Clarity AI: ESG Controversies Led to a 2% to 5% Stock Underperformance after Six Months
Higher severity ESG-related incidents led to larger divergence in stock performance compared to lower severity cases; the largest deltas were associated with controversies related to negative environmental impact and to mismanagement of a company’s products and services.
New York, July 12, 2023 – ESG-related controversial incidents often receive significant attention from the media but the link between these controversies and actual stock performance isn’t always clear.
Analysis by Clarity AI, the global sustainability technology platform, tests the hypothesis that involvement in ESG Controversies is a valid predictor of corporate medium-term value loss.
Investors can perceive controversial incidents as a potential sign of poor management or a lack of ethics, which can erode investor confidence and make them less willing to invest in the company’s stock. The legal and regulatory consequences of such incidents can also be expensive and time-consuming to resolve, further damaging the company’s reputation and market value. Finally, such incidents can disrupt a company’s operations, leading to a decline in productivity and profitability, which can negatively impact its market value.
The analysis indicates that controversial actions linked to ESG can have a significant negative effect on a company’s value compared to peers, resulting in a delta in valuation ranging from -2% for less severe controversies to -5% for the most severe controversies after a period of six months.
The analysis covered over 10,000 controversial incidents for more than 1,500 corporations spanning over a four year period. All incidents were classified into one of three different severity groups, namely: Low, Medium, and High. This classification has been done according to the increase in the ESG-derived risks for the company as estimated by Clarity AI’s models, which take into consideration the magnitude of the issue, its impact on stakeholders, and the management by the company. The magnitude of the impact was further broken down considering the type of incident and the industry to which the company belongs.
For the incident type, the research analysed the effect of controversies around four main topics: negative environmental impact, corporate governance issues, market dominance abuse and company mismanagement of its products and services. The largest deltas in stock performance were found for High severity cases and the topics of products and services mismanagement (-11.8% market value divergence on average) and negative environmental impact (-8.9% market value divergence on average). In general, higher severity incidents led to larger deltas in company value when compared to lower severity cases.
The analysis also tested whether the impact of controversies on market value can be greater if the controversy is related to a topic that is material to the industry the company operates in - for example the environmental topic for the mining industry or corporate governance topics for the consumer finance industry.
Results confirm that the effects derived from a company’s involvement in such activities exceeds that of the average of all similar incidents for all companies. The difference is significant, being as large as twice as much for environmental cases and almost three times as much for bad corporate governance controversies.
The analysis confirms that Controversy scores based on Natural Language Processing, like the ones developed by Clarity AI, can be an effective tool for identifying and tracking the evolution of these incidents. ESG frameworks must include these metrics to measure a company's controversial behavior as an additional outside-in measurement of the ESG risk that corporations are exposed to.
Borja Cadenato, Director of Product at Clarity AI, said, “Understanding the risks associated with corporate controversies and taking appropriate actions when controversies do occur can help investors build stronger-performing portfolios and help companies react appropriately to minimise market value loss and maintain investor confidence.”
Analysis Methodology
At Clarity AI we define controversies as instances of conflicts between a corporation and any given social agent or stakeholder, which have as their setting the breaking of Global Norms linked to Responsible Business Conduct such as the UNGC Principles, the ILO principles, or the OECD Guidelines for Multinational Enterprises.
The Clarity AI Controversies solution leverages state of the art Natural Language Processing (NLP) models to process 100,000+ news articles from 35,000+ trusted sources on a daily basis. The models enable us to swiftly identify which news items relate to controversies, classifying them into one of our 39 MECE controversial categories. Controversies are then assigned a severity depending on the category, the magnitude of the case, its management by the company (issue remediation) and the derived risks for the company. This powerful engine allows us to constantly monitor a large universe of companies, recording any changes in the risk they are exposed to derived from their corporate behavior.
We set out to leverage this large scale of data in order to test the hypothesis that ESG Controversies involvement is a valid predictor of corporate medium-term value loss. Furthermore, our research aims to understand the impacts of different types of controversies - by considering their category- and to take into consideration the effect of materiality on the impacts.
The analysis has been performed on available data for the period between 2018 and 2022, or over 150 million articles, with 10,000+ controversial incidents identified for 1,500+ different corporations.
For analysis purposes all controversies have been classified into one of three different severity groups, namely: Low severity cases, Medium severity cases, and High severity cases. This classification has been done according to the increase in the ESG-derived risks for the company as estimated by our models, which consider the magnitude of the issue, its scope and impact on other stakeholders, and the management by the company.
For each of the controversial instances, the evolution of the market value of the company (the company’s stock) has been monitored and benchmarked. To do so, our team applied a Synthetic Difference in Difference model¹ that compares the company’s real performance in the market against a modeled company used as a benchmark. This control company is the result of the combination of weighted averages of comparable companies, with weights set to maximize the similarity of the stock market performance in the period previous to the controversial event. Significant differences between the performances of both companies after the controversial event is assumed to be a causal consequence of the company’s involvement in the controversy.
Results were tested for statistical significance at the 5% level, with a total number of 12,690 incidents qualifying for the analysis.
About Clarity AI
Clarity AI is a sustainability technology platform that uses machine learning and big data to deliver environmental and social insights to investors, organizations, and consumers. Clarity AI’s capabilities are an essential tool for end-to-end sustainability analysis related to investing, corporate research, benchmarking, consumer ecommerce, and regulatory reporting. As of June 2023, Clarity AI’s platform analyzes more than 70,000 companies, 420,000 funds, 201 countries, and 199 local governments, which represents more breadth than any other player in the market. One way Clarity AI delivers on its mission to bring societal impact to markets is by ensuring its capabilities are delivered directly into clients' workflows through integrations with partners like BlackRock - Aladdin, Refinitiv an LSEG business, BNP Manaos, CACEIS, and Simcorp. Additionally, Clarity AI's sustainability insights reach more than 150 million consumers across more than 400,000 merchants on the Klarna platform. Clarity AI has offices in North America, Europe, and the Middle East, and its client network manages tens of trillions in assets and includes companies like Invesco, Nordea, BlackRock, Santander, Wellington, and BNP Paribas. clarity.ai
Media Contact
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clarityAI@edelmansmithfield.com
¹Arkhangelsky, Dmitry, Susan Athey, David A. Hirshberg, Guido W. Imbens, and Stefan Wager. 2021. "Synthetic Difference-in-Differences." American Economic Review, 111 (12): 4088-4118.
