Green Risk in Europe 

By | October 19, 2023

Aligning financial market activity with policy and regulation interventions is necessary to foster an orderly transition to a carbon-free economy. For instance, within the European Green Deal strategy, the European Union Taxonomy provides firms, investors, and policymakers with detailed criteria to assess the environmental sustainability of economic activities concerning climate change mitigation and adaptation, among other sustainability objectives. 

Directing funding and investments towards sustainable projects and activities should make the EU more resilient against climate change and environmental disasters. Ideally, the EU Taxonomy should enhance the security and protection of investors from greenwashing, help companies along the green transition, and help shift investments to where their “green” or “sustainability” return is highest. It will also impose company costs regarding strategy changes, reporting, and disclosure. It is crucial to assess how the stock market is pricing firms’ activities along their green transition path. This evaluation helps determine the impact of the transparency and disclosure requirements imposed by the Sustainable Finance Disclosure Regulation (SFDR) and the EU Taxonomy Regulation in directing financial investments toward products that are or at least are classified as, environmentally sustainable. Given the significant investments required for climate change mitigation and adaptation, assessing to what extent financial markets are already pricing these risks is of the essence.  

From an asset pricing perspective, many studies seek to explain the cross-sectional pattern of stock returns based on systematic risk factors augmented by a climate change or environmental risk factor. Some researchers introduce an arbitrary firm-level measure as a proxy for the firms’ environmental/climate risk exposure and use it to build a long/short portfolio and study its pricing in the market. Another strand of asset pricing literature assesses ‘climate sentiment’ measures constructed using textual and narrative analysis on climate change news from newspapers, Reuters, and X. The empirical results appear to depend on the choice of greenness measures. Some studies report evidence that climate change is priced in the market, for example, showing that higher CO2-emitting firms have higher stock returns. These findings indicate a carbon premium: stocks facing higher climate transition risk should require a higher expected return to compensate investors.   

On the other hand, and following the same logic, green stocks, which typically represent environmentally sustainable companies, should command lower expected returns if they are a hedge against climate risks. Brown stocks, conversely, often denote companies with significant environmental impact or those less focused on sustainability. A higher (lower) expected return also eventually entails a higher (lower) realized return, leading to a positive brown vs. green stock premium (or negative green vs. brown premium). Yet, due to the increased demand for green stocks stemming from factors like a shift in investor preferences and regulatory measures faced with the rigidity of its supply, green stocks’ realized returns could outperform brown stocks’ returns, even if they have a lower expected long-term return. This theoretical context provides some rationale for various studies documenting the overperformance of green over brown stocks. Evidence was found of a positive green vs. brown stock premium for the US and most G7 countries since 2012. 

In contrast, Alessi, Ossola, and Panzica (2021) find a negative green risk premium (greenium) linked to European firms’ carbon emissions and environmental transparency, indicating that investors might prefer a hedging strategy to reduce their exposure to climate risk. They argue that investors in the European equity market seem to prefer a hedging strategy when the transition towards low carbon becomes more credible or pressing, for example, after the Paris Agreement, the first global climate strike, and the announcement of the EU Green Deal.  

In line with this stream of literature, Gimeno and González (2022) propose a green factor (GMP, Green companies Minus Polluters) based on companies’ carbon footprints. Their green factor building methodology is close to Alessi Ossola and Panzica (2021). They show that investors prefer companies with lower carbon footprints, thus increasing greener stock prices.  

Moreover, conflicting empirical results also follow from the choice of the greenness measure. For instance, greenness can be measured by the level, intensity, or growth rate of CO2 emissions or the score of Environmental, Social, and Governance (ESG) ratings, which, in turn, might change according to the rating agency. For instance, some authors find a carbon premium for the emission levels. In contrast, others find a green premium for portfolios sorted on emission intensities and E-score. The sensitivity of the results also depends on the sample size and statistical procedures implemented.  

ESG ratings have been criticized for failing to be compiled on quality data. For instance, ESG data are self-reported by the rated companies and not audited, leaving the door open for companies to distort their information disclosure to inflate their ESG rating artificially. Other biases might be associated with company size, geographic location, and industry sector. For instance, larger companies might have more resources than small firms to invest in improving their ESG scoring, leading to a size bias; European firms are subject to stricter disclosure regulations than US firms, generating a geographic bias. Finally, while data are normalized by industry, they might fail to factor in company-specific risks. This failure might cause a biased rating for a company based on its sector rather than its company-specific risk. Moreover, ratings tend to differ according to rating agencies due to divergence in attributes, weight and aggregation functions, and indicators in measurement in ESG ratings. A market-based rating could improve upon all the above-listed shortcomings with the caveat that it still may be subject to errors in measuring green investment performance and/or transition and physical climate risks, also known as “green risk.” While market awareness of green risk is rising over time, it is unclear how univocal and accurate its pricing is. 

We make four main contributions following the methodology proposed by Alessi, Ossola, and Panzica (2021) to construct green vs. brown portfolios.  

First, we show that measures of green-brown investment performance contain information that goes beyond what could have been attributed to the pricing of climate risks. To capture green risk, financial and business cycle components, and firm-level characteristics should be filtered out of green vs. brown excess return measures.  

Second, using a filtered green factor,  find evidence that climate risks are already priced in the European stock market. This is confirmed by sectorial analysis showing that climate risks are negatively priced in typically brown sectors. Moreover, we find empirical evidence of rising investors’ environmental concerns following EU policy initiatives such as the launch of the Green Deal (possibly also because of the COVID-19 pandemic). This might explain the higher performance of green vs. brown stocks.  

Third, we find evidence that over the last two decades, green investments have been a hedge over the business and financial cycle and, perhaps surprisingly, that restrictive monetary and budgetary policies have negatively impacted green vs. brown excess returns. Importantly, these findings on the time variation of green vs. brown excess returns are independent of the pricing of climate risks. 

Finally, we propose a market-oriented rating tool based on the improved green risk measurement, yielding complementary information to standard ESG ratings and improving existing approaches to rate non-transparent or non-disclosing companies. 


Nuno Cassola is an Associate Researcher at the Center for Research in Mathematics Applied to Forecasting and Decision Making in Economics at the University of Lisbon, Portugal.  

Claudio Morana is a Professor of Economics at the Department of Economics, Management and Statistics (DEMS) of the University of Milano-Bicocca (Italy).  

Elisa Ossola is an Assistant Professor (RTDb) at the Department of Economics, Management and Statistics (DEMS) of Università degli Studi di Milano Bicocca.  


This post is adapted from their “Green Risk in Europe” paper on SSRN 

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