Arbeitspapier
GARCH models, tail indexes and error distributions: An empirical investigation
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 ranging from 1995-2014 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.
- Sprache
-
Englisch
- Erschienen in
-
Series: IES Working Paper ; No. 9/2015
- Klassifikation
-
Wirtschaft
Statistical Simulation Methods: General
Financial Econometrics
Financial Forecasting and Simulation
- Thema
-
GARCH
extreme events
S&P 500 study
tail index
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Šopov, Boril
Horváth, Roman
- Ereignis
-
Veröffentlichung
- (wer)
-
Charles University in Prague, Institute of Economic Studies (IES)
- (wo)
-
Prague
- (wann)
-
2015
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Šopov, Boril
- Horváth, Roman
- Charles University in Prague, Institute of Economic Studies (IES)
Entstanden
- 2015
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