| bibtype |
J -
Journal Article
|
| ARLID |
0487923 |
| utime |
20240103215756.5 |
| mtime |
20180313235959.9 |
| SCOPUS |
85030123221 |
| WOS |
000415912900140 |
| DOI |
10.1016/j.physa.2017.08.123 |
| title
(primary) (eng) |
Networks of volatility spillovers among stock markets |
| specification |
| page_count |
20 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0257423 |
| ISSN |
0378-4371 |
| title
|
Physica. A : Statistical Mechanics and its Applications |
| volume_id |
490 |
| volume |
1 (2018) |
| page_num |
1555-1574 |
| publisher |
|
|
| keyword |
Volatility spillovers |
| keyword |
Shock transmission |
| keyword |
Stock markets |
| keyword |
Granger causality network |
| keyword |
Financial crisis |
| keyword |
Spatial regression |
| author
(primary) |
| ARLID |
cav_un_auth*0359155 |
| name1 |
Baumöhl |
| name2 |
E. |
| country |
SK |
|
| author
|
| ARLID |
cav_un_auth*0312139 |
| name1 |
Kočenda |
| name2 |
Evžen |
| full_dept (cz) |
Ekonometrie |
| full_dept |
Department of Econometrics |
| department (cz) |
E |
| department |
E |
| institution |
UTIA-B |
| full_dept |
Department of Econometrics |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0359156 |
| name1 |
Lyócsa |
| name2 |
S. |
| country |
SK |
|
| author
|
| ARLID |
cav_un_auth*0359157 |
| name1 |
Výrost |
| name2 |
T. |
| country |
SK |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0281000 |
| project_id |
GBP402/12/G097 |
| agency |
GA ČR |
| country |
CZ |
|
| abstract
(eng) |
In our network analysis of 40 developed, emerging and frontier stock markets during the 2006-2014 period, we describe and model volatility spillovers during both the global financial crisis and tranquil periods. The resulting market interconnectedness is depicted by fitting a spatial model incorporating several exogenous characteristics. We document the presence of significant temporal proximity effects between markets and somewhat weaker temporal effects with regard to the US equity market volatility spillovers decrease when markets are characterized by greater temporal proximity. Volatility spillovers also present a high degree of interconnectedness, which is measured by high spatial autocorrelation. This finding is confirmed by spatial regression models showing that indirect effects are much stronger than direct effects, i.e., market-related changes in 'neighboring' markets (within a network) affect volatility spillovers more than changes in the given market alone, suggesting that spatial effects simply cannot be ignored when modeling stock market relationships. Our results also link spillovers of escalating magnitude with increasing market size, market liquidity and economic openness. |
| result_subspec |
WOS |
| RIV |
AH |
| FORD0 |
50000 |
| FORD1 |
50200 |
| FORD2 |
50202 |
| reportyear |
2019 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0282530 |
| confidential |
S |
| mrcbC86 |
1* Article Physics Multidisciplinary |
| mrcbT16-e |
PHYSICSMULTIDISCIPLINARY |
| mrcbT16-j |
0.432 |
| mrcbT16-s |
0.699 |
| mrcbT16-B |
43.846 |
| mrcbT16-D |
Q3 |
| mrcbT16-E |
Q3 |
| arlyear |
2018 |
| mrcbU14 |
85030123221 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000415912900140 WOS |
| mrcbU63 |
cav_un_epca*0257423 Physica. A : Statistical Mechanics and its Applications 0378-4371 1873-2119 Roč. 490 č. 1 2018 1555 1574 Elsevier |
|