How does greenwashing affect the stock market? – GreenLies

The goal of this project is to determine the impact of greenwashing on investors’ portfolio allocations and asset prices. Specifically, we want to develop methods to estimate the level of greenwashing used by firms. This will enable us to study which firms use greenwashing most (within which sector, ownership structure etc.), and how it affects portfolio allocations and asset prices. Our tools aim to help regulators reduce transition risk when designing new policies, and investors when selecting assets. We will use state-of-the-art methodologies in Artificial Intelligence, such as Natural Language Processing (NLP).

This project includes four Work Packages (WP). We start from the research hypothesis that when greenwashing is uncovered, it is most often reported in the newspapers. News may even be the direct source that investors use to update their beliefs on greenwashing and as a result their portfolios. In the first WP, we will measure the extent to which greenwashing practices are discussed in the financial news, and contaminate the discussion on climate risk. In the second WP, we aim to detect greenwashing at individual firms by comparing the contents and tonality of corporate websites, press releases and financial news articles related to a given firm. The underlying idea is that if a firm makes misleading claims, the contents and tonality used by these three communication channels in their coverage of the claims will be different. The third WP will be an industry-oriented paper that will aim to disseminate results to practitioners. The fourth WP will contain tasks related to project management.

This project has a strong interdisciplinary component and is at the confluence of three topical subjects: 1) transition to sustainability as a response to climate change, 2) use of AI to deal with big data, and 3) financial portfolio allocation. It is both original and ambitious: original as it builds on a literature in finance that almost completely ignored the possibility of greenwashing, and ambitious because greenwashing is, by nature, difficult to identify and measure. This project will build a toolbox that researchers will be able to use and further develop freely to advance research on climate risk. We will make all our algorithms publicly available after publication, hoping that they can serve as a basis for further research on greenwashing and more generally on the disclosure of misleading information (e.g., related to social issues) by firms.