Using this insight as a springboard, the researchers then integrated the idea of number-context interactions into an asset pricing model. They did this by focusing on profitability, which is one of the fundamental drivers of investment identified by Nobel laureate Eugene F. Fama of Chicago Booth and Kenneth R. French of Dartmouth. In 1993, Fama and French named three factors (market beta, size and value) that could explain average stock excess returns, and then in 2015 added profitability and investment as factors. Real-world experiments were incorporated into the fine-tuning. (For more information on investable factors, see “The 300 Secrets to High Stock Returns.”)
Taking previous findings into account, Kim and Nikolaev developed a context-adapted profitability metric for their model. This refined version, when applied to 1995-2020 data, provided more accurate stock value forecasts than traditional profitability measures, even for forecasts that predicted returns several years into the future.
The results could help explain a flaw in the five-factor model, the researchers write. Fama, French, and later scholars and practitioners have struggled to explain why the profitability factor sometimes loses its predictive power, particularly for small businesses. Context can help explain why smaller companies have seen positive returns despite their low profitability, or vice versa, says Kim. If a company is small, it may be young and less profitable because it is investing in its future.
Ideally, investors would use a company’s future profitability to predict its future stock returns. But since future profits are of course unknown in the present, they use current profitability as a rudimentary indicator – and perhaps recognize the inherent discrepancy. “Investors in early-stage companies can see their low profitability,” Kim explains. “They may believe that future projects are likely to be successful and invest in such companies despite low profitability levels. “It could be that small companies with low profitability are generating good market returns because of their potential” – a concept that is difficult to grasp from the numbers alone.
Because narrative information creates a more comprehensive measure of profitability, the researchers’ model is able to make better forecasts. It’s a big step forward from the days when intrepid analysts manually combed through quarterly reports in search of actionable information, and researchers suspect it will lead to investors developing other sophisticated models tailored to specific investment needs.