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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. 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.
    2. 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.
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    Citations

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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. 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.
    3. 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).
    4. Chris Kenyon & Andrew Green, 2014. "VAR and ES/CVAR Dependence on data cleaning and Data Models: Analysis and Resolution," Papers 1405.7611, arXiv.org.
    5. 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.
    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. 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.
    8. 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.
    9. 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.
    10. 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.
    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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