New Constructs' 'Novel Database' Shown in HBS & MIT Sloan Paper to Correct Market Inefficiencies and Generate Alpha

NASHVILLE, Tenn., Oct. 15, 2019 /PRNewswire/ -- "The implications of these findings are potentially far-reaching for investors and researchers."
– page 31, 2nd paragraph, 1st sentence

In "Core Earnings: New Data and Evidence", 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 use our "novel database" of earnings adjustments to reveal market inefficiencies and show investors how to:

• Measure & predict earnings more accurately
• Lower risks of using misleading data from traditional providers
• Generate alpha

"…this is the most comprehensive dataset that captures what a fundamental analyst would be likely to identify as transitory or non-operating earnings items..."
 – page 9, 2nd paragraph, 2nd sentence

Only our research utilizes the superior data and earnings adjustments featured by the paper.

This paper shows how our superior data and research helps investors:

• Pick better stocks
• Avoid losses from using other firms' data
• Build better cash flow & valuation models
• Exploit market inefficiencies
• Fulfill fiduciary duties

Pick better stocks:

"Trading strategies that exploit cross-sectional differences in firms' transitory earnings produce abnormal returns of 7-to-10% per year." – Abstract, 4th 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 13, last paragraph, 1st sentence

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 3-4, 3rd paragraph, 2nd sentence

Exploit market inefficiencies:

"Analysts and market participants are slow to impound the implications of transitory earnings." – page 1, Abstract, 3rd 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 31, 2nd paragraph, 4th sentence

Conclusion: Have Your Cake and Eat It Too

Now everyone can benefit from more accurate fundamental data and rigorous research without spending hours scouring financial filings.

This HBS and MIT Sloan paper shows that our Robo-Analyst technology delivers materially better data that can improve stock-picking. Unconflicted and comprehensive fundamental research is finally available to all who care to make it a part of their investing process.

Why take the unnecessary risk of using lower quality data and research? You and your clients deserve the best technology has to offer.

Get the paper here.

Get the only research based on a truly comprehensive assessment of earnings here.

Media Contact: Kyle Guske II
Email: [email protected]
Phone: 615-377-0443

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Core Earnings: New Data and Evidence

SOURCE New Constructs, LLC

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