Hedging carbon risk with a network approach

TL;DR

This paper introduces a network-based methodology to construct hedging portfolios for climate risk factors, demonstrating effectiveness for carbon risk but limitations for ESG risk due to broad indicator definitions.

Contribution

The paper presents a novel approach combining Triangulated Maximally Filtered Graph and node2vec algorithms to hedge climate risk factors, highlighting sector correlations and limitations for ESG.

Findings

Effective hedging for CO2 risk using the proposed network approach

Strong correlation between CO2 factor and Utility sector over time

Limited success in hedging ESG risk due to broad indicator scope

Abstract

Sustainable investing refers to the integration of environmental and social aspects in investors' decisions. 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.