The Derivative - The Conscientious Culture behind Risk Control with Kapil Rastogi of PlusPlus

Episode Date: March 23, 2023

As investors and traders, we all strive for success in the markets. But what sets the best apart from the rest? According to Kapil Rastogi, the President and co-founder of PlusPlus Capital Management, it's all about having the right culture. Ranking among the best in the industry in RCM’s semi-annual rankings report for best risk control certainly doesn’t hurt either.   In this episode of The Derivative, Kapil shares his insights on a range of topics, including his personal journey to becoming an investor and trader, how compensation structure and successful backtesting can be at odds, and his unique approach to a behavioral approach to trading. He also delves into the importance of culture versus strategy, why most investors are asking the wrong questions, and how to identify a firm with the right culture. With a focus on the two components of success, strategy, and culture, Kapil highlights the significance of hiring the right people and fostering a positive culture. Kapil and Jeff also discuss the concept of skew and how it affects risk, the importance of minimizing drawdown, and how the recent bond volatility has played out in the markets. Through his experience and expertise, Kapil offers valuable insights into what it takes to succeed in the world of risk control. Tune in to learn more about the conscientious culture behind risk control — SEND IT! Chapters: 00:00-02:14 = Intro 02:15-11:47 = Getting started with Neiderhoffer & backtesting blunders 11:48-30:49 = Meticulous Backtesting, complex behavior models & why A.I. can’t replace intuition 30:50-47:40 = Culture vs Strategy: The five types of Culture 47:41-01:04:21 = Risk control, minimizing drawdown & a simple definition of skew 01:04:22-01:19:58 = A calculated response to the SVB events 01:19:59-01:18:41 = Sports vs Hedge funds: staying above your high water mark Check out Kapil on LinkedIn and visit pluspluscapital.com for more information on PlusPlus Capital Management Don't forget to subscribe to ⁠The Derivative⁠, follow us on Twitter at ⁠@rcmAlts⁠ and our host Jeff at ⁠@AttainCap2⁠, or ⁠LinkedIn⁠ , and ⁠Facebook⁠, and ⁠sign-up for our blog digest⁠. Disclaimer: This podcast is provided for informational purposes only and should not be relied upon as legal, business, or tax advice. All opinions expressed by podcast participants are solely their own opinions and do not necessarily reflect the opinions of RCM Alternatives, their affiliates, or companies featured. Due to industry regulations, participants on this podcast are instructed not to make specific trade recommendations, nor reference past or potential profits. And listeners are reminded that managed futures, commodity trading, and other alternative investments are complex and carry a risk of substantial losses. As such, they are not suitable for all investors. For more information, visit ⁠www.rcmalternatives.com/disclaimer

Welcome to The Derivative by RCM Alternatives, where we dive into what makes alternative investments go, analyze the strategies of unique hedge fund managers, and chat with interesting guests from across the investment world. Hello there. We did it somehow. The ranking's white paper. I've been teasing about it on the pod here for the better part of six months, but we finally completed it and it is being released alongside this pod. Sort of my baby, a ranking methodology I came up with years ago, which tries to measure

all the different aspects of a track record important to investors. Some investors look for the best return, some for the best sharp, others for the best mar, others just for the lowest drawdown. We show best by all those and then combine them into an overall ranking. So it's kind of fun. It's kind of interesting. So jump over to rcmults.com slash rankings to download the rankings. After you do that, go subscribe to the pod if you haven't already, because we have macro ALF coming on next week to dish on the banking crisis,

inverted yield curve, if the Fed is trapped, and all the macro nonsense you could want. It's going to be fun. Okay, that brings us to today's episode where we have Kapil Rastogi of Plus Plus Capital, which happens to be in our Best by Risk Control listing in the white paper we mentioned, which we're going to be doing over the next couple weeks here of trying to get as many of those top-ranked managers on as possible. I wasn't quite ready for him to say the secret sauce is culture, but that's where we went. He's also got some quant stuff in there that helps with that risk control, but it was an interesting chat. Kapil also talks through the pitfalls of backtesting and overfitting, why he chose behavioral-based signals over trend, what questions investors should be asking, but don't. Send it. All right, everybody, we've got Kapil, and I'm not going

to try and pronounce his last name. I'm going to let him do it for us. Kapil, how do I say your last name? Rastogi. Rastogi, just like like it's spelled easy enough um so kapil is here with us i think you're in princeton new jersey right that's correct yeah is everyone all pumped up over the two wins in the turning oh absolutely it's huge hopefully let's let's let's pray they can keep it keep it going right right i can't remember who they have next round but that's right it's not a huge scene right they could keep going let's hope right let's hope uh and later on i think you've got some parallels with sports and your investment style so we'll get into that in a bit um but we've had roy niederhofer here on the pod dishing some gems and so you used to work with roy and at niederhofer right so give us a little bit of the background, how you got into there, when and why you left and what you're doing now.

Yeah, definitely. So my background. So I graduated from MIT in 2002 with a degree in math with computer science. After that, I started working at Merrill Lynch Investment Management out in Princeton. That's where the world headquarters were back in 2002 before they emerged with BlackRock. I quickly realized that risk management, it was a great place, but I had a real passion for markets and I wasn't really getting any market exposure. So I started interviewing different hedge funds and I got a job at Royce Firm, a wonderful place to work. That's for sure. You know, I started at kind of the bottom of the totem pole being a European execution trader. So right at the very bottom. So my hours, my glorious hours were 1 a.m. to I usually leave it around 1 p.m. or 2 p.m. Eastern Standard Time. So, yeah, I mean, you know, and I did it because, look, it was a it was a it was an opportunity, you know, and I knew this is what I wanted in the long run.

And myself. Quick side note, Mike Harris of now at Quest and formerly president of Campbell and president of the MFA started as a European desk guy. So for all you young listeners out there who want to get into the industry, go beg and plead at a hedge fund to say you'll work the overnight hours. Absolutely. Absolutely. Look, I think it was a wonderful experience. Obviously not great for my social life, but hey, one thing I talk about a lot is like, you know, if you want something badly enough, you're going to have to, you have to sacrifice a lot to achieve it. Right. That's a universal rule of life. So, yeah, look.

Were you up there in Vermont or New Hampshire, wherever he is? No. He was in the city at the time. He was in Manhattan. Got it. Okay. Yeah. So I did that for about two years. And then I came back on the New York shift and kind of, you know, the interesting anecdote is, you know, for the first two years, Jeff, I started trying to develop strategies and like pretty much every strategy I

tested failed miserably. It was just a colossal failure. And then one thing I tell, you know, I do guest speaking to at different universities, including Princeton, my neck of the woods. And one thing I tell people, you know, a lot of young individuals that want to break into our field is, look, for the first two years, like almost every strategy I've backtested didn't work. And when I finally did get one that worked with statistical significance, we put into live trading. And it didn't. And you know what happened is that it just lost money, lost money, and lost money. Yeah, I was going to say the backtesting is the easy part.

The live trading is even the harder part, but you got it. So you were even struggling in the beginning on the backtesting part. Oh, absolutely. I mean, and finally, when I got the backtest to work, backtesting part oh absolutely i mean and finally when i got the backtest to work the live trading part hey you know i can't tell you what it feels like to just kind of watch your strategy just kind of uh leave money in live trading i've been there yeah um and so um you know and again it all boils down to perseverance right i mean i got i i've done i don't know how many back tests

in my career, definitely, you know, tens if not hundreds of thousands. But I think, you know, after a few thousand back tests, I think it slowly starts clicking as to kind of like, you know, what works in the back test, and what will actually work in the live trading, and how to normalize those two. Look, that just comes through just sheer perseverance and willpower and just saying, Hey, look, I'm not going to give up. Cause there's no book to teach you how to do this. That's for sure. There's no training really. Yeah.

You just have to kind of like, you know, grind it out. And I played competitive sports my whole life. So I'm kind of, I had that mentality um so i just kind of went after it and ultimately yeah i mean the first couple years it was really tough uh you know definitely probably the most difficult years of my life to say the least and while you're sitting in at niederhoff for doing these were they like we got to fire this guy he can't even make a good back test no nothing like that and that. And he didn't, he wasn't, he wasn't really like that ever. You know, he gives people,

he gives people space. I was very young. So it's nothing like that. And what sports were you playing? In college, I was on the rowing team. I was a college rower. In high school, I played a variety of sports. I played soccer, I played volleyball. Right there on the charles river yes at the what's the big event they have the regatta head of the charles head of the charles never been that's it seems like a good time

oh you got to check it out i mean all right yeah yeah i mean rowing is a great sport to just teach you um just grit conversely the only people that do it are a little bit masochistic, but also, you know, really, you just have to push through the pain. And so that analogy worked well in the hedge fund space, because again, when it comes to backtesting, look, you just have to kind of just, you know, keep trying things over and over and over and over again. And eventually, you'll kind of figure out, okay, well, this is what actually works in live trading. Right. So yeah, just okay. So then you're,

you're at Niederhoff and you decide somewhere along the way to go off on your own. Yes. So the way that worked out, Jeff was, you know, in, you know, in around 2006, I met my nail partner, Murat Elour. So he was the head of software development. I was kind of building a whole bunch of quant strategies and slowly and slowly more and more of the portfolio was being kind of allocated to the quant strategies that I developed. And, you know, I still remember for the first, you know, I started kind of doing more marketing, um, just cause I knew the model models pretty well. Uh, so I started kind of getting roped into marketing a little bit. And for the first time I saw a peer group analysis.

You mean talking to investors basically? Yeah. Well, I wasn't really talking to investors too much, but I was doing, um, some analysis behind the scenes, right? Like helping the marketing team look at correlations. How are we different? Great examples, right? That's a big thing. You know, for the first time ever, I was kind of doing some marketing, which I'd never done before, right? I was just really kind of focused on building strategies with the highest risk adjusted return possible. So the first time I look at our peer group, I had no idea who these people,

these firms even were, right? We're talking about household names now, like Crable, for example. I remember looking at the risk adjusted returns. And the first thing I said to myself was, you know what, if I went out on my own, I knew, I know that I could produce a higher risk adjusted return than what I see. I knew it would be a long process. I knew it would be a struggle. But I knew that that was the first thing that popped out at me. Now, the second thing that popped out at me was that, wow, what we're doing, which is behavioral biases, it's different. There was one or two other firms that were doing something kind of similar, a little bit, but not really,

you know? And so I said to myself, okay, well, you know what, if I could go out on my own and do things, which I believe to be, you know, the right or optimal way of doing things, and everyone has their own perspective on this, right? But how to build a business. I said to myself, look, I firmly believe that we could be the best in the world. We could be the best CTA out there. And I still firmly believe that, you know, obviously the results are the results.

Right. You can't go for it without believing that, right? Yeah. And so that's where it really started. So I had a talk with my business partner over kind of a happy hour. And, you know, I saw that he had a similar kind of vision as I did, which is really to be the best of what we do. Right. I mean, that's really what it boils down to having that mindset of, OK, well, we want to be number one. And that's our definition of success. Now, everyone defines success differently.

Right. For me and our firm, success means being number one, number one, meaning having the highest risk adjusted return in the space. Getting into this with Marty Bergen last week of like, is a lot of trend followers, their track records are so long that all their warts are there for the world to see. So almost by definition, they're going to have lower risk adjusted returns than the newer flavors of hedge fund or even in their own strategy. So a little bit of it is just time and the window that you're looking at. But I think you would feel even if you had been around longer in those years, you're saying like, no, the way we do it would produce a better risk

adjusted return. Yeah. I mean, look, Jeff, you bring up a valid point, right? I mean, obviously, look, you have to have a sufficient time period to evaluate a track record, right? Now, in our case, our track record is five years, right? So if you look at our five-year track record, right, with the model we have called Plus Plus Global Alpha, I'm very proud to say that, you know, what we set out to achieve, which is the strongest risk-adjusted return in the CTA space, we've accomplished. So we have the highest Sortino ratio of all CTAs in the SOC-Chain CTA and SOC-Chain STTI indices, right? So what we set out to achieve way back in 2007, that vision that we had thus far, I'm very proud to say, has come to fruition.

And it's been quite a journey. My partner and I, we spent several years building our own back testing platform, easily put in over 10,000 hours just in the back testing platform alone. People always ask me, well, why do you spend so long building a backtesting platform? You can purchase one off the shelf. What's so special about your backtesting platform? One thing I tell people is like, look, I mean, at the end of the day, we're running a business, right? And so in a business, you have to have a competitive advantage. Moreover, you have to have a long-term sustainable competitive advantage if you want to be the best at what you do. And so one thing I quickly realized is that in the quant trading space or systematic space, you can have the most brilliant idea in the entire world. But you know what, Jeff? If you can't backtest that brilliant idea, it is totally useless. Or I would even correct it for you a little bit if you can't realistically backtest it.

Exactly. That's what I was going to say. The reality of the world is that if you can't backtest that idea quickly, it is effectively garbage, right? So, you know, building your own black backtesting structure from scratch, which allows you to backtest ideas very quickly, which other people can't test quickly, that's definitely a massive competitive advantage, which is sustainable, right? And this is where the business culture all comes in, in the sense that sense that you know if it takes me several years to back test an idea um which i think is really good i'm going to do it but if you're at let's say a really large firm um you know where the incentives are just a little bit different right i mean you have a you have a year of urine bonus right i mean you're not really you know going to pursue an idea which only produces results after

three years similar to our u.s political system right yeah right i mean nobody wants to plant trees they just want to harvest them right now yeah right i mean also it's you know it's the compensation structure right i mean you're getting paid based on the respective results you generate to some extent, right? You're not getting paid just to kind of like, you know, do backtesting, right? But the same is true for you, right? As a business, you can't get paid to sit there and backtest and not produce any results for five years. You'd go out of business. You'd have no clients. Oh, absolutely. And that's the reason why very early on, you know, this is way back from 2010 to 2012. We spent several years kind of building our back testing structure, knowing that, look, this is going to give us a real sustainable. Like before you had client assets or in conjunction with your launch, essentially?

Yeah, before we had real client assets is when we kind of really sat down and kind of just just coded six days a week. And what's that look like? So in my mind, when I hear that, I'm like, oh, you're doing higher frequency stuff that needs to be done really quickly. And that loses its edge over time when kind of, I would argue, more traditional managed futures is kind of like, hey, it's a core piece of the market that works. Trend following works kind of regardless of what you put it on, maybe not on a risk adjusted basis, but on a pure, what you're looking for, it works quote unquote. So I don't necessarily need to backtest it quickly. So explain those two pieces of like, why does it have to happen quickly? So why did the backtesting happen? How to happen quickly? Why does the back testing have to occur quickly? Yeah.

It seems like you're saying like, because you'll lose your edge, right? And once it's, if you don't get in there quickly, other people will find it and you won't have the edge anymore. Not so much really. I mean, the inefficiency that we recognize in our portfolio, they last for quite a while.

But the reason why, Jeff, they last for quite a while is But the reason why, Jack, they last for quite a while is because they're difficult to find. So there has to be a barrier to entry, which is high enough that it's very difficult for people to get in. So when it comes to a lot of the behavioral inefficiencies, which we implement in our portfolio, they're very difficult to find, first of all, because, you know, behavioral biases in the markets or inefficiencies, you know, there's people like Daniel Kahneman, which have done great work on it. But the reality is, like, in order to find a behavioral inefficiency, which you can exploit, you had to have been watching the markets for years, years upon years. And like, you know,

if you watch it for long enough, you develop good intuition, just like in any other field, right? If you've done 1000 surgeries, you'll, you know, experience leads to better judgment and better intuition. So in our space, in my case, again, as I said, like, you know, I was a quant, you know, but for the first couple of years, I mean, all the strategies I tested, nothing worked. And it's only after tens, maybe hundreds of thousands of backtests that I really kind of get in the rhythm of kind of finding strategies that work in the backtest and most importantly, also make money in live trading. trading, and then furthermore, being able to take a multiplier and say, hey, look, you know what? If my back test has a risk adjusted return X, I know that live trading, it'll produce 0.75 X. That just takes a considerable amount of time. Preston Pyshko I guess my question is, you could have, in

theory, come up with a very simple trend following model that worked. You write your first back test using an 80 day look back and a two standard deviation breakout model would quote unquote work in the back test. Right. Right. Especially if you add more markets and look back for them. So what drove you to be like, Hey, I don't want to go down that more simple model. Like basically I want to do these more complex behavioral models. And we might've buried the lead a little bit of like,

if we back up and say, what is plus plus doing at the top, you know, top down, looking down level with these behavioral biases. So I don't know if there's a question in there, but you know what I'm saying? Give us the top down view so we can level set. And then let's dig into why did you choose to go that path instead of the more simple path? Yeah, definitely.

So look, the name plus plus right that really signifies kind of our um everything we do the first plus have the strongest risk adjuster return in the space that's the first plus and we came up with that name jeff before we started trading right so you can see our objective our vision our vision statement it's embedded in our name, right? So two pluses. First plus, strongest risk-adjustable return on the space. Second plus, low correlation with everyone else in our space and obviously all the major indices, right? So that's our value proposition. That's what we do.

That's our competitive advantage. And that's the value add to an investor. Now, to answer your question very succinctly, look, if I just did a simple trend following model, we would not honor the first plus, which is being the best at what we do, right? And that's kind of, it's a reflection of kind of who we are as people, right? Trading to a large extent has to be a reflection of kind of who you are, right? Because you can't trade with a style you're not comfortable with. For me, from day one, we were always about kind of being the best.

So if you want to be the best, then you have to be different from everyone else, just by definition. Hence the reason why we built our own infrastructure, which took us so long to build. And we continue to add on. And secondly, I mean, the behavioral approach, it really is different. That's for sure. And I'm a firm believer that it will continue to be different, even as more quantum to the space, because, you know, you just you really need just many, many, many years of watching markets before you can really come up with a really good short-term strategy based on behavioral biases. And so what bucket would you put yourself in? You're probably going to say I'm outside of the categorization of the buckets, but if you were forced to, short-term trader, trend follower, pure absolute return, no correlation, any of those buckets?

Joe Consorti I would say if I had to classify ourselves into one of the three, which I guess you're forcing me to, I have to classify myself, I would put myself in a short-term bucket. Why? Because our average holding length is four and a half days. So clearly we're short-term. Preston Pyshko Yeah. And you do exhibit some correlation to managed futures as a whole and trend following, correct? clearly we're short term. Yeah. And you do exhibit some correlation to managed futures as a whole and trend following, correct?

We do. I mean, our correlation to, for example, the StockChain STTI index is a little bit over 0.2 as to whether you consider that material or not. That's a whole other pot. Right? Yeah.

Our correlation to trend following is zero. Our correlation with the S&P is slightly negative. And then, so can you give us a few examples of these behavioral trades without giving away the secret sauce? Yeah. Sure. Yeah. I can give you some examples. Yeah. I mean, one of the things we definitely look at is we look at, you know, so I'll give you one really good example I like to use is December 6th, 2019, right? The buy the dip trade in the S&P qualifies. Okay, buy the dip trading means that the market's going straight up

and then there's a big dip. And then whoever bought the dip on that day over the next four or five weeks, you would have made about a 5% or 6% return. It became so good it got called buy the fucking dip, right? BTFD, not just BTD. Yeah. So, you know, December 6, 2019, buy the dip trade in S&P works fabulously well.

You make about 5% in three weeks, right? About less than a month later, the buy the dip trade again qualifies. If you put that trade on, again, you would have made about 5% in three weeks. Buy the dip trade again, late February 2020. Buy the dip trade again qualifies. Let's take a step back. You're that investor, Jeff. First, buy the dip trade, you made a all of us. Okay. Let's take a step back, right? You're that investor, Jeff, right? First buy that trade, you made a lot of money, right? Second buy that trade, you know what? You made a lot of money. Third buy that trade, what are you going to do? Right? Human nature.

I'm an outlier. I'd start taking it off the table, but I know you're going like, most people at that craps table, they're pushing that six, right? Like, okay, it just hit. Put more on, put more on. Exactly. You put more on. Now, imagine Jeff for a second. You're that person. You know what? You missed the first buy-the-dip trade.

And you were to watch that market go straight up. And you missed the second buy-the-dip trade. I definitely missed both those, yeah. Right? And then the third buy-the-dip trade, well, what are you going to do? Yeah, get in let's get it and not only would you get in jeff you will get in with some real size right because you're going to say to yourself hey you know what i missed the first buy the dip trade i missed the second buy

the trade both those trades made a lot of money there's no way i'm missing the third buy the dip trade right so you're going to get. So you're going to get in and you're going to get in with size. Okay. So our models, for example, will sell that third dip. Right. You see that? Yeah. So that's, that's an example of something that we do. Right. And then, so you take this phenomenon, you codify it with a set of rules. Based on just because it's the third or based on a whole bunch of other? No, based on the fact that it's the third. I just want you to understand the behavioral thinking behind it. So this is the concept. You have to codify into a set of rules, back-test it across all the markets that we trade. I'm giving you an example in the S&Ps, but look, we treat all the markets

more or less the same. Why do these behavioral biases work? Why do these behavioral theses work? It's because markets consist of people and people are predictably irrational. That's why it works. So we take a behavioral thesis like this and we back test it across all the markets we trade. Right. And then we look at how it does in aggregate across all markets. We say, is it statistically significant? If the answer is yes, then we test it at a sample. Is it statistically significant at a sample? If the answer to that question is yes, then we can say to ourselves, hey, look, we have some real alpha here, right? So you can also see, Jeff, how our approach naturally leads to uncorrelated returns. Because if you think about this strategy, you know, this idea I just mentioned, it's not

going to be correlated with trend following, right? Is it going to be correlated with S&P? No. If anything, it'll be slightly negatively correlated, right? Because we know when the S&P goes down, the vol goes up. How do you avoid the trap of, hey, every third Thursday, the yen goes down? And is that just coincidental? Or is it, right, every March 17th of every year because it's close to saint patty's day something happens right like do you check it against fundamental anything or if it's held statistical significance it's in the portfolio no no so okay so what you're referring to jeff is how do we avoid overfitting yeah great question okay okay so the way we um tackle that problem is we have a thesis and we test that thesis across all markets.

Okay. So if you think about it, you know, using the example you used, you know, buy again on March 17th because of St. Paddy's Day. That's just a yen. So we would never trade that. Right. right now if you're saying the thesis is hey look let's buy all the currencies or all 62 markets on march 17th because of saint patty days great let's back test it and i can already tell you the results will look terrible yeah right now you see how jeff you know what you what you described is very common well like you have an idea which it just works on one market right why does it work on that one market why doesn't it work on tat why doesn't it work on aussie dollar what's so special about the yen and the reality is jeff there's nothing special about the end right they're all overfitting tradable widgets

the uh and so what does that portfolio look like 20 markets 50 markets 100 markets? 62. 62. So in all the normal kind of managed futures buckets, grains, energies. Yeah, the four sectors, right? Fixed income, currencies, commodities, and equities. Got it. And then I just jotted this down. Let's dive into it now if you want. You keep saying intuition, the 10,000 hours rule, all that stuff. Some would argue like, hey, we can shortcut that process with AI.

We can run this all through AI. We can get AI to identify these patterns much more quickly, much more whatever. And they can run many, many more iterations than you can do. What are your thoughts? Do you guys use that? Do you have thoughts on whether that's good, bad, indifferent? I mean, that's a different approach altogether. It's hard to say good or bad. I mean, look, good or bad is just dictated by the results. I mean, look, if you can generate great risk

adjuster returns in live trading, hey, all the power to you. i can share with you my opinion um you know with ai is it's a good tool but it doesn't replace intuition there's no way right i mean look if you give me a million different back tests i mean you know just again being a math person right take a one percent confidence interval right there's a certain percentage of them that will be significant just purely due to chance. Yeah. Right. But that's what I'm saying. Like, why not tap into that and get like, Hey, we've got 50 more just due to chance that are now significant that we could put into the portfolio.

Yeah. I would never do that. It's just not our style. I mean, behind every strategy, there has to be a real clear thesis, which is based on intuition. So what I share with you, Jeff, about the third dip, there's clear intuition behind that. And that's intuition. Look, it makes sense to me. It may not make sense to someone else, and that's okay too, right? But that's where the judgment and experience come in. You know, what happens with like what you've described is like you'll have all these different statistically significant strategies the thesis makes no sense to me right so the thesis has to make sense to me um as a portfolio manager yeah but some don't even have a thesis right they're complete black

box ai and just shooting out signals right yeah i mean for me that's very dangerous which i've told some of the guys like create the have the ai also produce a thesis even if it's totally unlinked from the actual signal just be like uh i mean that's where human beings come in right in terms of like pattern recognition and developing a thesis, right? I mean, if you can develop the thesis and then get the computer to basically test the thesis, you know, that's something a computer is very good at. If you're asking a computer to like come up with a thesis,

I don't think that's a wise idea at all. Yeah, mainly a joke of like, hey, you have trouble explaining this to investors? Have the AI just create an explanation? Right? Like the signal's totally random and you can't explain it. So why not just explain it away with some other totally random thing? Right.

That's a little bit tongue-in-cheek. So talk about this so this seems to tie in with like we were talking a little bit off screen of like culture versus strategy right so yeah anyone can create a strategy you could use ai to create it you could have experience in the bank and know what works yada yada yada so talk to us what you mean about like you have to have the culture i kind of took it as infrastructure but whatever what tell us what you mean by culture versus strategy yeah um definitely so um this is a big part of what we do is um so um i can share with you that uh there's a management guru called peter drucker i don't know if you've heard of him yeah but uh he has a very famous quote which i like which is um he says culture trumps strategy in the long run, always. And then he has another quote, which goes even further.

And he says, culture eats strategy for breakfast. Very strong words. And he's referring to business in general. And this is something that, having played competitive sports my whole life, it immediately resonates with me. Any competitive athlete, you don't have to tell them this, right? The importance of culture. Look, if you look at all the best sports teams in the world, New York Yankees, New Zealand All Blacks, right? Real Madrid, right? They have certain things in common. Number one is always culture. Always, always, always. Okay, so how does culture,

how does this apply to our space right and just march madness perfect right that cohesive team that believes in each other believes in the coach usually wins over the super talented team that is barely has a culture yeah i mean look you're talking about basketball right 2004 dream team right i don't know if you remember the u.s olympic basketball team yeah yeah full of superstars how can you lose? But guess what happened? First game to lose to Puerto Rico by 19 points. Puerto Rico. Yeah. What stars are on that team? How does that happen? Well, culture, culture, culture, right? It makes such a big difference in any business, in any team endeavor. Now, so let's talk about how it applies to our space, right? Because everyone will agree that culture is important.

The California Management Review, it's kind of a lesser known business review, which only kind of like geeks like me read. And I believe it was 2002. They did a great study where they said, okay, look, what Silicon Valley firms make it and which ones don't. Silicon Valley, like our space, is hyper competitive, right?

So over 10 years, they tracked all these startups. And they said from day one, okay, we're going to divide all these firms into five cultures, okay? Culture number one is commitment culture. Culture number two, sorry, is star culture. Culture number three is bureaucratic culture. Culture number four is engineering culture. And then finally, autocratic culture. So let me quickly give you a description. What is commitment culture? Commitment culture means as a leader, you're actually looking out for the long-term interests of your employees. And most importantly, all the employees know this. So again, you're looking out for the long-term

interests of your employees and your employees can see this. So in essence, you're committed to their long-term success. In preference to the shareholders or in conjunction with yeah in conjunction with right okay yeah okay then there's star culture what is star culture star culture means look you produce something for me and i pay you a lot of money that's star culture that's very prevalent on wall street also in silicon valley right um culture number three bureaucratic culture doesn't exist as much anymore, in my opinion. It's basically, look, we have job descriptions, project descriptions, and strong project management. That's bureaucratic culture.

Then engineering culture. Okay, we have an open atmosphere, basically free of any constraints. Have fun. Right? Yeah. And then finally, autocratic culture. You come into work and you get paid now interesting thing is jeff which culture do you think over the 10 years was the most

successful like of all those silicon valley firm startups right they're classified into one of these five categories from day one 10 years later the results were astounding. Which culture by and far do you think achieved the best results? I'm going to go commitment culture. Yeah, exactly. Now, not only did commitment culture succeed, and get this, in the hyper-competitive world of Silicon Valley startups, not a single startup failed that employed commitment culture from day one over the 10 years. Not a single one of them failed, which is, in my mind, just astounding. Now, what's the parallel to the hedge fund space? Well, there's many parallels, right?

So one thing I always talk to people about is I say, look, you know, superstar culture doesn't achieve the greatest results. But you know what? That's what's most common, right? So look, there's an inefficiency right away, right there is, as an investor, you know, it's all about asking the right questions. Good investing is all about is asking good questions. So if you can ascertain what kind of culture is prevalent at the hedge fund, well, automatically, that's a very valuable nugget of information because we know that commitment culture produces the best long-term results. So now, how do you know if a firm has commitment culture or superstar culture or engineering culture? So here's some basic guidelines is, look in hedge funds that have been in business for a long time. Question number one is how many successful traders have you produced?

How many of your traders have started their own hedge funds successfully, unsuccessfully? How many of your employees have gone on to be successful? Right. Now, if you think about it, if you're, if the hedge fund hasn't produced anyone that successfully created their own hedge funds, okay, that's a red flag immediately. Why? Well, there's only two possibilities, right? Why would a hedge fund over a long period of time

not produce anyone that successfully went on to start their own hedge fund. There's only two explanations. Explanation one, there's not many opportunities for growth within that firm, which results in all the employees at the firm just leaving. Yeah. Right? So in all my years in hedge funds, and I worked at two multi-billion dollar firms, every single employee I met at my hedge funds okay one thing that all in common jeff was all of them had an aspiration a dream to eventually start their own hedge fund there is no employee at a hedge fund that goes into the hedge fund and says okay i want

to be an employee my whole life that does not happen in the hedge fund space. Even in the back office and roles like that, for sure. That's a good point. I'm referring more to the research. Yeah, yeah. Research, trading. I've never ever seen a single person who is in the research or trading group at a hedge fund that does not have a dream

to eventually start their own hedge fund. Right. So if nobody in a hedge fund has ever successfully started their own hedge fund. Right. It's a red flag in my view. Why? Because there's only two possibilities. Possibility one is there's not many opportunities for growth within that firm, meaning that the leader is not providing enough opportunities or any opportunities at all for people within the firm to eventually start their own fund. And if people within the firm see that, hey, look, there's zero possibility of me starting my own firm, if I stay here, then everyone's eventually going to leave. It's going to lead to high attrition. And business literature all says, this is just common sense in my view, is that high attrition or a lot of people leaving eventually leads to poor results.

And in our firm, that means big drawdowns. Yeah. Right? Yeah. All right. I'll let you go ahead. But to me, it's like, how do you separate the strategy can be solid, right? It's not necessarily going to lead to bad results. That's a good point. So there's two components of success, right? There's a strategy and there's

culture. Okay. When you're evaluating, let's say a business, like a hedge fund, there's two components, right? There's strategy and there's culture, Evaluating the strategy, evaluating the pros and cons and the approach of the strategy, that's something that you basically just did in a very primitive form. You're asking me questions about the model building, asking me for an example. And that's something that, look, we're all trained to do that. There's training as an investment analyst, you know, and how do you evaluate a hedge fund strategy, right? Now, culture, that's much harder to evaluate. Like, how do you evaluate the culture within that firm? And in my opinion, I think that's really part of the secret sauce, right? As to what hedge funds make it and which ones don't make it, right? It's more than just a strategy. That's for sure. We all know that, right? But culture is a very critical long-term component of success. Yeah, but I guess I don't, why is it more important, right? I guess I would view the strategy could overcome any cultural issues,

right? That if you have a strong enough strategy, it's going to produce returns. No matter, say you have, right. A jerk at the top who just has the best strategy and he he's winning. You have a bad team, but the strategy keeps producing results. So what's that? Why of like, how does the culture leak into the strategy? Oh, a bad culture. Yeah.

Yeah, definitely. Look, a bad culture eventually leads to attrition, people leaving. Lots of people start leaving. Just like, you know, you're at RCM, right? If you happen to leave for whatever reason, well, your responsibilities have to be passed on to someone else. Now for you to pass on your responsibility to someone else, if you've been there for a long time, you can't pass it off in two weeks. It's impossible. How would you pass it off in two weeks? So a lot of things will be lost. Now you have to find new employees. Now imagine your firm is going through a drawdown, Jeff. Finding new employees and you're in a drawdown, good luck with that.

But I guess the strategy is still going to be right. So it's about the next step after that, right? Of like, fine, we couldn't get the new employees. Now we're not doing the new research. Now we're not doing the new project of the execution, improvement, whatever. Right. So it's those little pieces that get washed away. Oh, absolutely. All the details get lost. And honestly, being successful, it's really all about getting the details right. Right. It really is. I mean, yeah, I mean, look, first of all. But that seems like it would lead towards the process culture, right? What was that one called? Bureaucratic or automatic. Yeah, it seems like, okay, we got to get all the details right. Let's make sure we're a bureaucratic culture well i mean look getting the details right um i'm talking about the strategy now that's important anywhere you go right so again look if i if i create a model okay um it has a whole bunch of parameters there's

nuances to it um the intuition you know again my intuition is going to be different than your intuition maybe sell the third makes no sense to you at all. That's fine. But if I leave, then you know what? Then all of a sudden you have a strategy now with no strategy owner attached to it. Why is that dangerous? One can argue in the short term, there's no real danger. It's still running, as you said. In the long run, there's huge danger. Who knows the parameters are set the way they are. Why the third dip? Why not the sixth dip? Why not the second dip?

Why the dip altogether? Why did you quantify a dip the way you did? You know what I mean? So in the long run, it really is dangerous. That's for sure. You know, so that's where really the culture eventually leaks into the strategy. That's for sure. Because look, at the end of the day, Jeff, a firm is composed of people and the models

are built by people, built by humans. Yeah. Right. I think that's what some investors like. They think they're just buying this track record that exists through time. But really, you're buying the firm, their ability to innovate, their ability to research, right, and produce new alpha over the years as things change. Right. And look, Jeff, just going back to business literature again,

90% of the alpha is created by 10% of the people. Always, always, always, always. If that 10% is not there anymore, as an investor, you want to know that. I thought it was an 80 20 rule it's a 90 10 rule somewhere in there yeah yeah somewhere in between right i mean you get the you get the overarching idea right so when we talk about um investing the track record look i totally agree with that but hey you better be sure that track record is repeatable right right and and dynamic to some extent of like what what if, yeah. Yeah. I mean, look, if you look at, for example, look, let's take something like paleontology. Why do the dinosaurs go extinct? Why? Because they couldn't adapt. Right.

The ability to adapt and adjust is one of the key predictors of long term success in any field. Right. And again, you know, the CEO of Goldman Sachs, Hank Paulson said it himself, look, you know, he got a lot of heat for this, but he said, look, pretty much the vast majority of our alpha or our results are really being generated. As you said, by 20% of the people. Yeah. Right. He got a lot of heat. That's always the way it works. It's just kind of a, again, a management maxim. You'll see that at any company you go to, you'll see that. So as an investor, hey, you want to make sure that whoever that 20% is or 10% is, are they still there? Right. Right. Yeah. And we'll move on. But yeah, in my mind, there's still that piece of like, well, it doesn't, right. And I've heard it argued of like, yeah, no, they're not there,

but it doesn't matter because it's systematized and the processes are all documented and we know how to do right we've got that all documented so it doesn't really matter if that person's there or not fair enough yeah i mean look it's we can debate it all day i think like look the whole concept of idea generation um look in terms of generating ideas that's where human that's why you need human beings. Yeah. No, I like it because a lot of times you just hear people or other firms say, no, we have a robust research process and we're always looking to innovate. But it's rarely talked about is here's what we believe in terms of culture and making

sure the people we need to be here are succeeding. But it also is interesting to me if you have that commitment culture and you're saying we want to train them well enough that they can go start their own fund and they leave, right? Aren't you in the same spot? Like if you had the bad culture and they leave, you have the good culture and you've trained them well enough to leave. You kind of end up in the same spot that they left. That's a good point, Jeff. You do. Look, we have commitment culture at our firm, right? And it's something that I implemented from day one. And both my partner and I were completely on board with it. But we've known each other since 2006. We're working together through ups and downs. Now,

look, I'll give an analogy, right? If you have a tree or plant in your office and it keeps growing, growing, growing, eventually hit the ceiling, but then it won't stop growing it's going to start growing oh it's not going to start growing laterally across the ceiling okay so this is how this is just a law of nature right human beings were designed for growth so look people are going to leave whether you like it or not to start throwing funds if they have talent yeah right if they don't have talent okay okay, well, they probably won't leave them and they'll do something else. But if they do have talent, whether you like it or not, Jeff, they're gonna leave. And you know what, that's very natural. It's very normal for any

living organism to want to grow. Yeah, right. So brings me to my second point is, you know, when it comes to kind of culture is, you know, if nobody's kind of started their own kind of respective hedge fund, then the other question, you know, as an investor, I would ask is definitely. Are you not generating? Are you not kind of producing or you're not hiring good people, right? What is your hiring process? You know, and that's a very important question to understand. Like, are you hiring lackluster subpar individuals that are really not capable of performing at the highest level? And again, these are just questions, you know, I mean, and again, investing is all about asking the right questions as is good trading. Stig Brodersen

So let's switch topics for a minute. So our rankings white paper from RCM that by the time this launches will either have just come out or will shortly come out. You guys are ranked. We show the top five in all these categories. So you're in the top five of best risk control, essentially. Yeah. And I think, so talk to us a little bit about how you actually do that. Because a lot of, everyone says they can control drawdowns. You guys have actually done it over the long term. Yeah.

Flip side, I could argue you've done it by keeping vol super low. So just talk through that of how you view risk control, how you view I think the drawdown is under 5% historically, which is unheard of in the managed futures space. Jeff Ross Absolutely. So our max drawdown, Jeff, is 4.4%. It's important to look at drawdown as a percentage of the volatility you're running the fund at. If you're running a two vol and your max drawdown is 4.4%, I don't think it's really all that

attractive. For us in our example, if we're running a six vol and our 67 vol and our drawdown is 4.4%, as a percentage of volatility, vol and our drawdown is 4.4%, but as a percentage of volatility, if our max drawdown is about, let's say about half of our annual vol,

that puts us pretty much, from a downside deviation perspective, we're pretty much right at the top of the list in CTAs. I guess the second question you had was how do we do it, right? Yeah. Yeah, that's obviously a huge, huge topic. I guess the second question you had was how do we do it, right? Yeah. Yeah, that's obviously a huge, huge topic. And it kind of boils down to all the work we've done over the years, the backtesting infrastructure, right, which allows us to test ideas which other people can't, can do it in a very difficult way. That helps us a lot. Our approach is very different in the sense that we break down the market into different regimes.

And we have a whole army of strategies, which makes money in each respective regime. So when we think about risk, we obviously think about magnitude of drawdown, right? But another key piece of the puzzle here, which is not talked about enough in my mind, which is something we really focus on, is duration of drawdown. Yeah. Right. But we talk about risk management with two key components, magnitude of drawdown. Right. So our max drawdown is 4.4 percent. Right. The second thing, though, is duration of drawdown, which is in my view equally as important. So in our case, look, we've hit new high watermarks every year. And it goes back to our approach again of

wanting to be the best at what we do. So how do you produce the highest compounded returns in the long run? Well, it's pretty simple mathematically. The first thing you do is you minimize drawdown, right? Right. Look, if you lose 20%, right, you have to make 25% just to get a goal, right? So if you want to produce the greatest compounded returns in the long run, step number one is just minimize drawdowns, right? Which is, again, sounds common sense, but it's something I walk people through just mathematically to really understand this concept, right? Is how lethal and how detrimental drawdowns are to your long-term return stream, right? And so that's kind of, you know, when I talk about being the best at what we do,

minimizing drawdown is really one of the big pieces of that. We have very, very strict risk controls across all of our trades. If any of our trades loses 30 basis points, we're out immediately. We have really, really strict risk stops across all of our strategies and all the markets we trade, whereby if any market loses 100 basis points, that entire market's liquidated and it can't trade until the next business day, for example. Another- So you mean like not if crude oil is down 1% and get out of all crude oil trades, if all of your signals inside of that market lose 100 basis points? Correct. So if crude oil, hypothetically, if we lose 100 basis points at any time throughout the trading day, right? And all these markets almost trade 24 hours a day, then we completely liquidate that market.

So our models can't trade crude oil at all until next business day all right okay so it's absent the signals no matter if you're making money in that trade or losing money no no we have to be losing money so if we've lost more than 100 basis points in crude oil at any time across multiple signals got it right on a portfolio level yeah then we liquidate all of our crude oil signals and we can't trade until the next business day. How do you think about that? Because that can be a trap, right? If you're like, if you always are locking in that loss, but you might not ever get the gains to outsize the losses that you locked in.

I can't remember the name of the firm. It's since out of business, but they had this whole complex system of like, and basically they figured out they were just locking in losses. Right. And it kind of, it caused this downward sloping equity curve of like, we just continually quickly lock in losses. So how do you avoid that trap? Look, you have to backtest it is all I can say. I mean, for us, we backtested everything very rigorously. So in our case, also all of our strategies, about 32 of them, they all have a statistically

significant positive skew. So it makes sense for our type of trading to have this type of risk control because look, I mean, if I put a trade on, models put a trade on on let's say right now right and let's suppose um the trade goes south meaning we buy crude oil and the market immediately

starts moving against us so crudely goes straight down we know that that trade is most likely going to end up as a losing trade because generally speaking our good trades jet they likely going to end up as a losing trade. Because generally speaking, our good trades, Jeff, they're going to start working almost immediately. We've done all that research and done that analysis. So we know that, look, if we're losing 100 basis points plus all these signals in crude oil, then you know what? Those trades are all going to end badly. Right. Maybe one out of 10 or one out of 100 times there's this huge reversal and you made money, but you're saying across on average, it's a bad day. Right. And so again, this boils down to our style of trading, which is very different than the rest

of CTAs because we have a statistically significant positive skew in our daily return stream, which logically you would think that, you know, for example, trend following would have that, but it doesn't, right? I mean, the data doesn't lie, right? So because we have that, the one other really nice thing about this type of trading, Jeff, is that we can cut our losses very aggressively. And it actually, that actually increases our risk-adjusted return. It doesn't decrease it. And talk a little bit about SKU and what you said, because I would argue most trend following does have positive SKU. Maybe it's just the ones that I like.

And I, and I'll tie this back to when I was thinking about it, your mandate of like, Hey, we're going to have the best risk-adjusted return. I could create some option selling program and get lucky on the timing and have for sure the best risk-adjusted return, right? Essentially, no losses, huge sharp ratio because the risk is hidden. It hasn't hit yet. So two part of there, like first explain SKU and that would be negative SKU because eventually you're going to have the big loss, right? And it's going to SKw it the other way but uh explain how you think about skew because i think it's a little bit different from your background yeah absolutely so um you know anyone can look up the formula for skew online it basically means look your best case scenario is better than your worst case scenario

right like your best trades are better than your worst trades. That's great. Never heard it put so simply. I like it. Yeah. Yeah. I mean, look, a lot of these statistics, I like to look, you have to glean the essence of it, right? I think we were talking, Jeff, you and I offline about this is that a lot of these statistics, excuse an excellent example, was composed by individuals who were definitely not working in the finance space, right? The statistics were composed to help describe the natural world, biological world, right? It was not created to help us be better investors. So it's important to understand the essence behind the statistics.

But what we do is we create our own statistics, which reflects the underlying theme of what we're trying to capture. So if you look at the ratio of the best month to the worst month of a manager, that in essence is skew from an investment practitioner's perspective, which is far more meaningful than the mathematical skew. So let me give you an example, right? Our skew of our daily returns is, I believe, I think plus 1.6, something around there. And it's statistically significant. Let's say someone else's skew is, I don't know, 0.2. Those numbers, which I mentioned, 1.6 SKU versus 0.2 SKU, it doesn't have any real meaning attached to it. Right. But if I tell you, hey, look, Jeff, our best month, okay, is about three times our worst month. You understand that immediately. Anyone can understand that. You don't need to have a math background to understand that. Right. And so now we're really getting at the essence of why SKU is so important, which is, look, your best trades are better than your worst trades. Right. Which intuitively should be the case. But look, we all have access to databases. Just do the analysis. Right. I mean, how many firms, especially when you look at the daily returns, then it gets really interesting, right? I mean, Jeff, look at the SockChain CTA index, right?

Look at the daily returns. Do you know what the skew of the SockChain CTA index is, daily returns, or the SockChain STTI index? I do not off the top of my head. Thanks for putting me on the spot. Sorry. No, hit it. Yeah. Okay, well, I'll tell you. So I don't remember myself what the number is, but it has a statistically significant negative skew of daily returns. Both the SockTen CTA index and the SockTen STTI index have a statistically significant negative skew of daily returns. But not on a monthly basis? Or it but not on a monthly basis or it's even on a monthly basis roughly um you know i we don't really look i don't know at the top of my head if it has it on a monthly basis i'd have to check that yeah we do all of our analysis using daily returns just because look you get you have the sample sizes is so much larger, right?

But that's interesting in and of itself there, right? Like that you could have, it could be negative on a daily basis and positive on a monthly basis, perhaps. Usually it doesn't happen like that. It may be negative on a daily basis and kind of slightly negative on a monthly basis or even neutral. It's not going to change.

It's kind of like looking at daily returns versus monthly returns. Right? But part of me is, is that just a reflection of the right markets take the stairs up, elevator down. So even if you have risk control, you get some spikes down, you get stopped out immediately. So yeah, that would be my pro trend follower, pro, pro-soc-gen CTA index defense of like, okay, but on a monthly basis, it's not that bad. And they're just at risk of some huge

downspike days like last week. Sure. Absolutely. But as an investor, Jeff, you want to know that, right? I mean, you want to know that, hey, look, Jeff, put it this way. You want to invest in a CTA, right? By definition, there's some timing involved. You could invest today or tomorrow or next month or next year. To some extent, you have to time it. If a firm has negative skew, that timing problem becomes much harder, that's for sure. I talked about minimizing drawdown and how important that is towards achieving a high long-term compounded return.

The worst thing in the world, Jeff, that you want is, hey, look, you put your money into CTA today and it immediately goes into a drawdown. Now, the interesting thing, Jeff, is that the SockChunk STTI index, which is a short-term index. Yeah, short-term traders index. It's a whole bunch a short-term index. Yeah, short-term traders index. It's a whole bunch of short-term traders, right? Different short-term traders that all do different things, right? And that is a statistically significant negative skew as well.

Just something to think about, right? Like I said, investing, it's all about asking the right questions. So without knowing what's going on under each of those firms' black boxes, why do you think that is? What do you think they're doing that creates that profile? Massively, generally speaking. Yeah. Without me knowing, obviously, anything about what anyone else does, right? Again, I have no idea. I can just explain to you what the data says, and I can clearly tell you what the data says and what it doesn't say. As to the why behind the data, hey, I'll let you put your creative thinking brain cap on and explain that, right? Well, they don't use stops. Their risk isn't fixed. It's dynamic. All the above can create that. Exactly.

The stops aren't tight enough. I mean, they don't have stops at all. I can't say because we've always had a positive skew. And that's how all of our strategies have been designed. And if it's a strategy, the back test looks great, but it comes out as negative skew, it's out? Absolutely. It's out. And it has to be significant? It has to be, yes, the strategy level. So that's from a portfolio perspective, Jeff, I can't emphasize based on our analysis, how important it is to have constituents of a portfolio which have

a positive skew so for example we did internal research which shows that if a manager has a worst month greater than the best month over the past three years right which you just take a step back and think about this logically that shouldn't happen right like over three years okay you'll have good periods and bad periods yeah right shouldn't your best month be greater than your worst month you would think yeah okay so if your worst month's great in your unless you're an option seller but yeah right but if your worst month is greater than your best month over the past three years, hey, look, I can just say as being a trader for all these years, there's something amiss, right? There's something amiss in your risk management, right?

So we did a study using the Lipper hedge fund database, over 10,000 hedge funds, not just CTAs, long, short equity, global macro, everyone. We said to ourselves, okay, look, if over the past three years, a hedge fund has a worst month greater than their best month over the past three years, what does that say about their drawdown over the next three years?

And not surprisingly, what it said was those firms that have a worst month greater than their best month over the past three years well guess what over the next three years statistically they have a higher drawdown than they had in the past or higher than their peers higher relative to average statistically yeah no relative relative to the whole universe right So if I had a universe of 10,000 hedge funds, then over the past three years, if I look at the worst month to best month, that ratio, and I rank all the hedge funds, one to 10,000, based on that one statistic of worst month to best month, right? And I say to myself, hey, look, that the hedge funds that are kind of at the bottom or even bottom 50%, right?

What happens to those hedge funds over the next three years, right? How does their drawdown rank amongst those 10,000? Those hedge funds that are worst month, greater than best month over the past three years statistically have a much higher drawdown relative to the 10 000 hedge funds in the universe so let's talk a little bit about cta's got smacked last week with all this SVB bank stuff. Should you say SVB bank? That's saying Silicon Valley Bank.

But SVB rates crashed, bonds rallied, everyone was short bonds. So talk a little bit about, one, did you guys have a bad two days there along with everyone else? Was it quite different? And just explain that in terms of your model, how you viewed those two days of massive treasury action. Yeah. No, we made a small amount of money over those two days. Best performance, not necessarily indicative of future results. I'll throw that in there. Right. Yeah. I mean, look, what we do, we're not

doing a trend following, right? So we have look, we have a hard rule in our program that like, look, we don't we're not 200-day highs, 200-day lows, like we're not buying and selling them respectively, right? For many reasons for that. Because again, the risk adjusted return of that trade,

positive, but the alpha has slowly been kind of going down over the past 30 years, you know, that we've tracked it. So we don't do any trend following, right? So with that being said, yeah, it was definitely, vol definitely expanded very rapidly, which that's the part that makes it a little more challenging on our end because vol kind of like, you know,

expands extremely rapidly. Then position sizing, we obviously have modeled all this, but that can always be a little more challenging. You know, with that being said, definitely on this positive for us, that's for sure, because anytime there's a expansion of fear like real fear of the market which when i talk

about fear i really talk about implied falls not realizing and not just in equities across everything you're looking at exactly anytime you have an expansion in implied walls that always generally speaking represents a good environment for us so that's what you kind of saw a little bit. You saw that over the past couple days. And that moves you into those models that like that environment? Right, exactly. And how does that look? It's day to day. You're switching. These 14 are on the field. I think you have a sports analogy, right? But like explain that of that of like okay we're now moved into this environment last friday who's going on the field who's coming off the field yeah we have like a regime indicator whereby um we classify the market into four different regimes rising wall falling ball high wall low ball each market no overall just overall overall very broadly

speaking and then we identify first and foremost what regime we're in based on a proprietary volatility indicator that we've come up with based on implied vols around the world. And then once you've identified which of these four regimes we're in, then basically we allocate kind of more to the strategies that do well in averaging and less to the strategies that kind of don't do as well is how we approach it. And out of 38, like they're evenly split, there's nine-ish per bucket? Correct. By design, we have approximately even split across all four. Oh, and so it'll always be like, what does split look like is it ever everything in one bucket or there's always some hanging around in the other buckets no diversification we will never shut off three of the buckets and just have one that's not how you achieve a high risk adjusted return yeah well then you're you're guessing or you're not going to be able to react to the shifts

quick enough yes exactly like for example a good example I always use is March 2020. Clearly, we all know what happened in March 2020. But in April 2020, guess what? The market had a huge rally. Yeah. Right? So you've got to be able to switch regimes fairly rapidly. And that's what we did.

So like in March, for example, we had an amazing month. We were up about close to 7%, well over one standard deviation. But then most importantly, in my opinion, in April, we also made money, right? Which is a totally different environment because April 2020, the market rallied very strongly. But again, our regime indicator, it switched, right? So I'm waiting for you to say that you're sending the seven footers onto the floor then you're pulling the small guards off then you're putting the forwards back in yeah i mean using a sports analogy i mean look this is what any successful coach does right um you know if you want to use a basketball analogy that's exactly what they do right i mean

you identify what kind of regime or what kind of, you know, where you are in the game. And then, you know, you basically respond accordingly. And it's a calculated response. It's not an emotional reaction. It's something you've thought about ahead of time and you've calculated it, right? So, yes, Jeff, to your example, I mean, yeah, absolutely, right? I mean, look, I mean, you know, you want to throw your seven foot on there at a certain point in the game, very strategically, knowing that that seven footer, hey, he may not last the whole game. His endurance may not be the greatest. He may not be a good free throw shooter, but he's got other strengths. I mean, no, no player's perfect. Besides Michael Jordan. I mean, he had weaknesses

too, right? When he first started, the pistons kind of like beat him up. Yeah. Yeah. I mean, he had weaknesses too, right? When he first started the Pistons kind of like beat him up. Yeah. Yeah. I mean, you know, he, look, I'm not, I don't advocate that, but I mean, their coach had a strategy and it worked. Let's be honest. I mean, he didn't win championships. Let's not forget. MJ didn't win championships until later on in his career. That was just my duty as a loyal Chicagoan to point out that Michael Jordan was perfect. What did we cover? What do you want to share with us that we didn't cover anything? Yeah, I guess, you know, one of the things I like talking about a lot, just kind of more fun note is like, you know, the strong parallels again, between, you know, championship sports teams and championship hedge funds you know um you know um a while ago back at context last year um Derek Jeter was one of the guest speakers right I don't know if you were at context um not this year before that I didn't see him no okay well Derek Jeter was there this This is down in context, Miami.

And he was talking about what it was like to lead the New York Yankees. And he was talking about all the challenges of leading that team. And I thought it was a great talk because he talked about how you had Hispanic speakers and you had non-Hispanic speakers. You know what? They didn't really get along with each other. Very interesting. And I thought to myself, being naive and what, does it really matter?

I mean, honestly, if you can hit the ball really well, fine, you don't get along off the field. I mean, so what, right? But this is where, again, anyone that played competitive sports will know, it always translates into on the field performance, always. Right. And so one thing he said was, you know, the, what he did, you know, the Hispanic speakers, you know, I guess the coach or general manager said,

Hey, look, you know, you guys should learn English better. So you guys can all get along. And you know, what Derek Jeter said as a leader, he said, Hey, look, I actually want now the English speakers to learn Spanish better. Yeah. And that was actually the turning point right there is when he, as a leader said, Hey, look, you know what? The English speakers, they should also learn Spanish. You can imagine it got huge resistance. Yeah. Right. Right.

But it was just the thought, this is a real commitment culture. Right. Right. I play here. And it's something, look, I strive for that within our own firm. Like, look, I, I will never ask here. And it's something, look, I strive for that within our own firm. Like, look, I will never ask my employees, Jeff, to do something which I would do myself, right? Whether that's cleaning data, getting a Starbucks latte, let's say a tall pipe, right? I would never ask them to do something which I wouldn't do myself. Now, the reality is it may not be efficient for me to do some of those things because time is very valuable the whole idea is like i wouldn't ask them to do something which

i'm not willing to do myself and they can see that right they see that i have a committed to their kind of long-term growth and long-term growth means different things for different people right long-term growth for you may mean something very very different than someone else within your firm and that's okay right but the whole idea is the long that concept of long-term growth is something that is encouraged and ultimately that leads to greater loyalty and look greater loyalty it leads to results in the long run um that's for sure um so yeah that's i guess that's the only one i'm still torn on that or you just sign a really expensive superstar player right like you get you get messy on your team and you're instantly better even if he doesn't fit in with the culture

whatsoever or you get right so there's those i mean but you see this in the basketball world right now like they try and build these super teams brooklyn miserably failed um right we'll see phoenix what happens but yeah it's happening in real time in sports of like can you just pay buy your way into it right and other people would argue like well sure the yankees had the culture and jeter did that but they had the highest payroll and they did all the yeah i just like to argue the other side of it a little bit but yeah sure well hey i can say like the 2004 usa usa olympic team they definitely had the highest payroll yeah but they won the gold right no they didn't they won bronze oh well so that wasn't the real dream team that was the one before jordan and everything

yeah those guys won the one after them yeah yeah but they're still the most talented by far but i mean you know the los angeles lakers back in the early 2000s they had colby and shack i don't remember but they stopped winning championships at a certain point yeah yeah right um they get old yeah um but yeah i mean i guess you know i guess the one thing is is like you know going back to the sports analogies they always say the defense wins championships have you heard this yeah this famous saying amongst any coach always says this um there's literature debating it back and forth right but look if you look at let's go to baseball the teams that generally win the world series any general manager will tell you

jeff that good pitching beats good hitting any day yeah any day right basketball if you look at interviews with colby bryant he said himself he's like look we won because of our defense it's like offense like i may not have the opportunities to score you know what come winning comes down to good defense and you know um soccer you talked about messy hey um you know what now they're doing soccer stats like soccer saver metrics right where you know what the team that has possession the most they tend to win usually wins right so look there's in our field there's no difference right i mean what does it mean to play good defense it means to minimize drawdowns um you know that's really important

what does it mean to have possession the majority of time like in soccer those teams generally tend to win it means staying above your high water mark right then you're you're playing for a position of strength you're not playing a position of weakness anymore i was going to say you don't want to have i viewed it quickly as having possession being like having exposure you want as low exposure as possible, right? Right. But I mean, in soccer, for example, whatever team has possession the majority of time statistically tends to win. Yeah, yeah.

Right? So what's the analogy in trading? Well, it's basically possession means like staying above your high water mark. Because again, now you're in a position of strength, right uh you're not trading for a position of weakness right um that makes a big difference for sure um so yeah all right well we'll see good luck to your princeton tigers um have you adopted them you're an mit guy yeah um well you know I guess like you know my alma mater's basketball team um likely will not be in March Madness yes quite a while so yeah I've adopted them for sure awesome uh well thanks Kapil tell everyone where they can find you can they get your tear sheets and

everything when they go to your website uh it's not on our website for regulatory purposes, but they can just reach out to me directly. I'm on LinkedIn. That's the best way. We have a website, obviously. There's a contact information form on our website where you can kind of reach out to us and we just have to make sure that, you know,

you pass the hurdles necessary for us to send you. Understood. Well, keep it going. Keep controlling that risk. And we'll talk to you soon. Great. Thank you, Jeff. Thank you for having me. Yeah. Thanks for being here. Yeah. Take care. Okay. That's it for the pod. Go check out the rankings.

Thanks to Kapil for the fun chat. Thanks to Jeff Berger for producing and RCM for supporting. And we'll see you next week with Al. Peace. You've been listening to The Derivative. Links from this episode will be in the episode description of this channel. Follow us on Twitter at RCM Alts and visit our website to read our blog or subscribe to our newsletter at rcmalts.com. If you liked our show, introduce a friend and show them how to subscribe.

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