Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/120429
Authors: 
Šopov, Boril
Horváth, Roman
Year of Publication: 
2015
Series/Report no.: 
IES Working Paper 9/2015
Abstract: 
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.
Subjects: 
GARCH
extreme events
S&P 500 study
tail index
JEL: 
C15
C58
G17
Document Type: 
Working Paper
Appears in Collections:

Files in This Item:
File
Size
722.69 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.