Speaker 1: Bloomberg Audio Studios, Podcasts, radio News.
Speaker 2: Hello and welcome to another episode of the All Thoughts Podcast.
Speaker 2: I'm Tracy Allaway.
Speaker 3: And I'm Joe wysnent Thal.
Speaker 2: Joe, it's a big month for us.
Speaker 3: Big month for us. We've been doing this for ten years.
Speaker 2: I know, I can't believe it. Do you remember the
Speaker 2: first episode?
Speaker 3: Yeah, of course with Tom Keane.
Speaker 2: Yeah, But and then our second episode I think was
Speaker 2: about bananas for some reason, it was You're.
Speaker 4: Right, it took us a long time to figure out
Speaker 4: what we were doing. It took us a long time
Speaker 4: to figure out what we were doing, and I don't
Speaker 4: think at that point I would have expected that we'd be.
Speaker 3: Doing it ten years later. I don't know what I
Speaker 3: was expecting. I think turning on a microphone in a
Speaker 3: radio studio and talking for a while.
Speaker 2: We started doing it because we wanted to have a
Speaker 2: podcast and talk to interesting people. I think we were
Speaker 2: hashtag bless. No one was listening for a very very
Speaker 2: long time, which gave us a long runway to figure
Speaker 2: things out. So we got lucky. That said, you know,
Speaker 2: ten years, it is, in fact a long time to
Speaker 2: be doing this, and a lot has changed in that period.
Speaker 4: A lot has changed in that period, sometimes mind blowing.
Speaker 4: And we've talked about this before for sure, But the
Speaker 4: things that we were covering is capital and news at
Speaker 4: the time are now capital age history.
Speaker 3: And it's like these things that are we sort of
Speaker 3: take for granted. Everyone was there.
Speaker 4: It's like, no, children, let us tell you what it
Speaker 4: was like in the old days when people were worried
Speaker 4: the world was going to come to an end because
Speaker 4: you know, Greece is sovereign debt and all this stuff
Speaker 4: that we just sort of part of the landscape is
Speaker 4: people don't remember it.
Speaker 2: No, one of those things has to be the idea
Speaker 2: of value or fundamental investing, right, Like, let us tell
Speaker 2: you about the days when price actually mattered and had
Speaker 2: a limit to what investors would pile into.
Speaker 3: Yeah, that's exactly right.
Speaker 4: Let us tell you about the days when people used
Speaker 4: to talk about pe ratios and this stock, Oh so
Speaker 4: the twenty five pe we better sell it and buy
Speaker 4: the stock at a fifteen p or whatever.
Speaker 3: Yes, that feels quaint.
Speaker 4: Maybe it'll be back there one day, but for now,
Speaker 4: given how many things in the market seem to be
Speaker 4: the Graham and DoD kind of stuff, feels a little.
Speaker 2: Old, a little old fashioned, little old.
Speaker 5: Yeah.
Speaker 2: Okay, So one of the big themes that has emerged
Speaker 2: in the ten years that we've been doing this podcast
Speaker 2: is everyone seems to have grown more stupid. I would say,
Speaker 2: hopefully that's not related, so that's not like a correlation thing.
Speaker 2: It could be all right, but you know, we have
Speaker 2: all this gamification of investing, people betting onlines going up,
Speaker 2: we're down, people betting on random meme coins, things like that,
Speaker 2: and I think, you know, we talk about it a
Speaker 2: lot on the podcast, but this is actually a fundamental
Speaker 2: shift in the market. If you think about the market
Speaker 2: as something that's supposed to be about capital allocation, alignment
Speaker 2: of incentives. People are investing in something because they think
Speaker 2: it's going to be profitable in the future at the
Speaker 2: right price. And now people are just sort of piling
Speaker 2: into stuff because other people are doing it, and again,
Speaker 2: line go up.
Speaker 4: Deep down, I still believe that the value of a
Speaker 4: stock should reflect the net present value of all. I
Speaker 4: know you're an MH guy, but I've it's been a
Speaker 4: little bit hard with some of these things. And you
Speaker 4: know the other thing too, that is sort of changes
Speaker 4: that like half of our episodes these days are kind
Speaker 4: of AI related in some way, and so I think
Speaker 4: there's a lot of interesting stuff going on, particularly at
Speaker 4: the intersection of tech and applying tech to both investing
Speaker 4: in tech, but then the application of tech to investing
Speaker 4: and so forth.
Speaker 3: So yes, much has changed.
Speaker 2: A lot has changed, and we have the perfect guests
Speaker 2: to talk about how everyone has grown more stupid over time.
Speaker 2: We're going to be speaking with someone we've wanted on
Speaker 2: the show for a really, really long time. I'm very
Speaker 2: excited about this. It's Cliff Asnas, the co founder and
Speaker 2: CIO of AQR. Thank you so much for coming on.
Speaker 5: All thoughts, Thank you for having me.
Speaker 2: What's it like to be a rational person living in
Speaker 2: irrational Cliff, Yeah, you've been doing it for a long time.
Speaker 6: Well, a rational person is not always how I'm described,
Speaker 6: but this rational investing and in this rational conduct in
Speaker 6: your personal life.
Speaker 5: So let's just distinguish those.
Speaker 6: You guys in your intro said like, it's a it's
Speaker 6: a little scary for the next hour because you said
Speaker 6: like a third of the things I want to say. Oh,
Speaker 6: I wrote a rather gigantic piece in the Journal of
Speaker 6: Portfolio Management. They were having a fiftieth anniversary. None of
Speaker 6: us were quite old enough to have been there in
Speaker 6: the first issue, but they were looking for the old
Speaker 6: guys to write kind of retrospectives, and the piece I
Speaker 6: wrote was called the less Efficient Market Hypothesis. Now, I
Speaker 6: think you guys probably know this, but my dissertation advisor
Speaker 6: was a little known guy named Eugene Fama.
Speaker 3: We've heard of.
Speaker 5: I was his TA for two years. I grew up
Speaker 5: in EMH.
Speaker 6: I love that you guys just say EMH and your
Speaker 6: audience knows where you're talking about. That is not the
Speaker 6: norm for me when I talk about these things. I
Speaker 6: was not a perfect efficient marketer even back then.
Speaker 5: Neither is Gene.
Speaker 6: By the way, Genes not a zealot about third week
Speaker 6: of class. I know this because I took the class
Speaker 6: three times. I didn't fail, but as the TA, I
Speaker 6: sat through it three full years, and like the third week,
Speaker 6: he always tells the class.
Speaker 5: Markets are almost certainly not perfectly efficient.
Speaker 6: Because Jean's a brilliant guy and recognizes that perfection is
Speaker 6: a really stupid idea.
Speaker 2: He's been on the show. By the way.
Speaker 6: Oh, I don't know, yeah, yeah, And I don't know
Speaker 6: if that came up, but he's always very honest about that.
Speaker 6: He probably thinks they're considerably more efficient than I do
Speaker 6: these days, and I think I probably think it's they're
Speaker 6: more efficient than maybe.
Speaker 5: The active average retail trader.
Speaker 6: But I wrote a dissertation for him on the success
Speaker 6: of price momentum. That is not a very gene Fama dissertation.
Speaker 6: A gene Fama dissertation is I've studied price momentum and
Speaker 6: it loses gobs of money, and these idiots on Wall
Speaker 6: Street do it anyway. That's kind of a fishing market.
Speaker 6: It's lot how silly they are. And he was great
Speaker 6: about it. I remember I kind of mumbled, I'm like,
Speaker 6: I want to write a dissertation on price momentum, and
Speaker 6: by the way, I find it works very well.
Speaker 5: What was that, cliff?
Speaker 6: It works very well? And he said, if it's in
Speaker 6: the data, write the paper. So I've drifted at least
Speaker 6: a little bit further from efficient markets even way back then. Now,
Speaker 6: price momentum, I'll do a lot of segues. You're gonna
Speaker 6: have to stop. I do parentheticals within parentheticals. Price momentums
Speaker 6: often thought of as this index of irrationality. It can
Speaker 6: work for two different reasons. It can work because of yes,
Speaker 6: feedback loops, chasing line goes up just like you said before,
Speaker 6: and people pour in, which isn't very connected to reality.
Speaker 5: It's just chasing returns.
Speaker 6: But it can also work because of what the behavioral
Speaker 6: finance people would call underreaction. News comes out that should
Speaker 6: move the price by so and so on average. We
Speaker 6: have found, I say we it's the royal we of
Speaker 6: academia and private researchers that the price moves the right direction,
Speaker 6: but doesn't move all the way. So if you trade
Speaker 6: on that, there's still a little bit to go. That's
Speaker 6: a quant thing. You wouldn't want to bet on one
Speaker 6: stock that way. But if on average that happens and
Speaker 6: you could do that through observing the price or the fundamentals,
Speaker 6: usually a little bit more to go. So it's not
Speaker 6: always irrational momentum. But here's what I observed in the
Speaker 6: very beginning of AQR. EQR launched in nineteen ninety eight,
Speaker 6: after we had a fabulous run at Goldman sacks this
Speaker 6: survivorship bias. In this you don't get to start your
Speaker 6: own billion dollar hedge fun unless you have a fabulous
Speaker 6: runner at Goldman sacks or something equivalent. We had a
Speaker 6: good first month. You know how the story is going
Speaker 6: to go when you say you had a good first month, right,
Speaker 6: And then that first month, by the way, it was
Speaker 6: August of nineteen ninety eight when the S and P
Speaker 6: was down twenty percent on the Russian debt crisis, and
Speaker 6: we're doing high fives, like we say, we're marketing neutral
Speaker 6: and we're up a little bit in a crash. And
Speaker 6: it was my first of many lessons never to high
Speaker 6: five in this business. When you fully retire and divest,
Speaker 6: you get one high five.
Speaker 2: But that the well, no, it's the end when you
Speaker 2: do the high five.
Speaker 6: I'm a kwant who is also superstitious, which if that's
Speaker 6: a contradiction, what the heck. But the next eighteen months
Speaker 6: was the crescendo the famous dot com or tech bubble,
Speaker 6: and that was not kind to us. It was particularly
Speaker 6: not kind because we decided to start with a extremely
Speaker 6: aggressive market neutral fund. So momentum helped, as you can
Speaker 6: imagine in a bubble, but value was just destroyed and
Speaker 6: that was most of the model back then. Things have
Speaker 6: really broadened out. We hit spreads between cheap and expensive.
Speaker 6: This is something we invented at the time, and now.
Speaker 5: A lot of people do.
Speaker 6: People said shortstocks on valuations go along in the cheap,
Speaker 6: short the expensive, But the very obvious question of how
Speaker 6: cheap and how expensive are they sometimes pretty tightly clustered?
Speaker 6: Are they sometimes wider? Does that mean they're better or
Speaker 6: worse going forward? Was not asked before. So we invented
Speaker 6: this measure, and the spread between cheap and expensive for
Speaker 6: fifty years had looked like a well behaved series.
Speaker 5: It moved around a fair amount.
Speaker 6: And then I'm drawing on my hand if only see
Speaker 6: the video, Yeah.
Speaker 2: I should mention this is an audio medium.
Speaker 6: And then in late ninety nine two thousand and went
Speaker 6: to just way wider than anything ever seen for fifty
Speaker 6: plus years. We also showed that historically those were better times.
Speaker 6: You never saw that before. But when it was wider
Speaker 6: or better times for value, we stuck with it. We
Speaker 6: made money round trip life was good.
Speaker 5: If you had.
Speaker 6: Asked me after the round trip, which was harrowing. You know,
Speaker 6: you know, even if we love our process, you never
Speaker 6: want to start a business with poor returns. If you
Speaker 6: ask me at the end of that, which is probably
Speaker 6: a couple of years later, two thousand and three. Do
Speaker 6: you think you're ever going to see that in your
Speaker 6: career again? No one asked, thank God, because I think
Speaker 6: it would have gotten it wrong. But I think I
Speaker 6: would have said, oh, probably not hopefully. I wouldn't say definitely.
Speaker 6: No one who does what any of us do for
Speaker 6: a living should say definitely. That's a bad word in markets.
Speaker 2: Is the favorite term.
Speaker 5: But A it was the.
Speaker 6: Craziest thing numerically in fifty plus years. B. The question
Speaker 6: presupposed is it's built in that I and people of
Speaker 6: my core will still be around right and will probably
Speaker 6: be are to in charge. So how's it going to
Speaker 6: happen again? And then it happened again even before COVID.
Speaker 6: By late twenty nineteen, that spread between cheap and expensive
Speaker 6: was approaching dot com extremes, and then it blew past it.
Speaker 5: In COVID.
Speaker 6: It went to what I in a geeky math joke
Speaker 6: that no one ever gets called one hundred and twenty
Speaker 6: fifth percentile. There is no one hundred twenty five percentile.
Speaker 6: It's just a new hundred percentile. I'm trying to convey
Speaker 6: that it went further, and we survived that one too.
Speaker 6: We suffered somewhat, and then we made more than all
Speaker 6: of it back ground trip good. Most of the time,
Speaker 6: we really don't look like value investors, by the way,
Speaker 6: only in extreme bubbles do we have seem to have
Speaker 6: that property.
Speaker 5: And I think it's smaller now than it used to be.
Speaker 5: Last five years have been quite strong for us, and
Speaker 5: it's not been a very good value market.
Speaker 4: God, there's so many questions that I have that I
Speaker 4: want to ask that are sort of embedded or related
Speaker 4: to your answer. I'm going to ask at you just
Speaker 4: like a very narrow question, sort of skip ahead into something.
Speaker 5: Though.
Speaker 4: You make this spread between the most expensive than the
Speaker 4: cheapest stocks, how much easier it is to simply compile
Speaker 4: that spread? Is it today versus the technology that you're
Speaker 4: working with when you're starting your career?
Speaker 6: For that, I got to disappoint you and say not
Speaker 6: that much. Here we had the databases. A lot of
Speaker 6: technological investment is about speed and new data sets. What
Speaker 6: quanto Alternative data is something we're very into. But the
Speaker 6: classic data if you're looking for price to sales ratios,
Speaker 6: I'm old, but we had we have telephones and Bloombergs.
Speaker 6: But that does bring us to me observing these two episodes,
Speaker 6: and I stepped back and I asked a question, what
Speaker 6: the hell happened? Why did we see something crazier than
Speaker 6: fifty years? And then why did it happen again? And
Speaker 6: that led to this paper, the less efficient market Hypothesis.
Speaker 6: I do believe that markets have shown and I think
Speaker 6: I have some good guesses as to why that they
Speaker 6: are more susceptible to bouts of crazy than they used
Speaker 6: to be.
Speaker 4: Just before going further, one quick definitional question efficient markets,
Speaker 4: because one way you could define whether market is efficient
Speaker 4: is are these securities disconnected from what you would say
Speaker 4: the net present value of the all future free cash flows.
Speaker 4: Another way that I often think about it, but I'm
Speaker 4: no kuant is are there obvious opportunities for the active
Speaker 4: manager to make money?
Speaker 3: Just for our purposes here? How do you define market efficients?
Speaker 6: Much closer to the first one, Okay, The practical question
Speaker 6: of can you make money from these is if there
Speaker 6: are big deviations from fair value? And this relates to
Speaker 6: some stuff I did in a less efficient market hypothesis.
Speaker 6: If there are big deviations the classic and you'll notice
Speaker 6: a giant caveat if you can stick with your position
Speaker 6: not a small thing.
Speaker 5: You will make money.
Speaker 6: There are opportunities, and in fact, I think a less
Speaker 6: efficient market in that sense, in your present value sense,
Speaker 6: almost has to deliver bigger opportunities for people who can
Speaker 6: stick with it. It also makes it considerably harder to
Speaker 6: stick with because the extremes you have to live through
Speaker 6: and the length of time those extremes can go on.
Speaker 6: For one thing, that I'm dying for an academic to
Speaker 6: take me up on this. I'm too old to do
Speaker 6: the math on this, but I've never seen a model
Speaker 6: that looks at pain, disutility, the negative of losing money
Speaker 6: in terms of how long you've lost money for, not
Speaker 6: just magnitude. Right, And in real life, I can tell
Speaker 6: you a drawdown that is one and a half times bigger,
Speaker 6: but with six months instead of three years, is ridiculously
Speaker 6: easier to live through. So the bigger disconnect from reality. Again,
Speaker 6: I haven't even told you why I think it's going on,
Speaker 6: But if I'm right that we have these bouts of it,
Speaker 6: it's not necessarily every day things are crazy, but these
Speaker 6: bouts of it is a two edged sword. It's a
Speaker 6: bigger opportunity for people who can stick with it, and
Speaker 6: it's harder to do, and I find that not that
Speaker 6: what I think is fair is particularly relevant. But I
Speaker 6: find that really fair harder to do, but more lucrative
Speaker 6: if you can do it. I don't think the efficient
Speaker 6: market idea of buying what is fundamentally mismatched against its
Speaker 6: future cash flows adjusted for as risk forecasting those cash
Speaker 6: flows what risk really means? We still have some open
Speaker 6: issues there. Yeah, but I don't think that will ever
Speaker 6: go away unless markets are perfectly efficient. But how easy
Speaker 6: it is to identify and how easy it is to
Speaker 6: stick with. I think crazy markets make it easier to
Speaker 6: identify what to do and harder.
Speaker 5: To deal like that.
Speaker 2: I do want to ask you why you think this
Speaker 2: is happening, but before we do, this is a very
Speaker 2: basic question. But sometimes the basic questions are the most interesting.
Speaker 2: But when you say it's painful to try to stay
Speaker 2: rational during these bouts of irrationality, why is that exactly?
Speaker 2: Because I get that there are funding costs. I get
Speaker 2: that there are carrying costs. But on the other hand,
Speaker 2: you're a big hedge fund with deep pockets. This is
Speaker 2: presumably what investors are paying you to do. Is it
Speaker 2: just the emotional trauma or stress of having to explain
Speaker 2: to everyone why you're making the position that you have
Speaker 2: when it's not paying off yet.
Speaker 5: That is a big part of it.
Speaker 6: I have a running fight with one of my co
Speaker 6: founders who never gets upset. I'm always upset, but I'm
Speaker 6: more upset when we're losing money.
Speaker 2: This is sort of our dynamic. I have to I
Speaker 2: get more upset than Joj.
Speaker 6: Hunhes where He'll come in my office during a bad
Speaker 6: period and I'll be upset.
Speaker 5: It'll be a bad day in a bad period. He's like,
Speaker 5: why are you upset?
Speaker 6: And I'm like, well, cause people are yelling at us
Speaker 6: and I were losing money. And he's like, but you're
Speaker 6: pretty sure.
Speaker 5: We're going to win, right. I'm like yeah.
Speaker 6: He's like, and you have all your own money and
Speaker 6: your kids money in this right, so you're not doing
Speaker 6: anything different.
Speaker 5: You wouldn't do that if you weren't. I'm like yeah,
Speaker 5: He's like, so we're gonna win. It's just a question
Speaker 5: of when why do you care? And I look at
Speaker 5: him like he's from Mars and go, why do you
Speaker 5: not care?
Speaker 6: And we finally figured out it's kind of obvious that
Speaker 6: I talk to clients a lot more than he does.
Speaker 6: It's a lot easier to have that attitude when you're
Speaker 6: just sitting in your office. Also, we are not immune
Speaker 6: from this. Even if people love you and think you've
Speaker 6: done well for twenty five years, you have a bad
Speaker 6: two years, you get redemptions, and sometimes they're of serious size.
Speaker 6: We fell by like half over about three years, and
Speaker 6: that's not fun. You have to shrink your firm, you
Speaker 6: have to let some people you love go, so there
Speaker 6: is some real pain that goes with it. That period
Speaker 6: did not shake my confidence in the actual investment process.
Speaker 6: I feel bad. I think I did better than our
Speaker 6: investors because I kept adding and saying, take the ball
Speaker 6: up on what I do. Not everyone can do that,
Speaker 6: and I know more than they know. Not in a
Speaker 6: weird insider sense and just a I should be more
Speaker 6: confident in my own process than anyone else's. But it
Speaker 6: is excruciating the amount. I remember someone I admire tremendously,
Speaker 6: when Stan Druckenmeller retired to run his own money. He's
Speaker 6: still very active in markets. I think he wrote a
Speaker 6: note that resonated with me because I forget the exact details,
Speaker 6: but the essence was, it's too painful and too upsetting
Speaker 6: to run client money. The man never had a down year,
Speaker 6: and I'm like, if Stan can't take it, those of
Speaker 6: us and we've had a lot more up years than
Speaker 6: down years and life's been good, or I won't be
Speaker 6: sitting here. But we've had never three but two plus
Speaker 6: years of pain, and I'm like, Stan can't take it. Man,
Speaker 6: this is harder to do than it looks like.
Speaker 5: The whole world.
Speaker 6: Thinks you stupid when you losing money, no matter what
Speaker 6: you can point to, no matter what evidence you can
Speaker 6: point to, I should say, the whole world.
Speaker 5: Your mom still likes you, but a lot of your
Speaker 5: world and no, a lot of investors stuck with us,
Speaker 5: and I love them for it. But you do lose
Speaker 5: a lot of people. So it's not fun for a
Speaker 5: business to go through that.
Speaker 4: Intuitively, though, it's to your point measuring the disutility of
Speaker 4: long draw downs versus deep draw downs, this must be
Speaker 4: a very acute thing for anyone who's not just managing
Speaker 4: their own personal portfolio. For the reason that you've just described.
Speaker 6: Yeah, I've talked about this with other money managers, this
Speaker 6: idea of length versus severity. Yeah, and I've never had
Speaker 6: one who's not like, yeah, length is much worse.
Speaker 5: Well. One of the things is when.
Speaker 6: Something goes on, it's often a similar story for two
Speaker 6: and a quarter years. Right, So you go back after
Speaker 6: six months where rationality is getting absolutely punished. You get
Speaker 6: a lot of sympathy from people. You show them look
Speaker 6: bigger bargains, We're right, we're gonna be right. You go
Speaker 6: back six months.
Speaker 5: Later, they're like, Okay, you go back.
Speaker 6: Six months and six months later they're like, you're just
Speaker 6: saying the same adventure.
Speaker 4: And eventually they must just think maybe you're a dinosaur,
Speaker 4: Like maybe you just don't get this new wave that's
Speaker 4: going on.
Speaker 3: Is it possible that we've really had.
Speaker 5: Again, it's not everyone.
Speaker 6: We have the tremendous amount of investors stick with us,
Speaker 6: and we have ones who double up, who get it
Speaker 6: that those are often opportunities. But you shrink when you
Speaker 6: lose money for a while, and you grow when you
Speaker 6: make money for a while. It's the ironclad rule of
Speaker 6: this business. And sometimes it's just backwards.
Speaker 2: So one of the things that has been happening recently
Speaker 2: that has changed from twenty fifteen when we started doing
Speaker 2: this is retail participation in the market and it just
Speaker 2: feels like it is such a big thing for retail
Speaker 2: investors now to use things like options, even you know,
Speaker 2: one or zero day options, the kind of stuff that
Speaker 2: you might more traditionally associate with someone running a hedge fund.
Speaker 2: Now they're trading Oh.
Speaker 5: We're not stupid enough, Okay, options.
Speaker 2: All right, some hedge funds. Then, does the increased presence
Speaker 2: of retail in the market change the way that you
Speaker 2: do business at all?
Speaker 6: I think it contributes to what we're talking about of
Speaker 6: this dislocation. I hate this because I sound very elitist
Speaker 6: when I diss on retail, but there's a lot of
Speaker 6: academic work that shows retail on net loses net is important.
Speaker 6: They go through periods where they win, They go through
Speaker 6: periods where they win a lot. You know, if you
Speaker 6: buy a memestock into triples tomorrow, you don't always lose.
Speaker 6: But on average, retail transfers money to Wall Street and
Speaker 6: to institutions. So if there are a bigger force in markets,
Speaker 6: you're going to have more of that going on. And
Speaker 6: it jives perfectly because that would raise the opportunity if
Speaker 6: they're generally on the wrong side of things, but there
Speaker 6: are more of them many more of them than they
Speaker 6: used to be. They can be right even if they're
Speaker 6: wrong on the facts. They can be right on the
Speaker 6: numbers for longer than they used to be. So I
Speaker 6: do think this is part of it. And I apologize
Speaker 6: to all the really smart retail investors. Anytime you talk
Speaker 6: about averages, you're dissing a whole lot of people who
Speaker 6: don't deserve to be.
Speaker 5: But on average, retail loses zero day options.
Speaker 6: My god, they're making exactly the people they claim to
Speaker 6: despise on Wall Street very rich by trading these things.
Speaker 5: And it's just fan duels. I love that.
Speaker 4: Well, all right, we got to get to the question
Speaker 4: of why right, But one last question sort of leading
Speaker 4: up to it.
Speaker 3: How do you establish that what do you look.
Speaker 4: At in the market that right now you say this
Speaker 4: is a less efficient market than once it was. What
Speaker 4: is the measure or is it just feel where you
Speaker 4: just feel sort of crazy like all of us observe.
Speaker 6: Most of it is quantitative. I do start with this
Speaker 6: thing I've talked about, right, It spreads between cheap and expensive. Yeah, yeah,
Speaker 6: I don't just look at spreads. I wrote a piece
Speaker 6: back in two thousand during the tech bubble it's.
Speaker 5: Called bubble logic.
Speaker 6: It never got published because I tried to make a
Speaker 6: book out of it and the bubble came down too
Speaker 6: fast for me. That was good for my business, but
Speaker 6: bad form my author career. Where I didn't just look
Speaker 6: at price multiples. I looked at it in a more
Speaker 6: holistic sense. What growth do we need to justify these
Speaker 6: multiples trying to come up The only time I will
Speaker 6: use the word bubble is when I've tried very hard,
Speaker 6: and it doesn't mean we'll come up with the same answer,
Speaker 6: but this is the framework I use.
Speaker 5: I've tried very hard to come up with.
Speaker 6: Assumptions, even if I don't like them and think they're
Speaker 6: at the outer edge of possible, that could justify these prices. Yeah,
Speaker 6: and if they don't, I don't come close. Twice in
Speaker 6: my career I've been willing to go no, I'm willing
Speaker 6: to use the B word. I should tell you right now.
Speaker 6: When it comes to within stocks, the whole market is
Speaker 6: a different issue. The market is quite expensive right now.
Speaker 6: But when it comes to this spread between cheap and expensive,
Speaker 6: I'm not using the bubble word oka that same measure.
Speaker 6: It's not the one hundred and twenty fifth percentile anymore,
Speaker 6: it's the seventy seventh percentile. It's wider than on average,
Speaker 6: maybe making it a little more attractive if you can
Speaker 6: stick with it that big if. But I don't use
Speaker 6: the word bubble for seventy seventh percentile. I used it
Speaker 6: for blowing through. So five years ago I was saying
Speaker 6: it's a bubble. Now I'm just saying this is a
Speaker 6: little bit of an odd market.
Speaker 2: So I want to ask you more about the bubble.
Speaker 2: But we keep touting that we're going to ask you
Speaker 2: the why question. So let's ask the why question? Okay,
Speaker 2: why are markets becoming less efficient?
Speaker 5: Okay?
Speaker 6: Well, first of all, and I say this in the piece,
Speaker 6: a lot of conjecture going on.
Speaker 5: This is an op ed.
Speaker 6: As statisticians, it sound like a fifty page Yeah, fifty
Speaker 6: academic look our first time doing this, you will be convinced.
Speaker 6: I could do a fifty page, single space ofp ed.
Speaker 3: I believe it.
Speaker 5: I know you can't.
Speaker 6: It's just as a quant as a statistician, you'd like
Speaker 6: to see a hundred bubbles have stats on each one.
Speaker 6: This way, they're all they'd rhyme, but they wouldn't be
Speaker 6: exactly the same you tease out what's going on. If
Speaker 6: you see two in a thirty five year career, You're
Speaker 6: not gonna be able to prove this statistically. But I
Speaker 6: believe in my conjectures. I'm not soft selling them. I'm
Speaker 6: I just wanted clear that nobody is going to walk
Speaker 6: away saying.
Speaker 5: He proved it.
Speaker 6: I list a few reasons in the piece why markets
Speaker 6: might be prone to bouts of bigger disconnects from reality.
Speaker 6: My second favorite is one I'm sure you've talked about.
Speaker 6: I know I've listened to you guys talk about it,
Speaker 6: the rise of passive investing. I am not a passive hater.
Speaker 6: They're really smart people. Mike Green's out there the Mount.
Speaker 6: That guy hates passive.
Speaker 5: I don't know.
Speaker 6: The Middle East has never seen hate like the Mount.
Speaker 6: Mike Green hates pass but again, he's a smart guy.
Speaker 6: He makes interesting arguments. I'm not that guy. I think
Speaker 6: passive has been a huge positive for an investor welfare.
Speaker 6: I actually was lucky enough to be fairly good friends
Speaker 6: with Jack Bogel, and he was a hero of mine.
Speaker 6: We had a podcast briefly and he and he came
Speaker 6: on it. In fact, i'll tell you part of that
Speaker 6: story in a second. So I'm not a passive hater.
Speaker 6: But here's what we know. We know the whole world
Speaker 6: cannot be passive. And when I say passive, I mean
Speaker 6: in a Jack Bogel market cap weighted sence. Some nice
Speaker 6: people use passive for people like us, and they really
Speaker 6: mean rules base and that's not how I use the
Speaker 6: word passive.
Speaker 3: I mean someone who owns the entire mark.
Speaker 6: Yeah, we're long, short and leverage. How you get to
Speaker 6: passive on that, I don't know, but some people do.
Speaker 6: I own the entire market. We had Jack on the
Speaker 6: podcast and he absolutely agreed everyone can't be passive. Now,
Speaker 6: of course, being Jack Bogel, he thinks at that point
Speaker 6: the marginal investor should still move to passive. But he
Speaker 6: recognizes the obvious fact that if one hundred percent of
Speaker 6: the people are not looking at prices, nobody's looking prices.
Speaker 6: Who's figuring out if Nvidia is worth more or less
Speaker 6: than the corner drug store? Right, So the market gets
Speaker 6: very weird there. We don't even understand what happens. It's
Speaker 6: a singularity. I use a physics analogy. We don't know
Speaker 6: what happens there. PhD students in finance, and I used
Speaker 6: to be one of these, will stay up late at
Speaker 6: night in their cups talking about what happens if everyone
Speaker 6: was passive. What would it even look like? We know
Speaker 6: it's very weird, and I doubt all the weirdness happens
Speaker 6: between ninety nine point nine nine nine percent passive and
Speaker 6: one hundred. So we're on a curve. We're a lot
Speaker 6: more passive than we used to be. Even that you're
Speaker 6: probably aware, it's hard to measure exactly how much just passive,
Speaker 6: direct passive true market cap weight you can measure. But
Speaker 6: what about people who take you know, eighty basis points
Speaker 6: of tracking era, they're kind of mostly passive.
Speaker 3: You have, remember, pegged.
Speaker 2: To like custom indices. Now, it's kind of funny you.
Speaker 6: Guys remember the Princess Bride? Yeah, yeah, remember mostly dead.
Speaker 6: I'm fully dead. You're mostly passive. So I think fewer
Speaker 6: people thinking about prices, fewer people willing to take the
Speaker 6: other side when things get a little crazy. If one
Speaker 6: side really starts to get crazy, there are fewer people
Speaker 6: out there that has to exacerbate these swings. My actual
Speaker 6: number one reason, though you talked about the gamification, for me,
Speaker 6: it's the overall, I'm going to sound like a very
Speaker 6: old man yelling at the sky on my lawn right now,
Speaker 6: you know, get off my lawn, or.
Speaker 5: Yelling at the sky some Simpsons thing. Yeah, I'm abe
Speaker 5: in this case.
Speaker 3: But Saniel's a cloud.
Speaker 5: Yeah exactly.
Speaker 6: Thank you social media and the broader environment that you
Speaker 6: guys were talking about. I don't want to do politics
Speaker 6: except to say I don't think you find many people.
Speaker 6: There'll be some, but I don't think you find many
Speaker 6: people who don't agree with the idea that this environment
Speaker 6: has made our politics worse and more dangerous confirmation bias.
Speaker 5: We live in our own bubbles.
Speaker 6: We have algorithms that push us further and further towards
Speaker 6: You start out as a moderate belief, but it keeps
Speaker 6: pushing you towards extremes, and pretty soon you're saying stupid
Speaker 6: things like, Hey, that Tucker Carlson.
Speaker 5: He's a good guy. All right, I might have revealed
Speaker 5: a little poem.
Speaker 2: Yeah you did a bit of politics there.
Speaker 5: So all of that adds up to making our politics worse,
Speaker 5: more prone, in particular to swings and extremes. Markets are
Speaker 5: not arbitrage mechanisms that sometimes misunderstood they're voting mechanisms.
Speaker 6: The price is a weight at average vote, where the
Speaker 6: weight is by dollars. I lucky enough to get more
Speaker 6: vote than the average person, and Warren Buffett gets a
Speaker 6: lot more votes than I get if we all disagree
Speaker 6: on opinions. The reason it's not an arbitrage mechanism. And
Speaker 6: here I'll get a little geeky. Imagine you're reasonably sure
Speaker 6: this thing is mispriced in that Graham and DoD sense,
Speaker 6: and you think it's massively mispriced, trading enough to make
Speaker 6: it a third less mispriced. It's not very risky to
Speaker 6: you because it's not that big a trade, and it's
Speaker 6: it's very high expected return because it's that mispriced. Now
Speaker 6: you've moved it back to a third or maybe half,
Speaker 6: the next part of the trade is much riskier to
Speaker 6: you because you already have the trade on, so you're.
Speaker 5: Just adding more.
Speaker 2: Oh, I see it.
Speaker 5: Yeah, and it.
Speaker 6: Has half the game because you've already closed it by half.
Speaker 6: So arbitrage will not take things. If on net more
Speaker 6: people believe something stupid, stupid's gonna win, and we're going
Speaker 6: to be at least somewhat off of real prices. And
Speaker 6: I find it remarkably easy to believe that this same
Speaker 6: environment that makes our politics go a little crazy for
Speaker 6: markets to be efficient in any degree, not even perfectly efficient,
Speaker 6: This famous idea of the wisdom of crowds has to
Speaker 6: be helping us a lot. The hypothesis that we're all
Speaker 6: geniuses is never gonna fly, right. So the wisdom of
Speaker 6: crowds and you know it well says, even if on
Speaker 6: average most people don't know the answer, the stupid answers
Speaker 6: cancel and the right answers don't because they're the same.
Speaker 6: My favorite example of that, and this it might be
Speaker 6: dating myself is Regis philbin and who wants to be
Speaker 6: a millionaire?
Speaker 5: Right? Remember the show Multiple Choice.
Speaker 2: Showy, it's frightening that you're describing that as old, but
Speaker 2: I guess it is.
Speaker 5: Yeah, it's been off the air, sadly Regis has passed away.
Speaker 5: It's old.
Speaker 6: Sorry, sorry, but you had to answer multiple choice questions
Speaker 6: and if you miss one, you're out. They start off
Speaker 6: ridiculously easy, and they get harder and harder. You had
Speaker 6: multiple cheats, like three cheats. One was a friend was
Speaker 6: almost useless. A friend usually wasn't much smarter than you,
Speaker 6: and b people at least to my eye, I didn't
Speaker 6: watch every episode, but seemed to choose friends who knew
Speaker 6: the same stuff they knew, Right, you really want to
Speaker 6: choose a friend who is in like a totally different field.
Speaker 2: I think in some countries the friends also had a
Speaker 2: tendency to deliberately give the wrong answer because they just
Speaker 2: didn't want to see their friend actually win money.
Speaker 5: Well, the most cynical phrase ever is nothing succeeds like
Speaker 5: a friend's failure.
Speaker 6: I don't believe I'm not condoning that, but it is
Speaker 6: out there. The other one was eliminate two of the
Speaker 6: row answers. That's great, obviously, even if you have no idea.
Speaker 6: You go from one out of four to one out
Speaker 6: of two.
Speaker 5: The other one was pulled the audience.
Speaker 6: And at least to my non exhaustive examination, it seemed
Speaker 6: to work pretty much every time, even if.
Speaker 5: The question was hard.
Speaker 6: Because imagine you have one hundred people in a room.
Speaker 6: Ten of them know the answer, the other ones are guessing.
Speaker 6: The ninety distribute evenly over the four. Maybe not perfectly evenly,
Speaker 6: but roughly evenly. The ten all land on B. So
Speaker 6: you pick B because it's bigger. Work pretty much every time.
Speaker 6: There's a crucial assumption in that the audience has to
Speaker 6: be releively independent of each other.
Speaker 5: And they did that. They weren't talking. It was silent voting.
Speaker 6: If the audience all gets to talk, maybe the ten
Speaker 6: convinced the ninety, but maybe they don't. Maybe a demagogue
Speaker 6: with a better Twitter feed convinces everyone. And if you
Speaker 6: ruin the independence, and I think, have we ever come
Speaker 6: up with a better vehicle turning a wisdom of crowds
Speaker 6: into a craziness of mobs than social media?
Speaker 5: I'd be hard pressed to describe it.
Speaker 3: I find this would be very compelling.
Speaker 4: James sir Wicket at the New York Times, he came
Speaker 4: out with that book Wisdom of Crowds in two thousand
Speaker 4: and five, but that was right before social media blew up.
Speaker 4: And then you know, there's that famous book in eighteen
Speaker 4: forty one, Extraordinary Popular Delusion and the Madness of the Crowds.
Speaker 4: So we've always sort of understood that crowds can be
Speaker 4: both mad and wise. And I find this very interesting,
Speaker 4: the idea that perhaps the linkedness of the crowd is
Speaker 4: what sort of flips it from wisdom to meta.
Speaker 6: I think that's exactly It maybe can come up with counterexamples,
Speaker 6: but I think most of the time, if the crowd
Speaker 6: is making independent decisions, then this can go for political voting,
Speaker 6: it can go for markets. You're going to get some
Speaker 6: degree of wisdom. When the crowd is all making a
Speaker 6: unified decision, it could still work out, but you are
Speaker 6: much more susceptible to what the quants technical term is.
Speaker 4: Craig, Craig, I want to pivot a little bit and
Speaker 4: talk about AI. You've written or you've talked recently. I
Speaker 4: forget exactly the word that was used in some of
Speaker 4: the headlines succumbing to the rendering, our surrendering.
Speaker 3: To the I regret saying so forth.
Speaker 4: We tried to talk a lot about AI. I still
Speaker 4: don't know exactly what it means in any context. What
Speaker 4: does it mean to surrender to the machines in the
Speaker 4: AQR context?
Speaker 6: Well, first, not every journalist has Bloomberg's high standards. I
Speaker 6: am reasonably certain I said partially in that, and the
Speaker 6: word partially got dropped even skipping all the details. If
Speaker 6: you're going to use AI in your process at all,
Speaker 6: almost by definition, you were gonna lose a little intuition,
Speaker 6: and it bothered me for a couple of years. I
Speaker 6: think I slowed us down on AI by a year
Speaker 6: or two just by saying, you know, we've always prided
Speaker 6: ourselves on the balance of we intuitively understand why we
Speaker 6: think this makes money and the evidence that it makes money.
Speaker 6: And when you go to AI, you're normally giving.
Speaker 5: Up some not all. We actually do try very hard
Speaker 5: to figure out why we think this works or doesn't work.
Speaker 5: But if you weren't giving up some intuition, what the
Speaker 5: heck is the AI doing. If it's simple and you
Speaker 5: could have just seen it with the naked eye, it's
Speaker 5: hard to imagine it's helping. But let me give you
Speaker 5: a concrete example. We like good momentum.
Speaker 6: We like it in price, we like it in fundamentals.
Speaker 6: One way people on the QUANDT side have tried to
Speaker 6: measure this for years is something like Earning's calls, trying
Speaker 6: to decide if Earning's calls a good news are bad news,
Speaker 6: and if people underreact to good news, you want to
Speaker 6: buy when it's good news.
Speaker 2: Is this just like how many times people say great quarter, guys,
Speaker 2: or are you looking as something else?
Speaker 6: It's gonna sound about as silly as that you build
Speaker 6: up tables of words and phrases with numerical values and
Speaker 6: then you say, what's the numerical score of this? And
Speaker 6: they can be much more subtle than this. I'm gonna
Speaker 6: use a real simple example the word increasing plus one, right,
Speaker 6: and I'm sure you see the flaw. If the actual
Speaker 6: sentence was massive embezzlement is increasing, you know, are bad
Speaker 6: on that one.
Speaker 2: The amount of fraud we're seeing in our private credit
Speaker 2: deals is increasing.
Speaker 6: Quant can survive looking stupid a lot. If that's forty
Speaker 6: seven percent of the time, If fifty three percent of
Speaker 6: the time it's getting it right, fine, And those things
Speaker 6: had some efficacy, but they weren't great. What we do
Speaker 6: today is we train mL. It's called natural language processing.
Speaker 6: It's the sub field of mL to analyze corporate statements.
Speaker 6: But what it does, and this is going to be
Speaker 6: the geekiest thing, I'll say, it represents every corporate statement.
Speaker 6: It looks across them and presents them as a set
Speaker 6: of numbers, what the geeks will call a vector of numbers.
Speaker 5: Then what we do is empirics to.
Speaker 6: Say, all right, we have fifty years of this across
Speaker 6: many firms. We have different vectors or numbers for every
Speaker 6: earnings call. What combination go long when the first number
Speaker 6: is good, short when the second number is high?
Speaker 5: Blah blah blah. What best combination forecasts?
Speaker 6: That seems to be correlated to what we were doing before.
Speaker 6: These word count things just considerably better.
Speaker 5: It does a better job than word counts.
Speaker 6: That language is very nonlinear whether something is good, whether
Speaker 6: that word increasing is good. AI is not perfect, but
Speaker 6: it's chance of figuring out if increasing was good or bad,
Speaker 6: especially when it's trained on tons of these Yes, better
Speaker 6: than us. Here's where you lose the intuition. Though I
Speaker 6: skip a step.
Speaker 5: I like to do that. It's fun sneaky.
Speaker 6: If you ask myself or even some of the younger
Speaker 6: people who are much more tooled up on machine learning
Speaker 6: than I am these days, what does that vector of
Speaker 6: numbers actually mean? You often get, Ah, we really can't
Speaker 6: tell you that.
Speaker 5: We can say it.
Speaker 6: It's summing up, in a mathematical sense, the information content
Speaker 6: of that. We still get intuition because this indicator acts
Speaker 6: like a short term momentum indicator, so it's picking up
Speaker 6: what we wanted to pick up. It's also done fabulously
Speaker 6: well for us for multiple years in real life, but
Speaker 6: we are giving up intuition at one stage that we
Speaker 6: used to not do. So my answer was meant to
Speaker 6: be much more subtle, that there are give ups in
Speaker 6: intuition when you move to something like machine learning. They
Speaker 6: almost have to be or use again, what are you doing?
Speaker 6: I was uncomfortable for that for a while, so I
Speaker 6: was starting to do mia kulpa saying that I slowed
Speaker 6: us down, and it came out as well.
Speaker 5: I used to hate this, but now I have no job.
Speaker 6: The machine runs it, which is probably gonna be true
Speaker 6: in eight years, but not yet.
Speaker 2: This reminds me actually of something I wanted to ask,
Speaker 2: because another big multi year decade trend is the rise
Speaker 2: of the multi strats. And at AQR, as I understand it,
Speaker 2: you have a multistrat model in there, but it's more
Speaker 2: centralized than some other places. Can you go into a
Speaker 2: little bit more detail.
Speaker 6: Sure, they get used interchangeably, but I think this is
Speaker 6: the difference between multi strat and multi manager. Multistrat just
Speaker 6: means I wrote a dissertation on choosing US stocks. We
Speaker 6: have applied similar things to stocks around the world, to currencies,
Speaker 6: to commodities, to directional bets through trend following. They are
Speaker 6: correlated but low. So we think of these as different
Speaker 6: strategies and we think a set of our strategies is
Speaker 6: better than a single one. Or it's just the power
Speaker 6: of diversification. So we're big believers in particularly if you
Speaker 6: have a common philosophy. So it's not just fitting the data,
Speaker 6: it's fitting into an overall theme of what you believe in.
Speaker 6: We're big believers in multistrats. What we share with multimanager
Speaker 6: is that believe and diversification. Multi manager is what it
Speaker 6: sounds like it is. We are one team building these.
Speaker 6: We might of course have little separate teams at AQR,
Speaker 6: but we're one firm building these. They are farming it
Speaker 6: out to different people. To be frank, if you had
Speaker 6: told me their business model ten twenty years ago, I
Speaker 6: would have been very cynical that it worked. If you
Speaker 6: told me a what the total fees are gonna be
Speaker 6: when you add up everything that's passed through and a
Speaker 6: fair amount of them. And they vary in how quick
Speaker 6: they do this. If something's not working for what I
Speaker 6: would consider a very short while, yeah they stop doing it.
Speaker 6: And I know there are a lot of load to
Speaker 6: medium sharp ratio risk adjustive return strategies that are really
Speaker 6: good long term but have bad periods. So if someone
Speaker 6: told me that model, I would go, you're gonna charge
Speaker 6: a ton and you're gonna throw out people who have
Speaker 6: a bad two quarters. No, and there have been people
Speaker 6: who've obviously proven me wrong. And I'm humble about this.
Speaker 6: I don't fully understand why. They must be very very
Speaker 6: very good at actual selecting the alpha. Yeah, right, And
Speaker 6: this is something that we don't do. We're internal quants
Speaker 6: who build our own models. We've never maybe be interesting
Speaker 6: one day, we've never tried to apply that to choosing
Speaker 6: outside people.
Speaker 5: But plenty of people, by the way, have.
Speaker 6: Tried to start multi manager and failed. So it's not
Speaker 6: like you just apply this charge a ton, hire a
Speaker 6: bunch of active managers and fire them if they have
Speaker 6: a bad two hours. Just automatically works.
Speaker 2: It does seem though, that talent is the thing. That's
Speaker 2: like capping multi strat expansion, right, that's the limiting factor.
Speaker 6: They vary, but some of the major ones are giving
Speaker 6: back money. Even if you believe in this model, and
Speaker 6: I even from Afar, I have to be a believer.
Speaker 6: I've seen the results are too good for too long,
Speaker 6: in my view, to have a decent chance of randomness.
Speaker 6: I don't exactly know what they're doing. I'm still waiting
Speaker 6: for Ken and Stevie and Isy to send me their
Speaker 6: exact process. That would be wonderful is he doesn't share
Speaker 6: it with you. No, even better if Medallion would send
Speaker 6: me their exact process. But I respect it. But the
Speaker 6: amount of individual alpha from teams that can be out
Speaker 6: there has to all alpha's finite, but has to have
Speaker 6: a decently tight cap. And the ones I've seen are
Speaker 6: fairly disciplined about this, And again it varies.
Speaker 5: I can't speak for everyone. I know.
Speaker 6: We compete for talent with them much more than we
Speaker 6: used to. They have non quant parts of what they do,
Speaker 6: but they have quant parts of what they do. And
Speaker 6: for young quants, they're often considering an offer for ake
Speaker 6: you are and Citadel, to pick just one example. We
Speaker 6: win our fair share, we lose our fair share. I
Speaker 6: think we probably pay a little less in the short term,
Speaker 6: but we don't.
Speaker 5: Fire you if you have a bad week. So some
Speaker 5: people are and I'm he's not doing that. I'm just
Speaker 5: saying no. But we know that it's a more cutthroat environment.
Speaker 4: You've done a lot of episodes on that environment. We
Speaker 4: know like they cut pretty quickly if you lose money.
Speaker 4: I want to go back a little bit to the
Speaker 4: connection between sort of AI machine learning and interpretability of
Speaker 4: the factor, you know, the quintessential. You know, the risk is,
Speaker 4: of course, that you find something that works strictly from
Speaker 4: data mining.
Speaker 5: Right.
Speaker 3: Tickers that start with B tend to rise on Tuesdays, and.
Speaker 5: He's the CEO's middle initial.
Speaker 4: Yeah, stuff like that we don't like. But you know,
Speaker 4: even when you were talking about momentum and you said, well,
Speaker 4: there's two reasons theories for why momentum can work. Let's
Speaker 4: just go back to the canonical like quant factors. Is
Speaker 4: there complete consensus about why these factors work?
Speaker 5: Not at all.
Speaker 3: Okay, they you start out with the because intuitively like
Speaker 3: cheap stars go.
Speaker 4: But my impression is that there's even still disagreement about why.
Speaker 6: Yeah, you start out with the Great Divide and when
Speaker 6: when they split the Nobel Prize between Gene Fama and
Speaker 6: Robert Schiller, My co founder and I wrote a piece
Speaker 6: and the cover of Institutional Investor with that title, The
Speaker 6: Great Divide. Lars Hanson also want to share of it,
Speaker 6: I shouldn't leave him out. But Schiller and Fama were juxtaposed.
Speaker 6: Is the efficient market guy and the inefficient market guy,
Speaker 6: which is fairly close to only either of them as zealots,
Speaker 6: but it's fairly.
Speaker 5: Close to to true.
Speaker 6: So you start out if something has worked historically and
Speaker 6: made a lot of money over a long period.
Speaker 5: You start out with what you led with? Is it
Speaker 5: data mining? Let's say you convince yourself it's not. OK.
Speaker 6: Let's just put that away, and that's really important that
Speaker 6: I'm not, you know, poo pooing that step.
Speaker 5: You gotta do that. Then you got to ask yourself why.
Speaker 6: The two main contenders are a rational gene Foma kind
Speaker 6: of market where some stocks are riskier than others, and
Speaker 6: whatever you're using to say go long these and short
Speaker 6: these is loading on that risk. And if something is risky,
Speaker 6: you should make more for investing in it. One of
Speaker 6: the problems is identifying a There are sub fights within
Speaker 6: these fights. What do we mean by risk? Is risk
Speaker 6: beta like.
Speaker 4: The capital asset prices nan academics are like every other
Speaker 4: academic because fight.
Speaker 6: Talmudic at this point, But is risk beta like the
Speaker 6: capital acid pricing model? Well, the capital acid pricing model
Speaker 6: is a beautiful, elegant model that has failed everywhere it's
Speaker 6: ever been attempted. Is risk more multi dimensional? Is risk
Speaker 6: something like what happens in a great depression, which is
Speaker 6: very hard to measure. The other argument is markets are
Speaker 6: not perfect. People make errors, and its behavioral finance. So
Speaker 6: if a cheap stock beats an expensive stock because it's
Speaker 6: inherently adding some risk that you can't diversify away, that's
Speaker 6: a Gene Fom explanation. If it beats an expensive stock
Speaker 6: because people went too far, they went past the Graham
Speaker 6: and Dodd point, and if you can hold it, you
Speaker 6: make money when reality sets in.
Speaker 5: That's more than Bob Schiller point. I love Gene, He's
Speaker 5: my hero.
Speaker 6: I have probably drifted from seventy five to twenty five
Speaker 6: Gene to seventy five to twenty five Bob over my career.
Speaker 6: World's complicated. One of the hard parts is everyone wants
Speaker 6: to win. But both explanations can be true, and they
Speaker 6: can be true at different times. Life isn't so simple.
Speaker 6: But those are the two biggies. But once you get
Speaker 6: into behavioral finance, now you can fight about why what
Speaker 6: behavioral bias? Notice you could sum up the two reasons
Speaker 6: I gave you for momentum as underreaction and overreaction. Overreaction
Speaker 6: is chasing right. Underreaction is the information came out, didn't
Speaker 6: move far enough, and I hopped on that bandwagon. You
Speaker 6: know you're in a little bit of a dodgy area
Speaker 6: when your two best explanations sound a little like antonyms.
Speaker 5: Now I'm being intentionally funny.
Speaker 4: We know it works, we're just not sure whether it's
Speaker 4: literally opposite things or intuitively opposite things.
Speaker 3: If we know it's one of them, and.
Speaker 6: There's some being a little too negative, you can actually
Speaker 6: they're good papers. Teasing out the underreaction is easier to show.
Speaker 6: You can actually show the fundamentals do catch up. I
Speaker 6: think the overreaction probably kicks in more in bubbles where
Speaker 6: there is just more feedback trading. Again, both explanations can
Speaker 6: be true, and they can vary in their intensity over time.
Speaker 6: The overreaction might have a very small part of it,
Speaker 6: except plus a minus two years around a major bubble,
Speaker 6: when it may be the driving force. So we have
Speaker 6: to get really comfortable. We don't have to have the
Speaker 6: be all, end all, single explanation. But if there are
Speaker 6: a few good explanations and no real counter ones, and
Speaker 6: we have really strong fifty year empirical results. Yeah, we're
Speaker 6: okay with taking some.
Speaker 5: Bet on this. You never want to put all your
Speaker 5: money on one thing that's not a quant thing.
Speaker 2: I'm going to try to connect a bunch of the
Speaker 2: sort of decade long mega trends that we've been discussing.
Speaker 2: But I'm thinking behavioral finance, gamification markets, big data, AI,
Speaker 2: all those fun things combining into sports betting, which seems
Speaker 2: to be getting bigger and bigger than ever. And the
Speaker 2: reason I ask is because I was talking to someone
Speaker 2: in a bar the other day and they said that
Speaker 2: AQR was doing more sports betting stuff.
Speaker 5: Someone in a bar was talking about AQR doing.
Speaker 2: Sports Yeah, no, well, it probably says more about the
Speaker 2: bars that I'm in and the people I'm talking to
Speaker 2: than anything else.
Speaker 6: But yeah, they mentioned I'm picturing the Star Wars canteena
Speaker 6: right now.
Speaker 5: I gotta tell you.
Speaker 2: So, I'm just curious, is that a thing or are
Speaker 2: you maybe interested in the sort of prediction market aspect
Speaker 2: of things nowadays? Susquehanna is getting into it.
Speaker 6: I think no one again tells you exactly what they're
Speaker 6: they're doing my senses. They are into it and are
Speaker 6: good at it. This is incipient for us. We are
Speaker 6: considering and looking at it. We have a long history
Speaker 6: Toby Moskowitz, who's a Yale professor and an AQR partner.
Speaker 5: Great deal, by the way, you get paid for two
Speaker 5: full time jobs that are eighty percent overlap.
Speaker 6: I keep that in mind for the Toby's listening. Just
Speaker 6: you know, you're a lucky man. He wrote a book
Speaker 6: called score Casting that was all about sports. But the
Speaker 6: sports analytics, the moneyball type stuff looks a lot like
Speaker 6: what we do. It looks a lot like people are
Speaker 6: not pricing this right people. I wrote my most downloaded
Speaker 6: paper ever, which is really a little annoying because it's
Speaker 6: like the only one I've written outside of my field,
Speaker 6: was on when to pull the goaltender in a hockey game? Yeah,
Speaker 6: and I wrote it with a colleague and friend, Aaron Brown.
Speaker 6: We built a model and we came up with you
Speaker 6: should be pulling the goalie if you're losing by one
Speaker 6: with five or six minutes left, not with two minutes left.
Speaker 6: And I'm pretty sure we're right. We spent a lot
Speaker 6: of time in that paper saying why aren't they doing
Speaker 6: it and making analogies to investing, you know, when people
Speaker 6: know the right thing to do but can't do it
Speaker 6: because the public opprobrium if they get it wrong will
Speaker 6: be much worse.
Speaker 4: Like aren't there saying like football teams should go forward
Speaker 4: on fourth down a lot more than they do And
Speaker 4: that's like one.
Speaker 6: Of these things that happened and they have started to Yeah,
Speaker 6: there is a feedback where some of these things are slow,
Speaker 6: some of them are fast. Baseball has largely absorbed a
Speaker 6: lot of these things. You know, on base percentage was
Speaker 6: one of the major insights of moneyball, and no nobody's
Speaker 6: missing that one anymore. But we still think, particularly in
Speaker 6: the betting markets, are not probably not as rational as
Speaker 6: Toby's scorecasting book. So we do think there might be
Speaker 6: opportunities there. But I don't want to overstate it just
Speaker 6: because I am cynical about online sports betting.
Speaker 5: I gotta tell you two things.
Speaker 6: I was always a very libertarian guy. I still think
Speaker 6: I am, but a couple things have made me less libertarian.
Speaker 6: Children The existence of my children will make you go, yeah,
Speaker 6: maybe people shouldn't be able to do anything they.
Speaker 5: Want when they turn twenty with rules and sports.
Speaker 6: Betting and maybe walking down the New York City streets
Speaker 6: and getting a contact high sports betting. We're already, you know,
Speaker 6: some of these scandals were starting to see how do
Speaker 6: you not have them? When you know some of these
Speaker 6: people make a ton of money, but they don't all
Speaker 6: make a ton of money, and there's a lot of
Speaker 6: money in sports betting. Anything you do for entertainment is
Speaker 6: fine if you do it entertainment size. If you go
Speaker 6: to Las Vegas and you go the odds are on
Speaker 6: the house's side. I'm gonna lose five hundred dollars over
Speaker 6: two days probably If I win, great, but it's gonna
Speaker 6: be fun.
Speaker 2: It's factored into the cost of a Vegas.
Speaker 6: But like, I have a whole bunch of twenty something
Speaker 6: year old mostly guys in my extended family. A lot
Speaker 6: of them are sports betters, and they're not even It
Speaker 6: even pisses me off that they're not even rooting for
Speaker 6: their teams anymore.
Speaker 5: They're kind of rooting for this player to score on
Speaker 5: their prop.
Speaker 2: It is a strange dynamic.
Speaker 6: Y So do I think that gamification is highly related.
Speaker 6: I think if you go look at the robin Hood
Speaker 6: app and fan duel. I think you will find they
Speaker 6: are far more similar on their feedback and how they
Speaker 6: treat things and in how their investors do on average,
Speaker 6: particularly sports betting. You know, investors lose on average because
Speaker 6: the sports betting companies make money. It's like staying on average.
Speaker 6: Insurance is a bad deal, you know how. I know
Speaker 6: because insurance companies are profitable doesn't mean it's stupid to
Speaker 6: do because maybe if it's in a risk you can't tolerate,
Speaker 6: that could be a fair trade.
Speaker 2: If there's a price you pay for a peace of mind,
Speaker 2: which is something I've come to appreciate over the course
Speaker 2: of ten years.
Speaker 6: There is zero chance that the average online sports better
Speaker 6: is making money.
Speaker 4: Yeah, I just have one last question, you know. I
Speaker 4: think if you looked at, like some particularly crazy times
Speaker 4: in markets, here's something that's changed very much since we
Speaker 4: started the podcast first ten years ago. I think if
Speaker 4: you look at some crazy times in markets, whether it's
Speaker 4: you know, twenty nineteen when some of these measures were
Speaker 4: getting extreme, we're just you know, the spack mania of
Speaker 4: twenty twenty one. One theory that one might have offered
Speaker 4: is zerp and he's like, oh, this is now we have.
Speaker 4: You know, we haven't been at zert for a long time,
Speaker 4: and yet some of this sort of speculative mania crazes
Speaker 4: has not gone away. How surprised are you that the
Speaker 4: move from zero percent to say five percent or whatever
Speaker 4: didn't have more of a sapping effect on some of
Speaker 4: the behavior and speculative fraud or just sort of animal
Speaker 4: spirits in these markets.
Speaker 5: I am mildly surprised.
Speaker 6: Okay, I left this out, but I actually had three
Speaker 6: possible reasons in my paper, and the third one was
Speaker 6: super low interest rates for a long time for why
Speaker 6: things can get crazy now. The counter argument is, once
Speaker 6: you break people's brains, they don't necessarily repair themselves instantly,
Speaker 6: So I think it was probably a contributory factor. Again,
Speaker 6: very hard to prove. A lot of people in nineteen
Speaker 6: and twenty when the spread's being cheap and expensive. We're here,
Speaker 6: We're saying it was a super low interest rate environment,
Speaker 6: and gross stocks have more cast flows in the future.
Speaker 6: Low interest rates means they're worth more.
Speaker 5: We did the math on that.
Speaker 6: It explained like two percent of the insuring value spread,
Speaker 6: and in ninety nine two thousand interest rates were quite hot,
Speaker 6: so it's not a unified field theory explanation. Do I
Speaker 6: think it helped kickstart them. And again we're in the
Speaker 6: soft guess work, but I think these are educated guesses
Speaker 6: and I listed it as one of my three. I
Speaker 6: think it's certainly kicked us off on some of these things,
Speaker 6: certainly loosen the bounds of rationality.
Speaker 5: Absolutely, free money, we'll do that.
Speaker 6: I don't think it's not human nature that they take
Speaker 6: away zup and everything comes back. Would I have thought
Speaker 6: it was a bigger effect in going back to you know,
Speaker 6: at one point we hit about five percent on the
Speaker 6: ten year almost five percent.
Speaker 5: Would I have thought that would have mattered more.
Speaker 6: Yeah, only in twenty twenty two did we see one
Speaker 6: ugly year over that. But it has mattered less than
Speaker 6: I thought. It doesn't mean it will never matter.
Speaker 2: All right, Cliff Astnes, thank you so much for coming
Speaker 2: off all the lots kicking off our ten year anniversary
Speaker 2: celebration again.
Speaker 3: Yeah, thank you so much.
Speaker 2: That was really a pleasure.
Speaker 3: Thank you, Joe.
Speaker 2: That was so much fun.
Speaker 3: It was great.
Speaker 2: Literally the perfect guest, literally the perfect guest.
Speaker 5: One.
Speaker 2: Well, there's so many things that stuck out from that conversation,
Speaker 2: but one of the things that stuck out from the conversation.
Speaker 2: It's this idea about the thing that flips the wisdom
Speaker 2: of crowds into the madness of crowds, right, And the
Speaker 2: idea that maybe wisdom of crowd's theory works as long
Speaker 2: as everyone is sort of isolated and independent and making
Speaker 2: their own choice off of the information available to them.
Speaker 2: But it starts to fall apart when everyone is tied
Speaker 2: to everyone else and sort of in the same social network.
Speaker 2: And you know, if you think about one of the
Speaker 2: dominant themes in markets in recent years, it has been
Speaker 2: people hurting into the same positions. Right.
Speaker 4: I found that to be really fascinating. I think it
Speaker 4: makes it a lot of intuitive sense. It probably can
Speaker 4: explain a lot of things about the world of politics,
Speaker 4: about the world of markets, et cetera.
Speaker 3: This idea that we're all just sort.
Speaker 4: Of one connected global village, as Marshall mccluan put.
Speaker 2: It, we're all just gossiping with each other all.
Speaker 3: The time, just constant talk, talk talking.
Speaker 4: No, that's a very interesting idea, and also those interesting
Speaker 4: the idea of length of draw down versus depth of
Speaker 4: draw down and the former being more painful, which strikes
Speaker 4: me is something I hadn't really heard anyone talk about
Speaker 4: that before, but especially from the perspective of a manager
Speaker 4: of other people's money, it's a very highly intuitive that
Speaker 4: makes a lot of sense to me that Okay, like, yeah,
Speaker 4: you had a bad quarter or whatever. Eventually you're like, oh,
Speaker 4: your ideas are just out of date. It's been three
Speaker 4: years since you've made money. Maybe time to rethink some
Speaker 4: of your fundamental assumptions people.
Speaker 2: That's one thing I've learned over the course of ten years.
Speaker 3: Yeah.
Speaker 2: The other thing was the idea of markets not necessarily
Speaker 2: being an arbitrage mechanism, which I think is very counterintuitive
Speaker 2: to the way a lot of people will think about markets,
Speaker 2: and this idea that like, well, sometimes you can't compress
Speaker 2: the price all the way to where it should be
Speaker 2: rationally or logically or according to EMH or whatever, because
Speaker 2: the reward just isn't necessarily there to get to that
Speaker 2: like final ten percent.
Speaker 4: It's interesting to think about the sort of link between
Speaker 4: patterns and interpretability why something works.
Speaker 3: And in our.
Speaker 4: Conversation a couple of weeks ago with Ian Dunning of
Speaker 4: Hudson River Trading, is like, they do not put a
Speaker 4: lot of emphasis on interpretability there's a pattern and some
Speaker 4: reasons to establish that the pattern works, it makes money.
Speaker 4: The idea that they then have to also come up
Speaker 4: with an economic story about why it works is not
Speaker 4: so important to them. Maybe that's because it has to
Speaker 4: do with time frames. Obviously, cliffs trading time frame is
Speaker 4: going to be very different than a high frequency trading
Speaker 4: firm like HRT.
Speaker 3: But it is interesting. And then it's interesting to think
Speaker 3: that even in the.
Speaker 4: Most established quant patterns like why do cheap stocks outperform
Speaker 4: more expensive stocks over the long term?
Speaker 3: Right, even there.
Speaker 4: There's dispute about why this pattern holds, even though it
Speaker 4: feels a little bit more intuitive. So much interesting stuff here.
Speaker 2: It's also I guess it sort of warms my old
Speaker 2: cynical heart that maybe maybe the edge for humans will
Speaker 2: be spotting the regime change, right, which, you know, at
Speaker 2: least there's something left for us to do if it's
Speaker 2: not just pure pattern recognition. There's that one very difficult
Speaker 2: to good luck to us. Yeah, all right, shall we
Speaker 2: leave it there.
Speaker 3: Let's leave it there.
Speaker 2: This has been another episode of the All Thoughts podcast.
Speaker 2: I'm Tracy Alloway. You can follow me at Tracy Alloway.
Speaker 4: And I'm Jill Wisenthal. You can follow me at the Stalwart,
Speaker 4: follow our guest Cliff Asnest He's at Clifford Asni. Follow
Speaker 4: our producers Carmen Rodriguez at Carmen armand dash O Bennett
Speaker 4: at Dashbod and Kelbrooks at Kelbrooks. From our odd Logs content,
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