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Copula convergence theorems for tail events

Citations

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Cited by:

  1. 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.
  2. Takaaki Koike & Marius Hofert, 2019. "Markov Chain Monte Carlo Methods for Estimating Systemic Risk Allocations," Papers 1909.11794, arXiv.org, revised May 2020.
  3. Hato Schmeiser & Caroline Siegel & Joël Wagner, 2012. "The risk of model misspecification and its impact on solvency measurement in the insurance sector," Journal of Risk Finance, Emerald Group Publishing, vol. 13(4), pages 285-308, August.
  4. Alexandru V. Asimit & Raluca Vernic & Riċardas Zitikis, 2013. "Evaluating Risk Measures and Capital Allocations Based on Multi-Losses Driven by a Heavy-Tailed Background Risk: The Multivariate Pareto-II Model," Risks, MDPI, vol. 1(1), pages 1-20, March.
  5. Guoxiang Xu & Wangfeng Gao, 2019. "Financial Risk Contagion in Stock Markets: Causality and Measurement Aspects," Sustainability, MDPI, vol. 11(5), pages 1-20, March.
  6. Pei-song Mu & Xun-gang Zheng, 2010. "Research on the Tail Dependence of Agriculture Listed Companies," Journal of Agricultural Science, Canadian Center of Science and Education, vol. 2(2), pages 111-111, May.
  7. Bolancé, Catalina & Bahraoui, Zuhair & Artís, Manuel, 2014. "Quantifying the risk using copulae with nonparametric marginals," Insurance: Mathematics and Economics, Elsevier, vol. 58(C), pages 46-56.
  8. repec:hal:wpaper:hal-00834000 is not listed on IDEAS
  9. Jaworski, Piotr, 2015. "Univariate conditioning of vine copulas," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 89-103.
  10. Alink, Stan & Lowe, Matthias & V. Wuthrich, Mario, 2004. "Diversification of aggregate dependent risks," Insurance: Mathematics and Economics, Elsevier, vol. 35(1), pages 77-95, August.
  11. Hashorva, Enkelejd & Jaworski, Piotr, 2012. "Gaussian approximation of conditional elliptical copulas," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 397-407.
  12. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
  13. Durante, Fabrizio & Foschi, Rachele & Spizzichino, Fabio, 2008. "Threshold copulas and positive dependence," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2902-2909, December.
  14. Claudia Klüppelberg & Gabriel Kuhn & Liang Peng, 2008. "Semi‐Parametric Models for the Multivariate Tail Dependence Function – the Asymptotically Dependent Case," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(4), pages 701-718, December.
  15. repec:mth:ijafr8:v:9:y:2019:i:1:p:414-431 is not listed on IDEAS
  16. Takaaki Koike & Marius Hofert, 2020. "Markov Chain Monte Carlo Methods for Estimating Systemic Risk Allocations," Risks, MDPI, vol. 8(1), pages 1-33, January.
  17. Matthieu Garcin & Maxime L. D. Nicolas, 2024. "Nonparametric estimator of the tail dependence coefficient: balancing bias and variance," Statistical Papers, Springer, vol. 65(8), pages 4875-4913, October.
  18. Paul Embrechts, 2009. "Copulas: A Personal View," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 639-650, September.
  19. Jaworski Piotr, 2017. "On Truncation Invariant Copulas and their Estimation," Dependence Modeling, De Gruyter, vol. 5(1), pages 133-144, January.
  20. Kellner, Ralf & Gatzert, Nadine, 2013. "Estimating the basis risk of index-linked hedging strategies using multivariate extreme value theory," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4353-4367.
  21. Martin Eling & Denis Toplek, 2009. "Modeling and Management of Nonlinear Dependencies–Copulas in Dynamic Financial Analysis," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 651-681, September.
  22. Han, Shuang & Qiao, Yan-hui & Yan, Jie & Liu, Yong-qian & Li, Li & Wang, Zheng, 2019. "Mid-to-long term wind and photovoltaic power generation prediction based on copula function and long short term memory network," Applied Energy, Elsevier, vol. 239(C), pages 181-191.
  23. Di Bernardino Elena & Rullière Didier, 2013. "On certain transformations of Archimedean copulas: Application to the non-parametric estimation of their generators," Dependence Modeling, De Gruyter, vol. 1(2013), pages 1-36, October.
  24. Beare, Brendan K., 2012. "Archimedean Copulas And Temporal Dependence," Econometric Theory, Cambridge University Press, vol. 28(6), pages 1165-1185, December.
  25. Frahm, Gabriel & Junker, Markus & Schmidt, Rafael, 2005. "Estimating the tail-dependence coefficient: Properties and pitfalls," Insurance: Mathematics and Economics, Elsevier, vol. 37(1), pages 80-100, August.
  26. Charpentier, Arthur & Segers, Johan, 2008. "Convergence of Archimedean copulas," Statistics & Probability Letters, Elsevier, vol. 78(4), pages 412-419, March.
  27. Gonzalo, Jesús & Olmo, José, 2007. "The impact of heavy tails and comovements in downside-risk diversification," UC3M Working papers. Economics we20070208, Universidad Carlos III de Madrid. Departamento de Economía.
  28. Charpentier, A. & Segers, J.J.J., 2006. "Convergence of Archimedean Copulas," Other publications TiSEM 410237d0-4c38-48f6-8f36-6, Tilburg University, School of Economics and Management.
  29. Hofert, Marius, 2021. "Right-truncated Archimedean and related copulas," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 79-91.
  30. Damiano Brigo & Kyriakos Chourdakis, 2012. "Consistent single- and multi-step sampling of multivariate arrival times: A characterization of self-chaining copulas," Papers 1204.2090, arXiv.org, revised Apr 2012.
  31. Hua, Lei & Joe, Harry, 2011. "Tail order and intermediate tail dependence of multivariate copulas," Journal of Multivariate Analysis, Elsevier, vol. 102(10), pages 1454-1471, November.
  32. Charpentier, Arthur & Segers, Johan, 2007. "Lower tail dependence for Archimedean copulas: Characterizations and pitfalls," Insurance: Mathematics and Economics, Elsevier, vol. 40(3), pages 525-532, May.
  33. Müller, Alfred & Scarsini, Marco, 2005. "Archimedean copulæ and positive dependence," Journal of Multivariate Analysis, Elsevier, vol. 93(2), pages 434-445, April.
  34. Charpentier, A. & Segers, J.J.J., 2006. "Lower Tail Dependence for Archimedean Copulas : Characterizations and Pitfalls," Other publications TiSEM ae669e5a-1929-42d9-b137-6, Tilburg University, School of Economics and Management.
  35. Elena Di Bernardino & Didier Rullière, 2016. "On tail dependence coefficients of transformed multivariate Archimedean copulas," Post-Print hal-00992707, HAL.
  36. Gao, Hai-Ling & Mei, Dong-Cheng, 2019. "The correlation structure in the international stock markets during global financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
  37. Durante, Fabrizio & Jaworski, Piotr & Mesiar, Radko, 2011. "Invariant dependence structures and Archimedean copulas," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 1995-2003.
  38. Jaworski Piotr, 2017. "On Conditional Value at Risk (CoVaR) for tail-dependent copulas," Dependence Modeling, De Gruyter, vol. 5(1), pages 1-19, January.
  39. Hao Ji & Hao Wang & Brunero Liseo, 2018. "Portfolio Diversification Strategy Via Tail‐Dependence Clustering and ARMA‐GARCH Vine Copula Approach," Australian Economic Papers, Wiley Blackwell, vol. 57(3), pages 265-283, September.
  40. Charpentier, Arthur & Segers, Johan, 2009. "Tails of multivariate Archimedean copulas," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1521-1537, August.
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