In this episode, we get an exciting behind-the-scenes story of one of the most famous systematic trading firms of its time, AHL. Our guest is one of the firms founders and takes us from the company’s birth to its acquisition by Man Group. We also discuss how he started his next company, Aspect Capital, how he creates his trading models, and how to build and run a successful multi-billion trend-following firm. This episode is full of insights and stories that you won’t hear elsewhere.

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In This Episode, You’ll Learn:

• About Quantitative Investment research.
• About Martin’s background in physics.
• Martin’s time at his first company, AHL and how it had a profound effect on the whole managed futures industry.
• How Martin met his future AHL co-founders at university.
• Why AHL was a happy accident.
• How he met his friend Michael Adam and went to work for his dad after studying in Oxford.
• Martin started working for Michael’s dad as well, investigate many trading models and distilling them into key concepts.
• In 1987 they founded AHL with David Harding after leaving Michael’s father’s business.
• They started with $100k of investor money that bridged their split from the family business.
• About MINT, a pioneering systematic CTA in the early 80s.
• How they tried to articulate their trading patterns in the form of a computer trading model.
• What the initial AHL model looked like back then.
• How they over optimized in the beginning and had to learn things as they went along.
• How AHL got involved with Man Group.
• The skills that each of the 3 Founders brought to the table.
• In 1989 Man Group took a stake in AHL.
• How the Man buy changed their business.
• What happened after Man’s IPO.
• How Michael, David, and Martin went their own ways after they left AHL.
• How Martin started Aspect Capital with Anthony Todd, Eugine Lambert and Michael Adam.
• Why he parted ways with his other AHL founders initially and did not start AHL 2.0.
• What he does when he is not working.
• Aspect was founded on bringing managed futures to the institutional side of things.
• What it looks like running 100-person+ organization.
• What he looks for when adding new researchers and staff to his team.
• The lessons he has learned and the mistakes he’s made in building a culture of an organization.
• About their track record and how it should be viewed.
• Martin’s persistence in using trend following models.
• How his models have changed and how he has dealt with risk management over the years.
• What it means to change his models from a binary implementation to an analog implementation.

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Resources & Links Mentioned in this Episode:

• Learn more about AHL.
• Find out more about the MAN group.

Follow Niels on Twitter, LinkedIn, YouTube or via the TTU website.

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And you can get a free copy of my latest book “The Many Flavors of Trend Following” here.

Learn more about the Trend Barometer here.

Send your questions to info@toptradersunplugged.com

And please share this episode with a like-minded friend and leave an honest Rating & Review on iTunes or Spotify so more people can discover the podcast.

Follow Aspect Capital on Linkedin.

Copyright © 2023 – CMC AG – All Rights Reserved

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Disclaimer

For those of you who are new to the show I just want to let you know that you can find all of the show notes including a full transcript of today's episode on the TOPTRADERSUNPLUGGED.COM website. Now let's get started with part one of my conversation. I hope you will enjoy it.

Niels

Marty, thank you so much for being with us today. I really appreciate you taking the time.

Marty

Oh Niels, it's my pleasure actually; this is great.

Niels

Fantastic. Now Marty, I think it's fair to say that many people who are involved in the hedge fund industry, and certainly people who are involved in the managed futures industry are very familiar with your name and that of your partners from AHL. So instead of me doing my usual summary of some of the key point in your journey so far, I'd like to start a little bit differently today, and I hope that's OK with you? So here goes, let me start out by asking you this question. Imagine that you are invited to a dinner party with people who don't know you, and a few minutes into the dinner the lady sitting next to you looks in your eyes, she smiles politely and asks, "So Marty, tell me what you do?" How do you respond to that? How do you explain what you do?

Marty

Niels

No, and it's funny Marty, because actually it's something that I struggle with myself. When people ask what do you do? I think it's so hard to the uninitiated to come up with an answer which both makes sense and is somewhat interesting.

Marty

It keeps the conversation going.

Niels

Marty

So I left Nomura after a whole nine months there, so that was the last real job I had, and started working for Brockham Securities, which was Michael's father's small broking house. Together we investigated a huge range of trading strategies and sort of distilled it down to some fundamental rules. I'm glossing over a lot of work. Our first portfolio was six commodity markets. I think we traded cocoa, coffee, sugar, aluminum, copper, and zinc, and we had 25,000 pounds of Adam family money and we built that first systematic portfolio. Along the way we met this chap, David Harding, who was a Cambridge graduate and I met him when he was working for Sabre Fund Management, and that story, I'm sure, David would tell it far better than I. David was the understudy to a man called Robin Edwards who was a chartist, a fund manager, but it was entirely based on chart patterns. So every day David, the sorcerers' apprentice, would take the books off of the shelf and open up the charts and add the latest tick data point. In would come the grand vizier and determine whether that was indeed a rising pennant or a double bottom or a head and shoulders, and determine what the day's trading would be.

The relevant thing here is really, genuinely, Michael, David, and I didn't know that there was an industry doing this in the States. So you talk about the Turtle experiment going on. Actually David probably read the paper, so he maybe knew about it, but Michael and I just didn't. We woke up, and we found that we were doing something where there was precedent, where there was an industry and in fact it was quite a burgeoning industry. I think that that's relevant because we weren't looking over our shoulders at how other people had done it or were doing it. Literally this was three nerds, and we approached the process of model development like a scientific experiment. We had the historical data; we had some models that we distilled down to some essential characteristics and then we said can we do this better? Can we add additional markets? Can we improve the models? Can we go faster? Can we go slower? Can we add more components to it? It was a scientific exercise. I think that that DNA, that approach really took off in the industry. I would contrast that, and I know it's a gross generalization and therefore not true, but I think that a lot of the roots of the US early CTA industry were in floor traders that encoded their rule sets. So you look at the Richard Dennis story which you referred to, or John Henry, these were smart folks, but they had a rule set that they were comfortable with, and in fact, we came really close to that with MINT.

Niels

I was going to say, this is a bit fascinating for me personally because, and I want to go into more of what happens then of course in your story and with Man, but if we just take it back a step. In my own career, I have roots, in a roundabout way that goes back to Sabre. And we were never able to computerize the original chart patterns. Even though they were mathematically defined, we couldn't do it. So I'm curious what it was in the patterns that you were trying to model, or were you just trying to come up with rules that had the same effect as a pattern, but not really where the computer needed to recognize the pattern itself?

Marty

I think more that, Niels. That we were really trying to construct the rules. Actually we did spend a lot of time trying to figure out a semantic language that you could articulate Robin’s arcane voodoo. One of Michael and my early ... and in fact I'll credit Michael with it because each of us brought something different to the AHL story, but Michael was an obsessive programmer. What stood us in good stead at Brockham and AHL, was that we didn't just sort of plough in and write a piece of code to test a trading model, oh no, Michael had to generalize the whole thing. So we had a sophisticated language. Probably very much a forerunner, a pioneer that would probably have looked something like an early Mat Lab. Where you could use an inline language to define objects of time series, and apply different trading models or parameters, or constraints on it and just very quickly test and develop trading strategy. You didn't actually need to be a C or a Java guru. As part of that language, I do recall us trying to define chartist rule sets. I don't recall that being particularly successful, and, as you say, it really turned into a case of finding the sort of filter sets that generated the common features. Really, a lot of the old trader maxims and chartist features, I think, can be simplified to a more basic set of rules.

Niels

Marty

The really early days, Niels, it was more of a breakout model. It was a breakout model, and it would scale into a position. So if you saw the repeat, it sort of patterned an end day high being supported multiple times. You would scale into a substantial position. Unwittingly, despite us all having scientific or physics backgrounds, this was uncharted territory, so all of the schoolboy errors that we all know and everyone that works for us has learned back in finance 101: all those things about over-optimization and degrees of freedom, we did it all. We optimized the living daylights out of these models in their back history. Actually, by the happy accident of this scaling in feature of the models, that sort of disempowered our ability to over optimize, so those were reasonably robust models. When we started dabbling in the moving average that you allude to, those are far more prone to over optimization because if you do the schoolboy error of trying to optimize what would have worked in every single market over time, you come up with a fantastic simulation, but reality doesn't turn out to be nearly so nice.

Niels

When was that, actually? Just before we go back to your story, when did you first move into the moving average type area?

Marty

Niels

Yeah, yeah, interesting. Anyway, I interrupted your fantastic journey, so by all means go back and tell us what happened when you also I guess got involved with Man relatively early on. I guess in particular, given the time - this is really early in a firm’s career that suddenly you get approached by a big company.

Marty

Yeah, I was going on to make a point because I was just drawing the contrast between the US managed futures industry, which was, in my gross generalization or unfair generalization, was based on a set of traders rules, versus the AHL happy accident of some scientists who just began distilling and evolving and in the broad sweep of history, improving what we did, but it wasn't always a linear improvement. What that turned into in the fullness of time was I think the difference between the approaches. People talk about the AHL DNA or diaspora, I won't say dominating, but being a major feature of how the industry has evolved. I think that was the sort of introduction of the scientific method. Going back a little bit, I think that a couple of pieces of the story... as AHL still in... it was really a couple of years before we got very close to Man and before they took a stake in us. The three of us were over enthusiastic and distractible kids. Through none of this story did we have the laser-like focus that we would all love to claim.

Niels

Marty

Niels

A couple of questions before we move further. What was it initially...sort of back in the early days that led you to feel so strongly that financial markets...because as you say you're a physicist by background. You're not really of a financial background, but what was it that convinced you to apply models to financial markets. That's not something that was that common at the time and I would imagine if someone studied physics, it's not the first thing that you would think of to say, "oh, I can use this for trading the financial and commodity markets." What was it that made you believe that this is really the best way to make an investment strategy that's going to last for years or decades to come?

Marty

Happy accident, Niels. I don't think ... there was not a realization or a determination... I don't know how David would answer that question, but certainly on Michael and my part that said, "Gosh, if we systemize this we're going to be rich." So first of all I have to credit Michael's father with the ""why don't you see if there's anything in this," and then just backing us with some money. You know what, Niels? There was something in it (laugh). Number two, this is a fun one, I recall that what Mike and I did to amuse ourselves was ... so we had this database of market data, much of which, this tells you how old I am, we actually typed in the back history by hand. The brokers would send us over those big green fan fold printouts of historic prices, and we literally had to type them in. We came up with this trading game, and it would randomly select to market and randomly multiply it by a random multiplier which could be a negative number, so it might invert the market and it would present you with a number of days of data, and then you had to trade. You had to make a decision: am I going to buy this or sell it, or hold, or various trading rules, and then you'd click the space bar and move forward a day and it was easy. So without the emotion and the information flow that makes markets so challenging for all of us humans - so challenging and so interesting. I think that there was this sort of realization that clarity... if you could just get rid of all of the noise, then there was a lot of information available in what the price had done that could inform what the right thing to do was. There wasn't a eureka moment, Niels, just sort of gradually accumulating comfort with this approach that we suddenly found, "Oh, this is a real business." All of our friends at Oxford and Cambridge - the talented folks had all gone off to become investment bankers and I remember that the three of us, it felt a little bit like revenge of the nerds because it wasn't something that physicists or scientists thought about doing in those days.

Niels

Absolutely. Just a question that pops up in my mind, when you left Man, and of course as you say Anthony Todd was very much part of this equation at this time, but just out of curiosity, why did you not just start like AHL 2.0 and keeping the team together do you think, what was the reason that you parted ways with David at the time, other than maybe he was a Cambridger rather than an Oxforder?

Marty

(laugh) David had different priorities for the business. I think he was focused on the research that he and his team were doing on the other side of London in that quant research, and I think that formed the genesis of Winton Capital Management, because I think he probably found the Man machinery a little bit smothering and he left and set up Winton. As I say, Michael was doing something else. We've remained good friends, and we see each other from time to time, but it actually was never a debate where the three of us were going to do AHL 2.0. I think we all felt that that was one chapter that had closed, and it was time to move on. Sitting down with Anthony, Eugene and Michael was a shareholder and a backer, but he wasn't an executive in the business in the early years just because he had his software company. It really was, how can we do this and get it to a broader audience. The MINT and Man and AHL within Man was predominantly a retail business, Niels. It was retail; it was structured product - if you can call a guaranteed fund a structured product. It was high fee, and it was extremely opaque. I think that the sales pitch of the early MINT funds in all those far-flung offices was, "Look at that, bottom left to top right, very clever, trust me." You can imagine that doesn't go down well with institutional investors today. So the whole premise of Aspect was this has to be right for a broader audience. So we set up a business that would be institutional in outlook, in setup, in fees, and built from there.

Niels

Absolutely. You certainly did. Before we jump on to the next area, I just wanted to ask you... running the research efforts and building Aspect along with your partners is obviously a very big part of your life, but what do you do, or what do you like doing when you're not working?

Marty

Niels

Fantastic. Now give me a short, sort of Aspect summary just to bring us up from the beginning to now and then I want to learn a little bit more about how you've ended up organizing these things and so on and so forth. Of course, Aspect in itself is a journey, and I would love to learn more and share more of this with the audience.

Marty

Niels

So you have more than 100 people working for you today. How have you set up the infrastructure so to speak? Now-a-days with technology we see some firms using a lot of outsource facilities or services, and some people tend to do everything in-house. I imagine you have a pretty big research team within the 100 plus people. What does it look like today running such a big organization?

Marty

From day one, Niels, we felt that to attract the kind of institutions that we wanted to attract we needed to do it thoroughly, so we didn't manage a dollar of client money until we had enough people that we could man a 24 hour-a-day trading operation until we had a disaster recovery facility. So that speaks much more to an approach of building yourself, which doesn't mean we're luddites. Back in the early days of AHL we'd even write our own back office software. That would be nuts these days. We outsource certainly some software where we can, but a lot of the operational infrastructure is all handled in-house. We have organized the research team, and again the evolution of the business and the evolution of the research team and the research process is as much a part of the journey as the evolution of the models themselves. That development of the team from, once-upon-a-time where everyone did everything (laugh). We've been through phases where we divided the team up and people were siloed by asset classes, and we thought that created conflicts and incoherence, and then you sort of alight on where we are today where we're divided into ... in fact it's about 120 people in the organization, 70 of us are focused on research, trading, and technology to support those activities, and there's focus. There's division of labor so you've got from the technical production team, to the software development team that supports both the production systems and the research systems; you've got a core research team; you've got a dedicated risk management and risk review team, and I want to come back and talk about that for a minute, and then we have a fantastic product management group who basically are sort of an interface between our clients and the research team, that sort of protect the research team to stay focused on the job at hand; and then our technology team also supports data and gives us the tools to keep looking in new areas.

Niels

Sure, we're definitely talking much more about risk management and so on and so forth. I wanted to ask you a slightly different question, and that is, what do you look for when you want to add new members to your team? What are the personal traits that a good researcher should have in order to have a chance to come and work for a firm like yours?

Marty

Yeah. It's a great question. I think that one of the lessons along the way is that the cultural piece is more important than you might think. I think that that has ... along the way we've hired a lot of people, and a lot of people have left and the core team that we have, and now they're really experienced. I think that the average tenure with Aspect of my core research team is over 7 years, some of them well over 10 years. I'd say two things in answer to your question. First of all we don't... there isn't a graduate intake. We aren't just hoovering up PhDs willy-nilly. I think we have certain targeted hires, where we may have determined that we need a skill set, so, for example, we needed some statistical muscle, and we went out and we hired someone who is just the most fantastic statistician I've certainly ever come across. Then we also ... we have similar expertise in signal processing and in other disciplines related to or not far removed from... you will have read the stories of Jim Simon's going out and hiring the speech recognition team. So we haven't done that, but it's the same kind of thought process, where you need specific skills. In terms of bringing in junior folks, I think it's... obviously these days the qualifications are certainly more than Michael, David, and I had in terms of PhDs and finance and programming skills. It's an attitude, and it's a cultural fit that are the most important features.

Niels

Yeah, it's sort of looking, I guess, at the three Cs: the character, the competence and the chemistry, when you want to put together a strong team. On that theme, how do you build a strong culture in an organization? Do you have any thoughts on that?

Marty

I think that's a great question, and I can say it, I can talk to it because I've made mistakes along the way. I think that the nature of what we all do in the asset management space lends itself to, how can I put this delicately... to individuals. There's the cult of the individual. Whether people start to believe their own hype or investors want to believe the hype. Couple that characteristic with the fact that once-upon-a-time... every business has to start somewhere, and if you're successful, you might believe your own success. Where I'm going is that it's hard for a business to make the transition from being very much top down, character lead, so I'm going to tell you lot what we're going to research today. Making the transition from that to a genuinely academic multi-disciplinary collegiate research effort - that's actually a harder transitions than it may sound, and people may overlook that.

As you see fledgling businesses set up, they may have some very smart folks at the top of the firm who put together a terrific trading system on day one, but as you and I know, Niels, that trading system is going to have to evolve. Whether it's going to decay in the first month of operation or in the first decade of operation, it is going to need to be improved on and experience would tell me that no individual is able to corner the market in genius, number one. So your ability to build a team and to trust and to delegate, trust and verify, to build that robust team is essential to creating longevity in the program. You can come up with a fantastic system, but I think the real tribute to AHL, to Winton, to Aspect, is these businesses have continued to evolve. It's more the research process that we've all subscribed to rather than the genius of the individual model or any component peace along the way.

Niels

Speaking on longevity, I have another sort of question relating a little bit to that before we move on to sort of more trading oriented parts. You've also had a very long partnership with key individuals, and I wonder what is the recipe of keeping a partnership going for such a long time. Like in a marriage it takes an effort to keep things alive and well. How have you guys been so successful at working together for decades without getting tired of doing it so to speak?

Marty

Well, so Michael, David, and I all happened into one another and we made it work. We were the three musketeers taking on the world, or taking on the Man group. Man were absolutely great partners, but just at that age we needed someone to focus our ire on. The point I'm making is that actually through the transition when we went our separate ways, and then David did his thing at Winton and we formed Aspect, I remember Anthony and Eugene and I and Michael just said look, we have a chance to build something great and let's do it with the people that we want to work with. So we haven't gotten it right every time. You said the three Cs. You sometimes take your eye off the ball and the chemistry isn't right, but by-and-large, Niels, I think it's about the people that you choose to work with. Then it's about commitment. I'm sure Anthony could have killed me at various times along the way and vice versa. You keep going, and it has been a tremendous experience.

Niels

Absolutely. I want to shift gears a little bit now. We've talked about the organization and what sort of underlies your success on that side, but I want to talk also now about the track record. My contention is that investors often look at a track record of a manager and they think oh, so this is what I am going to get in the future. Of course we know that, as you rightly said before, programs evolve and therefore a track record isn't necessarily meaningful in the current form and I would argue maybe that, to get a better feel, you should ask for a backtest of the current configuration of any system, but usually that is not easily available. Tell me about how you look at your own track record. Is there a certain stage where one should look at it where you feel that yes, this is how we did it at that time and here's some major upgrades, or some changes in philosophy, whatever it might be and therefore from this period on maybe that's a kind of a separate part of the track record, if you understand.

Marty

Yeah. Great question. I think if I'm sitting with a potential investor or an investor who may be struggling with recent performance compared to what they might have expected. I am, first of all, at pains to point out that the length of the track record, of Aspect and of AHL before that and of Brockham Securities before that, is more a testament to two things: one to the persistence of predominantly trend following models, the persistence and the ability to capture positive returns in multiple economic scenarios. That's sort of big take-away point number one. The big take-away point two is that it is what you say, it's an evolving process. It's a business. The analogy I use for our research team and the research process is (so maybe this would have been a better answer to the lady at that dinner table) is it's much akin to pharmaceutical research. Not that I've ever worked in pharmaceuticals, but the point there is that at one level you look at Sandoz or Novartis or something like that and you get a sense of how good that business is at developing new drugs and how good are they both medically, and how good are they at exploiting them commercially. But meanwhile in the bowels of the business, it's not just one drug. You don't just say how good... tell me about that one anti-cholesterol drug. It's a pipeline, a pipeline of products, so the drugs in and of themselves at any time are important and are generating the revenue when you take a snapshot of the business, but they continue to evolve. I'll end the analogy there because our track record has not bounced around across different spectrums of drugs. It is all predicated on the same fundamental beliefs, drivers of market behaviors, behavioral effects that is captured in the grand term of trend following or momentum trading. As you well know, with most of the managers that have survived as long as we have, those models have evolved enormously over time. It 's the old story of the grandfather...this is my grandfather's ax, but I've changed the head three times and the handle twice. That's what we've got.

Niels

Marty

By and large it is very much an incremental process and we make a virtue of that because you don't want... the last thing we want to do, especially with our focus on institutional investors and a high level of transparency. The last thing you want to do is surprise an investor. With the benefit of hindsight, I highlight two particular features about the evolution of the approach. First, in an odd way... the first, Niels, is the importance of risk management and portfolio construction. I think this is something that investors and maybe managers that haven't been doing it for that long may underestimate the importance of this in the process, and again I'm saying this because I did (laugh). After all of the shenanigans of looking at Chartism and distilling it down into to so fundamental tech models, you come up with a pretty robust diversified set of medium term trend following models, or we did anyway.

Niels

Since you mention that, what have you learned in these last few years in terms of trading and systematic models and how the environment plays such a key role in all of this?

Marty

Niels

I think the other thing that people should do if they want to sort of satisfy themselves about why these strategies shouldn't actually make money in the environment we've just been through is just look at the price range compression that we've seen. Just looking at what's the high and low been for the last rolling three, or six month basis, it is so clear what happens to the prices a few years back and when you do trade momentum and the price ranges compress as they have done, it's very easy to visually see that we shouldn't be making money. It is so difficult for investors to accept that. What I think is even more interesting is that now that we've seen a lot in the news recently and in the last years about trend following not working and all of these things that normally pops up, a lot of the longer term, maybe, trend following strategies they're all calling back to all-time highs again. People are not noticing it. They're just obviously focusing on when things are not working, but they're not really focusing on the fact that we are back to all-time highs and I think you guys are as well, and many people. So it's very interesting, and I completely agree with everything that you've said.

Marty

Niels, the thread that I forgot there was just it reconfirmed my belief that a systematic approach is ... I mean horses for courses - there are some great macro traders but I can tell you I'm glad I do what I do rather than be a macro trader because how many times do you think folks have said, "well yields can't go any lower than this."

Niels

Now, with all of that context that we've now put around this frame. Tell me about the Aspect Diversified program today. How does it look, and sort of visually what does it look like?

Marty

Niels

Can you explain that a bit?

Marty

Ending

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