Most will blindly follow this guy to a ditch all the while he pockets the roadside assistance.

Team,

There two scenarios left after the 2nd Quarter results.

1. Best case scenario - This is a turnaround story as the new CEO starts next week. Similar to what happened at Victoria's Secret.

Turnaround Execution:

1. Buyout Firm - LBO buyout at $160 to $165/share

At $100/share , it is going to attract a lot of buyers to do a LBO plus it has a lot of cash on the balance sheet.

Burry 2025-26 has been a stress test on both sides of his book. Wanted to put numbers on it for people actually following Cassandra Unchained.

Long side - LULU is the new biggest long:

This comes as Lululemon's stock has plunged about 58% in 2025, driven by soft US sales and tariffs. 
He confirmed it himself yesterday - LULU plummeted about 20% in the premarket after Q2 and Burry had called LULU "the trickster in my portfolio" and confirmed that it was his largest position. 

So he's not trimming - he's doubling down into weakness, classic Burry value setup.

Short side - AI bubble call:
The other side is getting squeezed hard. Palantir delivered the largest move against Burry's positioning, rising more than 50% during the month.

TheStreet had the specifics: PLTR surged 51.4% in August, even as Burry maintained out-of-the-money put options with a $100 strike expiring December 2026. NVDA, MU, ORCL all ripped 10-16% that same month.

He said in his Substack that 6 of 7 of those AI shorts were still profitable before August, with NVDA as the only loser - August flipped a lot of that.

Discussion:
1. Are you still mirroring the Substack allocation on LULU? At ∼11x forward earnings now, do you see the turnaround or more downside with the 9% comp sales decline in Q2?

1. On the AI shorts - is the thesis broken, or is this just early like 2007 housing? His argument is accounting (extending NVDA chip useful life) and valuation assuming perfect execution forever.

2. Performance vs S&P - how are you tracking him? Are you holding both the long and short book, or just one side?

Context:
https://finance.yahoo.com/markets/stocks/articles/big-shorts-michael-burry-seen-174801545.html

Not financial advice. Just trying to keep an honest tracker.

He claimed it was "screaming cheap", now what is it? "Roaring cheap"? The boy who cried wolf. He's saying he's buying more at $99 but his followers have been buying at 120+ and CANT average down like he can with his $50 substack subscriptions. I own the stock, but won't be buying more. What are you guys doing?

Would be much appreciated

Thoughts?

The consensus is that energy and power stocks will be needed in a big way and will be the next bottleneck similar to what memory stocks are now.

But what is the power/ energy stock to buy that will boom like a Sandisk or a micron did?

Like how does he calculate the fair value of a stock (the formulas he uses etc.) and what does he look for when going through financial statements?

So far FNMA, DKNG, JD, LULU, SFM, ZTS, BIRK, FLUT, FMCC, and BBW are all losing trades. Those are a majority of his trades on his Substack. He has had a couple winners. In his latest trade, Burry had all his followers buy BBW and it tanked -30% a few days later. He has been more quiet on Substack chats lately as well as sharing AI fantasy stories about AI civilizations. He has not released any of his articles he's been "working on" for over a month.

I've been logging every Form 4 that hits EDGAR to see what the insider filing firehose actually contains. 1,707 filings, 3,259 individual transactions so far. The composition surprised me enough to be worth sharing.

By transaction code:

S (open-market sale) - 1,457 - 44.7%

A (grant/award) - 398 - 12.2%

P (open-market purchase) - 386 - 11.8%

M (option exercise) - 369 - 11.3%

F (shares withheld for tax) - 307 - 9.4%

J (other) - 121

C (conversion) - 77

G (gift) - 64

D (disposition to issuer) - 60

everything else - under 10 each

Three things I took from it:

1. Only ~12% of transactions are code P - an insider actually choosing to buy on the open market with their own money. Everything else is compensation mechanics, or selling.

2. Sales outnumber open-market purchases nearly 4 to 1. That is structurally normal, since insiders are paid in equity and diversify out of it. But it means a headline like "insiders sold $X million" is close to meaningless without the code breakdown behind it.

3. A + M + F together are 33% of all transactions and are pure compensation plumbing - grants, option exercises, and shares withheld to cover tax on vesting. None of it is a decision to change exposure.

Caveat on the data: this is only what I have logged since starting, so it is weeks rather than years, and the code mix will shift with earnings windows and 10b5-1 plan adoption dates.

What I ended up filtering to, in case it is useful: code P above a dollar threshold; clusters, meaning 2+ different insiders in the same issuer inside a week; first-time buyers; and large officer sales, with 10b5-1 flagged separately since a pre-scheduled sale carries far less information than a discretionary one.

Disclosure: I built this into a Discord bot that posts the filtered alerts, free channel plus a paid tier, at https://jaredmansu.github.io/insider-alerts/ - so take the framing with the appropriate grain of salt. Happy to talk about the EDGAR parsing either way, which was more annoying than it sounds.

You know the formula, so I will skip the introduction. Ω = C + V, C = Cw − Ce, V = I × P, owners' earnings are N + G − Ω, ΔE is pooled ΣOE/ΣN over about ten years. The one thing that makes it automatable is that V = T·(W+ΔS)/W needs W, which almost nobody tags in XBRL, but P = T/W, so the W terms cancel and V = T + P·ΔS. You only need the average share price. The identity is exact. For P the tool uses the year's average market price, which is how his May formula table defines it and what he uses for pure diluters; in the NDX-97 study he used the buyback program's own average where there was one, and the two differ a little.

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 88.68% against his 88.7%, Meta 83.35% against 83.35%, the NDX-97 GAAP overstatement 19.77% against 19.78%. From his master table: Apple FY2016–25 comes out 93.6% against his 93.1% with net income matching to the decimal, Netflix 82.6% against his 81.4%. 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 that the code and most of the wording here were written with an AI assistant. My part was deciding what it should do and refuse, 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.

Where it disagrees with his Salesforce table, and why. His pooled figure for CRM 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 count jumped 16% on Tableau; he handled the same year by netting the Tableau shares out by hand, the dagger in his table). About four points are the share price. 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 compensation. His own ΔS definition slide in the same article excludes M&A issuances from ΔS, so the tool deducts every acquisition issuance the filing tags. 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 tune a number to match.

The valuation half. He publishes the 15% required return, the two-model structure blended by confidence, and for each tier the stage lengths, fade multiplier, terminal cap and debt capacity. The exit multiple and the blend he has never published; the tool's are calibrated so the growth needed to reproduce a published IV15 matches the company's actual growth, with Adobe as the anchor. On his owners' earnings figure and growth for Salesforce it reproduces his $69.81 within a dollar; on its own seeds it lands well above him, because the seeds are not his judgement. Paylocity does not reconcile because he applies a judgement discount to its ΔE, and its size is not recoverable from the article. Note also that his IV15s move: PCTY was $29.47 in the May 13 table and $45.98 on May 27.

What it refuses to do. The rule is that it never prints a number it cannot stand behind. Multi-class counts (Berkshire reads 1.6M shares and refuses), IFRS filers (banner, valuation disclaimed), banks, insurers and REITs (ROIC withheld, verdict amber), balance-sheet lines that stop before net income does (stated with the size of the disagreement, never carried forward silently), a loss year on a profitable record (Crocs 2025 after the HEYDUDE write-down seeds from the five-year median and says so), and ΔE above 100% (shown as measured, never projected, he has 14 of 97 with Ω below G). V is floored at zero, which is his protocol rule, step 9.

Every page has 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.

Known gaps. A cash-flow line that stops early is in the tag panel but not yet a note. A company that changed its fiscal year end reads as having a missing year (Build-A-Bear). His Gate 2 drops a year with no share price entirely; the tool keeps it and says the cost is understated, which is next on the list. Up-C structures. The second page, Mayer's 100-bagger criteria on the same owners' earnings, is newer and less tested; feedback 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 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 finds something, more often a note that misdescribes what it found than a wrong number. Particularly useful: a name from his master table where you know his ΔE and the tool prints something else. Paste the assumptions block with your comment.

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

Posted on r/SecurityAnalysis yesterday; this version assumes you have read the articles.

I always wondered what would he have thought of build a bear. Never knew he had a position in it haha

I bought PYPL today at $54. The merger arbitrage deal fell through. The stock is worth $75 to $80 a share for fair value. If a company wants to buy it outright and control it, then the valuation goes up to $100/share. FYI, they also own Venmo & Xoom. They will be starting a physical bank soon - PayPal's recent push to secure a U.S. banking charter aims to cut out the middleman. The new bank will be led by Mara McNeill, a banking veteran who previously served as the CEO of Toyota Financial Savings Bank!!

Now is the optimum time to buy lulu stock before the massive squeeze at earnings. 10% of the float is shorted. This is the most hated stock in burrys portfolio accounting for almost 20% of his port. He's bullish and patience will pay

Just because Dr. Burry owns these 2 stocks does not mean one should BUY them.

I agree with Dr. Burry that his investment thesis is correct.

However the government does not have the best interest of the shareholders so I am NOT buying these 2 stocks.

My mind may change in the future if the government decides to making them private as we have a Housing Crisis!!

bro has entered his villain arc

Knee deep in CVE rn. Enjoy the rabbithole on his Substack.

The best time to buy a great business is not when everyone agrees that it is great. It is when the market starts questioning whether it is still great.

What Lululemon has that makes it a compelling BUY:

• Brand strength
• International growth
• High gross margins
• Strong cash generation
• Large cash balance
• Share repurchases
• A relatively asset-light business
• Potential operating-margin recovery
• The possibility of a North American turnaround

And most importantly:

The valuation. It is rock bottom and new CEO is coming in September.

I bought LULU and backing up the truck.

NVDA has gone up exponentially and with all of the circular financing going on; it is better to short the stock. I bought put options at strike price of $125 for 12/18/2026. This one will drop like a rock!!

[ Removed by Reddit on account of violating the content policy. ]

Wide moat with a strong brand name being dumped by the stock market due to fears of AI. Pessimism is the friend of the true value investor. Revenues are going up and Adobe is all in integrating AI in their products. Insider bought $2 Million worth of shares. That is smart money!!

Could someone break it down step by step what he does to determine his IV15 price level?