BTCUSD, TSLA/MSTR, and other names are treated as tradeable pairs: everything is framed as a pair, and 20% of the watchlist is said to be pair trades based on big deviations.
A 2022–2023 swap box moved out of MSTR into TSLA using options because self-custody wasn’t trusted; the ratio was about 110 to 1.45 TSLA shares per MSTR, and it worked well.
MSTR is still held with very low cost basis; more than 50% remains after selling a bunch, and the next swap is planned only when Bitcoin and relative pair action line up.
MSTR’s main risk is MSCI: a 16 October meeting could decide on possible withdrawal, with any booting leading to November 2026 rebalancing and about $2.88 billion of forced selling against a $61 billion market cap, or roughly 4.5% net sell pressure.
That MSCI scenario is called a liquidity bruise, not a total disaster, and the point is that there’d be zero-for-sale Bitcoin liquidation: the sell pressure is on the stock, not the 846,000 BTC held.
SpaceX is shown as a 1,000-share position at a $180 billion valuation and about $20 average cost, already up about 8x, and the preferred move is not to sell the shares.
For SpaceX, the recommended monetization is selling far-OTM calls: at roughly 150, a 30-point-OTM example pays about $0.46 per share, or about $460 on 10 contracts, annualized to about $6,440 and a 4.41% ROI.
A second SpaceX example uses $175 calls with a $700 premium, annualized to about $10,000 and 6.71% ROI; a third uses November 20th $2,000 calls, needing a $50 move in two months, for about $8,400 annualized ROI.
A closer SpaceX example uses October 16th $165 calls at $1.65 per share, or $1,650 total; repeated like clockwork, that is framed as about $20,000 a year, but monthly cover-call timing is warned against because it can get the bag called away.
The call-selling method is mean reversion: sell into overbought spikes, take put premium at green-dot bottoms, and use the sequence of blue-line upside spike, red-dot overbought selloff, then green-dot oversold bounce as the signal chain.
The house rules are: always rotate, always trim into strength, always hedge when you can, sell premium, and don’t roundtrip anything.
The core/trading split is 80/20: the 80% core is the mattress, the 20% trading bag is used to speculate, sell options, and generate cash to add to the mattress.
Round-tripping is treated as inevitable unless you actively harvest gains: EOS was bought at $5 after a long wait for $20, ran to about $350, and then gave it all back; SOL went from $10-$20 to $300, then back to $8 and now about $122.
The Lilo/profit-taking model is explicitly pre-calculated around volatility, historic trends, and expected path, with the point of using data science to set exit levels and prevent round-trips.
ALAB is the clearest example: $8,000 buys 100 shares at $80, then 39 shares are sold at 285, 20 at 365, and 11 at 493; that pulls out $23,838, later rebuys at level five, leaves 30 shares, and adds another 92.7 shares, with ROI cited as 464% or 5.63x versus 358% buy-and-hold over just over 6 months.
MRVL is the same template: buy 100 shares at 80, then sell 20 at level 6, 12 at level 7, 22 at level 8, 12 at level 9, and 7 at level 10; from an $8,000 start, $15,646 is pulled out and the ROI is cited as 3.82x.
Tax treatment matters: profit-taking is called especially good in tax-free accounts, while short-term gains are said to be heavily hit, so longer-term capital gains over 12 months are preferred.
TSLA is still the core example: no TSLA shares have been sold, the bag was built through LEAPS bought in 2017, 2019, heavy buying in March 2020, and again when TSLA fell to 300, including a ton of $300 strike LEAPS for December 2028.
LEAPS are described as a way to sit back and watch the fireworks, but only on assets that go up; the idea is to convert LEAPS to stock at a very low price, as with SpaceX $100 strike LEAPS.
AI models are criticized as backward-looking: they often lack real-time data, use data from 6 months or a year ago, can’t bottom-up model like CERN Basher, and would miss nonlinear growth even if Grok could print future prices.
TSLA upside is framed through huge future TAMs: humanoid robots are given a $25-$30 trillion TAM and cyber cabs a $10 trillion TAM, with Texas proving out the S-curve.
Texas cyber cab scaling is the big near-term trigger: 42 vehicles on May 28 and 546 on September 25 is cited as 13x growth in 120 days, with a path from zero to 126 in about 35 days and then a projected 2,000 by end-February.
The warning is that AI will not recognize that ramp and will arb it away; the advice is to be careful if using AI to reach financial freedom because it won’t understand the nonlinear S-curve.
TSLA’s fleet mix is said to be 76.9% Model Y and 23.1% cyber cab within 35 days, with more cars already deployed outside Texas in Florida, California, and Nevada.
A separate TSLA/Starlink angle says the mattress can absorb black swans, margin calls arrive every 1 to 2 years, and the long-term compounding plan uses margin at 5.4% to 4.5% while asset appreciation reduces the debt burden.
MSTR versus ASST is compared on NAV premium: ASST is said to be about 1.49 NAV premium, or a 50% premium to its Bitcoin bag, while MSTR trades at a 20% discount; the answer is no on ASST and yes on MSTR.
UMAC is called extremely undervalued at $23, after entry in the teens and a move to $32-$35 before mean reversion; the next earnings report is about 6 weeks away from the 6 August print, and the company is said to have beat revenue growth expectations by 81%.
The closing playbook is to buy early, buy hard, never sell the core, sell calls on spikes, sell puts on dips, take profits, rotate pair trades, learn options, and do not round trip.
TSLA’s long-term machinery is still the biggest narrative: the heat shield is said to be solved, boosters have been recaught once, fueling takes 30 minutes, flights per stack of 3.3 to 4.8 by next year or the year after would be bonkers, and Starship is expected to get to daily cadence eventually.
Starlink scaling is described as the near-term economic engine: 11,000 satellites are already up, one Starship load equals 440 legacy satellites, V3 satellites have 10x the bandwidth per bird versus V2, and one operational Starship with a V3 load can replace 4% of constellation capacity.
The operational cadence is accelerating: flight 14 is supposed to carry real V3 satellites, October is a potential start, then three flights per month, then possibly daily cadence next year or the year after.
The monetization case is that capacity will be sold directly to consumers and carriers, including Entity, Tacomao, and Deutsche Telecom, with four carriers already able to connect directly into the iPhone 18.
The demand pitch is that the market shifts from home Wi-Fi to global cellular communications; reaching 30% of the global market is framed as a $5 trillion TAM, and the specific customer may be machines and AI agents rather than retail consumers.