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I was hoping to be like one of those like clips on TikTok you see.
Fake that's the thing you look like you're on a podcast pads on home.
Now it just looks like, you know.
Instead of we just randomly got together the.
Chat and microphonest.
It is like with Bloomberg podcasts behind us.
Yeah right, I guess we've conveyed podcasts efficiently with all of the Bloomberg podcasts.
Joe.
Part of the reason this has to be on video is because Matt shaved. Matt has had a beard for the past I don't know that.
I've had a winter beard from like Christmas break through memorild.
That I shaved over COVID for the first time in about thirty years. Okay, and my kids freaked out. Yeah, they were like, you're an alien.
Yeah, my kids didn't care that much. But one of my sons said, it's a different daddy.
Well, you also have hair on the top of your head when you shave the beard and you don't have any hair, Suddenly you're mister clean.
You just does mister clean.
No, I don't think so, mister clean. You know clean, Come on, I think that's a fair point.
It's the Money Stuff podcast. We have a guest, Cliff has runs a q R. Thanks for coming in, Thanks for having me. I always like to ask how to my managers, like what do you do for a living? Like what is it like economic function of like the business that you run.
Okay, those are to me slightly different questions.
Right. One sounds like it's about you. One sounds like it's about AQR.
I'm more interested in even if it's about a q R. What you do for a living is And people might not like this phraseology, but you're trying to predict what happens to securities. You're trying to buy ones that go up either in the absolute or more than some benchmark, and and sell ones that do the opposite. The broader question, which I think is behind what you're saying, is what do you do for the world by doing that? And
they overlap, but they're not exactly the same thing. Something can have a net positive effect on the world even if you're not waking up. And I'll admit this, I don't think most people in their jobs waked up and always think that way, and certainly not active managers just go I am just making the world a better place.
They're thinking, is in Nvidia undervalued? Is it overvalued? The things that I think you do for the world.
Is first, take the other side of positions other people disagree with you on or don't want to bear. That can take two forms. That can mean one of you is biased and wrong.
You hope it's not you.
But in that case, what you do for the world is you move prices back towards not necessarily all the way too in the abstract, the correct price. That's hard to define, actually, but something is mispriced and you take the other side of that.
It could be a risk premium. Other people don't want to bear in a lot of strategies necessarily that they're making an error.
If a merger's announced and three quarters of the pop you should get if it closes happens, a lot of people might not want to stick around for that last quarter.
And if you're willing to.
Take the other side of that, maybe you get paid a little for doing that, and that is a service to the market. People want to get out and you're helping. That's kind of the positive side, But again it's not what you're thinking about.
When you do the trade.
There are positions active managers will take that are not about that.
Let me put it this way.
If what you're trying to do is predict returns, you can predict returns because the price.
Is moving towards truth.
But you can also make money if you predict the price moves further away from truth.
You know, if you're a.
Momentum memestock investor. And doesn't mean you can't get that right, you know. I think of that a little more as trading than investing. But they all come together, and it even gets complicated within some famous quantitative factors. One famous quant factor is the momentum factor.
I asked the finance professor I should I have asked? And he said, you should ask him if momentum trading makes markets more or less efficient.
We don't fully know, but I can tell you the framework. There are two.
Competing explanations in academia and a general world that cares about these things. For why momentum on average.
Works, there's always a third that it will never.
Work again and it was just random and it was just luck. But if it's true, why does it work? I actually think these can both coexist, so it's not truly embarrassing. But it sounds embarrassing that the two major explanations one is under reaction and the other is over reaction. When you've narrowed it down to two things that at.
Least feel like the opposites, you should feel a little shame.
For a second, there's the situation just like there's a correct price and momentum is trading from below to above the.
Credit friends, Well, I'll give you two scenarios.
Information comes out and people have a behavioral bias that behavioral psychologists would call anchoring an adjustment.
They move towards all the way to the.
New information, and I think that fits a lot of intuition in the short run that can make momentum work. If you're following fundamentals or prices, good news comes out or the price moves. If good news comes out, on average, the price goes up but not enough. If the price moves, it may on average be responding to good news, and simply by observing the price move, you can say, Okay, sometimes it's wrong, but on average it doesn't quite move enough. If that's the reason, And I think the weight of
the opinion in academia I believe is towards this underreaction explanation. Then, even though you're trading on momentum, you're still moving the price towards kind of truth or equilibrium or something. But the flip side is overreaction. Do you think of that more as just your classic positive feedback loop. Someone's buying something just for you know, fomo. It's been going up in there, and well that could be a negative reason, or they're just predicting more people buy it because of Fomo.
In that sense, if you buy some weird meme coin, you could do that for a rational reason, not that you are a long term holder, but you just believe it's going to keep going.
So did you make money on GameStop?
This the god's honest truth.
You won't believe me. I have no idea if we were long or short game stop during the whole thing.
You never went back and check.
No, I never did. I did have an episode where I mentioned on perhaps a different TV network that we were short, AMC.
What does your Twitter look like after that?
It was very ugly. Yeah, I certainly knew of that world, even though we're quants. I watch the markets all day, even even if I don't do anything about it. It's like the old joke about the weather. Everyone talks about it, but nobody does anything about it.
Best thing to talk about.
So it's not like everything that went on with GameStop Melvin Capitol. You know, I'm watching it every day, but we take relevant tiny positions in every stock. There was nothing weird in our P and L. And yes, I was not even curious. It probably wasn't even in our universe at that point of things.
We trade.
But then I'm going on this other network it's allowed and in kind of a pre call of what are we going to talk about?
You guys know, you.
Don't want to get on there and have absolutely nothing to talk about. You want to have some not necessarily the answers worked out, but agreed upon topics. They're like everyone in this segment gives us some longs and shorts, but I'm saying, as a quant that's kind of silly. They're not indicative, and we kind of made a deal where they'd let me briefly explain that doesn't make a whole lot of sense for quantum, but it might be fun.
And my way of saying it was, if I give you a few names long and a few names short, you could look in six months later and think we had a fantastic year or a terrible year and be terribly wrong in either direction because they're tiny. So I went through an AMC was I think I'm accidentally doing it again.
We'll keep going hopefully.
They don't listen to you, guys.
But it was bad on every single thing in our model practically, which is hard to do. It was expensive, unprofitable, high beta. They were issuing shares, not buying backshit. There are more examples, and so I said that, but then I added that were only short twelve basis points, so the crazy people could be right and it doesn't really matter. I discovered two things. They're not going to like a short period, and crazy people don't always like being called crazy. Yeah,
I had to discover that from myself. So my Twitter got ugly for a while. You may have noticed. I've gotten I think a fair amount better at this, But I used to be pretty bad about responding to ugly, which you learn your lesson on that.
You always feed the trolls.
Less so than I used to. At least I think I'm better.
Maybe I'm wrong, but I became public enemy number three to the meme.
Stock crowd for a while, I did.
Not really Yes, Kenny Ken Griffin was number one. I don't believe Ken did this, but it's the whole poll, the Bible. And oddly enough, Gary Gensler was clearly number two. Yeah, because they thought he was covering for the manipulators and the naked shorts and whatnot. I've met both, I know, and a little better than Gary. I don't think there are any two people on Earth less likely to be in cahoots than those two. I think they're on the opposite side of most issues. But that was the theory.
But both Ken and Gary are too smart to respond to them on Twitter, so I certainly became the most actively engaged, and then I never did that again before today, when I've accidentally done it.
Before we get back to stuff that matters, can I just on AMC, I tweeted, when did June two come out?
It was like last summer.
Yeah, year ago.
I tweeted that I.
Fell asleep during Dune two, and it reawakened that crowd, at least on my Twitter, because I've the same.
Crowds crowd because he's dissing a movie.
Don't understand you have to like every movie or else here anti America, And then there were.
A lot of conspiracy theories about Bloomberg reporter lies about falling asleep in.
Doom too because she hates AMC. It would be, but it wasn't to.
Oh, yeah, you do innocuous that I was obnoxious, so I'd kind of deserved it.
You didn't deserve Thank you for saying that you didn't deserve it.
I haven't sent. That's not doing what I was good.
That's all too. It's pretty good.
No you didn't, actually I didn't.
You were asleep, well no, not the whole time, not the whole.
Time, but also like you and and they were like, give me some shorts, and you gave them some lungs and shorts. Would you have known that or did you have to be like I got it.
I would not have known that, right, So you don't.
Know, you're ar It would have been better for me if we didn't have the call, because then I could have just said I don't know. I rarely know individual stocks, and if I do know, I'm probably not happy I know. And even then it's like we lost twenty BIPs on that today, which is a giant number for us to lose on one stock, and even then I probably don't notice twenty bit.
If someone comes to you and says that's not.
One, I might be told about it.
For us, it's whether these seven hundred and fifty stocks be these seven hundred and fifty stocks. Yeah, I don't memorize fifteen hundred stocks. Now, we take a fair amount of risks, some funds more, some funds designed to be less. And that's about the size of these two positions. So when I say small, I'm not saying we're not both taking risk and trying to generate pretty decent returns. But if you just think about it, a quant is playing the odds.
They're saying, affirm a company with these characteristics. And this can be old school factor quants from the nineteen nineties, these can be modern machine learning. But with these characteristics tend to beat these characteristics. If that's all you know, and it is all we know, why on earth would you take a lot of risk in any one company.
AMC really could have done well.
It could have been bad on every single thing that on average doesn't work, and it could be a special situation that we don't understand. Something could be good on everything and the CEO can embezzle all the money. We don't want to take a lot of risk on any one thing because we have no insight in that it's risk for no return.
One thing you've written is that like over time, the quant like factor model has moved closer to being what Gramm and dot investors do. Like are you like an abstract like Metagram and Dada investors? I like the way to think of what you do.
I think it's moved closer.
There are still differences and maybe some of the like momentum if it's overreaction, if you're riding momentum. I don't think a Graham and DoD manager does that. So I don't want to push the analogy. But this came out very very early in my career. This is like thirty years ago. This is like my Goldman Sax days. I started hearing a lot of active stock pickers, some I'm still still friends with one guy in particular. I was laughing at them, and I was telling my friend, you
all say the same thing. You all say you're looking for valuation plus a catalyst. It's like a I don't know if everyone says it, but I've heard it many times and I'm making fun of him, and at some point he looks at me and goes, you do value on momentum, and it was a gotcha. He won that round because I'm like, okay, I see your point. So even back then, you can think of those two together.
We literally add them up.
But if you think of him as this holistic system, we're looking for cheap things that are starting to get better in price or fundamentals over time. And now I'm I'm not talking the really modern stuff, alternative data, machine learning. I'm talking just classic quant stuff that's been academia and then imports over to applied.
Profitability is a factor.
Robert nov Mark's wrote a great paper that we all incorporated where also equal give evaluation and momentum.
If a company is more profitable on some.
Famous scale's gross profitability ROA Roe, that's some degree a positive low beta investing. Two of my colleagues, Andrea Frazini and los A. Peterson, resurrecting stuff Fisher Black did, and they're very good about saying Fisher did it first. That lower beta stocks. If you're famously a capital asset pricing model person, they're supposed to sell on average underperform higher beta stocks. That's the main output of that model. It doesn't work. I mean, it's one of the largest empirical
failures ever. It doesn't work in any kind even outside of stocks people tested in other places. Therefore, it kind of makes low beta stocks a little bit of a free lunch because they are lower risk and they keep up. If you actually go read Graham and DoD, they're not just buying low multiples. They're much more holistic than that. You know, high quality companies that have a moat, that have some kind of margin of safety I think was the term they use. Margin of safety and looking for
low risk doesn't sound so so different. So over time I've thought at least a core amount of what quants and academics, if you take them as a whole, are finding, is the full paneplyy of stuff that a Graham and DoD investor. We do it very differently. Again, we're betting on the concept working on average.
They are using it.
In a soft or a hard sense as a screen to look for candidates, and then they're trying to learn a lot about that situation. They're upside as if they learn a lot about that situation, they could be more reliable than my You know, hey, we could be wrong about AMC, and their downside is they better be right. The concept can work, and they can still lose if they're wrong about the specific So over time I've gotten a little less hubrious about this. I think quants caused
the problem, by the way. I think when Gene fam and Ken French started looking at like price to book in the late eighties and early nineties, and there were other people who did it too, I'm just Chicago guy, so I'm going to just go with Fama and French. They did it best. In my very biased opinion. I don't think i'd have to go back and check, but I don't think the first few papers use the word
value investing. Over time, low multiple investing in the quant world came to be called value investing, and in the Gramm and Dodd world they get kind of mad at that, and they'd be like, it's not value investing. There are plenty of low multiple companies that deserve to be low multiple, and there are plenty of high multiple companies that deserve it, and I think over time, the quantitative process agreed with them.
More and more.
So I still think it's a communication problem because they'll still talk about the value factor. In the quant world, that's just low multiples. And if a Gramm and Dodd gets mad or any old school active stock picker gets mad at that, I'll just say you're right, because value implies a more holistic thing.
But isn't like modern quantit and what you're doing now kind of just that more holistic thing, like you're just ingesting more data plans and you have a less linear model, and it's like moving towards that.
Anyway, if you look at machine learning, where either to construct factors. One of the best uses of mL we found is a subset of mL called natural language processing, where you take textual data and you try to say is this good news or bad news? Quants have kind of done this forever. You get transcript of an earnings call.
And the old school way to do this for a long time was you count up good words and bad words, good phrases and bad phrases, so increasing plus one and you tech parse the whole thing, and sure, you guys immediately see the problem. If the actual sentence was massive embezzlement is increasing, then you were off on that plus one.
Quantitative stuff can survive doing some horrifically stupid things in isolation, If fifty three percent of the time increasing is a good word, than forty percent of the time you were stupid, turns out natural language processing or NLP, if we want to sound like the cool kids. That is, taking that same data and training a mL model to say what predicts and what doesn't predict, and of course never gets near perfect at the end of the day, though we believe it does a lot better than the word count
methods and is additive to a model. But importantly, and I think this was your point, Matt, it's not qualitatively different. We've looked at both price and fundamental momentum forever. Fundamental momentum the classic measures of things like our earnings being revised and you want the revision.
You want the new news.
Up faster or slower. Our earning surprise is coming in positive or negative. And this is this anchoring and adjustment idea that if that's good or bad news, you can make money trading on it. Because it's not fully incorporated in the stock price parsing and earnings call poorly as in the past or better now, we think of it as just another form of our good things happening in the new year term, and if so, they're probably under appreciated.
So yes, I don't think it's changed dramatically. It's much more of an evolution rather than a spirit change.
But we got bigger tools in the tool chest now.
I mean, like, you know, you ask, like what a sort of like traditional old school fundamental manager would do. One thing they do is listen to their next call and like talk to management. So it's like your machines are moving in the direction of being an old school analyst.
Yeah, as someone with four kids in or around college age, my wife and I and she's done a lot more of this, has spent a lot of time trying to figure out what careers will not be utterly destroyed by MLO, and it's not an easy question.
A podcaster is probably a good one.
For a while.
They have those fakes, so it will all be podcasters.
But yeah, it's another example. I always say, these useless statements like them sufficiently long horizon, we're all replaced by machine learning.
It's a question of what.
We're getting way too philosophical, but the transition to that can be very painful and weird. But a world of abundance and leisure. Maybe our horrible fate in the long term, I'll take it.
Yeah.
I want to talk about market timing because I was reading the Virtue of Complexity paper from Brian Kelly at All.
Which is I will say he may be one of the only hosts of a podcast to read that paper.
This is not a simple paper. It's like he writes, very clue.
It's the sort of like it's the notion of taking like a sort of simple factor model and blowing it up into like a nonlinear AI model, and one almost throwaway sentence in the pieces like this, like simplified AI model that he built for like illustrative purposes, lowered its
risk before fourteen of the last fifteen recessions. And I always thought the naive like the best way to invest would be just market timing, just like you know, have all your money in the stock market before the market goes up and not before it goes down, if you
can do it. My impression is that like respectable headgeplot managers, respectable clime managers, respectable academics say the hardest thing in the world is market timing, and like no one claims to get alpha from at and it's not a thing. Is that changed, and is that changed due to like machine learning?
It has changed a big Do we do trend following on macro assets old school CTA stuff. We think we've made a new school by incorporating fundamental momentum by doing a lot of more esoteric market so we think even that's had a march of progress to it, But all else equal. I wrote my dissertation on momentum in individual stocks for some reason that I cannot explain. If you're using past returns to predict the future, just what's going up will keep going up, and vice versa to pick
individual stocks. The whole industry calls momentum. And if you think markets tend to keep going in the same direction, everyone calls it trend falling.
Same thing. Starting in I think two thousand and eight, we started.
We always had it in our macro models, but we started formally offering separate trend falling products.
It doesn't take hero bets on anyone market.
It's not Gazarelli selling all the stocks a minute before October nineteenth of eighty seven. I'm dating myself. My wife's birthday is October nineteenth, which always always gets a little amused.
Crash eighty seven meant to.
Be Did you really crashed them together?
Yeah, there have been some jokes over over time. So trend following it's essentially market timing, but it's highly diverse, many small bets. Whatever's been happening tends to keep happening. That's the main way we'll do market timing.
You want to like your main equity fund is like sometimes.
That that was kind of a toy model to illustraate a point. I know we're not taking a lot of risks on that model. Market timing I still think is quite hard. Might there be advances in it in the future, absolutely, but are we taking significant risk in it now aside from trend following, not really.
You probably sim in more papers to financial journals than the average like asset.
Manager, by like one hundred percent.
I want to ask two questions. One is like, I want to learn about your relationship with academia, because I think it is fascinating that like you employ half of the l faculty the finance PhD pipeline runs mainly to AQR and then too because I think of like what HEGEMA manager does as sort of like finding anomalies, finding like market inefficiencies, finding factors that are predictive every turns, and I think of what a finance academic does is mainly also that when do you publish and when do
you just trade on it?
Oh, there's so much to talk about here. First, there are a lot of reasons we do it. One is just personal consumption. We grew up in this world. We liked being part of it. We were interested in this stuff in a purely academic sense before we got seduced into making money.
I mean, I.
Would like pause it that you think there is a value to employing the finance PhDs to like build your models, and the way to attract fancy finance PhDs is to offer them the most academia like possible working.
And to letting them publish. There are people, including our two Yale professors. I don't don't know if would have come take you are if we said you can never write about this. We do a crass calculation, though, if we think there is something that we are relatively unique on entirely unique, or a very small handful of people
know this, we won't publish it. The optimal the optimal time to publish a paper is after you've made money from something for eleven years and an hour and a half before someone else is going to publish the paper, and we cannot get that right. I can think of
one example of momentum in factor. It's the fact that factors themselves, like value, profitability, also exhibit momentum as something that we've traded on for many years that we've always refrained from writing a paper on because no one else has. And again, we knew we couldn't be the only people who do this, but we didn't think the cat was out of the bag. And then someone else wrote the paper. And I'm sure we've done this to other people too,
because you never know what they're doing internally. So life, you know, you do it long enough, life works out kind of fair, but that.
Is the goal.
But you were mad there because, like as academics, you wanted credit for that paper.
It's fun.
You could call it childish, but it's human. It's it's fun to discover something.
Well, you also mad because publishing that reduces the value of the signal or maybe a.
Little bit, maybe a little bit.
So far, it's still worked wonderfully. The trend is still your friend when it comes to two factors, but it would be a fireable offense for make you are to publish something that we thought was truly proprietary.
Let me give you my favorite example of this, because it came up recently.
One of the things that we've gotten into in a fairly big way, as have some other quants, is what's called alternative data. Those are new data sets that put people put together with sweat equity. The classic example and the only one. And this is the point that I'm allowed to talk about our credit card receiver data were a credit cards because that's been discussed.
A million times.
Anative there.
Yeah, yeah, Well that's the point is this stuff is arbitrageble.
I mean, it can go away.
Value, be it the narrow Quan sense of value or the more broad gram and Odd sense of value, is trying to take advantage of I think basic human nature. I think spreads being cheap and expensive are wider still than the historical average, not tighter. I don't think there's a lot of evidence that so much capital is in that that.
It's making you go away.
If you get a short term information advantage because you have put the time in or paid someone who's put the time in to create a new data set that other people don't have. They're going to have it eventually.
So I am talking to the Australian Financial Review. I don't even know if we had discussed alternative data before him, but he asked me about it, and I said to him that our head of stock selection, a fellow named Andrea Ferzini, has asked me, I might have said, told me, but has asked me not to talk.
About these things.
There are things I'll talk about, but there are things we think are you know, overused word, but our true alpha that the world doesn't know, and I think it's reasonable,
So I really can't talk about him. He writes the article and what it says is mostly that, but instead of saying he's asked me not to talk about it, it says Andrea Ferzini won't tell me what we're doing in alternative data, which it has a slightly different connotation, and that's a connotation of adult old man, don't worry about it.
We're doing some stuff here.
So again it's an example where there certainly are things we won't talk about.
Is that ever true? Are you like most cutting edge machine learning people like that? Or are that or do you read all the papers.
I read most of the papers. I don't read all of the papers. I at least skim all the papers. I know the gist. We do a lot of different things at this point. Once you're a quant you want more factors and you want to trade it in more places. And I will admit that the week doesn't go by where I don't and ask someone for a review of what we're doing. Somewhere at some point I approved it,
so Pastcliff had some understanding. Yeah, but also just you know, some of this is pretty decent math, and the old mathematicians who their best work in their twenties, I can tell you I'm probably still decent in math, but I'm not what I was when I was twenty two. Wisdom has hopefully replaced some of mathematical ability because.
The personnel at AQR different from a like I don't know who you think of as like quantity competitors, but like, my impression is that like you have many more finance PhDs than like other places that might have more like pure math people or math undergrads or something like.
Yeah, I think there's some truth to that.
What makes them better or worse?
First, I think.
There's going to be a correlation that the closer you get to the high frequency world, the more you're going to be more in the pure math realm. My very tortured analogy is quantum mechanics versus Newtonian physics. When you get into the high frequency world, first you have a ton of data. By nature, you just have a lot more instances.
And a lot less theory.
So turning yourself over to the data more so than having an economic rationale is far more rational, and that becomes a more mathematical exercise.
We tend to think in our long.
Seven hundred short seven hundred stock portfolios, average holding period is maybe nine months, maybe closer a year.
Times. That's nowhere near high frequency. Yeah, high frequent. Two.
When I wrote my dissertation and I did have this in there was a monthly contrarian strategy. Now we're talking, you know, sub seconds kind of thing. I think when you're gonna have a medium holding period strategy, as I think of us, we're not Warren Buffett, but we're not HFT.
Even the machine learning stuff needs some economics too. You simply don't have enough data and there's too much of a dimensionality even with Brian's virtue of complexity, you need to give it some structure or else it's going to overfit and go mad. So I think think that's the reason, not saying we'll never do something in a higher frequency world,
in which case we'd probably have to shift more. But in our world being a mathematician, being an excellent programmer, but also having the economics behind it, it's kind of what we're looking for.
I think of like renaissances famously employing exclusively people who have never thought about markets or financer economics, and like they come to it pure, and I feel that you are very much like people who have math shops, but like have economic intuition and think about it as an economy.
I think that's accurate. I do have a couple of Renaissance observations.
Okay.
One of my favorite questions people asked me was howd they do it? And I love that question because I get to respond. So your hypothesis is, I know how they took a few billion dollars and still take a few billion dollars out of the market to share among a relevant tiny group of people every year would apparently very low risk, and I choose not to I have
some inklings of the general whether they've worked on. My biggest guess is that they were ten fifteen years ahead of everyone else on most of this stuff and are just have developed more sophisticated systems over time. I think natural language processing they were very early on.
It came from like from.
A few other things.
John Leu and I, my one of my founding partners, wrote when Fama and Schiller shared the Nobel Prize, we wrote a whole overview of market efficiency and the debate about it, and I brought them up as an example. The Medallion Fund has almost nothing to say about market efficiency. It says, these guys can extract a toll on the market with reliable consistency, But in terms of market size it's a giant number for a few people to make
each year. It's a tiny number in terms of whether the markets are efficient, and apparently the rest of us can't do it quite as well as them. They're the goat when it comes to this.
Yeah, I think of like, you know, like Jane Street can rely excite somebody from the market, and I think of that as like a few first service ye, like a market maker, rather than being like a predictor of asset precesce.
I'm gonna guess, and again it's a purely guess that not all of it, but a fair amount of Renaissance had a similar similar flavor.
I think when you talk to people who run pod shops, like, some of what they do they conceive of as it's not literally market making, but it has that sort of flavor.
And the constraint on those things is typically capacity. Now it's a ton of money for those firms. They're amazing firms, but give you an example of Renaissance. I've complimented them like crazy, so hopefully they won't be mad at me for this.
One last comment.
Everyone talks about the Medallion Fund, but no one's allowed to invest in that. They keep that for themselves. Another favorite question I get is this doesn't happen much anymore, but every once in a while I would get an investor saying, so, Medallion Fund better than you guys. I'd be like, oh, hell yes, but they won't take your money or my money, and I think we're pretty darn good and we will. So why is that relevant? But Renaissance also runs a fair amount of money in more
open institutional products where they look very good. I'm not gonna to ride them at all, but they don't look better than us. They look like really good, solid, regular quants. So what they cannot do, I think it's kind of obvious, is take the medallion process and scale it up many, many times bigger. They've discovered a way, as you put it, to just take a certain amount out to provide a service.
I called it taking a toll, and that's amazing. But they've not discovered a way to do that at institutional scale, which thank god, because that leaves something for the rest of us to do.
I'll get back to something you talked about the very beginning, because you mentioned that paper you wrote with John Leu, which you talking about like the two possible explanations for making money for anomolies for whatever, which are sort of behavioral irrationality or whatever, and you were bearing a risk
for someone. Everything you write, and like what you said here you have, you seem sort of like agnostic about which one or what combination there's like, do you prefer one, is it more reliable to get paid for taking your risk or.
Well forgetting which one you think is really going on? They do have different characteristics The positive behind a risk premium is you may be able to get it forever because it's rational that you get it. The negative behind it is it's a risk premium. You have to figure out why. If the risk premium is most of the time this is fine, but it has depression risk. It's going to do particularly bad in a depression. Well, that's not a very pleasant risk to have. You may get
paid for doing that. The positive of behavioral is it's essentially over the long term. Over the short term it can be very very painful lunch because the noise work. But if on average it works long term, it's a free lunch and that you're not taking additional systematic risk.
The negative is it can go away.
It can be arbitraged away if that ra stops being made, If too much capital chases it, it can be arbitraged away. It's hard to arbitrage some of them away, like basic valuation. It's very easy to arbitrage some others, like alternative data, where the point is to be quicker to getting a data set and to trading the day to set. I will say this, and I hope teen Fama isn't listening. I was probably seventy five twenty five. For risk guy thirty years ago, I'm probably seventy five twenty five.
A behavioral is that GameStop or something not?
Well, the GameStop maybe the unfairly extreme example. It's not fair to pick the most extreme. Craziness is to make your point, But yeah, it's real life experience. It's watching the spread between cheap and expensive stocks in ninety nine two thousand.
We started our firm in late ninety.
Eight, so right before the real crazy part of what's called now the dot com bubble, the spread between how we define cheap and expensive, either just using quant multiples or adjusting for forms of growth, set records. We had fifty seventy five years of data and we lived through it, blowing past those. Then after that, I'm like, all right, that was a once in fifty year event.
We survived it. We ended up being right.
We ended up making money round trip that was excruciating on the first leg. If you ask me back then, am I ever going to see that in my career again? I hope I'd be smart enough not to say never. None of us in our field, yours or mine, should say never. Markets are pretty hard things to say never about. But I think I would have said it's highly unlikely. For one, it was literally the most extreme event in at least fifty years. Second, the question presupposes I and
people like me will still be around. Unpresumably, if we're still around, we're in more supervisory and authoritative positions. So how's it going to happen again? And then it happened again almost exactly twenty years later, from twenty eighteen through twenty twenty. You can point to COVID. It went absolutely mad during COVID. You guys remember for the six month period after COVID when the only two stocks you're supposed
to own were Peloton and Tesla. One of them has still worked out mostly for you.
One of them did not.
But even before COVID, though you cannot pin it on COVID, by late nineteen early twenty we were approaching tech bubble levels, which again had not been seeing the prior fifty years before. The tech bubble again, painful period for us, again made money round trip. I'm going to brag about that we survived it.
I think we're.
Stronger than we were beforehand. But if the first one didn't make you start to go this behavioral stuff may be real and maybe bigger than it.
Used to be. Yeah, and I wrote a piece.
Called the less efficient market hypothesis markets getting less efficient. That may be true, but I think it's more accurate to say there what my evidence is there prone to some extreme bouts of craziness on occasion. It's not quite the same as in steady state always being less efficient, but probably some of both. But I do think that has happened. I probably was not giving behavioral enough credit early on, and I think it's gotten to be a bigger part.
I want to read something from the Johnlely paper from twenty fourteen. Suppose you imagine some investors get joy from owning particular stocks, for example, being able to brag out a cocktail party about the growth stocks that they own that have done well. One way to describe this some investors have a taste for growth stocks beyond simply their effect on their portfolios. It can be rational for them
to accept somewhat lower returns for this pleasure. But even if rational to the individuals who have this taste, if some investors are willing to give up returns to others because they care about cocktail party bragging, can we really call that a rational market and feel this statement is useful.
I feel like that was like a little prescient about how I have experienced some of the last five years, which is that, like it seems to me that it is hard to explain some of the stuff I write about, which is maybe not like the most important thing in the world. It's often like I think the most important do too, but like it's like, you know, it's maybe not like the biggest, you know, dollar, the test LIS's
pretty big. It does seem like a thing that is regularly happening is that people have a taste for stocks beyond any rational or irrational calculation about how we'll fight their portfolio.
Well, particularly the whole meme world. Meme coins are clearly a political statement slash.
Clearly there is a non economic motivation for some of that, and you can callude rational.
But it's odd, Well a few things that paragraph.
Even writing it, I think we went a little too far because I don't think these people, we kind of write it like they're consciously doing it, like I just love owning these I know I'm gonna lose money. I think they kind of end up they resolve cognitive dissonance by saying I'm gonna make money even if that's what's really going on.
Right, I think this is maybe a little harsh on growth investors in twenty fourteen, but on MEME investors.
And now instead on meme investors. We were also given a little mild shot to some academics who kind of try to save market efficiency by saying it's more meta efficient if you count people just have tastes for this. That argument's been made. I think that's kind of a cop out. You know, if we've done market efficiency down to that, what do we actually even mean by market efficiency?
If you go, I know, I'm gonna do terrible on this, but it's fun to me, that's functionally a fairly inefficient market. So we proposed in that piece which did not catch on that classically market efficiency and the testing of it has a joint hypothesis problem. You're testing whether markets are efficient, but you also need a model for how prices are set, and if that model for how prices are set includes this is fun to own, then you've pushed it too far.
It has to be a reasonable hypothesiz.
This is what I read about this is I want someone and it's probably not me. To write a finance textbook that incorporates the factor of this is fun to own and gives some guidance how to price that.
Be and how long it's going to continue.
And people like someone is making money on this, oh yeah, and like not just like fading it. Someone is like, I have a model for which meme coins will go up, And well, people have.
Tried to do that.
You think about all the different buzzy strategies, something about ETFs real cool, you can do it. Yeah, but you know there have been attempts if you scraped social media, et cetera and find out what people are buzzing about.
But it's the old value manager's lament.
But it's also I think true if ultimately it's a bad investment in return sense that will happen eventually.
I do think that time horizon and the extremes have lengthened a lot of the point of this way, Why will it happen eventually? Why will it happen eventually?
Well, if you buy a company that continues to perform poorly and you paid a ton for it, I think there's only so long that can go on. I think it gets more and more obvious.
For one thing.
I think a lesson of the meme stack and frankly, if crypto is that fundamental sety floor and valuation. But you know, you know he's like doing LBI, right. But I don't want to just be mean to bitcoin for no reason. But like, you can certainly have a model in which you say the fundamentals of bitcoin are nothing, and you could then say and in fifty years it'll go to zero, but like that's a weird thing to say. Now, I don't know.
Well, let me be clear, one short bitcoin with my worst enemies portfolio, and I one hundred percent sure I'll never say money is a little bit of magic. What becomes money is a little bit of magic. But I think most of the probability is eventually zero, but it may be a very long time arizon. I think what we've learned watching this stuff is that time horizon is lengthened.
Okay.
In my piece on this, I try to hypothesize, and I admit it's real opinionated hypothesizing. You cannot prove if I'm right that markets are somewhat less efficient. Why gets even harder. But one of my favorite explanations is an old man complaining about social media and twenty four to seven gamified trading. I don't think most people need a lot of convincing that this stuff has made, say, our politics worse, made us more in bubbles hate each other more when it was supposed to make us love each
other more. Marcus are just voting mechanisms. I don't think it's any different than politics. So this notion that things get crazier and can go on for longer, and I have a very cynical view of your statement that this stuff might take fifty years. I think the more absolutely unsubstantiated by anything something is, the longer the craziness can go on.
Right. I think that if you compare the longevity of bitkind to like the game Stop premium, I think right.
But go back to the tech bubble.
Cisco Systems great company, but was selling at a very stupid price, selling it about one hundred PE when the e was gigantic. You can have a small startup company it's growing super rapidly, sell at one hundred pee.
One of the largest companies in the.
World with some of the largest earnings in the world selling at one hundred pe. You needed some very heroic and I would argue near. I'll never say impossible, but near impossible assumptions even if the tech bubble didn't break in March of two thousand when it did, and by the way, I still don't know why it broke in March of two thousand and not a year earlier or
a year later. Once you're well passed what I would consider rational saying you know exactly where but the time horizon, you can imagine that going on for when the growth is good, maybe even great, but not nearly enough to justify that price. It gets more and more obvious if something is based completely on air. One of the weird of down Matt's point that there's there's no arm to the upside, there's no LBO mechanism, and shorting it is just frankly too dangerous.
It's a weird way to say.
Sometimes people say markets are efficient because you can't make money from these things, and I'm like, it's another weird way to defend efficient markets to go they can be so friggin stupid that they're terrifying to make efficient. That may be totally true, but it also is a weird way to argue that markets are efficient.
What does it mean for AQR if markets are less efficient.
Well, any active management is an inherently arrogant act. You cannot tell the average person we should all be active managers, we should all have podcasts.
But I agree, So it's it's top to believe you should be an active manager and to believe you're doing something good for your clients, you have to believe two things.
That you have alpha, and that you're not charging the full extent of that alpha through your fees. And we do believe that, and a lot of active management managers believe it. But it's an inherently arrogant act. It's consistent to say most people shouldn't do this, but we should, though the arrogance is obvious.
What percent of your alpha should in your face?
That is a super hard question. I've thought about writing about this at one point. It kind of depends on how unique your alpha.
Is, Okay, because I would think that if you got a podshot manager really drunk, they would say, no.
That's what they can charge for their fees, not what they should charge. I don't think they'd ever admit them at ALGI, like Wilvers shall.
Deef in their soul. They want one hundred and ten percent.
It's a great question, but it's a hard question if your alpha is doing FOM and French price to book. By the way, I still think Farm and French are going to be right in the next thirty years. They haven't been right in a while, but spreads have gotten wider and wider, and that's been a wind in their face. I wrote a piece on this saying the long run is lying to you, saying that x the spread widening values to the simple Farm of French value has delivered alpha.
It's just lost on the repricing.
But what you can actually charge for doing price to book should be very low, a very small fraction of the expected return.
That's not alpha data, right, But.
That's kind of what we're saying. Everything exists on a spectrum from one to the other. If you have discovered and built the database yourself, an alternative data source that you have built. This is extreme and I can't think of an example at AQR that fits this. But you can charge nearly one hundred percent of that alpha because what they're getting is still absolutely unrelated to everything else
what they're doing. There is some deminimous notion that if you charge ninety nine percent, maybe no one would bother to do it. But you can charge a large fraction of the alpha because what you're delivering is still ultimately net returns that you can not get elsewhere that aren't correlated to the rest of the portfolio are worth it.
We can talk abstractly about what percentage of your alpha you should charge, but like, no one could send a bill for like ninety percent on the alpha, right, Like is pricing sort of like set by just like anchored norms.
Anchored norms is another way of saying, what are other people charge or.
In the ballpark of what you're doing?
So of course that matters, right if you are way off the anchor, way off on the high side, no one should invest with you.
If you're way off on the low side.
People who charge really high fees and are pretty good at demonstrating they have alpha, and oh.
Some of the block shops charge insane fees and have been very good, And that goes to that are they doing something unique?
And I think to some extent they are.
I think their problem becomes kind of in the direction of Medallion without going all the way. I don't think they've rebuilt medallion. Nothing is that, but they should charge a higher percent if they're doing something very unique, and they do. I have a very you can you know violin playing I think rosy view of how we think about fees. We're building a long term business. We think we have business value. We do not think we're just
a hedge fund. We run a lot of traditional assets too, even the hedge funds.
We were a big.
Pioneer in doing the more obvious strategies and considerably lower fees, starting in merger, ARB and TREND. Following the way we broke into some of those as standalone products, not as part of our multistrats was charging less and saying, you know, this is real and it's good. But you know you can do one of every merger and make a fair amount of money. But that's not magic, and we shouldn't
charge magic fees for it. But in that kind of kumbay, a big picture sense, charging fees such that clients are happy with the long term results is probably how you build business value if you step.
Back from just AQR though, I'm curious to hear your thoughts on your industry overall and whether alternative strategies in general are too expensive.
Yes, they are.
I have some numbers to back up that statement. There's a new study out there. My understanding of it is that you basically take a sixty to forty since two thousand and eight, you add Alt's exposure to it in various proportions, and that blended portfolio basically trails that benchmark, basically in close proportions to the fees that are charged by some of the ALTS managers.
And I don't know.
I read that and I was just kind of wondering. I mean, you could make the case that why are we charging so much?
Well, this is almost a mathematical certainty. Yeah, forget about ALTS for a second. You cannot tell me the average active portfolio beats the market after fees and costs.
The average active adds up to the.
Market because for every deviation one way, there's deviation the other way. When I said it to inherently an arrogant act to be an active manager, it means you think you got it, even though if you buy one of each you can't have it. I mean a subset of the market like could. But I think a lot of that still applies. It's inherently arrogant act. But we've been
saying this for at least twenty four years. We wrote a paper, and yes, I started a lot of sentences with We wrote a paper in two thousand and one called do hedge funds Hedge where we took the known indices of hedge funds and we tried to take out just the market beta. You could argue for a more sophisticated risk model, and that could as usual and go down that rabbit hole. But we found that betas were.
First of all, this is more mundane but statistically underestimated, partly because a lot of hedge funds do some stuff that is not of perfect liquidity.
And this was a small.
Early version of what I got into at the private world later on. But if something doesn't trade all the time and you try to estimate its correlation with the market, you will underestimate it because one great way to look uncorrelated is to have a three day leg, and when you trade, your returns will be off. So the betas were underestimated by earlier studies. Given the correct betas, there was pretty much no alpha to the hedge fund world.
First of all, I was a lot younger than a lot less well known, so I cared Nowadays, I quite obviously court controversy. But back then I probably had ten famous managers call me and yell at me about that paper.
Yeah. The first time, I was, of course obnoxious.
They called and said, why did you write this? And I gave the obnoxious answer because we think it's true. Now it was apparently not an acceptable answer. I will only call out one person on the positive side, Richard Perry, famous hedge fund manager.
He called me up.
And I already been yelled at by a whole bunch of people. And so when I heard Richard Perry on the phone, people like Richard Perry didn't call people like me back then.
He was big, I was small. So I'm like, I know what this is.
He's just gonna yell at me. He gets on the phone, he goes, that paper you wrote.
That's just correct.
Good job, right, And I'm only telling that. I'm not giving the names. And I do remember him, of.
Course, in a book somewhere. It's all I have a list of Vedettas and my BRAINSU.
Wait, so you've been You've been making fun of private equity managers on some lines recently. Do you get calls from them?
No, they're so fat and happy, they don't even care about me making fun. No, I get yelled at by some usually friends. I live in Greenwich connection, so you all hang out.
The country club. They're like, I'm.
Actually a country club, but the old often used in a very bad way. Some of my best friends are so I'm off the hook. I have some good friends who are private equity managers. Most of them can accept the you're right about the industry but not our firm, which is.
Essentially what I'm saying. So I can't not being mean about this.
Right, You're not like, your criticism is volatility lunder right. Your criticism is that private equity seems to have a higher sharp because it has a lower of volatility because it doesn't report.
Yes, that is my main criticism, which I think is quite obviously true.
That's just me. Some people do disagree.
The best disagreement I've heard, and I have some sympathy for this because I do not think markets are perfect, is we are right about the valuations. You are right that we move at a highly damped version of the market, but market moves too much.
We are right.
My response to that is, why don't we get to do that?
It's fair?
You know when we've had a tough year because the market's gone crazy and we were on the wrong side of that. I have to tell my clients we're down twelve percent. I don't get to tell my clients we're up based on where I'd mark the portfolio. So why one group? And by the way, they could market just like we market. They're brilliant at valuing companies and they can tell you where they could sell it for today. So it's like an institutional legal quirk that they get to do it one way and we have to do
it another. Everyone can mark their portfolio at what they could sell it for today or what they think it's worth, and one side gets to do it one one gets to do the other. So that's a reasonable argument, but I still think it leads to an unreasonable conclusion. I will say ninety percent of my critique is about the volatility or the beta, is about saying these things are low risk.
Ten percent is.
About percent if not trailing future returns, because if I'm right about the volatility laundering, it has implications for returns going forward. If when David Swenson was pioneering, which is what he called his book, Private equity is part of an institutional endownment portfolio.
He's quite clear. It's a lot of it. It's an ill liquidity premium that no one wants.
Illiquidity. Everyone's scared of it. So if you're willing to do that, you get paid extra. If I'm right that people love the fact that they don't have to look at the volatility, that means illiquidity is no longer a bug. It is now a feature and very simple model for how expective returns are set. You get paid a higher expective return in something if you have to bear a bug nobody wants and you pay through a lower expector return. If you have a feature everyone wants, then you have
to pay up for it. So the chance that that is going on going forward, I think is quite high. Whether it means there's no edge to private equity or a negative edge or a smaller positive edge can tell you that. But I do think if you think of risk ajusy return as numerator of return denominator of risk, I think my statements are mostly about the denominator, but they're ten percent now about the numerator.
Going forward. You're in my concernami private equity, private markets by which is that it seems to me that like there is a ton of fee pressure in public markets and everyone has kind of like learned the gospel of like Bilow cost index funds and even charging for farma
French factors is not a two and twenty business. And private markets because they're not indexible because it's harder to like extract factors because they're not liquid, don't have those problems, and you can charge two and twenty for a lot
of private stuff. And so like it seems to me that there is a move to you put a lot of stuff that would have previously been public into private markets, and to say we can put privates into four oh one ks and there's a good economic grastionals we're putting private assets into four one case because you don't need liquidity. But there's also like this like really overwhelming if.
There's a positive illiquidity premium. Yeah too right, sorry, go no. I just like you know, you've written for years ago like criticizing people for charging alpha fees for beta, and it seems to me that like the reprivatization on the market is a way to sneak some alpha fies onto beta.
I think a tremendous amount of the private world is charging massive alpha fees for beta.
I won't mince words about that.
If they outperform or underperform on net after all these massive fees, and if performance going forward, it is tougher. And by the way, your point about the fee compression in the public world only makes my hypothesis that they won't beat the public world by the same amount going forward stronger. I think privates have a big function in the world. I don't think they're going away what you started out with me, what do you guys do for
the world. There are things that are in between what should be public and what's mom and pop. But I think where we are now, I think a lot of institutions are giving up some amount of expected return for the ease of limit, of reducing their agency problem of sticking with something. Now, if they're going to be terrible and not stick with things, it might be rational to
give up some return. But you can't double count and say we're making ourselves better investors giving up some expected return and oh yeah, our expected returns are going.
To be higher.
If that's the rationale, then you've accepted my argument, and I think you have to say, this is what we get paid for by making your life easier.
I am curious what you make of the push to put privates into more retail accessible wrappers. I'm talking about et avs, but I guess I'm also talking about interval funds a little bit.
It just seems like that's where the world is headed.
I'm going to hedge this and say it very carefully. I think it's a terrible idea.
Okay, go on.
There are things that end up in retail in a very good way eventually, but we've done some of this when we introduce mutual funds. I can't say always going to retail is a bad thing. You can price it reasonably, you can say these are strategies you've never had before. This feels a little bit more like we've exhausted the institutions. I think I saw a number saying endown. It's like forty three percent for a number I can't verify. That's
wildly specific, but that's the number I remember. So it has a feel of who else we're going to get to own this stuff.
It seems so explicitly, and it's really wild.
I think it's explicitly that it's one of these things that for the cynics, I don't think they'll ever be a satisfying moment where we get to say we were right. It'll just be somewhat worse over the next decade. It's not one of these things like a tech bubble in ninety nine two thousand that at least, I don't think there are scenarios where things get worse rapidly and secondary sales. We got close to some of that in the GFC.
I was on some investment committees where we were talking we didn't do it, but we were talking about whether we would have to do that. So I'm not saying it's a chance of ugliness, but I think the meat of the probability is is just somewhat worse. But it does cause me some worry sadness to say, yeah, what we really need is to stick a liquids in four.
To one case.
Yeah.
So yeah, bluntly, I think it's a bad idea.
Well, I just wanted to talk about and I don't know if this goes too far, but it feels like you had a change of heart when it comes to machine learning and AI in general.
This is something we've spoken about before.
I did well, was that like a light bulb moment or was that just you know, maybe people on your team wearing you down over time?
It was more the ladder.
Yeah, the ladder is the second one, right, I gotta think that through every time I tell that people this. I've said in a lot of public arenas I sell it to clients. I think I probably slowed us down by a couple of years in machine learning. I think it probably costs us some money because the stuff has worked pretty well. We've always described ourselves and we were
getting into this a little bit earlier. As a blend of data, back tests are nice out of sample long periods are even nicer, but also theory.
Theory can be a.
Formal economic theory, but it can also just mean a common sense story where you think you understand why you're making money. And there's no way to say exactly what percentage of both. But I've often described it as an attempt to be fifty to fifty. We want something to make sense to us as economists and have strong data
when you move into the machine learning world. I don't think you have to abandon theory, and this is something I think we do a little different than most I think there are some in the machine learning world to kind of throw theory out the window. We're still using common sense and theory to kind of limit the scope, but you are leaning more on the data. And again
I'm making up these numbers. But if regular stuff is fifty to fifty, machine learning seventy five twenty five data even for us, that was uncomfortable for me.
When you've been telling a story.
For twenty five years and it's worked for you and your clients, it's not easy to move. I also think it's not improper for the role for the old man of the firm to go, let's.
Just slow down.
You guys come in here doing this with a Southern droll and your new fangled machine learning. No, that's the villainous rule.
Oh no, I think it's kind of cool.
Yeah, okay, so I actually can defend it as entirely appropriate. But yeah, I had to be convinced. It wasn't a light bulb moment. It was people like Brian Kelly, Andrea Ferzini, Laura Serb and all partners of mine presenting great results that made increase it and I did a lot more reading.
I was probably I.
Programmed in a programming language called LISP in the nineteen eighties. That was an early machine learning or AI language, not even machine learning, and then I didn't do anything about that for the next thirty years. So I think part of it was just me getting up to speed.
Frankly, the thing I find compelling in the Kelly paper is like you seed like a sort of toy set of factors into like a ten thousand neuron model, And what he argues is basically you might get a better view of the actual like function that generates the results than if you just try to like use your economic intuition in a lineary aggression.
Right.
There's like theory behind it. In the theory is like things are not as linear as you know traditional methods, and.
It's basically saying it's still a sin to only look for patterns. You still need some economics, but machine learning is better at balancing those trade offs. So the idea of throwing more at it when you have a better technique for that, you lean in that direction. I did have a better title, I think than him. I wanted him that's not better. His titles great pretty well, no, but I wanted to call it simply. Ackham was wrong.
Okay, all right, and maybe not bad, but I still want him to use that for maybe a follow up paper.
All right, Cliff, thanks for coming.
Oh, this was fun.
Thanks for video with us.
And that was the Money Stuff Podcast.
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