It seems like a relatively straightforward idea that statements by a firms management would contain information outside of what the firms financials say. Now, while reading up on the corporate filings (10Qs and 10Ks) of your favorite five companies is pretty easy, what about analyzing the statements of say the largest 3000 companies in the country? This would be a daunting task, and Feng Li from University of Michigan set out to figure out a way to gather all this data and analyze it. He looked at the language in annual filings for for around 3,000 firms over a ten year time span. Using a text algorithm Li assessed the incidence of language associated with risk in companies annual filings (1oKs). Li finds that:
an increase in risk sentiment is associated with lower future earnings: Firms with a larger increase in risk sentiment have more negative earnings changes in the next year. Risk sentiment of annual reports can predict future returns in a cross-sectional setting: Firms with a large increase in risk sentiment experience significantly negative returns relative to those firms with little increase in risk sentiment in the twelve months after the annual report filing date.
To explain plainly, and again this is pretty straight forward, companies that suddenly begin to worry about risk a whole lot more are more likely to be exposed to more actual risk. This should be reflected in lower annual returns in companies with heightened risk concerns. To that end, Li contends that:
A hedge portfolio based on buying firms with a minor increase in risk sentiment of annual reports and shorting firms with a large increase in risk sentiment generates an annual Alpha of more than 10% measured using the four-factor model including the Fama-French three factors and the momentum factor.
While I take past returns and back-tested returns with a grain of salt, the idea makes intuitive sense and implementing Li’s strategy is an interesting way to take a broad look at how companies are thinking about the risks they are exposed to.
Here is the paper, for those interested in reading all about risk sentiment in annual reports -> ssrn-id898181
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