Paper: arXiv 2504.19307

Authors: Michele Azzone, Matteo Ghesini, Davide Stocco, Lorenzo Viola

Abstract

Climate-related phenomena are increasingly affecting regions worldwide, manifesting as floods, water scarcity, and heat waves, significantly impairing companies’ assets and productivity. It is essential for asset managers to quantify the exposure of their portfolios to such risk. To this aim, we develop a framework based on the Vasicek model for credit risk that introduces downward jumps due to climate phenomena in a company asset’s dynamics. These negative shocks are designed to mirror the negative effect of extreme climate events. The model calibration relies on companies’ asset intensity and geographical exposure. We apply the new multivariate firm value model with jumps to assess the impact of climate-related extreme events on expected and unexpected portfolio losses. Our findings indicate that expected losses increase over time, with pronounced differences in exposure observed across sectoral indices. From an environmental policy perspective, these results suggest the need for additional capital buffers to offset losses arising from physical climate risks, particularly in sectors with high asset intensity.

Complexity vs Empirical Score

  • Math Complexity: 6.5/10
  • Empirical Rigor: 6.0/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper provides an original adaptation of the Vasicek firm value model by adding jump processes to quantify physical climate risk in stock portfolios. It effectively bridges mathematical modeling with practical risk management application using accessible macro-data like the ND-GAIN index.

Research Flowchart

  flowchart TD
    A[Goal: Quantify Portfolio Credit Risk from Physical Climate Events] --> B[Inputs: Firm Asset Intensity & Geographical Exposure Data]
    B --> C[Methodology: Extend Vasicek Credit Model with Negative Climate Jumps]
    C --> D[Calibration & Simulation of Multivariate Firm Value Dynamics]
    D --> E[Outcomes: Higher Expected Losses Over Time & Sectoral Variance]
    E --> F[Policy Implication: Need Capital Buffers for High Asset-Intensity Sectors]

Cited References (48)

  1. On the pricing of corporate debt: The risk structure of interest rates (1974)
  2. Climate-related risks in financial assets (2023)
  3. Rollover risk and credit spreads: Evidence from international corporate bonds (2016)
  4. Additive normal tempered stable processes for equity derivatives and power-law scaling (2022)
  5. Hawkes processes and their applications to finance: a review (2018)
  6. Quantitative risk management: concepts, techniques and tools-revised edition (2015)
  7. Good and bad credit contagion: Evidence from credit default swaps (2007)
  8. How (Not) to Measure Companies’ Climate Transition Risk: A Framework and Categorized Literature Review (2025)
and 40 more
  1. External pressures or internal governance–what determines the extent of corporate responses to climate change? (2018)
  2. Corporate adaptation behaviour to deal with climate change: the influence of firm-specific interpretations of physical climate impacts (2016)
  3. Capital asset prices: A theory of market equilibrium under conditions of risk (1964)
  4. Poor and vulnerable countries need support to adapt to climate change (2022)
  5. Uncovering ESG Ratings: The (Im) Balance of Aspirational and Performance Features (2025)
  6. Probability of loss on loan portfolio (1987)
  7. What do firms say in reporting on impacts of climate change? An approach to monitoring ESG actions and environmental policy (2023)
  8. What do we know about ESG and risk? A systematic and bibliometric review (2024)
  9. A simple option formula for general jump-diffusion and other exponential L 'e vy processes (2001)
  10. University of Notre Dame global adaptation initiative-country index technical report (2024)
  11. Corporate debt value under transition scenario uncertainty (2024)
  12. Climate transition risk in US loan portfolios: Are all banks the same? (2023)
  13. A comparative anatomy of credit risk models (2000)
  14. A socio-technical approach for the assessment of critical infrastructure system vulnerability in extreme weather events (2023)
  15. Options, futures, and other derivatives (2016)
  16. The term structure of credit spreads with jump risk (2001)
  17. Explaining credit default swap spreads with the equity volatility and jump risks of individual firms (2009)
  18. A risk-factor model foundation for ratings-based bank capital rules (2003)
  19. University of Notre Dame global adaptation index (2015)
  20. Half a degree and rapid socioeconomic development matter for heatwave risk (2019)
  21. Fighting climate change: International attitudes toward climate policies (2022)
  22. Climate impact investing (2023)
  23. Climate risk and capital structure (2023)
  24. Climate value at risk of global financial assets (2016)
  25. Let’s get physical: Comparing metrics of physical climate risk (2022)
  26. Asset-level assessment of climate physical risk matters for adaptation finance (2024)
  27. Quantitative Risk Management: Concepts, Techniques and tools (2005)
  28. Introduction to HPC with MPI for Data Science (2016)
  29. Option valuation using the fast Fourier transform (1999)
  30. Modeling default risk (2019)
  31. Capital equipment analysis: the required rate of profit (1956)
  32. Asset-level assessment of climate physical risk matters for adaptation finance (2023)
  33. Ask BERT : H ow regulatory disclosure of transition and physical climate risks affects the CDS term structure (2024)
  34. Climate change and global environmental politics: North-South divide (2017)
  35. Global pricing of carbon-transition risk (2023)
  36. Climate change, firm performance, and investor surprises (2023)
  37. Nature stress testing and value at risk (2024)
  38. Minimum capital requirements for market risk (2019)
  39. Climate change: Strategies for mitigation and adaptation (2023)
  40. State of wildfires 2023–2024 (2024)

0 of 48 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.