Replicating Babies, Trend Following, Hedge Funds, and Warren Buffet with Corey Hoffstein

If a replicant in the 1980s sci-fi classic Blade Runner was a genetically engineered, bio-enhanced person with para-physical capabilities, “composed entirely of organic substance,” created for slave labor – what does that make Corey Hoffstein @choffstein and his takes on replicating?  On this episode of The Derivative, we’re joined by the model flirting, possible replicant, Corey Hoffstein, who takes us through the intricacies of replication strategies, comparing different approaches and digging deep into the pros and cons of indices vs strategies vs replication. Learn about the challenges faced by replicators in the hedge fund industry, the importance of benchmarks, and the complexities of dispersion in managed futures.

Corey and Jeff provide insights into the factors that drive trend-following performance in different markets, explore the potential of alternative markets for managers, and delve into the replication of Warren Buffett’s strategy, decoding its secrets. Plus, Corey discusses risk weighting, the role of market makers in the ETF ecosystem, and the integration of AI in various domains. This conversation goes beyond robots writing catchy descriptions. Get ready to become a replicant — SEND IT!

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Check out the complete Transcript from this week’s podcast below:

Replicating Babies, Trend Following, Hedge Funds, and Warren Buffet with Corey Hoffstein

Jeff Malec  00:07

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 I’ve been walking with my son on some golf tournaments this week it’s been fun but boy those kids good 70s For 13 and 14 year olds Wow. You know who else is good the pros on our panel out in Vegas that we got coming to you on next week’s pod with Cem Karsan, Zed Francis and Luke Rahbari edition on all things vol. Including zero d t e, vix and where we go from here on to this episode, where we’ve got the replicant of Corey Hoffstein speaking on replicating trend following how all that works from the top down and bottom up approaches wide dispersion of managed futures results might not be as bad as it looks. And I’ve got to say this Cory is an A plus plus podcast to go along with being an A plus plus pod host, which sort of annoys me that he’s that good at everything. But hey, if you can get him on the pod get him on a pod. That silky deep bass voice the intelligent answers the probing questions. He’s a pro’s Pro, send it. This episode is brought to you by our Sam’s guide to trend following white paper. We talked about the conflation between managed futures CTAs and trend following names in this pod. And we cover all that and more in the white paper plus highlights on top managers. Stats definitions, all the good stuff for trend following go check it out at RCM also.com today and now back to the show. All right, everyone, we are here with Cory Hartstein. Cory, how are you?

 

Corey Hoffstein  01:50

I’m doing great, Jeff, thank you for having me. How you doing?

 

Jeff Malec  01:52

I’m great. We were just debating offline the origin of the Lanai and if he’s become a Floridian enough to use the word Lanai instead of porch.

 

Corey Hoffstein  02:01

I’m not there yet. But I also don’t know whether I have a Lanai we really need to look this up.

 

Jeff Malec  02:07

A carport is not a Linna. Right? The so since you were on the pod last you’ve had a baby. How’s that all gone?

 

Corey Hoffstein  02:15

I will tell you I was I was actually just texting my mother earlier saying I don’t know what everyone’s complaining about. Babies are easy. Now this is mind you after Nakatsu. Two and a half months of just my child would not sleep last night. He slept for 12 hours. It actually got like, I couldn’t sleep because he was sleeping so well. I’m afraid something was wrong. Yeah, it’s

 

Jeff Malec  02:38

mine had, what did they call it? Group that group or whatever, where they cry, like every night from four to 8pm? Yeah. Which was awesome.

 

Corey Hoffstein  02:47

Yeah, we’ve got more recently, like six to 7pm. He sort of gets that witching hour. But for a while he just I didn’t know this about babies. He was like a night grunter. So he was asleep. And he would sleep for hours. But he would just make these grunting noises in the bassinet which made it impossible for my wife and I to sleep. So right on there. What’s wrong? Yeah. And so well, we had them sleeping next to the bed and the bassinet because he was young enough. And we eventually just said, This is insane. So we started taking shifts, we’d be up for three hours and then the other person, and then my in laws, who are phenomenal live near us. And they would come in and help do some shifts during the night. But knock on wood. Hopefully he’s sort of figured it out.

 

Jeff Malec  03:28

You’re strong enough for the co sleeper I would do that. And like reach over to grab the baby and to my wife in the middle of night and like throw out my shoulder.

 

Corey Hoffstein  03:36

Yeah. Well, I you know, I won’t say I was great. My side of the bed didn’t have room for the co sleeper. So it was always on my wife’s side anyway, so I wouldn’t even waking up and she gave me a firm, a firm elbow and a kick to make sure I was up to help.

 

Jeff Malec  03:53

All right. For all those people who didn’t come here to have us talk about babies, I’ll just offer my What am I now 12 and 14. So if you have any questions, shoot them at me. I appreciate it. The one now was the 12 year old just turned and she’s getting a phone, which I was heavy against but everyone else has and how she’s supposed to take pictures when we’re on vacation. That those are good questions, right? Good questions. But if Twitter and Facebook ruin her brain, I’m going to be upset. Let’s talk you had a thread, which was great. This is the multiverse where you had a thread on results paper that we’re coming into a podcast to talk about. So as a paper turned into a Twitter thread turned into a podcast, which then we’ll do a blog post about so that’s how the multiverse works. But something I’ve been in running into more and more replication DTMF came out, screaming out of the blocks so to speak. Was that two years ago,

 

Corey Hoffstein  04:58

two years ago, a little over three years ago. because they had their three year anniversary,

 

Jeff Malec  05:01

right? So that was a big deal. Everyone’s talking about that. Now we started, I’ve started to hear more and more about let’s do this. Let’s do that. Let’s just replicate it. So wanted to start with your kind of 30,000 foot view of like, Why? Why are we seeing more efforts at replication? Or are we or is it just that I’m noticing it more?

 

Corey Hoffstein  05:18

Well, I will say, I think strong kudos to Andrew beer here and his his team with DBMS. He has been a longtime advocate of replication. And I think he’s done a tremendous job in trying to educate the industry about where replication works and where doesn’t. If you go back and look at the literature, this was a really popular area of research for quants, in sort of 2007 through 2012. area, and there were a lot of replication ideas and indices that got proposed, many of which fell flat on their face for potentially methodology reasons. And there was I think the consensus of the research ended up being that, yeah, you might be able to broadly use factors or market betas to capture some of these hedge fund concepts. But look, if they’re if they’re creating true alpha, then then you shouldn’t be able to use the broad betas, right? It is the idiosyncratic return that really matters. I think Andrew presents us with a lot of nuance to say, there are categories by which you absolutely should not do replication. And there’s categories and I think the two, he would really highlight our Managed futures and long short equity, whereby it does seem like you can actually capture a really significant proportion of the total return using replication. And then if you can do that, and dramatically reduce the fee, not just, you know, the flat rate go from 2%, to say, 1%, but get rid of the carry, you know, the two in the 20, part of the 20, the incentive fee, then whatever you missed in the Alpha, you might be able to more than make up. And I think it’s a really great story. I think the last point that I would look at is is when most allocators look particularly at the Managed futures space, trying to make a decision about whether they want to allocate to manage futures, they’re very often using an index. They’re using something like the SOC Gen CTA index, or Barclays top 50 index, and then they’ll do a manager search. And this happens to be a category of pretty high dispersion. I think what Andrews argument has long been is if you’re using the index to make your allocation decision, why aren’t you trying to get index like returns? Like why is that not good enough? If that’s what you built your allocation around? I don’t know if we’re seeing a huge rebirth in replication. But I think when it comes to fortiAP products, I think replication is an interesting approach that can be used for smaller teams to try to give beta like exposure to these hedge fund categories.

 

Jeff Malec  08:00

And then it’s interesting as you were talking through that, I’m like, yeah, oh seven through 12 was all about risk premia. Right? That was the same thing, right? They’re just rebranding it now replication. Right?

 

Corey Hoffstein  08:11

I would, I would say risk premiums may be a little bit different than replication. But but the broad concept being a lot of these, what used to be fundamental discretionary ideas can be replicated with a systematic approach. risk premia was packaging that up from a quantitative investment strategy perspective and putting them in indices. I think replication is more is less about implementing the strategy necessarily, and more trying to create the return stream. And there’s a subtle difference there. And we can talk about the different ways in which replication works. But but it’s not about saying, you know, hedge funds do XYZ, and we’re gonna replicate all that mechanically. It’s hedge funds, do x, y, z. And actually, it turns out by using a combination of credit stocks, bonds, and short vol, we can get a return profile that looks very similar from a big muscle movements perspective. But

 

Jeff Malec  09:04

I think in managed futures in particular, they might be one in the same thing, or maybe that’s why replication so like the strategy, you want the index and the strategy to kind of be the same thing. And

 

Corey Hoffstein  09:16

this is this is an area again, where there’s a lot of conversation. So Andrew had a great not to talk about another podcast on your podcast. Yeah, no route, but But Andrew had a great conversation with Tim Pickering on top traders unplugged recently. Tim is a longtime CTA he was one of the first people to actually put a CTA in an ETF almost a decade ago. And so he and Andrew had had a debate because Tim is much more of a classical CTA Tim takes very strong off benchmark views he he happens to be very commodity focused. Whereas if you look at the broad socked in CTA index, it’s actually more equal risk weight between bonds Come on. oddities, equities and currencies. Andrew saying if people are looking at for the SOC Gen index, they should just buy something that replicates it as closely as possible. What Tim is saying is they can they can look at the SOC Gen index and still find value in off benchmark weights in tracking error that’s more valuable to the way they’re building their portfolio. And that that active approach can add a tremendous amount of value for allocators. So it’s a very open discussion, and I think that’s very healthy for the space.

 

Jeff Malec  10:27

I heard that there was a bit of an odd debate, you thought it was good debate? Well,

 

Corey Hoffstein  10:32

I believe they were, I think they were talking past each other. And I know both of them. I think it was one of those debates where it is difficult for two people who don’t know each other, to be thrown into a situation where they’re debating virtually, without a huge amount of context for the other person. And so I think it was a tough conversation, I would say, I think there were points, the two major points that they were disagreeing on, I think they were just largely talking past each other.

 

Jeff Malec  11:01

I kind of hate that phrase talking past each other. Right? What does that mean? Like, they were, like, we were both ignoring what the other was saying. And just,

 

Corey Hoffstein  11:09

we’re just not understanding what the other one was saying. Yeah.

 

Jeff Malec  11:12

And do you think replication is a American thing? Is it right? It seems to me there’s something in there like, oh, we can just cheat this, we can do this better than innovation. We’re entrepreneurs, like, why do we need to do the full thing we can just write like, it’s like a four hour work week? before? Yeah. Yeah. Like, it’s still don’t

 

Corey Hoffstein  11:32

know if it’s an American thing, necessarily, I don’t have enough context for that. What I do know is that the regulations here for the types of vehicles that we have, allow us to do things that aren’t necessarily as easily done in Europe, in particular, putting commodities into an ETF or mutual fund, often via a caiman blocker is a lot easier here than say, trying to get commodities into a traded product in Europe. So there’s a lot more complication around that in Europe, there’s a lot more. And again, I’m not an expert in the in the regulatory side in Europe, so you’d have to talk to someone who’s done that dance. But my understanding is, it’s just less trivial than it is here. There’s still plenty hoops to jump through here. But it’s much harder over there. And that might be one of the reasons you’re not seeing the adoption. And then I will also say having product both in the US and in Canada, different regions have different appetites for product. Right? ESG is particularly strong in Europe. And there is very little appetite in the US right now for ESG, despite the fact that major index manufacturers have been trying to push it for a decade. And so you just find different regional appetites as well.

 

Jeff Malec  12:42

And like, every third thing I read is about ESG. But it’s not big. It’s not big here, but you must read about

 

Corey Hoffstein  12:48

  1. Yeah, exactly. Well, they’re doing everything they can to make it big.

 

Jeff Malec  12:53

And then do you have any thought like we run our monthly asset class scoreboard, where we show managed futures versus hedge funds versus real estate? And just for ease of writing that post every month? Right? We just use these ETFs? So the one we use for hedge funds is QA I IQ hedge multi strategy tracker ETF? So essentially a replication strategy. I don’t know really actually what it does. But a lot of those I’ve seen on the hedge fund side haven’t really worked. So then my brain goes, have they not worked? Or is that a true representation? representation of what hedge funds have done?

 

Corey Hoffstein  13:27

Yeah, so I think it’s that that’s the interesting question, potentially, is, if they have track their index perfectly, but the index hasn’t done well, would you say the product hasn’t done well? Or is the product done exactly what it said it was gonna do?

 

Jeff Malec  13:40

Right. And but it has a hedge fund where you’re like this was supposed to make 40% a year what’s going on? Yeah, I

 

Corey Hoffstein  13:45

think the reality is, when you look at Broad hedge funds as a category, I It’s been a long time I know exactly the product, you’re talking about q Ai, that was one of the first replication ETFs that came out, I think it’s got well over a decade track record at this point. HF nd is another one

 

Jeff Malec  14:01

that came out 600, I was looking at it before this does 600 million in assets, you start a billion.

 

Corey Hoffstein  14:07

And if you look at the methodology, and again, it’s been ages, since I’ve looked at this, my recollection is that it’s looking at a broad hedge fund index. And then it’s using a regression based approach to buy US equities, bonds, gold, basically major asset classes, and trying to capture the beta elements. And then with the idea being that when you look at hedge funds in aggregate, those beta elements are not moving incredibly fast. And so you can catch the turning points and capture the major muscle movements. I actually don’t know what index they’re trying to track or whether they’ve done a particularly good job of tracking it. But that does sort of tell you the core concept, which is when you average all these hedge funds together, their alphas all sort of cancel out. You’re left with a bunch of beta common betas and hopefully we can use different betas to replicate

 

Jeff Malec  15:00

And then I think I’ve told you about this friend of mine here in Chicago runs a couple of funds. One’s a venture capital index. That’s pure replication has no actual exposure to venture capital. So it’s basically a little more long NASDAQ, short, some s&p to get the blue buds, enter and get the real pop real convexity of the NASDAQ. And then they’re talking about doing one in the healthcare space and some other stuff. So it’s like, how far can you push this? How far can you go to like, yeah, we’re, we’re replicating healthcare costs with E Mini futures like, what is there? Is that real? Or is it just anomaly?

 

Corey Hoffstein  15:36

There were some papers that came out a while ago about replicating E E and VC using levered small cap, you have to take the Right Sector tilts? I think the common idea here is whether private or public, whether hedge fund, are there common betas, right? Are there common driving factors, that if we’re looking at trying to capture like, not a particular VC or PE fund, but the industry as a whole to all their bets, sort of average together to look like a levered equity market data? And if they do, well, then why don’t we just do levered equity market data? I think against the same concept, whether you’re looking at a diversified basket of hedge funds and trying to replicate that diversified basket of managed futures managers, or trying to look at some of these private funds, right, can you do? Can you try to replicate private real estate investments with publicly traded REITs? Maybe. But I think that’s a lot of what we’re seeing nowadays. In fact, I think an ETF just launched recently, as early or maybe it’s launching tomorrow, depending on when this this is timestamped. That is, that is someone who’s trying to replicate privately traded REITs using publicly traded REITs.

 

Jeff Malec  16:56

So you can’t get out of the 10. Yeah, exactly. Yeah. We’ve replicated it, your money is now locked up for three years. Yeah. But that makes me think of like, everything’s just equity exposure, right? Like if we can replicate all this stuff with different leverage versions of different equity sectors. That really proves the point that hey, you think you’re diversified? You think you’re in this hedge fund strategy, that all strategy really all you have is some different levered version of some equity index?

 

Corey Hoffstein  17:25

I think the core question sort of becomes, how constant is that? versus how much does it change? So I went through this exercise years and years ago, I wrote a wrote a research note on my blog called Attack of the Clones, clever Star Wars reference, but it was all about Yeah, there you go. It was all about trying to replicate long short equity managers. And what I found was that you could get a high degree of replication to a broad basket of equity, long short managers, using things like broad equity exposure into the US international exposure, emerging market exposure, but you needed some other factors in there, like you needed to be able to make growth versus value tilts, large cap or small cap tilts. And if you had the ability to make those tilts, what you found is you could replicate pretty closely. But those tilts were definitely time varying. So for example, what I found in just the replication was that the index was heavily tilted towards foreign markets in the 2000s. dramatically cut its its net equity beta in 2008. And then when predominantly towards us equity markets post 2008. Now if I just said, I’m going to replicate equity long, short, by just having a beta of point two or three to global markets, it would be a much noisier fit than if I had these other micro levers that I could change over time, based on how the index performance was changing.

 

Jeff Malec  18:59

Do you think there’s anything to like, God, that’s too simple. You think investors are like I want the fancy, I want the big deck on everything that’s going on, instead of like, Hey, I give you point to beta to the index enjoy it.

 

Corey Hoffstein  19:11

I think there is a certain degree of the index is fine. But I there’s particular managers that I think will outperform the index or for the particular allocation. I want to choose a subset of these managers like I don’t just want equity Long, short. I want health care long, short, because it fills out something in my asset allocation profile, right to the conversation that Andrew beer and Tim Pickering we’re having. Tim might say, look, managed futures is phenomenal. But if you’re a stock bond investor, a commodity tilted managed futures product is better than a benchmark product because it’s more likely to have structural diversification versus what you already own. Yeah. I agree. Disagree. It doesn’t like I just think it’s an interesting argument, right? I don’t know. Want to again make his argument for him? But the point there is okay, how relevant is the benchmark? Like, maybe there is a good reason why you would choose an off benchmark manager, and therefore replication isn’t the approach you should take. And the

 

Jeff Malec  20:13

thing of replication is kind of like you’re throwing in the towel, it’s like that stat 76% of drivers think they’re above average drivers. Right? I think it’s right. But the same with investment, right? Like 78%, think they can beat the index, right? If you’re like, I’ll just do this replication strategy. It’s almost admitting like, I know, I can’t beat it, I know, I’m not going to beat the index, let’s just match it.

 

Corey Hoffstein  20:35

And the index for many people might be exactly what you want, right? Unless you like, let’s consider, let’s go back to manage futures. How many people really have the capacity and wherewithal to understand manage futures managers and do the adequate amount of due diligence, like they might be able to understand the category and they might be on there understand the historical return drivers, they might like the diversification profile. But can they take that next step to say I can choose the manager that I have a higher degree of confidence in? That’s a different skill. That’s not the same skill as being able to do top down asset allocation manager due diligence is a unique skill unto itself. And so I think we can have a little humility to say I like the category like what it’s doing. I like investing in equities. But that doesn’t mean I can pick a good equity manager. It’s not throwing in the towel to buy equity beta. It’s one of the best long term drivers of returns ever. Right? Yeah. Yeah. So so if I say, I like me as futures as a category, is it throwing in the towel if I buy five managed futures managers? Because I don’t know which one to pick? Is that any more throwing in the towel than trying to replicate the index?

 

Jeff Malec  21:46

Good rhetorical question, we’ll leave it possibly. Let’s get into your thread the thread on the paper on the Twitter. You started out by basically like, Hey, look at all the dispersion of managed futures. That’s a problem because you can’t or you don’t maybe want to prove what you just said, you don’t want invest in all 30 of them. So let’s do five of them or let’s do two of them. But then you have this dispersion, you might pick the wrong two. So I have take a little issue with that dispersion chart. I know it’s not yours is that result, but that again?

 

Corey Hoffstein  22:23

Yeah, this isn’t mine. So I don’t I like don’t get Don’t get mad at me for a chart. That’s not mine. But I know what you’re saying. Yeah.

 

Jeff Malec  22:28

Well, I just quickly, and I am the guy who like okay, let me look under the hood. So I looked under the hood and all the ones in that chart. And it’s it’s got ABI in there that has Crable, which is super short term, pe that’s a currency trader episode stem. That’s super high frequency. It’s got the Alpha centric one that’s 50%. mortgage backed securities. It’s got low cores, long, short commodities, no equities. No. So there’s a lot of stuff in there. It’s got man HL, who knows what they’re doing these days, they have AI and all sorts of stuff packed under that. So it’s a common problem in our space, right, like managed futures, what does that really mean? And if you just quickly take that jump to that means trend following. Yes, you’re gonna have a lot of dispersion in there. But you’re also going to have a lot of dispersion from the trend following index. Right. So? Well,

 

Corey Hoffstein  23:18

I think I think the broader issue here is, as an industry, CTA managed futures and trend following all became synonymous. Historically, they weren’t right managed futures was a category of strategies that was mostly being implemented by CTAs. Using trend following. More recently, that’s that’s diverge, particularly in the 2000 10s were trend following didn’t work as well. You had a lot of folks start to introduce carry and other different types of strategies, seasonality, Relative Value trading, all of which get are done via futures, and are typically major strategies. So I think if you look at the sock, Jen CTA index, I think it’s still over 50% trend, but there’s still there’s now a decent amount of area and other stuff going on in there. Right. And so that to me,

 

Jeff Malec  24:06

that explains, yeah, most of the dispersion is explained by that. Hey, yeah, great does down 4% Because they do it sounds good. Let’s try it. So let’s

 

Corey Hoffstein  24:14

explain. But but let’s like just let’s assume we’re only talking trend following First, right, let’s get rid of all the other variables. I mean, there is a huge degree of dispersion that it can occur just within trend following because of all the degrees of freedom of choice, right, so So let’s start with a couple of things we can do when we’re building a trend following program. One, what’s the universe we’re using? Right the futures market you I’ve seen trend followers who do nine futures markets and I’ve seen trend followers who do 90 Plus, right to what speed of trend are we looking at a really fast trends all the way to intraday to really slow trends. blends in between you’re gonna have massive dispersion from that So how are we doing risk weighting? Right? I mentioned the index tends to be like 2525 2525, commodities, currencies, equities and rates, sort of on average. But you look at individual managers, they’re nowhere near that. Right? You get massive. Anyone who’s just listening, there’s a, there’s a pirate walking around a very, very handsome pirate lock in background there is so so you can get some like very off benchmark weights for individual managers, someone might be very heavy commodities, you see these managers who will say, you know, what, we’re only trading rates and commodities, no currencies and equities, or you might be constrained in different ways. And then it’s a question of how are they running their portfolio optimization? Are they doing risk parity weights? Are they doing mean variance optimization? Are they doing something more naive, more complex, all these degrees of freedom of choice lead to really big dispersion in the space? And the numbers show that like, Yes, I get that chart that was put together in the paper maybe has more dispersion than just pure trend following. But when you look at academic research, this is a category that has some of the largest dispersion as a category where buying multiple managers has proven to dramatically decrease vol, dramatically decrease, realize drawdown dramatically decrease dispersion and terminal wealth over the long run, which is also a sign of just, again, large dispersion between managers, because there’s so many ways in which they can do things differently.

 

Jeff Malec  26:42

Yeah, my pushback on that would be like, if you spend, I want to say 10 minutes, but let’s call it 10 hours, and dig into what they’re doing. You don’t have to have a PhD and due diligence, but just like you’re saying, like, they trade our trends on just fixed income, like, Okay, I’m probably not getting the trend following profile I want out of that manager. So of course, there’s going to be bigger dispersion there. So if you’re, like, really want that index performance, and you focus in your search, on the ones that give you that index performance, it’s not as hard as, like the replication seems to be fixing a problem that maybe doesn’t exist in that regard. Maybe but all of them are

 

Corey Hoffstein  27:17

getting rolled up to the to the broad index, when people are allocating from a top down perspective. And they’re looking at I want the sock Jen CTA index, these different managers are getting rolled up, you look at let’s let’s not even talk about hedge fund indices go to Morningstar, right, they’ve got I think, managed futures category and systematic trader category, the dispersion in there is is incredibly large as well, because they’re just sort of catch all categories, there’s so many different ways in which these concepts can be implemented, that it becomes really hard to come up with subcategories, or maybe not really hard, but they just don’t want to do the work because there’s so many funds there. And so you say, Oh, I’m allocating to this category, you choose any three managers at random, you’re gonna get very different performance.

 

Jeff Malec  28:04

We could do a whole pot on there’s like, manager, firm level, alpha and choosing the right category, right? If you’re in the wrong category, and maybe no investor sees you, you’re absolutely you’re at the top of it. And you might be doing the same strategy. But you’re like, Well, I’m a performer in the option space.

 

Corey Hoffstein  28:21

Don’t think that people don’t try to game that and Morningstar for sure. Yeah, for sure.

 

Jeff Malec  28:27

So, moving on, let’s get to the you mentioned before, top down, bottom up, explain some of that. Oh, I wanted to one more thing on all these manager choices like, especially in that future space. Like I want to say, of course, this is doing that estimate, but maybe if the public doesn’t know, right, or doesn’t care to know, does it make a difference? So it’s making this kind of to your point of like, install? It’s still all in there. It’s all rolling up in the CTA index. I would argue it’s not rolling up in the trend index. Right, because that’s designed to fix that problem. Yeah,

 

Corey Hoffstein  29:03

a little bit. Look, I mean, there are trend followers. I’m blanking on the name, but I was listening to a great episode with a trend follower. Their firm specializes in only doing alternative markets, right? You’re you’re talking, you know, Turkish interest rates, and you’re talking inflation swaps. They don’t they don’t hold any of the major markets. They do trend following. And it’s all alternative markets, in their view, is there a completion manager that there’s really a lot there alpha as a firm as all the operational work it takes to actually trade these markets. That sort of thing is incredibly hard to package in a mutual fund or an ETF. But that’s going to have a huge amount of dispersion relative to the index, perhaps it will have a decent amount of alpha. I haven’t looked at the numbers. But it’s an interesting concept. Again, it’s going to look very off benchmark by definition, and maybe that’s a good thing. Maybe that’s a bad thing. When you start to think about putting these into a mutual fund or an ETF you start getting hit structural limitations of the vehicle choice itself that does narrow some of this dispersion but even still you can find a pretty decent degree of dispersion among managers even just this year look how different managers responded to the bond rally and march were they using stops you know, how much did they have bonds a lot a little you know, all that stuff really. They cap it by market by sector Yeah, exactly create the creates a pretty strong level of dispersion.

 

Jeff Malec  30:29

While you brought up those unique markets, we had Sarah I’m gonna forget her last name here live but um, used to be at AQR working on their trend. Would you call it unique markets or the alternative markets alternative markets trend, which led them into crypto now she’s doing crypto for Coinbase asset management. But my question herd which interested in your take? Who wants that? Like, cool, I’m gonna get this alternative. Maybe it performs well, but how much am I going to allocate it to where it moves the needle on my main trend? Like it’s almost not in there for a reason? It’s not going to take your trend was down 10%. One year, it’s not going to take it to up 10%. Right, maybe it takes it from downtown to down nine?

 

Corey Hoffstein  31:11

Well, I think there’s two questions I would ask and I’ve never done due diligence on these managers. So I don’t know how they would respond. My first question would be how much capacity to these different markets? If I’m trading Chinese Apple futures? How much can I start to allocate before I dominate that market? But I think I would answer on their behalf, which is, you say trend is up 10%? Or down? 10%? Is this really going to be up 10%, it might be these markets might be so different. That you’re you’re not expecting it to behave like the benchmark. And if you can make it a large part of your allocation, before they have to close the Fund for capacity reasons, that can be a really valuable diversifier as an allocator now, I did listen to an interview with this manager. And they said actually, surprisingly, like, even though it’s all alternative markets, they actually catch a lot of the major standard market movements, because correlations or correlations, you know, like, there’s only so many global macro muscle movements that are happening at any given time. These things sort of bleed into each other. And so even though they tried to say alternative, they did sort of track broad trend, exposure at large.

 

Jeff Malec  32:23

Yeah, no, my mind was saying more, if the main trends down 10. And this thing can be up 100. But how much are you realistically in an allocated, allocate to it where it’s a meaningful portion? And that’s going to take your negative 10 to plus 10? On the portfolio level?

 

Corey Hoffstein  32:38

Right? I mean, I feel like I would argue diversification is always valuable, right? No matter how much you have in it, whether it’s a small amount or a large amount, it’s just a question of comfort with that manager. So if you can get the diversification, you should almost always add it.

 

Jeff Malec  32:58

So let’s talk the paper the thread, they took two approaches top down and bottom down. Let’s start at the top. See what I do. Yeah.

 

Corey Hoffstein  33:06

So this is a question about like, replication methodology. Right? Yeah. Like, what will how do we replicate? So there’s a lot of ways in which you could replicate a strategy. So let’s often find talking about hedge fund replication, like mainstream replication be a little bit more confusing than it needs to be. So I’m gonna talk about replicating Warren Buffett, because I find that that’s actually an easier way to explain it.

 

Jeff Malec  33:28

But that’s it. Yeah, yeah.

 

Corey Hoffstein  33:30

So let’s say let’s say we wanted to replicate Warren Buffett’s returns the returns of Berkshire Hathaway, we didn’t actually want to buy Berkshire Hathaway, for whatever reason, we just wanted to replicate it. There’s, there’s two ways that come to mind in which you could do this. There’s more than two ways you can do replication. But there’s sort of two major ways are what we call top down and bottom up, top down basically says, Well, let’s look at the returns of Berkshire Hathaway and try to identify the portfolio of stocks, which stocks and how much we should allocate to them, that would give us a return profile that is as close as possible to the return profile of Berkshire. Right. And so you can use all sorts of mathematical techniques to try to suss this out. But the the salient point here is that we don’t actually care how Warren Buffett is picking stocks, all we care about is trying to find a portfolio that gives me returns that are super close to his portfolio and the returns, in theory, we would hope it actually backs out exactly what he’s holding. But we know that Berkshire, for example, has private holdings that we can’t get. And so this mathematical regression based approach might actually identify some proxies. We can’t buy some of his private holdings, but there are public holdings that end up creating a price return stream that fills the gap. And so you get this sort of approach that says, let me try to figure out what he’s holding and how much he’s holding it. any given time to replicate his returns as exactly as possible without carrying out the pick stocks. The problem with this approach, in theory is that if he suddenly say sells all of his Geico, or all of his apple, and I’m looking at the last five years of Berkshire Hathaway returns to figure out what portfolio to own, I’m gonna miss that turning point. Right? I’m assuming that he’s holding that portfolio constant. That may not be true. And so the question is, well, how much data can I really use? How often is he going to be shifting his portfolio? Warren Buffett may not shift his portfolio very quickly, trend followers do. Right. So if I’m trying to replicate the trend following index, it’s the same concept, I’m going to look at the indexes returns, I’m going to try to figure out which futures markets to hold how much long, how much short and each, that gives me the closest portfolio to replicate the returns over the recent history. But I can’t use that much history, because trends can turn on a dime. So maybe I can only look at the last 20 3040 days of returns. And then the core assumption is that portfolio I’m going to hold for the next day, or maybe the next week. And then I’m have to do all the analysis, again, to make sure that that replicating portfolio hasn’t changed dramatically, to no longer fit the most recent returns. So that’s the top down approach,

 

Jeff Malec  36:21

which, which I was confused about and trend following space, I thought they’re looking at, hey, we can replicate a 60 market portfolio with these nine markets. But then we’re going to trend follow those nine markets. With our own model, you’re saying no, no, no bottom up, but top down is like, Hey, we’re going to just we know, over the last 40 days, a lot of this return came from being long, 30 years and some 10 years. That’s what we’re gonna hold to replicate it. And I have no trend signal whatsoever.

 

Corey Hoffstein  36:50

Yeah, and you have no trend signal. In fact, you don’t even know you don’t care that these are trend following signals. They could they could go from trend following to using carry signals. And as an all you’re trying to do is replicate the returns. Now, there are things you can do as a manager to try to like dial in certain profiles. If you do know their trend following you can come up with some trend following factors that you can try to use in your regression. Like there’s there’s ways to be smart and clever here to build a more robust system. But just generically speaking, the top down approach is to say, I don’t really care how the return profile is being generated, all I want to do is find the portfolio that replicates the return profile as closely as possible and assume I’m going to hold that going forward over some short period of time. What’s kind of cool here about this is, let’s say the sock Jen CTA index or the sock Jen trend index is what we’re trying to replicate. Maybe I like DB MF doesn’t doesn’t trade 60 markets, DB, MF trades, I think 13 markets, 14 markets, it doesn’t trade Japanese government bonds, for example, which are a pretty, you know, common element of most CTAs. But what you might find is, while it doesn’t trade JGBs, there might be some mixture of US interest rate movements, and yen dollar movements, that come pretty darn close to explain JGB movements. And so you might find that it can find it’s sort of a basis trade, by by weighting these different futures, you might only need nine or 13 futures to explain the big muscle movements of the sock Jen trend index,

 

Jeff Malec  38:40

which which comes back to the point, then why bother with those

 

Corey Hoffstein  38:45

alternative markets at all. And now you’re talking things like cotton. And, well, if you’re silver and trying to track the index, you might not need to write. So common sense here is that the index itself is made up of very large players, very large players are going to be capacity constrained, which means the majority of their dollars are getting allocated to the most liquid markets. So if you then say I’m now averaging all these major players together, those small markets become an even smaller part of the index, you need all those managers to be trading those small markets in the exact same direction for that small market to really influence the index. So you would say, okay, I can replicate the major muscle movement of the index with just a handful of 1012 futures markets that really explains almost all of it, with the caveat of, if you can pick an individual manager who’s really good, they might be able to generate a tremendous amount of off index alpha from those small markets, right. But again, that doesn’t really matter at the index level.

 

Jeff Malec  39:54

And it’s but it’s almost like the very definition of trend following you know, risk a little bit to make a lot in those markets. Like they’re almost is by definition additive. Right? Yeah. Over the long term, so it’s

 

Corey Hoffstein  40:06

generally speaking, you don’t want to forego diversification when you can get diversification.

 

Jeff Malec  40:10

Yeah. But to your point, we are there. But maybe if that saves you a 20% incentive fee? Yeah, Brian, exactly.

 

Corey Hoffstein  40:18

How much Alpha? Can they generate in that? Like, what a, what’s the probability of you picking that manager? B, is the amount of alpha that that manager can generate going to exceed the higher fee versus the replication strategy? Okay, and there? And yes, there may be a large number of managers who can do that. So that’s top down.

 

Jeff Malec  40:40

And do you think real quick, do you think top down? approach is because surely people do try and do that with Buffett and other hedge funds and right of like, we’re into these, like, what do they call them hedge fund hotels have the most popular names and whatnot? Yeah, like, we think there’s like a self fulfilling action, they’re like people are trying to get into the same name is trying to replicate and then maybe they get out too late.

 

Corey Hoffstein  41:02

Maybe there’s, I mean, there’s an inherent lag to the process. Because you’re just saying, Let me replicate the recent results, you could argue that there’s actually a self fulfilling aspect to it of if enough, people are trying to replicate they actually are chasing the managers, and creating that positive price pressure to them names. It’s it’s hard to suss that out, particularly with like 13 F types of strategies. But you definitely see that in the in the hedge fund security selection side, there are 13 F strategies that try to go through and find the high conviction names of hedge fund managers, and then replicate those in a basket.

 

Jeff Malec  41:42

All right, bottom up.

 

Corey Hoffstein  41:44

So bottom up, if top down is about, we don’t care how Warren Buffett is actually picking stocks. Bottom up, says actually, we really care. We want to figure out what he’s doing. Warren Buffett, we believe is picking high quality value stocks and then levering them 1.6 times. So what we’re going to do is we’re going to come up with our own process that picks high quality value stocks and levers on 1.6 times. And we’re going to try to pick a process that gives us that result as close as possible to Berkshires historical track record. And then going forward, we’re going to kind of ignore his track record and just keep running that process. Alright, we’re going to every day, say, okay, which high quality value stocks should we buy today and lever up 1.6 times. And we’re basically using his historical returns to inform and our knowledge of how we pick stocks to inform a stock selection process. What does that mean for trend following like, if we’re trying to replicate the trend following index, let’s Let’s now cross that chasm? Well, it might mean, what we do is we build a different set of trend following indices, we might do short term trend following intermediate term trend following slower trend following. We might do it on commodities, and rates and currencies, and all this all these different markets. And then what we’re going to do is we’re going to try to find the weights of those different systems that when taken together, broadly replicate the index. So we might find, for example, and this is something that the paper finds is that something like nat gas seems seems to be traded a lot faster by CTAs. And something like the footsie 100, or the footsie looks like it gets traded, mechanically a lot slower. nat gas seems like when when you look at the contributing returns to the index that gets traded a lot faster. You put all that together and what you’re left with is actually a set of trading strategies, and how much you should wait them. So it might say, hey, look, you need to run the 60 day moving average system on nat gas every day, you need to run a 220 day moving average system on footsy futures, figure out whether that signal is positive or negative, and then trader. And so what you’re left with is a strategy. That is generally an ensemble of different signals, right, different weights for different futures contracts that you are running every single day. And and that strategy is in and of itself, a trend following manager in many ways, created a new trend going you’ve created a new trend Trend strategy that has been designed and tuned specifically to try to replicate the way the broad index works, or looks historically.

 

Jeff Malec  44:35

So that’s interesting when you think that the standard there would be to create a model per market, because a standard trend follower says, I don’t want to do that. I don’t want to overfit. And I’m going to have one strategy for all the markets.

 

Corey Hoffstein  44:49

There’s there’s a lot of ways to do this. Right. So this is where there’s art and science into how to do the replication. All I would define the bottom up as being is you’re trying To create your own trend following strategy, where you’re selecting parameters and a weighting methodology and all of that, such that What results is a trend following strategy that looks a heck of a lot like the index. What the paper does that that resolve wrote is it, it basically creates. So there’s 27, futures markets that they look at, they create trend signals from five days all the way up to 260 trading days for every market. And then when you take 27, by all those different, you know, signals they’ve got, I’m trying to remember the number of actual trading strategies they use. I mean, it’s hundreds that you could potentially select from, if not more, and then what they do is they run a long term regression and say, What weight of all these different markets stable, Lee gets us a profile that looks a lot like the sock Jen trend index, trying to trying to maximize the diversification here to take into account diversification as much as we can, while minimizing that tracking error, we don’t want to overfit. Right, we don’t want to just rely on some super isolated fit of a market. So what you find, at least when you when you replicate that is, you get a spread, for the most part, the wait seem to be in the sort of 150 to 220 day area, it’s sort of these nine month trends. But right I said nat gas leans a little faster, footsie leans a little slower. That faster might be okay, it’s 60 days to 200 days versus, you know, the footsie is something like 150 days that 260 Like, there’s still a range of parameters that are getting used to try to create a diversified ensemble to replicate the sock Jen index.

 

Jeff Malec  46:52

And that’s super interesting to me, because I don’t know many trend fighters who might trade net gas on five day look back and everything else in the portfolio 200. So it’s like, it’s interesting of like, they’re not looking at that performance of nat gas on that look back on its own price data, is just how does it fit with the index? Does it make the index? Does it make our tracking closer or further from the index? Okay,

 

Corey Hoffstein  47:16

well, how does it combined with everything else? Exactly. And so what you find actually is, when you look at the data, not they didn’t choose 510 15, I think, I think 20 Day was the fashion or grammar that got chosen for any model. And the weight on that 20 day was like, less than 1% of the like, it’s a very small proportion of the risk, vast, vast, vast majority of the model risk is in that 150 to 220 day range.

 

Jeff Malec  47:47

And then what would you say this makes, right? Often a pan on Managed futures on trend following is like, Oh, you just make all your money from interest rate moves? Like why do I need all those other markets? If I just try and follow some, you know, the 30 year bond 10 year notes and maybe some JGB? Like you said, I can get most of the performance? I think some of that negativity also comes with like, Oh, you just get the the tailwind of holding the cash in T bills. But ignoring that for a second of like, Okay, does this all just boil down to well, yeah, of course, I just got the core of what drives trend falling performance, which is the bond?

 

Corey Hoffstein  48:22

Yeah, I’m not I’m not 100%. Sure. That’s always true. I mean, the bonds or bonds are important, I think what you do find his door prickly? And who knows where things will go. Going forward? What you find historically is like equities haven’t been a big contributor. Yeah, I think that’s predominantly not because the signals haven’t been good. But what you find is that when the signals on equities turn off, that’s often when vol, rises dramatically and equities are you have that strong negative correlation between returns and volatility Within equities, which means those position sizes in equities often get crushed pretty significantly. You don’t see the same thing necessarily in commodities where you can actually have crashes up, right. And same with bonds, like you can see crashes up in bonds, you don’t tend to see equities crash up. So it’s a very different dynamic currencies as well. So So I think, if anything, the argument I often hear is why even bother having equities? Again, I would say, yeah, it takes it takes a part of the asset allocation away from rates and currencies and commodities that you could be allocated to otherwise. But there is an argument of of diversification potential, and you don’t know what the future necessarily holds. There could be market regimes in which equities could be a much more positive contributor. I don’t think the evidence is there, at least as far as I’ve seen that it’s always rates. I mean, yes, there is a tailwind from holding cash. But what I would argue is that that tailwind exists academically in every asset class. Yeah, we always look at asset classes as their excess return, right. That’s why we talk about the equity risk premia. It’s an excess return above cash bond risk premium excess return above cash managed futures. When I look at the performance managed futures, I don’t include cash I take the cash out, because that cash return is just a risk free rate that exists as the base return for evaluating every asset class. So I think that’s a that’s a bad argument. In my opinion, I won’t say there are many organs that are bad, but I think that was just fundamentally bad. So the question of is all our other returns coming from trend following and rates? I haven’t seen it. I think if you isolate trend following and currencies, isolate trend following and commodities isolate, trend following and rates, they have all been long term return drivers.

 

Jeff Malec  50:37

We had a good blog post, maybe a year ago now when silver had a move, and I we ran it on the sock 10 trend indicators like the last 15 we’re losers over maybe 15 years or more. Right? It’s like why would anyone in the right mind to have that in the portfolio? And then this one was a Six Sigma outlier, or whatever, and but boom,

 

Corey Hoffstein  50:58

you get that massive move.

 

Jeff Malec  51:01

And how do you think about like, now I’ve created this model, it’s tracking that. But in order to avoid idiosyncratic risk, I’ve like added my own idiosyncratic risk, right. I’ve like created my own problem by trying to avoid those problems.

 

Corey Hoffstein  51:13

Yeah. So this is this is the key. Right. So this was this was a part of the conversation that that Tim Pickering and Andrew beer were really getting after each other. And that time it was unplugged. Right. Andrew saying the whole point of doing replication is to avoid single manager risk. And Tim is saying, all you’ve done is created your own single manager risk. You’re a single manager. I think the point that again, I know you don’t like the phrase, they were talking past each other. But I think I think the core point of what Andrew was trying to say is if we do a good job, our dispersion from the index, and by definition, there’s you’re not replicating perfectly there will be tracking error, that tracking error should be substantially lower than the expected tracking error of picking any one manager at random. Right? So yes, you are absolutely introducing model risk, that model risk is absolutely a form of single manager risk. It’s a question of, if your dispersion around the index is call it, you know, you’re tracking errors 300 basis points a year. But as a category, the dispersion around the index is usually 800 basis points a year, you have, you could argue you have substantially less single manager risk you have cut down on the single manager risk, because of the way you’ve designed your program to try to track the index. So yes, absolutely. Whether you do top down bottom up, there is a degree of model risk that is its own unique single manager risk, it’s just a question of if you if you can do a good enough job to keep that substantially lower than the risk. People might realize otherwise in selecting one or even a small handful of managers to allocate to.

 

Jeff Malec  53:00

And then my last thoughts on replication, we’ll move on, why don’t the big pensions institutional investors just do this on their own in house? Like why why pay these high fees and get these managers just replicate it?

 

Corey Hoffstein  53:13

Why don’t they replicate? Or why don’t they run their own strategies? Why don’t they run their own replication? Well, some of them do run their own strategies. Yeah, likely teachers. Yeah. So that that’s out there. I don’t know whether they run their own replication or not. Again, I think it’s a question of,

 

Jeff Malec  53:33

there’s probably a whole lot to that of like, well, we can’t get we’ll get fired if we run around thing in house.

 

Corey Hoffstein  53:37

But yeah, there’s definitely principal agent risks there that should be considered. And there’s the operational burden of actually doing this stuff. Like, is it in their best interest to be spending time and money to, like, try to run a trend following strategy? And then if you’re gonna do it, do you really want to try to replicate? Or do you think you can find a particular edge if you’re gonna go through or build a program that is designed very specifically, to can take into consideration the other things that are unique to your alligator profile? Right? Again, not many people have the ability to say, This is what our allocation profile looks like, let’s generate a strategy to specifically address that, because we’re not taking outside money. Most of us who are managing money have to assume that money is coming from a variety of sources who have a variety of different utility profiles and wants and needs. So you end up somewhere with a more generic concept rather than a than a hyper specific one. So there’s, there’s a variety of reasons. I would be surprised if you don’t start to see more replication get picked up, particularly as DBMS grows. I don’t know whether it just from a behavioral perspective, it’ll ever truly replace the majority of hedge funds, and I would hope it doesn’t, right, right, because in a weird circular way It needs those hedge funds to be successful at what they do for it to continue to replicate the index. It wants those hedge funds to create a good index exposure.

 

Jeff Malec  55:08

Right? It’s like Mike Greene’s passive, like if we just get all these big replicators. Right, what are they replicating?

 

Corey Hoffstein  55:14

Exactly? Exactly. So you need the hedge funds? What I would, what I would say is that what I would expect to start happening is smaller. institutions that can’t get access to some of these hedge funds might start using replicators. And the larger institutions while they’re doing a manager search, might use the replicators to fill the liquidity bucket. You see this pretty often with credit? Yeah, but they might be looking for a high yield manager. And in the interim, they’ll use something like an hyg Just as an index proxy. Yeah, I could see them doing a manager search and managed futures but not wanting the cash just sits idle and so they might use a index replicator.

 

Jeff Malec  55:58

All right, I got five unrelated, not five, three, that will go quick on the rest a wire session. No before that. Just your quick thoughts on rebalancing real quick. You want to give us your 30,000 foot view on rebalancing rebounds, timing luck. Do you have an elevator pitch?

 

Corey Hoffstein  56:17

You got you got another three hours?

 

Jeff Malec  56:19

Yeah. No, I want it in like half a paragraph and half a paragraph.

 

Corey Hoffstein  56:23

rebalance. Timing luck is one of the largest sources of uncompensated risk in your portfolio that you know nothing about. There’s there’s no but here’s the real pitch, when you rebalance. Turns out it matters a lot. It defines the opportunity set that you are seeing, which I think is make sense. So people who are rebalancing once a year and something like a value strategy. Turns out if you rebalance at another point in the year, you could have incredibly different performance. This impacts the indices we’re benchmarking to it impacts the managers we’re evaluating, and just the same way we diversify across holdings and process we should be willing to diversify across when we rebalance,

 

Jeff Malec  57:08

which is as simple as dollar cost averaging fixes that yeah, basically.

 

Corey Hoffstein  57:12

So like the the real easy fix is to say, let’s say, again, I think sort of easy to use stocks as an example, if your value manager and your for the Russell 1000 value rebalances. Once a year, well, what did you probably do, is rebalanced 112 of its portfolio every month. And in doing so it takes the emphasis off of the when there’s a very famous case of this called the immaculate rebalance Research Affiliates, march 2009. They just so happened to rebalance in March that was a totally arbitrary random decision ended up creating about 1500 basis points of excess return above their benchmark, versus if they had chosen to rebalance in September they would have underperformed their benchmark. Right.

 

Jeff Malec  57:58

They ate Balian. And

 

Corey Hoffstein  58:01

I mean, you have to ask how would history be different if they had underperform their benchmark in 2009 versus absolutely smashing it? It’s a very different path that they would have taken as a firm I would argue, to their credit, they recognized that they got lucky. I don’t know if they’ll admit they got lucky. But they inherently recognize it and move to this staggered rebalancing approach where once a quarter they rebalanced 1/4 of their portfolio.

 

Jeff Malec  58:25

Did you coined that term or that was coined elsewhere? The America

 

Corey Hoffstein  58:29

the iMac? No, that one I don’t know who coined that term. It’s one of these weird things that in certain circles is incredibly well known. And then there’s other for many other folks is just something that was lost to history.

 

Jeff Malec  58:41

And what are your thoughts I argue with our pirate friend who just walked through of like rebalancing isn’t always great, right? If you’re rebalancing into a loser, say Bitcoin since 20, whatever sensitize you are losing more than you otherwise wouldn’t.

 

Corey Hoffstein  58:58

Yeah, like I actually just argued with our pirate friend about this last week. Alright, so there’s two things I’ll say. Look, if you are rebalancing into something that’s trending, it’s gonna hurt you. If you’re rebalancing into something at the right time of its mean reversion cycle, it’ll help you. So there’s the dynamics of what you’re rebalancing into, I think that’s hard to predict what I will say at the aggregate level, right come a timer, and you’re inherently trying to find what I’ll say it at the aggregate level right is compound annualized growth rate is approximately equal to your arithmetic expected return minus your variance drag. If I can rebalance, and keep my expected return the same right? What rebalancing does is it hopefully keeps minimizing that variance component right by because let’s say I don’t rebound let’s say I have stocks and bonds and I don’t rebalance for 30 years. Well, what happens? My portfolio is if as stocks go up more than bonds will become more are more stocks. And at the limit, the variance will then approach the variance of an entirely stock driven portfolio. And the expected return might go up. But what you might find is the compound growth rate actually goes down, right? The expected return might not compensate you for the variance drag, versus if you can rebalance back to the profile that maximizes the compound growth rate. Right? That has nothing to do with whether the assets are trending or not, you’re what you’re trying to do is maximize the expectation, the expectation of growth. And so to me, rebalancing is much more around making sure we’re diversified in a way that is maximizing our opportunity for compound growth.

 

Jeff Malec  1:00:42

My second quick one was the ETFs versus mutual funds. You said on a panel in Vegas, not everything needs to go into an ETF.

 

Corey Hoffstein  1:00:50

God knows my words against me, Jeff,

 

Jeff Malec  1:00:53

do you have a quick explainer on that? Yeah, so now it seems like everything we just talked about, like, well, you could just replicate it and put it in an ETF?

 

Corey Hoffstein  1:01:00

Yes, strategy and structure are different things. Right, and an ETF and a mutual fund are fundamentally different things. For those who aren’t super well versed, the way to think about it is a ETF is really just a mutual fund that trades on an exchange. But that last element is super important, because it means the market maker community is really intimately involved. And it requires a high degree of transparency into what you’re doing. So there are certain strategies, or certain things you might want to hold, that would make it hard to put an ETF. So there’s a well known CTA that I tried to hire as a sub advisor for one of their strategies, where they implement some shorter term mean reversion concepts, five day type strategies. And after doing the legwork with them, they said, Look, we can’t take this and put it we can put it in a mutual fund, but we can’t put it in an ETF. Because we think we don’t want to disclose these trades, that transparency element is a problem. And some of the things we trade, we don’t think the market makers are going to feel comfortable hedging. So for example, one of the things you’ll see is some of the CTA based ETFs really focus on making sure the futures that are trading are European and American listed. Yeah, you don’t see Asian listed futures in those ETFs. And that’s because it’s really hard for the market makers to try to hedge a product when the futures aren’t trading. Yeah, right or sleep, when there’s like, you don’t need that in the mutual fund. Because the mutual fund only needs to strike nap once a day, you’re not trading an intraday and so the types of products that can get wrapped in ETFs have to consider the entire ecosystem in which they exist. And the market maker is a huge whale in that ecosystem.

 

Jeff Malec  1:02:56

And explain that real quick, like in my mind, and some investors might like when I buy an ETF, you’re selling your shares, I’m buying my shares, and we match off against each other. And the market makers matching us know, right, like the market makers actually buying and selling from us. Yeah, what I mean, right, so he’s wearing the risks until he can offload that risk.

 

Corey Hoffstein  1:03:15

Yeah, and a lot of this comes down to how much liquidity is on the order book. How much liquidity will the market maker actually ingest? A lot of like standing liquidity has more to do with how much is the average volume trading, right? The market makers, they have capacity constraints, you know, if you’re, if your ETF is trading $500,000 It’s not like they’re gonna leave $20 million, just sitting on the order book, they’re gonna have substantially less, right. They don’t want to tie up capital. But the real measure is, what’s what’s the bid ask spread? The tighter that is, it means the market makers more comfortable, immediately hedging whatever they take, because, yes, in theory, you know, in an ETF that’s trading a ton. You might get players matching off against each other, but the reality is, almost every time you’re probably selling to a market maker, who’s then maybe turning around and immediately flipping it to another market participant, or if they’re acquiring inventory, they’re they’re gonna have to hedge it

 

Jeff Malec  1:04:19

get your thoughts on AI while we have you in chat? GPT. And we’ll start with good bad, indifferent for society as a whole.

 

Corey Hoffstein  1:04:28

This is an area that I can I can only speculate. I think it’s I think it’s really cool. Yeah, I think there’s some things about it that are that are really cool, that have nothing to do with the potential productivity lift that we can all get right. I think we’re already seeing ways in which it can get integrated into music and help people write things. I think there’s some things that are incredibly scary, like we’re already hearing about scam calls or voices are being replicated. I said to my wife, do you ever get a call that I’m I’m on the other Lying on the phone saying I’ve been kidnapped, just hang up like my voice is too out there assume it’s fake. All right, we’ll start with the people at podcast and around. Yeah, I mean, come up with a code word for sure. One of the things that I am kind of endlessly fascinated with, though, is the idea that all of these things are being trained up to a point in time, which means once it’s trained, right, there’s this snapshot that’s occurred of whether the training is right or wrong, it sort of incorporates all the bias within what it’s learned up to that point. Which means to me in 100, to one or 300 years, there might be the opportunity to go back and start to query that data set at a point in time to understand the bias as it truly existed then, versus the way it’s been written in history books, right. And I think it’s a very cool concept of being able to encapsulate everything known up to a point and be able to interact with that data and query it to really understand what what did people understand what was the bias at the time that was ingested within the data? And how did that evolve over multi 100 year periods?

 

Jeff Malec  1:06:03

That’s a cool insight, right? Like, it’s basically I can talk to this medieval times, Lord, yeah. What’s it like,

 

Corey Hoffstein  1:06:10

versus the way the history books were rewritten? Right?

 

Jeff Malec  1:06:14

And what do you think? Does it do anything for you modeling portfolio type work? Like that’s what’s weird in MySpace, cuz it’s like been here in our quant world for a long time? Yeah.

 

Corey Hoffstein  1:06:24

I mean, machine learning techniques, right? are just really, a lot of them are just sophisticated statistical techniques. I don’t see the AI of chat GPT being particularly useful, especially if it’s not fully online. Right? You need something that’s constantly ingesting the new data. If it’s trained up to last December, that doesn’t really help me.

 

Jeff Malec  1:06:46

It’s cool for me to think about like, one, your kid probably might have this always on tutor. Right, that has infinite patience. Infinite empathy. Can I don’t quite understand what you’re saying, okay, tell it to me, like, I’m Dora the Explorer, whatever, like, right, you can switch it all up. And it just

 

Corey Hoffstein  1:07:02

the interactive teaching, I think is a fascinating element, though. I’m sure you’ve seen the same things I’ve seen which are these hallucinations, I guess what they’re calling them like, They that it’s literally making up sources. So you have to learn a new skill will be identifying don’t hallucinate, right? AI that is lying to you. It’s not intentionally lying to you. But like, you know, that famous study, not the famous study that famous case where a lawyer tried to use it to write a brief. And then it was citing briefs that didn’t actually exist, and they threw it out. And the judge asked him about it, and then he tried to use it to make the briefs that didn’t exist. I mean, just compounding integrity issues, you’re obviously digging the hole, right. But the point is, like, I heard about this really cool homework that a professor gave their students that said, I actually want you to use chat GPT to write an essay about something you know, a ton about. And then show me all the ways in which chat GPT is wrong.

 

Jeff Malec  1:08:00

Ooh, that’s good. That’s a good feature, though. No, do you think RAS will start using it like, Hey, call our chat GPT line to talk about your portfolio or whatnot. Like instead of, like, just imagine the scale you can get like, I know, you’re worried I’m gonna give you a call. But it’s not really them calling. It’s just because all you say on those calls is a bunch of it’ll be fun long term.

 

Corey Hoffstein  1:08:22

So I chatting with Dave, Dave Natick, about this from Delphi. And because he is he I think his title is like Future. Future risks, basically, yeah, that might be his exact title. He thinks about this stuff all the time. And I said to him, I’d be really curious to have a survey among advisors to, to understand what part of they their job they think is best replaced by chat GPT or other sort of AI? Is it the conversation with clients? Is it responding to emails? Is it dealing with some compliance stuff like what what part of their business can actually be enhanced? I would wager that they, most advisors would feel like that human element can’t be replaced. You need to talk when someone needs to talk to someone, they need to talk to someone. Right? But if someone’s emailing in asking about an account paperwork thing, is that something that can be automatically reply by Jeff GPT 99.9% of the time, maybe that point 1% of time, it gets it wrong, though? Well, it sounds like a big risk to me. Yeah, I

 

Jeff Malec  1:09:34

lost that client.

 

Corey Hoffstein  1:09:35

And where and where’s the how do you talk about being a fiduciary in some of these cases?

 

Jeff Malec  1:09:41

Yeah. Who’s the fiduciary?

 

Corey Hoffstein  1:09:42

Who’s the fiduciary?

 

Jeff Malec  1:09:43

Well, for sure, I think it’ll be this email, right? There’s gonna be new footers of like this email was aI assistant or something, right. All right, something new going to try with you. Again, You pick the guinea pig of some. I don’t know when he caught word association ones. Yeah,

 

Corey Hoffstein  1:10:07

I’m gonna give you some words. This is some psychological stuff here.

 

Jeff Malec  1:10:10

Right then we’re gonna do Rorschach tests. This is a verbal podcast, Rorschach test, which I had to take as a young child of divorced parents. I’ve actually had to go to a psychologist and I was messing with the lady. I’m like, That’s my dad beat me up. That’s my mom lock me in the car. And finally, after like six questions, the lady’s like, Oh, I see what you’re doing. Stop it. Then I’m like, fine. It all looks basically like spaghetti to me. I’m hungry. Anyway, that was my personal version. So word association game. You ready? Let’s do it. All right, Jason. Buck. Handsome. Still, everybody hear me? No. Yeah. Tampa.

 

Corey Hoffstein  1:10:52

Tampa heart.

 

Jeff Malec  1:10:54

Boston. brick. Brick interesting. We’re on a location basis here came in, came on. Swimming, swimming. Did you ever switch to that came on pronunciations.

 

Corey Hoffstein  1:11:12

I gotta tell you it took me forever to try to figure out how to pronounce it. The the way I tried to get it listen to the radio is it sounds like caveman caveman. To see man caveman? Yeah, Caveman and No, I never I never got there

 

Jeff Malec  1:11:28

podcasting exhausting. This my favorite the next one clients.

 

Corey Hoffstein  1:11:38

Clients clients. This is a tough one. I don’t I’m trying to give a single word like I have amazing clients, by and large who asked me really thoughtful question. So the word I want to use is something like it’s about the feedback they give me like it’s it’s they they push me to look and research into new areas. There. It’s not inspiring, but it’s something along those lines.

 

Jeff Malec  1:12:04

Inspire full compliance.

 

Corey Hoffstein  1:12:11

necessary evil.

 

Jeff Malec  1:12:12

Good. And fts. Underrated under still, I was thinking you might go burn marks but still underrated.

 

Corey Hoffstein  1:12:23

I think I think the majority of the space is complete garbage. I think there is some really interesting technology within the NFT space that gets overlooked because it’s all people are going it’s just a bunch of annoying monkey JPEGs. But I think there’s some really cool stuff that can happen there.

 

Jeff Malec  1:12:42

I almost bought a $5,000 lightsaber. jpg back in the day, I might have to go look at that. It’s probably $5 And they’re

 

Corey Hoffstein  1:12:49

very cheap now. Yeah.

 

1:12:52

Gold complex. BMW. BMW.

 

Corey Hoffstein  1:13:06

falling apart is one minus. I got a 15 year old Beemer that I love and it is just followed me everywhere and it is falling apart at the moment.

 

Jeff Malec  1:13:15

I saw it when we did our illegal rum transaction. And that’s around the side of the highway.

 

Corey Hoffstein  1:13:19

I had to do a lot of work to it recently. And the mechanic just kept calling me he’s like, Well, I don’t know if you know how you have this problem. I was like, I didn’t know it explicitly, but i Yes, I just Just give me the laundry list at the end.

 

Jeff Malec  1:13:32

What do I do? Yeah, diapers. Papers. positive trend. Expensive. rucksack.

 

Corey Hoffstein  1:13:49

Shoulder pain.

 

Jeff Malec  1:13:50

Shoulder. You’re the like, I can’t believe you’re posting that stuff. You’re out. We’re out at like, 4am with the rucksack what? Yeah, unbelievable.

 

Corey Hoffstein  1:13:57

It was well, it was my last it definitely was my last time. I mean, I this was one of those I knew a kid was on the horizon. It was going to be the last time I could really pursue at least in the short term, like a real lean in in physical challenge. And so it was this luck. It was like 28 mile ruck march through the hills of Pennsylvania. I really wanted to push myself so I think I spent four or five months training for it. It was and then I haven’t picked up the backpack again and I don’t ever want to how many pounds it ended up being just around 80 pounds. Oh, you’re

 

Jeff Malec  1:14:30

a good one to ask this. Did you see Mark Zuckerberg stats on his? The Marine test? What do they call that?

 

Corey Hoffstein  1:14:38

What I gotta ask what what do you think is happening from a PR perspective here? Like there has been a strong change in marks like PR team pushing his jujitsu and it’s

 

Jeff Malec  1:14:52

like that just he’s watching those pictures of Bezos Bezos. Yeah, I want to be jacked and cool like you

 

Corey Hoffstein  1:15:00

Like, Oh, that’s right. I could do something with all this money to prolong my life forever, right?

 

Jeff Malec  1:15:04

I think that’s probably but yeah, there’s no way they were like, Oh, he was two minutes off the world record. Yeah, yeah, no last one Rome underrated, underrated

 

Corey Hoffstein  1:15:17

mass. I think rum is massively underrated everyone. Actually that’s that’s another word for that might be dispersion that is a category of massive dispersion because there’s really no rules when it comes to rum. But I think you can find some incredibly high quality rums for incredibly cheap relative to Bourbon and scotch. And people who are bourbon drinkers like there’s certain rums I would steer them towards Scotch drinkers or certain rooms I would steer them towards, if you’re like me, and you just naturally have a sweet tooth. Like there’s other rums just I just think they’re really underrated. By the way, I want to change my answer on Jason, he is incredibly handsome. I thought he was just there and could hear me potentially Darren’s got headphones on. Jason is this isn’t a single word. Jason is the most interesting person I’ve ever met potentially, for sure. You know, I like I’m not going through every single person I’ve ever met. But Jason is hands down one of the most interesting people I’ve ever met, if you can actually get him to talk about himself. Yes,

 

Jeff Malec  1:16:13

that’s the key. I keep trying to break him because I give him clothes every time. So I’m like, Here, here’s a t shirt. Here’s this. But he’s known for only living in having

 

Corey Hoffstein  1:16:24

a single single bag somehow pulls it off incredibly stylish is lived all over the Americas North and South America. Multiple lives within entrepreneurship, you know, from from high highs, the low lows, and it’s somehow just knows a little bit about everything in a very annoying way. Yeah, I

 

Jeff Malec  1:16:46

said that. He’s like, Well, I only know I like know, 90. I know about this 99% More than everyone else, but nowhere close to the people who are in that top 1%. Like yes, but when you know that about 99% of the stuff that’s I know.

 

Corey Hoffstein  1:17:00

I’ll be like I know this obscure fact about Aussie rules football, it will be like Well, let me tell you where that came from going back to the 1800s I’m like, How do you know this? Yeah.

 

Jeff Malec  1:17:13

What to well, Ren? Yeah. All right. Well, I’m looking forward to your rum success. Do you think it’ll be like the next right all these people made a billion dollars off their tequila? Branding? You think that’s coming next with celebrity? No, I

 

Corey Hoffstein  1:17:25

think what’s more likely is that I will lose a lot of money. Yeah, trying to launch rum. Yeah, I mean, this is this is listen, I am not Ryan Reynolds. I am not the rock. I do not have the following that is required to launch an actual liquor brand as I keep trying to explain to Jason but guys Guy No. No.

 

Jeff Malec  1:17:47

All right, man, this has been fun. Thank you for having me. Everyone go follow Cory Twitter listener flirting with models, podcasts and listen to the Pirates of finance. what else what else you got? That’s it. That’s it.

 

Corey Hoffstein  1:18:03

That’s it. appreciate it as always my friend.

 

Jeff Malec  1:18:06

All right. Good talking to you. Okay, that’s it for the pod. Thanks to Corey. Thanks to RCM for supporting thanks to Jeff Burger for producing. We’ll see you next week with Cem, Zed and Luke PEACE.

 

This transcript was compiled automatically via Otter.AI and as such may include typos and errors the artificial intelligence did not pick up correctly.

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