Speaker 1: This is Master's in Business with Barry Ridholts on Bloomberg
Speaker 1: Radio this weekend on the podcast Wow, what a what
Speaker 1: a delightful conversation I had with Roger Ibbotson. If you
Speaker 1: don't know who he is, well you need to become
Speaker 1: a little more familiar with financial histories. He is one
Speaker 1: of the founding fathers about modern thoughts on on asset allocation,
Speaker 1: portfolio management, valuation factor UM. Go down the list of
Speaker 1: a million things. He really was instrumental in the development
Speaker 1: and expansion of CRISP, which is the giant stock database
Speaker 1: UM originally out of the University of Chicago, Ibbotson associates.
Speaker 1: He's on the board of advisors at Dimensional Funds. His
Speaker 1: curriculum vitae is his pages and pages long. He was
Speaker 1: extremely generous with his time and shared all sorts of
Speaker 1: oscinating things with us. If you are at all a
Speaker 1: stock market wank, if you're at all interested in why
Speaker 1: some stocks go up and others don't, then you're going
Speaker 1: to find this conversation to be absolutely fascinating. So, with
Speaker 1: no further ado, my conversation with Yale Universities Roger Ibbotson
Speaker 1: this week I have an extra special guest. His name
Speaker 1: is Roger Ibbotson. He is a professor at the Yale
Speaker 1: School of Management, where he is Professor of Practice Emeritus
Speaker 1: of Finance. He is also the founder and chairman of
Speaker 1: Ibbertson Associates, which was sold not too long ago to
Speaker 1: Morning Star. He is on the board of directors of
Speaker 1: Dimensional Fund Advisors. He is the chairman and CEO of
Speaker 1: Zebra Capital Management uh an equity investment and hedge fund manager.
Speaker 1: He has also taught for many years and served as
Speaker 1: executive director for the Center for Research and Security Prices
Speaker 1: better known as CRISP. He's the author of numerous books,
Speaker 1: including Investment Markets, Gaining the Performance Advantage and Global Investing,
Speaker 1: The Professionals Guide to the World of Capital Markets. Roger Ibbotson,
Speaker 1: Welcome to Bloomberg. Great to be here. I've been looking
Speaker 1: forward to having this conversation with you for a long
Speaker 1: long time. I've certainly been familiar with Ibbotson Associates since
Speaker 1: you founded them back in nine But let's go back
Speaker 1: to your days when you got your PhD from Chicago.
Speaker 1: What was the state of the world in finance, like
Speaker 1: when when you first entered the markets, Well, you know,
Speaker 1: it was really things were happening at the University of Chicago,
Speaker 1: and ultimately many of the people there got Nobel prizes.
Speaker 1: But what went on So, but if you just take
Speaker 1: take us back a few years before that, uh, finance
Speaker 1: really hadn't developed as a as an academic step tacos
Speaker 1: security analyst or how to pick a stock or something
Speaker 1: like that. And then and then we started really developing
Speaker 1: a whole theory of how finance works. And I gotta
Speaker 1: say I had I had great people to work with. Their.
Speaker 1: My chairman of my committee when I wrote my dissertation
Speaker 1: was Eugene Fama. He want to know about prize. I
Speaker 1: had him my committee. Uh, Martin Miller, he wanted to
Speaker 1: know about prize. Myron Shows want to know about prize.
Speaker 1: Fischer Black he you know, you have to be alive
Speaker 1: to win a know about prize. And unfortunately he died
Speaker 1: before that, but he certainly would have. So it was
Speaker 1: really a tremendous group to people to work with. That's
Speaker 1: a Yankees murderous row of Nobel laureates there. Yes, uh so, yeah,
Speaker 1: it was. It was a wonderful time going on. So
Speaker 1: actually all the so many different discoveries were taking place
Speaker 1: you mentioned that the study of finance really hadn't developed,
Speaker 1: um academically as as much as it has since. Tell
Speaker 1: us about the Center for Research in Security Prices for CRISP.
Speaker 1: How did that come about and what was your involvement?
Speaker 1: So the Center for Research and Security Prices we called
Speaker 1: CRISP c RSP. Well, CRISP was really set up by
Speaker 1: James Lourie and Larry Fisher, and they were collecting data
Speaker 1: on on the stock market returns. And their data started
Speaker 1: in and now you see a lot of things started in.
Speaker 1: So they were collecting this data and um, that's what
Speaker 1: started the center. Uh. And I gotta say, um, they
Speaker 1: once they published this data, uh, they never kept it
Speaker 1: quite up to date. But once they published it was
Speaker 1: people were so interested because they had no idea what
Speaker 1: actually had happened in the stock market. They didn't actually
Speaker 1: have any sense for how stock market returns were like.
Speaker 1: In fact, they kind of remember the thirties and how
Speaker 1: terrible it was and so forth, and they knew things
Speaker 1: were better lately, but but they still didn't really aized
Speaker 1: the high returns and actually had happened in the stock market.
Speaker 1: That's quite fascinating. So when you say this was not
Speaker 1: much of an academic study. Are you really referring to
Speaker 1: the fact that previous to the creation of CRISP, there
Speaker 1: wasn't a whole lot of data that could be analyzed,
Speaker 1: at least not consistent data in a in anything approaching
Speaker 1: a um well structured way. Yeah, Chris really put the
Speaker 1: data on the map. And then and when I got
Speaker 1: my phdre the PhD there. But I actually stayed on
Speaker 1: as a professor, and and when I stayed on, I
Speaker 1: became the executive director of CRISP. So I wasn't, I guess,
Speaker 1: helping to put the data together. And uh, it was
Speaker 1: really not only the University of Chicago that was using
Speaker 1: that data, but all the other universities were really using
Speaker 1: that data. So this suddenly, suddenly finance became an empirical
Speaker 1: subject that people people could study. That's the word I
Speaker 1: was hunting for. It had no empiricism previous. This was
Speaker 1: what years did you begin with CRISP. Well, I I
Speaker 1: got there as a student in nineteen sixty eight and
Speaker 1: became a faculty member in nineteen seventy four, and I
Speaker 1: guess I became executive director. I don't remember a few
Speaker 1: years after that of the center. But I was always
Speaker 1: involved with Chris from the start because I was always
Speaker 1: interested in data. And in fact, um, well I got
Speaker 1: a I got a job while I was getting my
Speaker 1: PhD in the investment office of the university, and I
Speaker 1: came out the endowment right right. I was a consultant
Speaker 1: to the office and one of the things they asked
Speaker 1: me as a consultant was what do we do with
Speaker 1: his bond portfolio? And I said, well, I can manage that,
Speaker 1: And so they actually has a PhD student. I was
Speaker 1: actually managing the University of Chicago bond portfolio. And how
Speaker 1: large was that at the time, Well, these numbers were
Speaker 1: not large in today's time to take a couple of
Speaker 1: a couple of hundred million, you know, but still a
Speaker 1: PhD student is like, okay, congratulations, you're running a few
Speaker 1: hundred million dollars. That's out nothing, especially in the late sixties. Yeah,
Speaker 1: it was. It was a great thing to do. And
Speaker 1: and and it gets back to what you were talking
Speaker 1: about when people. Once I was running the bond portfolio,
Speaker 1: people would ask me when are Fisher and Lorie are
Speaker 1: gonna update their study? Because first the first day that
Speaker 1: came out and went from to nineteen sixty, and then
Speaker 1: it was the nineteen to nineteen sixty five and then
Speaker 1: nineteen but this was seventy to seventy three, and people
Speaker 1: were asking when we want to see the updated data,
Speaker 1: and I would ask. I would ask Larry Fisher when
Speaker 1: it's gonna get updated, and Larry would give me a date,
Speaker 1: but the date would go by and it wouldn't get done.
Speaker 1: And and so this is when I really took the
Speaker 1: ball by our hands, and I worked with Rex Sinkfield,
Speaker 1: who was a student of mine at the time, and
Speaker 1: we decided to put this put data that literally all
Speaker 1: the UM we used a certainly to the Center for
Speaker 1: Research for but we put some quicker data together to
Speaker 1: get a sense of what something up to date actually
Speaker 1: and and we brought it up to date actually through
Speaker 1: seventy six at the time. So that brings us to
Speaker 1: which not coincidentally, is when you launch Ibbanson Associates, tell
Speaker 1: us about what motivated you to go out and hang
Speaker 1: your own Shingle well West stock spons bills in inflation.
Speaker 1: I was an assistant professor and we're just we had
Speaker 1: just published stock spons Bills and inflation um first as
Speaker 1: a couple of journal articles and what one which was
Speaker 1: on the past and want to actually predicted the future,
Speaker 1: UM long term, but then also as a monograph from
Speaker 1: the cf A Institute. And every everybody was so interested that,
Speaker 1: UM I was. I was getting inundated with letters coming
Speaker 1: in CEOs asking me for information and and response of
Speaker 1: this this question and that question. And and I was
Speaker 1: at A. I barely had a secretary. I had a
Speaker 1: part of a secretary. And I didn't know what to
Speaker 1: do with all these letters from the c I O S,
Speaker 1: c E O S and c I os and and
Speaker 1: so forth. So I started hiring a couple of people
Speaker 1: to help me out with this. And that's what that's
Speaker 1: what it caused me to actually started ivots and Associates.
Speaker 1: I had plenty of business at the start because somebody
Speaker 1: people were actually requesting things from me. You sold Davidson Associates,
Speaker 1: UH and Advisers to morning Star back in two thousand
Speaker 1: and six, pretty good timing before the tide went out
Speaker 1: in O eight oh nine. Um, what was that process? Like,
Speaker 1: they're a pretty big shop, morning Star. How did that
Speaker 1: transaction go? Well? In two thousand and six. By that time,
Speaker 1: I was already at Yale Yale School of Management as
Speaker 1: a professor in practice there. But in two thousand and six, uh,
Speaker 1: the UM we had a hundred and fifty people and
Speaker 1: invots and associates with offices in Chicago, New York and Tokyo.
Speaker 1: Actually um, but still we were very small compared to
Speaker 1: morning Star also in Chicago, right, don't they They They
Speaker 1: were very far. They were just we were like two
Speaker 1: firms that were somewhat similar that were only a couple
Speaker 1: of blocks away from each other. That that's a pretty
Speaker 1: natural fit that the large morning Star will acquire the
Speaker 1: smaller Ibbotson in the same hometown. Actually, I gotta say
Speaker 1: that we we were around first because I remember when
Speaker 1: Joe Mansueto and then I in eighties but came to
Speaker 1: a few of our UM holiday parties and things like that,
Speaker 1: and um. But he but I gotta say, you have
Speaker 1: to give Joe Massuado credit. Morning Star really took off
Speaker 1: and grew. We were growing fast too, but nothing like
Speaker 1: they were. You focused on data about markets generally. They
Speaker 1: focused specifically on mutual funds, and that became a giant
Speaker 1: growth area for them, especially with the Ariskle laws in
Speaker 1: four oh one K coming up in in the early seventies. Well,
Speaker 1: everybody was in the arrested was more um yeah, four
Speaker 1: one case really started developing in the really in nineteenes.
Speaker 1: First it was those defined men define benefit pension plans,
Speaker 1: the dB plans, and uh we worked with them to
Speaker 1: something stanton. But Marty Sarra actually picked the retail end
Speaker 1: of it with a four OK market and the mutual
Speaker 1: funds yes and so um. But we were too very
Speaker 1: fast growing firms that were alongside each other for a
Speaker 1: couple of decades in Chicago before they actually brought us out.
Speaker 1: Quite intriguing. Uh, let's talk a little bit about CRISP
Speaker 1: and and we mentioned earlier you worked on the nineteen
Speaker 1: twenty six to present database of of stock market returns,
Speaker 1: but not too long ago a new historical database was
Speaker 1: added for the New York Stock Exchange, going back to
Speaker 1: eighteen fifteen, straight up to the original sixth date. What
Speaker 1: did you learn from that database about equity returns and
Speaker 1: about volatility? Well, you know, first of all, we uh
Speaker 1: we had to collect hand collect all that data back
Speaker 1: to UM. What do you mean hand collect? Well, it
Speaker 1: was it was in the Yale Bayneke Library where you
Speaker 1: had a look at micro fich and old newspapers of
Speaker 1: the New York Shipping and Commercial Chronicle, and it was
Speaker 1: mostly about which ships are coming in to the harbor,
Speaker 1: but they also listed to New York stock market prices. So,
Speaker 1: so how do you error check that to make sure
Speaker 1: that nobody makes a transcription error? That sounds like, you know,
Speaker 1: a century of data. It's really easy to make a
Speaker 1: mistake with that. Well it it is, uh, And I'm
Speaker 1: not saying there's no possible mistakes in there because it
Speaker 1: had to be hand collected. But there aren't that many
Speaker 1: companies in the early days either. So if we're not
Speaker 1: talking about the the three thousand stock that we might
Speaker 1: be talking about today, we're talking about, you know, less
Speaker 1: less than a hundred stocks over most of this period.
Speaker 1: Quite quite fascinating. Um, so what did you learn about
Speaker 1: equity returns and volatility? Well, you know that data in
Speaker 1: the nineteen eighteen nineties eight hundreds was kind of unusual
Speaker 1: because stocks tending to be issued around a hundred. It
Speaker 1: almost looked like you were looking at bond data because
Speaker 1: everything is trading at par or a little above. Well, yeah,
Speaker 1: they were trading. They may trade in the range of
Speaker 1: fifty to two hundreds or something, but they kind of
Speaker 1: looked like bonds, and we had to keep on investigating
Speaker 1: further and further to find out where are these these
Speaker 1: These are stocks, aren't they? You know? And they were,
Speaker 1: of course stocks, but they but they looked like bonds.
Speaker 1: They weren't that volatile. They weren't. Of course, the trading
Speaker 1: wasn't anything like the trading not a lot of volume
Speaker 1: and trade by appointment only or did they actually that
Speaker 1: was on the there was the the course of button
Speaker 1: uh button would agreement, you know, they were traded on
Speaker 1: on the curb and then uh then eventually inside. But
Speaker 1: so they were continuously traded but not uh and and
Speaker 1: and even the volume wasn't even recorded at that time,
Speaker 1: you know, but we did get the last prices. That's
Speaker 1: quite fascinating. So, you know, CRISP is very often associated
Speaker 1: with factor based investing and equity risk premium UM. What
Speaker 1: can you tell us about that? What What do we
Speaker 1: know today about the equity ris premium that we didn't
Speaker 1: know in the pre CRISP days back in UH The
Speaker 1: theory was developing in the nineteen sixties, especially with the
Speaker 1: UH and the nineteen fifties and sixties we had the
Speaker 1: Harry Marco Wits came out with his portfolio theory in
Speaker 1: in NFT two. It was at the University of Chicago. Actually,
Speaker 1: and I gotta say it's kind of interesting because at
Speaker 1: the first I didn't even Milton Freedman was reluctant to
Speaker 1: give Harry Marco it's a PhD for this because he
Speaker 1: wasn't sure this was economics. Okay, so you you've just
Speaker 1: lowered my estimation to Milton Freeman a notch. How do
Speaker 1: you not, Well, my hindsight biases Harry Marco. It's of
Speaker 1: course you give him a PhD. But I guess that's
Speaker 1: just hindsight bias, isn't it. Yeah, well, of course, now,
Speaker 1: of course Harry has a Nobel Prize too, and so so.
Speaker 1: And then we had the Capital Esta pricing models coming
Speaker 1: along and in the ve with Bill Sharp and and
Speaker 1: John Lettner and by the way, Harry Mark WIT's until
Speaker 1: Sharp there's still around today. We can talk to them,
Speaker 1: and so sure Sharp is out in um northern California.
Speaker 1: And where's Mark Wits these days? He's in southern southern California.
Speaker 1: So at the University of Chicago, when you get an
Speaker 1: office as a faculty member. Do they give you like
Speaker 1: a key to the office and a Nobel prize? How
Speaker 1: does that work? Everybody in that faculty has that. That's
Speaker 1: a lot of jewelry in that in that uh faculty department. Well, actually,
Speaker 1: Bill Sharp wasn't ever at the university see Chicago, So um,
Speaker 1: not every Nobel Prize went to the University of Chicago. People.
Speaker 1: But you've you've named seven or eight of not counting bills,
Speaker 1: if you've gone through a whole bunch of them. Um,
Speaker 1: what was it like working with that crew? That is
Speaker 1: some amazing list of advisors. Well, we did know, we
Speaker 1: did recognize that things were going on, that this was
Speaker 1: this was a special place. We we could see that.
Speaker 1: I mean, it wasn't like we were surprised afterwards or something.
Speaker 1: I guess we're surprised about the Nobel Prizes perhaps, but
Speaker 1: we weren't surprised that we were the center of thought
Speaker 1: leadership at that time. And and uh, one of the
Speaker 1: things we were theoretically understanding is risk premiums. So not
Speaker 1: not only in the stock byer where there's an equity
Speaker 1: ris primum, but also in the bottom market where there's
Speaker 1: an interest rate or I and risk premium that long
Speaker 1: bonds have higher yields and short bonds, and and then
Speaker 1: there's a default premium, the fact that that if you
Speaker 1: buy lower grade bonds, they tend to have higher certain
Speaker 1: higher yields, but even higher returns and higher grade bonds.
Speaker 1: So you had all these different, uh, different risk premiums.
Speaker 1: And that's what caused me to put this stocks, bonds, bills,
Speaker 1: and inflation together, this data because it was really the
Speaker 1: purpose of seeing what are what were the historical payoffs
Speaker 1: of stocks versus bonds, stocks versus treasury bills, bonds versus
Speaker 1: treasury bills, Treasury bills versus inflation, uh, the bonds that
Speaker 1: could default versus treasury bonds. All these things were risk premiums.
Speaker 1: And the purpose originally was to measure these risk premiums
Speaker 1: and see how they had done historically because we had
Speaker 1: the theory, yes, and it did that. Of course, they
Speaker 1: had great payoffs. And and that's part of the reason
Speaker 1: why it became so well known so fast, because everybody
Speaker 1: could now see the numbers of the kinds of things
Speaker 1: that we kind of knew were there, but we hadn't
Speaker 1: seen the numbers. You could quantify risk and apply it
Speaker 1: to future expected returns. Well, that's the other thing. These
Speaker 1: were historical, but we were other paper we had, uh,
Speaker 1: this is with Ibbotson and sink Field. The other paper
Speaker 1: we had back in nineteen was a projection of what
Speaker 1: would happen and how how you could go out the
Speaker 1: next twenty five years using the last fifty years to
Speaker 1: extrapolate out into the next twenty five years. And we're
Speaker 1: not literally just extrapolating just the pure numbers, but we're
Speaker 1: extrapolating the wrist premiums. And those wrist premiums were extrapolated
Speaker 1: out to come up with these forecasts, which actually turned
Speaker 1: out to be almost on the money forecasting what would
Speaker 1: happen and by the year two thousand, so, of those
Speaker 1: four stocks, bonds, bills, and inflation, which do you find
Speaker 1: is the easiest to forecast? And which is the hardest? Well,
Speaker 1: the easiest, well, the hardest to forecast is always the
Speaker 1: stock market because there's so much volatility, there's so much noise.
Speaker 1: It's a scary place to be. That's why it has
Speaker 1: that equity risky And and what which is the easiest
Speaker 1: to forecast? Actually it would be the UM I would
Speaker 1: say in a derivative form, it would be the real
Speaker 1: kind of the real interest rate, the difference between inflation
Speaker 1: and treasury bills. But of course treasury bills, treasure bills
Speaker 1: are mostly moving. Uh, the yields are and and bond
Speaker 1: yields in general are mostly higher or lower because of
Speaker 1: the expected inflation. So when you're in high inflationary periods,
Speaker 1: you have high bond yields, and when you're in low
Speaker 1: inflationary periods, you have low bond yields. Like we have
Speaker 1: very low bond yields today, but we have very low inflation.
Speaker 1: So a very large part of a body yield is
Speaker 1: the expected inflation. And so uh, if you we know
Speaker 1: at every point in time what the inflation is, and
Speaker 1: that's usually a pretty good indication of what the expected
Speaker 1: inflation is going to be. As you go further out,
Speaker 1: you can you can't forecast it quite as well, but
Speaker 1: at least in the near term, have a pretty good
Speaker 1: idea of what expected inflation will be, and and therefore
Speaker 1: you have a pretty good idea of what what what
Speaker 1: these yields and bonds are going to be. So you're
Speaker 1: the perfect person to ask a question about that. We've
Speaker 1: been debating internally in the office is and back and
Speaker 1: forth as too. Should stocks have a higher valuation these
Speaker 1: days for a variety of reasons. But I'm gonna ask
Speaker 1: it um differently. It costs nothing to trade today, It's
Speaker 1: practically free. You could buy mutual funds or ETFs for
Speaker 1: practically nothing. When you look at the historical returns and
Speaker 1: let's call equity with dividends reinvested um, you're paying a
Speaker 1: lot more for a portfolio. You're paying more for transactions.
Speaker 1: This was go back before discount brokerage. It was not
Speaker 1: cheap to buy yourself something. How does that figure into
Speaker 1: historical returns or on? In a large enough portfolio, even
Speaker 1: those higher prices aren't all that relevant. Well, it may
Speaker 1: mean that the valuations should be higher because because the
Speaker 1: trading costs are not as high anything. That's and I've
Speaker 1: certainly studied liquidity. Risk is one one big consideration, but
Speaker 1: liquidity is probably the second most important. Yes, the more
Speaker 1: liquid something is, the more valuable it is. The less liquid,
Speaker 1: the less valuable it is. And but but the counter
Speaker 1: this course is that that something that's less liquid might
Speaker 1: have a lower valuation but a higher expected return. Very
Speaker 1: very very interest them. So you are currently a professor
Speaker 1: at Yale. You spent time at the University of Chicago.
Speaker 1: Let's talk a little bit about academia and the real world.
Speaker 1: And you've moved pretty comfortably back and forth between the two.
Speaker 1: What is the difference between how ideas get applied in
Speaker 1: the business world. I probably shouldn't call it the real world,
Speaker 1: but the business world versus the scholarly application of ideas
Speaker 1: UM at a place like Chicago or Yale. Well, you know,
Speaker 1: there used to be a big gap of time. I
Speaker 1: remember like studying, as an example, duration on bonds, where
Speaker 1: the devoted duration was developed around and and I. And
Speaker 1: I was managing a bond portfolio for the University of
Speaker 1: Chicago at the time, and and um I was using duration,
Speaker 1: and I could figure out with duration, you could figure
Speaker 1: out easily in your head how much if yield changed,
Speaker 1: how's the price of a bond would change? And but
Speaker 1: nobody knew that in the nineteen seventies, Yes, and and
Speaker 1: I gave a talk on that, I remember, and and
Speaker 1: it drew a large crowd. But it wasn't new new material.
Speaker 1: It was merely uh stating something that was known, I
Speaker 1: guess academically, but not known in the business world of
Speaker 1: the real world, and so giant arbitrage opportunities. We're talking
Speaker 1: about thirty forty years of delay before something kind of
Speaker 1: caught on. And even though it's a very simple concept.
Speaker 1: So uh, I think that that time though, has dramatically shrunk.
Speaker 1: Now there is a connection, UM, all my life, I
Speaker 1: guess I've been trying to break that connection down. In fact,
Speaker 1: the title I have you've read these long titles that
Speaker 1: I have at at Yale University as a professor in
Speaker 1: in the Practice of Finance. Uh, that is a that
Speaker 1: is a title that actually is is a professor rank
Speaker 1: but not not tenured. But it allows me to have
Speaker 1: business activities on the side. And so ordinarily your constraint
Speaker 1: as a professor, you can't do a lot of business
Speaker 1: activities on the side, but with this title I can,
Speaker 1: and and I guess I in the end, I'd not tenured,
Speaker 1: so I don't go to the committee meetings, and as
Speaker 1: many as many as the committee meetings anyway, I still
Speaker 1: have to go. So you're you're identifying that effectively that
Speaker 1: bonds are misspriced relative to changes in interest rates. Was
Speaker 1: there an investment opportunity to to um arbitrage those prices
Speaker 1: relative to where they're supposed to be. This was a
Speaker 1: course in the nineteen seventies, so not not today. I
Speaker 1: don't think you find these kind of possibilities, but you
Speaker 1: did find distortions in in the nineteen seventies, and so
Speaker 1: it was one of the things I did. Now, of course,
Speaker 1: the bond market is dramatically changed, much more efficient than
Speaker 1: it was back then, and all the markets have become
Speaker 1: much more efficient since they were back then, because when
Speaker 1: something has discovered, it gets the financial literature is not
Speaker 1: something that just academics rate, it's something that that the
Speaker 1: business world reads. And so now there are things are
Speaker 1: almost immediately implemented. There's I don't know what the leg
Speaker 1: would be between. It wouldn't even be five years, uh
Speaker 1: between what's discovered and was actually goes into practice. Ed
Speaker 1: Thorpe wrote about um the arbitrage opportunity between equities and warrants,
Speaker 1: and nobody was tracking them. There was a joint gap,
Speaker 1: and that also took a good couple of years before
Speaker 1: everybody else got on. And for a while it was
Speaker 1: easy money. And then that arbitrage went away, and it
Speaker 1: particularly went away with the black shows options model which
Speaker 1: could price everything very accurately, from warrants to options to
Speaker 1: any derivative relative to the underlying Yes, and and I
Speaker 1: you know, I wasn't in at the University of Chicago
Speaker 1: with Fisher Black and Myron Shows there right after they
Speaker 1: developed it, and and before they published it. I said
Speaker 1: to them, why don't Yes, and I suggested that, And
Speaker 1: actually I had, I had actually bought a seat on
Speaker 1: the cbo E had a seat on cbo E. And I, um,
Speaker 1: I didn't go down there myself to trade, I said,
Speaker 1: a trader down there, But but I wanted I was
Speaker 1: trading at it. So I was trading on that, uh
Speaker 1: for a while, using their model, using their model after
Speaker 1: it was published. It didn't matter that it was published,
Speaker 1: because at first the Black Shows model, with all its
Speaker 1: long normal distributions and continuous time, was complicated enough that
Speaker 1: you could hand it out on a piece of paper
Speaker 1: to people nobody would get it right. But what did happen, uh,
Speaker 1: not long after I started trading these was people figured
Speaker 1: it out well more than that Black and So's Fisher
Speaker 1: Black Um put it up in the members lounge of
Speaker 1: the a computer system in the cbo E. So my
Speaker 1: game was over. Well, let's talk a little bit about
Speaker 1: your game and in the real world as opposed to
Speaker 1: or in the asset management world, as opposed to the
Speaker 1: theoretical academic world. Maybe that's a better way to describe it.
Speaker 1: Your chairman and chief investment officer of Zebra Capital Management,
Speaker 1: what do you do with Zebra? What sort of strategies
Speaker 1: do you invest in? And how do you take the
Speaker 1: academic theories that you work on and apply it to
Speaker 1: actual management of assets and capital. We have a new monograph.
Speaker 1: I have a new monograph with the c f A
Speaker 1: Institute at UM. It's called Popularity, a Bridge between Classical
Speaker 1: and Behavioral Finance. And this this monograph is co authored
Speaker 1: with Tom Azerich and Paul Kaplan and James Song. They
Speaker 1: are all three authors from morning Star and myself. But
Speaker 1: it's on popularity and really popularity is the main concept,
Speaker 1: the principle that we manage the money at Zebra Capital. Popularity.
Speaker 1: It comes down to something you can kind of easily understand.
Speaker 1: And of course you can get a copy of the monograph.
Speaker 1: It's not expensive. You can buy it on Amazon for
Speaker 1: twenty two dollars I think, and you can get it
Speaker 1: downloaded for free. I think the I c f A institute.
Speaker 1: So see if they institute dot org here it is
Speaker 1: perhaps you have to be a member. I have to
Speaker 1: be a um A see if a member in some
Speaker 1: form to to get the access to it. But it's
Speaker 1: free for the members membership anyway. So so when you
Speaker 1: talk about popularity, what does that mean in actual tone
Speaker 1: arms of of investment? How do you apply popularity to
Speaker 1: deploying capital? So a anything that is popular tends to
Speaker 1: have a higher price. Anything that is unpopular tends to
Speaker 1: have a lower price. So I think of two two
Speaker 1: assets that have the same cash flows, but one of
Speaker 1: them is popular, that will be more expensive than one
Speaker 1: that's unpopular. That's right. So are you long the unpopular,
Speaker 1: short the popular or how do you how do you
Speaker 1: do that trade? You're ready, You're ready to go here? Okay,
Speaker 1: it makes sense. So it's a hedge position, and you're
Speaker 1: even if they both go up, the theory is the
Speaker 1: cheaper one will go up more than the expensive one
Speaker 1: UM or vice versa. If they both go down, the
Speaker 1: cheaper one will go down less than the expensive one.
Speaker 1: UM And you do this across how many different asset classes?
Speaker 1: Is just equities not no bonds, no bills. At Zaber Capital,
Speaker 1: we just do it with equities. But the concept applies
Speaker 1: to anything, and and and and it's really getting to
Speaker 1: people to think differently about capital markets because, for example,
Speaker 1: in the capitalistic pricing model, it's systematic risk or beta
Speaker 1: risk that's that's unpopular. And therefore any any stock that
Speaker 1: has high systematic risk high beta risk is supposed to
Speaker 1: have a higher expected return according to the capitalized pricing model.
Speaker 1: But I sense you disagree with that. I don't necessarily
Speaker 1: disagree with that. But that's only one aspect of popularity.
Speaker 1: Risk is unpopular. But there are a lot of other
Speaker 1: things that are popular or unpopular, and one of them
Speaker 1: we've already talked about um I talked about in an
Speaker 1: earlier episode. Here we I talked about liquidity. Yes, so
Speaker 1: liquidity is popular. Pay do you pay a premium for
Speaker 1: more liquid stocks than in liquid stocks, or said differently,
Speaker 1: do you get a discount for in liquid stocks? Yes?
Speaker 1: And and of course it's also obviously true in other markets,
Speaker 1: and you can see it more directly in the bond market,
Speaker 1: for example, or at the most extreme case, think of
Speaker 1: the treasury yield. There's an on the run treasury yield
Speaker 1: where you buy the most liquid liquid security with a
Speaker 1: certain maturity, and then there's an off the run and
Speaker 1: there's a there's a spread out between those of ten
Speaker 1: or twenty basis points between the on the run and
Speaker 1: the off the run yields. So it's just a matter
Speaker 1: of one being more liquid than the other. And we're
Speaker 1: not talking about much difference here. The on the run
Speaker 1: things maybe trading every minute, every few seconds, even whereas
Speaker 1: the off the run might be trading every few minutes.
Speaker 1: You know, but even small amounts of liquidity might might
Speaker 1: make differences in how you get into differences of expected return.
Speaker 1: So is that one element of the thinking that goes
Speaker 1: into the portfolio or do you similarly create paired trades
Speaker 1: with the liquid versus in the liquid stock you're buying
Speaker 1: something at a discount and pit and shorting something at
Speaker 1: a premium. And I don't want to ask you to
Speaker 1: give away all your secrets, but I'm trying to get
Speaker 1: a handle on on how you use these different aspects
Speaker 1: of popularity. Well, they're not paired because we're just a
Speaker 1: whole bundle of UH stocks on alongside that are that
Speaker 1: are less popular and UH how bundle of another stocks
Speaker 1: of stocks that are more popular. But there are many
Speaker 1: different dimensions to be popular. We've already mentioned too, and
Speaker 1: that's the capitalist surprise. Amodel really focused on that first one,
Speaker 1: risk and and the whole financial literature has so much
Speaker 1: focused on risk UM too much focus well, perhaps because
Speaker 1: there are other aspects of things that are popular and unpopular.
Speaker 1: So we mentioned valuation, we mentioned capem, we mentioned liquidly.
Speaker 1: What other elements UM do you consider when when looking
Speaker 1: at your popular this is unpopular. Let's not hold pairs
Speaker 1: but pools of lungs and shorts. So the monograph that
Speaker 1: we're talking about says popularity a bridge between classical and
Speaker 1: behavioral finance. So some of the behavioral factors come up also,
Speaker 1: how do they apply? So let me give you one
Speaker 1: more though classical. I guess if I had a name
Speaker 1: three major the three big classical UH considerations. One of
Speaker 1: them misrisk and it might be systematic, but it can
Speaker 1: have all different dimensions of different types of risk. Another
Speaker 1: one is liquidity. Another one is taxation. Some securities are
Speaker 1: tax differently than others, so different tax treatments between different
Speaker 1: types of UM passed through holdings. What is the third one,
Speaker 1: tax treatment. At the most extreme you can see it
Speaker 1: with if you want to see it directly, would be
Speaker 1: compare a municipal bond to say a corporate bond of
Speaker 1: the same default and maturity characteristics. The municipal bond is
Speaker 1: going to have a lower yield, but it's going to
Speaker 1: have that's because it's popular. It has better tax treatment.
Speaker 1: MLPs are treated differently than regular equities according to the taxman,
Speaker 1: and that changes how you perceive them in the overall portfolio.
Speaker 1: Similar Tommuni bonds, which were also treated differently. A lower
Speaker 1: yield effectively net of taxes, turns out to be comparable
Speaker 1: to a non municipal bond. So things that are unpopular
Speaker 1: like MLPs are gonna be priced more attractively quite quite fascinating.
Speaker 1: So that's just on the on the classical side. But
Speaker 1: then you have the behavioral side. And on the behavioral
Speaker 1: side you have things like one of the things we
Speaker 1: tested in this monograph were brands uh brand value the companies,
Speaker 1: and there are there's different ranking systems of how valuable
Speaker 1: different bands are, but the companies that have the highest
Speaker 1: brand value, you might imagine those are the companies you
Speaker 1: would like in your portfolio, right, No, it would be
Speaker 1: the opposite. I know where you're going. I'm cheating because
Speaker 1: I know where you're going. But perfect example in in
Speaker 1: the beginning of the year, Apple was one of the
Speaker 1: time it was either one or two in the brand
Speaker 1: ranking down since then. And I don't know how far
Speaker 1: down the list of unpopular brands you go. Um, but
Speaker 1: I would imagine there's a line that in the sand
Speaker 1: where you say, on a list of five hundred, below
Speaker 1: this number, these unpopular brands start to become attractive. So
Speaker 1: first question on that is where is that line? How
Speaker 1: how unpopular is something you have to get before it
Speaker 1: becomes attractive. It's always relative. I mean you wouldn't you
Speaker 1: want to short the most popular names, uh, the most
Speaker 1: popular brands and and really the unpopular brands. You don't
Speaker 1: have to go after the brands that are in some
Speaker 1: sort of scandal or anything. But I meanly, most these
Speaker 1: brands you've never heard of, you know, they're not they're
Speaker 1: not well known brands. So not ge that's run into
Speaker 1: hard times, but some entity that just seems to have
Speaker 1: fallen out of favor, yes, or just or just overlooked.
Speaker 1: Things that are overlooked the stocks that are overlooked around
Speaker 1: popular stocks that are in the news all the time
Speaker 1: are the popular stocks, sure now, um and and the
Speaker 1: value effect is related to this because, uh stocks, you know,
Speaker 1: value over the long term outperforms growth. But the value companies,
Speaker 1: when you look at those things, those are not great companies,
Speaker 1: whereas the growth companies are the companies that are really
Speaker 1: much more exciting, much better companies. But there's a difference
Speaker 1: between buying a great company and buying a great stock.
Speaker 1: The great stocks are not the great companies the great stocks.
Speaker 1: In fact, it's easier to fix a company that has
Speaker 1: something wrong with that than to improve a company that's
Speaker 1: everything is going great but just isn't popular. Well, well,
Speaker 1: the ones that are great, they're they're too popular. That's
Speaker 1: their problems. So give us one more behavioral measure to
Speaker 1: consider with popularity. Well, another one we measured was reputation value. Well,
Speaker 1: I'll give you another one that's a little more different.
Speaker 1: Is tail risk. Any any stock that has actually gone
Speaker 1: through a h a tail event, a negative event that's
Speaker 1: called in its history recent history, last five ten years. Uh.
Speaker 1: So let's talk about BP and the Gulf of Mexico.
Speaker 1: We're Boeing and the seven thirty seven max. Uh, those
Speaker 1: are kind of tail events. What does that tell you
Speaker 1: about how you would expect the stock to do going forward?
Speaker 1: Are they is a stock like Boeing post seven seven
Speaker 1: issue become attractive because of that tail event? It can
Speaker 1: and not necessarily the next month or so, But people
Speaker 1: are going to remember that tale for a long time.
Speaker 1: They're gonna remember that bad event, and and it's gonna
Speaker 1: be the reputation is somewhat permanently damaged. Uh. But what
Speaker 1: we have actually studied this uh with one of my
Speaker 1: co authors that I named James Schong here or we
Speaker 1: looked at tail risk and it turns out that future
Speaker 1: tail risk is not so related to past tail events. Huh.
Speaker 1: That's interesting. So it's something really went wrong, say Boeing.
Speaker 1: They eventually fix it and get back on track with
Speaker 1: a lower reputation, but they're not necessarily prone to have
Speaker 1: another tail event. Quite fascinating. We were talking earlier about
Speaker 1: the difference between academia and real world application of ideas
Speaker 1: into actual investments and trades. How often you come across
Speaker 1: an idea that looks great on paper but just doesn't work.
Speaker 1: Can't be implemented UM in a real portfolio. The problem
Speaker 1: with real portfolios is, as they have a lot of trading,
Speaker 1: they may have trading costs. A lot of the very
Speaker 1: best ideas have high trading costs, and and most of
Speaker 1: us are not in a position to actually implement these
Speaker 1: and get rid of rid of those trading costs. There's
Speaker 1: another another problem, though, and that is that the kinds
Speaker 1: of things that have worked in the past, you look
Speaker 1: at it, you do some back testing, and you discover
Speaker 1: things in the past. Uh, those sorts of things, once
Speaker 1: they're discovered and known, tend to be heavily invested in
Speaker 1: get popular actually, and once they get popular, they get
Speaker 1: priced out out of the out of contention, and and
Speaker 1: they don't have the same sort of payoffs. So so
Speaker 1: it's uh no longer as easy to translate all these
Speaker 1: ideas that come out of academics and actually make a
Speaker 1: lot of money from them. Quite quite interesting. Um. One
Speaker 1: of the big topics these days is index funds and
Speaker 1: the move away from active towards passive. Where do you
Speaker 1: find yourself in terms of Some people seem to think
Speaker 1: the flow into index funds is distorting the market, or
Speaker 1: at least hurting price discovery. What are we index in
Speaker 1: the US? What's the impact of that? The I don't
Speaker 1: actually think it's hurting markets. Actually, the index has come
Speaker 1: in so many different forms. You can buy a whole
Speaker 1: index on say the Russell three thousand or the SP five.
Speaker 1: But you can also buy indexes in different forms and
Speaker 1: e t fs and and even mutual funds on by
Speaker 1: a specific industry, or by value stocks, or by small
Speaker 1: cap stocks, or buy a particular type of stock. So
Speaker 1: it's if it's really taking you're actually taking a bat
Speaker 1: when you actually buy that type of stock. If you
Speaker 1: if you thought, for example, that that oil or energy
Speaker 1: was going to do poorly in the future. In the
Speaker 1: old days, you'd have to how do I translate under
Speaker 1: which stocks to avoid and so forth. It's much easier
Speaker 1: to express the trade today, Yes, and that makes it
Speaker 1: markets more efficient because if we can target our opinions
Speaker 1: into a trade directly, rather than trying to mix it
Speaker 1: in with some stocks that that are really noisy and
Speaker 1: not so related to that trade. Uh, it makes it
Speaker 1: very hard to accomplish. So one of the things I
Speaker 1: keep hearing from you is it was much easier back then.
Speaker 1: It's more efficient today. Is this part of the reason
Speaker 1: why so many active managers seem to be unable to
Speaker 1: keep up with their benchmark? Have the markets become that efficient?
Speaker 1: By definition? Though, the market is a zero sum game
Speaker 1: before costs, in the sense that if if you're going
Speaker 1: to beat the market, I have to do worse than
Speaker 1: the market, or we have to sum up to the
Speaker 1: market collectively, and that's before costs, and after costs, Uh,
Speaker 1: we're gonna on average do a little bit worse than
Speaker 1: the market. So this isn't really efficient capital markets. This
Speaker 1: is just a mathematical identity. It's called a zero sum game,
Speaker 1: and in this case the zero relative sum game because
Speaker 1: it's relative to the market, so we could we never
Speaker 1: could collectively on average beat the market. We always had
Speaker 1: to have most of us, um actually do a little
Speaker 1: bit worse than the market about average. So it's not
Speaker 1: like Lake Wobegone, where um, all the children are above average.
Speaker 1: It doesn't work that way. Well, that's that's a good analogy,
Speaker 1: because that's what keeps the market going. We all think
Speaker 1: we're above average, and if we often this is behavioral course.
Speaker 1: But but if we all think we're above average, then
Speaker 1: then of course we can We're all willing to play
Speaker 1: the game, even though some of us are clearly not
Speaker 1: above average, and by definition all of us can be
Speaker 1: above average. My my favorite question, anytime I'm at a
Speaker 1: conference and presenting somewhere, I always ask a room full
Speaker 1: of people, how many of you are above average? Drivers?
Speaker 1: Just about every hand in the room goes up, and
Speaker 1: my response is always, I've been on the road with you, folks,
Speaker 1: some of you are wrong, because clearly we can all
Speaker 1: be above average. So let's talk a little bit about um.
Speaker 1: What What was discussed in Forward Thinker, which was something
Speaker 1: you wrote for Wealth Manager back in December eight You
Speaker 1: talked about the financial system being restructured UH following the
Speaker 1: financial crisis. Have we sufficiently restructured the system to avoid
Speaker 1: the next crisis? Or did we simply restructured enough to
Speaker 1: avoid a repeat of the last crisis. It would be
Speaker 1: mostly a repeat of the last crisis. Restructuring primarily involves
Speaker 1: having UH less leverage and and and actually we're also
Speaker 1: worried about counterparty risk. And of course some of that
Speaker 1: counterparty risk has been been fixed. We're getting more leverage
Speaker 1: back into the system probably now. Truly it's creeping back
Speaker 1: in Yeah, so I don't. I don't see these were
Speaker 1: as any permanent fixes. And of course anytime you regulate markets,
Speaker 1: you also add a lot of incumbrances to the way
Speaker 1: to the way the markets work. So it's both good
Speaker 1: and bad here that it's um where I don't see
Speaker 1: a uh, financial crisis coming soon. Most recessions, by the way, um,
Speaker 1: most drops in the market are not really a financial
Speaker 1: crisis crisis. But the one in two thousand and eight
Speaker 1: was like like the tech public crash in in two
Speaker 1: thousands or two thousand and two. Financial crisis wasn't to
Speaker 1: do with finance. It's just technology, right right, Speaking of behavior,
Speaker 1: excess sentiment had gotten so enthusiastic, people decided evaluation doesn't matter.
Speaker 1: You could pay any price for these things nifty fifty
Speaker 1: like it will all work out, except when eventually doesn't.
Speaker 1: So clearly not a financial crisis. Seven. How do you
Speaker 1: describe that not a financial crisis, really a plumbing and
Speaker 1: structural issue. Well, it was a financial crisis, it's just
Speaker 1: that it only lasted about a week, so not much.
Speaker 1: That's not much of a crisis. And I think back
Speaker 1: to seventy four, so just a deep recession not a
Speaker 1: financial crisis. The fifties predate me, but when you read
Speaker 1: the history books those late fifties early sixties recessions, they
Speaker 1: don't seem like you have to go all the way
Speaker 1: back to what ninety nine for a previous financial crisis.
Speaker 1: Nineties were financial crisis. So we had the big one,
Speaker 1: then we had the smaller one, and are the limited
Speaker 1: one in seven and we had a potentially severe financial crisis,
Speaker 1: said oh eight, and we got through it, which was um,
Speaker 1: very fortunate, but it was the potential financial real breakdown
Speaker 1: of financial markets. So that leads to the next question.
Speaker 1: People have been some people, especially people on the bond
Speaker 1: side of the universe, have been very critical about how
Speaker 1: the FED intervened in the markets, and they've continued to
Speaker 1: be critical about low rates being as low as they've been,
Speaker 1: causing risk assets to rise. What are your thoughts on
Speaker 1: the job the FED did during the financial crisis, and um,
Speaker 1: how do you think the FED has done since then?
Speaker 1: I think during the financial crisis, the FED really had
Speaker 1: to do some special things that they hadn't done. Had
Speaker 1: to buil up their balance sheet, which they had really
Speaker 1: never done before. Used to be the FED was just
Speaker 1: raising and lowering the uh, the interest rate, and um
Speaker 1: that was not that didn't do anything after you got
Speaker 1: down to zero interest or so they then had to
Speaker 1: build up their balance sheets. So I think they Fed
Speaker 1: UH did a great job, in my opinion, in helping
Speaker 1: to avoid that another great suppression, a real catastrophe. Definitely,
Speaker 1: you think it could have been. I think people have forgotten.
Speaker 1: It's been a decade and they've already forgotten. Were we
Speaker 1: on the precipice of another depression similar to the nine
Speaker 1: and the nineties. We were on the precipice of a
Speaker 1: financial breakdown. I don't know that it would cause a depression,
Speaker 1: but it would cause a lot of chaos and certainly, um,
Speaker 1: I'm not clear what it would cause, you know, but
Speaker 1: we were definitely on the precipice of that financial breakdown,
Speaker 1: which could have been very severe. I As far as
Speaker 1: what the FED has done since then, well I think
Speaker 1: they could have. We were now ten years later and
Speaker 1: we haven't. Were now interest rates less than the window
Speaker 1: the FED window. They're really only charging less than three
Speaker 1: at this point. UH. One of the one of the
Speaker 1: levels the FED has to protect against recessions is the
Speaker 1: lower the rate we can't lower the rate if we
Speaker 1: never royals it, and so I think they could have
Speaker 1: done much more, but they were very reluctant to raise
Speaker 1: rates over this long recovery, which has been now very
Speaker 1: long tenure recovery. And so we still don't have normalized
Speaker 1: interest rates, and the FED is are they behind the
Speaker 1: curve or have they just not gotten us to a
Speaker 1: place that resembles neutral? Yet the rates are still low,
Speaker 1: and and although they are finally reducing the balance sheet
Speaker 1: of the FAT, it's still a big balance sheet. So
Speaker 1: they don't have the same firepower going into any new
Speaker 1: activity that happens that we had back in oh eight.
Speaker 1: Quite interesting, So let's talk a little bit about annuities
Speaker 1: um which are somewhat controversial to some people. I don't
Speaker 1: know if that's really the right descriptor of it. You
Speaker 1: wrote not too long ago, investors should consider indexed anuities
Speaker 1: as bond substitutes. Explain what those are and how would
Speaker 1: that operate in a in a portfolio. Well, let me
Speaker 1: first explain why we might need a bond substitute. Uh,
Speaker 1: if you bonds today at least treasure yields are below
Speaker 1: three percent the tenure I looked lass. I looked recently,
Speaker 1: the tenure was definitely below three percent. And and uh,
Speaker 1: a return on a bond is the yield plus or
Speaker 1: minus a capital gainer loss. If yields rise, you have
Speaker 1: a capital loss on bonds. And I mentioned duration at
Speaker 1: an earlier time. The essentially, if he yields rise one
Speaker 1: percent and the duration is ten on a bond, you're
Speaker 1: you lose ten on that bond. So there was a
Speaker 1: potential for actually bonds that have negative returns in the future. Uh,
Speaker 1: if you look at the history of all these yields,
Speaker 1: we from the fourties on we had very low yields
Speaker 1: that rose and one they were double digits, and but
Speaker 1: since then they've been straight down thirty three years of
Speaker 1: falling interest rates. And that meant really good returns because
Speaker 1: not only did you get those high yields that you
Speaker 1: started with, but then you've got these capital gains. That's
Speaker 1: probably not going to happen going forward. Here we're gonna
Speaker 1: have a low yield and a potential capital loss. So
Speaker 1: I wanted to see what else so you could you
Speaker 1: could we could have that would be an alternative to that. Sure,
Speaker 1: so short of going back too and building a bond portfolio.
Speaker 1: How how so how would an index the nuity work?
Speaker 1: What is what's in? What's in? Because in the nuity
Speaker 1: is just a rapper, right and for the most part
Speaker 1: tax deferred. UM, how do index in what he's worked?
Speaker 1: And index I their insurance products? And UH, and I
Speaker 1: have to say that UM Zebra Capital has indexes, actually
Speaker 1: a co branded index with the New York Sack Exchange
Speaker 1: and UH that index is actually used by an insurance
Speaker 1: company to UH in creating a accumulation annuity. I'll mention
Speaker 1: here so so I I have some in set up
Speaker 1: here to Actually so you're talking your book, but you're
Speaker 1: the expert in this space. So we've we know that
Speaker 1: you take your academic theory and apply it in practical
Speaker 1: and then here's a perfect example of it. So what
Speaker 1: is that annuity holds? And aren't we kind of doing
Speaker 1: a little bit of UM magic taking something and creating
Speaker 1: a UM a yield that doesn't have the same parameters
Speaker 1: of a bond. What is that metamorphosis there? So the
Speaker 1: what what's happening as we take the index? Actually the
Speaker 1: insurance company takes this index and it it ensures the
Speaker 1: downside essentially, so it doesn't actually by buying, buying options
Speaker 1: and so forth. So what what it means is that
Speaker 1: a an actual person then can buy a annuity and
Speaker 1: index annuity that they get a participation in. Our index
Speaker 1: is an equity index that has the bonds in it,
Speaker 1: and it's risk control to have a five percent volatility,
Speaker 1: but they can buy that index with that with that
Speaker 1: five percent volatility, the insurance company ensures it so that
Speaker 1: you get equity participation, but you don't lose any money.
Speaker 1: So this isn't We're not taking lead and turning it
Speaker 1: into gold. This is essentially a hedged um equity product
Speaker 1: that behaves like a bond. Is that a fair way
Speaker 1: to describe it. It has roughly the same returns as
Speaker 1: a bond on average, but it doesn't have any losses
Speaker 1: that the losses are insured and uh and essentially you
Speaker 1: have equity participation on the upside, not full equity participation.
Speaker 1: It's not a substitute for stocks. It's a substitute for
Speaker 1: bonds that doesn't ever lose money. So it's a dividend
Speaker 1: yield plus whatever capital appreciation you get minus the cost
Speaker 1: of of hedging against the downside. You get the capital
Speaker 1: appreciation and um and a participation in the equity market. Uh,
Speaker 1: and of course UH, no losses on the downside of
Speaker 1: That's what by having less than participation in the equity
Speaker 1: market and by getting the capital appreciation, uh, you are
Speaker 1: be able to the insurance company to be able to
Speaker 1: use that to have ensured the downside so that there
Speaker 1: are no losses. So you end up with a distribution
Speaker 1: of returns that is is maybe roughly comptable in terms
Speaker 1: of returns to a bond market, but has upside but
Speaker 1: not downside. Quite fascinating. You're a Chicago guy. You worked
Speaker 1: with Gene Fama. There are a number of factors that
Speaker 1: just keep getting discovered. Last count it was excess of
Speaker 1: four hundred, maybe even more than that. What do you
Speaker 1: think about all these different factors in the textbooks and
Speaker 1: and how does that work in the real world. Well,
Speaker 1: these say four hundred factors, there are a lot of
Speaker 1: them are correlated with each other, so there's not really
Speaker 1: four hundred, but but there's still many of them, you know.
Speaker 1: And the way to evaluate it has to do with
Speaker 1: our monograph again, popularity, Because in order for a a
Speaker 1: factor to really pay off and forward from over the
Speaker 1: long term, in anyway, it has to be unpopular in
Speaker 1: some sense unpopular. So the popular ones are valuation, quality,
Speaker 1: momentum um. Uh, those are probably the four most popular
Speaker 1: ones I can think of. You want to go further
Speaker 1: on the list and find ones that are either overlooked
Speaker 1: or or unpopular. Well, for example, liquidity is something that's
Speaker 1: inherently popular, and less liquarity is inherently less popular. So
Speaker 1: if you have a factor based on liquarity, that's likely
Speaker 1: to pay off. If you have a factor based on risk,
Speaker 1: they're often likely to pay off because risk is always
Speaker 1: going to be unpopular and less risk is always will
Speaker 1: be more popular. If you have factors based on um,
Speaker 1: it could be quality, it could be any of these
Speaker 1: sort of things. It could be value, value based. Essentially,
Speaker 1: if value companies are distressed companies that we don't like,
Speaker 1: they value premium might be unpopular, I guess. So that's
Speaker 1: that's the rationale why you might have a value premium
Speaker 1: because if people if they're the type of companies that
Speaker 1: we don't like, then then they're going to be relatively
Speaker 1: less demand for them. They're going to be unpopular. But
Speaker 1: that means that less demand means that they're gonna have
Speaker 1: higher expected returns. So so here we are in value
Speaker 1: has gotten its butt kicked over the past decade by growth. Um,
Speaker 1: I'm gonna take that. I'm gonna interpret what you're saying
Speaker 1: as implying valuate value as a factor is less popular,
Speaker 1: but value should expect better returns going forward, or value
Speaker 1: should have a higher expected return going forward versus the
Speaker 1: more popular growth. Yes, I think it does, especially now
Speaker 1: that we've had this bad period, because once, once, after
Speaker 1: value does so well, everybody gets excited and stays saying, well,
Speaker 1: I should be buying value stocks instead of growth stocks.
Speaker 1: So the question you always have to ask yourself this question,
Speaker 1: that's what this monograph is all about. I can help
Speaker 1: but point out that a number of famous and infamous
Speaker 1: hedge fund managers over the past decade, all of whom
Speaker 1: kind of came to the public's attention eight, ten, twelve
Speaker 1: years ago. The more popular they got and the more
Speaker 1: capital they got, the worst their performance seems to be.
Speaker 1: Is this the same sort of issue where suddenly popularity
Speaker 1: just exceeds their ability to manage that capital, or is
Speaker 1: there something about, hey, that's way late in the cycle
Speaker 1: by the time it gets popular. It's just too late. Well,
Speaker 1: it's probably both of that that. Certainly, when they get
Speaker 1: a lot of money that their particular idea, they put
Speaker 1: a lot of money behind it, they're putting too much
Speaker 1: money behind it, and then and then they're moving the
Speaker 1: price themselves, and then that makes it overvalued and then
Speaker 1: too popular in our words, So too popular could be overvalued,
Speaker 1: too popular could be just classical uh types of things
Speaker 1: like risk, opic quality, um, uh popular. But popularity is
Speaker 1: the thing that ties everything together. That's why I guess
Speaker 1: I'm so excited about uh our new uh, our new
Speaker 1: monograph here, uh, because it's not only it ties all
Speaker 1: these premiums together that people are talking about, say the
Speaker 1: four premiums and which ones might work. And it also
Speaker 1: ties in the link because we were evolving into behavioral
Speaker 1: finance and classical finances being different fields to some extent,
Speaker 1: this ties them back together again. So I'm really I'm
Speaker 1: really excited about the whole approach here, and I'll I'll
Speaker 1: include a link to that white paper on the right
Speaker 1: of about this so people can find it. We have
Speaker 1: been speaking with Roger Ibbotson, Professor of Finance at the
Speaker 1: Yale School of Management and Chairman of Ibbotson associates, as
Speaker 1: well as chairman and ce IO of Zebrook Capital Management.
Speaker 1: If you enjoy this conversation, we'll be sure and check
Speaker 1: out the podcast That Straus, where we keep the tape
Speaker 1: rolling and continue discussing all things factor and popularity related.
Speaker 1: You can find that at iTunes, Overcast, Stitcher, Bloomberg dot com,
Speaker 1: wherever final podcasts are found. We love your comments, feedback
Speaker 1: and suggestions right to us at m IB podcast at
Speaker 1: Bloomberg dot net. Check out my daily column on Bloomberg
Speaker 1: dot com slash Opinion. Follow me on Twitter at Hults.
Speaker 1: I'm Barry Rihults. You're listening to Master's in Business on
Speaker 1: Bloomberg Radio. Welcome to the podcast, Roger, Thank you so much.
Speaker 1: I don't know what's called you, Professor Edwardson, Roger, what's
Speaker 1: your preferred uh, well with a person like you, Berry
Speaker 1: is I'll call you Berry. You should call me Roger.
Speaker 1: I feel like I'm I'm definitely uh punching above my
Speaker 1: weight in this conversation. Um, but this has been just
Speaker 1: really fantastic stuff. I know I've been following your career
Speaker 1: and your research and writings for um my whole career
Speaker 1: in finance, and I've been very much looking forward UM
Speaker 1: to this conversation. So let's jump to our favorite questions.
Speaker 1: I asked these of all our guests, and some of
Speaker 1: some of these UM are especially resonant for for different listeners.
Speaker 1: Let's start with UM. I used to ask this question
Speaker 1: just as a sound check for the UM Audio Engineer,
Speaker 1: and the answers were so fascinating that I've started asking
Speaker 1: all the guests this question. So, what was the first
Speaker 1: car you ever owned? Year, make and model. Well, it
Speaker 1: was the nine six one Plymouth Valiant light blue, and
Speaker 1: I was a junior, I guess, just a starting senior
Speaker 1: in college at Purdue. And I really love that car.
Speaker 1: I gotta say it look kind of a sporty looking car,
Speaker 1: and so it was a really do a four door
Speaker 1: it was. It was a four door car, but it
Speaker 1: was still a very very sporty looking car and it
Speaker 1: was great fun, although unfortunately I didn't get to keep
Speaker 1: it that long. I kind of remember the Valiant. I'm
Speaker 1: trying to remember if that was like a Dodge Dart,
Speaker 1: similar shape, sort of a big long hood and a
Speaker 1: big long No, it's actually a little bit smaller than that.
Speaker 1: Very smart sporty looking, all right, wasn't like that back
Speaker 1: in the day when Plymouth made some pretty substantial sports cars. Yeah,
Speaker 1: they didn't make the sports cars. But unfortunately that car,
Speaker 1: uh my first job after I got my m b A.
Speaker 1: So I had that car for three years, a senior
Speaker 1: year and then two years as an NBA student. Um,
Speaker 1: but I worked on a cattle ranch, actually my first
Speaker 1: job in Nevada. Huh. So I was gonna ask my
Speaker 1: next question is what is the most important thing we
Speaker 1: don't know about Roder Ribertson? But before I get to that,
Speaker 1: how do you go from the University of Chicago, an
Speaker 1: NBA in finance to a cattle ranch. Well, I thought
Speaker 1: I had an offer, so I took it that I
Speaker 1: thought it looked like a good opportunity to do something
Speaker 1: really great and but but I was out of my element.
Speaker 1: I was fired at the end of the summer. So
Speaker 1: you weren't trading cattle futures. You were actually on a
Speaker 1: horse within a ranch. Well, it was more like trucks
Speaker 1: and planes. But you're let me tell you, a car
Speaker 1: does not last on a cattle ranch very long because
Speaker 1: they're all dirt roads and the car was just covered
Speaker 1: with thick with dust and every and every bump and
Speaker 1: so forth, the transmission went out and all the things.
Speaker 1: So that was the my card. Uh had that kind
Speaker 1: of ending life there. And and I didn't work out
Speaker 1: either at the cattle ranch, and so I actually uh
Speaker 1: ended that job and put it on my resume as
Speaker 1: a summer job. That's pretty that's pretty hilarious. So I
Speaker 1: given that I'm reluctant to ask the next question, but
Speaker 1: what's the most important thing people don't know about? Roger Robertson,
Speaker 1: I would actually say, though I'll take it all the
Speaker 1: way to the present, sure that I'm not you know,
Speaker 1: I've always been working in finance all these years, but
Speaker 1: I'm actually very interested in um long term data and
Speaker 1: time over time and so forth. And I'm getting very
Speaker 1: interested and I might be writing at least researching whether
Speaker 1: or right on the subject of of long history going
Speaker 1: far forward and forward and back. Essentially. Uh, perhaps I've
Speaker 1: been starting with the Big Bang and and and then
Speaker 1: really for more predictive purposes though, and and long term
Speaker 1: kind of predictions and what's going to happen to to
Speaker 1: humanity and so forth. So that's that's one of the
Speaker 1: things you'll have to interview me a couple of years later.
Speaker 1: Times out. You're absolutely welcome back. We'd love to talk
Speaker 1: about that. So tell us about And I'm afraid to
Speaker 1: even ask this question, but i have to because I
Speaker 1: know who's coming up in the answer. Who were your
Speaker 1: early mentors? Oh? I it is the It is the
Speaker 1: University of Chicago, people with uh, the Farmer, Merton, Marco
Speaker 1: Wits who else is on that run? Well as Byron
Speaker 1: Shows and Fisher Black and yeah, and Merton Miller and
Speaker 1: Jane Farmer. There are all my early mentors. Yes, that
Speaker 1: that's that's an incredible lineup. What about investors? What investors
Speaker 1: influence the way you think about taking theory and applying
Speaker 1: it in the real world. You know, I they weren't
Speaker 1: literally investors, because I have to say that, uh, getting
Speaker 1: grounded in efficient capital market theory UH gives you a
Speaker 1: whole approach to investing. And and it's stead of starting
Speaker 1: out with imagining that every stock you imagine is is
Speaker 1: unrelated to the price in some way. If you start
Speaker 1: out with the fact that if you know nothing about
Speaker 1: a company or or a security, it's the prices the
Speaker 1: kind of the best guess of what its value is.
Speaker 1: And so that's such a dramatic approach, even if you're
Speaker 1: looking for inefficience for the market, it's such an uh
Speaker 1: changes your whole way of approaching everything and thinking about
Speaker 1: everything because you instead of well, for example, as a
Speaker 1: portfolio manager, you could do nothing and you might do fine.
Speaker 1: You know, it's you don't have to literally trade every
Speaker 1: day to make things work. It's a matter of of
Speaker 1: you only want to trade when you really do have
Speaker 1: the edge that you're actually going to add value. So
Speaker 1: one of the things I always think about and I've
Speaker 1: managed companies and I've managed stocks, and I think um
Speaker 1: stocks in some way manage themselves. People. Well, if you
Speaker 1: start out from the belief that the prices of fair
Speaker 1: estimation of the value that should really take care of itself.
Speaker 1: That's right. That's that's the key. I mean, once you
Speaker 1: sort of know that your stocks are managing themselves, but
Speaker 1: then you try to improve on that. But man your
Speaker 1: people don't manage themselves, that's right. So it's much harder
Speaker 1: to manage people than it is to manage stocks once
Speaker 1: you understand this principle. If you don't understand that principle, though,
Speaker 1: managing stock markets. You've got hundreds of thousands of stocks.
Speaker 1: You've got hundreds, hundreds or thousands or whatever. You've got
Speaker 1: all these stocks, and you're trying to think out it's
Speaker 1: just one over valued or undervalued. If you have to
Speaker 1: attack it that way, you can quickly get overwhelmed into
Speaker 1: the situation. So it's just a principle that so much
Speaker 1: simplifies the process. Starting with the assumption that, hey, most
Speaker 1: stocks gonna be more or less priced relative to their value.
Speaker 1: It's a good starting place. Um, all right, let's get
Speaker 1: to everybody's favorite question. UM, I get emails about this
Speaker 1: all the time. Tell us some of your favorite books. Well,
Speaker 1: but by the way, I will include your books when
Speaker 1: we when this goes live, I will include a list
Speaker 1: of all your published books. So tell us some of
Speaker 1: the favorite books that you've read of other authors. Yeah,
Speaker 1: I want to say, of course, I'm not going to
Speaker 1: promote my own books. I always love my own books.
Speaker 1: I guess who does it? What does But because I've
Speaker 1: been looking at long term things, I've been you know,
Speaker 1: are you're gonna go go ahead? Let's see for for example, UM,
Speaker 1: there's this, Uh, you've o Harari who's been writing and
Speaker 1: sapiens and then the predicting the future on that and
Speaker 1: reading that like I've been reading like Steven Pinker's Huh.
Speaker 1: I think it's called Our Better Angels, that our angels
Speaker 1: of our nature. Yes, about how how how we're changing
Speaker 1: over time and so forth, and how we're less violent
Speaker 1: and so forth. Uh. David Christian is an author and
Speaker 1: he's Australian. Well it's not really Australia, and he's been
Speaker 1: all over the world, but he's I think he's teaching
Speaker 1: in Australia at this point, but he he's he's written
Speaker 1: a book and done a lot of uh of course,
Speaker 1: uh electronic courses on on big History, which is looking
Speaker 1: at history from the start all the way out into
Speaker 1: the future. Is that the name of the book Big History? Well,
Speaker 1: he has a book that's his most storole book is
Speaker 1: Maps in Time from about ten ten, fifteen years ago.
Speaker 1: Do you have any other books you want to mention
Speaker 1: because I'm gonna circle back to something you said earlier. Well,
Speaker 1: I could name many kids like this subject when I'm
Speaker 1: just just just finished was Yeah. Johan uh Norberg out
Speaker 1: of Sweden wrote a book on progress and how how
Speaker 1: we're getting better off and lots of different dimensions and
Speaker 1: so forth. So these are all subjects that are of
Speaker 1: interest to me. I don't think it's all good news though,
Speaker 1: of course, uh because at Yale, for example, the recent
Speaker 1: Nobel Prize winner um Um Bill Northouse uh really worked
Speaker 1: on pollution and so forth, and how global warming and
Speaker 1: so forth. So lots of other things are going on.
Speaker 1: I'm not saying it's all good news. I'm I'm interested
Speaker 1: in the overall effect though, and trying to understand this.
Speaker 1: So I'm I am interested in long term history, and
Speaker 1: I'm always interested in long term forecasting. I'm fascinated by
Speaker 1: the two Harari books because Sapiens is so interesting and
Speaker 1: while some of it's got a little bit of negative cast,
Speaker 1: generally speaking, it's the history of progress, even though along
Speaker 1: the way he kind of annotates it with all these, yeah,
Speaker 1: well farms and cities or where diseases began, and but
Speaker 1: it's not a completely bleak picture. The Homo Dais book
Speaker 1: is a little more negative looking forward than Sapiens, sort
Speaker 1: of had this wide eyed wonder to it, and which
Speaker 1: did not come across at Home of Dais. I'm curious
Speaker 1: as to your your take on the two books. Well,
Speaker 1: I sense what you're saying, and and I must say,
Speaker 1: humans I've been a remarkable species. And I'm always just
Speaker 1: amazed at the fact that that we we actually can
Speaker 1: understand the start of the universe, and we can understand
Speaker 1: we maybe we do, We're not sure we do yet. Well,
Speaker 1: we know a lot about it. It's some amazing a
Speaker 1: lot about it. And we also know I mean, that's
Speaker 1: how they got the Higgs, Boston fixtion and all that
Speaker 1: kind of thing. They can predict these sort of things.
Speaker 1: And we also know something about the scale of the universe,
Speaker 1: which is astonishing. And this is all happened in the
Speaker 1: last three or four hundred years, you know, since since
Speaker 1: uh Copernicus and Kepler and Galileo and so forth, these things, Uh,
Speaker 1: we went from nowhere thinking the Earth was the center
Speaker 1: of everything to actually understanding everything that's at the macro level,
Speaker 1: but the micro level. We also understand how of course
Speaker 1: Adams and electrons and and courts and d n A
Speaker 1: and and so forth. So our um, our species has
Speaker 1: just uh may has amazing accomplishments and and and but
Speaker 1: I don't know where. So you have to wonder, then,
Speaker 1: given all this huge acceleration of knowledge and and actually
Speaker 1: collection of knowledge that just keeps building on itself. Where
Speaker 1: does that go, especially especially the past fifty years. We're
Speaker 1: in a golden age of physics, I mean the past
Speaker 1: fifty years and in the past decade, quite quite astonishing
Speaker 1: the sort of progress we've made. All that said, the
Speaker 1: Big Bang theory is still a very preliminary theory. We
Speaker 1: don't understand the whole inflationary expansion that took place. We
Speaker 1: still don't understand if we're measuring the universe right, how
Speaker 1: much dark matter is out there? What are we missing
Speaker 1: when we not say why are galaxies accelerating away from
Speaker 1: each other no matter what direction you look. I'm fascinated
Speaker 1: by that. I like you are. I share um, just
Speaker 1: a genuine astonishment about that. I'm also there was a
Speaker 1: book that came out about a decade ago um that
Speaker 1: you might appreciate if you're if you're working away forward
Speaker 1: from the Big Bang, called the rare Earth thesis, which
Speaker 1: basically says, well, life is probably common in the galaxy
Speaker 1: because in the universe, because every galaxy has all the
Speaker 1: build fundamental building blocks hydrogen, carbon, oxygen, nitrogen, etcetera. But
Speaker 1: intelligent life is really, really rare, and it's a whole
Speaker 1: series of incredibly unused usual events that lead to a
Speaker 1: planet like this that's stable enough for for billions of years,
Speaker 1: for long enough for intelligent, technologically advanced life to um develop.
Speaker 1: And I'm I'm just intrigued by that sort of circling
Speaker 1: back to the original pre enlightenment. Oh no, no, it's
Speaker 1: just humans. The rest of the universe doesn't doesn't matter.
Speaker 1: The whole universe was just created by God for us.
Speaker 1: And maybe there's actually some for completely different reasons, theoretical
Speaker 1: basis for that um thesis from a physics approach, But
Speaker 1: but I digress far off. It's not the best written book,
Speaker 1: but it's a fascinating concept if you if you're enjoying
Speaker 1: all the modern astrophysics work, and I'm sure you've you've
Speaker 1: come across Brian Green and his string theory work and
Speaker 1: other stuff. I'm endlessly fascinated by that. I'm just intrigued
Speaker 1: by that stuff. So one of the great things about
Speaker 1: being a professor, uh is is uh you get to
Speaker 1: study whatever you want and and you you share this
Speaker 1: fascination with me with this, And now I really can
Speaker 1: kind of work on this now you see. So do
Speaker 1: you ever pick up the phone at Yale and say, oh,
Speaker 1: so and so is in the astrophysics department, let me
Speaker 1: get him on the phone. And you have access to
Speaker 1: all these folks who can who can steer you in
Speaker 1: certain directions. I'm starting to do that. I hadn't been
Speaker 1: doing that, you know, because I've more had been pretty
Speaker 1: focused over the as you said, I've have a broad
Speaker 1: breath breath of activities here, but but they hadn't gotten
Speaker 1: into this sort of thing. Now I'm getting into all
Speaker 1: the other arms of the university, and uh, I find
Speaker 1: it really exciting to uh to see, really I'm applying
Speaker 1: the kind of things I've always done because I always
Speaker 1: was interested in history and data and I've always taking
Speaker 1: it to the next level and always interested in making
Speaker 1: projections and and so forth. And now I'm just trying
Speaker 1: to broaden this out. So so this is, uh, this
Speaker 1: a great I guess at this point I would say
Speaker 1: it's a hobby, but but it but it trying to
Speaker 1: make it into I don't think I'll make money from
Speaker 1: this car. Well, it's tough to do that. So so
Speaker 1: it makes me want to ask you the question universal
Speaker 1: entropy and we eventually just going to dissipate or the
Speaker 1: big crunch and all starts over again. You really do
Speaker 1: want the big question, you know, I I come prepared
Speaker 1: while the uh, of course entropy eventually dissipates everything. But
Speaker 1: but one of the things that the universe is built
Speaker 1: on is complexity. And even though you have this overall
Speaker 1: entropy going on, which is spreading everything out and dissipating,
Speaker 1: you have gravity has been one of the big things,
Speaker 1: pulling things, pulling parts of things together. So at the
Speaker 1: same time everything is dissipating. Obviously we are we are
Speaker 1: getting more and more complex, and that's certainly humans are
Speaker 1: an example of that. So the word own is getting
Speaker 1: more complex, not less complex, despite this, despite the second
Speaker 1: law thermodynamics. So I'm fascinated by the concept and I
Speaker 1: wish I can remember where I read it that and
Speaker 1: this will be the last astrophysics part of our conversation.
Speaker 1: The idea that nothingness is inherently unstable, and the Big
Speaker 1: Bang comes around that you can't have nothingness forever. Nothingness
Speaker 1: eventually just explodes into something else because if it's inherent instability,
Speaker 1: and that's a little mind blowing to me us humans
Speaker 1: can barely conceptualize it. But it's a fascinating concept. Where
Speaker 1: how does the universe come out of nothingness? And the
Speaker 1: answer is, well, maybe nothingness just is so unstable that
Speaker 1: it has no choice but to create a universe. I'm
Speaker 1: I'm fascinated by that. So in my case, I'm going
Speaker 1: to limit this a little more. You're gonna keep it
Speaker 1: limited to just the universe. Well, I mean I might
Speaker 1: look at the next hundred years or the next thousand
Speaker 1: days or something like that, so uh, the instead of
Speaker 1: uh or maybe mainly our planet, you know, instead of
Speaker 1: the whole universe and so forth. So, but but they're
Speaker 1: all related. I mean, it's certainly having some understanding of
Speaker 1: the big picture helps you, helps you understand still the
Speaker 1: very big picture quite interesting. So let me move forward
Speaker 1: away from the universe and ask you this, tell us
Speaker 1: about a time you failed and what you learned from
Speaker 1: the experience. You know, I failed quite a bit in
Speaker 1: my early days, and uh my my father was in
Speaker 1: the heating and air conditioning business, and had I been
Speaker 1: more mechanically inclined, you would have gone into that field. Yes,
Speaker 1: that's certainly goodness, you weren't because we we need you
Speaker 1: here in finance doing what you're doing. And and then
Speaker 1: even even when I, UM, so, when I went to college,
Speaker 1: my father to take engineering because the corporate presidents are
Speaker 1: mostly engineers. That was true after World War Two, but
Speaker 1: it's not true today. Um. And so I took engineering,
Speaker 1: but I really couldn't handle all the hands on stuff
Speaker 1: of even engineering, and and so I got into math
Speaker 1: and physics as my major. But then I but even so,
Speaker 1: I needed to be something more abstract. But when I
Speaker 1: got to math, it got too abstract from me and
Speaker 1: I couldn't even handle that. And and so I had
Speaker 1: to find a niche and finance. Finance is actually the
Speaker 1: perfect niche. It's it's kind of abstract, but it's not
Speaker 1: as abstract as as abstract. Um it's I I actually
Speaker 1: try to make something like abstract things practical. That's been
Speaker 1: my key. I guess that that that piece in between
Speaker 1: the fully abstract and the practical and blend them together.
Speaker 1: That's your sweet spot, right in the middle between the
Speaker 1: between the two of them. So what do you do
Speaker 1: for fun and when you're not contemplating, uh, the universe? What? What?
Speaker 1: What does Roger Ribintson do to keep himself entertained, Well,
Speaker 1: I mean I have a family, and so I have
Speaker 1: two sons here in Brooklyn, and um, it's great to
Speaker 1: get together with them. Of course I exercise and all that,
Speaker 1: and and um like hiking and all that. But but
Speaker 1: to me, the most fun and even connects my family
Speaker 1: and everything is the world of ideas. I mean, and
Speaker 1: that's what's so great about being a professor. Uh, you
Speaker 1: essentially are told do what you want. Um, you have
Speaker 1: to come out with something once in a while, but
Speaker 1: do whatever you want every once in a while. Educate
Speaker 1: the kids if you can. But also I actually do
Speaker 1: love teaching too, So the teaching is really exciting to
Speaker 1: me and stimulating. So it's a it's a it's a
Speaker 1: great combination. So so I thought that I'm a workaholic,
Speaker 1: because I'm really not a workaholic. But it's about the
Speaker 1: most fun you could have. And even when I talked
Speaker 1: to my sons, for example, and uh, it's all we're
Speaker 1: talking about economics all the time, and it's an exciting
Speaker 1: area and not only just economics about but about um,
Speaker 1: the universe or whatever, you know, talking about all these ideas.
Speaker 1: So the world of ideas is really fun. Quite quite
Speaker 1: um quite charming. Um. So you mentioned teaching. If a
Speaker 1: millennial or a recent college grad came to you and
Speaker 1: asked for career advice about the world of finance, what
Speaker 1: sort of advice would you give them, Well, it starts
Speaker 1: with follow your passion and follow your interests. Of course,
Speaker 1: don't just try to maximize money here the um and
Speaker 1: if if they they're gonna be likely successful if they
Speaker 1: are following their passion, so so that that's definitely what
Speaker 1: I would tell them to do. Uh. Fortunately, finance is
Speaker 1: a pretty well paid profession, so most people end up
Speaker 1: doing reasonably well. And uh that maybe that's not I'm
Speaker 1: glad that happens, because I guess at all worked out
Speaker 1: great for me. So and and and our final question,
Speaker 1: what is it that you know about the world of
Speaker 1: investing today that you wish you knew forty years ago
Speaker 1: when you were coming out of your NBA program and
Speaker 1: just getting started. And that question I'm not going to
Speaker 1: really answer the way you asked it, because in fact
Speaker 1: I did know, uh, And the whole idea of coming
Speaker 1: out of understanding what equilibrium is and how prices are
Speaker 1: formed and our version and how starting with market efficiency
Speaker 1: and so forth. That really changed my life and how
Speaker 1: I approach everything and made everything easier. So you were
Speaker 1: fortunate to figure out at the beginning of your career
Speaker 1: what a lot of people don't figure out until towards
Speaker 1: the end of their career. Yes, so it's not like
Speaker 1: I don't I don't know what to tell you about
Speaker 1: what I didn't know, because I actually did know these
Speaker 1: important concepts and they actually had wonderful I watched a
Speaker 1: wonderful impact on me. Well, that's quite fascinating. Roger Ibbotson,
Speaker 1: thank you so much for being so generous with your time.
Speaker 1: We have been speaking with Roger Ibbotson. He is a
Speaker 1: Professor uh in the Practice Emeritus of Finance at the
Speaker 1: Yale School of Management, as well as founder and chairman
Speaker 1: of Ibbotson Associates and chairman and chief investment officer of
Speaker 1: Zebra Capital Management. We love your comments, feedback and suggestions.
Speaker 1: Be sure and write to us at m IB podcast
Speaker 1: at Bloomberg dot net. Check out some of the other
Speaker 1: two hundred and forty eight such previous conversations that we've had.
Speaker 1: If you look up an inch or down an Inch
Speaker 1: on Apple, iTunes, Stitcher, Overcast, Bloomberg dot com, wherever final
Speaker 1: podcasts are sold, you can see the rest of all
Speaker 1: of our previous com stations. I would be remiss if
Speaker 1: I did not thank the crack staff that helps put
Speaker 1: this podcast together each week. Um Medina Parwana is my
Speaker 1: producer slash audio engineer. Taylor Riggs is our booker. Attica
Speaker 1: val Bron is our project manager. Michael bat Nick is
Speaker 1: our head of research. I have to thank Charlie Palett
Speaker 1: this week for giving us his desk and his UH
Speaker 1: recording studio because of my snaff who with daylight, savings
Speaker 1: time and the UK. I'm Barry Retults. You've been listening
Speaker 1: to Masters in Business on Bloomberg Radio