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.
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.
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.
“Trading strategies that exploit (adjustments provided by New Constructs) produce abnormal returns of 7-to-10% per year.” – Abstract, 4th sentence
The paper presents a long/short strategy that holds the stocks with the most understated EPS and shorts the stocks with the most overstated earnings. Positions are opened in the month each 10-K is filed and held until the next 10-K is filed, or about a year.
This simple, low turnover strategy produced abnormal returns of 7% to 10% a year. These abnormal returns show that the market misses important data in the footnotes and that investors who adjust for unusual items can make more money.
Our research shows AbbVie (ABBV) is a stock investors should look to buy ahead of its Q3 earnings report on November 1. ABBV had some of the largest expense adjustments, or most understated earnings, of all companies in the S&P 500 in 2018. Its largest non-recurring expense was a $5.1 billion asset impairment. ABBV also disclosed the following non-recurring, unusual expenses in the footnotes:
In total, we identified $3.91/share in net non-recurring expenses that artificially lowered reported earnings. $2.81/share of these adjustments were not disclosed on the income statement.
Without our adjustments, ABBV’s reported EPS show a modest increase, from $3.30/share in 2017 to $3.66/share in 2018. However, after removing non-recurring items, we find that ABBV’s core earnings increased significantly from $4.73/share in 2017 to $7.57/share in 2018.
ABBV’s understated earnings make it more likely to beat expectations when it reports third quarter earnings.
Also, ABBV’s valuation is cheap so there’s less risk in the stock. The combination of understated earnings and a cheap valuation earns the stock our Attractive rating.
Figure 2 shows the firms in the S&P 500 with the largest total after-tax expense adjustments in 2018. These items artificially decrease reported earnings and must be removed to calculate a firm’s true recurring profitability.
Figure 2: Top 5 Net Hidden Expenses in 2018 – $ value
Sources: New Constructs, LLC and company filings
Excludes Berkshire Hathaway (BRK.A), which represents a significant outlier
While our data and models are updated daily as new 10-K and 10-Qs are filed, we’re only showing data through 2018 because we do not give away too much valuable data for free.
In this report, Total Adjustments includes
See Figure I in the Appendix for the definition of core earnings and total adjustments used in the HBS & MIT Sloan paper.
We further break down each of the adjustment categories above in Figure II of the Appendix. This level of granularity allows investors to get a clear picture of all adjustments required to calculate a firm’s true earnings.
Appendix 2 provides details on the most complete data set we offer clients.
Disclosure: David Trainer, Kyle Guske II, and Sam McBride receive no compensation to write about any specific stock, sector, style, or theme.
Figure I contains the definition of core earnings used in the HBS & MIT Sloan paper. Certain adjustment categories we included in the analysis above were aggregated into the definition below. We believe breaking out these adjustments is necessary to ensure all necessary adjustments are captured and accounted for in calculating core earnings.
Figure I: Core Earnings Defined in the HBS and MIT Sloan Paper
Sources: Core Earnings: New Data and Evidence
Figure II details each specific adjustment type included in the total adjustments we detailed in this report.
Figure II: Breakdown of Adjustment Categories
The hidden and reported adjustment categories included in Total Adjustments defined earlier can be further broken down into the following adjustments:
Sources: New Constructs, LLC
Most of these categories have a 1-1 correlation with the categories in the HBS paper:
Other categories combine multiple categorizations in the HBS paper:
However, we are not sure which of our adjustments are included in “Net Other Expenses” in the paper. We also are unsure if or how the authors accounted for the tax impact of non-recurring items.
The HBS paper focuses on core earnings for direct comparison with GAAP earnings, IBES and First Call earnings and Compustat’s “income before extraordinary items” and “income minus special items.” Our preferred measure of profitability, net operating profit after tax (NOPAT), includes all the items in the HBS & MIT Sloan paper as well as several others. Our complete reconciliation of GAAP net income to NOPAT is below.
Reported GAAP Net Income
Total Net Non-Operating Expenses Hidden in Operating Earnings
Reported Net Non-Operating Expenses
Derived Datapoints
Net After-Tax Non-Operating Expense/(Income)
= NOPAT (Net Operating Profit After Tax)
[1] From First Call and IBES
[2] Both “income before extraordinary items” and “income minus special items”
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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.
Harvard Business School featured our unique technological capabilities in “New Constructs: Disrupting Fundamental Analysis with Robo-Analysts”.
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Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.