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Comparison of tail index estimators

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Cited by:

  1. Yifan He & Abootaleb Shirvani & Barret Shao & Svetlozar Rachev & Frank Fabozzi, 2024. "Beyond the Bid-Ask: Strategic Insights into Spread Prediction and the Global Mid-Price Phenomenon," Papers 2404.11722, arXiv.org, revised Oct 2024.
  2. Li, Deyuan & Peng, Liang, 2010. "Comparing extreme models when the sign of the extreme value index is known," Statistics & Probability Letters, Elsevier, vol. 80(7-8), pages 739-746, April.
  3. Andrey Pepelyshev & Anatoly Zhigljavsky & Antanas Žilinskas, 2018. "Performance of global random search algorithms for large dimensions," Journal of Global Optimization, Springer, vol. 71(1), pages 57-71, May.
  4. Wendy Shinyie & Noriszura Ismail & Abdul Jemain, 2014. "Semi-parametric Estimation Based on Second Order Parameter for Selecting Optimal Threshold of Extreme Rainfall Events," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3489-3514, September.
  5. Hashorva, Enkelejd, 2010. "On the residual dependence index of elliptical distributions," Statistics & Probability Letters, Elsevier, vol. 80(13-14), pages 1070-1078, July.
  6. Christian Schluter, 2021. "On Zipf’s law and the bias of Zipf regressions," Empirical Economics, Springer, vol. 61(2), pages 529-548, August.
  7. Giulio Bottazzi & Davide Pirino & Federico Tamagni, 2015. "Zipf law and the firm size distribution: a critical discussion of popular estimators," Journal of Evolutionary Economics, Springer, vol. 25(3), pages 585-610, July.
  8. Pere, Jaakko & Ilmonen, Pauliina & Viitasaari, Lauri, 2024. "On extreme quantile region estimation under heavy-tailed elliptical distributions," Journal of Multivariate Analysis, Elsevier, vol. 202(C).
  9. Igor Fedotenkov, 2020. "A Review of More than One Hundred Pareto-Tail Index Estimators," Statistica, Department of Statistics, University of Bologna, vol. 80(3), pages 245-299.
  10. Gomes, M. Ivette & Oliveira, Orlando, 2003. "Censoring estimators of a positive tail index," Statistics & Probability Letters, Elsevier, vol. 65(3), pages 147-159, November.
  11. Wagner, Niklas & Marsh, Terry A., 2005. "Measuring tail thickness under GARCH and an application to extreme exchange rate changes," Journal of Empirical Finance, Elsevier, vol. 12(1), pages 165-185, January.
  12. Ivanilda Cabral & Frederico Caeiro & M. Ivette Gomes, 2022. "On the comparison of several classical estimators of the extreme value index," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 51(1), pages 179-196, January.
  13. Fendel, Ralf & Neumann, Christian, 2021. "Tail risk in the European sovereign bond market during the financial crises: Detecting the influence of the European Central Bank," Global Finance Journal, Elsevier, vol. 50(C).
  14. Ghosh, Souvik & Resnick, Sidney, 2010. "A discussion on mean excess plots," Stochastic Processes and their Applications, Elsevier, vol. 120(8), pages 1492-1517, August.
  15. Gomes, M. Ivette & Pestana, Dinis & Caeiro, Frederico, 2009. "A note on the asymptotic variance at optimal levels of a bias-corrected Hill estimator," Statistics & Probability Letters, Elsevier, vol. 79(3), pages 295-303, February.
  16. Cuntz, A. & Haeusler, E. & Segers, J.J.J., 2003. "Edgeworth Expansions for the Distribution Function of the Hill Estimator," Other publications TiSEM 345501c7-c622-4b04-8d27-9, Tilburg University, School of Economics and Management.
  17. Ahmad Aboubacrène Ag & Deme El Hadji & Diop Aliou & Girard Stéphane, 2019. "Estimation of the tail-index in a conditional location-scale family of heavy-tailed distributions," Dependence Modeling, De Gruyter, vol. 7(1), pages 394-417, January.
  18. Natalia Markovich & Marijus Vaičiulis, 2023. "Extreme Value Statistics for Evolving Random Networks," Mathematics, MDPI, vol. 11(9), pages 1-35, May.
  19. Igor Fedotenkov, 2013. "A bootstrap method to test for the existence of finite moments," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(2), pages 315-322, June.
  20. Hsieh, Ping-Hung, 2002. "An exploratory first step in teletraffic data modeling: evaluation of long-run performance of parameter estimators," Computational Statistics & Data Analysis, Elsevier, vol. 40(2), pages 263-283, August.
  21. Haeusler, E. & Segers, J., 2005. "Assessing Confidence Intervals for the Tail Index by Edgeworth Expansions for the Hill Estimator," Other publications TiSEM e635c476-8fa8-4f16-8760-2, Tilburg University, School of Economics and Management.
  22. Gaoge Hu & Shesheng Gao & Yongmin Zhong & Chengfan Gu, 2014. "Random weighting estimation of stable exponent," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(4), pages 451-468, May.
  23. Frederico Caeiro & M. Ivette Gomes & Björn Vandewalle, 2014. "Semi-Parametric Probability-Weighted Moments Estimation Revisited," Methodology and Computing in Applied Probability, Springer, vol. 16(1), pages 1-29, March.
  24. A. Dematteo & S. Clémençon, 2016. "On tail index estimation based on multivariate data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(1), pages 152-176, March.
  25. Ko, Bonggyun & Kim, Kyungwon, 2017. "Simulation of sovereign CDS market based on interaction between market participant," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 324-340.
  26. Fang, Wen & Wang, Jun, 2013. "Fluctuation behaviors of financial time series by a stochastic Ising system on a Sierpinski carpet lattice," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4055-4063.
  27. Geluk, J. L. & Peng, Liang, 2000. "An adaptive optimal estimate of the tail index for MA(l) time series," Statistics & Probability Letters, Elsevier, vol. 46(3), pages 217-227, February.
  28. Haeusler, E. & Segers, J., 2005. "Assessing Confidence Intervals for the Tail Index by Edgeworth Expansions for the Hill Estimator," Discussion Paper 2005-129, Tilburg University, Center for Economic Research.
  29. Vygantas Paulauskas & Marijus Vaičiulis, 2017. "A class of new tail index estimators," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(2), pages 461-487, April.
  30. Neves, Claudia & Fraga Alves, M. I., 2004. "Reiss and Thomas' automatic selection of the number of extremes," Computational Statistics & Data Analysis, Elsevier, vol. 47(4), pages 689-704, November.
  31. Beirlant, J. & Joossens, E. & Segers, J., 2005. "Unbiased Tail Estimation by an Extension of the Generalized Pareto Distribution," Other publications TiSEM cfb08408-0775-4936-8f1f-b, Tilburg University, School of Economics and Management.
  32. Chao Huang & Jin-Guan Lin & Yan-Yan Ren, 2012. "Statistical Inferences for Generalized Pareto Distribution Based on Interior Penalty Function Algorithm and Bootstrap Methods and Applications in Analyzing Stock Data," Computational Economics, Springer;Society for Computational Economics, vol. 39(2), pages 173-193, February.
  33. Beirlant, J. & Bouquiaux, C. & Werker, B.J.M., 2006. "Semiparametric lower bounds for tail-index estimation," Other publications TiSEM 4f434455-72a7-4b68-b972-d, Tilburg University, School of Economics and Management.
  34. P. Lai & Stephen Lee, 2013. "Estimation of central shapes of error distributions in linear regression problems," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(1), pages 105-124, February.
  35. Yongcheng Qi, 2010. "On the tail index of a heavy tailed distribution," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(2), pages 277-298, April.
  36. Hüsler, Jürg & Li, Deyuan & Müller, Samuel, 2006. "Weighted least squares estimation of the extreme value index," Statistics & Probability Letters, Elsevier, vol. 76(9), pages 920-930, May.
  37. Beran, Jan & Schell, Dieter, 2012. "On robust tail index estimation," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3430-3443.
  38. Deme, El Hadji & Girard, Stéphane & Guillou, Armelle, 2013. "Reduced-bias estimator of the Proportional Hazard Premium for heavy-tailed distributions," Insurance: Mathematics and Economics, Elsevier, vol. 52(3), pages 550-559.
  39. Li, Yizeng & Qi, Yongcheng, 2019. "Adjusted empirical likelihood method for the tail index of a heavy-tailed distribution," Statistics & Probability Letters, Elsevier, vol. 152(C), pages 50-58.
  40. Beirlant, J. & Joossens, E. & Segers, J., 2005. "Unbiased Tail Estimation by an Extension of the Generalized Pareto Distribution," Discussion Paper 2005-112, Tilburg University, Center for Economic Research.
  41. Jan Beran & Dieter Schell & Milan Stehlík, 2014. "The harmonic moment tail index estimator: asymptotic distribution and robustness," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(1), pages 193-220, February.
  42. Lígia Henriques-Rodrigues & Frederico Caeiro & M. Ivette Gomes, 2024. "A New Class of Reduced-Bias Generalized Hill Estimators," Mathematics, MDPI, vol. 12(18), pages 1-18, September.
  43. Cuntz, A. & Haeusler, E. & Segers, J.J.J., 2003. "Edgeworth Expansions for the Distribution Function of the Hill Estimator," Discussion Paper 2003-8, Tilburg University, Center for Economic Research.
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