Volatility contagion between oil and the stock markets of G7 countries plus India and China

Guru, Biplab Kumar; Pradhan, Ashis Kumar; Ramakrishna, Bandaru

doi:10.1016/j.resourpol.2023.103377

Cited by 9 publications

(4 citation statements)

References 41 publications

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“…By using daily WTI data, they show although volatility spillovers of WTI significantly affect those of the S&P500, Chinese stock market volatility seems not be influenced by WTI. By employing similar method, [ 35 ] examines the volatility transmission between WTI and stock markets of G7 countries plus India and China. They find the significant volatility spillover amid stock markets, while no significant evidences of volatility transmission between WTI and stock markets are found.…”

Section: Empirical Analysismentioning

confidence: 99%

WTI, Brent or implied volatility index: Perspective of volatility spillover from oil market to Chinese stock market

Qin,

Bai

2024

PLoS ONE

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This study investigates the impact of oil market uncertainty on the volatility of Chinese sector indexes. We utilize commonly used realized volatility of WTI and Brent oil price along with the CBOE crude oil volatility index (OVX) to embody the oil market uncertainty. Based on the sample span from Mar 16, 2011 to Dec 31, 2019, this study utilizes vector autoregression (VAR) model to derive the impacts of the three different uncertainty indicators on Chinese stock volatilities. The empirical results show, for all sectors, the impact of OVX on sectors volatilities are more economically and statistically significant than that of realized volatility of both WTI and Brent oil prices, especially after the Chinese refined oil pricing reform of March 27, 2013. That implies OVX is more informative than traditional WTI and Brent oil prices with respect to volatility spillover from oil market to Chinese stock market. This study could provide some important implications for the participants in Chinese stock market.

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Section: Empirical Analysismentioning

confidence: 99%

WTI, Brent or implied volatility index: Perspective of volatility spillover from oil market to Chinese stock market

Qin,

Bai

2024

PLoS ONE

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“…The results confirmed that, during a crisis, the correlations between stocks and commodities returns increase. As for [6], they confirmed that the link was extremely volatile during the financial crisis period of 2007-2008. Some recent studies have focused on revealing the effects of the two recent crises, namely, COVID-19 and the Russo-Ukrainian war, on the dynamic connectedness between stock markets and commodities [32][33][34][35]; they tested volatility connectedness between the Indian stock market and six commodity markets using wavelet analysis. Their results showed higher volatility connectedness between the Indian stock market and all commodity markets; an increase after the COVID-19 pandemic and the transmission of contagion is significant in the medium-and long-term periods.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Ref. [33] proved an average volatility contagion between oil and stock markets in the G-7 countries in addition to India and China in the COVID-19 period. Ref.…”

Section: Literature Reviewmentioning

confidence: 99%

Which Commodity Sectors Effectively Hedge Emerging Eastern European Stock Markets? Evidence from MGARCH Models

Melki

Ghorbel

2023

Commodities

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This study aims at examining whether hedging emerging Eastern Europe stock markets with commodities sectors can help in reducing market risks and whether it has the same effectiveness among different sectors. As an attempt to achieve this goal, we opt for three types of MGARCH model. These are DCC, ADCC and GO-GARCH, which are used with each bivariate series to model dynamic conditional correlations, optimal hedge ratios and hedging effectiveness. Rolling window analysis is used for out-of-sample one-step-ahead forecasts from December 1994 to June 2022. The results have shown that the commodities sectors of industrial metals and energy represent the optimal hedging instruments for emerging Eastern Europe stock markets as they have the highest hedging effectiveness. Additionally, our empirical results have proved that hedge ratios estimated by the DCC and ADCC models are very similar, which is not the case for GO-GARCH, and that hedging effectiveness is preferably estimated by the ADCC model.

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“…Finally, Guru et al (2023) reported that the COVID-19 period registered important bidirectional effects between the oil market and the stock market.…”

Section: Literature Reviewmentioning

confidence: 99%

Shock transmission between crude oil prices and stock markets

et al. 2023

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Volatility contagion between oil and the stock markets of G7 countries plus India and China

Cited by 9 publications

References 41 publications

WTI, Brent or implied volatility index: Perspective of volatility spillover from oil market to Chinese stock market

WTI, Brent or implied volatility index: Perspective of volatility spillover from oil market to Chinese stock market

Which Commodity Sectors Effectively Hedge Emerging Eastern European Stock Markets? Evidence from MGARCH Models

Shock transmission between crude oil prices and stock markets

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