E261: How Sovereign Wealth Funds Create Alpha w/Peter Madsen

Peter, before SITFO, you ran money in London and Vice Pension Plans. What drew you to building a sovereign wealth fund in Utah? Well, candidly,

the last

dying breaths, if you will, of the fund-to-fund industry were taking place. And we, although where I was working prior, Cube Capital, we had a strong track record, a strong team.

When I joined, we were managing about a billion across some direct funds and a fund-to-fund strategy.

But after about five years, we were still at about a billion. You know, money coming in, being raised as part of our expansion into North America and some other markets outside of just the UK.

But at that same,

there were a few closely linked investors that all decided they'd rather be in private markets than hedge funds. And so the partners decided to wind down.

And that gave me a nice long runway of where to spend my next half of my career, so to speak.

So I went to the headhunter person and I said, hey, I'd like to be CIO in like a mountain town or a beach town at a college university or foundation.

And she literally laughed in my face and said, you and everyone else.

And then just a month or maybe not even two months after, she reached back out and said, you know, you're not going to believe this, but Utah has the sovereign wealth fund.

And they're looking, you know, the money's old, as I like to say, but there was no office. So the effort was new in terms of professionalizing it.

And I would be the first hire if I were lucky enough to get it. And I had, while I was at RVK, I had, we had clients that were this very same type of interior structure.

And I worked really closely with the state of Oklahoma. You know, even worked lobbying to try and help them amend their constitution to help modernize that trust.

So I had a lot of experience with the potential and how it could grow or be structured, especially if it was going to be brand new.

And

sure enough,

it's 10 years later now, but it worked out that it was an entrepreneurial endeavor, though,

being part of the state of Utah, still quite entrepreneurial, still a huge challenge. At theCUBE, you seem to have a good fund in a bad market.
Now, on the other side, as a CIO,

how important is being in the right market for a fund manager? And how do you assess that as part of a fund manager's success?

I don't even know if I'd say it was a bad market so much as just people were deciding they were skilled enough to pick their own hedge funds.

But then, when they were picking their own hedge funds, they were kind of sorting by AUM or brand name and starting from the top.

And so if you had a small hedge fund or a fund of funds, you're neither. And so the, you know, the industry kind of went the way it did.

And now that we're here and we're, you know, we've developed our beliefs in advance of making investments. We iterate on our beliefs.
And one of our beliefs is that

the, I mean, I guess two of our beliefs come to mind, but one is that mean reversion is real.

It may not seem like it. and public equities, the U.S.
stock market, et cetera.

But especially active management, you know, it comes and and goes in waves for the most part, especially if it's meaningful in size, you know, very low, small numbers, very low vol, that might be persistent.

But everyone wants higher returns, tends to come with some vol, and it tends to come in waves.

And so you should be looking at or investigating either managers or markets that have been out of favor or are down and out.

And where do you sit on this active versus passive debate? And what are the variables that you're looking to ascertain the market, whether you should be more active or passive?

We have some passive that can be useful for

liquidity sleeve, but if you don't have a huge concern around tracking error and you are what I'd like to say is like you know people refer to the total portfolio approach or being outcome oriented and less benchmark driven.

You look at passive benchmarks, they're sort of a active decision in that you chose to participate in passive. They tend to be momentum in nature.

And each cycle, they tend to become more and more concentrated or less diversified.

And if the idea is that it's supposed to be mitigating risk, I think the only real risk it mitigates is maybe career risk or benchmark relative risk. And

but it, you know, on the other hand, it may give you back some bandwidth or spare you the headaches of active management.

We kind of took a middle ground approach where we do have some passive, but we have a lot of what we call rules-based strategies, especially in public equity.

And that, for example, what, what you know, you think of like value, momentum, quality, weight those a certain way, hold a certain number of names. You're getting broad market exposure.

You're getting a beta of one. You're screening out, you know, bad companies, including companies that aren't terribly expensive and have some momentum.

And that seems to me to be a low-cost, kind of reasonable approach to diversification.

That while it does include some tracking error or career risk, I think it's from a total portfolio perspective, it's a better trade-off.

And Fama French came up with this three-factor model.

Ken French was my professor in business school, which basically weighed at small and value stocks versus, I guess, the opposite is growth, large and growth stocks.

Do you have a philosophical stance on where the future of the public markets are? Some people say value is a thing of the past. What do you say?

I think value will make its way back. But I think it's, you know, it's something that isn't, you know, it is mean reverting.
It is cyclical.

We're in a really long kind of odd cycle, I think, in terms of the value versus growth.

What happened in the 90s, it was pretty long, but post-GFC with monetary policy, and then now with the AI and the excitement around AI, I think it's just extending that cycle.

Something I'm more convinced of is that the small cap premium, I think the market structure has changed. And I'm not sure the small caps of today are the same as the small caps.
of years past.

There's been a decent amount of ink spilt on this.

And I think that's one area where we've changed our minds on thinking that because small cap has been out of favor and because valuations have been more attractive, that that should be a long-term overweight.

So in small capital end, we're looking for things that can do that.

And that means concentrated

micro caps that you hope get taken out. Or, for example, we have biotech hedge fund exposure as part of our small cap exposure.

The CIO of Hurdle Callahan, Brad Conger, and he actually believes that small public companies are fundamentally different than they were a decade ago. What does that mean?

A lot of them are fallen angels. They were SPAC targets or direct listings that fell down, or they were public companies that are now small.

And then to the second point of that is there's some companies that should never be public companies, via SPACs or other metrics that constitute the rest of some of these small cap companies.

So it's not truly smaller companies. The true smaller versions of the large public companies are actually still private companies in their middle market or large buyouts.
I agree with that.

And another maybe way of saying the same thing is companies used to go public earlier, so they were small cap-ish when they went public on average, and they might have been great companies that grow over time.

And that's just not the case, as you highlighted.

There's just fewer of those strong companies with momentum going public at small size. They go public at massive scale.

And our focus in private markets is really, you know, along the same lines that maybe the small cap premium is actually in private equity and very small micro, lower middle market, and lower type names.

I was going to ask you that exact question, which is, if you believe this, how do you operationalize that strategy in the market?

You would essentially shift some of your allocation from publics into privates, into private equity.

Yep. We actually did that.

So earlier on, we were, I think one of the ways of thinking about asset allocation is I had the good fortune of hearing Harry Markowitz present at a really small conference when he was presenting on something about the 401k,

how to like optimally use your company stock in your 401k but he started out his presentation by saying i don't want any of you young whippersnappers here to ask me about mean variance optimization and why you know it's so naive or whatever he's like i did that 50 years ago it's all you guys are the ones who are supposed to be improving on it and he said in fact the best you know the the best diversifying portfolio or the best diversification is just to go 50 50 and that's the naive approach and it tends to be like from an academic perspective the best diversification, if you will.

And the, so we, you know, I thought about that. And then I read another author put together something kind of similar.
But and then you look at risk parity and what Bridgewater has done.

And it's kind of the same concept of, you know, the naive portfolio is to not, you know, be concentrated in one thing if diversification is the goal. So when we started our

asset allocation, we kind of started from an equal weight perspective.

And, you know, we used optimization techniques and made sure that we were being quite quantitative in the end to stress test our decisions.

But we started with what if we were equal weighted, what would our expected returns be?

And then what dials should we turn to get our expected return up based on the size of the portfolio, the size of our resources, the fact that we have money coming in from land-based revenues, you can call it mostly oil and gas and real estate development.

So we thought we put all that together and we were... we were more or less an equal weighted portfolio.
Like it was pretty close and it was a terrible experience for the first few years.

And as we kind of lived with that and tweaked with it and evolved, one of the decisions we made was to take down the small cap exposure and move it into private equity.

That's been about five years or so in the making.

And it finally was, and being newer, you know, we didn't have enough private equity to have a 20% target when you're, you know, just pacing in your first dollars. It's kind of ridiculous.

So it made sense as we evolved over time to pull down our small cap exposure and direct it towards private equity.

The truly diversified portfolio, to me, is a very interesting thought experiment, which is if you worship at this altar of diversification, this is your model portfolio.

You start with that and then you kind of tweak it from that. But you guys literally did that.
Yeah. Yeah.
That's how we started the conversation. Yeah.

And are you not just trying to, and why not just optimize on sharp ratio and come up with this super efficient portfolio that is optimized on this one variable of sharp ratio?

I like to

say things that are kind of controversial. Maybe I end up just putting my foot in my mouth most of the times when I do.

One of the things I like, one of the things I like to remark is that sharp ratio is a perverse indicator.

So I think if you're optimizing on sharp ratio, and you're assuming distributions are normal and you're assuming your inputs are more correct than they probably are.

And if there is any mean reversion, you're sort of top ticking

with your optimizing on sharp or targeting a high sharp investment based on historical experience.

So if you really look out ex-ante, and by the way, like what, you know, as being a consultant and having working on a lot of institutions and a lot of asset allocation exercises, it's really hard to take a lot of risk when you have

all the different asset classes available to us.

If you have some exposure to those and you're, you know, thinking about it pretty clearly, it's pretty hard to have a really terrible experience that you can't survive, even in 08 and 2022.

I mean, those were really dark and terrible periods.

I had clients that had a lot of problems to deal with, but in the end, it was fine no one missed a benefit payment no one had to go out of business it is fine to have a decent amount of volatility ex ante

and it is fine to optimize on the return and not the sharp ratio like if you need a higher return you're not going to have a great sharp ratio and that's so as part of your investment philosophy you avoid investing from buckets instead you focus on facts or factor exposure tell me about that and how do you do that from a bottoms up yeah so the we actually i like to sometimes refer to it as as purpose-driven investing so we do have um you know we do live in the kind of conventional world if you will with you know you never really we can't pick our trustees and just thinking through that and again having that experience of sitting across from all types of trustees over a decent number of years wanted to make sure that we were having good conversations with stakeholders as well so we do have categories and asset classes but they're pretty broad and vague.

And so, for example, we have growth and within growth, we have public and private equity. And for us, we're like, okay, that's the high-risk, high-return part of the portfolio.

So, for something to be in that portfolio, we don't really care what the structure is, what the vehicle is, what the liquidity is. It could be public, it could be private.

You know, obviously,

like a venture fund traditionally structured wouldn't go in public equity. Maybe a crossover hedge fund that has 25% private markets could be in.

on public equity, an evergreen private equity fund, we could put that in public equity or private equity.

But as we try and keep that generalness or that vagueness, that allows us to be really opportunistic or open-minded about how we invest and what we invest in.

And we have pretty healthy ranges and latitude that our trustees have afforded us.

But at the end of the day, we run a factor model that, and we try to have straightforward benchmarks that also represent a factor. So obviously you have Acqui for public equity.

For real assets, we use S ⁇ P Real Assets Index. For income, we use high yield one to three because we don't want duration in that portfolio.
We want credit risk.

And so as you're thinking about that and communicating that with stakeholders, that's pretty straightforward.

Then when we go behind the scenes, so to speak, we're looking at that benchmark, the set of factor exposures, and how we can add value from it.

And we either want to have intentional overweights across factors

that we think will be rewarded, or we want to neutralize the factor exposure. but have a high residual.
We're not necessarily trying to have our factors beyond the benchmark.

We just want to know that, for example, we have equity beta coming from high yield.

If you de-smooth and interpolate private market returns, you have equity beta risk coming from private debt, from private real estate.

You might have interest rate exposure coming from infrastructure, private real estate, et cetera.

So we just want to make sure that we have a holistic view of the portfolio, what risks we're bearing, and whether or not we want to bear them or whether or not we think they'll be rewarded. And that

sophisticated regression type analysis analysis with factors is cheaper and easier to do than implement than, say, a risk system that looks at all of your holdings and then tries to give you the sector weights, geographic weights, et cetera.

And even still, I'm like, I'm not sure how much my equity beta really actually is, just seeing

how much tech exposure I have when I also have data centers in real estate, for example. And are those correlated?

Well, the holdings-based analysis doesn't tell you that, but a factor-based analysis can.

And what tools are you using to break it down on a factor basis?

Originally we were using MPI, Markov Processes.

I can't remember if it's International Incorporated, but that's a great system,

very sophisticated, very robust. It's a little more technical for the average user.

And given that we're a smaller team and some turnover at the smaller, or I mean, at the younger level where you would want people running the systems.

We switched from that system to Venn, which is, you might be familiar. It's a software company started by Two Sigma, the hedge fund group.
And

they have a really robust suite of factors and a user-friendly interface based on the web. And it can connect with your custodian, for example.

And just an easier way when you have interns and people with a couple of years of experience kind of helping you with analysis.

Let's talk about your private book. You go pretty far down the risk curve on the venture side.
You like funds under $100 million. oftentimes super angels or funds one and funds two.

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We first started as we were first building out our portfolio. Like I said, we have these broader categories and we have private equity as one.

And then it's left to us to iterate on our allocation between, you know, buyout, growth equity, venture, et cetera.

And we put venture to the side initially at first. And we,

because the the conventional wisdom and experience I had working with larger institutions and being a consultant is that if you can't access the really well-known brand names, then you're probably not going to do well in venture.

And, you know, our trustees agreed with that kind of sentiment. And I met some local investors here who were seed stage investors, running smaller funds and

doing it in Utah. And they kind of made their case, had some data to back.
their story up.

And so we worked on our philosophy for venture and decided that we probably probably don't have the connections or the bandwidth or the time or energy to try and get ourselves into, say, you know, Sequoia or whatnot.

If they're actually going to be capacity constrained, then you would want that.

And if they're not going to be capacity constrained, they're going to raise many different funds and kind of push you or, you know, require you to invest across all the different strategies and not just be in the early stage funds.

That wasn't ideal either. But perhaps there are,

in our initial philosophy was early stage, meaning pre-seed, seed, maybe series A, and kind of off-the-run markets that might feed up into the food chain of venture or some of these other shops that need to write bigger checks.

And as we spent time on that philosophy,

we deviated from it a little bit.

In the heyday, we got nudged into some bigger funds that an opportunity funds and so forth. We call them stapling on.

But we really honed the philosophy after we worked with a group called Sendana, a fund of funds, and they run an environment. I call them two time dash.
Okay, yeah, so

you know the story. So we were drinking the Kool-Aid from Michael and his team.
And then we also ran across another

group of individuals that run a venture fund to fund called Pattern.

And you read some of their work, look at some of their data. Moonfire also has a great website with a lot of data.

And if you think about not just fund size, but also portfolio construction, and you think about relative ownership early on when valuations are arguably cheaper and you have the ability to size up your ownership early on and your check sizes are

smaller, the deal sizes are smaller at that stage of the market, then your ability to generate a 5X or higher mathematically should be easier.

Even if you have a $100 million fund, you kind of need five unicorns to get a 5X, right? And

are you reliably going to get five unicorns

each fund, each vintage?

It seems a lot easier the smaller the check size, the smaller the fund size, the smaller the deal size. It's similar for us in private equity.

So all things being equal, you'd love to access the Sequoias and the other capital constrained strategies, but knowing that you can't access those, instead of going to second or third tier brands in that same space, you decide to go down market where you could get similar returns, maybe with some more vol,

but you actually had a shot to get those kind of great venture returns that you could get in the name brands.

Yeah, I think I agree with that summarization or simplification. And another interesting thing to us is, you know, you wouldn't, you wouldn't think of it as,

we didn't think of it as a good way to invest, but if you're a solo GP and you have a small fund, you're really well networked, really well connected, you're able to add value one way or another to the ecosystem, people will invite you or allow you to write what's often called a collaborative check.

And those funds tend to do really well. And that, you know, so it's just us trying to make sure that when we're investing in venture, we're not just doing venture for diversification.

We're doing it for as large of outcomes as we can. Taking a step back, how did you go about educating yourself in the venture space? Is this through the Fund to Fund construct?

And what's some best practices for NLP that wants to educate themselves on a new space? Yeah, regrettably, we didn't start out with a Fund to Fund adventure. I think in hindsight, we're a small team.

We're trying to be clever and implement our ideas. And we work with a mid-sized consulting group.

And it's just really hard to try and build out a portfolio across all the potential opportunities for investing. And arguably, we should have started with,

well, I could speak to kind of the collaborative model we use now at maybe a later point in the conversation, but either a more collaborative model or just allocating to a fund to fund to make sure you're in the market, getting some decent exposure, getting your diversification from those

asset classes that are harder to implement. And then over time, building up your experience and capability.
I think that's how most people do it. That's how we should have done it.
We spent,

you know, it's kind of a funny story.

One of the fund of funds we did was China Venture in China. It's early stage, met all our

criteria, except we were like, you know, we'll never get to China in terms of being good at selecting venture managers.

So the fund of fund was a pretty kind of a no-brainer if you wanted China exposure anyway. And it was supported by our consultants.
So that was something we did 2017-ish or, you know, plus or minus.

And at that conference, I met someone who I was describing, you know, this conversation we're having. And he said, oh, you need to meet this guy, Michael Kim.
And I couldn't find it.

I spent a decent amount of effort trying to get in touch with Sandana and it wasn't until a few years later that we actually synced up and ended up partnering with them.

But the amount, the the venture community, the GPs there, the fund of funds, and some of the advisors, there's a lot of data that they're working with it seems you know maybe it's just you know my you know a familiarity or recency bias but it seems like since sandana has grown in size and the garnered attention there's been a lot more thoughtfulness around fund size portfolio construction

and now when i'm on linkedin i often see a lot of data driven analyses around these topics and they don't always all point to the same thing but just back to the the actual question of how do you educate yourself i think there's a ton of stuff online that's data-oriented in nature that makes, you know, that lays all of that out for you.

The manager selection part really difficult.

Like I said, we ended up partnering with a couple of funded funds as scout funds or sourcing partnerships, if you will, just because of the sheer volume and difficulty and taking care of the portfolio while also trying to find.

you know, 50, 75 million dollar funds, you know, run by a single person or a couple of people. Tell me about this collaborative model that you alluded to.

So working with consultants is having been one, I think it's okay for me to say, and we still work with consultants. We appreciate the value they bring.
They're an extension of staff.

They have a lot more resources than we do.

But they need to, their business model is such that they need to serve the, I don't know if you'd call it the largest common denominator, but it is kind of a business of solving for a lot of clients.

And if you're. If you have a custom approach or a niche approach or a niche interest, that's a one-off for them.
It's, you know, it takes away from their bottom line.

And when you're working in a more collaborative model where

consultants would collaborate on the sense that you're sharing ideas and you're asking for services or getting some stuff off the shelf provided.

But if you enter into more of a commercial relationship where, for example,

we're anchoring some evergreen funds and with some advisory type firms, and we're receiving in exchange either revenue share, discounted fees, or advisory services, or database access, or other software, one or more of those in each case.

And now we have this commercial kind of relationship where

we are in business together, so to speak. And when we want

access to XYZ researcher database,

if that work is done

by them, then we can roll that off the shelf and we don't need to roll up our sleeves and do as much due diligence or underwriting because those very capable people with a lot more resources than we have and in some cases a lot more experience have done that underwriting.

So that frees us up on what you might call more conventional type exposures.

And then we also have the ability to bring either bring to them what you might call like satellite or niche type fund or strategy.

And they're, you know, they're obligated to work with you in some capacity, depending on the nature of your collaboration, commercial collaboration.

And we, or we just have that extra bandwidth to work on that ourselves and on those kind of satellite exposures, if you will.

And in addition to that, we're able to, in certain areas where we think the upside is more limited, like private, we call it private income, call it private debt, private real assets, which includes real estate infrastructure, all kinds of natural resources, maybe some other things.

You'd be really hard pressed to get... like a 2x net or 3x net from those strategies right there.

Odds are really good that if that your downside is really well protected, but your upside is pretty capped.

And I think that's like the diversifying benefit there's partially that those types of strategies bring.

But in order to really drive returns there, we looked at the structuring and fees on committed or how long it takes to deploy or both.

And we've, as part of our collaboration, we're able to structure co-invest accounts that are

with minimal expenses. So we're, you know, we're not paying management fees, we're not paying carry, we're not, you know, when the cap, we're not committing capital, paying fees on committed capital.

And so that kind of call it like structure alpha, if you will, from the nature of those relationships and how those deals are packaged, we have that uplift of being, you know, we're going to pretty easily get median gross returns, if not better.

But then we're adding back all of those fees, that fee drag over time.

And that allows us, again, more bandwidth for putting private markets money to work or hedge fund exposure to work where we can really focus on making sure we're picking the right strategy or the right manager that might be a little more difficult to require a little more heavy lifting.

Professor Steve Kaplan, who was on a podcast a few months ago, he came up with this Kaplan-Shore index and he figured out that 2 and 20 on a per year IR basis was actually six percentage points.

So to your point, if you have half of your funds in a 2 and 20, half in a co-invest was 0 and 0, you're actually getting 3% alpha across the entire portfolio.

It was pretty significant alpha when it comes to co-invests. 100% agree.
You're also using AI tools to screen decks. What are these AI tools and how are you using them strategically?

We tried to be early adopters of AI when ChatGPT first came out, but then we realized the confidentiality concerns and we weren't really able to put manager material in there.

You could obviously have it proofread a memo that doesn't contain any confidential information or all the other things we might use gpt for

but we really thought we were going to be able to you know adopt it early on we had a working group we called skynet but each time we met we were like i like we're kind of locked out because the you know because of our confidentiality provisions that we agreed to with managers and uh put it to the side and then we finally you know got our hands around the corporate for lack of a better term that you know subscription chat gpt

And then we were like, you know, individually using it with, you know, everyone's working on their own different prompts and with more or less success and and you know it's actually a lot of work to get you know those prompts right and to get get it where you need it to be and meanwhile we were working with and looking at uh software providers you know there were quite a few out there but the we spent about a year looking at names because each time we looked at a new name things were moving forward things were evolving And each time we had a question or like, well, we're looking for a CRM solution as well.

They'd say, oh, give us a month and we'll have that programmed in and we'll we'll talk again and sure enough you know people are coming back and so it took us a while we were pretty patient and then more recently you know we've we've adopted a group or you know we've subscribers signed on um implementing it and the idea is i think you know maybe to state the obvious that it does not make investment decisions for us doesn't make any decisions for us and not yet

and not yet um yeah it used to say the uh the interns were cheap ai now the interns are expensive ai but um you know that kind of level of work that you might have an intern or an administrative person do.

You have to gather the data, then you winnow it down somehow with criteria, then you collate the rest of it to make sure that you've got all the pieces you need to underwrite in one place.

And you do your best to score it. And maybe it's after lunch, or maybe you didn't have a good night's sleep, or you're mad because you didn't source the deal.
And now you got to work on it anyway.

And all these things, you're like, oh, that's a low score.

And we've always tried to have objective metrics to look at and point to when we you know in our templates that we're underwriting and it's just really hard to be objective and score certain things but now we can say you know take the first path like get all the data put it all in one place Make sure you're giving us the good and the bad.

So you don't just say like which man, you know, being simplistic, the prompt should be pretty specific on please don't give me an answer to a decision, but please highlight what the ownership structure looks looks like, what percent of this firm is employee-owned, and how is it distributed amongst the team.

And if it's greater than X or smaller than X or whatever, then that gets a certain score.

And when you point the system at a, it's, you know, say a folder or data lake with all your stuff in there, your meeting notes, your manager notes.

all the man of the collateral paraphernalia, all that stuff that comes along with doing the due diligence and investigating managers, you can take your criteria your philosophy your criteria and your own framework and your own template and have it be you know delivered to you as you want to know ownership here it is you want to know fees here it is you want to know what terms are in the lpa that you said are red flags here they are you can do that more or less um you know you can do a lot of the due diligence kind of data gathering and assessment really early up front if you have all the materials, including legal due diligence, operational due diligence, before really spending the time to do the softer work around culture and, you know, how do they generate, like, do I buy this philosophy?

Is this philosophy going to persist?

And it's just such a time, you know, it's a, it's a, it's leverage for the team.

We are, it affords us time to think and discuss and actually have everyone read the memos before a team meeting versus, you know, you're trying to write your own memos, let alone read everyone else's.

And, you know, a good example is, you know, someone has to go through the LPA or something to look up exactly what the fees and operating expenses are when it really should just be in a table somewhere.

It's pretty exciting. It's pretty early days.
So we'll, you know, we have no real kind of success stories yet other than people are pretty excited about the leverage that's affording us.

What practically is different about investing out of a sovereign wealth fund versus, say, a pension fund or an endowment?

Each entity is going to be different, right, in terms of at least marginally different. But for us, we're permanent capital or perpetual capital.
And

all sovereign wealth funds are, but our beneficiaries, like a lot of other Western states or 22 Western states that have had or still have sovereign wealth funds, and the beneficiaries are K through 12, public schools.

And in our case, that check goes directly to those schools. And so that's one aspect is thinking about the distribution and thinking about it all the way.
to the end beneficiary.

And then the other part of the ledger is the capital coming in from land revenues.

So we have to monitor or try and forecast or manage those income and cash flows and then think about making sure those distributions are not disrupted.

Well, Peter, this has been an absolute masterclass in how to invest like a sovereign wealth fund. Thanks so much for jumping on the podcast and looking forward to continuing this conversation live.

I appreciate it. Thanks for the invitation.
Good conversation.

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