IDEAS home Printed from https://ideas.repec.org/p/bat/basiq1/2024055.html

Green Energy Consumption and Stock Performance: Evidence from the German Market

Author

Listed:
  • Bogdan Ionut Anghel

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • Radu Lupu

    (Bucharest University of Economic Studies, Bucharest, Romania)

Abstract

No abstract is available for this item.

Suggested Citation

  • Bogdan Ionut Anghel & Radu Lupu, "undated". "Green Energy Consumption and Stock Performance: Evidence from the German Market," BASIQ Conference Proceedings 2024:055, Bucharest University of Economic Studies.
  • Handle: RePEc:bat:basiq1:2024:055
    DOI: 10.24818/BASIQ/2024/10/061
    as

    Download full text from publisher

    File URL: https://conference.ase.ro/papers/2024/24061.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.24818/BASIQ/2024/10/061?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
    ---><---

    References listed on IDEAS

    as
    1. Cortez, Maria Céu & Andrade, Nuno & Silva, Florinda, 2022. "The environmental and financial performance of green energy investments: European evidence," Ecological Economics, Elsevier, vol. 197(C).
    2. Ledoit, Oliver & Wolf, Michael, 2008. "Robust performance hypothesis testing with the Sharpe ratio," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 850-859, December.
    3. Borghesi, S. & Castellini, M. & Comincioli, N. & Donadelli, M. & Gufler, I. & Vergalli, S., 2022. "European green policy announcements and sectoral stock returns," Energy Policy, Elsevier, vol. 166(C).
    4. Emmanouil Karakostas, 2023. "The Macroeconomic Determinants of the Stock Market Index Performance: The Case of DAX Index," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(3), pages 21-38.
    5. Bauer, Michael & Huber, Daniel & Rudebusch, Glenn & Wilms, Ole, 2022. "Where is the carbon premium? Global performance of green and brown stocks," Other publications TiSEM 6b117156-316d-440a-9fa5-b, Tilburg University, School of Economics and Management.
    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. Kyriazis, Nikolaos & Corbet, Shaen, 2025. "Understanding the connectedness between US traditional assets and green cryptocurrencies during crises," The North American Journal of Economics and Finance, Elsevier, vol. 80(C).
    2. Amedeo Argentiero & Giovanni Bonaccolto & Giulio Pedrini, 2024. "Green finance: Evidence from large portfolios and networks during financial crises and recessions," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 31(3), pages 2474-2495, May.
    3. Konstantina Ragazou & Ioannis Passas & Alexandros Garefalakis & Eleni Zafeiriou & Grigorios Kyriakopoulos, 2022. "The Determinants of the Environmental Performance of EU Financial Institutions: An Empirical Study with a GLM Model," Energies, MDPI, vol. 15(15), pages 1-15, July.
    4. Weilong Liu & Yanchu Liu, 2025. "Covariance Matrix Estimation for Positively Correlated Assets," Papers 2507.01545, arXiv.org.
    5. Xu, Chong & Tao, Miaomiao & Qi, Lingli & Roubaud, David, 2025. "Can green CEOs trigger the green premium effect?," Finance Research Letters, Elsevier, vol. 80(C).
    6. Malavasi, Matteo & Ortobelli Lozza, Sergio & Trück, Stefan, 2021. "Second order of stochastic dominance efficiency vs mean variance efficiency," European Journal of Operational Research, Elsevier, vol. 290(3), pages 1192-1206.
    7. Alex Huang, 2013. "Value at risk estimation by quantile regression and kernel estimator," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 225-251, August.
    8. Nathan Lassance & Alberto Martín-Utrera & Majeed Simaan, 2024. "The Risk of Expected Utility Under Parameter Uncertainty," Management Science, INFORMS, vol. 70(11), pages 7644-7663, November.
    9. Nathan Lassance & Victor DeMiguel & Frédéric Vrins, 2022. "Optimal Portfolio Diversification via Independent Component Analysis," Operations Research, INFORMS, vol. 70(1), pages 55-72, January.
    10. Liusha Yang & Romain Couillet & Matthew R. McKay, 2015. "A Robust Statistics Approach to Minimum Variance Portfolio Optimization," Papers 1503.08013, arXiv.org.
    11. Sleire, Anders D. & Støve, Bård & Otneim, Håkon & Berentsen, Geir Drage & Tjøstheim, Dag & Haugen, Sverre Hauso, 2022. "Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations," Finance Research Letters, Elsevier, vol. 46(PB).
    12. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Efficient skewness/semivariance portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 17(5), pages 331-346, September.
    13. Seyoung Park & Eun Ryung Lee & Sungchul Lee & Geonwoo Kim, 2019. "Dantzig Type Optimization Method with Applications to Portfolio Selection," Sustainability, MDPI, vol. 11(11), pages 1-32, June.
    14. McDowell, Shaun, 2018. "An empirical evaluation of estimation error reduction strategies applied to international diversification," Journal of Multinational Financial Management, Elsevier, vol. 44(C), pages 1-13.
    15. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Papers 1910.13960, arXiv.org, revised Oct 2020.
    16. Jacobs, Heiko & Müller, Sebastian & Weber, Martin, 2014. "How should individual investors diversify? An empirical evaluation of alternative asset allocation policies," Journal of Financial Markets, Elsevier, vol. 19(C), pages 62-85.
    17. Olivier Ledoit & Michael Wolf, 2022. "Markowitz portfolios under transaction costs," ECON - Working Papers 420, Department of Economics - University of Zurich, revised Sep 2024.
    18. Francesco Lautizi, 2015. "Large Scale Covariance Estimates for Portfolio Selection," CEIS Research Paper 353, Tor Vergata University, CEIS, revised 07 Aug 2015.
    19. Jarrow, Robert A. & Kwok, Simon S., 2023. "Futures contract collateralization and its implications," Journal of Empirical Finance, Elsevier, vol. 74(C).
    20. Christopher Kath & Florian Ziel, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Papers 1811.08604, arXiv.org.

    More about this item

    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:bat:basiq1:2024:055. 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: BASIQ / Bucharest University of Economic Studies (email available below). General contact details of provider: https://conference.ase.ro/ .

    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.