The Derivative - Do Hedge Funds Suck? With Max Nissman, Olivier d’Assier, and Scott Treloar

Episode Date: July 30, 2020

We sat down with three different legs of the hedge fund stool who (feeling the currently hedge fund investment landscape is a bit broker) are partnering on bringing some disruption to the hedge fund space with a new platform/fund of funds approach to analyze and allocate to different strategies.  This three-way conversation touches on the perception that hedge funds suck in light of their stock market underperformance, and what investors can do about it. We’ve got Managing Member at Linnis, Max Nissman, Noviscient’s CIO, Scott Treloar, and Managing Director at AXIOMA, Olivier d’Assier. Are hedge funds outdated? Do they still provide the value that their known for? Are we being too hard and we shouldn’t “fix what isn’t broken”? Can AI help identify the poor performers. Take a listen. Follow along with our guests: Max Nissman on LinkedIn and the Linnis website. Scott Treloar on Twitter, LinkedIn, and the Noviscient website. Olivier d’Assier on LinkedIn Chapters: 00:00-01:50 = Intro 01:51-14:41 = Origins 14:48-29:21 = Hedge Fund Space 29:28-52:56 = Secret Sauce & A.I. 53:04-58:02 = Favorites And last but not least, don't forget to subscribe to The Derivative, and follow us on Twitter, 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

Thanks for listening to The Derivative. 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. 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. So, you know, and then you say, well, do hedge funds return? And then you say, well, what is it? What sort of risks are they really being exposed to? Are they long? You know, a lot of hedge funds are still running long market and if market crashes they do badly they they're stressed a little bit i think because the ones that generate good returns in a sort of uncorrelated way um if the equity markets are really doing well they underperform even if their kind of return

quality is different, right? So then their investors look at them and say, well, how come S&P was up 20% last year and you were up 8%? And they sort of feel, well, maybe I should take some market risk and sort of smooth it out. So they didn't have this weird thing happening. All right. Hello and welcome back to The Derivative. I'm your host, Jeff Malek, and looking forward to a bit of a hedge fund three-way here tonight with a manager, a quant analyst investor, and founder of a disruptive multi-strat hedge fund to fund

slash overlay slash platform that has brought them all together. Our three guests hail from across the world and we're excited to get into the nitty gritty about quant strategies, hedge funds, fintech and the future of our industry. So welcome guys. Thanks for having us. Thanks for having us. Yeah. So some quick introductions. Joining us today, we have Max Nisman, co-founder and managing member of a short-term systematic trading shop, Linus. We have Scott Treloar, co-founder of Novician. Say that again for me, Scott. Yeah, Novician. Novician. We just found out that I failed in the first two minutes. So co-founder of Novicient

and Olivier Dossier, head of applied research at APAC. So thanks for joining us all over the world, guys. We have Max in California and the rest of you are in Singapore, is that correct? Yes. But not together, right? Together. No, no. Olivier's in the boardroom, I think. Got it. So, Scott, I kind of wanted to start with you and have you set the scene, if you would, and lay out how and why the three of you ended up on a podcast together. Kind of the quick origin story for how you three fit together without going into too much of the nitty gritty of of your project but set the scene for us if you could yeah so um i used to work i was a sort of portfolio manager and chief risk officer for a fund here in singapore we were out trying to raise capital and we found it you know extraordinarily difficult we figured that we could generate sort of better returns, but capital was very hard to get, particularly from the big pools of capital endowment funds, even the very

large family offices. It was sort of flowing more towards safety, towards brand name funds, towards the big houses. And they have a sort of role but the interesting returns are coming from the smaller managers so the challenge was how do you actually open up the pipeline between smaller managers and the bigger pools of capital excuse me and sort of technology is a natural way to do that. So a platform that allows boutique managers that could be managing anywhere between 20 up to, you know, really up to half a billion dollars in capital, allows these managers to connect to a platform using APIs. We can then select dynamically which of these strategies are generating alpha at the time, construct, put them together dynamically.

In other words, a sort of dynamic portfolio allocation to build custom products for investors. So what we're really trying to do is to bring this industry, which to our minds, to my mind, is still operating as if it was the 20th century rather with spreadsheets and pdf reporting and and poor alignment bring it sort of online and into the 20th century so so having this sort of dynamic connection to groups like max where instead of a sort of standard fund of funds we take capital and we give it out which

means the same due diligence processes have to happen regardless we have to do due diligence on on 20 of our small managers we flip it so we take the signals in and what that means is you know what's relevant for us is the ability of max people like max to generate alpha signals. We can then get them executed and constructed into alpha portfolios, but we sort of start to reduce the whole due diligence process. It doesn't take us two years to make a decision. We can run real time risk management online. So that's the sort of bringing the industry into the 20th, 21st century.

And so we kind of have investors, so Olivier is both an investor into that firm, but also an investor into that fund. And Max is one of our sort of, you know, really interesting alpha partners in that, you know, his Linus strategy generates alpha, but it's also uncorrelated to broader markets, to other strategy classes, even negatively correlated,

even tends to outperform in periods of stress. So we're trying to construct alpha solutions for medium to sort of bigger investor pools by dynamically combining all these sort of interesting managers like Max. And so you're sort of the glue here of saying, hey, I want to build something where I can get big money access to these niche managers. Max is one of those niche managers.

And then Olivier said, hey, I really like what you're doing. I want a part of that both as a kind of an angel investor in the company itself, and then also as an investor in these end strategies. Yes, correct. Absolutely. Fair way to sum it up. Yeah. And sort of using platforms and some smart machine learning to do that, right? Starting to work in with technologies and APIs and connectivity and that sort of thing that exists now and exists in other industries, just not so much in finance yet. Yeah, and we'll dig into that a bit. So with that scene set, let me get into some of the quick bios here. So Max, I'll bring it over to you

first let's talk about your hat what do you what do you got going on there well it's kind of double meaning i mean i love math uh that's that's what i studied that's what i use every day um but also it's not seeing us on youtube he's got the uh just a black baseball cap with M-A-T-H, math, and bold letters on top. Yeah, and then it's also, it was Andrew Yang, one of the Democratic candidates. I just, I liked his approach, you know, kind of science, numbers-based.

A technocrat might be something that would be interesting to have in office. But, you know, he was a far way off. But I just love the slogan was a far way off. But I just love the slogan, Make America Think Harder. Wait, what was it? What was his pen? Math?

So the math stands for Make America Think Harder. Ah, okay. And then so it's a double meaning. Yeah. And then you said you're out in California right now? Yeah, first trip since the lockdown in NYC in mid-March.

So we're based out in New York. I typically travel a lot, but yeah, this is the first trip I came back to see my family. I haven't seen them for a while. Got it. And then what's your... So before you were at Linus, what was the quick background? Yeah, I met my business partner, G. Lynn, at BlackRock in 2010. We were both portfolio managers.

He was running a very early form of what we were doing in cash U.S. treasuries. And we kind of hooked up and started thinking about ways to take it into a incentive fee-based product internally, externally. We didn't get started until 2014. It was pretty early in our careers. Prior to that, well, at BlackRock, and prior to that, I was doing mortgage-backed securities. So, I had started at Merrill Lynch in January of 2008 in mortgage-backed securities research. Ah, great timing. Yeah, I'm a good market timer. Mortgage-backed securities 2008, managed futures 2014. My next move, you know, maybe do the opposite. Yeah, so it was at the time before the crash,

it was one of the kind of hottest quant products with copula pricing and all this kind of exotic pricing that was being done to price CDOs and mortgage-backed securities etc it was interesting when I had gotten out of my graduate school program in math but it quickly became a pretty much a distressed credit product where I was reading prospectus all day and not really doing a whole lot of math so when 2010 when I met G and he was working on a quant strategy and I was still doing mortgages, I just kind of quickly saw the value in what he was doing and appealed to me because it really went back

to my roots in education. I love it. So, Olivier, let's bring you into the conversation here. Let's give us some quick background, what you're doing now. So, well, I started as an investment banker, actually, for the first nine years. Every company I've worked at has been bought by someone, right? So I've had a similar kind of luck. I started working for Smith Newcourt.

I don't know if some of you may remember, it was a British market maker. It got acquired by Merrill Lynch. And then I worked at Niko Securities. It got acquired by Citigroup. And then I worked at Barra for seven years, got acquired by Morgan Stanley. And then I worked at Axioma for the last 14 years. And last year we were acquired by the Dirtier Borsa Group and merged with their stocks and DAX indices business into what we call Contigo. So I had applied research for AsiaPAC at Contigo and I've been in the quant field all my life, basically. And Contigo, any relation to the water bottle that we see all over the US? No no I guess not no it's Contigo with a Q actually. Yeah and no

and no relation to Contango in the futures markets. That's right Contigo is the only Spanish word together since it's three companies together in one. I like it and And so your quant background, what does that look like? Hardcore programming or on the applied math side? No, I see the programming. That's where you lost me because when I studied, I had Cobalt and Lotus 1, 2, 3. I didn't even have Excel yet when I went to college. So all my coding practice was useless. It's become obsolete. I've learned all of my coding on things that don't exist anymore.

It's like being Atari champion. What's that do for you today? Right, right. My wife works for Blue Cross here in Chicago, and they finally figured out they needed a new system to run the database of the claims because the guy who knew how to run the legacy system started coming into the office with an oxygen tank. And they're like, all right, we need to move off. I don't remember if it was Lotus or one of those, but there was key man risk there for sure. Great and then so Olivier how did you get tied up with Scott and what interested you in some of what he was doing? So the interest came from two different reasons I mean

the first is I work in financial services and the capital markets so my income is highly correlated with capital markets. And therefore, I'd like to find an uncorrelated source of return to invest my savings. Otherwise, I'm just doubling up on the same bet. So talking with Scott over the years, the last two years, and hearing about what he's doing, I thought that was great. Because looking for the needle in the haystack by myself, you know, I have a full-time job, so finding people like Max from Singapore with a full-time job is very, very difficult.

So the ability of Novi Science to find these needles for me, and instead of me finding one needle every two years, I can just simply buy the box of needles straight from Scott that was an instant appeal for me. It's always amazing to me how few people in finance understand that concept that they're double or even quadruple leverage yeah right and i have a lot of people because they've got their think the same way their fee yeah it's crazy because they've got their fee revenue they've got then their personal exposure their clients exposure so they've got way more exposure than they think that's right. Let's get into just the hedge fund space in general a little bit.

We just put out a blog post a little while ago asking the question, do hedge funds suck? Sort of tongue in cheek, but when you look at the stats, you know, and of the HFR indices and whatnot, you know, they have, they've given, they lost a little bit less in March and April when the market was crashing. But, you know, in 19, they've made significantly less than the upside. So it seems if you're just a novice investor saying, hey, I want to get into these hedge funds. They look like they make 15% of the upside and capture 80% of the downside. There's not a whole lot to like there. What are your guys' overall thoughts on that picture of hedge funds?

Let me jump in. I know Max has some ideas on this. Let me jump in first. I think even this idea of hedge fund, I don't know what that word means, right? Is it a sort of unconstrained investing style? Is it a way to transfer wealth from investors to hedge fund owners? That sort of thing. So you know and then you say well do hedge funds return and then you say well what is it? What sort of risks. Are they really being exposed to where they're long in a lot of hedge funds are still running long market or and if market crashes, they do badly. Dr. Michael Duignan- They they're stressed a little bit. I think because Dr. Michael Duignan- The ones that generate good returns in a sort of uncorrelated way if the equity markets are really

doing well they underperform even if they're kind of return quality is different right so then then their investors look at them and say well how come S&P was up 20% last year and you're up 8% and they sort of feel well maybe I should take some market risk and sort of smooth it out so they didn't have this weird thing happening as a guy best binder who wrote some stuff about how do you you have if you go and talk to hedge funds say show me your high convictions trades and you look at the performance of those high conviction trades, they actually do quite well as alpha there. But what they've also added to smooth everything out is all these sort of low

conviction trades, which strip all the alpha away. And what you're left with is sort of, you know, negligible performance. And they've sort of done that because investors are still kind of return centric, right? Their ability, and it's a broad generalization for investors, but it's not really untrue. Investors think about returns, but they don't often,

even in quite sophisticated places, get down to the depth of, okay, what's the sort of quality of returns? What's the sort of risk exposure that I'm having for that return stream? And so from our point of view, you know, we try to think about, well, there's three categories of return. There's return to cash, time value of money. There's return to exposure to various risk premium. And then there's mispricings and dislocations, which is alpha.

And, you know, any sensible investor. And slowly the really leading edge pension funds are starting to kind of come up towards this kind of more structured factor-based approach. But right now it just feels that we're in the midst of just weirdly enormous confusion about what is a hedge fund? What is alpha? What is beta? What is excess return? what is risk, what does it all mean, which is weird, but, but reality. Yeah. But I think to my point,

you can look at it across different hedge fund categories and it's sort of across the board, you know, and there's a bunch of issues with that, right. You're taking the average, you're not taking the best, you're realizing a lot of the worst when looking at those indices um so yeah and i we're all proponents of it we all are drinking the kool-aid but i'm just in your dealings with investors of are they believing in the world of hedge funds or not i Again, I understand what you're saying. It comes back to what is that worry? Yeah. So, yeah, the average is the problem, right? The stream that I want to cross is only two feet deep on average, but halfway down, halfway across, it's 12 feet deep and I sort

of drown because on average it's two feet. So averages kind of cover a lot of sins uh investors um uh i think this they're getting desperate right it feels like you know they are sort of what we might call gambling for redemption or sort of punting, almost lottery-like, right? We know that bond yields are very low. We know equity markets look precariously high given the potential shocks and events, maxes events that exist. And so sort of say,

I just hope I can find some good hedge funds that work. So let me clarify that. Hedge funds on average are going to, I think there's just too much money going to the very big funds, and the very big funds cannot deliver any excess returns because they become the market, essentially, right? So this channeling of funds, of hedge funds, $3.5 trillion, maybe $3 trillion now, 80%, 90% head towards the very big funds who just deliver some sort of more market-like return. And then the more interesting funds, the half a trillion dollars of boutique funds that can deliver the excess returns

are a bit hard to find. They can deliver if you can select them, if you can find them, if you can get access to them. We see that in our results. On average, it looks terrible. So you need help. That's the sales pitch. Yeah, I agree.

Max, what are your thoughts? Yeah, I mean, I'm pretty cynical about the industry. I think it's pretty much fundamentally broken for probably a number of reasons. I don't think incentives are correctly aligned. You know, at the end of the day, everybody just wants to keep their job. So not naming names, but there's a lot of people who you could give all your money to and they haven't done well. I don't think that they're going to do well in the future, but you probably won't get fired for it.

I think post-financial crisis with a lot of the fraud that's been, was uncovered, some of the big stuff out there. I think, you know, there's, people are shying away from the small managers. They're just a due diligence risk. So yeah, I mean, Scott said a lot of the money is just going to the top. But even at that point, you know, you'd think that, okay, the top has to just invest in some basic stuff and they are the market, then at least they could do a little bit better than the

market. I'm always surprised to see pretty much every risk parity portfolio as far back in time as I can look, it's publicly available. I don you know, I don't know about the private funds, but all the guys with mutual funds, et cetera, their benchmark is 60, 40 bonds equities. That's essentially what they're trying to beat. They've all dramatically underperformed it over three years, five years, 10 years. If you look at the fund to fund community,

a lot of them have pretty strong factors to most basic factors, equity factor, bond factor, often trend factors, yet they're sharp one maybe. And I'm looking at if you were just to blindly slam together stocks, bonds, and trend, you'd be much higher than sharp one. So it's kind of like, what are you doing wrong? I don't know. I don't know what all the issues are, but yeah, I mean, I've kind of created a very, I shouldn't, I shouldn't say it very unique. That's not proper.

I've created a unique product uncorrelated to really anything out there. That's been able to deliver alpha over the last six years um but being different is a double-edged sword i've created something but it's different it doesn't check people's boxes um there's a risk of us as a small manager at least that's a you know perceived risk so yeah i just think you know what people like Scott are doing and, and there's other, there's other people out there. Some of the large, you know, large multi-manager kind of potted out shops have certainly figured out this idea of number of uncorrelated returns, return streams, combine them together and create a higher sharp product. I like to say diversification is the closest thing that we have in this industry

to a free lunch. So some people get it, but surprisingly, it seems like most of the industry doesn't. Yeah. Sorry, go ahead, Scott. We think there's kind of a cost and information problem for investors getting through to Max. There's a cost problem, which is, you know, they have to go meet Max and team 10 times and do all the due diligence and it takes them a long time to finally decide and they're never quite sure from his returns. So it's costly and slow, but it's also information. How do you find Max? And then the analytics around, is his strategy really alpha or is it just a lucky strategy that delivered something good over a short period? And so there's sort of skills to identify that are you know, are around, but they're not everywhere. It takes a little bit of nuance to figure that out.

So there's kind of these two obstacles to try to get through to max. And you might expect the consultants and the sort of allocators to be better at it, but they're under pressure. They're risk resource constrained and time constrained and cover your ass job security incentive constrained. So as we're sort of very consistent with Max, we think the industry really needs new thinking, some new innovative approaches to break some of this method of operating. Hedge funds worked 20, 30 years ago when

hedge funds used to be running hundreds of millions of dollars. Now they're running tens of billions of dollars. Just excess returns, impossible. It used to be less efficient so you know those good managers, hedge fund managers, probably had some information advantages, right? But they could deliver excess returns. There were a few of them around. And now this, the industry has really changed and become different. And this concept of hedge fund, you know, the big AQR, you know, and even he says he's not a hedge fund, right?

So these big hedge fund giants just can't deliver returns um so how do we open up the channel for those managers that can and olivia what what are your thoughts on right my my thoughts are if i'm the big allocator my issue is i understand that there's maxes out there in the world who can deliver alpha. My problem is if I pick 10 of them, if I get the wrong one, the dispersion is way bigger, right? Between the worst performing one and the best performing one versus if I pick these large guys, the dispersion is really small. So I might not get the best, but I'm almost guaranteed not to get the worst. How do you look at that from like a quant perspective? So for me, I mean, the issue is,

again, that search for uncorrelated returns, right? So we know there are maxes out there. And the job doesn't stop at finding them. Okay, you found max. And as you say, okay, now I've got to find another max because what I'd like is a 10 max kind of strategy to basically diversify away my key man risk. But so ongoing, you have to be able to look at these guys and say, okay, is this still working or is it not working? And when I have this other strategy, the dispersion is getting big, but it's going in one direction.

Should I start to move together with it? So the amount of work that has to go on managing that pool of managers is also quite onerous. And if like me, you have a full-time job, you'd like to pass that on to someone. What Scott's platform has within NoviScience is the ability to test those strategies live, ongoing, make changes to the mix dynamically, which, you know, is something I wouldn't be able to do as an individual. Or, you know, by calling my account manager at the big firm who happens to be on lockdown right now so I can't reach him. Those kinds of things. So the technology comes to my help here because I definitely think, I don't think the entire financial services industry is broken because we have people like Max and others out there. So finding alpha or manufacturing alpha is still working in places. I think the distribution model is definitely broken.

And that's what NoviScience does, is it brings investors and the alpha generators together in one place. It's like having an entire financial services sector in your pocket. That's for me is a key aspect to it. And definitely where I think the industry is going moving forward. Everything is shrinking. Every industry, every sector, every process is shrinking thanks to technology. What Scott has done is just fast forward that.

And obviously the alternative or the hedge fund type of segment, these guys are early adopters. So that's the best place to start with this kind of platform and to try to bring investors and alpha generators together in an exchange platform and forego all the other middlemen in between. That's a good segue into Scott explaining a little bit more of what, say one more time for me, Novician. Novician. So tell me one more time what Novician's secret sauce is, so to speak, right? Like there's plenty of platforms out there where you could pick a menu of different hedge funds there's plenty of fund of funds out there where they're doing the due diligence and and collecting good

managers where do you see your difference in that spectrum right yeah so we're trying to we say we say this I'm not sure if people kind of get it. Sorry, I'll keep ripping it. No worries. I'll summarize it again. We're trying to bring the industry online. So we use a platform model not to help an investor find a manager, not a sort of matching platform.

I think you need to have a transformation function within the platform. Investors don't really say, I want that fund and I want that fund. What they really want is a sort of return profile that suits what they need, right? Their existing portfolio that helps kind of complete it and, and add value to it. They're not looking for seven hedge funds. They're looking for some sort of return profile.

So, so this idea of a platform that solves some of the cost and search problems, how do we find max? Let's take counterparty risk and operational due diligence out of the picture so instead of pushing money out where we have to do that sort of due diligence we take signals in so we're just thinking about a sort of signal stream rather than wearing it will lose capital somewhere having a sort of real-time control in over those signals so we run

real-time risk control so if any strategy is kind of having problems we can shut them down instantaneously rather than a month later when I get my PDF from a hedge fund saying you lost 8% and then we can dynamically construct so so essentially the secret source is the modeling that we do around Max's return streams to identify this there's some sort of hierarchical Bayesian probabilistic modeling that tries to sort of filter out okay is there alpha in this strategy if so then we can start to allocate capital to it how much capital well depends on the sort of objective

function of the investors so there's some modeling around trying to build the return distribution for the investor so the kind of two core bits of IP which are enabled by the platform but they are selection based on the existence of alpha and allocation, which then combines distributions. And so it's a little bit opposite of the, or contrast that with the old school model, right, would be to fly your analysts around the country, around the world, meeting with hedge fund managers, and they're kind of sizing them up asking a bunch of due diligence questions that may or may not apply uh and just getting a general feeling of if they quote unquote understand the strategy um and then all you know so there's that qualitative

piece and then there's the quantitative piece that many of those are doing it sounds like you're kind of saying hey we just we're going to discount that qualitative piece a little bit because a lot of it's fluff and we're going to increase the quantitative piece tenfold and have it really be a big data-driven approach.

So if you're a, there's a sort of false positive, false negative thing here, right? If you're a big allocator and you've spent the last 18 months and a few hundred thousand dollars investigating this manager you're really your pot committed and poker parlance right yeah that's right you're in right so you're very scared of making a mistake because you can't really get

out the day after so you're kind of very scared of false positives in other words I think they're good it turns out they're not good but what that means is you miss a whole lot of uh you know have this false negative problem right you reject a whole lot of strategies that potentially were good because you're so scared of of of getting putting money into the you know a lot of the the solutions for a lot of guys is to not take the calls in the first place to avoid getting committed, to avoid getting too involved. I just won't take those calls so I don't fall in love with a guy or girl. Exactly.

And if you're a $100 million manager and maybe you could go to $300 million, all that cost and effort is just not worth it for most consultants. You're not going to make many fees from it. So even if the returns are there, the technology doesn't allow you to kind of, the economics don't allow you to do it. It's just not worth it, but it should be, right? Technology should allow you to get much more granular to filter out the really good managers.

Let's make some friends or enemies in the industry here. Consultants, pension and endowment consultants, net positive or net negative for the clients they serve? What's everybody's side? Statistically, they're flat, right? Flat to negative. There's no... Consistency, that's the problem, yeah.

Yeah, they don't deliver. They're not selecting the right managers. And they're also naturally, for job reasons, predisposed to allocate because it's simpler and easier to just push your money to the very big funds, right? You keep your job. You stay in that centre of distribution, right, rather than some risk that you choose the wrong funds.

So they're not doing a good job I would say. Max what do you reckon? Honestly I don't know many people out there they're doing a good job I don't know the numbers for the various kind of sectors of investments but I mean the really good guys out there seem to be running pretty big multi-strats with a number of different strategies and a large number of managers. I just think it really comes down to diversification at the end of the day. That due diligence work is a lot. I mean, I talked to some of these large kind of multi-manager platform, you know, either allocated out or even internally multi-managers and it's a lot of resources to do the due diligence and everything, but the diversification model has never been broken.

Like that's really what works. And this, yeah, this idea of chasing big managers, chasing pedigree. This is something I hear a lot. So for some reason, I don't know why we don't qualify as having pedigree. I graduated second in my class out of 600 students at University of California in Berkeley. Summa cum laude, double major in mathematics, NYU, financial engineering master's, one of the best programs. Like, you know, I've worked at the big shops, but people like these kind of rock star names and they come and they go pretty quickly in most cases.

So, yeah, I just think people, most people are just not very well focused on what really makes a good investment and what makes a good investment and what makes a good portfolio and are probably underperforming. I think most people should just go back to 60-40 bonds honestly. If they don't want to do the work on finding someone like me, just do 60-40 bonds or 50-50 or something like that and don't touch it. Just let it sit there. It will grow eventually. I would argue that diversification has broken many

times, right? It was diversify between 30 stocks in the Dow, you're fine. And then diversify between growth and value, then diversify into foreign, then bonds, then foreign, right? So like every time they get a, although 60-40 is hung around for a pretty long time, this might be the final straw on 60-40 with bonds at the zero bound here. Yeah. Yeah. I mean, it certainly has a risk. And I mean, I'm just kind of saying 60-40 as, you know, an example of something that's been around forever and anybody could essentially implement in a very low fee, you know, buy the Barclays Aggregate ETF and the S&P ETF and call it a day. You want to get more diversified and diversified across regions, you know,

geos. That's one thing. You could obviously now get pretty low fee trend products too, which I don't believe is a crisis alpha, but it is an uncorrelated alpha. It's struggled for many years, but it's uncorrelated and you throw that together, you know, you have a kind of third uncorrelated piece to the story. And then, you know, maybe eventually you start getting into some other things that are not as broadly known to the regular investment community. But, I mean, yes, anything that you say probably eventually will be proved wrong in this world and in finance.

So I'm not saying it's bulletproof, but it seems to work a lot better than everything else I see going on out there. I'm all for keep it simple, stupid. Keep it simple. And then I would also argue that there's, as we noted, there's $3 trillion of investor bets on hedge funds that do believe in their diversifying powers and that aren't turned off on it, right? Like we've kind of made it, or not you guys, but I've kind of made it sound like investors are flooding out of the space in mass, but quite the contrary, they're holding in there quite a bit.

But it's all about, for me, knowing that I have transparency into my personal investments. So Scott will show me how my fund is doing daily I can get out of it you know when I when I want he is also able to through the platform if max has a bad day decide that like we're gonna drop that for the next few days or something until he gets it back and so on and so forth so that kind of dynamic process which I would not be able to do a by myself and B,

even if I was able to call Max and he has something like a month in liquidity, it wouldn't help. I would probably be getting out at the wrong time. When as a two, no intent, I can, you know, get out instantly and actually I don't have to get out instantly. Scott does that for me so i like that yeah and i think kind of in my mind around all this is the concept of the narrative right like too much of the industry is narrative based you know the monthly the quarterly hedge fund letters that are either making up outright making up stories for why

they did this or the market did that or worse maybe that they actually believe so it seems for saying novice Ian can kind of cut through all the narrative BS and just help you understand the true return and risk profile and and make sure you're comfortable that and then deliver that for you. And the transparency that comes with it. Yeah. Yeah. I mean, there's, there's people make decisions on stories or data, right?

And Max and Whit, we are trying to shift that towards the data side and away from the story side, because the stories are, are often these sort of exposed rationalizations of some gut decision that you made you know that lacks a lot of objectivity and is quite biased so we want to scientific the industry yeah and the world the world's hurtling towards that in every endeavor right like my father-in-law will still be like okay if you're getting over to that side of town go down this road over to here turn left there and I'm like there's a there's an app for that it'll tell me exactly the time and which roads to go on and he's like yeah but that's just guessing right that's just and I'm like no it actually pulls in real-time data from all sorts

of different sources and tells you the traffic and he's like no that can't be so it's we're still a little far ways off but right i think that the more quantity you are the younger you are you kind of get this of hey the world is moving towards algorithmic decision making and this should be no different you shouldn't base your investment decisions on Bob's recommendation or, right. Or some other narrative based item. So you bring up a good point. The fact is, you know, quants have been around now for 20 years. So 20 years ago, they moved to, you know, data driven decision-making,

but what we're seeing today is exactly what you described. It's real time data decision-making instead of, you know, yeah, I've got the annual reports from these guys. I got the quarterly reports. I'll crunch the numbers and get some alpha. That's what BGI and other people, places like that, did in the earlier part of this century. But now everything is moving real-time, online, and in my hand, in my mobile. Why do I have to go to a computer to find out about my investments?

Why do I have to, you know, if I have to print out a map from my computer to drive to that place, you know, nobody does that today. People take their phone with them, and the app is with them, the map is with them, and you can even see your car move real time. And they'll give you changes. So that's where we are right now but the financial industry or the investment industry is still you know a couple of possibly decades behind that and that's what we're trying to bring it in uh right except for the world of robin hood and lot of those, you know, there are apps and tools that have bridged that gap and are giving real time. But yeah, I would agree for the most part, institutional investing is for sure not real time. A year lag at best. What about the dangers to that, right?

Of like knee jerk reactions, too too much information information overload right it's joked that private equity does so well because people can't get out right if you if you if you did that for a lot of other investment strategies they would probably perform a lot better um yeah yeah i mean that's a risk but it's uh but it's there but that's what diversification is about right so you have multiple guys who have short-term signals, but you also have some maybe medium-term signals along as well. So you diversify not just across strategies, but across investment horizon as well.

And that gives you some clarity about that. The knee-jerk reactions, again, that's where technology comes in and applying machine learning to whether Max's performance was skill or luck. And if there's skill there, then you stick with it. If it was luck, then obviously you get out once the luck runs out because that's random. It becomes a random signal. And that's where not just getting real-time data real-time information and the expertise that people like max have on the supply and demand within their their their

specific uh investment universe but also machine learning techniques to find out what's what worthwhile just this other quick idea right newer managers more sophisticated more you know perhaps ml driven managers eventually are finding it harder to raise capital because the allocators just don't know what the hell because there's no narrative there's no narrative that's right that's right they can't tell a story about their stock picking they haven't got a sort of three to five year track record so it's scary to invest in them. They don't really understand what the hell is going on. For us, we think we're a natural partner for these guys, because we can bring them on pretty light and quickly. We bring them into a diversified pool. So, you know, with tight risk control. So investors are not exposed to their

investment into that machine learning strategy just going wrong and making them look silly and also because we can be a bit dynamic and moving in and out you know we can you know help them slowly build and grow you know to a certain extent they're our sort of heroes right they're the ones we're trying to make successful but that we can be successful and we think you know we're a natural partner for these more high-end strategies to to get access to the bigger pools of capital eventually yeah yeah i told a ai driven shop once that they should create an ai model to create a narrative so that they could say here's why we did what we did this month.

That was all AI driven too, but right, fit it to the data. It's a good idea. Because they do have that problem. What do you do when CalPERS goes, why did we lose 4% last month? And they just point to the black box and say, I don't know, the box lost it. That I think is untenable in this day and age for now. It also seems like maybe one of the bigger issues is, beyond not having a narrative, is that the term has just become so hyped. Yeah.

Look, at the end of the day, machine learning is the future, I believe, whether you want to call it AI machine learning. In a lot of cases, people are just doing statistics, but your output is only as good as your inputs. So in Scott's case, if he had 100 not very good managers, his machine learning would say that they're not very good managers. And if he invested with them in the best portfolio optimization ever it still would be a not so good portfolio because it was bad inputs bad managers and in the case of managers themselves using it I'm sure that there's some people that are doing some

pretty cutting-edge stuff I think most of those people probably we don't hear about you don't have access to but the majority are putting in the same old inputs that they were already looking at. You know, the CTA spaces, they're putting in technical features. So you put features into that machine learning does, like picks up discontinuities and nonlinearities and things like that, that you wouldn't maybe discover from a basic regression. Some of that may help you out a little bit, but at the end of the day, you're still using the same technical features to make an investment

decision. So it's, it's, they're important processes. They're helpful, but unless you come up with a novel idea or a novel data source, you're just going to get the same old thing out. And that's what a lot of people that I see on the management manager side that claim machine learning are doing. So I think it's just

turned people off is that they're really not delivering. And maybe lastly, a lot of the people who seem to be doing something more substantial, they had a pretty good story about their abilities. They just went through a period of this just this compression trade and, you know, and just this rising equity market. And depending on what your look back period is, is the model is just going to pick up that that movement after a certain point. So you saw a lot of the really, you know, the guys that were more recognized for their machine learning skills in March just completely fall apart because they'd just been lulled into the beta trade.

By the dip, yeah. Well, they probably made it all back now by the momentum. Yeah, by the Fed. Right. All right, we're going to wrap it up in a little bit and go on to some of your guys' favorites as we end every pod. Any last thoughts on Novisian or how you guys are involved before we move on? I think worthwhile just quickly pointing out, I think Max is absolutely right. If you say, how are you going to generate excess returns, there's sort of three things we think you need. You need some sort of, you need domain product market knowledge.

You need to understand the domain that you're sort of operating in. There's just a lot of people who kind of wandering and do not you need increasingly technical skills the ability to use computers to build better models that make better decisions and then you need this the magic the sort of differentiation whether that's a different set of data or just a really unique way of thinking about how this market is operating. So this combination of a sort of differentiated approach slash data set plus technical skills plus product market domain knowledge. That's our experiences. Those are the three necessary conditions to deliver excess returns and many managers are missing one or more of those. And then you're gonna deliver that. And then I was

gonna ask you of what does success look like for Novician in terms of assets, in terms of performance? Is there a benchmark for either? Yeah, sure. So with this diversification, we can take strategies that with sharps of one-ish, so there's some alpha there, there's some excess return, and build products that are delivering 20 plus percent returns, sharps of two to three, not because the underlines are very scary in high sharp, just because the mechanics of bringing uncorrelated

excess returns together allows you to deliver great products. So the growth story is really we're hitting family offices now, growing through them at the moment. We've spoken to a lot of very large institutions from, you know, Australia's Future Fund to AIG to the big Northern European pension funds. And they are sort of saying that is very interesting. You need to get to a sort of scale. So we continue to keep them updated. And ideally, we're starting to hit the endowment funds and some of the interesting pension

funds, you know, in small testing outsize next year but but really we want to revolutionize change bring this whole at least the alpha part online so that's a you know half trillion dollar sort of space that can probably grow because there's more inefficiencies with people just can't find them at the moment so 50 million million by the end of the year. And, you know, a couple of billion after that. There we are for you, Max. I'm looking forward to it, Scott. All right, let's end up with some of our favorites.

Max, you're a big foodie out here. What's one of your favorite New York restaurants? Oh. I love Tomo. Tomo for sushi. It's in Greenwich Village, West Village. It's a hole in the wall, but it's been there for 25 years and it gets the best fish ever.

And it's reasonably priced. All right, I'll take it. And Scott, we didn't even touch on this, but you're a big skier. Right, not so much in Singapore. We wander off to Japan or to Europe a little bit. I did spend after I was an engineer and then I decided to go ski instructing for about three years.

So I spent three years in Austria. Austria, wow. Skidding up on the mountains. Hermann Mayer, what was the Austrian legend? Yeah, it was Hermann Mayer. Is that him? So what's your favorite ski spot? I skied all the time in this place, Selmsee, in Austria.

So I had a sort of a mountain. The village was just at the bottom, had a big lake. So pretty in summer and winter. And up the road was a glacier. So we could actually ski all year round if we didn't mind avoiding the crevasses and things. It's kind of like finance. All right, Max and I will come out to join you

for a Japanese ski trip. Yeah, yeah, we should do that. Olivier, favorite Singaporean dish? Oh, actually I'm partial to the roti prata, which is this Indian kind of bread with curry. And you have that for breakfast here, which is weird. Nobody thinks about curry for breakfast. But here it's a big thing.

And it's one of my favorite. And you can get that anywhere anywhere on the island uh and then and then sticking with you what's your favorite investing book my favorite investing book uh i don't think it's been written yet because i've read a lot of them and every time every time i was like i threw that one away because they they keep you know writing about the past and and i need to find one that writes about the future, because my money is going to go into the future. So I'm waiting for that one to be written.

And hopefully Scott and I will write one at the end. Right, right, right. Yeah, exactly. The story, the narrative. And then we asked everyone's favorite Star Wars character. We'll start with you, Scott. Obi-Wan Kenobi. Obi-Wan Kenobi.

Perfect. The master. The master. Max, how about you? I had to think about that one. Salacious B. Crumb? Salacious Crumb, yeah. The little guy on Jabba the Hutt's shoulder.

I laugh a lot. I've been trying to spare you guys with my incessant giggle for the podcast, but I laugh a lot, so his giggling kind of gets me. I went to the new Disney Star Wars land late last year before the corona and whatnot. You can buy the doll of that little guy in the new land. So next time I'm there, I'll pick one up for you.

Nice. And then Olivier, are you a fan of the movies? Do you have a favorite? Yeah, I mean, I would have to say, I prefer the machines than the actors. I would say the Millennium Falcon is my favorite part of that movie. It's all beaten up and it keeps getting shot at, but it's still there and it still carries them through, you know. If you force me to pick up a character, then I'll say Rd2 because he's he can fly he can ride he can

sing laugh play videos and he's just plug into any computer and decrypt it in seconds that's right he's the man all right guys well it's been fun thanks so much and best of luck with uh novice what you guys are doing thanks for the time this has been fun all right we'll talk to you soon all right take care everybody 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 RCMAlts and visit our website to read our blog

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