Self-weighted recursive estimation of GARCH models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10382855" target="_blank" >RIV/00216208:11320/18:10382855 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1080/03610918.2015.1053924" target="_blank" >https://doi.org/10.1080/03610918.2015.1053924</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/03610918.2015.1053924" target="_blank" >10.1080/03610918.2015.1053924</a>
Alternative languages
Result language
angličtina
Original language name
Self-weighted recursive estimation of GARCH models
Original language description
The generalized autoregressive conditional heteroscedasticity (GARCH) processes are frequently used to investigate and model financial returns. They are routinely estimated by computationally complex off-line estimation methods, for example, by the conditional maximum likelihood procedure. However, in many empirical applications (especially in the context of high-frequency financial data), it seems necessary to apply numerically more effective techniques to calibrate and monitor such models. The aims of this contribution are: (i)to review the previously introduced recursive estimation algorithms and to derive self-weighted alternatives applying general recursive identification instruments, and (ii)to examine these methods by means of simulations and an empirical application.
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
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GBP402%2F12%2FG097" target="_blank" >GBP402/12/G097: DYME-Dynamic Models in Economics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Communications in Statistics Part B: Simulation and Computation
ISSN
0361-0918
e-ISSN
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Volume of the periodical
47
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
14
Pages from-to
315-328
UT code for WoS article
000424159000001
EID of the result in the Scopus database
2-s2.0-85038364267