bibtype J - Journal Article
ARLID 0367060
utime 20240103195825.7
mtime 20111125235959.9
title (primary) (eng) Comovement of Central European stock markets using wavelet coherence: Evidence from high-frequency data
specification
page_count 22 s.
serial
title IES Working Papers
volume_id 2011
volume 22 (2011)
page_num 1-22
keyword comovement
keyword stock market
keyword wavelet analysis
keyword wavelet coherence
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*0256902
name1 Krištoufek
name2 Ladislav
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
url http://library.utia.cas.cz/separaty/2011/E/barunik-0367060.pdf
cas_special
project
project_id 118310
agency GAUK
country CZ
ARLID cav_un_auth*0274537
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 this paper, we contribute to the literature on international stock market comovement. The novelty of our approach lies in usage of wavelet tools to high- frequency financial market data, which allows us to understand the relationship between stock market returns in a different way. Major part of economic time series analysis is done in time or frequency domain separately. Wavelet analysis can combine these two fundamental approaches, so we can work in time-frequency domain. Using wavelet power spectra and wavelet coherence, we have uncovered interesting dynamics of cross-correlations between Central European and Western European stock markets using high-frequency data. Our findings provide possibility of a new approach to financial risk modeling.
reportyear 2012
RIV AH
num_of_auth 3
permalink http://hdl.handle.net/11104/0201846
arlyear 2011
mrcbU63 IES Working Papers Roč. 2011 č. 22 2011 1 22