During 2Q26 Footnotes Season, we parsed 2,987 10-Q and 10-K filings and created $2,688,300[1] of value for clients. See Figure 1. It is very important to note that our data is very different from other fundamental data providers. In fact, our data is unlike any other fundamental data offering in the world because it is the only database with footnotes data categorized into an ontology that is proven to generate idiosyncratic alpha.
Footnotes Seasons give our Robo-Analyst AI[2] an opportunity to shine as it shows how quickly we process filings and deliver proven-superior research. We deliver this superior fundamental data and research to our clients through our memberships, stock picks, Model Portfolios, and FinSights, our AI Agent built by Google Cloud.
Figure 1: Putting a $ Value on Our Parsing Work for Clients: 2Q26 Footnotes Season
Sources: New Constructs, LLC
* FTEs = Full Time Employees at $100/hour for 8 hours a day.
This Footnote Season is mostly 10-Qs for second quarter earnings from companies with 12/31 fiscal year ends.
The cost of replicating the research we deliver would cost our clients multiples more money of what we charge.
The savings in Figure 1 are likely very conservative estimates because they do not account for the cost of any management or training of analysts. Nor, do they account for the cost of building the financial models and data taxonomies we use to transform the data into alpha-generating signals.
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Proprietary Footnotes Season Data Drives Alpha
While we’re explaining the diligence required to gather and organize superior fundamental data, we want to show you how our research delivers alpha.
We’ve developed multiple indices with Bloomberg’s Index Licensing Group based on Core Earnings and our Stock Ratings. See Figures 2-4.
- Bloomberg New Constructs Core Earnings Leaders Index (ticker: BCORET:IND)
- Bloomberg New Constructs Ratings VA-1 Index (ticker: BNCVA1T:IND)
- Bloomberg New Constructs 500 Index (ticker: B500NCT:IND)
The Bloomberg New Constructs Core Earnings Leaders Index, which allocates based on Earnings Capture and Core Earnings, beat the S&P 500 by 40% over the past five years. The Index (ticker: BCORET:IND) was up 110% while the S&P 500 was up 70%.
Figure 2: Bloomberg New Constructs Core Earnings Leaders Index Outperforms S&P 500: Last 5 Years
Sources: Bloomberg as of August 21, 2026
Note: Past performance is no guarantee of future results.
The “Very Attractive Stocks” Index, which allocates to stocks that get a Very Attractive rating by our AI Agent for Investing, beat the S&P 500 by 32% over the last five years. Bloomberg’s official name for the index is Bloomberg New Constructs Ratings VA-1Index (ticker: BNCVAT1T:IND). Figure 3 shows it was up 102% while the S&P 500 was up 70%.
Figure 3: Very Attractive-Rated Stocks Strongly Outperform the S&P 500: Last Five Years
Sources: Bloomberg as of August 21, 2026
Note: Past performance is no guarantee of future results.
Our “Core-Earnings Weighted S&P 500” Index, which weights the largest 500 U.S. companies by Core Earnings instead of market cap, beat the S&P 500 by 26% over the past five years. Bloomberg’s official name for the index is Bloomberg New Constructs 500 Total Return Index (ticker: B500NCT:IND). Figure 4 shows it was up 96% while the S&P 500 was up 70%.
Figure 4: Bloomberg New Constructs 500 Index Strongly Outperforms the S&P 500: Last Five Years
Sources: Bloomberg as of August 21, 2026
Note: Past performance is no guarantee of future results.
This article was originally published on August 27, 2026.
Disclosure: David Trainer and Kyle Guske II receive no compensation to write about any specific stock, sector, style, or theme.
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[1] Cumulative savings is calculated assuming it takes nine hours per filing and a full-time employee making $100/hour to parse each.
[2] Harvard Business School features the powerful impact of our research automation technology in New Constructs: Disrupting Fundamental Analysis with Robo-Analysts.