Jamie: [00:00:05] Hello and welcome to another episode of Hedge Fund Huddle with me, your host, Jamie McDonald. So today we're going to be talking about the behemoth that is Man Group. Now I'm going to go as far to say that if you were to study only one asset managers history over the past 50 years, then arguably Man should be it. They are the largest publicly traded hedge fund in the world. They cover all manner of geographies, 85 different strategies and approaches. They were the first, or least I think they were the first to introduce systematic and algorithmic trading decades before they were a thing. This is the famous AHL, which we're going to be chatting about shortly. Fun fact The Man Booker Prize. Yep, that's them as well. And above all, they have this uniquely long history, which makes for great reading too. And I'm going to just touch on that for a second because I found it fascinating. Very briefly, this is a company that is almost as old as America itself. It was founded in 1783 when it traded sugar before becoming the exclusive seller of rum to the Navy. Can you imagine what a good contract that was to get? No wonder they were off to a flying start. Now, moving forward about 200 years into the 1980s, that's when they focused a bit more specifically on finance. They founded AHL and the business really took off. Now, thankfully, I don't need to tell this story alone because I'm thrilled to say that we have the group CIO with us today, Greg Bond, welcome to Hedge Fund Huddle.
Greg: [00:01:36] Jamie, this is great. Thanks for having me on. Excited.
Jamie: [00:01:38] How did I do on the intro? Did I did I get most things in?
Greg: [00:01:42] I think you did a pretty good job. The Man Booker Prize. We don't do that anymore. But yes, we were a big supporter of the Booker Prize, and I think we acquired AHL. It was founded as a separate company, but yes. Good intro. Starting from our very, very deep history. And then as we slowly acquired and done different things to have a really good wide ranging set of investment capabilities. So yes, good intro.
Jamie: [00:02:02] Great. So we're going to spend the first bit of this pod talking about the history of Man and building on up to today and the various acquisitions that you've had. And then we're going to talk more specifically about today's strategy vision. You're obviously a firm that has believed for a very long time in the marrying of human ability and technology, and obviously AI will be a big influence. So we'll get on to all of that. But let's go back to the 80s briefly, and as you say AHL was acquired in the 80s. Can you talk a little bit about the genesis of AHL and really why it was so ahead of its time?
Greg: [00:02:37] Well, I think in general, going back into the 80s and this concept of trend following and taking advantage of that in a very systematic way was a new kind of approach and strategy. It was quite successful. Again, like any business that focussed on Alpha, there's always, trying to take advantage of short-term dislocations, long-term behavioural dislocations in the market. And I think the trend following type of strategies were quite successful into the 80s and continue to be today depending on the obviously in the market environment. So I think a lot of the history and if I think about Man Group is developing strategies that should work over long time periods and having that and that diversifying capability is really integral to the business model. So it could be trend. It could be, as you mentioned, having human traders, discretionary traders using their insights and then other kinds of systematic techniques. So I think a lot of this is just trying to generate Alpha at scale for our clients. And whether that's kind of off the shelf solutions or building custom solutions for folks taking all of the capabilities that we have.
Jamie: [00:03:38] So talking about exactly how AHL works, it's about the math of price movement. It's about, as you say, following trends. I think another general way of explaining it is that obviously, a human managed fund is going to intrinsically contain emotions and that humans have emotions when they trade, and AHL just takes all that out of the equation. There is no emotion involved. But can you explain a little bit about how it worked and you know how it follows the trend? When does it enter a trade and when does it exit?
Greg: [00:04:06] Well, I think across the broader trend space, you've got different kinds of windows, things that you look back in terms of what the trend is, is it months? Is it shorter than that? Is it quarters? Is it years? So I think that's the basic insight. And then the other insight on trend and just getting and developing that is also just having breadth. Applying trend across multiple markets has been quite powerful. So one of the nice things particularly in systematic is if you have an idea that works in a few markets, it's easy to scale that across multiple asset classes, multiple regions of the world, commodities. And I think that's been really one of the insights in the trend following not only in more developed markets, but also in what they call alternative markets. So things across the globe, different kinds of more esoteric commodities. And so I think a lot of that is just taking advantage of the various behavioural biases that one sees in the market, some of the risks associated with it. And then it also provides a pretty good complement in terms of managing your risk and convexity and things like that. So it's been one part, I think, of the broader Man strategy. You know, I think that's AHL but we have again the other the other capabilities. And I think we're kind of moving into this concept of a discretionary side of the business and just a broad, systematic side of the business, which not only has those macro type approaches, but also a lot of bottom up systematic, what we call micro capabilities.
Greg: [00:05:30] So picking stocks and bonds kind of bottom up in many ways, using some of the techniques you might see on our fundamental or discretionary side of the business. So what's been fun and particularly taking on this job is that there are so many different kinds of Alpha sources, hopefully, with relatively low correlations and all of that, that it's really been fun to put those together and work across the various parts of the business. I grew up I guess on the systematic side, it's called Man Numeric. That's part of the micro part of that systematic approach that I talked about. But really working with discretionary and particularly in one of the things that I think is coming up, particularly with the large language models, is that that difference maybe between discretionary and systematic starting to narrow a little bit, right? As you bring some of those, sophisticated techniques, ability to answer really sophisticated questions, using technical capabilities to the discretionary side of the business, it starts to narrow that. So it's a very, very exciting time in our industry. And I think the key to the next 5 to 10 years is can we marriage or bring together both the discretionary and systematic processes in a way that's really reinforcing? And I think that's really exciting time versus thinking about these historically as very distinct ways of approaching investments.
Jamie: [00:06:41] Now, Greg, I did a bit of a dive into your background. I hope you don't mind, but I noticed when you were at Yale you did economics and biology, which wouldn't ordinarily be, I think, two subjects I would put together, but they seemed quite interesting given Man Group. It's like it marries science and it marries, human behaviour as it pertains to, economics and industry. So for people out there who are looking to get into the world of finance and looking to apply for jobs at certain different hedge funds, do you feel that having both a scientific and an artistic type of background is actually a good setup for working at Man?
Greg: [00:07:19] Yeah, I think, and particularly in the coming years. Having a broad background, not being so narrowly defined in one particular area can be quite useful. So broad experiences learning how to ask the right questions, irrespective of the field that you're working in. It could be political science, it could be economics, it could be biology. But I will say the common theme that I'm seeing across whether it's humanities, social sciences or the hard sciences is that everything is being driven by data today. You've got a lot of places and a lot of majors across the university set. You can get a digital humanities certificate, right? How does data science work in journalism in analysing deep histories in English literature, right. So I think the key for me in thinking about the future is having that a really broad experience from an educational perspective but trying to tie it back to data. If you major in English, get that digital humanities certificate, if you're majoring in econ, make sure you can run the data. If you're doing political science, learn how to do the data part. And I think that's becoming easier again, particularly with the development of a lot of the large language models more recently.
Jamie: [00:08:29] There you go. Great life advice as well. So as I mentioned, you're the largest publicly traded hedge fund in the world. And can you remind me, when did you go public and what is the benefit for a company like yourself to go public?
Greg: [00:08:41] I think one of the benefits of being a publicly traded company is as we go into our client base, we are a well-established company. We've got really strong audited financials, a lot of oversight, so that when we go in and talk to clients, our $200 billion plus platform, we're not going anywhere. So particularly as you're thinking about stability, I mean, we can lean on the 1783. Maybe that's a little too far in the past to lean on, but the idea is that we've got a lot of really good capabilities. We've got a well-run organisation. I know that people have talked about the pros and cons of being a publicly traded company. I think people sometimes focus on more the negative side, but I think on the positive side is really this robustness, the attention to detail and the ability to go in. And again, we are a well-established, well-run company that has made it through multiple, multiple market cycles. So I think that has to be helpful. Anyway, I don't know what all of the different crises were in the 1780s and 1800s and 1900s, but we're still here. So that's a good thing.
Jamie: [00:09:42] I was thinking that it's quite rare to see that. And it shows real confidence in your own abilities and your own processes. So anyway, I thought that was interesting. So let's move on to 2010 and the series of acquisitions that happened. Speaking of a search for Alpha, you acquired GLG Partners, which is a more fundamentally driven certainly human driven long short equity or do they do credit as well? But can you talk a little bit about FRM, Numeric, GLG partners, what was the thought process into what did you acquire and why?
Greg: [00:10:13] Yeah, I think part of this is the idea of, we have this great platform and can we add additional capabilities to that platform. So we had the trend components that we talked about primarily driven from the AHL side, adding that complementary discretionary capability equity and credit. FRM is really one of the genesis of our kind of solutions business. How do we put multiple portfolios together? How do we work with external Alpha providers? And then the numeric part is that systematic micro that I was talking about creating models to pick stocks and bonds kind of bottom up. So that was a nice compliment. And I think what we've seen particularly in this year and sort of a broader performance, is while we have seen some struggles on trend, we've seen a lot of these other parts of the business be very additive and adding Alpha. So it's not that we're trying to be mediocre in these areas just to have breadth. It's really and I think maybe differentiates us from some of the other larger asset managers. We're really trying to be top quartile in everything that we do. So not only having that capability but then being able to put that together. So being top quartile and then obviously in as we'll get to it in sort of the more recent history of doing some work in credit, private credit in particular opportunistic credit
Greg: [00:11:27] But I think that what really the value proposition is that we try to have high quality capabilities and then putting that together in something that works for folks. And I think one of my biggest concerns, out in the broader financial marketplace is there's always this kind of FOMO thing where it's like, we got to have this or that because that's what's hot right now. And that's not a great way to do strategy. So I think our approach is really what fits. And a lot of it's cultural to what kinds of people do we want to work with at Man Group? And that goes into a lot of the, when we think about an acquisition and all of that, a lot of it's the fit of the people, not only the strategies that they're bringing to the table. And so while I was part of the Numeric business here in Boston, I mean, that's 2014, I'm a Man Group person. I've been here for over a decade now. And it feels like the cultures are quite similar, even though our past have come from maybe different parts of the finance world.
Jamie: [00:12:21] Yeah. It's interesting. I was reading a lot of your year end reports and stuff on the website from the employees who just talk a lot about the culture of the place, like it's extremely collaborative. And I think that's a really unique asset that you have now as an investor and as a shareholder investing in a company like Man, which is so multi-strat is obviously extremely reassuring, particularly when markets can be volatile. But how do you basically capitalise on cross-collaboration between the different businesses?
Greg: [00:12:52] Yeah, I mean, on one hand you don't want too much collaboration because then you have sort of group think and that destroys some of the low correlation that you want to get from these various businesses. But really I think the key is a couple of things. One, it's just peoples how they approach the market. Are they open minded, willing to talk about certain things that we're sharing necessarily code across the shop and those types of things, but just sort of that thought process. Also the platform itself. So a lot of commonalities and technology needs, whether you're discretionary or systematic investor, we all need great trading capabilities. So having the ability to face off to the market again, whether you're a discretionary or systematic manager, being very comfortable handing your order off to a desk, that's got great technology itself and great relationships with all of the various counterparties in the world of finance. I think that's also something to appreciate that having those connections are really, really important to help sustain the business. And so I think we pride ourselves a lot on internal transparency, discussing ideas. But at the end of the day, I think we've got the right kind of balance between collaboration and incentives to succeed. And I think that's really what's come together very nicely, particularly in our what I'll call our multi-strategy kinds of products that we have that have multiple things that we do in one place. I think that's been a nice reinforcing thing to see.
Jamie: [00:14:00] I’m glad you mentioned your specific multi-strat type products or capabilities, because it is the hottest part of the hedge fund industry at the moment and only seems to be continuing its meteoric growth trajectory. So let's actually go a little bit more basic if you don’t mind and talk about exactly what a multi-strat is and how does it differ from a single strat.
Greg: [00:14:10] Yeah I mean our space and the investments has a lot of jargon and I think people throw around multi-strat. It's kind of cool to talk about and use that phrase, and all it is in its most basic form is it's a single point of access to having multiple strategies in sort of one fund. So you're not just buying an individual hedge fund, you're buying into one fund that has many concepts inside of it. Many types of strategies could vary from geographies or styles, etc.. And I think that's really all it is, is literally the word multiple strategies. If you expand it from multi-strat to multiple strategies, that's what we're really talking about here, is having that a collection already kind of pre-built for a client or somebody to invest in directly.
Jamie: [00:14:53] And bringing things forward to today, obviously, multi-strat is a big focus and growth area for you. But how are you thinking about it and how is it evolving as a space?
Greg: [00:15:12] Yeah, I think in many ways multi-strat has become to mean maybe one thing kind of capital M, capital S with some of the big brand name, very successful organisations have gone about it in a certain specific way, in many cases having many discretionary pods, etc. And I think where we are today in that space is can you do something that is little and little s multi-strategy, meaning you can have diversification, get capital efficiencies, all the things that you'd want in a multi-strategy program, but something that in the space could be different or at least have low correlation to maybe some of the more established players. So I think there are opportunities. I think you'll see as we move into, I don't know where we are in the multi-strat lifecycle, but whatever the next phase is, I think you're starting to see a bit of a shakeout in terms of what is the added value proposition for each of the different multi-strats that are out there above and beyond great performance. Clearly that's an effective way to sell. But I think where you're seeing some of this is maybe on liquidity demands, I think a lot of the more successful funds have gone out and increased their liquidity lockups on some of the capital.
Again, rational for their business, but it might not meet the needs for individual investors who might be buffering between the public and private markets and needing liquidity on the public market side might be something that's beneficial. I think this concept of systematic and discretionary, bringing those together is a bit unique in the space. I think you've had a lot of discretionary success. You've had firms that have been focused on systematic have great success, but is there a way to bring those capabilities together? And I think there's a final point about transparency. I think investors appreciate transparency ultimately. And then what is the next phase of that? Maybe the second or third phase from now is, well, actually highly bespoke multi-strategy solutions where it's not just the one that's off the shelf. So it's a very fun, evolving environment. I think you might see some consolidation as well as some of this subscale multi-strats can't quite compete. So it's an interesting time, but I think it's also a time of competitive differentiation.
Jamie: [00:17:11] Yeah, it certainly is an interesting time for that. And I was going to move on to competition for talent. I'm sure you're reading the same articles as we all are about some of these hedge fund manager salaries, which are getting promised to people, up to $100 million. I should quickly say that if anyone wants to offer me that, I would consider a different role than podcast host. But with the competition for top talent at hedge funds being so intense. I mean, you've talked about culture, and I'm sure it's going to be a big part of it, but what do you propose as your sort of value proposition to attract the more elite portfolio managers?
Greg: [00:17:45] Well, I think it's quite linked to the way I was talking about offering something that has helped with low correlation to investors from the product side or the strategy side. It's also that's the same kind of pitch that we want to have as we think about people joining our platform and whether that's systematic or discretionary. And I think a bit of that, as you mentioned, is the collaboration. We also offer, at various points, people can run other sources of capital. So a lot of people that join these pod shops, they have one source, one primary source. And I think there's a group of portfolio managers out there that would like to maybe build a slightly broader business. You talk to clients again, various sources. So they're not just captured by one particular fund. So I think that part is quite helpful. And having that broader platform at Man Group is really helpful for that story. And I think we're also the benefits of diversification are there, obviously you want to have more rather than less. But at some point, if you're hiring multiple PMs to do the same thing, you start to get a lot of diversification benefits go away. So it scales quite quickly.
So our approach is to have their pockets that we like to have, but we don't need to have ten people doing that. Maybe 1 or 2 and get that diversification. And that does lower the temperature, I think a little bit on the PM floor. You're not battling to get into a company meeting with a bunch of other PMs at the same firm. So I think that's the approach. And I think frankly, there's some strategies that don't fit quite as well in some of those, the broader, pod shops only because if you've got multiple strategies there's a lot of tight risk limits and things like that. But there are certain strategies and certain market environments that will have difficulty. And if you're willing to absorb that inside your multi-strat, you'll get the long-term diversification that way, rather than necessarily just exiting strategy classes that might fall out of favour in a given market environment. So I think being a bit more open and being willing to sort of modify that, the approach, because we are, again, a solutions provider, even internally, and I think we can handle some of those very bespoke PM needs.
Jamie: [00:19:47] My next question is a little more left field. Quite a lot of our listeners are on the younger side and they haven't yet started their careers. They may even be at college or business school. Now, I know you went to Harvard Business School. Obviously you went to Yale, which is both extremely impressive. But for those people who are entering the job market now, what do you want to see on a resume that's going to get you to raise an eyebrow? Does business school still have the allure and still have the prestige that it once had? The sort of the value. And if someone's, let's say 18, 19, 20 years old today and they just love markets. They love the systematic side. They love the coding, but they also love the bottom-up fundamental research how would you point someone today to do the next stage? Is it to go out and start trading themselves, or do you still think the college degree has merit?
Greg: [00:20:37] Well, I think one of the hardest things as a talent evaluator over my career, and I think this is true, I've seen more time on the systematic side, but I think also clearly on the discretionary side is somebody that's coming into the business for the first time. Are they going to be a creative person? And so often they could have the most sophisticated PhDs from the biggest universities in the world that you would know of. And within a couple of years, you're like, wow, they don't really have a lot of creative ideas. They're very capable, very, very smart. You know, and they can execute on projects. And that's why they're great. They're very valuable to have in an organisation. But it's that idea generation part that's always the hardest. One of the things that people that can ask the right questions, they may not be able to write down the math or the maths, as I should say, for UK audience, that you can find people that can do that. If it's really that question, that immediate sort of reaction. And so I think that's the part, in terms of your experience, my personal view is doing multiple things in your career or in your academic training. Different kinds of internships are super useful, I found, particularly as I've advanced in my career, I lean more heavily on things that I haven't done within Man Group.
I worked in entertainment for Walt Disney for a few years. I wrote cases in the competition strategy group at Harvard. I worked in investment banking. I took a sabbatical and worked for the Boston Red Sox baseball team here. So I think there's some of those experiences are quite useful. So I think as you're coming up, it is that curiosity. Have you tackled a question? Do you write maybe write a thesis or do your own analysis? I mean, I think we see a lot of interviews now because the resume writing, cover letter writing traditionally that doesn't quite screen as well these days because people particularly on the cover letters, you can use some of the large language models to write those. But I think the ability to communicate, the ability to just write up something, it could be any project, whatever your academic study, that's super useful because a lot of it is that thought process, did you ask interesting questions? And ultimately, even if you maybe did the analysis wrong, that's okay. You're allowed to make mistakes on that. But it's that initial spark of question. And so I think people should take advantage of the large language model capabilities that are out there now to help them focus more on the questions and less on the technical aspects.
Jamie: [00:22:56] That is such an interesting point, Greg. I just want to highlight it again, I think for a while now, there may be people out there who have thought of themselves as more creative, and therefore a career in finance might not suit them. But as you rightly say, I think there's a lot more room for creativity in finance than you may ordinarily think, particularly when you know technology can do so much of the heavy lifting. So I think that's a point really well made. Let's talk a little bit about the systematic side of the business. And today, you were clearly pioneers by a long way with AHL. And there's a lot of other hedge funds out there starting quant teams, algorithmic teams. I'll be honest, I'm not even sure I quite know the difference between systematic, algorithmic and quant. But maybe you can help explain. But everyone's trying to sort of either catch up to you with AHL or do their own thing. But can you talk about the landscape of that world today?
Greg: [00:23:48] Yeah, I think we should think about it more holistically to at Man Group, just systematic investing in general. So again, the AHL rooted in the trend side. And then on the Numeric side, which was founded in the late 80s as well. So you've got a couple of businesses that have got 30 or 40 years of experience, whether it's the more macro components from AHL or the more bottom up from Numeric. And I think what's really evolved in my time, in that space, it really is the focus on innovation. And I think that a lot of people say that, you know, wow, okay. You innovate. We can't you can't not say that to your clients. So hopefully part of it is you can prove that you've done that. I think a lot of it is opening up and making it a flexible environment for people to be creative and not run away from different machine learning was a part that it was a little bit scary for some of our investors. And coming out of 2008, 2009, let's say, because, I mean, some of the machines didn't quite get the GFC correct? There's just sort of that, that effect. But I think now it's really the blending of kind of the research process, which is sort of an organic thing that's done by an investment committee and your researchers and then bringing that in with the technology and the data and be open. And one of my philosophies is sort of thinking about running a research organisation is there's never a good time to make a change.
So you're either maybe you're struggling, you don't want to, quote unquote, lock in your losses or you're doing really, really well. You don't want to mess that up in some way. Or your clients are saying, hey, don't change anything, you're doing great , you fit in a really nice part of our portfolio. So the way I think about it is can we make, let's call it 10% change every year, add something in kind of the 10% range every year to our process, whether we're doing well, whether we're doing poorly. And then over time, you're going to find yourself looking back over a decade or so and you're saying, hey, we have really evolved this process and then also be willing to fail, have things not work. And I think being transparent with your clients can be hard on that, right? "Oh, hey, we did this, it hurt us". But I think that kind of relationship with your clients is super important. So I think embracing what's going on. And I think the next phase, as I mentioned a little bit, is how can we take that organic part, that kind of the DNA of the organic research process and put it inside some of the digital technologies? Can you build digital researchers that look a lot like your organic researchers? And what that will allow you to do is create scale within an organisation.
Because I think there's a lot of concepts about research productivity. Will this enhance productivity? Well, I think it's not clear to me. And it may be the case. I hope it's the case that you can generate more ideas per researcher. But even if you're cynical that that's not going to improve. You can have more researchers. So ideas per researcher times an infinite number of researchers is a lot of ideas. So sort of offset as long as those digital researchers are part and look like it's almost like having almost like you need an HR department to help manage your digital research side. In a way, you think about them as kind of these quasi-employees. So I think that's going to be critical so that you don't lose your way. You don't want to change your investment philosophy because of the technology. What you want to do is figure out how the technology fits your philosophy. And I think the biggest winners coming up in the space are people that can navigate that very effectively and stay true to their philosophy as we go forward. So I'm excited again about this time. And frankly, I was probably a little more I was probably less optimistic at first for large language models being a huge game changer for systematic processes, because we've already got a lot of interesting technologies there. But this research enhancement, this research scalar type of thing is really, really exciting.
Jamie: [00:27:38] Now, I mean, we're obviously venturing into the world of AI here. And what I read is agenetic AI, am I right? Am I saying that right? Okay. And I mean, you've already alluded to it with large language models being extremely helpful in terms of idea generation, but how are you using basically AI on both the fundamental and the systematic side?
Greg: [00:28:00] So we've been working on a technology we call Alpha GPT. I think we actually just put a white paper out about it a couple of weeks ago. And really the idea here is building a digital version, if you will, of our organic researchers. So sort of mimicking all of the things that a researcher would do from data onboarding all the way through hypothesis testing, back testing and then maybe ultimately into our investment process. And so it's really interesting because it took a lot of human development to make it work. Sort of going through the various stages, picking the right large language models for each component there. So this is really a way of hopefully building scale, but in a way that's controlled and consistent with our broader investment philosophy. So yes, Alpha GPT is what we call it internally. On the systematic side. Again, I think you'll start to see this converge a little bit over time. But the basic idea is on. I mean, we've named it Alpha GPT. I mean, how original is that? I think we've got to stop putting GPT on everything. But the idea is just to going back to my earlier point of like, could we mirror or mimic what a researcher would do? Onboarding of a data set, analysing that data set, writing the code having hypothesis generation step and then learning to iterate. So that's a bit of that process like just replicating. And then you would use different kinds of models and different parts of that process. Some of the models are best at doing the code part, some are best at the hypothesis or writing part.
So you're kind of picking and tailoring the technology there. I think what we're seeing on the discretionary side is a big rollout of tooling. You know, a lot of it clearly in the documentation processing of analyst reports, other things that come in, but also trying to set up an environment. Going back to my earlier point about creativity, where a PM could ask a question right and get back maybe even a piece of code or something that would link back to a piece of data, right? So that you can start to see a little more, I guess I call it back testing, maybe you would see on the discretionary side because we've lowered the barrier for some of that. But at the end of the day, we need to show that the technologies are valuable. And I think that's the critical juncture. You can build something that's really, really interesting. But if people don't use it, it sort of fails. And so I think where we are right now, organisationally is we've got, I would call it good Alpha and Beta versions of these technologies, but how do we get it into the user domain, if you will? Because once you do that and you get uptake, you start to get a nice feedback loop on what would be useful for folks. And so that's really the next phase of this. I think we've got some good baseline technologies, but we got to use it right. And we got to learn how to use it and get the organisation to use it.
Jamie: [00:30:48] So we've started to hint towards looking out into the future. So let's keep going in that direction. As we alluded to earlier, the multi-strat sector has grown very rapidly. You mentioned earlier that we may see some M&A, continued M&A, I guess in the multi-strat world. Do you think there's going to be some offshoots of this in terms of potential fee compression. If we hit saturation, what may happen to inflows who will be the long-term winners? A few thoughts on that.
Greg: [00:31:16] I think there's just this next phase, about competitive differentiation, people offering different things. I think what's been good to see the thesis behind having multiple strategies in sort of a single point of access type structure has proven quite valuable. So that packaging.
Jamie: [00:31:35] Can I say is part of that because of the relationship you have with allocators as well? I mean, I think the relationship that you have and big hedge funds have with allocators is an interesting one that maybe people listening to this don't know too much about. As much as you're allowed to say.
Greg: [00:31:48] I think part of it, I'll call it the allocators dilemma. So what do I mean by that? I mean that if I'm trying to build a let's say I want to build a market neutral-ish type hedge fund exposure in my portfolio, meaning I've got a lot of beta equities, long only equity, long bonds and broader program. So I want something alternative, something that's going to diversify that exposure. So I could go out and I could look at various single strategy hedge funds and do my due diligence on 5, 10, 15, whatever the number of funds and put that together in my program. And that's historically how people have approached it. And some people have gone to things called fund to funds, which collect these hedge funds, and you get one access. One of the difficulties in that structure is that and this is sort of the maths of diversification, if I add 5 to 10 to 15 things that have low correlation and low vol, I put that together. I might not have something that's particularly interesting or going to move the needle organisationally. So one of the benefits of this multi-strat component is one or two. Many of the benefits. One is they can do that due diligence sort of embedded in the program. They're looking at interviewing managers. But two because they have daily insights into what's in those portfolios. They know how the risks are kind of evolving.
They can then put some additional leverage on top of what you could do on a standalone basis. So I can take those 10, 15, 20, or maybe even up to 300 portfolios, which on a standalone basis had relatively low levels of volatility. I can add additional leverage. So I can take that really good sharp ratio and hopefully magnify it to a level that makes it actually impactful on plants. So that's a bit of a dilemma. And I think that's why people have migrated a little bit to having multiple strategies. And that can be the big M and big S like I've talked about. Or it can be other fund of one structures and bringing that together. So allocators are really, they have many cases, many billions of dollars to allocate. And they're really saying what can I get for this dollar that I give to an investor. What can I do with that dollar? And they want to be cash efficient they want to get a lot for their dollar. And so that's really what's I think driven a lot of the multi-strat. I think we're going to start to see a little bit also in more of the wealth domain too where that diversification, getting a lot for your dollar is really, really important for folks. And so that's where we're sitting. And I think so the thesis of that concept now that's the package.
And then I think the content is where you'll start to see differentiation. What goes in there? What are the liquidity terms? Other things like that. That I think will be important as we go into that next phase. So that's really where we're going to be in the future. And I think people that can then also have sort of bespoke solutions there. Just pieces maybe of that broader multi-strat set that would be useful. Maybe a firm already has a lot of discretionary equity. Maybe they want more systematic in their plan. So we'll go out and you can maybe just focus on the systematic part so it's a lot of fun. And I think the technology stack really, you have to have that to be able to do that level of granular kind of allocation for your clients. And so we have a lot of successful clients, our best clients are the ones that engage in these kinds of strategic questions. We do a lot of advisory work as well. They may have questions on FX, hedging or whatever it might be. And so my favourite relationships are the ones where they're asking us a lot of hard questions and can we help answer them, whether in just sort of in an academic way or actually in a strategy way, product way.
Jamie: [00:35:20] So speaking of hard questions, Greg, the macro landscape of today I'm not going to pin you down and ask you about where the markets go up or down from here. But 2025 was a tough year. We're not talking about tariffs as much now, but they were a very big deal and very difficult thing to navigate for both sides of your business I imagine. But here we are looking out into 2026 and beyond. How do you see the macro landscape? Are we looking at an easier trading environment? Is it going to continue to have road bumps?
Greg: [00:35:50] Well it's interesting. You know we always say the markets are filled with uncertainty. And I think so it always is. And particularly it's been for a long time about the sort of the focus on diversification. All those kind of basic principles I think are super important. But it's kind of silly I think, for me to say the markets will continue to be uncertain. No duh. We know that. It's just a lot going on. But what's been very interesting is it's actually been a pretty good year for Alpha, like, generating excess returns above and beyond the kind of the basic market return. And I think part of that there could be a lot of reasons for that. I think particularly coming out as interest rates have come up the last several years, we've just seen better opportunities for stock picking, bond picking, and whether that's systematic or discretionary, I think that holds true. Clearly, some of the trend stuff has struggled a little bit in the last 18 months or so. We've seen a nice rebound there. And that I think is a direct by-product of some of the uncertainty. But some of that's also a Monday morning quarterbacking because it's like, oh, of course, trend wasn't going to work with all the uncertainty. But if you actually look at the longer record, trends actually pretty good at navigating some of that uncertainty. We've seen a nice rebound in the last part of the year here, and the markets are just as uncertain.
I think you've got the geopolitical tensions, political tensions, just in terms of economic policies, etc. So in some ways I'm more comfortable maybe talking a bit about the Alpha environment. I think that if this kind of environment sets up that, it should be good for active investing, I'll put it that way. And again, whether that's discretionary or systematic, whether that's Man Group or elsewhere, I think that it's a good environment for that. I think my last one last point is we have seen and this is quite interesting. Sorry to keep kind of running on here, but there have been a few what I'll call these kind of de-leveraging short-term events this year, right? Whether it was around Liberation Day, we saw some pressure on quants in July and October. So what are the things that might be different and put a more, to be a bit more cautious in my assessment of Alpha is in this sort of multi-strategy setup, you could have one area that has a lot of difficulty, and because that's part of a multi-strat that might cause the broader multi-strat to bring down its level of risk. So you have a little bit more of what I call contagion risk in the market. I think we've seen a little bit like why is this going over here affecting my strategy, which has nothing to do with oh, it's because they're bringing down the total risk.
And I think the other part that I found, particularly on the on the systematic side, is that people talk about and this is sort of a term of art, right? People talk about idiosyncratic risk versus factor risk. And what does that mean? Well, factor risk is things like traditional value investing, momentum quality, all the kind of quant factors that one would talk about. Idio is basically anything that's not that. And I think part of what's happened in the market is people have really focussed on that Idio component to the degree that maybe now it's a new factor, right? So that you can see a little bit of that in some of these events, that the idio stuff might underperform more than the traditional factor stuff. So it's a really interesting environment. But one thing that does give me some going back on the more optimistic side is the markets seem to have digested some of this. I remember August of 07 in the quant, I mean that's like ancient history now. But that whole within a week in August of 07 like broad deleveraging in the quant community quite stressful for everyone did come back and but so it's an interesting thing. Maybe people have gotten better at risk these kinds of things to think about.
Jamie: [00:39:20] It's a really interesting point you made about interest rates creating more Alpha, because when interest rates were close to zero, correlation seemed to verge closer towards one, which is not what you guys want. And interest rates were not being too high. But being reasonable feels like it's a good environment for you guys. Does that seem fair?
Greg: [00:39:40] I think so, and I think empirically we've seen that for a lot of our strategies. And again, it's something I say and do I have a formal model that would prove that from a hypothesis sort of t-test perspective. But it does feel like broader interest rates. And clearly the strategy that we should have done over the last 20 years is maybe just buy the S&P 500, right? Forget all your investing principles, forget about. But that's all very hindsight. And I think we're starting to see now. Oh having non-US equities is actually beneficial. So some of the historical correlations and things that we would have learned when I was in business school are actually starting to play out again despite having a period there where it was just buy US, buy S&P five.
Jamie: [00:40:20] Greg, I'm sad to say we're actually running out of time. But this has been a really fantastic extremely informative. You are an expert guest. And I feel we could keep going for another hour. But before we go looking back on your career, which has been enormously successful, right from the get go, is there anything that you would advise people out there to do who maybe at the start of their career, whether it's certain books that you read which made a big difference to you whether they're on economics or finance or psychology, were there any habits that you used to do, like trading futures yourself or anything, but just a few pearls of wisdom?
Greg: [00:40:57] Yeah, I think pearls of wisdom. I think being open to doing, having different experiences. Push yourself. You know, particularly early in your career, be willing to do things at different, not just finance, but other areas. I think you'll find that be quite useful. I found my time at one of my mentors in this. I know people in the audience have heard of him, but he's relatively famous. Michael Porter, who wrote about, five forces other things and thinking about competitive differentiation. So I think his thinking about what is strategy. Being different versus concepts of operational effectiveness, which is just doing things better. So what does it mean to be different? How do you drive strategy? There's a very 1996 article. I remember it quite well, quite ancient history called "What is strategy?" I found that that was quite influential in the way I think about the world, and I think particularly in this environment and going back to this kind of FOMO environment that we can often find ourselves in that, sort of copy or target the best, supposedly the best player in a certain space may not be the right way to go figure out what your capabilities are and how to be different, because that's what makes this job fun. If you're always running around chasing the quote unquote best players in a particular area, in any industry, that's just not fun, right? It doesn't lead to innovation. And I think that might be the criticism of having an MBA in certain cases. Right. Where does innovation come from? It may not be necessarily from a textbook. So I think having some frameworks to think about life and going out there and having some different experiences would be my recommendation.
Jamie: [00:42:23] Well, you've certainly done that from a biology degree to working at Disney to working at the Red Sox and now CIO of Man Group. Greg, this has been an absolute pleasure. Thank you very much for your time.
Greg: [00:42:34] Thank you. Jamie.
Jamie: [00:42:38] Introducing REDI on Workspace, providing a fully integrated EMS experience within LSEG workspace, allowing buy-side traders to monitor markets, analyse data and execute trades all from a single interface.
Jamie: [00:42:51] Thanks once again for listening everyone and please as usual, give us a follow like or subscribe wherever you get your podcasts.
Jamie: [00:43:00] The information contained in this podcast does not constitute a recommendation from any LSEG entity to the listener. The views expressed in this podcast are not necessarily those of LSEG, and LSEG is not providing any investment financial, economic, legal, accounting or tax advice or recommendations in this podcast. Neither LSEG nor any of its affiliates make any representation or warranty as to the accuracy or completeness of the statements or any information contained in this podcast, and any and all liability, therefore, whether direct or indirect, is expressly disclaimed. For further information, visit the show notes of this podcast or lseg.com.
