segers, Johan, 2016. "An M-estimator of spatial tail dependence," LIDAM Reprints ISBA 2016004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Einmahl, J.H.J. & Kiriliouk, A. & Krajina, A. & Segers, J., 2014. "An M-estimator of Spatial Tail Dependence," Discussion Paper 2014-021, Tilburg University, Center for Economic Research.
- Einmahl, John & Kiriliouk, Anna & Krajina, Andrea & Segers, Johan, 2014. "An M-estimator of spatial tail dependence," LIDAM Discussion Papers ISBA 2014008, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Carsten Bormann & Julia Schaumburg & Melanie Schienle, 2016.
"Beyond Dimension two: A Test for Higher-Order Tail Risk,"
Journal of Financial Econometrics, Oxford University Press, vol. 14(3), pages 552-580.
- Bormann, Carsten & Schienle, Melanie & Schaumburg, Julia, 2014. "Beyond dimension two: A test for higher-order tail risk," SFB 649 Discussion Papers 2014-042, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Bormann, Carsten & Schaumburg, Julia & Schienle, Melanie, 2016. "Beyond dimension two: A test for higher-order tail risk," Working Paper Series in Economics 80, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
- Einmahl, J.H.J. & Khmaladze, E.V., 2007.
"Central Limit Theorems For Local Emprical Processes Near Boundaries of Sets,"
Discussion Paper
2007-66, Tilburg University, Center for Economic Research.
- Einmahl, J.H.J. & Khmaladze, E.V., 2007. "Central Limit Theorems For Local Emprical Processes Near Boundaries of Sets," Other publications TiSEM c4c26f2d-99d3-473f-9900-e, Tilburg University, School of Economics and Management.
- Michael Falk & Gilles Stupfler, 2021. "The Min-characteristic Function: Characterizing Distributions by Their Min-linear Projections," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 254-282, February.
- Einmahl, J.H.J. & de Haan, L.F.M. & Li, D., 2004.
"Weighted Approximations of Tail Copula Processes with Application to Testing the Multivariate Extreme Value Condition,"
Other publications TiSEM
0b2c1bfa-d609-494a-8929-8, Tilburg University, School of Economics and Management.
- Einmahl, J.H.J. & de Haan, L.F.M. & Li, D., 2004. "Weighted Approximations of Tail Copula Processes with Application to Testing the Multivariate Extreme Value Condition," Discussion Paper 2004-71, Tilburg University, Center for Economic Research.
- Mikael Escobar-Bach & Yuri Goegebeur & Armelle Guillou & Alexandre You, 2017. "Bias-corrected and robust estimation of the bivariate stable tail dependence function," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 284-307, June.
- Georg Mainik & Ludger Rüschendorf, 2010. "On optimal portfolio diversification with respect to extreme risks," Finance and Stochastics, Springer, vol. 14(4), pages 593-623, December.
- Lehtomaa, Jaakko & Resnick, Sidney I., 2020. "Asymptotic independence and support detection techniques for heavy-tailed multivariate data," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 262-277.
- Einmahl, J.H.J. & de Haan, L.F.M. & Li, D., 2006. "Weighted approximations of tail copula processes with applications to testing the bivariate extreme value condition," Other publications TiSEM 18b65ac3-ba79-4bff-ad53-2, Tilburg University, School of Economics and Management.
- Goix, Nicolas & Sabourin, Anne & Clémençon, Stephan, 2017. "Sparse representation of multivariate extremes with applications to anomaly detection," Journal of Multivariate Analysis, Elsevier, vol. 161(C), pages 12-31.
More about this item
Keywords
functional central limit theorem; local empirical process; moment constraint; multivariate extremes; nonparametric maximum likelihood estimator; tail dependence;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tiu:tiucen:e9340b9a-fe69-4e77-8594-88794967cb15. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Richard Broekman (email available below). General contact details of provider: http://center.uvt.nl .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.