Modeling value-at-risk for green bonds and clean energy investments

Thomas Adjei Kuffour (), Peterson Owusu Junior () and Patrick Kwashie Akorsu ()
Additional contact information
Thomas Adjei Kuffour: University of Cape Coast
Peterson Owusu Junior: University of Cape Coast
Patrick Kwashie Akorsu: University of Cape Coast

Risk Management, 2025, vol. 27, issue 4, No 5, 26 pages

Abstract: Abstract This study employs 40 GARCH-based VaR models, assuming Gaussian and non-Gaussian distributional innovations to model the risk in green bonds and clean energy investments, addressing a critical gap in existing literature. By utilizing the Model Confidence Set (MCS) technique to generate superior set models (SSMs) and rank them based on the predictive performance of Value-at-Risk (VaR) forecasts, this research offers a more robust and rigorous approach for risk model selection. We employ 1601 daily log-returns of green bond and clean energy, which span 03/12/2017 to 13/12/2023. We find that for both 1% and 5% VaR forecasts, green bonds demonstrate greater heterogeneity across the models compared to clean energy. Specifically, green bonds have the fewest models included in the SSM. Our findings offer valuable insights into the unique risk dynamics of sustainable finance, risk modeling, and risk management. In contributing to the stability of financial systems as they adapt to the global transition toward a low-carbon and sustainable economy, this could not be more important.

Keywords: Clean energy; Green bonds; Model confidence set; Superior set model; Value-at-Risk (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1057/s41283-025-00175-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:risman:v:27:y:2025:i:4:d:10.1057_s41283-025-00175-7

Ordering information: This journal article can be ordered from
https://www.palgrave.com/gp/journal/41283

DOI: 10.1057/s41283-025-00175-7

Access Statistics for this article

Risk Management is currently edited by Igor Loncarski

More articles in Risk Management from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().