January 10, 2025 • 45 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 this week.
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.
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Episode Transcript
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Speaker 1 (00:02):
Bloomberg Audio Studios, Podcasts, radio News. Welcome to Meren Talks Money,
the podcast in which people who know the markets explain
the markets. I'm Merit suset Work. This week I'm speaking
(00:24):
with Dan Rasmussen, founder of the investment management firm Verdered 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 Investor, How
to Find a Winning Edge in 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
(00:46):
underlying theme, as Dan puts it, is the future is
hard to protect, vicually 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 eric 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
(01:07):
stock market bubbles. Are 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 2 (01:17):
Thanks for having me.
Speaker 1 (01:18):
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.
Nothing works, Oh God, absolutely absolutely. We'd be having a
(01:40):
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
actually 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 me, by forecasts from everybody in the
market about what they think is going to happen in
(02:02):
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
forecasts is wrong, well, not all of them, They'll be
one in the middle. By happen chance that that is correct.
So I wanted to start by talking about that full costs,
you say, full costs meet reality.
Speaker 3 (02:21):
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
(02:43):
ask how good are we predicting what's going to happen
three or four years from now on the side, and
I didn't. I didn't start out, and I didn't study
finance or accounting or economics in undergrad And so when
I started working 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
(03:05):
about theory and 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 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.
Speaker 2 (03:27):
How would I sort of figure this out?
Speaker 3 (03:29):
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 negatively correlated with stock market returns. In other words,
(03:52):
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,
or profits, you know what's going to happen in twenty
(04:13):
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
I found is that if you divide it into slow, medium,
(04:36):
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 percent right, the other That sounds good,
It sounds okay, right. But the challenge then is if
you say, okay, well, let's say you're forecasting really high
you know, you then think, oh, well, I should buy
(04:57):
all the companies that are forecasting really high growth. 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.
Speaker 2 (05:07):
Right.
Speaker 3 (05:07):
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
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 in total, but
a little bit worse. Whereas if you go to the
(05:29):
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 average. They return the same
as the high growth firms that achieved high growth. But
when the slow growth firms achieve high growth, which they
do fifty percent of the time, their stocks do really well.
Speaker 1 (05:45):
Okay, So knowing the growth thems 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
of reason. 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 likely
(06:08):
that the next year will be similar to the previous
year exactly.
Speaker 3 (06:11):
And this is where things get that get 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
(06:32):
day last year. And there's a wonderful study that I
updated and 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 one year, three year, five
year period. Does that forecast their growth rate over the
(06:55):
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.
Speaker 2 (07:05):
It's just pure coin flips.
Speaker 3 (07:07):
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, 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 not ei, there's no
(07:29):
way that that's true.
Speaker 2 (07:30):
But statistically it is true.
Speaker 3 (07:33):
And I think that when you start to understand that,
and you combine that 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
(07:55):
what you think relative to what the market thinks.
Speaker 2 (07:57):
And so you need to understand.
Speaker 3 (07:58):
What other people are forecasts, 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 1 (08:15):
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 do 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 forecasts come out over and
(08:36):
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,
that's a nonsense. We know it's nonsense. Why do we listen?
So tell us this lovely little weather anecdote from the
book which explains it.
Speaker 3 (08:50):
Yeah, so this is ken error. The famous economist was
in the weather Core in World War Two, and being
the genius that he was, he's and by the way
that the weather Core asked for one year forward weather
forecasts 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 there's once they're going to
(09:10):
be snow by day.
Speaker 2 (09:11):
And so he was.
Speaker 3 (09:12):
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 that laying out his argument,
and he gets a one sentence one back and it says,
(09:34):
you know, the General knows that the forecasts are are useless,
but he needs them for planning purposes.
Speaker 1 (09:40):
And then 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 3 (09:49):
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 use base rates. Right,
so you take a long historical time and you sort
of say, what's the average over this long period of time,
(10:12):
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
(10:32):
potential outcomes? And then to secondarily to say, because we
know everyone else is 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,
(10:52):
nobody knows is AI going to truly revolutionize the economy
or is that one trillion these companies are spending going
to be a to money. Maybe no one knows, you know.
And if no one knows, you know, what's the bet
that we should make.
Speaker 1 (11:06):
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 as a
game of meta analysis. That's right, 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.
(11:26):
I'm one of the 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
equity is worth the value of all the dividends that'll
be paid to the owner of that equity in the future.
And people spend hours on these models, don't they days
days working out is actually worth But as they have
absolutely no idea whatsoever what those dividends are going to be,
(11:48):
the final number they come up with is nonsense.
Speaker 3 (11:50):
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 taxing home
exactly for the next five years, And.
Speaker 2 (12:05):
Just model that first.
Speaker 3 (12:07):
And if you can't do that accurately, you know, why
do you think you can do it for Coca Cola?
Speaker 2 (12:10):
Yeah?
Speaker 1 (12:11):
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, etc.
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 you can extrapolate from
(12:34):
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 do it much better with chips.
Speaker 3 (12:56):
Well, it's a wonderful paper by a consulting economist here
for a day at Sam Hanson as the presser at
our business school. Really brilliant guy. And I love the
shipping industry. Actually spend 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.
Speaker 2 (13:15):
I mean, it's just so cool.
Speaker 3 (13:17):
But there's this fascinating 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.
(13:37):
It turns out that 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
(13:59):
from now, the ships are delivered 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
(14:21):
of ships that then show up on 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
(14:42):
cycles and driving shipping rates 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's the fact that I thought it means that
(15:04):
everyone else is thinking at the same time.
Speaker 1 (15:06):
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.
Speaker 2 (15:13):
Well, I think there has.
Speaker 3 (15:14):
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 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 winds search, Amazon winds, retail. You know, Microsoft winds productivity.
(15:40):
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
tech industry.
Speaker 1 (15:55):
And we can't choose them, and we can't choose the winner.
Speaker 3 (15:57):
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 1 (16:11):
And does that mean that as investors we should avoid
all of them?
Speaker 2 (16:14):
I think so. I think they're all terrifying.
Speaker 3 (16:17):
There's too much hype, too much optimism. How long have
we thought that we would have robots that could think
like us?
Speaker 2 (16:23):
Right?
Speaker 3 (16:23):
Like, this isn't the idea. Humans that 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.
Speaker 1 (16:34):
I don't think why do we think why do you
think we're at trying to do 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 3 (16:42):
Well, it's the it's the ultimate vanity to create something
in your own image, isn't it.
Speaker 2 (16:48):
The closes complex?
Speaker 1 (16:52):
Okay? One of the tiny questions, not.
Speaker 2 (16:54):
That any of our friends in the tech industry.
Speaker 1 (16:56):
Of god, 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 2 (17:07):
Yeah?
Speaker 3 (17:07):
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 force
this idea of excessive volatility. What Schiller did, which is
so brilliant, They said, you know, if the dividend discount
model is right, and the net present values equal to
(17:30):
some of the future cash flows discount by the interest rates,
and if we know future cash flows and we know
future indust rates, 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 changes
(17:51):
and fundamentals.
Speaker 1 (17:51):
Okay, so even if you had the information for the model,
it still wouldn't work exactly.
Speaker 3 (17:57):
Even with full pressions, you can explain a very high
percentage of volatility. And so where is this excess.
Speaker 2 (18:03):
Volatility coming from?
Speaker 3 (18:05):
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, 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
(18:28):
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,
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
(18:51):
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, How could
a stock be down thirty percent in a day if
it wasn't a mistake yesterday?
Speaker 2 (19:05):
Right?
Speaker 3 (19:05):
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 not be. How could anybody
who's ever experienced markets not know the mistakes are part
(19:27):
of things? And how is that therefore driving rebalancing decisions?
And then how can we as investors think through if.
Speaker 2 (19:33):
Other people are making mistakes, if we're making mistakes.
Speaker 3 (19:35):
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 market volatility.
Speaker 1 (19:46):
Okay, so was the answer, how are we going to
build that portfolio?
Speaker 3 (19:49):
What we're looking for is some barometer of optimism or pessimism, right,
If we 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, 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
(20:10):
we have a very simple metric for doing that. And
in the stock market, it's valuations.
Speaker 2 (20:14):
Right. You can pick almost.
Speaker 3 (20:15):
Any multiple, right, revenue multiples or book multiple, and you
can erase to haksana 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
last few years it hasn't in the United States.
Speaker 2 (20:36):
We should talk about why, but it.
Speaker 3 (20:38):
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 about this separately, apply that to thinking
about economy, whole markets and whole economy. But I think
(21:00):
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 think it's all well and good for me
to argue that we should use valuation ratios as a
metcoroptimism or pessimism, and that we should be long things
(21:22):
other people are pessimistic about.
Speaker 2 (21:23):
And there's an intuitive.
Speaker 3 (21:24):
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 hasn't worked in the US,
and so why And actually there was a period from
COVID until the release of chat GBT when it did work,
and then chat GBT just totally newked to value investing again,
and so what I like to say about value investing.
Speaker 2 (21:46):
What's going on in the market today is.
Speaker 3 (21:48):
That we've had a period from in the twenty tens
where there were a very small number of companies where
they were forecasts to grow fast, and then they grew
fast than the forecast, and they did that a few
years in a row. That was the sort of fan
mag stocks, as they.
Speaker 2 (22:05):
Were called them.
Speaker 3 (22:07):
What is that a tribunal too, I'd say it was
an innovation wave.
Speaker 2 (22:09):
And these innovation waves happen, they do.
Speaker 3 (22:12):
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
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.
Speaker 2 (22:29):
But in early windows they can be huge, huge booms.
And that's what we're in the middle of.
Speaker 1 (22:34):
In the middle of or towards the end of.
Speaker 3 (22:36):
It depends on the future of AI and everything hinges
on that. 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 and
(22:59):
then a client 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 least
(23:20):
the SPACs are companies.
Speaker 2 (23:21):
Well the hell is fart coin.
Speaker 3 (23:22):
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
linear math problem. And we know that there are certain
things that we can rely on and should rely on,
which is betting against tubris right, betting on things others
(23:46):
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 1 (24:02):
I mean, the other thing you can say, surely is
that value investing doesn't work during a bubble.
Speaker 2 (24:06):
It doesn't work during a bubble.
Speaker 1 (24:07):
Aunts 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 2 (24:21):
I think so too.
Speaker 3 (24:22):
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 Dallio, Peter Lynch, Howard 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 aboute about him,
(24:45):
Ray Daalio 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, investor are often you know,
smart data driven people. You can pick up on these
things instead, the evaluations are too high. The problem is
(25:06):
that smart investors tend to be way too early. Right,
the bubble didn't burst for five years, right, and meeps up,
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.
It actually turned out that value investing, if you looked
at it from ninety five to ninety nine, it looks
(25:28):
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 bursts so quickly that
value investing, international diversification, 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, but being guided by
(25:51):
a sensitivity towards these behavioral insights that it doesn't you know,
don't 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 in the 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, you know what should
(26:12):
I do? I should stay away.
Speaker 1 (26:14):
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 in value absolutely.
Speaker 3 (26:25):
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.
Speaker 2 (26:34):
Right.
Speaker 3 (26:35):
There are many reasons why passive is a wonderful, wonderful
thing for investors, right, It's been great for consumers.
Speaker 2 (26:40):
I love passive investing. I love Vanguard.
Speaker 3 (26:43):
The only problem I see, and maybe there 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 1 (27:04):
Yeah.
Speaker 3 (27:04):
And I think when I last did this math, about
eighty percent of Vanguard's assets were either in the S
and P five hundred or in the Vanguard Total Stock
Market Fund.
Speaker 2 (27:14):
Yeah. Right.
Speaker 3 (27:14):
In other words, passive has hrded people into the same idea,
and when Mordecai Kurtz, who has had that idea of
rational expectations.
Speaker 2 (27:24):
So the thing that we need to be most careful
of is correlated beliefs, right.
Speaker 3 (27:28):
Correlated beliefs are the will create risk When investors' beliefs
are too correlated, when everyone thinks the same thing, that's
the problem.
Speaker 1 (27:36):
And there was an interesting bit in the book where
you note that around seventy five percent of the US
relative app 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 3 (27:51):
Which is always the case, Marion, because if you go
back to Schiller's work, it's always valuation changes, it's always
changes in our expectations about the future that dry the
majority of stock market palito is always the case.
Speaker 1 (28:03):
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 a little bit more closely
should look at not necessarily at market cap when they
come to invest internationally, but look perhaps at percentagive 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
(28:24):
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 3 (28:33):
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.
Speaker 2 (28:43):
And when we see.
Speaker 3 (28:44):
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 just not where other
people are looking. I actually love the UK and Europe.
Speaker 1 (28:58):
We love to hear that give the Europe bit. We
love to hear you love the.
Speaker 2 (29:01):
UK, you know.
Speaker 3 (29:04):
And actually it was it was funny. I was I
was visiting with a friend who was a big Brexit supporter,
and I follow politics as closely as any 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, you know, pull up
(29:27):
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, and all of
a 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
(29:48):
the common narrative about Europe as a whole is wrong.
And I thought I do.
Speaker 1 (29:51):
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 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 GDPEP ahead doesn't tell the same
story as GDP. We've had a very fast growing growing population.
Speaker 3 (30:14):
Sorry, all right, no, no, that's helpful moment. I'll go
back and read visit 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 average, is way cheap relative to the
US U CAN in particular. And what's sort of the
(30:37):
second layer of that analysis, because you don't want to
just be a contrarian for the sake of betorian 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.
Speaker 2 (30:52):
Profit to asset.
Speaker 3 (30:54):
European companies are really high quality businesses. They're very well run,
they're very hymerrich, and they're a very higher return asset.
And in fact, the sort of leniars have actually that
sort of capital starvation has forced the return on assets
to go higher. The created higher discount rates, higher bar
for new investments, and so when you look at Europe,
(31:14):
you're not just buying really cheap companies, you're buying really cheap,
really well run, really high return on assets.
Speaker 1 (31:19):
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 2 (31:26):
The US, exactly. And it's funny.
Speaker 3 (31:30):
I did this analysis where I took share of revenue
in the US, and then I said 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. And it turns out that
(31:50):
the share of revenue in the US doesn't matter at all,
and all that matters is where the company's listed, and
I think that sort of relates to this passive investing
or the sort of structure of investing that und enlisted
companies just treated differently than the US last.
Speaker 1 (32:02):
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 3 (32:15):
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?
Speaker 2 (32:37):
Right? How far off of a piece deal are we?
Speaker 3 (32:38):
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.
Speaker 2 (32:51):
They haven't exercised that option.
Speaker 1 (32:52):
Okay, certainly not exercising yet, we have not, but.
Speaker 3 (32:56):
They bought the option. Brexit bought them the option, and
there's a power, the potential deregulation. And if you in
Europe can deregulate, and if they can solve the Ukraine issue, right, like,
why wouldn't valuations go off?
Speaker 1 (33:08):
There is the other big problem in Europe under the
UK's energy prices right, particularly in the UK is stunning
lee high industrial electricity prices.
Speaker 3 (33:16):
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 aren't paths to do it.
Speaker 1 (33:23):
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,
(33:44):
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 sector.
Speaker 3 (33:53):
There are a few sort of very important facts to
know about private equity. For the first, you know what
is private equity? Well, what is a private acta you know,
as opposed to a public equity, And it's really two
things are different.
Speaker 2 (34:05):
Right. The first thing is that private.
Speaker 3 (34:06):
Equities tend to be much smaller than public equities.
Speaker 2 (34:10):
That they're all microcaps.
Speaker 3 (34:11):
They have about a two hundred million dollars valuation on
equity market cap on average, right, 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 Forourtullion. 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 higher
default rates than big companies. We know they're riskier, they're
less diversified, their lower margin.
Speaker 2 (34:32):
Right, all of these things.
Speaker 3 (34:33):
Are stylized true facts about small companies. Of course, right,
once you get bigger, you're more stable you're more diversified,
you tend to scale vanges, higher margins, right, less volatile,
et cetera. But these are small companies, not just small,
but really small.
Speaker 2 (34:47):
Right.
Speaker 3 (34:47):
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 I have to remember is
that private equity backed companies are a very levered. Generally,
fifty to sixty percent of their total valuation is funded
by debt, and that's mostly coming now from private credit,
(35:08):
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 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.
(35:30):
That is reflective of the underlying risk and the underlying
volatility of these businesses. Now, the reason people don't think
it's risky is because it's private, and so you only
get a mark once a quarter. And who 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.
(35:53):
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 fair very risky, And of
course they are.
Speaker 2 (36:02):
They're very risky.
Speaker 3 (36:03):
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
(36:25):
these tech the tech industry is massively going to hurt
private equity. It's become a highly levered bit on microcap
software companies and.
Speaker 1 (36:34):
Also very expensive. I'm one of the things about to
when when the whole idea that you could invest in
private equity is a massive diversify. First began was private
eqty companies but very cheap, right, well, you could get
them at a stonking 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 listed.
Speaker 3 (36:54):
Right, Like, why should I pay more to have a
higher risk a smaller, smaller, more risky, more lever 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
(37:15):
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 backed companies, you know how big
are those companies relative to public companies? And they're about
(37:35):
two to four percent of the total revenue of 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 1 (37:52):
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 pool with money, because it looks
better with this moothing. It looks less volatile, it looks
it looks calmer, it looks like a Diversifyer's quite relaxing
for you. Really, you don't have to deal with that,
you know, pricing every day nonsense.
Speaker 3 (38:14):
Exactly, and you get this veneer being able to tell
everyone that you improve companies, right, like, yes, 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,
(38:34):
we open a new factory. Its 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 this is.
Speaker 1 (38:49):
Exactly the point where I say to all the listeners,
send your hate mail directly to Dan, don't send it
to us, and directly to Dan. He's ready.
Speaker 3 (38:58):
But it's like, you know, when did 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?
Speaker 2 (39:09):
Right? Why does that logical?
Speaker 3 (39:11):
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 like the fifty year
old veteran.
Speaker 1 (39:20):
Oh, if you're running that business for thirty years, it
seems much more plausible that what the banker is really
good at is adding a lot of debt to the.
Speaker 3 (39:27):
Balance sheet and doing ad on acquisitions and maybe you know,
dressing it up for sale. They seem good at, but
the idea that they're better at running companies just seems
a little crazy.
Speaker 1 (39:37):
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 equity companies are really worth in public markets, and
that will be fascinating. Okay, interesting, right, something completely different.
You talk about gold a little in the book and
(39:58):
when and when you shouldn't invest in golden You 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 3 (40:10):
Yeah, I think gold is a very important portfolio tool,
and if you think about why it's.
Speaker 2 (40:16):
An important portfolio tool.
Speaker 3 (40:18):
We need some low risk diversifying assets, right, and one
low risk, diverse fying acid is bonds, and one low
risk diverse fying acid is gold. The challenge with bonds
is that they react very natively to inflation, and our
country economy has had a bit of an inflation problem
of late and gold, in the opposite way, reacts positively
(40:38):
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 about inflation,
you should have more gold and fewer bonds, and if,
on the other hand, you're worried about deflation, you shouldole
more bonds.
Speaker 2 (40:58):
And less gold.
Speaker 3 (41:00):
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 don't have to have a big allocation for
it to make a big difference.
Speaker 1 (41:16):
Okay, and what about bitcoin? You I notice you do
not mention at all in the.
Speaker 2 (41:21):
Book, Oh dear bitcoin.
Speaker 1 (41:24):
I mean is 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 2 (41:30):
I'm not saying that because I don't think it's true.
Speaker 3 (41:32):
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 vallatile. So it's not low risk, it's high risk.
And then what's it correlated with?
Speaker 2 (41:48):
Right?
Speaker 3 (41:48):
Gold is sort of anti correlated. Gold's 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 sacks highly shorted as good of US talks.
It's very correlated with robinhood stock. Right, It's correlated with
any type of gambling activity that you see in public markets.
Speaker 2 (42:08):
And I think it's.
Speaker 3 (42:09):
Part of a broader trend towards people finding gambling opportunities
in public markets as opposed to find them betting on
sports teams.
Speaker 1 (42:17):
Yeah. Interesting. Do you think now, as that there's lots
more institutional interest in it and there's even 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 3 (42:31):
I think it certainly will, and I think institutional adoption
of bitcoin today is about 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 1 (42:43):
Okay, I think we have a very clear view there.
And again, just let me repeat hate mail direct to
Dan done. Can we find you on Twitter so they
can send you a hate mail? Director you on Twitter,
because that's where I get those? Absolutely, what'd you handle there?
Just to make apple sure it goes to you.
Speaker 2 (42:56):
Not me? It's at verdad cap.
Speaker 1 (42:58):
Okay, everybody, if you feel strongly about big cooeen filst,
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. Okay. 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 Europeean equities. Is there
(43:20):
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 2 (43:28):
You know, I actually like Eastern Europe.
Speaker 3 (43:30):
I find a lot of interesting things in Poland and
I think that people have tended to overlook Eastern Europe
in particular because of the Ukraine War, but I think
it also is the most leverage to any peace deal
going through that you'll make money in Polish equities.
Speaker 2 (43:43):
They're very thinly traded.
Speaker 3 (43:44):
You have to buy small caps, but I think it's
quite attractive.
Speaker 1 (43:48):
Okay, that is interesting. Poly small caps have never come
up on this podcast before, So thank you very much
for that. Congratulations something something you go. Okay, last ques
your book. I think it's excellent, and just to repeat again,
everybody by this book is excellent. Everything we've talked about
is in the books. A whole load more we didn't
(44:08):
get onto Private credit. Another fascinating chapter 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 would be helpful for our listeners.
Speaker 3 (44:23):
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 Corte has 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,
(44:45):
eight hundred men conquering several hundred thousand a person civilization
in It's just an insane.
Speaker 2 (44:54):
Story and beautifully written.
Speaker 3 (44:55):
So if you're looking from a break from markets, I
recommend it.
Speaker 1 (44:58):
I imagine people are going to be a for a
break from markets relatively soon this year. But we'll see you.
Speaker 2 (45:04):
Dan.
Speaker 1 (45:04):
Thank you so much for joining us today and congratulations
on an excellent book. Thank you, Marion, thanks for listening
for this week's Maren Talks Money. If you like our show,
rate review and subscribe wherever you listen to podcasts, and
keep sending questions or comments to Marin Money at Bloomberg
dot net. You can also follow me and John on
(45:26):
Twitter or x. I'm at Marin sw and John is
John Underscore Stepic. This episode were hosted by Me Maren
Sumset Web was produced by Samasadi, Production support from Moses
and and special thanks to Dan Rasmussen.
Bloomberg Audio Studios, Podcasts, radio News. Welcome to Meren Talks Money,
the podcast in which people who know the markets explain
the markets. I'm Merit suset Work. This week I'm speaking
(00:24):
with Dan Rasmussen, founder of the investment management firm Verdered 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 Investor, How
to Find a Winning Edge in 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
(00:46):
underlying theme, as Dan puts it, is the future is
hard to protect, vicually 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 eric 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
(01:07):
stock market bubbles. Are 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 2 (01:17):
Thanks for having me.
Speaker 1 (01:18):
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.
Nothing works, Oh God, absolutely absolutely. We'd be having a
(01:40):
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
actually 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 me, by forecasts from everybody in the
market about what they think is going to happen in
(02:02):
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
forecasts is wrong, well, not all of them, They'll be
one in the middle. By happen chance that that is correct.
So I wanted to start by talking about that full costs,
you say, full costs meet reality.
Speaker 3 (02:21):
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
(02:43):
ask how good are we predicting what's going to happen
three or four years from now on the side, and
I didn't. I didn't start out, and I didn't study
finance or accounting or economics in undergrad And so when
I started working 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
(03:05):
about theory and 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 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.
Speaker 2 (03:27):
How would I sort of figure this out?
Speaker 3 (03:29):
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 negatively correlated with stock market returns. In other words,
(03:52):
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,
or profits, you know what's going to happen in twenty
(04:13):
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
I found is that if you divide it into slow, medium,
(04:36):
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 percent right, the other That sounds good,
It sounds okay, right. But the challenge then is if
you say, okay, well, let's say you're forecasting really high
you know, you then think, oh, well, I should buy
(04:57):
all the companies that are forecasting really high growth. 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.
Speaker 2 (05:07):
Right.
Speaker 3 (05:07):
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
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 in total, but
a little bit worse. Whereas if you go to the
(05:29):
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 average. They return the same
as the high growth firms that achieved high growth. But
when the slow growth firms achieve high growth, which they
do fifty percent of the time, their stocks do really well.
Speaker 1 (05:45):
Okay, So knowing the growth thems 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
of reason. 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 likely
(06:08):
that the next year will be similar to the previous
year exactly.
Speaker 3 (06:11):
And this is where things get that get 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
(06:32):
day last year. And there's a wonderful study that I
updated and 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 one year, three year, five
year period. Does that forecast their growth rate over the
(06:55):
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.
Speaker 2 (07:05):
It's just pure coin flips.
Speaker 3 (07:07):
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, 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 not ei, there's no
(07:29):
way that that's true.
Speaker 2 (07:30):
But statistically it is true.
Speaker 3 (07:33):
And I think that when you start to understand that,
and you combine that 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
(07:55):
what you think relative to what the market thinks.
Speaker 2 (07:57):
And so you need to understand.
Speaker 3 (07:58):
What other people are forecasts, 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 1 (08:15):
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 do 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 forecasts come out over and
(08:36):
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,
that's a nonsense. We know it's nonsense. Why do we listen?
So tell us this lovely little weather anecdote from the
book which explains it.
Speaker 3 (08:50):
Yeah, so this is ken error. The famous economist was
in the weather Core in World War Two, and being
the genius that he was, he's and by the way
that the weather Core asked for one year forward weather
forecasts 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 there's once they're going to
(09:10):
be snow by day.
Speaker 2 (09:11):
And so he was.
Speaker 3 (09:12):
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 that laying out his argument,
and he gets a one sentence one back and it says,
(09:34):
you know, the General knows that the forecasts are are useless,
but he needs them for planning purposes.
Speaker 1 (09:40):
And then 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 3 (09:49):
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 use base rates. Right,
so you take a long historical time and you sort
of say, what's the average over this long period of time,
(10:12):
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
(10:32):
potential outcomes? And then to secondarily to say, because we
know everyone else is 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,
(10:52):
nobody knows is AI going to truly revolutionize the economy
or is that one trillion these companies are spending going
to be a to money. Maybe no one knows, you know.
And if no one knows, you know, what's the bet
that we should make.
Speaker 1 (11:06):
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 as a
game of meta analysis. That's right, 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.
(11:26):
I'm one of the 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
equity is worth the value of all the dividends that'll
be paid to the owner of that equity in the future.
And people spend hours on these models, don't they days
days working out is actually worth But as they have
absolutely no idea whatsoever what those dividends are going to be,
(11:48):
the final number they come up with is nonsense.
Speaker 3 (11:50):
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 taxing home
exactly for the next five years, And.
Speaker 2 (12:05):
Just model that first.
Speaker 3 (12:07):
And if you can't do that accurately, you know, why
do you think you can do it for Coca Cola?
Speaker 2 (12:10):
Yeah?
Speaker 1 (12:11):
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, etc.
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 you can extrapolate from
(12:34):
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 do it much better with chips.
Speaker 3 (12:56):
Well, it's a wonderful paper by a consulting economist here
for a day at Sam Hanson as the presser at
our business school. Really brilliant guy. And I love the
shipping industry. Actually spend 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.
Speaker 2 (13:15):
I mean, it's just so cool.
Speaker 3 (13:17):
But there's this fascinating 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.
(13:37):
It turns out that 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
(13:59):
from now, the ships are delivered 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
(14:21):
of ships that then show up on 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
(14:42):
cycles and driving shipping rates 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's the fact that I thought it means that
(15:04):
everyone else is thinking at the same time.
Speaker 1 (15:06):
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.
Speaker 2 (15:13):
Well, I think there has.
Speaker 3 (15:14):
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 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 winds search, Amazon winds, retail. You know, Microsoft winds productivity.
(15:40):
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
tech industry.
Speaker 1 (15:55):
And we can't choose them, and we can't choose the winner.
Speaker 3 (15:57):
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 1 (16:11):
And does that mean that as investors we should avoid
all of them?
Speaker 2 (16:14):
I think so. I think they're all terrifying.
Speaker 3 (16:17):
There's too much hype, too much optimism. How long have
we thought that we would have robots that could think
like us?
Speaker 2 (16:23):
Right?
Speaker 3 (16:23):
Like, this isn't the idea. Humans that 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.
Speaker 1 (16:34):
I don't think why do we think why do you
think we're at trying to do 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 3 (16:42):
Well, it's the it's the ultimate vanity to create something
in your own image, isn't it.
Speaker 2 (16:48):
The closes complex?
Speaker 1 (16:52):
Okay? One of the tiny questions, not.
Speaker 2 (16:54):
That any of our friends in the tech industry.
Speaker 1 (16:56):
Of god, 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 2 (17:07):
Yeah?
Speaker 3 (17:07):
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 force
this idea of excessive volatility. What Schiller did, which is
so brilliant, They said, you know, if the dividend discount
model is right, and the net present values equal to
(17:30):
some of the future cash flows discount by the interest rates,
and if we know future cash flows and we know
future indust rates, 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 changes
(17:51):
and fundamentals.
Speaker 1 (17:51):
Okay, so even if you had the information for the model,
it still wouldn't work exactly.
Speaker 3 (17:57):
Even with full pressions, you can explain a very high
percentage of volatility. And so where is this excess.
Speaker 2 (18:03):
Volatility coming from?
Speaker 3 (18:05):
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, 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
(18:28):
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,
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
(18:51):
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, How could
a stock be down thirty percent in a day if
it wasn't a mistake yesterday?
Speaker 2 (19:05):
Right?
Speaker 3 (19:05):
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 not be. How could anybody
who's ever experienced markets not know the mistakes are part
(19:27):
of things? And how is that therefore driving rebalancing decisions?
And then how can we as investors think through if.
Speaker 2 (19:33):
Other people are making mistakes, if we're making mistakes.
Speaker 3 (19:35):
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 market volatility.
Speaker 1 (19:46):
Okay, so was the answer, how are we going to
build that portfolio?
Speaker 3 (19:49):
What we're looking for is some barometer of optimism or pessimism, right,
If we 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, 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
(20:10):
we have a very simple metric for doing that. And
in the stock market, it's valuations.
Speaker 2 (20:14):
Right. You can pick almost.
Speaker 3 (20:15):
Any multiple, right, revenue multiples or book multiple, and you
can erase to haksana 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
last few years it hasn't in the United States.
Speaker 2 (20:36):
We should talk about why, but it.
Speaker 3 (20:38):
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 about this separately, apply that to thinking
about economy, whole markets and whole economy. But I think
(21:00):
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 think it's all well and good for me
to argue that we should use valuation ratios as a
metcoroptimism or pessimism, and that we should be long things
(21:22):
other people are pessimistic about.
Speaker 2 (21:23):
And there's an intuitive.
Speaker 3 (21:24):
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 hasn't worked in the US,
and so why And actually there was a period from
COVID until the release of chat GBT when it did work,
and then chat GBT just totally newked to value investing again,
and so what I like to say about value investing.
Speaker 2 (21:46):
What's going on in the market today is.
Speaker 3 (21:48):
That we've had a period from in the twenty tens
where there were a very small number of companies where
they were forecasts to grow fast, and then they grew
fast than the forecast, and they did that a few
years in a row. That was the sort of fan
mag stocks, as they.
Speaker 2 (22:05):
Were called them.
Speaker 3 (22:07):
What is that a tribunal too, I'd say it was
an innovation wave.
Speaker 2 (22:09):
And these innovation waves happen, they do.
Speaker 3 (22:12):
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
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.
Speaker 2 (22:29):
But in early windows they can be huge, huge booms.
And that's what we're in the middle of.
Speaker 1 (22:34):
In the middle of or towards the end of.
Speaker 3 (22:36):
It depends on the future of AI and everything hinges
on that. 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 and
(22:59):
then a client 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 least
(23:20):
the SPACs are companies.
Speaker 2 (23:21):
Well the hell is fart coin.
Speaker 3 (23:22):
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
linear math problem. And we know that there are certain
things that we can rely on and should rely on,
which is betting against tubris right, betting on things others
(23:46):
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 1 (24:02):
I mean, the other thing you can say, surely is
that value investing doesn't work during a bubble.
Speaker 2 (24:06):
It doesn't work during a bubble.
Speaker 1 (24:07):
Aunts 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 2 (24:21):
I think so too.
Speaker 3 (24:22):
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 Dallio, Peter Lynch, Howard 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 aboute about him,
(24:45):
Ray Daalio 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, investor are often you know,
smart data driven people. You can pick up on these
things instead, the evaluations are too high. The problem is
(25:06):
that smart investors tend to be way too early. Right,
the bubble didn't burst for five years, right, and meeps up,
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.
It actually turned out that value investing, if you looked
at it from ninety five to ninety nine, it looks
(25:28):
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 bursts so quickly that
value investing, international diversification, 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, but being guided by
(25:51):
a sensitivity towards these behavioral insights that it doesn't you know,
don't 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 in the 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, you know what should
(26:12):
I do? I should stay away.
Speaker 1 (26:14):
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 in value absolutely.
Speaker 3 (26:25):
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.
Speaker 2 (26:34):
Right.
Speaker 3 (26:35):
There are many reasons why passive is a wonderful, wonderful
thing for investors, right, It's been great for consumers.
Speaker 2 (26:40):
I love passive investing. I love Vanguard.
Speaker 3 (26:43):
The only problem I see, and maybe there 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 1 (27:04):
Yeah.
Speaker 3 (27:04):
And I think when I last did this math, about
eighty percent of Vanguard's assets were either in the S
and P five hundred or in the Vanguard Total Stock
Market Fund.
Speaker 2 (27:14):
Yeah. Right.
Speaker 3 (27:14):
In other words, passive has hrded people into the same idea,
and when Mordecai Kurtz, who has had that idea of
rational expectations.
Speaker 2 (27:24):
So the thing that we need to be most careful
of is correlated beliefs, right.
Speaker 3 (27:28):
Correlated beliefs are the will create risk When investors' beliefs
are too correlated, when everyone thinks the same thing, that's
the problem.
Speaker 1 (27:36):
And there was an interesting bit in the book where
you note that around seventy five percent of the US
relative app 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 3 (27:51):
Which is always the case, Marion, because if you go
back to Schiller's work, it's always valuation changes, it's always
changes in our expectations about the future that dry the
majority of stock market palito is always the case.
Speaker 1 (28:03):
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 a little bit more closely
should look at not necessarily at market cap when they
come to invest internationally, but look perhaps at percentagive 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
(28:24):
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 3 (28:33):
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.
Speaker 2 (28:43):
And when we see.
Speaker 3 (28:44):
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 just not where other
people are looking. I actually love the UK and Europe.
Speaker 1 (28:58):
We love to hear that give the Europe bit. We
love to hear you love the.
Speaker 2 (29:01):
UK, you know.
Speaker 3 (29:04):
And actually it was it was funny. I was I
was visiting with a friend who was a big Brexit supporter,
and I follow politics as closely as any 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, you know, pull up
(29:27):
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, and all of
a 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
(29:48):
the common narrative about Europe as a whole is wrong.
And I thought I do.
Speaker 1 (29:51):
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 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 GDPEP ahead doesn't tell the same
story as GDP. We've had a very fast growing growing population.
Speaker 3 (30:14):
Sorry, all right, no, no, that's helpful moment. I'll go
back and read visit 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 average, is way cheap relative to the
US U CAN in particular. And what's sort of the
(30:37):
second layer of that analysis, because you don't want to
just be a contrarian for the sake of betorian 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.
Speaker 2 (30:52):
Profit to asset.
Speaker 3 (30:54):
European companies are really high quality businesses. They're very well run,
they're very hymerrich, and they're a very higher return asset.
And in fact, the sort of leniars have actually that
sort of capital starvation has forced the return on assets
to go higher. The created higher discount rates, higher bar
for new investments, and so when you look at Europe,
(31:14):
you're not just buying really cheap companies, you're buying really cheap,
really well run, really high return on assets.
Speaker 1 (31:19):
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 2 (31:26):
The US, exactly. And it's funny.
Speaker 3 (31:30):
I did this analysis where I took share of revenue
in the US, and then I said 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. And it turns out that
(31:50):
the share of revenue in the US doesn't matter at all,
and all that matters is where the company's listed, and
I think that sort of relates to this passive investing
or the sort of structure of investing that und enlisted
companies just treated differently than the US last.
Speaker 1 (32:02):
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 3 (32:15):
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?
Speaker 2 (32:37):
Right? How far off of a piece deal are we?
Speaker 3 (32:38):
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.
Speaker 2 (32:51):
They haven't exercised that option.
Speaker 1 (32:52):
Okay, certainly not exercising yet, we have not, but.
Speaker 3 (32:56):
They bought the option. Brexit bought them the option, and
there's a power, the potential deregulation. And if you in
Europe can deregulate, and if they can solve the Ukraine issue, right, like,
why wouldn't valuations go off?
Speaker 1 (33:08):
There is the other big problem in Europe under the
UK's energy prices right, particularly in the UK is stunning
lee high industrial electricity prices.
Speaker 3 (33:16):
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 aren't paths to do it.
Speaker 1 (33:23):
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,
(33:44):
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 sector.
Speaker 3 (33:53):
There are a few sort of very important facts to
know about private equity. For the first, you know what
is private equity? Well, what is a private acta you know,
as opposed to a public equity, And it's really two
things are different.
Speaker 2 (34:05):
Right. The first thing is that private.
Speaker 3 (34:06):
Equities tend to be much smaller than public equities.
Speaker 2 (34:10):
That they're all microcaps.
Speaker 3 (34:11):
They have about a two hundred million dollars valuation on
equity market cap on average, right, 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 Forourtullion. 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 higher
default rates than big companies. We know they're riskier, they're
less diversified, their lower margin.
Speaker 2 (34:32):
Right, all of these things.
Speaker 3 (34:33):
Are stylized true facts about small companies. Of course, right,
once you get bigger, you're more stable you're more diversified,
you tend to scale vanges, higher margins, right, less volatile,
et cetera. But these are small companies, not just small,
but really small.
Speaker 2 (34:47):
Right.
Speaker 3 (34:47):
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 I have to remember is
that private equity backed companies are a very levered. Generally,
fifty to sixty percent of their total valuation is funded
by debt, and that's mostly coming now from private credit,
(35:08):
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 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.
(35:30):
That is reflective of the underlying risk and the underlying
volatility of these businesses. Now, the reason people don't think
it's risky is because it's private, and so you only
get a mark once a quarter. And who 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.
(35:53):
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 fair very risky, And of
course they are.
Speaker 2 (36:02):
They're very risky.
Speaker 3 (36:03):
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
(36:25):
these tech the tech industry is massively going to hurt
private equity. It's become a highly levered bit on microcap
software companies and.
Speaker 1 (36:34):
Also very expensive. I'm one of the things about to
when when the whole idea that you could invest in
private equity is a massive diversify. First began was private
eqty companies but very cheap, right, well, you could get
them at a stonking 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 listed.
Speaker 3 (36:54):
Right, Like, why should I pay more to have a
higher risk a smaller, smaller, more risky, more lever 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
(37:15):
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 backed companies, you know how big
are those companies relative to public companies? And they're about
(37:35):
two to four percent of the total revenue of 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 1 (37:52):
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 pool with money, because it looks
better with this moothing. It looks less volatile, it looks
it looks calmer, it looks like a Diversifyer's quite relaxing
for you. Really, you don't have to deal with that,
you know, pricing every day nonsense.
Speaker 3 (38:14):
Exactly, and you get this veneer being able to tell
everyone that you improve companies, right, like, yes, 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,
(38:34):
we open a new factory. Its 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 this is.
Speaker 1 (38:49):
Exactly the point where I say to all the listeners,
send your hate mail directly to Dan, don't send it
to us, and directly to Dan. He's ready.
Speaker 3 (38:58):
But it's like, you know, when did 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?
Speaker 2 (39:09):
Right? Why does that logical?
Speaker 3 (39:11):
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 like the fifty year
old veteran.
Speaker 1 (39:20):
Oh, if you're running that business for thirty years, it
seems much more plausible that what the banker is really
good at is adding a lot of debt to the.
Speaker 3 (39:27):
Balance sheet and doing ad on acquisitions and maybe you know,
dressing it up for sale. They seem good at, but
the idea that they're better at running companies just seems
a little crazy.
Speaker 1 (39:37):
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 equity companies are really worth in public markets, and
that will be fascinating. Okay, interesting, right, something completely different.
You talk about gold a little in the book and
(39:58):
when and when you shouldn't invest in golden You 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 3 (40:10):
Yeah, I think gold is a very important portfolio tool,
and if you think about why it's.
Speaker 2 (40:16):
An important portfolio tool.
Speaker 3 (40:18):
We need some low risk diversifying assets, right, and one
low risk, diverse fying acid is bonds, and one low
risk diverse fying acid is gold. The challenge with bonds
is that they react very natively to inflation, and our
country economy has had a bit of an inflation problem
of late and gold, in the opposite way, reacts positively
(40:38):
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 about inflation,
you should have more gold and fewer bonds, and if,
on the other hand, you're worried about deflation, you shouldole
more bonds.
Speaker 2 (40:58):
And less gold.
Speaker 3 (41:00):
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 don't have to have a big allocation for
it to make a big difference.
Speaker 1 (41:16):
Okay, and what about bitcoin? You I notice you do
not mention at all in the.
Speaker 2 (41:21):
Book, Oh dear bitcoin.
Speaker 1 (41:24):
I mean is 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 2 (41:30):
I'm not saying that because I don't think it's true.
Speaker 3 (41:32):
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 vallatile. So it's not low risk, it's high risk.
And then what's it correlated with?
Speaker 2 (41:48):
Right?
Speaker 3 (41:48):
Gold is sort of anti correlated. Gold's 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 sacks highly shorted as good of US talks.
It's very correlated with robinhood stock. Right, It's correlated with
any type of gambling activity that you see in public markets.
Speaker 2 (42:08):
And I think it's.
Speaker 3 (42:09):
Part of a broader trend towards people finding gambling opportunities
in public markets as opposed to find them betting on
sports teams.
Speaker 1 (42:17):
Yeah. Interesting. Do you think now, as that there's lots
more institutional interest in it and there's even 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 3 (42:31):
I think it certainly will, and I think institutional adoption
of bitcoin today is about 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 1 (42:43):
Okay, I think we have a very clear view there.
And again, just let me repeat hate mail direct to
Dan done. Can we find you on Twitter so they
can send you a hate mail? Director you on Twitter,
because that's where I get those? Absolutely, what'd you handle there?
Just to make apple sure it goes to you.
Speaker 2 (42:56):
Not me? It's at verdad cap.
Speaker 1 (42:58):
Okay, everybody, if you feel strongly about big cooeen filst,
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. Okay. 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 Europeean equities. Is there
(43:20):
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 2 (43:28):
You know, I actually like Eastern Europe.
Speaker 3 (43:30):
I find a lot of interesting things in Poland and
I think that people have tended to overlook Eastern Europe
in particular because of the Ukraine War, but I think
it also is the most leverage to any peace deal
going through that you'll make money in Polish equities.
Speaker 2 (43:43):
They're very thinly traded.
Speaker 3 (43:44):
You have to buy small caps, but I think it's
quite attractive.
Speaker 1 (43:48):
Okay, that is interesting. Poly small caps have never come
up on this podcast before, So thank you very much
for that. Congratulations something something you go. Okay, last ques
your book. I think it's excellent, and just to repeat again,
everybody by this book is excellent. Everything we've talked about
is in the books. A whole load more we didn't
(44:08):
get onto Private credit. Another fascinating chapter 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 would be helpful for our listeners.
Speaker 3 (44:23):
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 Corte has 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,
(44:45):
eight hundred men conquering several hundred thousand a person civilization
in It's just an insane.
Speaker 2 (44:54):
Story and beautifully written.
Speaker 3 (44:55):
So if you're looking from a break from markets, I
recommend it.
Speaker 1 (44:58):
I imagine people are going to be a for a
break from markets relatively soon this year. But we'll see you.
Speaker 2 (45:04):
Dan.
Speaker 1 (45:04):
Thank you so much for joining us today and congratulations
on an excellent book. Thank you, Marion, thanks for listening
for this week's Maren Talks Money. If you like our show,
rate review and subscribe wherever you listen to podcasts, and
keep sending questions or comments to Marin Money at Bloomberg
dot net. You can also follow me and John on
(45:26):
Twitter or x. I'm at Marin sw and John is
John Underscore Stepic. This episode were hosted by Me Maren
Sumset Web was produced by Samasadi, Production support from Moses
and and special thanks to Dan Rasmussen.
Host
Merryn Somerset Webb
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