IDEAS home Printed from https://ideas.repec.org/a/kap/ecopln/v57y2024i3d10.1007_s10644-024-09684-z.html
   My bibliography  Save this article

Unveiling time-varying asymmetries in the stock market returns through energy prices, green innovation, and market risk factors: wavelet-based evidence from China

Author

Listed:
  • Muhammad Ramzan

    (University of Sialkot
    Lebanese American University)

  • Mohammad Razib Hossain

    (The University of Adelaide
    Bangabandhu Sheikh Mujibur Rahman Agricultural University)

  • Kashif Raza Abbasi

    (Nisantasi University
    ILMA University)

  • Tomiwa Sunday Adebayo

    (Lebanese American University
    Cyprus International University)

  • Rafael Alvarado

    (Universidad Espíritu Santo)

Abstract

The study explores the nexus between crude oil prices (COP), financial risk index (FRI), political risk index (PRI), green innovation (GIN) and information globalization index (ING) for Shanghai stock exchange (SSE) in China from 1997/M9 to 2021/M12 by utilizes novel wavelet methodologies to handle co-movement dynamics of multivariate time series via moving weighted regression also wavelet-based causality employed to identify the causality. The finding of Wavelet regression indicates the highest multiple correlation from a linear combination of the and ING at each scale, which indicates these variables are impacted by the stock market index. While FRI relates investor confidence declining stock prices may be detrimental to the SSE. However, any changes in PRI government rules or regulations could influence SSE-listed enterprises. GIN develops and employs eco-friendly technologies and procedures. As global awareness of sustainability grows, pioneering green entrepreneurs may attract investors and increase corporate valuations. Investors may find green innovation-driven companies less enticing, resulting in lower stock prices. Yet, ING may propose improved access to global markets and information, hence increasing the value of SSE's shares. According to the findings of wavelet-based Granger Causality, COP, FRI, GIN, ING, PRI, and SSE show significant causal interconnections at several scales. The study offers policy insights based on these findings.

Suggested Citation

  • Muhammad Ramzan & Mohammad Razib Hossain & Kashif Raza Abbasi & Tomiwa Sunday Adebayo & Rafael Alvarado, 2024. "Unveiling time-varying asymmetries in the stock market returns through energy prices, green innovation, and market risk factors: wavelet-based evidence from China," Economic Change and Restructuring, Springer, vol. 57(3), pages 1-36, June.
    • Handle: RePEc:kap:ecopln:v:57:y:2024:i:3:d:10.1007_s10644-024-09684-z
    DOI: 10.1007/s10644-024-09684-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10644-024-09684-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10644-024-09684-z?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. Thampanya, Natthinee & Wu, Junjie & Nasir, Muhammad Ali & Liu, Jia, 2020. "Fundamental and behavioural determinants of stock return volatility in ASEAN-5 countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    2. Ding, Zhihua & Liu, Zhenhua & Zhang, Yuejun & Long, Ruyin, 2017. "The contagion effect of international crude oil price fluctuations on Chinese stock market investor sentiment," Applied Energy, Elsevier, vol. 187(C), pages 27-36.
    3. Marques, Luís Miguel & Fuinhas, José Alberto & Marques, António Cardoso, 2013. "Does the stock market cause economic growth? Portuguese evidence of economic regime change," Economic Modelling, Elsevier, vol. 32(C), pages 316-324.
    4. Zheng, Li & Abbasi, Kashif Raza & Salem, Sultan & Irfan, Muhammad & Alvarado, Rafael & Lv, Kangjuan, 2022. "How technological innovation and institutional quality affect sectoral energy consumption in Pakistan? Fresh policy insights from novel econometric approach," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    5. Wu, Chunying & Wang, Jianzhou & Hao, Yan, 2022. "Deterministic and uncertainty crude oil price forecasting based on outlier detection and modified multi-objective optimization algorithm," Resources Policy, Elsevier, vol. 77(C).
    6. Jiang, Zhangsheng & Xu, Chenghao, 2023. "Policy incentives, government subsidies, and technological innovation in new energy vehicle enterprises: Evidence from China," Energy Policy, Elsevier, vol. 177(C).
    7. Borisov, Alexander & Ellul, Andrew & Sevilir, Merih, 2021. "Access to public capital markets and employment growth," Journal of Financial Economics, Elsevier, vol. 141(3), pages 896-918.
    8. Pavel Sevcik, 2015. "Financial Frictions, Internal Capital Markets, and the Organization of Production," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 18(3), pages 505-522, July.
    9. Patrícia Hipólito Leal & António Cardoso Marques & Muhammad Shahbaz, 2021. "The role of globalisation, de jure and de facto, on environmental performance: evidence from developing and developed countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(5), pages 7412-7431, May.
    10. Sukcharoen, Kunlapath & Zohrabyan, Tatevik & Leatham, David & Wu, Ximing, 2014. "Interdependence of oil prices and stock market indices: A copula approach," Energy Economics, Elsevier, vol. 44(C), pages 331-339.
    11. Boubaker, Sabri & Liu, Zhenya & Sui, Tianqing & Zhai, Ling, 2022. "The mirror of history: How to statistically identify stock market bubble bursts," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 128-147.
    12. Corradi, Valentina & Distaso, Walter & Mele, Antonio, 2013. "Macroeconomic determinants of stock volatility and volatility premiums," Journal of Monetary Economics, Elsevier, vol. 60(2), pages 203-220.
    13. Miao, Hong & Ramchander, Sanjay & Wang, Tianyang & Yang, Dongxiao, 2017. "Influential factors in crude oil price forecasting," Energy Economics, Elsevier, vol. 68(C), pages 77-88.
    14. Cheong, Chin Wen, 2009. "Modeling and forecasting crude oil markets using ARCH-type models," Energy Policy, Elsevier, vol. 37(6), pages 2346-2355, June.
    15. Lehkonen, Heikki & Heimonen, Kari, 2015. "Democracy, political risks and stock market performance," Journal of International Money and Finance, Elsevier, vol. 59(C), pages 77-99.
    16. Wei, Yu & Wang, Yudong & Huang, Dengshi, 2010. "Forecasting crude oil market volatility: Further evidence using GARCH-class models," Energy Economics, Elsevier, vol. 32(6), pages 1477-1484, November.
    17. Pavel Sevcik, 2015. "Financial Frictions, Internal Capital Markets, and the Organization of Production," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 18(3), pages 505-522, July.
    18. Hossain, Mohammad Razib & Singh, Sanjeet & Sharma, Gagan Deep & Apostu, Simona-Andreea & Bansal, Pooja, 2023. "Overcoming the shock of energy depletion for energy policy? Tracing the missing link between energy depletion, renewable energy development and decarbonization in the USA," Energy Policy, Elsevier, vol. 174(C).
    19. Healy, Paul M. & Palepu, Krishna G., 2001. "Information asymmetry, corporate disclosure, and the capital markets: A review of the empirical disclosure literature," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 405-440, September.
    20. Clark, Ephraim & Kassimatis, Konstantinos, 2004. "Country financial risk and stock market performance: the case of Latin America," Journal of Economics and Business, Elsevier, vol. 56(1), pages 21-41.
    21. Diaz, Elena Maria & Molero, Juan Carlos & Perez de Gracia, Fernando, 2016. "Oil price volatility and stock returns in the G7 economies," Energy Economics, Elsevier, vol. 54(C), pages 417-430.
    22. Haejung Na & Soonho Kim, 2022. "The impact of globalization and the legal system on stock market quality," Applied Economics, Taylor & Francis Journals, vol. 54(36), pages 4203-4212, August.
    23. Drakos, Konstantinos, 2004. "Terrorism-induced structural shifts in financial risk: airline stocks in the aftermath of the September 11th terror attacks," European Journal of Political Economy, Elsevier, vol. 20(2), pages 435-446, June.
    24. Haidong Li & Ziming Qian & Shanyong Wang & Jing Wang & Qian Wang, 2023. "Do green concerns promote corporate green innovation? Evidence from Chinese stock exchange interactive platforms," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(3), pages 1786-1801, April.
    25. Arouri, Mohamed El Hedi & Jouini, Jamel & Nguyen, Duc Khuong, 2012. "On the impacts of oil price fluctuations on European equity markets: Volatility spillover and hedging effectiveness," Energy Economics, Elsevier, vol. 34(2), pages 611-617.
    26. Chan, Yue-cheong & John Wei, K. C., 1996. "Political risk and stock price volatility: The case of Hong Kong," Pacific-Basin Finance Journal, Elsevier, vol. 4(2-3), pages 259-275, July.
    27. Li-Chen Cheng & Wei-Ting Lu & Benjamin Yeo, 2023. "Predicting abnormal trading behavior from internet rumor propagation: a machine learning approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    28. Luís Aguiar-Conraria & Maria Joana Soares, 2014. "The Continuous Wavelet Transform: Moving Beyond Uni- And Bivariate Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 344-375, April.
    29. Zhang, Xu & Yang, Xian & He, Qizhi, 2022. "Multi-scale systemic risk and spillover networks of commodity markets in the bullish and bearish regimes," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    30. Dervis Kirikkaleli, 2020. "Does political risk matter for economic and financial risks in Venezuela?," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-10, December.
    31. Die Hu & Lu Qiu & Maoyan She & Yu Wang, 2021. "Sustaining the sustainable development: How do firms turn government green subsidies into financial performance through green innovation?," Business Strategy and the Environment, Wiley Blackwell, vol. 30(5), pages 2271-2292, July.
    32. Bhide, Amar, 1993. "The hidden costs of stock market liquidity," Journal of Financial Economics, Elsevier, vol. 34(1), pages 31-51, August.
    33. Jammazi, Rania & Aloui, Chaker, 2012. "Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling," Energy Economics, Elsevier, vol. 34(3), pages 828-841.
    34. Hamdi, Besma & Aloui, Mouna & Alqahtani, Faisal & Tiwari, Aviral, 2019. "Relationship between the oil price volatility and sectoral stock markets in oil-exporting economies: Evidence from wavelet nonlinear denoised based quantile and Granger-causality analysis," Energy Economics, Elsevier, vol. 80(C), pages 536-552.
    35. Lee, Chi-Chuan & Lee, Chien-Chiang & Li, Yong-Yi, 2021. "Oil price shocks, geopolitical risks, and green bond market dynamics," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    36. Abdullah Albaker & Kashif Raza Abbasi & Akram Masoud Haddad & Magdalena Radulescu & Catalin Manescu & Georgiana Tatiana Bondac, 2023. "Analyzing the Impact of Renewable Energy and Green Innovation on Carbon Emissions in the MENA Region," Energies, MDPI, vol. 16(16), pages 1-19, August.
    Full references (including those not matched with items on IDEAS)

    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. Li, Jinchao & Zhu, Shaowen & Wu, Qianqian, 2019. "Monthly crude oil spot price forecasting using variational mode decomposition," Energy Economics, Elsevier, vol. 83(C), pages 240-253.
    2. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    3. Mushtaq Hussain Khan & Junaid Ahmed & Mazhar Mughal & Imtiaz Hussain Khan, 2023. "Oil price volatility and stock returns: Evidence from three oil‐price wars," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3162-3182, July.
    4. Wang, Lu & Ma, Feng & Liu, Jing & Yang, Lin, 2020. "Forecasting stock price volatility: New evidence from the GARCH-MIDAS model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 684-694.
    5. Tiwari, Aviral Kumar & Trabelsi, Nader & Alqahtani, Faisal & Raheem, Ibrahim D., 2020. "Systemic risk spillovers between crude oil and stock index returns of G7 economies: Conditional value-at-risk and marginal expected shortfall approaches," Energy Economics, Elsevier, vol. 86(C).
    6. Xu, Kunliang & Niu, Hongli, 2023. "Denoising or distortion: Does decomposition-reconstruction modeling paradigm provide a reliable prediction for crude oil price time series?," Energy Economics, Elsevier, vol. 128(C).
    7. Manel Hamdi & Chaker Aloui, 2015. "Forecasting Crude Oil Price Using Artificial Neural Networks: A Literature Survey," Economics Bulletin, AccessEcon, vol. 35(2), pages 1339-1359.
    8. Zhang, Tingting & Tang, Zhenpeng & Wu, Junchuan & Du, Xiaoxu & Chen, Kaijie, 2021. "Multi-step-ahead crude oil price forecasting based on two-layer decomposition technique and extreme learning machine optimized by the particle swarm optimization algorithm," Energy, Elsevier, vol. 229(C).
    9. Tiwari, Aviral Kumar & Sharma, Gagan Deep & Rao, Amar & Hossain, Mohammad Razib & Dev, Dhairya, 2024. "Unraveling the crystal ball: Machine learning models for crude oil and natural gas volatility forecasting," Energy Economics, Elsevier, vol. 134(C).
    10. Xu, Kunliang & Niu, Hongli, 2022. "Do EEMD based decomposition-ensemble models indeed improve prediction for crude oil futures prices?," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    11. Jiang, Zhuhua & Yoon, Seong-Min, 2020. "Dynamic co-movement between oil and stock markets in oil-importing and oil-exporting countries: Two types of wavelet analysis," Energy Economics, Elsevier, vol. 90(C).
    12. Lin, Ling & Jiang, Yong & Xiao, Helu & Zhou, Zhongbao, 2020. "Crude oil price forecasting based on a novel hybrid long memory GARCH-M and wavelet analysis model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 543(C).
    13. Zheng, Li & Sun, Yuying & Wang, Shouyang, 2024. "A novel interval-based hybrid framework for crude oil price forecasting and trading," Energy Economics, Elsevier, vol. 130(C).
    14. Liu, Jing & Ma, Feng & Tang, Yingkai & Zhang, Yaojie, 2019. "Geopolitical risk and oil volatility: A new insight," Energy Economics, Elsevier, vol. 84(C).
    15. He, Zhifang & Sun, Hao & Chen, Jiaqi & Yang, Xin & Yin, Zhujia, 2023. "Dynamic interaction of risk–return trade-offs between oil market and China’s stock market: An analysis from the risk preferences perspective," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    16. Sun, Shaolong & Sun, Yuying & Wang, Shouyang & Wei, Yunjie, 2018. "Interval decomposition ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, vol. 76(C), pages 274-287.
    17. Chai, Jian & Xing, Li-Min & Zhou, Xiao-Yang & Zhang, Zhe George & Li, Jie-Xun, 2018. "Forecasting the WTI crude oil price by a hybrid-refined method," Energy Economics, Elsevier, vol. 71(C), pages 114-127.
    18. Zhenhua Liu & Zhihua Ding & Tao Lv & Jy S. Wu & Wei Qiang, 2019. "Financial factors affecting oil price change and oil-stock interactions: a review and future perspectives," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 95(1), pages 207-225, January.
    19. Guo, Jingjun & Zhao, Zhengling & Sun, Jingyun & Sun, Shaolong, 2022. "Multi-perspective crude oil price forecasting with a new decomposition-ensemble framework," Resources Policy, Elsevier, vol. 77(C).
    20. Patra, Saswat, 2021. "Revisiting value-at-risk and expected shortfall in oil markets under structural breaks: The role of fat-tailed distributions," Energy Economics, Elsevier, vol. 101(C).

    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:kap:ecopln:v:57:y:2024:i:3:d:10.1007_s10644-024-09684-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.