A different question produces a different model

“Where is Bitcoin’s price going?” skips the question that matters first: what job could Bitcoin do, for whom, and at what scale? Bitcoin Valuation Lab starts with the markets people use to hold wealth. It projects the size of that comparison universe and asks what a chosen Bitcoin share would imply.

This is the market-disruption question used in venture investing, adapted to a monetary asset. We are not assigning Bitcoin a company’s revenue multiple. We are calculating a conditional monetary valuation from a market size, an assumed share and a supply denominator.

Mark’s v1 thesis is deliberately visible: 1.5% of the combined store-of-value universe in 2030, 8% in 2040 and 15% in 2050. You do not have to agree. The calculator lets you change the shares without rewriting the historical evidence.

Two levers. One transparent equation.

Lever one is the size of the market. Historical monetary relationships and a frozen economic path inform the future size of the store-of-value, or SOV, universe. This part contains estimates and explicit long-run extrapolations.

Lever two is adoption. You decide what percentage Bitcoin represents. The current presets are scenario judgments, not probabilities, measured migration rates or forecasts issued by a bank.

The supply convention converts capitalization into a per-coin value. It does not create demand. A constrained supply schedule is compatible with many possible prices, including a much lower price if demand weakens.

Four labels that make the model readable

The same labels appear in the basket notes, technical appendix and source library. Passing software tests does not upgrade an assumed input into an observed fact.

How to use the lab

Start in Simple mode. Choose a monetary path, select a preset, and change one Bitcoin-share assumption. Watch market capitalization and price respond while the market-growth path remains fixed.

Next, keep adoption fixed and change the monetary path. That isolates a different question: how much does the result depend on money continuing to expand relative to economic output?

Use By market only when you want to assign capture separately to gold, property, bonds, loans, equities, money and collectibles. In that mode, the combined Bitcoin share is an output. It does not also obey your Simple-mode preset.

No wallet, brokerage account, live quote, personal balance sheet or subscription is required. This release runs offline and does not send your inputs anywhere.

The frozen 2025 working baseline

The credit-corrected incumbent basket totals $994.13T. Adding the retained Bitcoin starting value once gives a combined comparison of $995.87T. “Nearly one quadrillion dollars” is a rounded description of that modeled baseline, not a new current wealth survey.

The categories do not all have an independently observed December 31 closing value. Dates and transformations remain visible below. Future category shares describe this chosen gross inventory, not shares of all household net worth.

Real estate: compete for the savings role, not the building

Property can provide shelter, rent, productive land and a way to hold wealth. The model includes the broad all-property estimate, rather than pretending there is an observed global split between an investment component and an owner-occupied component.

The frozen source is Savills’ $393.30T end-2024 estimate. The model’s $408.79T 2025 amount is an explicit one-year bridge. Bitcoin capture denotes a hypothetical reallocation of some savings-related value. It does not mean Bitcoin provides housing, rental income or agricultural output.

Bonds and equities: different economic claims

Debt securities are outstanding negotiable obligations. They include more than sovereign bonds, and their source valuation conventions are not uniformly market-price marks. Listed equities represent ownership claims on companies. The model uses total capitalization, not an index’s dividend-reinvested return.

For equity, v1 retains a documented working adjustment to the India component. This is not an official correction by the publisher. A future data revision should be versioned rather than silently substituted into the calculator.

Bitcoin can be proposed as an alternative for some discretionary savings allocation, but it does not replace a bond’s contractual payment or a company’s productive earnings. The fraction that might switch remains an adoption assumption.

Why the loan category was added

Removing broad credit solved one duplication risk but also omitted identifiable loan-form claims. The targeted correction adds $70.22T from specified China, U.S. and euro-area loan series. It does not calculate a residual by subtracting unrelated money and securities totals from an IIF headline.

The selection uses China’s listed RMB, FX, entrusted and trust loan components; U.S. commercial-bank loans and leases; and the euro-area private-sector loan stock without the loan-transfer adjustment. The inputs, currency conversions and source definitions are available in the credit bridge download.

This is covered loan-form credit, not a complete global non-securitized-loan census. Some loans may remain on a bank’s balance sheet while a linked vehicle issues securities. That economic linkage has not been fully removed. Missing countries and lender classes are unmeasured, not zero.

Gold, money and collectibles: three different evidence standards

Gold means the retained estimate of all above-ground metal, marked at the corresponding bullion price. It is broader than private investment bullion. The model does not count gold funds on top of the metal they represent.

Money starts with an attributed $144.00T broad global compilation. Historical growth comes from a scaled U.S.-China-euro-area proxy. Broad money is more than physical currency, and the source definitions may include liquid securities or fund claims.

Art and collectibles use Mark’s explicitly unverified $18T art plus $6T other-collectibles estimate for 2023, assumed disjoint and bridged to 2025. The much smaller Deloitte UHNW estimate covers a different owner population; it does not validate the all-holder figure. Jewelry and collectible coins may also overlap bullion value.

A finite pie is an accounting convention, not a claim that overlap vanished

A property, a loan secured by it, an equity interest in its owner, and a deposit funding a lender can be distinct gross claims linked to the same economic activity. Adding them does not create an equal amount of unique net wealth.

The model reduces obvious literal repetition and makes its chosen categories explicit. It does not claim to have consolidated every financial intermediary or removed every look-through exposure. Its finite-pie rule keeps scenario outputs arithmetically coherent; it does not transform the basket into cash that could all migrate into Bitcoin.

Keep this distinction in any chart caption: modeled gross store-of-value comparison universe, not “all the money in the world.”

Three comparable-core anchors, not fifty complete annual observations

The retained five-category core includes money, gold, property, debt securities and equities. It excludes art and the later loan addition because matching historical stocks were not established. The historical money series is scaled to the working global anchor; it is not a direct worldwide census at each date.

The 2025 historical-core total is therefore smaller than the corrected seven-category starting basket. We do not join those two totals into one uninterrupted historical growth chart.

Measure elapsed time, not the number of rows

For comparable endpoints, annualized growth is (ending value / starting value)^(1 / elapsed years) − 1. A five-row lag is not necessarily five years. That distinction mattered when the early source files contained irregular intervals.

On the retained core, the 2015–2025 annualized rate is approximately 7.10%, compared with 6.71% for the scaled monetary proxy. The core’s earlier half-decade is approximately 8.67%; the later half-decade is approximately 5.55%. These describe selected endpoints and coverage, not a law that every asset’s growth must slow.

The historical observations are useful context. They do not by themselves establish causality, a stable money-to-asset response coefficient, or the next 25 years of growth.

Relative shares matter as much as absolute growth

An asset can rise in dollar value while losing share of the basket. Conversely, an unusually strong valuation period can make its share rise rapidly. We therefore examine each asset relative to the chosen core, rather than simply extending its fastest recent absolute CAGR.

The selected property drift is approximately −0.60% a year in log relative weight; equities use approximately +1.06%. Gold, bonds, collectibles and the added loans use zero selected relative-weight drift before normalization. Zero here means a neutral allocation assumption where evidence was insufficient or disrupted, not zero dollar growth.

The gold result is deliberately not described as a 30- or 50-year full-basket finding. The longer retained comparison was only a partial financial basket. Bond history also crosses a coverage change, and the property and equity vintages have limitations. Those gaps are a reason to label assumptions, not to hide them.

What this history does not tell us

It does not prove that faster M2 mechanically causes a particular Bitcoin return. It does not show a smooth, universal trend for every store of value. It does not measure the amount of each market that Bitcoin can take.

Nor does a larger dollar addition prove accelerating percentage growth. A larger base can produce a larger dollar increase at the same or even a lower annual rate.

The practical standard for this educational model is traceable evidence and correct mathematics. Sparse endpoints remain sparse. Interpolations and bridges stay labeled. A growth assumption does not become a fact just because the program reproduces it.

Follow the active path

The calculator does not choose seven unrelated future asset returns. It first projects money, then the size of the non-money pool relative to money. Asset weights allocate that pool. Changing a category’s relative-weight assumption changes the mix, not the externally determined total.

The active institutional starting point is the retained April 2026 IMF nominal-world-output series at market exchange rates. The published table includes $118.176T for 2025 and $158.392T for 2031. These are economic-output levels, not SOV stocks and not amounts added directly to the basket.

From economic output to the money path

The historical monetary proxy combines U.S. M2, China M2 and euro-area M3. In the reference path, the model preserves the 2018–2025 log-growth difference between that proxy and nominal world GDP. This is the monetary-deepening assumption: money continues changing relative to the scale of economic activity.

The retained reference drift is approximately 0.021341 log units a year. The shorter 2020–2025 alternative is approximately −0.006947. Those periods tell different stories. The reference implies roughly 7.02% annual money growth through 2050; it is not a reliable law estimated from a long stable sample.

The world-scale baseline uses $144T, while the historical relationship uses a narrower geography. Applying a constant scale does not make that history a direct observation of every country’s money supply.

From money to the finite pie

Let M be money and N be the non-money store-of-value pool. The model carries forward the selected historical drift in N/M. The retained annual log drift is 0.005784, approximately 0.58% in log terms.

That drift was calculated from the available gold-property-equity numerator relative to money over 2015–2025. Bonds were omitted from that calibration because of the source break; art lacked comparable history. Applying the drift to the larger current pool, including added loans, is a disclosed transfer assumption.

Money plus the non-money pool gives the incumbent total. A small starting-state bridge includes existing Bitcoin once, giving the combined comparison used for the price calculation. No separate credit-growth, inflation or AI multiplier is added on top.

What each institution does and does not supply

These roles are not a single sequential chain in which every source causes the next calculation. In the released finite-pie engine, CBO and the retained BIS liquidity commentary are context rather than active multipliers.

Where institutional forecasts stop

The retained IMF appendix supplies 2025, 2026, 2027 and 2031 nominal-output levels. Values for 2028–2030 are geometric model interpolations. After 2031, the model extends the 2027–2031 terminal GDP growth rate, approximately 4.68%, and continues the selected monetary-deepening assumption.

CBO’s long-term material has its own U.S. horizon. Its existence does not turn the global 2040 and 2050 paths into institutional forecasts. The extension is the model’s choice, and the source library preserves that distinction.

Begin with the job, the market and the reason to switch

A useful venture question is not “what stock price do we need?” It is “what problem does this product solve, how many customers could choose it, and how much economic activity could it win?” Bitcoin’s proposed job in this model is portable, verifiable, scarce long-term savings.

The v1 sequence is market size, market growth, assumed penetration, then implied value. It deliberately does not pretend that the penetration has already been derived from customer cohorts. Reach, retention and allocation expansion are the proposed v2.0 upgrade.

In 2014, Uber investor Bill Gurley argued that better service could expand addressable demand beyond the historical taxi market and that assumed share ceilings needed a rationale. That is a useful challenge to a narrow denominator. It is an investor’s argument, not a rule that any superior product achieves a particular market share.

What changes when the product is Bitcoin

For an AI application, a successful trial is not the same as organization-wide usage. Bessemer emphasizes retention and expansion into recurring workflows. That distinction transfers as a modeling question: Bitcoin adoption should ultimately concern retained capital, not only wallets or app downloads.

A share of annual rides or room nights is a flow measure. A share of the SOV universe is a stock-value measure. V1 does not insert “Uber or Airbnb took 10%” as a Bitcoin coefficient, nor does it equate a company’s market capitalization with a share of the property it helps users book.

Turn product advantages into hypotheses about behavior

Bitcoin’s design allows peer-to-peer transfer, self-custody, public verification and a constrained issuance schedule. Those characteristics can be attractive for particular savings needs. Holding through a volatile market, securing keys and meeting fixed nominal obligations create different considerations.

Mark’s thesis is that these advantages become sufficiently compelling to win a much larger savings role. The model does not quantify the statement “100 times better,” and it does not apply a 100× premium to an asset value.

The behavioral questions are concrete: does easier access bring in more retained capital? Do adopters maintain larger allocations? Do treasury and investment mandates permit meaningful holdings? Do people continue choosing Bitcoin after a severe drawdown? Product quality must eventually show up in those choices, not only in a persuasive analogy.

AI is an adoption channel, not an automatic valuation bonus

Lightning Labs documents tools for Bitcoin-based agent transactions. Coinbase also documents an agent-payment route using a stablecoin. Technical availability establishes possible payment channels, not the amount of savings that will remain in Bitcoin.

For AI to support a higher Bitcoin share, owners or operators would need to choose sustained Bitcoin savings, reserve, collateral or working balances. Rapid transactions with small balances can create high volume without proportionate retained value.

V1 adds no standalone AI growth multiplier. A future model could make access, retention or allocation respond to specific AI channels, while testing competing implementations. That work is deliberately deferred rather than smuggled into the present numbers.

The three whole-pie presets

Mark’s Thesis is the default. It assigns Bitcoin 1.5%, 8% and 15% of the modeled combined pie at the three milestones. The earlier 1.25% / 5% / 10% path remains available as “Conservative thesis.” That name means lower assumed capture relative to the other presets, not objectively low risk, a confidence level or a statistically conservative forecast.

The High Adoption preset uses 2%, 10% and 20%. None of these is a measured future adoption rate. The numeric controls also accept custom shares and do not require them to increase over time.

What the default calculates

These prices are arithmetic consequences of the chosen market path and capture fractions. They are not fixed annual Bitcoin growth-rate inputs, nor does the calculator estimate the probability of reaching them.

The strongest explanation is conditional: “This is my adoption thesis. Here is the projected market it applies to, and here is what the math implies.” Readers can disagree with either the market path or the share assumptions without disputing the arithmetic.

What would have to happen?

For the stronger paths to be persuasive, Bitcoin would need to move beyond occasional trial positions into durable savings behavior. Distribution would have to broaden, custody and operating practices would have to support continued participation, and enough holders would need to retain or increase their allocations through difficult periods.

Institutional and treasury adoption would need to be economically meaningful, not merely permission to purchase a small amount. Digital commerce or AI use would need to create sustained balances rather than transaction volume alone. Alternative stores of value and competing monetary technologies would still exist.

These are underwriting conditions, not five newly fitted coefficients. The model supplies no independent probability that they occur. A 15% share of this gross comparison universe is a substantial monetary-adoption thesis even though other large categories can still be larger.

Whole-pie share and category capture answer different questions

Simple mode asks, “What percentage of the entire combined universe does Bitcoin represent?” A 15% answer determines Bitcoin’s total capitalization and the aggregate residual. It does not uniquely determine how much gold or property remains.

By-market mode asks, “What effective fraction of each category is attributed to Bitcoin?” The program sums those contributions, subtracts each from its counterfactual category allocation, and calculates the resulting Bitcoin share.

The reset values in By-market mode are retained illustrative category settings, not a derivation of Mark’s whole-pie preset. Other credit mechanically matches the bond setting. Both modes preserve one finite pie, but their inputs are intentionally independent.

Bitcoin versus remaining gold appears only in By-market mode. At 100% gold capture, remaining gold is zero and the ratio is undefined; the app says so instead of displaying a misleading infinity.

A worked example with round numbers

Suppose the projected comparison universe were $2 quadrillion, Bitcoin’s assumed share were 5%, and the supply denominator were 21 million. Bitcoin capitalization would be $100 trillion. Dividing that by 21 million produces approximately $4.76 million per coin.

That is an illustration of the equation, not one of the released milestone forecasts. The app uses the retained, more precise pie and supply values. A large calculated capitalization does not mean the model has estimated an equal quantity of new cash inflows.

Same adoption. Different monetary paths.

The table holds Mark’s default 2050 share at 15% and uses the same supply denominator. Only the retained monetary control changes.

No continued monetary deepening removes the persistent rise in the money/GDP ratio. Recent monetary growth uses the shorter retained ratio trend instead. These are two specific tests of the monetary assumption, not arbitrary lower and upper forecasts.

Same market. Different adoption.

Now hold the reference pie fixed and change only the Bitcoin-share preset. This is the separate adoption question.

At a fixed pie and supply, doubling the share doubles the implied price. That is a mathematical identity, not evidence that adoption itself can be doubled. The app makes this dependence visible so the reader can see where conviction enters.

Nominal dollars are not unchanged purchasing power

The headline outputs are future nominal U.S. dollars. They do not have the same purchasing power as a dollar in 2025.

For illustration, the retained 2.3% annual consumer-inflation assumption makes a 2050 dollar worth approximately 0.57 dollars in 2025 consumer purchasing power. On that assumption, the default reference 2050 price of $43,977,147 is approximately $24,907,848 in 2025 dollars.

This is an illustration, not a new inflation forecast. SOV-market growth is not the same thing as consumer-price inflation. No inflation uplift is added to the nominal forecast a second time.

These tables are not a safe range

The lowest displayed preset is not a floor for Bitcoin. The controls do not exhaust possible technical, competitive, monetary or demand outcomes. A much smaller share, slower market growth, or both can produce a substantially lower result; zero future share produces zero modeled allocation.

The most informative test is specific: identify the disputed assumption, change it, and hold the rest fixed. The uncertainty does not disappear because the output is precise to the dollar. That precision is useful for checking arithmetic, not for claiming forecasting accuracy.

In the calculator, use the macro selector for the market question and the sliders for the adoption question. Export the selected scenario with its version and assumptions so another reader can reproduce exactly what you changed.

1. The measurement perimeter

All model stock values are in nominal USD trillions; one trillion is 10¹² dollars and one quadrillion is 1,000 trillion. The model retains gross real assets and financial claims, with incomplete consolidation and heterogeneous valuation conventions. This is not an investable portfolio or a market-cap-weighted security index.

The reference baseline is 2025, assembled using releases available in the research cutoffs. Some 2025 values are bridges from 2024, and the art reference begins as an unverified 2023 input. Retrieval dates are separate from observation dates. A 2026 publication can report a 2025 observation without converting a 2026 observation into 2025 data.

Version 1 freezes these estimates. A source website changing after release does not automatically alter the app.

2. Market-path equations

Let t be the target year, τ = t − 2025, M_t the modeled broad-money stock, and V_i,0 each non-money category’s starting value. The non-money starting pool N₀ includes the new covered loan category.

The frozen ratio drift d_R is 0.005784085289. Money is generated upstream from the retained IMF nominal-GDP path and the historical money/GDP drift. Reference and the two monetary controls are exported exactly, not recreated from rounded headline totals.

Property’s selected relative log drift is -0.005963207; equity’s is 0.010576055; the other non-money drifts are zero. A category’s selected drift is not its final percentage change in share after normalization. The normalizing denominator changes too.

3. The added loan calculation

The six selected loan-form inputs are converted and summed. The China rows use 268.4 + 1.05 + 11.35 + 4.67 trillion CNY, multiplied by 1.1750 / 8.2262 USD per CNY. U.S. loans and leases use 13,433.4 billion USD / 1,000. The euro-area input uses 13,630 billion EUR × 1.1750 / 1,000.

This amount increases N₀, not the selected historical drift. Its initial raw relative weight is based on the added stock and its selected drift is zero. Future values of other categories can change slightly through normalization even though their historical starting values and drift assumptions remain unchanged.

No compatible long historical aggregate for this precise loan perimeter was established. The future treatment is therefore a neutral relative-weight convention, not an empirically measured loan-growth forecast.

4. Bitcoin enters the combined starting pie once

The retained Bitcoin observation is 2025-12-31T00:00:00.000Z: price $87,509, publisher circulating supply 19,969,815 BTC and capitalization $1.75T. Its timestamp is the start of December 31, not an exact common close for all incumbent markets.

The bridge preserves the existing Bitcoin stock once without an independent growth bonus. Its common initial bookkeeping fraction is B₀ / (I₀ + B₀), approximately 0.1755%.

This proportional bookkeeping is not an observed history of which asset holders sold to buy Bitcoin. It must not be presented as such.

5. Capture and residual accounting

h is the whole-pie fraction, not the percentage number typed in the control. The app converts 15% to 0.15. Category residuals are unspecified in Simple mode.

The money category participates in the category sum. Total Bitcoin plus all residuals equals the combined pie. Capture fractions replace the initial fraction rather than being added to it, so existing Bitcoin is not counted again.

Market capitalization is a price-times-units valuation. It is not a calculation of net dollars that must enter the asset. The one-for-one residual rule is this model’s scenario convention, not a universal claim about market-price dynamics.

6. Supply, timing and rounding

The retained implementation uses an idealized 600-second block interval and the halving schedule, calibrated to a publisher circulating-supply observation. It advances an equivalent issuance coordinate, not an independently retrieved future chain height. Unclaimed rewards, actual block timing and supply-provider definitions can differ.

No lost-coin haircut, constrained liquid float or scarcity multiplier is added. Headline figures round for readability; the downloadable model retains full working precision. The app uses milestones only and does not draw a supposed daily Bitcoin forecast between them.

7. One calculation source for web, tables and downloads

The release contains a frozen model configuration and one shared JavaScript calculator engine. The browser, preset-result export and build-time report tables use that engine. The displayed monetary categories are not manually copied from earlier rounded examples.

Checks cover reference-output parity, all preset inputs, all monetary paths, category sums, zero/100% capture, invalid numeric input, residual conservation, mode independence, and browser behavior. Separate source metadata identify evidence limits. A passing calculation test cannot certify future economic behavior.

The build metadata records input hashes and the exact release identifier. Earlier research files remain unchanged; restricted publisher material is not embedded in the public site. Source citations link to original publishers, while the release provides its own derived model tables for inspection.

Is this a forecast or a thought experiment?

It is a conditional projection model. Historical evidence and selected relationships inform the future market path, while Bitcoin’s market share is explicitly assumed. A reader can use it to examine a thesis without treating the displayed price as the most likely outcome.

Calling it a scenario does not excuse incorrect numbers. It makes the assumptions that produce the numbers visible.

Does Bitcoin have to take all of gold’s value?

No. Bitcoin can receive modeled contributions from several categories. In the finite-pie convention, a category may grow in dollar value while losing relative share. A total Bitcoin target alone does not determine which categories surrender that share.

Simple mode therefore compares Bitcoin with the rest of the pie, not with an invented residual gold figure. By-market mode calculates the residual gold implied by your chosen category inputs.

Why not multiply Bitcoin by AI payment volume?

A payment is an activity over time. A savings balance is a stock at a time. The same balance can finance many transactions. Multiplying an activity forecast by an arbitrary factor would add a new model, not simply improve this one.

AI may matter if it changes sustained balances or allocations. V1 explains that possible channel but assigns no numerical AI premium.

Is the basket bigger than net wealth?

It can be, because it counts real assets and several layers of financial claims. A bond, a loan and an equity claim can be different instruments without being independent underlying wealth. The $995.87T combined starting number is a modeled gross comparison, not a consolidated net-wealth census.

Broad credit is not added again on top of money, securities and the selected loan-form bucket. Remaining look-through overlap is disclosed rather than declared solved.

Why is the baseline 2025 rather than today?

This is a frozen research release assembled from dated observations and estimates. A current Bitcoin quote would not make the rest of the global basket current. Mixing a live quote with stale market stocks would introduce a new date mismatch.

Future revisions can update the model as a dated version. The current app deliberately has no live API dependency.

A short glossary

What belongs in version 2.0?

The deferred work is a behavioral adoption model: reachable capital, new adopters, retention, and allocation expansion. It could compare those mechanisms with Mark’s explicit whole-pie milestones, rather than replace them silently.

Version 1 is intentionally finished without that upgrade. No later model, source update or category migration is implied to be running in the background.