August 15, 2025 • 46 mins
Daniel Rasmussen, founder of Verdad Advisers and author of The Humble Investor: How to Find a Winning Edge in a Surprising World, joins Merryn.
They discuss his book, why all forecasts are wrong (and why we need them anyway), the case for selling US tech and buying small caps, whether we’re in an artificial intelligence bubble, and Japanese equities.
This is a replay of a conversation taped in January this year.
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Episode Transcript
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Speaker 1 (00:00):
Bloomberg Audio Studios, podcasts, radio news.
Speaker 2 (00:08):
Hello Maren Talks Money listeners. Before we come back with
our new shows next week, wanted to republish another of
my favorite episodes from the year. It's a conversation with
Daniel Ramerson, founder of Verdad Advisors and author of The
Humble Investor, How to Find a Winning Edge in a
Surprising World. We talk about the book, where he thinks
all forecasts are wrong, and his take on us TECHTOCS
(00:28):
and artificial intelligence. Enjoy Welcome to Meren Talks Money, the
podcast in which people who know the markets explain the markets.
I'm Meren Sunset Work. This week I'm speaking with Dan Rasmussen,
(00:48):
founder of the investment management firm Verder Advisors. Before starting Verda,
Dan worked at Baine Capital, Private Equity and Bridgewater Associates.
And he's got a book coming out which I have
read already, called The Humble Up, How to Find a
Winning Edge and a Surprising World. It's available for pre
order now and out in bookstores in early February. I
strongly recommend that you order it. The underlying theme, as
(01:10):
Dan puts it, is the future is hard to protect
vctually impossible to predict so don't assume you really know anything.
The best approach is a humble one. The best investment
opportunities come to you when you can see other people's arrogance,
identify where they are too confident, be they too optimistic
or too pessimistic. We're going to get into all that,
plus his thoughts on investing during stock market bubbles are
(01:32):
we in one now by the way, European and UK equities,
Japanese equities, and what he is most bullish on. Dan,
Welcome to Marin Talk's Money.
Speaker 1 (01:41):
Thanks for having me.
Speaker 2 (01:42):
It's a pleasure now. I am excited to have been
one of the first outsiders to have read your book.
I finished it this morning and it is excellent, And
as I said to you before we started talking, it
fits with so many of my biases that I particularly
enjoyed it. Every page and affirmation of thoughts I have already.
Speaker 1 (01:58):
Nothing works passes, Oh.
Speaker 2 (02:01):
God, absolutely absolutely. We'd be having a different conversation if
I'd gone through the book going no, that's not what
I think already. Don't try and persuade me about things
like that. Now. I wanted to start. I see at
the very beginning of the book, what you talk about first,
which is this idea? And it's particularly important this time
of year, by the way, when we are overwhelmed, not
(02:21):
me by forecasts from everybody in the market about what
they think is going to happen in the coming year.
And we know, we know you, and I am pretty
much everyone else in the market from my years of experience,
that every single one of those forecast is wrong, well
not all of them, they'll be one in the middle
by happen chance that is correct. So I wanted to
start by talking about that forecasts, you say, fore costs
(02:43):
meet reality.
Speaker 1 (02:45):
It's probably the single idea that most changed my career,
which was, you know, I started out in investing, like
many of us, do you know, building these discounted cash
flow models, the LBO models that forecast revenue and profits
years into the future. And there was so much emphasis
put in on getting these Excel models right right, or
you know whatever right, meant that I never stopped to ask,
(03:07):
how good are we predicting what's going to happen three
or four years from now and the side and I didn't.
I didn't start out and I didn't study finance or
accounting or economics, and undergrad and so when I started
work in investing, I talked to my sister and a
few other folks who are in the business, and they said, well,
wanted to go read as much as you can, And
so I started reading all these books about theory and
(03:30):
academic research and investing. And one of the ideas that
I came upon was phil Tetlock's work on forecasting, and
Tetlock finds that experts in their fields are no better
than non experts at forecasting things, even in fields in
much they're experts, and the only difference is that they're
more arrogant about it. And I said, you know, gee,
I wonder if our growth forecasts are are right? You know,
(03:50):
how would I sort of figure this out? And I've
done a variety of studies since having that original question,
and the answer that I've come to is that our
forecasts are really bad. At we really don't know much
about the future, and the farther into the future we
try to peer, the worse we get. In fact, Andre
Schlipher at Harvard has done this wonderful study where he
shows that long term growth forecasts are actually a perfectly
(04:13):
negatively correlated with stock market returns. In other words, the
more optimistic you are about long term growth, it's actually
a totally contrarian signal. Now short term growth, you know,
next year, for example, there's a little bit more accuracy.
People have some good, decent chunk of ability to forecast. Okay,
when we're talking about revenue or EBIT das for example,
(04:34):
or profits, you know what's going to happen in twenty
twenty five. The problem is that it doesn't actually help you.
So I just finished this wonderful study where in Japan
almost all companies are required to issue one year forward
guidance on revenue and net income, and so you can
take you know, I took twenty years of this data
and said, you know, how accurate are they? And then
what does it mean for the stock prices? And what
(04:55):
I found is that if you divide it into slow, medium,
and high growth on a one year forward basis, Japanese
companies are about fifty percent accurate. So thirty percent would
be pure chance, you know, one hundred percent would be
totally accurate, fifty right, the other That sounds good, It
sounds okay, right. But the challenge then is if you say, okay, well,
(05:17):
let's say you're forecasting really high. You know, you then think, oh,
I should buy all the companies that are forecasting really
high growth because you know, if they achieve that growth,
it's going to be great. Well, it turns out that
the companies that achieve high growth have sort of average returns. Right.
They forecast high growth and they achieve high growth, and
they have average returns because that high growth was priced
in with the time the guidance was issued. But the
(05:38):
fifty percent of the time those companies that forecast high
growth don't have high growth, their stocks collapse and so
you end up doing worse in the companies that forecast
high growth or about you know, average and total, but
a little bit worse. Whereas if you go to the
companies that are forecasting low growth, yeah, fifty percent of
the time they hit low growth, right, But then when
they do, the stock returns out average, they re turned
(06:00):
the same as the high growth firms that achieved high growth.
But when the slow growth firms achieved high growth, which
they did fifty percent of the time, their stocks do
really well.
Speaker 2 (06:09):
Okay, So knowing the growth thumbs in advance doesn't help
you any even if you did. And is it also
true to say that over those very short periods, so
over a year or so. What we're not necessarily saying
is that anyone is particularly good at forecasting anything out
over a year. What we're saying is that people are
jolly good at extrapolating the future, the short term future,
from the past, and unless something goes wrong, it's quite
(06:31):
likely that the next year will be similar to the
previous year exactly.
Speaker 1 (06:35):
And this is where things get that quite interesting, because
I think you're exactly right, Marion, that the way people
form their forecasts is they look at the recent past
and they extrapolate that forward. That's the most common forecasting
method in markets, which is why you see all the
S and P five hundred forecasts for next year cluster
around exactly what the S and P five hundred day
(06:56):
last year. And there's a wonderful study that I updated
have done, you know, through for the last twenty years
of data, where I look at the level and persistence
of growth rates, and so you basically say, okay, let's
look at every you know, every company's trailing growth over
you know, let's say a one year, three year, five
year period. Does that forecast their growth rate over the
(07:18):
next one, three or five years, and what you find
is that revenue on a one year basis is a
little bit forecastable, and then everything else is total chance.
It's just pure coin flips. There's no relationship between past
and future growth. And that's probably the single hardest thing
for people to understand because it's just so against our views,
(07:40):
right because if you said, well, gee, Microsoft and I
don't know the gap, or some apparel retailer I'm trying
to think of something very boring have an equal chance
of having high growth over the next five years, you'd say,
come on, that's absolutely notty. There's no way that that's true.
But statistically it is true. And I think that when
you start to understand that, and you can buying that
(08:00):
with the insight about what's priced in and what's not,
you start to see how the importance of understanding the
structure of forecasts is to being a good investor, because
I like to say that investing is not a game
of analysis, it's a game of meta analysis. It doesn't
matter what you think, it matters what you think relative
to what the market thinks, and so you need to
(08:21):
understand what other people are forecasting, knowing that everyone else
is forecasting, and then you have to think, well, what
if they're wrong? You know, how would I make money
if they're wrong? And that I think is my sort
of key to unlocking or starting to think about what
should work as an investing strategy based on behavioral economics.
Speaker 2 (08:39):
Yeah, I mean it's not just we'll come back to that.
I've wanted to talk about an anecdote that you had
in the beginning of the book about the weather and
because one of the things that we often talk about
is why don't we bother with these forecasts? I mean
this not just at the company level, but at the
inflation level, GDP level, interest rates, etc. They're always wrong,
and we have these GDP full costs come out over
(09:00):
and over from all our governments selling us GDP is
going to be whatever it is with a couple of
decimal points off to it. And we look at him
like that it's a nonsense. We know it's nonsense. Why
do we listen? So tell us this lovely little weather
anecdote from from the book which explains it.
Speaker 1 (09:14):
Yeah. So this is ken Aarr, the famous economist, was
in the weather core in World War two, uh and
being the genius that he was he's and by the way,
that the Weather Core asked for one year forward weather forecasts, uh,
and so so they could plan troop movements and things
like that, you know, when of the road's going to
be too muddy, when they're once they're going to be
(09:34):
snow by day. And so he was tasked with creating
these and and you know, he did a little bit
of research and he found, you know, these these forecasts
are completely wrong. They're completely useless, and so we just
stopped doing them. And I'll just send you the historic
average table and just use that. And he sends a
note to the General and and and and saying, you
know that the laying out his argument, and he gets
(09:55):
a one sentence one back, and it says, you know,
the General knows that the forecasts are useless, but he
needs them for planning purposes.
Speaker 2 (10:04):
And that that's exactly it isn't it. We need something
to anchor what we're doing around even if we know
it's wrong. We need the anchor.
Speaker 1 (10:13):
We need some way to plan. And even if we're
not doing it consciously, we're often doing it subconsciously. And
so you need some alternative way of thinking. And I
think you know a lot of the research on forecasting
suggests that the best way to make forecast is to
use base rates. Right, So you take a long historical
time and you sort of say, what's the average over
(10:35):
this long period of time, and that's generally the best
you're going to get. And so I think that in
my mind, the game of investing, the way to make
good investment decisions is, on the one hand, to take
those base rates, to study history to understand what the
context is over a long period, not one year, not
three years, but what's a ten twenty year context, and
what's the sort of distribution of potential outcomes, And then
(10:58):
to secondarily to say, because we know everyone else's planning,
we know everyone else's forecasting, where are they concentrating their
excessive optimism and their excessive pessimism, And those are the
places where we're likely to be able to find an
arbitrage just betting that nobody knows, right, Like, nobody knows
is AI going to truly revolutionize the economy, or is
(11:20):
that one trillion these companies are spending going to be
a waste of money. Maybe no one knows, you know,
And if no one knows, you know, what's the bet
that we.
Speaker 2 (11:28):
Should make Yeah, if everyone else is betting that they will,
but we know that nobody knows, then we should bet
that they won't exactly. And that brings us to this
idea of investing being not a game of analysis, is
a game of meta analysis.
Speaker 1 (11:41):
That's right.
Speaker 2 (11:41):
It's all about the relativity, all right. So with that
in mind, that would make almost all the models that
we use at the moment irrelevant. I'm one of one
of the models that you talk about in the book,
the dividend discount model the Way of Investing, by saying,
you know, every company, every egguity is worth the value
of all the dividends it'll be paid to the owner
of that equity in the future. And people spend hours
(12:03):
on these models, don't they days days working out has
actually worked, But as they have absolutely no idea whatsoever
what those dividends are going to be, the final number
they come up with is nonsense.
Speaker 1 (12:14):
Call before you do the company. You know, you're the
world's leading expert on you. So just tell me what's
your year end bank balance going to be in twenty
thirty And by the way, what's your income pre and
post You know, your pre tax and post tax income
exactly for the next five years and just model that first.
And if you can't do that accurately, you know, why
do you think you can do it for Coca cola?
Speaker 2 (12:34):
Yeah right, Okay, interesting, So it's let's go move then
to what you think might work. So if none of
these models that most people use, that everyone who has
an MBA ETCA sits around making these breadsheets all day,
none of these work. What does? And the thing that
you say is that one thing that never changes and
(12:56):
you can extrapolate from is human psychology, which brings us
back to this idea of the meta analysis. And in
this section of the book, you use the analogy of
ships because you spent some time observing how shipping works. Right,
And this is one of my colleagues when I was
first starting as a broker, explained this to me in
terms of of chips, in terms of semiconductors, but you
(13:16):
do it much better with ships.
Speaker 1 (13:19):
Well, it's a wonderful paper by a consulting economist here
for dad Sam Hansen as oppressor at our business school.
Really brilliant guy, and I love the shipping industry. Actually
spent a summer in college working at a Greek shipping company,
and I find that endlessly fascinating of the personalities involved
and the dynamics and the way it interacts with global trade.
I mean, it's just so cool. But there's this fascinating
(13:41):
insight that these economists have by looking at shipping companies.
And what happens is that shipping rates are very variable, right,
so sometimes it's very expensive to ship rate. Sometimes it's
very cheap when rates are very high, and you plug
those rates into a model of whether you should invest
in a new ship or not. It turns out that
(14:02):
investing in a new ship looks really profitable whenever shipping
rates are high, and so people plug these into their model. Now,
the challenge is that it takes three or four years
to build a new ship, and so these Greek shipping
companies they see the high rates and then they go
and they order ships from these South Korean shipyards, and
then three or four years from now, the ships are delivered.
(14:24):
And what ends up happening And he calls this competition neglect,
which I think is such a wonderful and relevant term
to what's going on in AI. By the way, competition neglect,
they don't realize that all their other buddies also ordered
ships at the same time, because they all also did
the same math, and they plugged the same shipping rates
and the same cost to build a ship. And so
there's this lot of ships that then show up on
(14:46):
the market, all at the same time, three or four
ears down the road, and all of a sudden, shipping
prices crash because there are too many ships. And so
you see the competition neglect. The inability of these shipping
companies to anticipate that their competitors are doing the same
thing is what's exacerbating the cycles and driving shipping rates
(15:08):
too high and then too low, and then too high
and then too low, and then everyone seems to be
getting burned at the same time. And I think that
that's such a wonderful analogy to what's going on in markets.
Right you sort of say, wow, like AI is such
a great opportunity, I should buy into it. What if
somebody else figure this out before me, or what if
the fact that I thought it means that everyone else
(15:28):
is thinking at the same time.
Speaker 2 (15:29):
So do you think that there is overinvestment in AIO,
too many companies investing at the same time and the
same things, like the ships, Well, I think there has.
Speaker 1 (15:37):
To be, right. I mean, you just think about how
many of these AI companies there are. All of them
are trying to build pretty much the same thing as
far as I can tell. And I think there are
a few things that are are are clear, right, Like
we can study the history of the Internet, and one
of the things that we observed that tends to be
winner take all the best model tends to work. Google
(15:58):
wins search, Amazon winds retail, you know, Microsoft winds productivity.
So why should we think that AI will be twenty
percent chat GBT twenty percent, Gemini twenty percent, right, like
Claude twenty percent anthropic. It just is it's not plausible
based on the history of the of the of the
(16:18):
tech industry.
Speaker 2 (16:18):
And we can't choose them, and we can't choose the winner.
Speaker 1 (16:21):
And we can't pick the winners. So like, some of
these things are just incinerating capital, right, They've got to be,
Like probably probably all but one of them are incinerating capital.
We just don't know which of them is incinerating capital,
which of them are, and which of them aren't.
Speaker 2 (16:35):
And does that mean that as investors we should avoid
all of them?
Speaker 1 (16:38):
I think so. I think they're all terrifying that there's
too much hype, too much optimism. How long have we
thought that we would have robots that could think like us? Right? Like,
this isn't no idea. Humans of are perpetually attracted to
the idea of anthropic robots that can speak and think
like us. And every time we've tried to do it, it
has worked, and it's not going to work this time.
I don't think why do we think?
Speaker 2 (16:59):
Why do you think we're attracted to it? Is it
because we're lazy and we're just hoping to be able
to invent something that can do everything for us?
Speaker 1 (17:06):
Well, it's the It's the ultimate vanity to create something
in your own image, isn't it the closest complex?
Speaker 2 (17:15):
Okay? One of the tiny questions not that any.
Speaker 1 (17:18):
Of our friends in the tech industry.
Speaker 2 (17:19):
Of god Cox absolutely this idea about the measure analysis,
What does that lead us to? What does that tell
us about how we can actually invest? How can we
really do it? What works?
Speaker 1 (17:31):
Yeah? So I think that if we step aside and
we say, gee, you know, forecasting doesn't work and the
future is too unpredictable and actually markets are too volatile,
which is another thing. This is what Robert Schiller won
the Nobel Prize for us, this idea of excessive volatility,
which Schiller did so brilliantly. You know, if the dividend
discount model is right, and the net present values equal
(17:54):
to some of the future cash flows uh discount by
the interest rates, and if we know future cash flows
and we know future we can tell you what the
net present value of the stock market should have been
at any given time and how much it should have
moved as those things changed. And he finds that about
eighty plus percent of stock market volatility is inexplainable by
(18:14):
changes and fundamentals.
Speaker 2 (18:15):
Okay, so even if you had the information for the model,
it still wouldn't work exactly.
Speaker 1 (18:21):
Even with full pressions, you can't explain a very high
percentage of volatility. And so where is this excess volatility
coming from? And I love this theory by this Stanford
professor Mordecai Kurtz, and he comes up with this theory
that what's happening is that everybody's making forecasts and then
the future happens, and eighty percent of people realize they're wrong,
(18:43):
and so they sell and they buy something else, and
then they make new forecasts and then the same thing happens, right,
and it's that dynamic and he should use some fancy
match so that could explain it. All. Right, that's what's
going on. And I think what I sort of love
about that idea. And we're so focused on efficient market theory,
and efficient market theory is so many wonderful implications, right,
(19:05):
and it's so useful. But I think one challenge to
efficient markets theory is that it often gets interpreted as
the price is always right. But anybody who's actually invested
in markets at any point knows how frequently they make mistakes.
And not only how frequently they make mistakes, but how
frequently the market seems to make mistakes. Right. I mean,
how could a stock be down thirty percent in a
(19:27):
day if it wasn't a mistake yesterday? Right? I mean, like, yes,
the new news came out, but clearly the market didn't
get that right, otherwise the price wouldn't have moved as
much as it did. And I think trying to reintroduce
this idea of mistakes back into our vocabulary when we
talk about markets and make it more human. Right. Of course,
mistakes are an integral component of investing. How could they
(19:47):
not be How could anybody who's ever experienced markets not
know the mistakes are part of things? And how is
that therefore driving rebalancing decisions? And then how can we
as investors think through if other people are making mistakes,
if we're making mistakes, how should we build portfolios that
take into account the idea that we are going to
make mistakes and that everyone else is making mistakes too,
and that that's part of the dynamics of what's driving
(20:08):
market volatility.
Speaker 2 (20:10):
Okay, so what's the answer? How are we going to
build that portfolio?
Speaker 1 (20:13):
What we're looking for is some barometer of optimism or pessimism, right,
could if we could just have some barometer of how
optimistic or pessimistic the market was about an individual security
about the market as a whole, gee, then we'd be
in very good stead because we'd have a very good
way of saying, you know, here's the stuff that's too
extreme on one end or the other and going long
or short that it turns out, in fact that we
(20:33):
have a very simple metric for doing that. And in
the stock market, it's valuations. Right, you can pick almost
any multiple, right, revenue multiples or book multiple and you
can erase to hooks on a on a ranking system,
and you'll find that the ones that are the cheapest
end up doing the best and the ones that are
the most expensive end up doing the worst. And that
value reliably predicts stock returns. And in fact, over the
(20:57):
last few years it hasn't in the United States. We
should talk about why, but it has even internationally people
have declared the death of value investing. But value investing
are the idea of ranking stocks by their relative optimism
or pessimism and going along and things other people are
pessimistic about and short things they're optimistic about should work.
And I think you can also, and we should talk
(21:18):
about this separately, apply that to thinking about whole markets
and whole economies. But I think in the context of
single stocks, what we've seen over the last few years
has been some of the worst performance of value investing
over its history. The last time it did this badly
was in the late nineties during the tech bubble, and
so we have to reckon with that, right, So I
(21:38):
think it's all well and good for me to argue
that we should use valuation ratios as a metor optimism
or pessimism and that we should be long things other
people are pessimistic about. And there's an intuitive logic to that,
but there's also grappling with the fact that that hasn't
worked recently in the United States. Again, it has worked internationally,
it has worked in the US, and so why And
actually there was a period from COVID until the release
(22:01):
of chat GBT when it did work, and then chat
GBT just totally new to value investing again. And so
what I like to say about value investing what's going
on in the market today is that we've had a
period from in the twenty tens where there were a
very small number of companies where they were forecasts grow fast,
(22:22):
and then they grew faster than the forecast, and they
did that a few years in a row. That was
the sort of fan mag stocks, as they were called them.
What is that a tribunal too, I'd say it was
an innovation wave. And these innovation waves happen. They do.
They happen with the Internet, they happen with railroads, and
when they happen, they are these abnormal profit pools that
are earned by the innovators. Now that doesn't last that
(22:44):
long because at some point the customers need to benefit
more than the innovators, and at some point the innovation
get commoditized, and so these innovations don't last forever, but
in early windows they can be huge, huge booms. And
that's what we're in the middle.
Speaker 2 (22:57):
Of, in the middle of or towards the end of.
Speaker 1 (23:00):
It depends on the future of AI and everything hinges
on that. Ye. And again that's what you saw right,
like the sort of tech mania seemed to actually peak
in COVID right in twenty twenty one, and then with
the release of the vaccines, you had all that stuff
clearly coming off. It all gone too far. Zoom had
gone people were using Zoom too much, right, the people
were buying too much on Amazon. It was peak Internet.
(23:23):
And then it declined, and then it looked like we
were going to sort of return to a normal market
where value investing worked again. And then chat GPT was
released and it's just unleashed this total mania again and
it now feels like we're back at twenty twenty one peaks.
I mean, you know, you look at things like fart
coin and it's even worse than the SPACs, like at
(23:43):
least the SPACs or companies well the hell is fart coin,
and yet it's valued at most more than you know,
ninety percent of Japanese companies, for example. You have to
understand that, you know, markets are are reflective of human
history and human events, and it's not it's not a
line math problem. And we know that there are certain
things that we can rely on and should rely on,
(24:06):
which is betting against hubris right, betting on things others
are pessimistic about and being skeptical if things are too
optimistic about. But sometimes the optimists are right, and they
were right during the twenty tens. And the question is
now the only question that matters for markets right now?
In my mind, the most important question is are they
right about AI or not?
Speaker 2 (24:26):
I mean, the other thing you can say, surely is
that value investing doesn't work during a bubble.
Speaker 1 (24:29):
It doesn't work during a bubble.
Speaker 2 (24:31):
Answer, it doesn't work during a bubble, And so you
can then make the case. So you might have might
not want to make the case that the last few
years are being suggestive of a bubble in the US market,
And you look at the valuations, and these are bubble valuations.
So that could be the simplest way to look at it.
Speaker 1 (24:45):
I think so too. And I have this piece in
the book about the nineties because I spent a lot
of time thinking about bubbles. I went back and I
read a bunch of investor letters from the great investors,
Ray Dalio, Peter Lynn Choward, Mark Seth Clarman. You know
what were they saying in the nineties. And it was
really interesting because all these great investors knew it was
a bubble. They all wrote a boute about it. Ray
(25:09):
Dalio said, we're approaching a blowoff phase of the US
stock market. Peter Lynch said, not enough investors are worried.
The only problem is that those two quotes are from
nineteen ninety five, So you know, investors are often you know,
smart data driven people. You can pick up on these
things and say the evaluations are too high. The problem
(25:30):
is that smart investors tend to be way too early. Right.
The bubble didn't burst for five years, right, yeah, and
eked up on ear and each subsequent year it doesn't burst.
You look stupid, and the people that supported the bubble
look right. And I think that that's the type of
situation we're in now. And it actually turned out that
value investing, if you looked at it from ninety five
(25:50):
to ninety nine, it looked like the stupidest investment strategy
on the planet. So did international diversification. So right, but
if you just fast forward two or three years the
bubble or so quickly that value investing, international diversefication, all
these things came out ahead with only one or two
years after the bubble. And so I think that having patients,
and I think understanding that there's historical context, being patient,
(26:13):
but being guided by a sensitivity towards these behavioral insights
that it doesn't you know, don't overthink it. You don't
have to in some ways, you don't have to have
the ends. I don't need the answer to any I.
I don't need to know that extended will succeed. All
I need to know is are people too optimistic about
it or not? And what it would be the signs
of that excessive optimism. And if people are excessively optimistic,
(26:35):
you know what should I do? I should stay away.
Speaker 2 (26:38):
And so there is this sense from you anyway that
investors in general overinvested in the US, underinvested outside the US,
overinvested in AI, and underinvested.
Speaker 1 (26:47):
In value absolutely, And I think one interesting sort of
dynamic that's been going on, right is the rise of
passive investing, which is a wonderful thing. Right. There are
many reasons why passive is a wonderful, wonderful thing for investors. Right,
It's been great for consumers. I love passive investing. I
love Vanguard. The only problem I see, and maybe there
(27:10):
are others that other people can talk about, the real
problem I see with passive investing is that when people
go passive, they don't say, I'm going to put my
money in the S and P four hundred mid Cap
Europe Index if such a thing exists. They think, I'm
gonna put in the S and P five hundred or
the Vanguard Total Stock Market Fund.
Speaker 2 (27:28):
Yeah.
Speaker 1 (27:28):
And I think when I last did this math about
eighty percent of Vanguard's assets or either in the S
and P five hundred or in the Vanguard Total Stock
Market Fund. Yeah. Right. In other words, passive has hurted
people into the same idea and when Mordecai Kurtz, who
has had that idea of rational expectations. So the thing
(27:48):
we need to be most careful of is correlated beliefs, right,
Correlated beliefs are there will create risk when when investors
beliefs are too correlated, when everyone thinks the same thing,
that's the problem.
Speaker 2 (28:00):
There was an interesting bit in the book where you
note that around seventy five percent of the US relative
APT performances come from valuation changes as opposed to revenue
and profitability changes. And that's really interesting because it reflects
pure optimism as opposed to reality.
Speaker 1 (28:14):
Which is always the case, Marion, because if you go
back to Schuller's work, it's always valuation changes. It's always
changes in our expectations about the future that drive the
majority of stock market balto is always the case.
Speaker 2 (28:27):
And then you say, which again I thought was an
interesting way to look at it, that perhaps investors who
want to think about this but a little bit more closely,
should look at not necessarily at market cap when they
come to invest internationally, but look perhaps at percentative revenues
or net income that comes from the US against other countries,
and that would be about thirty percent US, right, So
that in fact, if you were going to look at
(28:47):
it in terms of the revenues from each country, you
should have about thirty percent of your efforts in the
US as opposed to what you probably do at the moment,
which is more like sixty percent maybe more exactly.
Speaker 1 (28:56):
And I think the sort of negative side. We've been
talking so much about being skeptical of bubbles, but we
should also and this is a big part of my
investment strategy, be excited about things people are pessimistic about.
And when we see people giving up, when you see
magazine covers about the death of that's the time that
I get really excited about things. And I think there's
actually a lot to be excited about right now. It's
(29:18):
just not where other people are looking. I actually love
the UK and Europe.
Speaker 2 (29:23):
Just give the Europe. But we love to hear you
love the UK, you know.
Speaker 1 (29:28):
And actually it was funny. I was visiting with a
friend who was a big Brexit supporter, and I follow
politics as closely as any normal person, but I honestly
didn't follow the UK stuff so much. And I said, well,
you know, reading the Ft and the Economist, I've come
to the you know, it sounds like it's been a
complete disaster and what were you all thinking? And he said, Dan,
(29:49):
you know, pull up your computer and look at UK
GDP growth since Brexit and then compare it to continental Europe.
GDP growth since Brexit, and so I went and did it.
All sudden I found the UK had grown faster than
continental Europe, and he was like, that's the only argument
I need to make, you know, And and I sort
of thought to myself, you know, if my narrative about
that was a little bit wrong, you know, maybe maybe
(30:11):
the common narrative about Europe as a whole is wrong.
And I thought, I do.
Speaker 2 (30:15):
I hate to say this down, but you need to
go and look up GDP per head growth in Okay,
all right, that might be a little bit of a
downer for you, I'm afraid, but I'm with the sentiment
that breaks it really hasn't been so bad so far
and could even have well, it's likely to have very
positive rammications in the future. But gdpeeperhead doesn't tell the
same story as GDP. We've had a very fast growing
(30:36):
growing population.
Speaker 1 (30:38):
Sorry, all right, no, no, that's that's helpful moment. I'll
go back and readvisit my analysis. But I think, you know,
when I look globally at valuations, what you see is
that Europe is phenomenally cheap. It's cheaper, way cheap relative
to long term marriage, is way cheap relative to the
US UK in particular, and what's sort of the second
(31:00):
layer of that analysis, because you don't want to just
be a contrarian for the sake oftarian, and you don't
want to buy cheap things just to buy cheap things.
If the cheap things are bad, you want to buy
cheap good things. And one of the interesting things if
you look at return on asset type metrics or my
favorite gross profit to asset, European companies are really high
quality businesses. They're very well run, they're very high merged,
(31:23):
and they're very high return on asset. And in fact,
the sort of leanears have actually that sort of capital
starvation has forced the return on assets to go higher.
They created higher discount rates, higher bar for new investments.
And so when you look at Europe, you're not just
buying really cheap companies, you're buying really cheap, really well run,
really higher recur assets.
Speaker 2 (31:42):
Absolutely, and same in the UK. You know, we have
some really brilliantly run businesses here and they're incredibly cheap
relative to similar businesses in.
Speaker 1 (31:50):
The US exactly. And it's funny. I did this analysis
where I took share of revenue in the US and
then I whether it's listed in the US. So it
was a two part regression. And what I found is
that because there are a lot of great UK companies,
for example, that have fifty percent or plus of their
revenues in the US, right, I mean, it's not unusual.
(32:12):
And it turns out that the share of revenue in
the US doesn't matter at all, and all that matters
is where the company is listed. And I think that
sort of relates to this sort of passive investing or
the sort of structure of investing that a London listed
company is just treated differently than the US. Last.
Speaker 2 (32:26):
Yeah, I mean the problem for US there is that
lots of these companies are now looking at whether they
can relist somewhere else get a higher evaluation. So we
don't want that to happen. We don't want that to
happen because we rely on the infrastructure of our capital
markets in the UK, so it's a big part of
our economy.
Speaker 1 (32:39):
It's in my mind, the greatest trade available at the
moment is to buy high quality, cheap European businesses. Sometimes
when everybody understands that there's a problem, you almost know
it's going to get fixed. So you know, what are
the big problems facing here? But what is this Ukraine war, right,
which is dragged down valuations a lot, And you wonder,
like how far off is that from getting fixed? Right?
(33:00):
How far off of a piece deal? Are we? Maybe
closer than we think? And I think, second, you know
this regulatory burden which is just obviously a problem. And
you say, like the UK, for example, Brexit has given
the UK an option on deregulation. They haven't exercised that option.
Speaker 2 (33:16):
Okay, certainly not exercising yet, we have not.
Speaker 1 (33:19):
But they bought the option. Brexit bought them the option,
and there's a path, the potential deregulation. And if you
can in Europe can deregulate, and if they can solve
the Ukraine issue, right, like, why wouldn't valuations go up?
Speaker 2 (33:32):
Is the other big problem in Europe under the UK's
energy prices right, particularly in the UK stunning lehigh industrial
electricity prices.
Speaker 1 (33:40):
Right, And who knows how that's get solved, but there
seems like there'll be a lot of pressure on people
to solve it. Yes, and there are paths to do it.
Speaker 2 (33:47):
Yeah, yeah, okay, brilliant. Now that is all fascinating and
as I say, fits neatly with lots of my verses.
Thank you very much. The other thing I really wanted
to talk to you about. You have a chapter in
the book about is private equity. And I know that
you are very concerned about private equity. And you make
this great point that people talk about it as though
it's a diversifier. It diversifies us from our equity holdings.
(34:08):
But of course private equity is just equities aren't listed.
They're exactly the same, and we should treat them in
the same way. And your concern is that there's trouble
brewing in that SECTI there are.
Speaker 1 (34:17):
A few sort of very important facts to know about
private equity that for the first, you know, what is
private equity? Well, what is a private equity? You know,
as opposed to a public equity, And it's really two
things are different. Right. The first thing is that private
equities tend to be much smaller than public equities. That
they're all microcaps. They have about a two hundred million
dollars valuation in on equity market cap on average, right,
(34:39):
And that's compared to say thirty billion or something for
the S and P five hundred, right, and the large
end of the microcap in nex is fourtu million. So
the first thing you know is that they're really small companies.
What do we know about small companies. We know that
small companies have hired default rates than big companies. We
know they're riskier, they're less diversified, their lower margin. Right,
all of these things are stylized true facts about small companies.
(35:00):
Of course, Right, once you get bigger, you're more stable,
you're more diversified, you tend to scale vages, higher margins, right,
less volatile, et cetera. But these are small companies, not
just small, but really small. Right. So if you love
private equity but don't love public small caps or public microcaps, right,
ask yourself why what's the disconnect? The second thing you
have to remember is that private equity backed companies are
(35:23):
very levered. Generally, fifty to sixty percent of their total
valuation is funded by debt, and that's mostly coming now
from private credit, and it's usually coming at very high rates.
And I joke that lending is the second oldest profession.
There are no new innovations in lending. And so if
a company has to borrow at very high rates, the
(35:43):
reason they have to borrow at high rates is that
they're very risky. And so you're looking at equity that's
subordinated a very high interest rate debt issued by these
private credit firms. That is reflective of the underlying risk
and the underlying volatility of these businesses now and people
don't think it's risky is because it's private, and so
you only get a mark once a quarter. And who
(36:05):
does the mark accountants? Well, if you look at the
volatility of private equity marks, it's about as volatility as
the volatility of book value of public companies. It just
isn't related to the market. And so what people get
fooled by that lack of volatility into thinking that these
tiny little companies with a ton of debt really aren't
very risky, And of course they are. They're very risky.
(36:27):
We just haven't realized that risk yet because we've had
a period of very declining rates. And then I think
coincidentally or not coincidentally, but importantly, you know, private equity
over the past ten years has massively shifted in its
sector composition to focus heavily on technology stocks, and that's
been a boon, but any turn in the future of
(36:49):
these tech the tech industry is massively going to hurt
private equity. It's become a highly levered bit on microcap
software companies and also very expensive.
Speaker 2 (36:59):
One of the is a but to when when the
whole idea that you should invest in private equity is
a massive diversify. But thus began was private equty companies
but very cheap, right you could get them at a
stunking discount to publicly listed equities. And now, of course
that is no longer true, and in fact, the valuations
of private equity companies tend to come in above those
of publicly.
Speaker 1 (37:16):
Listed right, Like, why should I pay more to have
a higher risk a smaller, smaller, more risky, more levered
company that I can't buy and sell every day? Why
should that be more expensive? It just boggles the mind.
And I think, you know, we've seen this, this correlated belief, right,
it's a correlated belief. But from all these pension funds
and college endowments and fancy investors that you need to
(37:39):
invest like Yale, you need to invest like David Swinson,
you need to have maybe forty percent of your assets
in private equity. And I did the simple math, which
is to say, you know, if you take the aggregate
size of private equity back to companies. You know how
big are those companies relative to public companies, And they're
about two to four percent of the total revenue of
(38:02):
public companies. Right, So it's a tiny, tiny, tiny set
of companies. And so to have forty percent of your
assets and two percent of the company and two percent
of the revenue share of the companies, right, because there
are a lot of small companies, they just don't make
much money.
Speaker 2 (38:15):
That seems completely insane when you put it like that,
completely insane, But it's very nice for fund managers or
for people managing large pools of money, because it looks
better with this mothing. It looks less volatile, it looks
it looks calmer, it looks like a diversify. IM's quite
relaxing for you. Really, you don't have to deal with that,
you know, pricing every day nonsense.
Speaker 1 (38:38):
Exactly, And you get this veneer being able to tell
everyone that you improve companies, right, Like I'm a hedge
fund manager, I buy and sell shares. You know, what
do I contribute to society? What do I know about companies?
How can you feel that good about investing? Like maybe
I'm a little smarter, you're right, Like, well, with private equity,
you know, I've been on the board and I really
helped the company grow, and I've talked to them about
this new product and then we you know, we open
(38:59):
a new factory. It's sounds better. And I think it's
actually hogwash, right, Like you know, and you sort of
know it's hogwash by just looking at the LinkedIn profiles
of who works in private equity, right, Like they're all
former bankers, right if.
Speaker 2 (39:12):
This is exactly the point where I say to all
the listeners, send your hate mail directly to Dan. Don't
send it to us. Directly to Dan. He's ready.
Speaker 1 (39:22):
But it's like, you know, when, when did the two
years you spent building Excel and PowerPoint models as a
junior banker, you know, give you this great insight on
how to run like mid market industrial companies in Germany? Right?
Why does that logical? I'd be like, oh God, it's
going to do so much better under private equity management.
It's like, okay, so the junior banker from Goldman is
going to do that much better of a job than
(39:42):
like the fifty year old veteran if you're running that
business that year it seems much more plausible that what
the banker is really good at is adding a lot
of debt to the balance sheet and doing that on
acquisitions and maybe you know, dressing it up for sale
that they seem good at. But the idea that they're
better at running companies just seems a little great.
Speaker 2 (40:00):
Well, we'll find out soon with me because a lot
of private equity companies they're going to have to start
moving assets on and they can't keep handing them around
between each other. So there's going to be surely a
spate of listings coming up where we will see what
private equidey companies are really worth in public markets, and
that will be fascinating. Okay, interesting, right, something completely different.
Do you talk about gold a little in the book
(40:21):
and when and when you shouldn't invest in gold? And
we have a lot of gold bug listeners, and I'm
a little bit of a gold bug myself, so maybe
we could talk a little bit about your views on
gold and where they fit in this where it fits
in this cycle.
Speaker 1 (40:34):
Yeah, I think gold is a very important portfolio tool,
and if you think about why it's an important portfolio tool,
we need some low risk, diverse fying assets right, and
one low risk diverse fying ac is bonds, and one
low risk di burst fying acid is gold. The challenge
with bonds is that they react very neatively to inflation,
(40:54):
and our country economy has had a bit of an
inflation problem with LID and gold and in the opposite way,
or reacts positively to inflation because you can inflate the currency,
but the price of gold should be unaffected. And so
what I think is that you should depend your low
risk portfolio should alternate between bonds and gold depending on
your views of whether inflation is present. If you're worried
(41:16):
about inflation, you should have more gold and fewer bonds,
and if, on the other hand, you're worried about deflation,
you stole more bonds and less gold. But the idea
that gold has to be a tool that you're using.
It's so important and it trades so differently that it
gives your portfolio more degrees of freedom if you include
it in the parameter of things you're considering, and you
(41:37):
don't have to have a big allocation for it to
make a big difference.
Speaker 2 (41:40):
Okay, and what about bitcoin? You I notice you do
not mention at all in.
Speaker 1 (41:44):
The book, Oh dear Bitcoin.
Speaker 2 (41:48):
I mean that you clearly are not going to say, well,
bitcoin is digital gold. It's the same thing. I'm not
hearing you saying that.
Speaker 1 (41:54):
I'm not saying that because I don't think it's true.
I said that gold was a low risk asset. Right,
Look at the volatility of gold. It's like the volatility
of bonds. It is a low risk asset. Bitcoin has
the volatility of a the nastac or microcaps. Right, It's
crazily vollatile. So it's not low risk, it's high risk.
And then what's it correlated with?
Speaker 2 (42:12):
Right?
Speaker 1 (42:12):
Gold is sort of anti correlated. Gold is its own thing.
It marks to its own tomb. That's why it's valuable.
But bitcoin is not. Bitcoin is very correlated with say
that Goldman Sachs highly shorted basket of US tucks. It's
very correlated with Robinhood stock. Right. It's correlated with any
type of gambling activity that you see in public markets.
And I think it's part of a broader trend towards
(42:35):
people finding gambling opportunities in public markets as opposed to
find them betting on sports teams.
Speaker 2 (42:41):
Yeah. Interesting, do you think now as that there's lots
more institutional interest in it, and there's even to be
a lot of passive investment into bitcoin that it might
get caught up in the same sort of momentum trade
as perhaps a lot of the US tech companies have
over the last couple of years.
Speaker 1 (42:55):
I think it certainly will, and I think institutional adoption
of bitcoin today is out as smart as institutional adoption
of investing in China and twenty seventeen or twenty eighteen.
It's equally as much of a mania, and it's equally
as dumb.
Speaker 2 (43:07):
Okay, I think we have a very clear view there.
And again, just let me repeat hate mail direct to
Dan Donk. Can we find you on Twitter so they
can send your hate mail director you on Twitter, because
that's where I get most absolute What's your handle there?
Just to make apple sure it goes to you, not me.
Speaker 1 (43:20):
It's at verdad cap.
Speaker 2 (43:21):
Okay, everybody, if you feel strongly about bigcoeen, feels strongly
about private equity, strongly about any of those things, please
let Dan know directly, and do not copy me into
your aggressive tweet. Thank you.
Speaker 1 (43:33):
Okay.
Speaker 2 (43:34):
So at the end, I normally try and ask people
what they would invest in now, but I think we
have a pretty clear steer from you on the value
front that you're interested in UK equities, you're interested in
European equities. Is there any sector in particular of that
interests you, or any part of the market, or any
even any particular company that you're finding fascinating at the moment.
Speaker 1 (43:51):
You know, I actually like Eastern Europe. I find a
lot of interesting things in Poland, and I think that
people have tended to overlook Eastern Europe in particular because
the Ukraine War. But I think it also is the
most leveraged any peace deal going through that you'll make
money in Polish equities. They're very thinly traded. You have
to buy small caps, but I think it's quite attractive.
Speaker 2 (44:11):
Okay, that is interesting polysh small caps have never come
up on this podcast before. So thank you very much
for that. Congratulations, something you something youre go? Okay, last question.
Your book I think is excellent, and just to repeat
again everybody by this book, it's excellent. Everything we've talked
about is in the book, plus a whole load more.
And we didn't get onto private credit. Another fascinating chapter
(44:34):
in it, so and the bond chapter also excellent. Do
read that. But Dan, if you were going to recommend
one book written by somebody else, is there anything you've
been reading recently that you've really enjoyed and think that
would be helpful for our listeners.
Speaker 1 (44:47):
Well, I don't know about helpful to your listeners, but
by far the best book that I've read recently is
The History of the Conquest of Mexico by William Prescott,
which came out in eighteen thirty, and it tells the
unbelievable story of how Cortez conquered Mexico in fifteen tens
and as a story that I like glossed over in
the history textbooks, but it is unbelievably fascinating, you know,
(45:09):
eight hundred men conquering several hundred thousand a person civilization
in It's just an insane story and beautifully written. So
if you're looking from a break from markets, I recommend it.
Speaker 2 (45:22):
I imagine people are going to be looking for a break
from markets relatively soon this year, but we'll see. Dan,
thank you so much for joining us today and gratulations
on an excellent book. Thank you, Mareon, Thanks for listening
this week's Maren Talks Money. If you like our show, rate, review,
and subscribe Wherever you listen to podcasts and keep sending
(45:44):
questions or comments to Marin Money at Bloomberg dot net.
You can also follow me and John on Twitter or
x I'm at Marin sw and John is John Underscore Stepic.
This episode is were hosted by Me Maren Sumset Web
was produced by some Saudi production support Moses and and
special thanks to Dan Rasmussen h
Bloomberg Audio Studios, podcasts, radio news.
Speaker 2 (00:08):
Hello Maren Talks Money listeners. Before we come back with
our new shows next week, wanted to republish another of
my favorite episodes from the year. It's a conversation with
Daniel Ramerson, founder of Verdad Advisors and author of The
Humble Investor, How to Find a Winning Edge in a
Surprising World. We talk about the book, where he thinks
all forecasts are wrong, and his take on us TECHTOCS
(00:28):
and artificial intelligence. Enjoy Welcome to Meren Talks Money, the
podcast in which people who know the markets explain the markets.
I'm Meren Sunset Work. This week I'm speaking with Dan Rasmussen,
(00:48):
founder of the investment management firm Verder Advisors. Before starting Verda,
Dan worked at Baine Capital, Private Equity and Bridgewater Associates.
And he's got a book coming out which I have
read already, called The Humble Up, How to Find a
Winning Edge and a Surprising World. It's available for pre
order now and out in bookstores in early February. I
strongly recommend that you order it. The underlying theme, as
(01:10):
Dan puts it, is the future is hard to protect
vctually impossible to predict so don't assume you really know anything.
The best approach is a humble one. The best investment
opportunities come to you when you can see other people's arrogance,
identify where they are too confident, be they too optimistic
or too pessimistic. We're going to get into all that,
plus his thoughts on investing during stock market bubbles are
(01:32):
we in one now by the way, European and UK equities,
Japanese equities, and what he is most bullish on. Dan,
Welcome to Marin Talk's Money.
Speaker 1 (01:41):
Thanks for having me.
Speaker 2 (01:42):
It's a pleasure now. I am excited to have been
one of the first outsiders to have read your book.
I finished it this morning and it is excellent, And
as I said to you before we started talking, it
fits with so many of my biases that I particularly
enjoyed it. Every page and affirmation of thoughts I have already.
Speaker 1 (01:58):
Nothing works passes, Oh.
Speaker 2 (02:01):
God, absolutely absolutely. We'd be having a different conversation if
I'd gone through the book going no, that's not what
I think already. Don't try and persuade me about things
like that. Now. I wanted to start. I see at
the very beginning of the book, what you talk about first,
which is this idea? And it's particularly important this time
of year, by the way, when we are overwhelmed, not
(02:21):
me by forecasts from everybody in the market about what
they think is going to happen in the coming year.
And we know, we know you, and I am pretty
much everyone else in the market from my years of experience,
that every single one of those forecast is wrong, well
not all of them, they'll be one in the middle
by happen chance that is correct. So I wanted to
start by talking about that forecasts, you say, fore costs
(02:43):
meet reality.
Speaker 1 (02:45):
It's probably the single idea that most changed my career,
which was, you know, I started out in investing, like
many of us, do you know, building these discounted cash
flow models, the LBO models that forecast revenue and profits
years into the future. And there was so much emphasis
put in on getting these Excel models right right, or
you know whatever right, meant that I never stopped to ask,
(03:07):
how good are we predicting what's going to happen three
or four years from now and the side and I didn't.
I didn't start out and I didn't study finance or
accounting or economics, and undergrad and so when I started
work in investing, I talked to my sister and a
few other folks who are in the business, and they said, well,
wanted to go read as much as you can, And
so I started reading all these books about theory and
(03:30):
academic research and investing. And one of the ideas that
I came upon was phil Tetlock's work on forecasting, and
Tetlock finds that experts in their fields are no better
than non experts at forecasting things, even in fields in
much they're experts, and the only difference is that they're
more arrogant about it. And I said, you know, gee,
I wonder if our growth forecasts are are right? You know,
(03:50):
how would I sort of figure this out? And I've
done a variety of studies since having that original question,
and the answer that I've come to is that our
forecasts are really bad. At we really don't know much
about the future, and the farther into the future we
try to peer, the worse we get. In fact, Andre
Schlipher at Harvard has done this wonderful study where he
shows that long term growth forecasts are actually a perfectly
(04:13):
negatively correlated with stock market returns. In other words, the
more optimistic you are about long term growth, it's actually
a totally contrarian signal. Now short term growth, you know,
next year, for example, there's a little bit more accuracy.
People have some good, decent chunk of ability to forecast. Okay,
when we're talking about revenue or EBIT das for example,
(04:34):
or profits, you know what's going to happen in twenty
twenty five. The problem is that it doesn't actually help you.
So I just finished this wonderful study where in Japan
almost all companies are required to issue one year forward
guidance on revenue and net income, and so you can
take you know, I took twenty years of this data
and said, you know, how accurate are they? And then
what does it mean for the stock prices? And what
(04:55):
I found is that if you divide it into slow, medium,
and high growth on a one year forward basis, Japanese
companies are about fifty percent accurate. So thirty percent would
be pure chance, you know, one hundred percent would be
totally accurate, fifty right, the other That sounds good, It
sounds okay, right. But the challenge then is if you say, okay, well,
(05:17):
let's say you're forecasting really high. You know, you then think, oh,
I should buy all the companies that are forecasting really
high growth because you know, if they achieve that growth,
it's going to be great. Well, it turns out that
the companies that achieve high growth have sort of average returns. Right.
They forecast high growth and they achieve high growth, and
they have average returns because that high growth was priced
in with the time the guidance was issued. But the
(05:38):
fifty percent of the time those companies that forecast high
growth don't have high growth, their stocks collapse and so
you end up doing worse in the companies that forecast
high growth or about you know, average and total, but
a little bit worse. Whereas if you go to the
companies that are forecasting low growth, yeah, fifty percent of
the time they hit low growth, right, But then when
they do, the stock returns out average, they re turned
(06:00):
the same as the high growth firms that achieved high growth.
But when the slow growth firms achieved high growth, which
they did fifty percent of the time, their stocks do
really well.
Speaker 2 (06:09):
Okay, So knowing the growth thumbs in advance doesn't help
you any even if you did. And is it also
true to say that over those very short periods, so
over a year or so. What we're not necessarily saying
is that anyone is particularly good at forecasting anything out
over a year. What we're saying is that people are
jolly good at extrapolating the future, the short term future,
from the past, and unless something goes wrong, it's quite
(06:31):
likely that the next year will be similar to the
previous year exactly.
Speaker 1 (06:35):
And this is where things get that quite interesting, because
I think you're exactly right, Marion, that the way people
form their forecasts is they look at the recent past
and they extrapolate that forward. That's the most common forecasting
method in markets, which is why you see all the
S and P five hundred forecasts for next year cluster
around exactly what the S and P five hundred day
(06:56):
last year. And there's a wonderful study that I updated
have done, you know, through for the last twenty years
of data, where I look at the level and persistence
of growth rates, and so you basically say, okay, let's
look at every you know, every company's trailing growth over
you know, let's say a one year, three year, five
year period. Does that forecast their growth rate over the
(07:18):
next one, three or five years, and what you find
is that revenue on a one year basis is a
little bit forecastable, and then everything else is total chance.
It's just pure coin flips. There's no relationship between past
and future growth. And that's probably the single hardest thing
for people to understand because it's just so against our views,
(07:40):
right because if you said, well, gee, Microsoft and I
don't know the gap, or some apparel retailer I'm trying
to think of something very boring have an equal chance
of having high growth over the next five years, you'd say,
come on, that's absolutely notty. There's no way that that's true.
But statistically it is true. And I think that when
you start to understand that, and you can buying that
(08:00):
with the insight about what's priced in and what's not,
you start to see how the importance of understanding the
structure of forecasts is to being a good investor, because
I like to say that investing is not a game
of analysis, it's a game of meta analysis. It doesn't
matter what you think, it matters what you think relative
to what the market thinks, and so you need to
(08:21):
understand what other people are forecasting, knowing that everyone else
is forecasting, and then you have to think, well, what
if they're wrong? You know, how would I make money
if they're wrong? And that I think is my sort
of key to unlocking or starting to think about what
should work as an investing strategy based on behavioral economics.
Speaker 2 (08:39):
Yeah, I mean it's not just we'll come back to that.
I've wanted to talk about an anecdote that you had
in the beginning of the book about the weather and
because one of the things that we often talk about
is why don't we bother with these forecasts? I mean
this not just at the company level, but at the
inflation level, GDP level, interest rates, etc. They're always wrong,
and we have these GDP full costs come out over
(09:00):
and over from all our governments selling us GDP is
going to be whatever it is with a couple of
decimal points off to it. And we look at him
like that it's a nonsense. We know it's nonsense. Why
do we listen? So tell us this lovely little weather
anecdote from from the book which explains it.
Speaker 1 (09:14):
Yeah. So this is ken Aarr, the famous economist, was
in the weather core in World War two, uh and
being the genius that he was he's and by the way,
that the Weather Core asked for one year forward weather forecasts, uh,
and so so they could plan troop movements and things
like that, you know, when of the road's going to
be too muddy, when they're once they're going to be
(09:34):
snow by day. And so he was tasked with creating
these and and you know, he did a little bit
of research and he found, you know, these these forecasts
are completely wrong. They're completely useless, and so we just
stopped doing them. And I'll just send you the historic
average table and just use that. And he sends a
note to the General and and and and saying, you
know that the laying out his argument, and he gets
(09:55):
a one sentence one back, and it says, you know,
the General knows that the forecasts are useless, but he
needs them for planning purposes.
Speaker 2 (10:04):
And that that's exactly it isn't it. We need something
to anchor what we're doing around even if we know
it's wrong. We need the anchor.
Speaker 1 (10:13):
We need some way to plan. And even if we're
not doing it consciously, we're often doing it subconsciously. And
so you need some alternative way of thinking. And I
think you know a lot of the research on forecasting
suggests that the best way to make forecast is to
use base rates. Right, So you take a long historical
time and you sort of say, what's the average over
(10:35):
this long period of time, and that's generally the best
you're going to get. And so I think that in
my mind, the game of investing, the way to make
good investment decisions is, on the one hand, to take
those base rates, to study history to understand what the
context is over a long period, not one year, not
three years, but what's a ten twenty year context, and
what's the sort of distribution of potential outcomes, And then
(10:58):
to secondarily to say, because we know everyone else's planning,
we know everyone else's forecasting, where are they concentrating their
excessive optimism and their excessive pessimism, And those are the
places where we're likely to be able to find an
arbitrage just betting that nobody knows, right, Like, nobody knows
is AI going to truly revolutionize the economy, or is
(11:20):
that one trillion these companies are spending going to be
a waste of money. Maybe no one knows, you know,
And if no one knows, you know, what's the bet
that we.
Speaker 2 (11:28):
Should make Yeah, if everyone else is betting that they will,
but we know that nobody knows, then we should bet
that they won't exactly. And that brings us to this
idea of investing being not a game of analysis, is
a game of meta analysis.
Speaker 1 (11:41):
That's right.
Speaker 2 (11:41):
It's all about the relativity, all right. So with that
in mind, that would make almost all the models that
we use at the moment irrelevant. I'm one of one
of the models that you talk about in the book,
the dividend discount model the Way of Investing, by saying,
you know, every company, every egguity is worth the value
of all the dividends it'll be paid to the owner
of that equity in the future. And people spend hours
(12:03):
on these models, don't they days days working out has
actually worked, But as they have absolutely no idea whatsoever
what those dividends are going to be, the final number
they come up with is nonsense.
Speaker 1 (12:14):
Call before you do the company. You know, you're the
world's leading expert on you. So just tell me what's
your year end bank balance going to be in twenty
thirty And by the way, what's your income pre and
post You know, your pre tax and post tax income
exactly for the next five years and just model that first.
And if you can't do that accurately, you know, why
do you think you can do it for Coca cola?
Speaker 2 (12:34):
Yeah right, Okay, interesting, So it's let's go move then
to what you think might work. So if none of
these models that most people use, that everyone who has
an MBA ETCA sits around making these breadsheets all day,
none of these work. What does? And the thing that
you say is that one thing that never changes and
(12:56):
you can extrapolate from is human psychology, which brings us
back to this idea of the meta analysis. And in
this section of the book, you use the analogy of
ships because you spent some time observing how shipping works. Right,
And this is one of my colleagues when I was
first starting as a broker, explained this to me in
terms of of chips, in terms of semiconductors, but you
(13:16):
do it much better with ships.
Speaker 1 (13:19):
Well, it's a wonderful paper by a consulting economist here
for dad Sam Hansen as oppressor at our business school.
Really brilliant guy, and I love the shipping industry. Actually
spent a summer in college working at a Greek shipping company,
and I find that endlessly fascinating of the personalities involved
and the dynamics and the way it interacts with global trade.
I mean, it's just so cool. But there's this fascinating
(13:41):
insight that these economists have by looking at shipping companies.
And what happens is that shipping rates are very variable, right,
so sometimes it's very expensive to ship rate. Sometimes it's
very cheap when rates are very high, and you plug
those rates into a model of whether you should invest
in a new ship or not. It turns out that
(14:02):
investing in a new ship looks really profitable whenever shipping
rates are high, and so people plug these into their model. Now,
the challenge is that it takes three or four years
to build a new ship, and so these Greek shipping
companies they see the high rates and then they go
and they order ships from these South Korean shipyards, and
then three or four years from now, the ships are delivered.
(14:24):
And what ends up happening And he calls this competition neglect,
which I think is such a wonderful and relevant term
to what's going on in AI. By the way, competition neglect,
they don't realize that all their other buddies also ordered
ships at the same time, because they all also did
the same math, and they plugged the same shipping rates
and the same cost to build a ship. And so
there's this lot of ships that then show up on
(14:46):
the market, all at the same time, three or four
ears down the road, and all of a sudden, shipping
prices crash because there are too many ships. And so
you see the competition neglect. The inability of these shipping
companies to anticipate that their competitors are doing the same
thing is what's exacerbating the cycles and driving shipping rates
(15:08):
too high and then too low, and then too high
and then too low, and then everyone seems to be
getting burned at the same time. And I think that
that's such a wonderful analogy to what's going on in markets.
Right you sort of say, wow, like AI is such
a great opportunity, I should buy into it. What if
somebody else figure this out before me, or what if
the fact that I thought it means that everyone else
(15:28):
is thinking at the same time.
Speaker 2 (15:29):
So do you think that there is overinvestment in AIO,
too many companies investing at the same time and the
same things, like the ships, Well, I think there has.
Speaker 1 (15:37):
To be, right. I mean, you just think about how
many of these AI companies there are. All of them
are trying to build pretty much the same thing as
far as I can tell. And I think there are
a few things that are are are clear, right, Like
we can study the history of the Internet, and one
of the things that we observed that tends to be
winner take all the best model tends to work. Google
(15:58):
wins search, Amazon winds retail, you know, Microsoft winds productivity.
So why should we think that AI will be twenty
percent chat GBT twenty percent, Gemini twenty percent, right, like
Claude twenty percent anthropic. It just is it's not plausible
based on the history of the of the of the
(16:18):
tech industry.
Speaker 2 (16:18):
And we can't choose them, and we can't choose the winner.
Speaker 1 (16:21):
And we can't pick the winners. So like, some of
these things are just incinerating capital, right, They've got to be,
Like probably probably all but one of them are incinerating capital.
We just don't know which of them is incinerating capital,
which of them are, and which of them aren't.
Speaker 2 (16:35):
And does that mean that as investors we should avoid
all of them?
Speaker 1 (16:38):
I think so. I think they're all terrifying that there's
too much hype, too much optimism. How long have we
thought that we would have robots that could think like us? Right? Like,
this isn't no idea. Humans of are perpetually attracted to
the idea of anthropic robots that can speak and think
like us. And every time we've tried to do it, it
has worked, and it's not going to work this time.
I don't think why do we think?
Speaker 2 (16:59):
Why do you think we're attracted to it? Is it
because we're lazy and we're just hoping to be able
to invent something that can do everything for us?
Speaker 1 (17:06):
Well, it's the It's the ultimate vanity to create something
in your own image, isn't it the closest complex?
Speaker 2 (17:15):
Okay? One of the tiny questions not that any.
Speaker 1 (17:18):
Of our friends in the tech industry.
Speaker 2 (17:19):
Of god Cox absolutely this idea about the measure analysis,
What does that lead us to? What does that tell
us about how we can actually invest? How can we
really do it? What works?
Speaker 1 (17:31):
Yeah? So I think that if we step aside and
we say, gee, you know, forecasting doesn't work and the
future is too unpredictable and actually markets are too volatile,
which is another thing. This is what Robert Schiller won
the Nobel Prize for us, this idea of excessive volatility,
which Schiller did so brilliantly. You know, if the dividend
discount model is right, and the net present values equal
(17:54):
to some of the future cash flows uh discount by
the interest rates, and if we know future cash flows
and we know future we can tell you what the
net present value of the stock market should have been
at any given time and how much it should have
moved as those things changed. And he finds that about
eighty plus percent of stock market volatility is inexplainable by
(18:14):
changes and fundamentals.
Speaker 2 (18:15):
Okay, so even if you had the information for the model,
it still wouldn't work exactly.
Speaker 1 (18:21):
Even with full pressions, you can't explain a very high
percentage of volatility. And so where is this excess volatility
coming from? And I love this theory by this Stanford
professor Mordecai Kurtz, and he comes up with this theory
that what's happening is that everybody's making forecasts and then
the future happens, and eighty percent of people realize they're wrong,
(18:43):
and so they sell and they buy something else, and
then they make new forecasts and then the same thing happens, right,
and it's that dynamic and he should use some fancy
match so that could explain it. All. Right, that's what's
going on. And I think what I sort of love
about that idea. And we're so focused on efficient market theory,
and efficient market theory is so many wonderful implications, right,
(19:05):
and it's so useful. But I think one challenge to
efficient markets theory is that it often gets interpreted as
the price is always right. But anybody who's actually invested
in markets at any point knows how frequently they make mistakes.
And not only how frequently they make mistakes, but how
frequently the market seems to make mistakes. Right. I mean,
how could a stock be down thirty percent in a
(19:27):
day if it wasn't a mistake yesterday? Right? I mean, like, yes,
the new news came out, but clearly the market didn't
get that right, otherwise the price wouldn't have moved as
much as it did. And I think trying to reintroduce
this idea of mistakes back into our vocabulary when we
talk about markets and make it more human. Right. Of course,
mistakes are an integral component of investing. How could they
(19:47):
not be How could anybody who's ever experienced markets not
know the mistakes are part of things? And how is
that therefore driving rebalancing decisions? And then how can we
as investors think through if other people are making mistakes,
if we're making mistakes, how should we build portfolios that
take into account the idea that we are going to
make mistakes and that everyone else is making mistakes too,
and that that's part of the dynamics of what's driving
(20:08):
market volatility.
Speaker 2 (20:10):
Okay, so what's the answer? How are we going to
build that portfolio?
Speaker 1 (20:13):
What we're looking for is some barometer of optimism or pessimism, right,
could if we could just have some barometer of how
optimistic or pessimistic the market was about an individual security
about the market as a whole, gee, then we'd be
in very good stead because we'd have a very good
way of saying, you know, here's the stuff that's too
extreme on one end or the other and going long
or short that it turns out, in fact that we
(20:33):
have a very simple metric for doing that. And in
the stock market, it's valuations. Right, you can pick almost
any multiple, right, revenue multiples or book multiple and you
can erase to hooks on a on a ranking system,
and you'll find that the ones that are the cheapest
end up doing the best and the ones that are
the most expensive end up doing the worst. And that
value reliably predicts stock returns. And in fact, over the
(20:57):
last few years it hasn't in the United States. We
should talk about why, but it has even internationally people
have declared the death of value investing. But value investing
are the idea of ranking stocks by their relative optimism
or pessimism and going along and things other people are
pessimistic about and short things they're optimistic about should work.
And I think you can also, and we should talk
(21:18):
about this separately, apply that to thinking about whole markets
and whole economies. But I think in the context of
single stocks, what we've seen over the last few years
has been some of the worst performance of value investing
over its history. The last time it did this badly
was in the late nineties during the tech bubble, and
so we have to reckon with that, right, So I
(21:38):
think it's all well and good for me to argue
that we should use valuation ratios as a metor optimism
or pessimism and that we should be long things other
people are pessimistic about. And there's an intuitive logic to that,
but there's also grappling with the fact that that hasn't
worked recently in the United States. Again, it has worked internationally,
it has worked in the US, and so why And
actually there was a period from COVID until the release
(22:01):
of chat GBT when it did work, and then chat
GBT just totally new to value investing again. And so
what I like to say about value investing what's going
on in the market today is that we've had a
period from in the twenty tens where there were a
very small number of companies where they were forecasts grow fast,
(22:22):
and then they grew faster than the forecast, and they
did that a few years in a row. That was
the sort of fan mag stocks, as they were called them.
What is that a tribunal too, I'd say it was
an innovation wave. And these innovation waves happen. They do.
They happen with the Internet, they happen with railroads, and
when they happen, they are these abnormal profit pools that
are earned by the innovators. Now that doesn't last that
(22:44):
long because at some point the customers need to benefit
more than the innovators, and at some point the innovation
get commoditized, and so these innovations don't last forever, but
in early windows they can be huge, huge booms. And
that's what we're in the middle.
Speaker 2 (22:57):
Of, in the middle of or towards the end of.
Speaker 1 (23:00):
It depends on the future of AI and everything hinges
on that. Ye. And again that's what you saw right,
like the sort of tech mania seemed to actually peak
in COVID right in twenty twenty one, and then with
the release of the vaccines, you had all that stuff
clearly coming off. It all gone too far. Zoom had
gone people were using Zoom too much, right, the people
were buying too much on Amazon. It was peak Internet.
(23:23):
And then it declined, and then it looked like we
were going to sort of return to a normal market
where value investing worked again. And then chat GPT was
released and it's just unleashed this total mania again and
it now feels like we're back at twenty twenty one peaks.
I mean, you know, you look at things like fart
coin and it's even worse than the SPACs, like at
(23:43):
least the SPACs or companies well the hell is fart coin,
and yet it's valued at most more than you know,
ninety percent of Japanese companies, for example. You have to
understand that, you know, markets are are reflective of human
history and human events, and it's not it's not a
line math problem. And we know that there are certain
things that we can rely on and should rely on,
(24:06):
which is betting against hubris right, betting on things others
are pessimistic about and being skeptical if things are too
optimistic about. But sometimes the optimists are right, and they
were right during the twenty tens. And the question is
now the only question that matters for markets right now?
In my mind, the most important question is are they
right about AI or not?
Speaker 2 (24:26):
I mean, the other thing you can say, surely is
that value investing doesn't work during a bubble.
Speaker 1 (24:29):
It doesn't work during a bubble.
Speaker 2 (24:31):
Answer, it doesn't work during a bubble, And so you
can then make the case. So you might have might
not want to make the case that the last few
years are being suggestive of a bubble in the US market,
And you look at the valuations, and these are bubble valuations.
So that could be the simplest way to look at it.
Speaker 1 (24:45):
I think so too. And I have this piece in
the book about the nineties because I spent a lot
of time thinking about bubbles. I went back and I
read a bunch of investor letters from the great investors,
Ray Dalio, Peter Lynn Choward, Mark Seth Clarman. You know
what were they saying in the nineties. And it was
really interesting because all these great investors knew it was
a bubble. They all wrote a boute about it. Ray
(25:09):
Dalio said, we're approaching a blowoff phase of the US
stock market. Peter Lynch said, not enough investors are worried.
The only problem is that those two quotes are from
nineteen ninety five, So you know, investors are often you know,
smart data driven people. You can pick up on these
things and say the evaluations are too high. The problem
(25:30):
is that smart investors tend to be way too early. Right.
The bubble didn't burst for five years, right, yeah, and
eked up on ear and each subsequent year it doesn't burst.
You look stupid, and the people that supported the bubble
look right. And I think that that's the type of
situation we're in now. And it actually turned out that
value investing, if you looked at it from ninety five
(25:50):
to ninety nine, it looked like the stupidest investment strategy
on the planet. So did international diversification. So right, but
if you just fast forward two or three years the
bubble or so quickly that value investing, international diversefication, all
these things came out ahead with only one or two
years after the bubble. And so I think that having patients,
and I think understanding that there's historical context, being patient,
(26:13):
but being guided by a sensitivity towards these behavioral insights
that it doesn't you know, don't overthink it. You don't
have to in some ways, you don't have to have
the ends. I don't need the answer to any I.
I don't need to know that extended will succeed. All
I need to know is are people too optimistic about
it or not? And what it would be the signs
of that excessive optimism. And if people are excessively optimistic,
(26:35):
you know what should I do? I should stay away.
Speaker 2 (26:38):
And so there is this sense from you anyway that
investors in general overinvested in the US, underinvested outside the US,
overinvested in AI, and underinvested.
Speaker 1 (26:47):
In value absolutely, And I think one interesting sort of
dynamic that's been going on, right is the rise of
passive investing, which is a wonderful thing. Right. There are
many reasons why passive is a wonderful, wonderful thing for investors. Right,
It's been great for consumers. I love passive investing. I
love Vanguard. The only problem I see, and maybe there
(27:10):
are others that other people can talk about, the real
problem I see with passive investing is that when people
go passive, they don't say, I'm going to put my
money in the S and P four hundred mid Cap
Europe Index if such a thing exists. They think, I'm
gonna put in the S and P five hundred or
the Vanguard Total Stock Market Fund.
Speaker 2 (27:28):
Yeah.
Speaker 1 (27:28):
And I think when I last did this math about
eighty percent of Vanguard's assets or either in the S
and P five hundred or in the Vanguard Total Stock
Market Fund. Yeah. Right. In other words, passive has hurted
people into the same idea and when Mordecai Kurtz, who
has had that idea of rational expectations. So the thing
(27:48):
we need to be most careful of is correlated beliefs, right,
Correlated beliefs are there will create risk when when investors
beliefs are too correlated, when everyone thinks the same thing,
that's the problem.
Speaker 2 (28:00):
There was an interesting bit in the book where you
note that around seventy five percent of the US relative
APT performances come from valuation changes as opposed to revenue
and profitability changes. And that's really interesting because it reflects
pure optimism as opposed to reality.
Speaker 1 (28:14):
Which is always the case, Marion, because if you go
back to Schuller's work, it's always valuation changes. It's always
changes in our expectations about the future that drive the
majority of stock market balto is always the case.
Speaker 2 (28:27):
And then you say, which again I thought was an
interesting way to look at it, that perhaps investors who
want to think about this but a little bit more closely,
should look at not necessarily at market cap when they
come to invest internationally, but look perhaps at percentative revenues
or net income that comes from the US against other countries,
and that would be about thirty percent US, right, So
that in fact, if you were going to look at
(28:47):
it in terms of the revenues from each country, you
should have about thirty percent of your efforts in the
US as opposed to what you probably do at the moment,
which is more like sixty percent maybe more exactly.
Speaker 1 (28:56):
And I think the sort of negative side. We've been
talking so much about being skeptical of bubbles, but we
should also and this is a big part of my
investment strategy, be excited about things people are pessimistic about.
And when we see people giving up, when you see
magazine covers about the death of that's the time that
I get really excited about things. And I think there's
actually a lot to be excited about right now. It's
(29:18):
just not where other people are looking. I actually love
the UK and Europe.
Speaker 2 (29:23):
Just give the Europe. But we love to hear you
love the UK, you know.
Speaker 1 (29:28):
And actually it was funny. I was visiting with a
friend who was a big Brexit supporter, and I follow
politics as closely as any normal person, but I honestly
didn't follow the UK stuff so much. And I said, well,
you know, reading the Ft and the Economist, I've come
to the you know, it sounds like it's been a
complete disaster and what were you all thinking? And he said, Dan,
(29:49):
you know, pull up your computer and look at UK
GDP growth since Brexit and then compare it to continental Europe.
GDP growth since Brexit, and so I went and did it.
All sudden I found the UK had grown faster than
continental Europe, and he was like, that's the only argument
I need to make, you know, And and I sort
of thought to myself, you know, if my narrative about
that was a little bit wrong, you know, maybe maybe
(30:11):
the common narrative about Europe as a whole is wrong.
And I thought, I do.
Speaker 2 (30:15):
I hate to say this down, but you need to
go and look up GDP per head growth in Okay,
all right, that might be a little bit of a
downer for you, I'm afraid, but I'm with the sentiment
that breaks it really hasn't been so bad so far
and could even have well, it's likely to have very
positive rammications in the future. But gdpeeperhead doesn't tell the
same story as GDP. We've had a very fast growing
(30:36):
growing population.
Speaker 1 (30:38):
Sorry, all right, no, no, that's that's helpful moment. I'll
go back and readvisit my analysis. But I think, you know,
when I look globally at valuations, what you see is
that Europe is phenomenally cheap. It's cheaper, way cheap relative
to long term marriage, is way cheap relative to the
US UK in particular, and what's sort of the second
(31:00):
layer of that analysis, because you don't want to just
be a contrarian for the sake oftarian, and you don't
want to buy cheap things just to buy cheap things.
If the cheap things are bad, you want to buy
cheap good things. And one of the interesting things if
you look at return on asset type metrics or my
favorite gross profit to asset, European companies are really high
quality businesses. They're very well run, they're very high merged,
(31:23):
and they're very high return on asset. And in fact,
the sort of leanears have actually that sort of capital
starvation has forced the return on assets to go higher.
They created higher discount rates, higher bar for new investments.
And so when you look at Europe, you're not just
buying really cheap companies, you're buying really cheap, really well run,
really higher recur assets.
Speaker 2 (31:42):
Absolutely, and same in the UK. You know, we have
some really brilliantly run businesses here and they're incredibly cheap
relative to similar businesses in.
Speaker 1 (31:50):
The US exactly. And it's funny. I did this analysis
where I took share of revenue in the US and
then I whether it's listed in the US. So it
was a two part regression. And what I found is
that because there are a lot of great UK companies,
for example, that have fifty percent or plus of their
revenues in the US, right, I mean, it's not unusual.
(32:12):
And it turns out that the share of revenue in
the US doesn't matter at all, and all that matters
is where the company is listed. And I think that
sort of relates to this sort of passive investing or
the sort of structure of investing that a London listed
company is just treated differently than the US. Last.
Speaker 2 (32:26):
Yeah, I mean the problem for US there is that
lots of these companies are now looking at whether they
can relist somewhere else get a higher evaluation. So we
don't want that to happen. We don't want that to
happen because we rely on the infrastructure of our capital
markets in the UK, so it's a big part of
our economy.
Speaker 1 (32:39):
It's in my mind, the greatest trade available at the
moment is to buy high quality, cheap European businesses. Sometimes
when everybody understands that there's a problem, you almost know
it's going to get fixed. So you know, what are
the big problems facing here? But what is this Ukraine war, right,
which is dragged down valuations a lot, And you wonder,
like how far off is that from getting fixed? Right?
(33:00):
How far off of a piece deal? Are we? Maybe
closer than we think? And I think, second, you know
this regulatory burden which is just obviously a problem. And
you say, like the UK, for example, Brexit has given
the UK an option on deregulation. They haven't exercised that option.
Speaker 2 (33:16):
Okay, certainly not exercising yet, we have not.
Speaker 1 (33:19):
But they bought the option. Brexit bought them the option,
and there's a path, the potential deregulation. And if you
can in Europe can deregulate, and if they can solve
the Ukraine issue, right, like, why wouldn't valuations go up?
Speaker 2 (33:32):
Is the other big problem in Europe under the UK's
energy prices right, particularly in the UK stunning lehigh industrial
electricity prices.
Speaker 1 (33:40):
Right, And who knows how that's get solved, but there
seems like there'll be a lot of pressure on people
to solve it. Yes, and there are paths to do it.
Speaker 2 (33:47):
Yeah, yeah, okay, brilliant. Now that is all fascinating and
as I say, fits neatly with lots of my verses.
Thank you very much. The other thing I really wanted
to talk to you about. You have a chapter in
the book about is private equity. And I know that
you are very concerned about private equity. And you make
this great point that people talk about it as though
it's a diversifier. It diversifies us from our equity holdings.
(34:08):
But of course private equity is just equities aren't listed.
They're exactly the same, and we should treat them in
the same way. And your concern is that there's trouble
brewing in that SECTI there are.
Speaker 1 (34:17):
A few sort of very important facts to know about
private equity that for the first, you know, what is
private equity? Well, what is a private equity? You know,
as opposed to a public equity, And it's really two
things are different. Right. The first thing is that private
equities tend to be much smaller than public equities. That
they're all microcaps. They have about a two hundred million
dollars valuation in on equity market cap on average, right,
(34:39):
And that's compared to say thirty billion or something for
the S and P five hundred, right, and the large
end of the microcap in nex is fourtu million. So
the first thing you know is that they're really small companies.
What do we know about small companies. We know that
small companies have hired default rates than big companies. We
know they're riskier, they're less diversified, their lower margin. Right,
all of these things are stylized true facts about small companies.
(35:00):
Of course, Right, once you get bigger, you're more stable,
you're more diversified, you tend to scale vages, higher margins, right,
less volatile, et cetera. But these are small companies, not
just small, but really small. Right. So if you love
private equity but don't love public small caps or public microcaps, right,
ask yourself why what's the disconnect? The second thing you
have to remember is that private equity backed companies are
(35:23):
very levered. Generally, fifty to sixty percent of their total
valuation is funded by debt, and that's mostly coming now
from private credit, and it's usually coming at very high rates.
And I joke that lending is the second oldest profession.
There are no new innovations in lending. And so if
a company has to borrow at very high rates, the
(35:43):
reason they have to borrow at high rates is that
they're very risky. And so you're looking at equity that's
subordinated a very high interest rate debt issued by these
private credit firms. That is reflective of the underlying risk
and the underlying volatility of these businesses now and people
don't think it's risky is because it's private, and so
you only get a mark once a quarter. And who
(36:05):
does the mark accountants? Well, if you look at the
volatility of private equity marks, it's about as volatility as
the volatility of book value of public companies. It just
isn't related to the market. And so what people get
fooled by that lack of volatility into thinking that these
tiny little companies with a ton of debt really aren't
very risky, And of course they are. They're very risky.
(36:27):
We just haven't realized that risk yet because we've had
a period of very declining rates. And then I think
coincidentally or not coincidentally, but importantly, you know, private equity
over the past ten years has massively shifted in its
sector composition to focus heavily on technology stocks, and that's
been a boon, but any turn in the future of
(36:49):
these tech the tech industry is massively going to hurt
private equity. It's become a highly levered bit on microcap
software companies and also very expensive.
Speaker 2 (36:59):
One of the is a but to when when the
whole idea that you should invest in private equity is
a massive diversify. But thus began was private equty companies
but very cheap, right you could get them at a
stunking discount to publicly listed equities. And now, of course
that is no longer true, and in fact, the valuations
of private equity companies tend to come in above those
of publicly.
Speaker 1 (37:16):
Listed right, Like, why should I pay more to have
a higher risk a smaller, smaller, more risky, more levered
company that I can't buy and sell every day? Why
should that be more expensive? It just boggles the mind.
And I think, you know, we've seen this, this correlated belief, right,
it's a correlated belief. But from all these pension funds
and college endowments and fancy investors that you need to
(37:39):
invest like Yale, you need to invest like David Swinson,
you need to have maybe forty percent of your assets
in private equity. And I did the simple math, which
is to say, you know, if you take the aggregate
size of private equity back to companies. You know how
big are those companies relative to public companies, And they're
about two to four percent of the total revenue of
(38:02):
public companies. Right, So it's a tiny, tiny, tiny set
of companies. And so to have forty percent of your
assets and two percent of the company and two percent
of the revenue share of the companies, right, because there
are a lot of small companies, they just don't make
much money.
Speaker 2 (38:15):
That seems completely insane when you put it like that,
completely insane, But it's very nice for fund managers or
for people managing large pools of money, because it looks
better with this mothing. It looks less volatile, it looks
it looks calmer, it looks like a diversify. IM's quite
relaxing for you. Really, you don't have to deal with that,
you know, pricing every day nonsense.
Speaker 1 (38:38):
Exactly, And you get this veneer being able to tell
everyone that you improve companies, right, Like I'm a hedge
fund manager, I buy and sell shares. You know, what
do I contribute to society? What do I know about companies?
How can you feel that good about investing? Like maybe
I'm a little smarter, you're right, Like, well, with private equity,
you know, I've been on the board and I really
helped the company grow, and I've talked to them about
this new product and then we you know, we open
(38:59):
a new factory. It's sounds better. And I think it's
actually hogwash, right, Like you know, and you sort of
know it's hogwash by just looking at the LinkedIn profiles
of who works in private equity, right, Like they're all
former bankers, right if.
Speaker 2 (39:12):
This is exactly the point where I say to all
the listeners, send your hate mail directly to Dan. Don't
send it to us. Directly to Dan. He's ready.
Speaker 1 (39:22):
But it's like, you know, when, when did the two
years you spent building Excel and PowerPoint models as a
junior banker, you know, give you this great insight on
how to run like mid market industrial companies in Germany? Right?
Why does that logical? I'd be like, oh God, it's
going to do so much better under private equity management.
It's like, okay, so the junior banker from Goldman is
going to do that much better of a job than
(39:42):
like the fifty year old veteran if you're running that
business that year it seems much more plausible that what
the banker is really good at is adding a lot
of debt to the balance sheet and doing that on
acquisitions and maybe you know, dressing it up for sale
that they seem good at. But the idea that they're
better at running companies just seems a little great.
Speaker 2 (40:00):
Well, we'll find out soon with me because a lot
of private equity companies they're going to have to start
moving assets on and they can't keep handing them around
between each other. So there's going to be surely a
spate of listings coming up where we will see what
private equidey companies are really worth in public markets, and
that will be fascinating. Okay, interesting, right, something completely different.
Do you talk about gold a little in the book
(40:21):
and when and when you shouldn't invest in gold? And
we have a lot of gold bug listeners, and I'm
a little bit of a gold bug myself, so maybe
we could talk a little bit about your views on
gold and where they fit in this where it fits
in this cycle.
Speaker 1 (40:34):
Yeah, I think gold is a very important portfolio tool,
and if you think about why it's an important portfolio tool,
we need some low risk, diverse fying assets right, and
one low risk diverse fying ac is bonds, and one
low risk di burst fying acid is gold. The challenge
with bonds is that they react very neatively to inflation,
(40:54):
and our country economy has had a bit of an
inflation problem with LID and gold and in the opposite way,
or reacts positively to inflation because you can inflate the currency,
but the price of gold should be unaffected. And so
what I think is that you should depend your low
risk portfolio should alternate between bonds and gold depending on
your views of whether inflation is present. If you're worried
(41:16):
about inflation, you should have more gold and fewer bonds,
and if, on the other hand, you're worried about deflation,
you stole more bonds and less gold. But the idea
that gold has to be a tool that you're using.
It's so important and it trades so differently that it
gives your portfolio more degrees of freedom if you include
it in the parameter of things you're considering, and you
(41:37):
don't have to have a big allocation for it to
make a big difference.
Speaker 2 (41:40):
Okay, and what about bitcoin? You I notice you do
not mention at all in.
Speaker 1 (41:44):
The book, Oh dear Bitcoin.
Speaker 2 (41:48):
I mean that you clearly are not going to say, well,
bitcoin is digital gold. It's the same thing. I'm not
hearing you saying that.
Speaker 1 (41:54):
I'm not saying that because I don't think it's true.
I said that gold was a low risk asset. Right,
Look at the volatility of gold. It's like the volatility
of bonds. It is a low risk asset. Bitcoin has
the volatility of a the nastac or microcaps. Right, It's
crazily vollatile. So it's not low risk, it's high risk.
And then what's it correlated with?
Speaker 2 (42:12):
Right?
Speaker 1 (42:12):
Gold is sort of anti correlated. Gold is its own thing.
It marks to its own tomb. That's why it's valuable.
But bitcoin is not. Bitcoin is very correlated with say
that Goldman Sachs highly shorted basket of US tucks. It's
very correlated with Robinhood stock. Right. It's correlated with any
type of gambling activity that you see in public markets.
And I think it's part of a broader trend towards
(42:35):
people finding gambling opportunities in public markets as opposed to
find them betting on sports teams.
Speaker 2 (42:41):
Yeah. Interesting, do you think now as that there's lots
more institutional interest in it, and there's even to be
a lot of passive investment into bitcoin that it might
get caught up in the same sort of momentum trade
as perhaps a lot of the US tech companies have
over the last couple of years.
Speaker 1 (42:55):
I think it certainly will, and I think institutional adoption
of bitcoin today is out as smart as institutional adoption
of investing in China and twenty seventeen or twenty eighteen.
It's equally as much of a mania, and it's equally
as dumb.
Speaker 2 (43:07):
Okay, I think we have a very clear view there.
And again, just let me repeat hate mail direct to
Dan Donk. Can we find you on Twitter so they
can send your hate mail director you on Twitter, because
that's where I get most absolute What's your handle there?
Just to make apple sure it goes to you, not me.
Speaker 1 (43:20):
It's at verdad cap.
Speaker 2 (43:21):
Okay, everybody, if you feel strongly about bigcoeen, feels strongly
about private equity, strongly about any of those things, please
let Dan know directly, and do not copy me into
your aggressive tweet. Thank you.
Speaker 1 (43:33):
Okay.
Speaker 2 (43:34):
So at the end, I normally try and ask people
what they would invest in now, but I think we
have a pretty clear steer from you on the value
front that you're interested in UK equities, you're interested in
European equities. Is there any sector in particular of that
interests you, or any part of the market, or any
even any particular company that you're finding fascinating at the moment.
Speaker 1 (43:51):
You know, I actually like Eastern Europe. I find a
lot of interesting things in Poland, and I think that
people have tended to overlook Eastern Europe in particular because
the Ukraine War. But I think it also is the
most leveraged any peace deal going through that you'll make
money in Polish equities. They're very thinly traded. You have
to buy small caps, but I think it's quite attractive.
Speaker 2 (44:11):
Okay, that is interesting polysh small caps have never come
up on this podcast before. So thank you very much
for that. Congratulations, something you something youre go? Okay, last question.
Your book I think is excellent, and just to repeat
again everybody by this book, it's excellent. Everything we've talked
about is in the book, plus a whole load more.
And we didn't get onto private credit. Another fascinating chapter
(44:34):
in it, so and the bond chapter also excellent. Do
read that. But Dan, if you were going to recommend
one book written by somebody else, is there anything you've
been reading recently that you've really enjoyed and think that
would be helpful for our listeners.
Speaker 1 (44:47):
Well, I don't know about helpful to your listeners, but
by far the best book that I've read recently is
The History of the Conquest of Mexico by William Prescott,
which came out in eighteen thirty, and it tells the
unbelievable story of how Cortez conquered Mexico in fifteen tens
and as a story that I like glossed over in
the history textbooks, but it is unbelievably fascinating, you know,
(45:09):
eight hundred men conquering several hundred thousand a person civilization
in It's just an insane story and beautifully written. So
if you're looking from a break from markets, I recommend it.
Speaker 2 (45:22):
I imagine people are going to be looking for a break
from markets relatively soon this year, but we'll see. Dan,
thank you so much for joining us today and gratulations
on an excellent book. Thank you, Mareon, Thanks for listening
this week's Maren Talks Money. If you like our show, rate, review,
and subscribe Wherever you listen to podcasts and keep sending
(45:44):
questions or comments to Marin Money at Bloomberg dot net.
You can also follow me and John on Twitter or
x I'm at Marin sw and John is John Underscore Stepic.
This episode is were hosted by Me Maren Sumset Web
was produced by some Saudi production support Moses and and
special thanks to Dan Rasmussen h
Host
Merryn Somerset Webb
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