Eugene Fama and David Booth on the Birth of Modern Finance
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Hello and welcome to another episode of the All Thoughts Podcast. I'm Traci Alloway. And I'm Joe Weisenthal. Joe, what's your favorite financial movie? I don't think I've ever asked you that question. Really? I mean, Trading Places. Oh, that's funny. That's mine too. Yeah. And not only because it's funny, but because it led to a real life development, which I don't think a lot of people know, but the CFTC set up something called the Eddie Murphy Rule. I didn't

I didn't know that. Because of trading places. I have no idea where you're going with this, by the way. And I think there has been an enforcement action. Well, what I was going to say is I think there is actually a lack of really good financial movies. Ah, okay. Here you go. Trading places aside. Yes, I would agree with it. Yeah. I know we have the big short and margin call was a very realistic description of what it's like to work at a bank.

But I think we need more in our lives. And I think we also need financial movies that sort of delve into some of the theories of financial markets. And I get why we don't. Those are really difficult to illustrate in a visual way, but I still want them. Me too.

All right. Keep going, Tracy. Okay. Well, the good news is I just watched one that fits into that category. So there's a new documentary out called Tune Out the Noise, and it's all about the birth of modern finance. And it features an

absolutely all-star cast of financial luminaries. So, you know, there are people like Merton Miller, Myron Scholes, Ken French, Markowitz, like the list goes on and on and on. And we're going to talk to two of them today. I'm really excited because I'm finally going to have a chance to ask, is it all priced in? Because this is my core belief about markets that it's like, nope, it's all priced in.

And yet there appears to be a financial industry that must on some level be premised on the idea that it's not priced in. But I always assume that it's all priced in. And so maybe we'll finally get an answer to this question. I suspect the way you feel about the term premium is the way I feel about the efficient markets hypothesis. But let's get into it. We are speaking with David Booth, the founder and chairman of Dimensional Fund Advisors.

and Professor Eugene Fama, who is, of course, a Nobel laureate. He is also a director at Dimensional, has had a long-running intellectual partnership with the firm. He's also sometimes called the father of modern finance. I could keep going on with the honorifics here, but you get the idea, I think. So, David and Gene, welcome to the show. Thank you. Well, thanks for having us. I'm looking forward to it.

I guess I'll start with the obvious question, but why a documentary movie about modern finance? It is, as I mentioned earlier, not exactly an easy story to tell visually. Well, it didn't start out to be a documentary. What happened was we started working with Errol Morris. You know, he

won the Academy Award for his film Fog of War, a well-known documentarian. And I was talking to him about how we could use some of his expertise for our firm. And he got really into it. He had not much background in finance and just got so fired up. He wanted to make it his film rather than our film, which I found to be very exciting. That's cool.

We've done an episode with Dimensionals co-CEO Gerard O'Reilly. Why don't you talk to us a little bit about the partnership of the two of you for people who are not familiar, for people who are going to be watching the film for the first time. The two of you have been working together for literally decades and really two of the biggest names truly in the history of finance industry.

What is the sort of short version of this sort of intellectual partnership and how this firm Dimensional came about? Well, David was my research assistant 55 years ago, David. Yeah. Anyway, he worked for me for several years at the University of Chicago. And finally he came to me and said, I see what you do and I don't want to do it. So...

He said he wanted to go off and work in the financial industries. So I called Mac McQuown and got David a job that way with Wells Fargo. I guess it was at the time, David, right? Right. In 1971. Then eventually he went off on his own, found a dimensional and came back to me and asked me if I wanted to be somehow involved. We've been going at it ever since.

Oh, yeah, this was in the movie. So I think Wells Fargo basically just decided to share some of its data and analysis with Vanguard, like at the very beginning of Jack Bogle's career. And everyone was sort of scratching their heads about why that happened. But do we have any sense of why that happened? Was there just a spirit of research or academic camaraderie that made private organizations share things with each other?

Well, one of the things I've always admired about Gene is his research, which we use extensively, he's always insisted that his research be in the public domain. We're not in the business of creating black box that nobody understands. So it's so critically important to have an open-air philosophy about sharing research.

Well, you know, we got off to a slow start in some ways, but it was a fundamental question. Can you even track the performance of an index? And so Wells had done a lot of simulations and stuff. And when the group I was working on at Wells got shut down, Mac just volunteered to Bogle to share all of his data with him. Hmm.

Gene, I'm curious from your perspective, how did this interest you as a intellectual field of study? And we'll get into some of the specific and sort of groundbreaking contributions to what many people now consider absolute truths to how the market worked. But this idea, some of your ideas, like why, what attracted you to the study of markets and some of your early research?

Well, I started on it in college, actually. I worked for a professor at Tufts that had a stock market forecasting service. And my job was to come up with new ways to beat the market. How'd that go? It didn't go very well in the following sense. He was a very good statistician, so he always kept a holdout sample. And my ideas always worked in sample, but they never worked out of sample. So that was my first lesson on

what you can expect by trying to beat the market. And after that, I went off to Chicago, took my data with me from Tufts, and eventually wrote my thesis using that data, which was kind of the first and maybe one of the bigger trumpeting of efficient markets. The term wasn't even called that at the time, but eventually that term came around as well.

One of the things that's interesting about that, observe, he did a study based on data collected by hand. And that was kind of the state of the world when I went to Chicago.

to do a research project, frequently had to hand collect the data. You know, these new kids today wouldn't be aghast if they knew how we did things in the old days. Well, I remember in the old days of Bloomberg, we often inputted a lot of financial—if you're working in the global data department, you certainly inputted a lot of things by hand as well—

This leads to a question I wanted to ask you. So a big chunk of the documentary is about all these different people who spent time at the University of Chicago. What was in the water at the university that it attracted all these names that went on to do big things in finance? Well, Merton Miller was an important person. He was deeply interested in this stuff. And Harry Roberts was another important person who had written on

something resembling what would be now called the fishing markets way back in the 50s. So he was very much interested in it. And they were kind of the two shining lights in this area. And plus, then there were a lot of PhD students, including me, who needed thesis topics. So having faculty interested in the topic was a good way of having research done by students in that topic because that was the way to graduate. And at the time I had

two kids with another one on the way. So I was very, very keen on getting out quickly. Well, I would also add, you know, Jim Lurie. I mean, Jim and Larry Fisher, they persuaded Merrill Lynch to fund a study to collect a survivorship bias-free database, which enabled all these new young hotshots to do their research. And until that point, the data had

had never been collected correctly. And so he couldn't really do the research. So when Larry started out to, Larry Fisher started out to collect that data and put it together, a computer didn't exist that could handle it. But he said, well, it's going to come along by the time we finish this, there'll be a computer that can handle it. And he turned out to be right.

Well, actually, this is exactly what I wanted to ask. And I think it sort of speaks to like a big theoretical question. Let's say part of good investing is having good data. Like if you have to collect the data by hand,

You're already going to probably knock out 99.9% of the people who have interest because I wouldn't do it because my wrists get really tired really fast and my handwriting is garbage. So I wouldn't even be able to read what I had written in the graph paper, etc.,

A lot of things that we take for granted about investing today, including measuring the performance of an index, are things that literally take a few keystrokes or less on a Bloomberg terminal today. And I'm curious, like when you think about like generating superior returns over time, how much of an edge was that to just be willing to do the hard work of collecting data?

Look, all these tests of market efficiency, which started in the 60s, you know, and keep showing the same result in every sense, even though with increasing levels of sophistication of researchers and people having access to more and more data, better data, faster data, all of that, it still shows the same outcome of it doesn't look like trying to outguess the market is a winning game. Hmm.

So since we're on the subject of the efficient markets hypothesis, one of your former students who also went on to great fame, Cliff Asness, he published his own paper called the Less Efficient Markets Hypothesis. And it argues that markets are less efficient than they once were, in part because social media has basically turned us all into trend following idiots, I guess. And

And this is something that I've occasionally wondered. If the efficient markets hypothesis is reliant on people making the right decisions with the information that they have or the data they have, what happens if we all get collectively more stupid? And I guess a different way of asking this is, has your view of the efficient markets hypothesis changed at all over time?

No, it hasn't really changed. It's adaptive in the sense that I never said that the market was efficient for everybody. There are, for example, there's lots of evidence, for example, that company insiders have information that isn't already in prices. So as far as they're concerned, the stock of their company is not priced efficiently.

That's one instance of it. But as far as professional managers are concerned, there is evidence that if you give them back all their fees and expenses, there are some who do have enough information to beat the market. But if you don't take out the fees and expenses, then the active managers look terrible relative to the passive managers. So that's the kind of...

data and results that makes market efficiency look pretty good. But it's not, it's just a hypothesis. It's not a literal truth. It's just an approximation to the world. But it worked really well for almost everybody.

Yeah.

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So this gets to like a question that I've asked before, and I'm now thrilled to get to ask it to you, which is why does the financial industry exist if markets are efficient? Because there are a lot of people that collect very big paychecks from some notion that they can deliver better returns than someone else to their clients.

If markets are efficient, at least to most people in the industry, why do we have this industry? Because there are people who think they can pick the managers that have special information. That's what keeps it going. That's what keeps the active managers going. It's individuals who don't think that passive investing is for them.

And they invest, they go with the active people. So that markets are always about competition among different kinds of players. And then we see who comes out on top. Gene, how serious are you when you say stuff like there's no such thing as a bubble or that bubbles are only identifiable after they burst? So it's pointless to talk about them. Yeah.

Deadly. Very serious? Explain it more, because Joe and I have lots of episodes where we talk about either past bubbles or overvaluations. Yeah, so with 2028, it's always explained why prices went up and why they went down, but

In my view, what a bubble means is price has gone up and you can predict when it's going to go down, when that whole phenomenon is going to, the whole price movement is going to go away. And that's what's proven really difficult to do. So lots of people use the word bubble very loosely. I canceled my subscription to The Economist because I'm using the word bubble.

- Us journalists are terrible about overusing blah, blah, blah. I will cop to that on behalf of the entire profession. - Right. So I need to know what the definition is before I can respond to it. And in that case, that's much more difficult. Most people aren't willing to do that. There are economists that are willing to do it and they can deal with that. It has to be some predictability about when it's gonna end. And that's what proven really difficult to establish.

Right. It seems fairly clear that you could sort of sense like we're in some sort of mania and even knowing that fact and everyone agreeing on that fact. In fact, to try to establish that fact is often a good recipe for losing all your money if you're short it or losing all your clients if you're avoiding it. So I certainly take that point. Let me press further, though. So a lot of your research and this idea of market efficiency, but.

You've also worked on factors that seem over time historically to outperform. And so the idea of small companies outperforming big companies or value companies outperforming over time, Dimensional has funds that aren't just the pure market portfolio. Reconcile the existence of that with the idea of efficient markets. Okay, that's a good question. So

Everybody has this confusion. The confusion is mixing together market efficiency and the dimensions of risk in portfolio selection. So...

Going back all the way to Markowitz, we've long known, for example, that people don't like variance. They don't like uncertainty about future returns. And they're willing to pay something to avoid it. So that gave rise to the Shab-Lentner so-called capital asset pricing model, in which sensitivity to the market was the measure of

What was the measure of risk? So basically, it's a confusion of prices being reflecting value and the story about what are the dimensions of risk in the market.

That's a confusion that almost everybody seems to have. So an official market doesn't say there aren't risk premiums in the market. It does not say that at all. One way to think about it is, you know, define the market to be all the stocks and bonds that are out there. Most of us believe stocks over the long haul have a higher return than bonds. But few people invest all their money in stocks. It doesn't mean stocks are inefficient or inefficiently priced. Those

Those are the market prices. And you look at different combinations of the two and they provide different distributions of outcomes and you just find that distribution that works best for you. So a big chunk of the documentary is about the birth of passive investing and its connection with the efficient markets hypothesis. What's been the impact of the growth of passive investing on the market?

Because we often hear that, you know, markets are reflexive. Moves can end up impacting the market itself. And David, I think you yourself have argued that one of passive investing's biggest flaws is still very much alive. The index effect where stock prices go up a lot when a company is added to an index, even though everyone in theory should know that this is going to happen. And so it should already be priced in. How has passive actually changed the market?

Well, that's an interesting question. First off, the impact of an index adding a new name, causing temporary prices to go up, that's a temporary effect. It doesn't really impact the long-term investor very much. One question that comes up a lot is, if everybody indexed, then there would be no price discovery and wouldn't markets become inefficient? That's kind of

And my answer to that is, well, let's take a look at the behavior of the market over the last 20 years. There's been an incredible movement to indexing over that time period. And yet there's been an incredible increase in trading volume. I don't think price discovery has been related to trading volume. So just because there's a big movement to indexing doesn't mean trading volume will decline.

What's happened, unfortunately, is it turns out, like a lot of things that can be used for good, they can also be used for bad. And, you know, index funds are the ideal market timing vehicle. I'll buy this healthcare index fund and sell my technology fund or whatever it is. And I think that's really kind of what's happened in the marketplace is it's kind of turned individual, instead of individual stock selection, it's kind of like a

a big gambling casino where you have a lot of different ways you can make your bets. So it doesn't look like in terms of the basic notion of market efficiency, it doesn't appear to have had much impact on that. Let me just take a little different direction. People worry that if everybody goes passive, how will prices get formed? And that's a legitimate concern. But then the issue is who drops out?

Who doesn't go active anymore? If it's bad active managers, people who have no special information, if they drop out, then you need fewer good active people to keep prices in line. So it depends on who drops out.

as to whether it has any effect at all on market efficiency. Now, we haven't been able to discern anything like that in the behavior of prices, but that is the question. Since we're on the topic of indexing, you know, the market nowadays, as you mentioned, is basically defined by benchmark indexes, things like the S&P 500 or the MSCI World Index. And the

The benchmark index providers will often say that they're just holding up a mirror to the market as it exists. They're neutral. But it seems kind of obvious to me that their decisions do impact the market. And some of those decisions can be subjective, you know, when it comes to measuring things like liquidity or how developed a particular bond market is or whatever. Are we just outsourcing investment decisions to index providers?

You have to choose the one you want. So my own takes run in the direction of a total market index being a good choice for almost everybody. So I don't go for the subset things like 30, whatever, 30 Dow Jones. That was always kind of dumb. But yeah.

Or even the S&P 500, that's only 500. There's a lot more stocks out there than that. Let me just recoil against the term passive. In my view, there's no such thing as passive management. And you're touching on something right there. The

to different index providers and how they do it and they all do it differently and so forth. And, you know, Standard & Poor's when it wants to add a stock to its S&P 500, you know, the investment committee sits around and talks about, you know, what do you like? You know, it's,

The S&P 500 is 500 of the largest companies, but it's not the 500 largest companies. And there's quite a bit of subjective judgment goes into deciding what stock goes into the index, which if you're going to an index fund because you don't like stock selection, that's not the kind of activity you want to see.

I want to go back to this idea of even if markets are efficient, there still are risk premia and certain asset classes are expected to go up more than others due to people wanting to avoid drawdowns, etc. You know, like I don't make many active decisions. I'm like a good like I follow what I read in the news and I like have some stocks and

And, you know, I'd probably have some treasuries and some fund or something like that. And I don't like pay attention to it much. Looking back, though, at historical trends in portfolio construction, I sometimes wonder why.

Why should anyone own bonds? Because you say hardly anyone just owns stocks. And that seems to be objectively true. But I wonder if like, is there a reason to question some of this dogma of like, why? Like, if I'm not going to retire in 30 years, do I care about, you know, I'm already diversifying over time because I make an allocation to my retirement funds.

with every paycheck. So I'm already getting time diversification. Are there fundamental questions in portfolio construction that you think need to be rethought? If over the next 30 years before I can retire, 25 years maybe, like...

If almost everyone thinks it's certain that stocks will outperform bonds, why am I holding bonds? That's nuts. If almost everybody thinks that's true, but it's not true. Stocks don't get...

Less risky in the long term. Risk accumulates. I don't understand that. I don't understand how... The risk is when you retire. When you retire, there will be a period when stocks have done particularly poorly and you will get hurt. That's always a possibility. It doesn't go away with time. So the presumption is what's incorrect. The risk is always there. You don't get rid of it. What do you think about the term smart beta? Yeah.

And is dimensional doing smart beta? Yeah. Smart is a marketing term. Show me a dumb beta.

I'm sure I could find some examples, but they certainly wouldn't have set out to create Dumb Moda. There's a lot of marketing in the financial business. That's one of them. That's one of the big ones. But what does it mean to you? So like when you hear that term, like what is the person trying to sell to me? Well, you have to give me an example because I don't take it seriously, obviously.

You're talking about me chuckling here. Well, I think it's Gene's research that he did with Ken French, you know, his landmark 92 paper on

called cross-section of expected returns. Anyway, that kind of gave empirical support to the idea that there can be many dimensions of returns. So if you focus on a certain dimension, some people came up with the term smart beta. It's not smart. I mean, it's just a reflection of the research and the dimensions of returns, you know? ♪

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the perfect mattress, update a subscription plan, or even troubleshoot a new device. Always friendly, always helpful, always ready. Visit sierra.ai to learn more. That's sierra.ai. Something that I'm really interested in when it comes to markets, particularly I would say over the last 15 years since the great financial crisis, small caps have certainly not

any sort of superior risk-adjusted returns to large caps. And you can see that on basically any chart. And growth companies year after year, you know, by the traditional metrics of what we call growth and value, and I know people sometimes try to redefine these to

allow them to put Nvidia in their value fund. Clearly growth has been outperforming for a long time. And part of the reason it seems very obvious to me that these big tech stocks have done so well is because the companies have all done extraordinarily well in beating earnings expectations year after year after year.

Does this pose a problem for a sort of factor-oriented investor when the fundamentals of one sector, the real fundamentals, not the stock performance, produce these abnormal periods of profitability growth?

Well, I don't know how abnormal they are. So the essence of all these dimensions of returns is that they're risky. The results are highly uncertain over any period of time.

They can do poorly for long periods of time. They can also go away. If too many people jump on things, it can cause them to go away. So it's possible, for example, that interest in small stocks and interest in value stocks kill the size and the value of premiums that existed in the historical data. That's quite possible. Pricing of securities is no more than

supply and demand. So if the demand goes up and the price goes up with it, then you can see these premiums disappear. It's very difficult to unravel the story in the data because there's so much uncertainty associated, so much volatility associated with prices and returns. But these are always possibilities that these dimensions of risk

are no longer compensated because people don't fear them anymore. They jump into them if they think the returns are better. That's always been a possibility. Ken French and I pointed that out in the initial papers we wrote on the dimensions of risk.

So just to press on this point further, small companies are always going to have certain types of risks. Low liquidity stocks are always going to have certain types of risks that don't exist in high liquidity stocks. But when you think about these factors, these do not strike you as iron laws of how markets work that you will at some point get compensated for taking on these risks into your portfolio.

Well, you're mixing in trading costs there. So there are differential trading costs and different kinds of assets, differential transactions costs. Those are part of what you pay to play the game. And in principle, they detract from the prices of the stocks. But I'm not sure about what your question was, actually.

Basically, the idea that at any given point you will be compensated for the risks of smaller, less liquid stocks, that's not necessarily a permanent characteristic of the market. Well, there was always a dimension of risk, which means...

There's volatility associated with it. Historically, during the periods when over the long term, small stocks did very well, there were always periods when they didn't within those periods, within the periods of good returns. That's always true. There have always been periods when stocks did worse than bills. There was a long period of that in the 30s, 40s, all the way up to the 50s.

So these are just dimensions of risk and return, basically. And risk means you can lose. I may also point out, in the direction you're headed, what we believe is, at the end of the day, you need to come up with sensible portfolios and well-diversified, low-cost, and so forth. And when we started the firm, we built it on the idea that you ought to have large and small-cap stocks in your portfolio, not just large-cap. Our first clients were large institutional clients.

And they were only holding stocks of bigger companies because they were trying to hire managers to outguess the market. And you can't build a business, much of a business, trying to pick the winners of the small caps because you can't buy enough of them to create a profitable business.

or it's hard to anyway. So the thrust wasn't so much that we guarantee you higher returns. The thrust is you ought to have a well-diversified portfolio and, in our view, it ought to include a significant chunk of small cap. Hmm.

David, you highlighted earlier the importance of data in modern finance, and that definitely comes through in the documentary, the idea that a lot of these studies and theories went hand in hand with the development of, to Jean's point, you know, computers and the ability to actually track more information and crunch it more efficiently. No.

Nowadays, it kind of feels like we're drowning in data. Almost everything is tracked. There's artificial intelligence, generative AI, all this stuff we could use.

Do you see any new interesting ways of using that data or any interesting ways that data is being translated into either new financial theories or investment strategies? Well, you know, kind of jeans you as the market reflects all available information. That's kind of the implication of efficient markets.

And with these AI programs and so forth, I mean, they have vast amounts of data, but no AI algorithm can reflect all available information. So even though they have lots of information, there's still lots that get reflected seemingly in stock and bond prices.

Looking at it from the academic side, what's happened with the coming of so many big databases that people do lots of research is that research and finance has expanded. There used to be just a few of us doing it in the 60s and 70s. Now we have big finance departments in almost every school, all with people who want to do work, most of it, or work on, lots of it, work on markets. So

where there was basically one journal in the 60s that was all open to this kind of stuff. Now you have four or five of them that are all pretty good and all coming up with new stuff, publishing three or four times a year. So there's been an explosion of research that uses all these new data. And that's been to the plus, I think. I really...

When I talk to my young people, I say, boy, in the old days, it was easy when I was coming up. It was like shooting a fish in a barrel. Nobody was doing anything. So everything you did was new. Now it's much more difficult. There's much more precedent about what's been done and what hasn't been done. You started this conversation by talking about your initial problems, which is that when you're identifying historical patterns, it's easy to find something that works better.

in sample and then it doesn't work out of sample. So I could probably come up with some story that tickers that start with the letter P tend to outperform on Tuesdays. And I could find some chart that shows that absolutely for years and years and years is the case. And then, of course, you know, that's totally made up. And so then it doesn't work. And we've seen this explosion of other factors. You have your three factors, but people are coming up with all kinds of factors and you've added factors, etc.,

When do you say like a factor loses legitimacy? It's like, you know what? This was p-hacked. This turned out to be, it turned out that actually it doesn't really work out of sample after a long enough time. And in my mind, I am going back to say value versus growth or small versus big here.

Is there a period at which if growth keeps outperforming value, you say, actually, that's not a real sustainable factor. It's not mean reverting. And this was a the appearance of these excess returns was a function of limited sample size. OK, so Ken French and I have always been very sensitive to exactly this problem. So every time we did a paper that seemed to have a new result discovered in it, we would

extend the data backward in time and see if the same pattern were observed. And then we'd go international and see if the same pattern was observed in another market. So we were very sensitive to precisely the issue you're raising. It's a very important issue. Not many people do that. They don't look at out-of-sample data to see if it worked there. Now, we only went forward when we found things that seemed to work backwards.

Looking backward in time, which is one way of going out of sample, and looking across markets, which is another way of going out of sample. But still, it's possible that the discovery of the effect causes people to

move to it to do stuff that basically makes it go away. And it takes a long time before you can tell that that's true because of the basic nature of the uncertainty of the whole process. The amount of uncertainty there is about the evolution of prices. There's really no way to get around that. So we won't know how I live in my lifetime anyway, but I'm only six years old.

We won't know in my lifetime whether the value premium or the size premium have actually gone away because you still don't have enough data to come to that conclusion. Well, also let me add one additional thing. When Gene and Ken did all this great research, they have the data there that jumps out at you. One of the questions was always, why would it be there?

And you can go through the algebra on why low-priced stocks have higher average returns than high-priced stocks. It seems sensible that low-priced stocks might have higher expected returns, maybe because they're riskier. Hmm.

Jean, towards the end of the documentary, just on the notion of going forward, you kind of talk about what's next in modern finance. And you make the point that we are not making these sort of quantum academic jumps as we did in the 1970s, and that someone needs to come up with a new innovation, a new burst forward, but you don't really know who that might be.

Do you have any sense of where people should be looking for the next big thing in modern finance or modern financial theory? That's, again, an excellent question. But I think the answer is all that stuff is basically unpredictable. You don't know where the new direction is until somebody discovers it. And where people think it might be...

almost always turns out to be the wrong place. Not that you shouldn't do it, but simply it's a very difficult task. So the question is excellent. The answer is unavoidably vague.

Fair enough. There's nothing, if a young student came to you and said, hey, I'm looking, you know, at 86, you might not want to dive into something new, but there's nothing. He's like, I'm sort of curious about that. You should try to pursue a, write a paper. There's nothing that comes to mind that sort of you would suggest a young researcher make a stab at? Well, the question we started with was,

What's the next big thing that changes the world? That's a much more difficult thing. What's the next research wrinkle that we can do that extends the world a little bit? Fair enough. That's mostly what goes on in research. The small little steps forward. And sometimes little steps backwards. Stuff doesn't work out. Since we have Gene Fama here, I cannot resist asking a sort of thought experiment question. But

What would be an EMH interpretation of the cryptocurrency market? Can you look at it through an EMH lens? I was wondering when you were going to come to that. But cryptocurrency gives me all kinds of problems because like Bitcoin is the only one I'm roughly familiar with. But

Nobody can explain why it survives because basically it's the old monetary theory says that something that has a highly variable real value can't be used as the medium of exchange because people won't want to deal with it. So, for example, a business that doesn't want to do business in terms of Bitcoin because the variation in price of Bitcoin itself can knock the company down.

out of business. Then the question becomes, who does want to use Bitcoin? Historical monetary theory, as I learned it, is not capable of answering that question. It would have predicted, and I'm still predicting, it'll bust it. It'll bust at some point. People will say, no, that's it. They'll stop piling into it, and then that market will just disappear. We'll see. If it survives,

We need a whole theory to explain how and why. That sounds suspiciously like you're saying it's in a bubble. I'm hoping it's in a bubble is what I'm saying. Well, I think it may be that he's also saying that if crypto is going to survive, it'll be because it has some value right now. And it could maybe someday...

You can do transactions cheaper than you can with MasterCard or something. That's a good point, Dave, because there's a difference between the medium of exchange and the method of exchange. So the method of exchange is how do you carry out the transactions? The medium of exchange is what do you put into it in order to carry out the transaction. So the question is about transactions.

the methods evolve all the time. We have a central bank method now that we use pretty much for everything in the US, but the blockchain is an alternative mechanism. What you put into it can be anything. It can be Bitcoin or it can be dollars. It doesn't really matter. Those are two different things. People worry that a system where

A central bank manages the transactions, which is the system we have. It's too open to manipulation by the government, and the blockchain avoids that. But then it turns out that the blockchain is not scalable. Its complication goes up basically exponentially as it handles more transactions. So that's not the answer to the method of exchange problem. And that's something people are struggling with.

All right, David and Jean, we're going to have to leave it there. But thank you so much for coming on Odd Lots. It was a real pleasure to speak with you both. And congrats on the movie. Okay, great. Thanks. It was really a lot of fun. Thank you.

Joe, that was really fun. Fama, especially, was someone I always wanted to speak to. I do have to say, you know, I mentioned earlier the way you feel about the term premium is probably the way I feel about the efficient markets hypothesis. And I recognize it's a theory that exists, but I guess I'm not sure how useful it is to basically say that the average investor can match the average return of the market. Like,

Does that lead anywhere? Yeah, yeah, it absolutely leads somewhere. It means that you almost certainly shouldn't try and that if you try, you will probably end up making mistakes. I mean, I think that's like- It's such a depressing view of human capability. I think this is one of the most useful maxims in finance because even if it's not formally true, right? Even if there are slight variabilities, etc.,

I do think it seems very clear that the vast majority of people, including many professionals, as the statistics have borne out, like can't actually generate superior returns. And so if the only thing that we like, if the only use we get out of the efficient markets hypothesis is like do something else with your life than trying to beat the market, that sounds like wonderful advice that I think most people should heed.

Should you say that on the All Thoughts podcast? Well, that's the funny thing. It's like, why are we all here? I mean, this is like the existential question of everything because like my interpretation of Gene's answers is,

is basically a recurring series of, yes, it's priced in. Yes, it's priced in. Yes, it's priced in. Yes, it's priced in. And so I do have this existential question about we support this news organization that supports an industry. And I talk about this stuff all the time. And then it's like, why?

I think I'm closer to David's position on this where true passive doesn't necessarily exist. There's sort of a middle ground where you can have systematic approaches, but you're still making active decisions in the way you either execute trades or in the cost of your investment and things like that. I think that's a reasonable middle ground. I am not sure I am an EMH fundamentalist.

camp just yet. But maybe you can convince me. Yeah. You know, here's what here's my this is not the weak form. There's a definition of the weak form efficient market hypothesis. What I would say is this. And I've actually given this advice to other journalists. And I think this is something that I could try to convince people of.

which is that if you look at the market and you think that you identify some security or anything that seems to you obviously mispriced,

you should start with the presumption you're missing something. It's very unlikely that you've just seen something in the market that obviously you can profit from. It occasionally happens and people have a thesis and something looks clear and they make a lot of money. But I think most of the time, if you see a line, you're like, it shouldn't be there. You should start with the assumption that the...

billions of dollars flowing through the market didn't all miss something that you see as obvious. Yeah, but there are people who outperform the market. And it's a little bit like...

Again, tautological, I guess, just to hand wave it away and be like, oh, they got lucky. Yeah, right. But can you identify the people who... This is the problem, right? Yeah, no, this is it. And this is why all these things break your brain. Maybe I can get lucky in choosing the lucky investment managers. How about that? I mean, that's right. That's like manager selection suffers from the exact same problem as stock selection, the out-of-sample, in-sample bias. This is why...

But one thing I am curious about, like, when we are long dead and maybe the Odd Lots franchise is so valuable that there's, like, you know, there's, like, new hosts of the podcast, right? Because they want to continue it. Maybe they'll be alive long enough to say, like, oh, turns out there's no small cap premium after all. Yeah.

Gene opened up the possibility that, yeah, all of finance and economics suffers from the tragedy of small sample sizes. It's like this known phenomenon, like the world is just getting started. Maybe one day it'll be like, actually, it turned out that wasn't really a thing, but that'll probably be after all of our lifetimes. In the long run, we're all dead.

In the long run, all factors suffer from sample bias. Since you mentioned the small cap stocks, there was this little visual in the documentary where they showed a headline from I think it was the early 1990s.

And the headline was mutual funds offbeat theory by stock in smaller firms. And I thought that was so funny and kind of quaint because they're basically talking about growth stocks. And, you know, nowadays, growth stocks are sort of an accepted idea. But back then it was.

offbeat, an offbeat theory. And it kind of shows just how much financial theory is embedded in the market now that we take for granted. But, you know, a decade ago or two decades ago or five decades ago, people didn't know it. Well, and just on this one point,

It is interesting, too, that now if someone says growth stocks, you think really big companies. And there was a time when if someone said growth stocks, you'd think about really small companies and that big companies were supposed to grow slowly. And so this is kind of what I wonder about. Like, these are fundamental realities of business changing. And could those fundamental realities of business changing change fundamental aspects of the stock market? Yeah.

Because we now have this era where you have gigantic companies still putting up growth numbers that in any time would be incredible.

All right. Shall we leave it there? Let's leave it there. This has been another episode of the All Thoughts Podcast. I'm Tracy Allaway. You can follow me at Tracy Allaway. And I'm Joe Weisenthal. You can follow me at The Stalwart. Check out the new Errol Morris documentary, Tune Out the Noise, that talks about all of these things and the beginnings of modern finance. Follow our producers, Carmen Rodriguez at Carmen Armit, Dashiell Bennett at Dashbot, and Cale Brooks at Cale Brooks.

For more OddLots content, go to Bloomberg.com slash OddLots, where we have a newsletter, our episodes, and a blog. And you can chat about all of these topics, including endless circular discussions about market efficiency in our Discord, discord.gg slash OddLots.

And if you enjoy OddLots, if you like it when we, in fact, have an endless discussion about the efficient markets hypothesis, then please leave us a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes absolutely ad-free. All you need to do is find the Bloomberg channel on Apple Podcasts and follow the instructions there. Thanks for listening.

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