I am joined today by Benn Eifert, founder of QVR Advisors. QVR specializes in managing option-based strategies and Benn describes what he does as volatility investing.
We quickly wade into the deep end with this one. Benn schools me on relative value investing and dismisses my favored mental model of style premia for what he prefers to call “the Star Wars framework.”
We chat about volatility ETPs, their impact on the volatility landscape, and how the market has changed since February 2018. And with some spectacular option-driven blow-ups in the last couple of years, I ask Benn for his guidance on how he would think about due diligence in the space.
Finally, while Benn deals exclusively with institutions at QVR, I get his thoughts on how volatility investing might play a role for individual investors.
We go deep with this one. So let’s dive in.
Corey Hoffstein 00:00
All right, Ben, are you ready? Yeah, absolutely. All right 321 Let’s do it. 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.
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 new found research may maintain positions and securities discussed in this podcast for more information is it think newfound.com.
Corey Hoffstein 00:55
In this episode, I am joined by Ben eifert, founder of QBR advisors. QBR specializes in managing option based strategies, and Ben describes what he does as volatility investing. We quickly wade into the deep end with this one, Ben schooled me on relative value investing and dismisses my favorite mental model of style premia for what he prefers to call the Star Wars framework. We chat about volatility etps, their impact on the volatility landscape, and how the market has changed since February 2018. And with some spectacular option driven blow ups in the last couple of years, I asked Ben for his guidance on how he would think about due diligence in this space. Finally, while Ben deals exclusively with institutions at QBR, I get his thoughts on how volatility investing might play a role for individual investors. We go deep with this one. So let’s dive in. Ben, welcome to the podcast. Corey. Thanks.
Benn Eifert 02:00
It’s great to be here.
Corey Hoffstein 02:01
So Ben, I think I came across you originally on Twitter started following you. I think you fall under obviously the big fin twit banner, but certainly a specialty in volatility related strategies, volatility products. But for the listeners who maybe haven’t come across you before, could you start with a little bit of an introduction and introducing your firm QBR.
Benn Eifert 02:23
Yeah, absolutely. So QBR stands for quantitative volatility research. We’re a boutique asset management firm that manages volatility strategies for large institutional investors. And we’ve been around since early 2017, I started the firm with Scott Toyama and Tae hyung. And really, I think what we what we try to do is, you know, it’s a natural evolution of, of what I’ve been doing in the marketplace for a long time, but really trying to bring the skill set and toolkit of options traders and volatility managers to the space but in a way where we can do a lot more customized and bespoke work in the sense that I really think about the business. As you know, we have a set of strategies that we run, the different investors have different interests and subsets of what we do. Some people want to talk about absolute return strategies and certain areas, some people are really excited about tail risk hedging, and we’re able to mix and match into bespoke mandates, you know, rather than the older school approach, which is, hey, I have a fund and you know, you can you can get some of that if you want. It’s a lot of fun. You know, my background originally, I was a macro economist, emerging markets macro guy, I worked for the World Bank for a little while, really got my start in, in finance full time on the Wells Fargo proprietary trading desk, which was a lot of fun back in the day, when most people don’t even remember that there was a Wells Fargo proprietary trading desk. And then after that, ended up starting and running with a partner John Laughlin, a fund called Mariner Korea doing relative value volatility trading under the Mariner Investment Group umbrella out in New York, and then QBR, we started in 2017, to do the same thing without a cross country commute to New York from San Francisco, which I think is a much better situation make
Corey Hoffstein 04:11
life a little easier. So I want to draw a bit of a line in the sand here because I believe most of our listeners would be sort of at least aware of the big option based strategies, right, where you have income generation on one side, you mentioned tail tail risk hedging on the other, but I know you define what you do. Acuvue are a little bit more as volatility investing and not really an option strategy. Can you maybe explain the difference between what you consider to be more of an option strategy versus what actual volatility investing is? Yeah,
Benn Eifert 04:47
absolutely. I think to your point, when most people think about when they think of options strategies, they think of call overriding for example, or cash secured puts selling or certain types hedging activity, you know, things that typically would have significant directional market exposure to them. So you think of, you know, call over writing or put writing, for example, both of those are long equity market exposures. And on a day to day or month to month basis, really the equity market exposure is going to be the biggest risk factor. And then there’ll be other risk factors second, and third order beneath those. But really, market exposure is the biggest driver, I would contrast that with volatility strategies broadly defined, and broadly speaking, which really try to isolate features of the distribution of returns, but not really the direction of returns. So for example, instead of having views on whether the s&p will go up or down volatility, investors might think about things like, how volatile is the s&p 500 likely to be over the next month, compared to the Russell 2000? For example, or maybe, you know, if the mark equity market goes down 2% Tomorrow, where’s the VIX going to be? And constructing you know, bets and views on aspects of the probability distribution of returns and cross sectionally within the universe or within the same underlying in that sense, I think that’s the really the key distinction is sort of, is the first order exposure to the underlying market direction, or the other features of the probability distribution.
Corey Hoffstein 06:24
And I know in your intro, you mentioned that you guys focus somewhat heavily on relative value strategies in the volatility space. Can you explain for me what constitutes a relative value strategy? What’s that sort of look like? What’s the trade kind of look like that you might put on?
Benn Eifert 06:41
Yeah, absolutely. In volatility, relative value, you could think of it analogously to equity market neutral strategies, or to fixed income relative value investing, where what you’re really trying to do is create value out of buying cheap exposures and selling expensive exposures at the same time, trying to hedge out the main directional market risks that would dominate a traditional asset allocation. So for example, a relative value portfolio at a point in time might be long short term volatility versus short, medium term volatility, for example. Or it might be long, deep out of the money, put options versus short near the money, put options. So a hedged exposure that’s generating some particular type of, of correlation, or it might be long volatility in large cap energy companies versus short volatility in small caps.
Corey Hoffstein 07:36
So I’m just thinking about it from a sort of Kwan equity standpoint, you know, we would say a value strategy, relative value strategy in the equity space, you would just sort of define as buy cheap, sell expensive, and you can sort of think in your mind categorically what that looks like, you gave a couple of examples there, you know, long short term ball short, long term vol, are there sort of traditional trades that you can put on that generally capture relative value within the volatility space are these types of trades moving around all the time, and identifying them is really an important part of the process, I
Benn Eifert 08:10
wouldn’t say they move around all the time, but over different, you know, cycle frequencies depending on, you know, the opportunity or exposure. So there might be some places I gave the example of, say, for example, long volatility and large gap energy companies versus short volatility in smaller energy companies, those type of things, you know, typically would be an opportunity at a point in time that might show up. But driven by a series of large transactions in the equity market where, you know, for example, a large fund was doing a bunch of overriding, you know, in, in their large cap energy names, which suddenly made them very cheap, right, that might be the kind of thing that shows up from time to time. And you really have to monitor and understand what’s going on and see the prices move and understand why there are, you know, other dislocations and other relative value opportunities that might cycle over time, but be much stickier in passing. So you know, we’ll talk in a little bit more detail about some of the types of things that large pension funds do in the in the equity options market. But over the last several years, there’s been a very substantial growth in index call over writing and index cash secured, put selling among pension funds, trying to generate income, relative to their equity portfolios. And that’s, you know, creating some certain types of opportunities that might last for several years while those strategies are popular. And then you can imagine it becoming too popular and over some number of years, then the pendulum swinging the other way. So there was there’s, I think there’s a spectrum of the time cycle. I wouldn’t say that there’s, there are many risk premia that you would expect in the space to just exist in perpetuity in a relative value sense.
Corey Hoffstein 09:57
That segues nicely into To sort of the next area I want to talk about with relative value, which is, again, coming from more of the quant equity space, we would look at something and say, Well, this is either a risk premium or maybe a Behavioral Anomaly that we’re trying to exploit the misbehavior of other investors. Sounds like from a couple of the examples you gave, the opportunity and relative value in the volatility space might be sort of a structural mismatch and the needs of different market participants. How would you characterize where the opportunity is coming from for this type of strategy?
Benn Eifert 10:36
I think the the really interesting thing about option markets in that regard is that they really are not a zero sum game in the way that you might think about certain investors, you know, trying to be smarter than the other guy in terms of whether you know, Apple is too cheap or Netflix is too expensive, really option markets. In a sense, there’s a large need to provide liquidity for end users of option markets and distribute risk from where options are being heavily supplied to where they’re being heavily demanded. Right. So option markets and derivatives in general. But the markets exist, because they’re our end users were trying to achieve certain objectives, right. There’s portfolio hedgers, who are trying to protect their positions. There are large pension funds trying to generate income by selling options. There are, you know, outside of equities, there are corporations trying to hedge their currency and their commodity exposures, for example, right. So the these markets really developed on the back of end user demand, and then user need to transfer risk. And you know, the key thing and Relative Value Investing in volatility is that the marginal price setter for, you know, the probabilities and the market prices that we think about and talk about, typically, that marginal price setter is not a volatility investor. That’s thinking about nuances in implied volatility, pricing, typically, it’s an end user of options and derivatives, right. So it’s a huge pension fund that’s right at running a call overriding program. Or maybe a retail investor buying a structured Note link to the price return of European equities, for example, these end users have their own objectives. They’re typically, you know, more structural long term objectives as part of a larger portfolio that aren’t necessarily focused on the exact price that they’re paying for an exact type of risk or particular, you know, a particular volatility skew parameter, they may just not focus on those things, right. So for a specialist volatility investor, many of the best opportunities really arise from either explicitly or implicitly providing liquidity to meet the needs of end users, and to warehouse basis risk between what they’re buying and what they’re selling. So when
Corey Hoffstein 12:47
we were chatting before, and trading some emails and going back and forth, I know I mentioned to you sort of trying to get my arms around this volatility space, trying to think through things from the lens of your traditional quant type mentality of value, momentum, trend defensive carry that sort of mentality. And you mentioned to me that you weren’t really a fan of using that mental model for the option space and the volatility space in particular, but you actually preferred something you called the Star Wars model. Would you mind maybe explaining why you don’t like the sort of big sort of factor Pantheon framework and why you prefer this Star Wars mental model? And what it is? Sure, absolutely.
Benn Eifert 13:34
So you know, there are I think some analogues in traditional factor investing to what goes on in the in the equity options space. So for example, the most obvious one is, you know, option selling strategies for income certainly are expressions of a carry style, right? They, they are in a predefined rate of income, if there’s no move in the underlying securities, they see that income slowly eroded if the underlyings starting to move around a lot. And similarly, strategies that sell vix futures, like XIV, for example, before it blew up in February of last year, are in carry from the typical upward sloping shape or the term structure of implied volatility, effectively generating compensation for taking the risk of loss and a volatility spike. That’s a very clear analogue. I think, you know, outside of that, I think that you see much less of the language of style premium broadly applied to volatility markets, there are some elements of momentum and mean reversion in volatility, in particular volatility over over long periods of time, is an has to be mean reverting, and so there’s people who, who think about the time dynamics of that, but over over short periods of time, it may or may not be true. But on the, you know, on your point about, you know, the Star Wars framework, of course, that’s a facetious word to some extent, but you know, the silly nerd analogy being that we’re all quants, after all, is that relative value strategies really sort of are there to bring balance to the Force, right? I mean, end users of derivatives do things in big herds. And they typically have very large size relative to the absolute return community. And they’re very sticky, right. So just take the the example of, say, the last five or six years, you know, when the huge pension funds of the world start to allocate a meaningful part of their portfolio to call overriding and equity replacement via put selling. And they all do it in very similar benchmark ways in the same types of one month near the money s&p options, in very, very big size, it creates a big disturbance in the force, it creates just this huge congestion. In one piece, small piece of the overall options market creates really steep term structures, market makers get stuffed with short term options, they don’t have the risk limits to hold. And the community, the relative value community’s job is really to distribute that risk much more broadly, throughout the ecosystem, relieve the congestion caused by very heavy benchmarking and very, very large sizes relative to the size of the market in that particular type of trade that those end users are doing. And try to create a nice risk reward profile and get paid to provide the liquidity to that to that market. So really, that’s what we’re talking about really end users of options, when you see that type of behavior tends to be very, very impactful, and a particular part of the market that needs someone on the other side to warehouse, the basis risk and to distribute that risk.
Corey Hoffstein 16:40
So when I think of the options market might, my head often starts to spin a little bit, you mentioned an example of a trade, this sort of long vol in large cap energy shortfall and small energy driven by either sort of a structural or event driven situation where you had perhaps some sort of fun, that was overriding options on their energy book. Sounds like, in my opinion, identifying that type of trade of all the possible trades that are out there, when you consider the option landscape could be somewhat overwhelming. And by the time you identify it, you might not be the first to identify it, you might be too early on the trade. I guess my question for you is, how do you think about identifying trades in this space? How do you think about managing trades? How do you think about exiting trades? How does the book come together? Because it seems like a very overwhelming landscape to try to get your arms around.
Benn Eifert 17:42
So we would think about the organization of our investment process, you can really think of it as a collection of bottoms up sub strategies or strategy sleeves. So an individual strategy sleeve would really be a theme that’s driven by some particular type of dislocation or some particular type of underlying flow that end users are generating. And there would be, you know, a process around that some strategy. So you know, what is the type of trade, you gave the example of the, the ER highlighted the example of the large cap energy versus small cap energy? No, that would be an example of a cross sectional relative value trade. So we would have a definition of what is the universe of underlyings that we look at within a cross sectional portfolio. And then in that particular strategy, because that’s very much, I think, the opportunities that often is more opportunistic, and more fleeting, as opposed to there being structural flows that are very consistent over long periods of time, to your point, it involves building out quite a lot of infrastructure to identify those opportunities quickly, right? So to look back over time, historically map a lot of data to try to understand, you know, how would you actually identify what looks like a good opportunity? What pieces of data are helpful in identifying and predicting that so typically, in that, that kind of case where I gave the example of a fund coming in and do it running a big overwrite sale on on their long, large cap, equity names portfolio, for example, typically, that would come through feed through quickly into the prices of, of options on that, within that universe, and you’d see a significant reduction in those prices, relative to the prices of the small cap energy names, for example. And you’d see also in that case, probably it wasn’t driven by underlying realized volatility dynamics, it wasn’t that the spread compressed because all of a sudden the the names and the short baskets started becoming very volatile and their prices started rising. Right and you’d have various other ways of triangulating that, that are very, you know, are data driven and quantitative, and that would trigger you know, an investigation and protect potentially adding that type of a trade to the portrayal Oil in a strategy sleeve, where the dislocations are potentially more persistent, it might be more a question of measuring the how do you measure those dislocations? How do you track the ebb and flow over time? Is it a particularly attractive opportunity set? Do you want to have maximum risk on? Is it a less attractive opportunity set? Do you only want to have 30 or 40% of risk on, you know, in terms of the the identification of those type of opportunities as a starting point, and the design of the strategies? You know, really, again, a lot of this, a lot of the themes are very much driven by what our end users have derivatives doing in really, really big size and affecting markets. And that’s not that hard of a question to answer. If you’re a really active market participant, and you spend a lot of time talking to market makers and talking to the end users of derivatives, you see it very quickly, right? Because, you know, I gave the example of overriding of call overriding and put underwriting among large real money asset owners being a huge theme that’s driving a lot of short term option pricing, right now, if you talk to s&p option, market makers, in this environment, the last several years, a very large part of their job is just showing up to work and figuring out how to how to take down, you know, the huge amount of flow that comes in in that space. And then and then get rid of it, because you know, they don’t have the risk tolerance to hold it as a as a market maker, right? And so you can observe and see very quickly, what are the what are the things that end users are doing? And then what you have to do is think carefully about how you would leverage that. And what is the mispricing? How would you leverage it to create a portfolio that has the risk reward characteristics that you want,
Corey Hoffstein 21:45
I’ve long sort of held the view that quant works really well, obviously, in a space when there’s a lot of data, and that data is somewhat stationary. So non idiosyncratic spaces, but also spaces that don’t have sort of massive degrees of freedom of all the sorts of directions you can play. And it it strikes me that, on one hand, what you’re talking about do sound like opportunities that can be somewhat systematically identified. But on the other hand, some of them do seem very event driven, which to me, are therefore not necessarily easy territory to be inherently quantified by some sort of system. How do you think about the trade off between systematic versus discretionary and volatility investing?
Benn Eifert 22:34
I mean, I very much think of it, I think, similarly, in terms of a spectrum between, on the one end, fully discretionary and gut feel Based Investing all the way to the other end of the spectrum of fully automated back to front systematic trading, it would say that most volatility managers, I think, lie somewhere in between on that spectrum, we are probably closer to the systematic and maybe, you know, a seven or eight out of 10. on that spectrum, say, in that we think about strategy, building blocks that are developed bottom up, using data and models wrapped together into a technology infrastructure that’s continually measuring opportunity sets, and wrapped together in a rigorous risk management process. But I think within options and volatility, it’s really hard to get that last, you know, that last mile to full automation, in that, first of all, and you alluded to this, there’s just a lot of degrees of freedom, right? Even just within the s&p, there’s, you know, 15,000 listed options, and there’s a tremendous amount of dimensionality to the problems that you’re addressing. There’s also liquidity is very, very good, but liquid the nature of liquidity in options and volatility trading is a little bit different, right? Because when you’re, if you want to execute a large transaction in s&p options, typically or not, and you want to do so very efficiently minimizing transaction costs, often you’re effectively sourcing liquidity over large numbers of different option contracts, but synthesizing a type of exposure that you want. That’s a an experimentation process to some extent, as opposed to just having a model spit out, Hey, by the, you know, 2700, strangle in big size and going and doing that. Also, it’s just worth mentioning, I mean, when you fully when you have a fully automated trading process, obviously, a big part of what you need to do is manage that point, oh, one percentile, you know, risk case of a bug or something going wrong and options are inherent, have inherent nonlinear risk characteristics. Right. So the, I think the potential risk of a fully systematic process is just larger in that regard. I think that’s why you don’t see many truly fully automated programs and in the space, but I think we we very much have a data driven process driven approach that at the end just has A fundamental traders juggle risk and portfolio management judgment on
Corey Hoffstein 25:03
top. I really like that notion of your payoff structure is nonlinear. So model errors, therefore have a very nonlinear impact. And that might not be true in more like traditional quant equity space. That’s a really interesting way of thinking about it. Are there any examples that come to mind where either an opportunity was systematically identified and you had a discretionary override? Because the opportunity was not what it seemed? Or perhaps the opposite, where you thought there was an opportunity? And the systems were correct in identifying that it wasn’t? Yeah,
Benn Eifert 25:41
absolutely. I’ll try to give one of each historically. So you know, one that made the jumps to mind on your first question, what was an opportunity that a model might have said was interesting that we stayed away from it was a while ago at this point, but you remember back in the early days of Abenomics, in Japan, back when the Nikkei was incredibly depressed, there was an interesting dynamic showing up in in skew on Japanese equity indices. So skew is the relative price in an implied volatility sense of upside, call options versus downside put options. And in Japan, that actually started to go positive, which is very unusual. In other words, upside call options, were trading at a higher implied volatility than downside put options. And, you know, there are some structured products that contribute to this, we’re not going to go down that rabbit hole. But a lot of folks in the you know, there were folks in the volatility community that got really excited about how silly it was, that an upside call option would trade at a higher implied probability than a doubt or implied volatility than a downside put option, and really aggressively sold upside call options. But the key thing to remember back then was that, you know, the Japanese equity market had just been incredibly depressed for a long time. And there was a tremendous macro narrative building around big structural reforms and aggressive, unconventional monetary policy driven by by Shinzo Abe, a and what you saw was a what followed, that was a very volatile rally. Right? So it was really a sucker’s trap to look at skew, and look at a historical data set and say, Oh, well, it’s extremely unusual for upside calls to trade, you know, above downside puts, you know, and as a result, put on some type of trade that express that, you know, very directly by being short, the upside calls, because, effectively what you were selling was the upside, you know, the up crash scenario, which was exactly what what happened. And I think as you know, we’re we are not first and foremost, offensive macro investors in the sense that we’re not creating a portfolio based primarily on macro views, but we certainly try to be very abreast of what’s going on in the world. And that, to me was a case where the model just didn’t know what was going, you know, what was going on in the world, and what the, the risk of that type of scenario was. So that’s an example on on the flip side, and then an example on the other side of things, where, you know, there was something that a model looking at historically might not have fully captured, when you think back to February 2018. So there were some things that models got really right about, you know, vol mageddon in February 2018. For example, the VIX term structure was both very very low and very, very flat. And you know, retail positioning in the exchange vix Exchange Traded products was very crowded short and all of that data was was there in the model and screaming Hey, you don’t want to be short vix futures into this, you know, you want to be long them and hedged with something else, but also implied volatility of volatility. So if you want to think about the V VIX, if you’re if you’re used to looking at that ticker, just the price of vix call options have gone up quite a lot. And I think a naive model that looked at historic that looks at historical data on vix option prices would have concluded that it was very silly, the prices that people were paying for upside vix call options and you would want to be short them and then hedged with something else. But really the driver of that was just this extreme negative convexity in the marketplace associated with the size of the rebalance that the VIX ETP is the leverage and inverse vix etps had to do on a large vol spike. And that was a known fact out there and people were aggressively betting on that possibility using options. And so again, very much was a type of thing where a model that only looked at historical data but didn’t didn’t understand that particular dynamic would have wanted to bet on. But, you know, for us, actually, that that convexity of in volatility of volatility was still quite cheap and given that given the scenario risk of exactly what happened.
Corey Hoffstein 29:49
Well, I’m glad you you brought up February 2018, and XIV and sort of the volume again, because now I can bring it up without you rolling your eyes. I know You you actually recently gave a talk at the CBOE Risk Management Conference where you spoke about sort of the different types of market participants and their response function to different environmental changes. As you look across the landscape today, and maybe take it back historically, pre vol mageddon, how did the etps affect the landscape of volatility investing? How has that changed post February 2018? And who are the big players today? And what sort of effect are they having on the market?
Benn Eifert 30:35
So the the VIX CTPs first started showing up VX X was actually listed back in 2009. But it wasn’t didn’t become popular for a few years really. 2012 was really when large inflows started coming into the long VIX, etps, which were the ones that existed at the time. So think VX x and t vix and UV X, Y, and those relatively large inflows into that product at a time when vix and vix futures were still, you know, relatively early stage products that only been listed for four or five years. Those really created quite a lot of excess risk premium index products. So you saw, you know, a number of RAS actually putting client assets into long volatility positions using these products that then lost money at a very, very rapid rate. Because there was really just way too much money effectively by all doing the same thing, buying short term vix futures back in 2012, you remember and then there was an incident where the T vix was actually suspended creation and redemption and T vix traded at a big basis to NAV and it was all a big mess. After you know, several years of losing quite a lot of money being long, vix CTPs, the general retail Fast Money universe started to discover that first of all, you can short those same etps Instead of buying them and second of all, but there were a newer set of etps like XIV, for example. And like s of xe, which rather than being being long held a short position in vix futures, and money, you know, slowly started rotating from the long etps into the short stylee TPS. And that position grew and grew and grew. And, you know, folks did fairly well on those exposures from, you know, 2014 2015 2016. And 2016, in particular, was a very, very good returns year for a lot of those strategies, because for various reasons, the the volatility term structure got quite steep. And it was pretty persistent. And then you had 2017, right, which was really a exceptional right tail events from a volatility perspective in that realized volatility was extremely low. We had this balanced global growth night, you know, coordinated across the economy is really very few surprises, nothing going on equity market just kind of very slowly melting up. And you saw spectacular returns and a lot of these a lot of these short volatility products. And what ended up happening was both because of in additional inflows into short volatility products, like XIV, but also very importantly, because of retained profits on those existing investments, that short vix CTP complex became just truly huge. And the last point is important. So explain a little bit. Typically, when you think about a balanced portfolio, you would think about, you know, rebalancing frequencies, right? And over some quarterly or annual cycle, you might say, hey, my equities are up, you know, 5%, so I’ll sell a few of them. And my bonds are down a little bit. So I’ll buy a little bit of those. But with you know, your typical equity investor and retail investor probably isn’t as aggressive as they should be about rebalancing. And if you think about something like XIV, it’s a highly leveraged product in of itself, right. So even though an investor might buy it, without using any margin or explicit leverage, you would think about a share of XIV, which is effectively a full dollar notional equivalent of volatility exposure as maybe eight times levered to the underlying equity market, if you think of like, what kind of a beta that it trades on. And, you know, that product had, you know, 150% return year or so in 2017. And so if you just held on to that whole position, it effectively reinvests all of your profits in more short volatility positions of this right at a lower and lower level. And so, you ended up in this position where both due to influence inflows and due to performance those positions just came extremely large. And the other important thing to understand about how a short volatility Etn behaves with the underlying portfolio of XIV is a set of short of short positions in vix futures right? And when volatility goes down, in order to maintain the same Market Value exposure that is supposed to have XIV as an exchange traded product has to go and sell more vix futures on the close. And on a day when volatility goes up, in order to have the right amount of exposure on a market value basis, something like XIV has to go by by vix futures back. Right. And if you if you have a mechanical response, where you run a fund that has to buy volatility, when vol was up and sold volatility when vol was bound, that can potentially be very problematic if you’re large, right. And once XIV and the other leveraged and inverse ETFs got sufficiently large, it meant that if there was really a volatility event, if there was if something like February 5 happened, right, where the market was down, four or 5%, and the front month vix future was up, you know, eight points, there would have to be just a tremendous amount, you know, a significant multiple of the average daily volume of those vix futures would have to go be bought by those products right at the end of the day, and everybody would know about it, right. So it was just a market microstructure time bomb waiting to happen. As you pointed out, the timing of that type of event happening was uncertain. But the sizes of those positions made it almost inevitable at some point, it did happen in early February. Now really, I think retail positioning in those ATMs is much, much lighter. And if anything biased back to the net long side. And really, you know, the VIX complex as a whole, it’s still quite large, it’s shrunk, somewhat volumes are down. And a lot of the you know, the the marketplace there, I think is actually much safer, and has doesn’t have obvious time bombs. And to your question about what are the big players, you know, really affecting markets in option land, in the current environment, I think the biggest thing that I would point to really, again, is the the rise and really rapid growth of large scale institutional real money, option selling for income. So again, that’s big pension funds and selling call options against their equity portfolio and replacing parts of their equity portfolio with put selling, you know, largely in the s&p largely very short dated, so one month or there abouts. And again, very congested in the sense that there’s not really that much variation in what all these different players are doing. They’re looking at, you know, 2530 year historical back tests of those type of positions and say, you know, doing some portfolio analysis on what type of risk allocation they should have, and the pension fund consultants are guiding a lot of big institutions on this, when I think they’re not really taking into account the equilibrium effects on risk premium, as the overall size of the flows doing similar things grow and grow and grow. And I think our view is that the expected returns and those kinds of strategies are falling very, very fast, and really changing gamma risk premiums, sort of the expected realized volatility versus the implied volatility for short term options.
Corey Hoffstein 38:00
So I want to stick with the TPS for a second, because you mentioned something there that you thought sort of retail, it shifted back to maybe a little bit of the net long. And I know that, as you mentioned, I mean, VXX sort of the the long side of buying volatility has historically gotten a lot of sort of hate because of its decay. I don’t remember where I saw his maybe as an email you sent me or maybe I saw this on Twitter, but I’m gonna throw a quote of yours in your face, and have you respond to it put you in the hot seat here. But I think he said something to the effect of like, buying VXX these days, isn’t really that bad. And the carrying cost is a lot less than it was in the old days. And I wanted to get your thoughts there. I mean, is this something is this a trade people should be putting on? Now
Benn Eifert 38:46
look, I would say first of all, everything is relative here, right? But buying volatility and hedging is pretty much always something you expect to cost you money. And I think that will that’s generally true should be true. There shouldn’t be a risk premium there. There’s also a time dimension to it. So actually, it’s funny, I think I remember that quote. I think the last few weeks, just call it two, three weeks, I probably agree a bit less with that statement than I you know, than I did a month or two ago. But I think you know, the key thing about volatility, the nice thing is right, as a hedge, you can understand what the forward looking cost of holding a position like long VXX is by looking at the shape of the term structure, right? Volatility can always go up or down, it can always go down and you can lose money on along the x x position because, you know, one month implied volatility goes down, but at some point if implied volatility is you know, 12 or something that’s not going to be your biggest risk really, certainly not over time. But you know, far and away the biggest cost of owning Vega or owning the xx vix futures like position really comes from the shape of the term structure from like, contango right because when you buy VX X really what you’re doing, the underlying portfolio of VX X is long, a portfolio of first and second month vix futures, with a weighted average maturity of a month. And so in order to do that every day, it has to buy volatility. Now, think of typically the term structure of the VIX is upward sloping in contango. So typically, you’re having to buy some contracts out at, let’s say, the six week point, for example, and sell some of the ones that you own at the two week point, that’s the second in the first contract. And typically that you know, you’re buying the deferred futures at a at a slightly higher price than than the near term futures. And that’s the way the markets way of charging you for insurance, right? You can measure how big that premium is. Typically, historically, when volatility is at relatively low levels, as it is now, you would see something like a premium of, you know, let’s think of the slope of the VIX term structure right around the one month point, you might think of a slope of two or two and a half ballpoints being a typical historical level when volatility is relatively low. Up until just recently, in the last three weeks, we’ve had trouble getting the VIX term structure that steep it stayed, you know, persistently somewhat flatter than that, more like maybe a ballpoint or a ballpoint and a half of steepness there, which would translate by the way for vix level around 12, maybe into a decay rate from VXX of like a percent per month or something. So I think, you know, his, it really depends, you have to look at the price, you have to see the term structure, you have to understand positioning. But if we can stay in a slightly flatter term structure environment, and if we get back there, you know, the risk reward if you need long volatility, if you need a hedge in your portfolio, that’s not a terrible risk reward when it’s too low points, or two and a half all points like it has been closer to the last few weeks, it’s less clear, that’s a higher cost of carry, significantly higher cost of carry. And, you know, there might be better alternatives, better alternatives elsewhere. But, you know, if you think about threw in, you know, 2018 2018 was not a 2018 had a few significant volatility events, both of them were short lived. And, you know, the market rallied back fairly quickly, and volatility fell fairly quickly. And, you know, VXX as a, as an asset, actually, you know, made some money over that, over that period. It wasn’t, you know, huge tail event and blow up, right, and performed actually quite well as a hedge, you know, the Sharpe ratio of being long VXX was pretty good. So I think it’s situational. You need to look at the cost. But, you know, I think that a lot of the truly bad perceptions of something like VXX, you know, come from the fact that when you look at 2012, for example, right, the VIX term structure was just silly for some periods there because of the amount of huge buying of of vix futures via the long Etn. So for example, I mean, there were times when vix spot where the vix index was, you know, 15 or 16. The front month vix future was 20. And the second month vix future was 23 or something like that, right? So you were, in order to hold vix futures position, you were just losing some preposterous percentage of your money every you know, every month. You know, I think that I don’t think we’re gonna get back to those days. I think that the market, there was more of a disconnect in those days between the underlying s&p options and the VIX futures. Now, that’s much better arbitrage by dealers and by by relative value, guys.
Corey Hoffstein 43:34
So yeah, look, there’s times I think there are times when owning VXX can absolutely make sense. That last point you bring up about the market structure, when you see a very, very steep vix Futures Curve, in your opinion, is that an expression of the market’s viewpoint or do you think that’s just an expression of a market imbalance?
Benn Eifert 43:57
Typically, it’s more related to risk premium than it is to some kind of unbiased forecast of future volatility. And I think that that statement, I think it’s true in the VIX term structure, but it’s true much more broadly. If you look at you know, academic research or practitioner research and strategies whenever you have a term structure of forward prices. Typically there are some fundamentals to that term structure and some expectation element of expectations but often quite a lot of elements of risk premium, right. So it’s that’s the origin for example of FX carry type of strategies, and of interest rates carry type of strategies. Within the VIX term structure. Usually it reflects excess buying or selling of volatility within certain parts of the term structure. So if you think back to January of 2018, the VIX term structure was both extremely low and extraordinarily flat, given its level. And I think they’re, you know, certainly among the institutional volatility and options trading community, I think there was quite a lot of excitement about the possibility of a near term blow up as we saw, you know, equity prices going parabolic in January and realized volatility actually starting to rise to fairly significant levels on the way up, and the extreme length and positioning. Right. So I think that was a great example of, you know, that that really flat term structure really didn’t represent the professional volatility tradings consensus view on the medium term volatility trends, it really was a reflection of largely of retail flow with larger and larger short positions and volatility.
Corey Hoffstein 45:38
So I’m going to go ahead and just change the topic a little and ask what is probably an insultingly naive question, but I always get excited to ask ask people who who know, options. Well, option strategies seem to blow up a lot, man. I mean, obviously, the big example Long Term Capital Management as the most famous, but more recently, last year, the ljm preservation and Growth Fund, you had option sellers.com At the end of last year, you know, what gives? Is it just sort of the the nature of an approach that has very nonlinear payoffs, that that sort of blow ups are inevitable?
Benn Eifert 46:11
It’s a great question. I think, all of these examples that you highlighted, and I think most of the other examples one could come up with, were highly leveraged sellers of tail risk, right? So if you looked at their portfolios LTCM it’s interesting because everybody, you know, when you think okay, what did LC TCM really do? What was its business model? What were its strategies, people remember and like to think about, you know, the Treasury, butterfly, right, the sort of 28, you know, 2920 and a half, nine and a half, you know, 30 year, you know, Treasury butterfly, because the on the run issuance and the supply and demand imbalances, and really kind of, well hedged, things like that. That was where they started, they blew up because they were short, absolutely massive amounts of variance swaps on largely on the s&p but also on global indices, right. And variance swaps are sort of the most negatively convex tail risk balm that you can imagine, other than maybe like a call option on variant swaps. So the larger and larger that they got, the more returns they had to generate, to generate, you know, a healthy return. And, you know, they were they were smart folks, but those were not hedged positions, those were not, that was not kind of smart, sneaky relative value that was just selling monstrous amount of tail risk. And that was a very large percentage of their loss much, much bigger than their losses on like Russian debt, for example, they had, you know, trillions of dollars of notional exposure on that type of stuff. ljm similarly, when you look at their portfolio, when you compare it to other portfolios in the option space, you know, they had huge leverage notional positions, in short crash puts, right, they used the futures options in the s&p in the ES options, specifically, because they allowed a lot more leverage than the s&p options, right. So again, this isn’t relative value, this isn’t cash secured, put selling, this is just sort of Monster Tail risk selling with a huge amount of leverage. And then, you know, options. sellers.com was, you know, it was funny, it was pretty sad. Obviously, seeing that that video, they were selling, you know, I saw their portfolio, I mean, they were selling short term $5 calls on natural gas with notional is much larger than the size of their accounts, right? That’s just insane. Natural gas is a highly idiosyncratic weather dependent commodity that can spike from $2 to $4. In a, you know, a week or two, right? And has many times historically, and there’s many famous blow ups of, of portfolios, Brian hunters and amaranth on natural gas, right? So the thing about, you know, selling tail risk, you never really know what the right price of tail risk is, right? For some extreme event happening. And when you see firms that engage in that type of activity, you know, typically they’ll make money for several years, because you know, it’s a relatively low probability event that’s gonna wipe them out, right, and they make a lot of money. While they do that, and they start, you know, the natural human behavior, I think there is to wrap, you know, increase sizes and increased sizes, because the volatility of the portfolio is extremely low, right, you’re, you’re taking a highly negatively skewed payoff, it’s going to show a very great a great Sharpe ratio until until you’re bankrupt, right. And so I think, you know, the vast majority of cases where you see option strategies that blow themselves up, really, when you when you dig into it, there was some massively over leveraged tail risk type of position under the hood. And that’s really what drives it.
Corey Hoffstein 49:41
It’s to your point to the to some of the conversation we were having earlier where it’s difficult to be systematic in a space where you don’t have a lot of data, sort of, by definition, tail events are low data, idiosyncratic events, so it’s hard to have a purely systematic approach there unless you think the market is just always over. We’re pricing tail insurance, but it sounds like and I don’t want to put words in your mouth. But if you were doing some sort of due diligence, on some sort of options strategy or volatility strategy, to initial red flags, at least for you would be leverage? And are they selling tail insurance? Or are there any other things? I mean, first of all, is that correct? Is that how you would at least start to look at red flags? And I guess, second question would be, as people are evaluating these types of strategies, are there any other red flags that you would pick up having been in this space for so long?
Benn Eifert 50:35
Yeah, I think that’s, that’s absolutely right. I mean, first of all, I would want to see and drill into, you know, sophisticated, top down risk systems that stress all of the main risk factors in the portfolio to very extreme levels, and see that the risks there were acceptable, right, there is no portfolio that, you know, is going to make money under all circumstances in all scenarios, and that’s fine. And a lot of times you know, what the type of risk you’re taking is, but you should always, if there’s a major risk factor in the portfolio, you should be able to take that to a very extreme level that you’ve never seen historically, and see that the portfolio is not going to be, you know, hitting big margin calls and getting liquidated at that level, right, it should have the level of risk leverage in that sense, you know, should be contained in a level that’s acceptable to the end investor, that level may be different, right? For different for different folks. But I’d also and I’d want to really get into detail there, and then I’d want to understand the assumptions they’re making in those stress tests, and be sure that they’re not relying on overly optimistic assumptions about, you know, how some particular hedge that they have in the portfolio performs that, you know, totally saved them against, you know, all the bad scenarios that they run. And then, you know, in my case, very much so and I think that, you know, other folks doing due diligence, really think similarly, I would really want to see the actual positions, and hear them explain what other parts of the market what other market participants are doing similar trades, and try to understand what the squeezed risk looks like. Right? I think that if, you know, across the alternative investments universe in general, the last, you know, five or 10 years, I think that you should really think of crowded trades and crowded positions as a big source of risk. And options potentially just can magnify that in nonlinear ways, right, as we talked about. And I think that’s a big risk factor, if it turns out that there’s certain types of things that they’re doing that everybody is doing and big size. And then I think, third point, and this can look, you know, there’s various ways that this can manifest itself. But I would want to see that they had at least contemplated thoughtfully and analytically how the strategy should be expected to perform going forward and really thought about, you know, how is the market changed in the, you know, 20 or 30 years of historical data that you’re looking at versus right now, not just a long term bet, certainly not a long term back test, or even a track record, right, because markets in general change over time. But volatility and options markets, I think chain have changed quite a lot. And if someone’s not thinking about, you know, who else is in a particular type of trade that or strategy that they’re doing? How much larger is positioning in that than than it was, you know, 20 years ago? And they’re back tests, for example? And, and how is the how does that affect their forward looking returns? That would be a big red flag to me,
Corey Hoffstein 53:34
as a firm that undergoes a decent amount of institutional due diligence. Are there any questions that you receive, that you sort of roll your eyes at and say, Let’s this isn’t really telling you as much as you think it is? Or maybe a second part of the question, are there any questions that you think you should be asked that you are very infrequently asked?
Benn Eifert 53:57
Let’s see on the on the first point, you know, sometimes people ask about things like, what’s your gross notional exposure? Which is a perfectly fine question, I don’t think it tells you tells you nearly as much. That’s interesting about a relative value options portfolio, you should really be focused on much more specific measures of risk. So just to give you a really simple example, right? Let’s say that someone sells $100 million dollar notional position in you know, downside s&p puts, right so that’s a and they’re $100 million fund, right? So that’s 100% Gross exposure and it’s an option selling type of strategy and that’s you know, that’s fine and you can think about you know, how much risk that is let’s say that instead of selling that put they instead sold a put spread and so they sold a near the money put but they bought back you know, a downside put to limit their risk, right. So in any state of the world with no A discussion about it, that’s a less risky, significantly less risky, much less tail risk strategy, much less tail risk position, but the gross notional is twice as high. And that type of problem, right. So the the assessment, the right way to assess the risk of that position is to look at the scenario risk look at, you know, shocking the market down 10 or 20%, what’s the expected performance of the position, you know, on a one day basis or a hold to maturity basis, for example, look at the forecasted p&l volatility or you know, var of that type of position, those are reasonable things to ask, it’s not a good idea to conclude that it’s a riskier portfolio because it has twice as much gross notional exposure. So I think that’s, you know, one point in terms of what should people really ask about that? They don’t always ask about a whole lot. I think, actually, I alluded to this earlier, but, you know, top down stress, you know, comprehensive, many scenario, stress scenario, analytics, I think are really, really important. And I think that large institutional investors always agree with that, and focus on that and get like to get into it, assessing the overall risk profile of a portfolio in different types of environments, I think that they should care more about in some really do but I think some don’t enough, you know, what some of the hidden assumptions sussing out what some of the hidden assumptions are in those types of frameworks. Because while comprehensive stress scenario analytics are really important, it’s also really easy in some sense, if you are, you know, either consciously or not, to make sets of assumptions that are beneficial to the particular type of portfolio that you have, whether it’s, you know, internal proprietary risk analytics, or third party risk analytics. And I think, really understanding what the hidden assumptions are trying to probe those out, and trying to, you know, look across a wide range of the types of assumptions that might be made in order to assess the sensitivity of the results. I think that’s a really good area. And again, I think there are lots of institutional investors that start to go down that road, but I just think it’s particularly in options and derivatives, it’s crucially important and worth focusing on.
Corey Hoffstein 57:17
So last couple of questions here, Ben, and I’m going to probably jump around a little bit, because I know, I’ve seen you express some interesting views again, on Twitter, and then in some personal back and forth, and I want to make sure I bring those out to you, because I think they’re really interesting points. Another really popular voice in the volatility space has been Chris Cole at Artemis, who has been very vocal for many years now saying that almost every investor is inherently short volatility in some respect. And I know that you actually hold a somewhat slightly different and nuanced view on that subject. And I would love to hear sort of your counterpoint to his view that everyone shortfall.
Benn Eifert 58:01
Yeah, totally, no, Chris is awesome. And a friend. I mean, I think that probably when we’re answering or thinking about that question, we’re just starting, like at a different level of abstraction and thinking about a different level of detail. I mean, I think, you know, he’s really coming at it from the perspective of, you know, risk assets are risky, and everybody’s long risk assets, and the low risk assets have embedded negative convexity. What, you know, my original training, in some sense in the in the hedge fund space was on the Wells Fargo prop desk. And on the Wells Fargo prop desk, one of the types of things that we were very involved in was capital structure arbitrage and capital structure, Relative Value trading within the corporate capital structure. So looking at, you know, the the equity and the secured debt and the unsecured debt and different tiers, within a corporate capital structure, a typical type of model, that conceptual model, and to some extent quantitative prediction model that people would use within that space, you would think of, what is the underlying there’s an underlying distribution of asset returns and returns on the business. And those different securities within the corporate capital structure really represent different types of derivative claims on on the business’s assets, right. So if you’re long equity, in that framework, you’re actually long a call option on the firm’s underlying assets, right? Because if the firm goes bankrupt, you’re going to lose all your money. But if the firm grows and does very well, and you know, in great excess of the cost of repaying its debt, you’re the residual claimant as an equity holder and you own all of the upside, right? And so, whatever that underlying distribution of asset returns looks like the equity owners are long a call on it, whereas the various different credit holders are all short some type of put right so an unsecured the unsecured debt holders might be the next part of the capital. structure, so they have a put, you know, with a higher strike and then the higher, you know, the senior secured notes are low strike put, but very likely won’t be exercised against them. Because there’s, you know, some recovery value in the underlying assets. But if things get very, very bad, then they might lose all their money too, right. So in that framework, you think about equity owners as call option owners. And I think, you know, sitting in Silicon Valley also think it’s very hard to think of venture capital, for example, venture capital is very long risk. But I think most most venture capital investors really think of themselves as buying, you know, portfolios are very, very, very deep out of the money, you know, long term call options. And I think they’re right to think about it that way. Right? They might well lose all of their money, they might well lose them eight out of 10 bets, and write them down to zero, but if you know what, but they all have very wide distributions, and if one of them hits that might pay for their whole fund, right. So benchmarks, initial investments in Uber are a good example. And I think that that, you know, those trades or in those positions are inherently very long convexity. That’s sort of how I think about it. Now, of course, even within Within equities, you know, different types of businesses have very different, you know, return profiles, right. So you could argue that, even if you want to think of equity as a call option, you know, think of it like a utility, right, a regulated utility business, clearly the, the distribution of underlying asset values for a regulated utility, are very truncated on the upside. And it’s sort of all, you know, generating a coupon, you know, with a left tail probability of something really bad happening and the utility going out of business, right, versus versus a really small, you know, growth technology company or something. So there’s plenty of nuance under the hood. But I think that there certainly are securities and assets that are long risk assets, but that are convex long risk assets and long volatility in that sense.
Corey Hoffstein 1:01:51
So I think we’ve pretty clearly established that the volatility space is a landscape that is very complex, both in execution and and in viewpoint. But do you think that there are any options strategies that can play a role in a meaningful role for your sort of average investor who may be starting with the framework of a diverse of diet, you know, globally diversified strategically allocated portfolio? Yeah,
Benn Eifert 1:02:18
I mean, historically, for your average investor, I think, a small allocation to a well managed risk contained option selling strategy has been a very reasonable thing as a long risk portfolio exposure along with their long equities and long credit and everything else that’s that’s in the portfolio. The key things there again, are well managed and risk contained. So not tail risk selling the one point I would raise many of the more popular and this is in some sense, always the way of the world right, but the flavors of risk contained option selling strategies that have become popular, have become too popular and too crowded and forward looking returns are probably a lot lower than you know, the 30 year the 30 year track record. So, a good example is you know, iron condors selling on an unlevered basis, which if you look at, you know, there are there are CBOE CBOE indices, like CMDR for this, you know, where an investor is selling a straddle or near the money, or a strangle and buying back the extreme tails, so that it’s, you know, clearly well defined risk, you’re earning some carry, typically, you know, again, one month, I think that there are versions of these type of strategies that can certainly make sense and probably have legs for five years or 10 years. But I think it’s not the most popular versions of those which are, you know, the one month s&p examples, I think unlevered cash secured, modestly downside put selling, you know, 30, Delta puts is probably the laggard and still the best place to look in terms of, and maybe a few months out, for example, in terms of a part of the risk contained option selling strategy spectrum that’s not overly crowded, although it is starting to grow as pension funds are getting more and more involved. I’ll be at off with a low base. You know, in terms of more complex options and volatility strategies, I think that realistically, it’s just the due diligence required to make sure it’s a well risk managed strategy that is not selling tails is probably too much for the average non specialist investor. And a lot of it, I think, you know, comes down to just really understanding what it is that you’re investing in and being able to ask, you know, a couple of incisive questions, you know, okay, can you send me the risk report for what if the primary market that you’re investing in, you know, goes down 20% tomorrow? And if the answer is, well, here’s why you shouldn’t really worry about that, then that’s just a huge red flag.
Corey Hoffstein 1:04:52
So last question, and I’m gonna have to apologize because I lied to you about what my last question was gonna be. I told you, it’s gonna be the same as season one. One, but this is Season Two. Nice. So we need to change it up. So you’re totally unprepared for this. And the question for you is, if I told you that you had to completely liquidate your entire investment portfolio today, and only buy one thing for the rest of your life, one investment, now it can be a strategy. It can be an asset allocation, it could be an individual security, whatever you want, but you can only buy that one thing. What would it be? And why?
Benn Eifert 1:05:30
Oh, that’s hard, man. And it’s a really good question. I mean, so really, I think, I think, to be honest, the way that I think about the volatility and options space, I think that actually rules out almost anything in the, in the core of what I do, because I don’t think the world is static enough to have good confidence around that. I think that the world changes and good opportunities, attract, you know, follow on money and things get crowded and lose their attractiveness. I think that really and it’s an incredibly dissatisfying answer, I would think, but I think if I could only make one, you know, long term investment for the rest of my life, it would probably be, you know, tier one emerging market equities, something that effectively, you know, represents a bet on the long term convergence of the world on, you know, the increasing sophistication of the India’s and the China’s and Brazil’s, you know, over the long cycle, to grow productivity and raise the, you know, raise the standard of living of their populations in the workforce and all, you know, I think that it’s an inevitable long trend and will be a very choppy path, though. I think that’s, you know, if I had to make the 60 year long term bet, I think that’s probably what it would be.
Corey Hoffstein 1:06:49
Then you’re, you’re a good sport. I’ve had a lot of fun chatting with you. Thank you so much for joining me today.
Benn Eifert 1:06:54
Absolutely. Cory, it was a lot of fun. Thank you so much for having me.