Podcast Transcript: Benn Eifert On Retail Options Boom, Over-Complex Derivatives, and Managing Tail Risk

This is an edited transcript of our podcast episode with Benn Eifert, managing member and CIO of QVR. We talked derivatives post GFC, how to manage convexity and tail risk, common quant mistakes and whether short vol strategies work. While we have tried to make the transcript as accurate as possible, if you do notice any errors, let me know by email.

Benn’s Background and Career Path

Bilal Hafeez (01:41):

Now, Ben, if you’ve heard any of my other podcasts you’ll know that I always like to start my conversations with a question around your background. Currently, obviously you’re at QVR, which is an alternative strategy quant fund and advisory firm, but presumably you didn’t start at QVR. So, what’s your origin story? What did you study at university, and then what did you do after that, and how did you end up where you are now?

Benn Eifert (02:04):

Sure, absolutely. I was actually an emerging markets macro economist back in the day. I was an undergraduate in economics. I went to work for the Chief Economist of the World Bank for a few years, working in India, Africa, and a variety of places. I then went back to Berkeley to do a PhD, worked with some really great folks there. Decided about halfway through that academia wasn’t really my bag. Got interested in finance, started doing some teaching and a master’s in financial engineering program at Berkeley, and through a variety of things, ended up spending the last year and a half or so of graduate school mostly working full time for a hedge fund.

Then, when I finished my PhD, I went to Wells Fargo’s prop desk. The Wells Fargo prop desk certainly wasn’t the most famous of the prop desks. People think of Goldman and Morgan and those guys back in the day. But the important thing about the Wells’ desk was that through the credit crisis, I’m sure you’ll remember, Wells Fargo was one of the banks that actually was in a position of great strength, primarily owing to the fact that they weren’t very smart and sophisticated and just weren’t involved at all in structured credit and any of the stuff that got other folks in trouble.

And so, while all the other prop guys around the Street were getting shut down, we were able to get very strong backing from the bank and took a ton of risk and had a ton of capital on the balance sheet. Then, we were very aggressive all throughout financial markets. I was a quant on the desk. I was the first quant hire, I built and grew the quant team and ran it over time and built a lot of the risk systems and analytics and so forth for the firm. The prop desk did extremely well through that period in the aftermath of the credit crisis, and then it spun out as a hedge fund called Overland Advisors. That would have been 2009, 2010.

I ended up managing some of the non-traditional assets like derivatives on currency volatility, for example, in the center hedging book. And then, a gentleman named John Loughlin, who would later become my partner, joined the firm. He had been a managing partner at Blue Mountain and had started the Blue Mountain Equity Alternatives Fund, which was one of the really pioneering relative value derivatives trading funds in the mid-2000s. John and I got along really well. I went to work for him, and hired a replacement to run the quant team. We built a portfolio there at Overland, and then we later left to start a fund called Mariner Coria on the Mariner investment group platform. Then in 2017, I started QVR here in San Francisco.

How Derivative Markets Changed After the 2008 Financial Crisis

Bilal Hafeez (04:40):

Oh, great. So, you’ve seen a lot of the ups and downs in the quant side of the derivative space in your career. I guess one question I would have is, was the Global Financial Crisis was a big form of structural break in terms of how the industry operated? From the derivatives perspective, what types of things were happening before the financial crisis or before 2008? Say over the 2000s, or late ’90s, 2000s, what was happening then, and what’s changed after the financial crisis? If there was a before and after, how would you characterize it?

Benn Eifert (05:11):

Absolutely. That’s a good question. So, there have been huge changes in derivatives markets over this period of time and the financial crisis was in some sense, the catalyst for the changes, but most of the big changes didn’t actually happen for several years after the crisis. I will explain what I mean a little bit.

Before in the pre ’08 era, think of late ’90s, or early 2000s, as was marked by the rise of complex, structured, exotic derivatives trading across the Street with hedge funds and asset managers and insurance companies, and it was really a Wild West market. There was huge risk taking and risk tolerance among banks and among their counterparties, tremendous increasing amount of leverage, increasing complexity and sophistication of products, much of which led to hidden tail risks and so forth, as it later materialized in a way. But really, banks were very happy to trade with aggressive relative value hedge funds; they would allow them to trade at mid-market all day long, and would do almost anything that you wanted to in big size.

There was a tremendous appetite for large volume for executing transactions. Banks really viewed that in part as just a franchise business. It wasn’t just about the trade that you just got done with a hedge fund and the sales credits you booked on that, or the bid offer spread you booked on that. It was also about the franchise, about growing, about being the biggest and the best so that when the corporate business came in, they’d see that you were the number one equity derivatives house, or the number one fixed income derivatives house. And they wanted to deal with you in that, not the other folks.

Bilal Hafeez (06:50):

Do you think the banks at that point understood the pricing of the products they were selling, or even the clients, do you think people understood the complexity they were taking on? Or did they ignore it intentionally almost just to just get volume, or what do you think people’s perceptions were of the risks of these products?

Benn Eifert (07:10):

I think they were very heterogeneous. You speak with banks as if they’re one line. But within a bank, there are sales managers, there are risk managers, there are traders. And at all points in time, it’s a push and pull between who has the power to get things done, right?

I think that you certainly saw, during the explosive period of growth, quite a lot of mis-modeling. There were many famous instances – for example, there was a large Swiss bank that discovered retroactively the huge losses they’ve incurred winning many trades on forward skew sensitive instruments because they were pricing complex forward skew trades that had sensitive exotic components with local volatility models. You can get in to a long discussion about why that doesn’t work. So, there was a lot of that.

But over time, I think there are many very smart quants, and many very smart risk managers that understood or had a better sense of some of the rest, of their complexities involved. But when a franchise is making money and volumes are making money, it’s very difficult for the lone Risk Manager to move the needle at the table with the Head of Sales who sees those sales credits. That’s just the nature of the beast. So then, risk managers become more empowered after big losses, and that’s always been the cycle.

Bilal Hafeez (08:18):

That’s a fair point. Yeah. I want to talk to your bank over that period before and after the crisis and thought your bank was one of the big players in the growth of derivatives. Who had the power? Was it the sales, or was it the risk guys? And as you said, during boom times it’s more the sales and the franchise side. And then later it’s more the risk guys.

Benn Eifert (08:39):

Yeah. That’s exactly right.

Bilal Hafeez (08:40):

And in terms of examples of some products that you would highlight as the examples of products in that era.

Benn Eifert (08:47):

Sure. So, we were always more on what you would call the vanilla and light exotic side so things like variance swaps, volatility swaps, and forward starting volatility agreements, but we also could get into correlation swaps and covariance swaps. There was exorbitant breadth and depth in the structured exotics that folks, including hedge funds, would trade. Think of it, at the height of the mortgage bubble – some of the most famous examples that everybody knows are CDOs and CLOs, of course, how you slice and dice credit exposures into tranches – but in the relative value space, you had large famous credit funds quoting very esoteric micro-tranche structures on ABS, that were very explicitly designed to be so complex and difficult to price that banks would have problems pricing them. And then those hedge funds would be able to get very attractive pricing from finding some bank that didn’t really do it right.

And so, the breadth of that activity and the scale of the risk was really dramatic. And then what really happened through 2008 – the credit crisis was, of course, a period of incredible stress on financial markets. There was great illiquidity in some pockets of the credit markets, especially right where the deepest information asymmetry was present. What was this stuff really worth and who’s holding it and who has to sell it?

But I think in hindsight, certainly from the perspective of today, one of the most surprising things about derivatives markets through 2008, I think, was how relatively liquid they were and how it was actually possible to quote and trade in very big size and do aggressive trades with lots of banks, even through the deepest parts of the credit crisis. And there are a variety of explanations for that. Certainly, one of them is that, or one slightly sarcastic one is that, a lot of the traders on the desks were pretty excited about the idea that if their seats didn’t work out, getting a job at a big hedge fund can be facilitated by quoting them some really good prices.

But in any case, you could still actually transact in big size and have a lot of banks show up to make prices in things like equity index variance derivatives, for example. In the end, the thing that really broke that market environment was the Dodd-Frank Act and Basel III – the widespread regulatory changes that were initiated in response to the credit crisis. A lot of the rules initially got drafted back there in 2009, 2010, but the real implementation didn’t start to bite for a few years down the road until 2013, 2014.

So, you started to see banks being subjected to a much broader array of much more precise stress tests, where you saw banks subjected to LCR (liquidity coverage ratio), wind-down ratios, much tighter regulations, and much higher capital requirements. The traders that we dealt with – even mid-level, VP-level book runners at banks – were getting asked questions by the Fed staff sitting within the bank, looking at their risks – e.g. down 30%, why do you lose X amount of dollars? This was just totally unheard of previously. The regulator’s perception, correct for the most part, was that ‘08 was a systemic crisis created by banks taking far too much risk and holding far too much inventory in complex products. The regulatory response to that was to have banks take much less risk and act more like agents and less like principals – to use less balance sheet, and to have much tighter restrictions. So, in some sense, the regulators got what they wanted.

One of the results of that was that, where you used to be able to quote 8 or 10 banks on a particular trade, gradually only 7 of them would come back with a market, and then 5, and then it was 3. And the size they would come back with was half, and then it was a quarter relative to what it was before. And the spreads were twice as wide, and then they were four times as wide. And dealers would need to work very hard if you came and asked for a price, they would say, “Okay, just give me a half an hour to check around.”

And they would also be trying to effectively act as agency-only brokers – to try to specifically line up the other side of the risks to do some transaction, rather than being able to actually take principal risk. And from the perspective of a client, that meant that it was much harder to get the trades that you wanted without paying a lot of spread and have them in meaningful size. And I think that environment really persists today, where the liquidity in derivatives markets, while it has grown overall, has moved really away from this complex market of banks, intermediated risk, and OTC markets to exchanges. So you’ve seen huge end user growth on exchanges.

The Centrality of Listed Derivatives

Bilal Hafeez (13:24):

That basically means that the products become less complex then as well, if everything moved to exchanges.

Benn Eifert (13:31):

Yeah, that’s right. There are, periodically, exchanges that try to list more complex products. For example, variance swap futures have been something that CBOE has tried over and over and over again to get to stick, but for the most part, the products on exchanges are listed options, things like VIX futures, options on VIX futures. You get into options on leveraged ETFs in volatility land – that’s actually a relatively complicated product and retail trades a lot of that type of stuff. And you can even raise some questions around that, but certainly, you’re not trading the bespoke complex hybrid, the path dependence, exotic types of structures on exchange.

So, that market still exists in a way but it’s really shifted, again, away from this two-way flow and big size between banks and the hedge funds and more into long-term risk transfer, where banks try to buy back tail risk and exotic risks that they don’t want to hold from hedge funds and pension funds. And that’s a little bit of a toxic one-way pick off market. In some sense, you saw that play out very poorly last year, for example. That’s really where a lot of the OTC volatility and derivatives trading has concentrated, away from the liquid two-way flow that you used to see on OTC and now you really see an exchange.

Why Understanding Supply-demand Dynamics is Important

Bilal Hafeez (14:50):

And so, if you are a trader in this space they want to fund, like yourself or other people that you know, how do you build an edge in this area? Because you can imagine the old days, because there was a lot of complexity, a lot more capacity, there was a perception that you can play around with more the moments of the distribution, so to speak. But now you’re more constrained and things are more transparent. Does that mean you have less of an edge?

Benn Eifert (15:14):

Yeah. I think it’s a reasonable theory that edge should come with complexities. I think in practice, it’s completely wrong. And when people tell you that they have edge in the complexity, what it turns out is that they’re really just taking some hidden non-transparent tail risks and either they realize it and they’re not telling you or they don’t realize it.

In a sense, keep in mind there are no options. There are of course, exotic payoffs that you can synthesize with listed options, but listed options fully imply the entire distribution, the joint distribution of volatility and spot. They’re extremely flexible in terms of the types of relationships that they can create. And when you think about where does edge in the derivatives market come from in the first place? I

think this is something that it’s very obvious in a sense but I don’t hear very many people say it. People make it sound like it’s all really complicated and “that’s why there’s an edge because I’m smart.” That’s crazy. Derivatives markets are very different than long/short equity, for example. In long/short equity, there are some stocks out there and there’s the zero-sum game of smart people to figure out which ones are the right ones to be long and which ones are the right ones to be short. If you get it right, and the other guy gets it wrong, you make money.

Derivatives markets exist because of the end user, because of the end client base – retail investors that are buying structured notes to get some long-term exposure, or of corporations that are trying to hedge their fuel price exposures or their currency risks, or pension funds that are trying to customize the upside downside profile of their portfolio. And some of these organizations are more sophisticated than others, but they all share the basic premise that they’re trying to achieve some objective that is typically a straightforward economic objective.

The market is not one that’s hyper-focused on the arbitrage properties of second-order skew of a surface or something. The clients don’t care at all about that stuff, whether or not they know. They care about the payoff profile they’re getting; they care about the hedge offset they’re getting; and they care about getting the trade they need in the size they need when they want to do it. And they pay a large amount of transaction costs. And collectively, the whole market of end-users of derivatives pays for a lot of market impact in transaction cost into the market to achieve their objectives.

And in that pool of transaction costs, the market impact is the return opportunity set available to market makers and to secondary market participants in derivatives that have to warehouse that basis risks – that have to be there to sell the expensive thing and buy the cheap thing that’s created by dislocation in derivatives markets when there are large persistent flows from end users. And so, the entire game is about understanding that, understanding how to measure dislocations in derivatives markets that are driven by end-user flow, and how to capture those dislocations while managing risk appropriately. It’s not about somehow having a better super stochastic local volatility model that has this one parameter that nobody else knows about that’s properly calibrated and that’s like the secret to making money. That’s what many people would have you know, but it’s just not true.

Bilal Hafeez (18:25):

Does that then mean that you need to have a really good awareness of the supply-demand dynamics in the derivative market?

Benn Eifert (18:32):

Absolutely. That’s fundamental to our understanding of where mispricings and dislocations come from and how to distinguish between a real dislocation and something that really is a price change driven by some underlying macro factor. That’s a real thing. Imagine going back to 2012, for example, and think of the Nikkei. Abenomics was just getting going, and the Nikkei had been on a slump for 30 years and suddenly the Nikkei started to rally and the Nikkei skew and the equity market went inverted, so call vols were trading above put vols. For an equity guy, that’s very weird. Generally, in an equity index downside put vols trade higher.

If all you do is look at charts and measures these scores…everyone noticed and you had a variety of people do things like sell a bunch of upside calls to buy downside puts. Because they settled the skew was just crazy. This is some mispricing, but it wasn’t a mispricing. It was a bunch of smart macro investors buying a ton of calls because they knew that there was this huge regime change in Japanese economic policy that was about to drive a highly volatile rally in the Nikkei. And that’s what happened, the Nikkei doubled in relatively short order on very high volatility. And if you were short calls, you just got destroyed. So, the point is, just because some variable is up to 95th percentile or z-score of 2 relative to history, doesn’t necessarily tell you that that’s a dislocation caused by someplace in sensitive actor that’s exploitable in some meaningful way.

You need to understand what’s driving dislocations. What are the supply and demand patterns? You want to be on the other side of effectively providing liquidity to the market, on the other side of smart macro investors, unless that’s your game. If your game is being a smart macro investor, that’s fine. But then, you’re back in zero sum world [of directional trading] where you’re just betting against other people on whether or not you’re right.

Bilal Hafeez (20:29):

Yeah. Yep. That makes sense. And you mentioned that example of the calls being more bid than puts, we can have a similar dynamic today with VIX, VIX is remaining quite elevated, even as stocks are rallying. How do you see that?

Benn Eifert (20:45):

Sure. I think a lot of people correctly know that there is, on average, an inverse relationship between implied vol and stocks and infer from that, that somehow, if we’re at all-time highs in stocks, we have to be at all-time lows in vol, which is not true at all. Volatility is the second moment of the distribution. If you’re having a volatile or relatively volatile rally or a rally that has a lot of downside risks, then people are buyers of options and volatility can remain elevated over extreme historical lows. And that’s perfectly natural.

We’re in a world right now where every month, there’s a new 5 or 10 standard deviation event somewhere in markets while underlying liquidity conditions are super fragile. There’s huge retail buying inflows and short-dated options all over the place. You’ve got companies like GameStop doubling or getting cut in half every day. This is not a VIX 12 environment; this is a VIX 20 environment. And will VIX eventually one day go back to 15, or 14? Sure. But not in this market.

The Impact of Retail Trading on Volatility Markets

Bilal Hafeez (21:50):

Yeah. And you mentioned retail trading. Is that a more recent phenomenon over the past few years, or has that been something that’s been going on for longer over the last say 10 years?

Benn Eifert (22:00):

No, that’s a very recent phenomenon, really. The origins of the big upswing in retail trading and options trading in particular date to later 2019 – you can really see it in the data when you look at small trader accounts, option volumes, account openings across all the major retail platforms, Schwab, and TD and so forth. You see a significant uptick starting in mid-to-late 2019. Late 2019 is actually when a lot of the competing brokerages moved to a zero commission model.

Robin Hood was the one that a lot of people focused on, but many of the other brokers moved to match that. I don’t know if it was the original cause, I think there’s probably a variety of causes, but that really amplified this trend of rapid growth of retail trading and retail volumes. Then, when the COVID crisis hit in early 2020, you had a lot of people sitting at home unsupervised, able to trade on their personal computer while they were doing work, or maybe they were unemployed and have lots of time anyway.

And I think that also dramatically amplified the trend. And what you’ve seen is just parabolic growth of retail trading across the board, most notably in options, and especially in short-dated options. So, if you were to look at call option volumes amongst small trader accounts, they’re up 10 times versus levels three years back, for example. And a lot of that is in extremely risky types of trades – things like buying far out of the money one-week options where the default outcome is just that you lose all your money. Because the stock doesn’t go up 30% or something like that. So, this is a huge trend in option markets.

It’s something that I think a lot of investors didn’t pay much attention to until very recently, especially after the GME (GameStop) episode in January. Volatility and options managers had been paying attention for a while because these flows are huge. You got a lot of people, I think who very naively say, “Oh, retail is not important, retail’s small, retail doesn’t have that much money.” Retail option trading volumes are astronomical, because you’re talking about collectively many, many millions of people. There’s the stereotype of college kids with 500 bucks in their account – I’m sure there’s some of that, but it’s really all of the 20 something-year-old professionals in the United States. Go talk to your law firm, or talk to your accounting firm, the VP-level 28-year-old kids all have Robin Hood accounts and they’re all trading options.

Bilal Hafeez (24:47):

And what’s the implication of that retail trading then? Does it mean that the short-dated vol surface gets heavily impacted by these retail guys? Is that the opportunity you have to focus on then?

Benn Eifert (24:57):

So, it does definitely affect the short-dated volatility surface a lot. And yes, it’s a good area to focus on. I think like many things in derivatives markets, it’s more complicated than just, “Oh, so retail is buying something, so you’re supposed to sell it.” The world doesn’t always work that way.

One implication, from the very heavy short-term option buying, particularly on smaller single names, is that the other side of that position is going to sit with dealers and market makers. So, dealers and market makers are going to be short a lot of gamma and a lot of convexity and they’re dynamically hedging those positions.

If you take GME, for example, where retail buys a ton of next Friday, 40% out-of-the-money, 30% out-of-the-money calls and GME stock is going up. So first of all, the leverage the retail investor gets in those products is very high, because instead of buying a share of the stock, you can just buy a call option that might have a 10 Delta, but it might only cost 40 basis points or something. So you’re getting some humongous leverage. And then, second of all, as the stock rallies, that delta is going from 10, to 20, to 30, to 50. This causes the market makers and the dealers to be buying, and buying, and buying the underlying just to maintain the hedge.

And so, that dealer gamma implication, where big short-term call option buying creates amplified realized volatility in the direction of the strikes and buying is very powerful. You can get run over real quick if you look and you say, “Oh, that vol just went from 30 to 35 on retail buying. So, I have to sell a lot of it.” You need to be real careful.

Do Short Vol Strategies Work?

Bilal Hafeez (26:34):

Yeah, of course. Yeah. I guess the gamma profile of the market then goes against you, if you’re trying to short it, in that scenario. And just more philosophical question here, one of the very common strategies people have, and I guess this is also linked to some of these flows, is to systematically sell vol. You mentioned earlier that there’s lots of structured notes. Implicitly, what many of these types of strategies and products do is they’re just implicitly short vol to capture some of the risk premia. Do you think your vol selling strategies should fundamentally work over time or do you think it gets arbitraged away? Or do you think that it depends what part of the curve you look at, so it’s further out the curve now than before? How do you think about short vol strategies?

Benn Eifert (27:25):

Sure. I think the first important thing is that short vol is a tremendously broad word. There’s a million different types of things that are one way or another short vol. And they’re all very different. If you were to take just the example of the most popular types of things that are relatively safe (in a sense), they’re not focused on selling extreme crash risk, but things like call overwriting strategies, or iron condor-selling strategies, shorter-term more limited types of option-selling strategies.

Those strategies are designed primarily to in some way capture or benefit from the volatility risk premium, usually in the shorter-dated part of the curve. So, that risk premium was relatively high for a long period of time. A lot of folks really noticed that. Consultants started to write white papers about it and suggest call overwriting and cash-secured put-selling strategies pension funds. By 2013, 2014, you saw huge inflows into those strategies.

And then, that risk premium started shrinking. And it eventually shrunk to around zero right before the COVID crash. Then of course, there was the COVID crash and that generated strong negative performance for a lot of those strategies. Now, I think the jury’s out. Volatility risk premium hasn’t been realized fairly consistently again since the COVID crash, as volatility has come down. Well, the jury’s out on when things will stabilize.

But to your question, there’s an equilibrium in the long run. In some sense, there absolutely should be a volatility risk premium, because there should be an equity risk premium, you should get paid for taking risks. And if you’re earning no return, taking a lot of risks, and doing that for a long enough period of time, you’re going to underperform. And eventually, some money’s going to flow out of that and so forth. So, over the long run, there has been a volatility premium, and then in general, you should expect there to be one.

It’s a different question, when you look at strategies that are extremely levered into the tails – so selling variance or selling options on variance etc. It’s harder to tell because your statistics, in some sense, are all about, “okay, there been three crashes or four crashes over X period of time. How much did you make versus how much did you lose?” What is the probability of 100% realized, of all months? Well, we had one instance in March. What’s the probability of 200% or 300%? None of us know, right? It’s some small probability. Everything depends on whether it’s a 10th of a percent or a 100th of a percent. Nothing about the world lends itself to know the answer to that question.

How to Manage Convexity and Tail Risk

Bilal Hafeez (29:55):

That’s true. And then in terms of you mentioned some structures you thought about the convexity. Do you think people don’t appreciate the convexity risk they’re taking in lots of the structures they have on?

Benn Eifert (30:08):

Yeah. I think that people don’t always necessarily think through how the risk in their portfolio will evolve as things happen. That’s essentially the same thing. It’s related to the point about the difference between simple vanilla risk-contained strategies like I was talking about and variance selling.

For example, the reason that variance swaps are popular is mostly due to the perception that they’re simple and give very clean volatility exposure. If you have a variance swap and you sell it at 20 (at least to a first order approximation), and if it realizes 19, you make a dollar. If you sold it at 20 (1 x your vega notional) and it strikes less etc. Those things are all nice, but the important thing about a variance swap – the main feature is that if volatility doubles, your volatility exposure on your position doubles. And if volatility expands by four times, your exposure expands by four times. If you’re short that convexity – that’s a very horrible risk property of a position. Because when you’re losing a bunch of money, your risk grows and that happens without bound.

And so, you had folks in March, for example, who didn’t think of it as selling tails, but had a lot of spread trades in variance, where they were long, for example, EuroStoxx variance and short S&P variance, or long Nikkei variance and short S&P variance. And they said, “Heck, this is a hedged relative value trade. I’m not short tails. I got a long, I got a short – it’s vega neutral.” But if you have a long and a short in variance, again, the same thing is true. There is a risk of that position growing without bound, as volatility moves higher. And if it’s moving against you, potentially, it’s moving against you catastrophically. Whereas if you have that same position on just listed options, or even in volatility swaps, which is the less nuclear cousin to variance swaps, you’d be in much better shape.

Bilal Hafeez (32:10):

Yeah. And from your perspective then, do you put tail-risk strategies or convexity strategies on for profit? Or, do you think about it more in terms of the risk of your portfolio or your client’s portfolios?

Benn Eifert (32:24):

Yeah. It depends on the problem that you’re solving. We run absolute return hedge fund strategies and we also run tail risk mandates for investors – those are two very different things. The way to think about a tail risk mandate is very much in a portfolio or an overall asset allocation context. It’s not a standalone strategy. The point is, you have an investor who is a big asset owner, who owns $10 billion worth of equities or whatever it is, and the problem they’re trying to solve for is the long-term growth of their overall capital base. And one really important thing about convexity and tail risks is that you can have a defensive long convexity, long tail strategy that loses money, on average, over time on its own.

But it can be added to an asset allocation where there’s rebalancing every month, every quarter etc., between the hedge and the underlying portfolio. Thus, if the market’s rallying, the investor’s making money on their equities and they’re losing money on their hedge. But then, if there’s a crash, they make a ton of money on their hedge, and they’re losing a bunch of money on their equities. What that rebalancing allows for, is that the portfolio tends to suffer much smaller drawdowns in that market crash and will have a lot of cash buying power for distressed assets down there at the bottom, and then the opposite during rallying periods.

And you can end up not just with a lower risk profile of the other overall portfolio, but with a higher compound growth rate of the overall portfolio, because of the complementarity of risk assets and a hedge. Making a lot of money in a negatively correlated way, i.e. in the worst environment, is very powerful for the overall portfolio.

Bilal Hafeez (34:09):

What’s an example of a hedge there, if you imagine a pension fund with a roughly 60/40 portfolio say, in that context what would a typical hedge look like?

Benn Eifert (34:20):

Sure, you could just think of 6 to 12 months, 20-delta put options. Generally, for hedged portfolios, one doesn’t want to get overly complicated, but one wants a simple, liquid, and really cost-efficient way of hedging. It tends to be somewhat further out in the term structure, because very short-term options usually have a lot of decay and therefore are a better match for more dynamic strategies or for expressing a tactical view. But something like that, that’s relatively low bleed and tends to lose money over time, but makes a lot of money at the worst time for the rest of an asset owner’s portfolio. The key thing is the interplay between the core portfolio and the hedge and rebalancing between the two.

Bilal Hafeez (35:04):

Yeah, understood. And then, what’s the alternative scenario when you’re running an absolute return fund? How do you think about some of these types of strategies?

Benn Eifert (35:17):

Yeah. So, in an absolute term strategy, the objective is for the overall strategy to make money over time in an uncorrelated way, rather than to have an interplay with another portfolio in this rebalancing dynamic. So, there’s a couple of ways that an absolute return trade can potentially perform on a forward-looking basis. There are symmetric types of opportunities where it’s a hedged long or short type of position or strategy, which has a relatively symmetric distribution with a positive mean. On the other hand, you can also have significantly positive expected return trades that have a 90% or 95% chance of being flat and a 1% chance of making a whole bunch of money in some crazy events – essentially a very cheap or free option.

And certainly, I think culturally, a lot of the types of people who had liked buying cheap options weren’t around anymore by the time the March hit. Unfortunately, you had this big cultural shift towards more short-vol strategies. But for us, we’re certainly happy in an absolute return context if we find trades that look like they might offer that profile: very low expected costs or no expected costs for a potential asymmetric win. Those are great opportunities and one can put them in the portfolio and not worry about them too much. And then if the appropriate event hits and they work out, then that’s great.

While they might pay out during market crash, for example, there isn’t the same logic as there would be behind the explicit tail risk strategy, where you have this long equity portfolio or long risk assets portfolio and you’re trying to compliment it in a very explicit way.

Derivatives to Replace Bonds as Safe Haven Hedge?

Bilal Hafeez (37:09):

Understood. And in terms of the clients that you speak to, you advise and so on, say over the past six to 12 months – what are the biggest challenges or questions they come up with?

Benn Eifert (37:21):

Absolutely. So, it’s been quite an evolution in the last year. Because immediately after COVID, there was this incredible market drawdown. And then, if anything, I think you saw the greatest desire among clients just to plow money into a lot of the types of assets that have gotten heavily beaten down, even while folks were hurting. In general, I think clients weren’t too conflicted about what the right thing was to do. They were buying credit; they were buying equity. They were investing with hedge funds that had been closed for a long time that temporarily opened up. There were a lot of opportunities out there that people saw.

Now, once you get to where we’re sitting now, with the S&P at nearly 4,000, I think that the common perception that a lot of asset owners have is that beta has rebounded much better than they could have ever imagined. They’ve lost most of the perceived diversification benefit of fixed income in their portfolios. Now, you can argue, okay, rates have moved higher this last month, and you can get into some arguments about, okay, at what point is the 10Y a better diversifier again. Certainly, at 160 basis points it looks a lot better than it did it at 60 basis points. But you have a very common notion that that the expected diversification benefits you’ve got in the offset between the 60 and the 40 won’t be realized with rates at zero and long-term yields near zero.

So, common questions people asked were, “What do I do with my fixed income allocation? How do I get uncorrelated return streams? And how do I get an offset to my equity portfolios?” That I think has been a very common theme.

Bilal Hafeez (39:00):

And do you have a view on whether the fixed income is an adequate hedge at the asset level or not?

Benn Eifert (39:08):

I think everything depends on price, I think that at 50 or 60 basis points on the 10Y, you had to make a very tough argument to think that there was a lot of diversification. You could argue, “Okay, if we had a big shock here, yields could go very meaningfully negative. We could go to negative 50 basis points.” You can tell that story and you can argue that point, but it’s tough. It’s a tough one. From there, we’ve since backed up 100 basis points plus. In yields, 1.7% is still pretty low, especially with the economy looking like it’s going to grow pretty strongly. But yeah, at some point in this range, it still compares well globally to where yields are. The appetite for U.S. fixed income is pretty strong from Europe and Asia, and that’ll probably continue. And if you’re starting at 160 or 170 basis points – for every 20 basis points, you back up and think about all the incremental demand from those investors that didn’t really like bonds at 60 basis points, but at 200 basis points, that 10Y looks pretty good for as a diversifier. So, I think that the narrative around is fixed income, “should it be a part of my portfolio at all?” will start to fade as yields keep pushing higher from here.

What Risks are Investors Focusing on Since COVID?

Bilal Hafeez (40:17):

Yeah. And then do you think about all of these big themes that people are discussing these days? Could we get an acceleration of inflation, stocks are overvalued, do you take these and these things? And secondly, do you think it’s useful to take these on these things?

Benn Eifert (40:35):

So, there are certainly people who make their living out of taking those views. Because of our strategy, we think it’s much more important to understand those narratives in the marketplace, understand who shares those narratives, how dominant they are, and what the positioning around those narratives is, and how that’s going to affect how markets might behave in different scenarios rather than forming those views or taking a side on a view. Again, it’s really dislocations between related variables and related products that we’re interested in. It’s really flows and positioning that drives a lot of the opportunities.

Is inflation going to be 2.7%, or 2.4%, or 1.8% over the next 10 years? Now, that certainly matters a lot for asset owners’ portfolios. We work on the solutions side of the business and tail risk hedging, and so forth. We certainly work with folks to think through those questions in terms of portfolio implications and how to structure hedges, but we don’t make our living on establishing that view of whether 2.8%, 2.4%, or 1.8% is or isn’t going to be the number.

Benn’s Research Process and Productivity Hacks

Bilal Hafeez (41:49):

Yeah. Yep. Understood. And on the flows and positioning side, the information you use there, is it generally publicly available information or do you have access to some data sets that other people don’t have access to?

Benn Eifert (42:03):

It’s generally a combination. For example, if you want to see the positioning of investors in VIX exchange trading products (in terms of what volatility exposures they have on by using those products) – that’s publicly available and you can work that stuff out for yourself. But there are also a lot of things that are in the middle. So certainly, you can understand things like – sudden sharp moves in markets usually comes from some combination of hedge funds (levered money being excessively net long and/or with excessive gross exposure), interacting with the option market micro-structure, where dealers are relatively short gamma. A lot of the various pieces of information are accessible to different investors one way or another. And the question is, how do you put all those pieces together in a consistent framework? That’s not a trivial thing.

Bilal Hafeez (43:00):

Yeah. I used to work with Ciamac Moallemi at Nomura and I actually had him as a podcast guest and he tends to track lots of these things quite well. I’m not sure if you follow some of his work.

Benn Eifert (43:09):

Yeah and more importantly, his incredible mustache.

Bilal Hafeez (43:12):

Yeah. It’s quite impressive mustache and beard. And it keeps growing every time I see him. And yeah, while we’re talking about more personal things, I always like to ask my guests not about their facial hair, but rather about their other habits. You obviously do a lot of research. You look at markets in a lot of different and interesting ways, how do you manage your research and information flow? It’s quite easy to get overwhelmed. There’s a lot of noise out there. How do you manage this?

Benn Eifert (43:43):

It’s a good question. So, we, at QVR, are very process-driven and internally-driven. So, on the absolute return side, we have a variety of specific strategy themes that all have a significant research base behind them. There, the continued research is incremental, such as improving something, getting a new piece of data that would fit within the framework etc. And then, we have a pipeline of new strategy R&D, but that’s much more like large projects that we’ve effectively been working on for 15 years and are pushing a little piece further one bit at a time. And there’s being a collection of those projects in a very structured process and workflow around that, as opposed to coming in every morning and looking for interesting topics, looking for an email that gives you a hint to go look at your Bloomberg or something like that.

So, we’re much more in the systematic research camp. And of course, there are things that get you started on some new idea, but I think people overestimate the importance of “blue sky imagination”, where you sit down in your chair and you have this light bulb go off and come to some truly unique insight, as opposed to the blocking, tackling, and carpentry of excellent ideas across a broad pipeline of what you are doing.

Bilal Hafeez (45:06):

Yeah, absolutely I’ve always found that as well. The waiting for inspiration – it just never seems to happen with me, and so I just have to plow away at the day-to-day and then therein, all the ideas will come out at. But, have you always worked in that process approach? Is that just part of your personality, or is that something you’ve learned over time?

Benn Eifert (45:26):

It’s certainly been an evolution, but we have essentially been running a very similar investment process for a very long time. When I started my career, in some sense by definition, when you’re young, you’re much more either on an existing team where you’re working with a boss and following his instructions and learning, or in my case, a little bit more, you’re sitting on a desk as the quant and working with senior portfolio managers and traders who have ideas and have things they want to do. You’re very responsive to those ideas and you’re working with them to try to think of how can you capture that idea? How can you build it into software and the way that someone’s explaining it and so forth.

And so, it’s less about independent research and just coming up with new ideas as it is about understanding the world better, working with really smart people, like the folks that I grew up with at Wells Fargo’s prop desk, to understand markets the way that they do and to capture the logic they’re thinking in math and code and so forth. And so over time, you really build that capacity to do independent research and then build the process for yourself etc. But I think you inevitably don’t start there.

Common Mistakes by Quants

Bilal Hafeez (46:34):

Actually, that kind of brings up a question in my mind, what do you think the most common mistakes are that people in the quant space or the derivative space make?

Benn Eifert (46:43):

Great question. I think that first of all, over complexifying things is innate problem that a lot of more junior folks have, related to that is trying to pursue the direction of very sophisticated, very complex, structured models that are used for exotic derivatives pricing, or that appear in academic literature. In some cases, there are uses for those things, but they tend to be very specific and very narrow. And usually at banks on an exotic desk, that process is managed pretty well, but when a more junior quants sits down outside of that kind of environment, then they’re thinking, “Okay, where am I going to find an edge in option pricing? I know I’m going to try to calibrate the newest, fanciest crazy model.” That’s not where edge comes from.

Benn Eifert (47:33):

Again, I think focusing very heavily when you’re a junior in your career on learning from people who’ve been in the business for a long time and understanding how you can use the skills that you have to attack the real problems that people have in this business, I think that’s really the key.

Bilal Hafeez (47:55):

Yep. That makes sense. Yeah, absolutely. It’s funny when I look back at my career early on, I definitely was in thrall of complexity and just using the latest quant techniques. And then as the years have gone on, I use less and less and less. I think it’s becoming simpler and simpler and simpler, it is an inverse relationship with my years of experience.

Benn Eifert (48:13):

Yeah, exactly. And I think luckily, it’s the direction the opportunity set has gone in derivatives markets as well in my view.

Benn’s Book Picks

Bilal Hafeez (48:20):

Yeah. The other question I wanted to ask was on books, I love reading books, I always like to get recommendations from other people, but have there been any books that really influenced you of your career or books recently that you read that you really have enjoyed?

Benn Eifert (48:33):

Oh gosh, there are many, many great books that I’ve read in life. I would say that I read one that I really enjoyed personally was The House of Morgan, which is about the Morgan Stanley and J.P. Morgan empire from its origins. But it’s really a book about the history of financial markets globally, the development of international trade and facilitation of that trade by the banks, some formation of the modern global financial system. I think it’s the kind of thing that it’s very difficult for people to understand how a lot of these things work when they just sit down at their computers and get their Bloomberg and read their sell-side emails and so forth without having the rooting in that type of detail around where central banks came from and how financial crises used to look back when we just had a bunch of banks. J.P. Morgan used to get into a room with 20 guys and try to figure out what they were going to do to bail out the brokers and all that stuff. I think that’s a fantastic book.

Bilal Hafeez (49:32):

Yeah. That’s a good book. I read it years and years ago. I started off my career at J.P. Morgan, and so it was part of the training program where they recommended that you read that book, although not many people did. I did. In some ways, J.P. Morgan, was almost like the equivalent of a Fed chair in his day. So, you definitely get that feeling when you read that period of history.

That’s excellent. Now, before we wrap up the conversation, if people wanted to follow your work in some way, the work you do or QVR does, what’s the best way they can follow your work, and if they wants to reach out to you, what’s the best way they can do that?

Benn Eifert (50:12):

Sure. It depends on what their angle is. For folks interested in casually following some of the kinds of ideas that come up in volatility and derivatives, occasionally I get into things like that on my Twitter feed. You can look me up @bennpeifert on Twitter. Or, you can also go to our website at qvradvisors.com, there’s contact information there.

Bilal Hafeez (50:33):

Okay. That’s excellent. Well, that was a really excellent conversation. I learned a lot as usual whenever we speak. And good luck with everything for the balance of this year, Benn.

Benn Eifert (50:44):

Thanks a lot, Bilal.