The Derivative - Trends, Tall Heads, and Transformations with Transtrend’s Harold de Boer

Episode Date: April 3, 2025

Dive into the fascinating world of trend following with Jeff Malec and one of the GOATs:  Harold de Boer, a pioneering systematic trader who transformed his life path from a Dutch dairy farm into the sophisticated global investment firm Transtrend. In this episode, Harold shares insights into the evolution of trend following, discussing how understanding market trends is similar to understanding herd behavior, navigating complex market correlations, and maintaining resilience during challenging periods. Learn about the nuanced approach to trading across hundreds of markets, the importance of diversification, and why trend following remains a dynamic and adaptive investment strategy. With humor, historical perspective, and deep expertise, Harold reveals the art and science behind successful systematic trading. - Don’t miss a particular riveting segment at the end of this discussion on US cinema at its best - SEND IT!Chapters:00:00-00:50 = Intro00:51-03:23= Lessons from the Pasture03:24-15:09= Rotterdam and the Netherlands: A Brief Introduction15:10-37:13= Market Diversification and the Evolution of Trend Following37:14-49:00=Navigating Market Complexity: Filters, Risks, and Trend Following Innovation49:01-01:03:59= Resilience and Adaptation: Surviving Trend Following Drawdowns01:04:00-01:10:59= Cinematic Insights: A Coen brother’s tributeFrom the episode:The Coffee Trader (Book)Fat tails and tall heads blog post: https://www.rcmalternatives.com/2013/02/fat-tails-and-tall-heads/Advanced Hedge Fund Replication with the Top Down – riding diverse ETF modeling flows with DBi’s Andrew BeerTrading Movies blog postFollow along with Harold and Transtrend on LinkedIn and be sure to check out their website for more information at transtrend.com/enDon't forget to subscribe to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Derivative⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, follow us on Twitter at⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@rcmAlts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and our host Jeff at⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@AttainCap2⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, or⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , and⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠sign-up for our blog digest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.Disclaimer: This podcast is provided for informational purposes only and should not be relied upon as legal, business, or tax advice. All opinions expressed by podcast participants are solely their own opinions and do not necessarily reflect the opinions of RCM Alternatives, their affiliates, or companies featured. Due to industry regulations, participants on this podcast are instructed not to make specific trade recommendations, nor reference past or potential profits. And listeners are reminded that managed futures, commodity trading, and other alternative investments are complex and carry a risk of substantial losses. As such, they are not suitable for all investors. For more information, visit⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.rcmalternatives.com/disclaimer⁠

Any strategy goes wrong if you leave your strategy when it's not working for a while. Unless you have a good reason that the strategy should be adapted, but adapting a strategy should not be dependent on, oh it has not been working for a while, adapting a strategy because you see something is happening in the world and you have to adapt for that. So adaptation is something you constantly have to do, but if you start to make strange moves it's not so wise. Welcome to the derivative by RCM Alternatives. Send it! Harold, how are you? I'm okay. Just okay?

Oh, it's great. In Errol's room, you see out of the window here. So you saw what nice sunshine we have. Exactly. Better than my rainy Chicago today. I was hoping you were going to wear the wooden bow tie in some of your marketing materials. Is that actual wood in that picture? Yeah, but they told me that this was going to be a podcast. My wife also wanted me to wear proper clothes.

I said I can do it naked because it's just a podcast. That's an actual wood bow tie. You wear it around? No, not that often. Just for the pictures. It's a real one, but I'm not wearing it that often. And give me, I've never been to Rotterdam, much less the Netherlands in general. So give us the quick lowdown on what's going on over there,

what we should look for when we visit. We say in the Netherlands we have three big cities. We have Amsterdam, we have Den Haag, and we have Rotterdam. And Rotterdam is where the money is made because here's the big harbor, the largest harbor of Europe. In Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have the Danube, we have because that's where the government is. And Amsterdam is where the money is spent. That's where tourists go. I love it. You ever read those books,

The Coffee Trader? There were a few of them. Yeah, it's a very good one. It plays partly in the Netherlands, partly in England. It's a great book. Yeah, I think there was a series of three of them, but yeah, that was very interesting. It was touching on some ancient futures trading a little bit too, right?

Yeah, yeah. It gets spooky. The car had to fly. He fled from London because he had done something wrong and then he ended up in the Netherlands in the, what was it? It was in the 17th century, I think it played. It's a great book. Yeah, we'll put a-

It was a scary episode where the coffee all the way was taken and there was... They should make a movie of it. Right. Let's produce it. We'll put the link to that in the show notes. So let's start. Tell us kind of your background, very well known, but let's hear it for our listeners what your background is and how you got into this crazy game. All started with writing a paper? It started with, yes, kind of. I was born on a farm in Drenthe, northern part of the Netherlands, dairy farms.

There were four sons and every dairy farmer wants one of their sons being the next farmer. The whole family was thinking that I was going to be the one, but at school I was very good in mathematics and I was then selected to be in the Dutch team for the international mathematical Olympiad. And then somehow I wasn't allowed to become a

farmer then. So I kind of had to study mathematics, which is a great study as well. Were you a family farmer? Yeah, my parents always told me you can study as long as you want and ultimately you will become a farmer. My name is the farmer anyway, so it's happy. But then when I was going to finish my study mathematics, the professor told me that I should find a real problem outside. So I wrote some letters to firms that did something with mathematics and I saw this crane trading company that wanted to do some research in futures.

I also saw a dairy factory that had a project. The project for the dairy factory seemed very good to me and I was thinking about when I grow up, I'm going to do that as a job. And since I know nothing about futures, let's do that to finish my study. So I ended up doing that and that the research project that ultimately became transparent and I'm still not grown up and working for the dairy factory. You might still pivot back to the dairy. My eldest brother took over the farm and he recently decided to stop and it will not

be continued anymore. So that's the end of the family business. No one knows yet, so don't broadcast this. Breaking news. Well you have a new family business. It's doing quite well soon. Yep. This is a different business. It's also great. And it's in essence, not much difference

because cows are herd animals and behave like that and people are not much difference. And to understand economy, you learn much more by watching cows than by watching dogs. Really? All right. They'll herd, they'll move together? Yeah, they really do.

And you also see some of the key principles in cow herds are really applicable to human. Really? All right. Don't tell the human because they don't want to be compared with the parents. How many cattle did you have up there? How many? Wouldn't call them cattle, I guess. You weren't getting the meat, but how many dairy cows did you have up there? How many, you wouldn't call them cattle, I guess. You weren't getting the meat, but how many dairy cows did you have?

No, it was about milking. So it was dairy cows. And when I was younger, my father was milking 60 and later on it became more than 100. Wow. For that standard, it's rather a larger side. For US standards, it's a very small firm I would expect. Yeah. Did you ever mess around with milk futures? Not in those periods, no, because the European way of handling risks in agriculture markets

was long term be completely different from the US way. This is a very interesting thing if you look around the world how essential agricultural commodities are because agricultural commodities is of course what we are all eating. I think it's the most essential commodities there are. We can do without Bitcoin, but we cannot do without milk. Yeah. And certainly not without meat, although some people think so, and certainly not without wheat, so we need all these markets. And internationally, there have been very many different experiments

to find a way to feed all people. So the Russian man, communist man, they did something. The result was a lot of people starving from that because they treated it wrong. The Chinese did something like that. It also ended up in many people dying. In Europe after the Second World War, we had this whole experiment of building up and promising prices to farmers, which was a big success for the farming industry. It paid my study for instance. But ultimately it ended up with having loads of butter

that had to be dropped somewhere, leading to people dying in Africa. And the US systems of futures markets, and starting around 1900, I really believe that's the most successful system. Really? All right. We'll take it.

It's not a coincidence that futures markets trading, as we all know them right now, started with these agricultural markets. It didn't start with oil markets. It only starts to do oil trading when they made a mess out of union trading and NIMAC had to do something but so they had no alternative but the the agricultural markets are at the basis of of the whole futures trading and to really understand futures trading you have to understand the agricultural markets I believe. Couldn't agree more I've always said they should be called nows,

N-O-W, nows not futures, because back then the farmer wanted to get paid now right for what he was going to produce in the future right. If I talk to my neighbor, I talk to people they're like oh you're betting on the future price of stuff, like not really, we're kind of betting on the price now of what we'll produce in the future, not the future price. Yeah, but it's easy to go a step further because it's a price discovery process. So this whole element of if there's a shortage, you want to have more production. But once farmers have seeded what they have seeded, they cannot all of a sudden decide, okay, now, no, no, probably I don't want the cord, now let's make it into potatoes. You cannot do it anymore.

You have to do that on forehand. So this whole price discovery process has to start before they start seeding. And that's the great thing with futures markets. It's this whole process of on the long term starting this price discovery process that works great with with agriculture markets. It's a little bit more difficult with fish but it can be done very well with agriculture futures and that's that's really become a success. Now are you an accidental historian? You've learned this along the way or is that was that an

interest of yours also back in the day? I always liked it, it's I'm following these things and I To to understand the now and to understand the future it helps to look back Yeah Um, we just did a podcast. I'm gonna forget the details, but there was future first futures market was actually in japan or the Underpinnings of it with race. I believe yeah Um, so back to that paper, what was the paper about? So you did it for the grain trading company? Yeah, it was the grain trading company. Was that a big like Cargill or someone or was it? No, no, it was a Nidera company was called. It was an international corporation. This N was

from the Netherlands and the A from Argentina and the D from Georgia. And I think they were all around the world, but they were mainly active in the vegetable oils. My paper was my research project was on the relationship between feed, so corn and soy, soybean meal, and hogs and cattle. People that learn econometrics right now, they learn about cointegration and it's a standard thing, but cointegration at that moment was something completely new. It was to be one of the first ones applying it to futures markets.

And it was a very, well, a very educative project as well to understand how it can be used and also how it should not be used. And what was your big takeaway? Like trend following became the takeaway or there was steps in between there. No, no, no because In this project we were looking at different ways my project con digression was something that would really Be applied normally in some kind of What is this called you buy one that's a little little bit higher and lower and sell the higher ones.

So it's arbitrage kind of strategy. But my conclusion was that it can be nice, but you cannot do it very massively in much different markets at the same time. And if you don't do that, you end up in a situation that once the position is going against you, you have to make a position even larger to ultimately make a profit. But that would be very extreme, very risky in the extreme.

Anti-Martin down. And that is typically what the LTCM later on did. So that's just the way we didn't want to go. There was also another person was working on fundamental research with agriculture. I've done that also myself and we had done a very good trade in that, in which we by looking at counting the number of pigs being born and looking what has happened on the fields have more a fundamental model of explaining this. We had some very nice traits by doing that and paid our research applying that, but that

also was something that was not very scalable. So that's also why we didn't really continue with that one. Another route was doing in the traditional technical analysis with head and shoulders and triangles and so on. It was very funny and you can have nice talks about it, but it wasn't very well applicable in by using it, doing it with computers because that was around 1990 was the period in which of course computers were really growing and becoming available for not that much money as before. And the traditional way of technical analysis in which you use a pencil and a line didn't translate as easy in making it programmable.

Makes it easier to make those nice lines so you can kind of fudge it a little and move the slope a little. Yeah. It's perfect. Nowadays with pattern recognition models, you would kind of do, could do that again, make the head and shoulders and so on. And then you could do it more in a technical way.

But in that period, that wasn't the right direction to choose. So that's why we ended up with having trend following models, building them themselves. And we saw that the biggest advantage, and that was our lesson, is that you can apply that in many more markets at the same time. And all the other ways was much more difficult to apply it in many more markets. So let's dive into that. When you started, how many markets?

50 or something? Well, we had some discussion because at that moment, mother company were agricultural traders. They only did agricultural markets. They had done a small experiment a few years before that in stock markets. Well, if you count well, a few years before 1989 was 1987 and they had a better experience with this. So they didn't want to go in that direction. So we had to convince them to do it outside the commodity area.

So initially they would like to have done it only within the commodities area and we traded our home markets where Palmoil of course, our mother company was one of the largest traders in the world in Palmoil, Oats, Flexseed we did. These were markets without discussion, but when we wanted to do the DMARC versus the dollar that had more discussion and the S&P 500 and the NASDAQ later on was a big discussion because there were very strange markets to them. But we did, we soon added all of those and it became a financial markets included portfolio. But you're one of the now largest, right?

It's 700, what's the number now? Yeah, it's something like that. It's not that relevant how many you do. I look, you can say if someone trading the S&P 500 can also say that he's trading 500. Yeah, yeah. So it's, if you trade 500 markets, you have not 500 different trends. And what it's all about how many different trends are we really looking at. But trading all these different markets can help in being active at one moment in which markets. So that helps. And so classic example of that is instead of just trading the 30 year

bond, I'm trading two, five, seven, 10, 30. Right? We, uh, the markets are the, no, no. The markets. Yeah. Yeah. I mean, maybe that's a bad example because you have the yield curve and yada yada. Yeah.

We trade, yeah. We trade yield curve things. We, we, we trade all kinds of synthetic markets and we combine one market with another market and look at this combined trend. another market and look at this combined trend. But it's not that we want to trade as many as possible markets, but we want to be invested in different trends. Well, or that you need different markets, but two different markets are not necessarily the same, they're different trends, so it's more than that. And having many markets also doesn't really help if you're not sizable investors in all of them. So you can see probably

a lot about Sunflower, for instance, when people talk about alternative investment programs, and then there's the story about Sunflower. Well, Sun sunflower is a nice market, but if you make $1 million a year in sunflower, you're a huge trader in that market. So that's never gonna really count. It's a very small market. So that doesn't really turn the needle. Which I was gonna ask like something like cocoa, right? How can you, if you have 700 markets,

I'm using air quotes on the pile, 700 markets, if that's just quotes on the pile, 700 markets, if that's just getting one seven hundredth of the risk budget, how can it make enough money to capture that huge trend? That's why you should not do one seven hundredth to every one of them. The more markets are different, so that, let's say, many people think that trend following is mainly about when to buy and when to sell an individual market, but that's what doesn't make a difference. The difference is how can you make sure that when there is a big trend in this example,

cocoa, that you're sizable invested in that. Most of the actions we do is not about getting in or out of a trend in a certain market, but to make sure that we are sizable in the area where something seems to happen. These are the losses part of our trading activity stems from that. And so you're looking more less than 700 markets and more we have a hundred independent bets, if you will. Yeah, well.

I don't know what the number is, but some other number. Let's say if you are invested in 10 really different trends, really different trends, that's a lot. Yeah. Okay. Yeah. But sometimes, let's say, technology stocks and energy stocks are the same trends, and sometimes they are completely different trends. So the number of different trends is not always the same as the number of different markets.

And which market are in the same trend can also be different from time to time. And so that you're what do you say the average number of independent trends per year is only something like two or three? The number of trends that really continue. Nah, you have to, there is also these more and more local trends that you can participate in and that continue to be local. Let's say cocoa in itself is a nice example because it's a pretty local trend and it's sizable enough, but there's also trends like that in so much smaller markets that you can participate in.

But let's say if you would trade in, still would trade in Turkey, you have some different trends than you have in other markets. And back to your synthetic market. So if I have two independent markets and then the combo is a third synthetic market. No? synthetic market? No. Let's say sometimes you do... A nice example is cordon and soybeans.

Nice to be combined because the same farmer can on the same field grow either one or the other. So it's a period that the farmer has to choose between one or the other. Cordon is essentially for the energy for the cows and the soybean meal is for the protein for the cows. So what's the demand side for? Since they are growing in the same area, if there is a drought in one, on one field, there will be a drought on the other field as well.

They're growing the same period as well. on one field, it will be drawn on the other field as well, they grow in the same period as well. Meaning that if there is a trend towards more need for protein, you can just look at the soybean meal, but you can also do soybean meal versus corn because then you can see the same soybean trend, but it's less sensitive to the weather developments. Because you take that side out, because both of them are sensitive to the same weather. So that way you can... It'd be long meals, short corn in that example. In that case, yeah. Yeah. So you're hedging out, got it, you're hedging out the field risk,

if you will, and just isolating the protein. Yeah. So that's the kind of synthetics we're looking at. It's not about, we're not trading crude brand versus crude light, for instance, that doesn't make any sense to us because that's a kind of traditional arbitrage thing that's a completely different strategy. But- And not like cocoa and Japanese yen or something? Like no-

No, no, we do combine commodities with currencies if we specifically, if we don't want too much of a currency risk. So since most of the commodities in the world are expressed in the US dollar, wanting, let's say if there is an inflationary environment in which you are long commodities, we of course want to be long commodities, but that doesn't mean that we necessarily want to be so much short dollar. Yeah. It has nothing to do with the dollar in that case. Well, if you trade all these commodities only against the dollar, you end up with a large short dollar position. That might not be the trend at that moment. So then it's better to trade commodities also against other

currencies. Which might not have their trending going on at the same time. But so how does that work if those trends, your long the dollar, short the foreign currencies on their own, own trends, but then you have this scenario where you don't want that exposure? Yeah, no. So that's why we constantly have to look. It's all netted. It's all, you know, portfolio is something getting too large. So if we have too much of a long dollar concentration, we have to bring that down if the long dollar risk gets too high for instance.

And you can do that by still being short commodities, but being them short versus something else or other ways. But it's always a nice thing that you can choose how you want to be invested. Using all these kinds of synthetics can help in getting sizable enough more different positions without having one or two isolated risks that are getting too large. And then back in 2009, 2010, it was kind of that it's all just one risk off risk on trade. So how did things, how did you guys handle that and think about that? This would have seemed to have helped in that scenario a bit, right?

Yeah. Well, we had to. Or did this come out of that environment? Now stepwise, let's say something really happened in that period or since that period. The first years we were trading, if you were trading, let's say, bonds or soybeans or so, these were really different markets. And these were markets in the sense that, let's say, the commodity traders were only looking at commodity price and only news they were seeing, commodity news.

There were no headlines that brought all these things together. Over the years when the use of social media and news flows, for instance through Reuters and so on, became much more centralized, all people are aware of the same thing and tend to watch at the same thing. So a nice example is the credit crisis 2007. It started the interest rates markets in the last days of February 2007, early March 2007. And it took more than a year before it really jumped to the stock markets. These were different markets, different players, and that still could happen in that period. That meant that in those years, by trading these different markets, we were more diversified

than later on. Because nowadays, if something like that would happen, immediately all these markets are starting to response. It will not take one year in between. A nice example was when there was the Brexit election, the referendum in 2016, one of the markets responding the most was the Brazilian real was really dropping extremely. And it took a few hours before people realized that Brexit was not about Brazil, although it starts with BR as well. It's just this reflex in which all markets are responding to the same thing.

And that makes this whole how to work with correlations, how to make sure that you have a diverse portfolio more of a challenge than before. We have to look at correlation measurements that are not being disrupted or disturbed by these kinds of short-term events that in the past didn't happen. Do you think that's because news is disseminated quicker or also in my opinion technology and risk departments are infinitely better than they were back in the day, right? So you'll have, hey, here's your portfolio-wide delta compared with the S&P or something. And if you want to lower that, you need to sell across this whole portfolio, all these positions, you could hit a button and make that happen.

You can do it better, but let's say in the past it was not necessary because people were really looking at different things. Yeah. Because people are looking at the same thing. The average stock trader didn't know back then that something was happening in the other markets or bear, or didn't think it was relevant. Using all these things, for instance,

value at risk measures that have been used worldwide by many large firms, you immediately catch if something happens in one place, it has a much more impact on the other markets. And it can sometimes take an hour like in the Brazilian case with the Brexit. Sometimes it takes more than that, a few days, but ultimately it's okay. They may have happened something here now in let's say Brazil, but what does it has to do with the wheat production in Australia?

Nothing, is it? No, nothing. So they act first and then think about it later. Yeah, yeah. And that's really changed. And so you can easily do charts that show that the correlations have been grown over the years, but you can also adapt those and realize that there's a lot of those short term events and that will be taken out and that improves. Where do you think that whole piece of the market goes? Does it keep going that way? We keep getting tighter and higher and higher short term correlations? Or do you think we're at our maximum of that.

Well, what I've learned over history is that it changes constantly, but some things keep on returning. So let's say the use of more of AI can also again result in different people that think they're doing different things or all of a sudden doing the same things. Yeah, training on the same. And they don't realize.

So it's that will keep on coming back that and that's not different than with these cows every time they tended to be hurt and will continue to be hurt even so now and then an individual cow can do great things. And that to me is why Cocoa was so exciting for trend followers. It was like the first example in years it seemed of, hey, here's this independent, totally unique thing that's happening outside of the macro. And it didn't matter if the Fed was doing XYZ.

But the nice thing was also that the Cocoa market for a long term wasn't really the trend followers best friend. Yeah, for very long. So if anyone did some historical optimization, we would have said, no, we leave it out and it's going to be better. And that's something that's not new either. When we started to do our research and did the trend following techniques, we also were thinking, does it work on all markets or not? And then there was one market

that was doing very, very bad in our historical testing. That was silver. I was going to say gold. It was the Hunt Brothers. It was because of that. And if you then say, okay, we should use it applied on all markets, but not silver because silver doesn't work, then essentially what you're saying, okay, there can be Hunt Brothers again and they will be in silver again. And to me, more logical seem that there will be people like the Hunt Brothers again, but most likely in other markets than silver. So it's better to see what happened in silver and to see what's the effect of using a system

in markets like silver as well and make sure that you can cope with that because the next time it's going to be in another market. So do you guys filter out any markets or you're saying as many markets as we can put into the universe? We don't filter out markets because historically something has happened. We do filter out markets for other reasons. You can imagine that we have been trading ruble for a long time, but after Russia invaded Ukraine we were among the many people that don't want to trade ruble anymore.

Yeah. And they are more markets that we are not trading. When we stopped trading the Turkish lira, when Erdogan starts to have his own ideas about speculation and that then, it's a safe market for us. From a justice standpoint or from a, right, of a governance standpoint or from a governance standpoint or a risk standpoint, like, hey, this might go to zero or it might go or both. No. Let's say one of the basic principles is when we are making money in a trade, then we want to receive that money.

And we don't want anyone else to take that money because he doesn't like us to make money. So it has to be safe. That's also a reason why a few years ago after the Nikkeli Vendom LME, we completely stopped trading LME, completely LME. Not only Nikkel, no, we completely stopped trading LME markets. And we have had some serious long-term discussions with them and see what kind of improvements they were going to make before we started trading again. That's our way of doing that.

It's not that we are starting a law case against them, cost lots of money, and it doesn't lead to anything. The market has to be reliable. We talk with our counterparties in this case, exchanges on these elements. They don't always like that, but it's very fundamental that the whole idea about is is to get my money back. When you are selling at a high price, we want to receive that high price. It's not that it's going to be adapted. And over the years we have been very, we had to be very active in that.

Because trend was massively, well, maybe not massively, but trend, most trend models were long, nickel going into that, right? Yeah. And we were one of the largest sellers in the moment when it was exploding because we think when a market is too high, you should sell. So that's what we did. And so when they canceled all those prices, we were one of the participants that lost the most due to that. It's not that we had direct loss, but they took away profits. And that's not the

whole idea. They should have been thankful to everyone that was willing to sell when the price was too high. They were thinking the price would go higher if you weren't there. The day before it ended at 50 and they were already thinking it was too high. So when it was at 100, we were one of the largest sellers and they should be glad that there were participants like us willing to sell at those high prices because these were needed participants willing to sell. And then it started to come down. It had already come down from 100 to below 80 before they decided to stop trading and throw

all the trades away. Yeah. I always joke that trend followers always get blamed for high prices, but we never get thank you letters for low prices. Oh yeah. Where's my thank you letter? Yeah, sometimes you get also blamed for low prices. It's just dependent on the market. So if you're trading stock markets and the stock

markets are coming down, then it's also. True. True. And we get blamed as well. How do you feel when you said we thought it was too high? I'm assuming that is a model. Not you're not in a room and someone's saying this looks too high.

No, don't. These are the ways we see ourselves. Okay, this is going wrong, we take away. So it was a manual over it. This was, yeah, yeah, yeah. We had, when things are going strange, we are, in our model is all kinds of elements, but when things are really strange,

we step in and over it. Yeah, I thought it was a misprint that day, right? I'm like, oh, the screen is wrong. No, we knew it was not a misprint. We had been we saw it happening. And we decided to sell it all and we were almost finishing finished with selling it all. Nice. Well, not nice. But and you're that's a big philosophy or core principle, right? Like it's humans interacting with the machines,

not just systematic. Yeah, machines do nothing. Machines are like a dog. Or a cow. No, yeah, but dogs, you can train a dog easier than a cow. They have to do what you want them to do. If they start running around and barking against everyone, then they are not well trained. So the program has to do what we want them to do. So then you can train a dog to cater to sheep and sheep will come.

But if the dog does something else, it's not well trained and then we are responsible. We are responsible for the sheep and the dog has to do it. And that's our trading is the same thing. Our trading strategies are developed by us. We write all the code ourselves. So everything that the training strategy does should be what we want to happen. And we cannot manually do all these markets. We are on a normal day, we are working a few

hundred orders at the same time. Most of them will not lead to fills, but we are on a normal day, we are working a few hundred orders at the same time. Most of them will not lead to fills, but we are working all of them together in all these different markets at the same time. Of course, we do not have that many traders that can do that. In the old days, it would have been many to be used. But still, we are doing what we want to do. And if trade isn't right, then we look where did we made a mistake? Where did we go wrong? Brokers don't make mistakes. It's people that are responsible for the program that make the mistakes. But how do you do

when you're driving in the car and you drive me off the road when I'm on my bike, I will blame you I will not blame your car. I want to get your thoughts on Matthew Vanderpool later, speaking of the bike. If you started at level one on your trend following model 30 years ago, right? What level are you at now? Level 50? Who knows what? And what level does it go to?

A lot of people could argue there's nothing left to do in trend following. Like all the alpha has been thought of and all the innovation has been squeezed out of it. No, because the world is constantly changing. So we have to adapt constantly. Um, when, when, when we, when we started around 1990, using a computer was really an advantage. Now being able to let people do the work is an advantage. Everyone is using computers so that the computers can run away.

So we have to be more aware that it's the people that have to do it. So it's constantly changing how the other participants are doing different things as well. And then this is the big difference between, let's say, physics and economy markets. What is happening in market is the result of people doing things. And then people start to do things differently, the market becomes different. And if we want to perform, we have to be do

different again, also. So that's not a result of physical laws of nature. No, physical laws is very, it doesn't really change. If you move from the earth to the Moon, then all of a sudden things get really different. But as long as we stay on Earth, the physical laws... And then some physicists would probably be on here. Well, actually the physical laws get a little wonky and change also, but we'll leave that for another podcast. Yeah. Yeah. The physical laws

that have direct impact on us are not changing that much. No, no. But so your take is it's not necessarily right. What, what if I had developed the model 30 years ago and I'm still using that classic trend model, right? It's going to probably still do, it probably still did well in 22 and 08, but it's going to have bigger drawdowns. Or what do you think the downside of that approach is?

There are many different things. One, the programs we are using right now, if we would have been using them 30 years ago, we wouldn't have a computer that would have been quick enough to get all these orders out quick enough. It was impossible. It was impossible. It was impossible. We are now trading synthetic markets in which we are, let's say, trading US bonds in combination with Australian bonds.

In the early days, if I wanted to trade Australian bonds, I had to call an Australian broker and be on the line with him to trade the Australian market. While at the very same time, I couldn't even trade the US market because I had to wait till it opened and then Australia was sleeping already. So many of the things we do right now could not be done in those days. But since they can be done right now, the world has been changing. So you hear a lot about, for instance, China. The Chinese markets would be very interesting because they are so low correlated.

Look at the history, how low correlated they are. Yes, but they are also low correlated because you've had a long period of time in which the Chinese markets were closed, which means automatically that they are not correlated. This is happening outside China. But the moment these markets are open, oil price in China will not move in another direction anymore than it will move outside China. Right, like a will move outside China. Like a law of arbitrage.

Yeah, so the world is changing. So it's not that relevant to see. I've seen of course those publications about CTAs being calculated 200 years back or something. Well, that doesn't make sense because from one place in the Netherlands, you could trade in Japan, the Netherlands did have a very good relationship with trading relationship with Japan a few hundred years ago, but to get an order from here to Japan in those days, it cost a few weeks of sailing before it ended there. It's not the way some big slippage were tested.

So it was technical not possible. So that makes also that it doesn't make sense to see what happens back then. You can make a nice movie, Back to the Future has been a very successful movie of course but it's not reality. And so your innovation is in these markets and in this access? You still think there's innovation inside of the core trend following signals? You said before entry exits don't matter so much but capturing the essence of that trend, do you think there's still innovation there? Yeah, yeah, there has to be innovation there because to make sure that we are really sizable and invested in really different trends, it requires us to do the things different than before.

So we have to do things different to get the same thing done. The Red Queen principle, right? You have to always be running. But it seems a lot of the innovation lately and trend following is more esoteric markets and illiquid markets and things like this where, hey, we're going further afield into these different markets rather than working on the signal itself. Yeah, well, the signal itself, the buy-sell, well, you have to do some things there as well. You have to make sure that you don't get disturbed by short-term disturbances in markets.

If the market can be short-term disturbed, you know, a flash crash we saw a few years ago, well, the things you have to learn from events like that is how can we make sure that we are not only losing directly in such an event, but is how can we make sure that we're not only losing directly in such an event, but also how can we make sure that it doesn't have an impact a few minutes later or a few days later. It can be on very many hidden ways that a large event in one market or in a few markets has a longer lasting effect which you didn't really want to happen. And that's something we are working on

and that can also be in the signals themselves in that individual market. Right. But that would seem counter to trend, right? Like the classic trend to me would be, I'm participating in every breakout so I don't miss the big one, right? Yeah, but if you determine a breakout

as the market makes a new low, you remember in that flash crash, a few stock markets went down more than 90% for a very short period of time. Yeah. So when would you do have a sell signal after that events in that market? No thanks.

It would have broken that low? No. Then you have to make an idea about how do I define a low? Do I calculate every trade or do I take out some markets, trades? Yeah. That doesn't mean that the exchange should take out these trades. Right, they did that as well. They should not take out those trades. No, but we using that information can choose which trades that have been

traded before are relevant to us for our strategy and which are not. And that's a decision we can make and are allowed to make. No one says to us that it has to be a breakout because it has not traded below that price forever. No, it can also be if we take out the strange ones. I think the LME. These didn't happen in open on the floor, these kind of trades. Didn't they bust those trades also?

They pulled an LME. I think they got rid of those trades. They did. They did. Some of those trades. Some of those, yeah, they did. But again, that should not make a difference. It should not be that an exchange starts to cut out trades and that has an impact on when we decide to buy or sell. The exchange policy is not and should not be aimed at having effect on people like us. Right.

You're a big customer. You should be helping. Right. Yeah. So that's why we say if prices... We saw now that there's a few exchanges that still have these strange policies about prices that are strange. And then one of the things they do is then they call other participants. So this is an exchange that calls us, says,

this discussion about this price, what do you consider a fair price? And then of course, the price looks somewhat high. And then we say, well, if we thought that price was too high, we would have sold there. If the buyer thought that price was too high, he shouldn't have bid that price. Yeah. So that's why you have a market. Yeah. That's, that's, let us not decide afterwards what we think it's a fair price.

We are in the market to help creating a fair price. And then we are doing that. We want to the other side to be held to that price. And that's change really, really something technical going on. And we can only fairly know only very few examples, really something technical going on, which allows to to cancel trades. And I'm sure somewhere on the exchanges website there's some language about price discovery like that's the point of what's going on not phone call price discovery. Yeah but exchanges different exchanges that have almost the same policy written can

explain that completely differently. So, yeah. How do you protect against all this, all this knowledge, all these filterings, like making your basically a risk-free rate of return, right? Is there a point of no return where you add so many filters and bells and whistles that it just becomes, you dampen the return too much? No, but of course you have to be, if you have these extreme prices and you hold them into your statistics, you will end up having a very high volatility or measure high volatility

or measure high risk, which is much higher than the real risk. And the result of that will be that you have smaller and smaller positions and then you have two small positions and you will not make any more. So you have to make sure that you're not over estimating the risk. But I'm saying even with the diversification and all the rest and the other filters right if you're like are we actually in a? What we talked about, I don't want to be short implicitly, you're implicitly short the dollar, right? If you start to add all that, do you start to lower the return? Or is the goal to increase the Marr ratio or whatever? No, no, no. But we talked about cocoa earlier. You have to make sure that when there is a big cocoa trend as there was until earlier

this year, you have to make sure that you're sizable positioned in that. And we were, that's why we made a lot of money in that market. But if we were using exactly the same techniques as we did 20 years ago, we would have been in the trends but not as sizable. So we had to adapt for that to make sure that, indeed adding more and more markets doesn't lead in having no sizable positions at all. Right, so that's some of the innovation of like

when making sure you don't actually lower the profile. Yeah. Right, like you're improving the profile, not lowering the overall probe Wanted to talk quick via a Couple of your papers. I'll start with an old one We did a blog post on one of my favorite pieces you did it was an old one I called skinny heads and fat tails Yeah, right, which basically was during the Fed and kind of all the quantitative easing and I think

your concept was, hey, they're just, and for those listening, I'm doing a bell graph and shoving in the sides, right? They were making the head taller by dampening all this volatility, but what does that do? It sure makes the head taller, but it squishes out on the tails too. So just, yeah. What's your thoughts on that? Is that still happening a bit with with all the federal government global government interventions?

It still can happen and it's coming back every now and then, but you have to be very careful when you let's say, kurtose, this is about kurtosis, you should not concentrate and trying to find the fat cells, you should be aware where you see a peak head. A peak head is the problem and that can be found and you have to know that, okay, if you see something like that and this has to be part of the filters we are using.

So now and then we stop trading in the individual market when it's becoming too much like that. Then we know already, okay, now it's not going to function anymore. So that market cannot be traded. Well, this can be because, okay, you can have it in a currency when the central bank is linking it too much to another currency. Well, then it cannot happen anymore. Sometimes you have it in interest rates instruments, short-term interest rates instruments. Well, you have to avoid being in that situation.

You of course get it with an individual stock when there's someone else that has bought the stock and it's promised to buy it and there's an agreement about the price, it doesn't move also. So these are the situations that you have to be careful about. So the fat tail is the result of having a peak and that peak is something that you can recognize. Right, versus another method.

Some people might be saying, which markets have fat tails. Yeah observable fat tails And I'm going to avoid those you're saying that's too late basically Yeah Love it, and then another paper I was reading just there was a very there was a very nice well about the one you said about the fat tails because there was a really fun I we cut and Remarked by someone who said he was statistics professor

and he didn't agree with it. He completely didn't agree with it. And then he referred to Wikipedia that wrote a different theory. And that was correct. The English Wikipedia page had a complete different way of looking at it. The French and the German and the Dutch Wikipedia had not. And then we were watching, but you can in Wikipedia, you can see who has changed it. It was that same man. So he had adapted to the Wikipedia page to fulfill his theory, which was completely against the statistic books.

But he forgot that we could read German and French as well. So we saw already, okay, this man is having his own story. That makes you scared of the large language models, right? If they're pulling stuff like that from Wikipedia or misinformed. Well, it's very easy nowadays to make up a story and get it published and duplicate it and let people believe in it. So it's... So wait, what was his theory? He believed there was no such thing as fat tales or he was saying... What was he saying? He believed that this peak in the middle

was not the cause of kurtosis of fat tails. So he had a very theoretical and arbitrary way of getting a fat tail without his peak in the middle, which was absolutely not realistic. So most the comedy fans are like we described it, that you, we gave a very simple example. We have the prices of a stock on every business day, but then we find out that, never realized, but the week also has a Saturday and a Sunday. So let's add the Saturday and Sundays to these prices and what happens is not traded so the price doesn't change. So we have a new list of prices and we include the Saturday and Sundays and no price change then. And then all of a sudden the same stock has all of a sudden a very high fat tail, the kurtosis is up. The kurtosis is up not

because of fat tails, now it's up because of the peak in the middle. And that's just how simple this statistics work. A cortosis happens because of that. If you add zeros, you get a fatale. And that's a very simple thing. And that's exactly how cortosis is defined. I imagine you have some big rubber curve in your office and you can push in, make the head go up and the tail squared out. Yeah there's all the ways you can do it but it's... I want you to have

one of them. And then wanted to get your thoughts before we end up on basically replication, right? You wrote that paper just by the index, some great points in there, so kind of share what your thoughts were there. We've had Andrew Beer here on the podcast and he agreed of like, I'm not trying to replace the trend follow. If I replace them, I can't exist. So it's an interesting kind of mind puzzle, right? Of how do you replicate something that you can't replace? Yeah, but I think trend following is about following trends in individual markets.

And the best trend followers that are working for a long time do that in many different markets. This diversification is part of the trend following strategy. There's no trend followers that only take a few markets. And the basis of the success of all these trend followers, and they can have different ideas about styles among the shorter-term and longer the longer term and some take out some markets and there is a lot of ways we can be different. But if you just look at what is the long lasting CTAs that are doing well, they are trend following

and do it diversified. That's the strategy. And for an investor you can even more diversification if you invest with different transform CTAs that have slightly different strategies. And the CTA index is the result of that. It's diversification by the independent CTAs and even more diversification by adding these CTAs. Yeah. Ensembles of ensembles basically. Yeah.

You can make something that, let's say if you want to reproduce that, you have to do the same thing. You have to trade in all these different markets and you have to do it in different ways. Then you have to do the same thing as what the CTA index is. Making something that is highly correlated with the index, with that particular index, is not that very difficult, but correlation is something else than having the same long-term return. If you take the performance of DTP and you do exactly the same,

but every day you do 0.1% less by making costs or whatsoever, the correlation will be 100%. But 0.1% every day in 250 business days a year is 25% a year. So you get 25% less return per year. With 100% correlation. So correlation is not the same and it's often being said, oh look, it, so correlation is not the same. And it's often being said, oh, look, it's correlated. So it's the same. No, then you forget about the absolute level.

And that absolute level is not part of correlation. And if you wanted to make as much as possible correlated, it's not going to help you. And also our investors and most investors want something else, something that is different. But we know our people, most people are afraid for something different. And that's the continuous, let's say, problem with CTAs, our clients want something different because they want diversification in the whole portfolio of investments they already have. At the same time, most people are afraid for something different.

Well, that is a nice thing if you say there's an index and it will be close to that index. Right, I can do something different without being totally different. Yeah, but the CTAs don't do well because they follow that index. No, the CTAs decided to do something different than all the other investment styles. And the average of them doing these different things is the index. And as soon as all of us are trying to bring that index, let's say if the whole index of CTA trend followers would be consisting of participants that do like what Andrew Beardos replicating the index, then it would be a whole index of dogs running after their

own tail. Right. It's like a sci-fi movie of like what came first. It would end up nothing. So there are many ways of trading and everyone should try his approach, but to do the index, you have to do what the index does. And that is very simple in CTAs. You have to be invested in different markets, in different trends.

And you can do that by investing with all these different CTAs. And yes, if there is 20 in the index, the standard index or 10 in the trend following index, you don't really have to invest in all of them. But more than one is surely recommended. And if you invest in 10, it doesn't even have to be the 10 that are in the index. There are some other ones that can add even more. I would think you can do better by that. But so do you think the replication will do better, will do worse, or it's just random?

It'll do different. The replication is not... The moment it becomes successful, let's say in a commercial way, it will in performance way not be successful anymore. Because then it becomes more of the standard and it doesn't work again. CTAs as a whole, we've had a period in which we did very well and periods in which we as an industry did not so well. And the periods in which we did better

was when we were more different from each other than in the periods we did less good. And then we say, well, the market is not friendly anymore and we had all kinds of excuses. No, we were not different enough, we have to be different animals. And we are different animals. Different dogs. Yeah.

The, uh, and speaking of drawdowns trend in general has been in a drawdown, what since middle of last year, basically what you've been doing this 30 plus years. What's your secret sauce for living through the inevitable trend following drawdowns? Does it still bother you or you take it in stride? Let's say we are not celebrating around the table, hey, hello, how deep a drawdown we have. That's absolutely not the case.

No, of course we are all about making money and trying to make money and doing our best. A very important element is how to make sure that when you're in a drawdown, you keep on doing the best thing. And that has to do, it's not so much the technical element is not the biggest issue, you have to make sure that the team keeps to be motivated and so on. And this is something we've been working on a lot the last years.

It's called resilience, but how do you make sure that the people when something is happening and it's not doing that well for a peer to keep just as motivated and do the right thing? Yeah. Then following goes wrong if you don't, and any strategy goes wrong if you leave your strategy when it's not working for a while. Right. Unless you have a good reason that the strategy should be adapted, but adapting a

strategy should not be dependent on, oh, it has not been working for a while. Adapting a strategy is because you see something is happening in the world and you have to adapt for that. We stopped trading Russia not because of we didn't make money off it anymore. No, because that currency was not being accepted anymore anywhere outside of Russia. So that's why you stopped trading Russia.

So adaptation is something you constantly have to do. But if you start to make strange moves, it's not so wise. It's like when you're going from Chicago to Canada, and you can do different ways. You have to cross that lake. Yeah. OK, you can take a boat. It's very nice.

Last time I took a boat, you can take a boat. It's very nice. Last time I took a boat there was a sailing boat. But somehow it didn't, there was no wind. So that was not that, that was not that enjoyable. Nice event. But okay, you can take a boat. If you decide to take a boat, you know, okay, this is okay. If you one time end up and it is freezing a lot, okay, then, and there's ice on the lake, which happens to now and then, okay, you will not make it to Canada that way. Right. That in itself is not the reason to next time to go on ice skates.

Because then you will see that ice skating on water is not as successful. So you have to, you have to, you have to, that one one time goes against you doesn't mean you have to adapt your strategy. If you find out that the temperature above Chicago is coming down constantly and in the future it will always be ice, well, better to have a sledge or ice cage. But as long as that is not the case, keep on using your boat and be aware. Sometimes it might freeze and then the boat doesn't function. a boat and be aware sometimes it might freeze and then the boat doesn't function. But historically speaking you have comfort from hey trend following has always come back or do you discount that?

Like well it's times are different and we'll see what happens. And now we constantly have to have adapted independent whether or not we did a good or not so good. So yes, we constantly have to change. But the underlying principle why trend following works keeps on working and will continue working. And we have to make sure that we are profiting from that. I was waiting for you to bring it full circle. The underlying reason is because we're all cows. Yes, indeed. But I'm not allowed to say that too often. Once or twice is fine. Okay.

I want to finish up a little bit of fun. I heard you mentioned Back to the Future movie. I heard you mentioned Back to the Future movie. What's your top four movies of all time? Your Mount Rushmore, if you will, of movies. Well, I can say the whole list of the Coon Brothers movies. I really am a fan of the Coon Brothers movies. If I recently saw one minute of a movie that I hadn't seen before, I immediately recognized this is Coen Brothers. One of the best ones is somehow not high on the list of the most... The Coen Brothers.

We would say Coen Brothers. Coen Brothers. You say, okay, Coen Brothers. Yeah. Coen, Coen, Coen. And Dutch would say Coen. We have the OE and this is the O. And Coen you say, okay.

Yeah. So like Big Lebowski, what are some of those? Well, most people talk about that one, but my favorite one is the Hutzucker Proxy. Ah, I know it. The Hutzucker Proxy. And there is this, when you talk about trends, there is this scene in it. The guy has a circle, he has invented the circle. And then this becomes the hula hoop thing.

This whole scene in which the hula hoop doesn't sell at all and all of a sudden becomes a success and then becomes a trend, it's such a great example of how a trend can start out of nothing. And then, and the way they filmed it, it's almost no speaking, no spoken words in it. They often do great things with just pictures and not too much words.

And the words they use are very minimal but very exact. But here is almost no spoken words in it. And this whole scene with this little boy and what's happening with this circle, the Hoolahoop thing is so great. The whole movie is great, but that thing is understanding how a trend can start and how big a trend it can become. And also in this movie is, of course, some of the people there didn't want it to become a success and it did become a success.

It tells you everything about trend following that movie. I would have guessed, I could have sat here for three days and guessed movies and not landed on Hudsucker Proxy. Hudsucker Proxy, you have to watch Hudsucker Proxy. I've watched it, but yeah, I wouldn't think that you would have watched it. Oh, no, no, no, it's great.

And there's another one of them. That's also trading related. I said the Coohn brothers normally are not having that much text but one of the movie is is True Crit. Yes. And through Crit there is this girl that is trading to get her horses back, the horses of her father back, the ponies. Yeah she should have got the Oscar I think. She was so good in that. And she was young at that time. Yeah, I don't know whether she was 14 years, or whether she played something 14 years. But this negotiation scene in this movie, you can watch it up on YouTube, this whole

negotiation scene. There's many people nowadays that kind of think when they're testing, trading things as well, they think you don't have to trade. It's a price and you trade the price. Now, of course, price is the outcome of a negotiation. And the negotiation in this movie when she wants her ponies, it's so absolutely great. And this has a lot of words, but that's absolutely great scene there. All of the movies are absolutely great, but these two is if you want to do something with trend following and trading, of course, when someone is new

in the office and doesn't know about futures markets, we always tell them, let's watch trading places and let's show soon exchange. Yes.. Trading, negotiation, that's in true crit. And the trend is in the Herzog and Proxy. No country for old men, too violent? Or you like that one? No, it's also very, very good. Oh, great, great one that also. Yeah, yeah, yeah.

I'll send you a list. We did our top trading movies of all time, a blog post once. I'll send it over to you. But there was no Coen Brothers in yet? I don't think so, no. We'll add those. We'll update the post. We had some fun ones. We had Goldfinger. Yeah. Right? Because he's basically trying to corner the gold market by irradiating at all in Fort Knox. And then we had Pretty Woman, which is about basically a private equity guy hold up going

over his deal for three days and falling in love. So yeah. Yeah. Now, but this is the true crit one is also this, of course, still discussion. Let's say on many trading floors and not many women and you can discuss whether women would be just as good in trading as men are. Well, this girl shows that girls can do trade very well. Definitely. And what's the other one I like? There's the Fargo. Fargo is of course, yes, somewhat comparable with this is this police woman that stays calm. The old brother with Otto, they black and white with these songs in it.

Yeah. Love it. All right. We will leave it there, Harold. Thanks so much. Um, it's been fun. I'm going to come visit Rotterdam. We'll do it in person next time.

Yeah, by boat. By boat. No ice skates. Just boat. Unless the Northern Sea is frozen. Yes. And I don't know if that's ever going to happen again, right? Alright, thanks so much, Herb. Okay, thank you. Bye bye. Take care. You've been listening to The Derivative.

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