March 6, 2025 • 49 mins
The 1970s were a pretty eventful time in markets. There was high inflation, the end of the gold standard, and a stock market crash. There was also a bunch of ideas coming out of the University of Chicago that would go on to be famous and highly influential for investors. Perhaps the most prominent is the Efficient Market Hypothesis, posited by Nobel Laureate Eugene Fama, which says that markets are right and it's useless for investors to try to outguess them. Fama later teamed up with David Booth, the founder of Dimensional Fund Advisors, and has been a longtime collaborator with the firm, which now has $777 billion under management. Today, they're releasing a documentary directed by Errol Morris and called "Tune Out the Noise," which chronicles this important time. We speak to both of these investment legends about the development of their theories, how they put them into practice, subsequent criticism, and what comes next.
Read more:
Wall Street Math Wizards Are Decoding Private-Market Returns
Upstarts Challenge a Foundation of Modern Investing
Cliff Asness Says Markets Are Less Efficient — And Social Media May Be to Blame
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Episode Transcript
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Speaker 1 (00:02):
Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 2 (00:18):
Hello and welcome to another episode of the All Thoughts podcast.
I'm Tracy Alloway.
Speaker 3 (00:22):
And I'm Joe. Why isn't thal.
Speaker 2 (00:24):
Joe, what's your favorite financial movie? I don't think I've
ever asked you that question?
Speaker 3 (00:29):
Really, I mean Trading Places.
Speaker 2 (00:31):
Oh, that's funny. That's mine too.
Speaker 3 (00:34):
Yeah, and not only.
Speaker 2 (00:35):
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 know because of trading places.
Speaker 3 (00:46):
I have no idea where you're going with, and I think.
Speaker 2 (00:48):
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.
Speaker 3 (00:55):
Okay, here you go.
Speaker 2 (00:56):
Trading Places aside, Yes, I would agree. Yeah, I know
we have the Big Shore 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
(01:19):
to illustrate in a visual way, but I still want them.
Speaker 3 (01:23):
Me too, all right, keep going crazy?
Speaker 2 (01:26):
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
(01:46):
are people like Martin 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.
Speaker 3 (01:57):
I'm really excited because I'm finally going to have as
to ask is it all priced in? Because this is
my core belief about markets, that is, like, no, 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
(02:17):
finally get an answer to this question.
Speaker 2 (02:19):
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 Fauma, 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
(02:42):
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.
Speaker 4 (02:51):
Thank you well, thanks for having us. I'm looking forward
to it.
Speaker 2 (02:55):
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.
Speaker 4 (03:08):
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
Warren Unknown documentarian, and now we're talking to him about
how we could use some of his expertise for our firm.
He got really into it. He had no not much
(03:28):
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.
Speaker 3 (03:37):
That's cool. We've done an episode with Dimensional's co CEO,
George 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
(03:59):
history of finance. What is the sort of short version
of the sort of intellectual partnership and how this firm
Dimensional came about.
Speaker 5 (04:09):
Well, David was my research assistant fifty five years ago.
Speaker 4 (04:14):
David, Yeah.
Speaker 5 (04:16):
Anyway, it actually worked with 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 McCown and got David a job that way
with the Wells figu I us. It wasn't the time, David.
Speaker 4 (04:38):
Right, right, nineteen seventy one.
Speaker 6 (04:40):
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.
Speaker 5 (04:48):
We've been going in it ever since.
Speaker 2 (04:50):
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 Bogel'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
(05:13):
share things with each other?
Speaker 4 (05:15):
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
(05:35):
philosophy about sharing research. And so Wells got off to
a slow start in some ways, but it was a
fund little question. You can 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 the walls got shut down, Mac just volunteered to
(05:58):
Bogel to share all of his NATA with him.
Speaker 3 (06:02):
Gine, 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 a 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
(06:25):
and some of your early research, well.
Speaker 5 (06:28):
As I stand on it. In college, actually I worked
for a professor at TUFFS that had a stock market
forecasting service, and my job was to come up with
new ways to beat the market.
Speaker 3 (06:40):
How'd that go?
Speaker 5 (06:40):
It didn't go very well, but in the following sense,
he was very good statistician, so we always kept a
hold out sample and my ideas always worked in sample,
but they never worked out of sample. So that was
my first lesson on what do you can expect by
trying to beat the market. And after that I went
off to Sego, took my data with me from Tefts,
(07:03):
and eventually wrote.
Speaker 7 (07:04):
My thesis using that data, which was kind of the
the first that maybe one of the bigger trumpeting of
fishing markets the term went.
Speaker 6 (07:15):
It wasn't even wasn't even called that at the time,
but eventually that term came around as well.
Speaker 4 (07:21):
One of the things is interesting about that observed 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 have if they knew how
we did things in the old days.
Speaker 2 (07:42):
Well, I remember, in the old days of Bloomberg, we
often input it a lot of financially, if you're working
in the global data department, and you certainly input it
a lot of things by hand as well. This leads
to a question I want 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
(08:05):
all these names that went on to do big things
in finance.
Speaker 5 (08:09):
Well, Marton Miller was an important person. He was deeply
interested in this stuff. And Harry Arms was another important
person who had written on something resembling what would be
now called the fishing markets way back in the fifties.
So he was very much interested in it. And they
were kind of the two shining lights in this area.
(08:33):
And plus then there were a lot of PhD students,
including me, these is topics. So having faculty interested in
the topic was a good way of having researched them
by students in that type, because that was the way
to graduate. And at the time I had two kids
with another one on the way, so it was very
very keen on getting out quickly.
Speaker 4 (08:55):
Well, I would also add, you know, Jim Laurie, I
mean gentleman Larry Fisher. They persuaded Barrel Lynch to fund
a study to collect a survivorship bias free database which
enabled all these new young hotshots to do their research.
Until that point to the data had never been collected
(09:18):
correctly and so he couldn't really do the research.
Speaker 5 (09:21):
So when Larry started out to Larry's Fish started out
to collect that data and put it together. A computer
didn't exist it could handle it, but he said, well,
it's going to come along by the time me finish
this to be computer you can handle it. And he
took out to be.
Speaker 3 (09:37):
Raised, 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
ninety nine point nine percent of the people who have interest,
because I wouldn't do it because my risk get really tired,
(10:00):
really fast, and my handwriting is garbage, so I wouldn't
even be able to read what I had written in
the graph paper, et cetera. 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
(10:21):
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.
Speaker 4 (10:35):
Look, all these tests and market efficiency, which started in
the sixties, you know, and have keep showing the same
result every sense, even though with increasing levels of sophistication
of researchers and people having access to more and more
more data, better data, faster data, all of that, this
still shows the same outcome of it doesn't look like
(11:00):
find how guess the market is a winning game.
Speaker 2 (11:03):
So, since we're on the subject of the efficient markets hypothesis,
one of your former students who also went on to
a great fame. Cliff asnas 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
(11:24):
following idiots. I guess, 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
(11:48):
efficient markets hypothesis changed at all over time?
Speaker 5 (11:52):
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.
(12:16):
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.
Speaker 6 (12:28):
But if you don't take out the fees and expensive
then the active managers look terrible relative to.
Speaker 5 (12:34):
The passive managers. So that's the kind of data and
results that makes market efficiency look pretty good.
Speaker 4 (12:42):
But it's not.
Speaker 5 (12:43):
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.
Speaker 8 (12:55):
M hm.
Speaker 3 (13:08):
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
(13:28):
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?
Speaker 5 (13:39):
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 manages going. Individuals who make
who don't think the 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.
(14:02):
And then we see who comes out on.
Speaker 2 (14:04):
Top, Geene, 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. Very serious, explain it more, because
Joe and I have lots of episodes where we talk
about either past bubbles or overvaluations.
Speaker 5 (14:24):
Yeah, so with twenty twenty, I didn't say, as you know,
it's explain why prices won't happen, why why they way
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 when that hope
phenomen it's going to that hope price movement is going
(14:46):
to go away. And that's what's just proving really difficult
to do. So lots of people use the word bubble
very loosely. I can't sell my subscription to the economists
because you're using the word.
Speaker 3 (15:01):
Journalists are terrible about overusing bubble. I will cop to
that on the behalf of the entire profession, right.
Speaker 5 (15:08):
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 are willing to do that.
There are econs that are willing to do it, and
I can deal with that. There has to be some predictability,
but when it's going to end, and that's what proven
really difficult to establish.
Speaker 3 (15:27):
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 at
or losing all your clients if you're avoiding it. So
I certainly take that point. Let me press further though,
(15:49):
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.
(16:13):
Reconcile the existence of that with the idea of efficient marketing.
Speaker 5 (16:18):
Okay, that's that's a good question. So everybody has this confusion.
The confusion is mixing together market.
Speaker 6 (16:25):
Efficiency and the dimensions of risk and portfolio selection.
Speaker 5 (16:31):
So going back all the way to Macrowitz. We've a
long known for example, the people don't like variants, they
don't like uncertainty about future liters, and they're willing to
pay something to avoid it. So they gave rise to
the chaplain and their capital so called capital asset pricing
model in which sensitivity to the market was the measure
(16:53):
of it was the measure of risk. So basically into
confusion of prices being reflect value in the study about
what are the dimensions of risk in the market. So
that's a confusion that almost everybody seems to have. So
Marcus doesn't say there aren't risk premeans in the market,
(17:13):
does not say that at all.
Speaker 4 (17:16):
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 believes talks are with
a long haul level higher return than bonds. A few
people invest all their money in stockses and doesn't mean
stocks are inefficient and efficiently priced, and just those are
the market prices. And you look at different combinations of
(17:39):
the two and they provide different distributions of outcomes, and
just find that distribution that works best for you.
Speaker 2 (17:47):
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 it 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
(18:08):
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 the theory should know that this
is going to happen and so it should already be
priced in. How has passive actually changed the market?
Speaker 4 (18:28):
Well, that's an interesting question. First off, the kind of
the impact of an index adding a new name, you know,
causing temporary prices to go up. That's a temporary effect.
It doesn't really impact the long term investor very much.
And one question that comes up a lot is, you know,
if everybody indexed, you know, then there would be no
(18:49):
price discovery. Wouldn't markets become inefficient?
Speaker 5 (18:52):
You know?
Speaker 4 (18:53):
That's kind of And my answer to that is, well,
let's take a look at it. The behavior of the
market over the last twenty years. There's been an incredible
movement to indexing over that time period, and yet there's
been an incredible increase in trading volume. You know, I
don't think of price discovery has been related to trading volume.
(19:14):
So just because there's a big movement to indexing doesn't
mean trading volume multi climb. 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
(19:38):
for or whatever it is. And I think that really
comes to what happened to the marketplace is it's kind
of to an individual instead of individual stock selection, it's
kind of like 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
(20:00):
much impact on that.
Speaker 5 (20:02):
So let me just take different direction. And people worry
that if everybody goes assive, 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 man, just people who have no special information.
If they drop out, then you need few good active
(20:25):
people to keep prices inline. So it depends on who
drops out as to whether has any effect at all
on market efficiency. And we haven't been able to discern
anything like that in the behavior of prices, But that
is the question.
Speaker 2 (20:43):
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 and P five hundred or the
MSCI World Index. And 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
(21:04):
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.
Speaker 5 (21:25):
To choose the one you want. So my own tastes
run in the direction of a total market index being
a good choice for almost everybody. So I don't go from.
Speaker 6 (21:36):
The subset things that thirty thirty down Jones that was
always kind of dumb.
Speaker 5 (21:42):
But or even five hundred, that's only five hundred. There's
a loves stucks out there.
Speaker 4 (21:48):
Then than that, let me just recall against the term passive.
You know, in my view, there's no such thing as
passive management. And you're you're touching on something right there.
You know the different index providers and how they do it,
and they'll do it differently and so forth. And you
know Standard and Poors when it wants to add stock
(22:10):
to its sm P five hundred, you know, the investment
committee sits around and talks about you know, what do
you like? You know, it's the S and P five
hundred is five hundred of the largest companies, but it's
not the five hundred 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
(22:33):
fund because you don't like stock selection, that's not the
kind of activity you want to you want to see.
Speaker 3 (22:39):
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's wanting to avoid drawdowns, et cetera.
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 you
(23:00):
know it, 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 should anyone own bonds? Because you say,
hardly anyone just own stocks, and that seems to be
objectively true. But I wonder if, like, is there reason
(23:22):
to question some of this dogma of like why, like,
if I'm not going to retire in thirty 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
(23:44):
be rethought if over the next thirty years before I
can retire twenty five years, maybe, like, if almost everyone
thinks it's certain that stocks will outperform bonds, why am
I holding bonds.
Speaker 5 (23:58):
That sense that if almost every but he thinks that's true,
But it's not true. Stucks don't get less risk. In
the long term, risk accumulates, So.
Speaker 3 (24:11):
I don't understand that. I don't understand how.
Speaker 5 (24:14):
When you retire, when you retire a period when stocks
have been particularly poorly and you will get hurt, that's
always a possibility, doesn't go away with the time.
Speaker 6 (24:26):
So the presumption is is what's incorrect? The risk is
always there, you don't get rid of it.
Speaker 2 (24:33):
What do you think about the term smart beta? And
is dimensional doing smart beta?
Speaker 5 (24:41):
Yeah, smart is a marketing term. Show me a dumb beta.
Speaker 2 (24:48):
I'm sure I could find some examples, but they certainly
wouldn't have set out to create dumb beata.
Speaker 5 (24:53):
There's a lot of Mike, there's a lot of marketing
in the financial business. That's one of them. That's one
of the big ones.
Speaker 3 (25:00):
Well, what does it mean to you? So like when
you hear that term, like, what is the person trying
to sell to me?
Speaker 5 (25:05):
Well, that have to give me an example because I
don't take it seriously. Obviously you can tell me checking here.
Speaker 4 (25:10):
Well, I think it's a Jeans research that he did
with Ken French. You know, his landmark ninety two paper
on called cross section of expected returns anyway that you know,
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 over the term
(25:33):
smart data. It's not smart, I mean, just it's just,
you know, a reflection of the research and the dimensions
of returns.
Speaker 3 (25:42):
You know, something that I'm really interested in when it
comes to markets particularly, I would say over the last
(26:04):
fifteen years since the Great Financial Crisis, small caps have
certainly not provided 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,
(26:24):
and I know people sometimes try to redefine these to
allow them to put in VideA 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 and beating earnings
expectations year after year after year. Does this pose a
(26:47):
problem for a sort of factor oriented investor. When the
fundamentals of one sector, the real fundamentals, not the stock performance,
produced these abnormal periods of profitability growth.
Speaker 5 (27:04):
Well, I don't know how I abnormal they are. So
the instance of all these dimensions of returns is that
they're risky. There is, the results are highly uncertain over
any finite period of any period of time, so they
can do poorly for long periods of time. They can
also go away. If there's too many people jump on things,
(27:25):
it can cause them to go away. So it's possible,
for example, then interest in small stocks and interest in
value stocks killd thes size and the value 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,
(27:46):
then you can see these premiums disappear. It's very difficult
to unravel the story in the data because there's.
Speaker 6 (27:53):
So much ensutancy 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 feel
them anymore.
Speaker 5 (28:08):
They jump into them if they think the returns out
are better. That's always been a possibility, Conferntion, and I
pointed that out in the initial papers we wrote on
the dimensions of risk.
Speaker 3 (28:20):
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
(28:42):
at some point get compensated for taking on these risks
into your portfolio.
Speaker 5 (28:48):
Well listen. And then the mixing and trading costs there,
So there are differential trading costs and different kinds of assets,
different transactions costs. Those are part of what you may
played play the game. In principle, it tract from the price.
Speaker 6 (29:02):
Of the prices of the stocks. But I'm not sure
about what your question was actually.
Speaker 3 (29:10):
Basically the idea that at any given point you will
be compensated for the risks of smaller, less liquid stocks.
That's not a necessarily a permanent characteristic of the market.
Speaker 5 (29:23):
Well, it was, it was always there was always a
dimension of risk, which means this volatility associated with it.
So through the historically, during the periods when on the
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, good, good return. So that's always true.
(29:44):
So there always been periods when stocks did worse than
bills through a long period of that in the thirties,
forties all the way up to the fifties. So these
are just dimensions of risk and return basically, and risk
means you.
Speaker 4 (29:58):
Can mose will point out a kind of the direction
in your head. It is 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, you know, we built
it on the idea that you ought to have large
and small cap stocks in your portfolio, not just large cap.
(30:18):
Our first clients were large institutional clients and they were
only holding the stocks of bigger companies because they were
trying to the hired managers to how guests 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
(30:40):
business or it's hard to anyway. So the thrust wasn't
so much that we guarantee your higher returns. The thrust
is you ought to have a well diversified portfolio, and
our view how to include a significant chunk of small cap.
Speaker 2 (30:56):
David you highlighted earlier the importance of data in modern
final 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 Gene's point,
you know, computers and the ability to actually track more
information and crunch it more efficiently. Nowadays, it kind of
(31:18):
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.
Speaker 4 (31:41):
Well, you know, Jeans you is the market reflects all
available information. That's kind of the implication of efficient markets,
and it was these AI programs so forth. I mean,
they have vast amounts of data, but no AI algorithm
can reflect all available information. So even though they have
(32:03):
lots of information, there's still lots to get reflected, seemingly
in stocking bond prices.
Speaker 5 (32:08):
Looking at it from the academic side, what's happened with
the coming up so many big databases that people do
lots of research, is that research and finances expanded. There
used to be just a few of us still doing
it in the sixties and seventies. Now we have big
finance departments and almost every school all with people who
(32:30):
want to do work. Most of it are work on
lots of it work on market. So where there was
well basically one journal in this in the sixties, there
was all open to this kind of stuff. Now you
have four or five of them that are all all
pretty good. No coming up with no stuff, publishing three
or four times a year. So there's been an explosion
(32:52):
of research and uses all these new data, and that's
been to the plus. I think, I really when I
and my young people, I say, boy, in the old days,
it was easy. When I was coming up, it was
like shooting fishing in barrow. Nobody was doing anything, so
everything he did was new. Now it's much more difficult,
that much more precedent about what's been done and what
(33:14):
hasn't been done.
Speaker 3 (33:15):
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 in the 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
(33:36):
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, et cetera.
When do you say, like a factor loses legitimacy. It's like,
(33:59):
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 out performing value, you say, actually,
(34:20):
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.
Speaker 5 (34:32):
Okay, So Kim French and I have always been very
sensitive so exactly this problem. So every time we did
a paper that seemed to have a new result discovering
in it, we would consciously 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 the market. So we were very sensitive
(34:55):
to the precisely issue they'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 back looking backward in the time, which is
one way of going out of sample, and looking across markets,
which is another way of going out of sample. But
(35:17):
still it's possible that the discovery of the effect causes
people to move through it to do stuff that basically
makes it go away. And it takes a long time
before you can tell.
Speaker 6 (35:30):
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.
Speaker 5 (35:39):
There's really no way to get around that.
Speaker 8 (35:41):
So we won't know what our life and my life
my life time anyway, but I meany six years old,
we won't know my lifetime whether the value bringium of
the size meanium have actually gone away, because you still
don't have enough data to come to that, to come
to that conclusion.
Speaker 4 (35:57):
Well, also, let me add one additional When the Gene
and Ken did did all his great research, they have
the data there that jumps out of here, and one
of the questions was always why would it be there?
And you can go through the algebra why low price
talks have higher average returns than high price talks. It
(36:18):
seems sensible that there would be that low price talks
might have higher expector returns because maybe because they're riskier.
Speaker 2 (36:28):
Gene, 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 nineteen seventies, and that someone
needs to come up with a new innovation, a new
(36:51):
burst forward. But you don't really know who that might be.
Do you have any sense of where people should be
look looking for the next big thing in modern finance
or modern financial theory.
Speaker 5 (37:05):
That's again 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, wrong, wrong place. Not that you shouldn't
do it, but simply this is a very difficult task.
(37:28):
So the question is excellent. The answer, it's unavoidably vague.
Speaker 3 (37:35):
Fair enough answer, there's nothing. If if a young student
came to you and said, hey, i'm looking you know
at eighty six, you might not want to dive into
something new, but there's nothing. He's like, oh, yeah, I'm
sort of curious about that. You should try to pursue
a write of paper. There's nothing that comes to mind
that sort of you would suggest a young researcher make
a stab at Well.
Speaker 5 (37:56):
The question we've started with was what's the next.
Speaker 3 (37:59):
Big Yeah, right, right, Okay.
Speaker 5 (38:01):
It changes the world. That's much more diffing.
Speaker 4 (38:05):
Sure, it's the next.
Speaker 5 (38:06):
Research wrinkle that we can do to extend that extends
the world.
Speaker 4 (38:10):
A little bit fair enough.
Speaker 5 (38:11):
That's mostly what goes on research, the small little steps
forward and sometimes little steps backwards. Stuff doesn't work out.
Speaker 2 (38:19):
Since we have gene fauma 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?
Speaker 5 (38:35):
I was wondering when you're 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
(38:56):
value can't be used as the medium of of exchange
because people won't want to deal with it. So, for example,
of business that doesn't want to do business in terms
of bitcoin because the variation in the price of bitcoin
itself can knot the company out of business. So then
the question becomes, who does want to use bitcoin? Historical
(39:19):
monetary theories I learned it it's not capable of answering
that question, so it would have predicted and I'm still
predicting that it'll bust. It it'll bust. At some point
people will say no, that's it, and they'll stop piling
piling into it, and then the market that marcro will
just disappear. But we'll see if it survives. We need
(39:39):
a whole theory to explain how and why.
Speaker 2 (39:43):
That sounds suspiciously like you're saying it's in a bubble.
Speaker 5 (39:47):
Oh I'm hoping it's in what I'm saying.
Speaker 4 (39:53):
Well, I think maybe that he's also saying that if
crypto is going to survive, because it has value right
now and it could maybe someday, you can do transactions
cheaper than they can with master cards.
Speaker 5 (40:10):
So that's that's that's a good, good point, dude. Because
there's the 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 transactions. So the question is about the methods.
The methods evolve all the time.
Speaker 6 (40:32):
So we have a central bank method now that we
use pretty much for every everything in the US, But
the blockchain is an alternative kind of mechanism.
Speaker 5 (40:43):
What you put into it can be anything it can
be can be bitcoin, or it can be dollars. Does
it didn't really matter? So those are two different things.
So people worry that a system where a central bank
manages the into transactions, which is the system we have,
(41:03):
is too open to manipulation by the government, and that
the blockchain avoids it. But then it turns out that
the blockchain is not scalable intent its complication goes up
basically exponentially as you as it handles more transactions, so
that that's not the answer to the method of exchange problem.
(41:23):
I mean, that's something people are struggling with.
Speaker 2 (41:27):
All Right, David and Gene, 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.
Speaker 4 (41:36):
Oh great, great, Thanks.
Speaker 9 (41:37):
It was really a lot of fun, Joe.
Speaker 2 (41:52):
That was really fun, Fama, especially with someone I always
wanted to speak to. I do have to say, you know,
I mentioned earlier, the way you feel about the term
prem 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
(42:13):
average return of the market. Like, does that lead anywhere?
Speaker 3 (42:17):
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, no, it's
such a depressing no.
Speaker 2 (42:30):
I think the view of human capability, I.
Speaker 3 (42:32):
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, et cetera, 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
(42:56):
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.
Speaker 2 (43:09):
Should you say that on the All Thoughts podcast?
Speaker 3 (43:11):
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 Jane's answers is
basically a recurring series of yes, it's priced in, Yes
it's priced in, and yes it's priced in. Yes it's priced in.
And so I do have this existential question about we
(43:32):
support this news organization that supports an industry, and I
talk about this stuff all the time, and then it's like.
Speaker 2 (43:39):
Why I think I'm closer to David's position on this,
where you know, 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 you know, in the cost of
your investment and things like that. I think that's a
(44:02):
reasonable middle ground. I am not sure I am an
EMH fundamentalist camp just yet, but maybe you can convince me.
Speaker 3 (44:10):
Yeah, you know, 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
(44:35):
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 could profit from.
Occasionally happens in 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
(44:56):
the assumption that the billions of dollars flowing through the
market didn't all miss something that you see as obvious.
Speaker 2 (45:03):
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.
Speaker 3 (45:13):
Yeah, right, but can you identify the people who right,
this is the problem? Like right, because yeah, and this
is why, this is why it's all these Maybe they're lucky.
Speaker 2 (45:22):
In choosing the lucky investment managers.
Speaker 4 (45:24):
How about that?
Speaker 3 (45:25):
I mean, that's right, that's like, I mean, that's like,
you know, manager selection suffers from the exact same problem
with 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
(45:46):
want to continue it. Maybe they'll be alive long enough
to say, like, oh, turns out there's no small cat
premium after all. Because Jane opened up the possibility that, yeah,
we all of finance and economics suffer is from the
tragedy of small sample sizes. Like it's like this known phenomenon,
like the world is just getting started. Maybe one day
(46:07):
it'll be like, actually, turned out that wasn't really a thing,
but they'll probably be after all of our lifetimes.
Speaker 2 (46:12):
In the long run, we're all dead. Since you mentioned it.
Speaker 3 (46:15):
In the long run, all factors, all factors are suffer
from sample bias.
Speaker 2 (46:22):
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 nineteen nineties, 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 gross stocks.
(46:44):
And you know, nowadays growth stocks are sort of an
accepted idea, but back then it was off beat and
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.
Speaker 3 (47:03):
And just on this one point, it is interesting too
that now if someone says growth stocks, you think really
big companies. Yeah, 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 like our fundamental realities of business changing, and could
(47:25):
those fundamental realities of business changing change fundamental aspects of
the stock market because we now have this era where
you have gigantic companies still putting up growth numbers that
in any time would be incredible.
Speaker 2 (47:40):
All right, shall we leave it there.
Speaker 3 (47:41):
Let's leave it there.
Speaker 2 (47:42):
This has been another episode of the All Thoughts podcast.
I'm Tracy Alloway. You can follow me at Tracy Alloway and.
Speaker 3 (47:48):
I'm Joe Wisenthal. 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 fire finance. Follow our producers Kerman Rodriguez
at Kerman armand dash Ol Bennett at Dashbot and kill
Brooks at Killebrooks. From our odd Lots content, go to
(48:08):
Bloomberg dot com slash odd lots, 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 dot gg slash od lots.
Speaker 2 (48:23):
And if you enjoy odd Lots, 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
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find the Bloomberg channel on Apple Podcasts and follow the
(48:45):
instructions there. Thanks for listening in
Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 2 (00:18):
Hello and welcome to another episode of the All Thoughts podcast.
I'm Tracy Alloway.
Speaker 3 (00:22):
And I'm Joe. Why isn't thal.
Speaker 2 (00:24):
Joe, what's your favorite financial movie? I don't think I've
ever asked you that question?
Speaker 3 (00:29):
Really, I mean Trading Places.
Speaker 2 (00:31):
Oh, that's funny. That's mine too.
Speaker 3 (00:34):
Yeah, and not only.
Speaker 2 (00:35):
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 know because of trading places.
Speaker 3 (00:46):
I have no idea where you're going with, and I think.
Speaker 2 (00:48):
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.
Speaker 3 (00:55):
Okay, here you go.
Speaker 2 (00:56):
Trading Places aside, Yes, I would agree. Yeah, I know
we have the Big Shore 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
(01:19):
to illustrate in a visual way, but I still want them.
Speaker 3 (01:23):
Me too, all right, keep going crazy?
Speaker 2 (01:26):
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
(01:46):
are people like Martin 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.
Speaker 3 (01:57):
I'm really excited because I'm finally going to have as
to ask is it all priced in? Because this is
my core belief about markets, that is, like, no, 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
(02:17):
finally get an answer to this question.
Speaker 2 (02:19):
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 Fauma, 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
(02:42):
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.
Speaker 4 (02:51):
Thank you well, thanks for having us. I'm looking forward
to it.
Speaker 2 (02:55):
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.
Speaker 4 (03:08):
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
Warren Unknown documentarian, and now we're talking to him about
how we could use some of his expertise for our firm.
He got really into it. He had no not much
(03:28):
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.
Speaker 3 (03:37):
That's cool. We've done an episode with Dimensional's co CEO,
George 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
(03:59):
history of finance. What is the sort of short version
of the sort of intellectual partnership and how this firm
Dimensional came about.
Speaker 5 (04:09):
Well, David was my research assistant fifty five years ago.
Speaker 4 (04:14):
David, Yeah.
Speaker 5 (04:16):
Anyway, it actually worked with 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 McCown and got David a job that way
with the Wells figu I us. It wasn't the time, David.
Speaker 4 (04:38):
Right, right, nineteen seventy one.
Speaker 6 (04:40):
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.
Speaker 5 (04:48):
We've been going in it ever since.
Speaker 2 (04:50):
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 Bogel'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
(05:13):
share things with each other?
Speaker 4 (05:15):
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
(05:35):
philosophy about sharing research. And so Wells got off to
a slow start in some ways, but it was a
fund little question. You can 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 the walls got shut down, Mac just volunteered to
(05:58):
Bogel to share all of his NATA with him.
Speaker 3 (06:02):
Gine, 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 a 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
(06:25):
and some of your early research, well.
Speaker 5 (06:28):
As I stand on it. In college, actually I worked
for a professor at TUFFS that had a stock market
forecasting service, and my job was to come up with
new ways to beat the market.
Speaker 3 (06:40):
How'd that go?
Speaker 5 (06:40):
It didn't go very well, but in the following sense,
he was very good statistician, so we always kept a
hold out sample and my ideas always worked in sample,
but they never worked out of sample. So that was
my first lesson on what do you can expect by
trying to beat the market. And after that I went
off to Sego, took my data with me from Tefts,
(07:03):
and eventually wrote.
Speaker 7 (07:04):
My thesis using that data, which was kind of the
the first that maybe one of the bigger trumpeting of
fishing markets the term went.
Speaker 6 (07:15):
It wasn't even wasn't even called that at the time,
but eventually that term came around as well.
Speaker 4 (07:21):
One of the things is interesting about that observed 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 have if they knew how
we did things in the old days.
Speaker 2 (07:42):
Well, I remember, in the old days of Bloomberg, we
often input it a lot of financially, if you're working
in the global data department, and you certainly input it
a lot of things by hand as well. This leads
to a question I want 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
(08:05):
all these names that went on to do big things
in finance.
Speaker 5 (08:09):
Well, Marton Miller was an important person. He was deeply
interested in this stuff. And Harry Arms was another important
person who had written on something resembling what would be
now called the fishing markets way back in the fifties.
So he was very much interested in it. And they
were kind of the two shining lights in this area.
(08:33):
And plus then there were a lot of PhD students,
including me, these is topics. So having faculty interested in
the topic was a good way of having researched them
by students in that type, because that was the way
to graduate. And at the time I had two kids
with another one on the way, so it was very
very keen on getting out quickly.
Speaker 4 (08:55):
Well, I would also add, you know, Jim Laurie, I
mean gentleman Larry Fisher. They persuaded Barrel Lynch to fund
a study to collect a survivorship bias free database which
enabled all these new young hotshots to do their research.
Until that point to the data had never been collected
(09:18):
correctly and so he couldn't really do the research.
Speaker 5 (09:21):
So when Larry started out to Larry's Fish started out
to collect that data and put it together. A computer
didn't exist it could handle it, but he said, well,
it's going to come along by the time me finish
this to be computer you can handle it. And he
took out to be.
Speaker 3 (09:37):
Raised, 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
ninety nine point nine percent of the people who have interest,
because I wouldn't do it because my risk get really tired,
(10:00):
really fast, and my handwriting is garbage, so I wouldn't
even be able to read what I had written in
the graph paper, et cetera. 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
(10:21):
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.
Speaker 4 (10:35):
Look, all these tests and market efficiency, which started in
the sixties, you know, and have keep showing the same
result every sense, even though with increasing levels of sophistication
of researchers and people having access to more and more
more data, better data, faster data, all of that, this
still shows the same outcome of it doesn't look like
(11:00):
find how guess the market is a winning game.
Speaker 2 (11:03):
So, since we're on the subject of the efficient markets hypothesis,
one of your former students who also went on to
a great fame. Cliff asnas 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
(11:24):
following idiots. I guess, 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
(11:48):
efficient markets hypothesis changed at all over time?
Speaker 5 (11:52):
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.
(12:16):
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.
Speaker 6 (12:28):
But if you don't take out the fees and expensive
then the active managers look terrible relative to.
Speaker 5 (12:34):
The passive managers. So that's the kind of data and
results that makes market efficiency look pretty good.
Speaker 4 (12:42):
But it's not.
Speaker 5 (12:43):
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.
Speaker 8 (12:55):
M hm.
Speaker 3 (13:08):
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
(13:28):
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?
Speaker 5 (13:39):
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 manages going. Individuals who make
who don't think the 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.
(14:02):
And then we see who comes out on.
Speaker 2 (14:04):
Top, Geene, 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. Very serious, explain it more, because
Joe and I have lots of episodes where we talk
about either past bubbles or overvaluations.
Speaker 5 (14:24):
Yeah, so with twenty twenty, I didn't say, as you know,
it's explain why prices won't happen, why why they way
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 when that hope
phenomen it's going to that hope price movement is going
(14:46):
to go away. And that's what's just proving really difficult
to do. So lots of people use the word bubble
very loosely. I can't sell my subscription to the economists
because you're using the word.
Speaker 3 (15:01):
Journalists are terrible about overusing bubble. I will cop to
that on the behalf of the entire profession, right.
Speaker 5 (15:08):
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 are willing to do that.
There are econs that are willing to do it, and
I can deal with that. There has to be some predictability,
but when it's going to end, and that's what proven
really difficult to establish.
Speaker 3 (15:27):
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 at
or losing all your clients if you're avoiding it. So
I certainly take that point. Let me press further though,
(15:49):
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.
(16:13):
Reconcile the existence of that with the idea of efficient marketing.
Speaker 5 (16:18):
Okay, that's that's a good question. So everybody has this confusion.
The confusion is mixing together market.
Speaker 6 (16:25):
Efficiency and the dimensions of risk and portfolio selection.
Speaker 5 (16:31):
So going back all the way to Macrowitz. We've a
long known for example, the people don't like variants, they
don't like uncertainty about future liters, and they're willing to
pay something to avoid it. So they gave rise to
the chaplain and their capital so called capital asset pricing
model in which sensitivity to the market was the measure
(16:53):
of it was the measure of risk. So basically into
confusion of prices being reflect value in the study about
what are the dimensions of risk in the market. So
that's a confusion that almost everybody seems to have. So
Marcus doesn't say there aren't risk premeans in the market,
(17:13):
does not say that at all.
Speaker 4 (17:16):
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 believes talks are with
a long haul level higher return than bonds. A few
people invest all their money in stockses and doesn't mean
stocks are inefficient and efficiently priced, and just those are
the market prices. And you look at different combinations of
(17:39):
the two and they provide different distributions of outcomes, and
just find that distribution that works best for you.
Speaker 2 (17:47):
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 it 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
(18:08):
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 the theory should know that this
is going to happen and so it should already be
priced in. How has passive actually changed the market?
Speaker 4 (18:28):
Well, that's an interesting question. First off, the kind of
the impact of an index adding a new name, you know,
causing temporary prices to go up. That's a temporary effect.
It doesn't really impact the long term investor very much.
And one question that comes up a lot is, you know,
if everybody indexed, you know, then there would be no
(18:49):
price discovery. Wouldn't markets become inefficient?
Speaker 5 (18:52):
You know?
Speaker 4 (18:53):
That's kind of And my answer to that is, well,
let's take a look at it. The behavior of the
market over the last twenty years. There's been an incredible
movement to indexing over that time period, and yet there's
been an incredible increase in trading volume. You know, I
don't think of price discovery has been related to trading volume.
(19:14):
So just because there's a big movement to indexing doesn't
mean trading volume multi climb. 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
(19:38):
for or whatever it is. And I think that really
comes to what happened to the marketplace is it's kind
of to an individual instead of individual stock selection, it's
kind of like 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
(20:00):
much impact on that.
Speaker 5 (20:02):
So let me just take different direction. And people worry
that if everybody goes assive, 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 man, just people who have no special information.
If they drop out, then you need few good active
(20:25):
people to keep prices inline. So it depends on who
drops out as to whether has any effect at all
on market efficiency. And we haven't been able to discern
anything like that in the behavior of prices, But that
is the question.
Speaker 2 (20:43):
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 and P five hundred or the
MSCI World Index. And 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
(21:04):
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.
Speaker 5 (21:25):
To choose the one you want. So my own tastes
run in the direction of a total market index being
a good choice for almost everybody. So I don't go from.
Speaker 6 (21:36):
The subset things that thirty thirty down Jones that was
always kind of dumb.
Speaker 5 (21:42):
But or even five hundred, that's only five hundred. There's
a loves stucks out there.
Speaker 4 (21:48):
Then than that, let me just recall against the term passive.
You know, in my view, there's no such thing as
passive management. And you're you're touching on something right there.
You know the different index providers and how they do it,
and they'll do it differently and so forth. And you
know Standard and Poors when it wants to add stock
(22:10):
to its sm P five hundred, you know, the investment
committee sits around and talks about you know, what do
you like? You know, it's the S and P five
hundred is five hundred of the largest companies, but it's
not the five hundred 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
(22:33):
fund because you don't like stock selection, that's not the
kind of activity you want to you want to see.
Speaker 3 (22:39):
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's wanting to avoid drawdowns, et cetera.
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 you
(23:00):
know it, 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 should anyone own bonds? Because you say,
hardly anyone just own stocks, and that seems to be
objectively true. But I wonder if, like, is there reason
(23:22):
to question some of this dogma of like why, like,
if I'm not going to retire in thirty 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
(23:44):
be rethought if over the next thirty years before I
can retire twenty five years, maybe, like, if almost everyone
thinks it's certain that stocks will outperform bonds, why am
I holding bonds.
Speaker 5 (23:58):
That sense that if almost every but he thinks that's true,
But it's not true. Stucks don't get less risk. In
the long term, risk accumulates, So.
Speaker 3 (24:11):
I don't understand that. I don't understand how.
Speaker 5 (24:14):
When you retire, when you retire a period when stocks
have been particularly poorly and you will get hurt, that's
always a possibility, doesn't go away with the time.
Speaker 6 (24:26):
So the presumption is is what's incorrect? The risk is
always there, you don't get rid of it.
Speaker 2 (24:33):
What do you think about the term smart beta? And
is dimensional doing smart beta?
Speaker 5 (24:41):
Yeah, smart is a marketing term. Show me a dumb beta.
Speaker 2 (24:48):
I'm sure I could find some examples, but they certainly
wouldn't have set out to create dumb beata.
Speaker 5 (24:53):
There's a lot of Mike, there's a lot of marketing
in the financial business. That's one of them. That's one
of the big ones.
Speaker 3 (25:00):
Well, what does it mean to you? So like when
you hear that term, like, what is the person trying
to sell to me?
Speaker 5 (25:05):
Well, that have to give me an example because I
don't take it seriously. Obviously you can tell me checking here.
Speaker 4 (25:10):
Well, I think it's a Jeans research that he did
with Ken French. You know, his landmark ninety two paper
on called cross section of expected returns anyway that you know,
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 over the term
(25:33):
smart data. It's not smart, I mean, just it's just,
you know, a reflection of the research and the dimensions
of returns.
Speaker 3 (25:42):
You know, something that I'm really interested in when it
comes to markets particularly, I would say over the last
(26:04):
fifteen years since the Great Financial Crisis, small caps have
certainly not provided 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,
(26:24):
and I know people sometimes try to redefine these to
allow them to put in VideA 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 and beating earnings
expectations year after year after year. Does this pose a
(26:47):
problem for a sort of factor oriented investor. When the
fundamentals of one sector, the real fundamentals, not the stock performance,
produced these abnormal periods of profitability growth.
Speaker 5 (27:04):
Well, I don't know how I abnormal they are. So
the instance of all these dimensions of returns is that
they're risky. There is, the results are highly uncertain over
any finite period of any period of time, so they
can do poorly for long periods of time. They can
also go away. If there's too many people jump on things,
(27:25):
it can cause them to go away. So it's possible,
for example, then interest in small stocks and interest in
value stocks killd thes size and the value 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,
(27:46):
then you can see these premiums disappear. It's very difficult
to unravel the story in the data because there's.
Speaker 6 (27:53):
So much ensutancy 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 feel
them anymore.
Speaker 5 (28:08):
They jump into them if they think the returns out
are better. That's always been a possibility, Conferntion, and I
pointed that out in the initial papers we wrote on
the dimensions of risk.
Speaker 3 (28:20):
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
(28:42):
at some point get compensated for taking on these risks
into your portfolio.
Speaker 5 (28:48):
Well listen. And then the mixing and trading costs there,
So there are differential trading costs and different kinds of assets,
different transactions costs. Those are part of what you may
played play the game. In principle, it tract from the price.
Speaker 6 (29:02):
Of the prices of the stocks. But I'm not sure
about what your question was actually.
Speaker 3 (29:10):
Basically the idea that at any given point you will
be compensated for the risks of smaller, less liquid stocks.
That's not a necessarily a permanent characteristic of the market.
Speaker 5 (29:23):
Well, it was, it was always there was always a
dimension of risk, which means this volatility associated with it.
So through the historically, during the periods when on the
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, good, good return. So that's always true.
(29:44):
So there always been periods when stocks did worse than
bills through a long period of that in the thirties,
forties all the way up to the fifties. So these
are just dimensions of risk and return basically, and risk
means you.
Speaker 4 (29:58):
Can mose will point out a kind of the direction
in your head. It is 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, you know, we built
it on the idea that you ought to have large
and small cap stocks in your portfolio, not just large cap.
(30:18):
Our first clients were large institutional clients and they were
only holding the stocks of bigger companies because they were
trying to the hired managers to how guests 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
(30:40):
business or it's hard to anyway. So the thrust wasn't
so much that we guarantee your higher returns. The thrust
is you ought to have a well diversified portfolio, and
our view how to include a significant chunk of small cap.
Speaker 2 (30:56):
David you highlighted earlier the importance of data in modern
final 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 Gene's point,
you know, computers and the ability to actually track more
information and crunch it more efficiently. Nowadays, it kind of
(31:18):
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.
Speaker 4 (31:41):
Well, you know, Jeans you is the market reflects all
available information. That's kind of the implication of efficient markets,
and it was these AI programs so forth. I mean,
they have vast amounts of data, but no AI algorithm
can reflect all available information. So even though they have
(32:03):
lots of information, there's still lots to get reflected, seemingly
in stocking bond prices.
Speaker 5 (32:08):
Looking at it from the academic side, what's happened with
the coming up so many big databases that people do
lots of research, is that research and finances expanded. There
used to be just a few of us still doing
it in the sixties and seventies. Now we have big
finance departments and almost every school all with people who
(32:30):
want to do work. Most of it are work on
lots of it work on market. So where there was
well basically one journal in this in the sixties, there
was all open to this kind of stuff. Now you
have four or five of them that are all all
pretty good. No coming up with no stuff, publishing three
or four times a year. So there's been an explosion
(32:52):
of research and uses all these new data, and that's
been to the plus. I think, I really when I
and my young people, I say, boy, in the old days,
it was easy. When I was coming up, it was
like shooting fishing in barrow. Nobody was doing anything, so
everything he did was new. Now it's much more difficult,
that much more precedent about what's been done and what
(33:14):
hasn't been done.
Speaker 3 (33:15):
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 in the 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
(33:36):
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, et cetera.
When do you say, like a factor loses legitimacy. It's like,
(33:59):
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 out performing value, you say, actually,
(34:20):
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.
Speaker 5 (34:32):
Okay, So Kim French and I have always been very
sensitive so exactly this problem. So every time we did
a paper that seemed to have a new result discovering
in it, we would consciously 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 the market. So we were very sensitive
(34:55):
to the precisely issue they'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 back looking backward in the time, which is
one way of going out of sample, and looking across markets,
which is another way of going out of sample. But
(35:17):
still it's possible that the discovery of the effect causes
people to move through it to do stuff that basically
makes it go away. And it takes a long time
before you can tell.
Speaker 6 (35:30):
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.
Speaker 5 (35:39):
There's really no way to get around that.
Speaker 8 (35:41):
So we won't know what our life and my life
my life time anyway, but I meany six years old,
we won't know my lifetime whether the value bringium of
the size meanium have actually gone away, because you still
don't have enough data to come to that, to come
to that conclusion.
Speaker 4 (35:57):
Well, also, let me add one additional When the Gene
and Ken did did all his great research, they have
the data there that jumps out of here, and one
of the questions was always why would it be there?
And you can go through the algebra why low price
talks have higher average returns than high price talks. It
(36:18):
seems sensible that there would be that low price talks
might have higher expector returns because maybe because they're riskier.
Speaker 2 (36:28):
Gene, 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 nineteen seventies, and that someone
needs to come up with a new innovation, a new
(36:51):
burst forward. But you don't really know who that might be.
Do you have any sense of where people should be
look looking for the next big thing in modern finance
or modern financial theory.
Speaker 5 (37:05):
That's again 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, wrong, wrong place. Not that you shouldn't
do it, but simply this is a very difficult task.
(37:28):
So the question is excellent. The answer, it's unavoidably vague.
Speaker 3 (37:35):
Fair enough answer, there's nothing. If if a young student
came to you and said, hey, i'm looking you know
at eighty six, you might not want to dive into
something new, but there's nothing. He's like, oh, yeah, I'm
sort of curious about that. You should try to pursue
a write of paper. There's nothing that comes to mind
that sort of you would suggest a young researcher make
a stab at Well.
Speaker 5 (37:56):
The question we've started with was what's the next.
Speaker 3 (37:59):
Big Yeah, right, right, Okay.
Speaker 5 (38:01):
It changes the world. That's much more diffing.
Speaker 4 (38:05):
Sure, it's the next.
Speaker 5 (38:06):
Research wrinkle that we can do to extend that extends
the world.
Speaker 4 (38:10):
A little bit fair enough.
Speaker 5 (38:11):
That's mostly what goes on research, the small little steps
forward and sometimes little steps backwards. Stuff doesn't work out.
Speaker 2 (38:19):
Since we have gene fauma 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?
Speaker 5 (38:35):
I was wondering when you're 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
(38:56):
value can't be used as the medium of of exchange
because people won't want to deal with it. So, for example,
of business that doesn't want to do business in terms
of bitcoin because the variation in the price of bitcoin
itself can knot the company out of business. So then
the question becomes, who does want to use bitcoin? Historical
(39:19):
monetary theories I learned it it's not capable of answering
that question, so it would have predicted and I'm still
predicting that it'll bust. It it'll bust. At some point
people will say no, that's it, and they'll stop piling
piling into it, and then the market that marcro will
just disappear. But we'll see if it survives. We need
(39:39):
a whole theory to explain how and why.
Speaker 2 (39:43):
That sounds suspiciously like you're saying it's in a bubble.
Speaker 5 (39:47):
Oh I'm hoping it's in what I'm saying.
Speaker 4 (39:53):
Well, I think maybe that he's also saying that if
crypto is going to survive, because it has value right
now and it could maybe someday, you can do transactions
cheaper than they can with master cards.
Speaker 5 (40:10):
So that's that's that's a good, good point, dude. Because
there's the 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 transactions. So the question is about the methods.
The methods evolve all the time.
Speaker 6 (40:32):
So we have a central bank method now that we
use pretty much for every everything in the US, But
the blockchain is an alternative kind of mechanism.
Speaker 5 (40:43):
What you put into it can be anything it can
be can be bitcoin, or it can be dollars. Does
it didn't really matter? So those are two different things.
So people worry that a system where a central bank
manages the into transactions, which is the system we have,
(41:03):
is too open to manipulation by the government, and that
the blockchain avoids it. But then it turns out that
the blockchain is not scalable intent its complication goes up
basically exponentially as you as it handles more transactions, so
that that's not the answer to the method of exchange problem.
(41:23):
I mean, that's something people are struggling with.
Speaker 2 (41:27):
All Right, David and Gene, 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.
Speaker 4 (41:36):
Oh great, great, Thanks.
Speaker 9 (41:37):
It was really a lot of fun, Joe.
Speaker 2 (41:52):
That was really fun, Fama, especially with someone I always
wanted to speak to. I do have to say, you know,
I mentioned earlier, the way you feel about the term
prem 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
(42:13):
average return of the market. Like, does that lead anywhere?
Speaker 3 (42:17):
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, no, it's
such a depressing no.
Speaker 2 (42:30):
I think the view of human capability, I.
Speaker 3 (42:32):
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, et cetera, 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
(42:56):
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.
Speaker 2 (43:09):
Should you say that on the All Thoughts podcast?
Speaker 3 (43:11):
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 Jane's answers is
basically a recurring series of yes, it's priced in, Yes
it's priced in, and yes it's priced in. Yes it's priced in.
And so I do have this existential question about we
(43:32):
support this news organization that supports an industry, and I
talk about this stuff all the time, and then it's like.
Speaker 2 (43:39):
Why I think I'm closer to David's position on this,
where you know, 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 you know, in the cost of
your investment and things like that. I think that's a
(44:02):
reasonable middle ground. I am not sure I am an
EMH fundamentalist camp just yet, but maybe you can convince me.
Speaker 3 (44:10):
Yeah, you know, 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
(44:35):
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 could profit from.
Occasionally happens in 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
(44:56):
the assumption that the billions of dollars flowing through the
market didn't all miss something that you see as obvious.
Speaker 2 (45:03):
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.
Speaker 3 (45:13):
Yeah, right, but can you identify the people who right,
this is the problem? Like right, because yeah, and this
is why, this is why it's all these Maybe they're lucky.
Speaker 2 (45:22):
In choosing the lucky investment managers.
Speaker 4 (45:24):
How about that?
Speaker 3 (45:25):
I mean, that's right, that's like, I mean, that's like,
you know, manager selection suffers from the exact same problem
with 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
(45:46):
want to continue it. Maybe they'll be alive long enough
to say, like, oh, turns out there's no small cat
premium after all. Because Jane opened up the possibility that, yeah,
we all of finance and economics suffer is from the
tragedy of small sample sizes. Like it's like this known phenomenon,
like the world is just getting started. Maybe one day
(46:07):
it'll be like, actually, turned out that wasn't really a thing,
but they'll probably be after all of our lifetimes.
Speaker 2 (46:12):
In the long run, we're all dead. Since you mentioned it.
Speaker 3 (46:15):
In the long run, all factors, all factors are suffer
from sample bias.
Speaker 2 (46:22):
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 nineteen nineties, 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 gross stocks.
(46:44):
And you know, nowadays growth stocks are sort of an
accepted idea, but back then it was off beat and
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.
Speaker 3 (47:03):
And just on this one point, it is interesting too
that now if someone says growth stocks, you think really
big companies. Yeah, 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 like our fundamental realities of business changing, and could
(47:25):
those fundamental realities of business changing change fundamental aspects of
the stock market because we now have this era where
you have gigantic companies still putting up growth numbers that
in any time would be incredible.
Speaker 2 (47:40):
All right, shall we leave it there.
Speaker 3 (47:41):
Let's leave it there.
Speaker 2 (47:42):
This has been another episode of the All Thoughts podcast.
I'm Tracy Alloway. You can follow me at Tracy Alloway and.
Speaker 3 (47:48):
I'm Joe Wisenthal. 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 fire finance. Follow our producers Kerman Rodriguez
at Kerman armand dash Ol Bennett at Dashbot and kill
Brooks at Killebrooks. From our odd Lots content, go to
(48:08):
Bloomberg dot com slash odd lots, 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 dot gg slash od lots.
Speaker 2 (48:23):
And if you enjoy odd Lots, 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 add free. All you need to do is
find the Bloomberg channel on Apple Podcasts and follow the
(48:45):
instructions there. Thanks for listening in
Hosts And Creators
Joe Weisenthal
Tracy Alloway
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