The Four Faces of Trend Following | Systematic Investor | Ep.361

Summary

Investment Philosophy: The podcast explores the diverse archetypes of trend following, highlighting the differences between replicators, core diversifiers, crisis risk offset strategies, and outlier hunters, each with unique objectives and design choices.
Diversification Strategy: Emphasizes the importance of diversification for outlier hunters, arguing that a wide market universe reduces the role of luck and increases the chances of capturing significant market trends.
Volatility Targeting vs. Static Bets: Discusses the debate between volatility targeting, which aims for smooth returns, and static small bets, which focus on maximizing payoff from rare market trends, underscoring that the choice depends on the strategy's objectives.
Symmetry in Trading Rules: Examines the use of symmetrical versus asymmetrical trading rules, where some managers adjust rules based on market conditions to optimize trend capture, particularly in outlier hunting strategies.
Speed of Execution: Highlights the trade-off between short-term and long-term trend following, with short-term strategies focusing on quick market responses and long-term strategies aiming to ride out larger trends for maximum payoff.
Market Selection and Risk: The podcast discusses the challenges of selecting the right markets to trade, balancing the need for diversification with operational and counterparty risks, especially when considering off-exchange or less regulated markets.
AI and Market Trends: The conversation touches on the rapid advancements in AI and its potential impact on market trends and investment strategies, emphasizing the need for adaptability in an evolving landscape.

Transcript

Imagine spending an hour with the world's greatest traders. Imagine learning from their experiences, their successes, and their failures. Imagine no more. Welcome to Top Traders Unplugged, the place where you can learn from the best hedge fund managers in the world, so you can take your manager due diligence or investment career to the next level. Before we begin today's conversation, remember to keep two things in mind. All the discussion we will have about investment performance is about the past and past performance does not guarantee or even infer anything about future performance. Also understand that there's a significant risk of financial loss with all investment strategies and you need to request and understand the specific risks from the investment manager about their product before you make investment decisions. Here's your host, veteran hedge fund manager Neil's Castro Larson. Welcome or welcome back to this week's edition of the systematic investor series with Richard Brennan and I, Neils Castro Blasten, where each week we take the pulse of the global market through the lens of a rules-based investor. And I also want to say a warm welcome if today is the first time you're joining us. And if someone who cares about you and your portfolio recommended that you tune into the podcast, I would like to say a big thank you for sharing this episode with your friends and or colleagues. It really does mean a lot to us. Rich, fantastic to be uh with you again. Um, how are you doing down under? >> Not bad, Neils. It's It's pretty chilly down here, so I've got my jumper on. Um, I know it's pretty warm up there in the northern hemisphere, but I think um next week I'm going to be joining all of you up there, so I'm going to be I'll get my bathers out and my togs and my uh my my my sun umbrella and come up and visit you. >> Yes, I I'm so much looking forward to meeting you in person. It's strange after all these years that I've never met you in person. So I really look forward to that. Um and uh but you know what? So actually it's very interesting in in Europe. Um just to stay on that topic for a second. So uh today I'm actually uh in Scandinavia and it's very pleasant up here. I mean it's not very warm but it's warm enough. Right. Switzerland very hot at the moment. Not to say southern Europe massive wildfires and and 40 plus degrees Celsius at the moment. So, you know, but I think you're coming to kind of the sweet spot uh when you come to Europe. Um so, it'll be it'll be super nice. Now, we got a really wonderful uh outline thanks to you today. Uh which I'll discuss in in a second, but um as we always do, um I'd love to hear what's been on your radar, even though I I have a feeling I know what it is, so to speak. Um and uh you'll be surprised when you hear my topics. Um, but what's been on your radar recently? >> Well, Neils, I've been playing around with the latest chat GPT version. It's version five, um, which has been released over the last few weeks. And, um, I've got to say, wow. Um, the future's coming at us fast. So, I've found that Chat GPT is a noticeable leap from its earlier versions. faster responses, deeper reasoning, better memory, and it's got a it has got a much stronger grip of nuance. And uh so, but this is where it's getting interesting, and I asked it a few questions. So, if you look at how fast we've gone from Chat GPT3 to Chat GPT5, the curve is getting far steeper. It's exponentially rising. Each jump is bigger and the time between jumps is shorter. So it got me thinking where this trend leads us. So at the moment AI still heavily relies on us. We feed it data, set the goals, and pull the plug if necessary. But at some point, maybe 5 to 10 years on, it's entirely possible we'll see AI systems evolve to sustain themselves without human intervention. They'll be able to source their own data, refine their own models, and decide which problems to solve next. So I I asked Chat GPT about this, and this is what it said. I asked it to estimate or paint three scenarios. a an optimistic scenario for humans, a a middle scenario for humans and a pessimistic scenario for humans. And it came back optimistic human control scenario 15 to 20 years away. And this is provided we have strong global regulation, tight um computer governance and cultural norms slowly um or or autonomy autonomous handover. The middle scenario is between 7 to 10 years and this is with gradual erosion of oversight as autonomous research agents become mainstream and open models keep improving and this is this is its fasttrack scenario. It told me 3 to five years. And this is where a combination of decentralized compute, permissive open-source releases, and commercial competition removes human bottlenecks much faster than safety frameworks mature. So under these scenarios, when humans lose their control over AI, the selection pressures no longer will come from humans anymore. They'll come from whatever the AI itself values, efficiency, self-preservation, problem solving speed. And that's where governance becomes tricky because the old off switch may not work the same way. So the uncomfortable truth is that in the fasttrack path, the inflection point could arrive before most governments have any effective monitoring or control systems in place. And that's why some in the AI governance space argue for treating compute allocation and model release like export control technologies the the same way we treat say nuclear material or advanced biotech. So I'm not saying to Neil's Skynet's around the corner, but it does raise a question. Are we moving fast enough with alignment and safety given how fast the capability curve is rising? And I'll tell you this, Neils, if Chat GBT6 arrives as quickly as uh Chat GBT5 over its predecessor 4, this conversation we're having now might feel very different a year from now. Well, it's so weird, a little bit scary, Rich, that you put down AI as your sort of what's been on your radar. It's exactly the same for me actually. But before I get to that, there was one other story I thought was quite funny. Um, so over here, obviously, footballers in the US, they would call it soccer is a really big thing. and the uh club that won the uh Champions League, which is the biggest tournament um uh in in Europe, um the uh the club PSG from Paris won it for the first time. And then I saw on uh on on the internet this week uh that they are now so PSG is hiring a quant to trade crypto. And you think what the hell it's a football club? No, it's true. So it says PSG is looking for a relatively junior trader. They're expected to have a PhD and or quantitative masters and expected to have three to five years of trading experience in crypto hedge funds and prop trading firms. The trader will also assist PSG labs broader efforts to create uh agentic AI tools to be used across the club. I thought I mean I thought that was quite funny that um that even a football club is moving into not just AI but kind of crypto trading. But anyways, back to the AI thing because it also hit me really hard uh this week um through a couple of interviews that I was listening to. Uh one interview was with this the ex Google uh head of um AI I think. Um and I forget his name right now. He's Egyptian. um and he's written a book a couple of years ago. Um and this is a relatively recent conversation only a couple of weeks uh old and he paints the picture but he actually thinks that you know even 3 to 5 years is is is not too >> well it's going to be even sooner. >> Yeah. and he actually sees a world that most likely could be some kind of dystopian world where a lot of people will be unemployed but they'll get you you know universal basic income and and so so in a sense he's saying that it might be really rough initially so to speak because people won't know what to do with their time and and and of course un universal basic income doesn't mean you're going to live well uh in any shape or form but >> at some point he thinks Well, it could actually turn out to utopia where we don't really have to do a lot, but we still get paid and we can actually do what we really want instead. So, anyways, and I can't it's such a long deep conversation, but um all I will say is that after listening to that, um I listened to another conversation from someone who and again I should have written the name down, but he's he's labeled as the godfather of AI. So he's an he's a 77year-old English guy who had been doing working on you know these um models for 50 years or so but way before it it turned out to be quote AI um and he was also quite worrisome but actually one of his students used to be or is the guy that was mostly responsible for chat GBT2 and who left open AI because he felt worried about the safety as you a that not enough was being done to make AI safe. So he's called I think it's called Ilia or something like that and he's now working on how to make AI safe. But in any event, I think your point about safety, I think the point about us controlling this uh of course you can imagine worst case scenarios where as as you rightly say is the self evolving AI where we have no control and if these things are put into say uh if they're weaponized and suddenly you may have armies of of AI soldiers that decide who to point the gun at and not. I mean this is not something that is unrealistic anymore. Um the other thing is of course that when you have a world that where we really don't know where it's heading. Um, and I personally think now I think I'm convinced now that there were, and I've mentioned this a few times over the years, uh, when we talked about the markets, right? We talked about we had to imagine the unimaginable that some of these market moves like Coco could happen and and and and this is exactly why our conversation today is going to be about uh some of these things. And but I think we can we can we should now expand that that we live in a world where we have to imagine the unimaginable that in 3 years maybe 2 years maybe 5 years our world and unfortunately our children's world um and their children will be so much different than any of us can imagine. I have convinced myself now that that's probably where we're heading and it makes me uh frankly a little bit nervous. But from an investment point of view, all I would say is that if you live in a world that can j change so dramatically and nobody even if they claim they have a clue of where that's going. By the way, what this guy was also saying, uh, the podcast host had had conversations with people who knows the top three CEOs of of these a of the top three biggest AI firms. And he could disclose the names of course, but there's only three people here we can think of. And what he was saying is that the conversations they have in private and what they say publicly about where AI is heading are two completely different things. We're getting the sugarcoated version of, oh, it's not too bad. It's gonna be great. >> Yeah, it's gonna improve the quality of life and it's going to help you do things much better, blah blah blah. But that's not the the dark version. And you know what? When I was listening to that uh episode, um I was kind of thinking, and this is pure speculation, right? I wonder whether that's exactly why Elon Musk is so committed to move to go to Mars that actually he deep down believes that the world is quote unquote f u c ke and and and you you need to go somewhere else because AI is going to ruin our world. I mean I know it sounds crazy but you know maybe not that crazy anymore. Anyways, that's pure speculation, but what I was going to say is that in a world like that, what better way to invest your money in something that does not have a clue or tries to predict where the markets are going? And I truly mean that. I mean, I've been optimistic about trend following the in particular in the last year or two because we could see that the world was delizing. We could see that uh economies were becoming more protectionist. We could see that central banks was diverging in their policies. All of that we could see yet. It hasn't played out great yet because of other because of the noise um from um the US is is at the moment overpowering and our systems need to adapt a little bit to the noise being maybe the signal. Not that they will interpret it that way, but it's just how the data will will pan out. So, I'm still very excited about that. not necessarily because I think we're heading into a better world, but it might be much better in terms of these non-predictive strategies. So, I know we'll we'll talk about that. The final point I want to make is there was maybe an all a little bit of an upside to AI because the FT had an article today uh or maybe yesterday where it talked about how the art of persuasion that the research now shows that the top AI chatbots can make people change their political views after less than 10 minutes of conversation. Right? So I'm thinking maybe all we need is each CTA install a chatbot so when people call them they start these conversations and within 10 minutes they're convinced that trend following is the right strategy for them. >> You're on to something. >> Yes I don't know maybe. So anyway that was a little bit of a rant but uh it is super interesting. Um so we'll see. Anyways, let's go back to something we know a little bit more about, we have a little bit more certainty about, and that's trend following. We're just chatting uh before we press record that it feels a little bit more constructive uh this month for for trend followers. Um and that will definitely be some people who have caught on to some some um great trends and and see strong performance, but actually my trend barometer is a little bit um it's not really confirming that just now. It's actually pretty weak. Um, of course, this is just 44 markets that I'm measuring and so if you are on a one or two outlier markets that um that I'm not uh including in that portfolio, uh you could still have a fantastic uh month. But uh overall the industry is up a little bit this month and yesterday uh which is not including in the numbers I'm going to mention. Yesterday was a positive uh day I would say uh pretty much all round as far as I can see from the early numbers. So Btop 50 up about 48 basis points as of Tuesday. Uh down 3 1/2% only now for the year. Uh so CTA up about half a percent down 7% for the year. Trend index up 1.4% for the month. Uh down 8.77 for the year. Uh the short-term traders index uh is down a quarter% and down 5.33. So that's probably the lagard. uh started out great uh and and did well uh or did better during the uh uh month of April, but it certainly lost some of that uh glory uh in the last uh few months. What hasn't lost its glory is the traditional markets. MEI World is up another 2 and a half% uh this month, up 14% now, which is pretty strong um this year. S&P US aggregate bond index up about 1% just shy of that, up 4.69 for the year. and the S&P 500 total return up 2.04% and up 10.81% as of last night. So tell me a little bit about how you um see trend environment uh similar differently to um to to what I'm seeing um and if there's anything anything any markets that particular is standing out to you. Well, the way I've seen it, we we of course had this very tough first six months of the year and uh I I just had this opinion and I see it see it sort of with what happened last month. There was this uh emergence of trends starting directionality started happening last month and things were going great for us last month. um you know we we're having a you know a bump aer month compared to to prior months and then the last two days of course we had that massive copper reversal and all of that went sideways and uh but then again it's uh this month once again another powerful start for this month you know I don't want to um you know I always get a bit uh worried when I'm very bullish about a month because you know the the time I say it the very next day or the following week I had an absolute thumping but things are going well so far this month. I just don't want to see it like last month where in the last few days we had this huge reversal but um you know the trends trends for us um you know of course the equities are booming for us um >> the metals um so it it's definitely you know all of the things we're seeing Bitcoin all of these things um it's a very difficult environment at the moment and the what I refer to as the stress assets tend to be sort of doing quite well um so I'm keeping Our fingers crossed that this holds for the month. And uh I'm hoping that the last few months of this year um bring us back to at least maybe a break even for the year, but uh it's been a tough year this year, Neils. >> Yeah. No, you know, I mean, anything can happen. It could still be a pretty good year at the end. But um what's interesting to me about this month so far, at least from my vantage point, and that is that it's kind of a kind of a barbell attribution in terms of sectors. So you have as you rightly mentioned equities continue to really um take the lead not so much for the year as a whole but certainly for the month and maybe last month as well. And then you also have the metals you as you point out you have the meats doing really well. >> Yes. >> Yeah. Yeah. But then you have uh at least to some extent some of the soy complex which has been doing well really sort of taking a little bit of a a reversal this month. Um and then you have all the fixed income markets which are um somewhat uh and softs for that matter are somewhat more tricky uh at the moment. So um so yes um very much depending on and of course I don't have any insights to to the crypto world. We don't trade that on our side but uh I understand of course from looking at the price that people must be doing uh well in that space right now. That is good to hear. Let's move across to your topics. Let me try and set the stage a little bit because I think it's going to be kind of a fascinating conversation both for the the traders, investors, uh meaning allocators because we're going to try and take a deep dive into some of the different archetypes of trend following. We're going to deal with some of the big debates that divide our industry and also why you feel that diversification plays a completely different role depending on the type of trend follower uh you are or you choose as an investor. Um, of course, I'm going to let you go through uh the main topics. But before I hand it over, let me provide the listeners with a brief overview of what of what we're going to be talking about. So, first we're going to try and break down um four broad camps of trend followers from replicators who hawk an index to core diversifiers to crisis alpha risk offset strategies and finally the outlier hunters who cast possibly the widest uh net so to speak. And along the way, we're going to try and explore some of the key philosophical debates like diversification versus concentration. We have volatility targeting versus static small bets. We have um symmetry versus asymmetry in rules and the speed at which you execute of course. And then we'll go deep into uh maybe the second part uh the second topic diversification itself uh and specifically why you feel that um for outlier hunters at least maximum breath isn't just a nice to have it's the edge. and we're going to look um at by portfolio test, the real world distribution of returns and how objectives dictate design choices. So, what I'm going to do the best I can is jump in and out um where I where I can keep up um and maybe I have some of my own observations on that, but um it's really going to be as usual. Um over to you and and let's see where we go on this. >> Well, thanks very much, Neils. And yes, you will definitely be joining in this conversation because we often have debates on this podcast together and I'm bringing them up again but under a different light to say that um there is no right answer but anyway we'll get into that. So the thing about trend following is that from the outside it looks like one unified philosophy. People think this is people not in the know that it's all just ride trends and cut losses short and let profits run. But once you step inside, you quickly realize even that famous mantra of cutting losses short and letting profits run isn't universal amongst trend followers. Some managers build rules that will cut losses short without ever truly letting profits run in the classic sense. Others optimize for smoothness or symmetry that naturally caps the upside. So while many of us share certain fundamentals and probably the things we do share is one systematic rules, non-predictive logic and participation in sustained price moves, our objectives can be completely different. And it's those differences that shape the systems we build. So if you spend any time under the hood, which you and I do all the time, you see a very different reality. Behind the shared principles we all agree with lies a spectrum of philosophies, objectives, and tradeoffs that can make two managers portfolios look like they belong to entirely different worlds. So, one manager might run 25 highly liquid markets, adjusting position sizes daily to keep volatility constant. Another might run 100 plus markets, never touching position sizes after entry, absorbing the noise in pursuit of a few life-changing outliers. Both wear the trend follower label. Both might even post similar long-term returns, but their design DNA and the experience they deliver to investors could not be more different. So, this is where the problem begins. Most industries conversations skip over these differences where we're thrown into the same league tables and judged by the same scoreboard. Sharp ratios, MAR ratios, drawdowns, year-to- date returns. These numbers are useful, but they homogenize everything, compressing radically different objectives into a single measure. So for instance, a high sharp might be gold for a manager whose mission is to smooth a multi-asset portfolio, but for an outlier hunter, that same number might signal that the design is leaving money on the table. So without understanding the objective, you're not reading the number correctly. So when this misalignment happens, it costs everyone. Allocators end up with strategies that don't behave as expected in stress events. Managers drift away from their edge, quietly optimizing for metrics that please investors in the short term, but erode survivability over the long term. So, I've seen managers that might start with an outlier mindset and slowly morph into volatility targeters simply because that's what the scoreboard rewards. And by the time they notice, their design is no longer fit for the purpose they began with. So, that's why today I want to pull back the curtain and talk about the decisions that really matter. The philosophical divides shape portfolios. Diversification versus concentration. volatility targeting versus static small bets, symmetry versus asymmetry in rules, and short-term versus long-term horizon execution. Because there's no universal right answer to these debates, a replicator tracking an index will land in one place. An outlier hunter chasing fat tails will land in another. And if you don't know your purpose, it's easy to borrow rules from a different camp that doesn't actually serve you and can quietly sabotage your long-term results. So, we'll start by breaking down what I believe are four broad archetypes of trend followers and walk through these debates one by one. And after that, we'll zoom in on one debate that defines my particular approach as an outlier hunter more than any other. that's about diversification and just how costly it can be when you cut to universe too narrow. But that is from the philosophical perspective of an outlier hunter. We've got to remember that. So, and through it all, one theme will stay front and center, survivability. So no matter what the trend following archetype, the ultimate proof of a design is whether it can remain intact and effective for decades through every type of market stress it can survive. This is a really important uh point that you're bringing up because I I do think that it's true that um we have been kind of put under one label. Um and I think also uh it's fair to say that a lot of uh allocators who want trend probably think that one trend follow is enough because when you look at the correlation they often look very similar. And so I'm really glad you brought this up and I'm excited to go through these things and I'm excited to debate some of them I'm sure. So uh let's see where we go. >> Carry on. All right. So here's how I see it. Once you step inside the tent of trend following, you quickly realize that trend follower is a label that covers very different species. Based on, for example, listening to the many great interviews you've had on TTU, particularly last year, your your interviews last year with Allan with the systematic managers. This is how I tend to group trend followers. I I group them into four broad archetypes. So the first, let's deal with the first, the Andrew Debeers of the world, the replicators. Okay, their mission is simple. Track a benchmark like the SGCTA index as closely as possible. They focus on low tracking error, operational efficiency and delivering the return profile allocators expect from that benchmark. So that usually means trading between 10 to 30 of the most liquid markets. I think um Andrew trades 14 if I remember correctly. Uh they run daily volatility targeting. They steer clear of anything that might create large deviations from the index and many blend in cross-sectional momentum and rebalance frequently to stay tightly aligned. That's the first category. The second category I call the core diversifiers. So trend following here is not a standalone product. It's a satellite allocation within a larger multiasset portfolio and it's deliberately built to lift sharp or MAR ratios by adding a diversifying return stream that zigs when the rest of the portfolio zags. So they might trade similar liquid markets to the replicators and they often use cross-sectional momentum over absolute momentum and they tend to be even more focused on smoothness and draw down control because their role is to complement not dominate the broader portfolio. So the third I call the crisis risk offset. So these are the convex hedges designed to shine in equity drawdowns. So they they're often called longv variants or tail risk protectors. So portfolios here might include shorter term trans systems or option overlays to be the first responders when stress hits. They often keep exposure to assets that deliver convex payoffs in crisis such as bonds in riskoff markets or certain commodities during inflation spikes. So a real world example would be a program that lost money for three straight years but returned 80% plus in 2008 while equities collapsed. That's the exact profile allocators want from this archetype. Crisis payoff first, smoothness second. And then there's this fourth category which I include myself in the outlier hunters. So this is where I sit. Outlier hunters cast the widest possible net above 100 plus markets because we know that in any given year just a few positions will deliver the outsized gains that define the long-term equity curve. We're happy to trade smaller markets, things like cattle that we've talked about, small um less liquid markets than the major players. And we can afford more operational complexity because the cost of missing a fat tail is greater than the cost of running a lean tidy book like some of the other archetypes. So for us it's pure absolute momentum. No cross-sectional overlays, no dilution. So of course there are the hybrids and the niche players you know things like macro trend blends, multistrat fusions, crypto specialists, commodity only funds, factor integrated quants, but most still trace back to one of these four philosophical archetypes. So here's the thing. If you don't know which archetype you are, you're essentially flying blind. It's like designing a vehicle without deciding whether it's meant to be a sports car, a four-wheel drive, a mini bus, or a long haul truck. All can get you from A to B, but they excel in different environments. So, a sports car and a four-wheel drive can both do 100 km an hour on the highway, but take them off road and one gets stranded. And the same in trend following. A rule set that's perfect for one archetype can quietly another. That's why I believe the very first step in designing a system is being brutally clear about which camp you're in. So without that clarity, you can end up debating tradeoffs that don't even apply to your mission because there's no single right answer across all four. So before I move on, do you want to do you want to comment here? >> Well, I feel there's one more category. >> Yeah. Um, and that's one that oddly enough I would call pure trend. And what I mean by that is that um, and I talk about say for example someone like Don, what our objective is to is to produce the best long-term compound returns. That's our objective. We're not designing it to provide crisis alpha in during certain periods. We're not doing that. that's happening inherently in terms of building for long-term best compound using only trend models. Um, we're not building it to be a core diversifier. Again, we're building it to be the best trend following strategy that we can do. We're certainly not building it to be a replicator. Maybe you would say, well, well, you're a little bit of an outlier hunter. Yeah, but then we have some of the quirks that you don't like as an outlier hunter. So I kind of feel that there may be room for a fifth category, but I do think you have to would have to be kind of strict about your definition there as well and say even though people say, "Oh yeah, we're pure trend." Well, then you have to kind of be able to prove that transparently that you are pure trend. But anyway, that would be my thought. But I do like your your framework of trying to define um the different types of quote unquote I don't know if we should say it's different kinds of CTAs, different kind of trend followers. I'm not entirely sure but but um so anyways just felt >> at least it's a start. So I put these four together just thinking broadly from my perspective you're right. Let's move on. And and I think there probably are more archetypes as you say, but at least uh it it's setting the principle that there is no correct style. It it's got to be objective driven. >> Anyway, I'll move on. So, >> yep. >> About these debates that exist and why a lot of them are across purposes. So, one thing I've noticed over the years is that most of the heated arguments and trend following aren't actually about facts, they're about objectives. So, two managers can be looking at exactly the same rules, the same data, even the same markets, and yet walk away with completely different conclusions about what's best. Why? Because they're optimizing for different outcomes. So, a replicator might want the smoothest possible ride so they can track their benchmark closely. An outlier hunter like me might want the most open-ended convex payoff from a rare runaway trend, even if that means years of bumpier returns in between. These aren't just preferences. They are fundamentally different design targets. And that's why so many of these debates are across purposes. Someone says, "Oh, you have to volatility target or you'll be too risky." Another says, "If you volatility target, you'll cut your outliers short." Both are right for their own objectives. Both are wrong if you apply their advice to a strategy with the opposite purpose. So, it's also why I think our industry has a metrics problem. We've ended up with a handful of common measures, sharp ratio, mar ratio, average draw down that flatten us into oneizefits-all comparisons. They make it look like we're all playing the same game when we're not. >> The truth is almost every metric is only meaningful in the context of the purpose of the strategy. The one exception, the only universal metric that applies to all archetypes is a long-term validated real track record. Why? Because survivability applies to all trend following styles. And this principle only can be gleaned from a long-term validated track record of survival across numerous different regimes. That's the one thing that cuts across styles because it's a proof that a manager has survived and delivered their particular objectives over time in real market conditions. Everything else however needs to be matched to purpose. So if I think about it, let's think of replicators tracking error versus the C S SGCTA index might be more relevant for instance to them than the MAR ratio. If I look at core diversifiers portfolio level sharp and correlation to the rest of the holdings might matter most to them. For crisis risk offset um archetypes, crisis period kaggar or convexity ratios could tell the real story for them. And for us outlier hound hunters, payoff asymmetry, skewess and contribution from top trades will always be more revealing than a point in time sharp ratio. So without making these distinctions, we risk running comparisons and making investment decisions based on measures that don't actually reflect the actual mission of the strategy. And that's why I think before we even get into specifics like diversification, volatility, targeting, symmetry, and rules, we have to accept that there's no universal right answer. There's only right for your archetype and objective. So what do you think so far? Well, I mean, I think you you're obviously bringing up some some very important points. Um, a lot of these metrics of course uh will be weaponized in the marketing slide deck. Of course, whatever fits best to your strategy is the one you're going to say is the most important. However, what I feel here that is also a challenge is that um yes, we can define um different kind of trend followers having different um characteristics uh so to speak. But I also think that in you know frankly a lot of investors want more than just one characteristic uh from from a manager. Ideally this is this is why initially in our conversation today I said um it is the wrong view to say that uh trend followers all the same and I I just need one. That that's definitely and I think you show that through this and in a sense if if a if an investor were to be fully satisfied with saying well I actually need some crisis alpha but I also need something that really can compound for me over time or whatever it may be. Well, that's exactly why they probably should come up with a frame for framework along these lines and say, "Okay, let's identify all the managers we're looking at in our peer group." Um, it being one of these four or five different types of managers. Let me decide which of these groups do I need in my portfolio to fill my overall objective of the allocation to CTAs. and then drill down uh on your short list and pick the best one or two in each of these categories. So, you may end up with with four or five, I don't know. But >> yeah, >> but but to I think it's a little bit unfair to ask us as managers to be able to deliver all the things you would want in one package because I think as as you and I will will get to that's not possible. >> It's not possible. Exactly. and and when you design for these different archetypes, you must take different roads which means that you you cannot um satisfy all investor requirements. So this is exactly right. So you know my preferred approach would be firstly to define these trend followers into their different buckets. Use different ratios that are valid for their objectives to look at their performance and then do your selection across multiple trend followers to seek a particular broader objective that that marries a range of different flavors if you like. >> So >> the first thing I'm going to get let's get into these debates. So let's get into the first debate diversification versus concentration. So let's if let's say you're a replicator 20 to 30 highly liquid markets is often enough for a replicator. That's all you need >> or even 10. I think only trade 10 by the way. >> So that's all you need to track the SGCTA index closely. Um keeping operational compliance. >> Let's define closely as being a little bit loose here because I think that's the challenge, right? >> Even they even they might >> he's been out performing them has he hasn't actually been benchmarking. I mean he's been outperforming. Well, that's the thing, right? So, again, going back to replication, right? It's you could all almost say the same about replication where we define it as being or someone who can just hog the index, but can they really hog the index? Probably not, right? ideally uh they would because then they're giving the benchmark to investors but you know sometimes they're going to outperform sometimes they're going to underperform and all of that is fine but I think you're right in saying maybe the best metric for them is really tracking error um because that's what they should be um you know held accountable for if they >> if they represent themselves as someone who can give you the index return ideally plus or something right >> yeah exactly So, back to this diversification. So, so for them, 10 10 20 30 markets is is sufficient for them um to try and minimize this tracking error. >> But for an outlier hunter like me, that's far too narrow for me. Um my whole edge comes from giving myself as many opportunities as possible to catch the big asymmetric moves. That means running the widest feasible portfolio I can, including markets that might be less liquid, might cost a bit more in slippage, or might be more quirky in behavior. But these are objectives that the replicator doesn't want because this this increases their tracking error. So here's the trade-off. If you run fewer markets, you might be tidier and more efficient operationally, but you're also increasing the role of luck in your results. missed the few markets that deliver the big wins in a given period and you're stuck with mediocrity. If you run maximum breath like riff, like the outlier hunter, you're reducing that luck factor. You'll inevitably have more unprofitable markets in the mix, but the one or two that go parabolic hopefully will more than compensate for it. So, this is where philosophy comes in. For me, diversification isn't optional. It's it's not just a portfolio construction choice. To me, it is my edge. Every additional market is another lottery ticket in the fat tail draw. If I only buy a handful of tickets, my odds of hitting the jackpot collapse. So, of course, this is not a universal law, but it applies to my outlier hunting. A core diversifier, for example, might not want 70 markets, 100 markets. The extra breadth could dilute their desired correlation profile. A crisis risk offset manager might be more selective, focusing on markets most likely to respond in equity drawdowns. But for an outlier hunter, cutting the universe down is like telling a fisherman they can only cast their net in one small bay instead of across the whole ocean. Sure, it's easier to manage, but the chance of landing the giant catch drops dramatically. So, this is where the debates get muddied. When someone says you don't need more than 30 markets, they might be perfectly right for their style, but if I applied that same advice, it would fundamentally compromise my ability to achieve my objectives. So before we get into the deep dive on diversification later, cuz I've actually got an example from an outliers perspective, which I think is going to be very interesting, it's worth remembering this isn't just a matter of personal taste. It's a structural decision that ties directly to your archetype and what you want your strategy to achieve. So before I move on into the second debate, do you want to make any comments here, Neils? No, I mean I think that this is the this is obviously one of the debates um that we've talked about a lot over the years. Um I think again um what often happens is that you get people from each camp talking in absolute saying, "Oh, this is better." or and the other ones are worse. Of course, the truth is that's not what the data shows. As you rightly said, at oddly enough, to some extent, at least many of the people who've been around for a long time, if you look at their returns, say over a rolling 10-year period, they're not vastly different overall, but they'll be vastly different in terms of when they occurred and so on and so forth. So um so I've obviously been part of the debate saying that when people uh a few years ago said well you need to trade three or four 500 markets uh you know I never bought quite into that because I couldn't see it in the performance data. I couldn't see the evidence. Um you can certainly agree that uh performance uh will is different but I'm just very cautious whenever I hear someone uh saying it's better and being very absolute about and this is also I think where some of the friction frankly uh in terms of this debate about are you a classic trend follower are you not a classic trend follower I think it's unnecessary and I know sometimes it's being said a little bit to be uh in gist and in being a little bit prerogative to get the debate going and that's perfectly fine. Um, but I think it's important for people who maybe not be as much into the details as we are that we're open about it that it's to some extent it's the preference from the design of our systems but it doesn't mean that we can objectively say oh if you look because as you well know rich some of the best performing strategies even in the outlier Honda camp so to speak has been portfolios with only 20 30 markets 40 markets in recent years. So of course there is no such thing as it's always going to be this way or that way. Um but you open a very important debate about it um in terms of how you see uh the best way of achieving your design goal meaning how many markets do I feel I should be trading if this is what I want to achieve because even within I guess your group of category uh as I said you'll find people who trade hundreds of markets I think you yourself trade less than 100 but you still get a lot of diversification and you're going to find people who trade even fewer than you do and they feel they get a lot of diversification. So it's >> it's a bit of you know there is some individual taste as well. Uh it's interesting Neil if you if you trade fewer markets you've got to you do different things with your strategies. So for instance with my say 100 markets or just just a bit less than 100 markets >> I have very simple strategies but if I deployed them um with less markets they'd be far less functional. So these decisions um they're not just um you know a single objective decision. They influence everything in your strategy design. So what I think if if you remember I think it was Harold Deir suggested that we really should be proud to call ourselves different in a trend following space. We we shouldn't be trying to be all homogeneous. And um I tend to agree with that. Maybe it's time that we started looking seriously at defining ourselves better into these different archetypes. It might help us better um rather than being classified as trend followers. So, you know, these debates are continually going to surface unless they take the deep dive we're doing here today to understand this. They're always going to be debated on on the social media, etc., oh, you're doing the wrong thing, he's doing the right thing, all of this stuff. But if they understand the broad objectives really that that all goes away. But anyway, look. Yeah. And and even even to a point uh Rich, even if they just understand the four or five categories you started out by laying out, I think that in itself will be extremely useful, very powerful actually from an allocator's perspective. Um because then they also know what to one expect um but also they would understand better how to combine these different design designs let's call it that uh in order to achieve um you know the highest probability of getting the outcome they want so they don't get disappointed. That's the >> the whole whole point. >> Okay. All right. So let's move on to the second debate. Absolute momentum versus cross-sectional momentum. So this tends to split the trend following world um in in debates, heated debates. So absolute momentum measures each market on its own terms. If a market is trending, you take the trade. If it isn't, you don't. Positions are allowed to run without being cut back just because something else is trending more. So this keeps your winners intact for as long as they want to go. But cross-sectional momentum on the other hand ranks all your markets against each other and tilts capital towards the strongest ones trimming or dropping the weaker ones. The approach smooth smooths returns controls risk and keeps a portfolio concentrated in current leaders. So for replicators or core diversifiers, two of those archetypes, cross-sectional momentum can be ideal. It keeps correlations in check, avoids dead weight, but for an outlier hunter, it can be poison. You may end up selling into strength and cutting the very trades that would have delivered your biggest lifetime wins. So, both camps have good reasons for their different styles. The key is knowing which one matches your purpose. Are you trying to smooth the ride or are you prepared to hold the choppy road if it means catching the rare monster trend? So, that that's a second broad debate. Once again tied to objectives, no right and wrong. So the third debate, this is where we talk about volatility targeting uh versus static small bets. So this is the debate that gets people fired up. We've had many of them Neils throughout the on the series because it touches the core of how you think about risk returns and philosophy as a trader. So on one side we have volatility targeters. So this is the camp where many replicators and core diversifiers live. They dynamically adjust position sizes as volatility changes, aiming to keep portfolio volatility constant. If a market's volatility spikes, they cut the position down. If volatility drops, they increase exposure. Now I'm not talking about done here, Neils, because that's a different form. That's dynamic position sizing, which classifies itself differently to that. But this is the broad general volatility target as I'm talking about here. So from their perspective, this makes perfect sense. It smooths the equity curve, keeps risk metrics like annualized standard deviation in check, and produces a more consistent ride for investors. It also helps align a strategy with a specific volatility budget, which is often a mandate requirement. So for an outlier hunter, this approach can be counterproductive, even dangerous for us. So my objective is to maximize the payoff from rare extreme moves. Those moves often come with surging volatility in the middle of a trend. So if I start cutting back my position size just because volatility has spiked, I'm potentially clipping the wings of my biggest winners. So if I think about it, if I catch a major uptrend in crude oil and volatility doubles halfway through, a volatility targeter will cut their position by half at the very moment the trend is accelerating. From my perspective, they've just reduced their potential payoff from my perspective because their metric told them to smooth the ride. I don't want to smooth the ride. I want to ride the wave in full. That's why I run equal small bets ATR ATR normalized at entry and then I leave them alone. I don't size up if volatility drops. I don't size down if it rises. Each trade is a small fixed piece of the fault portfolio designed that no single loss can hurt me too badly, but every winner can reach its full potential. And once again, that goes into the diversification. One reason why I diversify so widely, my bets stay so small for any particular adverse volatility move. But um so this is where philosophy splits. Are you optimizing for smoothness, consistency, and investor comfort? Or are you optimizing for convexity, the biggest possible payoff from the smallest possible risk on any single trade? Neither approach is right in a universal sense. Volatility targeting works brilliantly for strategies designed to deliver stable riskadjusted returns, especially when investors have a low tolerance for draw downs. But static small bets work brilliantly when your mission is to catch the home runs and accept that your equity curve will have more noise and bigger swings. And here it is where it loops back to my earlier point. If you judge both these styles on the same performance metrics, you might think one is better than the other, but you're not comparing like with like. One is optimizing for smoothness, the other for asymmetry. So I think this is why debates on social media get so heated. people talk past each other because they're implicitly defending the approach that fits their objectives, not necessarily your objectives. So, uh, before I move on to the fourth, anything you'd like to say here? >> That might be one or two things, Rich? >> Well, um, no, again, it's really about, for me, it's about the nuances, right? Because I I I I pay attention to the language you use. uh and you describe it really well. So great. But here here are a couple of things. When you talk about um the the static, you always talk about small bets, right? Well, actually, I think in fairness, I think there are small bets on both sides. I don't I don't think that the the volume targeting managers uh are taking big bets either. I think they're taking small bets. I think that's fine. um a and very importantly the volatility targeting and of course we know where that term kind of stems from right um I don't know that there are that many of them left because I think that some of the big firms um that we all know Europeanbased mainly I think >> um that's how they started >> but I don't think they do vault targeting today I I I think they do the same as on which is risk targeting. So we don't worry about whether the V will go from 20% rolling 12 months V to 30%. That's just the way it works, right? But we may have a cap on the overall uh value and risk we can take on any given day and so on and so forth. So there's this little hybrid in between which is very important because I actually think predominantly that's what people do today. Now that being said, that being said, there is one thing that I also think needs to be mentioned and that is when when in your camp the static position size even though it may be small to begin with. >> We have seen examples in the last few years where that little small bet became a monster in the portfolio and drove daily v drawd downs performance to an extreme. So much so that I've seen one fund go from an annualized V of around 35 to at some point have an annualized V of like 95. So this is what worries me to some extent is that it can be a little bit um seductive when you say oh we just take small bets so I'm not worried about it. No, no. Yeah. Yeah. But things can change. Um and so, but as long as people know that, it's not an issue. It's not a problem. It just needs to be made clear from upfront that that these are the differences. And investors, as you say, they have may one they may have one preference for someone who can really, you know, knock the ball out of the park um because of one market or two markets moving. um or someone where they say, "Yeah, if it gets too crazy, we're going to we're going to slow it down a little bit." But and this is the important part which rarely gets mentioned for people who do use volatility in the position sighting, whether they're risk managers or or va managers so to speak. The risk can also increase. It's not always about lowering the position size just because we have a big trend and and and we're we're uh limiting ourselves to have a great uh you know performance from that trend. No, no. We could in fact be actually lowering our position size at a time when the trend has risen but the volume increases then the market corrects then the market goes quiet then we increase the position size. We're still in the same position. It's just now being increased again and off goes the markets. So there's all these small nuances which of course in social media will never be mentioned. So we end up being you know as if we are massively disagreeing. I don't think we are because I think we understand what the real differences are and as you say there's no wrong or right. It's just a matter of preference. So internally within trend land we do we we have these vigorous discussions. They're not they're not uh you know in social media it might sort of turn into a bit of conflict here and there but certainly when we talk civily explain our position I think everyone in trend following land understands where we're coming from when we're talking about this. So yeah I agree with you but let's get on to this next debate. So >> this is something where I might be different to some other people in my space. This is symmetry versus asymmetry and rules. So >> Mhm. This one is about whether you treat long and short trades exactly the same >> or whether you design rules differently for each side. So replicators tend to keep symmetry. So if the long entry is a breakout above the 100 day high, the short entry will be a breakdown below the 100 day low. Same stop, same trailing logic, etc. Same risk parameters. This keeps the strategy clean and the benchmark aligned that it ensures no systematic bias towards one side. But not all camps take that approach. So crisis risk offset set strategies, for example, may intentionally favor the long side in certain markets, especially in government bonds or safe haven currencies because their primary mission is to deliver convexity during equity drawdowns. They might allow for slower, looser exits on those longs, but running tighter stops on shorts in risk assets. So outlier hunters like me sometimes I'm a bit different to other outlier hunters. So I'll consider asymmetry if it improves tail capture. So for example in commodity markets the most explosive moves are often on the long side during supply shocks. So like wheat in 2022, natural gas 2021. >> In those situations I might allow more room for longs to breathe than for shorts. So conversely in equities the most violent moves tend to be on the downside during crisis. So I might run wider trailing stops on shorts to fully participate in those collapses. So um this is where I might differ from some other of my colleagues. So the point is asymmetry is not about prediction. It's about structural reality. So different markets and different directions have different historical profiles for speed, magnitude and persistence. If your mission is to maximize convexity from those moves, it can make sense to reflect that in your rules. So, of course, symmetry does have its strengths, simplicity, elegance, fewer moving parts to explain to investors. But if you're willing to accept a bit more complexity, asymmetry can give you, I believe, an extra edge in those moments that matter most. So, again, this comes back to objectives. Are you designed for elegance and operational simplicity or are you designing for opportunistic capture of rare directional extremes? So that's on symmetry. >> You know, this is actually a point that I think uh is very rarely debated. Um and um I I don't think we've talked a lot about it actually on the podcast that being something of a design choice. I think for me >> asymmetry has a little bit of a taste of optimization, right? Let's be frank. That's kind of what we're trying to do. I think for me if you just use the same rules across all markets, etc. I think you could could argue um that maybe it's a more robust approach to to that. But again, why shouldn't you put your own taste in into your design? It's your system. So, of course, uh but and I think it's a really important point. Um not I don't know that many allocators ask us that question, frankly, which they should. Um, some do, some do, but I think it's a super super important one. And, um, yeah, I mean, it's worked really well for you, so why not? >> Well, it has, and you know, there might be instances as well where, uh, we're at a historic low on a particular commodity, etc. Um, we know that it hasn't got that far to go before zero. And, uh, you know, that therefore constrains how much of an outlier we can get from where it is now to where it is if if it gets to those >> those levels. So that that's why I do need to take that into account when I'm designing strategies. But um >> let's get on to this next debate, speed of execution. So >> how fast you want your systems to react. So short-term trend followers and traders running higher frequency systems, they want faster turnover, tighter stops, quicker responses to price reversals. Their argument is that the earlier you cut a losing trade, the smaller the damage and the earlier you enter a new move, the more of it you capture. This style often appeals to replicators who need tighter tracking of benchmarks and to some core diversifiers who value keeping portfolio risk tightly contained. So on the other side, however, the long horizon trend followers want to breathe through the noise. they're prepared to sit through more volatility in order to ride the multimonth, sometimes multi-year moves that deliver the real payoff. This is particularly true, for example, for us outlier hunters where the mission is not to catch every move, but to stay on the big ones for as long as possible. So, the danger with too much speed is that you can get chopped out of a long-term trend multiple times, missing the bulk of the payoff because you couldn't absorb the interim volatility. So speed is not just a technical parameter. It's a statement of philosophy. It says something about your tolerance for draw downs, your patience for building positions, and your willingness to endure short-term pain in pursuit of long-term gain. Ultimately, the right speed is determined by your true north, which of the four archetypes you belong to, and what your portfolio is designed to achieve. That's why for me this debate, like all the others, circles back to clarity of purpose. You can't choose the right reaction speed unless you're crystal clear on what your strategy is meant to deliver and over what horizon. Well, I mean, so speed is very interesting because it's something we often debate and it's something people will use uh as a classifier of what kind of manager they're looking for. Are you short-term, medium-term, and long-term? Now, of course, I think the the best answer is that you probably should be uh designing your system to be a little bit of everything, but not necessarily in a static way, which we did in the old days. I think it was natural in the old days that a lot of managers would sit once a year and have a committee saying 25% of our model should be short-term, 50% medium-term, and maybe 25% long-term. That's kind of how it was done. Today, you can do it in a much more um scientific way. You can do dynamic optimization. uh and and uh recalibration of your parameters and so on and so forth. The thing that makes a lot of sense. Now, when I look objectively at a trend model and I just simply apply different time frames, there is no doubt that long-term parameters work best. There's just no doubt. >> Yeah. >> For your objectives. But for instance in in the in the crisis offset camp or in in in those different object if their objectives are different it might not be for maximum kar >> it might be to provide downside protection and hence the short-term trend followers you know I can see it >> yes and that's the narrative that was sold to people a few years ago is a few years ago I remember that the word risk mitigation became a thing in the in the narrative right and and people were saying well markets are moving so quickly so you Oh, you should uh you should go with short-term managers. And some of the managers grew like massively, multi-billion dollar short-term managers. And I was kind of thinking, frankly, that's never going to work because you're going to have slippage and you got all these things. Now, so what's happened in reality? This is a good time to look back on it. Well, it's kind of the same thing as when people said, well, I'm just going to buy the VIX because when equity markets go down, I'm going to make money. They're going to go the VIX is going to go up. Well, surprise surprise. The VIX doesn't always go up when markets go down. And sometimes the VIX goes up when markets go up because it's much more nuanced today when you decompose what's causing say the VIX to move or not. We just did an episode that came out a couple of days ago on the on the whole VIX de composition. I think it's actually quite interesting to to learn from. However, back to our little uh sandbox. So, what I've seen at least or noticed is that some of these short-term managers um let's take the um uh the April liberation, right? Yeah. They may actually produce uh a decent better return for 2 days in the um uh you know when when when markets were tanking for two days in a row, but they lose it all the next 3 days or the next 5 days. So even within that space I think they provide less than a of a portfolio benefit today than they used to do. I think they used to the moves in the markets we used to be a little bit longer so that they could actually capture the the the the P&L from say a V breakout um capture that for 3 to 5 days and actually add benefit to the portfolio without detracting the next week for example. I see that it's a little bit more challenged today in doing so. Uh and as we talked about in the beginning, if you look at the uh stock and short-term traders index, it did really well relatively speaking in the beginning of the year. Today on a volad adjusted basis, it's doing worse than the trend following. And you wouldn't say that the last 6 months has been a trend following uh great environment. It should, if anything, be a short-term traders environment, but it's not. So, so I don't know. It must be something to do maybe with a market structure uh or something like that. But I think people have to be really careful uh in terms of saying, "Oh, we're short-term. We'll we'll definitely give you crisis alpha." H question mark today. It could it could >> validate first. Yes. >> True. I mean I mean the numbers is a good place to start, right? >> Yeah. Exactly. >> Okay. Where are we going now? >> So, where are we going to go now? So, now that we're living in this happy friendly place between trend followers, everyone knows what we're doing. We understand the archetypes. Now, I'm going to start looking at diversification. Um, because this to me defines my outlier edge and I just want to explain it to you. So if you're in the replicator camp, you can live with 20 to 30 very liquid markets, still meet your objectives. But if you're a quarter versifier, you might see trend as a satellite allocation and keep it even tighter. But if your objective is to hunt these outliers, max maximum breadth is not optional. It's the oxygen uh process breeze with. The fewer markets you trade, the higher the odds you'll miss the next wheat in 2022 or the JPY 2008 moment. That's where I want to go deeper next. Not just why diversification matters, but how the wrong approach to it quickly erodess the very edge you're trying to build. So I want to start with a real test I ran because it says more than any theoretical debate could. So, I built a 68 market portfolio designed for an outlier hunter. The test period was January the 1st, 2020 through to July 31st, 2025. In that time, the strategy generated 3,264 trades. So, here's the first surprising thing. Of those 68 markets, 27 were unprofitable over the entire test period. And yet, when we ran the portfolio equal weighted across all 68 with no hindsight application, it still delivered a MAR ratio of.8. So why? Because uh the big winners swamped the losers. the tail events when they happened more than paid for the markets that went nowhere or bled. So, let's flip this thought experiment. What if you could trade only 30 markets from this 68 market universe? No hindsight, no peeking at the winners. You just have to pick your set of 30 within the 68 and live with it. So, how many Neil's 30 market portfolios can you make from a universe of 68? And the answer is staggering. I don't expect you to get it. It's >> I was just going to say I hope it's not a question. >> No, it's 4.8 by 10 the 38th different combinations. It's almost an incomprehensible number. And to test what that means in practice, I randomly generated 300 different 30 market portfolios from this 68 market universe. Each was built blind by me. No for knowledge of which markets would perform the best. And I'll tell you what the results I got. Out of those 300 samples, only 35 of them achieved a mar greater than.8, eight, which is just 12% of that sample. >> Which means there's an 88% chance from that sample you'd underperform the full 68 market benchmark simply because of market selection. Not because your system was bad, but because of not because of execution errors, but because of the luck or lack of it in what you happen to include in your universe. And here's the thing. If you accidentally overweight those unprofitable markets in your smaller universe, you can spend years underwater. This is why for an outlier hunter like me, maximum diversification is non-negotiable. It's not about operational neatness. It's not about a clean marketing story. It's about reducing the role of luck in catching the next fat tail. So, if I think about it, small universes magnify luck. Large universes dilute luck. A great outlier in a market you don't trade is a missed opportunity. Pure luck if it's in your book. Pure bad luck if it's not. Managing that tradeoff is part of defining your archetype. So what the portfolio test really exposes is the shape of the return distribution for outlier hunting strategies. And it's not the tidy symmetrical bell curve that many investors imagine. Instead, it's lopsided, highly skewed, and brutally unforgiving to small sample sizes. So, if we look at those 300 random 30 market portfolios I tested, the median MAR ratio was nowhere near the8 we got from the full 68 markets. In fact, it was well under.5. That's the median. Meaning half the portfolios did worse than that. And if I looked at the 25th percentile, they were the unlucky quarter of portfolios that ended up in the bottom range. And many of them had mar ratios that would would be survival threatening if you're running real investor capital as an outlier hunter. These are the managers who would be showing three years of red ink, not because their process was broken, but because they simply didn't have have enough breadth to let probability do its work. And here's the kicker. At the other end of the distribution, a small handful of portfolios delivered absolutely extraordinary results, but you had to be lucky enough to land on them when choosing your 30 markets. That's the trap. So when you're hunting outliers, most portfolio outcomes will underwhelm a few will be exceptional. And if you reduce your universe, you dramatically increase the odds of drifting towards the noisy middle of the distribution where the edge erodess and your performance blends in with with everyone else's. So this is why I say the real enemy of the outlier is not volatility or drawdowns or even bad trades. It's the quiet invisible erosion of your edge through under diversification for the outlier hunter. So if your process is designed to capture rare events, you need enough hooks in the water to make sure you're there when they happen. And that's something the standard industry performance metrics. They don't reveal. Mah, sharp, kagar, they hide the fact the portfolio may be sitting on the knife edge of survivability risk simply because of the small number of markets being traded. So this is where the conversation comes full circle now is because diversification isn't a virtue in itself. It's a design choice that only makes sense when aligned with your objective. So if you're a replicator, 20 to 30 markets is often enough. Your job is to mirror the SGCTA index or a similar benchmark, keep cost tight, deliver a familiar performance profile. Brethren beyond that isn't necessary. In fact, it might just add operational complexity without adding much to your tracking accuracy. If you're a a core diversifier, trend following is probably just one sleeve of a larger multiasset portfolio. In that context, you're optimizing for incremental sharp or mar improvement at the whole portfolio level, not for maximum standalone performance from trend. Again, a smaller, highly liquid market will often serve you just fine in that context. If you're a crisis risk offset manager, the third archetype, you might have a longerterm, more convex profile and your market list could be biased towards assets that historically provide equity draw down protection. That's your northstar and diversification choices will reflect that even if it means trading fewer markets. But if you're an outlier hunter like me, the game changes here. Breth is not an accessory. It's a core operating principle. My edge comes from maximizing the number of independent opportunities to catch something truly explosive. And without a wide enough market set, the law of small numbers works against you. The cost of missing the big next move is far greater than the benefit of running a streamlined operation for me. So that's why in my own process, I'm prepared to trade some markets that aren't perfectly efficient, some that carry extra operational friction. live cattle, all of these small markets. Rubber, all of these small markets, milk, some that might spend long periods contributing nothing like Coco did for how many years because the payoff from just one of them hitting a fat tail event can outweigh years of mediocrity. So diversification, the approach you take should be dictated by your purpose. And that's where I think some of the industry debates get lost. They argue about the right number of markets or the right market selection criteria without first asking the most important question right for what objective. So I'm I'm going to close off now. I suppose we're getting to the end. But look, if there's one theme running through everything we've talked about today, it's that your objective dictates your design. Whether you're aiming for smoothness, index replication, crisis convexity, or outlier capture, each of these objectives demands different answers to the debates we've covered today. Volatility targeting versus static small bets, breadth versus concentration, symmetry versus asymmetry, and rules, short-term turnover versus long-term patience. None of these debates have a single right answer. They have a right for your purpose answer. And the trouble is the industry often flattens all these strategies into one homogenized peer group and then ranks them on the same metrics. It's like lining up a bus, sports car, a four-wheel drive, and a motorbike, then scoring them on their lap time around a racetrack. It's a misleading comparison, and it hides the strengths of each design. So, my encouragement to traders is this. Get crystal clear on what your strategy does and then build it to do exactly that. And for investors, look beyond the surface metrics and ask whether the strategy you're buying into is actually designed to meet the role you need it to play. So in trend following, alignment between purpose and design isn't just important to me, it's everything. So there you go, Neils. >> No, no, I mean, great. Let me um add a few thoughts. uh to the point um that you uh mention here I have two questions for you one is is there a number and I know it's going to be an approximate number where you would say well anything above this is not going to give me more indep because you mentioned the word independent uh markets or bets um so that's one thing because I do think that people also misuse that a little bit saying well 500 markets surely will be better. I don't agree with that. Uh so I I wanted to ask you if you in your research have roughly an idea of what that number will be where you feel I've got maximum diversification. That's one point. And then the other point and I do think this is relevant because it it it it does um introduce some other factors and that is would you go uh in order to have more markets would you go off exchange introducing counterparty risks uh would you go to countries where uh maybe the um regulation the regime is less uh as we're used to in the western world and introduces other risk. So what what are your thoughts on that in terms of your preferences? >> So so my preferences first market diversification to me that is limited by your capital. I would I would continue to diversify capital. So let's say I I had a diversification of 100 markets and my capital significantly increased. So typically there's the decision do how do I scale up my results? Do I increase position sizing or do I invest that extra capital in new markets or do I invest that extra capital in new systems? So my priority would be always invest in new markets provided and this this will flow into the second question for always invest in new markets. I do find system diversification to me maxes out at about 10 different trend following systems. So they are system diversification is wonderful to deliberately inject uncorrelated properties into your market portfolios. So that's why I can trade Brent and crude with trend following ensembles and they don't produce a correlated result. They deliberately break that down. But there is a limit to the benefit of diversification. So I'd go 10 systems. As far as market diversification, I would always prefer to invest in more markets and increase my position sizing for instance. >> But isn't there a limit rich though where you say actually at market number 251 I'm not getting I can't find any independent markets or um I don't want to go to a certain region of the world where you know >> there's definitely those limits. So there's definitely so that liquidity is another key requirement. I do require liquidity. Um and also um the additional risks you mentioned going off exchange and things I don't think it's worth the risk. So within that it it really does cap you out um as we we know but if if for instance it could increase I probably would go with it because my my my underlying mantra is I just don't know where the next outlier is going to come from. I do know that any liquid market over the long term has these fat tail properties. So um yeah I I I would tend that that's why to me you know that Pierce Brosman um the world is not enough James Bond I say diversification is never enough >> that's a good that's a good way to to end our conversation but I don't want to end it completely I I do want to say a big thank you for providing this wonderful framework of discussing trend in in in a new light that that's really wonderful I'm sure people will uh uh enjoy that and and find you know a lot of uh benefit from from this. Um and hopefully implement some of these things. Um and if you do let us know by the way if you've gone out and you know quantified or or categorized managers in in these buckets uh that would be fantastic. I do want to go back to AI though before we finish. I completely forgot to mention two things to you. So, uh, in terms of AI, this recording platform we're recording on, um, actually has, uh, which is new to me, um, and, um, and it has this feature where I noticed that in the post-prouction, it says, "Oh, I can do, uh, text to speech and it'll be used in AI." So, I thought that could be fun. So, I just posted in a a snippet of what I had said in an episode and let it generate a um, an AI voice for me. And you know what came out? It gave me an Australian accent. >> Oh, there. Look, you can't object to that, Neils. >> Well, no, I just thought that was funny. Why would you choose an Australian accent? Maybe I sound like an Australian. I I did I don't know. I think I I sound like a Dane who's living abroad too too long. Anyways, I thought that was a little bit funny since you're on. The second thing actually I completely forget forgot to say is you you praised the Chat DBT5. I read a very different post uh critique of chat DBT5 this morning actually someone who was very concerned about what was happening because it sounded like on on for in this post it sounded like what they're doing is they're limiting your choices that you cannot go back and choose number four or number three or whatever. Now they're giving you just five and they're saying oh we're going to choose the one for you that's the best for your purpose. But what they're really doing is saying, well, we're going to give you the one where we don't constrain our system too much because it's bloody expensive to do these uh queries. So in in people, oh, but if you want choice, it cost you $200 a month or whatever. So actually this guy was very critical about where it was heading and not seeing this as any improvement. On the contrary, for us as users, this was actually a much much worse outcome. Even though, of course, it's going to be sold as the best AI that's ever been uh published by by Sam and his his friends. Um, but not just OpenAI, also all the other ones. So, anyways, just to be mindful um about these things. Uh, I just wanted to throw that in. As I said, Rich, this was fantastic. I can't wait to see you in person soon uh here in in uh in Europe. Um if you want to say a big thanks to Rich, the best way to do that is just to go on your favorite podcast platform, leave a fivestar rating and review. Um and that's going to be the best way for other people to see uh the show and listen to this conversation. Next week I'm joined by Y of Git. He's back. So that will be another way for us to tackle some of your questions. Um, so if you have any topics that's related to uh what we like to talk about with Y, uh, do send me an email info@ toptradersblog.com. From Rich and me, thanks ever so much for listening. We look forward to being back with you next week. And until next time, as usual, take care of yourself and take care of each other. Thanks for listening to Top Traders Unplugged. If you feel you learned something of value from today's episode, the best way to stay updated is to go on over to iTunes and subscribe to the show so that you'll be sure to get all the new episodes as they're released. We have some amazing guests lined up for you. And to ensure our show continues to grow, please leave us an honest rating and review in iTunes. It only takes a minute and it's the best way to show us you love the podcast. We'll see you next time on Top Traders Unplugged. [Music]

The Four Faces of Trend Following | Systematic Investor | Ep.361

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