Exploring the asymmetric effects of economic policy uncertainty and implied volatilities on energy futures returns: novel insights from quantile-on-quantile regression
Abstract
This study examined the asymmetric effects of major uncertainty and volatility indices (economic policy uncertainty, Chicago Board Options Exchange crude oil volatility, CBOE volatility index, CBOE VIX volatility, and NASDAQ 100 volatility target) on the returns of global energy and its constituents (global energy index, Brent, heating oil, natural gas, and petroleum). The causalityin-quantiles test and the quantile-on-quantile regression technique were employed on daily data covering the period between April 2012 and March 2022. The findings evidenced asymmetries and heterogeneity in the causal effects of global uncertainty and market volatilities on energy markets. For all uncertainty and volatility measures, we found strong negative relationships with energy commodities at stressed conditions, signalling some hedging benefits for market participants. The current research is among the first investigations to explore the asymmetric relationships between major uncertainty and volatility indices, as well as global energy and its constituents. Essential portfolio implications of our findings are discussed.
Keyword : energy commodities, energy markets, uncertainty indices, volatility indices, causality-in-quantiles, quantile-on-quantile regression
How to Cite
Bossman, A., Gherghina, Ştefan C., Asafo-Adjei, E., Adam, A. M., & Agyei, S. K. (2022). Exploring the asymmetric effects of economic policy uncertainty and implied volatilities on energy futures returns: novel insights from quantile-on-quantile regression. Journal of Business Economics and Management, 23(6), 1351–1376. https://doi.org/10.3846/jbem.2022.18282
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Bossman, A. (2021). Information flow from COVID-19 pandemic to Islamic and conventional equities: An ICEEMDAN-induced transfer entropy analysis. Complexity, 2021, 4917051. https://doi.org/10.1155/2021/4917051
Bossman, A., & Agyei, S. K. (2022a). ICEEMDAN-based transfer entropy between global commodity classes and African equities. Mathematical Problems in Engineering, 2022, 8964989. https://doi.org/10.1155/2022/8964989
Bossman, A., & Agyei, S. K. (2022b). Interdependence structure of global commodity classes and African equity markets: A vector wavelet coherence analysis. Resources Policy, 79, 103039. https://doi.org/10.1016/j.resourpol.2022.103039
Bossman, A., Gubareva, M., & Teplova, T. (2023). Asymmetric effects of geopolitical risk on major currencies: Russia-Ukraine tensions. Finance Research Letters, 51, 103440. https://doi.org/10.1016/j.frl.2022.103440
Bossman, A., Owusu Junior, P., & Tiwari, A. K. (2022a). Dynamic connectedness and spillovers between Islamic and conventional stock markets: Time- and frequency-domain approach in COVID-19 era. Heliyon, 8(4). https://doi.org/10.1016/j.heliyon.2022.e09215
Bossman, A., Umar, Z., & Teplova, T. (2022b). Modelling the asymmetric effect of COVID-19 on REIT returns: A quantile-on-quantile regression analysis. The Journal of Economic Asymmetries, 26, e00257. https://doi.org/10.1016/j.jeca.2022.e00257
Broock, W. A., Scheinkman, J. A., Dechert, W. D., & LeBaron, B. (1996). A test for independence based on the correlation dimension. Econometric Reviews, 15(3), 197–235. https://doi.org/10.1080/07474939608800353
Chen, Z., Liang, C., & Umar, M. (2021). Is investor sentiment stronger than VIX and uncertainty indices in predicting energy volatility? Resources Policy, 74, 102391. https://doi.org/10.1016/j.resourpol.2021.102391
Domanski, D., & Heath, A. (2007). Financial investors and commodity markets. BIS Quarterly Review, March, 1–15. https://www.bis.org/publ/qtrpdf/r_qt0703g.htm
Dragomirescu-Gaina, C., & Philippas, D. (2022). Local versus global factors weighing on stock market returns during the COVID-19 pandemic. Finance Research Letters, 46(A), 102270. https://doi.org/10.1016/j.frl.2021.102270
El-Karimi, M., & El-Ghini, A. (2020). The transmission of global commodity prices to consumer prices in a commodity import-dependent country: Evidence from Morocco. Scientific Annals of Economics and Business, 67(1), 15–32.
Filimonova, I., Komarova, A., & Mishenin, M. (2020). Impact of the global green factor on the capitalization of oil companies in Russia. Oeconomia Copernicana, 11(2), 309–324. https://doi.org/10.24136/oc.2020.013
Hazgui, S., Sebai, S., & Mensi, W. (2021). Dynamic frequency relationships between bitcoin, oil, gold and economic policy uncertainty index. Studies in Economics and Finance, 39(3), 419–443. https://doi.org/10.1108/SEF-05-2021-0165
He, F., Ma, F., Wang, Z., & Yang, B. (2021). Asymmetric volatility spillover between oil-importing and oil-exporting countries’ economic policy uncertainty and China’s energy sector. International Review of Financial Analysis, 75, 101739. https://doi.org/10.1016/j.irfa.2021.101739
Huang, J., Dong, X., Zhang, H., Liu, J., & Gao, W. (2022). Dynamic and frequency-domain spillover among within and cross-country policy uncertainty, crude oil and gold market: Evidence from US and China. Resources Policy, 78, 102938. https://doi.org/10.1016/j.resourpol.2022.102938
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