Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 2: Hello and welcome to another episode of the All Thoughts podcast.
Speaker 2: I'm Tracy Alloway.
Speaker 3: And I'm Joe. Why isn't thal.
Speaker 2: Joe, what's your favorite financial movie? I don't think I've
Speaker 2: ever asked you that question?
Speaker 3: Really, I mean Trading Places.
Speaker 2: Oh, that's funny. That's mine too.
Speaker 3: Yeah, and not only.
Speaker 2: Because it's funny, but because it led to a real
Speaker 2: life development which I don't think a lot of people know.
Speaker 2: But the CFTC set up something called the Eddie Murphy Rule.
Speaker 2: I didn't know because of trading places.
Speaker 3: I have no idea where you're going with, and I think.
Speaker 2: There has been an enforcement action. Well, what I was
Speaker 2: going to say is I think there is actually a
Speaker 2: lack of really good financial movies.
Speaker 3: Okay, here you go.
Speaker 2: Trading Places aside, Yes, I would agree. Yeah, I know
Speaker 2: we have the Big Shore and Margin Call was a
Speaker 2: very realistic description of what it's like to work at
Speaker 2: a bank. But I think we need more in our lives,
Speaker 2: and I think we also need financial movies that sort
Speaker 2: of delve into some of the theories of financial markets.
Speaker 2: And I get why we don't. Those are really difficult
Speaker 2: to illustrate in a visual way, but I still want them.
Speaker 3: Me too, all right, keep going crazy?
Speaker 2: Okay, Well, the good news is I just watched one
Speaker 2: that fits into that category. So there's a new documentary
Speaker 2: out called Tune Out the Noise, and it's all about
Speaker 2: the birth of modern finance and it features an absolutely
Speaker 2: all star cast of financial luminaries. So you know, there
Speaker 2: are people like Martin Miller, Myron Scholes, Ken, French, Markowitz,
Speaker 2: like the list goes on and on and on, and
Speaker 2: we're going to talk to two of them today.
Speaker 3: I'm really excited because I'm finally going to have as
Speaker 3: to ask is it all priced in? Because this is
Speaker 3: my core belief about markets, that is, like, no, it's
Speaker 3: all priced in, and yet there appears to be a
Speaker 3: financial industry that must on some level be premised on
Speaker 3: the idea that it's not priced in. But I always
Speaker 3: assume that it's all priced in, and so maybe we'll
Speaker 3: finally get an answer to this question.
Speaker 2: I suspect the way you feel about the term premium
Speaker 2: is the way I feel about the efficient markets hypothesis.
Speaker 2: But let's get into it. We are speaking with David Booth,
Speaker 2: the founder and chairman of Dimensional fund advisors and professor
Speaker 2: Eugene Fauma, who is of course a Nobel laureate. He
Speaker 2: is also a director at Dimensional has had a long
Speaker 2: running intellectual partnership with the firm. He's also sometimes called
Speaker 2: the father of modern finance. I could keep going on
Speaker 2: with the honorifics here, but you get the idea I
Speaker 2: think so, David and Gene, welcome to the show.
Speaker 4: Thank you well, thanks for having us. I'm looking forward
Speaker 4: to it.
Speaker 2: I guess I'll start with the obvious question, but why
Speaker 2: a documentary movie about modern finance? It is, as I
Speaker 2: mentioned earlier, not exactly an easy story to tell visually.
Speaker 4: Well, it didn't start out to be a documentary. What
Speaker 4: happened was we started working with Errol Morris. You know
Speaker 4: he won the Academy Award for his film Fog of
Speaker 4: Warren Unknown documentarian, and now we're talking to him about
Speaker 4: how we could use some of his expertise for our firm.
Speaker 4: He got really into it. He had no not much
Speaker 4: background in finance and just got so fired up. He
Speaker 4: wanted to make it his film rather than our film,
Speaker 4: which I found to be very exciting.
Speaker 3: That's cool. We've done an episode with Dimensional's co CEO,
Speaker 3: George O'Reilly, why don't you talk to us a little
Speaker 3: bit about the partnership of the two of you for
Speaker 3: people who are not familiar, for people who are going
Speaker 3: to be watching the film for the first time. The
Speaker 3: two of you have been working together for literally decades
Speaker 3: and really two of the biggest names truly in the
Speaker 3: history of finance. What is the sort of short version
Speaker 3: of the sort of intellectual partnership and how this firm
Speaker 3: Dimensional came about.
Speaker 5: Well, David was my research assistant fifty five years ago.
Speaker 4: David, Yeah.
Speaker 5: Anyway, it actually worked with me for several years at
Speaker 5: the University of Chicago, and finally he came to me
Speaker 5: and said, I see what you do, and I don't
Speaker 5: want to do it. So he said he wanted to
Speaker 5: go off and work in the financial industries. So I
Speaker 5: called mac McCown and got David a job that way
Speaker 5: with the Wells figu I us. It wasn't the time, David.
Speaker 4: Right, right, nineteen seventy one.
Speaker 6: Then eventually he went off on his own, found a
Speaker 6: Dimensional and came back to me and asked me if
Speaker 6: I wanted to be somehow involved.
Speaker 5: We've been going in it ever since.
Speaker 2: Oh yeah, this was in the movie. So I think
Speaker 2: Wells Fargo basically just decided to share some of its
Speaker 2: data and analysis with Vanguard, like at the very beginning
Speaker 2: of Jack Bogel's career. And everyone was sort of scratching
Speaker 2: their heads about why that happened. But do we have
Speaker 2: any sense of why that happened. Was there just a
Speaker 2: spirit of research or academic camaraderie that made private organizations
Speaker 2: share things with each other?
Speaker 4: Well, one of the things I've always admired about Gene
Speaker 4: is his research, which we use extensively. He's always insisted
Speaker 4: that his research be in the public domain. We're not
Speaker 4: in the business of creating black box that nobody understands.
Speaker 4: So it's so critically important to have an open air
Speaker 4: philosophy about sharing research. And so Wells got off to
Speaker 4: a slow start in some ways, but it was a
Speaker 4: fund little question. You can even track the performance of
Speaker 4: an index, and so Wells had done a lot of
Speaker 4: simulations and stuff, and when the group I was working
Speaker 4: on the walls got shut down, Mac just volunteered to
Speaker 4: Bogel to share all of his NATA with him.
Speaker 3: Gine, I'm curious, from your perspective, how did this interest
Speaker 3: you as a intellectual field of study, and we'll get
Speaker 3: into some of the specific and a sort of groundbreaking
Speaker 3: contributions to what many people now consider absolute truths to
Speaker 3: how the market worked. But this idea some of your ideas,
Speaker 3: like why what attracted you to the study of markets
Speaker 3: and some of your early research, well.
Speaker 5: As I stand on it. In college, actually I worked
Speaker 5: for a professor at TUFFS that had a stock market
Speaker 5: forecasting service, and my job was to come up with
Speaker 5: new ways to beat the market.
Speaker 3: How'd that go?
Speaker 5: It didn't go very well, but in the following sense,
Speaker 5: he was very good statistician, so we always kept a
Speaker 5: hold out sample and my ideas always worked in sample,
Speaker 5: but they never worked out of sample. So that was
Speaker 5: my first lesson on what do you can expect by
Speaker 5: trying to beat the market. And after that I went
Speaker 5: off to Sego, took my data with me from Tefts,
Speaker 5: and eventually wrote.
Speaker 7: My thesis using that data, which was kind of the
Speaker 7: the first that maybe one of the bigger trumpeting of
Speaker 7: fishing markets the term went.
Speaker 6: It wasn't even wasn't even called that at the time,
Speaker 6: but eventually that term came around as well.
Speaker 4: One of the things is interesting about that observed he
Speaker 4: did a study based on data collected by hand, and
Speaker 4: that was kind of the state of the world. When
Speaker 4: I went to Chicago to do a research project, frequently
Speaker 4: had to hand collect the data. You know, these new
Speaker 4: kids today wouldn't be aghast have if they knew how
Speaker 4: we did things in the old days.
Speaker 2: Well, I remember, in the old days of Bloomberg, we
Speaker 2: often input it a lot of financially, if you're working
Speaker 2: in the global data department, and you certainly input it
Speaker 2: a lot of things by hand as well. This leads
Speaker 2: to a question I want to ask you. So a
Speaker 2: big chunk of the documentary is about all these different
Speaker 2: people who spent time at the University of Chicago. What
Speaker 2: was in the water at the university that it attracted
Speaker 2: all these names that went on to do big things
Speaker 2: in finance.
Speaker 5: Well, Marton Miller was an important person. He was deeply
Speaker 5: interested in this stuff. And Harry Arms was another important
Speaker 5: person who had written on something resembling what would be
Speaker 5: now called the fishing markets way back in the fifties.
Speaker 5: So he was very much interested in it. And they
Speaker 5: were kind of the two shining lights in this area.
Speaker 5: And plus then there were a lot of PhD students,
Speaker 5: including me, these is topics. So having faculty interested in
Speaker 5: the topic was a good way of having researched them
Speaker 5: by students in that type, because that was the way
Speaker 5: to graduate. And at the time I had two kids
Speaker 5: with another one on the way, so it was very
Speaker 5: very keen on getting out quickly.
Speaker 4: Well, I would also add, you know, Jim Laurie, I
Speaker 4: mean gentleman Larry Fisher. They persuaded Barrel Lynch to fund
Speaker 4: a study to collect a survivorship bias free database which
Speaker 4: enabled all these new young hotshots to do their research.
Speaker 4: Until that point to the data had never been collected
Speaker 4: correctly and so he couldn't really do the research.
Speaker 5: So when Larry started out to Larry's Fish started out
Speaker 5: to collect that data and put it together. A computer
Speaker 5: didn't exist it could handle it, but he said, well,
Speaker 5: it's going to come along by the time me finish
Speaker 5: this to be computer you can handle it. And he
Speaker 5: took out to be.
Speaker 3: Raised, well, actually, this is exactly what I wanted to ask,
Speaker 3: and I think it sort of speaks to like a
Speaker 3: big theoretical question. Let's say, part of good investing is
Speaker 3: having good data, Like if you have to collect the
Speaker 3: data by hand, You're already going to probably knock out
Speaker 3: ninety nine point nine percent of the people who have interest,
Speaker 3: because I wouldn't do it because my risk get really tired,
Speaker 3: really fast, and my handwriting is garbage, so I wouldn't
Speaker 3: even be able to read what I had written in
Speaker 3: the graph paper, et cetera. A lot of things that
Speaker 3: we take for granted about investing today, including measuring the
Speaker 3: performance of an index, are things that literally take a
Speaker 3: few keystrokes or less on a Bloomberg terminal today. And
Speaker 3: I'm curious, like, when you think about, like generating superior
Speaker 3: returns over time, how much of an edge was that
Speaker 3: to just be willing to do the hard work of
Speaker 3: collecting data.
Speaker 4: Look, all these tests and market efficiency, which started in
Speaker 4: the sixties, you know, and have keep showing the same
Speaker 4: result every sense, even though with increasing levels of sophistication
Speaker 4: of researchers and people having access to more and more
Speaker 4: more data, better data, faster data, all of that, this
Speaker 4: still shows the same outcome of it doesn't look like
Speaker 4: find how guess the market is a winning game.
Speaker 2: So, since we're on the subject of the efficient markets hypothesis,
Speaker 2: one of your former students who also went on to
Speaker 2: a great fame. Cliff asnas He published his own paper
Speaker 2: called the less Efficient Markets Hypothesis, and it argues that
Speaker 2: markets are less efficient than they once were, in part
Speaker 2: because social media has basically turned us all into trend
Speaker 2: following idiots. I guess, and this is something that I've
Speaker 2: occasionally wondered. If the efficient markets hypothesis is reliant on
Speaker 2: people making the right decisions with the information that they
Speaker 2: have or the data they have, what happens if we
Speaker 2: all get collectively more stupid? And I guess A different
Speaker 2: way of asking this is, has your view of the
Speaker 2: efficient markets hypothesis changed at all over time?
Speaker 5: No, it hasn't really changed. It's adaptive in the sense
Speaker 5: that I never said that the market was efficient for everybody.
Speaker 5: There are for example, there's lots of evidence, for example,
Speaker 5: that company insiders have information that isn't already in prices,
Speaker 5: so as far as they're concerned, the stock of their
Speaker 5: company is not priced efficiently. That's one instance of it.
Speaker 5: But as far as professional managers are concerned, there is
Speaker 5: evidence that if you give them back all their fees
Speaker 5: and expenses, there are some who do have enough information
Speaker 5: to beat the market.
Speaker 6: But if you don't take out the fees and expensive
Speaker 6: then the active managers look terrible relative to.
Speaker 5: The passive managers. So that's the kind of data and
Speaker 5: results that makes market efficiency look pretty good.
Speaker 4: But it's not.
Speaker 5: It's just a hypothesis. It's not a literal truth. It's
Speaker 5: just an approximation to the world. But it worked really
Speaker 5: well for almost everybody.
Speaker 8: M hm.
Speaker 3: So this gets to like a question that I've asked
Speaker 3: before and I'm now thrilled to get to ask it
Speaker 3: to you, which is why does the financial industry exist?
Speaker 3: If markets are efficient, because there are a lot of
Speaker 3: people that collect very big paychecks from some notion that
Speaker 3: they can deliver better returns than someone else to their clients.
Speaker 3: If markets are efficient, at least to most people in
Speaker 3: the industry, why do we have this industry?
Speaker 5: Because there are people who think they can pick the
Speaker 5: managers that have special information. That's what keeps it going.
Speaker 5: That's what keeps the active manages going. Individuals who make
Speaker 5: who don't think the passive investing is for them, and
Speaker 5: they invest they go with the active people, so that
Speaker 5: markets are always about competition among different kinds of players.
Speaker 5: And then we see who comes out on.
Speaker 2: Top, Geene, how serious are you when you say stuff
Speaker 2: like there's no such thing as a bubble, or that
Speaker 2: bubbles are only identifiable after they burst, so it's pointless
Speaker 2: to talk about them. Very serious, explain it more, because
Speaker 2: Joe and I have lots of episodes where we talk
Speaker 2: about either past bubbles or overvaluations.
Speaker 5: Yeah, so with twenty twenty, I didn't say, as you know,
Speaker 5: it's explain why prices won't happen, why why they way
Speaker 5: they went down. But in my view, what a bubble
Speaker 5: means is price has gone up and you can predict
Speaker 5: when it's going to go down, when when that hope
Speaker 5: phenomen it's going to that hope price movement is going
Speaker 5: to go away. And that's what's just proving really difficult
Speaker 5: to do. So lots of people use the word bubble
Speaker 5: very loosely. I can't sell my subscription to the economists
Speaker 5: because you're using the word.
Speaker 3: Journalists are terrible about overusing bubble. I will cop to
Speaker 3: that on the behalf of the entire profession, right.
Speaker 5: So I need to know what the definition is before
Speaker 5: I can respond to it, and in that case that's
Speaker 5: much more difficult. Most people are willing to do that.
Speaker 5: There are econs that are willing to do it, and
Speaker 5: I can deal with that. There has to be some predictability,
Speaker 5: but when it's going to end, and that's what proven
Speaker 5: really difficult to establish.
Speaker 3: Right, it seems fairly clear that you could sort of
Speaker 3: sense like we're in some sort of mania, and even
Speaker 3: knowing that fact and everyone agreeing on that fact. In fact,
Speaker 3: to try to establish that fact is often a good
Speaker 3: recipe for losing all your money if you're short at
Speaker 3: or losing all your clients if you're avoiding it. So
Speaker 3: I certainly take that point. Let me press further though,
Speaker 3: So a lot of your research and this idea of
Speaker 3: market efficiency, but you've also worked on factors that seem
Speaker 3: over time historically to outperform. And so the idea of
Speaker 3: small companies outperforming big companies or value companies outperforming over
Speaker 3: time dimensional has funds that aren't just the pure market portfolio.
Speaker 3: Reconcile the existence of that with the idea of efficient marketing.
Speaker 5: Okay, that's that's a good question. So everybody has this confusion.
Speaker 5: The confusion is mixing together market.
Speaker 6: Efficiency and the dimensions of risk and portfolio selection.
Speaker 5: So going back all the way to Macrowitz. We've a
Speaker 5: long known for example, the people don't like variants, they
Speaker 5: don't like uncertainty about future liters, and they're willing to
Speaker 5: pay something to avoid it. So they gave rise to
Speaker 5: the chaplain and their capital so called capital asset pricing
Speaker 5: model in which sensitivity to the market was the measure
Speaker 5: of it was the measure of risk. So basically into
Speaker 5: confusion of prices being reflect value in the study about
Speaker 5: what are the dimensions of risk in the market. So
Speaker 5: that's a confusion that almost everybody seems to have. So
Speaker 5: Marcus doesn't say there aren't risk premeans in the market,
Speaker 5: does not say that at all.
Speaker 4: One way to think about it is, you know, define
Speaker 4: the market to be all the stocks and bonds that
Speaker 4: are out there. Most of us believes talks are with
Speaker 4: a long haul level higher return than bonds. A few
Speaker 4: people invest all their money in stockses and doesn't mean
Speaker 4: stocks are inefficient and efficiently priced, and just those are
Speaker 4: the market prices. And you look at different combinations of
Speaker 4: the two and they provide different distributions of outcomes, and
Speaker 4: just find that distribution that works best for you.
Speaker 2: So a big chunk of The documentary is about the
Speaker 2: birth of passive investing and its connection with the efficient
Speaker 2: markets hypothesis. What's been the impact of the growth of
Speaker 2: passive investing on the market it because we often hear that,
Speaker 2: you know, markets are reflexive, moves can end up impacting
Speaker 2: the market itself. And David, I think you yourself have
Speaker 2: argued that one of passive investing's biggest flaws is still
Speaker 2: very much alive, the index effect, where stock prices go
Speaker 2: up a lot when a company is added to an index,
Speaker 2: even though everyone in the theory should know that this
Speaker 2: is going to happen and so it should already be
Speaker 2: priced in. How has passive actually changed the market?
Speaker 4: Well, that's an interesting question. First off, the kind of
Speaker 4: the impact of an index adding a new name, you know,
Speaker 4: causing temporary prices to go up. That's a temporary effect.
Speaker 4: It doesn't really impact the long term investor very much.
Speaker 4: And one question that comes up a lot is, you know,
Speaker 4: if everybody indexed, you know, then there would be no
Speaker 4: price discovery. Wouldn't markets become inefficient?
Speaker 5: You know?
Speaker 4: That's kind of And my answer to that is, well,
Speaker 4: let's take a look at it. The behavior of the
Speaker 4: market over the last twenty years. There's been an incredible
Speaker 4: movement to indexing over that time period, and yet there's
Speaker 4: been an incredible increase in trading volume. You know, I
Speaker 4: don't think of price discovery has been related to trading volume.
Speaker 4: So just because there's a big movement to indexing doesn't
Speaker 4: mean trading volume multi climb. What's happened, unfortunately, is it
Speaker 4: turns out, like a lot of things that can be
Speaker 4: used for good, they can also be used for bad.
Speaker 4: And you know, index funds are the ideal market timing vehicle.
Speaker 4: I'll buy this healthcare index fund and sell my technology
Speaker 4: for or whatever it is. And I think that really
Speaker 4: comes to what happened to the marketplace is it's kind
Speaker 4: of to an individual instead of individual stock selection, it's
Speaker 4: kind of like a big gambling casino where you have
Speaker 4: a lot of different ways you can make your bets.
Speaker 4: So it doesn't look like in terms of the basic
Speaker 4: notion of market efficiency, it doesn't appear to have had
Speaker 4: much impact on that.
Speaker 5: So let me just take different direction. And people worry
Speaker 5: that if everybody goes assive, how will prices get formed?
Speaker 5: And that's a legitimate concern, But then the issue is
Speaker 5: who drops out, who doesn't go active anymore. If it's
Speaker 5: bad active man, just people who have no special information.
Speaker 5: If they drop out, then you need few good active
Speaker 5: people to keep prices inline. So it depends on who
Speaker 5: drops out as to whether has any effect at all
Speaker 5: on market efficiency. And we haven't been able to discern
Speaker 5: anything like that in the behavior of prices, But that
Speaker 5: is the question.
Speaker 2: Since we're on the topic of indexing. You know, the
Speaker 2: market nowadays, as you mentioned, is basically defined by benchmark indexes,
Speaker 2: things like the S and P five hundred or the
Speaker 2: MSCI World Index. And the benchmark index providers will often
Speaker 2: say that they're just holding up a mirror to the
Speaker 2: market as it exists. They're neutral, but it seems kind
Speaker 2: of obvious to me that their decisions do impact the market,
Speaker 2: and some of those decisions can be subjective, you know,
Speaker 2: when it comes to measuring things like liquidity or how
Speaker 2: developed a particular bond market is or whatever. Are we
Speaker 2: just outsourcing investment decisions to index providers.
Speaker 5: To choose the one you want. So my own tastes
Speaker 5: run in the direction of a total market index being
Speaker 5: a good choice for almost everybody. So I don't go from.
Speaker 6: The subset things that thirty thirty down Jones that was
Speaker 6: always kind of dumb.
Speaker 5: But or even five hundred, that's only five hundred. There's
Speaker 5: a loves stucks out there.
Speaker 4: Then than that, let me just recall against the term passive.
Speaker 4: You know, in my view, there's no such thing as
Speaker 4: passive management. And you're you're touching on something right there.
Speaker 4: You know the different index providers and how they do it,
Speaker 4: and they'll do it differently and so forth. And you
Speaker 4: know Standard and Poors when it wants to add stock
Speaker 4: to its sm P five hundred, you know, the investment
Speaker 4: committee sits around and talks about you know, what do
Speaker 4: you like? You know, it's the S and P five
Speaker 4: hundred is five hundred of the largest companies, but it's
Speaker 4: not the five hundred largest companies. And there's quite a
Speaker 4: bit of subjective judgment goes into deciding what stock goes
Speaker 4: into the index. Which if you're going to an index
Speaker 4: fund because you don't like stock selection, that's not the
Speaker 4: kind of activity you want to you want to see.
Speaker 3: I want to go back to this idea of even
Speaker 3: if markets are efficient, there still are risk premia and
Speaker 3: certain asset classes are expected to go up more than
Speaker 3: others due to people's wanting to avoid drawdowns, et cetera.
Speaker 3: You know, like I don't make many active decisions. I'm
Speaker 3: like a good like I follow what I read in
Speaker 3: the news, and I like, have some stocks and you
Speaker 3: know it, probably have some treasuries and some fund or
Speaker 3: something like that, and I don't like pay attention to
Speaker 3: it much. Looking back though, at historical trends in portfolio construction,
Speaker 3: I sometimes wonder why should anyone own bonds? Because you say,
Speaker 3: hardly anyone just own stocks, and that seems to be
Speaker 3: objectively true. But I wonder if, like, is there reason
Speaker 3: to question some of this dogma of like why, like,
Speaker 3: if I'm not going to retire in thirty years, do
Speaker 3: I care about You know, I'm already diversifying over time
Speaker 3: because I make an allocation to my retirement funds with
Speaker 3: every paycheck, so I'm already getting time diversification. Are there
Speaker 3: fundamental questions in portfolio construction that you think need to
Speaker 3: be rethought if over the next thirty years before I
Speaker 3: can retire twenty five years, maybe, like, if almost everyone
Speaker 3: thinks it's certain that stocks will outperform bonds, why am
Speaker 3: I holding bonds.
Speaker 5: That sense that if almost every but he thinks that's true,
Speaker 5: But it's not true. Stucks don't get less risk. In
Speaker 5: the long term, risk accumulates, So.
Speaker 3: I don't understand that. I don't understand how.
Speaker 5: When you retire, when you retire a period when stocks
Speaker 5: have been particularly poorly and you will get hurt, that's
Speaker 5: always a possibility, doesn't go away with the time.
Speaker 6: So the presumption is is what's incorrect? The risk is
Speaker 6: always there, you don't get rid of it.
Speaker 2: What do you think about the term smart beta? And
Speaker 2: is dimensional doing smart beta?
Speaker 5: Yeah, smart is a marketing term. Show me a dumb beta.
Speaker 2: I'm sure I could find some examples, but they certainly
Speaker 2: wouldn't have set out to create dumb beata.
Speaker 5: There's a lot of Mike, there's a lot of marketing
Speaker 5: in the financial business. That's one of them. That's one
Speaker 5: of the big ones.
Speaker 3: Well, what does it mean to you? So like when
Speaker 3: you hear that term, like, what is the person trying
Speaker 3: to sell to me?
Speaker 5: Well, that have to give me an example because I
Speaker 5: don't take it seriously. Obviously you can tell me checking here.
Speaker 4: Well, I think it's a Jeans research that he did
Speaker 4: with Ken French. You know, his landmark ninety two paper
Speaker 4: on called cross section of expected returns anyway that you know,
Speaker 4: kind of gave empirical support to the idea that there
Speaker 4: can be many dimensions of returns. So if you focus
Speaker 4: on a certain dimension. Some people came over the term
Speaker 4: smart data. It's not smart, I mean, just it's just,
Speaker 4: you know, a reflection of the research and the dimensions
Speaker 4: of returns.
Speaker 3: You know, something that I'm really interested in when it
Speaker 3: comes to markets particularly, I would say over the last
Speaker 3: fifteen years since the Great Financial Crisis, small caps have
Speaker 3: certainly not provided any sort of superior risk adjusted returns
Speaker 3: to large caps, and you can see that on basically
Speaker 3: any chart. And growth companies year after year, you know,
Speaker 3: by the traditional metrics of what we call growth and value,
Speaker 3: and I know people sometimes try to redefine these to
Speaker 3: allow them to put in VideA in their value fund. Clearly,
Speaker 3: growth has been outperforming for a long time, and part
Speaker 3: of the reason it seems very obvious to me that
Speaker 3: these big tech stocks have done so well is because
Speaker 3: the companies have all done extraordinarily well and beating earnings
Speaker 3: expectations year after year after year. Does this pose a
Speaker 3: problem for a sort of factor oriented investor. When the
Speaker 3: fundamentals of one sector, the real fundamentals, not the stock performance,
Speaker 3: produced these abnormal periods of profitability growth.
Speaker 5: Well, I don't know how I abnormal they are. So
Speaker 5: the instance of all these dimensions of returns is that
Speaker 5: they're risky. There is, the results are highly uncertain over
Speaker 5: any finite period of any period of time, so they
Speaker 5: can do poorly for long periods of time. They can
Speaker 5: also go away. If there's too many people jump on things,
Speaker 5: it can cause them to go away. So it's possible,
Speaker 5: for example, then interest in small stocks and interest in
Speaker 5: value stocks killd thes size and the value premiums that
Speaker 5: existed in the historical data. That's quite possible. Pricing of
Speaker 5: securities is no more than supply and demand, So if
Speaker 5: the demand goes up and the price goes up with it,
Speaker 5: then you can see these premiums disappear. It's very difficult
Speaker 5: to unravel the story in the data because there's.
Speaker 6: So much ensutancy associated, so much volatility associated with prices
Speaker 6: and returns. But these are always possibilities that these dimensions
Speaker 6: of risk are no longer compensated because people don't feel
Speaker 6: them anymore.
Speaker 5: They jump into them if they think the returns out
Speaker 5: are better. That's always been a possibility, Conferntion, and I
Speaker 5: pointed that out in the initial papers we wrote on
Speaker 5: the dimensions of risk.
Speaker 3: So, just to press on this point further, small companies
Speaker 3: are always going to have certain types of risks. Low
Speaker 3: liquidity stocks are always going to have certain types of
Speaker 3: risks that don't exist in high liquidity stocks. But when
Speaker 3: you think about these factors, these do not strike you
Speaker 3: as iron laws of how markets work that you will
Speaker 3: at some point get compensated for taking on these risks
Speaker 3: into your portfolio.
Speaker 5: Well listen. And then the mixing and trading costs there,
Speaker 5: So there are differential trading costs and different kinds of assets,
Speaker 5: different transactions costs. Those are part of what you may
Speaker 5: played play the game. In principle, it tract from the price.
Speaker 6: Of the prices of the stocks. But I'm not sure
Speaker 6: about what your question was actually.
Speaker 3: Basically the idea that at any given point you will
Speaker 3: be compensated for the risks of smaller, less liquid stocks.
Speaker 3: That's not a necessarily a permanent characteristic of the market.
Speaker 5: Well, it was, it was always there was always a
Speaker 5: dimension of risk, which means this volatility associated with it.
Speaker 5: So through the historically, during the periods when on the
Speaker 5: over the long term small stocks did very well, there
Speaker 5: were always periods when they didn't within those periods, within
Speaker 5: the periods of good, good, good return. So that's always true.
Speaker 5: So there always been periods when stocks did worse than
Speaker 5: bills through a long period of that in the thirties,
Speaker 5: forties all the way up to the fifties. So these
Speaker 5: are just dimensions of risk and return basically, and risk
Speaker 5: means you.
Speaker 4: Can mose will point out a kind of the direction
Speaker 4: in your head. It is what we believe is at
Speaker 4: the end of the day, you need to come up
Speaker 4: with sensible portfolios and well diversified, low cost and so forth.
Speaker 4: And when we started the firm, you know, we built
Speaker 4: it on the idea that you ought to have large
Speaker 4: and small cap stocks in your portfolio, not just large cap.
Speaker 4: Our first clients were large institutional clients and they were
Speaker 4: only holding the stocks of bigger companies because they were
Speaker 4: trying to the hired managers to how guests the market.
Speaker 4: And you can't build a business, much of a business
Speaker 4: trying to pick the winners of the small caps because
Speaker 4: you can't buy enough of them to create a profitable
Speaker 4: business or it's hard to anyway. So the thrust wasn't
Speaker 4: so much that we guarantee your higher returns. The thrust
Speaker 4: is you ought to have a well diversified portfolio, and
Speaker 4: our view how to include a significant chunk of small cap.
Speaker 2: David you highlighted earlier the importance of data in modern
Speaker 2: final and that definitely comes through in the documentary. The
Speaker 2: idea that a lot of these studies and theories went
Speaker 2: hand in hand with the development of to Gene's point,
Speaker 2: you know, computers and the ability to actually track more
Speaker 2: information and crunch it more efficiently. Nowadays, it kind of
Speaker 2: feels like we're drowning in data. Almost everything is tracked.
Speaker 2: There's artificial intelligence generative AI, all this stuff we could use.
Speaker 2: Do you see any new interesting ways of using that
Speaker 2: data or any interesting ways that data is being translated
Speaker 2: into either new financial theories or investment strategies.
Speaker 4: Well, you know, Jeans you is the market reflects all
Speaker 4: available information. That's kind of the implication of efficient markets,
Speaker 4: and it was these AI programs so forth. I mean,
Speaker 4: they have vast amounts of data, but no AI algorithm
Speaker 4: can reflect all available information. So even though they have
Speaker 4: lots of information, there's still lots to get reflected, seemingly
Speaker 4: in stocking bond prices.
Speaker 5: Looking at it from the academic side, what's happened with
Speaker 5: the coming up so many big databases that people do
Speaker 5: lots of research, is that research and finances expanded. There
Speaker 5: used to be just a few of us still doing
Speaker 5: it in the sixties and seventies. Now we have big
Speaker 5: finance departments and almost every school all with people who
Speaker 5: want to do work. Most of it are work on
Speaker 5: lots of it work on market. So where there was
Speaker 5: well basically one journal in this in the sixties, there
Speaker 5: was all open to this kind of stuff. Now you
Speaker 5: have four or five of them that are all all
Speaker 5: pretty good. No coming up with no stuff, publishing three
Speaker 5: or four times a year. So there's been an explosion
Speaker 5: of research and uses all these new data, and that's
Speaker 5: been to the plus. I think, I really when I
Speaker 5: and my young people, I say, boy, in the old days,
Speaker 5: it was easy. When I was coming up, it was
Speaker 5: like shooting fishing in barrow. Nobody was doing anything, so
Speaker 5: everything he did was new. Now it's much more difficult,
Speaker 5: that much more precedent about what's been done and what
Speaker 5: hasn't been done.
Speaker 3: You started this conversation by talking about your initial problems,
Speaker 3: which is that when you're identifying historical patterns, it's easy
Speaker 3: to find something that works in the sample, and then
Speaker 3: it doesn't work out of sample. So I could probably
Speaker 3: come up with some story that tickers that start with
Speaker 3: the letter P tend to outperform on Tuesdays, and I
Speaker 3: could find some chart that shows that absolutely for years
Speaker 3: and years and years is the case. And then of
Speaker 3: course you know that's totally made up, and so then
Speaker 3: it doesn't work. And we've seen this explosion of other factors.
Speaker 3: You have your three factors, but people are coming up
Speaker 3: with all kinds of factors, and you've added factors, et cetera.
Speaker 3: When do you say, like a factor loses legitimacy. It's like,
Speaker 3: you know what, this was p hacked. This turned out
Speaker 3: to be. It turned out that actually it doesn't really
Speaker 3: work out of sample after a long enough time. And
Speaker 3: in my mind, I am going back to say value
Speaker 3: versus growth or small versus big. Here is there a
Speaker 3: period at which if growth keeps out performing value, you say, actually,
Speaker 3: that's not a real sustainable factor. It's not mean reverting,
Speaker 3: and this was a the appearance of these excess returns
Speaker 3: was a function of limited sample size.
Speaker 5: Okay, So Kim French and I have always been very
Speaker 5: sensitive so exactly this problem. So every time we did
Speaker 5: a paper that seemed to have a new result discovering
Speaker 5: in it, we would consciously extend the data backward in
Speaker 5: time and see if the same pattern were observed, And
Speaker 5: then we'd go international and see if the same pattern
Speaker 5: was observed in the market. So we were very sensitive
Speaker 5: to the precisely issue they're raising. It's a very important issue.
Speaker 5: Not many people do that. They don't look at out
Speaker 5: of sample data to see if it worked there. Now,
Speaker 5: we only went forward when we found things that seemed
Speaker 5: to work back looking backward in the time, which is
Speaker 5: one way of going out of sample, and looking across markets,
Speaker 5: which is another way of going out of sample. But
Speaker 5: still it's possible that the discovery of the effect causes
Speaker 5: people to move through it to do stuff that basically
Speaker 5: makes it go away. And it takes a long time
Speaker 5: before you can tell.
Speaker 6: That that's true because of the basic nature of the
Speaker 6: uncertainty of the whole process, the amount of uncertainty there
Speaker 6: is about the evolution of prices.
Speaker 5: There's really no way to get around that.
Speaker 8: So we won't know what our life and my life
Speaker 8: my life time anyway, but I meany six years old,
Speaker 8: we won't know my lifetime whether the value bringium of
Speaker 8: the size meanium have actually gone away, because you still
Speaker 8: don't have enough data to come to that, to come
Speaker 8: to that conclusion.
Speaker 4: Well, also, let me add one additional When the Gene
Speaker 4: and Ken did did all his great research, they have
Speaker 4: the data there that jumps out of here, and one
Speaker 4: of the questions was always why would it be there?
Speaker 4: And you can go through the algebra why low price
Speaker 4: talks have higher average returns than high price talks. It
Speaker 4: seems sensible that there would be that low price talks
Speaker 4: might have higher expector returns because maybe because they're riskier.
Speaker 2: Gene, towards the end of the documentary, just on the
Speaker 2: notion of going forward, you kind of talk about what's
Speaker 2: next in modern finance, and you make the point that
Speaker 2: we are not making these sort of quantum academic jumps
Speaker 2: as we did in the nineteen seventies, and that someone
Speaker 2: needs to come up with a new innovation, a new
Speaker 2: burst forward. But you don't really know who that might be.
Speaker 2: Do you have any sense of where people should be
Speaker 2: look looking for the next big thing in modern finance
Speaker 2: or modern financial theory.
Speaker 5: That's again excellent question. But I think the answer is
Speaker 5: all that stuff is basically unpredictable. You don't know where
Speaker 5: the new direction is until somebody discovers it, and where
Speaker 5: people think it might be almost always turns out to
Speaker 5: be the wrong, wrong, wrong place. Not that you shouldn't
Speaker 5: do it, but simply this is a very difficult task.
Speaker 5: So the question is excellent. The answer, it's unavoidably vague.
Speaker 3: Fair enough answer, there's nothing. If if a young student
Speaker 3: came to you and said, hey, i'm looking you know
Speaker 3: at eighty six, you might not want to dive into
Speaker 3: something new, but there's nothing. He's like, oh, yeah, I'm
Speaker 3: sort of curious about that. You should try to pursue
Speaker 3: a write of paper. There's nothing that comes to mind
Speaker 3: that sort of you would suggest a young researcher make
Speaker 3: a stab at Well.
Speaker 5: The question we've started with was what's the next.
Speaker 3: Big Yeah, right, right, Okay.
Speaker 5: It changes the world. That's much more diffing.
Speaker 4: Sure, it's the next.
Speaker 5: Research wrinkle that we can do to extend that extends
Speaker 5: the world.
Speaker 4: A little bit fair enough.
Speaker 5: That's mostly what goes on research, the small little steps
Speaker 5: forward and sometimes little steps backwards. Stuff doesn't work out.
Speaker 2: Since we have gene fauma here, I cannot resist asking
Speaker 2: a sort of thought experiment question, But what would be
Speaker 2: an EMH interpretation of the cryptocurrency market? Can you look
Speaker 2: at it through an EMH lens?
Speaker 5: I was wondering when you're come to that. But cryptocurrency
Speaker 5: gives me all kinds of problems because like bitcoin is
Speaker 5: the only one I'm roughly familiar with, but nobody can
Speaker 5: explain why it survives because basically it's the old monetary
Speaker 5: theory says that something that has a highly variable real
Speaker 5: value can't be used as the medium of of exchange
Speaker 5: because people won't want to deal with it. So, for example,
Speaker 5: of business that doesn't want to do business in terms
Speaker 5: of bitcoin because the variation in the price of bitcoin
Speaker 5: itself can knot the company out of business. So then
Speaker 5: the question becomes, who does want to use bitcoin? Historical
Speaker 5: monetary theories I learned it it's not capable of answering
Speaker 5: that question, so it would have predicted and I'm still
Speaker 5: predicting that it'll bust. It it'll bust. At some point
Speaker 5: people will say no, that's it, and they'll stop piling
Speaker 5: piling into it, and then the market that marcro will
Speaker 5: just disappear. But we'll see if it survives. We need
Speaker 5: a whole theory to explain how and why.
Speaker 2: That sounds suspiciously like you're saying it's in a bubble.
Speaker 5: Oh I'm hoping it's in what I'm saying.
Speaker 4: Well, I think maybe that he's also saying that if
Speaker 4: crypto is going to survive, because it has value right
Speaker 4: now and it could maybe someday, you can do transactions
Speaker 4: cheaper than they can with master cards.
Speaker 5: So that's that's that's a good, good point, dude. Because
Speaker 5: there's the difference between the medium of exchange and the
Speaker 5: method of exchange. So the method of exchange is how
Speaker 5: do you carry out the transactions? The medium of exchange
Speaker 5: is what do you put into it in order to
Speaker 5: carry out the transactions. So the question is about the methods.
Speaker 5: The methods evolve all the time.
Speaker 6: So we have a central bank method now that we
Speaker 6: use pretty much for every everything in the US, But
Speaker 6: the blockchain is an alternative kind of mechanism.
Speaker 5: What you put into it can be anything it can
Speaker 5: be can be bitcoin, or it can be dollars. Does
Speaker 5: it didn't really matter? So those are two different things.
Speaker 5: So people worry that a system where a central bank
Speaker 5: manages the into transactions, which is the system we have,
Speaker 5: is too open to manipulation by the government, and that
Speaker 5: the blockchain avoids it. But then it turns out that
Speaker 5: the blockchain is not scalable intent its complication goes up
Speaker 5: basically exponentially as you as it handles more transactions, so
Speaker 5: that that's not the answer to the method of exchange problem.
Speaker 5: I mean, that's something people are struggling with.
Speaker 2: All Right, David and Gene, we're going to have to
Speaker 2: leave it there, But thank you so much for coming
Speaker 2: on odd Lots. It was a real pleasure to speak
Speaker 2: with you both. And congrats on the movie.
Speaker 4: Oh great, great, Thanks.
Speaker 9: It was really a lot of fun, Joe.
Speaker 2: That was really fun, Fama, especially with someone I always
Speaker 2: wanted to speak to. I do have to say, you know,
Speaker 2: I mentioned earlier, the way you feel about the term
Speaker 2: prem is probably the way I feel about the efficient
Speaker 2: markets hypothesis. And I recognize it's a theory that exists,
Speaker 2: but I guess I'm not sure how useful. It is
Speaker 2: to basically say that the average investor can match the
Speaker 2: average return of the market. Like, does that lead anywhere?
Speaker 3: Yeah, yeah, it absolutely leads somewhere. It means that you
Speaker 3: almost certainly shouldn't try, and that if you try, you
Speaker 3: will probably end up making mistakes. I mean, no, it's
Speaker 3: such a depressing no.
Speaker 2: I think the view of human capability, I.
Speaker 3: Think this is one of the most useful maxims in
Speaker 3: finance because even if it's not formally true, right, even
Speaker 3: if there are slight variabilities, et cetera, I do think
Speaker 3: it seems very clear that the vast majority of people,
Speaker 3: including many professionals, as the statistics have borne out, like,
Speaker 3: can't actually generate superior returns. And so if the only
Speaker 3: thing that we like, if the only use we get
Speaker 3: out of the efficient markets hypothesis is like do something
Speaker 3: else with your life than trying to beat the market.
Speaker 3: That sounds like wonderful advice that I think most people
Speaker 3: should heed.
Speaker 2: Should you say that on the All Thoughts podcast?
Speaker 3: Well, that's the funny thing. It's like, why are we
Speaker 3: all here? I mean, this is like the existential question
Speaker 3: of everything, because, like my interpretation of Jane's answers is
Speaker 3: basically a recurring series of yes, it's priced in, Yes
Speaker 3: it's priced in, and yes it's priced in. Yes it's priced in.
Speaker 3: And so I do have this existential question about we
Speaker 3: support this news organization that supports an industry, and I
Speaker 3: talk about this stuff all the time, and then it's like.
Speaker 2: Why I think I'm closer to David's position on this,
Speaker 2: where you know, true passive doesn't necessarily exist. There's sort
Speaker 2: of a middle ground where you can have systematic approaches
Speaker 2: but you're still making active decisions in the way you
Speaker 2: either execute trades or you know, in the cost of
Speaker 2: your investment and things like that. I think that's a
Speaker 2: reasonable middle ground. I am not sure I am an
Speaker 2: EMH fundamentalist camp just yet, but maybe you can convince me.
Speaker 3: Yeah, you know, here's my This is not the weak form.
Speaker 3: There's a definition of the weak form efficient market hypothesis.
Speaker 3: What I would say is this, and I've actually given
Speaker 3: this advice to other journalists, and I think this is
Speaker 3: something that I could try to convince people of, which
Speaker 3: is that if you look at the market and you
Speaker 3: think that you identify some security or anything that seems
Speaker 3: to you obviously mispriced. You should start with the presumption
Speaker 3: you're missing something. It's very unlikely that you've just seen
Speaker 3: something in the market that obviously you could profit from.
Speaker 3: Occasionally happens in people have a thesis and something looks
Speaker 3: clear and they make a lot of money. But I
Speaker 3: think most of the time, if you see a line,
Speaker 3: you're like, it shouldn't be there. You should start with
Speaker 3: the assumption that the billions of dollars flowing through the
Speaker 3: market didn't all miss something that you see as obvious.
Speaker 2: Yeah, but there are people who outperform the market, and
Speaker 2: it's a little bit like again tautological, I guess just
Speaker 2: to hand wave it away and be like, oh, they
Speaker 2: got lucky.
Speaker 3: Yeah, right, but can you identify the people who right,
Speaker 3: this is the problem? Like right, because yeah, and this
Speaker 3: is why, this is why it's all these Maybe they're lucky.
Speaker 2: In choosing the lucky investment managers.
Speaker 4: How about that?
Speaker 3: I mean, that's right, that's like, I mean, that's like,
Speaker 3: you know, manager selection suffers from the exact same problem
Speaker 3: with stock selection, the out of sample in sample bias.
Speaker 3: This is why. But one thing I am curious about,
Speaker 3: like when we are long dead and maybe the odd
Speaker 3: lots franchise is so valuable that there's like, you know,
Speaker 3: there's like new hosts of the podcast, right because they
Speaker 3: want to continue it. Maybe they'll be alive long enough
Speaker 3: to say, like, oh, turns out there's no small cat
Speaker 3: premium after all. Because Jane opened up the possibility that, yeah,
Speaker 3: we all of finance and economics suffer is from the
Speaker 3: tragedy of small sample sizes. Like it's like this known phenomenon,
Speaker 3: like the world is just getting started. Maybe one day
Speaker 3: it'll be like, actually, turned out that wasn't really a thing,
Speaker 3: but they'll probably be after all of our lifetimes.
Speaker 2: In the long run, we're all dead. Since you mentioned it.
Speaker 3: In the long run, all factors, all factors are suffer
Speaker 3: from sample bias.
Speaker 2: Since you mentioned the small cap stocks, there was this
Speaker 2: little visual in the documentary where they showed a headline
Speaker 2: from I think it was the early nineteen nineties, and
Speaker 2: the headline was mutual funds offbeat theory by stock in
Speaker 2: smaller firms, And I thought that was so funny and
Speaker 2: kind of quaint because they're basically talking about gross stocks.
Speaker 2: And you know, nowadays growth stocks are sort of an
Speaker 2: accepted idea, but back then it was off beat and
Speaker 2: offbeat theory, and it kind of shows just how much
Speaker 2: financial theory is embedded in the market now that we
Speaker 2: take for granted. But you know, a decade ago, or
Speaker 2: two decades ago or five decades ago, people didn't know
Speaker 2: it well.
Speaker 3: And just on this one point, it is interesting too
Speaker 3: that now if someone says growth stocks, you think really
Speaker 3: big companies. Yeah, And there was a time when if
Speaker 3: someone said growth stocks, you'd think about really small companies
Speaker 3: and that big companies were supposed to grow slowly. And
Speaker 3: so this is kind of what I wonder about, like
Speaker 3: these like our fundamental realities of business changing, and could
Speaker 3: those fundamental realities of business changing change fundamental aspects of
Speaker 3: the stock market because we now have this era where
Speaker 3: you have gigantic companies still putting up growth numbers that
Speaker 3: in any time would be incredible.
Speaker 2: All right, shall we leave it there.
Speaker 3: Let's leave it there.
Speaker 2: This has been another episode of the All Thoughts podcast.
Speaker 2: I'm Tracy Alloway. You can follow me at Tracy Alloway and.
Speaker 3: I'm Joe Wisenthal. You can follow me at The Stalwart.
Speaker 3: Check out the new Errol Morris documentary Tune Out The
Speaker 3: Noise That Talks about all of these things and the
Speaker 3: beginnings of modern fire finance. Follow our producers Kerman Rodriguez
Speaker 3: at Kerman armand dash Ol Bennett at Dashbot and kill
Speaker 3: Brooks at Killebrooks. From our odd Lots content, go to
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