The Derivative - Why hasn’t “VOL” done better amidst stock market losses in 2022 with Logica’s Wayne Himelsein

Episode Date: December 8, 2022

Despite the market being down substantially this year, bouncing around inside of bear market territory, it's been a bit of a challenging year for long-vol traders. Simply put, the Vol spikes we’ve become accustomed to getting with a down market haven’t materialized as much.  While the retracement of vol on bounces higher in stocks has remained. it's hard not to think, "What is going on?!'  And that's why we're putting Wayne Himelsein, CIO at Logica, in the 'Vol' seat to share what he's witnessed in 2022. In our final episode of 2022, Jeff and Wayne delve into a variety of topics like; the lack of Vol sensitivity, contagion risks, and feedback loops, digging into Logica's straddle strategy, paying for long-term exposure, problems with machine learning, and is there enough data for machines and quants to work with when it comes to volatility? Tune in to see if this new Vol regime is our new normal — SEND IT! Chapters: 00:00-02:23 = Intro 02:24-05:28 = Sunny California from "the bunker" 05:29-27:00 = A difficult year for Long-Vol traders: Lack of sensitivity, contagion risks, feedback loops & is selling Vol protection 27:01-41:00 = Digging into Logica's strategy: Put spreads, Gamma Scalping & protecting what you're trying to protect 41:01-51:22 = Skew vs Distribution of Return: Panic events, debunking the signal & the skew price is lower than it used to be 51:23-01:00:21 = Is there enough data to cipher the VIX? / Problems with machine learning 01:00:22-01:12:03 = Seeking strength in the straddle 01:12:04-01:16:35 = Hottest take: Vol, there is no normal Other Derivative Episodes with Wayne: Wayne Himelsein: The Human Behind the Hedge Fund The Volvengers: Wayne Himelsein (Iron Man) & Mike Green (Captain America) on the derivative Follow along with Wayne on Twitter @WayneHimelsein and check out Logicafunds.com for more information Don't forget to subscribe to The Derivative, and follow us on Twitter at @rcmAlts and our host Jeff at @AttainCap2, or LinkedIn , and Facebook, and sign-up for our blog digest. Disclaimer: This podcast is provided for informational purposes only and should not be relied upon as legal, business, or tax advice. All opinions expressed by podcast participants are solely their own opinions and do not necessarily reflect the opinions of RCM Alternatives, their affiliates, or companies featured. Due to industry regulations, participants on this podcast are instructed not to make specific trade recommendations, nor reference past or potential profits. And listeners are reminded that managed futures, commodity trading, and other alternative investments are complex and carry a risk of substantial losses. As such, they are not suitable for all investors. For more information, visit www.rcmalternatives.com/disclaimer

Welcome to the Derivative by RCM Alternatives, where we dive into what makes alternative investments go, analyze the strategies of unique hedge fund managers, and chat with interesting guests from across the investment world. Okay, everyone, after a few weeks of radio silence there and an extended Thanksgiving break, we are back with a pod on a Thursday. I'm battling a little bit of whatever this non-COVID flu is that's going around, but the show must go on. So happy December, everyone, and happy holidays. This sadly will be our last pod of the year as we reset and reorganize the schedule to bring you a slate of great guests next year. If you've got someone you want to hear from, a topic you want us to dive into,

send us a DM on Twitter, at RCM Alts, or throw it in the comments on YouTube or Spotify or Apple or wherever you listen. On to this closing episode of the year. We bring back our first ever guest on The Derivative. We're talking with Wayne Himmelson, founder and CIO of Logica Capital Advisors. My first ever question on my first ever pod was why do you spell advisors with an E? So hopefully we can see just how far we've come in this one and get a few more, a little bit more intelligent questions. Wayne digs into why

it's been a bit of a weird year for volatility, the different definitions and ways to think about skew, why machine learning is so tough in and around vol spikes, and talks through what the new year may bring. Send it. This episode is brought to you by RCM's VIX and Volatility Specialists and its Managed Futures Group. We've been helping investors access volatility traders for years and can help you make sense of this volatile space. See what I did there?

Check out the newly updated VIX and Volatility white paper at rcmalts.com under the education menu, then white papers link. And now back to the show. Okay, we are here with Wayne Himmelsine. How are you, Wayne? I'm good. How are you, Jeff? Good. It was fun because I just saw you last, was that just last week? Yeah. Yeah. Yeah. Your visit to LA. Visit to LA was fun. And it was perfect weather when we were there. Didn't rain, almost made me want to move there. But yeah, I don't know. Some of the crazies I see down on Venice Beach made me think otherwise

oh really that's the whole fun of it is yeah the venice beach environment the kids love it but they complain about the smell and i was trying to explain to them what the marijuana smell is and what what that's about and they're like well i don't know i just don't like that smell yeah there's a lot of range of smells on venice beach A big range. If that's the one you picked up, then... Yeah. It's definitely pretty... I'll say the majority smell might be in that genre. Yeah, so love it down there.

Then we went down to Orange County, which was equally as good. I didn't get to get in the water as I wanted to do and go surfing. But next time. The weather was too nice. I mean, the water's... Sorry, go ahead. I was saying the waves were too small also, but... Yeah, and the water happens to be freezing.

So everybody talks about Southern California oceans, and they're beautiful to look at, but they're crazily cold to get into. So what's amazing is East Coast, like i sometimes go to carolina in the summer south carolina there are beautiful warm waters it doesn't have the the the popular appeal of southern california beaches but honestly the water is so much warmer and nicer to to be in so it's like one of these hidden unknown uh gems versus the popular opinion yeah the uh i just just watching that new chris helmsworth documentary on a national geographic on disney plus and he second episode it's all about shocking your system with the cold all right okay resets your immune system so he goes to the arctic circle and trains like

staying in the water for three minutes and then he swims across a channel with just a bathing suit no wet he was surfing in that water it was like i was cold watching it and then he swims across a channel with just a bathing suit no wet he was surfing in that water it was like i was cold watching it and the recommendation at the end was to shower 30 at every end of your shower for 30 seconds to do cold water and the shock supposed to be good for your system just to like get your it like your system going or something like that i think it like tells your body to worry about that shock instead of like the little aches and pains and reset i see i don't know sounded a little bit of crockpot science but yeah it was entertaining to see him surf in the arctic circle yeah seriously

we'll leave that to chris helmsworth yeah he's that's thor right yeah yeah um and you're you're there in the bunker i got to meet you at a nice outdoor coffee shop but you're back in the bunker i'm back in the bunker that's this my safe zone i wanted to come visit there because i envision it like uh some evil lair and i go in the front floor and then we go down like floors and floors like 17 floors down is the train i feel the heat of the earth here. So let's get down to business. Dive right in. It's been a bit of a difficult year for a lot of long ball traders,

which we were talking about out there, despite the sell-off. So you've had a lot of great charts in your monthly commentary and whatnot. So kind of tell us what you've witnessed from your seat and in relation to your models of why and how it's been kind of a hard long vol year. Yeah, absolutely. That's easy to talk about because we've been going through it for some time now. So there's lots of different versions of hard vol. I mean, long vol is not easy at the get-go, right? You have this constant headwind of long optionalities. Obviously, both Theta and Vega are usually against you. Theta, just the cost of owning an option, and Vega, with the market usually going up,

this vol is somewhat negatively correlated to equities upside. So you have this drag against you in multiple ways. And so it's always a challenge to own vol. But then you come to a year like 2022, you get actually two things that have been hurting, quote, even worse, making long vol exceedingly difficult. So one of the, I'll say two different sides of it. One side is the lack of reactions. So the lack of sensitivity to down market behavior. So equities down, vol should pop. And that down equity versus upside pop, that negative correlation that we also rely on in the vol world is, I mean, it's kind of there, but it's not, it's certainly not as sensitive.

So that's one side of the coin we can talk more about. And the other side is that on the little recovery rally on the S&P, after a little down, vol crushes even more heavily, right? So you get hurt on both sides. Like S&P is down 2% one day, say in this year, 2022. And instead of vol or VIX, we'll use vix as a proxy for implied vol obviously it's just one part of the surface but but it's an easy way to talk about it so um vix uh in this example s p is down two percent vix in historically might be up a point and a half to two points this time it's up 50 bps right so you get this lackluster reaction, really almost like doesn't pay attention to what the S&P is doing. So that doesn't help. That doesn't give you much of a pop on your options. Your vega is not really lifting to give you a pickup where you would otherwise expect it.

Then the next day, S&P is up a percent and a half and VIX is down a point and a half. Right. So it certainly crushes in line or and then some, but it doesn't gain in line. So the summary of that is that you get hurt by not having that reaction you expect on the way up. And then you get double hurt that if the market bounces a day or two, it gives it all back. And ironically, if you look today, I just noticing this um vix year to date is basically flat i mean it's yeah it's plus minus a pointer here there i think uh if i go to uh and go to a chart right now just to or a price just to look at it really quickly vix on 12 31 21 was um closed at i guess 17 and a Today, it's 18.8, right? So it's a point and a half-ish difference.

And the market's still down, whatever, 13, 14%. 14% on the year, right? S&P's down. And VIX is literally unchanged. Or thereabouts close enough, right? It's just so... And yet we did see these moves once in a while. There's, I'll call it three major leg downs in the S&P, January, June, and then in September was the

third leg down. And each one of those times, VIX tried to run up a little bit, ran from the low 20s to basically 30. So you had this minor gain, but then the next few days, S&P rallies, it just gives it all back. So there's no traditionally, vol is known to cluster, right? So once it pops, it kind of hangs out there, maybe waits for a new level up. This time there's no clustering, it just ran up and crushed back down. So I guess we'll call that the third problem, right? So problem number one, no sensitivity, no popping. Problem number two, giving back much quicker than we expect. And related to number two is number two and a half or three is not clustering, not hanging

out when there's a bad environment. So all those things together make for a difficult year for Longville. So I want to just say why, but I'll try and be a little more intelligent than that. But we'll get to the why. But is it too naive or too simplistic to think about it of like, hey, the VIX at 25 was expecting 2% daily moves. That's why it's not moving because the moves are inside the range of what the VIX is telling you. Right. Of course. So it's realized versus implied, right? So realized was up. And so you need

realized to keep on going for theoretically for higher implied, right? So you need, you need something outside of what that's what people have come to see as normal. You need that to be increasing for there to be a new wider band or new higher implied. Yeah, I mean, that's part of it, sure. But that never was an issue when something's going really wrong, right? I mean, let's talk about the obvious occasions where VIX or IV ran up to 80, 90, 100, right? Whether we go to the GFC in 08 or whether we go to COVID or more recently and some of the in-between events. When there's a serious event in the world, people aren't necessarily looking back at where the normal is. It's more this unbounded uncertainty of what, wow, anything could happen

from here. So that moment of panic or stress that leaves the potential wideness open hasn't happened, right? And so when you say as to the why, we believe the reason for that is because literally what I think what I just said was there's not an unbounded uncertainty. There's a bounded uncertainty, right? So the uncertainty is not, oh my gosh, the world might end, which was the initial panic. And for example, in February, March of 2020, it was like, okay, this crazy virus we've all never seen before is going to kill half the world. We just didn't know anything. So you had, quote, unbounded uncertainty. Or the GFC. What? Or the GFC. Who knows what's in AIG's book?

How many people are infected? How many banks? Who knows the dominant? I mean, when Bayer fell and then Lehman fell, I mean, it's just honestly, Citibank, who was next was the question, right? And was this going to take down the entire financial system, right? So the floor is unknown. In the recent environment in 2022, we've seen and described what we've called the bounded uncertainty, which is it's uncertain, but within very strict, or almost tight lines, right? It's like, okay, will the Fed raise 75 bps? And if it's, you know, feeling one way it goes to 100 bps and if it's you know feeling one way it goes to 100 bps and it's feeling the other way

it goes to 50 bps right hawkish or dovish and so the the at the end of the day we're literally at 25 basis points plus minus the expectation right yes had the fed come out and said hey we're raising 200 basis points instead of 75 bps, well, then there'd be shock because what's gone wrong? But not only has it not been 100 bps or 50 bps, which would have been plus minus 25 off of that, it's been right at the expectation of 75, which is where the bond market priced in, right? 75% likelihood, right? So it's- And what they were telegraphing. And what they were telegraphing, right. And And then so it's the same thing with the Fed. It's the same thing that with all the numbers leading up to the Fed decision, the trifecta of influence, the three numbers are variables that we all believe matter most.

Right. It's GDP and CPI and unemployment. Right. So it's we want to see jobs and we want to see less inflation and growth. So each time those numbers come out, it's the same thing. It's like, oh, the expectation is, you know, unemployment at 200,000, whatever the number is. And so instead of 200, it's 190. Like, oh, well, we're 10,000 off. Right. And so it's just not wide enough around it. And of course, once again, had we had the shocking number, suddenly 200 is now zero.

Well, then now we have, you know, there's no unemployment. Right. So now we have a problem or now we have a shock moment. But 200 versus 190. OK, missed by a tad. And once again, this bounded, bounded, highly bounded uncertainty is just not enough to shake people up and therefore not enough to create this potential wider variance than we're expecting. Do you think what I'll call the Apple effect? Is there like an Apple effect of, hey, Apple's not going to be affected by all this Fed stuff. They're going to keep printing money and it's in everyone's portfolios and it's a huge part of the S&P. And that's why there's no contagion for these darling stocks that people hold. And so they're going to kind of keep that bounded of... I know there's no uncertainty in Apple based on all these events, so I'm just going to continue to hold it.

Well, I mean, sure, that makes some sense. I haven't thought about that much. But to me, the contagion is in the cost of capital, right? I mean, if rates go up and up and people can't, people, companies can't have a problem, right? They're sitting in so much cash. They're actually earning more on their cash. They're like, oh, great. We have new. Right. They should just retire. We're not doing any more phones. We're just going to. Right. More. Right. Oh, great. We're earning more on all this cash we're generating. So, but in general, I think that the contagion risk is around the carry, right? And that affecting for, obviously if one major company came out tomorrow and said, oh my gosh, we're, this is, you know, we can't restructure our debt and we can't service it and we're done.

And it's some S&P name. That's the beginning of unbounded uncertainty because, oh, who's next? And what's the new domino? Who's the next AIG of that problem? Right. So now we get to the darlings, to the darlings. Yeah. So some of them, obviously, we've seen that there's been layoffs. I had Amazon and go down the list. They're all laying off 10,000 plus people. Right. So they're curtailing some of their growth initiatives. And that's maybe it's just again, it's the equation. It's not worth the capital at this cost and whatever reason.

So therefore, it seems like to both of our what we're saying is it's not going to hurt the darling stocks as much because they're in good cash positions. They're not debt heavy. They can they can manage their their their their their expenses. But I think elsewhere there might be this effect, this cost of money effect. And if that's the case, I don't know that the darling save the market. Right. If that gets to be an issue, it's contagion. Even if Apple's safe, there's a bunch of others who are not. And I feel like that might be wide enough or broad enough to have an effect. I'm not saying that it is an effect. And who knows yet, but I don't know that the darlings could save us. I guess that was your original question. Yeah, yeah. And then part of what we talked about out there, the energy stocks sort of saved us as a collective us of market holders, right? If the war hadn't been and oil hadn't been high and energy stocks hadn't held the market up, it might have been more contagion in a sharper sense. Absolutely.

Yeah. And energy stocks hadn't held the market up. It might have been more contagion and a sharper sell. Absolutely. Yeah. Yeah. I mean, that was definitely the sector of 2022 was energy. Yeah. And then for me, if you're out there listening to this and you're huge into the NASDAQ and a bunch of tech names and growth names like you were talking about, they're probably sitting there saying, what are you talking about? There was huge contagion, right? Like half of my book was marked down 80%. Like all those high flying growth stocks just got hammered and we're down huge, worse, some say than the.com. I guess some didn't all go out

of business, but I don't know if there's a question there, but it's interesting to me of like, nobody's really talking about that. Like you see the numbers, but it hasn't been like, it hasn't flowed into main street. It hasn't gone wide in terms of effect and in volatility, especially. Yeah, that is interesting. I mean, to your point, there's many brand names in the tech sector that are down 50, 60, 70%. It's, yeah, this would have been major conversation. I wonder if part of the reason that's not such a big discussion is because that basically just gave back 2021. Right. It's like when people are up so much on their Apple from along the way that now it's just still, you know, they're up on it. So it doesn't feel the same. I don't know if that's an answer, but just what immediately came to mind. But you're right. There's been some severe sell offs in various sectors. It has, you know, and it's certainly not been it's not felt like a contagion.

And the vol markets haven't woken up and said, we feel like there's real risk here. And it's, I think it's just because overall, we all know it's a product of the same larger economic issue. It's like the slow turning over the economy. It's not necessarily this immediate breakdown that we're going to see. The GFC 08 was, it all could have started happening like day after day, companies folding. And this just seems much slower, I guess that's maybe what I feel about it. And so, you know, those stocks that are down those big percentages, it didn't happen in one full swoop, like a COVID or a GFC, it happened kind of gradually so that the grind lets people adapt to their losses each month, right?

Oh, this month I was only down six and the following month, oh, it was only down another five. You know, and then you look back, you're like, wow, I'm down 60% on the year in this particular position, right? I mean, the way it happened didn't feel panicky. And what are your thoughts on, right?

So long held market axiom of the market will do what causes the most pain? So do you think in the vol space, a lot of people were conditioned off, like we were saying, GFC, coronavirus, et cetera, to be like, I want to be hugely long vega. That's where I'm going to get all my convexity as long as vegan looking for the vol spike in a down market to protect against a down market so that the market in a weird way, some controlling hand said, okay, we're not going to give you that vol spike because too many of you have that exposure. Yeah, I'm not, listen, it's not a controlling hand, but it's the, I mean, markets to me are supply demand is that it's consensus of market participants.

Right. So it's what's happening between buyers and sellers. And, you know, that's what's resulting in activity we see. So, yes, we in prior years when there was I think it's what I'll say to your comment is that it's a self-fulfilling kind of reaction. Right. Or it's a feedback loop. Let's use those words, right? So in 08 or any other major times, you know, even in late 18, VIX, like the end of 18 correction, VIX spiked up to the high 30s, but it had come from much lower, came from 15, right? So here, the spike might have made it to 30, but it came from 22 or 23, right? So it's still not, there's not a lot of, you know, available upside when when you're starting so much higher. That's I guess we'll call that a third or fourth problem. Right. It was starting at a higher median level or a higher level in general. So go back to the feedback loop is when it did react in prior events, it became trustworthy.

Oh, Vol's credible. This is this works great. It works great. The market's going to go down, and this thing we hold over here is going to go up a lot and pay for all our losses. Great. Then you have January of this year, the first leg down in the S&P, and there's barely a spike in vol, right? So this first signal of it not behaving or not being sensitive to equity downside alerts everyone, wait a second, I have all this vol on my books and it didn't really help in the first leg down. So it becomes this want to sell it. And so they're selling into the event. So then by the time the next leg down comes in June, there's an expectation is already it won't run. And so instead of the sellers starting at VIX 32, now they're starting at 31 and 30 and

29 because they want to get in front of the prior sellers. Right. Because it's shown the last time. And then everyone looks at the second leg and say, oh, look, it was even worse than the first. Now it's doing nothing. Right. And so by the September down, the S&P, whatever it was, 10 to 15 percent in that range. September moved down. Vol was even lower of a high than it was in June and January, right? It's because it became, it went from credible, reliable to unreliable, not doing anything. And so every next pop became a seller's opportunity or a holder's opportunity to liquidate some of your holdings. That's what I was going to ask. Do you think the selling is, people already had warehoused that as risk protection and they're selling some of their protection?

People who had warehoused, I think there was a lot of warehousing in prior years. For example, in 21, I think there was warehousing of all for what the market's seeming toppiness at that point. Then we come into 22 and the January event is like all these people that have been warehousing are not getting the payoff they expected. So then the unloading of the warehouse starts right uh or the unloading of the inventory starts uh and then go back to what i just said before then june comes the next like i'm like now everyone who hasn't originally oh now we got to get out of it quicker because everybody you know it's certainly not working and so by the time we're here now it's it it's become untrusted and unreliable. And do we even believe in the net? I've had questions or discussions with some of my own LPs is, can we depend on the negative

correlation between S&P and vol? Well, if S&P goes down, vol will go up. That's a core premise of long vol, right? That's what we all sit and rely on. So in my view, I look at all of this as. Great. I mean, it didn't work this year, but there's no there's no there are some reasons that can explain it, but there's no way that the human behavior of pure panic can change what Vol does next right so if tomorrow comes not covet 19 but covet 20 right some new variant that is much more deadly than the first suddenly this new unbound uncertainty arrives and of course or or the contagion from from from from expensive debt right in in corporate america if any of this

starts tomorrow or next week there's no reason reason, I believe, that humans are suddenly like, oh, we're not going to panic. That seems very manageable. It's just that's not how we behave, right? So to some degree, we might summarize and say that the feedback loop is creating a coil spring of payoff, right? That the more people are not trusting it, the more it's actually going to run because there's no sellers left. So if there, when, not if, because when there is that next panic event, because there always is, right? Whether terrorism or go down the list of bad things that can happen in the world, when that next event triggers, now everyone's sold out of their inventory. They don't believe it anymore. It's actually got tremendous upside to run

without that selling pressure. So I'm more of a long vol holder now than I might've been three months or five months ago. But it's weird to think of it coiling and everyone I think equates that to VIX at 15 or 12 or like a 2017 type really low level. Okay, so we're at 18, 19 right yeah so sure but but there's that doesn't those are kind of separated so yes vix cheap is 11 12 that's that's that's cheap buy all you can because your downside is so limited at that point right um and so you know

we all buy vol for its right skew behavior. When you're buying it at 30, you've got as much left skew risk as you have right skew payoff, right? You're kind of symmetrically exposed. That's not the ideal value of vol. The value of vol is fat right tail. So when you're down at 10, 11, 12, you've got a fat right tail and barely anything on the left. Like if you could, the floor of all is let's call it about 10, right? Obviously VIX can trade nine at one day of the week, but generally speaking, we're not going to get that much lower. So it's nice. So when you're here, going back to where we are now at 18, 19 below the historical realize that about 16 on the S and. Then, yeah, it's a tad expensive,

but if there's less sellers above, it's safer to own now. It's closer to the historical 16 level. So it's not as good as it could be at 11, but it's, of course, better than it was at 24, plus a lot of sellers wanting to get out of their inventory. So I'm going to take a step back and give us, for those too lazy to go back and listen to our previous pods with Wayne, give us what you do, how it's a little bit different than most long ball strats in a sort of short elevator pitch version, if you can. Sure. Yeah. Then we'll dig in on some of the pieces. Yeah. I mean, we trade vol. That's what we do.

That's the shortest elevator pitch we can go with. So how do we do it different from... Has that ever worked? Have you ever been in an elevator and said, we trade vol? And the guy's like, cool, call me. Yeah. No. Yeah. Might've been on a staircase. No, never been in that situation. So how we're different to most is really the interesting thing to talk about. So generally the vol world are spread trading world. So you want to be long vol and you get there by,

you want to pay for that long vol. When you buy long vol, you need something to pay for it. It's expensive and it bleeds, right? So the general way to pay for it is some form of a spread. And it's usually either the calendar. So you're going along the surface in time, or it's a money in a spread, right? So call it a put spread. You're long at some level and you're short above or below that level. And you've got some in between that you're trying to profit from where the vol you're selling is paying for the vol you're long. And obviously the net long vol is the objective, right? So you're going to sell a bunch of all either on calendars or moneyness or some idiosyncratic interesting vol that you've sold that you think is overpriced. And you're going

to use that to get net longer, a bunch of all that's going to help you involve spikes. And so we'll call that the net long vol book, whereas we are gross long vol. So it's 100% long vol. We do not have any short legs. We don't sell any calendars or money in the spreads. We're just long vol buyers and traders. We will buy options that are cheap and monetize as they get more valuable and try to buy them back when they dip again. And if you will, just swing trading long vol positions. And so at the end of the day, we hold the long vol inventory. We make money on scalping and trading along the path. And we have no short leg to counter the behavior that we expect from vol, i.e. when it spikes,

there's nothing spiky against us, which would happen if you're in a spread, of course. And then my follow-up, because you're explaining how those other guys pay for that. So how do you pay for that? It seems too good to be true. Like, oh, I can get all this long ball without having the short exposure, but you have to pay for that somehow. Right. So our trading approaches pay for it. Our scalping and trading are, if you will, stock picking. And I'm going to call it that, but I can drill down on that. So scalping trading is, very specifically, gamma scalping is trading the wiggles of vol itself, if you will, vol of vol, right? So vol has volatility and moves up and down.

And so if you were a trader of that, you'd want to buy lower levels of vol and sell higher levels of all. And because there's gamma embedded in, i.e., you're convex to upside and concave to downside. So you have an asymmetric payoff structure, which helps you as a trader, right? If you ask any trader, forget about options for a second, you ask any trader who trades any stock, they trade Apple, Netflix, whatever, right? They want some high fall stock who trades any stock, they trade Apple, Netflix, whatever, right? They want some high fall stock. And on average, or in general, they'll tell you that they want to get in when there's perhaps three points upside and one point of downside, like a three to one risk reward bet that they see. And they might see a technical trade on the chart and say, oh, there's about three, four points to gain and my stop is a point below. So they've taken that asymmetric payoff, but they've done it linearly, right?

It's a linear movement of the underlying. Whereas by design, we have that asymmetry in the shape of what we're trading. So we have that natural asymmetry. We still look for those upside-downside ratios to be good for the underlines that we pick. But in addition, we've got the convexity slash concavity of the instruments we're trading. So lay on being a good trader, i.e. having good asymmetry in each one of your trades, plus the asymmetry of options themselves organically. And you get you turn scalping into gamma scalping.

And if you're good at that, you make money. And so you can hold this inventory. I can hold a hundred puts on the S&P, but today I might've scalped 20. And so we began the day at 90 and then we bought 20 and then we sold five and then we bought six and then we sold 12 and we ended the day at 84, whatever. And so those buys and sells made us 7 cents a day and it didn't. I'm just giving you this proxy. And so you do that enough times every day, hopefully if you're good enough, you pay for theta. If you're losing on those trades, you basically can't lose on those trades because they're part of, you're just taking off exposure, right? They're not additive. You're not on top of the exposure of that trading. Yeah. I mean, you're modulating your long inventory, right? Because when you were saying that, I was worried you'd be like, right. And the risk to me is like,

okay, I'm going to trade in order to help pay for theta. But the risk is I lose on that. Now I have the theta plus the trading losses. Oh, absolutely. So that's the headwind is we already have the headwind of long vol, right? Which is theta. And generally in other markets, it's vega, right? It's vol itself. But so we have these organic headwinds. And then we have the headwind of not producing or or our alpha going wrong right

so if our alpha generation is positive it has to be first enough to cover the hurdle of our of our headwind and then when it's wrong now we're additive to your point we have three things going wrong the organic cost plus the cost we created by trying to meet or beat the cost, right? Yeah, yeah. Yeah. To you, that cost is less and less spiky than having a spread trade on where one leg might do some crazy stuff, right? That kind of the theory behind it. Yeah, the theory behind our not liking spread trading, and I want to say don't like,

I mean, it's very common in the world. You pick up any option book and it's all about the spreads you could put on. Right. Um, and so it's nothing, it's, it's such a industry standard for us, our, our mindset, our philosophy is that it's to some great degree counter thesis, right? The whole point of long vol is to get the pop, right? So if you're in a spread, right, by definition, your long pops and your short pops against you, right? That's what vol does, right? It pops. So we're in it for right skew. So you're going short a right skew instrument, which is left skew. That's what you don't want. So what I don't understand, I guess what feels

counterthesis is everybody who wants long vol wants it because they already have negative skew that's what you don't want so what i don't understand i guess what feels counter thesis is everybody who wants long haul wants it because they already have negative skew in their book right so if it's so predominant in already what they're holding then why are they going to go add some additional negative skew to own the right to the positive skew no you're just trying to add positive skew that's just do less positive skew if if you're right. What's that? I'm saying you just do less positive skew exposure and not try and ramp it up and add left tail to get the right tail. Right. If you're going to do that, let's say you own a book of multi-market neutral and market neutral is pretty stable, but it has negative skew in liquidity events. So then you're going

to add some spread trades. Well, you've added more negatives. Why not just add more market neutral and buy some right skew? Like do what you know well, and then just buy pure right skew that's going to have no hindrance to that upside when it happens. And I'll tell you the other major thing is the basis risk because you're oftentimes in the spread trading, you're trading things that are potentially like, oh, this seems expensive, so I'm going to sell it to buy this, right? So let's say the buy is the index. Let's say you're not you're trading things that are potentially like oh this seems expensive this seems expensive so i'm going to sell it to buy this right so let's say the buy is the index let's say you're buying s&p vol for your portfolio protection and you're like you're trying to find some expensive vault to spread against that and you say okay we're going to sell some some biotech vault because that's overpriced right and so you do that in january of 20 right and then covid comes

the greatest thing everybody wants to be in is biotechs, right? And so your biotech vault, your short loses, right? And your long, of course, pays off, but it's this double whammy, right? Because you took basis risk or idiosyncratic risk around the other leg to pay for your long or dispersion risk, whatever. There's many ways to describe that relationship. But that's another problem. Or if you go, for example, in calendar spreads, you've got backwardation versus contango risk, right? You've got the shape of the time curve. And so you could be right, but then if you're wrong in some other dimension, it hurts your payoff for what you were trying to protect. And it's actually happened a little bit to some of the VIX traders this year

who trade the calendar, right? It's because of the weird shapes. And so you're like, how can you protect when you've got this other thing, this basis that you need to go in your favor to protect what you're trying to protect? The first part of your job, right? And what about you guys do a little bit of this, but some of the worst performers in the ball space this year use, right.

Index falls too expensive, kind of similar to what you just said, but opposite of they're saying index falls too expensive. So instead of going out and selling some other expensive, I'm going to go find other cheaper ball in hopes of getting a spike there instead of paying up for the index ball. So if that thing happens to spike, right. expensive. I'm going to go find other cheaper vol in hopes of getting a spike there instead of paying up for the index vol. So if that thing happens to spike, right? So now you've accepted some new basis risk. We're long only, not only, but primarily index vol. And when I say primarily,

the grand majority and index vol, so S&P, right? Because we don't want basis risk. If the job is to ensure downside, then you have to be the market, right? And so the question becomes how to minimize the cost of long S&P vol, right? To me, that's the question. Should I say, oh, let me buy some, I don't know, some other vol I could find out there? Well, what if that's not the thing that pays off when the market goes down? It's just not, it's not worth it when you're in the business of, quote, insuring risk. And I say quote, because it's not pure insurance. It's like an insurance, right?

It's an attempt at insurance. Some of the best performances here have been using complex options. So I like to call them parlay bets, right? Like, okay, if the S&P is down, if bonds are down, if Europe's down, instead of this paying two to one, it pays eight to one. Sure. In gambling parlance. But what are your thoughts on that strategy as a whole?

I know you guys don't look into that, but I guess why not? Similar to what you're saying, Like there's basis risk there. There's you're, you're adding dimensionality, right? It's you're, you're adding more things to worry about. Just go, let's go with a simple. So however complex you get, each level of complexity is adding not just basis risk, but some other dimension that you then have to understand and track and worry about. Right.

So go with a simple idea of a calendar spread, right? Or even simpler than that is a money to spread on the same month, right? Now you've introduced skew risk, right? So you buy at the money, there's no skew. You're just dealing with expensive or cheap vol, right? So you have one dimension you're trading. Is vol cheap or expensive? And you can analyze that till your mind is numb, right? Then you say, okay, we're going to go out on the wings a little bit. Well, okay. So now you've got, is vol cheap or expensive and is skew high or low, right? So you've got compression or expansion of skew as their second dimension of risk next to is vol cheap, expensive because you could have vol getting cheaper, but skew getting more expensive. Right. And so. And be in the same spot.

And be in the same spot. Exactly. So by introducing additional dimensions slash complexity, you're, you're, you're, I mean, we can talk about in so many, there's so many analogies to this. The old, the oldest analogy is the three-planet problem, right? It's like we can figure out the relationship of gravity can figure out how the Earth is going to go around the sun, but introduce the moon, one more body, and no one can figure out where anything's going to be next, right?

Because the problem mathematically gets too complex. They call this three-planet problem. So the problem with introducing new dimensions is not only the summary idea of basis risk, but it gets more complex than I believe people can fully get a handle on. And so when that event comes, you don't necessarily know when and how you're going to be wrong because of the additional conditions on your insurance. Right. To me, how do you know if the payoff's correct? Correct. That's kind of what you're saying. Yeah. How do I know? There's more path dependency. Right. And then my gambling parlance, right? If it pays out 10 to 1, but the true odds are 16 to 1, the house just took 6 to one away from you right

you won but it pays out 10 to one but given the set of seven if thens right or or like a layered conditional tree right well it's 10 to one but assuming a b and c is that really a 10 to one yeah it's 10 to one on paper But the paper like has to be twisted in a certain way and flown like a paper airplane across and land exactly on the right spot on the ground, right? Right. Done. And now we've mentioned skew in a few different ways here. So I want to make sure, I don't know, for know for all those who watch smart lists you ever hear that podcast with justin bateman and they always refer when they're talking like inside baseball they go for uh one of the guy's sisters karen i think for karen skew means so for k so for karen if you could and karen's their sister in milwaukee or something they

bash on wisconsin but for k Karen, like we were talking skew in terms of the curve, but also right and left skew in terms of the distribution of return. So maybe if we could clean that up a little bit, how those are the same, how they're different. Yeah, I mean, they're the same, but they're not thought of,

they're the same and not the same. So the skew in the distribution is just the tilt of the distribution that kind of points it in. It gives it a fat tail on one side or the other. If you the way I love, I think it's a lesson I got decades ago. It's just if you push your if you take a normal distribution, you push your thumb in on one side. The area under the curve always stays the same, the same amount of stuff under the curve, but you want to redistribute that weight. And so if you push your thumb in and the right side will

kind of pop out, right? It's like squeezing in a water balloon and it pops out over here, right? So you can push your thumb on one side and get right skewed or the other side and get left skewed, right? IE a fat right tail or a fat or long right tail or a fat or long and or long left tail. Um, because skew can be fatness or length. Um, it's just more weight on that tail. Um, I eat more outlier events on that side than we would expect. Um, and how you were talking about it, you're always targeting right skew in your performance, which may be targeting left skew in the market's performance, but right skew in your performance of a lot of small losses in exchange for some big outlier gain.

Yeah. I mean, a right skew payoff structure is one where, and I gave the example earlier, it's the incredible right skew is VIX at 10, right? And we all know VIX can go to 100. It's done 10, right? And we all know VIX can go to 100. It's done it, right? And at 10, I don't think any of us believe VIX can go to five, right? I mean, is it possible? Sure. Anything's possible. Let's understand that the world is strange. Maybe the futures go negative, like oil.

Yeah, maybe, right? I mean, oil went negative, right? Some time ago, right? But let's just talk in general, major, all known circumstances, like 10 is pretty much the floor on VIX. Right. So if you're 9.8, whatever. Right. So you're buying it at 9.9. You've got 90 points of upside and maybe 10 bips of downside. That is the most right skewed situation you can put yourself in. And so that gives a hundred to one payoff structure, if you will. Right. And I'm using very general numbers. I'm just trying to describe the point. And so that's what we look for just to summarize that in a word is asymmetry, right? So we look for the maximum asymmetry upside versus downside. It's a ratio,

it's skew. You can talk about it in eight ways. Mathematically it's asymmetry upside versus downside it's a ratio it's skew you can talk about it in eight ways mathematically it's asymmetry right um so that's different you know people so skew on the on on the um on the uh which is which has been all over twitter recently skews at all time lows all this stuff it's a buying opportunity all this so kind of want you to debunk some of that as a signal as well as you're explaining that. I mean, so before we get into debunking this signal, right? So there's different what the price of that option should be as you go along the moneyless chain, right? So you start from at the money and you go down to out of the money, in the money, you get further out, right? at the, quote, wings. So under a normal assumption, right, i.e. a normal distribution where there is no skew or fatness on the tails, it's going to get – those options should get cheaper and cheaper. But that option way out there, out of the money, should be priced at, for ease of talking, a penny.

And it's actually trading at $0.10, right? So it's implied vol, the price it's trading at is showing skew. It's showing that the market believes it's so much more likely that that can happen, that it's not worth a penny, it's actually worth 10 cents, right? And so that's where you get this skew, i.e. higher IV or higher pricing of out-of-the-line options because the market believes that the normal assumption is not right. And that is true. It's not right. The normal assumption is not true in equities. Markets can correct much deeper than normal distribution would imagine or would dictate. And it's funny when I read in the papers years ago, like there's, there's some big drawdown, it's 08, or it's 2020. And some article says, oh, this was a

eight sigma event. No, it wasn't. It's not an eight standard deviation event. It's an eight standard deviation event, if your assumption was a normal distribution. Given the skewed distribution that we all expect, it's not an eight sigma event, it's maybe a one and a half or two, right, given the actual shape of the distribution. It's only eight sigmas if we assume this could never happen or if we assume normality to be specific. So with that being the case, now we get into what is the right skew? So people are saying, well, skew is cheaper. So skew was more expensive. The market at prior times in history believed that there was even greater likelihood of, for example, a 20% gap down, right? Where today SKU has gotten cheaper.

So the consensus opinion is- And just real quick, the SKU pricing is the put minus the call is how people are referring. When it's cheaper, it's that premium is cheaper. Yeah. I mean, if you look at the whole opt-in structure, it's kind of a you, right? And you have the call and the put on either side. And so, I mean, you could do put minus call. You could sum them. I don't know how different people can do it in different ways. You could look at one side, but this whole thing is kind of flattening out, right? But it flats out a different, there's the smile, they call it. And then a lot of options look like what's called a smirk because the call side traditionally doesn't have as much skew as the put side, right? Because markets don't pop up 20% as much as they can pop down 20% overnight, right? And so you have different

skew shapes to upside versus downside or call skew versus put skew. And so if I'm doing it, I'm just looking at put skew versus put skew and call skew versus call skew, right? I'm not summing or adding or doing any because they're independent behaviors. But so I'm not sure who in the market is talking about it. But there's different ways that different professionals might talk about it. But let's talk about put skew because that's what really we care about. put skew if if there's this black shoals price and that's assuming a normal distribution prices are far out of the money put at a penny and historically there was so much worry over over risk that the market was willing to pay let's go extreme 50 cents for that option so it's 50 times the price so it's implied vol

is high skew now it's come down to just for easy number 10 cents and everyone's like oh. So it's implied vol is high skew. Now it's come down to, just for easy number, 10 cents. And everyone's like, oh my God, it's so cheap, right? Yeah, it's cheap relative to the 50 cents high we saw, but it's expensive relative to the normally assumed penny that it's actually worth if we assume normality, which we know is not true. So now the question becomes, what's the true value? What's the right value, right? That's your concept of debunk. How do we assess value here? Well, the answer is we don't know. There's no, right?

Because it's all relative to what is the standard, what is the distribution within the tail, right? You can call that conditional variance or CTE, tail expectation. There's different mathematical tools, but the premise behind all of them is that you have enough data points to tell you what is the norm of tail events, right? So will the market correct 17% or 24%? We have no idea. That's ridiculous. Like we're dealing in events that have happened 22 times in the last 100 years, right? And from those 22 sample points, we have different magnitudes, we have different rates of happening. COVID happened in three weeks

and GFC happened in seven months, right? Both of them hit 30% declines. They had different recovery rates, different decline rates, some had gaps, some slid down, right? Some waited in gaps, some were step, stepping down, et cetera, et cetera. So all these different behaviors translate to, I'm not sure, nobody can be sure whether, yes, we can all be sure that normal assumption of pricing of a penny for that out of the money option is wrong, but is it worth 7 cents, 12 cents or 50 cents? We don't know. Nobody can say they know. And so the new cheap might not be cheap.

It might be that if the market, you know, if there's really no GFC pending, right, i.e. a 50% sell-off pending, and that's really super unlikely from here, then the max drawdown 2030 prices that thing at 8 cents. I don't know. And I'm talking really broadly to make the point once again, is there is no right price of a distribution of events that has 20 data points in it. And so we don't know fair value, but we do know it's cheaper than it once was. Right. I right. I think that's part of the problem. Cheap kind of implies that you're getting a value, right? Oh, I got it. I got this for cheap. I got a deal on it when it should just be quoted like it's it's prices lower than it used to be. Right. It's prices lower or cheaper than it used to be. Yeah. And at 10 cents, using the same example we've been talking about, we might say that the theoretically fair pricing,

if we study the distribution of tail events in history, maybe the fair pricing is 7 cents. But if that fair pricing is 11 cents, and someone could say, oh, look, it's cheaper than every event that's ever happened by one penny. I'll say, yes, but those are all outliers. The next event could make it worth less, right? Right. Like the CPI everyone's getting. When that new one comes on, the data set's too small. Right. It swings that thing.

Which brings me to an interesting concept. People trying to do AI and machine learning on VIX spikes in these markets, right? If you only have 22 out of a hundred years, is there a big enough data set in order to run those models in your opinion? Absolutely not. No way. I mean, there's, I'll say like the way we like to look at it is there's reasoned behavior, which we can all, we can study. We're experienced. I mean, I've been in markets for 27 years trading. I kind of understand by now how they behave. I'll use that word, right? And I understand how humans behave, right? So when I said earlier, do I believe there can be a new bad event in the world next week and vol not spike crazily no because i believe humans panic when

really bad stuff happens and and panicking is in our evolution right so i don't that's not changeable so if we if we go with theories like that or premises like that we can say okay we believe vol will spike in extreme events when panic ensues, given enough of an instigator. And once that happens, vol tends to decay slower because people are unsure as when it's going to end, right? So vol has this fly up and kind of slow decay behavior that if you look at vol pop charts over the last 10, 20, 30 years, that's what it's tended to do. That's not that you're looking at 20 data points and saying, oh, look, empirically, it does this. You're saying, no, reasoned, it does. This is why this seems to be the view we're looking at.

And so if we believe that human behavior persists, then let's make the assumption that vol will pop quicker and decay slower. So that's, yeah. Does that make sense? Yeah, definitely. Yeah. I wanted you to bash on the machine learning guys a little more, but. Oh, sure. I can do that. But it ties into. Let me give you one giant bash of all machine learning for, you know, for example, in the vol world is all years of vol up until December 31st, 2021, the prior 20 years, vol distribution was unlike 2022. So if you had machine learned everything until December 31st of 21, you're like, okay, I'm ready to start a vol fund because I did eight years of machine learning. Boom. you're down huge in 22. That's the problem. And if you fast forward,

if you train it just on the last three or six months or something, so it captured 22, now 23 or 24, you're going to get taken to the woodshed. I'll go even more extreme than that. If you machine learn 2022, which is vol having short pops and quick sell-offs, you become a mean reversion vol trader, right? Which what's going to happen when that next panic event happens? There's not reversion at 30.

There's spiking to 50, 60, and you get short squeezed to death, right? That's the problem is you can't learn reversion of an asset that's based on human panic, in my opinion, right? And so a machine would have learned to revert vol every time it pops to 30 sell it sell it all off get short i i don't know about that right i don't want to be around for that next event where that's what you were trained or in theory you could train it to if it's only long to not right be like hey learn on this but only go long ball, then it's kind of... Okay, so let's go with at-risk though. You're only long, but if you learned in 2022 or a machine learned long ball in 22, you would sell out of all your inventory in the low 30s. And so spikes from 30 to 40, oh wait, I don't have anything in my inventory. It was supposed to stop at that level.

That was the top. Right. I was going to reload at 22. I was going to reload at 22. I was going to reload at 22. I couldn't reload. It never went back. Right. These are the problems with machine learning. So there's, you know, we have this unique variable in our model.

We call it phase shift, which is when it switches from reversion to expansion. That's how we look at it. Right. So mean revert, mean revert, mean revert. And then the next time there's a panic, boom shoots to that that's what we want vix 80 90 wherever it's going to go uh as as the high um so how do you know when you're flipping from a reversion to expansion you know it's a it's a there's a probability there's a there's a behavior so revert revert but have some ready for an and as soon as it's an expansion do do something else, you know, for example, stop selling your long inventory, right? As you're expanding,

vol is expanding, it's not reverting. So to me, that's a really, that probabilistic transition and the modeling around that is fascinating because there's very few samples or there's little data, sparse data and history to work from. So it's very much human behavior based and what we can use and identify as switches to model that behavior and when we think the decision should be made. I enjoy that part of our business because vol is very metaverting until it's not. Until it's not. Then it's all you want to own and along these lines back when you were on twitter so first tell us why you don't do much on twitter anymore we

miss you um but back when you're on twitter a few of your threads were about hey quant is great modeling stuff like you just said is great it works it helps but it's not the end-all be-all you still have to have a human you still have have the brain. You still have to know the why. Touch on that a little bit of what you were kind of digging into there. Sure. So I think all of that really goes back to the last three questions. I mean, not the last three, but I was going to say three paragraphs or a bunch of stuff we just said about MLAI learning, right? So if you're a quant and you model to vol to the last 10 years, you did not that great in 2022. You know, if you're a quant and you modeled 2022 and said, this is the new vol, and now you're not prepared for some major panic event, for what long vol is good for, right? Then you're not prepared for what come for, for some major panic event for what long vol is good for, right? Then you're not prepared for that because you, you, you,

you think a top is much sooner than that. So that all of that discussion, begets this, this truth to me that you quant, the markets are amazing for empirical research. There's a lot of data. There's a lot we can learn from observing that data, from tossing that data in different ways and looking at potential patterns that arise. But then concurrently, I feel like the regimes change and market behavior and structure changes so much and just kind of throws it in our face. You think you knew, you think you know a lot. Well, here's a whole new world for you, Wayne, right? That's what the market is speaks on a relatively frequent basis.

I told you it's that controlling hand, the invisible hand. It's the hand. It's right. It's what's it? Yeah. Let me, let me pull your strings this way. You haven't expected that. Yeah. So the puppet master market is, is one that I, rather than a hand it's that there's so many people trying to eke money out and are the same things that when there's clustering or or or mass around the same inefficiency then it then then it's no longer works i think that's more of the driver of of the invisible hand is is just people doing the same thing because it gets too easy. And then because everyone's doing the same thing, it breaks. So either way, that begets an inability

to rely on past data, on empiricism, right? And so to me, there's tremendous value in empiricism. And then there's, of course, what we have to understand about what we're looking at and understand what could change and what could go wrong and ask lots of questions from understanding the human behavior, the human condition, et cetera, et cetera. And so that's what we believe. And that's why we infuse both into everything we do. I was going to say, you don't turn off your computers, fire all your quants. You just say, hey, you got to look at it from both sides.

Yeah, absolutely. And I love there's this quote, actually. I don't know if I remember the exact quote. I'm a big quotation person. It was Dwight Eisenhower who said something to the effect of, I found that before going into battle, planning is essential, but plans are useless. It's the same thing. You've got to model it all out, but when you're in battle, it's like you have your modeling so you can look at it, but then you have to deal with what is now

happening, which might be different than your model. For nothing else to be like, well, we know that plan didn't work right exactly exactly and we know how to handle it had it worked yeah here's 17 others we can try yeah yeah here's here's what yeah and then or to use two other plans that didn't work but this is similar so we kind of have a have a boundary to what we're going to do based on the few plans that almost worked or something like that and then i want to end on you you gave your elevator pitch on what you guys do without talking about a straddle oh yes i did or uh intentional or no not intentional i think i straddled the straddle um because i right I'm always explaining what you do as they do a straddle.

They buy individual stocks. They buy the puts on the S&P. Absolutely. There's many ways to talk about what we do. So the primary thought I put out there that we're not spread trading, we're only long vol. So now you ask the second question, well, how are you long vol? Are you buying all out of the money puts in five years from now? Right. That's one way to be long vol. And so our long vol positioning is a straddle, which is effectively and more front month. So near term options and a straddle is being at the money around the underlying. So in our case, the market, the S&P. So your long calls, long puts close to at the money on the S&P. You're straddling it, which of course is where the word comes from.

And so by straddling it, as soon as one side moves enough, half of your book starts paying off with convexity and the other half starts mitigating your risk with concavity. Right. So let's say you own 100 puts and 100 calls at the money. And so you're conceptually agnostic to which way the market goes as long as it moves enough. Right. And so the next day you come in and you're and the market gaps down 10 percent. So great. Your puts went from a dollar to wherever, five bucks, and your calls went from a dollar to zero. They're gone. Bye-bye. But it doesn't matter that you lost a buck because on the other side, you made five, right? So your asymmetry is designed upfront and you're just

waiting for enough of a move in other direction. But of course, that position to hold is very expensive. So now you have to find ways to carry it. But now that seems to be the same thing we're talking about with the spread trend. But the spread is different because you can have asymmetry against you on the short side. Right. And so here you have positive asymmetry in both directions. So you have convexity for you and concavity against or against you. So in other words, I'm long a call, I'm long a put, market gaps down. My long put is convex to the gain. It's going to have right skew.

And my long call, which is the business I'm long, is losing. But all I could lose is that dollar. And when that dollar loses a lot, it's down to 20 cents. After that, I can only lose 20 cents, right? And so I lose less and less and less as the market collapses on my long call because I'm only in a little bit of premium. And my dollar premium on the other side keeps on expanding to $5, $6, $7, all the way up theoretically to infinity, right? And you can make money on the call side as well, if there's big... Or the other way around. Yeah, sure. The market can go up and up and your puts

shrink less and less and less. They're concave to that gain while your calls are expanding convexly, right? So having convexity to your profit and concavity to your loss is having positive asymmetry in both directions, in gain and loss. Whereas the spread trade has convexity to your lost positions, right? It can gap against you worse if you're, for example, go with some trades people might do is short at the money to go along the tail, right? So there, if there's not enough of a correction, if you're long a 30% tail and you're short at the money, the market gaps down 10% or falls 10%, however way it falls,

you're at the money has lost more yet than you're out of the money has started kicking in because its attachment point is another 20% out, right? And so you're down when the market's up 10%. Or sorry, when the market's down 10% on your put spread. And in that way, it's, in my view, counter thesis risk more than it is counter positioning. I would say a straddle is more of a hurdle to making money.

Whereas IE calls are a hurdle to your puts paying off. And it's a fixed hurdle with a fixed downside. And then you have a twist that your calls are single name stock calls that you're trying to say, Hey, if I'm just, but I guess I'll ask a different way. If you just did S and P versus S and P calls and puts straddle still viable, still works. And you just think this is a little better for a portion of our book, but we don't do it for the whole thing, right? So that works, but that is solely dependent on timing, right? Timing alpha.

So you have to trade the S&P well enough in both directions to make money on scalping those two sides, right? So if you're SPX by SPX, you're SPX puts by SPX calls, you have to properly trade the S&P, right? So if you're SPX by SPX, you're put SPX puts by SPX calls, you have to properly trade the S&P, right? So it's all about timing alpha. What we do internally is we have all S&P for the downside because we don't want basis risk on any downside event. But on the upside, part of our portfolio does trade the market, but part of it, to your point, it picks individual positions or sectors to beat the S&P. So our alpha there is not timing alpha, it's selection alpha. For example, we talked about energy earlier. We picked some energy names or positions earlier this year, last year.

And so where they've been the winner in the S&P, that call upside has beaten the S&P, right? So it gives us idiosyncratic opportunities to make money different from the market. And it's not as much basis risk because that's not what we're depending on if things go wrong, because that's the call side of the book. It's not the put side. So it's just another source of alpha to generate the P&L we need to carry the straddle or to carry all that long vol. And then you said you picked these stocks, but you're not sitting there in your bunker with your barons out saying, oh, energy, I might add some of those, right? So there's a sophisticated model behind that. Yes. I have not picked up a barons since perhaps the 1990s.

I don't know if that's good or bad, but that's the truth. I don't read anything about media and financial news or stocks. And I don't watch the NBC. This is not what we do. We're going back to quants. We're quants, right? So we've got lots of data. We have models. And so how do we do the stock picking? We have a screen that screens a universe of positions, the S&P 500 and a whole big universe of sectors, the ETF universe, to find positions that have certain when I first built this model that is looking for relative strength effectively in positions. It looks for positive asymmetry and then we find cheap options to express that payoff, i.e. price volume behavior to find strength. And then we find the cheapest way to buy that strength through call options. And of course, get this

payoff on the one side of our straddle. Yeah. So hopefully that answers your question. Right. Well, I'm leading the witness because i know the answers already but the uh what i've liked about it right and i i don't want to say an argument but i was pressing you three years ago like well hold on and that was there was that was that late 2020 or was that 21 when growth and value just had like a to quote your yeah that was late 20 that an eight sigma move right it was great that was the late uh 20 that was late 20. An eight sigma move, right? It was crazy. That was the late 20. That was the election around November of 20. Yeah. Yeah.

I mean, it's not because of the election. It was around the election time. Yeah. Growth just sold off huge. Growth sold off huge and value rallied huge. It was one of the greatest dispersion days of growth versus value that we had seen in decades. Yeah. Yeah.

So in that way, you're taking on a little dispersion risk, right? If there's that quick shift, your stocks you pick versus the S&P, you're taking on a little dispersion risk, right? If there's that quick shift, your stocks you pick versus the S&P, you have a little bit of risk there on. Yeah. I would say absolutely we're taking on that dispersion risk. We're taking on that, if you will, regime shift risk, right? And especially if it's quick. If it's slow, the model will slowly- It could be to your benefit, yeah. Yeah. It could be to the benefit, right? Because the model will move out of those names into the other names. It transitions itself by finding the

new strength. Um, and, but that takes months, right? So if that event or that shift happens in a day or a week, it definitely does hurt us. Right. And we've seen it in real time. It was in growth. Then it was in value. Now it was in energy. That was in value now it's in energy that was right it it definitely is dynamic um i love how we're putting energy outside of growth or value it's just yes energy it's got its own realm um but you don't consider yourself a dispersion trader right so that's a little weird and to be short that dispersion risk not really short it, but it's there. I mean, it's there as a byproduct of our portfolio construction, right? So let's start high level and say, you cannot make any money in the markets unless you have some risk. And everyone tells me that, you know, we're low risk. The question is, what is your risk? Now, don't say you don't have risk, just understand what it is,

right? And so obviously there's many areas. We have cost to carry risk, just understand what it is. And so obviously there's many areas. We have cost to carry risk, just theta, start there. We have a hurdle to meet for us to make, even if our trade makes 20 bps next month, if theta was 25 bps, we're down. So we have a high bar to cover. So obviously that's just being long options. So in that vein, we can go down our risk. Dispersion is one of our risks because of how we've chosen to make money. And in my view, that risk that we're taking, the dispersion risk, our upside is far in excess of that risk. So we'll call it once again, asymmetry in our favor. I see way more opportunities where that picking system that seeks that strength, even though it can get toasted in a quick rotation, given how infrequent quick rotations are, it'll make more money over time than the times it loses.

And you saw that in real time, that time we're talking about, it wasn't a huge, right? It wasn't like you're down 20% or something. It was just a mere flesh wound. It was probably around 2%. I don't remember. No, certainly not 20%. That's not, no way. But I mean, I say no way, because we have different pieces of the portfolio. It's contained with portfolio construction boundaries. That whole model in itself is 30% of our up capture of our call side. So it's 30% of half, it's 15% of our up capture of our call side. So it's 30% of half, it's 15% of our book, right?

At the end of the day, it can't do that much damage. And so, yeah, we take things with known boundaries. We have a portfolio construction. We know where risks live in each module of our portfolio. And collectively, all of that is what we do to make money trading long haul. And we all have to take our risk somewhere. And yes, we have that risk and we understand that risk. And I'm not going to trade away that risk because I like that risk for what else it gives me all the time or most of the time.

As our similar friend, Jason Buck would say, that's the ultimate risk control is position sizing, right? So even if everything I'm doing is wrong and out of control, it's just that small piece of the portfolio. Exactly. I'll end it here with, I didn't prep you for this, but this year we're asking everyone for their hottest take. So you already gave a pretty hot one on AI. You got any other hot takes? Something doesn't have to be market related that the Rams are never going to win another game. I don't know if you're a big football fan. No, not really. Not really a fan. That Santa Monica is overrated. No, Santa Monica is underrated. Don't move move there there's no rating it's like that's that's

high enough for this town um i mean i that that that vol is anomalous this year how about that right that's like i i just find it funny that people like oh it's i mean i'll say it's it's misbehaving what does it even mean right it's like or vol is dead or it's it oh, it's, I mean, I'll say it's misbehaving, but what does it even mean? Right. It's like, or vol is dead or it's, it's just, it's doing what it does. Right. It's behaving in the way it needs to behave or it behaves. This is just a version of vol that we weren't used to in the last 10 or 20 years. And had we been trading vol for 700 years, we would have seen this many times before.

Oh, this is the vol of the 1422s. Right. I was going to say 1492. Of the 1492s. Oh, this is the Vol of the 1422s, right? I was going to say 1492. The Vol of the 1492s. Oh, this is Columbus Vol, we could call it, right? And so I just, I find it, I guess to me,

the popular, like, everything's terrible or everything, or Vol doesn't work anymore. I mean, statements like that. I just, this is just silly. It's just a different regime. We have to adapt to it. And if we're better to adapt. It's just a different regime. We, we, we have to

adapt to it. And if we're better to adapt, there's still going to be panic in the world. There's still going to be events that come up and crises and who knows when, and this is not an anomaly. This is just what we're, we are going through. And if this is the new, the new normal, then we trade it for a while, but it's likely not the new normal because there is no normal that that's what i'll do yeah um hot take there is no normal yeah uh awesome thank you so much wayne we had our our troubles getting this scheduled um sure yeah but we did it we got it done yeah actually i want to slightly amend that last um or not amend, append to there is no normal. There is no normal in tail events. Right.

Each one's different. And every, or is there no normal in risk, in the way risk plays out? Anyway, sorry, go back to the, you're closing. I didn't mean to interrupt your close. No worries. And I wanted to close by saying many sophisticated investors share your view, right? Because you guys are moving on going past 500 million or so in the near future here. So congrats on all the success. It's been fun to watch you along the way.

So congrats on the success and convincing people, although maybe they're convincing you versus vice versa that, Hey, we know there's not a normal ball event and we need to be there for it. Yeah. I think we're convincing each other. Right. So we're all holding hands and trying to make the best of this wackiness. And it takes longer than an elevator ride.

It does. It takes a long stairwell. Yeah. Yeah. There you go. All right, Wayne. Thanks so much.

We'll talk. Thank you, Jeff. Thank you. Okay. Take care. You've been listening to the derivative links from this episode will be in the episode description of this channel.

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