Operating Earnings Growth Slowing, But Still Overstated After Q1 2022

Jun. 17, 2022 12:12 PM ETTSLA, SPY, IVV, VOO, VTI, DIA, IWM, QQQ4 Comments

Summary

  • Operating Earnings calculated by S&P Global for the S&P 500 overstate Core Earnings through 1Q22.
  • Stocks are more expensive than they appear based on SPGI’s Operating Earnings. Despite falling in 2022, the S&P 500’s current valuation requires more earnings growth than analysts expect.
  • The bear market that began in 2022 has closed the gap between the S&P 500’s valuation and its true fundamentals, but not as much as either GAAP earnings or SPGI’s.
  • Looking for a helping hand in the market? Members of Value Investing 2.0 get exclusive ideas and guidance to navigate any climate. Learn More »

Dollar currency growth concept with upward arrows on charts and coins background

gesrey/iStock via Getty Images

Operating Earnings calculated by S&P Global (SPGI) for the S&P 500 overstate Core Earnings[1] through 1Q22.

Stocks are more expensive than they appear based on SPGI’s Operating Earnings. Despite falling in 2022, the S&P 500’s current valuation requires more earnings growth than analysts expect, even after many companies’ weakening guidance for 2Q22 and the rest of the year.

S&P Global’s Earnings Rebound Is Overstated

In 2021, S&P 500 company profits did not rebound as much as SPGI’s Operating Earnings lead investors to believe. For 2021 versus 2020:

  • SPGI’s Operating Earnings improved from $122.37/share to $208.21/share, or 70%
  • Core Earnings improved from $120.05/share to $197.10/share, just 64%

In 1Q22, Operating Earnings are still 5% higher than Core Earnings even though Core Earnings improved at a faster pace, rising 47% YoY, compared to Operating Earnings, which rose 40%.

Figure 1: Trailing Twelve Month Earnings: Core Earnings vs. SPGI Operating Earnings: 4Q19 –1Q22

Core Earnings vs. Operating Earnings S&P 500 Since 4Q19

Core Earnings vs. Operating Earnings S&P 500 Since 4Q19 (New Constructs, LLC)

Sources: New Constructs, LLC, company filings, and S&P Global (SPGI). Note: the most recent period’s data for SPGI’s Operating Earnings is based on consensus estimates for companies with a non-standard fiscal year. More details on the Core Earnings calculation are available in Appendix I.

SPGI’s Operating Earnings do not exclude the unusual expenses that exaggerated the decline in 2020 and subsequent reversal in 2021.

S&P 500 Is More Expensive Than Operating Earnings Imply

At the end of 1Q22, Core Earnings for the S&P 500 reached new highs, surpassing previous records set in each of the past three TTM periods ended 2021, 3Q21, and 2Q21. The bear market that began in 2022 has closed the gap between the S&P 500’s valuation and its true fundamentals, but not as much as either GAAP earnings or SPGI’s Operating Earnings would have you believe.

Figure 2: Price-to-Core vs. Price-to-SPGI’s Operating Earnings: TTM as of 12/31/15 – 5/16/22

Price to Core vs. Price to Operating Earnings S&P 50 Since 2015

Price to Core vs. Price to Operating Earnings S&P 50 Since 2015 (New Constructs, LLC)

Sources: New Constructs, LLC, company filings, and S&P Global. Note: the most recent period’s data for SPGI’s Operating Earnings incorporates consensus estimates for companies with a non-standard fiscal year. Our Core Earnings P/E ratio is aggregating the TTM results for constituents through 6/30/13 and aggregating four quarters of results for the S&P 500 constituents in each measurement period thereafter. SPGI’s P/E is based on four quarters of aggregated S&P 500 results in each period. More details in Appendix II.

As Operating Earnings continue to overstate the S&P 500’s Core Earnings, the index requires growing investor optimism about future profits just to maintain valuations and stop price declines. Using overstated earnings leads investors to understate risk, a fact that has been on grotesque display in equity markets recently. Based on warnings from companies willing to face reality, and the disconnect between Core Earnings and Operating Earnings, investors can expect more companies warning about slowing earnings growth or even outright decline in coming quarters.

Figure 2 shows the S&P 500 trailing P/E ratios based on Core Earnings and SPGI’s Operating Earnings have fallen significantly from their peaks in March 2021. Prices have come down relative to earnings since valuations peaked in 2021, but the faster rebound in SPGI’s Operating Earnings results in a lower P/E ratio based on Operating Earnings (19.0) than when using Core Earnings (22.9). The S&P 500 looks inexpensive when valued using Operating Earnings, but that is not the case when the more accurate Core Earnings measure is used.

Core Earnings Are Less Volatile And More Reliable

Figure 3 highlights the percentage changes in Core Earnings and SPGI’s Operating Earnings from 2004 to present (through 5/16/22). The difference between the measures is driven by flaws in legacy datasets that lead to a failure to capture unusual gains/losses buried in footnotes.

Figure 3: Core vs. SPGI’s Operating Earnings per Share for the S&P 500 – % Change: 2004 – 5/16/22

% Change in Core Earnings and Operating Earnings Since 2004

% Change in Core Earnings and Operating Earnings Since 2004 (New Constructs, LLC)

Sources: New Constructs, LLC, company filings, and S&P Global (SPGI). Note: the most recent period’s data for SPGI’s Operating Earnings incorporates consensus estimates for companies with a non-standard fiscal year. Our Core Earnings analysis is based on aggregated TTM data through 6/30/13, and aggregated quarterly data thereafter for the S&P 500 constituents in each measurement period.

An Example Of Overstated Earnings In The S&P 500: Tesla Inc. (TSLA)

Below, we detail the hidden and reported unusual items that GAAP Earnings misses, but that are captured in Core Earnings for Tesla Inc. (TSLA), a stock with some of the most overstated GAAP earnings in the S&P 500. We would be happy to reconcile our Core Earnings with Operating Earnings if S&P Global would disclose exactly how Operating Earnings differ from GAAP Earnings.

After adjusting for unusual items, we find that Tesla’s Core Earnings of $6.2 billion, or $5.46/share, are much worse than reported GAAP Earnings of $8.4 billion, or $7.40/share. Tesla’s Earnings Distortion Score is Strong Miss.

Below, we detail the differences between Core Earnings and GAAP Earnings, so readers can audit our research.

Figure 4: Tesla GAAP Earnings to Core Earnings Reconciliation: TTM Through 1Q22

TSLA Core Vs. GAAP Earnings Reconciliation

TSLA Core Vs. GAAP Earnings Reconciliation (New Constructs, LLC)

Sources: New Constructs, LLC and company filings.

More details:

Total Earnings Distortion of $1.94/share, which equals $2.2 billion, is composed of the following:

Hidden Unusual Gains, Net = $0.73/per share, which equals $823 million and is composed of:

Reported Unusual Gains Pre-Tax, Net = $0.68/per share, which equals $768 million and is composed of:

Tax Distortion = $0.54/per share, which equals $611 million

This article originally published on June 2, 2022.

Disclosure: David Trainer, Kyle Guske II, and Matt Shuler receive no compensation to write about any specific stock, style, or theme.

Appendix I: Core Earnings Methodology

In the figures above, we use the following to calculate Core Earnings:

While we prefer aggregated quarterly numbers, we have examined the potential impacts of the two methodologies and have found no material differences.

Appendix II: P/E Ratio Methodology for Core & SPGI’s Operating Earnings

In Figure 2 above, we calculate the price-to-Core Earnings ratio through 6/30/13 as follows:

  1. Calculate a TTM earnings yield for every S&P 500 constituent
  2. Weight the earnings yields by each stock’s respective S&P 500 weight
  3. Sum the weighted earnings yields and take the inverse (1/Earnings Yield)

We calculate the price-to-Core Earnings ratio for periods post 6/30/13 as follows:

  1. Calculate a trailing four quarters earnings yield for every S&P 500 constituent
  2. Weight the earnings yield by each stock’s respective S&P 500 weight
  3. Sum the weighted earnings yields and take the inverse (1/Earnings Yield)

We use the earnings yield methodology because P/E ratios don’t follow a linear trend. A P/E ratio of 1 is “better” than a P/E ratio of 30, but a P/E ratio of 30 is “better” than a P/E ratio of -15. In other words, aggregating P/E ratios can result in a low multiple due to the inclusion of just a few stocks with negative P/Es.

Using earnings yields solves this problem because a high earnings yield is always “better” than a low earnings yield. There is no conceptual difference when flipping from positive to negative earnings yields, as there is with traditional P/E ratios.

By using quarterly data as soon as it's available, we better capture the impact of changes to S&P 500 constituents on a quarterly basis. For example, a company could be a constituent in 2Q18, but not in 3Q18. This method captures the continuously changing nature of the S&P 500 constituency.

For all periods in Figure23, we calculate the price-to-SPGI’s Operating Earnings ratio by summing the preceding 4 quarters of Operating Earnings per share and, then, dividing by the S&P 500 price at the end of each measurement period.

[1] Our Core Earnings research is based on the latest audited financial data, which is the calendar 1Q22 10-Q in most cases. Price data as of 5/16/22. Operating Earnings from S&P Global is based on the same time frame.

[2] We treat the automotive regulatory credits as reported items in 1Q22 because they are reported directly on the income statement. In prior quarters, we treat the credits as hidden items, as they were disclosed in a table separate from the income statement that disaggregates Tesla’s revenue by source.

Get our long and short/warning ideas. Access to top accounting and finance experts.

Deliverables:

1. Daily – long & short idea updates as necessary, forensic accounting insights, chat features

2. Weekly - exclusive access to top-ranked long & short ideas

3. Monthly - 40 large, 40 small cap ideas from the Most Attractive & Most Dangerous Stocks Model Portfolios

4. Quarterly – Best & Worst ETFs and Mutual Funds in each Sector & Style

See the difference that real diligence makes.

This article was written by

David Trainer profile picture
15.87K Followers
Best fundamental research: most rigorous long & short ideas
New Constructs is an independent research technology firm that provides unrivaled insights into the fundamentals and valuation of private & public businesses. Combining human expertise with machine learning and NLP, the firm shines light into the dark corners (e.g. footnotes) of millions of financial filings and provides superior investment research. The firm's Robo-Analyst technology is the first-ever vertically integrated investment research platform: performing data collection, financial modeling and assigning investment ratings to over 10,000 securities - automatically. This new technology is research automation at its best according to:


   1. Harvard Business School & MIT Sloan prove our fundamental data is superior.


   2. Ernst & Young proves the superiority of our financial analytics over Capital IQ & Bloomberg.


   3. Indiana Kelly School of Business proves our stock ratings outperform human analysts.



If these prestigious institutions trust us so much that they decided to publish official papers to prove the superiority of our research, then you can safely trust us, too.

New Constructs' clients include investors of all types from quant funds like GSAM who subscribe to proprietary data feeds, advisors and individuals who subscribe to our investment research directly through our website.


David is CEO of New Constructs (www.newconstructs.com). David is a distinguished investment strategist and corporate finance expert. He was a 5-yr member of FASB's Investors Advisory Committee. He is author of the Chapter “Modern Tools for Valuation” in The Valuation Handbook (Wiley Finance 2010). 


Disclosure: I/we have no stock, option or similar derivative position in any of the companies mentioned, and no plans to initiate any such positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article.

Recommended For You

Comments (4)

To ensure this doesn’t happen in the future, please enable Javascript and cookies in your browser.
Is this happening to you frequently? Please report it on our feedback forum.
If you have an ad-blocker enabled you may be blocked from proceeding. Please disable your ad-blocker and refresh.