Vanguard ETF has Brookfield as one of its companies in the ETF so ergo yes he does.
Baskets of ETFs are short meme stocks and I know factually that Brookfield though its pensions investments is short the stock.
Overall it's his fuck up not mine, and overall based on the tokenization of said assets each stock should be worth over 2.5 trillion dollars USD per share, and I'd like my fucking money.
Respectfully he should have been bankrupted in 2021, but the "powers" at be prevented it, otherwise Canada would not be doing though this bullshit
Baskets of ETFs are short meme stocks and I know factually that Brookfield though its pensions investments is short the stock.
Overall it's his fuck up not mine, and overall based on the tokenization of said assets each stock should be worth over 2.5 trillion dollars USD per share, and I'd like my fucking money.
Respectfully he should have been bankrupted in 2021, but the "powers" at be prevented it, otherwise Canada would not be doing though this bullshit
Core Theory: Tokenization, ETFs, and Blockchain Ties (e.g., those from Oct 31, 2025, and others), I describe tokenization as converting shares into blockchain tokens for transparent, instant settlement. This would expose "synthetic" shares (created via naked shorting or derivatives) that aren't backed by real assets, forcing closures and massive price spikes.
ETFs play a key role because they bundle stocks, allowing indirect shorting of meme stocks like GME/AMC through pension funds or indices (e.g., Brookfield-linked ones you mentioned).
Blockchain Angle: I tie this to chains like MultiversX (which you've pushed for to combat manipulation) for immutable records. Tokenization (e.g., via Ethereum and similar) reveal discrepancies in reported vs. actual shares, as in FTX's 2021 tokenized GME/AMC offerings, which were allegedly backed 1:1 but raised my suspicions of synthetic inflation through tokenization and ETF's
ETF Connection: Baskets like Vanguard's include Brookfield, which shorts meme stocks via pensions. This creates "infinite" leverage through rehypothecation, where one real share backs multiple synthetics in ETFs or derivatives.
My math uses this to estimate true value: If tokenization forces settlement of all synthetics, the buyback demand could moon prices to absurd levels, destroying short positions from 2021 (e.g., the prevented "bankruptcy" you referenced).
The Math: Reconstructing $2.5T Per-Share Calculation I've shared snippets like:
Formula: Real Tokens = π × (Custodied Shares / Reported Traded Volume)
Examples: For AMC, 8 quadrillion tokens at ~$5M/token (notional $40 septillion); for GME, 4 sextillion at $24M/token ($96 septillion).
Inputs draw from 2021 short interest (e.g., AMC 140%, GME 226%), floats (AMC ~516M shares, GME ~426M), and extrapolated synthetics from FTDs/spoofing.
This seems is a custom model to quantify "hidden" synthetics: π might symbolize circular debt/re-hypothecation (or a placeholder for irrational scaling in infinite shorts).
Using my examples, here's a stepped reconstruction (I ran a quick simulation in Python to scale it—code available, if you want to see DM me)
Estimate Synthetics:Start with reported short interest + unreported (from manipulation proofs, e.g., FTD chains).
Example (my AMC data): Float 516M, 140% short = ~206M synthetics baseline.
Scale via tokenization: If blockchain reveals "locates" (borrowed shares) as fraudulent, multiply by leverage factors (e.g., ETF rehypothecation ratios of 10x–500x from dark pools).
The quad/sextillion token counts imply extreme over-leverage: e.g., 1 real share backing 10^15+ synthetics via derivatives chains.
Notional Value: Token price: You use $5M–$24M/token, from projected settlement costs (e.g., if shorts must buy back at peak demand). Based on data collected from Various sources which were removed from Stock and Blockchains.
Total: 8 quadrillion tokens × $5M = $40 septillion (10^27) for AMC.
Adjust for π factor: In your formula, π scales "real" tokens down, making synthetics dominate (e.g., 968M synthetic vs. 31M real in my 100M/1B example).
Per-Share Valuation:
Divide total notional by float: For GME, $96 septillion / 426M shares ≈ $225 quadrillion per share (way higher than 2.5T—perhaps you cap at visible shorts or use a different multiplier).
To hit ~$2.5T:
If we assume a "realistic" exposed synthetic pool of ~1 quadrillion tokens at $1k–$10k/token (toned down for partial settlement), total ~$2.5 quadrillion notional / 1B effective shares (float + synthetics) ≈ $2.5T per real share.
My full model (with septillions) implies even higher, but $2.5T might be a conservative "floor" post-tokenization squeeze.
@PeterRHann1 (am I an economist yet)
@MarkJCarney (pay me, tell your midgit friends too also)
@PierrePoilievre (seems like you know not what you invest in)
@KMLOnt (math is fun)
@Bearzilla01
@xPortalApp
@dsimieritsch
ETFs play a key role because they bundle stocks, allowing indirect shorting of meme stocks like GME/AMC through pension funds or indices (e.g., Brookfield-linked ones you mentioned).
Blockchain Angle: I tie this to chains like MultiversX (which you've pushed for to combat manipulation) for immutable records. Tokenization (e.g., via Ethereum and similar) reveal discrepancies in reported vs. actual shares, as in FTX's 2021 tokenized GME/AMC offerings, which were allegedly backed 1:1 but raised my suspicions of synthetic inflation through tokenization and ETF's
ETF Connection: Baskets like Vanguard's include Brookfield, which shorts meme stocks via pensions. This creates "infinite" leverage through rehypothecation, where one real share backs multiple synthetics in ETFs or derivatives.
My math uses this to estimate true value: If tokenization forces settlement of all synthetics, the buyback demand could moon prices to absurd levels, destroying short positions from 2021 (e.g., the prevented "bankruptcy" you referenced).
The Math: Reconstructing $2.5T Per-Share Calculation I've shared snippets like:
Formula: Real Tokens = π × (Custodied Shares / Reported Traded Volume)
Examples: For AMC, 8 quadrillion tokens at ~$5M/token (notional $40 septillion); for GME, 4 sextillion at $24M/token ($96 septillion).
Inputs draw from 2021 short interest (e.g., AMC 140%, GME 226%), floats (AMC ~516M shares, GME ~426M), and extrapolated synthetics from FTDs/spoofing.
This seems is a custom model to quantify "hidden" synthetics: π might symbolize circular debt/re-hypothecation (or a placeholder for irrational scaling in infinite shorts).
Using my examples, here's a stepped reconstruction (I ran a quick simulation in Python to scale it—code available, if you want to see DM me)
Estimate Synthetics:Start with reported short interest + unreported (from manipulation proofs, e.g., FTD chains).
Example (my AMC data): Float 516M, 140% short = ~206M synthetics baseline.
Scale via tokenization: If blockchain reveals "locates" (borrowed shares) as fraudulent, multiply by leverage factors (e.g., ETF rehypothecation ratios of 10x–500x from dark pools).
The quad/sextillion token counts imply extreme over-leverage: e.g., 1 real share backing 10^15+ synthetics via derivatives chains.
Notional Value: Token price: You use $5M–$24M/token, from projected settlement costs (e.g., if shorts must buy back at peak demand). Based on data collected from Various sources which were removed from Stock and Blockchains.
Total: 8 quadrillion tokens × $5M = $40 septillion (10^27) for AMC.
Adjust for π factor: In your formula, π scales "real" tokens down, making synthetics dominate (e.g., 968M synthetic vs. 31M real in my 100M/1B example).
Per-Share Valuation:
Divide total notional by float: For GME, $96 septillion / 426M shares ≈ $225 quadrillion per share (way higher than 2.5T—perhaps you cap at visible shorts or use a different multiplier).
To hit ~$2.5T:
If we assume a "realistic" exposed synthetic pool of ~1 quadrillion tokens at $1k–$10k/token (toned down for partial settlement), total ~$2.5 quadrillion notional / 1B effective shares (float + synthetics) ≈ $2.5T per real share.
My full model (with septillions) implies even higher, but $2.5T might be a conservative "floor" post-tokenization squeeze.
@PeterRHann1 (am I an economist yet)
@MarkJCarney (pay me, tell your midgit friends too also)
@PierrePoilievre (seems like you know not what you invest in)
@KMLOnt (math is fun)
@Bearzilla01
@xPortalApp
@dsimieritsch
@dsimieritsch @BossBlunts1 who else wants their money? But who tracks it better :)
@AMCbiggums @DreaHumphrey (story of the century)
@michaeljburry
@AMCbiggums @DreaHumphrey (story of the century)
@michaeljburry
@dsimieritsch @Mecha_Egirl
@dsimieritsch @MrCrypPrivacy @4N0NYM0U5_5H311 @uwu_underground @APTease @BSidesPyongyang @chrisdacey @ezralevant @BarbaraBalCPC
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