The Bubble Triangle

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Many investors today are drawing parallels between the current AI investment cycle and the Dot-Com bubble of the late 1990s/early 2000s.

Technology stocks now comprise over 50% of the S&P 500. Major tech companies are also committing hundreds of billions to AI infrastructure despite evidence suggesting AI initiatives have yet to deliver meaningful gains in revenue or profitability.

To help evaluate whether we're experiencing another dangerous bubble, we read William Quinn and John D. Turner's "Boom and Bust: A Global History of Financial Bubbles" (2020).

This book introduces the “bubble triangle” as a predictive tool, analyzes the Dot-Com bubble through this lens, and provides insights on predicting future bubbles.

Quinn and Turner propose thinking of financial bubbles like fires: self-perpetuating and difficult to control once started.

Just as the fire triangle consists of oxygen, fuel, and heat, the bubble triangle requires (1) marketability, (2) money/credit, and (3) speculation.

Marketability represents how easily an asset can be bought and sold. Like oxygen for fire, it's always present to some extent and essential for markets to function, but too much creates danger.

Quinn and Turner identify five key factors that determine an asset's marketability:

The authors note that bubbles frequently follow financial innovations that enhance one or more of these factors.

During the 2007-2010 Subprime bubble, mortgage-backed securities transformed individual home loans that banks previously held to maturity into tradeable securities that could be bought and sold like stocks. This innovation improved both divisibility (investors could buy portions of mortgage pools) and the ease of finding counterparties (through liquid secondary markets).

Online trading platforms have similarly revolutionized marketability by reducing/eliminating transaction costs and enabling digital transferability, allowing millions of investors to trade from home at any hour.

Each innovation made assets that were previously difficult to trade suddenly easy to buy and sell, creating the conditions for speculation to flourish.

Bubbles require abundant capital for investment, making them much more likely when money and credit flow freely. Low interest rates and loose lending standards stimulate bubbles through two mechanisms.

First, investors can purchase bubble assets with borrowed money, driving prices higher.

Since neither banks nor borrowers bear full responsibility for losses, both take greater risks. The more credit expands, the higher bubble assets rise, until investors start selling to repay loans and trigger a collapse.

Second, low rates on safe assets push investors to "reach for yield" in riskier investments.

If government bonds or bank deposits pay minimal returns, investors chase higher yields in stocks, real estate, or other volatile assets regardless of risk.

When banking systems become exposed to bubble assets, the economic damage multiplies exponentially. Banks that fail can trigger chains of bankruptcies affecting businesses with no connection to the original bubble, spreading financial contagion throughout the economy.

Speculation means buying assets solely to sell them later at higher prices, providing the heat that sustains bubbles.

While some speculation always exists, bubbles see masses of novices becoming momentum traders, buying when prices rise and selling when they fall.

Just as fire generates its own heat, speculation becomes self-reinforcing: early speculators profit spectacularly, attracting more speculative money, driving further price increases.

Experienced traders and institutional investors take advantage of this momentum by knowingly buying overpriced assets, planning to sell to "a greater fool" in what traders call "riding the bubble."

Speculation intensifies when investors face limited downside risk.

Quinn and Turner identify three common scenarios where losses are capped while gains remain unlimited:

Short selling could theoretically cool speculation, but it's often restricted, expensive, or extremely risky since potential losses are unlimited if prices keep rising.

The Dot-Com bubble demonstrated what happens when all three elements of the bubble triangle reach extreme levels simultaneously.

Between March 1990 and March 2000, the NASDAQ index rose 1,055%, with technology shares reaching valuations that implied "an implausible rate of growth in profits."

Quinn and Turner explain that bubbles need a spark to ignite, which can come from either technological innovation or government policy.

For the Dot-Com bubble, the spark was the internet's transformation of computing from standalone machines into a global network where each additional user made the system exponentially more valuable.

Netscape's 1995 IPO established the new approach when it went public before turning a profit, used the offering as a marketing event, and saw first-day returns of 107%. This became the standard playbook, with the median age of public companies dropping from 9 years in 1990-94 to just 5 years in 1999-2000.

All three sides of the bubble triangle intensified throughout the 1990s…

Marketability reached unprecedented levels:

Money and credit flowed abundantly:

Speculation became rampant:

These conditions were sustained by new era narratives that justified astronomical valuations.

For instance, authors published books like "Dow 36,000" arguing the index would quickly triple, while analyst "sell" recommendations virtually disappeared, dropping from 9% in 1989 to just 1% by 1999.

When the bubble burst, the NASDAQ lost 77% by October 2002. Internet stocks gave back their entire 1,000% gains within months. The AOL-Time Warner merger alone destroyed $99 billion in value, later called "the biggest mistake in corporate history."

Yet the economic damage proved surprisingly limited. The 2001 recession lasted only 8 months with positive GDP growth for the year. This was partly due to banks having minimal exposure to technology shares (never exceeding 4% of their portfolios) and maintaining lending throughout the downturn.

Quinn and Turner suggest bubbles have become more frequent because deregulation beginning in the 1970s increased all three triangle elements simultaneously. They claim that major bubbles now occur roughly every 6 years vs. gaps of 50+ years historically (though this hasn't held).

The authors classify bubbles by spark type (technological vs. political) and leverage source (bank debt vs. capital markets).

Political bubbles fueled by bank leverage prove most destructive. All four such bubbles in their book (Mississippi, Australian Land Boom, Japanese, and Subprime) devastated economies for prolonged periods.

However, technology bubbles funded through capital markets (Dot-Com bubble) often benefit society despite temporary disruptions.

Several modern trends affect future bubble likelihood:

So, what can governments do to prevent or mitigate bubbles?

When it comes to technology bubbles, Quinn and Turner argue governments rarely act because intervention can cause more damage than the bubble itself.

They also note that the post-1980 consensus treats marketability as purely positive, ignoring ~260 years when societies understood its dangers.

Specific policies that would restrict marketability include financial transaction taxes on each trade and restrictions on securitization that prevent mortgages and loans from becoming highly marketable securities.

Political bubbles (those sparked by government policy) present even fewer solutions since governments won't constrain themselves. Bank regulation limiting credit growth and directing lending away from speculation could reduce damage, but political incentives often undermine such rules.

Lastly, the media theoretically could expose developing bubbles, but Quinn and Turner found that outlets often amplify rather than moderate speculation. During bubbles, advertising revenue from bubble-related businesses, quid pro quo relationships with sources, and reader demand for optimistic coverage all incentivize puffing over skepticism.

Ultimately, investors should examine each situation for the bubble triangle's elements while watching for political or technological sparks. Understanding bubbles requires more than financial knowledge, as Quinn and Turner conclude:

We believe the current market displays all three elements of Quinn and Turner's bubble triangle at levels matching or exceeding the Dot-Com era.

Tech stocks now comprise over 50% of the S&P 500, surpassing dot-com peaks.

The ease of access has also reached unprecedented levels—anyone with capital can invest through public stocks, private funds, or even crypto tokens claiming AI capabilities.

Meanwhile, venture capital (VC) has poured $192.7 billion into AI startups this year, with more than half of all VC funding flowing to these companies.

Bain estimates AI firms need $2 trillion in annual revenue by 2030 to justify current investments but will fall $800 billion short.

This massive deployment continues despite poor returns:

The infrastructure demands themselves also reveal the gap between ambition and reality, with global shortages persisting in electricity, chips, and training data.

Speculation has become circular and self-reinforcing. Major players invest in each other while simultaneously transacting as customers, creating feedback loops that inflate valuations, as the Bloomberg visual below illustrates:

For context, The MacroStrategy Partnership found the current bubble is 17x larger than Dot-Com in absolute terms, though measurement methods vary.

Fortunately, this technology bubble appears funded through capital markets rather than bank leverage. Economic damage should stay contained when it bursts, with VCs and equity investors absorbing losses rather than triggering banking system failures.

The higher technological threshold and direct involvement of tech giants (vs. the retail-driven Dot-Com bubble) may also prevent the 78% crash that wiped out nearly 5,000 companies between 2000-2002.