ESG Risk: Lessons Learned from Utility Theory

Paper: arXiv 2507.23496

Authors: Sebastian Geissel, Christoph Knochenhauer

Abstract

We propose a new class of monetary risk measures for assessing financial and ESG risk. The construction is based on classical shortfall risk measures with loss function replaced by a multi-attribute utility function. We present an extensive theoretical analysis of these risk measures, showing specifically how properties of the utility function translate into properties of the associated risk measure. We furthermore discuss how these multi-attribute risk measures can be used to compute minimum risk portfolios and show in a numerical study that accounting for ESG risk in optimal portfolio choice has a significant influence on the composition of portfolios.

Complexity vs Empirical Score

• Math Complexity: 7.5/10
• Empirical Rigor: 6.0/10
• Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper provides a rigorous mathematical framework extending shortfall risk measures to multi-attribute ESG and financial utility, filling a notable theoretical gap. It supports its theoretical proofs with a empirical application to S&P 500 assets, though detailed code for replication is not explicitly provided in the excerpt.

Research Flowchart

  flowchart TD
    A[Research Goal: Assess Financial & ESG Risk via Multi-Attribute Utility Theory] --> B[Methodology: Construct Shortfall Risk Measures with Multi-Attribute Loss Functions]
    B --> C[Inputs: Equity Market Data & ESG Metrics]
    C --> D[Computation: Solve Minimum Risk Portfolio Optimization Problem]
    D --> E[Theoretical Findings: Map Utility Properties to Risk Measure Characteristics]
    D --> F[Practical Outcome: ESG Integration Significantly Alters Optimal Portfolio Composition]