The Anatomy of a CTA Recovery ft. Katy Kaminski

[00:00:00] Intro

You’re about to join Niels Kaastrup-Larsen 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.

[00:00:23] Niels

Welcome and welcome back to this week’s edition of the Systematic Investor series with Katy Kaminski and I, Niels Kaastrup-Larsen, where each week we take the pulse of the global market through the lens of a rules-based investor.

Katy, it is really great to be back with you this week. How are you doing? What’s going on where you are?

[00:00:38] Katy

Things are good. It’s, you know, good weather here in Boston, enjoying the summer

[00:00:43] Niels

You’re chilling in the Boston sun, hopefully.

We’ve got a great lineup today. We got a few talking points. We’re going to focus on your latest paper on the current state of the CTA and trend following space, but with a little bit of a difference, I feel, compared to the other papers that have been coming out lately. So, that’s always great. We’ve got a few other things we want to talk about which are highly relevant for where we are right now.

And so, you know, super excited about our conversation. But of course, as always, before we even get to that, I would love to hear what’s been on your radar the last few weeks, the last few days, whatever.

[00:01:23] Katy

I mean, it’s been fun. It’s summer. I mean, I think you and I talk about this a lot. I usually spend some time in Scandinavia in the summer. And recently I was actually here for the 4th of July, which I haven’t done in a long time. And it was so fun, so exciting, but I just couldn’t believe, I forgot how much fireworks are, like, they’re everywhere – everybody’s obsessed.

And there were explosions and lots of things happening that were bad as well too. So, I had forgotten, and sort of remembering, when I was a kid, and really loving that 4th of July. So, I think that that’s been an interesting thing, just kind of enjoying, you know, the US holidays celebration.

[00:02:07] Niels

Exactly, exactly. Good stuff. Well, I’ve got a few fireworks myself on my radar, but these are more from our industry.

One thing that actually caught my eye, which, I wouldn’t say I didn’t expect it. I didn’t even think about it. But I saw it yesterday, for the first time. Now it’s a little bit more out in the news, that the old floor traders of the CME are suing the CME group because of loss of their “the privilege they had to own a seat on the floor before the electronic trading.” I’m not going to go into the detail of the case as such.

[00:02:53] Katy

I thought you were saying loss of hearing.

[00:02:57] Niels

No, no, no. I mean this is a $2 billion suit. It’s probably a little bit more than hearing loss here. But it’s kind of interesting that there is this case where you could say it’s almost a case against technological advancement. Now, of course, if there were agreements in place and blah, blah, blah, that has to be upheld, of course.

But I find it interesting. I didn’t expect to see something like this because it’s been a while since we went to electronic trading. But I think I will keep a little eye on this to see how it all pans out. Even though a lot of these cases probably end up in some kind of settlement. But yeah, I thought that was interesting.

[00:03:39] Katy

I forgot about that.

[00:03:41] Niels

Yeah, yeah.

The other thing that I noticed was (this is actually related to our little world) and that is that CTA programs that are focused on China markets actually had somewhat of a different experience in June, doing somewhat worse than the traditional CTA programs. Now, we don’t, at Dunn, trade any Chinese market. So, I have no idea what went on there. So, I’m kind of curious if you know if there was anything unusual about Chinese markets last month.

[00:04:17] Katy

I haven’t looked at it, but what I would guess (I mean this is just my first guess), the Chinese markets are a lot of commodity focused, particularly the futures. So, I guess, you know, you did see big moves related to geopolitical conflict related to different commodities. So, some of the metals, the lead, it’s likely that that was an interesting trending environment. Although energies were much more shocked. Some of these more sort of supply chain metals probably could have been interesting from a trend basis, or in the month of June, which we didn’t see in other markets.

[00:04:55] Niels

Yeah, absolutely, absolutely. Now I’m going to keep the best news for last just to keep the suspense.

So, one more thing that I noticed before we get to the last one and that is that the euro is getting bigger. I saw a headline that Bulgaria has now been given the green light to introduce the euro as of January 1, 2026. I don’t know if it means they’re going to adopt the Euro. I don’t know if they need to approve some things domestically. But yeah, I mean, interesting to have another member of the euro.

[00:05:27] Katy

Is Denmark next?

[00:05:29] Niels

Oh, oh, that’s a really… that’s a really…

[00:05:33] Katy

Sorry, change the subject.

[00:05:34] Niels

You know what? You know what? The thing is (and I’ll be very transparent here), I was living in Denmark back when we had this big debate and vote about it. And of course a lot of people tried to get Denmark in the euro.

I will say that I was skeptical then. And I will also go as far as saying I actually think Denmark has done better than the Eurozone because they stand outside and can still determine their own interest rates and so on and so forth. So personally, I would like to keep the Danish kroner, frankly. I’m sure you must feel the same because you go to Sweden a lot and you have your kroner.

[00:06:14] Katy

The Swedish kroner is a lot weaker. So, it’s not quite the same story.

[00:06:18] Niels

You know what, they actually use that as an argument. Some Danish politicians in the last election, they said, oh, just look at Sweden, how bad the kroner is doing as an argument for Denmark having to go into the euro. I’m thinking, haven’t you looked at the Danish kroner? It’s doing pretty well.

[00:06:35] Katy

Exactly. I mean, and currencies are exciting these days. That’s what I’ve been interested in. I mean, it’s not very fun when you travel abroad because obviously your dollar just doesn’t go quite as far recently, especially this year. And it’s the only trend that’s really worked in trend following too.

[00:06:51] Niels

That is true, that is true.

Do you want to have the best news for last? You mentioned traveling. Do you want to have the very best? And I really mean, this is great news.

The TSA is ending the shoes-off policy for airport security screening. I mean, that’s fantastic news.

[00:07:08] Katy

Everybody’s going to smell better now. It’s going to be great. You know, I hate taking off my shoes.

[00:07:13] Niels

But it’s taken like 20 years to change that policy. So, you know, we can’t say that nothing good comes out of the new policies in the US, even though I’m not sure who actually decides these things. But it’s great news for those of us who still go to the US.

[00:07:30] Katy

I’m going to Google when it starts.

[00:07:31] Niels

Well, I think it has started actually. So, you might be traveling soon, and you might report back and saying, shoes-off, shoes-on. We’ll see.

[00:07:41] Katy

Sounds good.

[00:07:42] Niels

Sounds good.

All right, well, let’s move on to more traditional programming here. What’s going on in trend following right now?

And one thing, and I could have put this on ‘what’s been on my radar’, actually, and that is what happened yesterday in copper, but not copper broadly speaking, Comex copper specifically, i.e. the US traded copper because that had a big move. As far as I remember, this is the largest single day price surge in records, going back to 1968. I say as far as I remember. I mean, of course I read this like an hour ago. So, that’s a pretty sizable move. I think it was up 13% in a day.

And this time I actually think that that kind of surprise, CTAs were on the right side of that move, I have a feeling, can’t speak for everyone. Of course this is tariffs related. I think Trump came out with some tariffs on copper and people thought this is a great idea to make sure we get more copper on the books. Copper traded elsewhere, in London, in China (as far as I think that they also traded there), and are unaffected, as such, by this move. So, was that some good news on your side yesterday?

[00:09:02] Katy

Yeah, I’d say so. I mean, I think positioning was probably small, but you know, it shows how isolated incidents can actually directly link to trends that extend. I mean, obviously copper and a lot of the metals have been directly linked to the trade discussions.

So, we’ve seen sort of some long signaling starting to build in the metal sector just because of tensions and potential tariffs. So not just copper, you’ve seen some interesting moves in other metals as well, like platinum as well, last month was positive. So, I mean, it just shows the diversification of the commodity sector that a lot of investors don’t really have exposure to, directly.

[00:09:45] Niels

Yeah, absolutely. It’s one of those value-adds we certainly provide, for sure.

Other than that, so far this month actually has a little bit of a better feeling to it as far as I can see, on my side, the first week or so. I think CTAs are generally positive for the month. Long equities, of course, are playing out well; metals, you just mentioned. There’s also some short exposure in fixed income, US fixed income, I should say. It’s probably doing okay for managers and we’re also getting a little bit of support for those who trade livestock and grains. That seems to be working out okay. One thing, one area of the portfolio that I think might still be a little bit tricky is European fixed income.

So, what are your thoughts at the moment, based on sort of what’s going on in the CTA space, CTA world?

[00:10:39] Katy

Well, I think the two asset classes that have actually trended the most this year have been equities recently, and also all year it’s been sort of a weak dollar. But that has actually been reverting a little bit this month the dollar. So, there’s been a little bit of support for the dollar this month.

What has been really tricky to me has been fixed income. I mean fixed income has been very mixed. You’ve seen sort of steepening, flattening, you know, posturing with the Fed back and forth, back and forth. I mean it has been a little dance and with really no direction. So, I think fixed income is definitely underweighted by trend following signals.

The interesting one is going to be the commodities I think, because I think energies were really tricky last month. They shocked big and then they came back down and now they’re back up again. But I think metals, and other things linked to this trade policy as it slowly comes out, could be interesting.

And we’re just kind of waiting to see if there is truth to the pivot to positivity for equities or not. I think that’s the theme that most investors are interested in. I’ve seen a pretty large shift in sentiment in the last two weeks or so where the world is kind of saying, actually growth looks a little better than we thought. And we also saw some pivoting to small cap in the US versus large cap.

So, it’s kind of a tentative, you know, environment for equities or people are regaining some conviction I think, and we’ll see if that holds out throughout the rest of the year.

[00:12:20] Niels

You know, for those of us who are systematic, of course it doesn’t really matter. But I think for a lot of people who have to make the decisions, on a discretionary basis, having to probably reduce exposure in equities, long exposure quite heavily, only like three months ago, where there was a lot of angst, I think, in the markets, to now having to suddenly consider buying back at all-time highs. I mean these are psychologically very difficult decisions to make.

So yeah, I think you’re right. I mean the jury is a little bit out in terms of how many people will follow along on these. But I am, actually, as we record today, a little bit early this week, the DAX is making new all-time highs for example, so there could still be some upside I would say. We’ll see, we’ll see.

Anyways, on the positive news, BTOP 50 index is up 27 basis points so far in July. It’s down 3.19% so far this year but that’s really not a big deal. SocGen CTA Index up 22 basis points, down 7.4% so far for this year. SocGen Trend flat for the month so far, down 10% for the year. The Short-Term Traders index up 20 basis points for the month, but down 5.11% so far this year.

MSCI World, as of last night, up 9 basis points for July, up 8.7% for the year. The S&P US Aggregate Bond index is down 68 basis points in July and up 3.17% for the year. And finally, the S&P 500 Total Return up 33 basis points for the month, and 5.85% for the year.

Now I can’t remember exactly the date you and I last recorded on, but I think it would have been around the aftermath of the Liberation Day. So, this feels very different when you read positive numbers for equity suddenly.

[00:14:15] Katy

Yeah, it’s been a long year already.

[00:14:22] Niels

Well, at least we are more than halfway, Katy, so, you know.

The good news is that you have been busy with one of your colleagues trying to put some words on what’s going on, with a little bit of a spin, in terms of how we should think about the current performance, obviously the current drawdowns for the industry, and so on, and so forth. So, I think I’m going to let you dive into it initially. I’ll try and see if I can add a little bit of color or do some follow-up questions.

But why don’t you talk a little bit about not just what inspired you to write, because I’m sure everybody knows that, but actually why you took maybe a little bit of a different angle on this.

[00:15:10] Katy

Yeah, I mean, I love that anything we write about is always about what am I thinking about right now and how am I feeling about a particular environment. And that’s why I wrote a paper on Liberation Day. I wrote a paper now because, anytime you’re in the middle of something, you always kind of see just your nose in front of your face.

And so, it’s kind of like trying to think about, okay, if I step back and I sort of think more like an institutional investor and I try and think about the long term and sort of all history and sort of what is typical across different environments, it always helps me to get some perspective of what paths we might have going forward. So, I think this paper was a very interesting and fun one that kind of looks at market cycles and managed futures drawdowns and it’s really thinking about not just the drawdowns themselves, but recovery from the drawdown.

So, if we’re standing here in a difficult place, like many strategies have, what kind of things happened in the past to get us there and what kind of things happen in the future for us to kind of understand how strategies adapt and change and recover from drawdown?

And so, in the paper, why this is important is that if you look at the top five or six, or we actually list the top of any drawdown for managed futures that’s greater than 10%, the largest drawdown was actually between 2015 and 2019. So, that’s an example of sort of part of it was a little bit during Trump’s first presidency.

But we also know the longest, which is, I guess we would call that the CTA winter. There were also some drawdowns post 2008 and other times where it took a while, the drawdown was very long. And then there are other times where it’s very sharp and, or the recovery is very long.

So, we then plot all of these different drawdowns, how long they took to occur and how long they took to recover, where recovery means that you get back to the place that you were. And that just shows that there’s a lot of variation across different drawdown periods.

So, sometimes you can have something like what happened now and then it is either possible that it’s going to be a short recovery or a long recovery. This led us to ask the next question, and the next question was, when we’re in a drawdown, what is the typical state of the world?

So, you know, is it when everything is good or is it when things are neutral or is it when things are bad? And we simply use equity returns to define this.

And I have this (I love bubble charts, you know me) three dimensional, multicolored pictures that kind of visualize data. I love data visualization. But in this picture, basically you look at how far is the drawdown, how long did it take? So how long did you endure the pain? And then the lower down on this picture, it’s the deeper the drawdown.

And in this particular graph, what sticks out very clearly is that equities tend to be doing very well when things are difficult for us. And you can see that throughout the entire history of the SG Trend index, obviously there’s some variation, but, you know, there’s a clear theme there that, you know, when things are good, trends are maybe a little bit more difficult.

What was interesting is that when you look at recovery, so if you start a recovery from the bottom of the drawdown until the point you get back to where you’re made whole, the longer it takes (and we also plotted across how far you have to go to get there), a deeper drawdown means it’s going to take you longer.

But what’s very interesting in this graph (and we’re on a podcast, so I can just talk about it, I can’t actually show it to them, but they can look later) is something really pops out. And it’s the point that it tends to be that in really challenging environments recovery is a lot faster.

So, if the world goes into a state of stress, then recovery periods tend to be shorter, equities tend to do poorly. On the other hand, if the world is good and equities continue to make new highs and everything’s awesome, then the recovery time can take longer. Which, you know, for most investors, I’d say I think they have a big equity exposure.

So, either way trend looks good coming out of a drawdown in the sense that, you know, if things are great, it’s going to take longer, but your portfolio is going to be doing well. On the other hand, if things are not great, you have something there that actually does really well to recover the drawdown that you had before and is sort of doing relatively well, conditional. So that was kind of the main conclusions of the paper and just kind of giving a sense, standing at a drawdown, what kind of expectations of scenarios should you consider going forward for managed features.

[00:20:33] Niels

This is another way of looking at it, but it kind of also answers the question that I think is relevant because what you see right now is that there is a, how should I say, steady stream of new products being launched related to portable alpha, where you, of course, add the returns of equities to managed futures and the product looks fantastic.

This is not new, but it is relevant because it’s another way of helping people, I think, understand why these two investments are very well suited together. And I often make this example, and people will open their eyes really when they see it on a chart. And that is usually when you blend two investments together, say a 50/50 allocation, you tend to get some kind of average of the two. But actually, when you do it with trend following and the S&P 500, for example (and of course I’m referring to blending it with our own numbers), you almost get the sum of the two, meaning both returns on top of each other, which is, obviously, outstanding. So, there is something there.

Also, I don’t know if you listened to the conversation I had with Rob, I think it was a couple of weeks ago, where we talked about bonds and stocks. It was based on an AQR paper I think Antti Ilmanen had written, where it turned out that even though people think of, say, fixed income as more mean reverting, it actually has more of an inbuilt momentum. That’s how I remember it. And while the opposite is actually the case with equities and how people think about equities. They always think about them being kind of a momentum trade moving higher. But actually. from a trading point of view, they have all these reversions, and corrections, and V shape, this, that, and the other. And it makes it very difficult for trend followers to capture performance.

So, when you look at your return distributions, if I look at our return distributions, we would note that fixed income has done by far better in the portfolio trend portfolio than equities. So, I don’t know if I have a question there but it maybe will give you some ideas to explore it a little bit further before I move into something a little bit further in your paper.

[00:23:01] Katy

Well, I like that, and we can talk about it later, but we have a great paper where we talked about fixed income. And I also think fixed income can be very regime oriented. So, it depends on where you are in the cycle, whether rates are rising or falling, whether the yield curve is inverted, steep or flat, that kind of gives a sense of that it’s a very different market environment.

So, trend has done very well in a falling rate environment, especially when the curve is steep. And then trend does very well short, given this paper as well, when the curve is inverted. Right now we’re kind of in a flattish environment, so that’s a little more mixed. So, it’s very consistent with what we see historically. I think it can really depend on regimes, particularly for fixed income. And that also depends on inflation.

So, it’s complex. We just went through a regime of time, especially for trend, where you just had a lot of falling rates and it was a great trend for many years.

[00:24:07] Niels

Yeah, a couple of things stood out in some of the charts that you put together. One thing is, as you rightly say, that when you have the trend following ‘drawdown duration’ versus ‘drawdown recovery’, the worst two are really the trade war, number one, which is Trump’s first term, and then now the Liberation Day.

I mean, there’s definitely something about Trump and CTA performance that maybe not go so well hand in hand. I’m really hoping that’s going to change in the last three years of his term, for sure. The other thing that stood out to me, and it relates to something that Alan talked about last week (even though we had some awful technical issues, so, I don’t know how many people sat through that episode), he did mention that this time around, the recovery that we’ve seen in the S&P 500, since Liberation Day, of a 20% or more drawdown, is the quickest recovery on record. I think 57 days is what he’s mentioned. And this is even without the Fed stepping in, which is kind of really surprising in some ways.

So, putting that into perspective as well, I mean you can understand why long-term, specifically, trend following strategies are not built for that kind of market behavior. So, that’s something that is also worth just mentioning for those who say why are we struggling during this time? Well, it’s very unusual times in some respect.

[00:25:42] Katy

I definitely agree. I mean what’s interesting to me is that I don’t necessarily think that the longest drawdown was particularly just linked to that particular presidency. It just appeared with very low rates as well. So, that was another factor.

I think some of the shocks from Trump… I remember, actually, funny, we were doing a study of Trump’s tweets, and we just didn’t find that much trends that he could trump – like ‘trump the trends’, and this time I feel like it’s different, this presidency. And I think that’s why we had such a big shock is that people were expecting Trump 2.0 to be the same as Trump 1.0, where it was a talk about metals, and this and that, and we did see moves in metals in the first presidency. But I think it actually signified a much larger global change in geopolitics, a larger change in supply chain, and trade dynamics, as well as sort of a change in even some of the alliances and the way people see things.

And I think that is one of those situations for trend where the initial shock is often bad because it’s based on rhetoric and people realizing that change is coming. What I’m looking for is much more fundamental based information.

So, for example, you mentioned copper. Saying that you have a tariff on copper fundamentally should be directly linked to copper. And so, as we see that sort of fundamental data show us where the new direction is, then we should see trends in asset classes as that trickles out. Not a shock.

[00:27:34] Niels

But my point is, yes, but for me, although it feels nice right now because managers are long and copper’s going up, because it’s not a fundamental in my world, it’s just Trump saying this, and then next week he might say, oh, no, we don’t need that tariff anyway. And then it’s going to… So, I’m hoping for something a little bit more substantial than a tariff, frankly.

But it does lead me into one thing, I think that is in your paper also, and that is that recoveries are often linked to kind of a real narrative change, not just a few data points. It’s kind of we’re going in a different direction here in a broad range, and that kind of leads to then the recovery.

Maybe one way I could explain that or visualize that would be you mentioned that the CTA winter, the change that led to a very, very strong recovery was, of course, the change in interest rates and how they had been behaving for so long. And suddenly we realized, oops, they’re heading higher, they’re heading a lot higher.

[00:28:44] Katy

While we’re dating ourselves. The CTA winter was in 2010-2014, Niels.

[00:28:49] Niels

Oh, that’s the winter. I thought it was the ‘15 to ‘19. What do we call that?

[00:28:52] Katy

We actually called it ‘the CTA winter’ because that’s the second longest drawdown was that period before 2014, before energies exploded. It’s hard to remember it, but it was post GFC where the world had recovered and everything was good and then everything changed in 2014.

[00:29:14] Niels

What do we call then, the ‘15 to ‘19 period, if it wasn’t a winter? Was it like Autumn?

[00:29:18] Katy

We call it Trade War 1.0.

[00:29:22] Niels

Oh, that’s the… Okay, of course. Yeah, fair enough.

[00:29:24] Katy

I mean, aren’t these great names? I love them.

[00:29:26] Niels

Yes, yes. Well, it gets confusing when you have to put labels on every drawdown or flat period of return.

[00:29:32] Katy

It does. There’s a lot of back and forth coming up with these names because you have to kind of think about what is going on in the world. And it’s not equity focused, it’s CTA focused, so.

[00:29:41] Niels

Yeah, and one thing I will say, one of the key takeaways that kind of shows up when you look at the first chart, I think, your paper that you look at, which is really important, actually. And that is when you look at CTA drawdowns, and they are listed next to drawdowns in equities, I mean CTA drawdowns are so much smaller than equity drawdowns. So, I mean, there’s no competition here and people, I think, give us a hard time because the index is down 20%.

This is nothing compared to a 55% drawdown in the S&P 500. Let’s be real. And so, I think CTAs do a good job in managing the downside, generally speaking. Of course, individual manager returns will be different, but I think, as an industry we’ve always done pretty well because (and this was a statistics that I mentioned last week with Alan, which I think was really interesting) if you look at the rolling (and this is from the recent Man paper, I don’t know if you read that, but if you do, give me your thoughts afterwards), the rolling 12 months return, that are less than minus 15% for the CTA index, and this was at the end of April, that could be the number was 2, but it could be 3 now or 4, I don’t know, but it’s pretty small. compared to the rolling 12 months number that is more than plus 15%. I think that number is like 59%.

So, I think we are in good shape even though we get a little bit of heat at the moment in terms of the return. But feel free if you have anything that you took away from the man paper. Otherwise, I have one thing, before we move on to the next topic, that I wanted to put to you.

[00:31:23] Katy

I mean, I think for me this is a really good question. I mean I’m just going to finish one point on drawdowns. And I think people always ask me, you know, how to time trend.

They say like, oh, you know, is there a time where you can find predictability, and this, and that? And I say, you know, that’s a really tough thing to do, especially from the outside. I call it trend following squared, so, trend following trend following. I do not advise it.

The only thing that I tend to talk about is this concept more of rebalancing because the strategy tends to be mean reverting over longer time horizons. And the reason this paper is helpful is that there are plenty of times where the strategy has had a 20% drawdown. There are plenty of times when it has been 15% to 17%. And if you look over longer histories, the strategy has done well.

So, the key is that you shouldn’t time, but you should rebalance. And that’s what we see a lot of institutions understand is that when they’ve made big profits in a 2022, they adjust their allocations and buy equities when equities are low. And then, you know, in a time like this, we’ve actually seen, you know, definitely why investors are not moving managed futures or, you know, understanding that is that this is exactly the time when you don’t want to get out of managed futures because it’s mean reverting over long time horizons. If anything, it might be an opportunity to kind of rebalance to prepare for potential recovery.

And that’s what the end of the paper finishes with is just kind of showing how incredibly strong the recovery periods were once they started. So, I think our big question, Niels, is when does it start?

[00:33:11] Niels

Oh yes.

[00:33:11] Katy

So if you can tell me that I’ll be super happy. I can have a nice vacation this summer.

[00:33:17] Niels

Yes, we’ll definitely explore that as we go along. But you’re absolutely right.

I will say though, from my 35 years of experience in this industry, I will say I don’t really see many investors rebalancing like you talk about, unfortunately. I would love to see a lot more. It is just a hard…

[00:33:39] Katy

I see some on the upside, for sure. I think there’s an asymmetry there.

[00:33:44] Niels

I’ve seen the opposite. I see the opposite. I see people selling trend after it’s done well. I rarely see people buying trend when it’s done poorly. But this time might be different as they say.

I do want to finish with something along those lines and that is (and this is a little bit of a left field thing), there are a lot of “write-ups”, at the moment, about the challenges of CTAs and trend followers. On the other hand, if you’re looking from the outside and you kind of say okay, how do I put together a portfolio of different strategies with my bonds, with my equities? I still have not seen a paper that has come up with a better alternative to trend following. So, maybe you can spin on that a little bit because I think it is important to remind people that this is still pretty valuable.

[00:34:37] Katy

Yeah, I mean I think the challenges, and it was interesting because you had flagged this interesting Man paper, to me, about regimes and sort of this concept that you have a non-parametric approach to determine what regime we’re in.

Talking with some of my peers about this, the only one thing that really stands out when you look at the data as something that kind of naturally connects nicely with equities, where most people are holding growth and equity exposure, is trend following because it’s fundamentally very different. So, if you look historically, and even my drawdown paper kind of shows that, is that it’s one of the few things that tends to, on average, do well during periods of distress or challenging equity markets. And I think that kind of shows that… And it’s not, you know, a silver bullet.

That’s why you see a lot of these institutions that have, I think, rightfully had a more diversified approach to that. They say, you know, I have my first responders, my second responders, my third responders, and they’re just trying to put together portfolios of things that are different, that might be offensive in a defensive environment.

So really, I haven’t seen a lot of… Besides, obviously, there are always papers that find P values that are significant, but there’s really few things that have the robustness of a trend strategy combined with equities as a complementary investment. And I think even CFM had some great historical papers on that as well, talking about skew. And I mean, it’s just really one of the few…

It’s just sometimes it’s hard to hold a trend. And I think that’s why people have to just look at the empirical evidence to kind of understand why they’re doing it, why you and I have been in this space for a long time.

[00:36:34] Niels

Why you and I are still doing it because nobody else wants us, Katy. That’s why we’re still doing it. You know, hat.

Anyways, listen, if you are combining your equity portfolio with something, isn’t it fantastic that at least, typically, that something does poorly when you are doing so great on your equities? I mean, you couldn’t ask for more, really. I mean, it would be a lot worse if it always did poorly when your equities were doing poorly, frankly speaking. I mean, that’s just common sense.

So, yeah, I. But you know what? It is also because a lot of people like to look at individual line items rather than looking at what the effect on the portfolio is doing. And they use Sharpe for something they should never use Sharpe for and all of that stuff. So anyways, we will continue our little fight, Katy, to help people perhaps appreciate more this little space.

So, before we move to that paper you just mentioned, regimes, which I do think you want to say a few words about, there is this other thing that I think is somewhat relevant, maybe for people to understand what’s going on. And I think CFM, some years ago, Jean-Philippe Bouchaud wrote about exogenous shocks and impacts on CTA performance versus endogenous. So, things that come from inside the system and not from the outside.

And in a sense, what is interesting is that what we’ve seen this spring with Liberation Day and so on, and so forth, these are kind of coming from the outside. This is, in this case, Trump coming up with tariffs, and so on, and so forth. And comparing that to something that, for example, happened in the 2022 recovery of CTAs, where this was really more structural. It was positioning that was on the wrong side, in a big way, between expectations of interest rates and where they were going, and so on, and so forth. So, what are your thoughts?

Is it something you even take into account when you talk to people about the different types of impact to markets and how that reflects back on the CTA industry? Is it important to understand the difference, do you think?

[00:38:59] Katy

I mean, I think it’s important. I do agree that exogenous shocks are much harder to predict. But sometimes they can be gray swans as well, you know what I mean? So like, you know, an exogenous shock is something that’s, based on your definition, something that’s not inside the financial system based on, you know, NPV and monetary policy and whatever. But I do see that, you know, exogenous shocks can, depending on how they propagate, be positive for CTAs sometimes, if they extend.

So, what’s challenging is, I think, an exogenous shock that is not sustainable in shorter term, that just is sort of a whipsaw. Those are the worst. And so, you know, if you think about certain exogenous shocks like Covid, it was not anywhere as bad as, say, Liberation Day for CTAs. And why is this the case?

So Covid, even though we didn’t understand the magnitude of that, people did start to understand before that that there was going to be issues with supply chains. They did start to understand that people would be afraid, so they started buying bonds. So, there were some interesting trends that actually leaked out in other asset classes in Covid, whereas that exogenous shock really was an equity specific exogenous shock.

I would say the recent exogenous shock, from Liberation Day, was perhaps more pervasive in the fact that it really went across multiple asset classes in a way that kind of completely showing like, okay, trade policy is changing completely. And that really affected the dollar. It affected sort of people’s perception of what was to expect of the new administration.

And I honestly think, right now, even though we have these shocks like copper tariff, and this, and that, the market is much more reticent to react because the change and the shock has already occurred. So, I think the endogenous shocks are coming based on what you said.

So, the endogenous shocks of maybe a change in monetary policy, maybe inflation, that has to be controlled, and that’s where, you know, endogenous shocks tend to be more positive for trend perhaps because it’s really a fundamental based shift in sort of how people are valuing assets and what they’re worth based on sort of fundamental macro regime. And so, I think that’s for me why, you know, exogenous shocks are sort of, we always remember those dates. I remember really weird things like, you know, one weekend where Italian bonds blew up. You know, any exogenous shock, you remember them.

We wrote a great paper a couple years ago on turbulence, and actually that Man paper mentioned the turbulence metrics, and you can think of those as magnitude shocks, actually, magnitude surprise.

[00:42:11] Niels

Yeah, and this is something that obviously goes to kind of why trend following works. And this is the thing about that, well, we all get the news at the same time, but we kind of digest it at different speeds. And I think a tariff announcement is probably easier for everyone to understand straight away. Oops, things are getting more expensive.

Covid, I think was more difficult to quite understand quickly what that would mean. And it gave us a little bit more time to position ourselves in that case, getting short energies, and so on, and so forth. So, you’re absolutely right.

There are a couple of things I’d like to just mention, and that is you would think that within the CTA space, short-term models and short-term managers would handle exogenous shocks better than long-term. I think that seems reasonable, and vice versa.

This time around we saw it play out reasonably well in April, short-term doing better like it should, compared to long-term. But actually, it’s kind of completely reversed in the last couple of months. Now, you may run different time frames. I know you’re not a short-term manager, but you may run models with different time frames. I mean, is that also kind of how you’ve seen it internally rather than what I can see in the official performance numbers between managers, that it has been somewhat harder to deal with for short-term?

[00:43:43] Katy

It’s all about how long.

I mean, because we saw short-term work really well in Covid. I’m not talking like intraday, I’m talking about, you know, shorter term, like a month or two. But in Liberation Day it was really just, you know, a three day move – two or three days, and that is very hard to statistically to adjust to with data.

So, I think from a horizon perspective, it’s very hard to find significant signals based on such time horizons, depending on what your trading horizon is. So, I think that was why it was very hard too. It just wasn’t like three days and then the trend continued. It was three days and then it bounced back, and then now we’re back to everything’s up again.

[00:44:38] Niels

Yeah, we certainly are.

Well, you kind of alluded to it already and you will probably have read this a little bit more carefully than I have, but I do think it was an interesting concept. And I’m talking about the paper, Regime, written by some of our previous guests, Cam Harvey, Otto Van Hemert. Otto is at AHL, and Cam is linked to Agile, but there are a few other people involved in the paper so I’m only mentioning them because they have been linked to the podcast.

Anyways, of course it is interesting because wouldn’t it be wonderful if we could detect in advance what kind of environment we were going to be in as trend followers? We could say, oh, if it’s a wipsawing environment, let’s reduce our risk a bit. If it’s something with lots of momentum, let’s increase our risk. Now in a way our models are actually trying to do that in their own way. But in this paper they’re taking a very different approach which I’d love for you to explain. I’d love to hear your opinion about what you think this could do, or not, in a trend following world. But yeah, I’ll give you the floor.

[00:46:00] Katy

I really like the paper. I mean I’m obviously a big fan of anything nonparametric, which trend is supposed to be a little bit more nonparametric in some sense.

[00:46:09] Niels

Can you explain that? What do you mean by nonparametric?

[00:46:11] Katy

So, nonparametric means that you’re not sort of defining parameters to define regimes. So, because it’s really easy for us to go back (and I do it myself) and say, this is a rising rate regime and this is a falling rate regime and by defining those things you automatically create sort of bias in your results, and it’s all over in academia. So, it’s sort of like everywhere.

I do appreciate their idea to kind of just say, we don’t know what these regimes are, but we know that there are some key variables that are important. Of course, your first question, if you were reviewing this paper was (and they talked a little bit about this) what are the important state variables?

And the reason they get criticism about this is because when you’re looking for important state variables, you already know which variables are important after you live through these environments – like, Copper was one of their factors. But the idea is very simple and it works like this. If you look at this month and you take these key seven state variables, and so it’s things like equities, it’s the shape of the yield curve, it’s volatility, it’s seven of these sort of common things. Also, your friend Copper is in there too.

[00:47:28] Niels

Yes, Dr. Copper’s in there too.

[00:47:29] Katy

Yeah, exactly. And you take those values, of course they do Z scores, and they look at rolling adjusted volatility as a function of the changes in those variables. And then they look at sort of what are the levels of these key variables. And then what they do is they look at what is known as a Euclidean distance measure or a measure of similarity.

So, you can imagine a seven dimensional state space, with those seven variables, on seven dimensions. I can’t see in seven dimensional space, but why not?

[00:48:02] Niels

I’m trying to imagine that.

[00:48:03] Katy

So, imagine you have this seven dimensional space and then you look at every single point in history and you measure how far away is that seven dimensional dot of this month from all the months in the past based on those state-to-state variables, like equities, whatever. And the fun thing with this is that you’re kind of defining how similar is this month to any historical month in history. And then you kind of can rank, based on the distance metric, any months that are closer to what’s happening today.

[00:48:38] Niels

So, in my simplified world, that means if we look at Liberation Day, that period, and they will go back and say, okay, have we experienced something similar before?

[00:48:49] Katy

Exactly. But they’re going to use some math to define what that similarity is. And it’s not that complicated, but it’s like basically a distance metric.

And so, you take this particular distance metric, and you look at all of history, it’s basically a filtering mechanism. So, you say June, which months are most like June based on some key important variables. And then you take those similar variables, those similar periods of time, and if you’re looking at a particular strategy, this is where it gets a little complex, this paper, and there’s a few details that I would like to grill them on to understand implementation. But basically, you look and say, okay, in a month like June, does value do well? Does trend following do well?

And then they look, historically, at those similar events. So, it’s a little bit of a filtering strategy. And then you use those similar events, and then you determine, well, if it did well in all those past events, we assume that regimes are somewhat persistent. So, for next month, let’s say that value’s going to do well instead of trend, for example, or the opposite, depending on what historical performance is.

And so, it’s a way to kind of classify whether or not it’s a positive or negative state for a particular strategy. But this is pretty complex. Because you’re basically like looking at all history and then you’re going to say, for all the times where the world was like today, let’s go long this, if it worked in the past. And so…

[00:50:27] Niels

I was just going.to say I’ve come up with a buzzword for this while you’ve been talking. It’s regime replication. I mean, replication is so, you know, it’s so up.

[00:50:36] Katy

Everyone loves that word.

[00:50:37] Niels

Everybody loves replication. So, this is regime replication, right?

[00:50:40] Katy

Well, I would just say, it’s just a method of historical filtering.

[00:50:45] Niels

Sure.

[00:50:46] Katy

And it’s a method that doesn’t require you… Because here’s what I meant by nonparametric. You could come up with rules, right? So, whenever the S&P is up, and the yield curve is above a certain steepness, and the VIX is here, you come up with all these huge parameter space of decisions. You’re very likely to fit history and look like you’re the smartest person ever.

Because basically you could pick like, well, whenever the VIX is about to go up, then we’re going to be long equities. I mean, you got to do that on a walk forward basis. So, I think there’s the positive, and why I think they wrote this paper is they like the nonparametric approach as well.

My concern, and I think I have a homework assignment from this, is I would like to see how trend… to do a very similar analysis and look at trend. I’m pretty certain you’re going to see some regime connection between trend and certain sort of more recessionary regimes. And that goes back to the paper that I talked about for fixed income where we actually showed like, you know, trend tends to do well (and this is just for Fixed income) during an inverted yield curve environment. And so, you could see that connection to those state variables.

But this is done in a more nonparametric way than the way that I did it, which is more of sort of a historical study. It wasn’t a trading strategy, it was just an historical analysis.

[00:52:14] Niels

Yes, I mean, in a sense, and correct me if I’m wrong here, what makes it kind of interesting, also, is that this is not really kind of macro analysis. It’s more behavioral analysis of what actually happened.

[00:52:33] Katy

Yeah.

[00:52:34] Niels

Would you say?

[00:52:34] Katy

I would say that it’s not macro in the sense that, it’s basically data filtering, Right?

[00:52:40] Niels

Yeah.

[00:52:41] Katy

So, it’s using, I guess, the only macro side, you might say. And that’s where if someone reviewed this paper, the first thing they’d say is you have these seven variables. But how many did people try to use? And you know, maybe you tried 70 and those seven work. Right. If you tried 10 and those seven worked, then that’s a little better.

But you know, they try to make the argument that people knew that those worked much more historically. I don’t know, I didn’t talk to them about this. But you know, you’re correct. There is still some like macro connection. It’s just done in a purely empirical way.

[00:53:19] Niels

Yeah, Katy, thanks for doing that. I have one other little small surprise that I didn’t tell you about. So, you may not want to comment on it, and that’s perfectly fine. But one thing that also could have been under my… What I’ve noticed this year is of course that replication strategies have done quite a lot better than the benchmarks they’re trying to replicate. And last month I think was pretty noticeable, frankly.

And I know Andrew is coming on in a couple of weeks, so I’m going to tease him a little bit by saying this, but hopefully it’ll inspire him to push back, I’m sure. And that is that my understanding of replication is that it’s trying to give people benchmark returns, hopefully a little bit better because of some cost savings.

Great. Fantastic. Okay.

Well, if you’re trying to replicate that, it also introduces another question that is how accurate can you actually replicate the benchmark? I think that would be a natural question to ask. Now the fact that they have outperformed this year is fantastic. It’s great for the investor. So, well done on that. But it does introduce two questions for me. So, either we must admit that there is a big tracking error. So, either they’re not tracking well enough or we could start thinking about this as another alpha strategy, it’s just using a different input. So, instead of really saying, well, this is replication, no, this is kind of competing with everyone else, it’s an alpha strategy. We are just choosing to use a different input, you know, based on historical returns, etc., etc. But really there shouldn’t be a difference.

So, I don’t know if there is a real question. I don’t want to put you on the spot, but I do think this is really interesting to me.

[00:55:26] Katy

Oh, I think it’s super interesting. I mean, actually we had a recent paper that we talked about before, as well, a couple months ago, where we looked at replication techniques. So, I can definitely point any investors to that because it actually talks about some actual metrics.

I mean, you put me on the spot and that I didn’t memorize the results. So, I don’t remember the exact tracking error, but we actually do report tracking error for replication. And you know, something that, you know, when thinking about replication, tracking error is something that we’re actually monitoring in our space.

What I would say about the relative outperformance of replication recently, it’s not that extreme for the index, for some of the methods that this paper looks at, for example. But what you do see is replication has a few key features. First of all, it tends to be a little bit more slower. And this paper actually talks about the pros and cons of different types of replication. So, anybody wants to nerd out on it, it’s a great one.

But basically, you know, most of the replicator strategies out there are a little smaller in asset set. They also are tending to be more slow in terms of how they move. And so, if you look at some of the environments of the last year, you’ve had some really big exogenous shocks. And I think if you think about yourself like your own equity portfolio (hopefully you didn’t trade around Liberation Day), that’s a very slow moving strategy.

So, if you’re slower, you probably didn’t react as much to some of the data that occurred in the Liberation Day shock, which helped to kind of be closer to kind of the average return of the space. And what we’re seeing is that tracking error is kind of within range for what we expect based on the methodologies that we talk about in that paper. So, I’ll definitely turn anybody to that paper who wants to look at that. We haven’t updated it.

[00:57:41] Niels

Let me ask you, let me follow up on this a little bit, if you don’t mind. And that is, two things. things. One is, well, if it’s just because, by definition, replication is slow because it has to wait for the data, etc. etc., you could also say, well, okay, it’s luck. They’ve just been lucky this time around that they were slow and next year it could be different. So, okay, I understand.

[00:58:05] Katy

Everybody is lucky sometimes.

[00:58:06] Niels

Absolutely. Of course, I don’t mean to say that they’re… We can be lucky as well, being on the right side of a move.

[00:58:14] Katy

I would say… Okay, I want to make one clarification point about the slow part. For me, the speed, and that’s why we talked about this in our paper, is there’s direct, we call it, mechanical replication versus index based, regression based replication. And so, regression based is really sort of looking at the past and that is, is the slowest approach. If you combine some of these approaches, you get something that’s a little more hybrid, that can be faster if necessary to try and track the index or track typical CTA performance or of large CTAs.

Whereas, you know, I think what we have just seen is that there has been extreme shocks which maybe was just better positioned in those type of moves. And the smaller, like the market set, which is much more the developed markets has outperformed too. So, there are a couple of factors in there.

I wouldn’t, say, call those things luck because I think then everybody gets lucky sometimes. My view is that there are just different market regimes. If you were trying to trade cocoa two years ago, replication cannot pick that up. So, I think it just varies over time.

[00:59:33] Niels

Yeah. Okay, final question, promise. And that is, should investors think about some kind of band +/- X% “tracking error”? When is it tracking error? When is it just, you know, within the norm, so to speak?

Because I do think we need to define it a little bit more tightly as we see more and more of these products coming out. Because as I said, I’m starting to feel a little bit that some of this could be regarded as a separate, just alpha engine because I feel that it’s very loose in terms of replication or in terms of tracking error. But how should I think about that in your view?

[01:00:19] Katy

I definitely think it’s very well defined. We explain it in the paper and we actually document the tracking error. It’s something we monitor. It depends on how you implement it, of course.

So, the challenge for the investor is really understanding how the replication techniques are implemented, what type of things – their kind of inputs, and how they’re trading so that they can actually measure tracking error. And you will see variation in tracking error as a function of your approach.

So, let’s say that for example, if you’re using a wider market set. Let me give you a simple example. If you’re running a replication strategy that has no European debt and only trades US, you’re going to see variation where you don’t capture those European moves, so your tracking error will be higher.

There’s sort of a dance though between like how many markets are necessary or not. And that’s why that paper, I nerded back to that paper again there. We see pretty consistent results out of sample, for us, within tracking and replication techniques. And I’d say that it’s just a very different product. Especially what we’ve seen is some clients say it’s just another strategy that can be combined with other CTAs that might smooth the overall dispersion that you see across even replication techniques.

[01:01:48] Niels

All right, well, this was great as always, thank you so much for writing the paper and for all your thoughts and insights. As usual, Katy, I’m sure everyone listening right now feels the same. And if you do, why don’t you show that appreciation by going over to your favorite podcast platform and leave a rating and review praising Katy to the moon, of course.

Next week we’ve got another great guest. It’s Cem Karsan, who’s back. I’m sure people will be interested to hear what he’s thinking right now. He’s made some very bold calls this year. Not that we spend too much time about predicting the future, because of course, in the systematic world we realize that we can’t predict the future.

Anyways, if you have a question for Cem, then it’s your chance to email it to me, info@toptradersunplugged.com and I’ll do my very best to bring it up with him. With that said, from Katy and me, thanks ever so much for listening. We look forward to being back with you next week. And until next time, take care of yourself and take care of each other.

[01:02:54] Ending

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. And be sure to listen to all the other episodes from Top Traders Unplugged.

If you have questions about systematic investing, send us an email with the word question in the subject line to info@toptradersunplugged.com and we’ll try to get it on the show.

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 Systematic Investor.