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Extremes and Robustness: A Contradiction?

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  • Rosario Dell’Aquila
  • Paul Embrechts

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Suggested Citation

  • Rosario Dell’Aquila & Paul Embrechts, 2006. "Extremes and Robustness: A Contradiction?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(1), pages 103-118, April.
    • Handle: RePEc:kap:fmktpm:v:20:y:2006:i:1:p:103-118
    DOI: 10.1007/s11408-006-0002-x
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    References listed on IDEAS

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    1. Dell'Aquila, Rosario & Ronchetti, Elvezio & Trojani, Fabio, 2003. "Robust GMM analysis of models for the short rate process," Journal of Empirical Finance, Elsevier, vol. 10(3), pages 373-397, May.
    2. Marco Moscadelli, 2004. "The modelling of operational risk: experience with the analysis of the data collected by the Basel Committee," Temi di discussione (Economic working papers) 517, Bank of Italy, Economic Research and International Relations Area.
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    Cited by:

    1. Hubert, Mia & Dierckx, Goedele & Vanpaemel, Dina, 2013. "Detecting influential data points for the Hill estimator in Pareto-type distributions," Computational Statistics & Data Analysis, Elsevier, vol. 65(C), pages 13-28.
    2. Brazauskas, Vytaras & Kleefeld, Andreas, 2009. "Robust and efficient fitting of the generalized Pareto distribution with actuarial applications in view," Insurance: Mathematics and Economics, Elsevier, vol. 45(3), pages 424-435, December.
    3. Asimit, Alexandru V. & Badescu, Alexandru M. & Verdonck, Tim, 2013. "Optimal risk transfer under quantile-based risk measurers," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 252-265.
    4. Setareh Ranjbar & Eva Cantoni & Valérie Chavez‐Demoulin & Giampiero Marra & Rosalba Radice & Katia Jaton, 2022. "Modelling the extremes of seasonal viruses and hospital congestion: The example of flu in a Swiss hospital," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(4), pages 884-905, August.
    5. Okhli, Kheirolah & Jabbari Nooghabi, Mehdi, 2021. "On the contaminated exponential distribution: A theoretical Bayesian approach for modeling positive-valued insurance claim data with outliers," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    6. Goegebeur, Yuri & Guillou, Armelle & Ho, Nguyen Khanh Le & Qin, Jing, 2020. "Robust nonparametric estimation of the conditional tail dependence coefficient," Journal of Multivariate Analysis, Elsevier, vol. 178(C).
    7. Grażyna Trzpiot & Justyna Majewska, 2010. "Estimation of Value at Risk: extreme value and robust approaches," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 20(1), pages 131-143.
    8. Mora Valencia Andrés, 2014. "El uso de la distribución g-h en riesgo operativo," Contaduría y Administración, Accounting and Management, vol. 59(1), pages 123-148, enero-mar.
    9. Eling, Martin, 2012. "Fitting insurance claims to skewed distributions: Are the skew-normal and skew-student good models?," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 239-248.
    10. Chris Kenyon & Andrew Green, 2014. "VAR and ES/CVAR Dependence on data cleaning and Data Models: Analysis and Resolution," Papers 1405.7611, arXiv.org.
    11. Yuri Goegebeur & Armelle Guillou & Jing Qin, 2023. "Robust estimation of the conditional stable tail dependence function," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(2), pages 201-231, April.

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    More about this item

    Keywords

    Robust statistics; Robust estimation; M-estimator; Extreme value theory; Extreme value distributions; Generalized Pareto distribution; G10; G40;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G40 - Financial Economics - - Behavioral Finance - - - General

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