Ewan Kirk is the CEO and co-founder of Cantab Capital Partners, a systematic hedge fund based in Cambridge, England. Kirk was previously partner-in-charge of Goldman Sachs’s quantitative strategies group in Europe. His group was responsible for all of Goldman Sachs’s quantitative technology across commodities, currencies, interest rates, credit, and equities.¹

Michael:

A guy with a PhD in mathematical physics going to Goldman Sachs . . . you weren’t the guy that was living and breathing trading when you got there, were you?

Ewan:

Not at all, no. When I turned up for my first interview with Goldman Sachs in 1992, I didn’t actually know who Goldman Sachs were. I thought they were a bank but apart from that I wasn’t entirely sure. So no, I didn’t live or breathe trading, I didn’t even live or breathe quantitative finance.

The Federal Reserve is not currently forecasting a recession.

Ben Bernanke 
January 10, 2008

Michael:

They were looking for a certain type of thinker, a certain type of thinking?

Ewan:

Yes, they were looking for somebody who had some sort of mathematical background, and computer programming was also important. I say this to just about everybody that we interview, that it’s sort of useless being a mathematician, being a statistician without being able to computer-program . . . it’s like being a ­novelist who can’t write. The way that you express your views or express your ideas is through programming computers. And so I was a reasonably good computer programmer. I had a background in quant and Goldman very kindly took a punt on me.

Michael:

I saw that your cofounder called programming, today’s literacy. You have to have it.

Ewan:

It’s today’s literacy. And that strand runs through a lot of my career, but also runs through what we do at Cantab trading programs. I myself have just spent the last two or three weeks programming up a piece of our infrastructure. There’s no rest for the wicked, as they say.

Michael:

It’s going to look to the reader that there’s this perfect physics, mathematical background, but you’re also a guy that allowed yourself to turn up at a black tie dinner wearing a kilt.

Ewan:

Yes, that’s true. [laughter]

Michael:

You’re not a cavalier guy. Obviously, you’re very grounded, you think in terms of risk, but what was your thinking there? What is your thought process that you allow yourself to stand out like that?

Ewan:

The truth is, of course, that for somebody who like myself originally came from Scotland, the traditional black tie dress is a kilt and all of the attendant bits and pieces with that. It’s not like I turned up in a clown costume.

Michael:

I hope you did not infer that’s what I was saying!

A real decision is measured by the fact that you’ve taken a new action. If there’s no action, you haven’t truly decided.

Tony Robbins

Ewan:

No, no I’m smiling as I’m saying this. I do think that one thing that Goldman Sachs was very good at doing, and presumably still is, is it’s tolerant to some degree of idiosyncrasy. ­Certainly in the early days Goldman was a partnership with maybe 150 partners running their small businesses. That made it very much a meritocracy, very much a “what have you done for me today” kind of thing. Me turning up in a kilt is not the strangest thing that I’ve seen, but it’s a place where, really much more so than other banks, certainly in the ’90s, it is a place 
where all Goldman was interested in—were you good at your job. Within certain limits, obviously turning up in a clown costume at a client meeting would probably be a very quick way of getting fired.

Michael:

I took it as you saying, “I’m going to march to some music that is standard but I’m going to think outside the box. I’m not going to just be the guy that’s clocking in.”

Ewan:

I probably couldn’t violently disagree with that view. I think yes, there’s certainly some of that in me, to not just be the guy. Although, to put this in context . . . to take that as an example, Goldman Sachs is a very serious, very successful U.S. corporate and there’s a limit to how outside the box you can think in a bank, and quite rightly too. Banks are responsible for a lot of risk for their customers, they have a fiduciary duty in lots of cases. Yes, you can be a little bit idiosyncratic sometimes, but at the end of the day it is a big U.S. corporate.

In today’s world if you worry about what anybody thinks about your decisions, you’re going to drive yourself to a problem. A big problem. Alcohol, or something. You just gotta put your nose to the grindstone and believe in yourself, believe you’re making the right call and just go.²

Jon Gruden

Michael:

When I look at the success of the London CTAs [trend followers], the London Quants, many trend following backgrounds, why did the switch happen? Why did London become the spot? For example, so many of the long-standing, early, pioneer trend following CTAs were from the U.S. What was the switch flip?

Ewan:

That’s a good question. It’s not one I immediately have an answer for but I can speculate. If you think about the very early trend following, the history of the industry is, the very early trend following, the Turtles. We’re talking mid-80s there, maybe early ’90s. The kickoff for the London, or maybe better to call it the European scene, probably happened in the mid to late ’90s with AHL, obviously the granddaddy of us all. And then Winton, Blue Trend, and Aspect and ourselves, and a whole plethora of really great firms in Europe.

Partly the reason why we maybe managed to become more successful or grow was more the scientific approach to investment and statistics. I look back at some of these things that I see in the old tattered books about average true range and breakouts and it seems like the dark ages. We are thinking in a much more statistical sense, much more scientific. And it’s not just enough that it happens to work.

Maybe we can thank David Harding and the rest of the team at AHL for building that into the consciousness and then it just takes off. The question there, “Why didn’t the CTAs in the U.S. follow that lead?” I clearly believe that [there should be] a more scientific approach to investing, a rigorous statistical approach to it, I clearly believe that that’s better than just a rule that happens to have worked in the past. It’s not clear to me why that would then not be transplanted back.

I remember, even though we started in 2006, 2007, I do remember people asking me . . . again particularly in the States . . . why do you weight your positions by risk? Why don’t you just take a constant lot quantity? One lot of this or ten lots of this and ten lots of that and ten lots of the next thing? That’s just madness in a world where you have a contract like the wheat contract which is maybe, I don’t know, $20,000 and the nickel contract which is $250,000. It’s just an insane way of doing it.

But it was the tradition and our industry is quite conservative. There’s a small subset of investors who want the new thing . . . believe maybe that there’s some fabulous technique out there that’s just going to predict what the S&P’s going to be tomorrow. But there are also people who want it to be the way it was and anything that steps outside that is maybe a little bit different.

You are not special. You are not a beautiful or unique snowflake. You’re the same decaying organic matter as everything else.

Chuck Palahniuk 
Fight Club

Michael:

You’re talking to clients and you have to tell the new 
client, or this could be a very experienced client perhaps not experienced with your strategy yet, and you ultimately have to bring up the conversation of, “Look, losses are statistically inevitable, you can’t get around that fact.” There’s still a significant number 
of people in the population, whether they’re very astute about investing or not so astute—they still don’t want to imagine losses as part of the game.

Ewan:

Yes, people are desperate to invest in something which never loses money and that is of course why Bernard Madoff existed. There’s a great phrase by John Maynard Keynes where he said, “In the field filled with fraud and deception demand creates his own supply.” Everyone is desperate to invest in something that doesn’t lose money. I’d like to invest in things that don’t lose money. I’d like to come up with a strategy that never loses money. Of course we all want that.

But the reality of almost all investing: If you’re really good, really lucky, you’ve got a very long track record, maybe 20, 30 years, and you’ve never changed your strategy over that period, which of course none of these things are really true for anybody—then maybe the best you can look for is a Sharpe ratio of .8, .9, maybe 1. I know there are some more liquid, say, stat arb strategies, which can outperform that for a long period of time, and then of course August 2007 happens. But broadly, a good investment strategy, an outstanding investment strategy is something which over a long period of time has a Sharpe ratio of 1. Investors should really want that. So a 20 percent volatility with an average 20 percent return, that would be great. But a 20 percent volatility every two years is going to have a drawdown of 15 percent statistically. Every four years it’s going to have a drawdown of 20 percent.

My approach works not by making valid predictions but by allowing me to correct false ones.

George Soros

This is just what happens. Even if the system truly has that return profile, it’s going to experience those kinds of drawdowns and it’s going to experience losses. I have a little spreadsheet that I sometimes show to clients when I’m discussing this which . . . broadly, we don’t really use spreadsheets but it’s a nice little tool . . . which simulates five years of returns, daily returns, from something which is a 20 percent return, 20 percent volatility process. Effectively a Monte Carlo simulation if you want to call it that.

And every time you press F9 on this spreadsheet it draws another graph of another realization of this random but ­positive process. You don’t have to press F9 very often before you get a history which loses money in a straight line for five years, which has a 40 percent drawdown. Remember, this is something which is guaranteed to make 20 percent per annum over a long enough period.

The expectation of losses is something that everyone should build into their investment process at all times and it’s something that investors do. The majority of our investors are institutions. They’re pension funds, they’re insurance companies, they’re sovereign wealth funds, they’re endowments. To be very fair to these investors, they are really quite sophisticated and they understand that. Sometimes when you’re speaking to maybe high net worth individuals or smaller family offices, the desire there to protect capital is much stronger. You have to be extremely clear about the fact there are things that will happen in the future which will be unpleasant.

The other thing you have to do is explain to investors when you’re making money that it probably won’t last.

Speculative bubbles do not end like a short story, novel, or play. There is no final denouement that brings all the strands of a narrative into an impressive final conclusion. In the real world, we never know when the story is over.

Robert Shiller

Michael:

Do you see the demand for that discretionary macro trader or hedge fund that says, “Trust me, I have the experience. I can call the direction. I can position these multiple futures contracts across all these different markets. Just trust my discretion.” Do you see the demand for that waning?

Ewan:

Obviously, by the time somebody’s sitting on the other side of a table from me, they’re probably not going to be asking me that question and I am of course very clear about the fact, and par­ticularly when people say, “Do you take risk off, do you put it on? 
How about taking off your bond position or adding more this.” I’m very clear about the fact I cannot see into the future. I’m not psychic, so therefore I don’t have any skill in that. My skills lie elsewhere.

Maybe nobody has skills like that, maybe it is just impossible. I could certainly argue both sides of that. The demand for dis­cretionary trading probably comes from the reactive demand. It’s extremely hard to write a model, well it’s impossible to write a model, that can react to every last move in the market or react to a piece of information that’s coming in.

September 11 is probably a very good example of a piece of information that arrived, the world changed at two minutes past nine and systematic models knew nothing about it, whereas discretionary traders clearly did. In those kind of events it’s quite possible that discretionary traders will outperform, and I can understand why people have that demand for it.

But it is an extremely difficult job to be a good macro trader. We all know of those people who have great reputations in doing that. It’s maybe only a handful of people.

Of course, the interesting thing about macro trading is that everyone wants to be a macro trader. It’s really interesting when you hear stock pickers talk discretionary equity long short, people-talk. Very often what they’re talking about is macro things. We think the market’s going up, we think it’s going down, we’re doing this and then therefore we’re going to buy these stocks. And quite often macro decisions are wrapped up in security analysis which they probably shouldn’t be.

I really think trading [on a] macro discretionary basis is one of the world’s hardest jobs and it’s possible the people who are successful at it may just be the lucky pennies, I don’t know. I don’t have hugely strong views on this but it is a very hard job.

Michael:

When the macro discretionary guys hear that everything you do is systematic from strategy selection, asset allocation, portfolio construction, position sizing, execution, and risk control, that’s got to cause some people to go, “What the blank?” There’s got to be that aha! moment of, “This is an approach that’s different.”

Ewan:

I don’t think we are exceptional. Obviously whilst I know my peers well socially, I don’t know what they do and how they sell themselves. But I would be surprised if any of the large ­European CTAs are talking about how they intervene in what they do [to make discretionary] decisions. There is that little bit from people who say, “We have a model but we occasionally intervene.” My opinion, “That’s not systematic trading.”

In systematic trading, and I’ve used this phrasing before, it’s almost like being pregnant—you either are or you aren’t. You can’t just be a little bit systematic. I often say to people who are maybe pitching me with systems that are a model that they then put a discretionary label on, “Why don’t you just run two books. Run the model in one book and run your discretionary overlay as another book and then just see which one makes money.”

This is a way for people to hide really quite complex decisions. Remember what we’re all trying to do is we’re trying to say, “What’s more likely to go up tomorrow and what’s more likely to go down tomorrow?” And that’s the decision. Now what we have, and many other people like us, is we have lots of complex, or sometimes simple, models which have been tested statistically over many, many years, and then they’re weighted using very sophisticated weighting algorithms and costs control measures and all of those other things. Literally millions of lines of code running. And all we’re trying to do is forecast whether or not something’s going to go up or down tomorrow.

Very often people intervene in their models by saying things like, 
“Vol is going to come off tomorrow,” or “Correlations are going to go up,” or “I don’t think this model’s going to work as well tomorrow.” That’s a very complex statement. The amount of analysis you would have to do to say, for example, a trend following model isn’t working very well, is unlikely to work tomorrow . . . the idea that you can do that for something as complex as a model which is running on 120 different assets, with risk weighting and cost control measures on top of it, seems to me to be unlikely.

Michael:

Why don’t you talk about part of your process under the hood? In the sense that you like the idea of proving a strategy is broken rather than it’s right.

Ewan:

Yes, I don’t think I’m the first person to come up with that, in that effectively that is the scientific method which has been working pretty well for humans since the Greeks came up with it. Science is about proving things wrong, it’s not about proving things right. What you’re trying to do is break your strategy. You can never really prove that a strategy works or doesn’t work. Finance, despite pundits and newspapers and people in the television and maybe even people on podcasts, filling what they say with certainty, “This is going to happen. This is the best way of doing things. Our systems are better than somebody else’s systems. Our stock portfolio is better than somebody else. I know this, I know that.” Finance is full of all of that but in fact finance is dominated by randomness. Randomness is everything, and so because randomness is everything you need to be uncertain. You need to have a lack of conviction and dogma in certain things because you want to be able to prove that things are wrong.

Religion is a culture of faith; science is a culture of doubt.

Richard Feynman

When we come up with a new strategy or a new idea or a new trading system, what we’re trying to do is, at least when we’re simulating it and running it through all the systems, what we’re trying to do is find out what’s wrong with it. And then if you get what is 
literally months of testing and retesting and rethinking about it, and thinking about things, different environments and so on—if it gets through months of that, then maybe it’s going to work in the future.

These are all very weak, uncertain statements, but to a great extent our philosophy of what we do is around that uncertainty and lack of conviction. There are certain things I’ve got conviction about. 
Obviously, I’ve got conviction about the importance of technology. I’ve got conviction about the importance of risk weighting or ­coherent portfolio design. All of those things I’ve got a lot of conviction about, but I don’t have conviction about any particular technique. You just do what you think is best and what you think will be persistent.

Michael:

It seems like until the last handful of years in the fund management arena, so many people desire certainty and thus it’s refreshing to hear, “I don’t know. I’m doing the best that I can, but I don’t know. And I really don’t think anyone else knows.”

Ewan:

What we are trying to do as scientists in finance is a little bit like sort of dimly being able to forecast what the weather is going to be like tomorrow. It’s like meteorology in that sense. It’s full of uncertainty and technology helps and the models aren’t perfect and even the biggest computers in the world don’t forecast the weather very well five days forward, but meteorologists are trying hard to improve that both in the technology side and better theories about atmospheric circulation. And, they’re maybe not too bad at forecasting the weather tomorrow in certain places, probably not in the U.K. because it’s so rainy.

Apparently people don’t like the truth, but I do like it; I like it because it upsets a lot of people. If you show them enough times that their arguments are bullshit, then maybe just once, one of them will say, ‘Oh! Wait a minute—I was wrong.’ I live for that happening. Rare, I assure you.

Lemmy 
Motörhead

In the past, a lot of investment has really been people looking at the sky and saying, “Look at that cloud, it looks like a dog.” That probably captures the realism of the world. The other way of thinking about this is very often, and rightly, when something happens, either when you make money or lose money, or when a model does something or whatever it might be, there’s always the question that everyone asks, whether or not it’s internally people at Cantab or our investors or journalists, “Why did this happen?”

It’s a great question, “Why did this happen?” What we try and do is approach the problem from the perspective of the reason why this happened was chance. Now prove that it wasn’t chance. Very often that’s quite hard. You have a bad month or you have a great month, people say, “What happened?” Can we prove that it’s any different from chance? Quite often the answer to that question is no. It’s just a different mindset.

Obviously, you have to approach problems in lots of different ways, but approaching a problem from the mindset of, “This might just be a result of random noise, let’s see if we can prove that it isn’t,” is intellectually satisfying if nothing else. It’s quite a powerful technique.

Michael:

I saw this great article about you, featured in The New York Times, and I went through some comments, and I noticed some were highly negative. The thrust of the comments were that you don’t bring value to the economy. And I thought to myself, because I know something about what you do and what your peers do, those comments misunderstand. Many of your investors, even if they’re institutional investors, are representing the small guy. It’s the small guy’s retirement money that often makes it into the big institutional account.

Maybe people don’t see that, yes, you might not be accepting Ma and Pa’s retail account, that’s not your position, but I think someone misses the point and misses the boat when they make that criticism. What’s your feeling on that?

Ewan:

This is a hard question to answer. The question is, “Are we doing something that is socially useful? Are we doing a good thing for the economy?” Once you start going down that route, What is useful to the economy or useful to society?” The world only needs one car manufacturer, it doesn’t need hundreds of 
car manufacturers, it doesn’t need hundreds of models. Every car manufacturer is kind of not doing something useful for the economy.

Nobody really needs an expensive meal at an expensive restaurant, so expensive meals and expensive restaurants aren’t really doing anything useful to the economy. Nobody needs podcasts, we can live without them. Once you get into that, then you’re getting into some dangerous water.

One of the things that I love to do is travel around the world and look at archaeological sites. Because archaeology gives us an opportunity to study past civilizations, and see where they succeeded and where they failed. Use science to work backwards and say, “Well, really, what were they thinking?”

Nathan Myhrvold

We are, I believe, over time are providing something which is valuable to our investors. We are doing that as well as we can. We’re constantly trying to add little incremental improvements that make the returns better. We won’t make money every month and we won’t make money every year and sometimes we lose money and sometimes we make money. But we are doing the best we can to produce positive returns for investors.

And our investors are, as you say, a wide variety of people. They’re pension funds, it’s mum and dad, as we say here in the U.K., who are investing in this, and although this is not quite the same as finding a cure for cancer and it’s certainly not the same as landing a probe on a comet, which are fantastic things to do. This is what we do. We probably at the margin make the returns of our investors’ portfolios better in some way, either higher or lower risk or less correlated and so on.

Where I think there’s much more of a problem is with people doing something not socially useful like when relatively simple strategies are dressed up as something very complex. People effectively just being an index tracker doing long-only things, like just tracking the S&P index but charging 2 and 20 for it. That’s a very bad thing to do. At least I believe that what we do is something that is intellectually rigorous. It’s probably a good thing.

The other thing to remember of course is that trend following, systematic trading, the money comes from somewhere. If we make money for investors, somebody loses it.

Michael:

If you lose it, someone’s gaining it.

Ewan:

Someone’s gaining it. We would believe and hope that over time we will make money more often than lose. We will over time get positive returns, but it does mean that somebody is losing. It’s a very hard question to answer.

Michael:

There’s a game out there that everybody can play, everybody can pony up to the table, develop a strategy, and it is the ­ultimate game where everyone can try. I look at it like, “If you don’t like it, go try.”

Ultimately, the libertarian in me says we’ve got a lot of better things to do on this planet than draw those types of conclusions, and perhaps, if you look closely you can see those positive things. But of course we all know that some people will never see all positive things. You can’t convince everybody.

Financial crises are an unfortunate but necessary consequence of modern capitalism.

Andrew Lo

Ewan:

That’s probably true. I’m obviously always weary about talking about politics in any public forum because it’s not my job to do that. But I do believe that we do a relatively good thing. If nothing else, I provide employment for 50 people in ­Cambridge, which is the small-business side of what we do as well. It’s important to remember that this little community we have is an employer and it pays people money and does all these things as well.

I do believe that we run good small businesses and that is a good thing. One of the things that I’m very pleased about is that in 2006, I reckon I sat in a small office with two computers and a server that gave us electric shocks every time we touched it, and from that we have built a business. It’s a small business and it’s a business like any small business that can go through bad times and could potentially go bust. And all the efforts associated with running small, medium-sized enterprises means we’ve managed to survive for eight or nine years now and I’m really pleased about that. If I’m proud of anything, I’m proud of that.

Michael:

That’s inspirational. I’d love for you to expand on the idea that you like to ask clients what they like. Not necessarily force things on clients. If you could expand on that—because clearly some clients are not going to have the technical market know-how that you do—so there’s going to be some desire for guidance. Could you expand on seeking client feedback?

Many areas of modern life rely on scientific research and are guided by well-defined rules that are applied systematically. When flying aeroplanes or developing new medicines we rely on physics, maths, statistics and computer science. Taking these disciplines and applying them to investment research is a natural step.

Ewan Kirk

Ewan:

That’s maybe taking it a little bit out of context. It is ­important to understand what your client’s utility function is, to use that scientific phrase. What are they looking for? What do they expect from an investment? That sort of informs the way that you explain things to them. As you say, generally, although all of our clients are very knowledgeable and sophisticated in lots of different areas, and of course they have to cover all types of investments and all types of asset allocation, they’re almost certainly less knowledgeable than us in the very area that we do, systematic macro trading or systematic micro trading.

The point here is that you do have to understand your client’s ­drivers. What is it they are looking for in their portfolio? What do they expect? It isn’t a question of us sort of sitting on one side of the table saying, “What do you want? We’ve got it. You just ask, we’ll give you that.” But understanding what drives the decision-making process, who their stake holders are. [For example], we have two products. We have our original quantitative fund which is higher volatility, it’s 20 percent, it’s high octane, it’s 2/20 fee, so it’s very much in that mold of high-octane very diversified systematic macro and micro trading.

We also have another product which is lower volatility. It’s 10 percent volatility. It’s much more scalable. It’s got more basic trend and more basic value strategies in there, and it’s available to investors at a half and ten. Now, understanding your investor means that you can understand what their internal desires are: What do they need? Maybe they want low cost, very functional, but they want a low-cost system where it’s lower volatility and the headline numbers are smaller.

We all know that investing in a 20 percent volatility product is too risky, then all you have to do is invest half your money in the 
20 percent volatility product and keep half of it in your pocket, and you’ve got a 10 percent volatility investment. But somehow that doesn’t feel the same as a 10 percent volatility product, for reasons that I really don’t get. The pure mathematician in me says that’s nuts. But nonetheless it is true and I’m human, too, obviously, and I feel that.

It is important to understand your investor, who their stake holders are, and by understanding that and communicating with ­investors at the right level. None of our investors need to know or cares about the deep statistical details which might be embedded in some non-linear Bayesian-regression portfolio algorithm. That sounds great but they kind of don’t care and they shouldn’t care about that.

But they should care about things like culture, technology, people, the search processes, and these are all things that we can explain and want to explain in great detail. And if you can understand what your investor needs and wants, then maybe you can explain those things better.

I always feel that I’m not really in that camp of—and our industry is quite bad at this—“If I told you about my models I’d have to shoot you.” That’s quite common, that sort of, “I have to be massively secret, can’t tell you about it,” thing. That’s wrong. We as an industry are managing money for people, and it’s their money, and they have the right to know, and we have the obligation to tell them what it is we’re doing with it.

Michael:

That probably has been one of the reasons that you guys have gone from zero to significant in fairly short order, in a very competitive space.

Ewan:

Yes, well, we have. I’ll refer you to my previous [explanation] about randomness. Yes, some of that is of course luck. We had a good run; we didn’t have such a good year last year, we’re having a good year this year. Some of this is randomness, but . . . 
apart from being open and transparent and supporting investors and all these things that you have to be, the other strand that runs through everything we do is that sort of aggregation of marginal improvements. Little, small, marginal improvements that really in and of themselves maybe just don’t make much of a difference.

Let’s say, we work out some way of saving ourselves half a basis point in costs a day. That doesn’t seem like very much, half a basis point, that’s a tiny amount of money, but it adds up to nearly a percent and a half over the course of a year. That’s great. Fine, we’ll have that. And lots of those little marginal improvements are probably what distinguishes good funds from less good funds.

One of the things you have to remember in life is that not everybody’s going to think that you’re great. I’m quite pragmatic about these things. There’s valid criticisms about systematic trading, there’s valid criticisms about the finance industry. You’ve got to take those criticisms on board, understand why they’ve happened. There’s been a lot of, as we know, lots of stuff in the press, bad things have happened in finance.

People are right to criticize. I’m not going to get annoyed about it because maybe some of the criticisms aren’t bad. We certainly don’t have any monopoly on the truth.

We all fool ourselves from time to time in order to keep our thoughts and beliefs consistent with what we have already done or decided.

Robert B. Cialdini

Michael:

As somebody who has watched this particular space 
for a long time and going back many, many decades, there is something noble about the systematic guys that have done this for a long time. There is something generally consistent that you can hang onto in this systematic space. Like you said, though, maybe things break and it all falls apart at some point in time, but, knock on wood for several decades or more, it’s done pretty well.

Ewan:

I think people in the systematic space, we try harder, to use that old Avis ad, we do try. I know just about everyone in the European space. I know that everyone is completely focused on just doing the best thing they can, and that’s great. There’s very few charlatans or people that are just knocking together any old ­rubbish just so they can raise some assets. People try really hard and sometimes we fail, but on average the industry succeeds.

Michael:

That’s how it goes though, right? It’s not necessarily consistency, it can just come, boom, and you all of a sudden have a September 2014 and everyone goes, “Where did that come from?” Hold on, that’s trend following.

Ewan:

That’s the way it works. That’s an interesting thing for people. When people say, “Trend following hasn’t worked for three years.” I explain, if you take a simple trend following model and run it across 100 assets, when trend following’s working really well it’s maybe working on 60 assets and not working on 40, and when it’s not working it’s working on 45 assets and not working on 55 assets.

There’s never really been a period in history where trend following hasn’t worked on something, it just hasn’t worked enough. And . . . I’ve got to be careful always to say, “We’re not a trend follower alone, we do lots of other stuff: trends in bonds, trends in ags, trends in the yen, trends in energy.” This is all working out really well and we’re in one of those golden periods where trends are working on a lot of different things.

Where all think alike, no one thinks very much.

Walter Lippmann

That too won’t last. Over time there’ll be ups and downs, but over a long enough period of time, trend following, and more generally systematic macro trading, has done incredibly well and presumably—and this is the little scientist in uncertainty in me coming out—and presumably with a reasonable degree of probability it will continue to work in the future.

Michael:

If anyone out there looks at a systematic quant track record and it’s all black ink, then you’ve got trouble.

Ewan:

I refer you to my previous answer about Bernard Madoff.