Hedging carbon risk with a network approach

Paper: arXiv 2311.12450

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.

Complexity vs Empirical Score

• Math Complexity: 7.5/10
• Empirical Rigor: 6.0/10 (capped from 8.0: transaction costs not modelled; no out-of-sample test; see penalty flags)
• Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper employs advanced network theory concepts (TMFG, node2vec) and statistical methods, indicating high math complexity, while it provides a specific, backtest-ready methodology with empirical results on S&P 500 data and risk metrics, demonstrating strong empirical rigor.

Research Flowchart

  flowchart TD
  A["Research Goal: Hedge Climate Risk in Equities (S&P 500)"] --> B["Input Data: Historical Price Data & Risk Factors<br/>(CO2 Intensity, ESG Scores)"]
  B --> C["Core Methodology: Network Approach"]
  C --> D["Step 1: Triangulated Maximally Filtered Graph<br/>(Construct Asset Network)"]
  C --> E["Step 2: node2vec Algorithm<br/>(Extract Structural Embeddings)"]
  D & E --> F["Compute Correlations &<br/=> Build Hedging Portfolios"]
  F --> G["Key Findings & Outcomes"]
  G --> H["CO2 Factor:<br/>Successfully Hedged<br/>(Strong link to Utility Sector)"]
  G --> I["ESG Factor:<br/>Hedge Failed<br/>(Indicator too broad for market application)"]
  G --> J["Policy Implication:<br/>Bank Capital Requirements should<br/>incorporate Carbon Risk"]

Cited References (27)

1. Tilting the Wrong Firms? How Inflated ESG Ratings Negate Socially Responsible Investing under Information Asymmetries (2022)
2. The rise in investors’ awareness of climate risks after the Paris Agreement and the clean energy-oil-technology prices nexus (2022)
3. The impact of carbon disclosure and carbon emissions intensity on firms’ idiosyncratic volatility ({2023} publisher={Elsevier})
4. The environmental pillar of ESG and financial performance: A portfolio analysis (2023)
5. Reformulating taxes for an energy transition (2019)
6. Green investment and asset stranding under transition scenario uncertainty (2023)
7. The sharpe ratio (1998)
8. Carbon beta: A market-based measure of climate risk (2022)

0 of 27 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.