Cliff Asness on How Markets Got Dumber in the Last 10 Years

26:13I use it for blowing through. So five years ago, I was saying it's a bubble. Now I'm just saying this is a little bit of an odd market. So I want to ask you more about the bubble, but we keep touting that we're going to ask you the why question. So let's ask the why question. OK, why are markets becoming less efficient? OK, well, first of all, and I say this in the piece, a lot of conjecture going on. This is an op ed as statisticians. We like a 50 page, a 50 page academic op ed. Look, this is our first time doing this. You will be convinced I could do a 50 page single spaced op ed. I believe you.

26:50I know you can. It's just as a quant, as a statistician, you'd like to see 100 bubbles, have stats on each one. This way, they're all, they'd rhyme, but they wouldn't be exactly the same. You tease out what's going on. If you see two in a 35-year career, you're not going to be able to prove this statistically. But I believe in my conjectures. I'm not soft selling them. I just want it clear that nobody is going to walk away saying he proved it. I list a few reasons in the piece why markets might be prone to bouts of bigger disconnects from reality. My second favorite is one I'm sure you've talked about.

27:25I know I've listened to you guys talk about it. The rise of passive investing. I am not a passive hater. There are really smart people. Mike Green's out there. The amount that guy hates passive. I don't know. The Middle East has never seen hate like the amount Mike Green hates passive. But again, he's a smart guy. He makes interesting arguments. I'm not that guy. I think passive has been a huge positive for an investor welfare. I actually was lucky enough to be fairly good friends with Jack Bogle and he was a hero of mine. We had a podcast briefly and he came on. In fact, I'll tell you part of that story in a second.

28:00So I'm not a passive hater, but here's what we know. We know the whole world cannot be passive. And when I say passive, I mean in a Jack Bogle market cap weighted sense. Sometimes people use passive for people like us, and they really mean rules-based. And that's not how I use the word passive. You mean someone who owns the entire market? Yeah, we're long, short, and levered. How you get to passive on that, I don't know. But some people do. I own the entire market. We had Jack on the podcast, and he absolutely agreed everyone can't be passive. Now, of course, being Jack Bogle, he thinks at that point the marginal investor should still move to passive.

28:34but he recognizes the obvious fact that if 100 % of the people are not looking at prices, nobody's looking at prices. Who's figuring out if Nvidia is worth more or less than the corner drugstore, right? So the market gets very weird there. We don't even understand what happens. It's a singularity. I use a physics analogy. We don't know what happens there. PhD students in finance, and I used to be one of these, will stay up late at night in their cups talking about But what happens if everyone was passive? What would it even look like? We know it's very weird. And I doubt all the weirdness happens between 99.999 % passive and 100.

29:12So we're on a curve. We're a lot more passive than we used to be. Even that, you're probably aware it's hard to measure exactly how much is passive. Direct passive, true market cap weight you can measure. But what about people who take, you know, 80 basis points of tracking error? They're kind of mostly passive. People peg to like custom indices now. It's kind of funny. You guys remember the Princess Bride? Yeah. Remember mostly dead? That's right. Not fully dead. You're mostly passive. So I think fewer people thinking about prices, fewer people willing to take the other side when things get a little crazy.

29:47If one side really starts to get crazy, there are fewer people out there. That has to exacerbate these swings. things my actual number one reason though you talked about the gamification for me it's the overall i'm going to sound like a very old man yelling at the sky on my lawn right now you know get off my lawn or yelling at the sky some simpsons thing yeah i'm abe in in this case uh but old man yells at cloud yeah exactly thank you social media and the broader environment that you guys were talking about i don't want to do politics except to say i don't think you find many people, there'll be some, but I don't think you find many people who don't agree with the idea that this environment has made our politics worse and more dangerous.

30:32Confirmation bias. We live in our own bubbles. We have algorithms that push us further and further towards you start out as a moderate belief, but it keeps pushing you towards extremes. And pretty soon you're saying stupid things like, hey, that Tucker Carlson, he's a good guy. All right. I might have revealed a little Yeah, you did a bit of politics there. So all of that adds up to making our politics worse, more prone in particular to swings and extremes. Markets are not arbitrage mechanisms. That's sometimes misunderstood. They are voting mechanisms. The price is a weighted average vote where the weight is by dollars.

31:13I'm lucky enough to get more vote than the average person. And Warren Buffett gets a lot more votes than I get if we all disagree on opinions. The reason it's not an arbitrage mechanism, and here I'll get a little geeky. Imagine you're reasonably sure this thing is mispriced in that Graham and Dodd sense. And you think it's massively mispriced. Trading enough to make it a third less mispriced is not very risky to you because it's not that big a trade. And it's very high expected return because it's that mispriced. Now you've moved it back to a third or maybe half. The next part of the trade is much riskier to you because you already have the trade on.

31:52So you're just adding more. Oh, I see. And it has half the gain because you've already closed it by half. So arbitrage will not take things. If on net more people believe something stupid, stupid is going to win. And we're going to be at least somewhat off of real prices. And I find it remarkably easy to believe that this same environment that makes our politics go a little crazy for markets to be efficient in any degree, not even perfectly efficient, this famous idea of the wisdom of crowds has to be helping us a lot. The hypothesis that we're all geniuses is never going to fly, right? So the wisdom of crowds, and you know it well, says even if on average, most people don't know the answer, the stupid answers cancel and the right answers don't because they're the same.

32:38My favorite example of that, and this might be dating myself, is Regis Philbin and Who Wants to be a millionaire right remember the show multiple choice show it's frightening that you're describing that as old but i guess it is yeah it's been off the air sadly regis has passed away it's old sorry sorry but you had to answer multiple choice questions and if you miss one you're out they start off ridiculously easy and they get harder and harder you had multiple cheats like three cheats one was phone your phone a friend was almost useless um your a your friend usually wasn't much smarter than you.

33:11And B, people, at least to my eye, I didn't watch every episode, but seemed to choose friends who knew the same stuff they knew. Right. You really want to choose a friend who is in like a totally different field. I think in some countries, the friends also had a tendency to deliberately give the wrong answer because they just didn't want to see their friend actually win money. The most cynical phrase ever is nothing succeeds like a friend's failure. There we go. I don't believe I'm not condoning that, but it is out there. The other one was eliminate two of the wrong answers. That's great. Obviously, even if you have no idea, you go from one out of four to one out of two.

33:45The other one was poll the audience. And at least to my non-exhaustive examination, it seemed to work pretty much every time. Even if the question was hard. Because imagine you have 100 people in a room. 10 of them know the answer. The other ones are guessing. The 90 distribute evenly over the four. Maybe not perfectly evenly, but roughly evenly. The 10 all land on B. So you pick B because it's bigger. Work pretty much every time. There's a crucial assumption in that. The audience has to be relatively independent of each other. And they did that. They weren't talking. It was silent voting. If the audience all gets to talk, maybe the 10 convinced the 90.

34:29But maybe they don't. Maybe a demagogue with a better Twitter feed convinces everyone. And if you ruin the independence, and I think, have we ever come up with a better vehicle for turning a wisdom of crowds into a craziness of mobs than social media? I'd be hard pressed to describe it. I find this to be very compelling. James Sirwicki at The New York Times, he came out with that book, Wisdom of Crowds, in 2005. But that was right before social media blew up. And then, you know, there's that famous book in 1841, Extraordinary Popular Delusion and the Madness of Crowds. So we've always sort of understood that crowds can be both mad and wise.

35:10And I find this very interesting, the idea that perhaps the linkedness of the crowd is what sort of flips it from wisdom to madness. I think that's exactly it. You maybe can come up with counterexamples. But I think most of the time, if the crowd is making independent decisions, and this can go for political voting and go for markets, you're going to get some degree of wisdom. When the crowd is all making a unified decision, it could still work out. But you are much more susceptible to what the quant's technical term is cray cray.

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36:45Say more this holiday season with Pandora. I always look forward to the holidays because I live to give all the women in my life jewelry with a little something special engraved on it, just to show them I care with something personalized. You know, I love to get some gifts myself and a man wearing jewelry is quite cool. If you ask me, shop now at Pandora.net or visit your closest Pandora store. Hi, I'm Cindy Crawford and I'm the founder of Meaningful Beauty. When Dr. Sabah and I decided to do a skincare line together, he said to me, we are going to give women meaningful beauty. And I said, that's exactly right.

37:24We want to give women meaningful beauty, which means each and every product is meaningful. It has a reason to exist. It's efficacious. You're going to get results and then you just go out and live your life. Meaningful beauty. Confidence is beautiful. Learn more at meaningfulbeauty.com. I want to pivot a little bit and talk about AI. You've written or you've talked recently, I forget exactly the word that was used in some of the headlines, succumbing to the machine. Surrendering ourselves. Surrendering to the machines and so forth. I regret saying that. And so forth. We tried to talk a lot about AI.

38:00I still don't know exactly what it means in any context. What does it mean to surrender to the machines in the AQR context? Well, first, not every journalist has Bloomberg's high standards. That's right. I am reasonably certain I said partially in that. And the word partially got dropped. Even skipping all the details, if you're going to use AI in your process at all, almost by definition, you are going to lose a little intuition. And it bothered me for a couple of years. I think I slowed us down on AI by a year or two just by saying, you know, we've always prided ourselves on the balance of we intuitively understand why we think this makes money and the evidence that it makes money.

38:43And when you go to AI, you're normally giving up some. Not all. We actually do try very hard to figure out why we think this works or doesn't work. But if you weren't giving up some intuition, what the heck is the AI doing? If it's simple and you could have just seen it with the naked eye, it's hard to imagine it's helping. But let me give you a concrete example. We like good momentum. We like it in price. We like it in fundamentals. One way people on the quant side have tried to measure this for years is something like earnings calls. trying to decide if earnings calls are good news or bad news.

39:20And if people underreact to good news, you want to buy when it's good news. Is this just like how many times people say great quarter guys or are you looking at something else? It's going to sound about as silly as that. Okay. You build up tables of words and phrases with numerical values and then you say, what's the numerical score of this? And they can be much more subtle than this. I'm going to use a real simple example. the word increasing plus one. Right. And I'm sure you see the flaw. If the actual sentence was massive embezzlement is increasing, you know, are bad on that one. The amount of fraud we're seeing in our private credit deals is increasing.

39:58Quant can survive looking stupid a lot if that's 47 percent of the time. If 53 percent of the time it's getting it right. Fine. And those things had some efficacy, but they weren't great. What we do today is we train ML. It's called natural language processing. It's a subfield of ML to analyze corporate statements. But what it does, and this is going to be the geekiest thing I'll say, it represents every corporate statement. It looks across them and represents them as a set of numbers, what the geeks would call a vector of numbers. then what we do is empirics to say all right we have 50 years of this across many firms we have different vectors or numbers for every earnings call what combination go long when the first number's good short when the second number is high blah blah what best combination forecasts that seems to be correlated to what we were doing before these word count things just considerably better.

41:00It does a better job than word counts. Language is very nonlinear. Whether something is good, whether that word increasing is good. AI is not perfect, but its chance of figuring out if increasing was good or bad, especially when it's trained on tons of these, is better than us. Here's where you lose the intuition though. I skipped a step. I like to do that. It's sneaky. If you ask myself or even some of the younger people who are much more tooled up on machine learning than I am these days. What does that vector of numbers actually mean? You often get a, we really can't tell you that. We can say it's summing up in a mathematical sense, the information content of that.

41:41We still get intuition because this indicator acts like a short-term momentum indicator. So it's picking up what we want it to pick up. It's also done fabulously well for us for multiple years in real life. but we are giving up intuition at one stage that we used to not do. So my answer was meant to be much more subtle that there are give ups in intuition. When you move to something like machine learning, they almost have to be, or else again, what are you doing? I was uncomfortable for that for a while. So I was starting to do me a culpa saying that, that I slowed us down and it came out as well.

42:16I used to hate this, but now I have no job. The machine runs it, which is probably going to be true in eight years, but not yet. This reminds me actually of something I wanted to ask because another big multi-year decade trend is the rise of the multistrats. And at AQR, as I understand it, you have a multistrat model in there, but it's more centralized than some other places. Can you go into a little bit more detail? Sure. They get used interchangeably, but I think there's the difference between multistrat and multimanager. Okay. Multistrat That just means I wrote a dissertation on choosing U.S.

42:51stocks. We have applied similar things to stocks around the world, to currencies, to commodities, to directional bets through trend following. They are correlated, but low. So we think of these as different strategies. And we think a set of our strategies is better than a single one or, you know, it's just the power of diversification. So we're big believers in particularly if you have a common philosophy. so it's not just fitting the data, it's fitting into an overall theme of what you believe in. We're big believers in multistrats. What we share with multi-manager is that belief in diversification.

43:30Multi-manager is what it sounds like. We are one team building these. We might, of course, have little separate teams at AQR, but we're one firm building these. They are farming it out to different people. To be frank, if you had told me their business model, 10, 20 years ago, I would have been very cynical that it worked. If you told me, A, what the total fees are going to be when you add up everything that's passed through, and a fair amount of them, and they vary in how quick they do this, if something's not working for what I would consider a very short while, they stop doing it. And I know there are a lot of low to medium sharp ratio, risk-adjusted return strategies that are really good long-term, but have bad periods.

44:12So if someone told me that model, I would go, you're going to charge a ton and you're going to throw out people who have a bad two quarters? No. And there've been people who've obviously proven me wrong. And I'm humble about this. I don't fully understand why. They must be very, very good at actual selecting the alpha. Right. And this is something that we don't do. We're internal quants who build our own models. We've never, maybe it'd be interesting one day. We've never Many people, by the way, have tried to start multi-manager and failed. So it's not like you just apply this, charge a ton, hire a bunch of active managers and fire them if they have a bad two hours.

44:54Just automatically works. It does seem, though, that talent is the thing that's capping multi-strat expansion, right? That's the limiting factor. They vary, but some of the major ones are giving back money. Even if you believe in this model, and even from afar, I have to be a believer. I've seen the results are too good for too long, in my view, to have a decent chance of randomness. I don't exactly know what they're doing. I'm still waiting for Ken and Stevie and Izzy to send me their exact process. That would be wonderful. Izzy doesn't share it with you? No, even better if Medallion would send me their exact process.

45:33But I respect it. But the amount of individual alpha from teams that can be out there has to all alphas finite, but has to have a decently tight cap. And the ones I've seen are fairly disciplined about this. And again, it varies. I can't speak for everyone. I know we compete for talent with them much more than we used to. They have non-quant parts of what they do, but they have quant parts of what they do. and for young quants, they're often considering an offer from AQR and Citadel to pick just one example. We win our fair share. We lose our fair share. I think we probably pay a little less in the short term, but we don't fire you if you have a bad week.

46:15So some people are - That doesn't seem like a stressful environment. And I'm not picking on Ken. He's not doing that. I'm just saying - No, but we know - It's a more cutthroat environment. We've done a lot of episodes on that environment. We know they cut pretty quickly if you lose money. I want to go back a little bit to the connection between sort of AI machine learning and interpretability of the factor. You know, the quintessential, you know, the risk is, of course, that you find something that works strictly from data mining, right? Tickers that start with B tend to rise on Tuesdays. I usually use the CEO's middle initial.

46:48Yeah, stuff like that. We know, like, but, you know, even when you were talking about momentum and you said, well, there's two reasons, theories for why momentum can work. Let's just go back to the canonical like quant factors. Is there complete consensus about why these factors work? Not at all. Okay. You start out with - Because intuitively like cheap stocks go, but my impression is that there's even still disagreement about why. Yeah. You start out with the great divide. And when they split the Nobel Prize between Gene Fama and Robert Schiller, my co-founder and I wrote a piece on the cover of institutional investor with that title, The Great Divide.

47:24Lars Hansen also won a share of it. I shouldn't leave him out. But Schiller and Fama were juxtaposed as the efficient market guy and the inefficient market guy, which is fairly close to, not only either of them are zealots, but it's fairly close to true. So you start out, if something has worked historically and made a lot of money over a long period, you start out with what you led with. Is it data mining. Let's say you convince yourself it's not. Let's just put that away. And that's really important that I'm not, you know, poo-pooing that step. You got to do that. Then you got to ask yourself why.

47:58The two main contenders are a rational gene-fama kind of market where some stocks are riskier than others. And whatever you're using to say, go long these and short these is loading on that risk. And if something is risky, you should make more for investing in it. One of the problems is identifying, A, there are sub-fights within these fights. What do we mean by risk? Is risk beta like the capital asset pricing model? This is where finance academics are like every other academic. It's sub-fights within the fight. Define your terms. It's Talmudic at this point. But is risk beta like the capital asset pricing model?

48:37Well, the capital asset pricing model is a beautiful, elegant model that has failed everywhere it's ever been attempted. Is risk more multidimensional? Is risk something like what happens in a Great Depression, which is very hard to measure? The other argument is markets are not perfect. People make errors. And it's behavioral finance. So if a cheap stock beats an expensive stock because it's inherently adding some risk that you can't diversify away, that's a Gene Fama explanation. if it beats inexpensive stock because people went too far they went past the graham and dodd point yeah and if you can hold it you make money when reality sets in that's more the bob schiller point i love gene he's my hero i have probably drifted from 75 25 gene to 75 25 bob over my career world's complicated one of the hard parts is everyone wants to win but both explanations can be true and they can be true at different times.

49:30Life isn't so simple. But those are the two biggies. But once you get into behavioral finance, now you can fight about why. What behavioral bias? Notice you could sum up the two reasons I gave you for momentum as underreaction and overreaction. Overreaction is chasing, right? Underreaction is the information came out, didn't move far enough, and I hopped on that bandwagon. You know you're in a little bit of dodgy area when your two best explanations sound a little like antonyms. Now, I'm being intentionally - It's so funny. It works. We're just not sure whether it's literally opposite things or intuitively opposite things.

50:10We know it's one of them and there's some debate. I'm being a little too negative. You can actually, they're good papers teasing out. The underreaction is easier to show. You can actually show the fundamentals do catch up. I think the overreaction probably kicks in more in bubbles where there is just more feedback trading. Again, both explanations can be true and they can vary in their intensity over time. The overreaction might have a very small part of it, except plus or minus two years around a major bubble when it may be the driving force. So we have to get really comfortable. We don't have to have the be all end all single explanation.

50:44But if there are a few good explanations and no real counter ones and we have really strong 50 year empirical results. Yeah, we're OK with taking some bet on this. You never want to put all your money on one thing. That's not a quant thing. I'm going to try to connect a bunch of the sort of decade long mega trends that we've been discussing. But I'm thinking behavioral finance, gamification of markets, big data, AI, all those fun things combining into sports betting, which seems to be getting bigger and bigger than ever. And the reason I ask is because I was talking to someone in a bar the other day and they said that AQR was doing more sports betting stuff.

51:24Someone in a bar was talking about AQR doing sports. Yeah, I know. Well, it probably says more about the bars that I'm in and the people I'm talking to than anything else. But yeah, they mentioned that. I'm picturing the Star Wars cantina right now. I got to tell you. So I'm just curious, is that a thing or are you maybe interested in the sort of prediction market aspect of things nowadays? Susquehanna is getting into it. I think no one, again, tells you exactly what they're they're doing. My sense is they are into it and are good at it. This is incipient for us. We are considering and looking at it.

52:00We have a long history. Toby Moskowitz, who's a Yale professor and an AQR partner. Great deal, by the way. You get paid for two full time jobs that are 80 percent overlap. I'll keep that in mind for the if Toby's listening. Just, you know, you're a lucky man. He wrote a book called Scorecasting that was all about sports. But the sports analytics, the money ball type stuff looks a lot like what we do. It looks a lot like people are not pricing this right. People. I wrote my most downloaded paper ever, which is really a little annoying because it's like the only one I've written outside of my field was on when to pull the goaltender in a hockey game.

52:40Oh, yeah. And I wrote it with a colleague and friend, Aaron Brown. We built a model and we came up with, you should be pulling the goalie if you're losing by one with five or six minutes left, not with two minutes left. And I'm pretty sure we're right. We spent a lot of time in that paper saying, why aren't they doing it and making analogies to investing? You know, when people know the right thing to do, but can't do it because the public opprobrium, if they get it wrong, will be much worse. Like, aren't they saying like football teams should go for it on fourth down a lot more than they do? That's like one of these things that have.

53:10And they have started to. There is a feedback where some of these things are slow. Some of them are fast. Baseball has largely absorbed a lot of these things. You know, on base percentage was one of the major insights of Moneyball. And nobody nobody's missing that one anymore. But we still think particularly in the betting markets are not probably not as rational as Toby's scorecasting book. So we do think there might be opportunities there, but I don't want to overstate it. just because I am cynical about online sports betting. I got to tell you two things. I was always a very libertarian guy.

53:43I still think I am. But a couple of things have made me less libertarian. Children, the existence of my children will make you go, yeah, maybe people shouldn't be able to do anything they want when they turn 21. There should be some rules. And sports betting and maybe walking down the New York City streets and getting a contact high. Sports betting, we're already, you know, some of these scandals we're starting to see. Yeah. How do you not have them when, you know, some of these people make a ton of money, but they don't all make a ton of money. And there's a lot of money in sports betting. Anything you do for entertainment is fine if you do it at entertainment size.

54:17If you go to Las Vegas and you go, the odds are on the house's side. I'm going to lose$500 over two days. Probably if I win, great. But it's going to be fun. It's factored into the cost of a Vegas vacation. But like I have a whole bunch of 20 something year old, mostly guys in my extended family. A lot of them are sports betters. And they're not even it even pisses me off that they're not even rooting for their teams anymore. They're kind of rooting for this player to score on their prop. It is a strange dynamic. So do I think that gamification is highly related? I think if you go look at the Robinhood app and FanDuel, I think you will find they are far more similar on their feedback and how they treat things and in how their investors do on average.

55:05Particularly sports betting, you know investors lose on average because the sports betting companies make money. It's like saying on average insurance is a bad deal. You know how I know? Because insurance companies are profitable. Doesn't mean it's stupid to do because maybe if it's in a risk you can't tolerate, that could be a fair trade. But there's a price you pay for peace of mind, which is something I've come to appreciate over the course of 10 years. There is zero chance that the average online sports better is making money. I just have one last question. You know, I think if you looked at like some particularly crazy times in markets, here's something that's changed very much since we started the podcast first 10 years ago.

55:43I think if you look at some crazy times in markets, whether it's, you know, 2019 when some of these measures were getting extreme or just, you know, the SPAC mania of 2021, one theory that one might have offered is ZERP. And he's like, oh, this is what now we have. You know, we haven't been at ZERP for a long time. And yet some of this sort of speculative mania crazes has not gone away. How surprised are you that the move from 0 % to, say, 5 % or whatever didn't have more of a sapping effect on some of the behavior and speculative froth or just sort of animal spirits in these markets? I am mildly surprised.

56:21OK. I left this out, but I actually had three possible reasons in my paper. And the third one was super low interest rates for a long time for why things can get crazy. Now, the counter argument is once you break people's brains, they don't necessarily repair themselves instantly. So I think it was probably a contributory factor. Again, very hard to prove. A lot of people in 19 and 20, when the spreads being cheap and expensive were here, were saying it was a super low interest rate environment and gross stocks have more cash flows in the future. Low interest rates means they're worth more. We did the math on that.

56:56It explained like 2 % of the extra value spread. And in 99, 2000, interest rates were quite high. That's right. There was no zero boom. So 99, yeah. So it's not a unified field theory explanation. Yeah. Do I think it helped kickstart some? And again, we're in the soft guesswork, but I think these are educated guesses. And I listed it as one of my three. I think it's certainly kicked us off on some of these things, certainly loosened the bounds of rationality, absolutely free money. We'll do that. I don't think it's not human nature that they take away ZERP and everything comes back. would I have thought it was a bigger effect in going back to you know at one point we hit about 5 % on the 10 year almost 5 % would I have thought that would have mattered more yeah only in 2022 did we see one ugly year over that but it has mattered less than I thought it doesn't mean it will never matter all right Cliff Asness thank you so much for coming on and kicking off our 10 year anniversary celebration thank you so much Cliff that was really a pleasure I adore you.

57:58Thank you.

58:11Joe, that was so much fun. That was great. Literally the perfect guest. Literally the perfect guest. One, well, there's so many things that stuck out from that conversation. But one of the things that stuck out from the conversation, it's this idea about the thing that flips the wisdom of crowds into the madness of crowds. Right. And the idea that maybe the wisdom of crowds theory works as long as everyone is sort of isolated and independent and making their own choice off of the information available to them. But it starts to fall apart when everyone is tied to everyone else and sort of in the same social network.

58:44And, you know, if you think about one of the dominant themes in markets in recent years, it has been people herding into the same positions. Right. I found that to be really fascinating. I think that makes it a lot of intuitive sense. It probably can explain a lot of things about the world of politics, about the world of markets, etc. This idea that we're all just sort of one connected global village, as Marshall McLuhan put it. We're all just gossiping with each other. Yes, all the time. We're just constant talk, talk, talk. No, that's a very interesting idea. I also thought it was interesting the idea of length of drawdown versus depth of drawdown and the former being more painful, which strikes me as something I hadn't really heard anyone talk about that before, but especially from the perspective of a manager of other people's money, it's a very highly intuitive, that makes a lot of sense to me that, okay, like, yeah, you had a bad quarter, whatever.

59:37Eventually you're like, oh, your ideas are just out of date. It's been three years since you made money. Maybe time to rethink some of your fundamental assumptions and how powerful that must be. That's one thing I've learned over the course of 10 years. The other thing was the idea of markets not necessarily being an arbitrage mechanism, which I think is very counterintuitive to the way a lot of people will think about markets and this idea that like, well, sometimes you can't compress the price all the way to where it should be rationally or logically or according to EMH or whatever, because the reward just isn't necessarily there to get to that like final 10%.

1:00:12It's interesting to think about the sort of link between patterns and interpretability, why something works. And in our conversation a couple of weeks ago with Ian Dunning of Hudson River Trading, he's like, they do not put a lot of emphasis on interpretability. There's a pattern and they have some reason to establish that the pattern works, it makes money. The idea that they then have to also come up with an economic story about why it works is not so important to them. Maybe that's because it has to do with timeframes. Obviously, Cliff's trading timeframe is going to be very different than a high frequency trading firm like HRT.

1:00:48But it is interesting. And then it's interesting to think that even in the most established quant patterns, like why do cheap stocks outperform more expensive stocks over the long term, right? Even there, there's dispute about why this pattern holds, even though it feels a little bit more intuitive. So much interesting stuff here. It's also, I guess it sort of warms my old cynical heart that maybe the edge for humans will be spotting the regime change, right? Which, you know, at least there's something left for us to do if it's not just pure pattern recognition. There's that one very difficult thing.

1:01:23Good luck to us. Yeah. All right. Shall we leave it there? Let's leave it there. This has been another episode of the All Thoughts podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway. And I'm Jill Weisenthal. You can follow me at The Stalwart. Follow our guest, Cliff Asnes. He's at Clifford Asnes. Follow our producers, Carmen Rodriguez, at Carmen Armand, Dasho Bennett at Dashbot and Kale Brooks at Kale Brooks. For more OddLots content, go to Bloomberg.com slash OddLots with the daily newsletter and all of our episodes. And you can chat about all of these topics 24-7 in our Discord, discord.gg slash OddLots.

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