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Fama and French Dissect Anomalies

January 14, 2008 • Posted in Big Ideas, Buybacks-Secondaries, Momentum Investing, Size Effect, Value Premium

Which stock return anomalies are trustworthy, and which are not? In the June 2007 draft of their paper entitled “Dissecting Anomalies”, Eugene Fama and Kenneth French apply both sorts and regressions to examine the robustness of the momentum, net stock issuance, accruals, profitability and asset growth anomalies. They note that sorts on an anomaly variable offer a simple picture of how average returns vary, but microcaps (a few big stocks) can dominate the performance of a sort-based equal-weighted (value-weighted) hedge portfolio. In addition, sorts are ill-suited to determinations of: (1) the exact relationship between an anomaly variable and returns, and (2) relationships among anomalies. They note also that extreme behavior by microcaps and outliers generally can distort inference from regressions. Using a robust set of firm data for a broad set of U.S. stocks allocated to three size groups (microcap, small and big) over the period 1963-2005, they conclude that:

  • On average, microcaps are roughly 60% of sampled stocks, but they represent only about 3% of total market value (compared to 90% for big stocks). They boast a high average equal-weighted (EW) monthly return of 1.56% (1.07% for big stocks), but they also have the highest return volatility by far.
  • Using sorts based on anomaly variables, adjusted for size and book-to-market (B/M) factors:
    • Momentum, net stock issuance and accruals relate to large abnormal returns for all size groups. The EW and value-weighted (VW) abnormal hedge portfolio returns for these three variables are strong across all size groups.
    • Abnormal returns after net stock issues and accruals derive mostly from extreme values of these variables.
    • Higher positive profitability relates to higher abnormal returns, but negative profitability does not lead to abnormally low returns.
    • There is no asset growth anomaly for big stocks.
  • Using regressions of stock returns on anomaly variables:
    • Size owes much of its predictive power to microcaps. Its effect is marginal for small and big stocks.
    • The relationship between average returns and B/M is moderate and consistent across size groups.
    • Momentum and net stock issuance exhibit the strongest average regressions across all size groups. Momentum effects are only about half as strong for microcaps as for small and big stocks.
    • Positive accruals relate negatively to average returns for all size groups.
    • Among profitable firms, profitability relates positively to average returns for all size groups.
    • The negative relationship between asset growth and average returns is powerful for microcaps, weaker but statistically reliable for small stocks and largely non-existent for big stocks.
  • All these anomaly variables are at least rough proxies for expected cash flows and therefore reasonably affect valuations.

The following chart organizes key findings from the paper.

In summary, some anomalies are stronger and more consistent than others. Momentum appears to be the strongest and most consistent.

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