Speaker 1: Welcome to Trillions. I'm Joel Weber and I'm Eric bel Tunis.
Speaker 1: Eric Our colleague Sam Potter recently published a story that
Speaker 1: the moment I published, we started talking about it and
Speaker 1: we wanted to bring it on to this episode. UM.
Speaker 1: What was the story and why did it cutch your attention?
Speaker 1: It was really a story about the fiftieth anniversary of
Speaker 1: the Index Fund. And a lot of people really when
Speaker 1: they think of the Index Fund, they think of Vanguard
Speaker 1: and Bogel, which launched their's I believe in seventies six.
Speaker 1: But the real birth of the fund was four or
Speaker 1: five years before that. And so the guy behind it
Speaker 1: was interviewed in Sam's story, and this is a there
Speaker 1: was a lot that was going on pre Vanguard, and
Speaker 1: I think getting at that and looking at that is
Speaker 1: really interesting. But largely, look, it's the fiftieth anniversary the
Speaker 1: Index Fund. This is an e t F show et
Speaker 1: y s would not exist if it wasn't for the
Speaker 1: Index Fund. So the Index Fund is sort of the
Speaker 1: the route which has sprung all of this, UM, all
Speaker 1: these other things, and it's been obviously taking people have
Speaker 1: taken it and run with it. So to talk to
Speaker 1: the person who is even pre vogel uh, you know,
Speaker 1: is really exciting, and we have them today. His name
Speaker 1: is mc McCown and he'll be joining us from California
Speaker 1: for this episode as well as Sam Potter from London.
Speaker 1: This time on Trillions, Meet the man who started eleven
Speaker 1: trillion dollar index Revolution, Sam mac Welcome to Trillions, Thank you,
Speaker 1: good morning, and hello from Sonoma Wine Country. Okay, Sam,
Speaker 1: can you set the stage? How did you decide that
Speaker 1: this was going to be the story that that you
Speaker 1: were going to pursue? How did I How did I
Speaker 1: find mac? Well? Um? About six months ago, so I
Speaker 1: was actually on a cool with Salim Ramsey, who's the
Speaker 1: glogle head of ice Shares at Black Crop and um.
Speaker 1: It was just an introductory called. You know, we haven't
Speaker 1: spoken before, so we were just chatting, and I was
Speaker 1: telling him that I was getting really interested in the
Speaker 1: sort of science of indexing, you know, what was what
Speaker 1: was kind of underpinning the E t F tidal wave
Speaker 1: if you like, that's coming through markets and and he
Speaker 1: and I said, I'm kind of getting into the history
Speaker 1: of it of how the how Wall three got Bill?
Speaker 1: And and I said, I'm reading Capital Ideas by by
Speaker 1: Peter Bernstein. You know the history of Wall Street. And
Speaker 1: he said, ah, well, you you must know about Matt mcclown. Then, Um,
Speaker 1: I said, I don't actually know that name. He said,
Speaker 1: he said, you must know this guy. This is this
Speaker 1: is the guy. This is where it started. And I
Speaker 1: did the obvious. I thought it was Vogel or whatever.
Speaker 1: He said, No, it's Matt. He's still around. He's in
Speaker 1: Wine Country having you know this great life. I said,
Speaker 1: I haven't seen his name in the book though, and
Speaker 1: he said keep reading. And then sure enough I was
Speaker 1: reading couple ideas like one or two weeks later, and
Speaker 1: I read this. The first wedge into this system was
Speaker 1: driven by a man with the fine Scottish name of
Speaker 1: John Andrew mcquowen. Mcquowan has a boyis mop of hair that,
Speaker 1: though now gray as white, still tumbles down over his forehead.
Speaker 1: So I thought, okay, I gotta I gotta track down Mac. Um. So, yeah,
Speaker 1: I I sort of tracking down. He's also on the
Speaker 1: board of Dimensional Fund Advisors, which of course is just
Speaker 1: getting into the TF industry now, and they helped me
Speaker 1: get ahold of Mac and he was gracious enough to
Speaker 1: do an interview and it was. It was fascinating stuff. Mac.
Speaker 1: Can you rewind the Clark fifty plus years now and
Speaker 1: tell us how did you get the idea for the
Speaker 1: index one? Well, it's the story is kind of convoluted,
Speaker 1: as as all kinds of evolutionary transformative processes seemed to
Speaker 1: be when I when I was doing graduate work at Harvard,
Speaker 1: I was Harvard Business School. I was working with a
Speaker 1: professor from from Sloan School at M I T. Who
Speaker 1: had collected a bunch of data from Barrens on common
Speaker 1: stock on Friday closes. And I was doing programming. I
Speaker 1: had been involved in programming, and I was fascinated by
Speaker 1: the parent discrepancy between the behavior of share prices over
Speaker 1: time from a normal probability distribution. You know a nice
Speaker 1: bell shaped curve. Well, it doesn't actually look like that.
Speaker 1: And fast forward about four or five years and I'm
Speaker 1: in New York and I ended up at a meeting
Speaker 1: through more serendipity at Merrill Lynch when Jim, Professor Jim Lorrie,
Speaker 1: and Professor Lawrence Fisher we're presenting there are initial findings
Speaker 1: on return on common stocks that Mary Lynch had funded.
Speaker 1: And I went up to p pressor Lori afterwards, and
Speaker 1: I asked him a question about these fat tailed distributions
Speaker 1: as they were coming to be known, and he said, WHOA, Well,
Speaker 1: we have a graduate student who knows something about that subject.
Speaker 1: That's his dissertation. His name is Gene Fama. And one
Speaker 1: thing led to another, and I went out to visit
Speaker 1: my family was to Chicago, and I ended up spending
Speaker 1: them the Monday morning after Thanksgiving of I remember vividly
Speaker 1: having a conversation with Jeane Farmer, and he introduced me
Speaker 1: to Merton Miller, and uh, all of a sudden, I
Speaker 1: realized that this is what I was suspicious of, was
Speaker 1: maybe not entirely ill founded, but it was naive relative
Speaker 1: to what Jean was actually working on. Well, one thing
Speaker 1: led to do another, and I ended up being asked
Speaker 1: by an executive at IBM to give a talk at
Speaker 1: the IBM Executive Center at San Jose, south of San
Speaker 1: Francisco in January of sixty four, and in the audience
Speaker 1: was Ransom Cook, who was the chairman of Wells Fargo.
Speaker 1: Well I went back to New York and in a
Speaker 1: few days later, a week later, I got a phone
Speaker 1: call from from Ransom Cook and he says, I would
Speaker 1: like you to come back to San Francisco and meet
Speaker 1: some of my colleagues. So of course, I took a
Speaker 1: couple of days off and went back to San Francisco,
Speaker 1: and I met a number of people, and I went
Speaker 1: back into Ransom's office. He said to me, so, how
Speaker 1: much how much money are you making in your in
Speaker 1: your job in New York? And I said six thousand
Speaker 1: dollars a year. And he said, how about I offered
Speaker 1: you a job for eighteen thousand. Would you come to
Speaker 1: work for me starting immediately? Well, you could have. You
Speaker 1: could have knocked me over with a feather. So I
Speaker 1: get back to New York and I told my wife
Speaker 1: about this, and then she's not exactly thrilled. But the
Speaker 1: long and the short of it is, I took the job,
Speaker 1: and we moved to San Francisco and we began to
Speaker 1: work on what Ransom called the investment management problem. Bear
Speaker 1: in mind that computers had just come to the four
Speaker 1: in in in major banks, and they were mostly being
Speaker 1: used for accounting purposes. That was, which is exactly what
Speaker 1: had been handled by those with green eye shades and
Speaker 1: arm bands prior. But now the costs had gone up
Speaker 1: by an order of magnitude, and Ransom said to me,
Speaker 1: I think it's about time we started looking at what's
Speaker 1: going on in the data. Well, you gotta get that
Speaker 1: he was incredibly forsightful, and the fact that I was
Speaker 1: hired by the chairman really meant that the primary operatives
Speaker 1: in the Investment Department and in the Trust department. Um
Speaker 1: really didn't have very much to say, especially since he
Speaker 1: wanted me to set up an independent group to do
Speaker 1: the work, which we did and he personally funded it.
Speaker 1: We were removed from the Wealth Fargo budgeting process and
Speaker 1: given a budget by the Chairman. Well, Um, I have
Speaker 1: to tell you. The first thing I did was go
Speaker 1: back to Chicago and have a conversation with Jane Farmer,
Speaker 1: and we began. He introduced me to Myron Scholes and
Speaker 1: Fisher Black, and I made a deal with those guys
Speaker 1: to come work on this problem. Uh. And before all
Speaker 1: of the death settled, which was several odd years later,
Speaker 1: we had had twelve different academic consultants working in various
Speaker 1: in various ways and the various aspects of this puzzle.
Speaker 1: But what's really interesting about those twelve is that today,
Speaker 1: if you look back at those twelve. Six of them
Speaker 1: have won Nobel Prizes. So there was a heady group
Speaker 1: and how that happened I don't know, but Ransom Cook
Speaker 1: and his successor, Dick Cooley funded that research effort. And
Speaker 1: the upshot was what we called market portfolios. That you
Speaker 1: you were better off with a portfolio containing every name
Speaker 1: in the market than any subset, including any index. In fact,
Speaker 1: Larry Fisher made an astute observation and he simulated every
Speaker 1: possible portfolio from the original CRISP data set, which started
Speaker 1: in and ended in nine six. And what do you
Speaker 1: noticed was the distributions were bimodal, and what differentiated the
Speaker 1: two modes with whether the portfolio contained IBM or not.
Speaker 1: So if you had missed IBM, you would have had
Speaker 1: a distinctly different investment experience if you had owned everything
Speaker 1: on the New York Stock Exchange. You mentioned the investment
Speaker 1: management problem as you described, and can you tell us
Speaker 1: a little bit more about what that issue was as
Speaker 1: you guys saw it? Well, I don't. I'll tell you, Sam,
Speaker 1: I thought about that question an awful lot of in
Speaker 1: over the years, for various reasons. But I can I
Speaker 1: can kind of give you my synoptic view of the
Speaker 1: investment management problem. Ransom didn't like the way UH this
Speaker 1: the investment management process was working at the bank. He
Speaker 1: was suspicious of the way portfolios were being constructed, just
Speaker 1: pure intuition. Let me give you a specific example. Wells
Speaker 1: was just getting into the trust UH advisory business for
Speaker 1: pension funds at the time, and the largest client they had,
Speaker 1: whose name I remember vividly and will not identify, had
Speaker 1: a pension fund of about a half a billion dollars
Speaker 1: and it was invested in twenty five names. And his
Speaker 1: intuition was, and he wouldn't have stated it quite this way,
Speaker 1: but that that part was under diversified. Well that would
Speaker 1: go down as the understatement of the month. And he
Speaker 1: and he couldn't get an answer out of the investment
Speaker 1: department that satisfied him. And that is exactly why he
Speaker 1: went it was invited to and went to this conference
Speaker 1: that IBM had put on about down in San Josey
Speaker 1: about bringing analytical procedures to databases, and so it just
Speaker 1: it just was an outcropping of his intuition. Well, of
Speaker 1: course he was exactly right, as you work through all
Speaker 1: of this stuff that we were doing in those days.
Speaker 1: The one thing that struck me and a lot of
Speaker 1: us as just how representative of the New York Stock
Speaker 1: Exchange is or isn't. So we discovered that NICO had
Speaker 1: collected a bunch of data on Japan East first section
Speaker 1: of the Tokyo Exchange, and Wells Fargo used this relationship
Speaker 1: to NICO, actually too the Industrial Bank of Japan who
Speaker 1: had in turn and introduced me to NICO, and we
Speaker 1: got an opportunity to run some tests on the NICO data.
Speaker 1: And basically what we found was the same thing, which
Speaker 1: is the best portfolio with the portfolio that contained all names,
Speaker 1: same exact algorithms, same assumptions, same everything. So talk about
Speaker 1: an out of sample experience that's about as distant from
Speaker 1: from sample bias as you can get. So anyway, that
Speaker 1: is kind of the base and we call it from
Speaker 1: which what we called, as I said, we called the
Speaker 1: market market funds. And we began to look at the
Speaker 1: SPS just and remember the SNP didn't actually exist until
Speaker 1: somewhere around nineteen fifty seven or fifty six, or fifties
Speaker 1: seven or eight or nine somewhere there. Prior to that,
Speaker 1: there were variations that SMP had but the five itself,
Speaker 1: I think originated in the early in the mid fifties,
Speaker 1: and then they went back and and and back assembled
Speaker 1: the data to recalculate the SMP five hundred back I
Speaker 1: forget how far, quite a few decades, several decades, four
Speaker 1: or five decades. So while they were doing that, we
Speaker 1: got to know the SMP people and what was the
Speaker 1: basis upon which they chose the five stocks. And that
Speaker 1: made a lot of us pretty suspicious because instead of
Speaker 1: having a random sample or some kind of like the
Speaker 1: doll thirty index, which is pretty subjective as well, the
Speaker 1: investment committee at SMP was choosing the five hundred, So
Speaker 1: we were kind of right back in the same puzzled.
Speaker 1: But in any event, the S and P five hundred
Speaker 1: was becoming the benchmark by which people were judging portfolios.
Speaker 1: So it was perfectly obvious that the thing you should
Speaker 1: do is just offer the SMP five hundred at a
Speaker 1: price about a quarter of what they were selling investment
Speaker 1: management for at the time, which was by way about
Speaker 1: about a hundred basis points versus. And of course now
Speaker 1: that is down to five or whatever it is. But
Speaker 1: the point of the matter is what was clear to
Speaker 1: us that I think pretty much at the beginning was
Speaker 1: that the more names you had in the portfolio, the better.
Speaker 1: And we were instrumental also in getting the beginning of
Speaker 1: data collected for the American Exchange and also the OTC market,
Speaker 1: which became NASDAC. You mentioned the s and you a
Speaker 1: portfolio that s and pole of hundreds of way to go,
Speaker 1: but that that wasn't the first fund, wasn't. That wasn't
Speaker 1: what you did with the very first one. Can you
Speaker 1: tell us a bit about the construction of that one? Well,
Speaker 1: the first the first fund was actually the the All
Speaker 1: New York Fund, which was about six hundred names. But
Speaker 1: we made the mistake initially of equal weighting the portfolio
Speaker 1: in our simulations, and it became apparent right away that
Speaker 1: there was something wrong with that. And of course what
Speaker 1: happened was we realized that it needed to be market
Speaker 1: capitalization weighted, not equal weighted, because of course, what happened
Speaker 1: when you equal way of portfolio like that as you
Speaker 1: overwake the riskiest stocks. So the market cap weights were
Speaker 1: became all of a sudden the unambiguous preference for those
Speaker 1: kinds of portfolios. But it was not the SMP. It
Speaker 1: was the All New York I have a question, so,
Speaker 1: and I like asking this about people who were right
Speaker 1: there and at the option moment, when you locked into
Speaker 1: that moment where you're like, the more stocks the better,
Speaker 1: the diversified portfolio is better, which is obviously the inception
Speaker 1: moment of what would be the index fund. Did you
Speaker 1: know is a big idea at the time or was
Speaker 1: it just another you know, part of your day and
Speaker 1: you had your mind on other things like how much
Speaker 1: did you identify the legs this idea had? Well, I
Speaker 1: can tell I can tell you right now I did
Speaker 1: not have my mind on anything else. That I promise
Speaker 1: you my work week and those in those days was
Speaker 1: about eighty hours and you know, and and the Wealth
Speaker 1: Fargo people, to their credit realize that. And you know,
Speaker 1: within a very short time, my my wages went from
Speaker 1: eighteen thousand to forty So I was by far the
Speaker 1: highest paid, uh young vice president at well Fargo Bank.
Speaker 1: And I was the reason I I got away with it.
Speaker 1: It was because the chairman approved it. But if you
Speaker 1: don't think I wasn't conscious of the fact that we
Speaker 1: had uncovered something serious that I was, all of us were.
Speaker 1: I don't mean to say that I was alone by
Speaker 1: no means. I mean Myron and Fisher and and we
Speaker 1: we had a lot of We had a lot of
Speaker 1: influence from Jack Trayner, who was a very important thinker
Speaker 1: about this topic in the beginning. Uh. And the more
Speaker 1: we had conversations with various academics, including people from M I. T.
Speaker 1: And and Berkeley and Stanford and so forth, the more
Speaker 1: academic interest was surfaced. And I think that while the
Speaker 1: Chicago guys were leading the crowd, and especially Jeane Parma
Speaker 1: and Larry Fisher and Jim Laurie and and and the
Speaker 1: godfather I think was really Merton Miller. You have to
Speaker 1: give him probably the seminal original credit for the analytical
Speaker 1: foundation that just the Chicago School was based on. But
Speaker 1: when you got right down to it, uh, this was
Speaker 1: still with the influence of computers and data and it's
Speaker 1: very nascent years. Remember I'm very fond of pointing out
Speaker 1: that the first stock traded was that was the India East.
Speaker 1: It was the East India Company. It was traded on
Speaker 1: the on the fledgling Amsterdam Exchange in sixteen o two.
Speaker 1: And it wasn't until nineteen that we had an algorithm
Speaker 1: for measuring risk adjusted performance. So for three d and
Speaker 1: sixty six years people were constructing portfolios with no fee
Speaker 1: back loops. Yeah, I think, you know, we take a
Speaker 1: lot of that for granted, for sure. And I guess
Speaker 1: I would say, Okay, so you have this big idea.
Speaker 1: You know it's a good idea. Can you talk about
Speaker 1: how you tried to implement it and the first funds
Speaker 1: and and you know how it went to try to
Speaker 1: get to actually put money into in indexing. Well again,
Speaker 1: you know, all I would say is serendipity rears its
Speaker 1: proverbial head, all right. Keith Schwaider it was a graduate
Speaker 1: of the Graduate School of Business from Chicago and his
Speaker 1: family owned Sampson I in Denver, and Jim Laurie and
Speaker 1: introduced me to Keith, and he came to San Francisco
Speaker 1: and we had company. We had discussions about this and immediately, uh,
Speaker 1: he wanted to see some of the samson I pension
Speaker 1: fund invested in and what we did call an index fund.
Speaker 1: So we we we kind of invented an index fund
Speaker 1: that would would work. And that was the first one. Well.
Speaker 1: Immediately thereafter, or very close to immediately there after, the
Speaker 1: the Wells Fargo Pension Fund. We had a big shot
Speaker 1: of capital put into Remember this is a commingled trust
Speaker 1: now it's not a registered mutual fund. But the long
Speaker 1: and the short of it is, it became apparent very
Speaker 1: soon that we needed broader, diversified portfolios. And because of
Speaker 1: SMP five was such a popular a referent, it became
Speaker 1: apparent that that was one of the places to go.
Speaker 1: And of course it wasn't long thereafter until we had
Speaker 1: an opportunity to meet Jack Bogel and and and he
Speaker 1: was interested in and he was already interested for his
Speaker 1: own reasons and the idea of what amounted to an
Speaker 1: index fund. I'm not sure he called it that. In fact,
Speaker 1: I'm not sure anybody did. But I got introduced to
Speaker 1: Jack Bogel by a former SEC commissioner who I had
Speaker 1: met at the University of Chicago's Center for Research and
Speaker 1: Securities Prices that LORI engineered. Shortly after the the you know,
Speaker 1: the security that Center for Security Research and Securities Prices,
Speaker 1: the christ Data came into existence. He created this bi
Speaker 1: annual seminar twice a year seminar. It had about thirty
Speaker 1: different major financial institutions attending, and and and that that
Speaker 1: Pow Wow two Day, Powell Spring and Fall. I went
Speaker 1: to the very first one, which was in sixty four,
Speaker 1: and I went to everyone until I left well Fargo,
Speaker 1: and they invited me back on several occasions uh thereafter.
Speaker 1: So I was not only through my my period that
Speaker 1: through seventy four as well, but pretty close to n
Speaker 1: I was still going to the CRISP Seminar. Well, that's
Speaker 1: where all this stuff was being discussed. First National Bank
Speaker 1: of Chicago, JP, Morgan, Chase, you know, all the major
Speaker 1: names in banking. They were all members of the CRISP Seminar.
Speaker 1: And we're listening to all this stuff going on. Well,
Speaker 1: so this, this this influence that that index Funds was
Speaker 1: beginning to have, wasn't was not limited to Wells Fargo
Speaker 1: by any stretch of the imagination. And a quick quick question.
Speaker 1: You mentioned meeting Bogel. Were you still in the early
Speaker 1: early seventies here or is this more towards I was
Speaker 1: around seventy four. I'm going to say, Okay, so did
Speaker 1: he come to you. That's after he left Wellington, which
Speaker 1: was an active fund he was it was it was
Speaker 1: during okay, it was during the formation of Gotcha it's
Speaker 1: interesting um that obviously was a huge situation UM where
Speaker 1: Bogol was basically fired by the people he had acquired it. Uh.
Speaker 1: When he was running Wellington's he was an advocate of
Speaker 1: active funds to a degree. Then he starts Vanguard as
Speaker 1: a back office company. The index fund just is a
Speaker 1: is a way for him to not manage money while
Speaker 1: managing money. It was kind of an interesting loophole. My
Speaker 1: question to you is, as you saw a Vanguard come
Speaker 1: out with this unique mutual ownership structure and then they
Speaker 1: go and get the index fund, how did you see that? Like,
Speaker 1: because the mutual ownership structure I think probably deserves a
Speaker 1: lot of credit for constantly lowering the fees of the
Speaker 1: index funds over the years, But how did you see
Speaker 1: the potential of Vanguard or only on as well? Well, Eric,
Speaker 1: you put your finger on one of my hot buttons.
Speaker 1: Let me tell you what actually happened at Wills Fargo.
Speaker 1: We got registered at the SEC what was called the
Speaker 1: Stagecoach Fund. But in June, the Supreme Court came down
Speaker 1: in a decision of the Investment Company Institute versus the
Speaker 1: Controller of the Currency As giving permission to City Bank
Speaker 1: to sell commingled mutual funds being a violation of Glass Stiegel.
Speaker 1: Remember Glass Steagle separated investment banks from commercial banks. We
Speaker 1: were ready to sell the Stagecoach fund in in Ransom
Speaker 1: Cooks Branches, and it got shot down by that Supreme
Speaker 1: Court decision. I see I v. Camp Descent June. Look
Speaker 1: it up. The banks could sell co mingled trusts, but
Speaker 1: they could not sell registered mutual funds. They were securities,
Speaker 1: not loans, and not trusts. Remember the idiocy emerging from
Speaker 1: Congress created those laws. They did not know what they
Speaker 1: were doing, and I guess I would say as usual.
Speaker 1: So you basically were unable to really capitalize and commercialize
Speaker 1: on the idea because of that ruling in law and
Speaker 1: that when when I met Jack Bogel and told Ransom
Speaker 1: and Dick what Jack wanted to do, he said, give
Speaker 1: him Allery's Our research were restricted. We can't do it,
Speaker 1: but it needs to get done. You can read in
Speaker 1: Jack's writings too, he he gave us credit for it.
Speaker 1: Did you and Jack exchange Christmas cards from therefore? Yeah?
Speaker 1: I mean I had a very personal relationship with Jack.
Speaker 1: We weren't really very close, remember we were we were
Speaker 1: oceans apart or not like what a continent apart. I
Speaker 1: mean I saw him fairly often. And before Jack died,
Speaker 1: you know, we got the the CMME Award. I can't
Speaker 1: even think when that was for innovation in corporate finance.
Speaker 1: So mac h Wells Fargo was limited in in the
Speaker 1: way it could deploy this, and obviously Jack benefit immensely
Speaker 1: from that. But I think we should also note that
Speaker 1: um Wells Fargo did, did capitalize on on it, and
Speaker 1: had an incredible legacy because what you built, what you
Speaker 1: started at Wells eventually became Barkley's Global Investors, if I'm right,
Speaker 1: and that Lawrence Stye Shares, which was then brought by
Speaker 1: black Rock. So um, it was an incredible it was
Speaker 1: the beginning of an incredible uh kind of achievement. Well
Speaker 1: that's right. I mean, you know, we created well for
Speaker 1: our investment advisors to be the advisor to the Stagecoach Fund.
Speaker 1: That was the original plan before I see I V
Speaker 1: Camp came down. Ah and as a matter of fact,
Speaker 1: Coolly made me the chairman of of w f I
Speaker 1: A and we hired an independent guy to become the CEO.
Speaker 1: Came from outside the bank and uh, and we were
Speaker 1: all we were all literally we were literally ready to
Speaker 1: go to market when I see I V camp came
Speaker 1: down and I remember June one, like I was yesterday,
Speaker 1: we were on the on the cost of doing that. Mac.
Speaker 1: I have a question related to that time. How what
Speaker 1: was the computing speed and prowess like at that time,
Speaker 1: because obviously I'm I'm guessing these machines were huge. How
Speaker 1: what was it like to feed data into that? And
Speaker 1: how long were you waiting to get the feedback? I mean,
Speaker 1: your feedback loop was one thing, but like you know,
Speaker 1: this was state at the state of the art at
Speaker 1: the one at the time. Right. Well, you're that's something
Speaker 1: very very good question, Joel, because well, you know, another
Speaker 1: another innovation that was just coming to the four in
Speaker 1: those days was what we call time sharing. Well, time
Speaker 1: sharing was the idea that you could hook up a
Speaker 1: bunch of different as it were, teletype machine to a
Speaker 1: single computer and the computer could multiplex the input and
Speaker 1: output from a teletype machine to a computer. And the
Speaker 1: IBM three six seven was the first from commercial scale
Speaker 1: computer of that kind. And well farther we were just
Speaker 1: adopting three sixties at the time, and I convinced coolly
Speaker 1: to let us buy a sixty seven and so that
Speaker 1: we could have a terminal, actually two terminals in the
Speaker 1: Management Sciences department. And the reason he went for it
Speaker 1: was that he another group at the bank we're working
Speaker 1: on the idea of an automated teller terminal, and it
Speaker 1: became apparent that we could utilize we could have teller
Speaker 1: terminals that were being multiplexed by the same kind of
Speaker 1: a computer where when you went into the bank to
Speaker 1: cash your check, you could actually in real time discover
Speaker 1: whether or not there was a balance into your account.
Speaker 1: So there was there was a movement in the direction
Speaker 1: of what I call remote computing. And we had we
Speaker 1: the Management Science department had access to that three sixty
Speaker 1: six seven immediately upon them when it came out, and
Speaker 1: that was about nine sixties six or six seven, something
Speaker 1: like that. So we had gone from having to fuss
Speaker 1: around at an IBM data center h to having our
Speaker 1: own U teletype machine with access to the data that
Speaker 1: we stored on the three seven. So that was another
Speaker 1: very critical thing that that addict Cooley did was introduced
Speaker 1: time sharing or multiplexing, right terminal multiplexing into the picture.
Speaker 1: And that was about the same time so all of
Speaker 1: a sudden, the productivity of of these guys doing analytical
Speaker 1: work skyrocketed because you didn't have to go stand in
Speaker 1: the front of a computer and feed punch cards into it.
Speaker 1: The long and the short of it is, it was
Speaker 1: concurrent that that occurred. And again I would characterize that
Speaker 1: as yet more serendipity. You know, you said earlier you
Speaker 1: worked with what was it six people who went on
Speaker 1: in one Nobel Prizes um And I mean just you were,
Speaker 1: you know, a pioneer effectively right and working with a
Speaker 1: ton of smart people. And I'm just wondering, like, for
Speaker 1: those of us who get to, you know, you know,
Speaker 1: look back on your story, what do you feel like
Speaker 1: the keys of that of good collaboration were. Well, that's
Speaker 1: a that's a very that's a very interesting question, Joel.
Speaker 1: I mean, we spend the rest of the day on
Speaker 1: that question. A. H. Well, you need to have a
Speaker 1: certain openness. At the same time, you have a very
Speaker 1: critical mind, and you're you're and you're willing to challenge anything.
Speaker 1: I would characterize it as the Chicago school at work.
Speaker 1: I mean, I think that you know, Milton Freeman was
Speaker 1: a champion of that point and several others before him,
Speaker 1: including fa Hiak and so forth. But you know, really
Speaker 1: critical thinking and and economics was generally missing. And tell
Speaker 1: about that same time. Now. When I say in economics,
Speaker 1: I'm referring to predominantly macro economics and not micro econ comics.
Speaker 1: But critical thinking kind of came to both and with
Speaker 1: the onset of the computer and the database, and prior
Speaker 1: to that there was an awful lot of I regard Kenes,
Speaker 1: for example, as gibberish. It just it doesn't make any
Speaker 1: sense when you put the blade to it. It doesn't
Speaker 1: stand the test. That just wasn't available until considerably later.
Speaker 1: I guess it was like a perfect storm in that period,
Speaker 1: and it was influencing all kinds of things, index funds
Speaker 1: being only one. So can you apply that that critical
Speaker 1: thinking to the current moment? Oh well, I'm not a
Speaker 1: very big fan of um, I'm not a very big
Speaker 1: out of Let me call it h on grounded meaning
Speaker 1: without data analysis. I just I can't characterize it as
Speaker 1: subjectivism versus data driven science, and the world is a
Speaker 1: wash in subjectivism and data. Data driven science is only
Speaker 1: beginning to invade the hallowed halls of subjectivism and and
Speaker 1: of course politics is the is the epicenter of subjective
Speaker 1: is along with religion. And I can't tell the difference
Speaker 1: between politics and religion, but Matt can. Matt, what about
Speaker 1: for the investment industry, for the state of indexing now
Speaker 1: with you know, eleven trillion or whatever we are at now? Um,
Speaker 1: when look at that, now, what's your sort of critical
Speaker 1: thought crisis? Well, Sam, you know, eleven trillion is a
Speaker 1: major understatement, right, because that's only the admitted indexing. Just
Speaker 1: think about the closet indexing. There's a lot of incentive
Speaker 1: to keep fees high, and the way to do that
Speaker 1: is to do an index fund. But call it something else,
Speaker 1: or let me put it another way to do a
Speaker 1: market portfolio. Right, it's not necessarily an inda, but there's
Speaker 1: a you know, closet passive is everywhere. I would my
Speaker 1: guess is at least two thirds of the market is
Speaker 1: passive and maybe maybe maybe more like But it would
Speaker 1: be very difficult to put a number to that because
Speaker 1: you have to collect an off lot of data. But
Speaker 1: it's eleven trillion is an understatement by a lot. Um,
Speaker 1: let me jump in here with that whole premise, because um,
Speaker 1: eleven trillion is the public fund that's quote passive, but
Speaker 1: some of that is in smart data where they took
Speaker 1: the index fund and they put active metrics and overlays
Speaker 1: and on the flip. You're right, there's a bunch of
Speaker 1: active discretionary funds that basically hold the S and p UM.
Speaker 1: So it's very blurry, which is my answer to people
Speaker 1: when they say, oh my god, passive is taking over.
Speaker 1: It's going to ruin the stock market. We're all going
Speaker 1: to die, which is this sort of fear of But
Speaker 1: I'm like, it's so nuanced and gray between active and
Speaker 1: passive it just doesn't bother me. But I guess I
Speaker 1: would like to get your take on some of the
Speaker 1: people who fear that passive is growing too big and
Speaker 1: is distorting fundamentals could result in some kind of a
Speaker 1: market structure issue. They don't they just don't understand the situation.
Speaker 1: Eric Com, I'm right back to my basic point. It's
Speaker 1: subjectivism versus data driven science. When you when you allow
Speaker 1: the data to speak to you, that clears up that fog. Remember,
Speaker 1: share prices get formed because people are buying and selling shares. Right,
Speaker 1: if buying and selling shares stopped, I don't know what
Speaker 1: you would have for prices. You wouldn't have any prices.
Speaker 1: But do you think buying and selling is going to stop?
Speaker 1: I mean, it's and it's not because somebody thinks they
Speaker 1: know more than the market does. There's a whole lot
Speaker 1: of reasons why people buy and sell, and some of
Speaker 1: it is valuation related, and some of it is liquidity related,
Speaker 1: and some of it is a trust account related, and
Speaker 1: I mean it's just there's an impossible assortment of motives
Speaker 1: behind people buying and selling shares, and that's just that's
Speaker 1: just never gonna stop. I mean, I'm never worried about
Speaker 1: that one. And just generally the e t F Right,
Speaker 1: so you've got index funds were launched. Bogel popularized them
Speaker 1: with Vanguard. He was not a fan of e t F.
Speaker 1: He he wanted people to stick in the long term.
Speaker 1: E t F s come out, they trade, some of
Speaker 1: them are used in place of futures. What's your take
Speaker 1: on the e t F world? And did you ever
Speaker 1: meet Nate Most and Steve Blueman am X when they
Speaker 1: were coming up with their E t F for spy host? Yeah? Sure,
Speaker 1: you've got to remember what on E t F his
Speaker 1: Remember what preceded, You remember closed down the mutual funds,
Speaker 1: and then there was opened end mutual funds, and you
Speaker 1: t F is just an amalgam of those two things, right,
Speaker 1: And we were talking about e t F way before
Speaker 1: they existed. It Again, it's it's right back to foolishness
Speaker 1: in Congress of trying to distinguish between closed end funds
Speaker 1: and opened end funds. It was protocols that were put
Speaker 1: in place by regulation, not not by economics. So you
Speaker 1: you could have an e t F that was closed
Speaker 1: and would be called a closed end fund, and you
Speaker 1: could have a conventional mutual fund that was that is
Speaker 1: open ended, whose shares were traded in a competitive market,
Speaker 1: that would be an e t F. Right, there's just
Speaker 1: there's nothing novel and new about an e t F.
Speaker 1: It's just a it's an amalgam of opened and closed funds.
Speaker 1: We should have had him a long long time ago.
Speaker 1: We we talked about that idea going way back. We
Speaker 1: talked about that idea to the commissioners at the SEC.
Speaker 1: And again I'm the ex commissioner whose name I'm not
Speaker 1: going to use because I haven't seen him in years,
Speaker 1: and I don't even know whether he's alive, but he
Speaker 1: was a champion of thinking through new things, even though
Speaker 1: in his days as a commissioner of the SEC that
Speaker 1: was the last thing that they were doing. They weren't thinking,
Speaker 1: they were just regulating. There's a distinction, Mac, I want
Speaker 1: to ask before we we finish, Presumably you're invested in
Speaker 1: index funds. I imagine, Oh, yes, indeed we are. Are
Speaker 1: you like, are you like a by the total market
Speaker 1: fund kind of guy or do you sort of have
Speaker 1: maybe more index funds that you specialize at all or customize. Well,
Speaker 1: if you take all the different kinds of index funds
Speaker 1: and put them in a portfoli you get a market port.
Speaker 1: So your port you're a very simple portfolio, you know
Speaker 1: kind of investor. Okay, yeah, well I'm an entrepreneur. Most
Speaker 1: of my wealth is involved in startup companies. Right. Well
Speaker 1: that actually I had a really question which was, um,
Speaker 1: you know, Sam in the article reminded me that you
Speaker 1: were a mechanical engineer by training and I'm by by schooling,
Speaker 1: Just wondering how how do you think that informs your
Speaker 1: your outlook? I mean, obviously you're you made a really
Speaker 1: clear point on being you know, praising objectivity and data
Speaker 1: above all else. But like talked about talk to us
Speaker 1: about how you look at the world through the lens
Speaker 1: of a being a mechanical engineer. I grew up on
Speaker 1: a farm. I split my early life between my mother
Speaker 1: and father. My father was a businessman. We lived in
Speaker 1: the edge of this little town, and his elder brother
Speaker 1: rand the family farming operation, which was seven miles away.
Speaker 1: So I ended up growing up in two families uh
Speaker 1: one uh in literally in the country where we were.
Speaker 1: We were growing all kinds of grains and lagoons and
Speaker 1: so forth, of feed, the whole assortment of livestock right.
Speaker 1: And I've I've been often asked what because I'm very
Speaker 1: fond of my early life on the farm, And I'm
Speaker 1: often asked what did you learn and when you are
Speaker 1: on the farm? And I have evolved a good answer
Speaker 1: to that question. I learned that you can't bullshit the
Speaker 1: bull It does not work. And if you get into
Speaker 1: the world of data, it's the same point if the
Speaker 1: data doesn't if it's not in the data, it's not
Speaker 1: there now, mind you. Teasing conclusions out of big data
Speaker 1: sets is a complicated topic, and of course I began
Speaker 1: to do just exactly that when I was in an
Speaker 1: engineering student. And remember that was when computers first began,
Speaker 1: So I started programming computers when I was still an
Speaker 1: engineering student. I mean, I mean, don't don't ask me
Speaker 1: why because I have no idea. That's just the way
Speaker 1: it was. Um. The last question we always ask gun trillions.
Speaker 1: Really curious what you're gonna say? Um, what is your
Speaker 1: favorite each you have ticker? Well, uh, I have a
Speaker 1: good answer to that. None, I have to tell you,
Speaker 1: I think um. Jack Bogel had a very similar response. Now,
Speaker 1: Vogel's response was, because you know, he wasn't a fan
Speaker 1: of ets, was c r z y, which isn't a ticker,
Speaker 1: but it's what he thinks of them. You guys are
Speaker 1: similar in that in that answer with not really giving one.
Speaker 1: Mac Sam, thanks so much for joining us in trillion.
Speaker 1: My pleasure, You guys, thanks for listening to Trillions until
Speaker 1: next time. You can find us on the Bloomberg terminal,
Speaker 1: Bloomberg dot com, Apple Podcasts, Spotify, and wherever else you
Speaker 1: like to listen. We'd love to hear from you. We're
Speaker 1: on Twitter. I'm at Joel Webber Show. He's at Eric Faltunus,
Speaker 1: and you can find Sam at Sam J. Potter. This
Speaker 1: episode of Trillions was produced by Magnus Hendrickson. Francesca Levy
Speaker 1: is the head of the Homeberk podcast VI