Academic Anomalies Formed After Information Events

Asset pricing anomalies are trading signals that predict future abnormal returns. Boone Bowles, Adam Reed, Matthew Ringgenberg, and Jacob R. Thornock, authors of the November 2023 study “Anomaly Time” published in the October 2024 issue of the Journal of Finance, began by noting:

“Despite the importance of the timing of information releases for anomaly strategies, the academic literature largely ignores when anomaly returns occur and when they are arbitraged away. In fact, academic studies often form portfolios using information that has been publicly available for weeks.”

They then explained:

“In informationally efficient capital markets, investors compete to profit from asset-pricing anomalies before mispricing is arbitraged away. This competition creates a race to acquire and process information quickly, and this race begins as soon as information about an anomaly signal becomes public.”

Using Compustat Snapshot, a database that precisely identifies the dates of important information releases, they examined the timing of abnormal returns around release dates. From McLean and Pontiff’s list of 97 anomalies, they used 28 anomalies that rely on information released in either earnings announcements or 10-K filings. Their sample period began in January 1990 and goes through 2019. The following is a summary of their key findings:

• Anomalies based on annual financial data have provided abnormal returns that were largest in the first month after the release of financial statements, and then decayed quickly thereafter—anomaly returns are at least partly due to delayed information processing by investors.
• The academic convention of forming portfolios in June causes researchers to significantly underestimate return predictability—some anomalies appear insignificant even though they do reliably predict returns in the days and weeks immediately after information is first released as anomaly returns are much stronger using 10-K filing dates, instead of June rebalancing.
• The daily abnormal return to the average anomaly portfolio was 9.84%, annualized, over the first month following the release of information. 
• Over the first four months following an information release, the average daily abnormal return was just 4.69%, annualized, which implies the returns significantly dissipated after the first month.
• In the period after these first four months, the average daily abnormal return fell to 1.99%, annualized.
• Return predictability occurs in both the long and short legs of an anomaly hedge portfolio.
• In recent years, the returns to anomaly strategies are increasingly earned in the first few weeks after information releases, consistent with technological improvements leading to lower processing costs—the markets are becoming increasingly efficient. Price discovery happened twice as fast after the implementation in 1996 of EDGAR, relative to before—a reduction in information processing costs leads to faster arbitrage and shorter periods of return predictability and the market becomes more efficient.

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained.  Indexes are unmanaged and do not reflect management or trading fees, and one cannot invest directly in an index.

As the above figure highlights, the typical academic rebalancing date arrives 80 trading days after the information release date.

Their findings led Bowles, Reed, Ringgenberg, and Thornock to conclude:

“The academic convention of forming portfolios in June underestimates predictability because it uses stale information, which makes some anomalies appear insignificant. In contrast, we show many anomalies do predict returns if portfolios are formed immediately after information releases.”

They added: “Anomaly returns are at least partly due to delayed information processing by investors.” They also recommended that “instead of forming portfolios annually in June, future researchers should form portfolios using the actual information release date from Snapshot or, if that is not available, they should use the 10-K filing date from Compustat for all years after 1994.”

Investor Takeaways

Bowles, Reed, Ringgenberg, and Thornock showed that returns to many anomalies are concentrated in the first month after information releases, and these returns get weaker in the months that follow. They also showed that returns to anomaly strategies are increasingly earned in the first few weeks after information releases, consistent with technological improvements leading to lower processing costs—markets are becoming increasingly efficient as large databases and faster computers enable arbitrageurs to uncover anomalies and learn how to exploit them. In other words, the hurdles to adding alpha for active managers are getting higher—investment practitioners make use of it as soon as or shortly after it is available.