Shownotes
Rob Carver is back from summer break for a conversation that moves between past and present through the lens of lived experience. Starting with the anniversary of Lehman’s collapse, Rob and Niels unpack why strong performance often coexists with poor investor outcomes - and how timing, not strategy, remains the silent killer. They question the recent push into trend by asset management giants, weigh whether CTA underperformance marks a structural shift or a familiar cycle, and examine what the data can and can’t tell us when conviction fades. If there’s a theme this week, it’s simple: knowing what works is not the same as using it well.
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Episode TimeStamps:
01:14 - What has been on our radar recently?
12:09 - Industry performance update
19:23 - Q1, John: What are your recommendations for adapting a continuous forecast-based position sizing for a cash-only portfolio?
23:15 - Q2, Absolute: Is short/long symmetry optimal for a strategy in which the price of the traded instruments is measured in units (fiat currencies) that are inflated (devalued)?
30:19 - Q3, Lin: Got any ideas for trading a crypto portfolio?
32:04 - Why investors are losing money on 42% gain ETFs
39:50 - The difference between percentage return and cash return
43:24 - Debunking the persistent score card
46:19 - How the world has changed for CTAs
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2. Daily Trend Barometer and Market Score
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Transcripts
You're about to join Niels Kaastrup-Larsen on a raw and honest journey into the world of systematic investing and learn about the most dependable and consistent yet often overlooked investment strategy. Welcome to the Systematic Investor Series.
Niels:Welcome and welcome back to this week's edition of the Systematic Investor series with Rob Carver and I, Niels Kaastrup-Larsen, where each week we take the pulse of the global markets through the lens of our rules-based investor.
Rob, it is wonderful to be back with you this week. Don't think we've spoken since before the summer, actually. So how are you? How are things in the UK?
Rob:Yeah, I've been on a very long summer break as I'm very lucky to be in a position to do so and enjoying what was a very nice sunny summer in Britain and also a bit of Europe that I visited. And it's nice and sunny today, which is good as we're obviously welcoming VIP visitors to the UK at the moment. But I won't mention the name of these people, but you know, but we like to be good hosts so it's nice that they've got good weather.
Niels:Yeah, that is absolutely true. We’ve got a good lineup of topics as we always do, of course, and we got three questions coming in or that came in, I should say. And before we get into all of that, I was going to ask you, as I normally do, sort of what's been on your radar, and I imagine the last couple of weeks, not the whole summer holiday recap.
Rob:Yeah, when I was a child at school, the first thing you always have to do, when you came back in September, was write an essay entitled What I Did in my Summer Holidays. And because I've got quite a vivid imagination, I always felt the ability to make stuff up, which I hope amused my teachers immensely, rather than just reading about, you know, the normal standard stuff.
Yeah, it's actually an anniversary of an important event, and that is Lehman Day. So happy Lehman Day to those who celebrate – so, 17 years to a couple of days ago. It was the sort of financial crisis, and I find it astonishing that it's been 17 years. It makes me feel incredibly old to say that. It's still very fresh in my mind, but yeah.
So, if you follow the Financial Times Alphaville blog (which is free by the way, unlike the rest of FT that's behind an extraordinarily expensive paywall, as I know by my cost), they did an article last week. And they've got all kinds of a treasure trove of historical documents that you can read about, including (I won't mention the name of the bank) a note from a buy-side analyst, sorry, a sell-side analyst saying that Lehman's is a great investment at this price and you should definitely buy shares in them, that was written about 10 days before they went bust.
Niels:Yeah, well, let me be more precise, because I did look up the treasure trove, when you mentioned Lehman Brothers, and I will mention it's public knowledge. So, apparently, it's a note from Morgan Stanley, it's dated June 30th, and it initiates coverage of Lehman Brothers with an overweight recommendation that is iterated, apparently, on July 14 and August 27. Now the lead author (okay, here I will blank out the name, people can look it up if they want)…
Rob:Yeah, let's not kick him down.
Niels: He left Morgan Stanley in: Rob:Well, I suppose you could argue that having made mistakes in the private sector, he said he'd have learned valuable lessons that then the public sector could take advantage of in his new job. Let's be charitable about this. Everyone deserves a second chance and everyone makes mistakes. So, these things happen.
Yeah, they do say that if you're a hedge fund manager and you've lost a lot of money, then actually people are desperate to give you money. First of all, if people gave you a lot of money to begin with then you must have some credibility. But secondly, they're like, well, you must have learned something from that and hopefully it'll be much better in the future.
Niels:Sometimes the world just seems upside down, frankly. It's a little bit like George Costanza in Seinfeld: the opposite, you know, kind of works. You lose money and then people line up to give you money. I mean, it doesn't work in our... Funny enough, in the CTA world, it doesn't seem to be the way things work.
Rob:A sneak preview for some of the topics which I'm out with later is that will be one of the themes for today, definitely: should you give money to people after they lost money or not?
Niels:Ah, okay, fair enough.
Rob:So, yeah.
Niels:Okay. All right. Well, I mean, on my radar, it's not that I spend a lot of time looking for sensational stories, but even in the not so surprising rate-cut we had yesterday from the Fed, the 25 basis points that everybody was expecting, there are a couple of things I thought were kind of interesting.
One of the big headlines, of course, was that the new Fed governor, Stephen Miran, who was just sworn in like, I think, the day before, he dissented the decision. He wanted to go for 50 basis points - no surprise there. And I think even Powell dodged a question about Fed independence during the press conference because of Miran's presence on the FOMC.
But one thing that actually also that was kind of interesting, and that is that Christopher Waller, who I think is one of the contenders to be the next Fed Chair, he did not descend. So, he actually was in line with the 25 basis points. Probably not something that, necessarily, the administration would have liked to have seen.
So anyways, it'll be interesting to follow. It didn't sound like, from what I've read, that Powell was lining up complete surrender with lots of rate cuts coming our way. So, we'll have to follow it.
The other thing, and this is not news but it's something that I've noticed lately, is that I find it very interesting that some of these large institutions, the BlackRocks, the Fidelities, have entered the CTA trend following space lately. And actually, Fidelity put out a paper, I think in June, written by Roberto Crouch and Sladja Carton, about beautiful managed futures as a powerful portfolio diversifier.
I don't think there was anything new. I will read you the conclusion though because they say in the paper, “managed futures strategies represent one of the most time tested, research backed, and structurally unique investment approaches available today. Their ability to dynamically respond to trends, maintain low correlation to traditional asset classes, and protect capital during crisis makes them a valuable component to both traditional and alternative investments. While they may not always outperform in every environment, we believe their consistent contribution to portfolio resilience, over time, justifies serious consideration by any investor seeking long-term risk-aware diversification.”
Now, that's all good. There's nothing new in that. These are all the arguments that we would otherwise have put out in the last couple of decades. What's interesting to me is, why now? Why are these huge institutions coming out with their products now, because as they say in this article, this is not new, so they must have known about it. So why didn't they launch these products 10, 15 years ago?
Now, I know this could be personnel driven. Maybe Roberto, I mean, I actually spoke to him at some point, so I know he's been working with trend for a while, and obviously not necessarily at Fidelity, but also people like BlackRock, and so on, and so forth. It's just interesting.
me that it's all happening in: Rob:Yeah, actually, I had that article flagged as one for us to potentially discuss, but I'd assumed, because it was quite old now, that someone else would already have brought it up.
Niels:We haven't discussed it.
Rob:Yeah, so I did actually look at it. I think you're right in saying that there's nothing really new there. Like, if you look at all the kind of graphs that they use, it's the very standard. It's almost like if you're someone who works for a CTA and your job is to sell CTAs, you've got a kind of classic deck that you use of graphs.
lking about? What happened in:And they've also got the classic, you know, what happens to mean standard deviation drawdowns and Sharpe ratio when you add, say, I think this 10%? Yeah, when you put 10% of a 60/40 portfolio into trend, it does better. So yeah, it's the classic deck, and it's not particularly anything new.
But you're right, the significance is, that this is Fidelity, like, one of the biggest asset managers in the world. You know, you've got BlackRock, you've got Vanguard, you've got Fidelity, and I guess, in terms of just sheer number of assets, Pimco is probably out there as well. So, we're talking about the top four, top five asset managers in the world and they're suddenly interested in this.
So yeah, it's curious and it may just be a weird coincidence, or it may be because (and we'll get to this) trend hasn't done so well recently and who knows, maybe this is buying the dip. We'll see.
Niels:Yeah, absolutely. And for those who may have missed it, I think maybe it was not last week's episode but the week before, I did mentioned the paper that the firm I work with, Dunn Capital, produced and released. You can also find it in the latest Sunday newsletter that I publish, if you're subscribed to that. And I think, also, I put a link, and I think it was toptradersunplugged.com/5voltrend I think was the link.
But in any event, we didn't spend time, actually, repeating all these arguments. We just looked at the evidence and we compared it to all the major hedge fund strategies because we hadn't seen that being done before. So, if people are interested to see how our industry versus ‘hedge fund strategies’ have done, then they can look that up in the paper.
We've already touched a little bit on managed futures, so let me just get into that now. My own trend barometer finished yesterday at 41. So, that's an improvement. Still not very strong, I have to say, but it's an improvement in the last 10 days or so.
And you know, so far September… although the last couple of days leading into the Fed cut, and the Fed cut itself, has not been great. I see performance down a little bit the last couple of days, but it's still a positive month. And some of the kind of, how should I say, usual suspects from the last couple of months such as equity, such as gold, have been really pulling the performance forward and so we see a continuation of that.
In terms of hard numbers, let me find them here, BTOP50 is, as of Tuesday this week, up 2.43% for the month, now down only 45 basis points for the year. So, a great comeback. SocGen CTA index up 2.85 for the month, down only 3.62% for the year. SocGen Trend up almost 4%, down only 4% and change for the year. And the Short-Term Traders Index, actually a good improvement, 2.13% for the month, down just 4.37% so far this year.
Now, of course, the traditional world continues to deliver. MSCI world up another 2.2% in September, now up 16.6% for the year. The US Aggregate Bond index from S&P is up 1.25% for the month, up 6.25% for the year. And the S&P500 Total Return index up 2.25% for the month, and up 13.29% so far this year.
Not necessarily specifically about you... Well, what are your takeaways from trend, looking at your own kind of way of dealing with these signals this year, over the summer? I imagine you've also seen some improvement over the summer.
Rob:Yeah, actually, unfortunately my computer is temporarily broken.
Niels:That’s fine, just talk about from what you remember, Rob.
Rob:Yeah, it's fine, I can't give you P&L numbers. I can give you risk numbers though, so that's 10…
Niels:Well, just give me your thoughts.
Rob:Yeah, so, last time I checked I was kind of, you know, making some positive performance. I'm not sure whether I'm flat for the year as quite yet, but it's not too far off hopefully, yeah. So, I'm currently long equities, long FX, long bonds, a little bit short energies. So, that's kind of the overall pattern, and risk is running at, I guess, equivalent numbers to you really. So, it would be about 50 %or 60% of my kind of typical kind of risk level. So, still not putting on like massive positions. It doesn't look like there's still very clear trends out there.
It looks like I'm short Bitcoin though, so that's nice to see. I do like it when my system agrees with my own prejudices and biases. So, that's a nice pleasant sight. But yeah, I mean it does feel like the market is… Although the traditional markets are doing very well, it does feel like there's an awful lot of bad news out there that isn't, to me, priced in. I mean, particularly in interest rates.
I mean, in any other kind of universe the fact that Fed independence is being seriously threatened, as you mentioned, should be something to cause serious consternation. I mean, so where am I with bonds? Hang on…
Niels:I think (while you've looked that up), and may I may have mentioned it last week, I think right now in the CTA space, bonds are where there might be some divergence in positioning because I see the daily moves between some of these ETFs and mutual funds and it almost feels like that when bonds go up, some managers do much better than others, and so on, and so forth. So, I think maybe bonds, people or models just disagree on. I think equities, and gold, and silver, and all that stuff, people are fully aligned.
Rob:Yeah, I mean, one reason for that might be that carry is a much more significant factor in bond price movements than it is in equities. And so, the weight you have to carry will make quite a big difference to your positions versus trend. But yeah, for what it's worth, I'm long bonds. My risk is about half what is in equities. So, I'm long BTPs, which is the Italian 10-year, obviously. I'm long US 30-years. I'm long 10-year Canadian. So yeah, I basically have a sort of modest size but consistently long position in bonds.
So, you know, if there are serious concerns about Fed independence and inflation, then unfortunately, if I'm right, in the sense of my kind of gut feeling that Trump is bad for the bond markets, and bad for the equity markets, then, at least in my systematic portfolio, I'm going to lose money. So, there you go, that's life.
Niels:A fair point, but actually it's not just about one individual. I think, with the fiscal policies being implemented right now and everybody getting massive amounts of debt, I think you could probably argue that many bond markets probably should have a higher risk premia than what they have.
Rob:Yeah, but I mean, the bond market selling off with debt concerns is the dog that's never barked, really, to be honest. I mean, apart from, you know, Liz Truss a few years ago, politicians in developed markets, generally speaking, get away with levels of debt that a few years ago people thought would be inconceivable.
Niels:Yeah, you say that, fair enough. But in the UK we did hit a 27-year high yields only a couple of weeks ago, higher than when Liz Truss did. So, maybe someone in there is actually aligning with your thoughts that this is not a great idea.
Rob: quite a bit of inflation from:But that doesn't work with the debt story because Italian debt to GDP ratios are much worse than the UK. So, it can't just be a debt story, it must be an inflation story.
Niels:And the whole inflation story, I mean depending on which country and how they measure inflation, it's very hard to get.
Rob:Anyway, let's stop pretending to be macro economists and experts on this because people will think they've tuned into the wrong podcast.
Niels:Let's move on to the questions.
Rob:Let’s move on to things that we actually know about, yeah.
Niels:Question number one, from John (it came in a few days ago), “Hey Rob, big reader and implementer of your work. My question is about adapting your continuous forecast-based position sizing for a cash-only portfolio like stocks or crypto, where total notional exposure cannot exceed 100% of capital, the formula correctly scales a position-based on forecast strength. A forecast of 20 would target double the exposure of an average forecast of 10. When the sum of these ideal positions across all instruments exceeds available capital, what's the best way to scale them down? Should all positions be reduced proportionally to meet the 100% capital limit? Or is there another method you would recommend for managing the excess?”
Rob:This is a really good question, actually. It's extremely relevant because I'm currently writing a book about trading without leverage. So, there's my book plug for the day. Niels, you can take that off the list.
Niels:Is that a promise?
Rob:Yeah, (laughter) well, unless there's another question related to it, in which case, sorry.
So yeah. I mean, so obviously, if you can't increase your position size when you get more confident about your positions, then you've kind of have two options, really. So, one is to kind of just effectively cut everything in half. And what that would mean, in practice, is that your average investment would be 50% cash. On average, you'll be using 50% of your exposure. And then, if your forecast is really strong, you'd be up to 100%.
The problem with that is that, well it depends on what you're trading. So, if you're trading very illiquid, risky emerging market stocks that have, say, an annualized standard deviation of like 50%, then actually trading with half of that, on average (which would be 25%, ignoring diversification effects), wouldn't necessarily be a bad thing. That would be a reasonable risk target to run, like 25%. That's what I run myself.
On the other hand, if you're trading, say, like, liquid large-cap S&P 500 stocks, which have an analyzed standard deviation of like 25%, 30%, then you're going down from, say, 25% to 12.5%, which is a very low-risk target, and is unlikely to be optimal. So basically, what you do in practice is you just have to say, well, I'm going to live with the fact that I can't use forecast strength in such a clean way to actually construct my signals. So, if my forecasts become really weak, then yes, I will cut my position. But if they get stronger than average, then I can't really do anything about it. I just have to live with it.
So, what I would probably do is something like, rather than cutting… At the moment, I cut my forecasts off at 20%, which is twice the average. I would probably cut them off at 10%, which is the average. And what that would mean in practice is that, if you had instruments you were holding where you had less than the average forecast, then you'd have a smaller position in them. So, you basically would have cash creeping back into your portfolio.
The question is whether it's then optimal to reallocate that cash to other positions? Then it gets complicated. So, in theory, yes. In practice, unless it was a big effect, I probably wouldn't bother because it would get a bit too complicated.
So, for more details…
Niels:Yeah.
Rob:Buy the book.
Niels:There is a book out there somewhere.
Rob:Yeah, there probably is another book, But specifically for this problem, I'll definitely answer that question for you, but you just have to wait a few months, I'm afraid.
Niels:Okay, great. All right. Well, there is another question. This is from Absolute Gnosis, which I imagine is some kind of handle.
Rob:I mean, it could be their real name.
Niels:It could be their real name, and I will stress that I normally would only take questions that come from people with a real name. Just so people are aware of that.
Anyways, the question is, “Is short/long symmetry optimal for a strategy in which the price of the traded instruments is measured in units, “ fiat currencies”, that are inflated brackets devalued at 8% to 14% year per year?”
It's a very specific question. Maybe you can make more sense of it than I can.
Rob:Okay, so we obviously have someone who's a fan of crypto here because they're using the term ‘fiat currency’ and that term is never used except pejoratively by crypto people. Until about five years ago, I thought that fiat currency was the money you handed over when you went to buy a small Italian car. But no, when they say that, they mean traditional currencies like pounds, euros, dollars, etc.
Now, I would be curious where they got this figure of 8% to 14% a year, because as far as I'm aware, there's no major economy where inflation's running at that level (when I say major, I mean developed market), or whether that is what they think is the long-run appreciation of bitcoin versus fiat currencies is. Again, I don't know. Bitcoin has gone up by more than that recently, so I don't know if figures come from there.
But anyway, so let's reframe the question to terms that make more sense, I think. And that's the following. Let's suppose that I'm trading an instrument that's not denominated in my home currency. So, for example, I could be a UK investor (as I am), I'm trading S&P 500 futures (which I am), which are denominated in US dollars. Now, let's also assume, for the moment, that I'm trading the cash instrument and not the future because it gets a bit different with futures. But let's just, for the moment, assume I want to buy a US listed ETF that's denominated in dollars with my British pounds. And I want to say, well, I want to do some kind of trend following on that thing. So, I need the price of that thing.
The question is, which price should I use? Should I use the dollar price? So, I just get the dollar price, and I plot it on a chart, and I've had a wiggly line, and I apply my moving averages, or my Bollinger bands, or whatever it is I'm using to measure trends.
Or should I convert that price into a pound sterling price? So I get the wiggly line, and then I multiply it by the GBP USD FX rate, to get a sterling price, which obviously is going to look different. So, to kind of return to the terms used in the question.
If for example, the pound had depreciated against the dollar, then the trend on that ETF would look stronger, because it would have had a sort of systematic drift added to it, which is the depreciation of the currency effect on top of it. And that would make me more likely to want to buy that.
So, the question is, should we do that? And the answer is, well, if you do that, you're essentially trend following two things: an exchange rate and a currency. And you're kind of munging them into one thing and you're trend following that thing together rather than trend following them separately.
Another way, an equivalent way of doing it would be to trend follow the dollar price, but also then, simultaneously have another trend following model which looks at GBP USD. Now, generally speaking, diversification is better than less diversification. By adding those two things together and creating the pound version of the S&P ETF price, what you're essentially doing is removing the potential for diversifying across two instruments, a currency and a stock market index, and just having a single instrument. Now that will work if and only if trend following will work better on the combined thing than on the two things separately, which will have a diversification benefit.
Now, I haven't checked this, but generally speaking, I'm a big believer of the fact that it's quite hard to pick out statistically significant differences in performance of trend following of different instruments. So, when people say, oh yes, everyone knows that X trends better than Y, my first response is okay, what's the evidence? And they'll say, oh look, well, look, here you go. And I say, well, if I put these two return distributions on top of each other and do a statistical test, I find there's no difference between them. So, go away and come back to me when you've got a better idea.
And yes, if you check 250 different instruments, then yeah, you will find a few that are statistically significant. But that's just because you've checked so many. Then that's just the way that statistics work. So, you always find one or two by chance. So as a rule, I would not do that. I would not combine those two things together. I try to trade them separately.
Now, things are more complicated when you think about futures because in futures, if I'm trading and I want to buy an SPY ETF, say, I don't actually have to convert the entire notional value of my pound account into dollars to buy that. I just have to convert enough for the margin. And if the margin is, say, I don't know, 20% or 25% or whatever (which is kind of, roughly, an average futures margin tends to come in at that), then my exposure to the currency risk is only a quarter of what it would be otherwise. Of course, because I'm trading futures, I can then separately go and trade the currencies as a separate thing, and get the diversification benefit.
So, if you reframe the question as, you know, should we currency convert price series before trend following? My answer is no. I don't think you should do that because you’re kind of muddling two things together.
And actually if you're also trading GBP USD as well as the currency converted SPY, the correlation between those two things will increase significantly and you lose all the diversification benefit, essentially.
If you map that back to the original question, again, I would say no. I wouldn't, for example, reconvert all prices into bitcoin prices before running trend following things over them. Although, as I said, the whole premise of the question, the number in it - the 14%, I don't really know where that comes from.
Niels:That's fair, that's fair. All right, last question. We'll make it quick because we've got all your wonderful topics to get to. This is a question that came in from Lynn just a few minutes ago before we started recording. I'm going to read all the questions and then you can just quickly answer the ones that you may be able to answer.
Lynn simply writes, “I've tested a few strategies but they're not working well with crypto. Got any ideas?” I think that's a pretty open question.
Then there is one, “Is your new book about cryptocurrencies?”
“Are you considering a themed focus on stock picking?”
Rob:So, for the first question, I do know at least one person, who's an Australian guy, who's very active on X, who has made an awful lot of money using trend following on cryptocurrencies. And certainly, I've also, myself, have this sort of side hustle where I do a bit of consultancy for a crypto hedge fund. I've also tested trend following on cryptocurrencies and it seems to work fine. And this hedge fund, again, is doing very well trend following cryptocurrencies.
So, trend following on cryptocurrency seems to work pretty well. There's no guarantee of course, about the future, but there we go.
Yes, (sorry about the second book plug, Niels, but it was forced to me through the question) yeah, there is. The book I'm currently writing is about trading without leverage and that includes trading cryptocurrency without leverage. So, it's in there. And yeah, it's also about trading individual liquid equities, so you can call that stock picking, if you like, as well. So, there we go.
Niels:Okay, cool.
Rob:Something for everybody there.
Niels:Now I'm excited about the next few topics that you brought along, although we kind of exchanged ideas fairly late this time around. So, I will leave it up to you to guide us through because there are a few different articles that you're sort of combining into a bigger theme that we can then relate back to also to our world of trend following. So, I really need to just give you the floor and we'll see where we go.
Rob:Yeah, so it's always hard for me, coming back from summer holidays, because I've not thought about, you know, markets, or trend following, or anything for the best part of two months. It's quite hard for me to get my head back into, you know, like, what's going on. So, yeah, apologies for it all being a bit last-minute.
But, yeah, so, there are a few articles that kind of piqued my fancy. And I realized there was a bit of a theme to them. And then there was something else that happened that kind of tied into it. Anyway, so, the first article I'm going to mention is on Jeffrey Ptak. So, I think that's how you pronounce it. It's Ptak is how it's written. I don't know if the P is silent. Okay, Jeffrey, apologies if Neil's or I have got it wrong, but we've said it differently so one of us bound to be correct.
The article is titled Wish I Was Making This Up. And the headline says it all. An ETF gains 42% a year. Its investors still lose money.
Now it's perhaps not worth talking about the ETF itself in detail, for what it's worth, it's called the Yield Max Coin Option Income Strategy. So, that's going to be some kind of ETF that is selling volatility to gain income that may, in turn, have its own risks. But that's not really the point.
The point is the thing did make money, 42%, jolly good. But the investors in it lost money. Now how, you may ask, is this possible? Let's think about a really simple example.
Let's imagine a fund that does something really strange. For 364 days of the year, it loses 1%... Actually, that's not mathematically possible. Well it is, actually, if you have geometric losses. But let's change the math slightly. So, for 51 weeks of the year it loses 1%. So, it's down basically half pretty much. And on the last day of the year it makes 200%. So that's a doubling and then another doubling. The first doubling removes the original loss. So, basically over the year it's made 100%. Woohoo, brilliant, fantastic.
Now, let's imagine three investors. The first investor is buy and hold. Buys the fund beginning of the year, holds it till the end of the year, makes 100%. They're a very happy person.
Okay, the other two investors think that they're geniuses at market timing. So, the first one buys the fund at the beginning of the year. After about 40 weeks they just go, oh my God, this is ridiculous, I've lost 40% on this thing, why am I still holding onto this piece of absolute garbage? And they basically sell it and then just sit in cash the rest of the year. So, they lose 40%.
The final investor has some kind of God given talent for timing, and they wait till the very last week of the year and they buy into the fund, they make, you know, couple of hundred percent, maybe lots, minus 1%. So, they make quadruple their money. So, they're a even happier person.
So, that's three investors. And out of those three investors, only one of them has actually managed to match the return of the fund over the year. The other two have quite different returns. One's down 40%, the other one's up 200%. So, we've got very different return profiles.
So, obviously that's a kind of made up, an extreme example, but hopefully you can see that it's going to be impossible for any individual investor to actually earn the returns of a fund unless they literally buy and hold, and hold the whole time, and make no kind of withdrawals or additional income. All of the investors will receive a slightly different return.
So, we'll call those returns the percentage return and the cash return. Okay, so percentage return is the headline amount the fund makes over the year and the cash return is the money that any individual investor makes in it. But we can actually create an aggregate cash return because we can basically look at all the individual investors together and add up all of their withdrawals, and so on, and so forth, and work out how much they actually made in that year.
So, for example, you could hopefully see that if 99% of the investors in the fund were of type 2; in other words, they held for 40 weeks and then sold. And only 1% of the investors was type 3; in other words, they were the lucky person at the end. Then overall, the cash return on that fund for all investors aggregated is going to be of the order of minus 39%, is going to be minus 40% plus a little bit for the guy at the end who was really lucky. So, that's exactly what Jeffrey does.
We'll stick to his first name because I think we can agree that it's a lot easier to pronounce Jeffrey. He looks at the annual reports and the kind of cash movements and looks at the net flows in and out. And the issue is that there are a lot more people are putting money in just before the thing goes down than are putting money in when it's about to go up, and vice versa. So, they're taking money out before gains and vice versa. So, yeah, as the net result of that is that they do not make 42%.
Niels:Well, specifically, according to his accounting, he says that US$2.5 billion dollars were coming in in net inflows. But the investors lost a combined US$35.5 million over the very same period. I mean, that's extraordinary.
Rob:Yeah. I mean, so that's not a big percentage, but it is still a loss, you know. So, was it US$2.5 billion and US$35 million, did you say?
Niels:That's what the number said.
Rob:That's like a loss of 1.5%, isn't it? Yeah, so, yeah. So obviously, a 1.5% loss is very different from a, a 41%, 42% gain. And you know, this is going to be more problematic in funds whose returns are very, let's say, patchy or spiky or to be technical for a second, that exhibits strong negative or positive skew. You know, it's the fund I described earlier, they’re going to lose money for 51 weeks and makes a massive gain.
That's a kind of extreme example of a positive skewed strategy. Whereas, something like trend following, for example, is a less extreme example of a positive skewed strategy.
Selling option vol, as in the fund that Jeffrey describes, is, generally speaking, a negative skewed strategy. So, it's got the opposite pattern. That again, it's going to have a pattern of lots of small gains and then big losses. That's kind of, roughly speaking, what you expect to see. It's slightly different from that for this fund because it’s obviously not purely options selling.
But again, if you're selling immediately before one of those big losses, you're going to do very well. But if you're buying before one of those big losses, on the back of what probably look like persistent gains in the past, you're going to do very badly. So that's the first article.
So, a question; I think whenever you see an example of something happening, anecdote, as a kind of systematic person, as a quant, if you like, you should say, well, this is generally true. Or are the investors in this particular fund just uniquely stupid?
So, there was a nice piece of work done by, I think it's Morningstar, Jeffrey Ptak. And it's Jeffrey again.
Niels:It's the same guy. So now we know he works at Morningstar.
Rob:We know he works at Morningstar. We still don't know how to pronounce his name, but we know he works at Morningstar, and we know that he has a thing about this difference between percentage return and cash return or investor return.
So, in this piece of analysis, he looks at all US Investment funds. So, I guess that's basically mutual funds. It's not hedge funds, it's mutual funds. So, stuff that ordinary people buy and sell. And he looks at the difference between the investor return and the cash return over those funds.
And basically, in this context, a negative number means that the investors underperformed the fund, if you like. So, the previous example, that number would be like minus 40 something percent, because it's obviously a massive difference. In my stylized example, it would be even bigger than that.
So, the numbers here aren't as big, which is kind of what you'd expect because this is an average across the whole industry. And obviously, in some funds, people will do better than the funds because their timing happens to have been good. There's probably no skill here. It probably is just by luck.
You know, there are so many funds out there. At least with some of them, the investors would have got lucky. So, it's an average. The numbers are going to be smaller than for any individual fund, but they're still pretty damn impressive, to be honest.
So. if we look at the worst, for example, which is called equity, that's kind of, I guess, US equities, although there's a confusingly… Oh, sorry, sector equity, apologies. So, that would be something like a fund that has a thematic focus on say, oil firms, or tech, or something like that. There, the underperformance is 4.4% a year. Whilst it's not 40% a year, if you're going to underperform by 4.4% a year, and this is over 10 years, that's a pretty depressing long underperformance. Most people, in a situation where they were underperforming by an average of 4.4% a year for 10 years, would not be in a job for much longer.
And that's the biggest figure. But if you look at the whole universe of funds, the underperformance is 1.7% a year, which may not sound much, but again, over 10 years, that is a significant difference. And if you do a little maths, and see the effect on compounded returns over 10 years with the 1.7% underperformance, you're going to see a pretty substantial underperformance.
And I guess if I was to do some speculative thought on this, I think the reason why it's particularly bad in equity sectors is that's where I think people are going to be most affected by kind of news and emotion and stuff and things like, oh, the AI revolution is coming, let's put all our money in AI. And all the AI stocks have already gone up a lot and then they go down and it turns out to be spectacularly poor timing.
So generally speaking, people are quite poor at predicting. Well, they're quite poor at predicting the future, full stop. Otherwise, we'd all be, gazillionaires. But they're quite poor at predicting whether a particular fund or particular manager, if you like, is going to do better in the near future. So, they're pretty poor at timing; when to invest in things and when to take money out of things. That's the conclusion of Jeffrey's work, I would say. So, yeah. I found those articles interesting.
Niels:Yeah, and it kind of ties into a third article from the FT where they are kind of rebottling an article that was originally posted in Investment Advisor Association, and I think it's called Debunking the Persistent Score Card.
Rob:Yeah, I mean, this is interesting. I'd never heard of the Persistent Scorecard, and maybe that's because I'm not a regular reader of that particular, what would you call it, publication, I suppose. Publication, indeed.
So, yeah, I guess the idea behind this is, the whole passive versus active debate, which is the debate in finance that will never die. And you could argue that passive has gradually been winning that debate. And if you just look at the numbers, the percentage of assets that are passively managed, or managed by indices, has just kind of gone up persistently over quite a long period of time now. So that seems like an argument that’s been pretty much won.
But one of the things related to that is, well, if you are going to invest in active managers, should you invest in ones that have done well recently? In other words, is performance something that is persistent? And that kind of relates to it. Because if manager performance is persistent or has some signal, there's two options. So, one is that good managers continue to do well. The other is that good managers mean revert, and become less good managers or even bad managers.
So, to get technical for a second, if you look at the returns of a particular fund or a particular strategy, do their returns show positive auto correlation? In other words, good performance follows good performance. Or do they show negative autocorrelation? In which case, bad performance follows good performance? So, do managers have persistent skill or is it just luck?
Like, you know, a manager does particularly well in one year, are they likely to continue doing well in the future? So, apparently that's what this for persistent scorecard talks about.
So yeah, it's quite interesting because it sort of brought it to my attention. It’s taken a while to go into the debate, but basically, someone did an analysis of this persistent scorecard and the FT sort of said, well, this is a very poor analysis, but actually ultimately it doesn't really kind of settle the argument one way or the other.
So, I'd encourage people to read it because it’s a very interesting article, and I think it's a particularly hot topic as we will get to in a moment, indeed.
Niels:Sure, all right, well, let's get to that moment now, because the last, or the second to last question (we'll see if we get to the last one). But the next topic was very cryptic. When you sent it to me, you said, oh, I've been having a really interesting conversation with a CTA manager. So, tell me more.
Rob:Well, yeah, so earlier this week I had lunch with an old friend who's also a CTA manager, and I'm not going to mention their name because I've not asked them if I can do this. And their employer might not necessarily be happy about it anyway, but they know who they are.
So, we sort of got to talking about the fact that performance has not been great. Obviously, with, as we said right at the top of the program, it's recovered a bit recently, but overall it's not been great.
And I knew performance was bad because normally, well, let's just put it this way, we split the bill. Which, you know, I think all things considered means that the economic situation in CTAs must be pretty bad. Whereas, you know, I suppose if things get really, really bad, then I'd be expected to pay for the whole thing. But unfortunately, things haven't gotten quite that bad.
Anyway, we kind of got to this kind of eternal question, which is, you know, has everything changed or is this just a temporary period of poor performance? And I think this is, you know, every time there's an inevitable poor performance in CTAs, and for that matter, in any kind of strategy, equity value, for example, any strategy that will go through long periods of underperformance or negative performance, inevitably, at some point, people are going to be asking that question. And I'm sure, Niels, it's a question that you've been asked many times as well.
So, I sort of sat down and I thought, well, you know, okay, let's be systematic, let's be quants about this. So ultimately, what’s the answer to the question, has something changed or not? Well, we can waffle and say, well, you know, Trump's changed everything, or more algo trading has changed everything. Or, you know, we could say that, oh, just over time, markets get more efficient and therefore there's less alpha to be collected.
You can come up with all kinds of plausible reasons why things might have changed. But ultimately, if I was to say, let's just boil it down to a really simple problem. Let's suppose I'm an alternative allocator of assets and I've got two options for my portfolio. Let's return to that earlier paper, the Fidelity paper. My two options are I've got a 60/40 portfolio, and I've got potential to put some trend following in there. How should I do that portfolio optimization?
The one answer is to say, well, you should just take all the data you have, 25, 30, 40… I don't know how long the trend index has been going, but obviously it's possible to do something like (oh my goodness, I can't believe I'm saying this), you could do a replication of the trend index, which is something I don't normally advocate. But if you wanted, for example, to create a backfill trend index that goes back much further, then you can do that by replicating the trend index and then using underlying futures prices. So, it's not a hard thing to do, or you could just create your own trend index. It doesn't really matter, to be honest, as long as you've got something that's investable.
My own backtest goes back to: say, I think that, you know,:So, I'm just going to use all of my data and I'm going to treat it all equally. So that's kind of the starting point. The question is whether that can be beaten by doing something else.
So, what kinds of things might you do if you genuinely think that the world has changed? Well, one thing you could do of course is arbitrarily say, oh, I think the world changed three years ago and I'm just going to use the last three years of data, or one year ago, or some period of time and just say, right, I'm going to use that, that's what I'm going to do.
ll miss the outperformance of:And you kind of smugly say, well you know, I'm not putting any money into trend following because I've done this incredibly sophisticated analysis, and this is what I've done, and this is great. Now, the problem with that is you've done something that is not back testable because you have essentially created an arbitrary point. I mean it doesn't have to be arbitrary. You could come up with some logic for why you've chosen 2.5 years, or 3 years, or whatever. But you've been able to do something that you couldn't have done 3 years ago, which is to know 3 years ago that trend following performance in the next not quite 3 years, but 2, 2.5 years was going to be very poor. So, you've effectively kind of polluted your so-called rigorous testing with future information.
So, you actually need to do something that could be back testable. So, you need to have some way, a testable way of identifying when the performance of a particular strategy, whether it be 60/40 or trend following, or any other hedge fund strategy, is likely to go down in the future. And as we've discussed, people are really bad at that.
And if people are really, really, really bad at that, it means it's probably going to be quite hard to find any kind of algorithm that's truly in-sample, that's not being polluted with future information, or conditioning variable, or something like that, that's actually going to say, well, your performance in the future is going to be better or worse.
And if you do look at things like persistence, and autocorrelation, of things like that, generally speaking the effects aren't especially strong. And you know, it's really, really hard to say, well, yes, given recent CTA performance, what CTA performance is likely to be over, say, the next 12 months. It's really, really hard to do that.
So, the other thing you might do is say, well you know what, I'm just going to take a much more simplistic approach which is to say, rather than using the last 50 years of data, I'm only ever going to fit using the last 10 years of data, or the last 5 years of data, or the last 3 years of data, or the last 2 years of data. And that's sort of better from the kind of point of view you're no longer cheating with future information.
The problem is if you do that, what you will find is that your performance will be really bad because, generally speaking, the more data you have the better it is for fitting an optimization. And there's a degradation of out-of-sample performance as you reduce the size of the data you have available to you. So, you can imagine if you just are really silly, and do an optimization based on the last 10 days, you can see how that would be kind of crazy, even ignoring trading costs, because obviously you're going to be pulling your money in and out of funds nonstop, and putting it in 60/40, and vice versa. Even ignoring trading costs, you're just going to have mostly noise. It's just going to be, at best, it's going to be something just doing really badly.
So, there's a degradation of performance and it's sort of nonlinear. So basically, using 50 years of data is good. It doesn't make a lot of difference if you use 40 or even 30 years of data, or even 20 years of data. But when you're getting down to the point where you’re using the last two or three years of data because you think that something has changed in the last three years, and you test that, you find that it's not going to do anywhere near as well as just sticking to your guns and essentially assuming you can use all the data that you can.
So that's kind of the theoretical answer to the question. And I'd hoped, after saying that, they would pick up the bill, but they didn't. But anyway, that's life.
Niels:So, I'm curious, I obviously didn't know how long the lunch was, but I'm curious, did you conclude anything about has the world changed?
Can you imagine going back to:Now, clearly you need to adapt, and you need to do research. So, in that sense, I don't subscribe to the fact that you can just apply rules from the 70s today and expect necessarily the same outcome.
But I think the strength of this particular strategy is that it is adaptable and it has proven, over many, many decades, that it's capable of, over time, to produce not necessarily the same returns. But that's because people forget that actually volatility, the volatility of these benchmarks that we compare, has gone down significantly.
In the paper I mentioned, that we did at Dunn, we went back and looked at the rolling volatility of the Barclays CTA index. And back in the 70s and the 80s, it was more than 25% annual volatility. Today that index is less than 5% annualized volatility.
So, clearly returns should be lower if you're just looking at those kind of overall stats without looking into the stats. So, I mean, actually, I think it's a fair question to ask, but I think we have a really good answer, in our case.
Rob:Yeah, I mean, the issue is that, if you think about different kinds of statistical testing, which essentially is if you sort of look at the rolling performance of trend following over time and say, well, has that degraded? Visually, you can see some degradation.
e, because the markets of the:Particularly in the earlier days when there were fewer markets, there was less diversification. So that also made it harder to get a low vol. But even if you sort of accept the argument that, yeah, it looks like returns are degraded, you still don't see a statistically significant difference in returns. And because it's quite a low Sharpe strategy anyway, it's going to take quite a long time, possibly even another 50 years, to know for sure that things have changed and it has definitely ‘stopped working’.
So that's the kind of… I mean, I've said this before in a podcast and somebody picked up on LinkedIn. But really, you're at the point where statistics can't really help you. You either believe or you don't believe.
The only thing I can say is that, yeah, people have been really bad at sort of timing investment in and out of strategies, and there's lots of evidence of that. So, my kind of view is, generally speaking, your starting point with anything should be buy and hold. You know, buy and buy and hold underlying assets unless you're pretty sure, you've got a lot of confidence you can do better by trading them.
And if you're investing in funds, or strategies, or risk factors, then again, you should be buying and holding those funds, or strategies, or risk factors, unless you can prove very convincingly that you can do better. All the evidence I've seen is that it's quite the opposite. People do a terrible job of timing.
Niels:Yeah, absolutely. Speaking of timing, Rob, about one hour now.
Rob:Yes, I think it's a good time. We talked already about Fed independence, which was one of my final topics. So, I think we can leave it there.
Niels:Yeah, yeah, absolutely. This was great. Great to catch up with you and thanks for all the articles you brought along and all of that.
And of course, for all of you listening, if you want to send a little bit of love to Rob, why don't you go to your favorite podcast platform and leave a rating and review so that more people can join us when Rob and all the other great co-hosts are on the show.
Speaking of great co-hosts, the next one, next week, that is joining me will be Andrew Beer. So, definitely worth tuning in to. I'm sure we'll have our usual interesting conversations; proper CTAs versus people who replicate CTAs. And that's always fun. And he's a good sport, and I know he's been publishing some stuff recently that will be probably good discussion points.
If you have some questions for Andrew, which I hope you do, you can email them to info@toptradersunplugged.com and I'll do my very best to make sure that we get them in our conversation.
From Rob and me, thanks ever so much for listening. We look forward to being back with you next week. And in the meantime, as usual, take care of yourself and take care of each other.
Ending:Thanks for listening to the Systematic Investor podcast series. If you enjoy this series, go on over to iTunes and leave an honest rating and review. And be sure to listen to all the other episodes from Top Traders Unplugged.
If you have questions about systematic investing, send us an email with the word ‘question’ in the subject line to info@ptoptradersunplugged.com and we'll try to get it on the show.
And remember, all the discussion that we have about investment performance is about the past and past performance does not guarantee or even infer anything about future performance. Also, understand that there's a significant risk of financial loss with all investment strategies and you need to request and understand the specific risks from the investment manager about their products before you make investment decisions. Thanks for spending some of your valuable time with us and we'll see you on the next episode of the Systematic Investor.
