Invest Like the Best with Patrick O'Shaughnessy - Ricky Sandler - Building an Investment Compass - [Invest Like the Best, EP. 258]

Episode Date: January 18, 2022

My guest today is Ricky Sandler, founder of Eminence Capital. Ricky is a hedge fund veteran managing over $8bn of assets across Eminence's strategies. We cover Ricky's evolution as an active investor, why he thinks this is a stock-picker's environment, and what keeps him competitive after a long and successful career. Please enjoy my conversation with Ricky Sandler.   For the full show notes, transcript, and links to the best content to learn more, check out the episode page here.   -----   This episode is brought to you by: Canalyst. Canalyst is the leading destination for public company data and analysis. If you're a professional equity investor and haven't talked to Canalyst recently, you should give them a shout. Learn more and try Canalyst for yourself at canalyst.com/Patrick.   -----   This episode is brought to you by Levels. As one of their early access members, Levels was one of the most interesting products I've used. Levels is attempting to make continuous glucose monitoring mainstream by using real-time biosensors to see how food affects your health. Using Levels made me realize how little we understand about what's happening in our bodies - and it was the only product that has ever made me willing to log food. If you want early access to become a member of their private beta, (the waitlist is currently at 150K+ people), use this link – levels.link/PATRICK   -----   Invest Like the Best is a property of Colossus, LLC. For more episodes of Invest Like the Best, visit joincolossus.com/episodes.    Past guests include Tobi Lutke, Kevin Systrom, Mike Krieger, John Collison, Kat Cole, Marc Andreessen, Matthew Ball, Bill Gurley, Anu Hariharan, Ben Thompson, and many more.   Stay up to date on all our podcasts by signing up to Colossus Weekly, our quick dive every Sunday highlighting the top business and investing concepts from our podcasts and the best of what we read that week. Sign up here.   Follow us on Twitter: @patrick_oshag | @JoinColossus   Show Notes [00:02:42] - [First question] Whether or not great investment firms should be led by a single investor [00:03:25] - Episodes where singular investment power has proven effective and powerful [00:05:06] - Where he finds joy in the investing process on a regular basis [00:06:19] - Ways he’s learned to become better at guiding and helping teams he works with [00:08:14] - The most common types of fool's gold he comes across [00:11:00] - Evolution of the pricing mechanisms in ever-evolving markets [00:16:14] - Common features of a good mispricing opportunity [00:18:42] - How he interacts with other hedge funds and long-only investors [00:21:14] - An investor he often disagrees with but loves talking to  [00:22:13] - The investment he’s most proud of historically [00:25:11] - What the healthy draw that keeps him coming back to investing is [00:28:31] - His opinion on crossover funds and their growing popularity [00:32:09] - What the world in 2022 looks like to him and what both excites and worries him [00:38:19] - Key contributors that influence liquidity and how it flows into equity prices [00:41:26] - A macro view of the healthcare sector and why it’s so interesting today [00:42:59] - Lessons from the Titans [00:43:52] - Advice he’d give to younger investors for stepping into the space  [00:46:45] - The kindest thing anyone has ever done for him

This episode of Invest Like the Best is sponsored by Canalyst. Canalyst is the leading destination for public company data and analysis. Founded by a former byside analyst who encountered friction sourcing, building, and updating models, canalyst is now used by over 400 institutions, including the largest money managers globally, and by a number of guests on the show. With detailed company-specific models and data on virtually every public company, panelists clients are able to ramp up faster, update models instantly, and incorporate the highest quality fundamental data into any workflow.

If you're a professional equity investor and haven't talked to Canalyst recently, you should give them a shout. Learn more and try Canalyst for yourself at Canalyst.com slash Patrick. That's C-A-N-A-L-Y-S-T-com slash Patrick. Stay tuned after the episode from my sit-down with Roger Freeman of Newberger-Berman and Jed Gore from Canalyst. We talk about Canales quant product, Candace, and how data science is evolving in the investment process. This episode of Invest like the Best is brought to you by Levels. As one of their early access members, Levels was one of the most interesting products I've used. Levels is attempting to make continuous glucose monitoring mainstream by using

real-time biosensors to see how food affects your health. Using Levels made me realize how little we understand about what's happening inside our bodies. And it was the only product that has ever made me willing to log food. If you want early access to become a member of their private beta, where the wait list is currently 150,000 people, use this link, levels.com slash Patrick. Hello and welcome, everyone. I'm Patrick O'Shaughnessy, and this is Invest Like the Best. This show is an open-ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money. Invest Like the Best is part of the Colossus family of podcasts, and you can access all our podcasts, including edited transcripts, show notes, and other resources to keep learning at joincollossus.com. Patrick O'Shaughnessy is the CEO of O'Shaunacy Asset Management.

All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of O'Shaun's the asset management. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of O'Shaunacy asset management may maintain positions and the securities discussed in this podcast. My guest today is Ricky Sandler, founder of Eminence Capital. Ricky's a hedge fund veteran managing over $8 billion of assets across Eminence's strategies. We cover Ricky's evolution as an active investor, why he thinks this is a stock picker environment, and what keeps him competitive after a long and successful career. Please enjoy my conversation with Ricky Sandler.

Do you think that most great investment firms can or should be led by a single investor? Patrick, thanks. Great to be here with you. And I believe that the answer to that is yes. I believe that somebody needs to be CIO, needs to own it. he or she needs to have really strong lieutenants who have a ton of responsibility, who can deploy capital. It doesn't mean he's the only one deploying capital, but I think at the end of the day, management by committee is dangerous. I do believe that a single CIO structure

is important, how that all fits into someone who could be chairman and a CIO, but you need accountability at the top to set kind of direction. And how does that most manifest in the first? a productive way, meaning maybe in a way that would be harder by committee or with co-CIOs or something like that? What are the episodes where that power becomes the most valuable in your experience? So I'd say one, I think there is one person who is viewing all the opportunities across all the different sectors or analysts and is able to say, like, I know that's a really good idea to you, but it's six other ideas over here that are better. And you don't see that. you're just looking at this world. So that's one. I think two, some single person at the top

who's working with other people begins to see his people's biases. And some people come in, pounding the table, pounding the chest, great debaters, and their idea is actually mediocre. And some people come in, I kind of think this is a pretty good idea. I mean, there's some risks. Knowing your tools and people is important. And that is hard when you're more decentralized. in terms of decision-making. And maybe the last point is, I think investment committee could lead to consensus, think, and ways that are not as good. I love debate by committee.

And we have three sectors that we view the world from consumer, TMT, and we call it FIBO, which is financials, business services, industrials, healthcare, other, because that's kind of how our portfolio, and we have sector meetings every week, and we debate. among a group of six to nine people. And I love that, but ultimately, I think decisions at the top are important. I love the idea that Paul Enright taught me, which is that a CIA can be a great analyst, but often the skill of allocating capital across a set of ideas in the way you've described is quite a distinct skill from being a great individual security analyst. Which do you think you're personally better at and which do you enjoy more? Like, where do you get your joy in

the investing process on a repeated basis. It's an interesting question because I love digging into the stocks, but I think I'm good at zooming out and getting out of the weeds. So I think I'm better as an allocator than I would be as a digger and someone that's doing FOIA requests and walking trade shows. I'm better at having good people who do that, seeing those things. As a CIO investor, I'm much more of, that's a great idea, not let's go buy tech stocks or health care. I have some of those big picture views. I'm an individual company person at heart.

That helps me help them the most because I can kind of distinguish between pretty good and great and add a different perspective to the whole debate. How do you do that? You love the individual companies. You've got a talented team bringing you great ideas. How do you help them? And in what ways are you better at that via experience than you were maybe like the start 10 years ago or whatever?

Like what is that skill that you're bringing? What are you literally doing to bring the best out of them? I'm a heavy participant in these sector meetings and kind of direct them. And so my ability to boil things down to important things, shift the discussion to what will really be important for the business and for the stock, I think adds a lot to the discussion. And I think having both seen so much over my 30 years plus in the business and seen also lots of different sectors and different things, I think I'm good at distilling that and then hopefully helping them distinguish between, I could sort of say pretty good and great.

And I was an analyst first so I can start picking through their models and look at the cash flow statement and say like I can kind of get into the weeds of things as well. I think it's that longer-term perspective. I think the key is you go over time, we all have a lot of wisdom and experience from all the different things we had. And it's important that we don't get too colored by the winds and scars because you can have too many ends of one or two, but draw broad conclusions and things that generally work or generally don't work, but also have younger people around you to kind of challenge you sometimes to your closed-minded, I don't buy those kinds of businesses or this always works. And I think that's the push and pull of someone at the top

and team of younger people who I say a lot of value in naive energy, someone who loves an idea and it's a little bit naive, but it can open your mind to a different way to look at something. This could be in today's environment or just more generally. What are the most common types of what I'll call fools gold that you encounter that you've been trained to recognize, meaning an analyst brings you something for some set of reasons or whatever. It's something where you say, yeah, yeah, I realize why you think this looks good, but here's the reality or the thing you're not considering or whatever. If you think of fools gold conceptually, what comes most to mind? So one, I think classic one, is comping a stock or a valuation to itself, to another set of businesses or to a period of time,

which is just a period of time and valuations move a lot. And I think that an analyst can get anchored into a very recent example is these high growth companies have corrected to pre-COVID valuations. And I might say like actually pre-COVID valuation for growth stocks were pretty high. If you look back three or four years before that, they didn't trade there. Now, that might have been wrong. This might have been wrong. But anchoring it like it used to trade here.

And so if it gets back to this multiple, this is where it could trade. So I think that's kind of one common mistake that people. make. I think the other one is this notion that we're just trying to buy great businesses, that great things happen to when we're trying to short bad businesses, the bad businesses happen to. And the problem with that is if it's priced like a great business and it turns out to be just shy of a great business, you're going to earn a subpar return. And if it's bad and it turns out to be a little bit better than bad, you're going to lose a bunch on the short side. There's inherent expectations that we are in the stock business, which over a very long period of

time, yes, stocks move in line with businesses, but they do so much of this and that. And if you think about an investment timeline, I tend to think of our longs on like a three-year basis. And that's pretty long in today's environment. The dislocations from this, I just own a business that's going to grow for 10 years. I love, and I see this a lot on Twitter, like, where's this going to be? I'll take this portfolio 10 years from now. I'm like, do you know how long 10 years is? You know how many times you're going to have to stomach big changes? Do you know how much the real world changes in 10 years. Google was created like a little over 20 years ago. Ten years is a really long time. I'm a long-term investor. I think about businesses that way, but I do think that that notion

that we're just trying to buy good and short bad is a bit of fools gold. And we're trying to buy misprice securities and short disappointments and things that are going to underwhelm their investor base. That's what we're trying to do. We're trying to own by misprice securities among a subset of businesses, so I don't want to buy bad businesses. But I think that's a big thing that I see, particularly among the last five to 10 year investor base because they haven't seen as many cycles. I think it's so important to point out that while buying great businesses has been great in this past X period of time, a big chunk of that return. If you decompose it, is multiple expansion. So my friend Carl Krawad just says everything eventually trades for 12 times earnings.

Apple did and Microsoft did. And all these. companies did. And at the start of this great run, where the lesson seems to be by the great businesses, you have to realize, like a huge chunk of that return is going from five-time sales to 40-time sales or something like that. And so misprice security becomes the key term here, which leads me to a really important question of the pricing mechanism itself. I know you've thought a lot about market structure, market participants, the actual investors and their strategies that set prices. So if it's ultimately mispricing, price-setting mechanism is really important. The participants are really important. So talk me through that evolution because it's changed so

much in your career and the state of it today is critical to success. I'll start with the answer and then work backwards a little bit. Scott prices are moving around in a much bigger way, much more frequently on non-fundamental things and are much more divorced from fundamental value in a much bigger way than at any point in my career. If we just said, pick these four or five companies, bringing Bain McKinsey and two great investors to kind of give you a fair value, the number of things that would be way above and way below

and how far they'd be is way wider today. That is a great thing for an investor on the long side. I'll get into this in a second. It poses a challenge for an investor on the short side. I'll talk about that. And it's all caused by, I think, changing market structure. What's happened is, in short, the bottoms up fundamental investor is basically irrelevant in the daily trading and the daily movement of stock prices, maybe except for, in a couple of weeks before and a couple of weeks after major earnings event or something like that. Call that two-thirds or more 75% of the time.

They're kind of irrelevant, maybe 80%. We've gone from 20 or 25% passive to 55% to 55%. percent passive investing today. That means that a lot of the market is just price acceptors, price takers. It's there and I just continue it. Of the 45 percent that are supposed to be active, we now have quant funds, ESG funds, retail investors, momentum investors, macro investors. We have a lot of people who are not bottoms up fundamental investors. And so the world of, I think what adds the most value is a small world. Now, that's a wonderful thing. If you told me, competition in your business went down a ton, which is what I would tell people, you'd be like, God, that's amazing. And yet everyone's like, it's so hard out there.

Investing is hard. I talked through because we lived in a world where the market gave us signals. The stock was acting poorly. There was some chance that, like, somebody knew that they were going to miss numbers. Now it's like random. And the same stock's acting well. You're like, people are figuring out my thesis and it could be just random now. Or these other players, I don't, you know, random makes it sound even worse. People doing things for different reasons, a macro investor, an ESP investor, a pod who's using it as a part of a short basket to neutralize its factors. I mean, there's just big, big players out there that are not bottoms up fundamental investors. So that has created all this mispricing.

And for a longer term investor on the long side, this is, should be purely positive. Why is that? Well, if I think the stock's going to go from 10 to 20 and it goes to 6 first, I have less risk on the table. I can buy more. If I did my work, it's easy to buy more and you end up with more alpha if it ends up at 20. If I think it's going to go from 10 to 20 and it goes to 17 in two months, it's a bigger position. I've brought forward. I can sell it naturally. I can turn my capital and use the volatility to my advantage. The inverse is not true on the short side. If I think a stock's going to go from 20 to 10, okay, but it goes to 31st, I have a bigger position.

I have more risk on the table. I actually can't add. I might have to subtract. I know I have unlimited risk. I might get scared out. That dislocation creates a portfolio construction challenge. Obviously, we're seeing whether it's the mean stocks or the retail investors or other things that are going on with, there's a lot of new investors who don't do the kind of work that we do, setting stock prices. That creates a total construction challenge. So I think this is a definite change over my career that exists today, it's great for the long side. And the keys are, number one, use volatility to your advantage. Don't think the market is smarter than you if you've done your work. The market is giving you less and less signals today than it ever has. And then on the

short side, we've had to rethink our portfolio of construction some to navigate this. But it's like theoretically good, but practically doesn't work that way because of how short positions get bigger. you've got more risk on the table and you have unlimited open risk. So it just creates that different set of practical considerations. We've spent a ton of time, I think rightly so, with guests in the past, talking through the principles of good and bad businesses, which you've mentioned is, in the long side, let's say, necessary but not sufficient for a great investment. You want good or great in company with a big mispricing, right? Would be the sort of the Goli Lock scenario. I'd love to do that same walkthrough, not about company quality, but about what I'll call

mispricing quality, but in the same way that we can describe certain features, common features of a good business. What are common features of a good mispricing in your view? I think when you can look at the other side, the narrative, the supply demand of the stock, and say, I know why this stock is trading here. They've had decelerating revenue for five quarters. I know people in the sector don't like to own decelerating revenue or there's been margin pressure. By the way, I think that's going to change. So I think it's misprice. Being able to visualize that while the stock is mispriced, you understand what is mispricing it. To me, that's the most clear thing. Sometimes it's simple supply and demand like a distribution.

A lot of sellers, a company was spun out and IPOed and then a company distributed all its shares and there could just be simplistically supplying demand that can do it. Sometimes there are events like investors hate uncertainty. And so if there's a legal issue or other things that could create a probabilistic big mispricing, i.e. the market is pricing this like a 50-50 event, but it's a 90-10 event, but just because of the uncertainty. So I think there's certain things in human emotion. I think we do know following a period of earnings disappointments, you get investors who believe that,

A, there's negative price momentum, B, negative earnings momentum. People don't trust management. And there begins this whole narrative. This is a bad company. And every company goes from ups and downs. And so understanding the human emotion elements, I think, can be part of it. So there's a few recurring examples of it. But ultimately it comes down to like, I understand the guy on the other side.

he's totally wrong. He's doing things for other reasons, but I understand. Those are the best cases of this pricing because not only do you understand why the stock is where it is, but you think you have a path to that change. You know, I can probably name on not that many hands the number of other active equity investors with a pool of capital as big or bigger than yours. People would recognize their names. How do you interact with those people? If at the end of the day, there is quite a bit of concentration in terms of who is allocating the big pools of capital. Those people matter in setting prices. And you're part of that landscape. And they're your competitors, but maybe that are sort of your friends and frenemies or whatever. Talk me through

the dynamic of your social interaction or professional interaction with the other big hedge fund and long-only investors. I love to talk to other investors that I think are reasonably smart and sometimes different than me because I begin to understand some of these dynamics we just talked about it like why stock be trading here and you have someone else who's got a different framework. You know, I go to a lot of idea lunches and dinners. I have conversations with other big market participants a lot of times not even about stocks. So I can go to lunch with a peer and we can talk about analyst process and compensation and business aspects. I talk to a lot of young people because I teach a class up at University of Wisconsin, and I talk a lot of young people. And one of the

things I always say is find your own investing compass because you've got to be comfortable. And so you're going to meet all these people and talk about all these people and you're going to hear all these things. You're not going to recreate the wheel, but you're also not going to be just like Warren Buffett or just like Stan Druck and Miller. You might pick a few things and you create Patrick's investing compass. This is what I believe in. And part of why that's important is because you need conviction amidst volatility and you've developed it over time. I learned from other people both investing things and business things. I'll share with you one of your prior podcasts, Steve Mandel, and I had a Zoom with him a couple weeks ago because I reached out on a

business-related issue. We didn't even talk about markets or stocks. I like that. And I think understanding the other players in the game and how they think, learning from other people, even if it's little pieces, I'm an open book to other people. What do we own? Why are we doing it? It is such a big world of capital out there that I don't think my great ideas of running a business and running a portfolio. You have to actually be able to execute it and there's an art to it. And I don't worry that somehow there's some great secrets out there. It's kind of putting it all together. That's more important. Getting the right inputs is important. what investor comes to mind as someone that is just really different than you where you often

or mostly disagree with, but you nonetheless can't wait to talk to each time you do? I have on different ends of the spectrum. There are like more deep value types like a David Einhorn who's had great success and then been through a bit of a tougher period, but it's still a really thoughtful person. I wouldn't say I always disagree with him, but I different philosophy and we might only have a name or two in common. They'd be a problem. They'd be a problem. both ends of the spectrum. And then there's like the super high growth. I put my former boss in this camp of owning great high growth, best companies and how he thinks. And I like that aspect. And he's incredibly thoughtful. And there's other investors like Steve Mandel that would do similar types of

things. So for me, those extremes, I'm like somewhere in the middle of the deep value guys and the high growth, great business guys or gals. How do you think about the investment that you're most proud of historically. Maybe tell that story or the episode around it. I've been managing for 27 years, and there's so many stories. I would say Green Mountain is one that comes to mind because it was a controversial name. We had done a lot, a lot of research. Not only was it our biggest position, and we owned some option, call options, but I had pitched it at a couple of like big conferences and then relatively in short order they got taken over for like an 80% premium by JAB like by a really smart group that kind of validated the work

we had done and I would say this is a recurring theme for us where there is a growth company that goes through its difficult period you can look at Peloton today and say it might be going through something similar where it's good, has great growth. People think it's amazing, and then something happens and it starts to come down. So I think Green Mountain, Kureg and at home coffee, single serve coffee, they kind of invented that category or at least dominate that category. And I think that a combination of factors caused some growth to slow. There were patents that were expiring that were going to crush competition. They were going into the cold business, remember and people were like, see, this business is bad and people were actually capitalizing

the losses and cold into the earnings. So they weren't looking at just shut that down. And Green Matt was spending a ton of CAP-X. So the nitpicky value guys were like, they're burning a lot of money. But Greenmount was building a manufacturing capability to be able to serve the people that everybody thought was going to compete with them and provide a bunch of services and be the low-cost manufacturer in addition to being able to get some fee for the system, even if the patent went away. And so we could see the core business of selling pods and earning a profit per pod was doing well and was going to continue. And everybody was all caught up in a zillion other things, losses on cold, new competition,

CapEx. And going back to what I said to you, I could understand the other side why they were doing that. And I could also understand why they were missing all this. And this is one that got rewarded big and fast. And a lot of them take a lot more patience. I had the confidence because I could really understand what people just liked it. I think one of the things that for us is really good, I think being short sellers makes us better on the long side.

So I could pick through these issues that people had and say, like, no, it's not an issue. Or there's a reason for that and you're missing the good reason. whatever. There's no getting away from the fact that this is ultimately a very P&L-driven business. Success is pretty clearly objectively defined one way or the other. So obviously that is part of the motivation. And a lot of the people that have done really well in this get really wealthy, they make a lot of money. And I'm curious how you think about motivation. Like if P&L is ultimately the scoreboard that matters in this business, is that the right motivation? Like, what is the thing that keeps you coming back to the well that's healthy that you think is a good thing? And

Are there examples of things that kept you coming back to the well that maybe you think were bad in hindsight as the type of motivation for investing as a career? Yeah. I think you're right in your supposition that P&L is the ultimate arbiter. I'm a very competitive person. I have been my whole life. One of the things that I loved about the business I used to say is they print the answer in the newspaper every day. Now, we don't actually read the stock charts anymore, but that was true when I started. And so I like that ultimately, we get to figure out who's right and wrong over time and what's right and wrong in P&L. I think for me, what started out as just a competitive drive to, like, win and be better than other people and just have better performance. And somewhere along the way in building eminence, I work with incredibly great people. They are smart. They're hard work and they're good people. We've gone to great lengths to hire really good people, train them. I'd probably take a different view of this than others, which is that this is not a commodity. And it's not like if your P&L is bad, I turn you over.

There's a cost to finding people, to hiring people, and then to training them and to trusting them, that's very high. And I also want to come in every day and love what I do. So I've got to be around people, but I like that. So somewhere along the way it became about building a great firm that could endure beyond me. Part of that's going to be 40-year track record. You can't divorce yourself from P&L. You have to have a long enough horizon to measure that. what's the appropriate measurement. It's not daily. It's not monthly. Yearly is not terrible.

Three years is pretty good. Beyond three years, you're probably getting a little too far feel. So there are some measurement issues, but I have this annual investor conference, and I used to put up building a 30-year investment track record. But then a couple of years ago, I realized I was like in year 21 or 20. I was like, get closer to that. And then I updated that to build an enduring investment management franchise. And I think part of it's that I, I think it's really hard. There's not a lot of people who have been able to build, at least in the hedge fund industry, it's probably been more true in traditional asset management where there's been handoffs doing something that's hard, i.e. 40-year track record and building something that can sort of sustain.

Those are things that keep me motivated. And I build a structure into my life and day where I can work hard and still enjoy my life, which is important having that balance for everybody. We have a gym in our office. I don't question people like, where were you? You got to get your work done. You've got to be productive, but you have your time. So I think that helps attract the right people and have people stay. And so the 6 PMs that are below me have averaged probably like 12 years in eminence. One of the curiosity I have, it's just your view, given everything, we've talked about on the phenomenon of crossover funds and valuations, more generally speaking, you've alluded to some of this. I think I know where you'll go with this answer, but give me

your opinion on this style of investing. There's been so much capital raised and deployed into very late stage private businesses from investors that also be publics. What do you think is going to happen here? I think the prospect of looking at public and private is fundamentally a good one. You get to compare and you can allocate capital one way or the other. And ultimately, the public market in the long run is going to be your arbiter where all these private companies need to go. They need to sell to a strategic who needs to put it into their system and be public. They need to take it public and fully distribute it. So being in both, I think, at a high level is really good.

We have about 5% or 6% of our portfolio in privates. And doing the research on these private companies, really important. These companies are disrupting your public companies up on the new trends. I think that part of it makes total sense to me, and I'm a believer. I think where things got out of whack is in these private company valuations, I think that they were chasing a really small group of public company growth companies and paying ever and ever higher prices in rounds D, go to rounds E, rounds F. And I sort of say, like, you guys can keep trading amongst yourselves. But when you come to the public markets, Google trades at like 20 tons earnings.

And it's a phenomenal company. It's going to crush you all. thing like we have to get to some sense of real value. The other phenomenon that I hear from some people on cross-over funds is investors say, well, I don't have to hedge. I don't have to short against my private exposure. And there's this notion I'm trying to fight against that somehow P&L volatility equals risk. And this is something that has changed in the market. But a long short fund that doesn't run like Citadel and perfectly match. If you run with some leverage, actually, you have greater volatility now than you had before, maybe even greater than a 100% long-only portfolio because shorts don't directly hedge lungs as much anymore. But I wouldn't argue that that's greater risk.

And the phenomenon that follows that is somehow these private companies that get marked once a quarter or less are less risky, which is insane because my stocks get marked every day and less risky than some young growth software company seems insane to me. I think this is the phenomenon that created the private equity industry, the fact that allocators want to keep moving money to private equity is 2008. We all had bad performance, but you could take your money from us. Private equity had smoother numbers and you couldn't take your money. And they've got the chance to make that back.

And that created a cycle of that. So there's a fool's errand in looking at P&L. And that's, I think going back to the crossover fund specific question, I think there are some people that own privates. They're not even hedging their privates with shorts because they don't mark to market. And they think that that's the right thing to do. And I think we're going to enter the next two years where we're going to start to see private company markets. Not any specific crossover funds, but I do think when I look at private company valuations and where they're raising at, and then you can start to see the IPOs that they come, they trade up for like 10 minutes, and they trade down.

and ultimately they're going to have to fully distribute the public markets. And I think that will start to prove to people that paying these crazy multiples for young companies is very risky and probably not a good risk reward. Some may work out, but a lot may not. I'll repeat it again, Carl Fulag's idea. Everything will eventually trade for a reasonable earnings multiple at some point. That's where you've got to end up. I'd love to take the lens that you've helped us understand that you see the world through.

I understand this question is going to be a little weird because fundamentally you care about companies and the opportunities that individual companies represent. But those boil up into something, right? Like the portfolio looks a certain way relative to the S&B 500 or whatever. And I'm just always interested through if you collect a unique lens and set of experiences, how you then view the world at any given point in time. So I'd love to hear you riff on that a little bit. Like what does the world of 2022 seem like to you, feel like to you, the things that get you excited, the things that have you worried, just given that you've got a unique set of experiences. I'd love to hear your view on the world today.

I've said a bunch in the last month or two, this isn't going to be the year where real hedge funds are going to actually show their metal. And by that I mean individual stock shorting, moderate long short ratio, using some balance sheet, using volatility to your advantage, not being a slave to the P&L. And the reason I think that is because this has characteristics that are very post-1999 to me, like some insane valuation bubble concept, things that are going on. We can look at whether it's the IPOs that are happening in SPACs,

the retail investors, the fact that people accepted 50 times sales for companies, it's just like, we're going to make a 10-bagger, we're just going to own it for 10 years. Let's see how that plays out. You could have said that about Microsoft and Cisco in 1999, and they both did well in earnings, but for a decade or longer, you didn't make any money,

you're lost money. So price matters. The big distinction is that I think on November 15th, the Fed actually started withdrawing liquidity from the system, or became less easy. Talked about tapering, and then they talked about tapering, and then they kind of stuff. And if you look at when all this stuff peaked, that was actually when it peaked. I do think a lot of this was about liquidity. excess liquidity. And we are without question on the other side of something major. We had

the most accommodative Fed anyone's ever seen or heard of or read about in history books for the past 18 months. We had massive stimulus from Congress and levels that no one could ever think about. And then now the Fed is going to be on a tightening cycle as far as the eye can see until one of two things happens, until either inflation is sustainably at two percent or lower and they can sort of believe that, or they hike too far and the economy has a problem. We're just on this path. And so that inflection point, I think, is a really good one for fundamental investors. And beneath the surface, I think there's a lot of interesting longs and a lot of interesting

shorts, and we've had this dislocation. So you looked at what created the dawn of the hedge funds. It was the popping of the tech bubble in 1999. Guys had incredible years. We made good money in 99. We were 50% in 2000. We had a good 2001 while the markets were down. It was almost like your returns didn't bear in resemblance in the indices.

And the growth of the industry, and up until the GFC, the industry did what it was going to do. And then the GFC created a whole new set of things. This isn't just like that. There are differences. And rates aren't as high. And the companies are more real. And I'm not trying to say it's exactly, but there are a lot of parallels. And I also think that even with the Fed starting to tighten slash race rates, the economy is good enough.

I don't think the market's done. But I think that you can pay anything as long as the fundamentals are going in one direction. We're dreaming the dream on electric vehicles. And somehow the whole electric vehicle complex has market caps that can't be justified based on 10-year-out economics. doesn't make any sense. Like, that's going to come back to Earth. So I think that's one real important framework for how I think about the next couple years from one anecdote. I'll point to you is we have a long fund and a hedge fund. The long fund owns all the same longs as the hedge fund, just resize to 100%. And we have a fee structure that's 75 basis points plus an outperformance fee.

And we have a hedge fund, which is very traditional, which runs with some leverage and lower net. At many points along the way, if you just said, well, what should I go into? Patrick, pick the hedge fund. It's got all the flexibility. We can use leverage. I can be short bonds. I can do all sorts of clever things. And in late March of 2020, my hedge fund was 110% that long. The truth is that a lot of people, I said that too, my loan fund's done better for the last several years. And not that the hedge fund's done poorly, but it's been pretty good while the long fund's been great. And I get this question again now, and I say, I would have been wrong telling you this, and I'm going to tell you this again, but the hedge fund is the better place now, and it feels like the timing is more right.

So that would be kind of my perspective, and I think the thing that's important, I think a lot of growth investors want to believe that in multiple expansion came from low interest rates, and I think it came from two things. It came from economic uncertainty in 2017, 2018, and 2019. Therefore, people wanted to buy growth. And growth was actually expensive, precote, relatively speaking. Some of it justified, some of it not. And then it came from liquidity. And I think both of those things are different now. Liquidity's starting to come out. And actually, we have more economic certainty with the strength of what's happened coming out of the pandemic and consumer balance sheets and savings. Like, there's a lot of reasons why you feel pretty good about the earnings and you're

not worried about broad economics. Now, the Fed hikes two-finding. far too fast and kills the economy. We'll have to see how that all plays out. But that would be kind of my big picture view. Can you say a bit more about you mentioned liquidity a few times and its impact on maybe multiples slash prices? What is the causal link or connection there? Like, what's your model for thinking about where liquidity comes from or what changes it and how that flows through into equity prices? I'm going to give you two answers here because I am famous for saying that liquidity is as much of a psychological phenomenon as it is a real phenomena. Quiddity comes from availability of capital at banks, the cost of capital,

and it comes from ultimately how easy it is to get credit, to be able to invest that money. And I think that's like maybe the ultimate, you can talk about the Fed balance sheet and putting money into the system and the ultimate economic answers, I think, lie in availability and cost of capital, which real rates are still negative. Liquidity is still good, but it was the best we've ever seen at some point in time. Congress was going on and given out $6 billion to people. The Fed was buying up assets. Ten-year rates got down to like 50 basis points. Credit spreads came all way down. So like cost of an elevated capitalism. Those are the real reasons. Those are like the economic reasons. Liquidity is a psychological phenomenon at certain points in time, which is that

your desire to take risk, your desire to actually borrow that money, invest in that capital project, look out an extra year in your earnings model. That is a psychological phenomenon. And I like to say the world is reflexive. And it is like markets could take the economy down. We have a bad stock market. Eventually, the next thing you know, earnings start to come under pressure and it wasn't actually there. But that affects business leaders looking at the world and starting to make tighter decisions, tighter hiring, consumers having less money, and like feeds on itself. And I think liquidity has similar psychological phenomenons if people are more risk-averse.

If they have trouble in their business or in their investments, they're less willing to make that next investment. I think there's a psychological little to it too. Do you think that the, I can remember your acronym FIBO, I think is what you called it, what everyone's become so enament of consumer and TMT and technology and all this kind of stuff, understandably so, right? It's become a dominant force in markets, market cap-wise. But there's this big other group, FIBO in your case, that seems to have been entirely forgotten. My favorite example is that, you know, when I started, energy was 12 or 13% of the market, and today it's like 1% or something

by market cap. It's crazy small. Talk us through that segment, getting back down to your bread and butter of individual companies and sectors. Talk us through that part of the world through your eyes. If I am to look top down, I would probably tell you I think health care may be one of the most interesting sectors right now that there is. And I'll tell you why. For the first time in all of our careers, healthcare became cyclical during COVID because the health care system was the center of COVID. So somehow the elective procedures, which were not cyclical because people didn't have money. They were sick of a little because hospitals didn't allow you to come.

Sales reps weren't allowed to visit doctors' offices. High growth health care and high growth tech after we got through COVID, diverged. Tech kept on up and health care went down. And I think we sit here now where a big piece of health care, which has reopened benefits and is actually going to have a snapback and grow a lot faster. But what's more interesting about health care than most reopening is, it's after health care, after a company XYZ has its reopened benefit, it becomes non-cyclical growth, which is kind of what you want.

One of the challenges with reopening is you get the reopening and then maybe you don't own the greatest business in the world or a ton of growth or what happens after that. So I think healthcare is really interesting and partly because of what happened in COVID. I think financials are interesting for the same reason you said on energy. nobody's made any money in the sector. It's been terrible. People kind of hate it. We're very selective in financials and we own a few, but I do think it's hated. I think rates going up help. I think these companies, their balance sheets are a lot better and there are better businesses in there, what people remember. Industrial is kind of a big mix of everything. I actually think the guys that

wrote the book on studying the Titans. I just saw this. Yeah, I haven't read it yet. I know what you're talking about. I'm like halfway through this. to it's a great book for investors because they talk about how the industrials lessons from titans is the name of the book that book industrials covers everything from commodity things to like great business servicey type businesses and at periods in time aerospace was young and growing that was like a young tech industry guest turbines or you can look at a whole lot of things in industrials and they were the tech of the old and went through their own cycle. So that's sort of an interesting sector.

That's the ultimate bottoms up sector. If I were to tell a young person a sector to go into when they're young, that would be the sector. It wouldn't be community. Businesses are so very, you get a wide lens in that sector from great businesses, like these business servicing, growth businesses to your ultimate commodity and cyclical businesses. And so you see it all. You mentioned this unusually long tenure that a lot of your team members have had with your firm. You mentioned some of the key players like pods where the turnover Citadel or wherever else is incredibly high. And it does seem more like these are like very valuable commodities, but these positions are treated almost as commodities can sort of turn through.

With that in mind, what advice would you give to younger investors out there? You just said going to industrials. Do you encourage young people that consider going into the sort of career that you've had and built, given all the changes in dynamics? If so, what is relevant advice for them in today's world? I do. I think markets continue to be more inefficient than anything we've ever studied in school. And that is a good thing for investors. I think this is a business, industry, you continue to learn.

And it's very humbling. So I love it. And I would encourage somebody. I think the advice I would give young people, it's a few. One is what I mentioned to you before on finding your investing compass. Don't just try to be like one person. Try to take pieces of other people and figure out what you yourself can believe in and internalize and build your own investing framework out of that. The second piece of advice that I give young people is something that I didn't figure out to later in life and I could have done it a lot better is start building a network thoughtfully.

What does that mean? That means that when you meet people and you're going to get introduced to different people who can be helpful, it's probably up to you to start to maintain that relationship. And that doesn't mean being a pest. Every once in a while, hey, I read this article and I thought about you. And one of the things you said goes a long way to building your network. And then almost cataloging people among industries and expertise. Because as we go on and do our research, drawing on people,

people's experiences and expertise is really, really helpful. And when I was young, I got introduced to a ton of executives when I worked at Mark Ascent Management, the top executives at Viacom in Time Warner, and I didn't do a great job at keeping those relationships, and I could have. And they respected me for asking good, smart, analytical questions. I think being thoughtful about that and being proactive about that is a really good piece of advice. And then maybe the last thing I would say is who you work for is more important than where you work. Take investment banking, which is what a lot of young investors start as a stepping stone. I would much rather work for really good group of people at Jeffries or Lattenburg than I would work for someone that didn't care that much of Goldman.

And I think young people get enamored with brands and other things. Ultimately, you're at this phase in your career where the people that you work for and their interest in you is really, really. really important. This has been such an interesting conversation. I think because of your compass that you've developed that you've described, you have a different take on not just overall markets, but sort of the style with which we invest in what we're seeking the good mispricing versus the good business as an example relative to a lot of the investors that have become very famous in this cycle. So it's a refreshing conversation. I asked the same closing question of everybody that I talk to. What is the kindest thing that anyone's ever done for you? I've had a lot of kind things done from

me. So my current wife, we've been only been married a year, was incredible to me, and incredibly helpful to me as we started dating. And I was going through a divorce after 24 years and three grown but not grown children and also trying to run a business and a lot of the things. And she was just incredibly understanding and compassionate about the difficulties of all that stuff and helped me a ton through a very difficult personal period to also be able to do my day job, which is run the business and run evidence. Wonderful place to close. Ricky, it's been so much fun. Thank you so much for your time. Great to be here. Thank you.

Stay tuned from my sit down with Roger Freeman of Newberger-Berman and Jed Gore from Canalyst. We talk about Canales-Squant product, Candice, and how data science is evolving in the investment process. So Roger and Jed, let's begin this great conversation with just some background. I would love to hear from each of you a little bit about your career arc, how you got to hear and what you're doing now before we get into Candace. Roger, I'll start with you. Describe your role today and what your set of interests were that have led you to the current position in your career.

I work with the data science team, a Newburgh government and we're a team about 10 people. I came in here initially with a goal of increasing our engagement with the analysts here, the equity analyst, as well as the investing teams. My background as a sell side equity analyst for many years. So I had a fundamental investing background. and coming into a team that was largely data scientists and engineers, we believe that being able to connect the data analysis, the output of all of the data sets,

the alternative data sets that we use to actually make sense to the consumer of that data, being the portfolio managers, was a key ingredient needed to really increase the engagement within the firm. Jed, maybe the same for you. Obviously, working on Candice now with Canales, How did you get to this position and maybe just describe specifically what it is that you're working on? I've been with CanadaList almost a year now. My role is sort of a barbell.

I talk to clients twice a day at least, and I code and work with engineers. It's actually a fun and challenging role. The way I got to this point was out of college, I coded for five or six years, had Wall Street firms. The last was Montgomery Securities. And when they got bought by B of A and went to the by side. signed up with hedge funds. I had an 18-year career at hedge funds, a CFA, and got to level a portfolio manager. And I found in the last couple of years that I was working in the by side,

I was using Python more and more to, as the industry became more, well, at least the multi-strategy of the street became more and more interested in risk management pairs trading after 08. I found myself using Python more and more for analysis of pair trades. where open source libraries and languages had got to in the intervening 15 to 18 years that I was out of tech, made me realize that you could do things today that we couldn't do in the 90s. And things were so much easier today that I actually made the switch over to work in the tech startup industry. I have a question for both of you, Roger, maybe starting with you, which is about sort of the evolution of the role of data science in investing just writ large.

This is a great sounding thing to say that you pair data science, quantitative, of work with qualitative work, much different typically in practice. How have you seen the role and utility of data science evolve in your career through to today? Roger, starting with you. Let me step back to my cell side day. So I, like Jed had some tech background, more self-built out of personal interests. And what I saw happening on the south side was it was becoming an increasingly difficult environment to really make a difference, to add value to the research process.

I started to automate my research process. At the same time, the economics of the sales side business were getting more challenging. And what typically was happening, it certainly happened to me, was more coverage and a smaller team to do the coverage. That was seven years ago. And I don't think that the sales side of the time was ready for that kind of an evolution of the product. So I really wanted to get into an environment where data was the central focus, as well as automating the process. I would love to hear the same perspective from you. I love the idea of using technology and data is just sort of one version of technology

to sort of automate processes where there's not subjective value add from the analyst for the investor. Obviously, that's sort of what catalyst is predicated on writ large is the undifferentiated heavy lifting, as Bezos would refer to it. It shouldn't be happening in human hands or should let machines do it if it's undifferentiated. How do you think about the role and evolution of data science over time in the investing process? Data science is really just the conflation of statistics and computer science. And I always joke with my engineering team that I'm just the statistician like a barbarian at the gates of the engineering department.

The rejoinder was machine learning is just engineers who figured out statistics from the 50s and used it violently. The idea is putting these two things together, much as computer science really didn't exist as a field of study separate from engineering years ago, data science is just now carving out its own niche in the world of business science. in general. So the field is relatively new. For example, Yale just now offering a data science degree, but the languages date back to the early 90s. It's just that we've hit a tipping point in the past couple of years where open source libraries and growth in coding education broadly, people who are entering the investment services industry specifically have the skills and the tools to leverage traditional fundamental analysis in interesting ways. Historically, there's been a tremendous

cultural difference between systematic or quant investing and fundamental investing. And conflating those two things, it's almost the same as statistics and computer science coming together. And as Roger mentioned, and I see this every day talking to our clients, people have to do more with less all the time. I mean, it used to be the case for analysts who cover 20, 25 stocks. People I talk to now, I mean, 100 names is not unusual 150 for a single analyst. So being able to scale yourself, scale your workflow, has become increasing. important. Can you both talk a little bit, Jed, we'll start with you this time, on the challenge of implementation. So I'm really interested where, like, Rubber actually finally meets

the road here, where you've got, everything you just said makes a lot of sense. Again, I kind alluded to this already. Traditionally, the challenge has been getting fundamental teams to adopt the tools and actually use them in their workflows. Like any product, it's all about convenience and people don't like to change their routines. They have to do something better, cheaper, faster, whatever. How do you think about the actual bridging between the data science and sort of qualitative analyst investment function in the wild and practice? Any business that you're working with, if you want to understand its likely direction, it's a good idea to start with what its investors want the business to do.

And I think fundamentally investing, a lot of the capital that gets sourced in the industry comes in in search of a repeatable investment process or a proven investment process. for a proven investment process. And then also there's a reason they make bags out of marble. It's important that the repeatable and provable investment process is rooted in some form of tradition and gravitas that everybody can understand. So the investor base in a lot of fundamental shops,

at least from my experience with pension funds, for example, or high net worth investors, they weren't looking to us to ask us questions about how incredibly innovative we were in our technology. It was much more about our approach and how we thought about things. When I interviewed for the API job at Canales, they had an excellent traditional API platform, and they had systematic investors who were using it and had been tested over a couple years,

but they didn't have this last mile of Python library. And so that's why I joined the firm. And the thought there was closing that last mile just needs to be a lot easier to get access to these tools. And interestingly, today, it's kind of like the movie Footloose, where they're starting to dance and they sort of feel like they ought not to. But half the clients I talk to are not coders. They're fundamental analysts who realize they need to scale themselves, even though that's not ostensibly the mandate of the firm in terms of technology, as I mentioned. So I'm starting to see it happen. But yeah, you're absolutely right. The last mile needs to be built out. And quite often I have to, and I do work with clients on example workflows. And we have a system of workflows already built out in the form of notebooks that you can basically plug and play.

And that's really the future direction of Candace, which is going to be more and more of a hosted solution that lets people come in and say, okay, here's a workflow to do free cash flow analysis for a whole bunch of companies. And it's already built and you just change the tickers. Maybe Jedges real quick, just to get it on the record. It would be great to hear you just describe Candace. We got to it organically here, but just literally if you were meeting a counterpart at an investing firm for the first time and just saying, let's assume familiarity as the audience has with Canalist, what does Candace actually literally do? And then, Audrey, I want to hear how you've engaged with the product and implemented it.

There's a long tradition of puns and computer science. C++ is in the language C, if you want to increment an integer, you'll say integer plus plus. So C++ was the next step from C, and that's a bit of a pun. Canalist itself is, I wouldn't say it's a pun, but it's a planned words. And when I was interviewing, I saw what they had done to the API and I realized they needed a panel data solution, which is to say, serve the data like you would look at it in Excel, super easy. I said you should call this thing Candas because it's a pun on the very popular Python Library Pandas, which stands for panel data, which was invented at AQR in 2007 by the great West McKenna.

And it's the most popular open source library for data manipulation. So I named Candace in homage to Wes. And to my surprise, Camel said, yeah, that's a great idea. I didn't think that they would go for it, but they did. And what's good about it is when I talk to clients and I say, we have this data science library, we call it Candice. If they laugh, I know that they know about somebody. I know that they know. It's like a bad signal. Absolutely.

And I tell the sales staff this. If they don't laugh at Candace, then we probably have a lot more work to do with getting them on board with iPhone. So, Roger, I would love to hear how back to that concept of rubber meeting the road and using Candace as a part of that process, how you've engaged with this product and actually made real the intersection between data science and fundamental investing. at Newberger, the role of the data science team is to work with the investing teams to deliver, I'd say, curated output from data analysis. While some of the teams here have people on them who actually are interested and want to work with some of these tools, most of them, I would say, are more interested in getting our read of the data, the interpretation of the output and how it's relevant for them. we typically engage with PM teams on single names. They'll come to us with a question.

We're trying to figure out something that we're not finding an answer to anywhere else. Or maybe it's more open-ended. What trends are you seeing in Nike? And we can then go back to our new analysis across our data sets, credit card data, web traffic, etc., and put together basically a presentation of the trends we're seeing. And the key there, though, and this is where I've spent a lot of time, is to tie it back into what matters for that company. So our job is to actually dig into the investment thesis of the company we're looking at just like the fundamental analysts would. So it's not just all about automation and data analytics, because we need to understand what's relevant.

Because there's a lot of data we can look at. Some of it matters. Some of it doesn't. Or some of it might be relevant to a small 5% of the revenue. It's not going to move the needle. we want to focus on whether there's really insights that are worth sharing. Now, when it comes to the Candace product, I'll actually give you an example. It was over a year ago.

There was something was before Jet joined, but we were working with one of the teams here to look at some of the consumer. I mean, it's probably basket of like 45 tickers. And I want to look at earnings sensitivity, basically operating leverage in the businesses, where you would see with a working Excel model, how much earnings or operating income would change, were given change in revenue, right? So for a dollar or 1% change in revenue,

how much of that falls in the bottom line? Different companies have different levels of fixed structures. That ratio is going to differ. So without the benefit of Candace at the time, we were using Canales. We downloaded these 45 models and basically manually had to go through and tinker with the inputs

to make those revenue changes and then capture the earnings change and then manually copy and paste that into another sheet and basically build this up. Probably it took close to three days to do that. Since Jed came on board, and we talked about this use case of running sensitivity, he built functionality into Candace via Python now. We can basically throw a list of tickers in and get back earning sensitivity to a 1% change in revenue. And that, Jed runs in probably a couple minutes.

Yeah, it's slower than I like. Three days, right? And we're worried about it. And there's no mistakes either. The manual process had playing mistakes in it. We had to go back and do it twice to make sure we got it right. That's just to me a very, very clear example of the power. Jed, maybe just say a little bit more.

I'm always interested in, especially with products like this, sort of B2B products where it's complex. The work with early customers often is what shapes the product. Just say a little bit more about what that process has been like. Humbling. It took me a while to realize how it came. Candace was differentiated versus data source peers. And the reason is we're not serving a big can of data.

And we're not doing it in something where you have to have your IT department involved and you have to pull in a shard off of snowflake, etc. You literally just do a command line, PIP install, can or as Candace. And you're often running on your laptop. So the objects that I'm serving aren't just data frames. As I mentioned earlier, I should have been more clear. It's actually the model itself.

So when you get an object from Kandas, you get the design of the model. You actually get the structure of the model like a calculator. So it comes to you in this thing. You can look at the data, sure. But you can also interact with it. You can also visualize if I want to see the structure of the PNL sort of like trace precedence does in Excel, but in a tree, like a node tree. So I built a lot of this stuff and this theory. It took me a while to figure that out.

But once I figured that out, hey, we're not just serving the data. We're serving the actual model. then I started to pick up a little bit of traction. As much as a 53% hit rate allowed me to remain employed in hedge funds for 18 years, I got used to being wrong most of the time, at least 47% of the time, and technology development is really no different. So we went through this whole iterative process, and this is why people like Roger was so critical to it,

is I depend on clients to list ideas and test ideas and tell me what they like, but they don't. Portfolio optimization, nobody cared. If you could search for KPIs across our whole dataset, that's a huge hit. But yeah, I know that's been the power of the model. It's been an iterative process. About half the things I've tried to fail. But we've been doing it now for about six months. I feel pretty good about where it sits.

Obviously, this is a point in time that we're talking where it's doing something today and these things don't sit still. Processes aren't static. Things tend to keep getting better in technology and in data. Where do you see this all going, Jed, starting with you, over the next, I'll pick two to five years, sort of an intermediate period of time. What do you think changes from here? How does this become more embedded, less embedded, more important, less important? What are the major changes in this function that we'll see in the intermediate period? I see more and more of these

data science libraries offered by companies, Uber has one, Salesforce has one. Even McKenzie has a data science library. And they're intended as a combination of entree to the firm. It's street credibility with the coding world. It's also a recruiting tool. We can say, you come here, you could work on this and it's a neat thing. I see this trend increasing in corporations in terms of adoption and promotion of data science, particularly open source approach to data science. And following on with the open source idea, because Python itself is an open source library, Kandis itself will be its own open source project. So people like Roger could actually contribute to the project, if he has his own idea of workflows and such. And so where I see this type of product

going and where I hopefully we will be going is I see this as being almost a hosted solution where rather than necessarily doing a local install, you could just log in and you'll be working on your notebook. And that notebook is something that you can share with your team or you could share it with a broader community in an open source fashion. And I know people will say it's Wall Street. They never share anything with anyone. But it's interesting to see sometimes people really want to put something up and share it around because frankly it helps their standing in the community. So I'm curious to see if that'll work. What Jamie Diamond once said, the difference between a vision and a hallucination is other people can see your vision.

So I love that. I have a vision. Hopefully it's not a hallucination that we'd have almost like a Roblox style metaverse where clients could come in and reuse objects that have already been built like a free cash flow machine that will sort our whole universe by some kind of free cash flow formula they come up with or their own mechanism to determine the key KPI's in the stock. That'll be another object. You just basically flip some switches and hit go. And there'll be a bunch of these things in this hosted world where people can come in and do analysis and really free them up from the tools to the value added part of the job, which is the subjective determination of importance and discipline and implementation. I love the vision. Hopefully it's not a hallucination.

Roger, I'm curious from the other side, if you're maximally successful over the next two to five years, what looks most different about the investing process or the team? or where that rubber meets the road, if you continue to march in the right direction? For one, it'll be much more ubiquitous coverage for us across the firm that will be integrated, just naturally in the investment process. We're still at the stage, broadly speaking, of proving value. We have done it in pockets very successfully. In many ways, it's just it's almost a hand-to-hand combat in terms of getting an opportunity to work on a name, show the value of the data analysis, because when that succeeds,

there's always repeat business. There's a probably perception that data science, everything's automated. But to the judge's point earlier, this is not a systematic data science process. This is using data science techniques applied to big datasets to do the same sort of fundamental analytical work that's already being done in Excel on smaller datasets today. All this says is bigger data and the tools required to do that. And where we are today, in many cases, we do the data analysis and then tying it into this financial model like these catalyst models and ultimately the investment there's a lot of manual effort going

into that. We'll want to make that a lot more efficient. And then ultimately, I think to the extent that we sort of prove a repeatable process of tying data to fundamentals to investment recommendation, there may be opportunities to develop some data science driven fundamental product. Well, since I've been coming at this from the purely quantitative side my whole career, it's really thrilling and exciting to see some of these techniques start to be able to applied from the other side. I think it probably makes markets even harder. It probably makes alpha even harder to come by. But I think for the universe, it's actually a very good thing. For the best investors, it's a good thing. It's been fascinating to hear from you both about

how this is going to work in practice. And I thank you so much for your time. Thank you. Thanks so much, Patrick. If you enjoy this episode, check out join colossus.com. There you'll find every episode of this podcast complete with transcripts, show notes, and resources to keep learning. You can also sign up for our newsletter, Colossus Weekly, where we condense episodes to the big ideas, quotations, and more, as well as share the best content we find on the internet every week.