Using a Bootstrap Method to Choose the Sample Fraction in Tail Index Estimation
By Jón Dańıelsson, Laurens de Haan, Liang Peng, Casper G. de Vries. 2000
526 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/a913ecbe7a3ccbfbc6a96b75d4dd84273309f61f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Jan Beirlant
- Esther Ruiz
- M. Nieto
- Frederico Caeiro
- Stéphane Girard
- M. Ivette Gomes
- Carl John Scarrott
- Michael Rockinger
In Finance
- Jan Beirlant
- Stéphane Girard
- Laurent Gardes
- M. Ivette Gomes
- A. C. Davison
- Frederico Caeiro
- Armelle Guillou
- Sidney I. Resnick
In Global and Planetary Change
- Jan Beirlant
- Stéphane Girard
- Laurent Gardes
- M. Ivette Gomes
- Sidney I. Resnick
- Carl John Scarrott
- Armelle Guillou
- Frederico Caeiro
Citations in the corpus
- Are output growth-rate distributions fat-tailed? some evidence from OECD countries (2008, background): “23: 639–669 (2008) DOI: 10.1002/jae in Danielsson et al. (2001).12 As Table XII shows, the HE returns values always greater than 2 and smaller than 3.”
- Frontiers in VaR forecasting and backtesting (2016, methodology): “Danielsson et al. (2001) and Ferreira et al. (2003) develop bootstrap methods for optimal threshold selection in the context of the Hill and GPD estimators, respectively.”
- A Horse Race between the Block Maxima Method and the Peak–over–Threshold Approach (2018, background): “, Danielsson et al. (2001), Drees and Kaufmann (1998) and Guillou and Hall (2001). As an indirect solution to the problem, one may also rely on bias corrections, which typically allows for a much larger choice of k, see, e.g., Gomes, De Haan and Rodrigues (2008). After the bias correction, the “Hill”
- HEAVY-TAILED DISTRIBUTIONS AND RATING (2001, methodology): “This was done by bootstrap methods (see, for instance, [9]) or by regression diagnostics on a Pareto quantile plot in [2].”
- Statistics of Extremes (2004, methodology): “The idea of subsample bootstrapping is taken up in a broader method by Danielsson et al. (1997). Instead of bootstrapping the mean squared error of the Hill estimator itself, they use an auxiliary statistic, the mean squared”
- The choice of the distribution of asset returns: How extreme value theory can help? (2005, background): “As largely discussed in the extreme value theory literature, the choice of its value is a critical issue (see Danielsson et al. (2001) and Huisman et al. (2001) for a discussion).”
- Measuring Tail Thickness under GARCH and an Application to Extreme Exchange Rate Changes (2003, methodology): “Instead of applying the bootstrap to the MSE of the Hill estimator directly as in Eq. (2.12), an asymptotically equivalent criterion which does not depend on the choice of an initial estimator is proposed in Danielsson et al. (2001) .”
- A Tale of Tails: An Empirical Analysis of Loss Distribution Models for Estimating Operational Risk Capital (2006, methodology): “See Danielsson et al. (2001) for details on this bootstrap method.”
- Value-at-Risk and Extreme Returns (2000, methodology): “RecentlyDanielsson and de Vries (1997a) and Danielsson, de Haan, Peng, and de Vries (2000) have proposed general estimation methods for the number of extreme order statistics that are in the tails, but presuppose i.i.d.”
- How to make a Hill Plot (2000, methodology): “We quantify superiority of one plotting method over another in terms of the occupation timeof the plots in a neighborhood of the true value of .”
- Tail index estimation: quantile driven threshold selection (2016, methodology): “’Du bo’ refers to the double bootstrap procedure by Danielsson et al. (2001).”