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During bubbles, investors abandon traditional valuation metrics for unprofitable companies. They create and rationalize new KPIs like user growth or page views to justify sky-high prices, a clear sign of speculative denial.
While giants like Meta and Google have reasonable Price-to-Earnings ratios, this masks the real market speculation. A dot-com style bubble is more visible in smaller public tech companies and private startups with astronomical valuations and no earnings, which more closely resemble speculative darlings like Yahoo in the 2000s.
Despite concerns about an AI bubble, today's valuations are more grounded than those of the dot-com era. OpenAI's $500B valuation equates to about $650 per active user, which is below the ~$700 per monthly visitor valuation Yahoo commanded in 1999. This suggests today's metrics, while imperfect, are less speculative than the historical "eyeballs" standard.
During the bubble, a lack of profits was paradoxically an advantage for tech stocks. It removed traditional valuation metrics like P/E ratios that would have anchored prices to reality. This "valuation vacuum" allowed investors' imaginations and narratives to drive stock prices to speculative heights.
The dot-com era was not fueled by pure naivete. Many investors and professionals were fully aware that valuations were disconnected from reality. The prevailing strategy was to participate in the mania with the belief that they could sell to a "greater fool" before the inevitable bubble popped.
A recurring theme in every historical market bubble is the belief that current events are unique, justifying inflated valuations and risky investments. Recognizing this narrative is a key behavioral signal for investors to exercise caution.
The startup landscape now operates under two different sets of rules. Non-AI companies face intense scrutiny on traditional business fundamentals like profitability. In contrast, AI companies exist in a parallel reality of 'irrational exuberance,' where compelling narratives justify sky-high valuations.
Asnes employs a strict framework before using the word "bubble." He will only apply the label after exhaustively attempting—and failing—to construct a set of assumptions, however improbable, that could justify observed market prices. This separates mere overvaluation from true speculative mania disconnected from reality.
WeWork created "Community Adjusted EBITDA," a metric that conveniently excluded core costs like rent and salaries. This farcical KPI incentivized top-line growth at any cost, masking massive unprofitability and ultimately destroying shareholder value. Be wary of overly creative accounting.
SpaceX's massive valuation (e.g., 100x revenue) defies traditional analysis. Investors aren't buying current cash flows but betting on Elon Musk's track record of achieving the impossible. This "Price-to-Elon" ratio explains the premium his companies command over fundamentals-based valuations.
Instead of a vague label, Cliff Asness uses a rigorous test for a bubble: can you make the math work? He takes a stock like Cisco in 2000, assumes unprecedented growth for a decade, and if the valuation *still* doesn't make sense, he considers it a bubble.