Tail-Index Estimates in Small Samples

By Ronald Huisman, Kees G. Koedijk, C. Kool, Franz C. Palm. 2001

323 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/922b958552b733bc2d32542a879f354b3b821a93

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Citations in the corpus

Testing for Differences in the Tails of Stock-Market Returns (2003, methodology): “Monte-Carlo simulations An abundant literature discusses the small-sample properties of alternative tail-index estimators: Dekkers and de Haan (1989), Koedijk and Kool (1992), Dacorogna et al. (1995), Pictet et al. (1998), Danielsson et al. (1998), and Huisman et al. (2001).”
Measuring Tail Thickness under GARCH and an Application to Extreme Exchange Rate Changes (2003, methodology): “Previous studies of the tail index of return distributions include Dacorogna et al. (1995), Danielsson and de Vries (1997), Huisman et al. (1998, 2001) , Jondeau and Rockinger (1999), Lauridsen (2000), and McNeil and Frey (2000), among others.”
The vulnerability of learning to adversarial perturbation increases with intrinsic dimensionality (2017, methodology): “Practical methods that have been developed for the estimation of the EVT index, including expansion-based estimators [6] and the well-known Hill estimator and its variants [23], can all be applied to LID (for a survey, see [24]).”
Evaluating the impact of unconventional monetary policy measures: Empirical evidence from the ECB׳s Securities Markets Programme (2016, background): “Above we mentioned four channels through which the ECB’s SMP could in principle have affected bond yields: (i) the ‘classical’ signaling channel, which signals future low monetary policy rates (Christensen and Rudebusch, 2012; Bauer and Rudebusch, 2014), (ii) signaling that affects a country’s defau”
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).”
A Comparison of Extreme Value Theory Approaches for Determining Value at Risk (2005, unknown): “Huisman, Koedijk, Kool and Palm (2001) provide a generalised least squares estimator that corrects for the correlation and heteroscedasticity present in the residual series .”
Frontiers in VaR forecasting and backtesting (2016, methodology): “To address this problem, Huisman et al. (2001) propose a robust small sample bias-corrected estimator of ξ based on a linear regression of a set of Hill estimators obtained with different number of observations in the tail.”
Tail Index Regression (2009, unknown): “Other useful estimators include (for example): the kernel estimator (Csorgo, Deheuvels, and Mason 1985), the moment estimator (Dekkers, Einmahl, and Haan 1989), the weighted least squares estimator (Beirlant, Vynckier, and Teugels 1996), the small sample estimator (Huisman et al. 2001), and also an ”
Varying the VaR for unconditional and conditional environments (2007, methodology): “From a 8 This downward bias for relatively small samples can be circumvented with the appropriate tail estimation procedure (Huisman et al., 2001). number of alternative processes applied in a similar fashion including ARMAGARCH (Barone-Adesi et al., 1999) and AR-GARCH (McNeil and Frey, 2000)…”
Back to the Basics in Banking? A Micro-Analysis of Banking System Stability (2009, unknown): “Huisman et al. (2001) note that the bias is a linear function ofm and that the variance is inversely related tom.”
Extreme Value Theory for Finance: A Survey (2012, methodology): “A modification of the Hill estimator which results in an unbiased estimator for the tail index in the case of small samples23 is provided by Huisman et al. (2001).”