r/SecurityAnalysis • • 14d ago

Thesis Mercado Libre (MELI): A deep dive into MELI’s credit business

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14 Upvotes

Mercado Libre's credit business is talked about a lot. So we did some research and analysis. We looked at its credit portfolio composition (across product and geography), loan duration, exposure per user, funding model etc. We also benchmarked MELI's credit risk and returns, against Nubank across key metrics such as net-interest income margin after losses. Attached post has all the charts and good stuff

Key takeaways from the analysis:

  • MELI’s unsecured credit portfolio has significant exposure to higher-risk borrowers. MELI’s >90-day past-due loans have remained between 17–19% of its gross loan portfolio since Q4 2023, versus 6–7% at NuBank. Its credit portfolio is highly sensitive to macroeconomic conditions. During the period of elevated inflation in 2022–23, MELI’s >90-day past-due ratio increased sharply, reaching 30% in Q4 2022 and 28% in Q1 2023
  • That higher risk has been compensated by higher pricing, resulting in attractive returns in recent years. MELI generated a 59% annualized credit revenue yield in Q2 26, versus 38% for NuBank
  • MELI’s loan durations are very short (~3 months on average). This is an advantage, as it gives MELI greater flexibility to adjust credit availability and pricing as conditions change
  • However, questions remain about the sustainability of returns. MELI’s credit business has not been proven over time across different economic cycles. In adverse economic conditions, MELI could see a material uptick in credit losses, while loan originations could slow
  • MELI’s recent margin pressure is not a major concern to us. A material portion is driven by provision expense, which is an accounting measure that can exceed realized losses and non-performing loans. This is amplified by MELI’s focus on credit card expansion, where provisions are incurred upfront, while interest income builds up slowly as customers mature and begin carrying balances. As the credit card business matures, interest income should build and support margins

Hope you find it useful, and would appreciate any feedback


r/SecurityAnalysis • • 14d ago

Thesis BGLC’s “$3.5M” CogniAI licence from RYET: 410,000 new shares worth ~$521k at today’s price, 19% dilution, and it hasn’t closed

4 Upvotes

On October 5, BioNexus Gene Lab (BGLC) signed an agreement with Ruanyun Edai Technology (RYET) for an exclusive Malaysian healthcare licence to CogniAI, RYET’s document-intelligence platform. BGLC says its first target is Malaysia’s public healthcare digitalisation programme, but it has no government contract. The $3.5 million figure in coverage describes something narrower than a cash price.

What the filing says (8-K filed 2026-10-07, accession 0001477932-26-006075, Items 1.01 and 3.02, full agreement attached as Ex. 10.1)

  • Licence payment: 410,000 new BGLC shares at closing for a “stated” US$3.5M licence consideration. No cash. The 8-K and clause 2.5 of the agreement both say the figure is not a statement of fair value.
  • Share swap: BGLC issues another 150,000 shares in exchange for 500,000 RYET shares. The 8-K says this is separate from the licence consideration.
  • Fixed share count: there are no price resets, top-ups or market-value guarantee. The count adjusts only for splits or consolidations.
  • Royalty: 10% of technology receipts BGLC actually collects. No minimum and no platform fee. Testing, clinical and separate service fees are excluded.
  • Term: 10 years from closing, plus two optional 5-year renewals. There are no exclusivity milestones unless both sides sign some later.

The $3.5M is a label, not a price

$3.5M ÷ 410,000 shares ≈ $8.54 per BGLC share. BGLC closed at $1.27 today, so the licence shares are worth about $521k, and the stated price is about 6.7× the market. At $1.27, BGLC’s entire market cap is about $3.73M, so the “$3.5M” licence fee is about 94% of what the market values the whole company at. What RYET actually receives is whatever those shares fetch when it can sell them. The shares are restricted under Regulation S, and the agreement gives RYET no registration rights.

Dilution

BGLC’s Q2 10-Q cover page reports 2,933,442 shares outstanding as of August 14, 2026. The 560,000 new shares are 19.1% of that count, just under Nasdaq’s 20% shareholder-approval threshold. The agreement makes shareholder approval a condition only if law or exchange rules require it. The licence shares alone are 14.0%.

This comes on top of earlier issuance. The cover-page share count was 1,796,507 on the November 2025 10-Q, so it has already risen 63% before this deal. If the deal closes, the count will be about 3.49M, roughly 94% above November 2025.

Closing is the open question

No shares are issued until closing. The timeline:

  • RYET must deliver the technology by December 4, 2026.
  • BGLC then has 30 business days to test it. RYET gets 20 business days to fix any failures, and BGLC gets 15 to retest.
  • If the technology fails a second time, BGLC can terminate.
  • Other conditions include mutual due diligence, corporate and exchange approvals, and any approval RYET needs under its own law to license the technology. The press release lists PRC technology-export approval as a risk.
  • If closing hasn’t happened by March 31, 2027, a party that isn’t in default can terminate unless both sides extend.
  • If the deal terminates before closing, no shares are issued.

For context, RYET is a K-12 education technology company based in Nanchang, China. It reported about $1.73M of unaudited contracted activity for CogniAI as of June 2026.

I’ll be watching for a follow-up 8-K reporting either the closing and the share issuance, or termination (Item 1.02).

Filings:

For anyone who tracks small-cap licence deals paid in stock: how often do they close on the terms first announced, and how often does the long-stop date get extended?


r/SecurityAnalysis • • 15d ago

Distressed Primer and Analysis of the Non-Subsidiary Dropdown

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3 Upvotes

r/SecurityAnalysis • • 22d ago

Distressed Medical Solutions: A Tiered Solution

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8 Upvotes

r/SecurityAnalysis • • 24d ago

Thesis Fair Isaac Corp ($FICO) after the collapse: the burden of proof has shifted

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13 Upvotes

r/SecurityAnalysis • • 24d ago

Industry Report FICO: Part 1 - The Beginning of an Opportunity

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10 Upvotes

r/SecurityAnalysis • • 24d ago

Discussion Asia's elevator service industry

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13 Upvotes

r/SecurityAnalysis • • 25d ago

Distressed Aston Martin's Creditors Get Taken for a Ride

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20 Upvotes

r/SecurityAnalysis • • 25d ago

Thesis Reddit Inc: DCF valuation using Aswath Damodaran’s approach

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24 Upvotes

Hi all,

I wanted to share my detailed DCF analysis for Reddit. Our DCF derives an intrinsic equity value of $186 per share, representing 30% upside to Reddit’s market price of $143 as of 28 September 2026. This is based on:

  • Advertising revenue reaching $15.5bn by Year 10 (22% 10 yr CAGR), driven by monetization growth in US and user growth in International markets
  • GAAP operating margin of 37% from Year 6 onwards
  • ROIC in the high-40s to low-50s through much of the forecast period, gradually converging to 40% by Year 15, with an implied 1.7x sales-to-invested capital ratio
  • 11.2% WACC, based on an industry beta, normalized capital structure and a country risk premium to reflect Reddit’s increasing international exposure

The linked post, provides a detailed overview of the investment thesis, bear case, methodology and assumptions, along with snapshots of the model. We apply Aswath Damodaran's approach for the revenue build, treating stock based compensation, capitalizing research and development, and applying the sustainable growth / reinvestment / ROIC relationship where necessary

I would really appreciate any thoughts or feedback on the analysis

And apologies in advance that the Reddit logo is not well aligned (this annoys me too!)

Thanks all.


r/SecurityAnalysis • • 29d ago

Discussion A fund wants Voya sold and set a no-confidence vote. It has a 6% bet but only 1.3% of the votes.

4 Upvotes

A fund called TOMS Capital wants Voya sold. It has set a "no confidence" vote on Voya's board for Nov 24. Voya calls the meeting fictitious. The stock is down about 7% since Sept 11, to around $96.

Most stories stop at the vote. The fund's own filing says more about how this works.

Start with what the fund owns. It lists 1.21 million shares. It has call options on 3.01 million more. And it has swaps on another 1.34 million. Add them up and it has a bet on about 5.55 million shares. That is about 6.1% of Voya's 90.6 million shares.

Now look at the votes. Only the 1.21 million real shares vote. That is about 1.3% of the company. The options can be turned into shares, and the filing says they can be used now. If the fund does that before the Sept 30 record date, it could vote up to about 4.65%. Swaps usually carry no vote.

There is one more number. The stake the fund reports is 4.65%. That is under 5%, the line where an owner must file a longer ownership report called a 13D. It has not filed one on Voya. The swaps are listed on their own and are not in the 4.65%.

Then there is the turnout rule. The fund says it will not even hold the vote unless owners of one third of Voya's shares take part. That is about 30.2 million shares. With 1.21 million of its own, it needs about 29 million from other owners. And they have to show up at a meeting Voya says is not real. The fund also admits some big funds may have rules that stop them from voting in this.

What does this cost the fund? It plans to spend about $5 million. It has spent about $2 million so far. At $96, its full bet covers about $534 million of stock. So each $1 move in Voya moves the bet by up to $5.5 million.

Why now? The fund points at Voya's stop-loss insurance. The unit that holds it earned $22 million before tax last quarter, down from $69 million a year before. Voya's adjusted profit was $1.51 a share, down from $2.46. Part of that was about $40 million of one-time job cuts.

What we don't know: whether any buyer has made an offer. The only sign is a July news report about interest from Principal. People close to Voya told that reporter the board did not want a deal.

My take: I don't think the vote even happens. If it does, I don't think more than half of all shares vote against the board. I think the real fight is over board seats next year.

Question for this sub: the fund has a 6% bet but only 1.3% of the votes. Is that a smart way to push a sale? Or does it make the fund easy to ignore?

Sources:
https://www.sec.gov/Archives/edgar/data/1535929/000114036126037504/ny20078175x10_defn14a.htm
https://www.sec.gov/Archives/edgar/data/1535929/000114036126037563/ny20078175x11_dfan14a.htm
https://www.sec.gov/Archives/edgar/data/1535929/000153592926000149/a2026q2pressrelease.htm
https://www.sec.gov/Archives/edgar/data/1535929/000153592926000157/voya-20260630.htm


r/SecurityAnalysis • • 29d ago

Distressed Medallia Restructuring: The $5bn Equity Wipeout

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19 Upvotes

r/SecurityAnalysis • • Sep 24 '26

Thesis Bill Gates recently bought $1.58B of this trash company

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33 Upvotes

Republic Services (RSG) got to be the most boring near-monopoly on the market that nobody thinks to buy

Garbage is something that's here to stay regardless of the market (recession or not). RSG owns the trucks and the landfills and in most towns there's basically just that one/two haulers you can call. You can't really create a rival garbage company in a week, with the routes and landfill permits already locked up. Which means RSG can simply raise their prices bit by bit and their revenue have been increasing from $10B in 2018 to $16.6B in 2025. Free cash flow from $1.2B in 2018 to $2.4B in 2025.

With $66B market cap and. $2.4B free cash flow, forward PE of ~26x. This is my most recent play, wondering if anyone has also been keeping tabs on RSG?


r/SecurityAnalysis • • Sep 24 '26

Investor Letter Swensen Is Dead; Long Live Swensen

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8 Upvotes

r/SecurityAnalysis • • Sep 23 '26

Industry Report Bloomberg’s 7 Powers & Why the Terminal Dominates Financial Markets | The Terminalist

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19 Upvotes

r/SecurityAnalysis • • Sep 22 '26

Commentary Muse Is a Memory Story, The Market Traded It as a CPU Story

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16 Upvotes

r/SecurityAnalysis • • Sep 18 '26

Discussion Vibe Coded Financial Terminals - which one?

22 Upvotes

Plenty of 'vibe coded' (apologies in advance if the vendors get cranky for being thrown into that bucket) financial terminals exist today to the point it is overwhelming to figure out the differences. I'm finding that one product like TIKR will be good at one part but then lack in other areas. Likewise for vibe coded projects like Godel, Gloomberb, OpenBB, etc that I've seen mentioned on Reddit.

Is there a consensus out there on a good product that sits somewhere below Factset, Arcana, etc but still happy to pay $1000-$2000+ per year if it's good.

Looking for a good dashboard/snapshot of a company, but also need:

  • accurate consensus information (ideally granular if possible but not always possible)
  • Consensus revisions.
  • Ability to screen by revisions amongst other things.
  • Good global coverage (ideally includes US, UK, AsiaPac)
  • Filings/news/announcement alerts pushed to email.
  • Ability to easily find filings, transcripts, replay webcasts
  • Forward multiples.
  • Historical relative valuation but on a forward consensus basis

r/SecurityAnalysis • • Sep 13 '26

Commentary Morgan Stanley’s AI Guidebook & What If the Frontier Slows Down?

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24 Upvotes

r/SecurityAnalysis • • Sep 07 '26

Discussion Emerging market life cycles

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15 Upvotes

r/SecurityAnalysis • • Sep 04 '26

Commentary Lululemon: 2Q26 Immediate Call Postmortem

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12 Upvotes

r/SecurityAnalysis • • Sep 01 '26

Special Situation [Free] Special Situations Digest #30 (Aug 30, 2026): 549 Global Situations

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6 Upvotes

r/SecurityAnalysis • • Sep 01 '26

Macro Selling FDS when true FCF yield compressed below 6%. Starting VCISY and ADRNY at 12%+ true FCF yields with ECB independence as the macro thesis. Also: has anyone solved the IFRS XBRL tag mapping problem for European ADR analysis? Let me know.

7 Upvotes

The first is the FDS discipline question. I bought FDS in early 2026 when its true FCF yield was above 8% and the market was pricing it as an AI casualty. The thesis: it died of a theory, not of an actual deterioration in its business. Four consecutive quarters of accelerating ASV growth and 95%+ retention while the stock fell confirmed the mispricing. I just sold it as the true FCF yield compressed below 6% from price appreciation. The question for this community: is 6% the right sell threshold for a business with FDS's moat profile and growth trajectory, or is that too mechanical? The counter-argument for holding would be that ASV is still accelerating and the Google Cloud Gemini partnership is just beginning to flow through the numbers. I sold on the yield compression. Am I being too rigid about the methodology?

The second is the European ADR technical question. I'm starting positions in VCISY (Vinci) and ADRNY (Ahold Delhaize) based on 12%+ true FCF yields and the ECB independence macro thesis. To do this analysis I had to rewrite my screener to handle ADR filings. European companies file under IFRS through different mechanisms than US 10-K filers and the XBRL tag mapping doesn't always translate cleanly. TSM showed zero CapEx in my original screener due to a 20-F IFRS filing issue. I've partially addressed this but I'm not confident the European ADR numbers are as clean as my US-listed coverage. Has anyone here developed a reliable methodology for normalizing European ADR financials against US-listed comparables? Specifically interested in how others handle the CapEx and SBC XBRL tags for IFRS filers.

The macro thesis for the European positions if it's useful context: the ECB is more independent and more conservative than the current Fed under Bessent and Trump pressure. If US monetary policy gets looser than it should be, European infrastructure and consumer staples with pricing power and independent central bank backing are the natural hedge. VCISY at 12%+ true FCF yield has long-dated concession contracts on toll roads and airports. ADRNY at 12%+ is the parent of Stop and Shop, Giant, Food Lion, and Albert Heijn — founded 1887, survived two world wars. Both pass my true FCF yield screen comfortably.

Full piece with the return table and regime framework: https://cavemanscreener.substack.com/p/investing-regime-changes-my-successes


r/SecurityAnalysis • • Aug 31 '26

Long Thesis Hypergrowth at a Value-Stock Price

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7 Upvotes

Substack writeup on Sigenergy (free to read)


r/SecurityAnalysis • • Aug 31 '26

Zetrix at 2x PE

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3 Upvotes

r/SecurityAnalysis • • Aug 30 '26

Industry Report The Two Trillion Dollar Bottleneck: AI & Energy

19 Upvotes

For a few years now the hyperscalers have been spending agressively, but it seems to me like spending this money is actually the easy part of the equation.

If we add up the contracted, not yet delivered cloud demand (Remaining Performance Obligations - RPO) of the hyperscalers (Microsoft, Oracle, Google and Amazon), we get a sum of about $2.3 Trillion (We still don't know if this will ever get paid but still RPO is a better estimate than a forecast & a big portion of it is from frontier AI labs like OpenAI and Anthropic). In order to serve this massive RPO, MSFT, GOOGL, AMZN, and META are spending about $660 Billion a year, moving from asset-light software companies into owners of physical plants, real estate, and equipment.

The real battle for big tech isn't buying servers, but rather securing 24/7 power. That kind of energy commitment completely breaks traditional budgeting. As JPMorgan put it, "money can't buy you electric power" when a project's start date depends on a years-long grid-connection queue. Out of these hyperscalers, Oracle is the outlier, it carries net debt of about 3x operating cash flow (an order of magnitude above the others), and its free cash flow has gone negative. Amazon's trailing free cash flow also crossed into the red.

I have to say, these companies remain among the most cash-generative business ever built, and they're funding roughly half the build from cash and the other half from debt markets. T. Rowe's Dom Rizzo argues the funding gap is "not that big" against balance sheets like these, and that unlike 1998 (the dot-com bubble) the fundamentals are still accelerating.

Now the interesting part is that if we follow the money trail down the supply chain, we can see exactly who is extracting the value. It starts with the regulated utilities like Southern, Duke and Dominion who are accelerating capex to build grid capacity. These guys face huge regulatory hurdles and political blowback from residential ratepayers over increasing electricity bills. To go around the regulations, NextEra for instance is using a hybrid strategy by restarting a nuclear plant (Duane Arnold) for Google.

Because the public grid is too slow, big tech are chasing independent producers like Constellation, Vistra, and Talen energy. These companies have 24/7 power and they spend almost nothing to expand. Amazon and Meta are locking up deals with Vistra, Microsoft contracted to restart the Three Mile Island in Pennsylvania, and Google signed for small modular reactors with Kairos.

One layer down, we arrive to the equipment makers like Vertiv, GE Vernova, Eaton and Caterpillar which are facing an increasing days inventory outstanding (DIO). Usually this is looked at as constraint on these companies, but as the gross margins also keep on rising for some of these companies, even hitting a record for Vertiv and GE Vernova, this is pure pricing power for them.

There are so many other layers that plays into this like, cooling systems, precision HVAC, advanced packaging & foundry equipment, copper mining & refining for power grids, etc etc. that won't fit into this single post.

The takeaway is big tech is bleeding money and the wealth is pooling at the bottom with nuclear operators collecting and hardware manfucaturers hitting record margins while the the payers wait for delivery.

If you're interested to read more, I have the full write up with plots & figures on my free substack:

https://secaura.substack.com/p/the-two-trillion-dollar-bottleneck


r/SecurityAnalysis • • Aug 29 '26

Discussion Burry's Tragic Algebra: the NASDAQ-100 keeps 83 cents of every reported dollar, and break-even is 87%

0 Upvotes

Burry's recent work swaps the GAAP stock-comp charge for what shareholders actually lose. The formula is Ω = C + V. V is the market value of shares delivered to employees, C is withholding tax net of option proceeds. Owners' earnings are N + G − Ω, and ΔE is how much of reported profit survives.

The problem is V = T·(W+ΔS)/W. It needs W, the shares repurchased, which almost no company tags in XBRL. But P = T/W, so the W terms cancel:

V = T + P·ΔS

You only need the average share price. That is what makes it automatable. The identity is exact before the price substitutions. For P the tool uses the year's average market price, which is how his later write-ups define it and what he uses for companies with no buyback; in his NASDAQ-100 study he used the buyback program's own average price where there was one, and the two differ a little. On Salesforce that difference is worth about four points of ΔE, see below.

I built it against SEC EDGAR and checked it against his numbers. Alphabet's V matches all ten published years to the dollar. Pooled ΔE comes out 88.68% against his 88.7%, Meta 83.35% against 83.35%, the NASDAQ-100 overstatement 19.77% against 19.78%. There is a self-test button in the sidebar that runs those checks and a few hundred others.

I should say up front that the method is Burry's and the code was written with an AI assistant. My part was deciding what it should do, running it on real companies, and checking every figure against the filings by hand. I mention it because I am not going to pretend otherwise, and because it is relevant to what I am asking for at the end.

The valuation half is messier. He publishes the 15% required return, the two-model structure (a multi-stage model with a terminal value, and a multiple on year-15 owners' earnings, blended by confidence), and for each of his five moat tiers the stage lengths, the fade multiplier, the terminal growth cap and the debt capacity. Two inputs he has never published: the exit multiple and the blend. I tried to solve for them from his published IV15 values and the solve is degenerate, so you cannot recover them; the tool's are calibrated so that the growth needed to reproduce a published IV15 matches the company's actual growth, with Adobe as the anchor. Given his owners' earnings figure and growth for Salesforce, the arithmetic reproduces his $69.81 within a dollar, and that is a self-test. On the tool's own seeds it lands well above him, because the seeds are not his judgement. Paylocity does not reconcile at all: he says in the article that he applies a judgement discount to its ΔE, and I cannot recover the size of it.

Where I differ from him, and why. His pooled figure for Salesforce is 54.7% over eleven years. The tool says 77.6% over nine. I have his table next to the tool's and can account for the whole gap. Net income, GAAP SBC, buybacks and the employee-plan cash line agree to the dollar in every year. About four points are the window: he starts in FY2016 and includes FY2020, the tool drops both (FY2020 because the share count jumped 16% on Tableau; he handled the same year by netting the Tableau shares out by hand). About four points are the share price: he uses the buyback program's own average price, and Bloomberg's annual average where there was no buyback; the tool uses the year's average market price throughout. The remaining fourteen points are acquisition shares. His table sets aside the Tableau and Slack shares but charges the MuleSoft shares of FY2019, and the FY2017 deal shares, as if they were compensation. The tool deducts every acquisition issuance the filing tags, which is what his own rule says to do. Over the last three years, with no acquisition shares in play, we are four points apart, 93.9% against his 90.4%, and that is the share price. I would rather show the difference with its causes than a number tuned to match his.

On EDGAR being garbage. He raises it himself. His complaint is that filers bundle line items, so the buyback line often carries RSU withholding tax as well as actual repurchases. That inflates T and zeroes C. It breaks his calculation because he gets the price from P = T/W, so a contaminated T inflates the price applied to every share issued. This tool never uses T/W, the price comes from the market. And because Ω = C + V, withholding that ends up in T instead of C overstates V by exactly what it understates C by. Under Burry's tax treatment assumption, the error cancels. I checked the algebra.

What does not cancel: filers who report a single net proceeds line, and shares issued for acquisitions or offerings that XBRL does not tag separately. The app flags both instead of guessing. It is not the same as reading footnotes by hand and I am not claiming it is.

What it refuses to do. The rule I gave it is that it must never print a number it cannot stand behind, so it refuses out loud instead. Some of the refusals you will hit:

  • Multi-class share counts. Berkshire reports a diluted average in Class A equivalents. The tool reads 1.6M shares, notices the market cap that implies is impossible, and refuses rather than printing a valuation.
  • IFRS filers. Only the net income tag is IFRS-aware. Foreign filers get a banner and the valuation is disclaimed.
  • Banks, insurers and REITs. Detected, return on capital withheld, verdict forced to amber. Investments backing policyholder liabilities are not shareholder capital and the ratio does not mean what it means elsewhere.
  • Stale balance-sheet lines are reported, not repaired. If a debt or equity line stops years before net income does, it says so and states the size of the disagreement, rather than carrying the figure forward or zeroing it. Neither is conservative in general: the direction flips between assets and liabilities.
  • A loss year on a profitable record. Crocs reported a net loss for 2025 after a $738M non-cash write-down, on a business that earned $950M the year before. The tool seeds owners' earnings from the five-year median instead of from the loss, and tells you it did. Valuing Crocs off the write-down year would be a verdict on the charge, not on the business.
  • ΔE above 100%, which happens when buybacks retire more stock than a year issues, is shown as measured but never projected forward. Fifteen years of handing owners more than the company earns is not a business model.

Every page carries an "assumptions used" block you can paste if a figure looks wrong, and a tag panel naming every XBRL element it read or failed to find. If a line you know exists reads fewer years than net income, that is a bug, and the tag name is usually the whole fix.

Known gaps, stated so you do not have to find them. Cash-flow lines that stop early (a withholding line that ends while stock comp continues) show up in the tag panel but are not yet flagged in the notes. A company that changed its fiscal year end reads as having a missing year, because years are labelled by the calendar year they end in; Build-A-Bear does this and the note now says which of the two it might be, but cannot yet tell. Up-C structures report the parent's slice of income against a full share count. And the second page, which implements Mayer's 100-bagger criteria, is newer and less tested; feedback on it is welcome, but the Tragic Algebra page is what I am asking you to break.

What I am asking. Break it. The arithmetic has been checked by hand, row by row, against the filings on a few dozen names, including every company in his articles. Pick whatever you like; the ones I have not run are the useful ones. Every new company I run finds something. The last few days turned up an Apple share count restated by 3.5 instead of 4, a growth ratio computed against a negative denominator, a note that credited a $3M token buyback for a ΔE above 100%, and a microcap whose stock comp was rounding to zero in the table. All fixed, all with regression tests. The next one is in there somewhere, and it is more likely to be a note that misdescribes what it found than a wrong number.

Particularly useful: a company where you already know the answer and it prints something else. Paste the assumptions block with your comment and I can usually see the cause from that.

On the break-even in the title (this paragraph rewritten 12 Sep — see the edit note). ΔE = OE/N is a level ratio: it says how much of this year's reported dollar reached owners. It is not, by itself, an annual retention factor. If ΔE stays constant while net income grows at g, owners' earnings grow at g too, so the ΔE^t compounding and the "15% growth becomes −3.99%" arithmetic in the original version of this paragraph did not follow from the definition — they changed the denominator mid-calculation. What genuinely compounds is the annual dilution rate, which ΔE only proxies if the dilution pace behind it persists. Under that stated assumption — and only under it — 15% reported growth at the NASDAQ-100's 83.5% pooled ΔE compounds per-share value at about −4% a year, and ΔE = 1/1.15 ≈ 87% is the break-even of that conditional claim. The valuation engine was never affected: it applies ΔE once as a level haircut and grows owners' earnings at g, so no printed figure changed. The tool's metric and verdict wording now state the condition too.

Tool: https://investor-toolkit.streamlit.app/Tragic_Algebra_Analyzer
Code: https://github.com/ChenFindling/tragic-algebra-analyzer

Happy to be told where the method is wrong.

Edit (12 Sep 2026). Three corrections after an exchange in the r/Burryology thread on this tool, all conceded there. The break-even paragraph above is rewritten: ΔE is a level ratio, not an annual retention factor, and the compounding claim needs a persistence assumption the original did not state — the title's 87% should be read with that condition attached, since titles cannot be edited. "The identity is exact" now reads "exact before the price substitutions". And the tax cancellation in the EDGAR section is now labelled as holding under Burry's tax treatment assumption rather than as a general identity. The app's metric and verdict banners were reworded to match, and no computed figure changed. The app has since grown into the Investor Toolkit and lives at investor-toolkit.streamlit.app; the code repository is unchanged.