The current market is pricing in a future where AI is the sole engine of economic growth. This singular focus explains the poor performance of other sectors, like the S&P 500 equal weight and Russell 2000, which are struggling despite the headline index's strength. Investors are betting AI can overcome broader economic headwinds.
Despite the S&P 500 being near record highs, the percentage of stocks above their 200-day moving average is alarmingly low, a situation last seen the day after the dot-com peak. This indicates extreme market concentration. However, this condition also existed in 1998, two years before the actual crash.
In the current AI-driven market, traditional one-year forward sales estimates have lost their explanatory power for stock valuations. Instead, a company's multiple is largely determined by its projected sales growth three years out. This long-term focus rewards companies positioned for a sustained hardware buildout, even if near-term results are unremarkable.
The recent spike in global bond yields reflects a robust global growth story, heavily influenced by the AI investment boom. Despite higher yields, inflation expectations (break-evens) remain stable, indicating confidence in central banks. The move is in real yields, suggesting bonds need higher real returns to compete with AI-driven equities.
A large portion of corporate profits stems from two sources perceived as safe: debt-financed AI spending by hyperscalers and government fiscal deficits. This apparent stability supports high market multiples but creates a classic Minskyan dynamic, where prolonged stability encourages leverage and risk, eventually leading to fragility and a potential crisis.
The current stock market rally isn't based on widespread AI productivity gains yet. Instead, analysis from Goldman Sachs suggests about half of the S&P 500's earnings growth this year is directly driven by hyperscalers' massive capital expenditures on AI hardware. The market is rewarding the "picks and shovels" phase of the AI boom.
The current market is characterized by extreme velocity in prices and earnings revisions, a dynamic dubbed "too fast to fade." This speed is attributed to AI compressing economic cycles, the influence of fast-money pod shops, and high retail participation. This makes traditional counter-trend strategies increasingly ineffective and risky.
Historically, the housing market dictated the business cycle through its wealth effects and impact on consumption. Now, the AI infrastructure buildout has taken its place. This massive capital expenditure boom is the new source of construction impulse and wealth creation, making AI, not housing, the central engine of the current economic cycle.
Investors initially treated giants like Walmart and Costco as stand-ins for software stocks threatened by AI, valuing their stable, recurring revenue. As software stocks recovered, capital rotated out of these consumer names, causing their multiples to deflate. They became the assets to “punish” when AI performs well.