Speaker 1: Welcome to Merrin Talks Money, the podcast in which people
Speaker 1: who know the markets explain the market. I am Maren
Speaker 1: summrset Web and this week I am speaking with Simon Judes,
Speaker 1: who's the CIO of Winton.
Speaker 2: Now.
Speaker 1: Winton is a quantitrative investment management firm, headquarters in London,
Speaker 1: but with officers around the world. The firm managers around
Speaker 1: sixteen billion dollars worth of cash, mainly for institutional clients,
Speaker 1: but I think increasingly with an idea of having ordinary
Speaker 1: investors and wealth managers by their products as well. So
Speaker 1: we will talk about that along the way. Simon, Welcome
Speaker 1: to Merrin Talks Money.
Speaker 3: Thank you very much for having me.
Speaker 1: Right, let's start by trying to explain what on earth
Speaker 1: it is that you do.
Speaker 2: We hear a lot about quantitive investing.
Speaker 1: We hear about CTA, we all those model systems, et cetera,
Speaker 1: et cetera.
Speaker 2: What is it that you actually do.
Speaker 3: Well, let me talk about quant investing in a more
Speaker 3: general term, and then I'll come on to CTAs in particular,
Speaker 3: which is one type of quant investing. So the way
Speaker 3: to think about it is imagine you start off with
Speaker 3: a more traditional style of investment. Where perhaps you have
Speaker 3: analysts thinking about a company and whether they should buy
Speaker 3: shares in the company, whether they think the company is
Speaker 3: likely to do well. That would be something that a
Speaker 3: lot of effort goes into a lot of discussion, and
Speaker 3: if you want to make that decision not about one company,
Speaker 3: but about ten companies, you need to have ten times
Speaker 3: as much discussion, and that leads you to scale those
Speaker 3: organizations quite heavily and to focus on having a small
Speaker 3: number of positions that you have a high conviction in.
Speaker 3: That's how traditional investment works, and quantum investment is based
Speaker 3: on a different idea where you say, well, maybe we
Speaker 3: don't have to have that high conviction in every single
Speaker 3: investment if we can have a larger number of them.
Speaker 3: So it's a little bit more akin to how an
Speaker 3: insurance company might treat its products. It doesn't have to
Speaker 3: make money on every single policy itsels as long as
Speaker 3: it arranges things so that on average it does. So
Speaker 3: the idea is, well, what if instead of doing all
Speaker 3: this huge amount of analysis on each company that you
Speaker 3: decide to buy a share in, you instead come up
Speaker 3: with a rule that is perhaps much simpler. And it's
Speaker 3: something that's so simple that you can automate. You can
Speaker 3: get a computer to do it. So I suppose that
Speaker 3: you look at some valuation metrics or something else about
Speaker 3: how the company's performed recently, and you decide based on
Speaker 3: that you will have a position of a certain size
Speaker 3: in the company. And that's something that you can get
Speaker 3: a computer to do for you, and you can do
Speaker 3: that with a much much larger portfolio. Now that might
Speaker 3: sound a little bit speculative, like how could you know
Speaker 3: that following a rule like that would be a good
Speaker 3: decision for you in the long run. And the reason
Speaker 3: that you can get confidence in that is because you
Speaker 3: can do something that you can't do in the more
Speaker 3: traditional style of investment. What you can do is a
Speaker 3: back test where you take that rule and you test
Speaker 3: how it would have performed over a much longer time horizon.
Speaker 3: And that is what gives you confidence in quant investing
Speaker 3: that this is going to be a good rule for
Speaker 3: you to follow. And if you think about what that
Speaker 3: then looks like, it means that when you are allocating
Speaker 3: money as a quant investor, you're not allocating or you're
Speaker 3: not really thinking directly about each individual investment. You're thinking
Speaker 3: about allocating to these rules, these ideas or algorithms that
Speaker 3: are themselves going to decide which companies they buy and
Speaker 3: which companies they sell. So that's the general idea of
Speaker 3: quant investing. It's the difference from more traditional styles of investment,
Speaker 3: and that's how you can get confidence by doing these
Speaker 3: historical studies which show you how the rule would have performed.
Speaker 1: How does that work with a long term idea that
Speaker 1: every time an anomaly or a gap in the market
Speaker 1: like that has found, it's almost immediately traded away.
Speaker 3: That's a great question. You definitely see with many types
Speaker 3: of rules like that that they work for a while,
Speaker 3: and then you can even see in this back test
Speaker 3: that they gradually start to work less and less well.
Speaker 3: And that almost certainly is always because many more people
Speaker 3: are doing it. So what can you do about that? Well,
Speaker 3: the first thing you can do is that there are
Speaker 3: some ideas which don't have that fall off in a way.
Speaker 3: Perhaps they're not based on discovering a simple trick or arbitrage,
Speaker 3: which once somebody else has discovered it, it will just
Speaker 3: stop working. They might be based on more general behavioral
Speaker 3: biases that people have, and that's really where CTAs and
Speaker 3: momentum and trendfall going to sit in this way of
Speaker 3: thinking about it.
Speaker 1: So there's two types of rules that we might follow here.
Speaker 1: One would be purely in numerical statistical, and the other
Speaker 1: might be behavioral.
Speaker 3: Well, even the behavioral ones we would still measure through data.
Speaker 3: They would still be measured through the way that either
Speaker 3: prices or other sort of days that we might use
Speaker 3: are behaving. So they're still encoded as systematic algorithms that
Speaker 3: take in data, transform it in some or other way,
Speaker 3: and then come up with a rule for how you trade.
Speaker 3: So I think those two things might end up being
Speaker 3: the same. But the second way I was going to
Speaker 3: say that you can combat that people call it alpha decay,
Speaker 3: where the idea stops working, is by doing a lot
Speaker 3: of research and continuing to find new ideas. And that's
Speaker 3: a big component of our activity as well.
Speaker 2: Okay, so there are still new ideas to.
Speaker 3: Find, absolutely, because there's new data all the time as well.
Speaker 2: Can you give us an example of a new rule.
Speaker 3: Well, that's why you might be infringing.
Speaker 1: In Okay, you don't want to do that because it's
Speaker 1: proprietary stuff. And this is one of the problems I
Speaker 1: think the retail investors often have with this type of
Speaker 1: fund is that they're told the theory, but it's not
Speaker 1: possible for them to be told the practicalities because that's
Speaker 1: your model, your proprietary data.
Speaker 2: So why don't we go back a bit.
Speaker 1: Maybe you can give us an example of a rule
Speaker 1: that you use that once worked and doesn't anymore. That way,
Speaker 1: we're not infringing on your corporate knowledge.
Speaker 3: Well, I think we can do better on that because
Speaker 3: in the CTA space actually, which is a particular type
Speaker 3: of quant investment, the basic idea of how we come
Speaker 3: up with the trades is quite well known and it's
Speaker 3: in something we can talk about very openly. So CTAs
Speaker 3: are a particular subset of quant hedge funds which apply
Speaker 3: that same philosophy that I was talking about earlier to
Speaker 3: macro markets, primarily through trading futures, so that they're trading equities,
Speaker 3: that they're trading bonds, they're trading currencies and their training commodities,
Speaker 3: and predominantly the way they're doing that is by looking
Speaker 3: at recent price momentum. So the things that have gone
Speaker 3: up over some recent period, you have a long position,
Speaker 3: and if they've gone down, then you have a short position,
Speaker 3: and that is the algorithm. It really is looking mainly
Speaker 3: at recent price behavior.
Speaker 1: Okay, so you've got a fund that trays in futures
Speaker 1: in all the asset classes based on the direction prices
Speaker 1: are already going, with the idea that you can spot
Speaker 1: where the turn will come.
Speaker 3: No, we can't really spot when the that's very hard.
Speaker 3: It's based on the idea that if the price has
Speaker 3: been going in that direction, that's more likely than not
Speaker 3: to continue going in that direction.
Speaker 1: Okay, so you've got to have an awful lot of
Speaker 1: positions for that general rule to work.
Speaker 3: Yes, you need, you know, more than one hundred really
Speaker 3: to get the benefit of the diversification, because, like I said,
Speaker 3: in general, with quantuvesting, you don't have very much conviction
Speaker 3: in any one position. So I'm slightly suspecting at some
Speaker 3: point you'll ask me what gold is going to do next?
Speaker 3: For example, Yeah, that's coming. The answer is, I don't know.
Speaker 3: When the question comes, I don't know, but we believe
Speaker 3: that there's a greater than fifty percent chance that it
Speaker 3: will continue to go up, which is not saying very much,
Speaker 3: but as part of a large portfolio, it's still a
Speaker 3: very valuable thing to do.
Speaker 1: Okay, before we move into a CTR. What does CT
Speaker 1: stand for? By the way it.
Speaker 3: Sounds for Commodity Trading advisor, which is it's a regulatory
Speaker 3: term from the seventies in the US, so it doesn't
Speaker 3: have very much.
Speaker 1: It doesn't really the words don't really mean anything anymore.
Speaker 1: The acronym means something, but the words no longer mean anything.
Speaker 3: Correct.
Speaker 2: Okay, let's go back to the.
Speaker 1: Pre CTA conversation about the different rules and evaluations. I
Speaker 1: am actually really really keen to nail you down a
Speaker 1: little bit on the kind of thing that you mean
Speaker 1: when we talk about all these different rules, all these
Speaker 1: different diversification, different models, etc. For the purpose of the
Speaker 1: retail investor who is not used to this kind of
Speaker 1: fund and is used to more traditional equity funds where
Speaker 1: we're talking about or we're doing growth and this is
Speaker 1: what growth means, and we're doing value and there's more
Speaker 1: value means, and we're doing growth through a reasonaal price
Speaker 1: and that's what this means. And we're doing tech and
Speaker 1: that's but this means we're doing mining. That's what this means, etcetera.
Speaker 1: These this stuff is easy to get a handle on,
Speaker 1: but what you do is not. So a neat little
Speaker 1: example of one type of strategies, less models, less valuation metric, etc.
Speaker 1: That works or has worked for you would be super handy.
Speaker 3: Absolutely. I think value is a good one to focus on.
Speaker 3: So if you think about traditional value investors, Warren Buffett
Speaker 3: entering gain this kind of thing there is.
Speaker 2: We take issue with that one more on Buffet and
Speaker 2: value investing. Come back to that.
Speaker 3: Maybe, well, think of somebody who's doing a lot of
Speaker 3: effort into assessing a company and deciding if the current
Speaker 3: market price represents good value. So maybe if that's the way, so.
Speaker 1: That now describes every single investor there is, because no
Speaker 1: one buys something which they don't think is good value,
Speaker 1: even a growth investor. If they're paying seventy times for something,
Speaker 1: we'll think is good value because they expected to go
Speaker 1: up right absolutely same, same, same.
Speaker 3: So yeah, okay, a lot of people would would fit
Speaker 3: themselves into that that way of describing things. And now
Speaker 3: imagine instead of putting a huge amount of effort into
Speaker 3: each company into looking at what the management of said,
Speaker 3: into looking all over the balance sheet, into looking at
Speaker 3: the drivers of the company's profits and so on, and
Speaker 3: work out what the price should be Imagine that all
Speaker 3: you do is you look at the price siarnings ratio
Speaker 3: of every company that you can find, and you just
Speaker 3: rank them, and you just look at the ones that
Speaker 3: have lower than average and the ones that have higher
Speaker 3: than average price sarnage ratios, and you just decide to
Speaker 3: go along the ones that have lower than average PE
Speaker 3: ratios and short the ones that have higher than average.
Speaker 3: That is an example of an algorithmic rule, which in
Speaker 3: and of itself is not very sophisticated or clever, obviously,
Speaker 3: because it doesn't involve any interesting analysis of what those
Speaker 3: companies are doing. It just takes one piece of data
Speaker 3: per company and update it roughly once a quarter. Depending
Speaker 3: on how from these numbers are updated, it.
Speaker 2: Would rebalance once a quarter.
Speaker 3: Generally, yes, exactly. So this is an idea that many
Speaker 3: people have traded for decades. It doesn't work that well
Speaker 3: anymore as well as it used to, and many people
Speaker 3: have adopted more sophisticated tweaks on it. You know, perhaps
Speaker 3: you don't just rank every single company. Maybe you look
Speaker 3: at the ranking of a company within a sector. Maybe
Speaker 3: instead of looking at the trailing earnings, you look at
Speaker 3: analysts forecasts of earnings maybe you try to forecast what
Speaker 3: the next earning announcement will be yourself. You know, there
Speaker 3: are lots of ways to make the idea still quantitative
Speaker 3: and systematic, but more sophisticated than that original base idea.
Speaker 3: But ultimately, what they're all doing is something that is
Speaker 3: much less in depth than what a traditional investor would
Speaker 3: do to assess whether a company's good value or not.
Speaker 3: And on the flip side is that you can do
Speaker 3: it very easily for a very large number of companies,
Speaker 3: and you can back test it through history and you
Speaker 3: can see what following this rule would have done.
Speaker 1: Okay, so you can do all that, and you have
Speaker 1: maybe a one hundred different strategies running in in a fund.
Speaker 2: Do you said earlier?
Speaker 3: It varies. We have different products. So some of the
Speaker 3: CTA products, for example, are really based around the properties
Speaker 3: of momentum of trend following on macro and markets, and
Speaker 3: there are good reasons for that because that has a
Speaker 3: specific function for investor portfolios, which we can talk about products.
Speaker 3: We have combined a much larger number of different strategies
Speaker 3: where we're really trying to benefit from the diversification you
Speaker 3: get from a large number of different ideas.
Speaker 1: This sounds to me like the kind of thing that
Speaker 1: AI would be remarkably helpful for.
Speaker 3: AI certainly is helpful for us. It's not something that's
Speaker 3: extremely new in a sense, it's the latest example of
Speaker 3: a fairly transformative technology or set for techniques. It probably
Speaker 3: wouldn't surprise you, given that we have a huge technology
Speaker 3: component to our business and the people we employ are
Speaker 3: people with backgrounds and software engineering and sciences and so on,
Speaker 3: that this has always been something that's very important for us.
Speaker 3: Before AI, it was machine learning, and it was all
Speaker 3: times of data, and it was big data, and it
Speaker 3: was cloud technology, and it's very important for us to
Speaker 3: keep up with the way that all of these ideas
Speaker 3: develop and certainly the recent developments in large language models
Speaker 3: have been very helpful for us.
Speaker 1: Does it make everything move faster, faster and faster, so
Speaker 1: the edge that you might get from each new idea
Speaker 1: is removed much more quickly?
Speaker 3: Well, to some extent. I mean there's a general truth
Speaker 3: in investing that nothing you know ever totally transforms the
Speaker 3: business because at the end of the day, of everyone
Speaker 3: discovers something, then its value reduces because ultimately there's a
Speaker 3: certain number of dollars to be made out of forgiven idea.
Speaker 3: The more people who do it, the more they have
Speaker 3: to share it. But that doesn't mean that you can
Speaker 3: just not follow it. You still have to do these things.
Speaker 1: All right, Let's move on for what I know you
Speaker 1: really want to talk about, which is the CTA stuff
Speaker 1: and the trend following fund.
Speaker 2: Explain how that works.
Speaker 3: Yeah, absolutely so. This is a quant strategy that trades
Speaker 3: the macro markets, primarily through futures, and it has a
Speaker 3: particular role in investor portfolios, which has always been there,
Speaker 3: but it's become increasingly important really since twenty twenty two.
Speaker 3: There have been other moments as well where investors have
Speaker 3: become particularly interested in CTAs. The financial crisis was one,
Speaker 3: particularly where equities obviously fell a lot and lots of
Speaker 3: other asset classes that did poorly, and people start to
Speaker 3: look around for what things had done well. And at
Speaker 3: that time, the two things that had done well were
Speaker 3: bonds and CTAs, and so there was a big surge
Speaker 3: of investment into both of them after the financial crisis.
Speaker 3: And then in twenty twenty two, the remarkable thing that happened,
Speaker 3: which is a headache not just for the retail investors
Speaker 3: that you mentioned, but actually for all investors, is that
Speaker 3: bonds and equities fell together for a year. The reason
Speaker 3: is the problem is because a lot of allocation philosophies
Speaker 3: had relied on the idea that bonds could provide divestification
Speaker 3: to equities, and that wasn't a crazy idea. You'd had
Speaker 3: a twenty year period leading up to there where bond's
Speaker 3: and equities were negatively correlated, and not every time that
Speaker 3: pretty much every time stocks had gone down, bonds had helped,
Speaker 3: as they did in the financial crisis.
Speaker 1: So the traditional sixty to forty portfolio worked for everybody
Speaker 1: for a very long time and then suddenly kind of
Speaker 1: stopped working exactly.
Speaker 3: And in fact, it didn't have to be sixty forty.
Speaker 3: You know, any reasonable combination of bonds and equities would
Speaker 3: have performed extremely well over that time period. And then
Speaker 3: that diversification disappeared. Really starting twenty twenty, the correlation flip
Speaker 3: to being positive, which meant that the potential for them
Speaker 3: both to go down at the same time was there,
Speaker 3: even if it hadn't actually happened yet. But then in
Speaker 3: twenty twenty two that potential was realized and they both
Speaker 3: did go down together, and that really drove home that
Speaker 3: you can't just rely on bonds to be your diversified equities,
Speaker 3: and so people started again looking at at CTA strategies,
Speaker 3: which had done very well that year. So why is
Speaker 3: it that CTA strategies provide this diversification. There are basically
Speaker 3: two reasons. The first reason is that among the futures
Speaker 3: markets that they trade, there are a variety of things
Speaker 3: which are very uncorrelated. Exposures are things which are quite
Speaker 3: difficult for people to benefit from otherwise. So an example
Speaker 3: of that would be, for example, the big rise in
Speaker 3: the price of cocoa which took place in late twenty
Speaker 3: twenty three and early twenty twenty four, and then subsequently
Speaker 3: the big drop in the price of coca that happened
Speaker 3: in the last few months. That's a trend that you
Speaker 3: can benefit from by trading the futures markets, but it's
Speaker 3: very difficult to get that exposure through stocks, for example.
Speaker 3: So that's one reason. The other reason that you can
Speaker 3: benefit a lot from CTAs in a portfolio is that
Speaker 3: because they trade futures markets, and futures markets have this
Speaker 3: amazing property that it's just as easy to be short
Speaker 3: as it is to be long. You can benefit from
Speaker 3: short positions in the major asset classes. It's just as
Speaker 3: easy to maintain a position that short equities or short
Speaker 3: bonds as it is to be long equities and long bonds,
Speaker 3: and so trivially in the year like twenty twenty two,
Speaker 3: the strategy is short in those asset classes and it
Speaker 3: does well.
Speaker 2: So that was a good year for CTA.
Speaker 1: That was a period when you're the assets that you
Speaker 1: hold kind of peak, right, so that there's winter and
Speaker 1: as a whole managed less money now than it did
Speaker 1: at its peak. What's driven that is that because people
Speaker 1: looked at the successes in times like that and then go, well,
Speaker 1: since then, long equity has been marvel.
Speaker 2: It's very easy to make money. And why do you
Speaker 2: need to mess around the edges?
Speaker 3: Oh, our peak was at a different time from that, well,
Speaker 3: was it?
Speaker 2: But earlier?
Speaker 3: Yeah, well in twenty sixteen. But I think there's there's
Speaker 3: a peak of a single manager, which has more to
Speaker 3: do with what's going on in that organization. But the
Speaker 3: peak of the industry is a different question. So in
Speaker 3: terms of how much people allocating to CTAs, it's a
Speaker 3: little more difficult to tell because some CTAs are public
Speaker 3: like we are. Others are offered through products that perhaps
Speaker 3: banks offer, and is not publicly known how much is
Speaker 3: being traded there. But what we're certainly seeing is that
Speaker 3: the interest relates strongly to the performance of the strategy,
Speaker 3: as you'd expect.
Speaker 2: Of course, okay, and the performance of the strategy long term.
Speaker 3: Well, look, long term, it's been a great addition and diversifier.
Speaker 3: So you can take any combination you like of bond's
Speaker 3: and equities, and it's been beneficial to add an allocation
Speaker 3: to CTAs as well over the long term. Beneficial like her,
Speaker 3: Beneficial in the sense that performance has improved, and particularly
Speaker 3: the drawdowns that you get when you have these big
Speaker 3: moments like twenty eight or twenty twenty two are mitigated
Speaker 3: to some extent.
Speaker 1: Let's say, for example, you're a retail investor and you
Speaker 1: make five percent of your portfolio CTA.
Speaker 2: How would that how would that have helped your performance
Speaker 2: over I say a decade long period.
Speaker 3: Well, you know, the exact number is very depending on.
Speaker 2: I know, I know the exac num is very bad.
Speaker 1: But you know, we need we need to know that
Speaker 1: it would make a positive difference of more than a
Speaker 1: couple of basis points here are that it does.
Speaker 3: It makes a positive and you can measure in a
Speaker 3: couple of ways. So you can say, well, there's an
Speaker 3: annualized number which might go up by one percent or
Speaker 3: something depending on exactly the waiting you give to it.
Speaker 3: But then what is also important is not just that
Speaker 3: sort of average, but the fact that historically, at least
Speaker 3: the CTAs have performed well in the periods which haven't
Speaker 3: been good for equities. And so it's added the profits
Speaker 3: at particular moments when other things were doing badly, which
Speaker 3: isn't as easily quantified by just adjusting the annual return number,
Speaker 3: but it's a very important component of why people are
Speaker 3: allocating to it.
Speaker 1: Yeah, can you tell from of course you can, But
Speaker 1: looking back, what how much of your performance comes from
Speaker 1: being long asset classes and how much comes from being
Speaker 1: short asset classes?
Speaker 2: There any any differential there?
Speaker 1: Are you equally good at both or do they both
Speaker 1: equally feed into performance?
Speaker 3: You get good performance from both. So I'll give you
Speaker 3: some examples. So if we look at two thousand and
Speaker 3: eight at the financial crisis, that's a really good example
Speaker 3: to play through. So that year, a good portion of
Speaker 3: profits did come from long positions in bonds. Bonds did
Speaker 3: very well, but about a third of profits came from
Speaker 3: being short inequities. So you saw profits on both sides.
Speaker 3: Now you can pick other examples again on both sides.
Speaker 3: In twenty fourteen, that was a very good year for CTAs.
Speaker 3: Why was it a good year, Well, there were two
Speaker 3: enormous trends. One was the downward trend in oil prices
Speaker 3: that was driven by the shale boom, and that is
Speaker 3: a great example of a trend that is very very
Speaker 3: easy for CTAs to latch onto. Being short oil is
Speaker 3: as easy, like I said, as being long oil, but
Speaker 3: it's not so easy to do in other contexts. So
Speaker 3: cta'd very well being short oil in that year. The
Speaker 3: other thing that was going on was there was this
Speaker 3: tremendous upward trend in fixed income, particularly in buns, and
Speaker 3: it was quite surprising actually at the time, because yields
Speaker 3: on buns were getting towards zero, and in fact they
Speaker 3: ended up going below zero, which is something that people
Speaker 3: generally didn't expect could happen. And these two examples actually
Speaker 3: reveal something quite unintuitive about momentum, about the idea of
Speaker 3: following trends in these markets, because often people think, well,
Speaker 3: if you're following a trend, you must be getting into
Speaker 3: some very crowded trades and you must be sort of
Speaker 3: following a herd, and just the general received wisdom, And
Speaker 3: in fact, these examples show you that very often you
Speaker 3: can be doing precisely the opposite. And the way we
Speaker 3: know we're doing the opposite is that we can look
Speaker 3: at what fundamental analysts are saying about what the market
Speaker 3: is going to do at each moment, and we find
Speaker 3: there are these moments which are very profitable where the
Speaker 3: trend disagrees with what the fundamental analysts are saying. So
Speaker 3: if you look at what people were saying about where
Speaker 3: oil would be through twenty fourteen, people were not focused
Speaker 3: on the shell boom. They were focused on the apparently
Speaker 3: unquenchable demand from emerging markets, the policies which might lead
Speaker 3: to the reduction in supply. You heard people talk about
Speaker 3: pee oil supply, for example, at that time, and every
Speaker 3: analyst was predicting the oil would increase in value. And similarly,
Speaker 3: with that trend in buns, everyone was saying, well, buns
Speaker 3: cannot possibly go up from here, because why on earth
Speaker 3: would anyone give their money to the GM government to
Speaker 3: get less of it back in ten years time.
Speaker 1: Yeah, well we might still ask that question actually simon
Speaker 1: why they did that, But here we are.
Speaker 3: Yes, well you might. But the great thing about trend
Speaker 3: following and about these algorithms in general, is that they
Speaker 3: don't have to know. They don't have to have a
Speaker 3: theory about why the markets do what they do. They
Speaker 3: have a rule that this market has been moving in
Speaker 3: this direction, maybe it will continue, and they have evidence
Speaker 3: that following that in the past has been a good
Speaker 3: thing to do.
Speaker 1: Okay, so let's move on to talking about what trends
Speaker 1: are interesting at the moment, because of course that's what
Speaker 1: everyone really wanted to know, is if, as you say,
Speaker 1: the market is moving in one direction, there is momentum
Speaker 1: there before it has become a consensus view, what you're
Speaker 1: really looking at at the moment.
Speaker 3: Well, you know, the things are not necessarily things that
Speaker 3: are unknown. So the big trends that we've seen recently
Speaker 3: have been in the precious metals, to some extent, in
Speaker 3: base metals inequities. Obviously, equities have been going up in general.
Speaker 3: There's been good short trends in some places in US
Speaker 3: natural gas, for example, and particularly in cocoa, the example
Speaker 3: I mentioned earlier. Well, it's interesting you mentioned that because
Speaker 3: it's obviously a fairly niche market, and particularly when we
Speaker 3: trade a few hundred markets, why am I mentioning this one.
Speaker 3: The interesting thing is that the strategy itself is very dynamic,
Speaker 3: So when there's a big trend, it will take a
Speaker 3: big position, and when there's not much going on, it
Speaker 3: won't take a huge position. So what that means is
Speaker 3: that even though you're trading perhaps two hundred different things,
Speaker 3: it's not like building along any portfolio of stocks where
Speaker 3: you have to just always maintain this collection of posis.
Speaker 3: The strategy is behaving very dynamically, so at any given moment,
Speaker 3: there'll be a much smaller number of things which are
Speaker 3: really contributing, and it will be based on what those
Speaker 3: markets have done recently. So I'm talking about cocoa because
Speaker 3: it's had this astonishing rise and then equally astonishing for recently,
Speaker 3: and that's why it's making a big impact on the portfolio,
Speaker 3: and that it didn't do for perhaps twenty years prior
Speaker 3: to that. So if you'd have asked at any point
Speaker 3: in the last twenty years I wouldn't have been talking
Speaker 3: about it.
Speaker 2: Okay, this is great.
Speaker 3: Interesting.
Speaker 1: So when you talk about one of your funds, for example,
Speaker 1: having having all these different positions and things being traded, etc.
Speaker 1: The returns over over, say an annual period, will probably
Speaker 1: only come from a couple of those positions. There will
Speaker 1: only be a few that are of reasonable size.
Speaker 3: Well, it's certainly a smaller number than the two hundred.
Speaker 3: You're right, it's typically a few big things that are
Speaker 3: that are happening every year. That's absolutly right. So coco yes, cocoa,
Speaker 3: gold here, some of the base metals as well, Copper, yeah, Aluminium, uranium, uh,
Speaker 3: less less uranium because it's a less liquid market for
Speaker 3: us to trade. But that the yen as well, there's
Speaker 3: been a big market for us over the last few years.
Speaker 2: Uh huh.
Speaker 1: And would you expect the yen to turn lots of
Speaker 1: conversations without the yen?
Speaker 3: Absolutely?
Speaker 2: Again, you don't know, right, that has to be the answer.
Speaker 1: I don't know.
Speaker 3: No, Although it is another great example of the fact
Speaker 3: that the algrim you know, doesn't have a theory it's
Speaker 3: trying to follow as a massive strength. Because obviously what
Speaker 3: we saw the last couple of years, was everyone predicting
Speaker 3: that the yen is going to rally and in not
Speaker 3: doing it, or doing it for a bit and then
Speaker 3: and then resuming its slum.
Speaker 1: And you can tell so many good stories about would right,
Speaker 1: how it should rarely will rally, interest rates going up, inflation,
Speaker 1: and all the political change in Japan, etcetera, etcetera, and
Speaker 1: it never quite happened exactly.
Speaker 3: And in fact, you can see these kinds of episodes.
Speaker 3: This is an interesting point. I think that often these
Speaker 3: kinds of episodes are almost necessary for a trend to appear,
Speaker 3: because if you think about what a trend is, it's
Speaker 3: a situation where a market moves a long way, but
Speaker 3: that slowly. Right, If a market moves a long way
Speaker 3: very very quickly, then you know it's kind of fifty
Speaker 3: to fifty if you're on the right side of that
Speaker 3: or not. For there to be a meaningful trend that
Speaker 3: we can benefit from, it has to do it slowly.
Speaker 3: And that's a slightly surprising thing that it could ever happen,
Speaker 3: because what you hear about the way markets have developed
Speaker 3: is that information is incorporated into them at a never
Speaker 3: faster rate, and so you might think that if something
Speaker 3: is going to happen to a market, well it is
Speaker 3: going to be very very quick. But there are ways, nevertheless,
Speaker 3: that things can happen slowly, and one of the ways
Speaker 3: is if the market kind of has to fight against
Speaker 3: the narrative that is saying that the thing that is
Speaker 3: going to happen actually can't happen. And that's exactly what
Speaker 3: was going on with the en right, because all of
Speaker 3: the narrative was saying the end has to rally, and
Speaker 3: the fact that for whatever reason, which I'm not going
Speaker 3: to be able to tell you, for whatever reason, the
Speaker 3: marketing fact was really pushing in the other direction. The
Speaker 3: fact that that had to fight against what everyone thought
Speaker 3: was supposed to happen. It's part of the reason that
Speaker 3: it got drawn out into a long term trend and
Speaker 3: was therefore something that we were able to benefit from.
Speaker 1: Interesting, are there any other things that you're looking at
Speaker 1: the moment that are moving remarkably slowly?
Speaker 3: Well, look, gold is a good example. Well, but it's
Speaker 3: been over a couple of years that it's.
Speaker 2: Had a low and then very fast, that's right.
Speaker 3: And the dollar, obviously that the dollar has started to
Speaker 3: weaken over a relatively drawn out time.
Speaker 2: Period silver again very slow and then very very fast, which.
Speaker 3: Is in a way that is ideal behavior. Actually that
Speaker 3: there's another element of the algorithm which I hadn't talked
Speaker 3: about before, But what we do is when we have
Speaker 3: a strong signal that determines that we want a certain
Speaker 3: amount of volatility from that position. So when you get
Speaker 3: the situation like with silver, particularly silver, but gold, to
Speaker 3: where it starts small builds and then accelerates, that means
Speaker 3: that we start with building in a long position, and
Speaker 3: then as it accelerates, well, the volatility of the market
Speaker 3: goes up, and actually we don't need to own so
Speaker 3: much silver anymore in order to get the amount of
Speaker 3: volatility we want. So actually, as that market is accelerating upwards,
Speaker 3: we are selling again. It's another slightly surprising thing that
Speaker 3: you wouldn't necessarily expect from somebody who's following a trend,
Speaker 3: but that's typically what's happening as those markets accelerate, and
Speaker 3: in effect, you are locking in the profits that you
Speaker 3: make as you go.
Speaker 1: Okay, there's a sort of a view that pretty much
Speaker 1: all investing these days is momentum investing or trend following investing,
Speaker 1: because everyone everyone in a passive investment is effectively a
Speaker 1: momentum investor, just on the longside.
Speaker 3: In the sense of passive long in the aity investment.
Speaker 1: You know, if you've been invested, for example, soil relatively
Speaker 1: recently in a global equity ETF of any kinds, you've
Speaker 1: effectively simply been following American and tech momentum for years.
Speaker 1: That's it. You're not value investing, you're not a growth investor,
Speaker 1: and not anything in just a momentum investor.
Speaker 3: Yeah, there's an element of truth to that. I think
Speaker 3: it's slightly difficult to compare long only investments with long
Speaker 3: short investments because even though some of the ideas might
Speaker 3: be might be similar, the actual trading that you end
Speaker 3: up doing and the nature of the portfolio you end
Speaker 3: up holding is very different.
Speaker 1: Obviously, Just just this idea that most people have one
Speaker 1: side of your portfolio already to a degree equal part.
Speaker 3: Well, yeah, they have, yeah, one half perhaps of the
Speaker 3: of the equity portfolio. That in some sense that's right.
Speaker 1: And the point being that's kind of dangerous in that
Speaker 1: most most people passively investing in a global ETF are
Speaker 1: not aware that they have a one sided momentum strategy.
Speaker 3: Yeah, Look, it's an interesting point of view. You can
Speaker 3: think of any index, if you like, as a type
Speaker 3: of trading rule, as a type of algorithm, because it's
Speaker 3: it's effectively saying if it goes in the index, then
Speaker 3: you buy it. If it exits the index, then then
Speaker 3: you sell it, and other times you maintain it in
Speaker 3: these proportions. And it's interesting because obviously that is another
Speaker 3: rule that you can you can back test over time,
Speaker 3: so you can, if you like, think of it as
Speaker 3: a as a type of qunch strategy, and we often
Speaker 3: do try to think of it that way. I don't
Speaker 3: think I have anything useful to tell you really about
Speaker 3: whether that's dangerous or not, that that perhaps is a
Speaker 3: deeper question, and then I'm prepared to address.
Speaker 1: Listen, while we've been talking, remember I asked you earlier
Speaker 1: about about the extent to which it would have enhanced
Speaker 1: the performance of a portfolio. Luckily you have PR people, Simon,
Speaker 1: and they've sent me something saying. Winter research found that
Speaker 1: a ten percent allocation to trend following would have improved
Speaker 1: the returns of an equity bond portfolio in eighty seven
Speaker 1: percent of ten year periods since nineteen seventy two. Increasing
Speaker 1: the portfolio is our performance overcash to four point eight
Speaker 1: percent from four point one percent on average, and there's
Speaker 1: return improvement nearly doubled in the bottom decyle of ten
Speaker 1: year periods for the equity bond portfolio, highlighting diversifying properties
Speaker 1: and portfolio resilient.
Speaker 3: The VEGA fantastic. I'll congratulate them.
Speaker 2: I think you did the work. They just wrote it down.
Speaker 1: So in that sense, would you say that a ten
Speaker 1: percent allocation would be a reasonable amount for a retail investor?
Speaker 1: So let's say we've still got our long equity exposure,
Speaker 1: we've got some bond exposure. Maybe we've finally finally got
Speaker 1: the message, and we've got somewhere between five to ten
Speaker 1: percent in gold. Maybe maybe we've got three percent in bitcoin.
Speaker 1: Not recommending that, by the way, but maybe we.
Speaker 2: Do one percent.
Speaker 1: Should we also have ten percent in a trend following
Speaker 1: in a CTO strategy?
Speaker 2: Does that make sense to you?
Speaker 3: Look, it certainly makes sense that the right level of
Speaker 3: allocation depends on what your preferences are as an investor.
Speaker 3: If you allocate to things other than equities and bonds,
Speaker 3: then obviously you're departing from that benchmark and you introduce
Speaker 3: some risk of outperforming or underforming that benchmark, and different
Speaker 3: people have different tolerances for that. There's another way of
Speaker 3: doing it as well, where you get to maintain the
Speaker 3: exposure to equities, which we offer through a portable alpha
Speaker 3: type structure. This is something that has been really always
Speaker 3: on the radar of institutional investors, and we're offering now
Speaker 3: for retail investors as well in the usage product.
Speaker 1: Okay, and now I know I said you might have
Speaker 1: a couple of percentage points of your portfolio in bitcoin,
Speaker 1: but is crypto one of the asset classes that comes
Speaker 1: into your strategy.
Speaker 3: We do trade crypto in that way. If you think
Speaker 3: about what we're looking for, particularly with that kind of
Speaker 3: mentum strategy, we're looking for markets which might have trends
Speaker 3: and which are liquid enough that we can trade them. Obviously,
Speaker 3: crypto satisfies both of those things. The only question would
Speaker 3: be is there a way to trade them which is
Speaker 3: operationally safe? And there is actually because there are futures
Speaker 3: on some of the crypto assets. There are futures traded
Speaker 3: on CME on bitcoin and ether and a couple of
Speaker 3: others as well, and the structure of those is basically
Speaker 3: the same as most of the other futures that we trade.
Speaker 3: So it's fairly straightforward to add them in to the
Speaker 3: momentum system and to benefit from them, which we have
Speaker 3: done this.
Speaker 2: Year in which direction?
Speaker 3: Well, this year short, we benefited at other times. It's
Speaker 3: been long.
Speaker 2: Yeah, And would you be sure now?
Speaker 3: Well, look again, you shouldn't take any of this as
Speaker 3: insightful advice about.
Speaker 2: Well, now, we're absolutely not.
Speaker 1: We know that this is purely about momentum and trends,
Speaker 1: but we still want.
Speaker 3: To know that's right. Well, really, you're just asking me
Speaker 3: have they gone up or down recently?
Speaker 2: Now I'm asking you where are you expecting them to go?
Speaker 1: Now?
Speaker 2: How does a trend look?
Speaker 3: Yeah, like I said, the trend is just what has
Speaker 3: happened recently, which is down. But the chance that means
Speaker 3: it's going to go further down is only marginally above
Speaker 3: fifty percent.
Speaker 2: Okay, And what.
Speaker 1: Makes it difficult yet for you? What are the risks
Speaker 1: in their strategy? What makes it go wrong?
Speaker 3: Look, there are two kinds of situations where momentum investing
Speaker 3: is not going to do well. So one is where
Speaker 3: there aren't any trends, when markets just moved sideways The
Speaker 3: other is where there might be a trend, but then
Speaker 3: there's a sudden reversal. So we've had good examples of
Speaker 3: that recently. So last year, for example, there were big
Speaker 3: reversals in March and April our announcements, in particular calls
Speaker 3: for the equities that had been going up, they then
Speaker 3: started going down. That all had been strengthening, then it
Speaker 3: started weakening. You know, a lot of commodities have been
Speaker 3: going up, then they went down. So those kinds of
Speaker 3: situations are other situations where the structure won't do well.
Speaker 3: The case where it does well is where markets move
Speaker 3: steadily and consistently in a particular direction, or at least
Speaker 3: enough markets do that to outweigh the ones that are
Speaker 3: behaving in a more negative way.
Speaker 1: Yeah, so what are your expectations for the rest of
Speaker 1: this year, Well, you can only.
Speaker 2: Tell me some things will go up, some things will
Speaker 2: go down.
Speaker 1: But are you expecting the type of volatility that will
Speaker 1: make it a good year for you?
Speaker 3: Look, we have evidence, you know, when we look historically,
Speaker 3: we see that there are some years which are good,
Speaker 3: some years which are less good, And we can't predict
Speaker 3: if we could time when trend following is going to work.
Speaker 3: We would just build it into our strategy that it
Speaker 3: would take more risk in those periods and less risk
Speaker 3: at other times. What we found in terms of allocating
Speaker 3: to trend following is that it works best if you
Speaker 3: don't try and time it, if you just regard it
Speaker 3: as a permanent allocation and live with it. For example,
Speaker 3: after that period in April, April, May June were difficult
Speaker 3: months for the trend strategy for the reasons that I said,
Speaker 3: And if you'd been thinking about at that point, you
Speaker 3: get pretty depressed and you think, well, this just hasn't worked,
Speaker 3: is it. When is it going to start to work?
Speaker 3: And then what happened was over the course of the
Speaker 3: rest of the year we saw several big trends emerge.
Speaker 3: So obviously the precious metals rally continued, equities went up
Speaker 3: relatively steadily. We saw some of the base metals do
Speaker 3: well as well, and there wasn't a continuation of that
Speaker 3: negative whipswew and behavior that was really a prominent feature
Speaker 3: earlier on in the year. So that meant that overall
Speaker 3: the strategy did very well. But there was nothing that
Speaker 3: you could have pointed to in July that said, oh
Speaker 3: now is the moment. Now is the moment. It's definitely
Speaker 3: going to work, just as there was nothing you could
Speaker 3: have really pointed to in January which said now is
Speaker 3: them it's definitely not going to work. So unfortunately that
Speaker 3: that's that's the way things are, and I don't have
Speaker 3: any better answer to be able to predict it.
Speaker 2: This is a kind of trust us strategy, isn't it?
Speaker 3: Well not really, because this is where you can look
Speaker 3: back at the trap records and at the and we
Speaker 3: can look back at the back test, and it's those
Speaker 3: things that we are we are looking at. It's the
Speaker 3: more it's the more discretionary type of investor who's making
Speaker 3: one decision you know today, and it's totally different from
Speaker 3: the things they looked at last year and the year before.
Speaker 3: They're the people who are saying trust us because they
Speaker 3: don't have the history back test to look at.
Speaker 2: Yeah, so let me ask you something.
Speaker 1: One thing that comes up a lot on this podcast
Speaker 1: is ESG strategies and stewardship around investing. And if you're
Speaker 1: investing like this in a way that is entirely non
Speaker 1: company specific, you can't really have an EESG overlay of
Speaker 1: any kind.
Speaker 2: Can you.
Speaker 3: Not in the traditional sense that there are various things
Speaker 3: that you can you can do. There are, for example,
Speaker 3: ESG versions of traditional indices, and there are futures on
Speaker 3: those indices, so we trade those where there's sufficient liquidity
Speaker 3: to enable it. We obviously can't create that liquidity where
Speaker 3: it doesn't exist, so we're to some extent reliant on
Speaker 3: the marketmakers and other people to take an interest in
Speaker 3: those things. But we are we're well positioned to do
Speaker 3: it if if they become popular.
Speaker 1: Okay, and tell us briefly about the appropriate vehicle that
Speaker 1: you have for retail investors. That's the Winter and Trend Fund,
Speaker 1: right the use.
Speaker 3: Its Yeah, well, we have we have use sets vehicles
Speaker 3: for all of our major strategies. So we do have
Speaker 3: the Winter Trend Fund. In addition, we have another wint
Speaker 3: and CTA fund which includes some non trend elements as well.
Speaker 2: They've got the Trend Enhanced Fund.
Speaker 3: I'll hold on, I'll get back. There's the first one
Speaker 3: that I mentioned was the Winter and Armor divers Fied Fund.
Speaker 3: The Winter Trend Enhanced Fund is the fund I mentioned
Speaker 3: that has trend falling with and also maintains the exposure
Speaker 3: to global equities. So for example, if you wanted to
Speaker 3: add this into your portfolio, but you didn't want to
Speaker 3: disinvest from your equity portfolio, this is a way to
Speaker 3: do it because it maintains one hundred percent exposure to equities.
Speaker 3: And then the last use that's fund that I you
Speaker 3: mention is the is our quant multi strat hedge fund,
Speaker 3: which is also there.
Speaker 1: Okay, and these are all global funds, right, they're all
Speaker 1: looking at everything.
Speaker 2: Everywhere all the time.
Speaker 3: That's correct.
Speaker 2: Very busy two hundred employees you've got.
Speaker 3: There, They are very busy. But remember they're not individually.
Speaker 2: They're not doing any individual analysis.
Speaker 3: In the analysis, they're looking at the algorithms, and the
Speaker 3: algorithms are mostly things that can be applied relatively broadly.
Speaker 1: And do you think that over the next decade these
Speaker 1: jobs will still exist, because an awful lot of it
Speaker 1: does sound as though I'm obviously it's hugely automated already.
Speaker 1: Will it get more so? Will there be two hundred
Speaker 1: people require to run sixteen billion dollars in a decade
Speaker 1: using this kind of strategy?
Speaker 3: It's a good question.
Speaker 2: Can we just code everything?
Speaker 3: I don't think you'll be able to vibe code everything
Speaker 3: it's yeah, I struggle to make predictions about this. You can.
Speaker 3: It's interesting to look at.
Speaker 2: And I'm going to get a prediction.
Speaker 1: Ow do you before we got to the end of
Speaker 1: this podcast. If it kills me, don't make one.
Speaker 3: On this, I'm sorry, Maaron. Well, look when you look
Speaker 3: at how particularly technology jobs have changed, what you find
Speaker 3: it's not necessarily that you need more of your people.
Speaker 3: You find a great variation in the in the skill
Speaker 3: sets that are required, and that that really is driven
Speaker 3: by technological change. Often that's change in the type of
Speaker 3: software that we use. That you know, the development of
Speaker 3: Python as a programming language that's much more broadly accessible
Speaker 3: than previous programming languages, were the changes in the type
Speaker 3: of databases that we use the you know, going back
Speaker 3: a decade or two now, the introduction of virtualization of PCs,
Speaker 3: which drove a lot of the reduction in PC sales,
Speaker 3: and the types of expertise that were then required to
Speaker 3: maintain the computing resources also changed dramatically because you suddenly
Speaker 3: are not dealing with a computer that's in sitting under
Speaker 3: your desktop anymore, but it's sitting somewhere in a remote warehouse.
Speaker 3: And then the development from there to using cloud resources.
Speaker 3: All of these drive changes in the type of expertise
Speaker 3: that required, and I'm sure that that will be true
Speaker 3: with AI as well, but we are not. There are
Speaker 3: some types of business where there's just a fixed thing
Speaker 3: that you're trying to do, and if you can do
Speaker 3: it more efficiently, then you just have few people do that,
Speaker 3: And that is not really what our business is because
Speaker 3: our goal is a bit more open ended. We want
Speaker 3: to drive the best investment returns that we can and
Speaker 3: if we can do the task that we're currently doing
Speaker 3: more efficiently with fewer people than what we'll do is
Speaker 3: we will keep the same number of people and we'll
Speaker 3: do more.
Speaker 1: Okay, fair enough, What do you think you'll get your
Speaker 1: kids to study at university? When I asked this question,
Speaker 1: now there's a kind of clear division between people who
Speaker 1: still think it should be stem all the way and
Speaker 1: those who think, well, we're moving into an age when
Speaker 1: empathy is more important than anything else, and therefore you know,
Speaker 1: sold chemistry, do philosophy.
Speaker 2: Where do you stand on that?
Speaker 3: I'm not sure it's really up to me. My children
Speaker 3: have their own.
Speaker 2: Nothing, nothing will be up to you.
Speaker 1: But the bit where you try and feed it to
Speaker 1: them and make them think it's their own idea.
Speaker 2: What do you think that'll be?
Speaker 3: Well, my oldest son's interests at the moment are split
Speaker 3: between maths on the one hand, classics and history on
Speaker 3: the other.
Speaker 2: Classic combo, isn't it?
Speaker 3: They are? And I actually quite like that combination. I
Speaker 3: think there's great value in both.
Speaker 1: Okay, here was me desperately trying to get something to
Speaker 1: finish about for you, about the future, and we're coming
Speaker 1: up with do both.
Speaker 3: Was the path I took. So I studied physics and philosophy,
Speaker 3: and I think i've I've definitely benefited from having both.
Speaker 2: Yeah, you were on holiday last week, what were you reading?
Speaker 3: I was reading a Kubaqua detective fiction novel by Louise Penny.
Speaker 3: And then if you've come across those.
Speaker 1: Folks, I've read them all.
Speaker 3: I've just discovered them. So this is I think I
Speaker 3: was on my fourth one and I'm really enjoying them now.
Speaker 1: They get a little Dell Towald to the end. There's
Speaker 1: an awful lot of them. I've now shifted towards a
Speaker 1: series of murder mystery suspenses in Dublin by Tana French,
Speaker 1: which I recommend very highly.
Speaker 3: Oh, thank you, I'll give that a try.
Speaker 2: Thank you very much, Simon, thank you so much. Thanks
Speaker 2: for listening to this week's Maren Talks Money.
Speaker 1: If you like our show, rate review and subscribe whatever
Speaker 1: you listen to your podcast and keep sending questions or
Speaker 1: comments at Merror Money at Bloomberg dot net.
Speaker 2: You can also follow me and John on Twitter or x.
Speaker 1: I'm marinas w and John is John Underscore Stepic. This
Speaker 1: episode was produced by Me Maren sumsep Web used by
Speaker 1: Somersardian Roses and sound designed by Blake Maples and special
Speaker 1: thanks of course to Simon Juds