E338: How I Invest $9 Billion into VC & Private Equity
41 min
•Apr 1, 202618 days agoSummary
Chris Cole, CIO of the Margaret A. Cargill Foundation managing $9B in assets, discusses AI disruption risks to SaaS businesses, structural inflation concerns, venture capital consolidation, and his quantitative-qualitative approach to manager selection and portfolio construction across public and private equities.
Insights
- AI disruption risk is real for SaaS but not all software will be disrupted equally—system-of-record, compliant, and sensitive-data software face lower risk than commoditized solutions
- Structural inflation of 3-3.5% is likely permanent for the next 10-15 years, making traditional mean-variance optimization models unreliable for capital allocation decisions
- Manager selection requires detective-like diligence combining quantitative metrics (excess returns, idiosyncratic stock selection) with qualitative assessment (consistency, culture, behavioral cues) that models cannot replicate
- Venture capital is bifurcating into mega-funds (struggling to achieve venture-like returns due to scale) and smaller focused funds ($75M-$500M) that can realistically achieve 3-5x net returns
- Sizing of investments matters more than outcome accuracy—thoughtful position sizing protects against inevitable mistakes better than perfect stock picking
Trends
AI adoption is becoming table-stakes across all sectors, not just technology, creating productivity gains but also disruption risk for legacy business modelsStructural shift toward higher baseline inflation (3%+) is reshaping fixed income assumptions and requiring portfolio repositioning away from traditional bond allocationsPrivate companies staying private longer (IPO threshold rising to $500M+ revenue) is creating a gap where mid-market private companies replace small-cap public stocksBifurcation in venture capital with mega-funds struggling to achieve historical returns while emerging managers face fundraising challenges and consolidation pressureQuantitative equity managers outperforming fundamental managers in narrow markets, challenging traditional active management fee structures and justifying shift toward systematic strategiesVintage year diversification becoming more complex as capital call timing no longer aligns with fund closing dates, requiring rules-based approaches to measurementOffice culture and team stability emerging as leading indicators of fund performance, with turnover and poor culture predicting underperformance more reliably than quantitative metricsDPI crisis improving but not resolved—companies staying private longer means venture funds need extended 15-year terms rather than traditional 10-year structuresValue investing becoming crowded and commoditized with 7,000+ books and accessible pricing models, reducing alpha potential despite theoretical support from rising ratesOrganizational restructuring around risk assets (equity, credit, fixed income, real assets) rather than asset class silos improving portfolio optimization and reducing redundant diligence
Topics
AI Disruption Risk in SaaS and SoftwareStructural Inflation and Interest Rate OutlookManager Selection and Due Diligence MethodologyQuantitative vs. Fundamental Active ManagementVenture Capital Market ConsolidationPrivate Equity Vintage Year DiversificationPortfolio Organization by Risk Asset ClassOffice Culture as Performance PredictorDPI Crisis and Extended Fund TermsBehavioral Finance and Investor ParanoiaCapital Allocation and Position SizingPrivate Company IPO Threshold ShiftEndowment-Like Foundation Investment StrategyReference Checks and Qualitative DiligenceMean-Variance Optimization Limitations
Companies
OpenAI
Released ChatGPT in fall 2022, marking the beginning of mainstream AI disruption risk for SaaS businesses
DeepSeek
Made major AI announcement in early 2025, exemplifying ongoing AI model competition and disruption threat
Palantir
Trading at 100-200x sales with extreme valuations, cited as example of irrational pricing that quant managers can tra...
Margaret A. Cargill Foundation
The foundation where Chris Cole serves as CIO, managing $9 billion in public and private equity investments
Founders Fund
Pioneered best practice of preventing GPs from making investments in their first year to avoid early-stage bias
North Dakota Land Trust
Implements best practice of capturing asset class index exposure before making active manager investments
Russell 2000
Small-cap index historically used as proxy for private equity but may no longer be appropriate as IPO thresholds rise
MSCI World
Global equity index used as benchmark for quantitative manager performance evaluation
S&P 500
Referenced as example of difficulty in predicting annual returns, illustrating limitations of capital market assumptions
People
Chris Cole
Manages $9B in public and private equity, discusses AI risk, inflation, and manager selection methodology
David Weisburd
Podcast host conducting interview with Chris Cole about investment strategy and market outlook
Clayton Christensen
Wrote 'The Innovator's Dilemma' about disruption cycles; book influenced current generation of tech CEOs
Elon Musk
Example of CEO self-aware about disruption risk and actively working to disrupt own business model
Mark Zuckerberg
Example of CEO self-aware about disruption risk and actively working to disrupt own business model
Sergey Brin
Example of CEO self-aware about disruption risk and actively working to disrupt own business model
David Rubinstein
Made point that inflation rather than austerity is most likely path for government debt resolution
Frank McHale
Implements best practice of capturing index exposure before making active manager investments
Alex Hiddleston
Podcast guest known for exceptional reference-checking skills developed through deposition lawyer background
Cliff Hosnick
Discussed three-year underperformance cycle and career preservation pressures in manager evaluation
Stanley Druckenmiller
Learned from George Soros the importance of undersizing positions in macro investing strategy
George Soros
Taught Stanley Druckenmiller the value of undersizing positions in macro investing
Kim Scott
Wrote 'Radical Candor' about management culture emphasizing honest feedback and performance focus
Graham and Dodd
Pioneered value investing methodology 50-70 years ago, now commoditized with 7,000+ books on topic
Quotes
"AI risk is super topical. I think CEOs of SaaS businesses should be very scared of being disrupted. The critical part here is making sure that if you're invested in private equity that you have a very good general partner."
Chris Cole
"I would say structurally higher inflation, which I think is with us for the rest of my career. That's a big change from the past 40 years. I don't see us going back down below 2% inflation in the next 10 to 15 years."
Chris Cole
"All models are false by definition. Models are extremely useful, don't get me wrong. But one should always consider what is the logic of the model? How accurate is the data going into the model?"
Chris Cole
"In places where we've made mistakes, not always, but many times it's a bad culture. Partners leave or people below the partner level leave. Turnover is always bad, especially in a private fund."
Chris Cole
"When I think about throughout the career, we're all going to make mistakes, we're all going to get things wrong. So what really matters is sizing the investment. If you get something wrong that's giant sized, it's a major problem."
Chris Cole
Full Transcript
Chris, you run equity strategies at the Margaret A. Cargill Foundation. What part of the equity market keeps you up at night today? Being an investor or an allocator, you have to kind of paranoid in general. So I would say everything, but but to be more specific, I would say that AI risk is super topical, obviously, aside from private credit, which I don't manage and is well publicized in the media. I think software related private equity could see an adjustment period. You know, the AI risk is real. I think CEOs of SAS businesses should be very scared of being disrupted. You know, the critical part here is making sure that if you're invested in private equity that you have a very good general partner. On the other hand, OpenAI came out in fall of 2022. So it's not new. DeepSeq made their announcement in early 25. So hopefully good GPs are aware of risks to traditional SAS. And depending on the asset, not all SAS is going to be disrupted anytime soon. Think of like system of record, critical software, compliant software, highly sensitive data. The other thing is today, there's going to be a lot of opportunities because everybody's aware of the AI risk. So I think there's going to be a lot of stuff that's coming through the pipe right now that could be quite interesting. And lastly, I would say top 10 tech companies in the US today, or I think on average something like 35 years old, so they've gone through desktop, laptop, mobile, SAS cloud. And so not all these companies are going to disappear out of the blue. And on the other hand, it could be an incredible productivity boost that might help help asset prices long term. There's a meta angle to this. Clayton Christensen famously wrote this book, Innovators Dilemma, which talked about the disruption of cycles, how the next cycle kind of disrupts incumbent. But what happened was that this generation of CEOs, Elon Musk, Mark Zuckerberg, Sergey Brin, they all have this book on their bookshelf. So they're all much more self aware and sort of being like the Kodak or the IBM of last generation, they're trying to actively disrupt themselves. I think that's a great point. That's a lot to mention, kind of aside from the AI risk, I worry about a lot of what other investors worry about with sovereign bond crisis, higher interest rates because of it, you know, we have war going on. And I think kind of the bigger one is just structurally higher inflation, which I think is with us for the rest of my career. That's a big change from the past 40 years. So absent some exogenous shock, I think we're in for structurally higher rates. I'm not saying we're going to go much higher, but I'm just saying I don't see us going back down below 2% inflation in the next 10 to 15 years. The national debt also keeps me up at night. And thankfully, I have a lot of resources I could call up a lot of people. And it seems to be that the smart consensus view there is that the most likely scenario is not some austerity measure. But it's the increase of inflation over maybe a decade, maybe two decades, that's going to be able to allow the government to pay back its debt. What are your reviews on this? Yeah, I totally agree. I think David Rubinstein said something to this effect a couple years back is that he basically made the point of like, you cannot cut entitlements, you cannot raise taxes too much more, they're already very high in many states and federally. So the real way out of this is to slightly inflate. So you know, 3%, 3.2%, 3.5% inflation, which will significantly help over 20 year period. On the other hand, you know, you have a new Fed chairman coming in who you know, I think generally is considered a hawk. And it'll be very interesting to see if this plays out. If I were to guess, I would say the new Fed chair is not someone who's going to tolerate, you know, three plus percentage inflation. Expert calls have always been one of the most powerful ways to build conviction. But today, investors are asked to cover more companies move faster and do it with leaner teams. With Alpha Sense AI led expert calls, their Tejas call service team sources experts based on your research criteria, and lets the AI interviewer get to work. The magic is in the AI interviewer purpose built and knowledgeable based information to conduct high quality context stretch conversations on your behalf, acting as a trusted extension of your team. Then they take it one step further, your call transcripts flow natively into your Alpha Sense experience and become queryable, searchable and comparable. So your primary insights plug directly into earnings prep, digital work streams and pitch books with zero tool switching. 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Now the first to see wins the rest follow learn more at alpha sense.com slash how I invest one of the unique things about AI and this tech revolution is that it's not limited to the technology space in that if you had a biotech revolution, biotech might be transformed, but it's not going to transform SaaS companies. Talk to me about that. How do you look at the AI revolution? How it affects your entire equities portfolio? You mentioned biotech, it's already disrupting biotech. You know, there's numerous examples of AI led drug research, which is creating drugs much faster than than they have in the past, you know, it affects productivity everywhere. We're using it internally, I'm sure other companies and other foundations and elements, etc are using it. So that's the kind of crazy impact of this, which is still unknown, right? As I mentioned, it might lead to a massive productivity boost. And similar to software, it's not a vertical, it's across every single thing, you know, it'll eventually be in old school, industrials, maybe even utilities and things that are otherwise quite boring, it'll take some time. Again, as I mentioned earlier, with the whole critical software type of stuff, I don't know if anyone that runs a nuclear power plant is going to switch to an AI model anytime soon. But over time, I think it will, it can disrupt just about everything that we know in the in the economy. It's actually a very difficult question to answer, which is what will AI not disrupt? My first guess is plumbing, or electrical work, you know, kind of behind a wall, you need a new light put in your house. I think it's gonna be a long time before they have an AI robot that's going to come into your house and do that work. Although I think at some point, maybe maybe they will. I've seen a lot of very interesting roboticization applications that are coming. But I think that might be, you know, a decade plus off, it's not longer. So famous, more of X paradox, which is AI is going to struggle at things that humans could do and humans will struggle at things that AI will do. Backp, decided to put equities, public and private under one roof under you. Talking about that decision, and how's that played out? We're a relatively young organization. And one of the benefits, and there were some negatives too, but one of the benefits of being young is that we were able to kind of wipe forward on how to organize our CIO chose prior to my arrival, I had nothing to do with it, to organize us by risk assets. So equity, credit and fixed income and real assets. I was a high, I was very highly attracted to the structure as a dovetail dovetail well with a piece that I co-authored almost 15 years ago, it was entitled, hedge funds are not an asset class implications for institutional portfolios. This basically was the concept that many hedge funds, among other concepts, but one of the concepts was many hedge funds have traditional data embedded in their strategy. So, so they should reside in those risk assets, if you will, this makes for a much simpler strategic asset allocation, as they can be, you know, it can be uniform and singular, you don't have to have separate optimizations. For example, you have equity beta in perhaps three or four different asset classes, you have a private equity, you have a public equity, you have a hedge fund equity, and you even have it in some credit portfolios, depending on what the strategy is. So running multiple strategic asset allocation optimizations in a vacuum and each one of those is kind of clearly suboptimal. Moreover, equity is equity and doing diligence on public credit or hedge equity has significant overlap. There are differences, of course, on the periphery, you know, some some short securities, some use leverage, some are a liquid. But in the end, it's all equity risk. I'd also note that I think a lot of other institutions haven't structured this way. And I, I, you know, I think about why a lot, at least used to, and I think that, you know, very few institutions had large private equity portfolios in let's say the 1970s. So they added a private equity group, when private equity became popular. Likewise, in the 90s, hedge funds became popular. So they added a hedge fund team, which totally made sense. And I think today, you'd say, well, why don't they restructure? I just think it's there's a lot of operational pain there. You'd have to, you know, there's going to be turf warrants amongst people that run those different groups, they're going to have to go to their board and investment committee and see permission to restructure. There could be job losses. And so outside of a big catalyst internally, let's say a change over to CIO or maybe a sustained period of utter performance, I don't see other groups doing a do a re doing a reorg to somehow fit our model. And I'm sure they're supposing use to our model. You were the second hire at the foundation after CIO. How did you go about building your investment strategy from scratch? It's clear from the start that we were going to build an endowment like model. I saying endowment like because unlike endowments and some foundations, we had a sole donor. So we don't take in donations, we don't do fundraising, like many peers in ENF space. So in terms of risk, we're more conservative for a couple of reasons. First, we don't have fresh capital, we don't have fresh liquidity to work with or to help cushion the liquidity. Secondly, I think senior senior leadership here is committed to being a reliable donor to our vanties. So we take less risk in order to meet those commitments in both endow markets. Aside from these differences, the strategy was to create kind of a lower risk endowment like model. So we have much larger allocations to credit and fixed income and real assets than other endowment peers for sure and some foundation peers as well. When we last chatted, you mentioned that you use both a quantitative and a qualitative mindset. Talk to me about that. And how do you fit that into the investment process? Until recently with the rise of AI, especially like super AI, the one that does cognitive thinking and has feelings, etc. I don't think that there's a model or quantitative process that can pick the best managers. So I think the best allocators and this is somewhat self serving. As I have a liberal arts degree and a MBA from a school that's known for its quantitative analysis, I'll give you an example. In venture capital, data rooms often are lacking hard data. And the one thing I always mentioned as staff is that we want to select general partners who lie a little bit to us, rather than ones that lie a lot to us. I know that's very sensible. But I think it's hard to develop a quantitative model that could detect how accurate or how inaccurate a GP is being with us. If you work with models, or if you have an optimizer, it's going to seek a solution. And it might be a corner point solution. The famous example is me and variants optimization. So models love, you know, for example, in this case, a return series that are low ball and persistent access returns. But the made off fraud, for instance, was exactly that it was persistent returns and a low ball strategy. So you can't rely on a model just to pick that out because of course it's going to go there. That's what the model is designed to do. The other thing I'd say is like, you know, all models are false by definition. You know, I say that as an University Chicago graduate school business graduate, you know, I'll give another example. I used to build model airplanes, you know, the plastic model airplanes like World War II airplanes when I was a child. But nobody would ever assume that you'd fly that over the Atlantic, because it's a model. So models are extremely useful, don't get me wrong. But one should always consider what is the logic of the model? How accurate is the data going into the model? Again, I mean, variants optimization relies on on capital market assumptions. Capital market assumptions are frequently inaccurate. I've got ones in my drawer from 2010, 1112, they're all wrong. And so you have to be just highly aware that you're dealing with a model that's useful, but that is not a perfect solution. Unlike you have an MBA from Tuxco from Dartmouth and a master's in psychology from Harvard. And everyone always comments, Oh, that should be really useful. But I've actually never met anyone do both degrees. I think it's just there's no dual program. It is my simple, my alchemist razor to why more people don't do that. But when it comes to this quantitative and qualitative mindset, if you're to distill the main takeaways from that, when you're diligence, sing a manager, what exactly are you looking quantitatively? What is in the spreadsheet? And what are you looking that's not in the spreadsheet? The simplest things in the spreadsheet are, you know, are they are they are they producing excess returns? And what are those excess returns? You know, there's a lot of talk of alpha and then there's excess returns, I say excess returns because I know that that there's alpha in there, hopefully, and there's probably some types of alternative beta or betas that make up that excess return could be timing, it could be sector selection, things that aren't classically considered alpha. That's something we're going to look at on a quantitative side. You know, maybe digging a little bit deeper is if it's an active equity manager, we're going to look for idiosyncratic stocks selection. That's the highest that's the purest form of alpha. And so that's got to be high. But it's a hedge fund, we're going to want to see if they're deriving alpha or excess returns out of their shorts, you know, I don't want to just pay to have them short the market if they lose money on their shorts all the time. So that's maybe some of the higher level quant research that we'll do. You know, in the qualitative research, that's where it gets a lot, a lot more gray, a lot more foggy, if you will. And we're looking for consistency and kind of what the strategy is in discussions with them. I'm looking for that consistency through the entire employee staff from partner down to, you know, the first level analyst. It's one of the reasons I like in in in person meetings in their offices is that you can kind of get them separated by themselves and ask kind of the same questions. Similarly, what a police detective would do it in a crime investigation. And so those are kind of the softer things of like hearing consistency across what they're doing. And then on the way from just the manager meetings themselves, etc. is you know, referencing particularly off reference sheet references, which you have to do a lot of work there and kind of triangulate and figure out who should I talk to who's not on this list who probably knows this person from the past, or maybe the other current firm left, or, you know, situations such as that. It's funny, he's this analogy of a detective, Alex Hiddleston, who's been on the podcast three times. He's arguably the very best person I've ever met in terms of references. And he got his training as a deposition lawyer. So he knows exactly how to frame questions, how to ask questions and references, which are simultaneously probably the most boring part of manager selection, and also probably the most alpha is gained in terms of picking managers. That would be a great background. I'm sure he's so purulent at doing that. One of the things I was going to mention is I took a course, it was years ago, by a group of X CIA counterintelligence people. And they basically did this whole study on what people say and how they act mean like what do they do with their arms and they call them anchor points when they're lying. And they gave many, many examples and they showed many examples of famous people who were in either depositions or maybe just speaking with the press where they were lying, they clearly lie and everyone knows now because the stories have come out. And it was really enlightening to see something where you can actually begin. It's not totally foolproof. And it's not just that they say one thing that they're, you know, they're lying, but you can discern or kind of trace together dots if they're doing a lot of these different behavioral traits when they're speaking to you. It's interesting about references, which I obsess over on the podcast, I just think they're so critical is that you could have two institutional investors sitting in on the same conversation, and they have a completely different qualitative read on the reference from each other to very experienced people. That's a good point. I really like the diligence with one of my colleagues. And the reason is, you know, people, you know, I hear things that maybe they hear or they don't hear, or maybe I get it backwards sometimes. And so I think it's really helpful to have more than one touch point when you're doing diligence and maybe multiple touch points. I say that multiple touch points mean in private equity, I much prefer to meet the general partner prior to a fundraise, you know, a year in advance, two years in advance, you meet, you know, meet with them two, three, four times prior to the fundraise. Because in the fundraise, you know, there's at least two things that happen. One, the book is marked up in advance of the fundraise, almost always. And secondly, there, it's a beauty pageant at that point, they they're everything is framed in the best light. And if you get in there, you're two before and you know, I always ask what assets are doing well, and then give me at least one example of something that's not doing well. And what's, you know, what's the learning point from that, you get you get much better dialogue prior to the fundraise when they're not in kind of sales pitch mode. You're also measuring the slope. Where were they a year ago? How have they evolved over the last year, or ideally two, three years? You mentioned that you like to go to the manager's office and meet them in their office. Why do you like to do that? First, we want to establish that they have an office. I know that sounds ridiculous, but I think it's important. Secondly, I want or that they're even human. Yes. Secondly, I want to meet with partners and employees below the partner level. You know, maybe a famous example of this was during pandemic, when they did virtual annual meetings. And I was convinced first of all, it was just the three, maybe four partners that spoke. Secondly, I was convinced it was the script that the general council had reviewed. So it was very sterile and maybe not a lightning at times. It's much easier to meet with maybe the first level analyst when you're in their office. I also start diligence at the front door. What is the mood of the office when you walk in there? You can sense mood if you look around and kind of see people having a chat and in a good mood. How are you greeted at the door? I think that's an important one. I think you can get a sense of culture from kind of the minute you walk in, and certainly after you spend a few hours. I also start, I mentioned this earlier, I start with a uniform set of questions so I can get answers that are hopefully consistent and ensure that I had conversations in isolation. And sorry if that sounds parallel, but I think many investment managers are, you know, they're investment managers, Wall Street, whatever you want to call it, are motivated by most many, not most many are motivated by fees and performances can be an afterthought. And so we're trying to figure out are they are they high quality? Are they really motivated for performance? Not just the management? In many ways, diligence is just the operationalization of paranoia, figuring out whether what you're being told is the truth. That's brilliant. I'm going to use that a future. I want to double click on going to the office. So is there one office culture that out produces others? Is a happy office better? Or do you, are there like chip chip on the shoulder offices? What's a predictive office culture that leads to success? That's a good question. I, you know, I don't know if I know, but, but I'll say this in places where we've made mistakes. Not always, but many times it's a it's bad culture. Partners leave or people below the partner level leave. Pernarivar is always bad. Yeah, exactly. Turnovers bad, especially in a private fund. And, and so, so I do want a high performing office that maybe has a little bit of edge to it, but I also want to see a good culture, you know, and I could go into things like this concept of like a radical candor, which is a book by Kim Scott. You know, when it talks about basically this, this concept, like, I'm going to say what I need to say to you, because I care about you and I care about our performance or work as a firm. And, you know, I think that's kind of critical. So it's a bit of a balance. It's like, I don't want everybody all chummy and like, all friends and no focus on making sure that the hard work is done and that they, you know, that's a high performance up and out culture. I actually quite prefer up and out cultures. But the up and out culture can also be, it can also have a good culture to it where people are open, honest, communications good. And so those are the things you're looking for. So it's a little bit of a mix, if you will. It's kind of like the seven dwarfs, they're working, but they're happy. It's kind of like a jolly, jolly working culture. Yeah. So as a subset of building out the equity strategy, you had to build out your venture program. What were your first principles when you went about building a venture? I am going to take it beyond venture, but, but I would say that, you know, a couple of things, when we came in, the public side was heavily indexed. So to some extent, we could just start working on privates, plus private six a lot longer to build, it takes longer, you know, funds aren't open all the time, they're closed on funds by definition. So we spent most of our time in in private starting out. You know, if I if I think back and think what should I have done differently, you know, I wished and we tried, but we I wish we had delayed and taken our time, I think for two reasons. First, I think we would have made marginally better picks by doing more comprehensive market mapping, for instance, and just taking our time. Secondly, I think we would have had more flexibility. So let's say co investment, direct investment, specific secondaries. Keep in mind, we were building this portfolio during a very frothy period, you go 2015 through 2019. And my colleague and I were thinking at the time, let's go slow, we're building a portfolio for an entity that will exist in perpetuity. So why why do we want to rush forward in three to five years? And, you know, and the reason we we I wouldn't say we rushed forward, but we moved with a lack of tea is that there were some technical items in our reporting related to benchmarking, and it was painful from a performance perspective to go slow. These are technical items though. The other thing I'd stress is, I don't I don't have all you know, that's that's a minor regret. The portfolio is I think in great shape, but you know, it's doing well. But when I think about when I think back, I think this is an area of improvement that we could have, that may have been improved. A couple of best practices that I found on that one is this was originally popularized by Founders Fund, they didn't let any of their GPs make investment in the first year. So you had to see it's impossible you come in to venture, you meet a venture capitalist, by definition, they're the point 1% of person you'll ever meet. You think, wow, this is awesome. And you invest in the first three funds, because they're all point 1%. You're actually right. What you don't know is that you're actually looking for the point 0% 1% because everyone's point 1%. You want to be in the top 10% of that. So there's this principle of you have to see 100 200 300 managers before you really make that first investment. And you could you could operationalize that. The second, perhaps like a very qualitative approach to it that I've seen some foundations and family offices do is start by investing into secondaries, because they get exposure to early vintage, so you get more vintage diversification, you minimize the jaker. So you get to start to show how venture works. It's very difficult feedback cycle when you invest in you're like, Okay, just trust me for 14 years. This is going to work well. So there's a behavioral aspect to that. 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How is there opportunity cost to be exposure to the to the beta of the asset class, which doesn't sound sexy, but behaviorally, I love that because, you know, you're incentivized not to take action unless it's a really good manager. A couple things on that is that we did consider secondary is in retrospect, maybe we should have done some. However, I'll note that like, the reason I say that is at least one reason is that we were building a portfolio. So after we kind of built the portfolio in 2019, our average asset life was like 1.8 years. So there was a portfolio that was deep in the jaker, nothing mature because we were brand new people. And so that would have helped bring in some kind of older vintage and may have been cash flowing out. On the other side of that is that when you buy a secondary, let's say it's a let's say it's 2020, and it was a 2014 vintage secondary, we're buying you're buying a 2014 vintage priced in 2020, you're not getting a discount, you're not getting a you're not getting the initial investment that's now got up three X or two X or whatever the case is, you're buying into the two X or the three X. So I, you know, I caution to say like it's a it's a panacea, you know, some type of magical potion to fix a situation when you're building a portfolio. But but I also think like maybe we should have stopped and done that. Keep in mind, we were building so it was very much a startup environment, we're building performance systems, we're building risk systems. So to stop and to do a separate project like secondary, as opposed to just continue to fundamentally underwrite direct fund investments, it would have come at a cost, we could have done secondaries, but then we would have done less fund investments. And maybe that would have been better. But also, as I mentioned earlier, the portfolio I think is in great shape, significantly outperforming our benchmark. And so, so, you know, it's, it's ultimately a positive, I guess. When you're investing for a foundation, you want to get vintage diversification, which means you want to get diversification to different years, especially in venture capital, because some vintages are, are way up some are way down, as we know, historically, what do you consider a diversified portfolio from a vintage standpoint? Is this three years, six years? Is it just, you know, over longer time periods? Give me a sense for how you know that you're adequately diversified? It's a good question. I think three years is too short. Six years might be about right, but 10 years might also be about right. You know, I think what you want to do is, is because we don't know what the future holds, you know, as I mentioned back to the mean variance optimization, you're lucky to get the sign right in the S&P 500 in any one year, much less, whether it's up eight or 12 or 15 or 20%. And so because of that, in privates, it's even harder because you commit, but they call the capital. So you don't know what capital is going to be invested in. So I think you need to be really consistent and have an equity that you're putting out kind of, you're equally waiting every year, unless you have a crystal ball and you know that one year is going to be better than another. But we don't have one. And I wouldn't suggest the most investors that they should try to do that. So if you're being consistent and constantly, you're putting out more or less the same amount of capital with respect to your assets each year, I think you can achieve that diversification. The other area that I would mention is, you know, vintage year risk is a bit of a very complicated situation. I'll give you an example. A fund closes holds a dry close in September of last year. They call no capital during last year. And we have a current situation like we have with a war and lots of concern over the economy. And so they call 15% of the capital this year. And next year, they call 35% of the capital. And the year after that, they call 15%. What's the vintage year? Is it 27? Because they called 35% of the capital? Is it 26? Because they think that's when they first started calling capital. And so it just creates a complicated measurement as to what the vintage actually is. We have a rules based approach where it's the year that they first call capital. However, in reality, I know in certain cases, it's actually next year's vintage, not this year's vintage, because they might only call five or 10% this year. And they call the majority of it in the future years. So it's a very tricky question once you actually look into the details of when capital is called. So another way you might have to be more diversified because it's not if you invest across 10 years, you're not doing 1010 1010 1010. It might be 5515 5515. Yes, I'll give one other example. In October of 21, we committed to a fund that I think is top tier by our fund in tech. And they didn't call capital for over a year. So I didn't know that in its 2021 budget that I used for the private commitment, they didn't call capital until the end of 22, maybe even early 23. It's very hard to account like what vintage is that? I would say it's probably 2324 vintage, even though we committed in 21. I've been on a bit of a soapbox about this, keeping unfunded liabilities and cash. And everybody says you have to keep it in cash, because you don't know if it's going to be called. My perspective is better to do it in a diversified public security, because you still have 10 days to take it out. Why do you have to keep unfunded liabilities and cash? Well, because you have to meet those capital calls when they come in, I don't think you have to keep it cash. We basically funded out of our public equity. If we were in an extreme case where equities were selling off super hard or something like this, we might look at maybe we'll tap governments to fund it, depending on the size of the call, etc. That's managed by a separate team here. So I would have a I'd be able to comment on that. But we basically have a mechanism to fund it out of our if it's a private credit fund, it would come out of the liquid side of the credit portfolio. If it's a private equity fund, it would come out of the liquid side of the equity portfolio. Right now, we have this transformation in venture capital called the tail of two cities where Mark Andreessen jumps on a Zoom call, one call raises 15 billion. And you have by some accounts, 75, maybe even more emerging managers that are on their last fund. What do you see as the future of venture capital? Do you see this consolidation? Or do you see a reversion to the mean after kind of some of these emerging managers leave the market? Short answers, I don't know. But if I were to guess, I think I'd note a couple of things. You know, there was a big rise in small seed stage VCs between I don't know 2014, 15 up until I think 2021 or 2022. I think some of those managers will survive and have done well, I think many probably won't raise another fund. But I also feel like there's there is definitely a bifurcation going on. You have small funds, which I would actually categorize between let's say, 75 million up to maybe 500 million. And then you have the kind of giant multi stage groups. I think it makes sense to hold both or at least have both in your portfolio. I'd say that from kind of a career preservation perspective. But I also find it hard to believe that a multi billion dollar venture fund, or call it whatever you want, multi billion dollar fund can have historically venture like returns, let's say three x net or higher for x five x net. It's just a burden of a scale of large numbers, turning 10 billion into 40 billion is is a big lift. Those funds, I think frequently are not concentrated. If you have 100 investments like that, you better get a lot of those right if you're going to achieve a forex return on a $10 billion fund, where a $100 million fund, it's a lot, I don't say easier, but it's a lot more feasible to achieve a high venture like return. I could envelope math, if you have 100 investments of 100 million on average, you have a $10 billion fund in order for one investment to return the fund, you obviously need 100 x, but in order for it to return the fund three times, you need a 300 x and the problem is you're trying to deploy $100 million. So that's not a seed check. Although there are some seed companies, or some some so called seed seed around going on with with those kind of capital raises. When we started last year, there was a huge DPI crisis in the private markets. Has the DPI crisis been solved? Are we still in the midst of it? And if we're in the midst of it, what ending are we? That's a good question. I think it's in the process of being solved. Our portfolio, and I'm talking about private equity, so buyout growth and venture was very close to our model DPI last year. For the first time since 2021, it was well below our model in the years in between. But you know, we need the public market to be able to be continue to absorb IPOs. And last year was a much better year than it was. There's rumors of some really big IPOs coming here in the venture market soon. You know, apart from that, though, I think investors have to realize that companies, I'm sure many know this already, companies are staying private much, much longer. I think the number of public companies fallen by over 50% since maybe the late 90s or early 2000s. For a couple reasons, there's a very high cost to being public. I'm sure there's other reasons, you know, that the expectations of kind of revenue, you know, years ago, you could go public for a very low level of revenue. And now I think it's probably approaching 500 million or higher. So you have to be much bigger. So we don't have any expectation that venture is going to suddenly cash flow back much faster, etc. And in fact, our model, we've extended venture funds to 1515 years. And you know, in most of the limited partnership agreements, it's a, you know, three to five year investment period, a 10 year term, you know, extensions by the general partner. And I'm like, that's probably doesn't fit anymore, should probably be a 12 to 15 year term and extensions on top of that. I'd say that the some funds might extend out 20 years. Very curious, because you have a very unique vantage point in that you do both public and private equity, which includes venture capital. Second order effects if companies are staying private until they have 500 million in revenue. Is the 100 to 500 million dollar venture companies, are they not the small cap of the 2010s? In other words, is there not an argument that you should be invested more into the private markets in order to be truly diversified? There's certainly an argument for that. We used to, you know, model Russell 2000 small cap index as like a private equity index. But you may have to go back and think about that. And so far as companies are, you know, have to be or should be much larger now in order to IPO. The CIO of hurdle Callahan, which has 20 billion under management, he talked about, he explained why value stocks are doing poorly in the cap in the public markets, because value stocks are not your value stocks of before today, they're broken spec deals, their companies fallen angels companies that used to be mid and larger cap companies are now small. But the true kind of high octane value and also small stocks. Do you think about that as well on the public side? I guess we do. I was going to make a couple comments as a value for years. Anyway, it's come back a lot here recently. And it's had a couple of, you know, I think a decent run in 2022. And I was hopeful that once in 2022, when rates went up a lot, the big change was everyone was paying for growth, because interest rates are zero, the cost of money was zero. So you'd say, Hey, you know what, I'll just take growth, I'll get my dollar in the future, because the cost of money is low, or zero. Once rates went up, I thought, boy, this is gonna be really good for value. And because I want the dollar of earnings today, because I'm high interest rate. And that happened a little bit, and we're continuing to see it. But it's still not. I mean, obviously, like last year growth was growth that kind of finished up at its highs. And value investing, you know, was a great strategy. And it came about, you know, 50, 60, 70 years ago, Graham and Dodd, etc. Today, there's something like 7,000 books or more on Amazon and value investing. The cost of computing, obviously has dropped precipitously. I'm not talking about AI data centers, but just the cost of a PC, etc. And so everybody can run value pricing models at a quite cheap level. I think there's a Kotopia website where there's zillions of value models, etc. So everybody's focused on values, value, you know, I want to believe in it in terms of a theoretical like finance, I, it supports it. But I also think it's just a heavily crowded, heavily watched area. And so absent some type of catalyst in these stocks, I don't see what moves the needle given the immense amount of analysis in that space. What's something central to how you invest today, they've changed your mind on in the last couple years. Quantitative versus traditional fundamental stock picking in the public side. We looked at our portfolio, we have both types of managers in our portfolio. And by and large, over the last several years, the quants have done incredibly well, they do go through periods of de-grossing and de-risking, trying to think of the time periods of that maybe 2018, end of the year, etc. But in general, quant managers have been able to keep up in this market, which last year was a very narrow market. And but if you look at it from a fundamental perspective, let's say if you looked at Palantir, which was trading last year at one point at I don't know 100 or 200 times sales and even higher PE multiples. So any logical, rational, fundamental investor would look at that and say that stocks way overpriced. However, it continued to go up in price. And so a lot of fundamental managers underperformed last year, because they couldn't get their heads around a credibly, highly valued tech stock. Quants have somehow found, I think through their momentum models, an ability to keep up in that market. And you know, you can you can pitch the concept of like, hey, we'll keep up with the index in up markets, but we're really going to protect on the downside. And that's a great notion sounds great. I think you get buy in from investment committees on that. But that only lasts so long. And so far as they're going to want some excess returns, that's why we're here. And so I've really kind of started to think is, is doesn't make sense to hold any fundamental managers in the portfolio. There are some very good ones that have incredibly good excess returns. But I don't know if we have a lot longer data sets determine if that's a locker scale. And so what I do know is that many good quant managers have persistence in whatever sub asset class they're in, whether that's Russell 1000, or MSCI World, etc. And so I really think that, you know, well, well before I thought we needed a balance in fundamental versus quant, I don't know if we want to balance anymore. And that may not even be figuring in fees, if you're paying two and 20 to fundamental manager that's 600 basis points per year, that's, you have to be outperforming by at least 600 basis points because that's a fixed fee. And that's that's a high bar. Yeah, I totally agree. I've always looked at a fundamental manager, I'm sorry, any active manager. And if they're out performing on a five year basis by 1%, that can be wiped away in any one bad year. So you're right, you need a much larger margin for a to factor in the fees that are constantly headwind and be if they have lumpy performance, which many fundamental managers do, they need to be aware that there was a piece written 12, 13, 14 years ago that we actually replicated it was a Vanguard piece, you can find it online called the bumpy road to outperformance. And in that piece, they use just mutual funds. But the best managers the ones that performed, you know, over time, you needed sometimes to withstand a seven year underperformance period. The problem with seven year underperformance is that people in my seat are not going to go to the Investment Committee for seven years and defend the manager, they're going to fire them after maybe three. And that leads to that's a good career preservation move. It's a bad performance move according to this piece and we replicated it last year and found that that piece still holds. But it's just unsupportable if you want to keep your job. When I sat down with Cliff Hosnick, he's that same anecdote three years, one year, disappointment, two year benefit out three years, you're fired. Yeah, exactly. I brings up another guiding principle in mind, which is you can underperform a little bit for a while, but you can't blow up. And if you think about seven years of underperformance would be I put that in the blow up category, and that's a career end and potentially career end. You've had three decades of trial and error. What one time this piece of advice do you wish you could go back to a younger Chris and whisper in his ear in order to accelerate his career or help him avoid costly mistakes? Again, I'm getting this from another person who I highly respect the industry. But when I think about throughout the career, we're all going to make mistakes, we're all going to get things wrong. So what really matters is sizing the investment. If you get something wrong that's giant sized, it's a major problem. So the sizing of a trade or sizing of an investment matters much more than the actual outcome of the investment, because you're going to get things wrong, you're going to make mistakes. But if you're thoughtful about sizing any one mistake or even multiple mistakes is not going to create a major problem either in your career or in the portfolio. It's funny because I just watched an interview with Stanley drunken mill and he said the one thing he learned from Soros was that he was undersizing. Yes, I have great respect for him. And I think for a macro manager, especially successful ones, I totally agree with that concept. But I'm talking about managing institutional portfolio in an endowment or foundation. I'm not a macro manager. We're not a macro firm. And so I think that makes sense in that strategy. I don't think it makes sense in a portfolio that we're basically trying to make sure that we can ensure our grantmaking pay for the organization's costs and keep up with inflation. I think sizing is such an underrated aspect of investing. There's this whole concept in crypto, which is getting off zero. So many people will spend 10 years debating whether they should put all their money into Bitcoin or not or 20%, 30%. But there's a strong argument, at least in that asset class, but in any spiky asset, to just put a little bit to get access to that asynchronous return so that high upside without having to really put a lot of your portfolio risk. I know there's lots of differences. In some ways, I would think of it as like an allocation of gold. I think you shouldn't have some gold, but you shouldn't have 50% gold. You should have, I don't know, zero to 10, maybe zero to 5% gold. So I think it makes sense to hold, you know, alternative assets like that, but at the margin of the portfolio. Well, we can have a whole nother podcast on gold, but thanks so much for jumping on. It's been an absolute masterclass looking forward to doing this again soon. Great. Thanks. Thanks for asking me to join. 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