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10.3389-fenrg.2019.00146 |
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|a 2296598X (ISSN)
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|a Revisiting the Integration of China Into the World Crude Oil Market: The Role of Structural Breaks
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|b Frontiers Media S.A.
|c 2019
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|z View Fulltext in Publisher
|u https://doi.org/10.3389/fenrg.2019.00146
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|a The China's crude oil futures market (INE market), as it was first launched in late March of 2018, quickly draws much attention from global investors. In reference to the high frequency data, this research explores how well this new product reacts efficiently to international influences and to what extent it can be integrated with traditional benchmarks, such as WTI and Brent. The multivariate GARCH models are employed to capture the cross-market time-varying correlations, return and volatility spillovers, which are modified by incorporating the detected structural breaks in the return dynamics to improve the accuracy of model estimates. Empirical results indicate a strong integration of INE market with these international benchmarks. A high but time-varying correlation is observed with recurring highs around 0.7. Spillover effects have included significant bidirectional return and volatility spillovers between the INE and the international benchmark markets. Secondly, INE market appears to interact better with the Brent market than with the WTI market. Thirdly, structural breaks can influence correlations, the portfolio weights and hedge ratios. Lastly, the correlation between crude oil futures markets decreases significantly during the periods when structural breaks caused by economic and/or geopolitical events are identified. These findings have important implications in policy makings and economic decisions on portfolio management and hedging strategies. © Copyright © 2019 Liu, Ding, Zhai, Lv, Wu and Zhang.
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|a Commerce
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|a crude oil
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|a Crude oil
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|a Decision making
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|a dynamic correlation
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|a Dynamic correlation
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|a Financial data processing
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|a Financial markets
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|a Geopolitical events
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|a High frequency data
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|a integration
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|a Integration
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|a Investments
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|a Multivariate garch models
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|a Portfolio managements
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|a Structural break
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|a structural breaks
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|a Volatility spillovers
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|a volatility transmission
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|a Volatility transmissions
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|a Ding, Z.
|e author
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|a Liu, Z.
|e author
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|a Lv, T.
|e author
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|a Wu, J.S.
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|a Zhai, P.
|e author
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|a Zhang, K.
|e author
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|t Frontiers in Energy Research
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