Speaker 1: This week on the podcast, we have a special repeat guest,
Speaker 1: and he is one of my favorite people in finance.
Speaker 1: His name is Michael Mobisan and he is the chief
Speaker 1: strategist at Credit Swiss First Boston. UH. He used to
Speaker 1: work with Bill Miller over at leg Mason, who actually
Speaker 1: very recently just bought himself private. I really love the
Speaker 1: work of Mobisan. He I think he is a unknown
Speaker 1: or relatively unknown rock star. I find the way he
Speaker 1: looks at the world, the framework uh he creates two
Speaker 1: understand finance, understand how investors behave UH to be just
Speaker 1: absolutely fascinating and tremendously, tremendously insightful. UH. He is one
Speaker 1: of the few guests that we have invited back for
Speaker 1: a second time, and truth be told, our first interview,
Speaker 1: I was pretty uh. Met is probably the the nicest
Speaker 1: thing I could say about my own performance. He's always
Speaker 1: awesome and and I think you'll really enjoy this. So,
Speaker 1: with no further ado, here is my conversation with Michael Mobison.
Speaker 1: This is Masters in Business with Barry Ridholds on Bloomberg Radio.
Speaker 1: My special guest this week is Michael Mobisan. He is
Speaker 1: the head of Global Financial Strategies at Credit Swiss, he
Speaker 1: has quite the curriculum VITA. Previously, he was chief investment
Speaker 1: strategist at leg Mason Capital Management, working with famed investor
Speaker 1: Bill Miller. He's been a professor at the Columbia School
Speaker 1: of Business since, where he's won numerous awards for teaching excellence,
Speaker 1: as well as being named to the Institutional Investors All
Speaker 1: Star Research Team. He is the author of a number
Speaker 1: of books, most recently The Success Equation, Untangling Skill and
Speaker 1: Luck in Business, Sports and Investing, and he is also
Speaker 1: the author of some of the most interesting white papers
Speaker 1: in all of finance. Michael Mobiso, welcome back to Bloomberg.
Speaker 1: Thanks very awesome to do with you. So you and
Speaker 1: I know each other for a while, and I've been
Speaker 1: a fan of the sort of work you've done on
Speaker 1: a number of things. Let's let's start out with a
Speaker 1: quote of yours and see where you want to go
Speaker 1: with this. You said, perhaps the single greatest error in
Speaker 1: the investment business is a failure to distinguish between the
Speaker 1: knowledge of a company's fundamentals and the expectations implied by
Speaker 1: market price. What exactly do you mean by that? Yeah, So,
Speaker 1: in order to make money in markets you have to
Speaker 1: have a belief that's different than what the market believes.
Speaker 1: And the general tendency we all have is if things
Speaker 1: are going well, we want to buy, and we know that,
Speaker 1: of course from aggregate investor behavior, and when things are
Speaker 1: going poorly, we want to sell. But the way to
Speaker 1: make money is to have a view that's different than
Speaker 1: the market. And the metaphor that works the most vividly
Speaker 1: is the racetrack. Right. If you're a handicapper and you
Speaker 1: want to make money, there are two things that are important.
Speaker 1: One is how fast the horse is gonna run, we'll
Speaker 1: call that the fundamentals. And the second are the odds
Speaker 1: and the toweboard. And the way you make money is
Speaker 1: not picking the winner. The way you make money is
Speaker 1: picking miss price odds. And so that idea really carries
Speaker 1: over to the world investing. So I think it's most
Speaker 1: of us investors we sort of blur those two things.
Speaker 1: And I'll mention it kind of a funny story. I
Speaker 1: was in a big money management organization. They said, is
Speaker 1: there anything we could do that would be radical you
Speaker 1: in terms of how we approached the job. I said,
Speaker 1: here's an idea for you have half your analysts only
Speaker 1: work on fundamental stuff, right, one guy just works on
Speaker 1: Apple's future, you know, sales and profits and so forth,
Speaker 1: and then have the other guy just work on the
Speaker 1: expectations what does a hundred dollar stock price mean for performance?
Speaker 1: And then bring the two people together at the very
Speaker 1: last minute and see what happens, right, Because the problem
Speaker 1: is we tend to meld those two And I would
Speaker 1: say the great investors are those that really do think
Speaker 1: about those things separately. And I think it's a it's
Speaker 1: a real challenge for the rest of us. Again, things
Speaker 1: are going well, you want to buy it, things are
Speaker 1: going bad that you want to sell it, and you
Speaker 1: don't make those distinctions the way you should. What was
Speaker 1: the reaction to that proposal? And they kind of they
Speaker 1: kind of said, oh, that's kind of a cool idea. Yeah,
Speaker 1: see you later, So go very far. The interesting thing
Speaker 1: is when I when I speak with the quants, when
Speaker 1: I speak with investors with a mathematical basis, they tend
Speaker 1: to do pretty much what exactly what you're saying is
Speaker 1: they have an understanding of what the fundamental metrics are,
Speaker 1: and then their quantitative overlay is here's what we've seen
Speaker 1: in price relative to value, relative to book, relative to
Speaker 1: all these metrics. Hey, these this little subgroup looks wildly
Speaker 1: mispriced exactly, so I think the quantz I mean, this
Speaker 1: is another I'm sure we'll talk more about this, but
Speaker 1: I think the quants obviously have some of this captured
Speaker 1: in the way they approach the world, which makes enormous
Speaker 1: amounts of sense. The questions, are there things that fundamental
Speaker 1: analyst can do that quants can't do? Are there thing
Speaker 1: nuances they can pick up that might be? And that's
Speaker 1: an interesting sub separate conversation, but right, the virtue of quants,
Speaker 1: or even even basic rules for buying and selling are
Speaker 1: precisely you take the emotion out and that you're making
Speaker 1: those two the quantity of the fundamentals and expectations too separate.
Speaker 1: So anyone who's systematic, anyone who involved who is using
Speaker 1: some form of screening in order to help determine anybody
Speaker 1: who's using it's almost a cliche these days, but a
Speaker 1: factor or a dimension small cap value, momentum, quality, etcetera.
Speaker 1: They're using the math in order to help identify that
Speaker 1: that gulf on thing. That's right, I mean, the one
Speaker 1: thing this is a little bit off Barry, but I
Speaker 1: think this is interesting. So one of the things that
Speaker 1: I think a lot about is this idea of freestyle chess.
Speaker 1: I don't know if we've talked about this before, have
Speaker 1: you may know this? So you know, cas Brow loses
Speaker 1: Deep Blue, and so machine beats man. Fine, But surely
Speaker 1: thereafter what what emerged with something called freestyle chess? And
Speaker 1: I means you and I are playing a match, but
Speaker 1: we can avail ourselves or whatever aids we want. So
Speaker 1: we and on computer programs you can call your lifeline
Speaker 1: to your grand master, buddy or whatever it is. And
Speaker 1: it turns out these freestyle teams are better than the
Speaker 1: programs by themselves or of course any man or person. Right,
Speaker 1: So man plus machine beats man or machine, which is
Speaker 1: really interesting. And there's there's you know, Kevin Kelly, who's
Speaker 1: you know, just wrote a new book called The Inevitable.
Speaker 1: He's got a little section on this in the book.
Speaker 1: So this, to me is a very intriguing model to say.
Speaker 1: Are there cases where most of the time you default
Speaker 1: to the quantitative approach or to the program, But for
Speaker 1: every now and then, if you have a good feel
Speaker 1: for the game, you can step in and do something
Speaker 1: that's a little bit different that adds value. Now that's
Speaker 1: open open question whether that's true and investing, But to me,
Speaker 1: that's a really intriguing model for thinking about what where
Speaker 1: sort of humans and quantitative techniques may merge in the future. Well,
Speaker 1: we saw in late two thousand and seven and again
Speaker 1: a couple of years ago where all the quants kind
Speaker 1: of walking in lotstep and following their programs, and some
Speaker 1: see change took place, whether it was the financial crisis
Speaker 1: or something more recent, and even the math still got shelax.
Speaker 1: Sometimes the ground rules changed sufficiently that hey, whatever your
Speaker 1: methodology is is gonna at least temporarily be wildly out
Speaker 1: of favor. Which leads me to an interesting question. Um,
Speaker 1: so much of this stuff is not particularly intuitive, and
Speaker 1: think twice you use the phrase counter intuition. What is counterintuition? Well,
Speaker 1: I'm not even sure that's a word. My editor said
Speaker 1: that would be a good subtitle, but no, connor intuition.
Speaker 1: The big idea think twice is when we're faced with
Speaker 1: certain types of situations, our minds are naturally gonna want
Speaker 1: to think about the problem one way when there's a
Speaker 1: better way to think about it. Right, and so counterintuition
Speaker 1: is saying, hey, can I check myself and say I
Speaker 1: should think about it more effectively. Let me give an
Speaker 1: example to very famous one comes from Danny Kahneman, who
Speaker 1: obviously you know great psychologists, won the Nobel Price. He
Speaker 1: was our guest last week. Yeah, how is that? I
Speaker 1: gotta listen to it. He's awesome. Right, there is a
Speaker 1: fascinating story I'll share with you about about him in
Speaker 1: uh in the podcast portion, the idea is the inside.
Speaker 1: It calls the inside versity outside of you. So, Barry,
Speaker 1: if I give you a problem, it could be anything.
Speaker 1: It could be how long will take your remodel your kitchen,
Speaker 1: how much it will cost, or how the asset class do.
Speaker 1: The classic way to think about it, See if this
Speaker 1: resonates is you gather tons of information, you combine it
Speaker 1: with your inputs and your project into the future, right
Speaker 1: and left our own devices. That's how we solve problems.
Speaker 1: The outside view is by by contrast, is thinking about
Speaker 1: your problems in an instance of a larger reference class,
Speaker 1: basically asking what happened when other people are in this
Speaker 1: situation before. And it's a very unnatural way to think
Speaker 1: a because you have to leave aside this cherish information
Speaker 1: and be you have to find and avail yourself of
Speaker 1: this reference class. Take yourself out of yourself and look
Speaker 1: at it exactively. And let me give you an example.
Speaker 1: It's a trivial on Let's say you are remodeling your kitchen. Right,
Speaker 1: so you sit down with the contractor, you pick out
Speaker 1: all stuff, and you're all set to go where you've
Speaker 1: gotta budget. And so the work starts and your neighbor
Speaker 1: strolls over, say, Barry, what's going on. You go, Yeah,
Speaker 1: we're remodeling your kitchen. It's gonna cost us X and
Speaker 1: it's gonna will be done by this day. What does
Speaker 1: your neighbor say to you, knowing nothing about the details? Right,
Speaker 1: something like double the money, double the time, or something along. Right,
Speaker 1: you have all the inside view, right, you have all
Speaker 1: the ins he's just doesn't know about, but he's got
Speaker 1: the outside of you. So the point is that psychologists
Speaker 1: have demonstrated that introducing the outside of you almost always,
Speaker 1: almost invariably improves the quality of decisions. That's a classic example.
Speaker 1: Your mind naturally goes one way. Counter intuition would tell you,
Speaker 1: let's avail ourselves with this other information and we're gonna
Speaker 1: make more accurate forecasts. And the story Danny Kneman tells
Speaker 1: is when him and a group of psychologists we're working
Speaker 1: on a textbook, and these are folks who specialize in
Speaker 1: cognitive eras and foibles of of the mind. Uh, they
Speaker 1: ended up taking far beyond what their their consensus was,
Speaker 1: and it was it was right, uh, right in the
Speaker 1: sweet spott of what you're talking about. I'm Barry Ritolts.
Speaker 1: You're listening to Masters in Business on Bloomberg Radio. My
Speaker 1: special guest today is Michael Mobisan. He is head of
Speaker 1: Global Financial Strategies of Credit Swiss and author of numerous books,
Speaker 1: most recently The Success Equation Untangling Skill and Luck in Business,
Speaker 1: Sports and Investing. I love that title. It's so it's
Speaker 1: so fascinating. Let's let's pull a um a phrase out
Speaker 1: of that book. And and have you discussed that. I
Speaker 1: really enjoyed quote. Our love of stories and our need
Speaker 1: to connect cause and effect leads to all sorts of problems.
Speaker 1: The blend of those two ingredients leads us to believe
Speaker 1: that the past was inevitable and to underestimate what else
Speaker 1: might have happened. So obviously that applies to investing, but
Speaker 1: it also applies to sports and business to talk to them. Absolutely,
Speaker 1: it's a It is fascinating and bear you know when
Speaker 1: you when when an author puts down a book, you
Speaker 1: you've been through the same process. There may be a
Speaker 1: couple of ideas that keep banging around in your head
Speaker 1: and for me, this is one of those ideas. Um.
Speaker 1: The work here was done by professor named Michael Gazzaniga,
Speaker 1: who's a neuroscientist and and he did famous work on
Speaker 1: so called split brain patients. So these are people who
Speaker 1: deabilitating epilepsy, they failed all their treatments and as the
Speaker 1: last of jeffort, they sever the corpus close from the
Speaker 1: bundle of nerves between the two hemispheres of the brain
Speaker 1: left and the right hemisphere. And what allows the researchers
Speaker 1: to do is to figure out what what's going on
Speaker 1: each part of your brain. And to make a long
Speaker 1: story short, what they found and absolutely fascinating researches. And
Speaker 1: in your left hemisphere, which is where your language resides,
Speaker 1: there's a module they now call the interpreter, and the
Speaker 1: job of the interpreter is to close cause and effect loops.
Speaker 1: So I throw an effect at you, and this little
Speaker 1: module in your brain is gonna is gonna try to
Speaker 1: figure out how to close the close the loop. Right,
Speaker 1: So you know, we know the future is buzzing with possibility.
Speaker 1: Everybody gets that. But once an event occurs, all of
Speaker 1: us effortlessly and naturally create a narrative to explain that outcome, right,
Speaker 1: your interpreter. And when that happens, two things kick in.
Speaker 1: The first is hindsight biases. We start to believe that
Speaker 1: we knew what was going to happen with a greater
Speaker 1: probability than we actually did. And by the way, I
Speaker 1: cannot even count how the people have called me or
Speaker 1: emailed me to say I knew Brexit was gonna happen.
Speaker 1: So I said him, immediately, where did you write that down?
Speaker 1: Where's your pile of money from your wealth and your
Speaker 1: built right? I hear this about the financial crisis, So
Speaker 1: anybody could have told this was well, why were you long?
Speaker 1: And I'm actually exposed to banks, home builders and mortgage
Speaker 1: lenders right into the collapse if you knew it was
Speaker 1: coming precisely. And the second thing that happens, which is related,
Speaker 1: is this idea called creeping determines that you start to
Speaker 1: believe that what happened was the only thing that could
Speaker 1: have happened, right, So this is a little module in
Speaker 1: your brain. Now, the tie back to the skill and
Speaker 1: luck stuff is that the interpreter really knows nothing about luck.
Speaker 1: So if something good happens, your mind is going to
Speaker 1: assume that something good was behind it. And something bad happens, again,
Speaker 1: your mind's gonna make So this is a fascinating you know,
Speaker 1: we're in a world that's got a lot of randomness,
Speaker 1: a lot of luck, and we've got a little module
Speaker 1: in our brain that really struggles to understand what happened.
Speaker 1: So so to me the idea and you know, I know,
Speaker 1: you know, one of your guests is Phil Tetlock, who
Speaker 1: was horrific, and you know, Phil talks a lot about
Speaker 1: this idea of counter factuals is being being open obviously
Speaker 1: the future different futures, but also recognizing that the past
Speaker 1: we lived through was only one of many possible pasts.
Speaker 1: That's that's a very unnatural thing to think about, but
Speaker 1: it's also a very fertile thing to think about in
Speaker 1: terms of really understanding the complexity of the world. Warn
Speaker 1: Buffett's partner Charlie Monger is famous for saying, invert, always invert.
Speaker 1: When you're looking at a situation, Assume one of the
Speaker 1: main variables is either zero or a hundred and eighty
Speaker 1: degrees from what it is, and then see how things
Speaker 1: play out. And suddenly you end up with a very
Speaker 1: different set of possible outcomes. Uh. And and the past
Speaker 1: may not have been as as inevitable as as some
Speaker 1: people have suggested. There there are a number of things
Speaker 1: related to this that that are really fascinating. But but
Speaker 1: let's stick with the luck issue and let's try an inversion. So,
Speaker 1: so one of your comments was luck is a residual.
Speaker 1: It's what's left over after you've subtracted skill from the outcome.
Speaker 1: So let's invert that. Uh. If after a decade, I
Speaker 1: think it's safe to say that good luck and bad
Speaker 1: luck should probably cancel out. If you're a business person,
Speaker 1: or an athlete, or a or an investor, maybe not
Speaker 1: a dent. There'll be some outliers, but for a lot
Speaker 1: of them. So can we say that after luck cancels out,
Speaker 1: or you're left with this skill, I think that's a
Speaker 1: fair statement. Um. Now, I would say, when you think
Speaker 1: about luck. There are two different sort of categories where
Speaker 1: with luck is more independent a little bit like you described,
Speaker 1: and that would be athletes or or even money management
Speaker 1: probably realistic. But there are other other elements about luck
Speaker 1: that has a lot of a path dependence. So what
Speaker 1: happened before effects what happens next and so forth. And
Speaker 1: when you think about the success of music sales or
Speaker 1: book sales or any sort of social products, those social
Speaker 1: effects are actually, uh, make it a little bit of
Speaker 1: a different dynamic. So yeah, yeah, the answer is yes.
Speaker 1: Over the longer the sample size, the greater the sample size,
Speaker 1: the more we can we could get a signal from
Speaker 1: skill and less important luck is. So yeah, there's no
Speaker 1: question that's the case. So index thing is as big
Speaker 1: today as it's ever been. I think Vanguard is now
Speaker 1: coming up on four trillion dollars, black Rock is they're already.
Speaker 1: Is it safe to say that a lot of the
Speaker 1: public has looked at this process and said, you know,
Speaker 1: I'm kind of done with stock pickers. I'm just gonna
Speaker 1: index and not have to worry about it anymore. Is
Speaker 1: that a driving factor? And I think there's no question
Speaker 1: about that. And you know, for most people that's an
Speaker 1: absolutely correct prescription. Now, you know, that's an argument you
Speaker 1: can you can't take to the extreme. In other words,
Speaker 1: not every single person can index. There has to be
Speaker 1: some act of management in some way, shape or form
Speaker 1: to basically and by the way, they're creating a positive externality,
Speaker 1: which is basically, efficient markets were good prices that the
Speaker 1: indexers can take advantage of. But for most people that's
Speaker 1: really relevant. And you know, I was just looking at
Speaker 1: the numbers the other day. I mean, I know that
Speaker 1: Jack Bogel started the you know, his index fund in
Speaker 1: the seventies, but really for all intensive purposes, it really
Speaker 1: wasn't even going until sort of late eighties, early nineties, right,
Speaker 1: So this is a fairly new phenomenon we're seeing. And
Speaker 1: and the bulk of the assets at a place like
Speaker 1: Vanguard UH really have have come post financial crisis exactly,
Speaker 1: So so you know, it's interesting. And the other thing
Speaker 1: to think about when you think about that dimension is that,
Speaker 1: you know, active investing the zero sum game in the
Speaker 1: sense that UH, for any particular year, the winner's positive
Speaker 1: alpha have to be offset by losers negative alpha, right,
Speaker 1: just mathematically that has to be the case. So it's
Speaker 1: interesting if you if you say, sort of an analogy
Speaker 1: is sort of the poker table, right, So we have
Speaker 1: guys sitting around the poker table playing one night of poker.
Speaker 1: You know, if the people who are the less capable
Speaker 1: are walking out and indexing right, in effect, who's left
Speaker 1: sitting at the table the most skilled the most skilled players.
Speaker 1: So let's talk a little bit about the paradox of skill,
Speaker 1: and this sets right up the paradox of skills. So
Speaker 1: the paradox of skill, which is not my idea but
Speaker 1: I gave that name, says it at when activities have
Speaker 1: both skill and luck, which is most stuff in life.
Speaker 1: As skill increases, luck becomes more important, which doesn't seem
Speaker 1: to make sense, but they counterintuitive way to think about
Speaker 1: this is luck has a skill has two dimensions. One
Speaker 1: is absolute skill, but the second dimension is relative skill.
Speaker 1: And that's really what it's about when you're thinking about
Speaker 1: outperforming others. And what we've also seen is a collapse
Speaker 1: of relative skill. So say the fancier way to say,
Speaker 1: it's a standard deviation of skills gone down. So one
Speaker 1: examples in batting average in baseball or the the average
Speaker 1: batting average doesn't change all that much because it's picture
Speaker 1: hitter interaction, but the standard deviations collapse, and as a consequence,
Speaker 1: there aren't these sort of extreme hitters. No more, No more.
Speaker 1: Ted Williams, I'm Barry Ridults. You're listening to Masters in
Speaker 1: Business on Bloomberg Radio. My special guest today is Michael Mobisan.
Speaker 1: He is the head of Global financial Strategies at Credit Swiss,
Speaker 1: previously chief investment strategist at leg Mason, working with Bill
Speaker 1: Miller Uh Professor of Finance at Columbia Business School, and
Speaker 1: author of numerous books. Let's talk a little bit about
Speaker 1: how the great investors think and again another quote of yours,
Speaker 1: I'm gonna pull what is being wrong? Teach us about
Speaker 1: being right? It's a fascinating question. And by the way,
Speaker 1: there's a great book by Katherine Schulz basically Being Wrong.
Speaker 1: Of that title. Here's the interesting thing, Barry. We wake
Speaker 1: up every day and think that what we believe is right.
Speaker 1: What yours in your head is what you think is right.
Speaker 1: So then you wander into the world and you're confronted
Speaker 1: with the reality that all the stuff you believe may
Speaker 1: not be right. And the real big question is how
Speaker 1: do you deal with that? Right? And so there are
Speaker 1: some mult you and I disagree on something. There might
Speaker 1: be some ways I say, either Barry doesn't understand the facts,
Speaker 1: and if I just tell him the facts, he's going
Speaker 1: to come around to my point of view. It could
Speaker 1: be Berry's not quite smart enough to understand my nuanced
Speaker 1: point of view, or could be Berry's turned his back.
Speaker 1: You know, he doesn't get it anymore, and you know
Speaker 1: he's being, in a sense almost evil about this thing.
Speaker 1: So I think this idea of of recognizing, especially the
Speaker 1: world of investing right where where so important, so important
Speaker 1: because what happens is I mean, what is what is
Speaker 1: rational being? What does it mean to be rational? And
Speaker 1: the answer is that your beliefs map accurately to the world.
Speaker 1: That's a real challenge if the world's constantly changing, because
Speaker 1: that requires you to change your own views. And most
Speaker 1: of us, truth be told, are fairly cognitively lazy, would
Speaker 1: rather just sort of keep doing what we're doing. So
Speaker 1: that to me, when we say what are the characteristics,
Speaker 1: that's a big one. And being wrong teach you about
Speaker 1: being right is to say I need, yeah, I need.
Speaker 1: My map is off and I need to adjust it.
Speaker 1: The other thing I'll say, you know, you mentioned Charlie
Speaker 1: Munger a few moments ago. You know, Charlie Munger has
Speaker 1: got this great coro says, we got we did well
Speaker 1: Berkshire Health Hathway less by being brilliant and more by
Speaker 1: not screwing up a lot. And there's a little of
Speaker 1: that effect as well. So just by not making as
Speaker 1: many mistakes, yeah, you you, you will do better over time.
Speaker 1: So I think that's another aspect of the not being
Speaker 1: wrong dimension. You know, I'm fascinated now that we're in
Speaker 1: the midst of the political silly season, the idea of
Speaker 1: cognitive dissonance, that when a person has a wrong map
Speaker 1: and you can front them with in controvertable facts, Hey,
Speaker 1: crime is at decade lows, the number of police killed
Speaker 1: are at record lows relative to any time over the past,
Speaker 1: you know, thirty forty years. How the brain manages to
Speaker 1: either ignore the data or somehow deal with it because
Speaker 1: otherwise their whole worldview, uh falls apart. What does that
Speaker 1: How how does that manifest itself with investors? Yeah? I
Speaker 1: think that I think that people prefer not to change
Speaker 1: their view, right, and uh so they don't even want
Speaker 1: to entertain the evidence. But you know that if you
Speaker 1: if you said you know of conomin traversity's biases, you know,
Speaker 1: the one that probably shows up, well, maybe not the most,
Speaker 1: but certainly the top three would be confirmation bias, right,
Speaker 1: which is, once you've made a decision, you may have
Speaker 1: agonized over, but once you made a decision, you seek
Speaker 1: information that confirms your point of view. And you just
Speaker 1: avowed dismiss or discount, as you said, disconfirming evidence. And
Speaker 1: it's a very natural thing for all of us to do.
Speaker 1: And again, I think that characteristics of great investors are
Speaker 1: those who remain actively open minded, who remain open to
Speaker 1: the evidence, and who are willing and able to change
Speaker 1: their minds when the evidence suggests that they should. By
Speaker 1: the way in life, certainly with politicians, consistency is valued
Speaker 1: is a good thing, and if you're changing your view,
Speaker 1: you're called a flip flopper. Right in investing, if you're
Speaker 1: a flip flopper, you're if you're doing the right thing,
Speaker 1: that's what you need to do. It's not even a
Speaker 1: question of whether it's a good thing matter. So so
Speaker 1: that's another you know, that's that whole confirmation bias and
Speaker 1: this idea of consistency and the fact is once you
Speaker 1: most people have come up with a point of view,
Speaker 1: they'd much rather just stick with what they're doing than
Speaker 1: to change their views, even if it's money losing. Even
Speaker 1: if it's money losing, that that that's quite uh, that's
Speaker 1: quite a stuff of thing. So that that leads to
Speaker 1: a related question. So what are some of the bigger
Speaker 1: misconceptions about how investors should approach the market. What should
Speaker 1: they be doing that they're not, and what shouldn't they
Speaker 1: be doing that they are. You know, if saying I say, Baron,
Speaker 1: we talked a bit about this. For for most people,
Speaker 1: the answer is that they should probably using index funds
Speaker 1: or some sort of low cost approaches, having appropriately diversified portfolios,
Speaker 1: you know, doing all the things you're supposed to do
Speaker 1: rebalancing and tax efficiency and so forth. Right, So for
Speaker 1: for for a vast prenority people, that's probably the right
Speaker 1: way to go. If you're going to be an active manager,
Speaker 1: I would say the key thing is to think about
Speaker 1: what is your source of edge, What do you truly
Speaker 1: believe that you can do that's different than others, right,
Speaker 1: and and then organize your investment firm in order to
Speaker 1: do that. And then finally think a lot about portfolio construction,
Speaker 1: how you put together your bets in a way that's effective.
Speaker 1: Um so those it's it's really about having a really
Speaker 1: good process. It's also, as we were speaking a moment ago,
Speaker 1: it's about understanding and managing or mitigating the behavioral biases
Speaker 1: that are gonna inevitably show up. You know, way will
Speaker 1: avoid that, I know there is, but you try to
Speaker 1: weave this into your process. Maybe checkpoints will call them
Speaker 1: or stop points where you say, hey, am I thinking
Speaker 1: about this properly? And the final thing I'll say, which
Speaker 1: is a big issue, is that are you in an
Speaker 1: investment organization or any kind of organization that really is
Speaker 1: helping you versus hindering you? And I think that this
Speaker 1: is something again Charlie Ellis has talked a lot about
Speaker 1: is this business versus profession? Right? When when people start
Speaker 1: getting driven by raising assets under management or selling the
Speaker 1: hot product versus delivering access returns, that changes the nature
Speaker 1: of the basic proposition. I'm Barry Riddlts. You're listening to
Speaker 1: Masters in Business on Bloomberg Radio. My special guest today
Speaker 1: is Michael Mobisaw. He is of Credit Swiss and author
Speaker 1: of numerous books on investing, uh, human behavior psychology. Let's
Speaker 1: let's talk a little bit about emotions and decision making.
Speaker 1: And since since you mentioned Danny Kahneman, let's let's start
Speaker 1: with with one of the big subjects and again quote
Speaker 1: from you. We all operate with certain heuristics, rules of thumb,
Speaker 1: and predictable biases that emanate from those heuristics. Discuss Yeah,
Speaker 1: so you know Conomen and traverse ky Uh. Well, Conomen
Speaker 1: made these two incredible contributions to our understanding. One is
Speaker 1: the heuristics and biases, which we'll talk about in just
Speaker 1: a second, and the other is prospect theory. So how
Speaker 1: human behaviors depart systematically from what economic theories would mean,
Speaker 1: meaning people on the perfect profits seeking rational machines that
Speaker 1: economists describe them as precisely, and the fact that they
Speaker 1: depart in ways that are fairly systematic and predictable. So
Speaker 1: the heuristics and biases literature is really interesting because it
Speaker 1: says that, as you point out the word as rules
Speaker 1: of thumbs, so we all we operate with lots of
Speaker 1: rules of thumb for life. And what's good about rules
Speaker 1: of thumb? The answer is they save you a ton
Speaker 1: of time. And they're often right, keep you alive on
Speaker 1: the savannah Savanna, right. So that's all good, But the
Speaker 1: problem is that these heuristics often come with blind spots
Speaker 1: or these biases that can lead to suboptimal decisions. Let's
Speaker 1: talk about a couple of the big daddies of these biases.
Speaker 1: The first one is over confidence, and by the way,
Speaker 1: that tends to be more expressed than males and females.
Speaker 1: So just there's that's one where there's that tend to
Speaker 1: be a difference in gender. There's a lot of data
Speaker 1: that shows that female fund managers tend to app perform
Speaker 1: male fund managers because they are not afflicted with the
Speaker 1: same sort of testosterone poisoning that leads to over over
Speaker 1: confidence exactly. So how does over confidence manifest? And you've
Speaker 1: already given a little clue on that, right, there are
Speaker 1: two things. One is we we tend to project in
Speaker 1: ranges that are too narrow. We're we we think we
Speaker 1: understand the future much better than we actually do. Right,
Speaker 1: So that's one that's one aspect of it. The second
Speaker 1: is where you had the male female study, you decided
Speaker 1: is it men tend to trade a lot more, right,
Speaker 1: So they think they know what's going on, so they're
Speaker 1: much more active, and that just choose up performance in
Speaker 1: the form of costs. So over confidence. How do you
Speaker 1: mitigate that? The answer would be using things like base rates,
Speaker 1: which we talked about before, just saying what does the
Speaker 1: distribution of outcomes where does it look like historically? And
Speaker 1: if I overlay that on what I'm thinking about today,
Speaker 1: is a reason for me to stretch my expectations. So
Speaker 1: that's over confidence. And that's a really a big one.
Speaker 1: And even for money managers don't trade too much. Those
Speaker 1: are that's a that's the second one. UH framing is
Speaker 1: another really big one. And so the story here buries.
Speaker 1: If I present a story to you with mathematically one
Speaker 1: way mathematically, and then I present the same mathematical puzzle
Speaker 1: to you a different way, I can systematically get you
Speaker 1: to select one or the other right, And that just
Speaker 1: doesn't make any sense because people are actually just doing
Speaker 1: the math. They won't do it that way. So so
Speaker 1: let's let's take a look at an example of that.
Speaker 1: The one that I recall is the hypothetical UH illness,
Speaker 1: where if a doctor says bad news, you have fatal disease.
Speaker 1: Good news is a surgery. And here's the variable if
Speaker 1: the if this doctor says six chance of survival, if
Speaker 1: you have the surgery, a huge number of people do it,
Speaker 1: and the control group gets the bad news fatal disease,
Speaker 1: good news. Hey there's a surgery. One of three people
Speaker 1: don't survive the surgery, but you know it's the only
Speaker 1: choice we have, and that generates a totally different acceptance.
Speaker 1: Right precisely, so we're not we're not doing the math right,
Speaker 1: We're reacting with our affect or emotion because two out
Speaker 1: of three and one out of three or essentially the
Speaker 1: same numbers. If if it's one side as two out
Speaker 1: of three and the alternative is one out of three,
Speaker 1: it's the same transaction. So now you think about the world,
Speaker 1: to go out in the world and say how often
Speaker 1: are these framing effects influencing my own decisions? And you
Speaker 1: would have to guess that it's a pretty substantial amount
Speaker 1: of the time. So can we all systematically or be
Speaker 1: good at translating these different frames into more mathematical or
Speaker 1: more appropriate framework so allow us to make the right decisions.
Speaker 1: And it goes back to our discussion a few moments
Speaker 1: ago also about storytelling. Right if there's a little causality.
Speaker 1: And by the way, I mean, I was talking to
Speaker 1: Position about the same thing. He said. He said, you know,
Speaker 1: if I have a treatment that's fifty fifty in my office,
Speaker 1: some guy comes in with a f goes if I
Speaker 1: want the guy to use this, here's what I say,
Speaker 1: say Barry, it's do you understand that? And the guy,
Speaker 1: not the patient, nods his head say great. Last guy
Speaker 1: who's doing the treatment is doing great, and the guys
Speaker 1: like so the end of one, right, sample size of
Speaker 1: one people will go for right. And if he says not, Barry,
Speaker 1: the last guy who's doing it didn't work so well, right,
Speaker 1: then you know basically they all so it's it's this tagline, right,
Speaker 1: which is even though the numbers are the same, Hey,
Speaker 1: it's a coin to us that that that one example, Um,
Speaker 1: you know that that kind of goes back to back
Speaker 1: to Danny Kahneman, the whole issue of anchoring. If we
Speaker 1: toss out a number high enough when you're starting the negotiation,
Speaker 1: everybody is magically drawn because you're trying to make sense
Speaker 1: of that number and your brain lops in on it. Yeah,
Speaker 1: and anchor is another one I was going to mention
Speaker 1: and I do this with my students at Columbia Business
Speaker 1: School and it's awesome. Right. So I say to him,
Speaker 1: very first day class, I say, right down the last
Speaker 1: four digits of your phone number, right, so every no problem,
Speaker 1: kids do that. And I say, second question, I got
Speaker 1: this from Danny directly. Uh, the number of doctors in
Speaker 1: Manhattan burro of Manhattan higher or lower than that number? Right?
Speaker 1: They usually they know it's gonna be a little bit higher.
Speaker 1: And I say, write down your estimate of the number
Speaker 1: of doctors. And just as predictable as night follows day,
Speaker 1: the people who have high phone number last, which is high,
Speaker 1: guess many more doctors, and the people will low digits
Speaker 1: on their phone number. Right. And so a couple of
Speaker 1: things should be obvious about that number. One is they
Speaker 1: the students know there's no relationship between their phone number
Speaker 1: and the number of doctors. And had I asked those
Speaker 1: same questions in reverse order, tell me the number estimate
Speaker 1: of doctors and then tell me your phone number, you
Speaker 1: get totally different answers. So you know that this is
Speaker 1: an effect. And I think the point that that Danny
Speaker 1: Conmon makes is that this is fairly pernicious in the
Speaker 1: sense that you can do an hour lecture on anchoring
Speaker 1: and do another experiment on it and it still works. Right.
Speaker 1: So in other words, it's like your mind. It's a
Speaker 1: really hard one for your mind to get around. And
Speaker 1: you mentioned you know, M and A, and this shows up.
Speaker 1: Fifty two weeks is high levels for the markets, all
Speaker 1: these you know, round numbers for the down all these
Speaker 1: sorts of things show up. You know, what does what
Speaker 1: does it mean? The answer is basically nothing, but it
Speaker 1: has these sort of uh, these anchoring effects. So yeah,
Speaker 1: that's another one. So so there's a very rich literature
Speaker 1: on this. And again I say to people, really important
Speaker 1: understand it. Uh. And then as important is to try
Speaker 1: to think about are there ways again can I offset
Speaker 1: these forces? What is the antidote two overconfidence to framing,
Speaker 1: to anchoring, and how do I try to try to
Speaker 1: bring those to bear when I need to to make
Speaker 1: good decisions. So let's talk about one of my pet peeves,
Speaker 1: which which you have discussed many times, which is I
Speaker 1: get miffed every time someone is on TV and blaming
Speaker 1: uncertainty for the economy, the stock market for whatever. Um.
Speaker 1: I always think that's a dodge, And I really like
Speaker 1: the way you described it, uh, talking about whether or
Speaker 1: not the underlying distribution of outcome is undefined, UH, and
Speaker 1: what the risk distribution looks like. In other words, when
Speaker 1: you spin a Roulette wheel or roll a pair of dice,
Speaker 1: you may not know what numbers are going to come up,
Speaker 1: but the set of possible outcomes is well known in advance.
Speaker 1: What is it about uncertainty that leads people to so
Speaker 1: totally misunderstand that? Yeah, I don't know, and I think
Speaker 1: that you know this is by the way, this concept
Speaker 1: that you've articulated came from Frank Knight. So it's been
Speaker 1: an idea that's been around for mathematicians. Yeah, I think
Speaker 1: it was an economist years ago. So it's been around
Speaker 1: for a long time. And you know, I think it's
Speaker 1: a debate of you know, sort of an ongoing debate
Speaker 1: among economists and philosophers and so forth. But no, exactly
Speaker 1: what you said, So, risk is this idea that you
Speaker 1: don't know the outcome, but you know all the possible
Speaker 1: out as you said, to rule that wheel or the
Speaker 1: turn of car or what have you. And uncertainty is
Speaker 1: where we don't know the outcome, but we don't really
Speaker 1: know what the underlying distribution. So that's in character a
Speaker 1: very very different thing. War invasion of Iraq is a
Speaker 1: good exactly, But there's some interesting I mean, even some
Speaker 1: of these things you know not seemte lab is very
Speaker 1: well known for talking about things like black swans, but
Speaker 1: you know, in reality, most things in life are really
Speaker 1: not in the black swan realm. They're more in the
Speaker 1: gray swan realm. So for example, earthquakes, you know they
Speaker 1: follow power law, you can't really predict them, but we
Speaker 1: know what the distribution looks like, right, so you know, okay,
Speaker 1: So that so you have a sense of what's going on.
Speaker 1: So the question is whether these things are Are they
Speaker 1: practical in your day to day life. I think the
Speaker 1: answer to that is yes. But the second thing, and
Speaker 1: also I think this is an issue that we're we
Speaker 1: were in agreement on, is if you ask the question
Speaker 1: our markets risky or our markets uncertain? Now, if they're risky,
Speaker 1: we can try out a bunch of mathematics to model them.
Speaker 1: If they're not, or they have components of uncertainty, then
Speaker 1: we're not using the right tools. And I think I
Speaker 1: would just basically say most of the standard finance is
Speaker 1: based on normal distributions. Whenever you utter phrases like alpha, beta, uh,
Speaker 1: standard deviation. Right, you're using the language of risk to
Speaker 1: describe a system which may have elements and maybe big
Speaker 1: elements of uncertainty. So that to me is another really
Speaker 1: interesting disconnect um. And look, it may work of the time,
Speaker 1: but that one percent may be really challenging. So I
Speaker 1: think you're writing like you said, I mean, uncertainty is
Speaker 1: a phrase. It's a catch all, right, So it basically
Speaker 1: means I don't know what's going on, you throw it
Speaker 1: into uncertainty. But but I think that I found that distinction,
Speaker 1: at least personally, to be a useful one to make
Speaker 1: as as I try to navigate the world. We've been
Speaker 1: speaking with Michael Mobison, head of Global Strategies at Credit Swiss,
Speaker 1: author of such books as The Success Equation, Think Twice
Speaker 1: and more than you know. If people want to find
Speaker 1: your writings, where's the best place for them to to
Speaker 1: either get your white papers or any of your other writings. Um, well,
Speaker 1: I have a website which is Michael Mobison dot com.
Speaker 1: So you'll probably look up the spelling, but if you
Speaker 1: google it you'll find it probably one way or another.
Speaker 1: And um, the other thing is probably Twitter is another
Speaker 1: you know at MG Mobison, and so a bunch of
Speaker 1: the stuff tends to find its way onto Twitter one
Speaker 1: way or another. So those are probably the two best horses.
Speaker 1: If you enjoy this conversation, be sure and stick around
Speaker 1: and check out the podcast extras, where we keep the
Speaker 1: tape rolling and continue chatting about all things UH, decision
Speaker 1: making and cognitive. Be sure and follow my daily column
Speaker 1: on Bloomberg dot com or follow me on Twitter at
Speaker 1: rit Halts. I'm Barry Rit Halts. You've been listening to
Speaker 1: Masters in Business on Bloomberg Radio. Welcome to the podcast portion. Uh, Mike,
Speaker 1: thanks so much for doing this. You know you're one
Speaker 1: of our few repeat guests. And I listened to the first,
Speaker 1: uh first podcast you and I did. You were literally
Speaker 1: one of the first dozen or so podcasts, and I
Speaker 1: have to tell you, I was awful, but you were great.
Speaker 1: So UM, I would like to think that in the
Speaker 1: ensuing one hundred podcasts in the ensuing two years, I've
Speaker 1: developed some skill at shutting up, listening in and asking questions.
Speaker 1: Although that's arguable this there's a lot of questions that
Speaker 1: that we missed. I wanna jump back to some of them,
Speaker 1: but before I do, I have to come back to
Speaker 1: the uncertainty name. So I've been using your definition, which
Speaker 1: is based on the earlier mathematical definition. But the footnote
Speaker 1: to that that I wanted to share with you is
Speaker 1: the reason. My belief as to why the reason people
Speaker 1: fall back on it is we talk about how our
Speaker 1: expectations map or don't to reality. My belief is that
Speaker 1: most people's sixty degree in time and space worldview doesn't
Speaker 1: map remotely close. There are just little areas where almost
Speaker 1: accidentally it's right, and we lie to ourselves so successfully
Speaker 1: that we understand otherwise how do you even cross the street.
Speaker 1: So there's this bit of subconscious self deception that allows
Speaker 1: us to operate under normal circumstances. And there are moments
Speaker 1: of terror when it's revealed to us by the events
Speaker 1: that we really are completely um poorly mapped, let's call
Speaker 1: it that. And that's when people tried out the uncertainty defense.
Speaker 1: And you see it during financial crisis, you see it
Speaker 1: during geopolitics. It's a way of saying, all right, I
Speaker 1: will admit temporarily that I have no idea what's going on,
Speaker 1: and soon I'll be able to go back to deluding
Speaker 1: myself that I have a good handle. And we see
Speaker 1: it anytime people talk about the future, the the confidence
Speaker 1: or lack thereof as to here's what the next six
Speaker 1: months or a year it was gonna look like. Phil
Speaker 1: Tetlock does such a great job on on taking that apart. Absolutely.
Speaker 1: You know, there's a there's a great book by Dan
Speaker 1: Gilbert and Stumbling on Happiness where he makes the point
Speaker 1: that mentally healthy people are mildly cognitively delusional. So you
Speaker 1: are mentally healthy, you have a little bubble around yourself
Speaker 1: thinking that you, you know, know a little bit more
Speaker 1: than you do, your a little better looking than you
Speaker 1: actually are, and so forth, hence all the other confidence
Speaker 1: and yeah, exactly, and and in fact, people who are
Speaker 1: mildly clinically depressed actually have a much more accurate view
Speaker 1: of the world than the rest of us. Now, that's
Speaker 1: very funny, and that that explains everything that's going on
Speaker 1: in Bridgewater these days. With their radical transparency, I get
Speaker 1: the sense that they probably are mildly clinically depressed, but
Speaker 1: have a more accurate view of the world. Be couse,
Speaker 1: these guys call each other out for everything, it's quite amazing. Right.
Speaker 1: So so the what's good about this mild delusion often
Speaker 1: as it gets people out of bed in the morning. Right.
Speaker 1: So in other words, you if you think you're a
Speaker 1: little better than you are and so forth, you sort
Speaker 1: of you go at it again, and if you really
Speaker 1: had a more accurate view of the world, you might
Speaker 1: just stay in bed. But it is, it is this
Speaker 1: intriging thing. So so the key is for that that
Speaker 1: mentally healthy condition not to be debilitating your decision making
Speaker 1: it to your points. So you in the world of investing,
Speaker 1: you do have to have an accurate map. You have
Speaker 1: to have you have to have a good belief updating system,
Speaker 1: you have to be actively open minded, you have to
Speaker 1: consider different points of view, and all those things take
Speaker 1: a lot of cognitive energy that most of us, truth
Speaker 1: be told, would rather not expend or we'd rather do
Speaker 1: something else. Right. So so that's that's another thing. Who's
Speaker 1: what distinguishes great decision makers, not just investors, but in
Speaker 1: sports team managers or in business from the rest of us.
Speaker 1: And the answer is they tend to be those folks
Speaker 1: that are more malleable cognitively than the rest of us.
Speaker 1: In super foecasters. Tet Luck goes over the group of
Speaker 1: people who approached decision making almost with the checklist of
Speaker 1: what do we know to be true, what's relevant, what
Speaker 1: can we rely on? Where a blind spots before they
Speaker 1: even start the process of making So any of their
Speaker 1: so cold forecasts really are just more educated guesses than
Speaker 1: the rest of us lazy civilians. Engaging. Yeah, and the
Speaker 1: other thing I liked about super forecasters is that you
Speaker 1: know they're not the folks are making those good forecasts
Speaker 1: are not geniuses. I mean, they're they're brighter than average,
Speaker 1: but they're not geniuses, right, And like you said, it's
Speaker 1: much more about their systematic approach to making forecasts. And
Speaker 1: I think what's encouraging for the rest of us is
Speaker 1: that many of those behaviors can be emulated, many of
Speaker 1: those behaviors can be copied. Right, So so there's some hope,
Speaker 1: at least, even if I can't change anybody's I Q,
Speaker 1: that maybe we can contribute to their quality their decision making.
Speaker 1: So and better decision making would certainly go a long way.
Speaker 1: You know, I don't recall if we mentioned this last time,
Speaker 1: but I wanted to bring it up. Did we talk
Speaker 1: about Wall Street trading desks and why they're populated with
Speaker 1: college athletes that has that? Has that ever come up
Speaker 1: with us? No? I don't think so, have you? Well,
Speaker 1: so in my experience, I've noticed half of the desks
Speaker 1: on the street people played ball in college. Have you
Speaker 1: witnessed something similar? Yeah, you're young. Yes, so it seems
Speaker 1: like a lot of more lacrosse players. Yes, lacrosse. Um, well,
Speaker 1: usually because uh, there's only so many football, baseball, basketball players,
Speaker 1: and and but you see a lot of that, you
Speaker 1: see track. So my pet thesis on that is something
Speaker 1: that is your paradox of skill, which is, if you're
Speaker 1: playing an n c A sport, pick any division in
Speaker 1: Division one, A, Division two, any any any team can
Speaker 1: beat any other team on any other game the weekend.
Speaker 1: It's not you know, you don't end up or you
Speaker 1: very rarely end up with a dominant team that goes
Speaker 1: sixteen and oh for the uh, you win some, you
Speaker 1: lose some. And because of the skill level is fairly
Speaker 1: that tight range like batting averages, a bad call, a
Speaker 1: lucky bounce, an injury, and any team can beat any
Speaker 1: other team in any given game. So after you worked
Speaker 1: your butt off all week and then you go and
Speaker 1: then some bead you know, bounce loses the game for you.
Speaker 1: You have to get up Monday morning and start your
Speaker 1: routine all over again. Which describes sports as as accurately
Speaker 1: as it does working on a trading desk. I mean
Speaker 1: I buy all that. I mean I think that a
Speaker 1: lot of this athletes on trading desks. Is also the
Speaker 1: fact that, uh, they're often especially around here East Coast
Speaker 1: schools for the most part. Um also a lot of
Speaker 1: the lums. So there's a whole little pipeline, you know,
Speaker 1: in terms of what I could see the athletes you know,
Speaker 1: typically right, they work together, they were they're used to
Speaker 1: hard discipline, team or stuff. Is true. So um, yeah,
Speaker 1: so I think that's all. I buy all that. So
Speaker 1: so let's take before we get down to our favorite questions.
Speaker 1: Let's let's let's go through some of the questions that
Speaker 1: that we missed. Um, we've we've talked. Let's let's talk
Speaker 1: a little bit about probabilities and some interesting other factors.
Speaker 1: Another quote of your success in a probabilistic field requires
Speaker 1: waiting probabilities and outcomes. That is an expected value mindset.
Speaker 1: Why is that? Let's describe that a little bit. You know,
Speaker 1: it's a well because again, the future has many possible outcomes,
Speaker 1: and what you're really trying to do is figure out
Speaker 1: situations where you have some sort of advantage or some
Speaker 1: sort of an edge, where if you were able to
Speaker 1: play the world a lot of different times, you would
Speaker 1: win a lot more times than you would lose. And
Speaker 1: and of course there are scenarios where you would lose,
Speaker 1: but you would win many more times than you would lose.
Speaker 1: And the question then becomes, are there ways that we
Speaker 1: can thoughtfully assign probabilities and outcomes? But I think as
Speaker 1: a structured way of approaching any almost any kind of problem,
Speaker 1: it works. Right. So you might say even a more
Speaker 1: mundane thing like yeah, you're the general manager of the
Speaker 1: Yankees now or the Mets or whatever it is, and
Speaker 1: you have to find athletes, uh to play your team.
Speaker 1: You have to draft somebody. You know, you don't really
Speaker 1: know what that guy is about. You don't really have
Speaker 1: a completely known entity. It's a probabilistic view. But if
Speaker 1: you say, guys like this of this age and this
Speaker 1: ability have played certain way x percent have done well, right,
Speaker 1: so that's a probability and some sort of an outcome,
Speaker 1: and again they're gonna be some variance from that, but
Speaker 1: that's probably the right way to think about it. And
Speaker 1: then that allows you to understand how much you should
Speaker 1: probably wanting to pay for the guy right in terms
Speaker 1: of contract and so forth. I think that idea spills
Speaker 1: over to most things we look at, So it's just
Speaker 1: it is just getting into this constant discipline understanding. I
Speaker 1: know the range of outcomes, I know the probabilities or
Speaker 1: some sense of those things, and I'm only gonna bet,
Speaker 1: by the way, when the odds are really good and others.
Speaker 1: I can make a lot of money if I'm right,
Speaker 1: and I don't lose so much fun wrong. That's what
Speaker 1: made Money Bull so fascinating is the underlying expectations for
Speaker 1: the ability was not based on provable, quantified data, but
Speaker 1: all those heuristics and rule of thumbs that had basically
Speaker 1: dominated baseball for a century. And I found that book
Speaker 1: as well as the movie to be so fascinating because
Speaker 1: suddenly you have an industry that wakes up and realizes, oh,
Speaker 1: we've been doing this wrong for a century. Yeah, and Barry,
Speaker 1: I think that this remains remarkably, remains fairly pervasive. I
Speaker 1: think it's less true and Major League Baseball because everyone's
Speaker 1: read the book and has their analytical staffs. But you
Speaker 1: look at other professional sports, by the way, you know,
Speaker 1: things like the NFL, where they're big dollars at stake,
Speaker 1: they're still doing some things that don't make a ton
Speaker 1: of sense. The NHL right where it's a much more
Speaker 1: difficult analytical task, a lot of guys making decisions that
Speaker 1: don't make a lot of sense. So continues to be
Speaker 1: the case out there generally speaking. And a lot of it,
Speaker 1: by the way, is that people grew up with a sport,
Speaker 1: so they rely on their own experience, They rely on
Speaker 1: their own view of the world. It goes back before
Speaker 1: their frame or reference right, and they can't expand their
Speaker 1: you to understand different alternative points of view, and that
Speaker 1: can be really problematic. I am not a huge sports
Speaker 1: book fan. I find them to be predictable and tedious.
Speaker 1: But one that I always recommend to people is the
Speaker 1: former UH coach of the Giants, Tom Conklin, did a
Speaker 1: book called Earned the Right to Win, and one of
Speaker 1: his linebackers tells the story, and this guy goes on
Speaker 1: to have an all star career and he worked with
Speaker 1: Conklin for a few years, and a lot of the
Speaker 1: athletes chafed at Conklin's version of moneyball, So he would
Speaker 1: run a whole bunch of stats. What does this team
Speaker 1: do when it's third and one? What does this team
Speaker 1: do on on you know, first deep in their own territory.
Speaker 1: What they came up with. You're not gonna come up
Speaker 1: with every parameter people can possibly remember that, but they
Speaker 1: came up with enough of them. And this this linebacker
Speaker 1: is whose name escapes me at the moment, chafed and
Speaker 1: chafed and chafed about it, eventually adapts to the system
Speaker 1: and sort of subconsciously adapts to it. Years later, he's
Speaker 1: traded and he's playing for a different team and it's
Speaker 1: third and one, and he says, all right, what do
Speaker 1: these guys do on third and one? And he goes,
Speaker 1: oh my god, I don't know. Conklin was right all
Speaker 1: these year year and actually reached out to him and said, hey,
Speaker 1: you're right. Sorry, I gave you grief about it. It's
Speaker 1: it's one of those things. But stop and think about
Speaker 1: how many sports haven't adapted that, and how much money
Speaker 1: is involved. It's really quite fascinating. So speaking of not
Speaker 1: adapting and and how much money is involved. UM, I
Speaker 1: love this data point which my head of research, Mike Batnick, uncovered,
Speaker 1: and it's it's fascinating. Since two thousand and five, actually,
Speaker 1: from the period from two thousand five to two thousand thirteen,
Speaker 1: approximately fifty thousand new global funds were launched. That's not
Speaker 1: total funds. That's the number of new mutual funds, ETFs,
Speaker 1: hedge funds, etcetera. Were launched. Fifty seven thousand. It's ten
Speaker 1: times in a number of stocks in the US. What
Speaker 1: does this tell us about our abilities to distinguish between
Speaker 1: skill and luck. I don't know if it's about skill
Speaker 1: and luck as much as it is about um the
Speaker 1: idea of marketing and raising assets. And uh, you know
Speaker 1: before we talked a few moments before about the really
Speaker 1: powerful trend and it's accelerated since the financial crisis of
Speaker 1: a move into passive investing. And some of that's been
Speaker 1: index funds, but a lot of it's been E t
Speaker 1: f s as well. And uh, but not but there
Speaker 1: isn't t s, but there are others, so they're fun.
Speaker 1: So so I think there are a couple of things
Speaker 1: that you know, this is what Charlie Ellis talked about
Speaker 1: the difference between the profession and the business, and the
Speaker 1: professions about delivering and and Jack Bogo and others, the
Speaker 1: professions about delivering access returns. The business is about selling
Speaker 1: people what is in demand today. And going back to
Speaker 1: even five, what happened is we had a huge run
Speaker 1: up and energy. Guess what happened. Zillions of energy funds
Speaker 1: got launched. We had gold that was hot for a while.
Speaker 1: What happened, zillions of gold funds got introduced. You know.
Speaker 1: Then then the markets go down. People go, I need
Speaker 1: given in, I need yields, and now you have yield funds. Right,
Speaker 1: So whatever worked in the last two or three years
Speaker 1: is what people want to do now, and the marketers
Speaker 1: are more than happy to accommodate that. And that's the business,
Speaker 1: the business of finance, right and so that you know,
Speaker 1: So I mean these on on the you know, I
Speaker 1: don't even know what to say about a statistic like
Speaker 1: this is it seems mind blowing, and you know, not
Speaker 1: not a lot of these guys can have a lot
Speaker 1: of assets and so forth. But that is marketers trying
Speaker 1: to take advantage of recent asset class performance with an
Speaker 1: overlay probably of this move to passive and and to
Speaker 1: me so so and right and for investors, I think
Speaker 1: for our listeners, the main thing we want to emphasize
Speaker 1: is that it's just be very careful about. Uh, you
Speaker 1: know what has done well in last two years is
Speaker 1: you know again what you're gonna want. You're gonna say, hey, gee,
Speaker 1: these guys have made a lot of be careful about
Speaker 1: that idea because if it's done well or it's gone
Speaker 1: out for any particular set of circumstances, very unlikely those
Speaker 1: circumstances will repeat in the next twenty four, three, six,
Speaker 1: five years or whatever it is going forward. Mean reversion
Speaker 1: is a alive and well yep, to say the least.
Speaker 1: Um So another quote of yours I really like, along
Speaker 1: with the suggestions you have for dealing with this, is
Speaker 1: different levels of skill and of good and bad luck
Speaker 1: are the realities that shape our lives. Yet we aren't
Speaker 1: very good at distinguishing between the two. So that leads to, uh,
Speaker 1: the immediate question, how can we improve at at separating
Speaker 1: and identifying skill from luck, not only amongst ourselves, but
Speaker 1: at the people we hire, whether it's an investment manager
Speaker 1: or someone in a firm, a business, how can we
Speaker 1: separate skill from luck as a as a personal uh
Speaker 1: approach to the world of finance. So it's an amazing question. Uh.
Speaker 1: The first thing I would start with is sort of
Speaker 1: the centerpiece of the book. The success equation is what
Speaker 1: we call the luck skill continuum. So you might imagine
Speaker 1: sets of activities that are all luck, no skill, right,
Speaker 1: roulet wheels, lotteries, those types of things, and you might
Speaker 1: have a system for the lottery. I have these numbers.
Speaker 1: We'll talk about that later. And then on the other extreme, UH,
Speaker 1: all skill, no luck, right, So you know, you think
Speaker 1: about Olympic sprinters, the best guy is gonna win. Luck
Speaker 1: may play a tiny role, but for the most part,
Speaker 1: it's mostly skilled. Chess is probably over there. And then
Speaker 1: you can think about, you know, how you might even
Speaker 1: qualitatively place activities on that continuum and why you would
Speaker 1: play some And I think just that mental exercise in
Speaker 1: and of itself gives you a lot of insight. And
Speaker 1: by the way, tying into the comment on mean reversion,
Speaker 1: if you're on the luck side of the continuum, And
Speaker 1: by the way, even like performance of the markets are
Speaker 1: less from year to year, is basically random. It tells
Speaker 1: you there's complete reversion to the mean. In other words,
Speaker 1: outcomes that are far from marverage will be followed by
Speaker 1: an outcome it's expected to be very close to the average.
Speaker 1: And and and when there's all skill, no luck, there's
Speaker 1: basically no reversion to mean at all. Right, we sprint
Speaker 1: against usine bolt, he's gonna win every time we run, right, Um,
Speaker 1: so so that's another that's another really interesting. So so
Speaker 1: then you say, well, how do we identify skill? A
Speaker 1: couple of things come to mind on this. The first
Speaker 1: really fat. There's a fascinating strand of research by a
Speaker 1: guy named Boris Groisberg at Harvard Business School, and he
Speaker 1: wrote a book called Chasing Stars, and the idea is
Speaker 1: that when stars from one organization go to the other
Speaker 1: to another, their performance, almost without failure, degrades. Now, there
Speaker 1: could be a couple of reasons for that. The first
Speaker 1: is just classic mean reversion. So someone's been the star,
Speaker 1: they've been lucky, and so that doesn't carry over. So okay,
Speaker 1: we'll check that one off. But the second was that
Speaker 1: people massively underestimate the role of their organization in their
Speaker 1: own success, so they think that they're the one that's
Speaker 1: carrying the weight, but in fact it's everything that's going
Speaker 1: on around them. So that's the first thing, is just
Speaker 1: to be mindful of Hiring stars seems to be the
Speaker 1: path to quick success, but the studies on this, especially
Speaker 1: in the world of finance, demonstrate that that's actually not
Speaker 1: such a good thing. So the last thing I would
Speaker 1: say is when I if I were trying to identify skill,
Speaker 1: what I would A lot of things I would I
Speaker 1: would really want to do things that get at people's behaviors,
Speaker 1: because in interviews you tend to skim along the surface
Speaker 1: and see if you like the person. What you really
Speaker 1: want to do is press into their actual behaviors how
Speaker 1: they actually make decisions. So if I were interviewing a
Speaker 1: portfolio manager or an analyst, I would truly want to say, like,
Speaker 1: how do you value businesses? How do you think about strategy?
Speaker 1: Not just high level, get into the nuts and bolts
Speaker 1: of how they do that, to see what their actual
Speaker 1: processes are, what they're described their actual behaviors, and that's
Speaker 1: the best indication as to whether they're going to continue
Speaker 1: to do that. So so that's a couple of ideas. First,
Speaker 1: just the raw overarching messages is hard, right, And second
Speaker 1: is if you're gonna, if you do have someone you're
Speaker 1: trying to talk to, you is just to do as
Speaker 1: good a job as possible figuring out their actual behaviors,
Speaker 1: not just gimming along the surface of superficial questions. And
Speaker 1: you said something else that I thought it was similarly fascinating,
Speaker 1: which was, when you're trying to determine if something is
Speaker 1: the results of skill or luck, ask yourself the simple question,
Speaker 1: can you lose on purpose? And I found that to
Speaker 1: be quite fascinating. I love that, And you know, I
Speaker 1: don't want I don't want to take credit for that either.
Speaker 1: That came from the poker the poker community, but it's
Speaker 1: an interesting question. I I pose it to my students.
Speaker 1: On January one of every year, you say, give me
Speaker 1: twenty five stocks you're convinced will beat the SMP five.
Speaker 1: Let's get the list right, and we're gonna freeze it
Speaker 1: for the full year. Now, let's get January first. Give
Speaker 1: me the twenty five stocks you're convinced will underperform the market.
Speaker 1: You're sure you would short them with your own money,
Speaker 1: and let's tale up the results of in the year
Speaker 1: and by the way. If you can do the latter,
Speaker 1: you can do the former, right now, So as you know,
Speaker 1: I mean, your sense on this would be, it's really
Speaker 1: hard to beat the market. It's also really hard to
Speaker 1: do worse than the market on purpose, given the same constraints, right,
Speaker 1: given the same number stocks and so on and and so forth,
Speaker 1: you can you can do worse by treating. But that's
Speaker 1: a fascinating concept, right, And that just tells you that
Speaker 1: investing again not because of a lack of skill, rather
Speaker 1: because of a surfeit of skill, which means that everything
Speaker 1: is priced in. It's really hard to beat the market.
Speaker 1: You know. At the end of the second quarter and
Speaker 1: the first half of the year, there was a I
Speaker 1: want to say, wool Street Journal article. I don't know
Speaker 1: if this is consistent over time, but they had noted
Speaker 1: that the first half of the lowest ranked stocks amongst
Speaker 1: the analyst community had significantly outperformed the top rank stocks
Speaker 1: and the best stocks. I wonder if that's something that's
Speaker 1: consistent over time. Yeah, I mean, and I would say
Speaker 1: that seems that feels very consistent what we know to
Speaker 1: be the value factor. Right, So we talked about different
Speaker 1: factors that contribute to returns, and we know that over
Speaker 1: a long period of time, value factors works are basically
Speaker 1: cheap stocks we could say price to book or whatever
Speaker 1: it is, and those tend to be unloved. I mean,
Speaker 1: so that there's probably some relationship between what the analysts
Speaker 1: don't like and what's cheap, and those tend out perform.
Speaker 1: And when we say out perform, we don't mean just
Speaker 1: you know, doing better than the market. It's adjusted for risk. Right,
Speaker 1: So these are yeah, So that's a really interesting um observation.
Speaker 1: And again it goes back to our discussion about fundamentals
Speaker 1: and expectations. Right. People want to buy what's doing well,
Speaker 1: and they want to sell what's doing poorly, and they
Speaker 1: don't distinguish between what's priced in and what's likely to unfold.
Speaker 1: And you had also written about the morning star five
Speaker 1: star versus one star ratings and that funds that are
Speaker 1: five star come back next year they're not five star anymore.
Speaker 1: And the reverse funds that are at the bottom of
Speaker 1: the scale, the one star funds the following year, they're
Speaker 1: not ones. So what does that tell us about mean reversion?
Speaker 1: Is this just something that there's no escaping and and
Speaker 1: that's it. In the investment world. Right, So the degree
Speaker 1: to which UH investing is a luck laden activity. And
Speaker 1: again over short periods of time, certainly a year. Uh,
Speaker 1: it's got huge doses of luck. Um As I said,
Speaker 1: it's on the luck side of the continuum. That's rapid
Speaker 1: reversion to the mean. Right. So the best estimate of
Speaker 1: the expected value some measure much closer to the average
Speaker 1: of the population. So yeah, and by the way, I
Speaker 1: mean those morning stars, you know, these morning start their
Speaker 1: forced curve. So the vast majority of company funds or
Speaker 1: three star and then the two and four less and
Speaker 1: than one five or the extremes. So right, the best
Speaker 1: estimate for a five star once are fund the subsequent
Speaker 1: years basically three And that's roughly what we see my
Speaker 1: uh A little digression. There was a study that I
Speaker 1: give Morning Star credit for releasing it. Someone said, let's
Speaker 1: forget about the star rating and only look at one factor,
Speaker 1: and they went through all the price the book either
Speaker 1: if we can only look at one factor, what would
Speaker 1: it be? And more Star themselves discovered we look at
Speaker 1: the cost factor of owning that funds. If you know
Speaker 1: nothing else, but by the cheapest funds you're ahead of
Speaker 1: of the five star rating, they kind of eliminated their
Speaker 1: own for existence. I think they wish that that memory
Speaker 1: of that would go away, but I seem to bring
Speaker 1: it up every six months or so. It's quite astonishing,
Speaker 1: isn't that it is? And that's consistent with everyone we've
Speaker 1: been talking about, and you know that's That's the other
Speaker 1: thing is it's interesting when you think about fees, and look,
Speaker 1: I don't think anybody begrudges paying fees, but you know,
Speaker 1: when you're paying a fee of let's say, for an
Speaker 1: average metual fund on Hunter twenty five basis points in
Speaker 1: a world where the markets up, you know, ten fifteen
Speaker 1: percent a year as we saw nobody, it rolls right
Speaker 1: off your back. But now when you have effectively zero
Speaker 1: real interest rates in the States, you have you know,
Speaker 1: negative overseas, never the negative overseas, and it's hard to see,
Speaker 1: you know, X returns for the equity markets vastly higher
Speaker 1: and certainly in the double digits. Uh, those those numbers
Speaker 1: feel they sting a lot more. And then you look
Speaker 1: around and there are certain vanguard funds that are six
Speaker 1: basis points on the Admiral Institutional Clash d f A
Speaker 1: also really low fees, it becomes more and more challenging
Speaker 1: to justify. Maybe that's why there's fifty seven thousand new funds.
Speaker 1: Something will will get hot and stick, and maybe it's
Speaker 1: just part of the culling process. Hey, throw it all
Speaker 1: against the wall, see what what survives, and we can
Speaker 1: get rid of the rest. And I don't think that's
Speaker 1: I mean, I think the fifty seven thousand numbers obviously
Speaker 1: a huge number, and that's probably what is somewhat new.
Speaker 1: But this this idea of rolling out products of what's
Speaker 1: hot is it's certainly not a not a new thing. Right.
Speaker 1: So before I get to my favorite questions, I have
Speaker 1: to ask you one more question that really sums up
Speaker 1: a lot of of what we've been talking about and
Speaker 1: applying it to um the world of investing. So we
Speaker 1: all know who the great managers were, and and we
Speaker 1: always seem to discover these folks after their best years.
Speaker 1: Is it possible to identify skilled managers in advance? Is
Speaker 1: that something that's realistic for the average pension fund, the
Speaker 1: average institutional investor, or or are we just always chasing
Speaker 1: our tel It's a great question. I think it's really
Speaker 1: difficult to do, but there may be some things you
Speaker 1: can do to skew the odds a bit in your favor. So,
Speaker 1: if I wanted to be optimistic or give that optimistic
Speaker 1: side of the story, a couple of things I would say.
Speaker 1: The first is going back to a discussion we had
Speaker 1: a few moments ago, which is does that investor have
Speaker 1: a thoughtful process, analytical process and portfolio construction related? Are
Speaker 1: they mindful of the behavioral issues? And do they have
Speaker 1: an organization that tends to be the proper type of organization?
Speaker 1: But there are a couple of the things that will
Speaker 1: also skew your odds in your favor. Um. The first,
Speaker 1: interestingly is the age of the money manager, and UH
Speaker 1: research suggests that the optimal age for a money manager
Speaker 1: is in his or her early forties. Really so UM,
Speaker 1: so that's one thing. Another would be, UH, if they've gone,
Speaker 1: if they're bright people and silly, as it sounds, people
Speaker 1: that go to better schools or better SAT scores on average,
Speaker 1: or better investors. Uh. You'd like to see the size
Speaker 1: of the fund being not too big. So we know
Speaker 1: that size tends to be challenging, so you want to
Speaker 1: be big enough to have some critical masses and the
Speaker 1: resources you need, but not so so large that you're
Speaker 1: moving tons of money around, which makes it difficult. And
Speaker 1: the last one, which I think is still controversial, but um,
Speaker 1: but I think it's probably a heristic for something it
Speaker 1: is useful, and that's high active share, which is they're
Speaker 1: doing something quite different, right, So you're paying if you're
Speaker 1: paying someone a fee, you want them to be doing
Speaker 1: something quite different than say the SP five index. And
Speaker 1: so if you have a couple of those things working
Speaker 1: for you, the age, they're bright people, the size is appropriate,
Speaker 1: that they're doing something different, and the process seems to
Speaker 1: be sensible. Those probably shade the odds in your favor
Speaker 1: to some degree. But as you point out, I think correctly, Um,
Speaker 1: it's difficult to to find an anticipate performance excess returns
Speaker 1: in the future, for sure. Al Right, So in the
Speaker 1: last ten minutes or so that we have, let's let's
Speaker 1: go over um my standard questions. These were not in
Speaker 1: existence when we first did this two years ago. So, um,
Speaker 1: some of these are kind of kind of interesting. Um,
Speaker 1: how did you find your way into the financial services industry?
Speaker 1: You you come out of school with the b A
Speaker 1: and what made you attack in that direction? Well, can
Speaker 1: I tell you a very quick funny story about this.
Speaker 1: So I was. I went to Georgetown. I was a
Speaker 1: government major, had no idea what I want to do.
Speaker 1: No I knew I needed a job, and uh one
Speaker 1: of the firms interviewed on campus with Drexel Burnham Lombert,
Speaker 1: which you may recall, was it quite a firm, quite
Speaker 1: a hot firm back in the mid nine eighties. So
Speaker 1: I did well enough of my New York Washington interviews
Speaker 1: that invited me to New York. Isn't a big deal.
Speaker 1: Get my best suit, my best tie on, and we
Speaker 1: sit around. All the candidates sit around the table, you know,
Speaker 1: before the big day of interviews, and they say, hey,
Speaker 1: you're gonna have six interviews with different people on our program,
Speaker 1: and you get ten minutes with a head guy. Right,
Speaker 1: So obviously you want to be good all day. But
Speaker 1: that's a game for your for the day. So I
Speaker 1: go through the interviews. It's fine. I meet the big
Speaker 1: guy and you know, he's a great guy, really warm,
Speaker 1: and I sit down and I see peeking out from
Speaker 1: underneath his death Washington Redskins, trash can. I went to
Speaker 1: went to Georgia. The riskins were good back then I'd
Speaker 1: gone to a couple of games. So I say to him,
Speaker 1: kind of off handily, hey that's a great trash can, literally,
Speaker 1: and this triggers this guy's emotional seats. So he goes
Speaker 1: on about, you know, the virtues of athletics, and you know,
Speaker 1: metaphor for life, how much you love living in Washington,
Speaker 1: and my my ten minute interview becomes fifteen minutes and
Speaker 1: me mostly nodding up and down in agreement with everything
Speaker 1: he said. So I go back to school a couple
Speaker 1: of weeks later, get the letter offered the jobs is awesome,
Speaker 1: start the program, and about three months into it, one
Speaker 1: of the guys pulls me aside says, hey, kid, you're
Speaker 1: doing fine, so you know it's okay, but I have
Speaker 1: to tell you that the six people who you interviewed with,
Speaker 1: who are the core of the interview process, voted against
Speaker 1: hiring you. He goes but the head guy came down
Speaker 1: and reviewed our sheets and recommendations and said, Override, you
Speaker 1: have to hire this kid. He's great. Right, So, as
Speaker 1: I like to say, my my career was launched by
Speaker 1: a trash can, right, which is quite literally the case.
Speaker 1: And and and thankfully these more formal processes weren't in
Speaker 1: place at the time because I wouldn't have been hired.
Speaker 1: So so that was it. And and that was a
Speaker 1: really interesting experience because it was a year and a
Speaker 1: half long training program that led to be a financial advisor.
Speaker 1: So we did a lot of classroom stuff for a
Speaker 1: liberal arts guy, tremendous, right, so basic accounting and finance
Speaker 1: and so forth, and then we rotated through about twenty
Speaker 1: different departments at Drexel Burnham, everywhere from operations to investment
Speaker 1: banking to research, all the trading desks. So if you're
Speaker 1: a person that didn't know what your future, what you
Speaker 1: were about, you're gonna find yourself right through that program.
Speaker 1: And then I went on to be a financial advisor
Speaker 1: at drug we call them brokers back then, uh at Drexel,
Speaker 1: and was an abject failure at that job. Abject sales
Speaker 1: job as a sales job, and it was it was
Speaker 1: started in early so that was on the heels of
Speaker 1: the crash of eighty seven and Drexel at that point
Speaker 1: was in a little bit of hot water, so those
Speaker 1: were sort of mitigating factors. But basically I was not
Speaker 1: good at this at all. So fortunately I was able
Speaker 1: to figure out a little bit of what I wanted
Speaker 1: to do. But that was my my store, my exactly,
Speaker 1: but it was it was in some ways it was
Speaker 1: a great I mean, it was a great experience for sure,
Speaker 1: but knowing what you're not good at was a wake
Speaker 1: up call to saying, like I should go off and
Speaker 1: do something different. So so that raises the next question,
Speaker 1: so who are your mentors? So in my training program,
Speaker 1: actually a guy in my group gave me a copy
Speaker 1: of a book called Creating Sheer Older Value by a
Speaker 1: professor at Northwestern named L. Rappaport. And I was, you know,
Speaker 1: a liberal arts guy, and these guys are talking all
Speaker 1: this finance jargon. It was way over my head and
Speaker 1: actually candidly didn't make a lot of sense. That book
Speaker 1: was the first book that really made sense to me.
Speaker 1: And and and rapp reports said three things that to
Speaker 1: this day remained at my core. And I would say,
Speaker 1: he's not only a mentor, he's a dear friend and
Speaker 1: a co author and so forth. The first was that
Speaker 1: it's not about accounting numbers, is about economic value, which
Speaker 1: is really important. And we forget that lesson but it
Speaker 1: comes it rears its head from time to time. Second
Speaker 1: is that valuation requires understanding both finance and competitive strategy intimately,
Speaker 1: so they're not Valuation and strategy are not two separate activities,
Speaker 1: which is how we teach them in business school, by
Speaker 1: the way, but really should be joined at the hip.
Speaker 1: And the third was chapter seven called stock Market Signals
Speaker 1: for Managers, and it was the argument that stock prices
Speaker 1: reflect expectations and that a manager just investing in a
Speaker 1: way that earns the cost of cabal isn't going to
Speaker 1: get you excess returns. It's beating with the market believes,
Speaker 1: and that for me, it was a huge revelation, right,
Speaker 1: and he was His target was corporate executives, but the
Speaker 1: relevance for investors was obvious. So I started emulating a
Speaker 1: lot of the Rappaport techniques, which are basically standard finance techniques,
Speaker 1: and a lot of my research, including deep dies on
Speaker 1: competitive strategy and a lot of valuation work. And again
Speaker 1: that's how I got to I got to meet him
Speaker 1: in the early nines, about twenty five years ago, and
Speaker 1: from then we we sort of cultivated. So he's been
Speaker 1: he has been tremendous. The other guy for me has
Speaker 1: also been Bill Miller. And you mentioned I worked with
Speaker 1: Bill for nine years, but even going back to the
Speaker 1: early one of the early and this is before he
Speaker 1: was the famous money manager right the S and p F.
Speaker 1: This is before, this is before it was just a streak,
Speaker 1: highly unlikely random. It won't it won't get I don't
Speaker 1: think that one will be broken. But but he's also
Speaker 1: a guy who's uh, you know, very valuation focused, very
Speaker 1: widely read guy, very multi disciplinary guy. Um and you know,
Speaker 1: a wonderful guy to just talk to and learn from.
Speaker 1: So those are a couple of guys that certainly stand out,
Speaker 1: um in terms of in terms of mentor but Rapp
Speaker 1: in terms of actually understand the business and thinking about
Speaker 1: Al Rapp Reports stands above all for me as it's
Speaker 1: just a hugely, deeply influential person. So let's talk about books.
Speaker 1: We we've mentioned a number of different books. Uh, what
Speaker 1: are some of your favorite books? Be them, be they
Speaker 1: investing tons or otherwise just beside yours? Okay, okay, it
Speaker 1: goes without saying right, So UM, look, I mentioned already
Speaker 1: Al rapp Reports book Creating Shoulder Value, UM, which was
Speaker 1: written original version of it. A couple other books that
Speaker 1: for me been tremendously valuable. Um, Mitch Waldrop's book on Complexity.
Speaker 1: So this is the history of the of the Santa
Speaker 1: Fe Institute. So that introduced a whole sleuve ideas that
Speaker 1: were wildly influential for me. Love Robert Schildini's book Influence
Speaker 1: of Psychology or Persuasion. That should be a must read,
Speaker 1: especially for young people. Peter Bernstein just was whatever and
Speaker 1: so whatever he writes, but the two I would mention
Speaker 1: to be against the God. I just read that. You
Speaker 1: know it can't get enough right and you should reread that.
Speaker 1: And Capital Ideas was also terrific Um and then a
Speaker 1: couple more. Another ones a little bit off the radar
Speaker 1: for the investing world is John Gaddis's book The Landscape
Speaker 1: of History Really, and Gaddis is a professor of history Yale,
Speaker 1: And Um, this is a night it's actually a series
Speaker 1: of lectures that are written in a book. And it's
Speaker 1: the craft. It's about asking the questions about what is
Speaker 1: the craft of history? And I think what's so interesting
Speaker 1: to me is that many of those ideas are ideas
Speaker 1: that spill right over to the world of investing as
Speaker 1: an as an as an analyst or portfolio man your
Speaker 1: how do you craft stories, how do you understand causality?
Speaker 1: How do you grapple with complexity? So gaddis wonderful and
Speaker 1: it's it's really interestingly written book. So, um, you know.
Speaker 1: And then the other one I just mentioned is is E. O.
Speaker 1: Wilson's book Consilience. We may have talked about that before,
Speaker 1: but we have not ed. Wilson is Uh. He's a criminologists,
Speaker 1: a professor. As a professor at Harvard, he is the
Speaker 1: world's leading expert in ants. Okay, so I'm thinking of
Speaker 1: a difference. So yeah, it could be. And so and
Speaker 1: he wrote a book of years ago cults consilience, and
Speaker 1: consilience is one of these old words which means the
Speaker 1: unification of knowledge. And the argument that Wilson made in
Speaker 1: this book was, Hey, we've made enormous strides, uh in
Speaker 1: the last few centuries by being reductionist and disciplinary. So
Speaker 1: in other words, the biologists hang out with the biologist
Speaker 1: and with business. He said, Look, the most vexing problems
Speaker 1: in our world are standing at the intersections of disciplines,
Speaker 1: and so for us to really advance, we need this
Speaker 1: concilience's unification of knowledge very much resonated with me, and
Speaker 1: I truly believe that. And we talked about, you know,
Speaker 1: even Danny Khneman winning the Nobel Prize in economics even
Speaker 1: though he's never taught an economics class in his life, right,
Speaker 1: but what he's brought to bear something that's really useful
Speaker 1: for both psychologists and economists, right, So that intersection, and
Speaker 1: Dick Taylor, who will likely win the Nobel Prize, also
Speaker 1: operating in that intersection. But go on and on, I mean,
Speaker 1: what can you learn from a biologist? Offline? We were
Speaker 1: talking about some of the things you listen to about
Speaker 1: musicians or comedians. What can you learn from what those
Speaker 1: guys do their creative processes their businesses that it might
Speaker 1: might apply to your creative process in your business. Gotta
Speaker 1: be stuff that's relevant, right, And so to me, that
Speaker 1: whole way of thinking and reaching outside of your own
Speaker 1: little world for ideas that may apply. Um so, so
Speaker 1: Ed Wilson's book on that is probably you know, the
Speaker 1: great one. So my last two questions and and these
Speaker 1: are my two favorites. Some millennial comes up to you
Speaker 1: and says, hey, I'm thinking about getting into UH finance.
Speaker 1: You teach at Columbia so you must have a lot
Speaker 1: of students who occasionally say, I'm interested in finance. What
Speaker 1: sort of advice would you give them? You know, So
Speaker 1: there there are two sides this one night classical finance,
Speaker 1: of corporate finance, mergers and acquisitions and capital raising, all
Speaker 1: that stuff is likely to continue, so that if they're
Speaker 1: interested in that, that's fine. More of the questions I
Speaker 1: get about money management, And you know, Richard grin Old
Speaker 1: wrote this really fascinating paper twenty five years ago about
Speaker 1: the law of active management, and he basically said, we'll
Speaker 1: use English terms instead of Greek terms excess returns or
Speaker 1: a function of your skill times your opportunity set. And
Speaker 1: that's a really interesting way to think about this, right,
Speaker 1: because you can be the most skillful person in the world,
Speaker 1: but if your opportunity set is not very attractive, you're
Speaker 1: not gonna go very far with your access returns. So
Speaker 1: one thing I just asked to encourage the students to
Speaker 1: think about is where do you think the next twenty
Speaker 1: five years things are going to be a little more exciting? Right?
Speaker 1: Where where is the where the opportunity is going to reside?
Speaker 1: My guess is it's unlikely to be the dwive US
Speaker 1: value manager Large Camp. It's unlikely to be. It's much
Speaker 1: more likely to be somewhere in emerging markets, maybe even
Speaker 1: you know, uh, you know, Africa or parts of Asia.
Speaker 1: So to me, that would be the thing to think
Speaker 1: about is if you you're gonna lay out next years,
Speaker 1: where do you think that those, um, those excess returns
Speaker 1: are going to be. The other thing I would say
Speaker 1: is that and you know, I think you've talked a
Speaker 1: lot about this as well. We've really moved rapidly towards
Speaker 1: quantitative methods, and the other other thing to think about
Speaker 1: is are there ways that we can meld or advanced
Speaker 1: quantitative techniques so meld them with our without what we're
Speaker 1: doing fundamentally, So so some blend of those two techniques
Speaker 1: or advanced un quantitative So that if you said, where
Speaker 1: is the future going? To me, I think these quantitative
Speaker 1: techniques are certainly not going to uh be rolled back.
Speaker 1: I think we're going to continue to see that advancement.
Speaker 1: And our final question, what is it that you know
Speaker 1: about investing today that you wish you knew when you
Speaker 1: began in the nineteen eighties? Geez, A lot of things,
Speaker 1: But the first is I mean, we really have. The
Speaker 1: complexion of the market has changed a great deal. When
Speaker 1: I started thirty years ago, indexing was less than one
Speaker 1: percent of assets under management. By the way we looked
Speaker 1: this up, the equity US equity mutual fund industry assets
Speaker 1: under management were hundred and thirty five billion. Wow, that's amazing.
Speaker 1: It's just mind boggling. In thirties decent sized funds. Decent
Speaker 1: size fund today, Isn't it remarkable? So the whole complexion
Speaker 1: has changed a great deal. But there are a couple
Speaker 1: of things that I would note. One is that that phenomenon,
Speaker 1: so we've gone from basically a standstill to thirty five
Speaker 1: percentage something like that that's passive or index So that's
Speaker 1: a big change. The other fascinating change is that, um
Speaker 1: most fun were single managed by one person about years ago.
Speaker 1: That's now down about most teams. Yeah, their team run,
Speaker 1: which is it? Truly That's another really big change and
Speaker 1: what's going on. And I think the other thing is
Speaker 1: just the level of skill has gone up, and going
Speaker 1: back to our discussion on the paradox of skill, we've
Speaker 1: never seen more skill than we have today, and that
Speaker 1: has made it much more difficult to outperform the market.
Speaker 1: So I mean it's it's always exciting, as you point out,
Speaker 1: because there's always something going on, the world is always changing.
Speaker 1: What's deeply fascinating about this business is you've never figured
Speaker 1: it out right because the world is always changing and
Speaker 1: it requires you to keep up with what's going on.
Speaker 1: But those are some of the really big changes the
Speaker 1: backdrop that I think make it all so fascinating. We
Speaker 1: have been speaking with Michael Mobison of Credit Swiss. Mike,
Speaker 1: thanks for being so generous with your time. This has
Speaker 1: been absolutely fascinating. If you enjoy this conversation, be showing
Speaker 1: look Up an Inch or Down an Inch on Apple
Speaker 1: iTunes and you could see any of the other one
Speaker 1: hundred uh such episodes that we have had. UH be
Speaker 1: sure and check out Mike's white papers, books, et cetera.
Speaker 1: You can find that at Michael Mobison dot com. I
Speaker 1: would be remiss if I did not thank uh the
Speaker 1: hard work of the team who helped put this together. Uh.
Speaker 1: Taylor Riggs is my producer, booker Charlie Bohmer, and Today
Speaker 1: Guests recording engineer David Uh. Mike Batnick is our head
Speaker 1: of research. We love your comments feedbacks, questions and suggestions.
Speaker 1: Be sure and write to us at our new email address,
Speaker 1: m IB podcast at bloomberg dot net. I'm Barry Ritults.
Speaker 1: You've been listening to Masters in Business on Bloomberg Radio