Are Green Bonds and Oil Bonds Moving Together? Evidence from the Emerging Russian Green Bond Market

Stepan A. Bakhteyev, Oleg S. Mariev

Ural Federal University named after the First President of Russia B.N. Yeltsin, Yekaterinburg, Russia

Abstract

Green technologies are actively penetrating various sectors of the economy. This trend is supported by the international community's efforts to transition to a carbon-neutral economy, which aims to prevent the Earth's average temperature from rising to catastrophic levels that could lead to irreversible changes in established ecosystems. Against the backdrop of this trend, new green bond markets are emerging that meet established standards of responsible environmental behavior. This paper examines the Russian green bond market, which is at an early stage of development, and also aims to study its relationship with conventional bond markets. The main hypothesis is the assumption that the connection between the young emerging market and the market for conventional bonds from the energy sector should be high, and mutual hedging of risks for this reason is impossible. The methodological apparatus used in the work includes the use of the Cross-Quantilogram method and the spectral quantile coherency method. The use of these methods is due to its prevalence among foreign studies devoted to the analysis of the relationship between the green bond market and other financial markets, owing to their ability to handle heavy-tailed distributions of financial assets and to take into account differing market conditions. The obtained results confirm the main hypothesis, because we do see a strong correlation between the green bond market and the oil bond market over short horizons. At the same time, risk hedging proves possible over long investment horizons using federal loan bonds (OFZ). We also note that the federal bond market has a stronger impact on oil and green bonds than they have on it. The results provide practical recommendations for investors willing to build a diversified portfolio that includes both conventional and green bonds, and can also serve as a methodological basis for further research on the green bond market.

Keywords

green bonds; Russian stock market; risk hedging; cross-quantilogram; portfolio investment.

JEL classification

References

1. Lee, C.C., Lee, C.C. (2022). How does green finance affect green total factor productivity? Evidence from China. Energy Economics, Vol. 107, 105863. https://doi.org/10.1016/j.eneco.2022.105863

         2. Sohag, K., Hassan, M.K., Bakhteyev, S., Mariev O. (2023). Do green and dirty investments hedge each other? Energy Economics, Vol. 120, 106573. https://doi.org/10.1016/j.eneco.2023.106573

         3. Eyraud, L., Clements, B., Wane, A. (2013). Green investment: Trends and determinants. Energy Policy, Vol. 60, 852–865. https://doi.org/10.1016/j.enpol.2013.04.039

         4. Campiglio, E. (2016). Beyond carbon pricing: The role of banking and monetary policy in financing the transition to a low-carbon economy. Ecological Economics, Vol. 121, 220–230. https://doi.org/10.1016/j.ecolecon.2015.03.020

         5. Bogacheva, O.V., Smorodinov, O.V. (2017). Challenges to Green Finance in G20 Countries. World Eсonomy and International Relations, Vol. 61, No. 10, 16–24. (In Russ.). https://doi.org/10.20542/0131-2227-2017-61-10-16-24

         6. Porfir’ev, B.N. (2016). Green trends in the Global Financial System. World Eсonomy and International Relations, Vol. 60, No. 9, 5–16. (In Russ.). https://doi.org/10.20542/0131-2227-2016-60-9-5-16

         7. Vostrikova, E.O, Meshkova, A.P. (2020). ESG criteria in investment: foreign and Russian experience. Financial Journal, Vol. 12, No. 4, 117–129. (In Russ.). https://doi.org/10.31107/2075-1990-2020-4-117-129

         8. Izmailova, M.A. (2022). Implementation of ESG strategies of Russian companies under sanctions restrictions. MIR (Modernization. Innovation. Research), Vol. 13, No. 2, 185–201. (In Russ.). https://doi.org/10.18184/2079-4665.2022.13.2.185-201

         9. Kovalev, V.A. (2023). The development of green finance in the EAEU countries based on the assessment of the liquidity of green bonds. Theoretical and Applied Economics, No. 4, 18–34. (In Russ.). https://doi.org/10.25136/2409-8647.2023.4.69426

         10. Pham, L. (2016). Is it risky to go green? A volatility analysis of the green bond market. Journal of Sustainable Finance & Investment, Vol. 6, Issue 4, 263–291. https://doi.org/10.1080/20430795.2016.1237244

         11. Pham, L., Nguyen, C.P. (2022). How do stock, oil, and economic policy uncertainty influence the green bond market? Finance Research Letters, Vol. 45, 102128. https://doi.org/10.1016/j.frl.2021.102128

         12. Pham, L. (2021). Frequency connectedness and cross-quantile dependence between green bond and green equity markets. Energy Economics, Vol. 98, 105257. https://doi.org/10.1016/j.eneco.2021.105257

         13. Liu, N., Liu, C., Da, B., Zhang, T., Guan, F. (2021). Dependence and risk spillovers between green bonds and clean energy markets. Journal of Cleaner Production, Vol. 279, 123595. https://doi.org/10.1016/j.jclepro.2020.123595

         14. Reboredo, J.C. (2018). Green bond and financial markets: Co-movement, diversification and price spillover effects. Energy Economics, Vol. 74, 38–50. https://doi.org/10.1016/j.eneco.2018.05.030

         15. Reboredo, J.C., Ugolini, A. (2020). Price connectedness between green bond and financial markets. Economic Modelling, Vol. 88, 25–38. https://doi.org/10.1016/j.econmod.2019.09.004

         16. Reboredo, J.C., Ugolini, A., Aiube, F.A.L. (2020). Network connectedness of green bonds and asset classes. Energy Economics, Vol. 86, 104629. https://doi.org/10.1016/j.eneco.2019.104629

         17. 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, Vol. 40, 101739. https://doi.org/10.1016/j.frl.2020.101739

         18. Ferrer, R., Shahzad, S.J.H., Soriano, P. (2021). Are green bonds a different asset class? Evidence from time-frequency connectedness analysis. Journal of Cleaner Production, Vol. 292, 125988. https://doi.org/10.1016/j.jclepro.2021.125988

         19. Broadstock, D.C., Cheng, L.T.W. (2019). Time-varying relation between black and green bond price benchmarks: Macroeconomic determinants for the first decade. Finance Research Letters, Vol. 29, 17–22. https://doi.org/10.1016/j.frl.2019.02.006

         20. Naeem, M.A., Sadorsky, P., Karim, S. (2023). Sailing across climate-friendly bonds and clean energy stocks: An asymmetric analysis with the Gulf Cooperation Council Stock markets. Energy Economics, Vol. 126, 106911. https://doi.org/10.1016/j.eneco.2023.106911

         21. Huynh, T.L.D. (2022). When ‘green’challenges ‘prime’: empirical evidence from government bond markets. Journal of Sustainable Finance & Investment, Vol. 12, Issue 2, 375–388. https://doi.org/10.1080/20430795.2020.1769984

         22. Kanamura, T. (2020). Are green bonds environmentally friendly and good performing assets? Energy Economics, Vol. 88, 104767. https://doi.org/10.1016/j.eneco.2020.104767

         23. Wei, P., Qi Y., Ren, X., Gozgor, G. (2023). The role of the COVID-19 pandemic in time-frequency connectedness between oil market shocks and green bond markets: evidence from the wavelet-based quantile approaches. Energy Economics, Vol. 121, 106657. https://doi.org/10.1016/j.eneco.2023.106657

         24. Doğan, B., Trabelsi, N., Tiwari, A.K., Ghosh, S. (2023). Dynamic dependence and causality between crude oil, green bonds, commodities, geopolitical risks, and policy uncertainty. The Quarterly Review of Economics and Finance, Vol. 89, 36–62. https://doi.org/10.1016/j.qref.2023.02.006

         25. Saeed, T., Bouri, E., Alsulami, H. (2021). Extreme return connectedness and its determinants between clean/green and dirty energy investments. Energy Economics, Vol. 96, 105017. https://doi.org/10.1016/j.eneco.2020.105017

         26. Hammoudeh, S., Ajmi, A.N., Mokni, K. (2020). Relationship between green bonds and financial and environmental variables: A novel time-varying causality. Energy Economics, Vol. 92, 104941. https://doi.org/10.1016/j.eneco.2020.104941

         27. Ren, X., Li Y., Wen, F., Lu, Z. (2022). The interrelationship between the carbon market and the green bonds market: Evidence from wavelet quantile-on-quantile method. Technological Forecasting and Social Change, Vol. 179, 121611. https://doi.org/10.1016/j.techfore.2022.121611

         28. Tang, Y., Chen, X.H., Sarker, P. K., Baroudi, S. (2023). Asymmetric effects of geopolitical risks and uncertainties on green bond markets. Technological Forecasting and Social Change, Vol. 189, 122348. https://doi.org/10.1016/j.techfore.2023.122348

         29. Arfaoui, N., Naeem, M.A., Boubaker, S., Mirza, N., Karim, S. (2023). Interdependence of clean energy and green markets with cryptocurrencies. Energy Economics, Vol. 120, 106584. https://doi.org/10.1016/j.eneco.2023.106584

         30. Abakah, E.J.A., Tiwari, A.K., Ghosh, S., Doğan, B. (2023). Dynamic effect of Bitcoin, fintech and artificial intelligence stocks on eco-friendly assets, Islamic stocks and conventional financial markets: Another look using quantile-based approaches. Technological Forecasting and Social Change, Vol. 192, 122566. https://doi.org/10.1016/j.techfore.2023.122566

         31. Le, T.N.L., Abakah, E.J.A., Tiwari, A.K. (2021). Time and frequency domain connectedness and spill-over among fintech, green bonds and cryptocurrencies in the age of the fourth industrial revolution. Technological Forecasting and Social Change, Vol. 162, 120382. https://doi.org/10.1016/j.techfore.2020.120382

         32. 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, Vol. 361, 132088. https://doi.org/10.1016/j.jclepro.2022.132088

         33. Elsayed, A.H., Naifar, N., Nasreen, S., Tiwari, A.K. (2022). Dependence structure and dynamic connectedness between green bonds and financial markets: Fresh insights from time-frequency analysis before and during COVID-19 pandemic. Energy Economics, Vol. 107, 105842. https://doi.org/10.1016/j.eneco.2022.105842

         34. Han, H., Linton, O., Oka, T., Whang, Y.J. (2016). The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series. Journal of Econometrics, Vol. 193, Issue 1, 251–270. https://doi.org/10.1016/j.jeconom.2016.03.001

         35. Corbet, S., Goodell, J.W., Günay, S. (2020). Co-movements and spillovers of oil and renewable firms under extreme conditions: New evidence from negative WTI prices during COVID-19. Energy Economics, Vol. 92, 104978. https://doi.org/10.1016/j.eneco.2020.104978

         36. Kapetanios, G. (2005). Unit-root testing against the alternative hypothesis of up to m structural breaks. Journal of Time Series Analysis, Vol. 26, Issue 1, 123–133. https://doi.org/10.1111/j.1467-9892.2005.00393.x

Acknowledgements

The authors thank the editor and the reviewers for their suggestions and comments, which provided very scientific guidance for this study.

This study was supported by the grant of the Russian Science Foundation (Code: 25–18–01162).

About Authors

Stepan Andreyevich Bakhteyev

Post-Graduate Student, Graduate School of Economics and Management, Ural Federal University named after the first President of Russia B.N. Yeltsin, Yekaterinburg, Russia (620002, Yekaterinburg, Mira street, 19); ORCID https://orcid.org/0000-0003-0260-6754 e-mail: bahteevsa@yandex.ru

Oleg Svyatoslavovich Mariev

Candidate of Economic Sciences, Graduate School of Economics and Management, Ural Federal University named after the first President of Russia B.N. Yeltsin, Yekaterinburg, Russia (620002, Yekaterinburg, Mira street, 19); ORCID https://orcid.org/0000-0002-9745-8434 e-mail: o.s.mariev@urfu.ru

For citation

The authors thank the editor and the reviewers for their suggestions and comments, which provided very scientific guidance for this study.

This study was supported by the grant of the Russian Science Foundation (Code: 25–18–01162).

Article info

Received April 28, 2026; Revised May 28, 2026; Accepted June 1, 2026.

DOI: http://dx.doi.org/10.15826/vestnik.2026.25.3.026

Download full text article: