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- [00:01]
A
Welcome to Top Traders Unplugged in markets. Success doesn't come from predicting what happens next. It comes from being prepared for what you can't predict. In each episode we go deep with some of the world's most thoughtful minds in investing, economics and beyond to understand how they think, how they prepare and how they decide and the experiences that shaped how they see the world. No noise, no, no shortcuts, just real conversations to help you think better and invest with confidence.
- [00:36]
B
Welcome or welcome back to this week's edition of the Systematic Investor series with Rob Carver and I, Nils Caster Blasten, where each week we take the pulse of the global market through the lens of a rules based investor. Rob, it is great to be back with you today. Hope you're doing well. How are things in the uk? Is it summer yet where you are?
- [00:53]
C
I mean summer in the UK is a sort of a moving target. So we, we've, we've had like a number of potential summers appear and then disappear. So last week I think the weather was very good. I was actually in France, but I think the weather was good here as well. So yeah, it's, it's, it's pretty nice outside at the moment, I have to say. And I think the last time we chatted was early February and of course nothing's actually happened in the world since then. It's been pretty, pretty, pretty boring to be honest, in markets and with geopolitics. So, yeah, quite chilled out, relaxed to be honest.
- [01:25]
B
Yes, sounds like it. But let me start on a slightly different note today because I have a little bit of a service announcement to all the people listening and that is because we at Dunn, but also others in our industry I have noticed are currently being victimized by scammers, people impersonating, representing CTAs and therefore I just want to make sure, and this can happen by the way, both electronically on different platforms, on websites and also we've seen evidence of physical letters being sent out with, suggesting that they're representing us or some of these other firms that we know well in the industry. So just want to let everybody know that they should really be careful at the moment and they should definitely make sure that they contact the companies directly to verify as we've seen a few people do and that's how we became aware of it. My understanding is right now that Germany, Austria in particular are areas where these things are happening. So just wanted to make sure that everybody is extra careful at the moment if they do intend to make investments in this industry.
- [02:40]
C
So anyway, how do people at home know? And indeed how do I know that you are Niels and not an AI kind of replication?
- [02:46]
B
That is true. That is true. Of course, my voice could be an AI so. But luckily it's not. I don't think AI is very good with a Danish accent yet, but it might.
- [02:56]
C
Thank goodness. It's only a matter of time though, surely.
- [02:58]
B
Yes, absolutely. Anyways, by the way, speaking of that, I was listening to, you know, I like Howard Marks memos. I think they're very well written and they turned it into audio format a few years ago and the last one they published as an audio was actually. And they of course disclaim. Make a disclaimer for this. This was read by an AI it didn't necessarily sound exactly like Mr. Marx, but it was pretty similar. So for sure this is changing.
- [03:32]
C
Well, interestingly, my publisher has asked if they would like me to allow the release of audiobooks of my books. Um, but with an AI voice reading them. So. Which I think. I mean, my books are quite technical and some might say boring. I'm not sure an AI voice would help. I think you, you need a more interesting and kind of lively voice to do that. So. But yeah, we'll see. Maybe, maybe there'll be a big market for my books now in, in terms of helping people sleep at night by listening to the AI audiobook version of them.
- [04:03]
B
No, absolutely, yeah. It's. It's all about helping people, Rob, as you know, in any way we can. Anyways, before we dive in, we got a lot of topics to, to talk about today. A lot of questions came in, so that's great, wonderful, thank you so much. But before we do that, I'm always curious what's kind of on your radar at the moment that is not really related necessarily to what we're going to be talking about today. Anything exciting.
- [04:29]
C
I mean, there is a war happening and it's dominating the headlines. And, and I guess one thing that's quite interesting about it is, is the, the sort of almost muted reaction in the market, particularly in the equity markets. I do feel that at some point the rubber's going to hit the road because there is this substantial supply shock happening in oil. The oil price obviously reacted to it to some extent, but even the oil price reaction arguably is muted compared to what's happening. So one thing I noticed that there's quite a good article in the Financial Times on the Alphaville sort of blog of the Financial Times, which is actually free. So you don't need to be behind the quite Expensive FT paywall. And they're talking about the price of physical oil which seems, has become quite disconnected from the price of futures that we trade. The sort of two main futures being the WTI and the Brent futures contracts. So the sort of futures contracts are hovering around the sort of 90 to $100 a barrel level. Roughly speaking, you know, obviously the situation is very volatile and perhaps I should say that, you know, we're recording this on Thursday 16th April because, you know, things could change quite dramatically.
- [05:49]
B
1:15 Swiss time.
- [05:51]
C
Exactly. Even at the end of this podcast things could be, could be quite different. But yeah, so this quite interesting article saying that the price of physical oil is quite, quite different and also is very much dependent on location. So apparently the physical price of oil in Sri Lanka at the moment is, and I feel like a dramatic pause is required here, two $86 a barrel, which is, you know, over three times the futures price. So there does seem to be a bit of a, you know, a disconnect in the oil market in terms of the futures. So futures contracts obviously work with delivery. You know, also all futures contracts are specified for either, as you know and most of the listeners know, for either physical or delivery or cash settlement and that physical delivery will be against a particular specification also for a particular location. So you know, we've talked on this podcast before about, you know, buying say gold. If you buy a gold futures contract, then the delivery of that has to be to one of a certain number of warehouses that are nominated by the, by the exchange and sort of specified in the contract. So actually where your oil is and where it's being delivered to is extremely important. And you know, it does seem to be that there's a real disconnect between both the futures market but also the spot price in different parts of the world as well. So as someone who trades oil as futures, you know, we can kind of abstract away from all of this messy black sticky stuff and making sure it's in the right place around the world. But you know, there are people whose job that is and their job at the moment's very difficult and it does seem that even $100 a barrel doesn't really accurately reflect, you know, what, what the sort of pent up demand and lack of supply for oil is going to be. So yeah, watch this space.
- [07:47]
B
Yeah, no, I completely agree. I think there's definitely more to this story than what we see in the markets for sure. Actually mine one of what's been on my radar, I would say what's caught my Attention the last day or two, actually the first one was just really this morning very much aligned with, in line with what you're saying and that is that The S&P 500 closed at a new all time high yesterday, like nothing's going on in the world. So. And this was after what, a 10% correction or something like that, just by the dip.
- [08:16]
C
Just buy the dip. Nails. Forget all of your systematic models, forget your signals, forget your computers, just buy the dip. That's. That's what works, right?
- [08:24]
B
Yeah. Clearly the other thing that caught my attention, you know, I think was it last week or the week before I had Andrew on, we talked about ETFs and of course, you know, the different approaches and how people wrap strategies, either replication of quasi semi true CTA strategies in into ETFs. And of course ETFs have been. And I'm no expert I should highlight here, but ETFs for a long time was really known for this flat fee structure rather than what we have in the traditional hedge fund world, which is our CTA world, which is a management fee and a performance fee. But I just noticed that now there is, I think in Europe coming out a usage ETF that has a performance fee attached. So maybe things are changing, which from where I sit, is a good thing that we don't only get paid for raising money, but actually get paid for producing real returns for our clients.
- [09:31]
C
Yeah, I mean performance fees, at least in theory, do provide a better alignment of incentives between investors and managers. Right, yeah. So is this the, Again, I'm not an expert, but is this just the first kind of performance fee in the CTA space or is it the first performance fee in the, in the ETF usage space generally?
- [09:49]
B
Well, I mean ETF usage, ETF is I think a very new thing. Right. Usage has been around for a while, usage etf and frankly again, this is almost like two people not knowing very much about a topic leading each other, which is not a great thing to do.
- [10:06]
C
Listen to traders unplugged for uninformed insight about ETFs.
- [10:10]
B
Yeah, I think that should be the new tagline. But one of the key differences in terms of my understanding is of course that with an ETF you can trade it intraday, while with usage you have to trade it at the nav and it's only once a day. And in my view, of course it's biased, at least at this stage, as long as we don't have an etf. I'm very biased towards kind of just usage that is for my clients, frankly there is no need to have something that can trade intraday where you can end up paying more for just waiting for the nav. I mean we're talking about long term investments where encouraging people to put this in as a core allocation in their portfolio. Why do you need intraday trading? You really don't in my opinion. I know there will be some other reasons maybe and it's easier to put in a, in a ticker of some sort in a model portfolio.
- [11:08]
C
Yeah, I'm going to put the other argument across Niels for sure because I agree with you. I think we don't need intraday trading of long term investments for sure. But, but you know, so my, my, you know, all of the investment kind of accounts like in the UK for example, you know, if you want to put money in the two main sort of types of account, ISAs and SIPs, which are, you know, different tax shelter savings accounts, you're really restricted to either buying shares or buying ETFs. You know, you know, it's, it's. And if you want to get into other things then you can do it but often it's very dependent on the platform you're using. So you're sort of tied to a specific platform and you're also, then you know that platform will give you a list of investments that, that they're okay with and that may not be the ones that you want. And also there's often then additional platform fees to pay. So it's just another layer of fees on top which you know, if you were in a sort of general account that could only invest in ETFs that wouldn't be the case. So yeah, I, I, you know, I'm, I'm, I'm a big, for my own sort of personal investment on the long only side, you know, I'm, I have big allocation to ETFs and, and I would be quite tempted to be honest because you know, at some point I'm going to probably get to, well, not old necessarily, but I probably can't. At some point I'm not gonna be bothered running a kind of systematic futures trading strategy. You know, like when I'm 98 or something, you know, and it wouldn't, you know, it would make more, it would make sense at that point for me to, to potentially just buy an ETF instead and have that as my alternative
- [12:44]
B
or maybe to get a pure true offshore cheap hedge fund. You don't need to worry about.
- [12:52]
C
Yeah, but as I said that that's not necessarily an option for a lot of people.
- [12:57]
B
I understand. I'm teasing you. Okay. Anyways, the other thing I noticed, and this was just kind of more. It is obviously politically to some extent, it's just that we've seen now a long time where the current administration has been really trying to get Jerome Powell out and they've even sued him and so on and so forth. And then I noticed a comment by Scott Besant who was apparently speaking at something called Semaphore World Economic event in Washington D.C. on Monday and where he basically said, yeah, it seems to make sense for the Federal Reserve, they should wait and see before deciding whether to lower interest rates admit the Iranian war. So I'm kind of thinking, you know, it's kind of weird to see mixed,
- [13:49]
C
mixed messages though, because Bessant's boss, no, no, he who shall not be named as Eve. You know, just only yesterday, the day before, attacked Powell again, which just frankly seems bizarre because I mean, it's only like it's only got a few weeks left of his term anyway. So. You know what?
- [14:05]
B
Sure.
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C
Anyway, yeah, I'm gonna try not to talk about that, man.
- [14:09]
B
Yeah, yeah, no, no, I know that that's the, that's the arrangement we have when. But anyways, let's reverse to something we maybe know a little bit more about, which is trend following. My own Trend Barometer finished at 55 yesterday, which is pretty strong. Not the strongest we've seen this year, but it's strong. And I think that corresponds pretty well with what's going on so far in April. Of course, equity markets, as we noted a few minutes ago, has had a pretty strong recovery. So no surprise that perhaps managers with longer term time frames and who may not have, well, they would have reduced their exposure, I'm sure, in March, but they may not have gotten short equities and they will most likely benefit somewhat, relatively speaking, from holding on to some long exposure. But also some of the other things that have moved so far in April are metals. They're back in favor again. And, and some of the currencies, some of the, I think resource country type currencies are doing pretty well. So let me run through the numbers and then I'm interested to hear what, what you're seeing on your side, Rob. But as of Tuesday evening, and I think yesterday was a pretty uninteresting day, maybe some managers made a little bit of money, others, you know, would have lost a little bit, but nothing major. But anyways, as the beta 50 was up 51 basis points in April, up 8.03% so far this year. SoC gen CTA up 58 basis points, up 8.06% this year. The trend index SoC gen trend up 52 basis points, up 7.73 for the year and the short term traders index up 22 basis points, up 4.64%. However, the big winners are equities this month as mentioned. MSCI World up a whopping 7.82% so far. Now back in the black for the year up 4.07 and the S&P total return index up 7.62% in April so far as of last night, up 2.96 so far this year. And then finally the US S&P US aggregate bond index also making a little bit of headway this month, up 65 basis points in April, up 69 basis points so far this year. But share some of your experiences so far this year.
- [16:40]
C
Rob. Well, yeah, actually what I'm going to do if it's okay with you Niels, I'm going to talk briefly about this year and then I'm going to take a sort of 12 month view because one thing I do every year is do a review of my performance which is aligned with the UK tax year which for reasons far too tedious go into runs from 5 April to 5 April in the following year. So and I think that'll be interesting for people to give a. Yeah, it's
- [17:04]
B
an interesting time frame definitely.
- [17:06]
C
Yeah, yeah. Around the sort of markets and around the sort of signals that I've seen working or not working in the last 12 months. But yeah, let's do year year to date so far. So yeah, I mean I was up towards the end of March I was up about just kind of reached a peak of nine and a half percent up sort of late February, gave back a couple of percent of that in March and actually probably another percent or so in April. So I'm actually up about, I don't know, 5.8%, something like that. Just looking at it by eye, taking quite a lot of risk off the table. I think it's fair to say it's quite a difficult market to trade at the moment and that is reflected in sort of weak signals and forecasts. So if I look at my current risk level running at about a third of my kind of long term targets, that's very low. That's kind of something that's analogous to a trend barometer by the way, Nils, in terms of what it means. And if I look at my exposure by, by Sector I, my biggest exposure is. Is. Is actually long equities but when I say big it's not that big because as I said my risk overall is, is pretty low. I'm also long, you know, a little bit of energies and I'm, I've got a reasonably sized short position in bonds. So you know it's, it's not really obviously pinned for one thing or another to happen because the, you know, there's just so much uncertainty about where things are.
- [18:33]
B
A bit of inflation, that's kind of the.
- [18:35]
C
Sorry.
- [18:35]
B
A bit of inflation maybe? Is that kind of.
- [18:37]
C
Yeah, I mean long, long equities, short short bonds is kind of inflationary but. But I'm you know, and a little bit of long energies. So. So yeah, I don't know. I mean if, if this sort of oil shock plays out as I kind of expect it to then then then I would probably be flat to be honest because I'd imagine the equities position would, would get hit and that would be balanced out. So we'll see how that goes. But let's, let's take a slightly more long term view then. So from the, for the time period I said which is 5th of April to 5th of April in my futures trading I made. Drum roll please. 23.7% and the sort of. Most of that money was basically made in two periods. So from, from kind of, you know, so the, the sort of year started badly as we know that was sort of coming out of the tariff tantrum. But from kind of late May to sort of mid October I made pretty decent money. And then that sort of went sideways for a bit. And then from late December to early January I made a lot of money very quickly and I've kind of gone sideways since then. And that second, second ramp up obviously is the sort of now famous kind of metals bubble which we talked about actually in the last podcast. I think in terms of position sizing and how that affects the position and the way that P and L was taken out of that. So that's quite nice. Interestingly. So I do a number of different kind of deep dives analysis on that and that as well into a number of different things. So one thing I do is look at a couple of benchmarks. I look at the SOC Gen CTA index but I look at that just on an outright basis but also on a vol adjusted basis because my volume is quite a lot higher than theirs. And I also look at a fund run by my former employers AHL because you know the obvious people to compare myself against, of course, but also that fund is denominated in pounds, as is my own trading account. So it's more of a, it's kind of more of a direct comparison if you like, because it means there's less sort of currency related noise and interestingly so I made sort of, yeah, actually I made about 26% because I'm looking at month end performance rather than April 5th to April 5th. And the relevant figures were for the AHL Fund 18.1, for the SoC Gen CTA Fund 15.3. But that's before the volume adjustment. After the volume adjustment actually they're slightly ahead of me, so about 30% each. So I'd say, you know, net net slightly behind the benchmarks and some of them. My theory for that, which I'll talk about in a second when I get onto different signals and forecasts is because I'm less pure trend following than them and pure trend following did better than the other signals that I have in my portfolio, which I have a more higher weight to. But last year, which obviously was a terrible year for the industry, it was the other way around. So my wider variety of signals kind of saved me from. And my relativity performance was actually very good compared to those. So, you know, swings and roundabouts. The other thing I do is look at market by market performance. So on asset classes, you know, some of my best performing asset classes were equities, which. And metals. Metals, perhaps not a surprise because we've already talked about silver. My worst was actually bonds. So would imagine it would have been a tough 12 months for anyone running a kind of fixed income focused cta. And coincidentally I'm having coffee with our mutual friend Yoav tomorrow.
- [22:21]
B
Oh, nice.
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C
So we'll maybe chat about that in terms of individual markets. So the best market for me was Silver, so not perhaps a surprise there. The second, interestingly was actually live cattle, sorry, feeder cattle, apologies. And then there's some various equity markets up there. So silver, we've kind of talked about feeder cattle. Actually there was a much nicer kind of market to trade because it had a fairly decent trend upwards for most of the year up to about October and then it sold off and actually closed my position and then there was another little run up which I was able to participate in. So actually that's quite a nice smooth journey. Whereas silver as we talked about last time, was quite a violent move to say the least. So that, that's quite interesting. The other thing I look at is individual trading rule performance. So I've already given some of the story away but generally speaking to you know, divergent, we might call divergent trend type signals did, did better. And actually the best, best of all of those was the, the my sort of kind of what I call my core momentum signal which is just literally exponentially way to moving average crossovers and that did the best of all of those. So that's why I'm sort of thinking as I said, I underperform the purest CTA industry more widely. But the other thing that's quite interesting is on almost all of those divergent signals, the best performing out of them was the slowest, the slowest of those. So it was really a really, really good year for slow trend following. So that's true in I'm just looking, I can't see a single place where even if you ignore costs where my very fastest signals did better than my much slower ones. Then on the convergent signals, that's the non trend following which as I said I've got higher exposure to than most people. So carry was kind of flat, maybe slightly down. Relative carry was up a little bit. And then I have, I have a skew based signal which basically looks for markets where there's been, you know, effectively recent fat negative tails and then buys them. So it's kind of a bit like a bouncing cap strategy you might say that actually did quite well. So that that sort of helped a little bit. And then the final thing I look at is my slippage and my costs and they were, you know, the way I like to say sort of talk about this is performance is random, costs are not. Costs are very predictable from year to year and very consistent. And there therefore you should kind of give them a bigger weight in considering how to trade than you would performance. And my costs are exactly in line where I'd expect them to be. I think they're about one or two basis points different from last year. So that's very satisfying to see. So yeah, an interesting year and like I said, a good year to be overallocated to slower trend following and you know, not a sort of interesting mixture of where, where the money came from from, from a sort of asset class basis. But yeah, always nice to have a 20% plus year. Whatever happens.
- [25:46]
B
There we are, we try to, we try to please when we.
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C
So the whole, the whole time I was talking you were just, I was
- [25:52]
B
just waiting for that moment to applaud you. Of course.
- [25:57]
C
Thank you.
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B
All right, good stuff.
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C
You're too kind.
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B
Okay, good stuff. Okay, let's jump on to some of the great questions we had from our community. The first one that came in is from Mel. He. He or she. She, I guess. Ask how would you differentiate among the large London trend followers what are their strengths, weaknesses, competitive advantages and such?
- [26:29]
C
So I don't like this question, I'll be honest, but I thought it was only fair that we try and answer questions even if we don't like them.
- [26:38]
B
Now you have to be specific in explaining why you don't like them.
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C
Well, exactly. Well, one reason is that I know people working at all of the large London hedge ctos and I'd hate to kind of pick one out and say that, you know, you know, that say one one is better, better than another. And, and then there are, there are firm, there are reasons why I might not like particular firms, which is more subjective to be honest. It's not to do with their, their sort of investment process and I'd be far too polite to, to pick those out as well. And you know, so, so that, that sort of in mind. But I think we can perhaps talk more generally without being fair or unfair about what we would look for if we, let's say we were allocating to a CTA and we decided that that was our subset of CTAs that we would want to look at. What would be on the sort of list of questions that we'd ask and sort of in terms of our due diligence process and what would we be looking for? That I think is a fair question to answer. John, do you want to kick off on that, Niels?
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B
No, I mean again, because I have to kind of be neutral. I think the main thing that I've noticed in terms of the. I think the question was focused on London based managers. I actually think that we have to recognize that a lot of the managers specifically in London has the same origin, which is ahl. And my impression has always been that to a large extent the successful ones to some degree actually use more or less the same methodology which was a European methodology that got developed, unlike the US methodology which was more kind of breakout style, either volume or price breakout. I feel, and I could be completely wrong, I feel that it was much more moving average driven and maybe later time series momentum driven by the Europeans. Even though of course US firms have also adopted certainly times his momentum later on. But I think a lot of it, and obviously I'd love to hear your thoughts on this, but it's not necessarily that people use different methodologies, but it's kind of more the details about how we maybe manage the data before it goes into the engines, what criteria we may set for targeted volatility, targeted risk, of course, a big driver of difference between the firms, I would imagine, are just simply the markets they choose to trade. And these are not new things. Right. So it comes down to speed, methodology, markets, universe. So. So that's how I see it. I don't, I think, because I think all of our colleagues, established colleagues in Europe, in the US that are all doing great stuff and many of the firms have been around for decades. And I think that's a great testament to generally having real sound research teams, business models, of course. So I don't have anything, I don't have anything sort of more specific than that, because I don't want to be. Even if I may have access to information, I don't want to say something that I can't back up in the same situation.
- [30:08]
C
Yeah, I mean, the historical thing is quite interesting. I've talked about this before as well, the fact that the European hedge fund industry has a single parent, if you like, although it's slightly more nuanced than that, because before Man Group bought ahl, they bought a fund called Mint. So there's a little bit of the Mint, and Mint was a US fund. So there's a little bit of this sort of Mint lineage in there. But the fact that the systems were originally designed by three guys who all did physics at Oxford means that the
- [30:38]
B
way they were all at Oxford, I think they, they would be offended because I think one of them came from Cambridge, if I'm not mistaken.
- [30:45]
C
Anyway, they were all physicists. We can say that with, with, with with certainty. But yeah, I think you're right. I think it was two at Oxford, one at Cambridge. And that used the joke, used to be at ahl, that their idea of diversity hiring was hiring a physicist who hadn't been to Oxford or Cambridge. And the. But the point is that those systems were designed with sort of. From a kind of scientist type kind of looking at things from a sort of more of a scientific basis. I'm trying to, not to be rude about the US hedge fund industry here, but a lot of the US CTAs grew out of floor trading, I think it's fair to say, and grew out of guys who were trading on the floor and had a very particular way of looking at markets. Whereas I think the Europeans came across as more scientific. I'm not saying that either approach or wrong or better or worse, of course they have the advantages and disadvantages, but that is quite interesting. So I kind of agree with you about the details. So there was a very good British cycling team called Responsible by Sky originally that was sponsored by ineosu very well in the Tour de France and other competitions. And the coach is a guy called Dave Brailsford who's also the coach for the British Olympic team. And he had this concept of what he called marginal gains. And the idea is that there isn't like one big thing you can do, but you can do lots and lots of small things really well. So you know, I talked about slippage for example, you know, so if you can knock 50 basis points off your slippage, you might think that's not very much but actually that's 50 basis points pretty much guaranteed every year forever. Whereas if you add 50 basis points onto your top line expected performance, well, some years you might get that, some years you might not. Because that's randomness, you know, diversifying through adding lots of markets, for example, making sure you're not trading they're not markets too quickly, making sure you've got accurate estimates of costs, making sure you haven't overfitted. All of these things are quite small, but added up they can make a big, you know, quite a big difference. And I would say absolutely that that's what the big firms or the well established and the good firms tend to do, tend to do better. So, so I think that's, that's, that's definitely something I'd be looking for if I was, you know, doing due diligence. I wouldn't probably be asking about the sort of kind of quote source of alpha unquote because they wouldn't, probably wouldn't tell me that I'd be asking quite tedious questions about, you know, things like operational processes and cost estimation. Because that, I believe that focusing on those details is what tells you whether somebody is likely to be good or not.
- [33:18]
B
Next question is a long one, or at least it's a long question. I don't know if the question itself is long and we'll, we'll spend a little bit of time on it. But, but obviously there are other things we need to cover today. It is from Matthis. He writes, my question is about where in the systematic futures trading process you think mathematically complexity pays off. Where do all the PhD in the industry add value? Am I missing something? Of course I understand that if you're doing exotic derivative pricing or very short term trading, you can use more math. But even plain CTAs and slow trading firms seem to employ a lot of PhDs. What are these folks doing all day Nothing against PhDs, of course, but I'm just generally curious.
- [34:07]
C
Yeah. So I should disclose that I do not have a PhD. And Niels, I don't think you do either. So again, we're talking about things that we're completely unqualified to discuss. Again, this is the theme of this. I think the title of this particular episode could be, you know, two Ignorant People or something like that. Anyway, two ignorant old men opining on things they know nothing about. It is true for sure, that I'm certainly in fate. And, you know, so Mattis gives a number of examples, but I'm in favor of using simpler methods, rather more complex ones. But actually, one interesting thing I've noticed is that but people who are very smart tend to have a preference for simpler things, but they have an understanding of when you can use a simpler model and when you can't use a simpler model. Whereas people who are, I would describe them as a bit clever. So maybe they have got a PhD or they're highly qualified, but perhaps they haven't got much experience, so they've just come out of school quite recently, tend to use more complex methods almost for the sake of using more complex methods, because they assume that there's a number of reasons. One is to sort of justify the fact that they've been hired at this big fancy salary. So they're probably thinking, well, I wouldn't be expected to use just sort of naive mean variance optimization or linear regression or these are quite simple techniques, by the way, given the fancy salary I've been paid and all this work I did in my PhD. So I'm going to use this more complicated method when actually when you've been around the block a few times, and this is true irrespective of whether you're a PhD or not. You kind of realize when those methods are unnecessary and when they actually can make things worse and when you're better off using simpler methods. So that's one thing I would say is that actually not necessarily experience, but, you know, or sort of rather, sorry, not necessarily educational qualifications, but certainly experience will tell you give you a better idea of when you need to go simple and when you need to go complex. So that does mean you do need to have the, the kind of mathematical artillery to go complex. So, you know, you need to know, for example, that if you do need to use a more mathematically complicated method. Well, clearly you need to have the sort of ability to do that. And so that's important. And there's nothing more dangerous than someone using a more complex mathematical method that they don't really understand what it's doing. And this, I think is the obligatory point in the episode to say AI LLMs. There's a lot of people using them who have no idea what they're doing and what's going on inside them. In fact, it's almost impossible for a human being to know what's going on inside them. And I'd say that maybe only 0.01% of people using these financial data are actually doing it in a way that's not going to go horribly wrong. So I'd say that for a start, the more interesting question I think I've discussed this before is like, if you, you know, if what we do is quite simple and also quite, in a way quite static, so the research cycle is quite long, so you can use the same model for years, potentially decades. And we know we're not in the sort of place where, if we were trading much faster, where we'd be seeing very fast alpha decay and where we'd need to have big research teams continuously finding new signals and then incorporated into our models, the cycle is much slower. And actually a lot of the things that you can do to improve your performance, as we've discussed, are not necessarily kind of quote unquote clever things. They're tedious things like properly measuring your transaction costs and then diversifying into markets, which is a process that starts with something quite tedious involving getting data and making sure it's clean and things that you don't need to be necessarily kind of super intelligent to do. So it is a kind of interesting paradox whereby it's felt that to be seen as a good quant hedge fund, you need to hire lots of really smart people. But actually in, in the CTA business, as a general rule, well, what do these people do? Because, you know, you know, it's, it's, it's an interesting one. And some people could be cynical and say, oh, well, it's a marketing thing. Like, you know, funds like to put in their slide deck. Oh, we've got 55 PhDs, therefore, in our research team, therefore we must be good. So maybe there's an element of that. Some of it's the fact that, you know, a lot of the bigger CTA businesses have diversified different things like, for example, setting up equity funds, setting up, you know, HFT teams, setting up, you know, I don't know, private credit businesses in which, and for those diversification possibilities, if you like, then yes, you would need smart people. You potentially need smart people. If you're diversifying into other asset classes. Like for example, if you're going to start trading options as well as futures, well, clearly you need people who understand how options are priced and how to build volume surfaces and things like that. So there is always work for these people to do. But for sure, I do think if I was to start up a quant hedge fund tomorrow, I think one of the biggest challenges as a manager of quant research is often making sure that they, they kind of stick to the stuff that may seem a little bit boring, not sexy and exciting and interesting and cool. Because I've noticed that very smart people have a tendency to focus on things that they find sort of intellectually interesting and then overlook the, the sort of boring stuff that, as I said, I think genuinely adds to the bottom line of performance. But yeah, I, I always use the simplest model I can. But I'd say that it, it's, you know, the best part of two decades of experience that allows me to know when that's the right model and when I need to be more complex.
- [40:14]
B
Sure. No, absolutely. I think experience is of course always underrated in terms of.
- [40:20]
C
I've just realized what I've just said, Niels. Two decades. I've been in, in the CTA industry now for just short of two decades. That is terrifying and depressing. And I know that you're even.
- [40:29]
B
I'm coming up to four decades, so it doesn't feel very long to me. But there we are. Anyways. No, I just wanted to add, I think you've said most of what I wanted to say, but it is true that certainly in my career I've often been asked this thing about, you know, how do you compete, you know, with Don. We've had sort of one, two PhDs at a time, you know, in the research team, but actually long term performance has been better than firms with, as you say, 50 PhDs. How does that work? So I don't think it's, it's not necessarily the quantity. I think it's definite. You need people on your team that can work with very large sets of data and have that, you know, background to, to do that. But it always comes down to having people who can think outside the box and as you say, maybe take certain things that, you know, most people might go in one direction and maybe find another direction to go. And whether that's simplification or it's looking at the, the challenge in a different way. And, and certainly it's probably not spending much time on signal generation. It's probably all the other things including risk management and so on and so forth. But rest assured, I think most PhDs earn their full wage at these firms. So it's by no means.
- [41:52]
C
And if there's a university out there that wants to give the two of us honorary PhDs, I'm sure we would gladly.
- [41:58]
B
Maybe the only way we're going to get one.
- [42:00]
C
Yeah, well, for sure. One really, really quick thing, Nils, is to think you went said about thinking outside the box. I think it's really important to have a diversity of thought within a research business. And you know, I think, you know, we joked about it but if you did literally just hire physicists you wouldn't have that. And I think, I think I was the first economist that was hired by ahl and certainly I'd like to think I brought some diversity of thought against all the mathematicians and physicists that they employed. I think that's still true.
- [42:33]
B
Yeah. Okay, cool. We're going all the way to Canada now for a question from Paul that came in. My question to Rob relates to the process of assigning signal, e.g. trend carry skew weights to the instruments and asset classes he trades. My memory is that he advocates the same weight across all asset classes. I think part of the motivation is to avoid overfitting. I was curious of his insights on deviating from this approach because of crisis alpha considerations as some rules, for example equity skewness, have large equity crisis exposure.
- [43:12]
C
Yeah, it's an interesting one. So actually my sort of big kind of thing I'm doing this year is I'm going to do a big research project on fitting and backtesting and one of the outputs of that will be a book. I don't think I've mentioned it but I do have a book coming out in December. So it won't be that book, it'll be the one after that. But, but I'm sure there'll be many opportunities to plug plug the December book coming up but, but that's not for today. So the, the one of the things I do do at the moment is actually correct is I do actually basically assume that all instruments are the same as far as fitting goes. So I use the same ignoring costs, I use the same forecast weight. So I've got the same allocation to carry to trend, different trend models within that and so on and so forth irrespective of the instrument concerned. Now one of the things I'm planning to do in this giant project is to actually test, have something that tests that assumption statistically. So the way you might think about how this would work. What essentially it would do is look at, calculate the weights for different asset classes and instruments like the S and P, the US 10, gold, silver, feeder cattle, bitcoin, whatever, and then say are any of these weights sufficiently close to each other that we can treat them the same? So you might expect, for example the US 5 year and the US 10 year bond would trade similarly enough that you would have the same signal allocation to those two assets, in which case you'd then essentially pull your fitting across those two assets and use the sort of joint information between them if you like. So that, that's kind of the, the idea at the moment. It's just, just the sort of drawing on the back of a napkin. So it's, you know, watch this space in terms of whether, whether I, I get that to work or not. So because I think one thing that's worth saying actually is, you know, with certainly when, when I was at AHL the second sort of last few years, the way this process was done was each individual asset class team did their own fitting and so they may have ended up with different weights. So the question is whether that, you know, one question we kept asking yourself was does that add any value or not? So this is a sort of rigorous way of exploring that option. Now what's interesting about Paul's question is he actually talks specifically about, you know, crisis alpha. And every time I say that I feel I should add in brackets copyright, commitment and. But so this is slightly different because what you're sort of saying is that but what we call our objective function when we're fitting. So rather than being just say maximum Sharpe ratio, the objective function is going to be a little bit more nuanced and subtle than that. And it's actually going to say, well, I don't want to just have maximum Sharpe ratio, I want to have the best performance in crisis situations. I think last time we were on, we talked about a man group paper where they did something like that, right? They said how would your weights be different if you focused on crises rather than just on maximum Sharpe ratio? So it's an interesting question as to, as to whether that separately is an approach that you would use or not. So I would say that if all of your money was just in trend following and you had no other investments at all, then you definitely wouldn't do this. You would just focus on maximum Sharpe ratio. If on the other hand you had a portfolio consisting of some bonds, some equities, and then you add a trend following to that, then what you should be doing is optimizing the sort of joint performance of that portfolio. And one way of doing that is to make your CTA portfolio as sort of crisis alpha friendly as possible, if you like. So that sort of kind of makes sense. I'm not sure whether I'd necessarily go down that approach myself. I think I'd probably do something that would be a joint optimization of my equities, my bonds and my CTAs and that would do things like. So, you know, if you do that, it would do things like, for example, reduce your risk weighting in equities and bonds in the CTA sleeve because you already have an exposure in the other parts of your portfolio and because those assets have gone up over time, you'd have a long bias to those assets. You kind of already got that exposure elsewhere, so you need less of it in the CTA portfolio and you'd end up allocating more to, you know, things like ags, for example, and you'd probably also speed up your CTA portfolio a bit as well in that process as well, so that those are the kind of things you'd expect to happen. And you may also, as I haven't looked at it myself, but you may also end up changing your weighting between divergent and convergent within asset classes as well, potentially to get that extra crisis alpha. So you'd want maybe more like trend in equities than carry because you want back that sort of responsiveness of to sell offs of equity shocks to be very, very sharply defined. So it's an interesting idea. I probably wouldn't do it myself, but I am, as I said, I am exploring the idea of being a little bit less kind of strict with my fitting and going down the route of allowing my weights to be a bit different, but only if there's statistical evidence of that.
- [48:42]
B
Well, it kind of fits nicely into the next topic we're going to talk about because it is the latest paper from our friends at Quantica and it's called if you can't beat it, Stack it. But before we dive into the paper, let me just give you a big shout out to Bruno Nicholas, Rob Arthur and the whole team at Quantica, because they very kindly invited me this week to their annual investor launch in Zurich. And, and that was a great opportunity, not just to meet the whole team, but actually they did a really good job in terms of presenting some very relevant and interesting topics, including what we're going to be talking about, some of the research. Of course, we, we owe them a lot because they produce great research that we talk about every time it comes out. So yeah, just a wonderful opportunity, which I'm grateful for. So let's, let's talk a little bit about their latest paper. It's not that we're going to be doing any. Anything that will replace people should go and read it themselves on the Quantico website, of course, but we'll talk about some of the observations and maybe some of the different ways they have approached the problem because the problem has always been that it's been certainly in the last couple of decades maybe it's been very hard to beat equities and people often compare like a long only equity portfolio to say a trend following strategy. And to be frank, most of the time in the last 15, 20 years, as I said, it's been very, very hard to, to beat those returns that they've produced. But maybe, maybe the question is you don't necessarily have to sell your equities in order to benefit from having some trend following exposure. So, so I think that's really what the key takeaway from here. Now, Quantica are not the first people to talk about this. I actually remember back in the 90s working with Jerry that we looked at portable alpha strategies. We, I don't think we ever launched anything, but it's not a new concept. We know that Corey Hofstein has done a great job in that. And of course one of the first ones to reignite the interest was really Eric Crittenden and Matt over at Standpoint who launched I think back in 2020 just before COVID an interesting time to launch a strategy like that. But it proved the concept. And so that's why I think it is relevant even today because not enough investors look at their equity portfolio in this way and certainly not enough people have, have made the jump into putting a meaningful allocation into trend following along with their equity exposure. So can I turn it over to you, Rob, and talk a little bit about your kind of observations from this paper and maybe some of the things that Quantica does perhaps a little bit differently in their approach to this.
- [51:58]
C
Yeah, so portable alpha, which is the sort of like the old fashioned term, I guess as you say it was around in the 90s. In the last few years return stacking has become more popular and the idea basically is to sort of get away from this idea that, you know, when you're doing a portfolio allocation you have, it's like a piece of pizza and you have to kind of cut the pizza up into slices and you, you know, so would it be 60% in equities, 40% in bonds and then you know, you carve out a bit of the pizza for trend following, say to get away from that, that sort of simplistic idea and to say, well actually what we're really doing here is we're buying risk and we're buying risk with cash and the, the, the sort of, you know, the sort of different levels of efficiency of when you're doing that. So for example, if you were to buy short duration bonds with cash unleveraged, that's a really poor thing to do with your cash because you're not getting, you're not buying much risk and you're using a lot of cash to do that because it's a, you know, an unleveraged position, so it's a 100% funded. Whereas if you're buying that exposure with, with say a future, then you can, I don't know off the top of my head what the margin is, but it's probably not that different from about say 10% I think on a short US bond. So that's a very highly cash efficient thing to do. And if you look at a CTA portfolio as a whole, so I run with a 25 volume risk target which is a bit higher than most of the industry, but my cash usage typically is about 30 to 35%. So if you sort of scale those numbers back to sort of industry levels which are kind of similar to equities overall. So if you say, well, globally diversified basket of equities probably runs at say about a 15% volume. And if you run a CTA at a 15% volume, your average cash usually is probably going to be around the 25% level. So it's a very 25% cash. To get 15% volume is an extremely efficient, you know, use of cash. And that, that's not because CTAs or trend following itself is some kind of magic. It's purely because you're doing it using futures and futures are, you know, very, very cash efficient. So what that means is, is you, you kind of throw away the idea of your, your fixed piece pieces, slices of pizza and instead you, you say well actually we can make, effectively make the pizza bigger because you know, if, if we were just buying CTAs, our, our instead of having the sort of small, sort of eight, you know, 12 inch pizza, we'll be able to buy a pizza that was four times bigger than that which would be like a 24 inch pizza which would barely fit on the Plate. So that, that's sort of the, the kind of, you know, the lame, the layman's guide guide to what they're doing. The, the nice thing about this paper is I really like papers that kind of used maths correctly, but also in an intuitive way to sort of show an intuitive result. And this paper really does that. I'm a really big fan of papers that have kind of nice graphs that you look at and immediately you don't need to read the rest of the paper. It just makes a lot of sense. And in this question. So they've done that in some interesting ways. So what they sort of said to begin with, as you say, the point of the paper is, well, what's the best way of diversifying equities? And they look at a number of different alternative ways of doing that. So one thing that is interesting about the paper is that I think the kind of span of things they look at is wider than. So a lot of the time you read these papers and they're like, well, you want to diversify equities. Well, you can either go into bonds or trend following. Well, you know what, guys, the universe is a bit wider than that. There are many other things we could be doing, right? So they look at a number of different alternatives. So carry equity, market neutral, gold, Treasuries, long volume, short volume, equity long, short. So, so fairly standard sort of, you know, sources of alternative beta, if you want to use that term. But as I said, it's nice to see a variety of them in a single paper. And then what they basically do is say, well, these things have got different correlations to equities. And you know, intuitively we know, well, we want to have more of the things that are less correlated. But unfortunately in finance there's no free lunch. As I keep saying to you, Niels, you've got to appreciate this. In finance there's no free lunch. And things that are lower correlated tend also have to have lower returns. So diversification doesn't come for free. And because equities have just been this outstanding asset class, anytime you move away from them and into things that are more diversifying, inevitably there is a cost of lower performance. But the nice thing about the sort of return stacking or portable alpha approach is that you, because you can use leverage, that means that the improvements in diversification you get in the form of an improved Sharpe ratio, which would come with lower returns. If you had a fixed sort of piece of pizza, you can actually convert those into higher returns by sort of whacking your leverage up again as long as you don't get too crazy. And you're able to do this obviously more if you're adding a more cash efficient strategy rather than a less cash efficient strategy. So the sort of then three things determining what your optimal portfolio is going to be, the correlations we've discussed lower the better. What you might call the return trag or the diversification drag. So that's the loss of performance as you add things to this portfolio and then thirdly is the cash efficiency as well that also has an impact. So yeah, they've got this really nice graph and it basically shows that. But you know, essentially there's a sort of maximum amount of you can add to, you know, an equity strategy depending on these things. And that means for example if you add say I don't know, something like a short volume strategy, which obviously is going to be very correlated with equities because in a crisis short volume is going to get hammered, you know, non linearly to equities, maybe exponentially worse then you need, because they're so correlated you want to have quite a small allocation to those as a diversifier, maybe 10%. Another extreme, a long volume strategy. Unsurprisingly you know, because its correlation to equities is actually negative. You can actually have an allocation that's over 100% theoretically. Theoretically. And you know, there should be many caveats and warnings. These are all theoretical results and all past performance snow guide to the future as usual. But, but some more reasonable things like say trend following gold or Treasuries which also kind of sit in the middle. You can kind of stick 50% of your portfolio quite happily into these without, without any issues of, you know, 50% is way more than, than you know. So even people might be running 60, 40 equities to treasuries portfolio still. But no one's running a 50% trend following portfolio. Well I am at the moment, but that's another story. I'm a bit crazy and you know, only the most obsessed gold bug would necessarily have such a high allocation to gold. So that, that, that kind of result I found, I found very, very interesting. So that's a sort of theoretical result. And then they, they talk about, they're going to sort of details about. It's a very, there's another very nice picture which is figure 5 which I can't possibly explain because it has lots of lines on it. But I find it very intuitive in terms of understanding the trade off between adding things that are less correlated, more diversifying but then perform worse understanding that trade off in a very intuitive way that I'd never seen before. So yeah, it's a very, very interesting paper and I think anyone who's thinking about doing any kind of allocation should, should definitely be reading and understanding it because even if you're not potentially a CTA investor, I think it gives you a really good intuitive understanding of essentially the problem of portfolio optimization when you have different levels of cash efficiency.
- [60:26]
B
But you're right, I think there are a couple of things just to, I wouldn't say dumb it down but just kind of the basics. Right. I think a lot of investors, when they think about how to diversify their, their portfolio, they think about let me find something different that has a high sharp ratio because high sharp is always good and, and what they're, you know, concluding. And again as I said, it's not, they're not the first ones to conclude but it is a very important point and it really isn't about finding something with a higher Sharpe ratio. It's finding something that behaves differently that allows you and, and is cash efficient, that allows you to, to, to have a sort of a sizable addition to your, to your portfolio. So it's this room to scale that is so important. And I will mention one other thing from the paper that I think is relevant and that is they also, as you rightly say, they include other things and, and they include gold. And of course gold comes out very well in many of these statistics because it's had a phenomenal run pretty much since the inception of the soc gen trend index in around 2000 when gold was trading at I don't know, 200 or something like that. So obviously these numbers look great. So what I love about the analysis, not to fool people, the team at Quantica goes back and say well let's just look at gold. If you had made this since the 1990s, if you went back to 1990 and took that decade, what it would would have looked like. And they basically say that gold futures would have produced a cumulative return of negative 53%. So this is why when you look at these studies and analysis you need to really be careful and consider periods that may not be included in the study itself. And I love the fact that they, they just make that available for people to, to do, to do that.
- [62:32]
C
I mean the other thing you can do is incorporate some notion of forward looking returns which is a bit dodgy and a bit hand wavy. But one of the things I do quite a lot is just assume that all Assets have the same Sharpe ratio, for example, forward looking, which doesn't seem to me unreasonable thing to do compared to say assuming that the incredible run in US equities, for example, versus other equities would continue into the future. And the other thing you can do is look at the fundamental sort of returns you'd expect an asset to get. So you know, for example, in equities it's not unreasonable to expect that you'd earn sort of price earnings ratio with a sort of inflation component attached to it. And you know, I'd think in gold, to be honest, I think I would. If you ask me what my long term forecast for gold is, I'd say, well, probably just inflation plus zero because it doesn't, it doesn't earn anything. And although speculative runs and temporary demand runs may drive its price temporarily up, eventually there's enough of it left in the ground, I believe eventually the people will just mine some more and then that price will come back to a kind of long term trend. So I'm pretty confident if you go back far enough, you'll see that gold to gold, if you kind of plot an inflation line, the gold will have just gone around that with big swings, of course, huge swings. But that would be a reasonable.
- [63:54]
B
I think you're absolutely right and I think I've seen that chart going back 50 years or so. So that lines up well on that
- [64:01]
C
basis you'd probably say well maybe, yeah, you should have a little bit of gold in your portfolio because maybe it is a diversifier, but, but you know, given its return is, should be systematically lower than say equities, bonds or dare I say it, CTAs, then that allocation should be relatively low. But you know, I'm not a gold guy. You're not a gold guy. We're talking about things we don't understand.
- [64:21]
B
Again, there we are, there should be some bitcoin.
- [64:24]
C
Should be some bitcoin.
- [64:26]
B
Then we've done the full thing. No, I mean, and to just round it up. Before we move on to another article we wanted to touch on, I mean we did a study at our, on our side at Dunn six months ago. We'll probably update it with some new figures. Just looking at, actually if you just look at the alternative universe, what are the best strategies to combine with an equity portfolio? Because again, there are certain hedge fund strategies that get all the attention. But actually when you do the crunch, when you crunch the numbers, there's really only one standing and that is trend following. So it's not that we are, well we are biased, everybody knows that. But we also have the evidence to back us up when we make these claims and I think that's super important. Even though of course we have no idea what the future will hold. Anyways, let's turn to an article from another great source, namely Hedge Nordic. Wonderful publication that everybody should subscribe to. They had a number of different articles out, some CTA related, and the one that caught my eye is, you know, recently I had Andrew Beer on the show and he talked very much about replication from his vantage point. And they took a little bit of a different view on kind of the ETF versus CTA style space. And Drew, I would say in fairness, some slightly different conclusions in terms of outperformance or lack of outperformance by ETFs. So what were your thoughts about the way they approached the, the topic, Rob?
- [66:17]
C
I'm assuming that these guys, Hedge Nordic bought you some nice pickled herring or something, did they? In exchange for this?
- [66:24]
B
No, I'm not sponsored by anyone.
- [66:28]
C
Okay, so no free lunch in this case. Yeah, it's quite interesting article. So the sort of managed futures ETF space has been around in fact I think looking at the dates in this has actually been around since 2011. But their analysis only goes back 10 years to 2016 because I guess they wanted to have a few, you know, sort of more than like one fund essentially in the universe. So going back 10 years means they've got a couple of funds. And so just to say, sorry, this, I believe it's just pure US ETFs. I could be wrong.
- [67:02]
B
I think you're right.
- [67:04]
C
Yeah, so there's 13, there's 13 of them. And so there's sort of a reasonably even split now between what they call CTA ETFs, what they call replication ETFs, which of course would, Andrew would be the expert on those and what they call other ETFs. Now they make some good caveats about the fact that it's not been 10 years is a reasonable length of time. But many funds have been training for much less time. But even 10 years actually you may not want to draw too many conclusions from that. In terms of performance of course, because is it statistically significant? I don't know, I haven't checked. But it's better than nothing, clearly. So they've looked at as you, one might expect, both performance and correlation, but also interestingly what they call crisis alpha. Again, copyright Kaminsky. So maybe starting with the sort of, of, I don't know, with the correlation first so they look at the correlation to the, as mentioned many times already on the podcast, the SOC Gen CTA index and they find pretty decent correlations. There's a nice scatter plot in there which is always good to see the sort of a kind of hand waving discussion that maybe some kind of ETFs are got a higher correlation to the index than others. I'm not sure the data is enough to tell you that, but certainly you'd expect, you know, obviously if you've got a replication ETF that's trying and its benchmark is the SOC Gen index and of course by construction it should have a high correlation with that, otherwise it's just not doing its job properly. Whereas you know, some arbitrarily chosen managed futures ETF that hasn't got that as a mandate, then you know, clearly won't necessarily be sort of aiming for that. So that they all, you know, generally speaking they all have a pretty reasonable correlation with, with the Sockgen CTA index. I'd say that the correlations are, you know, if you were to choose 13 random CTAs and actual funds rather than ETFs and look at their correlations, you'd probably find they were quite similar. So that to me that's, that's some sort of test I would apply and I think they're pretty similar. So that's correlations performance as I said, because 10 years isn't necessarily a lot of time, is it long enough to judge? I'm not sure. So I think the sort of, as I discussed right at the beginning I was talking my own performance really this is a trade off probably between what you might call tracking error or perhaps let's call it a simplification tax. So if the ETF is doing something is forced or constrained in some way such that it can't do what the, you know, the sort of pure CTA can do, whether that be a limit on the number of positions on the types of markets that can be traded or in the case of a replication etf, if it's being done from in a top down way that limits the number of contracts you can trade for reasons which I've discussed before and there's also a blog article I wrote about it that's not a criticism of Andrew or anybody, it's just pure maths, isn't it? And there's sort of no way you can get around it really. But the question is how much that will detract from performance versus potentially gains you would get in terms of reduced costs. And again, we've discussed the potential controversy about the exact estimation of costs and some of the numbers thrown around in terms of cost savings seem a little bit large given that, you know, you potentially still have to trade the thing. But you know, that's another, another story again but on that basis, again, you know, obviously there's a differential in performance between the different kinds of ETFs. I'm not sure that the, the figures are necessarily, you know, there's enough history here to be, you know, with some funds only been around for a few years to actually draw any firm conclusions. But again, I'd say that you, you know, roughly speaking the performance is not massively out of line with the Soc gen etf. In some cases a bit better, in some cases about the same, in some cases a bit worse. So I'd say that, you know, if you're buying the ETF as a sort of. I'm not sure whether this is the right phrase I'd use and Andrew would probably be upset, but I'm going to say it anyway. Apologies in advance, Andrew, if you're buying the ETF as a sort of poor man cta. And as I said that's not an insult because as I said earlier, many people only want to try including myself in certain accounts can or only want to trade ETFs. But if you're buying it as that then it seems like pretty none of these funds are doing a terrible job. And actually in net net it's probably a reasonable thing to do. I don't think there's enough evidence to say one way or another whether one approach is better than another or whether ETFs are intrinsically worse than the quote unquote real thing. But they seem okay. I'm not sure I can be more positive or more negative than that and I'd certainly happily probably buy any one of these and maybe even buy a basket as an alternative to my current trend following portfolio should I decide that I can't be faced with the hassle of worrying about the rolling of 250 futures contracts anymore. So that's interesting. Now the one part of the article I found a little bit opaque to be honest in terms I don't really understand how they did the calculations and maybe I need to read more closely or maybe this is something they explain elsewhere. But they do measure crisis alpha, but I'm not sure exactly how they calculate it. So I don't know whether they're doing a sort of episodic thing which is, you know, where you Say, well, you know, all this was a crisis, this was a crisis, this was a crisis. Or whether they say they're defining a crisis as a move systematically, as a movement of more than X downwards in, in say, you know, S and P or MSCI world, I don't know, they don't actually say either way, I would say that 10 years isn't probably enough time to, I mean 10 years has last. 10 years has been pretty exciting. And we've had a few crises, you know, principally we've, we've had Covid, we had the tariffs last year. Maybe we're on the brink of another crisis as we discussed right at the top of the podcast. I don't know. So I think statistically this is probably the dodgiest part of the paper because regardless of their methodology, there just haven't been enough crises to say for sure whether a given type of fund is likely to provide a better or worse crisis alpha than another type of fund. But maybe the lovely people from Hedge Nordic want to send me an explanation of how they calculated this.
- [74:09]
B
Well, let me just interrupt here along
- [74:11]
C
with my free pickle herring.
- [74:13]
B
So let me just interrupt here. It's not Hedge Nordic who has written the article, I should make that clear. It Alexander Mende and Pierre Iverson at RPM in Stockholm who wrote the article.
- [74:25]
C
Yeah, so pictures of those gentlemen at the top.
- [74:27]
B
Exactly. So exactly.
- [74:28]
C
Alexandra and Per, if you want to write to me and explain your methodology, that'd be very interesting. And yeah, any bribes of food would be very welcome.
- [74:38]
B
So I don't think necessarily as you say, I mean it's not that because of the limited data, and I think this is the point that I would take away from it is that, but to some extent we've heard one narrative and that is replication. It's more efficient so it will continue to outperform CTAs and so on and so forth. I think what this paper showed me is that actually when you adjust for volatility, when you adjust for interest income, because the index that is often used to Compare to replication CTAs does not include 100% interest income. So you can't really just, you know, compare it, even though you, you probably have to. But so, but, but once you adjust for these things and maybe once you use a more appropriate index such as the soccer and trend index, there has been no outperformance by replication CTAs. I think the main thing that sort of sits with me is that it's not so much whether Managed Futures ETFs works or replication works. It's just whether if you simplify the strategy, you kind of remove the edge that the investor is buying it for. To me, and that is the crisis. And as you rightly said, with your own performance and your own analysis, for example, the last 12 months, the best thing you could be is very, very slow as a manager. And guess what? That's exactly what some of these replication strategies are. They're incredibly slow. So, you know, we'll just have to keep plugging along. And as we always say, it's great that people have alternatives and for some people it's critical that they have access to these type of strategies. But I think they present a slightly different case to what I hear in terms of this, you know, quote unquote guaranteed outperformance by replication. I think they, they present a different view on that. Of course, they have their bias as well. They run fast with real cta. So we understand that and we all have our biases, of course, but it's always good to see things from just
- [76:53]
C
a footnote on that and it sort of ties into the discussion about portable alpha. And my own performance is that if I look at my performance for the last 12 months, then just almost 300 basis points came from purely just from interest income on my margin.
- [77:07]
B
Yeah.
- [77:08]
C
So that including or not including that could. Can potentially make. Make quite a big difference. And yeah, as you say, guaranteed outperformance. Well, if anyone says guaranteed anything, I'm immediately suspicious, I have to say.
- [77:21]
B
Well, that's what the scammers are saying when they try to impersonate the CTAs at the moment.
- [77:27]
C
So I've also been been impersonated and it does make me laugh because they always try and sell people automated AI trading bots trading Bitcoin, which is about as far from what I'm likely to ever try and do as it's possible to be. So I find it slightly amusing, but obviously it's quite terrifying as well.
- [77:49]
B
Yeah, Rob, this is all we. I mean we've gone long today, so appreciate people sticking with us. We'll wrap it up now and just say a big thank you to you, Rob, for spending some time and preparing for this conversation. If you want to show Rob some some love and some appreciation, go to your favorite podcast platform, whether it's itunes, Spotify, Amazon. Wherever you listen to your podcast, leave a rating and review. It really does help. It also helps to follow the show. Maybe many people actually just listen to the podcast, but they don't press the one called follow, but you really should because the most popular episodes will show up in your feed perhaps more promptly. And some of this is pretty time sensitive stuff as well. So do follow the podcast as well. And of course, if you want even more from us at Top Traders Unblocked, you can subscribe to the weekly emails we send out and that will give you additional information. Next week I'm joined by Jim Kassar. He's back. This will be a timely conversation, I'm sure, but because of everything that's happening and also because a lot of people listening to the show loves to hear his thoughts and his ideas about what may happen next. From Rob and me, thanks ever so much for listening. We look forward to being back with you next week. And in the meantime, take care of yourself, take care of each other, and for sure stay away from anything that seems to be a scam from a cta.
- [79:20]
A
Thanks for listening to Top Traders Unplugged. If you feel you learned something of value from today's episode, the best way to stay updated is to go on over to your favorite podcast platform and follow the show so that you'll be sure to get all the new episodes as they're released. We have some amazing guests lined up for you, and to ensure our show continues to grow, please leave us an honest rating and review. It only takes a minute and it's the best way to show us you love the podcast. We'll see you next time on Top Traders Unplugged. This podcast expresses the views of its hosts and the guests appearing on the podcast as of the date of its recording, and such views are subject to change without notice. Top Traders Unplugged do not have any duty or obligation to update the information contained herein. Furthermore, Top Traders Unplugged make no representation to its accuracy and it shall not be assumed that past investment performance is an indication of future results. Moreover, wherever there is a potential for profit, there is also the possibility of loss. This content is made available for educational purposes only and should not be used for any any other purpose. The information contained in this podcast does not constitute and should not be construed as investment advice or an offer to sell or a solicitation to buy any securities or related financial instruments in any jurisdiction. Certain information contained herein concerning economic trends and performance is based on or derived from information provided by independent third party sources. Top Traders Unplugged may believe that the sources from which such information are obtained are reliable. However, Top Traders Unplugged cannot guarantee the accuracy of such information and has not independently verify the accuracy or completeness of such information or the assumptions on which such information is based. This podcast, including the information contained herein, may not be reproduced, copied, republished or posted in whole or in part in any form, without the prior written consent of top traders.
- [80:53]
C
Unplugged.