Excess Returns

Lessons from Investing Through Bubble Regimes with Andy Constan

Donnerstag, 14. Mai 2026 · 1 h 05

MP3

Shownotes

First Principles with Andy Constan launches with a deep dive into market bubbles, AI, semiconductor stocks, and the financial conditions that can turn powerful technological change into a dangerous investment regime. Andy explains how bubbles form, why they are almost impossible to time, how today’s AI boom compares to past episodes like 1987, the dot-com bubble, housing, and the bond bubble, and what investors should watch as expectations, financing, and FOMO build.
Andy Constan on X
x.com/dampedspring
Damped Spring Advisors
dampedspring.com
Topics covered:
• Why bubbles are easy to identify in hindsight but nearly impossible to define in real time

• The difference between an expensive market and a true bubble regime

• How new technologies, easy money, regulation, and exogenous shocks can create bubble conditions

• Why AI may rhyme with the internet boom without being an exact repeat

• The role of ChatGPT, Microsoft’s OpenAI investment, and semiconductor earnings expectations

• What the 1987 crash, Japan, housing, bonds, and dot-com bubble can teach investors today

• Why human nature, FOMO, and “keeping up with the Joneses” make bubbles so powerful

• How the late-1990s Fed response to Long-Term Capital Management helped fuel the final phase of the tech bubble

• Why tech’s current size in the economy and market may limit how far the AI boom can grow

• How AI capex, hyperscaler spending, buybacks, debt issuance, and IPO supply could determine what happens next

Timestamps:
Intro and the challenge of identifying bubbles
Expensive markets vs true bubble regimes
The five bubble episodes Andy compares to today
Root conditions, escalation events, and the peaking phase
Why the 1987 crash may also have been a bubble
The late-1990s setup and the Netscape Navigator moment
Crisis analogs, easy financial conditions, and today’s AI parallels
Long-Term Capital Management and rocket fuel for the tech bubble
Why tech’s market share matters more today than in the 1990s
Policy mistakes, subsidies, and how governments feed bubbles
Semiconductor earnings expectations and valuation risk
The AI capex chain and where the money has to come from
IPOs, corporate debt, and the financing risk behind the AI boom
What investors should do differently in a bubble regime

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