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Speaker 1: This is Master's in Business with Barry rid Holts on

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Speaker 1: Bloomberg Radio. This week on the podcast, I have an

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Speaker 1: extra special guest, William J. Bernstein, author of so many

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Speaker 1: fascinating books about finance, as well as being a practitioner

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Speaker 1: UH Efficient Frontier Advisors runs a nice lug of money

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Speaker 1: for ultra high net worth clients. What's so fascinating about

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Speaker 1: Bernstein is how he began his career as a neurologist

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Speaker 1: and then transition to being a financial theorist and and

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Speaker 1: money manager and book author. Really an amazing um career

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Speaker 1: path and and a fascinating conversation with no further ado.

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Speaker 1: My conversation with William Bernstein. I'm Barry Ridholts, your listening

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Speaker 1: to Masters in Business on Bloomberg Radio. My special guest

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Speaker 1: this week is William Bernstein. He began his career as

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Speaker 1: a neurologist before becoming a financial theorist and investment advisor.

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Speaker 1: He is the author of nearly a dozen books, many

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Speaker 1: of which cover finance, including The Intelligent Asset Allocator, The

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Speaker 1: Four Pillars of Investing, The Investors Manifesto, and several others.

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Speaker 1: He has also written several works of historical interest including

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Speaker 1: a splendid exchange all about global trade and the birth

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Speaker 1: of plenty, as well as masters of the word. William Bernstein.

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Speaker 1: Welcome to Bloomberg. Happy to be here, Barry. So, I've

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Speaker 1: been looking forward to this conversation for quite a while.

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Speaker 1: You and I have been emailing for several years. Um,

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Speaker 1: you have such a fascinating background and so unusual. Before

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Speaker 1: you became a professional investor and an author, you're a neurologist.

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Speaker 1: How long did you do that for and what made

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Speaker 1: you transition into finance. Well, I did it more or

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Speaker 1: less for a third of a century. And I transitioned

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Speaker 1: into finance and nonfiction writing by virtue of the fact

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Speaker 1: that I live in a country that doesn't have a

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Speaker 1: functioning social welfare system, and so I had to uh

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Speaker 1: save and invest on my own. And I approached the

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Speaker 1: problem in a way that I thought that any person

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Speaker 1: with scientific training would do, which is that you examine

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Speaker 1: the peer reviewed literature, You read the basic texts, you

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Speaker 1: collect data, you built models. And this got me to

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Speaker 1: about the mid nineteen nineties, and by that point I

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Speaker 1: realized that I had created something that was actually of

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Speaker 1: use too small investors, and so I began writing finance,

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Speaker 1: and as I'm sure we'll get into later in the interview,

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Speaker 1: one of the essential skills that any investor should have

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Speaker 1: as a working knowledge of financial history. And I discovered

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Speaker 1: that I enjoyed writing history, and so I segue uh

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Speaker 1: into that do you miss medicine at all? I miss

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Speaker 1: the camaraderie, I miss dealing, the personal interaction with patients,

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Speaker 1: which is golden uh. And and you know I I

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Speaker 1: missed the knowledge base and the competence that you exert.

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Speaker 1: But the day to day practice of medicine does wear

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Speaker 1: on you after a while. Uh. And there comes a

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Speaker 1: point I think in every doctor's career when or at

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Speaker 1: least most physicians careers, when they decided to call it quits.

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Speaker 1: So one of the things you did you mentioned data.

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Speaker 1: You assembled an asset class database before they were really

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Speaker 1: a philiple publicly. Uh. Why did you go about doing this?

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Speaker 1: And where did you get your data from? I basically

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Speaker 1: begged people uh for for data uh. And I just

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Speaker 1: collected as many data series as I could, and I

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Speaker 1: wanted to basically create what's called a mean variance optimizer,

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Speaker 1: which is something trades off return and risk measured as

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Speaker 1: standard deviation or variance and as much data as you

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Speaker 1: can throw into that is good. And so that was

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Speaker 1: why I collected all of those data. Now it turns

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Speaker 1: out that that sort of exercises of fools errand, as

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Speaker 1: I very quickly figured out. But it's still a useful skill,

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Speaker 1: and it was a useful thing to do for small investors. Well,

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Speaker 1: why is it a fool's errand other than the fact

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Speaker 1: that the data is relentless and it never stops, it's

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Speaker 1: a fool's Errand because the output of a mean variance

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Speaker 1: optimized or that is, what are the most efficient portfolios?

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Speaker 1: Giving you the most return for the least amount of

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Speaker 1: risk or vice versa, giving you the least risk for

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Speaker 1: a given amount of return is extremely sensitive to the

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Speaker 1: data that you put into it. So change the return

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Speaker 1: of an asset class by percent or two in either direction,

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Speaker 1: and it might completely dominate a portfolio or it might

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Speaker 1: completely fall out of the portfolio. These things started to

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Speaker 1: come onto people's desktops UH in the early nineteen nineties,

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Speaker 1: and when they tossed in historical data, what did they find. Well,

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Speaker 1: they found that the most efficient portfolios were heavy in

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Speaker 1: Japanese stocks UH and precious metal stocks, case closed. That's

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Speaker 1: all you have to know. Uh. And TPS nine was

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Speaker 1: the peak of the Japanese market and has yet to

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Speaker 1: recover those heights since exactly. And what some wags refer

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Speaker 1: you know to to a mean variance optimizer is as

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Speaker 1: an error maximizer. Just for that reason. That's really great.

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Speaker 1: So so you create a website called the Efficient Frontier.

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Speaker 1: What made you do this and what made you decide

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Speaker 1: to start putting all of your writings up in that

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Speaker 1: one place. Well, I'll give credit to a man by

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Speaker 1: the name of Frank Armstrong who is a financial advisor

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Speaker 1: in Florida. Uh, and he had done pretty much the

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Speaker 1: same thing. He hadn't collected the data, but he was

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Speaker 1: on the web before any you know, financial writing, before

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Speaker 1: anybody else was. And this goes back to well before

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Speaker 1: and uh, he encouraged me to do it. I had,

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Speaker 1: you know, after I completed the exercise, I wrote a

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Speaker 1: book called The Intelligent act Allocator, my first book, and

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Speaker 1: I approached a bunch of publishers with it, and of course,

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Speaker 1: being someone with no experience and no credentials, you know,

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Speaker 1: just just a manuscript coming in over the trans and

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Speaker 1: it got rejected by thirty thirty publishers, and Frank told me, hey,

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Speaker 1: just put the book on the web, and that's basically

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Speaker 1: how it took off. That was what was your first

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Speaker 1: published book? If that wasn't your first book, that was it.

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Speaker 1: That was it? So so you eventually got a publisher

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Speaker 1: for that. Yeah. The story is is that a man

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Speaker 1: by the name of Robert Barker, who was a reporter

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Speaker 1: for Business Week, actually came to interview me in about

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Speaker 1: uh and I told him the story and I can

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Speaker 1: still see look on his face as I told him

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Speaker 1: the story about the publishers, and he said, dear God,

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Speaker 1: please tell me that one of them wasn't McGraw hill.

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Speaker 1: And I said, well, yes it was. And he then

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Speaker 1: owner of Business Week now by Bloomberg LP right, and

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Speaker 1: he hit his you know, sort of made a show

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Speaker 1: of mock, putting his face in his hands, shaking his head.

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Speaker 1: And then six weeks later I got an offer from

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Speaker 1: McGraw hill. He swears he has nothing nothing to do

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Speaker 1: with it, but of course I didn't believe him. That.

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Speaker 1: That's absolutely hilarious. So so, given the nature of data

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Speaker 1: now being ubiquitous, how is this changing the world for

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Speaker 1: for investors? And for advisors. Well, uh, you know, I

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Speaker 1: think it was Bernard Baruk who said that something that

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Speaker 1: everyone knows isn't worth knowing. Uh, So that if everybody

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Speaker 1: has these data and can operate on them, uh, then

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Speaker 1: they become nearly nearly worthless. Gene Fama makes the point,

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Speaker 1: uh that everybody is basically working off the same data

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Speaker 1: as you know, going back to basically nineteen six. Uh.

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Speaker 1: And it's you have to be very cautious about different

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Speaker 1: studies that are still using based on the same database,

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Speaker 1: because I think it was Samuelson who said, we only

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Speaker 1: have two hundred years of history. Uh, and that's not

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Speaker 1: the complete that's not the complete sample. I think Roger

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Speaker 1: Ibbotson and the folks said, CRISP just backdated that from

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Speaker 1: six back another hundred and fifty or so years. Not

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Speaker 1: that there was a lot of data back then. It was, um,

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Speaker 1: a whole lot less companies and a whole lot less trading.

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Speaker 1: But the full run of of publicly traded US companies

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Speaker 1: I think goes back now to the early eighteen hundreds

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Speaker 1: if I'm remember that correctly. Yeah. Yeah, And and there

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Speaker 1: are people who've who've who've got probably far less uh

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Speaker 1: detailed databases than than Rogers. And of course you can

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Speaker 1: go you know, you can look at English stocks and

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Speaker 1: you you can at least get monthly and annual returns

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Speaker 1: all the way back to the at seventeenth century. So

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Speaker 1: one of the things you you've written, which I find

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Speaker 1: quite intriguing, is that most returns are determined by the

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Speaker 1: asset allocation of the portfolio rather than the assets selection.

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Speaker 1: Explain that, well, there are risky assets and there are

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Speaker 1: risky riskless assets, you know, Tobin separation theorem. Uh. And

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Speaker 1: that's that's how I view portfolios. Uh. Is You've got

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Speaker 1: the stuff that helps you sleep at night, and you

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Speaker 1: want to keep that as safe as possible. Things with

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Speaker 1: a government guarantee. Uh. That's you know, that's next month's

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Speaker 1: grocery money. Uh. And then there's the stuff which you're

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Speaker 1: really not going to be touching or shouldn't be touching

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Speaker 1: for decades, and that's the risky stuff. Uh. And that's

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Speaker 1: really all there is to it. And I think that

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Speaker 1: I think it is a bit of a mistake, not

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Speaker 1: a serious mistake, but a bit of a mistake to

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Speaker 1: mix the two. So junk bonds, for example, corporate bonds

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Speaker 1: in general, I think are our mistake. Anything where you're

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Speaker 1: reaching for yield is not optimal. That's correct. Yeah, Yeah,

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Speaker 1: Duration I'm sort of neutral about. You can make the case,

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Speaker 1: as you well know, that duration is certainly a risk,

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Speaker 1: particularly in an inflationary environment, but when the excrement really

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Speaker 1: hits the ventilating system, duration is generally a good thing.

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Speaker 1: Let's talk a little bit about physicians and why they're

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Speaker 1: such terrible investors. My instinct is to say it's ego

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Speaker 1: and an excess of misplaced confidence. I think you're gonna

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Speaker 1: say something else, what why are doctors such bad investors? Well,

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Speaker 1: you've you've hit two of the high points. But the

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Speaker 1: major reason I think is that they don't take investing seriously.

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Speaker 1: A physician, and I think most physicians who are properly

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Speaker 1: trained will not treat so much as a cold without

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Speaker 1: a detailed review of the peer reviewed literature, discussing things

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Speaker 1: with their their colleagues, uh, and you know, a thorough

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Speaker 1: review of the database that's available to them. On the

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Speaker 1: other hand, physicians, when they approach investing will do it

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Speaker 1: by you know, reading the Wall Street Journal or USA

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Speaker 1: Today or Kiplinger's Uh. And the way I explain that

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Speaker 1: to them is you know, when you have to treat

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Speaker 1: someone with a serious disease, you don't get your information

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Speaker 1: from psychology today or USA today. You go and you

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Speaker 1: look at the most authoritative sources. Investing is exactly the

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Speaker 1: same sort of subject. It's a serious endeavor. And just

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Speaker 1: like in order to do medicine, you have to start

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Speaker 1: with the basics anatomy, physiology, pathology, pharmacology. Uh so too

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Speaker 1: when you approach investing, you should exert a similar amount

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Speaker 1: of effort. You should learn about the theory of investing.

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Speaker 1: You should learn about the history of finance and of investing.

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Speaker 1: You should learn about its psychology. And lastly, you have

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Speaker 1: to learn about the business aspects of investing the people

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Speaker 1: who are selling you the products. That sounds a lot

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Speaker 1: like the four pillars of investing. Those are the four

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Speaker 1: broad categories theory, history, psychology, and actual business. The brand

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Speaker 1: envelope is in the mail, so let's talk a little

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Speaker 1: bit about that. How did you come to the conclusion

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Speaker 1: that those four um broad subject areas are what underlies

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Speaker 1: each investors or should underlie each investor's theory, the four

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Speaker 1: pillars that support their portfolio well by observing the mistakes

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Speaker 1: that people make, and I found that people made four

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Speaker 1: basic mistakes. Number one is they didn't understand market theory,

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Speaker 1: financial theory. They didn't understand that there's a correlation between

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Speaker 1: risk and return. It's the almost like the law of

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Speaker 1: gravity in investing. And they didn't understand the theory of diversification. UH.

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Speaker 1: And they didn't understand basic portfolio theory how you mix assets. Secondly,

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Speaker 1: they didn't understand the history UH. And that came whom

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Speaker 1: uh during the tech bubble of the late nineteen nineties,

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Speaker 1: when people had absolutely no idea that they were living

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Speaker 1: through something that had happened many times before. Uh. There

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Speaker 1: was a script to the movie, and if you read

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Speaker 1: the script, you knew how the movie ended. UH. And

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Speaker 1: of course of the people who invested in the nineties

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Speaker 1: did not know how that particular movie movie ended. There's

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Speaker 1: a psychological aspect of investing which you've alluded to. People

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Speaker 1: become overconfident, and it's not just that they're overconfident about

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Speaker 1: their ability to invest, but they're also overconfident about their

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Speaker 1: ability to bear risk. They throw, if they're smart, they

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Speaker 1: throw something into a spreadsheet, they throw a simulation, and

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Speaker 1: there was spreadsheet and they say, ah, here, I've lost

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Speaker 1: thirty or forty percent of my money but only lasted

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Speaker 1: for a brief period of time. I can ride that through, UM,

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Speaker 1: but there's a big difference between doing that in real

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Speaker 1: time and doing that in a spreadsheet. And way I

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Speaker 1: like to describe that is it's kind of like the

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Speaker 1: difference between crossing an airplane and a flight simulator and

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Speaker 1: doing it for real. Uh. Your your your your pucker

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Speaker 1: factor as pilots like to call it, uh changes and

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Speaker 1: then finally, UH, what you also uh find is that

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Speaker 1: physicians and a lot of people really don't understand the

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Speaker 1: conflicts of interest that are inherent in the business. Which

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Speaker 1: is a very polite way of saying that the financial

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Speaker 1: services industry uh maybe the country's largest repository of criminal activity. Well,

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Speaker 1: let's hold aside the actual criminal activity and look at

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Speaker 1: what's legally extracted in terms of fees. There was a

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Speaker 1: big debate about the fiduciary rule UM, coming from the

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Speaker 1: last administration to this one that people who were in

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Speaker 1: the business of managing other people's money argues, the camp

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Speaker 1: that I'm in should behave like doctors and lawyers and

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Speaker 1: account is where the client's best interest has to come first.

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Speaker 1: But a lot of Wall Street thinks that that is problematic.

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Speaker 1: It will impact fees at will impack services. What's your

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Speaker 1: view on the fiduciary rule. Oh, I think it's a

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Speaker 1: superb idea, and I think it's only a start. I

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Speaker 1: think the odds that you know, we're going to see

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Speaker 1: that in this administration, whether it lasts another two or

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Speaker 1: six two or six years, is about the same as

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Speaker 1: you and my starting at shortstop for the Yankees. I

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Speaker 1: got a good glove. Okay, well, good, I'm I'm, I'm

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Speaker 1: I'm you know, I'm short and I can't jump the

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Speaker 1: rotator cuff. I won't be able to anyone who's fast

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Speaker 1: will beat the throw to first. But other than that,

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Speaker 1: but but there's there's certain things that should just flat

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Speaker 1: out be, you know, felonies. It should be a felony

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Speaker 1: to place, for example, an insurance product within a retirement account. Okay,

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Speaker 1: so wait, you don't think putting an expensive tax defer

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Speaker 1: annuity in a four oh three B or otherwise tax

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Speaker 1: DEFEROD account is problematic? You you have an issue with that,

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Speaker 1: I'm afraid, I'm afraid I do. Uh And you know,

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Speaker 1: and I think there's certain products that should just flat

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Speaker 1: out the be outlawed. I think that, you know, uh,

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Speaker 1: double and triple and inverse H E T F s

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Speaker 1: are basically a mathematically certain way in the long term

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Speaker 1: of losing money. UH. And the rationales that are given

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Speaker 1: further use are that while they're useful for short term timing,

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Speaker 1: well you shouldn't be doing that either, you know. I

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Speaker 1: mean that's you know, short term timing of the market

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Speaker 1: is is one of those activities that's up there with

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Speaker 1: with high risk sex and UH and skydiving and visiting

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Speaker 1: a saudy consular. UH. If you're if you're an American journalist,

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Speaker 1: is exactly yes, you know it's funny. Um, I we'll

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Speaker 1: we'll move this to the back of the segment. But

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Speaker 1: I was doing research on four oh three B for

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Speaker 1: a column I was writing for Bloomberg, and I discover ward,

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Speaker 1: this is your point is so well taken about history

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Speaker 1: impacting how you think about things. As it turns out,

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Speaker 1: the four H three B the retirement plan for teachers

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Speaker 1: for state workers, for anybody who works for a charity

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Speaker 1: or nonprofit. It predates four O one case by decades

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Speaker 1: and was passed by Congress to sort of apparently a

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Speaker 1: number of charities were doing these all insurance based products

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Speaker 1: for their employees. They were inexpensive, they were tax deferred.

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Speaker 1: There was no other alternative, and Congress wanted to extend

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Speaker 1: that to everybody, including people who worked in various churches.

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Speaker 1: And that's sort of the history of four H three B.

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Speaker 1: And once the rules were changed and you you had

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Speaker 1: this tax deferral built in and there was no longer

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Speaker 1: need for an insurance product, the momentum in the infrastructure

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Speaker 1: around that didn't go away. And that's part of the

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Speaker 1: reason we see four three bees jam fold of overpriced,

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Speaker 1: inappropriate tax deferd annuities that are better off you know, nowhere,

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Speaker 1: but certainly not in a a tax deferred um nonprofit

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Speaker 1: retirement account. It's quite fascinating. I thought I would I

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Speaker 1: would mention that. I just thought it was really interesting.

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Speaker 1: All right back to where we were. Um, So, have

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Speaker 1: your thoughts and ideas changed about asset allocation over time

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Speaker 1: or was the original research compelling? And you've you've stayed

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Speaker 1: with where you began a good couple of decades ago.

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Speaker 1: I haven't changed my my point of view very very much.

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Speaker 1: I mean, one of the sort of sardonic things I

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Speaker 1: like to say about finance and how it's different from

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Speaker 1: other serious fields of endeavor, is it, if you want

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Speaker 1: to be a good doctor, you've got to internalize thousands

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Speaker 1: of uh medical articles uh and pieces of research. The

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Speaker 1: same thing with you know law and and all the

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Speaker 1: case law you you have to know. But I'm pretty

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Speaker 1: sure that that any competent practitioner could put up a

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Speaker 1: list of two dozen peer reviewed articles that if you

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Speaker 1: knew them, uh you and you had fully internalized them, uh,

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Speaker 1: you would know pretty much all that you have to

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Speaker 1: know at a practical level. So that's another way of saying,

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Speaker 1: there's not much new that comes out uh every year. Uh.

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Speaker 1: That's that's worth that's worthwhile. I mean, just the past

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Speaker 1: several months, there was an article published by the Abu

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Speaker 1: Dhabi Investment Authority on shared delution and long term equity returns.

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Speaker 1: Very important article because it showed that in the long term,

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Speaker 1: it's delution of shares or its opposite net buy backs

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Speaker 1: that determine returns and so you can explain, for example,

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Speaker 1: the really just awful returns of Chinese stocks. This is

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Speaker 1: a market with with with a lot of economic growth

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Speaker 1: and back of it. But the returns have been about

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Speaker 1: the worst of of any large national market be cause

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Speaker 1: of the delution. On the other hand, when you look

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Speaker 1: at the winners over the past hundred years, you know,

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Speaker 1: countries like the US, Sweden, Canada, the UK, Australia, South Africa,

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Speaker 1: those have been the countries that have deluded their share

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Speaker 1: pools the least. Quite fascinating. So let's talk a little

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Speaker 1: bit about the efficient Frontier Advisors LLC, where you manage assets.

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Speaker 1: What motivated you to shift from being a doctor to

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Speaker 1: an asset manager. Well, when you publish finance books and

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Speaker 1: you find yourself, you know, quoted in national media, people

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Speaker 1: start asking you to manage money. It's it's that simple. Uh.

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Speaker 1: And so at a certain point you just can't say

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Speaker 1: no anymore. Pretty much, Yeah, pretty much. And some people

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Speaker 1: do say now, but I I didn't, And I was

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Speaker 1: fortunate enough to be in contact with someone who already

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Speaker 1: had an advisory service h up and running, a woman

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Speaker 1: by the name of Susan Sharon, and uh we got

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Speaker 1: together on the internet. Uh, and we've been in business

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Speaker 1: for the past twenty one years. Wow, that's quite interesting.

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Speaker 1: So you describe this as a boutique investment advisory UM

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Speaker 1: intentionally designed for a limited number of clients. What what's

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Speaker 1: the thinking there? Well, the thinking is that both of

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Speaker 1: us have already had careers, uh, and we're at an

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Speaker 1: age when we don't want to do anything. Uh that

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Speaker 1: isn't fun. Uh. And it's not fun managing money for

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Speaker 1: people who don't know anything about finance. So we restrict

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Speaker 1: our practice to people who have a solid basis of

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Speaker 1: knowledge of financial theory and of financial history. Uh. But

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Speaker 1: I have to I have to interrupt you there. So

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Speaker 1: it's more than just hey, you need a twenty million

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Speaker 1: dollar minimum. It's you have to understand what we're talking

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Speaker 1: about and be familiar with this so you get what

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Speaker 1: we're doing with your capital. Is Is that what approaches? Well? Sure,

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Speaker 1: because you know, come two thousand and eight, two thousand

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Speaker 1: and nine, we don't feel like being woken up at

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Speaker 1: three am eight Right. So just in the broadest terms,

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Speaker 1: what sort of services are you providing for this client base?

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Speaker 1: It's it's investment management only, just pure What about financial

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Speaker 1: planning and taxes and state planning and all that fun stuff? Yeah?

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Speaker 1: Are our clients basically get that separately? I mean of course,

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Speaker 1: you know when you talk about the cumulation uh, and

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Speaker 1: life cycle planning, of course we're we're part of that

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Speaker 1: because that's part of the investment process. But no estate

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Speaker 1: planning and insurance recommendations. We make very little of those.

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Speaker 1: We leave that to other people. And you do not

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Speaker 1: accept new clients. You're not out on a promotional tour

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Speaker 1: to drum up business. No new clients for for efficient

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Speaker 1: fronteer advisors. When did you stop accepting clients? And and why?

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Speaker 1: Four years ago? Uh? And you know, I like to

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Speaker 1: joke back then that we were both pushing seventy with

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Speaker 1: a short stick. Uh. And that stick is now is

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Speaker 1: now well broken. Uh. And so it's it's it's we

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Speaker 1: really don't feel like taking on new clients at our age.

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Speaker 1: That's number one. And number two, it's not fair to

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Speaker 1: be taking on a new client. Uh, you know when

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Speaker 1: you're when you're both getting the maximum social security benefit.

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Speaker 1: You've written about the role of investment advisors and why

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Speaker 1: they should be fiduciaries. What do you think is the

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Speaker 1: appropriate way they should be compensated? This is like a

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Speaker 1: really big debate these days. Yeah, it really, it really

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Speaker 1: depends upon the level of expertise of the client. Uh.

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Speaker 1: You know, there are some people who are absolutely uh

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Speaker 1: fine with, for example, an hourly phase basis. But those

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Speaker 1: kinds of people have to be comfortable making their own transactions, right. Uh.

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Speaker 1: Once you know you're in the model where you're the

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Speaker 1: one who is making the transactions, you've got discretion. I

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Speaker 1: don't think that model works anymore. I could be wrong,

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Speaker 1: but I just don't think. I just don't think that

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Speaker 1: it does. Um. And you know there's the new fee

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Speaker 1: model that Jason's Wide wrote about recently. Yeah, just just

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Speaker 1: last week, a subscription of a subscription model, which I think,

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Speaker 1: I don't know. It sounds to me like a hybrid

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Speaker 1: of of the two. So it depends on how much

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Speaker 1: hand holding you've got. But it gets to a more

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Speaker 1: basic problem in our in our society, which is that

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Speaker 1: we live in a world where you're expected to do

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Speaker 1: your own retirement, uh saving and planning and investing in.

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Speaker 1: The analogy that I use is it's kind of like

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Speaker 1: a stuff on the airplane to go to Chicago, and

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Speaker 1: you go, you turn right off the jetway to go

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Speaker 1: to your seat, and and the flight attendant says, oh no, no, no, no,

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Speaker 1: you're turning left, you're flying the airplane. Uh, and everyone's

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Speaker 1: become do it yourself? Is not because they want to,

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Speaker 1: but it's been mandated. Yeah, and it's a I think

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Speaker 1: it's a colossally stupid system. So what's a better system.

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Speaker 1: How should we actually have retirement saving and planning set up? Oh?

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Speaker 1: I think that there are several systems that that that

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Speaker 1: work well, and I'm certainly not an expert on them.

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Speaker 1: But the Dutch in the Canadian systems are well funded

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Speaker 1: at the national level. Is that funded by individuals or

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Speaker 1: by taxpayers or are they the one and the same

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Speaker 1: people basically by individuals. The Australian system as well, and

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Speaker 1: of course the Australian system, you you have mandated savings

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Speaker 1: rates you know that are now going to be well

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Speaker 1: north of ten percent. So, in other words, when when

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Speaker 1: FICA and everything else comes out of my payroll, ten

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Speaker 1: percent gets pulled out and saved for retirement, regardless of

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Speaker 1: my desires one way or another, right, exactly, a mandatory,

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Speaker 1: a mandatory system. And of course you know that will

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Speaker 1: that will make a lot of libertarians happy. But but

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Speaker 1: then again, it's not fair for someone who doesn't save

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Speaker 1: anything and then expects the state to take care of

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Speaker 1: them at age sixty eight old ninety right, exactly exactly,

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Speaker 1: so that that's really quite quite a true Again, So

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Speaker 1: you're right, the wealthy are different than you and I.

428
00:26:03,840 --> 00:26:06,960
Speaker 1: They have more ways of having their wealth stripped away

429
00:26:07,000 --> 00:26:10,920
Speaker 1: from them. Explain, well, Uh, you know, when you become

430
00:26:10,960 --> 00:26:15,760
Speaker 1: wealthy in our society, it becomes quickly externally apparent, uh,

431
00:26:16,160 --> 00:26:19,480
Speaker 1: if you so choose to flaunt it in that way.

432
00:26:19,520 --> 00:26:24,720
Speaker 1: I think the new generation is less uh, less likely

433
00:26:24,840 --> 00:26:30,880
Speaker 1: to wear flashy watches and drive expensive cars. Yeah, but

434
00:26:30,920 --> 00:26:32,520
Speaker 1: you know, at the end of the day, human beings

435
00:26:32,560 --> 00:26:35,119
Speaker 1: are the are the apes who seek status for sure,

436
00:26:35,200 --> 00:26:38,560
Speaker 1: and and it's it's and the good evolutionary reasons having

437
00:26:38,600 --> 00:26:41,719
Speaker 1: to do why why people do that? And so when

438
00:26:41,760 --> 00:26:44,600
Speaker 1: you become wealthy, you're basically painting a great big bull's

439
00:26:44,600 --> 00:26:48,040
Speaker 1: eye on your chest, uh for the bad actors in

440
00:26:48,040 --> 00:26:50,920
Speaker 1: the business. And the more wealthy you display, uh, the

441
00:26:51,000 --> 00:26:53,440
Speaker 1: more likely you know you are to get hit by

442
00:26:53,440 --> 00:26:58,440
Speaker 1: one of these people. Quite interesting, your historical non fiction

443
00:26:58,640 --> 00:27:04,480
Speaker 1: works are very very different in tone and content than

444
00:27:05,080 --> 00:27:09,880
Speaker 1: the investing in financial books. They appear to be deeply

445
00:27:10,040 --> 00:27:14,960
Speaker 1: deeply researched. Every page is a dance in many ways.

446
00:27:15,000 --> 00:27:18,280
Speaker 1: They they remind me of your namesake, Peter Bernstein, whose

447
00:27:18,359 --> 00:27:22,280
Speaker 1: similar books. UM. Every page is just filled with so

448
00:27:22,359 --> 00:27:27,200
Speaker 1: much information. What made you decide to start writing like this,

449
00:27:27,400 --> 00:27:33,320
Speaker 1: like you are a full time author. Well, uh, when

450
00:27:33,359 --> 00:27:36,760
Speaker 1: you start writing about finance, you realize that the history

451
00:27:36,800 --> 00:27:38,639
Speaker 1: is so very important. We got into that in one

452
00:27:38,680 --> 00:27:42,359
Speaker 1: of the last uh segments. UH. You know, as Santiana

453
00:27:42,760 --> 00:27:45,479
Speaker 1: famously said, if you don't know your history, you're doomed

454
00:27:45,520 --> 00:27:49,960
Speaker 1: to repeat it. Nowhere is that more true than in finance.

455
00:27:50,200 --> 00:27:53,600
Speaker 1: And I discovered that I enjoyed writing writing history. In fact,

456
00:27:53,640 --> 00:27:55,600
Speaker 1: it was the part of the books that I wrote

457
00:27:55,920 --> 00:27:59,000
Speaker 1: that I decided that I liked the most. And so

458
00:27:59,119 --> 00:28:02,040
Speaker 1: after I had written uh two books of finance, The

459
00:28:02,040 --> 00:28:07,040
Speaker 1: intelligenaceid Allocator and The Four Pillars of Investing, I approached

460
00:28:07,280 --> 00:28:11,880
Speaker 1: my um uh then publisher McGraw hill, and I said,

461
00:28:11,920 --> 00:28:13,760
Speaker 1: I would like to write a book about the growth

462
00:28:13,800 --> 00:28:17,639
Speaker 1: inflection that occurred during the early nineteenth century. Before you know,

463
00:28:17,680 --> 00:28:21,600
Speaker 1: about eighteen twenty or so, economic growth UH in most

464
00:28:21,680 --> 00:28:24,840
Speaker 1: nations was very close to zero. And then in the

465
00:28:24,920 --> 00:28:27,960
Speaker 1: leading edge nations, the England, the United States, and most

466
00:28:28,000 --> 00:28:33,480
Speaker 1: of Western Europe growth rose to about two percent per year, which, uh,

467
00:28:33,560 --> 00:28:36,160
Speaker 1: you know, compounded over the centuries, has produced the enormous

468
00:28:36,200 --> 00:28:38,120
Speaker 1: improvement in standard of living that we have. And I

469
00:28:38,120 --> 00:28:41,960
Speaker 1: wanted to know why eighteen twenty, because you know, the

470
00:28:42,000 --> 00:28:45,240
Speaker 1: Industrial Revolution had had started almost a century before that.

471
00:28:45,240 --> 00:28:48,480
Speaker 1: There was something else that was happening, and I wanted

472
00:28:48,520 --> 00:28:52,040
Speaker 1: to write about that. So that was Birth of Plenty,

473
00:28:52,080 --> 00:28:55,080
Speaker 1: which was modestly successful, and it also became a calling

474
00:28:55,160 --> 00:28:58,520
Speaker 1: card as well. For that that got the attention of

475
00:28:58,520 --> 00:29:01,960
Speaker 1: of other publishers, and then that led to explain that

476
00:29:02,040 --> 00:29:04,959
Speaker 1: exchange correct. Yes, and Peter Bernstein gets into that story

477
00:29:06,160 --> 00:29:09,920
Speaker 1: because a couple of years after I had written Birth

478
00:29:09,960 --> 00:29:12,719
Speaker 1: of Plenty, I get this phone call from an acquisitions

479
00:29:12,800 --> 00:29:15,640
Speaker 1: editor at grow Atlantic by the unlikely name of Brando's

480
00:29:15,680 --> 00:29:20,000
Speaker 1: sky Horse. Uh. And that's a phone. That's a message

481
00:29:20,000 --> 00:29:24,000
Speaker 1: you'll take, Yeah, put him through. Yeah. And so he

482
00:29:23,800 --> 00:29:26,400
Speaker 1: he said, you know, we we want you to write

483
00:29:26,400 --> 00:29:29,200
Speaker 1: a book about the history of world trade. And I

484
00:29:29,240 --> 00:29:31,640
Speaker 1: said three things. Number one, I don't know anything about it.

485
00:29:31,760 --> 00:29:34,360
Speaker 1: Number two, I'm not interested in it. And number three,

486
00:29:34,360 --> 00:29:37,640
Speaker 1: you've got the wrong Bernstein. And and there was this

487
00:29:37,720 --> 00:29:40,120
Speaker 1: sort of pregnant pause at the end of the line,

488
00:29:40,160 --> 00:29:43,000
Speaker 1: and he said, well, we actually did have lunch with

489
00:29:43,080 --> 00:29:45,680
Speaker 1: him last week and we offered him the book, and

490
00:29:45,680 --> 00:29:47,640
Speaker 1: he said he was busy, he was busy writing his

491
00:29:47,640 --> 00:29:50,560
Speaker 1: history of the Erie Canal. But Peter said, there's this

492
00:29:50,600 --> 00:29:53,320
Speaker 1: other Bernstein and that's that's how I got to write

493
00:29:53,320 --> 00:29:56,800
Speaker 1: the book. That's very funny, this other Bernstein that that

494
00:29:56,920 --> 00:30:00,600
Speaker 1: really is hilarious. So this obviously how a whole lot

495
00:30:00,680 --> 00:30:04,280
Speaker 1: of work and research that went into it. What's the process, like,

496
00:30:04,360 --> 00:30:06,640
Speaker 1: how long did it take to research this? How long

497
00:30:06,640 --> 00:30:08,200
Speaker 1: did it take to write it? A book like this

498
00:30:08,240 --> 00:30:10,880
Speaker 1: takes about four years to write. Yeah, And and the

499
00:30:10,920 --> 00:30:15,120
Speaker 1: process is, uh, you start by doing, uh, just a

500
00:30:15,160 --> 00:30:18,960
Speaker 1: truckload of reading. Uh. You know when you when you

501
00:30:19,000 --> 00:30:21,680
Speaker 1: write a book like this, you're probably reading about somewhere

502
00:30:21,680 --> 00:30:26,680
Speaker 1: around fifty thousand pages of material. And the analogy I

503
00:30:26,760 --> 00:30:29,280
Speaker 1: like to use is it's kind of like you've got

504
00:30:29,440 --> 00:30:32,680
Speaker 1: a puzzle, this enormous jigsaw puzzle to put together, and

505
00:30:32,760 --> 00:30:36,360
Speaker 1: you're given ten thousand pieces, but you can only pick

506
00:30:36,400 --> 00:30:39,320
Speaker 1: a thousand pieces to make the picture with. Uh. So

507
00:30:39,360 --> 00:30:43,320
Speaker 1: it's a difficult process and it's it's a skill set.

508
00:30:43,400 --> 00:30:46,720
Speaker 1: I guess that not everyone has, but it's something you know,

509
00:30:46,840 --> 00:30:49,280
Speaker 1: is one of these things I discovered I actually knew

510
00:30:49,320 --> 00:30:53,560
Speaker 1: how to do, and it's an enormously enjoyable process I've

511
00:30:53,920 --> 00:30:56,880
Speaker 1: I've you know, this particular book was quite successful. The

512
00:30:56,880 --> 00:30:59,920
Speaker 1: book that I wrote after that was an absolute flop,

513
00:31:00,520 --> 00:31:02,480
Speaker 1: uh on the media. It was on the media, was

514
00:31:02,480 --> 00:31:06,400
Speaker 1: on the history of communications, technology and media. But the

515
00:31:06,440 --> 00:31:09,000
Speaker 1: point was is that I had just as much fun

516
00:31:09,320 --> 00:31:11,680
Speaker 1: writing both, and I feel just as good as I

517
00:31:12,840 --> 00:31:16,120
Speaker 1: about about about both. Is if you don't enjoy the process,

518
00:31:16,200 --> 00:31:19,000
Speaker 1: you should not be writing, to say the least. So

519
00:31:19,040 --> 00:31:23,280
Speaker 1: when you say you read fifty thousand pages quick back

520
00:31:23,400 --> 00:31:27,960
Speaker 1: the envelope, that's a hundred books at five pages each

521
00:31:28,080 --> 00:31:30,240
Speaker 1: or something like that. Yeah, of course you're not reading

522
00:31:30,240 --> 00:31:33,320
Speaker 1: a hundred books. What you're doing is you're climbing the

523
00:31:33,320 --> 00:31:35,600
Speaker 1: bibilio graphic tree. And you might read a few of

524
00:31:35,600 --> 00:31:37,960
Speaker 1: those books all the way through. But what in fact,

525
00:31:37,960 --> 00:31:40,240
Speaker 1: what you're really doing is you're reading lots of books

526
00:31:40,280 --> 00:31:43,120
Speaker 1: sections just maybe a couple of pages or even a

527
00:31:43,160 --> 00:31:46,000
Speaker 1: paragraph or two from each source, and then you're branching

528
00:31:46,000 --> 00:31:49,880
Speaker 1: out into the bibliographic tree, into the reference sources. And

529
00:31:50,040 --> 00:31:52,840
Speaker 1: it's this tree that goes out several branches, and you

530
00:31:53,160 --> 00:31:55,000
Speaker 1: the nice thing about it is, you know when you're

531
00:31:55,120 --> 00:31:58,720
Speaker 1: done when you keep coming back to the same sources

532
00:31:58,720 --> 00:32:00,920
Speaker 1: over and over again, when you reach that point that

533
00:32:01,000 --> 00:32:04,480
Speaker 1: you're being referenced back to the same the same academic articles,

534
00:32:04,520 --> 00:32:08,960
Speaker 1: the same text, the same secondary sources. Uh, you know

535
00:32:09,480 --> 00:32:12,160
Speaker 1: that you're done. Let me throw a few questions that

536
00:32:12,240 --> 00:32:16,680
Speaker 1: you from the book The World's greatest human cataclysm, the

537
00:32:16,840 --> 00:32:20,600
Speaker 1: plague the Black Death was the direct result of long

538
00:32:20,840 --> 00:32:24,680
Speaker 1: established trading patterns. Explain that, Well, it's a it's a

539
00:32:24,720 --> 00:32:28,240
Speaker 1: fascinating thing that epidemiologists like to talk about, which is

540
00:32:28,600 --> 00:32:31,520
Speaker 1: that when you at least his medical historians like to

541
00:32:31,520 --> 00:32:33,840
Speaker 1: talk about, which is that when you look at the

542
00:32:33,840 --> 00:32:38,080
Speaker 1: world around the year one thousand, you you had these

543
00:32:38,120 --> 00:32:42,480
Speaker 1: pools of people, these civilizations, uh and tribal societies that

544
00:32:42,640 --> 00:32:45,440
Speaker 1: never communicated with each other, didn't didn't talk, didn't deal

545
00:32:45,520 --> 00:32:48,280
Speaker 1: with each other, didn't even know that they existed, and

546
00:32:48,360 --> 00:32:51,040
Speaker 1: so they each developed their own gene pools that people

547
00:32:51,080 --> 00:32:57,080
Speaker 1: outside that pool were totally uh vulnerable too. And so

548
00:32:57,760 --> 00:33:01,880
Speaker 1: there is this organism called your ne epestis the plague Bacillus,

549
00:33:01,920 --> 00:33:09,280
Speaker 1: which existed in h ground roads uh or fleas on lease. Yeah. Fleas, yeah,

550
00:33:09,320 --> 00:33:11,760
Speaker 1: fleas on fleas on roads. And the the the animal

551
00:33:11,840 --> 00:33:14,280
Speaker 1: that you know back in that part of the world

552
00:33:14,320 --> 00:33:17,080
Speaker 1: was an animal called the tarabagin uh. And the rat

553
00:33:17,240 --> 00:33:19,680
Speaker 1: was did they didn't they did this. Fleas didn't learn

554
00:33:19,760 --> 00:33:23,280
Speaker 1: to to to jump onto the rats until much later. Uh.

555
00:33:23,320 --> 00:33:27,160
Speaker 1: And and this you know, was was present in East Asia,

556
00:33:27,240 --> 00:33:32,120
Speaker 1: Northeast Asia uh and probably in the Indian subcontinent as

557
00:33:32,160 --> 00:33:37,200
Speaker 1: as well. And then during the twelfth and thirteenth century uh.

558
00:33:37,440 --> 00:33:40,240
Speaker 1: You get a period of time called the PAXs Mongolica,

559
00:33:40,320 --> 00:33:45,000
Speaker 1: when the Mongol tribes conquered territory all the way into

560
00:33:45,160 --> 00:33:50,240
Speaker 1: eastern Europe and in the other cons yes, and and

561
00:33:50,320 --> 00:33:53,840
Speaker 1: so they opened up trade land trade routes uh. And

562
00:33:53,880 --> 00:33:57,640
Speaker 1: of course the fleas hopped a ride on the camels uh.

563
00:33:57,680 --> 00:34:02,560
Speaker 1: And they got to a place called Kafa uh in

564
00:34:02,560 --> 00:34:07,640
Speaker 1: in in Asia Minor or actually in what's now the Ukraine. Uh.

565
00:34:07,840 --> 00:34:11,520
Speaker 1: And and there's this terrible siege of Cafe where the

566
00:34:11,520 --> 00:34:16,640
Speaker 1: Mongols are are besieging Cafe and they throw over the

567
00:34:16,880 --> 00:34:22,800
Speaker 1: catapult over the city walls, these corpses uh biological office exactly.

568
00:34:23,239 --> 00:34:29,200
Speaker 1: And that that infects the Genoese traders who then UH

569
00:34:29,760 --> 00:34:32,759
Speaker 1: basically carried the disease first into I believe the port

570
00:34:32,800 --> 00:34:36,839
Speaker 1: of Messina in thirteen forty six, and then within three

571
00:34:36,920 --> 00:34:39,080
Speaker 1: years a quarter to a third of the population of

572
00:34:39,120 --> 00:34:41,479
Speaker 1: Europe was dead the damage and the rest of the world,

573
00:34:41,480 --> 00:34:43,839
Speaker 1: which much was much worse. Probably it killed as much

574
00:34:43,920 --> 00:34:47,680
Speaker 1: as people in the main ports of Egypt as well

575
00:34:47,719 --> 00:34:49,960
Speaker 1: as in China. And a lot of this has to

576
00:34:50,000 --> 00:34:52,440
Speaker 1: do with the fact that there is no indoor plumbing,

577
00:34:52,480 --> 00:34:57,000
Speaker 1: there is no system of sanitation, and that filth and

578
00:34:57,000 --> 00:34:59,360
Speaker 1: other things are are continue to be spread. Or is

579
00:34:59,400 --> 00:35:02,840
Speaker 1: that a different rent uh? That wasn't. That wasn't the

580
00:35:02,840 --> 00:35:05,640
Speaker 1: mechanism of of the plague. It was more of an

581
00:35:05,640 --> 00:35:09,279
Speaker 1: air air air airborne UH disease. People would develop a

582
00:35:09,280 --> 00:35:13,080
Speaker 1: cough and transmit UH disease disease that way, and it

583
00:35:13,160 --> 00:35:17,080
Speaker 1: was just very very rapidly, very rapidly spreading. Now, the

584
00:35:17,280 --> 00:35:20,279
Speaker 1: thing that's really interesting is that we worry about international

585
00:35:20,320 --> 00:35:24,360
Speaker 1: air travel and how rapidly diseases spread, but we've not

586
00:35:24,440 --> 00:35:28,560
Speaker 1: seen anything nearly as deadly as the plague, or for

587
00:35:28,640 --> 00:35:32,439
Speaker 1: that matter, the the the influenza outbreak that occurred after

588
00:35:32,560 --> 00:35:36,320
Speaker 1: nineteen eighteen. And the reason is the danger is not mixing.

589
00:35:36,400 --> 00:35:38,960
Speaker 1: It's not mixing, that's the danger. So in other words,

590
00:35:39,000 --> 00:35:41,000
Speaker 1: we now have a broader gene pool around the world,

591
00:35:41,040 --> 00:35:44,120
Speaker 1: and we're more capable of finding off. There are less

592
00:35:44,200 --> 00:35:47,839
Speaker 1: new things that are specifically capable of doing damage, for

593
00:35:47,880 --> 00:35:51,520
Speaker 1: a to a different gene sub subgroup. Is that right? Yeah,

594
00:35:51,600 --> 00:35:54,080
Speaker 1: I think we're in a much safer world than we were.

595
00:35:54,640 --> 00:35:58,480
Speaker 1: Uh uh you know, say, you know, say seven or

596
00:35:58,520 --> 00:36:03,239
Speaker 1: eight centuries ago. Um. And and we've also gotten to

597
00:36:03,280 --> 00:36:05,880
Speaker 1: be you know, public health authorities have gotten to be

598
00:36:05,960 --> 00:36:10,279
Speaker 1: really good uh at at disease prevention as well. We

599
00:36:10,320 --> 00:36:13,319
Speaker 1: tend to think of stock and bond markets as a

600
00:36:13,360 --> 00:36:17,440
Speaker 1: relatively recent historical phenomena, but you right, there have been

601
00:36:17,440 --> 00:36:21,279
Speaker 1: credit markets since human civilization first took root in the

602
00:36:21,280 --> 00:36:24,400
Speaker 1: Fertile Crescent, in other words, thousands of years ago. Is

603
00:36:24,440 --> 00:36:27,160
Speaker 1: that right? Well? Sure, And and there's actually a trace

604
00:36:27,320 --> 00:36:31,240
Speaker 1: of interest rates that goes back at least four thousand

605
00:36:31,360 --> 00:36:35,920
Speaker 1: years and perhaps as much as five thousand years. Uh.

606
00:36:36,320 --> 00:36:40,840
Speaker 1: You know, if you're a farmer, uh, a sedentary farmer

607
00:36:41,280 --> 00:36:46,800
Speaker 1: in the in Babylonia or Samaria, Uh, you need credit.

608
00:36:46,880 --> 00:36:49,600
Speaker 1: You need to borrow money. For farm implements and to

609
00:36:49,640 --> 00:36:53,120
Speaker 1: build a house, but most importantly to buy seed corn. Uh.

610
00:36:53,160 --> 00:36:55,719
Speaker 1: And of course you're not borrowing money, you're not even

611
00:36:55,760 --> 00:36:59,200
Speaker 1: borrowing silver. What you're doing is you're borrowing uh seed

612
00:36:59,239 --> 00:37:02,359
Speaker 1: corn from your your neighbor. And that seed corn has

613
00:37:02,440 --> 00:37:06,040
Speaker 1: a cost of capital. So typically in in in in

614
00:37:06,280 --> 00:37:09,759
Speaker 1: very primitive agrarian societies, it's probably around a percent per year.

615
00:37:09,880 --> 00:37:12,880
Speaker 1: So in other words, I bought borrow one bushel of

616
00:37:12,880 --> 00:37:18,120
Speaker 1: of corn or wheat seeds, and in exchange I returned

617
00:37:18,120 --> 00:37:20,239
Speaker 1: to is that is that about right? That's right? Or

618
00:37:20,360 --> 00:37:23,359
Speaker 1: one calf uh? And then a year later, at calving time,

619
00:37:23,360 --> 00:37:27,480
Speaker 1: you've got to return to calves. Quite quite interesting. UM's

620
00:37:27,560 --> 00:37:31,080
Speaker 1: capital and that's considered capital exact in those days. So

621
00:37:31,160 --> 00:37:33,840
Speaker 1: now that's going backwards, let me go forwards. One of

622
00:37:33,920 --> 00:37:37,640
Speaker 1: the things you wrote was trade almost always benefits the

623
00:37:37,719 --> 00:37:41,600
Speaker 1: nation that engages in it, but only when averaged over

624
00:37:41,640 --> 00:37:45,399
Speaker 1: the entire national economy. That will always be a minority

625
00:37:45,719 --> 00:37:51,080
Speaker 1: hurt by evolving trade patterns, and they always call for protection.

626
00:37:51,760 --> 00:37:55,080
Speaker 1: Sounds very similar to what's going on currently with this

627
00:37:55,160 --> 00:38:00,600
Speaker 1: administration and its battle with China and others over trade practices.

628
00:38:01,000 --> 00:38:04,640
Speaker 1: One of the things that is most satisfying about writing

629
00:38:04,760 --> 00:38:09,279
Speaker 1: nonfiction is to come up with historical examples of modern phenomena.

630
00:38:09,600 --> 00:38:11,839
Speaker 1: There are three and four hundred years old and even

631
00:38:11,880 --> 00:38:15,800
Speaker 1: thousands of years old, And there's this wonderful UH story

632
00:38:15,920 --> 00:38:20,680
Speaker 1: of these riots that swept London UH in around the

633
00:38:20,760 --> 00:38:26,480
Speaker 1: year Sevre, having to do with the textile trade UH,

634
00:38:26,880 --> 00:38:32,960
Speaker 1: where weavers stoned UH and attacked parliament, the East India

635
00:38:33,000 --> 00:38:37,160
Speaker 1: Company offices as well as the UH the home of

636
00:38:37,160 --> 00:38:39,080
Speaker 1: the Governor of the East India. It was basically the

637
00:38:39,120 --> 00:38:43,399
Speaker 1: Seattle riots, UH, you know, three hundred, three hundred years ago,

638
00:38:43,560 --> 00:38:46,880
Speaker 1: and the reasons for it were exactly the same. There

639
00:38:46,920 --> 00:38:49,520
Speaker 1: were people who were out of work. So you know,

640
00:38:49,640 --> 00:38:53,400
Speaker 1: clearly we're much better off now because of of trade

641
00:38:53,880 --> 00:38:57,239
Speaker 1: UH you know and cut off trade, increased tariffs. And

642
00:38:57,239 --> 00:39:00,120
Speaker 1: you're gonna find yourself, you know, in the situation of

643
00:39:00,680 --> 00:39:03,360
Speaker 1: the the Iowa soybean farmer who's going to lose his

644
00:39:03,560 --> 00:39:07,880
Speaker 1: farm very shortly because of the Trump UH tariffs. Are

645
00:39:07,880 --> 00:39:11,000
Speaker 1: you going to find yourself as a consumer paying three

646
00:39:11,000 --> 00:39:13,759
Speaker 1: and four times for your shirts and your electronics what

647
00:39:13,920 --> 00:39:18,239
Speaker 1: you're used to, Or of automobile manufacturers whose costs have

648
00:39:18,360 --> 00:39:21,960
Speaker 1: gone up because of metals UH tariffs. So clearly trade

649
00:39:21,960 --> 00:39:24,759
Speaker 1: benefits and entire the entire nation. And you saw that

650
00:39:25,160 --> 00:39:30,080
Speaker 1: in reverse during the nineteen thirties, UH, with the trade

651
00:39:30,080 --> 00:39:34,359
Speaker 1: wars that followed the Holly Smoot UH tariff. But they're

652
00:39:34,400 --> 00:39:38,000
Speaker 1: always losers. Okay, there are textile workers who've lost their jobs.

653
00:39:38,040 --> 00:39:40,600
Speaker 1: There are auto workers and steel workers who have lost

654
00:39:40,640 --> 00:39:43,520
Speaker 1: their jobs. UH. And you have to, you know, the

655
00:39:43,719 --> 00:39:47,640
Speaker 1: key to a successful global economy and a national economy

656
00:39:47,920 --> 00:39:51,200
Speaker 1: is simply to have a system that compensates the losers. UH.

657
00:39:51,239 --> 00:39:53,239
Speaker 1: And to think that, you know, you can cut off

658
00:39:53,280 --> 00:39:56,160
Speaker 1: trade and not compensate the losers, which is what this

659
00:39:56,239 --> 00:39:59,240
Speaker 1: administration wants to do, I think is the height of folly.

660
00:39:59,440 --> 00:40:02,480
Speaker 1: So so, when you say compensate the losers, traditionally that

661
00:40:02,600 --> 00:40:07,160
Speaker 1: has been some sort of job retraining or new education.

662
00:40:07,680 --> 00:40:12,680
Speaker 1: How else can we compensate people whose industries no longer exists.

663
00:40:12,680 --> 00:40:16,280
Speaker 1: If you're a coal miner or if you're a furniture

664
00:40:16,280 --> 00:40:20,400
Speaker 1: manufacturer in the US, these jobs are going away. What

665
00:40:20,560 --> 00:40:24,000
Speaker 1: should we be doing as a nation for the losers

666
00:40:24,080 --> 00:40:26,200
Speaker 1: on that end? Really, the better way to say it

667
00:40:26,280 --> 00:40:28,920
Speaker 1: is the people who are on the losing ends of

668
00:40:28,920 --> 00:40:32,239
Speaker 1: of these international trade deals. Well, those are the first

669
00:40:32,239 --> 00:40:34,560
Speaker 1: two things that you need to do, but you need

670
00:40:34,640 --> 00:40:38,440
Speaker 1: a broader social welfare network. You you know, if you

671
00:40:38,480 --> 00:40:41,840
Speaker 1: lose your job, you shouldn't lose your health insurance. Uh.

672
00:40:42,000 --> 00:40:45,280
Speaker 1: For the only nation in the world that does that exactly. Uh,

673
00:40:45,320 --> 00:40:48,560
Speaker 1: you know, we should increase do things that increase social mobility.

674
00:40:48,600 --> 00:40:51,640
Speaker 1: The United States, in fact, has the lowest social mobility

675
00:40:53,080 --> 00:40:56,319
Speaker 1: of any developed nation. If you are born into the

676
00:40:56,320 --> 00:41:01,880
Speaker 1: bottom quintile UH of of income, the odds of getting

677
00:41:01,880 --> 00:41:04,800
Speaker 1: into the top quintile of income are only six percent

678
00:41:05,160 --> 00:41:09,520
Speaker 1: in the United States. It should be a perfectly egalitarian system. Uh.

679
00:41:09,560 --> 00:41:12,239
Speaker 1: In most developed countries it's about thirteen percent. Now when

680
00:41:12,239 --> 00:41:15,680
Speaker 1: you look inside the United States, it's very interesting. Uh.

681
00:41:15,719 --> 00:41:18,520
Speaker 1: What you discover is that in Silicon Valley, for example,

682
00:41:18,560 --> 00:41:21,080
Speaker 1: if you're born into the bottom quintile, the bottom five,

683
00:41:21,840 --> 00:41:24,879
Speaker 1: you have a European chance of getting to the top

684
00:41:24,920 --> 00:41:27,799
Speaker 1: quintile about thirteen or fourteen percent. But if you're born

685
00:41:27,800 --> 00:41:30,440
Speaker 1: into the bottom quintile in Alabama, you've got a three

686
00:41:30,480 --> 00:41:33,080
Speaker 1: percent chance. What does that tell you? It tells you

687
00:41:33,160 --> 00:41:35,839
Speaker 1: that people in Alabama are not investing enough in their

688
00:41:35,920 --> 00:41:39,360
Speaker 1: young people. And so that's probably the primary thing we

689
00:41:39,360 --> 00:41:42,319
Speaker 1: should be doing at bases. We should be investing far

690
00:41:42,400 --> 00:41:46,239
Speaker 1: more money in education. I find it remarkable that the

691
00:41:46,280 --> 00:41:48,680
Speaker 1: people who rail against the public school system and the

692
00:41:48,719 --> 00:41:52,040
Speaker 1: money that we so supposedly wasted that system, will happily

693
00:41:52,040 --> 00:41:54,200
Speaker 1: spend three and four times that amount every year on

694
00:41:54,239 --> 00:41:57,880
Speaker 1: their to send their kids to private school. Quite quite interesting.

695
00:41:58,400 --> 00:42:01,640
Speaker 1: You discuss how economic ability has has is so low

696
00:42:01,640 --> 00:42:04,759
Speaker 1: in the US. It wasn't always the case. Wasn't there

697
00:42:04,840 --> 00:42:10,000
Speaker 1: much greater economic mobility previously, especially the post War War

698
00:42:10,040 --> 00:42:14,200
Speaker 1: two era. Well, just to give you one small, very anecdotal,

699
00:42:14,280 --> 00:42:17,720
Speaker 1: very small example, my medical school tuition was fifty dollars

700
00:42:17,760 --> 00:42:20,080
Speaker 1: a year. I came out of medical school with almost

701
00:42:20,640 --> 00:42:25,200
Speaker 1: zero debt. Good luck doing that today, right, it's two

702
00:42:25,280 --> 00:42:28,839
Speaker 1: hundred thousand a year. If it's anything, it's it's quite

703
00:42:28,920 --> 00:42:32,560
Speaker 1: quite insane. Um. Let's talk a little bit about Masters

704
00:42:32,600 --> 00:42:36,480
Speaker 1: of the word, how media shaped history from alphabet to

705
00:42:36,560 --> 00:42:39,880
Speaker 1: the internet. So there are a lot of really interesting

706
00:42:40,520 --> 00:42:44,600
Speaker 1: bullet points in this book. You make the case that

707
00:42:45,040 --> 00:42:50,080
Speaker 1: Guttenberg did not change the world with the printing press,

708
00:42:50,120 --> 00:42:54,000
Speaker 1: but in a slightly different way explain it's a fascinating

709
00:42:54,160 --> 00:42:57,360
Speaker 1: bit of of technology. Which is that, of course, he

710
00:42:57,400 --> 00:43:00,360
Speaker 1: didn't invent the printing press that the Chinese and the

711
00:43:00,440 --> 00:43:03,640
Speaker 1: Koreans had it. They even had, the Koreans even had

712
00:43:03,680 --> 00:43:08,759
Speaker 1: moving alf, even had movable alphabetic type. What Gutenberg did

713
00:43:09,400 --> 00:43:13,480
Speaker 1: was to make the production of that type much more efficient.

714
00:43:13,520 --> 00:43:16,000
Speaker 1: If you think about running a printing press or printing

715
00:43:16,000 --> 00:43:19,799
Speaker 1: a book, you're talking about literally owning hundreds of thousands

716
00:43:19,840 --> 00:43:23,359
Speaker 1: of pieces of type. Uh. And if you're casting that

717
00:43:23,520 --> 00:43:27,520
Speaker 1: individually via the pre existing processes, that was something that

718
00:43:27,600 --> 00:43:30,400
Speaker 1: was open only to two governments. That the Chinese government

719
00:43:30,440 --> 00:43:33,560
Speaker 1: was able to do it. Uh. Back then there were

720
00:43:33,600 --> 00:43:36,160
Speaker 1: some Korean printers who could do it, and that was

721
00:43:36,200 --> 00:43:41,600
Speaker 1: about it. Um Guttenberg invented a metal alloy process of

722
00:43:41,800 --> 00:43:45,640
Speaker 1: casting that enabled a skill type caster, my favorite word,

723
00:43:46,000 --> 00:43:51,719
Speaker 1: a type caster who who could produce about three pieces

724
00:43:51,760 --> 00:43:56,520
Speaker 1: per minute of alphabetic type and basically bring it down

725
00:43:56,560 --> 00:44:00,040
Speaker 1: to the artisan level. So what Guttenberg did was in

726
00:44:00,200 --> 00:44:03,719
Speaker 1: invent the printing press. What he did was invent efficient

727
00:44:04,160 --> 00:44:08,320
Speaker 1: the efficient production of movable alphabetic type, which was a

728
00:44:09,320 --> 00:44:13,080
Speaker 1: far more subtle invention. So here's another bullet point from

729
00:44:13,200 --> 00:44:16,440
Speaker 1: from Masters of the Word. You write the Fall of

730
00:44:16,480 --> 00:44:21,680
Speaker 1: the Soviet Union resulted from a colossal error in radio production.

731
00:44:22,280 --> 00:44:28,759
Speaker 1: Explain that, well, the Russians UH produced, mass produced their

732
00:44:28,840 --> 00:44:33,239
Speaker 1: radios uh and in a couple of factories. It was

733
00:44:33,320 --> 00:44:36,960
Speaker 1: very centrally driven, and they made a mistake that the

734
00:44:37,040 --> 00:44:39,560
Speaker 1: Nazis didn't make. The Nazis were smart enough when they

735
00:44:39,560 --> 00:44:43,040
Speaker 1: made their radios uh and the Nazi regime basically came

736
00:44:43,040 --> 00:44:45,680
Speaker 1: into being pretty much at the dawn of popular radio

737
00:44:45,800 --> 00:44:48,920
Speaker 1: in Germany, and they made sure that the radios were

738
00:44:49,600 --> 00:44:54,000
Speaker 1: not tuned well enough to produce foreign broadcasts uh and

739
00:44:54,040 --> 00:44:57,680
Speaker 1: the Soviets didn't do that. The Soviets built radios that

740
00:44:57,719 --> 00:45:01,640
Speaker 1: allowed tens of millions of the citizens to get the

741
00:45:01,719 --> 00:45:05,759
Speaker 1: BBC and Voice of America and deutschewella, uh, it was,

742
00:45:05,840 --> 00:45:08,000
Speaker 1: it was. It was just a colossally the sort of

743
00:45:08,080 --> 00:45:11,520
Speaker 1: colossally stupid thing you would only see an essentially planned economy.

744
00:45:12,320 --> 00:45:14,640
Speaker 1: That's hilarious. So so now, one of the things you

745
00:45:14,680 --> 00:45:18,520
Speaker 1: write about this in the sort of pre social media

746
00:45:18,600 --> 00:45:21,919
Speaker 1: days was that as more people get access to means

747
00:45:21,920 --> 00:45:26,239
Speaker 1: of communication, the result tends to be more democracy. Do

748
00:45:26,280 --> 00:45:29,959
Speaker 1: you still hold those views in the face of how

749
00:45:30,040 --> 00:45:35,399
Speaker 1: much fake news quote unquote um and and the way

750
00:45:35,440 --> 00:45:40,040
Speaker 1: Facebook has been weaponized to influence elections. You do you

751
00:45:40,040 --> 00:45:42,280
Speaker 1: still hold those views or what are your thoughts about

752
00:45:42,760 --> 00:45:47,600
Speaker 1: that change in in social media. I still believe the

753
00:45:47,600 --> 00:45:50,239
Speaker 1: basic precept and the the the analogy that I like

754
00:45:50,400 --> 00:45:54,920
Speaker 1: to use is that in the era of radio and television,

755
00:45:54,920 --> 00:45:58,919
Speaker 1: it was so centrally controlled that getting into a fight

756
00:45:59,160 --> 00:46:02,200
Speaker 1: with the national powers that be, whether it was the

757
00:46:02,200 --> 00:46:05,120
Speaker 1: media or the government or the government controlled media, was

758
00:46:05,160 --> 00:46:08,560
Speaker 1: like bringing a knife to a gunfight. Uh. Now both

759
00:46:08,600 --> 00:46:12,400
Speaker 1: sides have guns. What I really didn't anticipate, and I

760
00:46:12,560 --> 00:46:16,399
Speaker 1: don't think anybody anticipated even five or six years ago,

761
00:46:16,920 --> 00:46:22,960
Speaker 1: is that you've you've enabled the worst players in our society. Uh.

762
00:46:23,040 --> 00:46:26,800
Speaker 1: And and that's the you know, this industrial grade Uh

763
00:46:26,920 --> 00:46:30,200
Speaker 1: that that that's your phrase, By the way, it does feels,

764
00:46:30,880 --> 00:46:33,560
Speaker 1: but it's true. It's not just running the mill BS.

765
00:46:33,560 --> 00:46:38,720
Speaker 1: It's manufactured at a very high level. Yeah. And and

766
00:46:38,719 --> 00:46:42,520
Speaker 1: and of course there's there's this famous moral philosopher, uh

767
00:46:43,160 --> 00:46:46,560
Speaker 1: named Harry Frankfurt who will be known forever after for

768
00:46:46,600 --> 00:46:51,200
Speaker 1: a little sixty eight page essay B S Yes. And

769
00:46:51,280 --> 00:46:54,120
Speaker 1: what is BS BS is is not just things that

770
00:46:54,120 --> 00:46:57,440
Speaker 1: are necessarily false. Sometimes BS can actually be true. But

771
00:46:57,520 --> 00:47:00,720
Speaker 1: it's just words that are spoken that have no reference

772
00:47:00,760 --> 00:47:04,319
Speaker 1: and no intentional reference to the fact the facts, And

773
00:47:04,360 --> 00:47:07,520
Speaker 1: of course you know we've we've now enshrined that. In

774
00:47:07,560 --> 00:47:10,759
Speaker 1: our Commander in Chief. The description I like best is

775
00:47:10,880 --> 00:47:14,400
Speaker 1: we we live now in a post fact era, which

776
00:47:14,520 --> 00:47:16,560
Speaker 1: kind of cracks me up because I don't believe it's

777
00:47:16,600 --> 00:47:19,279
Speaker 1: such a thing as the post fact era. Um, but

778
00:47:19,560 --> 00:47:22,200
Speaker 1: here we are, and uh, can you stick around a bit.

779
00:47:22,200 --> 00:47:24,920
Speaker 1: I have a ton more questions for you. We have

780
00:47:25,120 --> 00:47:29,080
Speaker 1: been speaking with William Bernstein, author of such books as

781
00:47:29,120 --> 00:47:33,439
Speaker 1: a Splendid Exchange and The Four Pillars of Investing. If

782
00:47:33,480 --> 00:47:36,399
Speaker 1: you enjoy this conversation, well come back and check out

783
00:47:36,440 --> 00:47:39,360
Speaker 1: the podcast extras. Will we keep the tape rolling and

784
00:47:39,400 --> 00:47:47,880
Speaker 1: continue discussing all things finance. You can find that at iTunes, Overcast, SoundCloud, Stitcher,

785
00:47:47,960 --> 00:47:52,160
Speaker 1: wherever finer podcasts are sold. We love your comments, feedback

786
00:47:52,160 --> 00:47:56,200
Speaker 1: and suggestions right to us at m IB podcast at

787
00:47:56,200 --> 00:47:59,799
Speaker 1: Bloomberg dot Net. Check out my daily column at Bloomberg

788
00:47:59,800 --> 00:48:03,200
Speaker 1: dot calm slash Opinion. Follow me on Twitter at Rid Halts.

789
00:48:03,760 --> 00:48:06,880
Speaker 1: I'm Barry Ri Halts. You're listening to Master's in Business

790
00:48:07,320 --> 00:48:23,840
Speaker 1: on Bloomberg Radio. Welcome to the podcast. Bill, thank you

791
00:48:23,880 --> 00:48:26,680
Speaker 1: so much for doing this. I um, I've been looking

792
00:48:26,719 --> 00:48:30,080
Speaker 1: forward to having this conversation. You and I have swapped

793
00:48:30,120 --> 00:48:33,160
Speaker 1: emails over the years, and you've had some lovely things

794
00:48:33,200 --> 00:48:36,360
Speaker 1: to say about this format. So I'm thrilled to finally

795
00:48:36,400 --> 00:48:39,440
Speaker 1: get you in here in the booth and have this conversation.

796
00:48:39,680 --> 00:48:41,080
Speaker 1: Can I Can I say a lovely thing or two

797
00:48:41,120 --> 00:48:45,440
Speaker 1: about your format if if you feel inclined? Yeah, I do. Uh.

798
00:48:45,719 --> 00:48:47,640
Speaker 1: You know, there aren't very many people in this world

799
00:48:47,640 --> 00:48:51,000
Speaker 1: that I actually envy, but you're one of them. There

800
00:48:51,040 --> 00:48:52,560
Speaker 1: there are. There are a few things that I enjoy

801
00:48:52,680 --> 00:48:57,080
Speaker 1: more than talking to people have who have interesting things

802
00:48:57,080 --> 00:48:58,759
Speaker 1: to say, and that seems to me to be all

803
00:48:58,840 --> 00:49:01,799
Speaker 1: that you. You do. Whoever you feel like talking to

804
00:49:02,120 --> 00:49:05,719
Speaker 1: you can get on this program. Don't let anyone else know.

805
00:49:05,800 --> 00:49:08,839
Speaker 1: That's secret. Yeah, and I and I and I envy

806
00:49:08,880 --> 00:49:11,360
Speaker 1: the heck out of out of the platform that that

807
00:49:11,480 --> 00:49:13,719
Speaker 1: you have and how you enjoy yourself. I'm gonna let

808
00:49:13,719 --> 00:49:17,440
Speaker 1: you in a little secret. My writing is for no

809
00:49:17,600 --> 00:49:20,920
Speaker 1: audience of one, and this show effectively is for an

810
00:49:20,960 --> 00:49:25,480
Speaker 1: audience of one. I've managed to con everybody into thinking

811
00:49:25,520 --> 00:49:28,560
Speaker 1: that this is supposed to be a broadcast. But essentially

812
00:49:28,600 --> 00:49:31,600
Speaker 1: it's me having a conversation that I want to have. Yeah,

813
00:49:31,760 --> 00:49:34,000
Speaker 1: you get people to answer your emails who never answer

814
00:49:34,040 --> 00:49:36,839
Speaker 1: my emails, and I am green with envy. Well, if

815
00:49:36,880 --> 00:49:39,360
Speaker 1: I can help make an introduction, I would be happy

816
00:49:39,400 --> 00:49:41,560
Speaker 1: to do that. You're not, by the way, You're not

817
00:49:41,600 --> 00:49:43,879
Speaker 1: the only person who said that to me. Some other

818
00:49:43,960 --> 00:49:47,680
Speaker 1: people who I won't say on air, but i'll tell

819
00:49:47,719 --> 00:49:51,640
Speaker 1: you privately, have said that to me. And it's really

820
00:49:52,200 --> 00:49:54,960
Speaker 1: oh really, So people have figured out that this is

821
00:49:55,000 --> 00:49:58,200
Speaker 1: a giant self indulgence and they wish they could do

822
00:49:58,440 --> 00:50:00,279
Speaker 1: See if you are in an Oregon, if you were

823
00:50:00,280 --> 00:50:04,560
Speaker 1: in New York, you can wing something like this together. Um.

824
00:50:04,560 --> 00:50:07,760
Speaker 1: Other people have done this in a way. Mark Maron

825
00:50:07,880 --> 00:50:10,799
Speaker 1: started in his garage and Los Angeles, and since he

826
00:50:10,920 --> 00:50:14,320
Speaker 1: was a stand up comedian for forever, he would con

827
00:50:14,440 --> 00:50:17,359
Speaker 1: his comedian friends to come in and that's blown up

828
00:50:17,719 --> 00:50:22,279
Speaker 1: into this giant thing. So there's something to just engaging

829
00:50:22,320 --> 00:50:24,840
Speaker 1: in a little bit of self indulgence and speaking to

830
00:50:24,880 --> 00:50:27,840
Speaker 1: people you want to speak to. Yeah, one one thing, Barry,

831
00:50:28,000 --> 00:50:31,040
Speaker 1: it's Oregon. You say Oregon to Oregon. You say Oregon

832
00:50:31,080 --> 00:50:33,000
Speaker 1: too many times. That's a band. Actually, there was a

833
00:50:33,000 --> 00:50:35,839
Speaker 1: band called Oregon and I that's where that comes from. Yeah,

834
00:50:35,840 --> 00:50:37,200
Speaker 1: but you do it too many times. We take away

835
00:50:37,239 --> 00:50:42,440
Speaker 1: your visa to come to uh, what's going on in Portland, Oregon.

836
00:50:42,680 --> 00:50:46,160
Speaker 1: It's that that is a city that is now both

837
00:50:46,200 --> 00:50:49,880
Speaker 1: booming and kind of completely out of control, isn't it? Yeah,

838
00:50:49,880 --> 00:50:53,160
Speaker 1: it is. It's It's what happens to any city where

839
00:50:53,280 --> 00:50:57,680
Speaker 1: when it becomes too popular, uh, and the cost of

840
00:50:57,680 --> 00:51:01,040
Speaker 1: of residents, the cost of real estate goes up. Uh

841
00:51:01,080 --> 00:51:02,799
Speaker 1: as you get out of whack. Of course, you know,

842
00:51:02,840 --> 00:51:05,160
Speaker 1: we have you know, the the ultimate example of that

843
00:51:05,280 --> 00:51:08,719
Speaker 1: is San Francisco, which has gotten to be this ludicrously

844
00:51:09,160 --> 00:51:12,880
Speaker 1: bifurcated place that is populated but with this you know,

845
00:51:12,920 --> 00:51:15,759
Speaker 1: bimodally on on. You know, there's this one peak of

846
00:51:15,840 --> 00:51:18,480
Speaker 1: people to the to the right of the curve, who

847
00:51:18,560 --> 00:51:20,520
Speaker 1: who have you know, matth s a t s of

848
00:51:20,600 --> 00:51:24,160
Speaker 1: seven fifty and can talk in differential equations and in finance,

849
00:51:24,520 --> 00:51:27,520
Speaker 1: and who are very well dressed and are spending you know,

850
00:51:27,640 --> 00:51:30,960
Speaker 1: nine dollars on avocado toast for for breakfast. And then

851
00:51:31,160 --> 00:51:34,399
Speaker 1: you've got the other people who are on the cusp

852
00:51:34,440 --> 00:51:38,000
Speaker 1: of homelessness or are homeless speaking of which the West

853
00:51:38,040 --> 00:51:42,680
Speaker 1: Coast has far more homelessness than every time I'm out

854
00:51:42,719 --> 00:51:45,279
Speaker 1: there then I previously remember, and the last time I

855
00:51:45,320 --> 00:51:48,680
Speaker 1: was in Portland, I was shocked at the number of

856
00:51:48,760 --> 00:51:52,040
Speaker 1: people living on the streets. It's quite amazing. Yeah, serious,

857
00:51:52,040 --> 00:51:55,640
Speaker 1: serious problem is one factoid that I've seen repeated, I've

858
00:51:55,640 --> 00:51:57,799
Speaker 1: not verified it, which is that if you take Los

859
00:51:57,840 --> 00:52:01,960
Speaker 1: Angeles out of the analysis, the homeless rate in the

860
00:52:02,000 --> 00:52:05,960
Speaker 1: United States is actually falling. Oh really, so so why

861
00:52:06,160 --> 00:52:09,799
Speaker 1: Los Angeles other than the um weather allows you to

862
00:52:09,840 --> 00:52:13,799
Speaker 1: live out their year rounds? Uh? Probably probably just you know,

863
00:52:13,840 --> 00:52:16,239
Speaker 1: it's like any other complex social phenomena, it's a list

864
00:52:16,280 --> 00:52:22,520
Speaker 1: of factors whether uh, and the very high cost of housing. Uh,

865
00:52:22,600 --> 00:52:26,759
Speaker 1: it's it's geographically dispersed, so it can accommodate a lot

866
00:52:26,840 --> 00:52:30,440
Speaker 1: more homeless people without making people too upset. Just the

867
00:52:30,440 --> 00:52:33,360
Speaker 1: whole whole range and things. Yeah. And the stat I

868
00:52:33,400 --> 00:52:37,640
Speaker 1: saw that so disturbing is north of fifty of homeless

869
00:52:37,680 --> 00:52:42,400
Speaker 1: people are suffering from some mental or emotional disability, and

870
00:52:42,440 --> 00:52:45,359
Speaker 1: because they're homeless, they don't have access to medical care

871
00:52:45,600 --> 00:52:49,319
Speaker 1: or regular prescriptions. Yeah. If you you know, if you

872
00:52:49,360 --> 00:52:52,160
Speaker 1: if you dole out food in a in a homeless shelter,

873
00:52:52,200 --> 00:52:54,480
Speaker 1: which you very quickly find out is there's three populations

874
00:52:54,480 --> 00:53:01,080
Speaker 1: of people. One are substance abusers to our schizophrenics, uh,

875
00:53:01,160 --> 00:53:04,800
Speaker 1: and three and equally large people. A group of people

876
00:53:04,840 --> 00:53:07,280
Speaker 1: are people just like you and me who are working

877
00:53:07,440 --> 00:53:11,279
Speaker 1: their rear ends off h and are extremely conscientious. But

878
00:53:11,280 --> 00:53:14,319
Speaker 1: they got a bad draw, they lost their job, they

879
00:53:14,320 --> 00:53:18,279
Speaker 1: lost their health insurance, they became ill, uh, they went bankrupt,

880
00:53:18,440 --> 00:53:22,040
Speaker 1: and they wound up living in their car. That's quite horrifying.

881
00:53:22,080 --> 00:53:25,000
Speaker 1: And when we talk about lack of a social net,

882
00:53:25,440 --> 00:53:28,440
Speaker 1: that's the group that seems to fall through the cracks.

883
00:53:28,440 --> 00:53:32,040
Speaker 1: Although there are that many schizophrenics who are untreated and

884
00:53:32,080 --> 00:53:34,759
Speaker 1: they all eventually become homeless. Is that is that the

885
00:53:34,760 --> 00:53:37,239
Speaker 1: implication there that's a really good question is is to

886
00:53:37,320 --> 00:53:40,839
Speaker 1: what percentage of of of of schizophrenics become homeless. It's

887
00:53:40,840 --> 00:53:43,080
Speaker 1: a very high percentage of them, really Yeah. I mean

888
00:53:43,400 --> 00:53:45,200
Speaker 1: they're the ones who are most visible, because those are

889
00:53:45,200 --> 00:53:46,560
Speaker 1: the ones who were shouting at the top of their

890
00:53:46,600 --> 00:53:49,200
Speaker 1: lungs as you you know, walk by them on the street.

891
00:53:50,400 --> 00:53:52,840
Speaker 1: So so there's a bunch of questions we did not

892
00:53:53,080 --> 00:53:57,200
Speaker 1: get to during the broadcast portion. And I wanna run

893
00:53:57,239 --> 00:54:00,440
Speaker 1: these by you before we get to our favorite question, Shians.

894
00:54:00,880 --> 00:54:05,719
Speaker 1: Some of these are really quite quite intriguing. Um, let's

895
00:54:05,760 --> 00:54:08,200
Speaker 1: let's start with finance and then work our way through

896
00:54:08,280 --> 00:54:11,600
Speaker 1: some variations. When a quote, I'm going to give you

897
00:54:11,640 --> 00:54:16,120
Speaker 1: a quote of yours. When a famous investor starts publishing

898
00:54:16,160 --> 00:54:20,640
Speaker 1: a newsletter, it's a sure tip off his investing techniques

899
00:54:20,680 --> 00:54:25,120
Speaker 1: have stopped working. Discuss well, that's an elite, but a goodie. Uh.

900
00:54:25,280 --> 00:54:28,399
Speaker 1: You know, if if you or I actually know how

901
00:54:28,480 --> 00:54:32,759
Speaker 1: to reliably beat the market, you're not going to tell

902
00:54:32,760 --> 00:54:34,879
Speaker 1: anybody about it. You're not even gonna tell your own

903
00:54:34,920 --> 00:54:38,680
Speaker 1: mother about it. You are going to leverage yourself to

904
00:54:38,680 --> 00:54:42,240
Speaker 1: the hilt. You're not going to take anybody else's money. Uh,

905
00:54:42,280 --> 00:54:44,560
Speaker 1: that's not that's not you. That you haven't borrowed yourself.

906
00:54:44,600 --> 00:54:47,360
Speaker 1: And then when you're done, you'll go to the beach. Uh.

907
00:54:47,840 --> 00:54:50,319
Speaker 1: You're you're you're you're sure as not. You're sure as

908
00:54:50,320 --> 00:54:52,279
Speaker 1: heck not going to publish a newsletter and sell it

909
00:54:52,280 --> 00:54:55,680
Speaker 1: for two a year. My my favorite part of the

910
00:54:56,160 --> 00:55:00,920
Speaker 1: Jim Simon's Renaissance Technology Lure is after few years of

911
00:55:00,960 --> 00:55:07,200
Speaker 1: the medallion UM their their flagship fun throw off. Annually

912
00:55:07,680 --> 00:55:11,080
Speaker 1: they basically said to investors, listen, there's a finite amount

913
00:55:11,080 --> 00:55:13,920
Speaker 1: of alpha here and there ain't enough for you and me,

914
00:55:14,080 --> 00:55:17,279
Speaker 1: so you gotta go. And they returned all of the

915
00:55:17,320 --> 00:55:22,560
Speaker 1: outside money, and now the medallion fund has been Renaissance

916
00:55:22,600 --> 00:55:27,439
Speaker 1: Technology employees and Jim Simmons. That's basically at a year

917
00:55:27,480 --> 00:55:30,440
Speaker 1: for forty years something like that. It's a it's a crazy,

918
00:55:30,560 --> 00:55:34,920
Speaker 1: crazy number. Um speaking of crazy numbers, I don't remember

919
00:55:34,960 --> 00:55:38,760
Speaker 1: which book this is from, but this really um blew

920
00:55:38,800 --> 00:55:43,720
Speaker 1: my mind. An old Master painting bought from the artist

921
00:55:43,800 --> 00:55:48,080
Speaker 1: for a hundred dollars and sold three hundred and fifty

922
00:55:48,160 --> 00:55:52,160
Speaker 1: years later for tens of millions of dollars. Returns but

923
00:55:52,400 --> 00:55:57,120
Speaker 1: three point three percent annually. Explain that, Well, it's it's

924
00:55:57,160 --> 00:56:00,920
Speaker 1: it's you know, it's called the magic of compounding. Uh.

925
00:56:01,239 --> 00:56:02,759
Speaker 1: You know, if you if you save and you have

926
00:56:02,800 --> 00:56:04,960
Speaker 1: a decent rate of return, even a modest rate of

927
00:56:05,000 --> 00:56:08,000
Speaker 1: return over hundreds of years, then you know you'll have

928
00:56:08,000 --> 00:56:10,480
Speaker 1: a fabulous amount of money. But of course you can't

929
00:56:10,600 --> 00:56:13,200
Speaker 1: do that because you're gonna want to spend some of

930
00:56:13,239 --> 00:56:15,239
Speaker 1: the money. Let alone, let it ride for three or

931
00:56:15,280 --> 00:56:19,480
Speaker 1: four generations. Now, Ben Franklin did that, Uh, well, Ben

932
00:56:19,520 --> 00:56:22,840
Speaker 1: Franklin set up an investment portfolio, and I have to

933
00:56:22,880 --> 00:56:25,400
Speaker 1: admit I'm not aware of details of it, but it

934
00:56:25,480 --> 00:56:29,080
Speaker 1: was a portfolio that was designed to last some very

935
00:56:29,160 --> 00:56:34,200
Speaker 1: long period of time and benefit his charitable causes. And

936
00:56:34,280 --> 00:56:37,359
Speaker 1: it actually did earn a decent rate of return over

937
00:56:37,760 --> 00:56:39,640
Speaker 1: a period of more than the century and wound up

938
00:56:39,680 --> 00:56:44,080
Speaker 1: being worth a lot of of money. But what you know,

939
00:56:44,200 --> 00:56:47,759
Speaker 1: what I like to say about that is that yes,

940
00:56:47,800 --> 00:56:50,040
Speaker 1: if you, if you, if you put you know, a

941
00:56:50,120 --> 00:56:53,200
Speaker 1: hundred dollars into stocks and then save it for for

942
00:56:53,200 --> 00:56:56,200
Speaker 1: for seventy years and invested for seventy years, you're gonna

943
00:56:56,200 --> 00:56:59,759
Speaker 1: have a fabulous amount of money. But myself, I'd rather

944
00:57:00,200 --> 00:57:02,799
Speaker 1: be twenty years old with a few with a few

945
00:57:02,800 --> 00:57:05,799
Speaker 1: euros in my pocket on the boulevards of Paris, uh

946
00:57:05,880 --> 00:57:08,400
Speaker 1: than be ninety years old with with millions of dollars.

947
00:57:08,440 --> 00:57:12,080
Speaker 1: Thank you so much for saying that. I get the

948
00:57:12,280 --> 00:57:17,000
Speaker 1: fire group of of people who think you should live

949
00:57:17,120 --> 00:57:20,240
Speaker 1: like a pauper, pour every penny you have into the

950
00:57:20,280 --> 00:57:23,800
Speaker 1: stock market for ten or fifteen years and then retired

951
00:57:23,840 --> 00:57:27,600
Speaker 1: at age forty, and it just seems so wrong to

952
00:57:27,760 --> 00:57:31,440
Speaker 1: me to to not enjoy life in your twenties and thirties.

953
00:57:31,480 --> 00:57:33,560
Speaker 1: Who wants to live like that if you can avoid it.

954
00:57:34,040 --> 00:57:35,240
Speaker 1: I tend to be you know, I tend to be

955
00:57:35,240 --> 00:57:38,000
Speaker 1: fairly sympathetic to the fired group. But it's it's a

956
00:57:38,000 --> 00:57:41,040
Speaker 1: suspicious Uh, it's a suspicious group of people. A lot

957
00:57:41,080 --> 00:57:44,600
Speaker 1: of these people were people who were making six figure

958
00:57:44,720 --> 00:57:48,480
Speaker 1: incomes in the industry and then got to retire at

959
00:57:48,520 --> 00:57:50,800
Speaker 1: age thirty three or thirty five with a giant pile

960
00:57:50,800 --> 00:57:54,200
Speaker 1: of stock options to right, exactly, and and if that

961
00:57:54,280 --> 00:57:56,520
Speaker 1: works really well as long as you don't have children

962
00:57:56,560 --> 00:57:59,880
Speaker 1: or get sick, right, that's right. But there is some

963
00:58:00,040 --> 00:58:05,760
Speaker 1: thing to be said for being able to enjoy and

964
00:58:05,800 --> 00:58:09,600
Speaker 1: appreciate the work you do and have finding some some

965
00:58:09,680 --> 00:58:14,400
Speaker 1: meaning and some value in your hourly labors and not

966
00:58:14,680 --> 00:58:18,040
Speaker 1: just split wood and round up in water the horses

967
00:58:18,080 --> 00:58:21,840
Speaker 1: and live the life of a hermit or or so

968
00:58:21,920 --> 00:58:24,480
Speaker 1: it seems moderation in all things. That makes that makes

969
00:58:24,520 --> 00:58:29,160
Speaker 1: perfect sense. Um, So there's two others that were that

970
00:58:29,200 --> 00:58:31,920
Speaker 1: really stood out. UM. I have a pet thesis I'll

971
00:58:31,920 --> 00:58:34,800
Speaker 1: share with you in a moment, But you wrote, at

972
00:58:34,840 --> 00:58:40,280
Speaker 1: a very early stage in history, we are encountering survivorship bias.

973
00:58:40,400 --> 00:58:43,760
Speaker 1: The fact that only the best results tend to show

974
00:58:43,880 --> 00:58:49,080
Speaker 1: up in history books. Explain, well, there's a classic example

975
00:58:49,200 --> 00:58:53,000
Speaker 1: of that from World War Two uh Ari Woldman and

976
00:58:53,640 --> 00:58:57,120
Speaker 1: the planes coming Back. Yeah. Yeah, So it's you know,

977
00:58:57,720 --> 00:59:00,520
Speaker 1: just for the readers who listeners who haven't heard us

978
00:59:01,120 --> 00:59:03,960
Speaker 1: when you when they when they analyzed the bombers that

979
00:59:04,000 --> 00:59:05,720
Speaker 1: came back from World War Two and they looked at

980
00:59:05,720 --> 00:59:12,840
Speaker 1: the patterns of of the of the Shropnell uh bullets. Yeah,

981
00:59:12,960 --> 00:59:15,480
Speaker 1: they found that there was there were areas that that

982
00:59:15,600 --> 00:59:17,520
Speaker 1: didn't ever seem to get hit. And of course the

983
00:59:17,560 --> 00:59:19,160
Speaker 1: reason why they never get his when he got hit

984
00:59:19,200 --> 00:59:21,480
Speaker 1: in the fuel tank, you didn't come back, or the engine.

985
00:59:21,480 --> 00:59:23,080
Speaker 1: If it hit the engine, you're not going to make

986
00:59:23,080 --> 00:59:26,880
Speaker 1: the flight back. It's the same thing in in finance. Uh.

987
00:59:28,160 --> 00:59:30,280
Speaker 1: You know, you you see the people who did well.

988
00:59:30,360 --> 00:59:32,200
Speaker 1: You the thing that sticks in your mind is the

989
00:59:32,200 --> 00:59:35,920
Speaker 1: guy who bought Amazon or Microsoft on the I p O.

990
00:59:36,280 --> 00:59:39,560
Speaker 1: But what you don't see are the other of IPO

991
00:59:40,520 --> 00:59:45,080
Speaker 1: investors who who did uh? Who? Who who had their

992
00:59:45,080 --> 00:59:49,400
Speaker 1: heads hand into them? So there was um I call

993
00:59:49,480 --> 00:59:53,480
Speaker 1: this the the loss and found stock certificate. There was

994
00:59:53,520 --> 00:59:56,000
Speaker 1: a story in the papers. Uh, it's got to be

995
00:59:56,080 --> 01:00:00,760
Speaker 1: a decade ago, Uncle Fred buys some E M C

996
01:00:01,040 --> 01:00:04,600
Speaker 1: and he gets the certificates, and it goes into a

997
01:00:04,680 --> 01:00:07,240
Speaker 1: firebox and it gets stuck somewhere in the attic, and

998
01:00:07,680 --> 01:00:10,360
Speaker 1: nobody looks at it for twenty five years, and then

999
01:00:10,400 --> 01:00:13,400
Speaker 1: they find the stock certificates and wow, it's worth six

1000
01:00:13,480 --> 01:00:16,680
Speaker 1: million dollars and it makes the paper and it's fascinating.

1001
01:00:17,800 --> 01:00:20,600
Speaker 1: But the reason that's so misleading is if you would

1002
01:00:20,600 --> 01:00:25,120
Speaker 1: have bought GM, and and then GM subsequently declares bankruptcy

1003
01:00:25,240 --> 01:00:27,880
Speaker 1: or fill in the blank, Lehman Brothers or pets dot

1004
01:00:27,920 --> 01:00:31,680
Speaker 1: Com or whatever when he finds those stock certificates, Nobody

1005
01:00:31,680 --> 01:00:34,240
Speaker 1: tells the newspaper. Nobody writes the story. You don't hear

1006
01:00:34,280 --> 01:00:37,400
Speaker 1: about it. You only hear about the odd ones that, wow,

1007
01:00:37,440 --> 01:00:41,200
Speaker 1: a fortune was created. And that's pure survivorship bias. Yeah,

1008
01:00:41,240 --> 01:00:42,800
Speaker 1: and it's the same thing, you know, to a to

1009
01:00:42,920 --> 01:00:45,320
Speaker 1: a more subtle degree, but but a more important degree.

1010
01:00:45,360 --> 01:00:49,640
Speaker 1: Probably with with mutual funds. Uh. You know, there are

1011
01:00:50,040 --> 01:00:52,880
Speaker 1: there are There are mutual funds that have done very well,

1012
01:00:53,400 --> 01:00:56,200
Speaker 1: uh and have good long term records, have beaten the market.

1013
01:00:57,080 --> 01:00:59,920
Speaker 1: But you know, for every one of them, there are

1014
01:01:00,200 --> 01:01:03,760
Speaker 1: probably twenty or thirty that got euthanized by the fun

1015
01:01:03,840 --> 01:01:06,320
Speaker 1: family because so poorly, and you don't even see those

1016
01:01:06,360 --> 01:01:08,800
Speaker 1: in the record unless you have the right the right database,

1017
01:01:09,120 --> 01:01:10,960
Speaker 1: So that gets pulled out of the data, and it

1018
01:01:11,000 --> 01:01:15,200
Speaker 1: makes the surviving fund average look much better than it

1019
01:01:15,240 --> 01:01:17,120
Speaker 1: should be. Yeah, and and it's a it's a much

1020
01:01:17,160 --> 01:01:20,360
Speaker 1: even bigger problem with hedge funds and private equity. About

1021
01:01:21,680 --> 01:01:25,200
Speaker 1: of hedge funds disappear each year because of that high

1022
01:01:25,240 --> 01:01:29,840
Speaker 1: water mark, right it's two and twenty being the net

1023
01:01:29,880 --> 01:01:33,480
Speaker 1: gains above a previous high. So if you suffer a

1024
01:01:33,560 --> 01:01:36,840
Speaker 1: draw down, you're not gonna get that big fat so

1025
01:01:37,000 --> 01:01:39,400
Speaker 1: you're up and over. So they dissolve and start over,

1026
01:01:39,520 --> 01:01:41,120
Speaker 1: and it makes the numbers look much better than we

1027
01:01:41,240 --> 01:01:44,840
Speaker 1: should be. So my my pet thesis on survivorship bias

1028
01:01:45,400 --> 01:01:49,280
Speaker 1: is that everybody's conception of the world is completely wrong.

1029
01:01:49,920 --> 01:01:53,120
Speaker 1: Everything we see is survivorship bias. When you look at

1030
01:01:53,160 --> 01:01:56,000
Speaker 1: a pen, or when you go to a restaurant you like,

1031
01:01:56,120 --> 01:02:00,280
Speaker 1: which perhaps is the best example. How hard can running

1032
01:02:00,280 --> 01:02:02,760
Speaker 1: a restaurant being You get a good chef, you get

1033
01:02:02,880 --> 01:02:05,960
Speaker 1: a friendly hostess, uh, you get a little media buzz.

1034
01:02:06,240 --> 01:02:09,080
Speaker 1: You don't see the other For each successful restaurant. You're

1035
01:02:09,080 --> 01:02:11,600
Speaker 1: not seeing the other hundred that have come and gone

1036
01:02:11,680 --> 01:02:15,520
Speaker 1: after six months at great expense and anguish. And there's

1037
01:02:15,520 --> 01:02:18,120
Speaker 1: a reason it's a terrible investment. There's a reason films

1038
01:02:18,120 --> 01:02:22,120
Speaker 1: and plays are a terrible investment. Most plays are in Hamilton's.

1039
01:02:22,640 --> 01:02:26,280
Speaker 1: So everything is survivorship bias. And you know you're talking

1040
01:02:26,280 --> 01:02:29,440
Speaker 1: about how doctors are such awful investors. I mean doctors

1041
01:02:29,600 --> 01:02:34,400
Speaker 1: are certainly not the only occupational category that's that's susceptible

1042
01:02:34,440 --> 01:02:39,440
Speaker 1: to that. I mean, entertainers and sports figures in particular, uh,

1043
01:02:40,320 --> 01:02:44,160
Speaker 1: regularly lose their their shirts on restaurants. When you look

1044
01:02:44,160 --> 01:02:49,880
Speaker 1: at the bankruptcy statistics for specially NFL and NBA players,

1045
01:02:50,800 --> 01:02:54,680
Speaker 1: very very high, it's it's a shocking, shocking number. Um.

1046
01:02:54,800 --> 01:02:56,640
Speaker 1: And then you know, the one other book we didn't

1047
01:02:56,640 --> 01:03:00,240
Speaker 1: talk about, um, was the E book, the Deep Risk Book.

1048
01:03:00,280 --> 01:03:02,200
Speaker 1: Was that an e book or a print book? Well,

1049
01:03:02,440 --> 01:03:06,960
Speaker 1: I've produced four e books, actually five e books. One

1050
01:03:07,000 --> 01:03:08,960
Speaker 1: of them I giveaway for free, That's If you Can,

1051
01:03:09,000 --> 01:03:11,120
Speaker 1: And it's actually probably the most widely distributed of my

1052
01:03:11,400 --> 01:03:16,880
Speaker 1: IF which is a book for millennials. UH, And it's

1053
01:03:16,920 --> 01:03:21,920
Speaker 1: been hundreds of thousands of downloads because it's free. Uh

1054
01:03:22,800 --> 01:03:24,640
Speaker 1: it was, you know it was. It was an elamassinary

1055
01:03:24,960 --> 01:03:29,040
Speaker 1: project named millennials who didn't have assets. And then I

1056
01:03:29,080 --> 01:03:33,560
Speaker 1: have three short booklets, uh Deep Risk in the Ages

1057
01:03:33,600 --> 01:03:35,840
Speaker 1: of the Investor, in Skating where the puck Was, and

1058
01:03:35,960 --> 01:03:37,680
Speaker 1: I sort of combined that and a bunch of other

1059
01:03:37,760 --> 01:03:43,320
Speaker 1: things into a newer version of intelligenaceid Allocator called Rational

1060
01:03:43,360 --> 01:03:50,200
Speaker 1: Expectations Um, which was published four or five years ago.

1061
01:03:50,360 --> 01:03:54,760
Speaker 1: So that's probably a book that's superseded the intelligenaceid Allocator.

1062
01:03:54,840 --> 01:03:58,480
Speaker 1: It's basically meant for the same uh math geeky kind

1063
01:03:58,480 --> 01:04:02,400
Speaker 1: of audience. And you've called this investing for adults something

1064
01:04:02,440 --> 01:04:05,320
Speaker 1: like that. That's the those five those five series or

1065
01:04:05,360 --> 01:04:07,240
Speaker 1: those five books I sort of fold into what I

1066
01:04:07,240 --> 01:04:12,120
Speaker 1: call my invest Investing for Adults series, which is you know,

1067
01:04:12,120 --> 01:04:16,400
Speaker 1: it's for it's it's for investing adults people who basically understand, uh,

1068
01:04:16,520 --> 01:04:19,720
Speaker 1: market efficiency and who understand the relationship between risk and

1069
01:04:19,760 --> 01:04:22,600
Speaker 1: return and know that there is no returns ferry and

1070
01:04:22,680 --> 01:04:26,720
Speaker 1: no stock picking ferry and uh no market timing. Sorry,

1071
01:04:27,000 --> 01:04:30,560
Speaker 1: So when you say adults, you are not using that chronologically.

1072
01:04:30,600 --> 01:04:33,560
Speaker 1: You using it in terms of being a sophisticated investor,

1073
01:04:33,720 --> 01:04:36,600
Speaker 1: or at least an informed investor. Yeah, I've I've met

1074
01:04:36,640 --> 01:04:40,200
Speaker 1: fifteen year old investing adults, and I've met seventy five

1075
01:04:40,320 --> 01:04:44,040
Speaker 1: year old investing infants. I swear to God this is true.

1076
01:04:44,200 --> 01:04:47,720
Speaker 1: I used to get these emails all the time, especially

1077
01:04:47,720 --> 01:04:49,480
Speaker 1: when I was doing a lot of television, and the

1078
01:04:49,520 --> 01:04:53,920
Speaker 1: email went something like this, I just inherited a million dollars.

1079
01:04:54,240 --> 01:04:56,560
Speaker 1: What I'm going to or a substantial sum of money.

1080
01:04:56,960 --> 01:04:59,600
Speaker 1: I'm going to give a hundred thousand dollars to five

1081
01:05:00,120 --> 01:05:04,240
Speaker 1: uh different fund managers and whoever generates the best returns.

1082
01:05:04,280 --> 01:05:07,760
Speaker 1: I'm going to give my real money too. And it's like,

1083
01:05:08,040 --> 01:05:10,960
Speaker 1: why are you incentivizing people to take risks and hope

1084
01:05:11,000 --> 01:05:14,720
Speaker 1: they get lucky. You're you're not incentivizing anybody to manage

1085
01:05:14,760 --> 01:05:18,400
Speaker 1: your real money appropriately. They don't understand that. It's a

1086
01:05:18,520 --> 01:05:21,600
Speaker 1: it's bad game theory or the other one. I'm looking

1087
01:05:21,640 --> 01:05:25,800
Speaker 1: for double the market performance but with half the risk.

1088
01:05:26,400 --> 01:05:28,720
Speaker 1: I like that one. Also, that's an email used to

1089
01:05:28,760 --> 01:05:31,520
Speaker 1: get all the time. Well, as soon as you find that,

1090
01:05:31,640 --> 01:05:33,440
Speaker 1: let me know, I have a billion dollars for you.

1091
01:05:33,520 --> 01:05:37,000
Speaker 1: But short of that, you're that's that's not really Uh,

1092
01:05:37,040 --> 01:05:40,360
Speaker 1: that's not really going to happen. Um. Since you're not

1093
01:05:40,520 --> 01:05:43,800
Speaker 1: taking money from people anymore, how does that change how

1094
01:05:43,840 --> 01:05:46,720
Speaker 1: you interact with the public through your site. Is it

1095
01:05:46,840 --> 01:05:51,520
Speaker 1: a different relationship? Do you get sort of crazy emails

1096
01:05:51,560 --> 01:05:53,520
Speaker 1: like that? What? What is? What's what do you see

1097
01:05:53,560 --> 01:05:57,360
Speaker 1: flowing to you from that efficient frontier site? Well, I

1098
01:05:57,440 --> 01:06:02,000
Speaker 1: intentionally make my email address opaque. If it's there, you

1099
01:06:02,040 --> 01:06:05,240
Speaker 1: can hunt it down. You can hunt it down. Uh,

1100
01:06:05,280 --> 01:06:08,080
Speaker 1: And it basically makes you feel bad if you email me.

1101
01:06:08,120 --> 01:06:11,080
Speaker 1: It's it's one. It's one that's for press only, and

1102
01:06:11,160 --> 01:06:15,520
Speaker 1: that basically scares away of people who want to to

1103
01:06:15,840 --> 01:06:18,240
Speaker 1: run me down. The people who want to run me

1104
01:06:18,280 --> 01:06:20,280
Speaker 1: down and who actually go for that email are people

1105
01:06:20,320 --> 01:06:22,680
Speaker 1: simply who've who have read my books. They don't want information,

1106
01:06:22,720 --> 01:06:25,320
Speaker 1: They just want to thank me. Really, And that's that's yeah,

1107
01:06:25,360 --> 01:06:27,680
Speaker 1: that's the that is. You know, once a week I

1108
01:06:27,680 --> 01:06:29,560
Speaker 1: get an email from someone that says, you know, you

1109
01:06:29,640 --> 01:06:32,760
Speaker 1: saved my life, Thanks so much. That's delightful. Yeah, And

1110
01:06:32,880 --> 01:06:35,800
Speaker 1: it's it's you know, it's it's it's better than the royalties. Yes,

1111
01:06:35,920 --> 01:06:39,520
Speaker 1: I would certainly say so. Um. Before we get to

1112
01:06:39,760 --> 01:06:44,040
Speaker 1: our favorite questions, I had one last question to ask you,

1113
01:06:44,560 --> 01:06:48,640
Speaker 1: and that's the biggest distraction. What is the biggest distraction

1114
01:06:49,160 --> 01:06:53,520
Speaker 1: investors run into. Oh, well, it's just the entertainment aspect

1115
01:06:53,840 --> 01:06:57,800
Speaker 1: of of investing. It's the it's the c NBC uh

1116
01:06:57,960 --> 01:07:02,640
Speaker 1: market environment. Uh, the idea that that what's going to

1117
01:07:02,680 --> 01:07:05,280
Speaker 1: you know, where the market's going next year, or what

1118
01:07:05,360 --> 01:07:08,520
Speaker 1: company is producing the best product, or what country has

1119
01:07:08,520 --> 01:07:13,400
Speaker 1: the hottest economy. Uh, it's it's uh what Jane Bryant

1120
01:07:13,760 --> 01:07:18,240
Speaker 1: Quinn called a financial pornographer. So here's the quote of

1121
01:07:18,280 --> 01:07:22,800
Speaker 1: yours relevant to that of what you read about investing

1122
01:07:22,800 --> 01:07:25,720
Speaker 1: in magazines and newspapers, and a hundred percent of what

1123
01:07:25,760 --> 01:07:30,000
Speaker 1: you can run television is worse than useless. Are you

1124
01:07:30,080 --> 01:07:33,479
Speaker 1: overstanding that or is that pretty much a decent set

1125
01:07:33,520 --> 01:07:35,880
Speaker 1: of figures. Oh? I mean, if you really ask them,

1126
01:07:35,920 --> 01:07:38,880
Speaker 1: I'll tell you what I really think. But yeah, I mean,

1127
01:07:38,960 --> 01:07:40,760
Speaker 1: I mean that's true. The way I like to put

1128
01:07:40,760 --> 01:07:43,760
Speaker 1: it as at CNBC, at Base wants to make you

1129
01:07:43,800 --> 01:07:47,480
Speaker 1: poor and stupid. So that's a different website, the conspiracy

1130
01:07:47,520 --> 01:07:51,840
Speaker 1: to make you poor and stupid. I used to jokingly say, um,

1131
01:07:51,880 --> 01:07:54,280
Speaker 1: you know, you don't walk into a doctor's office and

1132
01:07:54,320 --> 01:07:58,400
Speaker 1: have General Hospital playing on the television. If you did,

1133
01:07:58,560 --> 01:08:01,800
Speaker 1: you would run screaming from the room. And my pet

1134
01:08:01,880 --> 01:08:07,280
Speaker 1: theory is each of the financial channels reflects their parent company.

1135
01:08:07,360 --> 01:08:11,600
Speaker 1: So Bloomberg is a data services company, Bloomberg Television is

1136
01:08:11,640 --> 01:08:16,040
Speaker 1: all about charts and data and graphics. NBC is an

1137
01:08:16,160 --> 01:08:19,960
Speaker 1: entertainment company, so CNBC becomes all about entertainment. And then

1138
01:08:20,040 --> 01:08:23,920
Speaker 1: Fox Business is is their parent company is Fox News,

1139
01:08:23,960 --> 01:08:29,000
Speaker 1: so it's all about politics and tribalism and partisan warfare.

1140
01:08:29,479 --> 01:08:34,800
Speaker 1: And each of the financial channels just reflects what the

1141
01:08:34,880 --> 01:08:37,759
Speaker 1: ethos of the parent company is. God, I thought Fox

1142
01:08:37,760 --> 01:08:41,000
Speaker 1: Business was about anchors and short skirts. No, No, that's

1143
01:08:41,080 --> 01:08:44,320
Speaker 1: generally across the whole line is that when you look

1144
01:08:44,439 --> 01:08:50,120
Speaker 1: at some channels more than others, um sex cells, and

1145
01:08:50,760 --> 01:08:54,479
Speaker 1: especially when you're marketing to a primarily male audience. I

1146
01:08:54,479 --> 01:08:57,559
Speaker 1: don't know if it's still a primarily male audience, but

1147
01:08:57,800 --> 01:09:01,800
Speaker 1: that sort of nineties thing, the pre me too era,

1148
01:09:02,360 --> 01:09:04,720
Speaker 1: that doesn't seem to have changed very much in the

1149
01:09:04,720 --> 01:09:07,920
Speaker 1: past couple of years. It's not not environments. Um the

1150
01:09:08,600 --> 01:09:11,920
Speaker 1: words you don't read anymore is leggy, blonde, anchor people.

1151
01:09:12,360 --> 01:09:16,360
Speaker 1: But pretty much that's mostly what it continues to be. Right,

1152
01:09:16,439 --> 01:09:19,920
Speaker 1: I'm I'm I've read descriptions like that in magazines and

1153
01:09:20,000 --> 01:09:22,400
Speaker 1: it's pretty straightforward. I mean, if I can get all

1154
01:09:22,479 --> 01:09:25,080
Speaker 1: monkey on you. You know, you asked about the return

1155
01:09:25,160 --> 01:09:27,200
Speaker 1: on art, and the reason why the return on artists

1156
01:09:27,240 --> 01:09:32,080
Speaker 1: so low is because it has an entertainment segment part

1157
01:09:32,080 --> 01:09:33,439
Speaker 1: of the return as well. And this is work that

1158
01:09:33,479 --> 01:09:36,480
Speaker 1: you know, Bill Baumble uh and why you very famously

1159
01:09:37,040 --> 01:09:42,639
Speaker 1: did which a U M. Hell yeah uh, in which

1160
01:09:42,640 --> 01:09:44,960
Speaker 1: he looked, you know, he actually has a return series

1161
01:09:45,200 --> 01:09:49,280
Speaker 1: of of art going back centuries and found that on

1162
01:09:49,360 --> 01:09:52,240
Speaker 1: average it's got a lower return than stocks and bonds

1163
01:09:52,280 --> 01:09:55,679
Speaker 1: because part of its return is is an entertainment return.

1164
01:09:55,800 --> 01:09:59,880
Speaker 1: So if you want entertainment from investing, you are going

1165
01:10:00,000 --> 01:10:01,920
Speaker 1: going to pay for it. You're gonna get a lower

1166
01:10:01,920 --> 01:10:05,040
Speaker 1: return courtesy of the entertainment. Exactly the investment you want

1167
01:10:05,160 --> 01:10:10,160
Speaker 1: is the one with zero investment excuse me, zero entertainment return,

1168
01:10:10,840 --> 01:10:13,760
Speaker 1: which leaves more room for the investment return. Right. So

1169
01:10:13,880 --> 01:10:17,400
Speaker 1: it's it's I always advise people who can't pull the

1170
01:10:17,400 --> 01:10:21,160
Speaker 1: needle out of their arm, set up a fun account

1171
01:10:21,240 --> 01:10:24,800
Speaker 1: of five, keep it in a different custodian from your

1172
01:10:24,840 --> 01:10:27,599
Speaker 1: real money, and if it works out, great, and if

1173
01:10:27,640 --> 01:10:29,960
Speaker 1: it doesn't. Thank goodness, it was only five percent, and

1174
01:10:30,000 --> 01:10:32,640
Speaker 1: it's sort of like a little bit of insurance, so

1175
01:10:32,720 --> 01:10:36,519
Speaker 1: people aren't day trading their retirement. But that's basically what happened,

1176
01:10:36,600 --> 01:10:39,040
Speaker 1: the same advice that I give. Really really that's quite

1177
01:10:40,040 --> 01:10:42,200
Speaker 1: that's that's quite interesting. It makes me feel good that

1178
01:10:42,200 --> 01:10:45,760
Speaker 1: that's the that's the right approach. So let's go to

1179
01:10:45,760 --> 01:10:48,799
Speaker 1: our favorite questions. We asked these of all our guests,

1180
01:10:49,400 --> 01:10:52,479
Speaker 1: starting with what was the first car you ever owned?

1181
01:10:52,720 --> 01:10:59,960
Speaker 1: Your make and model. It was a nineteen seventy two

1182
01:11:00,680 --> 01:11:06,080
Speaker 1: blue eight B baby blue Fiat eight fifty Spider purchased

1183
01:11:06,120 --> 01:11:11,759
Speaker 1: at the factory in Milan for eight hundred eight uh,

1184
01:11:11,800 --> 01:11:15,839
Speaker 1: and it needed to be tuned every three thousand miles.

1185
01:11:16,280 --> 01:11:20,280
Speaker 1: It was both tuned, not oil changed, but full tuned. Yes,

1186
01:11:20,320 --> 01:11:25,880
Speaker 1: every three thousand miles and mixed it again, Tony, Yeah, exactly.

1187
01:11:27,280 --> 01:11:30,680
Speaker 1: And uh. You also have another question about what's one

1188
01:11:30,680 --> 01:11:33,320
Speaker 1: of the one of the biggest mistakes you've made and

1189
01:11:33,320 --> 01:11:35,479
Speaker 1: and when did you learn from them? And it was both.

1190
01:11:35,520 --> 01:11:37,760
Speaker 1: It was both an enormous joy and you know, ever

1191
01:11:37,800 --> 01:11:41,000
Speaker 1: since then, I've owned Japanese cars. That that makes the

1192
01:11:41,080 --> 01:11:43,960
Speaker 1: pro sense. You know, you talk about art every now

1193
01:11:44,000 --> 01:11:47,519
Speaker 1: and then I'll see a column somewhere about if only

1194
01:11:47,600 --> 01:11:51,240
Speaker 1: you had bought the Ferrari to fifty, it's worth ten

1195
01:11:51,280 --> 01:11:55,200
Speaker 1: million dollars today, initially cost five thousand. Here's the return.

1196
01:11:55,280 --> 01:11:57,600
Speaker 1: It's like, well, what about all the other cars that

1197
01:11:57,640 --> 01:11:59,960
Speaker 1: came out that year that you could have bought and didn't.

1198
01:12:00,240 --> 01:12:03,680
Speaker 1: It's just a pure exercise and survivorship biased. Yeah, and

1199
01:12:03,920 --> 01:12:06,559
Speaker 1: if you will not you will almost you can. You

1200
01:12:06,600 --> 01:12:09,200
Speaker 1: can't find a Fiat eight fifty Spider now almost for

1201
01:12:09,240 --> 01:12:11,720
Speaker 1: love or money. You can, but they don't cost very much.

1202
01:12:11,760 --> 01:12:14,479
Speaker 1: They're very hard to find because none of them ever

1203
01:12:14,560 --> 01:12:18,320
Speaker 1: lasted that log that's right. So what's the most important

1204
01:12:18,360 --> 01:12:22,439
Speaker 1: thing that people don't know about you? That was? That

1205
01:12:22,479 --> 01:12:24,080
Speaker 1: was a tough one. But what I came up with

1206
01:12:24,320 --> 01:12:27,000
Speaker 1: is that only the people who know me the very

1207
01:12:27,040 --> 01:12:31,000
Speaker 1: best understand how easily bored I am. I'm the kind

1208
01:12:31,040 --> 01:12:33,800
Speaker 1: of person who likes being on the steep part of

1209
01:12:33,920 --> 01:12:37,120
Speaker 1: the learning curve. So most people, most people in medicine,

1210
01:12:37,120 --> 01:12:41,120
Speaker 1: fine neurology fascinating and I did too for about, you know,

1211
01:12:41,200 --> 01:12:44,800
Speaker 1: ten relatively short years, and then I got bored with it.

1212
01:12:44,840 --> 01:12:47,080
Speaker 1: And it's the same thing with you know, all the

1213
01:12:47,080 --> 01:12:49,120
Speaker 1: other things I've done with my life is you know,

1214
01:12:49,160 --> 01:12:52,400
Speaker 1: I've written a history about world economic growth, I've studied finance,

1215
01:12:54,560 --> 01:12:58,679
Speaker 1: I've written about world trade. Now I'm writing about human rationality.

1216
01:12:58,800 --> 01:13:04,760
Speaker 1: Uh and and you know, I just enjoy reading new things.

1217
01:13:04,800 --> 01:13:06,479
Speaker 1: For me, what I like, What I like to say

1218
01:13:06,680 --> 01:13:10,360
Speaker 1: is that is that writing is just a way of

1219
01:13:10,479 --> 01:13:14,400
Speaker 1: organizing my reading properly in an interesting manner. And it's

1220
01:13:14,439 --> 01:13:16,920
Speaker 1: a good it's a it's a fun way of staying

1221
01:13:16,960 --> 01:13:19,000
Speaker 1: on that steep part of the learning curve. So it's

1222
01:13:19,000 --> 01:13:22,080
Speaker 1: we always be learning new things. So you you're gonna

1223
01:13:22,320 --> 01:13:27,800
Speaker 1: be writing on human rationality. You obviously use behavioral economics

1224
01:13:28,040 --> 01:13:31,280
Speaker 1: in a lot of the work you do in finance. Um,

1225
01:13:31,320 --> 01:13:35,600
Speaker 1: and you are a neurologist. There's a subsection of behavioral

1226
01:13:36,200 --> 01:13:40,479
Speaker 1: economics that some people have called neurofinance, where you're really

1227
01:13:40,560 --> 01:13:44,640
Speaker 1: looking at what's going on within the brain within them

1228
01:13:45,680 --> 01:13:48,840
Speaker 1: and the current system. Is that right? You're talking about

1229
01:13:49,000 --> 01:13:50,960
Speaker 1: a lot of the work that gets done with functional

1230
01:13:51,000 --> 01:13:56,400
Speaker 1: imaging technically functional m R. I and I think it's overdone.

1231
01:13:56,400 --> 01:13:59,280
Speaker 1: It's become way fashionable, you know, as important as the

1232
01:13:59,280 --> 01:14:03,280
Speaker 1: econom and for ski work is, I think it has

1233
01:14:04,120 --> 01:14:06,960
Speaker 1: it's relevance to finance, although it's great, is not as

1234
01:14:06,960 --> 01:14:09,639
Speaker 1: great as as an area that I think is relatively ignored,

1235
01:14:09,680 --> 01:14:14,640
Speaker 1: and that's evolutionary psychology. Uh. We behave in certain very

1236
01:14:14,680 --> 01:14:17,439
Speaker 1: irrational ways, and it's nice to be able to identify

1237
01:14:17,520 --> 01:14:19,599
Speaker 1: the ways in which we're irrational, which is what Condomen

1238
01:14:19,640 --> 01:14:23,680
Speaker 1: and Versky are justifiably famous for. But if you just

1239
01:14:23,800 --> 01:14:28,200
Speaker 1: read Condomen into Versky, you don't understand what is in

1240
01:14:28,360 --> 01:14:32,439
Speaker 1: back of that behavior. To give you a small example, UM,

1241
01:14:32,479 --> 01:14:35,320
Speaker 1: you know, the fundamental characteristic that we have we've already

1242
01:14:35,320 --> 01:14:38,439
Speaker 1: mentioned is that humans imitator and finance. We say that

1243
01:14:38,560 --> 01:14:41,960
Speaker 1: humans heard. Why do humans heard? Well, if you think

1244
01:14:42,000 --> 01:14:44,200
Speaker 1: about it, the easiest way to think about that is

1245
01:14:44,240 --> 01:14:47,200
Speaker 1: to think about the history of our species in the

1246
01:14:47,240 --> 01:14:50,840
Speaker 1: Western hemisphere over the past depends upon what archaeological record

1247
01:14:50,920 --> 01:14:54,600
Speaker 1: you believe. Between fifteen and fifty thousand years uh and

1248
01:14:54,800 --> 01:14:57,200
Speaker 1: over a period of a very few thousands of years,

1249
01:14:57,200 --> 01:15:00,360
Speaker 1: maybe three or five thousand years, humans spread from the

1250
01:15:00,439 --> 01:15:04,120
Speaker 1: high sub Arctic uh in Alaska and the Yukon all

1251
01:15:04,120 --> 01:15:06,799
Speaker 1: the way down to the southern tip of South America,

1252
01:15:06,800 --> 01:15:09,800
Speaker 1: which has a not very dissimilar climate, and on the

1253
01:15:09,840 --> 01:15:12,360
Speaker 1: way they had to learn how to make kayaks. Uh.

1254
01:15:12,479 --> 01:15:15,320
Speaker 1: They had to learn how to make poison darts. Uh.

1255
01:15:15,360 --> 01:15:18,400
Speaker 1: They blowguns, they had to learn how to hunt bison

1256
01:15:19,479 --> 01:15:23,800
Speaker 1: on the great planes. Uh. And you can't learn how

1257
01:15:23,840 --> 01:15:26,240
Speaker 1: to do any of those things on your own. If

1258
01:15:26,280 --> 01:15:28,240
Speaker 1: each individual person had to learn how to do all

1259
01:15:28,280 --> 01:15:31,439
Speaker 1: of those things on their own, they'd have very quickly

1260
01:15:31,479 --> 01:15:35,120
Speaker 1: become lunch for for a predator. Uh. And so you

1261
01:15:35,160 --> 01:15:37,599
Speaker 1: find the one person who learns how to build the kayak,

1262
01:15:37,640 --> 01:15:40,160
Speaker 1: make the blowgun, hunt bison, and then you imitate what

1263
01:15:40,200 --> 01:15:43,200
Speaker 1: that person does. So we are the species that imitates.

1264
01:15:43,240 --> 01:15:47,519
Speaker 1: We are the ape who imitates. And once you understand that, uh,

1265
01:15:47,560 --> 01:15:52,120
Speaker 1: a lot of economic activity and particularly behavior and finance

1266
01:15:52,160 --> 01:15:55,680
Speaker 1: becomes a lot more understandable. So am I grossly oversimplifying

1267
01:15:55,800 --> 01:15:57,840
Speaker 1: this because I've looked at the same thing from an

1268
01:15:57,840 --> 01:16:04,000
Speaker 1: evolutionary standpoint, and I he's thought, Hey, primates are a um,

1269
01:16:04,040 --> 01:16:06,800
Speaker 1: They're a herd creature, they're a I don't know what

1270
01:16:06,800 --> 01:16:10,240
Speaker 1: it's called for, monkeys, a a tribe, a troop of monkeys,

1271
01:16:10,400 --> 01:16:14,599
Speaker 1: or or whoever, of chimps. And that the reason we

1272
01:16:14,800 --> 01:16:19,200
Speaker 1: care about social um status is that we want to

1273
01:16:19,200 --> 01:16:20,720
Speaker 1: be part of the group. If you're not part of

1274
01:16:20,720 --> 01:16:23,040
Speaker 1: the group, you can't survive on your own, and so

1275
01:16:23,240 --> 01:16:28,240
Speaker 1: only those creatures that can herd play well with others

1276
01:16:28,280 --> 01:16:30,240
Speaker 1: that can be part of the group end up being

1277
01:16:30,240 --> 01:16:34,480
Speaker 1: self selected to pass their genes on. If you're a contrarian,

1278
01:16:34,520 --> 01:16:38,759
Speaker 1: if you're an outlier, if you're a chimpanzee that isn't

1279
01:16:38,800 --> 01:16:42,200
Speaker 1: really going to be core to that social group. You're

1280
01:16:42,280 --> 01:16:43,960
Speaker 1: probably not going to get a mate, You're not going

1281
01:16:44,000 --> 01:16:47,840
Speaker 1: to pass those genes along. Am am I oversimplifying or

1282
01:16:47,880 --> 01:16:51,240
Speaker 1: bastardizing that, or is that just further back in our

1283
01:16:51,360 --> 01:16:55,679
Speaker 1: our conversation. Then, Um, that's three million, not thirty thousand

1284
01:16:55,760 --> 01:16:57,880
Speaker 1: years ago. Yeah, you you well that that's that that

1285
01:16:57,960 --> 01:17:00,439
Speaker 1: goes way back. And as you say, it's it's billions

1286
01:17:00,520 --> 01:17:04,479
Speaker 1: and millions of years ago. We seek status because it

1287
01:17:04,560 --> 01:17:07,559
Speaker 1: enables us to better, to make babies better, particularly if

1288
01:17:07,600 --> 01:17:09,519
Speaker 1: you're if you're a male, and particularly if you're a

1289
01:17:09,520 --> 01:17:13,040
Speaker 1: male bull you know bull elephant seal for example. But

1290
01:17:13,160 --> 01:17:15,599
Speaker 1: you know human beings have that have have that same

1291
01:17:15,600 --> 01:17:19,280
Speaker 1: basic mechanism operating. That is why we seek status. It's

1292
01:17:19,360 --> 01:17:21,920
Speaker 1: just a way of forwarding our our d n a

1293
01:17:22,640 --> 01:17:26,200
Speaker 1: uh And why use Scott Galloway talks about watches and

1294
01:17:26,240 --> 01:17:30,120
Speaker 1: he goes, everybody has a phone that's far more accurate

1295
01:17:30,439 --> 01:17:33,040
Speaker 1: than an expensive time piece. But it's a way to

1296
01:17:33,120 --> 01:17:36,760
Speaker 1: signal that I can afford to UM take care of

1297
01:17:36,800 --> 01:17:39,559
Speaker 1: you and your offspring, and therefore these have not yet

1298
01:17:39,600 --> 01:17:43,280
Speaker 1: gone away. It's the it's the broken bag, exactly, and

1299
01:17:43,360 --> 01:17:47,000
Speaker 1: it just shows UM ability to take care of the

1300
01:17:47,080 --> 01:17:49,720
Speaker 1: next generation. Well yeah, yeah, exactly. It shows that it

1301
01:17:49,760 --> 01:17:52,880
Speaker 1: shows that you're able to muster resources. This is signaling

1302
01:17:54,000 --> 01:17:56,920
Speaker 1: a signaling mechanism exactly. So so who are some of

1303
01:17:56,960 --> 01:18:01,439
Speaker 1: your early mentors who affected the way you practice medicine

1304
01:18:01,560 --> 01:18:06,799
Speaker 1: and then who affected the way you practiced finance. Well, uh,

1305
01:18:07,120 --> 01:18:11,600
Speaker 1: it's really difficult to point out, uh who, you know,

1306
01:18:11,680 --> 01:18:15,600
Speaker 1: It's something at some point I decided I love neurology, uh,

1307
01:18:15,680 --> 01:18:20,280
Speaker 1: And I guess there were some uh junior and chief

1308
01:18:20,320 --> 01:18:23,519
Speaker 1: residents who I glombed onto in my when I was

1309
01:18:23,560 --> 01:18:27,240
Speaker 1: in medical school, and I enjoyed the way they approached patients,

1310
01:18:27,240 --> 01:18:33,400
Speaker 1: and I enjoyed the the craft of neurology. Uh. You know,

1311
01:18:33,400 --> 01:18:35,200
Speaker 1: and I can think of a couple of names that

1312
01:18:35,240 --> 01:18:37,920
Speaker 1: no one will recognize, but they were basically my Now

1313
01:18:37,960 --> 01:18:41,080
Speaker 1: when you're a medical student, a junior and a senior

1314
01:18:41,160 --> 01:18:45,520
Speaker 1: resident in a subspecially field as a god. Uh. And

1315
01:18:45,520 --> 01:18:47,479
Speaker 1: and and so those are the people you tend to

1316
01:18:47,960 --> 01:18:50,439
Speaker 1: imprint upon. Uh. And then there was you know, several

1317
01:18:50,479 --> 01:18:52,720
Speaker 1: different you know, several different groups of people. The one

1318
01:18:52,760 --> 01:18:54,960
Speaker 1: person who certainly had mentored to me was my wife,

1319
01:18:56,320 --> 01:18:58,840
Speaker 1: who was an English major, and she knew how to write,

1320
01:18:59,240 --> 01:19:03,639
Speaker 1: and and she taught me how to to to write. Uh.

1321
01:19:03,680 --> 01:19:06,840
Speaker 1: Did she edit your early work? She edits my early work,

1322
01:19:06,840 --> 01:19:08,519
Speaker 1: in my middle work, in my late work. She just

1323
01:19:08,640 --> 01:19:11,280
Speaker 1: I will not send anything to a publisher without having

1324
01:19:11,280 --> 01:19:15,559
Speaker 1: her look at it. Uh. And you know she's she's

1325
01:19:15,600 --> 01:19:18,640
Speaker 1: that good. Uh. And then as far as you know,

1326
01:19:18,720 --> 01:19:23,800
Speaker 1: finance goes and finance writing. Uh. There was a person

1327
01:19:23,880 --> 01:19:27,080
Speaker 1: I've already spoken about, Frank Armstrong, who encouraged me. Another

1328
01:19:27,080 --> 01:19:29,760
Speaker 1: person with Scott Burns, who was a writer for the

1329
01:19:29,840 --> 01:19:32,320
Speaker 1: Dallas Morning News who was still rites and still also

1330
01:19:32,360 --> 01:19:36,680
Speaker 1: manages money, who told me very forthrightly that I had

1331
01:19:36,720 --> 01:19:40,160
Speaker 1: what it took to be a financial writer, that I

1332
01:19:40,200 --> 01:19:43,280
Speaker 1: was good with numbers, and I could write pleasing prose.

1333
01:19:43,320 --> 01:19:45,600
Speaker 1: And he he said that that I should pursue that.

1334
01:19:46,000 --> 01:19:48,240
Speaker 1: And then to other people who helped me greatly along

1335
01:19:48,240 --> 01:19:50,479
Speaker 1: the way were John raycenthal Or, whose chief of research

1336
01:19:50,560 --> 01:19:54,760
Speaker 1: at Morning Star, and Jonathan Clements of the Wall Street Journal,

1337
01:19:54,760 --> 01:19:58,519
Speaker 1: who very early on took uh an interest in me.

1338
01:19:58,960 --> 01:20:01,080
Speaker 1: And then there are the people who you know, I

1339
01:20:01,120 --> 01:20:03,439
Speaker 1: had only a very glancing knowledge of or almost no

1340
01:20:03,520 --> 01:20:05,920
Speaker 1: knowledge of it all. But who's writing affective me? And

1341
01:20:05,960 --> 01:20:10,120
Speaker 1: of course that's the holy trinity of of Bogel, uh

1342
01:20:10,160 --> 01:20:13,840
Speaker 1: and Malkiol Uh and Fama. If we if we're gonna

1343
01:20:13,880 --> 01:20:15,920
Speaker 1: do a mountain rushmore, all three have to go up.

1344
01:20:16,320 --> 01:20:19,080
Speaker 1: And I got to know Jack Bogel a little bit personally,

1345
01:20:19,439 --> 01:20:22,519
Speaker 1: not very well, uh, and then the other two I well,

1346
01:20:23,000 --> 01:20:25,479
Speaker 1: and then and then Gene Fama I do not don't

1347
01:20:25,520 --> 01:20:29,280
Speaker 1: really know at all. And I've become friends too with

1348
01:20:29,520 --> 01:20:32,240
Speaker 1: with John Ray canthall at all. He's enormously helped. It

1349
01:20:32,320 --> 01:20:34,200
Speaker 1: wasn't honest to help to me. I've been trying to

1350
01:20:34,240 --> 01:20:36,120
Speaker 1: get Fama in here for a long time. So if

1351
01:20:36,160 --> 01:20:39,680
Speaker 1: you ever do happen uh the befriend him, send him

1352
01:20:39,720 --> 01:20:42,920
Speaker 1: my way. He's I've had the other half of that

1353
01:20:42,960 --> 01:20:47,120
Speaker 1: Nobel Prize. I've had children here. But Fama remains elusive

1354
01:20:47,280 --> 01:20:51,400
Speaker 1: and is only rarely glimpsed in the wild. He does

1355
01:20:51,439 --> 01:20:55,479
Speaker 1: not have much of a public uh face. So you

1356
01:20:55,520 --> 01:20:59,120
Speaker 1: mentioned the writers that influenced, influenced you tell us about

1357
01:20:59,160 --> 01:21:03,040
Speaker 1: some of your favorite books, fiction, nonfiction, financial related whatever. Well,

1358
01:21:03,200 --> 01:21:05,439
Speaker 1: fiction wise, I don't read that much fiction. But there

1359
01:21:05,439 --> 01:21:08,160
Speaker 1: are two people who are or popular writing I should

1360
01:21:08,160 --> 01:21:09,920
Speaker 1: say that I read compulsively. And one of them is

1361
01:21:09,960 --> 01:21:15,080
Speaker 1: gen Lacaray, and the other is Michael Lewis. You know

1362
01:21:15,080 --> 01:21:18,360
Speaker 1: how often nonfiction Michael Lewis is nonfiction. He's nonfiction, of course,

1363
01:21:18,840 --> 01:21:20,720
Speaker 1: and and how often you know both you and I

1364
01:21:20,800 --> 01:21:23,680
Speaker 1: had the experience of reading an article somewhere in New

1365
01:21:23,760 --> 01:21:27,080
Speaker 1: York or Atlantic wherever, and you say, god, this is

1366
01:21:27,120 --> 01:21:29,080
Speaker 1: this is really good. I wonder who wrote this because

1367
01:21:29,120 --> 01:21:30,680
Speaker 1: you didn't really pay attention to who wrote it. And

1368
01:21:30,760 --> 01:21:32,320
Speaker 1: you go back and you slap your forehead, and of

1369
01:21:32,320 --> 01:21:34,479
Speaker 1: course it was Michael Lewis. So I'm gonna I'm gonna

1370
01:21:34,560 --> 01:21:37,719
Speaker 1: take it a step further. I always know who I'm reading.

1371
01:21:37,720 --> 01:21:41,240
Speaker 1: I I no longer read mastheads. I don't read the

1372
01:21:41,280 --> 01:21:43,760
Speaker 1: New York Times of the Wall Street Journal or The

1373
01:21:43,800 --> 01:21:48,320
Speaker 1: Atlantic or whatever. I read different authors. This is part

1374
01:21:48,400 --> 01:21:52,599
Speaker 1: of my reading evolution. And so I will read everything

1375
01:21:52,600 --> 01:21:56,080
Speaker 1: that Dan Gross or Michael Lewis or Jesse Eisinger or

1376
01:21:56,120 --> 01:21:59,080
Speaker 1: go down the list. Um, so I'd have a tendency

1377
01:21:59,200 --> 01:22:01,360
Speaker 1: to read I And I recall the last time I've

1378
01:22:01,400 --> 01:22:07,040
Speaker 1: experienced who wrote this. Oh, of course it's I I personally,

1379
01:22:08,000 --> 01:22:09,879
Speaker 1: but I spent a lot of time on the internet,

1380
01:22:10,080 --> 01:22:13,680
Speaker 1: and it's a fire hose. So to make that manageable,

1381
01:22:14,439 --> 01:22:16,679
Speaker 1: I try. There are people who whatever they put out,

1382
01:22:16,760 --> 01:22:19,400
Speaker 1: and certainly Michael Lewis is one of them. Whatever they

1383
01:22:19,439 --> 01:22:22,439
Speaker 1: put out, I just have to read it. Yeah. And

1384
01:22:22,479 --> 01:22:24,439
Speaker 1: then and then there are the three you know, the

1385
01:22:24,520 --> 01:22:31,080
Speaker 1: three great books that I recommend to everybody. Uh. Number

1386
01:22:31,240 --> 01:22:36,719
Speaker 1: number one is Expert Political Judgment by philth Tetle. Sure. Uh,

1387
01:22:36,760 --> 01:22:39,360
Speaker 1: you know about how what lousy forecasters we are, what

1388
01:22:39,479 --> 01:22:42,320
Speaker 1: mistakes we make, and you know his section on on

1389
01:22:42,560 --> 01:22:45,720
Speaker 1: the on the on the nexus between the media and

1390
01:22:45,920 --> 01:22:51,600
Speaker 1: pundits is required reading, sure for everybody. Uh. There is

1391
01:22:51,640 --> 01:22:55,160
Speaker 1: a book called The Moral Animal by Man Running of

1392
01:22:55,240 --> 01:23:01,000
Speaker 1: Robert Right, which gets to the heart of the origins

1393
01:23:01,040 --> 01:23:05,160
Speaker 1: of religion and morality and of human behavior. It's it's

1394
01:23:05,160 --> 01:23:08,360
Speaker 1: a book basically about evolutionary psychology. It's like Tetlock. It's

1395
01:23:08,400 --> 01:23:11,080
Speaker 1: a very dense book. And then finally there's a book

1396
01:23:11,080 --> 01:23:13,400
Speaker 1: which is easy, well, it's both easier and more painful

1397
01:23:13,439 --> 01:23:17,480
Speaker 1: to read, which is a book by a British documentarian

1398
01:23:17,680 --> 01:23:22,559
Speaker 1: called Lawrence Re's r e s called al Schwitz a

1399
01:23:22,640 --> 01:23:26,840
Speaker 1: New History, and it is about the camp personnel who

1400
01:23:27,200 --> 01:23:30,559
Speaker 1: worked at al Schwitz and how they did what they did,

1401
01:23:31,520 --> 01:23:35,640
Speaker 1: why they did it, and it basically explains to you

1402
01:23:36,439 --> 01:23:41,680
Speaker 1: Arrant's uh famous banality of evil. The Germans were not exceptional.

1403
01:23:41,720 --> 01:23:47,320
Speaker 1: They were not an exceptional people. Uh, they were just

1404
01:23:48,000 --> 01:23:51,040
Speaker 1: uh convinced by everybody. The Jews were vermin? What do

1405
01:23:51,080 --> 01:23:55,480
Speaker 1: you do to vermin? Uh? And what I tell everybody

1406
01:23:55,520 --> 01:23:58,760
Speaker 1: that I that I meet uh these days is that

1407
01:23:58,840 --> 01:24:05,080
Speaker 1: it's a very sure throw from vermin to rapists and murderers. Absolutely,

1408
01:24:05,120 --> 01:24:08,479
Speaker 1: it's it's I think that one of the things that

1409
01:24:08,560 --> 01:24:11,880
Speaker 1: have been revealed by the gas lighting we've seen over

1410
01:24:11,880 --> 01:24:14,640
Speaker 1: the past few years is that it's not hard to

1411
01:24:14,720 --> 01:24:19,360
Speaker 1: fool a huge swath of the population into doing unthinkable things.

1412
01:24:19,439 --> 01:24:23,960
Speaker 1: It's it's shockingly easy. Yeah, any any people, any people

1413
01:24:24,000 --> 01:24:27,559
Speaker 1: can do it. Uh. Any you know. One of the

1414
01:24:27,640 --> 01:24:31,519
Speaker 1: one of the most shocking things, most things will stick

1415
01:24:31,520 --> 01:24:35,320
Speaker 1: in your memory from from the reads book is that

1416
01:24:35,760 --> 01:24:39,360
Speaker 1: British officials in the Channel Island which we're taken over

1417
01:24:39,400 --> 01:24:44,919
Speaker 1: by the Germans, uh, gladly handed over Jews to the Nazis,

1418
01:24:45,080 --> 01:24:49,559
Speaker 1: the Brits during Brits during worldwide astonishing. Yeah, and it's

1419
01:24:49,600 --> 01:24:52,280
Speaker 1: also very useful when you're thinking about financial fraud and

1420
01:24:52,280 --> 01:24:55,720
Speaker 1: financial malthesis. If you understand Auschwitz, it's very easy to

1421
01:24:55,760 --> 01:24:59,280
Speaker 1: understand what happened in en Royn. Everybody brought into the

1422
01:24:59,320 --> 01:25:03,639
Speaker 1: whole company thing and despite obvious in this year fraud,

1423
01:25:03,720 --> 01:25:06,439
Speaker 1: they managed to overlook it. Um. I know you mentioned

1424
01:25:06,520 --> 01:25:10,120
Speaker 1: the FIAT was a failure, but let's talk more professionally.

1425
01:25:10,560 --> 01:25:12,599
Speaker 1: Tell us a power the time you failed and what

1426
01:25:12,640 --> 01:25:15,840
Speaker 1: you learned from the experience. Well, you know the last

1427
01:25:15,840 --> 01:25:18,720
Speaker 1: two nonfiction books that have been published and sold, where

1428
01:25:18,760 --> 01:25:22,800
Speaker 1: one was a splendid Exchange which succeeded beyond my wildest

1429
01:25:23,280 --> 01:25:27,640
Speaker 1: expectations in terms of reviews, sales, the speaking gigs. It

1430
01:25:27,640 --> 01:25:31,599
Speaker 1: continues to get me. Uh, it was wildly successful. And

1431
01:25:31,640 --> 01:25:33,720
Speaker 1: then the book that came after that, Masters of the Word,

1432
01:25:33,720 --> 01:25:36,880
Speaker 1: which we talked briefly about it was an absolute flop.

1433
01:25:36,960 --> 01:25:40,840
Speaker 1: I doubt it's sold five thousand copies. Really yeah? Uh?

1434
01:25:40,880 --> 01:25:44,320
Speaker 1: And and what that taught me is just how capricious

1435
01:25:44,840 --> 01:25:48,959
Speaker 1: publishing is. Are you equally satisfied with the final product?

1436
01:25:49,520 --> 01:25:51,680
Speaker 1: That's the whole point is is I had just as

1437
01:25:51,760 --> 01:25:54,280
Speaker 1: much fun writing both of them. I'm just as proud

1438
01:25:54,360 --> 01:25:58,160
Speaker 1: of of both of them. And and what it taught

1439
01:25:58,200 --> 01:26:00,000
Speaker 1: me is that you can spend three or four year

1440
01:26:00,200 --> 01:26:02,920
Speaker 1: is writing a book and it can disappear almost without

1441
01:26:02,920 --> 01:26:06,080
Speaker 1: a trace. Uh. And that doesn't mean that the exercise

1442
01:26:06,479 --> 01:26:09,519
Speaker 1: wasn't worthwhile, because hopefully you're writing books for other reasons.

1443
01:26:09,840 --> 01:26:11,160
Speaker 1: What do you do for fun? What do you do

1444
01:26:11,240 --> 01:26:15,840
Speaker 1: when you're not writing books or researching in the library? Well, um,

1445
01:26:15,920 --> 01:26:20,960
Speaker 1: you know, uh, I lead I'm afraid of very ordinary life.

1446
01:26:21,000 --> 01:26:25,600
Speaker 1: I'm your base acceptationtioneering and who enjoys his children and

1447
01:26:25,640 --> 01:26:30,840
Speaker 1: his grandchildren and traveling. Uh while I I still can uh.

1448
01:26:31,400 --> 01:26:35,680
Speaker 1: I I enjoy living in Portland, Oregon more than I

1449
01:26:35,680 --> 01:26:38,320
Speaker 1: can imagine. You can imagine. I live in a place

1450
01:26:38,640 --> 01:26:41,400
Speaker 1: where I can walk downtown and be there in fifteen minutes,

1451
01:26:41,479 --> 01:26:43,240
Speaker 1: or I can walk twenty minutes uphill and be in

1452
01:26:43,280 --> 01:26:48,720
Speaker 1: a Sequoia grove. Uh. And you know have have have

1453
01:26:48,840 --> 01:26:51,960
Speaker 1: first class Cuiscans and uh and begets right out in

1454
01:26:51,960 --> 01:26:55,760
Speaker 1: my front door. The food in Portland is outstanding. I

1455
01:26:55,760 --> 01:26:58,160
Speaker 1: don't know if people realize that that should be on

1456
01:26:58,280 --> 01:27:01,519
Speaker 1: the foodie city. So it's every time I'm there, I

1457
01:27:01,560 --> 01:27:07,360
Speaker 1: come away that was it was really amazing restaurants. We

1458
01:27:07,400 --> 01:27:11,320
Speaker 1: have an office in Portland. It's really astonishing the food there. Yeah.

1459
01:27:11,400 --> 01:27:14,200
Speaker 1: So I love that. And of course, you know, the

1460
01:27:14,680 --> 01:27:17,760
Speaker 1: things that that I that I really enjoy doing are

1461
01:27:17,760 --> 01:27:22,760
Speaker 1: are the research, the the the process of putting a

1462
01:27:22,840 --> 01:27:27,519
Speaker 1: book together. It is just great fun under uncovering these

1463
01:27:27,520 --> 01:27:30,519
Speaker 1: stories it almost no one knows about. So, so what's

1464
01:27:30,520 --> 01:27:32,519
Speaker 1: the next book that's going to be coming from you?

1465
01:27:32,840 --> 01:27:36,639
Speaker 1: The next book will be a modern remake, if you will,

1466
01:27:36,720 --> 01:27:41,040
Speaker 1: of Charles McKay's famous Extraordinary Popular Delusions in the Madness

1467
01:27:41,040 --> 01:27:44,360
Speaker 1: of Crowds or actually Memoirs of Extraordinary Popular Delusions in

1468
01:27:44,400 --> 01:27:47,080
Speaker 1: the Madness of Crowds. Uh. Let's got to be so

1469
01:27:47,160 --> 01:27:50,040
Speaker 1: much fun to dive into. Oh yeah, and it's a

1470
01:27:50,080 --> 01:27:53,439
Speaker 1: book basically that covers finance, of course, the three Great

1471
01:27:53,479 --> 01:27:59,599
Speaker 1: bubbles of the seventeenth and eighteenth centuries, as well as

1472
01:27:59,760 --> 01:28:02,640
Speaker 1: all out of religious manias. Uh. And so that's what

1473
01:28:02,720 --> 01:28:05,840
Speaker 1: this book is, it's it combines three things. Is financial

1474
01:28:05,840 --> 01:28:09,680
Speaker 1: mania's religious manias, and then the neuropsychology and particularly the

1475
01:28:09,680 --> 01:28:12,920
Speaker 1: evolutionary psychology that glues all of them together. But one

1476
01:28:12,960 --> 01:28:16,120
Speaker 1: of the things that I learned from my colleague Ben Carlson,

1477
01:28:16,160 --> 01:28:20,920
Speaker 1: who I know, you know, was that the Japanese um

1478
01:28:21,040 --> 01:28:25,400
Speaker 1: bubble that popped in nine made the Nasdaq bubble in

1479
01:28:25,439 --> 01:28:28,920
Speaker 1: two thousand look like child's play. It was like five

1480
01:28:29,040 --> 01:28:32,519
Speaker 1: or ten x what the NASDAK bubble was. It's it's stunning. Yeah.

1481
01:28:32,560 --> 01:28:36,120
Speaker 1: The Nikkei peaked very close to forty thousand, and I

1482
01:28:36,160 --> 01:28:39,200
Speaker 1: think that it's at it's nadir. Uh. It was somewhere

1483
01:28:39,240 --> 01:28:42,080
Speaker 1: around five thousand, and I don't know what it is now,

1484
01:28:42,120 --> 01:28:44,719
Speaker 1: but it's somewhere in the mid teens right now, I think.

1485
01:28:44,920 --> 01:28:46,880
Speaker 1: But it was it was the equivalent of the S

1486
01:28:46,960 --> 01:28:50,360
Speaker 1: and P five hundred during the dot coms was about

1487
01:28:50,400 --> 01:28:53,240
Speaker 1: thirty two times. I think the nick was a hundred

1488
01:28:53,320 --> 01:28:56,559
Speaker 1: times earnings at its peak or even worse. Yeah, very very,

1489
01:28:56,680 --> 01:28:58,400
Speaker 1: very very close to that. And that's what you know.

1490
01:28:58,439 --> 01:29:00,639
Speaker 1: People always talk about, my gosh, can the US stock

1491
01:29:00,680 --> 01:29:06,719
Speaker 1: market experience, Uh, what happened to the Japanese stock market

1492
01:29:06,720 --> 01:29:09,880
Speaker 1: post nineteen eighty nine, and the answer is it did

1493
01:29:10,000 --> 01:29:14,320
Speaker 1: of course. Uh In nine thirty two was the was

1494
01:29:14,360 --> 01:29:17,920
Speaker 1: the multiple that wildly out of whack, No, but the

1495
01:29:17,920 --> 01:29:21,439
Speaker 1: market fell by the S and P the the the

1496
01:29:21,479 --> 01:29:24,439
Speaker 1: dal Jones industrial average fell by about eighty eight percent,

1497
01:29:24,880 --> 01:29:27,799
Speaker 1: so it was the same order of magnitude of fall.

1498
01:29:28,280 --> 01:29:30,680
Speaker 1: The reason why I think it's unlikely we're unlikely to

1499
01:29:30,680 --> 01:29:33,519
Speaker 1: see anything like that happened to the US market, and

1500
01:29:33,520 --> 01:29:36,200
Speaker 1: why it's more believable in Japan is simply because you know,

1501
01:29:36,280 --> 01:29:39,719
Speaker 1: in nineteen ninety nine we only had a pe of

1502
01:29:39,840 --> 01:29:42,360
Speaker 1: like well as trailing p I think of forty and

1503
01:29:42,400 --> 01:29:44,360
Speaker 1: a cape of thirty, or maybe it was the other

1504
01:29:44,360 --> 01:29:46,200
Speaker 1: way around, a cape of forty and a por trailing

1505
01:29:46,240 --> 01:29:48,800
Speaker 1: pe of thirty, whereas now we're at a trailing pe

1506
01:29:48,960 --> 01:29:51,759
Speaker 1: of somewhere around twenty in a trailing cape of somewhere

1507
01:29:51,760 --> 01:29:58,040
Speaker 1: around what thirty? Yeah. Uh, So you know, it's much

1508
01:29:58,080 --> 01:30:00,120
Speaker 1: more believable that that happened in Japan that it will

1509
01:30:00,160 --> 01:30:05,120
Speaker 1: happen to us. And the cape. The rub on the

1510
01:30:05,160 --> 01:30:08,760
Speaker 1: Cape these days continues to be it's just gives you

1511
01:30:08,800 --> 01:30:13,559
Speaker 1: some insight into forward expectations, not a timing mechanism. It's

1512
01:30:13,720 --> 01:30:18,880
Speaker 1: it's been overvalued since something like eight percent of the time. Yeah.

1513
01:30:18,880 --> 01:30:20,840
Speaker 1: The one you finance way of saying it is that

1514
01:30:20,880 --> 01:30:24,640
Speaker 1: it's not a stationary parameter, okay, meaning that if you

1515
01:30:24,760 --> 01:30:27,880
Speaker 1: just look at how it works out of sample, it

1516
01:30:27,920 --> 01:30:30,960
Speaker 1: works very poorly. Out of sample and sample it works.

1517
01:30:31,000 --> 01:30:35,559
Speaker 1: But if you do, for example, what what Staunton, marsh

1518
01:30:35,640 --> 01:30:38,080
Speaker 1: and Dimpson did, which is to look at it at

1519
01:30:38,080 --> 01:30:42,360
Speaker 1: the say the dividend yield UH in multiple countries, and

1520
01:30:42,400 --> 01:30:44,800
Speaker 1: then you just stop the analysis each and every year,

1521
01:30:44,880 --> 01:30:47,880
Speaker 1: you look back UH, and you devise a set of

1522
01:30:48,000 --> 01:30:50,519
Speaker 1: rules depending on you know, that are based on looking

1523
01:30:50,560 --> 01:30:52,599
Speaker 1: back at a given point, and then you look how

1524
01:30:52,600 --> 01:30:54,960
Speaker 1: it does forward. It does very poorly going forward and

1525
01:30:55,200 --> 01:30:57,840
Speaker 1: in almost all countries. The one thing that that does

1526
01:30:57,880 --> 01:31:00,799
Speaker 1: work is is timing within countries, but that a different subject.

1527
01:31:01,320 --> 01:31:04,240
Speaker 1: So so out of sample is a big warning, UH

1528
01:31:04,400 --> 01:31:06,840
Speaker 1: to take the cape with a whole lot of grain

1529
01:31:06,880 --> 01:31:08,760
Speaker 1: assault exactly because you don't you don't know what the

1530
01:31:08,760 --> 01:31:11,599
Speaker 1: future distribution is going to look like. Alright, So our

1531
01:31:11,640 --> 01:31:15,400
Speaker 1: final two questions. If a millennial or recent college graduate

1532
01:31:15,439 --> 01:31:18,160
Speaker 1: came to you and said they're looking for advice about

1533
01:31:18,240 --> 01:31:23,799
Speaker 1: going into either medicine and neurology or finance and writing.

1534
01:31:24,000 --> 01:31:27,439
Speaker 1: What sort of advice would you give that medicine is

1535
01:31:27,479 --> 01:31:29,680
Speaker 1: a much surer way of making a living than writing is,

1536
01:31:29,720 --> 01:31:34,439
Speaker 1: that's for sure. I would. I tend to look at

1537
01:31:34,600 --> 01:31:39,840
Speaker 1: writing as something you do to amuse yourself in your dotage. Uh,

1538
01:31:39,920 --> 01:31:43,120
Speaker 1: it's it's it's it's fun. But if if you've got

1539
01:31:43,360 --> 01:31:45,920
Speaker 1: kids to raise and colleges to pay for, I I

1540
01:31:45,960 --> 01:31:50,240
Speaker 1: wouldn't become a writer. I would choose a much more

1541
01:31:50,320 --> 01:31:53,960
Speaker 1: solid profession. Live modestly. Uh, and then you know you

1542
01:31:54,000 --> 01:31:56,360
Speaker 1: can you can kick back and follow your blessing right

1543
01:31:56,400 --> 01:31:59,519
Speaker 1: if you feel like are. I've asked a number of

1544
01:31:59,560 --> 01:32:02,920
Speaker 1: doctors this question, and I'm curious as to your view.

1545
01:32:03,439 --> 01:32:05,599
Speaker 1: If your kids came to you and said they wanted

1546
01:32:05,600 --> 01:32:08,639
Speaker 1: a career in medicine, would when they were younger, would

1547
01:32:08,680 --> 01:32:11,439
Speaker 1: you have encouraged or discouraged them? Yeah? I would. I

1548
01:32:11,439 --> 01:32:14,120
Speaker 1: would encourage anybody who wants to go into real edison too.

1549
01:32:14,240 --> 01:32:18,840
Speaker 1: It's it's a very rewarding profession and uh it's it's

1550
01:32:18,880 --> 01:32:21,920
Speaker 1: it's a much more difficult profession than when I was

1551
01:32:22,040 --> 01:32:26,640
Speaker 1: in it because of all the bureaucracy and not only that,

1552
01:32:26,680 --> 01:32:28,479
Speaker 1: but you know, back in the day you could work

1553
01:32:28,520 --> 01:32:31,479
Speaker 1: for yourself. Now you'll almost certainly be working for the

1554
01:32:31,560 --> 01:32:36,679
Speaker 1: NBA from hell. Uh. Even even so, Uh, it's it's

1555
01:32:36,680 --> 01:32:39,680
Speaker 1: a it's a it's a fine profession that offers rewards

1556
01:32:39,720 --> 01:32:43,200
Speaker 1: that nothing else, no other professions that will provide you

1557
01:32:43,240 --> 01:32:45,760
Speaker 1: with And our final question, what is it that you

1558
01:32:45,800 --> 01:32:48,640
Speaker 1: know about the world of investing today you wish you

1559
01:32:48,720 --> 01:32:52,880
Speaker 1: knew when you first started out years ago. Well, there's

1560
01:32:52,920 --> 01:32:55,960
Speaker 1: this parlor game that economics like to play about how

1561
01:32:56,080 --> 01:32:59,360
Speaker 1: risky your stocks? Uh. And we've all heard the rationales

1562
01:32:59,439 --> 01:33:01,240
Speaker 1: of you know, how how they get risky or less

1563
01:33:01,280 --> 01:33:03,880
Speaker 1: more or less risky with time, and that how that

1564
01:33:03,960 --> 01:33:05,920
Speaker 1: argument goes back and forth. But what I've learned that

1565
01:33:05,960 --> 01:33:07,880
Speaker 1: I wish I knew back then is that it's a

1566
01:33:07,880 --> 01:33:12,559
Speaker 1: stupid question to ask without also adding for a given

1567
01:33:12,560 --> 01:33:15,559
Speaker 1: investor of a given age. Right, So, if you are

1568
01:33:15,600 --> 01:33:17,880
Speaker 1: a twenty year old saver who has a lot of

1569
01:33:17,960 --> 01:33:20,599
Speaker 1: human capital and no investment capital and a fifty year

1570
01:33:20,680 --> 01:33:23,040
Speaker 1: time horizon, stocks aren't the least bit risky. In fact,

1571
01:33:23,040 --> 01:33:25,080
Speaker 1: you should get down on your knees and pray for

1572
01:33:25,160 --> 01:33:29,800
Speaker 1: volatility and low returns all right. But once you know

1573
01:33:29,960 --> 01:33:34,200
Speaker 1: you're approaching your your geezer hood. Uh, stocks are are

1574
01:33:34,280 --> 01:33:38,480
Speaker 1: three mile Island toxic and you should be very approached

1575
01:33:38,479 --> 01:33:40,400
Speaker 1: them with with a great degree of caution. So I

1576
01:33:40,439 --> 01:33:43,240
Speaker 1: wished I had known when I was thirty years old

1577
01:33:43,280 --> 01:33:46,400
Speaker 1: that I could put acent of my savings into stocks

1578
01:33:46,680 --> 01:33:50,280
Speaker 1: and not worry at all about them. That makes perfect sense, Bill,

1579
01:33:50,320 --> 01:33:51,840
Speaker 1: Thank you so much for doing this. This has been

1580
01:33:51,840 --> 01:33:55,960
Speaker 1: absolutely fascinating. We have been speaking with Bill Bernstein. He

1581
01:33:56,200 --> 01:34:00,280
Speaker 1: is the author of numerous books. Go to Amazon or

1582
01:34:00,400 --> 01:34:02,559
Speaker 1: barn to Noble or wherever you pick up your books

1583
01:34:02,560 --> 01:34:05,080
Speaker 1: and you can see any of the dozen or so

1584
01:34:05,439 --> 01:34:08,880
Speaker 1: UM offerings he has, and I highly recommend any or

1585
01:34:08,920 --> 01:34:11,920
Speaker 1: all of them have Splendor exchange. UM. It was really

1586
01:34:11,960 --> 01:34:14,519
Speaker 1: fascinating and because of that, I'm gonna have to go

1587
01:34:14,960 --> 01:34:19,479
Speaker 1: get your book on on Media and Words. I was

1588
01:34:20,120 --> 01:34:22,880
Speaker 1: you said. It came and went so quickly. I don't

1589
01:34:22,920 --> 01:34:25,080
Speaker 1: even recall seeing that book come out, but this one

1590
01:34:25,120 --> 01:34:29,360
Speaker 1: I remember UM getting as soon as as it was published.

1591
01:34:29,760 --> 01:34:33,200
Speaker 1: So that thank you. Thank you for your time. UM.

1592
01:34:33,240 --> 01:34:35,639
Speaker 1: If you enjoy this conversation, We'll be sure to look

1593
01:34:35,680 --> 01:34:38,120
Speaker 1: up an Inch or down an Inch on Apple iTunes.

1594
01:34:38,160 --> 01:34:40,960
Speaker 1: And you can see any of the other two hundred

1595
01:34:41,000 --> 01:34:45,599
Speaker 1: and fifties such conversations we've had over the past five years. UM,

1596
01:34:45,640 --> 01:34:49,439
Speaker 1: we love your comments, feedback in suggestions right to us

1597
01:34:49,640 --> 01:34:53,920
Speaker 1: at m IB podcast at Bloomberg dot net. I would

1598
01:34:53,960 --> 01:34:56,080
Speaker 1: be remiss if I did not thank the crack staff

1599
01:34:56,160 --> 01:35:00,280
Speaker 1: that helps put together these conversations each week. But Dina

1600
01:35:00,360 --> 01:35:04,240
Speaker 1: Parwana is my audio engineer slash producer. Michael Boyle as

1601
01:35:04,280 --> 01:35:08,960
Speaker 1: our producer slash booker. Attica val Brunn is our project manager.

1602
01:35:09,360 --> 01:35:13,120
Speaker 1: Michael bat Nick is our head of research. I'm Barry Ritolts.

1603
01:35:13,360 --> 01:35:16,799
Speaker 1: You're listening to Masters in Business on Bloomberg Radio.