Interviewer (Ted Seides) (4:38)

To sell you something.

Ted Seides (4:40)

So while I can't tell you where the markets are headed next, I can share the greatest body of wisdom for how to think about these vexing questions. Where you ask. Well, when dropped into this particular part of the show, you might already know the answer from the guests on Capital Allocators. Now you know it's true, and so do I. So why not give the gift of knowledge and tell a friend about where to find the answers to the test? Or at least how to think about the answers? Or maybe how someone really smart thinks about questions they can't answer. Well, I'm not sure that's helpful, but in any event, thanks so much for spreading the word. Please enjoy my conversation with Ashby.

Interviewer (Ted Seides) (5:23)

Monk, Ash, great to see you.

Ashby Monk (5:26)

It's great to be here, Ted.

Interviewer (Ted Seides) (5:28)

I would love to jump right in on some of the recent research you're doing.

Ashby Monk (5:34)

Well, first of all, it's borderline scary to be on your podcast now, Ted, because it's gotten so big I have to be careful. Not that I say crazy things in private, Ted, but it is. You know, a few people are like, oh, you gotta get some good jokes. So I'll tell you really quickly before we jump in, that I actually went to ChatGPT and I was like, write me some pension jokes. And I could tell you with 100% certainty that all the jokes I tell today, if I tell anyone, will be mine. Because the ChatGPT joke authorship is not high quality. But look, I think why I'm excited to be back is I have this new platform at Stanford. It's called Stanford Long Term Investing, and we are studying the community that listens to this podcast. We study asset owners, and as you rightly pointed out, we're doing a lot of research on what we think of as the identity of these investors. First and foremost, we think these investors are hugely understudied. And so again, I want to give you kudos because I think you might have the first allocator university on the.

Interviewer (Ted Seides) (6:41)

Planet, Capital Allocators University. Nice little. Nice plug. It's good.

Ted Seides (6:47)

Thank you.

Ashby Monk (6:48)

No, but I'm telling you, man, I've been looking around because with my new program at Stanford, Stanford Long Term Investing, I'm teaching my first course that I have designed and written, and it is about allocators, whatever we want to call them. I call them long Term investors. Other people call them fiduciary investors, Some people call them asset owners. I actually think the fact that we don't have a name for this community is part of the issue that I'm trying to solve. What do we call this community of pension funds? Sovereign funds, endowments and foundations? They put the capital in capitalism is what I tell my students to try to get them excited about pension funds. We're trying to take this community of asset owners and unravel the complexity so that one, we get more students graduating from universities that really have a deep understanding of what pension funds do in general. There is no class at Stanford University until the one I'm teaching this spring that would actually walk you through any of this. You can get a PhD in economics, you can get a CFA or a Kaya designation and not necessarily truly understand how sovereign funds operate, how pension funds operate. So that's $120 trillion in capital that exists in this opaque world to the broader community of researchers, but also people that just are operating in the financial services industry. So anyway, that's a long winded way of saying we are doing a lot of work on identities and how these institutional investors first of all design their asset allocation, structure their portfolio implementation, and really try to go and pursue through investment activities their broader objectives.

Interviewer (Ted Seides) (8:32)

To some degree, we think of a lot of these as variations of the same theme. How have you gone about trying to articulate what this identity means?

Ashby Monk (8:43)

It's kind of like saying, what are the irreducible components that every one of these asset owners in effect, use to generate their performance to meet their return so if you're setting up a sovereign fund or you're setting up a pension fund, ultimately you're saying, I'm going to set some cash aside, I'm going to use financial markets and I'm going to get my cash back at some future date to pay some obligation that in effect. I just gave you a definition of the capital component. It's the first input. The capital component comes with encumbrances. You might have short term liabilities you need to pay, you might have sustainability requirements. Oh, I have a net zero commitment that I need to meet by 2050, which is very common understanding that capital is actually the first part of thinking about your production function. So we in this paper on identities, we talk about capital as a part of the production function, but then there's three additional pieces that go with that capital. There's your people, your process and your information. People are the obvious one. In this industry we tend to over index on people. We think that if we can get the right people in the right seat, we can deliver the performance. And that kind of boils down to things like track records, experience at firms, PhDs. All these different things kind of flow into our people. The process is how we empower them. Do they have a delegation framework? Do they have capital that they control and have autonomy over? Or do they need to go back to an investment committee and God forbid, go and talk to a board of directors about what they're able to do? Then there's the information component, which you see in all sorts of different ways. When you say the word information, you start to think, well, is that like Bloomberg? Is that like my networks? Yeah, it's all of that. It's where you get the information. The people go collect the information, they run it through the process and they invest their capital to meet their objectives. And so we think that little production function is irreducible. So that's the beginning layer of every identity. Obviously there's how we change those inputs and how we make them better and how we combine them. But that's the foundation of every investment organization.

Interviewer (Ted Seides) (10:59)

Are there best practices, particularly when you start thinking about process and information that you've divined from looking at it, I.

Ashby Monk (11:08)

Would say there are best ways to think about what asset allocation is possible given your current people, process, information and capital base. That's the first thing that we often say. The famous Brinson paper says, oh, 93.5% of the variability in performance on a quarterly basis is a function of asset allocation. Then you've got portfolio implementation that might deliver some of the rest. And the selection of securities comes in there. And we don't dispute that those things are very valuable. I think what we think is a best practice is to say actually 100% of your performance in your asset allocation is a function of your organizational capabilities. You just can't set asset allocation in a vacuum. So if you want to go and do highly illiquid investing in private equity or venture capital, first thing you need to go do is look at your process and your information. Do I have a process for managing my commitments? Turns out private equity and venture capital are commitment based investments. They draw down over time, they return capital over time. You need a strong process, really, it's a strong technology component to model all that out in order to pursue a more illiquid strategy.

Ted Seides (12:26)

I want to dive in on a.

Interviewer (Ted Seides) (12:28)

Couple of aspects you mentioned when you were talking about process. The first element of that sounded a lot like governance constraints. How does the governance or the decision making process factor into the beginning of that process as an input?

Ashby Monk (12:46)

The production function is people processing information. But what we learned is that basically every investment organization is trying to improve their performance in some way, shape or form. And the way they're trying to do that is through three things. Environmental enablers we call them. But the first and the most important one is the one you mentioned, or at least it's been the most important one. We can debate whether it will remain, but it's governance. When I think of the governance of an investment organization, the first thing that jumps to mind is the board or the investment committee. It's the fireman that is sitting on the pension fund board, or it's whoever overseeing and empowering the investment team to go and do their job. In the case of New Zealand, I love it, they call them the guardians. It's like it's out of Avengers movie. The guardians of the New Zealand Super Fund. So those organizations then turn to their board to say, how should we invest our capital? Should we do it directly? Should we do it through managers? Should we do it through fund to funds? What's the role for consultants? Do we empower people with strong delegation frameworks or do we force them to come and present to the board? This is the role of governance that you astutely pointed out. And ultimately there is a lot of best practice governance work that's been developed by Gordon Clark, Roger Irwin, Keith Ambotier and others to kind of talk about what a good board looks like. But boards are only one part. There's also culture and then Technology as ways of improving the entire investment organization and driving higher performance.

Interviewer (Ted Seides) (14:21)

What are some of those aspects that Erwin and others pointed out about how the governance best practices before we move on to culture and tech.

Ashby Monk (14:30)

So there's this great concept of a governance budget, which is similar to a risk budget. The concept is you need to align your risk budget with your governance budget, which is to say you can't take on a ton of risk in your risk budget unless you have a board that has the time and capacity and skills to really understand the portfolio and to properly resource the team to go and live up to the expectations. So you're aligning your governance budget, which is the skills, capacity and time of the board to meet the private equity portfolio needs or the venture capital portfolio needs. That's the biggest component, I think, that emerges out of that research. And obviously that means taking stock of the people you have on the board. Are you operating on a quarterly basis or can you call meetings when you need to? These are all big issues. And then the technology piece is like, well, does the board have a dashboard they can monitor target allocation, deviation from norms, things like that, so that they can then allow the staff to get on with investing.

Interviewer (Ted Seides) (15:36)

You mentioned that governance has been a big driver, a big constraint. Maybe it will, maybe it won't remain that way. What are your thoughts on the future?

Ashby Monk (15:46)

The other two components, culture and technology, they're almost in tension with each other. So the boards of directors, the culture of the organization and the technology, you can think about how each of those would empower those production inputs in different ways. So culture, maybe it's a knowledge sharing organization where people push information around, that allows people to make smarter, faster decisions through a bureaucratic process. That's culture. But technology is all about really moving information at scale, streamlining processes and pushing and empowering people to do things that they hadn't done prior. And there's a part of this industry, frankly, that I think is a little nervous about what technology can do to their organizations. And I think that stems from this thing I've noticed, which is I don't see a lot of technologists sitting on boards of directors of pension funds or sovereign funds or endowments. You see lots of ex finance professionals, you see lots of representative people coming out of the constituencies, teachers, firemen, public employees, et cetera. You don't see people that have built data businesses or analytics engines to improve decision making. So governance tends to view the technology component as kind of like an operational toolkit rather than what I think it is, which is a Potential enhancement for returns if you get your tech stack right. Fundamentally transforms what you know about yourself. It's less about what you know about the world. It's great to use technology and ChatGPT to go collect knowledge on the world. But ultimately I think the real unlock with technology will be to say, what do I own, what are the products I own, what are the risks I own? And how do we run scenarios against that to begin to model out my trajectory. What we think of as portfolio navigation and ultimately that's this massive unlock that I think will transform portfolios and ideally drive much higher performance.

Interviewer (Ted Seides) (17:54)

Where are we in the development of the technology tools for people to understand different risks in their portfolio? Where are we today and what still needs to get built so that people can use technology effectively to understand what they own?

Ashby Monk (18:11)

So I would say we are in that phase in the 1980s and 90s where we were just starting to get GPS and it was like, oh, this is fun, this GPS. But we didn't really know what to do with it. I literally can remember giving my dad a GPS that was giving him coordinates of where he was and he was like, I know where I am, I'm in California. What am I meant to do with this? And it was like, I know, but it's still pretty neato. So I think there's a whole component of this tech thing that I think we need to almost definance the discussion in order for people to understand what's happening. And the way that I often do that is through this personal navigation. We are operating in this moment where the GPS is just coming online. Back then you would have these paper maps in your cars and the co pilot that knew a shortcut to go from A to B, that person was actually quite valuable. You'd be like, oh, you know a shortcut? You're like, yeah, take this avenue here. The lights are all synced up so you can just drive along. We all remember those people, but they're gone from our lives now because we now have these devices that have the gps. They know where you are, but they have much more than that. Google has indexed the planet. If your destination is you want to go get a burger at In N Out Burger, Google will tell you which In n Out burger has the shortest line because they know that your destination actually is not the In N Out burger, it's the burger. They know you just want to eat a burger, so they're getting you to that burger joint faster. So you're saving time. So now when somebody next to you is like, oh, I know a shortcut. You're like, what are you talking about? Waze is driving me. There's. I am just using Waze. So what we've witnessed in the personal navigation space is this shift from what I would describe as process based decision making, where we naturally look to people as owners of knowledge. And those people know shortcuts, they've been here before, they know the neighborhood, et cetera, et cetera, to this new phase where, yes, people need to drive the car, but ultimately it's the data that comes together into this broader collective intelligence that guides us. And that is where we're headed right now. I would say in my community, the average institutional investor is spending somewhere between one and two basis points of AUM on their tech stack. And that tech stack is seeking to provide the GPS for their portfolio. So what do I own? It's shocking to say it, but when the SVB crisis was happening around us, I promise you, everybody had people pulling up spreadsheets to try to figure out what's our exposure, how do we model this out? Ultimately, what we want an investor to have is a dashboard that allows them quickly to look and feel. So there's huge investments at Addepar, but also at other places. And some of these investors are trying to do it on their own, frankly, also, which I think is a bit crazy given what I've already said about tech capability and TEC governance at these organizations. But they're investing in their gps. And what I think is this really exciting thing is about what comes next, because once you know what you own, yeah, that's valuable. You're like, oh, I wasn't where I thought I was. I have less exposure or more exposure to these vulnerable banking assets, so I'll move that. But imagine now you're like, all right, I know where I am, but now I'm going to start building optimization engines for my portfolio. We've built a lot of different businesses on GPS. There's Lyft, Uber, there's Amazon, there's DoorDash, there's all this stuff that exists as a function of gps. And I think we're going to get a lot of those verticals coming in the investment sphere in the next 10 years.

Ted Seides (22:02)

How do you think about the difference.

Interviewer (Ted Seides) (22:04)

Between if you're mapping GPS coordinates in a location, that's factual data, when you start thinking about that for an investment portfolio, it's not right. We don't know what the future is. We don't know what markets are going to do better. How might that GPS look.

Ashby Monk (22:23)

So this goes to what is the time horizon? Are you a long term investor? Are you short term investor? Are you navigating from your house to the burger joint? By the way, you still get rerouted sometimes when you're navigating to the burger joint. Because Google realizes something about where it's telling you to go. Their market assumptions have changed and so they reroute you. So as investors, what do we have? Well, we have our portfolio and we have our destination. But our destination, if I'm honest, is often defined as, oh, we need this expected return target. It's actually not the destination, that's an intermediate target to get to the destination. And actuaries somewhere out there have told us you have to get 7.2%. At some point we're going to have to pay somebody cash. We got to give the money back. So in theory, we could model those cash outflows with different sensitivities, different inflation components, et cetera. And then once you know where you need your cash in the future and what you have today as a portfolio, that's when people like me at Stanford, at Addepar elsewhere get really excited about the optimizations we can run. By the way, we're not all going to the same place. That's the beauty of the technology here. It becomes mass customization. Right now when you say, oh, I need 7.2%, which is a very generic destination, everybody's like, well, I need this amount of private equity and I need that amount of hedge fund. But when you say, no, no, here's your confidence interval for the amount of cash you need to deliver in 2031. Then you start actually having your own destination that's unique to you, that you can then tie back, by the way to your unique identity and the capabilities you have. And you can plot a course that's maximizing investment returns, minimizing damage to the environment, all this fun stuff that really is the technological unlock. When I look around the world of tech and investing, to put it in the Henry Ford parlance, feels like we were getting faster horses a little bit. It's like, oh, I can use ChatGPT to write my investment memo. Cool. Yeah, you still get a word document at the end. But I think what's really exciting is when technology lets you hold less cash, it actually changes your portfolio. Then you get just like we had the Yale model, which was let's invest more in illiquid alternatives. The tech model I believe, and we're starting to see some of this is about changing your portfolio to hold less cash. Because instead of over diversifying and using cash as a buffer for not really understanding your pacing or your unfunded commitments or all this stuff, now you have a precise understanding of where you are. You've defined the cash flows you need out. You've run many scenarios and optimizations to move you between the two. Instead of holding 5% cash, hold 3%. That one basis point you've now invested in your technology is going to deliver you one percentage point in return.

Interviewer (Ted Seides) (25:28)

When you look around the world, what institution do you think is closest to adopting some of these concepts?

Ashby Monk (25:38)

There's different parts around the world that are being done incredibly well. So I would say apg, they went out and actually bought a data team from Deloitte, a pension fund doing MA to get data inside their organization. Mark Walker at Cole Pension Trust worked with us to develop some of the technology around pacing Liquidity Cash Management. Again, it's a pension fund in the UK that has a very mature liability. So they need to be very precise with their cash projections. So they've really used technology well to reduce the amount of cash they're holding and invest that cash in private equity, venture capital, other high yielding assets, New Zealand super, Australian super. Investing heavily in their technology and really trying to find those unlocks. I know you've had RAF from the Future Fund. They've also invested heavily, so there's a few. When you think about the scale of what one basis point means, that's a big number. We're talking 30 to 100 million bucks a year going into technology. By the way, the problem I have with the fact that not everybody knows this is all these technologists at places like Stanford or Princeton or Harvard, they don't even know that these pension funds are spending this much on this technology. So when these big pension funds need technology, it's not like there's an ordinary army of startups out there that are trying to solve their problems. It's actually just the established players that are invited to participate in RFPs.

Interviewer (Ted Seides) (27:16)

When you take a step back from the tech stack, one of those enablers is culture. Culture usually has a history to it. How does that culture drive that ability and willingness to adopt technology?

Ashby Monk (27:28)

This is the tension a little bit. So we have a disposition, I think in our industry to see a lot of what we do is art rather than science. We're an LP investing in a gp. There's a trust component, there's a alignment component, there's a part of this that we really want to believe is about art. And I Don't dispute that, because I do think human beings will always have a comparative advantage in human relationships, even beyond what we're seeing with ChatGPT, sounding incredibly human and passing the Turing test, et cetera, but ultimately going and meeting people and building these relationships, this is the culture part of investing that I think is going to be there forever, I hope. But the reality is art and technology, art and science are two sides of the spectrum. Science is seeking to quantify, to codify, to take what is tacit and make explicit. There are tools to capture some tacit knowledge, like knowledge tools, but it's very difficult to do so. There is going to be a long, slow period, I think, where organizations that have built very strong cultures around alignment with their managers, around, for example, risk taking and direct investing. I feel like we could almost walk through what I would describe as the components of the Canadian model, where you really need talented people internally. You need to empower those people with strong delegation frameworks so that they can be credible in the marketplace. And you need to set up overseas offices so they can get the information they need. All these things don't feel all that technologized. Now, you might be able to automate some of what they do, but ultimately I would say that model of going out and building networks and originating deals, that feels like it is in tension with building the next great technologized investor because it requires such a big investment and those organizations have thousand people, plus they have overseas offices around the world. They're all operating in a very well defined environment. Just to swoop in and say we're going to replace this and that with technology, I think will be a challenge, but we'll see.

Ted Seides (29:49)

We're going to take a quick break in the action to tell you about private equity investing at Brookfield. With 100 plus years, its owner operators and a $1 trillion ecosystem, Brookfield focuses on essential industries and business services that help shape modern life, yet are often overlooked. It takes independent vision to see their potential perspective, to acquire with precision and expertise to build lasting value. It takes industry. Learn more@brookfield.com ittakesindustry and now back to the show. So how do you think about something.

Interviewer (Ted Seides) (30:30)

Like Yale, which everyone likes to point to, with a new chief investment officer laying your framework for Yale's identity and how that applies to the enablers.

Ashby Monk (30:42)

If we take the Yale case, it's a fun one, obviously because they invested very early and heavily in all the alternatives. Part of me thinks the technologized model is going to empower them to be Even better at the Yale model. Why? Because you're just going to have much more confidence in how your GPS draw and return capital. So right now, when we think about the traditional tools we use for predicting how a mid market buyout fund in Europe draws capital and returns capital, a lot of that is putting the finger in the air and hoping for the best and looking at historical means or turning to the manager and asking them for guidance. But this can be much better. We can do this with data. We can go and pull custodial data and look at the 9,000 GPS that are sitting in some custody data set and start to say, okay, biotech in North America, Series B and C fund. How did those organizations draw capital and return capital? And let's actually shock those assumptions with some past crises to see how they affected. With that type of analysis, if you're a chief investment officer of an endowment like Yale, you're just going to be able to make bigger commitments to managers, hold less cash and drive higher performance. That's the hope, right? That's the unlock that technology should deliver by helping you understand in more granular detail what you own, the people, the process. I think those things don't need to change that much. Given their strategy, you're going to empower those people to make bolder bets because they're going to have a stronger sense of what's coming in the future.

Interviewer (Ted Seides) (32:36)

I'd love to turn to talking about innovation a little bit. I know it's an area of great passion of yours. What have you seen from sitting in and around the Silicon Valley community of best practices of how innovation gets created as applied to the investment office of these pools of capital?

Ashby Monk (32:55)

I can't think of an R and D team that exists at a pension fund. So like we said in the beginning, this is the base of capitalism. These organizations put the capital in capitalism, $120 trillion. But they're pretty conservative. And by pretty, I mean outrageously conservative. So they have monopolies over their assets in most cases. The Australian super funds are a little different. They are actually fighting for survival, which is why I keep going down there, because it's fascinating. But most of these organizations are going to be there. Stanford Management Company, calpers. The people in those seats might change, but the organizations will exist, which creates this weird incentive, I would say, to follow the herd. I often joke that the only way you get fired from a pension fund is you innovate, which means you've deviated from a peer group and somebody says, huh, what are you up to? And Then all of a sudden, you've got to justify it. And so all that is to say, I spend a lot of my life looking for ways to bring innovation into these organizations. In fact, I would say I used to spend all this time focused on fees and costs. But the only reason I was really doing that was I realized that if you could reveal to the boards of directors and frankly the broader community of stakeholders, how much these organizations were paying private equity and hedge funds and venture capital, it would ultimately create a conversation like, is that right? Should we be doing this on our own or should we be thinking about some novel way? And that's the opening to in effect, change how that capital is being deployed at the base, which is for me the real motivation of everything I do. I'm trying to help that base level capital generate higher return. While if we can deliver positive things for the world, more infrastructure investment, more jobs, less waste flowing into Wall street, which is a tax on all those things. That is another way of saying, I'm trying to go into those organizations using data to reveal things about their portfolio that maybe they didn't appreciate, maybe was hidden, and then that's the opportunity to shift. But that actually means what we're doing is revealing little crises. What I've also then learned is these crises, yes, they exist, but they are very powerful drivers of innovation in our industry. So in 2001, 2003, we had the Perfect Storm crisis. We got liability driven investing, we got asset liability modeling. We got all this interesting stuff coming out of the perfect storm. In 2008 crisis, we got factor based asset allocation. All the work that Andrew Ang done is now being implemented. Products correlate. You really need to go to the core factors that drive return and get diversification there. Now we've got our next crisis. What are we going to get out of this? Is it investments in technology to do better modeling? I hope so. For a moment I thought this would be the big driver of ESG adoption, but now we're seeing this as a big rejection of ESG going on. So the punchline to answer your question is we often need crises to drive change because these organizations are fairly conservative, slow moving, and they are monopolistic. But interestingly, technology is going to reveal little mini crises inside these funds, which are opportunities to make change.

Interviewer (Ted Seides) (36:24)

When an organization does want to make change and innovate, how can they do that in an intentional way and not have to wait for a crisis for that impetus?

Ashby Monk (36:36)

You need to create organizational space. So the first thing to acknowledge is that innovation is Very different from efficiency. So most public pension plans, sovereign funds, endowments, they want you to be efficient. The number of times I've been lectured, like truly me lectured by pension employees to say we can't just spend money on that, we're a fiduciary. And I just groan, Ted, because it's like, look, I get it, you are getting pressure to be efficient, but innovation is messy. I think you've noticed innovation and failure, they go together, that's the business. You can't run a just in time process in the Japan style and then make changes at the last second and expect things to arrive just in time. So you need to create organizational space, which means you need to create safe spaces for failure. Recognizing that a lot of people went to work at pension plans wanting job security, they gave up the carry at the giant private equity fund because they liked the job security. And maybe it was the nine to five, maybe it was the less travel. And that doesn't mean that their job isn't exciting. The job, I find that the asset owner world is incredibly exciting. It was a trade. So as we go and we go to those same people and we say, let's get you doing innovative things, we need to acknowledge that we need to create new incentives. We need to create safe spaces for failure. And we need to pull these people that are working in monopolies to embrace that experimentation in a space where they know they aren't taking career risk because that career risk is a big motivator in the wrong way.

Interviewer (Ted Seides) (38:25)

What's an example of an organization that's done that effectively?

Ashby Monk (38:29)

I'm going to mention APG again because they have this innovation engine where they pilot things. Or maybe it was pggm. It's either PGGM or apg, but these Dutch are very process driven. So they built process around experimenting with their technology and they would do pilots and then the good pilots would graduate into full projects. So that type of experimentation is really valuable. I can think of a sovereign fund in the Middle East. I'm not quite sure how much I was supposed to know, so I'm going to leave them as anonymous. But they have this whole business process automation focus where they're going in and looking at small tasks and seeing can we automate them with technology. And they have a separate team that goes in and assesses them, builds the technology around it, and the core team is in effect facilitating innovation that's happening around them so they can continue to do their day job. So this concept of business as usual tends to be very pervasive. From Australia to Abu Dhabi to Sweden, you have this business as usual function. You need somebody to come in whose job it is to do the innovation. So that's what we saw a couple of times in that Middle Eastern fund. I think the mergers that you're seeing in Australia are a natural driver of innovation. You're bringing these big teams together, smooshing them and seeing what are the best practices that emerge.

Interviewer (Ted Seides) (39:55)

What's the low hanging fruit that you've seen in a non investment technology company, whether it's a Google or a startup that you're just waiting for an asset owner organization to adopt.

Ashby Monk (40:10)

I mean it is a separate research and development function, which is to say some team that is actually trying to spot the problems inside the organization that can be solved either with technology or with collaboration with peers, things like that. I mean, right now, just to be clear, I think the way that many investment organizations get around this lack of innovation infrastructure is through collaboration. We partner with our peers, we go to Stanford and we sit around the table and we talk with each other about our problems and then we pool our resources to try to develop solutions. And we do that because we don't have tons of resources at the ready to go and work on X problem. It also helps if you can go back to your board and you can say, yeah, look, we're doing this, but this famous Canadian pension plan is doing it with us and this big Australian sovereign fund is also doing it with us in a way that almost gets you to the prudent person rule because other prudent people are doing it with you.

Interviewer (Ted Seides) (41:15)

What are some of the specific examples you've seen of where collaboration works and where it breaks down?

Ashby Monk (41:22)

So collaboration is often incredibly effective. Where organizations don't feel like they're really competing to deliver. Outperformance is like these middle back office functions or thinking through how do we design a legal function. Those are parts that I've seen collaboration really inform one another and drive change. Where there's a lot of value add, I think you get sharper elbows. People see collaboration as a way of leaking ip. If you're worried you're leaking ip, then you're going to lock it down and you're not going to share. I see a lot of that in the endowment space. Very secretive organizations that are quite worried that whatever secrets they have are going to get out and be copied. And to give them credit, many other organizations have tried to copy the endowment model. So it's not like their fear of copying is baseless. Everybody has tried to copy the Swensen model, so you can understand why they're so careful. But you need to find those areas where it isn't scary to share.

Interviewer (Ted Seides) (42:31)

I know you've been involved with Capital Constellations, one of the larger collaborative efforts within that trajectory.

Ted Seides (42:40)

What are some of the things that.

Interviewer (Ted Seides) (42:41)

Have made that work more effectively than some of the other collaboration attempts you've seen?

Ashby Monk (42:47)

That's a super special one in that the capital that comes around the platform makes the platform more valuable. The bigger and the more sophisticated the LPs are around that table, the higher quality of the table. They're in the business of anchoring or incubating GPS and owning some of the gp and they get fabulous GPS to work with them because the platform is big. The world's best investors, general partners, they still feel distressed when they are starting their business. They're not distressed because of anything to do with their investment strategy. They are distressed because it is hard to build businesses. And so Capital Constellation, with that amazing network of limited partners and asset owners that own that platform, can come together and in effect de risk to remove that distress from some of those amazing gps. So that's partly what's so effective. You can show up at Capital Constellation and you can really get enough capital to get to business and really start investing and building your own track record. So I think that's partly where that has been so effective. It's also hard to build that kind of unique capability around anchoring and owning and managing GP stakes. Kind of liken a little bit to what you see in development funds like niif. In India. There's been another really successful collaboration with certain Canadian pension plans. Investing with niif that I raised my eyebrows a little bit like, wow, you're investing with a development fund. Well, part of that in the Indian case was it's hard to build that local knowledge of India and to really be able to go in and do deals. So by bringing all of these investors together in that Indian context, the value of the overall platform improves and increases. It gives them more leverage domestically to source the best deals. Just like Capital Constellation now has this, it's now probably the first port of call for most gps that want to go and put themselves in business.

Interviewer (Ted Seides) (44:58)

I'd like to pivot a little bit to talking about esg. What are you seeing the asset owner community doing as it relates to esg?

Ashby Monk (45:09)

Doesn't it feel like the whole industry has changed now when you talk about esg, it's like you'd rather be swimming in shark infested big waves. Or something because it's safer than talking about esg. But I think the reality is this. If you're really interested in understanding your portfolio, I think there's still huge value in esg. But I think the problem that we've all begun to recognize, which by the way, we were complaining, I was complaining about ESG well before Elon Musk complained that Tesla had the same rating as Exxon or something. And the reason we were complaining is because ESG ratings are difficult to understand. I joke with my students sometimes that the ESG ratings are like Big Macs. They're easy to get, they're cheap, they taste pretty good, but it's not clear. They make you healthier and you definitely don't know everything that's inside. There's a lot of sugar, a lot of salt, there might be some yoga mats in there. I don't know if you are trying to understand what's wrong with the ESG space. I think you can point to that product and say, look, there's bad data underneath this ESG rating world. We kind of borrowed that ESG rating logic from the credit rating logic. But with credit ratings, I can tell you that those credit ratings are associated with a probability of default on some instrument, some debt instrument. What is the equivalent for ESG ratings? What probability are they providing us? Another way of saying, let's go back to what we were talking about. Technology, like really good tech and data should empower you to change your portfolio. That's what we want. We want data so granular and useful you can hold less cash, you can invest more in alternatives. In the case of esg, you can pick one company over another. But if you are an equity analyst doing bottom up analyses of companies, what does a Big Mac do for you? You can't chop it up and make meals out of it. You don't really know what's in it. So it's a very blunt way of communicating environmental performance, social performance and governance performance. By the way, no fault to the ratings people that sought for a mechanism to deliver this stuff to the community. In the absence of great data, we didn't have great data. We still don't have amazing data. But we need to go collect that data for this new trajectory of the ESG space. I often talk about needing facts instead of ratings. We need to go and look at the factors underpinning ESG environmental performance. It's a useful one. What's your environmental footprint if there's a flood that wipes out a manufacturing facility? How resilient is that facility, does it have a huge footprint and it's going to be a massive cost, or is it a small footprint that can be agile and pivot? It's obvious as you start to talk through some of these things, workforces having loyalty to the company in times of trauma will allow those companies to be faster in their recoveries. So ultimately we will move away from ratings that are really hard to unravel and really frankly hard to know what to do with. And we're going to move towards facts. Oh, this company has treated this many people in this country and we have a healthier workforce.

Interviewer (Ted Seides) (48:45)

In that movement from ratings to facts, are there any good analogues of how you get to what those common categories of facts will be in the future?

Ashby Monk (49:01)

Yeah, I mean there's like the Nielsen ratings versus the data coming out of Netflix. So first off, maybe this is a useful aside, but you need to understand what data is. And data are signals and information are data in context. Knowledge is when you have enough information that you can begin to generalize about something. And then the tip of this little pyramid of insight is intelligence. You have enough knowledge that you can apply it in the context of your life, in your portfolio, whatever. So oftentimes, in the absence of great data, we over index on knowledge. And so this is what academics do. Like we go out and we collect some little sample of data, we clean it, we prepare it, we study it and we publish about it. And then other people use our findings to actually avoid having to collect the data. So that's this focus on knowledge. And again, if you go back to the beginning of this conversation, it's like, this is why we pay people so much in finance. You have people who have track records and experience, they have that knowledge, they've collected that data in their lives and they are using it to make sense of very messy data sets in order to say this company's performing well, this show on TV is performing well between 18 and 24 year old men in Idaho. I don't know. That's the old Nielsen rating. Well, the minute you get this infrastructure of data, you can calibrate the information and the knowledge and obviously make better decisions with it. And so right now we've got all these knowledge layers that are seemingly the focus. We've got these ratings frameworks, we've got, oh, you're a green on your climate physical risk score that is jumping to that knowledge layer without truly giving people the tools to understand what's underneath it. And obviously the tech revolution, from my perspective, is going to push US out of that knowledge focus, which is where we use process, we bring people into the data driven decision making. Where you don't need Nielsen when you have view counts and you can see exactly how every single person has watched your television show, here's where they paused, here's where they hit play again, here's what they fast forward, here's where they dropped off. It's so powerful. Now we just need that type of data infrastructure out into companies. And frankly, we need to explain to companies why it's in their interest. Right now they're doing all this work and their data's flowing into some rating. You can understand why they're pissed. It's like, am I getting a lower cost of capital because of all this work I'm doing? I hope we can point to a yes at some point. Then people will be like, okay, fine, it's worth the $2 million a year I'm spending on all these data services to collect and present because it should drive lower cost of capital. And I think the reason it will drive lower cost of capital is because the ESG movement will be more effectively tied to long term performance of these assets. And that's where I think, if you want to talk about it, the whole notion of recoveries from crisis needs to be integrated into our theoretical logic.

Interviewer (Ted Seides) (52:25)

Why don't we go there? Because I know it's been a subject of your recent research and just dive right in.

Ashby Monk (52:31)

We did this paper on submergences, which is basically when a drawdown starts. A submergence is the beginning of the drawdown, the downward trip underwater, all the way back to when it gets to the high water mark or the goal water mark. Because it doesn't have to necessarily be, oh, it's the high to the high. It's like you were tracking on your goals, you dipped beneath, you're underwater and then you get back. And I liken this concept of submergence to the risk that every surfer faces when they're riding waves. It's not so much how deep you go when you fall off your board and get slammed, it's how long it takes you to get back to the surface and get air. Weirdly, we don't have great tools in the investment industry to think about the shape of recoveries. We have a lot of work through MPT on drawdowns on value at risk. We do a lot of work on volatility and variance, but we don't think as much about the shape of recoveries. And because of that, we begin to think in Our risk management terms around what I would say is more a robust framework of portfolio management where we seek to immunize portfolios to shocks, all weather portfolios. We're hedging this risk, we're managing that tail risk that is really about trying to immunize a portfolio to shock. And so that's hard to do. It can be expensive, it can require huge investments in data and technology to really do it. Well, to avoid when the SVB crisis hits, you had all your hedges and derivatives in place. That's a robust portfolio. We don't build long term things that way, we don't build buildings that way. We move to a parallel. We don't want ecosystems that way, we don't even want people that way. We want you to be resilient, we want you to absorb the shocks, bounce with them and then recover. In fact, we press our armed forces, we push them all through these programs to teach them how to take hits and bounce back better. And that is kind of the philosophy we're trying to bring into our research on resilience, which is to say, well, if ecosystems and buildings and people have all of this work around resilience, why can't we bring that into the investment ecosystem through this concept of submergence? So then you begin to ask, well, what does change the shape of recoveries if a certain asset recovers much faster than another asset? That's actually really valuable to know given that drawdowns seem like it's a fact of life, like these hundred year crises are happening every six months at this point. So what we're learning and the findings are still being developed on our team, is that it's these sustainability factors, these long term factors, employee satisfaction, environmental footprint, things like that, that you would say, well, really good ESG tools would help you measure that those things are associated with recovery trajectories. It does feel strange to me that just as we're almost on the edge of showing exactly how ESG helps long term investors drive outperformance, is also the moment when we have state treasurers around the country banning ESG from integration into tools. We'll just have to call it something else. We'll just call it long term risk management or something.

Interviewer (Ted Seides) (56:07)

So as you looked at the research on drawdowns recoveries, that sustainability lens is one that you found. What are some of the other discoveries that you've had in thinking about the concept?

Ashby Monk (56:22)

Well, that Sharpe ratios are largely wrong. There's a bunch of reasons why the Sharpe ratios kind of distort our understanding of the risk we're taking. And it's not wrong in the sense that it's not a useful tool to use just to look. But as long term investors, sharps don't work in negative return environments. The math actually doesn't work. And yet every single investor is communicating to us, oh, here's my Sharpe ratio, here's my information ratio. So I think finding new ways of thinking about longer horizon risk have been at the forefront of what we're focused on. And then moving us into this frame of portfolio navigation, which is actually once you start thinking about drawdowns and recoveries, you really start wanting to have much more sophisticated scenario tools. So a lot of organizations use capital market assumptions to make projections. They'll use pretty blunt Monte Carlo style modeling tools. But what I think we're witnessing now as we explain some of this is the power of being able to model portfolios into the future with all kinds of different parameters, recovery being one of them. Submergence, all these different components then allows you to build a much more resilient portfolio. You can diversify your portfolio according to submergence. You don't just have to diversify according to risk factors and volatility and things like that. You can say, well this type of asset has this submergence profile and that asset has this submergence profile and we should diversify according to that to allow ourselves not to have as much of a overall drawdown. So those are the some of the things that we're working on.

Ted Seides (58:14)

So in the future, if we look.

Interviewer (Ted Seides) (58:16)

Out to using some of these technology tools, aligning it with someone's investor identity, we may have more efficient use of cash. We may be able to weather drawdowns in a more intelligent way. You've always been involved as an advisor and an investor in some of the companies that are working on that future and would love to hear either updates.

Ted Seides (58:37)

On companies you're invested with or anything.

Interviewer (Ted Seides) (58:39)

New that's come on your plate.

Ashby Monk (58:40)

I'm head of research at this company, Addepar. I'm splitting my time between Addepar and Stanford right now. And the reason I'm doing that is Addepar is investing in the GPS heavily. So for me, I admit that I almost have started thinking about this tech model of using less cash as like the endowment model is to Yale what the tech model is to Addepar. This could almost be the Addepar model. I am able to go into this company's data and begin to see that organizations that have really invested in their tech are using the navigation tools. And if you remember, one of the companies I started in 2017, timeframe was called RCI. We invented this software called Navigator. It's funny, it's not like any of this is new. Just nobody listens to me most of the time. So I've been working on this navigation concept for a long time, Ted. But what we're able to show is people on the core Addepar with the GPS and that Navigator, it's very promising. We can see 1.5% less cash holdings. And so I'm trying to write all that up right now as a kind of academic paper just to be able to show how technology can enhance returns. So that's really the fun for me right now is how do I leverage all of the entrepreneurial and corporate opportunities that I've been presented at Stanford? How do I actually bring that back into the academic community and through podcasts like this, to begin to explain in less commercial terms what I'm learning. Ultimately, all that commercial stuff is in the service of trying to solve that higher problem, which is helping pensions, sovereigns, endowments, foundations make more money. I think the world would be a better place.

Interviewer (Ted Seides) (60:32)

All right, Ash, I got one question. I probably asked you at this point in time, almost all the closing questions I usually do, but there's one new one, which is, what was the most challenging moment in your career or life?

Ashby Monk (60:44)

Is this the part of the show where we eat the super spicy wings? I was gonna.

Interviewer (Ted Seides) (60:48)

I think so.

Ashby Monk (60:48)

No.

Interviewer (Ted Seides) (60:49)

I think so.

Ashby Monk (60:49)

So, look, I think Covid was really hard. It was hard just with family, with all these little companies that you mentioned, like, you know, it almost killed two of them. It was just really a lot of uncertainty. A lot of sleepless nights wondering how we were gonna get through. I wasn't as worried about my health as I was about the health of the things I had been working on that I had dedicated my life to and brought my friends and family into. That was super scary. So in some of those instances, we really lucked out and we managed to land the ship or we managed to deliver on the project. And so looking back, I could say, wow, I learned a lot. And it was overall a pretty constructive time from a professional standpoint, but it was so scary. And I think that type of fear, it's not the first time I've had that level of uncertainty. I think I said this on the first time I was on, after the 911 events, my wife and I, we just picked up and we moved to Europe. And I can remember being like, oh, my God. What am I going to do with my life? And so I felt that feeling again through Covid. I feel like we're in a good spot now. In fact, look at us. Here we are. We've got this amazing setup. We're doing this podcast. We're both in our own place. I feel like I've got eye contact with you, Ted. In a strange way, certain things have really improved, but it took a lot of suffering and navigating uncertainty to get to this moment right here.

Interviewer (Ted Seides) (62:14)

Well, Ash, it's always fun to hear what you're up to. Really excited to continue to follow the progress of all these tools you're working on to help a community. So thanks for sharing.

Ashby Monk (62:24)

Thank you, my friend. You're an inspiration. All right, talk to you soon.

Ted Seides (62:28)

Thanks for listening to the show.

Interviewer (Ted Seides) (62:29)

If you like what you heard, hop.

Ted Seides (62:31)

On our website@capitalallocators.com where you can access past shows, join our mailing list, and sign up for premium content. Have a good one and see you next time.

Podcast Disclaimer Narrator (62:43)

All opinions expressed by Ted and podcast guests are solely their own opinions and do not reflect the opinion of Capital Allocators or their firms. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of Capital Allocators or podcast guests may maintain positions in securities discussed on this podcast.