What if trends in financial markets are not anomalies, but the natural consequence of how markets function? In this episode, Niels and Richard explore the structural foundations of trend following. Drawing on research spanning 68 futures markets across four decades, Richard explains why markets exhibit persistent trends, fat-tailed returns, and volatility clustering. The discussion moves from oil market shocks to deeper questions about feedback loops, participant behavior, and regime shifts in financial markets. The conclusion is striking: trend following does not rely on fragile patterns. It aligns with fundamental structural properties embedded in how markets actually evolve.

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Episode TimeStamps:

00:00 - Introduction to the Systematic Investor Series

02:08 - Oil market shock and the structural setup behind the spike

06:10 - Why calm markets can hide explosive potential

11:47 - How oil shocks ripple through inflation and the global economy

15:29 - Why trend followers focus on process, not predictions

22:15 - A changing regime that may favor trend following

24:43 - The research behind The Fractals of Finance

25:25 - Market memory and the meaning of the Hurst exponent

31:22 - Why trends are structural rather than random patterns

36:25 - Fat tails and why extreme market moves are far more common than expected

41:12 - Divergent vs convergent market participants

45:29 - The hidden risks in traditional volatility targeting

49:33 - Phase transitions and regime shifts in markets

55:33 - Why trend following aligns with market structure

59:02 - Oil shocks, inflation risks, and the next potential market regime

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2. Daily Trend Barometer and Market Score

One of the things I’m really proud of, is the fact that I have managed to published the Trend Barometer and Market Score each day for more than a decade...as these tools are really good at describing the environment for trend following managers as well as giving insights into the general positioning of a trend following strategy! Click Here

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You're about to join Niels Kostrup Larson on a raw and honest journey into the world of systematic investing and learn about the most dependable and consistent, yet often overlooked investment strategy.

Welcome to the Systematic Investor Series.

Welcome or welcome back to this week's edition of the Systematic Investor series with Richard Brennan and I, Nils Kastrub Larsen, where each week we take the pulse of the global markets through the len of a rules based investor.

And I also want to say a warm welcome.

If today is your first time you're joining us and if someone who cares about you and your portfolio recommended that you tune into 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, Niels, and sort of in Australia down here we either have fires or flood and at the moment we're in floods.

So to the north of us and 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 extremes from either end.

You know, the Danish King and Queen is going to visit Australia very shortly as well.

They might need a boat.

Yeah, I'm sure they're not coming by boat all that way, but they may need one.

So anyways, good to hear.

Well, we got an absolutely fantastic lineup of topics to discuss today.

Something I think is pretty groundbreaking, to be frank, and obviously related to trend following, but still in a brand new way that I think people are really going to want to 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 in the recent weeks.

And I know that you've been watching something in the energy markets that may have caught your attention.

So tell us what's 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'll set the scene first.

The WTI fell from around 87 all the way down to roughly US$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 stabilising 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 US$66 all the way up to around about in a very short space of time.

That was an 80% move.

And then almost immediately it started giving it back, dropping to around US$84 by March 10.

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 question I keep coming back to is this.

Does an 80% spike followed by an immediate 30% reversal look like a market that is carnally 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 for a market that it's like when lightning hits dry undergrowth, as Dave Dredge would say.

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 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 US$66 to $119 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 two years, suppressed volatility and a long period of one directional 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 snapback from 1:19 back to US$84.

That's not the market calmly reconsidering the supply outlook.

That's the system that overshot, with the participants who chased the spike getting stopped out, momentum signals flipping.

The same dynamics that drove it 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 primed for it.

What do you think?

So, first of all, and I don't know that people really think about it this way, but actually it first of all means that oil is in a bear 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.

Now, people who have listened to the podcast over the years, 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.

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, the more we build up the potential for something very consequential to take place after that.

Yeah.

And unfortunately, I do feel that a lot of what's going on in the world, it's always managed, it's always manipulated, it's always has some kind of political agenda.

I mean, 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.

And as, as Dave says in, in his writings about, you know, the, the undergrowth 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 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 never get bored, we never get tired.

The models just wait.

They don't.

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 that we could, that we could benefit from.

So it's the diversification, not just of returns, but it's the diversification of investment process that I find so powerful and so useful for pretty much 99% of people's portfolio.

So yes, 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 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, 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.

That's why it's so important to have in the portfolio, because they can have all the right opinions and they can possibly be right about many things.

But also, as 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 do you have in your portfolio when you're wrong.

So that's one.

The other thing I just want to mention something I learned yesterday, listening to the Odd Lots podcast where one of our previous guests, Roy Johnston, was on and talking a little bit about the oil thing.

I had not appreciated that actually right now the reason why the hormones strait is so critical is that we've got about 20 million barrels per day trapped in that area.

And 20 million barrels, that's actually the same amount that we saw in terms of demand destruction when the whole world closed down 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, and you remember this for sure, when oil prices were negative because of the storage.

So the fact that they cannot get 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, 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 effects of what's going on right now.

So anyways, we'll talk about 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 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.

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, because oil derivatives.

They're the raw material for plastics, synthetic fibers, pharmaceuticals, lubricants, countless other industrial agents,

even the top traders.

Unplugged 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, first fertiliser, 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.

And that was a cost that took decades 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 surcharge 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 spike 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 position driven 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 in advance.

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.

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.

But also, you know, with this old oil story, of course it is pretty significant the way, you know, the reactions, you know, this release that they talk about now of, I don't know, hundreds of millions of barrels 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 reliant on a place like Russia to increase its oil production to offset some of this, which from a European perspective is probably not really what we would like to see unfortunately if we should, if there should be any chance of stopping all these conflicts.

But there we are, we'll leave it at that.

Other things that hit my radar by the way, was the fact that our soc gen trend following index hit a new all time high at the end of February.

So we're back from the brink of June of last year where many commentators and the narrative was pretty much in this narrative political driven world where news flashes, drives markets 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.

Obviously I can't help notice the fact that the longer term strategies have had a very strong consistent run.

As I mentioned, the SOC gen trend index is back at new all time highs whilst the short term traders index also from Sockgen is still somewhat below.

It's.

It's only recovered about 50% of that drawdown that it was in and is still some way away from getting back to a new all time high.

In addition to that, of course the longer term performance between those two indices is, is, is very significant and, and in favor of the longer term strategy.

So interesting to see what's going on and why that is.

Hopefully we can bring someone on on the podcast soon that can tell us a little bit more about that.

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 that I publish, usually once a year there is a new version out, an eighth edition.

I think we're up to more than 600 books.

If anyone wants to download it, just hit go over to toptradersonblog.com ultimate okay now trend following.

Just do this section now before we get into the real meat of our conversation today.

My own Trend Barometer finished at 50 last night.

That's still a strong reading, meaning that there is fairly good breadth in a classical portfolio of trend following.

We do of course have an interesting start to march, some give back.

Clearly with what's happened 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 had been in a downtrend for quite a while but that kind of changed going into February mid February where where I think many models would have picked up a change in direction before it got too crazy, which was very useful when when you at the same time would have lost money in equities currencies probably fixed income as well did not quite react in the 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 in March indices are down.

Not surprising.

The beta 50 index is probably down a couple of percent, still up 4.467% so far this year.

Stockton CTA index is down 2.06 so far and also up about 6.11%.

Trend index also down 2.16% but still up 6.44%.

And the short Term Traders Index I'm not entirely sure about this number.

I think it's down also a little bit this month and up around three and a quarter so far this year.

In terms of the real traditional markets, MSCI World so equities are being hit down 2.8% as of last night.

They're now flat for the year.

The aggregate bond index in the US is down 1.21% so no help from bonds 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 but only slight 0.77% so far this year.

I already mentioned I think that you know the energy sectors have done well for trend followers.

We've been hurt elsewhere, of course, equities, some of the currencies and some of the fixed income, although some fixed income markets may actually have helped in the first few days of 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, even the precious metals, not done a lot, sold off a little bit, most likely because people can raise some cash to cover maybe losses elsewhere in the portfolio.

I did read somewhere this morning, Rich, that some of these quote unquote multi pot shops or multi strat funds or whatever has had a little bit of a tough time in March.

So maybe their style of trading, where I imagine it's not really trend following, has found its match when something like this happens.

But of course markets have moved dramatically.

Heating oil, to just give an example, despite the correction, it's still up 52% so far this month and crude is up around 40% from the end of February 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 understand.

Well, I'll allow you, of course.

Rich, any thoughts on the trend space right now before we dive into the more meaty topics we have to get through today?

Well, I think we're coming into a very beneficial regime for trend following simply because of the fact that.

But I think the market's starting to expose a lot of tail properties.

This is not something you see often, but we're certainly seeing it at the moment.

We saw it last month with gold, the metals, et cetera.

Now we're seeing, with the energies, we're seeing this, we talked about it before, the impacts of de globalization, all of these things are flowing through into being very beneficial markets for trend followers.

I would therefore suspect that a lot of the alternative styles of strategy that have been particularly successful over the last decade or so may find that they're struggling in this particular regime.

So when you talk about the pod shops, et cetera, this is sort of probably a regime they're not familiar with or used to, but you usually find that when you start getting into a market that exhibits these tail properties, nearly all strategies fall over apart from the good old trend followers, long volume strategies, those sort of variants.

So I think it's going to be a very challenging time for alternative strategies.

But I'm very thankful we've got our particular strategy going into this regime.

Well, let's dive into this.

I, I mentioned already that it is pretty, pretty extraordinary.

I think what we're going to talk about now, you just published a new book, the Fractals of Finance.

First of all, great, congratulations.

Not easy to bring about a book.

So, so that's great.

And what we're going to do today, we're going to spend the conversation going through the empirical findings that kind of underpins that book and that research that goes into the.

Into it.

Now in order to do this, you built a research program covering 68 futures markets across eight different classes.

It's so funny when I read these numbers, I mean it's almost like exactly like the portfolio we run at Dunn 84.

So.

And since 84.

Anyways, the question driving all of this is to some extent quite simple.

And that is why do patterns that trend followers depend on actually exist not as a matter of strategy aside, but 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 for a living or invest with managers such as ourselves.

So Rich, can't wait to hear what you found.

Well, thanks, Neil.

So the research that informed the book I wrote starts with a simple logical test.

And I want to explain it up front because 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 for following a normal bell curve.

And volatility 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 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 Hurst exponent.

That produces a number between 0 and 1.

A score of 0.5 means the price path is consistent with pure randomness, no memory, no structure.

But if 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 want to be precise here about what the Hurst exponent is 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 it were strong, it would be immediately arbitraged 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 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 0.5, it was 0.866.

It was not in some markets, not in some periods.

Every single market, every decade.

And when we break the data into decades, the results barely move.

So decade averages ranged from between 0.707 to 0.757 across four decades, through financial crises, 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 behaviour of these markets at all times.

So what, 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 that is long range dependence expressing itself.

So the HEARST 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 are 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.

Okay, well, let's just make sure that people fully embrace what you just said because there are some subtle and very important distinctions here.

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, that that's what they say is the reason why TRND 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.

If that's what I'm.

That's exactly right, Niels.

And look in our next podcast, we do go into a phase two of this exercise where we look at the autocorrelation feature that is in markets.

But when you look at very large data sets, the directional correlation effectively averages out to zero.

But this is something I'll reserve for 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 segment that we're talking about here.

So there is an important clarification.

So simple directional autocorrelation.

That means the idea that up today means up tomorrow is indeed close to zero over these large samples.

I'll talk about that in our next podcast.

How we broke that down.

Okay, I don't want to preempt that, but what the HEARST evidence is capturing in this research is something that can't be arbitraged 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, Niels, 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 absolute magnitude approach is telling us.

This volatility clusters that that's why we can exploit these opportunities.

It's not 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 a lot of our models.

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 three and a half million trading days.

So in the entire history of liquid financial markets, we have not accumulated three and a half million trading days.

So in a world of bell curve returns, we should essentially never see a five sigma event.

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?

This is measuring 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 leptokurtic distributions here.

We're not dealing with bell curves.

So in every single liquid market we assessed, it had this leptokurtic property and it had this tail exponent of about 3.33.

So the practical consequence of this is enormous.

So if your risk model assumes bell curve returns, you're not slightly underest 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 USD 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 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 0.353.

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 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 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, Niels, 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, arbitrage, is 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 dominate 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 direction the market's already moving rather than against it.

We are going in the we 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 for selling into a fall falling market.

These are all amplifying moves and they produce the fat tails 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 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 want to make this a controversial point for some listeners who may have a certain way of doing trend following, but you said something interesting.

You said something, and I obviously don't have the exact quote in my head, but you said something about that.

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, then that maybe means that there is some value maybe to dynamic position sizing in a sense that in order to capture that volume expansion, you kind of also need to reduce your exposure as the expansion happens before it collapses again or the price collapse again.

We don't need to go into it, but maybe we will get into it in a second.

The other thing, when I just heard you talk about how we are the amplifiers often.

But of course, 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're to blame for all of this.

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.

So in that sense we will sometimes suppress perhaps the move a little bit to the benefit of some perhaps.

So it's kind of an interesting, and it goes back to this idea about, we talked about earlier on about 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, 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 volume and sell it when you get out.

But, but you can also do it 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 to some extent at least.

So, so that was one thing I, I, I, I picked up on that.

But let's, let's go back to, to some of your things.

I mean, I think the three independent lines of evidence, you know, they're all pointing to the same conclusion.

I think that's incredible, incredibly important and goes to the robustness of the strategy.

Maybe there's a practical question linked to what I mentioned earlier from my side, and that is you probably know, 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 as their way of managing their risk.

But if that's the case, I would imagine that there is some kind of direct consequence of that.

You talk about this tail 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?

Doesn't sound very different, but I think it is very different.

So I'd love for you to be very careful.

If we do target volatility so 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 the future.

And that's effectively therefore being applied to your position sizing.

But this is therefore tied to the middle of the distribution for small and medium moves, because 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.

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 will experience losses that your risk framework was never designed to consider as realistic.

So the crude oil example makes this concrete.

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.

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 built on the bell curve is carrying more risk than it thinks it is.

And that's worth knowing.

So we've established these three empirical signatures.

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 divergent and divergent participants to then observe how market price emerges from their collective behaviour.

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, the simulated market behaves in a very stable way, very much dominated by this convergence signature.

We don't get these amplifying moves.

It's very calm, it's very sedate, it's compressed, so moves revert as it's dominated by these convergent impacts, volatilities 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 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 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 stabilising forces reassert and prices return towards the mid-70s.

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, 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 stabilising 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 calculation, 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 of 0.866 means that trend signals are not noise, they are not patterns, 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 properties.

That's what makes a diversified trend portfolio coherent rather than arbitrary.

And 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 optimised 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 fat tails are real, the memory is real, and they're all consequences of the same underlying structure.

A market where participant behaviour 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, 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 than 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 that the industry has just had one of its longest running profitable periods.

And if we take again, if I look at Duns track record just because it's been around for so long, I think in the 50 years, we've only had two periods now where we've had eight monthly winning months.

This obviously could continue a little bit longer.

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.

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 money every month or every other month.

And there's nothing unusual about it.

It's just the markets are not quite ready to shift into that new regime.

It's absolutely wonderful.

And your paper, of course, you're making it very, very accessible.

So it's like Michael Lewis meets Mandelbrot, I think 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 haven't really spoken about before that there is this, you know, this, these clusterings and as you say, the fat tails, they're really not, they're not random, they're not anomalies.

They're really how.

The kind of the natural behavior of markets, that's 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 findings.

That's what makes it so interesting.

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 said at the very start with the oil market in light of, you know, the idea of lightning hitting dry undergrowth, which of course you also say that our friend Dave Dredge likes to write about.

Because I think it's a perfect lens for everything we've discussed, really.

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 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 whether that tipping point holds or not.

And underneath all of this, the reminder that when crude oil moves this far and this fast, the effects of that run it go 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 settle down and reverse to how things were 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 so many of the other moves we've covered over the years?

I think you've nailed it, Niels.

I think the move in the energy, that's a significant move because of its global impact.

Although I felt the cocoa move was significant for my chocolate consumption, I will

just say true, true, and it affected my cocoa consumption as well.

But I think the energy might have more dramatic consequences.

But it's going to be an interesting regime going forward, Nils.

And for instance, if this oil move is sustainable, sustained, the inflation is going to come roaring back.

And I was thinking our mortgages were sitting up around 18, 19%.

And you know, we're currently in the sort of 5, 6% zone.

And our kids are thinking that's extreme.

But I don't think they remember just back to the 90s when we had it extreme over here.

And 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.

But within that particular context, I think trend following is going to be very healthy during that particular environment.

High inflation, high high interest rates.

I think the trends are going to be significant.

So maybe we're going into 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 while we're talking still, 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 people who've been writing about this.

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 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 get going.

So maybe that's another way for people to think about this.

That the fact that we had 40 years of lower lows 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, maybe people should start thinking about, well actually if what Rich is saying about regimes, we've still got another 35 years to go and that changes everything.

But there's one thing I'm fairly sure of, Niels, we're not going to go back to what was, I think this

the geo, but this is where again we come back to this point about diversification of investment process.

Most investors who do not follow strict rules will probably have this bias to go back 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 if that is unlikely, you need to have something in your portfolio that you, that that doesn't necessarily, you know, work just in the environment we just came out of.

Even if it took 10, 15 years of a certain 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 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.

It's not like we lost money over that period.

We just didn't make as much money as we would like or that we would expect and I wouldn't even say expect because we don't expect to make money in certain environments.

That's the key takeaway for me that this is not a strategy that can only make money when disaster strikes or when then, you know, oil goes from this to that 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 but I mean it's been wonderful.

I really hope that you have lots of take up on your, on your book.

I know people can find it on, on Amazon I'm pretty sure.

At least that's where I go your last book, so I'm pretty sure it's there.

But it's, you know, the more empirical, empirical evidence we can put forward where the logic is clear and there is a connection that we can all see happening in front of us.

It makes the story and the narrative so much more compelling.

And I also hope that people will go and leave some raving reviews to you 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 all the work that goes into coming up with these findings, it's incredible.

So I really appreciate that.

Any famous last words, Rich, from your

no, Niels, I'm done and dusted.

As they say, you're done and dusted.

Okay, well, great stuff.

Thank you so much.

Really appreciate that.

And as I said, go to your favorite podcast platform and leave a rating and review.

It really does help and I hope that many, many, many more people will go and listen to what Rich has just explained today because it's so fundamental in the understanding of why of how markets move and then also why certain strategies are really well designed for this next week I'll be joined by Nick Bolters from Goldman Sachs and so that'll be your chance to ask him some questions.

If you do have questions for Nick, you can email them to me@infooptoptradersonplot.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, from Rich and me, thanks ever so much for listening.

We look forward to being back with you next week and until next time, as usual, take care of yourself and take care of each other.

Thanks for listening to the Systematic Investor Podcast series.

If you enjoy this series, go on over to itunes and leave an honest rating and review.

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And remember, all the discussion that we have about investment performance is about the past, and past performance does not guarantee or even infer anything about future performance.

Also, understand that there's a significant risk of financial loss with all investment strategies and you need to request and understand the specific risks from the investment manager about their products before you make investment decisions.

Thanks for spending some of your valuable time with us, and we'll see you on the next episode of the Systems Investor.