Most people picture investing as a game of chess. Everything is visible on the board, the rules are clear, and if you’re sharp enough, you can see ten moves ahead. But markets don’t work like that. They shift in real time—rates change, policies flip, black swan events crash the party. That’s why I think investing looks a lot more like poker.

In poker, you never know all the cards. You play with incomplete information, and even the best players lose hands. What separates them isn’t luck—it’s process. Over time, making slightly better decisions than everyone else compounds into big wins. That’s the same discipline great investors use. They don’t wait for certainty—it never comes. They weigh probabilities, manage risk, and swing hard when the odds line up.

Risk isn’t the enemy. Fold every hand and you’ll bleed out. To win, you’ve got to put chips in the pot—wisely. Wealthy investors do the same. They protect the downside, but when they see an asymmetric bet—small risk, huge upside—they lean in. That’s what early Bitcoin adopters did. That’s what smart money did in real estate after 2008.

And just like poker, investing is about knowing when to quit. Ego and sunk costs can trap you in bad hands, but the pros know when to fold and move their chips to a better table.

In the end, both games reward patience, discipline, and emotional control. You don’t need to win every hand. You just need to stay in the game long enough for compounding to do its work. The amateurs play for excitement. The pros play for longevity.

That’s the mindset you need as an investor and the reason I interviewed a former professional poker player on this week’s Wealth Formula Podcast!

Transcript

Disclaimer: This transcript was generated by AI and may not be 100% accurate. If you notice any errors or corrections, please email us at [email protected].

  One of the things that we feel like when we decide to make a bet on a thesis and we’re thinking about, well, wait, what, what if it’s like this? Or what if it’s like this or whatever, is that we, we do have this sense that we get caught in those decisions, right? That we start something and that, uh, it’s very hard for us to get out of that position.

Welcome everybody. This is Buck Joffrey with the Wealth Formula Podcast. Coming to you from Montecito, California. Before we begin today, I wanna remind you that there is a website associated with this podcast called wealth formula.com. Lots of resources there, including the ability to sign up for our accredited investor club.

Now, of course, that is a, uh, also known as a investor club and, um, basically you sign up there. And, uh, you get onboarded and you get an opportunity to see private deal flow that you will not see anywhere else. So go check that out. Wealth formula.com. Topic of today’s show’s a little different. Um, it’s, uh, a little bit more, uh, about the cognitive side of.

Of, uh, investing. So, you know, most people picture investing as sort of a game of chess, right? Everything is visible on the board. The rules are clear, and if you’re sharp enough, you can see 10 moves ahead. But in reality, the markets don’t really work like that. They shift in real time. You know, you got rate changes, policy flips, black swan events, all these things can crash to party.

Uh, and that’s why I think investing actually looks a lot more like poker and poker. You know, you never know all the cards you play with incomplete information. And guess what? Even the best players lose hand, you do lose in investing. That’s something you have to understand. Now, over time, making slightly better decisions than everyone else compounds into big wins.

And that’s what makes a, you know, difference between like professional investors and people who lose money in the market. That’s the same discipline. Great investors use. They don’t wait for certainty because the reality is it never comes. They weigh probabilities, manage risk, and they swing hard when the odds line up, right?

So the thing to understand is that risk isn’t the enemy, right? In poker, if you fold every hand, you’re gonna, you’re gonna bleed out. You know, you’ve gotta have ships in the pot, you know, wisely. Of course. Wealthy investors do the same. They protect their downside, but when they see an asymmetric be a small risk, huge upside, they lean into it and you know.

That’s what, for example, we, we’ve talked about it before, but you know, people who, uh, you know, bought Bitcoin early and had conviction and stuff, like that’s what they did. And that’s what the smart money did in, in real estate after 2008. They knew that they had a reset point, and even though things looked dim and grim, but all of a sudden they saw rates coming down.

Um, they saw quantitative easing. They knew that a huge amount of liquidity was coming into. Space and they killed it for the next, you know, decade and a half. I mean, similarly, right now, like I think, um, I’ve been saying before, I, I think rates are coming down because of the Trump takeover of the Fed, because of, uh, job market that’s weakening because of ai, all these things.

But you know, just like poker investing is about knowing when to quit as well. Ego sunk cost and. Trap you in bad hands. But the pros know, uh, when to fold, move their chips onto a better table, right? Uh, in the end, chess, you know, or poker, they, they both are gonna do one thing. They’re gonna reward patient’s discipline and emotional control and understand you don’t need to win every hand.

And if you do, you don’t panic and stop playing. You just need to stay in the game long enough for compounding to do its work. Um, you know, the amateurs, they do it for excitement. The pros, they play for longevity and obviously investors were trying to make, uh, make some money. So that’s the mindset you need to have as an investor.

And the reason I interview a former professional poker player on this week’s. Wealth Formula Podcast. Hope you enjoy it. We’ll have that interview right after these messages. Wealth Formula banking is an ingenious concept powered by whole life insurance, but instead of acting just as a safety net, the strategy supercharges your investments.

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Turbocharge your investments. Visit Wealth formula banking.com. Again, that’s wealth formula banking.com. Welcome back to the show we went today. My guest on Wealth Formula podcast is Annie Duke. She’s a world-class professional poker player, winning millions at the table by mastering strategy, risk and human behavior.

Since retiring from poker, she’s become one of the foremost experts on decision science. Uh, she’s the bestselling author of Thinking and Bets and Quit, as she now advises investors, founders, and executives on how to make smarter decisions when the stakes are high and the information is imperfect. Annie, welcome to the show.

Thank you for having me. So you, um, uh, obvious a very interesting, uh, background. You went from a professional, uh. Poker champion to a decision strategist, essentially. So tell us, I mean, yeah, what parallels do you see between high stakes poker and the decisions, say every day investors face in in today’s markets?

Yeah, so first of all, I actually went from cognitive science to poker, back to cognitive science. Oh, okay. Well, a loopy loop. Um, okay, got it. All good. So here’s actually the interesting thing. So, um. Particularly when you’re thinking about things like investing, there’s, part of economics is a field called game theory.

And game theory is the study of decision making under uncertainty. Um, and the uncertainty derives for over time is the other thing. So, uh, so we can think about it as making decisions to invest limited resources, right, in situations where, uh, luck can affect the outcome. Um, and where, uh, you don’t know all there is to be known and know, you know, very little in comparison to all there is to be known for most of the decisions that you’re making.

And then, and then the over time piece has to do with, um, for most types of decisions, and this is particularly true in, uh, investing. The decision we you make now could affect de de decisions to come. So you could think about like in negotiations, right? Like when I’m negotiating with someone, it’s really different.

If it’s a one-off, it’s the only time I’m ever gonna negotiate. Against them versus if it’s gonna be a repeated negotiation. Right. Okay. So a guy named John von Norman, along with Oscar Morgan Stern, wrote a book long time ago called The Theory of Games, which was really kind of defining this as a field, um, and something that we ought to be thinking about and studying.

He was actually the mentor of John Nash, very famous economist, schizophrenia, um, who was the subject of a beautiful mind. And John Nash’s, um, uh, Nobel Laureate Nobel Prize was actually in game theory. That’s what he was studying. Um, okay. So what does that all have to do with the question that you asked, which is what are the parallels with poker?

Jon Van Neuman was actually thinking about game theory and trying to figure out sort of like the mathematic, how you would mathematically model this problem. He actually used poker as. That he, for the model of the way that he thought about it. So, um, he was actually asked by Jacob Broski, who’s a colleague of his, um, you know, oh, you know, I read the theory of games and it’s really interesting what you’re talking about, but I don’t understand why you didn’t use chess as the model.

The sort of thinking like chess is the game. And Van Neuman, I’m paraphrasing here, basically said chess, chess isn’t a game. It’s a calculation. Poker is a game. And what he was pointing out is that in chess there’s. You know, a much more, you know, smaller influence of luck. And the other thing is you can see all the pieces on the board, right?

So that it doesn’t, it doesn’t have these same components, right? So that’s really where you can see this sort of model of poker, not just for investing. Really for any kind of decision you make, and it’s like you’re making decisions where luck has a very strong effect on the outcome. You have to invest limited resources in these choices with very little information.

I certainly can’t see my opponent’s cards. Um, and how a hand turns out is not necessarily going to be per. Is not perfectly correlated in the short run with what the quality is of the decision that I made. Like was I mathematically correct to be making that decision? Because you can get like a bad deal of the cards, for example, right?

So, uh, it’s very, very much like an investing in, in that way. So it creates a really good model for understanding all decision making, but it particularly maps really nicely onto finance. Yeah. And I guess thinking in, in bets, uh, you, I guess you argue that good decisions aren’t outcomes, but you know, they’re about the process, right?

It’s, it’s more about the process. So that’s kind of what you’re getting. How do you suggest investors then evaluate whether they’re making smart choices, um, when the short term results may look bad? So, okay, so first of all, let me just sort of be clear about what I mean by an outcome. So obviously, like in the long run.

The outcome is gonna be very good signal for what the quality of a decision is not on one investment. I mean, across like many, many, many different investments. It’s kind of like if I flip a coin once, it doesn’t tell me very much, but if I flip a coin 10,000 times, then obviously the outcome of those 10,000 flips is gonna tell me a lot.

Right? So I’m, I’m really talking about sort of what’s happening, uh, with a small sample size, like, you know, one stock that you might buy. Um, or like in the short run, right? So where, where you don’t have enough time to sort of realize, uh, the expected val value and overcome whatever the volatility is, right?

So, IJI just wanna be clear about that. So one of the really biggest mistakes that we make is decision makers, is that we connect the outcome, we get to the quality of the decision. In the short run, like the short term outcome. So you, you buy something and the next thing you know it’s down 10% and you think I made, I made a really bad decision.

That kind of thing. Or it’s up and you think, oh yeah, great decision. Yeah, yeah, yeah. Right, right, right. Um, and there’s some, there’s some differences, um, with that. So I’m gonna have a tendency to do that, which is called resulting, uh, much more when I’m thinking about. Other people’s investing. When I’m thinking about my own and things go poorly, um, I’m gonna tend to say, oh, I got unlucky.

Which is bad because maybe you made a bad decision. And when I win, I’m gonna have a tendency to attribute that to my own decision making. This is called self-serving bias, which is also bad because maybe you made a bad decision. People have won on many investments where their thesis was ridiculous, right?

So the question is like, how do you actually overcome that problem? And it’s hard, uh, but it’s worth the work. Um, and it’s a little bit of a long answer, so I’ll just start the conversation and then we can go from there. Yeah, I mean, I guess the question is, you know, what kind of tools for decision science can really help people in this, these kinds of scenarios.

So I would ca, I would put tools into two categories, right? So, so one thing is that you have to start really making explicit. What it is that for you, the, those qualitative judgements that are, that are driving the decision, right? Not just the data, but like how are you interpreting the data? What do you believe to be true of the future that’s causing you to, to make this decision?

So, um, that’s number one. And we, we actually leave quite a bit of that implicit, believe it or not. Um, number two is you have to start to think about what are the tools that are. Not only gonna help me to be better at making the decision at the time that I’m making it right, and there’s all sorts of things that you can do that can be helpful with that, but also are gonna help me then to be able to actually close the feedback loop in the way that I want to, right?

Which is to, to close the feedback loop back to decision quality and not just sort of rely on how it turned out, which is bad. Figure out what I’m good at and what I’m bad at so that I can start to improve. Then also, and this is really important to start to develop a tool set that allows you post-decision to be more rational in the way that you react to new information.

And it turns out that even people who are really good. That initiative to, uh, decision to start something like, to invest in something are very bad at the decisions that, that they make after they invest. In other words, what do you do as you learn new information? Are you actually being, uh, reactive to that in a, in a rational way?

Are you reacting to that sanely? Um, and it turns out the answer is mostly no. Uh, we’re pretty bad at those decisions, so you have to actually sort of develop a whole toolkit to help you with that piece as well. Yeah. So in, in, uh, quit, uh, you make the case that knowing when to walk away is as important as persistence.

So how should investors think about quitting, uh, an investment or business venture without feeling like they’ve failed? So, I would actually argue that knowing when to walk away is more important than persistence for the reason that, um, we tend to be persisters. So it’s just kind of what our default position is, is to stick with stuff.

Number one and number two, you’re gonna stick with a lot fewer things than you’re gonna walk away from. So if that’s the case, if the majority of your decisions are gonna be walk away decisions and we tend to be persisters, then figuring out how to good at that, get good at that walking away thing is gonna be really important.

So why is it that we tend to be persisters? Well, there’s like a whole bunch of cognitive biases that. Really influence big. It’s kind of like a big pile on that makes you wanna stick with stuff. And this is a particularly big problem, um, in anything, but you can really see it in investing. So what happens is that we start something and then as soon as we start it, we have a few things.

One is we start to accumulate what are called sump costs. This is time, effort, money, attention that you have put into something. So you can think about it. If I buy an equity at 50 and it’s trading at 40, I’m down 10. Right? So that’s, that’s money that’s now gone. Um, you could also think about it as like, uh, if I start a race from like running a marathon, I just started putting effort into it.

Like I’ve done training. Sunk cost. Uh, I, um, you know, so I’ve been training for months and then I start running and I’m like part of the way through the race and like that all becomes stuff, you know, sunk cost. And so we have this tendency, whether it’s like running a marathon or you hear this with people who are in jobs that they don’t like, why are you still in there?

’cause then I, I, I don’t wanna have wasted all the time and effort and training and all this stuff that I’ve put into it. So it’s thing time, effort, and money that you’ve invested in the past. It’s now affecting your decision whether to continue in a way that it shouldn’t. So in reality, yeah, okay, you bought the equity at 50, now it’s trading at 40.

Um, we have this tendency to say, well, if I sell it now, I’ll lose $40. But it’s like, okay, but you already lost that. Would you buy that today? And if the is no, you shouldn’t sell it. But what sunk cost is it causes us to keep at it. Even if we wouldn’t buy it today. And that’s where you’ll hear people say things like, well now it’s really cheap, or It’s too cheap to sell.

So some cost is a big one. Another big one is, um, called the endowment effect, which just means that once you own something, you value it more. And if you don’t own it, and obviously you own the things that you invest in, uh, which is bad. And then there’s all these identity things, which goes to what you’re saying about how do you not feel like a failure, right?

When we make a decision, um, that becomes woven into our identity, right? We’ve decided that this is a good thing to do, it’s a good thing to buy. Um, and if we then all of a sudden say, no, wait, right? I think I should stop. What is the like that, that’s an kind of an attack on our identity. We sort of don’t see ourselves as consistent.

We think we made a mistake. We view it as failure because we’re quitting the thing. Like not only do we feel like, well, maybe, you know, my thesis was wrong, but maybe you lost money. Right? And that doesn’t feel good. And all of those things feel like a failure. And that’s true. Like investing or like, uh, if I start, uh, developing a product, if I stop it, does that mean that I’m a failure?

If I, you know, uh, if I’m doing a project and I stop it, does it mean I’m a failure? If I start a job and I quit, does that mean I’m a failure does, right? That kind of all wraps into it. So the question is like, if all these things are working against us, how do we actually start to say, well now we have to get really good at this?

Because the fact is that when you’re making decisions. As I said before, it’s like you’re non omniscient. You, you know, very little in comparison to all there is to be known, which means that you’re gonna learn a whole lot of stuff after the fact. Some of that times that stuff is gonna be like, wow, this is turning out really well.

Sometimes that stuff is gonna be like, Ooh, I wish I had known then what I known now, and I know we’ve all had that feeling. And when we have that feeling. We should walk away, but all these things make it so that we don’t. So how do we help that? The, one of the main ways that you can help that is to develop a set of kill criteria.

What are kill criteria? They are, um, basically you can think about it as like benchmarks where if you hit that benchmark, you are saying that’s a signal that things aren’t going my way and I ought to walk away. I should go. So let’s think about like, what’s the simplest form of a kill criteria? The simplest form of a kill criteria is a stop-loss.

So if I, if I can say I’m gonna buy this stock at 50, if it’s trading at 40, I have to sell. That’s the simplest form. Now, you know, like for a retail investor, absolutely. Like have at it. I think stop-losses are great. Um, but they’re pretty brute force, right? Because we know that even if the stock is now trading at 40, that your thesis could still be correct.

Um, and so when you’re brute forcing it, it’s definitely helpful if you have a tendency to, not to quit, but we’d like to get beyond that. Now. That’s something that I used in poker a lot, right? Because in poker, uh. When you’re playing in a game, it’s not always obvious. The reason that you’re losing it could be that you’re losing ’cause you’ve gotten very unlucky.

But it could also be that you’re not playing well. And I know I’m gonna be biased to think it’s because I got unlucky. So then I just put in a stop loss because it makes me get up from the table in situations where I’m gonna be a bad judge of why I’m winning or losing. So I did actually use that quite a bit in poker, and I think it’s very good in particular for retail investors to have stop losses in place.

What is actually even better to do than that is to be very explicit, not just about what your thesis is, but to imagine, well, let’s imagine that it’s X time from now, and I look back and I realize that my thesis wasn’t right. In other words, to think really explicitly about, well, what exactly does your thesis imply about what you think is gonna unfold in the future?

Then use that to say, okay, what are these early signals that are gonna tell me that the future isn’t unfolding? As my thesis is saying, thesis are probabilistic. Right? You’re saying, uh, it’s got a high enough probability that this is gonna occur. That I think that the price of this whatever asset class it is, that you’re, um, involved in, that the market doesn’t quite have this.

Right. Because I, I think the probability is high enough. I ought to be buying this, but it’s probabilistic, so it might be wrong, right? And also things just might change in the future. So write down what those things are in a very explicit way, and then have attached to that a pre-commitment as to what action you would take if you saw that.

So let me give you an example. Um, for example, from, if you like, a different type of thesis or like what we might do with like a value investor or something like that. So let’s just start with a simple thesis. Let’s imagine that my investment depends on a prediction that interest rates are gonna rise in the next six months.

So let’s just imagine that’s the case, right? Um, what I can do there is say what could occur in the future that would tell me that the interest rate environment isn’t actually what I was hoping for, and I ought to exit the investment. So it could be. If I see interest rates go down more than 25 Bs as an example, right?

Then in that case, maybe I have to sell as an example. Um, it could be things that actually drive interest rates, right? So, um, it could be that if I see some early signals that I think the Fed is gonna lower interest rates that can get out of the investment, right? Which might have to do with like how inflationary is the environment, is there a softening job market?

For example like that. So I can, I can see, I can start to think about what are the things that I might see in the future that would tell me that this core piece of my thesis that has to do with what’s happening with interest rates is, you know, now the probability is too low. Or maybe I’m actually observing them going down.

So like that’s one thing that you can do. Another thing we do is like with value investors, where you have a long hold bias, um, you get a lot of like short term overreaction to earnings. Reports, right? So what we do is we say, let’s get a lower bound and an upper bound within which the earnings report we’re, we’re gonna be pretty tolerant of it ’cause we’re not gonna think it changes anything.

And we decide that in advance because when you’re actually reacting to it in the moment, you’re not gonna be, that’s when you’re gonna be the least rational about it. So in advance we say, okay, this is what they’re projecting. Here’s the, the variance around that that we’re gonna tolerate. Then we know if earnings are above that range, that we have an action plan for that, which is probably gonna be to buy more, right?

It’s gonna be like, yay, we’re really happy. Um, and if earnings are below that, then there’s a whole bunch of things that we have to do, one of which might be sell, but a lot of it is to just look at other things that might be driving that, what’s happening in the actual environment is the environment re, you know, recessionary or so on and so forth, right?

We, we’ve already planned out what we’re gonna do in those, in those cases. So this kind of mental time travel where at some time, way in earlier you’re saying, if I observe these things occurring in the future, then I’m going to do these things. Right. You’re, you’re committing to that. Those, if thens actually really increases the chance that you’re gonna behave rationally when you see those signals in a way that you don’t.

If you allow that to happen without the pre pre-planning, and I’m sure that you’ve felt this yourself, you know, it’s like you get thesis creep, you know, all of a sudden no, well that’s not why I bought it. Or now it’s really cheap. Or these kinds of things that get people stuck in investments where from the outside looking in, you can see it’s very clear that they ought to be selling, uh, but they don’t because it’s really hard to make those decisions on the fly.

Yeah. You know, when you were talking about interest rates and, and such. It was got me thinking sort of about sort of the macro environment we’re in right now. And, and it’s interesting when I think about my own belief based on sort of what kind of some of the things you referenced, the job market and, and, um, essential political forces and the Trump administration going to the Fed.

And my own personal thesis is that interest rates are going down. And that they’re gonna figure out how to, you know, make the bond markets come down as well, maybe through quantitative easing, et cetera. So that’s like my thesis. Right. It’s interesting. Um, the, on the other hand, there’s this force of what happened with the markets, like, you know, in 21, 22, 23, where we took a beating in real estate, right?

And so you have this. I, I guess what I’m trying to get at is it’s hard sometimes to erase memory and fear and look rationally at the moment ahead of us and say, okay, so if I’m a rational investor and if this is what I truly believe, then maybe I should be buying right now instead of being worried about what happened in 22 and 23.

’cause that’s the past. I mean, how do you approach that? Uh, you know. How do you suggest approaching that for people? Yeah, so that’s a hard one. Um, so first of all, the past is actually important to understand, right? Because looking back at the past as an example is gonna tell you that, well, corrections are pretty common, right?

They’re not that odd. You know, it’s kind of interesting ’cause when people talk about 2008. They’ll often say like, oh, it was a Black Swan event. And I’m like, yeah, okay. There’s been like three, 2000 eights in like the last 20 years. Like how Black Swan is this, right? Yeah. Yeah. So I’m not saying that you shouldn’t, you shouldn’t look at the past, right?

But what you wanna do when you’re, when you’re looking at the past, um, I say, well, first of all, generally things go back to equilibrium, right? So if things seem really out of whack, they probably are. That doesn’t mean that you can time it in any. Don’t, please, I’m not telling you that. I’m just saying that you should probably say like, okay, there’s gonna be some sort of correction.

I don’t exactly know when it’s gonna happen, but it’s probably gonna happen. Um, and you know, and we’ve seen that several times where we get a big correction, so that can just sort of help you to understand like, okay, it goes up and then it corrects and then it, you know, but then when it corrects also it’s not gonna stay there, it will go back up like the markets recover.

Um, so that kind of stuff is actually really important when you’re looking back at, say, what you’re talking about like 2022 in terms of. It’s really important to understand and try to get a good look at what were the causal drivers of what happened then, and do tho those causal drivers also apply today.

So one of the things that we wanna understand is that things that happen don’t just happen by magic. There’s a cause of those things happening. And we wanna understand what those causes are so that we can figure out should I use that as a model for what’s going on today or not? And sometimes the answer is partly but partly not.

And then you have to interpolate, like you have to figure out how to blend that information. Like this is the same, but this is different. How do I think about what the influence of those different pieces might be on what the pricing might be? And that’s just part of good forecasting, right? Is to understand what those causal drivers are.

So that’s just kind of like that. What are we doing in terms of how do we use the past, right? Because we definitely wanna use it. We just wanna make sure that we’re thinking broad strokes, just in terms of there are corrections and then rebounds, and then that kind of stuff. But also just. Understanding that you can’t just say, oh, I’m scared because 2022 happened.

You have to say, well, wait. What were the underlying causes of 2022? Do do those things exist today? Um, and that also can help you predict that something like 2022 might happen when other people don’t see it, if you’re really thinking that way. So that’s number one. Number two is, um, when you have these quitting plans in place, it makes it a lot easier to go ahead and do it even if you’re scared, because it makes it less scary.

One of the things that we feel like when we decide to make a bet on a thesis, um, and we’re thinking about, well, wait, what, what if it’s like this? Or what if it’s like this or whatever is that we, we do have this sense that we get caught in those decisions, right? That we start something and that, uh, it’s very hard for us to get out of that position.

Yeah. The spec espec, especially if you’re not just dealing with stocks in a liquid market, right. If you’re dealing with, you know. Anything outside of just something that you can just sell on Schwab in 30 seconds. It’s, it’s a completely different animal. Well, even if, that’s the interesting thing. Even if you can sell it on Schwab in 30 seconds, you won’t.

So we, we do kind of sense that. So when we have these quitting plans in place ahead of time, um, then. It makes it easier for us to not be afraid to start it because we actually have plans in place, uh, to know that we’re gonna stop it earlier than we otherwise would’ve because we’re gonna be paying more attention when we’re in an illiquid market.

It doesn’t mean that you can’t quit because you can hedge. So one of the things that you can do is say, I can get into this, and if things start to look kind of bad. What would I then do to, to hedge that position? And so you can already have that in place. Then we could actually take that concept to de-risk now and say, well, what I should really do is I’m thinking about the probability of those two different worlds that might occur.

Right? A 2022 world, and then the world that you’re thinking is gonna happen, right? And say, what do I think the probability of those two things is? Right? And if you understand the probability combined with the payouts. Then you could actually do both things at once. That’s a really nice thing about financial markets.

And you could, let’s imagine that you think it’s, you know, more probable with an appropriate payoff, uh, what your thesis is, right? You can invest in that, but also put the hedge on at before, right? And you can say, I’m gonna do that. I’m gonna do it probability weighted, um, and have the hedge on. And then you still have quitting plans, which is, you’re gonna start to understand, as I see the world unfold.

What are the signals that would tell me to start reducing the hedge? What are the signals that would tell me to start increasing the hedge? Right? And then that makes it all a lot less scary because you’re already planning for that divergence that might occur in the future away from your thesis, but you’re also planning for the world starting to conform to your thesis as you learn new information.

So, um, the, the interesting thing is that like the decisions in the other direction are pretty hard too when you start making money on something and trying to figure out when to get out. Um, so the, this is the wonderful thing about kill criteria is that works for both. Yeah. Right. So, um, one of the things that happens on the winning side, uh, is that we actually tend to sell things too early.

And, uh, so why is that happening? So, uh, so we got these sort of opposing actions, right? If I’m losing, I will sell too late, and if I’m winning, I’ll sell too early. So this is actually goes way back to 1979, a very seminal paper from Daniel Kahneman and Amos Dki. It became one of the really key parts of, uh, something called prospect theory, um, which is what Daniel Kahneman won a Nobel Prize for.

So this is sort of the central thing that they found in their studies. They gave people the chance to take a loss or gamble, in other words, to, to continue in it with something or take a win or gamble. Um, so. Uh, so let’s, let me put this into concrete terms. So let’s imagine that you’ve won. I tell you, I’ll either, you can either take a hundred dollars, I’ll give you a hundred dollars, or you can flip a coin double or nothing.

Now, the expected value of those two things is the same. If I give you a hundred dollars, your expected value is a hundred dollars. If you flip a coin double or nothing, you’re gonna win 200 or zero each of those. Half the time the expected value is a hundred dollars. So there, and from that sense, from an expected value sense, they’re exactly the same.

The only difference is that one carries volatility with it and the other one doesn’t. So one is aho gain and one has volatility. So when you present people with that choice, they’re all like, what are you nuts? Give me the a hundred dollars. Why would I flip for it? Just gimme the a hundred bucks. But when you say, okay, you have to give me a hundred dollars.

You can flip double or nothing. Again, in both cases, the expected value is negative a hundred. It’s just one has gamble and the other doesn’t. Right? So when you say that to people, they’re like, oh, let’s flip. Okay. So that’s interesting. So what they wanna do when they’re in the gains is bring the volatility to zero.

Just give me my money. They just wanna get it. And when they’re in the losses, they wanna take the gamble, they wanna keep going. Now what’s interesting about that is that they’ll do it even when the expected value isn’t the same. So if I say to you, okay, I’m gonna give you a hundred dollars, or we can flip a coin and you can win 180, sorry.

Or you can win 220 or zero, now you’re making $10, right? That’s 10% return, right? So I say take the hundred. Let’s flip two 20 or zero. People still say no, even though the second bet is now more valuable, I can get a hundred, you know, I’m making, I’m making $10 on that. Right? On the losing side, let’s say that I say to you, okay, you can give me a hundred dollars, or we’ll flip it negative two 20 or zero.

That costs you $10 more, and you’ll say, let’s flip. So people will pay, they’ll give me $10 to take the money off the table when they’re winning, and they’ll give me $10 to keep the money on the table when they’re losing, right? So what is going on here, right? So this goes to this problem of people wanting to take the money when you have a gain on paper.

People want to realize that being. So what that means is that even when the expected value says no, you should stay, you should keep your money in this thing. They don’t want to because as long as they have the bet on they, they could lose the gains that are unrealized gains, they could lose those back and they don’t wanna do it.

That feels really awful to them. So they wanna get that money off the table super fast, and that’s what causes people to take wins off the table faster than they ought to. And on the flip side, when you have losses on paper, you wanna keep them on paper because as long as they’re on paper, you have a chance to get back to even.

And you want, you wanna keep that chance going even when the expected value is against you. Okay? So the kill criteria are helping you with that second problem, right? Which is, if you have losses on paper, just take them off the table so that you can take that capital and put it to use. It’s something that you’re gonna actually win at.

And don’t worry about the fact that you’re realizing those losses, because you don’t wanna keep that gamble on because you’re losing to it, right? So the kill criteria helping you with that, but they’re also helping you with the other problem. So, remember I said. With, at the value investor that I work with, we have a band.

Here’s the lower bound and upper bound for say, earnings. Um, within which you’re, you don’t care, okay? So that tops stops you from taking the wins off the table. And then if it goes above that band, we already know what we’re gonna do, right? So in some cases, right, if it goes above that band, there might be rebalancing that happens.

That has to do with portfolio dynamics and not with taking wins off the table. That’s a different reason. But we know, and it’s often gonna mean putting on more risk, right? It’s gonna mean things are more favorable than you thought or whatever. And if it goes below, um, you know, depending on what else is happening, we’ll take the money off the table.

So the nice thing about kill criteria is that they work in both directions. So they’ll actually make you be more rational about those decisions. About when do you keep the gamble on versus when do you take the money off the table. Let’s do a little exercise, if you don’t mind. Okay. And, um, because the, um, it makes me think about, so I, um, you know, I started talking on this show about my conviction of, uh, on Bitcoin in 2017.

And some people were smarter than me and actually went and bought a whole bunch of Bitcoin when it was very, you know, very inexpensive. And I, I have some, but. I have some people who are sitting on a lot of gains, a lot of gains, and there’s this question that kind of comes up for them now as we’re sort of hitting in.

We’ve got a hundred thousand dollars Bitcoin people buying this stuff when it was maybe four or $5,000. Right. Uh, they’re sitting on millions of dollars of gains and we’ve seen volatility in Bitcoin in the past. There’s an big, you know, we’re also seeing like a lot of. Information in terms of the institutionalization of this stuff, the, um, the, um, you know, nation states starting to adopt it and that kind of thing.

Now, somebody was sitting with those kinds of gains. Give me sort of a, and I, I’m not saying, telling you, asking you when to sell, but rather how do, how should someone approach this situation if they’ve got, you know, enormous gains and, but they still think they’re bullish. How would you suggest somebody start looking at that as a framework?

Well, first of all, I would wanna understand, I would hope that they had been explicit in some way about what their thesis was for why they bought it. Because what can happen, and I’m not saying this is true of the people that you’re talking about, is that the reason that you bought it is different than the reason it’s winning, right?

So I would wanna know, look, when you bought it at four or 5,000. Like, what was the reason? Were you buying it because you thought it would be disco correlated with the market? ’cause it’s not right? Would you? Well, well, does that, well, does that matter if, if you Well, if it does, it does. In the sense of, in that particular case, if my thesis was wrong, what I wanna say is, okay, I got lucky.

So now, so now I, I need to actually not just hold it because I have it, because maybe I actually don’t understand this asset class. Okay. So I might have a tendency, for example, in that situation to sell it, which just cleans the cognitive slate and then reexamine it once I’ve sold it. See, the problem is like doing the analysis when you actually hold the asset is gonna be actually kind of hard.

So I would wanna understand, do I understand this asset class? That would be really important. Okay. So as an example, we know that one of the drivers of what’s happening in crypto right now has to do with the specific attitudes and actions of the current administration. I’m guessing if you bought it in 2000 at at 4,000 or whatever, that wasn’t on your Bingo card.

So let’s imagine this world, and I’m not saying this, I’m, I’m not trying to give anybody investing advice, but let’s imagine a world where you said, I’m gonna buy Bitcoin because I think it’s going to be, uh, a good hedge against general market chaos. Um, and it’s gonna be, uh, disco, un disco correlated with like, uh, uh, interest rate.

Fluctuations. So let’s just imagine that that was your thing. So you were basically saying, this is gonna be good because I’m gonna hold equities, I have treasuries, I have, you know, all these different asset classes, and this is a different asset class that’s gonna work in a way that it’s gonna be a good addition to the portfolio because it won’t be really super correlated with the rest of the portfolio.

So let’s just imagine that that was your thesis. Well, does, does that feel like that thesis is correct? I mean, you know, again, not a Bitcoin expert, but I don’t think so. I think it tends to, I think as the market goes, Bitcoin tends to go Yeah, a little bit. A little bit, right? So if that were the case, I might, the, I, I would’ve set some band around correlation, right?

And a lower bound and an upper bound for how correlated is it is with other things. Um, because if that’s my thesis, and then if I’m actually not living in that band and it turns out to be more highly correlated, then I would, I would have a tendency to wanna sell it. And if it were, uh, less correlated, I might actually want more of it, right?

So I would actually be thinking that way. So let me just start with that. If it turns out that your thesis is wrong and that it’s one for different reasons, it doesn’t mean that you can’t have the asset. It just means that you need to do fresh work. One of the best ways to do fresh work is to sell it, right?

And so in my opinion, and again, this is just my opinion, that fresh cognitive slate is generally worth what worth whatever the transaction fee is, right? Like you, you should, I, I would gen generally say I would be willing to pay that transaction fee in order to create a clean cognitive slate so that now I can approach this.

Fresh ’cause I would wanna approach it fresh. So now let’s imagine that you approach it fresh, um, and you can do this and still hold the asset. I think it’s harder to do, but you can is to say, to really try to understand why is it doing well now, and then you have to make a bunch of forecasts, right? And this might include some kill criteria, which is, well, if those are the causal drivers of why it’s doing now, what do I think the probability is that that’s gonna change in the future?

Maybe I wanna then hedge against that, right? I might wanna say like, I wanna set up a hedge in case those things are occurring. And I certainly would wanna say, I would wanna go through the exercise of say, let’s imagine that there’s a, a change in the administration. Um, you know, so it’s 2028 and things are different.

Um, and Bitcoin has cratered. Why do I think that is? Or even don’t say the administration, just say it’s. Five years from now and Bitcoin has cratered why? And actually really run through that exercise of imagining why it is that this asset has cratered, right? And in there might be, there’s an administration change that isn’t as friendly to crypto or whatever, right?

That might be in there. So now having done that, you can say, okay, in those different worlds, what would I do? For each of those different worlds, like the, the things that I’m imagining might be occurring that would cause, cause, um, Bitcoin to crater looking back, I realized there were early signals that the world was gonna head in that direction.

What are they? And for any of those signals say what you’re gonna do about it, then I’m much more comfortable. Right? Then I’m like, okay, you’ve thought through this. Now you can do the other thing, which is imagine it’s five years from now and Bitcoin has quadrupled. Right. Why do I think that is what’s occurred in the world that’s caused that to happen?

What would I do in those different worlds? Looking back, I realized there were early signals that Bitcoin was gonna quadruple. What were they, when I see those signals, how am I gonna react to those things? Right? So I would want you to do that as well. That’s a particularly powerful thing to do if you have more than one person do it independently of each other, right?

Right. So you have, it’s called a pre-mortem is imagine the bad world, uh, a. Uh, a backcast is imagining the good world. It’s also called a pre parade. Um, and if you can have more than one person do that independently and then sort of compare notes that gets you to the best place and that, that gives you an action plan.

Last thing though, is that, um, everybody needs to decide for themselves what the value of the present day cash is, right? Versus the, you know, whatever the expected value of the bed is. Um, given risk. And so what I don’t want people to do is say, well, I’m positive expectancy, so I’m gonna keep the ba the bet on if there, for whatever reason in your own life, uh, there is a certain amount of value to getting some of that money off the table.

And sometimes to be honest, it’s just the pain of the swings is too much. So. I think people sort of have to decide that for themselves. Like I, I’m not somebody who says like, if those swings are too painful for you, and that what that generally means is that you don’t have enough financial cushion in terms of what sort of liquid or available to you.

Um, that what’s happening on a day-to-day basis with Bitcoin matters too much for what your. Net p and l, you know what your p and l is? I, I, I’m, I don’t mind people taking money off the table in that situation to get themselves in a situation where those daily swings don’t matter as much to them, and they can actually be more rational about the asset that they own.

Yeah. Interesting. Yeah. Annie, uh, thanks so much for being on the show today. The, the books again are thinking in bats and quit. How can we learn more about what you do? Well, you can read those books, which would be great. Um, I’m on lots of podcasts like this. And then the other thing is I would love for people to check out maven.com.

Um, maven.com is an online platform. It’s creators direct to consumers where you can take classes. I happen to teach on there. I’m actually teaching a cohort at the minute, and I do about three cohorts a year. Um, it’s, uh, spans over three weeks. It’s two sessions a week plus one office hour. Uh, and I teach sort of soup to nuts effective decision making on that platform.

It’s cohort driven. There’s an alumni group that still meets, and I’ve had lots and lots and lots of investors. Um, in that class, um, investors, uh, I think are naturally sort of attracted to what I do. Um, and so lot the, it’s one of the main groups of people that ends up in that class, but it’s maven.com and, um, I have a cohort running right now, but, um, you know, as soon as I finish a cohort, I open a new one that would start, you know, in a few months from then.

And so if people wanna check that out, that would be great. Um, and then the last thing is, um, I actually have a nonprofit that I co-founded. Called the Alliance for Decision Education. And what we’re trying to do is take some of these lessons, the kinds of stuff that we’ve talked about, uh, that I teach to adults, you know, that cognitive scientists and decision scientists really think about in the adult world and say, really what’s more important to teach to kids than decision making?

Seems like it’s more important than trigonometry. Um, and what we’re trying to do is bring decision education into every K through 12 classroom as an educational movement. And so I would love for people to check out the alliance. Yeah. Fantastic. Thanks so much for being on the show. Thank you so much for having me.

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Check it out for yourself by going to wealth formula banking.com. Again, that’s wealth formula banking.com. Welcome back to the show everyone. Hope you enjoyed it again. Yeah, really fascinating thing I think to think about, um, investing, uh, in this sort of more framework sort of way, right? Like, I think the thing that I, I like about what she’s talking about specifically are stop losses.

Um, you know, in certain situations I’ve had even, you know, with my own. Situation with real estate and that kind of thing. I’ve, I’ve had some situations where I had to sell early, uh, and take losses and, um, just know that, you know, you’ve stopped a hemorrhage or whatever and you’ve moved on other things.

You know, I think a wise man once said, you know, bury your losses quickly. Right. Uh, that’s an important thing to think about, especially when we’re moving into a high liquidity market from where we are right now. And, uh, you know, I, I think look at all the data in front of you, figure out what you’re gonna do.

Come up with a framework and stick to it. Um, well stick to it as long as you don’t have better information coming in, uh, in the meantime. Anyway, that’s it for me this week on Wealth Formula Podcast. This is Buck Joffrey, signing off.