Why Trend Following Works | Systematic Investor | Ep.391
Summary
Energy Markets: In-depth discussion of crude oil’s 80% spike and rapid 30% reversal, framing it as a structural overreaction in a market primed by suppressed volatility and heavy short positioning.
Inflation Transmission: Oil price shocks feed through transport, manufacturing inputs, and food costs, creating sticky inflation via fuel surcharges, higher input prices, and wage pressures.
Central Banks: Historical parallels to the 1970s suggest policymakers may tighten quickly, with higher borrowing costs across mortgages, business loans, and sovereign debt if energy-driven inflation persists.
Market Structure: Evidence of fat tails, volatility clustering, and long-range dependence supports the persistence of trends and explains sharp regime shifts when amplifying participants cross critical thresholds.
Risk Management: Bell-curve assumptions severely underestimate tail risks; the oil move exemplifies why VAR and fixed-vol targeting can misjudge exposures in power-law environments.
Global Supply Dynamics: Strait of Hormuz disruptions (c. 20 mbpd) and storage constraints can force production cuts and refinery shutdowns, amplifying second- and third-order effects.
CTA Performance: Longer-term trend strategies hit new highs while short-term traders lag, highlighting the advantage of capturing extended moves in volatile regimes.
Outlook: If the energy shock endures, inflation and rates could rise meaningfully, favoring robust, diversified trend-following approaches across asset classes.
Transcript
Imagine [music] spending an hour with the world's greatest traders. Imagine learning from their experiences, their successes, and their [music] failures. Imagine no more. Welcome to Top Traders Unplugged, [music] 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, [music] 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 [music] anything about future performance. Also understand that there's a significant risk of financial loss with all [music] 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 [music] 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 Blen, where each week we take the pulse of the global markets through the lens of a rules-based investor. And I also want to say a warm welcome if today's your first time you're joining us. And if someone who cares about you and your portfolio recommended that you tune in to the podcast, I want to say a big thank you for sharing this episode with your friends and colleagues. It really does mean a lot to us. Rich, it is wonderful as always to be back with you this week. How are you doing? How are you keeping down under? >> Well, it's very hot down here, Neils, and sort of in Australia down here, we either have fires or flood. And at the moment, we're in floods. So, the to the north of us and um certainly in the Northern Territory, they're experiencing very large floods at the moment. So, we can't get it right down here with the weather. It's it's either it's extremes from either end. you know, the Danish king and queen is going to visit Australia very shortly as far as Yeah. [laughter] Well, I'm sure they're not coming by boat uh all that way, but uh they may need one. So, anyways, good to hear. Well, we got an absolutely fantastic lineup of uh topics to discuss today. something I think is pretty groundbreaking uh to be frank and um obviously related to trend following but still in a brand new way that um I think people are really going to want to uh listen to. So can't wait to get into that. But of course as we always do we kind of share things that has been on our radar um in the recent weeks and I know that you've been watching something in the energy markets that may have caught your attention. So uh tell us what's uh share share your secrets. >> Well Neil's sort of crude oil is definitely on my radar right now. So but look rather than getting into the geopolitical narrative about it. What I find more interesting is regarding what the market's reaction itself is telling us about the state of the system when the shock arrived. So, and once I've covered that, I then want to talk about why a move like this in crude oil has consequences that go well beyond just the energy markets. So, I I'll set the scene first. So, this is how I see it. For most of 2024 through to 2025, crude oil was drifting steadily lower. The WTI fell from around $87 US all the way down to roughly $66 over about 18 months. And it was an orderly uneventful decline. No urgency. Each time the market tried to rally, it faded. And the stabilizing forces of the market were firmly in control during that period. But then a few weeks ago, as we all know, everything changed. Crude oil spiked from $66 US all the way up to around about $119 in a very short space of time. That was an 80% move. And then almost immediately it started giving it back, dropping to around $84 by March the 10th. That's a 30% reversal in just a matter of days. So I'm not dismissing the fundamental case. There is a genuine supply risk being priced here. Tension in a region that controls a meaningful share of global production. But the the question I keep coming back to is this. Does an 80% spike followed by an immediate 30% reversal look like a market that is calmly and rationally repricing a real supply threat? Or does it look like a system that was primed to overreact and did exactly that? So to me, this is exactly what it looks like um for a market that that it's like when lightning hits dry undergrowth as as Dave Dredge would say. The the undergrowth here was the setup over the last two years. Crude oil had been grinding lower for about 18 months. Short interest had built up steadily. The market had been quiet long enough that the amplifying forces, the momentum traders, the the trend signals had largely stepped away and the system was loaded with convergence. But all it needed was a catalyst. And that's the key point. So the move from $66 to $119 um dollars was not purely about oil supply to me at least. It was about the state of the market that received the shock. So when you have heavy short positioning as we did for 2 years, suppressed volatility and a long period of onedirectional drift, you have a market that is structurally coiled. So the geopolitical event was the ignition. The fuel had been building however for over a year and then the snap back from 119 back to $84 US. That's not the market calmly reconsidering the supply outlook. That's a system that overshot with the participants who chased the spike getting stopped out. Momentum signals flipping. The same dynamics that drove up is now working in reverse. So that's how I'm seeing this move in oil. It's not just about the fundamentals. I think the state of the market was prime for it. What What do you think? >> So, first of all, um and I don't know that people really think about it this way, but but actually it it first of all means that oil is in a bare market right now because it's more than a 20% correction from a high, which is obviously silly to say, but it's actually how technically it is. Um now you know people who have listened to the podcast over the years um they would have heard me say many times that I think we were entering this world where or maybe we've already always been there that you had to be able to kind of imagine the unimaginable right this is one way of visualizing something that we probably never thought would ever going to happen. your point about the buildup and all of that uh obviously takes me back to and I don't know if this is the right uh comparison but when you think about what happened to things like inflation whereby it was so wellmanaged uh for many many years in the 2010s and obviously we know that that wasn't great for trend following but as soon as the pandemic came and was maybe in that case kind of the trigger. We saw inflation go up by four or 500%. Right, from 2% to 10 11%. >> So, it's kind of the same thing as you're pointing out here that >> we can try and manage things for a while, but it also seems like the more we succeed in that, the more we build up the potential uh for something very uh consequential to take place uh after that. Yeah. >> And unfortunately, I do feel that a lot of what's going on in in in the world, it's always managed. It's always manipulated. It's always has some kind of political agenda. I mean, we we know that the current administration, maybe even the previous administration, they would like to have lower energy prices, right? Because it's good for the for getting reelected. And it may, as you say, it may work for a while, but when it doesn't work anymore, it also shows you the power of the markets, just like you say in as as Dave says in in his writings about, you know, the the undergrowth and and as soon as you ignite that, how quickly it spreads, how powerful it is, and we unfortunately see real life examples of that in California and other places. It's the respect of what comes after a calm period that I think sometimes people get just way too complacent. And that's obviously one thing that and I know we're going to be talking about obviously trend following today, but I think that's what I really love about our strategy and always have and that is we we never get bored. We never get tired. Uh the models just wait. They they don't you know even if it takes a year or even if it takes three years I mean think about Coco. it took like 15 years for it to really give us something uh that we could um that we could benefit from. So it's the diversification not just of returns but it's the diversification of of investment process that I find so powerful and so useful for pretty much 99% of people's portfolio. Um so yes it it manifests itself in a way of a non-correlated return stream. Sure, we can we can talk about that, but we need to dig a little bit deeper. What what is it that generates that non-correlated return stream and all the moving part that goes into that and the different way we approach things from an investment point of view? And I think certainly in my recent meetings and travels uh even this week when the penny drops in terms of diversification of investment process, it's almost like a little bit of a sort of light bulb moment. >> Yeah. Ah, that's why it's so important to have in in the portfolio because they can have all the right opinions and they can, >> you know, possibly be right about many things, but but also as as uh Dave writes, it's about what you have in your portfolio when you're wrong. >> It's not just about being right. It's what what what do you have in your portfolio when you're wrong? >> So, um so that's one. The other thing I just want to mention uh something I learned yesterday listening to um to the OddLots podcast uh where one of our previous guests Roy Johnson was on and talking a little bit about the oil thing. I I had not appreciated that actually right now. The reason why the Homo Strait is is so critical is that we've got about 20 million barrels per day trapped uh in that area. and 20 million barrels. That's actually the same amount uh that we saw in terms of demand destruction when the whole world closed down uh during the pandemic. So it's not an insignificant amount. Now it's not so much that it's stuck, it's also the fact that when things are stuck um and and you remember this uh for sure when oil prices went negative because of the storage. So the fact that they cannot get this the the oil out means that the storage facilities are basically filling up. And once you get to that point which may already have been reached um you have to start not only just lowering your production but if you get to the worst critical point and you actually shut down some of these refineries it takes a lot of effort and a lot of time to restart them. So then you get all these second, third, fourth, whatever uh effects uh of of of what's going on right now. So anyways, we'll talk about this some more, I'm sure. >> I'd like to stay on this a bit because it actually does relate to some of my topics a bit later on. So >> okay, >> um >> what makes this move in crude oil so much beyond the energy market itself is that crude oil is probably the single most consequential input price in any economy. So it flows through almost everything we consume and produce. So the transmission starts with transport. Every physical good on every shelf was at some point moved by a truck, a ship, a plane. Uh when diesel spikes, the cost of moving anything goes up and every business in the chain passes that forward rather than absorbing it. So there comes the inflation. So then you have manufacturing um because oil derivatives from uh they're the raw material for plastics, synthetic fibers, pharmaceuticals, lubricants, countless other industrial agents, >> even the top traders unplug merch that you're wearing so beautifully. >> Exactly. I'm glad you got it before this oil spike. So food of course modern farming heavily diesel dependent crucially you know nitrogen fertilizer I believe is made from natural gas. So an energy shock feeds directly into the cost of growing food and then with a bit of a lag you get wage pressures because when commuting costs rise food prices rise workers eventually push for higher pay to compensate. that embeds the shock in a way that's very hard to reverse. And on top of all that, you've got the central bank responses. So, this brings me back to the 1970s when policy makers tolerated oildriven inflation for too long. And that was a a [clears throat] cost that took decades um to bring back under control. So, the modern instinct for central banks is therefore to act quickly and raise rates. And when rates rise, borrowing costs go up across the board, mortgages, business loans, government debt, all of it, all associated to the underlying oil crisis. So this move from $66 to $119 in crude is not just an energy story. It's a potential shock to the cost of almost everything in the global economy, hitting through multiple channels at once. And here's this asymmetry that makes it particularly sticky. Prices go up fast and come down slowly. So the trucking firm that raised the fuel search charge at the peak of the move is not going to immediately cut it when crude drops back. The food producer that puts prices up, citing higher input costs, they're not going to reverse that spontaneously. So the inflationary pressure tends to linger well after the commodity prices pull back which brings me to how we started this conversation that spiked to $119 and the reversal to $84. They're telling us that the market has not yet made up its mind. Is this a genuine fundamental repricing or was it primarily a positiondriven overshoot? Those two scenarios have very different consequences for bonds, currencies, equities, central bank policy. But I suppose as trend followers, you and me, Neils, we don't need to decide this invance. I I suppose we just need to stay positioned to participate in whatever the outcome the market confirms. So the market's going to tell us ultimately and I suppose our job is just to follow the trend. >> Yeah. No, absolutely. Listen to the data. Um like often people say that actually we should all get better at listening and not talking too much which is hard sometimes on a podcast but there we are. [snorts] Um but also you know with this old oil story of course it is pretty significant the way um you know the reactions you know this release that they talk about now of I don't know hundreds of millions of barrels and and all of that stuff. The saddest thing I think in all of this is this is a little bit political which I try not to. It's just the fact that we are now relying on a place like Russia to increase its oil production to offset some of this uh which from a European perspective is probably not really what we would like to see unfortunately if we should if if there should be any chance of stopping all these conflicts. But um there we are. We'll leave it at that. Other things that hit my radar, um, by the way, was the fact that our shock gen trend following index hit a new all-time high at the end of February. M >> so we're back from the brink of uh June of last year where many commentators and the narrative was pretty much um in this um narrative political driven world where news flashes drives markets um more than anything else clearly a long-term slow strategy would not be the right thing to have in your portfolio. you should be in short-term quick moving strategies. Um, obviously I can't help notice the fact that um the longerterm strategies have had a very strong uh consistent uh run as I mentioned uh uh the sock gen trend index is back at new all-time highs. Uh whilst the short-term traders index also from Sockgen uh is still somewhat below it's um it's only recovered about 50% of that draw down that it was in um and is still some way away from getting back to a new uh all-time high. In addition to that, of course, the longerterm performance between those two indices is is is very significant uh and and in favor of the longerterm strategy. So interesting to see what's going on and why that is. Uh hopefully we can bring someone on uh on the podcast soon that can tell us a little bit more about that. Um that would be that would be great. Before I forget, by the way, for those who have not downloaded the latest version of the ultimate guide uh that I publish usually once a year, there is a new version out, an eighth edition. Uh, I think we're up to more than 600 books. If anyone wants to download it, just hit go over to toptradersblog.comultimate. Okay. Now, trend following. Just do this section now before we get into the the real meat of our conversation today. My own trend barometer finished at 50 uh last night. Uh, that's still a strong reading. Uh, meaning that there is fair fairly good breath in in a classical portfolio of trend following. We do of course have an interesting start to March. some give back uh clearly uh with what's happened uh trend followers I would say most of them were on the right side of the move despite what you mentioned correctly is that trend sorry oil uh had been in a downtrend for quite a while but that kind of changed going into February midFebruary where where I think many models would have picked up a change in direction before it got too crazy which was very um useful when when you uh at the same time would have lost money in equities, currencies, probably fixed income as well. Um did not quite react in a direction of of the trend followers would like. Anyway, so so that's where we are on that. In terms of performance so far in um in March, indices are down. Uh not surprising. Uh the beta 50 index is probably down a couple of percent still up 4.67% so far this year. Shock CTA index is down 2.06 uh so far and uh also up about uh 6.11% trend index also down 2.16% but still up 6.44% 4% and the short-term traders index um I'm not entirely sure about this number. I think it's down uh also a little bit this month and up around 3 and a quarter so far this year. Uh in terms of the real uh traditional markets, Msei World, so equities are being hit down 2.8% as of last night. They're now flat for the year. The uh aggregate bond index in the US is down 1.21%. So no help from from bonds. Uh still up 43 basis points. so far this year. And the S&P 500 down about 1.44% in March and it's down for the year. Uh but only slight 0.77% so far this year. I already mentioned I think that uh you know the energy sectors have done well for trend followers. Uh we've been hurt elsewhere. uh of course uh equities some of the currencies and and some of the fixed income although some fixed income markets may actually have helped uh in the first few days of uh March positioning wise I'm not so sure that a lot has changed markets are overall relatively muted except for what's going on in energies uh even the precious metals um not done a lot sold off a little bit most likely because people can raise some cash uh to cover maybe uh losses elsewhere in the portfolio. I did read somewhere this morning, Rich, that some of these quote unquote multi- uh pot shops or multistrat funds or whatever uh has had a a little bit of a a tough time uh in March. So maybe their style of trading where I imagine it's not really trend following um has found its match uh when something like this happens. Um but uh of course markets have moved dramatically. heating oil to just to give an example despite the correction it's still up 52% so far this month and crude is up around 40% uh from the end of February uh so far this month so pretty big on the other side of that spectrum we have things like silver platinum down around 9% so far this month so decent moves for sure >> now I well I'll allow you of course uh Rich any thoughts on the trend space right now before we dive into the more um meaty topics we have to get through today. >> Well, I I I think we we're coming into a a very beneficial regime for trend following simply because of the fact that um I think the market's starting to expose a lot of tail properties. Um this is uh not something you see often, but uh we're certainly seeing it at the moment. Um we we saw it uh last month with gold, the metals, um etc. And now we're seeing with the energies um we're seeing this, we talked about it before, the the impacts of delobalization um all of these things are flowing through into being very beneficial markets for trend followers. Um I would therefore suspect that um a lot of the alternative styles of strategy that have been particularly successful over the last decade or so um may find that they're struggling in this particular regime. So when you when you talk about the the pod shops etc uh this is sort of uh probably uh a regime they're not familiar with or used to. You usually find that uh when you start getting into a market that's uh exhibit C's tail properties uh nearly all strategies fall over apart from u the good old trend followers um long V strategies those sort of variants so um I think it's going to be a very challenging time for alternative strategies but I'm very thankful [music] we've got our particular strategy going into this regime. [music] Well, let's dive into this. I I I mentioned already that it is pretty um pretty extraordinary, I think, what we're going to talk about now. Um you just uh published a new book, The Fractals of Finance. First of all, great. Congratulations. Uh not easy to bring about a book. Um so, um so that's great. And what we're going to do today, we're going to spend the conversation going through the empirical findings uh that kind of underpins uh that book and and that research that goes into the into it. Now, in order to do this, you've built a research program covering um 68 uh futures markets across eight different uh classes. So we have equities, bonds, currencies, energies, metals, agriculturals using daily data uh stretching back to 1984. It's so funny when I read these numbers. I it's almost like exactly like the portfolio we run at done 84. [laughter] So and since ' 84. Anyways, the question driving all of this uh is to some extent quite simple and that is why do patterns uh that trend followers depend on actually exist? uh not as a matter of strategy aside but as more as a kind of a structural property of markets themselves. So what we're going to discuss today is the empirical case kind of the data the logic and what that really means for anyone who trades um for a living or invest with managers uh such as ourselves. So Rich um can't wait to hear what uh what you found. >> Well well thanks Neil. So the research that informed the book I wrote um starts with a simple logical test and I want to explain it up front because it it shapes everything that follows. So the test works like this. So imagine a world where markets had no memory at all where each price move was completely independent of the one before it. In that world, three things would have to be true. Trends could not persist because there would be nothing carrying a move forward from one day to the next. Returns would cluster tightly around an average following a normal bell curve and volatility would be all would be very steady and predictable because there'd be no mechanism for turbulent periods to bunch together. So those aren't opinions. They're the mathematical consequences of a world without feedback or memory. So therefore, I turned the question round. If we find that trends do persist, that returns are not bell-shaped and that volatile periods do cluster together and if we find all three of these things simultaneously in every market we can study, then the conclusion is therefore inescapable. Feedback is not a feature of some markets in some periods. It's the fundamental structural property of financial markets. So that's what I set out to test and I'll tell you what I found in this research. So >> okay, >> the first thing we measured was whether markets have memory in their structure. Not whether each daily move predicts the next, but whether the behavior of prices over time carries the fingerprints of a process that remembers its own past. So the tool for this that we used was the her hurst exponent. Um that produces a number between zero and one. A score of 0.5 means the price path is consistent with pure randomness. No memory no structure. But if the it falls above 0.5 this means the process exhibits long range dependence that the scaling behavior of price moves through time is not consistent with randomness but if it falls below 0.5 that means the process is mean reverting in its structure. So I I want to be precise here about what the Hurst exponent is and and what it's not measuring. So, it's not saying that because the market went up today, it's more likely to go up tomorrow. That kind of simple day-to-day directional persistence is actually close to zero in practice and rightly so because if if um it were strong, it would be immediately arbitrageed away. But what the Hurst exponent is measuring is something deeper. It's capturing whether the magnitude and the clustering of moves, the way volatility behaves, the way large moves small follow large moves and quiet periods follow quiet periods exhibits a kind of memory that a purely random process would not produce. So it's a measure of how the process scales through time. And what we found across all the 68 markets in the study, the average Hurst exponent was not.5, it was 0.866. It was not in some markets, not in some periods, every single market, every decade. And when we broke the data into decades, the results barely moved. So decade averages range from between 707 to 757 across four decades through financial crisis, regime changes and everything in between. So that structural memory was always there. It didn't go away. It was not a feature of one era. It was baked into the behavior of these markets at all times. So what this means practically is that the conditions which sustain a trend, elevated volatility, clustering of moves in one direction, amplifying participant behavior tend to persist once they're established. So the market does not reset to a blank slate each day. It carries forward the character of what has been happening. And that's the environment in which trend following operates. Not because each daily step is predictably directional, but because the conditions that produce sustained moves have memory. So think about that oil move we were discussing earlier. So the 80% spike that didn't happen because each day mchanically followed the last. It happened because the conditions that made the system explosive, the positioning, the suppressed volatility, the absence of amplifying participants accumulated over time from 2024 to 2025 and then they all released together. So that is long range dependence expressing itself. So the Hurst evidence is telling us that this kind of accumulation and release is not an accident of one market or one moment. It's the normal behavior of these systems. But the finding alone does not complete the case we're after. So a world with this kind of structural memory but normally distributed returns for example and steady volatility would still be a very different world from the one we actually trade. So, we kept going in our research. >> Mhm. Okay. Well, let's let's just make sure that people fully uh kind of embrace what you just said. Um um because there are some subtle and very important uh distinctions here. So, so you're not claiming that markets trend in a simple day-to-day sense. And by the way, is that what people sometimes refer to as autocorrelation? um that that's what they say is the reason why trend works and you're saying actually no you're saying the memory lives in the structure of how moves behave over time in the clustering and in the scaling so the way the conditions persist once they are established um if if if that's what I'm >> that's exactly right Neils and look um in our next podcast we we do go onto a phase two of this exercise where we look at the autocorrelation feature that that is in markets. But um when you look at very large data sets um the directional correlation effectively averages out to zero. >> But um this is um this is something I'll reserve for the the later podcast with you. It's a very deceptive average. I'll just say that. >> But what we are talking about now is really the absolute magnitude of moves. Very large moves follow large moves. Very quiet moves follow quiet moves. It's a magnitude we're talking about here in this particular um segment that we're talking about here. So there is an important clarification. So simple directional autocorrelation that that means the idea that up today means up tomorrow is indeed close to zero over these large samples. >> Um I'll talk about that in our next podcast how we broke that down. >> Okay. >> Um I don't want to preempt that. But what the hurst evidence is capturing in this research is u is something that can't be arbitrageed away as easily because it's not a simple signal you can trade on each day. It's a property of the process itself. So the way energy accumulates in the system, the way volatility clusters, the way the character of a market once it shifts into a trending state tends to persist rather than immediately revert. That's what creates the environment for trend following to work and that is what the data shows. So if you imagine that oil move Neils that was a volatility burst but it was a directional persisting move that could be exploited by trend it was actually the volatility expansion that we were capturing there and that is what this magn this absolute magnitude approach is is telling us this volatility clusters that that's why we can exploit these opportunities. is not the the directional day-to-day move. It's the explosive volatility out of a calm period or a compressed state. That's what we're actually exploiting with with um a lot of our models. But um so that's what the data is showing us consistently across every market and every decade we study. So this independence assumption at the heart of the standard model, the efficient market hypothesis, says none of this should exist. The fact is that it does universally and it's persistent. It tells us that the model was wrong from the start. So markets are not populated by independent agents processing information in isolation. They are populated by participants who watch each other, respond to each other, and in doing so create feedback that leaves a structural trace in the data. And that trace is what the hertz exponent is measuring. So we then moved on to a second piece of research just to give us a strengthening argument here. >> Okay. >> So this concerns the distribution of returns and this is where the standard finance model looks most seriously wrong. So under the standard model extreme daily moves are not just rare they are astronomically rare. So a five sigma event which is a daily move five standard deviations from the average should occur roughly once every 3 and a half million trading days. So in the entire history of liquid financial markets we have not accumulated 3 1/2 million trading days. So in a world of bell curve returns we should essentially never see a five sigma event. But in our data set that we studied, five sigma events occurred 5,791 times more frequently than the standard model predicts. It's not a rounding error. It's not a modest discrepancy. It's nearly 6,000 times more frequent. And when we looked at the mathematical shape of the tails, we found a pattern consistent with a power law distribution, not a bell curve. So the tail exponent was approximately 3.33. >> Can you explain the 3.33 I what? >> So this this is measuring the the power of the tails. What lies in the tails? The 3.33 is pushing us right out into the tail regions. It's saying that we're dealing with leptocortic distributions here. We're not dealing with bell curves. So in every single liquid market we assessed it had this leptocourtic property and it had this tail exponent of about 3.33. So the practical consequence of this is is enormous. So if your risk model assumes bell curve returns, you're not slightly underestimating the probability of large losses. You are underestimating it by orders of magnitude. And this isn't a quirk of one market or one period. it's present across all eight asset classes in the study. So the crude oil move is a perfect illustration. So a move from $66 to $119 followed by a reversal to $84 all within weeks. Both the spike and the correction sit deep in the fat tail territory. They're not anomalies. They're exactly what a power law distribution produces. So this is not exceptional behavior. This is what these markets do. So we looked at these sigma properties of the financial markets. Now the third piece of evidence we collected was volatility clustering and this is the tendency for turbulent periods to bunch together. So large moves followed by large moves, calm periods followed by calm. So we measured this using the autocorrelation of the size of daily moves across all 68 markets and the average was 353. That is a strong consistent signal that volatility has memory not just direction. So now we've got all three of these properties. We've got trend memory. We've got fat tails. We've got volatility clustering. All three predictions of the no feedback world are false. And they're false not in some markets or some periods, but in 68 of of across eight asset classes across 40 years of daily data. So there's something more interesting to say about what the distribution itself is telling us. And that's because that distinctive shape, the the tall narrow peak and the heavy tails, it's not just a consequence of feedback, it's a signature of a market with two distinct types of participant operating at the same time. This is where it gets interesting. So some participants in the market behave in a stabilizing way. And you and I Neils, we know them as convergent participants. So when price moves away from where they think it should be, they push back against it. Value buyers for example, arbitrageers, mean reversion traders, they fit into this class of convergent trader. They produce the actual tall narrow peak of the curve because most of the time they they dominate um at at most of the time and moves are small. So therefore they're clustering around the peak of the distribution. That's why we get the tall peak. But these other participants which you and I are, they behave in an amplifying way and we refer to them as divergent participants. So they push in the the direction the market's already moving rather than against it. We are going in the we're amplifying the move not suppressing the move. So this includes trend followers, momentum traders. It also includes when stop-loss orders accelerate a decline and when margin calls force selling into a falling market. These are all amplifying moves and they produce the fact tales because periodically their collective behavior overwhelms the stabilizing forces and you get these extreme outcomes. So this means that as trend followers we're not external observers of these dynamics. We are participants in the feedback system itself that generate the very phenomena we exploit. So understanding that changes how you think about what trend following actually is. It's not just a strategy. It's alignment with a structural feature of how prices form. So the universal vers the universality of this really matters. So those same three signatures that we discussed earlier across equities, fixed income, currencies, energy, metals, agricultural, commodities, every asset class, every decade, the architecture is the same everywhere. I want to go back to something you said and I don't I want I don't want to make this a controversial point for some listeners who may have a certain uh way of doing trend following but you said something interesting um you said something and I obviously don't have the exact quote in my head but you said something about that uh you know what we do also is we kind of capture this volatility expansion or something along those lines. Is that correct? >> Yeah that's that's right. In in a sense when I heard that I was immediately thinking well [snorts] then that maybe means that there is some value maybe to dynamic position sizing in a sense that in order to capture that vol expansion you kind of also need to reduce your exposure as the expansion happens before it collapses again or the price collapses. again um we don't know need to go go into it but maybe we will get into it in a in a second um the other thing when I just heard you talk about how we are the amplifiers often but of course and and this is actually something that people often use as a negative if we amplify the rise of of wheat prices or the rise of something oil prices for that matter now we are to blame for for all of this um but as you and I know at least the part of the CTA universe that does have dynamic position sizing. We're actually going to be selling oil as counterintuitive as it may sound, but we'll probably be selling oil the last few days in order to adjust our positions down within a certain risk framework. Um, so in that sense, we will sometimes suppress perhaps the uh the move a little bit um to the benefit of of uh of some uh perhaps. So, it's it's kind of an interesting and and it goes back to this idea about we talked about earlier on about the why I love trend following is also the fact that it's so adaptable. It's this investment process. It's almost like you know uh was it Bruce Lee who said be water. I mean it's almost like it flows into all of these things. Now you can do what Dave does really well and that is Dave Dredge is that you can be you can you can capture that volatility expansion by buying cheap V and sell it when you get out but but you can also do it um in a more mechanical way like we do. But I think this is where maybe the difference comes in terms of how you treat position sizing um to some extent at least. Um, so, so that was one thing I I uh I I picked up on that. But let's let's go back um to to some of your things. I mean, I think the three independent lines of evidence um you know, they're all pointing to the same conclusion. Um and what's fascinating is that it does it across all markets that you said and and across all of these different decades where, you know, clearly the markets have been very different from the 80s to the 90s to the 2000s and and 2010s and so on and so forth. I think that's incredible uh incredibly important and goes to the robustness of the strategy. Maybe there's a practical uh question linked to what I mentioned earlier uh from my side and that is uh you probably know uh at Don at least we use we use a daily risk target not a daily volatility target but I also think that a lot of managers still out there do use a fixed volatility target um as their way of managing their their risk. But if that's the case, I would imagine that there is some kind of direct consequence of that. H you talk about this uh tail uh exponent of 3.33 suggesting that it's not really a bell curve we're looking at here. What does that actually mean when you think about risk and when you think about these what sounds very subtle? Are you targeting risk? Are you targeting volatility? It doesn't sound very different, but I think it is very different. I'd love for you to be very careful if we do target volatility. And so I'll just explain this. So >> let's say you size positions to target a fixed volatility level. You're therefore implicitly assuming that recent volatility is a reasonable guide to future uh to the future. So um and that that's effectively therefore being applied to your position sizing. So, but this is therefore tied to the middle of the distribution for small and medium moves where they are the things that vastly occur much more frequently than these extreme moves. We're never positioning for the tails. We're always positioning for the bulk of the data. Uh that's how most people are applying volatility targeting. And that works very, you know, reasonably well over fairly stable regimes. But the problem is in those tails. So the tail exponent of 3.33 that means that the probability of a very large move does not fall away as fast as the bell curve would suggest. It falls away much more slowly. >> So the practical result is that periodically you'll experience losses that your risk framework was never designed to consider as realistic. So the crude oil example makes this concrete. So if you sized your position based on the quiet uh rangebound volatility of the two years preceding from 2024 up to where we are now um you were holding a position size therefore for a car market when crude ranged between you know around $66 maybe up to $80 that sort of range but then it went up to $119. [clears throat] That's that's not bad luck. That's the predictable consequence of using a bell curve tool to manage a power law risk and it matters not just for the energy position itself but for the entire portfolio exposed to the downstream inflation we talked about earlier. So the research doesn't prescribe that we did doesn't prescribe a specific solution. But what it does establish is that the problem is real. It's structural and it's universal. And any framework built on the bell curve is carrying more risk than it thinks it is. And that's worth knowing. >> Yeah. >> So >> we've established these three empirical signatures. uh the natural next question was whether we can say anything more precise about the mechanism itself not just that feedback exists but how it actually works and this is where the research took a turn I didn't fully anticipate so we built an agent-based simulation comprising populations of convergent and divergent participants to then observe how market price emerges from their collective behavior. We then explored what happens as you vary the proportion of amplifying divergent participants in the system and what we found was striking. So there is a threshold below a certain level of divergent participation roughly 25 to 30% in the models that we applied. Uh the simulated market behaves in a very stable way very much dominated by this convergent signature. uh we don't get these amplifying moves. It's very calm. It's very sedate. It's compressed. So moves moves revert as it's dominated by these convergent impacts. Volatility is contained. The distribution of returns looks approximately like a bell curve in those periods. But then as you cross that threshold of 25 to 30% divergent participation, the character of the market changes sharply. Persistent trends emerge. Volatility spikes and clusters. Fat tails appear. The simulated market starts producing exactly the three signatures we found in all of the real market data. But this transition wasn't gradual. It's very sharp. Below the threshold, one kind of market. Above it, a qualitatively different kind of market. and the the real markets we studied appeared to operate all of them above that threshold which is why we saw those three signatures so consistently. Now here's where the the this connects directly back to that oil discussion we had when I described crude as a system with dry undergrowth. I was describing a market that had been operating near or below that threshold. 18 months of falling prices, elevated short positioning, low volatility, less divergent players in that market. So the stabilizing forces of convergence was dominant during that regime. The amplifying first forces were contained. We didn't get this threshold breakout. So the geopolitical shock was the catalyst that pushed participation above that threshold. That's why the move was so violent. It wasn't just a reply pricing of supply risk. It was a system changing state or what we call a phase transition. And that's also why the reversal also was so sharp. When the initial impulse exhausted itself, the market pulled back because the underlying composition of participants had not fundamentally changed. We only went across the threshold shortly and then it reverted back. So this shock wasn't large enough or sustained enough to anchor the market at this new level above the threshold. So whether it ultimately does anchor depends on whether the supply disruption is real and persistent enough to keep amplifying participants engaged above that threshold. So if the geopolitical situation resolves, the stabilizing forces reassert and prices return towards the mid70s. If the disruption is sustained, the new price level builds its own structural support and the move becomes a genuine trend rather than a spike and revert. So this changes how I think about market regimes more broadly. So the standard view is that markets switch between trending and raging conditions somewhat unpredictably. But the threshold picture suggests something more structural. Regime changes are not random weather. They reflect shifts in the balance between stabilizing and amplifying participation. And those shifts are driven by conditions. You can observe volatility, positioning, fear, momentum, margin levels. So a market that's been grinding sideways for months is not broken. It is operating below a threshold with stabilizing forces in control. A market that suddenly develops a strong directional move is not anomalous. It's doing exactly what a system above the threshold does. So in both cases, the right response is the same. Follow your process, stay positioned, do not mistake a quiet period for evidence that trend following has stopped working. So this brings us back to the practical implications because this is ultimately where the research matters. So the fat tail finding means that any risk framework built on bell curve assumptions will systematically underestimate the true risk. Position sizing, value at risk calculations, stress tests calibrated to two or three sigma moves, all of these carry more exposure than they appear to. So the trend memory finding that we found of866 means that trend signals are not noise. They are not patterns that will dissolve on closer examination. They are reflecting genuine structural persistence in price behavior. And that's the empirical basis for conviction in trend following signals even when the positions feel uncomfortable for us. So the universality finding means that diversification across asset classes is more than risk reduction. It's participation across different feedback environments that share the same structural property. That's what makes a diversified trend portfolio coherent rather than arbitrary. So, and that that threshold finding we found means the opportunity is not constant through time. The density of trends, the persistence of individual moves, the frequency of sharp reversals, all of these shift as the composition of participants shift and strategies need to be robust therefore across all conditions, not optimized for one regime and we address that with our portfolios. So trend following works because financial markets are feedback systems. That's what we found. That's an empirical statement backed by 68 markets, 40 years of data, eight asset classes, and three independent lines of evidence. The trends are real, the fattales are real, the memory is real, and they're all consequences of the same underlying structure, a market where participant behavior creates feedback loops that sustain the very patterns those participants are responding to. So for anyone who trades this way, the significance to me at least is this. You're not relying on a statistical pattern that happened to part, you know, persist in the past. You're participating in a structural feature of how markets work. One that has been present across every asset class and every decade in the modern data that we analyzed. That doesn't mean every trade works. It just means not every year will be profitable, but it means our foundation is very solid. >> Yeah. No, absolutely. And I think I mean obviously we talked about this early on um that uh the industry has just had one of its longest running uh profitable periods. Um and if we take again if I look at Dun's track record just because it's been around for so long um I think in [snorts] the 50 years uh we've only had two periods now where we've had eight monthly uh winning months. Uh this obviously could continue a little bit longer. Uh I hope it does. But that's only two times in 50 years. But it shows you that once the regime is there, it really is uh it can be quite consistent for a while. But it also shows you why we sometimes can go through a six or a 12 month period where yeah we lose a little bit of of money uh every month or every other month and there's nothing unusual about it. It's just the markets are not quite ready to to shift into that new uh regime. It's absolutely wonderful and your paper of course it's you're making it very very accessible. Um, so it's like Michael Lewis meets uh Mandelro. I I think uh we can we can say about that and of course people can go and find it on on your website in more details. I mean I think it's just such a great foundation that we uh haven't really spoken about um before that there is this you know this these clusterings um and and as you say the fat tails they're really not uh they're not random. They're not an an um anomalies. Um they're really how the kind of the natural behavior of markets just how it is. It's it's almost like it's not really it's not an opinion. It's the evidence. Just go and look for it yourself and you'll find exactly the same uh findings. Um that's what makes it so uh interesting. [music] [music] Now Rich, we still have a little bit of time. So before we wrap up, I kind of want to go back to what you [music] said at the very start with uh the oil market in light of um you know the idea of lightning uh hitting dry undergrowth, which of course you also say that our friend Dave Dredge likes to write about because I think it's it's it's an it's a perfect lens uh for everything we've discussed really. the the move from 66 to $119 back to 84 as you rightly pointed out it's not just an energy story you know it's this live demonstration we're seeing it right in front of our eyes uh of all the research that you've done you know a system that was ready loaded a catalyst that just tipped it and then a market that is still probably deciding uh whether that tipping point holds or not and underneath all of is the reminder that when crude oil moves this far and this fast, the effects of that run, it goes through all sorts of parts of our economy. The transport cost you mentioned, food prices, wages, central banks, politicians, and this these things, they don't just quietly uh settle down and reverse to how things were um before. So, is that kind of a fair way of framing why, you know, a move when it happens like this deserves a little bit more attention than maybe um so many of the other moves we've covered over the years? >> I think you've nailed it, Neils. I think uh the the move in the energy that that's a significant move because of it its global impact. Um >> although I felt the cocoa move was significant for my chocolate consumption. I will just say >> true true and it affected my my um my cocoa consumption as well. So um but I think the energy might have more dramatic consequences but uh it's going to be an interesting regime going forward news. And you know for instance if this oil move is sustained um the inflation is going to come roaring back. And uh >> you know, I was looking at um a bit of fixed income the other day going back to the 1990s where our cash rate here in Australia was uh um 17.5%. Um and I was thinking our mortgages were sitting up around 18 19%. And you know, um, we're currently in the sort of five 6% zone and, uh, our kids are thinking that's extreme, but, uh, I don't think they they remember just back to the '9s when we had it at extreme over here. And I I just worry with an oil move like we've had now, if it is sustained, we might zip back into that territory very quickly, which would be significant. Um but um within that particular context I think trend following is uh is going to be very healthy um during that particular environment. High inflation, high high interest rates. I think uh the trends are going to be significant. So maybe we're going into a a marvelous decade for trend following coming. you know, as as we've talked about this today and as I've kind of listened to the conversation and I replay it in my own mind um while we're talking still um I wonder if in some ways when you look at charts right this is kind of one way of of noticing trends but you often see and I think there's a lot of uh people who've been writing about this um you know at the end of the day a lot of markets they move in cycles right and we talk even about you just brought up the interest rates, you know, they've been coming down in Australia for, you know, >> two or three decades, right? We know the 40-year interest rate cycle. Um, and we also know about, you know, how interest rates changes the relationship with or inflation between stocks and bonds from a correlation. And these things tend to persist once they once they get going. So maybe that's another way for people to think about this that the fact that we had, you know, 40 years of of of uh lower lows in in interest rates. Now we've started only recently really getting higher highs in interest rates. And instead of thinking about, oh, this will soon be over and central banks and politicians will win, um, maybe people should start thinking about, well, actually, if what Rich is saying about regimes, we've still got another 35 years to go. Um, and that changes everything. Uh, in >> there's one thing I'm fairly sure of, Neil. We're not going to go back to what was. I think this is the >> G is the normal but this is this is where again we come back to this point about um diversification of investment process. Most investors who do not follow strict rules will probably have this bias to go back and and to expecting something that they just experienced. Right? The recency bias is real. We expect things to go back to the way they were. How do we explain to people that that is unlikely? >> Right? And in an and if that is unlikely, you need to have something in your portfolio that you um that that doesn't necessarily uh you know work just in the environment we just came out of. Even if it took 10 15 years of a certain uh environment that doesn't mean that things can't dramatically change. What's and again what's beautiful and this is will this is like a love fest for trend following today rich I have to say [laughter] but what's beautiful about all of this is that even through the period where it wasn't necessarily conducive for trend following we still made money like we lost money uh over that period we just didn't make as much money as we would like or that we would expect um and I wouldn't even say expect because we don't expect to make money under certain uh in certain environments. That's the key takeaway for me that this is not a a strategy that can only make money when disaster strikes or when you know oil goes from this to that. It this is really a robust regime. We should come up with another name rich about you know that has the word regime in there somewhere I think. Um but I mean it's been wonderful. Um, I really hope um that you have lots of uh of take up on your on your book. I know people can find it on on Amazon. I'm pretty sure um at least that's where I got your last book, so I'm pretty sure it's there. But it's um you know, the more empirical empirical um evidence we can put forward where the logic is clear and uh and there is a connection uh that we can all see happening um in front of us. It makes it makes the story and the narrative so much more compelling. And uh I also hope that people will go and and and leave some um raving reviews to you for for the hard work you put into not just coming on board here and talking for an hour about the findings and we'll continue next time you're on of course but but all the work that goes into coming up with these findings. It's it's um it's incredible. So I really appreciate that. Um, any famous last words, Rich, from your >> No, any I'm I'm done and dusted, as they say. >> You're done and dusted. Okay. Well, great stuff. Thank you so much. Really appreciate that. Um, and as I said, go to your favorite podcast platform and leave a rating and review. Um it it really does help and I hope that many many many more people uh will go and listen to uh what Rich has just explained today because it's so fundamental in the understanding of why of of how markets move and and then also why um certain strategies uh are really well uh designed for this. Um, next week I'll be joined by Nick Balters from Goldman Sachs and um, so that'll be your chance to ask him some questions if you do have questions for Nick. Um, you can email them to me at infotoptradersonplot.com. Maybe he will have some commentary on what Rich has found and shared today. You never know, we'll get some more perspective on this. But in any event, um, 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 [music] take care of each other. >> Thanks for listening to Top Traders Unplugged. If [music] 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 [music] 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. [music] 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]
Why Trend Following Works | Systematic Investor | Ep.391
Summary
Transcript
Imagine [music] spending an hour with the world's greatest traders. Imagine learning from their experiences, their successes, and their [music] failures. Imagine no more. Welcome to Top Traders Unplugged, [music] 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, [music] 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 [music] anything about future performance. Also understand that there's a significant risk of financial loss with all [music] 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 [music] 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 Blen, where each week we take the pulse of the global markets through the lens of a rules-based investor. And I also want to say a warm welcome if today's your first time you're joining us. And if someone who cares about you and your portfolio recommended that you tune in to the podcast, I want to say a big thank you for sharing this episode with your friends and colleagues. It really does mean a lot to us. Rich, it is wonderful as always to be back with you this week. How are you doing? How are you keeping down under? >> Well, it's very hot down here, Neils, and sort of in Australia down here, we either have fires or flood. And at the moment, we're in floods. So, the to the north of us and um certainly in the Northern Territory, they're experiencing very large floods at the moment. So, we can't get it right down here with the weather. It's it's either it's extremes from either end. you know, the Danish king and queen is going to visit Australia very shortly as far as Yeah. [laughter] Well, I'm sure they're not coming by boat uh all that way, but uh they may need one. So, anyways, good to hear. Well, we got an absolutely fantastic lineup of uh topics to discuss today. something I think is pretty groundbreaking uh to be frank and um obviously related to trend following but still in a brand new way that um I think people are really going to want to uh listen to. So can't wait to get into that. But of course as we always do we kind of share things that has been on our radar um in the recent weeks and I know that you've been watching something in the energy markets that may have caught your attention. So uh tell us what's uh share share your secrets. >> Well Neil's sort of crude oil is definitely on my radar right now. So but look rather than getting into the geopolitical narrative about it. What I find more interesting is regarding what the market's reaction itself is telling us about the state of the system when the shock arrived. So, and once I've covered that, I then want to talk about why a move like this in crude oil has consequences that go well beyond just the energy markets. So, I I'll set the scene first. So, this is how I see it. For most of 2024 through to 2025, crude oil was drifting steadily lower. The WTI fell from around $87 US all the way down to roughly $66 over about 18 months. And it was an orderly uneventful decline. No urgency. Each time the market tried to rally, it faded. And the stabilizing forces of the market were firmly in control during that period. But then a few weeks ago, as we all know, everything changed. Crude oil spiked from $66 US all the way up to around about $119 in a very short space of time. That was an 80% move. And then almost immediately it started giving it back, dropping to around $84 by March the 10th. That's a 30% reversal in just a matter of days. So I'm not dismissing the fundamental case. There is a genuine supply risk being priced here. Tension in a region that controls a meaningful share of global production. But the the question I keep coming back to is this. Does an 80% spike followed by an immediate 30% reversal look like a market that is calmly and rationally repricing a real supply threat? Or does it look like a system that was primed to overreact and did exactly that? So to me, this is exactly what it looks like um for a market that that it's like when lightning hits dry undergrowth as as Dave Dredge would say. The the undergrowth here was the setup over the last two years. Crude oil had been grinding lower for about 18 months. Short interest had built up steadily. The market had been quiet long enough that the amplifying forces, the momentum traders, the the trend signals had largely stepped away and the system was loaded with convergence. But all it needed was a catalyst. And that's the key point. So the move from $66 to $119 um dollars was not purely about oil supply to me at least. It was about the state of the market that received the shock. So when you have heavy short positioning as we did for 2 years, suppressed volatility and a long period of onedirectional drift, you have a market that is structurally coiled. So the geopolitical event was the ignition. The fuel had been building however for over a year and then the snap back from 119 back to $84 US. That's not the market calmly reconsidering the supply outlook. That's a system that overshot with the participants who chased the spike getting stopped out. Momentum signals flipping. The same dynamics that drove up is now working in reverse. So that's how I'm seeing this move in oil. It's not just about the fundamentals. I think the state of the market was prime for it. What What do you think? >> So, first of all, um and I don't know that people really think about it this way, but but actually it it first of all means that oil is in a bare market right now because it's more than a 20% correction from a high, which is obviously silly to say, but it's actually how technically it is. Um now you know people who have listened to the podcast over the years um they would have heard me say many times that I think we were entering this world where or maybe we've already always been there that you had to be able to kind of imagine the unimaginable right this is one way of visualizing something that we probably never thought would ever going to happen. your point about the buildup and all of that uh obviously takes me back to and I don't know if this is the right uh comparison but when you think about what happened to things like inflation whereby it was so wellmanaged uh for many many years in the 2010s and obviously we know that that wasn't great for trend following but as soon as the pandemic came and was maybe in that case kind of the trigger. We saw inflation go up by four or 500%. Right, from 2% to 10 11%. >> So, it's kind of the same thing as you're pointing out here that >> we can try and manage things for a while, but it also seems like the more we succeed in that, the more we build up the potential uh for something very uh consequential to take place uh after that. Yeah. >> And unfortunately, I do feel that a lot of what's going on in in in the world, it's always managed. It's always manipulated. It's always has some kind of political agenda. I mean, we we know that the current administration, maybe even the previous administration, they would like to have lower energy prices, right? Because it's good for the for getting reelected. And it may, as you say, it may work for a while, but when it doesn't work anymore, it also shows you the power of the markets, just like you say in as as Dave says in in his writings about, you know, the the undergrowth and and as soon as you ignite that, how quickly it spreads, how powerful it is, and we unfortunately see real life examples of that in California and other places. It's the respect of what comes after a calm period that I think sometimes people get just way too complacent. And that's obviously one thing that and I know we're going to be talking about obviously trend following today, but I think that's what I really love about our strategy and always have and that is we we never get bored. We never get tired. Uh the models just wait. They they don't you know even if it takes a year or even if it takes three years I mean think about Coco. it took like 15 years for it to really give us something uh that we could um that we could benefit from. So it's the diversification not just of returns but it's the diversification of of investment process that I find so powerful and so useful for pretty much 99% of people's portfolio. Um so yes it it manifests itself in a way of a non-correlated return stream. Sure, we can we can talk about that, but we need to dig a little bit deeper. What what is it that generates that non-correlated return stream and all the moving part that goes into that and the different way we approach things from an investment point of view? And I think certainly in my recent meetings and travels uh even this week when the penny drops in terms of diversification of investment process, it's almost like a little bit of a sort of light bulb moment. >> Yeah. Ah, that's why it's so important to have in in the portfolio because they can have all the right opinions and they can, >> you know, possibly be right about many things, but but also as as uh Dave writes, it's about what you have in your portfolio when you're wrong. >> It's not just about being right. It's what what what do you have in your portfolio when you're wrong? >> So, um so that's one. The other thing I just want to mention uh something I learned yesterday listening to um to the OddLots podcast uh where one of our previous guests Roy Johnson was on and talking a little bit about the oil thing. I I had not appreciated that actually right now. The reason why the Homo Strait is is so critical is that we've got about 20 million barrels per day trapped uh in that area. and 20 million barrels. That's actually the same amount uh that we saw in terms of demand destruction when the whole world closed down uh during the pandemic. So it's not an insignificant amount. Now it's not so much that it's stuck, it's also the fact that when things are stuck um and and you remember this uh for sure when oil prices went negative because of the storage. So the fact that they cannot get this the the oil out means that the storage facilities are basically filling up. And once you get to that point which may already have been reached um you have to start not only just lowering your production but if you get to the worst critical point and you actually shut down some of these refineries it takes a lot of effort and a lot of time to restart them. So then you get all these second, third, fourth, whatever uh effects uh of of of what's going on right now. So anyways, we'll talk about this some more, I'm sure. >> I'd like to stay on this a bit because it actually does relate to some of my topics a bit later on. So >> okay, >> um >> what makes this move in crude oil so much beyond the energy market itself is that crude oil is probably the single most consequential input price in any economy. So it flows through almost everything we consume and produce. So the transmission starts with transport. Every physical good on every shelf was at some point moved by a truck, a ship, a plane. Uh when diesel spikes, the cost of moving anything goes up and every business in the chain passes that forward rather than absorbing it. So there comes the inflation. So then you have manufacturing um because oil derivatives from uh they're the raw material for plastics, synthetic fibers, pharmaceuticals, lubricants, countless other industrial agents, >> even the top traders unplug merch that you're wearing so beautifully. >> Exactly. I'm glad you got it before this oil spike. So food of course modern farming heavily diesel dependent crucially you know nitrogen fertilizer I believe is made from natural gas. So an energy shock feeds directly into the cost of growing food and then with a bit of a lag you get wage pressures because when commuting costs rise food prices rise workers eventually push for higher pay to compensate. that embeds the shock in a way that's very hard to reverse. And on top of all that, you've got the central bank responses. So, this brings me back to the 1970s when policy makers tolerated oildriven inflation for too long. And that was a a [clears throat] cost that took decades um to bring back under control. So, the modern instinct for central banks is therefore to act quickly and raise rates. And when rates rise, borrowing costs go up across the board, mortgages, business loans, government debt, all of it, all associated to the underlying oil crisis. So this move from $66 to $119 in crude is not just an energy story. It's a potential shock to the cost of almost everything in the global economy, hitting through multiple channels at once. And here's this asymmetry that makes it particularly sticky. Prices go up fast and come down slowly. So the trucking firm that raised the fuel search charge at the peak of the move is not going to immediately cut it when crude drops back. The food producer that puts prices up, citing higher input costs, they're not going to reverse that spontaneously. So the inflationary pressure tends to linger well after the commodity prices pull back which brings me to how we started this conversation that spiked to $119 and the reversal to $84. They're telling us that the market has not yet made up its mind. Is this a genuine fundamental repricing or was it primarily a positiondriven overshoot? Those two scenarios have very different consequences for bonds, currencies, equities, central bank policy. But I suppose as trend followers, you and me, Neils, we don't need to decide this invance. I I suppose we just need to stay positioned to participate in whatever the outcome the market confirms. So the market's going to tell us ultimately and I suppose our job is just to follow the trend. >> Yeah. No, absolutely. Listen to the data. Um like often people say that actually we should all get better at listening and not talking too much which is hard sometimes on a podcast but there we are. [snorts] Um but also you know with this old oil story of course it is pretty significant the way um you know the reactions you know this release that they talk about now of I don't know hundreds of millions of barrels and and all of that stuff. The saddest thing I think in all of this is this is a little bit political which I try not to. It's just the fact that we are now relying on a place like Russia to increase its oil production to offset some of this uh which from a European perspective is probably not really what we would like to see unfortunately if we should if if there should be any chance of stopping all these conflicts. But um there we are. We'll leave it at that. Other things that hit my radar, um, by the way, was the fact that our shock gen trend following index hit a new all-time high at the end of February. M >> so we're back from the brink of uh June of last year where many commentators and the narrative was pretty much um in this um narrative political driven world where news flashes drives markets um more than anything else clearly a long-term slow strategy would not be the right thing to have in your portfolio. you should be in short-term quick moving strategies. Um, obviously I can't help notice the fact that um the longerterm strategies have had a very strong uh consistent uh run as I mentioned uh uh the sock gen trend index is back at new all-time highs. Uh whilst the short-term traders index also from Sockgen uh is still somewhat below it's um it's only recovered about 50% of that draw down that it was in um and is still some way away from getting back to a new uh all-time high. In addition to that, of course, the longerterm performance between those two indices is is is very significant uh and and in favor of the longerterm strategy. So interesting to see what's going on and why that is. Uh hopefully we can bring someone on uh on the podcast soon that can tell us a little bit more about that. Um that would be that would be great. Before I forget, by the way, for those who have not downloaded the latest version of the ultimate guide uh that I publish usually once a year, there is a new version out, an eighth edition. Uh, I think we're up to more than 600 books. If anyone wants to download it, just hit go over to toptradersblog.comultimate. Okay. Now, trend following. Just do this section now before we get into the the real meat of our conversation today. My own trend barometer finished at 50 uh last night. Uh, that's still a strong reading. Uh, meaning that there is fair fairly good breath in in a classical portfolio of trend following. We do of course have an interesting start to March. some give back uh clearly uh with what's happened uh trend followers I would say most of them were on the right side of the move despite what you mentioned correctly is that trend sorry oil uh had been in a downtrend for quite a while but that kind of changed going into February midFebruary where where I think many models would have picked up a change in direction before it got too crazy which was very um useful when when you uh at the same time would have lost money in equities, currencies, probably fixed income as well. Um did not quite react in a direction of of the trend followers would like. Anyway, so so that's where we are on that. In terms of performance so far in um in March, indices are down. Uh not surprising. Uh the beta 50 index is probably down a couple of percent still up 4.67% so far this year. Shock CTA index is down 2.06 uh so far and uh also up about uh 6.11% trend index also down 2.16% but still up 6.44% 4% and the short-term traders index um I'm not entirely sure about this number. I think it's down uh also a little bit this month and up around 3 and a quarter so far this year. Uh in terms of the real uh traditional markets, Msei World, so equities are being hit down 2.8% as of last night. They're now flat for the year. The uh aggregate bond index in the US is down 1.21%. So no help from from bonds. Uh still up 43 basis points. so far this year. And the S&P 500 down about 1.44% in March and it's down for the year. Uh but only slight 0.77% so far this year. I already mentioned I think that uh you know the energy sectors have done well for trend followers. Uh we've been hurt elsewhere. uh of course uh equities some of the currencies and and some of the fixed income although some fixed income markets may actually have helped uh in the first few days of uh March positioning wise I'm not so sure that a lot has changed markets are overall relatively muted except for what's going on in energies uh even the precious metals um not done a lot sold off a little bit most likely because people can raise some cash uh to cover maybe uh losses elsewhere in the portfolio. I did read somewhere this morning, Rich, that some of these quote unquote multi- uh pot shops or multistrat funds or whatever uh has had a a little bit of a a tough time uh in March. So maybe their style of trading where I imagine it's not really trend following um has found its match uh when something like this happens. Um but uh of course markets have moved dramatically. heating oil to just to give an example despite the correction it's still up 52% so far this month and crude is up around 40% uh from the end of February uh so far this month so pretty big on the other side of that spectrum we have things like silver platinum down around 9% so far this month so decent moves for sure >> now I well I'll allow you of course uh Rich any thoughts on the trend space right now before we dive into the more um meaty topics we have to get through today. >> Well, I I I think we we're coming into a a very beneficial regime for trend following simply because of the fact that um I think the market's starting to expose a lot of tail properties. Um this is uh not something you see often, but uh we're certainly seeing it at the moment. Um we we saw it uh last month with gold, the metals, um etc. And now we're seeing with the energies um we're seeing this, we talked about it before, the the impacts of delobalization um all of these things are flowing through into being very beneficial markets for trend followers. Um I would therefore suspect that um a lot of the alternative styles of strategy that have been particularly successful over the last decade or so um may find that they're struggling in this particular regime. So when you when you talk about the the pod shops etc uh this is sort of uh probably uh a regime they're not familiar with or used to. You usually find that uh when you start getting into a market that's uh exhibit C's tail properties uh nearly all strategies fall over apart from u the good old trend followers um long V strategies those sort of variants so um I think it's going to be a very challenging time for alternative strategies but I'm very thankful [music] we've got our particular strategy going into this regime. [music] Well, let's dive into this. I I I mentioned already that it is pretty um pretty extraordinary, I think, what we're going to talk about now. Um you just uh published a new book, The Fractals of Finance. First of all, great. Congratulations. Uh not easy to bring about a book. Um so, um so that's great. And what we're going to do today, we're going to spend the conversation going through the empirical findings uh that kind of underpins uh that book and and that research that goes into the into it. Now, in order to do this, you've built a research program covering um 68 uh futures markets across eight different uh classes. So we have equities, bonds, currencies, energies, metals, agriculturals using daily data uh stretching back to 1984. It's so funny when I read these numbers. I it's almost like exactly like the portfolio we run at done 84. [laughter] So and since ' 84. Anyways, the question driving all of this uh is to some extent quite simple and that is why do patterns uh that trend followers depend on actually exist? uh not as a matter of strategy aside but as more as a kind of a structural property of markets themselves. So what we're going to discuss today is the empirical case kind of the data the logic and what that really means for anyone who trades um for a living or invest with managers uh such as ourselves. So Rich um can't wait to hear what uh what you found. >> Well well thanks Neil. So the research that informed the book I wrote um starts with a simple logical test and I want to explain it up front because it it shapes everything that follows. So the test works like this. So imagine a world where markets had no memory at all where each price move was completely independent of the one before it. In that world, three things would have to be true. Trends could not persist because there would be nothing carrying a move forward from one day to the next. Returns would cluster tightly around an average following a normal bell curve and volatility would be all would be very steady and predictable because there'd be no mechanism for turbulent periods to bunch together. So those aren't opinions. They're the mathematical consequences of a world without feedback or memory. So therefore, I turned the question round. If we find that trends do persist, that returns are not bell-shaped and that volatile periods do cluster together and if we find all three of these things simultaneously in every market we can study, then the conclusion is therefore inescapable. Feedback is not a feature of some markets in some periods. It's the fundamental structural property of financial markets. So that's what I set out to test and I'll tell you what I found in this research. So >> okay, >> the first thing we measured was whether markets have memory in their structure. Not whether each daily move predicts the next, but whether the behavior of prices over time carries the fingerprints of a process that remembers its own past. So the tool for this that we used was the her hurst exponent. Um that produces a number between zero and one. A score of 0.5 means the price path is consistent with pure randomness. No memory no structure. But if the it falls above 0.5 this means the process exhibits long range dependence that the scaling behavior of price moves through time is not consistent with randomness but if it falls below 0.5 that means the process is mean reverting in its structure. So I I want to be precise here about what the Hurst exponent is and and what it's not measuring. So, it's not saying that because the market went up today, it's more likely to go up tomorrow. That kind of simple day-to-day directional persistence is actually close to zero in practice and rightly so because if if um it were strong, it would be immediately arbitrageed away. But what the Hurst exponent is measuring is something deeper. It's capturing whether the magnitude and the clustering of moves, the way volatility behaves, the way large moves small follow large moves and quiet periods follow quiet periods exhibits a kind of memory that a purely random process would not produce. So it's a measure of how the process scales through time. And what we found across all the 68 markets in the study, the average Hurst exponent was not.5, it was 0.866. It was not in some markets, not in some periods, every single market, every decade. And when we broke the data into decades, the results barely moved. So decade averages range from between 707 to 757 across four decades through financial crisis, regime changes and everything in between. So that structural memory was always there. It didn't go away. It was not a feature of one era. It was baked into the behavior of these markets at all times. So what this means practically is that the conditions which sustain a trend, elevated volatility, clustering of moves in one direction, amplifying participant behavior tend to persist once they're established. So the market does not reset to a blank slate each day. It carries forward the character of what has been happening. And that's the environment in which trend following operates. Not because each daily step is predictably directional, but because the conditions that produce sustained moves have memory. So think about that oil move we were discussing earlier. So the 80% spike that didn't happen because each day mchanically followed the last. It happened because the conditions that made the system explosive, the positioning, the suppressed volatility, the absence of amplifying participants accumulated over time from 2024 to 2025 and then they all released together. So that is long range dependence expressing itself. So the Hurst evidence is telling us that this kind of accumulation and release is not an accident of one market or one moment. It's the normal behavior of these systems. But the finding alone does not complete the case we're after. So a world with this kind of structural memory but normally distributed returns for example and steady volatility would still be a very different world from the one we actually trade. So, we kept going in our research. >> Mhm. Okay. Well, let's let's just make sure that people fully uh kind of embrace what you just said. Um um because there are some subtle and very important uh distinctions here. So, so you're not claiming that markets trend in a simple day-to-day sense. And by the way, is that what people sometimes refer to as autocorrelation? um that that's what they say is the reason why trend works and you're saying actually no you're saying the memory lives in the structure of how moves behave over time in the clustering and in the scaling so the way the conditions persist once they are established um if if if that's what I'm >> that's exactly right Neils and look um in our next podcast we we do go onto a phase two of this exercise where we look at the autocorrelation feature that that is in markets. But um when you look at very large data sets um the directional correlation effectively averages out to zero. >> But um this is um this is something I'll reserve for the the later podcast with you. It's a very deceptive average. I'll just say that. >> But what we are talking about now is really the absolute magnitude of moves. Very large moves follow large moves. Very quiet moves follow quiet moves. It's a magnitude we're talking about here in this particular um segment that we're talking about here. So there is an important clarification. So simple directional autocorrelation that that means the idea that up today means up tomorrow is indeed close to zero over these large samples. >> Um I'll talk about that in our next podcast how we broke that down. >> Okay. >> Um I don't want to preempt that. But what the hurst evidence is capturing in this research is u is something that can't be arbitrageed away as easily because it's not a simple signal you can trade on each day. It's a property of the process itself. So the way energy accumulates in the system, the way volatility clusters, the way the character of a market once it shifts into a trending state tends to persist rather than immediately revert. That's what creates the environment for trend following to work and that is what the data shows. So if you imagine that oil move Neils that was a volatility burst but it was a directional persisting move that could be exploited by trend it was actually the volatility expansion that we were capturing there and that is what this magn this absolute magnitude approach is is telling us this volatility clusters that that's why we can exploit these opportunities. is not the the directional day-to-day move. It's the explosive volatility out of a calm period or a compressed state. That's what we're actually exploiting with with um a lot of our models. But um so that's what the data is showing us consistently across every market and every decade we study. So this independence assumption at the heart of the standard model, the efficient market hypothesis, says none of this should exist. The fact is that it does universally and it's persistent. It tells us that the model was wrong from the start. So markets are not populated by independent agents processing information in isolation. They are populated by participants who watch each other, respond to each other, and in doing so create feedback that leaves a structural trace in the data. And that trace is what the hertz exponent is measuring. So we then moved on to a second piece of research just to give us a strengthening argument here. >> Okay. >> So this concerns the distribution of returns and this is where the standard finance model looks most seriously wrong. So under the standard model extreme daily moves are not just rare they are astronomically rare. So a five sigma event which is a daily move five standard deviations from the average should occur roughly once every 3 and a half million trading days. So in the entire history of liquid financial markets we have not accumulated 3 1/2 million trading days. So in a world of bell curve returns we should essentially never see a five sigma event. But in our data set that we studied, five sigma events occurred 5,791 times more frequently than the standard model predicts. It's not a rounding error. It's not a modest discrepancy. It's nearly 6,000 times more frequent. And when we looked at the mathematical shape of the tails, we found a pattern consistent with a power law distribution, not a bell curve. So the tail exponent was approximately 3.33. >> Can you explain the 3.33 I what? >> So this this is measuring the the power of the tails. What lies in the tails? The 3.33 is pushing us right out into the tail regions. It's saying that we're dealing with leptocortic distributions here. We're not dealing with bell curves. So in every single liquid market we assessed it had this leptocourtic property and it had this tail exponent of about 3.33. So the practical consequence of this is is enormous. So if your risk model assumes bell curve returns, you're not slightly underestimating the probability of large losses. You are underestimating it by orders of magnitude. And this isn't a quirk of one market or one period. it's present across all eight asset classes in the study. So the crude oil move is a perfect illustration. So a move from $66 to $119 followed by a reversal to $84 all within weeks. Both the spike and the correction sit deep in the fat tail territory. They're not anomalies. They're exactly what a power law distribution produces. So this is not exceptional behavior. This is what these markets do. So we looked at these sigma properties of the financial markets. Now the third piece of evidence we collected was volatility clustering and this is the tendency for turbulent periods to bunch together. So large moves followed by large moves, calm periods followed by calm. So we measured this using the autocorrelation of the size of daily moves across all 68 markets and the average was 353. That is a strong consistent signal that volatility has memory not just direction. So now we've got all three of these properties. We've got trend memory. We've got fat tails. We've got volatility clustering. All three predictions of the no feedback world are false. And they're false not in some markets or some periods, but in 68 of of across eight asset classes across 40 years of daily data. So there's something more interesting to say about what the distribution itself is telling us. And that's because that distinctive shape, the the tall narrow peak and the heavy tails, it's not just a consequence of feedback, it's a signature of a market with two distinct types of participant operating at the same time. This is where it gets interesting. So some participants in the market behave in a stabilizing way. And you and I Neils, we know them as convergent participants. So when price moves away from where they think it should be, they push back against it. Value buyers for example, arbitrageers, mean reversion traders, they fit into this class of convergent trader. They produce the actual tall narrow peak of the curve because most of the time they they dominate um at at most of the time and moves are small. So therefore they're clustering around the peak of the distribution. That's why we get the tall peak. But these other participants which you and I are, they behave in an amplifying way and we refer to them as divergent participants. So they push in the the direction the market's already moving rather than against it. We are going in the we're amplifying the move not suppressing the move. So this includes trend followers, momentum traders. It also includes when stop-loss orders accelerate a decline and when margin calls force selling into a falling market. These are all amplifying moves and they produce the fact tales because periodically their collective behavior overwhelms the stabilizing forces and you get these extreme outcomes. So this means that as trend followers we're not external observers of these dynamics. We are participants in the feedback system itself that generate the very phenomena we exploit. So understanding that changes how you think about what trend following actually is. It's not just a strategy. It's alignment with a structural feature of how prices form. So the universal vers the universality of this really matters. So those same three signatures that we discussed earlier across equities, fixed income, currencies, energy, metals, agricultural, commodities, every asset class, every decade, the architecture is the same everywhere. I want to go back to something you said and I don't I want I don't want to make this a controversial point for some listeners who may have a certain uh way of doing trend following but you said something interesting um you said something and I obviously don't have the exact quote in my head but you said something about that uh you know what we do also is we kind of capture this volatility expansion or something along those lines. Is that correct? >> Yeah that's that's right. In in a sense when I heard that I was immediately thinking well [snorts] then that maybe means that there is some value maybe to dynamic position sizing in a sense that in order to capture that vol expansion you kind of also need to reduce your exposure as the expansion happens before it collapses again or the price collapses. again um we don't know need to go go into it but maybe we will get into it in a in a second um the other thing when I just heard you talk about how we are the amplifiers often but of course and and this is actually something that people often use as a negative if we amplify the rise of of wheat prices or the rise of something oil prices for that matter now we are to blame for for all of this um but as you and I know at least the part of the CTA universe that does have dynamic position sizing. We're actually going to be selling oil as counterintuitive as it may sound, but we'll probably be selling oil the last few days in order to adjust our positions down within a certain risk framework. Um, so in that sense, we will sometimes suppress perhaps the uh the move a little bit um to the benefit of of uh of some uh perhaps. So, it's it's kind of an interesting and and it goes back to this idea about we talked about earlier on about the why I love trend following is also the fact that it's so adaptable. It's this investment process. It's almost like you know uh was it Bruce Lee who said be water. I mean it's almost like it flows into all of these things. Now you can do what Dave does really well and that is Dave Dredge is that you can be you can you can capture that volatility expansion by buying cheap V and sell it when you get out but but you can also do it um in a more mechanical way like we do. But I think this is where maybe the difference comes in terms of how you treat position sizing um to some extent at least. Um, so, so that was one thing I I uh I I picked up on that. But let's let's go back um to to some of your things. I mean, I think the three independent lines of evidence um you know, they're all pointing to the same conclusion. Um and what's fascinating is that it does it across all markets that you said and and across all of these different decades where, you know, clearly the markets have been very different from the 80s to the 90s to the 2000s and and 2010s and so on and so forth. I think that's incredible uh incredibly important and goes to the robustness of the strategy. Maybe there's a practical uh question linked to what I mentioned earlier uh from my side and that is uh you probably know uh at Don at least we use we use a daily risk target not a daily volatility target but I also think that a lot of managers still out there do use a fixed volatility target um as their way of managing their their risk. But if that's the case, I would imagine that there is some kind of direct consequence of that. H you talk about this uh tail uh exponent of 3.33 suggesting that it's not really a bell curve we're looking at here. What does that actually mean when you think about risk and when you think about these what sounds very subtle? Are you targeting risk? Are you targeting volatility? It doesn't sound very different, but I think it is very different. I'd love for you to be very careful if we do target volatility. And so I'll just explain this. So >> let's say you size positions to target a fixed volatility level. You're therefore implicitly assuming that recent volatility is a reasonable guide to future uh to the future. So um and that that's effectively therefore being applied to your position sizing. So, but this is therefore tied to the middle of the distribution for small and medium moves where they are the things that vastly occur much more frequently than these extreme moves. We're never positioning for the tails. We're always positioning for the bulk of the data. Uh that's how most people are applying volatility targeting. And that works very, you know, reasonably well over fairly stable regimes. But the problem is in those tails. So the tail exponent of 3.33 that means that the probability of a very large move does not fall away as fast as the bell curve would suggest. It falls away much more slowly. >> So the practical result is that periodically you'll experience losses that your risk framework was never designed to consider as realistic. So the crude oil example makes this concrete. So if you sized your position based on the quiet uh rangebound volatility of the two years preceding from 2024 up to where we are now um you were holding a position size therefore for a car market when crude ranged between you know around $66 maybe up to $80 that sort of range but then it went up to $119. [clears throat] That's that's not bad luck. That's the predictable consequence of using a bell curve tool to manage a power law risk and it matters not just for the energy position itself but for the entire portfolio exposed to the downstream inflation we talked about earlier. So the research doesn't prescribe that we did doesn't prescribe a specific solution. But what it does establish is that the problem is real. It's structural and it's universal. And any framework built on the bell curve is carrying more risk than it thinks it is. And that's worth knowing. >> Yeah. >> So >> we've established these three empirical signatures. uh the natural next question was whether we can say anything more precise about the mechanism itself not just that feedback exists but how it actually works and this is where the research took a turn I didn't fully anticipate so we built an agent-based simulation comprising populations of convergent and divergent participants to then observe how market price emerges from their collective behavior. We then explored what happens as you vary the proportion of amplifying divergent participants in the system and what we found was striking. So there is a threshold below a certain level of divergent participation roughly 25 to 30% in the models that we applied. Uh the simulated market behaves in a very stable way very much dominated by this convergent signature. uh we don't get these amplifying moves. It's very calm. It's very sedate. It's compressed. So moves moves revert as it's dominated by these convergent impacts. Volatility is contained. The distribution of returns looks approximately like a bell curve in those periods. But then as you cross that threshold of 25 to 30% divergent participation, the character of the market changes sharply. Persistent trends emerge. Volatility spikes and clusters. Fat tails appear. The simulated market starts producing exactly the three signatures we found in all of the real market data. But this transition wasn't gradual. It's very sharp. Below the threshold, one kind of market. Above it, a qualitatively different kind of market. and the the real markets we studied appeared to operate all of them above that threshold which is why we saw those three signatures so consistently. Now here's where the the this connects directly back to that oil discussion we had when I described crude as a system with dry undergrowth. I was describing a market that had been operating near or below that threshold. 18 months of falling prices, elevated short positioning, low volatility, less divergent players in that market. So the stabilizing forces of convergence was dominant during that regime. The amplifying first forces were contained. We didn't get this threshold breakout. So the geopolitical shock was the catalyst that pushed participation above that threshold. That's why the move was so violent. It wasn't just a reply pricing of supply risk. It was a system changing state or what we call a phase transition. And that's also why the reversal also was so sharp. When the initial impulse exhausted itself, the market pulled back because the underlying composition of participants had not fundamentally changed. We only went across the threshold shortly and then it reverted back. So this shock wasn't large enough or sustained enough to anchor the market at this new level above the threshold. So whether it ultimately does anchor depends on whether the supply disruption is real and persistent enough to keep amplifying participants engaged above that threshold. So if the geopolitical situation resolves, the stabilizing forces reassert and prices return towards the mid70s. If the disruption is sustained, the new price level builds its own structural support and the move becomes a genuine trend rather than a spike and revert. So this changes how I think about market regimes more broadly. So the standard view is that markets switch between trending and raging conditions somewhat unpredictably. But the threshold picture suggests something more structural. Regime changes are not random weather. They reflect shifts in the balance between stabilizing and amplifying participation. And those shifts are driven by conditions. You can observe volatility, positioning, fear, momentum, margin levels. So a market that's been grinding sideways for months is not broken. It is operating below a threshold with stabilizing forces in control. A market that suddenly develops a strong directional move is not anomalous. It's doing exactly what a system above the threshold does. So in both cases, the right response is the same. Follow your process, stay positioned, do not mistake a quiet period for evidence that trend following has stopped working. So this brings us back to the practical implications because this is ultimately where the research matters. So the fat tail finding means that any risk framework built on bell curve assumptions will systematically underestimate the true risk. Position sizing, value at risk calculations, stress tests calibrated to two or three sigma moves, all of these carry more exposure than they appear to. So the trend memory finding that we found of866 means that trend signals are not noise. They are not patterns that will dissolve on closer examination. They are reflecting genuine structural persistence in price behavior. And that's the empirical basis for conviction in trend following signals even when the positions feel uncomfortable for us. So the universality finding means that diversification across asset classes is more than risk reduction. It's participation across different feedback environments that share the same structural property. That's what makes a diversified trend portfolio coherent rather than arbitrary. So, and that that threshold finding we found means the opportunity is not constant through time. The density of trends, the persistence of individual moves, the frequency of sharp reversals, all of these shift as the composition of participants shift and strategies need to be robust therefore across all conditions, not optimized for one regime and we address that with our portfolios. So trend following works because financial markets are feedback systems. That's what we found. That's an empirical statement backed by 68 markets, 40 years of data, eight asset classes, and three independent lines of evidence. The trends are real, the fattales are real, the memory is real, and they're all consequences of the same underlying structure, a market where participant behavior creates feedback loops that sustain the very patterns those participants are responding to. So for anyone who trades this way, the significance to me at least is this. You're not relying on a statistical pattern that happened to part, you know, persist in the past. You're participating in a structural feature of how markets work. One that has been present across every asset class and every decade in the modern data that we analyzed. That doesn't mean every trade works. It just means not every year will be profitable, but it means our foundation is very solid. >> Yeah. No, absolutely. And I think I mean obviously we talked about this early on um that uh the industry has just had one of its longest running uh profitable periods. Um and if we take again if I look at Dun's track record just because it's been around for so long um I think in [snorts] the 50 years uh we've only had two periods now where we've had eight monthly uh winning months. Uh this obviously could continue a little bit longer. Uh I hope it does. But that's only two times in 50 years. But it shows you that once the regime is there, it really is uh it can be quite consistent for a while. But it also shows you why we sometimes can go through a six or a 12 month period where yeah we lose a little bit of of money uh every month or every other month and there's nothing unusual about it. It's just the markets are not quite ready to to shift into that new uh regime. It's absolutely wonderful and your paper of course it's you're making it very very accessible. Um, so it's like Michael Lewis meets uh Mandelro. I I think uh we can we can say about that and of course people can go and find it on on your website in more details. I mean I think it's just such a great foundation that we uh haven't really spoken about um before that there is this you know this these clusterings um and and as you say the fat tails they're really not uh they're not random. They're not an an um anomalies. Um they're really how the kind of the natural behavior of markets just how it is. It's it's almost like it's not really it's not an opinion. It's the evidence. Just go and look for it yourself and you'll find exactly the same uh findings. Um that's what makes it so uh interesting. [music] [music] Now Rich, we still have a little bit of time. So before we wrap up, I kind of want to go back to what you [music] said at the very start with uh the oil market in light of um you know the idea of lightning uh hitting dry undergrowth, which of course you also say that our friend Dave Dredge likes to write about because I think it's it's it's an it's a perfect lens uh for everything we've discussed really. the the move from 66 to $119 back to 84 as you rightly pointed out it's not just an energy story you know it's this live demonstration we're seeing it right in front of our eyes uh of all the research that you've done you know a system that was ready loaded a catalyst that just tipped it and then a market that is still probably deciding uh whether that tipping point holds or not and underneath all of is the reminder that when crude oil moves this far and this fast, the effects of that run, it goes through all sorts of parts of our economy. The transport cost you mentioned, food prices, wages, central banks, politicians, and this these things, they don't just quietly uh settle down and reverse to how things were um before. So, is that kind of a fair way of framing why, you know, a move when it happens like this deserves a little bit more attention than maybe um so many of the other moves we've covered over the years? >> I think you've nailed it, Neils. I think uh the the move in the energy that that's a significant move because of it its global impact. Um >> although I felt the cocoa move was significant for my chocolate consumption. I will just say >> true true and it affected my my um my cocoa consumption as well. So um but I think the energy might have more dramatic consequences but uh it's going to be an interesting regime going forward news. And you know for instance if this oil move is sustained um the inflation is going to come roaring back. And uh >> you know, I was looking at um a bit of fixed income the other day going back to the 1990s where our cash rate here in Australia was uh um 17.5%. Um and I was thinking our mortgages were sitting up around 18 19%. And you know, um, we're currently in the sort of five 6% zone and, uh, our kids are thinking that's extreme, but, uh, I don't think they they remember just back to the '9s when we had it at extreme over here. And I I just worry with an oil move like we've had now, if it is sustained, we might zip back into that territory very quickly, which would be significant. Um but um within that particular context I think trend following is uh is going to be very healthy um during that particular environment. High inflation, high high interest rates. I think uh the trends are going to be significant. So maybe we're going into a a marvelous decade for trend following coming. you know, as as we've talked about this today and as I've kind of listened to the conversation and I replay it in my own mind um while we're talking still um I wonder if in some ways when you look at charts right this is kind of one way of of noticing trends but you often see and I think there's a lot of uh people who've been writing about this um you know at the end of the day a lot of markets they move in cycles right and we talk even about you just brought up the interest rates, you know, they've been coming down in Australia for, you know, >> two or three decades, right? We know the 40-year interest rate cycle. Um, and we also know about, you know, how interest rates changes the relationship with or inflation between stocks and bonds from a correlation. And these things tend to persist once they once they get going. So maybe that's another way for people to think about this that the fact that we had, you know, 40 years of of of uh lower lows in in interest rates. Now we've started only recently really getting higher highs in interest rates. And instead of thinking about, oh, this will soon be over and central banks and politicians will win, um, maybe people should start thinking about, well, actually, if what Rich is saying about regimes, we've still got another 35 years to go. Um, and that changes everything. Uh, in >> there's one thing I'm fairly sure of, Neil. We're not going to go back to what was. I think this is the >> G is the normal but this is this is where again we come back to this point about um diversification of investment process. Most investors who do not follow strict rules will probably have this bias to go back and and to expecting something that they just experienced. Right? The recency bias is real. We expect things to go back to the way they were. How do we explain to people that that is unlikely? >> Right? And in an and if that is unlikely, you need to have something in your portfolio that you um that that doesn't necessarily uh you know work just in the environment we just came out of. Even if it took 10 15 years of a certain uh environment that doesn't mean that things can't dramatically change. What's and again what's beautiful and this is will this is like a love fest for trend following today rich I have to say [laughter] but what's beautiful about all of this is that even through the period where it wasn't necessarily conducive for trend following we still made money like we lost money uh over that period we just didn't make as much money as we would like or that we would expect um and I wouldn't even say expect because we don't expect to make money under certain uh in certain environments. That's the key takeaway for me that this is not a a strategy that can only make money when disaster strikes or when you know oil goes from this to that. It this is really a robust regime. We should come up with another name rich about you know that has the word regime in there somewhere I think. Um but I mean it's been wonderful. Um, I really hope um that you have lots of uh of take up on your on your book. I know people can find it on on Amazon. I'm pretty sure um at least that's where I got your last book, so I'm pretty sure it's there. But it's um you know, the more empirical empirical um evidence we can put forward where the logic is clear and uh and there is a connection uh that we can all see happening um in front of us. It makes it makes the story and the narrative so much more compelling. And uh I also hope that people will go and and and leave some um raving reviews to you for for the hard work you put into not just coming on board here and talking for an hour about the findings and we'll continue next time you're on of course but but all the work that goes into coming up with these findings. It's it's um it's incredible. So I really appreciate that. Um, any famous last words, Rich, from your >> No, any I'm I'm done and dusted, as they say. >> You're done and dusted. Okay. Well, great stuff. Thank you so much. Really appreciate that. Um, and as I said, go to your favorite podcast platform and leave a rating and review. Um it it really does help and I hope that many many many more people uh will go and listen to uh what Rich has just explained today because it's so fundamental in the understanding of why of of how markets move and and then also why um certain strategies uh are really well uh designed for this. Um, next week I'll be joined by Nick Balters from Goldman Sachs and um, so that'll be your chance to ask him some questions if you do have questions for Nick. Um, you can email them to me at infotoptradersonplot.com. Maybe he will have some commentary on what Rich has found and shared today. You never know, we'll get some more perspective on this. But in any event, um, 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 [music] take care of each other. >> Thanks for listening to Top Traders Unplugged. If [music] 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 [music] 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. [music] 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]