Real-time changepoint detection in a nonlinear expectile model

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F24%3A10472400" target="_blank" >RIV/00216208:11320/24:10472400 - isvavai.cz</a>

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=Lcp~7jjdv1" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=Lcp~7jjdv1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s00184-023-00904-6" target="_blank" >10.1007/s00184-023-00904-6</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Real-time changepoint detection in a nonlinear expectile model

Popis výsledku v původním jazyce

An online changepoint detection procedure based on conditional expectiles is introduced. The key contribution is threefold: nonlinearity of the underlying model improves the overall flexibility while a parametric form of the unknown regression function preserves a simple and straightforward interpretation; The conditional expectiles, well-known in econometrics for being the only coherent and elicitable risk measure, introduce additional robustness-especially with respect to asymmetric error distributions common in various types of data; The proposed statistical test is proved to be consistent and the distribution under the null hypothesis does not depend on the functional form of the underlying model nor the unknown parameters. Empirical properties of the proposed real-time changepoint detection test are investigated in a simulation study and a practical applicability is illustrated using the Covid-19 prevalence data from Prague.

Název v anglickém jazyce

Real-time changepoint detection in a nonlinear expectile model

Popis výsledku anglicky

An online changepoint detection procedure based on conditional expectiles is introduced. The key contribution is threefold: nonlinearity of the underlying model improves the overall flexibility while a parametric form of the unknown regression function preserves a simple and straightforward interpretation; The conditional expectiles, well-known in econometrics for being the only coherent and elicitable risk measure, introduce additional robustness-especially with respect to asymmetric error distributions common in various types of data; The proposed statistical test is proved to be consistent and the distribution under the null hypothesis does not depend on the functional form of the underlying model nor the unknown parameters. Empirical properties of the proposed real-time changepoint detection test are investigated in a simulation study and a practical applicability is illustrated using the Covid-19 prevalence data from Prague.

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/GA21-10768S" target="_blank" >GA21-10768S: Pokročilé Ekonometrické Modely pro Oceňování Opcí II – AdEMOP2</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

Metrika

ISSN

0026-1335

e-ISSN

1435-926X

Svazek periodika

87

Číslo periodika v rámci svazku

Feb 2024

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

27

Strana od-do

105-131

Kód UT WoS článku

000960081900001

EID výsledku v databázi Scopus

2-s2.0-85151345662