IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v123y2023ics0140988323002256.html
   My bibliography  Save this article

Diversification effects of China's carbon neutral bond on renewable energy stock markets: A minimum connectedness portfolio approach

Author

Listed:
  • Bai, Lan
  • Wei, Yu
  • Zhang, Jiahao
  • Wang, Yizhi
  • Lucey, Brian M.

Abstract

Socially responsible investment (SRI) is becoming increasingly popular in China, with the announcement of carbon dioxide peaking by 2030 and carbon neutrality by 2060 (30–60 targets). As a conventional underlying asset of SRI, renewable energy stocks are attractive, but with higher price volatility than many other traditional industrial stocks. This paper aims to investigate the interaction and diversification effects of China's Carbon Neutral Bond (CNB), a new SRI underlying asset just launched in 2021, on renewable energy stocks using a novel minimum connectedness portfolio approach recently proposed by Broadstock et al. (2020). The empirical results show that, first, China's CNB is weakly related to renewable energy stocks, whether in the time or frequency domain, and is the main recipient of the net linkage effect. Second, different renewable energy stocks benefit differently from the diversification effect of CNB. However, in extreme market conditions, the diversification effect of the CNB is reduced. Third, the newly developed minimum connectedness portfolio approach can outperform traditional minimum variance and correlation methods by achieving higher cumulative portfolio returns. Finally, the Sharpe ratios of renewable energy stock portfolios with CNB are significantly higher than those without it across different allocation methods. These findings have important implications for policy makers and SRI investors.

Suggested Citation

  • Bai, Lan & Wei, Yu & Zhang, Jiahao & Wang, Yizhi & Lucey, Brian M., 2023. "Diversification effects of China's carbon neutral bond on renewable energy stock markets: A minimum connectedness portfolio approach," Energy Economics, Elsevier, vol. 123(C).
  • Handle: RePEc:eee:eneeco:v:123:y:2023:i:c:s0140988323002256
    DOI: 10.1016/j.eneco.2023.106727
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988323002256
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2023.106727?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Qureshi, Anum & Rizwan, Muhammad Suhail & Ahmad, Ghufran & Ashraf, Dawood, 2022. "Russia–Ukraine war and systemic risk: Who is taking the heat?," Finance Research Letters, Elsevier, vol. 48(C).
    2. Pham, Linh & Nguyen, Canh Phuc, 2022. "How do stock, oil, and economic policy uncertainty influence the green bond market?," Finance Research Letters, Elsevier, vol. 45(C).
    3. Farid, Saqib & Karim, Sitara & Naeem, Muhammad A. & Nepal, Rabindra & Jamasb, Tooraj, 2023. "Co-movement between dirty and clean energy: A time-frequency perspective," Energy Economics, Elsevier, vol. 119(C).
    4. Ma, Rufei & Sun, Bianxia & Zhai, Pengxiang & Jin, Yi, 2021. "Hedging stock market risks: Can gold really beat bonds?," Finance Research Letters, Elsevier, vol. 42(C).
    5. Ian Dew-Becker & Stefano Giglio, 2016. "Asset Pricing in the Frequency Domain: Theory and Empirics," The Review of Financial Studies, Society for Financial Studies, vol. 29(8), pages 2029-2068.
    6. Yufeng Chen & Wenqi Li & Xi Jin, 2018. "Volatility Spillovers between Crude Oil Prices and New Energy Stock Price in China," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 43-62, December.
    7. Connolly, Robert & Stivers, Chris & Sun, Licheng, 2005. "Stock Market Uncertainty and the Stock-Bond Return Relation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(1), pages 161-194, March.
    8. Dirk G. Baur & Brian M. Lucey, 2010. "Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds and Gold," The Financial Review, Eastern Finance Association, vol. 45(2), pages 217-229, May.
    9. Christoffersen, Peter & Errunza, Vihang & Jacobs, Kris & Jin, Xisong, 2014. "Correlation dynamics and international diversification benefits," International Journal of Forecasting, Elsevier, vol. 30(3), pages 807-824.
    10. Ederington, Louis H, 1979. "The Hedging Performance of the New Futures Markets," Journal of Finance, American Finance Association, vol. 34(1), pages 157-170, March.
    11. Arfaoui, Nadia & Naeem, Muhammad Abubakr & Boubaker, Sabri & Mirza, Nawazish & Karim, Sitara, 2023. "Interdependence of clean energy and green markets with cryptocurrencies," Energy Economics, Elsevier, vol. 120(C).
    12. 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.
    13. Lei Yan & Haiyan Wang & Seyed Alireza Athari & Faraz Atif, 2022. "Driving green bond market through energy prices, gold prices and green energy stocks: evidence from a non-linear approach," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 35(1), pages 6479-6499, December.
    14. Reboredo, Juan C. & Ugolini, Andrea & Ojea-Ferreiro, Javier, 2022. "Do green bonds de-risk investment in low-carbon stocks?," Economic Modelling, Elsevier, vol. 108(C).
    15. 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.
    16. Ciner, Cetin & Gurdgiev, Constantin & Lucey, Brian M., 2013. "Hedges and safe havens: An examination of stocks, bonds, gold, oil and exchange rates," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 202-211.
    17. Basher, Syed Abul & Sadorsky, Perry, 2016. "Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH," Energy Economics, Elsevier, vol. 54(C), pages 235-247.
    18. Naeem, Muhammad Abubakr & Karim, Sitara & Hasan, Mudassar & Lucey, Brian M. & Kang, Sang Hoon, 2022. "Nexus between oil shocks and agriculture commodities: Evidence from time and frequency domain," Energy Economics, Elsevier, vol. 112(C).
    19. Janda, Karel & Kristoufek, Ladislav & Zhang, Binyi, 2022. "Return and volatility spillovers between Chinese and U.S. clean energy related stocks," Energy Economics, Elsevier, vol. 108(C).
    20. Wang, Lu & Wu, Jiangbin & Cao, Yang & Hong, Yanran, 2022. "Forecasting renewable energy stock volatility using short and long-term Markov switching GARCH-MIDAS models: Either, neither or both?," Energy Economics, Elsevier, vol. 111(C).
    21. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    22. Zhang, Yaojie & Wei, Yu & Zhang, Yi & Jin, Daxiang, 2019. "Forecasting oil price volatility: Forecast combination versus shrinkage method," Energy Economics, Elsevier, vol. 80(C), pages 423-433.
    23. Hassan, M. Kabir & Hasan, Md. Bokhtiar & Halim, Zairihan Abdul & Maroney, Neal & Rashid, Md. Mamunur, 2022. "Exploring the dynamic spillover of cryptocurrency environmental attention across the commodities, green bonds, and environment-related stocks," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    24. Wei, Yu & Qin, Songkun & Li, Xiafei & Zhu, Sha & Wei, Guiwu, 2019. "Oil price fluctuation, stock market and macroeconomic fundamentals: Evidence from China before and after the financial crisis," Finance Research Letters, Elsevier, vol. 30(C), pages 23-29.
    25. Jozef Baruník & Tomáš Křehlík, 2018. "Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 271-296.
    26. Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Gabauer, David & Dwumfour, Richard Adjei, 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, Elsevier, vol. 51(C).
    27. Wang, Lu & Zhao, Chenchen & Liang, Chao & Jiu, Song, 2022. "Predicting the volatility of China's new energy stock market: Deep insight from the realized EGARCH-MIDAS model," Finance Research Letters, Elsevier, vol. 48(C).
    28. Adekoya, Oluwasegun B. & Oliyide, Johnson A. & Yaya, OlaOluwa S. & Al-Faryan, Mamdouh Abdulaziz Saleh, 2022. "Does oil connect differently with prominent assets during war? Analysis of intra-day data during the Russia-Ukraine saga," Resources Policy, Elsevier, vol. 77(C).
    29. Mensi, Walid & Shafiullah, Muhammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Spillovers and connectedness between green bond and stock markets in bearish and bullish market scenarios," Finance Research Letters, Elsevier, vol. 49(C).
    30. Wei, Yu & Bai, Lan & Li, Xiafei, 2022. "Normal and extreme interactions among nonferrous metal futures: A new quantile-frequency connectedness approach," Finance Research Letters, Elsevier, vol. 47(PB).
    31. Wei, Yu & Zhang, Jiahao & Bai, Lan & Wang, Yizhi, 2023. "Connectedness among El Niño-Southern Oscillation, carbon emission allowance, crude oil and renewable energy stock markets: Time- and frequency-domain evidence based on TVP-VAR model," Renewable Energy, Elsevier, vol. 202(C), pages 289-309.
    32. Billah, Mabruk & Karim, Sitara & Naeem, Muhammad Abubakr & Vigne, Samuel A., 2022. "Return and volatility spillovers between energy and BRIC markets: Evidence from quantile connectedness," Research in International Business and Finance, Elsevier, vol. 62(C).
    33. Bai, Lan & Wei, Yu & Wei, Guiwu & Li, Xiafei & Zhang, Songyun, 2021. "Infectious disease pandemic and permanent volatility of international stock markets: A long-term perspective," Finance Research Letters, Elsevier, vol. 40(C).
    34. Tomohiro Ando & Matthew Greenwood-Nimmo & Yongcheol Shin, 2022. "Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks," Management Science, INFORMS, vol. 68(4), pages 2401-2431, April.
    35. Nguyen, Thi Thu Ha & Naeem, Muhammad Abubakr & Balli, Faruk & Balli, Hatice Ozer & Vo, Xuan Vinh, 2021. "Time-frequency comovement among green bonds, stocks, commodities, clean energy, and conventional bonds," Finance Research Letters, Elsevier, vol. 40(C).
    36. Wei, Yu & Zhang, Yaojie & Wang, Yudong, 2022. "Information connectedness of international crude oil futures: Evidence from SC, WTI, and Brent," International Review of Financial Analysis, Elsevier, vol. 81(C).
    37. Myron T. Greene & Bruce D. Fielitz, 1979. "The Effect of Long Term Dependence on Risk-Return Models of Common Stocks," Operations Research, INFORMS, vol. 27(5), pages 944-951, October.
    38. Chen, Yongfei & Wei, Yu & Bai, Lan & Zhang, Jiahao, 2023. "Can Green Economy stocks hedge natural gas market risk? Evidence during Russia-Ukraine conflict and other crisis periods," Finance Research Letters, Elsevier, vol. 53(C).
    39. Dutta, Anupam & Bouri, Elie & Noor, Md Hasib, 2021. "Climate bond, stock, gold, and oil markets: Dynamic correlations and hedging analyses during the COVID-19 outbreak," Resources Policy, Elsevier, vol. 74(C).
    40. 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.
    41. Mensi, Walid & Naeem, Muhammad Abubakr & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Dynamic and frequency spillovers between green bonds, oil and G7 stock markets: Implications for risk management," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 331-344.
    42. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, 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. Zhang, Dongyang & Wang, Jinli & Wang, Yizhi, 2023. "Greening through centralization of environmental monitoring?," Energy Economics, Elsevier, vol. 123(C).
    2. Huang, Wenyang & Gao, Tianxiao & Hao, Yun & Wang, Xiuqing, 2023. "Transformer-based forecasting for intraday trading in the Shanghai crude oil market: Analyzing open-high-low-close prices," Energy Economics, Elsevier, vol. 127(PA).
    3. Gu, Leilei & Peng, Yuchao & Vigne, Samuel A. & Wang, Yizhi, 2023. "Hidden costs of non-green performance? The impact of air pollution awareness on loan rates for Chinese firms," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 233-250.

    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. Abdullah, Mohammad & Chowdhury, Mohammad Ashraful Ferdous & Sulong, Zunaidah, 2023. "Asymmetric efficiency and connectedness among green stocks, halal tourism stocks, cryptocurrencies, and commodities: Portfolio hedging implications," Resources Policy, Elsevier, vol. 81(C).
    2. Zhang, Jiahao & Chen, Xiaodan & Wei, Yu & Bai, Lan, 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, Elsevier, vol. 88(C).
    3. Qi, Xiaohong & Zhang, Guofu, 2022. "Dynamic connectedness of China’s green bonds and asset classes," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    4. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    5. Huang, Zishan & Zhu, Huiming & Hau, Liya & Deng, Xi, 2023. "Time-frequency co-movement and network connectedness between green bond and financial asset markets: Evidence from multiscale TVP-VAR analysis," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    6. Chen, Yongfei & Wei, Yu & Bai, Lan & Zhang, Jiahao, 2023. "Can Green Economy stocks hedge natural gas market risk? Evidence during Russia-Ukraine conflict and other crisis periods," Finance Research Letters, Elsevier, vol. 53(C).
    7. Zhang, Wenting & He, Xie & Hamori, Shigeyuki, 2023. "The impact of the COVID-19 pandemic and Russia-Ukraine war on multiscale spillovers in green finance markets: Evidence from lower and higher order moments," International Review of Financial Analysis, Elsevier, vol. 89(C).
    8. Doğan, Buhari & Trabelsi, Nader & Tiwari, Aviral Kumar & Ghosh, Sudeshna, 2023. "Dynamic dependence and causality between crude oil, green bonds, commodities, geopolitical risks, and policy uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 36-62.
    9. Lu, Xunfa & Huang, Nan & Mo, Jianlei & Ye, Zhitao, 2023. "Dynamics of the return and volatility connectedness among green finance markets during the COVID-19 pandemic," Energy Economics, Elsevier, vol. 125(C).
    10. Qian Wang & Yu Wei & Yifeng Zhang & Yuntong Liu, 2023. "Evaluating the Safe-Haven Abilities of Bitcoin and Gold for Crude Oil Market: Evidence During the COVID-19 Pandemic," Evaluation Review, , vol. 47(3), pages 391-432, June.
    11. Wei, Yu & Zhang, Jiahao & Bai, Lan & Wang, Yizhi, 2023. "Connectedness among El Niño-Southern Oscillation, carbon emission allowance, crude oil and renewable energy stock markets: Time- and frequency-domain evidence based on TVP-VAR model," Renewable Energy, Elsevier, vol. 202(C), pages 289-309.
    12. Wen, Danyan & Wang, Yudong, 2021. "Volatility linkages between stock and commodity markets revisited: Industry perspective and portfolio implications," Resources Policy, Elsevier, vol. 74(C).
    13. Gabauer, David & Chatziantoniou, Ioannis & Stenfors, Alexis, 2023. "Model-free connectedness measures," Finance Research Letters, Elsevier, vol. 54(C).
    14. Cui, Jinxin & Maghyereh, Aktham, 2023. "Higher-order moment risk connectedness and optimal investment strategies between international oil and commodity futures markets: Insights from the COVID-19 pandemic and Russia-Ukraine conflict," International Review of Financial Analysis, Elsevier, vol. 86(C).
    15. Hoque, Mohammad Enamul & Soo-Wah, Low & Billah, Mabruk, 2023. "Time-frequency connectedness and spillover among carbon, climate, and energy futures: Determinants and portfolio risk management implications," Energy Economics, Elsevier, vol. 127(PB).
    16. Benlagha, Noureddine & Karim, Sitara & Naeem, Muhammad Abubakr & Lucey, Brian M. & Vigne, Samuel A., 2022. "Risk connectedness between energy and stock markets: Evidence from oil importing and exporting countries," Energy Economics, Elsevier, vol. 115(C).
    17. Cagli, Efe Caglar & Mandaci, Pinar Evrim, 2023. "Time and frequency connectedness of uncertainties in cryptocurrency, stock, currency, energy, and precious metals markets," Emerging Markets Review, Elsevier, vol. 55(C).
    18. 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).
    19. Naeem, Muhammad Abubakr & Hamouda, Foued & Karim, Sitara & Vigne, Samuel A., 2023. "Return and volatility spillovers among global assets: Comparing health crisis with geopolitical crisis," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 557-575.
    20. Nyakurukwa, Kingstone & Seetharam, Yudhvir, 2023. "Quantile and asymmetric return connectedness among BRICS stock markets," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).

    More about this item

    Keywords

    Carbon neutral bond; Renewable energy stock; Socially responsible investment; Minimum connectedness portfolio;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    Statistics

    Access and download statistics

    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:eee:eneeco:v:123:y:2023:i:c:s0140988323002256. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.