My guest is Devin Anderson, co-founder of Convexitas.

The theme of this episode, as you can likely guess from the title, is strategy versus structure. While we often focus on strategy specifics on this podcast, Devin hosts a masterclass as to why the structure you wrap your strategy in can ultimately determine the type of strategy you can deliver.

Specifically, we discuss option-based tail hedging and the types of strategies that can be delivered in hedge fund, mutual fund, ETF, and separate account wrappers.
In the back half of the conversation, we dive into how Convexitas implements their risk mitigating strategies. Specifically, Devin explains why Convexitas focuses on convexity with respect to the S&P 500 and actually refuses to customize this mandate, despite having the ability to do so at scale.

Finally, we end the conversation on a bit of a spicier note, where Devin explains why most market pundits overstate the influence large, scheduled derivative rolls might have on the underlying market.

Please enjoy my conversation with Devin Anderson.


Corey Hoffstein  00:00

321 Let’s jam. Hello and welcome everyone. I’m Corey Hoffstein. And this is flirting with models. The podcast that pulls back the curtain to discover the human factor behind the quantitative strategy.

Narrator  00:19

Corey Hoffstein Is the co founder and chief investment officer of new found research due to industry regulations he will not discuss any of new found researches funds on this podcast all opinions expressed by podcast participants are solely their own opinion and do not reflect the opinion of newfound research. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of newfound research may maintain positions and securities discussed in this podcast for more information is it think

Corey Hoffstein  00:50

I guess this episode is Devin Anderson, co founder of convexity toss. The theme of this episode, as you can likely guess from the title is strategy versus structure. While we often focus on strategy specifics on this podcast, Devin hosts a masterclass as to why the structure you wrap your strategy in can ultimately determine the type of strategy you can deliver. Specifically, we discuss option based tail hedging and the types of strategies that can be delivered in hedge fund, mutual fund ETF and separate account wrappers. In the back half of the conversation we dive into how convexity loss implements their risk mitigating strategies. Specifically Devin explains why convexity Ross focuses on convexity with respect to the s&p 500 and actually refuses to customize this mandate despite having the ability to do so at scale. Finally, we end the conversation on a bit of a spicier note, where Devin explains why most market pundits overstate the influence that large scheduled derivative roles might have on the underlying market. Please enjoy my conversation with Devin Anderson. Devin, welcome to the podcast excited to have you here. This is going to be a pretty unique episode for flirting with models. So I’m excited to dive into things. Before we do though maybe you could start off with a little bit of background. let folks know who you are, and what you’re working on. Now with convexity us.

Devin Anderson  02:16

Sure. So my name is Devin Anderson. I’m a co founder of convexity toss along with my partner said Francis, we are a boutique asset manager specializing in derivative overlay strategies in small institution High Net Worth are a wealth like channels, I have actually an institutional background and worked at Deutsche Bank for 15 years in a variety of derivative desk trading roles in the investment bank, as well as to gently to the private bank in that capacity. From flow salesperson to running a structuring desk and the non flow solutions business at Deutsche Bank for a period of time, also spent a couple of years in the capital release unit after we shut down equities liquidating off businesses, which is a fascinating experience to have worked at a disposal unit or more colloquially called a bad bank. Before that, I had a whole career in technology where I was one of the early members of some very early days like 1996, AOL and CompuServe era internet service providers and commercial Internet businesses and some data center businesses. And I did that before going to business school, which led me to finance. So I’ve actually had a tech background as well as a relatively long derivatives background. And now is that am I running an asset manager?

Corey Hoffstein  03:38

Well, I think those two backgrounds are going to come together nicely for listeners, as they sort of understand what you’re bringing to market with convexity loss. And as I mentioned, this is going to be a pretty unique episode, as it relates to sort of the back catalogue of episodes I have because we’re going to spend a lot less time talking about strategy and a lot more time talking about how structure can enable or prohibit strategy, particularly as it relates to the realm of tail hedging. So we’re going to be talking mutual funds versus ETFs versus SMHS. And to start us off, I was hoping you could explain this concept of the long volatility tax scalability triad.

Devin Anderson  04:20

Yeah. So when we really break down the desire for people to access some sort of risk mitigation strategy, we we like the term risk mitigation strategy because I think it’s a little bit more encompassing of what are the more historical, fun based tail hedging strategies versus what we do versus the note and hedged equity ETF and mutual fund space. So I kind of think about risk mitigation is all of those things. So when you when you think about designing or allocating to a risk mitigation product, they come in, generally speaking, two forms, you either write a check to a fund And that does that thing or possibly provide your market beta or your market allocation plus a risk mitigating strategy, or you allocate to an SMA manager and the SMA manager, the separate account managers with SMA means runs that strategy on your behalf in your account, the path that you go down between these two things, has very serious consequential decisions for everything from the opportunity set that you have as the manager and the things that you can do as a manager to deliver those returns all the way down to the tax consequences for the individual investor. So you have to make very fundamental trade offs between the investment efficacy of the product, the tax treatment of the product, and then how scalable it is. And is it a reasonable business for the investment manager. And of these three things, you can’t have all of them. So you can create very scalable businesses that don’t have a ton of investment flexibility, and are essentially a trading strategy on a treadmill. That also ends up with a lot of path dependency risk, but could be okay, on the tax standpoint, you can create things that are very tax efficient, but are horribly unscalable for the investment manager. So the point is, you can’t just have all three of these things, you’re gonna have to make choices between path dependency, tax, and scalability. And you because you’re not going to get all of them. I think it’s important that when you allocate or subscribe to one of these products, you kind of understand where the manager is coming from, and the decisions that they’ve made along the way to get to the offering that they’re talking to you about.

Corey Hoffstein  06:48

So I wanted to sort of flesh that out maybe with a couple of examples. And perhaps we could start with the hedge fund structure. When you’re talking about a hedge fund, you were talking about a funded pooled vehicle. So what does that imply to you about the type of tail hedging strategy that’s ultimately feasible? What can actually be delivered by a manager in that structure, especially given that many of the allocators may be institutions who aren’t tax conscious?

Devin Anderson  07:13

Right? So the moment that we go into the funded world, you find whether it’s a commingled hedge fund or an ETF restructuring, it’s kind of all the same, all the same thing. The moment that we go into a structured vehicle, there’s really only two types of these, you can either get the derivative, return the tail hedge or risk mitigation return alone, or you can get the risk mitigation return, plus some market beta, some market access at the same time. So let’s kind of talk about why that is the case. So the first iteration of these products, after the financial crisis in 2009, was really all funded vehicles, it was a hedge fund as you would typically understand it with a two and 20 fee structure that you would write a check to. But long volatility is unique in that it’s not really an alpha strategy. I’m going to pick on that statement later. That’s not a complete sentence. But it is very important when we start to talk about reinvestment, but just for the time being, let’s stipulate that it’s not an alpha strategy. So when you allocate to this fun, you’re taking assets away from everything else that you’re doing for the rest of your alpha and beta portfolio. And that’s not optimal, right? So you don’t want to do as little of that as possible. So, you know, historically, like, how much assets are people really willing to take away from their portfolio in order to implement a risk mitigating strategy? The answer is two to 4%. Right? And we’ve got almost two decades of investing experience to tell us that that’s true. Well, if you’re allocating 2% of your portfolio to something that’s convex, and you need it to be meaningful at the portfolio level, well, then that thing that you allocate 2%, to has to allocate 10,000 20,000%, in order to be very meaningful at the portfolio level. If you have a 20 30% drawdown of public market equities, if you know that that’s your Bodie, as the manager, there’s actually a very small subset of things that you can do in order to be able to generate those kinds of returns on a draw. Right, and it can only be really the biggest draw downs. And all of those basically come down to relying on a substantial expansion of implied volatility and then the convexity that comes along with that, IE as the market goes lower, you’re getting longer vol, which is also going up a lot. That’s what we mean by volatility convexity. So that’s really the only option that you have in terms of strategy designed in the fund. To vehicle that does not include any beta, it’s kind of all you can do. So of all the things you can do an options, you’ve only got one tool, right? So either vol is going to expand and go up a lot when the market sells off or it’s not. And your entire return stream is going to be tied to that. Now you can have years like we had in 2022. There’s all this hand wringing and an explanation about fall not working or vols broken. You heard all about this in the first quarter kind of on a loop. And it’s not that vol was broken, s&p spot moved around plenty market off 18 and a half percent something on total return basis. So if that’s not volatility, I don’t know what it is. But what they mean is that implied volatility and gone. Alright, so this class of product did not perform. And that’s simply because of those the one tool that you can put in this commingle vehicle, it’s not going to work now. So what people will do to get around this is, they’ll say, Okay, well, I’m gonna give you both your market beta. And a return string, right. This is where the hedged equity mutual fund space essentially came from, right, because it wasn’t practical to have a 40 AKC registered vehicle that only had a bunch of options, right? So you can go down this road as well. But now you’ve got for taxable investors a relatively serious tax challenge that says, in order to switch into this product, they’ve got to get rid of their existing public market exposure, you know, whatever their Beta is coming from, and they’ve got to get their Beta from this. So now the decision to get your beta is being driven by the decision for your risk mitigation. And almost never can that be in a private fund, right, like no one’s gonna get, it’s very hard to tell an investor, I’ve got this great way for you to get risk mitigation. But that means you’ve also got to get your beta from a hedge fund. And when, you know, Vanguard will sell to you four basis points. So that doesn’t really work, right. But it does work in a mutual fund context. And that’s why you see some slightly different strategies, you get more, so you get some flexibility back to the manager once you’ve got the beta in there. So that’s why you see collar strategies, or put spread collars overriding these sorts of things and in registered vehicles, but even there, you’ve got some challenges. But you know, I know there’s questions coming about that. So but to answer your question, specifically about hedge funds. The problem with risk mitigation in hedge fund is that it’s very difficult to make it meaningful, a hedge fund allocation for long volatility is difficult to make meaningful at the portfolio level. And if you try to put the beta and the rest of the game strategy together a hedge fund, you’ve just got a very tough sale because people don’t want to get their beta for a private vehicle.

Corey Hoffstein  12:48

Well, we’re definitely going to get into the issues of the mutual fund in a minute. But I want to ask you another question first. And this one might be a little bit unfair to ask you because it was actually your partner Zedd, who brought it up to me. And he mentioned that for the hedge fund vehicle, particularly among institutional allocators, it invites an agency risk problem.

Devin Anderson  13:09

Yeah, so because there’s this very limited set of options, strategies that you can pursue that involve buying kind of far out of the money options, and relying on fall convexity, involve expansion, because that’s really the only strategy you can pursue to get that kind of convexity, you get very levered to what your monetization decision is. So if you’ve got a portfolio of seven to 10 month, you know, one or less Delta options, and you get the COVID sell off, okay, when you sell them, right. So essentially, the, the monetization decision becomes very, very difficult. The more you rely on vol expansion involve convexity as your primary lever of return. Now, you don’t have to like I think we’re going to talk about later that that’s, that’s actually a false choice. But if you’re going to rely on vol expansion, monetization is a very big concern. And the managers agency then becomes a very big concern, right, because they’re afraid of selling it too early. Because they sell it too early and lock in a game, particularly if there’s an incentive fee. Right now, there’s this big question of well, is the manager just they’re trying to lock in their incentive fee instead of trying to do what is best for the total return of the hedge allocation. The managers definitely afraid of selling it too late. Right. You know, there’s nothing worse than having a mark to market gain at the end of the month that’s then gone by the second week of the next month. So it’s just a very hard problem that ultimately is most likely to get resolved by the manager monetizing too much or too quickly.

Corey Hoffstein  14:52

So let’s now dive into the mutual fund structure. You started to talk about how that structure allows managers to come Syd are implementing slightly different tail hedging strategies. I’m not sure it’s totally obvious to me why they couldn’t be inherently limited to the same strategies that are available in the hedge fund space, maybe you can expand on that for me.

Devin Anderson  15:12

So in the hedged equity mutual fund space, as a rule, vols products are not just the options in the fund, it’s not just the risk mitigating strategy in the fund, it’s the risk mitigating strategy plus the market beta plus the market access, right plus the s&p or some replication portfolio. So because now they control both sides of it, their returns essentially don’t have to be 10,000% in order to be meaningful to portfolio level, because they control the underlying portfolio as well. So now we can start talking about things like collars and put spread collars, which are the popular strategies that are implemented in hedged equity mutual funds. The thing here is that those strategies tend to get pretty path dependent. So COVID sell off happens right before a quarter end, exploration of s&p options, market sells off and expiry, the roll happens. And you’ve monetized all this stuff looks great, right. But if the COVID sell off happens in April, instead, now it’s a much different question of what those returns would have looked like. So the mutual fund products tend to have relatively straightforward options, strategies like collars to get rolled on a treadmill, or you know, or they get broken up and kind of staggered out. But because of that, they tend to have a fair amount of path dependency embedded in them. So they’re not necessarily managing to the total risk all the time, they’re managing to the calendar of the expiry of their trays. So you can end up with quite a bit less, or quite a bit more market exposure in that product, then the end investor real realizes. So the day after the roll, let’s say you had a hedged equity mutual fund with a quarterly put spread Karna. Well, the day after the role, they’ve executed as put red color across the size of the whole fund. By the time you add the market exposure to the negative market exposure to the short exposure that results from the options, you may only have like 40 to 50% of the font size in active market exposure and actual delta or actual market exposure of the fund. And then as you approach expiry, assuming that you don’t get close to these calls, that they’re short, you know, that may look like 60, or 70, or 80%. But you know, most of the time when I ask people that use these vehicles, well, how much market exposure you actually have right now, they don’t really know, they know that they’ve allocated to this thing that is a market allocation plus an option strategy. But they tend to think about it as like two separate things, they’re not really adding the risk together, they don’t understand that if when you add those two things together, you only have a Delta of 50 and the market goes up 2%, you’re not gonna be up 2%, you’re gonna be up 1%, right. So the risk of those products to the I don’t mean the risk that they’re going to blow up, I mean, the actual market exposure that those products have, to most investors, they don’t really understand, in most cases, in my experience, what the risk actually is, they think they bought $100 in the market. But what they’ve really done is dynamically bought something like 30 to $80 of the market, depending on where the calendar is falling and how spot has evolved since the options were last struck. And it’s not that that’s not unmanageable. But it’s not ideal if you’re an RA to not really know what your risk is by a factor of two sometimes.

Corey Hoffstein  18:52

And one thing I’d add to that as well as I don’t think most investors in those products realize that they are actually at the roll, typically short vol. They think of them as being long convexity products. But Ronnie Israel often has written about this and spoken about this a number of times when you look at that zero cost put spread collar, it’s actually a short ball structure, which I don’t think most people expect it to be. So in particularly if you get close to this call strike that you’re short, right? So you could end up with situations where the hedged equity mutual fund rolls, their exposure, the market goes up gets close to the short calls that they’re long. And now

Devin Anderson  19:31

let’s say from there, now the market goes down. Well, they’re actually getting longer the market as it’s falling. Right. So that’s to your point. In that case. And this is a very stylized example. I could make one up and show you the numbers but I promise you it’s true. In that case, you can actually create situations and paths where the markets falling and you’re getting longer as it’s falling that is negative convexity. Now, if it falls long enough, that dynamic will reverse as the long option. Is that they own gain risk as the market falls. So it’s not, it doesn’t expand into infinity. Let’s be clear. But at the same time, in our view, if you’re hiring someone for a risk mitigating strategy, there shouldn’t be paths where the strategy displays some negative convexity. So let’s move on to talking

Corey Hoffstein  20:20

about ETFs. Because this is an area we’ve seen expansive growth in these option based ETFs. In many ways on paper, and ETF is very similar to a mutual fund, I would expect that the structure enables a very similar type of strategy. But you are introducing a host of new considerations. For example, you now have the authorized participant who is party to the trades, you have the market makers who need to be able to hedge the product, you need to have intraday pricing instead of end of day nav. And for many of these products, there’s a requirement for transparency into what is actually being traded, curious how that all comes together to potentially change the type of strategy that’s feasible in an ETF versus some mutual fund.

Devin Anderson  21:03

So let’s do a quick couple seconds on how ETFs actually work. Because it’s my experience. When I get asked this question, if I go right into the answer, we end up going backwards into how ETFs work and who all the players are. So I think people are broadly familiar with how 48 mutual funds work, right, there’s an issuer of 40 AKC registration is just basically an open ended issuance where the mutual fund company every day, creates or redeems units directly themselves, right. And then you own these units. They’re not traded among the investors that are issued to an investor or redeemed back to the mutual fund. And ETF, however, actually creates a security that is traded on an exchange between participants. So the way that works is a person that wants to start an ETF put strategy together, they find a sponsor, it’s seated, usually by an authorized participant. And an authorized participant is essentially a trading desk at an investment bank that has the authority to create shares. So somebody comes to them and says, I’m going to and there’s this thing called a creation unit. That is the standard holdings of that ETF, they say I want to create some amount of units, they give the authorized participant, either cash or securities and kind, those units are now created and sold to that particular investor. So that’s the role of the authorized participant, they’re essentially the gateway to creation redemption. But now that these things have been created, they can be traded on an exchange directly between investors, which means that market makers, either electronic market makers, or high touch liquidity providers and investment banks, need to make markets on those ETS. So in order to make a market on something, in my role as a market maker, I’m very likely to have inventory of that thing at specific times. And given that I’m going to have inventory of it, and I’m going to have to know what the value of it is, which means I need to know the contents of the ETF. And ideally, the contents of that is not going to change a lot. Because I want some certainty about what is in the thing that I’m being asked to make to a market on. You know, as a market maker, I’m in a role where I have to show a bid a price, I’m going to buy in an in an Ask a price at which I’m going to sell on of whatever this thing is. So I need to know what’s in there so that I can reasonably and professionally make a market on this ETF. So that’s fine. ETFs are great. The trick is when it comes to risk mitigation, is that by definition, we’re talking about strategies that are very convex. So a thing that’s very convex, doesn’t do well in an ETF. Because the market maker who has to make a market on the ETF is not going to be confident that they know what the value of it is. Right? So it’s one thing to say I have an ETF that has a bunch of stocks, and then I can easily observe the price of all the stocks and multiply it by the weights. And in real time, it’s pretty easy for me to come up with a value of an ETF that’s got a whole bunch of stocks, even if in the case of an ETF that is beta plus a bunch of options. Even if I could reasonably calculate the current value at that point in time of all the options. Once I have the inventory, it’s very possible that the value of those things can change very rapidly, which is not a desirable feature for the guy sitting in the ETF market making see. So like can it be modeled and can it be automated? Yes, of course, right? But that means that someone at virtue or pseudo securities is going to have to sit down and code something right at some level of abstraction to make a market on your Same and worse. And you know it kind of in the convexity loss case, if your option strategy has high turnover, which necessarily good option strategies and the risk mitigating space should be in order to maintain risk at the level that you need, because the risk changes quickly because they are convex. That’s even worse for the ETF market maker. Because anything that changes a lot isn’t great either, because now you just don’t know what’s in the basket. So there’s need to know what’s in the basket, as well as to be able to value and manage the risk of what’s in the basket, are critical requirements of anyone making a market and ETF. And those two things are just fundamentally violated by putting risk mitigating very convex strategies into ETFs. Now, certainly people do it. But if you look at the actual strategy being implemented in the ETF, they’re low turnover, and fairly easy to predict them. All right. So it will be the same kind of percentage out of the money puts in the same percentage ish out of the money call kind of all the time, right. And they’ll rebalance on a monthly basis or weekly basis or some long interval. And so that’s how people deal with this. But that restriction on the manager ends up being I don’t want to say terminal, but very difficult, right? We think if you’re going to the way that we’re the way that we run risk mitigation, the markets moving four or 5% in a week, we’ve got to train probably at least three times. Right? And if that happens in two days, like you know, you just can’t put a strategy like that in an ETF it just precludes. So the only way to have ETF is as I say, to have a very low turnover strategy, that’s not rebalancing its risk very often. And that, you know, that’s going to have investment consequences. Now we’re back to something that kind of looks more like the hedged equity mutual fund, just with intraday liquidity. Well, I’m not sure how badly you really need the intraday liquidity in this case. So that’s, you know, you end up taking on board, really material trade offs, when you think about this ETF structure. And we’ve had a lot of people just say to us, like, look, we love this thing, but it’d be a hell of a lot easier if I could just punch it up in my system, and it cleared on DTCC. And yeah, I agree with you. But unfortunately, the investment trade offs that we would have to make to deliver what we think is a really high quality risk mitigation product just aren’t congruent with that wrapper. Well, that brings us to the wrapper of choice for you, which is the separately managed account. And as you mentioned, that is not the wrapper of choice for many advisors today. In many ways. It’s a throwback,

Corey Hoffstein  27:31

I don’t think I’ve seen an advisor have an all equity SMA that they’re hosting for their clients since 2010. They’ve mostly migrated to ETF and mutual fund model portfolios. But I know that what you’re trying to implement in an SMA is far more difficult and complex than say, an all equity fairly vanilla SMA, can you talk to that a bit what makes implementing the SMA at scale with derivatives so much more complex than vanilla equities?

Devin Anderson  28:04

So first of all, I understand your point that the SMA feels like a throwback, what I would say is that in the current market, particularly in the world channel, it’s not that there aren’t estimates there are many, many SMA strategies. It’s just that SMEs are now being used where they’re needed for investment merit. Okay, so like, why would you have an SMA of large cap equity? Right, like that doesn’t make any sense. You can even buy an ETF. There’s no problem with turnover or liquidity or pricing or it’s easy to make markets on, it’s easy to distribute, like, depending on the strategy, there are many things that are much better suited for other rappers. But there are things that are for their own investment reasons like risk mitigating strategies, or money driven strategies, or even tax loss harvesting for that matter, where SMA strategies or places where you need lots of customization like direct indexing, where you had a real compelling need for direct indexing. Those do get implemented via SMA and in fact, every major custodian in the United States has SMA support and platforms and programs to cope with those managers. But here’s the thing about the SMA. The SMA is not ideal for the investment manager. Okay. And a couple of ways the first being distribution, it’s harder to onboard and just get SMA clients are up and running. Right? If I come into your office, and you like my ETF, that afternoon, do you can get on your trading platform and allocate to it right. You don’t need to ask anybody’s permission. Well, I mean, some platforms, maybe you do, but for the most part, all the plumbing, it’s all there, right? So a major difference to the SMA manager has to be able to act on that platform. There’s a bit of due diligence going on, it’s going to have to be done the actual positions themselves. holes are in the client’s portfolio. So that has some implications. It’s a harder thing to distribute, right. And the reality is that our business comes down to easy distribution. So, SMEs are not great for distribution for the manager. But more importantly, they’re harder on the operations side. If I run a hedge fund or any commingled vehicle, for that matter, I have one big pool of assets, right. And then the legal structure 40x, three C seven fund note, like whatever it is, the legal structure deals with the divvying out of the investors interests in that commingled vehicle in the SMA, that’s not the case, I’m dropping the trades right into the client’s account, which means I don’t have one big pool of assets, I have n number of pools of assets where n is equal to the number of accounts and clients that I have. And sometimes clients have more than one account. I mean, in the in the high net worth space, we can sign up one client and they show up with six different trusts. Right? So it’s, it’s not even one client. It’s six clients in a sense. So the tools out there to manage that at scale, or non existent to terrible, like there’s just no good answers if you’re the manager. And if you’re trading options, it’s even worse, like there basically is no answer. So we just put our thinking caps on a few years ago, and we built our own, we conceived of and coated the entire asset management backend that we run our business on from trade, staging, and pre compliance checks and Model Management, to trade reconciliation on to our entire trade staging platform. And then we collect files from custodians, run reconciliations, do our p&l right down to generating our billing. All right, we had to code it all. Because we had to be able to deal with a complex hierarchy of accounts, across many custodians. So it’s harder. The bottom line right now Zedd has the investment background. And I also, you know, kind of, by chance, have the technology background, and I’ve written code in previous jobs. So like, we were able to do it. So we invented this thing that allows us to run SMEs at scale within derivatives, and a very highly controlled, like, there’s a lot of risk control, and a lot of risk management and control functions that govern all of this, that we’ve had to create around this. But we did it that’s just beyond like the idea that an asset manager of any size is gonna like just start from scratch and build one of these systems. Like if you’ve ever worked in one of these firms, or worked in it at one of these firms, like it’s just not, it’s just not possible, right. So like, you know, to some extent, being a startup business two and a half years ago, and starting from an empty AWS account, and a blank screen of Python, was a real advantage, and that we’ve created now a tool that effectively solves this problem. We’re currently running many mandates across six custodians. And we can do it with three people and no stress, right. But that piece of technology and being able to trade and allocate across multiple clients with multiple accounts at multiple custodians, and then reconcile it, and then do the p&l reporting in the building, like every problem that you have, as a hedge fund is multiplied by the number of accounts that you have, instead of just one commingled vehicle. And, you know, for the most part, people aren’t willing to sign

Corey Hoffstein  33:32

up for that. reading between the lines. My presumption here is the need to build out that technology take advantage of the SMA vehicle was ultimately driven by your view as to the strategy you

Devin Anderson  33:45

wanted to implement. That’s exactly right. I didn’t do it, because I thought it would be a fun challenge. I can tell you that.

Corey Hoffstein  33:52

Yes, maybe you can you talk about the type of strategy, you originally set out why none of the other structures make sense and why that SMA was so important.

Devin Anderson  33:59

So you know, we went this entire calculus of going through all the vehicles that, you know, we kind of touched on at the first part of this podcast, we did that, right. And actually, I from my seat, at a solutions business at a bank, and Zed from his seat it at three or four different kinds of roles. You know, everything from large asset managers to hedge funds. You know, we both been looking at this problem from different angles for 15 years. And we’ve known each other that whole time he was that was actually one of my early clients that go to him. And I was approaching the end of my time in the capital release unit, and said, was looking to figure out his next thing, you know, we just said, and we started talking and went well, if we threw out all the operational constraints, we just didn’t pay attention to them for an hour. What would we build? What would we build in order to deliver for maximum capital efficiency and tax efficiency and investment efficacy? See, from an option strategy like forget about the rapper? And like, what would we want in order to be able to do that? And for all the reasons I talked about for the answer that we came to was, well, particularly when it comes to long convexity or long vol, you really got it delivered in an SMA, because you can’t take somewhat, you can’t ask someone realistically to sell down part of their portfolio in order to fund the risk mitigating strategy, like that is a non starter for most. And then even if they do that, they’re not going to do it in sufficient size, that you’re going to have, you know, an opportunity set that you really want, you’re just gonna be able to do kind of one trade. So that doesn’t work, right. So these just out of the box, the funded vehicles don’t work. And they also don’t work for tax because the switching costs are very high, you can’t, it’s tough to ask someone to switch into your, into your funded vehicle for your funding hedged equity vehicle, if you’ve got to take a big realized tax hit to switch into it, which by the way, is every family office in the United States, because since the financial crisis, they’re all sitting on a portfolio that’s at least 35% public market equities with a very low basis, that goes all the way back to the financial crisis. So the funding vehicle just didn’t work for those constraints. And then, if you want to integrate well, with tax loss harvesting, and direct indexing, which are the important trends in the retail world, well, you know, those folks are using SMS anyway, right. And we need to be able to interact with that. In fact, there’s some interesting but kind of complex tax efficiencies between derivative strategies and tax loss that you can flush out if you’re both running it as an SMA strategy. So in our view, really the only way to tick all the boxes on the investment side and really deliver the full power of derivatives, which are an unfunded instrument is to not put them through a funded intermediation, right. If you want to give someone the full power of the unfunded thing, you’ve got to let it be unfunded for them. Right, rather than wrapping it up in a funded vehicle for your own convenience. So then we just said, Okay, well, if we’re going to do that, what’s the technology stack that we need, in order to be able to do it at scale, and operate it many custodians with many accounts and many mandates. And so we, we built the technology infrastructure to be able to do it. And we’re really proud of it combination of Zeds accumulated investment experience and my accumulated technology experience and how it’s been working for the last 18 months, we’ve done, I don’t know, something like 17,000 trades or something through this thing that’s working,

Corey Hoffstein  37:34

you somewhat set it there explicitly, or at least alluded to it there. But you said it explicitly. In our pre call in preparing for this episode, you said you shouldn’t have to fund an unfunded a strategy. And sort of reading between the lines here, it sounds to me right, again, when you are ingesting an investor’s securities and using them as collateral for your derivatives overlay. I mean, ultimately, this is a question of margin, which to me introduces the risk of path dependency, one of the things I always say is that risk can’t be destroyed, only transformed. When we go from a funded structure where an investor has to explicitly sell down their Beta and put it in a pooled vehicle. They’re not necessarily taking any of that margin or collateral risk. But they are explicitly running down that data, versus I think, in what you’re talking about, they’re able to retain the beta, they don’t have to make that trade off. They don’t have to consider the tax implications of making that trade. But there is potentially some inherent path dependency that gets introduced through a potential margin call at some point. So hoping maybe you could talk to me about these trade offs, and maybe why you see it not really as a trade off that the risk isn’t there.

Devin Anderson  38:48

So it really comes down to strategy. So we actually do more than risk mitigating strategies. We have some other beta replicating strategies and some other things that we do. And this issue is specific to the strategy. So the concern that you’re highlighting is that something goes wrong and a strategy that results in a margin call that has to be met by liquidating other things in your account? Right, well, long convexity strategy, where risk mitigating strategies are stress positive, right, meaning that as things get hairy in the market, they should be adding mark to market value not taking mark to market value away. So as a general rule, in the risk mitigating space and an SMA, I don’t really think there’s much concern here, because the losses of the risk mitigating strategy should be at times when the rest of the portfolio is performing. And when the rest of the portfolio is not performing is when the risk mitigating strategy is supposed to be providing a convex benefit. So I don’t think that there’s the margin induced path dependency with respect to a long volatility strategy. However, with respect to strategies that have lots of short or have potential short option exposure to them, yes. It’s a concern, right? So if you’re going to hire an SMA manager, any SMA manager, you need to be real clear about what the risk limits are, and what the like kind of what the shock scenarios are. We’re very explicit about what we call guardrails. For any strategy, we have a list of things that is denominated in risk, you have to have a minimum of this much more exposure and a maximum of this much more exposure, and a minimum and a maximum amount of convexity. And then there’s some scenario stuff too, right? So you’ve got to have those limits in place to help manage these situations. But even then, when it comes to short options, things can go wrong and unexpected and seemingly not always. So yeah, it’s a risk. But I think it’s very dependent on the strategy that we’re talking about. The scalability of the technology solution you’ve

Corey Hoffstein  40:50

built seems like it naturally lends itself to a high degree of potential customization for clients. And I would imagine that that would be perceived as a value add, you had in our pre call, one of the things you said to me is that you don’t refuse customization, because you’re lazy. But you didn’t tell me why you did refuse customization. So I’m curious, why will you not customize your hedging overlays for clients?

Devin Anderson  41:15

Yeah. So this is really, really important, then the answer is that there’s an investable opportunity set in the options market, just like there’s an investable opportunity set in any underlying market, or cash market for anything. And that opportunity set does not care what’s in your portfolio. It is what it is. And it results from the structural imbalances and biases in the options market. So all good options, trading has to start from biases in options prices. All too often when I hear people talk about derivative trades, particularly in the wealth space. It’s like I have some story or some view on a sector or a stock or an index. And then it’s like, well, I can do this derivative trade, and people start drawing hockey sticks, you know, hockey stick, like payoffs and including option prices. But see, the problem is that’s not enough, right? If you’re going to do an options trade, you have to have a view on two things at once, at least actually, actually, I’m going to say three things at once. You have to have a view on whatever the underlying thing is, you know, I think some sector is going to go up fine. But in order to jump from just going and buying the ETF that represents that sector exposure into an option on that ETF, you should have a view on the value of that option as well. Just because you can describe the price and payout at expiry doesn’t mean that it’s valuable, the option can be overpriced, or under priced. So really, if you’re in trade options, you need to have a view on like at least three things, the underlying itself, right? On the specific structure that you’ve chosen, right? Those are the two things I see a lot. But then the third thing that I almost never see if it’s not coming from a professional brewers manager is what’s the price of that option, right. And I don’t want to get like super bogged down in the technicals of how we manage that price, or you know how we articulate that price? Most commonly, that’s going to be expressed as implied volatility, but there are kind of many ways we could do it. It’s not the only acceptable answer. But you’ve got to have a view on the value of the thing at the level of the derivatives, right? Well, so where does that value comes from? It comes from in derivatives markets, mostly flows. So whether it’s people selling options for yield, or certain actors that have to buy downside protection for statutory reasons, like insurance companies, or whether it’s coming from structured product re hedging, those things all have impacts on derivative prices, and we can take those, and jumping off from there, we can build product from that. So in order to really have an option strategy, you’ve got to have a view on direction, possibly relative value of all funds are kind of a separate matter, we could put that aside and get you know, options in in the wealth and family office space. For small institutions, you gotta have a view on direction. And you’ve got to have a view on the value of the thing that you’re buying. Alright. So the view on the options are kind of the biases and the options. That doesn’t change just because you have a portfolio that looks more like Russell 2000 than it does s&p Unfortunately. So we get asked all the time, can you take your strategy that you use in the s&p and then just run it for me on the Russell? And the answer is no, because the market for Russell and NASDAQ options is a completely different dynamic than the s&p there’s almost no meaningful structure product issue inside. There’s almost no meaningful insurance activity and those are pension activity. And those indices like the biases that are present in the s&p are completely different and most product Right, or we’ll get asked, can you take your sector exposure strategy and X sector and move it from? Can you do that in an energy instead of technology? And we’re like, no, because, again, the market dynamics are completely different. So now, that’s not to say that you can’t customize size, you can actually do quite a bit by sizing. And in fact, taking one well expressed in one managed product, like as we do, and then allowing people to size at different levels relative to the assets that they own, and change those sizes, because we have the technology to take the size changes easily, that we can actually accomplish a lot by sizing Well, so what I’m trying to say is that the investment opportunity, and the returns are driven from the value of on the option surface. And that’s not going to have anything to do what’s in within your underlying portfolio, what we can help you do is say, do the things that you own? Do they look like what we do enough that we’re not introducing a terrible amount of basis by using an s&p based strategy? And we tell people, if there’s I mean, we probably turn a couple of people weigh a month, let’s say, but you know, I really like the shape of the risk that you deliver. But my portfolio is 25 Microcapsule. Sorry, that doesn’t work at all. So could we come up with, you know, we get asked, you know, can you come up with a strategy that can give me what I want? And our answer is possibly for a minimum size. And if there is actually a market bias in the options that you’re asking us to trade that we can access, right, because if we aren’t starting from that imbalance or that bias, then I’m not sure where the value is coming from. If you’re trading

Corey Hoffstein  46:48

an identical strategy across, I think you mentioned six different custodians, it strikes me that you might run a risk where as you start to execute that strategy, you’re showing your hand, and creating worse execution with every custodian that you go and execute with, particularly during periods of acute market stress, where a given trade might drive prices further than the less stressful period. And I understand that a random rotation solves this problem from a fiduciary perspective. But that seems like little consolation to me for the client accounts that are at the sixth custodian who might achieve, you know, a worse convexity profile during a crisis, because they were the last to execute. Can you talk a little bit about how you think about managing that risk?

Devin Anderson  47:35

Yeah, I mean, this, this is a challenge for any SMA strategy, not just ours, but it comes down to the liquidity of the thing that you’re trading. So now, s&p options, we do have a randomized custodial execution. So essentially, the way it works is we, we have a master account, a block account at each custodian that requires us to execute via captive execution. And we traded within that blocked account, we allocated to all of our accounts, the order at which we trade each of those block accounts, we randomize as part of our own best execution policy. But when we’re talking about liquidity of s&p options, and in fact, almost all of our strategies, it just ends up not being that relevant in context of the depth of the s&p. And when we look, our experience, actually, is that more often than not, like we end up trading it at the same price across all those custodians, or within a tech almost all of the time, not each and every time. And certainly when things are moving fast, things are moving fast. But because of the technology infrastructure that we have in place, like we can communicate and get orders out quickly, in a sequence. And it’s not as if, you know, one has to be executed completely before the next like, we can execute in multiple places. But the other thing is, it’s also all going out in s&p options, which has enough depth that it’s just not that big of a concern. I think, you know, this is clearly something that if we were asked to run a strategy on, you know, a basket of four letter single stocks, and we thought it was a big enough opportunity, and there was a dislocation that we could lean on. Like, we’d have to think really hard about scaling that across custodians, but any s&p It’s not something I’m particularly worried

Corey Hoffstein  49:22

about. Is that true for the particular options you trade in the s&p Like, would that still be true if you were trading one Delta options as an example? Or is the depth there just because it’s the s&p and it can be hedged so easily?

Devin Anderson  49:35

s&p options are not universally liquid, the ones that we are trading both in terms of their moneyness as well as their tenor. It’s not a concern. But like, like, Could I come up with some s&p options that would be difficult to trade across six custodians? Sure, right. But those options wouldn’t be particularly useful to us on a risk mitigating strategy.

Corey Hoffstein  49:55

So in the past, I’ve heard you explain options as having really two major can Next, the levers, one with respect to implied volatility and one with respect to spot. And I know that you focus pretty much exclusively on the latter. Why?

Devin Anderson  50:11

Okay, so options are convex with respect to many things. The most two important are as the market level itself as the spot market moves around, and then as the implied volatility changes, and of course, those exposures are dynamic, and how close to the money the options are. So, when the options are exactly at the money, whatever, technically, they’re after money forward, all those risks are the greatest. So when you bite out of the money option, as the market goes down, both your exposure with respect to spot and your exposure with respect to all are getting larger. So the question is, which one of these are you gonna pull on to generate value in your strategy, and the just absolute conclusive fact of equity index options since the financial crisis is that implied volatility has not performed outside of some very, very small window. So, you know, after the financial crisis in 2011, you have the European sovereign debt crisis, vol did perform there. But then after that, there have been spikes, but they would have been very, very hard to monetize, right? The COVID is such an excellent example. It’s easy to look at the chart now and go, Whoa, I could have made a lot of money, if I own some options in January and, and sold them on this day that I pick, right. But when you’re standing in the middle of it, those monetization decisions are very, very hard. And it’s very easy to mess up. Right? People try to deal with this by setting up rules like, you know, for every x shift, I’m going to sell X percent of my exposure, like, that’s a professional way to do it, and I get it. But monetizing that stuff is really challenging, and particularly as the windows get shorter. Now, I think there’s good structural reasons why that dynamic has persisted since the financial crisis, that it’s a combination of we’ve had very accommodative monetary policy, but much more importantly, the regulatory regime has changed the landscape of people that can take and warehouse risk has changed a lot. You know, it used to be when I started at the bank, like, there was no CCAR on the Fed, there was no basil, there was no Dodd Frank, like, there was no one sending us a spreadsheet of balance sheet charges, I had started, none of that stuff existed, right. So fast forward to 2020. Right. And now, the risk limits are much different. There’s a lot more stress testing the entire market knows about and as paying attention to the stress test. So the landscape for the insurance guys has changed a lot too. So the need essentially, or the ability for vol, to expand a lot in these downturns we just think is a lot less, because you’re starting from there’s less marginal actors that have to run out and quickly cover risk on even a Down 20% Move. Right? So a lot of this risk has just been regulated out to different players. And and I’m not sure that that’s a bad thing. You know, you said before, you can’t destroy risk, you only transferred I mean, the way that derivatives, at the end of the day are a risk transfer tool that should be used to spread risk from someone that doesn’t want it to someone who’s willing to bear it for a fair price. So to some extent, the fact that we haven’t had major vol expansion in the last decade plus is a sign I think that that process is probably healthier than it was before him. But it doesn’t help you. If you’re running a risk mitigating strategy, and you’re trying to access that as a lever of value. What does work and what has worked is convexity with respect to spot worked last year, and as long as the market itself is volatile, it will continue to work low realize volatility solves are possible, though less likely. But the implication for the manager again, is a lot more rebalancing. It’s a much more active strategy to run a gamma strategy or convexity with respect to stock strategy requires you to trade more, have more trading infrastructure, and put stress on all the stuff that we’ve been talking about as you add more trades to an SMA platform. That’s that’s allocating across many accounts with many custodians. So you have to use technology to fix it. But again, this is another implication of how you know your operational environment and the way that you deliver the product has an important feedback loop into the investment opportunity set and the investment efficacy that the manager is able to deliver. So we think that based on both the supply and demand and behavior of implied volatility, really since the financial crisis, and combined with a different regulatory environment Do we think convexity with respect to spot is the better lever of value for now? Like, could that change? Right? If we went through a big deregulation cycle and a slightly different monetary policy regime? Could that change short? And you know, we’ll have to adapt if it does. But for now, we think this is the way to go.

Corey Hoffstein  55:16

So if your view is that convexity with respect to spot is the lever you want to pull on, and I’ll maybe lead you into saying something you wouldn’t say, which is you maybe you don’t want any Vega exposure, you want to minimize that Vega? Why bother trading options at all? Why not just delta replicate the options using something like futures overlay on a client account and avoid a tremendous amount of headache?

Devin Anderson  55:43

Yeah, this is a great question. And in fact, there are people out there that offer answer that I get asked by clients that I’ve known, you know, like, hey, Devin, what he disguises offering me a replication strategy. Can you talk to me about what the risks of that are? It is a great question. So first of all, let’s just talk about what kind of options are theoretically and the replication because this gets to the heart of that strategy. And I think that just kind of an interesting conversation. Because if you can, if you can get your mind around this, I think this is a an important way of thinking about options. So all derivative pricing is actually not just equity options, kind of any derivative of fundamental bedrock of, of all derivative pricing is this notion of replication, that the price of any derivative should be the cost of going out and buying some replicating portfolio. So we can think about is a very simple example of that. If you wanted to replicate a future, okay, a long futures position, you could borrow money, right, that has a cost, you can go out and buy some stock. And then you could sell that future. And then when we got to expiry deliver your long stock against that short futures position, and you’ve essentially perfectly replicated if there was a difference between the price that you paid to borrow and buy the stocks and sell that future, then there would be an arbitrage. Right. So this is what we mean by arbitrage repricing or replication. So the question you’re asking me basically says, Why actually go out and buy the options? Why not just go out and trade the replication of those options? And I think your question was slightly motivated about from Vegas, right? Well, actually, I want to talk about the replication specifically. But to directly answer the kind of the first question, it still has a Vega exposure, right? When I calculate my delta, or the amount of hedge ratio that I would need to train, I’m going to have to make a volatility assumption. So actually, there is in fact, evading exposure, even in that replication. But But importantly, what’s the difference between this replication strategy and actually going and buying options? Like Why does anybody bother with this? So starting from this notion of replication, the price of all these options that you see quoted today, you can literally interpret it as the cost of a trading strategy, replicating that option between now and expiry. So if I were to go out and follow the Black Scholes replication strategy, and trade the underlying and dynamically rep, which says I can dynamically, I can create the right can replicate the price of the derivative by trading the underlying by delta hedging it and updating that delta hedge continuously in the model, then that’s going to have a cost, I’m going to lose money as I do that, and that should be the price of the option. Well, the thing is that as you follow that process, the replication assumes some things that it turns out are kind of wildly inaccurate about real markets. So the most important assumptions of the Black Scholes dynamic replication is, first that you can trade continuously with perfect liquidity, meaning I can trade 24 hours a day, at all times, in any size that I need. And it also kind of implicitly to that assumption, assumes what you know, what we say is the slow arrival of new information. Neither one of those things are true in real life, okay. I learned the set of assumptions in a business school setting in a derivatives class. And you’re like, Okay, I know how to hedge a call option. I promise you, you’re going to be rethinking everything that you know, at 159 on fed announcement day, if you’re short, a bunch of options that are close to the money, right? It’s definitionally, not the slow arrival of new information and the ability to trade continuously. In fact, it’s the exact opposite of those things. So the replication that you’re proposing that I would do is fundamentally flawed kind of from the outset. You can’t actually do the replication with a lot of precision. To get the strategy, that’s why the option contract itself is useful. That’s why it has convexity. Right, because when that replication, there’s value in the contract that is captured, that is not captured by this replication that I’m talking about. So actually, now there are times we’re doing this replication would be cheaper than going out and buying options with the same result. And those would be the times when the market actually behaves. So linearly, in line with the assumptions that would work. So like imagine a market where you are replicating a put option, and the market goes down 50 basis points, or 25 basis points every day, between the day you started and expiry. Well, that’s going to look and feel a lot like the model assumptions you, you can update your delta hedge daily or maybe twice a day, and without a lot of disruption or gaps. And you’re gonna get a result that would have been very close to the plain vanilla option, but throw a 2% gap overnight move because some news came out of Europe, where you weren’t able to Delta hedge continuously. And now the replication has lost value relative to the contract itself. So it’s kind of like a long and maybe a little wonky answer. But replication strategies are interesting, because you can avoid maybe paying the volatility risk premium, you can maybe get your exposure a little cheaper. But it’s going to subject you to all risk in all of these scenarios where the replication would underperform the actual contract, which results from the difference between the assumptions that the models is making, because it has to and actual life mortgage.

Corey Hoffstein  1:01:35

So I tried to make it a policy to not annoy my guests. And I know that this next question is going to annoy you. But I think it’s going to be a fun one. And I do want to end this on a bit of a spicier note. This is a hot button topic for you. There is a lot of hand wringing nowadays about the end of quarter trades of a very large option based mutual funds strategy. And an argument that the rolling of their deltas is ultimately influencing the movement of underlying markets. And you have a strong view that this is a wildly misguided notion. So what are all these pundits missing? Okay, so,

Devin Anderson  1:02:17

I want to first differentiate, you know, before I was talking about structural dislocations and option prices, flows and options, markets can buy us option market prices do without a doubt, we’ve built a business around it. You’re asking a slightly different question. You’re saying Can the rebalancing flow of some commingled vehicles like mutual funds or even the hedging activity of dealers? Right, you know, hedging their zero to many day to expiry options, right? Can the hedging activity of option dealers, the hedging activity, the results from rebalancing the exposure in your mutual fund candles things affect the underlying level of the s&p market? So we’re not talking about the price of options anymore? We’re now talking about can these things affect the level of the market? And the reality is we don’t see any evidence for that. And the reason is, is many fold actually, and it depends on what we’re talking about. In the case of hedged equity mutual fund flows, dislocating and pushing around the underlying s&p, what I never hear, and those conversations is a sophisticated understanding of how those option dealers have different ways to manage their execution risk. So this is like a long topic. But like, I worked on a flow dealing desk for a long time, I’m an expert in this topic. There are many techniques that you can use to effectively spread out your execution risk. There are specific exchange exemptions that you can access. And like this is like super wonky execution stuff that you probably don’t want to get into. But there are both exchange exemptions, as well as an over the counter market that you can use to spread your execution when it’s large out over such sufficient time that the market impact is so diffuse, that it’s not going to matter. So like I hear these numbers, like somebody has 12 billion to buy or sell on the quarter, and then the market never seems to freak out. Right? It’s because the people doing this stuff aren’t dumb. They’re professional option risk managers, and they’re using techniques and working with their clients to execute that market exposure in a way that isn’t going to have an impact. You know, I can promise you like they don’t just call up the desk and be like making a risk market on 12 billion dolt doesn’t work like that. Right. When it comes to the dealer hedging in the zero DTE space, the thing that gets missed is that option market makers, particularly sophisticated electronic option market makers don’t just like have to hedge nonlinear option risk with linear things. Right? If you if I’m short some one day or same day, at the money option, I can transform that risk into something that’s kind of scary into something that is not scary at all, and in fact pretty linear by turning that one option into a portfolio of options, right? Which guess what, if you’re an electronic market maker, you have exactly the infrastructure in place to do that, right? You get lifted on the high touch desk, right? And now Now you’ve got a risk. Well, now we start offering all the options around it, or possibly, you know, things a couple days from expiry. And we can transform that risk into something that is far more manageable. So it’s not as if you just like trade these products in isolation, and then delta hedge them and say, You know, Jesus take the wheel, like, that’s not professional risk management, nobody does. So, you know, there are both ways to work with clients who have big orders to diffuse that impact over time, as well as ways to transform your risk essentially taking, you know, one strike and turning it into many strikes into a portfolio that smooths those exposures out. And between combining those techniques. That’s what option market makers do, they get paid a very small edge to facilitate those trades, and transform those risks into something that they can manage either themselves or by spreading that risk off to someone else that actually wants that risk. So I don’t really ever hear people talking about the tight edge exemption, or even alluding to its existence in this conversation. And I don’t ever hear people talking about professional risk management and how how you can take scary risk and make it non scary by turning it into a portfolio of things. But that’s actually what’s going on.

Corey Hoffstein  1:07:03

Last question of the episode for you, Devin. It’s the same question. I’m asking all my guests this season, which is that I had you pick a tarot card that would inform the design of the cover of your episode, and you picked the ace of pentacles. And I was hoping you could explain why that particular card spoke to you.

Devin Anderson  1:07:21

Sure. So first of all, I didn’t realize when I agreed to this that I was gonna have to read because I can’t like, maybe me, I can’t just like pick one. Okay, I had to read all 72 of them. So first of all, I didn’t know that there was 72 tarot cards, which is kind of amazing. And they’re organized into suits that has meaning at both the suit level and the car loans. So now I know a little bit about tarot cards, which actually might have been useful in the conversation of that last question. So I chose the ace of pentacles, kind of for a host of reasons. First of all, that card specifically represents opportunity and prosperity and new venture, which I feel like kind of speaks to speaks to our firm as a young firm. But also, you know, we spend a lot of time talking about how risk mitigating strategies enable reinvestment and create a lot of opportunity when they’re used well. So, you know, that kind of spoke to me on that level. But more broadly, that whole suit of tarot cards deals with investments in these themes of abundance, and reliability, and diligence and hard work, that I kind of feel like, are things that are germane to our strategy, and kind of how’s that and I view, our role and the service that we’re providing to serve our clients. There was this quote that I lifted out of the out of the thing it says, watering the seed has the potential to be very rewarding for anything that is grown on this energy is meant to be stable, secure, and give good yield. I mean, what could sounds awesome. I mean, I don’t love the yellow part. That usually means selling options, but it’s a tarot card. So we’re gonna throw that piece of the context out. And lastly, I figured out that that suit of tarot cards is aligned with my astrological science. That can’t be a coincidence, right?

Corey Hoffstein  1:09:08

Definitely not it was meant to be. Well, Devin, thank you so much for joining me. Thank you for taking that question. So seriously, I appreciate it.

Devin Anderson  1:09:17

I learned some stuff I actually learned. I mean, I didn’t learn how they work at all. I just read the faces of all all of them. But it was interesting.

Corey Hoffstein  1:09:23

And I appreciate you sharing all the insights you have on our strategy and structure need to align. It’s been a fascinating conversation.

Devin Anderson  1:09:31

Thanks, Cory. Be well. Thanks for having us.