This study addresses the key issues related to the connectedness, volatility spillovers (VS), and hedging effectiveness between the oil and the stock markets in top oil-importing and oil-exporting countries over different investment horizons. Our work extends previous research on the VS between the oil and stock markets by detecting and incorporating structural breaks in variance in a wavelet-based multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) framework. We also use cross-wavelet coherence analysis, which is an alternative method to investigate the interdependence and analyze the time-frequency comovements and lead-lag relationship between oil prices and stock indices. Using daily data over the period 2001-2017, we find that the model with structural breaks outperforms the one without and generates better estimates. The results suggest that the price spillovers and VS exist but are strongly dependent on the studied stock markets and mostly on the time scale. Spillovers are more important in the long run, indicating a higher interdependence between oil and stock indices. Volatility spillover results are homogeneous between groups of oil-exporting and oil-importing countries and seem to be country-specific. All hedge ratios (HRs) indicate that all studied indices are good hedges for oil. India and China are the countries offering the most profitable hedging opportunities with oil over all investment horizons. The wavelet coherence analysis shows that the correlation is high in the very long term and is more important for oil-exporting countries.
机构:
Beijing Univ Chem Technol, Sch Econ & Management, Beijing 100029, Peoples R ChinaBeijing Univ Chem Technol, Sch Econ & Management, Beijing 100029, Peoples R China
Yu, Lean
Zha, Rui
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Beijing Univ Chem Technol, Sch Econ & Management, Beijing 100029, Peoples R ChinaBeijing Univ Chem Technol, Sch Econ & Management, Beijing 100029, Peoples R China
Zha, Rui
Stafylas, Dimitrios
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Aston Univ, Aston Business Sch, Birmingham, W Midlands, EnglandBeijing Univ Chem Technol, Sch Econ & Management, Beijing 100029, Peoples R China
Stafylas, Dimitrios
He, Kaijian
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Hunan Univ Sci & Technol, Hunan Engn Res Ctr Ind Big Data & Intelligent Dec, Xiangtan 411201, Peoples R ChinaBeijing Univ Chem Technol, Sch Econ & Management, Beijing 100029, Peoples R China
He, Kaijian
Liu, Jia
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Univ Salford, Salford Business Sch, Manchester, EnglandBeijing Univ Chem Technol, Sch Econ & Management, Beijing 100029, Peoples R China
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Univ New S Wales, Sch Banking & Finance, Sydney, NSW 2052, AustraliaJinan Univ, Dept Finance, Guangzhou, Guangdong, Peoples R China
Chen, Zhian
Jiang, Hai
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Jinan Univ, Dept Finance, Guangzhou, Guangdong, Peoples R China
Jinan Univ, Res Inst Finance, Guangzhou, Guangdong, Peoples R ChinaJinan Univ, Dept Finance, Guangzhou, Guangdong, Peoples R China
Jiang, Hai
Li, Donghui
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Univ New S Wales, Sch Banking & Finance, Sydney, NSW 2052, AustraliaJinan Univ, Dept Finance, Guangzhou, Guangdong, Peoples R China
Li, Donghui
Sim, Ah Boon
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Univ New S Wales, Sch Banking & Finance, Sydney, NSW 2052, AustraliaJinan Univ, Dept Finance, Guangzhou, Guangdong, Peoples R China