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A New Regression-Based Tail Index Estimator

Author

Listed:
  • João Nicolau

    (ISEG-Universidade de Lisboa and REM/CEMAPRE)

  • Paulo M. M. Rodrigues

    (Banco de Portugal and NovaSBE, Universidade Nova de Lisboa)

Abstract

A new regression-based approach for the estimation of the tail index of heavy-tailed distributions with several important properties is introduced. First, it provides a bias reduction when compared to available regression-based methods; second, it is resilient to the choice of the tail length used for the estimation of the tail index; third, when the effect of the slowly varying function at infinity of the Pareto distribution vanishes slowly, it continues to perform satisfactorily; and fourth, it performs well under dependence of unknown form. An approach to compute the asymptotic variance under time dependence and conditional heteroskcedasticity is also provided.

Suggested Citation

  • João Nicolau & Paulo M. M. Rodrigues, 2019. "A New Regression-Based Tail Index Estimator," The Review of Economics and Statistics, MIT Press, vol. 101(4), pages 667-680, October.
    • Handle: RePEc:tpr:restat:v:101:y:2019:i:4:p:667-680
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    References listed on IDEAS

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    3. Yannic Rehm & Lucas Chancel, 2022. "Measuring the Carbon Content of Wealth Evidence from France and Germany," World Inequality Lab Working Papers halshs-03828939, HAL.
    4. Nicolau, João & Rodrigues, Paulo M.M. & Stoykov, Marian Z., 2023. "Tail index estimation in the presence of covariates: Stock returns’ tail risk dynamics," Journal of Econometrics, Elsevier, vol. 235(2), pages 2266-2284.
    5. Josep Lluís Carrion-i-Silvestre & Andreu Sansó, 2023. "“Generalized Extreme Value Approximation to the CUMSUMQ Test for Constant Unconditional Variance in Heavy-Tailed Time Series”," AQR Working Papers 202305, University of Barcelona, Regional Quantitative Analysis Group, revised Jul 2023.
    6. Lahr, Henry, 2023. "Fat tails in private equity fund returns: The smooth double Pareto distribution," International Review of Financial Analysis, Elsevier, vol. 86(C).
    7. João Nicolau & Pedro Raposo & Paulo M. M. Rodrigues, 2023. "Measuring wage inequality under right censoring," Economic Inquiry, Western Economic Association International, vol. 61(2), pages 377-401, April.
    8. Jo~ao Nicolau & Paulo M. M. Rodrigues, 2024. "A simple but powerful tail index regression," Papers 2409.13531, arXiv.org.
    9. Demetrescu, Matei & Georgiev, Iliyan & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2022. "Testing for episodic predictability in stock returns," Journal of Econometrics, Elsevier, vol. 227(1), pages 85-113.
    10. Zsurkis, Gabriel & Nicolau, João & Rodrigues, Paulo M.M., 2024. "First passage times in portfolio optimization: A novel nonparametric approach," European Journal of Operational Research, Elsevier, vol. 312(3), pages 1074-1085.

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