My guest this episode is Kris Sidial, co-CIO of The Ambrus Group, a volatility arbitrage focused firm founded in 2018.

Kris recently joined Ambrus after spending several years on BMO’s exotic and listed options desks. While time on these desks gave Kris the experience of managing a large derivatives book, what convinced him to take the leap to a new firm was growing confidence in a thesis that market micro-structure had undergone a regime shift. And in Kris’s view, this regime shift supports his approach to building a volatility arbitrage book.

Kris’s approach is broken down into two sleeves: long and short volatility. Within long volatility, Kris plays a unique flavor of dispersion trading. Within short volatility Kris plays contango in the VIX futures curve and kurtosis trades that seek to exploit mean-reversion and overpriced volatility.

With several moving pieces, we spend the back half of the episode discussing each sleeve, the underlying approach, how Kris thinks about managing risk, and how it fits into the whole.

What becomes clear is that while we discuss each sleeve independently, they do not exist in isolation. The portfolio is designed to co-exist, with careful thought about how positions in one sleeve offset risk in another.

From a unique fundamental outlook to the holistic approach to portfolio construction, this episode has a lot to offer.

I hope you enjoy my conversation with Kris Sidial.


Corey Hoffstein  00:01

All right 321 Let’s jam. 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  00:20

Corey 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 research 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 in securities discussed in this podcast for more information is it think

Corey Hoffstein  00:52

My guest this episode is Kris Sidial, co CIO of the Ambrus group, a volatility arbitrage focused firm founded in 2018. Kris recently joined amorous after spending several years on vimos, exotic and listed options desks. While time on these desks gave Kris the experience of managing a large derivatives book. What convinced him to take the leap to a new firm was growing confidence in a thesis that market microstructure had undergone a regime shift. And in Chris’s view, this regime shift supports his approach to building a volatility arbitrage book. Kris’s approach is broken down into two sleeves long and short volatility. Within long volatility, Kris plays a unique flavor of dispersion trading. Within short volatility. Kris plays contango into the VIX Futures Curve and kurtosis trades that seek to exploit mean reversion and overpriced volatility. With several moving parts, we spend the back half of the episode discussing each sleeve, the underlying approach, how Kris thinks about managing risk and how it fits into the whole. What becomes clear is that while we discuss each sleeve independently, they do not exist in isolation. The portfolio is designed to coexist with careful thought about how positions in one sleeve offset risk and another from a unique fundamental Outlook to the holistic approach to portfolio construction. This episode has a lot to offer. I hope you enjoy my conversation with Kris Sidial.  Kris, really excited to have you on the podcast. Thanks for joining me, listeners, I think most of you know that season three was a wrap. I was done. I was taking the rest of the year off. I was planning on going to the Caribbean. But Kris made a jump, which he’ll tell you about. And I had a lot of people reach out to me and say, Hey, you should get Kris on the podcast. He’s someone you should definitely talk to. And so I connected with Kris, we had a great conversation. And I am super excited to be doing this little bit of sort of like post season after hours chat with you, Kris. So thank you for joining me.

Kris Sidial  03:01

No, thank you so much. Thanks for having me. longtime listeners. So actually good to actually be on the show.

Corey Hoffstein  03:06

longtime listener first time caller. I know before we get started legal and compliance and a bit of a disclaimer they want you to read so let’s go ahead and get that out of the way. Yeah,

Kris Sidial  03:16

let’s get rid of this. So this is actually for educational purposes only. Nothing that is said on this podcast should be held as investment advice. Nor is this an attempt to solicit an investor or any investors. Nor should anything said on the podcast be held to myself, any firms I’m currently with any firms I dealt with in the past or in the future.

Corey Hoffstein  03:38

Perfect. Now that we’ve got that out of the way, Chris, I know you have a pretty non traditional background for folks who end up at big Wall Street banks. Maybe we can start there. How’d you get into the game?

Kris Sidial  03:50

I do have a pretty interesting background. I’m actually a graduate student at the University of Pennsylvania. But before the whole Ivy League thing, I actually came from a non target school. It was an interesting path because, well, just to take a step back. Before all this, as with most traders, I was infatuated with the market through gambling. So I kind of dabbled in sports gambling a little bit during my high school and early college days with one of my best friends. And funnily enough, I think users would actually appreciate this story, but we used to actually, during this time sports betting in the US was illegal. So we would western union money to some guy in Nicaragua. I kid you not That’s a true story. He’s gonna be listening to this. He’s probably laughing at this too. So we actually see western union money to the guy over in Nicaragua and

Corey Hoffstein  04:39

how did you find this guy?

Kris Sidial  04:40

He found the man that wasn’t he did all the research on this. So pretty much out of stats background, I wasn’t a Math Olympiad and whatnot like that. A little bit of a nerd growing up, and I thought you could use apply statistics to actually get an edge, but I was definitely wrong on that. At least I didn’t get an edge. Then. I was an accounting major at long On University and as an accounting major, obviously you partake in certain things where you’re intertwined with the market. And I started become a little infatuated with scientists and try to throw my money into trading lost all my money, most of my friends money, we lost his mom’s money, it was definitely an interesting path. But throughout this time, I was paying my tuition to the markets, not to the school. And I actually started to really get good at what I was doing, I got so good to a point, my finance professor was like, we should really think about this as career, my mind was set on just going and being an accountant at one of the big four firms. And I really became infatuated with the game, I really love the game at a genuine passion for it. And I remember just saying like cheese, you know, I’m coming from a non target, I don’t know, if I’ll be able to really break in, I didn’t have any internship experience or whatnot. But I know the only advantage that I did have was that I had actual trading experience. And I was managing a small account like $50,000 for like an investment club and a few investors or whatnot. So I actually had experienced trading and managing risk. And I thought that could give me a leg up. But unfortunately, it didn’t, because every recruiter just didn’t give me a shot. So it got so bad to a point, I was literally sending out like hundreds of emails and stuff on LinkedIn every single day to PMS and recruiters. And I specifically remember actually stalking a few PMS, I found out where they were, I would sit outside on the bench. And as they came out, I would realize I’d look down and be like, Oh, that’s the guy. This is like the photo, I would approach him and try to pitch him as he worked at Grand Central Station. So it was quite an interesting process. But from there, somebody actually gave me a shot. And I ended up working on the prop desk at Chimera securities. So that was my first real institutional gig training there. Then from there, I went to the buy side for a very small equity hedge fund. And then after there, I had the chance to actually work with one of the guys that started the CBOE. He’s actually the president of the CBOE market Makers Association. And this is a really smart guy, I’m so glad I had the chance to be a junior and am I was his only Jr. and I would basically drive out to the Hamptons every single day, it was like hour long drive and go to this guy’s house. And he would show me things on how he traded vol and how he looked at options and the entire space. So I definitely learned a lot from him. And from there, I actually went to BMO, and at BMO, I spent some time on the exotic desks, so trading derivatives, and then the listed options desk. So it’s quite a transition. But I think what makes my experience so special was that I have experienced from all different angles of the market, I got a chance to see what it’s like to trade as a retail trader and understand putting on risk as a retail trader, then trading on the prop side, and then from the prop side to the buy side. And then from the buy side to the sell side. So understanding where these different market players lie and understanding why they’re taking positions, I had the chance to literally sit in all those seats. So it gives me a better rounded view, better holistic view of the market and why guys do things and why would they do things. So I think that learning curve was great. So I’m happy that I experienced that struggle early on in my career, because it just molded me into the trader that I am now.

Corey Hoffstein  08:22

So maybe that’s where we can start and dive in. Because I think that experience is something that’s very unique. Not a lot of people necessarily have all of that perspective. So maybe for the listeners, you can give an idea as to what the real differences are between sitting in a bank, doing flow trading versus being on the buy side, doing a more speculative approach.

Kris Sidial  08:45

It’s a huge difference being a speculative trader, and being this trade on the sell side is literally two different games, you’re running the same race in two completely different ways. And when I’m on the speculative side, on the buy side, we are looking to take on positions that we believe are going to work. Whereas when I was at the bank, I was solely there for the purpose of trading float. So my job was to execute and trade flow between the clients. So there would be times where we would have large clients come in, like a Blackrock or PIMCO or something like that I was trading really large size, and they want to buy a particular derivative. And we don’t want to sell that because that’s not a good trait to us. But we’re forced to sell it, we’re forced to make them a market, because they’re our client. And that’s the name of the game, you have to keep the client happy. You have to keep flow going. It’s your job to provide liquidity in the open market. And we would have to make a quote unquote, why market to them because we didn’t want to take down that risk. Whereas if I’m in the seat that I’m in now, and somebody wants to trade something, I don’t have to take anything. I don’t take trades unless I want to take the trade or my partner wants to trade or we collectively agree to take trade but I At the bank, he was forced to make markets for clients. Sometimes this could really work against you. Because if you can’t get off that risk on your book, now you’re carrying a ton of exposure. And I think that’s the fine line with being a good market maker and a good trader on that side is, you have to know and understand when to really make markets where as opposed to being on the speculative side, you have to know understand when to actually just trade when you want. On the exotic side, it was a little bit different, because on the listed side, it was just more flow, he was just literally just trading institutional flow. Whereas on the exotic side, we was just more so a protection for the bank. So you had one job and my boss used to say this was like, the only job is just don’t lose money for the bank. Because what happens is, you put together one of these exotic structures like a phoenix auto callable with a barrier struck at like 75%, or something like that. And the clients have a big appetite for it. So you have a large client, let’s just say Blackrock will keep you some BlackRock, say Blackrock comes in and looks to take down a bunch of these notes, so that they could distribute it to their advisors, and they could distribute to their retail investors, we basically priced a note at our model, let’s just say we priced the note at like 95, we view this at 95, will now sell it into the open market to them at like 97 and a half. So we have like a two point advantage of rip. So now, when we put together one of these structures, we are actually long Vega, we’re long volatility. And in order to actually minimize that risk, we would go into the listed market and sell Vega sell volatility against that. And that was our job to make sure every pocket in the book that had Vega exposure, whether it’s six months in or year out or whatnot, was covered, we wanted to make sure our Gamma exposure and our Vega exposure was really hedged off so that when we had that nasty market move, we were able to not lose as much money for the bank, that was really the sole purpose. So you’re talking about being on the same desk with two different purposes, one to trade flow, and one to just protect the assets. Because to begin with, you are at an advantage when you’re the bank, you have an advantage when you’re structuring these products and actually selling the product to a client, you kind of hold the keys there. But obviously as with everything, no market is perfect. And you got to make sure the bank doesn’t go under overnight.

Corey Hoffstein  12:27

How do you think your experience on these two desks has translated and maybe informed the way you think and the way you approach your speculative buy side trading now,

Kris Sidial  12:39

it has helped me tremendously, I viewed how to really balance a portfolio and trade a large book. And I think that was really the key, because not too many guys could say that. They were a part of a team like that. And at the bank, people have this misconception that at the bank, you kind of have your own book or whatnot, right, which are part of a collective trading team. So everybody’s performance is merged into one basically, for that group. And I really learned from some senior guys how to manage risk and how to manage a book, especially when it came to the derivative side and understanding when to actually put on a little bit of risks, when to hold back. And when to literally just put up your hands and say, Listen, I don’t know, these are lessons that I learned early on from basic trader psychology book, like no reminiscences of a stock operator or Market Wizards, I could go on and on, we have the turtle, it trains you to have a certain psychology, but to actually apply it to a portfolio in an actual large book is two different things. So you have to be able to see and assess all the different strings and angles that a book could have. And as I started thinking about that, when I was under some of those senior guys, their way of thinking, force me to think that way and pursue trading in that form. So now, when I’m, let’s just say trading my own book, I view that vigorous with the same type of emphasis, as I did with the bank, because at the bank, you have overnight limits, you can’t go over your delta limits, and your Vega limits and your gamma limits. Because if you do go over literally three strikes and you’re out risk doesn’t want to they don’t want to hear that. So you go over those numbers three times without a valid reason. They’ll literally snip you on the spot. And just from also hearing and seeing other funds and how they performed and traded. That was big, because when I was trading customer flow, I started to get an idea as to why guys are trading a particular name. What are they looking at? Some of those guys were trading some very simple strategies, you know, it wasn’t as complex as people think they were. And just to see that and get a hold of that and understand where they put their risk on and why they’re putting their risk on there. It just transitioned your mind. So you’re looking at operating a huge book from a holistic standpoint and saying, Okay, I have to make sure that my shot levels are in line if the market does this, and one thing that my boss always used to say. And I specifically remember this, during the whole Corona sell off was, the market was down about 10% or so. And he basically told me, You have no idea. If this could go down 20%. Tomorrow, if we go down 20% The next day, you literally have no clue. And we as traders, we try to estimate that we try to put an end on historical data and say that this is the beginning. And this is the end, and it’s capped at that. And that’s not true, right? The market is just one large Brownian motion, that is forever changing. And we lose money when we try to overfit that and turn that into a form of some sort of quantitative approach of actually systematizing that, if that makes any sense anybody.

Corey Hoffstein  15:49

So you spend all this time trying to get this dream job, you hustle, you work, you stock PMS, you finally get your dream job. And just recently, you decided to leave and launch your own firm. And I have to know what was the catalyst there? What made you want to jump ship and do your own thing after finally achieving what you had spent so much time trying to achieve?

Kris Sidial  16:15

It’s actually really interesting, because I have a lot of friends and family that look at me like I’m crazy. They’re like, why are you leaving this high paying job? Why are you leaving this dream job per se to kind of go out and do your own thing. But no, I just think that the opportunity really presented itself. When I was on the buy side, I made friends with quite a few people. And during the time, I really kept in contact with them. And my current partner right now will really smart guy really good trader him and I just mesh really well on the way how we view markets. And we’ve been friends for quite some time. So probably about like, I want to say about like five to six years. Now, when you get a chance to know a person like that and you interact with them on a daily basis, you kind of get an idea is like, alright, this guy has the same ideology as me, we view things in the same way. This is what he does full time that guy’s a successful independent trader will actually bring on Sal bassy, a guy who spent 15 years at Citadel on the quiet desk. And when you have a guy like that he just speaks volumes for itself. years spent 15 years at Citadel, you’re extremely intelligent guy. And even a data guy might extremely smart dude. And even the stuff that he provides the value is immense. And I just think that it was a dream team kind of forming and will would kind of prompt me month after month like hey, man, we can really make this happen once you come on board if you join. And after a while I was just like the market condition is actually setting up for that. And I wanted to take advantage of it. Because we have a certain ideology and a certain belief that we believe that markets will continue to trend. We think that we’re long the US economy and for the foreseeable future, we will remain long US economy. But there’s a big butt to this. We also believe that market microstructure is changing immensely. And although we believe that the Fed will not disassociate itself from markets, especially with the way how the retirement plans and the pension funds have now starting to transition into being tied to US equities with global rates being so low, we really believe that market microstructure is going to continue to evolve in a way that it allows you to capture yields while the market is going up. However, at the same time, capture a large amount of convexity. As the market makes these moves upward and downward. The moves are much more emphatic and much more proclaimed as this microstructure changes. And there’s a few things that we have been watching. And specifically we’ve been seeing, I was going through the math last weekend and the weekend before on some of the variants in the SPX monthly moves, posted 2017 and pre 2017. And I was comparing different time series and you don’t really need to go into the weeds and check the math on this. You could just literally pull up an SPX monthly chart, and literally just see that the candles are have been much more emphatic to the upside answer the downside, we’re noticing these moves are much more stronger. That’s one thing. But the other thing is this interesting dynamic that there are so many structured products out there and being on the exotic this kind of gave me a really good insight to see. The appetite for Structured Products is immense. Everybody wants everything structured, and I’m a millennial. And as most millennials, everybody wants to put their money into something passive. They want a little bit of everything. They want the big suit, they want their money in egg corn and they want these ETFs and it’s just a big large mix. I mean, we’re seeing that even ETFs I think the stat is 7000 global ETFs to 3000 us listed names, you’re having that effect where and we’re seeing that I remember that was watching the markets, I think it was two weeks ago where the ETFs were up and the underlyings that comprise them were down. So you’re getting that effect where the actual tail is wagging the dog. And we’re seeing that the appetite for all that is changing the actual market dynamics. On top of that, you have to add in the fact that rates are low. And anybody who’s anybody could tell you, that is a tremendous thing, when you’re actually looking at this market, you can’t analyze this market, you can’t analyze this particular time series and give it the same amount of credence that you gave to a time series in the 80s. When you’re analyzing two data sets, you have to wait them accordingly. The market that we’re in now, is completely different from the market in the 80s. People have to understand that, if you’re watching price action, if you’re trying to make that comparison, it’s just not an equal comparison, it’s apples to oranges at that point. So with rates being low, it forces guys to search for yield, because guys literally have nowhere to actually generate yield. And you have to think about all these pension fund managers and all these asset managers in Nigeria and Thailand and all over the world, you’re getting this large base of new players that are coming into the market, whether people want to acknowledge it or not. I know for an absolute fact, and this is one of the benefits of actually working for a large bank, we started to see some of those clients from overseas come on board, and we’re just like, wait a sec, this guy only plays bonds? Like why is he not opening account to trade derivatives or equities? Because they had no other option? So search for you, what are you going to do put your money in Treasury like you’re gonna yield no money. And then if you’re like, Oh, I’m gonna go to a corporate bond, I’m going to yield any money there to if you’re going to take the default ratio, you might as well just go for the home run and US equities. So you have this dynamic where all these new market participants are coming in. And they’re inexperienced, these guys in Nigeria and Thailand and all over the world, they don’t know how to trade US equities. That’s not their field. So the moves are going to be much more emphatic, because they’re going to be chasing stocks up and selling off much faster. And you’re gonna see, and we’re also seeing with the retail investors, this whole new Robin Hood error, there are so many uneducated hands in the market, I think people actually give much more credence to that wave than that deserves, I don’t think it’s only Robin Hood users moving the markets. I think that’s actually said fund managers just trying to make an excuse for it. But it does play a factor like you have to take that into account. So you add in the fact that rates are so low, you have all these new participants, everybody’s just flocking to equities, because they have nowhere else to make money, then you also have to think about, well, what about these target funds, this is a big thesis on our part for 2021, I’m really going to stand by this, I believe you will start to see a lot of pension funds or retirement funds, their quote unquote, target funds are going to start to shift towards more equities. I think you’re going to start to see some of those managers. And those allocators start saying like, listen, we have to generate something because these funds have mandates they need to put cash to work. So what are you going to do just invest in a bond that’s yielding a negative return for these people, and you have a target date requirement. I think with all those things taking place, you will also have to factor in the fact that these guys are just literally leading to one trade and that one trade is quote, unquote, volatility suppression, we’re seeing that with some of these target funds, guys are coming in there. And there’s just systematically just selling volatility without any care, no quantitative approach at all is just, I’m going to capture the VRP, I’m just going to go in there, I’m just going to sell I’m gonna do call overriding. I’m just going to sell 10% down, SPX put and go about my day, time comes then we hedge off the risk, or we’ll probably hedge off a little portion of the risk. So in doing so, that’s adding to another part of quote unquote market microstructure changing because guys are synthetically suppressing balls, because they have no other choice. Where else are they going to make money? What other trait is there? Besides the character, guys are just searching for the territory, they’re searching for the easy money right now. And then what we really believe is that because those target funds are going to be leaned more towards equities, it’s going to be very difficult for the Fed to disassociate itself from markets, especially because a majority of the middle class savings is going to be in their 401, k’s and their pension funds or whatnot. And for the Fed to actually do all this to try to keep markets up for the time that it has to step away in the most crucial time where the consumers and the crux of the economy’s money is tied to their retirement savings. We just can’t see it. We just can’t see that governmental intervention will come to an end. So with that being said, we think that they’ll continue to try to find markets but doesn’t change the fact that the microstructure and the dynamics around how more markets operate aren’t going to be effective if the market drops off 7%. We’re seeing those moves. We seen those seven to 10% moves in early June, when the market just dropped off. I didn’t know where nobody had any clue what was going on. Why was it doing that? When all these things taking place, it just leaves a lot of opportunity for us to capture a lot of Vega. And a lot of convexity

Corey Hoffstein  25:24

is the ultimate idea than that these market microstructure changes that are occurring, which sound like are coming from a lot of different angles. It’s not just one source that’s easily identified. It’s a whole bunch of different pressures that are almost in an uncoordinated way, creating a coordinated source of risk, when all taken together, is the idea that the market isn’t appropriately pricing this risk. In the Options world,

Kris Sidial  25:50

I think we’re seeing the market start to price that in a little bit more as of late, especially with what’s going on right now, right now is September 2, and we’re seeing volatility move in relation with spot. So that’s a little bit different. But I think the actual real outliers, I think, are still under priced. I think people aren’t giving as much credence to some of the two to three standard deviation moves as they should be right now. And I’m also a believer that markets don’t fall apart when everybody’s anticipating them to fall apart, it just doesn’t work that way. It’s an effect that happens when everybody doesn’t see it coming. That’s when the unraveling effect takes place. So we really hold the belief that you’re not going to be able to sit there and time this. Of course, as with every volatility trader, we have our quote unquote, like GARCH models that we kind of throw out the window, because I don’t truly believe that anybody could accurately estimate and time when you’ll get that massive volatility spike, but what you can do is you can structure yourself around it. And that’s how we kind of view vol is we’re going to look for the best play that presents itself out there and structure the book around that.

Corey Hoffstein  27:08

So before we dive into the actual strategy, you and I, in the past have talked a little bit about back testing. And I am always interested in asking sort of technical back testing questions as they relate to options because options data is dirty and stale. And there’s a lot of interesting fundamental operational questions. But I think I’m going to steer here towards a more philosophical question, because a lot of these ideas that you’re talking about are new regime ideas, ideas that cannot, from a quantitative perspective, necessarily be tested the same way that a lot of quants have tried to look for hundreds of years of data. I mean, certainly in the option space, you can’t do that anyway, like you can with equities. But when you are saying, Hey, we have a regime break, this is something new, this is something that’s not being priced in, how do you think about testing for that? Can that be tested?

Kris Sidial  28:00

Yeah, that’s a really interesting question. And what we actually believe is that you can’t fully adhere to the back test, the back test is there for a guide. And that’s where people tend to make most of their mistakes is that they use the vectors as a holy grail. Of course, we back test stuff, and we have our models, but a large part of our model is actually based around a confidence interval. And that comes from our discretion and our experience as traders. So you perform it back to us. And it is used as a guide, it will guide you in the correct direction as to what you believe. But it’s not the end all be all. And it’s really hard to back test, different market and different market conditions. And people kind of fail when they’re doing their back tests, because they will analyze a time series just across the board and not trying to sub segments it. One thing that I like to do is I like to actually back test certain strategies and different regimes. So I’m not going to go through the actual numbers, but I like to break down the VIX into different regimes. So I’ll break it down into a low vol regime, a medium vol regime and a high vol regime and a super high vol regime. And from there, I will run a time series analysis on different strategies and how they have performed on different underlyings. So in a nutshell, it’s very difficult to give too much credence to the backtest you have to understand that, as a trader, you have to kind of remove yourself from the numbers at a time. That’s what really makes a good trader and I tweeted about this quite a few times is that you need to be able to understand the math, apply the quantitative side of it, but be able to use that discretionary side and move it into one being and once you take care of that and you move that you will find that find equilibrium where I am math base and quant driven. However, my discretion carries the You portfolio. And as you’re doing that your experience ties in, because as quants, everybody has ran into the same thing, how many quants are in college. And they’re like, Yeah, I’m gonna outsmart the market, I’m just gonna sell tails, and it goes against us, we’re gonna roll it down and yada yada, like everybody has came across this strategy, and it just does not work, you run the risk of Ruin, and you will go into ruin. And then the other strategy is, quote, unquote, not seem to leave type of thing, where you just bleed for years and lose a ton of money. And then finally, you get the move that you were looking for. And well, guess what, you still lost a ton of money for five years, and you only recoup probably about three years, after you get that large book, the math can only take you so far, because the market is, like I said earlier is one large Brownian motion. It’s always changing. As you as traders, everybody who’s a trader needs to adapt to the new condition, the new environment. And what they try to do is they try to lock on into an old environment and kind of keep that primitive way of thinking where they’re like, No, this cannot do this, and this cannot do that. And when you think that way, and you say, well, the math says this, well, guess what, you’re gonna get absolutely hammered when you move into a new regime. Because just like the early 2000s, and the late 90s. And even now in 2020, the market has seen new regimes, and it will constantly see that and unless you could adapt, that’s the number one thing about a trader, you could tell a good trader, from his ability to adapt. Everybody who’s a quant looks for like a holy grail or system. So many times as guys like, what’s your system, when I was coming up, that was my thing that I was fixated on, because I thought that there was some big trader out there who had this magical system. And it just doesn’t exist. Guys who are trading certain strategies and models can’t be applied to every single market, it just doesn’t work that way, if there are strategies out there like that, they’re just not scalable. So taking a step back, you really have to take the overall backtest with a grain of salt. And you have to understand that, as with everything that has to be a sense of discretion, and I think there will always be that trader input that quote unquote, confidence interval that we like to give in our model. Once the numbers pan out, and everything makes sense. We step in with our confidence interval and say, Okay, how much of the model is comprised of the confidence interval, and is to trade a goal based on that.

Corey Hoffstein  32:27

So we’ve set the table sort of talking about the existence of this new regime that you believe that we’ve transitioned into, talk us through at a high level, how you think about structuring your book, and a strategy to take advantage of this new environment.

Kris Sidial  32:42

Again, we have a basic premise of this, we are looking to yield returns and stable markets and slowly uptrending markets and really get the homerun hit when the market tends to fall apart. And when the market is actually blazing against us. That’s when we actually need to step in and make sure that our shock levels and our risk levels are online. And the book is kind of completely hedged out. So there are three separate approaches that we look, actually, we aim to break the book down into two segments. One is a long haul segment where we are about 70% allocated about to long haul and about 30% allocated to shortfall. And in that mix, we like to trade relative value on the long haul side. And we like to trade dispersion trading. It’s not a pure form of dispersion trading, but it’s our form of dispersion trading on the long side. On the shortfall side, we like to trade some kurtosis stuff. And also, we’d like to take advantage of the contango effect on the VIX Futures Curve. So we actually express that side of trading to the VIX, ETP products. And we really believe that the book is one big balancing act where we have positions that are moving in our favor that our long haul stuff and then moving against us to short haul stuff. And this is why we kind of constitute the book as quote unquote, vol ARB, because we’re not long only Guys. And we’re not only short guys, we like to take advantage of the mismatches in the market. And we will kind of position the book to bounce this off and more like a seesaw. That’s how the book moves in relation to each other. But the big premise is that as markets remain stable, or they slowly grind up, we look to generate some sort of a yield. That’s when our shortfall side of the book kind of steps in and kind of carries us through. We’re not looking to outperform the best performer on the year, but we are going to generate some sort of yield. And when the market does give its turn and gets hammered to the downside. That’s where we actually look to capture a lot of yield. And we actually believe and expressing this through some of the short data tenor because we believe that with the high theta effect So on to week 10, or one retainer, sometimes we like to play like a month or maybe two months at max, we now open up another portion of the book where we’re actually funding some two months stuff, just because we think that what the election time and everything that’s taking place, it just makes sense conceptually to buy cheap ball out there. But we like to structure those parts of the book into one big collective system. And that’s how the book kind of moves as a whole.

Corey Hoffstein  35:28

You mentioned you sort of before you go into the three strategies at a high level, it’s sort of two components long valance short ball volleys at about 70%. Long Vol. 30% shortfall, when you’re breaking that down, is that sort of Invega notional terms is the way you think about it.

Kris Sidial  35:42

Yeah, there’s a few ways that we actually think about it, we actually look to structure around the Greeks. So in a perfect world, we’re looking to be delta, neutral, and long Vega. But obviously, the book kind of moves with us and against us. And those positions are going to kind of move in favor out of favor with us. So it really all comes down to the trays that we’re taking and the structure that’s in place at the time, the allocation base is kind of based on our discretion, not every time not every second of the day, were carrying a 30% shortfall allocation, there may be some times where we are allocating about 10 to 15%. And on the long haul side, maybe sometimes we’re only allocating about 40% to 50%. But for the most part, that’s the numbers that we are kind of shooting for. But we would like to be long Vega. That’s, quote unquote, the name of the game. So it

Corey Hoffstein  36:38

sounds like to me, the book is not static, sort of a composite of moving pieces. Are these choices in terms of the discretionary nature in terms of how you make these allocation changes? Are they regime dependent? Are they sort of based on market conditions? How do you think through how much exposure you should have either on the long haul shortfall side or to any of these sort of sub strategies that you’re allocating to? A lot of

Kris Sidial  37:01

that is system based, as I was saying before, we do have a quantitative approach where we are analyzing particular things and particular ratios and charts and our own proprietary data that we actually go into. But if those signals are kind of playing out, we move the book in relation to that. So we may over allocate a particular time where we believe that is going to be a false bikal, we may actually retract some of that allocation if we’re wrong on a position. So that really boils down to some of our proprietary data that we have. So I’d

Corey Hoffstein  37:37

love to now sort of take a dive into each of the three sub strategies, maybe we’ll start on the long ball side with your relative value dispersion sleeve, can we just start with sort of high level explaining what is it and what sort of the opportunity you’re trying to capture? The structure

Kris Sidial  37:54

of the book is a really interesting one, because we really believe in selling at the money straddle to funding these very highly convex way out the money puts. And an example I would give you would be, let’s just say we sell a IV B, which is the biotech ETF at the money straddle, let’s just say two week tenor, and based on our model and everything that we’re looking at, we believe that, oh, Gilead is trading relatively cheap to IV B and the Gilead wings are actually trading really cheap. And let’s just say realize is trading at a negative mean, in comparison to two year implied, let’s just say we go through all our checks and balances, and this trade checks out, okay, well, we’re going to look to do is we’re going to sell the IV B straddle, and we are going to now fund the Gilead, let’s just say like the 10, Delta puts. So the beauty of this is that we’re literally not funding the entire structure, we’re not taking every dollar that we have in the premium and funding that we are taking a good portion of it and funding that. So for easy math, let’s just say we sell one IBP straddle, we’re gonna get a chance to actually buy about maybe like 10, or maybe 15. Generally, it’s around that ratio that we aim to get maybe like seven to 15 for every one that we sell. And the structure is pretty simple to fall for guys that are derivatives traders, they would understand well, at this time now, basically, we are leaned more towards the negative Delta, we’re not highly negative Delta, because a straddle is delta neutral. But buying those really low delta puts we have a little bit of negative Delta exposure that we have down there. That’s kind of a way that we express our view and actually carrying this long convexity type of position. And we also applied to dispersion trading to we have our way of actually segmenting the underlyings in a particular ETF or index and we look to buy falls on that if we believe that it’s cheap, but it’s a lot of discretion that comes into play. When it comes down to choosing some of these, we aim to Kelly sighs. So that’s one thing that we make sure that we focus in on is our Kelly sizing because we think there’s a little bit of an edge and Kelly sizing however, there’s a time where you also have to factor in your model, is there an upcoming catalyst. And that’s one thing that our model does really good is that it gives a little more weight to some of the stuff that can prove promising, you don’t want to just be buying cheap balls all the time, because at that time, your win rate is probably going to be like 5%, or something like that. You want to buy things that you actually know can move. And the catalyst is what’s really going to drive the long haul stuff. That’s where you get the quote, unquote, the mispricing. So it’s a mix, the book is a mix of buying cheap balls, and then buying things that could potentially make a move, not all the time, you’ll be able to get those for a cheap price. But you want to structure the book to capture that, when you get that two standard deviation move that you’re looking for. In this market, what we’ve been doing also as somewhat of a hedge as we’ve been buying some of the cheap calls to, that’s not generally our structure, we would like to literally just take most of the premium and put it to the downside. But in respect of what’s taking place when the market is just blazing up. Sometimes we also fund this and also because you can’t account for right tail risk on all ends of the spectrum either.

Corey Hoffstein  41:32

Just to clarify, making sure I’m hearing you correctly, when you sell that straddle, you are actually taking some of the premium and holding it aside just as a pure carry yield. And then you’re taking some of the premium and using that to buy the puts on sort of the underlying Is that correct? Right.

Kris Sidial  41:49

Most of the premium that the market is actually implying in there is going towards funding the downside puts on a name that we believe is trading relatively cheap, or the skew is trading cheap. We just look to take that out and fund that. And we leave a little bit in there. So we’re not getting absolutely hammered. It gives us a little bit of leeway with the actual ETF with the index.

Corey Hoffstein  42:11

So talk to me about monetization, because this is one I always find really interesting when you talk to people who operate in highly convex instruments, when you’re playing that downside put, and you start with something that’s five or 10 Delta, when the market starts to make a move to the downside, suddenly your delta massively picks up. Let’s say you end up way in the money, you go from a Delta of five to a Delta of one. Now you have a ton of linear market exposure that wasn’t in your book before. So how do you think about monetizing that profit and managing that risk in your book at a time when your call has been correct.

Kris Sidial  42:49

That’s the balancing act. That’s why traders get paid the big bucks is to make these type of calls. And this is where the quant who’s actually making a killing, he actually full as short as because as a trader, you have to have that quote unquote trader psychology where you have to find that equilibrium and maintain that mentality. Like look, I need to take profits off the table. And I need to do this in tears. And I had a really good example of this in Salesforce. Last week, Salesforce reported earnings and we were long the calls real long. So I’m like, Look, we bought the calls for like 86 cents. And after earnings, we got a chance to sell them at like 33 to like $35, that was a huge winner for us wasn’t an actual huge winner for the overall book, it hedged off a lot of risk in the book well, but the actual play that took place was Salesforce beat on earnings. And after hours, the stock just rallied up completely. Now, I’m calling well, and we’re talking on the phone and we need to make sure immediately that we’re taking some off the table. Now, obviously, we want to let this thing run you want to let this thing kind of take path and we want to wait till the open and we want all the financial advisors to start putting in their clients books and we want all the upgrades from the analysts, right. So we want to wait till the open in a perfect world. So we get those market on Open Orders especially when tech is super hot, a name like Salesforce on an earnings beat tech is hot. And every financial advisor is allocating capital to their clients and the world loves it. So you know you’re going to have the earnings upgrades. We want to hold on to that as much as we possibly can. But we know as traders that we have to start chopping them up. So after hours and in the pre market, we’re taking some more so we’re long the call so we’re selling stock against it, just lock some in each time as it moves in our favor. And at the open. We get the spike that we’re looking for The stock is rallying even after the market open orders went through, and we’re still selling some more. So we get to a point where we’re like, alright, we locked in enough we paid ourselves for the trade, we had the quote unquote, homerun. And now we’re just going to keep this on the book to let’s just see if this move turns into five, six standard deviation move. And we have been seeing that Salesforce actually did carry through with some of his strength, and it’s maintaining in line with dragging the queues with it. So it’s ways of taking profits in tears, because when we get the move that we’re looking for, and we know, we will get the move we’re looking for because market will correct itself eventually, when we get that move. You don’t want to just take a step back and walk away from the monitors and just say, oh, yeah, okay, I hit it out the park, you want to lock in and realize those gains, and I’ve seen it, I’m on Bloomberg, and I see I go through some of these long only funds, and I see their performance. And I’m like, Dude, how did you make over 100 something percent during the corona thing, and you gave all that back, and now you’re negative on the year, it doesn’t make any sense to me, that’s just bad money management. That’s just horrible trading. If you’re doing that, it’s just a myth, you should absolutely always take some off the table, you have to, quote unquote, pay yourself for the trade, you took the trade, the trade is now worked in your favor, take some risk off, pay yourself, pay your investors, and take some time off as it continues to work in your favor. And let the rest ride to get that huge standard do like six, seven standard deviation move.

Corey Hoffstein  46:39

So let’s move on to the second strategy, the VIX contango play, you’re playing the ETP there, same sort of start, what is it? Why do you think the opportunity is there?

Kris Sidial  46:50

It’s very simple to look at a chart on some of these fixed products and see which direction they go is only one way down. But an inexperienced investor would tell you like, oh, yeah, great, I could just jump in and short it. Well, that’s not the case, because these things could rip your face off in an instant. And if you actually jump in and just short it with stock, you run the risk of Ruin very fast. But that’s not the way we like to express capturing VRP. And capturing this roll yield, we actually have a very interesting way of doing it. We’ve actually back tested this, we have a quote unquote Delta optimization point where we believe in selling particular tenors staggered across the board at particular deltas. And we like selling call spreads, right. So the risk actually remains cat, we actually have a second VTP strategy that we’re running, it’s an intraday strategy, but the risk comes off immediately before the close. So this is a systematized type of product, where we just trade it solely intraday. But for the most part, the main balancing act of the book comes from selling the call spreads on the etps. And we actually believe that when you get that move, and the VIX blows, up to the upside, the most of our book is now moving in a relation that we want it. So those highly convex puts that we bought, that we funded with those straddles or we’re losing money on Australia, Australia’s going down, but we have a huge ratio, and those downside puts, and those are actually banking for us. And it’s covering the losses on the short fix stuff. Now, what we do well, is that we make sure we keep a very low allocation of the big stuff, as we’re saying most of our false self is never going to go over more than 30%. But it’s on a discretionary basis where we want to allocate more or less dependent on some of the regimes that’s out there and what our research says. But when you now blows out to the upside, all these things become capital. So when you now get that two standard deviation move, you’re fully capped, the risk is done, your long calls on the ETP products are covering themselves. And literally, you’re just running all profit when the Vega continues to expand on those highly convex puts. And that’s the ideology that we have is that selling these etps The call spreads on etps Help our yield in stable markets, because there are times where you will see the contango effect is very, very steep. And in stable markets, and even in slowly uptrending market, you’ll be able to capture that VRP on the contango. So, it’s interesting, because, as I was explaining before, our structure is set towards being a little bit negative delta. So when we actually execute our initial trade, which is short straddle along, all those highly convex puts, were a little bit lean towards negative Delta. But as you’re selling the call spreads, that brings you to a point of Delta neutrality. So you sell the call spreads and you’re actually positive delta. And that’s the balancing at the workplace Interesting enough, it’s September 2, and there has been a correlation break in spot. And vol. All the traders online are talking about this. I’ve had in depth conversations with some of the fall guys online about what’s taking place. And will this correlation break persists, generally in a regular environment will and I have both noticed that this takes place. It doesn’t take place too frequently. But we have given some sort of a nod to it. Like, we have to be aware that this took place. But for us, we actually like to, quote unquote ARB this back into play, when you have those coalition breaks, we would gladly short more. But because of the environment that we’re in, with all the instability with the election time coming up with possible potential of corporate earnings being horrible with another resurgence of Corona with all these things that are just constantly taking place. We don’t believe now is the time to be shorting that and going long correlations on that, because it’s correlations break. That’s just the nature of it. And some people are probably asking, well, is that a good correlation? Well, it is trading the market and trading the SPX, in relation to the VIX is a very, very solid correlation. And we don’t think that the correlation break will persist. But taking that trade to be long correlations right now. And the environment was not the optimal trade for us at least. And this goes back to what I was saying before, you have to know and when to understand. So user experience as a trader, when as opposed to trusting the math, this is a point where most people will look towards the math and be like, Oh, we have to just short it, we’re going to short it. But as a trader, we’re like, hold on, there’s a few things out here that are just not making sense. Let’s hedge off our risk on other areas of the book. And let’s make sure that we’re safe and protected. And then we’ll go on and we’ll assess. But in a nutshell, that is basically the balancing act of the book is we’re looking to fund these highly convex puts, capture them on a two week basis, a monthly basis. And that’s the beauty in the tenors that we trade to. Because when you’re trading such short data tenors, the gamma is extremely high, and the theta is extremely high. So as you get to carry this high theta effect on your short ball stuff, it’s really good. Although anybody who’s traded the VIX ETP products will know that this carries some sort of a very sticky Delta. Because the market gives a lot of props to the VIX that it could literally Spike 20% One day. So for the VIX, ETP stuff, you’ll notice that they may be way out the money and you may be safe, but the market makers in the market is just not going to price the falls down completely on that. So your bid ask is still going to be pretty high. And you won’t be able to really capture that high theta until the last remaining days. But in a nutshell, our ideology is we aim to take advantage of high gamma, and also capture high theta. That’s like the law of averages for us in a way.

Corey Hoffstein  53:06

So I want to ask you a little bit about the idea of managing the book. I know we haven’t talked about the third piece yet. But you mentioned how some of the positive delta here can offset the negative Delta you’re carrying in the long haul portion of the Book, by some of the things you’re mentioning about how you’ve got this correlation break right now between vix and SPX. It is a bit of a basis trade. I mean, the expectation is you need vix to be negatively correlated with the s&p, and you need those names to remain positively correlated with the s&p when the market sells off for this delta offset to really work. How much of that is just sort of based on well, you have a large enough number of names in your dispersion book that it should by almost definition on average workout versus how much of that is based on your beliefs about the regime in which we’re operating under that there will be sort of these correlation crashes in the environments you’re looking at profit under,

Kris Sidial  54:01

it’s a little bit of both. And you really have to take a step back, and you have to go through some of the correlations on the data that you’re watching. And again, as I was saying before, it’s key to analyze different time series. I don’t want to see the correlation. If I’m analyzing two names in a stable market, that doesn’t do me any good. I want to see how the correlations acting when everything is hitting the fan. And I want to analyze the data on that I want to see different names, I want to see how different sectors acted in relation to all of those things. And then it will make a discretionary call to say the math pans out this is done this in this regime. We can model it after this particular regime and we have the stats to base it on. We should expect this we check the bait on it we check the correlation on it. Does it even make sense conceptually, because the math could be saying some things it just doesn’t even make sense. Yes. Can you have a The Black Swan effect take place in any name in the market. Yes, you absolutely can. But do we really want to be buying falls on Colgate? Do we really want to be buy volatility on like a toothpaste company like there are much other plays out there that you could look to capture, structuring the book really comes down to that. So it is a little bit of regime base, it is a little bit of systematizing stuff from a quantitative standpoint, but it’s merging those two things. And with the dispersion trading, you are seeking value. And you are also structuring yourself to capture that move when it takes place. Also, and again, I just want to because I know there’s definitely some dispersion guys out there, they’re going to be like, if we talk about the structure of dispersion trading, and they’ll say, Well, you don’t trade period dispersion, just for the disclaimer, it’s not specifically pure dispersion. But we have our way of expressing what we believe is our form of dispersion trading. But even on the relative value level, you taking relative value type of trades to offset the other trade and funding the wings. That’s really the premise is being able to capture that downside convexity when the market just blows to the downside. And taking advantage of that, which it is regime dependent. A little bit is understanding the structure and what seems to make sense in some of the data.

Corey Hoffstein  56:18

So let’s talk about the third sleeve now, which was your kurtosis sleeve? Again, starting at the top, what is it? What’s sort of the opportunity that you’re looking for here?

Kris Sidial  56:26

So we have two areas where we like to express cartels is trading mainly it actually is on the short side. And I know some people are probably like, wait a second man, you literally just talked about the quant selling tails like Well, hold on, it’s much more different, we only allocate a small portion of the entire portfolio so that it can absolutely help yield the profits. But this is not our end all be all nor is this an unhedged type of play. Most people are just selling the tails systematically. They’re just like, Oh, I’m coming in, I’m just selling SPX, down 10% or whatnot. And that’s that they go away. Here’s where our system actually takes advantage of it, because we’re actually waiting for the two standard deviation move to take place. First, let’s just say well, I’ll give you an example of Tesla. Let’s say Tesla has now made a two standard deviation move on a weekly basis, we will now do is we will go in and we will analyze a particular time series, and we will run a Hurst and an ADF test. For those of you who are quant geeks, you probably know about these two tests, but what it is analyzing is a particular time series mean reverting does it have some sort of mean reversion component to it. So if we now wait till this particular asset has made that two standard deviation move, now what you realize is you get that massive spike in fogo we’ve always volatile. And the beauty of this is that the market only prices in that massive vulgar spike during the shell shock event. So after it’s down 5% Out of nowhere, it could continue going on and the focus could keep going. But it’s the shell shock that gets going that gives you the mispricing you get the most mispricing. When you get the shell shock, it happens so fast if it’s like this. And that’s when everybody’s scrambling. That’s where systems are breaking. That’s where market makers are like, oh shit, what’s going on? Like, what am I going to make the market at? That’s where everybody’s just like, What do I do? And that’s where you could actually capture the most mispricing. So what we do is we wait for that move to take place, we analyze the time series to see does it have some sort of mean reverting component. If it does now, then we actually look to price in a certain trade where we will actually look to sell the wings as the wings as inflated. If we believe this is trading too rich, there’s a little bit of proprietary data that goes into that. But our basic premise is this, if you could capture the Volga, when it makes that spike, when vol makes that spike. Sorry, I should have disclosed that we aim to only do this on one retainer. So this is only on a weekly basis. If you actually aim to trade on a one week tenor, the theta is so high that you get that data crush, even if the asset keeps going down, but the rate of selling slows down. So let’s just say if Tesla and please nobody hold me to this, this is just for an example, illustrative purposes, illustrative purposes only. This is not exact math. Don’t hold me to this. But let’s just say Tesla drops 10% Tesla drops 10% And you now price down selling puts like 10% down from there. So you’re implying a 20% overall move. That’s where your model says, Now, day two comes and instead of Tesla going down 5% It’s only down a percent. The next day was not 2%. The next day was was around 3% The next day and the next day it’s flat. What you’ll realize is you get such high data crush, that those wings that you sold For the high premium, it’s pretty gone by now. And you could cover for a pretty well profit if you’re fast on it. So it’s really aiming to take advantage of that initial shellshock and then capturing that with the data crush that takes place. What we do notice too, is we’ll get a bounce the next day or the next two days, and then you will also see that particular contract just literally lose all this premium. And we’ll exit the trade. However, there’s a big disclaimer on this thing, too. There are 567 standard deviation moves that take place from time to time. And our book is structured to capture that for the long stuff that we have. So we have risk that is hedged off essentially. And we aim to do this on a sector base. So if we have a particular name that we’re doing this on, we absolutely have long vol stuff that is going to be hedging that off. So I don’t want any college kid listening to this to think I could just jump in and start doing this. This is portfolio management. This is how you manage and run a book with interchanging things. It’s not on a trade by trade basis, where you’re saying, I like this trade. And I like this trade. All these things work together as of balancing. So if we’re losing on the Tesla thing, some of our long haul stuff may step in and may get to points of purpose where they step in, and we’re making money and that gets hedged up, so nothing is overexposed, we want to make sure we are fueling and assessing our shock levels and our slides and understanding where is our risk? What happens if the market moves down overall 7% and the Falls go up six or seven ball points or the market goes up. 5% of all points go down by five ball points, let’s just say we want to just have a good understanding of where the overall book lies and how it moves from a holistic standpoint. All these trades work together in unison, just like a seesaw.

Corey Hoffstein  1:01:53

So it’s not necessarily that, again, just stick with Tesla as the example. It’s not necessarily that you’ll play the kurtosis trade in Tesla, because you have a specific Tesla dispersion trade going. It’s not that they offset runs fairly one for one, but you have potentially other correlated trades, is that the idea?

Kris Sidial  1:02:10

Right? We can have other correlated names in the space that could be coming in and playing that. So it kind of balances that out. If those trades are not hitting for us will yield a little bit of profit on selling some of that stuff. And again, the Edge doesn’t lie and just saying well, okay, I’m just gonna sell a Tesla to standard deviation. That’s not it, you can’t just come in and just sell wings. And that goes against everything that we believe in. And that’s that’s systematic volatility suppression that we just don’t like, we want to do this in a quantitative approach. So we’re running through the numbers we’re seeing is this time series mean, reverting? Does it have some sort of mean reversion component to it? If it does, at what level? Is this a point where we could take the trade and have conviction in it? We’re waiting for a catalyst. We’re waiting to see the Volga pick up, we want the volatility to pick up, then we enter the trade. We don’t want to just wait on the sidelines and just jump in every single week and say, oh, yeah, we’re just systematically just selling puts on Apple 10 Delta puts on Apple, there’s not how you treat it. When you get the shell shock. And all the mispricing happens. And all the market makers are running and screaming and everybody’s like what’s going on? That’s where we kind of want to come in and see if we could get some mispricing on the wings.

Corey Hoffstein  1:03:24

So I’m gonna take a bit of a tangent here, but it’s related. This is the curse. By the way, when you tweet quite a bit, it means I get to go through whole your whole Twitter history and find things to call you out on. But on March 20, you tweeted, in environments of sustained volatility, the market shifts to a sense of adaptation, leading volgens to drop significantly, the velocity is not sustainable. And I think that this ties in a bit to what you’re talking about with the kurtosis shell shock. But can you talk us through what you mean by that? Because you did almost perfectly time sort of the top of the VIX there in March. So what was the Insight what was going through your head?

Kris Sidial  1:04:01

It’s really interesting because I was getting so much shit about that. So many people were just coming at me and my DMs like Oh, yada, yada, yada. And I was just like, man, alright. It’s funny, because if you go through the tweets to you’ll see, I was saying there’s only one trade I would want on my books right now. And it’s literally shortfall at that time. I just thought that the market was just completely overreacting. And it’s funny enough that our partner Sal, I remember getting on a conversation when we got a phone call. And we were talking about it and I was telling him and he was questioning me on what I thought about the particular environment. And I was explaining like, listen, volleyball appears just not sustainable. And I was seeing people on Twitter and even people in the office was just like, why is fixed down and market is down 3% or 4% or whatnot? Doesn’t make sense, like, well, it’s very simple. I just want to put all the quant stuff aside. I don’t want to talk about any mathematics. I don’t want to talk about any of that. I just want to talk about basic concepts so that people can under Stan from a conceptual level, what takes place? Because what drives markets? And we tend to overcomplicate this is one thing is human psychology. And people sit back and they’re like, why is this going up? That’s the herd. That’s the psychology behind it, you have to understand that there are buyers behind that, regardless of whether you accept it or not. So the psychology behind this is, when the market makes a move down, the overall sense of it starts to shift into a state of normalization once people start adapting to this particular condition. So like, let’s say the market makes a move 2% out every single day now for a month, you and I see the market drop down 2% We now start to pricing everything we’re doing in accordance with that, because you and I are now expecting the market to go down 2% every day. So what happens now is that we set into a period of adaptation, and the market normalizes this down 2% That’s fine is down 3% That’s fine, because you’re used to seeing down 10% days, we’re used to getting those circuit breakers. This was after we were getting those circuit breakers. And we were seeing the velocity just can’t be sustained in vx and vix the amount of selling that you would need to sustain that type of volatility. You literally start needing down like 20% SPX days to kind of sustain that. And that’s just not feasible, and it wasn’t feasible at that time. And as you and I were talking about, we knew the crux of that move was not predicated on only the Coronavirus this was a lot of negative gamma exposure out in the street. And don’t get me wrong. The catalyst was the Coronavirus if anybody says like what dropped the market in February and March it was the Coronavirus however, the velocity of the selling didn’t come from the Coronavirus. It came from all these dealers getting caught with their pants down all these firms having to liquidate. And I could say my first experience, I was on the exotics desk at that time. And I remember when my boys got the call from the heads up and usually like hedge everything, literally hedge everything. And what did that mean? That meant we were selling SPX futures. And we were also going to the open market and buying six month dated SPX puts. So we were contributing to that selling, we were buying SPX puts. So we’re contributing to the VIX spike, especially when you think about a huge bank like ourselves, where we’re moving the market just alone on that, think about all the other banks that are out there, they were much larger players out there than us. So that contributed to it. So we knew it was more so a microstructure or systemic problem than it was actually people saying like, Oh, my gosh, I’m actually selling Apple for 40% down or whatnot, people don’t really didn’t think the valuation of Apple was that. But they had to liquidate. And it goes back to what I was saying was, I know I went off on a little bit of tangent there. But the volume of vol is not sustainable. Once the market moves into this shift of normalization and adaptation, the market now starts to see down 2% days down 3% day down 4% days, it adapts to it, it’s cool, it becomes a point of normality, where we accept it for what it is. And when you had that, you’re not going to get that Volvo vaults, but you’re not going to get that velocity to the upside, because it’s not carrying the shell shock effect no more with the Tesla example, the most mispricing comes from when you initially get that first shell shock. And with that market basically accepted that we was in a freefall at that point.

Corey Hoffstein  1:08:41

So I want to go take a step back, because we’ve been in the weeds for a little while now. And I want to go back to sort of a more holistic portfolio view and ask you about risk management. You’ve got a lot of moving pieces here, not only from all the Greeks that you’re trying to manage, but the different sub strategies, the different positions. How do you think about managing risk in a book like this?

Kris Sidial  1:09:05

This is one of the reasons why I am really grateful that I spent the time that I spent at the bank because it really showed me how to manage risk being under some of those guys really taught me to look at the book from a holistic standpoint, you have to accept the fact that you have no idea what’s going to happen tomorrow, the market could just go down 30% Tomorrow, and those shocks and slide levels that you thought would never hit Well, here we are our Vega shocks. And all the Greeks that we kind of analyze on a day to day basis is super crucial. We want to make sure that we understand what pockets of the book are we exposed and what would happen if this takes place. What happens if this doesn’t take place? With a new firm, obviously, there’s technology issues and you got to get set up with certain systems or whatnot, you know, so we’ll and I have been doing our best to make sure that we adhere to Then we check the stuff every day and even double check it. But you’re not going to have the same type of software that you would at a huge bank, the systems or whatnot is super expensive, but for what it is, the understanding of what can happen and how you view and assess that, from a holistic standpoint is what we really tried to zone in on with the CRM tray. If I tell that tray to a kid in college, he was like, wow, you bought the calls for 86 cents, and you sold them for $35, you made an absolute killing? Well, yes, if you look at it that way, but we aren’t concerned about the individual moves like that, that serves as a hedge to other parts of the book. There’s certain Vega pockets that we want to make sure that we’re covering, are we to negative delta at this particular tenor? How are we looking for our expiration next Friday? are we carrying too much negative delta for next Friday? Is there an event that’s going to expose us to that? What about the Friday after? What about this Tuesday? What would happen here to our vague or where’s our Gamma exposure? Like is that balance? So that’s really the key is understanding what are the weights of the book? And what pockets are the book exposed in? What could potentially cause harm to that, and really getting a true analysis of your var, that’s really the key for us, we predicate our risk on bar and understanding where our shocks are. And our slides are, I know, it sounds like very repetitive. But that matters to us. That matters to us more than let’s just say we’re carrying along Apple put or a bunch of long Apple puts overnight that. And you tell us that Apple goes down 3% or 4%, or whatnot, that some people will be like, well, how does that impact you? And it could impact us? Is it going to take the overall market with us? Is it going to just be on that name? Is it going to take that sector, maybe we’re short, a little extra vague on that sector. So it’s just viewing an understanding from a holistic standpoint of running all these things together? Or it’s like one big balancing act. And you need to focus on the tenor, and the Vega and the gamma exposure for those particular pockets of the book.

Corey Hoffstein  1:12:07

Chris, last question of the podcast for you. It’s the same question. I’ve been asking everyone, because 2020 has been a real upside down year for most people. And so my question for you is, hopefully with a little bit of optimism, what are you most excited about going forward? And I know starting a new firm here, you’ve got quite a bit of things to look forward to. But what is it that over the next coming months to a year, you are most excited about?

Kris Sidial  1:12:32

I’m actually all in on this. It’s really exciting, starting a new firm and working with our investors and hearing what they have to say and even performing for them. That’s one thing that’s really exciting to me is being able to wake up every morning and say like, Oh, we’re managing this guy’s money. And we kind of want to give him the homerun, because we get the homerun hit too. That’s really exciting working with the guys that I work with such a smart team. And I know it may sound cliche, but this is literally what I do. This is my passion. And in my pinned tweet on Twitter, I say like, this is the MBA for me, this is no other place I would rather be than trading derivatives. So I’m excited. I’m excited to see what the future has for my partners and I and I’m excited to see what new investors we come across and their way of viewing risks the same way how we do and capturing opportunities in the market. I think this new venture is something really special. I think in a few years, it’s going to turn into something truly, truly special. And I’m excited to see what that takes place. Outside of that. I’m looking forward to going back to the gym for sure. It’s going to be something well gyms in New York open that up, but it’s just really hard to get a spot in the gym. It’s like that’s been a nightmare just working out in a basement. But I think things definitely look promising and I’m looking forward to seeing what takes place.

Corey Hoffstein  1:13:48

Well, congratulations on getting the new firm off the ground. I wish you the best of luck. Thanks for coming on. I know this has been a super educational chat for me and a super interesting one. So thank you for your time. Thank you