IDEAS home Printed from https://ideas.repec.org/p/bis/biswps/1362.html

Embracing carbon uncertainty in portfolio construction

Author

Listed:
  • Dora Xia
  • Omar Zulaica

Abstract

We propose a framework for constructing fixed-income portfolios of sovereign bonds that integrates financial and environmental considerations. Central to our approach is the introduction of carbon returns, a concept analogous to financial returns, modeled as random variables to capture the inherent uncertainty of future carbon emissions. Based on the financial and carbon return profiles of individual countries' sovereign bonds, we employ an algorithm inspired by Hierarchical Risk Parity (HRP) to construct portfolios that balance each country's contribution to the portfolio's tail risk, as measured by expected shortfall, of financial and carbon returns. Focusing on developed market sovereign bonds, our results demonstrate that it is possible to design portfolios that effectively align decarbonization objectives with financial performance, both in-sample and out-of-sample, while accommodating diverse investor preferences.

Suggested Citation

  • Dora Xia & Omar Zulaica, 2026. "Embracing carbon uncertainty in portfolio construction," BIS Working Papers 1362, Bank for International Settlements.
  • Handle: RePEc:bis:biswps:1362
    as

    Download full text from publisher

    File URL: https://www.bis.org/publ/work1362.pdf
    File Function: Full PDF document
    Download Restriction: no

    File URL: https://www.bis.org/publ/work1362.htm
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    2. Alexander J. McNeil & Rüdiger Frey & Paul Embrechts, 2015. "Quantitative Risk Management: Concepts, Techniques and Tools Revised edition," Economics Books, Princeton University Press, edition 2, number 10496, December.
    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. Nevrla, Matěj, 2020. "Systemic risk in European financial and energy sectors: Dynamic factor copula approach," Economic Systems, Elsevier, vol. 44(4).
    2. Sundusit Saekow & Phisanu Chiawkhun & Woraphon Yamaka & Nawapon Nakharutai & Parkpoom Phetpradap, 2024. "Estimation of Contagion: Bayesian Model Averaging on Tail Dependence of Mixture Copula," Mathematics, MDPI, vol. 12(21), pages 1-23, October.
    3. Tranberg, Bo & Hansen, Rasmus Thrane & Catania, Leopoldo, 2020. "Managing volumetric risk of long-term power purchase agreements," Energy Economics, Elsevier, vol. 85(C).
    4. Alexander J. McNeil, 2020. "Modelling volatile time series with v-transforms and copulas," Papers 2002.10135, arXiv.org, revised Jan 2021.
    5. Tiwari, Aviral Kumar & Adewuyi, Adeolu O. & Albulescu, Claudiu T. & Wohar, Mark E., 2020. "Empirical evidence of extreme dependence and contagion risk between main cryptocurrencies," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    6. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    7. Hofert, Marius & Prasad, Avinash & Zhu, Mu, 2022. "Multivariate time-series modeling with generative neural networks," Econometrics and Statistics, Elsevier, vol. 23(C), pages 147-164.
    8. Zhicheng Liang & Junwei Wang & Kin Keung Lai, 2020. "Dependence Structure Analysis and VaR Estimation Based on China’s and International Gold Price: A Copula Approach," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 169-193, February.
    9. Martin Bladt & Alexander J. McNeil, 2020. "Time series copula models using d-vines and v-transforms," Papers 2006.11088, arXiv.org, revised Jul 2021.
    10. Alexander J. McNeil, 2021. "Modelling Volatile Time Series with V-Transforms and Copulas," Risks, MDPI, vol. 9(1), pages 1-26, January.
    11. Kojadinovic, Ivan & Stemikovskaya, Kristina, 2019. "Subsampling (weighted smooth) empirical copula processes," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 704-723.
    12. Damette, Olivier & Goutte, Stéphane, 2023. "Beyond climate and conflict relationships: New evidence from a Copula-based analysis on an historical perspective," Journal of Comparative Economics, Elsevier, vol. 51(1), pages 295-323.
    13. Perreault, Samuel & Duchesne, Thierry & Nešlehová, Johanna G., 2019. "Detection of block-exchangeable structure in large-scale correlation matrices," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 400-422.
    14. Li, Guowen & Jing, Zhongbo & Li, Jingyu & Feng, Yuyao, 2023. "Drivers of risk correlation among financial institutions: A study based on a textual risk disclosure perspective," Economic Modelling, Elsevier, vol. 128(C).
    15. Tian, Maoxi & El Khoury, Rim & Alshater, Muneer M., 2023. "The nonlinear and negative tail dependence and risk spillovers between foreign exchange and stock markets in emerging economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    16. Abduraimova, Kumushoy, 2022. "Contagion and tail risk in complex financial networks," Journal of Banking & Finance, Elsevier, vol. 143(C).
    17. F. Durante & A. Gatto & F. Ravazzolo, 2024. "Understanding relationships with the Aggregate Zonal Imbalance using copulas," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(2), pages 513-554, April.
    18. Salvatore D. Tomarchio & Michael P. B. Gallaugher, 2026. "Mixtures of regressions using matrix-variate heavy-tailed distributions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 20(1), pages 11-38, March.
    19. Tobias Fissler & Yannick Hoga, 2024. "How to Compare Copula Forecasts?," Papers 2410.04165, arXiv.org.
    20. F. Marta L. Di Lascio & Andrea Menapace & Roberta Pappadà, 2024. "A spatially‐weighted AMH copula‐based dissimilarity measure for clustering variables: An application to urban thermal efficiency," Environmetrics, John Wiley & Sons, Ltd., vol. 35(1), February.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:bis:biswps:1362. 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: Martin Fessler (email available below). General contact details of provider: https://edirc.repec.org/data/bisssch.html .

    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.