Lehman’s Legacy, ETF Performance & What Investors Still Get Wrong | Systematic Investor | Ep.366
Summary
Lehman’s Legacy: The podcast reflects on the 17th anniversary of the Lehman Brothers collapse, highlighting its lasting impact on financial markets and the importance of learning from past financial crises.
ETF Performance: Discussion on an ETF that gained 42% annually while investors lost money due to poor timing, emphasizing the importance of understanding cash flows and investor behavior in fund performance.
Fed Rate Decisions: Analysis of recent Federal Reserve rate cuts, noting dissent within the Fed and implications for future monetary policy, with a focus on the potential impact of Fed independence on markets.
Trend Following and Managed Futures: Examination of the trend following strategy's performance, with insights into why large institutions like Fidelity and BlackRock are entering the CTA space now, despite the strategy's long-standing history.
Investor Behavior: Highlighting Morningstar's research showing that investors often underperform the funds they invest in due to poor timing, reinforcing the challenges of market timing and the benefits of a buy-and-hold strategy.
Market Adaptation: Discussion on whether the world has changed for trend following strategies, with a conclusion that while markets evolve, the adaptability of trend following remains a strength over the long term.
Active vs Passive Management: Exploration of the persistent scorecard debate, questioning the long-term viability of active management in light of increasing passive investment trends.
Transcript
Imagine spending an hour with the world's greatest traders. Imagine learning from their experiences, their successes, and their failures. Imagine no more. Welcome to Top Traders Unplugged, the place where you can learn from the best hedge fund managers in the world, so you can take your manager due diligence or investment career to the next level. Before we begin today's conversation, remember to keep two things in mind. All the discussion we will 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 product before you make investment decisions. Here's your host, veteran hedge fund manager Neil's Castro Larson. Welcome or welcome back to this week's edition of the systematic investor series with Rob Carver and I Neils Carl Lassen where each week we take the polls of the global market through the lens of a rules-based investor. Rob, it is wonderful to be back with you uh this week. I don't think we've spoken since um before the summer actually. So, how are you? How are things in the UK? Yeah, I've been on on a very long summer break as I I'm very lucky to be in position position to do so and uh enjoying what was a very nice sunny summer in in 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 uh I I won't I won't mention the name the name of these people but uh you know we like to be good hosts so it's nice that they've got good weather. >> Yeah. No, that is absolutely true. Um, we got a good lineup of topics uh as as we always do of course and we got three questions coming in uh or that came in I should say. Um, and um, before we get into all of that, um, I was going to ask you, as I normally do, um, sort of what's been on your radar, and I I imagine the last couple of weeks, not the whole summer holiday, uh, recap, but yeah, I won't I won't do the the what 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." Uh and uh because I've got quite a vivid imagination, I always felt the ability like to make stuff up. Um which I'm hope amused my teachers immensely rather than just reading about you know the normal standard stuff. Um yeah, no I'm it's a it's actually um an anniversary of an important event um recently uh and that is Leman Day. So happy Leman Day to those who celebrate. Uh so 17 years and to a couple of days ago um the we you know it was the 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 cuz it's still very fresh in my mind. But uh yeah so if you um if you follow the the Financial Times Alphavville blog um which is free by the way unlike the rest of EFT that's behind a an extraordinarily expensive payw wall as I know to my cost. Um they they did an article last week and they've got all kinds of um sort of a treasure trove of uh historical documents that you you can read about about including a um uh I won't mention the name of the bank but a a note from a buy side analyst sorry a sellside analyst saying that Lemans is a great investment at this price and you should definitely buy shares in them that was written uh about 10 days before they went bust. So um so yeah >> well let me be more precise because I did look up the treasure trove then when you mentioned Lehman Brothers it's and I will mention it's public knowledge so you know so apparently it's a note from Morgan Stanley um it's dated June 30th and initiate it initiates coverage of Lehman Brothers with an overweight recommendation that is iterated apparently on July 14th and August 27th. Now, the lead author, okay, here I will blank out the name. People can look it up if they want. >> Yeah, that's he left Morgan Stanley uh in 2009 and joined the C congressional oversight panel for market monitoring, regulation, and top management and spent 5 years at the Treasury Department where he was first executive director of the financial stability oversight council. I mean, you can't make this up, but it's I mean, well, I suppose you could argue that having, you know, made mistakes um in the private sector, he's he'd have learned valuable lessons that then the public sector could take advantage of in his his new job. Let's let's be charitable about this. Everyone deserves a second chance and everyone everyone makes mistakes. Uh so the these things happen but um yeah they do say they do say that um um if you're a hedge fund manager and you've lost a lot of money then then actually people are desperate to give you money um because um you you well 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 um from that and hopefully it'll be much better in the future. Um so yeah >> sometimes the world just seems upside down frankly. Yeah. Um, it's a little bit like George Castansa in Seinfeld. The opposite, you know, kind of works, right? You lose money and then people line up to give you money. I mean, it it doesn't work in our in funny enough in the CTA world, it doesn't seem to be the way the work things work. >> A sneak sneak preview for some of the topics we're talking about later is is that will be one of the themes for today. Definitely. Should you give money to people after they've lost money or not? >> Ah, okay. Fair enough. >> So, yeah. >> Okay. All right. Well, I mean on my radar. Not that, you know, it's not that I spend a lot of time looking for sens sensational stories, but even in the uh not so surprising rate uh rate cut we had yesterday from the Fed, the 25 basis points that everybody was expecting. There are a couple of things I thought was kind of uh interesting. Um, one of the big headlines of course was that the new Fed governor Steven Moran who was just sworn in like I think the day before he dissented uh the decision he wanted to go for 50 basis points. No surprise uh there. Um and I think even pow dodged a question about Fed independence uh during the press conference u because of Moran's presence at uh on the M fomc. Um but one thing that actually also 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 uh with the 25 basis points. Probably not something that necessarily the administration would uh have liked to have seen. So anyways, um it'll be interesting to follow. Uh it didn't sound like from what I've read that PAL was lining up um you know complete um surrender and lots of rate cuts coming uh our way. So it'll we we'll we'll have to follow it. The other thing and this is not news but it's something that I've noticed lately uh is that I find it very interesting so that some of these large institutions the black rocks the Fidelities have entered the CTA trend following space lately and and actually Fidelity put out a paper uh I think in June u written by Roberto Croach and Slaja Carton um about the you know the beautiful uh managed futures as a powerful portfolio diversifier. I don't think there was anything new. I will read you the conclusion though um because they say in the paper managed future strategies represent one of the most time-tested researchbacked 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 riskaware uh diversification. Now, that's all good. There's nothing new in that. These are all the arguments that we would otherwise have put out um 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 uh you know I mean I know I actually spoke to him at some point so I know he's been working with Trend for a while and and obviously not necessarily at at Fidelity but also people like Black Rockck and so on and so forth. It's just interesting. I think it's great news for the industry that some of these really heavyweights in our industry and um gatekeepers of huge model portfolios where um most likely they're going to be using their own products to give people exposure to trends. So that's wonderful news. But it is kind of funny to me that it's all happening in 2025 and uh and not sooner. >> Yeah. Actually, I I had that article flagged as one for us to potentially discuss, but I I'd assume because it was quite old now that someone else would already have brought it up. Um >> we haven't discussed it. >> Yeah. So So um I I I did actually look at it. I think you're right in saying that there's nothing really new there. Like if you if you look at all the kind of graphs that they use, it's the the very standard um it's almost like you know if you're um someone who works for CT and your job is to sell CTAs, you've got like a kind of classic deck that you use of graphs, right? So one is the um correlation matrix. They've got a correlation matrix in there, you know, um to both equities, bonds and also 6040. Um, one is the the kind of um the sort of selective performance where you say, well, what happened during the this GFC which we've been talking about, what happens during in 2022, you know, what happened in in um I think they've even gone back to 200 the crisis as well there. Yeah. >> Exactly. Yeah. So, so that's a classic kind of thing to show you know what in in those situations, how did bonds do, how did equities do, how did 6040 do, how did trend do. Um and they've also got the the classic um you know what happens to um you know um mean standard deviation draw downs and chart ratio when you you add you know say uh I think there's 10% yeah when you put 10% of a 60/40 portfolio into into um trend it does better. So yeah, it's the it's the classic the the classic deck. Um and um it's not particularly anything new, but you're right, the significance is that this is Fidelity like that the almost, you know, one of the biggest asset managers in the world. You know, you basically got um you've got Black Rockck, you've got um Vanguard, you've got Fidelity, and I guess in terms of just sheer number of assets, Pinco is probably up there as well, right? So it's it should we're talking about top four top five asset managers in the world and they're suddenly interested in this. Um so yeah it's it's curious. Um and it may just be we a weird coincidence. Um or it may be because and we'll get to this. It may be because you know trend hasn't done so well recently and who knows maybe this is buying the dip. We'll see. >> Yeah. No absolutely. Um, and for those who may have missed, I think maybe it was uh not last week's episode, but the week before, uh, I did mention the paper that, uh, the firm I work with, Don Capsule, uh, produced and and released, and you can also find it in the latest, uh, Sunday newsletter that I published if you're subscribed to that. And, um, I think also I put a link to some and I think it was like toptraders onplot.com/val trend, I think, was the link. But in any event, um we didn't spend time actually uh repeating all these arguments. We just looked at the evidence and we compared it to all the major hedge fund strategies um because we hadn't seen that being done before. So if people are is interested to see how our industry versus quote unquote hedge fund strategies um have done um then they can look that up uh in the paper. We've already touched a little bit on manage futures. So let me just um get into that now. Uh 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 uh in the last 10 days or so. Um and you know, so far September, although the last couple of days leading into the Fed cut and and the Fed cut itself has not been great. I I see performance down a little bit the last uh couple of days, but it's still a positive month. And um some of the kind of how should I say the uh usual suspects from the last couple of months such as equity, such as gold um have been really pulling uh the performance forward and um and so we see a continuation of of that. In terms of hard numbers um let me find them here. Beta 50 is as of Tuesday uh this week up 2.43% for the month. now down only 45 basis points for the year. So a great comeback. So CT index up 2.85 for the month, down only 3.62% for the year. Stocken trend up almost 4% uh down only 4% and change for the year. And the short-term traders index actually a good improvement 2.13% uh for the month down uh just 4.37% so far this year. Now, of course, uh the traditional world continues to uh deliver. Msei World up another 2.2% in September, now up 16.6% for the year. Uh the US aggregate bond index from S&P is up one and a quarter for the month, up 6 and a quarter for the year. And the S&P 500 total return index up two and a quarter for the month and up 13.29% so far this year. um not necessarily specifically u about your um well what's been your what are your takeaways uh from trend looking at your own kind of way of um dealing with with these signals um this year over the summer uh I imagine you've also seen some improvement over the summer >> yeah actually unfortunately my my computer is temporarily broken so >> that's fine just talk about from what you remember Rob it's not >> yeah yeah it's fine yes I can't I can't give you P&L numbers I can give you risk numbers So that's telling you like where your position. >> Yeah. So last time I checked I I was kind of um you know making some positive performance. I'm not sure whether I'm flat for the year as uh yet quite yet. Um um but but not too far off hopefully. Um yeah. So I'm currently long equities uh long FX long bonds. Um so quite a little bit short energy. That's kind of the the overall pattern and risk is running at yeah I guess equivalent numbers to you really. So like it would be about 50 or 60% of my kind of >> typical kind of risk level. So um still not putting on like massive positions. It doesn't look like there's still very clear trends out there. But um but yeah um as a it looks like I'm short Bitcoin there. 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 pleasant sight. But yeah, I mean it does it does feel like a kind of you know it does feel like the market is is although the you know traditional markets are doing very well. It 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 in interest rates. I mean in in any other kind of universe the fact that Fed independence is being seriously threatened as you mentioned should be should be something for um to cause serious constonnation. Um I mean so where am I with bonds? Uh hang on. I think while you while you look that up I think uh and may I I may have mentioned it last week. I think right now in the CTA space, bonds is where there might be some divergence in positioning. Um because I see the daily moves between some of these um ETFs and mutual funds and it almost feels like that uh when bonds go up some managers uh you know uh 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 you know fully >> aligned. I mean, one one reason for that might be that, you know, 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. Um, but yeah, for what it's worth, um, I'm I'm long bonds, but my risk is about half what is in equities. So, I'm long, you know, um, BTPs. I'm long, which is the, uh, Italian 10 year obviously. Uh, I'm long US, 30 years. I'm long 10 year Canadian. Um, so yeah, I'm I basically have a fairly a sort of modest size but persist consistently long position in bonds. So, you know, um if if there are serious concerns about Fed independence and inflation, then unfortunately, I'm going to if I'm basically if I'm right in the sense of my kind of gut feeling that, you know, Trump is bad for the bond markets, then then uh and bad for and you know, 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. A fair point, but but actually it's it's not just about one individual. I think with the fiscal policies being uh implemented right now and everybody getting into massive amount of debt, I think you could probably argue that many bond markets might uh you know probably should have a higher risk premier than what they >> but I mean the the the the bond market selling off with with debt concerns is the dog that's never barked really to be honest. I mean apart from you know less truss a few years ago politicians in in in developed markets generally speaking get away with levels of debt that a few years ago people thought would be inconceivable. >> Yeah you say that fair enough and that's not the topic of today but but in the UK we did hit 27year high yields uh only a couple of weeks ago higher than windless trust. So maybe someone in there are actually aligning with your thoughts that this is not a great idea. We also have persistently high inflation. I mean we we we've we've sort of maintained quite a bit of inflation from 2022 whereas you know in say the in the EU it's kind of mean reverted a fair bit. Um but yeah I mean if you look at the spreads to spread to buns it's pretty or even actually PTPs. I mean you know um it's it's it's you're better off lending to the Italian government than the British government apparently. But that doesn't that doesn't work with a debt story, right? Because Italian jet 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. So >> and and and the whole inflation story, I mean, depending on which country and how they measure inflation, it's it's very hard to get. >> Anyway, maybe let's stop pretending to be macroeconomists and experts on this because people think they've tuned into the wrong podcast. >> Let's move on to the questions. >> Let's move on to things that we actually know about. Yeah. Question number one from John came in a few days ago. Hey Rob, big reader and implementer of your work. My question is about adapting your uh continuous forecastbased 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 recommend for managing the excess s? This is a really good question and actually it's extremely uh relevant because I'm currently writing a book about trading without leverage. Um so there's my book plug for the day. Neils, you can take that off the list. >> Is that a promise? >> Yeah. Well, unless unless there's another question related to it, in which case, sorry. Um so so yeah I mean so obviously if you um if you don't if you can't increase your position size when you're you when you get more confident about your positions um then you you've kind of got two options really. So one is to kind of just effectively cut everything in half. And what that would mean in practice is that that that your average investment would be 50% cash. you know, using on average you' be using 50% of your exposure and then if your forecast is really strong, you' be up to 100%. Um, and the problem with that is that that well, it depends on what you're trading, right? So, if you're trading very very liquid, very um illquid, risky uh emerging market stocks that have a quite have have say an annualized standard deviation of like 50%. Then actually trading with half of that on average, which would be 25% um ignoring diversification effects wouldn't necessarily be a bad thing. And that would be a reasonable risk target to run like 25%. That's why I run myself. Um on the other hand, if you're trading say like um liquid um large cap S&P 500 stocks um then you know which have an annualized standard deviation of like say 25 30%. Um then then you know you're going to be going down from some say 25 to 12 a.5% which is a very low risk target and um is unlikely to be optimal. Um, so you could make more. You basically what you do in practice is you just have to say, well, I'm going to live with the fact that that the I can't use forecast strength in such a clean way to actually con 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. Um, so what I would probably do is something like, um, rather than cutting at the moment I cut my forecasts off at 20, which is twice the average, I'd probably cut them off at 10, which is the average. And what that would mean in practice is that um, if you had instruments you were holding where you had less than the um, average forecast, then you'd have a smaller position in them. So you you basically would have cash creeping back into your portfolio. The question then is whether it's then optimal to reallocate that cash to other positions. Um then 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 get a bit too complicated. Um so um and and and yeah, for for more details, >> yeah, >> buy the book out there somewhere. >> Yeah, there probably is another book, but 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. >> Okay, cool. Great. All right. Well, there is another question. This is from Absolute Gnosis, which I imagine is a some kind of handle. Um, >> I mean, it could be could be their real name. We we >> could be their real name. And I will just stress that I normally would only take questions that comes from people with a real name, just so people are aware of that. Um anyways the question is um is short/long symmetry optimal for a strategy in which the price of the traded instruments is measured in units um quote unquote fiat currencies that are inflated brackets devalued at 8 to 14% year uh per year. Uh it's a very specific question. Maybe you can make more sense of it than I can. >> Okay. So we we obviously have someone who's a fan of crypto here because um they're using the term fiat currency and and it's ne that term is never used except poratively by crypto people, right? So until about 5 years ago, I thought that fiat currency was the money you handed over when you went to buy a small Italian car. Um but but no, when they say that they mean traditional currencies like pounds, euros, dollars, etc. Um 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 is running at that level. Um when I say major I mean developed market you know um so um or whether that is the their what they think is the long run appreciation of Bitcoin versus you know fiat currencies. Um again I don't know Bitcoin's gone up by more than that recently so I don't know if 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 a currency that's not sorry in an instrument that's not denominated in my home currency. So for example, I could be a UK investor as I am. Uh I'm trading S&P 500 futures which I am which are denominated in US dollars. Okay. Um now let's also assume for the moment that I'm trading the cash instrument and not the future because of the it gets a bit different with futures. But let's just the moment assume I want to buy a USlisted ETF that's denominated in in dollars with my my British pounds and I want to say well I want to do some kind of trend following on that on that thing. So I need the price of that thing. Okay. The question is which price should I use? Should I use the dollar price? So I just get this get the dollar price and I plot it on a chart and I you know other than a wiggly line and I apply my moving averages or my Ballinger 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 the cable you know the GBPUSD FX rate to get a sterling price which obviously is going to look different. So to to kind of refer return to the terms used in the question, if for example um the pound had depreciated against the dollar, then the trend on that ENTF would look stronger, okay? Because it would have had a sort of systematic drift added to it, which is the depre depreciation of the currency effect on top of it. And that would make me more likely to want to buy that. Okay. So it the question is should we do that? Um, and the answer is well it you you know if you do that you're essentially trend following two things an exchange rate and a currency. Um, and you're kind of munching them into one thing and you're trend following that thing together rather than trend following them separately. um because you know another way of 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 GBPUSD. Now generally speaking diversification is better than less diversification. Um, by adding those two things together and creating the the the pound version of the S&P ETF price, what you're essentially doing is is removing the 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. Um now I haven't checked this but generally speaking um I'm I'm a big believer of the fact that um it's quite hard to pick out statistically significant differences in performance of trend following of different instruments. So you know you can't 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 at the 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 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. Um, so as a rule, I would not do that. I would not combine those two things together. I tra trade them separately. Now things are more complicated when you think about futures because um in futures if I'm trading um and I want to buy u an spy ETF say I don't actually have to convert the entire notional value of of uh my pound account into dollars to buy that. I just have to convert enough for the margin. Um and if the margin is say I don't know 20% or 25% or whatever which is kind of you know roughly sort of average futures margin tends to come in at that um then my exposure to the the currency risk is only is only a quarter of what it would be otherwise uh of course because I'm trading futures I can then separately go and trade the the currency 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'll be you're kind of muddling two things together and actually if you're also trading GBPUSD as well as the currency converted spy your the correlation between those two things will increase significantly and you lose all the diversification benefits essentially um if you map that back to the original question then I would I would again I would say no I wouldn't for example recon convert all prices into Bitcoin prices before running trend falling things over them. Um although as I said the whole premise of a question and the number in it the 14% I don't really know where that comes from. So that's fair. That's fair. All right last question. We'll make it quick because we've got all your uh wonderful topics to get to. Um, this is a question that came in from Lynn just a few minutes ago before we started recording. Um, I'm going to read all of the questions and then you can just quickly uh answer the ones that you may be able to answer. Um, 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. Um, then there is one. Is your new book about cryptocurrencies? Mark, are you considering a themed focus on stock picking? >> Um, so for the first question, um, I do know, um, at least one person who's an Australian guy who's very active on X, um, who has made an awful lot of money using trend following on cryptocurrencies. So, you know, um you might and certainly I've also myself as there's a have this sort of side hustle where I do a bit of consultancy for a crypto hedge fund. Um 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 um trend following on cryptocurrencies seems to work pretty well. Um there's no guarantee of course about the future but there we go. Um yes, sorry about the second book plug Neils, but it was forced to me through through the question, but yeah, there is the the book I'm currently writing is about trading without leverage, and that includes trading cryptocurrency without leverage. So, it's in there. >> Um and the Yeah, it's also about trading individually equities. So, you can call that stock picking if you like as well. So, there we go. >> Okay, cool. >> Something for everybody there. Now, I'm excited about the next few um topics that you brought along. Uh although we um kind of exchanged ideas uh 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 we can then relate back to also to our world of trend following. So, I really need to just uh give you the floor and uh and we'll see where we go. >> Yeah. So, um it's always hard for me coming back from summer holidays. Um because I I've not thought about, you know, markets or trend following or anything for, you know, 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 all being a bit last minute, but but but yeah, so um there's a few articles that kind of peaked my fancy and I realized there was a bit of theme to them and then there was something else that happened that kind of tied into it. Um anyway, so the art the first I'm going to mention was um on Jeffrey Tax. Um so I think that's how you pronounce it. It's P PTAC is how it's written. I don't know if the P's silent. Okay, Jeffrey, apologies if if if Neil's or I have got it wrong, >> but we we've said it differently, so one of us is bound to be correct. >> Um the article's titled, "Wish I was making this up." Um and the 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 um some kind of ETF that that is selling um volatility um to to to gain income um that may in turn have its own risks, but but um that's not really the point. The point is the thing did make money, 42% jolly good. Um but the investors in it lost money. Now, how you may ask, is this possible? Let let's think about a really simple example. Let's imagine a fund that does something really strange. Um for 364 days of the year, um it loses um 1%. And on the last So that's a to actually that's not mathematically possible. >> Probably not. >> Well, it is. It is actually if you have geometric losses, but let's let's change the math slightly. So for 51 weeks of the year, it loses um 1%. So it's down basically half pretty much. And on the last day of the year, um, it makes 200%. Um, so that's a doubling and then another doubling. The first doubling removes the original loss. So basically over the year has made 100%. Woohoo. Brilliant. Fantastic. Now let's imagine um three investors. The first investor is 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. Um, the other two investors think that they're geniuses at market timing. So, the first one um 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 on to this piece of absolute garbage?" And they they basically sell it and then and then just sit in cash the rest of the year. So, they lose 40%. the the final investor is um has some kind of god-given talent for for timing and they wait till the very last week of the year and they they they buy into the fund and they make you know couple hundred% maybe lots minus 1% so make double their money um quadruple their money sorry so they're they're even happier person >> um so that's three investors and out those three investors only one of them's actually managed to match the return of the fund over the year the other two have quite different returns happens. 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 um it's going to be impossible for any individual um 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, the cash return. Okay? Okay, so percentage return is the the headline amount the fund makes over the year and the cash return is the money that the any individual investor makes in it. But we can actually create an aggregate cash return um because we can basically look at all the individual investors together and add up all of their you know with withdrawals and and and so on and so forth and work out how much they actually made in that in that year. Um so for example you could hopefully see that if if 99% of the investors in the fund were of type two in other words they they held for 40 weeks and then sold and only 1% of the investors was of type three 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 39% minus 39% is going to be minus 40% plus a little bit for the guy at the end who was really lucky. Uh so that's exactly what what um Jeffrey does. We'll stick to his first name because I I think we can agree that it's a lot easier to pronounce Jeffrey. He he looks at the the um the annual reports and the kind of cash movements um and looks at the the net flows in and out. And the issue is that a lot of pe a lot more people are putting money in just before the thing goes down that are putting money in um when it's about to go up and vice versa. So they're taking money out before gains and vice versa. Um so yeah as the net result of that is that um they do not make 42%. >> Well specifically in according to his accounting he says that $2.5 billion were coming in in net inflows. >> Yeah. >> But the investors lost a combined $ 35.5 million over the very same period. >> Yeah. >> I mean that's extraordinary. >> Yeah. I mean so that that's not a big percentage but it's still a loss you know. So was it 2 and a half billion and 35 million did you say? >> That's what the number said in >> Yes. That's like that's like a loss of one and a half% isn't it? Yeah. Um so yeah so so obviously a one and a half% loss is very different from a a 41 42% gain. And um you know this is going to be more problematic in in funds whose returns are very let's say patchy or spiky or to be to be um technical for a second that exhibit strong negative or positive skew. Um you know it's the fund I described earlier that that loses money for for 51 weeks and makes a massive gain. That's a kind of extreme example of a positive skewed strategy. Um whereas and you know something like trend following for example is a less extreme example of a uh of a positive skewed strategy. Um option selling option vol um as in as in the 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 a pattern of big gains um sorry lots of small gains and then big losses. That's kind of you know roughly speaking what you expect to see. It's it's a bit more slight different that from that for this fund because obviously it's not purely option selling. Um but again if you're if you're in if you're selling immediately before one of those big losses you're going to do very well. But if you buying before one of those big losses you're going to 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. Um so a question I think whenever you see an example of something happening anecdote as a kind of systematic person right as a quant if you like you should say well this is generally true or is this just you know are the investors in this particular fund just uniquely stupid okay so there was a nice um piece of work done by I think it's morning star >> Jeffrey Pet >> and it's Jeffrey again >> it's the same Hi. He clearly now we know he works at Morning Star. >> We know he works at Morning Star. We still don't know how to pronounce his name, but we know he works at Morning Star. And we know that he he has a thing about about this difference between percentage return and cash return or investor return. Um so in this piece of analysis, um he looks at all US investment funds. So I guess that's basically mutual funds, right? It's not it's not hedge funds, it's mutual funds. So stuff that that ordinary people buy and sell. and he looks at the difference between the investor return and the cash return over those funds. Um and basically in this context a negative number means that the investors underperformed the the fund if you like. So the previous example that number would be like minus 40 something%. You know because it's it's obviously a massive difference. Um in my stylized example it would be even bigger than that. Right? 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 just just 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 just that by luck, you know, there are so many funds out there that at least some of them the investors would have got lucky. Um but so it's an average the numbers are going to be smaller than than for any individual fund, but they're still pretty damn impressive to be honest. So um so if we if we look at the worst for example um which is called equ just equity so that that's kind of uh I guess US equities um although there's this confusingly this oh sorry second sector equity apologies so that would be something like a funds that fund that has a thematic focus on say you know oil firms or tech or something like that. Um there the underperformance is 4.4% 4% a year, which whilst is not, you know, 40% a year, you know, if you're going to underperform by 4.4% of the year consists for, you know, this is over 10 years, that's that's a pretty depressing long underperformance, right? You know, 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. Um and I um I I guess and that's that's the biggest figure but but if you look at the the whole universe of funds the underperformance is 1.7% a year which you know may not sound much but again over 10 years that that is a significant difference and if you you know do a little of maths and see the effect on compound 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 kind of do some speculative thought on this I think the reason why it's particularly bad in in in uh equity sectors is that's where I think people are going to be most affected by kind of news and emotion and stuff and and things like oh the AI revolution is coming let's put all our money in AI you know and all the AI stocks have already gone up a lot so then that and then they go down and it turns out to be spectacularly poor timing so generally speaking people are quite poor at predicting the well they're quite poor at predicting the future full stop um otherwise we'd all be you know gazillionaires but they're quite poor at predicting ing whether a particular fund u particular manager if you like is going to do better in in the near future. Um so they're pretty poor at very poor at timing when to invest in things and when to take money out of things. That that's the conclusion of of of Jeffrey's work I would say. So yeah I found those articles interesting. Yeah, and it kind of ties into a third article from um the FT um where they are kind of uh rebotting uh an article that was originally posted in investment advisor association and um I think it's called debunking the persistent score card. >> Yeah, I mean this is interesting. I' I'd never heard of the persistent scorecard and maybe neither me. No, maybe that's cuz I'm not a regular reader of um you know of that that particular uh what what would you call it? Publication I suppose. >> Publication indeed. Um so so yeah um I guess the the idea behind this is and it this work goes so the the whole passive versus active debate which is you know the debate in finance that will never die, right? Um and you could argue that passive is is is is you know gradually been winning that debate. And if you just look at the numbers like the percentage of of um assets that are passively managed or in managed by indices has just just kind of gone up um persistently over quite long period of time now. Um so that that's um that seems like a pretty an argument that's been pretty much won. Um but one of the one of the things related to that is well if you are going to invest in active managers you know should you invest in ones who's that have done done well recently or should you you know you know in other words is is per performance something that is persistent and that's kind of kind of relates to it right because if if we if manager performance is persistent has or has some signal so there's two options right so one is that good managers continue to do well the other is that good managers is mean revert right and become less good managers or even bad managers. Um so to get technical for a second if you look at the returns of um a particular fund or a particular strategy um do those returns show positive autocorrelation words good performance follows good performance or do they show negative autocorrelation in which case bad performance follows good performance. So, do you know do managers have persistent skill or is it 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? Um, so apparently that that's what this this persistent scorecard um talks about. So, so yeah, it's quite interesting because it sort of brought it to my attention. Um but the this this you know go into take a while to go into the debate but basically someone did an analysis of this persistent scorecard and the the FT sort of said well this is a very poor analysis but actually ultimately um it doesn't really kind of settle the argument one way or the other. So you know it's not it I encourage people to read it because it's a very interesting article and uh I think it's a particularly um you know hot topic as we will get to in a moment. Indeed. All right. Well, let's get to that moment now because uh the the last or the second last question, we'll see if we get to the last one, but the uh the the the uh next topic was very cryptic when you sent it to me. You said, "Oh, I've been having a really interesting conversation with the CTA manager. Um so, tell me more." >> Well, yeah. So, um, earlier this week, I had lunch with, um, a old friend who's also a CTA manager, and, uh, I'm not going to mention their name because I've not asked them if I can do this. So, and their employer might not necessarily be happy about it anyway, but they know who they are. So, I knew, you know, we 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 um well let's just put it this way. We split the bill which you know I think all things considered is means that the economic situation in CTAs must be pretty bad right? Um whereas you know I suppose if the things get really really bad then I'd be expected to pay for the whole thing but unfortunately things haven't got quite that bad anyway. So, so um we kind of got to this 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 you know 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. Um, and I'm sure Neils, it's a question that you've you've been asked many times as well. So, I I I sort of sat down. I thought, well, you know, okay, let's let's be systematic. Let's be qu about this. So, ultimately the answer to the question, has something changed or not? Well, we can waffle and say, well, you know, Trump's changed everything. Or algo, more ALGO trading has changed everything. Or, you know, we could say that uh oh, just over time markets get more efficient and therefore there's less alpha to be collected. You know, you can come up with all kinds of plausible reasons why why why things might have changed. Um, but ultimately, um, if I was to say, let's just boil it down to a really simple problem. Let's suppose I'm an 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, okay? And I've got potential to put some trend following in there. Okay. 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 can't I don't know how long the the trend index has been going, but obviously it's it's possible to to create um to do something like a Oh my goodness, I can't believe I'm saying this. You could do a a replication of the the trend index, which is something I don't normally advocate, but but if you wanted to, for example, 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 it's not a hard thing to do, but but you know, or you could just create your own trend index. It doesn't really matter to be honest. Um, as long as you got something that's investable. Um, so so you you take your let's say let's say you got 50 you know my my own back test goes back to 1970. So let's let's call it around 50 years. Uh it's got 50 years of data. You just use the whole of the data and you treat all of that data equally. So you basically say I think that you know 2025 is just like 1975 is just like 1985 just like 1995. So think I'm saying things haven't changed. I'm saying that to do any kind of optimization, I want to use as much data as I possibly can. So, I'm just going to use all of my data and I'm going to treat it all equally. So, that that's kind of the 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 some period of time and just say right I'm going to use that's what I'm going to do you know I think the world's changed and you know if I if I use say the last um two if we go back say two two and a half years and obviously we'll miss the outperformance of 2022 and that means your CTA allocation would go down significantly depending on your exact methodology it might go to zero but certainly be a lot lower than it would be in the kind of is in the full 50 year 50ear span and and you kind of smuggly say well you know I'm not putting any money into trend following because you know I've I've done this this incredibly sophisticated analysis and this is what I've done and this is great. Now the problem is with with with that is you've done something that is not back testable because you have essentially created a an arbitrary point. I mean it doesn't have to be arbitrary. you could you you know you you could come up with some logic for why you've chosen two and a half years or 3 years or whatever. Um but you've you've you've been able to you've been able to do something 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 two two and a half years was going to be very poor. Um, so you you've effectively kind of polluted your your so-called, you know, rigorous testing with 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 of identifying when the performance of a particular strategy whether it be 6040 or trend following or any other hedge fun strategy is likely to go down in the future. Um, and as we've discussed, people are really bad at that. And you know that that if people are really really bad at that, it means it's probably going to be quite hard to find um any kind of algorithm that that's truly in sample. So, you know, that's not being polluted with future information um or conditioning variable or something like that that's actually going to say, well, your performance of the future is going to be going to be better or worse. And if you do look at things like persistence and autocorrelation of things like that, generally speaking, um the the effects aren't especially strong. Um and you know, it's it's really really hard to to say, well, yes, given recent CTA performance, what's CTA performance like 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 two years of data. And that's sort of better in a from a kind of point of view, you're no longer cheating with future information. The problem is if you do that what you'll find is that your performance will be really bad because generally speaking the more data you have the better it is for fitting and optimization and there's kind of a um there's a degradation of of out of sample performance as you reduce the size of the data you have available to you. So, you can imagine if you do something really silly, which is do an optimization based on the last 10 days. Um, you can see how that would be kind of crazy because you'd be well or even ignoring trading costs because obviously you're going to be pulling your money in and out of funds non-stop and putting it in 60/40 and vice versa. Even ignoring trading costs, you know, you're just going to have mostly noise. It's just going to be at best it's going to be something just really badly. So, the 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 starting you're getting down to the point where using the last two or three years of data because you think that something has changed in the last 3 years and you test that you find that it's not going to do anywhere near as well as just yeah sticking to your guns and essentially assuming you can use all the data that you can. So that that's kind of the the theoretical answer to the to the question and and um I'd hoped after saying that that they would pick up the bill, but they didn't. But anyway, that's that's life. >> So 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? Um, but let me let me preface this with the fact that what surprises me is when I hear this argument, uh, which I do, as you rightly point out, I do that a lot, uh, over the, uh, the years. Um, some things change and and usually is when performance is is is less uh, than than the average and all of that stuff. But my but my answer to that is well, the world is always changing. And if you look at say the company that I work with, you know, we've been doing trend following for 51 years. Can you imagine going back to 1974 and think about how much has changed in that period of time yet the strategy um continues to work. Now clearly you need to adapt and you need to do research. uh so uh in that sense I don't subscribe to the fact that you can just uh apply rules from the 70s today and expect necessarily the same outcome. Um but I think the strength of of this particular strategy is that it is adaptable and it has proven over many many decades that it's capable of over time produce um 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 Dawn um we went back and looked at the rolling um volatility of the Barclay CTA index and back in the 70s and the 80s it was you know more than 25% annual volatility. Today that index is less than 5% annualized volatility. So clearly return should be lower if you're just looking at at those kind of overall stats without you know looking into the stats. So um no I mean actually I think it's a fair question to to to ask but I think uh I think we have a really good answer uh in our case. Yeah, I mean the issue is that if you think about a different kind of statistical testing which essentially is if you sort of look at the sort of rolling performance of trend falling over time and say well has that degraded um visually you can see some degradation and I appreciate you know it's you kind of have to do volatility adjust in a sense because you know the the mark the markets of the 1970s were a lot more volatile than they are now particularly commodity markets. Um so in even though we are risk targeting we're trying to risk target over time to get the same level of risk um it's still going to be hard particularly in the earlier days when when there were fewer markets there was less diversification so that also made it harder to you know get get a lower vault um but but even if you you sort of accept the argument that yeah looks like returns are degraded you still don't see a statistically significant difference in returns and because it's quite a low sharp strategy anyway um you you know it's going to take quite a long time, you know, possibly even another 50 years to know for sure that that that you know that things have changed and it has definitely stopped working, quote unquote. Um, so that that's the that that's the kind of the I mean, I've said this I said this before in a podcast and somebody picked up on LinkedIn, but but really you're at the there's this, you know, you're at the point where statistics can't really help you. You either believe you either believe or you don't believe. The only thing I can say is that yeah, people have been really bad at at sort of timing investment in and out of strategies. Uh, and there's lots of evidence of that. Um, so I my my kind of view is is generally speaking your starting point with anything should be buy and hold. Um, you know, whether buy and buy and hold underlying assets, unless you're pretty sure you can, you know, you've got a lot of confidence you can do better by trading them. Um, and if you're investing in in funds or or strategies or risk factors, then then again, uh, you know, you should be buying and holding those funds or or strategies or risk factors unless you can prove very convincingly that you can do better. And, um, you know, all the evidence I've seen is that it's quite the opposite. People do a terrible job of timing. >> Yeah. No, absolutely. Speaking of timing, Rob, it's about 1 hour. It's a good time. We we talked already about Fed independence which was one of my final topics so I think we can leave it there. Yeah. >> Yeah. No, absolutely. This was great great to catch up with you. Um and um thanks for for all the articles you brought along and um and all of that. And of course, for all of the use, for all of you listening, uh if you want to send a little bit of love to Rob, why don't you go to your favorite podcast platform, leave a rating and review, um so that more people can join us uh when uh when Rob and all the other great co-hosts are on the show. Speaking of a great co-host, the next uh one uh next week uh that is joining me will be Andrew Beer. So, uh definitely uh worth tuning into. I'm sure we'll have uh our usual interesting conversations um proper CTAs versus uh people who replicate CTAs and that's always fun. Uh and he's a good sport and I know he's been publishing some stuff recently that um um will be uh probably good discussion points. If you have some questions for Andrew, which I hope you do, you can email them to info@toptradersunplot.com and I'll do my very best to make sure that we get them uh 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. >> 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 iTunes and subscribe to 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 in iTunes. 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. [Music]
Lehman’s Legacy, ETF Performance & What Investors Still Get Wrong | Systematic Investor | Ep.366
Summary
Transcript
Imagine spending an hour with the world's greatest traders. Imagine learning from their experiences, their successes, and their failures. Imagine no more. Welcome to Top Traders Unplugged, the place where you can learn from the best hedge fund managers in the world, so you can take your manager due diligence or investment career to the next level. Before we begin today's conversation, remember to keep two things in mind. All the discussion we will 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 product before you make investment decisions. Here's your host, veteran hedge fund manager Neil's Castro Larson. Welcome or welcome back to this week's edition of the systematic investor series with Rob Carver and I Neils Carl Lassen where each week we take the polls of the global market through the lens of a rules-based investor. Rob, it is wonderful to be back with you uh this week. I don't think we've spoken since um before the summer actually. So, how are you? How are things in the UK? Yeah, I've been on on a very long summer break as I I'm very lucky to be in position position to do so and uh enjoying what was a very nice sunny summer in in 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 uh I I won't I won't mention the name the name of these people but uh you know we like to be good hosts so it's nice that they've got good weather. >> Yeah. No, that is absolutely true. Um, we got a good lineup of topics uh as as we always do of course and we got three questions coming in uh or that came in I should say. Um, and um, before we get into all of that, um, I was going to ask you, as I normally do, um, sort of what's been on your radar, and I I imagine the last couple of weeks, not the whole summer holiday, uh, recap, but yeah, I won't I won't do the the what 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." Uh and uh because I've got quite a vivid imagination, I always felt the ability like to make stuff up. Um which I'm hope amused my teachers immensely rather than just reading about you know the normal standard stuff. Um yeah, no I'm it's a it's actually um an anniversary of an important event um recently uh and that is Leman Day. So happy Leman Day to those who celebrate. Uh so 17 years and to a couple of days ago um the we you know it was the 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 cuz it's still very fresh in my mind. But uh yeah so if you um if you follow the the Financial Times Alphavville blog um which is free by the way unlike the rest of EFT that's behind a an extraordinarily expensive payw wall as I know to my cost. Um they they did an article last week and they've got all kinds of um sort of a treasure trove of uh historical documents that you you can read about about including a um uh I won't mention the name of the bank but a a note from a buy side analyst sorry a sellside analyst saying that Lemans is a great investment at this price and you should definitely buy shares in them that was written uh about 10 days before they went bust. So um so yeah >> well let me be more precise because I did look up the treasure trove then when you mentioned Lehman Brothers it's and I will mention it's public knowledge so you know so apparently it's a note from Morgan Stanley um it's dated June 30th and initiate it initiates coverage of Lehman Brothers with an overweight recommendation that is iterated apparently on July 14th and August 27th. Now, the lead author, okay, here I will blank out the name. People can look it up if they want. >> Yeah, that's he left Morgan Stanley uh in 2009 and joined the C congressional oversight panel for market monitoring, regulation, and top management and spent 5 years at the Treasury Department where he was first executive director of the financial stability oversight council. I mean, you can't make this up, but it's I mean, well, I suppose you could argue that having, you know, made mistakes um in the private sector, he's he'd have learned valuable lessons that then the public sector could take advantage of in his his new job. Let's let's be charitable about this. Everyone deserves a second chance and everyone everyone makes mistakes. Uh so the these things happen but um yeah they do say they do say that um um if you're a hedge fund manager and you've lost a lot of money then then actually people are desperate to give you money um because um you you well 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 um from that and hopefully it'll be much better in the future. Um so yeah >> sometimes the world just seems upside down frankly. Yeah. Um, it's a little bit like George Castansa in Seinfeld. The opposite, you know, kind of works, right? You lose money and then people line up to give you money. I mean, it it doesn't work in our in funny enough in the CTA world, it doesn't seem to be the way the work things work. >> A sneak sneak preview for some of the topics we're talking about later is is that will be one of the themes for today. Definitely. Should you give money to people after they've lost money or not? >> Ah, okay. Fair enough. >> So, yeah. >> Okay. All right. Well, I mean on my radar. Not that, you know, it's not that I spend a lot of time looking for sens sensational stories, but even in the uh not so surprising rate uh rate cut we had yesterday from the Fed, the 25 basis points that everybody was expecting. There are a couple of things I thought was kind of uh interesting. Um, one of the big headlines of course was that the new Fed governor Steven Moran who was just sworn in like I think the day before he dissented uh the decision he wanted to go for 50 basis points. No surprise uh there. Um and I think even pow dodged a question about Fed independence uh during the press conference u because of Moran's presence at uh on the M fomc. Um but one thing that actually also 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 uh with the 25 basis points. Probably not something that necessarily the administration would uh have liked to have seen. So anyways, um it'll be interesting to follow. Uh it didn't sound like from what I've read that PAL was lining up um you know complete um surrender and lots of rate cuts coming uh our way. So it'll we we'll we'll have to follow it. The other thing and this is not news but it's something that I've noticed lately uh is that I find it very interesting so that some of these large institutions the black rocks the Fidelities have entered the CTA trend following space lately and and actually Fidelity put out a paper uh I think in June u written by Roberto Croach and Slaja Carton um about the you know the beautiful uh managed futures as a powerful portfolio diversifier. I don't think there was anything new. I will read you the conclusion though um because they say in the paper managed future strategies represent one of the most time-tested researchbacked 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 riskaware uh diversification. Now, that's all good. There's nothing new in that. These are all the arguments that we would otherwise have put out um 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 uh you know I mean I know I actually spoke to him at some point so I know he's been working with Trend for a while and and obviously not necessarily at at Fidelity but also people like Black Rockck and so on and so forth. It's just interesting. I think it's great news for the industry that some of these really heavyweights in our industry and um gatekeepers of huge model portfolios where um most likely they're going to be using their own products to give people exposure to trends. So that's wonderful news. But it is kind of funny to me that it's all happening in 2025 and uh and not sooner. >> Yeah. Actually, I I had that article flagged as one for us to potentially discuss, but I I'd assume because it was quite old now that someone else would already have brought it up. Um >> we haven't discussed it. >> Yeah. So So um I I I did actually look at it. I think you're right in saying that there's nothing really new there. Like if you if you look at all the kind of graphs that they use, it's the the very standard um it's almost like you know if you're um someone who works for CT and your job is to sell CTAs, you've got like a kind of classic deck that you use of graphs, right? So one is the um correlation matrix. They've got a correlation matrix in there, you know, um to both equities, bonds and also 6040. Um, one is the the kind of um the sort of selective performance where you say, well, what happened during the this GFC which we've been talking about, what happens during in 2022, you know, what happened in in um I think they've even gone back to 200 the crisis as well there. Yeah. >> Exactly. Yeah. So, so that's a classic kind of thing to show you know what in in those situations, how did bonds do, how did equities do, how did 6040 do, how did trend do. Um and they've also got the the classic um you know what happens to um you know um mean standard deviation draw downs and chart ratio when you you add you know say uh I think there's 10% yeah when you put 10% of a 60/40 portfolio into into um trend it does better. So yeah, it's the it's the classic the the classic deck. Um and um it's not particularly anything new, but you're right, the significance is that this is Fidelity like that the almost, you know, one of the biggest asset managers in the world. You know, you basically got um you've got Black Rockck, you've got um Vanguard, you've got Fidelity, and I guess in terms of just sheer number of assets, Pinco is probably up there as well, right? So it's it should we're talking about top four top five asset managers in the world and they're suddenly interested in this. Um so yeah it's it's curious. Um and it may just be we a weird coincidence. Um or it may be because and we'll get to this. It may be because you know trend hasn't done so well recently and who knows maybe this is buying the dip. We'll see. >> Yeah. No absolutely. Um, and for those who may have missed, I think maybe it was uh not last week's episode, but the week before, uh, I did mention the paper that, uh, the firm I work with, Don Capsule, uh, produced and and released, and you can also find it in the latest, uh, Sunday newsletter that I published if you're subscribed to that. And, um, I think also I put a link to some and I think it was like toptraders onplot.com/val trend, I think, was the link. But in any event, um we didn't spend time actually uh repeating all these arguments. We just looked at the evidence and we compared it to all the major hedge fund strategies um because we hadn't seen that being done before. So if people are is interested to see how our industry versus quote unquote hedge fund strategies um have done um then they can look that up uh in the paper. We've already touched a little bit on manage futures. So let me just um get into that now. Uh 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 uh in the last 10 days or so. Um and you know, so far September, although the last couple of days leading into the Fed cut and and the Fed cut itself has not been great. I I see performance down a little bit the last uh couple of days, but it's still a positive month. And um some of the kind of how should I say the uh usual suspects from the last couple of months such as equity, such as gold um have been really pulling uh the performance forward and um and so we see a continuation of of that. In terms of hard numbers um let me find them here. Beta 50 is as of Tuesday uh this week up 2.43% for the month. now down only 45 basis points for the year. So a great comeback. So CT index up 2.85 for the month, down only 3.62% for the year. Stocken trend up almost 4% uh down only 4% and change for the year. And the short-term traders index actually a good improvement 2.13% uh for the month down uh just 4.37% so far this year. Now, of course, uh the traditional world continues to uh deliver. Msei World up another 2.2% in September, now up 16.6% for the year. Uh the US aggregate bond index from S&P is up one and a quarter for the month, up 6 and a quarter for the year. And the S&P 500 total return index up two and a quarter for the month and up 13.29% so far this year. um not necessarily specifically u about your um well what's been your what are your takeaways uh from trend looking at your own kind of way of um dealing with with these signals um this year over the summer uh I imagine you've also seen some improvement over the summer >> yeah actually unfortunately my my computer is temporarily broken so >> that's fine just talk about from what you remember Rob it's not >> yeah yeah it's fine yes I can't I can't give you P&L numbers I can give you risk numbers So that's telling you like where your position. >> Yeah. So last time I checked I I was kind of um you know making some positive performance. I'm not sure whether I'm flat for the year as uh yet quite yet. Um um but but not too far off hopefully. Um yeah. So I'm currently long equities uh long FX long bonds. Um so quite a little bit short energy. That's kind of the the overall pattern and risk is running at yeah I guess equivalent numbers to you really. So like it would be about 50 or 60% of my kind of >> typical kind of risk level. So um still not putting on like massive positions. It doesn't look like there's still very clear trends out there. But um but yeah um as a it looks like I'm short Bitcoin there. 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 pleasant sight. But yeah, I mean it does it does feel like a kind of you know it does feel like the market is is although the you know traditional markets are doing very well. It 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 in interest rates. I mean in in any other kind of universe the fact that Fed independence is being seriously threatened as you mentioned should be should be something for um to cause serious constonnation. Um I mean so where am I with bonds? Uh hang on. I think while you while you look that up I think uh and may I I may have mentioned it last week. I think right now in the CTA space, bonds is where there might be some divergence in positioning. Um because I see the daily moves between some of these um ETFs and mutual funds and it almost feels like that uh when bonds go up some managers uh you know uh 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 you know fully >> aligned. I mean, one one reason for that might be that, you know, 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. Um, but yeah, for what it's worth, um, I'm I'm long bonds, but my risk is about half what is in equities. So, I'm long, you know, um, BTPs. I'm long, which is the, uh, Italian 10 year obviously. Uh, I'm long US, 30 years. I'm long 10 year Canadian. Um, so yeah, I'm I basically have a fairly a sort of modest size but persist consistently long position in bonds. So, you know, um if if there are serious concerns about Fed independence and inflation, then unfortunately, I'm going to if I'm basically if I'm right in the sense of my kind of gut feeling that, you know, Trump is bad for the bond markets, then then uh and bad for and you know, 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. A fair point, but but actually it's it's not just about one individual. I think with the fiscal policies being uh implemented right now and everybody getting into massive amount of debt, I think you could probably argue that many bond markets might uh you know probably should have a higher risk premier than what they >> but I mean the the the the bond market selling off with with debt concerns is the dog that's never barked really to be honest. I mean apart from you know less truss a few years ago politicians in in in developed markets generally speaking get away with levels of debt that a few years ago people thought would be inconceivable. >> Yeah you say that fair enough and that's not the topic of today but but in the UK we did hit 27year high yields uh only a couple of weeks ago higher than windless trust. So maybe someone in there are actually aligning with your thoughts that this is not a great idea. We also have persistently high inflation. I mean we we we've we've sort of maintained quite a bit of inflation from 2022 whereas you know in say the in the EU it's kind of mean reverted a fair bit. Um but yeah I mean if you look at the spreads to spread to buns it's pretty or even actually PTPs. I mean you know um it's it's it's you're better off lending to the Italian government than the British government apparently. But that doesn't that doesn't work with a debt story, right? Because Italian jet 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. So >> and and and the whole inflation story, I mean, depending on which country and how they measure inflation, it's it's very hard to get. >> Anyway, maybe let's stop pretending to be macroeconomists and experts on this because people think they've tuned into the wrong podcast. >> Let's move on to the questions. >> Let's move on to things that we actually know about. Yeah. Question number one from John came in a few days ago. Hey Rob, big reader and implementer of your work. My question is about adapting your uh continuous forecastbased 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 recommend for managing the excess s? This is a really good question and actually it's extremely uh relevant because I'm currently writing a book about trading without leverage. Um so there's my book plug for the day. Neils, you can take that off the list. >> Is that a promise? >> Yeah. Well, unless unless there's another question related to it, in which case, sorry. Um so so yeah I mean so obviously if you um if you don't if you can't increase your position size when you're you when you get more confident about your positions um then you you've kind of got two options really. So one is to kind of just effectively cut everything in half. And what that would mean in practice is that that that your average investment would be 50% cash. you know, using on average you' be using 50% of your exposure and then if your forecast is really strong, you' be up to 100%. Um, and the problem with that is that that well, it depends on what you're trading, right? So, if you're trading very very liquid, very um illquid, risky uh emerging market stocks that have a quite have have say an annualized standard deviation of like 50%. Then actually trading with half of that on average, which would be 25% um ignoring diversification effects wouldn't necessarily be a bad thing. And that would be a reasonable risk target to run like 25%. That's why I run myself. Um on the other hand, if you're trading say like um liquid um large cap S&P 500 stocks um then you know which have an annualized standard deviation of like say 25 30%. Um then then you know you're going to be going down from some say 25 to 12 a.5% which is a very low risk target and um is unlikely to be optimal. Um, so you could make more. You basically what you do in practice is you just have to say, well, I'm going to live with the fact that that the I can't use forecast strength in such a clean way to actually con 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. Um, so what I would probably do is something like, um, rather than cutting at the moment I cut my forecasts off at 20, which is twice the average, I'd probably cut them off at 10, which is the average. And what that would mean in practice is that um, if you had instruments you were holding where you had less than the um, average forecast, then you'd have a smaller position in them. So you you basically would have cash creeping back into your portfolio. The question then is whether it's then optimal to reallocate that cash to other positions. Um then 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 get a bit too complicated. Um so um and and and yeah, for for more details, >> yeah, >> buy the book out there somewhere. >> Yeah, there probably is another book, but 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. >> Okay, cool. Great. All right. Well, there is another question. This is from Absolute Gnosis, which I imagine is a some kind of handle. Um, >> I mean, it could be could be their real name. We we >> could be their real name. And I will just stress that I normally would only take questions that comes from people with a real name, just so people are aware of that. Um anyways the question is um is short/long symmetry optimal for a strategy in which the price of the traded instruments is measured in units um quote unquote fiat currencies that are inflated brackets devalued at 8 to 14% year uh per year. Uh it's a very specific question. Maybe you can make more sense of it than I can. >> Okay. So we we obviously have someone who's a fan of crypto here because um they're using the term fiat currency and and it's ne that term is never used except poratively by crypto people, right? So until about 5 years ago, I thought that fiat currency was the money you handed over when you went to buy a small Italian car. Um but but no, when they say that they mean traditional currencies like pounds, euros, dollars, etc. Um 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 is running at that level. Um when I say major I mean developed market you know um so um or whether that is the their what they think is the long run appreciation of Bitcoin versus you know fiat currencies. Um again I don't know Bitcoin's gone up by more than that recently so I don't know if 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 a currency that's not sorry in an instrument that's not denominated in my home currency. So for example, I could be a UK investor as I am. Uh I'm trading S&P 500 futures which I am which are denominated in US dollars. Okay. Um now let's also assume for the moment that I'm trading the cash instrument and not the future because of the it gets a bit different with futures. But let's just the moment assume I want to buy a USlisted ETF that's denominated in in dollars with my my British pounds and I want to say well I want to do some kind of trend following on that on that thing. So I need the price of that thing. Okay. The question is which price should I use? Should I use the dollar price? So I just get this get the dollar price and I plot it on a chart and I you know other than a wiggly line and I apply my moving averages or my Ballinger 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 the cable you know the GBPUSD FX rate to get a sterling price which obviously is going to look different. So to to kind of refer return to the terms used in the question, if for example um the pound had depreciated against the dollar, then the trend on that ENTF would look stronger, okay? Because it would have had a sort of systematic drift added to it, which is the depre depreciation of the currency effect on top of it. And that would make me more likely to want to buy that. Okay. So it the question is should we do that? Um, and the answer is well it you you know if you do that you're essentially trend following two things an exchange rate and a currency. Um, and you're kind of munching them into one thing and you're trend following that thing together rather than trend following them separately. um because you know another way of 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 GBPUSD. Now generally speaking diversification is better than less diversification. Um, by adding those two things together and creating the the the pound version of the S&P ETF price, what you're essentially doing is is removing the 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. Um now I haven't checked this but generally speaking um I'm I'm a big believer of the fact that um it's quite hard to pick out statistically significant differences in performance of trend following of different instruments. So you know you can't 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 at the 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 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. Um, so as a rule, I would not do that. I would not combine those two things together. I tra trade them separately. Now things are more complicated when you think about futures because um in futures if I'm trading um and I want to buy u an spy ETF say I don't actually have to convert the entire notional value of of uh my pound account into dollars to buy that. I just have to convert enough for the margin. Um and if the margin is say I don't know 20% or 25% or whatever which is kind of you know roughly sort of average futures margin tends to come in at that um then my exposure to the the currency risk is only is only a quarter of what it would be otherwise uh of course because I'm trading futures I can then separately go and trade the the currency 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'll be you're kind of muddling two things together and actually if you're also trading GBPUSD as well as the currency converted spy your the correlation between those two things will increase significantly and you lose all the diversification benefits essentially um if you map that back to the original question then I would I would again I would say no I wouldn't for example recon convert all prices into Bitcoin prices before running trend falling things over them. Um although as I said the whole premise of a question and the number in it the 14% I don't really know where that comes from. So that's fair. That's fair. All right last question. We'll make it quick because we've got all your uh wonderful topics to get to. Um, this is a question that came in from Lynn just a few minutes ago before we started recording. Um, I'm going to read all of the questions and then you can just quickly uh answer the ones that you may be able to answer. Um, 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. Um, then there is one. Is your new book about cryptocurrencies? Mark, are you considering a themed focus on stock picking? >> Um, so for the first question, um, I do know, um, at least one person who's an Australian guy who's very active on X, um, who has made an awful lot of money using trend following on cryptocurrencies. So, you know, um you might and certainly I've also myself as there's a have this sort of side hustle where I do a bit of consultancy for a crypto hedge fund. Um 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 um trend following on cryptocurrencies seems to work pretty well. Um there's no guarantee of course about the future but there we go. Um yes, sorry about the second book plug Neils, but it was forced to me through through the question, but yeah, there is the the book I'm currently writing is about trading without leverage, and that includes trading cryptocurrency without leverage. So, it's in there. >> Um and the Yeah, it's also about trading individually equities. So, you can call that stock picking if you like as well. So, there we go. >> Okay, cool. >> Something for everybody there. Now, I'm excited about the next few um topics that you brought along. Uh although we um kind of exchanged ideas uh 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 we can then relate back to also to our world of trend following. So, I really need to just uh give you the floor and uh and we'll see where we go. >> Yeah. So, um it's always hard for me coming back from summer holidays. Um because I I've not thought about, you know, markets or trend following or anything for, you know, 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 all being a bit last minute, but but but yeah, so um there's a few articles that kind of peaked my fancy and I realized there was a bit of theme to them and then there was something else that happened that kind of tied into it. Um anyway, so the art the first I'm going to mention was um on Jeffrey Tax. Um so I think that's how you pronounce it. It's P PTAC is how it's written. I don't know if the P's silent. Okay, Jeffrey, apologies if if if Neil's or I have got it wrong, >> but we we've said it differently, so one of us is bound to be correct. >> Um the article's titled, "Wish I was making this up." Um and the 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 um some kind of ETF that that is selling um volatility um to to to gain income um that may in turn have its own risks, but but um that's not really the point. The point is the thing did make money, 42% jolly good. Um but the investors in it lost money. Now, how you may ask, is this possible? Let let's think about a really simple example. Let's imagine a fund that does something really strange. Um for 364 days of the year, um it loses um 1%. And on the last So that's a to actually that's not mathematically possible. >> Probably not. >> Well, it is. It is actually if you have geometric losses, but let's let's change the math slightly. So for 51 weeks of the year, it loses um 1%. So it's down basically half pretty much. And on the last day of the year, um, it makes 200%. Um, so that's a doubling and then another doubling. The first doubling removes the original loss. So basically over the year has made 100%. Woohoo. Brilliant. Fantastic. Now let's imagine um three investors. The first investor is 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. Um, the other two investors think that they're geniuses at market timing. So, the first one um 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 on to this piece of absolute garbage?" And they they basically sell it and then and then just sit in cash the rest of the year. So, they lose 40%. the the final investor is um has some kind of god-given talent for for timing and they wait till the very last week of the year and they they they buy into the fund and they make you know couple hundred% maybe lots minus 1% so make double their money um quadruple their money sorry so they're they're even happier person >> um so that's three investors and out those three investors only one of them's actually managed to match the return of the fund over the year the other two have quite different returns happens. 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 um it's going to be impossible for any individual um 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, the cash return. Okay? Okay, so percentage return is the the headline amount the fund makes over the year and the cash return is the money that the any individual investor makes in it. But we can actually create an aggregate cash return um because we can basically look at all the individual investors together and add up all of their you know with withdrawals and and and so on and so forth and work out how much they actually made in that in that year. Um so for example you could hopefully see that if if 99% of the investors in the fund were of type two in other words they they held for 40 weeks and then sold and only 1% of the investors was of type three 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 39% minus 39% is going to be minus 40% plus a little bit for the guy at the end who was really lucky. Uh so that's exactly what what um Jeffrey does. We'll stick to his first name because I I think we can agree that it's a lot easier to pronounce Jeffrey. He he looks at the the um the annual reports and the kind of cash movements um and looks at the the net flows in and out. And the issue is that a lot of pe a lot more people are putting money in just before the thing goes down that are putting money in um when it's about to go up and vice versa. So they're taking money out before gains and vice versa. Um so yeah as the net result of that is that um they do not make 42%. >> Well specifically in according to his accounting he says that $2.5 billion were coming in in net inflows. >> Yeah. >> But the investors lost a combined $ 35.5 million over the very same period. >> Yeah. >> I mean that's extraordinary. >> Yeah. I mean so that that's not a big percentage but it's still a loss you know. So was it 2 and a half billion and 35 million did you say? >> That's what the number said in >> Yes. That's like that's like a loss of one and a half% isn't it? Yeah. Um so yeah so so obviously a one and a half% loss is very different from a a 41 42% gain. And um you know this is going to be more problematic in in funds whose returns are very let's say patchy or spiky or to be to be um technical for a second that exhibit strong negative or positive skew. Um you know it's the fund I described earlier that that loses money for for 51 weeks and makes a massive gain. That's a kind of extreme example of a positive skewed strategy. Um whereas and you know something like trend following for example is a less extreme example of a uh of a positive skewed strategy. Um option selling option vol um as in as in the 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 a pattern of big gains um sorry lots of small gains and then big losses. That's kind of you know roughly speaking what you expect to see. It's it's a bit more slight different that from that for this fund because obviously it's not purely option selling. Um but again if you're if you're in if you're selling immediately before one of those big losses you're going to do very well. But if you buying before one of those big losses you're going to 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. Um so a question I think whenever you see an example of something happening anecdote as a kind of systematic person right as a quant if you like you should say well this is generally true or is this just you know are the investors in this particular fund just uniquely stupid okay so there was a nice um piece of work done by I think it's morning star >> Jeffrey Pet >> and it's Jeffrey again >> it's the same Hi. He clearly now we know he works at Morning Star. >> We know he works at Morning Star. We still don't know how to pronounce his name, but we know he works at Morning Star. And we know that he he has a thing about about this difference between percentage return and cash return or investor return. Um so in this piece of analysis, um he looks at all US investment funds. So I guess that's basically mutual funds, right? It's not it's not hedge funds, it's mutual funds. So stuff that that ordinary people buy and sell. and he looks at the difference between the investor return and the cash return over those funds. Um and basically in this context a negative number means that the investors underperformed the the fund if you like. So the previous example that number would be like minus 40 something%. You know because it's it's obviously a massive difference. Um in my stylized example it would be even bigger than that. Right? 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 just just 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 just that by luck, you know, there are so many funds out there that at least some of them the investors would have got lucky. Um but so it's an average the numbers are going to be smaller than than for any individual fund, but they're still pretty damn impressive to be honest. So um so if we if we look at the worst for example um which is called equ just equity so that that's kind of uh I guess US equities um although there's this confusingly this oh sorry second sector equity apologies so that would be something like a funds that fund that has a thematic focus on say you know oil firms or tech or something like that. Um there the underperformance is 4.4% 4% a year, which whilst is not, you know, 40% a year, you know, if you're going to underperform by 4.4% of the year consists for, you know, this is over 10 years, that's that's a pretty depressing long underperformance, right? You know, 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. Um and I um I I guess and that's that's the biggest figure but but if you look at the the whole universe of funds the underperformance is 1.7% a year which you know may not sound much but again over 10 years that that is a significant difference and if you you know do a little of maths and see the effect on compound 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 kind of do some speculative thought on this I think the reason why it's particularly bad in in in uh equity sectors is that's where I think people are going to be most affected by kind of news and emotion and stuff and and things like oh the AI revolution is coming let's put all our money in AI you know and all the AI stocks have already gone up a lot so then that and then they go down and it turns out to be spectacularly poor timing so generally speaking people are quite poor at predicting the well they're quite poor at predicting the future full stop um otherwise we'd all be you know gazillionaires but they're quite poor at predicting ing whether a particular fund u particular manager if you like is going to do better in in the near future. Um so they're pretty poor at very poor at timing when to invest in things and when to take money out of things. That that's the conclusion of of of Jeffrey's work I would say. So yeah I found those articles interesting. Yeah, and it kind of ties into a third article from um the FT um where they are kind of uh rebotting uh an article that was originally posted in investment advisor association and um I think it's called debunking the persistent score card. >> Yeah, I mean this is interesting. I' I'd never heard of the persistent scorecard and maybe neither me. No, maybe that's cuz I'm not a regular reader of um you know of that that particular uh what what would you call it? Publication I suppose. >> Publication indeed. Um so so yeah um I guess the the idea behind this is and it this work goes so the the whole passive versus active debate which is you know the debate in finance that will never die, right? Um and you could argue that passive is is is is you know gradually been winning that debate. And if you just look at the numbers like the percentage of of um assets that are passively managed or in managed by indices has just just kind of gone up um persistently over quite long period of time now. Um so that that's um that seems like a pretty an argument that's been pretty much won. Um but one of the one of the things related to that is well if you are going to invest in active managers you know should you invest in ones who's that have done done well recently or should you you know you know in other words is is per performance something that is persistent and that's kind of kind of relates to it right because if if we if manager performance is persistent has or has some signal so there's two options right so one is that good managers continue to do well the other is that good managers is mean revert right and become less good managers or even bad managers. Um so to get technical for a second if you look at the returns of um a particular fund or a particular strategy um do those returns show positive autocorrelation words good performance follows good performance or do they show negative autocorrelation in which case bad performance follows good performance. So, do you know do managers have persistent skill or is it 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? Um, so apparently that that's what this this persistent scorecard um talks about. So, so yeah, it's quite interesting because it sort of brought it to my attention. Um but the this this you know go into take a while to go into the debate but basically someone did an analysis of this persistent scorecard and the the FT sort of said well this is a very poor analysis but actually ultimately um it doesn't really kind of settle the argument one way or the other. So you know it's not it I encourage people to read it because it's a very interesting article and uh I think it's a particularly um you know hot topic as we will get to in a moment. Indeed. All right. Well, let's get to that moment now because uh the the last or the second last question, we'll see if we get to the last one, but the uh the the the uh next topic was very cryptic when you sent it to me. You said, "Oh, I've been having a really interesting conversation with the CTA manager. Um so, tell me more." >> Well, yeah. So, um, earlier this week, I had lunch with, um, a old friend who's also a CTA manager, and, uh, I'm not going to mention their name because I've not asked them if I can do this. So, and their employer might not necessarily be happy about it anyway, but they know who they are. So, I knew, you know, we 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 um well let's just put it this way. We split the bill which you know I think all things considered is means that the economic situation in CTAs must be pretty bad right? Um whereas you know I suppose if the things get really really bad then I'd be expected to pay for the whole thing but unfortunately things haven't got quite that bad anyway. So, so um we kind of got to this 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 you know 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. Um, and I'm sure Neils, it's a question that you've you've been asked many times as well. So, I I I sort of sat down. I thought, well, you know, okay, let's let's be systematic. Let's be qu about this. So, ultimately the answer to the question, has something changed or not? Well, we can waffle and say, well, you know, Trump's changed everything. Or algo, more ALGO trading has changed everything. Or, you know, we could say that uh oh, just over time markets get more efficient and therefore there's less alpha to be collected. You know, you can come up with all kinds of plausible reasons why why why things might have changed. Um, but ultimately, um, if I was to say, let's just boil it down to a really simple problem. Let's suppose I'm an 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, okay? And I've got potential to put some trend following in there. Okay. 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 can't I don't know how long the the trend index has been going, but obviously it's it's possible to to create um to do something like a Oh my goodness, I can't believe I'm saying this. You could do a a replication of the the trend index, which is something I don't normally advocate, but but if you wanted to, for example, 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 it's not a hard thing to do, but but you know, or you could just create your own trend index. It doesn't really matter to be honest. Um, as long as you got something that's investable. Um, so so you you take your let's say let's say you got 50 you know my my own back test goes back to 1970. So let's let's call it around 50 years. Uh it's got 50 years of data. You just use the whole of the data and you treat all of that data equally. So you basically say I think that you know 2025 is just like 1975 is just like 1985 just like 1995. So think I'm saying things haven't changed. I'm saying that to do any kind of optimization, I want to use as much data as I possibly can. So, I'm just going to use all of my data and I'm going to treat it all equally. So, that that's kind of the 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 some period of time and just say right I'm going to use that's what I'm going to do you know I think the world's changed and you know if I if I use say the last um two if we go back say two two and a half years and obviously we'll miss the outperformance of 2022 and that means your CTA allocation would go down significantly depending on your exact methodology it might go to zero but certainly be a lot lower than it would be in the kind of is in the full 50 year 50ear span and and you kind of smuggly say well you know I'm not putting any money into trend following because you know I've I've done this this incredibly sophisticated analysis and this is what I've done and this is great. Now the problem is with with with that is you've done something that is not back testable because you have essentially created a an arbitrary point. I mean it doesn't have to be arbitrary. you could you you know you you could come up with some logic for why you've chosen two and a half years or 3 years or whatever. Um but you've you've you've been able to you've been able to do something 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 two two and a half years was going to be very poor. Um, so you you've effectively kind of polluted your your so-called, you know, rigorous testing with 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 of identifying when the performance of a particular strategy whether it be 6040 or trend following or any other hedge fun strategy is likely to go down in the future. Um, and as we've discussed, people are really bad at that. And you know that that if people are really really bad at that, it means it's probably going to be quite hard to find um any kind of algorithm that that's truly in sample. So, you know, that's not being polluted with future information um or conditioning variable or something like that that's actually going to say, well, your performance of the future is going to be going to be better or worse. And if you do look at things like persistence and autocorrelation of things like that, generally speaking, um the the effects aren't especially strong. Um and you know, it's it's really really hard to to say, well, yes, given recent CTA performance, what's CTA performance like 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 two years of data. And that's sort of better in a from a kind of point of view, you're no longer cheating with future information. The problem is if you do that what you'll find is that your performance will be really bad because generally speaking the more data you have the better it is for fitting and optimization and there's kind of a um there's a degradation of of out of sample performance as you reduce the size of the data you have available to you. So, you can imagine if you do something really silly, which is do an optimization based on the last 10 days. Um, you can see how that would be kind of crazy because you'd be well or even ignoring trading costs because obviously you're going to be pulling your money in and out of funds non-stop and putting it in 60/40 and vice versa. Even ignoring trading costs, you know, you're just going to have mostly noise. It's just going to be at best it's going to be something just really badly. So, the 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 starting you're getting down to the point where using the last two or three years of data because you think that something has changed in the last 3 years and you test that you find that it's not going to do anywhere near as well as just yeah sticking to your guns and essentially assuming you can use all the data that you can. So that that's kind of the the theoretical answer to the to the question and and um I'd hoped after saying that that they would pick up the bill, but they didn't. But anyway, that's that's life. >> So 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? Um, but let me let me preface this with the fact that what surprises me is when I hear this argument, uh, which I do, as you rightly point out, I do that a lot, uh, over the, uh, the years. Um, some things change and and usually is when performance is is is less uh, than than the average and all of that stuff. But my but my answer to that is well, the world is always changing. And if you look at say the company that I work with, you know, we've been doing trend following for 51 years. Can you imagine going back to 1974 and think about how much has changed in that period of time yet the strategy um continues to work. Now clearly you need to adapt and you need to do research. uh so uh in that sense I don't subscribe to the fact that you can just uh apply rules from the 70s today and expect necessarily the same outcome. Um but I think the strength of of this particular strategy is that it is adaptable and it has proven over many many decades that it's capable of over time produce um 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 Dawn um we went back and looked at the rolling um volatility of the Barclay CTA index and back in the 70s and the 80s it was you know more than 25% annual volatility. Today that index is less than 5% annualized volatility. So clearly return should be lower if you're just looking at at those kind of overall stats without you know looking into the stats. So um no I mean actually I think it's a fair question to to to ask but I think uh I think we have a really good answer uh in our case. Yeah, I mean the issue is that if you think about a different kind of statistical testing which essentially is if you sort of look at the sort of rolling performance of trend falling over time and say well has that degraded um visually you can see some degradation and I appreciate you know it's you kind of have to do volatility adjust in a sense because you know the the mark the markets of the 1970s were a lot more volatile than they are now particularly commodity markets. Um so in even though we are risk targeting we're trying to risk target over time to get the same level of risk um it's still going to be hard particularly in the earlier days when when there were fewer markets there was less diversification so that also made it harder to you know get get a lower vault um but but even if you you sort of accept the argument that yeah looks like returns are degraded you still don't see a statistically significant difference in returns and because it's quite a low sharp strategy anyway um you you know it's going to take quite a long time, you know, possibly even another 50 years to know for sure that that that you know that things have changed and it has definitely stopped working, quote unquote. Um, so that that's the that that's the kind of the I mean, I've said this I said this before in a podcast and somebody picked up on LinkedIn, but but really you're at the there's this, you know, you're at the point where statistics can't really help you. You either believe you either believe or you don't believe. The only thing I can say is that yeah, people have been really bad at at sort of timing investment in and out of strategies. Uh, and there's lots of evidence of that. Um, so I my my kind of view is is generally speaking your starting point with anything should be buy and hold. Um, you know, whether buy and buy and hold underlying assets, unless you're pretty sure you can, you know, you've got a lot of confidence you can do better by trading them. Um, and if you're investing in in funds or or strategies or risk factors, then then again, uh, you know, you should be buying and holding those funds or or strategies or risk factors unless you can prove very convincingly that you can do better. And, um, you know, all the evidence I've seen is that it's quite the opposite. People do a terrible job of timing. >> Yeah. No, absolutely. Speaking of timing, Rob, it's about 1 hour. It's a good time. We we talked already about Fed independence which was one of my final topics so I think we can leave it there. Yeah. >> Yeah. No, absolutely. This was great great to catch up with you. Um and um thanks for for all the articles you brought along and um and all of that. And of course, for all of the use, for all of you listening, uh if you want to send a little bit of love to Rob, why don't you go to your favorite podcast platform, leave a rating and review, um so that more people can join us uh when uh when Rob and all the other great co-hosts are on the show. Speaking of a great co-host, the next uh one uh next week uh that is joining me will be Andrew Beer. So, uh definitely uh worth tuning into. I'm sure we'll have uh our usual interesting conversations um proper CTAs versus uh people who replicate CTAs and that's always fun. Uh and he's a good sport and I know he's been publishing some stuff recently that um um will be uh probably good discussion points. If you have some questions for Andrew, which I hope you do, you can email them to info@toptradersunplot.com and I'll do my very best to make sure that we get them uh 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. >> 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 iTunes and subscribe to 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 in iTunes. 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. [Music]