Mudville rejoiced:

It was much worse over in the land of “What’s Next,” led by our friend, fElon:

The AI bubble is not simply a valuation story. It is a financing story. The market has treated AI as a demand shock for a handful of capital-light monopolies. But AI is turning those same firms into capital-intensive infrastructure companies. The passive bid absorbed buybacks. It may now be asked to absorb issuance.

Perhaps this is the start of the turn in the localized mania of AI breaking. While much of the behavior remains “passive at work,” we’ve seen a growing role from the actual flows into AI stocks as retail increasingly decides it has “figured it out” — it’s all about AI:

I wish it were that simple. We’re increasingly seeing behaviors that suggest more sophisticated parties are now playing along — with leverage. For example, look at the behavior between NVDA and its 2x levered ETF variant. The shares outstanding for NVDU, the Direxion 2x levered NVDA ETF (one of a surging number of levered single-stock ETFs classified as “active”), have begun tracking inversely to NVDA share price, a notable change from 2023-2024:

Typically, when we see this pattern, it’s a sign that the volatility harvesters are in play. Buying NVDU while selling NVDA call options is a fairly efficient call overwriting strategy. The emergence of derivative-income ETFs (like NVDY or similar capped-upside, high-yield products) plays a massive role in changing the plumbing of single-stock levered ETFs:

• These yield-harvesting funds often use a mix of options and levered underlying instruments to generate high monthly distributions.

• Because they harvest premium by selling upside call options, they cap their gains on the way up but absorb downside beta. When the underlying stock rips through the strike prices, these funds are forced to dynamically manage their collateral and delta-hedging exposures—often resulting in trimming underlying levered long exposure (NVDU redemptions) during massive rallies to lock in premium or cover assignments.

• This suggests the characteristics of NVDA’s shareholder base are starting to shift. Rather than a performance-chasing retail play, it has matured into an institutional tool with many holders trapped by a highly-appreciated stock they are unwilling to take taxable profits on. When a single stock becomes a systemic macroeconomic proxy, professional desks use the 2x vehicle as a highly efficient, capital-insulated tool to trade mean reversion, harvest high variance, or hedge complex options books without tying up massive amounts of prime brokerage margin.

In other words, it’s no longer about love for NVDA — it’s just become another stock. That alone SHOULD be a warning sign.

But there were others this week:

I’m increasingly convinced that the AI universe has deeply misunderstood its product offering. While many, myself included, are loving the access to productivity-enhancing tools, AI has been embraced by users in an unprecedented manner:

There are a number of key points in the above graphic, but let’s focus on the “2:1 Personal use exceeds work use.” My growing conviction is that AI is being perceived by personal users as “Subsidized access to ‘help’ in answering the many questions that would have previously been unavailable to me in an economic manner, delivered in a non-judgemental and non-invasive manner.” Consider:

This appears unsurprising to me. The most popular columns in newspapers for decades were the “personal advice” columns. In internet parlance, “AITA” (Am I the asshole?) is a common theme. The market for professional-level advice seems unlimited at $0 to $20/month. There’s only one problem:

Those who lived through the original online retail bubble may remember this model. Yes, there is tremendous demand for Ben & Jerry’s ice cream delivered by Kosmo.com at subsidized prices below those of local retail stores. It is not a good business model. So AI companies have turned to marketing themselves to businesses as “labor replacement.” It’s not going so well:

Why? Because it’s a very deep misunderstanding of economics. AI companies are marketing AI as “labor replacement” and appear captured by the narrative that we can move to a “post-capitalist” society where all the “work” is done by machines. In economics, labor has a unique signature — a backward-bending labor supply curve:

This, in turn, plays a critical role in forming models for utility and innovation. Since humans exist in non-ergodic space, i.e., they have only one life to live, as incomes rise, the demand for leisure increases. This, in turn, spurs innovation in time-saving goods and services to replace previously labor-intensive tasks. In other words, technology exists to AUGMENT human labor. TASKS can be replaced by machines, but the core of economics remains the system of human wants, and humans cannot be replaced.

The AI industry has mistaken usage for a business model and task completion for labor replacement. What consumers have discovered is extraordinary: subsidized access to nonjudgmental, always-available help in answering questions, organizing choices, drafting language, interpreting conflict, and reducing the cognitive burden of daily life. It may be one of the largest reservoirs of latent demand ever revealed. But it is not the same thing as enterprise labor displacement. The former is advice-column economics at a planetary scale. The latter requires workflow integration, accountability, liability transfer, trust, and measurable P&L impact. The industry is trying to monetize the first by promising the second.

And subsidized access to help is not, by itself, a capitalist victory. It is a revelation of demand. The business demand for AI will emerge, but it will require business-process reinvention, not merely sprinkling models over existing workflows. The early enterprise buildout resembles the pre-factory stage of industrialization: semi-skilled human labor was gathered into larger rooms and organized more tightly, but the production process itself had not yet been fundamentally redesigned around the machine. Much of today’s enterprise AI effort is similar. It asks: “How can we do the same thing with fewer people, faster?” That is not nothing. But it is rarely transformational. The real value arrives only when the workflow is rebuilt around the new capability.

With the introduction of the assembly line, a factory was not simply a workshop with more workers inside it. It was a new production architecture: power, sequencing, specialization, supervision, inventory, distribution, and capital intensity reorganized around machines. Likewise, AI will not create durable enterprise value merely by letting existing employees draft emails faster or summarize meetings more cheaply. The value comes when firms redesign the unit of work itself.

I’m fortunate that my work puts me in contact with younger, thoughtful individuals who have enough domain-specific knowledge in their industry to start this process. They are having tremendous success. In my own work, AI tools have transformed my ability to rapidly build agent-based models to simulate the behavior of individual stocks in an index, enhancing my insights on passive investing more in the last nine months than in the prior nine years. But it could not have been done without the knowledge accumulated over those prior nine years (and the ~25 years of work in financial markets that preceded those).

As a result, I am convinced we are cresting the peak of inflated expectations and shifting to the trough of disillusionment:

The question is no longer whether AI is useful. It is. The question is who funds the enormous gap between subsidized consumer usefulness, slow enterprise reinvention, and the capital intensity required to build the infrastructure. Increasingly, the answer appears to be: “public equity investors.” And this is occurring just as the (Air) Supply is shifting. It’s no longer just about new IPOs:

Read more

And then I read the comments. While I typically avoid this exercise (“Don’t read the comments!” is sage advice from any public speaker), when I am introducing new concepts (e.g. “buy bonds, you fools” [not investment advice]), I do check them because it helps me understand what examples/analogies “work” and which do not, as well as where the audience is completely missing the point I am trying (often inelegantly) to make. Clearly, this new shtick needs some work:

And those were the kind ones. Some were a bit more personalized:

If anyone knows where my “paid off” check went, I’d appreciate the insight. I post these not because I want your sympathy, but rather to illustrate a different point. I learned long ago that presenting facts does not change perspectives except at the margin. Facts do not break identity. They threaten it. And when identity is threatened, the mind does not ask, “Is this true?” It asks, “What must I believe to remain myself?” A good example is the 2018 documentary, “Behind the Curve”:

From Wikipedia: The 2018 documentary Behind the Curve followed two groups of American Flat Earth believers who were attempting to gather first-hand empirical proof for that belief. One group from the YouTube show GlobeBusters used a ring laser gyroscope in an attempt to show that Earth was not rotating. Instead, they detected the actual 15-degree-per-hour rotation of Earth, a measurement they dismissed as corrupted by the device somehow picking up the rotation of the "firmament". Another group used lasers in an attempt to show a several-mile stretch of water is perfectly flat by measuring the distance between the water level and the laser beam along three vertical posts. They were unable to align the beam as they expected to because the surface of the still water was in fact bent by several feet over the distance measured; the experiment was dismissed as inconclusive.

What we are largely seeing in these comments is “identity politics.” The most popular tribe in the Western World is currently the “I do not trust the government” tribe. And it’s a useful exercise to ask yourself, “Do I object to the data because I can prove it’s wrong or do I object to the data because it challenges my world view/identity?” I am finding the “understated inflation” story to be the latter.

I want to be perfectly clear — I cannot PROVE that the government is not lying to you about inflation. I can DEMONSTRATE to you that private researchers tracking inflation find that government-reported inflation is overstated:

Read more

There’s lots of nonsense chatter that “we need higher rates”:

Readers of YIGAF should know by now that I will NEVER show a chart and say, “Maybe it should be the average of previous cycles.” Among other issues, define “previous cycles”? I would guess most of my readers have not thought to update this popular chart from a decade ago:

The evidence that rates are restrictive is painfully clear to anyone looking beyond the equity market into the real world of “financed products”:

We can run an analysis on the “neutral” mortgage rate that would get population adjusted sales of housing “back to normal.” Suffice it to say, it’s much lower:

And yet, nobody seems to care. I was at an institutional investment conference on Tuesday, speaking to some of the largest institutional allocators. I pointed out the surge in rates we’ve experienced and asked the room, “How many of you have increased your allocation to sovereign debt?”

Not one hand went up of roughly 500 in attendance.

The same day, a headline from Bloomberg caught my eye — finally, people are beginning to notice this is not a “US story” and recognizing that “something deeper is in play”:

Now the article itself is the typical nonsense — “equities seem impervious” while “bonds hit levels not seen since 2000” and “we have too much debt.” Readers of YIGAF know how I feel about this:

“Maybe I don't want to spend my life sittin' around and explaining shit to people.” — Good Will Hunting

And then the Stones remind me of the simple truth:

You can't always get what you want
But if you try sometime, you'll find
You get what you need

So I felt compelled to dash off a message to our Treasury Secretary.

Attached is my open letter to the US Treasury Secretary explaining exactly what is happening to the US Treasury market and exactly what I think we should do about it — the Sovereign Debt Optimization Facility (SDOF). I have no idea if we’ll do this, but I think it’s about as coherent a plan with as few downsides as humanly possible. I have no idea why we WOULDN’T do this.

For those who want the “Explain it Like I’m a Golden Retriever” version:

• The Problem: When interest rates were almost zero, the U.S. issued trillions in long-term bonds and mortgage bonds paying tiny interest (0–2.25%). Now rates are higher, those old bonds are worth only about 55–75 cents on the dollar. Big banks hold roughly $1 trillion of them and can’t sell these positions without triggering huge losses that would freeze their ability to lend money. As a result, capital is “frozen” in the banking system.

• Why It’s Dangerous: Giant “passive” bond index funds automatically make things worse. When bond prices fall, they buy less of the long bonds exactly when the market needs buyers — creating scary feedback loops that can spike rates and crash markets (like the U.K. in 2022, but much bigger).

• The SDOF: Keep an emergency “swap program” on the shelf. When a real crisis hits (and we’re very close now), the Treasury would allow banks to voluntarily exchange their old, low-price bonds for new Treasury bonds at today’s fair market price. No new cash is printed — it’s an even swap of value for value. See the duration-weight math below.

• How the Swap Works: A bank hands over $100 of old bond (now worth $65) and gets $65 of new bond. The bank’s balance sheet heals, and it can start lending again. The government pays a little more interest each year but owes $35 less principal later.

• Big Benefits: Could lower long-term rates and mortgage rates by 0.4%–0.9%, helping homebuyers and the whole economy. It breaks the dangerous loop without bailing anyone out.

So without further ado, let’s SDOF our caps as the midshipmen did under rainy skies this week:

May 21, 2026

An Open Letter to the Secretary of the Treasury:

A Contingent Playbook for the Sovereign Debt Architecture

Michael W. Green, Chief Strategist, Simplify Asset Management | www.yesigiveafig.com

I. Executive Summary: The Structural Fault Lines

Mr. Secretary,

The modern financial architecture is increasingly defined by structural inelasticities that impair monetary transmission and threaten orderly price discovery. Three intersecting phenomena drive this friction: (1) a multi-trillion-dollar overhang of legacy low-coupon sovereign debt — and crucially, Agency MBS and Agency multifamily MBS/CMBS — trading at severe market discounts; (2) an acute asset-liability lock within the regulated commercial banking system; and (3) a hollowing-out of active market liquidity and fundamental price discovery. These stresses are fundamentally intensified by a massive, underappreciated structural blind spot in contemporary capital markets: the unyielding rise of passive indexing within fixed-income portfolios. While standard academic literature has treated passive aggregation largely as a phenomenon isolated to equity markets, its scale and mechanical structure inside debt portfolios create severe, non-discretionary volatility loops that directly fracture the sovereign transmission mechanism and the “information” available to a sovereign debt issuer.

During the near-zero-rate and zero-rate environment of 2010–2021, the United States Treasury and other sovereigns issued an unprecedented volume of long-duration obligations carrying coupons between 0% and 2.25%. In the aftermath of the Covid re-opening inflation shock, central banks globally raised policy rates rapidly. As real yields adjusted upward, the market value of these off-the-run vintage bonds collapsed, with many trading between 55 and 75 cents on the dollar.

Aggregate commercial bank unrealized securities losses (across both Held-to-Maturity and Available-for-Sale portfolios) stood at $306.1 billion at the end of 2025[1]. However, as of mid-May 2026, the current bond market selloff has accelerated aggressively, pushing the 10-year yield to 4.61%–4.67% and the 30-year yield to a cycle peak of 5.14%–5.18%[2], driving these accounting impairments back toward critical thresholds and severely widening off-the-run liquidity fragmentation.

Empirical data reveals the concentration of this paralysis: the three largest HTM holders — Bank of America ($497B), JPMorgan Chase ($334B), and Wells Fargo ($237B) — account for approximately $1.07 trillion, representing roughly 88% of the expanded target universe (inclusive of Agency MBS/CMBS)[3]. Their portfolios are uniformly dominated by Agency MBS with blended book yields of 1.66%–2.22%, generating an aggregate unrealized HTM loss of nearly $146 billion for these three institutions alone.

Under prevailing accounting standards (ASC 320)[4], commercial banks holding these instruments within Held-to-Maturity portfolios cannot liquidate to reallocate capital without triggering a “tainting” violation. Such a violation forces reclassification of the entire HTM book to Available-for-Sale, with mark-to-market impairments flowing through Accumulated Other Comprehensive Income; for Category I and II institutions (including each of the three named banks above), that flow-through reaches Common Equity Tier 1 capital directly[5]. Trillions of dollars of risk-bearing capacity therefore remain structurally frozen.

This memorandum establishes a comprehensive, contingent policy framework to defuse these vulnerabilities and reinvigorate the potential for private credit creation while directly reducing the term premium that has emerged: the Sovereign Debt Optimization Facility (SDOF).

The SDOF is not a peacetime debt management tool, nor is it proposed for prophylactic deployment. Pre-emptive intervention under normalized market conditions carries severe and asymmetric signaling, term-premium, and moral-hazard costs that compromise expected value. Instead, the SDOF is engineered as a “next-level” emergency playbook built upon the routine liquidity-support and cash-management buyback operations institutionalized by the Department since May 2024[6]. While the existing program provides critical operational precedent — scaling up to an anticipated $38 billion in off-the-run liquidity-support purchases and up to $75 billion in short-term cash-management buybacks per quarter by early 2026[7] — the SDOF represents an order-of-magnitude systemic escalation. It is maintained in operational readiness, to be deployed only upon defined quantitative trigger conditions, to absorb acute long-end dislocations before they propagate into broader portfolio-mechanics cascades.

Within a total marketable Treasury debt landscape of approximately $30.7 trillion[8], the targeted tranche is highly material for systemic liquidity without being structurally dominant.

II. Trigger Conditions and Quantitative Dashboard

Because of asymmetric reserve-currency and term-premium reflexivity risks, the SDOF is held in reserve as a rule-governed, contingent instrument. Under normalized market conditions, its deployment would damage Treasury issuance credibility. Under acute systemic dislocation, however, the asymmetric payoff inverts, and non-deployment becomes the higher-variance choice. The current market stress appears to be rapidly approaching these red-threshold conditions; the final determination as to whether the threshold breach qualifies rests with the Department.

1. The Liquidation Loop Trigger Scenario

The trigger scenario is a self-reinforcing long-end sell-off in which falling bond prices drive systematic and rebalancing flows, destabilizing the system. As fixed-income assets suffer mark-to-market drawdowns, multi-asset systematic strategies (Target Date Funds, 60/40, risk-parity, etc.) are mechanically forced to liquidate equities to rebalance bond sleeves. Concurrently, leveraged liability-driven investment (LDI) pools, basis traders, and pension margin programs hit thresholds requiring liquidation of their most liquid assets — including off-the-run Treasuries and Agency MBS — into the same market weakness.

The rebalancing flows designed to stabilize the system become destabilizing. Liquidity provision breaks down, and equity-bond correlations converge toward unity. The September 2022 United Kingdom gilts episode is the canonical recent template, scaled to the United States Treasury market[9].

2. The Fixed-Income Index Duration Engine: An Academic Blind Spot

Contemporary market macrostructure literature remains heavily equity-centric, exploring how passive vehicles skew stock valuations while leaving fixed-income dynamics entirely unaddressed[10]. This omission is critical: passive bond indices do not operate like equity indices. Because market-capitalization-weighted fixed-income portfolios price their components continuously, passive flows are mechanically forced to buy more duration when yields are low (and prices are high) and less duration when yields spike (and prices collapse).

This dynamic operates as the exact pro-cyclical mirror image of traditional Asset-Liability Management. In a strict ALM framework, raising policy rates collapses the present value of future liabilities while expanding cash income from floating-rate assets; the institution’s net structural deficit shrinks and its required investment duration falls. Conversely, the passive bond index has no liability duration to match — it reduces its long-duration buying simply because long bonds have become cheap and their market-cap weight has fallen.

Crucially, the current May 2026 bond market selloff is actively weakening the passive bid for duration. To illustrate the raw mathematical reality of this structural distortion under current conditions, consider a simplified two-bond index composed of a 2-year and a 30-year maturity bucket (assuming an index aggregate consisting of 10 bonds of $1,000 face value each, representing a nominal block value of $10,000 per maturity bucket) issued with identical initial 3% coupons:

A 50/50 weight index with each $1 inflow buying ~12.17 units of effective duration. Now the Fed cuts rates:

Due to price appreciation and the resultant 54.56% concentration in the 30-year slot, a marginal $1,000 capital inflow is now mechanically allocated to purchase 13.92 units of duration — a structural step-up in duration exposure at lower yields, i.e. momentum investing in bonds.

And now the Fed hikes rates aggressively:

With the 30-year bond trading down to $692.55 per bond, its index weight collapses to 41.84%. A marginal $1,000 capital inflow now purchases only 9.24 units of duration — a 33.6% reduction in duration purchasing power relative to Stage 2.

Methodological note: Duration purchasing power is defined as the one-sided down-shock effective duration (D-eff) acquired by a marginal $1,000 inflow, weighted by market-value composition. Effective duration is computed as (P₋ − P₀) / (P₀ × Δy) for a 100 bp downward shock from each stage’s prevailing yield. Because positive convexity is asymmetric, this measure runs systematically higher than modified duration; it is the appropriate metric for capturing the asymmetric price response that drives the pro-cyclical loop. The 33.6% reduction in marginal duration absorption from Stage 2 to Stage 3 demonstrates that the index aggressively buys duration when it is expensive and systematically starves the sovereign long end of structural demand when it is cheap and dislocated.

By converting marginal inflows into minimal duration support precisely when a sell-off accelerates, the engine amplifies long-end yield spikes and forces the onset of systematic liquidation loops. Treasury’s recent strategy of starving the market of long duration by funding at the front end mitigates this in the short term, but leaves the underlying structural vacuum unresolved.

III. Facility Mechanics and Fiscal Optics

The SDOF operates on strict corporate-finance principles. Day-one risk parameters remain equalized across the system while cash-flow composition is restructured to repair institutional balance sheets and restore monetary transmission.

1. Voluntary Tender Exchange and Expanded Asset Inclusion

Rather than utilizing a coercive framework that invites soft-default concerns, the SDOF is structured as a voluntary tender exchange supported by a pre-cleared HTM accounting safe harbor.

The target universe formally accepts both Treasury obligations and Agency MBS/CMBS. Treasury does not issue Agency MBS; Fannie Mae and Freddie Mac securities are government-sponsored enterprise (GSE) obligations issued under federal conservatorship, supported by Treasury’s Senior Preferred Stock Purchase Agreements, and treated by markets as high-quality government-supported mortgage credit. Accepting these instruments in exchange for Treasury bonds of equivalent duration isolates the interest-rate risk without altering the sovereign credit profile. With the three largest banks holding nearly $1 trillion in Agency MBS at deep discounts, this expansion is necessary to truly unlock the HTM paralysis.

Under acute red-threshold stress, voluntary tender uptake is realistically estimated to range between 60% and 85% of the targeted institutional par universe. To overcome the collective-action problem — the prisoner’s dilemma in which banks wait for others to tender to reap the systemic benefits — the SDOF employs a First-Mover Incentive: early participants receive operational priority, settlement certainty, and a modestly more favorable exchange ratio (e.g., 66 cents rather than 65 cents on the dollar), marginally increasing Treasury’s cost but substantially guaranteeing coordination.

2. Blunt Assessment of Fiscal Optics

The transaction is settlement-cash-neutral: Treasury does not raise new net cash from the market at inception, but exchanges market value for market value. It is explicitly not cash-flow-neutral over time. The facility converts a portion of future principal obligations into current coupon expenses.

For ease of exposition, the macro calculations below use a full-universe engagement case: $650 billion legacy par exchanged at a blended market price of 65 cents on the dollar, establishing an aggregate market value of $422.5 billion. Treasury issues exactly $422.5 billion of new, on-the-run 30-year bonds at current market yields at par (100 cents).

On the illustrative assumptions of this framework (mirroring Bank of America’s 1.66% HTM book yield as the lower bound and 5.2% as the new-issue coupon), the math reflects the following profile:

• Legacy interest outlay: $650B par × 1.75% blended coupon ≈ $11.4 billion annually.

• Optimized interest outlay: $422.5B new par × 5.2% coupon ≈ $22.0 billion annually.

• Annual cash interest expense delta: +$10.6 billion.

• Headline principal reduction at maturity: $650B − $422.5B = $227.5 billion.

The public-finance case therefore rests entirely on systemic stabilization, monetary transmission, and liquidity restoration — not on deficit reduction. This is standard liability management: swapping long-term capital claims for immediate liquidity stabilization to prevent a systemic market failure that would cost the fiscal authority vastly more.

IV. Accounting and Legal Authority

The central implementation hurdle of the SDOF is the regulatory bridge across ASC 320. Surrendering legacy Agency MBS or Treasuries in exchange for new current-coupon Treasury bonds constitutes a sale under current GAAP, triggering tainting regardless of systemic purpose[11]. To enable bank participation without triggering systemic capital impairment, the SDOF requires pre-authorized, system-wide accounting treatment. Three pathways are ordered below by execution credibility.

Pathway 1 — Substance Over Form (Cleanest Margin)

The economic substance is a modification of terms on the same sovereign credit, not a market exit. FASB codifies a principle through which an exchange that is (a) issued by the same sovereign obligor or conservatorship, (b) of equivalent credit quality, (c) executed under a government-directed financial stability program, and (d) immediately re-classified as HTM does not constitute a sale for ASC 320 purposes. This pathway requires FASB to issue an interpretive update through its standard process.

Pathway 2 — Federal Banking Agency Interagency Capital Guidance

Separately and in parallel, the federal banking agencies (FRB, OCC, FDIC) can issue interagency guidance on regulatory capital treatment that effectively neutralizes the GAAP consequence for capital adequacy purposes — without changing the underlying accounting. This is the more realistic near-term route, as it is squarely within existing supervisory authority and does not require FASB action.

Pathway 3 — New Sovereign Exchange Safe Harbor

FASB adds a seventh safe harbor to ASC 320-10-25 specifically for government-directed sovereign instrument exchanges, tightly circumscribed with mandatory re-classification. This is the most durable solution but the slowest to implement.

The AOCI Carry-Forward and Forbearance Mechanics

The facility must be described honestly: it is not loss forgiveness, but a pre-authorized, system-wide loss-recognition bridge. To satisfy FASB’s investor-protection mandate, the accounting treatment mirrors existing AFS-to-HTM transfer mechanics under ASC 320-10-35-10(d). The unrealized loss on the surrendered security is carried forward in AOCI (MWG note for readers— Accumulated Other Comprehensive Income — a line on the equity section of a bank's balance sheet that captures certain unrealized gains and losses that bypass the income statement) and amortized straight-line through earnings over the remaining life of the new instrument.

For a standard institution tendering a $100 million legacy par block, the balance sheet transitions under the preferred safe harbor as follows:

The $35 million unrecognized loss does not disappear from the ledger. It is reclassified into the AOCI carry-forward account and amortized straight-line through earnings over the 30-year life of the new security ($35M ÷ 30 ≈ $1.17M per year). Gross coupon income expands from $1.75M to $3.38M; deferred-loss amortization of ~$1.17M reduces net income to approximately $2.21M, resulting in a true incremental uplift of roughly $460,000 per $100 million of legacy par block relative to the prior baseline. Required AOCI disclosures ensure the economic substance of the permanent reduction in principal recovery remains fully visible to market participants.

V. Multi-Asset Transmission Channels

1. Convexity Squeeze and Curve Compression

Because the exchange converts $100 of old par into $65 of new par, the relevant duration comparison must be evaluated on an original-par-equivalent basis. The aggregate DV01 risk is permanently extracted from the market scales according to institutional participation thresholds. Drawing on historical Federal Reserve Operation Twist precedents and the foundational banking-intermediary transmission literature[12], the resulting compression in long-end term premium falls within a range of 15 to 50 basis points on the 10-year benchmark under upper-bound participation.

Insurance companies and pension funds are excluded from the primary target parameters, but for different reasons than banks. U.S. life insurance companies report primarily under NAIC statutory accounting, which carries most fixed-income holdings at amortized cost — functionally analogous to HTM and therefore not subject to the same market-value capital pressure. Defined-benefit pension funds, meanwhile, have liability-duration matching requirements that make them likely to actively resist an exchange that shortens portfolio duration. Calibrating their specific ALM resistance levels is material to confirming the 15–50 bp compression estimate.

2. Mortgage Market Transmission

The retail mortgage market provides the primary consumer-facing transmission channel. As of mid-May 2026, Freddie Mac’s official PMMS showed the 30-year fixed rate at 6.36% as of May 14[13], while higher-frequency market surveys placed top-tier 30-year fixed rates closer to 6.49%–6.68% by May 18[14], tracking multi-month highs alongside structural long-end volatility. The SDOF impacts mortgage rates through two channels: the Duration Channel (15–50 bps via long-end term-premium compression) and the Capital Channel (25–40 bps via bank balance-sheet relief that compresses primary-secondary MBS spreads).

VI. Risk Controls and Boundary Setting

1. Federal Reserve Coordination

The SDOF operates directly in the Treasury market. A $422 billion duration extraction is functionally equivalent to an Operation Twist in its market effect. If the Federal Reserve simultaneously sells long-end Treasuries (Quantitative Tightening) while Treasury is attempting to swap them, the uncoordinated QT could nullify the term-premium compression entirely. A formal Fed-Treasury coordination annex, analogous to the 2020 emergency facility framework, is a prerequisite for deployment.

2. Sovereign Signaling and Foreign Holders

Foreign holders collectively own approximately $8–9 trillion in U.S. Treasuries, of which the foreign-official segment (central banks and sovereign wealth funds) accounts for roughly half. A sovereign-directed structural exchange, even if domestically targeted, could be interpreted as evidence that the United States is willing to manage obligations through structural modification rather than full market redemption. The penalty is mitigated by a dedicated foreign-holder communication strategy explicitly defending why the SDOF does not constitute a soft restructuring — voluntary tender, fair-value-neutral pricing, and preserved contractual integrity for non-participants — thereby protecting the reserve-currency premium.

3. Rate-Path Dependency

Present-value neutrality is structurally true at current discount rates, but it is rate-path dependent. A 100 basis point increase in long-end yields following SDOF deployment would immediately create a new cohort of discounted 30-year Treasuries. Constant sensitivity analysis stress-testing the NPV neutrality across renewed rate-rise environments must be maintained.

VII. Post-Deployment Distributional Audit

To maintain transparency and defend the facility against the narrative of an unearned institutional subsidy, Treasury should implement an objective post-deployment audit framework. The audit will track the functional integrity of baseline deposit-competition rails to ensure the expanded coupon income is shared between institutional capital rebuild and depositor return.

Where these rails are operational, they act as the primary line of defense to narrow the deposit gap. Where the diagnostic data identifies a persistent, structural failure of these competitive rails — or institutional hoarding of the SDOF coupon expansion — Treasury will utilize a graduated escalation path, moving from targeted public disclosures to the operational activation of the competitive backstop detailed in Appendix B.

VIII. Objections and Responses

Objection 1: This facility represents a taxpayer-funded bailout for banks that mismanaged duration risk.

Response: The SDOF does not provide financial extraction above market pricing. Banks tender assets at a deep, market-validated discount (e.g., 65 cents on the dollar) and receive new par paper matching that exact market value one-for-one. The transaction is fair-value neutral at inception; no losses are erased, and long-term terminal principal claims are permanently reduced. The required AOCI disclosures ensure the economic substance of the permanent reduction in principal recovery remains fully visible. The subsidy that does exist is the regulatory accommodation itself — the safe harbor against tainting — which should be named directly rather than denied. Its justification is systemic, not institutional.

Objection 2: Treasury is increasing near-term cash interest expenses during a period of fiscal deficit strain.

Response: The near-term cash-coupon service expansion (+$10.6 billion annually in the illustrative baseline) is counterbalanced by a structural reduction of $227.5 billion in terminal principal obligations. The arrangement represents standard liability management: swapping long-term capital claims for immediate liquidity stabilization to prevent a systemic market failure that would cost the fiscal authority vastly more in lost tax base, emergency facility deployment, and reserve-currency erosion.

Objection 3: Why not allow market discipline to work by letting under-capitalized or duration-trapped institutions fail?

Response: Allowing systemic liquidation loops to fracture the sovereign transmission architecture in the name of ex-post discipline creates extreme, uncompensated systemic variance. The underlying assets are United States sovereign obligations and Agency MBS — not impaired private credit ledger items. The balance-sheet freeze is an artifact of regulatory accounting rules (ASC 320) interacting with an unprecedented macro duration shock, not a default-risk insolvency.

IX. Concluding Disposition

By maintaining the Sovereign Debt Optimization Facility as a contingent, defined-trigger instrument, the Treasury preserves its policy capital, inoculates the institution against political and moral-hazard critiques, and remains fully prepared to stabilize the global financial architecture at the moment market-structure fragility breaks.

The facility’s success is not measured by maximum benefit to any single class of participant. It is measured by the restoration of orderly monetary transmission, the equitable distribution of benefits between institutional capital rebuild and broad public welfare, and the preservation of confidence in United States sovereign issuance.

The playbook is nearly complete. The accounting bridge is the remaining critical item. To compress activation from days to hours, the legal parameters must be pre-authorized. Once the liquidation loop begins, design time will have expired.

Appendix A — Illustrative DV01 Mathematics

The target universe comprises specific off-the-run Treasury obligations issued between Q2 2020 and Q4 2021 with maturities ranging from 2050 to 2051, plus eligible Agency MBS/CMBS vintages issued under near-zero-rate underwriting conditions. The mathematical extraction of DV01 is defined by the structural shift from deep-discount long bonds to par-value current-coupon obligations.

On a static-yield basis, duration compression reduces the portfolio’s sensitivity to parallel rate shifts and flattens the convexity profile, thereby reducing the systematic hedging requirements that primary dealers must absorb during a market rout. Per $100 million legacy par tendered: an old 1.75%-coupon, 25-year-remaining bond priced near $65 (book yield ~5%, effective duration ~19.3 years) carries a DV01 of approximately $125,700; the replacement $65 million of new 5.2% par 30-year bond (effective duration ~15.4 years) carries a DV01 of approximately $100,000. Net duration extraction per $100M old par is on the order of $25,700 per basis point, or approximately 20% of the original DV01 exposure. Scaled to $650 billion legacy par at 65% participation, the aggregate DV01 extraction is on the order of $108 million per basis point. (MWG Note: For readers interested in understanding this exposure more deeply, please refer to my great friend Harley Bassman’s latest note where he highlights the growing risk of the “Convexity Beast”)

Appendix B — Competitive Deposit Rails as a Post-Crisis Distributional Backstop

To ensure a credible deterrent against margin hoarding, Treasury should commence a parallel, long-term workstream to develop a digital sovereign savings platform utilizing the United States Postal Service network infrastructure.

To optimize execution efficiency and eliminate bureaucratic expansion, the frontend interface and backend clearing ledger are structured for competitive open bidding to private financial-technology and banking consortia. Standing up this deployment-ready infrastructure requires a parallel 18-to-36-month implementation timeline, encompassing procurement cycles, USPS operational integration, KYC/AML compliance buildouts, identity verification at scale, and FedNow rail integration. This framework requires navigating either targeted legislative authorization modeled on the historical Postal Savings System or an expansion of emergency statutory authorities under Treasury–Federal Reserve fiscal-agency mandates.

To insulate the regional and community banking sectors from destabilizing wholesale disintermediation, individual balances within this facility are strictly capped at the historical pre-2008 FDIC limit of $100,000. While accounts below this threshold constitute the numerical majority of domestic retail depositors, they represent a minority of aggregate system dollars. Quantitative modeling indicates full-scale activation would plausibly migrate 5% to 10% of the total domestic deposit base. This magnitude is precisely calibrated to establish an effective competitive price-setting mechanism for retail savings without impairing the baseline solvency or credit-extension capacity of the traditional banking ledger.

End Notes

[1]Federal Deposit Insurance Corporation, Quarterly Banking Profile, Fourth Quarter 2025 (Washington, D.C.: FDIC, February 2026). Total unrealized losses on held-to-maturity and available-for-sale securities portfolios declined $31.0 billion to $306.1 billion, the lowest level since Q1 2022.

[2]U.S. Department of the Treasury, Daily Treasury Par Yield Curve Rates, reporting cycle May 18–19, 2026. 10-year constant-maturity yield: 4.61% (May 18) / 4.67% (May 19); 30-year constant-maturity yield: 5.14% (May 18) / 5.18% (May 19), per Federal Reserve H.15 release.

[3]SEC EDGAR XBRL filings, 2024 Form 10-K and Q4 2024 earnings supplements for Bank of America Corporation, JPMorgan Chase & Co., and Wells Fargo & Company. HTM portfolio carrying values aggregated to disclosed securities footnotes.

[4]Financial Accounting Standards Board, Accounting Standards Codification Topic 320, Investments—Debt Securities, particularly ASC 320-10-25-9 through -14 governing classification and the consequences of sale or transfer out of the held-to-maturity category.

[5]FDIC Supervisory Appeals Review Committee Decision, 2024, addressing regulatory capital consequences of HTM portfolio reclassification under interagency capital rules (12 CFR Part 217 for the Federal Reserve; analogous provisions for OCC and FDIC). For Category I and II institutions, AOCI flows through regulatory capital; the AOCI opt-out remains available for Category III and IV institutions pending Basel III endgame finalization.

[6]U.S. Department of the Treasury, May 2024 Quarterly Refunding Statement, formally introducing regular liability-management and cash-management buyback operations.

[7]U.S. Department of the Treasury, February 2026 Quarterly Refunding Statement, detailing scheduled expansion to approximately $38 billion in off-the-run liquidity-support purchases and up to $75 billion in short-term cash-management buybacks per quarter.

[8]Federal Reserve Bank of New York, Treasury Market Data Baseline, Q1 2026; cross-referenced with SIFMA U.S. Treasury Securities Statistics (April 2026), reporting $30.7 trillion in outstanding marketable Treasury debt.

[9]Bank of England, Financial Stability Report, December 2022. Provides the structural review of LDI-driven liquidation cascades in the September 2022 UK gilts episode—the canonical recent template for sovereign-debt market dysfunction driven by leveraged-portfolio mechanics.

[10]Haddad, V., and Muir, T. (2025), “Market Macrostructure: Institutions and Asset Prices,” National Bureau of Economic Research Working Paper 33434. Documents the rise of passive investing above 40% of the equity market and articulates the structural blind spot in contemporary macro-finance regarding the analogous (and underappreciated) mechanics in fixed income.

[12]Haddad, V., and Sraer, D. (2020), “The Banking View of Bond Risk Premia,” The Journal of Finance, 75(5), 2465–2502. Establishes the empirical link between bank balance-sheet exposure to interest-rate risk and bond risk premia, providing the foundational banking-intermediary transmission framework for term-premium estimation.

[13]Freddie Mac, Primary Mortgage Market Survey, reporting cycle of May 14, 2026; 30-year fixed-rate mortgage benchmark at 6.36%.

[14]Mortgage News Daily and Bankrate higher-frequency survey indices, mid-May 2026; top-tier 30-year fixed rates at 6.49%–6.68% as of May 18, representing multi-month highs alongside structural long-end volatility.

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There's always gonna be another mountain
I'm always gonna wanna make it move
Always gonna be an uphill battle
Sometimes I'm gonna have to lose
Ain't about how fast I get there
Ain't about what's waiting on the other side

“The Climb” by Miley Cyrus

Dave Collum, a remarkably financially numerate Cornell chemistry professor, and someone I consider a “Twitter friend” who actively follows and promotes my work shared a poll on Twitter this past week:

I want to make clear a number of assumptions that Dave outlined later in his responses (but should have been clear from the language):

1. No Social Security or Medicare

2. No children (“just you and your spouse”) to take care of

3. Pre-tax sheltered retirement account (401K or IRA) [so no house, business, etc]

Simultaneously on my screen:

So let’s do some simple math:

At the “crowd weighted average” (ignoring the “or more” on the 25x), the opportunity exists to replace 100% of PRE-TAX income with 30yr nominal treasury bonds simply with interest on that bond. Never touching principal. And since it’s “just you and your spouse” there’s nobody to benefit from that principal, completely intact, at age 95 except (possibly) you and your spouse. Odds you’ll both make it that far? About 5% for affluent (ie 20x) households. 1% for the deplorables.

In the comments, Amy Nixon, a financial commentator, said she’d initially leaned toward 20 times salary and then rolled it back to 15 (where I voted) — her reasoning being that expenses fall off once the kids are through college and the household is two adults again, for meals, for travel, for the ordinary buying of things. You can disagree with the number. But notice what she’s doing: she’s reasoning about spending. Remember your pre-tax income includes money paid for taxes, FICA, etc. And saving to get to that 20x level. Your SPENDING runs about 65% of that pre-tax income. So 20x is 31x your spending.

Dave said 25x. And then he flagged what he called the interesting part: that Fidelity’s website, at one point, said 8x.

An 8x-versus-25x gap is not a curiosity. It is a threefold discrepancy with an important message. Fidelity’s number assumes you draw your principal down over retirement and that Social Security carries a large share of the load. A 25x-of-salary number quietly assumes something completely different: that you live off a withdrawal rate of roughly 3 percent, Social Security is untrustworthy, and never touch the principal at all. Those aren’t competing estimates of the same quantity. They are answers to two different questions. The question Dave is answering is “fear” — and we see it permeating our society:

The older generation’s saving is income NOT received by their children. Dave, admittedly, is saving more because he’s worried about the prospects for his children to adequately provide for THEIR retirement. As I noted to the younger generation in a recent (terrible btw) podcast, their behavior is part of the problem; but the older generation isn’t helping:

At 20x+ (64% of respondents obviously skewed by Dave’s follower orientation), you’re saving 31x your spending. At 65, you could earn 0% and cover spending until 96.

I know what the crowd is shouting — “Inflation! It’s coming, and it’s understated! You can’t buy nominal bonds, you fool!”

And maybe they’re right (I don’t think so). But I’d like you to consider something:

The shift from Defined Benefit to Defined Contribution, beginning in 1978, shifted the “fear” of providing retirement from the corporate (and public) sector to the household sector. As discussed in my analysis of the Coimbra paper, the shift from COLLECTIVE security to individual security drives an astonishing outward shift in aggregate demand for financial assets:

While Coimbra doesn’t specify the fraction of Type-A (spenders) and Type-B (savers), the aggregate results for the paper suggest roughly 50/50. If we reverse solve for the drivers of the increase in Financial Assets/Income, we get these rough ranges:

The aging of the society that has occurred since 1978 would have driven expected financial asset/income ratio higher by 0.7-1.5x — roughly 1/8 to 1/4 of the amount we’ve seen. Between 60% and 99% (conjoint lower and upper ranges) is due to the shift to DC and an increase in valuation (a combination of shift to passive and increased aggregate demand), or (and this is an important point) the decline in labor share of the economy. The NY Fed has recently written that labor share appears to play an important role in setting real rates:

And as my readers know, I believe the evidence strongly supports this conclusion:

Why does this relationship exist? Because the production frontier in economics ASSUMES a capital/labor ratio. With fast labor force growth, the demand for capital must rise to maintain the capital/labor ratio, driving real rates higher. THIS was the story of the 1970s — an explosion of domestic labor created a large outward shift in aggregate demand both for consumption AND capital:

And so today, with labor force growth expected to be negligible, real rates SHOULD be lower.

But they’re not:

Now we have multiple solutions to this conundrum. Possible solutions:

1. The market is brilliantly telling us that the US government is lying about inflation

2. The market is stupid and real rates are going much higher because (pick A/B/C) — the theoretical models are stupid as well. It’s different this time.

3. The market is stupid because mechanical features are driving neglect of bonds in portfolios that mechanically buy in proportion to market capitalization of bonds and an age-based allocation to assets that ignores reasonable expected returns.

We can evaluate #1 and #3. #2 is simply expectations. Ewe have one. So does everyone else. I’d urge you to consider what’s special about yours.

On #1, the “government is lying”, many like to roll out the chart on UMich inflation expectations where the “mean” has soared. Unfortunately, this is due to outliers amplified by the 2023 switch from phone to internet surveys. On the internet, nobody knows you’re a conspiracy theorist, dawg. The median expectation is 3.1% — slightly elevated, but far from 1981 levels:

We’ll always have ShadowStats, but legitimate PRIVATE sector peers to the CPI suggest the BLS is OVERSTATING inflation by about 1.5%. Please ask yourself, “What incentive does Truflation have to lie?” I can assure you, their business model is better served by suggesting the opposite:

You can also ask yourself, “What incentive does Mike Green have to lie to me?” Well, obviously, I’m just an active manager trying to hold on to my fiat power base as I type away on Sunday morning. (We are legion in case you’re wondering)

The data does not suggest the BLS is “lying to you” — and as many have noted, never assume conspiracy when incompetence will suffice. And there is plenty of evidence of incompetence (mostly from my barber, but also at the BLS):

As I noted, #2 is “Like, just your opinion, man…” so let’s take a look at number three — mechanical:

I cannot emphasize this enough—we KNOW this is true. It’s been confirmed by passive bond funds to the US Treasury. We also know what happened to small cap value stocks in 1999 when improperly constructed market cap wtd indices ignored float and overweighted new IPOs vs depressed value stocks:

Do ewe see what I see?

So I’ll leave you with this observation — as of May 18, 2026, you’ll have the opportunity to sell your other financial assets and buy 30yr US treasuries at a level of income replacement unmatched except for the four years of Volcker rates 1979-1982:

You don’t need to care about my “real rates argument” — you don’t need the capital gains, and your principal is protected in nominal terms. Again, at 5% and 20x you’re never touching principal. You’re starting out your retirement with income 1.5x your current spending. You’ll ADD to principal. At 10x (America's average), even with Social Security cut by 25%, most will also never touch the principal. Will you do it? Almost certainly not. Because we’re sheep. And the lone sheep is prey for the wolf.

“Worldly wisdom teaches that it is better for reputation to fail conventionally than to succeed unconventionally.” — Keynes

But that’s not the question, really. The question is, when are OTHERS going to come to the conclusion that the future might not be driven by an overtly manipulated SpaceX IPO at 100x revenue, but rather by bonds? The “Keynesian Beauty Contest”:

. . . in which the competitors have to pick out the six prettiest faces from 100 photographs, the prize being awarded to the competitor whose choice most nearly corresponds to the average preferences of the competitors as a whole: so that each competitor has to pick, not those faces that he himself finds prettiest, but those that he thinks likeliest to catch the fancy of the other competitors, all of whom are looking at the problem from the same point of view . . . We have reached the third degree where we devote our intelligences to anticipating what average opinion expects the average opinion to be. And there are some, I believe, who practice the fourth, fifth, and higher degrees.

And just remember, that rising multiple of financial assets to income has an expiry date based on demographics. If equity valuations begin to retreat as Boomers decumulate, it will fall faster (note my work suggests somewhere between 2030 and 2035 is when passive makes this all moot):

Your call, America. My hunch is that you’ll go with the IPO and emerge shaken, not stirred.

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Cap-weighted passive investing, when it gets large enough relative to the active capital on the other side, should leave a measurable trace in returns. Not because index funds are bad, or because low fees are wrong (although I think we’ve lost perspective when discussing a fee cut from 3 to 2 bps as “largest ever”), or even because people buying them are making a mistake. The argument is the societal risk created by a growing mechanical bid. Every dollar that enters a cap-weighted index fund is distributed by existing market capitalization. Bigger companies get more of every dollar. If the dollar volume gets large enough and the active investors who would normally arbitrage that flow become small enough, the rule itself starts to move prices.

The fair objection has always been, “Show me.”

I’m about to release a white paper that I believe does this.

The trend above is the heart of it. Let me walk you through what you are looking at, because the argument is more measurement than opinion.

The simple question

We are all well aware that large stocks have outperformed small stocks for the last few decades. But inside groups of similarly sized companies, are the largest companies increasingly outperforming the smaller ones?

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• S&P 500 Rule Changes: The S&P 500 is removing long-standing profitability requirements — the “enshittification” of the index. This change potentially turns the index into a “dumping ground” for Private Equity to offload unprofitable, highly leveraged companies onto retail index investors.

• The Iran “Blockade”: While the Trump administration claims the war has “terminated” to avoid Congressional authorization deadlines, the strategy has shifted from active combat to a long-term blockade. The objective is to bait an Iranian breakout while consequences include sustained higher oil prices and a strategic pivot toward advanced nuclear reactors.

• Powell’s “Resistance” Strategy: Jerome Powell’s decision to remain on the Board of Governors after his Chairmanship ends is a calculated act of subterfuge. By encouraging Fed staff to remain “true” to independent, rigorous analysis, he is effectively positioning the staff to resist the incoming Chair, Kevin Warsh.

  ---

Three topics:

1. S&P 500 changes the rules

2. The “war” is over and we won; would be a shame if Iran tries to breakout of the blockade

3. Powell’s continued subterfuge

The S&P Changes the Rules

I’ll write more on this in the coming weeks, as it’s the penultimate act of “enshittification” that has been sweeping the nation, but Dave Nadig is standing by expectantly:

So, as temporary recompense, I offer an ode stolen from the most famous of poems, “Casey at the Bat” by Ernest Thayer:

The outlook wasn’t brilliant for the Retail crowd that day:

The market caps were floating on a Mag7 display.

And then when Nasdaq dropped its guard to let the fast-tracks in,

A pall-like silence fell upon where honest trades had been.

A straggling few cashed out their funds in deep despair.

The rest clung to the S&P to stand as Wall Street’s final test;

They thought, “If Standard & Poor’s stays true, and keeps GAAP intact —

We’d put up even money now against this shameless pact.”

But a whisper swept the bleachers, then a devastating shout:

The S&P had waived the rules to bring the big boys out.

Oh, somewhere in this favored land, the bankers’ smiles are bright;

PE will ring the opening bell, and Wall Street’s hearts are light.

And somewhere brokers celebrate their billionaire’s payout;

But there is no joy for Retail—the S&P sold out.

The S&P500 has indeed “sold out.” By proposing to kill the long-standing “profitability” requirement for the S&P500 (already weakened by the use of operating vs GAAP earnings), the S&P500 has offered itself up as the dumping ground for private equity. We can expect it will soon lead to notable headlines:

BREAKING NEWS — OCTOBER 2026

KKR Champions the ‘Democratization of Alpha’ with $250B Mega-Merger IPO of ‘Schlemiel! Schlimazel! Hasenpfeffer Inc.’, Finally Granting Retail Investors Access to a Next-Gen, AI-Synergized Corn Syrup and Car Mat Ecosystem

In a historic victory for Main Street, everyday investors are no longer barred from participating in the exponential growth trajectory of a bespoke, $500B-leveraged portfolio. IPO proceeds are generously earmarked to reward the visionary private equity sponsors who made this paradigm shift possible.

NEW YORK, NY — In what Wall Street analysts are already dubbing the “philanthropic financial event of the decade,” KKR announced the simultaneous merger and initial public offering of Schlemiel! Schlimazel! Hasenpfeffer Incorporated Technologies! (Ticker: SHIT) at a visionary $250 billion valuation.

For years, everyday retail investors have been tragically locked out of the private markets, forced to watch from the sidelines while institutional elites capitalized on the explosive synergies of disparate, zero-revenue enterprise rollups. Today, that gatekeeping ends.

By seamlessly integrating Schlemiel (a disruptive, pre-profit holistic car mat cleaning rollup), Schlimazel (a legacy high-fructose corn syrup manufacturer currently pivoting to wellness), and Hasenpaffer (a fully AI-enabled AM radio broadcasting network), SHIT has created a totally frictionless, synergistic flywheel. Management notes that consumers can now passively absorb AI-generated radio advertisements for dietary corn syrup while their vehicular floor mats are sanitized—a true omni-channel ecosystem.

“Retail investors have been systematically denied the right to buy into our highest-conviction verticals,” read the S-1 filing. “By merging these three remarkable companies, we are unlocking an unprecedented growth trajectory that the public markets simply haven’t had the privilege to fund until today.”

To achieve this democratization, SHIT will debut with a highly optimized, capital-efficient $500 billion debt load. While critics might point out that these three companies were originally acquired during the zero-interest-rate heyday of 2019 and are actively hemorrhaging cash, KKR’s prospectus brilliantly outlines why this declining profitability actually justifies a staggering premium multiple.

“Negative EBITDA is simply deferred hyper-growth,” the filing explains. “The fact that our operational margins are steadily compressing proves that we are shedding the dead weight of legacy revenue models. Because our current earnings are approaching absolute zero, our growth potential is mathematically infinite. We are pricing the IPO at a highly conservative 4,000x forward-looking hypothetical adjusted r/WSB community-EBITDA.”

In a move that highlights the firm’s commitment to strategic capital reallocation, 100% of the proceeds from the retail IPO will be utilized to pay a massive, one-time special dividend back to KKR. Management emphasized that allowing retail investors to personally shoulder the half-trillion-dollar debt burden of three unrelated, failing businesses is the ultimate form of financial inclusion.

“We did the hard work of leveraging these assets to the absolute brink of systemic failure,” a spokesperson noted. “Now, we are stepping aside so the retail community can enjoy the limitless upside of paying our exit liquidity. Welcome to the future of public equities.”

Analysts anticipate robust demand for shares.

Well, of course, they anticipate robust demand. After all, the analyst recommendations from underwriters should follow closely on the heels of the announcement.

Goldman Stanley Coinbase analyst, Deep Sheth initiated coverage on SHIT:

Initiating Coverage: STRONG BUY on SHIT

This is a masterclass in modern financial engineering. KKR hasn’t just filed an S-1; they’ve penned a love letter to the retail investor, wrapped in a half-trillion-dollar leveraged bow.

The strategic brilliance here cannot be overstated. By pivoting away from archaic, boomer metrics like “revenue,” “profit,” or “solvency,” they have successfully untethered the valuation from earthly constraints. The concept of “deferred hyper-growth” through negative EBITDA is a paradigm shift—why settle for a company that makes money now when you can invest in a company whose earnings are mathematically approaching absolute zero, thereby guaranteeing infinite upside?

Furthermore, the decision to use 100% of the IPO proceeds to pay a special dividend to the sponsors is exactly the kind of robust capital reallocation that signals strong corporate governance. By graciously allowing Main Street to become the exit liquidity, institutional finance is finally breaking down the walls of privilege.

If this flywheel gains any more traction, the AI-generated AM radio ads for wellness corn syrup might just cure inflation.

We expect the management team to further generate liquidity by tokenizing the opportunity for forward sales of the integrated offering through NFT launches of tokenized coupons.

As my friends at Cornhole Capital might say:

‘I didn’t know what to expect.’

‘I don’t know... maybe grown ups?’

The obvious conclusion is that the eventual impact will be a surge of unprofitable mega-caps dumped from PE and VC into the hands of index investors. The S&P500 GAAP EPS, already at risk from hyperscalar overspending and subsequent depreciation, should begin to resemble the Russell 2000:

And you’ll own nothing and be quite happy.

The War is Over and We Won

Hegseth and Joint Chiefs Chair Gen. Dan Caine were peppered with questions about the war against Iran during the budget hearing, where they defended the Trump administration’s $1.5 trillion defense budget. The pair defended the blueprint in the House on Wednesday.

The Pentagon chief again touted the U.S. military campaign in Iran and argued the effort was a resounding success.

Exactly as I forecast /s

Unfortunately, it is not over, of course, but headlines are fading as the blockade strategy replaces “shock and awe” and markets have “healed” (hit all-time highs) on the back of the passive bid. As we noted over at Tier1, we saw the largest inflow of systematic capital into markets ever:

Marines are in place. The USS Gerald Ford has been “relieved” of its extended tour (a pain point for the US Navy). And the clock is ticking. Iran has only a few weeks before its primary asset, oil fields, begin rotting from the corpse. The expected objective of the Trump administration is to bait Iran into an attempted breakout, allowing the administration to begin fighting again, but this time under a self-defense claim.

Iran has lost. I know that’s not the headline, but it’s the truth. Had European allies fallen into line, there was a chance that this would have ended much sooner. Instead, their dithering helped the Iranians fall for the same trap the US South did in the Civil War when they believed “King Cotton” was irreplaceable and European nations would join their side.

I can only hope that the next stage doesn’t require a direct commitment of US troops on the ground, but I am skeptical; my next hope is that the administration sticks to the plan of “no nation building.” Only time will tell.

The mid-term consequences is oil higher for longer; the long-term consequence, as the UAE has demonstrated, is even less influence for OPEC and global oil. Expect many more headlines like this:

Jerome Powell exits… or does he?

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The source, of course, was Avis Car Rental — an AI-enabled transportation company with distributed resources accessible to a highly-educated cohort of high-mobility workers and leisure consumers, uniquely suited to guide the development of society in the 21st century:

Yes, the rental car company. Efficient markets at work. But it did provide me with the opportunity of a very long career:

The broader point is that we are now seeing that which was unthinkable only a few years ago. Another forecast from my passive work that has (unfortunately for markets, but good for my credibility) come true.

Many critics of my work believe I am arguing that “valuation doesn’t matter” in the long-run and they retreat to the safety of their efficient market cathedral. This week we demolish it, because “in the long-run” we’re all dead. And I will not go quietly into that night.

We continue to be in the largest divergence in history between returns and “value.” If this week taught us anything, it’s to strap in — there’s a wild ride ahead.

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You have likely seen the confusing headlines:

Got it? Perfectly clear. To help you understand this complex topic, we bring you Samuel Jackson:

What?

“Iran” no longer exists as a unified political voice. The IRGC, the National Security Council, and the diplomatic class are arguing publicly:

“Following the unexpected tweet from the Foreign Minister about the liberation of the Strait of Hormuz, Iranian society has been plunged into an atmosphere of confusion.”
They also directly called out the “absolute silence” of the Supreme National Security Council and the negotiating team, demanding explanations so the “narrative of the enemy” doesn’t fill the vacuum. — Fars News Agency (IRGC outlet)

“Bad and Incomplete Tweet by Araghchi and Incorrect Ambiguity-Creation Regarding the Reopening of the Strait of Hormuz.”
“Publishing this tweet, without any verbal explanation or at least sufficient written explanations, constitutes a complete lack of tact in communication.” — Tasnim

Now some in the media are, of course, seizing on the confusion to highlight that Trump is once again deeply out to a Taco Bell salad lunch. And I want to emphasize that there can be two truths — Trump can be deeply disturbed AND Iran’s leadership has fractured as the US prevails in the conflict. We have precedent. After victories in Italy, Germany, AND Japan in WW2, internal conflict prevented consolidated messaging. After Hitler’s suicide and contested elevation of Karl Dönitz, pockets of German and Czech military refused to accept the surrender.

The US Navy is fully in control of the Hormuz. Those carriers hanging outside missile range are no longer threatened.

We’ve moved from Iran enforcing a blockade, to the US enforcing a blockade ON Iran. The terms to open the SoH from Iran? “Stop being so mean to us! It’s not fair you’re blocking the way!”

Feels pretty spot on with the outline from exactly a month ago:

This bifurcated dynamic is the foundation of the macro landscape. The Hormuz crude issue is an asymmetric warfare problem that U.S. air and naval superiority will resolve within weeks to months. Once escorts and minesweeping begin, signaling American control, it’s largely over. Marine deployments will likely limit incursion to control of coastal regions, leaving the Iranian people to resolve their remaining internal conflicts. Unlike Iraq, a shadow government embraced by the people is ready to go.

Now I know many readers will say, “You can’t know this!” And they’d be right. There is no “knowing” until it’s over. But it’s pretty much over. There was no 5-D chess. Just math.

The oil story collapsed under its own weight on Friday. Sure, Trump was the catalyst. But the reality that many are recognizing now has been well publicized on these pages — much of the oil was already making it out and demand destruction, particularly in emerging markets has been significant:

By my calculations, roughly 2MMbd in demand has already been destroyed. Had prices maintained at these levels, within six months we were looking at 10-20MMbd. Some of that lost demand will return as prices fall and we restock strategic reserves, but some will be permanently lost. We don’t run HVAC twice as much after skipping for a day, nor do we make two trips to the store to make up for the one we skipped last week. Combined with modestly increased production and (as predicted) removal of restrictions on Russian exports, oil will be increasingly well supplied. Meanwhile, the disruption is likely to prove unhelpful to a fuel likely already at peak demand.

Equity markets have recovered, albeit narrowly (poor breadth). Again unsurprising — “macro” products (SPX) have dominated single stock. It’s “RISK” on, not “specific risk” on. With that said, though positioning remains muted overall as the flow has been dominated by retail inflows and short-covering, the PACE of inflows is among the fastest in history:

I am reminded of the language of 1968:

“And all through the stormy course of 1967 and 1968, when things had been coming apart and it had seemed that the center really couldn’t hold- the rising national economic crisis culminating in a day when the dollar was unredeemable in Paris, the Martin Luther King and Robert Kennedy Assassinations, the shame of the Chicago Democratic convention, the rising tempo of student riots– the silly market had gone its merry way, heedlessly soaring upward as if everything were O.K. or would surely come out O.K. as mindlessly, maniacally euphoric as a Japanese beetle in July. Or as a doomed man enjoying his last meal. One could only ask: Did Wall Street, for all its gutter shrewdness, have the slightest idea what was really going on?” — The Go-Go Years, John Brooks

As history can tell us, 1968 was not “the end.” But it WAS the beginning of the end. With the late 1960s, the IPOs slowed and the torrid pace of retail participation began to disappear despite markets making new all-time highs. By the early 1970s, corporate distress was beginning to restructure the American economy as “old economy” behemoths could no longer cover their mounting pension bills.

My hunch is that this will be similar. Not because inflation will return and the Fed will be forced to hike rates to 13%, as “accommodative” Arthur Burns did in 1974, but because the economy is slowing and restructuring. High-tech buildouts and tariffs are slowly leading to a recovery of domestic manufacturing capacity which has expanded for 48 consecutive months — a new post-2000 record:

In contrast, Services PMI has been below the series average for the last three years. We are slowly healing from our 25 year manufacturing devastation, but that sector has shrunk to ~20% of the US economy and only 8% of employment. Meanwhile, as I hypothesized almost exactly three years ago, services is retreating (pre-ChatGPT btw):

The US economy has undergone a significant shift towards a services-driven economy over the years. However, there has been a recent downshift in services consumption per capita growth, even before the pandemic. This downshift is similar to the decline observed from 1907 to the end of World War II. — Yigaf, May 2023

The late Industrial Revolution was really a revolution in services. Washer women became washing machines. Single-viewing theater performances became “movies.” Singers and orchestras became records. Lamp lighters became light switches. Over this period, lifestyles changed radically. As I posited in 2023, we are on the edge of a similar shift where LLMs and “AI” will radically shift our experience of services from “work” to “products.” And with that shift, we’ll likely see services employment plummet as a fraction of work:

Where this stops, we don’t know. But with self-driving cars, autonomous delivery robots, humanoid robots, and “self-programming computers” either here or on the near horizon, I can rest confidently that while our war in Iran is winding down, our war with the machines is just beginning.

So let’s pivot to the conservative movement…

What’s Left to Conserve?

Why the “Invention of Conservatism” is Fracturing

I had the pleasure of attending the Spring 2026 meeting of The Philadelphia Society. For the uninitiated, this is the intellectual “town square” of the American Right, founded in 1964 following the Goldwater defeat. It was intended as a sanctuary for the movement’s brightest—academics, journalists, and high-conviction activists—to debate the future of freedom away from the immediate, distorting pressures of the next election cycle.

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War Update

In the summer of 1989, I returned from freshman year college to live and work in San Francisco. I held three jobs — mail clerk at a law firm, valet parking attendant, and designing an inventory control system for an apparel company. You can guess which one paid the bills (hint: it paid good tips). But I also picked up my lacrosse stick for the first time in six months and played adult club lacrosse with some of my high school buddies.

I was a mediocre crease defense. Good enough to play varsity at the high school level, but nowhere good enough for Penn. Fine for club. But one day that summer, I pulled an All-American NCAA lacrosse attackman as my coverage. It did not go well. Our goalie stopped a shot, and pitched it out for me to clear. Being clever and lazy, as most 19-year-old men are, I decided I’d pull that attackman off the midfield line, towards me, and increase the space available to my mids. I distinctly remember the look of exasperation on his face — “Are we really going to do this?” He began to jog towards me. I patiently waited. When he pulled far enough off the mids, I prepared to pass. His jog became a sprint. The ball left my stick headed to a midfielder…

Which was when this attackman jumped seventeen feet into the air, picked off the pass, and before he hit the ground had dumped an assist to wide open wing attack. And that was when I knew I had better work harder on that inventory control system. Because my future was not in sports.

The relevance? “Are we really going to do this?”

I know what the headlines say, “Talented upstart defenseman holds all-star attack at bay in early play!” I also know what really happened.

Oil is now transiting the Straits of Hormuz. The US Navy is in the Strait. The IRGC appears powerless to stop them. You’re welcome to disagree. But facts are facts.

Inflation

A “disappointing” inflation report reinforced a few key themes. First, remember that “residual seasonality” has corrupted the seasonally adjusted inflation data we receive. As a result, CPI is overstated in Q4 & Q1 and understated in Q2 & Q3. The February PCE and March CPI captured the two largest seasonal impact months; that is over now.

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We’ve been here before:

Let there be no mistake about the cost of war. We have arrayed an impressive international coalition against Iraq, but when the bullets start flying, 90 percent of the casualties will be Americans. It is hardly a surprise that so many other nations are willing to fight to the last American to achieve the goals of the United Nations. It is not their sons and daughters who will do the dying. Most military experts tell us that a war with Iraq would not be quick and decisive, as President Bush suggests; it’ll be brutal, and costly. It’ll take weeks, even months, and will quickly turn from an air war to a ground war, with thousands, perhaps even tens of thousands, of American casualties. — Senator George Mitchell, Jan 11, 1991

I fielded a call this week from a hedge fund manager who told me I was delusional. His exact assessment was that “Iran has already won.”

It was a perfect, real-time distillation of the consensus analytical trap. He sees the Strait of Hormuz functionally closed, U.S. interceptors being drained by cheap drones, and Brent crude elevated. To a standard model, that looks like an unmitigated U.S. defeat.

If this is an Iranian “victory,” it is the most suicidal victory in modern history. Winning a war of attrition by threatening your own country with a return to the pre-industrial age is only a victory if your goal is martyrdom. And some monolithically ascribe that goal to the Iranian people. I do not. But if Iran has “won” by breaking the global energy plumbing—specifically the structural 3-to-5-year hole in LNG and refining from the Ras Laffan strikes—who are the actual losers?

It is not the United States.

The consensus is screaming about a permanent, 1970s-style geopolitical rupture. But the commodity term structure is calling their bluff.

Look at the COZ6 (Dec 2026 Brent) contract. It is sitting at $79.02. That is up a mere 12.5% from June of last year—a period when the market was completely asleep. This is an absolute joke for a “World War III” energy crisis. The back of the curve is telling you the Strait of Hormuz will be cleared quickly. If you disagree, there are plenty of trades available. The on-the-ground reality is that over 50% of the blocked oil has already found alternate routes. Traffic is slowly opening in the Strait through the Oman coastline (~1.6 MMBpd starting this week), Saudi pipelines are maxed out (7 MMBpd), UAE pipelines are flowing (~1.5MMbpd), and Iran is shipping it’s own oil and tolling additional oil (~2MMbpd). While press headlines scream “$2MM toll!”, that is a $1 per barrel premium for a VLCC. And those deals become free if the IRGC falls. For those counting, that’s roughly 11MM of the 20MMbpd. The threshold for complete replacement, given gains in pipelines, increased production, and likely demand destruction, is 35%. We’re already well ahead of COVID…

Tanker rates are falling, but insurance remains expensive at 4x normal if you can get it. Both are likely to continue to retreat. But impressive as the numbers you may hear sound, that quadrupling of tanker insurance adds about $0.50 per barrel.

And remember that the “lost” 20MMbpd were from an oversupplied 105MMbpd total market. So we’re now delivering roughly 96MM of 105MMbpd pre-war demand. That excludes releases from strategic petroleum reserves (which must ultimately be made up in the future). The net result is that the alarming inventory drawdown of 10.2MMbpd will be lower this week. And likely even lower the week after that. And the 2025 floor of ~7700 mb is important, but we can go lower if needed. Rich countries can afford it. Poor countries cannot. Sucks to be poor, I’m sure. Never given it much thought (since it is 2026, I feel obliged to add the “/s”. At least it’s not March 2020).

Super backwardation in oil markets — prompt delivery at a 30% premium to spot, spot at a 30% premium to Dec 2026 futures — is incentivizing inventory release into markets; and the premium of prompt for both crude and products is destroying demand. Leisure travel is being reduced, work from home is being deployed, and emerging markets are introducing emergency rationing.

More importantly, the imminent arrival of U.S. ground troops fundamentally alters the kinetic math. The moment Marines land, the IRGC can no longer afford to waste their degraded missile inventory lobbing shots at passing tankers. They must pivot 100% of their surviving assets to a defensive, anti-invasion posture. By forcing Iran to fight a symmetric ground war, the U.S. functionally neutralizes Iran’s asymmetric anti-ship campaign. The crude blockage is temporary, even if the UAE LNG hole is structural. If traders actually believed in a permanent oil void, that Dec ‘26 contract would be in the triple digits. Maybe you believe differently. The markets are there for you to place your bets.

With this degree of positive carry, shorting is somewhat pointless. If I’m right, those Dec 2026 contracts fall to $60 (perhaps lower, depending on supply and demand). If I’m wrong, the carry from $79 to $110 (or higher) eats me alive. There is no trade on the short side. So you are hearing the motivated reasoning of crude oil longs in market commentary, and the cowardly voice of “no position” on the other side. I’ll remind you, that my insights took you for a 30% loss in Oil vs Gold last September… or a 44% gain, depending on how you want to look at it. Right now, there is no clear trade in either asset in my opinion.

Where I do think there is a trade, the US 2-year yield has violently reversed more quickly. We watched it spike to a 4.00% high in mid-March, prompting pundits to declare a new regime of structural inflation and endless Fed hikes. That was an illusion. It was a mechanical liquidity event—a VaR shock where levered yield-curve steepeners hit margin calls, and front-end Treasuries were indiscriminately liquidated to reduce gross exposure. Inflation is not the concern. I continue to believe Truflation is the “most” honest reporter of current prices:

But if you don’t believe them, perhaps you should check out Penn State, which, like Truflation, uses current real estate prices:

Today, that 2-year yield has fallen back under 3.80%. The mechanical liquidation is exhausted. The global panic is actually funding the U.S. Treasury market, as capital flees the structurally “doomed” industrial centers of Europe and Asia and floods into the only sovereign safe haven that is a net-energy exporter. But it didn’t reach 3.80% in a straight line. A “stellar” jobs report and rising PMI prices has raised doubts that the Fed will need to cut. First PMI Prices… whatever could it be? Oh… oil.

“Yeah, you’re delusional, Mike. Fine… so PMI is being driven by oil… I get it. But oil is a pass-through to everything else.”

Yes, by and large it is. A doubling of oil prices will raise prices… by about 1.5%. You know what else causes prices to rise? Tariffs. And we’re about to celebrate the anniversary of the largest tariff increase in nearly 100 years… with CPI down 0.4% YoY. Inflation swaps have this figured out… short-term inflation up. Forward inflation down. They did the same thing last year when tariffs were introduced:

“OK… but the strong job report…”

Yeah… about that:

And that’s before we get to the still-not-fixed Birth/Death adjustment, plugging away, adding roughly 100K to-be-revised-away jobs per month:

Which just might leave the BLS in the same position as private credit… “lying.”

And now… what you have all been waiting for…

The Toll Booth: Bitcoin’s Extraction Machine in Practice

Part 2 of “Bitcoin Is Not Sound Money”

Introduction to Part 2

Part 1 established the theoretical machine: Bitcoin’s design hardwires a temporal caste through perfectly inelastic supply, front-loaded issuance, and zero holder accountability. The extraction mechanism is not a bug—it is the system operating exactly as its parameters dictate.

More fundamentally, Part 1 demonstrated that Bitcoin does not fix the pathologies its proponents often correctly diagnose in the existing monetary system. The Cantillon effect is made permanent and immune to democratic correction. Wealth concentration is intensified and stripped of any productive obligation. Rent-seeking is perfected into a “constitutionally protected” (code) activity requiring zero effort.

That was the mechanism. This is what it looks like in the world—what it would become at scale—and why the maximalist endgame would make every problem they identify in fiat catastrophically worse.

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YIGAFers,

I apologize in advance. This note is asking you to read roughly 5,000 words across two long, dense letters — Radigan Carter’s extraordinary Twitter post and the one I publish below. Market conditions leave me no choice. We are in live conflict with real energy infrastructure offline, a violent bond repricing underway, and a Fed credibility trap colliding with mechanical market plumbing. Half-measures won’t cut it. The stakes require both lenses.

I wrote “The Fed’s Credibility Trap Meets the Flow-Inelastic Unwind” before reading Radigan’s letter. My thesis was already locked from the data: front-end yields at 3.9%, December 2027 Fed funds futures pricing almost no cuts, and the MOVE Index spiking 28% to 109. Only later did I see Radigan’s framework, and the contrast was immediate.

Radigan writes as the Operator — visceral, scarred by two decades of GWOT failure and his direct experience in nation-building in Iraq. From Oman, evacuating his wife while watching missiles fly, he walks you through the physical reality of a shattered Ras Laffan LNG train: custom vessels, Mammoet heavy-lift crews, sulfur cascades, fertilizer spikes, and the 6-week freight-contract trigger that locks in CPI pain no matter what any president tweets. His Shia theology lens explains the expected Iranian resolve. His “Suez moment” framing sees this as the definitive unravelling of the American empire. Phase 3 — summer earnings misses, AI-for-survival cost cuts, midterms panic — becomes his buying window. It is human, friction-filled, and impossible to dismiss from someone who actually commissioned those LNG facilities. And it mirrors many of the concerns you will read in the popular press.

My note is the Tactitian’s structural calculus with a laser focus on the front of the curve. I separate the reversible oil/Hormuz shock (solvable in weeks to months once Navy escorts and minesweeping begin) from the structural 3–5 year LNG hole at Ras Laffan. The Fed and market, still haunted by 2020–2023, are over-pricing permanence and erasing 2026 cuts — most visibly at the front end. That mispricing was triggered not by thoughtful repricing but by a flow-inelastic unwind: levered steepener books hit margin calls, the MOVE Index exploded, and Treasuries were liquidated first to raise cash. Europe and Asia eat the multi-year pain while the U.S., as net exporter, captures the windfall. The pivot will come from a violent K-shaped credit fracture — youth and non-college cohorts absorbing the entirety of net job destruction and credit stress — once oil normalizes faster than the market expects.

The two views clash in important ways. Radigan’s perspective is shaped by Iraq, where he saw, in person, the limits of U.S. power to reshape a tribal society held together only by Saddam’s brutality — a conflict turned worse by Iranian support for insurgency. That fuels his emphasis on theological resilience and inevitable quagmire. In my view, his Shia theology lens risks conflating the Iranian people with the IRGC regime that now cynically controls and weaponizes it — as evidenced by the new religious leader’s elevation in direct defiance of the former Ayatollah’s wishes and the new leader’s own compromised stature. This suggests the regime may prove more brittle under sustained pressure than the martyrdom narrative implies.

Yet the frameworks reinforce each other powerfully. Radigan’s ground-level friction — 6-week trigger, summer earnings pain, desalination risks, regional militias — keeps my models honest on repair lags and escalation. My front-of-the-curve mechanics and flow-inelastic unwind highlight the U.S. advantage that pure operator cynicism can underweight.

The practical synthesis is clear: use his physical timelines to time the exact moment delinquencies spike and the front end snaps. When that credit fracture arrives, the violent reversal in yields, the dollar, and the policy response will be profound.

I recommend keeping some cash and watching for the first clear Hormuz convoy catalyst. When the US fleet enters the Straits, the conflict is functionally “over.” But for now, the conflict continues to evolve (largely as I’ve expected). The opportunity remains.

The Fed’s Credibility Trap Meets the Flow-Inelastic Unwind

The bond market has undergone a violent repricing in recent weeks. Readers may remember that I turned structurally bearish bonds on a seasonal inflation framework last December 2027 Fed funds futures now imply a terminal rate around 3.75%–4.00%. Two-year Treasury yields closed near 3.88–3.91%, the 10-year Treasury yield settled at 4.39%, and equities weakened further—S&P 500 at 6,506.48, Nasdaq at 21,647.61. The US Dollar Index (DXY) ended around 99.50–99.65, elevated on safe-haven flows.

The mainstream narrative claims this stems from a geopolitical energy shock colliding with a Federal Reserve that may be forced to hike to contain oil-driven inflation.

This narrative is structurally false. It fundamentally misunderstands both the internal dynamics of the Fed and the mechanical plumbing of the bond market.

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For the last two years, a fierce debate has raged over why. Now that the dust is settling, the macroeconomic establishment is busy writing the official post-mortem. But a close look at the recent literature reveals that academia and the Federal Reserve are relying on contaminated statistics and accounting illusions to explain away what actually happened. And, of course, they are doing it to benefit the elite and corporate interests that increasingly dominate the discussion.

Let’s look at two of the most prominent recent attempts to explain the disaster—one pinning the blame on fiscal deficits, the other absolving corporate pricing power—and why the math underneath both of them completely falls apart when you look at the actual receipts.

Part I: The Fiscal Mirage and the Endogeneity Trap

A popular narrative among macroeconomists is the “fiscal mechanism”—the idea that unexpected government deficits were the primary driver of the unexpected surge in global inflation. A recent high-profile paper by Ricardo Reis attempts to prove this by plotting the unexpected deficit shocks of OECD countries against their unexpected inflation shocks, drawing a neat red trendline through the scatter plot.

It looks like a definitive macroeconomic law: countries that ran bigger deficits suffered worse inflation. My partner, Harley Bassman, would be thrilled (always a sign of errors in analysis). But to get that trendline, Reis errs in two massive, highly revealing ways.

Error 1: The Outlier Illusion vs. Statistical Rigor

In the paper, Reis explicitly notes that if you selectively discard two glaring outliers on the far left of the chart (Norway and Denmark), his regression line steepens and his R-sq improves. But subjectively cherry-picking which countries to exclude to make a theory look better is terrible statistics.

If you instead apply standard statistical rigor to the dataset—such as a 5% Windsorization, which objectively trims the extreme tails on both sides of the distribution rather than subjectively dropping two data points—the narrative collapses. The R-sq doesn’t improve; it drops by nearly 50%, falling to a meager 0.189. The trend is a fragile mirage entirely dependent on extreme outliers.

Error 2: Unnecessarily Complicating the Y-Axis

Worse, Reis unnecessarily complicates the inflation story. If you want to explain the consumer cost-of-living crisis, you should plot Consumer Price Inflation (CPI). But Reis didn’t do that. Because he is aiming to prove the Fiscal Theory of the Price Level (FTPL), his Y-axis uses a convoluted “debt impact” analysis, measuring how much the national debt was erased by unexpected inflation (the denominator effect).

It’s a niche academic debt metric, not a measure of household purchasing power. And it fundamentally distorts the data, hiding the mechanical effects of inflation on government balance sheets behind an accounting identity.

The Receipts: What Happens When We Clean the Data?

We can strip out these illusions. If we go to the IMF’s World Economic Outlook and Fiscal Monitor databases, we can rebuild this chart using the metrics that actually matter:

1. A Clean X-Axis: The Cyclically Adjusted Primary Balance, which explicitly strips out cyclical noise, inflation-tax windfalls, and interest payments to isolate the actual discretionary legislative choices made by politicians.

2. A Clean Y-Axis: The actual 5-year unexpected surge in pure consumer inflation, throwing out the convoluted “debt impact” math.

When you plot the clean structural data against actual consumer prices, the vaunted “fiscal mechanism” begins to breakdown even further. First, the full sample R-sq falls to only 0.08, weak sauce at best. Second, Windsorization now IMPROVES the outcomes, suggesting that there very well may be a mechanism with a similar coefficient (0.25) to the fabricated Reis’ result:

But the coefficient is far from statistically significant. You can always draw a regression line through a scatter plot—but if it collapses into statistical insignificance, you must look elsewhere.

Another method of testing this is to extend the regression into polynomial form. I’ve included a four-factor polynomial just for kicks, as it’s oddly shaped like my career trajectory and I always like to remind myself that this is the downslope, but the point remains — any higher order (2 factor, 3 factor, 4 factor, etc) regression suggests that there’s a “magic middle” fiscal deficit that drives unexpected inflation. Or maybe not. Because when we look at the countries, a different grouping falls out naturally:

This approach groups countries by WHY they experienced inflation. Estonia, Latvia, Lithuania, etc are all sitting on the front lines of the Russia embargo. Countries like the UK chose to subsidize domestic energy, keeping a lid on prices, but exploding deficits. Zero covid countries did zero covid things. And of course windfall exporters, e.g. Norway, experienced inflation largely as a result of economies booming due to oil exports. Asia? Safe havens? They remained structurally deflationary in a sea of elevated inflation. Can we rethink this chart even further and offend 90% of the world’s population in the process? Well, yes, this is YIGAF, and that’s our specialty:

The only trend I can actually identify that has any statistical validity is in the “increasingly European” path navigating between Scylla (unlucky) and Charybdis (stupidity). I’m sure my European readers are familiar with this trajectory. Relatively deflationary conditions persist in the “old.” And the United States? Really, the only country that aggressively engaged in fiscal stimulus? It’s sitting right in the center of the universe where Donald Trump thinks it belongs.

We can find statistical support for these groupings using the “coefficient of variation” — basically a test of “do groupings make sense?” If the coefficient of variance declines when data are grouped, it statistically suggests that the datapoints indeed share a common descriptive. If it increases versus the total sample, there is little evidence that the groupings are valid. This is exactly what we see — inflation CV falls when grouped. The same grouping results in an expansion of the deficit CV. This is yet another demonstration that Reis’s approach is completely wrong, and that deficits are not “the” driver of increased inflation. But then again, he’s in the UK, so fully in the grasp of the Charybdis whirlpool.

When you throw out the politics-contaminated math, the truth emerges. Inflation was a byproduct of who you relied on (Russia) and how stupid your politicians were. Both of these are solvable for almost any nation. Just not through deficit targeting.

Part II: The Fed’s “Flat Markup” Illusion

This kind of methodological blind spot isn’t isolated to academia’s fiscal theories. It’s exactly the same type of statistical gaslighting that the Federal Reserve Bank of San Francisco (FRBSF) used to confidently dismiss the “Greedflation” narrative.

During the inflation surge, critics argued that highly concentrated firms used the fog of global volatility to aggressively hike prices and pad their profit margins. In their May 2024 Economic Letter, the FRBSF attempted to put this debate to rest. They concluded that “aggregate markups... have stayed essentially flat” and that the post-pandemic path of markups “is not unusual compared with previous recoveries”. Therefore, they argue, corporate pricing power was not a main driver of the inflation surge.

To prove this, they plot the cumulative change in aggregate markups during the last four recoveries (1991, 2001, 2008, and 2020). To make the lines comparable, they index the start of the 2020 recovery to the exact moment the NBER declared the recession over (Q2 2020).

But treating the summer of 2020 like a normal business cycle trough is absurd. The economy wasn’t “recovering” in the traditional sense; it had been legally halted by government mandate and was waiting to be thawed by trillions in fiscal stimulus.

When you adjust for this and look at what happens when the economy actually reopens and the stimulus fully hits the system (starting in Q4 2020), the Fed’s “normal” narrative completely implodes.

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1. A shared presentation with fun family photos

2. Another comment on credit

3. A warning on flow chasing

4. An answer to the question, “What do you mean by ‘running the table’?”

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1. A quick share: I had the privilege of speaking at TCU this past week. My niece is a senior there and asked if I could guest lecture a class, sharing my work on markets, geopolitics, and thoughts on life. If you’re interested, you can find the presentation here.

   

2. For the US, the week was all about credit, with a host of voices joining my long-term refrain on private credit (from a prior piece):

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I sometimes remind people that the right mental model for Xi and Putin is Tony Soprano — not particularly bright, but devastatingly ruthless. In my early advisory work for the US military, I often emphasized, “We should not become China to defeat China.” Unfortunately, I think we have made significant strides on both fronts. I’ll take the good (geopolitics), and hopefully, we still have a chance against the crime families.

The US is on the verge of “running the geopolitical table” to use a straight pool term. Control of the Western Hemisphere is within reach, geopolitical chokepoints are increasingly closed to China, strategic sourcing is increasingly solved with TSMC and Mountain Pass now both operational on US soil (do not confuse military strategic sourcing with “no concerns on the consumer/industrial front”). Drones deployed in the Iranian attack are the 21st-century equivalent of the WW2 Liberty ships — not invented here, but cheap as chips to deploy.

While I’ve been privileged to have the opportunity to help “solve” the problems of America, I’ve been making incredible progress on my work on passive — theory, book, speaking, understanding, and implementation. Many of you may have noticed a change in my tone in recent discussions. It matters, so let’s discuss.

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Let’s recap where we are.

In Part 1, we showed that in a world of geometric growth and volatility, talent doesn’t win — buffers do. The Gifted Poor went extinct at 25x the rate of the Normie Rich. The Ferrari broke an axle on the dirt road.

In Part 2, we added the costs of actual life — eating, children, and retirement — and watched the model reproduce the American economy with eerie precision. The average wealth skyrocketed while the median flatlined. The bottom 80% were pinned to the subsistence floor. The top quintile retirees became Capital itself — compounding, extracting, and never resetting. We called it the Gerontocracy, and it wasn’t a metaphor. It was the physics.

We ended with a question: Can you tax your way out of this?

You might expect the answer to be simple. Tax the rich. Redistribute. Done. It wasn’t simple at all. In fact, the first two “obvious” reforms made things worse. But the third — the one that most policy experts would dismiss as politically impossible — produced something I did not expect.

The simulation independently derived the tax code of the 1950s.

The Three Prescriptions

We tested three distinct tax philosophies against our baseline model (the untaxed Gerontocracy from Part 2). Same economy. Same agents. Same unemployment shocks. Same random seed. The only thing that changed was the tax structure.

Prescription 1: The “Orthodox” Reform

This is the tax code that both libertarians and mainstream economists call “optimal.” The logic: capital is sacred. Don’t tax it. Instead, shift the burden to consumption. Cut labor taxes (from 10% to 5%), eliminate capital gains taxes entirely, eliminate estate taxes, and introduce a 15% consumption tax. The idea is that by making capital “free,” you accelerate growth, and the rising tide lifts all boats.

Prescription 2: The “Naive Progressive” Reform

This is the populist left’s instinct. Tax capital gains aggressively — 30% annually on all gains — and redistribute the proceeds as a universal dividend. No estate tax. The logic: take from the rich every year and give to the poor.

Prescription 3: The “Deferred” Reform

Let capital compound freely during life. Zero annual capital gains tax. But at the point of intergenerational transfer — death — impose a 50% estate tax. Redistribute the proceeds as a universal dividend. This is, in essence, the structural logic of the New Deal tax code.

Let’s see what happens.

Prescription 1: The Orthodox Failure

The consumption tax is the darling of think tanks. It is “efficient.” It is “neutral.” It does not “distort” capital allocation.

It is also a torpedo aimed at the hull of every low-SES (low socioeconomic status, i.e. “poor”) household in the economy.

Here’s why. A consumption tax is functionally a tax on survival. In our model, every agent must “eat” — $50/year in non-negotiable cost-of-living. A 15% consumption tax raises that floor from $50 to $57.50. That’s $7.50 per year taken directly from the ability to form a buffer.

For the High SES agent sitting on $500 in savings, this is a rounding error. For the Low SES agent entering the workforce with $0 and trying to save $5/year (the gap between their $55 salary and their $50 cost of living), it is catastrophic. Their already razor-thin surplus — the only dollar that could compound — gets taxed before it can be saved.

The consumption tax doesn’t tax consumption. It taxes the attempt to build a buffer.

The results confirm the mechanism:

Read that again. The “optimal” reform made every metric worse. Aggregate wealth fell slightly (less capital formation from buffer-depleted agents). The median didn’t move — it was already zero. And the solvency rate — the percentage of the population with more than a dollar to their name — declined.

The “rising tide” argument requires that you already have a boat.

I want to be precise about the mechanism, because it maps perfectly to the empirical data. The consumption tax is regressive, not because of some abstract distributional concern, but because of the physics of geometric growth. A dollar taxed from the consumption floor of a low-SES agent destroys more future wealth than a dollar taxed from the surplus of a high-SES agent — because the low-SES agent’s dollar was the marginal dollar that determined whether they could compound at all.

This is not a political argument. It is a mathematical one.

Prescription 2: The Naive Progressive Disaster

If the right’s instinct (free capital, tax consumption) fails because it depletes buffers, surely the left’s instinct (tax capital, redistribute) succeeds?

No. It is worse. Much worse.

A 30% annual tax on capital gains doesn’t just redistribute wealth. It destroys the compounding mechanism itself. Every year, the tax skims 30% of any positive return. This is equivalent to reducing the effective return on capital from 8% to approximately 5.6% — but with a critical asymmetry: the tax takes on the upside, but the agent bears the full downside.

This converts an already volatile growth engine into a systematically sub-critical one. The agents can no longer outgrow their costs. The buffer — the very thing that drives survival — can never form:

The aggregate wealth didn’t just decline. It collapsed. From $1.48 billion to $32,555. That is not a typo. That is a 99.998% destruction of total wealth. The solvency rate fell from 16.7% to 8.1%. You made more people destitute, not fewer.

This is the trap that the simulation reveals with brutal clarity: annual capital taxation and consumption taxation fail for the same reason. They both attack the buffer during the accumulation phase — the precise moment when the low-SES agent is most vulnerable to the Volatility Tax and the high-SES agent is on the border of compounding wealth that ultimately benefits society. One taxes the input (consumption). The other taxes the output (returns). Both destroy the same thing: the ability to compound.

The simulation doesn’t care about your ideology. It cares about where you interrupt the compounding process.

The Insight: When You Tax Matters More Than How Much

Let’s pause on this, because it’s the key to everything that follows.

The first two prescriptions share a fatal design flaw: they are synchronous taxes. They extract revenue in real-time — every month, every year — while the agent is still trying to build the buffer that determines their survival.

Imagine a farmer planting a field. You can tax the harvest (which arrives once, at the end of the season). Or you can tax the seeds, the water, and the fertilizer — every day, as they’re applied. Oh, and lop the tops of the plants as they grow as well.

The first approach lets the crop grow. The second prevents it from ever forming.

The question is not how much to tax. The question is when.

Prescription 3: The Tax Code We Already Had

The third scenario is structurally different. It lets capital compound freely during life with zero annual capital gains tax. But at the moment of intergenerational transfer, it imposes a 50% estate tax. The revenue is redistributed as a universal dividend.

This is a deferred, asynchronous tax. It does not interrupt buffer formation. It does not destroy the compounding mechanism. It waits. It lets every agent — High SES and Low SES alike — participate in the growth engine for their entire working life and retirement. And then, at the point of dynastic transfer, it reclaims half of the accumulated surplus and recycles it into the system as new buffers.

The results are not incremental. They are transformative:

Read that table slowly.

The aggregate wealth is lower — about 26% less than the baseline. The “pie” is smaller. Every economist trained in the last fifty years will tell you this is a failure. The system is less “efficient.”

But the median — the household in the middle, the one that votes, the one that sends kids to public school — went from functionally zero to $32,703. And the solvency rate — the percentage of the population with meaningful wealth — went from 16.7% to 100%. Every single agent in the simulation is solvent.

The pie is smaller, but everyone gets a slice.

The Quintile Transformation

This is where the simulation stopped being a model and started being a before-and-after photograph of the American middle class.

Look at those two tables, because they tell the entire story of the last seventy years of American economic history.

In the baseline, Q1 through Q4 have nothing. The bottom 80%, parents and retirees alike, are pinned to zero. All the wealth sits in Q5, and within Q5, the retirees hold 4x more than the parents. This is the Gerontocracy. This is the buffer-ocracy. This is America in 2026.

Under the 1950s code, every quintile has meaningful wealth. Q1 parents hold $10,059. That’s not luxury. But it’s a buffer — two years of breathing room. Q3 parents hold $37,508. That’s a down payment on a house. Q4 parents hold $77,114. That’s a college fund for their kids.

And look at the retirees. Under the baseline, Q5 retirees held $3.5 million, while every other retiree cohort held zero. Under the 1950s code, Q5 retirees still hold $2.1 million; they are still wealthy, but Q3 retirees hold $35,265, and Q1 retirees hold nearly $10,000. They can eat. They can live. They can care for grandchildren. They have dignity.

The 1950s code didn’t abolish wealth. It didn’t punish success. The Q5 agents are still rich. What it did was break the dynastic lock that prevented the bottom 80% from ever entering the compounding regime.

The Gini Tells the Story

For the economists in the audience, here is the same transformation expressed in the language you were trained in.

The Gini coefficient measures inequality on a scale from 0 (everyone has the same wealth) to 1 (one person has everything). The current U.S. wealth Gini is approximately 0.85 — already one of the highest in the developed world. The income Gini sits around 0.41.

In our simulation, the Gini tracks the trajectory of the system’s inequality over 100 years:

Look at the trajectories, not just the endpoints.

The baseline and orthodox scenarios march steadily toward a Gini of 0.98 — a system in which one agent holds essentially all the wealth. This is not an aberration. It is the mathematical inevitability of geometric compounding without a reset mechanism. The consumption tax doesn’t slow it down. It doesn’t even register.

The annual capital gains tax is a fascinating failure. It starts lower — a Gini of 0.50 at Year 10 because the tax successfully suppresses capital accumulation. But by Year 100, it converges to 0.97 anyway. Why? Because it destroyed the compounding engine for everyone. When nobody can build wealth, the Gini rises not because the rich got richer, but because everyone got poorer. The economy collapsed into a shared destitution that is, paradoxically, almost as unequal as the baseline — because even at the floor, the tiny differences between agents get amplified when there’s nothing left to distribute.

And then there’s the 1950s code. It is the only scenario where the Gini stabilizes. It rises to 0.87 around Year 50, then declines slightly to 0.85 by Year 100. The system finds an equilibrium. Inequality exists — it must, because agents have different ages, different compounding histories, different luck — but it is bounded. The estate tax creates a ceiling on dynastic accumulation while the universal dividend creates a floor on destitution. The system breathes.

A Gini of 0.85 is still high. But it is approximately where the U.S. wealth Gini sits today. The question is not whether we can achieve perfect equality. The question is whether we can prevent the system from converging on 0.98, where democracy itself becomes a formality.

A careful reader will object: the simulation above uses a uniform age distribution. Real America in 2025 does not have a uniform age distribution. Real America has the Baby Boomers — the largest, wealthiest generation in human history — sitting on approximately $78 trillion in household wealth, aged 61 to 79, and about to die.

So we reran the simulation. Same four tax scenarios. But instead of a uniform age-wealth distribution, we initialized the population to match 2025 America: a Boomer bulge aged 61-79 holding the majority of wealth in a Pareto distribution (a few with enormous wealth, many with moderate), Gen X with moderate accumulation, Millennials with little, Gen Z with nearly nothing. The starting Gini: approximately 0.85 — exactly where the U.S. sits today.

The results are not merely different. They are alarming.

Under the baseline — no estate tax — the Boomer wealth concentration drives the Gini from 0.85 to 0.995 by Year 100. That last digit matters. At 0.98 in the uniform model, the system was already approaching feudalism. At 0.995, it has arrived. The Boomer bulge doesn’t just reproduce the inequality problem — it accelerates it, because the wealth is concentrated in agents who are still alive, still compounding, and approaching the generational boundary all at once.

And here is what alarms me: the 50% estate tax — the rate that produced 100% solvency in the uniform model — does not work under real-world demographics. The Gini under the 50% rate keeps rising straight through the Boomer death wave. It reaches 0.94 at Year 25, 0.94 at Year 40, and 0.97 by Year 60. Solvency reaches only 75%. The dividend generated by a 50% rate, spread across the entire population, is simply too thin to push agents above escape velocity when wealth is this concentrated.

The uniform model was a proof of concept. It showed that the estate tax mechanism works — deferred, asynchronous taxation at the generational boundary. But it understated the required dose. When you initialize the simulation with actual American wealth concentration, 50% is not enough.

This is why the window is now.

The Boomers hold approximately $78 trillion. They are between 61 and 79 years old. The actuarial peak of the death wave begins around 2030 and crests around 2045. Every year that passes without an effective estate tax is a year in which Boomer wealth flows into the perpetual trust architecture we described earlier — into the vampires, into South Dakota, into legal structures specifically designed to ensure that this wealth never triggers a generational transfer event.

The concentration of wealth in a single generation is not just a problem — it is an opportunity. It is the largest potential buffer-recycling event in American history. But it is a one-time event. Once the wealth has passed into perpetual trusts, the generational boundary ceases to exist, and the mechanism never fires.

We are not arguing for a policy that would be nice to have someday. We are arguing for a policy with a window of approximately fifteen years before the opportunity closes permanently.

So the question becomes: if 50% is not enough, what is?

50% Is Not Enough

The Gini Coefficient still rises during the first 25 years of the Boomer death wave, even with a 50% estate tax. The dividend generated at a 50% rate is insufficient to push agents above escape velocity when wealth is concentrated in a single generational cohort rather than distributed uniformly across age groups.

So we swept the rate. Same Boomer demographics. Same simulation. Seven estate tax rates from 0% to 90%.

At 50%, the Gini never inflects. It keeps climbing straight through the death wave. Solvency reaches only 75% — better than the baseline, but a system that still condemns a quarter of the population to financial death.

At 70%, the Gini finally peaks and reverses — the inflection occurs around Year 25, precisely during the death wave. Solvency reaches 87.5%.

At 77% — the actual top marginal estate tax rate from 1941 to 1976 — the system achieves 99.4% solvency. The Gini peaks at 0.87, then falls to 0.82 during the death wave and stabilizes at 0.83. This is the rate at which the dividend just barely exceeds the threshold needed to push agents above escape velocity under real-world wealth concentration.

The number 77% is not arbitrary. It is the critical rate — the point at which the estate tax dividend, distributed across the population, generates enough buffer to overcome the compounding advantage of the surviving wealthy. Below it, the system improves but does not heal. Above it, the system heals, but at the cost of unnecessary compression. At 77%, it finds equilibrium.

They Knew

Here is the part of this story that stops me cold.

The top marginal estate tax rate in the United States was 77% from 1941 to 1976. Not 50%. Not 60%. Not “somewhere in the 70s.” Exactly 77%. The rate was reached through a series of legislative increases: 10% at inception in 1916, 25% in 1917, 40% in 1924, 70% in 1935, and finally 77% in 1941, where it stayed for thirty-five years.

Did the policymakers who set that rate understand the mechanism revealed by our simulation? Did they know about absorbing barriers, escape velocity thresholds, and the minimum dividend required to overcome geometric compounding under concentrated wealth?

No. Not in those terms. But they understood something arguably deeper.

In 1889, Andrew Carnegie argued that wealth did not belong to the wealthy — it was merely entrusted to them temporarily by the society that made its accumulation possible. He advocated heavy inheritance taxes and declared that a man who dies rich dies disgraced.

Theodore Roosevelt, in his 1906 address to Congress, called for an inheritance tax “increasing rapidly in amount with the size of the estate” — to prevent what he called “swollen fortunes” from perpetuating. His language anticipated our simulation’s findings almost precisely: the tax should be small on moderate estates — don’t interrupt buffer formation — and heavy on the largest — clip the dynastic tail.

Franklin Roosevelt warned in 1936 that “economic royalists” had “carved new dynasties” and that “new kingdoms were built upon concentration of control over material things.” He wanted a 100% tax on incomes above $25,000. Congress negotiated him down. The Revenue Act of 1935, called the “Soak the Rich Act” at the time, pushed the estate tax to 70%. By 1941, it reached 77%.

Keynes, writing in 1936, argued that there is “social and psychological justification for significant inequalities of incomes and wealth, but not for such large disparities as exist today.” He called for the “euthanasia of the rentier” — the functionless investor who lives off capital scarcity rather than productive effort. He explicitly advocated “a scheme of direct taxation which allows the intelligence and determination and executive skill of the financier... to be harnessed to the service of the community on reasonable terms of reward.” This is almost verbatim our distinction between taxing passive returns from luck and infrastructure while exempting active returns from skill.

Even Eisenhower — the Republican who maintained the 77% rate — warned that any society tolerating a “fabulously wealthy” class is asking for trouble.

They did not have agent-based simulations. They did not have ergodicity economics or stochastic process theory. What they had was thirty years of iterative calibration. They kept turning the dial up — 10%, 25%, 40%, 70%, 77% — because each lower setting proved insufficient to prevent dynasty formation. They were empirically converging on the same number that our simulation derives from first principles.

And before them, the Torah commanded Jubilee. The Babylonians decreed misharum. The Romans limited the concentration of ager publicus. Every durable civilization, through experience, arrived at the same structural insight: geometric accumulation requires a periodic reset at a natural boundary, and the reset must be large enough to actually recycle the buffer.

Five thousand years of civilizational experience. Three decades of American legislative calibration. And now a simulation with 5,000 agents and 1,200 monthly time steps. Three entirely independent methodologies. The same answer: approximately 77%.

Policymakers in the 1950s didn’t have our simulation. But they had something better: experience refined through iteration. And they got the number right. And then the business lobby, fronted by Reagan and Friedman, undid it.

And here is the final perversity. The ultra-wealthy already know this.

In 2010, Warren Buffett and Bill Gates launched the Giving Pledge — a commitment by billionaires to donate at least 50% of their wealth to charity during their lifetimes or at death. The remaining 50% is then, in theory, subject to the current 40% estate tax. Do the math: 50% donated, plus 40% of the remaining 50% = a 70% effective transfer rate. The billionaires are voluntarily self-prescribing an estate disposition almost identical to the rate our simulation identifies as the minimum threshold for systemic healing.

They know the wealth needs to be recycled. They just insist on choosing the recipient. The Giving Pledge routes the transfer through private philanthropy — where the donor names the building, selects the cause, retains reputational control, and employs their progeny in perpetuity — rather than through a public dividend, where the democratic process allocates the buffer. The effective rate is nearly identical. The difference is who decides.

This is not generosity. It is the last-ditch defense of allocation authority by a class that understands, intuitively if not mathematically, that the wealth must flow back. They would rather give 70% on their own terms than have 77% recycled on society’s terms.

The rich have already conceded the principle. They have merely reserved the right to administer it privately. The simulation says that’s not good enough.

Why It Works: The Buffer Recycling Mechanism

The estate tax is not a punishment. It is a buffer recycler.

Here’s the mechanism. When a wealthy individual dies, up to 77% of their accumulated capital above the exemption threshold is returned to the system as a universal dividend. That dividend does something specific and measurable: it raises the wealth of every low-SES agent above the critical threshold where compounding can begin.

Think of it in terms of our simulation’s physics. Below a certain wealth level, the Volatility Tax — unemployment shocks, restart costs, the cost of eating — consumes every dollar of surplus before it can compound. The agent is stuck in the Capital Decay Regime. No amount of talent or effort can escape it, because the math prevents escape.

The estate tax dividend pushes agents above the escape velocity. It provides the buffer that allows the compounding engine to finally engage. Once above the threshold, the agent’s own returns do the rest. The system becomes self-sustaining.

But there is a design problem that the simulation glosses over: timing risk. In the model, deaths are distributed uniformly, so the dividend flows smoothly. In reality, estate tax revenue is lumpy. A billionaire dies in 2027; the fund swells. No billionaire dies in 2028; the fund starves. A child born in 2028 receives a smaller buffer than a child born in 2027 — not because of anything about them, but because of the accident of when a stranger died. We have replaced one form of birth lottery with another.

The solution is, ironically, to use the vampire’s own weapon: a trust. Not a perpetual dynastic trust designed to hoard wealth across generations, but a public buffer trust — a sovereign fund that receives estate tax revenue, invests it in U.S. government debt, and distributes the dividend on a smoothed, predictable schedule. The trust absorbs the volatility of revenue timing and converts it into a steady stream. The same way a pension fund smooths contributions over decades to deliver predictable benefits, the buffer trust smooths the generational harvest to deliver predictable buffers.

This is not a new idea. Norway’s sovereign wealth fund, Alaska’s Permanent Fund, and Singapore’s Temasek all operate on variants of this principle — public capital pools that convert volatile revenue streams into stable citizen dividends. The mechanism is well understood. The engineering is solved. What’s missing is the revenue source, and the estate tax provides it.

This is why the solvency rate nears 100%. It’s not that the government is supporting everyone indefinitely. It’s that the buffer recycling mechanism gives everyone enough runway to support themselves. The tax code isn’t redistributing income. It is redistributing the ability to compound.

And here I need to address something directly, because it is the first objection that any fiscal conservative will raise: “You want to grow government.”

No. Emphatically, no. And this is why the universal dividend is the critical design choice, not a detail.

The federal government already spends roughly $6 trillion per year. The vast majority of that spending on social programs operates through a pass-through architecture: federal dollars flow to states, states administer benefits through local bureaucracies, and at every layer of the chain, the dollar is diminished. Administrative overhead. Compliance costs. Eligibility determinations. Case workers. Appeals processes. The bureaucratic friction that exists between a federal tax dollar and a low-SES family’s bank account is enormous — and it is a feature, not a bug, of the current system. It sustains an entire class of administrators, consultants, and state-level political operators whose livelihoods depend on the complexity of the redistribution apparatus.

We monitor charities for efficiency. A charity that spends 60 cents of every dollar on overhead and delivers 40 cents to its mission gets an F rating and donors flee. Yet the federal-to-state-to-local benefit pipeline routinely operates at comparable or worse ratios, and we call it “government spending.”

The universal dividend bypasses this entirely. It is a direct transfer. No state administration. No eligibility bureaucracy. No means testing. No case workers determining whether you are sufficiently poor to deserve a buffer. The estate tax revenue goes in; the dividend comes out. To every American citizen. Upon naturalization and age of maturity, there are catch-up distributions — so that no one is penalized for the accident of when they entered the system. The efficiency ratio approaches 1:1.

This is not a libertarian fantasy about eliminating government. Government has essential functions: defense, courts, infrastructure. Public goods that markets cannot provide. But the redistribution function — the buffer recycling mechanism — does not require a bureaucracy. It requires a ledger. And in 2026, we have the technology to maintain that ledger at trivial cost.

The simulation models this as a direct, frictionless transfer for a reason: because that is how it should work. Every dollar consumed by administrative overhead is a dollar that never becomes a buffer. Every layer of bureaucratic intermediation is a tax on the tax — a synchronous friction applied to the very mechanism we are trying to optimize. The same physics that tells us not to tax consumption during buffer formation tells us not to filter the dividend through five layers of government on its way to the recipient.

We are not proposing bigger government. We are proposing fewer intermediaries between the tax and the buffer.

The Gerontocracy Dissolves

Notice something else in the quintile tables. Under the baseline, the generational divide was obscene: Q5 retirees held $3.5 million vs. Q5 parents at $814,000 — a 4.3x ratio. Under the 50% estate tax, Q5 retirees hold $2.1 million vs. Q5 parents at $742,000 — a 2.8x ratio. A 77% rate normalizes it further still.

The Gerontocracy doesn’t vanish entirely; older agents have compounded longer, and they should be wealthier. But the 50% estate tax reduces the dynastic acceleration that turns retirees into a separate economic species. It clips the tail of the distribution at the exact point where intergenerational transfer would otherwise create an aristocracy. The 77% rate “solves it.”

The 1950s code doesn’t fight the physics. It uses physics as a judo master might use their opponent’s strength. It acknowledges that geometric compounding will always produce concentration over a lifetime, and it introduces a reset mechanism at the natural boundary between generations.

But We’ll Be LESS Wealthy!

The 77% estate tax does have an unfortunate reality: the aggregate absolute wealth DOES decline versus baseline. By nearly 60%! But that’s because we’re defining wealth narrowly. Look what happens to the number of children… consumption… the number of participants with ownership stakes. You want “the ownership economy” replete with the social goods (safety, reduced crime, greater civic engagement) we were promised? This is the path. A small segment of our society will be worse off in relative terms. A not insignificant number of my readers (and my children) will be among them. But our society will be richer; our trust will be higher.

Addressing Sandy’s Objection

One of the most thoughtful comments on Part 2 came from Sandy, who raised a structural point I want to address directly. Sandy argued that the 1950s tax code was the last layer of a multi-layer buffer system: manufacturing employment providing wage floors, unions providing surplus transfer, employer benefits providing non-wage buffers, and then the tax code compressing top-quintile decoupling. Today, three of those four layers are gone.

The estate tax is the only one of the four mechanisms that works through the compounding channel. Unions and manufacturing provide income floors — they raise the salary line at the risk of higher unemployment. Employer benefits reduce the cost line, but the predictable risk is that they lock workers into coercive relationships. The estate tax operates on neither. It operates on the starting condition — the buffer, the endowment, the initial coordinate that our simulation has shown is THE driver of lifetime outcomes.

The other three layers address symptoms. The estate tax addresses the root cause.

You can have unions without an estate tax and get a strong middle class for one generation. But without the estate tax, the dynastic compounding eventually overwhelms every other buffer. The aristocracy reconstitutes itself. Which is, of course, exactly what happened in the real world.

The political obstacles to this reform are real — we'll return to them. But first, the mechanism requires more than a tax rate.

But the Vampires Already Thought of This

I can hear the objection already: “The estate tax exists. We already have one. It doesn’t work.”

And that objection is correct — but not for the reason most people think.

Regular readers will recall my January 2025 piece, “The Undead Among Us,” where I detailed how the American elite effectively achieved immortality through legal engineering. The estate tax has a statutory rate of 40%. The effective rate is approximately zero. And the mechanism by which this was accomplished is one of the most elegant pieces of financial engineering in history — far more impressive than anything Wall Street has produced.

It starts with the Generation-Skipping Trust (GST). Prior to 1986, English and subsequently American law had limited trusts to 21 years past the death of the creator — the Rule Against Perpetuities. This was not an accident. For 500 years, the common law understood that allowing wealth to compound in perpetuity, beyond the reach of any living person’s judgment, was a threat to the social order.

Then came the 1986 tax reform, which created a GST tax exemption. The idea was modest: allow a small amount to pass to grandchildren without double taxation. But it opened a door. Almost simultaneously, states began competing to attract trust business by abolishing the Rule Against Perpetuities. South Dakota won the race to the bottom. Today, South Dakota — a state most people associate with plains and cold weather — holds more than twice the banking assets of New York. $3.4 trillion vs. $1.7 trillion. It is the world capital of the perpetual trust.

Here is what a perpetual trust does in the language of our simulation: it removes the generational boundary entirely. The agent never dies. Its wealth compounds forever. It pays no estate tax because there is no estate — the trust owns the assets, and the trust is immortal. It pays no capital gains tax because nothing is ever sold — the trust distributes income while the principal compounds untouched. The step-up in basis at death? Irrelevant. There is no death.

In our simulation, the estate tax works because every agent dies at 85 and the wealth is recycled. In reality, the Q5 retirees figured out how to become vampires. They created a legal structure that compounds like a corporation — forever — while being taxed like a dead person — never. And like Chicago, the “undead” get to vote through Citizens United.

The 1950s tax code worked because the vampires hadn’t been invented yet. The Rule Against Perpetuities was still intact. Trusts expired. Wealth was recycled. The generational boundary was real. Today, it is fictional, and the estate tax is a Maginot Line — impressive on paper, trivially circumvented in practice.

So our simulation tells us the mechanism that works. But to implement it, we need to slay the vampires first.

The Complete Prescription

The simulation has identified the core principle: tax at the generational boundary, not during accumulation. But the real world has created legal structures specifically designed to eliminate that boundary. A complete reform must address not just the tax rate, but the avoidance architecture that renders it meaningless.

Here are the five pillars:

With detail:

Pillar 1: Restore the Generational Boundary

Abolish perpetual trusts. Restore the Rule Against Perpetuities — the 500-year-old principle that trusts must terminate within a generation of their creator’s death. Eliminate the GST tax exemption. Every dollar of wealth must eventually pass through the generational boundary where the estate tax applies. No exceptions. No South Dakota. No vampires.

This is not radical. This is restoration. For half a millennium, Anglo-American law understood that immortal wealth was incompatible with a free society. We abandoned that principle in a fit of deregulatory enthusiasm in the 1980s, and we are living in the wreckage.

Pillar 2: Tax Scarcity, Reward Development — The Land Value Tax

Henry George figured this out in 1879, and the economics profession has spent 150 years pretending he didn’t. A land value tax — a tax on the unimproved value of land, not on the buildings or improvements upon it — is the only tax in existence that even Milton Friedman called “the least bad tax.” I’ll add more to this discussion in future pieces, but grant me the grace to consider it for now despite the lack of simulation.

Land value is not created by the landowner. It is created by the community — by the roads, the schools, the hospitals, the neighbors, the economic activity that surrounds the parcel. When a landowner’s property appreciates because a new subway stop is built nearby, that appreciation is pure societal luck. It is the equivalent of our simulation’s “Luck Bucket.” Taxing it does not interrupt buffer formation, because the landowner did nothing to create it. It is a tax on scarcity rent, not on productive effort.

Better yet, the LVT actually encourages development. A vacant lot in Manhattan and a skyscraper on an adjacent lot of the same size pay the same land tax. The skyscraper pays nothing additional for the improvement. This reverses the perverse incentive of our current property tax system, which penalizes building and rewards holding empty land as a speculative asset.

In the language of our simulation, the LVT is an asynchronous tax on positional scarcity — it extracts revenue from a source that cannot flee, cannot be hidden in South Dakota, and whose taxation does not destroy productive incentive. It is the ideal complement to the estate tax.

Pillar 3: Distinguish Luck from Skill — Passive vs. Active Investment

This is where we connect directly to the work I’ve been doing on passive investing for the past decade.

Our simulation treats all capital returns identically — 8% with 25% volatility. But in the real world, there is a critical distinction between active investment (selecting companies, building businesses, allocating capital based on judgment) and passive investment (buying an index fund that mechanically allocates capital based on market weight).

Active investing is an attempt at skill. It can fail. It adds information to markets. It performs the essential capitalist function of price discovery — directing capital toward productive enterprises and away from unproductive ones. In the language of our simulation, the active investor is the “Gifted” agent: high return, high risk, high social value.

Passive investing is societal luck. The passive investor makes no judgment about which companies deserve capital. They buy everything in proportion to its existing size. They are, in the language of our simulation, free-riding on the price discovery performed by others. And as I’ve documented extensively, when passive investing exceeds a critical threshold — roughly 40-50% of total flows — it creates a mechanical feedback loop that inflates prices based on index weight rather than fundamentals. The Price-Weight Spiral.

The tax code should reflect this distinction. Active capital gains — from businesses you built, stocks you selected, risks you took — should be taxed lightly during life and at the generational boundary at death. Passive capital gains — from index funds that mechanically benefit from the societal infrastructure of price discovery without contributing to it — should be taxed at a higher rate. Not because passive investors are bad people, but because the return is a social externality that the investor did not create.

This is the same logic as the land value tax: tax the returns from luck and societal infrastructure. Exempt the returns from effort and skill. Both Henry George and Adam Smith would approve.

Pillar 4: The Estate Tax That Actually Works

With Pillars 1-3 in place, the estate tax can finally function as the simulation predicts. A progressive estate tax reaching 77% on the largest estates — the actual rate that prevailed from 1941 to 1976 — with no step-up in basis, no GST exemption, no perpetual trust escape hatch. Revenue recycled as a universal buffer dividend. Our rate sweep under real-world Boomer demographics shows that 50% is not enough — it achieves only 75% solvency when wealth is concentrated in a single generation. The 77% rate is the critical threshold: the point at which the dividend just barely exceeds escape velocity for the bottom quintiles. Below it, the system improves but does not heal. At 77%, solvency reaches 99.4%, and the Gini inflects and reverses during the death wave.

The key insight is that the estate tax alone is insufficient without closing the immortality loopholes on the collection side and the bureaucratic friction on the delivery side. But with both cleared, it is transformative. The expectation that each successive generation should expect to do better than their parents is restored.

Pillar 5: Abolish Public-Sector Collective Bargaining — Clear the Delivery Channel

This is the pillar that will make the left uncomfortable, just as Pillar 1 makes the right uncomfortable. Good. Discomfort is symmetry.

The simulation models the universal dividend as a frictionless transfer — estate tax revenue divided equally, deposited directly. The real world interposes a bureaucracy between the tax and the buffer, and that bureaucracy has, since 1962, been unionized. Kennedy’s Executive Order 10988 granted federal employees collective bargaining rights. The political logic was impeccable: it built a permanent Democratic coalition. The economic logic was catastrophic: it created a constituency whose employment relies on the complexity of the redistribution architecture.

Every means test requires a case worker. Every eligibility determination requires an appeals process. Every layer of federal-to-state-to-local pass-through requires administrators at each level. The universal dividend eliminates all of them. It replaces an army with a ledger. And the army, understandably, will fight.

This is not an argument that public employees are lazy or undeserving. It is a structural observation identical in form to Pillar 1. Perpetual trusts are a private architecture that prevents wealth from reaching the generational boundary where the estate tax can harvest it. Public-sector bargaining rights are the public architecture that prevents the harvested revenue from reaching the citizen as an efficient buffer. One blocks collection. The other blocks delivery. Both must be dismantled for the mechanism to work.

FDR, notably, agreed. He explicitly opposed collective bargaining for public employees, writing that “the process of collective bargaining, as usually understood, cannot be transplanted into the public service.” The 1950s policymakers who built the tax code our simulation rediscovered did not build it on top of a unionized delivery mechanism. Kennedy added that layer later, selling out the taxpayer for electoral victory, and the efficiency of every social program has suffered since.

The Synthesis

Let me pull this together, because the five pillars are not independent policies. They are a system — each addressing a different failure mode that our simulation has identified.

The estate tax addresses the core problem: dynastic compounding across generations. It is the generational reset mechanism.

Abolishing perpetual trusts prevents the legal circumvention of the generational boundary. It ensures that the estate tax actually collects.

The land value tax provides revenue from a non-distortionary source — scarcity rent that the owner did not create — without interrupting buffer formation during the accumulation phase.

The passive/active distinction aligns the tax code with the economic function of capital allocation — rewarding skill and price discovery, taxing free-riding on societal infrastructure.

Abolishing public-sector collective bargaining clears the delivery channel, ensuring that the collected revenue actually reaches citizens as buffers rather than being consumed by administrative friction. It ensures that the estate tax actually arrives.

Pillars 1 and 5 are mirror images: one dismantles the private immortality architecture that blocks collection, the other dismantles the public complexity architecture that blocks delivery. Together, they create an unobstructed channel from the generational boundary to the citizen’s account. The estate tax is the pump. The pillars clear the pipes.

Together, the five form a coherent system that respects the physics of geometric growth while preventing the inevitable concentration that uninterrupted compounding produces. They do not punish success. They do redistribute income — let’s be honest about that. But they redistribute it with a specific purpose: not to provide consumption, but to create buffers. To give the next generation a starting condition from which compounding can begin. The distinction is not whether redistribution occurs, but whether the redistribution creates the capacity to compound rather than merely the capacity to consume.

And critically, for those inclined toward the Charles Murray objection: bad decisions are still penalized under this system. The buffer is not a guarantee of outcomes. It is a guarantee of survivable mistakes. A kid from Q1 who picks the wrong degree financed with $80,000 in debt is not “learning a valuable lesson.” He is experiencing a catastrophic, irreversible shock that the simulation tells us pushes agents below the absorbing barrier from which there is no recovery. The same kid from Q5 who makes the same mistake? His family writes a check or calls a friend. He resets. He tries again. He compounds.

The system we are proposing does not eliminate consequences. It eliminates the asymmetry where identical mistakes produce recoverable setbacks for the wealthy and permanent financial death for everyone else. It gives low-SES kids — and their families — the same reset that wealthy families already provide privately. The conservative who objects to this is not defending meritocracy. He is defending a system in which the punishment for being eighteen and wrong is lifelong, but only if your parents are poor.

The Political Economy Problem

Now the hard part.

The simulation can derive the optimal system. It cannot implement it. And this is where I must be honest with you, because the political economy problem is genuinely harder than the policy design problem.

The estate tax was effectively dismantled between 1981 and 2017 — from a top rate of 77% with a $175,000 exemption to a top rate of 40% with an $11 million exemption. The perpetual trust was created. The GST exemption was expanded. The step-up in basis at death was preserved. Each of these changes was the product of a fifty-year campaign by precisely the cohort that our simulation identifies as the primary beneficiary of the Gerontocracy: wealthy retirees in Q5. They funded the think tanks. They wrote the talking points. They convinced the bottom 80% — the people harmed by the policy — to vote for it, using the language of “family farms” and “death taxes” and “double taxation.”

It was, as Sandy noted in the comments to Part 2, strategically coherent. You cannot sustain low capital taxation if unions retain the power to recapture surplus at the point of production. So you dismantle unions first. Then you dismantle the estate tax. Then you create the perpetual trust. Then you cut capital gains rates. Each step is logically prerequisite to the next. Whether it was explicitly coordinated is irrelevant — the sequence was functionally optimal for the beneficiary class.

This creates what I’d call the Reform Paradox: the cohort with the resources to fund political change is the cohort that benefits from the current structure. And the cohort that would benefit from reform — the Sandwich Generation, the buffer-less workers, the Low SES agents trapped in the Capital Decay Regime — has neither the capital nor the political bandwidth to organize. They are too busy surviving.

Systems that reproduce their own conditions across generations are not typically reformed from within by the cohorts they disadvantage.

But they are occasionally reformed from without — by coalitions organized around clarity rather than ideology. The New Deal was one such moment. The physics haven’t changed. The design problem is solved. The question is whether enough people understand the mechanism to demand its implementation.

Left and right have been arguing about redistribution for fifty years. The simulation shows that the argument is malformed. This is not about taking from the rich and giving to the poor. It is about when you tax, not how much. Let capital compound. Let people build. Let the Ferrari run on fresh asphalt. And at the natural generational boundary, recycle the buffer so the next generation can run too.

This is not socialism. It is not libertarianism. It is the mechanical insight that a system governed by geometric growth and volatility requires a periodic reset at the point of intergenerational transfer, or it will inevitably produce an aristocracy.

This is not even a new idea. It is arguably the oldest economic idea in civilization. The Torah commands a Jubilee every fifty years — debts forgiven, land returned to its original holders, slaves freed. Leviticus 25:10: “Consecrate the fiftieth year and proclaim liberty throughout the land.” The Babylonians practiced misharum — periodic royal edicts canceling debts and resetting economic claims. Roman law limited the concentration of ager publicus — public land — in private hands, and the failure to enforce those limits was, by the republic’s own historians, a proximate cause of its collapse.

Every durable civilization in recorded history understood that geometric accumulation, left unchecked, eventually consumes the society that enables it. They didn’t have simulations. They had experience. And they arrived at the same answer: a periodic reset at a natural boundary.

The Founders understood this. Jefferson wrote about it. Adams warned against it. And for thirty years — from roughly 1945 to 1975 — we actually built it.

We can build it again. But only if we stop treating the economy as a morality play and start treating it as what it is: a physical system with knowable dynamics and designable interventions.

This concludes the Summer Slide Economy series. The full executable code for all simulations, including the tax policy scenarios in this piece, is available here. The code runs in Google AiStudio or any Python environment with numpy and matplotlib.

If you found this series valuable, please share it. The paywall is down. The argument is free. The only question is whether enough people hear it.

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A Quick Review

Last week, we showed that in a world governed by geometric growth and volatility, talent doesn’t win—buffers do. The “Gifted Poor” went extinct at 25x the rate of the “Normie Rich.” The market selected for safety, not skill. The Ferrari broke an axle on the dirt road.

But that simulation was still a game. The agents didn’t eat. They didn’t have children. They didn’t retire.

This week, we add all three. And the model stops looking like a thought experiment, and it starts looking like a census report.

Phase 3: The Volatility Trap (or, “Why You Can’t Save Your Way Out”)

In Phases 1 and 2, our agents lived in a frictionless world. They bet, they won or lost, and the only cost was the bet itself. But in the real economy, you have to eat—every single day, whether you won or lost.

So we introduced the physical requirement of survival.

The Setup:

We gave every agent a job paying $55/year and a non-negotiable cost-of-living allowance of $50/year. That’s a theoretical 10% savings rate—generous by American standards. We then introduced a realistic unemployment shock: a 4% steady-state rate with a 3-month average duration.

Here’s the critical addition: re-employment isn’t free. Every restart costs $10—the new clothes, the lost security deposit, the COBRA payment, the repo’d car. That’s the “Restart Haircut.” It’s a small number that produces catastrophic results.

We split our agents into two classes. Not by talent—everyone is equally skilled. The only difference is the starting buffer:

• High SES (high socioeconomic status): Starts with $500. Ten years of breathing room.

• Low SES: Starts with $50. Exactly one year of subsistence.

The Result: A massive widening of outcomes.

Importantly, note that we are assuming 100 years(!). The compounding eventually takes over, which is an important clue to our current gerontocracy. But with only a 40-year working life, the median low-SES ends up worse off than they started. Less than 10% of high-SES people end up worse off than they started.

The High SES group compounding is nearly uninterrupted. Their buffer absorbs decades of shocks. They barely notice unemployment, the way you barely notice a pothole in an SUV.

The Low SES group enters what we can call the Capital Decay Regime. For the unlucky agent, the Restart Haircut and the unemployment shocks overwhelm the 10% savings rate. They spend their working lives recovering from the previous restart rather than compounding. Two unemployment events in a decade—which is not unusual, it is average—is enough to drive their wealth to zero.

The survival rates are the most damning output. The High SES group: near 100%. The Low SES group: nearly 13% ruin rate (bankrupt). And remember this is with a constant 4% unemployment rate — near the lowest in history. Same talent. Same work ethic. Same economy. Different starting coordinates. Different outcomes.

If we introduce recessions every 10 years, with unemployment rising to 8% and the duration of unemployment during recessions doubling to 6 months. Look familiar?

The Insight: Redundancy—starting wealth—is THE driver of outcomes. Without a buffer, the low-wealth agent is trapped in a sub-critical regime where growth is challenged, regardless of skill or effort. We have built a system where the “Cost of Survival” is set by the average, but the “Ability to Survive” is denied to the median.

I want to pause on that, because it maps perfectly to the empirical data.

When researchers decompose the White-Black lifetime earnings gap, two factors explain the overwhelming majority of the differential at the low end: years of full-time work (largely a proxy for unemployment frequency) and possession of health insurance. Not education. Not “grit.” Not IQ. Time in the game and a buffer against medical ruin.

At the 85th percentile—the high-outcome cohort—these factors explain almost nothing. Why? Because by definition, the people at the top already have the buffers. The variance has been absorbed. Of course, “they” think talent explains everything and that meritocracy asserts itself over time; unfortunately, we readers of YIGAF know that to be “untrue.” From the summit, the road looks smooth, and we can comfort ourselves that we “deserve” what we’ve made.

This is also why wealthy people don’t want to pay for universal healthcare. They literally cannot see the point. Their buffer makes the problem invisible.

Phase 4: The Sandwich Generation

Having established that buffers drive outcomes more than talent, we asked the obvious next question: What happens over a lifetime? Not just one agent’s lifetime—across generations.

We added three things that economists love to model in the abstract but rarely simulate in combination: children, retirement, and inheritance.

The Rules:

• The Inheritance Gap: High-SES children enter the workforce at 20 with a $500 buffer (their parents’ gift). Low-SES children enter with $0.

• The Parent Trap: You can only have a child if your wealth exceeds $375—roughly three years of subsistence. Each child costs $25/year for 18 years. Maximum three children.

• The Sandwich Transfer: Workers pay 10% of their salary to a retiree pool. Think of it as Social Security, Medicare, and the informal family obligations combined.

• Retirement: At 70, your salary disappears. You survive on accumulated capital (still compounding at 8%) and the transfer pool.

We ran this for 100 years—a full “Post-New Deal Era.”

The First Graph: Average vs. Median

The Average Wealth line shoots upward. If you were an economist looking at aggregate GDP, you would say the system is working. The pie is growing. As Nick Maggiulli correctly points out, the average wealth is disrupted by inheritance dilution, but the family wealth continues to compound.

The Median Wealth line crashes and flatlines. The typical household—the one in the middle, the one that votes, the one that sends kids to public school—cannot compound. The combination of child costs, the retiree transfer, and the ever-present unemployment shock consumes every dollar of surplus before it can grow.

This is the Ensemble Illusion. The average is being pulled upward by the top 1%, whose buffers are so large that they operate in a fundamentally different economy. The median is treading water. And the bottom quartiles are drowning. It’s an America where “we’ve never been richer” and “59% of households can’t afford a $1,000 emergency expense.”

The Second Graph: The Quintile Breakdown

This is where the simulation stopped being a model and started being a photograph.

When we broke the terminal wealth into quintiles and compared Parents (ages 25-45) against Retirees (ages 70-85), the picture was devastating.

Q1 through Q4: There is no meaningful difference between working-age parents and retirees in the bottom 80% of the economy. Both groups are pinned to the subsistence floor. The 10% transfer and the 8% capital returns are insufficient to lift the median retiree out of the Capital Decay regime. If you didn’t enter retirement with a massive buffer, you’re just as broke as the young family down the street.

Q5—The Decoupling: The only meaningful wealth accumulation happens in the top 20%. And within that quintile, the Retirees pull away from everyone else. They are the only cohort with enough capital to actually benefit from 50 years of compounding. They receive the transfer payments. They consume a shrinking fraction of their wealth. They have zero dependent costs—their children are grown. They don’t work, so they take no unemployment shocks.

They have become Capital.

Not “people who have capital.” Capital itself. A wealth object that compounds, extracts, and never resets.

The most profitable strategy in our simulation wasn’t to invent the future. It was to have already invented it 40 years ago and get “lucky.”

The Gerontocracy Is Not a Metaphor

We have inadvertently created a society in which the old hold all the capital, and the young are burned as fuel to keep them warm.

This isn’t generational warfare rhetoric. It’s the physics of the system.

The retiree class in Q5 benefits from every feature of the economy simultaneously: compound returns on a large base, transfer payments funded by workers, zero labor risk, zero child costs, and—here’s the kicker—preferential tax treatment on capital gains. The step-up in basis at death means that a lifetime of untaxed gains can be passed to heirs with the tax liability erased entirely.

Meanwhile, the Sandwich Generation (ages 30-50) is simultaneously funding:

• Their own rent (Cost of Living)

• Their children ($25/year per child for 18 years)

• The retiree transfer (10% of salary)

• The restart risk (unemployment shocks with no buffer)

They are paying for everything and compounding nothing.

I recently saw Rob Arnott present data showing the “declining fortunes” of wealthy individuals across generations and label it “hopeful”—evidence that wealth doesn’t persist. But he misread his own data. What he was seeing wasn’t degradation; it was inheritance dilution. The family dynasty’s wealth continues to compound. It’s just being split across more heirs. The per capita decline is an illusion. The dynastic wealth is growing faster than ever.

The Mechanism We Refuse to See

What our simulation reveals is that the American economy has a caste system, and it is not based on race, gender, or even education. It is based on Redundancy at birth.

If you enter the labor market with a buffer—parental wealth, a paid-for education, a family home to fall back on—you can survive the volatility. You can take risks. You can fail and try again. You can be a Ferrari on fresh asphalt.

If you enter without one, the math is against you from day one. You are not lazy. You are not untalented. You are simply operating in a sub-critical regime where the physics of geometric growth cannot help you, because every dollar of surplus is consumed by the cost of survival before it can compound.

We haven’t built a meritocracy. We’ve built a buffer-ocracy. And the biggest buffer of all is age—specifically, having been born early enough to accumulate capital before the ladder was pulled up.

The Cliffhanger

We have now diagnosed the disease: a system that selects for starting resources over talent, that concentrates wealth in retirees, and that traps the working-age population in a subsistence loop.

The obvious question was: Can you tax your way out of this?

I expected the answer to be simple. It wasn’t.

When we tested the reform that both libertarians and orthodox economists call “optimal”—cutting taxes on capital and raising them on consumption—the system didn’t just fail to improve. It got worse.

But when we tested a different structure entirely—one that most policy experts would dismiss as politically impossible—the simulation independently derived something remarkable: the tax code of the 1950s.

Part 3: “The Tax Code We Already Had” next week.

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There are FOUR parts to this piece, the first three are brief, but important.

(1) An update on the search for candidates with a follow up discussion with Phil Andrew, who remains the sole candidate I’ve found that I can completely endorse. Several of my readers went to Phil’s congressional campaign site and came back complaining about his concerns on ICE. Long before the current headlines, Phil made a prescient call regarding the degradation of training standards at ICE. He warned that you cannot slash training curriculums—reducing months of instruction to mere weeks—and expect a professionalized force capable of handling complex enforcement scenarios. We are now seeing the results of those decisions. Phil breaks down exactly why "enforcement" without "professionalization" is a liability, not an asset.

Competent expertise proves prophetic. Funny how that works. Check out my most recent video, and please, please help. We face an uphill battle in restoring our Republic. We will NOT keep it under the current trajectory. One voice can make a difference. If you know anyone in Chicago, and remember it’s Chicago, so both the living and the dead vote, please forward the video.

(2) A brief update on markets

What I am watching VERY closely is the uptick in credit spreads as we see growing awareness that lending to the SAAS/software complex is metastasizing. Credit spreads ticked higher this week even as the cyclical elements of the economy are showing signs of life. I continue to think we’ll see the economy turn lower, but at least headline data says I’m wrong (PMI rebounds). Bankruptcies, credit card delinquencies, auto delinquencies, etc continue to march higher.

(3) A full-throated endorsement that ALL readers check out Marco Rubio’s speech at the Munich Security conference. There are adults in the room and this articulation was brilliant.

For the last few decades, we have lived under the “End of History” delusion—the idea that unfettered free trade and financialization would inevitably lead to global peace. Rubio’s speech was a systemic dismantling of that failure. He didn’t just offer “America First” slogans; he offered a coherent, intellectual rejection of the policies that deindustrialized the West and hollowed out our middle class.

Rubio explicitly linked the “euphoria” of globalization to the fragility we face today. This is the exact argument I have been making regarding market structure and labor arbitrage: when you prioritize efficiency over resilience, you lose your sovereignty. To hear this articulated from the podium in Munich—framing America not as a separate entity but as a “child of Europe” that must save the West from its own managed decline—signals a return to competence in US foreign policy that is deeply aligned with my own views.

Which brings us to the main event. As compensation to paid subscribers, the full code for all simulations is below the paywall. Have fun!

(4) The Achilles Heel — the domestic economy. I am not worried about our ability to win based on capacity. Nor am I quite as hyperbolic as Alex Karp (I have my own special hyperboles). Like most “foes”, China’s strengths are overstated. Their vulnerabilities are often ignored. We can win, but only if we build a system at home that utilizes the best of all of my fellow citizens. And to do that, we have to stop gaslighting. Milton Friedman, The Chicago School, and the Business Lobby took us on a fifty-year detour that threatens the foundations of our society. We can reclaim it, but first we must understand what we have lost. So let’s slide into summer…

Part 1 (of 3): The Summer Slide Economy

We tell ourselves a comforting story about success. It goes like this: The economy is a sorting mechanism. “Talent” (intelligence, grit, risk-tolerance) naturally rises to the top. If you are smart and unafraid, you will win. Everyone else is just drafting off your wake.

It is a seductive narrative. But it is physically wrong.

I didn’t arrive at this conclusion by debating philosophy. I arrived here by looking at the data—specifically, by trying to understand why poor kids fall behind rich kids, even when they are just as smart.

The “Twin Study” Sleight of Hand

To sustain the meritocratic narrative, defenders often point to Twin Studies. They cite data showing that identical twins have similar IQs, and then, in a magician’s sleight of hand, insist this proves that Wealth is genetic.

They are conflating the engine with the road.

While IQ has heritable components, Wealth is not a biological trait. It is an environmental condition. The most rigorous recent work on this, such as Fagereng, Mogstad, & Rønning (2020), uses adoption data to sever the biological link. Their finding is stark: Genes explain very little of who gets rich. Inheritance—specifically the ability to accumulate assets without interruption—explains almost everything. A more accessible version that extends the dataset to the UK is available here.

Same Salary, Different Outcome

Consider homeownership rates in the UK. When we compare children from wealthy families against children from poor families, we see a massive divergence.

The solid lines show reality: Rich kids buy houses; poor kids rent. But the dashed lines are the smoking gun. They represent a simulation where we control for the child’s income.

The result? Take two 30-year-olds with the exact same job, the exact same salary, and the exact same “grit.” The one with wealthy parents buys a house. The one with poor parents rents. The “merit” (income) is identical, but the outcome is strictly determined by the starting condition.

The Clue: The Summer Slide

This dynamic isn’t limited to housing. Years ago, education researchers stumbled upon a “natural experiment” that explains this perfectly.

They tracked the learning growth of students—high-income vs. low-income—over a calendar year.

• During the School Year: When structure, meals, and supervision (buffers) were provided by the state, the learning growth rates of poor kids and rich kids were statistically identical. The “Talent Gap” vanished.

• During the Summer: When those buffers were withdrawn, the divergence exploded. Rich kids continued to grow (camp, books, travel). Poor kids stagnated or regressed.

The “Achievement Gap” wasn’t a measure of intelligence; it was the mathematical sum of volatility shocks accumulated over twelve summers.

This led to a terrifying question: What if the entire economy is just one long Summer Slide?

The Simulation: A Thriller in Two Acts

To test this, we built a simulation of the US economy. We didn’t program it with ideology; we programmed it with the physics of Geometric Growth subject to Volatility.

Phase 1: The “Talent” Extinction Event We started with a world of “Pure Meritocracy.” No taxes, no safety nets, just raw probability. We created “Gifted” agents (High Return/High Risk—think Ferraris) and “Normie” agents (Low Return/Low Risk—think Camrys).

The Result? The “Gifted Poor” went extinct. While the Average Wealth of the talented group skyrocketed (driven by a few lucky survivors), the Median Wealth told a horrifying story. The typical “Gifted Poor” agent ended up poorer than the “Normie Poor.”

Why? Because high-risk strategies are geometrically unstable. Without a buffer to absorb the shocks, the “Gifted Poor” hit zero (bankruptcy) at nearly 25x the rate of the “Normie Rich.” The market didn’t select for Talent; it selected for Low Variance. The Ferrari breaks an axle on a rough road.

Phase 2: The “Volatility Tax” Next, we modeled the impact of random life shocks—unemployment, health crises, or family emergencies.

• High SES (Buffered): When a shock hits, they pause. They rely on savings or family support to smooth the blow.

• Low SES (Unbuffered): When a shock hits, they crash. They are forced to liquidate assets, take predatory loans, or move homes.

The result was a divergence engine. Even with identical talent and identical income, the Unbuffered group fell permanently behind. Inequality wasn’t driven by who worked harder. It was driven by who paid the Volatility Tax.

The Cliffhanger We had proven that volatility kills talent. But our simulation was still missing the most expensive parts of real life: Eating and Children.

When we added those to the model, the results went from “unfair” to “catastrophic.”

Part 2: “The Rise of the Gerontocracy” next week.

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Appendix: Python Code

Can be executed in Google AiStudio: https://aistudio.google.com/prompts/new_chat?model=gemini-3-pro-preview. Make sure you have “Code Execution” selected on the lower right portion of your screen.

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Phase 1: The “Talent” Extinction Event

import numpy as np
import matplotlib.pyplot as plt

def run_phase_1_final_three_panels_v2():
    # Parameters
    n_agents = 5000 
    T = 40
    dt = 0.1
    steps = int(T / dt)
    
    W0 = 1000.0
    W_barrier = 200.0  # Ruin Barrier
    
    # Groups: (Name, Mu, Sigma, Color, Style)
    # Using distinct colors/styles to ensure all 4 are visible
    groups = [
        ("Normie / High SES", 0.05, 0.10, "tab:blue", "-"),      # Safe / Safe
        ("Normie / Low SES", 0.05, 0.20, "tab:cyan", "--"),      # Safe / Risky
        ("Gifted / High SES", 0.08, 0.20, "tab:green", "-"),     # Risky / Safe
        ("Gifted / Low SES", 0.08, 0.40, "tab:red", "--")        # Risky / Risky
    ]
    
    # Store data
    results_avg = {}
    results_median = {}
    results_survival = {}
    
    np.random.seed(42)
    
    for name, mu, sigma, color, style in groups:
        wealth = np.full(n_agents, W0)
        alive = np.ones(n_agents, dtype=bool)
        
        avg_hist = [W0]
        median_hist = [W0]
        survival_hist = [1.0]
        
        for t in range(steps):
            if np.any(alive):
                z = np.random.normal(0, 1, n_agents)
                growth = (mu - 0.5 * sigma**2) * dt + sigma * np.sqrt(dt) * z
                
                # Update wealth for alive agents
                wealth[alive] *= np.exp(growth[alive])
                
                # Check Ruin
                ruined = (wealth < W_barrier) & alive
                alive[ruined] = False
                wealth[ruined] = 0.0
            
            avg_hist.append(np.mean(wealth))
            median_hist.append(np.median(wealth))
            survival_hist.append(np.mean(alive))
            
        results_avg[name] = avg_hist
        results_median[name] = median_hist
        results_survival[name] = survival_hist

    # Plotting
    fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(18, 6))
    time = np.linspace(0, T, steps + 1)
    
    # Common function to plot with distinct styles
    def plot_lines(ax, data_dict):
        for name, data in data_dict.items():
            # Retrieve style info
            grp = next(g for g in groups if g[0] == name)
            color = grp[3]
            style = grp[4]
            # Plot
            ax.plot(time, data, label=name, color=color, linestyle=style, linewidth=2.5, alpha=0.9)

    # Panel 1: Average
    plot_lines(ax1, results_avg)
    ax1.set_title('Average Wealth (The Illusion)', fontweight='bold')
    ax1.set_ylabel('Wealth ($)')
    ax1.grid(True, alpha=0.3)
    ax1.legend(loc='upper left', fontsize='small')
    
    # Panel 2: Median
    plot_lines(ax2, results_median)
    ax2.set_title('Median Wealth (The Reality)', fontweight='bold')
    ax2.grid(True, alpha=0.3)
    ax2.legend(loc='upper left', fontsize='small')
    
    # Panel 3: Survival
    # Multiply by 100 for percentage
    results_survival_pct = {k: np.array(v)*100 for k, v in results_survival.items()}
    plot_lines(ax3, results_survival_pct)
    ax3.set_title('Survival Rate (The Mechanism)', fontweight='bold')
    ax3.set_ylabel('% Surviving')
    ax3.set_ylim(0, 105)
    ax3.grid(True, alpha=0.3)
    ax3.legend(loc='lower left', fontsize='small')
    
    plt.tight_layout()
    plt.show()

run_phase_1_final_three_panels_v2()

Phase 2: The Summer Slide Economy

import numpy as np
import matplotlib.pyplot as plt

def run_phase_2_random_shocks():
    # Parameters
    n_agents = 5000
    T = 20  # Years
    dt = 1/12 # Monthly steps
    steps = int(T / dt)
    
    W0 = 1000.0
    W_barrier = 200.0
    
    # Common Baseline (Stable Times)
    mu_stable = 0.08
    sigma_stable = 0.25
    
    # Shock Parameters
    shock_prob = 1/12 # Probability per month
    
    # High SES (Buffered) Shock
    mu_shock_H = 0.00
    sigma_shock_H = 0.25
    
    # Low SES (Unbuffered) Shock
    mu_shock_L = -0.20
    sigma_shock_L = 0.45
    
    # Setup Groups
    groups = [
        ("High SES (Buffered)", "green", "-"),
        ("Low SES (Unbuffered)", "red", "--")
    ]
    
    # Data Storage
    results_avg = {g[0]: [W0] for g in groups}
    results_median = {g[0]: [W0] for g in groups}
    results_survival = {g[0]: [1.0] for g in groups}
    
    wealths = {
        groups[0][0]: np.full(n_agents, W0),
        groups[1][0]: np.full(n_agents, W0)
    }
    alives = {
        groups[0][0]: np.ones(n_agents, dtype=bool),
        groups[1][0]: np.ones(n_agents, dtype=bool)
    }
    
    np.random.seed(42)
    
    for t in range(steps):
        for name, color, style in groups:
            w = wealths[name]
            alive = alives[name]
            
            if np.any(alive):
                # Determine who gets shocked (Individual Shocks)
                is_shocked = np.random.rand(n_agents) < shock_prob
                
                # Parameters for each agent
                # Default to stable
                mus = np.full(n_agents, mu_stable)
                sigmas = np.full(n_agents, sigma_stable)
                
                # Apply shock params
                if name == "High SES (Buffered)":
                    mus[is_shocked] = mu_shock_H
                    sigmas[is_shocked] = sigma_shock_H
                else:
                    mus[is_shocked] = mu_shock_L
                    sigmas[is_shocked] = sigma_shock_L
                
                # Geometric Brownian Motion Step
                z = np.random.normal(0, 1, n_agents)
                growth = (mus - 0.5 * sigmas**2) * dt + sigmas * np.sqrt(dt) * z
                
                # Update Wealth
                w[alive] *= np.exp(growth[alive])
                
                # Check Ruin
                ruined = (w < W_barrier) & alive
                alive[ruined] = False
                w[ruined] = 0.0
            
            results_avg[name].append(np.mean(w))
            results_median[name].append(np.median(w))
            results_survival[name].append(np.mean(alive))

    # Plotting
    fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(18, 6))
    time = np.linspace(0, T, steps + 1)
    
    def plot_panel(ax, data_dict, title, ylabel=None, ylim=None):
        for name, color, style in groups:
            y_vals = np.array(data_dict[name]) * 100 if "Survival" in title else data_dict[name]
            ax.plot(time, y_vals, label=name, color=color, linestyle=style, linewidth=2.5)
        
        ax.set_title(title, fontweight='bold')
        if ylabel: ax.set_ylabel(ylabel)
        if ylim: ax.set_ylim(ylim)
        ax.grid(True, alpha=0.3)

    plot_panel(ax1, results_avg, 'Average Wealth', ylabel='Wealth ($)')
    plot_panel(ax2, results_median, 'Median Wealth')
    plot_panel(ax3, results_survival, 'Survival Rate', ylabel='% Surviving', ylim=(0, 105))
    
    # Legend
    lines, labels = ax1.get_legend_handles_labels()
    fig.legend(lines, labels, loc='lower center', ncol=2, bbox_to_anchor=(0.5, -0.05))
    
    plt.tight_layout()
    plt.subplots_adjust(bottom=0.15)
    plt.show()

run_phase_2_random_shocks()

Phase 3: Eating

import numpy as np
import matplotlib.pyplot as plt

def run_phase_3_4pct_unemployment():
    # Parameters
    n_agents = 5000
    T = 100  # 100 Years
    dt = 1/12  # Monthly steps
    steps = int(T / dt)
    
    # Calibration for 4% Unemployment Rate:
    # If duration (D) = 3 months, and prob (p) is monthly:
    # Steady State Rate (u) = p*D / (1 + p*D - p)
    # 0.04 = 3p / (1 + 2p) -> 0.04 + 0.08p = 3p -> 0.04 = 2.92p -> p ≈ 0.0137
    shock_prob = 0.0137 
    unemployment_duration = 3 # months
    
    # Endowments (Latent Heat)
    w_high = np.full(n_agents, 500.0)
    w_low = np.full(n_agents, 50.0)
    
    # Economic Physics
    salary_yr = 55.0
    col_adult_yr = 50.0
    job_penalty = 10.0 # Restart penalty
    
    mu_cap = 0.08    # 8% annual return on savings
    sigma_cap = 0.25 # 25% annual volatility
    
    results = {
        "High SES": {"avg": [], "median": [], "survival": []},
        "Low SES": {"avg": [], "median": [], "survival": []}
    }
    
    np.random.seed(42)
    
    for name, wealth in [("High SES", w_high), ("Low SES", w_low)]:
        w = wealth.copy()
        alive = np.ones(n_agents, dtype=bool)
        unemp_timer = np.zeros(n_agents)
        
        for t in range(steps):
            if np.any(alive):
                # 1. Labor Market Dynamics
                # Check for new shocks
                new_shock = (np.random.rand(n_agents) < shock_prob) & (unemp_timer == 0)
                unemp_timer[new_shock] = unemployment_duration
                
                # Monthly Salary
                monthly_salary = np.full(n_agents, salary_yr * dt)
                monthly_salary[unemp_timer > 0] = 0.0
                
                # Apply Job Penalty at re-employment (end of month 3)
                just_hired = (unemp_timer == 1) 
                w[just_hired & alive] -= job_penalty
                
                # Decrement timer
                unemp_timer[unemp_timer > 0] -= 1
                
                # 2. Capital Growth (Multiplicative)
                z = np.random.normal(0, 1, n_agents)
                growth_mask = (w > 0) & alive
                growth = (mu_cap - 0.5 * sigma_cap**2) * dt + sigma_cap * np.sqrt(dt) * z
                w[growth_mask] *= np.exp(growth[growth_mask])
                
                # 3. Fixed Costs (Eating)
                current_col = col_adult_yr * dt
                w[alive] += monthly_salary[alive] - current_col
                
                # 4. Survival Check
                ruined = (w <= 0) & alive
                alive[ruined] = False
                w[ruined] = 0.0
                
            results[name]["avg"].append(np.mean(w))
            results[name]["median"].append(np.median(w))
            results[name]["survival"].append(np.mean(alive) * 100)

    # Visualization
    fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(20, 6))
    time = np.linspace(0, T, steps)
    
    for name, color, style in [("High SES", "green", "-"), ("Low SES", "red", "--")]:
        ax1.plot(time, results[name]["avg"], label=name, color=color, linestyle=style, linewidth=2)
        ax2.plot(time, results[name]["median"], label=name, color=color, linestyle=style, linewidth=2)
        ax3.plot(time, results[name]["survival"], label=name, color=color, linestyle=style, linewidth=2)
    
    ax1.set_title('Average Wealth (The Illusion)', fontweight='bold')
    ax2.set_title('Median Wealth (The Struggle)', fontweight='bold')
    ax3.set_title('Survival Rate (The Attrition)', fontweight='bold')
    for ax in [ax1, ax2, ax3]:
        ax.grid(True, alpha=0.3)
        ax.legend()
    ax3.set_ylim(0, 105)
    plt.tight_layout()
    plt.show()

run_phase_3_4pct_unemployment()

Phase 4: The Sandwich Generation

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

def run_phase_4_silver_aristocracy():
    # ---------------------------------------------------------
    # 1. Global Parameters (Phase 4 Logic)
    # ---------------------------------------------------------
    n_agents = 5000
    T = 100            # 100-year Post-New Deal Era
    dt = 1/12          # Monthly steps
    steps = int(T / dt)
    np.random.seed(42)
    
    # Endowments (The Inheritance Gap)
    # High SES: $500 (Latent Heat / Buffer)
    # Low SES: $0 (The Sub-Critical Floor)
    w = np.concatenate([np.full(n_agents//2, 500.0), np.full(n_agents//2, 0.0)])
    is_high_ses = np.concatenate([np.ones(n_agents//2, dtype=bool), np.zeros(n_agents//2, dtype=bool)])
    
    # Demographics
    age = np.random.randint(0, 85, n_agents).astype(float)
    unemp_timer = np.zeros(n_agents)
    
    # Child Tracking (Max 3 Children per household)
    n_children = np.zeros(n_agents, dtype=int)
    child_timers = [np.zeros(n_agents) for _ in range(3)] 
    
    # Economic Constants
    salary_yr = 55.0        # Labor Income
    col_adult_yr = 50.0     # Baseline "Eating" Cost
    child_cost_yr = 25.0    # Fixed 50% "Child Tax"
    job_penalty = 10.0      # Restart Haircut (delta)
    parent_threshold = 375.0 # Required wealth (3yrs CoL)
    
    # Market Risk/Return
    mu_cap = 0.08           # 8% "Gifted" Potential
    sigma_cap = 0.25        # 25% "Ferrari" Volatility
    shock_prob = 0.0137     # Calibrated for 4% steady-state unemployment
    unemployment_duration = 3 
    
    # Storage for time-series visualization
    results_median = []
    results_avg = []
    
    # ---------------------------------------------------------
    # 2. Main Simulation Loop
    # ---------------------------------------------------------
    for t in range(steps):
        age += dt
        
        # A. Death & Dynastic Replacement (Inheritance)
        dead = (age >= 85)
        if np.any(dead):
            # The next generation begins - High SES inherit, Low SES reset to 0
            w[dead & is_high_ses] = 500.0
            w[dead & ~is_high_ses] = 0.0
            age[dead] = 0
            n_children[dead] = 0
            for i in range(3): child_timers[i][dead] = 0
            unemp_timer[dead] = 0

        # B. Labor Market (The Effort Bucket)
        is_worker = (age >= 20) & (age < 70)
        is_retiree = (age >= 70) & (age < 85)
        
        # Unemployment shocks
        new_shock = (np.random.rand(n_agents) < shock_prob) & (unemp_timer == 0) & is_worker
        unemp_timer[new_shock] = unemployment_duration
        
        salary_mo = np.zeros(n_agents)
        salary_mo[is_worker & (unemp_timer == 0)] = salary_yr * dt
        
        # Apply Job Penalty (Restart Cost) at the moment of re-employment
        just_hired = (unemp_timer == 1)
        w[just_hired] -= job_penalty
        unemp_timer[unemp_timer > 0] -= 1
        
        # C. The Sandwich Transfer (10% Wage tax from workers to retirees)
        total_transfer_pool = np.sum(salary_mo) * 0.10
        salary_mo[is_worker] *= 0.90 
        
        num_retirees = np.sum(is_retiree)
        if num_retirees > 0:
            w[is_retiree] += (total_transfer_pool / num_retirees)
            
        # D. Capital Growth (The Luck Bucket)
        z = np.random.normal(0, 1, n_agents)
        growth = (mu_cap - 0.5 * sigma_cap**2) * dt + sigma_cap * np.sqrt(dt) * z
        w[w > 0] *= np.exp(growth[w > 0])
        
        # E. The Parent Trap (Reproduction Mechanic)
        can_have_kid = (age >= 25) & (age < 45) & (w >= parent_threshold) & (n_children < 3)
        # Random birth chance if threshold is met
        new_kid = can_have_kid & (np.random.rand(n_agents) < (1/48))
        for i in np.where(new_kid)[0]:
            idx = n_children[i]
            child_timers[idx][i] = 18.0
            n_children[i] += 1
        
        # F. Fixed Drains (Eating + Children)
        active_child_costs = np.zeros(n_agents)
        for i in range(3):
            is_active = child_timers[i] > 0
            active_child_costs[is_active] += (child_cost_yr * dt)
            child_timers[i][is_active] -= dt
        
        w += salary_mo - (col_adult_yr * dt) - active_child_costs
        
        # G. The Ruin Barrier (Volatility Trap)
        w[w < 0.01] = 0.01 
        
        results_median.append(np.median(w))
        results_avg.append(np.mean(w))
        
    # ---------------------------------------------------------
    # 3. Visualization
    # ---------------------------------------------------------
    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 7))
    time = np.linspace(0, T, steps)
    
    # Figure 1: Average vs Median
    ax1.plot(time, results_avg, label='Average Wealth (Ensemble)', color='green', linewidth=2)
    ax1.plot(time, results_median, label='Median Wealth (Typical Agent)', color='red', linestyle='--', linewidth=2)
    ax1.set_title('Figure 1: 100-Year Wealth Divergence (Post-New Deal Era)', fontweight='bold')
    ax1.set_xlabel('Years')
    ax1.set_ylabel('Wealth ($)')
    ax1.legend()
    ax1.grid(True, alpha=0.3)
    
    # Figure 2: Log-Quintile Distribution
    retiree_w = w[(age >= 70) & (age < 85)]
    parent_w = w[(age >= 25) & (age < 45)]

    def get_quintile_means(data):
        if len(data) == 0: return [0.01]*5
        data_sorted = np.sort(data)
        chunks = np.array_split(data_sorted, 5)
        return [np.mean(c) for c in chunks]

    p_quint = get_quintile_means(parent_w)
    r_quint = get_quintile_means(retiree_w)
    
    x = np.arange(5)
    width = 0.35
    ax2.bar(x - width/2, p_quint, width, label='Parents (Ages 25-45)', color='navy', alpha=0.8)
    ax2.bar(x + width/2, r_quint, width, label='Retirees (Ages 70-85)', color='darkorange', alpha=0.8)
    ax2.set_title('Figure 2: Wealth Concentration by Quintile (Log Scale)', fontweight='bold')
    ax2.set_xticks(x)
    ax2.set_xticklabels(['Q1', 'Q2', 'Q3', 'Q4', 'Q5'])
    ax2.set_yscale('log')
    ax2.set_ylabel('Wealth ($)')
    ax2.legend()
    ax2.grid(True, which="both", ls="-", alpha=0.2)
    
    plt.tight_layout()
    plt.show()

# Execution
run_phase_4_silver_aristocracy()

Phase 5: Tax Policy

import numpy as np
import matplotlib.pyplot as plt

def run_comparative_tax_simulation():
    # ---------------------------------------------------------
    # 1. Global Parameters
    # ---------------------------------------------------------
    n_agents = 5000
    T = 100            # 100 Years
    dt = 1/12          # Monthly time steps
    steps = int(T / dt)
    
    # Common Economic Parameters
    salary_yr = 55.0        
    col_adult_yr = 50.0     
    child_cost_yr = 25.0    
    job_penalty = 10.0      
    parent_threshold = 375.0 
    mu_cap = 0.08           # 8% Return (The "Ferrari")
    sigma_cap = 0.25        # 25% Volatility
    shock_prob = 0.0137     # 4% Unemployment Rate
    unemployment_duration = 3 
    
    # The Two Scenarios
    scenarios = [
        {
            "name": "Scenario A: Annual Tax (30% Cap / 0% Estate)", 
            "labor_tax": 0.10, 
            "annual_cap_tax": 0.30, 
            "estate_tax": 0.0
        },
        {
            "name": "Scenario B: Deferred Tax (0% Cap / 50% Estate)", 
            "labor_tax": 0.10, 
            "annual_cap_tax": 0.0, 
            "estate_tax": 0.50
        }
    ]
    
    results = {}

    print(f"Running Simulation for {T} Years with N={n_agents} Agents...")

    for sc in scenarios:
        # Reset Agents
        # High SES start at $500; Low SES start at $0
        w = np.concatenate([np.full(n_agents//2, 500.0), np.full(n_agents//2, 0.0)])
        is_high_ses = np.concatenate([np.ones(n_agents//2, dtype=bool), np.zeros(n_agents//2, dtype=bool)])
        
        # Consistent demographics reset
        np.random.seed(42) 
        age = np.random.randint(0, 85, n_agents).astype(float)
        unemp_timer = np.zeros(n_agents)
        n_children = np.zeros(n_agents, dtype=int)
        child_timers = [np.zeros(n_agents) for _ in range(3)] 
        
        median_history = []
        aggregate_history = []
        
        # Re-seed for loop dynamics
        np.random.seed(42) 

        for t in range(steps):
            age += dt
            
            # --- DEATH & ESTATE TAX (The Harvest) ---
            dead = (age >= 85)
            estate_tax_revenue = 0.0
            
            if np.any(dead):
                dead_wealth = w[dead].copy()
                
                # Apply Estate Tax
                tax_collected = dead_wealth * sc["estate_tax"]
                estate_tax_revenue = np.sum(tax_collected)
                
                # Inheritance (Heir gets the remainder)
                w[dead] -= tax_collected
                
                # Reset Demographics for Heir
                age[dead] = 0
                n_children[dead] = 0
                for i in range(3): child_timers[i][dead] = 0
                unemp_timer[dead] = 0

            # --- LABOR MARKET ---
            is_worker = (age >= 20) & (age < 70)
            
            new_shock = (np.random.rand(n_agents) < shock_prob) & (unemp_timer == 0) & is_worker
            unemp_timer[new_shock] = unemployment_duration
            
            salary_mo = np.zeros(n_agents)
            salary_mo[is_worker & (unemp_timer == 0)] = salary_yr * dt
            
            just_hired = (unemp_timer == 1)
            w[just_hired] -= job_penalty
            unemp_timer[unemp_timer > 0] -= 1
            
            # --- LABOR TAX ---
            tax_labor_rev = np.sum(salary_mo * sc["labor_tax"])
            salary_mo *= (1 - sc["labor_tax"])
            
            # --- CAPITAL GROWTH & ANNUAL TAX ---
            current_w = w.copy()
            z = np.random.normal(0, 1, n_agents)
            growth = (mu_cap - 0.5 * sigma_cap**2) * dt + sigma_cap * np.sqrt(dt) * z
            w[w > 0] *= np.exp(growth[w > 0])
            
            # Annual Capital Tax (Only for Scenario A)
            annual_tax_rev = 0.0
            if sc["annual_cap_tax"] > 0:
                gains = w - current_w
                taxable_gains = np.maximum(gains, 0)
                tax_collected = taxable_gains * sc["annual_cap_tax"]
                annual_tax_rev = np.sum(tax_collected)
                w -= tax_collected
            
            # --- DIVIDEND (The Mechanism) ---
            # Pool all three sources: Labor Tax + Annual Cap Tax + Estate Tax
            total_revenue = tax_labor_rev + annual_tax_rev + estate_tax_revenue
            dividend = total_revenue / n_agents
            w += dividend
            
            # --- COSTS ---
            active_child_costs = np.zeros(n_agents)
            for i in range(3):
                is_active = child_timers[i] > 0
                active_child_costs[is_active] += (child_cost_yr * dt)
                child_timers[i][is_active] -= dt
            
            w += salary_mo - (col_adult_yr * dt) - active_child_costs
            
            # Floor (Absorbing Barrier)
            w[w < 0.01] = 0.01 
            
            # Reproduction
            can_have_kid = (age >= 25) & (age < 45) & (w >= parent_threshold) & (n_children < 3)
            new_kid = can_have_kid & (np.random.rand(n_agents) < (1/48))
            for i in np.where(new_kid)[0]:
                idx = n_children[i]
                child_timers[idx][i] = 18.0
                n_children[i] += 1
            
            median_history.append(np.median(w))
            aggregate_history.append(np.sum(w))
            
        results[sc["name"]] = {"median": median_history, "aggregate": aggregate_history}

    # ---------------------------------------------------------
    # 2. Visualization
    # ---------------------------------------------------------
    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 6))
    time = np.linspace(0, T, steps)
    
    # Plot Aggregate Wealth
    for name, data in results.items():
        color = 'red' if "Annual" in name else 'green'
        style = '--' if "Annual" in name else '-'
        ax1.plot(time, data["aggregate"], label=name, color=color, linestyle=style, linewidth=2)
    
    ax1.set_title('Figure 1: Aggregate Wealth (The Pie)', fontweight='bold')
    ax1.set_ylabel('Total Wealth ($) - Log Scale')
    ax1.set_xlabel('Years')
    ax1.set_yscale('log') # Log scale needed to see the magnitude difference
    ax1.legend()
    ax1.grid(True, which="both", ls="-", alpha=0.2)
    
    # Plot Median Wealth
    for name, data in results.items():
        color = 'red' if "Annual" in name else 'green'
        style = '--' if "Annual" in name else '-'
        ax2.plot(time, data["median"], label=name, color=color, linestyle=style, linewidth=2)
    
    ax2.set_title('Figure 2: Median Wealth (The Household)', fontweight='bold')
    ax2.set_ylabel('Median Wealth ($)')
    ax2.set_xlabel('Years')
    ax2.legend()
    ax2.grid(True, alpha=0.3)
    
    plt.tight_layout()
    plt.show()
    
    # Print Final Stats
    print("\nFinal Statistics (Year 100):")
    for name, data in results.items():
        print(f"{name}:")
        print(f"  Aggregate Wealth: ${data['aggregate'][-1]:,.0f}")
        print(f"  Median Wealth:    ${data['median'][-1]:,.0f}")
        print("-" * 30)

run_comparative_tax_simulation 

Read more

We invoke “American Exceptionalism” constantly without pausing to ask where the idea came from. The origin of the term is far more precise—and far less flattering—than its modern usage suggests. But there is a deeper version of the idea, one that predates the phrase by 150 years, and it begins with a man giving power away.

The First Refusal

In December 1783, George Washington performed an act of political self-denial that the 18th-century world considered a physical impossibility: he resigned. He held absolute command of the Continental Army and the implicit offer of a crown—and he walked away. In doing so, he reached back across two millennia to the Roman ideal of Cincinnatus, proving that the American experiment would be built not on the reach for power, but on the capacity to refuse it. George III reportedly said that if Washington did this, he would be “the greatest man in the world.” He did it.

This is the founding act of American Exceptionalism. Not the Declaration. Not the Constitution. A man to whom the maximum power was given chose to diminish it in favor of the people. Everything that follows in this essay—every crisis, every choice, every failure—is measured against that standard.

Stalin’s Sneer

In the late 1920s, Jay Lovestone, General Secretary of the Communist Party USA, argued that American capitalism was unusually resilient—temporarily exempt from the “universal laws” of Marxist collapse. When Lovestone defended this view in Moscow in 1929, Joseph Stalin responded with fury. He denounced the argument as a “theory of American exceptionalism,” not as praise, but as a sneer. To Stalin, America wasn’t special; it was just behind schedule. Within months, the Great Depression began, and it appeared the “universal laws” were reasserting themselves.

To understand what happened next—and why it matters for 2026—you have to understand what “money” meant to the men who ran America.

Morgan’s Hierarchy: Money vs. Credit

“Money is gold, and nothing else; all the rest is credit.” J.P. Morgan said this to Congress in 1912, and he wasn’t being poetic. He was defining a hierarchy. Bank deposits were merely a promise to pay money—they were credit. And the “Gold Clause,” a contractual legacy of the fear of Civil War Greenbacks, was the creditor’s insurance policy: all debts were repayable in gold coin at the creditor’s option.

In periods of prosperity, the ratio of credit-to-money (gold) functioned as a useful abstraction. But by 1933, the public stopped believing in the promises. They rushed to convert their “credit” into “money”—physical gold and currency. The math was a physical impossibility. The private sector was legally committed to settling $100 billion in gold-linked contracts. The total gold in private hands was approximately $1 billion.

It was a systemic margin call. And because settlement was at the creditor’s option, any government attempt to devalue the dollar would simply trigger the Gold Clause. The nominal value of the debt would have exploded to match the devaluation, wiping out every debtor in the country instantly.

Three New Deals

Confronted with this impossibility, Roosevelt surveyed a world where the classical liberal model had failed. As Wolfgang Schivelbusch outlines in The Three New Deals, the 1930s offered three distinct paths:

The Mussolini Model (The Corporate State): Enforce the creditors’ claims by force. Use the state to suppress the mob and ensure nominal financial claims remain whole.

The Hitler Model (National Socialism): Nationalize the logic of the nation. The state absorbs private property and industry into a monolithic command structure.

The Roosevelt Model (Principled Abrogation): The “Exceptional” Path. Roosevelt—in the tradition of Washington’s resignation—chose to save the private market by attacking the mathematical ghost that haunted it. He used the Pen to abrogate the Gold Clause, performing a surgical strike on the $100 billion liability.

By choosing this path, Roosevelt effectively “printed” $69 billion in equity for the nation. He saved the railroad equity, the farmer’s land, and the average citizen’s bank deposits by sacrificing the creditors’ unrealistic “option.”

This is the distinction that matters: the Refinancer changes the rules to save the system. The Manager picks winners to control it.

The Business Plot and the Black Book

The creditor class did not take the 1933 abrogation lying down. The Business Plot of 1934 was a plan by financiers — including names like Robert Sterling Clark and allegedly Prescott Bush — to overthrow FDR and replace him with a fascist military state.

The plotters approached Major General Smedley Butler, the most decorated Marine in American history. Butler was the “Refinancer” of the military; a man who had already exposed the structural rot of the defense industry in War is a Racket. He held the pedigree to lead a coup and the credibility to sell it to the rank and file. Butler refused. He went to Congress instead.

In the taxonomy of this essay, Butler was Washington’s echo: a man who held the power to become the Manager and chose constraint. Washington resigned a commission. Butler refused one. The pattern of American Exceptionalism isn’t ideological—it’s behavioral. It is the repeated choice of constraint by those to whom the maximum power was offered.

Roosevelt didn’t just survive the plot; he weaponized it. Instead of a public trial that might have sparked revolution, he worked with the McCormack-Dickstein Committee to suppress the most damning names from the final report. He kept the evidence of treason as a private file of kompromat, ensuring the elite’s subsequent obeisance. They didn’t sign on to the New Deal because they believed in it; they signed on because the President held their lives in his desk drawer.

The Epstein Model: Obeisance by Redaction

This is the historical precursor to the Epstein model of governance: a system where the state ensures elite compliance not through the rule of law, but through the possession of the “black book.” Hoover’s FBI ran the same playbook for decades. The mechanism is always the same: you will do what I tell you, or I remove the blackout.

In 2026, the Epstein Files Transparency Act was supposed to break this pattern. Instead, we are witnessing the logic of 1934 perfected. On January 30, 2026, the Department of Justice dumped 3.5 million pages of files, but the “transparency” is a facade. The DOJ has withheld nearly 200,000 pages under “privilege” and has systematically blacked out the names of public figures while “accidentally” exposing the victims.

The true “Black Book” has simply been moved to a DOJ reading room. On February 2, 2026, the administration announced that only members of Congress—the very people most susceptible to institutional leverage—would be allowed to see the unredacted names. The public gets the redacted mess; the Manager gets the leverage. When Deputy Attorney General Todd Blanche stated that there was “nothing in there that allowed us to prosecute anybody,” he wasn’t declaring a lack of crime; he was declaring a refusal to act. The blackout remains the tool of the Manager. “You will do what I tell you, or I remove the blackout.”

Likewise, the investigation into Jerome Powell—a man I loathe for his intellectual incuriosity, but accept is trying his limited best—is a transparent pretext to remove a “for cause” referee and replace him with a political manager. Kevin Warsh is that man. While reshoring strategic minerals is a valid act of national security, it is being used as a license for bespoke management—dictating winners through executive deals.

Roosevelt saved the country as a Refinancer in 1933 but nearly broke it as a Manager by 1937. The “Roosevelt Recession”—triggered by premature fiscal tightening and ongoing interventionist management of industrial relations—proved that even the most skilled Refinancer becomes destructive once he starts believing he can manage outcomes indefinitely. The surgical act saved the system. The ongoing management destabilized it.

Today, we have the worst of both: a state too weak to refinance the structural imbalances and too arrogant to stop managing the chicken coop. But don’t take my word for it. Look at the numbers.

Where the State Actually Fails

The narrative machinery of the current moment—amplified by figures like Elon Musk through X’s new long-form content prizes—wants you fixated on government spending fraud. The inaugural $1 million X article award went to a piece casting Deloitte as a “$74 billion cancer metastasized across America,” alleging that taxpayer dollars were siphoned and that there were revolving doors of insiders. Runners-up included exposés on welfare fraud in Minnesota—state-level fraud, notably, not federal. The awards align neatly with Musk’s DOGE-adjacent critiques of government waste.

Here’s the irony: Musk himself faces fraud accusations ranging from misleading claims about Tesla’s Full Self-Driving capabilities to the controversial SolarCity acquisition—widely seen as a bailout for his cousins’ failing company. But the deeper irony isn’t the hypocrisy. It’s that the entire spending-fraud narrative is a distraction from where the government actually underperforms—not expense management, where it’s roughly on par with the private sector, but revenue collection, where evasion drains far more.

Private companies collect 97–99 cents on every dollar owed. The U.S. government collects 85–87 cents. That is the number that should define the fiscal debate. Everything below explains why it doesn’t.

On the expense side, the federal government loses an estimated 3–7% of its ~$7 trillion in annual outlays to genuine spending fraud—roughly $233–521 billion per year (per GAO estimates isolating willful misrepresentation from documentation errors where payment was substantively proper). That range is mediocre, not catastrophic—and much of it persists due to a principal-agent problem baked into cooperative federalism. States run programs such as Medicaid with federal funds under matching formulas, in which the federal share ranges from 50–90%, thereby diluting the incentive to enforce aggressively. It’s not their money, it’s yours. This is why high-profile cases, such as Minnesota’s Medicaid schemes, arise at the state level.

The private sector, by comparison, loses 1–5% of its ~$45–50 trillion in gross output to occupational fraud and theft, per the ACFE’s 2024 global survey. Government is worse on expenses, but not by the order of magnitude the headlines suggest.

On the revenue side, the picture is devastating. The IRS projects a net tax gap of $606 billion for tax year 2022—roughly 13% of the $4.7 trillion in true tax liability. Two leading government economists disagree about where the worst abuses of that gap live: Guyton (IRS) uses detection-controlled estimation to capture sophisticated evasion that random audits miss—offshore accounts, pass-throughs, complex partnerships—and finds evasion rates rising sharply with income, with the top 1% driving roughly 30% of the gap. Splinter (Joint Committee on Taxation) argues those multipliers overstate true fraud, conflating gray-area documentation issues with willful evasion—the same measurement critique we correctly apply to spending-side “improper payment” figures. Even under Splinter’s more generous methodology, 65–70% of the gap in dollar terms still concentrates at the top. The debate is about the slope of the evasion curve, not its center of mass.

The Fiscal Mirror: The Spend vs. The Collect

The current narrative focuses on the 3–7% expense-side fraud because it suggests the state is a bumbling thief. We must reduce its power! It ignores the 13% revenue-side gap because doing so would reveal that the state is a selective partner.

The Mussolini Model in Fiscal Form

This is where the fiscal data meets the political philosophy. A genuine Refinancer would attack the revenue side, because that’s where the structural failure actually lives. Closing even one-third of the true intentional tax gap would generate more new revenue than almost any realistic spending cut.

But a Manager doesn’t want to fix the revenue side. The revenue gap is the patronage system.

The ability to selectively enforce tax obligations is itself a form of the black book. You collect from those who don’t comply politically; you look away from those who do. Musk's amplification of the Deloitte story on X constitutes the active construction of the managerial frame—the NRA Blue Eagle of 2026, a symbol of compliance. By awarding prizes for exposés on spending, the Manager ensures the public never asks why the most “Exceptional” citizens are the ones least likely to pay the entry fee for the Republic. It tells the public: your problem is that the government spends too much. It never asks: why does the government collect so little from the people who owe the most?

This is the Mussolini model in fiscal form: not the enforcement of rules, but the management of outcomes. The state doesn’t fix the tax code; it uses the broken tax code as leverage.

The Exceptional Path

Exceptionalism was never about American superiority. It was the willingness of a traitor to his class to accept constraint in order to preserve the system. Roosevelt’s genius in 1933 wasn’t that he was powerful—it was that he used power surgically and then stopped. The Refinancer says: I will change this rule, and then the market will sort itself out. Gerald Corrigan in 1987. The Manager says: I will sort it out myself, permanently. Ben Bernanke in 2008. One requires faith in the system. The other requires faith in the manager.

Today, we are fulfilling Stalin’s prophecy—not by collapsing under Marxist laws, but by choosing the corporate state, where the executive manages outcomes rather than enforces rules, and where the public is kept focused on the 3–7% expense-side problem so they never notice the 13% revenue-side catastrophe.

So the questions for 2026 are the same ones that have defined every genuine crisis in this republic: who is the traitor to his class? Who will accept power and then relinquish it in favor of the people? Washington resigned a commission. Butler refused a coup. Roosevelt abrogated a claim, but needed death to be stopped. Our luck is fading, as we acknowledged with the 22nd and 25th amendments. The Exceptional Path requires someone to whom the maximum power was given to choose to diminish it in favor of the people. We used to believe they would do it from civic duty. We were lulled into complacency by Washington.

Is the current candidate the person firing the Federal Reserve chair? Is it the tech billionaire awarding prizes for spending-fraud exposés while his own regulatory history fills a docket? Or is it someone we haven’t met yet—someone willing to enforce the 97–99% collection rate that the private sector considers standard, hold the narrators to the same arithmetic as the narrated, and then accept the constraint of stopping?

I don’t know. But don’t let the headlines distract you. That’s the point.

Section End

Markets In Space!

Well, let’s see how the year is going?

Bitcoin? Pffthhh… and largely for the reasons I hypothesized — ETF selling

Commodities? Little rocky past few days, but looking good so far, Louis.

Public listings of Trillion Dollar IPOs facilitated by early index inclusion?

Wait… what?

Yep. Nasdaq and Elon Musk are effectively weaponizing the savings of passive investors to provide an exit for a billionaire who settled federal fraud charges and was forced out of his Chairmanship for misleading the public.

We are reaching the end stage. Rome is truly a city for sale to a ready buyer, and, as Adam Butler has highlighted, we are monetizing intergenerational trust for short-term profits. But ewe, dear reader, can still play a role. The Nasdaq comment period is open. You can find it here. Damn the torpedoes and sail into the harbor of action. I’ve made it easy for you. Let’s see if 50K subscribers can change the world:

Email address: indexconsultations@nasdaq.com

Subject: Response to Nasdaq-100 Index Consultation – February 2026

To the Nasdaq Index Committee,

I am writing to formally oppose the methodology enhancements outlined in the February 2026 Consultation Paper, specifically the “5x Free Float Multiplier” (Proposal 3) and “Fast Entry” (Proposal 2).

While these proposals are presented as modernizations to ensure the index captures the largest companies, they essentially function as an engine for insider enrichment and leveraged front-running. By artificially inflating the index weights of low-float securities, Nasdaq proposes to subsidize issuers that restrict public access, thereby forcing passive investors to finance a manufactured squeeze.

My specific objections are as follows:

1. The “5x Multiplier” Incentivizes Liquidity Hoarding

The proposal to weight securities with <20% float at five times their actual free float fundamentally breaks the bargain of public listing. Traditionally, to achieve a high index weighting and the associated lower cost of capital, an issuer must provide commensurate liquidity to the public.

Under Proposal 3, Nasdaq is effectively paying insiders to not sell.

• Enrichment of Insiders: By allowing a company to retain 80-90% of its equity while receiving the index flows of a 50% float company, you create a massive multiplier effect on the stock price. This ensures that insider holdings, options, and RSUs move deep in-the-money immediately upon inclusion, driven by mandated passive buying rather than fundamental value.

• Subsidy for Scarcity: This rule penalizes companies that provide true liquidity and subsidizes those that maintain artificial scarcity. It creates a perverse incentive structure where the optimal strategy for a “Top 40” issuer is to float the absolute minimum required to trigger the multiplier.

2. Structuring a “Leveraged Front-Running” Opportunity

The combination of “Fast Entry” (inclusion at Day 15) and the “5x Multiplier” creates a mathematically guaranteed trade for index arbitrageurs.

• The Squeeze Math: Sophisticated market participants will immediately calculate the imbalance: Index Demand > Available Float. When the index is mandated to buy 5x more exposure than the available liquidity supports, a squeeze is not a risk—it is a certainty.

• Predatory Mechanics: Arbitrageurs will “buy like mad” ahead of the index inclusion, cornering the thin float. By the time passive funds execute their mandated buy orders on Day 15, they will be purchasing inventory from these intermediaries at artificially inflated prices.

• The Loser is the Passive Investor: The ultimate purchaser in this chain is the passive index holder (retirement accounts, pension funds). This proposal systematically transfers wealth from these holders to early speculators and corporate insiders.

3. Conclusion

The proposed changes do not merely “modernize” the index; they weaponize it. They turn the Nasdaq-100 into a mechanism that rewards governance structures designed to restrict supply.

If Nasdaq proceeds with Proposal 3, it will engineer a wealth transfer from the investing public to private insiders, using passive flows as the delivery mechanism. I urge the Committee to reject the “5x Float Multiplier” and maintain a link between index weight and tradable liquidity.

Sincerely,

_______

Your Name Here

As always, questions, comments, space garbage, and sofa lint are appreciated.