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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GA18-01137S" target="_blank" >GA18-01137S: Náhodné procesy regresních kvantilů v analýze finančního rizika</a><br>

Návaznosti

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

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Journal of Applied Statistics

ISSN

0266-4763

e-ISSN

—

Svazek periodika

—

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

28

Strana od-do

—

Kód UT WoS článku

000532048300001

EID výsledku v databázi Scopus

2-s2.0-85097559363