We Study Billionaires - The Investor’s Podcast Network - RWH015: Betting Better in Markets & Life w/ Annie Duke

Starting point is 00:00:00 You're listening to TIP. Hi folks, I'm thrilled to introduce today's guest, Danny Duke, who has a fascinating background. Annie was poised to become a college professor when she got ill, dropped out of the academic world, and started playing poker as a way to make ends meet. Over the next two decades, she won more than $4 million as a professional poker player. That experience led her to become a leading expert on decision-making, not only in poker, but in financial markets and life. She wrote a bestselling book titled Thinking in Betts, and she's just published an excellent new

Starting point is 00:00:34 bestseller titled Quit, which explores how to decide when to fold and when to stick. That's a vitally important question for investors, as we're repeatedly faced with difficult decisions about when to take our profits on winning investments and when to dump our lousy investments. As Annie explains in this conversation, we tend to be especially bad at making rational decisions when we're losing money, which is a situation many of us are facing right now. So what can we do to make better decisions, both in markets and life? That's really the central theme of this conversation. As you'll hear, Annie shares some very practical lessons about how to handle loss and uncertainty,

Starting point is 00:01:15 how to deal with bad luck, and also how to reduce the impact of our many cognitive biases. She also talks about her experiences in poker and how they apply to investing in really everything from stocks to Bitcoin. And she shares what she's learned from a wide range of extraordinary friends, including two Nobel Prize winning economists, Richard Thaler and the legendary Danny Carneman. I found this conversation hugely enjoyable, but also really eye-opening in terms of understanding my own biases and blind spots. I hope you enjoy it too. Thanks so much for listening. You're listening to The Richer, Wiser, Happier Podcast, where your host, William Green, interviews the world's greatest investors and explores how to win in markets and life.

Starting point is 00:02:04 Hi folks, I'm really delighted to welcome today's guest, Annie Duke, who's written a fascinating new book titled Quit, which is all about knowing when to fold and when to stick in really many different areas of life, including your investments and your career and I guess your relationships as well. I just finished reading the book last night, and I highly recommend it. It's a very interesting and thought-provoking book. So Annie, thank you so much for joining us. Well, thank you for having me, William.

Starting point is 00:02:40 I'm excited. It's a great pleasure. I wanted to start by asking you about a pioneering psychology professor named Lila Gleitman, who died last year at the age of 92. Because at the very end of the acknowledgement section of your book, you write one last final thank you to the late Lila Gleitman, my mentor and best friend. Right up until the week she passed, Lila would inquire about this project, excited about the topic and eager to be my thought partner.

Starting point is 00:03:07 A mentor's work lives on through their students, and I hope she would have been proud of the finished project. I miss her every day. And so I was wondering if you could just start by telling us who Lila Gleitman was and how she influenced you so profoundly. So now I'm tearing up. Yeah, so Lila, just an intellectual giant in cognitive psychology. Her specialty was first language acquisition.

Starting point is 00:03:31 She did psycholinguistics. And she started way back when it was a very interesting time to be a woman in academics. She studied at Penn. She's very good friends with Nome Chomsky, very much under the influence of him. Zellick Harris was her advisor, who these are all obviously giants and psycholinguistics. And she originally couldn't get a job as a professor because she ended up marrying Henry Gleitman, who also just like larger than life. He died about 10 years ago.

Starting point is 00:04:00 And Henry had a professorship at Swarthmore, and so she could not get one because you weren't spouses weren't allowed to be at the same place. She ended up being like a research assistant for a while before she actually got a tenure track position. But she was a real pioneer in thinking about something really important about, I mean, I really think about this as informing the way that I thought about poker, which is how does a child learn their first language, which is not trivial, right? I think that we think that, well, people say words and then they point to things. And then obviously, if I say book and I point to a book as the child, you go, oh, that's a book. And then that's sort of how it proceeds. But it's actually, if you start thinking about it, it's like that seems incredibly hard to do because there are all sorts of things, which first of all are non-obvious about pointing to. Like, how would a child ever learn a word like think?

Starting point is 00:04:50 So you point to someone who's thinking, what are you pointing at? Right. Or believe. that doesn't exist in the world. It's conceptual, right? And then you can also think about other types of even action verbs like walk, which is really hard because when you point the action of walking, you're also pointing to lots of things. And that's separate and apart from the structure of the language, things that we call

Starting point is 00:05:10 a closed class, like preposition, articles, like, uh, the, those kinds of things. So she was really thinking about, well, in that case, like there isn't, it doesn't seem like there's a very clear mapping between the world and the things that are being set. not in a way that it makes sense that someone would be able to learn this language in the space of two years. And I think that we can all feel that when we're trying to learn a foreign language, how incredibly hard it is. And we even have a language already that we can base it on. And so kind of taking a lot of influence from Chomsky, what she said is, but there's a structure to the language. And the structure is very specific about what a word could or could not mean.

Starting point is 00:05:48 So as an example, if I say to you, the man daxed into the store, even though you don't know, know the word dax, I have confined, like, it can't be believe, right? It can't be thought. It has to be something that has, like, walked into, stepped into, looked into. I've constrained the set of things that that could be. And if I gave you more structures within which that was I said, the man daxed into the store, but also I could say the dog daxed, right? Then that starts to constrain it even further and that if there were some way that the child had access to the structure of the language, that the structure actually creates real constraints about what any word could or could not mean, right, and that this would allow the mapping to occur more quickly.

Starting point is 00:06:33 And so she just started sort of thinking about that problem and really just a bot, you know, through many, many brilliant students like Alyssa Newport, Susan Golden Medal, Sharon Armstrong, Barbara Landau, just a variety of really, really brilliant students who have come out of her lab, Gary Marcus is another one, started building this body of proof that the child does actually have access to the grammar. And one of the, like, amazing proof points of that was that if you take children who are deaf, who can't hear, and you deny them sign language, so you don't give them any language input, which actually happened in the 70s, there was a movement to try to make them be able to read lips. And so you weren't, you were, that you were told not to

Starting point is 00:07:16 allow your children, not to sign to your children. The children themselves create a fully grammatical sign language with no input. So it looks like there's kind of like a language function that's built in where you will produce these fully grammatical languages. There's a variety of other proof points for this. And that that then allows the child to sort of bootstrap, you know, what do all of these words mean and then build out the language. So you can kind of think about it is there's certain settings for the grammar. Like, is it more like German or is it more like French? Because there's some grammatical differences. And if you, once you sort of figure that out, you can unlock the whole system. So she was working right up until the moment that she died. And I went to

Starting point is 00:07:59 graduate school. I studied under her. That was really mainly what I was working on was this concept of syntactic bootstrapping. And she was really, really amazing. And then right at the end of graduate school, I got sick as I was going out for my job talks, actually. And I ended up taking a year off. And then during that year was when I played poker and I lost touch with her, which was my fault, not hers. I was just ashamed that I had left graduate school. I felt like I had let her down. I had a whole big talk track happening for me about what a failure I was. And we reconnected a little over a decade before she died. And just accidentally, I saw her in a doctor's office, actually. And it was like no time had passed. And it's one of those amazing moments for me where I had this whole track about how

Starting point is 00:08:41 shame she was of me. And it turned out that she was just proud and sad that we hadn't been seeing each other. And from that moment on, we started basically having lunch literally every week, at least. And we just picked right back up where we came from. I found out that she was actually really proud of me. And she had been cheerleading me the whole time. And I got this person back who was this incredibly important figure in my life intellectually and also emotionally. And I'm very, very grateful for the last 10 years that I had with her. I was looking at an interview with her and she had this kind of impish charm. She is so impish.

Starting point is 00:09:18 She is so mischievous. Yeah, so funny and smart. I showed a picture of her, my daughter over Zoom yesterday, my daughter, Madeline is at college. And my daughter was like, that is one cool woman. Like you could just see, like she exuded attitude and fun. I mean, she had to clot and fight her way into a place in academics at the time. You know, there weren't a lot of women around.

Starting point is 00:09:41 And, you know, she literally, I mean, she was probably the smartest person in the room. And she had to be a research assistant in order to be able to do her work. And she just was like, I mean, she's just so funny. Just one of the funniest people ever. And just, you know, the thing I can say about her is as much as I loved her, she really loved me. And I'm really sad that we lost that time, which was because of my own, you know, just that my own feelings of shame about whatever, not having fulfilled. the things that I thought that people were expecting of me. And I'm so grateful for that day. I was

Starting point is 00:10:14 sitting in a waiting room. And there she was and went over to her. And, you know, it was, I mean, and this is one of the things about her. I mean, I think that there are people who might have been very irked, to say the least, that we had fallen out of touch after putting so much time into my education. And our relationship was quite close. And I think a lot of people could have really held that against me. And I walked over in the minute she saw me, it was just this huge smile on her face. And there was never one minute, not one. And when I visited her in the hospital a couple days before she died, we had talked about it a little bit before. But when we're in the hospital, I actually told her, I just said, you know, Lila, I lived with so much shame over that for 20 years. And I'm so sad.

Starting point is 00:10:57 Like, I'm just so sad that I missed that time and I'm so afraid that I disappointed you and that it wasn't okay. And she just said, not for a second should you ever think that. I have never done anything but love you. And I've never been anything but proud of you. And, you know, I mean, she was just that type of person, you know, and I just, I miss her every day. I really do. And I hope she would be really proud of what I'm doing now. I know, here's the thing. We were talking about, she was really encouraging me to go back and finish my dissertation. I've been talking about it for a little while. And she knew that the plans were afoot at the time that she passed. And as much as I really hope she's proud of this, I really hope she's proud somewhere to know that I've now enrolled back at Penn

Starting point is 00:11:40 and I'm finishing up. And on the days where I'm like, why am I doing this? It's always like, because I can just see the smile on Lila's face, you know? This is an amazing thing that we need to sort of explain to our listeners that basically here you are this kind of famous author who's written three, I think, big books and, you know, become kind of a very well-known speaker and expert on decision-making. And here you are in early middle age, going back to college to finish the five years of research that you did under Lila. Is that fair to say? Yeah. So the rules are, if you've been gone for too long, you have to a tiny bit start over, not all the way. So the way that graduate school, at least at Penn, the way the program works,

Starting point is 00:12:20 is that the first two years you're learning, you're doing seminars. And then, well, the first first two and a half years. And then the second semester of your third year, you would do something called qualifying exams, which would qualify you to be a PhD candidate. So that's essentially showing a command of the literature that you're working in, the space that you're working in. Then after that, that's when you can start to TA. Well, you're TA before that, but you can start to teach your own classes because you're considered qualified. And then you're putting together your dissertation for the last two years. So I was actually on my way to job talks. What that means is that I'd already done all of my research for my dissertation. It was ready to go. I just.

Starting point is 00:12:55 really needed to defend it. But I got sick. I got really sick. I ended up in the hospital for a couple weeks. And I needed to take time off. That's when I started playing poker so I didn't defend. So now you had to go to go. I mean, to go back to that. So you had what, it was something called gastroparaseous, which is some sort of disorder. Sorry, yeah, you can see my knowledge of medicine. Yeah. So it's some sort of disorder of the stomach, right? So you're in your, in your final period at the university. I'm literally about to go to NYU for a job talk to go. get a, hopefully get a tenure-track position. And so then, as I understand it, and so you were, you were a star student, right? You were a National Science Foundation fellow and the like,

Starting point is 00:13:34 you're applying for jobs to become a college professor. But you thought you were going to become a college professor. And then suddenly at the age of 26, you get sick and it kind of catapults you from one path into this whole new direction. Can you talk more about becoming a poker player and the sense of shame? Because this was not a, I mean, it was a slightly tawdry, and disrespectful profession in those days, right? If anyone even considered it a profession. So can you talk about that shift and the role also that your brother played in shifting the direction of your life away from this incipient academic career into a raffish poker career? Sure. So let me just say also about re-enrolling is they're not making me do the whole thing over again. So I'm writing the

Starting point is 00:14:20 dissertation as soon as I defend that, I'll be done. And I'm doing that with Phil Tellock. I don't know if you're familiar with super forecasting. He's amazing. He wrote a great book. And his wife, Barb Mellers, who's equally amazing. We should talk about super forecasting later because I know that. I'd love to because that's what my dissertation is on. We're actually working with novice forecasters, which is super fun trying to help them to

Starting point is 00:14:39 become better forecasters. It'll make no difference, Annie, because the expert forecasters are equally lousy. So the novices, the novices. Well, yeah, that's true. It turns out you can turn people who've never forecasted into really good forecasters pretty quickly. But we'll talk about that with giving them. handing them the right concepts.

Starting point is 00:14:56 It's funny because, I mean, Tel-Lock writes that basically the experts do less well than chimpanzees throwing darts. And so, so, yeah. Except for the super forecasters who do, who do better than CIA analysts. That's true. All right. So let's go back to, yeah, the dramatic shift at the age of 26. So I get sick.

Starting point is 00:15:14 I actually had, I had job talks lined up at a whole bunch of places. I think it was NYU Duke, University of Oregon, I think Cornell, Yeah, Texas, I think. Yeah, yeah. You know, so I was really on the tenure track path and I get sick. I end up in the hospital for a couple weeks. But I want to just explain to everybody that it's 1992, I think, something like that, 19902.

Starting point is 00:15:37 So it's hard to imagine because now we see poker on television all the time. It seems like, I mean, it's an odd thing to do, but certainly people know that you can do that for a living. And they think it's like a relatively respectable thing to do now, I think. But at this time, there was not poker on television. Obviously, there was an internet poker. So this was not anything that was in the realm of possibility for what somebody would consider doing for a profession. But I needed money.

Starting point is 00:16:05 So I didn't have my fellowship because I wasn't in school. I was taking time off. And I needed money. So my brother had gone to New York in the 80s in order to become a chess player. He wanted to be a grandmaster. So he was a master, but he wanted to be a grandmaster. So he was studying with someone there, deferred a year of college in order to do that.

Starting point is 00:16:26 And in that time, he started playing poker. He actually became really good at it. So there was like a whole underground poker scene in New York. He started winning a lot of money at that, actually made it to the final table of the World Series of poker at the age of 23. And so that was all happening sort of at the end of high school for me. And then also when I was in college in New York for four years, and I would sometimes go watch and play.

Starting point is 00:16:48 Certainly when I was in graduate school. And during graduate school, he would bring me out. out to watch him at the World Series of Poker, but it was boring. And so I asked him if I could play. And so I played a little recreationally. But that was it. So now, now all of a sudden, I'm like, oh, no, I don't have any money. And he suggested that I play poker in the meantime to make some money. And, you know, I understood enough about the game. I was better than the average bear just because there was somebody who was like a world champion, basically, who was related to me. And he helped me to sort of work through the game. And I started playing and I started winning right

Starting point is 00:17:19 away. And it was kind of the perfect thing for me to do at the time because I didn't know day to day like how I was going to feel. And so I needed something where it was like, make your own hours, which poker definitely is, where you weren't obligated to a boss. There was no like calling in sick or something like that. And I did really well. But like just so that people understand, like at that time, again, like it's not on television. I mean, people definitely think about this is something that the vice squad should be dealing with. So when I would tell people that I was playing poker, you know, it'd be kind of like, are you dealing drugs on the side also? But I think because I was a woman, a lot of times it would be, what does your husband do?

Starting point is 00:17:55 You know, because I think they assumed, like, I had a gambling addiction. And so my husband must be really rich. I think it's interesting. My husband was a house husband at the time, by the way. So I was actually making the money. But so it was just weird, right? And then they would often ask me if I had been to Gamblers Anonymous. That would also be a thing that they would ask.

Starting point is 00:18:14 So it wasn't, you know, and I try to explain to people, it's like investing. But I don't think, now I think that people sort of realize that, right, but at the time they didn't. And in a way, Annie, it seems to me that just looking back on your earlier book, Thinking in Betts and on this new book, Quit, that it was this amazing education for you in terms of learning to respect uncertainty, which is obviously one of the great themes, both in poker, but also in investing. And I wonder if you could talk a bit about that, about how you came to understand.

Starting point is 00:18:47 that it was kind of this perfect microcosm of life. You start to see just how complex and uncertain life and games like poker and investing are. I think what happened was that the first, I really started playing for real in like 94. And I would say that the first eight years, I was just trying to figure the game out, which is trying to sort of get your arms around the uncertainty, that really understanding, like, you have to get down to what do I have control over and what don't I control over and I have to accept the tremendous influence of luck. I have to accept the fact that I'm having to make these very high stakes decisions without being able to see my opponent's cards.

Starting point is 00:19:28 Like that's just, that's just the nature of the game is that you don't have very much information. You're having to build models and try to make these maps of, you know, mapping your behavior, William, onto like the cards that you might be holding, right? And it's very complex, right? And then there's also the issue of just like applying base rates to that problem, right? Understanding like how often do you get certain hands? How often does someone generally enter a pot? If I understand that you're going to enter the pot 25% of the time, then that tells me something about like likely what you have. Are you above the base rate?

Starting point is 00:20:03 Are you below the base rate? Like those kinds of questions so that you start to get some good anchor points for like making these forecasts. But then just be really accepting of the fact that I can get my money in the pot 98% advantage. And, you know, two percent of the time, that means I'm going to lose. And, like, you just have to be okay with that because you don't have control over that. You're going to observe it 2% in the time and that you have to not let that mess with you, which is actually quite a hard problem. So I was really trying to sort of tackle that for myself.

Starting point is 00:20:31 And then in 2002, this was right when poker was sort of coming on TV. In 2002, I got asked by someone named Roger Lowe, who at that time had a, he had founded a hedge fund called Parallax. And he wanted me, well, he actually wanted Eric Seidel to come and speak. to his traders, but Eric Seidel couldn't do it for whatever reason. So he asked me to do it. I was two weeks from having my fourth child. So I was very pregnant. None of my shoes fit. So I actually did not wear shoes when I gave this talk to these options traders. And that was that was the first moment where I really thought in a explicit way about the way that my

Starting point is 00:21:07 background in cognitive science and sort of really thinking about, remember, I was thinking about these mapping and uncertain systems, right? That's what I was thinking about. And I also had done a lot of work and just sort of general cognitive psychology, bias. I'd taken seminars from John Barron, who's one of the giants in that field. Thinking about the way that poker and cognitive science could have this very interesting conversation that then applies to kind of any type of decision making that you might be thinking about. And so Roger had asked me to speak specifically about how poker informs you're thinking about risk. And what I ended up doing was actually saying how uncertainty distort your risk attitudes. And particularly,

Starting point is 00:21:44 the way that we sort of, first of, first of all, process wins and losses in terms of how do we assign that, right? Do we assign that to skill elements or luck elements, which is actually really hard to do in retrospect, right, because you don't know for sure? And then how does the path that we're on distort our risk attitudes going forward? So this was very much like a collision of my background in cognitive psychology and the things that I had been thinking about in poker, which I think you can see expressed. I mean, I think that was the first time that I started writing Thinking and Betts because that is what Thinking and Betts ends up being about is that is that particular problem in large part. And then I just realized like, oh, I really like this conversation and I just

Starting point is 00:22:25 kept going at it, you know, and that was just sort of the start to really thinking about this explicitly. It's interesting how so often in life, it's these unexpected things that don't seem to have any relationship to each other that come together and somehow create something new and fresh, that it was your weird interest in cognitive bootstrapping in the acquisition of language and, you know, whether there's some grammar innate in the mind when we're born or something. And then that somehow leads you into poker kind of randomly. And then you sort of, you understand poker and I think also Lila had kind of taught you to think very scientifically in a way that very few poker players would.

Starting point is 00:23:08 So you're sort of bringing together these different strands, and then you stumble into the financial world. And so you're able to apply. Does that make any sense? There's something kind of weird and beautiful and sort of random and sort of lucky and sort of fated. Yeah, I mean, there's definitely a lot of luck. There's definitely a lot of randomness.

Starting point is 00:23:26 I mean, to harken back to David Epstein, you know, there's a lot of range. Yeah. And I think that, you know, one of the things that I think, when people look at my life, I mean, I think they tend to describe it as you just did, which is like, oh, a lot of random things that you were doing. But when I look back at it, I say, I have never done anything which wasn't pulling the exact same threat.

Starting point is 00:23:50 And that thread is, how are you learning? How are you making decisions? How are you closing feedback loops under uncertainty? Because that's the whole language problem, right? It's like closing the feedback loop in this incredibly uncertain system where it's just not clear. It's like I pointed a dog, am I talking about panting, barking, fur, a paw, the dog itself, an animal, a mammal, right? Like, thinking, sleeping. What on earth does that mean? And how does this little being actually manage to close those feedback loops, right? And it has to

Starting point is 00:24:28 do with constraints in the system that then becomes a big part of the way that I think about poker, which is how do you constrain the way that you're processing that world in order to avoid the mistakes that you might make in mapping, you know, an outcome to why did that outcome occur? Which I think is such a huge problem for us as decision makers, right? Like you lose on an investment. Was it like, was it just bad luck? Was your thesis wrong? Was some part of your thesis wrong?

Starting point is 00:24:59 What was the contribution of either one of those two things? and I think it's incredibly hard and left to our own devices, I think we do a very bad job of it. And so starting to think about those constraints, which is really the solution within the language space, and how do we take that type of solution and apply it to our own decision-making, to both say, which is this real, in the end, it's embracing the uncertainty.

Starting point is 00:25:21 It's saying, I'm not going to try to get to 100% certain because I think that's ridiculous to try to do that. We can't do that. And if that's our goal, we're going to be really bad decision-makers because we're not acknowledging the position that we're in as decision makers. So instead, what I have to do is embrace the uncertainty and also embrace the mindware that I came in with, right? Like, I just, there are biases that are innate to me. That's separate apart from the noise in the system, right?

Starting point is 00:25:46 The noise is the embracing of the uncertainty. And then I know that I'm going to be viewing the world in a biased way that's going to be relatively systematic. And so how can I create constraint that will then allow me to be a good decision maker within the environment that I have to make decisions? And I don't think that there's anything in my adult life that I've ever, I don't think I've thought about anything else. And I know it's like, you know, graduate school and language acquisition, how on earth could that possibly relate to poker? And how on earth could that that then relate to the books that I've written or the consulting that I've done or helping a company that's a SaaS startup to, you know, work through the stuff that they're doing. And whoa, isn't that a lot of different things?

Starting point is 00:26:25 But no, it's the exact same thing. I do the exact same thing. I just have had. been lucky enough because of weird stuff that's happened in my life to have been able to think about that thing as it applies to what look like very different problems that I think have really informed that in a good way. So, you know, in the end, I kind of look back and say, wow, that was really lucky that I got sick. It wasn't lucky that I lost two decades with Lila. That my fault, and had that not happened, that would, you know, I would not have reacted that way and done that. But in terms of everything else, it was incredibly lucky. Yeah, I remember Ed Thorpe once when I asked him how you approach life as a game.

Starting point is 00:27:06 He said, well, look, there's the stuff like your DNA that's just like the hand that you're dealt. And then there are the decisions you make about how to play it, like whether you get vaccinated, whether you have your annual checkup, whether you exercise, whether you eat well. It sounds so logical and obvious once you hear it, but it's not that obvious. Yeah, but then we don't. It's like we're so bad at it. Yeah. And so I wanted to ask you actually about someone whose name you mentioned, which in your world of poker, everyone will know.

Starting point is 00:27:34 But for many of our listeners, he won't be familiar, which is Eric Seidel. So because your brother had this extraordinary group of poker players around him in New York when you were coming up in the game. I met Eric Seidel when I was 16 years old. Amazing. So for people who don't know, I mean, Seidel, and I know so little about poker, I can't even tell you. I'm embarrassed to admit. but he, as I understand it, won nine worlds series of poker bracelets and made something like... He's ridiculous.

Starting point is 00:28:01 Yeah, he made something like $40 million as a player so far. And was also a stock exchange trader before he became a professional poker player. So you've written before that he was in some ways the person who taught you what it means to strive to be a rational thinker. And you've also said that you have a crush on his intellect. So I wondered if you could explain to us what you learned. in this sort of unlikely field about how to think more rationally. What did Seidel teach you? So Eric Seidel is an amazing poker player, like really incredible.

Starting point is 00:28:36 And, you know, one of the things I think that people need to realize that's so amazing about him is, first of all, there's a lot of short-term luck in poker. So there are people who come and they have like a great year, you know, and then they just sort of never do well after that, for example. And, you know, partly I think because people figure them out and they don't have a strategy to figure them out, you know, back out, I guess. And you see that in a lot of sports. Someone comes in and does something really unusual. At first, they do really well.

Starting point is 00:29:08 And then their opponents figure them out. And if they don't have a response, it's, you know, they're not going to do particularly well. But also the game itself has changed. Right. So there's lots of people who will have a great year. And then it turns out they just got lucky. but even if they didn't get lucky and they really were great for that time, as the game changes, as new people come in, are they able to adjust and do well in those new environments?

Starting point is 00:29:34 And that's something that we've seen, you know, particularly with the introduction of some deep learning, you know, the strategy that used to be considered correct in back and for example, or chess, what we're finding is that AIs are telling you to do very different things, generally to be more aggressive. And then as the new generation comes in and they've sort of metabolized, those lessons, are you as someone who's been doing this for a very long time, able to adjust back and change your game in response, which is very difficult to do? And so here you have Eric Seidel who's been doing this now for four decades. And it's just year after year after year, one of the top tennis, one of the top poker players. And I remember you telling a story about

Starting point is 00:30:15 going to him and complaining about some game. I think that the term you used was a bad beat where you just sort of got unlucky. And how did he respond when you complained about your bad luck? Yeah, so this is one of the things that I think makes him so great, which is, so it's really, you know, poker is a really tough environment because there is a lot of luck. And you are going to have situations where you are absolutely a gigantic favor and you're going to lose.

Starting point is 00:30:45 And by the way, sometimes you're going to think that you got unlucky, but you actually didn't. But that's a whole, I mean, this is sort of the issue of what he was trying to get at. So I came to him. This was like, this was like one of the first final tables that I ever made. And I remember I raised with two jacks and this guy, Gus, who was from Costa Rica, this is the things I remember about him, moved all of his chips in. And this was either, if I win the hand here, I'm going to be the chip leader in the tournament with six people left. And if I lose, I'm going to be out six.

Starting point is 00:31:16 So this is a pretty big swing here. And so he moves all his chips in, and I thought about it. I really thought about it for a long time because Jacks is like sort of a middle of, you know, middle of the road hand. And I ended up calling. I really thought, I really just decided that he didn't have a great hand. And he had two nines. So just to set the stage, I'm going to win that pot around 82% of the time, just shy of that. And he won the hand.

Starting point is 00:31:41 And this was the biggest stage I'd ever been on. It was the most money I had ever played for. I mean, this was a really big deal. You know, had I lost hands like that. that before, sure, but never, never when it mattered so much. So I walked away from that table and I was really, just really upset and I went to him, you know, and I was just complaining to him. And I was like, can you believe this? Like, I made such a great call and this idiot moved in with two nines and blah, blah, blah, blah, you know, is this whole thing about how unlucky I was. And he just stopped me and said,

Starting point is 00:32:11 is there a question here? And, you know, I was taking aback because like you would expect most people would be like, I'm so sorry, that's so unlucky. I feel so bad for you. It really mattered to you. Like, I mean, I think I was like 20, I was 26 or 27. I mean, I was young, you know, and oh, that's so, you know, and that's normally what you would expect. But he was just like, is there a question?

Starting point is 00:32:32 And I just said it was like, what? He goes, I don't want to hear about it if there's not a question. Like, I don't care that you got unlucky. I get unlucky too. And I have to deal with losing with two jacks against two nines all the time also. I certainly don't want to take on your emotional trash about it myself. And what's the point of talking about it? You made a great call and lost.

Starting point is 00:32:51 Who cares? Would you have changed anything about what you did? Do you think you got the read wrong? It sounds to me like you did everything right. So why are we even talking about this? You know, and it, you know, it's like, ugh, right? And at first I was like really mad. And then I realized, no, he's totally right.

Starting point is 00:33:11 Like, I mean, this is the thing. It's like if it really was just bad luck, who cares? This is about embracing. that uncertainty, right? If you have a question, you know, and he said that to me, if you have a question, if you think maybe you shouldn't have called there, or maybe you shouldn't have opened, or maybe you should have opened for more, or maybe you should have moved in the, maybe you should have done something different, then I will talk to you about that all day. But if all you're talking about is that the poker gods came down and were mean to you, I don't care because

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Starting point is 00:37:53 All right. Back to the show. It's a beautiful story. There's great depth in that. I wanted to pick up on one thing that you mentioned there where I think you said there was an 82% probability that you were going to win that hand if I heard correctly. 81.5%. And I've interviewed a lot of great investors over the years, like people like Charlie Munger.

Starting point is 00:38:14 and Ed Thorpe and Howard Marks and Bill Miller, Joe Greenback, these guys who just think constantly in terms of probabilities, they're always looking at the future as a distribution of probabilities and they're assigning sort of odds to those different probabilities. And I once asked Howard Marks if it was possible for an investor like me who's not really wired that way to learn to think probabilistically. And I was kind of disappointed. He was like, yeah, no, probably not. And I was interested in this whole question of, hey, how important it is to learn. to think in terms of probabilities and B, whether you actually think that is something that we can become much better at? Yes, I think I'm going to disagree with Howard Marks here. So I think I'm

Starting point is 00:38:55 going to disagree on two counts. And by the way, I love Howard Marks. He's super, super smart. And actually, he may not disagree with me when I phrase it this way. And he may just admit me that I could never learn to think so. No, no. But I think, no, because Howard and I have actually talked about this. And I think here he's going to agree with me because I'm going to reframe it. And I think with the reframe, he's going to be on the same page as me. Okay, here's thing number one. You are thinking probabilistically. So I think this is really important to understand. So I actually had someone recently say to me like, oh, you're talking about probabilities and expected value and those kinds of things, but that doesn't apply to merit because that's like a one-time decision where you just got to

Starting point is 00:39:33 go with your heart or whatever. And my response was, oh, do you just walk out onto the street and marry someone at random? You know, and of course the answer is no. And it's because you, are making a forecast of the future. You are saying, what have I learned from people that I dated? What what is my model of myself? What is my model of this person? And yeah, just because you're not going to repeat the decision over and over again, obviously you're still doing a forecast. You're still saying, I think my expected value is higher if I marry this person, given the constraints of the time that I have, maybe your biological clock, so and so forth, what your values are, you know, in comparison to continuing to search for other people. And also, even if you, even if you, even if, sorry, Annie,

Starting point is 00:40:13 to cut you off, even if you look at the, you know, I had a close relative who was a serial philandra who got himself in trouble. And he was playing the odds. He's like, what are the odds that I'm going to get caught and this is going to ruin my family? Well, yes, that would be a good negative example of thinking probabilistically, but exactly right. And I remember warning him as a kid and saying, look, you're going to get caught if you do it enough time. And he was like, no, no, no, no. And then he got caught and it ruined his family. Right. And hopefully you learn from that. that. So that's the thing is like, even if, even if you don't think you're doing it explicitly, literally every single decision you make is probabilistic. It's because it's a forecast.

Starting point is 00:40:55 It's a forecast made under conditions where you don't have all the facts. You generally know very little in comparison to all there is to be known. And there's going to be the influence of luck on the outcome. Right. And that's true like, look, when you decide a particular route that you're going to take to work, it's a forecast. I think this is going to get me to work. in the time that it's going to take me to get there. Or maybe you value the scenic route. And so you're saying this is more likely to let me see lots of scenery in comparison with when I need to be there.

Starting point is 00:41:24 And then if there's an accident on the road and you decide to exit to take a different route, that's an expected value calculation. You are thinking probabilistically. If I exit, even though normally this would take longer, there's a higher probability I'm going to get there on time. So I think that's number one, is that we have to reject the idea that if you're not doing it explicitly, that you aren't thinking

Starting point is 00:41:48 probabilistically, because every decision is a probabilistic decision just by its nature, because the world is probabilistic. That is how we decide. So that's the first thing that I just want to say there. Now, the act of trying to make these things explicit will make you better at it because what it will start to do is allow you to create good feedback loops. Remember, this is my obsession. How do we start to create good feedback loops? Well, so I'll give you an example from a company that I work with that had this implicit, explicit thing. So I'm a special partner focused on decision science at first round capital partners. So there is a seed stage company. So when I first started working with them, there were certain things about their voting process that we decided that we really should change to

Starting point is 00:42:37 fit with what we know about the science of decision making. And one of them was to include some very explicit forecasts in what they were in their decision. So one of the forecasts that we wanted to include was, what's the probability that the company that you're currently considering is going to successfully raise a series A? Now, the pushback that I got from the partners was, well, we don't even think about that because what we care about is, is it going to exit for, you know, a billion dollars. And so I rolled it back. Again, this isn't implicit in the decision and should we make it explicit? Because I felt it was implicit in the decision. And the way that I got to that was to say to them, well, once you funded a company at Seed,

Starting point is 00:43:14 have you ever had a company that was a fund returner that didn't successfully fund at Series A? And they said, no, we have not. And I said, then it's in the decision. It's implied that one of the predictions that you're making when you decide to invest, this is company will successfully above a certain rate, right, funded Series A. So we now made that an explicit part of the decision process. So they have to make that forecast. And now what that does is it gets them to think about things that are actually part of the decision in a probabilistic way.

Starting point is 00:43:49 And we can now close those feedback loops because you do that enough times. You can start to see, well, how good are a predictor? Are you better than random? Knowing which company when it comes in the door is going to fund at the next round or the round after that. And we've actually started to be able to close those feedback loops. They are better than random. They are quite good at it. It maps to experience.

Starting point is 00:44:09 The more experienced you are, the better you are at predicting that. And that does great things for the junior partners because they see that the senior partners are better at this prediction. They start to try to understand their rationale for that, which then improves their ability to forecast those things. And what happens is they get better. Now, are they perfect at it? Of course not. They're not perfect at it. But they're better than if you just threw darts.

Starting point is 00:44:33 And that is, as you know, like, this is where we start to get those edges that we can grind over and over and over again in investing. So I just don't accept it. I say, you are thinking probabilistically. So let's start making explicit. And if you start to do that explicitly, you will get better. Will you be perfect? No. Does some people think this way more naturally than other people in an explicit way?

Starting point is 00:44:57 Sure. But every little bit that you improve is going to really matter to you. for your outcomes. How transferable have you found the skills that you developed in poker when it comes to the investing world? How much is it the same thing and how much is it actually a different type of game? Yeah, so this actually gets into a little bit of what my doctoral research is about. So there's a whole history of question about transfer of training from one domain to another, and the history is pretty dismal. It actually starts way back in the 1900, early 1900s,

Starting point is 00:45:31 where the idea around education was like, if I teach you, if you do hard math problems like trigonometry, it will help you to be a better thinker in all other domains. And it turns out that that actually isn't true. But there's some work that sort of begins with Fong and Nisbet on a very specific thing that does transfer, which is statistical concepts. So something like the law of large numbers as an example. So if I teach you about the law, law of large numbers as applied to a particular domain, I can get very far transfer where you will now sort of have this concept in your head. You'll understand that large numbers matter and it will transfer into other domains. So that's the thing that I think was so helpful for me in poker was there's a whole bunch

Starting point is 00:46:13 of statistical concepts, which also I had learned in cognitive psychology, right, because you're having to work with data all the time. And so you're thinking in that way already. And then in poker, you have to start to think about things like base rates, for example. And a base rate is just how often does something happen in a situation similar to the one that I'm currently considering? So that's where I say like the average player will play 25% of their two card combinations and hold them, right? So that helps me with a starting point. And that concept of base rates actually transfers very well.

Starting point is 00:46:43 The law of large numbers, which becomes very important in poker, I don't want to think about what happened on a particular hand. I need enough reps to be able to say something about it. Those types of things, the way that you sort of view the world through these kind of statistical mental models and statistical concepts, transfers really, really well. So I think that that's actually been incredibly helpful to me because everything looks a little poker-like when you start to think that way. And then the other thing is that I just think that depending on the type of investing, it's actually relatively near transfer. So we think about near transfer and far transfer,

Starting point is 00:47:17 which is just how easily can you map one domain onto another. And if you take something like poker versus and options trading. Now you're talking about relatively near transfer. They're very, very, very similar to each other. So in fact, as I'm sure you're aware, there are large options trading firms like Susquehanna International Group that actually force their traders to play poker

Starting point is 00:47:40 because those are so similar. Now, obviously, when you get into something like seed stage venture capital, you're starting to get into a much further domain. But these statistical concepts still apply. And so I have found it to be incredibly helpful. It's just a matter of not thinking about it as analogical transfer. Like you're trying to take analogies from poker and lay them onto other areas, which I don't

Starting point is 00:48:04 think transfers particularly well. That doesn't work very well. But thinking more about what are those sort of statistical lessons and underpinnings and concepts that you would then transfer to anything that you're thinking about. It's really striking to me how many of the great investors have been very serious game players. And I'm thinking, I remember Sir John Templeton told me once that he put himself through college during the Great Depression with his winnings from poker. I mean, Ed Thorpe, as you just mentioned, right? Brilliant gambler who figured out how to beat the casino at Blackjack and then and then back around and even roulette, which is crazy.

Starting point is 00:48:39 Yes. Buffett and Munger passionate about Bridge. I remember Mario Gubelli once telling me that when he was 11 years old, he was a caddy at a golf club and he made money beating people at cards because they assumed an 11. 11-year-old wouldn't know what he was doing. And actually, Peter Lynch once told me, over 20 years ago, I said to him, you know, what books should we be reading about investing? And he said to me, well, actually learning to play poker or bridge is way more helpful because it teaches you to deal with probabilities. Because you have to feel it. Say more about that. So it's one thing to talk about if you have a 60, 40 shot that 40% of the time you're going to observe a bad outcome.

Starting point is 00:49:22 And to understand that conceptually is one thing. To experience it is another. I think that this is one of the things that we need to understand is that there's a whole bunch of things that we think we know because we understand them kind of from a sort of, if I borrow from Daniel Kahneman, like there's system one and system two, right? There's the more deliberative part of our brain. That's kind of more of what we think about thinking about things. And then there's most of the rest of our thinking, which is just, you know, automatic or reflexive. And so there's one thing for me to like conceptually get that 40% of the time I'm going to, I'm going to observe a bad outcome. But if I can grind a dollar, it's, you know, 60, 40, I'm obviously going to make a ton of money, right?

Starting point is 00:50:04 Like I'll take three to two on an even, you know, dollar to dollar every single time that I can. So I can know that intellectually. but when you experience betting that dollar even money where you're three to two favor and you lose, that is a whole different animal. It really is. And you can see with amateur players and in investors all the time, this, you know, where they say like, well, you know, any two cards can win, but not enough of the time. They forget that part.

Starting point is 00:50:34 They'll play like, they'll have some sort of hand that they fold and then the rest of the cards will come out and they would have won. and it's so incredibly painful for them that they'll start playing hands till the end because that worry about like, but what if this is the one that wins? It's just, it's so awful for them to experience that situation that they won't let go of the hand because of it. Because that feeling of when you actually lose, it's just so, it's so hard. So when you play poker a lot, you just become very sanguine about that stuff, right? You just sort of learn like, well, I was a 60-40 favorite.

Starting point is 00:51:05 What was I going to do? Kind of in the same sense of what Eric, that's what Eric was. trying to get across to me. You were going to win the hand 81 and a half percent of the time. Like, what are you talking about? Go play it again. Would you call again? Would you play the hand exactly the same way and run it a hundred times? Of course. So why are you worried about this one time? And that's the thing that I think that games playing gets for you separate and apart from just sort of like starting to understand this strategy and really starting to figure out how do I model people in these uncertain systems. Poker is one long game. And if you don't have the

Starting point is 00:51:39 reps, you're never going to be able to get that under your belt and try to find a way to success in that environment. I think it's just really hard. I remember also Ed Thorpe saying to me, as far as gambling is concerned, if I don't have an edge, I don't play. And I said to him at one point, well, so how can I tell if I have an edge when it comes to investing? And that there's, that's the whole thing. Yeah. And he looks at me and he says, unless you have a rational reason to believe you have an edge, then you probably don't. And you just sort of hear that and you're like, oh, God. And so there's that sort of discipline as well that I really learned from Ed Sork. I don't apply it myself, but I learned it, which is simply not to play games that you're not equipped to win.

Starting point is 00:52:19 I would actually amend what Ed Thorpe said about unless you have a rational reason to win, that you have an edge. So first of all, I think we're very good at fooling ourselves into believing that we have a rational reason that we have an edge. And I think that that's particularly so when we're in a situation where the thesis would affirm other things that we're, we already believe about the world. I think it's particularly so when we're already in the investment. So one of the things that we need to realize is that every day that we wake up and we're looking at our portfolio is a day that we could sell everything in our portfolio, right? And so the decision not to sell is saying, I believe I still have an edge going forward. And but one of the things

Starting point is 00:53:00 to understand is that once we're on a path, particularly if we're in the losses, right? If we have a loss on paper, we're going to do all sorts of ways to convince ourselves. We have a rational reason that we have an edge going forward. So one of the things that we need to do is like set up structures around us that will allow us, first of all, to be better at those, are we really being rational and starting? But more importantly, because the starting decision is always uncertain, is to say, as we discover new information after we've started, are we stopping? Right. Are we figuring out when we should stop because it turns out that we're very, very dense when it comes to actually paying attention to the signals after we've started something that we ought to stop it.

Starting point is 00:53:43 And that's where we get particularly irrational. And I think that that's just something really incredibly important to understand. So there's two pieces there, right? If you don't understand the game, don't play. So I completely agree with that. There's a reason why I never owned a single coin. because I didn't understand it. I didn't want to understand it at a point in my life where I was like, you know what? I don't really need to sit down and like research Bitcoin and NFTs. I just, I don't have the energy for it.

Starting point is 00:54:13 Like I don't want to turn my attention to that. And so I don't understand it, so I'm not going to play it. So I never invested in it just because I didn't understand it. But then what we also need to understand is that let's say that I, you know, I was in it, that one of the arguments that I kept hearing as an example for Bitcoin, was that it was going to be uncorrelated with inflation. Okay, so look, I don't know from anything. That seems like a reasonable thesis.

Starting point is 00:54:37 We haven't experienced any inflation. So you probably have a rational reason that that you have an edge there because of that piece of the puzzle, that it's going to be uncorrelated. So it will act somewhat as a hedge against inflation. And who am I to argue with that? And by the way, who are you to argue with that because that's a forecast and we haven't experienced inflation yet, right? But the question is, what do you do when it turns out it's not.

Starting point is 00:54:59 uncorrelated. That's the big question. And William, I mean, that's what I would ask you. Were people selling when they figured out it wasn't correlated, that it was very much correlated with inflation? And the answer for most people is no. And so that's where we need to start thinking about, like, that's where that you better have a rational reason and behave rationally to those signals, I think comes into even much more play is post decision. So you describe in the book quit a very valuable, tool, which you call kill criteria, which obviously relates to what we're discussing here, where you develop in advance a set of kill criteria for when to cut your losses, say,

Starting point is 00:55:39 can you talk more about this and how we should do it? Like, let's say we're about to buy a stock or we're about to buy a fund or we're about to buy a cryptocurrency. Can you take us through the process of laying out kill criteria, making what you call a pre-commitment contract so that you actually know what you're going to do when things start to go horribly wrong? So here's what we need to realize about these decisions about stopping. I think that we, particularly for investors, we get lots and lots of focus on the starting question.

Starting point is 00:56:11 What are you buying? What thesis are you deciding that you actually want to trade? What positions do you want to put on? But we need to get a lot more focus on the selling side. And I think that one of the reasons why we don't focus on it so much is that we have an intuition that if we have a particular thesis that implies certain things about, say, the fundamentals, What are the fundamentals going to look like in the future? That when those fundamentals move against us, that obviously we're going to take risk off.

Starting point is 00:56:35 And I think that that's true, whether it's investing or anything else, right? Like we think if we run a marathon and we break our ankle, we're not going to run anymore or our leg. If we're going up a mountain and a snowstorm comes in or the fog rolls in, we're going to turn around. If we have a business and things just start going to crap, that obviously we're going to do something about it. And the fact is that like just this decades and decades and decades of research shows that we don't. We're not very good at paying attention to those signals when they occur. So like, you know, with the Bitcoin example, you know, if you're investing in that, let's say in part or maybe in whole, let's say you're the main part of your thesis is I'm using this as a hedge against inflation because it's not going to be correlated with inflation. Yeah, or financial chaos in general.

Starting point is 00:57:19 If the financial system starts to melt down and stocks start to melt down, it's not going to be correlated with stocks. it's going to be a hedge. And then suddenly everything falls apart. And you're like, oh, no, this is falling too. This is falling too. I think that because that's part of our thesis, right? We assume that just because it's part of our thesis that when those things occur in the future, that would be a signal that maybe the thesis wasn't on point, that will react

Starting point is 00:57:44 to those in a rational way, which would be to take the risk off. That is what our intuition is. But again, decades and decades and decades of science tells us that that is not what we do. When, as you say, when financial chaos occurs and things are melting down, Bitcoin melts down too. Do people then now no longer become Bitcoin believers? That's the question. And I think that we've seen, no, no, that's not what happens at all. I think it's a good example of it. Okay, so the question is then, so how do we actually solve for this problem, right? Because if we know that we're not going to be good at paying attention to the signals when they happen, right, which is so bad because the option to quit is

Starting point is 00:58:22 so incredibly valuable because when you learn new information after you've started something, the option to quit is what lets you do something about it. Imagine if you didn't have that option. Imagine if when you bought something, you had to hold it for the rest of your life. Oh, my God, nightmare, right? Okay. So what we need to do then is say, if we can't rely on ourselves to react in a rational way to the signals when they occur, what we need to do then is do that work in advance. So this is kill criteria. So I've done this work with PMs, and basically what we do is we say, look, it's not enough for you to write down what your thesis is, which is worth that you need to do. So you have to do that quant work.

Starting point is 00:59:04 You have to get the analyst, the quant work, model it, make sure we know what your thesis is. And that's fine, but it's not enough. What you have to then do is say, what could I see in the future that would make me say that my thesis was wrong? So, for example, if you have some sort of idea about correlation, and then you see the world unfold, and it turns out that it is correlated, it's not uncorrelated. That would be a good example of a kill criteria. So what I could do is I could have done this, right, because I didn't really understand Bitcoin. What I could have done in order to deal with the fact that I didn't know much about it was to say,

Starting point is 00:59:46 I'm going to buy Bitcoin. But the reason I'm buying it is because people say that it's a good hedge against inflation or general financial case. So as inflation goes up, I'm going to see if Bitcoin is going down. And I would have some parameters, right, to try to make sure it wasn't just noise. And I would say, so if this happens, right, if I see that it's going down in a way that's very much correlated like at one with what's happening with inflation, this is how long I will tolerate that situation for. So maybe I would tolerate it for like one point, you know, one and a half points of inflation or something like that. And then I'll sell. And so I just, I write down in advance.

Starting point is 01:00:22 what I'm going to do. Now, I think that people really think it's a distinction without a difference. Because it's clearly like if you have a thesis, those moves against you are implied in the thesis. So why wouldn't you pay attention to them? And you just got to trust me on this one, you're not going to. So write it down in advance. And it's what I call kill criteria. Well, I think one of the really important insights is that when you're actually in the heat of the moment, your emotions kind of go, hey, why, and your rationality just isn't great. And one of the things I love, when you wrote about poker is talking about different states in which you saw people making bad decisions, whether they were drunk or tired or whatever. And you said at one point, you knew that,

Starting point is 01:01:03 I can't remember which of your books this was in, that you knew that you played best in six to eight hour sessions. And so you had to set out the rules beforehand, rather than waiting until, as Daniel Conneman would say, until you're in it. And I think that's actually such an important insight that we need to recognize before we're in the muck, in the extreme situation. Yeah, because like who's making good decisions right now? Yeah. Like the world is melting down. My friend Ken Schubenstein, who I write about in Richel, Wiser Happier, is very, very smart, former hedge fund manager and private equity manager who's now become a neurologist. So he's an expert on the brain. Oh, I love that. Yeah, he's an amazing guy. And one of the things that,

Starting point is 01:01:47 that he developed because he studied so much scientific literature, including addiction literature, is he said, okay, so I know that I'm going to behave suboptimally when I'm hungry, angry, lonely, tired, in pain, stressed. So he has this mnemonic halt PS to remind him of those states. And he said to me, I write about this a bit in the book, that he said to me, in the early days of COVID when he was treating patients on ventilators, he could see, for example, when he was really stressed or when he was scared, he had a four-day-old newborn child and he moved into a hotel room to keep his child and his wife safe. And he said his equipment hurt and his back hurt. He had a back injury. And so he had to just be doubly careful because he knew in advance that those were

Starting point is 01:02:34 states in which he was going to behave suboptimally. Right. Yeah. So that's exactly. And then put on top of it, there are particular states where you're going to feel suboptimally that have to do with your own, like, physical state, like you're tired, you're stressed, whatever. But then there are also cognitive states where you're going to behave suboptimally. And the particular cognitive state where you're really going to behave suboptimally is when you're in the losses. So the reason why I'm calling that a cognitive state is that it's not objectively true. So being in the losses, which means that you have some sort of loss on a mental account,

Starting point is 01:03:11 it lines up somewhat with what your balance sheet really looks like, but not exactly. So it's true that if you bought a stock at 50 and it's trading at 40, you're both cognitively in the losses and you're in the losses in terms of your balance sheet, right? You're carrying an unrealized loss. But what's interesting is if you bought a stock at 50 that went to 100 and is now trading at 75, you are in the gains in terms of your balance sheet, but you're in the losses cognitively. Because you were at 100, you're now at 75. So you're experiencing that in the losses. Another example would be if you're running America, and you've run 12 miles of the marathon, you're like technically in the gains in the sense

Starting point is 01:03:51 of like you've run 12 miles more than zero, but you're cognitively in the losses because you're short the finish line by 14 miles plus, right? So that's in the losses. So this, this in particular, the 68 hours was dealing with the physical issue, but then I also had a loss limit to deal with the cognitive issue, which is that when you're in the losses, you're going to be a terrible decision maker. And the reason that you're going to be a terrible decision maker is separate apart from it's going to cause you to be emotional is that you're going to want to get your money back. And this is a really big problem for investors, right? Like you start down a path, it starts to lose. And you don't want to sell because you can't get your money back. That's the moment that you go from

Starting point is 01:04:35 a loss on paper to a sure loss. It's when it becomes a realized loss. And that is a moment that we do not like. And so we will come up with all sorts of reasons to think we're being rational in continuing on when we're being completely irrational because we're just trying to protect ourselves from having that moment of having to take the sure loss. This is what Daniel Conneman calls sure loss aversion. And it's related to obviously to sunk cost. And we better set up some things in advance that stop us from doing that. Now, again, in poker, there were things I had like if good bad players got up and good players sat down instead. So that would have something a little more to do with the fundamentals. But I also just had simple loss limits in place just because

Starting point is 01:05:23 I recognize like I'm probably going to be a bad judge of like who's playing well and who's not. When I'm personally losing, I'm going to be terrible at that. And those were things that I just thought about in advance to try to deal with these issues. So like many people, I'm nursing some losses on individual stocks at the moment. And the most comically awful of them is is Alibaba, this Chinese company, which I looked at this morning and I'm down 59% in it, I think probably a year or something. And I bought this after having this amazing kind of Zoom call with Charlie Munger and Lou Simpson and various other great investors. And so, you know, you feel like really special. You're like, okay, so wait, I'm talking to some of the

Starting point is 01:06:04 greatest investors of all time about why they love Alibaba and why it's so cheap. And so, you know, I suffer from authority bias, right? So I sort of fall in. in love with the ideas of these brilliant people I talk to and I have access to brilliant minds. And so then I'm like, wow, I feel so special. I've got this insight into what they're doing. And so then I buy this stuff occasionally. I very rarely buy an individual stock, but I own like about three of them. And then it's down 59%.

Starting point is 01:06:31 And so I'm just sort of sitting there watching it kind of in a sort of somewhat paralyzed, somewhat amused, somewhat fascinated way. And I wondered if you could just talk about some of the, the cognitive biases that are kicking in here, right? So there's loss aversion or sure loss aversion that you just talked about. Talk a bit more about sunk cost effect and status quo bias and things like that. Because it's kind of this lollipaloozer of idiotic cognitive biases that are making it impossible for me to make a good decision.

Starting point is 01:07:04 So I think people are familiar with loss aversion. We don't like to start things that carry with them a chance of loss, even if we're winning to the decision, right? So we'll prefer like some sort of low volatility but not particularly valuable investment over one that's higher volatility but more valuable because the higher volatility investment obviously carries with it a higher chance that you'll lose and probably a larger possible loss. So that's a problem with starting. Sure loss aversion on the other hand is when you already have a loss on the books or even

Starting point is 01:07:32 a cognitive loss on the books, right? Like it was trading at one level and now it's trading lower. We don't like to sell. In other words, this becomes loss aversion. stops you from starting. Sure loss aversion stops you from stopping. In other words, we won't sell because we already have the loss on the books. So sure loss aversion is related. It plays with sunk cost effect, which is simply that we take into account what we've already spent on an endeavor, time, attention, money on whether we should continue and spend more, in part because we fear

Starting point is 01:08:07 that if we don't, we'll have wasted what we already spent. We don't want to do that. And also in part because we feel like we want to get our money back, basically, or our time back. And if we exit, that's the moment that we can no longer do that. But as long as we continue, we could recover the cause. Of course, this is irrational because what matters is the next dollar that you spend worthwhile, not did you already spend a dollar? We shouldn't care. So if you're holding a stock at 40, that's the same thing, less transaction costs,

Starting point is 01:08:40 as saying, I'm willing to buy this stock at 40, right? But what happens is that even stocks that you wouldn't buy at 40 today, you'll hold because you've already lost on the position to date, and you're trying to get that back. That's an error in the way that we do mental accounting because we don't think about it as fungible across a portfolio. So that's the sunk cost effect that stops us from stopping, rather. Then bring loss aversion, again, as opposed to sure loss of aversion,

Starting point is 01:09:10 back into the equation with this stopping us from starting that loss aversion does, because when we quit, it's usually because we're considering starting something new. So what ends up happening is that we have this very strong preference for the status quo, whether it's the job you're already in or an investment that you're already holding, a relationship that you're already in, a project you're already doing, a product you're already developing, whatever, a route that you already take to work. we have a preference for sticking with the status quo. And partly, that's because we're much more tolerant of the possibility of bad outcomes

Starting point is 01:09:47 that come from a status quo choice than we are from switching to something new. And that's because loss aversion gets recruited for things we're thinking about starting. And we don't think that sticking this, we don't think about sticking with the status quo as starting. Right. So when we hold on to a stock each day, we don't think about that as buying a new. It's just what we're already doing, right? It's not sort of, this also goes along with something called omission, co-mission bias, right? Like we think about switching as making a decision, the commission, and sticking is an omission,

Starting point is 01:10:21 a failure to act. And so what happens is that you'll hear people say, like, you'll say, like, why aren't you switching? And they'll say, well, what if that turns out badly? Even in cases where they already know that the thing they're doing is turning out badly. So I've had this happen like I had a conversation with this woman, Dr. Sarah Olsen-Martinez, who was in a job. She really hated. She was an ER doc, but also a hospital administrator. And she had really grown to, she was very miserable in the job for a variety of reasons. Many of them had to do with the administrative work coming home with her and interfering with her relationship with her children. And she had another job offer. And she was really having trouble deciding whether to switch or not. Should I quit this job I have and go to this new job, which was going to be working for an insurance company. So she described to me how incredibly miserable she was in her work. And I was a little confused as to why we were having this conversation, why she was seeking my advice. And so I said to her,

Starting point is 01:11:12 well, I just want to understand like, what's the hang up here? Like, why are you thinking that you don't want to switch? And she said, because what if I go to the new job and I don't like it? And it's awful. So I said, okay. So here's loss aversion, right? We can say this. I don't, I don't want to go start this thing because what if it turns out poorly? That's very classic loss version, but it obviously wasn't being recruited for the status quo for the things she was already doing. So I just said to her, well, it's a year from now you stay in the job you're in. What's the probability you're happy? And she said, zero percent. She'd had enough experience to say that with confidence. So I said, okay, if you switch to the new job, it's a year from now. What's the probability

Starting point is 01:11:49 you're happy? So I don't know, that's kind of hard, but probably 50-50. And I just said, okay, so would you rather have a zero percent chance of happiness or a 50 percent chance of happiness? And then she got it and she switched, but she was so concerned about the 50% chance of being unhappy that she had been having a terrible time trying to decide whether to switch. So that's a whole bunch of things. That's loss aversion, omission, co-mission bias, status quo bias, and also something called ambiguity aversion that has to do with fear of the unknown, which you could also kind of see in that decision-making. And then we also have the issue, which I think is really important for investors,

Starting point is 01:12:25 of something called endowment, we value things we own much more than we value things that we don't own. And it's not just like ownership over investments. Like we actually own the stock, right? Or we own the bond or whatever. We own the option. But it's also our ideas. And every time we invest, we have ownership over our thesis. And here's the interesting thing is that when the thing that we're doing, is out of consensus. This is when it gets really bad. So when we think about these issues of sunk cost and sure loss aversion and the way our identity gets wrapped up in things and the way we have ownership over things and the way

Starting point is 01:13:11 that that affects our inability to stop, you have to put a big, huge, big, huge blinking warning sign when the thing we're doing is out of consensus. So like, let me, so William, I assume that when you grew up, you thought Pluto was a planet. Yeah, if I cared about it. Yeah, I cared more about something. But literally did everybody else think that too. Yeah. So when there was new data that came in where the scientists said, oh, by the way, it's not a planet, it's some other thing. Did you care? Did you change your mind? Did you switch your belief? Yeah, I looked at it and I'm like, yeah, okay. Yeah, I didn't care enough to challenge the belief, right? Right. And the reason is that it wasn't, it wasn't part of you

Starting point is 01:13:51 because it was a consensus belief. But when we start to do things that are out of consensus, when we get signals from the world that what we believe to be true isn't correct, then it becomes very hard to change our mind. Because we feel much more ownership over those things that are different than everybody else. Our identity is much more wrapped up into things that are different than everybody out. So there's this wonderful study that demonstrates this from John Boucher's and Katie Milkman, Kaye Milkman of the Wharton School,

Starting point is 01:14:19 where they just looked at stock analysts and they looked at like 6,000 forecasts or something that that was a lot of forecasts. And there were some forecasts that were completely in the mainstream where all the analysts agreed, these were earnings projections. So everybody agreed on the earnings projections for, say, the next quarter. But then sometimes the analysts would take a really out of consensus position

Starting point is 01:14:41 about their forecast for the earnings in the next quarter. And what they wanted to know was essentially when you actually see what the earnings report is and it conflicts with the forecast, what happens? Do they stick to their previous forecast and sort of double down on it for the next quarter? Or do they update their forecast? So that's the question that they were asking. And they found something really interesting that when the analysts made in consensus forecast and then the actual earnings conflicted with the forecast, they made they changed their minds. They updated their forecast. when they made an out-of-consensus forecast and then the earnings conflicted with that

Starting point is 01:15:21 forecast, they wouldn't update. They doubled down on it. They escalated their commitment to the out-of-consensus forecast. So there was a really big difference between in-consensus and out-of-consensus where they stuck to these sort of like very extreme positions that they had taken and they wouldn't change their minds. And I think that we need to realize that that, which is really an issue about identity, ends up starting to play a very large role in whether or not we're willing to quit things.

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Starting point is 01:18:58 risks, charges, and expenses. This and other information can be found in the income fund Funds Perspectus at fundrise.com slash income. This is a paid advertisement. All right. Back to the show. I think there's actually something really profound going on here. And you write about this a bit in the book, this whole issue of identity. And I realize in some ways that I'm a perfect example of it in that buying something like Alibaba or buying Serratich, which is one of the other stocks that I earned, which crashed during the first day, the early days of COVID, because all the mall operators and all the malls shut. And so then I have this friend Monich Pabri,

Starting point is 01:19:36 who buys 13% of the company, and it's this beautiful contrarian bet. And so with both Seretage and Alibaba, there's something tribal there. Part of my identity is wrapped up in the fact that I like people like Munga and Monish and Lou Simpson. I admire them greatly. They're contrarian value investors.

Starting point is 01:19:56 They're smarter than the crowd. They have the guts to go against the herd. But I see myself smiling as I talk about them. And so it's part of my identity. And likewise, I think one of the things, I know very little about Bitcoin and cryptocurrencies, and I'm sure people will be writing in to complain about our discussion already. But I think one of the dangers with Bitcoin and cryptocurrency is actually the zealotry, where people started to define themselves as being disbelievers in the system.

Starting point is 01:20:30 They saw very rightly that there was financial and monetary recklessness. And so they were saying, well, you know, this came out sort of around 2008, 2009, during the financial crisis, as I understand, where there was this loss of faith in institutions justifiably. And so there's something rebellious, subversive, you're allying yourself with a tribe of highly intelligent people who understand this technology that most of us don't understand. And so I think you're onto something that's really profound where I think we have to just be very aware of just how vulnerable we are to this sort of self-image.

Starting point is 01:21:06 Very much so. I mean, so on a broad scale, you know, we see people hold very extreme political beliefs. And when the world comes into conflict with those beliefs, they don't let them go. You know, you scratch your head, why? But it's for just, it's the same reason, right? Like, you're part of a tribe. That is your identity. And I've done some research with J. Van Baville and D.R.

Starting point is 01:21:30 Diego Rivera and some of our collaborators up at NYU. And what we found is that like when people hold a particular belief, if you fact check them, they will change their belief a little bit, but it's completely overwhelmed. And we're talking in order of magnitude, overwhelmed by the tribe. You know, we can predict what your belief is by whether you're like Republican or Democrat, right? So if we then correct it, you will, you will both sides, whether you're Republican or Democrat, you will change your mind a little bit, but it's completely overwhelmed by the issue of what tribe are you in.

Starting point is 01:22:04 And I don't think that we realize how much that really matters, right? Particularly when we're talking about these positions that we hold that are quite extreme. And you see this with like doomsday cults, right? Like they literally predict like the world's going to end on December 20th. And then December 20th, the world doesn't end. Are they all fleeing the cold? No, right? Because again, this is their identity.

Starting point is 01:22:27 It's their tribe. they've probably abandoned their families to these beliefs. They've given away their worldly goods. They've acted on it on this in some way that's very extreme. They've staked their identity on this and they won't let it go. And then you see this behavior, you know, lest you think this is just about politics and political tribe or, you know, even like I'm going to be an anti-establishment, like person who really believes in like stable coins or whatever it is, that this is now seeping into the way

Starting point is 01:22:58 we make everyday decisions. So one of the, one of the things that I think about like how this is such a cautionary tale comes from actually just Sears, the retail store. They were founded in the late 1800s. Which Seretitch was spun out of, by the way. There you go. So, oh, full loop. I love this. So Sears is later, you know, founded in the late 1800, start with the book of bargains, 512 pages, basically sort of riding off the back of the mail system, that infrastructure that was created to get goods to rural America that wasn't available to them, that were only available in cities. Incredibly successful.

Starting point is 01:23:36 I think in the 1920s Sears, Richard Sears, was worth $26 million in the 1920s. Like a crazy amount of money back then. They eventually, you know, get actual store locations. That starts to happen in late 20s, early 30s in order to accommodate the fact that people have cars. By 1950, they represent one percent of USGNP. that's nutty. This is a huge company.

Starting point is 01:24:00 And then we know kind of what happened. You obviously know what happened. They start to falter starting in the late 70s as, you know, the Walmarts and the Kmart's come along and start sort of pushing them out from below. And then the Nordstrom's and sort of higher end department stores start to push them out from above. By the 90s, they aren't the largest discount retailer anymore that belongs to Walmart and Kmart at that point and then eventually Target.

Starting point is 01:24:24 They merge with Kmart in the 2000s. at that point, Kmart is also faltering and what's known as a double suicide. That was what one financial observer called it. Then we know that they went bankrupt. Okay, so that, that seems like, you know, a standard, like they were around for a long time. Competitors came in. They didn't do well. But here's where we really get into this problem with identity. The thing that people don't generally know about Sears is that Sears was also a financial services company. So that started because they had a banking division that was offering credit to their customers who were buying in the catalog. But then remember, they created these retail locations as opposed to just the catalog

Starting point is 01:24:59 business to accommodate the fact that people had cars. And somebody at Sears had a very good idea, which was, well, people are driving these new cars to our stores. We should sell them insurance for the cars. And so they founded a company called Allstate Insurance. There is them everybody has heard about. When I checked for the book, its market cap was $40 billion. I don't know what it is today. So this is a very big company that they founded. Originally, the deaths were in Sears and was only auto insurance. Obviously, it ended up expanding to, you know, be more independent and offer liability for anything. And by the 50s, I think it was the largest personal liability insurer that was around. They also acquired a company called Dean Witter, which was a stock workage firm,

Starting point is 01:25:40 also incredibly valuable. Morgan Stanley bought it. At that time, it represented 40% of Morgan Stanley's values, very big company. They founded the Discover card to be able to allow their customers to have credit. That became Dean Werder Discover. And they also bought a company called Coldwell Banker, which merged with another company reality. That market cap last time I saw was over $2 billion. Again, I don't know today, but about a year ago, it was $2 billion. So these are all very valuable companies that they own. They have a thriving financial services business. And I mean, I assume William, you're like, hold on a second. Like how on earth did these people go broke? because when you take the market cap of all of those together,

Starting point is 01:26:20 we're talking about billions and billions of dollars, right? Like a lot of money. And the answer is because of identity. Because when they were faced with the faltering retail business, remember, the retail business starts to falter in the early 80s, and the shareholders start demanding action as the retail business is starting to lose money, they decide, and this is in the notes from the board meeting, to get back to its retailing routes.

Starting point is 01:26:44 And so they make the decision to sell off all the financial, services assets in order to save the retail stores. Now, from the outside, you're looking in, you're like, what are you talking about? You have bad assets here that, you know, these stores that aren't are being pushed out by competitors and aren't making any money. You have the thriving financial services business. Why aren't you getting rid of the stores? And the reason is because Sears was a retail company. They sold stuff. And they wanted to protect that identity. And we know what ended up happening. You of all people know what ended up happening with that. And you're adding in things like endowment effect and sunk cost identity.

Starting point is 01:27:22 Again, it's a lollapaloozer of these cognitive biases. And I think what's interesting, Annie, also is you mentioned in the book that knowing is not the same as doing. And knowing, for example, about sunk cost effect doesn't protect you from it. And I was looking over many of the questions that came in when I asked people on Twitter to send in questions for me to ask you. And someone called Atfixius 14, who is also called Michael Field says, well, how does one actually internalize the concepts discussed in the book as opposed to just being able to articulate them? And I think that's a hugely important question. We can listen to all of these discussions of cognitive biases. I mean, I can actually look at Alibaba and say, okay, I'm down 59%.

Starting point is 01:28:06 Here are all of the biases that are making me stupid. And I still can't decide what to do. So how do you shift from knowing that you're irrational and that all of these things are happening to you, that you're subject, all of these idiotic cognitive biases to actually internalizing something and doing anything about it to protect yourself? That's a good question. So the first thing is we talked about one of the things is kill criteria. So think in advance about what are the signals that I might see in the future that would tell

Starting point is 01:28:39 me that it's time to walk away. and you will get better at it. Now, even in the case of Bollabba, right? So you're already in it. You didn't do this in advance. But it's not too late because what you can do, and hopefully you will when we get off, is sit down and say,

Starting point is 01:28:51 what do I need to see within the next quarter or the next two quarters from the way that this investment might perform? So essentially think, how long can I tolerate this, or how much time do I need in order for me to actually get the information that I would need in order to be able to make a decision, figure out what that time period is, and then figure out at the end of that time period, what would I have to see? What are the benchmarks that this thing would have to hit in order for me

Starting point is 01:29:13 to feel like I ought to continue? And if it doesn't hit these things, then I should walk away. Now, you can certainly get help on trying to figure out what those benchmarks are from somebody who's very experienced, who's going to be a good advisor to you, right? And that brings us to the second thing is get yourself a quitting coach, because you're in it. You've lost money on the investment. You made the original decision to invest in it, but go find somebody who didn't make that decision along with you who can really help you to see things from the outside. Because I'm sure you've seen people in these situations where they're holding on to investments where you're going, how can they not see that's a dog? Like they should have sold that a long time ago. Well,

Starting point is 01:29:49 trust me, people are looking in on you and thinking the same thing. So go find them and tell you to help you. And something that's important about this is to understand. I'm sure you have lots of very smart people in your life. And you may have the intuition, well, wouldn't they tell me if they see it? And the answer is, no, they wouldn't. In the same way, you don't say it to somebody else because you don't want to get yelled at or make them feel bad or ruin your friendship. And you might be wrong as well. I mean, I had this discussion with Thomas Rousseau, who's a famous international investor

Starting point is 01:30:17 a couple of weeks ago. And he's like, no, I was wrong about Alabama when I started to sell my position. I've trimmed it. I didn't understand just how much risk there was of the Chinese government messing with this stuff. And I said to him, I sort of have a five-year rule where I'm just going to hold stuff for five years so that I don't make so many decisions. And he's like, well, you're probably do better than me. And that's what's also so hard is it's so murky. It goes back to your

Starting point is 01:30:42 question, your conclusion from poker, which is, I'm not sure. There's so much uncertainty. Yeah. So I would say, first of all, with the quitting coach, you want to sit down and create these kill criteria together. So that's something that you can do. Like, is this a situation where I should just hold for five years? Because I think we should agree, you shouldn't hold everything for five years, right if if something let me give you a simple example for some reason you decide to buy a meme stock are you supposed to hold that for five years

Starting point is 01:31:09 well obviously not if something goes to a penny right like if the business is clearly going out of business hopefully you notice that beforehand so we can have a rule of five years but we have to have someone lesses that are attached to that and this is true of all goals that we have

Starting point is 01:31:25 so we want to set out kill criteria with ideally with a quid and coach, that we can go and check in someone who's very experienced who can help us look at those criteria, revamp them because you're going to want to, you know, obviously like if you make criteria for a particular quarter, then you would want to make a new set of them, and then get somebody to help you to be able to see it from the outside. And then when it comes to goals, hard and fast rules, like I only hold for five years, make sure that you have some

Starting point is 01:31:53 unlesses that are attached to that. And let me explain why just like, this isn't going to seem related, but it is. There's this woman, Chavon O'Keefe, who is running the, the two 2019 London Marathon. And right around mile four, she started to experience a lot of pain in her leg. And then on mile eight, her fibula snapped. But she literally broke a bone in her leg. Now, I assume you share the intuition that she stopped running. One would assume. But she didn't. She finished the race. Now, this is weird. She broke her leg. She was in excruciating pain. All of the doctors were telling her, like, don't run. Like the people in the medical, like stop running. you shouldn't be running.

Starting point is 01:32:32 And you can see here where she's risking never being able to run another race again. Like what if it becomes a compound fracture? Like it's going to obviously take a lot longer to heal a broken leg that you've now run an extra, what was it, 18.2 miles on, right? But she kept running nonetheless. And this is part of the problem with sticking to things too long is that it stops us from having the opportunity to do other things, right? We can't use that time and attention for other stuff.

Starting point is 01:32:57 Now, lest you think that she's strange, there were three other people. in the same race who basically did the same thing. And if you look at any marathon, there are people just running with broken legs all the time. So the question becomes why? Like, why are they doing that separate and apart from like the sunk cost issue and whatnot? And it's because there's a finish line. The finish line is 26.2 miles. And when we talk about being in the losses as a cognitive phenomenon, it doesn't matter that she ran eight miles. She's short 18.2 miles. So therefore, she has to keep going because otherwise she has failed. If you get three, 300 feet from the top of Everest, you didn't climb 29,000 feet. You failed. You failed to get to the finish line. So when we set these goals, right, these marks, these lines in the sand, the problem is that we will keep going toward them basically no matter what, because otherwise we will have failed. So just a, you know, this would be the caution with I have a five-year hold, which is unless. So an example might be, here's my thesis. I have. I have a five-year hold. I have. You know, I have. You know, I have. You know, I have. You know, I have. I have. I

Starting point is 01:34:01 have some sense of the effect, for example, of what the Chinese government is going to have on this particular investment. So as long as that holds, as long as the status quo is the same, and nothing tells me that that was a silly assumption, I'm going to hold for five years. I don't care if it goes up or down or whatever, right? I'm just going to hold for five years. Unless I see that Jack Ma disappears, at which point, I should say maybe I don't know so much about the Chinese government. And maybe they're going to really interfere with investments here. And I should get out of this because there's something that I thought was true of the world that I now have new information that isn't true of the world. And while normally my five-year-old, you know,

Starting point is 01:34:46 is a rule that I really try to follow in order to protect me from overreaction to the ups and downs of the way things are going. And I'm trying to ride the base rate, right? I want to make sure that I'm not missing out on that, which is that things tend generally go up and I want to have enough time to do that. Sometimes there's going to be something that happens where I should put this big on less to that goal. So what I would say with something like Alibaba right now is to just sit down and say, what are the things that I would have to see over the next order that would tell me that I have to change my mind? Or maybe go talk to somebody and say, how bad do you think it is that there's been this interference from the Chinese government? You know, someone you really

Starting point is 01:35:27 trust and find out what they think. And then no matter what, you're going to be making the decision under uncertainty. So the question that I would have for you is not so much, are you going to do better than that investor? But if you had talked to him today and you knew what you knew about Alibaba today, you knew what happened to Jack Maugh today, would you buy it today on his advice? And if the answer is no, then you shouldn't be holding it even if you have bought it in the past. Right. And that's the I think that's where we have to start to change the way that we're approaching these problems. I think also, Annie, you bring up this really important point that's a thread through all of your work. And wait, I just want to say, that's not stock advice for anyone.

Starting point is 01:36:04 I'm not advising anybody to sell Alibaba nor buy it. I am not. Yeah, and likewise with our cryptocurrency expertise or lack thereof, this is just an example of the kind of. Yeah, we're just talking really about the difficulty of thinking rationally given our cognitive bias. And one of the things you talk about that's a recurring theme in your work is the importance of bringing in other voices, bringing in other perspectives. And this goes back all the way to when you were learning poker where you would be listening to people like Eric Seidel or to your brother Howard. Likewise, I see it in investing where, for example, Howard Marks has Bruce Cash as his partner. Buffett calls Munger the abominable no man because he says no to so many of the things that Buffett thought were really good ideas. I see people like Monish Pavar and Guy Speer talking about their ideas. And it doesn't always hold. I mean, Guy, I think thinks Monash is taking way too much risk, putting lots of money in Turkey. And Munger often makes these great points that then Buffett ignores. You know, it's not like you have to take the advice.

Starting point is 01:37:10 But this idea of actually having somebody who you trust who, as you say, Kahneman, I think, you know, Danny Kahneman is one of the smartest guys on Earth who you're friends with, has Richard Thaler, another Nobel Prize winning, a Conno. An economist, can you talk about the fact that Connaman actually gave explicit permission to Thaler to tell him what he doesn't want to hear? Because that also seems to me really important. Yeah. So I think that we think that people are going to tell us what they see, particularly if they love us. And we assume that people who love us have our long-term best interest at heart. So if there's something that we should be stopping, like for, you know, Connman says, like if I'm pursuing some sort of

Starting point is 01:37:51 line of research, whatever, I assume that people will tell me. But the thing that it's, you know, that I shouldn't be. But nobody wants to do that, right? Nobody wants to say, oh, by the way, you're failing or the thing that you chose to do isn't working or by the way, you should break up with this person, God forbid, that they actually don't. And then they know you think that they shouldn't be with that person anymore. But separate and apart from just sort of that kind of danger, there's also, we have a tendency with people we love to want a cheer lead, you know? So, look, if you're talking to me and you say, I have a five-year rule, And so this is why I'm sticking to this.

Starting point is 01:38:24 My tendency, less anything else, is going to be like, that's great. You're so disciplined and what I cheerily do to, you know, because I want you to feel good. And I don't want to be the abominable no man, right? And just to be clear, before I sound even more stupid than I am with that decision, really what I was trying to say is, once I buy something, I've got to hold it for a minimum of five years. Because I'm like, one of the biggest problems investors have is that they're too impatient. And if I just tie my hands, then even though I'll be wrong sometimes, over time, I'm pushing myself towards good behavior of deferral identification. Listen, I completely agree.

Starting point is 01:38:58 I don't want people to start making individual decisions. All I want is that when you say, I'm buying it, I'm going to hold it for five years, that you just add some key on lesses. That's it. Yeah, it's a great point. So this is my general strategy. But let me remember why I bought this. So if there's something that really changes, right?

Starting point is 01:39:19 You know, Annie, there's a really beautiful essay that George Orwell wrote on writing, on how to write. And he lists all of these rules. And the final rule he says is ignore all of these rules rather than do anything downright barbaric. And it's such a beautiful unless, isn't it? That's the perfect unless, right? In fact, Churchill, when he said never, never, never, never, never, ever give up. You know, there was, he said, accepted matters of honor. And, you know, so he even had an unless on that one when he was telling people never to quit.

Starting point is 01:39:50 He was like, except when you're supposed to, basically is what he said. Yeah. So I think that what we, I think that the thing is that what we want to do is make a distinction between, is this a situation where that unless should apply, for example, with you? Or is this a situation where I'm just sort of panicking and I got this rule and the rule is in place for a reason. I have a similar rule, by the way, as you do, which is I want to make sure that I'm realizing those gains and not overreacting or thinking.

Starting point is 01:40:15 thinking that I know more than I do, for example, right? And what we need to do is find someone that we can trust to tell us the truth when they see that things aren't going well for us, when our job isn't going well, or a relationship isn't going well, or research isn't going well, or we're so sure of, you know, this NFT that we own or whatever, the NFTs or the next thing and we're literally taking all of our money and putting it into NFTs. And don't we want someone to stop us? I mean, just strictly from a risk standpoint, right? Don't you want someone to say, don't do that. Don't take all of your money out of here and put it all over into one asset class. That's nuts. But people tend not to step in and do that unless we give them permission.

Starting point is 01:40:56 And that's the key thing is that we have to tell somebody, I don't want you to cheerlead. I don't want you to support. I don't want you just to bite your tongue when you see that I shouldn't be doing this. I actually want you to tell me. And you have to be very explicit in giving them permission to do that because what you have to say to them is, I recognize that I'm going to make a lot of decisions that are bad for me in the long run, that I'm going to rationalize away or they're going to feel good in the short run or whatever it is. And I need you to be on the right ride with me. And I need you to tell me what's good for me in the long run, even if it hurts in the moment. So please tell me the hard things. I promise I will not be mad at you. I promise that this will be

Starting point is 01:41:35 really important feedback for me. I promise that I will try to listen. I won't always follow what you say, but I know it's going to make me better for it. And if you can do that with someone and find people in your life who are willing to enter into that game with you, you're going to do a lot better. One thing that's really striking when I look at your life, Annie, is that you've, you've been helped by an extraordinary array of unbelievably talented people. I mean, obviously, it goes back to Lila, who we talked about at the start. But also, when I look at the acknowledgement sections of your books. I can see, you know, you talk about Michael Mobycin, introducing you to Sasha Cohen, who's one of the, someone you write about in this book,

Starting point is 01:42:19 or talking through the book with you in the early days of the book. You talk about getting help from people like Danny Kahneman and Richard Thaler in developing the ideas in this book. So two incredible Nobel Prize winning economists. You talk about Philip Tetlock, the author a super forecasting. You talk about getting Charles DeHig, who wrote this great book, The Power of of Habit, lending you his book proposal so you could see how to write a book proposal. Dan Ariely, the great expert on pain and the like, introduce you to your agent, Jim Levine, who's also my literary agent, who's amazing. And I think of, you know, think also of Eric Seidel helping you. or why is it that so many extraordinary people have been so generous with you?

Starting point is 01:43:05 And is there, I'm sort of asking this, it's difficult for you to be honest about it and self-effacing about it. I think because I ask. Really? I think. I don't know. I don't know. You know, Michael Mobson in particular has been so incredible and generous.

Starting point is 01:43:23 And I just really enjoy talking to him so much. And I guess maybe he enjoys. talking to me. I don't know. Like, he, I sort of pinch myself all the time. I mean, Phil Tetlock is not just a collaborator of mine, but he's now my PhD advisor. And I've known him for 10 years. I was one of the people he talked to about, talked to for super forecasting. So we developed a relationship back then. And his wife Barb is like so incredible and incredible researcher in her own right. I don't, yeah. I mean, I first of all, I do ask. I think maybe I've been, I've been lucky enough. I mean, some of it I think is luck. Like, you know,

Starting point is 01:43:57 obviously, there's a lot of hard work to get Lila, you know, to get into that program and have Lila be my advisor. So that I would less call luck. But I think that I was really lucky to end up in poker. And I think people think it's kind of a cool thing that I did. And I think that that gets people to talk to me. And then it's like my job then to make it interesting. And at least when it comes to, at least when it comes to this topic of quitting, what I found is I was as I was sort of reaching out to people, Don, more I would include in this as someone who's been incredibly supportive and amazing. He wrote perfectly confident. David Epstein, who wrote Range, is that they were all, they were excited about the topic. So in some ways, I think that's also just like a nice thing is that

Starting point is 01:44:37 the kind of thing that I was really interested in thinking about, which was like, how do we solve these problems of quitting when that decision is made under uncertainty itself? Just the people, people were kind of on that ride with me in thinking that this was a fun, cool, important thing for somebody to write about. And so they, they were very generous with me. about that, but I had to ask. You know, and I think this is really important. Just ask, what's the worst that happens? Like, they say, no, whatever.

Starting point is 01:45:04 Maybe it goes back to loss aversion, right? Like, we have this fear that the pain of loss is going to be twice as intense as the pleasure of gain. And so we're afraid. We're afraid to ask. So, like, that fear of getting said, no, but like what comes out of it is so amazing that, you know, and then once people are excited about the topic, they then start thinking about it. And, like, Don Moore, I had a conversation with him about quit.

Starting point is 01:45:26 and he ended up sending me like a three-page thing with like a whole lit review of things that he thought were relevant. And I mean, how generous. Like how incredibly generous with your time and attention that you would send me that. And then he wrote a, he read an early version of the book and said, I really think you need a section that's just on over optimism. And he helped me with that and worked on that with me and I definitely made the book a lot better.

Starting point is 01:45:50 So I don't know. Like, I don't know. I really don't know why I'm so darn lucky to have. have these people to talk to you. But thank God I am because I'm not smart enough to write a book without them. So you wrote in thinking in bets about the superlative players who, quote, bestowed their expertise and friendship, a truly wonderful gift. And I just was sort of thinking about that, that it's so central to the way that you learn, obviously, is by getting a peer group of people who were really intellectually engaged. I guess that's one of the common denominators,

Starting point is 01:46:24 is both with poker and with your research and your books, there's an intensity to your curiosity about the subject that people probably feel. And so they engage with it. And it's cool, interesting work. So these are all people who are actually intellectually very engaged. And so I think that's part of it. But I also, if I'm honest about it, I think part of it's just if you're a decent and amiable and a nice person.

Starting point is 01:46:53 there's a weird competitive advantage to being nice. Maybe. Yeah, I guess I don't know. The thing is, like, I really, like, I learned a long time ago in poker that confidence does not mean thinking you know everything. And in fact, if you do, then you're not going to do well. So you can be pretty confident that in that moment you're playing well and going to, you know, like, I was pretty confident.

Starting point is 01:47:21 I could write a reasonable book about quitting. But that doesn't, in no way did I feel like I knew anything. You know, like if I have the chance to talk about Richard Thaler, who was the first person to identify the sunk cost effect as a general phenomenon, I'm going to spend all the time that he's willing to give me and hopefully soak up everything that he has to say because I know it's going to make what I'm doing much better. And I don't feel like, you know, I've come across people in my life who I can,

Starting point is 01:47:47 like, you can sort of see that they're borrowing ideas from other people, but then not acknowledging it. they're not, they're sort of acting as if those are their own thoughts. I don't know why that I think maybe because they think they want to appear to be smart. And I'm someone who's just like, that wasn't my idea. That was Mobeson's idea. Thaler told me that. Connumann told me that.

Starting point is 01:48:08 Because what's wrong with that? Right. That's the thing is that I really truly believe that. I'm like, I, you know what I say? With my books, I say, I don't think I have an original idea in any of the books that I've written. I think I put the things together pretty well. Like I think that's the thing that I do pretty well.

Starting point is 01:48:22 is to put ideas that have obviously come from people who are much smarter, think much more deeply about these topics than I possibly ever could, have done the original research, really identifying these phenomena. And then I think I put it together in an interesting way. And I'm totally okay with that. Like, that's fine by me because I'm excited that I get to, in some way, translate the work of these people who are so incredible in a way that's like nicely consumable for the average person. I think that's an important role to play. And I'm perfectly happy playing that role. It's a role that I really enjoy.

Starting point is 01:48:58 And I get to learn in the process. I get to explore the ideas in the process. And I become smarter in the process. And isn't that lucky for me? It's lucky for us as well. It's a very cool book. And I have to say, before we go, one of my favorite parts of it is tucked away in a footnote where there's a perfect

Starting point is 01:49:16 example of this, where you synthesize this stuff from Neal's Bohr and Thomas Mann from an essay that he wrote in like 1928 about Freud. And then not necessarily new ideas, but it's also something that Philip Tuttlock said about how the opposite of a virtue is also a virtue. Yeah, I'll see, and this is people, you have to read the footnotes to know that that came from him. So I appreciate that. But there's something beautiful about that synthesis, and you synthesize this idea,

Starting point is 01:49:43 and it kind of expressed something that I've been thinking about a lot, but that you've drawn together from these different sources. It's a very valuable thing. And I'll just say, I was telling my daughter on Facebook yesterday about this. She's at college in Boston. And she took a picture of me looking incredibly excited, holding a spatula as I was cooking my oatmeal because I was telling her. And this is what Neil's forth. So, no, I think you're doing something very valuable in taking your own experience from poker and investing and cognitive bootstrapping and the like.

Starting point is 01:50:14 And then drawing in lots of insights from other people and from the reporting. doing. And it's, it's, it's, it's a, it's a really interesting and thought provoking book. And and so was thinking and bets. And so I wish you much success with them. I'm, I'm sure, I'm really, I really appreciate it. Thank you so much. This was such a great conversation. Thanks. It's been a great pleasure. And I hope we'll, we'll get to meet in person for too long. It's been, it's been really fun. And by the way, I always say this, edit away. I don't care. I know I'll sound better if you edit me. So you sound great. Annie, best of luck with the book and and everything else. It's been a real pleasure chatting. Thank you so much, William. This was really

Starting point is 01:50:51 fun. Thanks. All right, folks, thanks so much for listening to this conversation with Annie Duke. I had an absolute blast chatting with her, and I hope you enjoyed it as much as I did. If you'd like to learn more from Annie, I'd definitely recommend her best-selling book, Thinking and Betts. I also really enjoyed her new book, which is titled Quit, The Power of Knowing When to Walk Away. Meanwhile, I want to thank everyone who suggested questions over Twitter for me to ask Annie. For each episode of the podcast, I like to send out one signed copy of my book, Richer Wiser, Happier, as a way of saying thanks for all of your excellent questions. This time around, the prize winner is a listener in New Jersey who goes by the Twitter handle at Fixius 14. Please feel free to follow me on Twitter,

Starting point is 01:51:34 William Green 72, and do let me know how you're enjoying the podcast. I'm always delighted to hear from you. I'll be back very soon with some fascinating guests, including the Nobel Prize winning economist, Robert Schiller, who wrote a famous book on irrational exuberance, and a renowned investor named Francois Rochon, who's beaten the market by an enormous margin over the last 30 years. In the meantime, take care and stay well. Thanks a lot for listening. Thank you for listening to TIP. Make sure to subscribe to We Study Billionaires by the Investors Podcast Network. Every Wednesday, we teach you about Bitcoin, and every Saturday we study billionaires

Starting point is 01:52:13 and the financial markets. To access our show notes, transcripts or courses, go to theinvestorspodcast.com. This show is for entertainment purposes only. Before making any decision consult a professional, this show is copyrighted by the Investors Podcast Network. Written permission must be granted before syndication or rebroadcasting.

We Study Billionaires - The Investor’s Podcast Network - RWH015: Betting Better in Markets & Life w/ Annie Duke

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