Cipra, T., Hendrych, R.: Robust recursive estimation of GARCH models

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10386440" target="_blank" >RIV/00216208:11320/18:10386440 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.14736/kyb-2018-6-1138" target="_blank" >https://doi.org/10.14736/kyb-2018-6-1138</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14736/kyb-2018-6-1138" target="_blank" >10.14736/kyb-2018-6-1138</a>

Result language
angličtina
Original language name
Cipra, T., Hendrych, R.: Robust recursive estimation of GARCH models
Original language description
The robust recursive algorithm for the parameter estimation and the volatility prediction in GARCH models is suggested. It seems to be useful for various financial time series, in particular for (high-frequency) log returns contaminated by additive outliers. The proposed procedure can be effective in the risk control and regulation when the prediction of volatility is the main concern since it is capable to distinguish and correct outlaid bursts of volatility. This conclusion is demonstrated by simulations and real data examples presented in the paper.
Czech name
—
Czech description
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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

Project
<a href="/en/project/GA17-00676S" target="_blank" >GA17-00676S: Dynamic models of risk in finance and insurance</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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