A climate stress-test of the financial system


The urgency of estimating the impact of climate risks on the financial system is increasingly recognized among scholars and practitioners. By adopting a network approach to financial dependencies, we look at how climate policy risk might propagate through the financial system. We develop a network-based climate stress-test methodology and apply it to large Euro Area banks in a ‘green’ and a ‘brown’ scenario. We find that direct and indirect exposures to climate-policy-relevant sectors represent a large portion of investors’ equity portfolios, especially for investment and pension funds. Additionally, the portion of banks’ loan portfolios exposed to these sectors is comparable to banks’ capital. Our results suggest that climate policy timing matters. An early and stable policy framework would allow for smooth asset value adjustments and lead to potential net winners and losers. In contrast, a late and abrupt policy framework could have adverse systemic consequences.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: Diagram illustrating the reclassification of sectors from NACE Rev2 codes into climate-policy-relevant sectors.
Figure 2: Equity holdings in EU and US listed companies in 2015 (data from Bureau Van Dijk Orbis).
Figure 3: First- and second-round losses in banks’ equity for the 20 most-severely affected EU listed banks, under the Fossil fuel + Utilities 100% shock.
Figure 4: Individual banks’ value at risk under green and brown investment strategies.


  1. 1

    Carney, M. Breaking the tragedy of the horizon–climate change and financial stability Lloyd’s (29 September 2015); http://www.bankofengland.co.uk/publications/Pages/speeches/2015/844.aspx

  2. 2

    Too Late, Too Sudden: Transition to a Low-Carbon Economy and Systemic Risk (ESRB Advisory Scientific Committee, 2016).

  3. 3

    McGlade, C. & Ekins, P. The geographical distribution of fossil fuels unused when limiting global warming to 2 °C. Nature 517, 187–190 (2015).

    CAS  Article  Google Scholar 

  4. 4

    Meinshausen, M. et al. Greenhouse-gas emission targets for limiting global warming to 2 °C. Nature 458, 1158–1162 (2009).

    CAS  Article  Google Scholar 

  5. 5

    Leaton, J. Unburnable Carbon—are the World’s Financial Markets Carrying a Carbon Bubble 1–36 (Carbon Tracker Initiative, 2012).

    Google Scholar 

  6. 6

    Robins, N., Keen, A. & Night, Z. Coal and Carbon Stranded Assets: Assessing the Risk (HSBC, 2012).

    Google Scholar 

  7. 7

    Fleischman, L., Cleetus, R., Deyette, J., Clemmer, S. & Frenkel, S. Ripe for retirement: an economic analysis of the US coal fleet. Electr. J. 26, 51–63 (2013).

    Google Scholar 

  8. 8

    Caldecott, B. & Robins, N. Greening China’s Financial Markets: The Risks and Opportunities of Stranded Assets Briefing Paper 1–29 (Smith School et Enquête du PNUE, 2014).

    Google Scholar 

  9. 9

    World Resource Institute and UNEP-FI Carbon Asset Risk Discussion Framework Tech. Rep. 1–67 (2015).

  10. 10

    Weyzig, F., Kuepper, B., van Gelder, J. W. & Van Tilburg, R. The Price of Doing Too Little Too Late Tech. Rep. 1–69 (Green European Foundation, 2014).

    Google Scholar 

  11. 11

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

    Article  Google Scholar 

  12. 12

    Nordhaus, W. D. Rolling the ‘DICE’: an optimal transition path for controlling greenhouse gases. Resour. Energy Econ. 15, 27–50 (1993).

    Article  Google Scholar 

  13. 13

    Nordhaus, W. D. The economics of tail events with an application to climate change. Rev. Environ. Econ. Policy 5, 240–257 (2011).

    Article  Google Scholar 

  14. 14

    Battiston, S., Caldarelli, G., Georg, C.-P., May, R. & Stiglitz, J. Complex derivatives. Nat. Phys. 9, 123–125 (2013).

    CAS  Article  Google Scholar 

  15. 15

    Battiston, S. et al. Complexity theory and financial regulation. Science 351, 818–819 (2016).

    CAS  Article  Google Scholar 

  16. 16

    Battiston, S., D’Errico, M. & Gurciullo, S. DebtRank and the network of leverage. J. Altern. Invest. 18, 68–81 (2016).

    Article  Google Scholar 

  17. 17

    Battiston, S., Roukny, T., Stiglitz, J., Caldarelli, G. & May, R. The price of complexity. Proc. Natl Acad. Sci. USA 113, 10031–10036 (2016).

    CAS  Article  Google Scholar 

  18. 18

    May, R. M., Levin, S. A. & Sugihara, G. Complex systems: ecology for bankers. Nature 451, 893–895 (2008).

    CAS  Article  Google Scholar 

  19. 19

    Haldane, A. G. & May, R. M. Systemic risk in banking ecosystems. Nature 469, 351–355 (2011).

    CAS  Article  Google Scholar 

  20. 20

    Rogelj, J. et al. Emission pathways consistent with a 2 °C global temperature limit. Nat. Clim. Change 1, 413–418 (2011).

    Article  Google Scholar 

  21. 21

    Peters, G. P. The ‘best available science’ to inform 1.5 °C policy choices. Nat. Clim. Change 6, 646–649 (2016).

    Article  Google Scholar 

  22. 22

    NACE Rev. 2—Statistical Classification of Economic Activities (Eurostat, 2008); http://ec.europa.eu/eurostat/web/nace-rev2

  23. 23

    North American Industry Classification System (United States Census Bureau, 2017); http://www.census.gov/eos/www/naics

  24. 24

    European System of National and Regional Accounts (Eurostat, 2010); http://ec.europa.eu/eurostat/web/esa-2010

  25. 25

    IPCC Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al.) (Cambridge Univ. Press, 2015).

  26. 26

    Kriegler, E. et al. What does the 2 °C target imply for a global climate agreement in 2020? The LIMITS study on Durban Platform scenarios. Clim. Change Econ. 4, 1340008 (2013).

    Article  Google Scholar 

  27. 27

    Battiston, S., Puliga, M., Kaushik, R., Tasca, P. & Caldarelli, G. DebtRank: too central to fail? Financial networks, the FED and systemic risk. Sci. Rep. 2, 541 (2012).

    CAS  Article  Google Scholar 

  28. 28

    Battiston, S., Caldarelli, G., D’errico, M. & Gurciullo, S. Leveraging the network: a stress-test framework based on DebtRank. Stat. Risk Model. 33, 1–33 (2016).

    Article  Google Scholar 

  29. 29

    Eisenberg, L. & Noe, T. H. Systemic risk in financial systems. Manage. Sci. 47, 236–249 (2001).

    Article  Google Scholar 

  30. 30

    Battiston, S., D’Errico, M. & Visentin, G. Rethinking Financial Contagion Working paper series no. 2831143 (2016).

  31. 31

    Basel Committee on Banking Supervision: Capital Requirements for Banks’ Equity Investments in Funds (Bank for International Settlements, 2013); http://www.bis.org/publ/bcbs266.pdf

  32. 32

    Statistical Data Warehouse (European Central Bank, 2017); http://sdw.ecb.europa.eu

  33. 33

    Recommendations of the Task-Force on Climate-Related Financial Disclosure (Financial Stability Board, 2016); https://www.fsb-tcfd.org/publications/recommendations-report/

  34. 34

    Wolf, S., Schütze, F. & Jaeger, C. C. Balance or synergies between environment and economy a note on model structures. Sustainability 8, 761 (2016).

    Article  Google Scholar 

  35. 35

    Towards Green Growth (OECD, 2011).

  36. 36

    Shiller, R. J. Market Volatility (MIT, 1992).

    Google Scholar 

  37. 37

    Mazzucato, M. & Semmler, W. Economic Evolution, and Learning Complexity (Springer, 2002); http://doi.org/fckmx3

    Google Scholar 

  38. 38

    Irvine, P. J. & Pontiff, J. Idiosyncratic return volatility, cash flows, and product market competition. Rev. Financ. Stud. 22, 1149–1177 (2009).

    Article  Google Scholar 

  39. 39

    Brogaard, J. & Detzel, A. The asset-pricing implications of government economic policy uncertainty. Manage. Sci. 61, 3–18 (2015).

    Article  Google Scholar 

  40. 40

    Erickson, P. & Lazarus, M. Accounting for Greenhouse Gas Emissions Associated with the Supply of Fossil Fuels Tech. Rep. 1–4 (2013).

    Google Scholar 

  41. 41

    European Commission: Decision of 27 October 2014 determining, pursuant to Directive 2003/87/EC of the European Parliament and of the Council, a list of sectors and subsectors which are deemed to be exposed to a significant risk of carbon leakage, for the period 2015 to 2019 (notified under document C(2014) 7809); http://data.europa.eu/eli/dec/2014/746/oj

  42. 42

    FSA The Prudential Regime for Trading Activities Tech. Rep. (Financial Services Authority, 2010).

Download references


The authors would like to thank J. E. Stiglitz and A. C. Janetos for fruitful comments on an early version of the paper, M. D’Errico for precious suggestions on macro-network data from the ECB Data Warehouse, and J. Glattfelder for help on equity holdings data extraction from Orbis. We also would like to thank A. Barkawi, P. Monnin and M. Tanaka for their comments during the Bank of England conference on Climate Change and Central Banking. S.B. acknowledges financial support from the Swiss National Fund Professorship grant no. PP00P1-144689. All the authors acknowledge the support of the European Projects Future and Emerging Technologies (FET) SIMPOL (grant no. 610704) and DOLFINS (grant no. 640772), and the European Project SEI Metrics (grant no. 649982).

Author information




All authors contributed to the writing of the manuscript, as well as material and analysis tools. G.V. and S.B. also performed the data analysis.

Corresponding author

Correspondence to Stefano Battiston.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary Information (PDF 1332 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Battiston, S., Mandel, A., Monasterolo, I. et al. A climate stress-test of the financial system. Nature Clim Change 7, 283–288 (2017). https://doi.org/10.1038/nclimate3255

Download citation

Further reading