Jeff Malec sits down with Christopher Reeve 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!
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From the Episode:
Hi Ho Silver Post: https://www.rcmalternatives.com/2020/07/hi-ho-silver/
Trend Following’s Bond Problem: https://www.rcmalternatives.com/2026/04/trend-followings-bond-problem/
Check out the complete Transcript from this week’s podcast below:
Crisis Alpha, Cocoa Trends, and Correlated Trendlessness: Inside Aspect Capital’s Strategy with Christopher Reeve
Jeff Malec 00:00
All right, everyone. We’re here with Christopher Reeve, Chris. Christopher, Which one, which one you prefer?
Christopher Reeve 00:05
Very happy with
Jeff Malec 00:06
Chris. How are you?
Christopher Reeve 00:09
Yeah, very well. Thank you.
Jeff Malec 00:11
How’s things over in London,
Christopher Reeve 00:13
nice, sunny, breezy day today, an interesting month in the markets. But yeah, all is, all is pretty good here. Thank you.
Jeff Malec 00:22
We’re recording this on April 29 is actually my birthday today,
Christopher Reeve 00:27
birthday,
Jeff Malec 00:28
but your King Charles is here. Yes, we’re the derivative is in London, and King Charles is here in the US. What’s, what’s the view on the king and all that? Everyone still loves the monarchy there?
Christopher Reeve 00:39
Yeah. I mean, it’s, I think it’s something we we don’t talk about in everyday life, but there’s, yeah, I think lot of support for for the monarchy and for the king. I was personally impressed by his speeches yesterday and the job he’s doing at sort of reconciling between, between the Trump administration and the UK.
Jeff Malec 00:58
Yeah, great. We were in a meeting. We wanted to listen to it anyway. So, and you guys are right there in the financial district of London, or where you where’s the offices. So
Christopher Reeve 01:07
we’re over in sort of just north of Mayfair. So not the traditional City of London, part of London. Perhaps we were quite a lot of asset managers and hedge funds are based either in Mayfair or where we are a bit north of there on on Baker Street. So yeah, it’s one, one of the definitely finance heavy areas in the city. And
Jeff Malec 01:24
then I got to ask you about this lovely painting behind you, before we get get
Christopher Reeve 01:28
dusk in the aisles of silly. Is its title.
Jeff Malec 01:31
All right,
Christopher Reeve 01:33
I don’t know the background to this particular one, but it’s as a firm, we used to sponsor an Art Prize, and so a lot of the art around the office is, is from this art prize we used to sponsor. But that’s going back many years. It’s, I think it shut down a while ago. This, this might be one of them, I’m not sure.
Jeff Malec 01:49
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, at aspect?
Christopher Reeve 01:56
Well, the 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, 1004 when I just finished my undergraduate degree at University, was looking to get into into the space, and didn’t know much about it. Really found finance at the time, because I hadn’t done a finance degree, it was hard to hard to understand the space, if you like. It was sort of finding an impenetrable area.
Jeff Malec 02:26
What was the degree? Well,
Christopher Reeve 02:27
so my degree was in chemistry, so very scientific subject, and 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, set 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 the most appealed. So out of all the firms I spoke to in late 2000 after graduating, aspect was the one that that really appealed.
Jeff Malec 02:58
You were doing AI back in 2004
Christopher Reeve 03:01
Yeah, well before
Jeff Malec 03:02
they were calling
Jeff Malec 03:02
it that.
Christopher Reeve 03:04
Yeah. So the professor I did my master’s project with his his research group was looking at artificial intelligence methods in chemistry. He wrote, he wrote a textbook on that back in the early 2000s and so, yeah, I didn’t know it at the time, but it was an area that would 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.
Jeff Malec 03:48
Love it so that what you get hired on as, and how did you move up the ranks?
Christopher Reeve 03:52
Yeah, so I started as sort of a junior risk off risk analyst or financial engineer, as we called it at the time. So sort of part of research team, but more looking at risk management and product engineering for for different client products, structured products, sorts of things I looked at, 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 in 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, and while keeping one foot in the 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 our investors on how the systems work, what research we’re doing, I 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 and. Um, probably about eight or nine years ago in committee, and more recently, moved to run the investment, the whole investment part of the business.
Jeff Malec 05:09
Did that work with the client side and trying to explain what the models were doing help you right? Did it kind of taint the wrong word? But did it do something to your process where you’d be like, hey, we need to make sure this is explainable to investors.
Christopher Reeve 05:21
I think that’s always been, that’s always a bit of a consideration you can be get you there is a risk that you worry about that too much when investors, I think they want to understand, brush what, what it is we’re doing, but they don’t always need to full detail we’re 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
Jeff Malec 05:57
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? What actually makes risk adjusted money is more important than what the clients want?
Christopher Reeve 06:09
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, but yes, I think having that commercial experience, that grounding in talking to investors of all different types, is really valuable for decisions we we now make on the Investment Committee and on our product Committee, which is the group that,
Jeff Malec 06:39
yeah, I think it was Steve Jobs. I think 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.
Jeff Malec 06:50
Yeah,
Jeff Malec 06:50
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 choices, or you were just going down a list?
Christopher Reeve 07:07
No, I hadn’t heard of them. Actually, I didn’t probably know enough about finance industry, let alone the alternatives.
Jeff Malec 07:14
Yeah,
Christopher Reeve 07:14
investments industry. To know those firms. I’d I’d heard of de Shaw, I think because they came to a careers fair at the university. None of things.
Jeff Malec 07:23
Where’d you go?
Christopher Reeve 07:25
There was Oxford University.
Jeff Malec 07:27
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.
Christopher Reeve 07:37
So sort of, this is before, before my time, before joining but 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 1997
Jeff Malec 08:08
moment. And so the L and HL is,
Christopher Reeve 08:10
that’s right. So the four, the four original founders, two of them were Mike Adam the A from Ahl and Marty Luke the L from Ahl. And out of those four original founders. Two of them are still still working at aspect today. The other two have retired. So Anthony Todd, our CEO, and Marty Luke, who you mentioned, one of the original AHL founders, Director of Research here.
Jeff Malec 08:32
Yeah, that’s such a crazy story that they were all in the same dorm room, or or whatever. What do you Brits call it?
Christopher Reeve 08:38
Yeah, college, I think. And they weren’t
Jeff Malec 08:41
all in the
Christopher Reeve 08:41
same college, but, but, yeah, they definitely, they were in, they were in the same university, and I think, studied physics. Two of them studied physics together. Three of them knew each other from from way back then, instrumental in sort of getting back together a few years later.
Jeff Malec 08:57
It’s got to be the biggest, the most billions coming out of one, right? Like you had, ah, went up to however many 10s of billions went and went up to 10s of billions you guys have up there.
Christopher Reeve 09:08
Yes, there’s a lot of 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
Jeff Malec 09:27
of the Earth is a family tree
Christopher Reeve 09:29
born out of one out of those three. I
Jeff Malec 09:32
think I’m going to give you a call, and when we can do a little infographic, tracing it all down, tracing it all back to the college.
Jeff Malec 09:38
Yeah.
Jeff Malec 09:49
So let’s dive into that strategy and kind of give us the broad strokes of what it is now, what your flagship is doing now, and then we can dive into different details.
Christopher Reeve 09:59
Yeah. Yeah, of course. Aspect was launched, say, back in 1997 as a Managed futures firm. Still, what we’re best known for, our flagship strategy is a trend following strategy at heart, but it’s enhanced with a range of other still systematic 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
Jeff Malec 10:38
that’s more of like still all in futures markets, or it’s doing long, short equity kind of
Christopher Reeve 10:43
thing. It’s, in a couple of the cases, we do have some allocation to it to a single name, equities, long, short, but yeah, 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 absolute return one is, is much more diversified. It’s designed to be to produce more sort of stable. So
Jeff Malec 11:15
back to the so did you know trend following when you came in? Absolutely not. No,
Christopher Reeve 11:19
I genuinely didn’t. So I was one of these sort of, as a chemistry student who’d left left to Oxford, decided I wanted to learn about finance. 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 asset 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 very 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 remember my sort of first boss and mentor at the time, taking me into to 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 that doesn’t work, but so the last 22 years have proved, proved, proved, proved me wrong,
Jeff Malec 12:28
right? But that’s but over those 22 years, surely, right? There’s been 10s of 1000s of pages written again on it’s too trend filings, 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 has it shifted? Has it become just this beta that you can capture?
Christopher Reeve 12:48
Yeah, lots of different points there actually raised, I mean, lot 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, just we don’t think that’s the case. It was. I remember doing some analysis on this way back, sort of 1520, years ago, proxying the whole industry based on, if one of 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. It’s 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. 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 big in most cases, macro or supply and demand effects that override the impact of trend, of the trend following community,
Jeff Malec 14:12
I’ll go through my list. Too simple. Too simple.
Christopher Reeve 14:16
It’s a great sort of topic to discuss, because, in many ways, one of the beauties of it is its simplicity. The thing
Jeff Malec 14:25
we’re trying to
Christopher Reeve 14:25
capture is a very simple concept that that’s okay. I’d rather and 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 capture easily with. The simple model. So really, the devil is in the details and how you do it. You don’t want to have too simple a model, because you’re just going to be leaving leaving opportunities on the table, which you can’t afford to do given how weak the 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 to me when I’m assessing new research or new models, because it just starts to look like you’ve over fitted, fitted to the to the to the data set, to the historic data set, and you can have less confidence in in its future predictiveness,
Jeff Malec 15:44
and you move away from,
Christopher Reeve 15:47
like, a lot of these things, it’s a balance,
Jeff Malec 15:49
I think, to you’re seeing the cartoon Disney movie, rat tattooing, right? Like,
Jeff Malec 15:54
yes,
Jeff Malec 15:54
simple dish, well executed is, is a masterpiece.
Christopher Reeve 15:58
And you often see that on, you know, not just, not just in that film you often see
Jeff Malec 16:02
in
Jeff Malec 16:02
real life at restaurants.
Jeff Malec 16:04
Yeah.
Christopher Reeve 16:06
And what have you guys tested? I think I did a pod with 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 chance 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 8020, chance of success, or even 6040 doing sort of 5149 kind of odds. If do that consistently, that’s a great, 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 do research to keep enhancing your models and keep coming up with new models as well.
Jeff Malec 17:39
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.
Christopher Reeve 17:49
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 in what you’re doing, the more different places you can do it, and more truly independent place you can do it. You can turn that small edge into into a very attractive return profile of the portfolio level. So you diversify across markets, and you try and diversify across time frames. So yeah, we’ve always done multi time frames. The models were a lot simpler back then, and there were sort of one or two key types of model.
Jeff Malec 18:25
And now it’s how many models now?
Christopher Reeve 18:27
Well, on the trend side, it’s, 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.
Jeff Malec 19:00
Do you ever think so, all those stages, all those time frames 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 sock Gen trend index? Or would you get something else? Do you start to, like, diversify away any edge and you just kind of left it zero, or at, like, the risk free rate or something?
Christopher Reeve 19:20
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 give 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 bigger. So there’s a there’s a real risk of over relying on diversification that that isn’t reliable.
Jeff Malec 19:56
That’s another way of saying correlation shift, like not just between market. But between models?
Christopher Reeve 20:01
Definitely? Yeah. In fact, one most dangerous shift can be between models, because even totally different model, and this is something we do do, because we supplement our trend systems with non trends, 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.
Jeff Malec 20:38
And are those models counter trend, or what do you kind of label them as
Christopher Reeve 20:43
well. The term we 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 other price driven effects, or more macro or economic type models, but always done systematically and built in a way that that complements the trend following, rather than either doubling up on it or being explicitly anti to it. Because that’s that doesn’t help anyone to just take the opposite bet in a different part of your portfolio,
Jeff Malec 21:35
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. Not that simple,
Christopher Reeve 21:48
not necessarily. We try to avoid negatively skewed return profiles everywhere. Yes, trend is well known for having its positive, positively skewed profile, but it’s an interesting and often, I think oversimplified oversimplification to say trend is positively skewed, because over the short term timeframe, 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 position. 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 positive skew. And for that to work, you need to have it only it only sort of manifests 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 following 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 that we build. We’re not just sort of throwing all sorts of data at researchers and saying, come up with stuff that works, even if you don’t understand
Jeff Malec 23:25
why, right? Then you’d be selling cocoa on Tuesdays or something,
Christopher Reeve 23:29
which, which, which, if you can explain why that’s an effect. My
Jeff Malec 23:33
Well, if there’s some comes in every Tuesday, well, exactly
Christopher Reeve 23:36
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.
Jeff Malec 23:55
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 and time right? We’ll either take trend exposure down or ramp it up, depending on the environment, the volatility, the trendiness, or whatever you want to call
Christopher Reeve 24:14
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 in recent years, 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, 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 we do a little bit of that. We think we’ve got a system that. Allows us to turn the trend following up or down a little bit, depending on the the portfolio we’re holding. But it’s it’s difficult to get a ride because it is an unpredictable and episodic strategy.
Jeff Malec 25:12
I’ll give you the secret sauce you you base it on client emails, additions and redemptions, right when the redemptions start coming trends about to the bottom and start going up.
Christopher Reeve 25:22
Well, sadly, I think sadly, I think there’s something in that, Jeff, because 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 them understand that it’s a strategy that is really difficult to time. And if you miss out on the big upswings, the big, big sort of trends, then that can have a real impact on the returns, 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. The trend following as a strategy is is sort of known for, and that’s part of the thinking behind adding the non trend models into our flagship program.
Jeff Malec 26:26
Little bit of sugar make the medicine go down
Christopher Reeve 26:39
the and how about the last two plus years, right? We’ve had some rather whipsawy, right? The tariffs, this Iran war beginning, just things whipping back and forth. If that research said this is just more the same and it’s or are we seeing things consolidated into smaller and smaller timeframes? We 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, 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, one of our larger drawdowns. But now, on the whole, it’s, yeah, it’s trend following acting as it 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 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, I’d rather have the current environment, speaking totally personally, from my own viewpoint, rather than anything we’ve done any research on.
Jeff Malec 27:55
I’m with you. It feels like there’s, it’s almost like there’s more bull whip 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 corns trending, making this up, but whatever’s trending because they can’t get the fertilizer because of what’s happening in this country. And yeah, it seems more independent bets might be a more statistical way of looking at it.
Christopher Reeve 28:20
Thing, 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, 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 to handle. I’m
Jeff Malec 28:47
going to borrow that. If I can correlated untrendiness
Christopher Reeve 28:51
correlate. Yeah, it’s a trendlessness. Whereas now we’ve got, we’ve got some trends in recent, recent couple years. We’ve also had some tough periods. We’ve also had some shot reversals. We’ve got more, I would conjecture, we’ve got more diversification of opportunities and or opportunities.
Jeff Malec 29:07
And do you have you leaned in over the years to selling it as crisis health, of like, hey, it’s going to perform in no way, in an on all that kind of stuff as trendy lean into that, or kind of more of like, No, this is absolute return. No, we
Christopher Reeve 29:19
definitely, we’ve definitely lent into that over the years. I mean, I even before, even before genius term crisis Alpha was coined, who were already part of my role, part of my role as a junior guy on the product specialist desk was building presentations to highlight how well the strategy did in in equity drawdown periods, in equity crisis periods, in 2001 to 3008 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 lackluster. In the meantime,
Jeff Malec 30:32
I view it kind of flipped out of 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, and 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 trends going to do, which is factual, right? And that’s the model has a longer time frame.
Christopher Reeve 30:56
I think that’s right. Education is important. We want our investors to 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 short 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. And the month of the S P for the month of April last year, I think, finished just into positive territory,
Jeff Malec 31:44
yeah. But trend was down. Call it, who knows five or something, so that people like, Wait, it bounced, and you still lost. And now, sure.
Christopher Reeve 31:52
But my point is that you’re holding trend as a crisis protector or a risk mitigator. The risks you want to mitigate all 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, 612, month drawdowns where the equity market is off 2030, 40% historically as a strategy. Trend following has really good track record of delivering in those sort of scenarios.
Jeff Malec 32:25
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 that the crisis didn’t totally present itself in? Yeah,
Christopher Reeve 32:39
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 all time frame biases. We prefer, as I mentioned earlier, that principal diversified approach.
Jeff Malec 33:05
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
Christopher Reeve 33:22
correct? We didn’t do that either. So you’re right. There’s temptations on both sides for the long term, Foreman’s, 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 or 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 its 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 we’ve stayed really principled, which is great thing to be able to say, but won’t be right in itself. It means you’re 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 the approach we take,
Jeff Malec 34:30
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
Jeff Malec 34:42
we did, yeah,
Jeff Malec 34:44
yeah. So Right. I think we did a blog post last year too, of Hi Ho Silver. I think silver had never, it was like 15 years on the suction 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 mark. Gets 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
Christopher Reeve 35:08
well, and that’s to your silver example. That’s because salt Jen don’t run their indicator back long enough to the early 90s,
Jeff Malec 35:14
when
Christopher Reeve 35:15
brothers tried to corner the market and you saw some fantastic trade trends, but yeah, then it did nothing. And there are markets that do nothing is 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 half 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 or the like
Jeff Malec 35:56
dairy or something,
Christopher Reeve 35:57
capped currencies, pegged currencies, somewhere where we where there isn’t a chance of a bi directional trend emerging beer marketing would be much more cautious of and often wouldn’t trade, or would remove if, if we had been trading it, but it became subject to to such, such controls. But other than that, no we look to diversify across as many things as we can, because we think every, every normal, normally functioning market that is on a a real financial or physical commodity has 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, outweigh the losses. And in the classic example, you mentioned silver, the other classic example we’ve had of that, and not too not too distant history, is the cocoa market. Because cocoa really work. Have the two cocoa futures we trade really were always my example when explaining this, of the markets that have never made money. And then they really did.
Jeff Malec 37:01
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, it’s conditions,
Christopher Reeve 37:10
totally, totally diversifying, yeah, very independent drivers of those trends.
Jeff Malec 37:15
And so what’s that total portfolio look like? 200 300 like,
Jeff Malec 37:18
yeah.
Christopher Reeve 37:19
I mean, across the flagship portfolio, it’s something like 200 different contracts we trade, as well as something like 1800 single name equities across Europe and the US. Although, as I mentioned, that’s quite a small risk allocation to those equities. The bulk of the risk is in the 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.
Jeff Malec 37:57
And how do you So, Coco, what are you guys at 789, billion? What’s your AUM, again,
Christopher Reeve 38:04
roughly 9 billion at the moment,
Jeff Malec 38:06
right? So 9 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 you have this huge outlier move in market. 249, is that really moving the portfolio? Like, how do you 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
Christopher Reeve 38:27
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 cocoa contract is our fourth best performing contract. 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 and 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 Coco. Were we to see those moves, where we see those trends, even at our size, the ability to deploy risk is is definitely still there, and it’s an area we’ve been working on at the moment, most recent research projects we’ve done is improving our portfolio construction to make better use of the available capacity we have.
Jeff Malec 39:35
And do you bump into position limits at exchange level and whatnot?
Christopher Reeve 39:39
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. So we don’t, we don’t always see the position limits as a constraint. Sometimes our own sort of tolerance for liquidity risk will be the constraining fact. To so might be the of
Jeff Malec 40:01
you. 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.
Christopher Reeve 40:09
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 models tolerance, our tolerance that we’ve given the models and built into the systems is we don’t want to be that much about a percentage of the open interest.
Jeff Malec 40:27
You want to be the fly on the bull or Rhino, right? Not driving the reins, not deciding where it goes
Jeff Malec 40:33
exactly.
Jeff Malec 40:35
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
Christopher Reeve 40:45
became a cool thing. So the sort of markets we’re trading there, it’s, it’s non futures, derivatives. It seems like credit swaps on indices and single names. It’s interest rate swaps traded over the counter. It’s ETFs. It’s single name equities traded on a trend following side, the more Futures On The commodity side, they’re broadly futures, but they’re harder to access or harder to price or harder to trade. Systematically. 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 by 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. We ran the analysis on an individual market basis, we can’t really tell the difference. We think their future trend is about the same as your traditional major, major futures markets portfolio,
Jeff Malec 41:57
which would make sense. There’s still the same behavioral effects, right?
Christopher Reeve 42:01
Yeah, exactly, but, but they’re more different. So back to the diversification point. If they’re more diversifying to diversified from each other and diversifying to a traditional market set, then they’re great additions to a portfolio, to a trend following portfolio,
Jeff Malec 42:16
and coming back to this small edge. Do you think there’s bigger edge there? Well, there has been, over the last few years,
Christopher Reeve 42:24
not on a per market basis, not on an individual market basis, but the better edge comes 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 Trump volume. Will turn to markets is a is a valuable and diversifying thing to investor.
Jeff Malec 42:56
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? 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 do you look at what they’re
Christopher Reeve 43:19
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 replication depends what we 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.
Jeff Malec 43:41
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 80 90% of the return of the trend following index.
Christopher Reeve 43:52
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. What top trend following 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 tapes, gets less steep as you add more markets, 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
Jeff Malec 44:34
and then it breaks my brain thinking of, what if the replicators become bigger than what they’re replicating? Right? The tail is eating the dog, and you don’t, you don’t, you don’t know which way is up and what’s happening there. Then there might be driving trends that you’re capturing that then they have to try and replicate.
Christopher Reeve 44:50
I think that starts to depend how it how they’re replicating it.
Jeff Malec 44:54
Yeah,
Christopher Reeve 44:57
you will trade. We will always trade. So. Of independently based on our view of what the markets themselves are doing, not what anyone else is doing.
Jeff Malec 45:05
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 22 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.
Christopher Reeve 45:33
Well, so
Jeff Malec 45:35
or correct me, yeah,
Christopher Reeve 45:36
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 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 declined, but then in 2022 on the short side, as inflation expectations and yield sprung back up really, really quickly and in a 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 an individual market level, you’re following the trend. Put that all together and 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 can. We could survive without there being strong trends in bonds. And I hope we don’t have to love love.
Jeff Malec 46:56
We sort of have been. The last two years.
Christopher Reeve 46:58
We have survived. You know, we’ve seen drawdowns where we broadly recover 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. 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
Jeff Malec 47:22
14 was good, I think, and
Christopher Reeve 47:24
14 was fantastic. For for oils and energies. Currencies did a similar thing for a while. Currencies was the best performing sector. For for trend following. Then it went sideways for a long time. The skill with designing a trend following system is to have model that can capture the opportunities when they emerge, but also minimizes the cost of waiting and deploys risk elsewhere when you see that choppy beard, like we have done in fixed income recently.
Jeff Malec 47:50
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 capped this sector limits, or the model just sort of works itself out.
Christopher Reeve 48:04
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 over deploy risk when there isn’t a trend. It’s having that balance between stability being stable, not over committing in a whip soaring period,
Jeff Malec 48:29
but
Christopher Reeve 48:30
but do commit when, when a trend emerges? And 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, then the system that will get away from it keep those positions. We still trade those markets, but keep those positions small, while we hopefully see some opportunities elsewhere.
Jeff Malec 48:54
But if I just looked at all of your symbols, fixed income and bonds, like 40% of them or something good. So 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.
Christopher Reeve 49:06
And the other thing to say about fixed income is in the major bond futures have been tough, but actually, suddenly last year, we saw some trends in in the OTC interest rate swaps. So it’s another benefit of diversifying. If the g7 futures. Actually, the 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 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.
Jeff Malec 49:56
I like that. So some of us are fooling ourselves with all this diversification in. In the bond features. It’s actually just a couple g7 bets, seven yield curves.
Christopher Reeve 50:05
I think, yeah, maybe you’ve got career as well. So you’ve got that. You haven’t got 20 different fees to trade, whereas in the equity space, just looking at big liquid futures, you can easily get to sort of 30 odd individual, 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 in 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.
Jeff Malec 50:56
Twitch and gears, you guys do some vol targeting. Is that, I don’t know if that’s a you like that term or not, but I’ve generally been against vol targeting. So talk, talk me into it. Why is
Christopher Reeve 51:06
it good? When do we mean by vol targeting? Because arguably, anyone running a portfolio has done a degree of vol targeting.
Jeff Malec 51:14
I would mean on the top level, right of like, hey, we start to lower, lessen positions if the ball gets too high and whatnot, instead of a, I would say a classic trend, right is using some sort of all proxy to enter the trade. And then the classic maybe it’s us versus European. The classic us is, let it run as long and as far as possible, like, kind of draw downs. Be damned.
Christopher Reeve 51:36
Yeah,
Jeff Malec 51:36
be damned.
Jeff Malec 51:37
It
Christopher Reeve 51:37
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 the portfolio level. But it’s also a question of how it seems what you’re getting is a question 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, it almost certainly gives us a better risk adjusted return, but it may not give us the best outright return. In as you say, you can get higher, higher returns from a trend, if you know it’s going to be a trend by by keeping your position big, but equally, you could also get 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 vol spikes 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 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 is 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.
Jeff Malec 53:40
And you’re so on risk adjusted, 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? What kind of risk adjusted Are you kind of trying to increase there?
Christopher Reeve 53:53
So yeah, we we think about various different metrics when we’re assessing strategies, when we’re assessing research, but a simple Sharpe ratio is a 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 Sharpe ratio. We’ve done a lot of research looking at downside risk adjusted metrics as well. We care about care about sorting their ratios. We care about what our investors care about, which is metrics measured over sort of monthly periods as well as daily returns.
Jeff Malec 54:32
But you’re like 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,
Christopher Reeve 54:42
I think you absolutely need to have an eye towards that Stan because, as we discussed earlier, I think if you just focused on maximizing your Sharpe ratio,
Jeff Malec 54:51
it’d be sell calls.
Christopher Reeve 54:52
You’d run much well, could do that, just run much slower trend following models, and then then you’d have some pretty big. Drawdowns along the way, which might be quite hard for investors to live with. So yeah, the payments can be long drawdowns, and it can also be short, sharp drawdowns. So you want to have a degree of responsiveness, which, which actually the more responsive position sizing helps with as well. So it helps with the livability of the returns, as well as just which, which, I think is something you need to focus on, as well as just the overall sort of bottom left, top right, on your on your returns curve.
Jeff Malec 55:26
And then this feeds into something I was reading about, the you don’t use stops, right? So it’s kind of makes sense now that you said all that it’s modulating its position sizing within the within the trend, so you don’t necessarily need stops,
Christopher Reeve 55:39
yeah, exactly. I would say we don’t use explicit stops,
Jeff Malec 55:42
yeah,
Christopher Reeve 55:42
actually, the trend following model itself is implicitly
Jeff Malec 55:46
a
Christopher Reeve 55:46
it stops out. It’s losing position. How quickly it does that 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,
Jeff Malec 56:01
yeah, an antiquated I’m all
Christopher Reeve 56:04
it’s a binary approach to trading, which we don’t like. We don’t like having big square edges or path dependencies in our our systems, partly because, as you grow and our size, stocking out of your whole position in one go is going to be costly. But also just the trading costs, as well as the sort of the past dependency of whether you stop out, whether you just get stopped out or just don’t, will have a huge impact on on your returns.
Jeff Malec 56:34
Luck.
Christopher Reeve 56:35
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 position, our target position, and trading accordingly. So we trade, we trade little and often, rather than in big size, either to get into positions or big size to stop out of them.
Jeff Malec 56:55
Was that harder to test? Maybe not in today’s world with today’s tech but 1015, years ago, was that harder to test than just hey, we enter here. We use this risk level.
Christopher Reeve 57:05
No, even, I mean, going, going way back, it would have been, but even 1015, even 20 years ago, we developed the technology to be able to test, and we believe, simulate that level of fidelity to trading, yeah,
Jeff Malec 57:20
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 V wop, or how does that look?
Christopher Reeve 57:32
Yeah, it varies. But we do trade for the majority of what we do. We trade algorithmically, we trade we trade automatically. And we’ve developed our own algos, and typically, as I said, would be re updating our position in some markets every half hour. Some markets slightly less frequently than that, typically will 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 is. It does tend to be trading,
Jeff Malec 57:58
and
Jeff Malec 58:00
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 day you’re kind of back where you were. Or it’s not that fast moving
Christopher Reeve 58:11
can happen, but it’s rare. So typically, because our signals are moving in the medium term, we 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 the risk management side, the position sizing side, then, then, yeah, we can see the when we started the day buying, we then change our mind and start selling to reduce positions, primarily on on risk grounds.
Jeff Malec 58:42
I get, I was confused there so that the signal itself is still longer term, and then just the trading buckets or the half hour. But the signals not
Christopher Reeve 58:50
exactly. We break everything down, the signals, signals getting frequently and but it’s because it’s it’s a long term signal, it’s frequently updated. But it’s likely, far from an extreme circumstance. It is likely to only be moving in small, in small.
Jeff Malec 59:16
Last bit, you guys run a systematic macro as well. Is that the absolute return, or that’s something a third, third piece.
Christopher Reeve 59:22
Yeah. So we run macro models. We don’t currently have a systematic macro program, but we do have this absolute one program which has a much higher weight to those macro models, minimal weight to trend. It just sees trend following as one of the multiple different factors it’s trying to capture. So, yeah, it’s roughly 5050, between macro and macro strategies and more sort of technical behavioral strategies.
Jeff Malec 59:49
And how do you view that’s still systematic macro you don’t have macro traders.
Christopher Reeve 59:53
Clearly, everything, everything we do, aspect, is totally systematic. That is kind of the one boundary to what. Wouldn’t, wouldn’t consider,
Jeff Malec 1:00:01
and
Jeff Malec 1:00:01
how do you view that difference between systematic, macro and trend, right? So they can oftentimes look quite similar.
Christopher Reeve 1:00:07
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 these, 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.
Jeff Malec 1:00:28
But it’s like price base for some fundamental input base.
Christopher Reeve 1:00:32
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 include 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 the into those models.
Jeff Malec 1:01:03
You got anything else for us? What’s something you’re into some English based something
Christopher Reeve 1:01:07
English. But what do I spend my time doing?
Jeff Malec 1:01:09
Yeah,
Christopher Reeve 1:01:10
yeah. Well, I get away from it. Or 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.
Jeff Malec 1:01:28
Are you
Christopher Reeve 1:01:28
colic, countryside stuff?
Jeff Malec 1:01:30
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 that you don’t get scared at that?
Christopher Reeve 1:01:39
No, well, it’s a good point. I fell off him a couple of months ago, broke some ribs and was shoulder blade.
Jeff Malec 1:01:44
No, do you have a helmet?
Christopher Reeve 1:01:46
Of course, yeah. But luckily, yeah, luckily. All recovered now. So it wasn’t, it wasn’t as serious as his accident. So, yeah, you got, you’ve got to be careful, but you can’t live your life no risk. You’ve got to, got to live your life and enjoy it, haven’t
Jeff Malec 1:01:59
you? I love it. And are you a Do you like to bet on the horse racing? Do you go to the What’s your race? There? The Ascot there? I’ve
Christopher Reeve 1:02:08
Yeah, Ascot is one of the big ones, the sort of flat racing. It’s Ascot or or Epsom jumps racing. It’s the ground national, which happened a couple of weeks ago, or Chelm, to be honest, I’m not hugely into it, but everyone, everyone sort of follows the Grand National bit of a random bet on a horse you like the name of rather than know anything about them.
Jeff Malec 1:02:27
Yeah, we’ve got the derby. It’s going to be next weekend, which is our
Christopher Reeve 1:02:31
Kentucky
Jeff Malec 1:02:32
Exactly.
Christopher Reeve 1:02:32
Yeah,
Jeff Malec 1:02:33
Kentucky Derby. And which brings me into sports betting too. 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.
Christopher Reeve 1:02:43
So I think they’re suddenly on our radar. But where 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 Did you see the story this week about guys making money betting on the prediction markets for the temperature in Paris, and
Jeff Malec 1:03:05
then they had
Christopher Reeve 1:03:06
to manipulate by sticking a hair dryer into the temperature sensor near the airport. Why on earth would you want to bet? Or
Jeff Malec 1:03:13
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,
Christopher Reeve 1:03:19
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 on,
Jeff Malec 1:03:41
but it requires,
Christopher Reeve 1:03:42
it’s like betting on a horse race after the race has happened.
Jeff Malec 1:03:46
If you knew, right, it’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.
Christopher Reeve 1:03:53
Likewise, will do thank you. It’s been a pleasure.
Jeff Malec 1:03:55
You.
This transcript was compiled automatically via Otter.AI and as such may include typos and errors the artificial intelligence did not pick up correctly.
