Networks of volatility spillovers among stock markets

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11230%2F18%3A10363576" target="_blank" >RIV/00216208:11230/18:10363576 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985556:_____/18:00487923

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.physa.2017.08.123" target="_blank" >http://dx.doi.org/10.1016/j.physa.2017.08.123</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.physa.2017.08.123" target="_blank" >10.1016/j.physa.2017.08.123</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Networks of volatility spillovers among stock markets

Popis výsledku v původním jazyce

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 &apos;neighboring&apos; 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.

Název v anglickém jazyce

Networks of volatility spillovers among stock markets

Popis výsledku anglicky

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 &apos;neighboring&apos; 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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50201 - Economic Theory

Projekt

<a href="/cs/project/GBP402%2F12%2FG097" target="_blank" >GBP402/12/G097: DYME-Dynamické modely v ekonomii</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Physica A: Statistical Mechanics and its Applications

ISSN

0378-4371

e-ISSN

—

Svazek periodika

490

Číslo periodika v rámci svazku

January

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

20

Strana od-do

1555-1574

Kód UT WoS článku

000415912900140

EID výsledku v databázi Scopus

2-s2.0-85030123221