By |Published On: September 30th, 2014|Categories: Research Insights|

Textual Classification of SEC Comment Letters

Abstract:

SEC Comment letters appear to be under-utilized by investors because these largely text-based disclosures are more difficult to access and interpret than other common disclosures. Using a naive Bayesian textual analysis procedure, I classify important SEC comment letters where the signal of importance is significantly negative abnormal returns following comment letter disclosure. Text analysis alone can identify important letters between 10% and 40% better than chance. The text analysis signal provides additional power to identify important comment letters over other signals such as insider sales and the presence of revenue recognition related comments. The incorporation of comment letter information into security prices is more pronounced for comment letters known to have been accessed by investors, using the SEC’s EDGAR download logs, providing evidence of investor inattention to important comment letters.

Alpha Highlight:

Should we be paying more attention to SEC Comment Letters? The authors of this paper say “Yes!”

  • All SEC comment letters can be found at ftp.sec.gov.

There are a lot of findings in this paper, but Figure 1 was interesting for reasons that have nothing to do with textual analysis. The figure below shows the evolution of CAR, or cumulative abnormal returns, over a disclosure date -10 to +90 day window. We can see that information in comment letters may be slowly incorporate into prices, perhaps due to investor inattention.

2014-08-15 10_41_22-Textual Classification of SEC Comment Letters.pdf - Adobe Reader


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, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

  1.  Panel (a) illustrates an unexpected positive drift with delay for all firms. This drift may be explained by the fact that the receipt of an innocuous letter is in effect a certification that the SEC has found no significant financial reporting issues.
  2.  

  3. Panel (b) shows a negative drift of firms with greater than 2 requests in the 3 days following disclosure. It indicates that comment letters with bad news appear to be read more frequently.

Perhaps there are ways to identify firms with comment letters that have the most positive drift by eliminating those with multiple comment letter requests? Unfortunately, the author doesn’t share those results…
But he does share results after controlling for insider trading patterns:

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, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

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, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

Looks like there may be some legs to a strategy that avoids firms with comment letters and insider selling…

We’re new to comment letters, but this paper sparked some ideas.

Anyone worked with comment letters?

About the Author: Wesley Gray, PhD

Wesley Gray, PhD
After serving as a Captain in the United States Marine Corps, Dr. Gray earned an MBA and a PhD in finance from the University of Chicago where he studied under Nobel Prize Winner Eugene Fama. Next, Wes took an academic job in his wife’s hometown of Philadelphia and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management firm dedicated to an impact mission of empowering investors through education. He is a contributor to multiple industry publications and regularly speaks to professional investor groups across the country. Wes has published multiple academic papers and four books, including Embedded (Naval Institute Press, 2009), Quantitative Value (Wiley, 2012), DIY Financial Advisor (Wiley, 2015), and Quantitative Momentum (Wiley, 2016). Dr. Gray currently resides in Palmas Del Mar Puerto Rico with his wife and three children. He recently finished the Leadville 100 ultramarathon race and promises to make better life decisions in the future.

Important Disclosures

For informational and educational purposes only and should not be construed as specific investment, accounting, legal, or tax advice. Certain information is deemed to be reliable, but its accuracy and completeness cannot be guaranteed. Third party information may become outdated or otherwise superseded without notice.  Neither the Securities and Exchange Commission (SEC) nor any other federal or state agency has approved, determined the accuracy, or confirmed the adequacy of this article.

The views and opinions expressed herein are those of the author and do not necessarily reflect the views of Alpha Architect, its affiliates or its employees. Our full disclosures are available here. Definitions of common statistics used in our analysis are available here (towards the bottom).

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