Earnings Data Is Wrong: How You Can Make More Money

Oct. 28, 2019 12:25 PM ETABBV7 Comments
David Trainer profile picture
David Trainer
15.95K Followers

Summary

  • Unusual gains/losses distorted earnings per share by an average of $1.16/share (22%) for firms in the S&P 500 in 2018.
  • Traditional data providers and analysts are missing or mis-categorizing a very material and growing amount of unusual gains/losses.
  • Our research shows AbbVie is a stock investors should look to buy ahead of its Q3 earnings report on Nov. 1.
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Unusual gains/losses distorted earnings per share by an average of $1.16/share (22%) for firms in the S&P 500 in 2018. The popular measures of “core” earnings – i.e. street earnings[1], Compustat[2] or non-GAAP metrics – do not properly account for unusual items and are subject to significant bias according to new research from Harvard Business School (HBS) and MIT Sloan.

Why is earnings data wrong?

In “Core Earnings: New Data and Evidence,” Ethan Rouen and Charles Wang from HBS and Eric So from MIT Sloan show that traditional data providers and analysts are missing or mis-categorizing a very material and growing amount of unusual gains/losses.

The authors show the market is inefficiently assessing earnings because too few people read financial footnotes.

Earnings Data Is Getting Worse

The average per share impact of unusual items has increased 170% from $0.43/share in 1998 to $1.16 at the end of 2018. Figure 1 plots the total impact of unusual items or “Total Adjustments.”

Figure 1: Total Adjustments Per Share for the S&P 500

Sources: New Constructs, LLC and company filings

Excludes Berkshire Hathaway (BRK.A), which represents a significant outlier in all years

Total Adjustments captures the after-tax value of all the unusual items that we collect from the income statement and the footnotes. Though our numbers bear a close resemblance, the HBS & MIT paper is circumspect about exactly which of our adjustments are used to provide the superior measure of “core earnings” featured in the paper. To bring as much value as possible to investors, we share details on all of our adjustments.

For a full description of the adjustments used here and in the HBS paper, please see the final section of this report and the Appendix.

How You Can Make More Money

“Trading strategies that exploit (adjustments provided by New Constructs) produce

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This paper compares our analytics on a mega cap company to other major providers. The Appendix details exactly how we stack up.

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This article was written by

David Trainer profile picture
15.95K Followers
We aim to help investor make more intelligent capital allocation decisions. Our research is driven by proven-superior fundamental data, models and equity/credit ratings.

Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.

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