Institutional crypto adoption has historically been constrained by structural roadblocks: no regulated spot products, exclusion from retirement plans, unclear custody rules for banks, and punitive capital treatment. Over the past 8 months, those barriers have largely fallen, spot Bitcoin and Ether ETFs launched in 2024, regulatory guidance now explicitly permits bank custody, and 401(k) access is expanding via brokerage windows and policy shifts.
Today, crypto’s ~$4T market cap is just ~1.5% of the ~$272T global equity-and-bond universe. If the average portfolio allocation to crypto rises into the 2–5% range over the next cycle, a plausible shift given the new infrastructure, that implies a steady-state market size of roughly $5–14T before accounting for reflexive price effects or broader asset growth.
The Single Greatest Predictor of Future Stock Market Returns
In The Single Greatest Predictor of Future Stock Market Returns, the author (name unknown, but do check out his blob Philosophical Economics!) introduces a simple but powerful metric for predicting long-term U.S. equity returns: the average investor allocation to equities, defined as the market value of all stocks divided by the market value of all stocks plus the total liabilities of all real economic borrowers (households, corporations, governments, and the rest of the world). This measure requires no valuation inputs like earnings or book value and can be built from Federal Reserve Flow of Funds data. Historically, it has outperformed common valuation metrics such as P/E, CAPE, Tobin’s Q, and Market Cap-to-GDP in forecasting 10-year returns.
The accounting logic starts by grouping all financial assets into cash, bonds, and stocks. Every unit of these assets must be held in someone’s portfolio at all times, and prices adjust to ensure that happens. Cash and bonds increase in supply as the economy grows and borrowers take on debt, either directly from investors (bonds) or through banks (loans creating deposits). Stocks, in contrast, grow very little in net supply because corporations rarely issue more than they buy back or retire through M&A. This imbalance means that to maintain constant equity portfolio allocations in the face of growing cash and bond supply, stock prices must rise over time.
An implication is that if equity allocations are already high, future returns will be smaller because prices must eventually fall to keep allocations in balance; if allocations are low, future returns will be larger as prices rise to restore typical portfolio weights.
Traditional valuation frameworks assume that prices oscillate around “fair” P/E or CAPE levels and that deviations revert over time, creating the inverse correlation between valuation and future returns. But the author argues this misses the actual driver: aggregate investor allocation preferences. Prices change because investors adjust how much of their wealth they want in stocks, not because they consciously target a long-term historical P/E. In other words, if everyone invested n% of their assets into stocks, then stocks will by definition be worth n% of global assets.
Valuation as a concept is not fixed, it’s learned and shaped by market experience. Investors anchor to the valuations they’ve grown accustomed to, which shift higher in bull markets and lower in bear markets. Anchoring and reinforcement from recent returns explain why markets can sustain high or low multiples for long stretches, and why “valuation discipline” often fails to halt or reverse trends until an external shock, like a recession, forces a change in allocations.
This behavior means that valuation rarely provides strong selling pressure except at extremes. During expansions, optimism raises equity appetite; during contractions, fear reduces it. In practice, portfolio allocations are influenced heavily by mechanical investors (like buy-and-hold or target-date fund investors) who rebalance regardless of valuation, and by active allocators whose forecasts of returns are themselves swayed by prevailing sentiment and recent performance. Total return is by definition :
Total Return = Price change from allocation shifts + Price change from cash/bond supply growth (if allocation stays constant) + Dividend yield.
In low-allocation environments, investors gain from both supply growth and from rising allocations (multiple expansion). In high-allocation environments, returns are limited by the drag from falling allocations (multiple contraction). This framework explains episodes like the 1980s bull market, when earnings were flat but prices rose dramatically because investors started from record-low allocations to equities.
Empirical evidence supports the metric. A scatterplot of average equity allocation versus subsequent 10-year S&P 500 total returns shows a tight, linear relationship. As of the article’s writing, the metric implied future nominal returns of roughly 5–6%, with historical analogues ranging from slightly under 5% to about 9%.
However, we note that even if the risk premium on an asset compresses to zero (as they are on stocks at the time of writing), meaning its expected return over safer alternatives is negligible, there is no automatic mechanism forcing prices down. Prices only fall if the preferred allocation to that asset declines. If investors remain comfortable holding the same percentage of their wealth in it, the market can clear at those lofty valuations indefinitely. In other words, valuation alone isn’t gravity; you need a catalyst, often a recession, liquidity squeeze, regulatory shock, or other event that materially changes portfolio preferences, to create sustained selling pressure.
History shows that in many markets, the final stages of an advance can be the most explosive. The power law of returns is a good mental model here: a disproportionate share of total gains often arrives in the last 10–20% of the cycle. In equities, crypto, commodities, you repeatedly see that 70–80% of cycle-to-peak returns can occur in that compressed window, driven by accelerating inflows and reflexivity. The implication is that “too expensive” is not a timing tool. In fact, the period when risk premiums are thinnest can be the very stretch where the largest nominal gains accrue, simply because allocation preference remains high and supply is tight.
Implications for 10-Year Crypto Returns
Let us now consider crypto returns like equities in the original essay: prices clear where investors’ desired portfolio weight in crypto equals the available float. If aggregate portfolios want a higher crypto weight and new supply (net issuance) is scarce, prices must rise to make the existing supply “big enough” to fill that desired weight. Conversely, if desired weight falls, prices must fall. This supply–demand framing tends to explain multi-year returns better than arguing about “fair value.”
For most of the last decade, large institutions had structural barriers to owning crypto directly: (i) no plain-vanilla, ’40-Act-style exposure on major exchanges, (ii) retirement plans couldn’t easily include it, (iii) banks lacked a clear U.S. green light to custody digital assets, and (iv) capital rules for banks penalized exposures. Those frictions suppressed the achievable portfolio weight even for allocators who were philosophically open.
Those frictions cracked in 2024. The SEC approved 11 spot Bitcoin ETFs on Jan 10, 2024, opening mainstream brokerage pipes to the world’s largest asset managers. Then in July 2024, spot Ether ETFs started trading following the SEC’s May approvals, again putting a blue-chip, exchange-listed wrapper around ETH. While workplace plans have historically been the biggest “allocation firewall.” That has now also changed, in August 2025, a new Executive Order directed the Department of Labor to revisit guidance that discouraged crypto in 401(k)s, with the explicit aim of broadening “qualified assets.” It’s not an instant switch, plan sponsors still need to approve, but the policy signal points to wider access.
U.S. national banks got formal custody authority for crypto in OCC Interpretive Letter 1170 (2020). In May 2025, the OCC reiterated and expanded the scope in Interpretive Letter 1184, confirming that OCC-regulated banks may provide custody and execution services for customer-directed crypto assets (with normal third-party risk management). Recent interagency materials also describe crypto safekeeping expectations. Translation: the bank plumbing that large allocators require is now explicitly permitted.
With spot BTC/ETH ETFs live, bank-grade custody clarified, and retirement channels thawing, many CIOs can now express small crypto weights inside normal governance. And they’re doing it: spot Bitcoin ETFs amassed large AUM quickly (BlackRock’s IBIT leapfrogged Grayscale’s legacy trust by mid-2024), and research notes keep flagging ETF-driven inflows as a structural demand source. This is precisely the kind of plumbing shift that raises the mean-reverting “preferred allocation” over a cycle.
As of today, total crypto market cap sits around $3.9–4.0T with BTC ≈ $2.3T and stablecoins ≈ $275B. That’s still tiny versus the other major asset buckets: global equities ≈ $126.7T (2024) and global fixed income ≈ $145.1T (2024). In other words, crypto is roughly ~1.5% of the combined allocation.
Using the supply–demand lens of valuation. If the investable “trad-fi core” (equities + bonds) is about $272T (126.7T + 145.1T), then each 1.5% average portfolio weight implies ~$4T of crypto market value (holding supply constant). Push that to 2–3% and you’re implying ~$5–8T; at 5% you’re implying ~$13–14T; and 10% would imply ~$27T, before considering reflexive effects (price rises create room to hold the desired weight) or new issuance. We also don’t even assume an expansion in the price of assets in general, but instead just use arithmetic on today’s capital-market base.
Crypto’s net new supply is structurally constrained: BTC issuance halves on schedule; ETH burn can offset issuance during high activity. Meanwhile, the supply of “everything else” (cash/bonds/equities) keeps growing with credit and earnings. If the preferred crypto allocation nudges up even modestly, thanks to ETFs, bank channels, retirement access, the clearing price must adjust upward over time to keep the percentage weight constant. That’s the same mechanism that pushed equities higher across decades despite modest net share issuance.
This isn’t a one-way street. Policy can reverse. And crypto is volatile; recessions and liquidity shocks can drop the preferred allocation sharply (and thus price). But the plumbing that once capped allocation near zero has changed: ETFs, bank custody, prudential templates, and an on-ramp for retirement plans now exist.
Some will argue “it’s all priced in,” but the equity example shows why that’s not a usable trading rule. Even if you can predict 10-year returns with an R² of 0.9, you still can’t place a high-confidence trade today because you don’t know the path. The journey to a 200–300% increase in crypto market cap could involve drawdowns of 50%, 75%, or even 90% along the way. The supply–demand dynamics make the long-term hold case strong, but they say nothing about the sequence of gains and losses between here and there. In allocation-driven markets, path risk is the price of admission for capturing the end-point.
Relative to $272T in global equities+bonds, crypto at $4T is still small. If the average institutional+retail allocation settles into a 2–5% band over the next cycle, a steady-state range of roughly $5–14T is plausible on today’s base, higher if (a) the underlying asset base grows, (b) allocators lean toward the top of that band, or (c) reflexivity amplifies price on limited net issuance. That’s the allocation framework’s core claim: access lowers frictions → desired weight rises → price must clear at a larger market cap, absent a fall in preference.
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