This week, we’re adding another stamp to our Derivative passport and traveling to Zurich, Switzerland, as we talk to the Head of Systematic Solutions and Portfolio Construction at Sygnum Bank’s Asset Management, Artur Sepp @ArturSepp — who specializes in crypto-assets and decentralized finance. Artur has led quantitative research at systematic trend-following hedge fund Quantica Capital, focusing on data-driven investment strategies and asset allocation in global managed futures.
In this episode, we dig into his background to discover what it’s like being a quant (not as much like TNG character Data as Jeff would like…) and discuss; coding, mathematical modeling, and why statistics matter (testing simple, yet complicated models), the framework of trend following (be sure to download our trend-following guide here), pros and cons of risk premia strategies, quants trying to figure out the short data sets in Crypto and more! Plus, find out where Artur would invest 1K, 1 MM, and 100MM in Crypto.
About Artur Sepp
Artur is committed to connecting financial applications with science and technology. His expertise covers quantitative investing and asset allocation, modeling of financial markets and instruments, statistical and Machine Learning methods, modern computational and programming tools. Artur has more than 16 years of professional experience dedicated to leading roles at top quant teams in New York, London, and Zurich.
Artur has a Ph.D. in Mathematical Statistics from University of Tartu, an MSc in Industrial Engineering and Management Sciences from Northwestern University, and a BA cum laude in Mathematical Economics from Tallinn University of Technology. He is the author and co-author of several research articles on quantitative finance published in key journals. He is known for his contributions to stochastic volatility and credit risk modeling with an H-index of 16. He is also a member of the editorial board of the Journal of Computational Finance. He loves quality time with his family and playing chess with his son. He also enjoys reading, martial arts, and water and mountain sports.
Follow Artur on Twitter at @ArturSepp
Check out the complete Transcript from this weeks podcast below:
Trend Following, Signal Deterioration, & Crypto Modelling With Quant Artur Sepp
Jeff Malec 00:07
Welcome to the derivative by our RCM Alternatives, where we dive into what makes alternative investments go analyze the strategies of unique hedge fund managers and chat with interesting guests from across the investment world. Happy birthday to me, well tomorrow, but if can’t watch yourself happy birthday, what’s the point of even having a podcast? Speaking of we’ve got some good pods coming in May will be written with resolve about return stacking. Talking prop trading involves surfaces with Nolan Smith, and getting into wine and entrepreneurship with Anthony Zeng, so make sure to subscribe and check out those upcoming shows. This pod was super interesting digging into the quirky quant details with Artur set, head of systematic solutions and portfolio construction at Signum bank in Zurich. We chat about his days at trend falling from Quantica and research into quicker and quicker information flow affecting returns. His work on volatility modeling and why the data and testing and quant approach and crypto is both infuriating and fascinating all at once. Send it This episode is brought to you by RCM outsourced trading group where they’re 24. Six traders do Colin’s spreadsheet FTP director exchange algos and more order types to help firms be cost efficient and not have to staff their own trade desk. Check it out under the Services slash trading firms slash 24 hour desk on the main navigation at our CM alternatives.com. Now back to the show. All right, everyone. We’re here with Artur Sepp, Live from Switzerland. What part of Switzerland Artur?
Artur Sepp 01:46
Hi, everyone. I’m based in Zurich,
Jeff Malec 01:49
Zurich. All right. And I got to ask What’s this little painting or drawing over your left shoulder there?
Artur Sepp 01:57
Well, it says Samson is from Chicago. It’s a favorite painting of my wife.
Jeff Malec 02:02
Perfect. You’re saving up for debate, the real one.
Artur Sepp 02:09
Maybe tokenized tokenized. chef
Jeff Malec 02:16
one day. So let’s start with telling us just a little bit of what it’s like to be a quant? I think most people think of them as sort of the data character from Star Trek. Not sure if you’re a Star Trek fan. But it seems like you’re not all Android there. So what’s what’s the quiet life? Like?
Artur Sepp 02:35
It was a hard question to answer, I think. Really to, for me, it’s more lifestyle, right? Relationships, too much of my profession, right? I’m one by profession. What it means is that I’m tempted to look at scenes in a broader scale, it’s, for me, it’s more interesting the to build up a system of how and why things happen. Right? And therefore, this idealism is obstruction. It’s what I like what I like in within markets. I’m not married, I charge too much, per se, it is just part of part of my profession, or part of what I can deliver working in a larger teams are some people they tend to be more so as a discretionary or more intuitive. Yeah. And here, we try stick chamado for me. I think the key will be in a quant is really to have a systematic way of looking at scenes. And to be able to answer why. question why?
Jeff Malec 04:09
It seems just the modernized version of the word engineering. You’re just a
Artur Sepp 04:14
yes. I actually for me, it’s the same way. Yeah, I actually I have four degree in Industrial Engineering, Comoros and university. So I studied the system several topics and and for me, it’s always it’s it’s indeed it’s great in a system system that can work through different cycles that can work through a process different data sources, different parameters and things and it’s produced some utility.
Jeff Malec 04:48
Right? And I think that’s the main engineering carryover is kind of to make it last to write for more than one purpose to exist in more than one environment.
Artur Sepp 04:59
Exactly. Yes. With these with this profession, what I like it’s almost I think I notice all of this is true, I changed a few few few firms, few companies, but more or less, what I do is the same, it has different things between, say crypto volatility, CTS, but but more or less, it’s almost the same, not almost the same, but it’s can be attacked, approach this the same set of tools and see a set of approaches.
Jeff Malec 05:37
And have you coded in the same language that whole time?
Artur Sepp 05:41
Well, that’s a good question actually changed. So since when I just started early 2000s, it was C++ was predominant. I didn’t see possibility to deal with this. C++. It’s almost like probably a Latin language, right? Because it has everything. But if you process it, you understand. I think it’s more about architecture, how makes it scalable? What is important? And right now, of course, most of time now I go with Python. It’s simpler. Right? But the idea, I think, when we talk about programming, ability to put mathematical formulas and data into code is a skill that is does not depend on language, something that you you have to learn, right, some old ones, especially the ones that want to work in industry in asset management. But it’s say, language should not depend on language you choose.
Jeff Malec 06:52
Yeah. And what came first for you the the interest in the statistics and probabilities and math or the coding skill?
Artur Sepp 07:01
Actually, so so it’s a good point. Actually, as an undergraduate, I studied finance and economics was fairly it was like, very quantitative, quantitative, right. But then I end we added modern portfolio theory like Markowitz and Black Scholes. And at that time, I started to actually, I was very curious, because those were mathematical models that you could implement in that time in Excel and VBA. But then over time, I saw that it’s very interesting. It’s why I went to graduate program in statistics, but in between I got after that, I got PhD and I got three master’s degrees. And yes, indeed, through all time, I did coding, I think it’s important as say, more people with applied a background theory always. Mathematics is one way you you make a hypothesis, you can create nice theories, but then they to to apply since in practice, you need to do some experiments and experiment experiments. It’s using data. And like driving some outputs, and therefore I think programming skills are important. And everyone nowadays, everyone who plans to to get some sort of science degree for fruit take enough time to learn this?
Jeff Malec 08:43
Yeah, it seems to me right, a bit almost at a tipping point, right? Where you have some of these no code platforms and things where the code can kind of create itself, especially like you said, for some of these math equations, that seems like a simple plugin for lack of a better term, right? Are we going to get to a point eventually, where the coding is less important, and the more important part is knowing how to apply and do the different testing and the different models on it?
Artur Sepp 09:11
So it’s a valid point, I think, yes or no. Nowadays, what I what I see in candidates like say, the one that I interview, most of especially this data science, guys, they know how to use particular say Python package right as cyclone or 10s of TensorFlow. What I think they’re missing this understanding of why Actually, why and under what conditions you expect something to York, what are the miracle limitations, right, what the say convergence, how would you analyze the convergence of your algorithm so For, and especially, also in, say in production, right, I can do something for experiment. I can take plug and play solution. But usually it’s always it’s very limited. It’s limited almost. It’s limited to work in 95% of cases. Right? All this is is Mr. Insane. This mathematics is, is a complicated, fairly complicated organisms. Yes, it’s very simple to use for some, say, Nice problems. But the ones that we have in finance, you always almost hit that 5% that you have to think yourself a little bit how to tweak it.
Jeff Malec 10:46
With that 5% can put you out of business, it’s important. Moving on, can’t have you on and not talk about trend, given what’s going on in the world right now and given your time at Quantica. So part of me feels bad for you. Right? You left Quantico in August of 21, which is right around the time trend started to go vertical? Do you look back and say, oops, I shouldn’t have left or in kick yourself for a target?
Artur Sepp 11:18
Oh, good. Two points. So So also for like CTAs in particular trend for when cities cannot be tight, right. So don’t try, you can enter you can leave for you can enter them all the time. Like, you cannot say oh, yes, I left at the time. But I actually so we, of course, when I exited this, before that election last year, what was interesting last year was very similar to this year. So almost also was short trend, like racy rows, right? Correction rates. So all cities will short bonds, long commodities, agricultural is especially in flight to shake witches. But then around May it’s all winter. It’s all corrected. I didn’t reverse. So I wouldn’t say that. I mean, like almost say I can’t say I left that local. Peak, Gannett. In the second point, I see like half my own portfolio, more or less CCT based. And so I still participate in that I like I think, dreadful for me, it’s one of the best systems, systematic strategies, it fits my mentality into I like, say, in terms of diversification in terms of return potential. And I’ll say skewness. Yeah, it’s one of the best stuff is out there. I think for me, there is no way I can exit the site.
Jeff Malec 13:10
Well, now, it seems you have the best of both worlds, like you’re not dependent on it for your paycheck and for your investments. Now you can have some diversity in your in your exposures. Right. So what what was some of the most interesting trend research you did there? You were head of research, right? Yes, yes. You got any good, good stories and some of the cool stuff you did?
Artur Sepp 13:34
Yes, it’s definitely it’s interesting. As I said, a CTS is an interesting business, because you have data, you come back to like, yeah, tons and tons. For example, for crypto, right. You have most cases is like two or three years of data. And here we have data seen say even tradable data for commodities since 1960s. Right? In my research, one of the interesting parts, and also in line with our fears is to see the deterioration of going forward since a 70s 80s 90s. And how, what are the implications? So in say, in 70s 80s, even you had the transaction cost very high, you could run a short term trend following system meaning that your holding period on average would be maybe two weeks rather than one month. But if you had stable performance it was it’s almost was like an alpha strategy. It traded video is traded. Turnover was high. Transaction costs were high, but the statistical nature of markets While you had this sale feed in cycles, I, they they generated performances, depends of specification, but say between two on CD sharp, right up to mid 90s, then of course, professional cities started, the bigger guys, they started to enter the market around 90s, it had bigger players, then of course, it started to deteriorate. And the way to respond is, of course, to increase the rent the scale, like so your holding period would have to be around one month, increase your holding period. Exactly, yeah, increase in some way. It’s increasing the decay rate of your signal. So the decay, you always take some sort of a loop back up. So what we can use, but you always depend on some history of, say, one, one week, ideally would be one week, they can adapt fast. But if these conditions resist you, you would adapt fast.
Jeff Malec 16:08
That’s real quick, if you’re thinking of it in like terms of bars, right? So if I’m trading daily bars, and I the signal deteriorates after 500 bars or something, if I’m trading monthly bars, that’s 500 months, I’ve greatly expanded the the time till deterioration
Artur Sepp 16:29
into is also good point. So with bars, you can think also how bars like say, week over week, right? Ideal for trend food, if bars kind of increase –
Jeff Malec 16:44
right, you can go up lower lows – right?
Artur Sepp 16:46
Yes, or doubt or right. Yeah. And what happens since 2000, in especially over the last decade, market change, right? You have like, say, market takes elevator down, and then go steps up. Right? What? So you got the negative and then if it goes too much up, then it kind of again, it’s correct, corrected. And this environment is more like mean reversion right? You have mean reversion. And to avoid that on shorter scales on say, one week, right? So if one week is positive next week is most likely should be needed. So across almost all asset classes. And these are difficult condition for train forward. Because what you want is market resistance here, the statistical resistancy called positive autocorrelation. So this was one part that I found interesting. What was maybe unusual or
Jeff Malec 17:50
real quick on that, did you? Did you get to a reason of why that changed? Was it big, right? Some people say the space got too big, there was too many assets chasing too few contracts. Others have argued against that saying that the stats don’t really show like the price action, you could say, but the volume stats don’t really show it.
Artur Sepp 18:10
Yes, well, I’m a mathematician. So, I cannot serve in mathematical terms. The nature of market changed before markets, it should be more like there was more of this positive outlook valuation what would they call probably it was slow propagation of news right? It would take a time that market would converge to equilibrium through several steps through several weeks or several days, several weeks. And therefore by say, kind of discovery early discovery you would be able still to participate. Now this especially overpass the case right you it’s more like this kind of mean reversion where the news propagates very fast market corrects very fast and then the rest you have white kind of this positive trend, but it’s not because it’s positive right there is say QE programs or people get them into a quickest discount of not something that you want
Jeff Malec 19:19
some resistance it comes back starts to become more binary just right there’s some new shifts that just shifts the market from here to here and then it’s exactly I’m being on here so yeah, that’s interesting that right around the time the internet obviously then social media then computers so right, everything was just getting faster in terms of the the market moving news propagating high frequency trading firms. So for you not because trend following got too big, but rather the rest of the players got too much information too for
Artur Sepp 19:52
efficiency too fast, efficient trading, especially in commodity markets in the US informed traders right there. will be bigger trading colleges that could adjust very fast, much faster than say, traditionally to be, say more clusters of smaller traders that would take longer time to adjust. Now this you, you have a few concentrated players that could move very fast in a form in a way that is not readable by by, like CTAs.
Jeff Malec 20:27
But so then how do you explain the recent performance and how they keep going? Right? So, because,
Artur Sepp 20:34
again, it’s unattractive, right? It’s waited for a long time and trends were very good. If you it’s a perfect environment, because I think great 10 year use T rate it was last August, it was 1.2. And then it went almost like this straight line to now we have 2.7 Right? Yeah, so it was 1.5. Like it’s really, and correction didn’t last more than one month. So it’s a perfect environment where you you get like, like, increase increase, this is exactly what you want for a 10 fold, increase shorts, shorts and goes your way. By the time you can move your style. Exactly. Yeah. And also the soil was very good. It’s some kind of it was really good combination. Also oil and thermal. So I think it was a three three least recent meetup October, right, we were under 60. And end of February it was one sorted. And actually, in CTS I think we were alone, I would say November December you didn’t wait until once you’re right and after the correction I think actually must be most of the guys must be flat. It was also good in terms of say portfolio diversification when the correction in oil happened, right? Raise even top so actually it was things where
Jeff Malec 22:06
we do you have any thoughts I’ve long said on here that a lot of trend followers went long bias added more equity beta, right to survive because it was such a long period of nothingness that they had to do something to survive. And now those programs are kind of underperforming here. Were you tempted in your research to say hey, if we just made long bias it would work a lot better.
Artur Sepp 22:33
Well, so there’s a part of that I know from from safe from other sources, I can tell you so part of research what’s also important framework I developed was Korea. It’s entitled why it’s important. So for futures Korea say for bones is very important. Carry carry you the ones that if your return from backwardation and contango, so when commodities in backwardation in misery economic benefits of holding the asset. So, for example, for bonds, if it’s and also commodities are always excess returns. So if I buy a 10 year treasury bond on the margin, I get the coupon that my car is rate current and I get the coupon and I pay for dinner. Yeah, for me, it’s beneficial funding rate is zero, right. And I buy 10 year coupon at 1%. I get the second important companies this roll down, because I’m constantly changing my contract to 10 year future. And if slopes are in rising, right if market expects rates to rise, but actually nothing happens, right? Say in one year 10 year bond will be at point nine, right? So I get 10 basis points multiplied by duration.
Jeff Malec 24:06
So, but that’s what was happening for the past 30 years. There was always expectation of higher and it never came up.
Artur Sepp 24:13
But actually, this is surprising part. A lot of people that the people, like you have to understand fixed income, actually with negative rates, German bonds were the best investment in your CTA portfolio.
Jeff Malec 24:28
Yeah, isn’t it?
Artur Sepp 24:32
Yes, even before that, so especially say 10 Year 10. Year was or five year is NTP excess servitor right. And if your 14 rate is minus seven to five, but your coupon is like 50 basis points, you get the spread of 25 basis points, right. Plus if the if Tom structure, right so you bought it that’s a minor As at minus 50, but then it moves to minus 75. Right, you get this duration is declined. More neg, Yorkshire and plus, because we are all almost everything is on this basis, right? Volatility was very low. So the company and say carry company warns of fraud dated say both were more than one. So Sharpe ratio, if I just buy bonds at negative rate, I hold my expected return this sharper one. On the risk adjusted
Jeff Malec 25:35
there’s a lot a lot of money being spent on stuff more fancy than just buying Yes.
Artur Sepp 25:39
It means also commodity so similar in commodities, a lot of stuff that’s a right now, right, it’s always some sort of deterioration, right, right now, short term supply, needless to say, is affected, right. So short term, people expect higher prices. But lawyers are lawyers. So we have backwardation, right. Yeah. What actually also most of the time is actually, if you buy now, say if nothing happens, right? So you get this car company. And this is for many commodities. It’s always economic thinking things this that all producers want this year, higher prices, they would like supplies the market. But it’s never why this is not linear. In evil, but in theory, so carry also in commodities, it’s important company like the come. And then so what brings us to trend following is that overtime say in say with the sages, if you make a breakdown of your p&l, how much you actually God because prices changed, or how much you got from just getting the correct component. Right that that since didn’t change into just get your your coupon or your accommodation in commodities, actually 10 20% in the early 70s 80s 90s. Right now over the past decade, especially last year, it came to 40 50%. I’d say a lot prior to the last year,
Jeff Malec 27:30
so seven 20% of the profits were from carry and 90s and 2000s 80% of the profits from carry
Artur Sepp 27:40
no no. Vice. Montes work worth 20%. So okay, well, mine is worth 22,000 sorties 2000 10s 40%, I got it. And this is the reason exactly as you said, two companies that holding periods increased at end, may maybe not many cities even realize that you actually you benefited a lot from bike paths. 10 years, most people were on bonds. And bonds didn’t. Okay, there was, of course, we say benefited from fallen rates, but it’s not as big as say, benefiting from this carry effects like moreso
Jeff Malec 28:27
benefiting from poor estimates on what the future would be on that rage. Exactly. And so what do you make? Have you seen Roy Niederhoffer research on that? If you flip the chart, right, if bonds go off on a 30 year rising interest rates because of this carry trend falling might be flat to negative, right? It’s not necessarily going to make the same money. Have you seen his piece?
Artur Sepp 28:56
No, but I see is I see the reason and it will in my actually why I’m positive now going forward. I as I said I did a lot of long term studies in 70s, late 70s early 80s Were the best time for trend forward because they were short they were both short equities. And once and the reason is right now actually a carry effect is not very strong because don’t structure a flat it’s actually the opposite if for example so if I have say now slopes are negative I’m actually benefiting have been short. Yeah. So but being said that is always you have to be careful, right the restraint phone with say. I prefer to keep with us curiosities and Kermit carries a second In order effect, right, but it’s important, it’s important to maybe adjust position. So understand what are saying drivers of returns or to his point that it cost? It would cause when when, say you short long term bonds, and your current rate is still very small, right? Yeah, you would lose on this coupon. Carry, right. There is not much of robed on that right now. term structure is flat.
Jeff Malec 30:37
Yeah, which we could see in the next five years or something, maybe short terms at 2%. And longer terms at 10%. or something. Yeah. But now, right. It’s we’re basically flat, or twos or above. Yeah.
Artur Sepp 30:50
Because bonds or or futures or excess returns. So if say, short term rate goes to whatever 5% and 30 year bond yields you 5%. In term structure, it’s flat. My carry zero, right. Yeah,
Jeff Malec 31:04
yeah. So then it’s just the price action?
Artur Sepp 31:07
Yes. Yeah. I’m not like, that’s the difference that I’m not shorting, say cash, cash bonds in futures, you always on, like, excess funds.
Jeff Malec 31:21
And so part of it was part of your leaving Quantica that there wasn’t enough to research and trend. Did you get bored with the trend research? Right? It seems like there’s only so many ways to skin the cat, you can do a bunch of moving averages, you can put a bunch of filters on but there’s not like a blue ocean of new things to research there. And is it right or wrong?
Artur Sepp 31:43
Well, I mean, I think city has survived, right? Since it’s probably the oldest construct theory out there. A lot of equity like this kind of mean reversion. He didn’t survive. Right. Yeah. And I think partly is because it’s very conservative. It says, but there is a lot of things to do some part I mentioned also some what I think most interesting apart of a traditional price based trend following was sentiment that data and we so sentiment, you know that if you’re that some people are applied for Stokes, what I found interesting in say in my my application that you can also trade say global futures like OROSEI US based futures, equity bonds, commodities, based on useful and useful in my opinion, so since like, no question, it’s it has been a new world since Corona crisis. Reasons that traditional models, they need to take some time. So want models, you need to always you need to absorb the phenomena, you need to say train, you need to think how it translates this phenomena into actionable ideas, how I build my model high back back tested and how it puts in production. And so of course, it’s takes time with sentiment, what we absorb, intuitively say, each news, economic news, for example, unemployment numbers, if it’s, you expect that in certain regimes. A bad number is a good number some sense? Like right now, I would say bad number would mean that the Fed is on pause. So you would benefit before crisis say no one knew the extent right, how deep the economy can contract. And therefore everyone would expect that that number is a bad number. Next time it will be even worse. In this type of system, where you have different news, right, so imagine you have different sentiment you can track say news related to unemployment, news related to COVID to oil supply, to wars, to everything and you can create the continuous time series I would say. Maybe you can normalize so it would almost like us course, right? So negative score would mean that this news feed right now it’s very negative. Yeah, then you you study impact. So a little bit of machine learning. We try to select factors that actually drive right now the market Now everything that relates to fit now to will drive the market anything relates to war. Right? And
Jeff Malec 35:12
in the trick there is it went, how do you know when it switches? Right?
Artur Sepp 35:16
So it’s a short term, it’s a short term system, where you constantly update your your, your SE model, maybe week, every month, you just try to select factors that matter most. And also the loaders. This is a perfect what I like it’s, it’s a statistics, it’s first of all, for me, it’s a high frequency. It’s not high frequency, high turnover, high turnover strategy. It has very good defensive profile. Right? It’s almost like being long volatility is very sensitive to transaction costs. But what I found interesting is, for me some sort of print food, or news or sentiment, and it can be made to your
Jeff Malec 36:07
writing basically, long and short, the same piece of news at different environments. Yes.
Artur Sepp 36:11
And also what what people were calling now costume that don’t become popular. But yes, I come up with some more Dorothy’s into that I like it.
Jeff Malec 36:26
And what do you make, I can’t remember the authors of the paper. But there’s a paper about a year or two ago, talking about as soon as a factor is identified, it actually ceases to be a factor. Right? Like the very fact that you’ve identified it and put it into the market. Other players have done the same work and identified it put it in the market, and it ceases to be, you know, kind of a value to drive the the alpha that you thought it could drive. Have you seen that in real in real practice?
Artur Sepp 36:57
Unfortunately, not the probably in my case, I can say it’s always question is always what kind of camera right so. So say. So most of academic research literature, especially the fact that it’s very simplistic ways to find some sort of whatever fundamental or some sort of behavioral factor, you sort of build your rankings and then you put like, some kind of Doc test, right? Whereas we go save for the end is of course, I mean, first of all, is obviously if there is something that you’ve come up, I’d say okay, it’s academia. You will tell you we expect that people profit if it has value is natural, this will disappear because yeah, people would profit in more see in our systematic trading, I mean, everyone knows what cities right say for example, cities, but there are so many different ways. You cannot actually tell that is a risk premia is a dynamic strategy. That is more say the values from rules from applying the rules and from harvesting the betta. So in almost it’s more like with sticking to the values from Yes, enduring.
Jeff Malec 38:28
So you mentioned risk premia you were at Julius Baer doing risk premia, right? Yes. So dish, the dirt for a son, the pros and cons of risk premia strategies, to me sometimes a little too simplistic, and like we just talked about, if everyone rushes into one on some bank platform, it’s likely to stop working. What do you thought
Artur Sepp 38:50
restream is because we have for say fundamental factors like probably valuation will have structural like say short volatility, that say is more demand imbalances. In my opinion, you have to be very clever how you implemented it, it’s it’s a strategy for good times. My opinion, yeah, you can build the wealth diversify a portfolio of different risk premia. What is good probably risk premia you have all this expectation right? Always say like simple cash and carrier arbitrage right you buy or short the future dependent vertonung structure is into buy into sales support. Of course problem with endorphins. So whiskery strategists, always say risk premia strategies, most of them you make money 2% of the times at night, right? The problem is that those remaining 10%, they actually can invalidate any return that you make. So therefore, I believe that a lot of this stuff exists, like say short volatility is because it’s difficult to overtime, right? You have to be data. So we also the times, right that in their careers, it exists.
Jeff Malec 40:29
But they’re like terminal breakeven, you’re saying basically, if you access it, make sure you only do it for a certain period of time, but then your timing, which is difficult, but Sure, but there’s surely like positive skew, risk premia strategies or no, or people don’t select those because they lose, lose, lose, lose and then make money. Right is there. Can I go on a platform and get the momentum risk premia are the trend premium? Right?
Artur Sepp 40:59
I think I think for me, it’s more like say, a classic trend phone is a dynamic strategy. So it’s actually is making you trying to replicate this data profile that works in certain situations. risk premia for me, it’s almost always like a some sort of a term structure right when the implied volatilities if there is a normal Pierotti of calmness, but you still you expect something bad to happen. So you actually baked in that these things are not going to have right and you will get your coupon like your excess return. Right. So to your point, it’s so and maybe inequities. If you say, Okay, there’s a value, but the problem is that it’s not something that you have to be sufficiently one period of time, right? If you’re saying okay, if strategies has positive skewness, it means it must realize over short periods of times that in the value factor so you have like a decay. And suddenly you can have a really sharp return. Most of the risk premia is naturally short skewness
Jeff Malec 42:22
Okay, interesting. Yeah, and to me, it hasn’t really built that hasn’t fulfilled its promise that was coming out a few years ago, like oh, you’re gonna be able to do anything and pull some alpha off the off the shelf so to speak. When it’s by definition, not really Alpha it’s, it’s some sort of beta, right?
Artur Sepp 42:42
Yes, kind of delayed.
Jeff Malec 42:51
So let’s move on to vol trading. You had your delta hedging paper way back on. We’ve had some debates on this podcast between different episodes of some people, right, who are basically saying the whole the gamma the delta hedging, that’s what the whole game is in the s&p. And if you’re not cued into where those levels are from the dealers you’re going to you know, they’re going to do so well and other guys saying, yes, it’s a factor but it’s very small. Right? Maybe it’s moving the s&p points at certain thing but right it’s not causing it to move 50 handles or something. So take us through what you found in your paper and what your thoughts are on the whole dynamic especially currently as options volume has exploded and whatnot
Artur Sepp 43:39
well, so I tell you my my background so with Volvo so first I was working for this home made markets in emerging market equities. So in that it’s it’s OTC big size in liquid, my liquid underlyings. And where that idea came from the EU really try to look at your risk and how much it would cost you to hedge. So that origin of that data. Now, if and of course flows or like on OTC market flows are important, but there are one way it’s only as a dealer, the price and you can always say you always who can say put your spreads high. And but moreover to the point yes, your position creates feedback books and they are very strong if you and most of the time. Yes, it depends on how clients pay Position center how that definitely would create very strong feedback effect going to s&p I doubt I think its market is too deep and this more position of market overall that matters rather than position of several dealers. Like for example, what we had in February 2018 When Walmart didn’t Yeah, I just it was Mark It was everyone was short Volvo. So I don’t know what did the dealer
Jeff Malec 45:42
Yeah, they Well, you could argue the s&p didn’t really move all that much even though vol right. So,
Artur Sepp 45:48
yes, it was position of market. Well, some people believe in this labels. For me, I think I thought this was more like getting divorce are important for can for say, especially on a loan side, like most of for example, or traditionally, especially private banks, where clients are typically short volatility so they sales through structured products, choose a bank loan dated offers or return to some sort of kind of coupon rife problem. But it’s almost everywhere, even though you can buy it’s cheaper than you would say go in listed markets. You You are long volatility and you have this current decay. And you need something bad to happen in markets that you need that floor. So to build on volatility, you somehow you need to be attached to a good flow of cheap, relatively low current.
Jeff Malec 47:09
Yeah, your clients blow that short. The other says
Artur Sepp 47:13
you cannot just buy a market like a for example, I would not assume that you would be able to profit systematically from being lowness and the options unless you incorporate some sort of positive information.
Jeff Malec 47:30
In what you’re Vic’s blow up paper as well. What was what was the conclusion there on on those products? We’re having a we have involved shares who just launched the new vix ETFs on either the week after or the week before you, but what are your thoughts on those products? Are they useful tools? Are they dangerous?
Artur Sepp 47:51
I think they’re very dangerous, especially for I think for retail, I mean, professional player they would implement anyway, through this kind of strong structure. They would not be of course, it’s how they would have you you have to manage your margin code at the margins. But here it was product that was just Wipeout. Right. It’s just wipeout of equity. And I think, yes, people discuss it was a feedback object. Because it closed, I think the reason was that it closed the end of the day, right. And price declined and dealers like well known Swiss banks, they had to liquidate their loan, their short position in a 15 minute period when markets like Canada was close futures was open. And that really created some some crazy liquidity effect that product blog. Right. And I think it’s so good. Statistically, I think it was high convexity. We’re at the s&p drop like minus four minus 5% and leaks almost double
Jeff Malec 49:16
Yeah. Right because of those flow effects and because in the prospectus it said they’d have to exit right if it was below a certain level that was seemed to be the biggest mistake but at the same time that was they wanted to stay solvent right. So they weren’t there that language in there so they had an out instead of you know, going bankrupt. And then what have you done any quant any modeling on the VIX itself? What do you see as the challenges on like, doing quant work on the VIX. It seems like its own animal there.
Artur Sepp 49:48
Definitely. I did some conduit different empirical work. I think the most interesting aspect is relationship between puts SNP puts skew and VIX, right? Yeah. And sort of vix calls call skew, right? So it’s more or less the same function. SNP tanks. Right. You can be say one listen to puts, but also long weeks calls. So this is interesting. Another interesting the fact is, so this is more like a skew and
Jeff Malec 50:30
that ratio should be the same. Ish, right? You’re saying it gets dislocated against?
Artur Sepp 50:36
Yes, typically, as a second taller premier Vic’s. Deixe skewness is steeper than say two. That opens up say a party is I’d say arbitrage right? You would be shown week’s call center. Last week’s foods, SNP foods. Yeah.
Jeff Malec 50:58
Except Feb. 18. I would have taken you to the cleaner excuse probably there because there’s things that can happen where the VIX moves without the s&p movement. Yes.
Artur Sepp 51:11
I love that one. So, this is more like yes, this kind of skewness another one is jump structure. That is like the most interesting counterintuitive. So when Tom structure is in contango, so you should sail. Yeah, because when it’s actually in backwardation, right, you should buy. But you really get in yours when VIX is above short. So this creates some sort of interesting strategies where the VIX is above shorty, you would buy it buy, even though it’s not cheap. Yeah, that’s a is the expectation. It’s again, if not the carry based, sort of for you by the future because cash is above the futures. Exactly. Yes. Even though it says nothing. Yeah, nothing happens, your own volatility. And you get the car, right. This is ideal. Few few times in PA but it’s, it’s again, it’s not tradable. It’s interesting. But it’s very hard. Because this really looking at a handful of events that where it would work. And it’s all the time it’s so much conditional on the rebalancing, what, what future expiry you got? Yeah, this is definitely interesting. I think. And I know that some people they they do basic strategies, were looking at the term structure of beaks. You would say, trait? One way or another this SNP, meeting this anti s&p options, beads? And probably the exceptions.
Jeff Malec 53:08
And then do you tie in a little bit of machine learning? Like if there’s so few of those big spikes? Right, like how do you do any valuable back test or research of right? Do you have enough data on those big spikes to make it statistically significant? Your research?
Artur Sepp 53:28
No, the point that you can make. It’s really like Yeah, I saw in fact, so of this kind of floodwater is really you make money two or three points, right? And therefore, it’s always always this strategy, you you you need to look at robustness right you somehow if you want to do something like that, as a stand alone, it will not work. It will be part of more of a broad, some kind of how they’re called. Yeah, actually
Jeff Malec 54:11
are just a long equity. Yeah. Okay, let’s move on finally, to your new gig at Signum, my saying that correct signum, yes, signal, signum. So tell us what you’re doing there, why you joined in other goods
Artur Sepp 54:35
fell so I actually part of my decision was a new book. So I have a bookshelf and there is some mathematical methods, extracted returns. So risk premia, active portfolio management and then there is a new one that is blockchain and distributed ledger. That yourself shoot is not. Unfortunately not mine. Not yet at least, it’s Alex Lipton a he, he is. He was previously he he was global head of quants at Banco at Merrill Lynch and Bank of America Merrill Lynch. And we got to he, he was manager of my managers, but we had still very good relationships. And so he moved to blockchain, like few years back and then I was following here in Zurich, his publications. Last year, we decided to work start to work more closely like defy application. So automated market makers, stuff like that. And so I kind of got interested I, I still have, say, my reservation about where the source is in Go, but it’s interesting is developing fast. And when I saw opportunity at Signum, I already had some some some feet in this area, I said, this is it, I should go. And their dirt basement, zero case, zero case, digital bank, we do a lot of scenes, like tokenization. Custody, but also sort of traditional asset management.
Jeff Malec 56:28
So digital banks with all crypto has some Fiat has good old fashioned francs and dollars as well.
Artur Sepp 56:40
Like you can hold cash, but all activities are devoted to crypto. Got it, especially on the investment side.
Jeff Malec 56:51
And so we just talked about the craziness of modeling VIX. Now take us through the craziness of doing some quant modeling on crypto.
Artur Sepp 57:00
Yes, that’s that’s for? Sure. Yeah, of course, is that I cannot share my screen. But I tell you one in one, it’s very interesting. A piece of figure that I want to show to everyone. Part of my role. I created a database of all tokens, or protocol tokens, or coins that were traded over time. And
Jeff Malec 57:35
traded anywhere, anyplace.
Artur Sepp 57:37
Anywhere. Yes. So we’ve worked with several data providers. So they all have this data. It’s just a lot of stuff change over time. You have different themes, different tickers, but I did work and take off more than 5000 different stuff that traded. Moreover, the stuff cut volumes, that word insolvent No, not that in market cap 5002 and a half still active. Active in crypto means that there are still some activities, the protocol can be dead, right? So most of the time it goes up it spikes then it goes down to say whatever 000 Samsung, but because in crypto per se there are no listing requirements. So since it says that we can be Jarrah so in my data set, there are 5000 sort of debt stuff in five. So 5000 total, however, with it’s kind of it’s just disappeared, it probably was not economical. To keep track of them. Tuna 5000 are still even though some of them don’t read frequency. Then what I did for each of them during the period that they were live, I computed the maximum drawdown in the PA return just if I plot so if I plot, my x is a drawdown it my wife is a return right. So you understand that drawdown usually if sees goes minus 90% Say drawdown minus 95 is no way to get there because you need like, yeah, 1000 tax returns doesn’t count. And of course, then the your random return also is negative. So actually, you would be surprised how much scenes are in your wardrobe with drawdown or more than 90%. And effective negative for random because, yeah, we want to be left quadrant right? Yes. So 95% of it didn’t mean Extra 95 That means that they will legit kind of projects with market cap is volumes, but they didn’t make it through 95%
Jeff Malec 1:00:13
or negative return and and
Artur Sepp 1:00:15
negative return and effectively drawdown. So if you invested $1. Maybe right now, we would be less than one cent, even though it’s still you will still you you would have it in your wallet. Right? Yeah, you would not? Probably. But so
Jeff Malec 1:00:33
what? What does that tell you trade these things?
Artur Sepp 1:00:37
You done the recitation? Nevertheless, if we compute, so, of course, there are two biggest survival survivors is Bitcoin in the theorem. Moreover, if you build sort of theoretically equal weighted portfolio, right, that you invest in all tokens that have available market cap, you would actually decent return. So like, it would be of course, risky, but say we would be talking of maybe 200% Daniels?
Jeff Malec 1:01:14
Which is even with the 95% fan? Yes,
Artur Sepp 1:01:17
yes. Because few of them, right, there were exceptional guys, like more than say, two solid? Yeah, I would not. There was exceptional return. But more. So that would be for me, it’s more like venture capital, right, you would invest in smaller stuff, you would make fun. Also market cap. So instead of just taking an equally weighted, we’ll just go market cap, that would also make it through. So you invest in no investable universe, whatever is available at that time, just in proportion to the market cap. So you will also something even slightly better than Bitcoin, and it’s not accounted for transaction costs.
Jeff Malec 1:02:09
But does that put too much faith in the past? Right of likewise, most of that return in the 15 to 20? Range?
Artur Sepp 1:02:18
I think for me, yes. But also it’s quite ins in down. Yeah. So what for me? Tails, crypto is all about the recitation, especially if you want to go. Okay, you can invest in a theorem, Bitcoin, probably. Those are all established. The rest? Like, it’s almost like a lottery tickets, right? Yeah. Don’t buy if you think that it’s kind of every single sport, keep doing this. No, just go buy lottery tickets in the same type of way, happens faster, right?
Jeff Malec 1:03:04
And what about trading? And what about building quant models to go in and out of them? Yes.
Artur Sepp 1:03:08
So we actually, we’re building right now, what I think most interested in what we build in these sectors. And in crypto is of course it’s very, there are trends. What everyone say last, like say, beginning of last year was defied and meet of was Miata viewers and E is Vf three. And in my opinion now, also, it’s much better chances. If you say if you select the right sector with proper diversification, you can generate high excess returns that say outperformance at your Bitcoin add in for me in what we are building like it’s rebuilding. Clip the sector’s one of the projects that I think is very innovative and very interesting. What we’re also doing in LP base classification, because unlike the traditional industry, you have very well defined sectors like financial utilities, oil, pharma and so on. Right and you for pharma you have sub sectors may be right. Encrypted there’s nothing like it’s easy. So people know say d phi sector they can define Right? Like maybe web three you can define sub sector so web three are difficult to define. Right in wire. What we do is an op ed, what do you what?
Jeff Malec 1:04:53
What’s your take on web three? Like there’s a lot of hot takes that it’s kind of a scam and just made up?
Artur Sepp 1:05:01
Yes, yes, we are very, I mean, webs the way or zero, what is called layer zero is polka dot ICP atom, these are more almost like a foundational layers to create blockchains. So to create a distributed chain of interconnected blockchain, right? Important is that those are more almost like programs where you could replace a protocol, change the source code, and it will preserve the existing application, right. As you know, with Blockchain, with Bitcoin, you have this fork version, when something happens that algorithm or protocol cannot develop, or there’s some very big conflict where it cannot be resolved, right, we say blocks, some kind of either fraudulant or some logical field or that you have to fork you have to create a restart a new copy of your blockchain with layer zero avoid. And it’s a code. It’s a platform to create the apps, digital applications, so all kinds of maybe defy NFT gaming, they can be viewed seamlessly on these platforms. So therefore, this part is definitely the top ones, they will survive. Right, that I definitely don’t think it’s
Jeff Malec 1:06:46
in from an investor’s standpoint to have heard before, right, like it’s like getting paid to own the HTTPS protocol, right? Or the all that stuff. So similar to that we’re saying you could own a piece of that protocol and get paid every time it gets used? Or is it a programming language that we’re just going to build things on?
Artur Sepp 1:07:08
This one, this would be more programming language, right. But and the protocols themselves that would generate the utility of like the Apps applications and build they would generate utilities through transit transaction costs. But yeah,
Jeff Malec 1:07:31
yeah, but that seems to be the knock on all this to have like who nobody wants to pay all these gas fees and and all these transaction costs and the new environment to have what’s the solution there.
Artur Sepp 1:07:44
Yes, that is a point where say what I’m a bit skeptical on defy on this sense that there is no economic utility yet created for a fight for webserie in relationship to Mita viewers to gain an ease. This is our like, say it’s a game right? People play to play. Yeah, these are natural. Why I personally actually I believe in the metaverse not not say more of this because it doesn’t have a clear competitor in traditional space right it’s been developed it’s its traditional players are coming Zara and it creates some need for for sage is the opposite that that either some some kind of entry point to your universe to your to your collection.
Jeff Malec 1:08:49
And what’s an example of that, like I could bring my virtual currency across games or something right? Spend it in this game, spend it in that game? Use it in this metaverse.
Artur Sepp 1:09:01
Yes. So therefore there’s like several so within say, so we have three so we have three as we talk it’s interesting. Like as I said, we run an OP so so we have an OP bill. Again, so imagine in traditional company you always have four you have like very big when company like it feels IPO. Alrighty, yeah, you have every single what they are doing. Once they’re up and running, you have quarterly calls, you know exactly what they’re doing in this space in crypto space, zero, right? You have Bitcoin white paper is 10 pages or 11. This is what they do. Yeah, most of the protocols, but what we created we created what is called natural language process processing, where we would turn on lice, actually textual content of protocols by like indiquant different analysis like say, what viewers do the most frequently used. And that information, once you have that information, you can say build costs, right? More or less, we can identify, say VFC. And we can create some clusters. And so for example, we have three. So we have zeros, the ones that we said that used to build the application, where’s the most the three words that make it different from layer one, from like, say Aetherium. And defy like, say from uniswap. With soul, this is not a security and provider. So which makes sense. So So web three is about providing secure data is a storage or exchange for uses, right? For then we go into this, like chain link, for example, the ones that actually use for them specific words or data in Oracle. That being said, they, they connect different applications, and especially whether there’s a price information, or there’s some sort of, like reward information, this type of stuff that kind of connects you or allow you to connect different sources I can or exchange your money through different sources. Right, and
Jeff Malec 1:11:42
then I got it, but it sort of makes sense.
Artur Sepp 1:11:44
Oh, it’s a nice, interesting stuff, right? Is the best visit web three was the best last year was best was performing actually a business to customer, the one that kind of distribute either videos, right? Or some sort of information, but that’s a company or a token or a coin. It’s a sector I call it more of a sub sector.
Jeff Malec 1:12:13
So sectors are made up of the coins. Not all coins. Yes. Yes. Got it.
Artur Sepp 1:12:16
Okay. I strictly speaking this Dao decentralized, autonomous organization, yeah, but they for me, it’s almost like, for me, it’s almost like a some sort of fun, maybe startup or those are things that they have valid, say application, right? They have valid white papers, developers.
Jeff Malec 1:12:44
Right. So it’s your whole point of coming back to the VC world, the digital VC world, who knows who the winners are going to be? Choose the sector.
Artur Sepp 1:12:53
Choose? I said that diversify. Mandala is a volume market cap. A lot of the especially biggest challenge for be building a systematic Solution Suite with data. I spent much more than I imagined that I want to Yeah, data on lenient on understanding differences between different providers.
Jeff Malec 1:13:19
As I’ve joined, there’s no standard for like their API is to pull the data. Yeah. So you’re in the wild west there. And then how many exchanges are there? You
Artur Sepp 1:13:29
trade in application is? Yeah, usually I would. Yeah, I would always follow fundamentally it is important that this these kinds of screening that at least there’s a white paper, you can compare it you can identify then you have market cap that some protocols actually, they may overstate or understate. So you need to have different ways of comparing actually, outlier side, he can outliers, then accounting for volumes, especially once we build up scalable Asset Management Solution.
Jeff Malec 1:14:16
Gonna let you go here, but I need to know first, what’s on your shirt. Looks like some math.
Artur Sepp 1:14:20
Ah, yes. It’s actually I want it to be for for this. Yeah. I like it is from store. It’s just some form of
Jeff Malec 1:14:32
just some form. I thought it said Jeff, for me. I see a lot of F’s on the top one. Okay. Fair Market.
Artur Sepp 1:14:43
I think it’s basic. So it’s a force or something is the force mass
Jeff Malec 1:14:47
times volume or mass times velocity is force right? Was will show our lack of physics knowledge here. And then I was going to close with our what would you invest in but you sort of answered so if you got a foul. $1,000 Crypto addition $1,000 Were you putting it?
Artur Sepp 1:15:06
Once? So 1000 theses, I mean, they just go with Aetherium. Theory. I mean, Bitcoin you probably want marks for for your buck. So I think you see when will outperform.
Jeff Malec 1:15:20
And now if I 100 access from 100,000,
Artur Sepp 1:15:24
how did you think, then I would go a little bit more like say second base, or growth market, but a little bit with, like what I said some fundamental ways, even as simple as market cap that you don’t need to rebalance frequently. But it’s definitely if you’re to have more diversification.
Jeff Malec 1:15:47
And then so at a million same thing, just larger numbers.
Artur Sepp 1:15:51
at Milan, yes, I would do the same would try to build up a diversified portfolio.
Jeff Malec 1:16:00
And then 100 million in it scares me.
Artur Sepp 1:16:06
So actually data I would do this, for example, at Signum, we actually have different pockets of investors, so we have venture capital, so because our two should go, venture capital is the highest risk, highest return potential, then we have for, say, fund the funds, we’re also building up systematic strategies that say, but most of the staff, say, to invest in crypto, you need to have one beat exposure, you cannot do shorts, it’s not a market that where you will benefit. So that being said,
Jeff Malec 1:16:52
even when the past two years and some of these drastic spikes lower,
Artur Sepp 1:16:57
too hard for critical, difficult to throw first of all, you can only short a safely is Bitcoin and cerium. The rest are very hard. It’s not say
Jeff Malec 1:17:08
you’d be paying 80% Borrow rate or something. Yeah.
Artur Sepp 1:17:11
Yes. So going back to so find the font or services, demotic strategist, we also call for you. So more some sort of arbitrage. There are different ways either staking, also like arbitrage, say, cash and carry arbitrage, which more or less the same, and also some meter like fuel beat Explorer.
Jeff Malec 1:17:39
And last bit on that. You mentioned, the staking and the yield farming like is that even further afield than traditional finance, right, like the coins are one thing, but that seems to be what are your hesitations there? What have you seen that scares you there? What excites you there?
Artur Sepp 1:17:59
I think so what excites you? Of course, they offer rates higher than say traditional finance, as Oh, I think that is a definitely protocol risk. Wallet risk. So those
Jeff Malec 1:18:14
when you basically it’s an unsecured loan, right? Yes. So that’s the arguments against is like, Hey, you could do an unsecured loan on people’s cars and stuff and get high rates also. So it seems it seems to me some of the arguments against or you’re getting unsecured loans that rates lower than they should be? Yes. But we’ll let that we’ll let people argue that one. Right. Aren’t there any last thoughts? But um, you’re on Twitter there and your blog post to write? Tell everyone where they can find you?
Artur Sepp 1:18:48
Yeah, so so so. People can find me on Twitter. I try to be active. Now they say I think there’s a lot of useful information. Right. And yeah, I wrote an email.
Jeff Malec 1:19:11
I’ll do a what’s your Twitter handle? We’ll put it in links. Tada. Awkward. Alright, as EUR SCPP. Quick, I was went down to the office yesterday, which is near the Board of Trade there and I parked in what’s called the traders self Park. It’s from 40 years ago, right where people would trade when they went to the Board of Trade and did the hand to hand combat training. So the elevator buttons are all like gold we T bills, Euro dollars right there. All the floors are named after futures trades. So I just I took a picture of that and tweeted it out and it’s like, going on 3000 likes I’m like I’ll put out some well thought out threat or something intelligent and it gets two likes and one one reads take a picture of an elevator buttons and it gets 3000 links. So Twitter’s a weird place. Not that anyone needed to know that. And then what’s the blog?
Artur Sepp 1:20:09
i Yeah, so also my blog. So I think as we spoke a little bit at the beginning for me, quantity theory is is my passion. So I really separate that is my profession that makes assumptions that creates say utility, but I also it’s more like a passion where I spent more time say, understanding how Cindy works so using either maybe more difficult staff or maybe more Sumption, beyond. And of course, I try to keep the blog there’s our to say my older academic staff. Someone was like, memoirs on quant and systematic trading, but also new stuff is coming, especially on crypto. Right now we’re working on very interesting work. It’s more say academic Of course, academic right now, technically, it’s like the modeling flavor. But when he didn’t mention it,
Jeff Malec 1:21:18
what’s the URL? We’ll send people there? We’ll put it in the show notes. But tell him tell the list.
Artur Sepp 1:21:24
My website is also Arthur save that calm.
Jeff Malec 1:21:27
Easy. You got the best ones. It’s nice having a unique name. Alright, Arthur, thanks so much. I’ll let you go enjoy your evening there. My last question when you’re your head, I saw a picture is that your kids and ski goggles? Yes, exactly. It’s nice. Where do you skis
Artur Sepp 1:21:46
my wife? Well, whiskey, I mean, it’s so lucky to be in Switzerland. Yeah. And we regularly go skiing. Actually. Our son now is six years and he’s he’s turbo ski. Yeah, I really I never expected that I would be able to ski with my son. So like, really six right. And
Jeff Malec 1:22:13
that’s my main goal in life. I keep in shape just so my son’s 13 now so he’s almost faster than me but right. I want to be in shape for when he’s 18 and going down super hard stuff and I gotta keep up with them. Well, that’s my motivation. Now we got to get a trip out to Switzerland to ski together. We’ll bring Bastian alone. Get it Get a little quant quant ski trip. Alright, thanks so much.
