This Is How the AI Stock Boom Plays Out

In the years after the internet stock boom-and-bust of the late 1990s and early 2000s, financial economists searched for more satisfying explanations of what had happened than “investors went crazy.” Among the most successful were Lubos Pastor and Pietro Veronesi of the University of Chicago Booth School of Business, whose paper “Technological Revolutions and Stock Prices,” published in the American Economic Review in 2009 (ungated version here), was the focus of an entire conference at the Massachusetts Institute of Technology this month.

The occasion was that the paper had won the biennial Stephen A. Ross Prize from the Foundation for Advancement of Research in Financial Economics (Ross, who died in 2017, was a prominent MIT finance scholar), but the question of how technological revolutions play out in financial markets has also become Topic A again amid the investment boom in generative artificial intelligence. The paper and two precursors by Pastor and Veronesi are built around simple mathematical models that make no predictions about when that boom will end or whether it will end badly, but offer insights into how it will play out. The simplest takeaway is that as the economic significance of AI becomes clearer, the valuations — that is, price-to-earnings, price-to-book and other such ratios — of AI-linked stocks will fall.