Global financial uncertainties and China’s crude oil futures market: Evidence from interday and intraday price dynamics

Ahmad, 2020, On the intraday dynamics of oil price and exchange rate: what can we learn from China and India?, Energy Econ., 91, 104871, 10.1016/j.eneco.2020.104871 Alam, 2019, Causal flows between oil and forex markets using high-frequency data: Asymmetries from good and bad volatility, Energy Econ., 84, 10.1016/j.eneco.2019.104513 Andersen, 1998, Deutsche mark-dollar volatility: intraday activity patterns, macroeconomic announcements, and longer run dependencies. J. Finan., 53, 219 Andrada-Félix, 2018, Fear connectedness among asset classes, Appl. Econ., 50, 4234, 10.1080/00036846.2018.1441521 Antonakakis, 2020, Oil and asset classes implied volatilities: investment strategies and hedging effectiveness, Energy Econ., 91, 10.1016/j.eneco.2020.104762 Bahloul, 2018, The role of economic and financial uncertainties in predicting commodity futures returns and volatility: evidence from a nonparametric causality-in-quantiles test, J. Multinatl. Financ. Manag., 45, 52, 10.1016/j.mulfin.2018.04.002 Bai, 2020, Infectious disease pandemic and permanent volatility of international stock markets: a long-term perspective, Financ. Res. Lett. Bakas, 2019, Volatility forecasting in commodity markets using macro uncertainty, Energy Econ., 81, 79, 10.1016/j.eneco.2019.03.016 Balcilar, 2016, Does economic policy uncertainty predict exchange rate returns and volatility? Evidence from a nonparametric causality-in-quantiles test, Open Econ. Rev., 27, 229, 10.1007/s11079-016-9388-x Balcilar, 2017, The role of news-based uncertainty indices in predicting oil markets: A hybrid nonparametric quantile causality method, Empir. Econ., 53, 879, 10.1007/s00181-016-1150-0 Balcilar, 2017, The effect of investor sentiment on gold market return dynamics: Evidence from a nonparametric causality-in-quantiles approach, Res. Policy, 51, 77, 10.1016/j.resourpol.2016.11.009 Balcilar, 2018, Geopolitical risks and stock market dynamics of the BRICS, Econ. Syst., 42, 295, 10.1016/j.ecosys.2017.05.008 Balcilar, 2020, Credit ratings and predictability of stock return dynamics of the BRICS and the PIIGS: evidence from a nonparametric causality-in-quantiles approach, Quart. Rev. Econ. Finan. Barndorff-Nielsen, 2004, Power and bipower variation with stochastic volatility and jumps, J. Financ. Econ., 2, 1 Barndorff-Nielsen, 2010, Measuring downside risk: Realised semivariance, 117 Benedetto, 2020, Does OVX affect WTI and Brent oil spot variance? Evidence from an entropy analysis, Energy Econ., 89, 10.1016/j.eneco.2020.104815 Bildirici, 2019, The chaotic behavior among the oil prices, expectation of investors and stock returns: TAR-TR-GARCH copula and TAR-TR-TGARCH copula, Pet. Sci., 16, 217, 10.1007/s12182-018-0281-7 Bonaccolto, 2018, The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk, Physica A Stat. Mech. Appl., 507, 446, 10.1016/j.physa.2018.05.061 Bonato, 2020, Moments-based spillovers across gold and oil markets, Energy Econ., 10.1016/j.eneco.2020.104799 Bouri, 2017, Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions, Financ. Res. Lett., 23, 87, 10.1016/j.frl.2017.02.009 Bouri, 2019, Geopolitical risks and movements in Islamic bond and equity markets: a note, Def. Peace Econ., 30, 367, 10.1080/10242694.2018.1424613 Cai, 2019, Multifractal detrended cross-correlations between WTI crude oil price fluctuations and investor fear gauges, Appl. Econ. Lett., 26, 587, 10.1080/13504851.2018.1488044 Charfeddine, 2020, Investigating the dynamic relationship between cryptocurrencies and conventional assets: implications for financial investors, Econ. Model., 85, 198, 10.1016/j.econmod.2019.05.016 Chen, 2018, The predictive content of CBOE crude oil volatility index, Physica A Stat. Mech. Appl., 492, 837, 10.1016/j.physa.2017.11.014 Chen, 2020, Forecasting oil price volatility using high-frequency data: New evidence, Int. Rev. Econ. Financ., 66, 1, 10.1016/j.iref.2019.10.014 Chuang, 2009, Causality in quantiles and dynamic stock return-volume relations, J. Bank. Financ., 33, 1351, 10.1016/j.jbankfin.2009.02.013 Czudaj, 2019, Crude oil futures trading and uncertainty, Energy Econ., 80, 793, 10.1016/j.eneco.2019.01.002 Dai, 2020, The role of global economic policy uncertainty in predicting crude oil futures volatility: Evidence from a two-factor GARCH-MIDAS model, Working Paper. arXiv preprint arXiv, 2007, 12838 Das, 2018, On the relationship of gold, crude oil, stocks with financial stress: a causality-in-quantiles approach, Financ. Res. Lett., 27, 169, 10.1016/j.frl.2018.02.030 Demirer, 2018, Time-varying rare disaster risks, oil returns and volatility, Energy Econ., 75, 239, 10.1016/j.eneco.2018.08.021 Demirer, 2019, Geopolitical risks and the predictability of regional oil returns and volatility, OPEC Energy Rev., 43, 342, 10.1111/opec.12160 Diks, 2006, A new statistic and practical guidelines for nonparametric Granger causality testing, J. Econ. Dyn. Control., 30, 1647, 10.1016/j.jedc.2005.08.008 Ding, 2020, Tail causality between crude oil price and RMB exchange rate, China World Econ., 28, 116, 10.1111/cwe.12335 Dutta, 2017, Modeling and forecasting oil price risk: the role of implied volatility index, J. Econ. Stud., 44, 1003, 10.1108/JES-11-2016-0218 Dutta, 2018, A note on the implied volatility spillovers between gold and silver markets, Res. Policy, 55, 192, 10.1016/j.resourpol.2017.11.017 Dutta, 2019, Nonlinear relationships amongst the implied volatilities of crude oil and precious metals, Res. Policy, 61, 473, 10.1016/j.resourpol.2018.04.009 Engle, 2013, Stock market volatility and macroeconomic fundamentals, Rev. Econ. Stat., 95, 776, 10.1162/REST_a_00300 Ewing, 2018, The dynamic effects of oil supply shocks on the US stock market returns of upstream oil and gas companies, Energy Econ., 72, 505, 10.1016/j.eneco.2018.05.001 Fousekis, 2019, Crude oil price and implied volatility: Insights from non-parametric quantile regressions, Stud. Econ. Financ., 36, 168, 10.1108/SEF-04-2018-0117 Gkillas, 2020, Spillovers in higher-order moments of crude oil, gold, and bitcoin, Quart. Rev. Econ. Finan. Gkillas, 2020, Jumps beyond the realms of cricket: India’s performance in One Day Internationals and stock market movements, J. Appl. Stat., 47, 1109, 10.1080/02664763.2019.1663157 Gkillas, 2020, Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss, J. Int. Money Financ., 10.1016/j.jimonfin.2020.102137 Gong, 2018, The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market, Energy Econ., 74, 370, 10.1016/j.eneco.2018.06.005 Granger, 1969, Investigating causal relations by econometric models and cross-spectral methods, Econometrica, 37, 424, 10.2307/1912791 Gupta, 2019, Time-varying predictability of oil market movements over a century of data: the role of US financial stress, North Am. J. Econ. Finan., 50 Haugom, 2014, Forecasting volatility of the US oil market, J. Bank. Financ., 47, 1, 10.1016/j.jbankfin.2014.05.026 Huang, 2020, Identifying the comovement of price between China’s and international crude oil futures: a time-frequency perspective, Int. Rev. Financ. Anal., 72, 10.1016/j.irfa.2020.101562 Huang, 2005, The relative contribution of jumps to total price variance, J. Financ. Econ., 3, 456 Jawadi, 2016, On oil-US exchange rate volatility relationships: an intraday analysis, Econ. Model., 59, 329, 10.1016/j.econmod.2016.07.014 Jena, 2019, Distributional predictability between commodity spot and futures: evidence from nonparametric causality-in-quantiles tests, Energy Econ., 78, 615, 10.1016/j.eneco.2018.11.013 Jeong, 2017, Quantile causality from dollar exchange rate to international oil price, J. Kor. Data Inform. Sci. Soc., 28, 361 Jeong, 2012, A consistent nonparametric test for causality in quantile, Economic Theory, 28, 861, 10.1017/S0266466611000685 Ji, 2016, Modelling the joint dynamics of oil prices and investor fear gauge, Res. Int. Bus. Financ., 37, 242, 10.1016/j.ribaf.2015.11.016 Ji, 2019, China’s crude oil futures: Introduction and some stylized facts, Financ. Res. Lett., 28, 376, 10.1016/j.frl.2018.06.005 Ji, 2018, Uncertainties and extreme risk spillover in the energy markets: A time-varying copula-based CoVaR approach, Energy Econ., 76, 115, 10.1016/j.eneco.2018.10.010 Jin, 2019, Global oil shocks and China’s commodity markets: the role of OVX, Emerg. Mark. Financ. Trade Jurado, 2015, Measuring uncertainty, Am. Econ. Rev., 105, 1177, 10.1257/aer.20131193 Kang, 2015, The impact of oil price shocks on the stock market return and volatility relationship, J. Int. Financ. Mark. Inst. Money, 34, 41, 10.1016/j.intfin.2014.11.002 Kang, 2017, Oil price shocks, policy uncertainty, and stock returns of oil and gas corporations, J. Int. Money Financ., 70, 344, 10.1016/j.jimonfin.2016.10.003 Kang, 2019, The asymmetric response of gasoline prices to oil price shocks and policy uncertainty, Energy Econ., 77, 66, 10.1016/j.eneco.2018.09.007 Kang, 2020, Impact of global uncertainty on the global economy and large developed and developing economies, Appl. Econ., 52, 2392, 10.1080/00036846.2019.1690629 Karagianni, 2012, Tax burden distribution and GDP growth: non-linear causality considerations in the USA, Int. Rev. Econ. Financ., 21, 186, 10.1016/j.iref.2011.06.002 Kido, 2018, The transmission of US economic policy uncertainty shocks to Asian and global financial markets, North Am. J. Econ. Finan., 46, 222, 10.1016/j.najef.2018.04.008 Lee, 2019, Do country risk and financial uncertainty matter for energy commodity futures?, J. Futur. Mark., 39, 366, 10.1002/fut.21976 Lei, 2019, Does the financial crisis change the economic risk perception of crude oil traders? A MIDAS quantile regression approach, Financ. Res. Lett., 30, 341, 10.1016/j.frl.2018.10.016 Li, 2018, The dependence and risk spillover between crude oil market and China stock market: new evidence from a variational mode decomposition-based copula method, Energy Econ., 74, 565, 10.1016/j.eneco.2018.07.011 Li, 2020, Are Chinese crude oil futures good hedging tools?, Financ. Res. Lett. Li, 2020, Which uncertainty is powerful to forecast crude oil market volatility? New evidence, Int. J. Financ. Econ. Liang, 2020, Which sentiment index is more informative to forecast stock market volatility? Evidence from China, Int. Rev. Financ. Anal., 71, 10.1016/j.irfa.2020.101552 Liang, 2020, Uncertainty and crude oil market volatility: New evidence, Appl. Econ., 52, 2945, 10.1080/00036846.2019.1696943 Liang, 2020, Is implied volatility more informative for forecasting realized volatility: An international perspective, J. Forecast., 39, 1253, 10.1002/for.2686 Liu, 2017, Dynamic return-volatility dependence and risk measure of CoVaR in the oil market: A time-varying mixed copula model, Energy Econ., 68, 53, 10.1016/j.eneco.2017.09.011 Liu, 2019, Revisiting the integration of China into the world crude oil market: the role of structural breaks, Front. Energy Res., 7, 146, 10.3389/fenrg.2019.00146 Ludvigson, 2020, Uncertainty and business cycles: Exogenous impulse or endogenous response?, Am. Econ. J. Macroecon. Lv, 2020, Do the crude oil futures of the Shanghai International Energy Exchange improve asset allocation of Chinese petrochemical-related stocks?, Int. Rev. Financ. Anal., 71, 10.1016/j.irfa.2020.101537 Ma, 2018, Is economic policy uncertainty important to forecast the realized volatility of crude oil futures?, Appl. Econ., 50, 2087, 10.1080/00036846.2017.1388909 Ma, 2018, Forecasting the volatility of crude oil futures using high-frequency data: Further evidence, Empir. Econ., 55, 653, 10.1007/s00181-017-1294-6 Ma, 2018, Forecasting realized volatility of oil futures market: a new insight, J. Forecast., 37, 419, 10.1002/for.2511 Ma, 2019, Oil financialization and volatility forecast: Evidence from multidimensional predictors, J. Forecast., 38, 564, 10.1002/for.2577 Naifar, 2016, Do global financial distress and uncertainties impact GCC and global sukuk return dynamics?, Pac. Basin Financ. J., 39, 57, 10.1016/j.pacfin.2016.05.016 Nazlioglu, 2015, Oil prices and financial stress: a volatility spillover analysis, Energy Policy, 82, 278, 10.1016/j.enpol.2015.01.003 Nishiyama, 2011, A consistent nonparametric test for nonlinear causality: Specification in time series regression, J. Econ., 165, 112, 10.1016/j.jeconom.2011.05.010 Palao, 2020, Is the leadership of the Brent-WTI threatened by China’s new crude oil futures market?, J. Asian Econ., 70, 10.1016/j.asieco.2020.101237 Qin, 2020, The stability of US economic policy: does it really matter for oil price?, Energy, 198 Ratti, 2016, Oil prices and global factor macroeconomic variables, Energy Econ., 59, 198, 10.1016/j.eneco.2016.06.002 Reboredo, 2016, Do financial stress and policy uncertainty have an impact on the energy and metals markets? A quantile regression approach, Int. Rev. Econ. Financ., 43, 284, 10.1016/j.iref.2015.10.043 Rehman, 2019, Energy and non-energy commodities: an asymmetric approach towards portfolio diversification in the commodity market, Res. Policy, 63 Robe, 2016, Fundamentals, derivatives market information and oil price volatility, J. Futur. Mark., 36, 317, 10.1002/fut.21732 Sari, 2011, Do global risk perceptions influence world oil prices?, Energy Econ., 33, 515, 10.1016/j.eneco.2010.12.006 Shafiullah, 2020, Quantile causality and dependence between crude oil and precious metal prices, Int. J. Financ. Econ. Shaikh, 2019, On the relationship between economic policy uncertainty and the implied volatility index, Sustainability, 11, 1628, 10.3390/su11061628 Shaikh, 2020, Does policy uncertainty affect equity, commodity, interest rates, and currency markets? Evidence from CBOE’s volatility index, J. Bus. Econ. Manag., 21, 1350, 10.3846/jbem.2020.13164 Song, 2019, The co-movement between Chinese oil market and other main international oil markets: a DCC-MGARCH approach, Comput. Econ., 54, 1303, 10.1007/s10614-016-9564-5 Troster, 2019, A quantile regression analysis of flights-to-safety with implied volatilities, Res. Policy, 62, 482, 10.1016/j.resourpol.2018.10.004 Wang, 2018, Asymmetric volatility spillovers between crude oil and international financial markets, Energy Econ., 74, 592, 10.1016/j.eneco.2018.06.022 Wang, 2019, Multifractal characteristics analysis of crude oil futures prices fluctuation in China, Physica A Stat. Mech. Appl., 533, 10.1016/j.physa.2019.122021 Wei, 2017, Which determinant is the most informative in forecasting crude oil market volatility: fundamental, speculation, or uncertainty?, Energy Econ., 68, 141, 10.1016/j.eneco.2017.09.016 Wei, 2019, Oil price fluctuation, stock market and macroeconomic fundamentals: evidence from China before and after the financial crisis, Financ. Res. Lett., 30, 23, 10.1016/j.frl.2019.03.028 Wei, 2020, Can CBOE gold and silver implied volatility help to forecast gold futures volatility in China? Evidence based on HAR and Ridge regression models, Financ. Res. Lett., 35, 10.1016/j.frl.2019.09.002 Wen, 2019, Forecasting realized volatility of crude oil futures with equity market uncertainty, Appl. Econ., 51, 6411, 10.1080/00036846.2019.1619023 Wu, 2020, Study on the optimal hedging ratio of Shanghai crude oil futures based on Copula models, Asia-Pac. J. Account. Econ. Xu, 2019, Asymmetric volatility spillovers between oil and stock markets: evidence from China and the United States, Energy Econ., 80, 310, 10.1016/j.eneco.2019.01.014 Yang, 2020, Return and volatility transmission between China’s and international crude oil futures markets: a first look, J. Futur. Mark., 40, 860, 10.1002/fut.22103 Yang, 2020, The pricing efficiency of crude oil futures in the Shanghai International Exchange, Financ. Res. Lett., 36, 10.1016/j.frl.2019.101329 Yang, 2020, Extreme risk spillover between chinese and global crude oil futures, Financ. Res. Lett. Yang, 2021, Geopolitical risk and renewable energy stock markets: an insight from multiscale dynamic risk spillover, J. Clean. Prod., 279 Zhang, 2018, Energy finance: background, concept, and recent developments, Emerg. Mark. Financ. Trade, 54, 1687, 10.1080/1540496X.2018.1466524 Zhang, 2019, Are Chinese and international oil markets integrated?, Int. Rev. Econ. Financ., 62, 41, 10.1016/j.iref.2019.02.015 Zhang, 2019, Energy finance: frontiers and future development, Energy Econ., 83, 290, 10.1016/j.eneco.2019.07.003 Zhang, 2017, “De-financialization” of commodities? Evidence from stock, crude oil and natural gas markets, Energy Econ., 68, 228, 10.1016/j.eneco.2017.09.024 Zhang, 2019, Improving forecasting performance of realized covariance with extensions of HAR-RCOV model: statistical significance and economic value, Quant. Finan., 19, 1425, 10.1080/14697688.2019.1585561 Zhang, 2019, Forecasting oil price volatility: Forecast combination versus shrinkage method, Energy Econ., 80, 423, 10.1016/j.eneco.2019.01.010 Zhang, 2020, Forecasting the Chinese stock market volatility with international market volatilities: the role of regime switching, North Am. J. Econ. Finan., 52, 101145, 10.1016/j.najef.2020.101145