Many AAII members are familiar with Joseph Piotroski’s F-Score as a methodology for identifying undervalued stocks. A key part of his strategy is the F-Score. The F-Score is calculated from nine fundamental signals. Though Piotroski designed the score to be applied to stocks trading with low price-to-book-value ratios, his F-Score methodology works with a wide variety of stocks.

The outperformance associated with high F-Scores and the underperformance associated with low F-Scores is particularly evident among stocks with the greatest information uncertainty. Stocks fitting this description include small-company stocks, stocks with low levels of trading volume (“illiquid”) and those covered by few analysts. The higher (lower) returns for such stocks with high (low) F-Scores is greater than would be expected when risk is accounted for.

H.J. Turtle of Colorado State University and Kainan Wang of the University of Toledo reached these conclusions after applying the full F-Score to more than 125,426 firm-year return observations for the period of 1973 through June 2014. High F-Scores were defined as ranging from seven to nine. Low F-Scores were defined as zero to two. Scores from three to six were defined as mid. The average nine-variable F-Score for the companies studied on a full firm-year basis was 4.6; the median score was 5.0.

The study’s authors found that “every” high F-Score portfolio outperformed its corresponding low F-Score portfolio. This outperformance occurred across companies of all sizes. The returns were the highest for the small-firm portfolio, however. This difference was also evident when the analysis was done on a quarterly basis—the authors described small-company stocks as exhibiting “significantly larger positive marginal performance.” This outperformance was found to exist even after adjustments were made to account for the general return premium realized by small-company stocks over large-company stocks (defined as small minus big).

Information uncertainty is credited as playing a big role. Prior research suggests that investors underreact to public information when they are overconfident about their private information. This behavior, according to Turtle and Wang, results in bigger positive returns following good news and lower expected returns following bad news.

Source: “The Value in Fundamental Accounting Information,” H.J. Turtle and Kainan Wang, forthcoming in Journal of Financial Research, SSRN, January 17, 2017.