My guest this episode is Cem Karsan, Founder and Senior Managing Partner of Aegea Capital Management.

Cem began his career in the pits, and so we begin our conversation with a discussion by comparing and contrasting today’s market versus days gone by. And, perhaps more importantly, the wisdom gained from that era.

It was in the pits that Cem began to understand and develop his intuition for markets and what would become the colorful cast of characters he uses to describe what’s driving flow: Gary the Gorilla, Vanna, and Charm the Sloth. How these characters cooperate or fight amongst themselves provides Cem with a forecast as to how markets should behave.

It seems like these are new and growing forces, but Cem argues they’re as old as time. And, more importantly, increased awareness does not mean they can just be arbed away: they are, potentially, fundamental forces of markets.

We end our conversation with a discussion of how these flows can have profound impacts for equity factor performance and what this all means for stock pickers.

I hope you enjoy my conversation with Cem Karsan.

Transcript

Corey Hoffstein  00:00

All right 321 Let’s bogey. Hello and welcome everyone. I’m Corey Hoffstein. And this is flirting with models the podcast that pulls back the curtain to discover the human factor behind the quantitative strategy.

Narrator  00:19

Corey huff Hoffstein Is the co founder and chief investment officer of new found research due to industry regulations he will not discuss any of new found researches funds on this podcast all opinions expressed by podcast participants are solely their own opinion and do not reflect the opinion of new found research. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of newfound research may maintain positions and securities discussed in this podcast for more information is it think newfound.com.

Corey Hoffstein  00:50

This season is sponsored by simplify ETFs simplify seeks to help you modernize your portfolio with its innovative set of options based strategies. Full disclosure. Prior to simplify sponsoring the season, we had incorporated some of simplifies ETFs into our ETF model mandates here at New Found. If you’re interested in reading a brief case study about why and how visit simplified.us/flirting with models and stick around after the episode for an ongoing conversation about markets and convexity with the convexity Maven himself simplifies own Harley Bassman. My guest this episode is Jim Karsan, founder and senior managing partner of Igea Capital Management. Jim began his career in the pits. And so we begin our conversation with the discussion by comparing and contrasting today’s markets versus days gone by, and perhaps more importantly, the wisdom gained from that era. It was in the pits that Jim began to understand and develop his intuition for markets, and what would become the colorful cast of characters he uses to describe what’s driving flow, carry the gorilla, Vana, and charm the sloth. How these characters cooperate or fight amongst themselves provides Jim with a forecast as to how markets should behave. It seems like these are new and growing forces. But Jim argues they’re as old as time. And more importantly, increased awareness does not mean that they can just be archived away. They are potentially fundamental forces of markets, we end our conversation with the discussion of how these flows can have a profound impact for equity factor performance, and what this all means for stock pickers. I hope you enjoy my conversation with Jim Karsan. Jim, welcome to the show. Really excited to have you here. I feel like I’m getting you a little late, though you came hot on the Twitter scene, everyone all of a sudden knew who you were knew your colorful cast of characters you showed up on every podcast, and I feel like I got that’s sort of the short end of the stick, given the fact that do a seasonal podcast here,

Cem Karsan  02:59

you had your chance you could have had messy.

Corey Hoffstein  03:03

That’s where I was playing hard to get. This is what happened. That’s all it was? Well, you know, I think the good news is, at least for our listeners, is that we’re going to try to take this a little bit of a different angle than maybe some of the topics you’ve tackled on other podcasts. I know if folks want more of your background in terms of your life story, and you being a world traveler, they can sort of get that other places here, we’re hopefully going to dive into some more technical details. So without further ado, let’s jump into it. And maybe to get started and set the table with a little bit of context. Can you provide a little bit of a high level overview of some of the strategies that you actually manage, for example, what instruments you’re trading the horizons, you’re trading over that sort of thing?

Cem Karsan  03:43

Yeah, absolutely. So my background is in volatility arbitrage, particularly equity arbitrage. Our three strategies are legacy strategies, a long vol strategy that focuses on the first three to four months of the curve in both equities and equity indices. It trades long vol on a both a correlation and dispersion basis. But it also is always long kind of units and convexity, its long skew, which is rare for a lot of long haul strategies unless you’re a tail fund. We are relative value though. So in being long haul, our long haul strategies kicked off over 15% alpha for over eight years, which is you know, a badge of honor despite the market going straight up and volatility particularly as several years they’re not doing very well in 2016 70 in the with the lowest performance of all time. That is our oldest strategy. We also have a vol neutral version of that that focuses on the same kind of alpha generating piece but without the long volatility exposure. And then we have a third newer strategy which is focused on the distributions. Underlying those long haul and vulnerable strategies for market direction and law have gotten better and better over time and I talk a lot about vana and charm and these functions of reflexivity that affect market directions. Those take those distributions from the factors and really use them for directional vol, skew and market directional bets. So those are the three products. But that one’s completely different, obviously not volatility arbitrage, but really came out of necessity from the other two products.

Corey Hoffstein  05:15

Now you started your career in the pits, and we’re working there during the.com era. A lot of people are looking at markets today and saying they’re frothy, they sort of echo with a lot of what was happening during the.com era. Can you compare and contrast for me markets then versus markets today? And maybe in particular, what’s going on in the volatility markets?

Cem Karsan  05:36

Yeah, so I started in this business in 98. So right on the tail of long term capital. So 2000, the the tech bust was really my first volatility event that I experienced as a trader. And it really informed a lot of how I see the world, even though everybody speaks about it as a kind of evaluation of that there were a lot of vol, driven factors that led to what happened in 2000, through 2003. And those factors are now stronger than they’ve ever been. So I think that although there are similarities, the key here is that there is a much bigger vol complex now than there ever was, the factors that are at play in the oil markets that drove a lot of kind of the unwinds in 2000 are, are significantly bigger and significantly more important now. So in that sense, now, this market is almost 100%, more leverage than it was in 2000. So I think that’s a key difference, the Fed reaction function is very different. Obviously, in 2000, the Fed had a lot of room to move interest rates lower and to provide liquidity. We’ve seen the effects of that over the last 20 years, they obviously pushed the bubble from equities over into the real estate market. And then we had the second kind of trauma from that in 2008. I think right now, the Tina effect and the move to fiscal and the change, that that’s going to have on how this plays out is going to be very different. I think details are much more dangerous in this market than they were back then. And not just because of the size of players in the volatility market and the lack of liquidity. But also the fact that the Fed will not be able to come provide the same amount of liquidity almost by choice as well, because of the move to fiscal and increasing inflation.

Corey Hoffstein  07:26

Before we sort of dive into those factors more deeply, I do want to take a moment to sort of acknowledge that a lot of the physical pits have disappeared. And the skills learned in those pits aren’t necessarily learned by traders that are coming up today. I’m always curious to ask people who worked in those pits, what lessons from that era do you think are sort of permanent and are still important to you? And what lessons are now outdated?

Cem Karsan  07:51

Yeah, so on social media, I talk a lot about kind of these flows, the reason I came to learn about their importance was really a function of necessity, as one of the biggest market makers in the s&p 500, and equity indices during the financial crisis, from 2007 to 2010, I had what all the dealers had on and in size. And so, you know, variably, you would set the positions against kind of where the flow was going, as all market makers do, you’d always make sure to have a significant amount of edge and the trades when you put them on, and that structurally good trades, you try and hold for a little bit longer. But invariably, when you went back and did your analysis, you’d realize that those were not profitable trades, more times than not, especially the bigger ones. And then you go do an attribution analysis and say, Okay, why is that what we came to learn very early on was that that edge was going into other places in the market that was going into the distribution of markets, it was moving the markets, it was changing the skew dynamics, it was changing the implied volatility dynamics at play, as those positions kind of move through time and market move. And so those lessons, what I’ve learned there has really informed a lot of the edge and alpha that we generate. Now, as a firm, even though you know, we’re not making markets anymore. So I think that those lessons are incredibly valuable. I honestly don’t think there’s a better place to learn than actually physically being in a pit, seeing how actually the flow comes through who the customers are, what they’re doing, how they’re managing the portfolio, what kind of reactions they may have to different scenarios, that understanding has really allowed us to understand the data that we look at now. Much better. I couldn’t have modeled or come up with these theories by just data mining by looking at the data on hand it really, because a lot of it is very complex, multi dimensional decision making stuff. So really having that qualitative understanding has been incredibly powerful for coming up with a sound quantitative framework.

Corey Hoffstein  09:52

For folks coming up today. Is that still a skill set they can learn given that the pits are no longer here? Is that something you can really only Learn through apprenticeship at this point.

Cem Karsan  10:01

Well, I mean, how do we all learn, right? We all learn through, like you said apprenticeship from learning from others. The beauty of the pit was it was like apprenticeship, with 300 other traders surrounding you at once. We are watching great traders who have been around for 20 3040 years who’ve lived through it have gone through that pressure cooker all at once and the same, right? It’s an intense place you, you learn probably 10x What you would at 10x The speed right? All at once. And so I think, you know, there are some other lessons to there, right? Learning how about yourself, and how to control the emotional aspects of managing capital and being in stressful environments, all those things, I think it’s a very hard thing to learn in other places without working, at least for other people who have had that experience or have that expertise.

Corey Hoffstein  10:47

So you’ve taken Twitter a bit by storm, and you use a large number of colorful characters to sort of get your point across, I think there’s Gary the gorilla, there’s charm, the sloth, and Vanna Vanna White, and you use these characters to illustrate your views. And it’s a really fun way to get your message across. But I know that it’s also they serve as really, really important personifications of your investment philosophy, in the lessons you’ve learned over time. So can you explain who these characters are and why they’re so important to you?

Cem Karsan  11:19

Yeah, so one thing people don’t know is, along with financial mathematics and macro policy, in college, I studied English literature. So So that’s part of the driving force here. It’s like I figured, if I’m gonna be communicating this stuff, I want to do it with a little bit of color. But yes, they’re very important. So this all starts with an understanding that options, positions, dealer positions move, you know, their deltas change, and their vol aspects change over time. And if dealers are position and a major with major positions and are getting longer and longer vol, that naturally reflexively is going to have a dampening effect on if they’re getting longer skew, that’s going to have a dampening effect on that skew. If they’re getting longer deltas, that’s going to drive the market up. All of this is reflectivity. At the end of the day, I put out a piece a while back early on about a clerk named Gary in the pits, and Gary would always be challenged to do 500 Chicken McNuggets something crazy or shoot 100 free throws and, and make them and so you know, but betting against Gary was always a bad idea. Because Gary was invariably on the winning end of these trades, people would give him money or a cut of the pie if you accomplish the task. So unlike insurance, where you know, tornado insurance where you want to have, if you have insurance, the tornado, having the insurance doesn’t affect whether the tornado comes through town or not. That’s real insurance. In this situation, there’s reflexivity, Gary is going to actually work harder, make sure that he knows that he’s going to be able to make XYZ bet. And so you don’t want to bet against Gary, you don’t want to bet against the reflexivity that was the point that’s what kind of Gary came from this idea of dealer positioning is critical positioning in general the markets people realize this across all other assets, right? Short interest, like people look at short interest, right? That’s reflexivity to things along those lines. I looked at it lots of different ways, but people don’t understand how important they are in a leveraged market that’s growing tremendously and has very kind of significant exposure like vol exposure. So there’s Gary who’s dealer positioning particularly a gamma is what I tend to refer to him and there’s vana which is the change in you know, per change in volatility. The change in delta of dealer positioning charm, who we colorfully Use a slot for because he’s very slow and just working it works overtime, charm is per amount of time that change in delta. There’s also other ones that I don’t talk as much about, but Volga and BOMA and those two are, you know, those same effects but on volatility, all of these really we measure them very closely we look at dealer positioning we take without giving too much secret sauce we take from the actual executing brokers all of the flow both prime brokers as well for structured trades as well as exchange traded. And we mark them as you know, whether they’re dealers or type of customer that’s executing it, whether it’s hedge, not hedge, and we structure this data and then we use our own kind of we look at the volatility surfaces, we kind of create some models that allow us to kind of process all this data and give us a real good sense of estimation of what the dealer positioning is like over different explorations. And that allows us to essentially say okay, this is about how much Volvo or vomo or aurvana or charm or gamma exposure we have, and that is a major input to our distributions, both for volatility as well as market and so, you know, our strategies really look at these distributions of market vol moves in each market move as well as kind of skew moves. And so all of these are inputs to those distributions, and drive a significant amount of structural alpha

Corey Hoffstein  14:53

2020 felt like a year where this concept of option dealers having a major reflexive impact upon the underlying went mainstream, you started to see it appear in the news a lot more. And there’s been a lot of people putting different theories out there as to why as to really what the driving Greek is a lot of people talking about gamma, or delta, you very much seem to focus on vana and charm as being the real meaningful drivers. And I think you’re very unique. In that view, one of the few I really hear talk about those Greeks in particular, why do you think they’re so much more important than the others?

Cem Karsan  15:30

Yeah, so I’m glad you asked that question, because it’s actually the one thing I haven’t really discussed as much as I think is necessary. If you think about it, tail events don’t happen frequently, right? And tail events, that convexity is when gamma really matters, especially for indices for especially for markets writ large, right for single stocks, like GameStop, or whatever gamma might be more important because of the idiosyncratic kind of tail risk. But for markets writ large for indices. Broadly, those tail events are rare. So gamma matters a lot for those events. I’m not diminishing the value of gamma for risk management and for understanding, kind of for a big move, how much gamma FX there are, like March of this year, gamma was was everything right? But in 95 97% of scenarios, they’re not tail events. They are day to day, what’s happening in the markets, what are the driving forces? And how can we predict and understand what’s happening? And what vana and char Mars are those Delta effects like gamma are, but for those other 95% of scenarios, and they really drive so much of kind of these old market adages and understandings of how markets work. If you understand Vaughn and charm, you’re really understanding risk premia. And you’re really understanding the effects that risk premia have that convexity which is being hedged, managed and warehoused in places and hedge with linear hedges, and the effects of time on that construct on these carry trades, so to speak, and the movement of volatility on those constructs, like the risk that actually levels in those products. So, again, I could name a million adages actually want to do this on social media at some point, just have people throw in an adage and give them an explanation for why vana and charm are driving that because almost every single one is driven, you know, never shorted all market, right? Like why because if you’re sitting there and nothing’s happening times gonna pass, dealers are short, put long call in the indices, because everybody’s long, the whole world is long. If you live, you eat, sleep, breathe, your long, you want a home, you have a job, you know, your lungs. And so everybody, all dealers are short, the carry trade of short put long call. That’s why SMP skew is as high as it is the highest in the world. And if that’s the case, dealers have stock to buy every minute day, time passes, the more we don’t move vol comes down as well. term structure is upward sloping. So there’s a natural vana in the market, as vol slides down the term structure. So all of these factors every day show you you know, kind of how the vol is going to be bought back. Also what times it’s going to be about back when people are going to re hedge their books, it explains a lot of kind of weekend effects and a lot of other day to day things.

Corey Hoffstein  18:11

I’m actually gonna give you the opportunity now, because I found a tweet of yours that I want to read to you where you said, so many cliche market adages which seem to describe almost magical market phenomenon can be relatively easily explained by structural derivative flows. Now sort of have two thoughts. One, I obviously want you to explain that which you just mentioned, but to what it brings up for me is this idea of is this new. For many of us thinking about modern markets, it does seem like this reflexive option based hedging flow that’s having such a large tail wagging the dog impact seems like a new phenomenon. It sounds like to you it’s not and I don’t want to put words in your mouth. But I’d love to know when you think this really all started happening. And maybe whether it’s accelerated over time,

Cem Karsan  18:58

at least since I’ve been in the business, which is 22 years. This has been a phenomena that’s existed. I know that for a fact because I’ve traded off of it. But my broad view is that this has been around almost since the beginning of time. And the reality is that risk premia is not new risk premia has always been there. The need to hedge structural long exposure and all assets, right has always been there. The need for insurance has always been there. And you know, one of the biggest risk premia is is is market exposure, right everybody, like I said, As long so that is a structure carry trade. We have other carry trades, right? We have currency carry trades. We have all kinds of other characters but they’re structural and they’re not going away. And when you have that, that risk premia that’s going to create these effects, you know, we call them Greeks, and we refer to them as if they’re tied to options, but risk premia itself is essentially this, you know, this carry trade this volatility exposure that I’m talking about. So, these effects have been around forever as far as I’m concerned, you know, they may grow as and they may be much more predictable, which I believe they definitely are now, because not just Are there more people doing it, but there are more set products that people use. So it’s easier to predict kind of timing of some of that risk premia, when things get bought back, etc. But the exposure itself has always been there. I’ll throw a couple adages out here just to kind of make this fun. But markets climb a wall of worry, right? Why do markets climb a wall where everybody thinks it’s because well, there’s some shorts out there, right? They’re more shorts and they can be bought back. That’s some of it. That’s reflectivity as well. But the reality like we saw at the election, when we were able to predict that election, the distributional outcome of that was fairly easy to predict from our point of view, because we understood the positioning, people were very worried implied volatility was very high skew was very high, that leads to a ton of potential energy right in the form of vana and charm, especially when the curves in backwardation like it was. This is a slingshot waiting to be kind of released the second that event or that insurance premia that risk premia gets pulled out markets take the stairs up and the elevator down. Why is that not just because people are scared on the way down and they sell and they’re long you know those things are connected to the need for insurance premium and dealers are essentially embody that risk by being short that that premium which causes gamma effects on the way down which is reflexive which causes vana and charm flows on a decay of those of those premium you know, I already mentioned never shorted all market, sell the rumor buy the news, same thing, right. I mean, all of these things, if you think about these are, these are core principles to what how we trade markets day in day out. And they’re structurally tied to this idea of insurance premia in the market and risk premium. Anyway, I can keep on going never catch a falling knife. bull markets are born on pessimism, growing skepticism. But all of these things, which are again, the adages that really matter in day to day are again, in my view, tied to risk premia, and these effects which we can actually measure. And I think that’s the important part. They’re not just concepts and ideas in general views, we can measure these, again, measure the flows and demand that come out of them, and really add structural alpha to our trades.

Corey Hoffstein  22:11

There’s a big time based element when you discuss these effects. So for example, you often mentioned windows opening or closing van or going on vacation, or really specific dates that seemed to impact the path dependency of your views. Can you expand on what you’re looking at and why certain dates are more important than others?

Cem Karsan  22:33

Yeah, so one of the great things about time is it’s predictable, not just seconds, and minutes and days, but also, you know, expiration cycles, understanding also weekends and how dealers measure time, which is not linear, it has to do with, you know, trading days versus calendar days. Also events, right? Time is different around events. And so, if you can understand those concepts and understand the positioning around these different prospects, or other expiration kind of cycles, when that risk premia is coming out of the market, you can really understand when these vana and charm flows are coming to fruition, there’s also again, this isn’t just understanding the risk premia that’s out there, it’s understanding the participants in the market, and how they are managing or having to manage risk around these positions. And some of the bigger ones. And again, remember, everybody’s got kind of the same position on it’s a good position, it has, you know, structural edge to it. It’s a carry trade, it has a tail because everybody’s in the same position. But there’s a chase, right? Everybody’s trying to get ahead of these flows. And the bigger entities, which are sometimes not as nimble, like banks, etc, really do it at a somewhat predictable end of day beginning of day kind of window. And so people are on to some of these flows, right? And then people will try and front run or get ahead of these flows, right? And so understanding these participants understanding that they’re coming, that they’re inevitable, and how the Marketplace is going to react to that is critical. But you know, these are the things that we’re looking at when we look at kind of the path dependency tied to time and what’s driving these factors. We model the behavior and it’s changing over time, right, as people become more cognizant, we’ve talked a lot about the overnight kind of outperformance that’s something that has always existed to some extent, but has really accelerated and that acceleration, in our view, we feel very strongly is tied to these flows from vana and charm which are growing over time and which are quite consistent and participants have have realized it and realize that there’s an edge to kind of getting ahead of these flows. And so this really drives an outperformance and the extended day now question is, you know, will there be front running of that and how does that affect it? You know, all of this stuff, those flows aren’t going away. They’re growing if anything, you know, the edge and alpha that’s you can gain from it is growing, but that also kind of affects the market, you know, and how participants are going to time that so Have those are kind of the things we’re looking at.

Corey Hoffstein  25:02

Speaking about the acceleration of these events, in a prior conversation that we had, you said that you thought the one devaluation in 2015 really served as, and I’m quoting here a warning shot for what the new market regime was gonna look like. What do you mean by that?

Cem Karsan  25:20

Yeah, it’s interesting. People don’t really, you know, you hear a lot of talk about 2018 XIV blowout and how that may have been kind of a first kind of clue that things are changing in the market. My view is August 2015, was really kind of a new thing. In my 22 years of doing this, there was no more stressful that, especially given how small a move that relatively was, screens were black for about 30 minutes to an hour there, there was no market for how small a move that was, you know, it really exposed this illiquidity on the tails that now exists dramatically. That, you know, has always existed to some extent, but as a structural phenomenon. And we had a situation where skew was at a record level because of margin calls. It really spoke to kind of again, a warning shot to what was coming 2018 was a similar scenario in February, with the XIV blowout, but at least people had some participants had experienced something and is a bit more controlled, despite being somewhat chaotic than August 15, was because it was at least something that was in the dataset. I think that was an important moment. And now that we’ve had two events like that, call it three now with March, I think people are beginning to realize that this is not the same market and that extent, especially with a moving towards a removal of liquidity. With the move to fiscal that I mentioned earlier, I think there, people are waking up to the fact that there’s a very toxic, dangerous kind of set of risks here, with a volatility market that’s as big as it is with illiquidity on the tails, and a increasingly lack of ability to respond with the liquidity necessary given them.

Corey Hoffstein  27:03

So I remember one of our first really in depth conversations, which was incredibly illuminating for me actually occurred when I was writing my illiquidity cascades paper, and you were one of the first people to really highlight for me how these index flow effects within the world of derivatives and options could actually be having profound impacts upon the return structure of the underlying stocks. So for example, you actually argued that volatility in 2017 was a low, most people would argue that volatility in 2017 was low because stock correlations were low, you might actually argued the inverse, that correlations were low, because volatility was pinned. And I think that’s counterintuitive for a lot of people. So I was hoping maybe you could expand on that idea. Yeah. So

Cem Karsan  27:52

again, going back to days, in the pits, you see the trades happening, you see the hedging happening in real time. You understand? This isn’t correlation that’s making me make his statement. This is causation. I’ve seen it in real life. There was a fun called Catalyst. Some people might remember it, and 2017. They pin the market in August, literally to the strike. And they’re one by three, they were way bigger than the market. And that’s just one of many examples in 2017, probably the biggest example and then, you know, there’s something should be written up about that actually episode because, again, very illuminating important thing that happened, the market did not move in August away from that strike, because there was so much open interest, we moved exactly to that strike set. And they had an incredible performance. Obviously, they ended up getting bigger than the market. Everybody knew, like their positions at some point. And they ended up having major problems soon after that, as the market kind of tends to do reflexively, kind of get after the potential whale that’s out there. But we saw in 2017, the lowest implied and realize volatility in history, realized volatility was 30%, lower than the next lowest in history, which was in 2006, which again, is not really a coincidence, right? These are times when implied volatility was at its most supplied in history. Why are these periods Why was there so much selling of implied volatility? Tina, right, there is no alternative to chase for yield, people discovered options, option selling was incredibly profitable, that profitability led to more assets, not just coming in, but just from the profits alone, which led to more selling and eventually led to the situation where everybody all dealers were oversupply with vol at incredibly at historically low levels. What does that do that forces gamma hedging, and this is all focused on the indices to be very clear, not in single name, all focus directly on the indices. So all the gamma hedging forces realized volatility down. That said this wall selling is not happening in the single list, names and idiosyncratic risk still exists. At the end of the day, there’s a cure for cancer, that stock that came up with a cure for cancer is going to move if a stock meets earnings. dramatically, they’re gonna move and because the volatility there is not pinned, it also allows it to move. But if those stocks move, and the index is pinned, that means another stock or another set of stocks have to move in the opposite direction. And so we also had the lowest correlation in history by about 20%. Not a coincidence, it’s a structural phenomenon, the index is pinned, ultimately, that’s a different center of trading. And the single names have to go in another direction, this has to happen again, saw it in real, you know, real life, dispersion trading was the most profitable it’s ever been during that time, despite higher and higher dispersion valuation. But yes, something I saw in real time knew it before. Again, this goes back to this reflexivity that I’ve talked about. Again, again, it’s amazing to me how few people really understand this critical kind of component of how markets work. It’s all a big machine. At the end of the day, there are flows that’s mechanical, so many people are trading these markets, based on valuations and other things that that aren’t the daily voting machine. They’re this kind of long term weighing machine, and the voting machine is really what matters, day in, day out. And, you know, I think to be a participant in the market, if you don’t understand that machine intimately, well, you’re, you’re gonna have big problems, not only because you’re not gonna have that edge, but actually it puts you at a disadvantage, because you’re making bets on things that ultimately are not tied to the ultimate performance. So in

Corey Hoffstein  31:26

a similar line of thought, in the last year, one of the things that we’ve witnessed is this really dramatic increase in speculative call option buying, in particular, in single name, equities. And so much so that, you know, the new narrative is about orchestrated gamma squeezes through this unstoppable force. And so my question to you is, if we have this pinning, that’s occurring at the index level, and these gamma squeezes that are occurring at the individual stock level, what happens when the unstoppable force of the gamma squeeze meets the immovable object of the index pinning,

Cem Karsan  32:01

great dispersion trading? That’s what happens. And that’s what’s happening now, right? I mean, implied correlation is, at some of the highest levels, it’s been in a long time, and it’s happening at a relatively high vol level. And again, that is exactly because of what you’re saying, we’re also seeing incredible rotation. We early on, you know, from a macro perspective kind of picked up on this, you know, interest rates are likely to go higher with the move to fiscal right. But it’s important that a lot of this rotation we’re seeing is not just those macro effects underlying the market, they’re actually these volatility effects, these mechanical effects where, if there’s so much retail call buying in these single, these high flying single names, and the momentum slows, that creates negative vana flows and those products, whereas in the indices, like we’ve talked about, there’s significant positive on the flows, because puts are morbid, and dealers are short put. So you have this kind of opposite situation where these high flying single names have really high cost skew, and dealers are short call long put, whereas in the indices, you have the exact opposite. So you’re having this really heavy flow in opposite directions here. And it’s almost across the board, everybody has the same position on this is ultimately reinforcing this massive rotation we’re seeing and can really give it legs for a significant period of time. And again, it’s something that people don’t understand are talking about people talking about the duration trade and interest rates as a fundamental view, there’s a lot more going on under the hood.

Corey Hoffstein  33:24

So I do want to talk about some of those macro pieces, because you don’t shy away from expressing your views about them. You talk about the macro landscape, and the macro landscapes, effects on sectors and factors and styles and individual securities and thematic baskets. So can you explain for me maybe how these puzzle pieces do fit into this flow driven market?

Cem Karsan  33:49

Yeah, so I’ll be clear, I, I try and shy away from what I call fundamentals, which are kind of earnings and other things. Specifically, I want to know how are these things affecting flows? That’s ultimately how are they affecting the machine. And the biggest input into the machine is the Federal Reserve or central banks in general, and the Treasury for the longest time the Treasury wasn’t doing much. So it was just the Federal Reserve, right? So when we talk about, you know, again, another adage, like don’t fight the Fed, why, because of the reflectivity of the Fed is pumping, if the Fed is pumping a ton of money in right, there’s a ton of liquidity. That means gamma essentially, is over supplied. if gamma is over supplied, the markets not going to move, it’s not going to be able to have the tail which is going to create vana flows, which are going to drive the market up. This is how things work. So the biggest flow of all the pipe is coming out of New York Fed right and so or has been and so understanding that has made a lot of people a lot of money even though they don’t understand understand the underlying mechanics thing we were able to pick up on early on as a move from the central banks and monetary policy to fiscal policy changes everything. The pipes all of us wouldn’t flow to a completely different set of constituents. It’s not flowing to companies or wealthy individuals anymore, it starts flowing to individuals. And so the second you start thinking through that, what does that mean? What does that mean for you know what participants are going to change the market, you get to places like retail option buying is going to go through the roof. And that’s going to have XYZ effects. Or more importantly, once this economy, reopens a lot of that money that was flowing into the market is going to flow into goods into services. And ultimately, that’s going to drive not asset inflation, that money’s not falling into investments is falling into goods, that’s going to create a better earnings, a stronger economy, and ultimately, inflation. Now, inflation, higher rates is very different than lower rates, right? less liquidity to the markets is very different than more liquidity. And the second you start piecing through that framework, you really begin to understand the risks on a liquidity driven bubble or market right with all these teen effects. Now rates are going higher the Tina effect on wines, money comes out of equities, vol goes higher, there’s nowhere to you know, hedge, there’s all kinds of risk parity issues, all the things that we know. But that framework, this understanding of the machine, and just looking at the flows from the top down, really allows us to make I think, sound, long term and very short term kind of models for distributions of the market. We talked about shying

Corey Hoffstein  36:25

away from fundamentals, and a lot of people do ultimately think right that inequity should be equal to the discounted future cash flow, in the short term, the markets a voting machine in the long term. It’s a weighing machine. And I guess what I would suggest is based on this conversation, it almost seems like the weighing machine never comes into the equation that that this is all a flow machine. And so I guess my question to you would be, is that ultimately dangerous? Or does it not matter that there’s any true connection here to underlying fundamentals in any way? What happens if this just becomes a flow machine for another 10 years, and it becomes wildly distorted in terms of what prices are relative to fundamental company cash flow.

Cem Karsan  37:07

So I want to be clear, in the very long term, all that matters is cash flows, because at the end of the day, at some point, you’re gonna have a liquidity crisis, at some point, liquidity is not going to be available. And when the Quiddity is not available, companies have to create their own liquidity. And that’s where fundamentals matter. I’ve used this analogy before, it’s kind of hokey, but I can’t think of a better one, if you think of a better one, let me know. But if you’re on an airplane, and you’re 30,000 feet off the ground, that 30,000 feet off the ground is the valuation gap, right? That’s the things are really, you know, valuations are really high. But if those engines are firing, are you worried up in that plane about the valuations are you worried about is the speed and trajectory of where you’re going based on the rocket, you know, based on the engines, based on the flows, that’s what matters, the flows are what matter for where you’re going in the market. But when all of a sudden those engines go off? How far off the ground you are, is all that matters. And so it’s more of a risk management tool. And ultimately, it really matters when you have a liquidity crisis. It also matters when not just a crisis, but really when rates start to go higher. If rates were to go back to a 910 something crazy. Again, nobody can borrow money, there is no liquidity ultimately, then it this kind of cash flows are all that matters again, and we have a world where fundamentals are all that matters again. So I want to be clear, it’s not that fundamentals don’t matter at all, it’s they don’t matter in a world of massive liquidity, they only matter to the extent that they are necessary for purchasing their own stock or paying, you know, or buying other companies or supporting their ultimate valuation.

Corey Hoffstein  38:45

So assuming we continue to swim in a world of massive liquidity, what’s a traditional stock picker to do? Or even what’s an equity quant to do a factor quant to do in this environment? If they’re trying to pick based on fundamentals or some traditional measure characteristics that used to matter? Is any of that relevant anymore? Or should they be totally changing how they’re thinking about building equity portfolios?

Cem Karsan  39:11

I mean, correlation still matter to some extent, right. And they matter to the extent that the participants themselves think they matter. At some point, all of this will matter much more when liquidity is not infinite. But if you’re not looking at the flows, and you don’t understand the positioning, you’re ultimately playing a very dangerous game, which is you’re betting on something that doesn’t ultimately in the short term, have anything to do with the outcome. And that puts you in a really dangerous situation. We saw this with certain hedge funds and you know, playing the valuation game in these meme stocks, they’re playing evaluation game valuations don’t matter that puts them at a huge disadvantage. They’re not looking at the flows they ultimately are massively at risk. And so my unfortunate answer is I until the liquidity situation changes it is not other than And the fact that there are other participants playing that same game and affecting those flows, it is not what’s ultimately driving price and can put you at a disadvantage.

Corey Hoffstein  40:08

You’ve become far more vocal in the last year about these effects. And as I mentioned, one of the only people talking about the vana and charm effects. Are you not concerned that as more people become aware of all of this and start to try to factor it into their analysis, that these flows ultimately become our the way that people keep front running it faster and faster and faster?

Cem Karsan  40:31

That’s a great question. So a couple of things. People ask me again, again, why are you telling everybody this? You know, this is so important? And you have the secret key? Why would you give it away? Well, the reality is, there are a lot of participants who already know there’s a couple of corners of the world, these things are already being front run in a major way. And these are not going away. To be clear, none of these effects again, they’ve been there, since as far as I’m concerned, the beginning of time these flows are not going to disappear. The question is, how are they going to be hedged. And so, you know, my view is that on two levels, democratizing this, to some extent, is, in some ways, a good thing, because it’s not just a couple of big players kind of taking this away, it allows everybody to have a better understanding of the market and the efficiency, it also makes the system quite a bit more stable, in my view, which in some ways is a positive, from my perspective to talking about these things. Life is short, I’ll be here for 20 years, but being somebody who got out here made, you know, introduce people to an important concept, and kind of changed the kind of maybe the trajectory of how 10s of hundreds of 1000s of participants play is very important to me, you know, I do enjoy teaching, I do enjoy that process. But also, secondarily, I think it’s important to get these ideas out there for my brand and what we do and to educate people for understanding how we are the experts at understanding these whether they go to first, second, third, fourth order effects of how this will affect the markets will be kind of at the front of that and wanting to communicate that as part of my talk about as well.

Corey Hoffstein  41:59

Well, Jim, last question for you. I believe you mentioned to me your wife recently received her vaccines vaccines are around the corner fingers crossed the world is getting back to normal pretty soon. What is the first thing you’ll do when you get back to freedom?

Cem Karsan  42:14

I’m gonna go to Italy and I’m gonna go eat in a cafe outside pasta wine, go to a museum or to go to a concert, travel in a big European city with my wife and friends, and enjoy a lot of the things that we did what feels like many years ago.

Corey Hoffstein  42:31

I love it. And I hope you can put me in your suitcase.

Cem Karsan  42:35

You’re welcome to come. Always a pleasure to talk to

Corey Hoffstein  42:37

you. Well, my friend. It has been a real joy. I know I learned a lot I hope that listeners did as well. Thank you for joining me. Thanks for having me, Cory. If you’re enjoying the season, please consider heading over to your favorite podcast platform and leaving us a rating or review and sharing us with friends or on social media. It helps new people find us and helps us grow. Finally, if you’d like to learn more about newfound research, our investment mandates mutual funds or associated ETFs please visit think newfound.com. And now welcome back to my ongoing conversation with Harley Bassman. Harley, you are well known as the progenitor of the move index, which is maybe to a layperson who hasn’t heard of it’s sort of a vix equivalent for US Treasuries. Curious, what’s the origin story?

Harley Bassman  43:30

Thank you. Well, vix equivalent is more than that. I’m kind of copying the VIX. The VIX came out in like 1990. And I was running the option business at Merrill Lynch. And I recognized that we did not have a way to communicate to our clients, the relative nature of volatility, because there’s no easy way to talk about it. And so we created the move. And interestingly enough, we actually have data that goes before the move, we have data, because we can make an 88. It’s a very simple index. It’s not weighted, per se. It’s a one month options on the two year, five year 10 year and 30 year treasury. And it’s easy to read easy to have a context until financial repression, it ranged from 80 to 120. You’re supposed to buy it under 80 and sell it over 120. Of course, that never worked. When it was in the 70s you’d be bored out of your mind and thinking it’s going to zero. And when it got to 120 You’d be under your desk and crying for your mother. I guess it wasn’t quite as effective as we’d hoped. But it does give a good sense. Presently, if it’s 66. There’s technical reasons why it’s that low having to deal with the front end and the zero boundary. But even adjusting for that volatility right now is very low for interest rates, which is anomalous, relative to the shape of the curve and to public policy going forward.