Roxton McNeal, QIS Lead Portfolio Manager, Simplify Asset Management

[00:00:01] Hello, this is Dean Curnutt and welcome to the Alpha Exchange, where we explore topics in financial markets associated with managing risk, generating return, and the deployment of capital in the alternative investment industry. This is not your father's ETF market would be one statement used to highlight the ever-expanding product mix available to investors via exchange-traded funds.

[00:00:29] Today's suite of ETFs embed derivatives, target non-traditional assets like private credit and crypto, and can offer daily resetting leverage as well. Add to this efforts to deliver exposures to quantitative investment strategies via the ETF wrapper. With this in mind, it was a pleasure to welcome Roxton McNeil, Lead Portfolio Manager of the QIS product at Simplify Asset Management, to the Alpha Exchange.

[00:00:54] Our conversation begins with a review of Roxton's background at the UPS pension as an active client of the streets in utilizing QIS in the plan's efforts to deliver returns above a fixed-income bogey for retirees. We explore a broad taxonomy of types of quantitative investment strategies, rules-based trades that Roxton puts into two categories, defensive and carry.

[00:01:18] We spend a fair amount of time exploring the concept of carry, which he suggests result from market frictions, risk aversion, and liquidity premium. He further breaks down the carry bucket into trend, absolute return, and volatility carry. Here, and with the pitfalls of backtesting front and center, I ask him to share his thoughts on how he evaluates carry strategies. Stress testing and scenario analysis are critical, especially as they relate to properly sizing exposures.

[00:01:48] We finish the discussion on what might be coming next to the fast-moving ETF landscape. Here, Roxton volunteers the potential for the tokenization of assets in markets like commodities or real estate bundled into an ETF via smart contracts. I hope you enjoy this episode of the Alpha Exchange, my conversation with Roxton McNeil. My guest today on the Alpha Exchange is Roxton McNeil.

[00:02:15] He is the head portfolio manager at the QIS franchise at Simplify Asset Management and a gentleman with a deep background in quantitative investment strategies. Roxton, it's a pleasure to welcome you to the podcast. Thank you so much, Dean, for having me on Alpha Exchange. I really appreciate it. I have been a big fan of the podcast for a while, so it's a real treat to be here with you today and certainly looking forward to digging in the QIS and all the good stuff you've got lined up.

[00:02:40] As am I, and one of the joys for me in hosting this podcast coming up on seven years is learning myself. So I like using these conversations to kind of contribute to the investment community's understanding of complex matters, but also my own understanding. So I'm looking forward to learning through this conversation. And you've got a great background, so you have been on the buy side, but really the pension buy side, the kind of allocator practitioner side of things for quite some time.

[00:03:09] And some pensions are quite sleepy in terms of asset allocation and so forth, but the role you had, and maybe we'll start with UPS, took on complexity as well. So why don't you walk us through your experience at UPS and how you employed some of the quantitative strategies that we're going to talk about today? Sounds great. Well, UPS was a pivotal chapter.

[00:03:32] I was Managing Director of Investment Strategy and Allocation and went to four on the Investment Committee, overseeing a massive defined benefit plan for thousands of retirees, mostly union folks who fueled UPS's logistics engine. My path there was built over 30 years, starting with systematic trading at hedge funds and CPAs, then running long duration fixed income and QIS at General Motors Asset Management.

[00:03:56] And most recently at UPS, I led the strategic and tactical allocation decisions, all the derivative overlays and the asset liability management, all with derivatives as our backbone. At UPS, as fiduciaries, our primary goal was funded status, keeping the plan's funded ratio steady and managing the major risk of the plan, that being rate swings and return-seeking asset drops, both of which could erode our funded status.

[00:04:23] Most importantly, it's the outperformance of bonds over those return-seeking assets during stress period that's the main driver of risk to our funded status. And it's a scenario where rates drop and equities tank, widening that liability asset gap. This rate outperformance could definitely be exacerbated in plans not fully funded like UPS's was at the time because the present value of the liabilities outstrips the market value of the assets, amplifying the impacts of that mismatch.

[00:04:50] On top of that, like any defined pension plan, the sponsors really pressed us to hit a specific expected return on assets target. These goals obviously pulled in opposite directions. Improving funded status often meant leaning harder into fixed income as funding rose, shrinking returns on the asset base. It was the classic pension, stabilize the balance sheet while boosting earnings per share for the sponsor.

[00:05:15] When I think about a pension, just from a high level, I think there are certain characteristics that make them unique. And as I alluded to, I've seen pensions that embrace complexity. And I think some version of that is embracing the durability of their capital. Some of the risks that the market allows you to monetize, the risk premiums really force you to be pretty mark-to-market insensitive. So that's one.

[00:05:43] And I think a second aspect you alluded to this, and I'd love to just learn a little bit more about this, is the exposure to ultra low rates, right? I mean, if you're covering a hedge fund, they really don't care so much about rates going down to zero. Maybe they care in 2020, because as you also alluded to that, commensurate with that is a gigantic market sell-off, a VIX that spiraled to 83.

[00:06:11] But the pension fund problem was around well before COVID, right? Just with respect to the long-dated nature of the liabilities and ultra low rates. And that even amidst a low VIX and well-behaved equity market, maybe it's 2015, 16, and so forth.

[00:06:30] I'd love to just learn a little bit more about the non-equity meltdown risk-off periods of low rates and how a pension fund, from a risk perspective, interacts with that. Yeah. As I alluded to, it's not even so much about rates selling off and increasing your liabilities. It's more about the relative performance of rates with equity. The thing that will really deteriorate your funded status as a pension is the outperformance of rates.

[00:06:59] So if rates go down, even without the commensurate move in equities, you're going to be losing on your funded status. So being able to mitigate that and creating a framework that allows you to view that as your utility function is paramount in managing a pension. I think a lot of people lose sight of that. I think a lot of glide paths lose sight of that. They're just hedging on maybe just the equity side or just looking at the rate side. The most important factor is the relative outperformance.

[00:07:26] That is what drives funded status and funded status volatility and is the biggest risk to the sponsor on their balance sheet. One risk event that I just always found fascinating, and it's pretty recent, is the UK pension LDI crisis from, I want to say it's kind of September, October of 2022.

[00:07:45] So fascinating that they're so leveraged to trying to prevent the scenario that you mentioned, which is guarding against low rates, that they need to employ leverage such that when rates pop up fast, they're totally vulnerable. I thought that was, I don't know, just really telling about some of the systemic risks that can originate from places you don't expect. Absolutely.

[00:08:09] Especially in places like in the UK where they don't really have a supply of the longer-dated duration to hedge, and that's why they had to take that leverage. I don't think that is necessarily a problem for the United States in the managing of their liabilities, but certainly was for the UK. Okay. And interesting enough, we did have a QIS trade-on for that, where we actually were able to take advantage of what we thought were compressed levels because of the buying. We didn't know when it was going to work out, but it was carrying positively.

[00:08:36] And when the rates did start moving up very quickly, we were able to monetize that position and make some money off. We're going to circle back to this, but one of the things that you're in some ways implicitly talking about there is just crowding, right? That everybody kind of needs to do the same thing, and you're finding an opportunity and a reasonable carry way to take the other side. So I want to just learn a little bit more about UPS and I guess the appetite for complexity.

[00:09:03] So you're at this pension fund, again, you're going to know this so much better than I would, but many pension funds are just not equipped to engage in complexity as you did at UPS. Would you say that that is a cultural issue? Did you and your team bring this to UPS? What was the kind of evolution of going from more traditional exposures to diving into some pretty complex product mix? It was very path-dependent for me.

[00:09:32] I was fairly fortunate early in my career. I worked as a trader, as a portfolio manager at hedge funds, CTAs. So I kind of had that mindset of being able to use different structures to create a return risk profile. And I was lucky that my first job in asset management was at General Motors Asset Management, where it was encouraged to look for different structures, look at different ways to think about how to manage a pension portfolio. I was able to work with some very intelligent colleagues there.

[00:10:02] I think Mila Krasnopolsky, who really started the whole liability-driven investment theory and then LDI Plus and worked very closely with her and looking for different solutions and different ways to manage a pension and take advantage of your balance sheet. That's a big thing with pensions. You mentioned and alluded to, we have a very long time horizon. We're very insensitive to short-term downtrends. And one of the big advantages of a pension is to utilize your balance sheet to take advantage of different ways to manage that profile.

[00:10:31] So I was very lucky coming from that hedge fund space into a pension that really valued looking at things from a different perspective and bringing in new product ideas. And then got lucky again when I was able to go to UPS. There was good leadership there and governance that was bought in. They had known of me from my GM days and was asked to come in and kind of help because they were getting to the point where GM was,

[00:10:55] where they were becoming a pension that delivers packages and their liability started getting outsized as compared to their market value. So again, I was able to come in with that mandate, with being able to think about how to manage the pension in a different way. And they were the ones that afforded me that opportunity. They wanted that. They hired the right people. They brought me in and a few other colleagues that were very talented in the investment space to be able to really come in and rethink how to manage a pension.

[00:11:23] Give us a little bit of history on QIS, Quantitative Investment Strategy. That's the acronym. If you can, just take us back a little bit in terms of big picture, the early days, maybe some key developments that took the industry to another level with regard to the ability to offer complex products. You know, we always say liquidity begets liquidity. So sometimes you've got to have enough action in order to reinvest back in the product.

[00:11:51] But I'd love to just get a broad history that kind of takes you through your time at UPS in terms of product development. Yeah, no, it's definitely been an exciting ride to watch. I've been working with the street for over 15 years on QIS strategies for portfolio management. And the evolution has been certainly striking. Early on, I'd say it was basic futures options and swaps, very simple tools for simple tasks. But things got much sharper over time.

[00:12:20] I think a key milestone from my perspective was the shift from OTC, over-the-counter light exotics like variant swaps, gamma swaps, correlation swaps, knockouts, etc. that were able to be replicated within quantitative investment strategies using exchange-traded derivatives. OTC obviously offered tailored payoffs, but it was very murky and slow.

[00:12:42] So the real turning point was, I think, when the banks had the ability to crack delta hedging advancements and pair that with the delta replication for indices and single stocks. That really unlocked the replication of OTC products into exchange-traded instruments with intraday delta hedging. Sometimes now, multiple times a day in very low latency.

[00:13:06] But really was able to deliver that transparency, liquidity, and precision to volatility management within portfolio constraints. As an example, take variant swaps as a specific case. QIS didn't just replicate them efficiently. It let me target specific distribution zones. We'd split them into down variant swaps and up variant swaps. Down variants really honed in on the left tail going long variants when markets fell below a strike. Pretty much crash protection at its finest.

[00:13:36] Up variants grabbed the right tail, amplifying upside volatility and rallies. During COVID, this hit big. Down bar turned into a very deep value move. Cashed out at peak turmoil and it's a play liquidity provider in a broken market. While up bar really powered the rebound. Unlike OTC variant swaps where you'd really tussle with the counterparties, these exchange-traded versions were very smooth and clear. And I was able to monetize them very effectively.

[00:14:04] The street, I think, is even pushed further into mixing like gamma swaps with variant swaps for long and short skew products. Long skew, obviously strengthening downside defense by targeting skewness. Against systemic risk and short skew, cash in on upside bursts all dialed in. So if we step back and we just think about optionality. And I think what you're exploring is, okay, you've got the delta hedging regime of either buying or selling an option and then delta hedging it.

[00:14:34] And then creating some outcome that is contingent on some version of realized versus implied volatility with all kinds of path dependencies. And the variant swap solved very nicely for reducing that path dependency, packaging it up. And as you said, outsourcing the delta hedging activities, the strike risk activities to the dealer.

[00:14:58] And those variant swaps have been and continue to be offered on a bilateral OTC basis where I call up my favorite dealer and price it out. And I'm now either long or short implied versus realized on a ISDA contract basis.

[00:15:16] Take us through where that development or that advancement from listed options and internally running the delta hedge to, okay, I've got this clean package called the variant swap. Where does QIS take the variant swap to? So what QIS is able to do is they're able to replicate that variant swap and exchange traded instruments.

[00:15:38] Which by first principles is very important to me because it gives me much more transparency and liquidity that I can value and monetize quickly as opposed to an OTC. As an example, they can replicate a variant swap by selling the whole strip of puts and calls across the surface. And then by delta hedging that exposure, they're essentially replicating what a variant swap was.

[00:16:06] And again, it's all in exchange traded, so it's very liquid and transparent. The other thing it can do is it actually allows you to split a variant swap into the left and the right distribution. So if I don't want to target right volatility or up moves in volatility, I really want to concentrate on the defensive part.

[00:16:25] By replicating that, I just take the put strip and delta hedge the put strip to the downside to create a defensive strategy for me with a lower bleed profile than you would get from, for example, buying an out-of-the-money put. Which also, as you correctly mentioned, also comes with kind of that path dependent risk as well.

[00:16:44] So really the delta hedging, the fact that they're able to delta hedge, delta hedge, enter day, really afforded them the ability to take some of these OTC derivatives that were only available in OTC bilateral format and create strategies in exchange traded markets. That allow me to trade, give me the flexibility, the transparency to trade more effectively in my portfolio management. So provide for us some big picture, I'll just call it taxonomy of QIS. Some people will say there's only two asset classes, long vol and short vol.

[00:17:16] Another AlphaExchange guest, Corey Hofstein, likes to talk about vol. He says no pain, no premium. You're kind of on one side of the ledger or not, but not totally. You've got a couple of subcategories here you call carry, hedge, roll, trend. Take us through just sort of the big picture of how someone should think about the various, because I know you can kind of do these for each asset class,

[00:17:39] but perhaps you can just take us through the big picture of when you think about a portfolio of QIS strategies, take us from the top. Absolutely. So at Simplify, we've really taken that broad universe of bank offering and really shaped it into our own taxonomy framework. As you mentioned, absolute return, vol carry trend, upside convexity and hedge. That being said, there's many ways to classify a taxonomy.

[00:18:04] And the way we've crafted it is really based on a multidimensional approach that blends each strategy's risk return profile, liquidity tenor, and investment style that creates these five risk factors that are orthogonal and are there to really maximize the diversification across the different return drivers. Where it's differentiated is we did not rely on the traditional one-dimensional approach of utilizing correlation and covariance matrices,

[00:18:33] because as we both know, they're very unstable and tend to correlate during the crisis. These risk factors that we define from that methodology then roll up into two complementary buckets. Call it defensive, which includes the hedge risk factor, and carry, which encompasses the absolute return, vol carry trend, and upside convexity.

[00:18:52] And it's this modularity that lets us dynamically tilt at the bucket level, dialing up defensive for a cautious stance in rough markets or really leaning in to carry your upside convexity for a more offensive push when the conditions favor returns. And that's how we package it into our QIC ETF for a really streamlined, diversified solution. So when we talk about carry, I'm a simple guy and mostly in listed options.

[00:19:19] And, you know, we all know that S&P and other assets, they go up slower than they can go down, right? There's not an upside equivalent to March of 2020, thankfully. Well, maybe not thankfully, but it's just the way traditional markets, at least equities, work. I mean, you might not be able to say the same thing about corn or Bitcoin, right? Because those can really experience up shocks. With respect to options, you take a very long-term view and there's a vol risk premium.

[00:19:48] Geico gets paid to sell car insurance. Goldman Sachs should get paid to sell market insurance, right? That's over a long period of time. You can't just hedge. You're going to bleed out, even though you can hit big sometimes. So that's my very basic definition of one form of carry. I know there's a lot of nuances to it. How do you think about the carry bucket in a QIS strategy? I'd say at its core, I define carry as the return that you pocket just for holding an asset over time.

[00:20:17] Assuming everything else, price and conditions stay pat. It's the reward you get without needing the market to swing your way. One of the quotes that I heard, I can't remember where I heard it from, but always references, carry is the expectation of return, all else equal, but all else is never equal. So really, it's a fancy word for hope. So that's, again, just to get a laugh, but there is truth in that. Carry is more than just simple income. It's really tied to market quirks and human behavior.

[00:20:45] And a lot of different drivers of carry out there that, like you said, over time, create that profile where you can earn return for just sitting there and holding the asset. Another quote I like is, the road to hell is paved with positive carry. Yeah, I like that one. So we know you have to be careful, right? There's GFC, XIV, LTCM. I mean, these are short convexity trades gone wrong, obviously in 2020.

[00:21:14] And I know that these are not all the same, but there are certainly some really bad stories about, call them alternative risk transfer trades, right? It's the selling variance caps, totally improperly sized and priced, where folks are just very much on the wrong side of events that you just could not have possibly anticipated. So you have to obviously be very careful on these things.

[00:21:42] And a lot of that in terms of carry, at least from my perspective, I'd love to just hear you kind of riff on this, is sizing. You can't go broke selling vol unless you size it wrong, right? And so sizing is really difficult. And of course, when we size things, we're to some extent always looking backwards a little bit. We have to understand the nature of the asset, the nature of what a shock would mean historically.

[00:22:10] But we just never know, just kind of as your carry, what you said about carry, it's like it is never the same going forward. How should you think about on the carry bucket of your QIS portfolio? How do you think about the sizing? What's the work that goes into sizing? Yeah. So there's a lot of work on that. And it's done from that risk factor perspective. The way that we manage a portfolio, I guess we have a different perspective.

[00:22:35] The way I look at managing a portfolio is I try to get rid of as much of left tail risk as I possibly can. So I can take and tame that volatility upside and take the risk to earn that return. And then it becomes a matter of function of if I were to get a shock event, we run a lot of stress and scenario analysis across the portfolio. Diversification is key. So not only are we carrying premium and equity, but also rates and credit and FX.

[00:23:03] So we have a diversified set of carry that should be working in our favor. But you can think of the portfolio as those risk factors in the carry bucket with a defensive overlay on top of it that tracks both the short-term kind of low bleed dislocations and tail events. And we run a lot of scenarios on that to let us know how much can we carry in a very bad scenario? What would the move be? And what is the expectation of the protection that we're getting from the defensive portfolio?

[00:23:32] So we'll always have carry with defensive matched. The goal is, like I said, to get rid of the left tail risk so we can be comfortable taking on more volatility and higher risk on the return-seeking side. Carry has referenced this idea of just holding an asset with, what do you get paid for just the capital that you're committing if nothing changes? And I go back to, I mean, this is going to go way back, but one of the things that always fascinated me and just shows you the time variation

[00:24:01] of the return on capital is, go back to before the crash of 87, you're getting 8%, 8.5% on a 10-year note with roughly 4% inflation. So 450 basis points of real yield. Fast forward to 2016, 2017, your real yields are negative, right? So what do they call that? Returnless risk. So two questions. One, how would you describe the, not on things like fixed income and interest rates,

[00:24:31] perhaps that's tied to Fed policy and so forth, but what is it that you think is the source of carry? Like why the market's enabling you to peel off an attractive level of what's called static income, if nothing changes. And then related to that, how do you evaluate carry? It's going to vary over time. Markets change, the investor base changes, the financial system goes through evolution.

[00:24:59] How do you think about the sources and then evaluating whether carry is a good deal? So great questions. On your first question, what are the main sources of carry and what drives carry? I think there's a number of them. First, I think there are frictions and imperfections in the market. They aren't necessarily slick machines. There is a grit in the gears. Transaction costs for one. If trading's pricier, sluggish, investors want that little extra for tying up their money. And that boost carry. And then there's liquidity premium.

[00:25:29] Hard to sell assets like some bonds or niche commodities will often pay more to offset that hassle. So structural hiccups create carry opportunities if you're patient enough to hold on. Again, there is a timeframe associated with that. Next, I'd say you have to look at capital constraints. Not everyone's swimming in cash or free to chase every deal. Banks might hit regulatory leverage caps, keeping them from pouncing on tiny yield gaps.

[00:25:53] I think regulatory leverage also has increased the offering of what you call art strategies as well, which I had a fairly big book that I was running at UPS because I do believe it was very efficient carry. You had the same risks as regular carry, but I think it was the most efficient form that you could get. Smaller players might not even have the firepower to do like, say, currency trades. So when capital gets boxed in, the gaps don't get arbitraged away that fast, which can leave carry on the table.

[00:26:22] And lastly, probably risk aversion is a big driver too. People don't like uncertainty. And that's always been the case. So carry often means taking a risk and investors demand a premium for that. High yield bonds would be a classic example for that. It's not free, but the compensation for what if, that's where the risk averse folks like us can actually step in to get those premiums. And lastly, I mentioned time horizons play a role.

[00:26:48] So long haul investors like us at UPS at Pension Fund love steady carry from like dividends in real estates, for example. Really focusing on decades and not days. Short-term traders like hedge funds might start nipping at mispricings, but their moves don't always close the door for longer-term carry plays. And that mismatch can keep opportunity alive. And lastly, behavioral factors, I think, will play a fact.

[00:27:13] Markets are human after all, and overreactions to bad news can overshoot, which tanks prices and can create some pretty juicy future carry. Yes, and it's fascinating that the sort of linkage sometimes, maybe this is a Hyman-Minsky reference, but the relationship between risk on and risk off, they're opposites, but kind of joined at the hip. Very closely related. Yeah, you get the big risk off as a function of maybe a risk on event occurring for too long.

[00:27:43] I just always go back to 2018 as an example. And then, you know, maybe sort of running with Feb18, the Valmageddon, not to say that that was a function of QIS. It's really poorly designed products, or maybe they were designed to do exactly what they did. But how do you hedge against the risk of being wrong? Like reserving the right to change your mind. If I'm long NVIDIA and I want to get out of it, it's pretty simple. It's near zero transaction costs and friction.

[00:28:11] These are more complicated constructions. If you have re-evaluated something, it's not doing what you thought, or as you try to re-underwrite it, you just can't get there. How do you give yourself an effective escape hatch from getting out of the trade? I think that is part of the beauty of QIS strategies themselves, right? So there's strategies that are created in coordination with us and the banks to target a certain premia.

[00:28:37] They're wrapped in a swap, and it's that swap that we trade in our portfolio. The swap itself, I can get in and out of that trade whenever I want. So if the carry is not working, or I don't think it's working, or any risk premia or any QIS strategy isn't working, as we're assessing it and taking the data in on a daily basis, we can just lower that exposure, get out of the exposure. Or if we think it's just a timing thing and it's going to recover, we can add overlays or hedges on top of that to mitigate the risk.

[00:29:07] But if there's a real crash event, it's very, very difficult to get out of. If it's just not working and it's dragging every day and it's not just behaving the way that I expected it to when I ran the initial analysis, that's easy enough. But unfortunately, if you're in it and you have a real fast gap event like Balmageddon, it's almost impossible to time that and get out of it.

[00:29:29] And that's where the real risk and identifying the risk of those moves in your portfolio and being able to handle those within the portfolio construction framework that you set for yourself, that's vitally important. You got to really do a lot of stress and area analysis on your portfolio, use Fab18th as an example, and even use up made up stress events that you can't even imagine that could be worse through multiple Monte Carlo simulations and bootstrapping of the strategies that you have.

[00:29:59] Risk and the managing of risk is paramount in those particular cases. So let's shift to your joining Simplify to lead the charge on creating a really unique product. Walk us through kind of that transition, and then we'll talk about what's a really unique effort to bring a complex set of exposures to an ETF. Great.

[00:30:22] So the chance to build QIS at Simplify actually grew organically, actually starting from my time at UPS, where I managed the QIS assets for that pension. I had actually worked closely with Simplify's founding partners as a senior advisor while I was at UPS on the QIS ETF. That was a legacy ETF before I had started.

[00:30:42] They had new my background, 35 years with quant strategies, systematic trading derivatives from hedge funds to UPS, and saw it meshing with their goal of making these sophisticated tools accessible to all. So when the UPS OCOIO transition was finalized with Goldman, and that transition was wrapped up, kind of the stars aligned.

[00:31:05] They had pitched me on leading the QIS charge, and I was hooked, not just to copy what was out there, but to really reimagine it in a scalable, cost-effective ETF for individuals, investment, advisors, and institutions. Perhaps the product mix is going to be similar, but boy, the architecture, the implementation, the end investor. You mentioned kind of retail investors owning an ETF, perhaps the durability of the capital.

[00:31:32] I'd love for you to just give us what is similar and then what's very different, and then how the building out of the structure at Simplify reflects those differences. Yeah, so a lot of it is focused more, I was really concentrated at UPS on more of the defensive profile. So I really added defensive tilt to the profile. At the ETF, a lot of what drives ETF and flows in the ETFs is the returns.

[00:31:58] So we're really trying to stay within the framework of really mitigating what the left tail losses are, but really juicing up on the return side and building out really a dual-factor machine that blends both the defensive and carry strategies to deliver really consistent, uncorrelated, absolute return. It's really about, like I said, taming that tail risk so we can really embrace the volatility for the bigger rewards. I can imagine there's got to be a fair investment in education on something like this.

[00:32:27] Yes. I mean, the implementation, an ETF definitely has its hurdles and perks. One of the challenges I mentioned is really nailing down that orthogonality by keeping the clusters distinct during tough markets. Costs are tricky too. Translating bank strategies into an ETF means wrestling with slippage and fees, but we do a lot of in-house replication to really pin down the real numbers. But then on the flip side, the advantages are huge. We do get daily liquidity, broad access to beat the clunky bank deal models.

[00:32:57] Dynamic allocation lets us shift between defensive and carry on the fly. It's set up that, like you said, we want a buffer downside, fuel growth, and it's really perfect for investors looking to take smart risks with a safety net. And that's really the vision for QIS that we're trying to drive at Simplify. So you use that term orthogonal, which brought me back to an econometrics class and had me shivering. But the idea of trying to make sure that your exposures are uncorrelated, and that got me thinking about two things.

[00:33:26] One is just going back to carry again. I used to say like a rising tide of vol lifts all boats, right? And it's not altogether the same. Some vols are more correlated than others, right? Equity vol and credit vol or credit spreads, they're moving together. You know, the move index is going to go up with the VIX, but not entirely. You can get into stuff that has its own dynamic. Gold is going to do its own thing. Certainly, you get into things like soft commodities there.

[00:33:53] That's just much less correlation to something like the VIX. So that's the first part. And you referenced just trying to make sure that you haven't, I guess, overestimated the degree of diversification you're getting. And then the second part, maybe riff on this one, is crowding. That VIX product unwind is a function of the daily reset. But boy, it sure felt like those VIX ETPs got really big, you know, $2 billion plus.

[00:34:20] And the rehedge just overwhelmed the liquidity available in the market. So as you do your work on underwriting strategies, what's the process of trying to kind of look around and say, you know, I feel like there's a lot of consumption of this same risk exposure. And that's got me just looking over my shoulder a little bit. Yeah. To your first point, obviously, like you said, orthogonality and that maximum diversification is key to us.

[00:34:47] And that's really how we initially set that taxonomy, right? By crafting those orthogonal risk factors through a very multidimensional approach using the characteristics, as I mentioned, of the strategies, not just the correlations of the strategies, but a multidimensional characteristics that really creates the distance measure to drive the orthogonality. And then it gets tested.

[00:35:40] So we are very billaging. Rising participation, like carry trade getting involved, definitely sets off alarms. Returns thinning or moving in lockstep with each other is another sign. Execution costs climbing means that the field's pretty packed. And we check capacity. If the inefficiencies are drying up, the edges toast. And we eye flows, right? Billions flooding into a factor definitely wave a red flag.

[00:36:06] So I term it almost like a systematic discipline plus a streetwise edge that we're trying to eye and ensure that QIS stays robust and delivers. And because we do have a lot of relationships with the banks that have established a lot of the structures and the QIS desk are, you know, I can call them friends of mine on the street. But regardless of that, we're able to get a lot of information from them on what the capacity of the strategies are, how much of the capacity is filled. And we obviously keep track of what the costs are being offered.

[00:36:35] So it's subtle, but we look at many different things to try to really understand what the crowding is within a particular strategy. So there's a bunch of dimensions we can look at this. Again, your way of partitioning some of these carry, hedge, roll, trend. Those are four. We could look at the asset classes. There's probably those in each asset class. And then is it fair to say you have geography as well? Or does each of these exist within a geographical segment or at least a major market segment?

[00:37:04] I don't look at geography, but the geography has a distinguishing characteristic that creates a different distance measure from the classification that I'm adding than it will. So you can look at that. That is certainly a way to look at classification. But I'm taking a little more of a quantitative approach and looking at like really the characteristics and the metrics of the strategies that are driving the distance measure. Like I said, just because Eurostoxx, SX5e and S&P, they're still going to be fairly highly correlated.

[00:37:34] So I want to make a distinguishing characteristic or distinguishing cluster more based on more representative kind of quantitative measures and metrics, mathematical parameters, as opposed to just signing geographies or asset classes. We go across all asset classes and we have a mapping of the asset class to the vector that it sits in, but we don't look at it that way.

[00:37:57] We look at it from the vector and the risk vectors that we created that we think provide optimal orthogonality to the markets. And if we looked at the asset classes and the kind of subcategories of components like carry and hedge, would you say that there's a dominant component? I mean, carry seems like a pretty important component of this universe, but I don't know if that's correct.

[00:38:23] And then just asset class wise, is there one where the banks are engaged in delivering this product more than other asset classes? Yeah, that's a great question. So it's really a three-step process. The first step is looking at what universe do we want to include within the strategies? And that's 80% of the work. There's a lot of work that has to go on there and you got to look, making sure that you're never going to see a bad backtest, right? And we don't hold a lot of credence to the backtest that's provided to the bank.

[00:38:51] We take that and do a lot of our own work so we can have a true expectation of what the profile is going forward. And that's how we set our universe of QIS strategies. The second step is the aggregation, and that's where the taxonomy fits in. How do we then take these strategies and put them and fit them within these orthogonal risk factors? The third is the portfolio construction. We looked into a lot of ways to see if it added value. You know, we're looking at Kelly Criterion maybe, looking at different metrics to building a portfolio, looking at drawdown risk, carry to drawdown risk.

[00:39:20] What we settled on, we think works good most of the time. So I'm going to work best all the time is a simple vol-weighted measure. So once we have those buckets, they simply get vol-weighted. So because of that, carry has had a pretty good historical return profile, a fairly good return to risk profile. So it is going to load up more on, say, the volatility carry strategies because of that, but not by an exorbitant amount. But it does have a higher loading just by the way that we're constructing it.

[00:39:50] An investor is typically thinking about, I would call it three buckets of risk. Equities, credit risk, maybe duration risk. Those three. And my sense is that the objective of Simplify's QIS is to clearly deliver positive return, but do so in some kind of all-weather fashion. Low correlation to the more traditional factors.

[00:40:13] I'd love for you to just talk about how folks should think about owning this in the context of the traditional risk exposures that they already take on. Yeah. From my perspective, I think you should view QIS strategies like our Simplify ETF as a complementary layer, not to stand in for traditional exposures like equities, credit, or duration risk.

[00:40:34] We do target alternative risk premium that don't follow the same playbook as your traditional drivers, making it, we hope, a diversification ace. In our QS ETF, defensive strategies like convexity and vol hedges kick in during tail risk, crashes or liquidity crunches where bonds may stumble. Another way to look at it is maybe it could be a little bit of replacement for fixed income in a 60-40 portfolio.

[00:41:00] I think there's concern of why bonds may not be a good hedge at this time around. Lower yields have gutted their cushion rising rates like 22 hammered their value. And shocks like what happened in COVID March 2020, they've sold off right along with equities not against them. Correlations crept up and their safe haven status is ironclad anymore. So we think that using us, in particular, that defensive cluster, it's really engineered to shine during those dislocations.

[00:41:27] And at the same time, you have your care and your trend strategies are able to tap those structural inefficiencies or momentum to deliver nice, steady returns in stable and trending markets. So we look at it as almost like an overlay. The ETF itself will fit in. It would be like a layer to your portfolio. But interesting enough, we also are running a QS mandate in an institutional space, which may even offer some additional edge, like an unfunded alpha source.

[00:41:55] Because in that particular way, we can actually port this QIS strategy as a portable alpha or an overlay defensive strategy onto a given portfolio to create an unfunded profile for you. Again, to diversify what your current portfolio beta risks are. Yeah. And I think diversification is the golden goose. It's really difficult to access. So anything that can do that is going to be valuable in the context of the portfolio.

[00:42:22] So some of what you discussed was just your interaction with the street. As a client of the street, it seems to me that you and colleagues are in the lab sometimes. They're coming to you with stuff. But I think when a client relationship is fruitful with the sell side, there's mindshare going on there. So I just think back on you've had periods of incredibly high vol and low rates, call it GFC or 2020.

[00:42:49] You had low vol and low rates, which is 2015, 16, 17. 2022 is kind of high vol and high rates, the joint drawdown of stocks and bonds. And so it seems to me, I'd love for you to talk about this, but some version of the product development cycle is going to be a function of the set of prices or correlations or returns that clear the market at a given point in time. And we're kind of solving for something.

[00:43:16] And I would just love to understand a little bit around where the product development, where you see it now, big picture. Are there things that you were excited about? Are there not to reveal anything confidential, but just from a where you see QIS going with respect to trying to add value to portfolios? What are some of those conversations like? No, that's great. You know, and I'd say at Simplify, it's all about pushing the envelope with these strategies, right?

[00:43:46] And there's actually a few areas that we're having initial discussions on that have me particularly jazzed as we innovate. First up, I think it's structured products in ETFs like autocallables may be the next big thing. There obviously have been the domain of big institutions and wealthy clients through private setups. But being able to stuff those into ETF opens the door wide. Just imagine an ETF with autocallable style payoffs, downside protection plus upside tied to equity indices.

[00:44:16] It's perfect for a cautious investor still chasing growth and a smart complement to like fixed income, especially with bonds struggling against rising rates. So we're working with options and overlays and dynamic hedging, trying to keep it lean, liquid and transparent. Another area is tokenization of assets. Still early, but that's loaded with promise.

[00:44:40] Turning ownership into blockchain tokens, we think will certainly unlock liquidity in clunky markets like real estate, commodities, and also cut costs as well. So think about like tokenizing carry from rental yields or commodity spreads, bundle that in an ETF or smart contract, smoothen out trades. I think that would be super interesting.

[00:45:00] And we're tracking this closely, testing out how those baskets might slot into QIS framework and enhance the transparency and tapping into that kind of fresh premium, as it were. As you mentioned, tokenization, I couldn't help but just think of crypto in general. Does Bitcoin as a risk exposure make its way into any of the QIS products at this point or it's too early? We're still assessing that. It was nothing I was involved in.

[00:45:26] I like some of the characteristics of Bitcoin and cryptocurrencies, especially it's a ball profile. It is that up ball profile that is diversifying and very hard to come by. The gold has a similar profile from time to time. So we like that profile. And then the options on crypto look like they could offer some pretty decent carry opportunities. Of course, it's going to come with some risk. So we're assessing that now, but we can certainly see that in the program once we finish our analysis on it and really understand the underlying risk of what that profile looks like.

[00:45:56] And where do we find the Simplify QIS ETF? So it's traded on the American Stock Exchange under symbol QIS. So it is the best symbol out there. You got it. Yeah. So very easy to find. Or you can go to the Simplify website as well and search up alternative investments and look for the QIS ETF there. And as a profile of what we're trying to target, our investment philosophy and some of the underlying holdings that the ETF has.

[00:46:24] The only caveat I'd say to that is it was a legacy ETF before I took over the management of it. And we finished the enhancement of that strategy around October 8th of this year. And it was about an 85% or 90% turnover within the ETF to structure it the way that we wanted to implement the QIS. So even though it has a kind of a longer time history than that, and we don't have a long time history to go on, it's really our DNA has been implemented as of October 8th on the strategy.

[00:46:53] So as you're looking at it, it's something to keep in mind. Excellent. Excellent. Well, we wish you the best of luck as you bring a really interesting and new product to the market. Roxton, I have very much enjoyed the conversation. And as anticipated, I learned a bunch just in being able to hear you talk out loud about what I think is a pretty interesting, really advanced innovation aspect of the street, which is QIS. So thanks again for the time. Thanks, Dean, for having me. It's been a fantastic experience. I really enjoyed chatting with you.

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