As interest in environmental, social, and governance (ESG) investment grows, ESG factors have become increasingly relevant to risk and quant investment workflows. There is an argument, for example, that ESG factors have predictive power for stock performance, as discussed in this recent FactSet Insight. In today’s article, we examine the effect of suppliers’ ESG sentiment signals on their customers’ stock performance and evaluate the return predictability as a quantitative factor.
Current events demonstrate how ESG topics can impact a company’s business and supply chain management. Recently, the U.S. government banned goods from China’s Xinjian region due to suspicion of forced labor. The European Commission proposed a ban on goods made with forced labor.
Abusive labor practices can become a scandal both for companies and downstream customers. For example, a recent investigation found child labor violations in Hyundai’s U.S. supply chain.
Does the ESG sentiment of suppliers have a material impact on their customers’ performance? Yes, based on our analysis.
We are leveraging two databases to derive suppliers’ ESG signal factors.
FactSet Supply Chain Relationships covers close to 35,000 global companies and provides company-disclosed relationships to understand each company’s ecosystem.
FactSet Truvalue SASB Scores uses artificial intelligence (AI) to unlock ESG insights from massive volumes of unstructured text that capture external stakeholder viewpoints about company behavior.
To calculate the factor, we use the average of first-tier suppliers’ all-categories insight scores from the Truvalue SASB Score database. It measures long-term performance for the aggregate of 26 SASB categories. Then we rank the constituents of the target universe based on the average score of their suppliers and create three equal-weighted portfolios where all portfolios consist of the same number of securities.
Using holdings of the SPDR S&P 500 ETF as the universe, we conducted a backtest from the end of 2015 through January 2023 with monthly rebalancing and no transaction cost. Figure 1 shows the cumulative returns of three portfolios.
As hypothesized, the portfolio consisting of the highest ranked companies based on our supplier ESG signal (portfolio group 3) generated the highest cumulative return, while the portfolio with the lowest ranked constituents (portfolio group 1) performed the worst. This result indicates suppliers’ ESG performance is predictive to customers’ stock performance.
To gauge the effectiveness of our supplier ESG signal, we compare its stock return predictability against the all-categories insight score of the constituents themselves. Figure 2 shows the cumulative returns of three portfolios ranked by the insight scores of their constituents.
While the top group also outperforms the bottom group, the spread return between the top and bottom groups has tightened and is not persistent over the analysis period. Moreover, the middle group (portfolio group 3) shows the best performance over the entire period.
We extended our analysis to global markets to determine if the factor performance is persistent. Figure 3 illustrates the cumulative return of three portfolios constructed from constituents of the iShares MSCI ACWI ETF.
Although the top- and middle-ranked portfolios demonstrate similar performance, the bottom group underperforms them with a significant spread return. While the factor's performance is not as strong as it is in the U.S. market for the top-ranked portfolio, its underperformance in the bottom group is particularly noteworthy in the global market.
Our analysis suggests that incorporating suppliers’ ESG sentiment as an investment signal may lead to outperformance compared to more traditional (issuer-focused) approaches. This makes intuitive sense as the news flow for a given issuer is unlikely to adequately incorporate all of the material events and insights associated with other economically linked companies that make up their production chain.
A key consideration overall is that individual SASB category scores may have a more significant impact as a supplier factor. Additionally, the factor impact on performance may differ across sectors. For example, ESG factors related to suppliers may have a greater influence on customers in the Consumer Discretionary sector than those in the Utilities sector.
There is undoubtedly potential to further optimize this approach. Potential enhancements may include combining issuer and supplier-driven factors, or even extending the network analysis to include multiple tiers of each issuer’s supply chain.
Colin Smith, Product Manager for Content and Technology Solutions, also contributed to this article.
This blog post is for informational purposes only. The information contained in this blog post is not legal, tax, or investment advice. FactSet does not endorse or recommend any investments and assumes no liability for any consequence relating directly or indirectly to any action or inaction taken based on the information contained in this article.