Transcript
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One of the interesting characteristics of the
venture asset class is this persistence of
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return.
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University of Chicago had the study that over
half of funds that were in the top 25% continue
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to be in the top 25%.
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Percent.
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Have you found that to be the case, and why is
that the case?
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Yeah.
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We we absolutely have.
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I I know I've I've seen similar research from
Tim Jenkinson at the University of Oxford.
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He said, I think he the data he was looking at
was Burgess data, and he was seeing a 45%
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chance of having successive top quartile funds.
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And interestingly, there was also a similar
chance of having consecutive 4th quartile funds
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as well.
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So it's not just at the top quartile where that
persistence plays out.
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It's also at the bottom quartile.
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And I think it's worth just mentioning that,
you know, when compared to private equity, that
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persistence of performance is much greater.
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So, David, you posted a really controversial
post on LinkedIn implying that smaller venture
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managers may not actually outperform larger
managers.
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Tell me a little bit about that.
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There definitely seems to be, a a common belief
that smaller funds and emerging managers will
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outperform, And it feels like that that meme is
being shared and repeated without too many
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people actually looking at the underlying data
to see if it's backed up.
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So, you know, one of the things we always try
and do at Venkat is is to go to the the primary
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data source, and see if if actually the
conclusions are justified from from the data.
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So this is data that we got from PitchBook.
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So they have data on about 14, 15,000 funds
that were raised between 20 10 and 2019.
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But there's only about a1000 of those that
where they have performance data.
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So, you know, first of all, you are working
with a sample that is incredibly small.
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And then if you look at at, you know, the
sample by fund size, for that smallest fund
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size group, the 0 to $99,000,000, there are
only about 5% of the funds that raised, where
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there's performance data.
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We're not saying that small funds don't, you
know, can't perform well or large funds perform
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better.
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What we're saying is that that you can't really
use the publicly available data to draw those
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sorts of conclusions.
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Because particularly in a power law asset class
where, you know, you do have a small number of
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funds that that, you know, massively
outperform, you know, you just don't know if
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those funds are being captured in the
performance data that comes out.
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And certainly when we look at our portfolio,
the vast majority of the funds that we back are
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not captured in the publicly available data,
that's that's on PitchBook.
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If you're thinking about basing your investment
strategy off the fact that, well, everybody
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knows small funds outperform, you gotta be
really careful about that because, you know, of
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our view is it's just not supported by the
underlying data.
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For those listening on audio only, we have a
graph on the screen based on pitch book data
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that shows that 0 to $99,000,000 funds, only
5.1% have actually shared the data, and then a
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100 to 250,000,000, 13.9, 250 to 523%, and 500
to a 1,000,000,000, 29.7%.
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So, essentially, half a 1000000000 to
$1,000,000,000 funds are 6 times more likely to
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have shared their data on PitchBook.
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Yeah.
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I I I think that's I think that's right.
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And you believe this show survivorship bias.
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What is survivorship bias?
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So survivorship bias is something that, you
know, that we have to contend within in the
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venture industry because, a lot of a lot of the
data sources, so PitchBook and and certainly
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Cambridge rely on the managers themselves self
reporting their performance data.
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And so what you tend to find is that if a
manager has a has a really unsuccessful fund or
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poor performing funds, then that data tends not
to get submitted.
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And certainly if managers, you know, maybe
raise 1 fund and then aren't able to raise any
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more, it's unlikely that they're gonna continue
to report their data into a Cambridge or a
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PitchBook.
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So what that ultimately does is overstate the
performance in a lot of these instances because
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you only have the successful managers that are
contributing their performance data into the
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into the dataset.
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So, yeah, the whole survivorship bias is a is a
real challenge.
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The the the one thing that I think the one
dataset that doesn't suffer from that is Carta,
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because they are able to report all of the
managers that raised funds using their
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platform, and so there's no survivorship bias
there.
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The the downside to the Carta data at the
minute is is that it only goes back 5 or 6
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years.
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But as that data matures, that could be a
really interesting source of of much more
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accurate truth about, you know, what what VC
performance looks like.
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Again, it's very much concentrated on smaller
funds so they don't have, any of the of the
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really established manager funds on there.
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But certainly for that emerging smaller fund
segment of the market, I think that's gonna be
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a much better indicator of how those funds are
actually performing in aggregate.
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To use an analogy, we all have that one friend
that goes to Vegas and always talks about how
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much money he wins.
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When in reality, he's only letting you know
maybe the 20% of times that he wins or he wins
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1 night and then he loses the next night, and
he only tells you about the wins.
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What are the consequences of potential
survivorship bias in small funds?
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I remember someone always once saying to me
that that the the plural of anecdote isn't
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data.
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And so, you know, you need to you you hear a
lot of anecdotes on, you know, I've heard
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people on on podcasts like yours, David, who
will say that, you know, I invested in a fund
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that did 10 x and I invested in a fund that
did, you know, 20 x, and and and that's great,
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you know.
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It's great to have those funds in your
portfolio, But but but a single data point
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doesn't give you any real conclusions around
whether an investment strategy is successful.
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You know, you have to look at things over the
aggregates and you have to look at things not
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just at a particular point in time.
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But we would argue you have to look at it
across an entire cycle because there might be
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certain types of strategies that outperform
when the market's going up, but they might
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massively underperform as the market corrects.
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And and in a way, we're seeing that a little
bit at the minute.
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You have data from Venkat going back to 1985,
and you've seen many funds.
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Tell me about what you see in terms of the
returns of growth funds.
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And is there also extreme outcomes in growth
funds like we see in emerging managers?
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So I I posted something on on x, a week or so
ago, where we where we looked at the the power
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law concentration of of the growth funds that
we've invested in.
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So, you know, in terms of, you know, how do we
classify early versus growth?
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For us, you know, we don't really do pre seed.
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There are you know, we have a small number of
seed funds, and then the early so so so early
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would be categorized as those small number of
seed funds plus funds that are predominantly
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investing at around the sort of series a, and
and they'll do some b rounds into those.
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But if it's predominantly a rounds, we'll
classify them as early.
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And then growth would be anything that's from b
onwards.
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I would say the bulk of what we do would be
kind of early growth, so it would be sort of
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b's and c's.
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And, you know, we've we've talked about this
previously, about what the power law looks like
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for for early stage funds.
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You know, 60% of companies don't return
capital.
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Around 1% of companies are ultimately fund
returners.
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And it's those fund
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So 1%.
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So you invest in a 100 companies.
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1 of them will retire the return the entire
fund?
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Yeah.
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At least one time is the entire fund.
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Very often it's multiples of the fund.
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And so that, you know, that's that's the
typical power law dynamic for for an early
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stage fund.
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We thought it would look very different for
growth funds because of, again, because of the
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sense that, you know, growth funds are
investing later, they're taking less risk, and
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so it would have something that resembled much
more of a kind of private equity type return
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distribution where you got few companies that
ultimately lost money, few companies that that
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generated, you know, 10x or more, and and most
companies in that kind of fat middle at, you
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know, let's call it a sort of 2 to 5x.
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What was interesting when we ran the numbers,
it looked quite different to that.
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So even for the growth funds, they lost money
on more than 40% of deals.
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So 4 in 10 deals, they wouldn't get their
capital back, which, you know, was was quite
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surprising I think for us.
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But it's also indicative of just how much risk
is still involved in these companies even at
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the B, C or D round.
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You know, you're not going into companies that
that are definitely gonna make it.
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There's a high mortality rate even for those
types of businesses.
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And and the flip side of that was even more
interesting for us because when we looked at at
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10x, you know, companies that have generated a
10x, For for early stage funds, it's about 5 a
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half percent.
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For growth funds, it was just under that.
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You're still seeing that that real kind of
concentration of returns in a relatively small
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number of of companies at the growth fund.
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And then we looked at fund returners, and and
this was the thing where we really, really were
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shocked.
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So for early stage funds, we've said about 1%
of their investments ultimately, in in funds
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that we've backed.
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1% of their investments ultimately turn into
fund returners.
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For growth funds, that's currently running at
1.6%.
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So we're seeing a higher incidence of fund
returners for growth funds than we are for
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early stage funds.
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And and that was, you know, that was shocking.
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You mentioned that your highest performing fund
was actually a growth fund, not an early stage
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fund.
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Explain how that could be the case.
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Yeah.
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So so our best performing firms that we've
invested in in that 2010 to 2019 sample size
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was an $800,000,000 growth fund.
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And it was able to and it's generating a 13 and
a half x multiple.
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Now, again, I'm just throwing an anecdote out
here.
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That doesn't that doesn't mean that this
strategy works just because we've got one fund
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that's doing particularly well.
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But I think it's interesting because I think,
again, the general the general view is that,
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you know, you can't generate those sort of
multiples on anything but a small emerging
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manager fund.
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And that is just absolutely not the case.
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So this fund was able to do it because it it
was a relatively early investor, you know, a b
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round investor in one of the largest companies
that was founded in the last 15 years.
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The company is still private.
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It hasn't it hasn't, it hasn't had an exit
event, but but the manager has been able to
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take a little bit of money off the table on its
investment.
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But it's it's still holding, you know, many
multiples of the fund, in terms of the
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unrealized value there.
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Let's take a step back.
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You're chief investment officer of VendCap.
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Tell me about VenCap and what is the VenCap
strategy?
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Yeah.
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So so VenCap has been investing in venture
funds since the the the kind of mid to late 19
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eighties, and and that's all we do.
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So, you know, we're a 100% focused on venture
And over time, our strategy has evolved.
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So, you know, back in the day we were, you
know, similar to a lot of of other investors
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out there in in in that we had a, you know, a
diversified portfolio investing in 30, 40, 50
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different managers.
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And and what we found was that, you know, the
average the aggregate returns from from that
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strategy just didn't make sense.
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You know, we weren't getting the outperformance
that we wanted to see from the VC industry.
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But within that cohort of managers that we
backed, we found there was a relatively small
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number that were consistently able to to
outperform.
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And by outperform, it really means, you know,
hit that top quartile, you know, benchmark on a
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on a regular basis.
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And so we we we we spent a bit of time, you
know, trying to dig in and understand what was
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causing these managers to to outperform.
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And what we found was was, you you know, when
we looked at at funds that have generated a 3 x
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net return for us, at the early stage, 90% of
them had at least one company that returned the
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entire fund.
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And so, you know, we really then started to
focus on, okay, who are the managers that can,
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you know, back the very best companies and do
so in a way that allows them to generate fund
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returning outcomes from those investments.
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And what we found is there's a relatively small
number of managers that are that are able to do
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that consistently.
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So really, for the last 15 years or so, our
portfolio has been very concentrated into those
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managers.
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So, you know, 90% of the capital we've invested
over the last decade has gone to 12, 13
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managers, and and, you know, we don't add a new
manager very often because the the bar is is
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exceptionally high.
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Interestingly, we we added one earlier this
year.
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That was the first new manager we've added to
our core program in probably 5 or 6 years.
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One of the interesting characteristics of the
venture asset class is this persistence of
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return.
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University of Chicago had the study that over
half of funds that were in the top 25% continue
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to be in the top 25%.
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Have you found that to be the case, and why is
that the case?
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Yeah.
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We we absolutely have.
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I I know I've I've seen similar research from,
Tim Jenkinson at the the University of Oxford.
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He he said, I think he the data he was looking
at was Burgess data, and he was seeing a 45%
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chance of of having successive top quartile
funds.
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And interestingly, there was also a similar
chance of of of having consecutive 4th quartile
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funds as well.
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So it's not just at the top quartile where that
persistence plays out, it's it's also at the
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bottom quartile.
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And I think it's worth just just mentioning
that, you know, when compared to private
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equity, that persistence of performance is much
greater.
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So in private equity, it's about a 3rd, I
think, of of of funds that have you know, if a
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manager has a a top quartile fund, they'll go
on to have a successor top quartile fund.
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So, you know, venture is is very is very
different, to private equity in in in that
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respect.
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And I think, ultimately, it comes down to the
power law nature of the asset class.
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And and, you know, it was it was interesting.
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Yeah.
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I I was at Slush, you know, a week or 2 ago,
and and talking to a lot of of European
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managers, talking to a lot of of US managers
that were over.
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And and one of the US managers, you know, said
something that that that really resonated with
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me, and and it was almost a kind of light bulb
moment, which was the best founders can raise
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an infinite amount of capital from anybody they
like.
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So why are they gonna choose me?
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You know, first of all, to to sort of see the
deal and to to be in the network of those
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founders.
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So, you know, I think that's a that's a
prerequisite for for for doing that.
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But but why is it, you know, why is the world
class founder gonna choose you as an investor?
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I think, generally, it's because, you know,
they're looking at
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And what what are some good answers for that?
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Today's episode is brought to you by Reed
Smith.
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00:16:09,514 --> 00:16:14,475
The practice of law has the power to drive
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00:16:14,475 --> 00:16:16,095
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By seizing opportunities and overcoming
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00:16:25,230 --> 00:16:30,190
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00:16:31,070 --> 00:16:36,750
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client service that drives progress for your
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business.
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What's the what's the like, do I wanna work
with you for the next 10 to 15 years?
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That's that's one of them.
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So, you know, there there is a there is a
personality thing there that that's you know,
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if if you're an absolute dick, then people
aren't gonna want to work with you.
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So, I I think, you know, you have to have a
personality that that is is is supportive of
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founders and and and makes founders want to
spend time with you.
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I also think, you know, the as as a firm, you
have to be able to, in a way, kind of add value
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to those companies that you're backing.
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00:17:12,085 --> 00:17:13,605
And and and how do you do that?
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You know, one of the things we hear
consistently is the best firms are able to lend
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their brands to the companies that they back,
And and that brand allows those companies to
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raise capital, to hire employees, to bring in
customers.
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Not that the companies couldn't do that
themselves, but the addition of that brand, you
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know, it's a real it's really additive in their
ability to do that.
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00:17:39,335 --> 00:17:45,654
Just to play devil's advocate, you know,
there's been this persistence of returns for
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many decades, but there's also been this
discipline around venture fund size over many
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00:17:52,039 --> 00:17:52,539
decades.
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00:17:53,240 --> 00:17:58,839
First principles would say that as funds get
much larger, those returns are going to get
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smaller.
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00:17:59,480 --> 00:18:01,634
Why would that be the wrong way to think about
it?
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Yeah.
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I I think you have to look at the relationship
between fund size and exit size.
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So if fund sizes increased, disproportionately
to, exit sizes, then I would agree with you.
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I mentioned the the quarterly review we did.
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You know, just looking over the last, you know,
the last few months about, you know, some of
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the valuations that the best tech companies are
able to raise capital at today with a view
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that, you know, there's gonna be by the time
they ultimately exit, they could be worth, you
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know, multiples of that.
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I I think that's really tying into to our
perspective, which is that that the size of the
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best tech companies is only going to continue
to increase.
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00:18:43,930 --> 00:18:49,930
And so what you need to do is to compare the
size of funds today with where we think the the
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00:18:49,930 --> 00:18:54,670
value of the best companies is gonna be in 10
to 15 years time when they ultimately exit.
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00:18:55,049 --> 00:18:59,755
Is there a fund size where you basically say,
okay, guys, like, it's been a great
284
00:18:59,755 --> 00:19:04,255
relationship, but we can't back you in a 10,
$20,000,000,000 fund?
285
00:19:04,315 --> 00:19:09,434
I think what we're seeing is is from early
stage that that the largest early stage funds
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00:19:09,434 --> 00:19:16,380
we're seeing are probably these days, around a
$1,000,000,000, maybe a 1,000,000,000 5.
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00:19:17,000 --> 00:19:21,960
So what do you have to believe that for for
them to return a $1,000,000,000 on a single
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00:19:21,960 --> 00:19:22,460
investment?
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00:19:22,839 --> 00:19:25,740
You know, they need to own 10% of a
$10,000,000,000 company.
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00:19:25,964 --> 00:19:29,345
You know, do we think that manager is capable
of doing that?
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00:19:29,644 --> 00:19:33,505
Well, the first question we look at is how
often have they done that historically.
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00:19:34,444 --> 00:19:39,644
And and if they've done that multiple times
historically, then that gives us much greater
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00:19:39,644 --> 00:19:42,470
conviction on their ability to do it going
forward.
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00:19:43,009 --> 00:19:48,210
So I think it's not about it's not necessarily
about is there a fund size that that is too
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00:19:48,210 --> 00:19:48,710
big.
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00:19:48,930 --> 00:19:54,769
It's much more about what is the maximum fund
size that we can sensibly underwrite a fund
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00:19:54,769 --> 00:19:57,315
returner for this particular manager.
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00:19:57,694 --> 00:20:02,115
Tell me about the state of the venture market
post 2024 election.
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What changes, if any, have happened in the
space?
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00:20:06,095 --> 00:20:11,670
I think it's really interesting, you know, that
that people focus on on kind of short term
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events and and thinking what's changing here.
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00:20:14,529 --> 00:20:18,769
Like, nothing's changed in a way, you know, in
the in the long term.
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You know, for us, venture's about, you know,
can you get the best managers backing the best
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founders?
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00:20:23,890 --> 00:20:28,184
Like, that's what venture is all about, And
don't try and over complicate it.
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00:20:28,325 --> 00:20:34,025
And don't try and impose, you know, what might
happen over the next 4 years into, you know,
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how that affects your long term strategy.
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00:20:36,644 --> 00:20:41,350
Because I can guarantee you that Trump is not
gonna be president of the United States when
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00:20:41,350 --> 00:20:46,070
companies that are founded today ultimately
exit in 10 to 15 years' time.
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At least, I hope I can guarantee that.
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00:20:49,990 --> 00:20:55,285
But so so I think I think you can get as an LP,
you can get really sort of fixated on what's
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happening in the in in the near term and lose
sight of ultimately, like, how do you build a
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portfolio and a program that's gonna deliver
over the long term.
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And as I said, for us, it's about, like, just
find those managers that can consistently back
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00:21:11,029 --> 00:21:12,250
the very best founders.
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00:21:12,390 --> 00:21:18,230
Now having said that, clearly, we have seen we
have seen some changes in the in in the market
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sentiment since since Trump was elected.
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00:21:22,054 --> 00:21:25,835
You know, we do invest in a number of crypto
funds and blockchain focused funds.
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00:21:26,375 --> 00:21:33,015
You know, it feels as if there will be, a much
more sensible regulatory environment for those
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firms to operate in and for their portfolio
companies to operate in.
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00:21:38,429 --> 00:21:42,130
You know, Marc Andreessen was was very vocal on
Joe Rogan recently.
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00:21:42,190 --> 00:21:42,690
Yeah.
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00:21:43,230 --> 00:21:44,049
Great episode.
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00:21:44,429 --> 00:21:46,130
Something everybody should watch.
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Yeah.
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00:21:48,194 --> 00:21:48,515
Yeah.
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00:21:48,515 --> 00:21:49,714
It was it was brilliant.
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00:21:50,515 --> 00:21:54,835
And and, you know, for those that haven't seen
it yet and and haven't seen the the all the
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00:21:54,835 --> 00:22:00,369
conversations on x, you know, they were he was
he was highlighting, the fact that the
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00:22:00,369 --> 00:22:05,109
traditional banking system was effectively
debanking people that were in the crypto space.
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00:22:05,250 --> 00:22:10,130
And we've seen this firsthand as well, with,
you know, with our portfolio, how difficult
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00:22:10,130 --> 00:22:14,690
that it's been for for some of the the the
funds the crypto funds to open bank accounts
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00:22:14,690 --> 00:22:18,634
and what they have to go through, and some of
the things they've been talking about with
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00:22:18,634 --> 00:22:20,075
their portfolio companies.
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00:22:20,075 --> 00:22:25,674
So so this is real and it and it does feel like
that in that in that part of the market, you
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00:22:25,674 --> 00:22:29,375
know, that there there is gonna be a much more
sensible regulatory framework.
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00:22:29,569 --> 00:22:37,190
I think for tech more broadly, you know, it it
again, Marc Andreessen was talking about the,
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00:22:38,049 --> 00:22:43,490
the the the regulatory environment that a lot
of tech companies had to operate in, which was
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00:22:43,490 --> 00:22:46,985
stifling innovation and stifling the ability to
grow.
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00:22:47,684 --> 00:22:53,945
It does feel as if that handbrake will be
lifted, when when the Trump administration
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00:22:54,485 --> 00:22:55,305
comes in.
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00:22:56,085 --> 00:23:00,869
You know, I think what we don't know is is what
the sort of second and third order consequences
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00:23:00,930 --> 00:23:07,410
of a Trump presidency are going to look like
for the tech industry, particularly if he
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00:23:07,410 --> 00:23:13,894
becomes or if the US becomes, you know, more
protectionist, if tariffs come into play.
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00:23:14,914 --> 00:23:19,715
So I I think, you know, our sense generally is
we feel in the short term, it could actually be
346
00:23:19,715 --> 00:23:25,975
a positive for the tech industry, but we we are
kind of reserving our judgment on on ultimately
347
00:23:26,035 --> 00:23:33,029
what that will look like longer term until we
see, you know, exactly which bits of of of
348
00:23:33,029 --> 00:23:35,210
policy they end up implementing.
349
00:23:36,150 --> 00:23:41,625
I think there's a bit of a paradox when you
think about politics or trying to play macro
350
00:23:41,684 --> 00:23:43,144
investor from one perspective.
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00:23:43,525 --> 00:23:46,244
You wanna be long the asset class from another
perspective.
352
00:23:46,244 --> 00:23:51,465
You you wanna be smart in how you allocate your
investments.
353
00:23:52,220 --> 00:23:54,299
There's also I think it's true.
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00:23:54,299 --> 00:23:59,279
Obviously, we're gonna have a different
administration, 8, 12, 16 years.
355
00:23:59,820 --> 00:24:06,640
But there is there is this reflexive nature to
start ups where they become self fulfilling.
356
00:24:06,859 --> 00:24:12,275
If suddenly nobody is investing in crypto or
nobody is investing in new AI companies, it
357
00:24:12,275 --> 00:24:13,894
becomes a self fulfilling prophecy.
358
00:24:14,355 --> 00:24:20,194
So sometimes the prognostication on the future
could actually affect even seed companies
359
00:24:20,194 --> 00:24:20,579
today.
360
00:24:20,659 --> 00:24:25,140
I think you have to understand where you are in
the in the kind of food chain, though, is is is
361
00:24:25,140 --> 00:24:25,640
LPs.
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00:24:25,740 --> 00:24:30,039
You know, I I feel like an LP strategy is a
little bit like an oil tanker.
363
00:24:30,099 --> 00:24:34,519
You know, you can't be navigating what's
happening on a day to day basis.
364
00:24:34,734 --> 00:24:40,335
You know, you've gotta set a course, and and
take the volatility that's in invariably gonna
365
00:24:40,335 --> 00:24:45,075
come, as as as you kind of play out your your
investment strategy.
366
00:24:45,454 --> 00:24:51,519
And I think it's actually dangerous to try and
jump around too much, because, you know, again,
367
00:24:51,519 --> 00:24:56,000
our our sense is is that it's it's almost
impossible to to time the market.
368
00:24:56,000 --> 00:25:00,960
It's almost impossible to pick, you know,
individual verticals that are gonna generate
369
00:25:00,960 --> 00:25:05,565
those next, you know, the next set of of top 1%
companies for LPs.
370
00:25:06,265 --> 00:25:11,565
And and so, you know, we would much rather take
a view that we want to invest consistently.
371
00:25:12,105 --> 00:25:19,279
You know, we want to keep a a a a fairly
consistent annual investment pace, and we
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00:25:19,279 --> 00:25:24,319
really want to focus on, as I said, those
managers that are consistently able to back the
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00:25:24,319 --> 00:25:28,400
top 1% founders and and not try and not try and
overthink it.
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00:25:28,400 --> 00:25:32,640
We've seen some of the greatest companies of
all time started during recessions like
375
00:25:32,640 --> 00:25:33,779
Microsoft, Airbnb.
376
00:25:34,985 --> 00:25:40,265
What needs to happen for other LPs to become
excited about the venture asset class again?
377
00:25:40,265 --> 00:25:42,184
I'm a bit of a contrarian by nature.
378
00:25:42,184 --> 00:25:46,664
So so I get excited about the venture asset
class when everybody hates it, and everywhere
379
00:25:46,825 --> 00:25:48,525
and it's really hard to raise capital.
380
00:25:49,140 --> 00:25:51,559
You know, that's that's what gets me excited.
381
00:25:52,580 --> 00:25:57,059
You know, I think if you're talking about more
generalist investors, then, you know,
382
00:25:57,059 --> 00:26:02,455
historically, we clearly have seen a
relationship between, you know, performance,
383
00:26:02,595 --> 00:26:04,695
the exit market, and fundraising.
384
00:26:04,914 --> 00:26:09,955
So, you know, if you're asking what will it
take for, you know, more dollars to be, to come
385
00:26:09,955 --> 00:26:14,835
into the VC asset class, I think the answer
there is, you know, we need to see that exit
386
00:26:14,835 --> 00:26:16,055
market open up.
387
00:26:16,349 --> 00:26:21,549
And and again, you know, the the indicate the
early indications we've seen over the last few
388
00:26:21,549 --> 00:26:26,130
weeks are that, you know, companies are
starting to to have those discussions again,
389
00:26:26,829 --> 00:26:34,345
and and so I wouldn't be surprised if if we see
2025 as a much stronger year when it comes to
390
00:26:34,345 --> 00:26:39,865
to IPOs, and and then hopefully, we can get
some clarity on the on the m and a market as
391
00:26:39,865 --> 00:26:40,184
well.
392
00:26:40,345 --> 00:26:44,985
You know, clearly, we haven't seen much
happening in in that space over the last over
393
00:26:44,985 --> 00:26:46,184
the last couple of years.
394
00:26:46,184 --> 00:26:46,924
I'm curious.
395
00:26:47,440 --> 00:26:53,440
A lot of LPs are concerned that venture funds
are marking their positions higher than they're
396
00:26:53,440 --> 00:26:54,259
actually worth.
397
00:26:55,119 --> 00:27:01,914
Looking back at VenCap's data going back to the
eighties, have you found that TVPI or where a
398
00:27:01,914 --> 00:27:07,355
venture fund marks its book closely tracks DPI,
which is actual capital return back to
399
00:27:07,355 --> 00:27:07,855
investors?
400
00:27:08,714 --> 00:27:09,214
No.
401
00:27:10,315 --> 00:27:10,974
We haven't.
402
00:27:11,755 --> 00:27:12,794
So, again, we looked at
403
00:27:13,250 --> 00:27:15,109
So the skepticism is warranted.
404
00:27:16,450 --> 00:27:16,769
Yeah.
405
00:27:16,769 --> 00:27:23,410
But again, I I think so we looked at, you know,
we looked at the data to say that how does how
406
00:27:23,410 --> 00:27:30,295
do, you know, how does DPI or even TVPI in the
f five, how does that correlate to where a fund
407
00:27:30,295 --> 00:27:31,755
will ultimately end up?
408
00:27:32,214 --> 00:27:35,115
And the answer is it's not really a great
predictor.
409
00:27:36,054 --> 00:27:43,119
And and so, you know, the the early performance
of a fund to us is is kind of irrelevant, and
410
00:27:43,119 --> 00:27:48,480
and what we need to see is evidence of of one
of those 1 or more hopefully of of those
411
00:27:48,480 --> 00:27:51,460
potential top 1% companies in the portfolio.
412
00:27:51,919 --> 00:27:58,924
And I think that's a much stronger signal for
us than, you know, than than than, early
413
00:27:58,984 --> 00:28:03,705
liquidity or, you know, early write ups
because, you know, you have to understand where
414
00:28:03,705 --> 00:28:09,919
you are in the cycle because it was, you know,
we saw a lot of seed funds do exceptionally
415
00:28:09,980 --> 00:28:15,200
well, in terms of getting those unrealized
gains through 2019, 2021.
416
00:28:16,940 --> 00:28:22,754
And and interestingly, you know, we still see
indications that they are holding a lot of
417
00:28:22,754 --> 00:28:26,615
those companies at last round value, not at
what they would be worth today.
418
00:28:26,914 --> 00:28:32,514
You know, in contrast, when we look at our
established managers, they were probably pretty
419
00:28:32,514 --> 00:28:36,534
quick to write things down and and did so, you
know, reasonably aggressively.
420
00:28:37,299 --> 00:28:39,299
You know, it varies by manager to manager.
421
00:28:39,299 --> 00:28:44,099
You know, not everybody is is as conservative
as as perhaps we would like them to be or to do
422
00:28:44,099 --> 00:28:44,759
it as quickly.
423
00:28:45,779 --> 00:28:51,220
And and so, you know, what but what I would say
is it it feels as if we've gone through that
424
00:28:51,220 --> 00:28:59,044
wave, certainly with our managers now, and we
think that portfolios are possibly undervalued,
425
00:29:01,345 --> 00:29:03,105
on a on an aggregate basis.
426
00:29:03,105 --> 00:29:05,284
How do people follow you online?
427
00:29:06,849 --> 00:29:11,429
So I'm I'm on x, at at, Dave Clark, 85.
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00:29:12,369 --> 00:29:15,170
I'm also on LinkedIn as well.
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00:29:15,170 --> 00:29:18,049
So, it's a it's a mixture of of stuff.
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00:29:18,529 --> 00:29:21,009
Some things I'll post on x, some things I'll
post on LinkedIn.
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00:29:21,009 --> 00:29:23,644
It kind of a slightly different different
audience there.
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00:29:24,424 --> 00:29:28,684
So, yeah, feel free to feel free to to follow
me on on either of those.
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00:29:29,704 --> 00:29:35,625
You know, also, you know, Venkat, is is also
active on on LinkedIn so, you know, follow us
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00:29:35,625 --> 00:29:36,089
there.
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00:29:36,169 --> 00:29:43,049
You know, we we try and we try and post things
that are data driven because that's how we
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00:29:43,049 --> 00:29:45,369
think of the of the VC industry.
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00:29:45,369 --> 00:29:47,549
That's how we approach the VC industry.
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00:29:47,690 --> 00:29:53,684
I think there's a lot of a peep there's a lot
of people in in VC, that that, you know, tends
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00:29:53,684 --> 00:29:57,785
to have strong opinions, but those opinions
aren't necessarily backed by data.
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00:29:58,164 --> 00:30:00,325
So, you know, we we prefer to
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00:30:00,644 --> 00:30:02,664
Strong opinions loosely backed?
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00:30:04,644 --> 00:30:06,085
As opposed to weekly held.
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00:30:06,085 --> 00:30:06,569
Yeah.
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00:30:07,450 --> 00:30:07,950
Yeah.
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00:30:08,409 --> 00:30:08,809
Yeah.
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00:30:08,809 --> 00:30:15,369
So I think for us, you know, we we we like we
like to we like to to to have, a very strong
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00:30:15,369 --> 00:30:20,089
foundation of why we do things and and, you
know, we recognize the data is not perfect and
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00:30:20,089 --> 00:30:25,375
the data is backward looking, and and, you
know, there are reasons when, you know, we'll
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00:30:25,375 --> 00:30:28,734
go against the data if we think it's it's not
relevant moving forward.
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00:30:28,734 --> 00:30:35,214
But but I think understanding the data and and
and using it to to really push back on some of
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00:30:35,214 --> 00:30:40,710
the the kind of common myths that are out there
in the venture industry, I think, is is really
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00:30:40,710 --> 00:30:42,390
important for investors to do.
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00:30:42,390 --> 00:30:46,549
You know, one of the things we say internally
is is that, you know, when someone says, well,
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00:30:46,549 --> 00:30:50,884
it's common knowledge that this is the case in
venture, we say, well, common knowledge in
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00:30:50,884 --> 00:30:52,105
venture is usually wrong.
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00:30:52,884 --> 00:30:58,164
So, you know, don't just don't just take, these
assumptions at first hand.
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00:30:58,164 --> 00:31:03,304
You need you need to you need to go and really
examine the underlying data and understand
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00:31:03,365 --> 00:31:04,410
what's driving it.
459
00:31:04,570 --> 00:31:07,630
Well, David, it's been great to have you back
on the podcast.
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00:31:07,769 --> 00:31:10,890
I look forward to sitting down in New York or
London very soon.
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00:31:10,890 --> 00:31:11,210
Yeah.
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00:31:11,210 --> 00:31:11,690
Sounds good.
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00:31:11,690 --> 00:31:12,009
Brilliant.
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00:31:12,009 --> 00:31:12,809
Thanks so much, David.
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00:31:12,809 --> 00:31:13,289
That's been fun.
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00:31:13,289 --> 00:31:13,998
Thank you, David.
