How LPs Allocate to Venture in 2026: What They Want, What They Don’t | Baylor University CIO

The single reason that privates exist is to make money. Period. I'm a little perplexed by the length of some of these funds. It's not clear to me that the GP incentives are aligned with the math that runs endowments.

Sure. Happy to be here.

Right, it's a pretty important job, right? Particularly in the place that we are with higher ed right now. You know, we obviously have fewer high school students in the US, you know, kind of coming out of the great financial crisis. And so as the number of high school students decline, that's obviously fewer tuition dollars. The other thing that we have going on obviously is that the last couple of years it's been more difficult for international students to come over to the States, appropriate visas, stay, etc. All of those things, those are full-pay students obviously. And so that kind of compresses higher ed, you know, financial books a different way. And so what that means is that collectively there's a lot, a lot of competition for domestic students these days. And if you just look at the last, like this incoming class, I guess it would be the class of 2030, there are a lot of schools across the country that did not meet their targets for, you know, incoming student class. And what that means of course is that the revenue has to come from somewhere else. And so in this time and space, and I think realistically for the next 10 or 15 years, distributions that are coming off of endowment funds are going to be increasingly important. And so we manage sort of like with that in mind. Now we've always been good at the downside. So historically our office, like first quarter of 2026, I think the S&P was down 4%, we were flat. You know, if you go back over time and you look at the fourth quarter of 2018, the first quarter of 2016, 2012, if you look at a lot of these different times, our office in general tends to outperform to the downside. And what we've kind of gone back and looked at is how could we get better at the upside. We started this about five years ago, kind of knowing that this high school, you know, student issue was going to kind of rear its head, be a problem. And so we've reorganized things over the last five years to make sure that we're doing better on the right side of the distribution.

Well, I've had finance faculty actually laugh at me, right? So when I say like what we're trying to do, and I'll let you be a little bit the judge of that. I mean, effectively what we're doing is we run sort of like a value-centric, high-quality book, particularly on the equity side, because it's really, really hard to control sort of like the equity beta, right? So you could buy puts. That's kind of like a money-losing effort like over long periods of time. And so we try to do it thematically through factor allocations. But that then means of course that to the upside, when you're in a momentum-driven market, a growth-led market, that you're going to trail. And so the issue is, you know, the market's up 70% of the time. If you're going to trail to the upside, that's going to be problematic. And what we've tried to do over the last really three to five years is we've tried to increasingly solve that with convexity. And we've tried to do that in a manner such that we're actually not paying a theta bill on sort of like a normalized basis.

Yeah. So basically what we've done is typically higher ed outsources the investment of the endowment to a whole set of different managers. And so we by nature have a bunch of investments in a number of co-mingled funds. And co-mingled funds by definition means that there's one GP who's managing the money and then there's like a hundred or a thousand LPs who are receiving the returns on that money. The issue with co-mingled funds is of course at any given point in time you're receiving the average risk-return profile that that manager is providing in order to keep all of those LPs satisfied. And at any given point in time, Baylor's risk-return need might vary from what the average LP in that fund would desire. And so what we've tried to do is kind of go directly to the GP and say, 'Hey, this co-mingled thing isn't like totally working for us. We need to like optimize our risk-return profile better. If we give you a bunch of money, would you run the same strategy but do it just for us and then we have a look or a call into what's going into the portfolio.' So let me give an example. Say we have Nvidia in the portfolio, right? And then the next marginal manager wants to add Nvidia to his or her portfolio. Well, we can look at the portfolio, like the GP doesn't know that. We can look at our portfolio and be like, look, we've got plenty of Nvidia. We actually say no, we don't need more Nvidia, right? Or conversely, let's say that we're, you know, value, high quality, the next marginal manager wants to add Nvidia and we're like, we actually don't have any of that. So we'd take the Nvidia that you're offering, but why don't you make it three times as big because that's what we need to like back into a more appropriate, more optimized risk-return profile for our portfolio. And it's actually worked like exceedingly well over the last two, three years.

It's interesting. We actually spend a lot of time talking about this and in fact I think we probably spend more time talking about this than we actually do manager selection, which is kind of unique in the space. Presently we're around 45% private, 47% private, 53-55% public. And I think it's really important for if you're starting with a blank sheet and you're going to do privates, you really need to nail down the private side first, right? Because the private side is going to suck your liquidity and sort of like hogtie your ability to allocate between managers or between strategies. And so you really need to figure out what sort of liquidity environment can I live with on the private side and sort of determine what that allocation is going to be. And then I think you just need to sort of like box it and set it aside and be like, this is what's going to be operating here. And the reason you have to do that is because this can't change, right? Yeah, I mean you can do secondaries, you can, you know, tweak it at the margin, but it's really, really hard to move a private book around.

Right. So our allocation range around privates is 35 to 55, which means that we want 55 to be the case when we have a denominator issue, right? When equities have gone down and the public side is smaller than it usually is because of this particular difficulty in the market, that the private side isn't going to kick up so much that we're going to be forced into selling, right? Like the number one thing to avoid is fraud and the number two thing to avoid is force selling, right? That's a disaster. And so we kind of target 45%. You know, if publics race ahead then it puts some downward pressure on that and if we get into, you know, a financial crisis, something like that, it would put upward pressure on that. But for example, the last bit in 2022 when tech, you know, kind of slid a bunch, or you could go back a couple years prior to the pandemic, I think that our private side got to like 51, 52, but it wasn't so much that it either constrained our ability to allocate and it certainly wasn't enough that we got into a force-selling situation.

Right, we've had a different perspective on this over the last five or six years that really came out of what I was talking about before when we knew that the school was going to have issues as it related to enrollment, right? And it's not just a Baylor thing, but like every school, demographics can kind of be a slow-moving train wreck, right? But the benefit of the slow movement is that we can sit back and look five years out and know what's going to happen. And so we started this five or six years ago, like shortly after the pandemic, and we basically said the single reason that privates exist is to make money. Period. End of story. And so anything in the private book that isn't going to lend itself to excess returns, again, we need to create money to create more distributions for the school that's going to have enrollment concerns. And so if you're not going to keep up with the highest returns that we can generate out of the private book, we've kind of moved on from that. And so a lot of the real asset stuff in our book is sort of like winding down, not being renewed. And so we're really focusing, to get back to your question today, we're focusing on VC, expansion, growth equity, capital, and buyout. That's kind of it, right? So if we're going to lock up money, we want the highest returns.

I will say that, you know, we're coming along a little bit later to the party than some of the Ivys, Leagues, or Stanford or what have you as it relates to the sort of like VC brand names that you're talking about. And so it hasn't been for lack of trying. It's just like when you knock on the door, they kind of like don't answer, right? So we've kind of had to go, we've kind of had to like try to figure that out differently. What I will say though is that the ladies in our office have had exceptional, absolutely exceptional returns out of like the expansion growth equity category. So we've actually had, you know, some questions of like should we just allocate more dollars to that sector of the market. At the margin we have, but I would say, you know, we still do VC, it's still in probably newer upstart names.

I do. I'm a little perplexed by the length of some of these funds. And I've got to be honest, I'm not sure. It's not clear to me that the GP incentives are aligned with the math that runs endowments. And so...

Let's just do it for example, right? You know, historically they were like 10, 12-year funds. Now they're like 15, 18-year funds, right? So much to the chagrin of like all LPs, right? But the issue that you run into is that okay, so you get your money back in 15 or 18 years and let's just say it was like phenomenal experience and you're up like 15x. You're like, that's fantastic. But the issue is that it happened over 15 to 18 years. And what simple math would suggest is that like if you were in a growth equity fund that was six years in weighted average life and you were up 3x, and then you redeployed into another growth equity fund that was up 3x in six years, and then you did it again, that over the course of 18 years you'd be up 27x, which is better than 15x, like a factor of two. So I understand why people want to hang on to their winners, but the compounding of capital, and I'm trying to create the largest pile of money for students. Students can't pay their tuition with returns. They have to pay with dollars. So I'm expressly interested in creating the largest pile of money. And the largest pile of money is governed by like simple compounding math. And so what we're really after is the velocity of capital, not just returns on capital. Whenever the velocity of capital is going to start to asymptotically approach like wherever it's going to be, then we want to be out and move on to the next thing. In other words, like it's really, really hard to do like 3x in six years, right? It's easier. You have winners now. The company's going okay. It actually looks better on your marketing if you're up 6x instead of 3x. So like if people held on to it for another five years and got like a double, then they'd be up 6x instead of 3x. That suggests that the next fund will be raised, etc., etc. But I actually don't care about any of that, right? Like that's a business decision, right? That's related to the business. And I'm not optimizing for the best business for the GP. I'm trying to optimize for the biggest pile of money for our students. And so I get that there's a little bit of a disconnect there, but the math issue does kind of drive me nuts.

I get you, David. I'm not doing that for you and neither's the best firms. Yeah, well, and that is a question that gets batted around a lot in our office. And so, you know, there is something to be said about sort of laddering returns, right? So it's okay, you know, to go, you know, allocate money to some manager and say like those returns are going to show up like six, seven, 10 years from now, these other returns are going to show up three to five years from now, and then like kind of on my side those returns are going to show up one to three years from now. So we do think about it that way. But I would say that time actually, there's a rule in our office that you're not allowed to talk about returns without also talking about time because it's very common on the private side to just say everything like, well, you're up 2x, 3x, 5x, whatever. But that tells you nothing, right? If you're up 5x over 30 years, that's horrible, right? And if you're up 5x in five months, that's, you know, that's amazing, right? I guess that's SpaceX.

It is for us. Yeah, it is. It's a stage, you know, it could be the case that somebody allocates to something that really takes off and goes quite well. Like for example, we happen to have about 2.5% of the endowment in Anthropic. We have no exposure to SpaceX. We've had no exposure to OpenAI. But about 2.5% of the endowment is in Anthropic.

I mean, that's not us, right? Like that's managers.

That's not really how we roll at Baylor, but...

It'll depend on what we think about the name and it'll also depend about the size of the position once it is public, right? So we've sold, you know, shares before. We've also had shares before. We've also let shares run before. So it kind of depends to us what we're expecting, what the profile of the portfolio looks like, and the position and the risk associated with it.

Only because we're in the middle of the country, I think.

Yeah, we do. I would say like if we had an edge, I would say that we're pretty good on human behavior. And so a lot of these things, you know, I don't dispute at all, like I'm not an engineer. You know, much of the stuff that comes out of Silicon Valley is over my head. But I do know how people think and I do know how people make decisions. And so it's pretty easy in this case, you know, like software is dead. It's all going to zero. Somebody's going to vibe code this and, you know, whatever. And like I have friends that run, you know, 300, 500-person, you know, private family businesses. And it's easy enough to pick up the phone, call them. We're like, 'Hey, say your son-in-law vibe codes something and you're going to like tear out your CRM.' And they're like, 'Not in a million years.' Right? It's not their job, right? Like I have a good friend who runs like a vertically integrated like potpourri business, right? Like he knows everything that there is to know about that, but he is not going to tear out key important parts of, you know, what makes his business run behind the scenes on some unproven thing that, you know, I think it was the CEO of Salesforce, like I don't know, six or eight months ago, said that like the best that AI was going to be is like 93% right, which is like phenomenal. And that might be like better than like a lot of people, but the issue is software is 100% right. Right. So like if you need your books to like match up and whatever, like yeah, that's not going to happen. So I actually think as we've kind of like thought about it more, I actually think that in some of these vertical industries that software is actually going to be the delivery mechanism for AI. That in other words, for like my friend who's in like a niche business, very, very good at what they do, I think they're the only vertically integrated potpourri maker in the world. I think that what's going to happen is that the trust that's been built up with the software providers is going to translate into, 'Hey, could you add AI bits, you know, for me on the back of this software.' And of course, like, you know, the SaaS companies aren't stupid. It's not like they're sitting there and like, 'Hey, we're worth, you know, 20 or $50 billion. We should let this go to zero.'

Like Sean and others have like told me that, but like I don't actually understand, right? Because like if it's on sale, right? So software at that point is like on sale to the tune of like 50, 60% from like October of '25. And if the thesis is software's going away, software's going away, it's down 50, 60%. You call businesses and they say that's not true. You're like, I'll own that.

And that's why we have managers like Sean, right? So he's the expert. So I'm like, I'm going to give you more money, but I want you to go through your list with me and tell me all the things that are least likely to be interdicted by AI and then like own those. So I'm making a decision based on human behavior and how I know people make decisions, right? And I'm allocating based on that. But I'm relying on the manager to be expert in their individual field and give me the correct perspective and what's going on on the ground.

I kind of think that that's our job, right? I mean, like we are, like my seat is like an allocator seat. My job is to allocate. To go back to the like the Buffett or Charlie example, right? Like they also are allocators, right? And they're deciding who gets the incremental dollars. Do they send it to Burlington Northern or do they send it to, you know, their energy company, right? And depending on what the outlook is, what the capex requirements are, etc., you know, they get budgets submitted to them and they may or may not allocate more of their cash pile to those companies.

Not for me. I would say it goes the other way. I actually learn a lot from the public side managers, right? And what I find is that there's a lot of this like, you know, spun up like, 'Oh my gosh, like we're going to have autonomous cars in like three years,' like in 2016, right? Yeah. Right. Right. Like all the regulatory stuff that you have to go through so that you don't kill somebody. Yeah, we're 10 years on and what do we have, like 5,000 cars on the road? Like please. Right. So like I get sort of like the mental imagination that, you know, you can go like, 'Oh yeah, we could put, you know, we could put something on the moon and we could mine the moon and whatever.' Yeah. Okay. Like get back to me in 30 years.

No. Public markets are the big leagues.

They're being... like, you know, whatever, there's millions of people making decisions on dollars every single day for every single company. You know how things get valued on the private side? Of course you do. Three people get in a room and say, 'Hey, I think the value is X,' and they're like, 'I'll fund it at that.' Great. And that resets the whole price.

They can be irrational because they are governed by people. The difference is that there are tens of millions of people trading on that information. Whereas on the private side, there's like three.

Yeah. That doesn't mean that they're right. It just means that it incorporates all available information, which does not happen on the private side.

Correct. Correct. I don't think there's any question about that. I literally have been in these conversations, right? Where like three guys get together and are like, 'Hey, I think it should be this,' right? On like, on what, right? And we're like, 'Well, I'll give you $50 million at that price.' Okay, fine.

Exactly.

So that's one thing that the ladies have done an extremely good job of. Recall again that I'm coming from the public side. So, you know, when you run trading books, everything has to be priced every day, right? So and ostensibly it's so you make better decisions, right? Because if you have things mismarked, then psychology works against you, right? Like if you say that this is worth $30 million and it should be worth $10 million and somebody offers you 20, then because you would ostensibly take a loss from 30 to 20, you're liable not to hit that even though it's a premium to the actual value. And so pricing is just a way to make sure that you are psychologically aligned to the reality of the market. And so one of the things that we really try to do is to make sure that our managers are not pushing valuations, right? We want valuations to be conservative rather than aggressive. And you can see that in sort of our return data in sort of like the six months, nine months prior to something being taken out. Our, I think, average gain on that is sort of like 60 to 90% and I think from a market perspective it's more like 30 to 50%. Which would suggest that our marks, our managers' marks tend to be more conservative than others. So I feel, you know, like I kind of sit on top of this thing and I kind of have to vouch for, you know, the valuations that we have as it relates to, you know, talking to the regents or administration. And I feel pretty comfortable that on the private side, our marks are actually more sane than on average.

No, I feel pretty comfortable with where we stand. I would say I think our biggest allocation is in growth equity on the private side and we feel pretty comfortable with our capability and the manager set that we have there.

The return timeline, there's also fewer zeros, right? And so that kind of goes to the value bit. Of course, if there, I mean, it's just simple math. If there are fewer zeros, then everything else doesn't have to cover for the things that don't work, right? Which is what helps get you to like, I think that their book is like annualizing at like 30%, right? On sort of like the growth equity side. So that obviously meets our like 8% bogey. So I don't even actually know that I've ever had that question before.

That just kind of comes with the territory, right? I mean, like if what you're going... basically what we do is we say this is the amount that's going to be in privates and then we say we're going to allocate to PE, expansion capital, and VC and we're going to do it in these sectors and then I let the ladies have at it and they come up with a portfolio and the portfolio overall has sort of like an expected return hurdle that they need to clear. If they're not clearing it, then that's a problem. If they are clearing it, then that works great.

It's on a couple fronts. Like obviously on the distribution side, that's something that we can't get around, right? And that's about 5% on an annual basis. And so that, you know, on a dollar amount that keeps going up, which we want it to, right? Like that is the thing that, you know, pays for scholarships and professorships, etc. On the sort of like subjective side, so let's call that like the objective side of the liquidity equation. On the subjective side of the liquidity equation is sort of like what capital do you need to have around to allocate to the next thing that's going to go up, you know, 20, 30%. So we talk to our newer analysts about this and we say like, 'What do you think the odds are that we find something to, you know, be up 20% sometime in the next four years, like anything anywhere?' And they're like, 'Wow, really high.' And we're like, 'Great. So then cash is worth 5% a year apart from what you're going to earn on cash.' So if cash is earning three and a half percent plus 5%, so opportunity cost, you know, cash is worth eight and a half percent. So if we find things to do that are north of that, then we do them. And if there's a period in the market sort of like '17, '18, '19 where we're not finding things to do in that ballpark, then we let cash get larger. So we kind of came into the pandemic with sort of 15, 16% in cash because we were looking around and we're like, I don't see something to do. And so our cash balance is sort of indicative of, you know, what we're seeing to do to make money.

Interestingly, in this period, so in the '17, '18, '19, you know, kind of cycle, we weren't finding other things to do. This time we actually are finding stuff to do and so we've actually kept our cash balances pretty low because we keep finding, you know, 20, 30% annualized things to do. So it's just, and so our cash balances just end up being a function of like, you know, what the environment is.

I can't come up with a specific example right off the top of my head, but I will say this is that whenever you're trading, you for sure are going to lose money and sometimes you're going to lose a lot of money and sometimes you're going to lose a lot of money for a long period of time. And the takeaway from that, basically everyone goes through it. Everyone, you know, walks into the seat and thinks like that it's not going to happen to me. This seems pretty easy. Sort of invariably, you know, you get kicked in the shins and then hit over the head by a 2x4. And the takeaway from that is I never want to be all in. Things can always get worse, right? So when we're allocating to software in, you know, Feb, March of this year, we're not like drawing a line in the sand and we're like every available dollar is going into software, right? It's down 50, 60%. Like who's to say it's not going to be down 70, 80%? Right? And so we've set it up so that we're methodically and sort of mechanically allocating into difficult markets. And the reason we do that is to try to take the emotion, the psychology out of it.

Yeah. So I'll give you a perspective on like the overall markets, right? So we basically say if the market's down 0 to 10%, we don't care, right? We're an infinite live portfolio, you know, 0 to 10% is like normal stuff. The way that I approach it with young analysts, I'm like, if something's on sale for 10%, do you rush out to the store to buy it? And they're like, well, no, not really. I'm like, what about 20%? And they're like, I think about it. Maybe 30%, yeah, probably 40% for sure. Right. And so we think about declines in the market in sort of 10% increments and we have liquidity set up in such a way...

way that we could allocate sort of like every 10 percentage points down. We don't really worry about, you know, 0 to 10%. That's normal.

And that's why we do it methodically and mechanistically, because we're never like drawing a line in the sand and saying like, down 20, oh, I'm all in, right? Where do I like down 20, maybe I'm 20% in. Down 30, I'm another 20% in. Down 40, I'm another 20% in, right? So we're doing it in that way. The reality is that we actually never get all the way invested before it rebounds. And so you could say that, you know, we leave money on the table. That's true. But the benefit is that we're never in the situation where we're like, 'Oh my gosh, I love this so much and it's down and I just can't have any more of it,' right? So that's the scenario that we're trying to avoid. And that just comes from like perspective, history, and experience of like, you know, having trading scars all over your body from you. You thought that you were right. You thought that you knew where it was going to go. You put a whole bunch of money to work and then it went lower, right? It's a terrible place to be.

Yeah, a lot of that is in the hands of the managers, of course, right? Because we're not like trading individual stocks. But what I do find is we spend a lot of time working with managers sort of making sure that their psychology and their emotions are in the correct place. So, for example, interacting with Shawn, you brought it up, software space, you know, first part of this year, I was probably on the phone with Shawn every day for four weeks, right? And we're talking through individual names. I'm relaying what I'm hearing in the market. He's relaying what he's hearing in the market. We were sending each other like articles or quotes or, you know, news stories at all hours of the day, etc. And I like constantly ask him, 'Okay, you have this name, but if it goes down like another 20%, what are you going to do?' Right? Or you have this name and you have another name versus each other. Which one do you feel better about or has better risk-adjusted opportunity set here? And then I'd push him to be more concentrated. And that's actually what the portfolio ends up doing. And I think kind of to your point, that's what ends up happening in most cases in sort of real-life downdrafts is that portfolios end up getting more concentrated.

No, we own everything under the sun. So does every endowment portfolio, right? So like we own everything from like sunscreen to helium to like tech to, you know, like I don't know what, right? Like we own all sorts of consumer product goods that you would see in the mall. We own all sorts of business-to-business, you know, software or tech companies that I've never even heard of before, right? Like we own like real estate development projects. We own everything, right? So like it's always funny to me when people like compare an endowment portfolio to the S&P 500 or something like that. You're like, we're like infinitely more diverse than the S&P 500. It's not even close. If we get a little bit more concentrated at the margin, like that doesn't remotely change anything for us.

There's something that we do that not a lot of schools at our size do, and that is we almost hire exclusively from undergraduate ranks. Now, to be clear, the caveat there is schools or endowments our size, right? So we're about 2.7 billion. You know, 14 months ago we were 2.2 billion. A couple years before that we were 1.4. So in that sort of like 1.3 to 3 billion kind of range, and I've sort of figured out why a lot of people don't do it. So it was a little bit of something that I missed. But the bit is like if you hire undergrads, and based on where our office is located in Waco, we're about 100 miles from Dallas, we're 100 miles from Austin, we're right in the middle between the two. It's pretty difficult for us to hire a mid-career professional and get them to stay for a long period of time. It'd be really difficult to pull somebody from LA or New York to Waco and say like, 'I need you to be here for 10 years.' And so what we've done to try to solve that is hire from undergrad ranks. They clearly have chosen the school by definition. They've chosen the area, etc. They've been around. We actually screen pretty hard for that when we're hiring people. The issue is that when you do that for the next five or six years, you're spending a lot of time pouring into that person and helping them kind of like level up. And during that period of time while they're leveling up, it's like all still on your shoulder. So I now, I totally kind of like forgot that part. Like I totally got the, you know, we'll have, you know, a stable investment team and, you know, these people won't go anywhere or whatever, but I kind of forgot the bit of like, yeah, and for the next five or six years, you're going to be wearing like all sorts of hats during that time.

I think that nuts is not the word that I would use. I would say that they are accepting alternative risks, right? And so the alternative risks are on the upside to me is that I have a stable team, right? So I have worked with Renee for almost 16 years. The next person that we hired, Jyn, she's been here 11 years, right? And you can like kind of go on down the line. That actually occurs is pretty evident across the industry. It's like longevity begets returns. So I'm benefited on the stability front. The negative for me is that the upfront bearing of all of that time, I have to, there's a period of time where I have to like carry the team. On the flip side, if you hire mid-career professionals, you don't have sort of like that upfront cost of like having to carry the team, right? Because they're more plug-and-play. But you sort of wear this risk of turnover and, you know, potentially poorer returns.

I don't think it's a wrong incentive mechanism. I think that it requires people in the space to be very missional, right? So like I wake up every morning motivated by sending some, you know, sophomore in high school to Baylor that hasn't even thought about college yet, right? Or some like seventh or eighth grader who doesn't know if they're going to go to college and, you know, they're thinking about baseball scores from the prior night, right? Like me getting out of bed in the morning, going to work and wanting to crush it is entirely due to that, right? So, you know, everyone likes to be able to get their wife something nice or to redo the kitchen in their house or go on trips, but like that is not the motivating factor for either myself or the people on my team.