# Extreme value theory based confidence intervals for the parameters of a symmetric L\'evy-stable distribution

## TL;DR

This paper develops confidence intervals for symmetric Lévystable distribution parameters using EVT estimators and assesses their accuracy via simulations.

## Contribution

It introduces EVT-based confidence intervals for Lévystable parameters and evaluates their performance through simulation studies.

## Key findings

- Confidence intervals are constructed using EVT estimators.
- Simulation results demonstrate the intervals' accuracy.
- Method provides a new approach for parameter inference in stable distributions.

## Abstract

We exploit the asymptotic normality of the extreme value theory (EVT) based estimators of the parameters of a symmetric L\'evy-stable distribution, to construct confidence intervals. The accuracy of these intervals is evaluated through a simulation study.