The Derivative - Crisis Alpha, Cocoa Trends, and Correlated Trendlessness: Inside Aspect Capital’s Strategy with Christopher Reeve

Episode Date: May 7, 2026

Jeff Malec sits down with Christopher Reeve, Chief Investment Officer of Aspect Capital, one of the original managed futures shops with roots tracing back to the "L" in AHL. Chris shares his path from chemistry and early-2000s AI at Oxford to 22 years at Aspect, where he now runs the investment side of the business. Jeff puts every trend following critique on the table, too big, too simple, too crowded, just beta, and Chris pushes back on all of it. They dig into why the edge is real but small, why multi-model diversification is the whole game, and why stacking lookalike models is fake diversification dressed up in a lab coat. The conversation covers cocoa and silver finally paying off, the replicator debate, why bond futures are really just seven yield curves in a trench coat, the case against explicit stops, and prediction markets.Plus King Charles, horses, chickens, and the Superman jokes that write themselves. - SEND IT!Chapters:00:00-01:21=Intro01:22-11:00= From Oxford AI and Chemistry to Building a Managed Futures Powerhouse11:01-18:51= Is Trend Following Too Big and Too Simple? Edges, Critics, and the Evolution of Models18:52-27:49= Designing Durable Trend: Multi‑Model Diversification, Modulators, and the Real Meaning of Crisis Alpha27:50-35:39= Correlated Trendlessness, Crisis Alpha Expectations, and Why Aspect Refused to “Optimize” for the Last Decade35:40-44:05= From Silver to Cocoa: Why Obscure and Alternative Markets Supercharge Trend Diversification44:06-52:04= Replicators, Bond Pain, and the Illusion of Fixed-Income Diversification52:05-01:00:25= How Aspect Sizes Positions, Builds Macro Models, and Lives with Real-World Risk01:00:26-01:06:42= Systematic Macro, Horses, and “Hair‑Dryer Alpha” in Prediction MarketsFrom the Episode: Hi Ho Silver PostTrend Following’s Bond ProblemThe History of Managed Futures (whitepaper)Follow along with Christopher Reeve & Aspect Capital on LinkedIn and be sure to check out aspectcapital.com for more information!Don't forget to subscribe to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Derivative⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, follow us on Twitter at⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@rcmAlts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠sign-up for our blog digest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.Disclaimer: This podcast is provided for informational purposes only and should not be relied upon as legal, business, or tax advice. All opinions expressed by podcast participants are solely their own opinions and do not necessarily reflect the opinions of RCM Alternatives, their affiliates, or companies featured. Due to industry regulations, participants on this podcast are instructed not to make specific trade recommendations, nor reference past or potential profits. And listeners are reminded that managed futures, commodity trading, and other alternative investments are complex and carry a risk of substantial losses. As such, they are not suitable for all investors. For more information, visit⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.rcmalternatives.com/disclaimer⁠⁠⁠⁠

Welcome to the derivative by RCM Alternatives. Send it. Hello there. Welcome back. We found the derivative. It's Star Wars Week. We had May the Fourth be with you on Monday, Revenge of the 5th on Tuesday,

execute Order 66th on Wednesday, and the 7th sister here on May 7th Thursday. That last one's a real deep cut, so see me after, if you've got a problem, and are familiar with that particular inquisitor. Anyway, I winked out on wearing this here, Star Wars gear for the pod, but got it on here for the intro. So just your classic Star Wars T. On to the pod where I get to talk to a guy who manages many billions for the firm's

clients for a firm which is as steeped in managed futures history as you get. Coming out of the AHL tree, which spawned Man AHL and Winton, and of course the firm Christopher Reeve. Our guest today is CIO for Aspect. Send it. All right, everyone. We're here with Christopher Reeve. Chris. Christopher, which one you prefer?

Very happy with Chris. All right, Chris. How are you? Yeah, very well, thank you. How's things over in London? Nice, sunny, breezy day today. It's an interesting month in the markets. But, yeah, all is pretty good here, thank you.

We're recording this on April. 29th is actually my birthday today. The birthday. But your King Charles is here. Yes. The derivative is in London and King Charles is here in the US. What's the view on the King and all that? Everyone still loves the monarchy there?

Yeah. I mean, I think it's something we don't talk about in everyday life. But there's, yeah, I think a lot of support for the monarchy and for the king. I was personally impressed by his speeches yesterday and the job he's doing a sort of reconciling between the Trump administration and the UK. Yeah, great. We were in a meeting. We wanted to listen to it.

Anyway, and you guys are right there in the financial district of London? Or where's the offices? So we're over in sort of just north of Mayfair. So not the traditional city of London, part of London. But actually where quite a lot of asset managers and hedge funds are based, either in Mayfair or where we are a bit north of there on Baker Street. So, yeah, it's one of the definitely finance-heavy. areas in the city. And then I got to ask you about this lovely painting behind you before we get

dusk in the aisles of silly is its title. All right. I don't know the background to this particular one, but it's as a phone we used to sponsor an art prize. And so a lot of the art around the office is from this art prize we used to sponsor, but that's coming back many years. It's, I think it shut down a while ago. This might be one of them. I'm not sure. All right. Love it. So yeah, give us give us the background. How'd you get into the space and how'd you end up at Aspect? Well, the two are actually one of the same because Aspects was the first role I had in the space and that's going back nearly 22 years now. 2004 when I just finished my undergraduate degree, university, was looking to get into

the space and didn't know much about it, really. You found finance at the time because I hadn't done a finance degree. It was hard to understand the space. space, if you like, it was sort of finding an impenetrable area. What was the degree? Well, so my degree was in chemistry, so a very scientific subject and the sort of the master's part of my degree. The final year project was in applying artificial intelligence methods to chemistry.

So all of that, I think, sent me up quite well for quantitative finance, and that was definitely given the skills I thought I had at the time. That was the part of the industry that most appealed. So out of all the firms I spoke to in late 2000, after graduating aspect was the one that really appealed. You were doing AI back in 2004? Yeah, well before they were calling it that. Yeah, so the professor I did my master's project with his research group was looking at

artificial intelligence methods in chemistry. He wrote a textbook on that back in the early 2000s. So yeah, I didn't know it at the time, but it was an area that would, become very trendy. The actual artificial intelligence technique I used, perhaps wasn't the one that has taken off in subsequent years. It was a slightly arcane one, but it gave me a really good grounding in what I was doing was writing a quantitative simulation. In this case, it was of a chemical process, but coding stuff up to simulate quantitative processes is an exactly transferable skill to what we do here at Aspect in the research team.

Love it. So what did you get hired on as and how did you move up the ranks? Yeah, so I started as sort of a junior risk analyst or financial engineer, as we called it at the time. So sort of part up research team, but more looking at risk management and product engineering for different client products, structure products, sorts of things I looked at. I did that for a little while to really learn the ropes, got to know the systems. And even from a really early stage, I was reviewing the new research that was coming out and the new developments we were making to the programs we were running at the time. I then moved, actually made a bit of a shift while keeping one foot in the pure research strategy side.

I spent many years working with our business development team in a sort of a product specialist role, what we now call investment solutions, trying to provide transparency to. to our investors on how the systems work, what research we're doing, why we do what we do and why they would want to invest in it. Did that for a while before moving back onto the pure risk side to run the risk team probably about eight or nine years ago in committee

and more recently moved to run the investment, the whole investment part of the business. Did that work with the client side and trying to explain what the models were doing, how you, right? it kind of taints the wrong word, but to do something to your process where you'd be like, hey, we need to make sure this is explainable to investors. I think that's always been, it's always a bit of a consideration.

You can be, there is a risk that you worry about that too much when investors. I think they want to understand, brush what it is we're doing, but they don't always need to know full detail. We're often very happy to provide it. And one of the great things about that role is being able to go into detail, but not all investors have appetite for all the detail. And you forget that we're often in the best position to judge what's best for our, for our portfolios.

But, but yes, I think that's a really invaluable sort of. Yeah, I feel like sometimes it could go too far. And you're like, no, we can't do that. It could do, right? The clients want this. The clients want that. Well, what actually makes risk adjusted money is more important than what the clients want? A bit of both.

Yeah. Yeah. We definitely pay a lot. We pay a lot of attention to what our clients want, feedback from our investors. But that's only one of the inputs. We have to be the ultimate arbiter of the decisions we make for our portfolios. But yes, I think having that commercial experience, that grounding in talking to investors of a whole different types is really valuable for decisions we now make on the investment committee and on our product committee, which is the group that is. Yeah, I think it was Steve Jobs.

Steve Jobs was saying like they would have never designed any of their products if they'd had, right? If it was a committee of clients or whatnot. Yeah. Sometimes they don't know exactly what they want. And so the firm, did you know if you came out perfectly, you said, hey, I want to go into finance. Here's these 10 firms. Or did you know aspect? Did you know Winton?

Were they all their big things at university? No. Chances or you were just going down a list? No, I hadn't heard of them, actually. I didn't probably know enough about finance industry, let alone the alternatives, investment industry, to know those firms. I'd heard of D.E. Shore, I think,

because they came to a careers fair at the university. Where'd you go? There was Oxford University. I've heard of it. Very nice. So tell us a little bit, speaking of Oxford, right? What's the backstory of aspect is a very unique one? Give us a couple minutes on that.

Yeah, so this is before my time before joining, but the founders of Aspect themselves had back in the 90s, in fact, studied physics together at Oxford, and that's how they knew each other. And then they founded AHL and sort of in the, I think, late 80s early 90s, built that business up, sold it to the man group and after a while went their separate ways for various reasons. And four of them as colleagues from the man group got back together to found Aspect back in 19. 1997. Love it. And so the L and HL is... That's right. So the four original founders, two of them were Mike Adam, the A from A.L and

Marty Lick, the L from AHL. And out of those four original founders, two of them are still working at Aspect today. The other two have retired. So Anthony Todd, our CEO and Marty Lirk, who you mentioned one of the original HL founders, Director of Research here. Yeah, that's such a crazy story that they were all in the same dorm room or what What do you brutes call it?

Yeah, college, I think. And they weren't all in the same college, but yeah, they definitely, they were in the same university and I think studied physics. Two of them started physics together. Three of them knew each other from way back then, instrumental in sort of getting back together a few years later. It's got to be the biggest, the most billions coming out of one, right? Like you had, H.L. went up to however many tens of billions, went and went up to tens of

billions you guys up there. Yes, there's a lot of firms and there's the big ones, the obvious ones. And there's even more from people who have worked at those different firms along the years and over the years and then gone out and launched their own places. So definitely the sort of the managed futures genealogy, if you like, on this side of that is born out of one out of those three. I think I'm going to give you a call and we can do a little infographic, tracing it all Yeah, tracing it all back to the college.

Yeah. So let's dive into that strategy and kind of give us the broad strokes of what it is now, what your flagship's doing now, and then we can dive into different details. Yeah, yeah, of course. Aspect was launched as say back in 1907 as a managed futures firm, Dillwald we're better known for. Our flagship strategy is a trend following strategy at heart, but it's enhanced with the range of other still system.

strategies and that sort of remains the largest part of our business. We also run pure trends strategies for some investors in some of our products and we also run an absolute return program which is growing nicely. It's a sort of a more recent launch but it's really taking off because in the last couple of years. That's more of like still at all in futures markets or it's doing long short equity kind of thing? It's in a couple of the cases we do have some allocation to a single name that which is long short. But yeah, the majority is futures. I think it's sort of 90 plus percent futures at the moment or futures and other derivatives. And yeah, it's it's all systematic, but unlike our flagship diversified program, which is

deliberately very much a trend following dominated strategy, the absolutely return one is, is much more diversified. It's designed to be to produce more sort of stable. So back to the So did you know trend following when you came in? Absolutely not. No, I genuinely didn't. So I was one of these sort of, I say, chemistry student who'd left to Oxford, decided I wanted to learn about finance. So I was reading up about it myself and reading all the sort of finance academia about efficient

market theory, efficient market hypothesis and the capital acid pricing model and all these theoretical concepts that were and still are very sort of parts of traditional finance. but I get this job in an alternative quantitative asset manager, which is what I wanted. And on my first, genuinely, on my very first day there, I get told, yeah, all that stuff you've been teaching yourself, we don't believe it. We think trend following works. I said, really? But isn't that against all of the, I remember my sort of first boss and mentor at the time, taking

me into room for a welcome chat and explaining what we actually did here, because the interview process had been definitely very quantitative and testing. but didn't go into real details on the strategy and saying, yeah, we, we bet on trends continuing. And my initial response was, but everything I've read over the last six months tells me that's, that doesn't work. But so the last 22 years have proved, prove, prove me wrong. Right. But that's, but over those 22 years, surely, right, there's been tens of thousands of pages written again on it's too, trend filing's too big, it's too simple, it's too expensive, all those arguments. So kind of how did you guys, right? Like, what's,

your view or has it changed over the years of like, no, there is still alpha in it or is it shifted? Is it become just this beta that you can capture? Yeah, lots of different points there are actually raised. I mean, and lots of points we've obviously, as you'd expect, read lots of what's been written about it, written some of our own stuff about it, run our own analysis on it. Perhaps the two big point is perhaps an easy one to address. We don't think that's the case. It was, I remember doing some analysis on this way back, sort of 15, 20 years ago,

proxying the whole industry based on if, well, if everyone traded the same way, exactly the same way, would it be too long, would it be too big? And even then it kind of wasn't. Since then, futures market liquidity has grown by more than the industry has grown. It's diversified across trend following, is diversified into many more different derivative products outside of just futures. So size is definitely something you've got to watch for. you've been capacity, but whether it's too big as a strategy, I think we can be pretty confident

that it isn't as an overall thing. But as I say, you have got to watch for that. You've got to, as an individual firm, you've got to watch for your capacity in individual markets and be aware of crowding in individual markets as well. But ultimately, the trends we're trying to capture are in the biggest liquid markets in the world, which are driven by other bigam, in most cases macro or supply and demand effects that override the impact of the trend following community. I'll go through my list, too simple. Yeah, simple. Question mark.

It's a great sort of topic to discuss because in many ways, one of the beauties of it is its simplicity. The thing we're trying to capture is a very simple concept. That's okay. I'd rather, we've spent a long time researching lots of different strategies, ones with simple hypotheses are often the ones you can be most confident in. But does that mean that to do it is simple? No, it absolutely does.

The concept is simple, but because it's a simple concept, and importantly, it's one that has quite a weak edge, trends in markets. It's a behavioral phenomenon that we strongly believe is persistent, but it's not a strong phenomenon. It's not something that you can catch it easily with a simple model. So really, the devil is in the details of how you do it. You don't want to have too simple a model because you're just going to be leaving

opportunities on the table which you can't afford to do given how weak the edge is, weak the effect that we're trying to capture is. But at the other end of the spectrum, too much complexity in your systems also starts to look like a bit of a red flag to me when I'm assessing new research or new models because it just starts to look like you've overfitted, act fitted to the data set, to the historic data set, and you can have less confidence in its future predictiveness. And you move away, kind of move away from.

Yeah, like a lot of these things, it's a balance. I think to the, you were seeing the cartoon, Disney movie, rat tattooing, right? Like simple dish, well executed is a masterpiece. And you often see that on, you know, not just in that film. often see that in real life at restaurants yeah um and what have you guys tested i think i did a pod with uh someone like last year maybe they had actually seen the alpha if we want to call it that over the years over the decades has decayed with a simplistic trend model so that's what you're saying like the edge is very small and is it small and declining or just small always been somewhat

small it's a tough question because what's the model what's the but you get the just i definitely and there's again lots lots you could unpack there i think the edge as in are there trends in markets i think it's small because these are weak effects no trend following trade you do has like an 80-20 chance of success or even 60 40 thing sort of 51 40 in kind of odds if you can do that consistently that's a great um a great source of returns but yes i think it's in an individual in any individual market possibly has decayed a little bit and if you were just using a simple model then yeah the returns for some of the simple models certainly the ones we were running 20 years ago would would not be anything like as good if we'd stuck with those models we probably wouldn't still be in business

because we do believe that markets evolve and the exact way that trends manifest themselves can can and it's important in fact critically important to to do research to keep enhancing your models and keep coming up with new models as well So take us through all the different, you mentioned the research, the evolution, your multi-model, multi-time frame now. So at the beginning was it single model, single time frame? So I think even back at the beginning it was multi-time frame. I think that's always been a key tenet of our approach to diversification because, as I say, if you've got a small edge in what you're doing, the more different places you can do it, the more truly independent place you can do it, you can turn that small edge into a very attractive. return profile at the portfolio level. So you diversify across markets and you try and

diversify across timeframes. So yeah, we've always done multi-timeframes. The models were a lot simpler back then and there were sort of one or two key types of model. And now it's how many models now? Well, on the trend side, it's still not hundreds actually. We don't take the approach of trying to diversify by lots of different ways of doing the same thing because actually it's not real diversification, they're all going to behave in a similar way. So we have, I think it's eight one, it's eight different speeds in our trend following model, but the models, each of those speeds has lots of different stages in it. So we've led on sort of pre-processing stages, signal mapping stages on top of the sort of the core trend measurement stage as well.

Do you ever think, so all those stages, all those timeframes, or you mentioned like if you just have all that diversification, what do you get? Like, what would you, get if you did that. If you had hundreds of models, like, would you get the SACGen trend index or would you get something else? Do you start to, like, diversify away any edge and you're just kind of left at zero or at like the risk-free rate or something? It's not that because they're all similar things. They'd all be different ways of capturing trends if we're still focusing on the core trend systems that we use. The risk is that you get sort of apparent diversification because they're not identical. So in order to hit your risk target, you need to gear the whole thing up,

turn the volume dial up and take a bit more risk, which is fine until you realize that they're all doing a similar thing. They're all in the same trade at the same time. And when that trade goes south, because you've turned the volume dial up, your drawdowns get even big. So there's a real risk of relying on diversification that isn't reliable. It's another way of saying correlation shift, like not just between markets, but between models. Definitely, yeah. And in fact, one most dangerous shifts can be between models because even totally different model, and this is something we do do, because we supplement our trend systems with non-trend, systematic non-trend models, looking at all sorts of other behavioral and economic effects in markets.

And you think they're doing totally different things, but because they're trading the same markets, there will come a time when they're positioned the same way. And you've got to have a portfolio construction and a risk management approach which can deal with that and means you're not sort of over-concentrated on in the occasions when that happens. And are those models counter-trend, or what do you kind of label them as? Well, the term we've historically used for them is modulating models or modulating factors because, and that's more because of the way they're deployed alongside the trend-following signals to try and modulate the trend-following signal to give us a smoother overall return

profile. But no, they're not, none of them are explicitly counter-trend. We're not trying to sort of take the opposite bet, we're trying to capture orthogonal effects, so uncorrelated effects. Could be a range of, broadly, they're either in the technical camp, so other price-driven effects or more macro or economic type models, but always done systematically and built in a way that complements the trend following rather than either doubling up on it or being explicitly ante to it because that doesn't help anyone. to just take the opposite bet

in a different part of your portfolio. And are they mostly negative skew, right? Your trend portfolio, I'm assuming is massively positive skew and all the good trend profiles and then the modulators have kind of the opposite profile or not that simple? Not necessarily.

We try to avoid negatively skewed return profiles everywhere. Yes, trend is well known for having its positively skewed profile, but it's an interesting and often, I think, oversimplified, over-simplification to say trend is positively skewed because over the short-term time frame, trend isn't necessarily positively skewed. Positive skewness comes from the fact that trend is able to adapt to what's going on in the market and therefore will sort of run its winning positions, but when the markets go against it, it will start to react and to close its losing

positions, so therefore it cuts its losers, runs its winners, its winners end up being bigger than the losers and that generates a very simple explanation but that's what generates a positive skew and for that to work you need to have it only it only sort of manifest itself over time frames that are similar to or longer than the length of time it takes your trend system to react so that's what sort of the positive skewness and trend falling comes from the other models no we're not looking to sort of run arbitrage type models where there's a small edge small mispricing we're trying to capture but we're exposed to a big left tail a big negative skew. It's more just other other effects, other behavioral effects or other persistent

things, hypotheses we can identify about market behavior. And the key word there, I think, is hypothesis. We try to make sure that we can explain everything that we build. We're not just sort of throwing all sort of data at our researchers and saying, come up with stuff that works, even if you don't understand what. Right. Then you'd be selling cocoa on Tuesdays or something. Which if you can explain why that's an effect, might well be. Yeah, if there's some shiftment comes in every Tuesday. Yeah, well, exactly, because there are sort of periodic effects in markets, seasonal patterns or behavioral patterns that are driven by investors on particular days or months or timings and so on.

So those are some of the sorts of things we might try and exploit. But no, not if we can't explain it. And have you found over the years it's easier to add these modulators and keep the trend running full gas, so to speak, versus others have said, forget modulating and we're going to try and kind of filter in time, right? We'll either take trend exposure down or ramp it up depending on the environment, the volatility, the trendiness, whatever you want to call it. Yeah, so we do a bit of both. Certainly in a flagship program, we've been adding complementary models, modulating models. I think that's been a certainly recently has been a success story

for us, shows, we can clearly demonstrate the flagship program with all those extra systems has outperformed the pure trend. But even on the trend side, yeah, we look at ways of timing it if we could, because trend is such a sort of intermittent strategy that there's a huge prize to be had if you can time it successfully. But it's like all these things, it's coming up with reliable things you can be confident in that do allow you to time it to any extent at all. And And we do a little bit of that. We think we've got a system that allows us to turn the trend falling up or down a little bit, depending on the portfolio we're holding.

But it's difficult to get right because it is an unpredictable and episodic strategy. I'll give you the secret sauce. You base it on client emails, additions and redemptions, right? When the redemption start coming, Trent's about to the bottom and start going up. Well, sadly, I think there's something in that, Jeff, because it's, It is a sad fact that investors haven't made as much out of trend, their investment in trend following as they probably should have done because certainly in the early years, they weren't able to time it successfully.

They did redeem at the wrong points and subscribe at the wrong points as well. And obviously we do a lot of work with our investors to educate them, to help understand that it's a strategy that is really difficult to time. And if you miss out on the big upswing, the big sort of trend. then that can have a real impact on the returns you get and the benefit it has in your portfolio. Education is key and also building the strategy in a way that can be lived with so that we don't get those redemption requests because we don't see these sort of really testing drawdowns that trend following as a strategy is sort of known for.

And that's part of the thinking behind adding the non-trend models into our flagship program. a little bit of sugar, make the medicine go down. How about the last two plus years, right? We've had some rather whipsaw-y, right? The tariffs, this Iran war beginning, just things whipping back and forth. If that research said this is just more the same, or are we seeing things consolidated into smaller and smaller timeframes? We haven't got any evidence for that sort of, for that anything's changed yet.

I mean, the last two years, as you say, have been quite remarkable. We've seen some really strong periods of performance and some really difficult periods. So sort of talking drawdowns, we just emerged from what was one of our larger drawdowns. But now on the whole, it's trend following, acting as it often has done. And if anything, I prefer the current environment of there are strong trends, but then there are some sharp reversals which are painful to live with. Stuff's going on in the world. Trend as a strategy hopefully can capture.

Whereas I sort of contrast that to previous periods of tough performance back in the sort of the mid-2010s when almost nothing was going on in the world. There were no trends in the first place. So I'd rather have the current environment speaking totally personally from my own viewpoint rather than anything we've done any research on. I'm with you. It feels like it's almost like there's more bullwhip effects now, right? Like when it was just waiting for the next Fed meeting or waiting for a bailout or whatever, that's when everything kind of was going the same. And now it's like, well, that corn's trending, making this up, but whatever's trending because they can't get the fertilizer

because of what's happening in this country. And it seems more independent bets might be a more statistical way of looking at it. I think that's right. Both on the diversification, the number of independent bets you can find, and also just on how likely those bets are to succeed. Because back, as you say, back in the sort of risk on, risk off, and lurching around period, there was no diversification. and there were very little in the way of direction.

So it was sort of correlated trendlessness. And that was a tough period to live through and a tough period to design models to handle. I'm going to borrow that if I can. Correlated untrendiness. Correlate, yeah, it's a trendlessness. Whereas now we've got some trends in recent, recent couple of years. We've also had some tough periods.

We've also had some sharp reversals. We've got more, I would conjecture. We've got more diversification. of opportunities and or opportunities. And do you, have you leaned in over the years to selling it as crisis alpha? Like, hey, it's going to perform in a no way in a one, all that kind of stuff as trend. You lean into that or kind of more of like, no, this is absolute return? No, we definitely lent into that over the years.

I mean, even before, even before genius term crisis alpha was coined, you were already part of my role as a junior guy on the product specialist desk was building presentations to highlight how well. strategy did in in equity drawdown periods in equity crisis periods in 2001 two three 2008 more recently in 2022 so yeah we've we've definitely lent into that but but it's a balance we don't try and design the strategy or sell the strategy as just that we have we have lots of investors who use it for that and explicitly choose aspect in their portfolios because that's the role they're trying to want us to play that's the return profile

they're trying to get, but we also are very mindful of the fact that they've got to be able to live with the investment over the full cycle and deal with drawdowns along the way, deal with just the level of returns if we focused it too much, tuned it too much to just being crisis alpha. I think a lot of our investors wouldn't still be with us when the crisis came along because the returns would just be too lacklustre in the meantime. I, if you would kind of flip that, they've gone through the tariff tantrum and said, like, hey, where's my crisis alpha? Right.

And then you have to explain, well, this wasn't a real crisis. This reversed than it was. So it gets tricky in that regard, too, of like, okay, what they want it for that kind of stuff. But it's a weird explanation of like, well, this wasn't really the type of thing trend's going to do, which is factual, right? The model has a longer time frame. I think that's right. Education is important.

We want our investors to understand it. I spent a large part of my career, as I mentioned, helping our investors to understand the strategy and what they should, and importantly, what they shouldn't expect from it. And yet, tariff tantrum last April was a case in point where if it's a really sure lived event, you shouldn't necessarily, you might get lucky, but you shouldn't expect to get lucky with your trend strategy because it won't have had time to react and adapt to the new trends yet. But equally, I think what I often say is if it's short-lived and it bounces, you don't actually need your crisis response to kick in because it's bounced and the rest of your portfolio has recovered under the month of the S&P for the month of April last year, I think finished just into positive territory. Yeah.

But trend was down, call it, who knows, five or something. So that's when people are like, wait, it bounced and you still lost and now. Sure. But my point is that if you're holding trend as a crisis protector or a real, you're a real threat. risk mitigator, the risks you want to mitigate or the crises you need to protect against are not the ones where it bounces within two weeks and you're, you finish the one positive. The ones you really care about are the prolonged wealth destroying four, six, 12 month drawdowns where the equity market is off 20, 30, 40 percent.

Historically as a strategy trend following has really good track record of delivering in those sort of scenarios. I'm going to switch my thinking or I'll start. to put in some of our materials like the cost of getting the good years-long trend performance is this poor performance in these whipsaw quick events that the crisis didn't totally present itself in yeah i think i think that's fair and obviously you can tune it you can put in biases to be more short equity you could try and tune it to the to the quicker end so you react more quickly to to a crisis we tend not to do too much of that we don't like to have biases in our model either

biases or asset class biases or time frame biases we prefer as I mentioned earlier that principle diversified approach so you didn't there was a siren song like over the last decade right of like make it longer term make it equity positive bias right kind of helped if you ran the back test over that period those right it made your trend much better look much better so you guys have resisted that correct we didn't do that either so you're right there's temptations on both sides for the long-term performance if you just look at history and certainly if you just look at the last 10 or 15 years of history when equities have been so good then slow has been better more equities have been better on the long side has been better whereas if you obviously if you want to tune it to a crisis then

maybe more reverse any long bias you've got in equities and go and go faster and you could get something that probably in most of the historic crises would have done a bit better but it's long-term performance would have been a lot worse and investors might struggle to live with it over the long term. So, yeah, we've resisted both temptations. We've stayed really principled, which is a great thing to be able to say, but won't be right in itself. It means you're not perfect for either scenario. You've got to hope we've got the balance about right.

And I think we have. I think our investors are generally very happy with the approach we take. Take us through the markets, like which sectors, how many markets, all that? Because I'm guessing inside of the market structure, too, you have stuff that's probably never made money in a back test, but it's still in the portfolio. We did it, yeah? Yeah. So, right, I think we did a blog pose last year, too, of high-ho silver. I think silver had never, it was like 15 years on the SACGen trend indicator had never made money.

And then all of a sudden, just this huge outlier moves. Somewhere in there was a question. But like, yeah, take us through the markets, take us through the sectors and markets. And then if you have some examples of like why something's in there that maybe a pure quant would say this shouldn't be in there at all. Well, that's to your silver example, that's because salt gen don't run their indicator back long enough to the early 90s. Yeah, yeah. The Hunt brothers tried to corner the market and you saw some fantastic trade trends. But yeah, then it did nothing.

And there are markets to do nothing. It comes back to that diversification point. We don't think we can predict where trends will emerge, let alone how long they'll, last or which direction they'll be in. So how very principal philosophy is diversify across as many things as we can, as long as to your point about what we don't trade, as long as we think those markets are normally operating with sort of unconstrained price discovery markets we would tend to avoid are ones that are heavily manipulated by massive forces like governments or the like dairy or something. Cap currencies, pegged currencies, somewhere where we, where there isn't a chance

of a bidirectional trend emerging. The market would be much more cautious off and often wouldn't trade or would remove if we had been trading it, but it became subject to such controls. But other than that, no, we look to diversify across as many things as we can because we think every normally functioning market

that is on a real financial or physical commodity has the chance of developing a profitable trend. It comes back to that positive skewness point, you can go for a very long time in an individual market not making any money, not seeing any trends, but when the trends do kick off, they can very quickly outweigh the losses. And in the classic example, you mentioned silver, the other classic example we've had of that in not too, not too distant history is the cocoa market, because cocoa really work, the two Coco futures we trade really were always my example when explaining this of the markets that

have never made money. And then they really did. And they're also a pure example of like not the cocoa logistics don't have anything to do with the Fed or the inflation or right. That was totally separate conditions. Totally, totally diversifying. Yeah. Very independent drivers of those trends. And so what's that total portfolio look like 200, 300?

Yeah, I mean, across the flagship portfolio, it's something like 200 different contracts we trade as well as something like 1,800 single name equities across Europe. In the US, although as I mentioned, that's quite a small risk allocation to those equities. The bulk of the risk is in the 200 derivative contracts we trade. We also have an alternative markets portfolio where we go even further into the sort of the more obscure or harder to access or harder to trade derivative contracts. And we have a China portfolio where we trade Chinese futures, all in the search for diversification. And how do you, so Coco, what are you guys at? Seven, eight, nine billion? What's your AUM again?

Roughly nine billion at the moment. Right. So nine billion. How do you meaningfully get that cocoa exposure, right? Using, we'll stick with Coco as the example. Much less these 250 markets. Like if you have this huge outlier move in market 249, is that really moving the portfolio? So like how do you do that work to say, okay, this is in, but it's not going to really do much

when it hits. It really depends on the market, but when Coco is a big enough market that when it moved the way it did, it had a massive impact. So it remains over the last five years, it remains our single best performing market. And the London Coco contract is our fourth best performing contracts. You know, those markets, they're not viewed as biggest liquid markets because of what trend following tries to do. It tries to sort of tactically time its exposure to the trends. When they really kicked off the moves the moves the size of the moves and the amount of risk we could deploy was was definitely big enough to have a big impact on on our portfolio clearly there's a there's an even longer tail of less liquid markets which if we saw similar size moves wouldn't have such

a big impact there's equally there's a the bulk of the portfolio is more liquid than cocae were we to see those moves where we see those trends even at our size the ability to deploy risk is definitely still there and it's an area we've been working on at the moment. The most recent research projects we've done is improving our portfolio construction to make better use of the available capacity we have. And do you bump into position limits at exchange level and whatnot? It's something we have to be mindful of and the right way to make the best use of capacity is to go up to, but not over, obviously not over, but to go up to those position limits to

make best use of them in some cases. We don't always see the position limits as the constraint. Sometimes our own sort of tolerance for liquidity risk will be the constraining factor. So it might be the... Of you don't, even the exchange might let you be making up numbers. 20% of the open interest and your model will say, no, we don't want to be more than 5% or whatever. Exactly. Yeah, exactly that sort of thing.

If the exchange position limit were 20% of the open interest, we wouldn't let ourselves go up to it because our own, it's not so much the model's tolerance. our tolerance that we've given the models and built into the system is we don't want to be that much that percentage of the open interest. You want to be the fly on the bull or rhino, right? Not driving the reins, not deciding where it goes. Exactly.

And give me an example of one of those alternative markets, right? And like how did that research, it's become a cool thing, I guess, for lack of a better word, in the last few years? Yeah, yeah, it became a cool thing. So the sort of markets were trading there, it's non-futures derivatives, it's things like credit swaps on indices and single names,

it's interest rate swaps, traded over-the-counter, it's ETFs, its single-name equities, traded on a trend following side. Some of them are futures, so on the commodity side, they're broadly futures, but they're harder to access or harder to price or harder to trade systematically. It could be Chinese futures, could be some of the power contracts and other energy markets, where the pricing is different or the expiry cascades, more specialist markets, I guess, which obviously are traded easily by specialists in that sector, but are harder to build into a systematic process. And yeah, it became quite popular. And I think there's two schools of thought on this.

One is these markets are more alternative and they trend better. We never really subscribed that. We never subscribed to that at all. around the analysis on an individual market basis, we can't really tell the difference. We think their, due to trend, is about the same as your traditional major, major futures markets portfolio. Which would make sense. There's still the same behavioral effects, right?

Yeah, exactly. But they're more different. So back to the diversification point, if they're more diversifying to diversified from each other and diversifying to the traditional market set, then they're great additions to a port. portfolio to a trend following portfolio. And coming back to this small edge, do you think there's bigger edge there? Well, there has been over the last few years? Not on a per market basis, not on an individual market basis, but the better edge comes

from- As a portfolio. Because they're more diversified from each other, when you put them together, you get a bigger uplift in your risk-adjusted return. That's our pitch for why alternative markets, transformuling alternative markets is a valuable and diversifying thing to invest. And now while we're on this market conversation, so you're doing whatever that number is,

300 plus some groups out there have been on this podcast say, hey, we can replicate what they're doing with 12 markets, right? Which comes back to that, do I really need that long tail? So what's your thoughts on what the replicators are doing? Is it good for the industry, bad for the industry? Do you care? Do you look at what they're doing? I think they can replicate.

They can definitely replicate a decent, correlation to what we're doing with a small number of markets, but there will be opportunities that they can't, that they miss. I guess also the concept of replication, depends what you mean by replication, whether it's just running a simple trend model or trying to sort of piggyback off what the rest of the industry are doing and replicate. I'd say top down replication where they're saying if I had owned euro dollars and gold for the last month, I would have 88% correlation and 90% of the return of the trend following index. Yeah.

There's clearly something to be said for it. I think if you go into it with your eyes open, knowing what you're getting and knowing what it is they're doing, there's an argument for it. But the replication is updated only periodically. We're top trend falling managers. We are updating our positions intraday and daily, and we're capturing way more potential opportunities.

Again, that diversification point. Yes, the curve sort of tape slant gets less steep as you add more, but it does keep going off. So you might well capture a good percentage of the returns. You'll capture a high correlation, but with this strategy, the devil is in the details, and it's a small edge, so you need to do it as well as you can to make it...

And then it breaks my brain thinking of what if the replicators become bigger than what they're replicating. You know, the tail's eating the dog and you don't know which way's up and what's happening there. Then there might be driving trends that you're capturing, that then they have to try and... replicate. I think that starts to depend how they're replicating it. Yeah. You will trade, we will always trade sort of independently based on our view of what the markets and

all they're doing, not what anyone else is doing. Yeah. And then last bit on markets, we just did a recent blog post. We'll put it in the show notes on bonds have been, and this was back to the tariff and earlier this year like bonds have been terrible in most trend portfolios over the last five years, I'd say, four years maybe, since 20. I don't know if you guys have exact research on that of how bad it's been and just I want you to give me some comfort that it'll turn that it'll change because you guys need, right? Trend needs bonds to be successful. Well, so. Or correct me, yeah.

I agree with you. Bonds have been really difficult for the last couple of years. I mean, every time you think there's going to, there's a new trend developing. It reverses as we saw last month with total change in inflation expectations when Trump attacked Iran. and just what had been developing a nice bond trend in one direction, totally reversed. So, so yeah, it's, it has undeniably been difficult for us as well as for other, um, other trend followers. But does trend following need bonds? Well, not necessarily. Historically, trend following has really has benefited from bonds largely because they've been the sector

that's had some of the best trends for much of history on the long side as yields declined and decline, but then in 2022 on the short side as inflation expectations, and yield sprung back up really, really quickly and in a sustained fashion. So, yeah, they've provided great opportunities in the past, but that doesn't mean we need them. We're a tactical asset allocation model. At a port, although at an individual market level, you're following the trend, put that all together in aggregate what the portfolio is doing is tactically allocating its risk

from one sector to another, from the long side to the short side, depending on where it sees those opportunities. So, yeah, we could survive without there being strong trends in bonds, and I hope we don't have to. We sort of have been the last two years. But we have survived. You know, we've seen some drawdowns where we broadly recouple from them. We've seen examples of this in the past. The energy sector is a great one, which goes through periods of being best performer.

It's flatlined for about five years, at least five years, in fact. 2000 and between the big oil trend in 2008 and back down in 2009, it was another five years of losing. Yeah, 14 was good, I think. And 14 was fantastic for oils and energies. Currances did a similar thing. For a while, currencies was the best performing sector for trend following. Then it went sideways for a long time.

The skill with designing a trend falling system is a model that can capture the opportunities when they emerge, but also minimizes the cost of waiting and deploys risk. elsewhere when you see the choppy period like we have done in fixed income recently. Yeah. I think the trick with fixed income is there's so many good liquid markets, right? Like how do you not let it dominate the portfolio? So do you guys make a conscious decision on that of like we cap this sector limits or the model just sort of works itself out? Yeah, so we have limits. We have concentration limits on all our markets and sectors, but typically in a in a sideways period it isn't those limits that are kicking

in it's the signals themselves having design you need to have designed your signals in a way that doesn't overdeploy risk when there isn't a trend it's having that balance between stability being stable not overcommitting in a whipsawing period but but do commit when a trend emerges and i think i think we've done okay on that you can always work out ways you could have tweaked it to be a bit better but no we don't force fixed income to be any particular percentage of the risk that the system and cater away from it, keep those positions. We'll still trade those markets, but keep those positions small while we hopefully see some opportunities elsewhere. But if I just looked at all of your symbols, fixed income and bonds like 40% of them or something?

It's a, like if the risk, even if the risk isn't like the number of markets you can trade there is quite large, right? It is, yeah. And the other thing to say about fixed income is in the major bond futures have been tough, but actually certainly last year we saw some trends in the OTC interest rate swaps. So it's another benefit of diversifying. If the G7 futures actually futures universe in fixed income is relatively limited, say there's a lot of them and there are if you include all the different sort of short-term interest rate contracts on each strip. Broadly speaking, you're only trading seven yield curves. Each yield curve is kind of different points on the yield curve are all going to be fairly correlated from a directional trend following

perspective. And you've basically got futures on the G7. If you look, beyond that and start trading interest rate swaps on Scandinavian yield curves, New Zealand, emerging markets, then actually the story hasn't been quite as bad over the last couple of years. I like that. So some of us are pulling ourselves with all this diversification in the bond features. It's actually just a couple of G7 bets. Seven yield curves?

I think, yeah, maybe you've got career as well. So you've got, you haven't got 20 different. Right, right. to trade, whereas in the equity space, just looking at big liquid futures, you can easily get to sort of 30-odd individual index futures. But with them as well, the diversity number of markets is not a good measure of diversification because all these equity index futures are correlated. The world's fixed income futures are broadly correlated to each other. So you need to take into account how correlated markets are and how much risk you can deploy in them rather than just how many of them you've got.

Switching gears, you guys do some vault targeting. I don't know if you like that term or not, but I've generally been against vault targeting. So talk me into it. Why is it good? Turn to we mean by vault targeting? Because arguably anyone running a portfolio has done a degree of vault targeting. I would mean on the top level, right, of like, hey, we're going to start to lower less in positions if the ball gets too high and whatnot. instead of a classic trend, right, is using some sort of all proxy to enter the trade.

And then the classic, maybe it's U.S. versus European, the classic U.S. has let it run as long and as far as possible, like kind of drawdowns be damned. Yeah. Orpitos be damned. It sort of becomes a question of, this is a question of how you size your position, both in which is relevant, both at individual market level when you're entering into a trend, as you say, or at the portfolio level. but it's also a question of how, it seems what you're getting is a question of how frequently

you size your position, whereas what you're saying is the traditional approach would be, or traditional US approach would be choose the position size at the start of the trend, put it on and hold it. Whereas, yeah, I think you're right that our approach is a bit more dynamic. In fact, deliberately it's more responsive in sizing our positions. So we look for trends over the medium term, but we will size our positions responsibly. and that does give us a better control on our risk and it almost certainly gives us a better risk-adjusted return

but it may not give us the best outright return as you say you can get higher higher returns from a trend if you know it's going to be a trend by keeping your position big but equally you could also work against you if some trends the vol diminishes as it extends and in our case we'd be growing our position into that trend, whereas the less responsive approach to position sizing wouldn't, so it'd

be less exposed. So I think there's very strong reasons for being reactive in your position sizing, especially in the current environment where we see vols bikes all over the place. We see big changes in the volatility environment at quite short notice. So intuitively, from a sort of macroeconomic perspective, it makes sense to me. Mathematically, I can talk about why risk adjustment. makes a lot of sense and you can demonstrate certainly if you go to a portfolio level that if you don't have any timing skill on when is a good period for the strategy when there's a bad period

for a strategy then the best way to make money from that strategy is to run it at a constant risk rather than letting your risk vary by running it at a sort of a constant leverage therefore hugely variable risk and you so on risk adjuster are you targeting like a higher mar or a higher sharp. Most of people in our space don't care for the sharp, but what kind of risk-adjusted are you kind of trying to increase there? So yeah, we think about various different metrics when we're assessing strategies, when we're assessing research, but a simple sharp ratio is an important one. What is our risk-adjusted return? Because if you maximize that, then you can deploy it at any risk level you want to get the best return for that risk level that you're comfortable with.

But yeah, so we look at, we do look at Sharp ratio. We've done a lot of research looking at downside risk-adjusted metrics as well. We care about, care about sort of ratios. We care about what our investors care about, which is metrics measured over sort of monthly periods as well as daily returns. But the main pain point for investors is the drawdown and length of drawdown. So that kind of works itself out when you increase sharp or you need to have an eye towards that exact step? I think you absolutely need to have an eye towards that stand because, as we discussed earlier, I think if you just focused on maximizing your sharp ratio, it would be sell calls.

You'd run much, well, could do that, or you could just run much slower trend-falling models, and then you'd have some pretty big drawdowns along the way, which might be quite hard for investors to live with. So, yeah, the paint can be long drawdowns, and it can also be short, sharp drawdowns. So you want to have a degree of responsiveness, which actually the more responsive positions, sizing helps with as well. So it helps with the livability of the returns as well as just, which I think is something you need to focus on as well as just the overall sort of bottom, left, top right on your returns curve. And then this feeds into something I was reading about the you don't use stops, right? So it kind of makes sense now that you said all that. It's modulating,

it's position sizing within the trend, so you don't necessarily need stops. Yeah, exactly. I would say we don't use explicit stops. Yeah. Actually, the trend following model itself is implicitly. It stops out its losing position. How quickly it does that. It depends on which speed of model you're looking at. And obviously, the faster ones will stop themselves out more quickly.

And also, we don't, I think stops is a sort of a... Yeah, antiquated. I'm old. It's my birth to, I'm old. It's a binary approach to training, which we don't like. We don't like having big square edges. path dependencies in our systems, partly because as you grow and our size, stopping out of your whole position in one go is important and it's going to be costly, but also just the trading

costs as well as the sort of the path dependency of whether you stop out, whether you just get stopped out or just don't, will have a huge impact on your returns. Yeah, right. Yeah, exactly. So instead we build our models to be continually updating their view. So every day and in fact every hour during the day we're resizing our target position and trading accordingly. So we trade little and often rather than in big size either to get into positions or big size to stop out of them. Was that harder to test?

Maybe not in today's world with today's tech, but 10, 15 years ago was that harder to test than just, hey, we enter here, we use this risk level? No, even I'd say, I mean, going way back, it would have been. but even 10, 15, even 20 years ago, we developed the technology to be able to test. We believe simulate that level of fidelity to trading, yeah. And then what using, I'm sure, Algo execution and getting all the, right, you're letting the machine kind of get the best price over what time frame over like a VWOP? Or how does that look? Yeah, it varies.

But we do trade for the majority of what we do. We trade algorithmically. We trade automatically. We've developed our own algos and typically, as I said, we'd be re-updating our position. In some markets every half hour, some markets are slightly less frequently than that. Typically, we'll schedule a trade for the bin, we call it, the half-hour bin, and let the algo do its best to get that trade done. So it does tend to be trading.

And you don't find there's like, is it moving back and forth within that, within a day? Like at some days you might have exited a lot and re-entered a lot and at the end of the you're kind of back where you were or it's not that fast moving. That can happen but it's rare. So typically because our signals are moving in the medium term, we're going to be extending a position or reducing a position during the day and we'll schedule the trades accordingly. But if something changes and specifically if something changes on the risk management side, the position sizing side, then yeah, we can see that when we started the day buying,

we then change our mind and start selling to reduce positions primarily on risk grounds. I got it. I was confused there. So the signal itself is still longer term and then just the trading buckets or the half hour, right? The signal's not using it. Exactly. We break everything down. The signals are operating frequently and but it's because it's a long term signal that's frequently updated.

But it's likely, apart from an extreme circumstance, it's likely to only be moving in small, in small Up. Last bit, you guys run a systematic macro as well? Is that the absolute return or that's something a third piece? Yeah. So we run macro models. We don't currently have a systematic macro program, but we do have this absolute program which has a much higher weight to those macro models, minimal weight to trend.

It just sees trend falling as one of the multiple different factors it's trying to capture. So yeah, it's roughly 50-50 between. macro in macro strategies and more sort of technical behavioral strategies. And how do you view that's still systematic macro? You don't have macro traders sitting on the desk. Completely. Everything we do aspect is totally systematic. That is kind of the one boundary to what we wouldn't consider. And how do you view that difference between systematic macro and trend, right?

Because they can oftentimes look quite similar. You've got to be aware of the correlation between them. They'll capture, they might capture similar effects for different reasons, or they might capture different effects, but certainly over the long term for us to be adding a new model in, it's because it has some diversifying properties. We look at that religiously every time we do research, we won't add a new model in if it is just capturing the same thing

as something we've already got. But it's like price base for some fundamental input base? Yeah, exactly. I mean, it's a bit of an artificial distinction because we've got so many models in each camp, but broadly for that absolute return program that you asked about, we split the models into two camps, technical ones are the primary input is price-based it's included trend in that but also various

other sort of reversion type strategies or skewness type strategies seasonal patterns in markets all those sort of things and then the macro bucket tends to be where we're looking at non-price based inputs as the input into that into those models you got anything else for us what's something you're into some english based something english what do i what do i spend my time doing yeah yeah uh well i I get away from it all. I live outside of London. I don't live in the city anymore. We have horses.

We have a small holding with family at home. Ride a horse, look after the chickens and sheep and cows and goats. We do all sorts of sort of bucolic countryside stuff. And you're well aware that our Christopher Reeves, Superman, got paralyzed on a horse, and you're still out there. You, Christopher Reeve, are riding a horse. You don't get scared at that? No, well, it's a good point.

I fell off him a couple of months ago, broke some ribs and a shoulder blade. No. Do you have a helmet? Of course. Yeah. But luckily, yeah, luckily all recovered now. So it wasn't as serious as his accident. So yeah, you've got to be careful.

But you can't live your life. No risk. You've got to live your life and enjoy it, haven't you? I love it. And are you, do you like to bet on the horse racing? Do you go to the, what's your race there, the Ascot? I've, what's the big one? Yeah, Ascot is one of the big ones.

the sort of flat racing it's Ascot or Ebson jumps racing it's the Grand National which happened a couple weeks ago or Cheltenham to be honest I'm not hugely into it but everyone everyone sort of follows the grand national a bit of a random bet on a horse you like the name of or other than know anything about them yeah we've got the derby it's going to be next weekend which is our Kentucky one exactly yeah Kentucky Derby and which brings me to sports betting to are you guys looking at all or what prediction markets are they on your radar of using as a price input or as some sort of model? So I think they're certainly on our radar,

but I'm reading the news about them, and I'm thinking, why on earth would anyone want to trade these things? Because they're certainly easily manipulated. You're just giving money to people who have inside information on it. Did you see the story this week about guys making money betting on the prediction markets for the temperature in Paris? And they're going to manipulate it by sticking a hairdry

into the temperature sensor near the airport. Why on earth would you want to bet or... Would you think the platforms themselves would want to clean that up? Because eventually people would be like, this is an unfair game, I don't want to play. Of course, yeah. So I think they're in their infancy, and I'm sure this stuff will get cleaned up, and it will get more regulated or better regulated, because there's a lot of interesting potential diversification out there

that, yeah, we're steering well clear at the moment and just monitoring rather than jumping in to bet on stuff that other people clearly have inside information. But it requires. It's like betting on a horse race after the race has happened. If you knew, right, that'd be good. Awesome. I think we'll leave it there, Chris.

Thanks so much. We'll look you up next time I'm in London. Do the same in Chicago. Likewise, we'll do. Thank you. It's been a pleasure. Okay, that's it for the pod. Thanks to Christopher for coming on.

Thanks to Jeff Berger for producing. Thanks to RCM for sponsoring. Thanks to all of you for listening and bearing with my Star Wars intro. We'll be back next week with a former MLB pitcher turned RAA, getting into all the money in sports if athletes are good investors and some old stories from his days in the bigs. Peace.

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