GARCH models, tail indexes and error distributions: An empirical investigation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11230%2F16%3A10325682" target="_blank" >RIV/00216208:11230/16:10325682 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.najef.2016.03.006" target="_blank" >http://dx.doi.org/10.1016/j.najef.2016.03.006</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.najef.2016.03.006" target="_blank" >10.1016/j.najef.2016.03.006</a>

Result language
angličtina
Original language name
GARCH models, tail indexes and error distributions: An empirical investigation
Original language description
We perform a large simulation study to examine the extent to which various generalized autoregressive conditional heteroskedasticity (GARCH) models capture extreme events in stock market returns. We estimate Hill's tail indexes for individual S&P 500 stock market returns and compare these to the tail indexes produced by simulating GARCH models. Our results suggest that actual and simulated values differ greatly for GARCH models with normal conditional distributions, which underestimate the tail risk. By contrast, the GARCH models with Student's t conditional distributions capture the tail shape more accurately, with GARCH and GJR-GARCH being the top performers.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
AH - Economics
OECD FORD branch
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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)

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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