Study Finds That New Constructs Earnings Estimates Are More Accurate Than IBES Street Earnings & Compustat's Income Before Special Items
Harvard Business School & MIT Sloan Paper Shows New Constructs Earnings are Best in Market, Free of Managerial Bias
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NASHVILLE, Tenn., February 11, 2020 (Newswire.com) - New Constructs (NC), the leading provider of insights into the fundamentals and valuation of private and public businesses, announced an updated edition of Core Earnings: New Data & Evidence, a paper written by professors at Harvard Business School & MIT Sloan. The paper shows NC’s “novel dataset” creates a measure of earnings superior to “Street Earnings” from Refinitiv’s IBES (owned by Thomson Reuters and Blackstone) and “Income Before Special Items” from Compustat (owned by S&P Global). See page 27, paragraph 1.
The paper says NC provides:
“the most comprehensive dataset that captures what a fundamental analyst would be likely to identify as transitory or non-operating earnings items in detailed analyses of firms' 10-Ks.” (page 9).
The professors show that NC’s earnings are free of manager manipulation, which the paper shows occurs frequently when companies meet or beat consensus.
New Constructs’ Founder and CEO David Trainer commented, “Millions of investors all over the world rely on earnings data and estimates from IBES and Compustat, and now Harvard Business School and MIT Sloan professors demonstrate that our new technology more accurately measures and predicts (page 23, paragraph 3) earnings for thousands of stocks.”
The professors show that “Special Items” from Compustat and “Street Adjustments” from IBES capture just half of the non-core items that NC collects. They provide specific examples for unusual items that NC collects and Compustat misses on pages 14-15 and 37 of the paper.
The professors show that the non-core items NC identifies produce a measure of core earnings that is “incremental to alternative measures of operating performance in predicting an array of future income measures.” See section 3.4 of the paper.
Take Advantage of Superior Data
In Section 4.3 of the paper, the professors present a long/short strategy that generates 10% in annual returns using our Earnings Distortion data. Individual investors can use the same data to invest smarter:
- Short-term – use NC’s Earnings Distortion Scores to trade stocks most likely to beat or miss consensus estimates. Get the Earnings Distortion Scorecards for this earnings season.
- Long-term – use NC’s Stock Ratings to own more stocks with understated earnings and avoid/sell stocks with overstated earnings.
About the Professors
Ethan Rouen and Charles C.Y. Wang of Harvard Business School (HBS) and Eric So of Massachusetts Institute of Technology (MIT) Sloan School of Management used New Constructs “novel dataset” to analyze disclosures in corporate 10-Ks, including those hidden in the footnotes and the MD&A. They show that disclosures of non-operating income-statement items are both frequent and economically significant, and increasingly so over time. Further, Compustat’s core earnings and street earnings do not properly account for such unusual items and are subject to significant bias, which creates more risk for investors.
About New Constructs
New Constructs provides insights into the fundamentals and valuation of private and public businesses. Combining human expertise with natural language processing (NLP), machine learning (ML) and artificial intelligence (AI) technologies, the firm’s research shines a light in the dark corners (e.g. footnotes) of hundreds of thousands of corporate financial filings to unearth critical details that drive uniquely comprehensive and independent debt and equity investment ratings, valuation models and research tools. New Constructs technology brings critical and material footnotes research to the market for the first time ever, enabling analysts to measure and predict profits more accurately and deliver more alpha for clients. Elite money managers, advisors and institutions have relied on New Constructs to lower risk and improve performance since 2004. New Constructs and its research have been featured in national business news including CNBC, Wall Street Journal, Barron’s, Forbes, Seeking Alpha, Benzinga and more. Strategic content partnerships with TD Ameritrade, E*TRADE, Refinitiv/Thomson Reuters, Interactive Brokers and EY enable New Constructs to deliver our investment ratings and research on over 10,000 stocks, ETFs and mutual funds to millions of self-directed investors, financial advisors and corporate executives.
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Media Contact:
Daniel Delson
[email protected]
Source: New Constructs, LLC
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Tags: Compustat Income Before Special Items, core earnings, David Trainer, earnings distortion, earnings manipulation, Harvard Business School, IBES Street Earnings, machine learning, MIT Sloan School of Management, New Constructs, novel dataset, Street Adjustments