Benn Eifert, Founder and CIO, QVR Advisors

[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. The clearing price of optionality in the market is impacted by a myriad of factors. To be sure, the economy and corporate profit cycle, the stance of monetary policy, and geopolitical risk all matter.

[00:00:31] Flows in the derivatives markets are also of consequence as they impact the environment for supply and demand. And in this context, it was excellent to welcome Ben Eifert, Founder and Managing Partner of QVR Advisors, back to the Alpha Exchange. Ben brings a data-driven lens to today's complex volatility markets, and in this conversation, he discusses the unintended consequences of crowded risk-managed option strategies such as buffered ETFs and overriding.

[00:01:00] We explore how structural flows have drained the vol risk premium, especially from the front end of the curve, where the flow has especially been one-way, leading to substantial optionality being sold into the marketplace. Ben states that since 2012, the VRP has largely vanished, leaving the returns to owning short-dated straddles actually positive since then.

[00:01:22] For risk-managed ETFs, the implications are unfavorable, as many of these strategies often reduce beta without providing meaningful downside protection, results that are posted on the QVR website. From Ben's perspective, even for a large and liquid options complex like the S&P 500, the sheer volume of capital chasing the same trade is distorting expected returns.

[00:01:46] We finish the conversation by exploring the evolution of QVR's trade implementation and risk management practices. Here, Ben shares that the listed options market has become a focal point relative to years ago when OTC products transacted bilaterally with large banks were of greater importance. The approach now leans into technology and seeking to exit and enter trades more passively with a market-making approach.

[00:02:12] I hope you enjoy this episode of the Alpha Exchange, my conversation with Ben Eifert. My guest today on the Alpha Exchange is Ben Eifert. He is the founder and managing partner of QVR Advisors, a firm out on the West Coast doing all kinds of interesting things in the vol space. Ben, it is a pleasure to welcome you back to the Alpha Exchange. This is your third visit. Dean, it's great to see you again, man. It's been too long. Thanks for having me.

[00:02:39] I can say another three-time guest on the Alpha Exchange is Vinir Bonsali. So perhaps you have to have a PhD to get asked back three times. But no, I'm looking forward to this conversation. It's been a while since we spoke. The VIX got to 50. Rare precedent for that to happen. So there's been certainly a lot of action in the vol space. And as always, markets are reacting to news flow.

[00:03:04] They're reacting to trades that live and breathe in the markets, to the economy. And then market structure is always changing as well. So we'll have a bunch to talk about here. I wanted to start just by soliciting some of your thoughts on one of your research papers. It's been a topic of conversation for me on this podcast, which is just the risk-managed equity structures that are out there. They could be collars, split-spread collars, overwriting.

[00:03:34] And I'll just set the table before. I'd love for you just to explore your own findings. But I had Dan Villadon, who heads Portfolio Solutions at AQR, on the podcast recently. They've done a couple of pieces on buffered ETFs, effectively saying that these are 60 beta products that are underperforming a 60-40 portfolio. I thought the results were pretty disappointing for trying to advocate for these strategies.

[00:04:03] And what they find is that both on a return basis and on a minimization of drawdown basis, which was really surprising to me, they just, by and large, haven't done all that well. So you got a piece that you've published on your site, done with some of your partners on, I think you had more of a 50-50 approach. Big picture, give us what you found in effectively sizing these structures up against some portfolio that's basically of equivalent risk.

[00:04:34] So I'm quite sympathetic to their view. And again, as you said, there's a wide variety of different types of trades and structures here. But I'll speak a little bit maybe to buffer ETFs, and I'll speak a little bit to call overwriting. In buffer ETF land, they're exactly right. So the first order, when you have a put spread caller, you have to kind of keep in mind, it's not a really what I would call a hedge. It's not a long convexity trade. It's more of just something that to first order, what it does is it reduces your exposure. It just takes sort of your 100 beta equities down to 60 beta.

[00:05:03] And then there's some noise around that for like, where do the strikes land and all that kind of stuff. And then you have obviously some transaction costs, you have some commissions that you're paying. Over time on average in general, it significantly underperforms 60-40. I can be a little bit bearish right now on 60-40 because of what's going to happen to sort of fixed income with deficits and all that. That's tactical, and I may or may not be right about that, certainly over long periods of time. Fixed income has tended to perform somewhat like a hedge to equities, at least over the last 20 or 25 years.

[00:05:32] And you've gotten a lot more efficiency out of, instead of doing that put spread caller, taking down your equity exposure and putting in the bonds. And I think that's the right way to think about that on average. You may have a tactical view based on pricing of options and based on what you think about fixed income that might lead you to do that. But I think the idea of long-term, systematic equity plus put spread caller just doesn't actually make a lot of sense. When you get into thinking about call writing, the issue here is, as with anything in derivatives markets, where does risk premium come from?

[00:06:02] Call writing, the idea conceptually, right, is you're harvesting this volatility risk premium, and that's paying for this position. And there's a little bit of maybe path diversification. You can try to argue that if you have like a range of bound market, maybe you're going to outperform equities because you're collecting some premiums. But the problem is, inherently, a lot of the logic used to talk about call writing doesn't really have to do with how big is the volatility risk premium, when actually the performance of call writing is entirely driven by that over long periods of time.

[00:06:28] And if you look at flow in, say, one month S&P options, there are 95% to sell by clients in strategies like this. No strategy will ever work in derivatives if you're part of 95% of people who are all doing the same thing, because it means that whatever risk premium used to be there is not going to be there anymore. And your backtest is going to have nothing to do with your forward-looking returns. And that's exactly kind of what's happened in your typical benchmark-oriented, systematic call-right, put-right type of strategies.

[00:06:56] So if you break up the sample pre-2012, post-2012, it doesn't matter exactly where you put that benchmark. There kind of was a big regime shift around then when pension fund consultants started writing white papers about call writing and started pitching them to their boards and started getting the giant pension funds of the world, starting to allocate meaningful capital. And now there's just absolutely massive flow selling exactly the same thing and totally a price in sense of the way with no buyers on the other side. And what that means is that there's literally no volatility risk premium anymore.

[00:07:23] Backtest selling straddles systematically one month since 2012 to now, you lose money doing that. You make money buying straddles just outright. That's crazy. And that exists because the kind of pension funds and clients that got put into these types of strategies starting 10 or 15 years ago, it's a line item on a very long portfolio once a year. They kind of look at it. It doesn't blow up. Call writing is not like a risky ball strategy where it's going to cause catastrophic loss. You just underperform your expectations consistently.

[00:07:51] Money is very sticky and these strategies just kind of stays around. And I don't think it's going anywhere anytime soon. And then when you actually take that back to look at a lot of the buffer ETFs, another reason for underperformance is they're selling those same upside calls that are massively oversold by a huge community of overrider. At the end of the day, in derivatives, lesson one is where are there dislocations in markets that come from big one-sided flows that are persistent? And if you're thinking of doing the same thing as those flows, it's probably not going to work nearly as well as you expect it to.

[00:08:21] So let's go through some of what you said there. So the first thing, an active thing for me to think about is the time variation of risk premium in general, of even things like the VRP. These are not static. And of course, you know, the VRP chugs along at maybe three, four or five vols. Then suddenly you over-realize by 20 and then you under-realize by 15. And it kind of gets back to four or five for a period of time.

[00:08:47] But what you said was around 2012, supply started to come into the market such that the profitability of these strategies changed. Now, I'm thinking back. So you had the GFC. Obviously, you'll know better than just about anyone. That was the impetus for a lot of folks revisiting this concept of crash risk and having something. And then you had the flash crash of 2010 and the sovereign crisis of 2011.

[00:09:16] And so I want to say by early 2012, there was kind of a peak in the interest in doing these types of trades of, at least in my mind, of going the other way, of buying protection. When you look at your back tests of just a simple strategy of robotically owning straddles, maybe bucketing it by timeframe, what are you seeing? You're seeing it just slowly deteriorate or actually get better, I guess, on the long side.

[00:09:45] But by harvesting it, it's just getting worse and worse. And you think that's from excess supply? I would consider volatility risk premium. That's short-dated gamma. It's not six-month, nine-month options. That has more to do with vega and term risk premium and stuff. VRP is one month or shorter, ball swap, structure at every one. That risk premium went to zero in 2012 and has been zero ever since on average, to your point with time variation.

[00:10:09] The year or two after the COVID crash, it went back to positive because obviously people got really blown out on short gamma-type positioning. But then it's come back in and compressed back to zero relatively quickly. Because again, to your point about interest in tail hedging, what do tail hedgers buy? They don't buy one month 25 delta calls. They don't even buy one month 25 delta puts. They buy one month very far out of the money puts. But actually, more often, they buy six-month 20 delta puts or something, right?

[00:10:35] Because your typical portfolio manager, an equity portfolio manager that's got a 130-30 type of setup and they get bearish over the medium term. They get worried about some stuff. Sometimes they have a very tactical view about an event or a central bank meeting or something. And then they might buy something short-dated. But most of the time, it's, look, I just want to have a hedge in the book. I don't have a really strong time view. I don't want to be rolling this thing constantly. I'm just going to go buy three months or I'm going to go buy six months or something. I'm going to buy 10% out of the money. Those are the typical durations of trade.

[00:11:03] So when you just think about the flow that happens in an equity index, short-dated stuff is only sold. Long-dated stuff is mostly sold via structured products. And then most of the net buying flows in options happen in kind of those medium tenor buckets. Three-month, six-month, nine-month kind of ranges. That's where most of the bigger portfolio hedging is. That's where most of the bigger directional market buying longer term, I'm going to buy some call spreads to have some exposure into the end of the year kind of stuff is. And as a result, you get a, most of the time in the natural state of affairs,

[00:11:33] you get a volatility term structure that reflects that. So you get a volatilist structure that's really low and really steep in the front and then goes pretty flat out to the back more than the natural concavity. And that's just completely flow-driven. If you compare what that term structure looks like to, say, pre-GFC or in that 2010-11-12 timeframe, in those environments, you have sometimes higher vol-term structures, but they were much flatter that didn't have that crazy steepness in the front that comes from the entire world being sellers of short-dated vol.

[00:12:01] Anytime there's a big flow, you can always see it at price for obvious reasons. And it creates those kind of dislocations and distortions. And so in the old days, in a quiet market, you'd be selling short-dated vol at 14 and realizing 10 or something. Now you sell it at 10 and realized, then there's no VRP left on average. The second time you came on the podcast was really in the immediate aftermath of the COVID crash. And as, of course, we've discussed many times, there was real destruction of capital in the equity derivative space specifically.

[00:12:31] If you held a distressed bond, of course, your mark-to-market loss was pretty scary for a short period of time. But if you held, it fully came back. You just had to hold on. I'm not saying it was easy. Equity derivative strategies, correlation swaps, and things like that, this just doesn't work that way. The capital is just gone. In the aftermath of the COVID crash, call it the second half of 2020, certainly through 2021, there really was a kind of reemergence of the vol risk premium.

[00:13:00] Skew was super steep. And I'd love for you to give us a timeline here. Obviously, that's changed since then quite a bit. 2022, even as the market fell, was a really difficult year to hold hedges. A big part of what you're saying is the capital that's been raised in these various products, they could be mutual funds, they could be ETFs. There's just so much new money going one way, selling vol. So take us through kind of the last five years of this VRP

[00:13:29] and how it's interacted with all the capital that's been raised. Just prior to 2020, you very much had this configuration where both there was a tremendous amount of what I'm describing, these big overriding flows that are price insensitive and not risky, not blow up kinds of things. But there was also a tremendous amount of very scary short tails positioning and people doing totally wild and crazy stuff, selling caps on variants, capped on cap, doing skew locks, doing stuff that was absolutely guaranteed to blow a massive crater in the universe when something like this happened.

[00:13:59] When the pandemic hit, that completely blew out all of the tail stuff in a massive way. Repriced tail risk and skew and convexity massively, massively higher. Also, of course, made short dated vol go much, much higher because we were realizing, you know, 100 plus vol in the S&P at the time blew out a lot of acquisition. And then we had a medium speed vol compresses relatively fast, but as vol kind of fell and fell and fell from there, if you sold vol at exactly the right time, that generally worked out. We're not directional vol people.

[00:14:29] In regards of people will ask about trying to time vol. Usually it's tough to pick the top and to sell the spike because most of the time it works, but the times that it doesn't makes up for that really blows you out. The thing that works a little bit better is waiting until the event has really passed and then riding that long tail of risk premium that persists after that once the danger is cleared a little bit. So then vol had a long way to fall back from VIX 100 as the market was ripping back. You got into 2021

[00:14:55] where really you had this resurgence throughout all this. Retail had been growing, getting more active, trading more aggressively. And then you have in 2021 emergence of some of the crazier things in retail like GME and that whole dynamic. You had SoftBank trading like levered retail traders coming out and buying, you know, billions of dollars of notional of DGN tech stocks and stuff and really creating some upside volatility through that whole process. By late 2021, you saw really the vol term structure

[00:15:24] starting to come down a lot, starting to see a lot more normalization. 2022, to your point, was interesting because we sold off quite a bit peak to trough and equities in a 20 plus percent in the S&P, but never in a volatile way. 2022 was a world where people were pretty hedged, people were pretty bearish, positioning was pretty light. And you really didn't have any crashy type of dynamics with 5%, 10% moves in the S&P. You had a bunch of 1% or 2% down base, especially when positioning is light and people are well hedged.

[00:15:54] You're just not going to be able to get a big volatility response to that. Volatility really tried to go higher. I mean, I think we got VIX into the 30s a little bit at a few points, but in some sense, that was kind of overpriced relative to what was happening in Realizable. And so those moves kind of got sold. You had people who were doing tail-y type of hedges that really didn't work at all because you didn't have any kind of tail move. What you needed was just to be underweight risk assets or to be short deltas in order to make that market work. We were short delta and short volatility in one of our core strategies

[00:16:24] throughout that whole move, and that worked really well. The vol response to a given sell-off depends a lot, obviously, on the path, and it depends a lot on positioning. Even if you just think about December 2018, the idea that markets are down 20% in a month, vol is up a little, seems totally crazy, but there are configurations of positioning and paths for the market to take that can totally do that. And so if you're trying to structure some portfolio head, you really have to think about how robust it is to different ways in which that painful scenario can happen for you because the market

[00:16:53] likes to kind of find the worst thing for your book and do that to you. Let's just talk a little bit about some of the structures that go up. So obviously, a very common one is put spread collar. The way I think about it is you bought a put, you sold the strangle. You're protected in the sense that you've got a defined outcome, but you are certainly short vega, short mark-to-market risk from an implied vol standpoint. How do you square those two where you don't have the true crash hedge,

[00:17:22] but something down 5%, down 20% is a fair amount of protection. Obviously, you sold off some of the upside. How do you square the defined outcomes or the boundaries relative to being short vega? How should we think about that? Almost dichotomy. With a put spread collar, when I think of the net optionality in the trade is actually relatively small. Your small short vega and small short gamma, by far the dominant exposure in that trade is just short delta, which is exactly why you get the results

[00:17:50] that a first order over time, mostly if you put a put spread collar on equity, all you're doing is just cutting your exposure on average. You're taking your one delta down to 0.6. And then there's some other small stuff that will create some noise in any particular path, but over time just averages out to not very much. And that, I think, is why most of the time, unless there's a good tactical reason for it where the skew is really steep and, you know, you really like the delta or whatever, why I think most of the time it just makes sense to cut your exposure if that's what you're looking for rather than try

[00:18:19] to do a put spread call. The other question I have just on this topic, last question is, there's a number of reasons why both you and AQR find these vehicles underperforming a reasonable benchmark. Yours is 50-50, Dan Villalon used 60-40, pretty close. And so a couple of things come to mind. One is just the size. And so I think that's really largely where you're going, which is the size of the trades or the industry itself

[00:18:48] is putting undue pressure on the clearing price. And it's just making it less efficacious for the folks that are all on one side. So that's one. I think that's where you're going to put the balance of or most of the emphasis. The other thing is just, you know, having been on the sell side for so long, trading costs are real. Bit offers are real. I always say, again, just having covered a lot of accounts, there are some folks that are very, very good at kind of extracting the last penny

[00:19:17] from the sell side and some that are less good. So those are real frictions as well. Do you think that those non-size oriented frictions, are those a part of this underperformance as well? They absolutely are. It's going to depend on the underlying, whether you're trading single loans or they're trading S&P and how efficiently you do it. But I think if you look at a QIS type of strategy that's doing put spread callers, there's going to be meaningful transaction costs embedded in that stuff. If you're looking at an ETF, especially the big one you can think of like the JP Morgan

[00:19:47] hedged equity program, that program is so big and so high visibility that it might look optically like they get filled pretty close to mid-market, but you're not taking into account the fact that everybody front ran the damn thing and the whole ball surface moved the day before. There's really meaningful trading costs in a lot of those strategies. They're not being executed the way that a professional volatility manager would execute them slowly and condescently in randomized batches at mid-market, providing liquidity and slowly working into a position. You go in, you sort of lift an offer.

[00:20:16] In some of the bigger cases, the market knows you're coming. And so those costs can be very meaningful. One more question just around this sort of modern day of markets. So we have this big growth in derivatives-oriented ETFs, and we also have this other category of ETFs, which are levered ETFs. One of my little sayings is this is not your father's ETF market. This is not spy and triple Q anymore. You've got 2X longs, 2X shorts,

[00:20:45] so many different types of assets. Sometimes these overlay strategies, whether it's the MSTUs and MSTXs on top of an already volatile MSTR, they just get very big. The day that Trump climbed down on the tariffs on April 9th, the triple Q was up 12%. The T-triple Q was up 36%, 3X. And the amount of trading volume that that T-triple Q did over those three days,

[00:21:15] I think it was 500 million shares a day. It's enormous. And so I'm just curious if you could just reflect on feedback loops. There's a lot of folks that analyze gamma. I think it's a little overdone, some of the analysis. It's very hard to pinpoint, but it's impossible to suggest that these markets are in any way similar to even 10 years ago. There's just new products, there's new exposures, how should we think about all of these almost mechanistic flows and what

[00:21:45] risks they may or may not create? There are many of these in the market and they have been growing and evolving over the last five to seven years. You pointed out several of the big ones. So obviously, triple levered and double levered and inverse ETFs all mechanically trade in the same direction of the move. I think probably the most famous example of that was XIV back in 2018 on the entire market knew that there was this massive short volatility ETF that was going to blow up from month fixed futures doubled.

[00:22:14] And so what that meant was actually if they were only up 50%, they were still probably going to blow up because everybody was going to front run the rebalancing of that ETF on the close. There would be no liquidity for it. And you know, exactly that happened in February 2018. Those flows are very important and you can model those very precisely and you know how big the rebalancing effect is going to be. So of course, the market is front running those type of effects. You mentioned gamma positioning. A lot of the modeling on that is pretty bad. You can do decent modeling on it if you try, especially now with some of the newer data sets that CBO has made available where

[00:22:43] you actually know who's buying and who's selling on exactly every trade that goes up. And you can have some sense of how, you know, dealers are positioned. That is obviously very important coming back to like the massive size of that overriding flow. Most of the time, the street and people like us are very long gamma because we're the only buyers of short dated options. Everybody's selling them and so that means in the natural state of affairs, the market's kind of trending around where it has been and where the strikes of those calls and what's at them sold. We all own them and we're going to be pushing against the market moves, the

[00:23:13] opposite of the levered ETF rebalancing. But that's very localized because it's short dated options. And so if the market's moved away from like the concentration of those strikes, the matter of fact kind of goes away and really frees up the market to move a lot more. But I think that's why you can get these regimes of volatility suppression and then some slow choppy downside and then the catalyst that can finally generate big volatile moves to the downside. It's hard to have those really big volatile moves to the downside out of thin air when so many of us have to buy a massive amount of stock on a 1% down

[00:23:42] day that comes from a lot of that overwriting and underwriting flow. This hasn't come back yet, but it eventually will. Back in 2020, you had a huge amount of crazy crash risk selling and variance swap selling and cap on variance selling and that creates that same crazy momentum into the close dynamic when the street has to re-hedge those positions. You really have a balance between all these different forces, where is spot relative to a lot of the strikes of the short day adoption selling flow versus how big is the levered ETF dynamic and versus how big are those other kind of dynamics in the market. Derivatives have become

[00:24:12] so large relative to the underlying cash market compared to like 15 years ago or 20 years ago that those kind of effects are much, much more important. When you really see those effects be massive, obviously, when markets really do start to come under stress and liquidity deteriorates, then the impact. You have a 10% down move in the S&P, the levered ETF rebalancing is massive and the liquidity to absorb that flow is very low and everybody knows it's coming. And so that's why back in 2020, you would see days where market was down 7 or 8% with 10 minutes to go and then

[00:24:42] it closes down 12 because you just have this massive forced trade that has to go through. Everybody knows it's coming through. Nobody's going to stand in its way. So 1998 is LTCM. That's swap spreads and long-dated vega. 2008 is the entire system. Maybe it's centered in mortgage mispricing, but convexity everywhere you look, people are short. 2018 is XIV. So we got three years to 2028. We got through that period of April 2nd to April 9th, which was a

[00:25:10] spectacular explosion of vol. At least by my own calcs, I'll exclude the crash of 87. Maybe I'll start in 1990, but it's really GFC and COVID that are the only comparables if you measure it over maybe a 10-day period. You had consecutive 5% down days. There's really very little precedent for that. But the market cleared with all of the ETFs you just talked about. With all of the short

[00:25:38] exposures, there were no counterparty blowups, at least none that were reported or large. The zero DTE product made it through. What does that tell you? We came out on the other side of a very big stress event and market structure feels pretty sound. Is there anything lurking that worries you that's kind of the next 2018 XIV? It's all about positioning and market structure. If you look at what was happening earlier this year and with Liberation

[00:26:06] Day, you had had a month or so before, or a little bit more than that, the deep seek thing. It wasn't all about deep seek, but you had a big 10 standard deviation move or whatever it was in relative value relationships, in equities that were the kind of things that pod shops are very exposed to. You had some relatively big losses and you had very big de-risking across a big part of the buy side. And then you had a fair amount of bearishness on top of that and underweight positioning coming into Liberation Day. You had skew was pretty steep. Market participants were pretty well hedged.

[00:26:36] All of that crazy kale risk selling from pre-COVID hasn't come back yet. Investors know better questions to ask now about are you selling variant swaps? Are you selling Vick's calls naked? It'll eventually come back. It always does, but it's going to take more time. In order to get a really big accelerated market crash and massive outsized ball spike and blowout of skew and convexity, you need people to be over levered and long. You need people to be over their skis. You need short ball positioning that's dangerous and the tails to blow up. And you didn't really have most of those things.

[00:27:06] What you had was a relatively big surprise to the market. I don't understand why it was a surprise to the market, but people really thought that Trump wasn't going to do all that stuff. The market was offsides and wrong. There was this fundamental event. Oh, wait, there's these policies that would be very harmful and it seems like we're doing them, so we're going to sell off pretty hard. It was justified. Ball moved a lot, but I think ball moved in line to what you would see for the spot move. The impressive thing really was how fast we sold off. It wasn't necessarily what happened in the derivatives market on the back of that. Everything traded very reasonably relative to

[00:27:36] the move in spot. There were some fun dislocations that opened up in ways to make money, but the Vick's in the 50s wasn't unreasonable given what was happening. Versus a world where in COVID, obviously the pandemic was a very big deal, but the market probably wouldn't have gone down nearly as much as it did and ball wouldn't have gone up nearly as much if all of that crazy tail sell wasn't there because we had to blow out all that stuff, liquidate it, hedge it with short delta, and that forced that last huge aggressive leg down. Well, let's talk about the evolution of your risk management process.

[00:28:06] So you and I have known each other for at least a decade, probably more, and I'm guessing that the way in which you think about risk has changed quite a bit. What I can observe as a starting point is that your process is considerably more underpinned by technology and electronic, almost a market-making approach to getting into and out of trades, basically being the provider of liquidity. One opening question I have for you is

[00:28:35] just walk us through some of the way in which your process for getting into and out of trades has evolved as markets have changed. Tell us a little bit about that. Think back to like 2008 or 2010, 2011. Banks were very happy to trade with aggressive relative value hedge funds in OTC, making really big markets, trading at mid-market or better than mid-market in many cases on whatever you wanted to do. They would lose lots of money trading with us and they just didn't care because they were making 100 times more money

[00:29:05] doing layup trades with pension funds and sovereigns and corporates. They wanted to be at the top of the league tables so that it was like who's the best equity derivatives desk in the world? Oh, it's Merrill. Oh, it's BNP. The volume they're doing with us translates into that business franchise value. That world changed dramatically starting 2013, 14, 15 as Dodd-Frank and Basel III really started to bite. The regulations started to get rolled out and what you had was banks just becoming much less able to take risk, more like utilities, much more tightly regulated,

[00:29:35] much less interested in losing money trading with people like us. And the size of the markets that they would make and the width of those markets and the ability to get at a good price just deteriorated. And I think you saw returns in the derivatives relative value type of space start to suffer as a result. So when we started QVR in 2017, we made the decision to just go to completely shift execution models because it wasn't really the case necessarily that overall volumes in derivatives

[00:30:04] were falling, but they were really migrating to exchange and migrating to listed markets. And we didn't even at that time have any clue how much more further that was going to go with retail trading taking off in 2019, 2020, 2021. What we've effectively done is gone through and for most of our strategies where it was possible to kind of take the similar approach, but to replicate the same kind of exposure that we used to get, say, in a volatility swap or a variance swap to replicate that and listed and to trade using a lot of technology in a way

[00:30:34] that looks where we look in the market, more like market makers where we're effectively best bid in the market for everything that we want to buy, best offer in the market for everything that we want to sell, you know, very controlled and tech intensive way for managing, you know, legging risk of different trades and everything. Rather than trading with a broker and saying done, the risk being willing to take all day to work into a big position or, you know, however much time it takes. So being passive liquidity providers, what you give up is the immediacy of here's the trade I want. Okay, done. Okay, I've got it. But the upshot is we

[00:31:03] trade at or better than the market and across, you know, wide range of products and markets. And that's pretty phenomenal. Plus, it's nice to never have to do like another novation of some correlation swap from out bank to gold and then you get it, you know, having to yell at people and stuff. So operations are very highly automated for the business. That's really, really nice. That's really been an evolution of the business model. And again, yeah, we didn't have any idea of the extent to which we were going to get this massive explosion of liquidity in listed markets with retail traders getting really excited about options and all the opportunities that came up with that.

[00:31:33] So it's been a really important business decision for us. And I think a big comparative advantage. It was helpful that we were starting a new business doing that. That's a relatively hard switch to make live with your existing business, which is complicated and you're doing all this stuff and you're going to have to make huge investments and change how you do things. It's much easier to build something new than it is to change an existing business and investment process. Most of the time when we talk about a blow up, it's typically associated with short vol. The Warren Buffett weapons

[00:32:02] of financial mass destruction. We mentioned LTCM before. What do they say about short gamma? You eat like a bird and shit like an elephant. But being on the long vol side of things can be very challenging sometimes. We mentioned to be early is to be challenged and potentially wrong. And I'm curious to sort of learn about how you think through managing losses on the long vol side of things. You own something that you like, but it's

[00:32:32] clear that there's more runway for the market in terms of low realized and then the feedback down to implied. So you're sitting on something that it's at a very low level, but it's just not realizing there's downward pressure on implied. Walk us through your thought process there around liking the position, but also having to manage the risk that you're wrong. There's a couple different parts of our business. In the core hedge fund business, we're completely non-directional market neutral all the time in every trade always. We might be long

[00:33:01] tails, but that's different than being long vol. You can often synthesize basically free long tails exposure or positive carry long tails exposure in a way that doesn't cost you, doesn't have theta bleed, maybe it's positive beta. That's different than the core long volatility exposure that's got negative beta to market. And now we do separately run a solutions business where we do tail risk catching and that's clearly directional. That's clearly long volatility designed to be thought of in an asset allocation context paired together with the

[00:33:30] risk assets that are being hedged and how you rebalance between them. And in that case, it's very explicit. The investor has kind of a budget for what they're willing to spend and lose in a normal year where markets don't really do anything or market goes up. And you have parameters around that of different kinds of paths, different kinds of exposures that limit how much you can lose in a variety of different paths. And the expectation is that you're going to be losing money over time on a standalone basis in that strategy. And that's the whole point is that that strategy is going to be making a massive

[00:33:59] amount of money when the rest of the book is under pressure and then they can liquidate that stuff, put it into risk assets at really good levels and everything. So the important thing obviously in that case is that everybody's completely aligned about the objectives of the strategy, what you're trying to do. In the absolute return stuff, there are cases where we'll have just a cheap long volatility exposure really only if it's something that has no hedge. The example I'll give you is back in 2017, 2018, banks started putting natural gas volatility selling into QIS products. Which sounds nuts

[00:34:28] because that's a relatively small market where obviously crazy things can happen. If you start putting institutional scale assets into just selling vol, what obviously happens is that implied vol goes down by 50%. Because you all of a sudden have massive amounts of price insensitive flow. In 2017, natural gas vol went to like half the level that it had ever been historically. And we said, look, we're relative value guys, so we want to buy that. There's nothing you can hedge it with because natural gas is completely idiosyncratic, weather driven. But even selling oil vol against it is very little relationship. So we just said, fine,

[00:34:58] we'll just buy some, pick our spots and pick our levels. Then it becomes all about sizing, about some sense of extreme stress tests of how much further you think it could go. You don't really know, but you're risking a certain amount of premium and you know exactly where your risk lives. Not that surprisingly, not too long later, there was a winter, there was a little bit cold and natural gas blew up and that optionsellers.com, James Cordier guy, you know, had his apology video. That's unusual for us. That really only happens in cases where you can't make it a relative value trade because there's just nothing that would really hedge this thing.

[00:35:28] Almost everything that we do in the hedge fund world is where is the dislocation? What does that mean about the relative value trade that you can do where obviously dislocations can get bigger, but you're not in a situation where it's just, hey, you're trying to buy vol, but yeah, it can go down a lot more. It's directional. How do you deal with that? I'm curious when you think about, let's just maybe stay with the hedging and solution side of things. If you're trying to think through the value proposition of vol, another Warren Buffett price is what you pay, value is what you get.

[00:35:58] 10 VIX in 2017, of course it wound up being very valuable if you got to the other side of Feb 18, but there was a lot of risk premium VRP in 2017. So low vol doesn't necessarily mean it's cheap. You have to have some maybe view on what the forward-looking uncertainties look like. I'm wondering how much of that makes its way into your process. You'd referenced tariffs before and that you were surprised the

[00:36:27] market was surprised because he telegraphed some of this stuff, maybe not the extent of it, but how much of the macro evaluation of uncertainty is part of your process. You said several things there that are all exactly correct. There's a very common misperception in the market among non-specialists that every specialist will tell you is wrong, which is that you're supposed to buy vol when it's low and sell it when it's high. A more general point actually is that markets in this stuff are

[00:36:56] reasonably efficient to first order. Anytime you have like a really first order thinking kind of view, oh, that thing is high, so you should sell it or it's low, so you should buy it. You're probably wrong. Markets aren't stupid. Vol in general actually prices reasonably well on average. If vol is really high, there's a good freaking reason for it. There's a lot of expectations that things are going to be crazy. If vol is really low, 2017 to your point, there's kind of a good reason for it. And maybe it won't last, but also by the way, vol term structures are upward sloping in the price that it's not going to last. And there might be

[00:37:26] certain things that actually are way too cheap. You have to think about that in a more nuanced way. If you do the research and you just look at what's the performance of selling one month vol based on what's the initial level of vol, there's literally no relationship between oh, I sold it at 100, I'm going to make money. I sold it at 10, I'm going to make money. Absolutely zero relationship. And that surprises a lot of people. Same thing is true for SKU, buy SKU when it's low, sell SKU when it's high. It doesn't work. You shouldn't expect it to work. That's a little too easy. Really simple first order thinking in derivatives markets is usually wrong. When we're thinking about tail hedging, to your point about the

[00:37:56] value, one exercise that it's interesting to go through, and we have a little research paper on the website, is it's very important to think about tail risk hedges in a portfolio context, obviously not in a standalone context. So in a standalone context, you should of course expect tail risk hedges to lose money over time. The world would be totally stupid if that wasn't the case. You shouldn't be able to make money over time owning an exposure that's inversely correlated with risk assets. And the reason is, by the way, when you put tail risk hedging

[00:38:23] into a portfolio of risk assets, it's going to have a different effect on the long term returns of that portfolio than just adding in the standalone returns of the tail hedge. Because you're rebalancing between the two and you're compounding, when you cut drawdowns, you actually improve long term compounding returns. There's no guarantee, it doesn't always happen, but in principle, you can actually add a tail risk hedge on a systematic basis to risk asset portfolio and get not just lower drawdowns and the higher sharp ratio, but you can actually get higher long term compound

[00:38:53] rate of growth in the portfolio if it's inefficient and not tail edge. Because what you're doing is you're cutting drawdowns of the portfolio right at the right time when everything is really cheap and then you're able to redeploy cash into risk assets at really good levels and rebalance between these two things. And that dynamic rebalancing effect has an impact on long term returns. That's really where a lot of the value proposition comes from. Dealing with people who are empowered to think at a whole portfolio level, not just like at a line items level, is really important for those kind of things.

[00:39:22] I always think of a hedge as one you want to be extremely liquid, very transparent. You want to get out of this thing at a moment's notice and then potentially redeploy into newly cheapened assets. I'd love for you to reflect on August 5th of last year. What do you think happened there? And really not the VIX complex. I mean, that was really just an afterthought of what happened in the S&P options market. What broke there? So obviously you had devaluation in Japan, but I think in the options market, really what happened,

[00:39:52] everybody remembers that day that the VIX was printing, I forgot what the number was, it was a 60 something pre-market. And what was happening is that the VIX index itself is just a very mechanical calculation looking at a bunch of S&P options. And once they find two options, as they go down into the put tail, once they find two nickel bit options in a row, then they cut off the calculation. And what you had that morning, there was various stuff going on, but what ended up happening was those put markets all went crazy

[00:40:21] wide, all the way down to like the 400 strike puts. The bid and ask were really wide. So all of a sudden, this huge fat tail where the mid-market levels were actually like really high got included in the VIX calculation. Totally an artificial thing. It's not like VIX is a variance swap calculation. You couldn't have sold variance at 65 or whatever, right? It was 25. That blew the VIX up. And then there's lots of VIX strategies that look at VIX spot versus the front line of VIX future, which is generally sensible to do, but very much not in that context,

[00:40:50] triggering risk mitigation and buying a VIX futures and buying short covering a VIX calls. And you had this goofy cascading effect. There was a fund getting liquidated in VIX calls. And so basically you had this strange technical mirage with VIX 60. Everybody's freaking out what's going on. It caused a huge bit of the VIX futures and this very temporary move that then chopped back and forth and then came right back out. It's a great example of the way that we run our strategies. Nothing that we do is fully systematic for exactly that reason. The type of models that

[00:41:19] we use would have wanted to actually get long volatility versus long delta, for example, in that structure, because it sees all of a sudden this very steeply backwardated term structure and a lot of the signals would be kind of going off. What is going on here? Is this real? Is this going to persist? The answer is no. This is like a weird data glitch. Your model doesn't know that. So if your model is just spitting out trades and it's going to go put on some very large position that thinks this is really attractive, that's really, really dangerous. So in our case, we use models across everything that we do to kind of systematize and improve

[00:41:48] the efficiency of tracking the opportunity set and generating conversations about what trades we should be doing. Hey, is this good? But the conversation is always about does this make sense? Is this right? Is the data right? What's going on in the world? Is there something the model is missing? It's not blindly following some kind of mechanistic process. Well, I'd love to end by having you just reflect broadly on some of the things you observe in financial markets. And first, I just want to offer something and get your reaction. So one of the things I've seen is that trading volume

[00:42:17] seems to be very much flowing to a set of assets that I just put in the stock up vol up camp. The asset rallies and the vol rallies with it. It's a very non VIX S&P relationship. NVIDIA, Tesla, certainly MSTR, the Bitcoin ETF. I can't imagine that circle will be anything different. You have a number of these new assets. Gold, of course, had a big run up and the vol went up with it.

[00:42:47] It's a new thing and it just seems to be very associated with extraordinary trading volume. If I'm going to launch a new ETF, not that I'm going to, but the first thing I'm going to look for is, is this a stock up vol up asset? Because that's what people are going to trade. And I just would love to get your sense as to, is there information content in the trend for some of these new assets to exhibit that? This is very different than the 2005, 2006 heyday for banks.

[00:43:16] Banks rallied, vol went down. These new assets, they go up and the vol goes up with it. What do you think is going on there? Is there information around the speed of technological change? How do you think about it? Yeah, I mean, I think it's broadly defined the manifestation of the meme stock phenomenon and it's not entirely driven by retail, but certainly a big part of that is the rapid growth in highly speculative leveraged trading among retail investors using options. It comes even into

[00:43:46] structured notes. So if you think about structured notes, historically, that was really an Asia and Europe thing. Now, actually, the US market is what's growing spectacularly and a lot of it is in single name. It's in these names. It's in Palantir. It's in HIMS. It's in Tesla because there's just massive demand for leverage derivatives based exposure to popular themes. And you see those themes rotating slowly, right? Things will fall out of favor and new things will come into favor. That's what you get when you have investors crowding into particular positions, doing so with the synthetic leverage that the option market

[00:44:16] gives you buying calls, buying call spreads. You even had SoftBank participating in that in 2021. And there's some speculation that a big trader in the market right now that's doing the same thing as again, SoftBank might be, might not be, or a big investor that's related to SoftBank. Derivatives have become so much larger of a component of the toolbox, both of retail and of institutional investors today versus 20 years ago. You can really get these dynamics and it's the kind of thing that obviously really frustrates old school value investors or whatever because you look at like a Palantir or you look

[00:44:45] at some of these names and there's no way to make sense of the stock price, but that doesn't mean it's a good short. Actually, it's extremely dangerous unless somehow you can really sense the tide turning and get that right, but just shorting something on valuation just because these supposedly uninformed, you know, retail investors are driving it up is not a good strategy. Because there's no catalyst for it. And stock prices can kind of be whatever they want to be in a sense over any meaningful time frame unless there's a catalyst that forces them to come back down. That's kind of how I think about it. Those are the kind of things where we're looking

[00:45:14] for dislocations and derivatives markets on the back of that flow. Structured products where these guys are effectively selling two-year 40% of the money puts in these names, so we're on the other side of that and we're figuring out how to hedge them. We're not going to try to bet against those companies or short them or buy puts on them or whatever because God knows that kind of thing is very, very hard. Calling the top in these kind of names is quite tough. We're very comfortable using that flow to create exposures for us that in that case generate some very tremendous exposure in the tails where if this all blows up, well, we know we'll do really, really

[00:45:44] well, but isn't like a short bet on the names. Well, we live in a time of frenetic change. The AI stuff in markets, in society, the geopolitics of the world are being quickly reordered. What are some of the in-the-lab projects that you and your team are thinking about working on? What's kind of on your mind in terms of product research and development? We've revamped a little bit our absolute return hedge fund business to be structured more like a multi-manager business.

[00:46:13] So my team runs the center book, but I'll also allocate risk to other portfolio managers internally or externally. And the idea there really is to allow us to expand our scope within our core wheelhouse of volatility and derivatives and leverage top talent to do that rather than trying to do everything myself at some point. Like I become a real bottleneck if I'm trying to run research and portfolio management across a bunch of different protocols. In a year, I would love to have a great FX volatility portfolio manager, a great commodities portfolio volatility manager, a great crypto derivatives portfolio

[00:46:43] manager. I think that would be super cool and dovetail really nicely into the business. It's very opportunistically driven. Do we find the right person that works within the culture of the firm and is aligned with how we think about things usually that we know really well or that we have very strong references on for a long time? Taruda's markets are pretty small and we kind of know everybody as it stands. The important thing being orthogonal type of exposures. I mean, you'll see some of the big pod shops that have 30 pods doing dispersion. I just don't understand what the point is, right? You got a bunch of same way exposure. Maybe they do it a little

[00:47:12] bit differently, but you're not getting a lot of diversification in that context. The thing that makes our strategy better is having more idiosyncratic uncorrelated return streams that take advantage of different dislocations coming from different places. All right. Very last question. I can't help but want to ask it because you did mention dispersion. Of course, implied and realized correlation popped when realized vol is going to accelerate the way it did in early April. It's not reset all the way down, but we're still 20, 23 implied correlation on S&P one month, three

[00:47:42] months and so forth. These are unheard of levels even five years ago. These are super low. Is this just a structural change in how the market assesses single stock fall versus index fall? Do you see this changing anytime soon? How should we think about the path forward for the market clearing price of correlation? correlation. We've had different regimes in correlation over the last 20 or 25 years, and they don't tend to be permanent. People tend to assign explanations for them,

[00:48:11] which are at least partly correct, but probably tend to project them more permanently than deserves. I would tend to say it's at least partly due to the much greater interest in trading options and trading derivatives among crowd that didn't use to retail investors and mutual funds and big long only guys buying calls and call spreads and names where they might be used to just buy stock. And so that's going to drive more decorrelation to some extent. We haven't had any big recessions or any kinds of events that really drive

[00:48:41] super high correlation. Even in the pandemic, there was a brief moment of high correlation that then kind of settled down a lot. For us trading dispersion, we don't think there's any risk premium in pretty much anything. You should always trade the same way. We have like a modest size long correlation position right now because correlation is sort of too expensive. We look at it in terms of the spread of weighted average single name vol over index vol because vega neutral is really the market neutral concept for dispersion. Implied correlation is an extremely directional variable that will always go up when vol goes up and so forth.

[00:49:10] That spread is, call it, 14.5 on a three-month implied basis. Realizing 12 and with long-term averages being more like 9 or 10 or something. We're in a very expensive single name stock. Long-term average regime realized hasn't even necessarily been keeping up with that. So if you're doing dispersion trades here, you're not getting on a good level and you're losing money on a realized basis. There's a lot of people that will just always do dispersion. They think it's a trade you're just always supposed to do. I don't think that makes any sense. I don't think the data bears that out at all anymore. It once did when index

[00:49:39] volatility used to be expensive, but index volatility is not expensive anymore. There's plenty of sellers of index volatility and there's plenty of buyers of single name volatility. Like everything, it gives us a nice opportunity to sell. And do you tie the decline in implied correlation could be some function of the decline in the VRP and the S&P itself, which is some perhaps result of all the capital selling index vol. Interesting. Well, Ben, it's been awesome to catch up and have you back on the

[00:50:09] podcast. Always enjoy the conversation. Awesome. It was really fun being thanks for having me. You've been listening to the Alpha Exchange. If you've enjoyed the show, please do tell a friend. And before we leave, I wanted to invite you to drop us some feedback. As we aim to utilize these conversations to contribute to the investment community's understanding of risk, your input is valuable and provides direction on where we should focus. Please email us at feedback at alpha exchange podcast dot com. Thanks again and catch you

[00:50:39] next time. Thank you.