The Tim Ferriss Show - #659: Michael Mauboussin — How Great Investors Make Decisions, Harnessing The Wisdom (vs. Madness) of Crowds, Lessons from Race Horses, and More

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Starting point is 00:02:06 slash Tim to discover some of the most delicious and nutritious nuts on the planet. One more time, that's houseofmacadamias.com slash Tim. This episode is brought to you by Shopify. Shopify is one of my favorite companies out there, one of my favorite platforms ever. And let's get into it. Shopify is a platform, as I mentioned, designed for anyone to sell anything anywhere, giving entrepreneurs the resources once reserved for big business. So what does that mean? That means in no time flat, you can have a great looking online store that brings your ideas, products, and so on to life. And you can have the tools to manage your day-to-day business and drive sales. This is all possible without any coding

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Starting point is 00:04:16 more than a store Shopify grows with you. And they never stopped innovating, providing more and more tools to make your business better and your life easier. Go to shopify.com slash Tim to sign up for a $1 per month trial period. It is a great deal for a great service. So I encourage you to check it out. Take your business to the next level today and learn more by visiting shopify.com slash Tim. One more time, shopify.com slash Tim, all lowercase. Optimal minimum. One more time, shopify.com slash Tim, all lowercase. The Tim Ferriss Show. My guest today is Michael Mauboussin, spelled M-A-U-B-O-U-S-S-I-N. You can find him on Twitter, MJ Mauboussin. He is the head of consilient research on Counterpoint Global at Morgan

Starting point is 00:05:32 Stanley Investment Management. Prior to joining Counterpoint Global, Michael was director of research at Blue Mountain Capital, head of global financial strategies at Credit Suisse, and chief investment strategist at Legg Mason Capital Management. Michael originally joined Credit Suisse in 1992 as a packaged food industry analyst. Some of you long-term listeners will perhaps recognize some of that from my conversation with Bill Gurley and was named chief U.S. investment strategist in 1999. Michael is the author of many books, including The Success Equation, subtitled Untangling Skill and Luck in Business, Sports, and Investing, Think Twice, Harnessing the Power of Counterintuition, which I've mentioned several times on this podcast, and More Than You Know, Finding Financial Wisdom in Unconventional Places.

Starting point is 00:06:15 More Than You Know was named one of the 100 best business books of all time by 800 CEO Read, one of the best business books by Businessweek, and best economics book by Strategy and Business. That's in 2006. Michael is also co-author with Alfred Rappaport of Expectations Investing, Reading Stock Prices for Better Returns. Michael has been an adjunct professor of finance at Columbia Business School since 1993 and is on the faculty of the Heilbrunn Center for Graham and Dodd Investing. He received the Dean's Award for Teaching Excellence in 2009 and 2016 and the Graham and Dodd-Murray Greenwald Prize for Value Investing in 2021. He earned an AB from Georgetown University and is Chairman Emeritus of the Board of Trustees of the Santa Fe Institute, a leading center for multidisciplinary research in complex systems theory. You can find

Starting point is 00:07:02 all things Michael at michaelmobison.com. Michael, thank you for making the time. It's nice to see you again. Tim, it's awesome to see you. I thought we would start with some Latin. That's my favorite place to start, especially as someone who knows very little about Latin. And I wanted to ask you about your course, and it's two unofficial mottos. So maybe you could just mention those mottos and explain why they are the unofficial mottos and what they mean. So first of all, there are no official mottos, so I made these up. But these are an

Starting point is 00:07:38 attempt to set a tone with the students, but it's not just the students in my course, but really broadly speaking in life. So the first one, I mean, the Latin is nullius in verba, which is the motto of the Royal Society. So the Royal Society is the oldest, I think, scientific society in the world, and it's been around for 350 years, more than 350 years. And basically translated, it means take nobody's word for it, kind of see for yourself. And I really like this idea that a lot of the information that people use or even things that they're taught are things they take from authority and they don't go figure them out for themselves. And so this idea of constantly having an open mind and seeing for yourself and not working just on authority and questioning

Starting point is 00:08:20 everything, that's the tone I want to set in the course. The second one is a quote from Carl Gauss, and I'm not going to even try the Latin, but basically the idea is notions, not notations. And the idea is don't focus on only equations. Computation is obviously super important, but really the key is to grasp the intuitions, the underlying ideas, and then allow the computation to serve that rather than the other way around. Now, sometimes you can solve a problem, you know, computationally, and then you have to go back and figure out what the intuition is to get you there. But that's the main thing. So I think that's, for example, for business school students,

Starting point is 00:08:57 it's a potential problem because from time to time, they'll run equations without thinking about what they're doing, and they'll forget about the concepts behind them. So, you know, Charlie Munger, the vice chairman of Berkshire Hathaway, has got this line where he says, people calculate too much and think too little. And I think that's what we're trying to fight against with that idea. So, Michael, this strikes me as the perfect segue to ask a question about some of your earlier chapters. And specifically, I would love to know how your lack of business education was an asset

Starting point is 00:09:26 on Wall Street when you first started out. By the way, I did take one business class. My father strongly encouraged me to take accounting for basically non-business majors when I was a senior. And out of the complete generosity of the professor's heart, I got a C plus, a gentleman C plus and knew nothing about what was going on at all. I will say that I was in a wonderful training program and there's a lot of remedial work so folks like me could learn, get up to speed on some of the basic issues. But Tim, I think the answer

Starting point is 00:09:57 is that I went in kind of wondering about and thinking about and being open to understanding things from first principles. And Wall Street, even to this day, is replete with lots of rules of thumb and sort of old wives' tales and, you know, shorthands for how to do things. And some of these things, when I would sit there and listen to them and try to cobble it all together, just didn't make sense. And so for me, it was this idea of sort of the beginner's mind and really saying like, how does this stuff really work? And I had, for me, a clear professional epiphany. It was a two by four across the forehead. Guy in my training program gave me a copy of Al Rappaport's book called Creating Shoulder Value, which was published in 1986. So this is probably a year and a half or two years after that book was out. And he gave it to me for a completely

Starting point is 00:10:43 different reason. It had nothing to do with the basic concept, but I read that book and the light bulbs all went off for me personally. And I very much connected with that whole way of thinking about things. And I guess I'll summarize. There were sort of three things that he talked about that have really remained the cornerstone of how I think about everything since. One is it's not about accounting numbers, but about cash. And I don't want to get too much down the financing road, but basically accounting doesn't always represent the underlying economics of businesses that effectively. And he was one of the people that really emphasized understanding value and how value is created. Second thing, which I think is really interesting is that valuation and strategy sort of go together. So when you're thinking about

Starting point is 00:11:24 as a business person trying to build a business, you have to make a bunch of strategic choices, but a good strategy is one that creates value. And to do a valuation of a business, you have to understand the competitive position of the company and the industry and so forth. So the idea that those are really joined at the hip and going back to even business schools, we tend to teach these things separately, but they really do go together. And then the third and final point, which ended up being the collaboration of the book we did together, is that stock prices reflect a set of expectations. And it's very obvious when you say that, any asset price, right? What has to happen in the world for that thing to make sense? His target audience was corporate executives, but clearly that was relevant for investors as well.

Starting point is 00:12:03 So from there, Tim, I would just say that I was sort of open to that. And I think that to me was a good set of ideas to work with. And yeah, that's why I think I was unencumbered with any knowledge to be open to thinking about the world that way. I came across something in doing research for this conversation. This was from Farnham Street. So fs.blog. This was a transcript of an interview that you did over yonder. And there was a line in passing that I wanted to revisit. And this is from your earlier chapters yet again. In the early to mid-1980s, Drexel, that's Drexel Burnham Lambert, if I'm pronouncing that correctly, Drexel had a great food industry analyst. To this day, I believe he's the best analyst I've ever

Starting point is 00:12:43 seen. So I naturally followed him closely, and then it goes on. Shortly after, I believe he's the best analyst I've ever seen. So I naturally followed him closely, and then it goes on. Shortly after, I left Drexel, et cetera, et cetera, et cetera. But I wanted to double-click on that comment. So if it's still true, or maybe even if it was just true then when you said it, I believe he's the best analyst I've ever seen. What made this person such a good analyst? Tim, that's a great question. And I'm going to tie a bunch of ideas here together. The first thing I'll say is my first job was with Drexel Burnham Lombard in 1980s. That's where that training program was. And I just think that there's a big professional imprint on the first job. And so Drexel at the time, this is when Michael Milken, high-yield bonds, the firm was really hot.

Starting point is 00:13:25 It ended up getting in trouble, and then there was a crash of 1987. So things unwound, and the firm ended up going bankrupt. But at the time, it was quite hot. And they had an equity research department. I should back up and say one thing. In our training program, we first did some classroom work, and then we rotated through different departments in the firm. So we really got exposed to all different aspects. And indeed, there was this one analyst that followed the Package Food Companies. His name was Alan Greter, who was extraordinary. And what made him great was he had a very different

Starting point is 00:13:56 view of things than traditional. So he was very focused on, for example, financial cash flows versus simple accounting numbers. Some of the things I was just talking about. He was very focused on things like share buybacks before those were a big deal, understanding asset values. And then he had the ear of many management teams. So he was able to talk to those management teams and understand how they were thinking about things. And so he was just the complete package. And interestingly, here's the connection to sort of my own career path. One is, I mentioned my training colleague gave me a copy of Creating Sure to Learn. The reason was there was a case study in the back of the book about Quaker Roads' acquisition of Stokely Van Camp. It seems completely remote. You've never heard of Stokely Van Camp, but you probably have

Starting point is 00:14:42 heard of their most famous product, which was Gatorade. Oh, yeah. And it turns out there's this little jewel, and it ended up being a really great acquisition, but in part because they found this little jewel and built it into this incredible brand. That's the reason he drew my attention to this book in the first place, actually, about this Quaker Roads Stokely Van Camp thing. So I ended up learning a lot about that industry, again, by following this particular individual. And then when it became time for me to become an analyst, one of the areas that I was drawn to, logically, was the food industry. So literally the reason I was a food analyst is because this guy was so good and because I learned. And by the way, I was a nobody or the little peon.

Starting point is 00:15:21 I had a training in a training program. So he had no idea who I was. But it just gives you a sense of like how these little things happen that almost like set the trajectory. So it was both his analytical prowess and it so happened to be applied in this particular industry, which is why I became an analyst in that particular industry.

Starting point is 00:15:37 Now, hearkening back to my conversation with Bill Gurley, not long ago, friend of yours, and he invoked your name as someone who is able to connect ideas, principles, best practices from disparate areas. And I thought this might be an appropriate time to grab a word from your bio. In fact, it's in the first line, head of consilient research, and maybe just define some terms. Consilience, what is consilience? It's probably not a good thing when your job title, you have to explain it to everybody, and that's really the case.

Starting point is 00:16:17 So I was very taken in the late 1990s by a book called Consilience by E.O. Wilson. You know, so we'll talk about that book in a moment, but Consilience itself is a fairly old, well, not that old, about 1850s probably is when that word was coined. And it's really about the unification of knowledge, right? This idea of bringing ideas together. So E.O. Wilson wrote this book. He was a Harvard biologist. He's most renowned for his work on ants. So he's sort of the ant guy. He's also famous for his early work on evolutionary biology. And there was some incidents, he wrote a book about sociobiology in the 1970s that was very controversial at the time, at least. But in this book, Consilience, Wilson argued, you know, hey, we've made enormous strides as a world in using

Starting point is 00:17:07 reductionism, scientific reductionism, right? So we're breaking things into their components. We're understanding how those components work. And if you look around you, many of the marvels you see are the result of that extraordinary capability. But he said, as we look forward, many of the most vexing and difficult challenges and problems in the world are actually at the intersections of disciplines. And we're going to need to bring these different ideas together from different disciplines to really tackle these big problems. And so, of course, that idea very much resonated with me. So I'll just mention, so consilience, that's where, so consilient would be the verb for that. And then this is probably about 2000 or something like that.

Starting point is 00:17:44 And I was just one of those guys who, I mean, I published from time to time, but I wasn't publishing on a sort of set schedule. And I'm one of those guys, I'm reading an article or watching a television show and I'm talking back to it like, oh, no, that guy should be doing it this way. Or here's an insight that they should be having. So I was like, you know what? Instead of me muttering to myself, maybe I should start to write about this stuff. And so I launched a newsletter called The Consilient Observer. And the idea was, let's look at different topics and see if we can shine a sort of shine a different light on it, look at it through a different type of a lens. And so that The Consilient Observer series ended up when you mentioned a moment ago, more

Starting point is 00:18:22 than you know the book, that was sort of the greatest hits of the Consilient Observer. And those were all sort of 1,500-word essays, so they were short, kind of pithy. It was hard to get really into ideas, but they were all over the place. As a consequence, I think they were somewhat fun for the audience to read. So that's where that word consilience comes from. And that's, you know, again, a big, as I think about the world, you know, this idea of being able to draw from various disciplines to thoughtfully address the problem or problems that you're thinking about. Wheels on luggage, bam, how'd it take so long for somebody to figure that out? I'm giving perhaps a silly example, although there's a lot of utility there. Question. Can I tell you, Tim, I said to my wife, I actually think that wheels on luggage is like the indication of the decline of Western civilization. Okay. And the reason is

Starting point is 00:19:10 because, because it used to be like, you'd have to lift your luggage, like carry it around, like a little bit of effort. And now it's like everybody's wheels, everything around. So anyway. Now we're, we're two steps away from Wally. If you remember the people with the super big gulps and the floating on the reclining chairs. And you get some of these things that are like tiny little bags with wheels on them. Like, all right, come on. You got to have that one. Anyway, sorry about that. No problem.

Starting point is 00:19:31 So E.O. Wilson, also for people who don't recognize the name, chances are you have latched on at some point to a quote from E.O. Wilson without even realizing perhaps the attribution and this person's background. He's one of the most quotable writers in my mind of the last hundred years. It's just remarkable how punchy and memorable so much of E.O. Wilson's writing is. Do you have any examples from natural systems or biology that you have translated to business or evaluating companies or understanding markets in some fashion? One is, and this is really, I think, probably one of the more common threads through the research that's being done at the Santa Fe Institute, is a study of complex adaptive systems. So complex means lots of agents. Those could be neurons in your brain,

Starting point is 00:20:26 ants in an ant colony, people in a city, whatever it is. Adaptive means that those agents operate with decision rules. They think about how the world works, and so they go out in there and try to do their thing. And as the environment changes, they change the decision rules. So that's the adaptive part. There are decision rules that are attempting to be appropriate for the environment. And then system is the whole is greater than the sum of the parts. It's very difficult to understand how a system works, an emergent system works,

Starting point is 00:20:53 by looking at the underlying components. Two or three obvious examples. One would be something like consciousness, right? So conscious is very likely an emergent phenomenon. We have these neurons, we have this physical genesis, but the system is more complex than the underlying neurons themselves or ants in an ant colony. If you study an ant colony, it's almost like an organism in and of itself. It has a life cycle. It's pretty smart about when it forages, they fight each other. Some of our more docile, I mean the whole thing. So understanding markets as complex adaptive systems, to me, has been an extraordinary insight. So the classic ways to get to kind of efficient markets is that people are really smart. They're rational.

Starting point is 00:21:33 So they understand all the information. They know what to do with it, and they reflect that in prices. Now, nobody really believes that, but that might be the starting point. And then the second way, you know, economists would talk about this is this idea of no arbitrage. So in other words, you don't need everybody to be super smart. You just need a subset of people to be super smart. And when there are gaps between price and value, these super smart people come in and they buy what's inexpensive and sell what's expensive and close the gaps. And so in their wake, the rest of us can benefit from these efficient prices.

Starting point is 00:22:01 Problem is, here again, they're just famous episodes where these arbitrage wars fail to do their jobs. The third way to think about things is complex adaptive systems. And, you know, I think that the way that's most easiest to understand this is using some of the language from Jim Cerwigge's great book,

Starting point is 00:22:16 The Wisdom of Crowds, which came out probably 2004, 2005. And, you know, The Wisdom of Crowds says, crowds are wise when three conditions are in place. A, we have diversity of the underlying agents or heterogeneity, right? So this is one of the reasons diversity is so important is because we need different points of view and different decision rules represented. Second is an appropriate aggregation mechanism.

Starting point is 00:22:37 You can have all the information in the world in the heads of people sitting around your boardroom, but if you're not extracting it and aggregating it, it's of no value, right? And then the third is incentives, which are rewards for being right and penalties for being wrong. In markets, that's money. But it doesn't have to be money. It can be reputation. It could be fitness for a species or other measures of incentives that allow you to propagate. So to me, thinking about markets as complex systems is very powerful. And in the wisdom of crowds, why are crowds smart? And the answer is when those conditions are in place. And then why do they go haywire periodically, which we know that they do? And the answer is that one or more of those conditions are violated. And by far, the most likely to be violated is diversity. So rather than you and I, Tim,

Starting point is 00:23:17 thinking independently, we sort of correlate our views and we become uniformly positive or uniformly negative. And as a consequence consequence that reflects in asset prices. So that would be one example. May I pause just for one second to say, I think the second comment after diversity that you made earlier is really important, which is representing different decision rules. Because you could have, for instance, people who are every possible gender, every possible color. But if they're all econ majors from Yale who took

Starting point is 00:23:45 exactly the same classes, they may actually represent the same decision rules or similar decision rules. Or how do you think about that? Maybe I'm misreading. You are absolutely right. And I think that the way I would think about that and the way I read that literature is there are really three types of diversity that we care about. The first is social category diversity, which is what you just sort of described, right? That people look different, but they have the same sort of way of thinking about the world. When most organizations talk about diversity, they're almost always talking about social category diversity. And one of the benefits of that is because we can count, right?

Starting point is 00:24:19 We can see how many women there are versus men and so forth. The second kind of diversity is cognitive diversity. That's what you just described. And that's really perspectives, points of views, mental models, training, versus men and so forth. The second kind of diversity is cognitive diversity. That's what you just described. And that's really perspectives, points of views, mental models, training, personalities, and so forth. Nearly all the literature I've seen suggests that it is cognitive diversity that is the key to solving problems.

Starting point is 00:24:37 To your point, it's possible to have people that look the same and think very differently or people that look very different but think the same. You know, that's not likely, right? So there's some correlation between social category diversity and cognitive diversity, but cognitive diversity is sort of what we're after. And then the third thing is values diversity. And, you know, you could rephrase this as almost a sense of purpose. And here we want to be uniform, right? We want that kind of diversity to be low. So we'd like

Starting point is 00:25:01 to really have people that have a common mission in any sort of organization that would be the case. And I'll just mention that my favorite researcher on this topic is Scott E. Page at University of Michigan. And Scott's written a number of great books. The Difference is his big book on this. And he wrote a smaller book called The Diversity Bonus, which is a shorter treatment of the same topic. But the reason I like Scott's work so much is that it's not about hand-waving or feeling good. It's actually mathematical, and he can demonstrate mathematically why precisely this idea of cognitive diversity adds value. And so it is the cognitive component that seems to be that diversity seems to be, you know, so you want smart people and you

Starting point is 00:25:40 want diverse people, and both of them are important contributors to solving problems for corporate success. I'm glad you picked up on that because that's actually a very interesting and important point. And I'll just mention back in, you know, this is probably now 20 years ago, but when I was at Credit Suisse, well, it was the time of CS First Boston, the guy that ran the business asked me to co-chair the diversity advisory board. So we were setting diversity policy for 20,000 employees. And you sort of say, why would you want a straight white guy to do that? And it was because that CEO thought that this cognitive diversity argument should be heard and should be part of every dialogue as we think about who we hire, who we promote, how we assess people,

Starting point is 00:26:22 and so forth. I want to double-click. For whatever reason, this double-clicking metaphor has been on my mind, so I apologize if I use it another 47 times. But I'd like to double-click on two components of what we've been discussing. So the first that I suppose we could touch on is the wisdom of crowds or the stupidity of crowds, depending on how many checkboxes are checked. And one example, real-world example, sort of a classroom demo, hopped out of me when I was watching your 20th year tribute video,

Starting point is 00:26:57 which included many of your students. And there was a jelly bean guessing exercise that you had them perform. I don't know if this is still the case, but could you just describe that? And then I have a follow-up question related to my own audience. I believe the Wismac Crowd's book

Starting point is 00:27:17 opens with a story of Francis Galton, who was a Victorian polymath, cousin of Charles Darwin, by the way, who invented a number of important concepts and statistics. But Galton, toward the end of his life, went to a fair. There was a contest to guess the weight of an ox. And you had to pay a little fee, and about 800 people participated. A few of them had illegible handwriting, so I think he had 787 contestants.

Starting point is 00:27:46 And Galton was fully expecting to show how foolish this crowd was. And by the way, he's got a really interesting, it's in Nature magazine. He sort of says, you know, some of these people are butchers or whatever, you know, so they would know, they have a sense of this. But he goes, some of these people were sort of operating on with their own fancies, you know, I'm in a good mood, here's what I'm thinking about. And when he tallied up the results, it came out to be very different than what he anticipated, essentially the collective. So the average or the median of all the guesses were within 1% of the actual weight of the ox. So this sort of extraordinary illustration of that point. And so that was picked up. There's a really interesting article by Jack Treanor, T-R-E-Y-N-O-R. And Jack was a very famous guy in the world of

Starting point is 00:28:26 finance. He died a few years ago. And the article was called this from the late 1980s, I think. It was called The Jelly Bean Jar and Market Efficiency. It's a short little article, but he described this experiment he did with jelly beans. I think they were actually not jelly beans. I think they were like actual beans. And he did that, and he came up with a very similar type of result. So he was trying to explain market efficiency through this wisdom of crowds that that name wasn't being used yet, but through this idea. By the way, as a funny side story, many years later, I was presenting at a conference and lo and behold, in the front row was Jack Traynor. So I'm like, you know, I had to give the nod to the man, right? The OG on this

Starting point is 00:29:05 thing. So he was totally quilled at it. So I had the slide. I actually had a copy of my own slides and I'm like, Mr. Traynor, would you sign this? I have an autographed copy of a picture of a jellybean jar autographed by Jack Traynor. By the way, one other weird thing is that I also talked about that day. There's a famous social psychology experiment by Solomon Asch. Do you know the Asch experiment with the three lines? Do you know this one? You know what?

Starting point is 00:29:29 You probably do. It's pretty famous, but very quickly, Solomon Asch was a psychologist and a social psychologist, and he wanted to understand the idea of conformity. So the setup is you have, and they did it in different ways, but let's say you have eight people around the table,

Starting point is 00:29:42 seven are in on the experiment with Asch, and the eighth person is the subject. And the task is very trivial. You have three lines, A, B, and C, and then you have X. And the question is, which lines, which of the A, B, and C lines are the same length as X?

Starting point is 00:29:55 It's actually a very easy visual task. And in controls, people get, you know, they start with controls. People get like 95% plus, right? So it's not a hard task. And then the experiment started for real which was ash signaled his confederates to give the wrong answer and now instead of it being c which is the correct answer everyone says aaa and they put the subject in seat the last seat

Starting point is 00:30:16 and so by the time it comes around to you the question is how do you answer because you're thinking like am i insane like i see this as being answer c and everyone's answering a and it turns out the reason we still talk about this today is about a third of the people actually, most of the people actually at some point go with a majority. And so they just basically override their own senses. And Ash talked about why this was the case, but this is this idea of social conformity and how important it is and going with the crowd and so forth. And this goes back to our stuff on diversity. So I'm describing this experiment, and Traynor raises his hand.

Starting point is 00:30:46 Again, like this is twofer, right? And he goes, I was at Swarthmore College in like whatever, it's the 1940s, and I was a subject in this thing. And he said, I just want to tell you that I remained independent. I didn't listen to anybody else. So I was like, oh, man, that's really cool. So Jack Traynor was like, obviously, he was a super important guy in the world of finance. But there are two little touch points that tie back to our two stories. One is sort of that he made that connection to the jelly bean jars in the world of finance

Starting point is 00:31:12 and why it was important to understand how markets work. I think Jim obviously came along. I mean, Jim Sirwicki, the idea of the wisdom of crowds had been around, obviously, to some degree, but Jim, I think, did an incredible job of putting a name to that and really being careful about saying, as you said, like, what conditions are the crowds wise and on what conditions do they go mad? And we know that both happen from time to time. My understanding, tell me if I'm flubbing on this, is that you replicated this experiment in class where there's a high degree of variance, but among your business school students, ultimately at the end, they were within say one to 2% of the actual count.

Starting point is 00:31:53 Am I getting that? Yeah, no, we do it every year and we do it every year. It's like my little parlor trick and you know, it vacillates. So in the last, I actually, cause I did it, you know, my course started in January and we just did it in January. It's usually somewhere between two and 10%. I've done times where it's been almost perfect, but it's usually two to 10%. And then the other thing is let's just pick 10% as sort of a non-uncommon number. What's interesting is if you pick any person within the group at random, right? So you just close your eyes and pulled out somebody's guess. They're usually off by about 50%, 5-0. Collectively, people are way better than they are individually, which is super interesting. And it's often the case, by the way, that the

Starting point is 00:32:33 collective guess is better than any individual within the collective. It's not mathematically necessary, but that's often the case as well. So the group is smarter than any person in the group. My follow-up to that is, what is the minimum effective dose of cognitive diversity? And if we fine slice it, are there particular types of cognitive diversity that are more valuable for this type of wisdom of crowds than others? Because in the state fair example, you have butchers, you probably have painters, you have a very broad swath of society with very, very obviously different people in different professions, perhaps different levels of education. In your business school class, I would think there is a higher degree of uniformity of thinking. Maybe that's very unfair, but similar age ranges, probably similar

Starting point is 00:33:28 priorities they've chosen to apply to your class or to join your class. So I'm wondering, I suppose, just to restate the question, how much cognitive diversity you need and are there different types of cognitive diversity that are more valuable than others for this type, harnessing this type of wisdom of crowds? I mentioned Scott Page a moment ago, and sort of one of the ideas he's promoted is an equation called the diversity prediction theorem. And I'm not going to go through the math, but basically it says collective error, so how smart the group is, is a function of the smarts of the group, so how accurate each individual is, minus cognitive diversity. So what you get is the collective accuracy is a function of both

Starting point is 00:34:11 smarts and diversity. So I just want to say one thing just to be super clear that there are many tasks where having a smart person is better than having a crowd, right? So in other words, if you have a leaky toilet or need a really hard math problem solved, you know, by all means, get a plumber or a mathematician. Don't bring in like an astrophysicist and a poet and whatever, right? So that's the first thing to say is that we want to think almost like a taxonomy of types of problems. And there are some problems where just the right person will answer it much more efficiently than any of these kinds of things. But I think, Tim, it turns out that, and this is why Scott's thing's interesting, is it just ends up being a mathematical problem that whatever models people are using,

Starting point is 00:34:50 and you might think about it this way, it's not exactly right, but you might want to think about this way. Let's say there is a truth. There is a number of beans in the jar, right? And I'm the god, G-O-D, I know that number. You might imagine what happens is people, and like you said, even the business school students, and I give them some tips, like, you know, here's some ways to think about this. You might think they're going to have almost some sort of sense of the answer, some sort of sense of the truth with an error term. And those errors might go too low or too high. And you can think about it almost like a normal or bell-shaped distribution,

Starting point is 00:35:19 where the mean is the actual answer. And that's what Jack Traynor was trying to, how he was explaining it, which is you have this distribution of outcomes. And by the way, the standard error goes down. I mean, I don't want to get too fancy, but the standard error goes down as a function of the square root of N of the number of people are guessing. So it's actually less about, again, if they're all skewed, that's going to be really bad and that's going to be the madness of the crowd. You want them to have different guesses, right, based on their models, their representations. But a bigger problem would be if there are too few people doing it, right? So it's a sample size growth. And so, you know, I have my classes probably, I don't know, 60 or 70 people

Starting point is 00:35:52 doing it. Golden had, you know, close to 800. So as you get that sample size larger, the number of people participating greater, it homes in on the answer more accurately, typically. So this is leading to a very self-interested question that I wonder a lot, which is what fun or useful things could I do with my audience? Because in this particular case, the N is quite large.

Starting point is 00:36:17 And depending on the means of accessing them, but if we're talking about social podcasts and newsletter, I mean, it's 10 to 20 million people a month. It's hard to de-dupe the people who are overlapping or appearing more than once in those categories, let's just say. But nonetheless, it's a large N for a lot of purposes. Do you have any thoughts? And I would also say that politically, geographically, from a gender perspective, quite a high level of what I would consider diversity. And I think psychographically, from an education perspective, probably a little less, perhaps, on the education side.

Starting point is 00:36:55 I'd say my listeners tend to be pretty well educated. But do you have any thoughts on how to perhaps design experiments for doing interesting, fun, or valuable things with my audience? I know that's a very broad question. These kinds of problems might be fun. It depends a little bit on what your goal is, right? If your goal is simply to demonstrate how some of these principles work and to use your audience as the way to show that, it would be super fun. And even something like a jelly bean jar thing would be cool. I'll mention, you know, we're going to do this in class. I think the

Starting point is 00:37:29 Academy Awards is mid-March, and we also do an experiment with Academy Awards. And I say to the student, I give them 12 categories. You know, the front page is the best actor, best actress, best film, things you might have a shot at getting. And then the back is, you know, best costume design or something like that. You know, things that are going to be much less front and center. And I just, I say to the students, don't tell me who you think should win. Tell me who you think will win by popular vote. Again, the winner in each category is the modal, so the most popular selection. And once again, the Academy Awards, the group does vastly better than any person in the group. So there's an

Starting point is 00:38:05 example that might be, that would be a fun one. There's another one I've always found interesting, and I think the Financial Times, the newspaper, did a version of this 15 or 20 years ago. Do you know about the two-thirds game? Have you heard of this before? No, I don't. So here's the setup. So one of the things that's interesting in markets, but it's interesting in a lot of games, generally speaking, is there are sort of orders of thinking, right? First order, second order, third order. And this is an attempt to capture how many orders of thinking they actually go through. So here's the setup. You ask people to, I typically ask for a whole number from zero to 100. Then you hold that thought, and then you say the person who's going to win this contest is the person whose guess is closest to two-thirds of the average of everybody else's guesses right so you follow that

Starting point is 00:38:51 so you everybody writes down their number and then you as the mc of this thing take two-thirds of that value and then whoever's closest to that number wins you're probably already thinking about how would you go through this right mentally because mentally? Because, you know, you sort of say it was 0 to 100, it started 50, two-thirds of 50 is 33, but, you know, people are going to go that level, especially your educated audience. Well, two-thirds of 33 is roughly 22, but maybe they'll go that far, two-thirds of 22, and so forth, right? So you keep iterating down. Now, this is a problem that has an equilibrium solution, and that's the answer is zero, because it iterates just down to zero. The problem is, and zero, by the way, is often a common answer in my course when I do this. And I say to students, like, you're real smarty pants, right?

Starting point is 00:39:33 You found the equilibrium solution, but you're not making any money, right? Because if anybody writes a non-zero number, you're not going to win. So the question is, how do you integrate other people's decision-making? And I'll tell you one other story about this, which is interesting. So when I was at Credit Suisse, I was part of a research group, and it had a number of very prominent, you know, kind of world leaders, you know, former president of Mexico, one of the prime ministers from the UK, prominent economists. I mean, this was like a really erudite group of folks. And we were appropriately having a meeting in Switzerland

Starting point is 00:40:05 and we had a behavioral economist leading a session on risk. And this guy decides to do the two-thirds game. And I'm thinking, now this is going to be interesting, right? Because we have like literally world leaders who probably negotiated these high-powered things. And they were absolutely horrible at it. It was embarrassingly bad. So I was like, oh, my God. I'm glad they're all retired now. But I'm like, isn't that interesting?

Starting point is 00:40:30 I don't know if they didn't get the setup, but they just hadn't thought through those levels. And so, as you know, in negotiation, but most things in life, understanding the position of somebody else is really important, whether it's the basic concept of empathy is super important, right? And so it's really, I thought that was a really interesting little side note, but that might be another fun, taking it back to your broader question, that might be a fun exercise just to demonstrate these principles rather than come up with some sort of a dashing solution to a problem. I like the idea of attempting some type of prediction through experimenting with my audience. And maybe I make it explicit, maybe I don't, right? Maybe it's couched in some other way, but I do love that idea. So we can table that for now. Here's one other thought, you know, you're probably familiar with a little bit of this

Starting point is 00:41:19 literature. So Phil Tutlock and some of the members of his team at the University of Pennsylvania have done these forecasting tournaments. And the big thing, of course, is this idea of super forecasters. So the question is, would the Tim Ferriss audience be a super forecaster, right? And so if you gave them geopolitical or economic events, in six months, will interest rates be X? In 12 months, will China do X, Y, or Z? That'd be super interesting to see. And now the problem is, again, that you're getting one answer from a large group and so forth. So how easy is it to update? Because the super

Starting point is 00:41:54 forecasters actually update their probabilities as things change and so forth. But that might be another fun way to, but then again, that's what markets do, right? So to some degree, they're prediction markets. That's what they're trying to do as well. Mm-hmm. Well, I they're trying to do as well. Well, I will allow that to gestate because I would just love to run more experiments and then share the results of those experiments with the people who participated. I think it would be a lot of fun.

Starting point is 00:42:15 So TBD, TBD, but I will certainly come back to that at some point. Just a quick thanks to one of our sponsors and we'll be right back to the show. This episode is brought to you by AG1 by Athletic Greens. I get asked all the time what I would take if I could only take one supplement. The answer is invariably AG1. I view it as my all-in-one nutritional insurance. I recommended it long ago in my 2010 number one New York Times bestseller, The 4-Hour Body, and I did not get paid to do so. With approximately 75 vitamins, minerals, and whole food source ingredients, you'd be very hard-pressed to find a more nutrient-dense

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Starting point is 00:43:49 Now, in addition to The Wisdom of Crowds, there are a number of books that came up in the process of doing research for this conversation that you have mentioned. And I don't mean to imply that we need to spend a ton of time on all of these, but I would love to at least get your take on two that have popped up. And there may be one or two more, but I'll mention two. One is Against the Gods, The Remarkable Story of Risk. And this came to mind because you just mentioned risk in the context of Switzerland. And the other is Complexity by Mitchell Waldrop, if I'm getting that pronunciation right. Why are either or both of these books meaningful or must-reads or important in any way?

Starting point is 00:44:38 So let's start with Against the Gods. It's written by Peter Bernstein, who was a brilliant economist and historian. And it is the history of human understanding of risk. So it's a fascinating thing. Now, I'll just say that, broadly speaking, I think understanding the history of ideas is incredibly valuable in pedagogy, generally speaking, right? So if I'm talking about an idea or I'm using an idea today, I think it's very helpful to understand where it came from, who were the propagators, what were their blind spots, where did they take a turn one direction where they could have gone a different direction and so forth. And so Bernstein just brilliantly lays this out in Against the Gods. And he was a wonderful writer. It's a very interesting book.

Starting point is 00:45:22 By the way, he also wrote a book called Capital Ideas, which basically does the same thing for the history of finance. So Peter Bernstein, that is money. And if anybody's interested in the idea of how we understand risk, and this goes back to the Bernoullis in the 1700s up to relatively modern times, it's a fabulous book. I'll give one other backup, one little step on this, which is, it's a book I almost never talk about. But one day when I was a food analyst, I was visiting a money management firm. It was actually the state

Starting point is 00:45:49 of Michigan, the pension fund state of Michigan. And I was in the waiting room, literally waiting for my meeting. They had a bunch of books and I just strolled over there and I picked up a book called Bionomics by a guy named Michael Rothschild. I don't think anybody's, I mean, I think it's a somewhat obscure book, but as a name would indicate, you know, and this book was written, I think, originally in 1990. And as a name would indicate, you know, what he was saying was the way to understand economics is really through biology. And, you know, starting really in the late 1800s, but into the early 20th century, economics became very mathematized. And in fact, there's a wonderful book called More Heat Than Light by a professor named Phil Mirwoski, which documents how economists literally,

Starting point is 00:46:32 and I mean literally mapped over equations from Newtonian physics to basically give economics street cred. So economics and finance went sort of this mathematical slash physics envy route versus going more biological. And I think that in retrospect, you could sort of say that biological way would have been a very logical way to go or as logical, albeit not as mathematically straightforward or tractable. So I've read this book, Bionomics, and I'm like, this is like so cool. And the guy sort of opens the book by saying, hey, you can't really understand economies unless you understand sort of evolution and so forth. So I was very drawn to all that. So that's the backdrop. I'm like sort of primed.

Starting point is 00:47:11 I'm thinking about this idea. And then along comes Waldrop's book, Complexity. And this is really the story of the founding of the Santa Fe Institute. And by way of background, the institute was founded in 1984 by a number of scientists who felt, and very prominent scientists, many Nobel Prize winners, who felt that academia had become too siloed, right? So the physicists hung out with the physicists, and the economists with the economists, and the chemists with the chemists. But again, most of the interesting problems in the world were really at intersections of these disciplines. And gee, wouldn't it be awesome if we got these different scientists to hang out and talk to one another? And so, this is how this thing got going in some of the early conferences. For example, one of them was the economy is a complex adaptive system, right? So, the idea of economics being in there early on

Starting point is 00:47:58 was early days. And so, why this book is so, I think, still to this day kind of exhilarating is because you read about these scientists and how they were coming up with ideas that were far from the mainstream. And when we look back on them now, many of them have become much more mainstream ideas, but it's just, it was super cool. And so one of the main protagonists, I think the book does open with a story, is Brian Arthur, who's an economist now. And Brian was promoting this idea of increasing returns. Now, if you've taken economics, microeconomics at any point, you learn about decreasing returns, right? So if Tim's lemonade stands super profitable, Michael will open up and let him stand right next door, charge slightly lower prices, and so you'll become less profitable, and then you'll have to match my prices and so

Starting point is 00:48:43 forth, and we'll compete our way down to less profitability, so decreasing returns. And Brian pointed out that under certain circumstances, there were these increasing returns. There were sort of these winner-take-all effects. This is now, again, he was writing about this in the 80s and 90s, completely heretical. And by the way, basically, the mainstream economists wanted nothing to do with it. Waldrop, I think, in a very engaging way, describes how all these ideas developed. And so if you said at the Santa Fe Institute, is there a unifying theme? It would be sort of this idea of a complex, adapting, evolving system as a way of thinking about it.

Starting point is 00:49:15 So those would be my answers. Those are two wonderful things. And my oldest son, before he went off to college, he did a gap year. And I thought, what would be a list of books that would be really great for him to read and internalize? And, you know, I think we had a list of 15 or 20 books, but these were both on that list because I just think it's super cool to understand the history of ideas. And by the way, as a teacher, if you're ever teaching something, I think it's just super helpful to know where it came from. Like, what is the genesis of this? By the way, there are a couple of things that I'm actually trying to track down now.

Starting point is 00:49:47 These are specific finance type of things. And I'm having a hard time finding the first person to come up with it. So it's kind of cool, right, to sort of go on these little wild goose chases. So I'm going to definitely come back to the Santa Fe Institute. And I'll cede my question now so it can marinate over on your side. But I'm going to take the conversation in a different direction, then we'll come back to it, which is, it seems like value investing and value investors pop up a lot around the Santa Fe Institute. It seems like Bill Miller, value investor introduced due to the Santa Fe Institute in, I guess, the 1990s.

Starting point is 00:50:26 And then I've seen a number of other mentions. So this could be just a misread, but I wonder why, maybe we can just tackle this now. Why not? Why it seems that value investors seem to gravitate towards or be involved with the Santa Fe Institute? And I suppose for a definition of terms, if you wouldn't mind just defining value investing for folks as well. I'm not sure that's the wrapper I would use, but let me just say what value investing is. And one very specific distinction here, often when you hear people say value investing, they think about buying things that are statistically cheap, low price-to-earnings ratio or low price-to-book ratio. And that way of thinking was founded by Ben Graham, who taught at Columbia Business School.

Starting point is 00:51:16 And many of the Graham acolytes were sort of these low-PE, low-price-to-book folks, and they were just buying, again, statistically cheap stocks. I think the modern manifestation of value investing is simply buying something for less than what it's worth. So it seems like all investing should be value investing, right, if it's done intelligently. So I think that's the distinction. But to your point, I think that the Santa Fe Institute, I mean, there are two reasons that I've always found it so exciting. One is the ideas that come out of it. And the second is, and perhaps even more important from my point of view, is the type of people that tend to be drawn there. Many academics are perfectly happy to stay in their lanes, right? And in fact, much of academia is aligned to encourage you to do that for promotion and recognition and so forth. And so the type of people that go to Santa Fe

Starting point is 00:52:06 are massively self-selected to be interested, have polymath-type tendencies. And by the way, investors are a really fun group. As you know, investors are a fun group to hang out with, in part because they tend to be curious people. And I think curious is the main adjective I would use to describe most of the great investors that I know, and they're learners, right? So almost all the people read a lot and try to think about things. So Bill Miller is a great example. Bill's been extraordinary in my life. You think about different people along the way that have been really important. He's certainly been that for me. He introduced me to the Institute, as you pointed out, in the 1990s. We were at a baseball game. We're sitting there and he talked about it. But that's a guy that reads all over the place, reads very widely,

Starting point is 00:52:49 reads different disciplines, and thinks a lot about how those ideas might apply, how he might be able to apply those ideas to areas of markets. You mentioned Bill Gurley. Bill Gurley's a venture capitalist, right? You wouldn't really call a venture capitalist a value investor in that classic sense, but you certainly would say they're trying to buy things for less than what they're worth and cultivate them to some degree. And he got all these ideas, grokked all these ideas as well. Josh Wolf is on our board. So we have a lot of really, I think the connection between all these folks, the thread is this idea of intellectual curiosity and a willingness to pursue that curiosity by immersing yourself in that type

Starting point is 00:53:22 of an environment. I'll add one thing to the investor comment, which is part of the reason I enjoy, if not spending time with, at least observing and studying investors because they also have a report card in a lot of cases, right? So they are placing bets based on their thinking. So it's not simply opinion versus opinion. You can look at the returns, at least for some of them,

Starting point is 00:53:44 which I find very, very refreshing. I also really appreciate that aspect of interacting with, or at least studying, a lot of investors. And in preparation for this conversation, I also shot texts to two mutual acquaintances, both thinkers I respect greatly, Josh Waitzkin and Patrick O'Shaughnessy. So I wanted to actually grab a few of the possible questions that Patrick had forwarded. Also a great podcaster. I recommend people check out Patrick's podcast. And you can feel free to decline, divert, or transmogrify this however you like. But he sent me quite a few things, and we'll probably dig into a number of them. But I thought one that would be fun for listeners, and I include myself in that group, is the

Starting point is 00:54:34 following. An asset class tour with him could be really fun. In other words, how do you think about private equity, venture credit, public equity, cash, gold, real estate, and what they do for you when done well and the role they can play. Is that a sandbox you're willing to hop into for a little bit? Well, I mean, it's just something I actually don't know that much about, but I could probably make one or two comments. One of my COVID projects was in 2020 was to do a big piece on public to private equity. And we needed to find a bunch of things just to get it out of the way. So public equities are just stocks that trade in the United

Starting point is 00:55:12 States. Today, they're around 3,500 of them, roughly speaking. What's fascinating is there are about as half as many companies that trade, public companies that trade today as there were in the mid-1990s. And they're, in fact, less than they were in the 1970s. So obviously, our economy is bigger, our population is bigger, right? You would expect the number of public companies to roughly grow in line with all those other metrics, but that has not been the case. So that's an interesting thing, like in and of itself, why is that? And at the same time, we've seen the emergence of private equity. Now, private equity is a wrapper that really covers two different areas. One is buyouts. And in a buyout, typically a sponsor will buy a company, usually using leverage, and then own it for typically five years or so,

Starting point is 00:55:56 and then try to sell it for a profit. But the key there is that they buy stable businesses, typically with lots of cash flow. Venture capital is the other side of that, which is buying very young companies, often when they're just getting going, and actually playing a very important role in fostering that development. So being on the board, giving guidance, and so on and so forth, right? So a couple observations that come out of that

Starting point is 00:56:18 that are interesting. One is, why are there fewer companies? And basically, the simple answer is, there have been lots of mergers and acquisitions and not a lot of IPOs. So part of it's the cost of IPOs have gone up. And so there are simply fewer public companies than there used to be. The flip side is they're much bigger now and more profitable on average and so forth. So that's interesting. And then the second thing I'll just say, Tim, this is just me sort of speculating a bit, which is roughly speaking,

Starting point is 00:56:42 since 1980, so let's call it the last 40 years or so, there's been roughly, and maybe we've reversed this in the last year or two, but roughly a steady decline in interest rates. That means your expected returns basically go down, right? Because you put money in the bank or invest in something, you get lesser expected return. And at the same time, our liabilities are going up, right? If you have to put a kid through college or you're contemplating your own retirement, right? You're expected to live longer and so forth. So your liabilities aren't going down. So if the expected returns are going down and liabilities are going up, like, what do you do about that? And the answer is typically you go out on the risk spectrum. You take on more risk.

Starting point is 00:57:15 And how do you take on more risk? The answer is there are two interesting ways to do that. One is to use more financial leverage, right? More debt. And that's what buyouts do specifically. And the second is to buy young companies that are inherently riskier companies, and that's venture capital. So I think part of the answer of the emergence of those two segments, those asset classes, is precisely to accommodate that basic reality that returns in more public markets have been less exciting than they have been in the past. Some of the other ones you mentioned like credit or gold or whatever, I don't really have much to say about those things. Okay. Well, we can park those. I would like to transition then to base rates. So the power of

Starting point is 00:57:54 base rates in life and business slash investing. And the prompt that I got was something related to one of the famous triple crown horses. If that is enough of a catalyst to get the party started, then I'll let you run with it. Let's start the party. Let me just say, Tim, that if there were an idea that I could go back and tell my young self, my 18-year-old self, it would be this idea of base rates. I learned about this from Danny Kahneman.

Starting point is 00:58:23 He used slightly different language, but we'll lay out the terms and go back and forth. So Kahneman used this idea of the inside versus the outside view, and the outside view is base rates. Okay, so here's the basic setup. If I present you with a problem, and it could be almost any kind of problem, you know, how long will it take you to remodel your kitchen and what will it cost? When will you be done with your book manuscript? You know, you're a college student. When will you be done with your term paper or your problem set or whatever it is, right? The standard way to think about that is to gather a bunch of information, right? So think about it, combine it with your own inputs, and then project. And like left to our own devices, that's how we all do these things.

Starting point is 00:58:57 That's called the inside view. The outside view or the base rates, by contrast, says I'm going to think about my problem as an instance of a larger reference class. I'm going to ask a really simple question, like, what happened when other people were in this situation before? And it's a very unnatural way to think about the world, right, for a couple reasons. First is you have to leave aside, like, your own views and your own cherished information, right, which we tend to place a disproportionate amount of weight on. And then second is you have to find and appeal to this base rate. And it may not be at your fingertips. You may not even think about it that overtly.

Starting point is 00:59:27 But what psychologists have demonstrated, and it's not all one or the other, but some thoughtful combination of the inside versus the outside view, sort of your own analysis versus base rates, tends to lead to better and more accurate predictions. And this sort of was a real time. I don't know what year this was, 2008, 2009, something like that. There was a horse running for the Triple Crown. So right, the first race is the Kentucky Derby, and it won the race by like four and a half lengths. Big brown this is. The second leg is the Preakness. It's in Baltimore. It was stronger still. I think it won by like five lengths or something. So it's one race away from horse racing immortality, which is pretty impressive. Now, the last race is the Belmont.

Starting point is 01:00:05 It's the longest, which is difficult. So many of these horses are actually quite fast. They're sprinters. Longer distances are more challenging for them. But Big Brown was obviously sort of the favorite, appropriately so. And he went off at odds that suggested a 77% probability of winning the Belmont. 77%. So the question is, like, all right, how likely is it that he's going to win at that probability?

Starting point is 01:00:29 And what you do is you look at base rates and you ask how many of the horses in a position to win the Triple Crown, what percent actually did that? There have been Triple Crown winners since this. So this is the date at the time. At the time, there had been, I think there was like 28 or 29 horses that had tried. 40% had succeeded. So 40% is really a lot lower than 77. But what's interesting is that eight of the nine horses that tried before 1950 succeeded. And only three of the 20 since 1950 had succeeded.

Starting point is 01:00:56 So it was a 15% success rate since 1950. All right, so you're like, okay, well, that's an interesting data point. He's going off at 77. Now it's okay. And then the second thing is, maybe there is just like a wicked fast horse, right? Maybe this is like the new secretariat. And there's a way to measure that. It's called a buyer speed figure.

Starting point is 01:01:13 And speed figures really haven't been kept accurately since the 19, I think they started about 1990, so about 30 years, call it. At the time, it was probably more like 20 years. And this horse was actually the slowest by speed figures of the last seven contenders for the triple crown all of which that had failed so you know he's going off at 77 and of course he ran the race and what made the story sort of cap the story was the horse basically took the day off the jockey technically eased him but he came in last basically right so the next day they give him a physical, you know, from his nose to his tail and they're like, is he okay? She's fine. He was just fine. So the guy who I was talking to

Starting point is 01:01:49 about this guy named Steven Crist, who's an awesome guy, by the way, fascinating guy and a famous handicapper and a brilliant writer. So I'm like, Steve, like, what's up with this? And he's like, people don't seem to realize we're talking about horses here. They just take this. So anyway, the story was he was a favorite. He was probably a 40% probability, you know, 45% if you're using all these data. But at 77%, he's a bad bet. And this goes back, Tim,

Starting point is 01:02:13 just to circle back around to our wisdom of crowds thing, right? So what happens is this is a diversity breakdown, right? So most people don't bet on horse races day in, day out. There are professional handicappers and people do it for fun.

Starting point is 01:02:24 But for the most part, there's not a lot of volume and so forth. However, when there's a Triple Crown contender, people get fired up. In fact, the Belmont, I think the attendance doubled from the prior year, even though it was a really hot and steamy day. And people pull out their wallets and they start plunking down their bets, right? Because you want that ticket that says, I bet on the Triple Crown winner, right? And, of course, these are markets that are set by the dollars flowing in. They're parimutuel markets, right? So the dollar flows are what dictate the odds.

Starting point is 01:02:49 So it's a classic example of diversity. There's a perfect example of diversity breakdown. It makes perfect sense. And again, it's like day in, day out, horse race results are actually incredibly efficient. And they're certainly very hard to beat when you take out the track take, for example, the VIG. Obviously, there are professional handicappers, but not many. And those who are doing it are very sophisticated and so forth. But you know, you and I, like regular Joes, we're not going to make money doing this. Anyway, so there's a good, that's a good example. And it's hard to short,

Starting point is 01:03:13 you could bet the field or something, but it's hard to short a horse. It seems a little bit unsporty to do that. But anyway, that's the big brown. But the broader lesson is that no matter what you're thinking of doing, you know, moving to a new city, taking a new job, anything you're thinking about doing is asking, is there an appropriate reference class? Is there a base rate that I can look at to see if I can get some information about a little bit about my prospects? We spend a lot of time on this, for example, things like corporate performance. So I know you do a little bit of investing as well, but questions like if a company has sales a company has sales of a billion dollars, like what's the distribution of growth rates I should expect, right? Let's look at history to figure out how good could it be? How bad could it be? What's the average? And then where do I think my company is going to fall within this distribution? And you know, how

Starting point is 01:03:56 optimistic or pessimistic it might be. So I could ask a million questions about base rate, but the one that's really sticking out for me is what on earth happened around 1950 with the horses? Was it anti-doping measures? What clicked in that led to that? Might be the opposite, right? Could be the ubiquity of doping. The secret's out. This is a fascinating conversation. I'm way over my skis already, but I want to tell you that for almost all the big races, the Kentucky Derby, because they've been run for a very long time under the same conditions, right? I think the horses today run essentially the same speed as they did in the 1950s. They're no faster. So I think that thoroughbred horses, this topic is fascinating in and of itself, right?

Starting point is 01:04:43 Because they've been bred from a very, very narrow stock. So there are a handful of horses that are essentially the ancestors of every horse that's around today. So the genetics are really crazy. And that's why they're such fragile animals. But I think that they're at their physiological limits and they have been for a while.

Starting point is 01:04:59 Secretariat was a freak, literally a genetic freak. And as you know, you probably heard these stories when, I don't know if they actually did this, but apparently there was some sort of an autopsy, and the secretary's heart was much, much larger than was normal for a horse like that.

Starting point is 01:05:10 So secretary really was like one in a multi-generation freak. But yeah, I think they're at their physiological limit. So the horses all today are no faster than they were back in the day. Yeah, certainly hasn't stopped people from doping horses. I know that is, I know of quite a few drugs that have made their way from research to racehorses, to bodybuilders, to the billionaires who want to live for a million years with six-pack abs.

Starting point is 01:05:37 So the racehorses have been a sort of test bed for a lot of drugs for a long time. But it's interesting that as far as speeds go, it seems that at least the top end, I wonder if the averages have changed at all. We can go look at all the numbers, but I would imagine things like marathon times or 100 meter dash and so forth. I'm sure they're all faster, right? Swimming times, for sure, they're all faster than they were in 1950. So it is interesting that this is one domain where they hit the wall. But part of it is because this goes back to our thing on diversity, right?

Starting point is 01:06:05 You have no diversity in the genetic pool. So as a consequence, you've sort of tapped it out. So if you want to build a faster horse, you would have to shuffle some genes around, which has not been happening, right? By definition, it can't happen. Yeah, I'm not going to become a handicapper, but I may have to chat with Stephen Crist and learn a bit more about this horse game. I would like to jump though to

Starting point is 01:06:26 discussing what separates good from great investors. And there's a line here that I believe is your writing. Please fact check me if I'm not getting that. But this is part of a larger piece, but what separated the good from the great investors had little to do with their analytical tools, but a great deal to do with how they made decisions. And I suppose that's maybe a subset question of just in your experience, in your studies, in your practice, what have you found most reliably separates good from great investors? The analytical stuff is anti for the game, right? So you have to understand basic accounting and finance and so forth. So there's no getting around that, and you need to do that. But I think that quote captures certainly what I think about this, which is the key is making really good decisions.

Starting point is 01:07:17 And this is particularly difficult under a bunch of different circumstances that we could talk about. But maybe the two or three biases I think are really difficult to circumvent. The first is overconfidence. We tend to think we understand the future better than we actually do. And this is something we can test pretty well in sort of experiments. And as a consequence, people think about ranges of outcomes that are too narrow. And that gets them into some trouble. So overconfidence.

Starting point is 01:07:44 And the second one, I think is even more difficult, which is confirmation bias, which is once we've made up our minds about something, we tend to seek information that confirms our point of view and dismiss, discount, disavow information that does not. And one of the vital things in investing is updating your views. And if you're not constantly doing that and doing that honestly and objectively, or as objectively as possible, that's going to put you at a substantial disadvantage. That's that decision-making aspect. Now, there's another aspect to all this that's

Starting point is 01:08:14 really important, right? Which is you ultimately have to come up with a view that's different than other people. And that view ultimately has to be correct. And so there's a little bit of an antisocial component to all of investing. Like, great investors, there's a little bit of an antisocial component to all of investing. Like, great investors, there's a little bit of an antisocial component to it. You know, some people, I think, do that better than others or more naturally than others. But that ends up being decision-making because at the end of the day, often you buy something and it goes down in your face, even if your thesis is correct. And, you know, do you have the fortitude to sort of stick with that position? The third thing I'll mention, Tim, have you had Robert Sapolsky as one of your guests? No, I haven't actually. No. Do you know Robert Sapolsky?

Starting point is 01:08:49 I recognize the name. You should probably remind me. He'd be a fun guy for you to talk to on many levels. He's a neurobiologist and a primatologist at Stanford University. You know, he wrote a book called Behave in 2017, which is, I would say, probably the best book I've ever read on human nature. It's not an easy read, but it's very well written and very interesting. He has a book coming out later this year, I believe, on the topic of free will. So, interesting guy. But Robert spent, you know, for years, obviously his academic years at Stanford in his lab, and then he would spend the summers in Kenya studying baboons. And if you ask him, why do you study baboons? He would say, because they're physiologically like humans, and like humans, they spend three hours a day

Starting point is 01:09:33 feeding themselves and the rest of the time tormenting one another. But what Robert was interested in is the topic of stress. And so he wrote a book called Why Zebras Don't Get Ulcers in the mid-1990s, which is a wonderful title, and it's a wonderful book about the idea of stress. So he's like a key guy in understanding stress. And so, of course, in these baboon troops, what he can do is, you know, the questions he's asking is like, hey, who's stressed out here? Is it the alpha male, the beta male, like, you know, the females? Like, who's getting stressed out? Or the low-ranking males? And of course, you can shoot a dart into the flank of a baboon and draw blood and measure cortisol. So they're actually, they can understand exactly what's going on, at least this rough proxy for stress. This is all a big windup to sort of talk about how,

Starting point is 01:10:12 you know, something is important for investors and particularly time horizon. So Sapolsky sort of asked this question, like what stresses out an animal, right? You're a zebra hanging out in the Savannah, right? Pursuant to his title. What stress you out? And the answer is a lion decides you're the target for lunch bad news right your structure response is going to kick in you're going to pump blood you're going to pump adrenaline and you're going to run really fast what's also important is you're turning off all your long-term oriented systems right you're turning off growth immune digestion reproductive systems these are caloric luxuries for another moment if you elude the lion you go back to your group and you

Starting point is 01:10:45 reverse all those processes. You go back to homeostasis, right? Now the question is, what stresses a human being? And we have, Claire, we have episodic physical stressors, and you've put yourself through more than your physical stressors and your different antics. But for the most part, our stressors are psychological. You know, it's the big deadline at work. It's a relationship concern. It's a relationship concern. It's something about money or whatever it is. And the point that he makes is those psychological stressors trigger the same physiological response. And your brain is not always so good at distinguishing between a physical threat and a psychological threat.

Starting point is 01:11:17 And if you're constantly psychologically threatened, your body turns the stress system on, stress response on, it never turns it off. So if I said, you know, what are the symptoms of stressed people? You come up with a very familiar list of, they're sick all the time, they have problems with their gut, they have reproductive problems, and extreme cases there don't grow properly and so forth. So here's the punchline. This is why I think this is so interesting. When you turn on your stress response, you tend to shorten your time horizon. So you're the zebra running away from the line. You're not thinking about, what am I going to be doing in two weeks, right? You're thinking like, how am I going to survive 20 seconds? Likewise, if you're human and you're stressed, you pull on your time horizon.

Starting point is 01:11:51 And that's a really interesting issue for an investor because it can be the case that as markets, for example, are tumbling and one could argue that your opportunity set is becoming more attractive because you're getting the same asset at a lower price, everything inside you're going to say, man, I need to survive now. I don't need to worry about what's going to happen in two or three years. And I actually lived through this. I mean, one of the big drawdowns of 08 and 09 in the financial crisis, we had certain, you know, some of our investors were recommending stocks to the portfolio manager and the portfolio manager would say like, hey, this seems like a great idea over three years, but if I put this in my portfolio and it goes down the next three months, I'm going to be out of job, right? I'm going to be gone.

Starting point is 01:12:32 So this is another aspect of it is this equanimity, right? This ability to sort of keep your eyes on the horizon, even when you're feeling the short-term stress, because we all do. And that leads obviously, what should you be doing to do all the natural de-stressors and so forth? There's obviously a list of things we could talk about there. But to me, those are some of those qualities. And I guess the other thing I just say overall, I already mentioned it, Tim, but I'll just emphasize it again, is that almost all the great investors I know are just incredibly intellectually curious. And they want to understand how things work. They're willing to listen and read and learn. None of them think they've figured it out, right? None of them think that the game has been mastered.

Starting point is 01:13:08 They're constantly trying to improve their ability, their craft, and so forth. And that's why they're so much fun to be around, right, for the most part. Because they're typically very interesting people because they read a lot and think about how various ideas that are swirling around there might apply to what's going on in the world today. I'd love to chat a bit about some of the content of your book, Think Twice, which for people who haven't read it, I recommend, and also has a great cover quote from Billy Bean, the general manager of the Oakland A's, or then general manager, who was profiled and highlighted in Moneyball. So one hell of a quote. So congratulations for the cover quote as well. My question relates to a component of the basic book description. So I'll just read this. In Think Twice, Michael Mobison shows you how to recognize and avoid common mental missteps,

Starting point is 01:13:58 including one, misunderstanding cause and effect linkages. Two, aggregating micro-level behavior to predict macro-level behavior. Three, this is the one I want to talk about, not considering enough alternate possibilities in making a decision. And four, relying too much on experts. Not considering enough alternative possibilities in making a decision. Could you perhaps give some examples or just recommendations for how people can expand the number of alternative possibilities they can generate or consider in making decisions. You know, by the way, think twice. Just the premise of that is that when you're faced with certain types of situations, those that you described, your mind naturally wants to think about it one way when there is a better way to think about it.

Starting point is 01:14:46 It's often a better way to think about it. So this is an encouraging to say from time to time, slow down, think twice, right? So that's where that idea came from. And you put your finger on something so important, right? Which is again, thinking about a wide range of alternate possibilities and wider than people typically think. Okay. So what are the techniques to allow people to do that? I'll mention maybe three of them and I'll try to do this fairly quickly. The first is what we've already talked about, which is base rates, right? So let's just pick something specific. You know, you're trying to figure out the growth rate of a company or something, something mundane like that. You might say, well, if the world is consensus, it's going to grow 5%. And if they kill it, they're going to grow 8%. If they do really badly, they'll grow 2%. So you have this

Starting point is 01:15:27 sort of fairly narrow band. Then you might say to yourself, well, okay, let me look at other companies that were sort of in the same situation, same size, roughly the same industries, and look what their actual growth rates were and see if that's different. And quite commonly, they're going to have much bigger range of outcomes. And that's going to open up your mind to say, okay, perhaps I should be thinking about something more expansive than what I'm doing now. The second idea is a concept called a premortem. Have you talked about this on the show before?

Starting point is 01:15:53 I think I discussed premortems. Well, premortems and their opposite. I think I discussed this with Rolof Botha of Sequoia, and there are a few other folks, but I think this is worth revisiting. Yeah, and I'll be quick about it. So we all know about postmortems, right? So postmortem, the patient has died. And we sit around, we say, given the information we had at the time, could we or should we have done something differently to lead to a better outcome, right? So we learn from our mistakes, if there are mistakes that were made. And we're all familiar with forecasting. So we're staying in the present, peering out into the future. A premortem, as the name sort of implies,

Starting point is 01:16:27 is actually a third exercise. And by the way, it's developed by a psychologist named Gary Klein. So if you want to know more about premortems, look up Gary Klein. He wrote an HBR article, Harvard Business Review article about this specifically, that'll allow you to track this down. So a premortem is that you're standing into the future. You pretend like you've made the decision. Now you're in the future, say a year from now, and this decision's turned out horribly. It's embarrassing. Then each person individually, and again, going back to our concept of diversity, each of us individually writes down why this decision turned out so poorly. So essentially, we're documenting the ways things can go bad. And so what happens often in organizations is we all coalesce around making a decision,

Starting point is 01:17:04 making a particular investment, whatever it is, and we're kind of optimistic and we're sort of positive about it. And the premortem, again, just draws out the possibilities of things not going well. And perhaps there is the junior person in the room who didn't feel emboldened to talk about this downside scenario that no one seemed to be contemplating. But when he or she has to write it out and we all read them, that opens up our minds to some degree. The last thing which is related to this is just red teaming. So most people are familiar with this concept, but it comes from military strategy. Originally, I think cybersecurity is a really good example of it today, but the blue team defends the strategy, the red team attacks. So if you're a general laying out a strategy, you say, okay, here's our strategy. If we were to attack ourselves, how would we do this? So you're

Starting point is 01:17:44 red teaming. So in cybersecurity, you develop your security, and then you hire hackers essentially to hack yourself, right, to see how vulnerable you are. So again, it's just opening up your mind to other possibilities in a way that I think is so important. And it was part of your conversation you had with Neil Ferguson. And that was this idea of counterfactuals. And, you know, I think he said something which is correct, which is historians don't really like counterfactuals. There are some psychologists that talk a bit about counterfactuals. But a counterfactual, again, is what didn't happen that could have happened. And I think it's just a really important thing that once we all understand that the future is pulsing with possibilities, and even if we do lay out these ranges of possibilities, we know that there are different paths the world can take. But once things happen, you know, it's like we forget about all the other possibilities, right? And there are two things. One is called hindsight bias.

Starting point is 01:18:38 We start to think we knew it was going to happen with a greater probability than we actually did. And the other is called creeping determinism. We start to think that what happened was the only thing that could have happened. And those are both very dangerous things to fall into as well. So it's this idea of always keeping your mind open and saying, okay, this turned out this way, but we understand there was a counterfactual

Starting point is 01:18:54 and things could have turned out differently. Building off of learning from failures and just premortem, post-mortem, all these wrappers we can put around mistakes and what we can sort of learn or attempt to learn ahead of time in terms of expanding possibilities, but also learning afterwards. It's a very clumsy way to lead into a very simple question, which is, do you have any favorite failures of your own? So these could be failures that ultimately seeded later successes, things that taught you disproportionate amount compared to perhaps other mistakes or failures you've experienced.

Starting point is 01:19:33 Do you have any favorite failures? So I mentioned Drexel Burnham-Lambert and this training program and all the positive things that came out of it. And by the way, David Epstein, well, I think it's not David Epstein talked about it, but I'm sure the idea has been around, is this idea of skill matching, which is you figure out what you're likely to be okay at and where you can add some value. That benefit happened there. But that job at Drexel Burnham ultimately led to being a stockbroker. Today, it'd be a financial advisor. And Tim, I was just an abject failure at this job. And I resigned, in quotation marks, right? But effectively, I was fired. Yeah, it was pretty bad, right? Like, in other words, I was doing something I wasn't good at. I wasn't happy doing. I was getting negative feedback on that. And so that was, I would call that a failure. And that was the culminating point of the training program. By the way, other kids,

Starting point is 01:20:18 kids, other people in my training program went on to be quite successful. So it was me, not others. And what I took away from that was, I'm probably not doing what I should be doing. And I should think more about what kinds of things I could be, where I could be more valuable and more useful and try to pivot my activities in that direction. Going back to think twice, over-reliance on experts. I'd love to hear you expand on that. And maybe just defining experts as compared to, say, people with experience we could do first. But I would love to know how people can counteract or how they should think

Starting point is 01:20:54 about over-reliance on experts. The psychologist Greg Northcraft has this great distinction between experience and expertise. He says, an expert is someone who has a predictive model that actually works, right? And this is like a super big deal in the world of investing. So there are a lot of people who have been around for a long time, they've sort of gotten through maybe a couple of good breaks along the way, and they're experienced, but they don't necessarily have predictive models that work, whereas a really, a true expert has a predictive model that works. I'm increasingly skeptical about experts, and I think the pressure on experts is coming from two different directions. The first is algorithms. And, you know, this goes back to

Starting point is 01:21:37 some famous work by Paul Meal from the 1950s on clinical psychologists, but just demonstrating that it's almost always the case that algorithms, so basically rules that we write down, outperform many experts in many different fields. By the way, it's actually even more interesting than that because sometimes you can go to somebody and say, tell me how you do this. Tell me how you think about what you're doing. And you can actually write out a bunch of rules and they're telling you the rules, right? And then if you actually compare the person with the model that the person created, the model does better than the person themselves, right? So it's not, the slippage is not the way they're thinking about the world.

Starting point is 01:22:19 The slippages are not executing, right? And this is a lot of the work on the checklist and so on and so forth. But anyway, so that's, the first thing is there can be algorithms. And I think what we're seeing in our world is more and more of these, now they're downsized algorithms, but more and more of these algorithms. And then the other one, Tim, is what we've already talked about, which is in the complex domains. I think in many instances, there's a lot of evidence that crowds, the wisdom of crowds is better than experts in quotes. And this goes back to, we talked about Phil Tetlock and the work on super forecasting a few moments ago. You know, Phil Tetlock's, the first book I read of his was in the mid, I think, 2006 or 2007 called Expert Political Judgment. And there he actually took about 400 experts, asked them to make very specific, and by the way, these are master's, PhD-level people, right, at the top of their field, and asked them to make very specific predictions in economic, political, and social domains, and then kept track and found that they were, you know, not much better than chance in making their predictions.

Starting point is 01:23:15 And by the way, they're like you and me. When they get something wrong, they have a litany of excuses, right? Like, oh, you know, you just wait, or, you know, oh, had this happened, I would have been right about this. One of my favorites is somebody said, like, my prediction was so important, it changed the course of world events. I was like, okay. So that's an interesting one. That's also interesting. So I think that the wisdom of crowds can outperform.

Starting point is 01:23:37 And so I think that's leading to this idea called the expert squeeze. But in certain domains, again, you should listen to experts. One of the ways that you can figure this out is to say, like, okay, if I appeal to a bunch of different experts, are they going to basically give me the same answer? And so tomorrow you want to say, hey, how's the weather going to be tomorrow? You could turn on various TV channels, probably a couple of internet sources, and you're going to get roughly the same thing. So those experts are going to converge on the same solution. By contrast, if you say, again, geopolitical stuff or, you know, what will the price of oil be and whatever, you can get some very well-qualified and credentialed experts with different views. They're going to say things that can be potentially wildly different. And so, you know, one example, for instance, where this is a really big deal today is stuff like

Starting point is 01:24:18 climate change. So even if you and I agree on the inputs and we're both experts, you know, we may both build models that are on some level credible, but they may generate very different outcomes. And so what do you do with that? So that's an area where we're experts. Where do you have to put the question marks? I suppose a lot of folks rely on experts in many, many different domains. And let's just say if they're trying to look at some way of analytically chewing on all the data from experts to make a decision or from one or two select experts.

Starting point is 01:24:52 On the opposite end of the spectrum, there's this term that gets used by many people, I think, very haphazardly, which is intuition. However, one of the questions that I suppose broad questions I had that I wanted to explore with you was how you think about intuition, question mark, end of question. And broadly, here's one from Josh, which is how can an awareness of cognitive biases be internalized into intuition? And then he added to that, and somatically accessed. But we can potentially hit pause on that. You and I both know, Josh. But how do you think about intuition? It's an absolutely fascinating topic.

Starting point is 01:25:34 And here again, by the way, I'll mention Gary Klein, the premortem guy, has been a pretty strong advocate for something called naturalistic decision-making, which relies a lot on intuition. Danny Kahneman, who won the Nobel Prize in economics as a psychologist, has been one who's pointed out the heuristics and biases and things like prospect theory and so forth. So they were sort of on opposite ends of this. And interestingly,

Starting point is 01:25:59 they did an adversarial collaboration in 2009. They published a paper called A Failure to Disagree. So that's interesting, Kahneman and Klein. So Tim, I would take one step back and say, using some language from psychology, this is brilliant branding, by the way. There are two systems of the mind, system one and system two. It's just like inside, outside view. It's like those guys need marketing. They need a marketing department over those psychology departments. So system one, as you know, people have talked a lot about this. It's your experiential system. So it's fast, it's automatic. It's difficult to train, but it basically runs your life for the most part. System two is slow. It's purposeful. It's

Starting point is 01:26:39 deliberate. It's costly, right? You have to recruit it often. It's lazy. It doesn't really want to do much work. And I would say that intuition is a situation where you've trained your system one in a particular domain to be very effective. For that to work, I would argue that you need to have a system, so this is the system level, that is fairly linear and stable. So linear, in that sense, I mean really the cause and effect are pretty clear, and stable means the basic rules of the game don't change all that much. So if you have those conditions,

Starting point is 01:27:15 and by the way, even driving your car, you've got some intuitions about how that works, you can get around, that's fine. If I put you in a stressful driving situation, of course, like bad weather or certain speeds whatever you're what you know to do is going to not be sufficient to get the job done so um i had this interesting conversation with josh about this specifically by the way the art of learning is fabulous i'm a huge fan and by the way just in awe of his accomplishments all

Starting point is 01:27:42 his accomplishments but certainly when you think about two domains, chess and martial arts, for instance. And he was, you know, working with different investors and he would say to him, he told me, he's like, I would tell him like, rely on your intuition. And I was like, dude, I don't know if that's good advice, right? And the reason is, I'm like, for you, Josh, you happen to excel and become world-class in two domains that were linear and stable. Chess is a perfect example. It's almost like the canonical example where experts exist, they're grandmasters, they chunk. I mean, all that kind of stuff, they're just operating at a different level than certainly I am. And then you go to the martial arts. And I just remember reading in The Art of Learning,

Starting point is 01:28:25 he's got this interesting section toward the end where i think he was in some sort of like world championships for tai chi and it was in taiwan and and so he goes there and i don't know enough about how all this works but i hope i get this roughly right is apparently they decided to change the rules to change the like a starting position for engagement and the size of the ring which seemed like a really big deal so he's been training using these other things. And all of a sudden, essentially my, my system didn't be, became unstable, right? Likewise, by the way, if you said chess, you know, we're going to make the board now 10 by 10 and the pieces move differently, right? All the expertise of the grandmasters would go out the window. So I think that intuition tends

Starting point is 01:29:03 to be way, cause we all feel it, by the way, we all have that sensation of an automatic answer that comes to us. But I think it tends to be way overweighted. And, you know, the other thing we have, another problem with intuition is a big sampling bias problem, right? Which is like people say like, how'd you come up with this idea? And like, ah, it just came to me in a flash, like intuitively, right? And we forget about all the dumb ideas that came to people that don't talk about, right? So there's a sampling problem as well. So that to me would be the thing on intuition that I think is really important.

Starting point is 01:29:30 So it's not that it doesn't exist. It absolutely does. It can be through this training. Now, this goes back, I mean, Josh's question is a little bit another level, right? Which is how do you eradicate bias from this? And I do think that's almost part and parcel of the system, right?

Starting point is 01:29:43 Because if you're learning in one of these stable and linear systems, your failures become – it's much more – it's easier to point out your failures, I think, or your mistakes or your errors than it is perhaps in other systems. So I think they kind of get weeded out to some degree. We also have these also – I mentioned before like overconfidence and confirmation bias. We have biases and all sorts of other things, but those tend to be more relevant for more open domains per se. And by the way, I should ask you, Tim. So would you say like,

Starting point is 01:30:11 when you think about your experience as a wrestler, let's just focus on like wrestling perhaps, or even dancing, but wrestling. Do you feel like you trained yourself in such a way that you, not to say it was perfectly automatic, you may have had a little dialogue in your head, but you sort of knew what you were doing

Starting point is 01:30:26 and how to do it fast and hard and accurately. Would you say that? I would say that probably even more so in judo, but I certainly think I went from, say, unconscious incompetence to conscious incompetence to conscious competence to unconscious or kind of automatic competence which is part and parcel of competing in probably i would have to imagine most sports not all but speed is a deciding factor so i do feel like i got there yeah no i think that's and that's a good example where

Starting point is 01:31:00 and again like i don't know exactly how the rules are in judo, but again, if I change the rules somehow or even in any sports you watch, popular sports like basketball or ice hockey or football, whatever. So if you change the rules, it does change – it takes people time to adapt and in quotes retrain in order to internalize. And like you said, you go from that awkward phase of like I'm thinking about what I'm doing to sort of being automatic. And I – it should provide maybe a little bit more context to you for, I'm thinking about what I'm doing to sort of being automatic. And I, it should provide maybe a little bit more context to you for why I'm asking about intuition. Certainly I'm asking because I wanted to build off of what Josh had, had put forth.

Starting point is 01:31:36 And I know he thinks very deeply about different systems of thinking and is, is truly a spectacular competitor and is almost just beyond comparison for me in his ability to systematically deconstruct and become world-class in different domains. I mean, he's doing it with foilboarding right now. And to watch his progress over the last few years has just been astonishing, quite frankly. I've also started to ask other podcast guests and friends in different domains about intuition, not because I'm looking to justify it in any kind of new age way or overweight it, but I'm curious how, perhaps put a different way, they utilize different systems of thinking in their own lives. And so I had, for instance,

Starting point is 01:32:26 John Vervaeke, who's a professor of a few different things, cognitive science among them, at the University of Toronto, and he talked about intuition as implicit learning. So pattern recognition and how that can be well-shaped or poorly shaped. I'm using my words and not his. I am, and this isn't a question, I suppose, more a confession of context, which is just to say I am increasingly interested, though, in very fast decision-making, understanding that there is a sampling bias, right? It's very easy to remember the handful of times where you come up with something brilliant very quickly and subconsciously or consciously dismiss all the stupid things that you came up with.

Starting point is 01:33:08 But nonetheless, an area of interest, I guess, partially because I've just focused so much on the analytical side and the more laborious forms of arriving at answers that that's something I'm deeply interested in. But I do think, I mean, even your point on implicit, I don't know what your exact phrase was but implicit it certainly would fit what i would believe about this which is again often experts if you ask them how they're conceptualizing things they're i'm not sure they're completely aware of how they're doing it right even things like chunking you know chunky was something that was observed by psychologists looking at chess players i don't know the players themselves were

Starting point is 01:33:43 saying this is how i'm doing it so it it's super interesting. Yeah, no, I think it's super interesting how the mind works. And experts, they definitely work in a different way than the rest of us. But I'll just say like in the world of investing, investors often talk about this idea of pattern recognition. And again, pattern recognition, if your system has certain characteristics, I think works great. The question again is in investing is how do I parse what I think would be lend itself to where pattern recognition will be effective versus where it's unlikely to be effective. And that's, that's the interesting question. That's the line I'm interested in, in understanding. I'm similarly interested. Well, let me bring up maybe just one or two

Starting point is 01:34:19 final questions and we can certainly go anywhere else that you might like to go. But this one is less conceptual, more personal. So this is something that came to mind for me, but also came up with some of your students in your tribute video. And that a lot of books. You have five kids. The list goes on and on. And I would love to hear any advice or tenets or rules you have for time management. Maybe that's the wrong term to use. Life management, perhaps. You mentioned one of them before we started recording, which was being religious about sleep. I don't know if that's one of the pillars, but how on earth do you juggle all of these things and still seem to have a reservoir of energy

Starting point is 01:35:17 left over? It's pretty staggering to me. Yeah, it's certainly not as impressive as it looks but let me just say that i'll start with my life partner my wife you know and i really mean a partner and i've always thought this is at least my own view i don't i don't people have talked about this so this is how they feel but it's almost like an amplifier and if you have a really good relationship and someone that works well with you and you're compatible and you have the same sort of sets of goals, it just amplifies everything and makes everything better. And I've had that. So we've been married, you know, 30 plus years.

Starting point is 01:35:53 And that is the number one single factor, I would have to say, just being with a partner who's really supportive and understanding. And, you know, even like for years when we go off on vacation, she would always allow me a couple hours to go off and read stuff and something like that. So just being thoughtful about that. So that is first and foremost, and dealing with a lot of stuff, including with the kids and so forth. The second thing is, I don't know. I've been doing this for a very long time, right? So it sounds like you're reading up all these things. It's over a very long period of time. I will just say that I enjoy a lot of this stuff. So I really enjoy learning things.

Starting point is 01:36:29 I enjoy reading things. I enjoy trying to understand things at first principles. I enjoy trying to track ideas down to their genesis to understand where they came from and how they got to where they are today. I also enjoy writing. I'm not that good at it, but I need to keep working on that. By the way, was John McVie your professor at Princeton? He was.

Starting point is 01:36:48 And I still, much like some of your students were saying that their friend took your course 15 years before and kept all the notes, I still have all of my notes from John McVie's seminar at Princeton. Well, I read, I mean, I just read, I'm embarrassed to say I got to it late, but I read draft number four last year. And I was just like, it's so, on some level, it's like brilliant and on the other level, it's like so discouraging. It's like, this guy is like so off the charts, so good, right? Or you read Michael, another Princeton guy, Michael Lewis, or you read these guys and you're like, oh my God, spectacular, right? But I think this idea of organizing your thoughts and trying to communicate them effectively,

Starting point is 01:37:28 that's also very motivating. I will say this, and this is something I share with my students, and I try to embody this to the best of my ability, but sort of the foundation, you know, I use the lame term, but like a mental athlete, but like if I were trying to compete at a high level as an athlete, what kinds of things would I do? And I would practice and I would make sure I was getting my rest. I would recover. I'll make sure I'm eating properly and so forth. So like, what would that be for cognitive tasks for me? And by the way, I really appreciate that you've spent so much time with Matthew Walker and brought his ideas to the world because I think his stuff is really, really powerful. And in particular, just to zoom in on this idea of the cognitive performance.

Starting point is 01:38:07 Well, let's just say negatively, the cognitive degradation, if you're not sleeping properly, is just staggering, right? So to me, the cornerstone is sleep. And I really do try to focus on that pretty religious about the sleep thing. And I'm an eight-hour guy. That really does make a difference for me. And then for me, what follows is exercise. I've always been a lifelong athlete. So I've always enjoyed movement. But for me, that's really

Starting point is 01:38:29 important to be able to move every day and be very active. And I don't know that I do everything, Tim, that you're telling me I should do, but I do, you know, I lift and I could mix it up a little bit more. And then for me, actually diet, and I try to be very careful with diet too, but that is actually falls. If the first two are in shape, like the last one seems to go pretty much. It's like if I'm not sleeping or exercising, everything else goes to hell in a handbasket for me personally. So those are the things. So that allows me to perform, I think, to operate at a fairly high level for me. Now, I'll just, one quick story on this is that in the late 1990s, I was at Credit Suisse, as you mentioned, and I had a brief stint as a job called the product manager, which meant I ran the morning research meeting, which started at 7.30 in the morning, which meant I had to get in there a little bit earlier.

Starting point is 01:39:12 We live in Connecticut, so I had to commute in. So I was getting up really early every day. And with five kids, it's hard to go to bed super early, right? So I was just massively sleep deprived. And I signed a book with Al R Rapoport to write the first edition of Expectations Investing. So I was like, all right, I'm going to do this. I got clearance from my boss. I'm like, I'm going to work from home, you know, like three days a week. This is back, you know, whatever, this is like 1999, 2000. And so what did I do, right? I slept an hour more,

Starting point is 01:39:37 spent an hour more of my time, but I slept an hour more. I'm like, oh my God, this is how I'm supposed to feel? Like at three o'clock in the afternoon, I'm still productive. Like for years, for years, literally, like afternoon, I was like a basket case, right? I could talk to people, but I could certainly not do any hard lifting cognitive work. Whereas correcting all that has really made a huge difference. So that works for me.

Starting point is 01:39:58 Now, I would just say the other thing is, you know, because people often comment like how much I read and whatever. I actually don't do a lot of other things too. So I don't, I've never seen Game of Thrones, you know, for instance, I'm not proud of that. So it's, there's some trade-offs, right? Just to be clear about all these things. So people focus on one aspect of something without looking at the deficits and other categories. It's very important to balance all that out. What are other things on your not to do list

Starting point is 01:40:21 for you personally? Okay. So for me, the things that I try to avoid, so first of all, I just would say that this by constitution, this is just the keys that were handed to me. I don't have an addictive behavior, so that really helps a lot in things. So I'm not, for example, a drinker, a big drinker, very light social drinker. So I think alcohol itself is a huge thing, and I would not do more of it. So that's one big one. Yeah. The other one is just, it would be time allocation and just be like how I'm spending time. Again, it's not good because I'm not up on all the things in pop culture and so forth, but I think you'll be fine. Yeah. Yeah. Well, I don't know. Yeah. I hope so. Five kids, any resources you'd recommend or thoughts on parenting that you'd like to share

Starting point is 01:41:03 with people who are in earlier innings? People often ask this question, like, have you changed your mind about anything? The one thing, I don't know that I completely changed my mind, but the one thing that I found to be really interesting and to some degree liberating is the work of Judith Rich Harris. I don't. Do you know Judith Rich Harris' work? And her first book is called The Nurture Assumption. And then I think she wrote a second book called No Two Alike. She passed away a few years ago.

Starting point is 01:41:39 First of all, her background is very interesting because she was sort of shunned from a PhD program in psychology, but went on to like write textbooks and was basically an independent scholar. You know, one of the premises I think most people operate with is that parents are really important in how their children turn out. And I think what her work shows, and by the way, the fascinating literature in twin studies, right, twins separated at birth, I think just demonstrates for the most part that obviously you need to put a roof over a kid's head and love them and feed them and do all those good things. But for the most part, there's a big chunk of nature that's important in how people turn out. That to me was a really interesting one because when you have five kids, you have under one roof, you have a lot of diversity in their own interests and capabilities and so on and so forth. And then the other one, this is probably totally pop, but I always liked this book called Parent Effectiveness Training, PET. And what I liked about it was the guy, I hope I'm getting this accurate,

Starting point is 01:42:33 presenting this accurately, but the author argues like, you know, you should think about, and this is not when they're babies, but when they're a little older, you know, you should argue like, what are the problems, your problems, and what are the problems your problems and when are the problems the kid's problems? By the way, this is a little bit of the Jonathan Haidt work, incidentally, sort of free-range kid thing, right? So when is it your problem, when is it the kid's problem? If it's your problem, then you say to the kid, listen, I need you to help me to get this thing solved so that you're asking for the help from the kid, but it's your problem. If it's the kid's problem, the natural inclination of parents is to solve the problem because you know how to do it rather than let the kids solve the problem for themselves and you

Starting point is 01:43:09 might say something like this is your problem i need you to solve it i'm here to help you if you'd like but you can do this kid with five years old right i'm here to help you if you need help but i want you to figure this out on your own so this idea of again taking the initiative thinking about alternatives for yourself as a little kid even, I just always like that distinction. And there's a lot of other stuff in the book. But that, to me, is one idea I've always thought about is, is this my problem or is this the kid's problem? Is this the kid's problem? Let me make sure that I let him or her solve the problem, me to help if they need it, but only playing that secondary role.

Starting point is 01:43:42 Well, thank you for answering that. As much as you dislike talking about yourself, I may force you to do it one or two more times. Complex adaptive systems. I'm curious to know, outside of business and investing, how being exposed to the Santa Fe Institute and or complex adaptive systems and learning more about such systems

Starting point is 01:44:03 has just changed how you look at the world or experience the world. Unbelievable. Totally changes your point of view on everything, I think. It makes you much more circumspect, right? You know, I think you recently were talking to Jonathan Haidt, and I think he kept talking about this basic concept of when you're messing with a complex system. I think the big point, and there's a chapter about this in Think Twice, I think we use the example of Yellowstone National Park, is that it's very difficult to manage a complex adaptive system, right? So in other words, the perturbations, the outcomes are not corresponding always with the size of the perturbation, which is really hard for people. So classic examples, ecosystems, economies, all the climate issues,

Starting point is 01:44:47 these are all complex adaptive systems, and they're just very difficult to think through and manage and even to model to some degree. So yeah, I think once you have that framework in your mind, and by the way, for me, just professionally, this is, I think, the best way to think about markets specifically and why, again, markets are hard to beat, which they are, but why they periodically go haywire, which they do. I think it's just a lens through which to see a lot of different things in life in a way that's, I think, more representative. Now, I think the downside is that the recognition, I think it makes you feel like you have less control, which is, I think, fundamentally correct. But I think that's in some ways liberating. And so as you look at these systems and you try to improve the world,

Starting point is 01:45:30 and people always talk about unintended consequences, but if I have an intervention or I try to engineer an intervention, what is the unintended consequence? Can I think about those things? And understanding if you're messing with a complex adaptive system that's a nonlinear system, it's going to happen. And so you find that freeing because you're not grasping too tightly to the misfounded belief that you can control these things. Precisely. Yeah, precisely, precisely.

Starting point is 01:45:54 It's interesting. If you're trying to understand a system, is it useful to be able to describe it in terms that seem to be reflective of what's going on? And I think that's probably right. So I think this is just a better description of a lot of systems that we deal with and we don't necessarily describe things properly. So I think this helps in that regard too. I'm ready to dig in after being waterboarded with all the value of studying complex adaptive systems from Dr. Bill Gurley and yourself.

Starting point is 01:46:24 I'm sold. So I need to, sounds like, well, I don't know, if I wanted to read about complex adaptive systems, is, let's see, I'm trying to find the title of the book, Complexity, that came up earlier. Is that the place to start? Or are there other books you would suggest starting with? There's a book by Melanie Mitchell, who is now a resident faculty at the Santa Fe Institute called Complexity, a Guided Tour. And it's more than just the narrow concept of complex adaptive systems, but there's tons of stuff in there that's absolutely fascinating. And I would just say like every thinking person, certainly scientifically literate person, if you can grasp the ideas in

Starting point is 01:47:02 Melanie Mitchell's book Complexity, that would be a great start. There are a lot of resources on the website at the Santa Fe Institute. So that is santafe.edu. So I would check that out as well. But if you really just go to a bookstore or go to Amazon and type in Complexity or Complex Adaptive Systems, a bunch of stuff will show up. Melanie, by the way, one of the people she worked with was John Holland. And John Holland, he may have coined the term complex adaptive system, but John Holland is also like another, he's also passed away, but a titan in this whole area as well. So I wanted to perhaps wrap with the question of the metaphorical billboard, and I'll put this in context.

Starting point is 01:47:40 And if this is a dead end, I'll take the blame for it. And the question is, I suppose, pretty simple. It's simple to ask, which is, if you had a billboard on which you could put anything, metaphorically speaking, to get a message, a quote, a question, an image, anything out to billions of people, ideally non-commercial, what might you put on that billboard? Does anything come to mind? One thing that comes to mind is there's a quote from Phil Tutlock's book, Phil and Dan Gardner, super forecasting.

Starting point is 01:48:13 There's just a quote, which I love. And I find myself repeating it often. And it says, beliefs are hypotheses to be tested, not treasures to be protected. I love that. That's great. Beliefs are hypotheses to be tested, not treasures to be protected. Oh, I love that. That's great. Beliefs are hypotheses to be tested, not treasures to be protected.

Starting point is 01:48:29 Now, we all have treasured beliefs, right, to some degree, but to the degree to which we can really, like you said, sort of have a light touch on our beliefs, a light hold on our beliefs. I think that's a great way to try to go through the world. So I love that, and I think that would be great for people. Can I mention another one? Again, this is too wordy, but there's a really interesting book

Starting point is 01:48:51 called The Psychology of Intelligence Analysis. Do you know that? You probably do know that book by Richards Heuer. It's called The Psychology of Intelligence Analysis and the author is Richards Heuer. And there's actually a PDF of it, which you can get through the CIA website. So if you just Google Heuer, H-E-U-E-R, the psychology of intelligence analysis, and then CIA, it'll pop up somewhere.

Starting point is 01:49:13 And I'm going to paraphrase this. It's toward the beginning of the book, but I always love this, too. And it goes along these lines. He says, analysts who know the most about a situation have the most to unlearn when the world changes. It's kind of a related theme, right? Which is, Phil Tetlock talked a lot about this in Expert Political Judgment. You know, you're an expert on the Cold War, and you've been studying, you know, U.S.-Soviet relations for a long time. And all of a sudden, the Berlin Wall comes down, and there's a whole new reality. What are you going to do, right?

Starting point is 01:49:46 You have to unlearn all the stuff that you know and start anew. And that's just really difficult for people to do. So one of my takeaways in that latter, why I think that one's interesting, is that's why the beginner's mind is so important. And as I always like to say in organizations, what's bad about young people is they don't know anything. And what's good about young people is they don't know anything. And what's good about young people is they don't know anything, right? So this idea, can we have people around us?

Starting point is 01:50:11 Can we surround ourselves with people who are willing to ask the naive question or willing to have fresh eyes or willing to not carry around baggage perhaps? And that baggage may have been very helpful for us at some juncture, but to not have that baggage. And so that to me would be another, you know, this idea of trying to avoid this situation where you fail to unlearn based on your past. What a great place to begin to wind to a close. So Michael, people can find you on Twitter at M.J. Mauboussin. That's M-A-U-B-O-U-S-S-I-N. Your website, michaelmauboussin.com. Where should people start with respect to your books? If they are a layperson, not focused on investing, but would like to become better thinkers,

Starting point is 01:50:54 where would you suggest they start? And then for professional investors who are new to your work, or people who would like to become better investors, where should they start? For decision-making, the more fun ones would be Think Twice and the Success Equation, which is about specifically the topic of luck and skill. So there is investing stuff in there, but there's a lot of sports stuff and business stuff.

Starting point is 01:51:15 Now, what's interesting, I'll tell you, these are all these little backstories. So I wrote Think Twice, and I had a chapter about luck. There's a chapter about luck and skill toward the end, but I had it as chapter two. And my editor goes, oh, you know, I don't know. Like, this seems like a little bit boring. No one's going to really care about this. Like, you could keep it, but like put it at the end. You know, nobody reads the whole book.

Starting point is 01:51:36 So I put it at the end. And then I sent out the book and a bunch of friends contacted me, people I like. And of course, they're going to say nice things, but there's a bunch of people, like a bunch of people said to me, like, you know, that was they're going to say nice things, but there's a bunch of people, like a bunch of people said to me, like, you know,

Starting point is 01:51:46 that was fine, it was all good, but boy, that luck and skill stuff, I wish you talked more about that. So I was like, oh man, I knew that was good, right?

Starting point is 01:51:52 Because the Big Brown story, we did lead the book with the Big Brown story. And so, that got me thinking more about what can we do with that luck and skill topic. Now, Nassim Taleb wrote a book

Starting point is 01:52:01 called A Fool by Randomness in 2001. And I have to say, you know, Michael Lewis's book, Moneyball, I was a lacrosse player. I played lacrosse in college. So like, I was never like a big baseball guy, but I read that book. In the hands of Michael Lewis, that topic was absolutely fascinating and got me very excited about thinking more about sports analytics. So I delved into that community a little bit. And, you know, there's a ton, because it's obviously a very, there's a lot of data and

Starting point is 01:52:25 more constrained systems. There's a lot those guys can talk about with luck and skill. So that ended up being the success equation, which is a book about luck and skill. So if you're broader decision-making, think twice. If you're interested in luck and skill, particularly as a topic, the success equation. I mentioned already more than you know, which were the greatest hits of The Consilient Observer. That one is going to be, it's a little bit all over. It was the most commercially successful of my books, but it's a little bit like all over the place. So if you like just picking up a book and reading a random chapter without a lot of structure, because I end up putting it just in sections, but that's the book to read. So these are 1,500 word chapters.

Starting point is 01:53:00 You're not going to get bogged down by anything. Repeat the title one more time. Yeah, more than you know. Got it. Yep. Yep. And then the final one is Expectations? Yeah, more than you know. Got it, yep. Yep. And then the final one is Expectations of Estimating. There are two versions of it. By the way, think about this, Tim.

Starting point is 01:53:10 This is amazing. The first, we signed the contract for this book in 1999, right? The stock market's roaring. The economy's doing great. The book came out September 9th. No, September 10th, 2001. So the day before a national tragedy, which happened to be in the

Starting point is 01:53:25 middle of a three-year bear market and stuff, because it was like, timing is horrible. Anyway, expectations investing. And so we did another version of it 20 years later, and that came out in the fall of 2021. So expectations revised. And so if you're a serious investor, and by the way, there's a website that goes with that called expectationsinvesting.com, which also includes a bunch of downloadable Excel tutorials that brings those ideas to life. And I'll just mention, I already mentioned Al Rapoport creating Shorter Value. He's an extraordinary guy. He's now in his nineties. I talk to him very frequently. He's fabulous. His mind is going, he's working on multiple projects. His mind is going great. It's been throughout my career, knowing him for 30 plus years, a complete delight

Starting point is 01:54:03 working with him, but it's not stopped. It's been so much fun. So I'll just say that was for the series. What a gift to be and what a turn of fate to be introduced to his work and have it impact you so deeply when you were just getting started and then to get to the point where you're collaborating. That's just incredible. It's just wonderful. You're absolutely right. And again, as we know, we all have our lucky turns. I met him first in May, 1991. And I can remember it. Somebody called me up and they're like, Professor Rapoport's going to be in New York. He has 20 minutes to meet you. You could bow. And I was like, oh my God. It was like, I'm not worthy kind of scene.

Starting point is 01:54:41 And I hit it off with him him and he invited me to join some executive programs at Kellogg in the early 1990s. So I was a young guy, I was in my 20s. And I think it was, you know, kind of risky for him to do that. And that's where that relationship got going. So yeah, it's been incredible. And by the way, as someone who's tried to teach, I've now, I'm on my 31st year at Columbia Business School, with someone who tries to teach, it's extraordinary because if I need how to explain something, all I need to do is call him up and we talk it through.

Starting point is 01:55:09 And he's just such a brilliant teacher. He sort of helps me understand what I'm talking about and get to the right place. Anyway, these are the kinds of relationships that are so valuable. Yeah, what a beautiful relationship. Michael, this has been a lot of fun.

Starting point is 01:55:23 I've taken copious notes. I have a lot to read. And I really appreciate you taking the time. Is there anything that you would like to add? Any closing comments, requests of the audience, complaints that you'd like to lodge formally? Anything at all that comes to mind that you'd like to say? I think we covered a lot of terrain, Tim,

Starting point is 01:55:44 and I really appreciate it. First of all, I want to say how much of a fan of yours that I am and how much I've learned from your podcast over the years. And there's so many things I admire about what you do in particular that I sometimes feel I am trying to contribute in a way to help people think better and work better, especially in the domain of investing. But I really appreciate that you're actually a guy doing stuff all the time. So I'll just say that as a point of admiration. And I leave this as sort of the final thing I say to my students. But this idea that recognizing that if you're in a domain that's largely cognitive, what would you do to try to improve your performance? We talked about sleep and exercise and diet. But I just think that these are things people should take really seriously to be really good

Starting point is 01:56:28 performers. So that's what I probably would leave with is just to make sure that people, to the best of their ability, we all, you know, you have kids running around, things happen in life. I totally get it. But your ability to do those kinds of things, that's really, that's awesome. Absolutely. Well, thank you, Michael, for saying that and for being so game to cover so much terrain. And to everybody listening, we'll have links to everything we discussed in the show notes as usual at Tim.blog.com. And if you can't spell Mobison, then just type in Michael and chances are you'll find Michael right away. And until next time, thanks for tuning in. Be just a bit kinder than necessary to other people and to yourself. And remember, if you're doing a lot of work cognitively, you're a cognitive athlete and your brain is not separate from the rest of your body. So you need to mind your P's and Q's when it comes to the basics, the fundamentals,

Starting point is 01:57:22 and that includes sleep. So thank you for listening, sleep. So thank you for listening, everyone. And thank you, Michael. And until next time, this is Tim Ferriss signing off. Hey guys, this is Tim again. Just one more thing before you take off. And that is Five Bullet Friday. Would you enjoy getting a short email from me every Friday that provides a little fun before the weekend? Between one and a half and two million people subscribe to my free newsletter, my super short newsletter called Five Bullet Friday. Easy to sign up, easy to cancel. It is basically a half page that I send out every Friday to share the coolest things I've found or

Starting point is 01:58:00 discovered or have started exploring over that week. It's kind of like my diary of cool things. It often includes articles I'm reading, books I'm reading, albums, perhaps, gadgets, gizmos, all sorts of tech tricks and so on that get sent to me by my friends, including a lot of podcast guests. And these strange esoteric things end up in my field, and then I test them, and then I share them with you. So if that sounds fun, again, it's very short, a little tiny bite of goodness before you head off for the weekend, something to think about. If you'd like to try it out, just go to tim.blog slash Friday, type that into your browser, tim.blog slash Friday, drop in your email and you'll get the

Starting point is 01:58:40 very next one. Thanks for listening. This episode is brought to you by Shopify. Shopify is one of my favorite companies out there, one of my favorite platforms ever. And let's get into it. Shopify is a platform, as I mentioned, designed for anyone to sell anything anywhere, giving entrepreneurs the resources once reserved for big business. So what does that mean? That means in no time flat, you can have a great looking online store that brings your ideas, products, and so on to life. And you can have the tools to manage your day-to-day business and drive sales. This is all possible without any coding or design experience whatsoever. Shopify instantly lets you accept all major payment methods. Shopify has thousands of integrations and third-party apps from on-demand printing to accounting to advanced chatbots, anything you can imagine. They

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The Tim Ferriss Show - #659: Michael Mauboussin — How Great Investors Make Decisions, Harnessing The Wisdom (vs. Madness) of Crowds, Lessons from Race Horses, and More

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