Cem Karsan – Insider’s Guide to Volatility Hedges
In this episode, we talk with Cem Karsan, CIO and Founder of Kai Volatility Advisors (formerly Aegea).
After his successful trading career, Cem decided to leverage his volatility arbitrage expertise by improving upon many of the flawed strategies he had witnessed during his tenure as a market maker. To that end, Kai Volatility Advisors has created a non-correlated and scalable investment vehicle that takes advantage of the structural mispricing inherent in option indices worldwide, while offering the superior transparency and liquidity that today’s investors demand.
We talk about Cem’s experience as a market maker and how that affects how he thinks about trade flows. We dive into the 3 components to his strategy: 30 day skew, dispersion, and VVIX. We also discuss how dealer hedging can affect Vanna and Charm, which can pin the index or exacerbate moves depending on their hedge positioning.
I hope you enjoy Cem’s insights as much as I did…
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Have comments about the show, or ideas for things you’d like Taylor and Jason to discuss in future episodes? We’d love to hear from you at info@mutinyfund.com.
Transcript for Episode 24:
Taylor Pearson:
Hello and welcome. This is the Mutiny Investing Podcast. This podcast features long-form conversations on topics relating to investing, markets, risk, volatility and complex systems.
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This podcast is provided for informational purposes only and should not be relied upon as legal, business, investment or tax advice. All opinions expressed by podcast participants are certainly their own opinions and do not necessarily reflect the opinions of Mutiny Fund, their affiliates or companies featured.
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As such, they’re not suitable for all investors and you should not rely on any of the information as a substitute for the exercise of your own skill and judgment in making a decision on the appropriateness of such investments. Visit mutinyfund.com/disclaimer for more information.
Jason Buck:
This is Jason Buck. I’m the CIO at Mutiny Fund and it’s my pleasure to have a conversation with Cem Karsan of Aegea Capital. He’s the Managing Director there. Aegea goes back to 2011, but they are changing their name currently to Kai Volatility Advisors. We’ll talk a little bit about their name change maybe. But Aegea and now Kai is specialties and volatility arbitrage.
Jason Buck:
We’re going to talk all things long convexity, long skew and long vega. Don’t worry, we’ll also explain what those mean. For you diehards out there, we’re definitely going to talk about Gary, Vanna and Charm as well. But we tend to have a little bit of background of our investors and maybe the first seat or desk they worked in at maybe an institutional trading desk. But I want to start a little bit earlier with Cem. Let’s actually start with Cem Karsan. What kind of name is Cem and how do you pronounce a C as a J and why does that happen?
Cem Karsan:
Yeah. Turkish. I grew up, both my parents are Turkish, but born in London. Lived in Turkey as a child. I spent every summer there. All my cousins, everybody grew up on the Mediterranean in the summers. But moved to Texas. My dad was in oil industries. A PhD structural engineer. Grew up going from Texas to Oklahoma to the… My parents moved to Norway.
Cem Karsan:
Lived all over the world as a kid. I was very fortunate. My parents moved to Norway when I was in late junior high and I went to prep school in East Coast to Andover. I was lucky enough to travel across Europe every summer. A really skinny [inaudible 00:02:43] in the winter and I hit the Mediterranean in the summer. A really blessed childhood and I really had an amazing experience there at Andover.
Cem Karsan:
I eventually went to Rice University. Studied financial mathematics along with policy. Was always on the edge of debating whether to go do school of foreign service, study broad macro policy or I really go the math quantitative side, which was always my other leaning coming from my structural engineer father.
Cem Karsan:
I found the perfect mix of both worlds ultimately. Which is a broad equity index quantitative volatility arbitrage. Which really takes into consideration both volatility. Both quantitative arbitrage as well as broad macro views. That’s what we do here.
Jason Buck:
Starting with your experience at Rice, you’re either a dilation or a polymath. But also are you a polyglot as well? How many languages do you speak of?
Cem Karsan:
Turkish, Spanish and English. I spent a year in South America in college. Had lived in Spain for a summer prior and really fell in love with a Chilean woman when I was down there. I was supposed to be down there for a semester. I ended up staying for over a year. That’s a whole nother story we can talk about some other time. But amazing experience. I do speak a little bit of Norwegian here and there as well as my parents lived there five years and we spent a lot of time there.
Jason Buck:
Fantastic. Correct me if I’m wrong, but you got your first job trading in ’99 and how did that come about?
Cem Karsan:
Yeah. It actually started the summer of ’98. Right on the tail of longterm capital is where I got my first experience. That really informed a lot of my view of supply and demand and how powerful that was relative to just statistical arbitrage. In ’99, I started really full-time here in the pits in Chicago and it was a different language. This was back in the day when we were still arbing. That’s my fourth, my fifth language, I guess. [crosstalk 00:04:52].
Jason Buck:
I was about [inaudible 00:04:52] you got that [crosstalk 00:04:52]. Yeah.
Cem Karsan:
Yeah. Yeah. I could give you the whole [crosstalk 00:04:57].
Jason Buck:
[inaudible 00:04:57].
Cem Karsan:
The whole thing. I could still do the whole thing. No. But ’99 started in there. I got to really move into a important role at that firm that I was at. RBC Dominion Securities. Head of equity options really early, two years in because the gentleman in front of me left and started a proprietary trading group here in Chicago called Belvedere.
Cem Karsan:
Trial by fire in 2000, was leading that group as we saw a major obviously decline during the tech bubble burst. As we’re prone to do, made a lot of money in the trading world and looked at myself and said, “Look, I’m getting paid X and I’m making the company many multiples of X.” I thought I could do it on my own.
Cem Karsan:
After about four years, I left and I started a group for a specialist firm in New York called Bear Wagner Specialists, which is a division of Bear Stearns that was looking to diversify away from their specialist business. John Mulhern, which is an old famous Wall Street name hired us to start the business for him. Built it out to almost 30 traders across the CBOE, CME, Board of Trade, Amex, [P Coast 00:06:13] and really built out a real presence.
Cem Karsan:
Unfortunately, their business, the specialist business was even greater decline than they expected. We never got to the capital that we hoped to. And so I amicably left after several years. We got a good several years there and started my… Took some gentlemen with me and started my own market-making firm. Which eventually was good timing because it’s late 2016, the vol markets really started picking up. From 2017, sorry. 2006. Sorry. 2007, a decade. Well, I lost a decade there. 2000-
Jason Buck:
Yeah. It happens. It happens. We are getting old. [crosstalk 00:06:49].
Cem Karsan:
Exactly. 2007, we really came into our own and became one of the biggest market-making groups in there. By 2008, we were up to 13% of the volume in the S&P 500. Became one of the biggest market-making groups in the indices. Took our several million dollar investment and grew that to many multiples. I won’t put an exact number on it. But many, many multiples of that number and enough so where I had 99% of my net worth in the business in 2010 and I decided it was a crazy run for me and really wanted to take a step back from market-making and really start investing my own money separately. I had an exit from that business and eventually started a Aegea Capital in 2011.
Jason Buck:
Before we get back to Aegea, let’s go back to your… When you went from trader and decided to go out on your own, a lot of people make that transition, but a lot of people don’t realize what’s actually involved in running a business. It’s definitely going different from being an employee to business owner. But you did it twice. You must have had a good experience the first time or you’re going for punishment. Or how did you think about that transition?
Cem Karsan:
I’m going in for punishment. No. Candidly, obviously I did very well economically. Being an entrepreneur it’s very different than just being a trader and I had to be both. I think I had a skill at both. I’ve been able to bridge that divide and there’s a lot of things I really genuinely enjoy about running a business.
Cem Karsan:
There’s the part about building things. That really appeals to me. Teaching is a big, big thing. I love working with employees and whatnot to build a better mouse trap and learning from other people. Yeah. I think those are the things that keep drawing me back to it as opposed to just going and running a major book for Citadel or some other big group. This is what we do and I enjoy every single bit of it.
Jason Buck:
But after selling the market-making firm, did you think about taking retiring for a while? Did you take some time off?
Cem Karsan:
A 100%. The original plan was not to start a hedge fund. Actually, quite the contrary. I started managing my own capital on the side early in a structured trade. It was really a long volatility trade that was meant to diversify my long real estate and equity positions. It’s something that we use in the background of the market-making operation that made us a ton of money in 2008 and nine.
Cem Karsan:
Eventually, the X million dollars I had in there, which was very small relative to how scalable the strategy was. The more I coded up and built out the strategy, the more I realized that there was an opportunity for other people to join along. I had talked to a lot of friends about the strategy in passing that we’re in the business. Some people encouraged me. They wanted to co-invest and encouraged me to bring on other investors.
Cem Karsan:
That’s how it came to be. It was not meant to be a business initially. About a year after starting that, I took a break and traveled a bit. Got married. I had a child and eventually we started a home. I started looking. I was thinking, I’m not going to be a stay at home dad, that’s for sure. As much as I love parenthood, I was ready to start the next thing. That’s how it came to be.
Jason Buck:
Well, it’s always a great way to start a business when people are banging down your door to take their money. That’s always [inaudible 00:10:15].
Cem Karsan:
It’s a little bit easier. Yeah.
Jason Buck:
At the time though, how did you think about volatility, arbitrage or long volatility in relation to the real estate investments? I’m curious how you combine that book.
Cem Karsan:
Yeah. For me, it was always a beta story. Particularly the strategy initiated was more to hedge a secular decline. It has some tail risk, long volatility convexity to it. But a lot of the best parts about it is how it performs in the 2008 type scenario where it’s a… Or 2000 type scenario. Which is the environments that I experienced.
Cem Karsan:
And so the idea was if we ever got a secular several years of decline where illiquid assets like real estate would also decline in a meaningful way, that you’d have significant liquidity on this side to take and reinvest into the real estate market or the equity market. That’s really the broad appeal here. It’s not just the quick mean reverting move that you get to quickly cash out. It’s really month after month strategy that can pay major dividends and allow you to buy-in when things are cheap.
Jason Buck:
Yeah. That was one of the impetuses for the Mutiny Fund was exactly that. Is coming from a background of commercial real estate development and going through GFC, I was like, there’s got to be a hedge to have a convex cash position. Also have a liquid part of your book when you’re illiquiding part of your books taking that right down over extended periods of time.
Jason Buck:
It’s a really interesting combination. I was curious there. I’ve never heard that part that you were looking to hedge a bit of that out. And so in 2011, you started Aegea. What was the original thesis when you were starting and I guess, how has that changed over time a little bit?
Cem Karsan:
Yeah. This strategy really started as a skew swap. It’s not to your average [crosstalk 00:12:11].
Jason Buck:
Explain skew [inaudible 00:12:12].
Cem Karsan:
You are right. I was about to say-
Jason Buck:
Skew swap.
Cem Karsan:
… to your average investor, that’s a very odd thing that most people aren’t familiar with. But as a vol trader, it’s something that’s very important. If you think about it, you have vol levels like buying and selling vol. You have a term structure. Which is whether or not something on the term structure is too steep or flat and whether you want to own something longer-dated or shorter-dated.
Cem Karsan:
You have skew, which really measures the downside protection versus the upper side protection. People trade all of these things fairly liquidly and they’re pretty efficient. But one thing that we’ve discovered over time is that what’s not efficient and has an incredible set of opportunities in it is the relative, the term structure of skew.
Cem Karsan:
Basically looking at skew at one expiration. Maybe shorter data. Maybe a month out versus maybe two months out looking at skew and the relationship between the two in a statistical way. There’s an opportunity in that, especially in the equities and the indices that has presented itself over time as a function of supply and demand. That creates a major structural opportunity.
Cem Karsan:
Again, it’s structural. It’s not something that’s going to be arbed out on the market. It is a carry trade in a sense. Essentially, similar to how VRP is. Volatility risk premium is a structural occurrence and skew itself is a structural carry trade. Skew swap is a much better risk adjusted carry trade because on a risk adjusted basis, it’s possible to get long volatility. The downside for credit, essentially.
Jason Buck:
I wouldn’t say it’s skew swap, though. Are you structuring that in the listed markets? Are you buying that from [inaudible 00:14:07]? Is that an OTC product?
Cem Karsan:
We’re doing this on listed products. We believe especially if we’re going to be long volatility doing it, OTC markets is it creates basis risk and a part of risk that essentially can be a major problem as it would have been in March of this year.
Cem Karsan:
If you don’t have the liquidity of listed markets. That’s an important consideration for us. We’ve always wanted it to be primarily on listed markets. We do look at OTC. We do model a lot based on flows and OTC as well. But we’d like to be in as transparent markets as possible especially during what can be liquid times.
Jason Buck:
Yeah. I was just wondering if in 2011 it was different from now that you are going a lot of OTC products and that change is more listed or you’ve basically been listed from the start?
Cem Karsan:
No. We’ve been listed from the start. That’s always been in our view you get a much better view of the world that exists. Again, it’s much more liquid. Our turnover is less than a week. If you’re getting that… If you need that liquidity to constantly be [inaudible 00:15:20] portfolio, you’re better off in the most liquid products as well.
Jason Buck:
Got it. It sounds like though over the history, everything obviously changes and evolve. But the general thesis hasn’t changed that dramatically since 2011. Is that fair to say?
Cem Karsan:
The framework and the thesis hasn’t changed. What’s changed considerably is our modeling of the opportunity set. We’ve just gotten a lot better at what we do, A. B, in particular not just finding what is the cheapest and most expensive specifically on the curve. Whereas it started actually as a monthly structural trade that would rebalance, it’s really moved to a trade that where we’re pinpointing the exact peak of inefficiency.
Cem Karsan:
How we hedge that portfolio has dramatically changed as well. How we view our deltas, the distribution, potential outcomes. When we started it was really more of a simple Black-Scholes approach to hedging the portfolio delta neutral. What we’ve discovered over time is obviously I talk about this a lot on social media and whatnot is there’s a reflexive power to this positioning.
Cem Karsan:
When something’s high, that reflexively tends to mean that dealers are short that and there’s a likelihood for that to be a loser for dealers or to move in the direction where it’s not as profitable for dealers. Hedging and withdrawing our distributions has dramatically changed. As we’ve gotten better, our rebalanced time has come in considerably because there’s a better opportunity set. It allows us to pay a little bit more slippage if and when necessary to capture more edge on a regular basis.
Cem Karsan:
Yeah. The tools, the knowledge base, the modeling has all dramatically improved and the rebalance periods have also tightened. But the broad thesis is still the same and the beauty of it is this as a structural phenomenon. That if anything is increasing over time because of more and more people in the marketplace needing to hedge in the market and also gaining interest in [inaudible 00:17:32] of products.
Jason Buck:
I think we’ll dive a little bit later into the reflexivity and the dealer positioning and all that stuff. But at a high level, you have basically three core positions or three core ways you think about it. From that trading 30-day, evolve for the peak and the range to sell, to dispersion, to Vivex. If you want to start maybe diving into how you look at it in three different trades or three different buckets and maybe we can dive deeper into each one.
Cem Karsan:
Yeah. At the top level, there’s this 30-day skew. It tends to represent relative to historic outcomes.
Jason Buck:
Can you define skew just for the people that maybe [crosstalk 00:18:19]-
Cem Karsan:
Yeah. Sure.
Jason Buck:
… [inaudible 00:18:19].
Cem Karsan:
Sorry.
Jason Buck:
No worries.
Cem Karsan:
Yeah. Skew is a downside. When I say downside, out of the money to the downside in the market. It’s the implied volatility that those options are priced on. And so that versus the at-the-money or out of the money calls to the upside.
Cem Karsan:
The skewness is essentially a skewness of the distribution of the implied volatility of options. And so downside options are priced at a much higher implied volatility than at-the-money or even more out of the money calls. This is a function of two things. One, in reality, realized volatility historically is higher to the downside. There should be some skew based on historical realized vol.
Cem Karsan:
That said, skew itself is especially in the S&Ps is structuring much higher than realized volatility difference of downside moves versus upside moves. That’s just simply because the world is long. If you live, if you breathe, if you own a home, if you have a job, you’re long and insurance premium is going to be in the things that hedge that. That’s essentially downside protection.
Cem Karsan:
In terms of supply and demand, that means people are buying puts to protect themselves. Structural institutions are doing that and they’re selling calls. They’re riding calls. Again, on the equity, on the index level at least, they’re riding calls to pay for this downside protection or to create some type of yield and take off some of the potential upside.
Cem Karsan:
These are both hedges. The portfolio creates a massive skewness to distribution. The skew in the S&Ps is the highest historically in the world. That’s because again, that’s supply and demand. This is where people come to hedge.
Jason Buck:
Then, so I interrupted you. You were starting to talk about 30-day skew and how you look at it over 30 days.
Cem Karsan:
There’s a heuristic. If you think about it, people particularly portfolio managers know that puts are overvalued historically and that there’s a vol premium that they have to pay. They don’t want to sink their money into long-term historically, one-year, two-year, three-year puts and just sit on them.
Cem Karsan:
Because in general, that tends to be a losing battle. They like to hedge dynamically. They hedge dynamically when they feel it’s an opportune time. That has even before the VIX existed or we go back to the beginning of options. The peak of volume was always about 30 days out. About one month.
Cem Karsan:
That’s a reporting period for most managers obviously. It’s also a natural time to say, okay, I think this month people don’t want to go on one week protection. Historically they don’t want to own two, three, four month protection because it just seems expensive. They’d rather go buy it dynamically when they want.
Cem Karsan:
It’s a self-reinforcing thing because the more people there are trading 30-day, the more liquidity there is. The more it’s easy to come in and trade a bigger… Hedge a bigger book where the liquidity exists. Because of that, there is historically a peak in skewness relative to historic outcomes. It’s right before a decline in that skew occurs.
Cem Karsan:
Obviously that skew goes to flat, to zero at expiration. There’s an opportunity there on a risk-adjusted basis to monetize that supply and demand imbalance and hedge that relative to other skew that exists in the marketplace. And so the strategy is essentially finding where skew is cheap behind that one month. Where it’s cheap in front of it structuring portfolios.
Cem Karsan:
Again, we do this with our own proprietary tools. It’s a structured quantitative approach. But structuring a portfolio that essentially will take out this premium from the market and do it in a way that’s actually long skew and long convexity. Long units the downside while still being able to monetize a lot of that skew overvaluation as it comes into expression.
Jason Buck:
How do you think about getting that ratio right when you’re selling the rich and buying the cheap, but then making sure you don’t get your face ripped off if something unusual happens?
Cem Karsan:
It’s all about modeling and doing it. The way we model everything is not… We’re not data mining, obviously. I have a 22 years of experience and everything we did is informed by a qualitative approach to understanding how the supply, demand dynamics work and what the potential distribution, potential outcomes are.
Cem Karsan:
We really start with a three layer approach. We take a distribution of market outcomes based on again, this has grown over time, as I said. But it started really, as based on the VIX bucket you’re in, based on the market [inaudible 00:23:12] there are, we model the distribution. We have a sense of how fat those tails are. Then with Vanna and Charm and these other effects that we talk about, we help affect that distribution a little bit. That’s level one.
Cem Karsan:
Not starting with a log normal distribution, which is what Black-Scholes would do. We have a much more sophisticated view of what the potential outcomes may be. Then we model implied volatility moves of at-the-money vol based on each potential market move. Again, this is based on deep understanding analysis of how different terms structure at-the-money can move. This is the vol path.
Cem Karsan:
Then we’re looking at skew and the potential outcomes for skew in a similar model. We model all of these. Then we go look at the actual surface of these products that we’re trading. We look at also what’s high and what’s low based on a very smooth dynamic surface. Then we look at where that is relative to current. Then we look at that also relative to historical outcomes.
Cem Karsan:
We have a tool that essentially will run through the scenario structure, the portfolio with certain restrictions. It has to be long vol. It has to be long skew. It has to have X percent of winning in different… Out of all the potential outcomes, the percentage winning expected return, we do an expected return over a risk. Several different risk metrics.
Cem Karsan:
It brings us up to the most, the optimal portfolios. We put that on and we rebalance as the expected return. The second something if it gets to a threshold where there’s a better expected return. It’s really a quantitative approach. How do we do it? We really try to quantify everything that we do and really take a really quantitative algorithmic approach to putting these positions on and rebalancing.
Jason Buck:
How do you think about with a statistical arbitrage like that? How do you think about remaining an arbitrage or market neutral versus being long skew or long vega in those scenarios? [inaudible 00:25:09], a lot of people would just try to be, do the VIX arbitrage and just have that income stream. But it’s different to be positioned in case of a spike event. I’m curious how you think about that.
Cem Karsan:
Yeah. We have two parts to the portfolio. You alluded to this earlier. We’re not just monetizing this 30-day vol. You can do that and structure yourself long vol. That’s the part that really works well in this secular decline. Because you keep monetizing that 30-day as it goes away.
Cem Karsan:
The longer days if you have moves up the curve and you can, again, digest this month after month and really make a good return over an extended secular period. But there’s also a different move which is really this spike like March move. Which is really about owning the most convex products available. That’s where the VIX comes into the picture.
Cem Karsan:
Our view is really, as most people know that if you’re looking for real convexity, that Voleval, those calls and VIX and whatnot are generally the most penny for your buck for a really convex move. We do add, when the opportunity is there in those types of products, we will add those for the convexity.
Cem Karsan:
If not, we’re also just owning, again, as long convexity, long units, long skew as part of our structural bias. We’re always modeling all of these potential outcomes. We’re looking at not just a vol, but really looking at extreme tail events and modeling those tails.
Jason Buck:
Yeah. So far we’ve talked about the 30-day skew part of your book. About VVIX, buying calls on the VIX. Another place you look at maybe opportunistically is dispersion. Can you talk about dispersion a little bit?
Cem Karsan:
Yeah. We look at dispersion and correlation quite a bit. Dispersion in particular is a great opportunity. This in particular is something that I think a lot of people haven’t really until recently, and I’ve been talking about this quite a bit on social media. Really zeroed in on. But this understanding that as we saw in 2017, that there’s reflexive pinning of markets that comes from when dealers are oversupplied on index implied volatility. That’s very often locally. If often locally or oversupplied.
Cem Karsan:
In 2017, we saw the lowest implied volatility of all times. We also saw the lowest realized volatility in history. If you go back 150 years of data market history, by 30%, the lowest realized volatility in history. We also, what we saw through that period was that it was also the lowest correlation in history. Again, by 20 to 25% significant margin.
Cem Karsan:
Most people would have said, “Well, the low volatility was a result of the low correlation because everybody takes this equity view when they’re starting with everything.” What we knew being as a market makers and as also understanding those markets intimately well, is that the index was ultimately what was pinning the other, the market. The index.
Cem Karsan:
Ultimately, if that index is pinned, you don’t get rid of idiosyncratic risk. You still have earnings. You still have cures for diseases. You still have new technologies. You still have a stock going in one direction based on that idiosyncratic risk. Which means that the index is pinned. That ultimately some other constituents have to go in an opposite direction.
Cem Karsan:
And so, that understanding has informed a really a robust view of modeling when the opportunity set is particularly good for dispersion and being long names versus short index vol. And so when there’s an opportunity for that, that can be very profitable and counter correlated to long volatility trades. It’s a very profitable trade when volatility is compressed and when low volatility isn’t performing. It’s a nice diversifier to those types of portfolios. Then those opportunities can really give you some extra alpha.
Jason Buck:
Not to state the obvious then, do you just stay in a high vol environment? Do you just stay away from dispersion trades or do you think about it in a different way?
Cem Karsan:
It’s more nuanced than that. You obviously you could look at the implied volatility environment we’re in now. Which is really had this floor at around 20. Which a lot of people would say, “Wow. That’s high.” But in this environment, despite volatility being on the tails, being very liquid and under supplied and skew being very high and products like the VVIX and those tails being incredibly bid, local volatility is actually very oversupplied to dealers.
Cem Karsan:
You really have a situation where at-the-money vol is broadly owned. Unless you can get beyond this at-the-money area where gamma is owned by the street, the market really has this mean reverting aspect. The index is due. Meanwhile, it’s a volatile period. There’s a lot going on in terms of macro. Fiscal versus monetary rotation. A lot of crazy moves and name stocks with all the retail demand.
Cem Karsan:
And so there’s a lot of volatility going on underneath the surface because of the, again, the idiosyncratic risk is immutable to a great extent because there’s not enough supply in those products. If anything, there’s a lot of demand for the volatility in those because of these retail products and whatnot.
Cem Karsan:
In this environment, we’ve seen an incredible opportunity for dispersion despite vol being quite high. It’s not just a function of where is that volatility. It’s really understanding dealer supply and demand. That’s something we do very well.
Cem Karsan:
I think being, again, coming from the belly of the beast and understanding how market makers take on positions and the type of positions they have and being able to model that has informed not only our distributions of how vol moves, but also how dispersion moves and when that’s an opportunity.
Jason Buck:
Thinking about that, we talked about puts queue earlier. Then like you said, with these single names, we’re seeing a lot of call skew coming into the market. The classic dispersion trade is to sell a straddle on the index by a straddle or strangle on individual names. Do you think about just taking directional plays when you have call skew and individual names in a higher volatility environment?
Cem Karsan:
We take a very statistical approach with this product. We have other funds that we are launching. With that, we’re managing on a proprietary level. Actually next quarter that we’re going to be launching that really focus on the distribution of potential outcomes and taking more directional. That’s based on that. That is quite profitable.
Cem Karsan:
Essentially modeling these distributions as part of our long volatility involved neutral books. Really beta, we’ve always known how valuable it was. But really doing that, putting in that work for this really informed us on how profitable that was on its own. Those directional indicators do get integrated into the long vol distributions, like I said, and do provide a significant amount of edge and alpha here.
Cem Karsan:
But as a standalone, we really take directional bets in another product. That’s not really the focus of our product here. It’s really the model. The best opportunity set for long volatility exposure.
Jason Buck:
Great. And so you’ve hinted at it many times with the dealer and the reflexivity of dealers. I don’t want to bury the lead too much. If people aren’t obsessively following you on Twitter, can you fill them in who Gary and Vanna and how Gary, Charms, Vanna and walk through the higher [inaudible 00:32:57] of how the reflexibility of dealer positioning happen?
Cem Karsan:
Yeah. Gary is, it’s a long story. I won’t get into the whole thing. But there were clerks on the floor back in market-making days that would be asked to do several different bets. Whether it was eat 150 Chicken McNuggets or something crazy. Make a 100 free throws or whatever it was.
Cem Karsan:
And so as you learn over time being the pit, you usually don’t bet against the guy who’s being challenged to do these things because the odds of them having, as outlandish as they may seem are much higher when somebody is incentivized to make sure that… That guy’s going to go practice a 100 free throws. He’s going to go eat 150 Chicken McNuggets. Make sure he can do it because he’s getting some cut on that trade.
Cem Karsan:
That idea is really, that guy’s name that I’ve made up for is Gary that used to do this. And so my name for dealer positioning is essentially Gary. If the positioning is a certain way, it’s more likely to affect the outcomes. It’s not like tornado insurance. Tornado comes through town. The tornado, whether or not the tornado comes in town does not affect… The likelihood of the insurance and how it’s priced is not based on whether or not a tornado come through town or not.
Cem Karsan:
The point here is, ultimately when dealer positioning is a certain way, you have to change your probabilities based on that positioning. Because ultimately, if everybody owns puts, the market’s less likely to go down. If everybody short puts, the market is more likely to explode and more likely to cause a problem like we saw with XIV in 2018. That’s Gary. Long-winded way of saying dealer positioning affects the market. That’s Gary. I talk about that quite a bit. That’s what I was talking about with the dispersion trade and how important that is.
Cem Karsan:
Vanna and Charm are really a function of some of this dealer positioning. Which is broadly in the index as I alluded to, skew is bid. Downside protection is what people own and people sell upside. That’s a structural occurrence because again, we’re all low in the market in one way or another.
Cem Karsan:
Because of that positioning, dealers are short put, long call. It’s a structured great trade. There’s a lot of edge in it. It’s a carry trade essentially. But it has a tail to it just like all carry trades. It’s a massive carry trade. Much like borrow in yen and lend in lira.
Cem Karsan:
That massive structural carry trade leads to a short stock underlying position against being short put, long call. As that position expires and as those positions which we can track, the dealer positioning comes into expiration. As the volatility declines on that, as time passes, you can measure that Vanna. Which is the change in implied volatility effect on delta as well as that Charm, which is the change in day effect on delta.
Cem Karsan:
You can measure that and really see the effect of those flows and that dealer positioning on the market. A deep understanding of that is really a structural, extra structural alpha and edge to understanding what the real distributions look like. We’ve been very good at predicting this stuff online, obviously. That’s why we’ve gotten such a quick following in the six months since we started talking about it. But this stuff really informs a lot of our again, our distributions and our directional understanding.
Jason Buck:
Thinking about this dealer positioning, obviously it can create an issue where things are pinned and you have a very mean reversionary environment. Then beyond a certain barrier point, you can have this reflexive breakout that can really exacerbate moves.
Jason Buck:
But without getting the secret sauce, a lot of times we get a lot of questions of how can retail traders somebody follow this? Is there good metrics for measuring dealer positioning? Outside of modeling your own models that you have from decades of being a market maker, to talking to people on the street that you’ve built relationships with, how do people get an idea of whether dealer positioning is an immune reversionary environment or in a breakout environment?
Cem Karsan:
Yeah. Look. Having experience-
Jason Buck:
A rhetoric question [crosstalk 00:37:03].
Cem Karsan:
Yeah. I have 23 years of experience and have the relationships from all the floor brokers. Get all of the real-time information across these products. What a retail trader can do is they can take in the volume. They can look at open interest. They can in theory, if they have the tools and understanding, they can model the volatility surfaces of these products.
Cem Karsan:
With those three things, they can piece together some portion of the information that we look at. Which is, what is the positioning of dealers? If something’s really high on the volatility surface, that’s likely to give you some insight into positioning. Especially if you understand the broad dynamics of why it’s high and what trades are causing it.
Cem Karsan:
But the key to do it at the highest of levels is really to understand when those trades come in, who are those… What are those trades? Who are they? Are they hedged? Are they not hedged? What does that mean for the effect on dealers?
Cem Karsan:
Again, understanding the full picture and understanding how the market makers are going to react and how they broadly hedge. What the dynamics are in terms of timing of when they’re going to need to rebalance those portfolios.
Cem Karsan:
I would like to add, we talked about Vanna and Charm. But just as important, and this is alluded to in that conversation about dispersion is, these dealer affects also really affects implied volatility. They’re really good predictors for not just the distribution of market outcomes, but distribution of the implied volatility outcomes as well as skew.
Cem Karsan:
If you have a certain calendar, puts bet on in the indices and it’s really cheap. As that decays, people are going to have to buy back stock. People are going to have to… Dealers are going to have to sell the longer data volatility. They’re getting longer volatility. As that passes, they’re going have to sell that. The skew is likely to also collapse.
Cem Karsan:
Between these three things, that trade even though it looks great, it may not end up being a very profitable trade. But if you knew how the positioning was going to react, you can really monetize that by modeling the outcome better and hedging the delta properly. Hedging the vol properly and hedging the skew properly.
Jason Buck:
You also have that good idea of where large institutional flows are coming from with non-economic hedgers and how that’s going to affect skew and therefore implied volatility too.
Cem Karsan:
Correct. We not only look at listed products, like I said at the top of this conversation, we also look at structured products from banks. We’re really trying to take in the whole universe. We’re looking at not just indices, we’re looking at single list names and the big orders coming across there and how those are getting filtered across to the indices and how that affects correlation. Not just dispersion and how that will ultimately likely affect the whole universe on different moves.
Jason Buck:
I think about it a lot like when you’re running a fine dining restaurant. You build up these avatar profiles of the best food reviews in the world. And so when people come in, you have the way they make the reservation. You start to get a glimpse or a hunch and you start correlating all these different data sets and you go, “This may be a Michelin star reviewer here. I’m going to really pay attention to this table.” Is that the way you look at that order flow? If somebody’s constantly 10,000 lots here or there, that’s likely bridge water. You’re just trying to create an avatar profile of that flow.
Cem Karsan:
A 100%. That’s modeling in general. This is a unique data set. Much like many other unique data sets, I think the big differentiator is it’s a massive one and it’s growing and tremendously in sizes. People understand. It has a structural, regular structural effect on markets. The better you understand that the potential value of it is so much more than most any other data sets out there. It’s amazing how few people truly understand how essential this is and how important it is to the functioning markets.
Jason Buck:
How do you think your experience as a market maker, how general or how unique was it? Is it an advantage or a disadvantage that you’ve built up a gut feel? It’s like, if I was a dealer, this is how I’d be positioned in this environment. Then broadly applying that to all dealers, is that accurate or does that sometimes lead you to the wrong conclusions?
Cem Karsan:
I think it’s the right [inaudible 00:41:32]. Look. It’s a huge advantage in my view. Obviously it’s given me a completely different perspective than your average person. I’m not the only person who had that experience, but I think the difference is we manage such a big book for so long that we were… This came out of necessity.
Cem Karsan:
Just like all the best inventions do, it was a result of putting on things relative to our surfaces that looked like tremendous trades. And regularly seeing them not be profitable. We had the three or 13% of volume. We had what everybody else, every other market maker had on.
Cem Karsan:
Understanding how that chase and that competitive trying to get ahead of the other people who had the same position and get out ahead of them and monetize it, that effect, seeing that in real time really gives you a feel for what would happen. Then eventually, with all the improve, you asked how things changed as well. 22 years ago, we didn’t really have machine learning. We didn’t have a lot of these statistical tools that we use.
Cem Karsan:
Now we have these tremendous tools that we can now given the qualitative insights that we have can really go hunt out the optimal modeling of each one of these factors that we’re looking at. I danced around. Obviously it’s a great value, but it’s not the whole thing. I think if you start with this, a lot of great data sets. People use great data sets and then data mine them. Then you’re learning to find the… That hasn’t been our approach.
Cem Karsan:
It’s been always understanding what’s going on. Making sure that we’re focusing on the things that we know are structurally there. We understand the causality, not just the correlation. I think that’s critical especially in a world where things are quickly changing and a lot of quantitative strategies aren’t performing as well as they used to. Because exactly because of that.
Cem Karsan:
People don’t understand the causality. They’re just playing correlation and those things are fleeting. But starting with that causality, that understanding qualitatively and then using the tools to better optimize, create statistical models I think has really been a huge advance for us.
Jason Buck:
I wonder, it makes me think. Do you think there’s a lack of people in your seat because there’s very few people that go from market-making, from clipping that coupon no bad days, to then want to be a long vol trader where it’s all bad days?
Cem Karsan:
Yeah. There are many people, like you said earlier like that, that are a glutton for punishment. As much as I am, I guess. No. Yeah. I think again, now I’ve had going on almost nine years, 10 years of experience as a fund manager too and it’s really helped me tune in to some of the macro that I’ve always really enjoyed. But really taking, understanding the bigger picture stuff and understanding when things are turning to better understand these distributions.
Cem Karsan:
Also putting out products out there that institutions and people will benefit from on a broader level as opposed to just trading for profit. Not really understanding or worrying as much about the drawdowns or whatever. I think, again, I have a really unique, I agree, combination of those two things at this point. I do think it’s a huge advantage for not just modeling the market, but structuring portfolios and strategies that are good for the broad world.
Jason Buck:
Previously in this discussion, you talked about using that 30-day skew and trading around that. But then you hinted at sometimes longer-dated. I think this is really interesting is that a lot of people about long volatility as long gamma and therefore in very acute sharp tail off, that’s where you make money. Then a prolonged recession like 2008 like a GFC, maybe long volatility [inaudible 00:45:15] is not going to do as good. But commodity trend would really pick up that move or some form of trend following would pick up that move.
Jason Buck:
But you hinted that as soon as maybe as you start going out longer-dated, and if that curve is in backwardation in a prolonged recession, you could be riding up that curve. That may apply, I think we’ve talked privately about this. This may apply to inflation as well. Can you talk about how you’d moved a longer-dated and if it’s curves in backwardation how that leads to maybe a more positive carry during a recessionary environment or an inflationary environment?
Cem Karsan:
Yeah. Absolutely. This is all modeled within our tool itself. The opportunity set looks at the opportunity set at any given time and structures the portfolio accordingly. That said, the optimal short tends to be a two-star deviations of the occurrences, two weeks to six weeks out. That’s where the portfolio tends to be.
Cem Karsan:
That said, we go from being more structured as balanced with more gamma in front of it and some vol behind it, to really having much more when it’s in backwardation longer-dated exposure. Structurally that’s what tends to happen when that curves in backwardation. That type of positioning allows a 2008 to be a situation where you’re riding up the curve, like you said, and really monetizing. Benefiting from more of a secular move in markets to the downside in a more secular moving in higher vol longer-dated.
Cem Karsan:
It allows the rebalancing to happen. Ultimately, a lot of our tools and modeling does this for us. It’s not just a discretionary view when the opportunity set is particularly great there. People are buying short-dated because they don’t want to go… Vol’s at 40 and they’re not willing to go buy back the thing they were short from a 20 vol at 40. They’d rather cover it with band-aid hoping that you’ll get the reflexive bounce back.
Cem Karsan:
You can really ride that 40 vol to a 50 vol and monetize the 80 vol in front of it over and over again, once the vol goes higher. This can be, you can win on both sides of that trade for an extended period of time as we did in ’08. As we would have done in 2000 through 2003 as well.
Cem Karsan:
Yeah. The portfolio does naturally turn as the surface changes. As the opportunity set changes. Again, that allows us to both have the tail in the portfolio for when vols are lower and there’s more likelihood of more of a convex initial move. Then eventually or naturally when the curve goes into backwardation, move to a more structured longer vega downside structure.
Jason Buck:
We can model it, but it’s more of punches because nobody’s really traded it because nobody’s been around that long. But what if we had this sustained inflationary environment or a stagflation, do you think you see more of that backwardation and you can go longer days and ride up that curve or how do you think about it?
Cem Karsan:
Yeah. In inflationary environment actually, interestingly higher vol, higher rates should mean more of a trending market and more out of correlation. If you have an environment where interest rates are going higher, vol is going higher and a decline into it, which we haven’t really seen in recent history. I think that’s a perfect environment for this type of a structure because you’re going to see vol heading higher in a more trending downmarket. Which we haven’t seen in a while.
Cem Karsan:
We’ve had an incredible mean reversion in the markets because of really low interest rates. This is a strategy that particularly performs well in that environment. On top of that, there’s an added inflationary hedge underneath the strategy because of the margin for the strategy only eats up maybe 20 to 30%. The actual cash position gets put into boxes on a regular basis.
Cem Karsan:
And so there’s also as interest rates go higher, there’s an extra yield because that cash underlying the strategy will actually be reinvested at higher and higher rates as time goes on as well. There’s actually an added inflationary hedge in here as well.
Cem Karsan:
I’ll add, this is a side notice too. This is not what most vol managers are focused on, but there’s a tax advantage side of this as well. It’s all index and future options. You also get, make straddle or 1256 treatment which is actually a huge advantage obviously as well.
Jason Buck:
Preach. You’re preaching to the choir on that one.
Cem Karsan:
It’s all right.
Jason Buck:
[inaudible 00:49:50] at capital efficiency-
Cem Karsan:
Very excited.
Jason Buck:
… and the tax advantage [crosstalk 00:49:54] contract to know exactly. We hinted at your previous as sitting on desks to a market maker to growing volatility, arbitrage at Aegea. But now, like you said, you’re changing your name to Kai. K-A-I Volatility Advisors. Part of that you alluded to is that you’re adding new products. But what are some of the other new products you’re adding and how do you think about looking at applying your modeling to the global macro environment moving forward?
Cem Karsan:
Yeah. Our legacy funds have always been on the equity side. That’s where the broad appeal was for margin efficiency against equities. That was a more logical fit for our customers in our early history. But there’s a lot of efficiency to be gained from trading more on the future side. Also as we built out this, the more directional trading component which really was as a symbol, more focused vol [inaudible 00:50:52] shop.
Cem Karsan:
We weren’t as focused on prior. There’s a lot more futures trading both in terms of correlation and dispersion, whatnot, that we’ll be doing with the new products. That’s really made us want to shift to a more NFA, FINRA-focused firm. I think we’re moving more in that direction.
Cem Karsan:
That’s what necessitated the new entity for us. Really wanting to focus more on some of these really valuable directional indicators that we’ve been using within these vol strategies for some time and building out, but that have really become best in class, I think. That’s really what’s driven that shift. Kai is my son’s name, by the way.
Jason Buck:
[inaudible 00:51:37].
Cem Karsan:
My daughter’s initials are I, A, K. She gets the reverse and that’s… My wife though is very… She’s a big believer in that. That if you have the name of your children in it, you’re going to work that much harder. Yeah. I figure you can’t not have a great product when your children are involved.
Jason Buck:
Yeah. But then keeping the peace in the household if you name it after your son [inaudible 00:52:03]. Then slide in the initials. Very cute [crosstalk 00:52:07].
Cem Karsan:
Yeah. That was key. We never could have done it if that wasn’t the case, but yeah.
Jason Buck:
Then outside the box question. I want to timestamp this. This is February 22nd, 2021. Just in case people are listening to us way in the future or whatever. I’m sure I’m going to mischaracterize this so I want you to be able to clarify for me.
Jason Buck:
But you and I had a private conversation I found very interesting a few weeks ago. We were talking about just S&P 500 index and how, obviously over the last years, people see this as a momentum trade or a growth trade. You do the index weighting and even float weighting. You’re seeing what used to be the NIFTY 50, probably now the NIFTY five or 10. Or NIFTY 15 and you’re riding that growth.
Jason Buck:
But if we were to have some real economic shock or drawdown or a phase shift lower and value came back as a factor strategy, that would actually rise to be represented in the S&P 500 index. I thought that was an obvious but interesting thought point that as a S&P 500 index investor, you’re essentially riding whatever’s in Vogue or in fashion. Whether that is growth or value.
Jason Buck:
But you might have to go through a violent phase shift to be able to track that fashionable movement. Which obviously volatility tail risk can help you in that sense. But I was curious about, that was an interesting way of looking at the S&P 500 index.
Cem Karsan:
Yeah. This came about, I talked to Mike Green who’s big on passive investing quite a bit on these things. He was very adamant for a long time that, “Hey, look. Passive is going to keep growth continuing along this path for a long time.” About six months ago, I was very focused on how this rotation was coming. We called this, actually. We’re fortunate enough to call this very early.
Cem Karsan:
My own point to him was, if you get a situation where value does start to… Whether it’s through active managers or just via the duration trade, if it’s able to get past this hurdle, at some point, passive is really a momentum trade. It’s not a growth trade and most people automatically tie those two things together. But the reality is, momentum is not growth.
Cem Karsan:
You can have value outperform for significant period times and be the thing with the most momentum. If value can take the mantle of momentum, which it’s slowly doing here. If it can do that over a year or two years through products like the S&P and other passive Vanguard type products, it can become the thing that ultimately creates its own momentum and has a self-fulfilling move back to its place of a more balanced S&P.
Cem Karsan:
To your point. One of the great things about being hedged in the S&P and in the product, you’re really hedging the changing face of the market at all times.
Jason Buck:
Did I mischaracterize it that they would take a violent sell-off? Do you think it can be a benign rotation to value?
Cem Karsan:
It’s hard to get all the way there without, I think a more… I don’t think it has to be violent per se, but at least a more secular sell-off. I think that’s just because it’s going to take active managers or corporations themselves buying back those value stocks for the momentum names or the growth names to really underperform relative as well in a meaningful way.
Cem Karsan:
And so I don’t think active has the volume and stature that it had relative to passive at this point to do it on its own. That’s why a market sell-off or something along those lines would really help to really reiterate the relative momentum of value over growth and get it to that point where passive then can carry the torch from there.
Jason Buck:
Speaking of passive, as Mike alluded to that. Especially around the March 2020 sell-off, you still had passive buying into that. That could be part of that V-shape, K-shape recovery, whatever anybody wants to call it. But I actually brought it up with a piece that [Cory Ovstin 00:56:12] and I did the other day. That you were beating the drum that it’s actually a lot of that dealer positioning on quarterly options expiration, especially triple or quadruple witching.
Jason Buck:
It actually coincided really well with the passive inflows in that third week of March. We saw it also in the previous December timeframe. But as I brought up the Cory, we only have a few data points. It’s more of a hunch at this point. Or how do you look at this? The combination of quarterly options, exploration and passive inflows or do you think it’s primarily on the dealer positioning going into quarterly OPEX? Or is that a way to pin it or also to cascade events? Or how do you look and it depends on the positioning each time?
Cem Karsan:
Yeah. Two different things.
Jason Buck:
[crosstalk 00:56:52] five questions. That’s five questions.
Cem Karsan:
Yeah. Two different… No. My view is, look. It’s dealer positioning and the flows that come from that. Then you have passive and the flows that come from that. They’re different things. They both have dramatic effects. They’re all part of the equation. The supply and demand equation.
Cem Karsan:
We really don’t look at fundamentals. Broadly, other than when I say fundamentals like macro flows. Some people call those fundamentals. Those are flows. For me, it’s all about flow. Growing up as a market maker right in the business, that’s what matters. It’s where the price clears for things. And so you have different structural flows. You have the passive versus active, which is very important. Much slower turning and just does its thing over periods.
Cem Karsan:
There are rebalancing periods where it’ll change a little bit or whatnot. But the thing about risk premium hedging and particularly as it relates to options hedging is, those work on very co-structured calendar intervals. They’re very significant in terms of size, but their change is significant. How much the change in those flows is, is really dramatic over different periods.
Cem Karsan:
Really understanding when that positioning changes is much more powerful in terms of prediction, I think, over shorter periods prediction. They’re more quick tip, quick twitch flows that change quicker. Whereas passive is a lumbering, slow, constant thing that’s happening underneath the market.
Cem Karsan:
When we’re talking about what happened with quarterly in March and how we saw it [inaudible 00:58:42]. In September we saw it of last year. That was actually a big period where we saw rotation begin and that initial decline. That was also something that we were able to call based on these flows.
Cem Karsan:
It’s really quarterly matters it could happen to other big monthlies where the open interest is big enough. But there tends to be a quarterly explorations particularly the ones that explorations that have been on the books for quite a bit longer. Bigger positioning and bigger effects.
Jason Buck:
Can you explain how, going into that quarterly expiration, how you have all of those dealers hedging leading into expiration, but then expiration rolls off those contracts and it clears the market for allowed to a bounce back. Maybe people, it’s counterintuitive for some people.
Cem Karsan:
Yeah. Walk through March, the positioning in March was short enough that on the downside that… A lot of people were hedged with February options in front of them. As February rolled off, if people didn’t… We could see that people weren’t rehedging enough relative. It opened up a situation where dealers were caught flat-footed and really short.
Cem Karsan:
So that when other factors came into the picture, the way we see it is as that February was expiring, [inaudible 01:00:02]. That exposure was expiring. That was causing Vanna flows positive. Pushing the market up to an unreasonable height. There’s a natural when that Vanna and Charm disappears as a natural giveback.
Cem Karsan:
Now, that giveback may just be something where it creates a correction in time or a digesting and people get rebalanced if the positioning isn’t too bad. But if that has gone too far and there are other factors and other rebalancing things that come into the picture and that tail is really not hedged in particularly big following, that can lead to particularly with the right, with the news that we had with COVID and whatnot, it can allow for an opportunity for things to really steamroll.
Cem Karsan:
When that happens, now you have a situation where everybody’s trying to get out of the door this big with leveraged positions at the same time and most of those positions were in March. There was a big buyer and VIX calls. A lot of people [inaudible 01:01:01] or whatever.
Cem Karsan:
He was one of the drivers for a lot of other short positions from firms that we know that are no longer with us. That led to a steamrolling effect where everybody was trying to chase the same positions at the same time. That forces the market lower. We’ve seen this again, XIV in 2018. August, 2015, [inaudible 01:01:25] devaluation when that positioning is that it can be the driver. It becomes the driver. That reflectivity is actually way more powerful than the fundamental underlying factors that other people may think are driving. [inaudible 01:01:36].
Jason Buck:
Then not to overly simplify, so it exacerbates the move. But then once those contracts expire, they no longer have to hedge those moves and they’re not accelerating those moves. It’s just like the air pop can collapse and just allows it to go the other way.
Cem Karsan:
Yeah. Not only that. If you think about it, if something is really crazy high because everybody’s shorted, everybody’s trying to get it back, the March is here and things behind it are here, what are people going to go do? They’re going to go buy what’s cheaper to try and hedge there, what’s going crazy. They’re not going to try and just buy the thing that’s going nuts.
Cem Karsan:
The positioning got to a place at the bottom where people were longer, longer-dated vega against this March that was on the way out. The second this March expired, it looked again, a great trade. Everybody was like, “Oh, this stuff’s expiring. I own this stuff really cheap relative.”
Cem Karsan:
Well, guess what? Now, everybody went from being really short gamma and really short protection to decaying longer, longer vol and shorter and shorter delta and longer and longer skew. And so what had happened? What happened? Skew collapsed. Vol collapsed.
Cem Karsan:
The market started to… The Vanna and Charm flow started to kick in. Where all that vol compressions leading to more buyback of deltas and we’re off to the races. It’s not just that the shorts expired, it’s the positioning that came about because of that demand on those things leads to a reflexive move the opposite direction.
Jason Buck:
Exactly. This is going to kill me because we try to be fairly ever green on our content. I can’t help the topical nature of this, but it relates to what you’re saying. Hopefully, I’m curious to your take on the GameStop scenario because it’s related to what we just talked about as far as where the positioning are. Where the hedges? Then eventually things collapse when people no longer have to hedge their position. You’ve probably thought about it 10 different ways. I’m going to give you the floor to pick and choose your spots and tap dance through that.
Cem Karsan:
Yeah. That’s a gamma story. That’s almost way simpler than a lot of the other things I talk about because it’s, you have these Vanna and Charm flows and everything. But this was so focused on upside calls and against stocks that where the float was really low and it became a squeeze.
Cem Karsan:
Just like we saw in March on the downside, this is the same thing but on calls and single list on the upside. An identical scenario. Put it in reverse, what are people doing who are short there? They’re not going to go buyback that short-dated thing. They’re going to go buy something behind it. Eventually, we saw this with Tesla very recently. I was able to call essentially the top here. Right now for the short period in Tesla because essentially all those calls had been bought.
Cem Karsan:
Dealers are short them in the long stock. The second you see, the momentum slows. It doesn’t take a reversal, it just takes a slowing. All of that decay of those… That call premium means all these dealers now have to go sell all their stock that they’ve been riding up against them.
Cem Karsan:
And so eventually that leads to selling. That creates even more of a lack of momentum. It becomes a self-fulfilling prophecy and eventually it can lead to an unwind. It’s usually not the thing. There usually has to be something else to set it off.
Cem Karsan:
Like we saw in this case it was Robin Hood and these other entities having margin calls and not being able to allow that same level of flow to continue. But once that happens, much like with passive and these other factors, they’re momentum driving factors. That a second something stops, it naturally there are flows that are technical that essentially force it the opposite way.
Cem Karsan:
And so understanding how those dynamics work is really important. A lot of people have modeled these things with technical analysis and again, correlation. Things that they understand well. When the momentum slows, then I want to be X, Y, and Z.
Cem Karsan:
The problem there is, it’s correlation not causation. Understanding how these things work and modeling based on understanding the underlying dynamics is much more powerful and much more as a strategy that will last for history, as opposed to a lot of these other quantitative strategies which don’t work as well.
Jason Buck:
Was it making you want to rip your hair out when people were talking about payment for order flow and the evil market makers and with lack of nuance or what are your thoughts?
Cem Karsan:
Well, yeah. Look. Running a market-making firm, I understand the positions that a Citadel or whatnot are in, in that scenario. This is for people who have traded these markets as actively as we have. You understand, it’s an accent. It’s war. It’s self-preservation.
Cem Karsan:
These guys are getting massive flows in a direction and what are they going to do? This is not a sympathy thing that they’re going to profit from it. They’re going to try and protect themselves and get ahead of it. They’re not only going to raise the implied volatility as much as they can, they’re going to own whatever flow’s coming proactively to try and… If somebody’s going to come buy something from you constantly every day, you better own it just so you can sell it to them. Otherwise, you’re going to get short a lot of it.
Cem Karsan:
There’s a lot of analysis and a lot of finger pointing, but the reality is, they as market makers and dealers are providing liquidity in the marketplace. The best way to do that is to actually take the same direction side as all the flow is coming and ride the flows.
Cem Karsan:
In a sense, we’re riding flows too. We’re sitting here looking at where the flows are coming from and what that’s going to mean for the market and changing our distributions as we talked about accordingly. That’s what any honestly good trader who’s been in these markets long enough understands and needs to understand to be profitable.
Jason Buck:
I always save my hardest question for last. Obviously, we’re riding the fashionability of long volatility. It always, after a sell-off, all of the sudden everybody wants to talk to the long vol guys and talk about the higher order Greeks, which I’m sure you’re surprised by.
Jason Buck:
If I was smart, I would have bought call options on your Twitter account a year ago. And so I’m curious at the end of the day, how you see the Thunderdome of Twitter as a long vol or short vol. Or do you think you’ve figured out a statistical Arb with long wings?
Cem Karsan:
Oh, man. For followers? Are you talking about-
Jason Buck:
Yeah. In general. How do you manage Twitter? You seem to navigate it well. And so that’s what I’m saying. You’re riding that wave and maybe capturing the upside in trying to… Do you use your mute button fluently or how do you think about it?
Cem Karsan:
Yeah. Look. The beauty of social media is if you have… It’s the best ideas rise to the top. This is something that people don’t understand. I’d love to say I have some magic model that allows us to grow our Twitter accounts and our exposure.
Cem Karsan:
But the reality is, these ideas are things that we’ve developed in-house. This is not in a book. This comes from experience where we’re writing white papers as we speak. But we’re really getting the word out there on something that’s very powerful and I think people are seeing the benefits of it. The value, the convexity of a powerful idea is tremendous. I’m never short of powerful ideas. Or long ideas.
Jason Buck:
[inaudible 01:08:55]. I like that. You can find Cem on Twitter @jam_croissant. But thank you so much for being on. We appreciate it and look forward to our future endeavors and conversations.
Cem Karsan:
My pleasure. Thanks, Jason.
Taylor Pearson:
Thanks for listening. If you enjoyed today’s show, we appreciate it if you would share this show with friends and leave us your view on iTunes as it helps more listeners find the show and join our amazing community. To those of you who already shared or left a review, thank you very sincerely. It does mean a lot to us.
Taylor Pearson:
If you’d like more information about the Mutiny Fund, you can go to mutinyfund.com. For any thoughts on how we can improve this show or questions about anything we’ve talked about here on the podcast today, drop us a message via email.
Taylor Pearson:
I’m Taylor@mutinyfund.com and Jason is Jason@mutinyfund.com. Or you can reach us on Twitter. I’m @TaylorPearsonMe and Jason is @JasonMutiny. To hear about new episodes or get our monthly newsletter with reading recommendations, sign up at mutinyfund.com/newsletter.
