IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i5p1893-d764268.html
   My bibliography  Save this article

On the Dynamic Connectedness of the Stock, Oil, Clean Energy, and Technology Markets

Author

Listed:
  • Amirreza Attarzadeh

    (Department of Economics, Eastern Mediterranean University, North Cyprus, Via Mersin 10, Famagusta 99628, Turkey)

  • Mehmet Balcilar

    (Department of Economics, Eastern Mediterranean University, North Cyprus, Via Mersin 10, Famagusta 99628, Turkey
    Department of Economics, OSTIM Technical University, Ankara 06374, Turkey)

Abstract

Using monthly data from September 2004 to February 2020, this paper investigates the connectedness of the renewable energy, common stock, oil, and technology markets. The time-domain Diebold and Yilmaz spillover index approach is used to analyze the volatility spillover between these four markets. The study’s findings reveal that the oil and clean energy markets have bidirectional volatility spillover. The oil market has been found to be a net receiver of volatility. Furthermore, the study shows that volatility spillover is stronger in extreme positive and negative shock periods than in medium shock periods. Our findings show that, during crisis periods, the volatility spillover index rises, while the total connection reached its lowest point in 2015. Our findings suggest that policymakers should be informed that, as long as oil prices remain low, alternative energy-producing industries will not require specific policies to mitigate their vulnerability to crude oil price shocks. However, large spillover in the tails—particularly in the right tail—indicates vulnerability to extreme events, such as the negative effect of oil price increases.

Suggested Citation

  • Amirreza Attarzadeh & Mehmet Balcilar, 2022. "On the Dynamic Connectedness of the Stock, Oil, Clean Energy, and Technology Markets," Energies, MDPI, vol. 15(5), pages 1-18, March.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1893-:d:764268
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/5/1893/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/5/1893/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    2. Elie, Bouri & Naji, Jalkh & Dutta, Anupam & Uddin, Gazi Salah, 2019. "Gold and crude oil as safe-haven assets for clean energy stock indices: Blended copulas approach," Energy, Elsevier, vol. 178(C), pages 544-553.
    3. Paramati, Sudharshan Reddy & Ummalla, Mallesh & Apergis, Nicholas, 2016. "The effect of foreign direct investment and stock market growth on clean energy use across a panel of emerging market economies," Energy Economics, Elsevier, vol. 56(C), pages 29-41.
    4. Karanfil, Fatih, 2009. "How many times again will we examine the energy-income nexus using a limited range of traditional econometric tools?," Energy Policy, Elsevier, vol. 37(4), pages 1191-1194, April.
    5. Balcilar, Mehmet & Ozdemir, Zeynel Abidin, 2013. "The causal nexus between oil prices and equity market in the U.S.: A regime switching model," Energy Economics, Elsevier, vol. 39(C), pages 271-282.
    6. Reboredo, Juan C. & Ugolini, Andrea, 2018. "The impact of energy prices on clean energy stock prices. A multivariate quantile dependence approach," Energy Economics, Elsevier, vol. 76(C), pages 136-152.
    7. Managi, Shunsuke & Okimoto, Tatsuyoshi, 2013. "Does the price of oil interact with clean energy prices in the stock market?," Japan and the World Economy, Elsevier, vol. 27(C), pages 1-9.
    8. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    9. Ole E. Barndorff‐Nielsen & Neil Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
    10. Sadorsky, Perry, 2011. "Financial development and energy consumption in Central and Eastern European frontier economies," Energy Policy, Elsevier, vol. 39(2), pages 999-1006, February.
    11. Henriques, Irene & Sadorsky, Perry, 2008. "Oil prices and the stock prices of alternative energy companies," Energy Economics, Elsevier, vol. 30(3), pages 998-1010, May.
    12. Larissa Batrancea & Mircea Iosif Rus & Ema Speranta Masca & Ioan Dan Morar, 2021. "Fiscal Pressure as a Trigger of Financial Performance for the Energy Industry: An Empirical Investigation across a 16-Year Period," Energies, MDPI, vol. 14(13), pages 1-17, June.
    13. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    14. Inchauspe, Julian & Ripple, Ronald D. & Trück, Stefan, 2015. "The dynamics of returns on renewable energy companies: A state-space approach," Energy Economics, Elsevier, vol. 48(C), pages 325-335.
    15. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    16. Mehmet Balcilar & Stelios Bekiros & Rangan Gupta, 2017. "The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method," Empirical Economics, Springer, vol. 53(3), pages 879-889, November.
    17. George Kouretas & Leonidas Zarangas, 2005. "Conditional autoregressive valu at risk by regression quantile: Estimatingmarket risk for major stock markets," Working Papers 0521, University of Crete, Department of Economics.
    18. Sadorsky, Perry, 2010. "The impact of financial development on energy consumption in emerging economies," Energy Policy, Elsevier, vol. 38(5), pages 2528-2535, May.
    19. Mehmet Balcilar & Zeynel Abidin Ozdemir & Huseyin Ozdemir, 2021. "Dynamic return and volatility spillovers among S&P 500, crude oil, and gold," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 153-170, January.
    20. Razmi, Seyedeh Fatemeh & Ramezanian Bajgiran, Bahareh & Behname, Mehdi & Salari, Taghi Ebrahimi & Razmi, Seyed Mohammad Javad, 2020. "The relationship of renewable energy consumption to stock market development and economic growth in Iran," Renewable Energy, Elsevier, vol. 145(C), pages 2019-2024.
    21. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    22. Ahmad, Wasim, 2017. "On the dynamic dependence and investment performance of crude oil and clean energy stocks," Research in International Business and Finance, Elsevier, vol. 42(C), pages 376-389.
    23. Sadorsky, Perry, 2012. "Correlations and volatility spillovers between oil prices and the stock prices of clean energy and technology companies," Energy Economics, Elsevier, vol. 34(1), pages 248-255.
    24. Ferrer, Román & Shahzad, Syed Jawad Hussain & López, Raquel & Jareño, Francisco, 2018. "Time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices," Energy Economics, Elsevier, vol. 76(C), pages 1-20.
    25. Kumar, Surender & Managi, Shunsuke & Matsuda, Akimi, 2012. "Stock prices of clean energy firms, oil and carbon markets: A vector autoregressive analysis," Energy Economics, Elsevier, vol. 34(1), pages 215-226.
    26. Bondia, Ripsy & Ghosh, Sajal & Kanjilal, Kakali, 2016. "International crude oil prices and the stock prices of clean energy and technology companies: Evidence from non-linear cointegration tests with unknown structural breaks," Energy, Elsevier, vol. 101(C), pages 558-565.
    27. Tao, Zaipu & Li, Mingyu, 2007. "System dynamics model of Hubbert Peak for China's oil," Energy Policy, Elsevier, vol. 35(4), pages 2281-2286, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rui Dias & Nuno Teixeira & Paulo Alexandre & Mariana Chambino, 2023. "Exploring the Connection between Clean and Dirty Energy: Implications for the Transition to a Carbon-Resilient Economy," Energies, MDPI, vol. 16(13), pages 1-21, June.
    2. Manivannan Babu & C. Hariharan & S. Srinivasan & P. S. Shabi Shimny & Gayathri Jayapal & G. Indhumathi & J. Sathya & Brintha Rajendran & Veeramani Anandhabalaji & Chinnadurai Kathiravan, 2023. "Return and Volatility Spillovers of Asian Pacific Stock Markets Energy Indices," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 61-66, January.
    3. Talat S. Genc & Stephen Kosempel, 2023. "Energy Transition and the Economy: A Review Article," Energies, MDPI, vol. 16(7), pages 1-26, March.
    4. Si Mohammed, K. & Mellit, A., 2023. "The relationship between oil prices and the indices of renewable energy and technology companies based on QQR and GCQ techniques," Renewable Energy, Elsevier, vol. 209(C), pages 97-105.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Capucine Nobletz, 2021. "Return spillovers between green energy indexes and financial markets: a first sectoral approach," EconomiX Working Papers 2021-24, University of Paris Nanterre, EconomiX.
    2. Çelik, İsmail & Sak, Ahmet Furkan & Höl, Arife Özdemir & Vergili, Gizem, 2022. "The dynamic connectedness and hedging opportunities of implied and realized volatility: Evidence from clean energy ETFs," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    3. Matteo Foglia & Eliana Angelini, 2020. "Volatility Connectedness between Clean Energy Firms and Crude Oil in the COVID-19 Era," Sustainability, MDPI, vol. 12(23), pages 1-22, November.
    4. Urom, Christian & Mzoughi, Hela & Ndubuisi, Gideon & Guesmi, Khaled, 2022. "Directional predictability and time-frequency spillovers among clean energy sectors and oil price uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 326-341.
    5. Umar, Muhammad & Farid, Saqib & Naeem, Muhammad Abubakr, 2022. "Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis," Energy, Elsevier, vol. 240(C).
    6. Tiantian Liu & Shigeyuki Hamori, 2020. "Spillovers to Renewable Energy Stocks in the US and Europe: Are They Different?," Energies, MDPI, vol. 13(12), pages 1-28, June.
    7. Tan, Xueping & Geng, Yong & Vivian, Andrew & Wang, Xinyu, 2021. "Measuring risk spillovers between oil and clean energy stocks: Evidence from a systematic framework," Resources Policy, Elsevier, vol. 74(C).
    8. Saeed, Tareq & Bouri, Elie & Alsulami, Hamed, 2021. "Extreme return connectedness and its determinants between clean/green and dirty energy investments," Energy Economics, Elsevier, vol. 96(C).
    9. Fernanda Fuentes & Rodrigo Herrera, 2020. "Dynamics of Connectedness in Clean Energy Stocks," Energies, MDPI, vol. 13(14), pages 1-19, July.
    10. Elsayed, Ahmed H. & Nasreen, Samia & Tiwari, Aviral Kumar, 2020. "Time-varying co-movements between energy market and global financial markets: Implication for portfolio diversification and hedging strategies," Energy Economics, Elsevier, vol. 90(C).
    11. Naeem, Muhammad Abubakr & Peng, Zhe & Suleman, Mouhammed Tahir & Nepal, Rabindra & Shahzad, Syed Jawad Hussain, 2020. "Time and frequency connectedness among oil shocks, electricity and clean energy markets," Energy Economics, Elsevier, vol. 91(C).
    12. Dai, Zhifeng & Zhu, Haoyang & Zhang, Xinhua, 2022. "Dynamic spillover effects and portfolio strategies between crude oil, gold and Chinese stock markets related to new energy vehicle," Energy Economics, Elsevier, vol. 109(C).
    13. Ferrer, Román & Shahzad, Syed Jawad Hussain & López, Raquel & Jareño, Francisco, 2018. "Time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices," Energy Economics, Elsevier, vol. 76(C), pages 1-20.
    14. Ahmad, Wasim, 2017. "On the dynamic dependence and investment performance of crude oil and clean energy stocks," Research in International Business and Finance, Elsevier, vol. 42(C), pages 376-389.
    15. Dan Nie & Yanbin Li & Xiyu Li & Xuejiao Zhou & Feng Zhang, 2022. "The Dynamic Spillover between Renewable Energy, Crude Oil and Carbon Market: New Evidence from Time and Frequency Domains," Energies, MDPI, vol. 15(11), pages 1-28, May.
    16. Niu, Hongli, 2021. "Correlations between crude oil and stocks prices of renewable energy and technology companies: A multiscale time-dependent analysis," Energy, Elsevier, vol. 221(C).
    17. Ahmed, Walid M.A. & Sleem, Mohamed A.E., 2023. "Short- and long-run determinants of the price behavior of US clean energy stocks: A dynamic ARDL simulations approach," Energy Economics, Elsevier, vol. 124(C).
    18. Fahmy, Hany, 2022. "The rise in investors’ awareness of climate risks after the Paris Agreement and the clean energy-oil-technology prices nexus," Energy Economics, Elsevier, vol. 106(C).
    19. Çevik, Emre & Çevik, Emrah İsmail & Dibooglu, Sel & Cergibozan, Raif & Bugan, Mehmet Fatih & Destek, Mehmet Akif, 2022. "Connectedness and risk spillovers between crude oil and clean energy stock markets," MPRA Paper 117558, University Library of Munich, Germany.
    20. Tiantian Liu & Shigeyuki Hamori, 2021. "Does Investor Sentiment Affect Clean Energy Stock? Evidence from TVP-VAR-Based Connectedness Approach," Energies, MDPI, vol. 14(12), pages 1-21, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1893-:d:764268. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.