Differentiating Good Bubbles from the Bad 

Some of the greatest investments are made during times of doom and gloom, and some of the worst are underwritten during the boom times. Most investors who have weathered large bubbles, like the dotcom or housing bubbles, carry the scars and resulting instincts to distrust excess and hubris. But some forget this and gleefully pay eighteen times for an HVAC company in Idaho whose CRM is an Excel spreadsheet and hope consolidation will simply do the work. No matter where your instincts around bubbles reside, Boom: Bubbles & the End of Stagnation by Bryne Hobart and Tobias Huber provides a framework for distinguishing between good bubbles and bad bubbles. 

Moving beyond ex-post narratives, which tend to treat all bubbles as foolish and with little benefit, Boom provides a simple framework for discerning good bubbles from bad: 

• Good Bubbles: Capital flows into areas with high uncertainty but high potential upside. Most projects fail, but the few that work change the cost curve, infrastructure, or production frontier (railroads, the internet, cloud computing). 

• Bad Bubbles: Capital chases financial engineering, regulatory arbitrage, or copycat models where learning is minimal and positive spillovers are low. 

Central to the authors’ argument is that while bubbles tend to be speculative and early investors often lose significant sums, good bubbles leave productive infrastructure behind. Good bubbles produce infrastructure that becomes an ecosystem for new production methods, new products and services, and produce societal benefits. Put more succinctly, the pioneers take the spears, and the settlers take the land.  

All bubbles get a bad rap because both good and bad bubbles share three central features: 

• Both bubbles rely on devotion and blind faith on positive outcomes.  

• Both face the fact that the future is uncertain.  

• Feedback loops are often long and wicked. 

Boom is helpful in establishing some bedrock questions to assess investments in early-stage sectors or boom conditions. As always, diligence is the art of asking good questions: 

• Is capital funding discovery or duplication? 

• If this company fails, does the market still learn something durable? 

• What becomes permanently cheaper or easier if this works? 

• Are losses buying insight, or merely subsidizing demand? 

• What do I have to believe for this investment to make sense? 

• What is the company’s growth rate? Is it slowing? / What is the industry’s TAM and penetration rate?   

• Are we seeing tangible spillover effects that support the long-term relevance of the product or service? 

Bad bubbles leave investors holding the bill and society with little to show for it. They are expensive precisely because they fund promises without ever finding a repeatable cash engine. In the long run, even the most visionary companies are valued on the cash they can reliably generate—and investors cannot subsidize tomorrow forever. 

And yet, excess is not pointless. The same overfunding that produces spectacular write-offs can also bankroll the infrastructure that real innovators later turn into durable businesses. Ride-sharing is a useful example of this. After Uber’s introduction to Houston in February 2014, one study found crash traumas fell by nearly 24% during peak weekend-night hours. Nationwide drunk driving fatalities fell by 6% thanks to rideshares. Uber did not produce annual profits for investors until 2023.  

Good bubbles are better—but they rarely deflate gently. Survivors endure brutal repricing, then justify the earlier hype by compounding into something real. For instance, Amazon lost roughly 90% – 95% in the dot-com unwind and still became one of the defining businesses of the next era. Around the time Amazon regained its share price of over $107, it began working with third-party staffing agencies to recruit and manage its warehouse workforce. Here we see how not just cash flow but also the growth in derivative businesses demonstrates the long-term value good bubbles eventually deliver.