Hank Bessembinder is a professor and the Francis J. and Mary B. Labriola Endowed Chair in Competitive Business. He returned to Arizona State University in 2015, after holding positions at Emory University and the University of Utah. Prior to his first assignment with ASU, Professor Bessembinder taught at the University of Rochester. His research focuses on market design and trading, including stock, foreign exchange, fixed income, futures, and energy markets, as well as on measuring long term investment performance. He has published numerous articles in the Journal of Finance, Journal of Financial Economics, and Review of Financial Studies, among others. 

A frequent speaker at conferences, financial markets, and universities around the world, Professor Bessembinder has more than 25 years of successful consulting experience, providing strategic advice and analysis for major firms, financial markets, and government agencies. 

Did you know that just a handful of stocks drive nearly all of the stock market’s long-term gains? In this episode, we sit down with Hendrik Bessembinder to discuss his groundbreaking research on why most stocks fail to outperform Treasury bills and how a small fraction of stocks generate the most long-term market returns. Hendrik is a Professor in the Department of Finance at Arizona State University whose research focuses on market design, trading, and long-term investment performance across stock, foreign exchange, fixed income, futures, and energy markets. In addition to his academic contributions, Professor Bessembinder has over 25 years of consulting experience, advising major firms, financial markets, and government agencies. In our conversation, we delve into the findings of his research and find out how a small fraction of stocks generate the majority of long-term returns. We explore why traditional investment strategies often overlook the impact of skewness, the impacts of broad diversification and passive investing, and why active fund managers struggle to beat the market. Discover why chasing past returns can lead to costly mistakes, his latest research on 'sustainable returns', what type of industries have the highest stock returns, common investing mistakes, and more. Join us to uncover the surprising realities of stock market returns and how you can build a portfolio that stands the test of time with Professor Hendrik Bessembinder.

Key Points From This Episode:

(0:03:54) Explore Hendrik’s research on long-term stock returns and how most returns come from a small group of stocks.

(0:08:30) Learn how company size interacts with the skewness in stock returns and what it means for individual investors.

(0:11:39) Considering fundamentals in stock returns and the implications of skewness for measuring portfolio performance.

(0:15:42) Unpack how he used bootstrap simulations in his paper and the performance of stock returns versus Treasury bills.

(0:19:01) Find out the proportion of US firms responsible for dollar wealth creation and why diversification is essential for long-term stock returns.

(0:25:23) Navigating volatility in the market and why it is difficult to identify skilled managers in time to leverage the market.

(0:28:00) Compare the performance of US stocks versus global stocks and what is driving their performance.

(0:32:04) What the findings of his research means for financial planners and individual investors. 

(0:35:35) Uncover which US firms generated the highest returns and what type of industries these companies are in.

(0:42:07) Hear about the long-term performance of US mutual funds and how investor behaviour contributes to it.

(0:49:54) How passive investing and index funds have reduced the contributions of actively managed mutual funds and the lessons for investors.

(0:55:48) Discover Professor Bessembinder's broader research interests and his definition of success.

Read The Transcript:

Ben Felix: This is the Rational Reminder Podcast, a weekly reality check on sensible investing and financial decision-making from two Canadians. We are hosted by me, Benjamin Felix, Chief Investment Officer at PWL Capital, and Mark McGrath, Associate Portfolio Manager at PWL Capital.

Mark McGrath: This is a good one. This is one I was really looking forward to. I think a lot of our listeners will know today's guest.

Ben Felix: I was looking forward to this one, too. This is episode 346 with Hendrik Bessembinder, Hank, as we call him during the conversation. I think a lot of our listeners, they know who he is. They've heard me talk about him.

Mark McGrath: I don't know. You've talked about him. The paper that he wrote, the one major paper that got a ton of eyeballs was the 'Do Stocks Outperform Treasury Bills?', right? I think some of the findings from that were so interesting to people, especially the type of people that follow us, or follow the Rational Reminder, or in the community, or follow your YouTube videos. They’ve probably come across at least some of the statistics that came out of this paper, even if they weren't familiar with the paper themselves.

Ben Felix: Yeah. It was a huge paper from the perspective of the asset management industry and for reasons that become pretty quickly obvious when you listen to him talk about it. Okay, so introduction to Hank. Hank Bessembinder is a Professor and the Francis J. and Mary B. Labriola Endowed Chair in Competitive Business at Arizona State University. He returned to Arizona State in 2015 after holding positions at Emory and the University of Utah. Prior to his first assignment with Arizona State, he taught at the University of Rochester.

His research focuses on market design and trading, including stock, foreign exchange, fixed-income futures and energy markets, which we talked a little bit about at the end of conversation, as well as measuring long-term investment performance, which is what we talked about for most of the work conversation. He's got publications in all the major journals, Journal of Finance, Journal of Financial Economics, Review of Financial Studies and others. Like we mentioned at the beginning, he became a pretty well-known name in the asset management industry in those circles for his 2018 paper, 'Do Stocks Outperform Treasury Bills?' We talked about that paper, and then we also talked about a bunch of interesting follow-on, or related work that he's done, just on that concept of skewness and stock returns. Most of the returns of the market come from relatively few stocks. There's a whole bunch of interesting implications for long-term investors and financial planning and portfolio management.

Mark McGrath: A lot of his answers are really interesting because you'd assume, based on the research in this paper, that the obvious answer is that, well, then don't manage a portfolio actively. I think Hank took not necessarily as puritanical views, you and me might on that subject. It was really interesting to hear his perspective on the active management industry and indexing it. What should investors do with all this information?

Ben Felix: Yeah. We talked a lot about data, and we talked a lot about theory and statistics, but I think every piece of the conversation was tied back to how is this useful and how is this relevant for individual investors and financial planners that are managing portfolios and thinking about long-term returns. This was a fantastic conversation. I've been wanting to have Hank on the podcast since before 2018, before his paper came out. Long-time coming.

Mark McGrath: Yeah. Good? Should we go to the episode?

Ben Felix: Let's go ahead to our episode with Professor Hendrik Bessembinder.

[INTERVIEW]

Ben Felix: Professor Hank Bessembinder, welcome to the Rational Reminder Podcast.

Hendrik Bessembinder: Thanks, Ben. I'm happy to be here with you today.

Ben Felix: We're very excited to be talking to you after having read many of your papers and finding them all super, super interesting.

Hendrik Bessembinder: Yeah. Well, thank you.

Ben Felix: Great stuff. As listeners, I'm sure we'll agree as we go through them. Okay, so to start off, what does it mean to say that individual stock returns are positively skewed?

Hendrik Bessembinder: Well, I mean, skewness is a statistical concept, but what it basically means, positive skew, is that you have a few really big outcomes. Probably, the most important thing to just recognize intuitively about skewness, when you have positive skewness, those few really big outcomes pull up your mean, your average, to the extent that the average doesn't really represent the more typical outcomes. To use statistical language, the mean will be higher than the median, which is half are above and half are below. That's when it comes to a nutshell. There's a few relatively big outcomes pulling the mean up to where the mean isn't representative of the typical outcome.

Mark McGrath: Got you. You had a paper in 2018, 'Do Stocks Outperform Treasury Bills?' And it blew a ton of people's minds, including ours. Why do you think that was? Why do you think that paper blew so many people's minds?

Hendrik Bessembinder: I might mention real quickly that the paper is really about skewness, but I chose that title, because I thought it would be a little harder to resist than saying, “Hey, the skewness in returns.” Why did it come such a surprise to so many people? I might throw in here, by the way, that there were some people who were not surprised. There were a few people who came back to me and said, “Well, of course. What did you expect?” I think most of us hadn't already taken the thought process that they did.

I think there were quite a few people who understood or had seen some indication that when your compound returns, start looking at longer horizons, there's positive skewness. Apparently, nobody had actually dug in and done this on a systematic basis and over long periods of time. Or if they did, they kept it to themselves. Didn't broadly disseminate it. It's not so much that the existence of positive skewness was a surprise to a lot of people as the magnitudes when you actually compound the returns over longer horizons. It really starts to kick in if you start looking at, say, a decade horizon, or longer. Just surprising how strong the skewness is.

Ben Felix: That was definitely the thing, was the magnitude, because there was that Heath and Paulson and Witt paper. It wasn't really an empirical paper, but they just said, “Hey, this is a property of stock returns. Here's what it might mean for active management.” But when you actually came at it empirically and showed the extent of it, I was like, wow. I guess, it made the suggestion in their paper that much more powerful.

Hendrik Bessembinder: Yeah, indeed. I should be giving credit to papers like theirs and I cite a couple of others. This wasn't completely novel. The idea was not completely novel, but it seems to be fairly novel to have shown just how big it is in the data.

Ben Felix: Yeah, totally. In your sample, what percentage of stocks have lifetime buy and hold returns that exceed one-month Treasury bills?

Hendrik Bessembinder: It turns out to be about 42%. It's just about three out of seven succeed in beating Treasury bills in the long run.

Ben Felix: Wow.

Mark McGrath: Wow.

Ben Felix: Crazy.

Mark McGrath: What percentage have lifetime buy and hold returns that exceed the market return?

Hendrik Bessembinder: For the overall market, about 31% of individual stocks beat the overall market. The overall market, obviously, is higher hurdle than the Treasury bill is, so you get lower percentage, but it's the same phenomenon at work.

Ben Felix: That's crazy. Over the lifetime of the stock in your sample, 70% of them underperform the market as a whole.

Hendrik Bessembinder: That's right. Yup.

Ben Felix: That is wild. How common is it for stocks to deliver negative absolute returns, or even total losses?

Hendrik Bessembinder: Slightly more than half of the stocks delivered negative returns. On the total loss thing, it depends a little bit on how literally we take a total. The database I use, KRIS, many people would be familiar with it. For stocks that disappear, it lists a final delisting return. That number is not usually negative 100%, but it's oftentimes really close. Anyway, if we say total return is losing 98% or more of your capital, that's about 11% of all stocks turning into total losses.

Ben Felix: That's crazy, 11% of all stocks. Fifty percent of stocks that have negative absolute buy and hold negative lifetime returns. That's not adjusted for anything else.

Hendrik Bessembinder: Right. No adjustments for inflation. No adjustment. Just you have less dollars at the end than you had at the beginning for a slight majority of stocks.

Ben Felix: That's wild.

Hendrik Bessembinder: Yeah. It was a surprise to me and a lot of people. As I said, it's skewness that's driving it, but how strong the effect was surprising.

Mark McGrath: Yeah, that's wild. And 11% had, I guess, total losses. Half are negative and 20% of those effectively.

Hendrik Bessembinder: That's right.

Mark McGrath: Effectively total losses. That's wild. Okay, how does company size interact with the skewness in stock returns?

Hendrik Bessembinder: It is important. And maybe I can throw in something because it comes up in thinking about things more broadly. I had some simulations in the original paper that suggested this. I think there were a couple of really talented fellows in Sweden, Adam Farago and Erik Hjalmarsson. I apologize to Erik if he hears this and I didn't get his name right. They did a much more rigorous study and they basically dug into the question of where does skewness in compound returns come from? The answer suggested by my simulations and they show much more rigorously, volatility in the short run translates into skewness in the long run. The more volatility in the short run, the more skewness in the long run.

That shows up in several ways. One of them is in your question about firm size. Big firms have returns that are less volatile than small firms. We put those together. There is skewness in the compound returns of big firms, but it's not as pronounced as in the compound returns of small firms. The same point is going to come back later when we talk about portfolios. Portfolios also have skewness in their long-run returns. By the way, that includes the overall market. The overall market is just a portfolio. Portfolios also have positive skewness in their long-term returns, but not as much as individual stocks. Why not? Diversification means there's less volatility. It all comes together.

Ben Felix: On company size. You mentioned volatility. One of the things that was crazy when I read the paper, that I found crazy was that the skewness in small stock returns is way higher. You're much more likely to lose money picking an individual stock. Then, it's not as bad in larger stocks, like you just said. Larger stocks in aggregate tend to underperform, at least in your overall sample period. Smaller stocks tend to outperform. I mean, it's just super interesting.

Hendrik Bessembinder: It helps to highlight again, that when there’s skewness, the means don't tell you the whole story. In terms of mean returns over long periods, big stocks have done worse than small stocks. The small stock effect, people argue about, is it still in the data? But it definitely was over the long term. In terms of mean returns, small stocks do better than large stocks, but they also have more skewness. There's also a bigger wedge between that mean return and what a typical stock does in the small stocks.

Ben Felix: So interesting. You mentioned volatility is the explanation. Is that the only explanation for why we see so much skewness in stock returns?

Hendrik Bessembinder: I don't know if I'd say it's the only explanation, but I think it's the strongest explanation. You can get a lot of skewness in compound returns, even if there's no forecast ability of stock returns at all to use statistical terminology, even if successive returns are statistically independent, you can get a lot of skewness. Now, if on top of that, we have long-run momentum, I don't think we do, but just speaking hypothetically, if we had long-run momentum, you'd get even more skewness. There is room for additional things, but I think it's mainly the short-run volatility that does it.

Ben Felix: What about fundamentals? When I think about small stocks, a lot of small stocks just suck, because they're not as robust businesses. Is there any of that?

Hendrik Bessembinder: I mean, definitely fundamentals matter, but I don't want to go out on a limb and say, the stock markets are efficient because we'll get into an endless debate over well, what do you mean? How close? Etc., etc. But it's competitive out there, and individuals in the market are collectively valuing assets based on what's knowable, or forecastable. At any point in time, the market is taking into account what's known about fundamentals. Most of the volatility comes from surprises.

Ben Felix: Interesting. Yeah.

Hendrik Bessembinder: The compounding of those surprises is what gives us the skewness. It depends on your perspective. Let's take a firm like Amazon, which ends up doing really well. It's near the top of the leaderboards. One way to look at that is to say, well, at each point in time, Amazon was priced based on the wisdom of the crowds. It turned out that there was a bunch of lucky draws. That would be one way to look at it. I have a hunch, if Jeff Bezos was around, he'd say, “What are you talking about, a bunch of lucky draws?” I had the great plans all along. What happened is it took the market time to figure that out. Those can both be true at the same time.

Ben Felix: Yeah, that's really interesting to think about.

Mark McGrath: What are the implications of skewness for standard measures of investment management performance, things like the Sharpe ratio?

Hendrik Bessembinder: Well, I think the most obvious thing is that the standard measures are somewhat incomplete. The Sharp ratio takes into account the mean return and the standard deviation of returns. Skewness doesn't enter. I could go a little further. A lot of what we do in performance measurement has its intellectual roots in the capital asset pricing model from the 1960s, which was a single-period model. It didn't tell you the length of the single period. I think a lot of performance measurement is still intellectually rooted in that single-period model. I think Sharpe is quite clear that that's, after all, is the Sharp Lintner capital asset pricing model. Pretty clear, that's a very clear measure came from.

If you take another very commonly used performance measure, Alpha. If you go back, that's Jensen's Alpha. If you go back to Jensen's original paper, he's very explicit that this is all based on the capital asset pricing model. Anyway, capital asset pricing model, single period model, no skewness accounted for. I just think there's something missing and there's room to bring skewness into performance evaluation, and we haven't really done it.

Ben Felix: You have a newish paper on that. We didn't have questions about it, but I think you tried to address it in that paper?

Hendrik Bessembinder: Yeah, I have one paper, I call it 'Extending Portfolio Theory to Compound Returns.' By the way, if anybody who's listening is interested in any of the papers we mentioned, you can find them on Social Science Research Network, so ssrn.com. Just keyword search, or search on my name. You can easily find them. I did take a stab in that direction and I should mention, I was piggybacking on other scholars who unfortunately, name I don't recall at the moment, but there is a skewness-adjusted Sharpe Ratio measure that I spend some time on. I think it might be good if people thought more about measures that do take skewness into account.

Ben Felix: Yeah. I definitely agree with that. One thing that I found interesting, how do you reconcile most individual stocks trailing Treasury bills at long horizons? When asset pricing models, we just talked about the CAPM, they predict a positive expected return for taking on equity risk. How do you square that circle?

Hendrik Bessembinder: It's actually not that hard to square. When we're done squaring it, we might still ask, well, could we demand more from the asset pricing models, those that develop asset pricing models, could we demand more? But you used the phrase ‘expected return’. In statistical space and statistic lingo, expected and mean are synonymous. The expectation is the mean of the possible outcomes. The models are about the mean. They make implications about the mean. Once we bring skewness into it, as I said, what's driving things is that the mean, well, it's an informative number is not informative about the typical stock. We could imagine asset pricing models that focused a little more specifically on what the median return would be.

Mark McGrath: So in the paper, how do the bootstrap simulations work?

Hendrik Bessembinder: Sure. Let me first back up just a little bit about why I did the bootstrap simulations in the paper. It turns out that stocks don't stick around very long. I don't remember the exact number. But in the 90-some-odd years of data that I studied in the original study, I think the median time that a stock was in the database was seven, or eight years. Before anybody lets that scare them too much, recognize that stocks can disappear for positive reasons, as in they got acquired, not just because they got delisted for performance. Anyway, the average stock is there for a median of seven or eight years. When I said here's how the single stock did over its life, I had 90 years of data, but for most stocks, that was a lot less than 90 years.

Anyway, I was interested in the question of, well, what if we had a single stock strategy over the whole 90 years? That's where I went to the bootstrap. The way the bootstrap works is I just pick a stock at random each month, and it's a different stock every month. A single stock strategy. Would you decide again every month? Anyway, just pick a stock at random every month, compound the returns. Compare that to benchmarks. That was the bootstrap simulation.

Ben Felix: As you were talking there, I was thinking about the lifetime buy and hold. If a lot of those stocks that existed for longer times, they probably would have had better returns, like there's some survivorship bias there?

Hendrik Bessembinder: The survivorship is definitely a factor. I wouldn't call it biased in the sense that I used every stock that was there. Survivorship bias didn't really show up if you say, well, I'm only going to consider the stocks that were around for at least 15 years or something like that. I mean, these things are intertwined. If stocks that had longer lives, would they have also had higher average returns? Probably. In particular, that suggests that they avoided being delisted for negative reasons, so those probably go together. That's a counterfactual.

Ben Felix: Right, right, right. That bootstrap, if we look at the single stock bootstrap strategies, how frequently do they beat Treasury bills at the 90-year horizon?

Hendrik Bessembinder: In the actual data, about 42% of stocks beat Treasury bills. When I look at the simulated single stock strategies, that drops down to about 27%, beat the Treasury bills.

Mark McGrath: What about the market? How frequently do they beat the market?

Hendrik Bessembinder: In my mind, this is one of the more striking results I got in the paper. Single stock strategies only beat the market 4% of the time.

Ben Felix: 4% of the time. That's wild.

Hendrik Bessembinder: A little side story here. Back when I was first running out these results, I was actually a little conflicted about whether I should write it up in a paper because I'm thinking, maybe everybody knows this stuff, and I'm just the one who doesn't know this. I bounced this exact question off of some of my colleagues. I had just obtained the result and I bounced it off to some of my colleagues at lunchtime. I said, so here's this single stock strategy. How often do you think this beats the market? Their responses and I think what they had in mind is the small firm effect because you're going to be drawing at random a lot of small firms because there's a lot of small firms in the database. In any event, the guesses were over 50%, when the reality, the data was 4%. That helped get me over the hump that, okay, there's really something going on here that even a lot of smart people don't know. I'm glad I went ahead and I wrote it up.

Ben Felix: Yeah, that is surprising and super interesting. Earlier, you mentioned diversification. What effect does adding more stocks to those bootstrap portfolios have?

Hendrik Bessembinder: If you roll back to our earlier discussion, I think you'll see the answer coming. When you add more stocks, you get diversification, it reduces the volatility, it reduces the effect of skewness. The effects of skewness are still there, but not as dramatic. Single stocks only beat the market 4% of the time in the simulations. Portfolios of a 100 stocks, it's still less than 50%, but it's up to 43% portfolios of 100 stocks. Again, I've got to emphasize here, randomly selected 100 stocks each month, randomly selected that beats the market 43% of the time over the full 90 years. The skewness is still there, but not nearly as stark as it was with the single stock.

Ben Felix: That's still pretty crazy though. For 100 stock portfolios to underperform that frequently.

Hendrik Bessembinder: Yeah. I mean, I guess, it depends on what you expected, but it's still notable. Actually, that's one point I think should be emphasized. My paper was about single stocks, but it would be a mistake to think that this is only an issue for single stocks or for really narrow portfolios. For the broad portfolio, skewness remains an issue.

Mark McGrath: Okay. What proportion of US firms are responsible for the dollar wealth creation over Treasury bills, over your sample period?

Hendrik Bessembinder: I should just give a little embellishment about that. Most of what I did and what most people do is percentage returns. But you can make an argument that stock size matters. Evaluated portfolio is basically taking that into account, that in some sense big stocks are more important than small stocks in the economy. That's part of why I shifted to dollar-based measures or didn't shift. Just also reported some things in terms of dollar-based. There's another more subtle issue when we just compound the returns, I think you already use the terminology, which is correct. You just compound the returns. That's the outcome to a buy-and-hold strategy.

As I said, a more subtle point, the market as a whole is not buy-and-hold. Firms issue new stock, firms repurchase stock, a little even more subtle yet, dividends in aggregate don't get reinvested, because if I'm buying to reinvest, somebody's got a sale to reinvest. Anyway, the market as a whole is not a buy-and-hold portfolio. There's an alternate measure out there. The dollar-weighted return that takes us into account, as opposed to the buy-and-hold return. This dollar wealth creation measure that I've got accommodates both that some firms are bigger than others and the fact that the market as a whole is not a buy-and-hold portfolio. With all that in place, when I do measure things in dollar terms, 4% of the stocks explain all of the net wealth creation since 1926. That was another striking figure.

Ben Felix: Yeah, that figure is striking. I think it's worth just mentioning because I think some people got confused on that statistic. That's on the dollar wealth creation specifically, not on returns.

Hendrik Bessembinder: Right. Even on the dollar wealth creation, I sometimes feel I need to fill in a few more words around that, because it is an easy one to misinterpret. Roughly speaking here, 57% of the stocks reduced shareholder wealth, but then we still got 47% to work with. Out of that 47%, about 44% did enhance shareholder wealth. it was positive. But they collectively just generated enough to offset the destruction from the first 50 some odd percent, leaving 4% to explain all of the icing on the cake, if you will.

Ben Felix: Right. Yeah, that statistic really is crazy.

Hendrik Bessembinder: Yeah, that would surprise some people, too.

Ben Felix: Yeah, they definitely did. The answer to this question is obvious, but I still want to hear what you say. Based on the findings we talked about so far, how important is diversification for long-term investors?

Hendrik Bessembinder: It's still really important. I know you also want to talk about what are the implications for investors here. These are intertwined. I don't give investment advice, partly because I'm not a registered investment advisor, so that would be a problem. Even philosophically, I don't tell people what they should do. I view my job as helping to educate them, to get the facts out there, so that they can make the choices that work best for them. That's how I see my role.

The big question is, what does all this imply for the desirability of being broadly diversified, versus the desirability of having a narrow portfolio? I've said this before. It may sound a little odd, but there's new ammunition for both sides of that debate. I've heard second-hand about conferences where people are debating and both sides are pointing to my paper, so that's interesting. We already know the arguments for broad diversification. I would say, what's been added to that is the knowledge that if you just pick some stocks at random, the odds are stacked against you.

Another way to put that is, the only way to be sure of having tomorrow's big winners in your portfolio is to own all the stocks. Was it Jack Bogle that said, buy the haystack? Anyway, so there's that. On the flip side, and there's always a flip side. With economists, there's always two sides. On the other hand. But there are some arguments to go the other way. The first one is, what if you know something that others don't? What if you're skilled? When their skewness, the payoffs to being skilled are bigger than if there's not skewness. I would throw in there, are you really skilled, or are you overconfident? I don't have the answer for you, but give some long, hard thought to that.

Anyway, if you're truly skilled, the upside is bigger than we thought. Then one other thing I'll just throw in there, economists use the phrase skewness preference. Truth is, some people like skewness. Even if you don't think you're skilled, some people just like this idea of a possible, really big game. If you just look around, there's lots of evidence that there's a lot of people that like skewness. People gamble, people play the lottery. You loosely use the word invest. People dabble in crypto. I think this is all skewness preference.

If you have a skewness preference, well, I just showed you how big the skewness is, just make an educated decision. Recognize that the odds are against you. You probably won't get that big payoff. If you want skewness, diversification reduces skewness, so just take that into account.

Mark McGrath: I know you don't want to give investment advice, but maybe you can educate us instead. Between these two potential interpretations, diversification is very important, of course. Then you talked about, it may be possible to hugely beat the market because of that skewness with a concentrated portfolio. Which view do you think investors should take?

Hendrik Bessembinder: I really do think it depends on the investor. I can't read people's minds. I really think for most people, the traditional advice, diversify broadly and be a long-term investor, as opposed to trying to time the markets. I really think for most people, that's good advice. Who would want to deviate from that if you have a really strong taste for skewness, or you're pretty confident, you're skilled. Or, I should throw it in the mix, or you're confident you can identify managers that are skilled. I will throw in there that I do think there are skilled portfolio managers out there. The challenge is identifying them in real-time.

Ben Felix: Yup. That's exactly it. You referenced in your paper, Berk and van Binsbergen 2015 and Fama and French 2010, that both look at different interpretations of why it's so hard to identify winning managers before the fact.

Hendrik Bessembinder: Yeah. There's a lot of randomness in the market. From a statistical viewpoint, the problem is the signal-to-noise ratio is not high. Fama and French have done some calculations of how many years of data would you need to use statistics to identify a skilled manager. There are some real challenges there. I'll just throw in that I don't rule out using more subjective measures to try to find skilled managers. It's going to be a challenge. But to put it in a different context, I believe Warren Buffett has said that when he invests in companies, to a certain extent, he's investing in the management team at those companies. I think there's a corollary in looking for investment managers. Yes, there's their track record, but the signal-to-noise ratio is not high. What do you think of these people? I think that matters, too.

Ben Felix: Yeah. The Berk and van Binsbergen paper and Berk and Green talked about how once the market knows a manager is skilled, they're going to flood them with capital up to the point that their skill doesn't benefit investors. But if you can find some characteristic that the market is undervalued, I think, I don't know if it's Jules, or Jonathan and Jules, but some combination of those guys had a paper on managers with foreign last names, then they have better performance, because people under-allocate capital to them, even though they're skilled.

Hendrik Bessembinder: I think that's right. My colleague, Denis Sosyura, has a paper about fund managers from working-class backgrounds. If I remember the punchline, it was that there's also some outperformance there, perhaps, because they're not members of the social network. These are interesting twists, but it just brings back to the point that it's competitive out there. Trying to spot a misvalued security, while there are a lot of other smart people trying to do it. Trying to spot the skilled manager, there are a lot of other smart people trying to do it.

Ben Felix: We talked about this paper that blew everyone’s mind, based on US stocks, a pretty long sample of US stocks. But you've also done a paper on global stocks. How do the results compare if we look at global data?

Hendrik Bessembinder: After I did the first paper, this was just one obvious next question. With the help of some co-authors, I was able to get a pretty broad global sample. It wasn't as long. Only 30 years of data, as opposed to the 90 that I originally had for US stocks. But it was enough to get the answer. The same phenomenon exists in global stocks, but even a little stronger. Maybe we shouldn't be surprised that global stocks are a little more volatile in the short run, and that translates to a little more skewness in the long run. It's a global phenomenon, and I can't forecast the future in the sense of telling you which stocks are going to be in the right tail. 

At this point, I feel really confident saying, skewness is an essential feature of investing in competitive markets. You're going to see it everywhere you look. If it's a less volatile market, you'll see less of it. If it's a more volatile market, you'll see more of it, but you're going to see it everywhere you look for long-run returns.

Mark McGrath: You just touched on this, but what do you think explains the stronger skewness in global stocks compared to US stocks?

Hendrik Bessembinder: I think it's mainly that there's a little more volatility there. We can dig a little bit further into where the skewness comes from at a more mechanical level if that's useful. Once you see where it comes from, I think it also follows intuitively that if there's more volatility, you get more skewness. As I said earlier, in principle, there's other things that can also contribute, like if you had long-run momentum. But I think at a practical level, that's not really where it's coming from. It's just volatility in the short run gives you skewness in the long run.

Ben Felix: What's the expansion on that? You said we could go deeper mechanically. Let's do it.

Hendrik Bessembinder: Sure. The first thing is just to take things at the really big picture level. As long as we have limited liability, the downside, we can't do worse than negative 100%. On the upside, there's no hard cap in terms of the symmetry. We certainly can do more than plus 100%, and many stocks do more than plus 100% in the long run. Just limited liability alone gives you some indication of where the skewness is coming from. But you can also get it from the mechanics of compounding. If you bear it with me for a numerical example, but it really drives it home. I think it's the simplest possible numerical example. Let's just say, there's two possibilities. Your stock will go up 10%, or it'll drop 10%, and then we're going to consider running that two times in a row. Let's think about what the possibilities are.

You could get lucky and draw 10% twice in a row, but with compounding, that's not 20%. That's 21%. Anyway, that's one possibility. You could get 21%. All right, you could get unlucky, and you could draw the negative 10% twice in a row. But with compounding, that's not negative 20%. It's negative 19%. You can already see some asymmetry. Two good draws in a row gives you a bigger outcome than two bad draws in a row.

Now to finish out the whole thing, the other possibility is you get one good draw and one bad draw. You're up 10% one year down, 10% the next year, and that can be an either-order. But again, with compounding, 10% up, 10% down doesn't give you zero, 10% up, 10% down gives you negative 1%. That's a simple example, but it already captured every feature. The upside is bigger than the downside. If you don't get momentum, that is you don't get a good followed by a good, or a bad followed by a bad, if you get reversals, you actually slightly lose money. That simple example gives all the essential features. The upside is bigger than the downside, and there's going to be a lot of outcomes that are a little bit below the average, or somewhat below the average.

Ben Felix: Awesome. I'm glad we dug into that.

Hendrik Bessembinder: If you want to see the effect of volatility, just take that example instead of doing it with 10% up, or 10% down. Do it again with 20% up, or 20% down. That's more volatile. You'll see the effects get bigger. Anyway, that's it in a nutshell.

Ben Felix: A lot of financial planners listening to this podcast, Mark and I are ourselves financial planners, what do you think the practical implications of this research are for financial planning?

Hendrik Bessembinder: The biggest single thing is don't focus just on the mean. The mean is really important, and there's a lot of debate. For financial planning purposes, should we assume a mean risk frame of 6%, or should we assume 7%, or should we assume 5%? I mean, that's really important. People debate it. They should debate it. If the expected return is 6%, and this is a little bit of a techy point, but hate to say it wrong. If you know that number, you can compound it out and say, here's the mean of my wealth distribution. Just zoom by and hold here. You can compound that out and say, here's the mean of my wealth distribution.

Okay, fine. The thing is there's a lot of skewness, both uncertainty and skewness. Probably, you won't end up at the mean. You might end up higher. You might end up lower. With skewness, it's not 50/50. It's much more likely that you'll end up lower than higher, as compared to your mean. The biggest thing is don't just focus on the mean. A lot of financial planners will have already done this, even without any prodding for me. To me, the simplest thing is think about the whole distribution. Think about the whole range of outcomes. The simplest way to do it is with some simulations. I'm sure lots of financial planners have already done simulations. If you do the simulations, or you've already done the simulations, you're going to see that most of your outcomes are below the mean. You can see where the median is. You can see the whole distribution if you just run some simulations.

Ben Felix: Is that just a simple Monte Carlo simulation? How would you approach that?

Hendrik Bessembinder: Simulations could be simple or complicated. The simplest thing would be what you refer to as a Monte Carlo simulation, and assuming that each draw is statistically independent of prior draws. That would be the simplest thing. That would be enough to see the main points. If you just said, look, I think I'm going to have a risk premium of 6% per year. I have volatility of 20% per year, whatever you think is the right number. Just simulate it out for 30 years and see what the distribution looks like. That would make the point. Then, of course, you might say, well, can't we be more realistic than that in our simulations? Of course, there's room to run with that for a long time. As soon as you do the simulations, you'll see the essential point that focusing on the mean is missing a lot.

Ben Felix: Yeah. I'm laughing, because I've played with adding mean reversion to simulations and stuff like that. You can do that in Excel. Most financial planning software though are not built to handle that kind of thing. A little tricky.

Hendrik Bessembinder: I didn't know that the software is mostly not built to handle it. What that says to me is people need to be thinking more about these things.

Ben Felix: I agree with that. We've talked with this already. I'm going to ask one more time just to make sure it's really driven home for listeners. What are the main practical implications of this research for investors?

Hendrik Bessembinder: Well, I think we touched on it. Again, to drive it home, don't focus entirely on the means. Give thought to the fact that there will be skewness in long-run outcomes and that most likely, you'll be below the mean. For financial planning purposes, if you're going to focus on a single number, maybe the median is more informative than the mean, but try to think about the range of possible outcomes. That's the single biggest thing that comes out of it, I believe. I said range. That's a statistical term that's more limited than I meant. No, try to think about the distribution or all the possible outcomes.

Ben Felix: Yeah, that makes sense. I appreciate the precision of language. Okay, I'm going to move on to another paper that was also super interesting. It's which 'Which U.S. Stocks Generated the Highest Long-Term Returns?' The first question is the title, which stocks in the US market have delivered the highest returns to investors? I do want to actually say that you answer this question in multiple different ways in the paper because there are a lot of different ways to look at it. I'll leave it open to interpretation, how you want to answer the question.

Hendrik Bessembinder: Yeah, sure. Part of it is, what do you mean by long-term returns? I have at this point, I think, 96 years, 97 years of data to work with from the KRIS database. One way is to say, over the whole 96 or 7 years, who delivered the highest return? The answer there is Altria Group. It is a mind-boggling number when you actually compound the returns. I don't have the exact number in front of me here, but it's in the vicinity of 250 million percent. It's just a crazy high compound number.

On the other hand, somebody might say, “Well, that's odd. I thought it was an NVIDIA.” Well, NVIDIA actually is at the top of the list if you don't measure things over the whole 95 years. NVIDIA has been there. I don't remember the exact number, 25 years or so. NVIDIA has the highest compound return of any stock over at least a 20-year period. Since they only have about 25 years or so, it's not as big as the ones that have been there the whole 95 years. Answering the question does require saying, well, how long does the stock have to be in the market to be eligible to be included on the list? It makes a difference.

Mark McGrath: I think I read once. I don't remember when or what the time period was, but there was a point where Domino's Pizza was actually the highest compounding stock in history, more so than all of these tech giants and stuff. Totally anecdotal, and I just saw a chart a bit somewhere. I don't remember again what the time frame was, but it was just one of those things where it's like, yeah, it's not always the stocks immediately come to mind that are the biggest winners.

Hendrik Bessembinder: Yeah. Another point of perspective is, do we want to focus on the compound return, the buy and hold return, or do we want to focus on the annualized return, which, again, if we want to be precise in our language, would be the geometric mean, annual return. If you don't say, well, let's look at stocks that were there for at least 20 years, if you look at shorter periods, you can find some stocks with crazy high returns. I don't remember Domino's in particular, but you can find stocks with returns of 1,000% per year for a year or two.

One of the lessons of the paper is that those crazy high returns never persist over long periods. As a matter of fact, among the stocks that were at the top of the all-time leaderboard, that is their buy and hold returns over the 90-some-odd years were the highest, those were mostly stocks that were actually there for 70, 80, 90 years. If you look at their annualized returns, they were good, but they weren't crazy good. They were more 13%, 14%, 15%.

Mark McGrath: Do you see any relationship between the type of company, or industry and earning high returns?

Hendrik Bessembinder: In the particular paper we're talking about, I didn't dig very deeply. I do have another paper that can be found on SSRN, that goes to the question of which industries end up in the right tail. In that paper, I basically did things decade by decade, and I said, okay, what 100 stocks ended up in the right tail for this decade? There might be a tendency to think it's consistently technology stocks that are over there because if you look at the actual lists I put together, you'll often see a lot of tech stocks near the top of the list. I did not find that tech stocks were disproportionately likely to end up in the right tail.

Another way to put that is there's a heck of a lot of tech stocks that ended up in the left tail that we've all forgotten their names. It's not as simple as tech stocks are the stocks that are there. I'll even go further and say, it's not necessarily even what you'd call a "sexy stock." Let me take a particular example. On that list of stocks that delivered the highest lifetime compound returns, South Korea Group is number one. Many of your readers will understand that's a tobacco stock. Don't blame me. I'm just the messenger. Number two on the list is a company called Vulcan Materials. I didn't know what Vulcan Materials was. I had to look it up. Vulcan Materials is a company that has products like sand, gravel, and asphalt.

I don't want to be pejorative to our friends at Vulcan Materials, but most people would not call that a sexy business. I think it's a really interesting lesson. I mean, Warren Buffett, among others, have pointed out the importance, or desirability, or an investor of competitive moats. Competitive moats can arise in a lot of different ways. If you think about sand, gravel, and asphalt, those things are really heavy. You don't move them a long ways. Even those resources in the right locations is a competitive moat. I think that's relevant to understanding why this non-sexy company ended up performing so well.

If there's any lesson, it’s that performance can show up anywhere. Maybe you've got to look beyond the obvious things, like this is a tech firm, or this is a firm that's engaged in disruptive technologies. Okay, makes sense to look there. But let's take one of my favourite examples. I personally think that passenger-carrying drones are going to change the world. That's my view. If you run with that, you might say, well, let's start investing in the companies that are working in that area. Maybe so. Again, it's competitive. We're not the first ones to think about this.

Also, there's going to be a shakeup. Today's companies, some of them aren't going to make it. There's the possibility that even if I'm right, 20 years from now, passenger-carrying drones have changed the world. It could be a company that we haven't heard, of or doesn't exist yet, that ends up at the top of the leaderboard. I don't think it's as simple as go for the glamour companies. It’s do your homework.

Ben Felix: Yup. We've seen that in lots of industries like, I don't know, electric vehicles recently, where prices shot up for all of them and a lot of them ended up being either actual frauds or there just wasn't much there.

Hendrik Bessembinder: I have a couple of follow-up papers that we haven't touched on, but I created some lists of the biggest wealth-destroying companies. You can find a couple of electric car companies on that list.

Ben Felix: I missed that paper. What was the name of the industry paper?

Hendrik Bessembinder: The industry paper, the name was just something like, Do Technology Stocks Dominate? Something like that. You can find it on SSRN. The other one that I referred to was just one of the updates. I've been updating the papers on a three-year cycle. There's one that says, wealth creation to 2019, then there's another one that says, wealth creation to 2022. In a while, there'll be one that says, wealth creation to 2025. Slight variations on the titles.

Ben Felix: Okay, got it.

Hendrik Bessembinder: I think you can find. What I just referred to was the one that went through 2022.

Ben Felix: I just found that new technology stocks dominate. I wish I'd found that one. I didn't find it when I was preparing for our conversation. I'm going to read that one, though, right after this.

Hendrik Bessembinder: I appreciate that. I guess, that means I've turned out enough papers that not everybody knows about all of them. There’s still room if you're interested.

Ben Felix: On this, which stocks are generally the highest long-term returns paper, what do you think the practical insights are for investors?

Hendrik Bessembinder: I really think it comes back to this question of, do you want skewness or not? If skewness doesn't get you excited, the arguments are stronger than ever for just diversifying broadly. If skewness gets you excited, two reasons for that. You either think you're skilled, or you just like the possibility of the dream. You want to keep the dream alive. If you like skewness, then my paper says, well, diversification reduces the skewness. I think those are the practical implications.

Ben Felix: All right. One more paper I want to talk about on mutual fund returns, which was super cool to see this paper because it takes the predictions, I guess, from the skewness and stock returns paper and puts it into what happens in live portfolios when people are actually building relatively concentrated portfolios in an attempt to beat the market. It's like an empirical investigation of the Heath and Paulson and Witt paper that says, yeah, this will probably happen. Then you show that, yes, it in fact does.

Hendrik Bessembinder: Yeah, exactly. This was to take the ideas from the first paper to portfolios and not to random bootstrap portfolios, but to actual portfolios that actual fund managers compiled and managed.

Ben Felix: Yeah. Some of the results are crazy. I'm not going to get ahead of myself at all. I'll ask you the first question I have here. What proportion of US equity mutual funds in your sample outperform SPY? By the way, I love that you used a live fund as a comparison. What percent proportion of US equity mutual funds beat SPY in your sample at the decade horizon, specifically?

Hendrik Bessembinder: Actually, I think I've got here the lifetime number, it's a 30-year sample and it's not going to be greatly different. It's 30%. 30% of funds beat the SPY. I'm glad you mentioned that, but I think it's important to compare to a benchmark that in principle, somebody could have earned. Anyway, that's why we chose the SPY as the benchmark. By the way, I'll mention here, there's another widely recognized study that goes after the same question, and that's the SPIVA scorecard. I'll just refer people to the paper for the details, but a 30% is actually a higher number than what SPIVA reports. If you're curious why that is, I'll refer interested people to the paper.

Mark McGrath: I assume fees.

Ben Felix: Yeah, I read that part of the paper with interest, because your number is quite a bit higher than SPIVA.

Mark McGrath: SPIVA also benchmarks to the index, not to a live fund, is that right?

Hendrik Bessembinder: I believe that's true, but it's not the main thing driving it.

Ben Felix: Should we talk about it? Because people might be interested.

Mark McGrath: Can we, please?

Hendrik Bessembinder: I guess, we could. I mean, I think in some sense, the SPIVA people are transparent about it. They focus on funds that outperform and survive. They take, say, a 20-year period and they say, okay, during the 20 years, they take the funds that were there at the start of the 20 years, and then they say, did you outperform? Yes, or no? Were you there for the whole 20 years? Yes, or no? To be in their number, you have to both outperform and be there for the 20 years. You might not see this coming, but there's quite a lot of funds that outperform but were not there for the whole 20 years. That's the difference.

Ben Felix: Yeah, that's interesting. I'm not sure how the US study is done. But in Canada, I know they also mix in commission-based funds into their sample, which have much higher fees to pay for the cost of advice. that drives down the performance just because the fees are so much higher. I don't know how they do it in the US report, though.

Hendrik Bessembinder: Yeah, I'm not sure either. They have footnotes that detail their methods, but I can't recall all of them.

Ben Felix: Yeah, that one's not in a footnote. That one, I had to email years ago to ask about their methodology. I don't know if that contributes, but it could make a difference, obviously, if the fees are a lot higher than your sample.

Hendrik Bessembinder: Yeah, good.

Mark McGrath: Okay, so back to this paper. How does the average mutual fund perform?

Hendrik Bessembinder: If we focus on means, averages, in some sense, I've got the same result that the prior papers have, which is basically, that on average, mutual funds turn in slightly negative performance. They slightly trail their benchmarks. This is something that other people have found, too. There is some evidence of skill among fund managers, but not quite enough to overcome their fees on average. When I compound the returns, I've still got essentially the same punchline about what happens on average. But I've been trying to emphasize one of the messages is we need to look beyond averages. There is skewness in the distribution of compound fund returns. It's for the same reasons that there is an individual stock. It's not nearly as dramatic as it is an individual stock for the reasons we've been talking about it, but there is skewness in the distribution and it's enough to matter.

Ben Felix: Yeah, that's one of the things that I found so interesting about this paper is that the majority of funds underperform before fees, like gross of fees. That's crazy. It's expected based on what we've been talking about, but it's just crazy to think about.

Hendrik Bessembinder: Exactly, right. On average, they outperform before fees. But again, the average is not the typical fund. The typical fund underperforms, even before deducting fees.

Ben Felix: That's wild. Now, the other side of that, as we've been talking about, so most funds underperform by number of funds, but are there also some big winners, like we see in stock returns?

Hendrik Bessembinder: Yup, exactly. It's not as dramatic as in the stock returns. I'm not going to tell you about anybody getting 250 million percent. We had almost 8,000 funds in the study. Among those, there were about 450 that doubled the SPY over their lifetimes, and there were about 160 that tripled the SPY over their lifetimes. The SPY is a pretty high hurdle during the 30 years we studied, 1990 to 2020 roughly. Tripling the SPY is really impressive. There were some fund managers that really delivered, or we still have the question of can you identify them in real time, as opposed to looking back.

Ben Felix: Yup. The persistence question. It's a tough one.

Hendrik Bessembinder: Yup.

Mark McGrath: Can you hold throughout that whole period, too? You have to capture the entire period returns yourself, and you have to behave well.

Ben Felix: Oh, yeah. That's an interesting point.

Hendrik Bessembinder: Maybe we're getting a little ahead of ourselves here, because I'm pretty sure you're going to ask me about the 1 trillion-dollar number in a minute, so we can maybe jump to that. In the abstract of the paper, we say mutual fund investors underperformed by a trillion compared to the SPY benchmark, which is a big number, a striking number, but it's got a few pieces built into it. Again, we do find, consistent with others, that there's evidence that on average, fund managers are skilled, but their fees are bigger than the skill, on average. That's one contributor, fees.

There's also, we consider opportunity costs. Essentially, if you paid a 1% fee back in 1990, that's 1% less that you had invested as the market had a great three decades. I'm measuring things at the end of the sample. We're also picking up opportunity costs on fees. The third thing that you touched on there, it's partly investor's own fault. Return chasing behaviour has not helped. It's actually hurt investors. We touched on this earlier. You can compute buy and hold returns. They're hypothetical if somebody had done buy and hold. The SPY is a buy-and-hold benchmark. If this is what you mentioned, Mark, the benchmark is the hypothetical person who bought and held the SPY.

In actual funds, people are not buy-and-hold investors. You can measure the buy-and-hold returns, which is the geometric mean, or you can measure this dollar-weighted return, which takes into account money going in and out, the effects of return chasing. A significant part, we couldn't find a way to cleanly break it into pieces, but return chasing also contributes to that negative 1 trillion number. It's a combination of fees, compounding on fees and investors' own return-chasing behaviour.

Mark McGrath: Crazy.

Ben Felix: Yeah, it's cool that you're able to get that piece in there. I did not realize that when I read through the paper.

Hendrik Bessembinder: It's subtle. All three of them are going on in there.

Ben Felix: Yeah. Makes sense though.

Hendrik Bessembinder: I might throw in here an editorial comment because if you see that one trillion-dollar number, it'd be easy to conclude from that, well, I'll just stay away from actively managed mutual funds. Again, part of the problem is investors own behaviour. Control this tendency to chase returns. It's not helping you. The other thing is in the past, there's this question, how big is active versus passive? What I take away from this is in the past, we had some combination of too much active money and too high a fees. Active has gotten smaller and fees have gotten lower. We got to make decisions based on the future, not the past. With a smaller active segment and lower fees, those past numbers don't have to dominate our thinking about the future.

Ben Felix: That is really interesting. Because the index share is getting pretty significant, especially in the US market.

Hendrik Bessembinder: Just doing thought experiments, if that index share got up to, say, 95%, then I have really strong intuition that there would be money to be made in active funds. Because if everybody's indexing, why should the prices be efficient? If the prices aren’t efficient, now you know the reasoning.

Ben Felix: Yeah, the Grossman-Stiglitz Paradox.

Hendrik Bessembinder: Exactly.

Ben Felix: We had Marco Sammon at Harvard on the podcast a while ago, and he has a paper estimating the total active share, not just of funds, but he uses transaction volume around reconstitution dates, I think. His number was, geez, 34% or something like that of the US market. Still got a ways to go, maybe, I don't know, from 95%. I don't know what the limit is, though.

Hendrik Bessembinder: I don't know either. Marco's got a series of interesting papers. We're hosting a conference here. My academic department is hosting a conference here. One of his papers is on the program. I'm looking forward to seeing it.

Ben Felix: Okay. Nice. Yeah. He was great on the podcast here. We talked about mutual fund underperforms. We talked about fees. We talked about skewness.  Do you know roughly even, how much of mutual fund underperformance is explained by fees and how much by skewness?

Hendrik Bessembinder: Yes. The way we sunk our teeth into that, we've got the finding that the majority of funds underperform the SPY. We asked ourselves, well, if you artificially added performance to every fund, how much would you have to add to get to the point where half the funds outperform the SPY? Our answer was, you have to add 12 basis points per month. That's the effect of skewness. The net effect is about 12 basis points per month. Now fees, in our sample average, about nine basis points per month. What I take away from that is that the skewness effect is actually a little bigger than the fee effect in terms of what a typical fund does.

Mark McGrath: What are the lessons from this research for investors?

Hendrik Bessembinder: It's parallel to the individual stock stuff. The central question again, maybe the single biggest question is, should I be a passive diversified investor, or should I be an active investor? It's the same question here. I think many investors make sense for a lot of investors to be indexers, or be broadly diversified. There's actually a distinction there that we maybe should spend a little time on. You don't have to be in an index to be diversified. The debate about the magnificent seven and their effect on the evaluated indices is relevant in the background there.

Let me rephrase it a little bit. Be broadly diversified, versus being active. For many people, it makes sense to be broadly diversified. But if you either value skewness, or you think you can find the right fund manager, you'd deviate from that.

Ben Felix: I just made a video on this that by the time this episode is out, I think my video will have been released. My conclusions were way more extreme than that. I said, most people should be indexing. I did think about it, my YouTube videos are shorter than this podcast. They're 10 or 15-minute videos. It's harder to keep people's attention, I think, in those shorter videos. I don't have as much nuance, but my case for index funds was something like low costs, broad diversification, tax efficient, simple, and theoretically consistent. You can get all of those things in an actively managed fund. Telling that to a random person with relatively low financial literacy is not going to help them, I don't think.

Hendrik Bessembinder: Yeah. I'm not sure your punchline and mine are that much different. If people did say, “Well, what do you advise for me?” Not that I've given advice. Most of the time, I think, my answer would be broadly diversified and a low-cost index fund can deliver that for you. Some people are skilled. Some managers are skilled. Some people like skewness. Should I tell them that they shouldn't like skewness? I mean, that's their decision.

Ben Felix: That's very true.

Hendrik Bessembinder: I just want them to be educated about it.

Ben Felix: We had, I think Vanguard's former CIO on this podcast a while ago, and he talked about how there was some evidence, I can't remember if this was academic, published papers or not, or if it was Vanguard evidence, but they had evidence that fund companies were able to identify skilled managers before the fact.

Hendrik Bessembinder: I'm at least open-minded to the idea. In economic speak, it's comparative advantage. Some people have a comparative advantage at running funds, and some people have comparative advantage at identifying those with comparative advantage. The question we all have to ask ourselves though is, is that me? Do I have the comparative advantage?

Ben Felix: The other interesting question on the size of the active management industry is, even if we decided at some point, okay, the passive is too big, it makes sense to go active, you still have to make the decision at some point to go back to passive, which is not an easy decision.

Hendrik Bessembinder: Yeah. The best answer might differ at different points of time.

Mark McGrath: And the risk of being wrong is really high too, right?

Ben Felix: Yeah. Years ago, we had Lubos Pastor on this podcast, and he talked about his research on that. We had the same conversation. I left thinking, I still don't know when I would switch back to passive. We've got a couple more questions here. Mark, I'll leave the last one for you. I'll ask the second and last one. We talked a lot, Hank, about your research on skewness, broadly speaking, and just how it affects long-term returns. You've got a ton of other research though. What other areas of your research do you think investors should know about?

Hendrik Bessembinder: Well, you're right. I've been doing finance research for almost 40 years, and I did a wide array of other things before I stumbled into this idea of looking at long-run market outcomes. It's obvious that the world has been less interested in the other things I did as compared to the long-run stuff. Probably doesn't make sense to try and go through the whole list. But if anybody is curious, you can find almost everything on SSRN. I've pivoted a few times in my career. I just follow what seems interesting to me. What's interesting and also gives an opportunity to ask interesting questions.

I worked for a few years on commodities or futures, and it was mostly from a risk-return perspective on how commodities can alter risk-return. That was fun. Then I pivoted to what we call market microstructure, which is basically trading strategies, trading rules, and such. I actually think some of the things that I've done in market microstructure might be of interest to a somewhat broader set of people if they came across them. For example, I've got some papers about bond market trading and what determines liquidity and trading costs in the bond markets that some people might find interesting. I've also done some papers on the various rules for trading.

Take one example, it might seem almost irrelevant if you haven't really thought about it. The tick size in financial markets, the minimum price increment, you might think, who cares about that penny? But it turns out to be actually quite important for people's order submission strategy and order management strategies, the tick size. I studied the tick size and have some things to say about whether a big or small tick size is good for the markets.

I took a very unusual pivot. This definitely has a specialized audience, but I just think the industry is so fascinating, and that's electricity. There's been a ton written about commodity trading and about hedging, but what makes electricity uniquely interesting is it's so hard to store it. Of course, people are working hard at strategies for being able to store electricity. Think batteries, pump storage and such, but we're a long way away from it being storable like other commodities are. That means its prices are really volatile and it also means that the instruments for risk management, options, futures, swaps and such, the theory about how to value, or how to price those derivatives is all based on storing. It's all based on arbitrage strategies between being in the spot or being in the derivative and it's all based on storage.

None of the standard stuff applies to electricity. That's what made it so interesting for me. I've done a couple of papers about electricity markets that I think they're interesting, but others are only going to find it interesting if they think the lead in here was a good motivator.

I'd like to throw in one other thing and it's actually really recent, but I'm excited about it. The studies that I started with and we've been talking about got me to thinking more about long-run outcomes in investments. This is still under the umbrella of long-run outcomes, but it's not about skewness in particular. But I think it's a big issue to be thinking about. Most of the ways that we measure returns implicitly have built into them. This applies to what I've done also. They implicitly have built in that it's all about wealth accumulation. It's all about getting a big portfolio. Buy and hold returns, what the wealth creation measures. But I think that misses the point of why we invest.

Maybe you do want to have a big portfolio at some target date, but I don't think the idea is to have the biggest possible portfolio in the last month of your life. We think about why do we actually invest. We invest, because you can pull money out of your investments. For other stuff, the narrow version of that is I pull money out so I can consume. You’re a retiree and you pull money out to live off of. Okay, but you pull money out for real purposes, whatever those are. You're pulling them out to give money to charity, you want to fund cancer research, or you're running an endowment, you're talking about pulling money out to fund research, or operate your university. I think we actually invest to be able to pull money out for other purposes.

Anyway, with that lead in, my co-authors developed, in some sense, it's just a new measure of returns, but we call it the sustainable return. Yes, we are cashing in a little bit on the popularity of that term, sustainable. What it is is instead of measuring what your portfolio accumulates to, we measure how much could you have pulled out each period such that your final value is equal to your initial value. That's the sustainable part. You haven't eaten the seed corn. It's written up in a paper that was just published in the Financial Analyst Journal last month, or you can find it on SSRN. The reason I think this is powerful and the reason I'm excited about it is I think we should be thinking more about measures of investment performance that focus on what can you pull out of the investment for other purposes, as opposed to these ones that implicitly assume it's all about how big a portfolio can you build.

Ben Felix: Yeah, I did see that paper. I didn't include it in the questions, because I had a lot to read with the skewness papers already. That one did look really interesting. I like the concept a lot.

Hendrik Bessembinder: Yeah, I'm excited about it, and to the extent, I couldn't use this to go into a marketing role. I recommend that paper to other people. I think it's an avenue worth thinking more about it.

Ben Felix: Cool. I'll have to go back and reread it carefully.

Mark McGrath: It's obviously very relevant to us as planners because that's a lot of what we're trying to solve for clients. How much can you spend from your portfolio over certain time frames and when can you stop working and rely on the portfolio, more on that type of thing? Yeah, we'll have to go take a look at it.

Hendrik Bessembinder: Anything related to pension planning, or endowment management in my mind, this is the natural way to think about it.

Mark McGrath: Awesome. This has been great. Hank, we've got one more question for you, which we like to ask all of our guests and that’s, how do you define success in your life?

Hendrik Bessembinder: Philosophical question. I'm a finance professor, so I'll answer it partly in finance terminology. To some extent, it ties into what I was talking about in this most recent paper. If you have enough money and wealth that you don't have to worry about money and wealth, it's not the whole story, but I think it's a measure of financial success. Circling back, I don't think it's about trying to always make your portfolio bigger. You've got a lot of things to balance in your life, including what are you going to pull money out for other purposes. But if you've managed your finances so that you don't have to worry about your finances, that sounds like success in the finance domain to me.

Then, of course, I throw in other things like, if you've got a job that you enjoy, which I'm fortunate enough to have, that would be a measure of success. If you've got a balance between your job you enjoy and the other things that are important to you, like your family and your hobbies and your interests, that's a measure of success. Anyway, those are the things that come to mind for me.

Ben Felix: Great answers.

Mark McGrath: Great.

Ben Felix: All right. That's our last question, Hank. This has been a fantastic conversation. I know our listeners are going to love it. We really appreciate you coming on the podcast.

Hendrik Bessembinder: All right. Well, it's my pleasure. We covered a lot of ground. I hope it's useful to people. I like to do research, but part of the reason I like to do it is the hope that will actually be useful to people.

Ben Felix: This will be useful, I'm sure.

Hendrik Bessembinder: All right. Well, thanks, gentlemen.

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Papers From Today’s Episode: 

'Do Stocks Outperform Treasury Bills?' — https://www.sciencedirect.com/science/article/abs/pii/S0304405X18301521

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Rational Reminder on iTunes — https://itunes.apple.com/ca/podcast/the-rational-reminder-podcast/id1426530582.
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Benjamin Felix — https://pwlcapital.com/our-team/

Benjamin on X — https://x.com/benjaminwfelix

Benjamin on LinkedIn — https://www.linkedin.com/in/benjaminwfelix/

Mark McGrath on LinkedIn — https://www.linkedin.com/in/markmcgrathcfp/
Mark McGrath on X — https://x.com/MarkMcGrathCFP

Professor Hendrik Bessembinder — https://search.asu.edu/profile/2717225

Arizona State University — https://www.asu.edu/

KRIS — https://www.kris-online.com/

Professor Hendrik Bessembinder papers on SSRN — https://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=667

SPIVA — https://www.spglobal.com/spdji/en/research-insights/spiva/

Episode 322: Professor Marco Sammon — https://rationalreminder.ca/podcast/322

Episode 124: Professor Lubos Pastor — https://rationalreminder.ca/podcast/124