EBTailIndex: Expectile Based Tail Index Estimation

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EBTailIndexR Documentation

Expectile Based Tail Index Estimation

Description

Computes a point estimate of the tail index based on the Expectile Based (EB) estimator.

Usage

EBTailIndex(data, tau, est=NULL)

Arguments

data

A vector of (1 \times n) observations.

tau

A real in (0,1) specifying the intermediate level \tau_n. See Details\.

est

A real specifying the estimate of the expectile at the intermediate level tau.

Details

For a dataset data of sample size n, the tail index \gamma of its (marginal) distribution is estimated using the EB estimator:

\hat{\gamma}_n^E =\left(1+\frac{\hat{\bar{F}}_n(\tilde{\xi}_{\tau_n})}{1-\tau_n}\right)^{-1} ,

where \hat{\bar{F}}_n is the empirical survival function of the observations, \tilde{\xi}_{\tau_n} is an estimate of the \tau_n-th expectile. The observations can be either independent or temporal dependent. See Padoan and Stupfler (2020) and Daouia et al. (2018) for details.

  • The so-called intermediate level tau or \tau_n is a sequence of positive reals such that \tau_n \to 1 as n \to \infty. Practically, \tau_n \in (0,1) is the ratio between the empirical mean distance of the \tau_n-th expectile from the smaller observations and the empirical mean distance of of the \tau_n-th expectile from all the observations. An estimate of \tau_n-th expectile is computed and used in turn to estimate \gamma.

  • The value est, if provided, is meant to be an esitmate of the \tau_n-th expectile which is used to estimate \gamma. On the contrary, if est=NULL, then the routine EBTailIndex estimate first the \tau_n-th expectile expectile and then use it to estimate \gamma.

Value

An estimate of the tain index \gamma.

Author(s)

Simone Padoan, simone.padoan@unibocconi.it, https://faculty.unibocconi.it/simonepadoan/; Gilles Stupfler, gilles.stupfler@univ-angers.fr, https://math.univ-angers.fr/~stupfler/

References

Anthony C. Davison, Simone A. Padoan and Gilles Stupfler (2023). Tail Risk Inference via Expectiles in Heavy-Tailed Time Series, Journal of Business & Economic Statistics, 41(3) 876-889.

Daouia, A., Girard, S. and Stupfler, G. (2018). Estimation of tail risk based on extreme expectiles. Journal of the Royal Statistical Society: Series B, 80, 263-292.

See Also

HTailIndex, MomTailIndex, MLTailIndex,

Examples

# Tail index estimation based on the Expectile based estimator obtained with data
# simulated from an AR(1) with 1-dimensional Student-t distributed innovations

tsDist <- "studentT"
tsType <- "AR"

# parameter setting
corr <- 0.8
df <- 3
par <- c(corr, df)

# Big- small-blocks setting
bigBlock <- 65
smallblock <- 15

# Intermediate level (or sample tail probability 1-tau)
tau <- 0.97

# sample size
ndata <- 2500

# Simulates a sample from an AR(1) model with Student-t innovations
data <- rtimeseries(ndata, tsDist, tsType, par)

# tail index estimation
gammaHat <- EBTailIndex(data, tau)
gammaHat

ExtremeRisks documentation built on June 8, 2025, 10:50 a.m.