Mariana Chambino – Polytechnic Institute of Setúbal, (ESCE/IPS), 2910-761 Setúbal, Portugal

Rui Dias – Polytechnic Institute of Setúbal, (ESCE/IPS), 2910-761 Setúbal, Portugal; Center of Advanced Studies in Management and Economics, University of Évora, 7004-516 Évora, Portugal

Cristina Morais da Palma – Polytechnic Institute of Setúbal, (ESCE/IPS), 2910-761 Setúbal, Portugal

Keywords:                     Clean energy stocks;
Oil prices;
Hedge;
Portfolio diversification

DOI: https://doi.org/10.31410/ERAZ.2023.57

Abstract: This paper analyses whether clean energy stock indexes, name­ly WilderHill Clean Energy, Clean Energy Fuels, and Nasdaq Clean Edge Green Energy indexes, can be considered coverage assets for the dirty ener­gy stock indexes such as the Brent Crude Spot and Euro Stoxx Oil & Gas in­dexes during the events that occurred in 2020 and 2022. The results suggest low levels of integration, which shows that clean energy indexes are isolat­ed. Based on these findings, the clean energy index may offer a better op­portunity to cover oil prices. However, it is important to highlight that mar­ket conditions, transaction costs, and asset performance affect hedge strat­egy returns. Therefore, it is important to carefully assess the potential risks and benefits of any hedge strategy before making investment decisions. In addition, past performance does not guarantee future results, and market conditions can change quickly and unpredictably.

9th International Scientific ERAZ Conference – ERAZ 2023 – Conference Proceedings: KNOWLEDGE BASED SUSTAINABLE DEVELOPMENT, hybrid – online, virtually and in person, Prague, Czech Republic, June 1, 2023

ERAZ Conference Proceedings published by: Association of Economists and Managers of the Balkans – Belgrade, Serbia

ERAZ conference partners: Faculty of Logistics, University of Maribor, Maribor (Slovenia); University of National and World Economy – UNWE, Sofia (Bulgaria); Center for Political Research and Documentation (KEPET), Research Laboratory of the Department of Political Science of University of Crete (Greece); Institute of Public Finance – Zagreb (Croatia); Faculty of Tourism and Hospitality Ohrid, University of St. Kliment Ohridski from Bitola (North Macedonia)

ERAZ Conference 2023 Conference Proceedings: ISBN 978-86-80194-72-1, ISSN 2683-5568, DOI: https://doi.org/10.31410/ERAZ.2023

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission. 

Suggested citation

Chambino, M., Dias, R., & Morais da Palma, C. (2023). Will There Be Dependencies between Oil Prices and Clean Energy Indexes?. In V. Bevanda (Ed.), ERAZ Conference – Knowlegde Based Sustainable Development: Vol 9. Conference Proceedings (pp. 57-65). Association of Economists and Managers of the Balkans. https://doi.org/10.31410/ERAZ.2023.57

References

Arfaoui, N., Naeem, M. A., Boubaker, S., Mirza, N., & Karim, S. (2023). Interdependence of clean en­ergy and green markets with cryptocurrencies. Energy Economics, 120. https://doi.org/10.1016/j.eneco.2023.106584

Choi, I. (2001). Unit root tests for panel data. Journal of International Money and Finance, 20(2), 249–272. https://doi.org/10.1016/S0261-5606(00)00048-6

Dias, R., da Silva, J. V., & Dionísio, A. (2019). Financial markets of the LAC region: Does the cri­sis influence the financial integration? International Review of Financial Analysis, 63, 160-173. https://doi.org/10.1016/j.irfa.2019.02.008

Dias, R., Horta, N., & Chambino, M. (2023). Clean Energy Action Index Efficiency: An Analysis in Global Uncertainty Contexts. Energies, 16(9). https://doi.org/10.3390/en16093937

Dias, R., Pardal, P., Teixeira, N., & Machová, V. (2020). Financial Market Integration of ASEAN-5 with China. Littera Scripta, 13(1). https://doi.org/10.36708/littera_scripta2020/1/4

Dias, R., Pereira, J. M., & Carvalho, L. C. (2022). Are African Stock Markets Efficient? A Compara­tive Analysis Between Six African Markets, the UK, Japan and the USA in the Period of the Pan­demic. Naše gospodarstvo/Our economy, 68(1), 35-51. https://doi.org/10.2478/ngoe-2022-0004

Dias, R., Santos, H., Heliodoro, P., Vasco, C., & Alexandre, P. (2021). Wti Oil Shocks in Eastern Eu­ropean Stock Markets: A Var Approach. 5th EMAN Conference Proceedings (Part of EMAN Conference Collection), October, 71–84. https://doi.org/10.31410/eman.2021.71

Dias, R. T., & Carvalho, L. (2021). The Relationship Between Gold and Stock Markets During the COVID-19 Pandemic. May, 462–475. https://doi.org/10.4018/978-1-7998-6643-5.ch026

Dias, R. T., Pardal, P., Teixeira, N., & Horta, N. R. (2022). Tail Risk and Return Predictability for Europe’s Capital Markets: An Approach in Periods of the 2020 and 2022 Crises. Advanc­es in Human Resources Management and Organizational Development, 281-298. https://doi.org/10.4018/978-1-6684-5666-8.ch015 

Dickey, D., & Fuller, W. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057–1072. https://doi.org/10.2307/1912517 

Farid, S., Karim, S., Naeem, M. A., Nepal, R., & Jamasb, T. (2023). Co-movement between dirty and clean energy: A time-frequency perspective. Energy Economics, 119. https://doi.org/10.1016/j.eneco.2023.106565 

Guedes, E. F., Santos, R. P. C., Figueredo, L. H. R., Da Silva, P. A., Dias, R. M. T. S., & Zebende, G. F. (2022). Efficiency and Long-Range Correlation in G-20 Stock Indexes: A Sliding Windows Approach. Fluctuation and Noise Letters. https://doi.org/10.1142/S021947752250033X

Hadri, K. (2000). Testing for stationarity in heterogeneous panel data. The Econometrics Journal. https://doi.org/10.1111/1368-423x.00043 

Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and seri­al independence of regression residuals. Economics Letters, 6(3), 255–259. https://doi.org/10.1016/0165-1765(80)90024-5 

Kumar, S., Managi, S., & Matsuda, A. (2012). Stock prices of clean energy firms, oil and carbon markets: A vector autoregressive analysis. Energy Economics, 34(1). https://doi.org/10.1016/j.eneco.2011.03.002 

Managi, S., & Okimoto, T. (2013). Does the price of oil interact with clean energy prices in the stock market? Japan and the World Economy, 27. https://doi.org/10.1016/j.japwor.2013.03.003 

Pardal, P., Dias, R., Teixeira, N., & Horta, N. (2022). The Effects of Russia’ s 2022 Invasion of Ukraine on Global Markets : An Analysis of Particular Capital and Foreign Exchange Markets. https://doi.org/10.4018/978-1-6684-56668.ch014  

Pardal, P., Dias, R. T., Santos, H., & Vasco, C. (2021). Central European banking sector integration and shocks during the global pandemic (COVID-19). In Handbook of Research on Reinventing Economies and Organizations Following a Global Health Crisis. https://doi.org/10.4018/978-1-7998-6926-9.ch015  

Peng, C. K., Buldyrev, S. V., Havlin, S., Simons, M., Stanley, H. E., & Goldberger, A. L. (1994). Mosaic organization of DNA nucleotides. Physical Review E, 49(2), 1685–1689. https://doi.org/10.1103/PhysRevE.49.1685  

Podobnik, B., & Stanley, H. E. (2008). Detrended cross-correlation analysis: A new method for ana­lyzing two nonstationary time series. Physical Review Letters, 100(8). https://doi.org/10.1103/PhysRevLett.100.084102  

Ren, B., & Lucey, B. (2022). A clean, green haven? – Examining the relationship between clean energy, clean and dirty cryptocurrencies. Energy Economics, 109. https://doi.org/10.1016/j.eneco.2022.105951  

Saeed, T., Bouri, E., & Vo, X. V. (2020). Hedging strategies of green assets against dirty energy as­sets. Energies, 13(12). https://doi.org/10.3390/en13123141 

Santana, T., Horta, N., Revez, C., Santos Dias, R. M. T., & Zebende, G. F. (2023). Effects of Inter­dependence and Contagion on Crude Oil and Precious Metals According to ρDCCA: A COV­ID-19 Case Study. 1–11.

Sharif, A., Brahim, M., Dogan, E., & Tzeremes, P. (2023). Analysis of the spillover effects be­tween green economy, clean and dirty cryptocurrencies. Energy Economics, 120. https://doi.org/10.1016/j.eneco.2023.106594 

Silva, R., Dias, R., Heliodoro, P., & Alexandre, P. (2020). Risk Diversification in Asean-5 Financial Markets: an Empirical Analysis in the Context of the Global Pandemic (COVID-19). 6th LIMEN Selected Papers (Part of LIMEN Conference Collection), 6, 15–26. https://doi.org/10.31410/limen.s.p.2020.15 

Teixeira, N., Dias, R., & Pardal, P. (2022). The gold market as a safe haven when stock markets ex­hibit pronounced levels of risk : evidence during the China crisis and the COVID-19 pandem­ic. April, 27–42.

Teixeira, N., Dias, R., Pardal, P., & Horta, N. (2022). Financial Integration and Comovements Be­tween Capital Markets and Oil Markets : An Approach During the Russian. December. https://doi.org/10.4018/978-1-6684-5666-8.ch013  

Zebende, G. F. (2011). DCCA cross-correlation coefficient: Quantifying level of cross-correlation. Physica A: Statistical Mechanics and Its Applications. https://doi.org/10.1016/j.physa.2010.10.022 

Zebende, G. F., Santos Dias, R. M. T., & de Aguiar, L. C. (2022). Stock market efficiency: An intr­aday case of study about the G-20 group. Heliyon, 8(1), e08808. https://doi.org/10.1016/j.heli­yon.2022.e08808