Zobrazeno 1 - 10
of 176
pro vyhledávání: '"Yuri Goegebeur"'
Autor:
Lazar, Nicole A.
Publikováno v:
Technometrics, 2005 Aug 01. 47(3), 376-377.
Externí odkaz:
https://www.jstor.org/stable/25471041
Extreme-value based estimation of the conditional tail moment with application to reinsurance rating
Publikováno v:
Insurance: Mathematics and Economics. 107:102-122
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4907cdc926a2f58034b14e456d88ad8f
https://doi.org/10.1016/j.insmatheco.2022.08.003
https://doi.org/10.1016/j.insmatheco.2022.08.003
Several risk measures have been proposed in the literature, among them the marginal mean excess, defined as MME_p = \mathbb E[(Y^{(1)}-Q_1(1-p))_+|Y^{(2)}> Q_{2}(1-p)], provided \mathbb E|Y^{(1)}|< \infty, where (Y^{(1)}, Y^{(2)}) denotes a pair of r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43379e6713678e960fe23d1ce9170dee
https://hal.archives-ouvertes.fr/hal-03271590
https://hal.archives-ouvertes.fr/hal-03271590
Publikováno v:
Dierckx, G, Goegebeur, Y & Guillou, A 2021, ' Local Robust Estimation of Pareto-Type Tails with Random Right Censoring ', Sankhya A, vol. 83, no. 1, pp. 70-108 . https://doi.org/10.1007/s13171-019-00169-0
Sankhya A
Sankhya A, Springer Verlag, 2021, 83, pp.70-108. ⟨10.1007/s13171-019-00169-0⟩
Sankhya A
Sankhya A, Springer Verlag, 2021, 83, pp.70-108. ⟨10.1007/s13171-019-00169-0⟩
We propose a nonparametric robust estimator for the tail index of a conditional Pareto-type distribution in the presence of censoring and random covariates. The censored distribution is also of Pareto-type and the index is estimated locally within a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ba0438e32b1078672b113488ba854df0
https://doi.org/10.1007/s13171-019-00169-0
https://doi.org/10.1007/s13171-019-00169-0
Publikováno v:
Econometrics and Statistics
Econometrics and Statistics, Elsevier, In press, ⟨10.1016/j.ecosta.2021.09.006⟩
Econometrics and Statistics, Elsevier, In press, ⟨10.1016/j.ecosta.2021.09.006⟩
The marginal expected shortfall is an important risk measure in finance, which has been extended recently to the case where the random variables of main interest (Y^{(1)}, Y^{(2)}) are observed together with a covariate X\in \mathbb R^d. This leads t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f49c75fefbb4974f5d3cc634b54fcef
https://hal.archives-ouvertes.fr/hal-02613135v3/document
https://hal.archives-ouvertes.fr/hal-02613135v3/document
We propose a robust estimator of the stable tail dependence function in the case where random covariates are recorded. Under suitable assumptions, we derive the finite dimensional weak convergence of the estimator properly normalized. The performance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe5201c0990ce6bda277169659a1d277
https://hal.archives-ouvertes.fr/hal-03132477/document
https://hal.archives-ouvertes.fr/hal-03132477/document
Publikováno v:
Extremes
Extremes, Springer Verlag (Germany), 2021, 24, pp.797-847. ⟨10.1007/s10687-020-00403-1⟩
Goegebeur, Y, Guillou, A, Le Ho, N K & Qin, J 2021, ' Conditional marginal expected shortfall ', Extremes, vol. 24, no. 4, pp. 797-847 . https://doi.org/10.1007/s10687-020-00403-1
Extremes, Springer Verlag (Germany), 2021, 24, pp.797-847. ⟨10.1007/s10687-020-00403-1⟩
Goegebeur, Y, Guillou, A, Le Ho, N K & Qin, J 2021, ' Conditional marginal expected shortfall ', Extremes, vol. 24, no. 4, pp. 797-847 . https://doi.org/10.1007/s10687-020-00403-1
In the context of bivariate random variables $\left (Y^{(1)},Y^{(2)}\right )$ , the marginal expected shortfall, defined as $\mathbb {E}\left (Y^{(1)}|Y^{(2)} \ge Q_{2}(1-p)\right )$ for p small, where Q2 denotes the quantile function of Y(2), is an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a2998abd38f34ac15b55874eed3bb685
https://hal.archives-ouvertes.fr/hal-02272392v4/file/ims-condmes-v4-Hal.pdf
https://hal.archives-ouvertes.fr/hal-02272392v4/file/ims-condmes-v4-Hal.pdf
Publikováno v:
Insurance: Mathematics and Economics
Insurance: Mathematics and Economics, Elsevier, 2021, 96, pp.68-80. ⟨10.1016/j.insmatheco.2020.10.010⟩
Goegebeur, Y, Guillou, A & Qin, J 2021, ' Extreme value estimation of the conditional risk premium in reinsurance ', Insurance: Mathematics and Economics, vol. 96, pp. 68-80 . https://doi.org/10.1016/j.insmatheco.2020.10.010
Insurance: Mathematics and Economics, Elsevier, 2021, 96, pp.68-80. ⟨10.1016/j.insmatheco.2020.10.010⟩
Goegebeur, Y, Guillou, A & Qin, J 2021, ' Extreme value estimation of the conditional risk premium in reinsurance ', Insurance: Mathematics and Economics, vol. 96, pp. 68-80 . https://doi.org/10.1016/j.insmatheco.2020.10.010
International audience; In the paper we study the estimation of reinsurance premiums when the claim size is observed together with additional information in the form of random covariates. Using extreme value arguments, we propose an estimator for the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed31389bf0ac1e8d1900fb2a18476f56
https://hal.archives-ouvertes.fr/hal-02614153
https://hal.archives-ouvertes.fr/hal-02614153
Publikováno v:
Goegebeur, Y, Guillou, A, Ho, N K L & Qin, J 2020, ' Robust nonparametric estimation of the conditional tail dependence coefficient ', Journal of Multivariate Analysis, vol. 178, 104607 . https://doi.org/10.1016/j.jmva.2020.104607
Journal of Multivariate Analysis
Journal of Multivariate Analysis, Elsevier, 2020, 178, ⟨10.1016/j.jmva.2020.104607⟩
Journal of Multivariate Analysis
Journal of Multivariate Analysis, Elsevier, 2020, 178, ⟨10.1016/j.jmva.2020.104607⟩
International audience; We consider robust and nonparametric estimation of the coefficient of tail dependence in presence of random covariates. The estimator is obtained by fitting the extended Pareto distribution locally to properly transformed biva
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a1bd89f25c038003949a73bba12b2d3
https://portal.findresearcher.sdu.dk/da/publications/c880ae76-82ea-4a41-b08d-ac611e0402a7
https://portal.findresearcher.sdu.dk/da/publications/c880ae76-82ea-4a41-b08d-ac611e0402a7
Publikováno v:
Scandinavian Journal of Statistics
Scandinavian Journal of Statistics, Wiley, 2018, 45, pp.590-617. ⟨10.1111/sjos.12315⟩
Escobar-Bach, M, Goegebeur, Y & Guillou, A 2018, ' Local estimation of the conditional stable tail dependence function ', Scandinavian Journal of Statistics, vol. 45, no. 3, pp. 590-617 . https://doi.org/10.1111/sjos.12315
Scandinavian Journal of Statistics, Wiley, 2018, 45, pp.590-617. ⟨10.1111/sjos.12315⟩
Escobar-Bach, M, Goegebeur, Y & Guillou, A 2018, ' Local estimation of the conditional stable tail dependence function ', Scandinavian Journal of Statistics, vol. 45, no. 3, pp. 590-617 . https://doi.org/10.1111/sjos.12315
We consider the local estimation of the stable tail dependence function when a random covariate is observed together with the variables of main interest. Our estimator is a weighted version of the empirical estimator adapted to the covariate framewor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::78ebd275efd8a265bb489d5e9f583b52
https://doi.org/10.1111/sjos.12315
https://doi.org/10.1111/sjos.12315