When Bubbles Burst: Lessons From Dotcom to AI

The Minsky Moment framework, named after Harvard economist Hyman Minsky, describes how bubbles collapse in four phases. First, the hedge finance phase, where companies take on debt they can repay from cash flows. Second, the speculative phase, where companies take on more debt than earnings can cover. Third, the Ponzi phase, where companies need new investors just to service existing debt. Finally, the Minsky Moment itself: the culminating event when investors finally catch on and the market suffers a massive collapse.

Rickards maps this framework directly to the current AI boom. He points out that the dotcom bubble followed the same pattern before the Nasdaq plummeted nearly 80%. The 2008 financial crisis followed it before the market fell close to 60%. The Great Depression of 1929 followed it as well. His argument is that AI is now in the Ponzi phase, and the Minsky Moment is imminent.

Rickards draws extensive parallels between today’s AI boom and the dotcom bubble of the late 1990s. During the internet boom, companies spent nearly half a trillion dollars on infrastructure, installing 80 million miles of fiber optic cable across America. Eventually, 85% of those cables went unused. Internet companies spent billions on infrastructure funded by debt they could not repay because they were not making money.

The parallels to today are striking. Tech companies are pouring unfathomable amounts into data centers. Speculative funds say AI will add $200 trillion to the global economy, which is nearly double the size of the entire global economy. The media is once again proclaiming a new paradigm. But underneath the hype, Rickards argues, AI companies are going broke and need new investors just to stay afloat.

Rickards makes perhaps his most provocative claim by comparing data center financing to the subprime CDO crisis of 2008. Private equity funds build data centers, charge AI companies rent, and then combine multiple leases into securities sorted into tranches based on default risk. This is the exact same CDO structure that caused the 2008 financial crisis.

Charlie Warzel of The Atlantic confirmed this practice, writing that private-equity firms put up or raise the money to build a data center, which a tech company will repay through rent, and multiple data-center leases can be combined into a security. Tech journalist Ed Zitron refers to it as subprime AI because it is equivalent to giving no income, no asset loans to subprime borrowers in 2008. David Dayen of The American Prospect said we have a 2000s housing bubble level of financial engineering on top of a 1920s level of private unregulated lending on top of something bigger than a 1990s internet level of technology and infrastructure build-out. Oliver Wyman, a top financial consulting firm, warned that an equity crash like the early 2000s would wipe out approximately $33 trillion of value, more than US GDP.

Rickards pinpoints August 26th as the date the final domino could drop. This is when AI companies like Nvidia, Meta, and Coreweave release their earnings statements. He argues that a single earnings miss could be the pin that pricks the bubble. He draws a historical parallel to March 20, 2000, when Barron’s published an article called Burning Up warning that at least 50 dotcom companies would run out of money within 12 months. Within a week, stocks began to crater. Pets.com, which had IPO’d just one month earlier, plummeted 67% within a month and was bankrupt within nine months.

Rickards also points to September 28, 2007, when NetBank collapsed, marking the beginning of the subprime mortgage cascade. The Minsky Moment always takes everyone by surprise, he says. One day the market is beginning to soar. The next day, a single sobering report comes out and reality sets in.

Rickards introduces the concept of extrapolation bias to explain why most investors will miss the coming crash. People believe that because something has happened in the recent past, it is likely or even inevitable that it will continue happening in the future. This psychological trap makes even the highest IQ people deny a pending disaster, no matter how obvious the danger may be.

Rickards references his experience negotiating the LTCM bailout, where Nobel Prize winners with 150+ IQs managed a fund built on models that assumed the future would look like the past. Those models nearly blew up the entire U.S. economy. Myron Scholes, who developed the Black-Scholes Pricing Model that won a Nobel Prize, was among them. The lesson: intelligence does not immunize against extrapolation bias.

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The package includes six months of Strategic Intelligence plus six special reports: AI Fallout (the biggest AI losers to remove from your portfolio immediately), The AI Black Paper Blueprint (his personal million-dollar roadmap), AI Meltdown Insurance (how to profit from the coming crash), Trump’s AI Arsenal (how investing in AI superweapons could turn $1,000 into $162,000), The Perfect Physical Gold Portfolio, and How to Make Your Home Your Personal Fortress.

Where to Learn More

For the complete analysis, read our AI Black Paper review covering Jim Rickards’ full thesis on the AI Minsky Moment.

Learn more about the AI Minsky Moment framework in our dedicated explainer.

Read our deep dive on circular financing in AI for the full Lucent comparison.

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This is not financial advice. Always do your own research before investing.