Dergiler / Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty / 2026 / Volume: 12 Issue: 3

Return Transmission among Fossil Energy Commodities, Clean Energy Stocks, Green Bonds, and Energy Cryptocurrency

Pinar Evrim Mandacı(Dokuz Eylül Üniversitesi Faculty of Business)0000-0002-9805-9937
Birce Tedik Kocakaya(IZMIR UNIVERSITY OF ECONOMICS)0000-0003-3611-6892
Efe Çağlar Çağlı(Dokuz Eylül Üniversitesi)0000-0002-8250-141X
Sayfa
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Yayın Tarihi
2025-09-30
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

These conclusions have important implications for investors and policymakers.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:This paper investigates return transmission among fossil energy commodities (crude oil, natural gas, gas oil, unleaded gasoline, and heating oil), clean energy stocks, green bonds, and energy cryptocurrency markets.
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Temel Bulgular & Veri:We employ the TVP-VAR frequency connectedness technique for the period from November 12, 2017, to September 28, 2023.
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Sonuç & Katkı:These conclusions have important implications for investors and policymakers.
🔬Tür:Research Article
📍Kapsam:2017 Verileri
⚙️Değişkenler:Green markets · Energy market · Energy cryptocurrency

Abstract

This paper investigates return transmission among fossil energy commodities (crude oil, natural gas, gas oil, unleaded gasoline, and heating oil), clean energy stocks, green bonds, and energy cryptocurrency markets. We consider Bloomberg’s fossil energy subindices to proxy various energy commodities. We use the WilderHill Clean Energy Index (ECO) and Solactive Green Bond Index (GB) as proxies for clean energy stocks and green bonds. In addition, the Powerledger (POWR) coin is used to proxy energy cryptocurrency. We employ the TVP-VAR frequency connectedness technique for the period from November 12, 2017, to September 28, 2023. Our findings indicate a moderate level of interdependence with an apparent increase observed during the COVID-19 pandemic. Notably, short-term factors play a significant role in shaping this connectedness. Furthermore, the analysis identifies clean energy stocks, green bonds and energy cryptocurrencies as recipients, while all fossil energy commodities other than natural gas and gasoline are identified as transmitters. These conclusions have important implications for investors and policymakers.

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Bu Makaleye Atıf Yap

Mandacı, P. E., Kocakaya, B. T., Çağlı, E. Ç. (2025). Return Transmission among Fossil Energy Commodities, Clean Energy Stocks, Green Bonds, and Energy Cryptocurrency. Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty, Volume: 12 Issue: 3. https://doi.org/10.30798/makuiibf.1557183

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Kaynakça (60)

  1. Abuzayed, B., & Al-Fayoumi, N. (2023). Diversification and hedging strategies of green bonds in financial asset portfolios during the COVID-19 pandemic. Applied Economics, 55(36). https://doi.org/10.1080/00036846.2022.2128178
  2. Atri, H., Kouki, S., & Gallali, M. I. (2021). The impact of COVID-19 news, panic and media coverage on the oil and gold prices: An ARDL approach. Resources Policy, 72. https://doi.org/10.1016/j.resourpol.2021.102061
  3. Attarzadeh, A., & Balcilar, M. (2022). On the dynamic return and volatility connectedness of cryptocurrency, crude oil, clean energy, and stock markets: A time-varying analysis. Environmental Science and Pollution Research, 29(43), 65185-65196. https://doi.org/10.1007/s11356-022-20115-2
  4. Bouri, E., Jalkh, N., Molnár, P., & Roubaud, D. (2017). Bitcoin for energy commodities before and after the December 2013 crash: Diversifier, hedge or safe haven? Applied Economics, 49(50), 5063-5073. https://doi.org/10.1080/00036846.2017.1299102
  5. British Petroleum. (2024, July 10). BP Energy Outlook 2024. https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/energy-outlook/bp-energy-outlook-2024.pdf
  6. Cagli, E. C. (2023). The volatility spillover between battery metals and future mobility stocks: Evidence from the time-varying frequency connectedness approach. Resources Policy, 86. https://doi.org/10.1016/j.resourpol.2023.104144
  7. Chatziantoniou, I., Abakah, E. J. A., Gabauer, D., & Tiwari, A. K. (2022). Quantile time–frequency price connectedness between green bond, green equity, sustainable investments and clean energy markets. Journal of Cleaner Production, 361. https://doi.org/10.1016/j.jclepro.2022.132088
  8. Chatziantoniou, I., Gabauer, D., & Gupta, R. (2023). Integration and risk transmission in the market for crude oil: New evidence from a time-varying parameter frequency connectedness approach. Resources Policy, 84. https://doi.org/10.1016/j.resourpol.2023.103729
  9. Chatziantoniou, I., Gabauer, D., & Perez de Gracia, F. (2022). Tail risk connectedness in the refined petroleum market: A first look at the impact of the COVID-19 pandemic. Energy Economics, 111. https://doi.org/10.1016/j.eneco.2022.106051
  10. Companies Market Cap. (n.d.). Largest renewable energy companies by market cap. Retrieved July 8, 2024, from https://companiesmarketcap.com/renewable-energy/largest-companies-by-market-cap/
  11. Cryptoslate. (n.d.). Energy Cryptos. Retrieved September 12, 2024, from https://cryptoslate.com/cryptos/energy/
  12. Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1). https://doi.org/10.1016/j.ijforecast.2011.02.006
  13. Dogan, E., Madaleno, M., Taskin, D., & Tzeremes, P. (2022). Investigating the spillovers and connectedness between green finance and renewable energy sources. Renewable Energy, 197. https://doi.org/10.1016/j.renene.2022.07.131
  14. Dogra, G., & Murugaboopathy, P. (2022, March 31). Global green finance rises over 100 fold in the past decade -study. Reuters. https://www.reuters.com/business/sustainable-business/global-markets-greenfinance-graphics-2022-03-31/
  15. Elliott, G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient tests for an autoregressive unit root. Econometrica, 64(4). https://doi.org/10.2307/2171846
  16. European Commission. (2022, July). A European gas demand reduction plan. EU Commission. https://ec.europa.eu/commission/presscorner/api/files/attachment/873148/Factsheet_European%20Gas%20Demand%20Reduction.pdf
  17. Ferrer, R., Shahzad, S. J. H., López, R., & Jareño, F. (2018). Time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices. Energy Economics, 76. https://doi.org/10.1016/j.eneco.2018.09.022
  18. Fisher, T. J., & Gallagher, C. M. (2012). New weighted portmanteau statistics for time series goodness of fit testing. Journal of the American Statistical Association, 107(498). https://doi.org/10.1080/01621459.2012.688465
  19. Foglia, M., & Angelini, E. (2020). Volatility connectedness between clean energy firms and crude oil in the COVID-19 era. Sustainability (Switzerland), 12(23). https://doi.org/10.3390/su12239863
  20. Gargallo, P., Lample, L., Miguel, J., & Salvador, M. (2022). Dynamic comparison of portfolio risk: Clean vs dirty energy. Finance Research Letters, 47. https://doi.org/10.1016/j.frl.2022.102957
  21. Gök, R. (2025). Spillovers between cryptocurrency, DeFi, carbon, and energy markets: A frequency quantile-on-quantile perspective. The Quarterly Review of Economics and Finance, 100, 101954. https://doi.org/10.1016/j.qref.2024.101954
  22. Granger, C. W. J., & Jeon, Y. (2004). Forecasting performance of information criteria with many macro series. Journal of Applied Statistics, 31(10). https://doi.org/10.1080/0266476042000285495
  23. Hao, W., & Pham, L. (2024). Dynamic connectedness in the higher moments between clean energy and oil prices. Energy Economics, 140, 107987. https://doi.org/10.1016/j.eneco.2024.107987
  24. Henriques, I., & Sadorsky, P. (2008). Oil prices and the stock prices of alternative energy companies. Energy Economics, 30(3). https://doi.org/10.1016/j.eneco.2007.11.001
  25. International Energy Agency. (2023, March). CO2 Emissions in 2022. https://www.iea.org/reports/co2-emissions-in-2022
  26. International Finance Corporation, & Amundi Asset Management. (2025). Emerging Market Green Bonds 2024. https://www.ifc.org/content/dam/ifc/doc/2025/emerging-market-green-bonds-2024.pdf
  27. Jain, P., Maitra, D., McIver, R. P., & Kang, S. H. (2023). Quantile dependencies and connectedness between stock and precious metals markets. Journal of Commodity Markets, 30. https://doi.org/10.1016/j.jcomm.2022.100284
  28. Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3). https://doi.org/10.1016/0165-1765(80)90024-5
  29. Ji, Q., Bouri, E., Roubaud, D., & Kristoufek, L. (2019). Information interdependence among energy, cryptocurrency and major commodity markets. Energy Economics, 81. https://doi.org/10.1016/j.eneco.2019.06.005
  30. Le, T. H. (2023). Quantile time-frequency connectedness between cryptocurrency volatility and renewable energy volatility during the COVID-19 pandemic and Ukraine-Russia conflicts. Renewable Energy, 202, 613–625. https://doi.org/10.1016/j.renene.2022.11.062
  31. Lee, C. C., Lee, C. C., & Li, Y. Y. (2021). Oil price shocks, geopolitical risks, and green bond market dynamics. North American Journal of Economics and Finance, 55. https://doi.org/10.1016/j.najef.2020.101309
  32. Mensi, W., Selmi, R., Al-Kharusi, S., Belghouthi, H. E., & Kang, S. H. (2024). Connectedness between green bonds, conventional bonds, oil, heating oil, natural gas, and petrol: new evidence during bear and bull market scenarios. Resources Policy, 91. https://doi.org/10.1016/j.resourpol.2024.104888
  33. Naeem, M. A., Gul, R., Farid, S., Karim, S., & Lucey, B. M. (2023). Assessing linkages between alternative energy markets and cryptocurrencies. Journal of Economic Behavior & Organization, 211, 513–529. https://doi.org/10.1016/j.jebo.2023.04.035
  34. Naeem, M. A., Husain, A., Bossman, A., & Karim, S. (2024). Assessing the linkage of energy cryptocurrency with clean and dirty energy markets. Energy Economics, 130. https://doi.org/10.1016/j.eneco.2023.107279
  35. Naeem, M. A., Nguyen, T. T. H., Karim, S., & Lucey, B. M. (2023). Extreme downside risk transmission between green cryptocurrencies and energy markets: The diversification benefits. Finance Research Letters, 58. https://doi.org/10.1016/j.frl.2023.104263
  36. Naeem, M. A., Nguyen, T. T. H., Nepal, R., Ngo, Q. T., & Taghizadeh–Hesary, F. (2021). Asymmetric relationship between green bonds and commodities: Evidence from extreme quantile approach. Finance Research Letters, 43. https://doi.org/10.1016/j.frl.2021.101983
  37. Naifar, N. (2025). Interactions between renewable energy tokens, oil shocks, and clean energy investments: Do COP26 policies matter? Energy Policy, 198, 114497. https://doi.org/10.1016/j.enpol.2025.114497
  38. Nasreen, S., Tiwari, A. K., Eizaguirre, J. C., & Wohar, M. E. (2020). Dynamic connectedness between oil prices and stock returns of clean energy and technology companies. Journal of Cleaner Production, 260. https://doi.org/10.1016/j.jclepro.2020.121015
  39. Nguyen, T. T. H., Naeem, M. A., Balli, F., Balli, H. O., & Vo, X. V. (2021). Time-frequency comovement among green bonds, stocks, commodities, clean energy, and conventional bonds. Finance Research Letters, 40. https://doi.org/10.1016/j.frl.2020.101739
  40. Patel, R., Kumar, S., & Agnihotri, S. (2025). Unveiling the crypto-green nexus: A risk management and investment strategy approach through the lens of NFTs, DeFis, green cryptocurrencies, and green investments. The North American Journal of Economics and Finance, 75, 102289. https://doi.org/10.1016/j.najef.2024.102289
  41. Pham, L. (2021). Frequency connectedness and cross-quantile dependence between green bond and green equity markets. Energy Economics, 98. https://doi.org/10.1016/j.eneco.2021.105257
  42. Pham, S. D., Nguyen, T. T. T., & Do, H. X. (2024). Impact of climate policy uncertainty on return spillover among green assets and portfolio implications. Energy Economics, 134, 107631. https://doi.org/10.1016/j.eneco.2024.107631
  43. Qi, S., Pang, L., Li, X., & Huang, L. (2025). The dynamic connectedness in the “carbon-energy-green finance” system: The role of climate policy uncertainty and artificial intelligence. Energy Economics, 143, 108241. https://doi.org/10.1016/j.eneco.2025.108241
  44. Reboredo, J. C., Ugolini, A., & Aiube, F. A. L. (2020). Network connectedness of green bonds and asset classes. Energy Economics, 86. https://doi.org/10.1016/j.eneco.2019.104629
  45. 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
  46. Saeed, T., Bouri, E., & Alsulami, H. (2021). Extreme return connectedness and its determinants between clean/green and dirty energy investments. Energy Economics, 96. https://doi.org/10.1016/j.eneco.2020.105017
  47. Shao, S.-F., Li, Y., & Cheng, J. (2025). Clean cryptocurrency and green assets: A quantile connectedness approach. Applied Economics Letters, 32(6), 775–783. https://doi.org/10.1080/13504851.2023.2289395
  48. Tiwari, A. K., Abakah, E. J. A., Rehman, M. Z., & Lee, C. C. (2024). Quantile dependence of Bitcoin with clean and renewable energy stocks: New global evidence. Applied Economics, 56(3). https://doi.org/10.1080/00036846.2023.2167921
  49. Tiwari, A. K., Aikins Abakah, E. J., Gabauer, D., & Dwumfour, R. A. (2022). Dynamic spillover effects among green bond, renewable energy stocks and carbon markets during COVID-19 pandemic: Implications for hedging and investments strategies. Global Finance Journal, 51. https://doi.org/10.1016/j.gfj.2021.100692
  50. Umar, M., Farid, S., & Naeem, M. A. (2022). Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis. Energy, 240, 122702. https://doi.org/10.1016/j.energy.2021.122702
  51. Umar, Z., Choi, S. Y., Teplova, T., & Sokolova, T. (2023). Dynamic spillovers and portfolio implication between green cryptocurrencies and fossil fuels. PLoS ONE, 18(8 August). https://doi.org/10.1371/journal.pone.0288377
  52. Ustaoglu, E. (2024). Extreme return connectedness between renewable energy tokens and renewable energy stock markets: Evidence from a quantile-based analysis. Environmental Science and Pollution Research International, 31(4). https://doi.org/10.1007/s11356-023-31563-9
  53. Wang, X., Liu, J., & Xie, Q. (2024). Quantile frequency connectedness between energy tokens, crypto market, and renewable energy stock markets. Heliyon, 10(3). https://doi.org/10.1016/j.heliyon.2024.e25068
  54. Wu, R., Yan, J., & Işık, C. (2025). The dynamics between clean energy, green bonds, grain commodities, and cryptocurrencies: evidence from correlation and portfolio hedging. Economic Change and Restructuring, 58(4), 60. https://doi.org/10.1007/s10644-025-09902-2
  55. Yadav, M. P., Tandon, P., Singh, A. B., Shore, A., & Gaur, P. (2025). Exploring time and frequency linkages of green bond with renewable energy and crypto market. Annals of Operations Research, 348(3). https://doi.org/10.1007/s10479-022-05074-8
  56. Yahoo Finance. (n.d.). Crypto. Yahoo Finance. Retrieved April 3, 2024, from https://finance.yahoo.com/markets/crypto/all/
  57. Yang, Y., Zhao, L., Chen, L., Wang, C., & Wang, G.-J. (2025). The spillover effects between renewable energy tokens and energy assets. Research in International Business and Finance, 74, 102672. https://doi.org/10.1016/j.ribaf.2024.102672
  58. Yousaf, I., Mensi, W., Vo, X. V., & Kang, S. H. (2024). Dynamic spillovers and connectedness between crude oil and green bond markets. Resources Policy, 89. https://doi.org/10.1016/j.resourpol.2023.104594
  59. Yousaf, I., Nekhili, R., & Umar, M. (2022). Extreme connectedness between renewable energy tokens and fossil fuel markets. Energy Economics, 114. https://doi.org/10.1016/j.eneco.2022.106305
  60. Zhang, J., Chen, X., Wei, Y., & Bai, L. (2023). Does the connectedness among fossil energy returns matter for renewable energy stock returns? Fresh insights from the Cross-Quantilogram analysis. International Review of Financial Analysis, 88. https://doi.org/10.1016/j.irfa.2023.102659