Podcast: Avoiding investment pitfalls in 2024 with Caspar Berry

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[00:00:09.050] - David Brett

Caspar, a very warm welcome to the show. Good to see you on screen anyway. How are you?

[00:00:14.160] - Caspar Berry

Very good, thank you. How are you?

[00:00:15.440] - David Brett

Yeah, not too bad at all. Not too bad at all. Now, from your profile, it seems like you've done many things. Actor, producer, poker player, commentator, speaker. Have missed anything out?

[00:00:26.810] - Caspar Berry

No, most of those were a long time ago. It should be said speaker for the last 20 years or so. But tv commercials, director. Yeah. And sort of short film television director.

[00:00:39.310] - David Brett

Okay. And just from we got a lot of UK listeners and some of them might be of an age where they remember a program called Biker Grove. Apparently you were in that. Is that true?

[00:00:47.820] - Caspar Berry

They're really old. Yeah. I go back 34 years now to the first two series with Dec, but before Ant and that original. Yeah, he didn't come until series two.

[00:01:00.160] - David Brett

Before they became a partnership. Truly. It was some hard hitting stuff as well, as I remember from biker growth. They tackle some strong storylines.

[00:01:08.530] - Caspar Berry

About the blindness, obviously.

[00:01:10.150] - Caspar Berry

Yeah, well, in our 89, 90, it was really hard hitting and then they went down a couple of years. So a lot of biker Grove is quite sort of kiddie, but when it started, its intention was to be a sort of challenger for BGrange Hill, but the BBC wanted it to be a little. Okay.

[00:01:28.510] - David Brett

Okay. So for anyone that doesn't remember it or haven't seen it, by all means, google it. You could probably find it on the interweb somewhere.

[00:01:35.890] - Caspar Berry

It's on the youtubes.

[00:01:37.170] - David Brett

It's on the youtubes. Excellent. Check it out. It was very good. Okay. But we're not here to talk about that, unfortunately. We are here to talk, well, mainly based around your poker playing days, but certainly relationship with some of the stuff that you went through on poker playing days to what it might be to investors. So investors got this long year to look ahead and there's plenty of risks out there, as we saw from last year as well. I just want to start with the first question. How do you know when to take risks given whatever backdrop you're in? So on a poker playing days, you're sitting at your poker table. How do you know when to take a risk and when to stick or when to twist?

[00:02:14.170] - Caspar Berry

Okay, well, I'm going to answer that two ways, actually, because I think there's a more interesting answer in a way to why should we take risk generally. Right. And the answer to that question is when you want increased returns. Right. Because I'm a speaker talking about taking risk. I think some people sometimes interpret what I'm saying is you should always take risk. Right. And that's not true at all, of course. So, like, for example, I've had a number of people say to me over the years, you're telling us to take risk, but you've been a speaker now for 20 years. Now. There's two things to say. Yes, but that's because I did take risk every two years, did those things, other things that you said, screenwriter, director, actor, et cetera, entrepreneur. Until I found this thing that I love, right. And I'm very happy in this situation and love my job. And so why would I want to disrupt that? Do you know what I mean? Like, I don't want increased returns by all the intangibles that we judge our job. Now I'm always trying new things. I take a risk every time I go to a stage, believe me, because I can die.

[00:03:26.850] - Caspar Berry

But that's the reason why we take risk. And if you're not happy, if you are completely happy, then you don't need to take risk unless you go, well, life would be boring. And go, yeah, cool, life would be boring. So we always need to mix it up a little bit. So we always need to take some risk. Where I think companies are interesting, there's that great documentary, isn't it? The Corporation, that says that a company in law is a psychopath, right? Because it has a duty to shareholder to keep maximising returns. So technically, a company should never be happy. A company should never be content. So a company actually should always be taking risk, which is why I think they like athletes as speakers, because they're also always driving for more. As an athlete, even if you just won the gold, you've got to get better than the next Olympics because everyone else is. So that's the first thing why people take risk. And the second thing about poker, you talk about sticking and twisting. Obviously, that's blackjack is the first thing to say. But I mean, in poker, you should be playing if you think that that game has an opportunity to take risk.

[00:04:28.560] - Caspar Berry

That is what we call expectation positive, right? And that's where we come back to the calculation I showed in the presentation. I showed which many people watching this will be second nature to, but some it won't be. It's the calculation at the origin of the phrase the calculated risk. And basically, in poker, you should carry on playing, or you should take a risk with this hand. If you believe that the opportunity as calculated for risk with upsides, downsides and probabilities, is expectation positive, and that's when we should be taking risk in life, that's not always the case because it might be that the upside or the increased expectation is not worth the potential downside. In other words, you don't want that enough.

[00:05:09.280] - David Brett

Practically, how are you calculating those probabilities and those odds when you're taking those risks?

[00:05:17.050] - Caspar Berry

In poker? I guess one answer to that is, as well as possible, right, in the presentation, I showed a very simple situation where we had an upside of 4000. That's in the middle of the table. That's what we can win, a downside of 400. And I constructed a situation where we had a 25% chance of success. Now, technically, by the way, in that poker situation, I didn't say this in the presentation, but that's a very rare situation, because someone's giving you a return on your investment, they're 175%, which is obviously huge. And therefore, the person that's betting the 400 is making a mistake in that situation. But we're getting that calculation by multiplying our upside by 25%. So 25% is 4000 is 1000, our downside by 75%. So 75% of 400 is. -300 that creates an overall expectation of our long term upside plus our long term downside, which is 1000 -300 which equals 700. Right? So that's the basis of that calculation. Now, poker players didn't make up that calculation. Again, I know I'm talking to a very experienced audience of risk takers here. It's taken from the risk reward analysis that is basically born of Fermat and Pascal's language of probability.

[00:06:31.060] - Caspar Berry

First, actually given to us by Gerolamo Cardano, a renaissance italian mathematician. And all we did in poker is just nick a little bit of it. And that calculation forms the basis of insurance. It's like, that's the true value of the policy, so I'm going to sell you it for that. Forms the basis of credit. Forms the basis of the valuation of anything under uncertainty. And when I say do it as well as possible, what I mean is that there are some situations in poker, like the hypothetical but perfectly real situation that I've relayed there, where it's calculable, and even sometimes where the probability is what you might call semi objective, right? But the second thing is. But most of the time in poker, we might have a decision tree that goes out to 64 different points, right? Not just two upside and downside, but 64 different ones. Like, what if we call and they raise? What if we call and they call? What if we raise and they fold? What if we raise and they re raise? Do you what know? I mean, so there's all sorts of different possibilities and although there are some players at the highest levels of the game doing that calculation live and making decisions accordingly.

[00:07:33.460] - Caspar Berry

It's too far beyond most of us mortals right to do it. And then the second problem is, as Bruno di Fenetti, another italian mathematician, says in his two volume maestro work on the subject of probability, there is no such thing as probability, right? Even the toss of a coin is a synthetic probability. Because what if it's brilliantly relayed in Nassim Taleb's black swan? Right? If a coin comes down heads 40 times in a row, is that a statistical outlier, or is it a two headed coin? Right. So even logical probabilities in the real world are still subjective, right? And so all probabilities are subject to our assessments based on our experiences and based on what we know. And everyone knows different things about a situation. So you do that calculation as best you can, but don't be deluded into thinking that the number you have on the bottom line is real or objective, because it's not.

[00:08:34.450] - David Brett

We talk about there's lots of risk coming out for the coming year ahead, and investors probably poker players as well. When the going's good, they're notoriously greedy. When the going's bad, they're notoriously fearful. How do you know when enough is enough? When things are going well, how do you know enough is enough and to take your profits, or when things are going badly to cut your losses?

[00:08:54.510] - Caspar Berry

So you might have a cultural reason for that. Like you might have had a target given to you by a boss or your team or what have you, in which case you stop for that reason. Interesting. We had this question during the session itself, and it's not important not to confuse two things, right. Because sometimes people talk about stop loss limits with respect to gambling, by which I mean roulette, blackjack, for gambling games in a casino where you pretty much always have a negative expectation and it's part of a longer point, but the longer is that it's all bunkem. It doesn't matter when you stop playing roulette, it doesn't matter whether you're $200 down or $400 up or whatever. If you carry on playing roulette, it's still all one session. The wheel is going to take 2.7% or 5.4% of every dollar you put down. Right? So again, it comes back to, culturally, when do you feel like this roulette session is now no longer enjoyable? Like, you've lost too much money and you should go to bed. Okay, so that's when you should stop playing roulette. When you should stop playing poker, again, could be cultural, as I said in the session, like, you might have just had enough, right?

[00:10:05.990] - Caspar Berry

You might want to go and have dinner with someone. There might also be lots of different things that make it now a negative expectation for you personally because you're making bad decisions. What might cause that? You've lost too much money, you're hurting, you're emotionally affected, you're tired, you don't want to play with these particular people because one of them sends you on tilt, you don't like them, all sorts of things like that. But technically, if all of that is put to one side in poker, you should carry on playing as long as you have a positive expectation. And you might be 50 big blinds down, right? You might be a lot of money down. If you know that these four players are bad players and they're donating to the game, you should absolutely carry on sitting there and playing as long as, again, you're not tired or emotionally affected or what have you. And that's something if I can try and sum that up. It's important not to take ideas which are already wrong for gambling, right? Stop loss. We're knowing when to stop, right? If you want to make money in gambling, don't gamble because you're not going to.

[00:11:07.680] - Caspar Berry

You might aberrationally in the short term, but in the long term, it doesn't matter when you start and stop, you have a negative expectation every time you play roulette. So don't take those bad ideas and apply them to positive expectation situations, because it's the expectation that dictates whether you should carry on playing, not how long you've been doing it or how much you're up or down at the time.

[00:11:25.920] - David Brett

So if you relate that to investment, if you've done your homework and you truly believe that company is a good company, do you think you should keep investing in them?

[00:11:35.760] - Caspar Berry

You see, again, I'm going to come back to the cultural problems, right? One of the things that Kahneman and Tversky won their Nobel Prize for in the early two thousands, I think, was the s shaped utility curve. Now, the s shape utility curve is really interesting for a lot of trading rooms, right? It explains human nature in a lot of situations. And in fact, in some ways it's actually interestingly different to what you said earlier on, which is when people get greedy and fearful. Because in a lot of trading rooms, people will bank a profit, right? Because they want to see lots of green numbers, but they'll hold on to losses, red numbers, because all they want is for them to become green. Right. The s shape utility curve explains that, because once we've got our green profit, more green profit, which might emanate from a positive expectation, is not going to make us feel that much better because it's a green number and more red loss that might emanate from holding on to a negative expectation doesn't really affect us because it's still a red number. Right. And so we actually become greedy and fearful in the opposite direction there because we just want to bank wins.

[00:12:44.850] - Caspar Berry

That's like leaving a poker room when you're up because you want to be able to put a green tick on that day of the calendar, but it's mental because you're not maximising expectation. So theoretically it's as pure as that. But I'm not trying to override whatever very sensible cultural, what's the word, sort of buffers that a trading room or an organisation or a team or a boss may bring into that for two reasons. A, because the culture is king, right. Certainly what your boss says, is king. And secondly, because some of those cultures are built up to try and prevent other mistakes. The taking of risk when the expectation is low because someone feels bulletproof, because they've had a lot of wins in the past, right. And their part of the theory is to stop when you're ahead and good. There's a brilliant book called the hour between Dog and Wolf by Dr. John Coates, which talks about testosterone in this process, that testosterone is both a reward for and an instigator of risk taking. And can precipitate what may start off as virtuous but become vicious circles, because gains turn into inappropriate risk and cultures have instigated buffers to prevent that.

[00:14:06.380] - Caspar Berry

And I'm not trying to override those at all. But the theory is pretty clear that when the expectation is positive, we should be taking that risk. But in practice, there are all sorts of reasons why we shouldn't do that, and they're fine.

[00:14:17.250] - David Brett

So with everything that's going on, I mean, how do investors in particular overcome, you've mentioned quite a lot of psychological biases there. How do they overcome those biases to potentially, hopefully make the right decision?

[00:14:28.640] - Caspar Berry

Yeah. Again, a poker player does have a certain luxury here, which is, and by the way, not all poker players. I was going to say we're lone wolves, right? Because a lot of poker players these days, particularly the hardest limits, are backed. They have backers. And what you want is a backer that thinks long term too. Again, what I said during the session was that we want to try and map our emotions onto our results. So we do want some pleasure from the upside because that will motivate us to take good risks and upsides of the reward for that. And we do want some pain for downsides, right? Otherwise we go around touching hot saucepans all the time. So some emotional response is a good thing, but we want it to be proportionate. So greed is a disproportionate upside and fear is a disproportionate downside. So that's the first thing. But the second thing, the thing that a poker player can do that again, we can't always culturally do, is just think as long term as possible. I mean, ideally you want to be thinking over the infinite time period, right? My simple analogy for that is, let's say you're a salesman and you've got two piles of leads and one pile of leads, the actual value of each sale.

[00:15:40.260] - Caspar Berry

So the expectation is very low, but you got a very high expectation of someone saying yes. Then you've got another pile of leads where the potential sale value is huge, but it's very hit and miss. Now if you've got a sales director who's not going to check over you for a quarter, then you're going to go to the high value leads, right? Because you've got a time period there over which to hit some sort of expectation law of large numbers to kick in. If you've got a sales director who are a boss or who's looking over you at the end of every day, then you're going to go for the low value leads, right? It's as simple as that. I honestly think that the greatest company that I know on the planet, a big company corporation, not startup, where they inculcate that mindset quite a lot, but the one that's maintained it through trillion dollar worth is Google. They just understand from day one that if you cut open Google like a stick of rock inside that company, you've got hundreds of thousands of decision makers and decisions being made every day. And they, we want them all to be incentivised to maximise ROI, not results at the end of every 8 hours, basically.

[00:16:52.210] - Caspar Berry

And that's how we should be motivating and judging people who make any investments, either coalface money investments or the more intangible investments of business on a daily basis.

[00:17:09.450] - David Brett

Well, you mentioned Google there, and there's an entity we do need to throw into the mix here, and that's AI. How do you think that might be changing the game, because in the past, again, poker players, and from an investment point of view, you always thought you were betting, not betting, you were trading against humans. I mean, electronic trading systems have been in use in the investment industry for a very long time now. But now, throw in AI, how do you think that might change things?

[00:17:37.920] - Caspar Berry

Moving massive, isn't it? In lots of ways that some are quite easy to see and about which we might be wrong, and some of which are quite hard to see. Again, during the session, we had brilliant questions. During the session, someone mentioned AI, and I said, in a slightly long winded way, that it's going to kill online poker, ultimately, in a way that bots never did. Right? Because a couple of things about bots. Number one, they have to be programmed, so the algorithms have to be good, okay? And number two? Number two, it was okay if you had four bots at a table, because in some ways, they actually provide a level of ballast. Like if you've got four or five pros at a table, that's not a bad thing, because you're all basically picking on what you want is three or four tourists who are donating. Okay? So bots never really cause that much of a problem. AI in poker is going to kill the game, I think, above a certain level. Below which it's just not worth people's bother, right? There's better ways of directing AI than low limit poker or even mid limit poker.

[00:18:41.330] - Caspar Berry

But above a certain limit is going to kill it, because after 3 trillion hands, these blank slate, just machine learnt, neural network based decision makers are going to make the best possible decisions. They are already better than human decision makers. Now, if we apply that to the markets, look, this is my belief of markets, right, which is all markets tend to want efficiency. But the two caveats to that are, the period of time in which it takes to get there usually leaves a lag, which might be a couple of minutes, or it might be several years of inefficiency to exploit. Okay? And the second thing is, while poker is a zero sum game, in fact, it's a slight negative sum game, because the poker site or the casino is taking a small vig of every hand, or the tournament take or whatever, markets in general, I think, what's his name? Benoit Mandelbrot calculates it at about a 6.67% average return if you're on mass, all the trades made by big company for ten years. Okay? So it might tend toward efficiency, but if the efficient return is 6.67%, then that's pretty good anyway, right?

[00:19:53.070] - Caspar Berry

But AI surely is going to expedite the time frame that that efficiency has reached from minutes to microseconds or from years to days, because it's just a way of disseminating perfect information. I mean, the promise of AI in the long term is that Her, I think, is a brilliant, it's a film called her with Jaoquin Phoenix, is a brilliant model for where AI will go. And you have an earpiece and you have a screen, right? And this thing is the best doctor on the planet, and we all have as much access to it as we want to because it's treating billions of patients at the same time and it's read every single medical journal. And so if you're Bill Gates, you can't get a better doctor than this. It's not right there yet, and now. But that's the promise of this. It's the best lawyer on the planet, it's the best joke teller on the planet, and therefore, in theory, it will be the best trader on the planet, right? Why wouldn't it be? If that's the access to the perfect information that we will have, I get that there will be a certain time reward for the kind of split microseconds that the black boxes can make.

[00:21:15.340] - Caspar Berry

But beyond that, that kind of democratisation of knowledge, which started with Google, as you said, but will reach its apotheosis with AI. I don't see where our edge in any market is going to be as a result of that. And it's not just poker, and it's not just know, take my work. My work is teaching people. And what happened with Google was, it was amazing. We all got access to this perfect information. So if you wanted to create a course on risk taking or learning French, you had access to the information that could create that course. But with AI, it will create the course. Right, so where's the edge that the course creator has in that? Where's the edge that any creator of information has when it's not just access to perfect information, but perfect analysis and synthesis of that information? I don't see where that goes and I'll be interested to experience it.

[00:22:08.740] - David Brett

Yeah, I suspect we'll find out sooner rather than later on that, given the speed with which everything's moving. So, just to sum all that up, if you were to give our listeners three tips for the coming year ahead, they're going into their trading in terms of their biases, how they might want to view things. What are the best three tips you might be able to offer them?

[00:22:26.350] - Caspar Berry

Yeah, great. So, I mean, always think about future expectation. Don't succumb to sunk costs bias. It's not about how much we've put in. It's about what the expectation is. Try and think as long term as possible. Again, you'll have cultural constraints to doing that, but probably too late in the day now for me to tell a little story, but there's a little story that I tell that I think illustrates. It's a true story about a CEO of a company we all know. And the point is that even when you get to be CEO, people still tell you what you should do and how you should think and all the rest of it. And if you want to have the space to make decisions in your way, you have to fight for that. You're never going to get to a point where, oh, I can just do what I want now. So try and fight for the space to think as long term as possible. And then the third thing is something we haven't really mentioned yet. But again, I talk about in presentations, which is Tetlock's study about political judgment and the slightly counterintuitive finding that the people who are most humble at the point of making their predictions about the future tend to be the most successful.

[00:23:28.440] - Caspar Berry

So the people who regard it as very difficult respect the size of the task, try and get as much data and information as possible in order to make their decisions, rather than going, yeah, I've been trading for 20 years now. I've got this licked because the black swans will always surprise us. And I've got a final little tip, I think, about black swans, actually, which is that they don't come from extrapolation of data and lines, because everyone watching this will have more data than most people out there in this slightly just pre AI age. And so I actually believe there's an edge to be had from using our intuition and trusting our feelings and sensations beyond the data. And I think that, actually, that explains some of Tetlock's findings, that people who were successful couldn't necessarily put their feelings into words. I think that sometimes it's good to look at the state of geopolitics at any given time and just feel how the future might be. And if that involves a big upturn, then have some faith in that feeling, because there's reasons that we have those feelings, ultimately.

[00:24:37.420] - David Brett

Casper, some very sage advice. Hopefully, our listeners can go and take that away and hopefully look forward to a positive new year. Thanks so much for joining us. It's been a pleasure to speak to you.

[00:24:47.210] - Caspar Berry

Thank you.

[00:24:47.840] - David Brett

That's very. Thanks so much.