Networks of volatility spillovers among stock markets

0487923 - ÚTIA 2019 RIV NL eng J - Journal Article
Baumöhl, E. - Kočenda, Evžen - Lyócsa, S. - Výrost, T.
Networks of volatility spillovers among stock markets.
Physica. A : Statistical Mechanics and its Applications. Roč. 490, č. 1 (2018), s. 1555-1574. ISSN 0378-4371. E-ISSN 1873-2119
R&D Projects: GA ČR(CZ) GBP402/12/G097
Institutional support: RVO:67985556
Keywords : Volatility spillovers * Shock transmission * Stock markets * Granger causality network * Financial crisis * Spatial regression
OECD category: Applied Economics, Econometrics
Impact factor: 2.500, year: 2018
http://library.utia.cas.cz/separaty/2018/E/kocenda-0487923.pdf

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.
Permanent Link: http://hdl.handle.net/11104/0282530