How many stocks do you actually need to be diversified?
4 min read by Opthest
A 2026 survey of investors found that for 31% of them, individual stocks of specific companies — not funds — now make up the biggest slice of their portfolio, and only 30% said they rebalance on any set schedule. Picking your own stocks instead of buying a basket isn’t a mistake by itself, but it quietly raises a question almost nobody asks before doing it: how many different companies does it actually take before adding one more stops meaningfully reducing your risk?
What’s the classic answer?
Evans and Archer ran that exact test back in 1968: build random equal-weighted portfolios, add one stock at a time, and watch how much volatility falls with each addition. Their finding — most of the benefit shows up by around 30 stocks, after which each new name cuts almost nothing more — became one of the most repeated numbers in investing, and it’s still taught as a rule of thumb today.
Why do more recent studies land on much higher numbers?
Because the bar changed. Instead of asking “where does the average risk reduction flatten out,” later research asked a tougher question: how many stocks do you need before you can be 90% confident you’ve captured 90% of the possible risk reduction — not just on average, but reliably. Individual-stock returns aren’t tidy and symmetric: a small number of big winners (and a long tail of laggards) drive an outsized share of the outcome, so a stricter confidence bar pushes the number up. On that test, research on equity diversification has put the figure closer to 40-50 stocks for an equal-weighted portfolio, and higher still — around 60-plus — once you weight by market value, since a cap-weighted mix keeps concentrating risk in its largest few names even as the holding count grows. Other research goes further, arguing that an investor who wants a realistic shot at capturing the market’s full long-run return — which tends to be produced by a small number of exceptional performers — needs something closer to 200 names, because most individual stocks underperform the market average over long stretches.
Why does the “right” number move around so much?
Because “diversified” isn’t one fixed target — it’s layered. How much short-term volatility are you trying to shed? How confident do you want to be that you’ve actually shed it? And are you trying to merely survive one bad stock, or to make sure you’re holding the handful of future winners that end up carrying the whole market’s return? Thirty stocks go a long way toward the first goal. They do very little for the third.
Does the count even matter if the stocks move together?
This is where the headline number can mislead you. Evans and Archer’s test — and most of what followed it — assumes the added stocks aren’t all exposed to the same thing. A 50-stock portfolio made of 50 different AI-adjacent names, or 50 companies feeding the same supply chain, doesn’t diversify the way 50 stocks drawn from unrelated sectors and geographies do. The correlation between your holdings decides how much risk actually washes out — not the number printed on your statement. Your 40th stock reduces risk by far less than the textbook curve promises if it’s highly correlated with the other 39.
What does this mean next to the 2026 survey numbers?
Put the two findings together. A meaningful share of investors are now assembling portfolios stock by stock rather than through a fund, and most of them aren’t rebalancing on any schedule. Neither fact is damning on its own — but together they describe a portfolio where nobody is actually checking the diversification: not the number of names, not how correlated those names are to each other, and not how the mix drifts as a few positions grow while others shrink.
How do you check this instead of guessing?
Not by counting tickers and comparing to 30, 50, or 200 — by measuring how concentrated your actual risk is, given the real covariance between your real positions. That covariance matrix is the same input behind the efficient frontier: it’s what separates genuine risk reduction from the illusion of it. Running your own mix against historical data shows directly how much of your volatility is being driven by a handful of correlated names — a far more honest answer than any single number from a 1968 study, or a 2026 one.
What this is NOT
This isn’t a case for or against picking individual stocks instead of funds, and it isn’t a target number to hit. Thirty, fifty, or two hundred are research findings about historical equity return distributions under specific assumptions — not a rule guaranteed to hold for your mix, and not investment advice about what or how much to buy. How many positions you hold, and how correlated you let them become, stays your decision.
The number of stocks on your statement tells you how long the list is. It doesn’t tell you how diversified you are — the correlation between them does.