ESG events have significant investment implications. For instance, a corruption controversy negatively affects ESG scores as well as the ability for a company to secure credit lines for future investments, leading to lower growth prospects and a lower company valuation. The degree to which ESG and traditional risk management overlap is substantial. Additionally, the adoption of ESG-conscious oversight by governments, the public, and investment firms has created new types of social and governance risks.

Below are examples of high-profile companies experiencing ESG-sensitive events which drove their decline in value:

ESG Datasets

The Problems with Traditional ESG Data

The majority of the developed world has established mandatory frameworks for ESG disclosures. However, firms often lack the resources or motivation to report their ESG metrics completely and accurately, resulting in much of their self-reported data being omitted or inaccurate.

Moreover, some ESG frameworks such as the SFDR and CSRD in the EU are imposed with an annual update frequency, meaning that major ESG events, such as oil spills, human rights abuses and corruption scandals are likely to be reported long after the most informed market participants have reevaluated a company's value.

Our Solution

MarketPsych's ESG data updates in real time and excludes channels through which self-reported company data is published such as corporate filings and press releases. Populated systematically with a robust suite of NLP tools, MarketPsych's ESG data tracks universal ESG thematic sentiments for 100,000+ companies public and private back to 1998. The data is produced from the outside perspective, removing corporate commentary that could distort (“greenwash”) the scores. Additionally, half of the Advanced ESG metrics are controversies, intended to provide an unvarnished view on a company or country’s ESG practices.

Source of Alpha

Quantitative research studies demonstrate numerous potential sources of alpha in MarketPsych’s ESG data. The controversies data is particularly valuable, and a whitepaper with python code is available for subscribers.

The below monthly rotation model demonstrates how higher workplace sentiment appears to drive higher stock returns for the top versus the bottom 5% of ranked companies in the S&P 500.

Case Studies

AGF incorporates MarketPsych's ESG data into their quantitative models to better identify investment opportunities for their Sustainable ETFs. For example, by tracking positive or negative ESG sentiment towards specific companies or industries, AGF can select high-potential investments and avoid those with higher risks. This data-driven approach enables AGF to make more informed decisions, supporting ESG leaders and leading to better investment returns.

MarketPsych's data is also essential for AGF's risk management processes, helping them anticipate market volatility and adjust their portfolios accordingly. This proactive risk management helps mitigate the impact of sudden market downturns or unexpected events.