The Derivative - High Frequency Trading and Systematic Macro Funds with Matthew Hanna of Teza Technology

Episode Date: February 10, 2022

There are not a lot of Florida Gator fans in Utah, just like there are few firms that move from high-frequency trading (HFT) into the mutual fund space. That's why Matthew Hanna from Teza Capital Management is here to talk us through what it is like running a systematic macro mutual fund. He reviews Teza's HFT and prop trading roots, how Teza’s algorithms approach the market, all while mixing his love for UF sports into the conversation. We also flip the script and ask the lead PM of the Catalyst/ Teza Algorithmic Allocation Fund (TEZAX) to dig deeper by covering some off-colored topics that viewers want to know more about, like the decision to pivot away from HFTs, why the Catalyst TEZA Algorithmic Allocation Fund essentially went flat for the first seven months of 2021, and how is Teza’s strategy doing now? Plus, we put Matt in the hot seat to provide his perspective on topics that nobody is talking about, or everyone is wrongly talking about. Highlights and topics from this episode include: How to determine what volatility is on a forward-looking basis and where risk models come into play The algorithmic allocation and breaking down the equity bucket Why absolute return in the alternative mutual fund space means low volatility and low return Why you need to adapt if stocks and bonds are down together over the next 16 months A closer look into the reality of why your model will work better sometimes than other times and the importance of allowing your volatility to float. Plus, more! Chapters:  00:00-01:42 = Intro 01:43-10:19 = Tim Tebow, Gator Sports, & Lawyer turned Quant PM 10:20-18:26 = High-Frequency Trading 18:27-34:36= The Algorithmic Allocation & Breaking down the Equity bucket 34:37-58:28= Multi-Model Methodology Approach / It's All About the Data 58:29-01:04:26= Hottest Take - NFL Hiring practices Don't forget to subscribe to The Derivative, and 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. Okay, happy Super Bowl week, everyone. I think I'm going with the Rams. Love that Bengals story, but not sure they can pull one more rabbit out of the hat. But hey, if the Bengals can go from worst to first in a few years, maybe there's hope for my Bears. A little sneak peek on the next week.

We'll have John Krautsack of EMC talking through the inflationary environment and just how good trend following has been of late. So make sure to subscribe to get that delivered straight to your door next week. And we've got a good one for you here today, talking through what it's like in the so-called liquid alts world, where hedge fund strategies are utilized inside the plain old vanilla mutual fund wrapper. Here to talk through how that works is the PM of Catalyst Tezza Algorithmic Allocation Fund. Say that 10 times fast. Matthew Hanna, whose firm Tezza was a high frequency trading firm before moving into the

hedge fund world. And now the mutual fund space, send it. This episode is brought to you by RCM's outsource trading group, where their 24, six trade desk to call in spreadsheet, FTP, direct to exchange algos,

and more orders to help firms be cost-efficient and not have to staff their own trade desk. Check that under the services slash trading firm slash 24-hour desk on the main navigation at rcmalts.com. Okay, we're here with Matt Hanna, and I didn't ask how to pronounce your last name. Is it Hanna? That is correct. I appreciate it. All right. Okay, we are here with Matt Hanna of Tezza Capital Management to talk through running

a systematic macro mutual fund, some of the firm's high-frequency trading and prop trading routes, and what it's like being a Gator fan in Utah. So welcome, Matt. Thanks, Jeff. I really do appreciate you giving me the opportunity to speak with you today. Yeah. So I'm a Gator fan. I grew up, my stepdad went to UF, so we'd drive up from Vero Beach to all the Gator

games, Galen Hall and Emmett Smith when he was there. So love the Tebow jersey behind it, but it seems to be the wrong, in the wrong colors. Yeah, that's a Jets Jersey and I'm certainly not a Jets fan. I'm a Tampa Bay Buccaneer fan. So, you know, I shed some tears with Tom Brady retiring and we're going to go back to the basement pretty soon. Buccaneer legacy, but yeah, so that's a Jets jersey. But a big obviously big Tim Tebow fan, big Gator fan.

I went to school a little before Tim Tebow got to UF. So not quite my my era, but I got to enjoy a basketball national championship. And, you know, as a student a student and you know kind of growing up followed the Gators and even today try to attend as much as I can in person whether it's football basketball baseball gymnastics softball anything and now you know with just tv becoming more broad sec network uh plus I'm able to really watch anything i i can get my hands on so collegiate sports is definitely my thing more so than than pro sports but uh you know tim tebow is a big part of that and he's a great gator ambassador i hear you uh so the basketball championships that was joe came

noah back to backs yeah al horford coryian Lee Humphrey, all those guys. Obviously it was awesome. I got to see one of the championships live in Atlanta. So that was fantastic. Great team. I think still highly underrated. But right now we're struggling, to be honest with you. This is year seven in the Mike White regime. that's our head coach and it's not really going the way i'd like it we're basically best way to put it is just average uh you know i don't think you can settle for average in anything so i'd rather shoot for

the moon and if it gets worse fine but at least you're giving it a shot yeah and then that was the football season was super weird fired their coach halfway through and whatever. We could spend an hour on Gator Gator sports. And that school is super hard to get into. Now, I was talking with a buddy in Florida whose kid had straight A's down in a school in Palm Beach and couldn't get into Florida. Yeah, I don't even know if I could get in at this point. But, yeah, I mean, it's definitely becoming a more international school. I know they had a big thing this year about becoming like a top five public uh university so it's definitely a highly

competitive it's a great school great culture i love gainesville great location uh but you know it's a little bit different now than it was yeah when i was there 20 years now um now you're way away from gainesville and in layton utah right just north of salt lake yeah i'm in salt lake city uh utah like i said little north in a suburb long story short uh i moved out here for a job call it five years ago and uh you know i love it out here and my understanding is you're actually coming out here uh later today to go skiing uh yes we won't this will be released later than that so i'll be back in chicago by the time this is released but yeah fine make it out there twice a year probably at least um so love it out there we got to get a utah office rcm utah office um and so talk through a

little bit more of the background. So you came out, you went out there for a hedge fund job and then ended up here at Tezza running the macro mutual fund. So give us a little bit of the personal background. Yeah. I mean, before I jump into that, before I start talking about Tezza, so obviously, you know, all my opinions here expressed here today are my own opinion, do not reflect Tezza Capital, parent companies, or anything affiliated. You should not treat my opinion as a specific inducement to make an investment in the mutual fund I'm a portfolio manager of, which is the

Catalyst Tezza Algorithm Allocation Fund, or any Tezza fund, or to follow a particular investment strategy. My opinions, of course, based upon info I consider reliable, but do not warrant to its completeness or accuracy. Past performance is not indicating future results. I don't guarantee any specific outcome or profit. The listener should be aware of real risk of loss following any strategy or investment. This discussion does not take into account any listeners individual particular investment objectives needs and is not intended as a recommendation as a listener you should take

your own independent decision regarding any investments discussed here and consider whether it's suitable for your circumstances and of course seek advice from your own financial advisor or investment professional so i am done with that. That is good. So long story short, make sure anything is suitable for your own needs in your circumstances and seek out advice where appropriate. Yeah, I think we should just have a whole industry reset. And the default will be anything you hear on TV or social media or read on a website

is not investment advice. Investment advice is only given in person. Right. We can flip the whole script instead of everyone always having to say this is not investment advice. But anyway, out of the way. So we were going back a little bit of how you ended up at Tezza? Yeah, so we can kind of begin on a, you know, nighttime way back in the early 80s. Matt Hanna was born in Tampa, Florida. Again, that's kind of how I led myself to the University of Florida. So kind of grew up there, very middle-class parents, blue collar parents, uh, gotten to university of Florida. My undergrad was actually in political science. So I wanted to be a lawyer, uh, until I sat down to take the LSAT. And then I realized I don't want to be a lawyer. It's not, not what

they show on law and order. So long story short, I had to find a job and I applied pretty much everywhere. So I got a very basic operational job at Raymond James in Tampa, St. Pete, Florida. Actually, that was my first kind of foray into finance and quickly realized, hey, you know, I want to kind of move up the ladder, make a little bit more money, provide for my family, challenge myself. So I went to night school, got my CFA charter, a CAIA certification, took the FRM as well, and got into basically you can think of as mutual fund research and asset allocation at Raymond James. The beauty there is I got to interview, see, talk to hundreds of investment managers like where I am today, but just think of kind of the wide range of mutual funds, all trying to raise a dollar and get on our platforms. So I got to see what worked, what didn't,

not only from an investment strategy perspective, but also just from a marketing sales perspective, what resonates and where do firms like Tez at this point go wrong? What's the hurdles they have to overcome? Over time, basically late 2016, early 2017, got a job at a firm called Summit Global Investments out here in Salt Lake City, where I was a portfolio manager on seven different mutual funds, four of those being quantitative equity strategies, and three of those being asset allocation mutual funds, all quantitatively systematically managed. I also developed a hedge fund for Summit as well.

Then decided to take the leap and kind of jump to Tezza, which they're based in a variety of different offices, Austin, Chicago, and New York. But the primary goal is to manage their alternative mutual fund in terms of research, development, portfolio management, but also spread the word to people like yourself and your listeners. So a little on the Tezza background, your firm's a bit different than most in the mutual fund space, having been a high-frequency trading shop, trading proprietary money before venturing into the hedge fund world and eventually the mutual fund world. So let's start with that high-frequency trading part. It's not exactly the same as most other Chicago based prop trading firms or options based.

So kind of take us through, if you can, the history of the firm. Like, are we talking full on microwave towers and spending billions of dollars to shave a microsecond? What does that high frequency history kind of look like? Short answer is yes. So, again, I'll kind of go back in time, not as early as the 80s when I was born, but our CEO, Misha Milashev, worked at Citadel and he kind of built out their high-frequency trading business. He did fantastic there in 2008 and decided to launch his own firm in 2009. And that's the kind of the TESA start. And that's our owner, CEO's background in the high frequency space. So that's where TESA began trading as

primarily focused in the high frequency space. And like you mentioned, telecom assets and trying to shave microseconds, highly competitive business. As you entered the past, call it five, six years, seven, eight years in that range, just profitability in that business kind of shrunk, highly, highly competitive, various edges and trying to shave those microseconds kind of dissipated. So Tezza found frankly, another better opportunity. And that's kind of how we led to today. So we sold some of our assets in the high frequency space, whether you're talking those kind of towers we're talking about, or some of those just the IP, you know, as well. So we pivoted and pivoted in a kind of a broader direction,

where we're now we're trying to bring solutions to the public, whether it's kind of more of your private solutions or mutual fund solutions as well. And we're trying to gain alpha in a variety of different methodologies. The original pivot is actually very similar to high-frequency. It's utilizing a lot of the same data. So think like order flow data, but instead of trying to win by a microsecond, we're trying to utilize a lot of that data to help predict where the market's going to go over the next day, two, three week. So that's very similar data, but just timeframes a little bit different. Utilization of that data is a bit different. But we also do a lot of cool stuff at Tezza beyond just the microstructure order flow predictions.

One, I think what I do is quite interesting. We're in the global macro tactical allocation side, but we also have individuals that do a lot of cool stuff, whether it's arbitrage, long-short trading, various power markets, runs the gamut. Wherever you can find alpha, we're interested to seek out. And then we can kind of deliver those solutions in a variety of different formats, whether it's mutual funds or just kind of bespoke solutions for clients.

And then, so is there any firm capital put to use as well still or no? Is it all deployed for clients? I'm sure Misha has some of his own stuff kind of going on as well. So, yeah, but it's primarily, I'd say, the focus is on kind of raising outside capital. And back in the high frequency days, if they found a new edge, they found a new market, like what kind of sharp are they looking for? Right. You hear these stories of like, I'm not interested if it's less than an eight sharp or something. I'm not a huge fan of the sharp ratio to begin with, but do you have any insight into kind of what,

what the bar was for being able to be deployed with the firm capital? Not exactly sure what, what the kind of the expected sharp ratio was, especially back then. But it is, it is public knowledge that when Misha was at Citadel, he, he, his group was able to post a profit, not of seven figures, but of 10 figures, which is a lot of zeros. So basically, we did quite well. So that's obviously a very high Sharpe ratio.

But now I think if you can hover in that, depending on what you're doing, that two to three sharp ratio, I think you're doing a pretty good job. Yeah, for sure. And so talk a little bit about how that high frequency pivot you said, like it was looking at microstructure and saying, hey, we want to be in this trade for the next millisecond and then get out. Now that might be we want to be in it for the next. Are we talking minutes or hours or days? What does that look like? Generally days, but that depends on the exact trade. And there's different PMs that utilize that data in different formats too.

So I can't speak to what everybody does at Tesla. Different people do different things and try to find different alpha sources. But for us, it's primarily not about the millisecond anymore. It's more, I think a day is the best kind of, I would say, look back period that we're trying to analyze, the look forward period that we're trying to analyze. But some people certainly still trade intraday, but some people might not put on trades every day. It might be every week. So it kind of runs the gamut. And I think that's part of risk management is not just to have your firm focused on a millisecond or the day or the week or the year, but have people do a lot of different things that all complement each other

at the end of the day. Right. And do you think just generally speaking, a lot of the same firms that just became too expensive to compete with one another and the edge just kept getting smaller and smaller? Yeah. I mean, that's business and that's going to happen every which way. And that's why a lot of hedge funds really kind of guard their secrets and their IP. Because once that edge gets out there, it's going to shrink to the point where it goes away and you got to find another source of alpha. And honestly, I think that's a big issue hedge funds have had going to public in a mutual fund is a totally different pitch. One is very non-transparent and one is you have to be ultra transparent just in your approach. And I think a lot of mutual funds that are in the alternative space, they've made a big mistake because it is not build it, you will build it and they will come type approach.

You have to really pound the pavement and spread the word and let people know what you're doing. And it seems like, right, I've been at dinners around Chicago here, like prop trading firms laugh at the mutual fund industry, right? Like these suckers, they don't know what they're doing, just buying and holding. There's better ways. They're right. They're running a one sharp. We have an eight sharp. So it's a little funny, like to see that pivot, to see that movement towards that space and say, Hey, no, there's still smart ways to approach it. There's still smart ways you can deliver this alpha in the mutual fund wrapper. Yeah. I mean, there's different clients. I mean, the reality is your neighbors across the street, they have their 401k, the rich lawyer, dentist, they have their retirement, you have institutional money. There if you become a, call it a hedge fund trying

to raise outside capital, your client base is still, I'd say, quite narrow. But from a mutual fund perspective, we're able to help provide good solutions to a lot of different people. And if you open up your mind, you're able to really give excellent solutions above and beyond what typically are found in the mutual fund space for those clients. And frankly, I'd argue my neighbor who's trying to save for retirement has a far bigger need for something interesting, different, that can produce a decent shark than a crazy rich exit founder somewhere. Right. XYZ, you know, exit founder somewhere. Right. XYZ fund of funds.

OK, on to the mutual fund. So you're the lead PM, right, of the Catalyst Tezza Algorithmic Allocation Fund. Yeah, it's definitely a group effort, but certainly I spend most of my time on this fund, if not all my time on this fund in a variety of forms. Misha, the individual, the CEO I talked about before, he's definitely heavily involved as a portfolio manager. And then we have our chief risk officer, Ryan Holt, he's heavily involved as well. But we all talk about exactly the direction we want to go and what we're trying to achieve. And at this point, I think the fund is rocking and rolling and we're excited about the future. And the symbol is T-E-Z-A-X, right?

Yeah, T-E-Z-A-X, which TESA X, or the iShare, which is T-E-Z-I-X. I think what's really interesting and important to think about is what's in the name. So like, as you mentioned before, the Catalyst has an algorithmic allocation fund. I think the key word here is allocation. And, you know, Jeff, when I bring up the word allocation to you, I mean, what do you think about? What is allocation? How do you view allocation in the kind in the broader mutual fund retail landscape? I like it.

We're flipping the script. To me, just, yeah, diversifying, saying I need to have, right, the basic would be 60-40 stock bond. But to me, I want some trend. I want some long volatility. I want some bonds, some stocks. So, yeah, just my percentage allocations. I'm using the word in the definition,

but yeah. That's okay. This isn't like jeopardy or anything of that sort, but I think you're right on the button. And especially with your point on what you would prefer is to have some trends, some other stuff. And I think the reason why I think that's really pertinent, especially these days, is most clients that might be not 60, 40, I'd call that just kind of average age, average risk. Some might be mostly stocks, somebody young, really aggressive. And some people might be closer to retirement and might have 30% stocks and 70% bonds. But the classical 40-ish past years thought is when stocks do poorly, bonds help you. That is kind of the whole theory of asset allocation and how financial advisors generally set up portfolios. So if somebody's really conservative, they may have 30% stocks,

70% bonds. Their stocks go down, but their bonds protect them. But Jeff, I'll ask you another question here. In this new paradigm where interest rates are beginning to increase, does that allocation make sense? I mean, there's clearly a potential issue there, don't you think? Huge issue. Yeah. We've had all the lines on here. Return-free risk is the best one. But yeah, in the old days, if I'm going to get paid to hold this thing that should increase when there's a market crash, so be it. Today, if I'm going to get paid next to nothing for this thing that maybe won't protect me in a crash, does it make any sense?

Yeah. And even worse, if interest rates go up, you lose money. Yeah. It's not even a performing asset. It doesn't help protect you. And long-term, your expected return is pretty crappy. Not saying necessarily interest rates are going to rise for a long period of time, but clearly, especially over the past January, we saw that where interest rates went up, that caused the NASDAQ especially to go down. That's a really rough combination for a lot of clients.

So long story short, the Catalyst has an algorithm allocation fund. We're trying to help solve some of that issue. As an allocation fund, we recognize that just being static 60-40, 30-70, 80-20 might not always be in the best interest of your goals. And knowing that, sometimes it makes sense to increase the equity percent. Sometimes it makes sense to decrease the equity percent. Sometimes it makes sense to do the same for interest rates, as well as other assets. Sometimes it makes sense to increase your overall risk or decrease your overall risk. It's good to be flexible and tactical. So our solution here is not something I would say makes sense as you're only holding. I think for most, say,

retirees, you want to be well-balanced and kind of set up long-term with your goals, but something that could really help you around the edges, I think that's where we come into play very, very well. We're able to help kind of control your risk, control some of those kind of esoteric outcomes in the market in ways your traditional allocation can't. And how do you consider, right? So part of me thinks, yeah, the old way of like, ooh, China's doing some saber rattling and oil's high.

I think we should pull back on our equity, right? Like the old way would just be some PM having a feeling about, oh, I'm going to adjust my allocation because this looks risky. So tons of problems with that. When does it unlook risky, right? What if you're wrong? Opportunity costs, all that. So juxtapose that with algorithmic. I go on the algorithmic part of the name. Algorithmic, the con would be, oh, it's always backwards looking. It's just going to move into what was working, which by definition probably is not going to be what will be working. So how do you kind of weigh those two methods of asset allocation?

Where do you guys fall in between those? Yeah. So we're certainly systematic all the way through. And I'll kind of talk about some of the pros and cons with that. So first, if you gave me a call, I know this is going to air after you're out skiing, but if you gave me a call when you're out here in Salt Lake and I got to meet you on the slopes and I'm a terrible skier, but say I got out of control and I fell and broke my leg or anything like that, the beauty of something algorithmic is it's still going to run. It's still going to do exactly as we intended. And there's going to be no hiccups where if it's purely discretionary, somebody, you know, reading the news,

their finger up also the market all the time, if they had that same accident, well, you're kind of SOL is clearly not going to be able to, you know, function. So there's certainly a business continuity benefit of being algorithmic, but I also kind of go back to risk management. And risk management is typically at the core of really most hedge funds, but definitely here at Tezza. And I would view risk management as not just a focus on your volatility or your risk of losing capital, but also what are the causes of potentially losing capital? And one of those causes would be, say, bias. And bias comes in a lot of forms. If you're

heavily discretionary, confirmation bias is my favorite bias, or maybe you can call it my least favorite bias. But generally, you're hunting out information for a cause or a hypothesis that you're already predisposed to. So you're just kind of confirming your own opinion. And there's a lot of issues potentially with discretionary managers falling victim to a lot of bias. Now, quantitative strategies have their own potential bias blind spots as well, but a lot less when it comes compared to discretionary strategies. So we're able to reduce risk that way. And I mentioned before, it's not just quantitative in a singular fashion. One particular model mentioned kind of looking backwards, maybe trend following in that. And certainly I believe in that, but that's risky because it's isolated. It's only one particular

strategy. Here, we're trying to get alpha sources in an allocation framework from many, many, many different methodologies, timeframes, processes, people. In doing so, we're able to minimize some of those risks that can't really be seen if you just pull up a Morningstar page, but really do exist once you kind of pull back down. Which leads me to, so there's no mandate to be like a 0.6 beta to the S&P or to bonds or anything to a blended portfolio, right? Is it just pure absolute return and we're going to get the most return for the least amount of risk? Or is there a mandate to say we want some equity exposure, some bond exposure? That's a great point. So I'll hit on the volatility. So at this point, we try to target something between 13% and 18% annualized volatility. I'd be thrilled if we can long run

average around 17%. I think that's incredibly, incredibly important because you hit a keyword absolute return. And a lot of times absolute return in the alternative mutual fund space means low volatility and low return. Well, when you're charging a high fee, that's a really bad value proposition for most clients. And I think that's a very common pitfall of alternative mutual funds. We're taking the opposite approach. We want to give really high volatility, equity-like volatility, and hopefully returns commensurate with that. But that's a much better value proposition. So we want to keep that mandate around that 13%, 18% vol in terms of how we allocate to get that. Generally, I would say it's about 50% of our risk is allocated to equities, 30-ish percent to interest rates, and 20% into, I would call like an other basket, diversifying basket,

primarily commodities. Each one of those buckets can go long short, and each one of those buckets are global in nature. But we are long biased, especially on the equity and interest rate side. Primarily, equities generally go up. You see the big green hammer or the green button. You don't want to necessarily fight that. A lot of models, I think if they're geared right, would recognize that equity generally go up. Now, hedge funds, if they're trying to be absolutely return oriented, can fight around

that margin. But we're an allocation fund for mutual fund clients, for potential retirees. We want to make sure we kind of fit into their overall portfolio. So having a slight long bias, I think makes a lot of sense for us, but we're able to fight around the edges on a long, short basis at times. Got it. So if I'm looking, I'm building the portfolio, maybe more as an equity replacement or a 60-40 replacement with a portion of that bucket. Because if you have the long bias, I should get some of the upside. Yeah.

So if you could think like 50-30-20 is generally how we are. In theory, we could be a replacement for equities or bonds, depending on the client. And that's where that disclaimer I crumbled up and through makes a lot of sense because your own situation, whether what your risk tolerance is makes a big, big difference on whether you source something like this from your equity portion, your bond portion or a combination. But the beauty is we're diversifying enough that it can fit really into the most conservative client.

But if you are very aggressive and you want equity-like returns and risk, we can also fit in there. Where most alternative mutual funds with lower risk, lower return, that's a really hard fit. I mean, you certainly would lose the long run if you sold your passive S&P 500 ETF for an absolute return five vol product. You're just not going to get the same return. So we wanted to make something that can fit into most clients and having a higher volatility allows that flexibility. But that's certainly up to your own needs and your own specifications and your

own portfolio. Right. So would it be fair to say if you have the same vol as 60-40 and do a little bit better, right? And so the risk adjusted ratio is higher that you're happy as a clam, as the PM, right? I'd be happy. I'd put it this way. I'd be happy if we beat equities from a return perspective. I think that's really important. And then also, I would say buy a decent amount, but also being able to do it in a very diversifying way, I think is very, very important. And then let's let's break down the equities in the bond bucket for that matter of it's heavily U.S. centric. Are we all we're talking S&P, S&P, Nasdaq, Russell.

What goes inside that equity piece? All of the above. So kind of think of your kind of broader equity index features across the globe. So S&P, NASDAQ, Russell 2, FTSE, DAX, Nikkei, kind of go down the line. They're all fair game. And there are times where we prefer one, call it asset group, perhaps US large caps over something international. But there also could be times where it could be flopped. And then also from a long short perspective, even though we're long biased equities, that doesn't necessarily mean we're going to be long every equity out there,

every equity index out there. We could long short variety different features to be able to capture alpha the best way you know we possibly can what does that look like so right us is trounced foreign and emerging over the last yeah five ten years right so is the model going to be more heavily us there and if that if that narrative flips or not the narrative but if that data flips, if the next 10 years U.S. gets trounced, is the model going to say, hey, we're more in these foreign markets, we're more in the emerging markets now? I mean, certainly there's a lot more that goes into it than just merely say trend or that conversation is heavily momentum focused. And I would generally agree if that is your methodology looking at momentum trend. Absolutely. We want to see what's worked in the past.

And generally that continues to work at least for a little bit into the future. The way we approach this fund, we certainly have elements of that. So if international began to trounce US, that would be a feather in the cap for international. That being said, there could be other things at play that could trump that effect. For example, if economic data was poor internationally, the valuations were poor internationally, some of our kind of faster statistical machine learning AI models look negative on international, then certainly maybe the final output might not be more tilted international than we are today. That being said, that's the beauty of a multi-model, multi-methodology approach,

is it's truly some of the evidence. You just don't want to look at one part. You want to look at all the evidence you could possibly find to make the most informed decision. Right. So I think that's both like a blessing and a curse, right? Because the curse would be like, okay, you're always going to be underperforming one of those sleeves. But if someone's taking on concentrated risk and emerging markets, God bless it, right? Like, go ahead. But that's been a painful bet for many years. And it's going to be your portfolio. Your whole goal is you don't want your portfolio to be solely dependent on one sleeve, right? Yeah, yeah. And that's why traditional allocations for retail clients might have

an active manager or passive ETF in US large caps or emerging markets dedicated to that. And I'd say a lot of hedge fund managers might be very niche with their edge in a very specific spot. But what we're trying to solve here, and I think most alternative mutual funds really should be thinking about, is how you fit in that kind of broader landscape. So the importance is kind of smoothing out that ride. And it's not just smoothing out the ride in terms of volatility, but smoothing out the ride in terms of how you perform. It's much better, in my opinion, to be consistently good than occasionally great and sometimes bad. So long-term, I mean, that's, you talk about what would make me happy is to be consistently solid,

not necessarily on a day-to-day basis, but even something on a quarter-to-quarter, year-to-year, we want to be consistently good. And the best way to do that is that sum of the evidence approach. We talked momentum, as I'll throw out the word factor. You can correct me if you think that's a bad term, but right. Momentum, some AI models. So there's a whole bunch of stuff going on behind the scenes. How many, I'll say factor again, if you think that's the right word, but how many models, what's going on behind the scenes that's informing all these different asset classes? Yeah. I mean, there's dozens of different methodologies and that's something we have

a lot of people looking at constantly, whether we want to add something new that has potential alpha, or even if a potential resource of alpha kind of lost its ability, perhaps we need to pull back on it. That's something that's ongoing, that research. But certainly there is, we talked about kind of that switch gears of order flow microstructure to something longer term. That is something, you know, we utilize a little bit, whether it's trend, we utilize that. We look at the relationships amongst asset classes, that prime example of stocks going down and interest rates going up. That's very abnormal. That influences some of our decision making, economic data, inflation, industrial production, et cetera, that can influence some of our decision-making fundamentals, whether it's bottom-up or even things like valuation could certainly and do influence a lot of our decision-making.

So it is a wide net that we try to cast, trying to get alpha from a lot of different sources. We do then kind of sum it up. But that's just on the alpha side. On the risk side, we utilize a lot of different risk models. So for some of your listeners, you might just view risk as, like I said, capital loss, but also volatility. But the question is, how do you determine what volatility is on a forward-looking basis? And that's where risk models come into play.

There's lots of different ways to predict risk models and predict risk. And some of these alpha sources utilize very smaller windows of timeframes. So looking at, say, 15-minute data intervals and seeing how assets are relating in a short time horizon. And some of our alpha sources utilize models that are much more long-term, looking at how assets behave over the course of a short time horizon. And some of our alpha sources utilize models that are much more longer term, looking at how assets behave over the course of a year or two, or even longer. So being able to kind of blend that gives us a good chance. Hopefully, I'll be happy if we can be consistently good. But the reality and whether discretionary or quantitative, like you said, one of those strategies,

one of those methods is going to do well. But what does that also mean? One of those strategies is going to do pretty poor. And I can tell you, there's going to be times individual strategies ebb and flow and you don't want to be, if too many eggs in one basket, you can make some bad decisions

if your strategy is not performing at that given moment. That doesn't mean it's a bad strategy. It's not going to perform. It just means it's not as time. And that's why it's really important to cast that wide net. And that's what we do. And so all these different strategies, do they operate singly? So each one's putting in its own orders, had its own risk.

And then the sum of all those is the net positioning. Or are they netting beforehand and then derive kind of like a voting system? This one, this signal saying this should be three. This one saying it's negative one. And that's the netting. And then you put in an order. Yeah. So it's, again, comes down to risk management and diversification of process.

So the answer is both. Some of our alpha sources are designed to work interconnected with others and some are truly independent so the ones that work interconnected they kind of learn from each other and make a a position intent based upon their own positions working together and some are very very different uh where they're not interconnected and they're kind of netting out at the end and then that is there like an ai machine learning overlay that's running all this or that's considering all this uh not at that kind of final netting stage but step a step before that uh certainly we have various forms of AI machine learning, some at the risk model stage and some at the alpha stage. And then you call it macro, but as we talked about, there's no discretionary.

So there's no classical macro view of you're saying we're in an inflationary period. All the risk is coming down 10 percent or something of that nature. Yeah, I mean, I guess it depends. Like our morning star category at this point is macro trading. So, you know, it depends if you view macro as like a discretionary thing. I think a lot of people would understand like tactical allocation. I think that's another good way of putting it. But I think it's kind of six one ways, half dozen another. I mean, the overall goal is to produce a better allocation by analyzing at a high level, both alpha sources globally, risk sources globally, and have that flexibility to long and short across the globe.

And then just jumping back a second. So all this, I'll call it fancy stuff, it's happening behind the scenes. It's coming out with this portfolio. At the end of the day, the portfolio is going to look like what? It's going to be, hey, we're long U.S. growth, U.S. value, we're short European value, we're short Japanese, right? So it'll be kind of this mishmash of these different positions that create this one position. Is that fair? Yeah, exactly. So like you said, long, say S&P futures contracts, NASDAQ, but potentially short, say various parts of the US interest rate curve, but long some parts of the Australian interest rate curve. So it's a mishmash. Certainly, like I said, long bias. So there's all these strategies probably have a slight gear to the long side. But overall, without understanding and kind of pulling back the risk and the potential alpha sources, I think mishmash in positions makes a lot of sense as a descriptor of what you might see.

Yeah. Sorry to belittle these brilliant alpha sources into the word mishmash. And then you talked a little bit, you said some of the more advanced models. What did you mean there? And I think we talked offline about this bonds up, stocks or bonds down, stocks down. Just talk through that for a second, if you could. Yeah. So, I mean, it's on the alpha side, I think we can kind of dive into, but on the risk side makes a lot of sense too. Like I mentioned before, we're trying to target that 13, 18% volatility. So it's a matter of, again, kind of that sum of the evidence approach on ways to predict volatility and end up kind of producing in that range. So we utilize a variety

of different methods to give us confidence that we're going to be in that range. So we utilize a variety of different methods to give us confidence that we're going to be in that range. What we don't want to do is undershoot volatility too much. And then frankly, like I said, that becomes a really bad deal for consumers. That being said, there could be times where

we don't want to take on much risk for a variety of reasons. And that could be due to the alpha side. So that's a good segue to kind of what you're talking about. A good time I don't want to take on risk from an alpha side perspective is when assets are behaving abnormal. And abnormal can be defined a handful of different ways, but a good example here is January. Again, stocks down, interest rates up. That is quite abnormal market behavior. Typically, stocks go down and your bonds protect you. So from a quantitative perspective, it's not just a

question of, do I like my model from a long-term back-tested historical perspective? That's great. And you want to also run it live for a period of time too, but also when does your model work and when does it not work? And a lot of times that takes just a quantitative methodologies, but just some knowledge of how things are built and why they are built the way they are. And when the markets are behaving abnormal, that tells me that this is not the best time to be taking on a lot of risk. My confidence in certain models would be lower if markets are not behaving in a way they typically behave. When things are very normal, then clearly you can rely on a lot more of your historical data

than when things are not behaving normal. So we look at things like that that would take risk off the table just because our alpha models might not be producing such a strong signal, but it certainly runs the gamut between very sophisticated models and targeted risk to, you know, alpha models that kind of gives confidence on other alpha models to something very simple on we're going to bet on what's been working. Right. So talk through that a little bit more. So when I hear normal, but part of me is like, well, maybe that's the new normal, which is always gets people in trouble. Right. But

say we have 14 of the next 18 months are stocks down, bonds down, right? Rates up. Right. Which could easily be the case if we are going to this rate, increasing rate cycle, and we've had the past 40 years, we can agree, right? Anytime stocks were down, bonds were generally up, rates down. But the next 40 years, if we go from zero to even 7% or something, interest rates, you could see that flip. So how do the models or how do you think about that of, okay, this was not normal, but that normal is based on the last X number of years, not the next X number of years. So what I would say, Jeff,

you'd be a great fit on our team because that's kind of how we think about it as well. So it's not a matter of just looking at one timeframe, one kind of a back period and slice and dice the time frames in one way. To your point, if stocks down, bonds or rates up over the next 16 months, you certainly need to adapt. So what we do is not only look at, say, daily data going back a period of time, but also

daily data going back a variety of periods of time, but also weekly data and monthly data and intraday data. So we're able to glean that information and utilize that information both on a very small kind of day-to-day nuanced view, but also more along the lines of a weekly or even a monthly view. So again, it kind of goes back to that diversification of process. So it's going to hit on your question. If for the next, call it, month, we continue to see that, then our models begin to learn that, hey, this might be the new normal. And we might not want to punish our other models as much because we're consistently

seeing this behavior. And then if we continue to see it over the course of months, that'll become even more powerful, more powerful to the point where, you know, if we're sitting here in five years, that would be the complete new normal. And that would be the expectation. Not that I would expect that to happen, but our models are able to adapt and adapt at different timeframes. And then while we're talking about rates up, how do you view, right, if there's a long bias, you said both in the equity side and the bond side. So long bias, meaning bond price rates down. So how do you view if we were going into a rate,

increasing rate cycle, having that long bias, is that you just handle that with duration or what are your thoughts there? Yeah. So, I mean, we do, especially on the collateral side, we own some ETFs primarily on the fixed income ETF. So we have a bias there. On the future side, again, we can do a short. So even in January, you know, rates going up, we made money on U.S. interest rates because we were short interest rates. So we're able to adapt depending on what the environment is. Long-term, I would certainly want to lean into even still long interest rates. But that being said, if rates rise over the next year or two, when I say long biased,

that long bias might not hold over the next year or two. I'm talking over kind of a longer term cycle. So kind of shorter term, we're able to be quite flexible, but in a longer term, I don't expect interest rates to rise perpetually over the next five, 10 years. At some point, they'll level out. And at some point,

the Fed will have the ability to kind of cut interest rates again and kind of do what they've been doing. So yeah, I don't think- Longer the way of saying if interest rates go up in the near term, we have the tools in our tool belt to be able to combat that. Yeah. And to me, like this whole rates are going back to 15% or something. I just said, no way, like the world's not built for that anymore. Yeah. I mean, demographic trends

certainly don't favor that. Economic growth trends don't favor that. So, I mean, I'm not thinking rates are going to go up tremendously, but certainly inflation in near term can and probably should push it up a little bit higher. And talk to me about that remaining 20% diversification bucket. I'm assuming there's some commodities in there, some other stuff, or tell me what's in that bucket. Yeah, primarily commodities at this point. I'm assuming there's some commodities in there, some other stuff, or tell me what's in that bucket. Yeah, primarily commodities at this point. I mean, that's an edge we have in the commodity space. Again, these are all features contracts, so long and short, primarily commodities at this juncture. This is very distinct. So kind of going back to

your question about certain signals talk to each other before the combining stage or post combining stage. Our diversification bucket is definitely kind of after, it doesn't necessarily inform, although we do have some commodity signals that inform kind of equity and rate positions, but the models here, they come up with a view on whether to be long gold or short silver or whatever it might be. And we're able to kind of reflect that in overall portfolio. Once we get that view that we want to be, say, long gold or short silver, then we're able to utilize that information and target that overall risk of that 13, 18%. But kind of the theme on how we determine which commodities are long, short, very similar.

Multi-model, multi-method approach, trying to figure out what drives commodity prices higher or lower. And quite a few things can do that. And kind of that sum of the evidence approach that determines whether we want to be long or short. Sometimes it could be on that side of the book, can be a bit more combined, right? So there's obviously decent correlation between certainly some commodities,

but also looking at models that look at, say, gold independently from, say, silver. Got it. But then, so if those models say, hey, we want to be long oil, but you're already long stocks, and if it said, hey, the correlation is trade's rather high,

we're either going to pass on that or we're going to do it in smaller numbers so that that net correlation, that net positioning doesn't get too high? Yeah, that second point. So if those assets are behaving highly correlated at that point in time, that'll mean we still want to hit that 13%, 18% vol range, which means we'll have to take a smaller position size to be able to hit that. Got it. And then Todd just made me think of it on this vol targeting, would you call it vol targeting? So what if you're in all these positions, everything's going great, but it's going over your targets, will you reduce existing positions? Yeah. And I think that's an edge we have too. Just a lot of this kind of comes from my background at Raymond James, where I got to see a lot

of different alternative mutual funds. I think a problem a lot of funds face is when they try to target a particular vol all the time. The reality is sometimes your model is going to work better than other times. And sometimes they're going to be more confident than other times. So allowing your volatility to float, I think is incredibly important. And that's what we do here. So our range is 13, 18%, but at any point in time,

we could actually be lower or higher than that. And that comes down to, and this is from a, you know, ex-ante perspective, not just kind of looking back, that could be driven off of our signals are just not very confident. We're not seeing a lot of alpha sources. That case, we want to actually take a little bit less risk. It doesn't make sense to just take risk for the sake of taking risk. And that actually gives us the powder that when we are highly confident in what we're seeing out there, we're able to take on even more risk to kind of end up in that range we want to be at. Right. And that, I love that

because there was a meme going around a year or so ago of like, well, the correlation, this, that, like a lot of people missed the part of like, you need a positive expected return, right? So even if it's non-correlated, even if it's hits your risk target or decreases you down to your risk target, if it doesn't have a positive expected return, what's the point? Yeah. Yeah, exactly. I mean, that's, that would be the opposite of what you want to do is to lever up and target a high risk at something that's supposed to lose you money. That's, that's clearly not, not what you want to do, but also, you know, we all say we have an expected return, but like I kind of mentioned, alluded to it, it's not just your expected return.

It's your confidence in that expected return number. And there's, you know, we both could have an expected return of, of seven or eight or nine or 10. But if I'm way more confident in that number than you are, then I should take on a lot more risk knowing I'm much more likely to achieve that number and say what you would do. Right. Is that a little like Kelly betting there? I mean, it's, it's all, I mean, everything here happens under the hood, but it's, there's certainly that level of dynamicness. So while yes, that's certainly true. There's also times where, you know, we do, we don't want to deviate too much from our

volatility range. So there are some guardrails and the beauty of having so many models and so many methodologies. It's not likely that we're just going to sit here and say, well, we have no view at all. Therefore we're going to take no risk. And then six months down the road, well, we have tons of views. So we're going to take infinite amount of risk. So there is a little, certainly some boundaries.

We want to emphasize that being said it's it's important to to check your ego at the door you're not going to know everything at all you know every time and then switching gears a little i was going to start with this i forgot but the uh looking back at the fund over time so it was rather flat a little contrary to what you just said it was rather flat for seven months of 2021. So what was going on there? And then you joined somewhere in the between. So give us the 2021 history, if you will. Yeah. So honestly, just to be frank, I would say the fund at that point in time fell victim to a lot of those issues that I would have seen in my previous life doing

mutual fund research. The vol target or vol range was probably a bit too low, especially relative to the fee. So one thing we did do is bump that range up when I came on board. And then also, I think a lot of call it hedge funds, prop firms that want to go to the mutual fund landscape, like I mentioned before, they're kind of guarded in their IP, their secrets, their methods. So, and maybe a little bit of arrogance too, that Joe Public only deserves a little bit of what we can do versus a lot of, or everything that makes sense of what we can do. And that was something I felt very strongly.

Like if we're going to, if we're going to give something to the public, they got to get their, our best ideas all the time. And they got to get our best ideas of what makes sense here for this particular product. And that's where Tessa had multiple methods and processes and strategies before I joined, but that's something I really emphasized. You know, we have to continue to build, grow, and put more and more things here, regardless of, we can say it's typically found

just for a private hedge fund client. Well, if we're going to have a mutual fund, we need to make sure those things are available for our neighbors, our friends, our families as well. Talk through that a little bit. Are you allowed to just walk into the main firm and say, okay, I want this, I want this, I want this? Like for sure, there's some structural things. You can't do some of the trades that they do on that side. You couldn't go into any swaps or something like that, right? So, or real estate, or there's some limitations there.

But in terms of the strategies, what's that delineation look like? You have full realm now? You have full Roam? What's the word? I mean, I view Tessa as a firm. I can think of it as a buffet of PMs and strategies all trying to deliver alpha.

And if I'm trying to eat, I don't know, breakfast, I'm trying to find eggs, hash browns, maybe some fruit, yogurt, et cetera. I'm not necessarily looking for filet mignon. So there's certain things that don't fit with what we're trying to achieve. But if we brought on board a really smart PhD somewhere and he makes kind of

the best scrambled egg out there that fits what I'm doing, then I do have the ability to say, hey, you know what, that makes a lot of sense. We can fit that in here and deliver that to the public. But if we bring on somebody that does something totally different, then obviously, that wouldn't make a lot of sense for what we're doing for the mutual fund. But certainly I'm able to kind of have an idea of what other people are doing. If it makes sense, if it adds value, increases the Sharpe ratio, hopefully increases the return, helps us target risk a little bit better. We are able and we do want to continue to evolve and add those types of things. Right. And in the, in the past, a prop firm would be like, we,

this strategy, this niche we found can only take on $200 million or something. Right. Like there was some limiting factor to that's, we only want to put so much money in there, but you're talking exchange traded futures. You're talking things that, so in that conversation, like, Hey, we can take more, we have more capacity in that strategy, let's put it into the mutual fund. Yeah. And I think that kind of breakfast buffet example is kind of pertinent. Like what I'm looking for here is strategies on the alpha side that are generally trading around equity index features, interest rate features, and either making a judgment between them or a certain particular asset within them, and then finding a way to put that in here.

If it's not in that realm, then it's obviously a harder fit. Now, we have that 20% bucket, which certainly kind of opens things up a little bit more. But generally speaking, we want our particular alpha sources to be in that equity index or interest rate, you know, future, you know, ballpark. But I think a good way to put it is I think a lot of hedge funds or private funds coming to mutual fund world, they might say we make the best, best eggs out there, best scrambled eggs out there. Here you go, Jeff, here's your scrambled eggs. But A, you might not want scrambled eggs. You might not need

scrambled eggs. And some of these might not be in the mood for scrambled eggs, right? So I think the importance is from an ego perspective is to recognize that it's not about the best things necessarily we can do. It's also about what you need and what you want and what kind of fits into your circumstance. So having that kind of buffet solution, you know what, it comes together as a great meal, a great, you know, breakfast. If you're not in mood for our scrambled eggs today, that's okay. You don't have to eat that. You can eat something else. And ultimately, you know, you're going to have a heck of a heck of a meal either way. And that's, that's kind of how we approach this is we want to be consistently good, knowing that sometimes one sleeve or one process might

not work, but the other ones will pick up the slack. I love it. I do hate scrambled eggs, by the way. I think we should rename it the Catalyst Tezza Alpha Source Buffet. There you go. I think that actually might resonate to some people. I like it. We'll finish up here. Ask you for your hottest take a new segment. We're doing this here. Something you can't believe nobody else is talking about something everyone else is talking about, but they're wrong in your opinion, or something like Utah football is better than Florida football.

What's what's your hottest take okay so you mentioned uh football uh for those that have been paying attention uh Brian Forrest just sued the NFL and a variety of different teams and from a hot take perspective uh I I I love it uh you know i certainly think there's a lot of things that need to be improved upon you know hiring but i from a hot take perspective is that's very high level not that controversial but for those that know the nfl uh what is really focused on is what they call the rooney role which is uh teams have to interview minority candidates candidates prior to making a hire. And I think the end result is going to be some sort of change to the Rooney rule or just getting rid of it altogether. Because like Chief Justice John Roberts says, if you want to stop discriminating against on race, you have to stop discriminating on race.

And I think what's happening here, and I think, uh, for us, I had this issue, just a team already decided they loved the candidate and he was a token interview. Uh, so it's not achieving what they wanted to achieve. So ultimately I think there's going to be a decent amount of change in kind of NFL hiring practices and, and, and that's somewhat pertinent to that, but I don't know how hot takey that is. Yeah. Well, you're kind of saying like, Oh, a little bit might backfire on Florence. Cause they might even just remove the Rooney rule altogether. I'm like, okay, they're just going to interview who they're going to interview. Which now, you know, I think that's where John Roberts is, is right on track. If you want to solve the minority

hiring in the NFL or really anywhere, it's not at the end stage of forcing interviews. You have to start way before that in terms of a pipeline of minority candidates to minority owners, to minority GMs, not just like you have to interview. I mean, I think that's kind of crazy. Just like if Jerry Jones wants Sean Payton as his coach, any other interview would be ridiculous. Yeah, exactly. But his mind's made up.

Some of the other salacious stuff in there, like he was going to pay him 100 grand a game to tank. And so, yeah. Yeah. It was going to pay him a hundred grand a game to tank and so yeah yeah it's gonna be fun to watch which is wild when you think about just how gambling is now becoming a bigger part of our pro sports landscape uh you know an owner telling his coach to tank i don't know uh yeah if our las vegas overlords will like that too much right is that Is that reflected in the line? Should it be reflected in line? Should it be public information? Right. They're trying to take. Awesome. Matt, you got any last thoughts before we let you go?

Where can they find you or can they find more info on the fund? Yeah. So then I'll just kind of bounce around a little bit. You know, again, I appreciate everyone listening to my story, the Tezza story, the algorithmic allocation story. I think, you know, for most clients, the way we risk allocate across assets, utilizing alpha and kind of our risk models is a pretty good fit for most people. If you have any questions, certainly you can reach out to me. My email is Matthew at Tezza.com and the last thing

I kind of want to hit on it's a little different topic but none of you probably know this but I actually have hearing aids and I've struggled with my hearing all my life and especially I usually don't bring this up but in the era of masking if I had to be in school these days as a fourth fifth sixth grader mask I would not be in school these days as like a fourth, fifth, sixth grader mask, I would not be sitting here today due to my, my hearing. So just be kind to others. Uh, you know, it, it might help in terms of spreading disease, but there's certainly consequences. So, you know, speak up, listen to people, help people out, you know, be kind. You never know what issues other people are going through. And that's, that's the end of,

of, of that. Amen. Love it. Um, be kind, speak up, tell my kids, I'm going to tell my kids that story and say, Hey, this is why I need to speak up. Um, really important. Speak up, look someone in the eye. I met so good to see you hopefully next time on the slopes in Utah. Yeah, sounds good. I appreciate the opportunity and have fun and stay up straight. All right. Thanks. 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. And be sure to leave comments. We'd love to hear from you. This podcast is provided for informational purposes only and should not be

relied upon as legal, business, investment, or tax advice. All opinions expressed by podcast participants are 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.