All Options Considered: Equity Derivatives Dynamics With UBS

Welcome to FICFocus, where Bloomberg Intelligence fixed income credit currency and commodity strategists and analysts discuss their short and long-term views on debt markets and issuers. Now here's the Bloomberg Intelligence FIC research team. Welcome to this edition of all options considered. I'm Tanves Sandu, Chief Global Dributive Strategies for Bloomberg Intelligence, the research arm of Bloomberg. It's Friday, January the 16th, 2026, and this episode we will focus on US equity derivatives, discuss the current vol dynamics and democratization of the options market with the growth of derivative base ETFs and retail demand. I'm joined by Maxwell Grinikov, head of US equity derivatives research at UBS, great to have you on Maxwell. Thanks for having me. So FICFs had a higher floor of around 15 last year compared to about 12 in 2024, despite the double digit return on the S&P 500. We saw the median 1 month S&P realize vol rides somewhat last year, but to less of an extent than implied, given historical low stock correlation. So let's start with correlation, which is help reduce index vol, and the market is pricing persistent low correlation with the one year implied correlation near the lows. So what do you make of it? Yeah, it's quite fascinating. Over the last 18 months, you've had realized correlation on the S&P 500 hit zero or even go slightly negative four different times and after each time, you had a subsequent volatility spike within the next two to four weeks, right? So realized correlation at zero has actually been one of the best signals for forward volatility in recent times. Now with that said, I do think a lot of it has had to do with the kickoff of the AI tailwind in mid mid 2023 with AI exposed stocks and tech plus effectively driving this divergence or bifurcation, both in terms of earnings momentum, earnings revisions relative to the rest of the market, think cyclicals, X tech, and defensives, and as well as lack of performance breadth, right? So the way I always like to illustrate it is if I think of the S&P 500 as a portfolio of say 10 stocks, five or going up 10%, five or going down 10%, equally weighted, my return is effectively flat and my vol is effectively zero. But there's a lot of action under the surface, right? Now, if I apply a higher weighting to the top five stocks and let's say there's top five stocks are now moving up 20%, that's basically been my S&P 500, right? Very heavy concentration in the Mag 7, the great eight, notorious line, whatever acronym you'd like to use, right? And if you look at realized correlation even just amongst the Mag 7 constituents themselves, which command, you know, upwards of a 30 to 40% weighting in the S&P 500 nowadays, realize correlation between those stocks hit zero in July or August of 2025, right? So when you have your top seven plus stocks in a 500 stock index that are commanding upwards of 30, 40% of your index, moving in varying degrees and directions, it becomes, you know, a fool's errand to buy index volatility when your index is being dominated by stocks that are just moving in different degrees and directions and not manifesting in higher index volatility. So carrying index volatility has been very, very difficult post April in particular, right? And in April 2025 post liberation day realized correlation on the S&P hit 70 or 80%, right? That is the environment to be buying index volatility, albeit, you know, a very exhausting moment for the market to continue to carry a 70% or 80% correlation, right? And ultimately that 80% went to zero in the months ahead. Right. And to that point, we've seen the spread between single stock fall and index fall reach record levels in Q4 in 2025 ahead of the earnings season. And that was largely driven by the large cap tech stocks, which have exhibited this spot up, bottom dynamic, which is typical when there's fear of the right tail and chase for the upside. And you probably would expect that going forward, like greater price moves to earnings at elevated valuation levels and chasing off their AI trade, you know, can support single stock vols. So we've got this scenario where we've got correlation near or at record lows. And every single stock vol elevated that's elevated for the reasons we've discussed, like, and that's happened really post COVID, right, where that AI momentum has just been supporting single stock vol and recent years. So what do you make of the dispersion trade, where, you know, the classic dispersion trade is selling index vol against the basket of single stock vol positions, but long dispersion requires, you know, higher single stock vol and correlation remaining low. So what do you think the setup right now for dispersion? Yeah, look, the entry point is a little bit better. I made the joke last week. In fact, that court realized correlation isn't at zero, but sorry, it's at 10, but at least it's not at zero, right? But it's still, you know, an ultra ultra suppressed and still a difficult environment to be, you know, selling subdued index volatility. Again, based on what we, you know, saw over the last 18 months where, you know, when realized correlation is the suppressed volatility tends to tends to move higher following that, you know, becomes that sort of coiled, coiled spring effect. You know, what we've been talking about in terms of in terms of the dispersion trade is, and you kind of alluded to this is just by single stock vol, right? You know, Q2 earnings, so July and August, you know, for the most part of last year was, was quite interesting. You saw some of the highest moves on record in the single stock space for, for S&P 500 constituents on average, right? You know, you had, you had names like Intel up, you know, 20, 30 percent, right? And then what you saw heading into Q3 earnings was retail start to chase that almost, almost starting to chase this, the next open AI headline, if you will, right? Looking to capture those moves. So Q2 earnings, you had some of the highest realized moves you've ever seen, then heading into Q3 earnings, you had some of the highest implied moves you've ever seen, right? The average implied move for, for a, for a tech stock heading into Q3 earnings last year in September and October was upwards of 7 percent. And so it was, it became a very difficult environment to, to even buy single stock wall. Now heading into this earnings season, things have come down a bit, things have normalized a bit, that sort of retail euphoria that you saw heading into Q3 earnings season has, has died down a bit. But we, we do make, you know, the statement that as long as there's a pocket of momentum to chase, retail will likely be back enforced. Right. And let's focus on those flows now, then. So we've seen a growth of derivative-based ETFs. Yep, leverage ETFs, you know, single stock, et cetera, and increase in retail demand, particularly after COVID, right? I mean, that's just been going up. And there's a shift in product composition where the markets move more towards zero-day to expiry options, following the listing of Tuesday and Thursday's option expiry in 2022. And yield enhancement structures as a huge demand for income from derivatives. So, you know, these can create short-term dislocations in the market, whether it's the impact of overriding flows on risk premium or the shape of the skew. You know, what are you making of all this flow and how it's, you know, changing the dynamics, maybe even if it's in the short term of the vault space? Yeah, it's, you know, 2025 was, was a year where we really had to look into basically what are the products and solutions being traded on the street and where is the tail wagging the dog effect, right? It was for, for, you know, a bit as simple as retail just just buying call options, right? And kind of chasing momentum. That has its own sort of impact, right? As they alluded to, heading into Q3 earnings, just driving up these implied moves, driving up the call wing, just simple demand for upside calls, right? As you mentioned as well, the single stock leveraged ETF complex, right? Largely launched in 2022, 2023. You've always had, you know, for quite a bit the link to the index products, right? So, T triple Q, for example, but it's more of a newer phenomenon to have, you know, on names like Nvidia and Tesla and even some of the quantum computing names, the, you know, the micro strategies of the world, right? The amount of issuance and, and just product launches on these names in particular has, has been quite vast and the exposures and the, the assets under management within these products has, has risen quite substantially to the point where even on some of your highest weighted names in S&P and Nasdaq like Nvidia and Tesla, for example, on a day where you have an upper down 10% move, the amount having to be traded into the close, into the last call, 10, 15 minutes of the market, is sometimes upwards of 5 to 10% of ADV, right? That, that can be quite significant and that gives you a sense of how much assets have grown in these products, right? And now it's one thing to note about leverage ETFs and we remember this with the VIX-ETP complex, you know, back in, you know, 2017, into 2018 is the leverage moves in the same direction. So whether it's levered shorter, levered long, if the underlying is up, you know, 5% on that day and you have a 2x levered product, they need to deliver two, two times that return. The inverse product needs to move in the, in the same direction, right? So at the end of the day, if the name is up 5%, both the longs and the short, are buying into the close. If the name is down into the close, they're selling into the close, right? So they're amplifying moves in both directions. Essentially it's a momentum exposure, right? So with these leverage ETFs, you know, you can't act perform in a trending market, but you then underperform when it's been reverting. Exactly. And now one, one thing we were also looking out for was, which you mentioned as well, is a lot of the kind of the yield max products, which have also been launched, which are supplying gamma or supplying optionality to the market. So they're effectively just, you know, selling sort of out of money calls or call spreads as sort of an income or yield generating vehicle. But what we're seeing, particularly in the single stock space, one, it's about a third of the total AUM of the leverage single stock leverage ETF complex. But two, even though you're supplying, you know, single stock gamma to the market, and it does, you know, in a sense, have this sort of, or impose this sort of range boundness to single stocks in a particular day, call it, you know, between up and down 1%, once you break out of those ranges, right, then the leverage ETFs come back into play, right? And now you have names, you know, breaking out of those ranges very easily, going up or down 5% in a day, and then, you know, the last 10, 15 minutes of the close, those moves are being amplified. I mean, with the income stuff, doing it systematically over time, I mean, the rationale is, you know, selling these call options can provide an income. And, you know, you trade what's in front of you in my mind, but essentially, you're cutting the right tail, right? And most of the returns over time, and, you know, the magic happens in that right tail, and the effect of the over time, you're cutting that. We also saw these income ETFs get a bit more exotic and they started wrapping auto-callable structures. Structures that provide investors with high coupons and have a large downside buffer. So what do you make of that space? Yeah. Well, I traded structure products much earlier, my career. So it was, you know, quite interesting to see, having been in that space for quite some time. And if you look at the product issuance in the SRP, the structured retail product space last year, issuance absolutely blew out in the US last year, right? It was one of one of the strongest issuance years on record. That goes to show you the demand, particularly from retail for these types of products, right? So whether it's issued in structured product format, whether it's issued in a, you know, much more liquid, tradable, accessible ETF format, you know, retail is interested, right? And we're doing the work on our desk to understand, you know, we've been so focused on this short end of the volatility term structure. Now we've been needing to look at the long end of the volatility term structure, right? In terms of the issuance in the one, you know, one to five years space. It's not just structured products. It's insurance products like Ryla, which are, you know, kind of a structure product to cousin, if you will, in terms of how they're structured. We're looking at the impact on funding levels, right? For S&P 500, we're looking at the impact on dividends, on S&P dividends, and how that's, you know, kept the S&P dividend term structure quite flat, because as more structured products or structured product types are issued, dealers are left long dividend risk, and they just sell different risk out the curve, right? So that's kind of flattening implied growth. So we've been, you know, looking at, looking at interesting opportunities in the dividend futures space as well. So it's, it all becomes quite interlinked. So I would say what's been interesting over the last years, we've needed to focus way more on the longer dated and less so on the shorter dated with, you know, the zero DTE complex, and what's been going on there. So let's finish with your top two trades of the AMax wealth. What do you have? Yes. So one of our highest conviction trades for this year is actually quite simply NASDAQ over S&P volatility. One of the reasons being, as I alluded to before, is just the concentration risk. So if you think about NASDAQ 100, it's around 80 to 85 percent tech plus exposed at this, at this point in time. S&P, if you can believe it, is around 50 percent, right? So still very much a high concentration risk in S&P, but even more so in NASDAQ. So in our global economics and markets outlook, we did model two scenarios, an AI boom and an AI bus scenario. We think NASDAQ over S&P could perform potentially in both. So an AI boom scenario, I think about that as a sort of tech meltup scenario. So think back to August 2020, when you had this spot-up volum moment in even some of your largest cap names like Apple and Alphabet, for example. So that spot-up volum correlation up environment is an environment where I think you want, if you're going to be owning upside, that's owning upside in NASDAQ over S&P. For an AI bus scenario, as I kind of mentioned earlier on the podcast, when you had MAG-7 correlation hit zero, or even today it's only around 20, 30 percent, still quite subdued, if you do get a sort of re-correlation amongst the MAG-7 grade 8 and notorious 9 constituents, right? Particularly if that's to the downside, if everything sort of started to potentially sell off at once, if the AI tailwind falters, that is an environment where I think NASDAQ downside is going to underperform relative to the S&P 500. The second trade, I won't get into the weeds. It's a bit of a credit-related hedge. I kind of alluded to this with respect to the structure product space in terms of S&P dividends and dividend futures. We are looking at hedges in S&P dividend futures as opposed to traditional vehicles like high yield or put structure on HYG. The reason being is that if you look at any credit-related drawdown back to 2016 in the US, dividend futures had actually underperformed HYG in almost every scenario, particularly in 2020 and in more recent times like April of 2025. One of the reasons being is there is this inherent one-way risk in dividend futures. It effectively trades as a credit product in terms of as you're approaching expiry and as the dividend points have accrued. There is this pull-to-par effect, but if you do get a market downturn, particularly if credit-related, there is typically dealer offloading of the inventory and that has created the environment for quite sharp drawdowns in that particular space. Are you spreading that against HYG? Either outright or against HYG out to 2026 or out to 2027. We've got NASDAQ versus S&P Vol and S&P dividend futures. Thanks for this, Maxwell. Great to have you on. Yes, thank you, Tanvir. All right, see you next time.