Does venture follow a power law?

Research
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Venture returns are clearly concentrated. Whether they follow a power law in the strict statistical sense is a harder and less settled question. For an allocator, the practical lesson is the same either way: a small number of companies drive most outcomes, so the way a manager constructs a portfolio, and the way you construct a program, matters a great deal.

The concentration is real

CF Private Equity's analysis of U.S. venture-backed exits finds the top one percent of companies accounting for 80 percent of total exit value since 2023, up from 17 percent in 2005 to 2010. Mayfield describes the current period as an AI power law era, with liquidity flowing mostly to category leaders. Both accounts suggest rapid scaling in AI may be widening the distance between leading companies and the rest. That is an interpretation of the pattern, not a causal result established by the concentration figures alone.

Heavy-tailed is not the same as power law

The claim that venture returns follow a power law is a statistical hypothesis, and there is an established way to test one. Clauset, Shalizi and Newman explain why the common practice of fitting a straight line on a log-log chart is unreliable, and set out a procedure that estimates the distribution, tests the fit and compares it with alternatives. The most important alternative is the lognormal. Newman's own example of a process that produces a lognormal is investment returns, since a quantity that is the product of many random multiplicative factors tends toward that shape. A lognormal with high variance can look like a power law over much of its range.

The affirmative case

There is serious research on the other side. Gabaix documents power laws as a robust regularity across economics and finance. Studies fitting private fund returns place venture at the extreme end of the distribution, and others test venture return distributions directly and report power-law behavior, though methods and sample sizes vary.

What it means for LPs

  • Portfolio construction matters. If outcomes are highly concentrated, a fund needs enough companies to have a real chance of holding an outlier, and enough ownership for that outlier to matter. See How many portfolio companies should a venture fund have?.
  • Reserves matter. The ability to keep backing the best companies affects how much an outlier returns.
  • Program breadth matters. Committing across enough managers and vintages improves your odds of holding the funds that hold the outliers.
  • Averages mislead. Median and mean outcomes can sit far apart. Ask managers to describe the distribution of outcomes they expect, not just a target multiple.

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Sources

This page summarizes published research for context. The interpretation for allocators is Colibrí Strategies' own.