Can You Identify Winning Stocks in Advance?

Back in June, I had the honor of interviewing Professor Hendrik Bessembinder at the Morningstar Investment Conference in Chicago. For those who aren’t familiar, Dr. Bessembinder’s research has challenged fundamental assumptions about stock investing. His 2017 paper, Do Stocks Outperform Treasury Bills? and recent update, One Hundred Years in the U.S. Stock Markets, found that while the stock market overall has generated strong returns, most individual stocks haven’t. A small number of superstar stocks have contributed disproportionately to wealth creation. The column I wrote previewing our conference session was called “Why Most Stocks Aren’t Worth Owning.”

Several readers wrote asking for more information. So, I’m pleased to share a transcript of our Q&A session with Dr. Bessembinder at the conference. I was joined on stage by my colleague Alex Poukchanski, who came over to Morningstar as part of our February 2026 acquisition of the Center for Research in Security Pricing (CRSP), a former affiliate of the University of Chicago. Dr. Bessembinder used the CRSP database for his research.

Our questions, and those of the attendees, followed a brief presentation in which Dr. Bessembinder walked through his findings (which I detailed in my preview column). The transcript below has been edited for clarity and length.

Why the Pools of Superstar Stocks May be Shrinking

Dan Lefkovitz: I first wanted to follow up on the point you made about time-period variability. You mentioned that the results changed from your original study to the 100-year update, and that the number of superstar companies actually shrank. I’m curious, first of all, if you have any explanations, any theories as to why that happened, and whether you saw differences in the results over different time periods historically.

Dr. Hendrik Bessembinder: So, the outcomes are highly skewed, highly asymmetric, and the extent to which that’s true has accelerated recently. Now, in terms of the why, one of the things I learned when I first started teaching 40 years ago is it’s liberating to say, “I don’t know.” So, I don’t know. But a couple of things that are relevant. This is not original to me, but some people have said this is a reflection that the internet has enabled more winner-take-all outcomes, and that has a degree of plausibility to it. The other thing I already touched on is that, I’m not sure I know why, but in the last dozen years, the biggest firms have also delivered abnormally high returns. And that was not the case in prior decades. That certainly contributes to the acceleration. But to be more specific, I touched on one statistic: How many firms does it take to explain half of all the wealth creation? And when I did the original study, that number was in the 80s. And now, with a nine-year update, it’s down to just 46. And that’s although wealth creation doubled within the nine years. That’s also striking. But the number of firms that explain half of it has been cut in half. I said earlier that the asymmetry is hard-wired in the math of random compounding, so I feel really confident saying there will be asymmetry going forward. I’m less sure whether we’re going to see this continued acceleration in the degree of asymmetry.

Lefkovitz: I also wanted to ask about variability of the results by market capitalization or stock size.

Bessembinder: This might be a little counterintuitive in terms of what I already said. But the skewness in the compound returns is strongest for small stocks, and more moderate for large-cap stocks. In terms of the underlying math, which, as I mentioned, I can point people to the reference, but the mathematicians, the econometricians who have focused on this, they’ve pointed out that the main driver of long-term skewness is short-term volatility. Small stocks tend to be more volatile. In that lens, it’s not a surprise that you actually get more skewness in the small stock returns than the large stocks. So, if you’re surprised by seeing that more than half underperform Treasuries, that’s heavily driven by smaller-cap stocks. It’s not more than half for the large-cap stocks. But we get even bigger asymmetry in the market cap outcomes just because when it does show up for the large-cap stocks, it’s more important in terms of dollar outcomes. But anyway, in terms of the percentage returns, it’s strongest in small cap stocks.

What Qualities Do Winning Stocks Share?

Alex Poukchanski: One of the things that surprises people is the small number of stocks that contributed to wealth creation. Dan asked about size, but have you looked at attributes that may have explained these winners or indicate any patterns?

Bessembinder: When I completed the first study, one of the biggest questions I got was: Who are these big winners? Now, I’m going to disappoint you all because when I used the sort of data that I as a financial economist can get my hands on, which is CRSP data, Compustat data, and things you can compute from them, and tried to forecast which stocks end up in the right tail, there’s essentially nothing there. I’m not saying it’s impossible for somebody with the right comparative advantage to identify winners. I just said with the data I could get, I couldn’t detect any reliable forecast power for which stocks end up in the right tail. But that doesn’t mean you necessarily stop looking. So this was done on the decade horizon. I said, “Well, what if we just go within a decade and say, ‘OK, for the stocks that ended up in the right tail in this decade, how do they differ within the same decade from other stocks?’” Again, that’s not forecasting, but it’s potentially useful. And I came up with something surprisingly simple. The right tail stocks are growth stocks. Except I don’t mean by that what many people mean by growth stocks, like having a certain market/book ratio. Matter of fact, I checked. Market/book ratio was not a reliable predictor of who ends up in the right tail. Now, what it is, is that their fundamentals grew rapidly during the decade; things like assets, cash flow, profitability, revenue. I ran a statistical horse race among these measurables, and by far the dominant variable for explaining who ends up in the right tail is income growth. I thought that was striking. There may be some surprises in the big picture, but explaining who ends up in the right tail is about something really fundamental. Growth in the bottom line.

Lefkovitz: What about consistency of returns? Do the wealth creators tend to be slow and steady growers, or does their outperformance come in spurts?

Bessembinder: I think people will not be surprised to hear, no, it’s not slow and steady. It’s not just going up by 1% per month for 10 years. Maybe people will be surprised by the extent to which it’s not slow and steady. So, I measured drawdowns. Again, this was done at the decade horizon. I said, “OK, which are the stocks that end up in the right tail for a given decade?” And they have surprisingly big drawdowns. Even within the decade that they end up in the far right tail, they have drawdowns that average, I’m going a little bit by memory here, about 35%. And then if you look at the prior decade, they have drawdowns that average over 50%. It’s far from a smooth ride. And just a couple of case studies: Apple AAPL and Amazon.com AMZN both had drawdowns in the vicinity of 90% when the dot-com bubble burst. Even if you can identify these stocks, do you have what it takes to stay through a 90% drawdown?

The Rise of Private Markets = Fewer Winning Stocks?

Lefkovitz: One of the big themes of this conference is the rise of private markets. Companies are staying private much longer. We saw SpaceX SPCX IPO last week after what, 24 years as a private company? So, companies are doing more of their growing and scaling before they list. Any thoughts about what that trend might portend for results?

Bessembinder: Only loose thoughts … The more recent listings are bigger firms. And that trend is accelerating as firms stay private longer. From my perspective, I studied the public markets partly because the data was easier to get thanks to CRSP, and partly because I’m thinking about what’s available to any investor. And those are good reasons. But first of all, I would love to be able to expand it to private markets, which requires more and reliable and broad data. But also the point brought up that the longer firms stay private basically means they’re bigger when they come into the database, and that in and of itself, I think, is going to tend to accelerate the extent to which the wealth creation is in a few firms.

Lefkovitz: OK, we’ve gotten a bunch of questions from the audience that have come through the app. Here’s one about the implications of your research. It would seem that this analysis would imply that market-cap weighted indexes would outperform equal weight. However, since the ’70s, equal weight has outperformed. How do we interpret this?

Bessembinder: Well, there’s still a small firm premium. Well, actually, I should back that up a little bit. There has been, for portions of history, a small firm premium. Who knows what the future will bring? So, none of what I’ve said overturns that over long periods, on average, small firms have had higher average returns.

Poukchanski: You mentioned that there is a lot more skewness in outcomes for small cap. Is that related to what you’re suggesting in terms of the premium?

Bessembinder: I don’t think they have to go together. That is, the driver of the skewness is the volatility. But I don’t think there’s any mechanical reason that the higher skewness in small firms relies on the higher average return for small firms.

Are Most International Stocks Also Not Worth Owning?

Lefkovitz: Your research was focused on US stocks using the CRSP database. Have you seen any of your research applied globally?

Bessembinder: Yeah, actually, I have a study with a team of co-authors from Hong Kong. We kind of pooled forces because it was obvious the study should be done, and it ended up in the Financial Analysts Journal. So, it’s basically the same phenomenon globally. Slightly stronger. The skewness is slightly stronger. And if we rely on what the mathematicians said, that it’s driven by volatility, to the extent that non-US stocks are a little more volatile than US stocks, it’s not a surprise that the skewness is a little stronger. The one distinction though is that overall wealth creation hasn’t been nearly as robust outside the US as inside the US. The last 40 years in the US have just been an amazing thing historically, in terms of the wealth created by the US stock market.

Lefkovitz: Here’s an interesting one. If Standard Oil had not split up, how would it change the older holdings?

Bessembinder: Well, I don’t know the exact answer to that, but I understand the premise because Standard Oil was broken up into multiple companies. If we traced them all down and summed it, it would be a bigger number for sure, but I don’t know how much bigger. There is an underlying issue here. Saying what a company is through time, tracing a company through time is not necessarily a simple thing because companies that have been around for a while have had lots of corporate events, mergers, spinoffs, et cetera. One of the things that I really appreciate about what the people at CRSP have done is create what they call PERMNO, which allows the tracing of an investment entity through time. Of course, that requires some judgment calls along the way, but I’m happy to defer to people who have thought long and hard about that. I had a conversation with some people who were trying to do a parallel study, but without using the CRSP database, and they ran into exactly this question about how do we decide what is a single investment entity through time? And they were struggling. It’s a hard question. It takes a lot of thought. And my point is, the people at CRSP have been thinking carefully about it for decades.

Superstar Stocks and the Active/Passive Debate

Lefkovitz: There are some questions from the audience about the active/passive investing debate. You mentioned that your research is like a Rorschach test. People look to your study and see validation for passive management, like the old Jack Bogle quote, “Don’t look for the needle in the haystack, just buy the haystack.” But then active managers say, “No, you need to hire us to identify the winners and avoid all the many losers out there.” There’s a question: How do you identify stock-pickers with comparative advantage? And then there’s also a question about what your personal preference is, where you come down in the active/passive debate.

Bessembinder: Well, I’m perfectly willing to give the glib answer that if I knew, I wouldn’t have to work. But just a few thoughts. Fama and French have done a ton of really important work, but one of the papers they have out there is that if you’re just going to use the data to identify skilled managers, good luck. You might have to wait 100 years. There’s just a lot of randomness in the markets. Even if somebody’s skilled, they can have bad luck. Even if somebody’s perversely skilled, has some behavioral bias or something, they could still have good luck. The signal-to-noise ratio is not high. I’m going from memory here, but I think Fama and French said something like you need nearly 100 years of data to reliably identify a skilled manager from the data. So, what I take away from that is it takes more than data. Data’s informative. I think I’m paraphrasing Warren Buffett here, but if not, sorry, Warren, for misattributing. But I think I remember Warren Buffett saying you invest in people. And I believe he was referring to the companies that he invests in, but I think the same thing goes for evaluating investment managers. It’s some combination of the data and your sense of, does this person have it? I know we’re all capable of fooling ourselves, but I also think that smart people are capable of paying attention to those intangible signals.

Lefkovitz: Here’s an interesting one. You mentioned what you see as the limitations of the capital asset pricing model and Alpha. What type of tools do you see replacing things like the Sharpe ratio and mean-variance optimization?

Bessembinder: Well, I’m glad whoever posed the question asked because I’m working on that … with some very bright co-authors. We’re still thinking through all of the issues. But if all goes well, we will later this summer release a paper titled “Universal Alpha,” and I’ll just leave it at that.

Lefkovitz: Are you doing any research into creating multifactor risk premia for returns?

Bessembinder: I actually have some research on—it’s not new factors, but I have some research that’s more mainstream. I have a paper on time variation and factor premia and what taking that into account can do to Sharpe ratios. So, on the one hand, I’m saying we should have a revolution. On the other hand, I’m still applying some of the standard tools. Anyway, we’re not developing new factors, but I am also doing some work in that sphere.

Lefkovitz: OK. We’re out of time. Thank you so much. Please join me in thanking Dr. Bessembinder. 

Also published on Morningstar.com