2016
DOI: 10.1016/j.irfa.2016.10.002
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Time-varying correlation between oil and stock market volatilities: Evidence from oil-importing and oil-exporting countries

Abstract: This paper investigates the time-varying conditional correlation between oil price and stock market volatility for six major oil-importing and oil-exporting countries.

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Cited by 140 publications
(78 citation statements)
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“…Other studies that also concentrate on oil-exporting and oil-importing countries are those by Boldanov et al (2016) and Maghyereh et al (2016). Maghyereh et al (2016) use a sample of 11 countries (3 oil-exporters and 8 oilimporters) for the period 2008-2015, and find evidence that oil price volatility is the main transmitter of volatility shocks to stock market volatilities, a finding similar to Awartani and Maghyereh (2013).…”
Section: Time-varying Relationship Between Oil and Stock Market Volatmentioning
confidence: 94%
“…Other studies that also concentrate on oil-exporting and oil-importing countries are those by Boldanov et al (2016) and Maghyereh et al (2016). Maghyereh et al (2016) use a sample of 11 countries (3 oil-exporters and 8 oilimporters) for the period 2008-2015, and find evidence that oil price volatility is the main transmitter of volatility shocks to stock market volatilities, a finding similar to Awartani and Maghyereh (2013).…”
Section: Time-varying Relationship Between Oil and Stock Market Volatmentioning
confidence: 94%
“…The diagonal elements of , ℎ , , = 1,2, represent the conditional variance terms, while the off-diagonal elements of , ℎ , , ≠ , , = 1,2, represent the conditional covariances. Once the BEKK model parameters are estimated, the conditional correlations can be derived as improvement to the VECH model, as the number of parameters to be estimated is reduced and the positive definiteness of is ensured provided that W W  is positive definite (Terrell and Fomby, 2006), and to the Dynamic Conditional Correlation model (Boldanov et al, 2016), since consistency and asymptotic normality of the estimated parameters of the latter model have not yet been established (Caporin and McAleer, 2012).…”
Section: Modelmentioning
confidence: 99%
“…Compared to related studies, such as Kilian & Park (2009), Filis et al (2011) and Boldanov et al (2016 among others, we show that (i) stock return volatility exhibits a greater response to precautionary demand followed by aggregate demand-190 side shocks, compared to supply-side ones, albeit the size of the impact and/or the degree of persistence of each type of shocks varies across countries, and that (ii) the responses of the correlations to oil price shocks are relatively smaller, compared 195 to those of stock return volatility, for most countries, and, moreover, such correlations mostly react to precautionary demand shocks, compared to the other types of shocks, where the responses are negative for all countries except China, Norway and 200 Russia, which are positive. Our findings are of paramount interest to investors and risk managers in terms of portfolio diversification and their risk exposure to the different types of oil price shocks, and to regulators as they shed light on the extent 205 to which such shocks have effects and persistence on the dynamics of stock return volatility and its linkages with that of oil price changes.…”
Section: Concluding Remarks 185mentioning
confidence: 91%