Chris Schindler: Hedge Fund Sorcerer Schindler Shares Secrets from his Spellbook

And so that's the, and so think of that as your definition of passive, as your definition of beta. Build the best portfolio you can that you'd be happy having in 10 years. And then think of active as everything that you do between now and then.

So, we're gonna cover a variety of topics today related to his past and his present and potentially his future. And, um, so let's, let's start with what

We don't have any specs to contend with at the moment, but it, you know, we're back into that, massively concentrated technology oriented large cap rally that we experienced for much of the 2010s, certainly the back half of the 2010s. So I thought it might be useful to revisit that period. You know, I think a, a lot of people who've only been investing for the last 10 or 15 years have only really experienced an environment where U.S and especially U.S, big cap tech.

Was really the only game in town. Do you think we're back in that kind of environment or do you think there's gonna be a lot more opportunities over the next decade than we experienced in the previous decade?

But you can kind of point to some features of tech that make it much easier, I think, to explain how it can get so concentrated and how it can get like what looks bubbly at times I guess, as well. and part of it I think has to do with just, it'll be pretty hard for someone to just say, I'm gonna start up a new business and, and turn it into a billion dollar show and, you know, in a couple years.

But like, obviously with the infinite leverage of technology, especially, you know, online technology and, and the huge scalability, you know, you can create these huge potential future businesses, uh, almost out of like, it feels like out of nothing. And, and, and they're so hard to value and right. Part of the problem with the NASDAQ bubble was, everything looked reasonable.

Well, I dunno if stuff looked reasonable or not, but you want, you can imagine why this one company, if it succeeds, could be massively successful and could be massively valuable. but the challenge was. All 10 or 20 of them couldn't be. and so you had situations where, individually it might make some sense if you didn't get a, a sense of the context of the entire, space or sector. So that's like, that's part of the problem.

And we've seen that over and over again where it, they, they can't all succeed because they're together. They're, they're making a bigger claim on future, economic growth or future wealth that that is impossible to exist. And so together, like, all these valuations can't make sense and then you gotta figure out like, does the entire index have to re reset or do you have to go after the individuals and, and figure out, you know, which ones will go, which ones won't.

Because it's, it's so easy looking back to say, man, these were billion dollar companies, but if they're the one in 50 survivors or if you got entire spaces that just didn't work and went to zero, it's, much harder to predict that going forward. But, you know, and, and like, I mean obviously that's the challenge. you know, and I guess the other thing is. Because a lot of these businesses, and, and I understand, I'm talking about more of the ones that we just don't know what they're worth yet.

Because, because so many their cash flows are, way out in the future. They're kind of, well they're, they're almost like a private equity firm that's marked to model. They don't have anything that really moves 'em up and down, you know, uh, you know, on sort of, on the, on the day to day. And, they're just based on some future possibility. And that leads to two or three really weird price dynamics, which can lead to this concentration.

The first one is when you like, know analysts and, and, and, and I think that there's a, a fair amount of evidence that analysts tend to crowd with each other, and strangely, the more volatile and uncertain the stock, the more they tend to crowd with each other relative to the volatility. They have this benchmark risk of being benchmarked to their peers and looking wrong relative to their peers.

And so you actually find that for really uncertain stuff that's a really high ball that they crowd even more and it creates more of these crowding effects and you get more of these sort of bubbly effects. And, and so that's like part of it and that leads to momentum, in these names, which can really happen. And that, and of course they drag retail in along with them along the way.

and you can put that up against what feels like almost a totally different statement, but I think are they actually kind of work together, which is the, you know, when you have a Dispersion of opinions on something just straight up though, like, and, and I'm not talking about like analysts all crowded here. I mean like actual people in the market who are betting actually have a dispersion of opinions.

You know, like cap in sort of assumes that everyone has a modest expectations, but like, that's clearly not true. And as soon as you allow for heterogeneous expectations, you get these sort of weird effects where, the more uncertain the outcome, the more the price gets pushed up. And I don't know if you guys have seen any of these papers, but I mean, these are, this is sort of a, a, is this making any sense to you or do you want me to go into this a bit more detail?

Yeah. So, imagine if you had a world where, you know, there's a, there's some people thought a stock was worth 101 and some worth 102, and some were 103 and somewhere 99, 98, 97. And you kind of think that in a perfect world, it would settle up what the average dollar thinks it's worth. And we've had this conversation a lot about privates because it really, really shows up in privates and in private equity is the most extreme form of this.

The, the price doesn't settle what the market thinks it's worth, the price settles in what the most wildly optimistic person's willing to pay. So. You know, if someone, if someone's gonna buy a house and, and you know, the market thinks it's worth a million and some people think it's worth 800 and someone, and one guy goes, it's worth 200 or it's worth 2 million. It sells for 2 million.

It sounds more like, and, and so prices push off to the right when you have dispersion of opinion, when you can't short the price back down to zero and the privates cannot be shorted back. So they go all the way to what the most wildly optimistic person's gonna pay.

But if you have a world where you've got more longs and shorts, or you have a, a, not enough shorts to pull the longs back, and we're always in a world where there's a long bias, there's more like there's more, you know, potential long buyers and short buyers that a dispersive opinion is going to bias you towards the tails and to the right tail.

And so the bigger the dispersion of like, like, I don't know, this thing is worth, and some people think it's worth nothing, something is worth a ton that pushes you to the right as well and creates a bubble in that space as well. So you can kind of see how the massive uncertainty of these things will result in, in a, a bias high and momentum. Which we see all the time. and so, does it, so you can push all that against Hmm.

It makes it pretty risky against, I think like one other thing you have to pay attention to and, and like, look, there's always crazy issues when you're doing market cap and market cap waiting and people, people have that as a benchmark, right? And the challenge with market cap is your benchmark meet is that it, it can be an incredibly painful benchmark.

It's because if the, if the, if the small number of names do extremely well and, and you're anything other than the, than the market you're going to get, it it's gonna crush you at times. And there are gonna be times when you crush it because it does badly. But it's, it's a really inefficient benchmark in a lot of ways to measure your performance against. But it is, it is what people do measure performance against. And so you get these benchmark issues associated with it.

and so like, there's, there's a whole universe of quant and, and you know, how do we think about alternative to market cap indices, and think of them as, as as processes and, and, and benchmarks and, This is gonna go on, uh, uh, on a total left turn, by the way here.

Um, but, uh, you know, I spend a lot of time thinking about how do we alternatives to market cap weighting because you do get this massive concentration risk in a small number of names and like, the most naive alternative to market cap weighting, which, which for sure eliminates like, you know, any kind of mega a cap bias is just to equal weight things. And, it's actually like in the very long term, a surprisingly strong solution for equities is just to equal weight All the names.

but it's, oh, it's shockingly naive. and, and it's got, so we did this, we, we, we ran like an alternative to, to market cap weight. We, we ran an equal weight and the pro and there are lots of problems with equal weight, but what it does do is it says, I don't care what anyone thinks this is worth, I don't care what the market thinks it's worth. I don't care. I'm just gonna put $1 in each of these things and, and, and so be it. Now, lots of problems with that.

But one of the ones that always bugged me about equating anything was this definition of, well what's the thing you're equating? I mean, you could say like, imagine I'm equating countries around the world and I'm gonna put $1 in the United States and $1 in Canada and $1 in France. And then imagine the United States breaks up into 50, you know, independent little countries. And that thing that used to have $1 in you now go, now I'm gonna put $50 in it.

You're gonna bet 50 times as much on the exact same thing, just because of how it was defined. And, and you have this problem with equal weighting, which is, I call the unit problem of equal weighting, which was like, how do I think about what's the unit? Because it's clearly, it's a definitional issue. And if, if things come together, if things split up, I'm gonna completely change my weightings based on what shouldn't change my weightings. And that's like a big problem with equal weighting.

And so market cap weighting, it's got like a lot of efficiencies to it. It's got a lot of, you know, like I say, efficiencies, it's got theory behind it that you can kind of stand by. but at the end of the day, it's people's opinions about things. It's the whole market's opinion about things, but the price does move on. That Ecoweight's got this definition of, of independent unit problem. And so there's a subcategory of things in between.

And, and so this is what we, this is the sort of the three categories of of alternative indices. We created what we call kind of like a fundamental valuator, right? And a fundamental valuator is, is is different again, because it takes something about the companies. And so like, you know, when Rob Arnett, I, I think is a guy who's really covered this a lot, but he would say like, it's, it can be anything. It could be a number of parking spots in the parking lot.

It could be a number of employees, but it's typically revenues or dividends or cash flow or something that kind of speaks to the size and he doesn't sell it this

Or if you take an equal weight and you don't rebalance it, then the companies that get surprised, the upsides grow. So they have, they have positive shocks and the companies that have negative shocks shrink, and you end up over-weighting the ones that have positive shocks and under-weighting the one with negative shocks. And, and if there's any reversion to the mean.

And so if, if prices project those further out, if there's any reversion to the mean, then you've, you're kind of backwards in what you'd like to do. What you really want to do is buy the one you expect to, to revert back and you wanna sell the one that's, that's had a positive bias and market cap is the exact opposite of that.

So anytime you equal weight or anytime you rebalance to a starting process, you're gonna capture some of that, that natural mean reversion and, and in fact a huge, huge proportion of a lot of quant. Alpha and value add is in fact that energy recapture. And so I think Rob is able to show, I don't know if he showed this or something else did, but you could take like the inverse of his portfolios and they also beat market cap just because that energy capture is, is pretty, is pretty helpful anyway.

But so one of the things that, the, that any kind of fundamental weighting does is that, you know, when the fundamentals change, you buy more or less, but it doesn't move the price because of people's opinions. Because the market's opinion and projecting that into the future 'cause that projecting into the future tends to cause issues.

So, and if he's never sold it as this, I've never really seen it presented this, but the reason I like, I like this idea is if I took a company, I split it into 10 pieces, I will still have the same amount of weight in that new thing, split up 10 ways that I would've had the original and vice versa. And so it's kind of an equal weight, but it's an equal weight by size or something a bit more fundamental than just like this equal weight.

And, and between those, now you start to say, how do I invest in a, in a market that's got. some very, very concentrated companies in it. And, and you have to think, take a step back and say, if those concentrated companies were in fact a hundred companies that came together, well maybe it's not so bad. Maybe that is, well, you know, like it's a quarter of the weight. But, but if it was a massive conglomerate that brought together, maybe it's not as concentrated as I think

And, and, I'll just say those are, there's a lot of topics in that, but just say like, is there a fundamental reason why tech, and especially tech with earnings that are being projected way out of the future is way harder to value? Like Absolutely. Does that result in trending and possibly higher prices? Look that, that then have to correct and, and disappoint going forward. Like probably, does that mean that. Google.

Is Google a single factor or is it a conglomerate, or how do you think about it? I think you gotta get a little bit deeper before you say, is this, this is a massive tech concentration. 'cause Google's not really Google's a tech company, but it's also an advertising company. It's also, it's, it's a media company. I mean, maybe it's a bit more, maybe it's not quite as concentrated as it feels.

You know, it's these kinds of concentrated bets on, on these narrow tech, outcomes that become especially risky. Right. But I mean, just from an advisor standpoint, how do you manage this and manage client expectations? It terrifies me to see investing in global cap weighted U.S equities above 60% of global cap weight now, and seven companies worth, you know, up almost 30% of U.S. Equity valuation.

Like it's just a. You just have this sort of, you're, you're going on this massive amount of faith and taking this huge concentrated bet. If you don't, you risk being totally left behind. If you do, then you're taking this concentrated bet. It feels like a no-win situation. I mean, how do big asset managers deal with this, especially when they're benchmarking against peers on a year-in-year-out basis, like it seems like it's just a hard problem.

And, and you've, and instead of being a maximum share ratio investor where they're trying to make as much money for, as, you know, as much, much return, for as much risk as possible, you've forced 'em to have a different definition of risk, which is, their tracking error to the benchmark. And, and their optimization becomes return over tracking outta the benchmark, which is a fundamentally, like, much less useful thing. Uh, and, and it's much less useful for you.

And I say like when typically I say you're looking for managers and I think you just have to get comfortable with, I mean, if a manager's properly a long, short space, they should have no beta anyway, and you shouldn't care. You literally should just say, I've got my, you know, and, and whether I'm talking about as a portfolio constructor, how much of this stuff do I want in, in my beta? Separate that question out for a second.

Say, let's say, let's say I've somehow made that decision then for my managers. I, I should give them the right benchmark and I should give them the right risk definitions and the right governance. And so that, so that this doesn't affect 'em at all. They have a good stock pick over here and, and, and they should make it regardless of what the beta is and is doing. Now, that's, that's, that's a pie in the sky kind of nice statement. It, it typically doesn't go that way.

But even for, you know, even if you're saying like, I still, I'm investing my money in this beta, what do I do about it? And, and it's funny because when we first started looking at this and how to think about waiting countries and, and I think we're doing this research in the early two thousands and the, and, and the country that really stuck, stuck out in the history, you know, the last 20 or 30 years was Japan.

'cause Japan in the late eighties had had what looked exactly like the US does now. It was a massive portion of MSCI and of course it got super expensive as again, there was all the tiger funds and everyone was, was, was, was just throwing money into it for 15 years and it got so expensive and then, and then it just broke. And it broke, and if you were MSCI weighting Japan, you got crushed.

If you had, you know, underweighted a bit, you did well because you had a very, very large concentrated exposure to a relatively small subset of the universe. And, and I think over the very long term, these moves tend to punish you and you tend to want to disparate because, because there's the, there's always the mixture of the fundamentals and then the market mania behind it.

And, and the market mania behind it is the, is the piece that always over-projects and, and any market cap weighted, which is a mixture of the fundamentals and the market's projection of that into the future is, is almost certainly gonna lead to over-projections. The problem is, can you survive in the short run long enough leading against that to, to prove your thesis. That's the tricky part.

And the world of investors is always sort of slower to pick that up in, in the final trend change. And then you have this exposure, this overexposure to the largest market just by the market cap chasing. And you have the risk unwind and, And so that's, you know, the valuation side of it is important, but man, when the trend is strong, it's a really hard problem.

I don't know if the retail side sees it as clearly, but I think a lot of players get the growing riskiness of it. But there's always that. Yeah. But you have to keep playing while it's still happening. And, and it's very, 'cause it's just so painful to lean against it. So, uh, and this, it all comes down to it's a benchmarking problem.

And Jeremy, Grantham, GMO has done a huge amount of work on trying to just, you know, he's, he's basically all bubbles being revert. But the, the challenge with that is, after the fact, yes, all bubbles being reverted because you kind of defined it as a thing that went up and came back down. It, you know, Microsoft or Apple, just like, are they bubbles? Well, it's hard to say. They just, they kept going for like 15, 20 years.

And, and so, I mean, maybe at some point in, in the far future you'll be to look back and say, yeah, yeah, they were bubbles, they mean reverted. But, but it's, it's, I don't think it's quite as obvious. And, and so he tries to fight in bubbles relative to fundamentals. But the, the problem is they mean revert or the fundamentals catch up. and it's one of those two,

They were gonna completely dominate global tech, manufacturing and auto manufacturing. And, you know, that all got swept up in their, in their banking sector and, and the real estate sector. You know, I remember in 1989 the Emperor's, Palace in Tokyo was valued at a. Higher total valuation than all the land in California. Right? Like, and there's a plausible reason for this every time, right? And, there's this potential every time for this time to truly be different.

You know, maybe, fast takeoff AI actually does, mandate this kind of overvaluation, maybe software, you know, uh, mark Andreessen said Software eats the world. Maybe this is the time when software eats the world. Like there's always gotta be this plausible explanation in order for the markets to rise to this kind of bubble level, right?

Because if they're claiming two x of what it it will ever be, then no, those things don't all add up. It's just the question is like, one of those 10 may be correctly valued. Maybe that goes even bigger. But, but that's, I mean that's obviously, yeah, there's, there's always a story. Uh, there's no doubt there's always a story. and it has to make a bit of sense. It can make a lot of sense.

The, the, the, you know, and we, we all heard the stories, like all the way through, like through the, through the years and through the decades. We've heard the stories. I mean, I guess NFTs had a story. I, it it doesn't necessarily mean that they're gonna hold their wealth when the story moves on to someone else

It's, it's

And maybe that's true, maybe it isn't, who knows? But like, you know, if this guy runs off at a sharp of one over the last 10 years, it's either getting ahead of itself or catching up. And I don't know if you really know, because at the end of the day I mean, who's to say. But, uh, or maybe a bit of both and, and it is either getting in front of itself and you should sell it or it's catching up and it's a good deal. and I, I guess that's kind of like a risk-parity statement.

It's like if you were, uh, if there, if the only two things you could invest in in the world were stocks and bonds and you had 'em, would you care if this one happened to take from this one and then this one happened to take from this one? If you have both of them, I guess you're, you're probably kind of fine.

so if you have the world and the world is taking from here to give to here, as long as you've got a well diversified basket, maybe you don't care as much, um, as, as, as, as long as you do that, right?

But when the, you know, that bathtub sort of contracts, the levels contract, then, you know, you've got stocks and bonds both losing together. Right. Which is why stocks and bonds, the, the two-legged stool typically doesn't, balance Right. You gotta add that, that third leg.

and, and assuming correlations are static and either zero or negative is also massively dangerous. And so, you know, if it, it's gonna require some dynamicism and it is gonna require some dynamicism on risk and correlation measures, and it's gonna require other stuff because you, and I think I presented this a while ago, to you guys I know I gave this presentation back in 2018. When the last thing anyone in the world was thinking in 2018, you gotta really stretch your mind back and remember.

But it was like people were still kind of freaking about deflation at that time. And the last thing anyone was thinking about was inflation. But, but it was, it's just all it is, inflation is always a risk and discount rate shocks are always a risk. And, and so building a portfolio that's resilient to, to inflation shocks and discount rate shocks, Inflation shocks is easier 'cause you, because you can put some other stuff.

You've got some, you know, some gold or some break-evens or some, you know, commodities. There's things that you can put together to, to get a decent attack on inflation. I just can't write shock, you know, that, that's, it's self distinct from growth and inflation shocks is much harder to defend against. because, you know,

Gone through these long stretches of disinflationary growth and, you know, any I, any effort to diversify outside of stocks and bonds kind of makes you look silly for a long time. And then, you know, you get this, you get this spike and, and that sort of pays off. But it's just the investors haven't had much experience with that level of diversity paying off over the horizon that they've been managing money or had money invested in markets. So it's hard.

And, so if you think about the things that, like that you mentioned where you go, I, I want to have a positive expected return because I want it to contribute to my total portfolio. And, and yeah. Like it's gonna be spiky at the right times. And then how do you build something that's inflation sensitive that has more of a smooth, positive return over time while still covering your inflation shocks?

And that was the big, I think, you know, sort of effort in saying, first of all, when we, when we built our inflation sensitive asset class against all sorts of pressure to say like, why, why would we bother? The answer is because it's a risk and it could happen. And, and so. Whether or not you think it's gonna happen, let's call that your alpha on this whole thing.

But, but, you know, portfolio construction at the, at the portfolio level is just, I want to build things that are resilient to a variety of outcomes, regardless of who thinks what's gonna happen. I call that like a data portfolio construction. And, and even then you say, what's inflation? And, and, and everyone's got a different definition of inflation, right? An economist might say it's a CPI or, you know, wage inflation, or they might say it's monetary inflation.

A lot of 'em will say it's monetary inflation is the correct definition of inflation. you know, it, it obviously, as we saw in the seventies and, you know, the late sixties or even early eighties, inflation can be driven by commodities. Um, and it's, so I call a supply side inflation. And, and if the price of commodities like go up by four times, well yes, that's going to be massively inflationary. If it's persistent and it's across the set.

and so for each of those different definitions of inflation, you actually have different basket of assets to, to handle them. And so for monetary inflation, like what, what's your, what's your best defense guess? Monetary inflation. I don't know. There's like, there's a variety of things you can think about from real assets to gold.

Uh, you know, if it's, if it's, if you're looking purely at a definition of something like CPI, then maybe a real return bond or, or a breakeven is a better focus on that. If you're looking at like a source of inflation from the energy side or from the ags or from commodities in general, then obviously commodities are the best source of that.

You know, we built a, a very broad basket inflation-sensitive set of assets because we thought inflation can be, there's lots of different definitions, there's lots of different, causes, but that the reason you care about inflation and the reason you need this, this asset class is because in general inflationary shocks have a deleterious effect on most of the other assets in your portfolio.

And so there's gonna be times when your other assets get hit, especially your bonds get hit by inflationary, like unexpected inflation, but so do your businesses. And so, you know, if you think of your. Your equity in your businesses and your, you know, are, are, are generally exposed. You need something to protect you. And then the real question is, well, how do you build something that protects as well as possible, but still has a positive drift to it?

And so that's where like, that's where we kind of built a quant program or a systematic program that does that, right? And you can start to think about if I got these, like, what am I trying to do? Is I'm, I'm trying to cover inflation, but I'm also trying to get the positive risk premiums and drifts in the commodity space. Well then you gotta get, you gotta dig a, dig a bit deeper than just going along a couple things.

And that once again, requires a bit more expertise, a bit more specialization, and a bit more leverage and a bit more like effort. But ultimately I think something like that can be really, really helpful for a lot of investors.

Like, I want to time that I want to add value by getting in front of that sloshing or avoiding the sloshing or, you know, and of course that's what all active and macro and everything is, is trying to time the flows of money around. And it's like, yeah, stocks and bonds and commodities. If you got that, if, if somehow that flows your entire path, that's great, but I'd still like to capture some of that energy between them. And, and that's where, you know, I think a lot of the fun is.

Like I. Do you think it's, it's conceivable to be able to manage inflation risk through more effective security selection? Like, can you just select a diverse basket of equities and or credits that make you more or less resilient to inflation and you don't need to have that third leg of the macro stool?

Like Yeah, I mean there's probably some inflation sensitive equities and, and, and I think, you know, you, you could probably find things that have some inflation sensitivity. you know, is that, is that going, is that something you would add to your basket of inflation sensitive assets? Yeah, probably.

I think you have to be careful and this is, um, you know, this is just an alpha beta separation statement, but you go, like, if, if you think of like portfolio construction as I'm gonna try and build my portfolio and, and I think of past and we've had this conversation before, like what's passive, like nothing's truly passive, you know, and, and what's beta and, and my definition of beta like goes all over the place.

But if you say one definition of it is like it's gonna do what it's gonna do regardless of what anyone expects it to do. And, and so if you put money in it, it doesn't matter what you think this is gonna do once, if you just, if you just leave it, it will, it does what it does. Um, that definition of, beta, well, if you go, I'm gonna put my betas together to try and create the best beta portfolio possible.

There's obviously some active decisions there, but let's say there's like, you know, a not as much timing, then you need pieces that interact with each other in a nice way. And, and if you're leaning on your ability to see the future and, and stock pick correctly to cover your inflation risk, that's, that's a little bit different.

That's, that's, that's like saying like, if I could see the future properly and I can call winners and losers, then I don't have this risk because I'm, because I can see the future. And it's like, well, maybe you do, maybe you don't. But that's active management and you're now relying on active management to cover your inflation risk. And I would say you, you should do that as well.

But when I think about how pieces of my portfolio interact and portfolio construction the way, and this is how we sold it to our board, and I think it's a really interesting thought process when you talk about your, portfolio, your beta. And we said, what's the portfolio you wanna have in 10 years from now? It's like, not over the next 10 years. Like in 10 years, if you had to build a portfolio and say, 10 years from now, this is the portfolio I want, what would it look like?

And the key part of that statement is you have no idea what the world's gonna look like in 10 years. You have no idea if you're gonna like stocks more than bonds, if you're gonna like commodities. If you're gonna, you have no active, you have no possible active view in 10 years. And so that's the, and so think of that as your definition of passive, as your definition of beta. Build the best portfolio you can that you'd be happy having in 10 years.

And then think of active as everything that you do between now and then. So like I'll have a view over the next month or the next two months, or the next five years and start to layer on that.

But your center point, your starting point should be that thing that, that, that is the most, Unaffected by your view of the future, because your view of the future make it, make those bets and, and, and decide how much risk to put in that bet based on how much, how confident you are in your ability to see the future and do that. But, but just understand that, that you could be wrong and you might not see the future right. And you might not have that ability.

You might not be as good as you think you are. You might be better than you think you are, who knows? But, but, separate those two pieces out and build the best beta you can and that needs assets that interact well together regardless of your ability to call the future. And then, and then if you want to try and add value through active management, absolutely do that.

And if you think part of that value is alpha and part of it is inflation protection, however you wanna define that, for sure, go for it. Size it, right? But separate those decisions there.

And now you can actually measure whether your steps were in fact a creative or were they Dilutive to the actual long-term returns of your portfolio?

But that's, if that's your center point, that, then you can measure your distance from that and you can start to justify your distance from that. And, and that starts to really be your act, your set of active decisions. You have to start justifying why you are no longer what, what and why you're not going in that direction or why you're leaning against that. And, and, start to think about how much active risk you're taking in, in those active decisions relative to that data.

It's a really, really helpful starting point and it's a much, at least from my opinion, 'cause this is what we kind of, you know, put in place. It's a much better benchmark portfolio than almost anything else you can define.

Like, this is, like, we talked at the beginning about the challenge of benchmarks and if you're, if you have your, your CIOs responsible for, for investing at the total fund level and you give them a benchmark that's 60 40, then it's gonna be really hard for them to be anything that's like too far off of 60 40 because you've made that their benchmark. And now that their definition of risk is tracking error to a 60 40.

And if you say your benchmark is the median manager or the median pension plan or the median, anything that's gonna look a lot like a 60 40 or an 80 20 or it's gonna, you know, at the end of the day, they, once again, they're centered around something. That isn't necessarily the, the, the right starting point. And you go, how do we ever move off of that paradigm and how do we move to something better if you're always getting benchmarked back to that paradigm?

And, but then the question inherently comes, well then what's, what do you want your benchmark to be? and that becomes a, a really tricky question, but you say like, look, this is a good center point to start thinking about. And, and, and you have to be careful that it's, that it's not too pie in the sky theoretical.

Like if you, it can't assume that you can do certain things that you, you can't, in reality, like, like a leverage requirements or, you know, assets, there's not enough real return bonds on the planet to do what you want to do. It's like, well, that's not a fair benchmark. So it has to be like, you know, it has to move back to reality a little bit, but like, as a, benchmark construct that, that you sort of say like, I can measure.

And, and, and, and I guess the one other way you can think about benchmarking yourself, and this is like also super weird, but we also put in place a little bit, was. Benchmark each year to the start of that year. So, 'cause I'm just trying to break the, compare myself to the rest of the world or do what the rest of the world's doing.

And now you can say, if I'd held the portfolio that I started with for the entire year versus what I actually did, I could not measure my changes to some arbitrary starting point, which is just as arbitrary as anything else. But I can start to like, once again, focus in my alpha without contagioning it with someone else's definition of alpha, which is in their starting portfolio, which is, which becomes my beta unfortunately.

And I, I don't want my beta to be someone else's alpha as my starting point because, because that really messes up the whole decision,

Because the most important set of decisions, the asset allocation, maybe even the amount of risk you're taking have been, ab like have been taken over by a different group. And, and, and now you're just a, like a long short TAA around someone else's starting benchmark. And like, I believe the CIO should own the total portfolio, should own every major important decision. And so, and, and you can really see, the challenges of that.

But at the same time, you're a board member, you go, oh, like what are you completely unconstrained? And so then you can start to define, well here's a, here's an alternative benchmark, or here's the definition of risk, which is how much movement from where we are comfortable here to, to the end of the year. Like, and, and, and we were just trying to come up with alternative benchmarks that.

gave you the flexibility you needed to do the right things without giving you too much flexibility to, to cause unmitigated

Like, you know, if, the true definition of risk is tracking error and not the deviations and the value of the overall portfolio, then that is going to drive behavior that is aligned with minimizing tracking error, not aligned with minimizing total wealth variance and that produces the opportunities that alternative managers, many alternative managers use to generate their returns.

So, you know, you don't, you don't want everybody to become enlightened and, and abandon their benchmarks because then it has the potential to, to kill the goose that that lays the golden eggs for many alternative managers.

Whenever, whenever too many people crowd into, into any particular area, the prices get bid up and, you know, if the cash flows aren't affected by that crowdedness 'cause why would they be, you know, the, the, the prices get bid up and the cash flows the same and returns fall. Like crowdedness is always gonna result in, in, lower Sharpe ratio.

Because at the same time is that, you know, the returns fall, the risk goes up because the possibility of that crowd all trying to lead together at the same time becomes significant as well. So crowdedness of which benchmark hugging is a major one, uh, is a significant source of potential alpha if you can, if you can avoid or take advantage of that crowdedness.

so all of that to say, you know, if we, if we backtrack and went, inflation and we can come at it from the alpha side, we can come at it from the stop making side and, and whether or not, I know you kind of started with inflation or, or you even sort of went back and said, look, are we, are we micro or macro efficient? I don't know.

Like these, these are, these are interesting questions because like in one sense it really does look like, we have massive examples where we've been incredibly macro and efficient over the last 20, twenty-five years to the point of so obvious in hindsight, and maybe for many people, super obvious at the time as well.

and so, so you might argue them for microefficiency and, and like, and I guess microefficiency, it's got one other thing going for it, which is like, as human beings, if you think about it for a second, like everything that we, like all of our senses are, are really good at relative, but terrible at absolute right? Like, like I go, like, if, if you asked me what stars brighter in the sky, I could say That one's brighter. But you know, or what's bigger, you know, or what sound is louder.

I can, I can do relative really well. And that's what our senses are built to do. We're terrible at absolute. I could not give you like any sense of it, how bright that that is. And in fact, even our relative senses are like log scale and you know, like what seems like twice as loud to us might actually be 10 times.

And we probably are quite good at orderly ranking things, but then you, I guess, like you got a bunch of things that might even be ranked correctly, but when the whole picture, the absolute piece can just be miles off. And I think as humans we're probably no good at the absolute piece or, and, and so without something to anchor that absolute two, it, it probably can go off, in extreme distances.

Like taking major, equity overweight versus target or major credit overweight or duration overweight versus target carries a lot of risk, whereas taking, you know, maybe there's more tolerance for risk within the, you know, individual asset classes, And then there's just the agility, like you're, you're swinging these massive portfolios around, you just don't have the, the ability to move quickly enough to take advantage of, of many of the macro or micro inefficiencies that exist. Right?

So, sort of taking a down one level, I would argue kind of 99% of all cognitive and computational energy focused on investing. Is within the individual silos, right? So you've got the equity group and you've got the credit group. You've got the, the rates group, you got the

I can also say like, the last three or four years, like the micro-efficiency argument seems to have like, you know, if you get too many people, uh, you know, you've had a lot of craziness, uh, uh, intraday. I mean, like, think about, I think much of the market's changed in the last two or three years with, you know, we were talking about the, the retail, like player just coming and doing some crazy, you know, meme stocks. But you also have like, like what's happened the last three years.

It's like, I don't, I don't know how many day traders are still playing with cash equities versus the ones that are just playing with like, like massive, massive size of one day options. And the the ability for a small player or a small set of players to come in and. significantly move the market is, is changed a lot.

And, and like these, I I don't know why these things are like, it blows my mind that these, these are legal because it just, it feels like if someone came in and fat fingered the market to the size of the amount of manipulation, that's a market manipulation because you just hammered the market that hard.

But if you went to 10 dealers and you bought, you know, enough of these things and then, and then just nudge it, then suddenly you've got a whole bunch of other people buying aggressively on your behalf, bracing each other and, potentially slamming way more into the market than, you would ever do as an individual.

And, and you've, just, you've given like this incredible weapon to, to a small number of players and it's been really disruptive at the micro and at the macro level, uh, you know, over the last two to three years. And so you can really see like, I mean that's changed a lot.

And they go like, I'm being very, I'm being a good, I'm being a good player. When I, when I, buy a big put because I, you know, like if the market crashes, I make this money on the other side. And what you don't realize is an option is not really a thing. you know, you buy equity, you bought a thing and you kind of know what you've got. But an option is kind of a promise by someone else to buy and sell on your behalf. Because when you buy an option with a dealer.

You know, they have to delta hedge it and so on the other side of that trade, if you're, if, if the dealer's on the wrong side market starts to rise and they have to buy to cover that, that, you know, the deltas that runs away from them, they become a massive accelerant into the market. And same thing on the put side.

And so if the dealers get stuck on the wrong side of that trade, which they do all the time now, like this is, like, this has been the last three or four years, this has been the story. it, it's just, it's just quite an incredible, force in the short term. And it can be an incredible short, and so, so you can, you can really like see a lot of market movement when the dealers are on the wrong side of their gamma exposures. now they, they've started to reprice it and they started to figure it out.

But, but it's, it's been a real change in the market because, I mean, for the longest time ever it was, you know, it was priced by puts and, and you know, as such there was this like strong negative correlation between the VIX and the S&P and p and like that has gone positive at times. And, and, and, and the whole relationship between, you know, vol and market moves is growing. And, and these one-day options are super interesting.

Uh, they really transform things, but like I, I would say that they're taking a ton away from Microefficiency as we speak. um, you see how the stat-art guns are able to pull that together?

From, beta alpha and, you know, you've already talked about that a little bit. But, but how would you kind of rank, where would you wanna start as you're adding. You know, completely different flavors to the portfolio in terms of what big players can actually allocate to. you know, with the actual dollar size of these premia are large enough for a sufficient number of players to actually be able to participate.

Like how would you think about, adding to the diversification of the portfolio in what order? If you could, if you could rank

You need it and then you look like a loser for nine years. But if you can get strategies that, that, that actually make money over time and give you that protection, you're miles ahead just 'cause there's so much easier to stick with. And. And so, the alternative assets to stocks and bonds are obviously, you know, credit and, and then the privates. And, and we, and that's a totally separate discussion.

But it's actually a very cool asset class in its own because it's this. It's not exactly risk parity, but it's a nice mixture of four different risk premiums. So it looks pretty good on its own. It just doesn't bring as much as people think it does to a, to a total portfolio. But it's a, but it's a really big universe for value add. And so there's a, there's a lot of room for value add within credit, and I think there's a, there's a lot of, so, so is

you know, you've also come pretty close to defining most of the factors that are in your privates as well. and so, you know, when it comes down to. A little bit of a timeframe. Uh, you know, privates are, like they are diversified. Like they literally, like, they're definitely diversifying in the short term.

So if you look at your one year, uh, you know, model privates, they look, they look really uncorrelated because they're lagged and because they're smooth and the smooth means you get to make up their valuations. And, and in some cases you really just make up the valuations and they're lagged because it doesn't matter. They, they're not in real time anyway. And so, you know, those two effects are incredibly helpful for CIO in the short term.

They're probably not that useful for a sponsor in the long term. And so that's a, that's, I call it like a classic agent management mismatch because the CIO gets paid on return on risk. And, you know, anything that cuts risk that significantly and recently is doing boosting returns is super helpful. but it's not necessarily really accretive to the portfolio in the long term.

Um, so, so that's the, you know, that's the trade or, or it is in some cases, and it probably is at a certain size, it's just probably gets over allocated to, because it looks artificially, diversifying and artificially less risky than it actually is. And so, from that perspective, it probably gets over invested to, so illiquidity in general is probably over invested in portfolios and it, and it has some inherent sources of risk as well that, that you have to be super aware of.

but if we say like, let's set the assets aside and think about strategies, my gosh, there's so many. and, and I think if you're saying, I, I I, I'm gonna invest in strategies or I'm gonna invest in man, just creating strategies, you've gotta, you gotta split them into, I'm trying to think about the buckets you put them into. I mean, obviously, you break 'em down by asset classes and you break 'em down by holding period. I think it's probably the, the starting point.

And then you say within asset classes and holding periods, what have you got? And, know, holding period is. Particularly important because it's such a significant source of diversification, right? Like if, if you have managers who are trading intraday, you know, even in and out a couple times a day, they're for sure gonna be uncorrelated with your managers.

They're holding for five days or for 10 days or 20 and, and they actually create, like at the daily level, it was like a different asset, And so, from a pure diversification perspective, that's super helpful. I mean, you can have a bunch of managers who are uncorrelated all trading at the same frequency, let's say 10 days. Then, you know, if over the long time, over the long period, you know, they're, they're, they're doing different things from each other.

They're gonna look uncorrelated instantaneously, they're all either long or short at the same, at the same time for a given day. So whatever happens that day, they're gonna look like they're either, they're either lost or, or won together. And, and this is, this is one of the challenges with diversification over time. Is that some definition of time, you don't, you're not diversifying. Right?

I think we've talked about this before, but you know, diversification sort of says if I have two assets that are, that are uncorrelated, then I get a square root of two reduction in my risk, like 1.4 times reduction in my risk between two uncorrelated assets. And that happens at any definition of time.

But if I have two managers that are uncorrelated over the long term at any, like, at some definition of time, they're either both long, the SMP or both short, the SMP and, and, and, and, and that's, that's actually not diversifying. That's a, that's additive. And, at some definition of time. So at the one day level or the one hour level, your managers don't diversify. They add and subtract to each other. But over time, that turns into diversification.

And so, it's, it's very, very helpful to have managers with that have different holding periods. And, you know, if you are building a multi-strat of managers, that's probably one of the things you start to think about, to start with is how do I get different holding periods? And, and then what are the strategies? Well, what are intraday strategies and what are the risk readings of those? And, and how do I collect them? and, and my God, there's, there's a lot to think about

you know, if you think, if you're a multi-Strat and you've got all a bunch of these strategies together, I mean, you think about this for a second and you go, one of the massive advantages to a multi-Strat, especially if they're trading lots of different models in the same space. Is netting. And I don't think, you know, I don't think it's quite as obvious to people like what a big advantage that is.

But if you had 10 managers and at any given point in time, you know, some are buying S&P and P and some are selling, well then you don't get any netting, right? And, and you what is that worth? And the answer, it is worth a, a, a shocking amount because massive amount, because transaction costs are so expensive and, and they're such a big part of, of any, of any trading strategy

but if, if you were to think about like, you know. let's say, let's say for us, we have like 20 models, and if you look at any one of these models, there's a couple of things. There's a couple really interesting concepts that come into play. on one hand you could think about it, you said like, imagine I was intraday playing and I had lots of different strategies that came and, and I was running like a, what we call a complex event processor, which is, which is responding in real time.

It says like it's 10 0 2 and your trend falling model said buy, or it's 10 14, and this model said do this or it's, and, and if you just do those, all those in real time, yeah, you get that diversification benefit, but what, but you lose all netting because you've said, I'm trading this at this time, and you go and you buy and then an hour and a half later you trade this one and, and, and, and, and you're selling. And, and those don't touch each other.

And so you're paying twice the transaction costs. If you can take all those trades and bring them together and trade them like say one time a day. Then by definition, you know, some are buying, some are selling, and you're gonna net those guys out and, and you, and that's, that's, you know, so, so you connect, so you take trading time and instead of trading in real time, you, you, you, you compress that down to one or two or a certain number of times a day.

Well then you, then, you've created a netting process. But the trade off is you're, you're a bit slower in responding. So like, the question is like, how do I trade off the speed of response versus the, the, the value of this netting. And you've gotta quantify both of those. What's my alpha decay, what's my cost of waiting to do a trade versus my netting value? And, and it's, it's quite amazing.

Like for us it's a, it's, it's one of the assets that you think you have as a manager is like, if you only had one process, and let's say it was a sharp ratio of one, but before transaction costs and it's making 10% a year, but your t cost cost 5% a year. It's like, well, that, you have to think of that thing as losing 5% in trading costs.

If you had 20 of those and you went to bring that, that new one into your process, you might, like literally net out something like 75 to 80% of the trading costs. And so that becomes much more accretive.

And in fact, it's, it's, it's something that you have when you have like multi-processes is, kind of this brand new, call it like an asset, this new benefit, which is that if I wanted to run this new process, if I, if this was, if this was, if I was a single manager and this was the only thing I did it may not be feasible. But when I, when I bring it in and when I net it with the rest of my process, like it's T-cost almost disappear.

And it's a bit of a function of how big it is and how it turns and how it trades with the other stuff. But like it's, it's quite amazing how much of this T-cost can, can diversify away or just disappear into, into the process.

So you've got different strategies that on their own, for example, may not be particularly accretive, but when you trade them with other strategies because of the trade netting effects and the diversification you get within the portfolio. it's highly accretive, but then you've got an investor who wants to know where you generated your returns from, right?

You could, you could obviously describe that at the market level very easily, but going one level below the market level into the model level or the strategy level, that gets really hard, Because you don't know on a net basis how each of these constituents has contributed to the overall process. How do you guys think about that?

So, so, and then, then it's like, well, like, I like to let my models run independently, but every now and then if, if every single one of 'em is long equities today, I'm gonna say, I'm like, I'm not sure I'm gonna bet 20 times as much equities when just because all 20 models like it, it's very unfrequent and very unlikely. But yeah. And so there's gonna be, a point in time when you, when you're gonna lean against the, that aggregate decision.

And, and maybe that should come at a, a negative expected cost. You're leaning against the alpha process. But, but hopefully it's a creative on the risk side because like there are occasional times when you know when it wants to do that and you go, those are super risky. Like if something happens in the market that one day you could, you could have a really good or really bad day. Uh, but it's pretty random.

And so, you know, we, you know, we say, well, we've got aggregate risk that we're trying to control. And now, and now you're at the level of, I'm, I'm mixing models, I'm netting models, I've got overlays on, on aggregate risk, and how do I assign those back to the models? And you just can't. And, and so the best you can do is, is, I say, is talk about the models in, growth space and then, and then describe these layers and, and speak 'em almost as if they're models themselves, right?

This is a transformation process and, and this transformation process, it transformed risk this way and it, and it cost us, or it added this value. And think of it as a, as a process That's a yield. It's, it's in there because you think it's utility or creative. And, and then you always have to just pay attention to how much risk is in that thing relative to these things. And, and, and in terms of the utility that you're trying to provide from it.

'cause it's from a, if you think of it as a, you know, either Sharpe ratio or utility enhancer, it's, it's gotta be, it is gotta be either reducing risk or improving return or improving utility in some way that makes it creative.

And then, while you can communicate this to institutional investors or, you know, accredited or qualified investors, then you can't communicate any of this extra context or color to non-accredited or non-qualified investors, right, who always operate at a, a, major disadvantage to qualified investors who are able to then provide all this extra color, even though it's actually a possible, from an accounting standpoint to describe the accretion from all these different strategy sleeves that are

trading the same markets within the same, the same account.

If we had no netting, what would our T cost be? And with netting, what's our T costs? And it's really interesting because it's the, what is the incremental transaction cost associated with adding this new model? And you have to say like if we, and, even then, like adding new models, people always get this wrong, but you go like, I'm expecting this model to make $10 million because I'm gonna put this much and expect the Sharpe ratio of one, but it, it doesn't work that way. Right?

It's like when you add a new model, unless you take your risk up, the new model doesn't get to make it standalone money. It's just, it's just how much did it improve your expected Sharpe ratio? Because, if it, if it only takes your risk up by, by, you know, 1% when you gotta shrink the rest of the process by 1% to, keep the same risk target and you know, whatever it's suspected to make comes out the other side.

And so it's really, it always comes down to how much does improve your expected Sharpe ratio. And you can also say, if I was running this amount of money, here's the total dollars I'd pay in t-cost. And if I was just running this model alone, here's the dollars I pay in t-cost. And when I add them together at the same risk, what does my dollars in t-cost?

And it's interesting 'cause occasionally you can add models that are, that have quite high turnover and you can add 'em to the whole process and your transaction costs come down and it has a little bit to do with the size of the model versus the stuff you're doing. It has a lot to do with what is the model buying when the rest of your stuff is buying.

And, and so, you know, if it's truly uncorrelated, you know, it might add incrementally or it might take away because every single time that the rest of the process is buying and this guy's either buying or selling, you save some transaction costs on this, but you also save it on this one. And so you, you can, it it is quite amazing. But bringing stuff in that turns over quite high can take your transactions down and, and suddenly you go, that's a, that's a huge benefit to a multi-strap.

I think it's a huge benefit.

It's unlikely that that one model trades at a more rapid frequency than all of the other models, and then it helps inform those other models on their

Every time you do that, this guy covers some of this one as well. And so like that comes right back on the other side. And so if you realize the total savings, it's both of those together, you can get to 75, 80%.

And so it's a, it's a pretty interesting reduction, meaning that you go, if you found, if you found these five processes and five different managers and they're each a sharp ratio one, but like they lose 5% in trading costs when you bring 'em all together, or if you bring 20 of these guys together, these incremental managers are only, are, are coming at like 20% of, of, of the turnover. Which, which is, which is just incredible.

And so it's not, we're not talking about the diversification of the alpha. We're talking like that. In addition to that is this massive reduction in cost. which, which is what you can see is like, the, and this is where, you know, like if you have these, I don't know, like a medallion, like who's, who knows what they're up to, but assume that they're doing a ton of short-term stuff.

and the danger with, with, individual short-term stuff, once again, as we said, is that, you don't get your netting, but if you do enough of it and then you can aggregate it carefully into slices, you could probably get a ton of netting and just incredible diversification. So, and so, time diversification is super important. And, and all of this was just to say like, if I was putting together a multi-Strat, you gotta think about the different feature sets that you're diversifying across.

And so you're diversifying across strategies and across assets and across time. And that's the three major distinctions. And to all of that across strategies and time, you've got this netting thing to think about, or even assets and strategies and time. You've got this netting consideration, which is, which is an important consideration. Um, and I went way off track on your question. but, and then you say, what are the big categories?

And, so at the, global macro level, you know, if you, you've got your. Broadly speaking, you've got your carries. And so, you know, obviously like most fixed income models start with, relative or absolute carries, and whether they're risk-based or not is a big question. If they're not risk-based, then you're still gonna end up with a bunch of betas underneath it. But like, you know, some concept of carries, like, like obviously FX carries a really big and well-known strategy.

you've got your carries, you've got the values, you've got the qualities, and you've got momentum, and then you've got the volatilities. And I think broadly speaking, that captures a lot of 'em. And you can capture that, that set, in all of your major asset classes.

Then you have, you know, like the other ones like merger arbitrage, classic risk premium where it's, it like the classic definition of risk premium where it's like, you know, like someone owns a company, you know, it's trading at 20 and, you hear that there's a, there's a merger announced and it immediately pops to something and you go, what, what does it popped here?

and like obviously a lot of people spend a lot of time thinking what they think it should, it should go to, but it, goes to, it used to be a company that's prices moved, you know, based on earnings and it had a beta and, and suddenly what you own for a brief period of time is a coin flip. And it's a coin flip on the probability of this merger going through the price popped from 20 to 30 and if the merger doesn't go through, I guess it goes back down to 20.

If it goes through, it goes to something, it's, that's usually a posted price that maybe it's 40. And you go, why is it trading at 30 and not 40? It's like, well, there's an implied probability of this deal going through. And so what you own briefly, you've just made 20, do you, it was at 20 a day ago, now it's at 30 and now you own this thing, which is no longer a stock, it's a coin flip. and you said, I don't want a coin flip.

I don't wanna like make or lose $10 on this thing that I have no understanding about. And I'm gonna ask someone else, like, someone else can take that trade on from me and they can own that and diversify. And I want out. It's a classic risk-free. So someone else will take on, they say, I'm gonna, I'm gonna. I'm gonna buy these things and I'm gonna, I'm gonna bet that there's a certain probability of default and, a certain, probably this thing failing.

I mean, and, and a certain probably going through. And I'm gonna price and size this thing correctly. And so that was, you know, merge arbitrage is, is a very classic risk premium. and, and like, I think a beautiful one, if it's done well, where, where I always saw it done badly is on the portfolio construction side. Because like, like anything else, people would tend to screw it up and market cap weight it and they go, the size of the deal would dictate how much what I owned.

And the last thing you want when you're flipping coins is to bet a thousand times more here and then bet because, because at the end of the day, that's gonna catch you, uh, one day because the only thing that matters is the big one. And then the other thing to understand is that if you have a whole portfolio lease, you have a, a growing data risk.

We saw this in oh eight, if the market crashes or if you have a credit crisis or something happens, then all these deals, which you think are independent coin flips, can suddenly be very highly correlated with each other. And so that's like you have in the background, a tail beta risk in merge arbitrage as well. but like, a great risk for you to, to add if you can, if you can find it. and I really ran through like the, like quality.

there's so many different definitions of quality in across asset classes. Within asset classes. Like that's a very broad statement. Uh, same thing with value.

Some are higher, some are lower at any given point in time, and you can kind of think of that as a relative. You could even risk that guy if you wanted to. And we actually do have one model that that does that. But, but it's like that, that it, it's a very sloppy definition of cross sectional quality. but it's, you know, like a series of time series definitions brought together. We'll have it all around our weight, across sectors and, and of a quality definition.

Um, you know, and then, so we got, think about FX for a second and say like, the major risk periods and effects would be momentum value. Carry. And then, maybe some definition like, like country, like, whether they, whether they sit in value or not, like value quality. And that would be kind of like a, a throw-together concept there. But that, like even that, that three-legged stool in FX is a pretty powerful starting spot. and then you always got your vol and so

So the interesting, when we first started trying to think about, and this is like back to 2006, 2007, we were talking about bringing credit to the portfolio level. But way back before we were talking about bringing into our risk parity. and so we were building our risk parity as a mixture of stocks and bonds and commodities and, and strategies across all these non-assets. And, and when it came time to look at credit, we found credit is a super weird asset class.

especially if you're staring at, IG and this is back in 2006, 2007, but we were looking at it going, it's really weird because if you just invest in, in investment grade, if you look at the returns of that process over time, they're not very good. But meanwhile, if you go to the academic literature at the time it was literally saying like, we don't understand what's going on with credit. Why does credit pay so much? Like it's if the credit spread is paying more than it should.

And, and, and there was this massive disconnect between what the academics were saying. Like, look, if you look at company by company, look how much, look at the probability default and look at the actual defaults and look what they're getting paid. And like this is like, we can't explain why the spread is so rich. Meanwhile, the people investing in credit are making very little. And, and it was super unusual.

And it turns out the disconnect was most people when they invest in credit are, you know, for the same reason that you'd see that, like the bond investors, they're trying to get some duration and they're sitting at the back end of the credit curve. And if you, if you're sitting like I own credit, I, I buy a ten-year bond and then maybe by the time such as seven, I roll it back out to 10.

And if you're doing that sort of seven to 10 rolling out process, which is where the vast majority of people sit, you capture almost none of the credit risk premium. it's, you get all the risk and almost none of the fun. I mean, the sharp ratio there is, is almost nothing.

But if you hold credit right through the maturity, which means that you're holding companies that live with one to two years of default and, and, and the other default that they don't, it's a very different structure where if you hold it, that's where the all the sharp ratio is. And you go, that's super weird.

And then once again, it was like early on in our research going, that's this clearly a leverage issue because to get the amount of risk that you need and to get the exposure you need and the cash that you need to hold the stuff at the front end. like very few people hold bonds right through to, they either like, like right through to time zero. But if you do, that's where all the Sharpe ratio is. You go, why is everyone out here? And it's like, oh, there's two reasons.

And the first one is like, and they're both classic credit reasons. And the first one is the vast majority of credit players who are just rolling this process out thinking they're collecting the risk premium because they're taking the risk without knowing that, that, there's this massive in the curve because you've got these people selling here and buying here. And at the other side is like, it turns out that the credit curve is, is the discount curve for corporate liability for pension plans.

And so if you want to immunize your pension plan, that's the piece you have to hold. It's like, well you should never be investing in a space where people are forced to be investors because that's gonna be a very naturally crowded, it's the last place in the world you want to be. But the vast majority of people playing credit at the time were out there at the back end of the curve where there was just like no Sharpe ratio and all the risk.

Like why is, why is the sharp ratio so low when, when it looks like they haven't made a lot of defaults and we know that they're paying a lot and the answer is. Well, because it's, it's literally the curve has a pretty significant kink because this is where the buyers are and this is where the sellers are. And, and it's huge pressure points. And if you just hold past that, there's, there's something quite interesting there. You know, it's the same thing. We talked about this a lot.

you know, if, if all you're allowed to invest in is investment grade, well then every time something gets downgraded, you're forced to sell it. And, and that's, you know, that it's you, you wouldn't sell it if you didn't, if you didn't have to. And you know, it's a bad trade, you know, it's a money losing trade. But across that, you know, constraint of, if I, if I own this name, once they're being downgraded, I'm gonna get fired.

I'm, I'm happily gonna sell it and I'm gonna give that money to someone else happily. And that, transfer of utilities is, is a classic risk premium. So if you're an unconstrained investor buying the fallen Angels, like this is like, this is like 20-year-old unknown strategies. But buying the Fallen Angels is a, is a very winning strategy and

You know, how much of these you're seeing and, and once again, these are stuffing the dealers full of haha just, crazy amounts of gamma I thought they're trying to handle, like, on the sharp downside. So, so, you know, it's just like. But, um, you know, those are very simple strategies. I, I'm not a big fan personally of every aspect of that, but like, you know, if you build a proper, vol selling process and size it, right?

Like, like, like vol selling within FX within actually, of course is the main one. and to a certain extent in some, in commodities. Like, there's, there's interesting opportunities there. so if you think about like, like what are the major strategies the very, like, as I would've defined them back in 2006, 2007, asset by asset. You've got a,, well, you've actually got a, let's call it a low vol if you want. Define it that way. Where's the least leverage point within assets?

You've got a low vol piece, you've got an inventive piece, you've got a vol piece, you've gotta carry it. And you've got like some vol, some value versus quality definition. and then every major asset probably has some sort of seasonality or cyclicities in it as well. And so, That basket is probably like the modern alternative risk premium basket.

And then I would say like, you know, next generation that we sort of focused on a little bit is like, well, what about the players playing those baskets? Because if there's all those baskets and all those players, and, and in many cases now the risk premium of the player playing the basket is stronger than the basket itself. and you'll see this all, and like that's by the way, longer term macro, you know, ETF index anticipation.

You know, like, like I, I'm trying to, trying to anticipate names coming in outta the indices. Like you've got so many players who are so big and, and doing that, it's such aggressive size now. Like, like in anything, you can easily get more people offering the insurance than, than you have people buying it. And you can get caught on the other side of that trade.

I mean, it's almost like, I think a lot of those strategies, which has sharks of two have just gone like minus two because very, very quickly it's like, Too many people tried to hoard toilet paper during, covid and then, and they all tried to give it back at the same time. It's like you're, you're literally trying to buy the toilet paper before someone else buys it, and hopefully there's enough buyers to buy it from you.

but if too many people do that, you can get, you can get caught holding your toilet paper, if you don't mind the analogy.

And you've got, you know, people who are familiar with value. They like buying, you know, cheap companies or cheap credits or, or what have you, right? But the real magic for, vol selling carry, it doesn't matter. The real magic is in selling all the vol isn't getting, all the carry is in, arming all the value across all the asset classes, all the different securities, to the extent that you can then, you know, trade against the baskets. there's a whole other level there.

But just to kind of diversify global premium strategy, it's available, well, it may not be available to everybody, but it's becoming more available every year. And most people just take little pieces of it, right? Like, I've got a, a value tilt in my portfolio or a quality tilt in my portfolio. But it's purely on the equity side when, if you're just in into FX carry, that actually doesn't have a very attractive profile. It used to have a more attractive profile.

Now the profile isn't attractive at all, but global Carry is

And, if they're good at that, they can add a ton of value where, where the systematic players may get caught in those structural shifts. But in a world of more stability, the systematic player and the breadth that just can't be beaten and, and, and can really do quite well. And so those two, like, they, they really do diversify at, at, at difficult times. but the expertise in systematic investing is in the systematic investing.

And so you'll see that like, if you do carry an FX or fixed income or equities or vol or credit, it rhymes so much across those that the expertise is in building the models as opposed to the asset class expertise required to go capture it. And it's the same for almost everything. I mean, I say if you're building a systematic model or, or, or management, you would never have a commodity carry expert. It makes no sense.

And, and, and you might, you might wanna talk to a discussion I call my commodity trader to make sure that you got all the pieces right. but at the end of the day, the, the, the, the commodity carry model is going be 99% resonant to the FX carry and to the fixed income carry. And, and there's obviously gonna be a little bit of like asset class specifics that you have to understand and know.

But the, but once you're past that, the, the model building piece of it, and like the signal generation, the risk calculation, the portfolio construction, the putting all the pieces together and like, it should be, the expertise is in the model building as opposed to in the asset classes is, is needed to capture that. And, and, and there's a little bit of expertise that the asset class required, but they, I think, quite a bit less. And, and so, the systematic trader can capture all of those.

In fact, I would say a small number of traders could probably capture all of those strategies all at once, pretty well. And, and then you say like a discretionary investor could probably go in and, and really clean up on the, around the edges and, and, and those two could be, could be quite helpful together. but the, like, say like how do you collect all those things? You know, it's, it's actually not as difficult as it sounds.

I mean, I think if you started to build these processes and models like bit by bit then like the, the advantage of systematic investing is. Once you've built a model and built it well, it just goes off and runs. It's like an annuity, and you can start to build the next one and build the next one. And, you know, you build five, 10 models a year. After two or three years, you've got a really interesting diversified suite of processes.

And some of these can be built much quicker because, because like I said, they rhyme in such significant and obvious ways. And, and so, you know, and, and, and this is not a news story. I mean, there's, there's been a, you know, a number of very successful multi-Strat risk premium collectors over the years. And, and, like anything, they're gonna have good years and bad years. and, and the space gets more or less crowded as the space gets crowded, returns get driven down.

But, but I'm a solid believer that the space will never get so crowded that it will never make any money. Because like on one side you've got people with actual demands who are like always gonna have the constrained investors. You're always gonna be investors who are in the spot. There's always gonna be a flow of wealth. They're there and they're naturally there. You're gonna have the demands for insurance.

Like, like, you're gonna have the players creating the risk premiums and if you've got other players collecting it, when too many people come in and collect Yeah. for a while it can get driven very low or even negative. And then most players will leave, or the size will fix or you know, like, like all that're normalized.

And at the end of the day, because its natural demand is there, these players will, there will be an equilibrium where a correct equilibrium risk premium collection process will and can exist on, on average over time. And the only question is you know, what is, what is the expected sharp ratio of that process long term?

You know, it's never gonna, uh, we talked about this four or five years ago, it's never gonna be as good as it was in the early two thousands because it was just too unknown at that point and there just weren't enough people doing it. It's never gonna go to zero because, because naturally these players will leave if it does. And so there's the, what is the sharp ratio that will keep players interested? And where does that balance to?

And I, you know, and, and, like it comes down to the, everyone, everyone always throws out a numbers. Like what's, what's the Sharpe ratio per strategy? Is it, is it gonna be 0.25 or 0.35, or 0.4 or 0.5? And what is the Sharpe ratio at the, at the aggregate process? Is it gonna be 0.5 or one or one and a half? And, and I don't know where that settles.

Like I would probably guess these things each come in at like a 0.25 and this thing comes in at a one, but that's a extraordinarily helpful, you know, and I think people have been so spoiled by the equities over the last, you know, 10 or 15 years and go one Like, I can get that from equities. And it's like, yeah, the equities are a 0.5 long term.

and you just have to be careful with equities because like, they make, very, very high Sharpe ratios for a while and they make very low Sharpe ratios for a while. if you could find a, like a proper one that you could put next to the 0.5 of equities in the 0.4 or whatever of bonds you'd be so happy long term.

It's like I, I buy things when they're cheap and, and they're on their way up, or I buy Exactly. you know, and you have to, you're trying to explain a little bit more, something a little bit more complicated that when it doesn't go well, people lose faith in it much quicker. And, and you can have a value investor who's just being crushed for a year, and they'll come back and say, it's worth even more. Just trust me. You know?

Like they, you know, the marginal price center is trying to determine the price at which their expected return meets some required return on risk. It should be the same for everything. and so there's no reason, except if you have too many people trying to sell at the same time or two people trying to buy at the same time, the price will adjust and move and those players will come in and out.

That should be a natural expectation of what this process is gonna be and, and it has a fairly long life to it. But that's fine. If your portfolio construction in the long term, you should be totally fine with it.

It leads to some pretty, pretty significant

and I'd love to come back and do it again at some point.