[Paper Review] Measuring Transition Risk in Investment Funds

Ricardo Crisóstomo|arXiv (Cornell University)|Oct 27, 2022

Market Dynamics and Volatility4 citations

TL;DR

This paper proposes a comprehensive framework to measure climate transition risk in investment funds using granular data across geography, sector, company, and security levels. It finds that funds face a median 5.7% loss under high transition risk, with extreme tail losses reaching -21.3% for the worst 1% of funds, while equities and corporate bonds are most vulnerable, and sustainable funds show lower risk exposure and better performance.

ABSTRACT

We develop a comprehensive framework to measure the impact of the climate transition on investment portfolios. Our analysis is enriched by including geographical, sectoral, company and ISIN-level data to assess transition risk. We find that investment funds suffer a moderate 5.7% loss upon materialization of a high transition risk scenario. However, the risk distribution is significantly left-skewed, with the worst 1% funds experiencing an average loss of 21.3%. In terms of asset classes, equities are the worst performers (-12.7%), followed by corporate bonds (-5.6%) and government bonds (-4.8%). We discriminate among financial instruments by considering the carbon footprint of specific counterparties and the credit rating, duration, convexity and volatility of individual exposures. We find that sustainable funds are less exposed to transition risk and perform better than the overall fund sector in the low-carbon transition, validating their choice as green investments.

Motivation & Objective

• To develop a detailed framework for measuring climate transition risk across investment portfolios.
• To assess the impact of transition risk on different asset classes, funds, and individual securities.
• To evaluate the resilience of sustainable funds relative to the broader fund sector under low-carbon transition scenarios.
• To incorporate counterparty carbon footprints, credit ratings, and fixed-income risk metrics (duration, convexity, volatility) into transition risk assessment.

Proposed method

• The framework integrates geographical, sectoral, company-level, and ISIN-specific data to assess transition risk exposure across investment funds.
• It models transition risk by simulating a high-carbon transition scenario, incorporating carbon intensity of counterparties and credit quality metrics.
• The analysis uses duration, convexity, and volatility to assess interest rate and term structure risk in fixed-income holdings.
• Equities are assessed via sectoral and country-level climate transition risk exposure, with stress testing under policy and transition shocks.
• The framework computes fund-level transition risk by aggregating individual security-level risk metrics, weighted by portfolio holdings.
• Sustainable funds are evaluated based on their lower carbon footprints and improved risk-adjusted performance under transition scenarios.

Experimental results

Research questions

• RQ1 How does climate transition risk affect the overall performance of investment funds under a high-transition-risk scenario?
• RQ2 Which asset classes—equities, corporate bonds, or government bonds—are most vulnerable to transition risk?
• RQ3 To what extent do sustainable funds exhibit lower transition risk and better performance compared to the broader fund sector?
• RQ4 How do individual security-level characteristics such as carbon footprint, credit rating, duration, and volatility influence transition risk exposure?
• RQ5 What is the distribution of transition risk losses across funds, and how severe are tail risks for the worst-performing funds?

Key findings

• Investment funds experience a median loss of 5.7% under a high transition risk scenario, with significant left-skewness in the loss distribution.
• The worst 1% of funds suffer an average loss of 21.3%, indicating substantial tail risk exposure.
• Equities are the most affected asset class, with a -12.7% loss, followed by corporate bonds (-5.6%) and government bonds (-4.8%).
• Sustainable funds are less exposed to transition risk and outperform the broader fund sector in low-carbon transition scenarios.
• Incorporating counterparty carbon footprint, credit rating, duration, convexity, and volatility improves the precision of transition risk measurement.
• The framework demonstrates that granular, security-level risk metrics significantly enhance the accuracy of transition risk assessment in diversified portfolios.