bibtype J - Journal Article
ARLID 0341829
utime 20240111140738.8
mtime 20100423235959.9
title (primary) (eng) Tail Behavior of the Central European Stock Markets during the Financial Crisis
specification
page_count 17 s.
media_type www
serial
title IES Working Papers
volume_id 2010
volume 4 (2010)
page_num 1-17
keyword financial crisis
keyword tail behavior
keyword stock markets
keyword stable probability distribution
author (primary)
ARLID cav_un_auth*0242028
name1 Baruník
name2 Jozef
full_dept (cz) Ekonometrie
full_dept (eng) Department of Econometrics
department (cz) E
department (eng) E
institution UTIA-B
full_dept Department of Econometrics
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101217
name1 Vácha
name2 Lukáš
full_dept (cz) Ekonometrie
full_dept Department of Econometrics
department (cz) E
department E
institution UTIA-B
full_dept Department of Econometrics
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101230
name1 Vošvrda
name2 Miloslav
full_dept (cz) Ekonometrie
full_dept Department of Econometrics
department (cz) E
department E
institution UTIA-B
full_dept Department of Econometrics
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
source_type pdf
url http://library.utia.cas.cz/separaty/2010/E/barunik-0341829.pdf
cas_special
project
project_id GP402/08/P207
agency GA ČR
ARLID cav_un_auth*0241655
project
project_id GD402/09/H045
agency GA ČR
ARLID cav_un_auth*0253998
project
project_id GA402/09/0965
agency GA ČR
ARLID cav_un_auth*0253176
research CEZ:AV0Z10750506
abstract (eng) In the paper we research statistical properties of the Central European stock markets. We focus mainly on the tail behavior of the Czech, Polish, and Hungarian stock markets and compare them to the benchmark U.S. and German stock markets. We fit the data of the 4-year period from March 2005 to March 2009 with the stable probability distribution model and discuss its tail behavior. As the estimation of the tail exponent is very sensitive to the size of the data set, the estimates can be misleading for short daily samples. Thus, we employ high-frequency 1-minute data, which proves to be a good choice as it reveals interesting findings about the distributional properties. Furthermore, we study the difference in stock market behavior before and during the financial crisis.
reportyear 2011
RIV AH
permalink http://hdl.handle.net/11104/0184695
arlyear 2010
mrcbU56 pdf
mrcbU63 IES Working Papers Roč. 2010 č. 4 2010 1 17