Stock market volatility spillovers: Evidence for Latin America

Gamba-Santamaría, Santiago; Gómez, José Eduardo; Hurtado-Guarín, Jorge Luis; Velandia, Luis Fernando Melo

doi:10.1016/j.frl.2016.10.001

Cited by 93 publications

(60 citation statements)

References 14 publications

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“…It is clear from the figures and the tables that the reactions are different in different countries. In summary, we conclude that there is evidence for contagion and interdependence of squared stock index returns during the GFC and EZC that is in line with previous studies (e.g., Wang et al 2017;Gamba-Santamaria et al 2017;Jiang et al 2017;Bonga-Bonga 2018). Wang et al (2017) find evidence for contagion during the GFC on G7 countries (except for Japan), Russia and India where US is used as sources of contagion and no contagion is found on Brazil, China, and Japan from the same source.…”

Section: Resultssupporting

confidence: 91%

Equity Market Contagion in Return Volatility during Euro Zone and Global Financial Crises: Evidence from FIMACH Model

Quoreshi

Uddin

Jienwatcharamongkhol

2019

JRFM

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The current paper studies equity markets for the contagion of squared index returns as a proxy for stock market volatility, which has not been studied earlier. The study examines squared stock index returns of equity in 35 markets, including the US, UK, Euro Zone and BRICS (Brazil, Russia, India, China and South Africa) countries, as a proxy for the measurement of volatility. Results from the conditional heteroskedasticity long memory model show the evidence of long memory in the squared stock returns of all 35 stock indices studied. Empirical findings show the evidence of contagion during the global financial crisis (GFC) and Euro Zone crisis (EZC). The intensity of contagion varies depending on its sources. This implies that the effects of shocks are not symmetric and may have led to some structural changes. The effect of contagion is also studied by decomposing the level series into explained and unexplained behaviors.

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Section: Resultssupporting

confidence: 91%

Equity Market Contagion in Return Volatility during Euro Zone and Global Financial Crises: Evidence from FIMACH Model

Quoreshi

Uddin

Jienwatcharamongkhol

2019

JRFM

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“…They construct spillover indexes within a VAR system in which the covariance matrix is assumed to be time-invariant, and compute volatilities through a particular definition involving daily high and low prices. Gamba-Santamaria et al [2016] present an extension in which a DCC-GARCH model is used for modelling the multivariate relationships of volatility among different assets. This extension allows for a better representation of observable volatility clusters (e.g.…”

Section: Introductionmentioning

confidence: 99%

Volatility spillovers among global stock markets: measuring total and directional effects

et al. 2017

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In this study we construct volatility spillover indexes for some of the major stock market indexes in the world. We use a DCC-GARCH framework for modelling the multivariate relationships of volatility among markets. Extending the framework of Diebold and Yilmaz [2012] we compute spillover indexes directly from the series of returns considering the time-variant structure of their covariance matrices. Our spillover indexes use daily stock market data of Australia, Canada, China, Germany, Japan, the United Kingdom, and the United States, for the period January 2001 to August 2016. We obtain several relevant results. First, total spillovers exhibit substantial time-series variation, being higher in moments of market turbulence. Second, the net position of each country (transmitter or receiver) does not change during the sample period. However, their intensities exhibit important time-variation. Finally, transmission originates in the most developed markets, as expected. Of special relevance, even though the Chinese stock market has grown importantly over time, it is still a net receiver of volatility spillovers.

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“…Of the papers surveyed in this study, just one study have examined volatility transmissions in the Nigerian stock market (see, Kpughur er al,, 2017) however, it adopts aggregate data and examines transmissions between the naira exchange rate and the stock market using approaches different from this study. There are also studies for other regions, worthy of mention is China (see, e.g., Wang and Zhang, 2011;Sharma, 2017;Jebran et al, 2017), BRICS (see, e.g., Ramaprasad and Biljana, 2007;Boubaker and Raza, 2017;Nareshet al, 2018), U.S (see, e.g., Arouri et al, 2011;Ghouse and Khan, 2017;Kinnunen, 2017;Oh, 2017;Bekiros et al, 2016), Europe (see, e.g., Arouri et al, 2011;Chang et al, 2013;Sharma, 2017;Blau, 2017), South America (see, e.g., Vasco and Agudelo, 2014;Gamba-Santamaria et al, 2016)among others. Furthermore, we notice that there are few or no studies on returns and volatility transmission at the sectoral level in Sub Saharan African regions, this is probably due to data inadequacies or constraints.…”

Section: Literature Reviewmentioning

confidence: 99%

Measuring Return and Volatility Spillovers among Sectoral Stocks in Nigeria

Fasanya¹,

Oyewole

Agbatogun

2019

Zagreb International Review of Economics and Business

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This paper examines the return and volatility spillovers of different sectoral stock prices in Nigeria using monthly data from January 2007 to December 2016. We employ the Diebold and Yilmaz (2012) spillover approach and rolling sample analysis to capture the inherent secular and cyclical movements in the sector stocks market.We show that there is substantial difference between the behaviour of the sectoral stock return and volatility spillover indices over time. We find evidence of interdependence among sector stocks given the spillover indices. While the return spillover index reveals increased integration among the sectoral stocks, the volatility spillover index experiences significant bursts during major market crises. Interestingly, return and volatility spillovers exhibit both trends and bursts respectively.

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Stock market volatility spillovers: Evidence for Latin America

Cited by 93 publications

References 14 publications

Equity Market Contagion in Return Volatility during Euro Zone and Global Financial Crises: Evidence from FIMACH Model

Equity Market Contagion in Return Volatility during Euro Zone and Global Financial Crises: Evidence from FIMACH Model

Volatility spillovers among global stock markets: measuring total and directional effects

Measuring Return and Volatility Spillovers among Sectoral Stocks in Nigeria

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