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Mapping global financial risks under climate change

Abstract

There is growing concern about the potential impacts of climate change on financial stability but little quantitative evidence available on the potential magnitude of financial risks induced by climate extremes. Here we provide a forward-looking assessment of the impacts of floods, storms, and wildfires on a universe of securities representative of global market capitalization, using the structural climate credit-risk model CLIMACRED-PHYS. We show that there can be a substantial amplification of direct economic losses arising from firms’ financial leverage. We highlight the importance of cross-border climate financial risks, notably the transfer of impacts from production facilities in emerging economies to firms in developed economies. Finally, we quantify the potential increase of financial risks induced by climate change. Overall, our results emphasize the relevance of asset-level climate risk assessment for financial regulation and the importance of integrating financial impacts in the assessment of adaptation policies.

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Fig. 1: Distribution of losses over the universe of bonds and equities.
Fig. 2: Summary of equity impacts generated and received per country.

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Data availability

All data on natural hazards used in our analysis are publicly available from their respective sources mentioned in Methods. Data on firms’ geolocation can be requested from Sequantis (alou@sequantis.com).

Code availability

Replication code is available from the corresponding author on request but requires at this stage over 1 terabyte of storage space to be executed.

References

  1. Carney, M. Breaking the Tragedy of the Horizon—Climate Change and Financial Stability (Bank of England, 2015); https://www.bankofengland.co.uk/speech/2015/breaking-the-tragedy-of-the-horizon-climate-change-and-financial-stability

  2. A Call for Action: Climate Change as a Source of Financial Risk (NGFS, 2019).

  3. Conceptual Note on Short-Term Climate Scenarios (NGFS, 2023).

  4. Blake, E.S. et al. Costliest US Tropical Cyclones Tables Updated (National Hurricane Center, 2021); https://www.nhc.noaa.gov/news/UpdatedCostliest.pdf

  5. Weather and Climate Extremes in Asia Killed Thousands, Displaced Millions and Cost Billions in 2020 (World Meteorological Organization, 2021); https://wmo.int/media/news/weather-and-climate-extremes-asia-killed-thousands-displaced-millions-and-cost-billions-2020#:~:text=Geneva%2C%2026%20October%202021%20(WMO,toll%20on%20infrastructure%20and%20ecosystems

  6. Special Report: Update to the Economic Costs of Natural Disasters in Australia (Deloitte, 2021); https://www.deloitte.com/content/dam/assets-zone1/au/en/docs/services/economics/deloitte-au-economics-abr-natural-disasters-061021.pdf

  7. IPCC Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021); https://doi.org/10.1017/9781009157896

  8. Weitzman, M. L. On modeling and interpreting the economics of catastrophic climate change. Rev. Econ. Stat. 91, 1–19 (2009).

    Article  Google Scholar 

  9. Pindyck, R. S. Climate change policy: what do the models tell us? J. Econ. Lit. 51, 860–872 (2013).

    Article  Google Scholar 

  10. Bressan, G., Duranović, A., Monasterolo, I. & Battiston, S. Asset-level assessment of climate physical risk matters for adaptation finance. Nat. Commun. 15, 5371 (2024).

    Article  CAS  Google Scholar 

  11. Le Guenedal, T., Drobinski, P. & Tankov, P. Measuring and pricing cyclone-related physical risk under changing climate. Amundi Research Working Paper 111 (2021); https://research-center.amundi.com/files/nuxeo/dl/683eaa33-0ded-41e5-a604-8bea583d4def?inline=

  12. Mandel, A. et al. Risks on global financial stability induced by climate change: the case of flood risks. Climatic Change 166, 4 (2021).

    Article  Google Scholar 

  13. Calabrese, R., Dombrowski, T., Mandel, A., Pace, R. K. & Zanin, L. Impacts of extreme weather events on mortgage risks and their evolution under climate change: a case study on florida. Eur. J. Oper. Res. 314, 377–392 (2024).

    Article  Google Scholar 

  14. Dietz, S., Bowen, A., Dixon, C. & Gradwell, P. Climate value at risk of global financial assets. Nat. Clim. Change 6, 676–679 (2016).

    Article  Google Scholar 

  15. Hain, L. I., Koelbel, J. F. & Leippold, M. Let’s get physical: comparing metrics of physical climate risk. Financ. Res. Lett. 46, 102406 (2022).

    Article  Google Scholar 

  16. Guide on Climate-Related and Environmental Risks: Supervisory Expectations Relating to Risk Management and Disclosure (European Central Bank, 2020).

  17. Basel Committee on Banking Supervision Basel III: Finalising Post-crisis Reforms (Bank for International Settlements, 2021).

  18. Bertram, C. et al. NGFS Climate Scenario Database: Technical Documentation v2.2 (NGFS, 2021).

  19. MSCI ACWI Index (USD) (MSCI, 2021); https://www.msci.com/documents/10199/8d97d244-4685-4200-a24c-3e2942e3adeb

  20. Mahony, M. & Timmer, M. P. Output, input and productivity measures at the industry level: the EU KLEMS database. Econ. J. 119, 374–403 (2009).

    Article  Google Scholar 

  21. Multi-hazard Loss Estimation Methodology, Earthquake Model, Hazus-mh 2.1, Technical Manual (FEMA, 2013).

  22. IPCC Climate Change 2014: Synthesis Report (eds Core Writing Team, Pachauri, R. K. & Meyer L. A.) (IPCC, 2014); https://www.ipcc.ch/report/ar5/syr/

  23. Damodaran, A. Damodaran Online https://pages.stern.nyu.edu/~adamodar/ (accessed 6 January 2024).

  24. Hallegatte, S., Hourcade, J.-C. & Dumas, P. Why economic dynamics matter in assessing climate change damages: illustration on extreme events. Ecol. Econ. 62, 330–340 (2007).

    Article  Google Scholar 

  25. Oosterhaven, J. & Többen, J. Wider economic impacts of heavy flooding in germany: a non-linear programming approach. Spat. Econ. Anal. 12, 404–428 (2017).

    Article  Google Scholar 

  26. Semieniuk, G. et al. Stranded fossil-fuel assets translate to major losses for investors in advanced economies. Nat. Clim. Change 12, 532–538 (2022).

    Article  Google Scholar 

  27. Schubert, J. E., Mach, K. J. & Sanders, B. F. National-scale flood hazard data unfit for urban risk management. Earths Future 12, 2024–004549 (2024).

    Article  Google Scholar 

  28. Battiston, S., Monasterolo, I., Riahi, K. & Ruijven, B. J. Accounting for finance is key for climate mitigation pathways. Science 372, 918–920 (2021).

    Article  CAS  Google Scholar 

  29. Moss, R. H. et al. The next generation of scenarios for climate change research and assessment. Nature 463, 747–756 (2010).

    Article  CAS  Google Scholar 

  30. Warszawski, L. et al. The Inter-sectoral Impact Model Intercomparison Project (ISI–MIP): project framework. Proc. Natl Acad. Sci. USA 111, 3228–3232 (2014).

    Article  CAS  Google Scholar 

  31. Frieler, K. et al. Assessing the impacts of 1.5 °C global warming–simulation protocol of the Inter-sectoral Impact Model Intercomparison Project (ISIMIP2b). Geosci. Model Dev. 10, 4321–4345 (2017).

    Article  Google Scholar 

  32. Dufresne, J.-L. et al. Climate change projections using the IPSLl-CM5 Earth system model: from CMIP3 to CMIP5. Clim. Dyn. 40, 2123–2165 (2013).

    Article  Google Scholar 

  33. Aznar-Siguan, G. & Bresch, D. N. Climada v1: a global weather and climate risk assessment platform. Geosci. Model Dev. 12, 3085–3097 (2019).

    Article  Google Scholar 

  34. Knapp, K. R., Kruk, M. C., Levinson, D. H., Diamond, H. J. & Neumann, C. J. The International Best Track Archive for Climate Stewardship (IBTRACS) unifying tropical cyclone data. Bull. Am. Meteorol. Soc. 91, 363–376 (2010).

    Article  Google Scholar 

  35. Knutson, T. R. et al. Global projections of intense tropical cyclone activity for the late twenty-first century from dynamical downscaling of CMIP5/RCP4.5 scenarios. J. Clim. 28, 7203–7224 (2015).

    Article  Google Scholar 

  36. Emanuel, K. Global warming effects on US hurricane damage. Weather Clim. Soc. 3, 261–268 (2011).

    Article  Google Scholar 

  37. Synthetic Windstorm Events for Europe from 1986 to 2011 (Copernicus Climate Change Service Climate Data Store, 2022); https://doi.org/10.24381/cds.ce973f02

  38. Feser, F. et al. Storminess over the North Atlantic and northwestern European review. Q. J. R. Meteorol. Soc. 141, 350–382 (2015).

    Article  Google Scholar 

  39. Ranson, M., Tarquinio, L. & Lew, A. Modeling the Impact of Climate Change on Extreme Weather Losses. Environmental Economics Working Paper Series 02 (US Environmental Protection Agency, 2016); https://www.epa.gov/sites/default/files/2016-05/documents/2016-02.pdf

  40. Feuerstein, B. et al. Towards an improved wind speed scale and damage description adapted for central europe. Atmos. Res. 100, 547–564 (2011).

    Article  Google Scholar 

  41. Ward, P. J. et al. Aqueduct Floods Methodology (World Resources Institute, 2020).

  42. Winsemius, H., Van Beek, L., Jongman, B., Ward, P. & Bouwman, A. A framework for global river flood risk assessments. Hydrol. Earth Syst. Sci. 17, 1871–1892 (2013).

    Article  Google Scholar 

  43. Huizinga, J. et al. Global Flood Depth–Damage Dunctions: Methodology and the Database with Guidelines (Joint Research Centre, 2017).

  44. Fire Burned Area from 2001 to Present Derived from Satellite Observations (Copernicus Climate Change Service (Climate Data Store, 2019); https://doi.org/10.24381/cds.f333cf85

  45. Land Cover CCI Product User Guide Version 2.0 (ESA, 2017). http://maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdf

  46. Pettinari, M.L., Lizundia-Loiola, J. & Chuvieco, E. ESA CCI ECV Fire Disturbance: D4.2 Product User Guide - MODIS v.1.0. (ESA, 2020); https://www.esa-fire-cci.org/documents

  47. Sullivan, A. et al. Spreading Like Wildfire: The Rising Threat of Extraordinary Landscape Fires (United Nations Environment Programme, 2022); https://wedocs.unep.org/bitstream/handle/20.500.11822/38372/wildfire_RRA.pdf

  48. Nadim, F., Kjekstad, O., Peduzzi, P., Herold, C. & Jaedicke, C. Global landslide and avalanche hotspots. Landslides 3, 159–173 (2006).

    Article  Google Scholar 

  49. Hicks, D. A way to estimate the frequency of rainfall-induced mass movements (note). J. Hydrol. 33, 59–67 (1995).

  50. Crozier, M. J. Deciphering the effect of climate change on landslide activity: a review. Geomorphology 124, 260–267 (2010).

    Article  Google Scholar 

  51. Dasgupta, S. et al. Effects of climate change on combined labour productivity and supply: an empirical, multi-model study. Lancet Planet. Health 5, 455–465 (2021).

    Article  Google Scholar 

  52. Stull, R. Wet-bulb temperature from relative humidity and air temperature. J. Appl. Meteorol. Climatol. 50, 2267–2269 (2011).

    Article  Google Scholar 

  53. Kjellstrom, T. et al. Occupational Heat Stress: Contribution to WHO Project on “Global assessment of the health impacts of climate change”, Which Started in 2009 (HEIT, 2014).

  54. Santos, J.A. & Viswanathan, S.V. Bank Syndicates and Liquidity Provision (NBER, 2020).

  55. Merton, R. C. On the pricing of corporate debt: the risk structure of interest rates. J. Financ. 29, 449–470 (1974).

    Google Scholar 

  56. Battiston, S., Mandel, A., Monasterolo, I. & Roncoroni, A. Climate credit risk and corporate valuation. SSRN https://doi.org/10.2139/ssrn.4124002 (2023).

  57. Garbarino, N. & Guin, B. High water, no marks? Biased lending after extreme weather. J. Financ. Stab. 54, 100874 (2021).

    Article  Google Scholar 

  58. Nguyen, D. D., Ongena, S., Qi, S. & Sila, V. Climate change risk and the cost of mortgage credit. Rev. Financ. 26, 1509–1549 (2022).

    Article  Google Scholar 

  59. Deghi, A. et al. Global Financial Stability Report: Markets in the Time of COVID-19 (IMF, 2021).

  60. Gostlow, G. Anything goes: pricing physical climate risk. SSRN https://ssrn.com/abstract=3501013 (2024).

  61. Acharya, V.V., Johnson, T., Sundaresan, S. & Tomunen, T. Is Physical Climate Risk Priced? Evidence from Regional Variation in Exposure to Heat Stress (NBER, 2022).

  62. Kruttli, M.S., Roth Tran, B. & Watugala, S.W. Pricing Poseidon: extreme weather uncertainty and firm return dynamics. SSRN https://doi.org/10.2139/ssrn.3284517 (2023).

  63. Braun, A., Braun, J. & Weigert, F. Extreme weather risk and the cross-section of stock returns. SSRN https://doi.org/10.2139/ssrn.3952620 (2021).

  64. Briere, M., Duranovic, A., Huynh, K., Monasterolo, I. & Ramelli, S. Does the Stock Market Price Physical Climate Risks? (Amundi, 2024).

  65. Hong, H., Li, F. W. & Xu, J. Climate risks and market efficiency. J. Econ. 208, 265–281 (2019).

    Article  Google Scholar 

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Acknowledgements

The authors acknowledge the financial support from the European Union’s Horizon Europe research and innovation programme under the grant agreement no. 101056898 DECIPHER (Decision-making Framework and Processes for Holistic Evaluation of Environmental and Climate policies). In particular, the work of A.M. on this paper has been entirely supported by CLIMAFIN through the DECIPHER project.

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A.M., S.B. and I.M. designed the research. A.M. designed the model and the computational framework. A.M. wrote the paper. S.B. and I.M. provided comments and suggestions.

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Correspondence to Antoine Mandel.

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Nature Climate Change thanks Gregor Semieniuk and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Mandel, A., Battiston, S. & Monasterolo, I. Mapping global financial risks under climate change. Nat. Clim. Chang. 15, 329–334 (2025). https://doi.org/10.1038/s41558-025-02244-x

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