Bridge over ocean
30 March 2020 Financial Analysts Journal

Public Sentiment and the Price of Corporate Sustainability (Summary)

  1. Phil Davis

This summary gives a practitioner’s perspective on “Public Sentiment and the Price of Corporate Sustainability,” by George Serafeim, published in the Financial Analysts Journal 2Q issue 2020.

Listen to an audio version of this summary.

This summary gives a practitioner’s perspective on the article “Public Sentiment and the Price of Corporate Sustainability,” by George Serafeim.

What’s the Investment Issue?

Fund managers integrate environmental, social, and governance (ESG) data into their investment analysis and portfolio management decisions, but the question remains whether the value of ESG information has already been accounted for by investors and reflected in share prices.

This article harnesses big data techniques to examine whether public sentiment about the ESG activities of companies affects their future returns. The author shows how companies’ ESG efforts and the public perception of their ESG performance intersect to create valuation gaps that investors could exploit.

How Does the Author Tackle the Issue?

The author first combines ESG performance scores from MSCI, the largest provider of ESG data, with big data from TruValue Labs, which gauges US public sentiment momentum on ESG issues. Public sentiment momentum indicates whether sentiment about a company has turned negative or positive in the past 12 months.

He finds that market prices over the period of the study (2009–2018) did indeed vary depending on public sentiment. This finding raises the question of whether the price paid for ESG activities is efficient. The article tests the theory that the market undervalues strong ESG performance when there is negative public sentiment about a company. It also examines whether the market overvalues strong ESG performance when there is positive public sentiment about a company.

To address this efficient pricing question, the author creates high-sentiment and low-sentiment ESG portfolios. The high-sentiment portfolio buys companies with strong ESG performance and positive sentiment momentum and shorts companies with weak ESG performance and negative sentiment momentum. The low-sentiment ESG portfolio buys companies with strong ESG performance and negative sentiment momentum and shorts companies with weak ESG performance and positive sentiment momentum.

The author then compares these ESG portfolios with six well-known factors—market, size, momentum, value, profitability, and investment. The process is then repeated using data from 37 other countries to assess the extent to which investor behavior outside the United States is informed by public sentiment about ESG activities.

What Are the Findings?

The author finds that negative public sentiment momentum about companies’ ESG activities is associated with undervalued stock prices, so companies are likely to deliver positive alpha in the future. Specifically, the low-sentiment ESG factor produces positive alpha of 4%–5% a year. It also has a higher Sharpe ratio than the six other factors and has a low correlation with these factors. The low-sentiment factor delivers even higher alpha among companies traded in Europe and Asia Pacific.

No such future positive abnormal returns are associated with corporate sustainability activities when public sentiment about ESG governance is positive. The high-sentiment factor has a strong negative correlation with the value factor, suggesting that portfolios of companies with good ESG governance and positive public sentiment may generate returns similar to growth stocks.

What Are the Implications for Investors and Investment Managers?

The author makes the case that public sentiment influences investor views about the value of corporate ESG activities. Specifically, the market undervalues companies that are experiencing negative sentiment about their ESG performance. To that extent, ESG efforts are not always fully incorporated in stock prices and investors have an opportunity to exploit a value gap.

The article also presents compelling evidence that big data, natural language processing, and linguistic analysis can be useful in unearthing stock market value.

We're using cookies, but you can turn them off in Privacy Settings. Otherwise, you are agreeing to our use of cookies. Learn more in our Privacy Policy.