Confidence intervals based on L-moments for quantiles of the GP and GEV distributions with application to market-opening asset prices data

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24510%2F21%3A00008475" target="_blank" >RIV/46747885:24510/21:00008475 - isvavai.cz</a>

Result on the web

<a href="https://www.tandfonline.com/doi/abs/10.1080/02664763.2020.1757046" target="_blank" >https://www.tandfonline.com/doi/abs/10.1080/02664763.2020.1757046</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/02664763.2020.1757046" target="_blank" >10.1080/02664763.2020.1757046</a>

Result language

angličtina

Original language name

Confidence intervals based on L-moments for quantiles of the GP and GEV distributions with application to market-opening asset prices data

Original language description

In a ground-breaking paper published in 1990 by the Journal of the Royal Statistical Society, J.R.M. Hosking defined the L-moment of a random variable as an expectation of certain linear combinations of order statistics. L-moments are an alternative to conventional moments and recently they have been used often in inferential statistics. L-moments have several advantages over the conventional moments, including robustness to the presence of outliers, which may lead to more accurate estimates in some cases as the characteristics of distributions. In this contribution, asymptotic theory and L-moments are used to derive confidence intervals of the population parameters and quantiles of the three-parametric generalized Pareto and extreme-value distributions. Computer simulations are performed to determine the performance of confidence intervals for the population quantiles based on L-moments and to compare them to those obtained by traditional estimation techniques. The results obtained show that they perform well in comparison to the moments and maximum likelihood methods when the interest is in higher quantiles, or even best. L-moments are especially recommended when the tail of the distribution is rather heavier and the sample size is small. The derived intervals are applied to real economic data, and specifically to market-opening asset prices.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10103 - Statistics and probability

Project

<a href="/en/project/GA18-01137S" target="_blank" >GA18-01137S: Random Processes of Regression Quantiles in the Financial Risk Analysis</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Applied Statistics

ISSN

0266-4763

e-ISSN

—

Volume of the periodical

—

Issue of the periodical within the volume

7

Country of publishing house

GB - UNITED KINGDOM

Number of pages

28

Pages from-to

—

UT code for WoS article

000532048300001

EID of the result in the Scopus database

2-s2.0-85097559363