Latest / Merryn Talks Money / The 'Humble' Investor Says Sell Private Equity, Sell US Tech, Buy Polish Small Caps

Transcript

The 'Humble' Investor Says Sell Private Equity, Sell US Tech, Buy Polish Small Caps · Merryn Talks Money

0:02
Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. Welcome to Meren Talks Money,
0:19
Speaker 1: the podcast in which people who know the markets explain
0:21
Speaker 1: the markets. I'm Merit suset Work. This week I'm speaking
0:24
Speaker 1: with Dan Rasmussen, founder of the investment management firm Verdered Advisors.
0:27
Speaker 1: Before starting Verda, Dan worked at Baine Capital Private Equity
0:31
Speaker 1: and Bridgewater Associates. And he's got a book coming out
0:33
Speaker 1: which I have read already, called The Humble Investor, How
0:37
Speaker 1: to Find a Winning Edge in a Surprising World. It's
0:40
Speaker 1: available for pre order now and out in bookstores in
0:42
Speaker 1: early February. I strongly recommend that you order it. The
0:46
Speaker 1: underlying theme, as Dan puts it, is the future is
0:48
Speaker 1: hard to protect, vicually impossible to predict. So don't assume
0:52
Speaker 1: you really know anything. The best approach is a humble one.
0:56
Speaker 1: The best investment opportunities come to you when you can
0:58
Speaker 1: see other people's eric identify where they are too confident,
1:02
Speaker 1: be they too optimistic or too pessimistic. We're going to
1:05
Speaker 1: get into all that, plus his thoughts on investing during
1:07
Speaker 1: stock market bubbles. Are we in one now? By the way,
1:09
Speaker 1: European and UK equities, Japanese equities and what he is
1:13
Speaker 1: most bullish on. Dan, Welcome to Marin Talk's Money.
1:17
Speaker 2: Thanks for having me.
1:18
Speaker 1: It's a pleasure now. I am excited to have been
1:21
Speaker 1: one of the first outsiders to have read your book.
1:23
Speaker 1: I finished it this morning and it is excellent. And
1:26
Speaker 1: as I said to you before we started talking, it
1:28
Speaker 1: fits with so many of my biases that I particularly
1:30
Speaker 1: enjoyed it. Every page and affirmation of thoughts I have already.
1:34
Speaker 1: Nothing works, Oh God, absolutely absolutely. We'd be having a
1:40
Speaker 1: different conversation if I'd gone through the book going no,
1:43
Speaker 1: that's not what I think already. Don't try and persuade
1:44
Speaker 1: me about things like that. Now. I wanted to start
1:48
Speaker 1: actually at the very beginning of the book what you
1:51
Speaker 1: talk about first, which is this idea, And it's particularly
1:54
Speaker 1: important this time of year, by the way, when we
1:56
Speaker 1: are overwhelmed, not me, by forecasts from everybody in the
2:00
Speaker 1: market about what they think is going to happen in
2:02
Speaker 1: the coming year. And we know, we know you, and
2:05
Speaker 1: I am pretty much everyone else in the market from
2:06
Speaker 1: my years of experience, that every single one of those
2:10
Speaker 1: forecasts is wrong, well, not all of them, They'll be
2:12
Speaker 1: one in the middle. By happen chance that that is correct.
2:15
Speaker 1: So I wanted to start by talking about that full costs,
2:18
Speaker 1: you say, full costs meet reality.
2:21
Speaker 3: It's probably the single idea that most changed my career,
2:25
Speaker 3: which was, you know, I started out in investing, like
2:27
Speaker 3: many of us, do you know, building these discounted cash
2:30
Speaker 3: flow models, the LBO models that forecast revenue and profits
2:34
Speaker 3: years into the future. And there was so much emphasis
2:37
Speaker 3: put in on getting these Excel models right right, or
2:40
Speaker 3: you know whatever right, meant that I never stopped to
2:43
Speaker 3: ask how good are we predicting what's going to happen
2:46
Speaker 3: three or four years from now on the side, and
2:49
Speaker 3: I didn't. I didn't start out, and I didn't study
2:52
Speaker 3: finance or accounting or economics in undergrad And so when
2:55
Speaker 3: I started working investing, I talked to my sister and
2:59
Speaker 3: a few other folks who are in the business, and
3:01
Speaker 3: they said, well, wanted to go read as much as
3:03
Speaker 3: you can, and so I started reading all these books
3:05
Speaker 3: about theory and academic research and investing. And one of
3:08
Speaker 3: the ideas that I came upon was phil Tetlock's work
3:11
Speaker 3: on forecasting, and Tetlock finds that experts in their fields
3:15
Speaker 3: are no better than non experts at forecasting things, even
3:18
Speaker 3: in fields much they're experts, and the only difference is
3:20
Speaker 3: that they're more arrogant about it. And I said, you know, gee,
3:23
Speaker 3: I wonder if our growth forecasts are are right.
3:27
Speaker 2: How would I sort of figure this out?
3:29
Speaker 3: And I've done a variety of studies since having that
3:32
Speaker 3: original question, and the answer that I've come to is
3:35
Speaker 3: that our forecasts are really bad. At we really don't
3:38
Speaker 3: know much about the future, and the farther into the
3:41
Speaker 3: future we try to peer, the worse we get. In fact,
3:44
Speaker 3: Andre Schlipher at Harvard has done this wonderful study where
3:46
Speaker 3: he shows that long term growth forecasts are actually a
3:49
Speaker 3: perfectly negatively correlated with stock market returns. In other words,
3:52
Speaker 3: the more optimistic you are about long term growth, it's
3:56
Speaker 3: actually a totally contrarian signal. Now short term growth, you know,
3:59
Speaker 3: next year, for example, there's a little bit more accuracy.
4:02
Speaker 3: People have some good, decent chunk of ability to forecast. Okay,
4:07
Speaker 3: when we're talking about revenue or ebit das for example,
4:10
Speaker 3: or profits, you know what's going to happen in twenty
4:13
Speaker 3: twenty five. The problem is that it doesn't actually help you.
4:16
Speaker 3: So I just finished this wonderful study where in Japan
4:20
Speaker 3: almost all companies are required to issue one year forward
4:23
Speaker 3: guidance on revenue and net income, and so you can
4:26
Speaker 3: take you know, I took twenty years of this data
4:28
Speaker 3: and said, you know, how accurate are they? And then
4:30
Speaker 3: what does it mean for the stock prices? And what
4:32
Speaker 3: I found is that if you divide it into slow, medium,
4:36
Speaker 3: and high growth on a one year forward basis, Japanese
4:39
Speaker 3: companies are about fifty percent accurate. So thirty percent would
4:43
Speaker 3: be pure chance, you know, one hundred percent would be
4:45
Speaker 3: totally accurate. Fifty percent right, the other That sounds good,
4:49
Speaker 3: It sounds okay, right. But the challenge then is if
4:52
Speaker 3: you say, okay, well, let's say you're forecasting really high
4:55
Speaker 3: you know, you then think, oh, well, I should buy
4:57
Speaker 3: all the companies that are forecasting really high growth. You know,
5:00
Speaker 3: if they achieve that growth, it's going to be great. Well,
5:02
Speaker 3: it turns out that the companies that achieve high growth
5:05
Speaker 3: have sort of average returns.
5:07
Speaker 2: Right.
5:07
Speaker 3: They forecast high growth and they achieve high growth, and
5:09
Speaker 3: they have average returns because that high growth was priced
5:12
Speaker 3: in with the time the guidance was issued. But the
5:15
Speaker 3: fifty percent of the time those companies that forecast high
5:17
Speaker 3: growth don't have high growth, their stocks collapse, and so
5:21
Speaker 3: you end up doing worse in the companies that forecast
5:24
Speaker 3: high growth or about you know, average in total, but
5:27
Speaker 3: a little bit worse. Whereas if you go to the
5:29
Speaker 3: companies that are forecasting low growth, yeah, fifty percent of
5:32
Speaker 3: the time they hit low growth, right, But then when
5:34
Speaker 3: they do, the stock returns average. They return the same
5:37
Speaker 3: as the high growth firms that achieved high growth. But
5:39
Speaker 3: when the slow growth firms achieve high growth, which they
5:42
Speaker 3: do fifty percent of the time, their stocks do really well.
5:45
Speaker 1: Okay, So knowing the growth thems in advance doesn't help
5:47
Speaker 1: you any even if you did. And is it also
5:50
Speaker 1: true to say that over those very short periods, so
5:52
Speaker 1: over a year or so. What we're not necessarily saying
5:56
Speaker 1: is that anyone is particularly good at forecasting anything out
5:59
Speaker 1: of reason. What we're saying is that people are jolly
6:01
Speaker 1: good at extrapolating the future, the short term future, from
6:04
Speaker 1: the past, and unless something goes wrong, it's quite likely
6:08
Speaker 1: that the next year will be similar to the previous
6:10
Speaker 1: year exactly.
6:11
Speaker 3: And this is where things get that get quite interesting,
6:14
Speaker 3: because I think you're exactly right, Marion. That the way
6:17
Speaker 3: people form their forecasts is they look at the recent
6:21
Speaker 3: past and they extrapolate that forward. That's the most common
6:25
Speaker 3: forecasting method in markets, which is why you see all
6:28
Speaker 3: the S and P five hundred forecasts for next year
6:30
Speaker 3: cluster around exactly what the S and P five hundred
6:32
Speaker 3: day last year. And there's a wonderful study that I
6:35
Speaker 3: updated and have done, you know, through for the last
6:38
Speaker 3: twenty years of data, where I look at the level
6:41
Speaker 3: and persistence of growth rates, and so you basically say, okay,
6:46
Speaker 3: let's look at every you know, every company's trailing growth
6:49
Speaker 3: over you know, let's say one year, three year, five
6:51
Speaker 3: year period. Does that forecast their growth rate over the
6:55
Speaker 3: next one, three or five years. And what you find
6:59
Speaker 3: is that revenue on a one year basis is a
7:02
Speaker 3: little bit forecastable, and then everything else is total chance.
7:05
Speaker 2: It's just pure coin flips.
7:07
Speaker 3: There's no relationship between past and future growth. And that's
7:11
Speaker 3: probably the single hardest thing for people to understand because
7:14
Speaker 3: it's just so against our views, right, because if you said, well, gee, Microsoft,
7:19
Speaker 3: and I don't know the gap or some apparel retailer,
7:22
Speaker 3: I'm trying to think of something very boring have an
7:25
Speaker 3: equal chance of having high growth over the next five years.
7:27
Speaker 3: You'd say, come on, that's absolutely not ei, there's no
7:29
Speaker 3: way that that's true.
7:30
Speaker 2: But statistically it is true.
7:33
Speaker 3: And I think that when you start to understand that,
7:36
Speaker 3: and you combine that with the insight about what's priced
7:38
Speaker 3: in and what's not, you start to see how the
7:41
Speaker 3: importance of understanding the structure of forecasts is to being
7:46
Speaker 3: a good investor. Because I like to say that investing
7:50
Speaker 3: is not a game of analysis, it's a game of
7:52
Speaker 3: meta analysis. It doesn't matter what you think, it matters
7:55
Speaker 3: what you think relative to what the market thinks.
7:57
Speaker 2: And so you need to understand.
7:58
Speaker 3: What other people are forecasts, knowing that everyone else is forecasting,
8:03
Speaker 3: and then you have to think, well, what if they're wrong?
8:05
Speaker 3: You know, how would I make money if they're wrong?
8:07
Speaker 3: And that, I think is my sort of key to
8:10
Speaker 3: unlocking or starting to think about what should work as
8:13
Speaker 3: an investing strategy based on behavioral economics.
8:15
Speaker 1: Yeah, I mean, it's not just we'll come back to that.
8:18
Speaker 1: I've wanted to talk about an anecdote that you had
8:20
Speaker 1: in the beginning of the book about the weather, and
8:23
Speaker 1: because one of the things that we often talk about
8:25
Speaker 1: is why do we bother with these forecasts? I mean
8:27
Speaker 1: this not just at the company level, but at the
8:29
Speaker 1: inflation level, GDP level, interest rates, etc. They're always wrong,
8:34
Speaker 1: And we have these GDP forecasts come out over and
8:36
Speaker 1: over from all our governments selling us GDP is going
8:39
Speaker 1: to be whatever it is with a couple of decimal
8:41
Speaker 1: points off to it. And we look at him like that,
8:42
Speaker 1: that's a nonsense. We know it's nonsense. Why do we listen?
8:45
Speaker 1: So tell us this lovely little weather anecdote from the
8:47
Speaker 1: book which explains it.
8:50
Speaker 3: Yeah, so this is ken error. The famous economist was
8:53
Speaker 3: in the weather Core in World War Two, and being
8:57
Speaker 3: the genius that he was, he's and by the way
9:00
Speaker 3: that the weather Core asked for one year forward weather
9:02
Speaker 3: forecasts and so so they could plan troop movements and
9:07
Speaker 3: things like that, you know, when of the road's going
9:08
Speaker 3: to be too muddy, when there's once they're going to
9:10
Speaker 3: be snow by day.
9:11
Speaker 2: And so he was.
9:12
Speaker 3: Tasked with creating these and and you know, he did
9:15
Speaker 3: a little bit of research and he found, you know,
9:17
Speaker 3: these these forecasts are completely wrong, They're completely useless, and
9:20
Speaker 3: so we just stopped doing them and I'll just send
9:23
Speaker 3: you the historic average table and just use that. And
9:26
Speaker 3: he sends a note to the General and and and
9:28
Speaker 3: and saying you know that that laying out his argument,
9:31
Speaker 3: and he gets a one sentence one back and it says,
9:34
Speaker 3: you know, the General knows that the forecasts are are useless,
9:38
Speaker 3: but he needs them for planning purposes.
9:40
Speaker 1: And then that's exactly it, isn't it. We need something
9:44
Speaker 1: to anchor what we're doing around even if we know
9:47
Speaker 1: it's wrong. We need the anchor.
9:49
Speaker 3: We need some way to plan. And even if we're
9:52
Speaker 3: not doing it consciously, we're often doing it subconsciously. And
9:56
Speaker 3: so you need some alternative way of thinking. And I think,
10:00
Speaker 3: you know, a lot of the research on forecasting suggests
10:03
Speaker 3: that the best way to make forecast is use base rates. Right,
10:06
Speaker 3: so you take a long historical time and you sort
10:09
Speaker 3: of say, what's the average over this long period of time,
10:12
Speaker 3: and that's generally the best you're going to get. And
10:16
Speaker 3: so I think that in my mind the game of investing,
10:19
Speaker 3: the way to make good investment decisions is, on the
10:21
Speaker 3: one hand, to take those base rates, to study history
10:23
Speaker 3: to understand what the context is over a long period,
10:27
Speaker 3: not one year, not three years, But what's a ten
10:29
Speaker 3: twenty year context, and what's the sort of distribution of
10:32
Speaker 3: potential outcomes? And then to secondarily to say, because we
10:36
Speaker 3: know everyone else is planning, we know everyone else's forecasting,
10:39
Speaker 3: where are they concentrating their excessive optimism and their excessive pessimism,
10:44
Speaker 3: And those are the places where we're likely to be
10:48
Speaker 3: able to find an arbitrage just betting that nobody knows. Right, Like,
10:52
Speaker 3: nobody knows is AI going to truly revolutionize the economy
10:57
Speaker 3: or is that one trillion these companies are spending going
10:59
Speaker 3: to be a to money. Maybe no one knows, you know.
11:02
Speaker 3: And if no one knows, you know, what's the bet
11:05
Speaker 3: that we should make.
11:06
Speaker 1: Yeah, if everyone else is betting that they will, but
11:08
Speaker 1: we know that nobody knows, then we should bet that
11:10
Speaker 1: they won't exactly. And that brings us to this idea
11:13
Speaker 1: of investing being not a game of analysis as a
11:15
Speaker 1: game of meta analysis. That's right, It's all about the relativity,
11:19
Speaker 1: all right. So with that in mind, that would make
11:23
Speaker 1: almost all the models that we use at the moment irrelevant.
11:26
Speaker 1: I'm one of the one of the models that you
11:27
Speaker 1: talk about in the book The Dividend discount model the
11:30
Speaker 1: way of investing by saying, you know, every company, every
11:34
Speaker 1: equity is worth the value of all the dividends that'll
11:36
Speaker 1: be paid to the owner of that equity in the future.
11:38
Speaker 1: And people spend hours on these models, don't they days
11:41
Speaker 1: days working out is actually worth But as they have
11:44
Speaker 1: absolutely no idea whatsoever what those dividends are going to be,
11:48
Speaker 1: the final number they come up with is nonsense.
11:50
Speaker 3: Call before you do the company. You know, you're the
11:53
Speaker 3: world's leading expert on you. So just tell me what's
11:56
Speaker 3: your year end bank balance going to be in twenty
11:58
Speaker 3: thirty And by the way, what's your income pre and
12:00
Speaker 3: post you know, your pre tax and post taxing home
12:04
Speaker 3: exactly for the next five years, And.
12:05
Speaker 2: Just model that first.
12:07
Speaker 3: And if you can't do that accurately, you know, why
12:09
Speaker 3: do you think you can do it for Coca Cola?
12:10
Speaker 2: Yeah?
12:11
Speaker 1: Right, okay, interesting, So it's let's go move then to
12:19
Speaker 1: what you think might work. So if none of these
12:21
Speaker 1: models that most people use, that everyone who has an MBA, etc.
12:25
Speaker 1: Sits around making these breadsheets all day, none of these work.
12:28
Speaker 1: What does And the thing that you say is that
12:31
Speaker 1: one thing that never changes, and you can extrapolate from
12:34
Speaker 1: is human psychology, which brings us back to this idea
12:37
Speaker 1: of the meta analysis. And in this section of the book,
12:41
Speaker 1: you use the analogy of ships because you spent some
12:43
Speaker 1: time observing how shipping works, right, And this is one
12:47
Speaker 1: of my colleagues when I was first starting as a broker,
12:49
Speaker 1: explained this to me in terms of of chips, in
12:51
Speaker 1: terms of semiconductors, but you do it much better with chips.
12:56
Speaker 3: Well, it's a wonderful paper by a consulting economist here
12:59
Speaker 3: for a day at Sam Hanson as the presser at
13:01
Speaker 3: our business school. Really brilliant guy. And I love the
13:04
Speaker 3: shipping industry. Actually spend a summer in college working at
13:06
Speaker 3: a Greek shipping company, and I find that endlessly fascinating
13:10
Speaker 3: of the personalities involved and the dynamics and the way
13:14
Speaker 3: it interacts with global trade.
13:15
Speaker 2: I mean, it's just so cool.
13:17
Speaker 3: But there's this fascinating insight that these economists have by
13:20
Speaker 3: looking at shipping companies. And what happens is that shipping
13:23
Speaker 3: rates are very variable, right, So sometimes it's very expensive
13:27
Speaker 3: to ship rate, sometimes it's very cheap when rates are
13:30
Speaker 3: very high, and you plug those rates into a model
13:34
Speaker 3: of whether you should invest in a new ship or not.
13:37
Speaker 3: It turns out that investing in a new ship looks
13:40
Speaker 3: really profitable whenever shipping rates are high, and so people
13:44
Speaker 3: plug these into their model. Now, the challenge is that
13:46
Speaker 3: it takes three or four years to build a new ship,
13:49
Speaker 3: and so these Greek shipping companies they see the high
13:53
Speaker 3: rates and then they go and they order ships from
13:55
Speaker 3: these South Korean shipyards, and then three or four years
13:59
Speaker 3: from now, the ships are delivered and what ends up
14:01
Speaker 3: happening and he calls this competition neglect, which I think
14:05
Speaker 3: is such a wonderful and relevant term to what's going
14:07
Speaker 3: on in Ai. By the way, competition neglect. They don't
14:10
Speaker 3: realize that all their other buddies also ordered ships at
14:14
Speaker 3: the same time, because they all also did the same math,
14:16
Speaker 3: and they plugged the same shipping rates and the same
14:18
Speaker 3: cost to build a ship. And so there's this lot
14:21
Speaker 3: of ships that then show up on the market, all
14:23
Speaker 3: at the same time, three or four ears down the road,
14:26
Speaker 3: and all of a sudden, shipping prices crash because there
14:28
Speaker 3: are too many ships. And so you see the competition neglect,
14:33
Speaker 3: the inability of these shipping companies to anticipate that their
14:38
Speaker 3: competitors are doing the same thing. Is what's exacerbating the
14:42
Speaker 3: cycles and driving shipping rates too high and then too low,
14:45
Speaker 3: and then too high and then too low, and then
14:47
Speaker 3: everyone seems to be getting burned at the same time.
14:50
Speaker 3: And I think that that's such a wonderful analogy to
14:53
Speaker 3: what's going on in markets. Right you sort of say, wow,
14:55
Speaker 3: like AI is such a great opportunity, I should buy
14:58
Speaker 3: into it. What if somebody else figure this out before me?
15:01
Speaker 3: Or what's the fact that I thought it means that
15:04
Speaker 3: everyone else is thinking at the same time.
15:06
Speaker 1: So do you think that there is overinvestment in AIO,
15:09
Speaker 1: too many companies investing at the same time and the
15:11
Speaker 1: same things like the ships.
15:13
Speaker 2: Well, I think there has.
15:14
Speaker 3: To be, right, I mean, you just think about how
15:16
Speaker 3: many of these AI companies there are. All of them
15:18
Speaker 3: are trying to build pretty much the same thing as
15:21
Speaker 3: far as I can tell. And I think there are
15:23
Speaker 3: a few things that are are are are clear right,
15:26
Speaker 3: Like we can study the history of the Internet, and
15:29
Speaker 3: one of the things that we observed that tends to
15:31
Speaker 3: be winner take all the best model tends to work
15:34
Speaker 3: Google winds search, Amazon winds, retail. You know, Microsoft winds productivity.
15:40
Speaker 3: So why should we think that AI will be twenty
15:42
Speaker 3: percent chat GBT twenty percent, Gemini twenty percent, right, like
15:47
Speaker 3: Claude twenty percent anthropic. It just is it's not plausible
15:50
Speaker 3: based on the history of the of the of the
15:54
Speaker 3: tech industry.
15:55
Speaker 1: And we can't choose them, and we can't choose the winner.
15:57
Speaker 3: And we can't pick the winners. So like, some of
15:59
Speaker 3: these things are just incinerating capital, right, They've got to be, like, probably,
16:04
Speaker 3: probably all but one of them are incinerating capital. We
16:07
Speaker 3: just don't know which of them is incinerating capital, which
16:09
Speaker 3: of them are, and which of them aren't.
16:11
Speaker 1: And does that mean that as investors we should avoid
16:13
Speaker 1: all of them?
16:14
Speaker 2: I think so. I think they're all terrifying.
16:17
Speaker 3: There's too much hype, too much optimism. How long have
16:20
Speaker 3: we thought that we would have robots that could think
16:22
Speaker 3: like us?
16:23
Speaker 2: Right?
16:23
Speaker 3: Like, this isn't the idea. Humans that are perpetually attracted
16:27
Speaker 3: to the idea of anthropic robots that can speak and
16:30
Speaker 3: think like us, And every time we've tried to do
16:32
Speaker 3: it it has worked, and it's not going to work
16:34
Speaker 3: this time.
16:34
Speaker 1: I don't think why do we think why do you
16:36
Speaker 1: think we're at trying to do it. Is it because
16:37
Speaker 1: we're lazy and we're just hoping to be able to
16:39
Speaker 1: invent something that can do everything for us?
16:42
Speaker 3: Well, it's the it's the ultimate vanity to create something
16:46
Speaker 3: in your own image, isn't it.
16:48
Speaker 2: The closes complex?
16:52
Speaker 1: Okay? One of the tiny questions, not.
16:54
Speaker 2: That any of our friends in the tech industry.
16:56
Speaker 1: Of god, absolutely this idea about the measure analysis. What
17:01
Speaker 1: does that lead us to? What does that tell us
17:03
Speaker 1: about how we can actually invest? How can we really
17:05
Speaker 1: do it? What works?
17:07
Speaker 2: Yeah?
17:07
Speaker 3: So I think that if we step aside and we say, gee,
17:11
Speaker 3: you know, forecasting doesn't work and the future is too unpredictable,
17:15
Speaker 3: and actually markets are too volatile, which is another thing.
17:19
Speaker 3: This is what Robert Schiller won the Nobel Prize force
17:21
Speaker 3: this idea of excessive volatility. What Schiller did, which is
17:24
Speaker 3: so brilliant, They said, you know, if the dividend discount
17:26
Speaker 3: model is right, and the net present values equal to
17:30
Speaker 3: some of the future cash flows discount by the interest rates,
17:34
Speaker 3: and if we know future cash flows and we know
17:35
Speaker 3: future indust rates, we can tell you what the net
17:37
Speaker 3: present value of the stock market should have been at
17:40
Speaker 3: any given time and how much it should have moved
17:42
Speaker 3: as those things changed. And he finds that about eighty
17:47
Speaker 3: plus percent of stock market volatility is inexplainable by changes
17:51
Speaker 3: and fundamentals.
17:51
Speaker 1: Okay, so even if you had the information for the model,
17:55
Speaker 1: it still wouldn't work exactly.
17:57
Speaker 3: Even with full pressions, you can explain a very high
18:01
Speaker 3: percentage of volatility. And so where is this excess.
18:03
Speaker 2: Volatility coming from?
18:05
Speaker 3: And I love this theory by this Stanford professor Mordecai Kurtz.
18:09
Speaker 3: And he comes up with this theory that what's happening
18:13
Speaker 3: is that everybody's making forecasts and then the future happens,
18:17
Speaker 3: and eighty percent of people realize they're wrong, and so
18:20
Speaker 3: they sell and they buy something else, and then they
18:22
Speaker 3: make new forecasts and then the same thing happens. Right,
18:24
Speaker 3: And it's that dynamic, and he should use some fancy
18:28
Speaker 3: match so that could explain it. All, right, that's what's
18:31
Speaker 3: going on. And I think what I sort of love
18:34
Speaker 3: about that idea. And we're so focused on efficient market theory,
18:37
Speaker 3: and efficient market theory is so many wonderful implications, right,
18:41
Speaker 3: and it's so useful. But I think one challenge to
18:44
Speaker 3: efficient markets theory is that it often gets interpreted as
18:46
Speaker 3: the price is always right. But anybody who's actually invested
18:51
Speaker 3: in markets at any point knows how frequently they make mistakes.
18:55
Speaker 3: And not only how frequently they make mistakes, but how
18:57
Speaker 3: frequently the market seems to make mistakes. Right, How could
19:01
Speaker 3: a stock be down thirty percent in a day if
19:03
Speaker 3: it wasn't a mistake yesterday?
19:05
Speaker 2: Right?
19:05
Speaker 3: I mean, like, yes, the new news came out, but
19:08
Speaker 3: clearly the market didn't get that right. Otherwise the price
19:10
Speaker 3: wouldn't have moved as much as it did. And I
19:12
Speaker 3: think trying to reintroduce this idea of mistakes back into
19:15
Speaker 3: our vocabulary when we talk about markets and make it
19:18
Speaker 3: more human. Right, of course, mistakes are an integral component
19:21
Speaker 3: of investing. How could they not be. How could anybody
19:24
Speaker 3: who's ever experienced markets not know the mistakes are part
19:27
Speaker 3: of things? And how is that therefore driving rebalancing decisions?
19:31
Speaker 3: And then how can we as investors think through if.
19:33
Speaker 2: Other people are making mistakes, if we're making mistakes.
19:35
Speaker 3: How should we build portfolios that take into account the
19:38
Speaker 3: idea that we are going to make mistakes and that
19:40
Speaker 3: everyone else is making mistakes too, and that that's part
19:43
Speaker 3: of the dynamics of what's driving market volatility.
19:46
Speaker 1: Okay, so was the answer, how are we going to
19:48
Speaker 1: build that portfolio?
19:49
Speaker 3: What we're looking for is some barometer of optimism or pessimism, right,
19:53
Speaker 3: If we could, if we could just have some barometer
19:55
Speaker 3: of how optimistic or pessimistic the market was about an
19:58
Speaker 3: individual security about the market as a whole, then we'd
20:00
Speaker 3: be in very good stead because we'd have a very
20:02
Speaker 3: good way of saying, you know, here's the stuff that's
20:05
Speaker 3: too extreme on one end or the other and going
20:07
Speaker 3: long or short that it turns out, in fact, that
20:10
Speaker 3: we have a very simple metric for doing that. And
20:12
Speaker 3: in the stock market, it's valuations.
20:14
Speaker 2: Right. You can pick almost.
20:15
Speaker 3: Any multiple, right, revenue multiples or book multiple, and you
20:18
Speaker 3: can erase to haksana on a on a ranking system,
20:23
Speaker 3: and you'll find that the ones that are the cheapest
20:25
Speaker 3: end up doing the best, and the ones that are
20:26
Speaker 3: the most expensive end up doing the worst. And that
20:30
Speaker 3: value reliably predicts stock returns. And in fact, over the
20:33
Speaker 3: last few years it hasn't in the United States.
20:36
Speaker 2: We should talk about why, but it.
20:38
Speaker 3: Has even internationally. People have declared the death of value investing.
20:42
Speaker 3: But value investing are the idea of ranking stocks by
20:46
Speaker 3: their relative optimism or pessimism and going along and things
20:49
Speaker 3: other people are pessimistic about and short things they're optimistic
20:52
Speaker 3: about should work. And I think you can also and
20:54
Speaker 3: we should talk about this separately, apply that to thinking
20:57
Speaker 3: about economy, whole markets and whole economy. But I think
21:00
Speaker 3: in the context of single stocks, what we've seen over
21:03
Speaker 3: the last few years has been some of the worst
21:05
Speaker 3: performance of value investing over its history. The last time
21:09
Speaker 3: it did this badly was in the late nineties during
21:11
Speaker 3: the tech bubble, and so we have to reckon with that, right,
21:14
Speaker 3: So I think it's all well and good for me
21:16
Speaker 3: to argue that we should use valuation ratios as a
21:19
Speaker 3: metcoroptimism or pessimism, and that we should be long things
21:22
Speaker 3: other people are pessimistic about.
21:23
Speaker 2: And there's an intuitive.
21:24
Speaker 3: Logic to that, But there's also grappling with the fact
21:28
Speaker 3: that that hasn't worked recently in the United States. Again,
21:30
Speaker 3: it has worked internationally, it hasn't worked in the US,
21:32
Speaker 3: and so why And actually there was a period from
21:36
Speaker 3: COVID until the release of chat GBT when it did work,
21:39
Speaker 3: and then chat GBT just totally newked to value investing again,
21:43
Speaker 3: and so what I like to say about value investing.
21:46
Speaker 2: What's going on in the market today is.
21:48
Speaker 3: That we've had a period from in the twenty tens
21:52
Speaker 3: where there were a very small number of companies where
21:55
Speaker 3: they were forecasts to grow fast, and then they grew
21:59
Speaker 3: fast than the forecast, and they did that a few
22:02
Speaker 3: years in a row. That was the sort of fan
22:04
Speaker 3: mag stocks, as they.
22:05
Speaker 2: Were called them.
22:07
Speaker 3: What is that a tribunal too, I'd say it was
22:08
Speaker 3: an innovation wave.
22:09
Speaker 2: And these innovation waves happen, they do.
22:12
Speaker 3: They happen with the Internet, they happen with railroads, and
22:15
Speaker 3: when they happen, they are these abnormal profit pools that
22:18
Speaker 3: are earned by the innovators. Now that doesn't last that
22:20
Speaker 3: long because at some point the customers need to benefit
22:23
Speaker 3: more than the innovators, and at some point the innovation
22:26
Speaker 3: get commoditized, and so these innovations don't last forever.
22:29
Speaker 2: But in early windows they can be huge, huge booms.
22:32
Speaker 2: And that's what we're in the middle of.
22:34
Speaker 1: In the middle of or towards the end of.
22:36
Speaker 3: It depends on the future of AI and everything hinges
22:38
Speaker 3: on that. And again that's what you saw right like
22:40
Speaker 3: the sort of tech mania seemed to actually peak in
22:44
Speaker 3: COVID right in twenty twenty one, and then with the
22:46
Speaker 3: release of the vaccines, you had all that stuff clearly
22:50
Speaker 3: coming off. It all gone too far. Zoom had gone.
22:53
Speaker 3: People were using zoom too much, right, the people were
22:56
Speaker 3: buying too much on Amazon. It was peak Internet and
22:59
Speaker 3: then a client and then it looked like we were
23:02
Speaker 3: going to sort of return to a normal market where
23:04
Speaker 3: value investing worked again. And then chat GPT was released
23:08
Speaker 3: and it's just unleashed this total mania again and it
23:12
Speaker 3: now feels like we're back at twenty twenty one peaks.
23:15
Speaker 3: I mean, you know, you look at things like fart coin,
23:18
Speaker 3: and it's even worse than the SPACs, like at least
23:20
Speaker 3: the SPACs are companies.
23:21
Speaker 2: Well the hell is fart coin.
23:22
Speaker 3: And yet it's valued at most more than you know,
23:25
Speaker 3: ninety percent of Japanese companies for example. You have to
23:28
Speaker 3: understand that, you know, markets are are reflective of human
23:32
Speaker 3: history and human events, and it's not it's not a
23:36
Speaker 3: linear math problem. And we know that there are certain
23:39
Speaker 3: things that we can rely on and should rely on,
23:42
Speaker 3: which is betting against tubris right, betting on things others
23:46
Speaker 3: are pessimistic about and being skeptical if things are too
23:49
Speaker 3: optimistic about. But sometimes the optimists are right, and they
23:52
Speaker 3: were right during the twenty tens. And the question is
23:55
Speaker 3: now the only question that matters for markets right now?
23:57
Speaker 3: In my mind, the most important question is are they
24:00
Speaker 3: right about AI or not?
24:02
Speaker 1: I mean, the other thing you can say, surely is
24:04
Speaker 1: that value investing doesn't work during a bubble.
24:06
Speaker 2: It doesn't work during a bubble.
24:07
Speaker 1: Aunts it doesn't work during a bubble, and so you
24:09
Speaker 1: can then make the case. So you might have might
24:11
Speaker 1: not want to make the case that the last few
24:12
Speaker 1: years are being suggestive of a bubble in the US market.
24:15
Speaker 1: And you look at the valuations and these are bubble valuations.
24:18
Speaker 1: So that could be the simplest way to look at it.
24:21
Speaker 2: I think so too.
24:22
Speaker 3: And I have this piece in the book about the
24:24
Speaker 3: nineties because I spent a lot of time thinking about bubbles.
24:27
Speaker 3: I went back and I read a bunch of investor
24:30
Speaker 3: letters from the great investors, Ray Dallio, Peter Lynch, Howard Mark,
24:34
Speaker 3: Seth Clarman. You know what were they saying in the nineties.
24:37
Speaker 3: And it was really interesting because all these great investors
24:40
Speaker 3: knew it was a bubble. They all wrote aboute about him,
24:45
Speaker 3: Ray Daalio said, we're approaching a blowoff phase of the
24:48
Speaker 3: US stock market. Peter Lynch said, not enough investors are worried.
24:53
Speaker 3: The only problem is that those two quotes are from
24:55
Speaker 3: nineteen ninety five, So you know, investor are often you know,
25:01
Speaker 3: smart data driven people. You can pick up on these
25:04
Speaker 3: things instead, the evaluations are too high. The problem is
25:06
Speaker 3: that smart investors tend to be way too early. Right,
25:08
Speaker 3: the bubble didn't burst for five years, right, and meeps up,
25:16
Speaker 3: and each subsequent year it doesn't burst. You look stupid,
25:18
Speaker 3: and the people that supported the bubble look right, And
25:21
Speaker 3: I think that that's the type of situation we're in now.
25:24
Speaker 3: It actually turned out that value investing, if you looked
25:26
Speaker 3: at it from ninety five to ninety nine, it looks
25:28
Speaker 3: like the stupidest investment strategy on the planet. So did
25:31
Speaker 3: international diversification. So right, but if you just fast forward
25:34
Speaker 3: two or three years, the bubble bursts so quickly that
25:37
Speaker 3: value investing, international diversification, all these things came out ahead
25:40
Speaker 3: with only one or two years after the bubble. And
25:43
Speaker 3: so I think that having patients, and I think understanding
25:47
Speaker 3: that there's historical context, being patient, but being guided by
25:51
Speaker 3: a sensitivity towards these behavioral insights that it doesn't you know,
25:56
Speaker 3: don't don't overthink it. You don't have to in some ways,
25:58
Speaker 3: you don't have to have the ends. I don't need
26:00
Speaker 3: the answer to in the I. I don't need to
26:01
Speaker 3: know that extended will succeed. All I need to know
26:04
Speaker 3: is are people too optimistic about it or not? And
26:07
Speaker 3: what it would be the signs of that excessive optimism.
26:09
Speaker 3: And if people are excessively optimistic, you know what should
26:12
Speaker 3: I do? I should stay away.
26:14
Speaker 1: And so there is this sense from you anyway that
26:17
Speaker 1: investors in general overinvested in the US, underinvested outside the US,
26:22
Speaker 1: overinvested in AI, and underinvested in value absolutely.
26:25
Speaker 3: And I think one interesting sort of dynamic that's been
26:29
Speaker 3: going on right is the rise of passive investing, which
26:33
Speaker 3: is a wonderful thing.
26:34
Speaker 2: Right.
26:35
Speaker 3: There are many reasons why passive is a wonderful, wonderful
26:37
Speaker 3: thing for investors, right, It's been great for consumers.
26:40
Speaker 2: I love passive investing. I love Vanguard.
26:43
Speaker 3: The only problem I see, and maybe there are others
26:47
Speaker 3: that other people can talk about, the real problem I
26:48
Speaker 3: see with passive investing is that when people go passive,
26:53
Speaker 3: they don't say I'm going to put my money in
26:55
Speaker 3: the S and P four hundred mid Cap Europe Index
26:58
Speaker 3: if such a thing exists. They think I'm gonna put
27:01
Speaker 3: in the S and P five hundred or the Vanguard Total
27:03
Speaker 3: Stock Market Fund.
27:04
Speaker 1: Yeah.
27:04
Speaker 3: And I think when I last did this math, about
27:07
Speaker 3: eighty percent of Vanguard's assets were either in the S
27:10
Speaker 3: and P five hundred or in the Vanguard Total Stock
27:13
Speaker 3: Market Fund.
27:14
Speaker 2: Yeah. Right.
27:14
Speaker 3: In other words, passive has hrded people into the same idea,
27:19
Speaker 3: and when Mordecai Kurtz, who has had that idea of
27:23
Speaker 3: rational expectations.
27:24
Speaker 2: So the thing that we need to be most careful
27:26
Speaker 2: of is correlated beliefs, right.
27:28
Speaker 3: Correlated beliefs are the will create risk When investors' beliefs
27:32
Speaker 3: are too correlated, when everyone thinks the same thing, that's
27:35
Speaker 3: the problem.
27:36
Speaker 1: And there was an interesting bit in the book where
27:37
Speaker 1: you note that around seventy five percent of the US
27:41
Speaker 1: relative app performances come from valuation changes as opposed to
27:44
Speaker 1: revenue and profitability changes. And that's really interesting because it
27:48
Speaker 1: reflects pure optimism as opposed to reality.
27:51
Speaker 3: Which is always the case, Marion, because if you go
27:53
Speaker 3: back to Schiller's work, it's always valuation changes, it's always
27:57
Speaker 3: changes in our expectations about the future that dry the
28:00
Speaker 3: majority of stock market palito is always the case.
28:03
Speaker 1: And then you say, which again I thought was an
28:04
Speaker 1: interesting way to look at it, that perhaps investors who
28:06
Speaker 1: want to think about this a little bit more closely
28:08
Speaker 1: should look at not necessarily at market cap when they
28:12
Speaker 1: come to invest internationally, but look perhaps at percentagive revenues
28:16
Speaker 1: or net income that comes from the US against other countries,
28:19
Speaker 1: and that would be about thirty percent US, right, So
28:22
Speaker 1: that in fact, if you were going to look at
28:24
Speaker 1: it in terms of the revenues from each country, you
28:26
Speaker 1: should have about thirty percent of your efforts in the
28:28
Speaker 1: US as opposed to what you probably do at the moment,
28:30
Speaker 1: which is more like sixty percent, maybe more exactly.
28:33
Speaker 3: And I think the sort of negative side, we've been
28:36
Speaker 3: talking so much about being skeptical of bubbles, but we
28:38
Speaker 3: should also, and this is a big part of my
28:40
Speaker 3: investment strategy, be excited about things people are pessimistic about.
28:43
Speaker 2: And when we see.
28:44
Speaker 3: People giving up, when you see magazine covers about the
28:47
Speaker 3: death of that's the time that I get really excited
28:50
Speaker 3: about things. And I think there's actually a lot to
28:52
Speaker 3: be excited about right now. It's just not where other
28:55
Speaker 3: people are looking. I actually love the UK and Europe.
28:58
Speaker 1: We love to hear that give the Europe bit. We
29:00
Speaker 1: love to hear you love the.
29:01
Speaker 2: UK, you know.
29:04
Speaker 3: And actually it was it was funny. I was I
29:06
Speaker 3: was visiting with a friend who was a big Brexit supporter,
29:10
Speaker 3: and I follow politics as closely as any any normal person,
29:15
Speaker 3: but I honestly didn't follow the UK stuff so much.
29:18
Speaker 3: And I said, well, you know, reading the Ft and
29:20
Speaker 3: the Economist, I've come to the you know, it sounds
29:22
Speaker 3: like it's been a complete disaster. And what were you
29:24
Speaker 3: all thinking? And he said, Dan, you know, pull up
29:27
Speaker 3: your computer and look at UK GDP growth since Brexit
29:30
Speaker 3: and then compare it to continental Europe GDP growth since Brexit.
29:34
Speaker 3: And so I went and did it, and all of
29:36
Speaker 3: a sudden I found the UK had grown faster than
29:38
Speaker 3: continental Europe. And he was like, that's the only argument
29:40
Speaker 3: I need to make, you know, And and I sort
29:43
Speaker 3: of thought to myself, you know, if my narrative about
29:45
Speaker 3: that was a little bit wrong, you know, maybe maybe
29:48
Speaker 3: the common narrative about Europe as a whole is wrong.
29:50
Speaker 3: And I thought I do.
29:51
Speaker 1: I hate to say this down but you need to
29:52
Speaker 1: go and look up GDP per head growth in Okay,
29:56
Speaker 1: all right, that might be a little bit of a
29:58
Speaker 1: downer for you. I'm afraid I'm with the sentiment that breaks.
30:02
Speaker 1: It really hasn't been so bad so far and could
30:05
Speaker 1: even have well, it's likely to have very positive rammications
30:08
Speaker 1: in the future. But GDPEP ahead doesn't tell the same
30:11
Speaker 1: story as GDP. We've had a very fast growing growing population.
30:14
Speaker 3: Sorry, all right, no, no, that's helpful moment. I'll go
30:19
Speaker 3: back and read visit my analysis. But I think you know,
30:22
Speaker 3: when I look globally at valuations, what you see is
30:26
Speaker 3: that Europe is phenomenally cheap. It's cheaper, way cheap relative
30:30
Speaker 3: to long term average, is way cheap relative to the
30:32
Speaker 3: US U CAN in particular. And what's sort of the
30:37
Speaker 3: second layer of that analysis, because you don't want to
30:39
Speaker 3: just be a contrarian for the sake of betorian and
30:42
Speaker 3: you don't want to buy cheap things just to buy
30:44
Speaker 3: cheap things. If the cheap things are bad, you want
30:46
Speaker 3: to buy cheap good things. And one of the interesting
30:49
Speaker 3: things if you look at return on asset type metrics
30:51
Speaker 3: or my favorite gross.
30:52
Speaker 2: Profit to asset.
30:54
Speaker 3: European companies are really high quality businesses. They're very well run,
30:58
Speaker 3: they're very hymerrich, and they're a very higher return asset.
31:01
Speaker 3: And in fact, the sort of leniars have actually that
31:05
Speaker 3: sort of capital starvation has forced the return on assets
31:08
Speaker 3: to go higher. The created higher discount rates, higher bar
31:12
Speaker 3: for new investments, and so when you look at Europe,
31:14
Speaker 3: you're not just buying really cheap companies, you're buying really cheap,
31:16
Speaker 3: really well run, really high return on assets.
31:19
Speaker 1: Absolutely, and same in the UK. You know, we have
31:21
Speaker 1: some really brilliantly run businesses here and they're incredibly cheap
31:25
Speaker 1: relative to similar businesses in.
31:26
Speaker 2: The US, exactly. And it's funny.
31:30
Speaker 3: I did this analysis where I took share of revenue
31:34
Speaker 3: in the US, and then I said whether it's listed
31:37
Speaker 3: in the US, So it was a two part regression.
31:40
Speaker 3: And what I found is that because there are a
31:41
Speaker 3: lot of great UK companies, for example, that have fifty
31:44
Speaker 3: percent or plus of their revenues in the US, right,
31:46
Speaker 3: I mean, it's not unusual. And it turns out that
31:50
Speaker 3: the share of revenue in the US doesn't matter at all,
31:52
Speaker 3: and all that matters is where the company's listed, and
31:55
Speaker 3: I think that sort of relates to this passive investing
31:57
Speaker 3: or the sort of structure of investing that und enlisted
32:00
Speaker 3: companies just treated differently than the US last.
32:02
Speaker 1: Yeah, I mean the problem for us there is that
32:04
Speaker 1: lots of these companies are now looking at whether they
32:05
Speaker 1: can relist somewhere else get a higher evaluation. So we
32:08
Speaker 1: don't want that to happen. We don't want that to
32:09
Speaker 1: happen because we rely on the infrastructure of our capital
32:12
Speaker 1: markets in the UK, so it's a big part of
32:14
Speaker 1: our economy.
32:15
Speaker 3: It's in my mind the greatest trade available at the
32:18
Speaker 3: moment is to buy high quality, cheap European businesses. Sometimes
32:23
Speaker 3: when everybody understands that there's a problem, you almost know
32:27
Speaker 3: it's going to get fixed. So you know, what are
32:29
Speaker 3: the big problems facing here? But what is this Ukraine
32:31
Speaker 3: war right, which is dragged down valuations a lot, And
32:34
Speaker 3: you wonder, like how far off is that from getting fixed?
32:37
Speaker 2: Right? How far off of a piece deal are we?
32:38
Speaker 3: Maybe closer than we think. And I think, second, you
32:41
Speaker 3: know this regulatory burden which is just obviously a problem,
32:45
Speaker 3: and you say, like the UK, for example, Brexit has
32:48
Speaker 3: given the UK an option on deregulation.
32:51
Speaker 2: They haven't exercised that option.
32:52
Speaker 1: Okay, certainly not exercising yet, we have not, but.
32:56
Speaker 3: They bought the option. Brexit bought them the option, and
32:59
Speaker 3: there's a power, the potential deregulation. And if you in
33:02
Speaker 3: Europe can deregulate, and if they can solve the Ukraine issue, right, like,
33:07
Speaker 3: why wouldn't valuations go off?
33:08
Speaker 1: There is the other big problem in Europe under the
33:10
Speaker 1: UK's energy prices right, particularly in the UK is stunning
33:14
Speaker 1: lee high industrial electricity prices.
33:16
Speaker 3: Right, And who knows how that's get solved, but there
33:19
Speaker 3: seems like there'll be a lot of pressure on people
33:21
Speaker 3: to solve it. Yes, and there aren't paths to do it.
33:23
Speaker 1: Yeah, yeah, okay, brilliant. Now that is all fascinating and
33:27
Speaker 1: as I say, fits neatly with lots of my verses.
33:29
Speaker 1: Thank you very much. The other thing I really wanted
33:31
Speaker 1: to talk to you about. You have a chapter in
33:32
Speaker 1: the book about is private equity. And I know that
33:35
Speaker 1: you are very concerned about private equity, and you make
33:38
Speaker 1: this great point that people talk about it as though
33:41
Speaker 1: it's a diversifier. It diversifies us from our equity holdings,
33:44
Speaker 1: but of course, private equity is just equities aren't listed.
33:47
Speaker 1: They're exactly the same, and we should treat them in
33:49
Speaker 1: the same way. And your concern is that there's trouble
33:52
Speaker 1: brewing in that sector.
33:53
Speaker 3: There are a few sort of very important facts to
33:56
Speaker 3: know about private equity. For the first, you know what
33:57
Speaker 3: is private equity? Well, what is a private acta you know,
34:00
Speaker 3: as opposed to a public equity, And it's really two
34:04
Speaker 3: things are different.
34:05
Speaker 2: Right. The first thing is that private.
34:06
Speaker 3: Equities tend to be much smaller than public equities.
34:10
Speaker 2: That they're all microcaps.
34:11
Speaker 3: They have about a two hundred million dollars valuation on
34:14
Speaker 3: equity market cap on average, right, and that's compared to
34:17
Speaker 3: say thirty billion or something for the S and P
34:19
Speaker 3: five hundred, right, And the large end of the microcap
34:21
Speaker 3: in nex is Forourtullion. So the first thing you know
34:23
Speaker 3: is that they're really small companies. What do we know
34:26
Speaker 3: about small companies. We know that small companies have higher
34:28
Speaker 3: default rates than big companies. We know they're riskier, they're
34:31
Speaker 3: less diversified, their lower margin.
34:32
Speaker 2: Right, all of these things.
34:33
Speaker 3: Are stylized true facts about small companies. Of course, right,
34:37
Speaker 3: once you get bigger, you're more stable you're more diversified,
34:39
Speaker 3: you tend to scale vanges, higher margins, right, less volatile,
34:43
Speaker 3: et cetera. But these are small companies, not just small,
34:45
Speaker 3: but really small.
34:47
Speaker 2: Right.
34:47
Speaker 3: So if you love private equity but don't love public
34:50
Speaker 3: small caps or public microcaps, right, ask yourself why what's
34:54
Speaker 3: the disconnect? The second thing I have to remember is
34:57
Speaker 3: that private equity backed companies are a very levered. Generally,
35:02
Speaker 3: fifty to sixty percent of their total valuation is funded
35:05
Speaker 3: by debt, and that's mostly coming now from private credit,
35:08
Speaker 3: and it's usually coming at very high rates. And I
35:12
Speaker 3: joke that lending is the second oldest profession. There are
35:15
Speaker 3: no new innovations in lending. And so if a company
35:18
Speaker 3: has to borrow at very high rates, the reason they
35:20
Speaker 3: have to borrow at high rates is that they're very risky.
35:23
Speaker 3: And so you're looking at equity that's subordinated a very
35:25
Speaker 3: high interest rate debt issued by these private credit firms.
35:30
Speaker 3: That is reflective of the underlying risk and the underlying
35:33
Speaker 3: volatility of these businesses. Now, the reason people don't think
35:37
Speaker 3: it's risky is because it's private, and so you only
35:39
Speaker 3: get a mark once a quarter. And who does the mark? Accountants? Well,
35:43
Speaker 3: if you look at the volatility of private equity marks,
35:46
Speaker 3: it's about as volatility as the volatility of book value
35:49
Speaker 3: of public companies. It just isn't related to the market.
35:53
Speaker 3: And so what people get fooled by that lack of
35:55
Speaker 3: volatility into thinking that these tiny little companies with a
35:58
Speaker 3: ton of debt really aren't fair very risky, And of
36:01
Speaker 3: course they are.
36:02
Speaker 2: They're very risky.
36:03
Speaker 3: We just haven't realized that risk yet because we've had
36:06
Speaker 3: a period of very declining rates. And then I think
36:09
Speaker 3: coincidentally or not coincidentally, but importantly, you know, private equity
36:14
Speaker 3: over the past ten years has massively shifted in its
36:17
Speaker 3: sector composition to focus heavily on technology stocks, and that's
36:21
Speaker 3: been a boon, But any turn in the future of
36:25
Speaker 3: these tech the tech industry is massively going to hurt
36:28
Speaker 3: private equity. It's become a highly levered bit on microcap
36:33
Speaker 3: software companies and.
36:34
Speaker 1: Also very expensive. I'm one of the things about to
36:37
Speaker 1: when when the whole idea that you could invest in
36:39
Speaker 1: private equity is a massive diversify. First began was private
36:42
Speaker 1: eqty companies but very cheap, right, well, you could get
36:45
Speaker 1: them at a stonking discount to publicly listed equities, and now,
36:48
Speaker 1: of course that is no longer true, and in fact,
36:50
Speaker 1: the valuations of private equity companies tend to come in
36:52
Speaker 1: above those of publicly listed.
36:54
Speaker 3: Right, Like, why should I pay more to have a
36:56
Speaker 3: higher risk a smaller, smaller, more risky, more lever company
37:01
Speaker 3: that I can't buy and sell every day? Why should
37:03
Speaker 3: that be more expensive? It just boggles the mind. And
37:06
Speaker 3: I think, you know, we've seen this, this correlated belief, right,
37:09
Speaker 3: it's a correlated belief. But from all these pension funds
37:12
Speaker 3: and college endowments and fancy investors that you need to
37:15
Speaker 3: invest like Yale, you need to invest like David Swinson.
37:18
Speaker 3: You need to have maybe forty percent of your assets
37:20
Speaker 3: in private equity. And I did the simple math, which
37:24
Speaker 3: is to say, you know, if you take the aggregate
37:27
Speaker 3: size of private equity backed companies, you know how big
37:31
Speaker 3: are those companies relative to public companies? And they're about
37:35
Speaker 3: two to four percent of the total revenue of public companies. Right,
37:40
Speaker 3: So it's a tiny, tiny, tiny set of companies. And
37:43
Speaker 3: so to have forty percent of your assets and two
37:46
Speaker 3: percent of the company and two percent of the revenue
37:48
Speaker 3: share of the companies, right, because there are a lot
37:50
Speaker 3: of small companies, they just don't make much money.
37:52
Speaker 1: That seems completely insane when you put it like that,
37:54
Speaker 1: completely insane, But it's very nice for fund managers or
37:58
Speaker 1: for people managing large pool with money, because it looks
38:02
Speaker 1: better with this moothing. It looks less volatile, it looks
38:06
Speaker 1: it looks calmer, it looks like a Diversifyer's quite relaxing
38:09
Speaker 1: for you. Really, you don't have to deal with that,
38:11
Speaker 1: you know, pricing every day nonsense.
38:14
Speaker 3: Exactly, and you get this veneer being able to tell
38:16
Speaker 3: everyone that you improve companies, right, like, yes, I'm a
38:19
Speaker 3: hedge fund manager. I buy and sell shares. You know,
38:21
Speaker 3: what do I contribute to society? What do I know
38:23
Speaker 3: about companies? How can you feel that good about investing?
38:25
Speaker 3: Like maybe I'm a little smarter, you're right, Like, well,
38:28
Speaker 3: with private equity, you know, I've been on the board
38:30
Speaker 3: and I really helped the company grow, and I've talked
38:32
Speaker 3: to them about this new product and then we you know,
38:34
Speaker 3: we open a new factory. Its sounds better. And I
38:38
Speaker 3: think it's actually hogwash, right like you know, and you
38:41
Speaker 3: sort of know it's hogwash by just looking at the
38:43
Speaker 3: LinkedIn profiles of who works in private equity, right, Like
38:47
Speaker 3: they're all former bankers, right if this is.
38:49
Speaker 1: Exactly the point where I say to all the listeners,
38:51
Speaker 1: send your hate mail directly to Dan, don't send it
38:55
Speaker 1: to us, and directly to Dan. He's ready.
38:58
Speaker 3: But it's like, you know, when did when did the
39:00
Speaker 3: two years you spent building Excel and PowerPoint models as
39:03
Speaker 3: a junior banker, you know, give you this great insight
39:06
Speaker 3: on how to run like mid market industrial companies in Germany?
39:09
Speaker 2: Right? Why does that logical?
39:11
Speaker 3: I'd be like, oh God, it's going to do so
39:12
Speaker 3: much better under private equity management. It's like, okay, so
39:15
Speaker 3: the junior banker from Goldman is going to do that
39:17
Speaker 3: much better of a job than like the fifty year
39:19
Speaker 3: old veteran.
39:20
Speaker 1: Oh, if you're running that business for thirty years, it
39:23
Speaker 1: seems much more plausible that what the banker is really
39:25
Speaker 1: good at is adding a lot of debt to the.
39:27
Speaker 3: Balance sheet and doing ad on acquisitions and maybe you know,
39:30
Speaker 3: dressing it up for sale. They seem good at, but
39:34
Speaker 3: the idea that they're better at running companies just seems
39:36
Speaker 3: a little crazy.
39:37
Speaker 1: Well, we'll find out soon with me, because a lot
39:38
Speaker 1: of private equity companies they're going to have to start
39:40
Speaker 1: moving assets on and they can't keep handing them around
39:42
Speaker 1: between each other. So there's going to be surely a
39:44
Speaker 1: spate of listings coming up where we will see what
39:47
Speaker 1: private equity companies are really worth in public markets, and
39:50
Speaker 1: that will be fascinating. Okay, interesting, right, something completely different.
39:54
Speaker 1: You talk about gold a little in the book and
39:58
Speaker 1: when and when you shouldn't invest in golden You have
40:00
Speaker 1: a lot of gold bug listeners, and I'm a little
40:02
Speaker 1: bit of a gold bug myself, so maybe we could
40:04
Speaker 1: talk a little bit about your views on gold and
40:07
Speaker 1: where they fit in this where it fits in this cycle.
40:10
Speaker 3: Yeah, I think gold is a very important portfolio tool,
40:15
Speaker 3: and if you think about why it's.
40:16
Speaker 2: An important portfolio tool.
40:18
Speaker 3: We need some low risk diversifying assets, right, and one
40:22
Speaker 3: low risk, diverse fying acid is bonds, and one low
40:24
Speaker 3: risk diverse fying acid is gold. The challenge with bonds
40:28
Speaker 3: is that they react very natively to inflation, and our
40:31
Speaker 3: country economy has had a bit of an inflation problem
40:34
Speaker 3: of late and gold, in the opposite way, reacts positively
40:38
Speaker 3: to inflation because you can inflate the currency. But the
40:41
Speaker 3: price of gold should be unaffected. And so what I
40:44
Speaker 3: think is that you should depend your low risk portfolio
40:48
Speaker 3: should alternate between bonds and gold depending on your views
40:50
Speaker 3: of whether inflation is present. If you're worried about inflation,
40:53
Speaker 3: you should have more gold and fewer bonds, and if,
40:56
Speaker 3: on the other hand, you're worried about deflation, you shouldole
40:58
Speaker 3: more bonds.
40:58
Speaker 2: And less gold.
41:00
Speaker 3: But the idea that gold has to be a tool
41:03
Speaker 3: that you're using. It's so important and it trades so
41:07
Speaker 3: differently that it gives your portfolio more degrees of freedom
41:10
Speaker 3: if you include it in the parameter of things you're considering,
41:13
Speaker 3: and you don't have to have a big allocation for
41:15
Speaker 3: it to make a big difference.
41:16
Speaker 1: Okay, and what about bitcoin? You I notice you do
41:19
Speaker 1: not mention at all in the.
41:21
Speaker 2: Book, Oh dear bitcoin.
41:24
Speaker 1: I mean is that you clearly are not going to say, well,
41:26
Speaker 1: bitcoin is digital gold. It's the same thing. I'm not
41:29
Speaker 1: hearing you saying that.
41:30
Speaker 2: I'm not saying that because I don't think it's true.
41:32
Speaker 3: I said that gold was a low risk asset, right,
41:35
Speaker 3: Look at the volatility of gold. It's like the volatility
41:37
Speaker 3: of bonds. It is a low risk asset. Bitcoin has
41:40
Speaker 3: the volatility of a the nastac or microcaps. Right, it's
41:44
Speaker 3: crazily vallatile. So it's not low risk, it's high risk.
41:47
Speaker 3: And then what's it correlated with?
41:48
Speaker 2: Right?
41:48
Speaker 3: Gold is sort of anti correlated. Gold's its own thing,
41:51
Speaker 3: It marks to its own tomb. That's why it's valuable.
41:55
Speaker 3: But bitcoin is not. Bitcoin is very correlated with say
41:58
Speaker 3: that Goldman sacks highly shorted as good of US talks.
42:01
Speaker 3: It's very correlated with robinhood stock. Right, It's correlated with
42:04
Speaker 3: any type of gambling activity that you see in public markets.
42:08
Speaker 2: And I think it's.
42:09
Speaker 3: Part of a broader trend towards people finding gambling opportunities
42:14
Speaker 3: in public markets as opposed to find them betting on
42:16
Speaker 3: sports teams.
42:17
Speaker 1: Yeah. Interesting. Do you think now, as that there's lots
42:19
Speaker 1: more institutional interest in it and there's even be a
42:22
Speaker 1: lot of passive investment into bitcoin, that it might get
42:25
Speaker 1: caught up in the same sort of momentum trade as
42:28
Speaker 1: perhaps a lot of the US tech companies have over
42:30
Speaker 1: the last couple of years.
42:31
Speaker 3: I think it certainly will, and I think institutional adoption
42:34
Speaker 3: of bitcoin today is about as smart as institutional adoption
42:38
Speaker 3: of investing in China and twenty seventeen or twenty eighteen.
42:41
Speaker 3: It's equally as much of a mania and it's equally
42:42
Speaker 3: as dumb.
42:43
Speaker 1: Okay, I think we have a very clear view there.
42:45
Speaker 1: And again, just let me repeat hate mail direct to
42:48
Speaker 1: Dan done. Can we find you on Twitter so they
42:50
Speaker 1: can send you a hate mail? Director you on Twitter,
42:52
Speaker 1: because that's where I get those? Absolutely, what'd you handle there?
42:54
Speaker 1: Just to make apple sure it goes to you.
42:56
Speaker 2: Not me? It's at verdad cap.
42:58
Speaker 1: Okay, everybody, if you feel strongly about big cooeen filst,
43:00
Speaker 1: strongly about private equity, strongly about any of those things,
43:03
Speaker 1: please let Dan know directly, and do not copy me
43:06
Speaker 1: into your aggressive tweet. Thank you. Okay. So at the end,
43:11
Speaker 1: I normally try and ask people what they would invest
43:13
Speaker 1: in now, but I think we have a pretty clear
43:14
Speaker 1: steer from you on the value front. That you're interested
43:17
Speaker 1: in UK equities, you're interested in Europeean equities. Is there
43:20
Speaker 1: any sector in particular of that interests you, or any
43:23
Speaker 1: part of the market, or any even any particular company
43:25
Speaker 1: that you're finding fascinating at the moment?
43:28
Speaker 2: You know, I actually like Eastern Europe.
43:30
Speaker 3: I find a lot of interesting things in Poland and
43:32
Speaker 3: I think that people have tended to overlook Eastern Europe
43:35
Speaker 3: in particular because of the Ukraine War, but I think
43:37
Speaker 3: it also is the most leverage to any peace deal
43:40
Speaker 3: going through that you'll make money in Polish equities.
43:43
Speaker 2: They're very thinly traded.
43:44
Speaker 3: You have to buy small caps, but I think it's
43:46
Speaker 3: quite attractive.
43:48
Speaker 1: Okay, that is interesting. Poly small caps have never come
43:51
Speaker 1: up on this podcast before, So thank you very much
43:54
Speaker 1: for that. Congratulations something something you go. Okay, last ques
44:00
Speaker 1: your book. I think it's excellent, and just to repeat again,
44:03
Speaker 1: everybody by this book is excellent. Everything we've talked about
44:06
Speaker 1: is in the books. A whole load more we didn't
44:08
Speaker 1: get onto Private credit. Another fascinating chapter in it, so
44:11
Speaker 1: and the bond chapter also excellent. Do read that. But Dan,
44:14
Speaker 1: if you were going to recommend one book written by
44:16
Speaker 1: somebody else, is there anything you've been reading recently that
44:19
Speaker 1: you've really enjoyed and think would be helpful for our listeners.
44:23
Speaker 3: Well, I don't know about helpful to your listeners, but
44:25
Speaker 3: by far the best book that I've read recently is
44:27
Speaker 3: the History of the Conquest of Mexico by William Prescott,
44:31
Speaker 3: which came out in eighteen thirty and it tells the
44:34
Speaker 3: unbelievable story of how Corte has conquered Mexico in fifteen
44:38
Speaker 3: tens and as a story that I like glossed over
44:41
Speaker 3: in the history textbooks, but it is unbelievably fascinating, you know,
44:45
Speaker 3: eight hundred men conquering several hundred thousand a person civilization
44:51
Speaker 3: in It's just an insane.
44:54
Speaker 2: Story and beautifully written.
44:55
Speaker 3: So if you're looking from a break from markets, I
44:57
Speaker 3: recommend it.
44:58
Speaker 1: I imagine people are going to be a for a
45:00
Speaker 1: break from markets relatively soon this year. But we'll see you.
45:04
Speaker 2: Dan.
45:04
Speaker 1: Thank you so much for joining us today and congratulations
45:06
Speaker 1: on an excellent book. Thank you, Marion, thanks for listening
45:15
Speaker 1: for this week's Maren Talks Money. If you like our show,
45:17
Speaker 1: rate review and subscribe wherever you listen to podcasts, and
45:20
Speaker 1: keep sending questions or comments to Marin Money at Bloomberg
45:23
Speaker 1: dot net. You can also follow me and John on
45:26
Speaker 1: Twitter or x. I'm at Marin sw and John is
45:30
Speaker 1: John Underscore Stepic. This episode were hosted by Me Maren
45:33
Speaker 1: Sumset Web was produced by Samasadi, Production support from Moses
45:36
Speaker 1: and and special thanks to Dan Rasmussen.