Over the last decade, financial analysts have been incorporating a type of information into their work for which their predictive models were not prepared, as it is information that has emerged over time and today contributes to improving the functioning of companies. Traditional financial statements have been supplemented by governance reports, ESG ratings, taxonomies, and more recently, sustainability information statements derived from the CSRD. All of this contributes positively: ESG disclosure favours more accurate forecasts from financial analysts and mitigates the excessive optimism present in their estimates, particularly when the company also shows good financial health.
ESG indicators measure what the company does in terms of sustainability, its performance, but say nothing about what may happen to it because of what has been done. This is a different issue and, for someone like analysts, who have to anticipate a profit, likely more pertinent. ESG risk is the part of the company's economic value exposed to environmental, social, or governance contingencies. One does not necessarily entail the other, and there are indications that the opposite may even occur: a strong ESG commitment can lead to increased exposure to risk, as it also raises the expectations of stakeholders and because a good part of these initiatives are qualitative and difficult to verify. Thus, if ESG risk management reduces uncertainty about future results, it should also be reflected in the quality of the estimates of those who try to anticipate them, the financial analysts.
Hence the question: are the forecasts of financial analysts about companies that manage their ESG risks better more accurate?
To answer this question, in the paper “The Impact of ESG Risk on Financial Analysts’ Forecast Accuracy”, 583 listed companies from 46 countries, developed and emerging, are analysed over nine economic years, from 2015 to 2023: 3,873 observations in total. The accuracy of the forecasts is measured based on the error made by financial analysts, calculated as the absolute difference between the earnings per share published by the company and the consensus forecast for that same year. To facilitate interpretation, values closer to zero indicate more accurate forecasts. The forecasts and financial data used come from LSEG Workspace; the ESG Risk Score and its two components (exposure and management), from Sustainalytics; the sustainability recognition, from the Sustainability Yearbook of S&P Global. The empirical analyses take into account the size, profitability, the weight of tangible assets, sales growth, and the indebtedness of the companies, in addition to controlling for the effects that location and temporal dynamics may have.
Main findings: implications for professionals
1. Unmanaged risk comes at the cost of accuracy
Sustainalytics classifies companies into five levels of ESG risk, from insignificant to severe. Graph 1 shows, for each of these levels, how much the forecasts deviated on average. Companies with insignificant risk deviate by 0.13 on average, while those with severe risk deviate by 0.53. That is, the higher the level of ESG risk, the lower the accuracy of the estimates made by the analyst.
This first signal is confirmed when estimating the model, which measures the effect of ESG risk once the other characteristics of the company (size, profitability, indebtedness) and year and country are discounted. The effect of the ESG Risk Score on accuracy is negative, with ten more points of risk widening the deviation by around 0.05, about 14% of the average error. For someone following a portfolio of comparable companies, that is the difference.
The underlying reason is simple. Poorly managed risk by the company generates information that is difficult to verify and quantify. It is known that the risk exists, but there is no data to incorporate it into the forecast, so it remains outside of it and reappears later unexpectedly.
2. Recognition does not protect: it exposes
It might be expected that companies awarded for their sustainability would escape this effect. However, the opposite occurs. The Sustainability Yearbook of S&P Global distinguishes the best companies in each industry each year with a medal (gold, silver, bronze, and industry mover), and crossing this distinction with the level of ESG risk does not mitigate the effect on accuracy: it worsens.
The most plausible explanation relates to scrutiny. From a distinguished company, it is expected that it manages these risks well. When it does not, the contrast with what was expected from it is greater, and so is the mismatch it causes in market expectations. The distinction attracts attention and, with it, demand. For the analyst, the practical consequence is clear: a sustainability award informs about the relative position of the company compared to its peers, not about the solidity with which it manages its risk, and does not replace analysis.
3. Management weighs more than exposure
The most practically useful result is obtained by breaking down the risk indicator into its two components. Sustainalytics distinguishes between exposure, how much ESG risk the company's activity brings with it, something that mainly depends on its sector and which it can hardly avoid, and management, what part of the risk is effectively addressed. When viewed separately, it is management or, more precisely, its absence that leaves a mark on forecasts.
The quality of management clearly improves accuracy. Exposure, on the other hand, shows little effect, and the small effect it has fades when the full set of controls is introduced. External recognition, moreover, becomes irrelevant here: the benefits of managing well do not depend on whether anyone has awarded them.
The market, through analysis, does not penalise operating in a sector intensive in emissions or with complicated supply chains. It penalises not knowing how to handle it. This is reasonably good news for companies in exposed sectors, as the only variable they can act on is precisely the one that makes the difference.
Conclusions and implications
ESG risk has ceased to be a reputational issue to become a problem of information quality, and as such it should enter the valuation model: as an adjustment of the risk premium, as an alternative scenario, or as a factor that explains the greater or lesser accuracy of analysts.
It is also advisable to change the criteria by which each company is evaluated. Knowing whether it is sustainable leads to a global rating or an award, and neither of these anticipates the behaviour of its profits. What does anticipate it is the part of its ESG risk, and measuring it requires looking separately at exposure and management, something that not all data providers allow with the same clarity.
Companies have the other part of the work. Informing about the processes and capabilities with which risk is managed, and not just about exposures and performance indicators, reduces information asymmetry and improves the coverage they receive. This is also the direction in which the CSRD and ISSB standards push, so the regulatory and market incentives point to the same place.
Market credibility, ultimately, is not given by the recognition obtained but by the coherence between what the company says about its sustainability and what it is truly capable of managing. For those making forecasts, that coherence has become another variable.
Outstanding issues
None of these conclusions closes the matter. It remains to understand the role of the regulatory framework: comparing markets subject to different disclosure requirements would indicate whether the CSRD and ISSB standards are truly narrowing the information gap or simply transferring it to other indicators. And there is, above all, one question that directly ties to the profession: whether specific training in ESG analysis, which is accredited by certifications like the CESGA, translates into more accurate forecasts for those who possess it. This would be the most direct way to verify that understanding these risks is not just a requirement of the moment, but an analytical advantage.