Hedging carbon risk with a network approach

Michele Azzone, Maria Chiara Pocelli and Davide Stocco

Physica A: Statistical Mechanics and its Applications, 2025, vol. 676, issue C

Abstract: Sustainable investing involves the incorporation of environmental and social factors into the decision-making processes. We propose a novel methodology based on the Triangulated Maximally Filtered Graph and node2vec algorithms to construct an hedging portfolio for climate risk, represented by various risk factors, among which the CO2 and the ESG ones. The CO2 factor is strongly correlated consistently over time with the Utility sector, which is the most carbon intensive in the S&P 500 index. Conversely, identifying a group of sectors linked to the ESG factor proves challenging. As a consequence, while it is possible to obtain an efficient hedging portfolio strategy with our methodology for the carbon factor, the same cannot be achieved for the ESG one. The ESG scores appears to be an indicator too broadly defined for market applications. These results support the idea that bank capital requirements should take into account carbon risk.

Keywords: Network embedding; Risk factors; Hedging; Carbon; Sustainability (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:676:y:2025:i:c:s0378437125005102

DOI: 10.1016/j.physa.2025.130858

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