I have just finished reading Goldman Sachs’ latest Global Strategy Paper, which discusses how today’s lofty valuations aren’t a bubble because earnings and balance sheets appear solid. But through the lens of classical economics, Hayek’s price theory and Friedman’s monetarism, the real question isn’t whether valuations look justified, but whether valuations come from sound capital signals or easy money.
The research paper claims markets are “not yet in a bubble” and rests on familiar data, price-to-earnings ratios, return on equity, and profit growth. Those aggregates can look reasonable in isolation. But when we zoom out to the monetary environment, the signal changes.
As of August 2025, the U.S. monetary base stood at roughly $5.68 trillion, still more than double its pre-pandemic level. The M2 money stock remains near $22.1 trillion, and the ratio of M2 to GDP continues to hover above longer-term norms. Real M2 growth has flattened, meaning the expansion now expresses itself less in consumer inflation and more in financial-asset inflation (herd behavior), as has the velocity of M2.
Milton Friedman’s lesson was simple: when money supply growth outpaces real output, apparent prosperity reflects liquidity, not productivity. Rising asset prices become a monetary event; therefore, what appears to be earnings strength may actually be multiple expansion fueled by past stimulus. As of today, it’s too soon to know, but it’s worth keeping an eye on.
Austrian theory explains how artificially cheap credit alters the time structure of production when interest rates fall below the natural rate of return, causing capital to shift toward longer-duration, more speculative projects—a phenomenon that Friedrich Hayek referred to as malinvestment.
That’s visible in the current cycle. Multi-trillion-dollar commitments to AI infrastructure, data centers, and venture portfolios make sense in a world of near-zero borrowing costs. But as financing costs normalize, the same projects must clear higher discount rates. What once appeared to be “growth” may prove in the future to be capital mispricing.
In Goldman’s research paper, they discuss Big Tech’s dominance as “unsustainable but not dangerous.” A Hayekian reading would see danger precisely in that alert. When monetary conditions and regulatory preferences favor incumbents, the market’s discovery process weakens. Prices stop conveying dispersed knowledge and start reflecting policy design.
Goldman’s reassurance rests on trust in central banks to engineer a soft landing. Friedman would call that the real bubble, the faith that policymakers can fine-tune demand and liquidity without overshooting.
History argues otherwise. Monetary lags and feedback effects mean that policy adjustments often take effect after long delays. Today, markets appear orderly because the full impact of prior tightening may not have yet taken effect. The Bank of England recently warned that “AI-related stock valuations show early signs of speculative behavior,” echoing a report by The Guardian on October 8, 2025. The next day, Reuters noted that “high stock valuations are sparking investor worries about a market bubble” as capital crowds into the same trades.
A May 2025 study on arXiv introduced a “Capability Realization Rate” model to quantify the gap between AI hype and realized output. It concludes that current valuations likely exceed measurable productivity gains. Does that mean any of this is true? No, but it is a helpful weather vane for us to gauge sentiment against fundamentals.
For our students of capital markets, the lesson is analytical, not alarmist. Prices and sentiment can remain mismatched for years, sometimes long enough to convince nearly everyone that the mismatch is normal. So, this isn’t a forecast of a near-term collapse; such timing is only apparent in retrospect. Rather, it serves as a reminder to observe how fundamentals, politics, and sentiment interact with one another. Market calm doesn’t invalidate risk; it often precedes repricing. To understand how markets work, we need to pay attention to the gap between perception and reality.
