Rethinking the Stock-to-Flow Model for Bitcoin: Scarcity Matters — but Demand Rules the Cycle

Table of Contents

Main Points :

  • The Bitcoin Stock-to-Flow (S2F) model is fundamentally a scarcity-based valuation tool, linking Bitcoin’s total supply (stock) to the annual issuance (flow).
  • Prominent analyst André Dragosch (European Head of Research at Bitwise Investments) warns that while the S2F model predicts a peak around US$222,000 for this cycle, it omits a critical piece: the demand side of the market.
  • The rise of institutional demand—especially via spot Bitcoin ETFs and ETPs—has created inflows that exceed the supply shock from the latest halving by more than seven times, thereby altering the supply-demand equation S2F presumes.
  • There is increasing skepticism in the market: traditional scarcity-only models like S2F may be losing relevance in a matured Bitcoin ecosystem where macro-economics, regulation, institutional adoption and speculation all play bigger roles.
  • For investors seeking new crypto assets, income opportunities, or practical blockchain applications, the takeaway is clear: use the S2F model as one reference point, but integrate demand signals, institutional flows, macro context, and on-chain metrics for a more complete outlook.

1. What the S2F Model Is and How It Works

The Stock-to-Flow (S2F) model for Bitcoin is based on a simple yet powerful idea: if you know how many coins (stock) exist already, and how many new coins are being issued per year (flow), then the ratio of stock to flow gives a measure of scarcity. That scarcity, in turn, has been argued to correlate strongly with price.

Using the formula: S2F=Total BTC in circulationNew BTC mined annuallyS2F=New BTC mined annuallyTotal BTC in circulation​

— the higher the ratio, the more scarce the asset is (in theory) and thus the higher the potential price. For example, after the 2024 halving, the S2F ratio for Bitcoin was estimated around 110-120, exceeding even the ratio of gold (~60-70).

Charts of S2F show Bitcoin’s historic price overlaid on a regression line drawn from the S2F ratio. Many analysts point to the model’s ability to track Bitcoin’s bull cycles around halving events.

In short: S2F treats Bitcoin like “digital gold” in virtue of its capped supply and predictable issuance schedule.

2. The Model’s Appeal and Typical Forecasts

Because S2F gives a neat, logical framework for scarcity, it captured the imagination of the crypto community. The argument: Bitcoin’s halving events—occurring roughly every four years—cut the flow of new coins, thus increasing the S2F ratio, which suggests a higher price in subsequent cycles.

Forecasts derived from S2F have ranged widely, for instance, projecting Bitcoin to reach $100,000 or higher in mid-2020s, or even into the hundreds of thousands of dollars in later years.

Because the model is simple and has a clear narrative (“scarcity drives value”), it became widely referenced by both retail and institutional participants.

3. Why the Model Now Deserves Caution

Despite its appeal, the S2F model is now facing strong critique. According to André Dragosch of Bitwise, the core limitation is that S2F focuses almost exclusively on supply-side mechanics (how many coins are issued) and neglects the demand side of the market—the capital flows, institutional adoption, regulatory change, and macro-economic factors.

Key issues highlighted:

  • Institutional investment vehicles (such as spot Bitcoin ETFs and ETPs) have introduced demand that dwarfs the supply-side scarcity created by halvings. Dragosch estimates institutional demand is more than seven times larger than the annual supply reduction from the latest halving.
  • Because the S2F line is derived primarily from historical data and halving cycles, it may no longer capture new structural dynamics in the market (for example, the shift from retail to institutional, rising regulation, and macro-liquidity flows).
  • As markets mature, the “halving → scarcity → price” relationship may weaken or change, especially if demand becomes the dominant driver of price, or if new entrants, altcoins, or regulation alter the narrative.

Therefore, while the S2F model may offer a broad long-term reference, relying on it solely to time investments or set price targets carries risk.

4. What Does This Mean in Today’s Market?

Given these critiques, how should investors and practitioners interpret the S2F model in the current and coming cycles?

4.1 Demand is a critical variable

The rise of institutional capital means that demand is no longer only a function of scarcity and sentiment. Tools like Bitcoin ETFs, treasury allocations by corporates, and wealth-fund entries amplify demand and introduce capital flows that can support prices independent of halving-driven scarcity. For example, some analysts suggest that the price floor for Bitcoin is now meaningfully supported by institutional inflows hovering above the US$100,000 level.

4.2 Scarcity matters—but it’s not everything

The S2F model remains conceptually valuable because Bitcoin’s issuance schedule will still raise its S2F ratio over time. Scarcity does confer value—but scarcity alone does not guarantee price appreciation if demand weakens or other negative factors intervene.

4.3 The broader macro and structural context matters

Several broader factors now influence Bitcoin’s price:

  • Global liquidity conditions and inflation expectations
  • Regulatory developments (e.g., ETF approvals, jurisdictional regulation)
  • On-chain metrics such as exchange flows, accumulation by whales, and MVRV (market-value to realized-value) ratios
  • The competition from altcoins, DeFi, and different token-economies
    As seen in recent reports, traditional valuation frameworks face pressure because of these evolving dimensions.

4.4 Practical take-aways for crypto investors and blockchain practitioners

  • Use the S2F model as a baseline long-term framework, but do not treat it as a standalone predictive tool.
  • Monitor demand-side metrics: institution flows, ETF holdings, corporate treasuries, large-wallet behaviour.
  • Use on-chain analytics and macro overlays rather than only supply-side modelling.
  • For those exploring new crypto assets, consider not just issuance/halving cycles, but tokenomics, real-use cases, network adoption, and institutional interest.
  • For blockchain practitioners considering use-cases (e.g., asset-backed tokens, autonomous trust tender models), recognise that market maturity is shifting from scarcity-narratives to utility, liquidity and institutional infrastructure.

5. A Closer Look at Forecasts: What the Numbers Suggest

Under recent reporting, the S2F model, according to Dragosch, suggests a current implied value of around US$111,000, and a peak of US$222,000 by 2026—if the model’s assumptions hold.

At the same time, the model’s limitations are acknowledged: negative drift in the residuals (i.e., actual price underperforming versus the S2F line), and misspecification concerns (the time-based nature of halvings being conflated with scarcity).

Additionally, recent flow data suggests that institutional demand is now a multiple of the annual reduction in issuance from halving, meaning the supply side (flow cut) is overshadowed by demand side dynamics.

In effect: if the supply shock from the halving once drove the major bull-runs, the next frontier may be driven even more by transformational demand—institutions, new infrastructure, and regulatory change.

6. Implications for Investors, Ecosystem Builders and Blockchain Operators

For Investors Seeking New Crypto Assets & Income Opportunities

  • Apply a layered approach: evaluate scarcity (issuance schedule) and demand (who is buying and why).
  • Be cautious relying on a singular metric—the crypto market has grown more sophisticated.
  • Look beyond Bitcoin: new assets may not follow the same S2F logics; instead focus on token-economics, utility, adoption, and institutional pipelines.
  • Timing: The “halving event” narrative remains meaningful, but may no longer serve as the dominant trigger for massive price moves unless accompanied by demand catalysts.

For Blockchain & Token Ecosystem Builders

  • Incorporate demand engineering: token issuance models matter, but so does how tokens are used, adopted, and demanded by real-world participants.
  • Recognise institutional infrastructure and regulated channels matter: if your token is to attract institutional participants, integrate clarity, compliance, and utility.
  • Consider the broader narrative: As scarcity becomes less of a differentiator (many tokens issue limited supply), how your network drives real use-cases, integrations, and liquidity will matter more.
  • For systems aligning with your “Two-Extremes Model” (Asset-Backed Representation vs Autonomous Trust Tender), note that scarcity alone doesn’t resolve trust or usage; institutional demand, regulatory clarity, and ecosystem maturity come into play.

7. Visual Insertion: Charting the S2F Model

Please insert the following chart here to illustrate the relationship between Bitcoin’s historical price and the S2F model projection:

This visual helps contextualise how actual BTC prices have tracked—but also sometimes diverged—from the S2F‐predicted trendline.

8. Conclusion: Scarcity’s Role Hasn’t Faded But Its Dominance Has Evolved

In summary, the S2F model remains a compelling conceptual framework: Bitcoin is scarce, and its issuance schedule gives it unique token-economic properties. But the market into which Bitcoin is now embedded is far more complex than earlier cycles. Institutional demand, regulated investment vehicles, macro-economic dynamics and evolving token-ecosystems are reshaping how we should view value and opportunity in crypto.

For those looking to uncover new crypto assets, generate income or build blockchain applications, the lesson is clear: don’t rely solely on scarcity metrics. Build your analysis around both supply and demand, understand structural shifts, and orient for practical usage—not just speculative cycles. The S2F model still has value as one piece of your analytic toolkit—but it must be complemented with demand signals and ecosystem insight.

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