Climate change is increasingly recognised not only as an environmental issue but also as a financial risk for companies and investors. Extreme weather events such as hurricanes, floods, droughts and heatwaves are becoming more frequent and costly. As a result, policymakers, investors and regulators are exploring how the costs of these events might be linked to the companies whose emissions contribute to global warming.

A recent academic study proposes a new framework for estimating the potential financial liabilities companies may face due to climate-related extreme weather events. The research connects climate science with financial valuation models to help analysts better understand how emissions could affect company value.

Linking Emissions to Financial Risk

The starting point of the research is a simple idea: greenhouse gas emissions contribute to global warming, which increases the likelihood and severity of extreme weather events. Climate science now allows researchers to estimate how much more likely certain events have become due to human activity using a metric called the Fraction of Attributable Risk (FAR).

By combining these climate attribution methods with economic data, it becomes possible to estimate what proportion of the damage from an extreme weather event might be linked to emissions. The study then allocates a share of that damage to companies based on their historical contribution to global emissions.

A Financial Model for Climate Liability

To estimate how these costs could affect corporate valuations, the researchers adapt the Gordon Growth Model, a common tool used in finance to value companies. Instead of modelling dividends, the model estimates the present value of future climate-related liabilities.

The approach assumes that extreme weather events will not only continue to occur but may also become more frequent as global warming intensifies. This means potential climate liabilities could grow over time rather than being treated as one-off events.

Using this framework, analysts can estimate:

• The damage caused by extreme weather events

• The proportion of those damages attributable to global warming

• A company’s share of global emissions

• The portion of damages society might hold companies responsible for

These inputs allow analysts to estimate the expected annual climate liability for a company and its present value.

What the Results Suggest

The study illustrates the model using a hypothetical high-emissions company. Applying data from the 2017 North Atlantic hurricane season, the researchers estimate potential climate liabilities equivalent to roughly 3% of the company’s market capitalisation.

While this is only an illustrative example, it highlights how climate risks could meaningfully affect corporate valuations, particularly for companies with high emissions.

Why This Matters for Investors

Climate risk is increasingly relevant for investors, regulators and businesses. Financial markets are beginning to incorporate emissions-related risks through mechanisms such as:

• Climate-related financial disclosures

• Carbon pricing policies

• Climate litigation

• Investor demand for lower-emissions companies

If climate liabilities become more widely recognised, companies with higher emissions may face higher risk premiums, reduced valuations and increased regulatory pressure.

Looking Ahead

The framework proposed in this research offers a practical way to connect climate science with financial analysis. By estimating the potential cost of emissions-related damages, analysts can better assess climate risks and incorporate them into investment decisions.

As extreme weather events become more frequent and climate accountability grows, understanding these financial implications will be increasingly important for investors, policymakers and companies alike.

If you'd like to read the full article by Dr. Quintin Rayer and Professor Panagiotis Andrikopoulos, please take a read here: https://www.emerald.com/jaar/article/27/6/22/1346075/Extreme-weather-attribution-re-assessing-company