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Regional and copula estimation effects on EU and US energy equity portfolios

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  • Waqas Hanif
  • Jose Arreola-Hernandez
  • Syed Jawad Hussain Shahzad
  • Thi Hong Van Hoang
  • Seong-Min Yoon

Abstract

The aim of this paper is to investigate the regional interdependence structure of energy equities in the US and in the EU. Based on weekly stock prices of 28 big energy firms in the two regions from 2008 to 2019, we compare the efficiency of using bivariate or multivariate copulas to describe the dependence structure of energy equities. Furthermore, we investigate the impact of the choice between these two methods on the performance of energy equity portfolios. Our empirical results show that multivariate copulas, such as C-Vine, allow to better describe the dependence structure of energy equities. We also find that there is a stronger and more complex dependence structure among EU energy equities than among US energy equities. Our scenario analysis also shows that the dependence structure is stronger during the GFC while being weaker during the ESDC. More importantly, the correlation matrix obtained from the multivariate copula method allows to obtain optimal mean-CVaR portfolios with a higher performance than that from the bivariate copula method. More importantly, optimal portfolios constituted with multivariate copulas allow to reduce the portfolio’s sensitivity to oil prices.

Suggested Citation

  • Waqas Hanif & Jose Arreola-Hernandez & Syed Jawad Hussain Shahzad & Thi Hong Van Hoang & Seong-Min Yoon, 2020. "Regional and copula estimation effects on EU and US energy equity portfolios," Applied Economics, Taylor & Francis Journals, vol. 52(49), pages 5311-5342, October.
    • Handle: RePEc:taf:applec:v:52:y:2020:i:49:p:5311-5342
    DOI: 10.1080/00036846.2020.1763244
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    Cited by:

    1. Izabela Horzela & Sławomir Gromadzki & Jarosław Gryz & Tomasz Kownacki & Aneta Nowakowska-Krystman & Marzena Piotrowska-Trybull & Radosław Wisniewski, 2021. "Energy Portfolio of the Eastern Poland Macroregion in the European Union," Energies, MDPI, vol. 14(24), pages 1-28, December.
    2. Tian, Maoxi & Alshater, Muneer M. & Yoon, Seong-Min, 2022. "Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model," Energy Economics, Elsevier, vol. 115(C).
    3. Radu Lupu & Adrian Cantemir Călin & Cristina Georgiana Zeldea & Iulia Lupu, 2021. "Systemic Risk Spillovers in the European Energy Sector," Energies, MDPI, vol. 14(19), pages 1-23, October.
    4. Ki-Hong Choi & Insin Kim, 2021. "Co-Movement between Tourist Arrivals of Inbound Tourism Markets in South Korea: Applying the Dynamic Copula Method Using Secondary Time Series Data," Sustainability, MDPI, vol. 13(3), pages 1-13, January.

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