“…the adjustments in
Street Earnings are not only incomplete… but also reflect managerial biases.”
– Page 28, 2nd paragraph, 5th sentence
The recently updated edition of the Harvard Business School and MIT Sloan paper, “Core Earnings: New Data and Evidence,” adds Section 4.1 to empirically prove that corporate managers bury gains & losses in the footnotes to help them meet or beat quarterly earnings goals.
The paper also shows that “Special Items” from Compustat and “Street Adjustments” capture just half of the Earnings Distortion that our research shows managers bury in footnotes.
Only our research captures and enables clients to reverse the Earning Distortion created by Wall Street insiders.
Why Earnings Data is Wrong and the FIRST-EVER Research to Fix It
Corporate managers get away with misleading the markets because too few investors read the financial footnotes. Honestly, who can blame them - who has time to read filings that can be 200+ pages long? That’s why we spent the last 17 years training our machine learning engine to read SEC filings and analyze footnotes with unprecedented scale and accuracy. No other firm has the footnotes data to fix Earnings Distortion.
Only New Constructs accurately identifies and adjusts for footnote disclosures to provide a more accurate view of core earnings.
Street Earnings Ignore Important Adjustments
“…for every dollar of income-increasing Core Earnings adjustments, only 55 cents is incorporated in Street Earnings; similarly, for every dollar of income-decreasing Core Earnings adjustments, only 54 cents is incorporated in Street Earnings.” – Page 27, 3rd paragraph, 3rd sentence
“These results are consistent with the earlier conclusion that the adjustments used to compute Street Earnings are incomplete.” – Page 27, 3rd paragraph, 4th sentence
Managers Manipulate Earnings to Beat Expectations
“…firms that meet or just beat consensus exhibit a more positive association between Total Income-Increasing adjustments and Street Adjustments, consistent with managers defining non-GAAP earnings to exclude more losses to meet or beat analysts’ expectations.” – Page 28, 1st paragraph, 1st sentence
“Street earnings for firms that meet or just beat analyst expectations are more likely to selectively exclude these items [non-operating and less persistent income-statement items].” – Abstract
More Takeaways from the Paper
Apart from proving managerial bias in street earnings, the paper shows:
- markets are inefficiently assessing earnings because too few investors analyze footnotes,
- new technology provides access to this important footnotes data and enables analysts to correct managerial manipulations.
In other words, our cutting-edge technology collects important footnotes data that can make you more efficient and, frankly, feel safer about your investments. To access the data used in the HBS & MIT Sloan paper for nearly all U.S. stocks from 1998 – 2018, click here
Pick better stocks:
“Trading strategies that exploit cross-sectional differences in firms’ transitory earnings produce abnormal returns of 7-to-10% per year.” – Abstract, 5th sentence
“The findings…suggest that firms in the highest decile of Total Adjustments outperform firms in the lowest decile by approximately 9-10% in the year after firms’ 10K filings.” – page 31-32, 4th paragraph, 2nd sentence
Avoid losses from using other firms’ data:
“…many of the income-statement-relevant quantitative disclosures collected by NC do not appear to be easily identifiable in Compustat…” – page 14, last paragraph, 1st sentence
“To further explore Compustat’s treatment of non-recurring items that appear on the income statement, we examined a random sample of 30 firm-years that reported economically meaningful items on their income statements to determine if and where Compustat reported these items. In all instances, NC identified the items as non-operating, and Core Earnings includes adjustments for these items. In 10 of the firm-years, the item was not reported in any Compustat variable; the other 20 items were reported in 13 different variables.” – page 15, 1st paragraph, 4th-6th sentences
Build better models:
“Core Earnings [calculated using New Constructs’ novel dataset] provides predictive power for various measures of one-year-ahead performance…that is incremental to their current-period counterparts.” – page 4, 1st paragraph, 3rd sentence
“Because of the comprehensive nature of NC’s approach to identifying non-operating and transitory income-statement related items, and because of its status as an independent research firm, the resulting measure of core earnings is less likely to exhibit the systematic bias that has been found in managers’ pro-forma earnings.” – page 2, 3rd paragraph, 4th sentence
Exploit market inefficiencies:
“The results … suggest that the adjustments made by analysts and Compustat to better capture core earnings are incomplete. Moreover, the non-core items identified by NC produce a measure of core earnings that is incremental to alternative measures of operating performance in predicting an array of future income measures.” – page 26, 3rd paragraph, 1st-2nd sentences
“Analysts and market participants also are slow to impound the implications of these [non-operating and less persistent income-statement] items.” – page 1, Abstract, 4th sentence
“…these figures show that the NC dataset provides a novel opportunity to study the properties of non-operating items disclosed in 10-Ks, and to examine the extent to which the market impounds their implications.” – page 20, 2nd paragraph, last sentence
Fulfill fiduciary duties:
“An appropriate measure of accounting performance for purposes of forecasting future performance requires detailed analysis of all quantitative performance disclosures detailed in the annual report, including those reported only in the footnotes and in the MD&A.” – page 33-34, 1st paragraph, 4th sentence
“These findings also suggest that Income before Special Items is not a good measure of operating or core income.” – page 22, 1st paragraph, 6th sentence
“…Core Earnings is a superior accounting measure of a company’s operating earnings, and incremental to other measures when predicting future performance.” – page 25, 1st paragraph, 1st sentence
This article originally published on November 21, 2019.
Disclosure: David Trainer, Kyle Guske II, and Sam McBride receive no compensation to write about any specific stock, sector, style, or theme.
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