Real-time changepoint detection in a nonlinear expectile model
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Real-time changepoint detection in a nonlinear expectile model
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GA21-10768S" target="_blank" >GA21-10768S: Advanced Econometric Models for Option Pricing II – AdEMOP2</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Metrika
ISSN
0026-1335
e-ISSN
1435-926X
Volume of the periodical
87
Issue of the periodical within the volume
Feb 2024
Country of publishing house
DE - GERMANY
Number of pages
27
Pages from-to
105-131
UT code for WoS article
000960081900001
EID of the result in the Scopus database
2-s2.0-85151345662