The Derivative - Opportunities in Option Mutual Funds with Russ Kellites

Episode Date: September 21, 2023

In the ever-evolving world of finance, change is the only constant. Like the shifting tides of the market, options trading has transformed from monthly expirations to weekly and even daily strikes. It's like going from a leisurely stroll to a thrilling daily marathon in the world of trading. Alongside these shifts, hedging strategies have also had to adapt, especially after the rollercoaster ride that was 2018.   On this episode of The Derivative, we're taking you on a journey through the financial landscape with none other than Russ Kellites from Alpha Centric Funds. From the intriguing story of San Francisco's economic landscape to the evolution of computer science and AI, to the transition from Goldman Sachs to starting a fund - we're covering it all — SEND IT! Chapters: 00:00-01:42= Intro 01:43-10:23= Hard hits in San Fran & Building blocks of A.I. 12:24-22:21= Hitching a ride w/ Warren Buffet & Designing a Fund 22:22-39:17= Diversifying Options & the 4/5 Quadrants of Volatility 39:18-53:07= Market Environments (Long & Short positions) 53:08-59:41= Market Participation 59:42-01:05:22= The value of time: It’s a long-term investment From the episode: Portfolios of Power Futures with Tim Kramer LJM – The Autopsy Follow along with Russ on LinkedIn and for more information visit alphacentricfunds.com 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. It's back to school season, and we're back with a great lineup the next few weeks. Battling a little bit of a cold here doing this intro, so I apologize. Might have been from the great trip to Philly we had. Recorded the live panel event there as a pod, so we'll put that up in a couple weeks.

For you to hear yours truly, moderating a panel with Tim Pickering of Hospice, talking commodities. Corey Hofstein of Newfound, talking return stacking. And Brian Maloof of Campbell & Company talking systematic macro. It was a lot of fun. Check it out. On to this episode, we're back talking options trading and volatility and the like with computer scientist turned mutual fund PM, Russ Kalaitis. We get into Russ's background as that computer scientist, what's going on in San Francisco. We talk Uncle Warren selling naked puts, and then dive into the various option strategies Russ uses in his model to do all sorts of things like market participation, upside capture,

and downside protection. Send it. This episode is brought to you by RCM's Outsource Training Desk, which does voice, electronic, DMA, all sorts of other execution services for groups from mutual funds to hedge funds to individual investors. 24-6. Six because the market is an open Saturday. So 24-7 minus the Saturday is a 24-6. Visit rcmallets.com to learn more. And now, back to the show. All right. Hey, everybody. We're here with Russ Kalaitis or Russell. What do you prefer? Russ? I always call you Russ. You're the one. Sure. All right. We'll go with Russ. Thanks for being here. Where are you in your lovely home there?

San Fran? I am right in the middle of San Francisco. So is it as bad as everyone's making it out these days uh you know that's a great question um i get the same question every time from chicago right we just had some woman snuck a gun into uh the white socks game under a fat roll she put a gun under a fat roll to get through the metal detectors and then shot someone during the game. So we got our own problems here in Chicago. But sorry. So yeah, to that question. So I can't have that happen. You know, parts are parts are pretty

bad. But the main kind of residential areas are really fine. In fact, the area I've been is, you know, really perfect. We've got very few problems. But have you seen people moving out en masse or is it contained? Is that just in the headline? Not really. Again, I think some of the areas that were sort of hard hit were kind of the downtown financial district, Soma, I think was hit pretty hard. We actually had a kind of an odd incident the other day here,

which is unusual. Someone was carjacked. Five people jumped in the car and drove down a street that actually you know we've got all these hills and this particular street just sort of ended there was a staircase that it picked up down below well they drove right off the end of the the car careened off of that did a somersault it was probably about three stories high and um landed on his roof wasn't like the 70s car chase movies in san francisco it looked a lot like that we had the commercial real estate guy in the pot a while back he was like he wouldn't buy commercial real estate in san francisco chicago or new york so we feel your pain. But yeah, I'm fine. I'm still living here in Chicago. Can't scare me away. Well, this made the news and everything. I'll send you a link to it.

Yeah, send it. After I've been here. But you went to school in New York, correct? That's right. So what was that like? You grew up in California, went to New York, or grew up in New York and ended up in California? I was actually born out west. I was born in Hawaii. We moved around a lot when I was younger. Army brat? Navy brat? My dad worked for Pan American.

So. Grew up in Seattle a little bit. We were in California. We actually lived in Afghanistan for a couple of years. Really? And then moved to Long Island, New York, where I mostly grew up. And then I went to Manhattan for school. And I went to Columbia and I

got a bachelor's degree there, entered a master's degree program that was all in computer science, focusing on on ai doing research in ai and then went into the mba program and got an mba in finance and marketing nice uh and not to insult you right off the bat and call you old but right what was it like back then with the computer science and ai versus today right must be different, or you think the nuts and bolts of it were pretty much the same? Well, we were really kind of at the early stage of, you know, the building blocks of what you see now. So,

you know, something that I was particularly interested in was natural language processing, which is, you know, the recognition of text words etc as opposed to um you know computer programming and direct database access so for example um you know we would work on a zoology database where you could query the computer, you know, how many legs does a panda have? And it would answer a panda has four legs, which was, you know, really kind of a pronounced step forward at the time. You know, of course, now we take that for granted.

And with chat GPT three and a half and four and, you know know some of the others uh the computers have really gotten you know much more advanced than that do you think it's mainly the processing speed and what they're able to do on the back end or is it they've made leaps and bounds on how it's handled right i'm sure you were dealing with much slower speed in order to run those queries and whatnot. Oh, yeah. The compute, as they call it, has increased dramatically. We really were bumping up against the upper edge of what was possible because of computation speeds. Of course, now I've got more power in my

iPhone than I do in the, you know, we use digital equipment's tech 20s back then. So there's a huge movement forward. The pod last week on the power trader, and he was quoting that it's 10 times the amount of energy is used for a ai query than a normal google search right so and then it's like something like a hundred or a thousand x i can't remember to actually train the model right right so it has consequences all this electricity reason all this power all the uh chips we need all the materials to do the chips, all that.

That's right. Yeah, I mean, I listened to someone the other day who was saying that chat GPT-4 took 10 times the resources of 3 and 5 would be 10 times 4, et cetera. But the results that you get out of that are, you know, tremendous. I mean, some industry leaders are suggesting that the reduction in workforce utilization is something like 30% kind of across the board for all these, you know, kind of more sophisticated human resource intensive roles, you know, marketing and consumer. Lawyers. Communication.

Yeah. Lawyers. Accountants. Yeah. So what made you go down the finance path instead of the computer science path something in there said like yeah this isn't for me it really was that we were bumping up against the the edge of what was what was possible at the time i mean we spent you know tremendous amounts of manpower getting to the point where

we could build this sort of a database and be able to access it through a natural language. But, you know, the next, it looked like the next big movements forward, the next big leaps were probably going to be 10 or 20 years off. And I, I just didn't think there was a lot of return and spending a lot more, you know, spending the next 10 or 20 years making these very small incremental gains. And, you know, finance numbers were really pretty interesting to me. So I went to business school. And then out of there, got into, where was it, Goldman Sachs? Right.

So you must have been doing something right to catch someone's eye over there. Well, I think large financial firms are really just kind of catching up to the progress being made in the computer side. So they were looking for people that had technological capabilities and were good with numbers and that sort of thing. And so. Right. Just like they're looking for high end coders and whatnot today. Yeah.

It's really, you know, frankly, it's been pretty consistent. It's been a good way for them to try and separate themselves to get some competitive advantage. So take us through the backstory from got entry level or whatever level job at Goldman through the next stages to eventually starting your own fund, running your own fund. Well, I moved around Wall Street a little bit.

It was Goldman and then Merrill and then some bulge brackets and boutiques. And I guess my last job at a large, it was an international investment bank. I was running the structured finance group. So we were doing cross-border, complicated trades involving derivatives and accounting and tax and things like that. And I'd been trading for my own account for a long time. And in fact, I was doing some options strategy trades and there were really kind of two components to it one was picking a an instrument stock

and the other was the structure around that stock and it was it involved primarily buying puts and calls and my my technique for choosing stocks was working pretty well. But I wasn't really making any money. And at the same time, we were approached by, actually it was Goldman, who was doing large trades for Berkshire Hathaway. And you can go back and see this in the press at the time. But Warren Buffett was selling large out- selling large uh out of money put options on major indices it was the s&p nasdaq russell uh the nikai i think he was doing something in europe as

well not uncle warren he's famously like anti-derivatives to the general public even though on the back end yeah he didn't didn't like them. He sold them. But he's selling... Sorry, I meant he was selling puts? Yeah, yeah, exactly. Naked? And so they were million-dollar trades, I think, at the time. And so gold was the other side of these, but they were running out of the exposure they could take

to warrant to Berkshire Hathaway. So they were looking to offload that. And so we did some analysis looking to take on that exposure from them. And it was around then that I realized, or in fact, it was then that I realized I was just on the wrong side of the trade. When I was buying, I really should have been selling. And so I kind of revamped that half of my equation to more focus on the premium collection, the premium writing. Preston Pyshko And you're saying from a

Flo's perspective or just you saw Warren earning premium and said that might be a better gig? Warren Cullen Yeah, it was really that. It was, you know, he's obviously a really smart guy. And if that was the side of the trade that he was on, it's a good reason to think it's a good side of the trade for me to be on. Good way to look into it more. Yeah. And so then said, you peeled out of whatever firm you were and started your own? oh well so this was end of 2007 going to 2008 so there was you know as you know there was this uh you know financial meltdown yeah hopefully didn't sell puts right my my group was eliminated so at that point i just turned to trading for my own account

um and then eventually said hey this is good. I'm making progress in my models to roll it out to customers. Right. So, you know, I've been helping out friends and family. And in 2011, that turned into a hedge fund. In 2016, we turned the hedge fund into a mutual fund, which is, you know, the fund we're working on now. So the idea behind the fund and your overall strategy so well let's back up is your how different is what you do today from what you were originally thinking up and and designing for your original fund So I developed a model to analyze what the best positions, options, strikes, explorations were to buy or sell.

Back tested that and then ran it through an AI engine for further refinement. That's really been, that model has really been the cornerstone for what we've been doing ever since. And that really hasn't changed. Was it the entire universe of single name stocks? No, really just the S&P 500. Got it. And it ingests the entire universe of strikes and tenors? Right.

Yeah. And the advantage of that was that there's a lot of liquidity. The premium options were really pretty consistent. And, you know, there was a lot of strikes and expirations for us to work with. And so that's changed a bit. You know, we went from really kind of monthly expirations to weeklies and now really pretty much daily. So there are really strikes for every day of the week. And so that's given us an opportunity to take more positions and further refine what we're doing. we find our hedging strategy a bit, really quite a bit, is a reaction to what happened

to the market in 2018, where we had, you may recall, Volmageddon, when the market dropped about 4%, but volatility spiked, actually went up 100%, over 100% on that small downward S&P. Real quick backup. That's interesting. I hadn't thought of that. If you're feeding this data into an AI model, there could be an argument of like, I don't have enough data from monthly expirations

to give the model enough to work with. Now you're doubling it with twice a month. You're quadrupling it with weeklies. You're whatever the number is. 16th thing with, or 20th thing with dailies. So now the model has even more and more data to work with and can be better refined, right? Is there some sort of statistical significance in there?

Like the more data I have, the better? That really hasn't affected so much how the model works. I mean, we're really looking at things like what the movements in the markets are like, the volatile market, say, versus the amount of volatility priced into the options um and looking over the landscape of that to see where the mispricing is is the greatest where we take the best advantage of that now you're you're not an option guru unless you call it the vol surface i was trying to avoid the lingo that's all right the um but yeah like right and i think of those 3d heat maps of yellowstone or something right of like all these peaks and valleys and blue and orange and red right of like that's what the balls surface and you can say okay this doesn't make sense on this

one slice right it should maybe be gently rising gently gently falling. You could have some slope, but if there's a big peak and a big valley on one slice, something's amiss there. Sure, sure. And the heat map tends to have a gradual gradient type pattern, but you still look at where the price is high at one expiration versus low and another expiration and take advantage of that um and so it strikes me that it's pun intended strikes me that it's not that easy right like so just because one's more expensive than the other doesn't necessarily mean the one's overpriced and the one's underpriced there may be good reasons for that

so kind of how do you view that of like, okay, this is the market is pricing it there, right? So am I, do I have a better model? Am I identifying just the mispricing or am I identifying an opportunity? Right. Well, we feel like if we're taking into consideration, you know, kind of the known external factors that affect the market, and we try and take a balanced approach. So rather than just kind of selling something outright, we'll buy another thing to hedge. So even if we're wrong, we're really trying to look more at the differential between those things rather than kind of the absolute of one thing versus another. And that's a good segue. Is that why options

instead of, right, you could have run single stocks into the model. You could have run global stock indices, been long or short stocks. Why did you settle on options? Because it's cliche, gave you more optionality, gives you more, like you were talking about, I can know that my loss will be truncated here because I just spent premium. We found that the liquidity and the consistent differential between the amount of risk embedded in the market versus the amount of risk you're being paid for in the options, that differential tends to be pretty consistent in the broad indices. Whereas it can move around a lot more with individual stocks. With individual stocks, you get that idiosyncratic risk. You know, it's just really hard to tell what's, you know, what's affecting an individual stock. It could be, you know, the CFO is about to step down or, you know, he's got some health

problem that isn't widely known. You know, earnings miss could come out or earnings beat could come out. There are just so many factors that can affect an individual stock, whereas, you know, the broad market tends to diversify all those idiosyncratic risks. I could argue that these days, like those top 10 stocks have mastered taking away all those idiosyncratic risks, right? That's why they just keep getting bigger and bigger. If you're a trillion dollar company, you're not going to move 10% in a day on some unknown risk, right? They're going to telegraph. Well, look at NVIDIA just over the last couple of months.

You know, they had a day a month or so ago where they were up 30%, 40% or something. And then on earnings, they were up 10%. I think they gave a lot of that back. But that's the sixth largest company by market cap, I think. Right. But to your point being, it kind of isn't worth it to trade that.

If you're right, sure, you're going to make some money. But if you're wrong, you could be really wrong in that scenario. Yeah. Yeah. You know, I'm sure there are people that, you know, look at the large companies and do the deep dives and, you know, have a really good handle on, you know, what to expect, what's going to affect the stocks, but that's just not how we want to operate. Right. You want to be the good boring, the good type of boring, right?

So we kind of buried the lead a little bit here, but let's take a step back. Let's take a step up 30,000 foot view, talk about the trading strategy overall, what you're trying to accomplish. And then we can dive into some of the details. What's the 30 second elevator pitch on what you're trying to do with it? Well, I think the principle underlying what we're doing is really taking advantage of that differential that I mentioned. So it's the differential between the amount of risk in the market and the amount of risk you're being paid for in the options. to an insurance company, say like a Geico, where if you have a car and you insure it with maybe Geico, you are paying them, say, $1,000 a year for insurance. But when they take all the people like you and they add them all up and they average them, the cost embedded in that policy is

more like, say, $800. And so they've got this $200 dollars, 20 percent profit margin. It's really the same thing with options and options is really the only financial instrument that I can think of aside from, say, insurance policy where you've got that positive expected future value on a risk adjusted basis. So with stocks, you know, if you buy and I sell, if it goes up, you win, I lose, vice versa. And it's a it's a random walk with bonds really the same thing and when you take when you take out the default rate and the recovery rate you're you're left with the risk-free rate of return but with options you really got that that profit margin built in and so what we're trying to do is find the best way to

take advantage of that profit margin find where where that profit margin is the highest and sell those policies or where it's the lowest and buy those policies. So like Geico with less funny commercials? We don't have a Geico. And so the whole concept there is I need to be widely diversified, right? So is the index giving you enough of that diversification? Or you're saying it's not just the index, but different strikes, different tenors? Well, we think the index diversifies out a lot of that risk, that idiosyncratic risk. So, you know, if a hurricane goes through and, you know, wipes out NVIDIA's manufacturing plant, that's going to be a pretty

bad event, but it's the impact on the S&P 500 is going to be pretty minimal, you know, so we're really diversifying out that idiosyncratic risk. And then how do you think about that? Shouldn't the option already reflect that pricing? Or you're saying there's built-in skew that investors are overpaying for protection or something of that nature that kind of builds this mechanism? It's really the latter. So there really are no natural sellers of options, just like there are no natural sellers of insurance policies. There are natural buyers of options.

The value of the U.S. equity market is $30 trillion or something. It's probably even larger now. But you've got all these insurance companies, pension funds, endowments that are long the market.

And so they need to buy protection to protect against downside. You know, so your retirement funds need to buy downside so they can, if the market is up, they can still pay the obligations they've got to all their insurers, all their pensioners. So they're natural buyers, but there aren't really any natural sellers on the other side. And so that's why you've got that embedded premium, that excess risk premium. And so talk a little bit, but it's not always like that, right? So in a risk-off environment that can get, or vice versa, can move around. So we talked offline, you have a bit of a construct of these four, the markets always in one of four quadrants. Can you talk through that a little bit, what those four quadrants are and how you kind of view what makes them different and what you do different in each of them? Sure. So our models are attempting to look at the direction of really the two main components of

what we're working with, the underlying market and the volatility that's reflected in that market. So the S&P and the VIX for simplification purposes. And so we're looking at whether we see the market going up or down and whether we see volatility going up and down. And so depending upon that, we'll modulate the amount of risk or the type of positions that we're taking on. When the market's going down, we, of course, try and take less market exposure, you know, probably less short S&P put exposure, maybe even go long S&P puts. Similarly, when the market's going up, we'll try and take, you know, long S&P exposure, less short call exposure. And then when the volatility, we see the volatility going down, we'll try and take more short volatility exposure. We'll try and hedge that, of course. And the opposite, we see volatility going up. So I lost the four quadrants in there. So quadrant one. So the four quadrants are,

you could say, kind of across the top. It's what's the market doing up or down. And then across the side of what's volatility doing up or down. And so you've got these two factors times two is four dimensions. Got it. So market up, vol up, market up, vol down, market down, vol up, market down, vol down. Exactly. And so that shifts how often? Monthly, in real time in your model? It really varies.

There are periods where we'll be in one quadrant. And the quadrant where we find ourselves most frequently is up market, down volatility. And in general, you see those two instruments inversely correlated. And that's the case. They're inversely correlated about 80% of the time. But so probably about 65% of the time it's up market, down volatility probably another 15 it's up market up volatility and the other you know 10 each say and down market down volatility up market up volatility um 65 15 10 10 100 good work off the top of your head there um so 65 percent up market down volume right and to your i think you answered i was kind of saying does the Off the top of your head there. So 65% up market down volume. Right.

And to your, I think you answered, I was kind of saying, does the, yeah,. We can be in that quadrant for long periods of time. If you go back to 2020 from, say, early March through middle, well, even the end of the year, we really only shifted out of that quadrant for a couple of days kind towards the end of the summer, and then a couple of days in the fall. So that was kind of nine months of the year where we were in one quadrant. Not 2020 with COVID, you mean 2019? No, 2020, once we got through the big drop in March, the market just, you know, we were down, what, 25, 30%. The market just rebounded and really pretty consistently came back. And so in those environments and overall, let's take a step back. So you're trying

to capture as much of the market upside as possible? Right. And avoid the downside as much as possible. Right. And avoid the downside as much as possible. And so that seems like it makes you different from some of these other, right? So if I hear that upfront, I'm like, oh, you're kind of in this hedged equity bucket, right? Of like, I'm participating in equities with a bit of a hedge. Right. But from what you said before, the elevator pitch, it's not quite like that because you have these other option strategies that you're trying to generate some income from and generate some different types of returns than just owning the stocks and hedging them or owning the index and hedging them. That's right. The hedge equity funds that we see really kind of have one approach, which they use consistently, really all the time so they're typically uh the best you know the vast majority of fig ones are long in equity position and then they'll a lot of them will do a

costless collar around that so they'll they'll buy a put underneath they'll sell a call up above and they'll sell another put down below to to balance out the the economics um and there are you know some very large funds that do that but again it's just sort of sort of one thing and so they do well within that you know the top part of that band so when the market's doing up going up and they're up you know say less than five percent for the quarter they'll do they'll do pretty well and track the market. When the market's down between 0% and 5%, they'll typically be down 100% of the market. So you really get kind of that 100% correlation between, say, plus 5, minus 5, or wherever they place their bands, where we're really doing really four things to add economics, five things really to add economics to our fund.

You know, one of them is this premium capture that I mentioned, where we're selling positions around the market. And so that'll do well as long as the market stays within a band, say, you know, up or down. So that contrasts really dramatically with the hedged equity, which are really kind of linearly correlated with the market within that, you know, plus minus 5%. So we'll have economics really that are pretty consistent from that strategy as long as the market stays within up a couple percent, down a few percent

when we're doing premium collection. It's really a weekly position that we're taking. We take those positions three times a week, so Monday, Wednesday, Friday, we're dealing with the three expirations. So we're looking for a minimal amount of market movement over the course of a week. And since we're putting those positions on three times a week, we're really rolling the positions constantly. So the average life of those positions is about three and a half days. So the market really has to move pretty dramatically for those positions to get hurt. Is it fair to just say that's classic

option selling? Right. Yeah, it really is. But on both sides? Right. So in theory, you're a little bit hedged there. If one side goes, the other side's going to erode. Exactly. It's impossible to lose money on both sides. So one side will be profitable. And that's an important part of what we do.

But it's one part where there are option premium funds that do just that. And so they'll do that and they'll lever up, you know, 10, 15 to one. There was a fund that got hurt pretty dramatically in 2018. They were levered, I think it was 60 to one. So they'll take a lot of leverage to get consistent returns, which look really good until something dramatic happens. And so that dramatic event, that once-in-a-lifetime event happens every couple of years now. We will put a link.

We did all, we called it an autopsy. That was the LJM fund. So we have a great blog post doing an autopsy on that funds demise. Right. Yeah. Which we'll put in the show notes of this. But yeah, like you can get in trouble in a hurry there. So that was 2018.

And there were a couple in 2020 that had the same sort of problem. So that's one part of what we do. Another part of what we do is we look for some market participation. And our market participation component is typically around 40 percent so that's going to give us about 40 percent of the upside and downside but through the entire range of the markets of the markets up 10 it would be you know 40 of that 10 the market's down 10 same thing but there we're using our directional indicators to try and modulate that. So we're trying to get a little bit more of that when the market's up,

a little bit less than that when the market's going down. And when the market has these long-term trends, we do a little bit better during those cycles. When it's vacillating on a daily or by daily basis, we can get whipsawed and get hurt on those positions. So we're looking for the market to go up, we increase our participation, the market goes down, we lose a little bit more than we'd like. And that's accomplished via the options or via just holding futures? A little bit of both.

Just holding the future. And so sometimes that'll ramp up to close to 50%, sometimes down to 30%. Right. In that band? Right. It's usually kind of 40% plus or minus 10. And how did you arrive at the 40% target? We were looking at the overall risk of our portfolio, looking at kind of how much risk

we wanted to take on. And that was where we came out, 40 plus or minus 10. And I think it seemed to be a good counterbalance to what other funds in our space were doing. We saw hedged equity funds, for example, that seemed to have kind of that 50 percent correlation. So that seemed like it would be a good counterpart to those funds. And then you sort of mentioned it. Is this your understanding? I think it's mine. Right. Some of the hedged equity products, they're selling the call in order to buy the put. So that's capping their upside. So if the market's up 50% a year, they might only get 10%.

Who knows where that top upside call is? Depending on what their expirations are. So if they're doing quarterly, they would be limited to that 5% on, say, a quarterly basis. If it's annual, it would be limited on an annual basis. So a lot of people do sort of a quarterly reset. And it'll be like clockwork. So December 31st, they'll put their business on that run through March 31st, et cetera.

Right. And I feel like a lot of those programs haven't had a bad run because they haven't seen either this big up market where they got capped out and everyone's like, what the heck? We only made 8%. Why?

Or vice versa, like it goes through that short put on the bottom and the loss is great. Be like, okay, I only lost only lost right if they're down 10 maybe they only lose eight if they're down 40 they might lose 38 so it seems like a uh right i mean there are markets that can be really bad for them like a you know like a market that just declines five percent a quarter four quarters in a. So they'll be down 20% in a year when the market's down 20% in the year.

Right. Nothing hedged about it. Yeah. Versus you guys, because you don't have the full exposure, by definition would be some percentage. Right. In fact, depending upon the exact circumstances, a slow grind down of 5% a quarter

could actually wind up being a good year for us. Well, I want to talk through some of these different environments and how you view them. And so we were talking about the... Yeah, so it was one was premium capture, two market participation. Right. So the third thing we're doing is an upside participation. And so what we're trying to do is set up positions so that if the market does

ramp up, we can take a little bit more advantage of that. So a structure we like for that is a call ratio. What we're typically doing there is we'll use a what we call one by two so we'll be long one call near the market and short two calls further out typically those positions are about two months to expiration the long is about 200 points out of the money and the short is 100 points out of outside of that so that position will be profitable all the way up to 400 points above the market. We typically do those two to three months in expiration. And we'll do them typically every other week.

So we'll have four to six of those on at a time. So kind of every other week going out for two to three months. And then we'll stagger the strikes as well. So the first one, the two-month might be 200 points above the market. Two and a half might be 250 points above the market. The three and a half, three months might be 300 points above the market, et cetera. So even if the market does really accelerate through that first earlier set of positions,

we could capture the economics on the longer dated positions. And do you view that as, so it's a bullish trade. It needs the market to move up in order to make, in order to be profitable. Right. And so we're doing those because we're selling to and buying one way we position them uh we're doing those pretty inexpensively we're typically getting them for it's about a dollar um a dollar to two depending really upon the ball surface yeah what's going on in the market. You know, we've actually paid up a little bit for some recently, but typically they're pretty cheap.

So even if the market doesn't ramp up into that lower long position that we have, the economic impact is pretty modest. And then that's a good example for people to try and understand. So I'm buying it for, call it a dollar. What does success look like there? You're selling it out for how much? Well, we did well with those, say, in the third, second, third, fourth quarter of 2020, where we were buying them for a dollar,

we were getting them for free. We started selling them out around $20. We were selling them all the way up into the 40s. I think the best we've ever done is 60. So, you know, the economics can be pretty dramatic. But at some point, if it goes through the upper strikes, it starts to come back down and it can go negative. So what we're doing is we'll, you know, depending on where the market is and the time to expiration, et cetera,

we'll be selling those out as they start to become profitable. Sometimes we sell too early. We rarely sell too late. We're, we're taking economics when we can. All right. Number, is there a fourth? I think you said five originally.

This is the old, who was that politician? You said three things and could only remember two of them. Yeah. Well, it was actually five, but so the fourth, what was that guy? The Texas governor,

Rick Perry. I think that's who it was. So the fourth is, is downside protection. And there, you know, The Texas governor, Rick Perry. I think that's who it was. Does he do that? So the fourth is downside protection. And there are a lot of ways we can protect against downside. When volatility gets cheap, we'll be buying puts. We can buy those outright. We can buy them in verticals.

So we'll buy a put near the market and sell one further from the market to minimize the cost a little bit we can do uh we can do calendars where we'll say um buy one for a month out and sell one for a month further out or do the opposite depending on what the market, the economics look like. We like actually hedging by going long VIX futures. So we'll do that frequently, depending upon what the volatility space looks like. Sometimes we'll actually even, in fact, frequently we'll go short volatility. And when we do that, so we'll sell a VIX future.

And when we do that, we'll take an offsetting position. And so there are a couple of ways. There are three ways we can do that. We can sell volatility, say sell a VIX future, and sell S&P futures against that, modeling that there's a certain relationship between how much the VIX moves against how much the S&P moves.

And so we're typically doing kind of two to four to one. So we'll sell, you know, say a dollar worth of VIX futures and we'll sell two, three or four dollars worth of S&P futures against that, expecting that the S&P will go up less than the VIX will go down. So that's not necessarily part of the downside participation? It actually is in that you'll see it

really earlier in the month where the market would actually move down a little bit but we would make really earlier in the month where the market would actually move down a little bit, but we would make money on the decline in the S&P and lose less on the decline on the short VIX. And so when the S&P is down two and the VIX is down one, that would be a profitable trade for us. There were days actually when the VIX was high enough as a starting point where both the VIX and the S&P were down. So we made money on both sides of that trade. So the third way we do that is calendar. So it will be short or long, the front month,

and then the opposite on the back month. So for example, we might be short a dollar of the VIX 30 day and long a dollar or a dollar 10 or a dollar 20 of the VIX 60 day. And that, do you view that as a long VIG or it's short fit? Like what's, it's totally dependent on the curve. It really depends on the curve. What we really like to do is when you've got the right volatility structure, we like to take the opposite where we're long the front month and short the back month. And so that would be, you know, what you'd call long vega.

Of course, if we're short front, long back, it would be short vega. And then the third thing we do is we will go short volatility, but we'll, so it'd be just short of VIX future, but we'll go, we'll go long VIX calls against that. And we typically do that in a pretty high ratio. So we'll be long VIX calls, you know, two to one, three to one, four to one. Currently it's five to one. And so in a March 2020 type thing, that's going to do much better than the short does worse. Absolutely. All right.

So that whole bucket under downside protection is designed to be. If the market and this happened with the fund in March 2020, right, the market's down sharply. These which we don't get too far in the weeds, but we do here on this podcast, it's fine, but they have convexity. Right. So you're you're maybe short the less convex thing and long the more convex thing so the right and so i think one of the the key aspects of what we're doing which again differentiates us from many of the others like you mentioned the hedged equity is we'll move around you know we'll change our portfolio based on where we are in that on that quadrant uh on that on that four by four grid and so for example in March of 2020 we went from being you know short vol short S&P to long vol to long vol long S&P and so we were losing money on our

long S&P position but we're making up for it in the long long fixed futures position and there again it was kind of it was about a three to one that we had so we were long one long VIX futures position. And there again, it was kind of, it was about a three to one that we had. So we were long $1 VIX, long $1 of S&P, but the S&P went down 25-ish percent. The VIX futures went up 400%. So we right, 400, 450. So we made

16 to 1 on our VIX futures where we were losing 0.25 to 1 on the S&P. And I want to circle back to that because I think that's important, but let's finish out your five pillars here.

Right, so the last, and this is really something that's probable for us recently. We've been doing it for years, but it just hasn't really added much to our economics because what we're doing is in the derivative market, we don't actually purchase positions. We post collateral against those positions on margin. And the margin rates on the instruments that we trade is really very favorable. So it leaves us with typically 70 to 80 percent of our NAV in cash, the rest being what we post against the collateral against our positions. David Steinbergen So that cash recently, starting really kind of last year, is now earning interest income for us again. Starting last year, it was in the 2% range,

it's gone up to 4%. I think we're getting 4% to 5% on our cash balance now. And so that just drops right to the bottom line. Now, we've always done that. It was profitable for us back in the mid-teens. But then, of course, with zero interest rates, it really didn't add much for us. So that's essentially like the fund is a 90-10 fund or something, right? Or a 75-25 cash alts fund, right? And that 75 is income producing T-bills. It really is. And that touches on, you know, what we think is an important part of what we're doing,

which is, you know, we want to have a return. We want a positive return. We want to do well relative to, you know, what we look at really is not the S&P so much as a balanced portfolio, like a 60-40 portfolio of S&P versus debt. We're not really just looking at the return itself, but we're looking at the volatility of our returns versus the volatility of that, of that basket.

And we think because of these five components that we've got embedded in our fund, we really compare pretty favorable beyond volatility perspective relative to that 60, 40 basket. Certainly than, you know certainly than other funds. Right. And if I'm being critical, I'd say, okay, but I could lower my volatility by just doing half the amount of S&P, right? And could I get the same or similar volatility if I just did half? But would you come back and say, well, yeah, but then you're not getting the ability to flip

the sign in a big down move. You're not getting the ability in a flat market to earn some of this option premium, right? So help me understand that of like, why wouldn't I just do 40% S&P and get lower volatility and lower return? Like your pillar two, like I could just do half the s p and get nearly the same place i i think you'd have to look at how the 60 40 performs versus some percentage of the s p and i imagine there's a a point there where they they equate equate but the the 60 40 is going to give you a lower volatility than the S&P itself will, whether that's just S&P or some percentage S&P. And we think that lower volatility is important because it lets an investor or a financial advisor keep their investor in the fund when times get really tough.

So if you look back at times like, say, early 2020, when the market's down 20%, 25%, 30%, there were countless investors that would call up their financial advisor, do it themselves, and just exit the market because they'd had enough pain. They don't want to deal with it anymore. And so they wind up, because of the volatility, getting out at exactly the wrong time. And the market turns around and goes up 30, 40, 50%. And so they turn around,

get back into the market exactly the wrong time. And so the lower volatility we think lets an investor stay in and weather that storm a lot better. And then, so talk through, we kind of hinted on it, like how you would expect the strategy in some different environments. So, right, like 2017 type, very little volatility, markets just crawling, you know, higher, higher, higher, higher market. I think we went 11 out of 12 months and six months without a 1% down move in 2017. So that kind of market, you're probably most of the time in the up market, down vol quadrant, and are expecting what, to have that maximum market participation? Yeah, that can be a very good market for us because, you know, our market participation is doing well.

If the volatility is low, there aren't a lot of, you know, the volatility of volatility, if you will, you know, is low, then we can do well with our premium capture. Our upside participation could be kicking in. We're wasting money on our downside protection, but the other should more than offset that. And then with high interest rates, getting, say, 5% on 70% of the portfolio can add 3.5% to the bottom line, you know, before we do anything.

So that could be a good market for us. I think really kind of the markets that are difficult for us are where, you know, we kind of touched on this before, but it's really kind of where we get whipsawed. So, you know, we go from an up market to a down market. So we're changing our participations and our structures. And then we work back to an up market and we revert back to a down market. And so the whipsaws can really wind up eating our economics. You know, we had we had kind of a tough time in 2020. You know, we outperformed the market, but sorry, 2022, we outperformed the market, but, you know, not as much as we would like. And really the reason for that is that our, you know, while we're buying protection on the downside, as we entered the year,

volatility was priced pretty high. In fact, it was probably pretty fairly priced, maybe even overpriced. So as we were buying protection, there really wasn't a lot of upside for it. There really wasn't a lot of room for it to go. And then I know you said you're wasting money buying protection, but I know you don't really believe you're wasting that money, right? So you have this slow grind upward, probably going to be good for the strategy. You're going to almost max participation, plus some option, plus some slow grind downward 2022. You said not that great, but to me, like you're only going to lose somewhere half ish.

Right. Of what the of what the market did because you're only participating 40 so even if those option strategies don't kick in they're not going to bleed enough to turn right into a full s&p loss or something um so i know yeah clients probably don't like that of like hey i can't eat relative performance right it's the old line of like great you lost me half but i still lost uh and then the third scenario would be a sharp move downward. So in a sharp move downward, that's where I come in. I don't think you believe that you're wasting money buying that downside protection. Right.

Well, right. I mean, I said wasted. It didn't fall down to our bottom line. Yeah, yeah. Just like an insurance policy, you know, when you're writing your check to geico if you haven't had an accident you might you know it was it was important that you had that position but it didn't really do a lot of good but um you know so so a good market for us can be well you know a good example is is early 2020 where um you know we were coming into the year in a pretty normal environment.

It had been pretty calm, so volatility was priced pretty low. The VIX was in the 12-ish range. And so as the market started to turn, it was a great opportunity for us to buy protection very economically. And so we started buying those VIX futures as the pricing was around $16. And then the market just really started to drop. The price of protection in the VIX really took off. And so, you know, the price of those positions went from, you know, 16 to, I think we started, I think we held on to them all the way up to 82. We added on the way up.

But, you know, we sold some out at the top, which was, well, they expired at 82. So it's, you know, kind of a fourfold increase in the value of those. So that can be a good environment for us where, you know, you're kind of coming out of this, there's this calm before the storm and there's an opportunity for us to acquire some protection inexpensively.

And then of course the market just, you know, flips and we can take real advantage of that. It seems like that's the answer to a smart, smart ass like me. Like why wouldn't I just do, there's plenty of things I could do to get less volatility, right? Why do I need to do all this? Like, well, because I can, right. I can change the sign in a big down move like that, a big spike down. That's true. And we do think we compare on a

risk adjusted, so volatility comparable basis. We think we compare pretty favorably to the 60-40 portfolio, which is really kind of a benchmark. We could look at different scenarios of how long you'd have to be the S&P to outperform us, I think you'd still have more volatility. But in fact, I'm certain of it. The only way to get the return and lower volatility is by adding that debt portion, which of course, you know, hurts you pretty dramatically in 2022. Right. A lot of those logic is based on before bonds were super volatile, right? So even if they're clipping along a nice return, if they're super volatile, it's going to make that portfolio a little more volatile, which breaks a lot of that modeling.

Thoughts on zero DTE? It's an interesting space. It's not one we've really gotten involved in yet. Meme stock, option traders, all that stuff. Yeah, it's not our thing either. Leave it to the pros. Have you seen the...

There's a movie coming out about the GameStop stuff. Oh, yeah. It looks fantastic. Like, it's got Ken Griffin and all the Fed and the guy from Melvin Capital. Not themselves, but actors playing them. That was an interesting story. So, yeah.

I'm going to try and get that going. There's some about crypto and SBF coming out as well. Oh, yeah. I'm sure they're lining up, paying to get that going um great russ but this has been fun thanks for all the info um what's your um just quick before we go like what's your thought on you're running the private fund you know each investor maybe on you know outside your family and friends you know people personally and you're explaining it to them versus mutual fund model if you don't really know who's buying it or what their motives or questions are like has that

been hard for you or it's recommended to recommend all fund managers do it um no it's it's interesting i mean i think i think that the biggest difference between the you know the hedge fund and what we're doing now, and we've been doing this since 2016, so coming on seven years, is the daily price discovery. So with the hedge bond, we had an entire month to work on achieving economics. 15 days after the end of the month, the economics would come out. A week or two after that, investors would want to talk to us. And so then, you know, maybe they'd subscribe or redeem. They would put in the notice at the end of that month. And so then the funds would flow at the end of the following month so really there was

kind of a two-month window for ebbs and flows of economics the the communications around the fund were a lot more sporadic um here you know if we have a if we have a good day investors see it immediately if we have a bad day investors see it immediately. If we have a bad day, investors see it immediately. We'll get calls from investors, well not from investors, from FAs, asking why wasn't the fund up more or why was the fund down or

whatever, really kind of on a daily basis. We've kind of managed to work with the financial advisors so they kind of know what to expect. And they can moderate how they communicate with their investors a little better. But it strikes me, what you're just saying, it doesn't make sense a lot of time to judge funds like this and some other alternatives on a day-to-day basis right like if i sold this option with an expectation that it's going to do x over the next 45 days on day five if it's losing money and i'm like i'm out right that doesn't make a lot of sense it's like being a distressed debt mutual fund wouldn't make a lot of sense right like month two people are like oh this isn't

working like no the whole point is we need time in order for it to play out that's that's exactly right and that's the point of a kind of low volatility um more lightly correlated fund it's a it's a long-term investment that lets someone put their put their money into it and watch it grow over time if they're looking for you know the the fast profitable trade then you know they've got to turn to the cryptos and the memes and things like that you know they can you know maybe make 50 in a day or whatever the crazy numbers are of course it works the other way as well right all right the most important question did you have all of your hair when you started this one i have a lot of it still yeah right because then we'd be really worried yeah i had as much hair as you whoa all right so there you go

folks don't be an option trader for a living you might lose your hair hi russ it's been fun so you don't have to exactly appreciate it that is true right right? Like you're looking at all this day to day. You're taking on this volatility. You're analyzing it, right? So the investor doesn't have to do all that work. That's right. Awesome. Appreciate it.

We'll talk to you soon. Thanks, Jeff. Appreciate it. Thanks, Russ. Have a great day. All right. That's it for the pod. Thanks to Russ. Thanks to RCM for sponsoring. Thanks to Jeff Berger for the pod. Thanks to Russ.

Thanks to RCM for sponsoring. Thanks to Jeff Berger for producing. Come back next week. Hear our live panel from Phillip. It'll be fun. Peace. You've been listening to The Derivative. Links from this episode will be in the episode description of this channel.

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