TTU126: Kevin Cole, CEO & CIO at Campbell & Co.

[00:00:00] Kevin

I think this last year has really shown that the change in the macro environment, I think we believe that’s going to continue to be front and center for the next year or two as inflation dynamics play out, as the impact of central bank tightening on economies plays out. We believe that this is a really good environment for this strategy set, and we’re excited about where it’s going to go from here.

[00:00:35] Intro

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, Niels Kaastrup-Larsen.

[00:01:30] Niels  

Hey everyone, and welcome to another edition of Top Traders Unplugged, where today, Alan Dunne and I are joined by Kevin Cole, CEO and CIO at Campbell & Company as part of our mini-series focusing on the one investment strategy that beat everything else in 2022, namely trend following and managed futures more broadly. 

First off, Kevin, it’s great to have you on the podcast. Thank you so much for joining us today. We have really been looking forward to our conversation. How are you doing? I hope you had a good start to the new year.

[00:01:59] Kevin

I did. Niels and Alan, thank you so much for having me. It’s an exciting time to be in this industry and it’s great to talk to you.

[00:02:06] Niels  

Yeah, likewise. Now before we dig into all of the different topics we’re going to discuss, I would like maybe to set the stage a little bit for our conversation so that the audience knows a bit about your firm’s background. So perhaps Kevin, could you share just a few highlights about the type of strategies you focus on and where the business stands as we head into 2023?

[00:02:27] Kevin  

Sure. Campbell is a systematic multi-strat or quant multi-strat hedge fund. We’ve been in business for 50 years now, and as you may know, we got our start back in the ’70s in the early days of trend following on of course liquid futures markets at that time, grew up with the expansion of the market set in industries. 

I would say it was in the late ’90s and early 2000s that we really started to expand the conception of what we could do beyond pure trend into quant macro, into equity market neutral, short-term statistically driven strategies. Throughout that whole period, I would say we’ve seen the value of the systematic approach, we’ve seen the value of trend as being one important part of that strategy set, and also, we’ve seen the importance of continued focus on research and innovation. 

I think we understand that markets are really competitive. The dynamics change, the themes that are prevalent evolve through time, and we need to continue to evolve our strategies and risk management to stay at the forefront.

[00:03:33] Niels  

Yeah, absolutely. By the way, congratulations. Fifty years! I work for a firm that’s only 48 years old, but 50 years is just such a magical milestone, I think. I don’t think a lot of people actually appreciate what it really means to have a 50-year track record and how valuable that is. 

But anyways, our conversation today will be a little back and forth, different topics that Alan and I picked out. So as usual, Alan, why don’t you kick it off and dive into our first topic?

[00:04:05] Alan  

Great. Thanks, Niels and hi, Kevin. Nice to chat with you. You touched on a few key components of your approach in terms of things that have underpinned a lot of what you do, systematic strategies, trend being at the core, that focus on research and innovation. 

If you were to package that into maybe an investment philosophy or a set of beliefs that underpin how you approach markets and why there is an alpha to be extracted from markets, how would you describe the investment philosophy?

[00:04:42] Kevin  

Well, I would say our philosophy really starts with the belief that markets are not perfectly competitive, but they are not terribly far from efficiency and being perfectly competitive. That means that we can find opportunities that arise out of investor psychology, behavioral mistakes that investors make, the interaction of investors and the impacts those have on markets, the interaction of central meetings and economic forces with markets. All of those create opportunities for us, but we have to work hard to uncover those opportunities to make sure they hold up to research scrutiny. 

Again, we continue to change our thinking and the types of models we build as markets evolve. So that’s, I would say, the core philosophy. That means that research is the core of the team; it’s over half of the members of our firm. We continue to really focus on that research and innovation process. We do believe that quant and systematic-based strategies have a lot of benefits and they really work well for us. That means that we can continue to work efficiently to evolve the strategy set and avoid some of those investor behavioral biases that we mentioned earlier.

[00:06:06] Alan  

Fair enough. I guess as the business has evolved, you’ve developed multiple programs. So, it’s probably hard to say what the investment objective of your trading is. I guess it probably varies. When you look at the quant space and managed futures, very often, there’s a little bit of a debate. Is the objective absolute return or is it absolute return plus crisis alpha or some kind of protection? So when you’re constructing portfolios and programs, what are you thinking in terms of the objectives for those programs?

[00:06:41] Kevin  

Yeah, absolutely. I would say we do, across our programs, want to deliver strong absolute returns, low correlation or diversification to traditional assets, and a stable level of risk. Now, depending on the particular program or the way that’s packaged, that can vary a little the weight that we put on these different things. 

So, we start with the Campbell Absolute Return Portfolio, which is our flagship. That trades about 130 derivatives markets about 5000 cash equities. That’s roughly equally balanced between trend, macro, short-term, and equity market neutral. In that program, we’re laser focused on delivering the strongest risk-adjusted return, higher Sharpe (a 1 or above Sharpe) over the long term, stable level of risk of about 10 vol, and then again, low correlation, meaning roughly zero correlation on average to stocks and bonds. 

Also in that program, we’re looking to deliver meaningful alpha above and beyond what you might call risk premia factors. Now, beyond the absolute return program, we do have a managed futures program that is essentially a carve out of absolute return without equity market neutral. So the objectives there are largely the same. We want to deliver again strong Sharpe, stable risk, low correlation, and meaningful alpha. 

We do also offer standalone trend strategies that are primarily for large institutional investors like US pensions, and investors such as that, that are looking for that more trend specific profile. So there, strong returns are an important part of that. But also, we would have more of an emphasis on delivering that complementarity to traditional assets and that could be what you call crisis alpha risk mitigation. That would be focusing on very liquid strategies, liquid markets. 

Trend is the dominant strategy, and again, something that will deliver particularly when investments in traditional assets are not working so well.

[00:08:37] Niels  

Now, Kevin, when you write down a set of questions and topics that you want to speak about, you of course don’t exactly know what has been said prior to this. So I hope you don’t take it the wrong way. But you mentioned Sharpe, focusing on Sharpe a couple of times, and actually, one of the questions we had was kind of inspired by Cliff Asness. 

Because he wrote a paper recently where if we read between the lines (I think maybe you don’t even have to read between the lines), he’s saying, have we become too concerned about the Sharpe? Are we putting stuff together, are we doing things that take us away? Now, it seems to me like you’ve done this, obviously, on purpose. You’re not saying, “Oh, we’ll do trend, but then we’ll stick something in and don’t mention it to people and then it will have a better Sharpe?” 

Tell me a little bit about the process that led you to say, “Well, actually, instead of staying with our roots as a pure trend follower, we’re going to focus on absolute return and we’re going to do that with a much higher risk-adjusted return profile.” I’m curious about that sort of evolution.

[00:09:46] Kevin  

Yeah, it’s an important question. I think we were on the early side in terms of thinking about these questions and thinking about how we thoughtfully expand the strategy set. So again, we started doing this work in the late ’90s and early 2000s and I think there’s a couple of important considerations. 

Number one, it goes back to that investment philosophy that we believe that there are opportunities that we can uncover and extract in markets and trend strategies using momentum signals is one useful way to uncover those opportunities. But it’s a rich opportunity set. The macro themes that are constantly taking place in markets really create a lot of opportunities for us to use fundamental data, macroeconomic releases. 

Sometimes, the actual mathematical models that we would use to trade those types of signals might look like a momentum signal but are applied on fundamental information. Other times, they would be relative value or other types of nonlinear statistical models. When you think about short-term opportunities in markets, it’s understandable to believe that there are speculative dynamics that take place, in the short term, that we can actually uncover using these statistical models and trade those. 

In equity market neutral, equities are a very rich data set where you might have some themes. There are factors that might look like a momentum factor but that’s one of many types of themes and alpha opportunities you can capture in equity. So again, it’s a very rich space. And I guess we would say, why would you want to limit yourself to one area? 

Now, I think when we think about the pitfalls of expansion, and maybe some of the problems that some managers have run into as they’ve expanded beyond pure trend, you have to think about, are you really uncovering these two alpha opportunities, are you increasing your Sharpe by less high quality means.

One trap that people might have fallen into over the last 10 or 15 years was that you could easily pick up beta exposure to, for example, long stock and long bond. And sometimes that would be done in a very simplistic way, but sometimes, you could have a very complex model that might hide the reasons you’re picking that up. Maybe, if an investor is not thinking carefully, they may not even realize that they’re picking up that bias. 

That would be something that we would not want to be driving or increasing Sharpe. Indeed, our research process would actually take a close look to make sure that we’re not picking up biases that may increase the backtest to Sharpe but really not increase the alpha of the strategy. 

So, I guess to summarize, I would say we believe that trend strategies do form an important part of the overall strategy set, but there’s a rich set of opportunities beyond that that we want to take advantage of.

[00:12:26] Niels  

Yeah. 

Just staying with one thing that you mentioned. You mentioned you trade more than 5000 different equities. Now, I don’t come across so many of our colleagues that trade a lot of individual stocks. I have two questions, I guess. One is very simple. What type of strategies do you apply to equities? If you also apply pure trend to individual equities, my question would be whether you think that if you were a trend follower, and you wanted to include exposure to equities (because our industry historically, we focused on the index, not the individual equities), I’m curious about what your research has found, if you have looked at this, whether it’s better to try and do trend following also on the individual equities, rather than just staying on the indices?

[00:13:14] Kevin  

Yes. Well, we’ve been trading equities since around 2001, 2002. We got our start stat arb and that’s still about a third of the overall risk allocation of our equity book. Really, stat arb rhymes somewhat with the short-term strategies on the futures side in terms of the underlying dynamics we’re trying to capture there and essentially the time horizon and other features. 

We also, over time, added fundamental strategies which would be things related to the health of the company, the quality of the company. Alternative datasets can be really useful there. We’re typically not looking for traditional risk premia or equity factors like the simple value factor. We’re looking to go beyond that to capture other dynamics. But that’s a pretty rich opportunity set, and it rhymes actually with macro on the futures side. 

So finally, we get to momentum, which again, is parallel to the trend strategies on the futures side. But all of these strategies, momentum, fundamental, and stat arb or short-term, in equities, they are all market neutral to the overall direction. So it’s not picking up overall equity beta. And indeed, the vast majority of these strategies are also neutralized at the sector level. So they’re really looking for micro relative value relationships among individual stocks. For that reason, even within momentum, the correlation of equity market neutral momentum to trend, on the futures side, tends to be pretty low. 

There tends to be some positive correlation there, but maybe on average, call it 0.2 or 0.3. We believe that there’s really not that much marginal value to trading trend signals directionally on individual stocks relative to what we get by trading a broad set of stock indices on the futures side. So, we focus on more of this relative value neutral opportunities to trade momentum in cash equities.

[00:15:10] Niels  

Alan, why don’t you dig into one of your favorite topics?

[00:15:14] Alan  

Well, actually, I was going to jump forward a bit and ask, as Campbell runs a number of different strategies, from diversified trend to pure trend to multi-strat, when you’re thinking about the role of those in the context of an overall portfolio, how would you think about that in the sense that if people typically allocate to trend following and managed futures as a portfolio diversifier (we’ve been making the case for how that makes sense at the moment or certainly has been for the last 12, 15 months, particularly with low bond yields, etc.), so thinking about that, most allocators would have a slot for diversifiers and absolute return. Would you say there’s a merit for pure trend over diversified trend over multi-strat? If somebody was looking for guidance as to which of the programs, how would you think about which one to allocate in the context of a diversified multi-asset portfolio?

[00:16:13] Kevin  

It really depends on the investor and I would say maybe their sophistication and also the amount of capital they have to allocate, and that would probably determine where we would think the best fit would be. I think for a large institutional investor that has an extremely diversified book and a team of fairly sophisticated analysts and team members, having a targeted allocation to trend (as a part of their overall diversifying strategies) can be very useful. That’s where they understand what they’re getting with the strategy. They understand how to evaluate it in the context of the overall book, and in particular, that they will not fall prey to evaluating that trend strategy on its own over short time periods.

 Because I think that’s where a lot of allocators have fallen into problems over the last 5 to 10 years where maybe they allocated a trend, they saw the arguments for having it as being a complement to the rest of their strategies. But maybe, if there were a couple of years where trend-only strategies underperformed, maybe they lost faith and deallocated at the wrong time and then they didn’t have it in their portfolio in a period like the last year or two where it really delivered. 

For investors that do not have as large of an amount of capital to allocate or maybe they just aren’t as sophisticated, I think there’s a clear argument for having a broader multi-strat type of diversifier where you can expect the Sharpe to be higher, you can still expect it to deliver some of those complimentary return profile characteristics that we’re looking for, but will be a little bit easier to hold through the full cycle. So, I think that’s one benefit of the multi-strat approach.

[00:18:06] Alan

So it’s partially driven by this behavioral characteristic of making it more digestible as an expression people have used or making it easier for people to… Obviously, you’re not going to get the benefit of managed futures when you need it if you can’t stick with the strategy over time. So maybe having some of these diversifying strategies can make it easier to hold over time. Is that it?

[00:18:25] Kevin  

I think that is one important characteristic. There’s a number of other benefits that we see from the multi-strat approach, beyond that behavioral aspect. The embedded leverage of these markets we trade really have a lot of attractive properties in terms of being able to get around some of the potential drawbacks of diversification. If an allocator is going out and allocating to individual managers in these different spaces, so allocating to a trend manager and a macro manager and maybe a short-term manager and so on. 

Suppose each of those is running at 10 vol, the diversification you get among those managers is essentially going to water down the risk but also the return you’re going to get at the end of the day. By managing these in a single portfolio, we’re able to use that embedded leverage to our advantage. So hit the vol targets at the underlying style level and then deliver at the top of the portfolio what we’re looking for, which typically it’s about 10% vol. 

That’s one attractive benefit of the multi-strat approach. You get fee netting, you get integrated risk management so that again, if an allocator is allocating to individual managers, on average, they may have low correlation, but at times they may end up having high correlation just by chance or just because of the way these different strategies cycle through. 

Our risk management is able, in real time, to look at the exposures of all these different elements of the portfolio and adjust the risk at the top level, adjust concentration limits and so on to make sure that we’re not overexposed to any one area which we see as a big benefit of the multi-strat approach.

[00:20:00] Alan  

If you think about the history of managed futures, Campbell has been in the business 50 years. It started off very much as this absolute return strategy to capture those trends in markets. But as we’ve been talking about, it has been increasingly used by institutional allocators as crisis risk offset or crisis alpha, etc. 

What’s come with that, sometimes, has been discussion given that it’s going to be it’s a trend following program is going to be used as a component in a multi asset portfolio and for that possible diversification protection component, people would say should you then cap the equity beta or should you also be maybe more responsive, particularly with respect to trading equities? Are they valid ideas or are you getting too much into optimizing the trend portfolio when you go down that path? What do you think?

[00:20:58] Kevin  

I think it, again, comes down to understanding the objectives and the profile of a particular investor and having the conversation with the investor to understand what is best suited to their needs and their goals. So we do have, in those trend-only mandates that I mentioned, we do have a couple of clients that do have some type of beta cap or exposure cap or correlation cap on equities. 

Without getting specifically into that, we have clients that are happy with that, understand what they’re getting, understand the trade-offs with that where you would expect maybe the full sample strat to be lower but the other risk mitigating properties like convexity or skewness to be better. So for that type of client, we do feel that’s suitable, but for others, it’s better not to put on that type of constraint. So, you just need to understand what’s best for the client.

[00:21:56] Niels  

Listening to this conversation, it also reminds me of another new (I wouldn’t say it’s new, because it’s been around for a while), it certainly got a lot more attention in 2022 (not least, because I think our industry did well), but then comes along this point about, why not just do a replication of what these great managers are doing and do it more cheaply? 

Although, I do believe that (certainly in the trend space) we know there are some flat fee 1% strategies out there so it’s not really that much cheaper. The idea of replication, as a whole, I’d love to hear your thoughts about it, whether you think it can be successful in the long run. I don’t mean the shops that a few years ago tried to build (cheap is not the right word, but let’s just use it anyway) cheap trend following models because they say, “Well, this is a factor, we can do it. No problem,” and then they didn’t really deliver what they promised. 

The strategy, or the replicator I’m thinking about right now is the one that actually takes the constituents of the SocGen CTA Index and replicates it on the background of just analyzing the daily returns and then doing a linear regression of some sort to come up with what they believe are the exposures only across 14 different markets, and so on and so forth. So I’m curious about that. I’m curious about how you feel about being replicated because you’re in that index, of course, and so on and so forth.

[00:23:36] Kevin  

I think we welcome the evolution in the space and competition in the space. I don’t personally believe that the replication approach that you described, where you’re actually looking at manager returns and then using regression-based approaches to back out exposures, is a very efficient way to build a low-cost trends strategy.

I think first of all, a lot of the managers in this space, including us, have really become pretty competitive in terms of these trend-only strategies and the fees that are charged for that. So, I would say investors currently are getting very good value for the money they pay for trend-only strategies from reputable managers that have a lot of experience doing this. 

I think the understanding of how to build a basic trend strategy is fairly well-known now. It’s not a secret how you construct a diversified set of momentum signals and how you can do that in a robust way with a wide set of lookbacks and specifications, understanding what markets you should include and exclude in terms of liquidity and trading costs and so on, thinking about how you build risk management and portfolio construction on top of that, and also how to build trading models that will be efficient and minimize slippage and costs. 

All of those are things that high quality managers in our space have done for decades. I think there are many good examples in the space of managers that an investor can go to to make that allocation for a very competitive price. So, I don’t really see the argument so much for going to somebody that’s replicating their strategies based on inferring positions from the returns of those managers.

[00:25:20] Niels  

You mentioned that you didn’t think it was very efficient. Can you see specific risks actually, as well, in doing so? Because obviously, they don’t know what the manager’s positions are so they don’t know how to necessarily manage any risks associated with those positions, I would imagine. I take on board the efficiency of it, but is there anything else that you think investors should think about when they look at replication versus going to the source?

[00:25:52] Kevin  

Yeah. I think especially when market conditions are changing quickly, which we’ve seen a few instances over the last year or two, that’s a time where that lag in the measurement and estimation could make a difference. Also, as you said, the inference from regression of a manager’s returns is inherently going to boil down these exposures to a few key factors. 

On average, I think in a year like 2022, that will pick up the proper exposures. But I think there are other times, especially turning points, where that really might not work that well. So again, I think there’s no substitute for the experience of a manager that’s been doing this for a while and that has the risk management overlay on top that’s point in time to the actual positions that the manager is holding.

[00:26:42] Niels  

Yeah. I appreciate that. Alan, where do you want to go next?

[00:26:45] Alan  

Well, we just kind of jumped ahead to the whole topic of research, which I guess is part of this as well. You talked about the evolution (and this is a very conscious evolution for Campbell) of moving away from trend into all of these other various strategies. 

You mentioned how an important part of the research process was ensuring that you’re not somehow picking up equity beta or bond beta even when that’s not part of the objective. So what is it that you put in place or what is a good research process that allows you to harness the capability of all of the researchers that you have and ensure that you’re developing systems in a robust fashion?

[00:27:34] Kevin

Well, we actually believe that our research process and that full lifecycle of research that we developed over the last two-plus decades is really an important part of our edge. Sometimes we call it our metamodel, that there’s not one model that we trade in the portfolio today or at any point in the past or the future that’s going to be the holy grail that will be our edge. But instead, this process that we’ve refined in terms of how to identify new areas of research that would be valuable, how do we undertake that research in the early stages, and then importantly, how do we review that research in a rigorous way to make sure it stands up to scrutiny. All of that is really valuable to us. 

We’ve had in place for, I would say, probably 15-plus years what we call a peer review process, where once a new model or a new piece of research has gone through the early stages of validation and shows promise, it will go to a set of meetings and discussion and ideas sharing with other team members that are not part of that core research team that built the model. In that process, we’re looking for a number of things. We’re certainly looking for how did it perform in a variety of environments or regimes historically. We also are thinking about how does it correlate with what we have in the portfolio today. 

But it’s really important, from our perspective, to stress test that idea as much as possible, to try to challenge it and think about where are the situations where it might break down or why might the thesis that we’ve developed for why that model should work, would those conditions not be in place or when would they be violated? So that, again, is something that has been an important part of our process for a couple of decades. 

I think it’s really worked well for us in terms of what I would say closing the gap between backtested in-sample performance versus out of sample. Because the main danger, I think, for quant researchers is to find those spurious relationships or spurious strategies where maybe in the backtest, you have a nice Sharpe, in the equity line, it goes up and as soon as you put it in hock it sticks. That’s really what we want to avoid. 

I think increasingly over time, we’ve gotten better and better at identifying those strategies that will likely add value out of sample and discarding those that are not likely to.

[00:30:06] Alan  

What are the kinds of things that would make you believe that something is just spurious? Do you need to have some intuitive rationale and does that come before the model is generated or is it an exposed explanation? How do you think about that?

[00:30:24] Kevin

For the most part, we do want a rationale, what we call an investment thesis, that’s dated and written down before we start looking at the data, essentially pre-register that idea. Now, that thesis is more important for models like macro or models related to trend or maybe some of the equity fundamental models. For some of the shorter term statistically driven models, the thesis may be a little bit more vague, and in that case, we might rely much more heavily on the empirical validation. 

But in every case, we want to have some type of understanding about where are the conditions in which you would expect this to work and when would we expect it not to work. Yeah, so that’s really the starting point, and then we would, through the research process, think about how do we stress test that, how do we think about the conditions where it might not work.  So a big part of that would be thinking about some type of out-of-sample holdout or out-of-sample test that the data has not been exposed to. 

Sometimes that would be based on a time period for those same markets that have not been seen yet. But often, it would be applying the data to a different set of markets. That’s where having quant equities, for example, can be really useful or thinking about could we test this on alternative markets that we’ve not tested it on yet or maybe even Chinese commodity markets. Things such as that can be really useful to just stress test and validate an idea.

[00:31:46] Alan  

One of the things that you hear often from managers is about how their systems are adaptive and responsive to changes in market conditions, etc. How do you balance the adaptability objective or desire versus having very long data sets? So for example, if it was the case that markets were now trading… Last year was very unusual in terms of very strong directional moves. 

We see bigger and expanded ranges, much more volatile conditions in bonds, much more like what we saw back in the ’80s and ’90s, I’m guessing, and very different to 2010. So, from a multi-strat and system selection perspective, how much weight does the overall system put on more recent data versus longer term data or does it just test it on the whole data series?

[00:32:50] Kevin  

It’s a mix, but I would say we would put more weight on the whole data series in understanding the behavior across as long a history as possible. I think this last year is a good example where having that understanding of macro dynamics in the ’70s was really important. I think that was something that maybe because of our DNA, our history at Campbell, we had been thinking about those questions even when maybe it seemed completely esoteric to worry about inflation. That was something that we built into our research and review process even in (call it) the 2010s when inflation was nowhere to be seen. 

So, we want to understand the behavior of these different models in this wide variety of regimes and not just put weight on what’s happened in the last year or two. Also, when we have extremely diversified portfolio of strategies, we understand that not all strategies are going to be performing at all times. Diversification means that some things will be working when others aren’t, and we’re perfectly comfortable with that. 

We do want to have in place some way of evaluating when a strategy, maybe, is no longer suitable for the market environment or maybe just is not performing in line with expectations. We use statistical guidance to help us with that decision. We think about defining distribution of expected outcomes for every strategy in the portfolio and monitor that in real time. But those are pretty wide ranges that we allow a strategy to go through in terms of its performance before something is pulled. 

So again, it’s not a very reactive response based on recent performance but more just some statistical guidance for how something is doing relative to expectations.

[00:34:30] Alan

If something is pulled, does it stay within the repertoire, does it sit on the bench waiting to come back on if it starts to show life again?

[00:34:41] Kevin 

 It would, typically. Yes. There’s actually an intermediate step we would typically deallocate a strategy by maybe half for a period of time when it goes below a certain threshold. If it continues to underperform, we could remove it entirely, but we would then keep it on the bench and it could go back if it seems like it’s suitable for the market environment as things change.

[00:35:02] Alan  

There’s an inherent kind of belief there that if something has deteriorated, that that’s likely to continue and if something is starting to improve, that that’s likely to continue. Is that just a belief in that’s how the markets operate, that these things come in and out of fashion or work for a period of time and then won’t, but when they do start to work that there is an element of persistence? Is that fair to say?

[00:35:28] Kevin  

Maybe to a limited extent, but again, I would say that it’s not very reactive. It’s not that we’re changing the allocations as performance changes incrementally. It’s more meant to be at the extremes to have guardrails to say we might be missing something here, there may be something about market conditions interacting with strategy that we don’t understand. 

Fortunately, when you have, as we do, over 100 individual strategies in the flagship portfolios, that gives a lot of room to remove a few strategies and still have sufficient diversification. I think if you have a limited set of strategies, then it’s more a challenging problem because if you remove something, you’re clearly hurting your diversification if you’re not able to replace it with something else. So it is a balance for us that’s given against the background of that strong diversification of the overall portfolio.

[00:36:23] Niels  

Speaking on diversification, there’s two debates we often have on the podcast. One is the number of markets you should trade. Is there real evidence that 300 markets or 200 markets is better than the most liquid 60 markets, for example? And the other thing is actually about the benefit or potential benefit of diversifying across strategies even within just trend following, different types of trend following strategies. I’d love to hear your thoughts on these topics.

[00:36:59] Kevin  

The organizing principle we start with is the concept of effective bets, and we want, as good quants, to essentially maximize the number of effective bets we trade subject to each of those having positive Sharpe or positive expected return. So what we mean by that is that we want either more markets or more, you can call them effective markets so things like relative value trading, or more strategies that will each have low correlation so that as we add more of those, then we’re going to increase the expected risk-adjusted return to the overall portfolio. 

So in the market space, what that means is of course we would like to have a diverse market set. We understand that as you go from the 25th to the 26th equity index in a particular region among what you trade, the incremental value of that is not going to be high for directional strategies because the correlation both for the buy and hold and for the momentum strategy would be high. So, it’s fine to add more of those, but you’re probably not going to expect a lot of incremental value at a certain point. 

Now, as you start doing relative value trading, you can get quite a lot of incremental value by adding highly correlated markets, because there you are neutralizing to that common variation and you’re picking up on those residuals. So that can really increase the number of effective bets by trading these markets on a relative value basis. 

But subject to those points I just made, I think other considerations when we’re thinking about new markets would be the liquidity of the trading costs is certainly important. Thinking about, are there any regulatory restrictions currently or that we would expect to be coming soon that would make us not want to trade a market? And then just the operational lift. 

There’s been a lot of push from some managers in our space to more esoteric markets or alternative markets. We’ve definitely pushed some in that direction as well. But we have to think about where do we want to devote our resources to have the biggest marginal impact. At some level trading a trend strategy on very operationally difficult alternative markets may not be the best approach for us as a firm as opposed to focusing more on new strategies or trading the existing markets on a relative value basis. 

So that would be the way that we think about markets. Then when we think about the strategy set, we do want to increase the number of effective bets to diversifying strategy. So that’s where historically we’ve seen so much value by adding macro in equity market neutral short term because those have been very low correlation with the strategies currently in the portfolio. 

As we add more strategies in those areas, they tend to be low correlation even to other strategies within their set. A new macro strategy tends to really add a lot of value to the existing macro book. So if we get back to trend and think about diversification within trend, we understand that the underlying momentum factor in trend is powerful and strong and there’s a lot of different ways to capture that, there’s a lot of different mathematical specifications and sets of lookbacks that you can use that will tend to have reasonably strong correlation, call it 0.6 or point 0.7, maybe even 0.8 is not unusual across trend models that would have different specifications trading similar market sets. 

That means that the increase in the number of effective bets through adding more trend strategies is not going to be as high as it is in short-term and macro. But that does not mean that you shouldn’t continue to diversify your trend book. I think we’ve seen a lot of value and a lot of benefit by having a very broad set of trend strategies and specifications. Because even if, over a long sample, the correlation is quite high and the Sharpe may be similar among the strategies, over short periods of time, you can get quite large, just random variation in those and you can get either lucky or unlucky by your particular choice of parameters. 

So, I think it’s a mistake to look at that full sample correlation and similarity of Sharpe among different specifications and conclude from that, well, I can just do a moving average model with the six-month lookback and that’s going to be just as good as anything else. I think we really want to have that diversification. 

The final thing I’ll say about trend is we’ve actually been finding a lot of opportunities in basing some new alphas off of underlying trend signals. So, thinking about ways to capture some different themes that start from a momentum signal but apply either relative value or using other mathematical methods around that will still be picking up the trend beta exposure but have alpha on top of that. That’s been a big focus for us the last couple of years and it continues to be a big push for us.

[00:41:46] Niels

Yeah, that’s great. I want to just stay on the topic of markets for a second even though it has its own little section here in our question sheet, but it does apply because I think you mentioned it earlier, and that’s actually ESG. I think there is certainly, as you rightly said, there’s been a big push by many managers to move into alternative markets. But there’s also this universal push from all sides about ESG, and so on and so forth. 

I’d love to hear your thoughts about (and I don’t even know whether you trade markets where you could say)… A good example would be China, right? I mean, China is probably not that ESG friendly if you had to score it. Do you have any thoughts about it? If you do, have you had any pushback from people saying this doesn’t smell right. How do you combine all of this as a firm?

[00:42:48] Kevin

Yeah. We’ve been giving attention to ESG for a few years now. I would say it’s been a gradual opening and a gradual process for us. I’d say in terms of investor interest, we have been getting quite a number of questions for the last few years. It’s probably been tilted more to European investors. I think in Europe, it’s a much bigger theme and we do actually have a UCITS fund that, in terms of the cash equity book, has a restricted list or an exclusion list that meets ESG criteria. And also because that portfolio doesn’t trade commodities, I think that gets around a lot of the more sensitive markets that investors would be curious about. 

Beyond that question, I think a lot of managers in our space, on the futures and derivatives side, have been struggling to identify how do you think about ESG in this market set, particularly if we get beyond saying let’s exclude certain commodities markets that might be difficult. 

When we’ve done research on this, we’ve looked at expanding our risk factor approach that we apply using traditional market risk factors and thinking about, can we identify at the country level using data from official sources like the UN, World Bank, and so on, measures of a country’s scoring, its level and rate of change of progress in environmental, social and governance indicators. Then if we can identify those scores for a country, we can map that back to markets and we can potentially put point in time constraints in the portfolio using essentially risk factors to say let’s make sure we’re not too exposed on the long side or the short side, or particularly on the short side, to these themes. 

We actually have not put that into the portfolio in production yet. I think we haven’t had the desire from investors to do that, but it’s just research that we’ve done to make sure we understand how we could apply ESG themes in the future. We’re continuing to look for those, I think, on the alpha side. We do see weather as being an important factor for some markets and particularly as climate change leads to more extreme weather conditions, you can think about energy prices and the way that those are affected by temperature swings potentially. 

We do have a model that actually trades something like that based on weather data. We’ve also done research on trading grain markets, for example, based on some weather extremes. But it’s something that I’d say we continue to explore, but it’s not been our highest priority. The one other thing I’ll add is that as a firm, I think we have been aligned with ESG goals in terms of our corporate culture. Our founder, Keith Campbell, has one of the largest clean water foundations in the world and it’s something that has been an important part of our DNA as a firm, so that will definitely not change going forward.

[00:45:47] Niels  

I completely agree with you. It is really a difficult topic for I think, in particular, our industry to deal with. One of our previous guests, Harold from Transtrend, he actually had an interesting point that I had not thought about myself (and I don’t necessarily know if I’m saying it completely the way he meant it). What I think he said was that because we don’t really have an opinion about the investments we do, we follow rules and that’s how it is.  So, essentially, when we have exposure in certain markets, we just carry risk, meaning we allow other people to actually transact because we are there to take some of that exposure off their hands in one way or another. That carrying of risk actually doesn’t really mean that you, I don’t know, have an ESG footprint the way other investment strategies might have it. I thought it was an interesting observation or opinion that he had about it, but I’m sure there’ll be more about these things for sure in the future. 

Alan, where are we heading next?

[00:47:04] Alan  

Well, I guess we’re veering into risk considerations a little bit. So maybe just to delve into that a little bit more, obviously. I guess you’ve kind of touched on a little bit from a pure trend perspective, what are the key ways to try and mitigate drawdowns? I guess we’ve kind of touched on it a little bit with terms of diversifying strategies and being diversified across managers. But maybe it will be useful to get your perspective on the risk management process. 

Is it difficult or more difficult or different between, say, a pure trend portfolio and a multi strat? You talked about how you can get into relative value trading, quant macro, all of those things which can give you good opportunities. But we’ve all had plenty of experiences of troubles or periodic blowups like the quant crisis in 2007 and relative value trades gone astray as well. So, is that a more challenging portfolio to manage from a risk management perspective?

[00:48:11] Kevin  

I don’t know if I’d say it’s more challenging, but there are some nuances or some differences between a pure trend portfolio and a multi-strat portfolio for us in terms of risk management. So, if we start with the multi-strat portfolios in our flagships like Absolute Return and the Diversified Managed Futures Portfolio, there our risk management objectives boil down to a couple of key aspects. 

One is we want to deliver a stable level of risk at the top level of the portfolio. So that means we actually do have a risk target for an expected risk level that we’re looking to hit. We set a band around that in terms of the expected risk that we seek to keep the portfolio in and if the risk, in terms of exposures, is getting higher or lower than the outer edges of that band, then we will adjust the overall portfolio positioning to make sure it stays within that. 

We’re also looking for diversification among those styles to ensure that we actually do have that balanced approach. So, for that, we also have expected risk budgets and ranges around those budgets for the individual styles of the portfolio. Finally, we really want to make sure we avoid concentration in any one dimension. We want to avoid tail risk. So there are a lot of different aspects of tail risk management that we probably don’t have time to get into in detail today. But that would be things like CVaR and VaR limits at the market level, at the sector level. 

At the factor exposure level, we’ve built up a large risk factor library over the years that has both market and sector and geographical exposures, but also things like macro exposures. How are we exposed to central bank tightening? How are we exposed to the risk of stagflation or even a political event like Brexit or something like COVID? We can build risk factors that measure exposure to that, and that’s another way that we protect against tail risk. So all of that, for these multi-strat portfolios, are helping to deliver that strong risk-adjusted return with stable risk with low correlation. 

So, then if we turned to a trend only portfolio, you can certainly manage a trend portfolio with those same approaches. You do need to think about that tradeoff between the expected Sharpe and those other risk mitigation or skewness type properties that you might want from a trend portfolio. There you see that if you do tightly target risk for that portfolio, you probably on average will have a somewhat higher Sharpe. But you will have the cost of having maybe less convexity and less skewness at times when you want it. 

For those portfolios, typically, we do allow a wider variation in that top level of risk. We actually in our trend only portfolios have an additional approach we call dynamic risk targeting that actually adjusts the risk level of a portfolio based on essentially its complementarity to equity exposures. So, when the correlation to equities is low and equity vol is high, you would allow your trend portfolio to have a higher risk. 

Conversely, when it’s picking up some of the same exposures as equities and equity vol is low, then you would say let’s bring down the risk. That’s the way that we do that within the trend portfolios, and also the trend portfolios might have less tight constraints on some of those tail risk measures, because you want to allow them to run for some of these exposures, but still have some type of limits to make sure you don’t have too much concentration in these portfolios.

[00:51:34] Alan  

When you’re speaking in terms of risk there, is that in terms of forecast volatility of the portfolio?

[00:51:40] Kevin

Yes, that’s right. There’s various ways we can measure that but I think that’s a good way to say it, forecasted volatility. 

[00:51:47] Alan

What are the topics that come up with a couple of the participants as rules versus discretion?We all know about the value of systematic trading. But periodically, there might be areas or instances when there may be an override or a discretionary decision has to be made. And of course, the whole research process is discretionary on deciding what markets to trade and all of that. So where do you see the opportunities for where it’s important to have that discretion? Where do you try to avoid making discretionary decisions and be rule-based as much as possible?

[00:52:24] Kevin  

We start from the perspective that we believe in the value of the systematic process and that we believe that as humans, we’re naturally prone to make mistakes, particularly at times when things are moving fast and maybe we’re under stress. So we want to take advantage of the systematic process as much as possible. 

That being said, we do believe that it’s not realistic to have a 100% automated system from start to finish. As you said, the research process inherently requires, at least at this point, some human judgment, both in terms of coming up with the topics you want to explore and evaluating those topics, and ultimately making some decision about allocating. 

Now in terms of the live production portfolio, for the most part, it runs behind the scenes every time an event occurs to generate desired exposures and positioning and risk constraints and so on. But we actually do have an investment committee that meets every day at 8:30 AM. We’ve had this in place going back all the way to just after 911 was when Campbell’s investment committee was put in place. 

It’s intended to be a largely passive observatory process where each day we come in and we use some of the analytical and visualization tools we have to help make sense of the exposures in this pretty complicated set of portfolios. You can imagine when you’ve got over 100 derivatives markets, 5000 cash equities, 130 strategies across 10 or more individual portfolios, the dimensionality is quite big. So, you need to have ways to help boil that down into exposures that you can quickly analyze. 

Each day, that’s what we do. We come in and take a look at how are we positioned, how are those positions changing overnight or over the last few days, thinking about what macro news is coming out that might affect the portfolio, what other events might be happening, making sure from a production standpoint everything is running properly and if there’s a deployment upcoming, that we know about it and we have eyes on it. 

All of that is just meant to make sure that we are not missing anything and that we’re up to speed on where we have exposures. It’s actually very valuable in the sense of thinking about what events might be upcoming that maybe the standard risk management process may not fully be suited for. 

If you think back to 2016 with Brexit or the US election in November 2016, those were cases where we felt that maybe just the standard VaR and CVaR type risk measures might not be sufficient for the event risks that would be upcoming. So we had time to (because we had time and we knew that that event was coming) work with the risk team and other researchers to build in place additional layers of protection, like build additional risk factors, additional measures of volatility that we could monitor. That was really helpful and that’s the playbook we followed with going into COVID. 

That’s the playbook we followed in the early part of this year going into the Russia-Ukraine crisis. That additional layer of human oversight, helping to build additional layers of systematic protection, is really useful. The final layer is those times when there’s an unknown that hits markets or something that really can’t be systematized and we need some human judgment. That’s rare, but there are times where we maybe have a market where there are issues with that market and we might need to temporarily remove it. 

Again, taking the example of Russia-Ukraine, as that was heating up at the end of February, we were trading the Russian ruble going into that and we made the decision to remove that. It was probably about a week afterwards that I guess most counterparties required that their trading partners removed that market, but we preemptively did that. That’s the kind of thing that we would do rarely but if needed just to make sure that we don’t end up with an exposure that wouldn’t be suitable for the portfolio.

[00:56:19] Niels

Now, before I jump to a completely different topic, I’ll stay with one particular thing. Some of the very best friends we have here on the podcast, we have some slight differences of opinions in terms of whether you should have static position size or dynamic position size. I know you speak very eloquently about many topics. I know you just mentioned earlier you have some dynamic position sizing in some of your portfolios. 

But leave that aside, just in general, because the argument is that if you have static position size (like probably some, not all, but some of the pioneers of trend following started out), you get into your position, you keep that position until you exit it, and that’s how it’s done. So, you look at it on a trade-by-trade basis. You don’t use a vol or risk management framework or anything like that. 

One of the arguments is that if you have a static position size and you’re hunting for outliers, that’s your best chance of really sticking with the position throughout the 5% of trades that really goes completely far beyond what you could imagine oOf course, there’s also giveback side to those trades, I guess). The argument is that if you do dynamic position sizing, you can’t be sure what exposure you’re going to have during that outlier trade. It can be smaller, it could be bigger, etc., etc. But in general, the argument is it’s probably not going to be as big and so on and so forth. Now, I’m on record saying I don’t see the evidence of one being better than the other. They’re kind of different. The whole point about ignoring volatility and correlations, etc., etc. (which you do if you stay static), I’d love to hear your thoughts maybe on that and see if you have a more compelling argument than I have as to one side of this debate.

[00:58:18] Kevin  

I am hesitant to wade too deeply into that debate. But I would just say that we are strongly on team dynamic sizing. I think it fits more clearly with our overall investment philosophy. We believe that you need to account for changing market volatility and correlations. Again, to make sure that you’re avoiding tail risks, to make sure that you do actually capture that large number of effective bets that were going for. 

In fact, I’d say we went probably even a little more strongly in that direction during the period after COVID where we actually sped up the reactivity of our position sizing and our momentum and macro models, because I think we had the belief that markets are evolving more quickly now and that you need to adjust your exposure to reflect that. I guess we kind of take that as a starting point and it’s a little bit hard for me to argue for one side versus the other. I’m just going to say that that’s the approach that works for us and not to say that another approach might not work for somebody else. 

[00:59:29] Niels  

Absolutely. I thought that was perfectly phrased as I would have expected from you, Kevin. 

Anyways, let me ask you about something completely different. I call it capacity fees flows. After 2008, a lot of managers had great inflows. Some managers probably hit capacity without necessarily knowing it or admitting to it. This is just my interpretation on the fly here, but maybe as money left the industry, the industry was left with a lot of capacity suddenly, and I think that it also allowed investors, certain types of investors, large investors, to really put the pressure on fees. They got some great deals from some managers. 

Now, what I’ve heard in the last year or so is that some managers are actually starting to get back towards capacity of some sort and therefore, it’s not so great to have a lot of very low fee money in your AUM. I’m kind of thinking, if we are so good at what we do, which I believe we are, we’ve been around for four decades and I think the strategy continues to deliver on its promise, maybe fees should go up. 

Why should we continue to just lower our fees because it is not as easy as people might think it is to do what we do and the investments that you have to do in order to be on top of being a systematic quant firm is significant. So I’d just love to hear your thoughts on this. Also one other thing, maybe just to hear your perspective on this and that is, people might think that after a year like this (and it was clear already, maybe by the summer, that trend followers and CTAs would have a good year or at least they were doing well while traditional assets were not), you would think a lot of people would then start allocating to it. 

When I look around and I see sort of the early numbers that we’ve seen at the end of 2022, it doesn’t strike me that there was a lot of inflow. On the contrary, I actually think a lot of investors might have taken profits or rebalanced out of the one thing that made money. So I’d love to hear your thoughts or observations about that as well.

[01:01:49] Kevin  

There’s a lot there to unpack. I would start by saying you’re not going to get an argument from me that I think we are earning our fees as an industry. I think that maybe there is an argument that some investors have undervalued systematic investors in terms of the margin of value they can provide. I share your feeling that probably continuing to lower fees further from here doesn’t really make sense for the investor or the allocator or the manager. 

But when we think about capacity, we do somewhat differentiate pure trend strategies from the multi-strat portfolio. When we think about capacity, we really start at the granular level of individual strategies and think about the capacity of those strategies. So, for us short term, is actually fairly capacity constrained as you might expect based on the speed and the risk of slippage, and so on. Equity market neutral, to some extent, is capacity constraints. Some of the macro RV trades are also capacity constrained. Momentum is less so, at least based on our size. 

So we’re currently $4 billion as a firm. I think we feel that we’ve got a lot more capacity to go in on some of the pure trends strategies, but in some of those multi-strat portfolios, there is a limit there. So we’re being very thoughtful about the fees that we’re offering for these different products. 

Thankfully, we have been seeing good interest from investors at the fee level that our products are offered. So, we thankfully have seen good inflows over the last year – year and a half. When I think about the flows for the space overall, I think probably what you’re saying is true. Particularly on the institutional side, I think there may not have been as much institutional money flowing to the space this year as one might expect. That might be just partly based on that the decision process is longer there, the evaluation process takes time. So maybe the industry will see that in 2023. 

I think on what you might call the retail side, like 40 Act mutual funds in the US, there have been I’d say quite strong flows. We’ve seen that for ourselves as well as some of the other high-quality managers out there. So it’s mixed. I would say there’s certainly attention on this space now, positive attention. I think investors are finally realizing maybe having a long stock and long bond position is not enough for the overall portfolio. So I think it’s our job now as an industry to really continue making the case and helping investors to see the value that can get by investing in our space.

[01:04:27] Niels

Yeah. Alan, do you want to do your last round of questions before I wrap up?

[01:04:29] Alan  

Just a couple of quick ones. We talked a little bit of trend and managed futures in a multi-asset portfolio. Going back to that perspective, if you’re an allocator trying to think about these strategies, how should people think in terms of expected returns for say trend following and managed futures strategies? Is there a reason why the Sharpe should be 0.4, 0.5 or whatever it is? 

That’s roughly what the SocGen trend has delivered historically. Maybe on a forward-looking basis, obviously, it’s always very hard to say whether we’re going to have more or less trends. Who knows? But if somebody was saying to you for the next five years (obviously, you can’t do that), how would you help investors think about the range they should reasonably expect?

[01:05:30] Kevin  

I think if we focus first on trend strategies, as you said, the realized Sharpe over the long term of trends strategies out of sample is in that range of 0.5, maybe, maybe a little higher, maybe 0.6. You can think about a range around that. I would use the long term experience that we’ve seen in the industry of realized strategies to provide some guidance there. So, I think that’s where I would start in terms of giving an allocator expectations. 

I would definitely emphasize to not think only about the Sharpe on a standalone basis for these strategies, but to think about how it can be complementary to the investor’s overall portfolio. So that’s where correlation comes in. We’ve probably all done that exercise where you look at what would be the optimal allocation mix with traditional assets, and it’s much higher than most investors would expect or typically have today. So that’s where I would emphasize not just the Sharpe, but the complementarity. 

Then when we think about our multi strategy portfolio, as I said, I think we do expect to deliver a higher Sharpe than a trend-only strategy. I think the arguments from a theoretical standpoint are very clear in terms of increasing the number of effective bets, in terms of really maximizing the diversification. I think out of sample, we’ve delivered a Sharpe of 1 in that kind of range for those multi-strat portfolios and some of the other managers in the space have done too as well. 

So I think for an investor that is looking for somewhat higher Sharpe, then that’s a good place to look. But again, either way, think not just about the Sharpe but about the benefit to the investor’s overall portfolio as important.

[01:07:13] Alan  

Going back to the pure trend, you talked about how it’s reasonably well known how to run a trend portfolio. The execution of it, I guess, is a matter of question in terms of having the trading infrastructure, etc., in terms of being multi speed, multi market, etc. How much of an improvement do you think a sophisticated trend follower can generate over a more vanilla trend follower, for lack of a better expression? Is it going to be 20% better or 10%?  What’s the magnitude of the potential outperformance would you say?

[01:07:48] Kevin

Yeah. I would say probably in that 10% to 20% range would be reasonable in terms of the long term Sharpe. Again, I think there’s other things you would want to consider like the variability around that, the risk of maybe an outlier based on a short term performance deviation, maybe the range would be tighter for a sophisticated manager, and other risk management considerations would also go into that. 

If I could, I realized I missed one aspect of your last question that maybe I could return to which is the question about expectations going forward. One thing that I think we’d like, as systematic investors, is that we’re not macro pontificators, or we’re not prognosticators. So I am hesitant to do that. But I think we do need to acknowledge that it seems like the macro environment has changed pretty dramatically over the last year or two. 

I think a lot of us know that that period between 2010 and 2020 was frustrating for a lot of quants maybe because of central bank intervention to markets and factors such as that. The opportunity set maybe didn’t seem as rich and investors maybe didn’t see the need to go beyond that long stock and long about. 

This last year has really shown the change in the macro environment. I think we believe that’s going to continue to be front and center for the next year or two as the inflation dynamics play out, as the impact of central bank tightening on economies plays out. So, we believe that this is a really good environment for the strategy set and we’re excited about where it’s going to go from here.

[01:09:29] Niels  

Sticking with central bank tightening, in the last 20 years or so, cash management, for us on the funds we manage, has been pretty dull because there was not much we could do and maybe try to avoid the drag of some of the currency negative interest rates that we saw. Interest rates are not zero anymore as you alluded to. I’m just curious, generally speaking (sort of cash management today for the funds that you manage), how do you see that and what are the things that you do?

[01:10:03] Kevin  

It’s become a really nice tailwind after a long period where maybe it wasn’t a factor at all or potentially a drag. We’ve seen for our programs, cash returned currently in that range approaching 4%, which is really, really excellent. One benefit of that actually that maybe investors don’t realize is that that can more than cover the cost of fees. So essentially, you can think of it as them investing for negative fees net of that cash, which is great. 

In terms of our cash management program, I would say we’re not seeking for that to be a major incremental driver of returns beyond what you can get with pretty straightforward cash management. So we do work with an external cash manager for a lot of our programs, but they’re investing in extremely safe assets. They’re short-term, very high quality, high credit, liquid cash instruments. We’re not looking to go into more risky areas to get a little bit of marginal return there.

[01:11:06] Niels

Sure, that makes sense. Now, I’ve just got two questions left for you, Kevin. These are more personal but don’t be worried here. The first one is really just, what’s the one thing you hear about trend following that you disagree with the most?

[01:11:23] Kevin

Well, maybe it is that it’s easy. I think it is easy to come up with a trend signal and it’s fairly easy to replicate that basic idea. But I think underneath the surface, there is a lot of sophistication that high quality managers undertake in terms of those aspects of risk management and execution and thinking about the market set that really can add value, and it’s an important part of it. 

So I think that’s one and maybe that we’ve completely uncovered all there is to know about trend following. I think continued innovation is still occurring in the area. We’re seeing that here. I think other managers are as well, and it’s something that still warrants further research as well.

[01:12:06] Niels  

Yeah, absolutely. Last question. Very simple, actually. It’s kind of just about what you get most excited about or maybe concerned about when you look into 2023. That can be quite broad. It doesn’t have to be specifically about trend following or whatever. But is there anything that springs to mind?

[01:12:26] Kevin

Yeah. I think it’s exciting and fascinating to see how the macro environment is going to play out. I think that again, we don’t pretend to be macro prognosticators but our models are very adaptive and can get repositioned quickly. I’m just excited to see, or I’m curious to see how the impact of the central bank tightening is going to play out in terms of the economy and inflation into 2023.

[01:12:56] Niels  

Yeah. Great stuff. 

On that note, let’s wrap up this fascinating conversation. Kevin, thank you so much for being on the podcast and for sharing your thoughts and insights with us. We hope that we can do this again sometime in the future. 

To all of you listening today, I hope that you were able to take something from today’s conversation on to your own investment journey. If you did, please share these episodes with your friends and colleagues. From Alan and me, thanks so much for listening. We look forward to being back with you on the next episode of Top Traders Unplugged as we continue our deep dive into the CTA industry. 

In the meantime, go check out the show notes for this episode and all the other resources you can find on our website and not least, take care of yourself and take care of each other.

[01:13:39] Ending

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