276 Systematic Investor Series, Group Conversation Part 2 – December 30th, 2023

[00:00:00] Intro

You’re about to join Niels Kaastrup Larsen on a raw and honest journey into the world of systematic investing and learn about the most dependable and consistent yet often overlooked investment strategy. Welcome to the Systematic Investor series.

[00:00:23] Niels

Welcome and welcome back to this week’s edition of the Systematic Investor series with Katy Kaminski, Cem Karsan, Rob Carver, Mark Rzepczynski, Rich Brennan, Alan Dunne, Nick Baltas, Andrew Beer and I, Niels Kaastrup Larsen. As you can tell from this introduction, today as well as last week’s episode are very special because it’s the first time all nine of us are together for one big conversation and debate.

As you may remember, we did, unfortunately due to some technical issues, lose Rich during our recording, so that will explain why they are not so active in today’s conversation. But without further ado, let’s continue our conversation where we left off last week. I know that Rob already stole one of your topics, but your list was pretty long. So hopefully you have something else.

[00:01:14] Andrew

I guess the question I would ask, we’re trying to define trend following, I’d be curious how people define non-trend. Because back when we started in 2015, machine learning was a big thing, then it went to counter-trend. It seems like there’s a sort of catch-all for non-trend strategies. I guess I would really turn it back to the group and say, how do you define that side of it?

[00:01:42] Niels

All right. Well, Alan, you are the one person that has allocated to non-trend, I think. How does that feel?

[00:01:49] Alan

Yeah. I think there’s a pretty decent understanding of the taxonomy in the industry overall. I think some strategies tend to fall between the cracks a little bit, but down to answer Andrew’s question, I think when we talk about trend following, there is an inherent assumption that one, it’s price-based, so price is your primary input. Secondly, we’re talking about medium to long-term timeframe. Thirdly, we’re talking about, obviously, trading in the direction of the prevailing medium to long-term trend.

So, thinking about strategies that don’t fit within that, say, short-term strategies. I think generally we understand short-term systematic strategies to be strategies that are of a timeframe of intraday out to maybe five day, possibly a little bit longer, maybe an eight days average holding period. So they’re distinct from trend following, in terms of that timeframe.

You could be trend following momentum strategies, but if you’re pursuing them over that very short-term timeframe, generally, people think about them as short-term strategies as opposed to trend following strategies, so they’re still in the non-trend category. The second thing then, obviously, in terms of the input, if your inputs are non-price inputs, then that puts you into other categories like quant macro.

So if you’re looking at either market data such as yield curves or yields, etc., or you’re actually looking at economic time series (and I suppose recently we’ve had the idea of economic trend following but to keep the trend part of that out of the argument), but certainly, non-price, i.e. market or economic time series being part of your input, that puts you into more of a quant macro.

The third bit is that if you’re not actually trading in the direction of the trend, then obviously, you’re counter-trend. So that’s very clearly non-trend as well. So that’s three very clear categories. You can also have traders who are discretionary and they could be trend followers. A lot of macro traders are effectively trend followers but they manage their risk differently. They’re not systematic. Their portfolios aren’t as diversified. They’re not trading 50 to 100 markets.

But if you speak to a lot of macro traders, very often they’ll make a lot of their gains from one or two big trades in the year before they capture a big move. So it is trend following in terms of philosophy, but it is differentiated from trend in terms of the discretionary input. I guess when we think of trend, it’s systematic, medium-term, price-based, and in the direction of the trend.

If you’re not doing that, you’re doing something non-trend in some shape or form. So I think there’s a fairly reasonable understanding. Sometimes you find strategies that are maybe 10 to 20-day average hold. Is that short-term? Is it trend following? And then obviously you have the hybrid strategies which have trend and non-trend. So where do they fit in? But that would be my perception on it.

[00:04:59] Andrew

Going back to what Katy was saying about preference functions, I think one thing that’s interesting about trend, as an allocation, is that there’s a sense of permanence to it; that you can look at it over seven years, you can model in all sorts of different ways and you feel like this is something. The thing is, if we’re asset allocators, we are building capital markets assumptions.

Going back to Nick’s point about having an index, somebody needs to decide what they think a strategy is going to do over time. In hedge fund land, we know these things change a lot over time. You model equity long-short in 2005, it’s very different than how you would model equity long-short today.

I think one of the interesting things about the distinction between trend and non-trend is that trend should be more predictable in that it should reflect some underlying economic rationale as to why you’re able to extract excess returns at very specific moments in time, in particular, but not get killed the rest of the time.

Whereas the non-trend stuff, on the other hand, it can sound really, really appealing because it often sounds great, I think it’s just hard to say, I wish I’d been doing this in 1972. So for long-term allocators, I think one of the challenges with the space, and going back to the language on it, Katy coined one of the best terms in the space which is crisis alpha. So I was shamelessly copying that for a while and attributing it to it.

But the problem I found is that people then made their allocation a tactical call, and if there hadn’t been a crisis in six months, it wasn’t just how they were making a decision to add it to their portfolio, it’s that they were communicating the rationale for putting this weird, complicated thing in their portfolios to their clients as basically something that was going to make money in the next six months because the world was going to fall apart. The world doesn’t fall apart and the clients are saying, well, why do we still have it?

So I think part of the challenge is, around the language and the definitions and everything else, to understand the audience of the people, because there are a lot of people who will listen to this call and you’re talking to a receptive audience. But the space hasn’t grown in 10 years. I think part of the reason is because the language is really intimidating and the description of products is really intimidating to a lot of people out there who control a lot of money.

Anyway, I’m the guy who’s trying to do it in English. Katy, I’d love to hear what you think.

[00:07:24] Katy

The most interesting thing that happened to me in the last year or so, I had one client that came in and said to me, and I thought this was a very interesting way to put it is, they were saying, we know that the world is changing now. We know that the macro environment is uncertain, that there’s a lot of change. Whether it’s crisis, whatever it is, there’s change coming. Inflation has returned and our portfolios don’t like it.

But we like trend following because if you think about macro trading, what I always thought was fascinating, macro trading is about 50% – global macro is 50% correlated with trend. The reason for this is because trend and macro traders get into the same trades, they just get into them at different times.

So what this particular client said to me that I really appreciated is he said, I’ve tried to source macro managers, it’s so hard because it’s hard to trade all of the macro themes out there. How do you trade the yen trade perfectly and also trade what’s going on in other parts of the globe, in Argentina and all that stuff? It’s hard, right? So investing in a systematic trend portfolio is really about having a liquid global macro exposure where you’re capturing a good part of where the world is moving.

When it moves a lot, no matter if it’s from crisis or if it’s from rising rates, you just want to be there as part of those moves. Yes, you’re not going to pick the tops and the bottoms and you’re not going to be prognosticating on what the trade is, but you’re at least going to be in there, in those moves, and you’re going to do it in a liquid way so that if the world changes, you have that exposure.

I thought that was a really interesting way to put it is really talking about how trend, as a strategy, has long macro uncertainty and it’s always going to be highly correlated to macro themes no matter what they are. So if you want macro exposure in a liquid and less manager-specific and thesis-specific way, you add some of that liquid systematic exposure. I thought that was a really nice point that he made and I’m saying it again because it was so good.

[00:09:43] Niels

All right. I will jump to you Mark since you are up next. What have you brought along for our conversation?

[00:09:50] Mark

Well, only because we have such an esteemed group of systematic managers beyond just trend following of the taxonomy, we’ve been having a number of discussions with clients in showing some new models, and I want to talk about backtesting. What I mean by that is that you get the comment from a lot of investors, “I’ve never met a bad backtest in my life.” And then I say, “Would it be any better if I didn’t show you a backtest?” They say, “No, no, I want to see them.”

I show them a backtest and then they’ll say, “It doesn’t matter what you do, I’m probably going to discount it by 50% as a rule of thumb because whatever you showed me in the past is probably going to do half as well in the future, and maybe I might consider it if it does half as well as what you’ve shown in the past.”

So based on those types of comments, which I’m sure everybody has heard, what do you think is necessary to convince someone that you have a good backtest and what do you look for in a backtest if you’re assessing an investor? Because I think that ultimately, that has a lot of value for a lot of people who might be listening of how you would look at or view or what you consider as a good backtest at a very high level, because I know that there’s a lot of nuances you can look into.

[00:11:16] Niels

Well, of course, we’re super lucky because Rob has, I think, written about all of this in one of his many great books. So Rob, what do you think about that?

[00:11:28] Rob

Two separate questions really. One is, how do you deal with people who say those silly things to you? The second thing is, what do you look for in a backtest? I’m very fortunate not to be managing anyone’s money apart from my own, so I just have to convince myself that my backtests are okay and that’s normally fairly straightforward, although I do sometimes run into problems if I’m in a bad mood.

So I’ll probably go with the second question and hope that those of you who are still managing money can deal with the first. To be honest, when I look at a backtest, I’m not necessarily looking for a really good Sharpe ratio. I think this is probably the difference between, I suppose, people who work with backtests all the time and someone who’s just being shown one as a kind of buy-this-product thing.

There are lots of other things that, to me, are more important than that. For example, if you told me you’re running a trend following fund and I looked at your returns and you did really badly at times when trend following funds generally did really well, or vice versa, you did really well in periods when trend following funds have done badly, I have questions about exactly what it is that you were doing.

If it really is trend following, how come its correlation or its pattern of returns is so different? I’d also be looking at other distributional properties apart from just the straight-out Sharpe ratio. So, I’d be looking at the actual risk as well. If the risk is very high, for example, and you were trading futures, I might be a little bit concerned about the degree of leverage you’re using.

Whereas, if you have big upward movements, because you’re generally a person who’s buying vol, I’d be less worried because the downside is naturally more limited. I would be hoping to see statistics on things like correlation and costs and things like that because, at the end of the day, what I’m trying to say is not necessarily, “Is this widget the best widget that exists there?”

That’s a really hard question to answer just based on a backtest and it’s probably dangerous to do that just based on the backtest. I think you’d be quite naive to pick one manager over another purely because they have a better backtest; the Sharpe ratio alone was better. But I would definitely pick one manager over another if their backtested Sharpe looked a bit worse. But there are other characteristics of strategy that I expected to see were there versus somebody who had this amazing account curve but which bore no relation to what I’d expect.

[00:13:51] Niels

I’d love to actually hear Cem, for sure, but also either Katy or Nick actually, because you probably, in your model building, also deal with this issue about backtesting. So maybe one of you first and then Cem.

[00:14:09] Nick

Backtesting is the only tool we have to bring a hypothesis in the data, and I think in itself is the curse as well. We have a big team and we look into those patterns and how we can systematize them. I think the first thing we have to do, even before running a backtest, is to build some discipline and awareness.

I know it sounds very theoretical, but unless we call it out, we will all become genuinely biased by the natural temptation of just picking the best line, whether that is a Sharpe or performance in the drawdown, or whatever the characteristic we’re after. I think unless we call it out and become conscious, it will not become second nature.

The extent to which we can make it second nature to our process of researching, then I think it’s a matter of hypothesis forming and testing, and again, resisting the temptation of looking into another result and then, “Oh, yeah, of course that happened and then obviously that happened, and that, oh, it makes total sense.” No, it doesn’t make any sense. I think that is the time when you do research; that you say, okay, now we’re data mining or now we’re entering into a territory of just reading the data.

I think it’s more of a cultural build rather than how do we build a system or a research engine for us to conduct research. So that’s the first step. The second step is, obviously, we end up having a backtest. So what do we do about it? I’m going to quote some of the points that Rob made here. We have to look into some stats. By the way, something that is better on a backtest is not necessarily better on a forward-looking basis.

Even more so, something that we have in a backtest that has no impact, it doesn’t necessarily mean it shouldn’t be there in the first place. For example, some of the work we do is to put some kind of last line of defense in concentration risk in some of our portfolios. You know that in the backtest, historically, it doesn’t have any impact, but surely you know that if the extreme scenario occurs, in principle, you wouldn’t be hit as much as you would have been, possibly at the expense of not deploying some extreme exposure that ends up being your way. But those coin tosses, we’d rather not have.

The last thing I would say is that in that cultural build that we’re bringing in the team, we’re also trying to stress the way we think about methodologies and tests of methodologies. I’ll give you one example. It’s not in the trend space but I think it was quite a nice example to showcase some of the work we’ve done recently. We’re looking at some commodity curve strategies; the classical buying the back end of the curve, shorting the front of the curve, doing it across commodities, and so on and so forth, benefiting from the steepness of the curve on the front.

There’s this notion that the roll yield on the front of the curve is extremely expensive to maintain. So here came the hypothesis, if I short the front, do I always make money? So then we said, okay, fine, let’s run some sort of a Monte Carlo that tries to position itself across a curve in a random fashion but always short the front. So, really stressing the selection mechanism on the back and trying to identify whether shorting the front is a panacea and all the rest is just statistical fluke.

So this are some of the analyses we tried to bring forward, stressing the methodology, but also building the culture. I think the culture is the most important thing. Anything else just follows. Katy, over to you.

[00:17:24] Katy

You said all the good stuff. I agree, pretty much 100% with you, all the things that you said. I think the other thing that we try to think about, in addition to that, is not being overconfident. Also, complexity is something that we’re very concerned about because complexity is something that is much more akin to backtest bias. So trying to fix a model and be smarter than what you thought before is just tinkering oftentimes. So it’s really about having that philosophical view.

I’m always a little skeptical when someone comes in and says, “I have the next best thing.” I say, “There are a lot of smart people out there doing this.” It seems to me like that is more likely going to be tinkering with your process. So really sticking to a process and having a high amount of skepticism for change and complexity, I think is a very important part of a good systematic backtesting and research framework process.

[00:18:28] Cem

I think the most critical thing, and you kind of alluded to this with the Monte Carlo simulations, is to try and remove path from the backtest. You have to do simulations that allow for all scenarios. To the extent that outcomes depend on path, and some strategies will work because certain paths are more likely, that needs to be explicitly laid out in the dataset that you’re managing so that’s well understood.

The second part is understanding the degrees of freedom of the strategy. So being very explicit about what the strategy can or cannot do, how many factors it involves, where those play out, and how those can be used potentially to manipulate outcomes, those things have to be explicit when looking at a backtest and well understood and statistically analyzed not just on some historical dataset.

[00:19:23] Andrew

I think the questions you’re getting are from people who have had bad experiences with a lot of people presenting indices that were nonsensical, or backtested data that was nonsensical. Just to sensitize around a certain point, if somebody came to you and said these are the stocks I would have bought 10 years ago, you’d laugh them out of the room.

But if you’ve been running a systematic strategy that has clearly codified for 10 years and you haven’t changed it, and then you tell people this is what it would have looked like in the preceding 20 years, it’s much more credible than if you come to them and say we’ve just found the holy grail of Sharpe ratios and this is what we would have done if we’d been doing it. So I think if you can link it to stability of the underlying strategy.

The second thing I would do is show them what happens if you play with the parameters. Because what people are used to seeing is somebody goes into a room, they turn all the dials on this until it comes back with a Sharpe ratio of 1.5. They come out of the room and say, we found it. Show them. What if we take the dial here and turn it from seven to four and that one from five to eight, and we make dumb decisions in it? Does it still look close to what we’re talking about or is the backtest so sensitive that you change one parameter at the margin or something in your notes?

So, on the replication space, one of the things that ended up convincing people that it wasn’t crazy was we could show we’ll pick the dumbest factor sets and see if they work. We’ll pick timeframes that we think are highly suboptimal and see if they work. If it works okay in those circumstances, then you’re starting with, it’s okay, these are the judgments that we’ve made to make it better. That’s from being on the front lines.

[00:21:09] Niels

Okay, cool. I’m going to ask a question which is, unfortunately, something that I wanted to ask Rich about because I think that since he’s part of that small group of people who will define themselves as classic trend, I think that is one of the discussion points we’ve had. But overall, my question or my thought is this thing about whether or not trend followers, but even I guess vol managers as well, whether we can afford to stand still in our research.

Of course, we know from some of the classic trend, they say that they actually evolve by standing still because there are fewer of them. But from my point of view, I guess I have an interesting seat because the firm I work for has been around for 49 years. So, we started out as what you probably would classify as a classic trend follower, today, using volatility breakout systems as our signal generator.

But later in life, about 15, 18 years ago, we started to evolve that whole process. Of course, it was based on the evidence that our research team could find. In one sense, one thing we did was we added an extra signal generator to the process, and then later on, we also changed the whole risk management from going from a market-by-market approach, which is the classical approach, to this holistic approach of risk managing the whole portfolio using correlations and volatility and so on and so forth.

I guess what’s interesting for me is that I can kind of see both, to some extent, when I look inside the engine. I can see how both of those approaches have evolved from some of the research data that I have access to. So, I’m curious to know, and since we can’t get through to Rich right now, but let me throw it to you, maybe, Katy, to begin with, this thing about research and whether in a strategy like trend following, for example, where you could say that we’re standing on shoulders of the pioneers in terms of the golden rules.

But what are your thoughts about this thing about research and how much change is too much change in our research, so to speak?

[00:23:39] Katy

I love that question because one of the challenges that people often forget about our space is that it’s really easy to replicate correlation but not easy to replicate returns. What I mean by that is that you could take a simple moving average model and get very high correlation to the industry, but you don’t want to invest in that. So what that means is that investing in our space is about the details. It’s about getting the details right, getting the risk management framework right, thinking through the small parts, not just the big overall strategy.

Another thing, for me, that is also very important about a philosophical trend system is really building a system that will change as markets change over time. So yes, that means you’re not going to be throwing in tons of new models, but you always need to be receptive to the idea that with some of your models, that you might have more diversification if you think about this in different ways.

So really, the goal is parameter diversification and smoothing the reliance on one thing that gives you that correlation but doesn’t give you good returns: risk-adjusted. I think that’s where we struggle because everyone says, well, I’ll just use a moving average and then I get 90 something percent correlation. Good luck treating that in practice as opposed to, I think, the real sophistication which is making sure you get all the details correct.

[00:25:12] Niels

I want to come to you, Cem, in a second because I want to hear your thoughts about research. But I, actually, want to first go to Andrew because I think this is quite relevant, in a sense, also from where you sit looking into this industry, trying to replicate, so to speak, the sum of all of this research, so to speak. Actually, what Katy said about that you can get the correlation right, but it doesn’t mean you get the returns right. You kind of have to get both right. So, I’d love to hear your thoughts.

[00:25:42] Andrew

One of the things I love about this space, I think the space does evolve over time. We run our own internal simple trend following models and part of the issue that we had with it was that we don’t think that, if we went back to 2005, these are necessarily the models we would have chosen at that time. In terms of what we do from a replication perspective, we’re not trying to actually do what managed futures funds do, we’re just basically betting on some short-term stability in the correlation structure of the market.

Because when you think about diversification, and we believe that diversification helps enormously when you’re running one of these funds. But if you’re looking at in a short period of time, over the past two or three or four weeks, all those 70 instruments are either going up or down or staying flat.

So, when we looked at it from a replication perspective, the idea was, basically, how confident do we feel that those near-term correlation characteristics of the market will continue, again, over a short period of time? So, it is a balancing act because we don’t optimize around correlations.

All this stuff is a judgment call. We were more concerned about what we thought would be out of sample out of performance relative to the underlying index but with all the nuances that Katy is describing and that you’re describing in terms of the evolution of it.

The reason we like what we do versus in the US, there’s an ETF that uses a static trend following model that really hasn’t changed in a couple of decades. If you guys are all doing something, if the giants decide that there’s a better way to do this, on a going forward basis, and you evolve what you do, then a good replication of the space should adapt and follow what you’re doing as opposed to making a bet that you’re going to be doing the same thing in 10 years.

[00:27:35] Niels

Cem, before we jump to the next topic, what are your thoughts on this?

[00:27:39] Cem

Again, I’ll give you a quick-ish answer here. My view, broadly, is that markets are very much a voting machine in the short term and has much more to do with flows and supply and demand in short time intervals. That changes dramatically as market structure changes. Market structure is constantly evolving. So, to sit and somehow stick to models from 5 years, 10 years, 20 years ago, where market structure was very different, I think is an incredibly flawed process.

You have to be constantly mindful of market structure and what’s changing and how that changes the system. That said, the longer timeframes you go to, the less the just supply and demand, on a short-term basis, the more it kind of reverts to the broader trends. So I think time interval matters a lot.

I think you want to not lose the core things that are important to kind of trend and strategy over longer time intervals. But over any period less than a couple of years or a year, I think you really have to be mindful of market structure and evolving constantly.

[00:28:50] Niels

Okay, great. Now that we’ve been through all of us, except for Rich of course due to technical problems, I wanted to throw out a quick question to everyone, and I’ll call out who I would like to answer this. This is literally something where it’s like a 10-second answer, but I just wanted to get your thoughts on that.

It’s a very simple question. It’s the most important lesson that you’ve learned from the year 2023. If I could start with you, Alan, just a very quick answer to what’s the most important thing you’ve learned in 2023.

[00:29:31] Alan

I think you phrase it as learned or relearned, so it wasn’t a new learning. Again, as an allocator around, it was another year of dispersion and the importance, from my perspective when selecting or allocating to managers of being diversified, if you look at the performance of the industry, it’s flat to slightly negative overall, but managers plenty positive for the negatives. Some managers are particularly challenged here, but some are doing well. So it reiterated the importance of diversification in terms of manager selection.

I think the second thing that came back to me as well is the challenge of timing performance or forecasting performance from the perspective of, if we went back to the end of last year, coming on the back of a really strong year for trend following and managed futures, looking at the macro environment, you could make a really compelling case for the strategy. Higher interest rates were also a tailwind for the strategy, but yet, it was a tough year. That’s just part of the statistical fluctuation that you get with a strategy that you just have to accept.

So while people will always ask you what’s the outlook, you always have to caveat that from the perspective of yes, the outlook is positive or was positive and still is positive, but year to year, the fluctuations will always be so great that it’s very hard to forecast on a short-term 6-month to 12-month time horizon what returns will look like. So they’re not new lessons, but certainly, there were old lessons we learned this year.

[00:31:10] Niels

All right. That was a long 10 seconds, so maybe we can do this a little bit quicker. Rob, anything particular that you learned in 2023?

[00:31:17] Rob

I don’t want to be cocky. I think March taught me, again, that you can get kicked up the ass whenever you least expect it. The last time was Thanksgiving a couple of years ago. Same thing. You think you hit a new high watermark and then bang, you lose 6%, 7%, 8% in a day, two days. So , yeah.

[00:31:38] Niels

Okay, cool. Andrew?

[00:31:41] Andrew

Just how unpredictable the business is. I think if you had gone to the end of 2022, going back to the point I made earlier, again, long-term trend looked unbeatable. This year, a lot of the things that had cramped people’s returns, etc., last year and had caused people to get whipsawed in other years are actually working quite well this year. So in this space, just year to year, we’ll have different winners and losers and it’s hard to know who’s going to be on the top.

[00:32:09] Niels

Sure. Cem, quick thought on what you learned.

[00:32:12] Cem

It will be almost like a reference to what I just said before. Early in the year a lot of the signs were there for too much vol selling and a potential existential risk, but the structured product supply is something that I had not been focused on before, and the more we dug in, the more we realized the volume and size and scale of what was happening there.

That was a really illuminating thing for me and something that always, you’ve got to keep your eyes open for things that you’re maybe not thinking about historically, that aren’t in the data set in how market structure is changing.

[00:32:47] Niels

Sure. Nick, anything on your side in terms of learning or do you know everything?

[00:32:52] Nick

One thing was just the déjà vu of end of 2020. At the time, we had a variety of clients coming and feeling the act of regret and putting some long vol trades because March was like the most recent experience. Guess what happened in 2021 and 2022? All those long vols did not perform. And then this year, we’ve seen clients coming back and say I want to trend. Again, another act of regret but look what trend has done this year.

So I think the point is when we look into those strategic allocations, we should be looking at those without necessarily acting as regretting what happened, but rather just looking forward and hedging all the outcomes.

[00:33:27] Niels

Great. Katy, thoughts on 2023?

[00:33:30] Katy

I think the biggest thing that I learned that was interesting in 2023 is that we wrote this interesting paper that talked about the phases of the bond trend. In that paper, it was a totally historical analysis, but this showed me how much history, even though it doesn’t repeat, it rhymes.

So this whole year, just looking for the flattener in the curve and looking for the bottom of the fixed income curve and paralleling that to how trend signals had done in history or hypothetical history, it was really interesting to see that there is really a cycle of fixed income that we’re involved in that we’re kind of seeing go from phase to phase.

So I think, for me, that was really fascinating to learn how history is actually repeating itself, not exactly in the same incarnation, but walking through that trade was very fascinating to me to see it from that perspective.

[00:34:33] Niels

Yeah, absolutely. Mark, what was your key takeaway from 2023?

[00:34:39] Mark

I’m going to go to the esteemed investor, Yogi Berra, who said predictions are very hard, especially about the future. I think that that’s what we find out every year. In some sense, the reason why a lot of people like trend following because at some level, it’s supposed to be, to some degree, non-predictive. So you say, I follow what the market is telling me, I’m not making a prediction.

Many other strategies, you have to implicitly make a prediction level. If you’re a value investor or if you’re looking at valuations, you’re making a prediction that they’re going to meet revert. So we have to always embrace non-predictability or understand predictability is hard.

[00:35:26] Niels

For me, the biggest takeaway was really just relearning that a combination of stocks and trend following is such a powerful combination. Just looking at two extremes, 2022 and 2023, they couldn’t have been more different, but yet a simple 50/50 portfolio of those two assets or strategies would have had positive returns in both years, and combined, they would have done really well.

So even as a practitioner and finding it really hard to embrace the stock part of that, I’m truly hoping that investors will take that evidence as a good inspiration for diversifying their stock portfolio with some trend.

In terms of other topics, we’re going to go around as many as we can. So, Katy, I’d love to hear what your second topic that you brought along is, and let’s see if we can add some answers to it.

[00:36:31] Katy

I think the biggest thing that I’ve spent the last two or so years thinking about is fixed income. A lot of this coming from we’re trend followers, we’re always looking at trend in different horizons. The interesting thing with the fixed income trend is it was a 40-year horizon in one direction.

Going through the pivot to a rising rate environment led us to talk a lot about very different things. One is, we were very interested in when is trend following going to be long, when is it going to be short, in what environments are we going to… what’s the next phase? We actually just have a paper that just came out that I think published today about thinking about what’s the next phase of the fixed income trade. So give some prefix to that and then I’d love to hear my fellow panelist’s thoughts on this.

We did this empirical study where we looked at how trend signals did during rising rate and falling rate environments and conditioned that also on the shape of the curve. What was interesting with this is that when the yield curve was inverted, trend following did very well being short and less well being long, and it was predominantly short. And then as the curve flattened out, it was much more mixed and trend still tended to be short, but the signals struggled. So it really sounds a lot like this year.

As you got that flatter yield curve, you started to see that pivot point to when you are going to be possibly long again. So I think the question that we’re asking ourselves right now is, what is the next phase of that fixed income trade? We think it’s a steeper yield curve. But of course, there’s a lot of ways to get to that steeper yield curve. Everyone in the marketplace tends to be very optimistic thinking we’re going to get cuts and then we’ll have this naturally nice steep yield curve.

I always think that there’s usually a couple of things out there that people are missing or underestimating as a risk. Is it the fact that fixed income, maybe, has too much supply and that we can get actually that bottom of the long end of the curve at some point? Or are we going to go into a totally different phase? But I think, from the trend perspective, the next natural progression is to get to that steeper curve.

I think the real macro question is, what gets us there and what is the exact shape of it? So I think that’s what I’ve been thinking a lot about, and I think it’s a really good point for discussion. I think Rob has something he wants to say, which is good.

[00:39:16] Niels

Before Rob jumps in, because I want to hear his answer to that as well, I just want to mention that I actually heard on another podcast in the last day or so that apparently, the Bank of America survey of fund managers that just came out has the fund managers being more bullish, more long bonds than ever before in its history. So that’s very interesting.

Something else was raised I think in the same podcast, and that is whether or not there is a law out there that dictates how much funding the US can do in the short end versus the long end and whether or not Janet Yellen was in breach of these rules and therefore had to shift much more the future funding into the long end, by the way. Anyway, this is just what I heard. Let’s jump to Rob and get some thoughts.

[00:40:05] Rob

I’m not going to speculate on what’s going to drive the yield curve going forward because I don’t really feel qualified to do that. But spookily, I did a very similar analysis to Katy but about 11 years ago. You’re right that the shape of the yield curve is important. Of course, that’s because that affects the amount of carry that you’re getting on your positions.

So if the yield curve is very steep, then your longer-end bonds are going to be getting more carry. That means that you if you’re long those bonds, you’re getting that extra headwind from that return. But also, assuming that your trend signal is based on the total return series or what we’d call the back adjusted price, it’s a much cleaner and stronger signal.

If you’re trading carry separately as well, as I do, then you’ll get a double helping of that. Whereas, obviously, if the yield curves flat, then the carry component of the price isn’t really doing very much. One thing that I did recently that’s quite interesting is that if you strip the carry out of a bunch of futures total return series and look at both the behavior and profitability of trend following in those assets, a lot of it disappears. So that kind of tailwind of extra carry on the long side, I agree, is definitely an important factor. But as to where that’s going to come from, over to you guys because I have no idea.

[00:41:16] Cem

Actually, my topic will just dovetail right into this. I think the most important thing, when looking to the future, is not to try and predict an outcome but to try and predict the distribution of potential outcomes. I think doing that is actually way easier, not that it’s easy, but it’s a way easier path. All kinds of things can happen between A and B, but understanding the forces at play and what that is likely to mean for the broad distribution is much more straightforward to do.

From my perspective, we were able to do that, for example, in 2020 by just realizing that populism had become a big thing and fiscal spending, there was likely to be a massive fiscal wave. That meant a lot of things, not just for higher rates, which is critical as highlighted here, the most important thing. But it also is important to understanding the deglobalization trend and the coming conflicts that were coming.

We were out there very publicly saying in 2020 that expect some big geopolitical, global, economic and hot war to come. People think that was an idiosyncratic thing. It’s not idiosyncratic when you look at the pressures and understand the risks and understand the probabilities and pressures. It’s all about incentives, as we all know, and if you start to understand those incentives better based on broad structures, you can really model distribution better.

So to that end, what are those distributions like going forward? What might that mean for trend? What might that mean for volatility? Our view is that this pressure that we’re seeing that is more recent is a regime change, and at the core of it is this populism, this desire to fix inequality which has been created by monetary policy for 40 years. That is driven by a political reality, by millennials on down, and a desire with who are at 40% of the wealth creation household formation, as I’ve stated many times before, baby boomers.

That simple reality, which seems like such a simple little thing, is so critical, because at the end of the day, that drives a demand push structural economy and it puts the Federal Reserve in a box. It no longer allows monetary policy to be dominant. That simple fact changes the distribution of outcomes for so many assets in so many ways. We saw that in 2022. In the context of that, you still see what we’re seeing now in 2023, which are cyclical pressures against that within a secular trend.

So if you start to understand this, where we are secularly in a regime change and what that means broadly, and then you understand the cyclical pressures and the reaction function of it, then you can begin to model. So our view is broadly that 2023 is a counter-trend year into a much bigger, broader trend. I think that will hopefully be good for trend following, broadly, given that 2023 was a challenging year.

I think 2022 is more the core of where the broad trend will be. I think that will also mean more short for volatility, much like we saw in the ’70s, more recessions, more vol of vol, seeing a lot more geopolitical conflicts, a lot more currency issues, a lot more cross-national commodity and other pressures where entities are battling and in competition.

So for me, nobody’s really talking about geopolitical issues this year because narrative follows price. But the reality is that’s only gotten hotter in a lot of ways. Obviously, Israel, Gaza, what we’re seeing there with Iran coming into the fray and working with Russia and China behind the scenes as a second front, I think that’s something that’s going to be way more important in 2023.

I think price and volatility amidst a recession and the reignition of inflation, which I think will likely come later next year, I think are all very important trends that will really be critical and important in the coming year.

[00:45:44] Niels

Okay, great. So maybe we’ll just have a more fluent conversation as we slowly, slowly start to wrap up the final part. We have another 30 minutes or so. So I don’t know whether Cem you want to throw out another topic or otherwise, Alan, what are your thoughts? Cem, do you want to throw another topic?

[00:46:08] Cem

We’re talking systematic trend following, I’d love to kind of discuss a little bit more geopolitics for a second to see if anybody wants to dive in and opine. But I’m really curious to see what other people think about what’s going on in emerging markets, Japan. I’ll leave it open here. What are the things that people have on their radar as the biggest risk for the year and things that they may be thinking about as they’re modeling 2024?

[00:46:35] Niels

Yeah, I’d love to see who raised their hand. While they think about that, I will say to you, Cem, that I can’t wait for the first conversation we’re going to release. Well, maybe not the first one in the new year because that’s going to be you and I alone, but maybe the second or third where we’re going to be speaking to David Dredge.

I think he is someone who’s uniquely positioned because he’s based out in Asia and has a clear focus on Japan and what’s changing out there. Of course, this will have a massive effect not least because of people using the yen so heavily in their funding, and so on and so forth. Andrew, you have a thought on this?

[00:47:20] Andrew

Back to your point about the distribution of outcomes, the distribution of outcomes seems really wide to me. Occasionally, people get asked or ask me questions about, where do you think the S&P is going to go? Where do you think interest rates are going to go? I fight it and I fight it and fight it, and then I finally throw out an opinion because I don’t think my opinion has much predictive value.

But about a year ago, I got asked where I thought the S&P was going to be, and I said, look, we have no idea. It could be down 20% from here, it could be up 50% from year to year. I got asked recently about interest rates and my personal view is interest rates are going to stay high for all the structural reasons you describe, but we could have deflation next year. People have not been wrong by a little bit on these predictions. I encourage you guys to look at it.

Jim Bianco did this incredible chart of short-term interest rates since 2010, and it shows where interest rates went and where the markets thought they were going over the course of the next year. You wouldn’t give a penny to anybody making these predictions. I’m a perennial optimist, but when I look at the world today, it feels really dark.

It feels like we have an entire generation of people whose brains have been melted by social media, that we have profound changes in a geopolitical structure where there seem to be common agreement on certain things that no longer exist anymore. So I think we’re looking at a world today where we’ve had, I think Katy mentioned this point earlier about we keep having these things that just don’t feel like they’re sitting on a bell curve.

We have a land war in Eastern Europe. We have the potential for war in the Middle East. We have taken a certain level of stability in the world for granted since World War Two, essentially. So I don’t know whether that’s good or bad for managed futures and for trend following. My view on the Fed last year was they finally ripped the boot off. In a sense, they had flipped from wanting to suppress volatility and a fear of ending up and being like Japan to the fear of being Arthur Burns, and that changed the calculus.

But look at the past six weeks. Trend following has been standing underneath a propeller for six weeks. I think volatility is going to be the name of the game, and those expected outcomes are going to be very wide.

[00:49:47] Niels

Yeah. I’d love to hear maybe also your thoughts, Alan, but before I do, I’ll throw something a little bit your way. Also, the way of Nick but I know he’s not going to comment on this particular part, and that is another thing that actually, Cem, we should raise with David Dredge. I think he put in one of his recent wonderful newsletters a plot from the Bank of England where they have like, I don’t know, 800 years’ worth of inflation data and volatility.

They group it together in blocks of 20 years. There’s like one block that has hardly any inflation and very little volatility and is like a standout plot, and it’s the period from 1997 to 2016. Everything else is just completely different. So this thing about that we may be looking back, and I think that’s maybe something we will do and about the last decade or two saying that was the odd one out, I think that is so true, but of course, not knowing what the future will hold.

But Alan, since you also do a lot of the global macro conversations on the podcast, what are your thoughts on this?

[00:51:02] Alan

I’ve seen that chart from the Bank of England. It basically shows what an outlier in the last 20 years have been in terms of inflation being on target and not fluctuating much around the target. Historically, we’ve seen much more variation in inflation. I agree with what’s been said.

The way I would summarize it is that if you look at last year, how many articles did we see last year about the end of 60/40 and the need for diversification and how the world is going to be very different going forward. Then we have a big rebound at the S&P this year and suddenly, you’re not reading about the end of the 60/40 so much anymore and everybody seems to be okay.

Last year was a year where, if you go back to Jackson Hole of 2022, all the policymakers were saying the world is going to be really volatile going forward and we’ve got these structural supply constraints. And then you get a year where inflation comes down and everybody forgets about these points that were supposed to be structural impediments for the global economy for the next few years. So I do think it is a question of which is the outlier? Is 2022 the outlier or is 2023 the outlier?

If you go back a couple of years, Ray Dalio wrote a piece where he looked at every decade back to the 1920s. Very often, at the end of the decade, you’ll get a change in the environment. So obviously, the 2010s was very much low inflation, stable GDP at a low level, QE, low rates. Now we’re into a new period of, I think, more volatile conditions. His point was that, within those 10-year periods, you will always get one or two years that are against the trend.

So my own personal view is that 2023 will probably be the outlier in terms of the Goldilocks disinflationary period coming back and that people are suddenly forgetting about all of those structural headwinds that policymakers pointed to last year in relation to supply chains and nearshoring and all of deglobalization, all of the things that we think might push up inflation and make it stickier over time.

Ironically, I would say in terms of how this impacts the bond trade and managed futures, if we’re going back to the old world, like the 2010 period, there’s going to be an enormous bond rally for the next two years which would be great for managed futures, I would guess. But then probably maybe beyond that, it could be a bit more challenging. Whereas if we’re in the new environment, it’s probably going to be a bit more choppy around bonds for the next 6 to 12 months or 18 months, but you will see bigger trends over the next decade. So I’d be more in that camp.

But even if you’re pessimistic on that outlook and think actually, the world is going to revert, bond yields would fall a lot more and there’d be a big trend there as well in the short term. So I think there are positives to be taken from both scenarios, but I am more in the camp of 2023 may prove to be the outlier in terms of being such a positive Goldilocks type scenario.

[00:54:13] Niels

Cem?

[00:54:15] Cem

Yeah. I would actually not take them as separate years. I’d take them together and look at them and say, hey, what does this look like? And it looks exactly like the data you see for the 10, actually, the 14 years from ’68 to ’82 when we had structural inflation. You had cyclical downturns. You get significant short-term volatility. There is a lot of rotation in, particularly, FX and rate. In precious metals, you get dramatic volatility way higher than the other regimes, but the market goes nowhere in nominal terms, and we live in a world of nominal illusion.

In the meantime, we’ve had inflation for two years. Where has the market really gone? The market is really, in real terms, down about 20% over two years. So this is what happens. If you fast forward, if you go to ’68 to ’82, the market went nowhere for 14 years, the S&P did, you had dramatic short-term volatility, dramatic recessions, you had multiple 40% declines, many 75% rallies.

But long-term vol got demolished and short-term vol actually was higher than normal. It actually fits exactly the distribution you’d expect given the model we’re seeing. So I think it’s important to back up and look at the bigger picture sometimes, and not just look month to month, year to year, and really see what regime we’re in.

[00:55:31] Niels

Rob, I was going to jump to you because you stole from the others in terms of topics in the first part of our conversation. So maybe you’ve found some more good ones.

[00:55:46] Rob

I feel that I should maybe do some roleplay here and pretend to be a classical trend follower as, due to technical difficulties, our classical trend follower has been silenced. Although some might say it’s a conspiracy and actually that we’ve done it deliberately. But there we go. So I’m going to steal one of Rich’s topics but actually something that’s quite close to my own heart as well, which is diversification.

I think one of the few things that I agree with these guys is that measuring diversification with a linear measure of correlation really underestimates what you can actually get with a nonlinear strategy like trend following, or for that matter something else that’s long gamma like buying vol, I suppose, although that’s not really my bag.

If we are in this weird new world that we weren’t able to perhaps articulate or describe or forecast, it’s different from what we’ve had. We haven’t got this lovely tailwind of a bond bull market behind us, for example, is diversification really the kind of thing that everyone should be focusing on?

In this weird regime where we can’t rely on traditional ways of making money, should we just be going all out with diversification in alternative markets? Just throwing equities, dare I say, Bitcoin, just throwing everything into the big bag and hoping for the best or is the value diversification what it’s always been and it’s not really dependent on the regime that you’re in?

[00:57:20] Niels

Okay, so I’d love to hear both from Nick and Mark on this one and anyone else who wants to jump in afterwards. But, Nick, I know you do have some exposure to alternative markets in some of your portfolios. What are your thoughts on diversification in general?

[00:57:37] Nick

I’m looking at diversification, I guess in Rob’s question, in two ways. How we think about diversification when we build a portfolio alternatives, but also, how we combine that with more classical asset allocation portfolios. There’s certainly an argument to be made with regards to diversification and the value of adding a few more assets. Obviously, they are much more costly and how you manage liquidity.

Obviously, if they’re not liquid enough, you wouldn’t trade too much of it so then we might not have the benefit that we thought we would have in the first place. Frankly, if I were to pivot slightly without changing the gist of the question and if I were to make almost like a mental jump to a radical point, we’ve had the 60/40 being the pinnacle of asset allocation for decades.

Cem mentioned the same thing. When we look into alternatives, we always think about a complement to 60/40. How about we replace the 60/40? I know that’s quite big, but what is 60/40 at the end of the day? It’s a combination of two themes that historically have delivered the two more traditional reward premia, that being growth risk and storing your money for a longer period, therefore getting a term premium.

A byproduct of that, with the anchored inflation, is you had the diversification that paid out quite nicely on the downside. What’s the key risk? Well, inflation rising and then equity-bond correlation skyrocketing.

So there comes a point that diversification is key. But it’s not about how we manage an alternatives allocation. It’s how we put that next to asset allocation or possibly start thinking about replacing it. Ultimately, if it’s about growth risk, well, we can achieve that by selling volatility in a way in a much more concise manner with reducing the spot movements, or we can do, I don’t know, linear carry.

And then you have trend following, not only to capture the opportunistic moves in the market, but also help when equity bond correlation spikes. So I would think of those alternative strategies, however we construct them, to a certain extent in a diversified format.

So again, to Rob’s point, we have to be very thoughtful. I’m personally a big believer not of just diversification, but prudent risk management in how we build those portfolios. But ultimately, that’s the radical point I’m going to leave you with. Is it about complementing 60/40 or really reshaping how we think about it on a forward-looking basis? So big question mark here. I don’t have a good answer.

[01:00:05] Niels

Maybe Mark does.

[01:00:06] Mark

I don’t have an answer, but I want to go back to this geopolitical issue because it’s always fun to have geopolitical discussions. But at the same time, we have a joke in a lot of our investment meetings with my partner. We say you can’t use the word feelings. Feelings are banned. So I always think about as systematic managers, what we’re really thinking about is there’s two views.

One is that you could say, what we want to try to do is identify regimes. Regime identification, like in machine learning, could be supervised or unsupervised. Supervised, you’d say, okay, this is where we are in the business cycle and here’s what should happen if we’re in this regime.

It could be unsupervised where you say like, well, I’m looking at data and the data seems to change to tell me I’m in a different regime.

But ultimately, the question comes for a model builder that, do you care whether we’re in a different regime? Now, some would say that I’m regime agnostic, that it doesn’t matter what regime because my models do what they do. Whether you say I’m at this point in the business cycle or if I have this geopolitical risk or this event is going on, I’m indifferent because my models just run no matter what because it doesn’t incorporate regime.

The other view is to say, well, I want to be regime dependent. If the shape of the yield curve has changed, I might change my behavior. If let’s say I’m at a different point in the business cycle, I might change the weights of my exposure. If I’m in a different type of regime, I might do something different. So, the real question that comes from a systematic manager is are you regime agnostic or are you regime dependent?

If you’re in either one of those, how do you incorporate that in models? I don’t have the answer because that’s why I’m asking you and that’s why we’re on a panel. So that’s the way I frame the problem.

[01:02:21] Niels

Andrew, you get the last word on this topic and then we’ll finish off with a quick round of outrageous predictions.

[01:02:30] Andrew

I should respond to both things. I think the evidence is that it’s incredibly hard to predict what regime we’re in. Even if you get the regime right and you get the macro call right, figuring out how to make money off it is, I think if you go back to the lesson of this year, if you nailed that… I know guys who said all right, we’re basically buying value stocks on the thesis that interest rates are going to go up. Interest rates go up in value stocks get killed because AI comes out of nowhere.

But I think just think in terms of the broader managed futures space, and going back to what Nick was saying, this change in correlations in stocks and bonds, if it persists, and AQR and others have put out I think pretty strong evidence that if inflation stays above maybe 2.5%, you’re likely to have positive correlations between stocks and bonds. That’s an earthquake across the asset management industry. Because the whole model of diversification, diversification was so easy.

The rolling standard deviation of a 60/40 portfolio in the US by the mid-2010s was 4%. The Sharpe ratio was well north of 1. It outperformed 98.5% of hedge funds over the course of the decade. But the underlying assumption was that stock and bond correlations would remain negative. So when people built their asset allocation models, the easiest thing for them to do was to say, okay, I’ve got equities over here and then I’m going to add a little bit of private equity because it’s kind of close to that. And I’ll expand into EM, I’ll do other things. You had two legs of an asset allocation stool.

The flip in correlation means that everything’s converged. We have this pithy expression which we coined back in 2022 that at a time like that when everything is going down, you have the sea of red across your portfolio. It feels like the correlation of everything goes to 1, managed futures is this beautiful beacon of green. In September, that was true. In October, it was true. We are a nasty red blotch in a sea of green this month or over the past six weeks.

I think the key though is that, fast forwarding to five years, the guys that we talk about, the allocators who are going to look good in five years are the ones who embrace the idea that this core tenet of diversification has changed. And whether you throw out 60/40 and say I don’t need bonds anymore because they’re not hedging and I’m just going to take equity risk or whether you go to a 50/30/20 model or you look for other sources of diversification.

The vol on a 60/40 portfolio is more than double what it was a few years ago. So clients and institutions that have been promised a smooth ride are not getting it. That’s where I think managed futures is almost uniquely positioned to serve as a vol dampener because of its long-term characteristics.

[01:05:16] Niels

Great, Andrew. I appreciate it. All right. Well, we’re going to wrap up this epic conversation that we’ve had, and that people have listened to in the last couple of weeks with a quickfire round just in terms of some outrageous predictions for 2024. I’m going to jump and start with you, Rob. What is your outrageous prediction for 2024?

[01:05:40] Rob

My outrageous prediction is that I will indeed turn to the dark side and become a classic trend follower.

[01:05:46] Niels

Okay, that is outrageous actually. Alan, what’s your outrageous prediction?

[01:05:51] Alan

Mine is to market forecast, and maybe not so outrageous to where things are going, but I’d say 10-year yields to trade below 3% next year and above 5% by the end of the year.

[01:06:03] Niels

Okay, nice. Andrew, what’s your outrageous prediction?

[01:06:08] Andrew

I think we’ll realize, by early next year, that people have no idea where we’re going, that we’re tearing up a lot of old playbooks. Maybe it’s not outrageous given what’s happened, but I think we are seeing a recognition that macroeconomic forecasting is not doing very well for us.

[01:06:32] Niels

Fair enough. Cem, I’m sure you might have some outrageous predictions since we speak a lot about these things.

[01:06:38] Cem

I have two but Alan kind of stole one of mine. I was actually going to say trades down to 3.5% and then gets above 6% by the end of the year. So that’s pretty outrageous given the current assumptions. In the process of that, the curve actually steepens, 10-year yields actually go higher eventually with lower short-term yields. And then second one, China starts moving on Taiwan at the end of the year.

[01:07:09] Niels

Wow. Well, Nick, can you top that with your outrageous prediction?

[01:07:14] Nick

I have two different points on prediction if I may. Number one, there’s a very nice paper by Tetlock called Superforecasting. It basically says when people make predictions, they’re actually lacking two important points. Number one, the time horizon, thanks for setting at least the time horizon right next year. But second one, not actually being checked regularly on their prediction. So the first thing we have to actually get here in a year from today and actually see what those predictions get right.

The second thing I’m going to say is that I wrote a paper about four years ago basically saying that when we try to time or make a prediction, what we have to not forget is the base rate. If it’s a coin toss, 50% chance point something is enough to get us in a better place. But when we’re talking about investments, and I’m thinking about investments more than macro in a particular way, these are all like high Sharpe ratio strategies.

In other words, the hit ratio of just holding them is 60%, 70%, whatever, you can work it out. So my point would be, it’s hard to even call the shots. I’ll just go for diversification on this one. I’m not going to make any call because I think 2022 and 2023 got everything wrong in a particular way. So these are two points that I have.

[01:08:26] Niels

Great stuff. Katy, what is your outrageous prediction for next year?

[01:08:34] Katy

I definitely got myself in a corner saying 6% this year, so we did get 5%. I do kind of agree the outrageous call would be that we did see that massive steepener later next year at some point. So I think my guess is that we’re going to see a steepener, but I’m going to be open to the range of possibilities of how steep that steepener is and exactly how that occurs.

[01:09:02] Niels

Good stuff. Well, Mark, what are your big, outrageous predictions for 2024?

[01:09:11] Mark

The important point in making an outrageous prediction is make sure that it’s going to be very hard for a measure, so I could still be correct at the end of next year. I’ll say something that 2024 will be the year that debt matters. Supply of debt, especially in the government side around the world is going to have an appreciable impact in a way that we haven’t seen.

Now, of course, how you measure that and rates and such is fairly difficult. So I could say debt matters, and next year, I could assure you that I’ll come back and say my prediction is probably true, but I won’t say how we’ll get there or what that means.

[01:09:53] Niels

All right, good stuff. Well, that kind of leaves me with the last outrageous prediction. I have two, two very different ones. One is that neither Joe Biden nor Donald Trump will be part of the US election, probably for different reasons. The second one is that DBMF will start to inflation adjust their low fixed management fee to cover the cost of inflation. There we are. We’ll see if any of those come true. We’ll have to go back next year in our session in a year’s time to see if anyone got close to our outrageous predictions.

That is it for part two of our 2023 year-end special group conversation. We hope that you enjoyed it. If you did, perhaps, as a sign of appreciation to all of my co-hosts, you could take five minutes of your time and go to Apple podcasts, Spotify, Amazon, or wherever you listen to your podcast, and leave us a rating and review. This will mean a lot to us. While you’re there, make sure you follow the podcast as this is also very helpful for us to grow the show. If you want to receive my weekly newsletter, just head over to toptradersunplugged.com/TTU-news. F

rom all of us at Top Traders Unplugged, thank you so much for listening. We look forward to being back with you next week for our regular weekly conversation and where I will kick off the year with Cem, what I’m sure will be a much-anticipated conversation by many of you.

If you want Cem to tackle some of your questions or if you have suggestions for topics, you can, as always, email them to me at info@toptradersunplugged.com. Until then, Happy New Year, and take care of yourself and take care of each other.

[01:11:52] Ending

Thanks for listening to the Systematic Investor podcast series. If you enjoyed this series, go on over to iTunes and leave an honest rating and review and be sure to listen to all the other episodes from Top Traders Unplugged. If you have questions about systematic investing, send us an email with the word “question” in the subject line to info@toptradersunplugged.com, and we’ll try to get it on the show.

Remember, all the discussion that we have about investment performance is about the past and past performance does not guarantee or even infer anything about future performance. Also understand that there’s a significant risk of financial loss with all investment strategies and you need to request and understand the specific risks from the investment manager about their products before you make investment decisions.

Thanks for spending some of your valuable time with us and we’ll see you on the next episode of the Systematic Investor.