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

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Speaker 1: Bloomberg Radio.

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Speaker 2: This week on the podcast, I have a special guest.

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Speaker 2: His name is Peter Atwater and he is the author

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Speaker 2: of several books, most recently The Confidence Map, Charting a

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Speaker 2: Path from Chaos to Clarity. Peter has had a fascinating

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Speaker 2: career in finance, JP Morgan, Bangwan, a few other large

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Speaker 2: places where he got to see how people's sentiment and

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Speaker 2: confidence levels affected their decision making. And this is everything

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Speaker 2: from securitized credit cards to investing and beyond. I found

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Speaker 2: this to be an absolutely fascinating conversation. We discussed everything

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Speaker 2: from the shape of cars to January sixth, and how

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Speaker 2: each of the events that we talked about or milestones

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Speaker 2: in society reflect the confidence, life level and the degree

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Speaker 2: of uncertainty that the population at large feels. These are

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Speaker 2: things that can be measured, and from those measurements you

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Speaker 2: could get a sense of what's likely to come next.

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Speaker 2: I thought this discussion was absolutely fascinating, and I think

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Speaker 2: you will also with no further ado my discussion with

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Speaker 2: Financial Insights. Peter Atwater, Welcome to Bloomberg.

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Speaker 1: Thanks so much, Barry.

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Speaker 2: So let's talk a little bit about your background, which

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Speaker 2: I find is kind of fascinating. You graduate William and

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Speaker 2: Mary in eighty three. How did your career begin? Where

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Speaker 2: did you go from college?

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Speaker 1: Yeah? I have a very traditional finance background. Started at

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Speaker 1: JP Morgan right out of school, went through their bank

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Speaker 1: training program. Wanted a foreign assignment, and the next thing

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Speaker 1: I knew, I was in Delaware. And what I was

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Speaker 1: ended up doing, though, was the beginning of what we

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Speaker 1: call asset back securities today, pulling to get other credit

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Speaker 1: card loans for seers, for mbn A and first USA

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Speaker 1: car loans. And if you remember your history, banks at

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Speaker 1: that point were just beginning to compete with the big

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Speaker 1: Wall Street firms and commercial paper and asset backed securities

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Speaker 1: were the first securities that the FED gave banks permission

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Speaker 1: to underwrite. And so suddenly we were having to compete

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Speaker 1: with Solomon, with Bear, with the CSFB in their territory.

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Speaker 1: And so my job basically became how do we outthink them?

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Speaker 1: Because there was no way we could out muscle Marrow,

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Speaker 1: and so we had to We had just had to

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Speaker 1: be better at structuring, finding ways to make things less expensive,

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Speaker 1: you know, bring something else to bear.

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Speaker 2: So what years were this. When were you at JP Morgan.

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Speaker 1: I was there from eighty three to ninety six.

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Speaker 2: Okay, and then what ultimately, so you missed all the

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Speaker 2: fun during the.

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Speaker 1: I did I did. I planted the seeds.

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Speaker 2: Although back then performing credit card debt wasn't quite the

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Speaker 2: same as ninja loans being fed into mortgage.

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Speaker 1: Back I mean square. And you know, I left JP

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Speaker 1: Morgan to actually go work for First USA, one of

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Speaker 1: the credit card companies, and and you know, part of

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Speaker 1: that was this clear view of the trajectory that securitization

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Speaker 1: was going to change the business. You know, little did

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Speaker 1: I realize that a year later we'd get bought by

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Speaker 1: Bank One because Bank One needed desperately to have a

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Speaker 1: credit card business. And so my career made another pivot

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Speaker 1: to go from the treasure of a startup credit card

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Speaker 1: company to being the treasure of the eighth largest bank

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Speaker 1: in the country.

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Speaker 2: Eventually you rise to the role of CEO of Private

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Speaker 2: Client Services at Bank One. Tell us a little bit

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Speaker 2: about that job.

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Speaker 1: Yeah, So Bank One had merged with for Chicago, the

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Speaker 1: merger with Tumultis, and so the board ultimately brought in

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Speaker 1: Jamie Diamond. I talk about it merging with Jamie, you know,

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Speaker 1: because this combination was a terrible cultural fit. It was

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Speaker 1: almost viewed as a Tiffany by his Walmart combination. The

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Speaker 1: egos were not happy with it, and Jamie did a

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Speaker 1: great job of sort of reminding people that the enemy

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Speaker 1: was outside the business. But he quickly uncovered where the

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Speaker 1: merger had not executed the way it meant to. One

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Speaker 1: of those was in the client the wealth management area,

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Speaker 1: where we had lots of great skills in terms of

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Speaker 1: trust and private banking and all of these elements, but

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Speaker 1: no general practitioner. It was like we were running a

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Speaker 1: hospital with no folks who could who could look at

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Speaker 1: the patient holistically. And so one of the first things

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Speaker 1: I did in that job was to identify who can

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Speaker 1: be the point person so that you can cross sell

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Speaker 1: and deliver a much fuller array of products than just,

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Speaker 1: you know, the single products we were offering.

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Speaker 2: You know, it's fascinating because there's the practice of investing

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Speaker 2: and then there's the business of investing, and there are

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Speaker 2: two very different things. I would imagine it's very similar

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Speaker 2: in banking. There's the practice of banking and then the

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Speaker 2: business of running a bank. You're what you're describing where

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Speaker 2: the folks at Bank one were better at the former

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Speaker 2: than the latter. Is that a fair way to say

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Speaker 2: it was?

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Speaker 1: This was an organization that had grown by acquisition, and

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Speaker 1: so the mindset was always buy revenue, cut expense by

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Speaker 1: revenue cut expense, and so long as you can keep

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Speaker 1: doing that, you leave some fundamentals un dealt with, right

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Speaker 1: and when you stop the roll up, then you have

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Speaker 1: to look at how do you how do you integrate

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Speaker 1: it or in some cases spin things off. But I'll

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Speaker 1: tell you my timing couldn't have been worse, Sperry. I

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Speaker 1: took that job in early two thousand and basically rode

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Speaker 1: the market down, and I'll tell you nothing teaches you

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Speaker 1: more about how things work than watching them not work

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Speaker 1: on the way down. And so it was really eye

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Speaker 1: opening to see how overconfidence turns into panic as we

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Speaker 1: went through the dot com bubble.

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Speaker 2: So you're anticipating my next question. It was your first

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Speaker 2: book was Moods and Markets, the second book is all

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Speaker 2: about confidence. What led to this interest in that aspect

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Speaker 2: of behavioral finance? Was it the asset backed securities, was

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Speaker 2: it watching a roll up entity, or was it the

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Speaker 2: dot com collapse that sent asset prices depending on where

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Speaker 2: you were invested. I like to remind people, nastec fell

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Speaker 2: pete to troth eighty one percent. It's a big, big whack.

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Speaker 2: That's great depression level fall.

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Speaker 1: Yeah. I would say that my interest didn't arise until

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Speaker 1: the Great Financial Crisis. You know, I had left the industry.

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Speaker 1: I turned forty five and my son said, halfway, your dad,

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Speaker 1: you're halfway to ninety and not horrifying kind of a

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Speaker 1: tough you know, punch to the gut. And the other

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Speaker 1: way to look at it is all right. I man,

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Speaker 1: at this far, it's so far, so good. So this

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Speaker 1: was two thousand and six. For the first time in

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Speaker 1: my adult life, I had the opportunity to move away

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Speaker 1: from the trees and start to see the forest, and

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Speaker 1: to see what was happening in the mortgage space to

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Speaker 1: your point Ninja loans and the wildness there, and then

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Speaker 1: to watch as sentiments started to fall, how things started

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Speaker 1: to come apart. And I ended up advising some hedge

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Speaker 1: funds because my background as a treasurer bank treasurer, I

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Speaker 1: dealt with the rating agencies. I'd securitize stuff. I mean,

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Speaker 1: I knew how things go bad. Having spent a lot

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Speaker 1: of time in troubled banks at my time at JP Morgan,

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Speaker 1: and so what interested me as Lehman collapsed and what

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Speaker 1: was going on was this sense that the crisis isn't done.

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Speaker 1: We're moving a lot of risk from the private sector

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Speaker 1: to the public sector, but we have an eliminated risk.

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Speaker 1: And at the same time, everybody's saying things are getting

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Speaker 1: going to get worse, and now the market starts to

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Speaker 1: turn up. And that combination of the crowd saying things

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Speaker 1: are only going to get worse and the market going

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Speaker 1: up was a game changer for me.

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Speaker 2: It's like, well, the term capitulation means surrender. Yeah, right,

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Speaker 2: so when everybody throws in the towel, you know, I

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Speaker 2: love asking people, you know, if they're bullish or beersh as.

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Speaker 2: The first question and then the second question is what

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Speaker 2: was your last transaction in the market. And invariably, if

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Speaker 2: they're bullish, they just bought something, and if their bears,

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Speaker 2: they just sold something. And it's a chicken and egg issue.

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Speaker 2: Are they bullish because they bought something or did they

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Speaker 2: buy something because they're bullish? Sometimes it's hard to tease

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Speaker 2: the two apart.

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Speaker 1: It's entirely reflexive, and so I say a lot. Our

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Speaker 1: confidence level, our stories, and our actions exist in equilibrium

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Speaker 1: at all times. I don't care which is chicken or egg.

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Speaker 1: I just know that if I talk to Barry Ritholtz

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Speaker 1: and I know what you're doing, I know what your

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Speaker 1: story is, and I know how you feel, and I

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Speaker 1: can pick one of the three and pretty well deduce

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Speaker 1: what the other two are likely to be.

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Speaker 2: You know, the old trader's aphorism is news follows price,

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Speaker 2: meaning when the price stocks are going up, the narratives

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Speaker 2: are great, and when the prices are going down, the

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Speaker 2: narratives are usually negative. Although I have a vivid recollection.

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Speaker 2: In the beginning, if they war, oil prices had spiked

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Speaker 2: the same day US accidentally bombed and important mosque, and

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Speaker 2: that was a headline, U Air Force accidentally destroys mosque,

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Speaker 2: causing oil prices to spike. By the end of the day,

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Speaker 2: oil prices had come back down and got negative. So

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Speaker 2: the online headlines were US bombs my mosque accidentally, oil

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Speaker 2: prices fall. It's like, well, which was it? Or maybe

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Speaker 2: you're these just wholly unrelated things and we're trying to

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Speaker 2: create a story.

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Speaker 1: Yeah, I always feel sorry for the daily news writers

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Speaker 1: when you see major market reverses, because to watch them

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Speaker 1: contort themselves to create a comfortable narrative, it's humorous.

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Speaker 2: Right, It's all hindsight bias and narrative fallacy and storytelling.

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Speaker 2: So one of the things I was surprised to learn

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Speaker 2: as I was reading your background, and you say you

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Speaker 2: build on the insights of Robert Prector's work in socioeconomics, socioonomics, socioonomics,

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Speaker 2: I've always pronounced that wrong. So a long time ago

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Speaker 2: I read Prector's perspectives and was very influenced by his

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Speaker 2: concept of the long cycle. You come out of World

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Speaker 2: War Two, all these gis are returning to the US.

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Speaker 2: There's the GI bill sending him to college, where building

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Speaker 2: out suburbia, the rise of car culture, the rise of

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Speaker 2: just the middle class, and that cycle seems to go

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Speaker 2: a long time and last a while. How did Prector's

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Speaker 2: work affect you?

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Speaker 1: So in twenty ten he did an interview for an

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Speaker 1: organization called Minionville. Oh sure, Tod Harrison and I had

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Speaker 1: been writing for Minionville, and I listened to Bob talk

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Speaker 1: and he said something that I had not paid much

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Speaker 1: attention to before or which was a reversal in causality,

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Speaker 1: which is we tend to look at events causing us

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Speaker 1: to change our feelings. Bob's recommendation and the foundation for

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Speaker 1: socionomics is look at the mood before things happen. And

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Speaker 1: suddenly it made so much sense to me that of

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Speaker 1: course we act as we feel, and if I could

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Speaker 1: then figure out what is consistent in those actions and

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Speaker 1: connect them to feelings, then that might be something really useful,

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Speaker 1: as whether it was in consulting or trading, to be

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Speaker 1: able to connect preferences to the choices we make and

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Speaker 1: how we feel.

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Speaker 2: So how does one go about measuring mood? How can

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Speaker 2: you measure the sentiment of the public. It's not especially uniform.

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Speaker 2: It seems to fluctuate, and as we've learned, we can

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Speaker 2: always trust what people say.

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Speaker 1: Yeah, so I look at it very qualitatively, because mood

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Speaker 1: is a feeling, and so the qualitative pieces matter more

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Speaker 1: than the data to us data. We always have to

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Speaker 1: interpret data, and so our feelings determine how we interpret.

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Speaker 1: You know, sixty five degrees can feel both warm and cool.

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Speaker 1: But what I try to do is to look at

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Speaker 1: the stories, and stories are a great indicator of how

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Speaker 1: we feel because our imagination of the future, the stories

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Speaker 1: we tell perfectly mirror how we feel. Confidence is forward looking,

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Speaker 1: and so my imagination of what's coming is going to

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Speaker 1: be a reflection on my mood right now. And the

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Speaker 1: media does a great job of letting me know what

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Speaker 1: those stories are. Twitter and social media does a spectacular job.

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Speaker 1: So does Google, I mean Google searches. I'm a big

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Speaker 1: user of Google trends. It helps me to see what's

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Speaker 1: the crowd interested, what are the stories we tell, and

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Speaker 1: the word choices. So recently I see the word relentless

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Speaker 1: being applied to the rise and interest rates as we're

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Speaker 1: coming to an end of the third quarter of twenty

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Speaker 1: twenty three. Well, relentless is a word that doesn't show

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Speaker 1: up in stories until it's beginning to feel like something

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Speaker 1: significant is about to happen.

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Speaker 2: Right, And if we're going to be objective and put

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Speaker 2: some numbers on it, as much as we all would

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Speaker 2: prefer lower rates, we've had eighteen nineteen months of rising rates,

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Speaker 2: and rates are now back to where they've averaged over

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Speaker 2: the past fifty years. So if you're being bloodless about it, hey,

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Speaker 2: rates have returned to normal fairly quickly, and yet it

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Speaker 2: doesn't feel that way.

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Speaker 1: But I can also look at the behavior of bond

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Speaker 1: investors and look at the stampede that took place two

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Speaker 1: years ago into negative yielding bonds and the stories that

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Speaker 1: and along that, and the confidence that investors had.

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Speaker 2: And meaning at the very peak of the bond bull

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Speaker 2: market just before the reversal took place.

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Speaker 1: Yeah, I mean you could. You could see this sense

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Speaker 1: of permanence and power that that you know, nothing was

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Speaker 1: going to be able to raise interest rates at that point,

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Speaker 1: and so you had a story that perfectly aligned with

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Speaker 1: negative interest negative yielding interest rates that was overlooked because

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Speaker 1: of the the excitement that was happening in the markets

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Speaker 1: and bond prices at record highs.

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Speaker 2: So, so how do you tease out of these broad

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Speaker 2: events in society? What what the underlying nugget of important

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Speaker 2: signal is? Uh, you had a tweet that cracked me up.

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Speaker 2: I want to share when confidence is low, cars are round.

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Speaker 2: So I started to think about that, and you have

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Speaker 2: some of these ugly old citrones and the qt VW beetle,

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Speaker 2: and then later on the pacer there have been some

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Speaker 2: pretty round and not necessarily beautiful cars over the years.

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Speaker 2: What's the correlation?

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Speaker 1: So I have to give credit to Mark Elishski, who

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Speaker 1: works with Bob Prector on socioomis, because because Mark did

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Speaker 1: this fabulous study that shows that cars are soft, they're round,

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Speaker 1: their colors are bland, even though the woody. You know,

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Speaker 1: if you think about sure, that's another low confidence indicator.

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Speaker 1: And then you go to the other extreme and you

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Speaker 1: have chrome, very.

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Speaker 2: Angulag war e type just long, beautiful.

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Speaker 1: Wide, you know, big engines. You know, you look at

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Speaker 1: the Hummer, that was a classic, you know, that would

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Speaker 1: be an indicator of of huge.

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Speaker 2: Sentiment, really really interesting. You know what.

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Speaker 1: The Mayback is one of my favorite indicators because it

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Speaker 1: sort of comes and goes at these extraordinary moments in history.

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Speaker 2: Is that how you think about cars like the Hummer

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Speaker 2: or the Maybach as just votes of confidence as to

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Speaker 2: the near future.

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Speaker 1: Yeah, you know the Phaeton from Volkswagen. Again I recall

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Speaker 1: terribly timed.

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Speaker 2: B twelve big long seven series competitor.

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Speaker 1: You know, the car companies want to deliver uber luxury

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Speaker 1: to everybody at the top. I mean I spend a

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Speaker 1: lot of time looking at LVMH because I think there's

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Speaker 1: no better real time indicator for the financial elite.

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Speaker 2: People give me grief because I track Rolex and Protect

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Speaker 2: prices and Ferrari and Porsche prices. There are a bunch

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Speaker 2: of services that track that. It's like, why are you

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Speaker 2: so obsessed on watchers and cars. No, I'm obsessed with

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Speaker 2: what the top one or ten percent does because what

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Speaker 2: they do is going to trickle down to the rest

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Speaker 2: of I don't mean trickle down in Oregan sense, but

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Speaker 2: their behavior has a huge impact on the rest of

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Speaker 2: the economy. Absolutely, talk about that a little bit.

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Speaker 1: Yeah, So there are indicators to me to all levels

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Speaker 1: of the economy. So if I want to look at

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Speaker 1: the upper middle class, I'll look at a Carnival cruise line.

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Speaker 1: Because travel requires us to plan, to have again a

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Speaker 1: strong imagination of the future. We're going to admit some

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Speaker 1: money we're committing. It's not an insignificant amount of money,

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Speaker 1: and so that that becomes a great bell weather for

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Speaker 1: me in terms of how how are those that are

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Speaker 1: not you know, the one percent, but those that are

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Speaker 1: doing well, how are they faring?

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Speaker 2: So I'm glad you mentioned carnival cruise lines because there's

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Speaker 2: something that's been perplexing me and I don't want to

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Speaker 2: just dumb it down to explain it, but sometimes dumbing

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Speaker 2: it down does explain it. On the one hand, when

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Speaker 2: we look at sentiment measures of the US population never

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Speaker 2: been more negative, worse than nine to eleven, worse than

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Speaker 2: the financial crisis, worse than the pandemic. People are super negative.

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Speaker 2: And yet at the same time we have record boat

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Speaker 2: sails pleasure craft. I don't mean like Carnival Corps line.

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Speaker 2: I mean twenty twenty five thirty forty foot boats. If

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Speaker 2: you're gonna go out and buy a boat, you're spending

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Speaker 2: a lot of money. The boat is the cheapest part

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Speaker 2: of boating, slip, the winter rising, the maintenance, They're just

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Speaker 2: boating is not a cheap hobby. I don't understand why

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Speaker 2: so many people are saying they're negative and yet so

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Speaker 2: many people are going out and buying boats. Or are

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Speaker 2: these just two different demographic cohorts.

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Speaker 1: So I think there are multiple demographic cohorts, and I

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Speaker 1: wouldn't discount that today.

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Speaker 2: I bet this is a big overlap though that's my sense.

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Speaker 2: When I see the like the Maga Armadas, everything is

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Speaker 2: terrible with the Maga signs on their boats. It can't

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Speaker 2: be that bad if you're in a forty foot yacht

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Speaker 2: on the lake.

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Speaker 1: Yeah, and gallup. And you know, the University of Michigan,

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Speaker 1: everybody's looked at the political impact on sentiment surveys.

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Speaker 2: A lot of it's just partisans. It's partisan.

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Speaker 1: And in fairness that this has been the case for

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Speaker 1: quite a while, I.

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Speaker 2: Mean, but it's gotten much much worse.

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Speaker 1: It's gotten far worse. You know, the last time the

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Speaker 1: parties felt the same was really the Great Financial Crisis.

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Speaker 1: Coming out of that, you saw recovery on the part

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Speaker 1: of Democrats, but no recovery whatsoever among Republicans.

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Speaker 2: Which in terms of sentiment, in terms of.

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Speaker 1: Sentiment, and so you know when people talk about, well,

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Speaker 1: where did Donald Trump come from? When you look at

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Speaker 1: consumer sentiment by political category, it becomes very evident what

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Speaker 1: was behind that. You know, eight years of of Republicans

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Speaker 1: feeling the same way they felt the weekend Lehman Brothers collapsed.

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Speaker 2: So let's talk about that for a second. Chris, I've

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Speaker 2: heard this and I just don't get it. When Lehman

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Speaker 2: collected and I'm not a believer that Lehman caused the

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Speaker 2: financial crisis, it was merely the first trailer in the

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Speaker 2: trailer park that the tornado took, but everybody had eaten

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Speaker 2: the same bad food at the buffet. To mix metaphors,

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Speaker 2: there were genuine moments of terror, Like I was in

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Speaker 2: New York City. People were very frightened. I remember the

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Speaker 2: head of my firm saying, you gotta stop spiking the

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Speaker 2: football because there's blood in the streets and everybody's really

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Speaker 2: not doing well. And that was a moment of like

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Speaker 2: just genuine financial panic, which by the way, kept going

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Speaker 2: for another six months until the market made their lows

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Speaker 2: in March of two thousand and nine. That was September

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Speaker 2: of two thousand and eight. And then you look around

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Speaker 2: today and listen, nobody is thrilled with the state of

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Speaker 2: Nobody likes either of the two leading candidates, Biden or Trump,

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Speaker 2: to record negatives. You have all sorts of problems in

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Speaker 2: the country, but can you really compare the state of

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Speaker 2: the economy and three point something percent unemployment to unemployment

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Speaker 2: over ten percent. People are concerned the ATM isn't going

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Speaker 2: to work. How is that comparable to what's going on today?

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Speaker 1: It isn't if you measure it in terms of economic conditions.

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Speaker 1: But confidence is about vulnerability, relative vulnerability, and I think

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Speaker 1: that there are a lot of Americans who feel especially vulnerable.

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Speaker 1: They feel culturally vulnerable, they feel religiously vulnerable, they feel

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Speaker 1: in terms of issues of gender, and so I think

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Speaker 1: that what a lot of our quote unquote economic confidence

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Speaker 1: indicators are picking up is vulnerability that is far more

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Speaker 1: fundamental to people's lives. And I think one of them

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Speaker 1: is stakes the economists have been making is they're attributing

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Speaker 1: too much of these indicators to economic connections rather than

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Speaker 1: to the social and political connections that we're seeing that

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Speaker 1: are quite profound.

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Speaker 2: So let's stay with that theme of political disenfranchisement and

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Speaker 2: fear and nervousness about changes in society. When I look

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Speaker 2: around at the sociological and demographic changes that have been

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Speaker 2: taking place recently, they're the end of product of trends

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Speaker 2: that have been around for decades. So the US has

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Speaker 2: becoming increasingly diverse. Right, you and I are a bunch of

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Speaker 2: old white males. We used to be the dominant majority.

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Speaker 2: Then now we're a plurality, and eventually we're going to

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Speaker 2: be a large minority. That trend has been in place

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Speaker 2: for decades. The country kind of swings back and forth

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Speaker 2: between the left and the right. I think what's happened

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Speaker 2: is the younger generations have always been more progressive, but

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Speaker 2: now the younger generations are you know, the sixties and seventies.

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Speaker 2: Generations from those decades are in their forties, fifties, sixties, seventies,

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Speaker 2: and very often are in charge of organizations. Isn't a

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Speaker 2: lot of what's going on just the culmination of things

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Speaker 2: that are a long time coming. And I'm not saying

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Speaker 2: people shouldn't be unaware of it. It just seems funny that,

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Speaker 2: you know, post pandemic. Okay, now it's here and we

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Speaker 2: all need to freak out.

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Speaker 1: Yeah. I look at the roots of this as having

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Speaker 1: been sown in a comparable tumultuous time in the late

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Speaker 1: nineteen sixties, early seventies.

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Speaker 2: Half a century ago.

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Speaker 1: Yeah, and so you had, I mean, think about the

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Speaker 1: concerns that folks had in the early nineteen sixties. You

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Speaker 1: have issue of civil rights, you have stonewall.

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Speaker 2: Gay rights, civil rights, women's rights rights straight down the list.

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Speaker 1: And so you have those who have felt vulnerable for

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Speaker 1: a prolonged period of time saying I've had enough.

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Speaker 2: But the groups that seem to be making and maybe

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Speaker 2: this is my So I'm college educated, I went to

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Speaker 2: grad school, I live in a major East Coast city.

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Speaker 2: I make a decent living. So I don't think of

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Speaker 2: myself as the typical middle American, and so I will

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Speaker 2: own up to Hey, that's my You know, I love

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Speaker 2: the Woody Allen line from Annie Hall elitist New York

413
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Speaker 2: Jewish socialist summer camp. Like that funny, funny line. But

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Speaker 2: I know I don't see the world like a middle American.

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Speaker 2: But that said, a lot of the folks who seem

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Speaker 2: most upset about what's going on, none of this is new.

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Speaker 2: If you're in West Virginia and used to work in

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Speaker 2: the coal mine, Hey, is it a surprise that coal

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Speaker 2: is going away? Am I Am? I to glib when

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Speaker 2: I say that, or.

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Speaker 1: Yes, I think you are. Because if I think about

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Speaker 1: those that are feeling vulnerable, they have clear senses of scarcity.

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Speaker 1: They have job scarcity, they have relative health scarcity, they

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Speaker 1: have mobility scarcity. I mean the abundance that those who

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Speaker 1: have gained over the past fifty years they now see

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Speaker 1: as having come at their expense. And this is something

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Speaker 1: that we see a lot. When confidence is low. We

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Speaker 1: acquire what I call zero some thinking where I now

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Speaker 1: attribute my misfortune to your gain. That's interesting that you

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Speaker 1: somehow benefited at my expense.

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Speaker 2: So we saw something very similar to this in the

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Speaker 2: eighties and nineties as a lot of manufacturing jobs when overseas,

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Speaker 2: and at the same time, the finance world, the banks,

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Speaker 2: the private equity, the venture firms that were essentially financing

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Speaker 2: these changes did exceedingly well. And so if you were

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Speaker 2: if you worked in a clothing factory or a furniture factory,

437
00:27:16,800 --> 00:27:21,960
Speaker 2: or even a steel or auto plant in the seventies, eighties, nineties,

438
00:27:22,760 --> 00:27:26,040
Speaker 2: a lot of those jobs were shipped to cheaper labor

439
00:27:26,080 --> 00:27:31,400
Speaker 2: overseas and entirely different group of people benefited. Is that

440
00:27:31,720 --> 00:27:36,880
Speaker 2: some of the underlying animis absolutely across political, although it's

441
00:27:36,880 --> 00:27:39,960
Speaker 2: hard to tell because a lot, very often it's almost

442
00:27:39,960 --> 00:27:43,800
Speaker 2: like Russian nesting dolls, that it's not a clear Venn

443
00:27:43,840 --> 00:27:47,840
Speaker 2: diagram of this blue circle and that yellow circle. There's

444
00:27:47,840 --> 00:27:49,520
Speaker 2: a lot of green overlap in the middle.

445
00:27:49,640 --> 00:27:53,080
Speaker 1: Yeah, And I say to my friends in politics that

446
00:27:53,119 --> 00:27:56,560
Speaker 1: the biggest divide is not left right, it's up down.

447
00:27:56,880 --> 00:28:01,040
Speaker 2: And I have said that for decades and felt like

448
00:28:01,080 --> 00:28:05,040
Speaker 2: I was a lonely voice it's not left versus right.

449
00:28:05,280 --> 00:28:08,840
Speaker 2: It's who owns the means of production and what your

450
00:28:08,960 --> 00:28:12,719
Speaker 2: role is. Are you a capitalist owner or are you

451
00:28:12,960 --> 00:28:16,399
Speaker 2: a wage slave? And not to again not to be

452
00:28:16,680 --> 00:28:20,560
Speaker 2: too glib, but that's what's determined the winners and losers

453
00:28:20,760 --> 00:28:21,720
Speaker 2: in our economy.

454
00:28:21,840 --> 00:28:25,719
Speaker 1: Yeah, and the pandemic only heightened that. You know you

455
00:28:25,800 --> 00:28:29,840
Speaker 1: mentioned you know, the case shaped recovery because that phrase

456
00:28:30,640 --> 00:28:33,480
Speaker 1: is a evolution of something that I started writing about

457
00:28:33,520 --> 00:28:36,400
Speaker 1: in March of twenty twenty, which was the work from

458
00:28:36,440 --> 00:28:41,479
Speaker 1: home confidence divide. Talk about an awkward mouthful, but you

459
00:28:41,520 --> 00:28:45,800
Speaker 1: could see even before the month was out. Did those

460
00:28:45,880 --> 00:28:49,640
Speaker 1: who could work in an office and migrate to home.

461
00:28:49,920 --> 00:28:52,320
Speaker 2: Meaning you had a computer at home, you had access

462
00:28:52,320 --> 00:28:54,920
Speaker 2: to high speed internet, and you had a space where

463
00:28:54,960 --> 00:28:58,120
Speaker 2: you could physically work. That's not everybody.

464
00:28:58,240 --> 00:29:02,640
Speaker 1: It's a very small populace. When you look at if.

465
00:29:02,480 --> 00:29:05,240
Speaker 2: You're if you're in a rural area that doesn't have broadbands,

466
00:29:05,560 --> 00:29:07,920
Speaker 2: if you're in an inner city where you might not

467
00:29:08,000 --> 00:29:11,440
Speaker 2: have forget internet, you might not have a computer. Big

468
00:29:11,480 --> 00:29:14,600
Speaker 2: swaths of the population did not have access to work

469
00:29:14,640 --> 00:29:15,040
Speaker 2: from home.

470
00:29:15,160 --> 00:29:19,560
Speaker 1: No, and we have a delivery system today that is

471
00:29:19,760 --> 00:29:25,000
Speaker 1: extraordinarily enabling of that from Amazon to instacart, those at

472
00:29:25,040 --> 00:29:29,720
Speaker 1: the top, the pandemic became an inconvenience. But let's talk

473
00:29:29,760 --> 00:29:33,360
Speaker 1: about those that were serving those at the top.

474
00:29:34,040 --> 00:29:40,600
Speaker 2: Meaning medical people, delivery people, restaurant workers, food supermarket staff, transportation,

475
00:29:41,280 --> 00:29:42,360
Speaker 2: food prep.

476
00:29:42,400 --> 00:29:45,320
Speaker 1: You know, all the factory you know, the chicken factories

477
00:29:45,320 --> 00:29:48,040
Speaker 1: in Delaware, they didn't close. And so it's to me,

478
00:29:48,080 --> 00:29:50,440
Speaker 1: it's not a surprise at all that where we're seeing

479
00:29:50,640 --> 00:29:55,320
Speaker 1: work stoppages and strikes and protesters are highly constituted in

480
00:29:55,400 --> 00:30:02,080
Speaker 1: people who felt intensely vulnerable during the pandemic and saw

481
00:30:02,560 --> 00:30:06,200
Speaker 1: the rest of the world living a life that was

482
00:30:06,400 --> 00:30:11,520
Speaker 1: unattainable to them. And so what concerns me, Barry, is

483
00:30:11,600 --> 00:30:17,280
Speaker 1: not the depth of consumer confidence falling, it's the duration

484
00:30:17,440 --> 00:30:20,800
Speaker 1: of it. You know, you can hold your breath underwater,

485
00:30:21,000 --> 00:30:23,000
Speaker 1: whether it's ten feet or one hundred feet, you know,

486
00:30:23,200 --> 00:30:27,240
Speaker 1: for a short period of time, but eventually you gotta breathe,

487
00:30:27,680 --> 00:30:31,720
Speaker 1: And so all of the focus and sentiment is missing

488
00:30:32,440 --> 00:30:36,280
Speaker 1: the compounding effect of duration. And I talk a lot

489
00:30:36,320 --> 00:30:41,480
Speaker 1: about this notion of stacked vulnerabilities, where it's not one

490
00:30:41,600 --> 00:30:45,640
Speaker 1: thing those at the bottom are struggling with, it's multiple things.

491
00:30:45,920 --> 00:30:48,640
Speaker 1: One on top of the next, on top of the next,

492
00:30:48,640 --> 00:30:51,600
Speaker 1: on top of the next. And so when you look

493
00:30:51,640 --> 00:30:55,400
Speaker 1: at the social movements like Black Lives Matters that occurred

494
00:30:55,640 --> 00:30:59,960
Speaker 1: when confidence was terribly low, you have this triggering event

495
00:31:01,240 --> 00:31:04,640
Speaker 1: on the surface was relatively minor. I mean, we'd seen

496
00:31:04,920 --> 00:31:08,480
Speaker 1: so many instances people being was but how many young

497
00:31:08,520 --> 00:31:10,960
Speaker 1: black men were murdered over by cops over the best.

498
00:31:11,200 --> 00:31:14,239
Speaker 2: The difference is everyone has iPhones now, and so there

499
00:31:14,280 --> 00:31:16,440
Speaker 2: was video of a lot of this, and everybody was

500
00:31:16,680 --> 00:31:21,640
Speaker 2: already feeling stacked vulnerabilities, one on top of the next.

501
00:31:21,680 --> 00:31:24,680
Speaker 2: So let me push back a little bit economically on this,

502
00:31:25,200 --> 00:31:27,920
Speaker 2: and I just want to take the other side of

503
00:31:27,920 --> 00:31:31,920
Speaker 2: the argument to flesh this out. So we have the

504
00:31:32,040 --> 00:31:35,959
Speaker 2: Great Financial Crisis, so eight o nine, and essentially the

505
00:31:36,000 --> 00:31:40,480
Speaker 2: banks were rescued, the average American not so much. Rates

506
00:31:40,480 --> 00:31:44,880
Speaker 2: were taken down to zero, and that helped anything priced

507
00:31:45,000 --> 00:31:49,680
Speaker 2: in dollars or credit. So owners of capital and owners

508
00:31:49,720 --> 00:31:53,520
Speaker 2: of stocks, bonds, in real estate they did great. The

509
00:31:53,640 --> 00:31:56,120
Speaker 2: average American not so much. And you could see that

510
00:31:56,160 --> 00:32:00,360
Speaker 2: in the data. Mediocre recovery from nine to let's call

511
00:32:00,400 --> 00:32:07,200
Speaker 2: it fourteen fifteen week GDP subpart job creation, little wage gains,

512
00:32:07,600 --> 00:32:11,640
Speaker 2: consumer spending was mediocre, and by the way, the bulk

513
00:32:11,840 --> 00:32:14,920
Speaker 2: of the government action was monetary. We're going to drive

514
00:32:15,000 --> 00:32:19,880
Speaker 2: rates low, fiscal stimulus really mild. Then comes the pandemic.

515
00:32:20,240 --> 00:32:23,120
Speaker 2: You have the biggest fiscal stimulus in US history, over

516
00:32:23,160 --> 00:32:26,920
Speaker 2: ten percent of GDP, bigger than on a relative basis

517
00:32:26,960 --> 00:32:29,719
Speaker 2: than the start of World War two, two point two

518
00:32:29,760 --> 00:32:33,000
Speaker 2: trillion under Trump, then another eight hundred billion under Trump,

519
00:32:33,000 --> 00:32:36,520
Speaker 2: then another nine hundred billion under Biden, and then all

520
00:32:36,640 --> 00:32:42,240
Speaker 2: the Biden programs, the semiconductors, the infrastructure, the Inflation Act.

521
00:32:42,480 --> 00:32:46,400
Speaker 2: So suddenly we go from all monetary, no fiscal, to

522
00:32:46,520 --> 00:32:50,240
Speaker 2: all fiscal and some monetary. And as it turns out,

523
00:32:50,280 --> 00:32:53,880
Speaker 2: the fiscal stimulus falls into the hands of the middle

524
00:32:53,880 --> 00:32:56,880
Speaker 2: class and the lower class. Their savings rates go up,

525
00:32:56,920 --> 00:33:00,880
Speaker 2: their spending goes up, inflation goes up. Aren't these two

526
00:33:01,160 --> 00:33:05,240
Speaker 2: very different sets of circumstances, the post financial crisis and

527
00:33:05,280 --> 00:33:09,000
Speaker 2: the post pandemic era. Isn't the middle and lower class

528
00:33:09,560 --> 00:33:14,600
Speaker 2: better off? I think unemployment during the lockdown peaked in

529
00:33:14,840 --> 00:33:18,440
Speaker 2: June of twenty one at one point six trillion dollars,

530
00:33:18,480 --> 00:33:22,120
Speaker 2: a crazy number, Whereas the average American had to fen

531
00:33:22,240 --> 00:33:26,040
Speaker 2: for themselves post financial crisis. Why are people more upset

532
00:33:26,200 --> 00:33:29,880
Speaker 2: now than they were? I mean, what was Occupy Wall Street?

533
00:33:29,920 --> 00:33:30,320
Speaker 1: What was that?

534
00:33:30,520 --> 00:33:33,120
Speaker 2: Six months a year and it was forgotten about?

535
00:33:33,520 --> 00:33:37,640
Speaker 1: Yeah, but again was it occurred at a major low

536
00:33:37,680 --> 00:33:43,680
Speaker 1: in confidence. Again, these spontaneous social movements are wonderful pinpoint

537
00:33:43,760 --> 00:33:47,960
Speaker 1: moments that highlight when consumer confidence is low.

538
00:33:48,120 --> 00:33:51,160
Speaker 2: So I'm focusing on the economics, but what you're really

539
00:33:51,200 --> 00:33:55,680
Speaker 2: saying is, despite the rescue plan, it hasn't really moved

540
00:33:55,720 --> 00:33:58,160
Speaker 2: the needle on the confidence level.

541
00:33:58,240 --> 00:34:01,760
Speaker 1: No, and part of that is to those at the bottom.

542
00:34:02,160 --> 00:34:08,439
Speaker 1: It was a necessary oxygen mask. But think about where

543
00:34:08,480 --> 00:34:12,160
Speaker 1: that money went. It went to rent, It went to car.

544
00:34:12,120 --> 00:34:17,120
Speaker 2: Payments, basic basic survival things, food, medicine, rent, But that

545
00:34:17,239 --> 00:34:18,480
Speaker 2: was it.

546
00:34:18,000 --> 00:34:21,080
Speaker 1: And it went through energy. It went through them. It

547
00:34:21,160 --> 00:34:26,880
Speaker 1: didn't stay with them. It allowed them to catch their breath.

548
00:34:27,280 --> 00:34:30,120
Speaker 2: Allowed them to survive, for everybody was out of a job,

549
00:34:30,600 --> 00:34:31,640
Speaker 2: but those.

550
00:34:31,440 --> 00:34:36,360
Speaker 1: At the bottom were under no illusion that it was temporary.

551
00:34:36,600 --> 00:34:38,920
Speaker 2: Yeah, No, that makes perfect sense. I want to get

552
00:34:38,920 --> 00:34:40,399
Speaker 2: to the book. But before I get to the book,

553
00:34:40,440 --> 00:34:45,399
Speaker 2: I got to ask a political question, which is what

554
00:34:45,560 --> 00:34:50,080
Speaker 2: was the impact of the January sixth attack on the

555
00:34:50,160 --> 00:34:55,560
Speaker 2: capital on the confidence of the nation because everybody kind

556
00:34:55,560 --> 00:34:59,480
Speaker 2: of forgets the first days after that, I think everybody

557
00:34:59,520 --> 00:35:02,720
Speaker 2: was really taken up, and then the story kind of changed.

558
00:35:03,280 --> 00:35:07,440
Speaker 1: I'd look at January sixth a little differently. January sixth

559
00:35:07,520 --> 00:35:13,320
Speaker 1: is what happens when a large group sees a sense

560
00:35:13,360 --> 00:35:19,480
Speaker 1: of powerlessness and uncertainty and feels defeated and needs to act.

561
00:35:19,680 --> 00:35:23,600
Speaker 2: Well, let's address that. Because a large group is defeated

562
00:35:23,760 --> 00:35:27,040
Speaker 2: every four years, and normally they go back to their

563
00:35:27,120 --> 00:35:30,520
Speaker 2: jobs and say we'll get them next time. This group

564
00:35:31,280 --> 00:35:34,600
Speaker 2: did not feel that way, and if you watch the video,

565
00:35:34,760 --> 00:35:38,560
Speaker 2: it's pretty clear they're hell bent on stopping the transition

566
00:35:39,040 --> 00:35:43,319
Speaker 2: transition of power. This was very unusual. So what led

567
00:35:43,360 --> 00:35:43,680
Speaker 2: to that.

568
00:35:44,080 --> 00:35:46,800
Speaker 1: Let's keep the politics out of it. I'm just looking

569
00:35:46,800 --> 00:35:50,359
Speaker 1: at sentiment. To me, no one should have been surprised

570
00:35:50,640 --> 00:35:55,520
Speaker 1: by what happened, really, yeah, and why because there are

571
00:35:55,760 --> 00:36:01,040
Speaker 1: five natural reactions that we have in those moments. Flight

572
00:36:01,440 --> 00:36:05,000
Speaker 1: and flight we're familiar with for sure, the other follow

573
00:36:05,320 --> 00:36:07,520
Speaker 1: and there was a lot of that going on, for sure,

574
00:36:08,000 --> 00:36:10,200
Speaker 1: Freeze and there was a little bit of that, and

575
00:36:10,200 --> 00:36:12,279
Speaker 1: then the last one, if you'll pardon my French is

576
00:36:12,320 --> 00:36:15,960
Speaker 1: the F word where we just say it and so

577
00:36:16,640 --> 00:36:21,279
Speaker 1: We should have been expecting all of that to manifest

578
00:36:21,360 --> 00:36:24,200
Speaker 1: in that moment. The groups had been primed for it.

579
00:36:24,640 --> 00:36:24,920
Speaker 2: Huh.

580
00:36:25,080 --> 00:36:27,360
Speaker 1: I mean you go back and look at the messaging.

581
00:36:27,840 --> 00:36:32,520
Speaker 2: The message boards were on fire. The FBI has subsequently revealed, Yeah, No,

582
00:36:33,160 --> 00:36:34,680
Speaker 2: there was a lot of chatter.

583
00:36:35,160 --> 00:36:40,440
Speaker 1: Stories, feelings, actions exist in equilibrium, Berry, and that was

584
00:36:40,920 --> 00:36:48,759
Speaker 1: absolutely a situation where the stories and feelings naturally manifested

585
00:36:48,760 --> 00:36:52,959
Speaker 1: in that behavior. I look at that moment not any

586
00:36:53,000 --> 00:36:56,800
Speaker 1: different than I look at other spontaneous social events, you know,

587
00:36:56,880 --> 00:36:59,879
Speaker 1: the Arab Spring. You know, this is what happens free

588
00:37:00,360 --> 00:37:06,799
Speaker 1: by something that's relatively insignificant in that and so your point,

589
00:37:06,840 --> 00:37:09,719
Speaker 1: then confidence fell. It depended on which side of the

590
00:37:09,719 --> 00:37:13,040
Speaker 1: political spectrum you were on, because at that moment you

591
00:37:13,200 --> 00:37:18,040
Speaker 1: had confidence among Republicans being impacted by the failed attempt.

592
00:37:18,320 --> 00:37:22,680
Speaker 1: At the same time you had Democrats feeling vulnerable because

593
00:37:22,719 --> 00:37:28,240
Speaker 1: of this underlying sense of threat. And so you saw

594
00:37:28,480 --> 00:37:31,440
Speaker 1: in the data. You know, January twenty twenty one is

595
00:37:31,480 --> 00:37:36,440
Speaker 1: not a pretty sentiment indicator of mood, just given.

596
00:37:36,320 --> 00:37:41,000
Speaker 2: What was happening, quite fascinating. So let's talk a little

597
00:37:41,040 --> 00:37:45,520
Speaker 2: bit about the confidence map. Essentially, your argument is a

598
00:37:45,640 --> 00:37:50,960
Speaker 2: hidden factor driving both human decision making and broad economic

599
00:37:51,000 --> 00:37:56,480
Speaker 2: decision making. Is confidence? That thesis seems like a big lift.

600
00:37:57,080 --> 00:37:57,680
Speaker 2: Explain it.

601
00:37:57,840 --> 00:38:00,440
Speaker 1: Yeah, it is a big lift. But I think first

602
00:38:00,480 --> 00:38:02,720
Speaker 1: of all, we have to come up with an accurate

603
00:38:02,840 --> 00:38:07,000
Speaker 1: definition of confidence, okay, because we end up getting caught

604
00:38:07,040 --> 00:38:09,040
Speaker 1: up in a lot of confidence theater, you know, the

605
00:38:09,040 --> 00:38:12,840
Speaker 1: appearance of you know, entertainers and sports figures, sort of

606
00:38:12,560 --> 00:38:17,520
Speaker 1: the bravado of culture, and we also mix it with

607
00:38:17,680 --> 00:38:21,160
Speaker 1: self esteem and self confidence. That's not what I'm talking about.

608
00:38:21,520 --> 00:38:24,800
Speaker 1: I'm talking about our feeling relationship with the world around

609
00:38:24,880 --> 00:38:26,160
Speaker 1: us and in.

610
00:38:26,080 --> 00:38:32,640
Speaker 2: The meaning how confident we are about our ability to survive, thrive,

611
00:38:32,760 --> 00:38:34,600
Speaker 2: et cetera in the world around us.

612
00:38:34,640 --> 00:38:38,839
Speaker 1: Yeah, to navigate what's ahead. So if we think about that,

613
00:38:38,920 --> 00:38:41,960
Speaker 1: then it becomes what does that really mean? And to

614
00:38:42,000 --> 00:38:45,120
Speaker 1: be successful in that, I need to feel that things

615
00:38:45,160 --> 00:38:48,600
Speaker 1: are predictable, that there is a sense of certainty to

616
00:38:48,760 --> 00:38:51,360
Speaker 1: what will happen next. And that could be because I

617
00:38:51,360 --> 00:38:54,520
Speaker 1: can extrapolate from the past, but I need to have

618
00:38:55,160 --> 00:38:57,160
Speaker 1: a vision of a clear road ahead of me.

619
00:38:57,320 --> 00:39:01,319
Speaker 2: Why is that so important? Because they think about through

620
00:39:01,360 --> 00:39:04,520
Speaker 2: most of human history everything has been uncertain. You know,

621
00:39:04,600 --> 00:39:08,239
Speaker 2: you didn't have local police or a military. You never

622
00:39:08,320 --> 00:39:10,399
Speaker 2: knew when the next tribe over was going to come

623
00:39:10,440 --> 00:39:13,040
Speaker 2: and take your food and your women and chop your

624
00:39:13,040 --> 00:39:16,200
Speaker 2: head off and go on with their lives. Why is

625
00:39:16,360 --> 00:39:18,680
Speaker 2: certainty so important.

626
00:39:18,080 --> 00:39:22,840
Speaker 1: Because we abhor randomness. To not have a sense of

627
00:39:22,880 --> 00:39:26,840
Speaker 1: predictability means that everything is potentially random, which means that

628
00:39:26,880 --> 00:39:29,200
Speaker 1: I have to be on alert and that's.

629
00:39:29,080 --> 00:39:33,239
Speaker 2: Exhausting, stressful, tiring. Just yeah, I could see that.

630
00:39:33,360 --> 00:39:38,160
Speaker 1: Yeah, So you're having to just survey the landscape all

631
00:39:38,280 --> 00:39:41,640
Speaker 1: the time. And you know, COVID is a great example

632
00:39:41,680 --> 00:39:46,600
Speaker 1: where the visibility that people had was negligible, and so

633
00:39:47,560 --> 00:39:50,640
Speaker 1: knowing what's coming next, or at least thinking we do,

634
00:39:51,600 --> 00:39:55,400
Speaker 1: is vital. The second piece of that is a sense

635
00:39:55,440 --> 00:39:59,920
Speaker 1: of control that I have the skills, the resources, the prepper,

636
00:40:00,400 --> 00:40:04,800
Speaker 1: the training, whatever I need to be able to succeed.

637
00:40:04,880 --> 00:40:07,160
Speaker 1: So having a clear road is great if I'm behind

638
00:40:07,160 --> 00:40:10,880
Speaker 1: the wheel, but knowing how to drive is as important. Sure,

639
00:40:11,480 --> 00:40:16,040
Speaker 1: And so the only way we're confident is when those

640
00:40:16,160 --> 00:40:20,040
Speaker 1: two feelings coincide. When I feel that I know it's

641
00:40:20,080 --> 00:40:24,239
Speaker 1: coming and I've got it. Those feelings are what give

642
00:40:24,400 --> 00:40:26,080
Speaker 1: me a sense of confidence.

643
00:40:26,360 --> 00:40:30,759
Speaker 2: So I'm not necessarily disagreeing with you, but I want

644
00:40:30,760 --> 00:40:36,160
Speaker 2: to point out maybe the exceptions. In my world, people

645
00:40:36,280 --> 00:40:41,040
Speaker 2: are confident about things they shouldn't be. They see certitude

646
00:40:41,120 --> 00:40:45,000
Speaker 2: in things that are random. They claim to understand what's

647
00:40:45,000 --> 00:40:48,640
Speaker 2: coming next, when reality is they have with the slightest idea,

648
00:40:48,920 --> 00:40:54,600
Speaker 2: how do you transfer studying societal confidence to a field

649
00:40:54,680 --> 00:40:59,920
Speaker 2: like investing When my definition is investing as a probabilest

650
00:41:00,680 --> 00:41:07,200
Speaker 2: exercise using unreliable information about an inherently unknowable future, meaning

651
00:41:07,360 --> 00:41:13,719
Speaker 2: wherever you look there's no certitude, lack of predictability. How

652
00:41:13,760 --> 00:41:16,440
Speaker 2: do you apply confidence to the world of investing.

653
00:41:16,520 --> 00:41:18,480
Speaker 1: Yeah, so I teach a class in financial economics at

654
00:41:18,480 --> 00:41:21,399
Speaker 1: William and Mary. In the first day of class, what

655
00:41:21,480 --> 00:41:24,200
Speaker 1: is it about finance that makes its difference? It's, you know,

656
00:41:24,400 --> 00:41:28,520
Speaker 1: it's decision making where the outcome is to be determined.

657
00:41:28,960 --> 00:41:33,719
Speaker 1: So whether I'm lending, borrowing, investing, and so anytime I'm

658
00:41:33,760 --> 00:41:38,560
Speaker 1: doing that, I am deluding myself if I do feel confident,

659
00:41:38,680 --> 00:41:42,960
Speaker 1: because all investment decisions are made in an environment where

660
00:41:43,000 --> 00:41:45,360
Speaker 1: I have control but no certainty. In my book, I

661
00:41:45,400 --> 00:41:46,359
Speaker 1: call that the launch pad.

662
00:41:46,520 --> 00:41:49,120
Speaker 2: It's control but no certainty.

663
00:41:49,239 --> 00:41:53,000
Speaker 1: Okay, And so if I'm talking to a group of investors,

664
00:41:53,480 --> 00:41:57,719
Speaker 1: I'm challenging them with their belief that they should be

665
00:41:57,800 --> 00:42:00,680
Speaker 1: confident in the first place. So, what's the story you're

666
00:42:00,719 --> 00:42:04,359
Speaker 1: telling yourself, Barry. If you're buying something, well, now you're

667
00:42:04,400 --> 00:42:07,799
Speaker 1: imagining the future. Now you're creating this vivid picture of

668
00:42:08,040 --> 00:42:11,600
Speaker 1: what the future looks like, and to the extent that

669
00:42:11,640 --> 00:42:16,240
Speaker 1: you're really certain. What's that's saying to me is you're

670
00:42:16,680 --> 00:42:20,440
Speaker 1: risking being delusional, both if you're certain it's going to

671
00:42:20,440 --> 00:42:23,040
Speaker 1: be unicorns and rainbows or if it's going to be

672
00:42:23,120 --> 00:42:27,520
Speaker 1: the depths of hell. So when you're making an investment decision,

673
00:42:28,080 --> 00:42:31,480
Speaker 1: it's okay to plan for the future that you imagine,

674
00:42:31,800 --> 00:42:34,080
Speaker 1: but you need to be prepared for the future that

675
00:42:34,120 --> 00:42:37,799
Speaker 1: you can't imagine, but to appreciate that you're making a

676
00:42:37,840 --> 00:42:42,279
Speaker 1: decision in an environment that is not confidence.

677
00:42:42,719 --> 00:42:45,600
Speaker 2: So I don't disagree with any of the things you're saying.

678
00:42:46,080 --> 00:42:51,080
Speaker 2: How can we use the general lack of certainty? How

679
00:42:51,120 --> 00:42:54,320
Speaker 2: can we evaluate what at least what people say about

680
00:42:54,640 --> 00:42:59,279
Speaker 2: their confidence level, their certitude to help us make investment decisions.

681
00:42:59,360 --> 00:43:03,640
Speaker 1: Yeah, the more certain the crowd, the less likely the outcome.

682
00:43:03,960 --> 00:43:08,440
Speaker 1: If I look at extremes in sentiment, there is not

683
00:43:08,480 --> 00:43:14,400
Speaker 1: only a certainty of what's coming, the expectation is prolonged.

684
00:43:15,080 --> 00:43:19,480
Speaker 1: It's powerful, it's unstoppable. You know, the word unstoppable is

685
00:43:19,560 --> 00:43:22,239
Speaker 1: one that always catches my breath. You know when when

686
00:43:22,280 --> 00:43:25,880
Speaker 1: Time magazine put unstopped, you know, can Hillary Clinton be stopped?

687
00:43:25,960 --> 00:43:28,359
Speaker 1: It was like, no, She's done. So I appreciate that

688
00:43:28,400 --> 00:43:32,080
Speaker 1: these these narratives, there's force to them. There's a real

689
00:43:32,239 --> 00:43:37,360
Speaker 1: strong energy to the narratives that is mirrored in decision

690
00:43:37,400 --> 00:43:43,200
Speaker 1: making and action. That reflects this unbridled disregard for any

691
00:43:43,320 --> 00:43:47,400
Speaker 1: kind of risk management because I know what's coming. That

692
00:43:47,840 --> 00:43:51,279
Speaker 1: the headlines around SPACs in early twenty twenty one were

693
00:43:51,400 --> 00:43:56,680
Speaker 1: extraordinary in terms of this cornucopia of clear certainty of

694
00:43:56,719 --> 00:43:57,520
Speaker 1: what was ahead.

695
00:43:57,640 --> 00:44:02,000
Speaker 2: That's pretty fair. In fact, the there's rarely consensus in

696
00:44:02,040 --> 00:44:05,520
Speaker 2: the marketplace, but when there is, I always like to

697
00:44:05,560 --> 00:44:09,560
Speaker 2: point out it's right before a major reversal. So early

698
00:44:09,600 --> 00:44:12,520
Speaker 2: two thousand, hey, it was pretty clear that trees grow

699
00:44:12,640 --> 00:44:15,680
Speaker 2: to the sky, go to March oh nine, it's clear

700
00:44:15,719 --> 00:44:18,640
Speaker 2: the market's going to zero, right, who's ever going to

701
00:44:18,719 --> 00:44:21,680
Speaker 2: be on the other side of your trade? The consensus

702
00:44:21,880 --> 00:44:25,440
Speaker 2: when everybody agrees is okay, who's left to sell at

703
00:44:25,440 --> 00:44:26,160
Speaker 2: that point, right.

704
00:44:26,360 --> 00:44:28,680
Speaker 1: And there's another angle to it, which is you're an

705
00:44:28,680 --> 00:44:29,880
Speaker 1: idiot if you don't agree.

706
00:44:30,040 --> 00:44:32,560
Speaker 2: That comes a little earlier though, but there's like, think

707
00:44:32,600 --> 00:44:37,200
Speaker 2: about the fomo trade in crypto that have fun being

708
00:44:37,280 --> 00:44:40,920
Speaker 2: poor whoor yeah, right, that was forty fifty not quite

709
00:44:40,960 --> 00:44:43,960
Speaker 2: sixty thousand, but it was close. It was on the

710
00:44:44,000 --> 00:44:44,319
Speaker 2: way up.

711
00:44:44,680 --> 00:44:49,759
Speaker 1: And so you see these same behavioral trades, same narratives,

712
00:44:50,080 --> 00:44:53,719
Speaker 1: over and over and over, and in my book, what

713
00:44:53,920 --> 00:44:56,120
Speaker 1: makes them so wonderful is I can put a pin

714
00:44:56,160 --> 00:45:00,360
Speaker 1: in it. I can identify, oh, we're around here, just

715
00:45:00,480 --> 00:45:02,040
Speaker 1: based on the stories the actions.

716
00:45:02,440 --> 00:45:06,360
Speaker 2: So let's talk about something you mentioned, the COVID pandemic.

717
00:45:07,280 --> 00:45:11,040
Speaker 2: In the book. You have like a six year chart

718
00:45:11,719 --> 00:45:16,319
Speaker 2: of the corporate mentions of the word unprecedented, and essentially

719
00:45:16,920 --> 00:45:20,160
Speaker 2: it's the bottom of the chart. It's just scooping along

720
00:45:20,200 --> 00:45:22,640
Speaker 2: the bottom for years, and then by the time you

721
00:45:22,680 --> 00:45:26,480
Speaker 2: get to June July of twenty twenty, it spikes and

722
00:45:26,600 --> 00:45:29,000
Speaker 2: stays up for the better part of the next year

723
00:45:29,120 --> 00:45:33,920
Speaker 2: or so. And ironically, as COVID nineteen might have been

724
00:45:34,000 --> 00:45:37,960
Speaker 2: unprecedented in the modern era, a century earlier we had

725
00:45:38,000 --> 00:45:43,879
Speaker 2: a national influenza pandemic a respiratory illness COVID wasn't as

726
00:45:44,000 --> 00:45:45,480
Speaker 2: unprecedented as people thought.

727
00:45:45,800 --> 00:45:50,320
Speaker 1: No, and there's nothing unprecedented about the nature of our response,

728
00:45:50,760 --> 00:45:53,960
Speaker 1: the nature of our stories, the nature of our feelings.

729
00:45:54,520 --> 00:46:00,560
Speaker 1: It was history rhyming in so many ways. Beauty of

730
00:46:00,600 --> 00:46:05,680
Speaker 1: the word unprecedented is it became shorthand for almost whatever

731
00:46:05,719 --> 00:46:09,319
Speaker 1: we wanted it to mean. For executives, it became this

732
00:46:09,960 --> 00:46:13,120
Speaker 1: universal get out of jail free cart because.

733
00:46:12,800 --> 00:46:16,920
Speaker 2: Our earnings and revenues stink because of this unprecedented.

734
00:46:16,520 --> 00:46:19,359
Speaker 1: How could I have been expected to be prepared for this?

735
00:46:20,560 --> 00:46:22,880
Speaker 1: And we see this over and over and over, and

736
00:46:22,960 --> 00:46:25,440
Speaker 1: a few pages later I put up the chart that

737
00:46:25,560 --> 00:46:29,400
Speaker 1: shows the same terminology was used during two thousand and

738
00:46:29,440 --> 00:46:33,080
Speaker 1: eight during the financial crisis. Suddenly you know, once again,

739
00:46:33,160 --> 00:46:39,759
Speaker 1: we have this unprecedented catastrophe, and we accept that because

740
00:46:40,160 --> 00:46:44,160
Speaker 1: it mirrors the way we feel. At the same time.

741
00:46:44,320 --> 00:46:48,920
Speaker 2: Ray Dalio has this wonderful definition of unprecedented. He says,

742
00:46:49,000 --> 00:46:54,040
Speaker 2: unprecedented means you're too young to have remembered. It hasn't

743
00:46:54,040 --> 00:46:56,400
Speaker 2: happened in your lifetime, but if you look at history,

744
00:46:56,960 --> 00:47:00,759
Speaker 2: it certainly has happened before. Nothing is under the.

745
00:47:00,680 --> 00:47:05,240
Speaker 1: Sign No, the means at which we express our level

746
00:47:05,280 --> 00:47:10,839
Speaker 1: of vulnerability or euphoria may change, but the actions and

747
00:47:10,880 --> 00:47:15,040
Speaker 1: the underlying nature of the behaviors, the preferences are all

748
00:47:15,040 --> 00:47:15,399
Speaker 1: the same.

749
00:47:17,000 --> 00:47:21,360
Speaker 2: Quite amazing. So let's talk a little bit about launch pad.

750
00:47:21,640 --> 00:47:26,440
Speaker 2: You mentioned the launch pad environment. Explain what that means.

751
00:47:26,600 --> 00:47:28,880
Speaker 1: Yeah, So there are four environments that I highlight in

752
00:47:28,920 --> 00:47:33,240
Speaker 1: my book that relate to our mix of certainty and control.

753
00:47:33,719 --> 00:47:35,799
Speaker 1: The comfort zone where we have both of them, the

754
00:47:35,840 --> 00:47:37,640
Speaker 1: stress center where we have neither of them.

755
00:47:37,880 --> 00:47:41,239
Speaker 2: And when you say certainty in control ones, the X

756
00:47:41,280 --> 00:47:44,640
Speaker 2: axis ones of ys that you have four quadrants of

757
00:47:44,800 --> 00:47:48,560
Speaker 2: either high certainty and high control, low certainty and low control,

758
00:47:48,680 --> 00:47:50,200
Speaker 2: and then one or the other.

759
00:47:50,320 --> 00:47:52,960
Speaker 1: And so most people when they think about confidence, think

760
00:47:52,960 --> 00:47:53,880
Speaker 1: about those two.

761
00:47:53,719 --> 00:47:56,320
Speaker 2: Boxes high certainty, high control.

762
00:47:56,000 --> 00:47:58,520
Speaker 1: And low certainty low control. It's like a buy one,

763
00:47:58,520 --> 00:48:02,400
Speaker 1: get one free. But the reality is that our lives

764
00:48:02,560 --> 00:48:05,239
Speaker 1: give us moments where we have one but not the other.

765
00:48:05,920 --> 00:48:09,360
Speaker 1: If you've taught your kids to drive, that's an environment

766
00:48:09,400 --> 00:48:12,520
Speaker 1: where you have certainty but no control, and then suddenly

767
00:48:12,960 --> 00:48:15,320
Speaker 1: it can go from feeling really good in the passenger

768
00:48:15,400 --> 00:48:18,640
Speaker 1: seat to feeling terrifying. It's the same thing on an airplane,

769
00:48:18,760 --> 00:48:21,200
Speaker 1: I call it the passenger's seat. For that reason, the

770
00:48:21,280 --> 00:48:24,160
Speaker 1: launch pad is an environment where we have control but

771
00:48:24,280 --> 00:48:27,120
Speaker 1: no certainty. You could think about this as a rock

772
00:48:27,160 --> 00:48:31,279
Speaker 1: climber rising up a cliff side, and so that the

773
00:48:31,360 --> 00:48:34,040
Speaker 1: issue is do I plummet to my death back into

774
00:48:34,080 --> 00:48:36,560
Speaker 1: the stress center, or do I safely navigate it into

775
00:48:36,600 --> 00:48:39,680
Speaker 1: the comfort zone. It's the classic hero's journey is comfort zone,

776
00:48:39,719 --> 00:48:45,520
Speaker 1: stress centers, launchpad back into the comfort zone. The launch

777
00:48:45,560 --> 00:48:49,800
Speaker 1: pad is important because a lot of our decision making

778
00:48:49,920 --> 00:48:53,359
Speaker 1: is there anytime we set off on a journey, anytime

779
00:48:53,480 --> 00:48:59,480
Speaker 1: we're investing, we're making choices without knowing what's ahead, and

780
00:49:00,560 --> 00:49:05,440
Speaker 1: organizations go back and forth between liking those environments and not.

781
00:49:06,000 --> 00:49:08,560
Speaker 1: Entrepreneurs love that environment, you know, give them a steering

782
00:49:08,600 --> 00:49:12,040
Speaker 1: wheel and they'll put the car in forward, reverse, you know,

783
00:49:12,200 --> 00:49:14,800
Speaker 1: whatever it takes. They love that area.

784
00:49:15,120 --> 00:49:18,480
Speaker 2: So let's take this to the ten thousand foot view.

785
00:49:18,760 --> 00:49:22,480
Speaker 2: Can we look at historic economic cycles and see how

786
00:49:22,640 --> 00:49:25,640
Speaker 2: confidence waxes and wanes, and can we use that to

787
00:49:25,719 --> 00:49:29,440
Speaker 2: extrapolate forward from where we are currently.

788
00:49:29,760 --> 00:49:31,920
Speaker 1: Yeah, So I think of us as going on this

789
00:49:32,120 --> 00:49:36,240
Speaker 1: trolley car ride from the peak of the upright corner

790
00:49:36,280 --> 00:49:38,680
Speaker 1: of the comfort zone to the bottom of the lower

791
00:49:38,760 --> 00:49:41,800
Speaker 1: left side of the of the stress center, and that

792
00:49:41,920 --> 00:49:45,400
Speaker 1: we just go back and forth. In terms of economists

793
00:49:45,440 --> 00:49:47,440
Speaker 1: think of that as cycles. I think of it in

794
00:49:47,440 --> 00:49:48,000
Speaker 1: this sort.

795
00:49:47,800 --> 00:49:49,600
Speaker 2: Of well moving it's a sign wave.

796
00:49:49,640 --> 00:49:51,719
Speaker 1: And if it's the quatran, you're back and forth, just

797
00:49:51,800 --> 00:49:55,399
Speaker 1: back and forth, and you can see it. And one

798
00:49:55,440 --> 00:49:58,319
Speaker 1: of the easiest ways to see it Berrier is in

799
00:49:58,320 --> 00:50:00,680
Speaker 1: our preferences, because.

800
00:50:01,280 --> 00:50:02,600
Speaker 2: What sort of preferences give us.

801
00:50:02,680 --> 00:50:07,839
Speaker 1: Example, so what we want when confidence is low is

802
00:50:08,000 --> 00:50:11,200
Speaker 1: all about me here now. So if there's a problem,

803
00:50:11,280 --> 00:50:14,000
Speaker 1: if I'm feeling vulnerable, there's a bear outside my tent,

804
00:50:14,719 --> 00:50:19,080
Speaker 1: the only thing that now matters is me in this moment,

805
00:50:19,440 --> 00:50:23,880
Speaker 1: right here, and that has a big bearing on the

806
00:50:23,960 --> 00:50:24,839
Speaker 1: choices that I make.

807
00:50:25,080 --> 00:50:29,680
Speaker 2: I'm not so personal, local and present.

808
00:50:29,480 --> 00:50:33,080
Speaker 1: And present right now. So my decision making is impulsive,

809
00:50:33,440 --> 00:50:38,400
Speaker 1: maybe tactical, but it's sure not strategic. It's reactive. It

810
00:50:38,680 --> 00:50:42,440
Speaker 1: is focused on what's good for me, and if it's

811
00:50:42,520 --> 00:50:45,400
Speaker 1: bad for you, too bad. If it's bad for tomorrow,

812
00:50:45,640 --> 00:50:46,120
Speaker 1: too bad.

813
00:50:46,320 --> 00:50:47,799
Speaker 2: I'm right now, I'm dealing with a bet.

814
00:50:48,200 --> 00:50:49,719
Speaker 1: I'm dealing with what I got.

815
00:50:49,800 --> 00:50:51,799
Speaker 2: But whether it's a real bear or a market bear,

816
00:50:51,840 --> 00:50:52,479
Speaker 2: it doesn't matter.

817
00:50:52,560 --> 00:50:56,239
Speaker 1: It doesn't matter, right. So, and there's another element to it,

818
00:50:56,280 --> 00:51:00,120
Speaker 1: which is I need things to be concrete. That that

819
00:51:00,200 --> 00:51:03,839
Speaker 1: psychologists use the term hypotheticality. I hate that word. But

820
00:51:04,320 --> 00:51:08,240
Speaker 1: everything I want when confidence is low has to be

821
00:51:08,760 --> 00:51:13,120
Speaker 1: really concrete. It's why we it's why we hoard physical cash.

822
00:51:13,239 --> 00:51:16,680
Speaker 1: We get the water from Costco. We know, we.

823
00:51:16,640 --> 00:51:22,760
Speaker 2: Want talking maslow hierarchy of needs like food, shelter, you know, uh, heat, energy,

824
00:51:23,320 --> 00:51:24,520
Speaker 2: just real basics stuff.

825
00:51:24,600 --> 00:51:27,520
Speaker 1: And it's here that the cash in the bank isn't

826
00:51:27,560 --> 00:51:29,640
Speaker 1: close enough. So to your point, you know, why are

827
00:51:29,640 --> 00:51:32,200
Speaker 1: you going to the atm on that day Lehman collapse

828
00:51:32,280 --> 00:51:34,759
Speaker 1: because the bank that was around the corner is too

829
00:51:34,760 --> 00:51:37,520
Speaker 1: far away from you. I want the cash in the mattress.

830
00:51:37,520 --> 00:51:38,520
Speaker 1: In fact, during that Greek.

831
00:51:38,400 --> 00:51:40,160
Speaker 2: And who knows if the bank is even gonna work.

832
00:51:40,040 --> 00:51:41,600
Speaker 1: On Yeah, I mean in the Greek crisis, they were

833
00:51:41,640 --> 00:51:44,280
Speaker 1: selling mattresses with pre installed safety.

834
00:51:44,360 --> 00:51:47,680
Speaker 2: Come on, no really, but but.

835
00:51:47,360 --> 00:51:51,480
Speaker 1: But so let's think about our preferences today. We have

836
00:51:51,600 --> 00:51:57,160
Speaker 1: a whole industry geared towards me here now, preferences, Netflix,

837
00:51:57,560 --> 00:52:03,160
Speaker 1: cuic all of the I phone, iPod you know, everything

838
00:52:03,239 --> 00:52:07,400
Speaker 1: is geared to deliver what I want when I want now.

839
00:52:07,840 --> 00:52:10,600
Speaker 2: I can't wait for instant gratification. I need it sooner,

840
00:52:10,760 --> 00:52:14,840
Speaker 2: right and so Amazon New York City same hour delivery.

841
00:52:15,400 --> 00:52:18,439
Speaker 1: Twitter is another, I mean, talk about me here now,

842
00:52:18,520 --> 00:52:21,320
Speaker 1: manifestations of decision making.

843
00:52:21,800 --> 00:52:24,719
Speaker 2: It's called X now excuse me, but it's the same thing.

844
00:52:24,800 --> 00:52:27,560
Speaker 2: It's that instant dopamine hit. I want it right now,

845
00:52:27,600 --> 00:52:28,120
Speaker 2: I want.

846
00:52:27,920 --> 00:52:28,400
Speaker 1: It right now.

847
00:52:28,760 --> 00:52:28,920
Speaker 2: Huh.

848
00:52:29,080 --> 00:52:33,680
Speaker 1: And so we're You know, if I look at our culture,

849
00:52:34,440 --> 00:52:38,600
Speaker 1: it's incredibly me here now environment. And if I look

850
00:52:38,600 --> 00:52:42,920
Speaker 1: at its impact take pre and post pandemic. We go

851
00:52:43,040 --> 00:52:46,600
Speaker 1: from just in time supply chain delivery to just in

852
00:52:46,640 --> 00:52:52,840
Speaker 1: case to nearshoring. So suddenly I want my warehouses, my manufacturing.

853
00:52:53,400 --> 00:52:55,560
Speaker 1: You know, you look at Europe. You know, during the

854
00:52:55,680 --> 00:53:00,760
Speaker 1: energy crisis last summer, suddenly national energy po es, national

855
00:53:00,800 --> 00:53:06,200
Speaker 1: manufacturing policies, national security policies, that the the our willingness

856
00:53:06,239 --> 00:53:11,200
Speaker 1: to rely on complex global systems evaporates. In a crisis.

857
00:53:11,520 --> 00:53:15,520
Speaker 1: We want to be sure that what we need is

858
00:53:15,560 --> 00:53:17,719
Speaker 1: available within arm's length.

859
00:53:18,280 --> 00:53:22,760
Speaker 2: How much of this is just generals fighting the last war? Listen,

860
00:53:22,960 --> 00:53:27,080
Speaker 2: just in time inventory clearly proved itself to be problematic,

861
00:53:27,520 --> 00:53:30,200
Speaker 2: and near shoring or even building plants here in the

862
00:53:30,280 --> 00:53:33,800
Speaker 2: US is a solution to that. But it always feels

863
00:53:33,840 --> 00:53:36,719
Speaker 2: like anybody who looked at this issue knew this was

864
00:53:36,760 --> 00:53:40,720
Speaker 2: a problem. Nobody believed it until after a crisis.

865
00:53:40,520 --> 00:53:43,640
Speaker 1: Right, And that's that's always the nature of it. So

866
00:53:43,640 --> 00:53:50,320
Speaker 1: so we build bigger, wider, further distributing, you know that

867
00:53:50,480 --> 00:53:53,920
Speaker 1: the change we create this complexity. We saw this in

868
00:53:53,960 --> 00:53:58,800
Speaker 1: the in the mortgage world, where you know, we wertgage going.

869
00:53:58,600 --> 00:54:01,000
Speaker 2: From here to there, video square and on and on.

870
00:54:01,360 --> 00:54:05,320
Speaker 1: And at the same time it's it's like a Jenga tower.

871
00:54:05,640 --> 00:54:08,480
Speaker 1: Whereas we're building it taller and taller, we're also taking

872
00:54:08,520 --> 00:54:11,880
Speaker 1: pieces out because we think we can create even greater

873
00:54:11,960 --> 00:54:16,600
Speaker 1: and greater efficiency. And I joke a lot that our

874
00:54:16,719 --> 00:54:21,560
Speaker 1: level of scrutiny and our confidence levels are inversely related.

875
00:54:21,760 --> 00:54:25,759
Speaker 1: The more confident I am, the less I have to focus,

876
00:54:25,960 --> 00:54:27,520
Speaker 1: so the less I do focus.

877
00:54:27,719 --> 00:54:32,840
Speaker 2: So let's address me here. Now, what's the opposite of

878
00:54:32,880 --> 00:54:36,400
Speaker 2: that is that we there later.

879
00:54:36,239 --> 00:54:39,040
Speaker 1: What I say, us everywhere forever.

880
00:54:39,200 --> 00:54:44,640
Speaker 2: Us everywhere forever. So when does confidence signal us everywhere?

881
00:54:44,680 --> 00:54:48,759
Speaker 2: For was that a late two thousands then? Because confidence

882
00:54:48,840 --> 00:54:52,919
Speaker 2: was so so in the late two twenty twenties also.

883
00:54:53,320 --> 00:54:57,279
Speaker 1: So a lot of futuristic investing, and I would say

884
00:54:57,400 --> 00:55:01,240
Speaker 1: early twenty twenty one we saw a one wonderful bubble

885
00:55:01,280 --> 00:55:05,480
Speaker 1: of it in terms of EVS and space and SPAX.

886
00:55:05,040 --> 00:55:09,280
Speaker 2: And what about today with AI and large language models?

887
00:55:09,600 --> 00:55:12,440
Speaker 2: Is that a very long distance confidence sort of thing.

888
00:55:12,480 --> 00:55:12,920
Speaker 2: It is.

889
00:55:12,960 --> 00:55:15,760
Speaker 1: But what's so interesting to me, Berry is our picks

890
00:55:15,920 --> 00:55:20,440
Speaker 1: of the companies that we're interested in. So in twenty

891
00:55:20,520 --> 00:55:26,000
Speaker 1: twenty one, are intrigued with futuristic technology led us to

892
00:55:26,080 --> 00:55:29,680
Speaker 1: buy startups, you know, companies that didn't even exist at

893
00:55:29,680 --> 00:55:34,600
Speaker 1: that point. Today we're buying shares of Amazon and Google and.

894
00:55:34,600 --> 00:55:37,400
Speaker 2: Apple, that the thorough magnificent seven.

895
00:55:38,239 --> 00:55:42,000
Speaker 1: And to me, that's a real telling indicator that we're

896
00:55:42,120 --> 00:55:45,760
Speaker 1: not as confident today as we were, because.

897
00:55:45,560 --> 00:55:49,560
Speaker 2: It's very interesting. In other words, the focusing on the biggest, best,

898
00:55:49,920 --> 00:55:53,680
Speaker 2: most well established companies is a sign of a lack

899
00:55:53,719 --> 00:55:57,680
Speaker 2: of self confidence, whereas the remaining four hundred and ninety

900
00:55:57,680 --> 00:56:00,920
Speaker 2: three companies in the S and P five hundred we're ignoring.

901
00:56:01,440 --> 00:56:05,200
Speaker 2: And that's a sign of that, that lack of future expectation.

902
00:56:05,320 --> 00:56:08,920
Speaker 1: Yes, I mean, you look at the gap between you know,

903
00:56:08,960 --> 00:56:10,480
Speaker 1: the small cap index and the.

904
00:56:10,760 --> 00:56:13,280
Speaker 2: Megans large as it's ever ever been, and that.

905
00:56:13,040 --> 00:56:18,160
Speaker 1: That is us our natural preference for, you know, certainty

906
00:56:18,680 --> 00:56:22,680
Speaker 1: in cash flow and earnings, and you know, we know

907
00:56:22,800 --> 00:56:26,920
Speaker 1: those brands and those products, and so that's fascinating.

908
00:56:27,040 --> 00:56:31,640
Speaker 2: So I had recalled during the pandemic lockdown the first

909
00:56:31,640 --> 00:56:34,560
Speaker 2: few months, I went back and looked at some history,

910
00:56:34,880 --> 00:56:38,919
Speaker 2: because when you see the pandemic and the thirty four

911
00:56:38,960 --> 00:56:42,239
Speaker 2: percent market drop, you know, you go back and look

912
00:56:42,280 --> 00:56:48,320
Speaker 2: at history for non market related, non economic issues, terrorist

913
00:56:48,320 --> 00:56:54,240
Speaker 2: attacks and wars and presidential assassinations and you know, tsunamis

914
00:56:54,280 --> 00:56:58,600
Speaker 2: and just something that comes from outside the financial system.

915
00:56:58,880 --> 00:57:02,360
Speaker 2: You know, I jokingly said, the asteroid that destroyed the

916
00:57:02,440 --> 00:57:06,880
Speaker 2: dinosaurs had the same impact. Historically, you could look at

917
00:57:06,920 --> 00:57:10,520
Speaker 2: about a four dozen of these. What happens is markets

918
00:57:10,560 --> 00:57:14,000
Speaker 2: wobble and then they continue doing what they were doing before.

919
00:57:14,320 --> 00:57:18,120
Speaker 2: So when nine to eleven happened, markets were falling beforehand,

920
00:57:18,400 --> 00:57:21,120
Speaker 2: they wobble and then they continued to fall. When the

921
00:57:21,160 --> 00:57:25,680
Speaker 2: pandemic happened, markets were rising, they wobbled, and then they

922
00:57:26,200 --> 00:57:30,920
Speaker 2: really recovered very rapidly. So I wrote a column for

923
00:57:30,960 --> 00:57:35,760
Speaker 2: Bloomberg that unfortunately has published April first, April Fool's Day,

924
00:57:35,760 --> 00:57:38,880
Speaker 2: of twenty twenty. Don't assume the pandemic has ended the

925
00:57:38,880 --> 00:57:42,840
Speaker 2: bull market. I have never gotten more hate mail for

926
00:57:43,000 --> 00:57:48,080
Speaker 2: anything I've written since before or since. And the irony

927
00:57:48,240 --> 00:57:50,680
Speaker 2: is I wasn't saying go buy him. I was just saying,

928
00:57:51,360 --> 00:57:54,920
Speaker 2: don't assume it's over, because here's what history came before.

929
00:57:55,440 --> 00:57:58,080
Speaker 2: And by the way, that turned out to be correct.

930
00:57:58,640 --> 00:58:01,000
Speaker 2: And we got a lot of pushback from clients. I

931
00:58:01,120 --> 00:58:05,400
Speaker 2: understand my dry cleaner's closing, the local movie theater shut,

932
00:58:05,480 --> 00:58:09,040
Speaker 2: the local retailer shut. Yeah, but those guys aren't in

933
00:58:09,080 --> 00:58:10,640
Speaker 2: the s and P five hundred. Look at what's in

934
00:58:10,680 --> 00:58:14,200
Speaker 2: the s and P five hundred. Microsoft, Apple, Hey you

935
00:58:14,200 --> 00:58:19,360
Speaker 2: could work from home. Netflix and docu Sign and Peloton

936
00:58:19,720 --> 00:58:22,960
Speaker 2: and all of those companies did really well. And the

937
00:58:23,000 --> 00:58:26,440
Speaker 2: ones that survived were the ones that continued to operate

938
00:58:26,920 --> 00:58:31,480
Speaker 2: after the pandemic. So Teledoc and Peloton and docu Sign

939
00:58:32,600 --> 00:58:36,440
Speaker 2: and to some degree Netflix, they all got shellacked after

940
00:58:36,480 --> 00:58:40,520
Speaker 2: we reopened. But the big tech companies have held up well.

941
00:58:40,800 --> 00:58:44,760
Speaker 2: How much of this is just their addressing the market

942
00:58:45,240 --> 00:58:50,320
Speaker 2: versus concern about uncertainty. So we're going to stick with

943
00:58:50,720 --> 00:58:51,640
Speaker 2: the tried and true.

944
00:58:52,280 --> 00:58:56,000
Speaker 1: I think that we saw a major peak in early

945
00:58:56,040 --> 00:59:02,200
Speaker 1: twenty twenty one in terms of enthusiasm. All the speculative bubble, right,

946
00:59:03,240 --> 00:59:08,760
Speaker 1: we're seeing a less robust peak.

947
00:59:09,520 --> 00:59:11,760
Speaker 2: People are running, people are running out of savings. All

948
00:59:11,800 --> 00:59:15,880
Speaker 2: the pandemic large ass is now fading that biggest through

949
00:59:15,920 --> 00:59:16,760
Speaker 2: the python.

950
00:59:18,800 --> 00:59:25,840
Speaker 1: We've also connected mood between stocks and bonds. One of

951
00:59:25,880 --> 00:59:28,200
Speaker 1: the things that was so interesting to me about early

952
00:59:28,240 --> 00:59:35,720
Speaker 1: twenty twenty one is we had a reasonably coincident peak

953
00:59:36,560 --> 00:59:41,000
Speaker 1: in bond prices and stock enthusiasm at the same time you.

954
00:59:41,000 --> 00:59:43,840
Speaker 2: Had a forty year bullmarket and bonds that came to

955
00:59:43,880 --> 00:59:47,000
Speaker 2: an end. You know, you had that ice. Blame fiscal

956
00:59:48,040 --> 00:59:50,120
Speaker 2: but there are a lot of other theories for why

957
00:59:50,200 --> 00:59:54,560
Speaker 2: inflation spiked and started that tightening round by the Fed.

958
00:59:55,080 --> 00:59:58,440
Speaker 2: But there's no doubt a bond market ended around the

959
00:59:58,480 --> 01:00:02,040
Speaker 2: same bull market ended around the same time the post

960
01:00:02,120 --> 01:00:04,720
Speaker 2: pandemic bull market slowed.

961
01:00:04,880 --> 01:00:09,520
Speaker 1: And so we have this declining confidence in stocks and

962
01:00:09,560 --> 01:00:10,840
Speaker 1: bonds at the same time.

963
01:00:11,280 --> 01:00:13,280
Speaker 2: And which is the last time we had that was

964
01:00:13,320 --> 01:00:14,160
Speaker 2: forty years ago.

965
01:00:14,320 --> 01:00:18,320
Speaker 1: Yeah, And people look at their diversified pie charts and

966
01:00:18,400 --> 01:00:21,720
Speaker 1: see all these different asset classes. I look at those

967
01:00:21,760 --> 01:00:25,960
Speaker 1: pie charts differently to say how's the sentiment aligning with

968
01:00:26,000 --> 01:00:29,640
Speaker 1: all of these because we have a lot of cooling

969
01:00:29,720 --> 01:00:32,640
Speaker 1: sentiment in many, many pieces of the pie at the

970
01:00:32,680 --> 01:00:33,200
Speaker 1: same time.

971
01:00:33,480 --> 01:00:37,360
Speaker 2: Huh really, that's quite fascinating. So the world isn't black

972
01:00:37,400 --> 01:00:41,000
Speaker 2: and white. There's a lot of subtlety and nuance, a

973
01:00:41,120 --> 01:00:45,720
Speaker 2: spectrum of choices, but we all tend to reduce everything

974
01:00:45,760 --> 01:00:49,320
Speaker 2: to yes, no, up, down, black or white choices. How

975
01:00:50,080 --> 01:00:52,800
Speaker 2: can you look at confidence? How can you look at

976
01:00:52,800 --> 01:00:56,200
Speaker 2: sentiment to help you make decisions when there's so many

977
01:00:56,240 --> 01:00:56,920
Speaker 2: shades of gray?

978
01:00:57,320 --> 01:01:01,040
Speaker 1: Yeah, So if I'm an investor, I think it's useful

979
01:01:01,440 --> 01:01:04,680
Speaker 1: to look at the crowd sentiment rather than your own.

980
01:01:05,040 --> 01:01:09,600
Speaker 1: We're not always good judges of our own behavior, and

981
01:01:09,800 --> 01:01:13,880
Speaker 1: we can be more honest judges of others sometimes, you know,

982
01:01:13,960 --> 01:01:19,760
Speaker 1: painfully honest. But market crowds tend to be almost like

983
01:01:19,840 --> 01:01:25,880
Speaker 1: a middle school environment where it's it's very social. I

984
01:01:25,960 --> 01:01:29,080
Speaker 1: joke that, you know, financial markets are social networks with

985
01:01:29,160 --> 01:01:32,120
Speaker 1: money instead of likes. We put money in and take

986
01:01:32,120 --> 01:01:32,439
Speaker 1: it out.

987
01:01:32,600 --> 01:01:35,520
Speaker 2: It's a popularity. It's a peculiarity, but no thumbs up.

988
01:01:35,560 --> 01:01:36,320
Speaker 2: It's just cash.

989
01:01:36,400 --> 01:01:39,760
Speaker 1: It's just cash, and and that becomes a useful way

990
01:01:40,040 --> 01:01:43,640
Speaker 1: to look at where's the crowd putting money, where's the

991
01:01:43,640 --> 01:01:46,959
Speaker 1: crowd excited? Where's the crowd you know, Oh, you wore

992
01:01:47,040 --> 01:01:49,720
Speaker 1: that you you're a you know, you can't sit with us,

993
01:01:50,240 --> 01:01:54,520
Speaker 1: And so that that sort of middle school arrangement in

994
01:01:54,560 --> 01:01:58,840
Speaker 1: the markets becomes a pretty honest sense of where the

995
01:01:58,960 --> 01:02:03,800
Speaker 1: crowd broadly is. Are their managers who are on the

996
01:02:03,840 --> 01:02:07,640
Speaker 1: other side of those trades. Absolutely, when I think about

997
01:02:08,160 --> 01:02:13,960
Speaker 1: the market's mood, the market is a pretty quick, deciding,

998
01:02:14,760 --> 01:02:21,000
Speaker 1: homogeneous blob that is of average middle school intelligence. It

999
01:02:21,120 --> 01:02:24,160
Speaker 1: cannot do system too thinking to borrow from connoment. It's

1000
01:02:24,240 --> 01:02:27,360
Speaker 1: only capable of system when thinking, So you shouldn't try

1001
01:02:27,400 --> 01:02:29,840
Speaker 1: to you know, don't try to be too smart, just

1002
01:02:30,080 --> 01:02:33,080
Speaker 1: try to think. You know, how is the high school

1003
01:02:33,120 --> 01:02:34,240
Speaker 1: student thinking about this?

1004
01:02:34,680 --> 01:02:38,200
Speaker 2: So you're reminding me of the famous Benjamin Graham quote.

1005
01:02:38,400 --> 01:02:40,920
Speaker 2: In the short run, the market is a voting machine,

1006
01:02:41,400 --> 01:02:44,520
Speaker 2: but in the long run it's a weighing machine. So

1007
01:02:44,560 --> 01:02:48,200
Speaker 2: you get sentiment in the beginning, but later on things

1008
01:02:48,320 --> 01:02:51,400
Speaker 2: should return to what their actual values are.

1009
01:02:51,640 --> 01:02:55,440
Speaker 1: Yeah, I mean, we're going to overshoot, and particularly when

1010
01:02:55,560 --> 01:02:59,560
Speaker 1: confidence is low, we're likely to be much more impulsive,

1011
01:03:00,120 --> 01:03:03,400
Speaker 1: more emotional than we might otherwise be. I think that

1012
01:03:03,520 --> 01:03:07,720
Speaker 1: was one of the lessons that people missed with meme stocks.

1013
01:03:08,520 --> 01:03:11,000
Speaker 2: It wasn't about the stocks, it was about the mood

1014
01:03:11,000 --> 01:03:11,640
Speaker 2: at the moment, the.

1015
01:03:11,640 --> 01:03:14,760
Speaker 1: Mood and the willingness of people to jump into the crowd.

1016
01:03:14,800 --> 01:03:17,080
Speaker 1: You know, nothing attracts a crowd like a crowd in

1017
01:03:17,120 --> 01:03:20,880
Speaker 1: the markets, and so we should not be surprised if

1018
01:03:20,960 --> 01:03:23,480
Speaker 1: what goes up like that also comes down like that.

1019
01:03:23,880 --> 01:03:27,080
Speaker 2: Huh really really quite interesting. So let's talk a little

1020
01:03:27,120 --> 01:03:30,680
Speaker 2: bit about some recent market moods. We were talking about

1021
01:03:30,920 --> 01:03:35,120
Speaker 2: meme stocks. You know, the old timers like myself looked

1022
01:03:35,120 --> 01:03:38,560
Speaker 2: at the various meme stocks and kind of snickered to

1023
01:03:38,600 --> 01:03:42,080
Speaker 2: ourselves and said, I've seen this movie before, I know

1024
01:03:42,160 --> 01:03:46,400
Speaker 2: how it's going to end. And yet still those meme

1025
01:03:46,440 --> 01:03:50,560
Speaker 2: stocks did their thing. They exploded higher before ultimately they

1026
01:03:50,600 --> 01:03:56,360
Speaker 2: crashed and burned. Where's amc now? Down ninety eight percent?

1027
01:03:57,880 --> 01:04:00,840
Speaker 2: A lot of the big meme stocks games stop also

1028
01:04:01,000 --> 01:04:05,560
Speaker 2: way off its eyes when you see this starting during

1029
01:04:05,600 --> 01:04:09,000
Speaker 2: the lockdown? What are your thoughts about these memestocks? What

1030
01:04:09,040 --> 01:04:10,000
Speaker 2: does that triggering you?

1031
01:04:10,560 --> 01:04:14,240
Speaker 1: Two things? It's sort of an interesting combination of both

1032
01:04:14,280 --> 01:04:17,960
Speaker 1: extremes and mood because you have the nihilism that naturally

1033
01:04:18,000 --> 01:04:21,680
Speaker 1: comes with low confidence, and so you have folks who

1034
01:04:21,720 --> 01:04:26,840
Speaker 1: have cash to actually execute that nihilism and buy lottery tickets.

1035
01:04:26,960 --> 01:04:31,120
Speaker 1: Is kind of what was going on. But you also

1036
01:04:31,400 --> 01:04:36,400
Speaker 1: have the novice and naive, and they're a crowd I

1037
01:04:36,560 --> 01:04:38,840
Speaker 1: like to follow because they're always the last to the

1038
01:04:38,880 --> 01:04:44,320
Speaker 1: party and they're a great tell. In fact, more recently

1039
01:04:44,360 --> 01:04:49,000
Speaker 1: we had a little flurry of memestock behavior in the

1040
01:04:49,040 --> 01:04:52,000
Speaker 1: summer of twenty twenty three. It's a great indicator that

1041
01:04:52,080 --> 01:04:56,840
Speaker 1: we're reaching a climax in mood when it's amateur hour.

1042
01:04:57,120 --> 01:05:00,400
Speaker 2: Meaning to the upside or to the downside both, Oh

1043
01:05:00,520 --> 01:05:01,240
Speaker 2: really yeah.

1044
01:05:01,280 --> 01:05:05,360
Speaker 1: Because sadly the novice and naive are the last to buy,

1045
01:05:06,200 --> 01:05:08,960
Speaker 1: they're also the last to sell, the last to capitulate.

1046
01:05:09,080 --> 01:05:11,120
Speaker 2: Someone's got to be on the wrong side of the train.

1047
01:05:11,120 --> 01:05:15,840
Speaker 1: And so they buy at the extreme and they sell

1048
01:05:15,840 --> 01:05:19,280
Speaker 1: at the low and are just brutally punished as a result.

1049
01:05:19,760 --> 01:05:24,120
Speaker 1: But it's useful because bubbles unwind on a lipho basis

1050
01:05:24,680 --> 01:05:27,360
Speaker 1: last and first, last in, first out. So no surprise

1051
01:05:27,480 --> 01:05:30,200
Speaker 1: that the meme stocks and companies like Peloton have just

1052
01:05:30,240 --> 01:05:32,640
Speaker 1: been pummeled the shots at the top and then they

1053
01:05:32,880 --> 01:05:34,720
Speaker 1: leave via a high story window.

1054
01:05:35,080 --> 01:05:38,680
Speaker 2: You know, if you've lived through this before. And I

1055
01:05:38,760 --> 01:05:43,000
Speaker 2: remember watching Tealdoc and Docu Sign and Peloton all the

1056
01:05:43,040 --> 01:05:47,520
Speaker 2: work from Homestocks, and I remember specifically saying, I know

1057
01:05:47,600 --> 01:05:49,560
Speaker 2: these are going to be moonshots, and I know they're

1058
01:05:49,560 --> 01:05:52,920
Speaker 2: going to be disasters. I'm not sure I'm confident enough

1059
01:05:52,960 --> 01:05:55,400
Speaker 2: that I'm going to get the timing right. And I

1060
01:05:55,440 --> 01:05:57,960
Speaker 2: got to think a lot of other people looked at

1061
01:05:57,960 --> 01:06:00,480
Speaker 2: it similarly. Someone made a ton of money on the

1062
01:06:00,480 --> 01:06:02,280
Speaker 2: way up, and someone made a ton of money on

1063
01:06:02,320 --> 01:06:02,720
Speaker 2: the way.

1064
01:06:02,600 --> 01:06:05,360
Speaker 1: Down, and it may be the same people. Uh huh,

1065
01:06:05,440 --> 01:06:08,000
Speaker 1: I mean, sadly, I think those that wrote it up

1066
01:06:08,200 --> 01:06:08,800
Speaker 1: also wrote it.

1067
01:06:08,800 --> 01:06:09,919
Speaker 2: Down crushed on the way down.

1068
01:06:10,000 --> 01:06:12,960
Speaker 1: And we've seen the same thing in crypto, that sense

1069
01:06:13,000 --> 01:06:15,560
Speaker 1: that it's going to come back, It's definitely going to

1070
01:06:15,600 --> 01:06:16,680
Speaker 1: come back, and.

1071
01:06:16,760 --> 01:06:21,240
Speaker 2: That muscle memory fades after about a year of beating yep,

1072
01:06:21,320 --> 01:06:24,240
Speaker 2: and finally you just stop buying the dips. That just

1073
01:06:24,320 --> 01:06:28,040
Speaker 2: goes away. So let's now roll this into the twenty

1074
01:06:28,160 --> 01:06:34,720
Speaker 2: twenty three fourth quarter. Environment politics generally has become darker

1075
01:06:34,720 --> 01:06:37,840
Speaker 2: and negative, But I don't ever recall a period in

1076
01:06:37,920 --> 01:06:42,440
Speaker 2: American history where the leading candidates for the two major

1077
01:06:42,520 --> 01:06:48,600
Speaker 2: parties are both widely disliked not only by the population

1078
01:06:48,720 --> 01:06:52,120
Speaker 2: at large, but their own parties aren't big as fans.

1079
01:06:52,520 --> 01:06:57,600
Speaker 2: The Democrats say Biden's too old. The Republicans say Trump,

1080
01:06:57,600 --> 01:06:59,960
Speaker 2: who's only what two and a half years younger than Biden,

1081
01:07:01,240 --> 01:07:06,479
Speaker 2: isn't fit. You have both parties wishing for alternatives. When

1082
01:07:06,560 --> 01:07:08,160
Speaker 2: was the last time that happened?

1083
01:07:08,440 --> 01:07:11,640
Speaker 1: So you can go back to the early nineteen eighties.

1084
01:07:11,680 --> 01:07:13,280
Speaker 1: I think it was John Anderson.

1085
01:07:13,080 --> 01:07:15,000
Speaker 2: I recall helped Clinton get elected.

1086
01:07:15,800 --> 01:07:20,720
Speaker 1: It would not surprise me if both Biden and Trump

1087
01:07:21,120 --> 01:07:23,320
Speaker 1: are not on the ballot a year from now.

1088
01:07:23,760 --> 01:07:27,520
Speaker 2: Really yeah, because you go to the bedding sites, they

1089
01:07:27,560 --> 01:07:29,200
Speaker 2: seem to think it's a head to head.

1090
01:07:29,400 --> 01:07:36,640
Speaker 1: Absolutely, But watch how we use the term old. You know,

1091
01:07:36,680 --> 01:07:41,880
Speaker 1: the old can mean wives experience or resilient. It can

1092
01:07:41,960 --> 01:07:46,280
Speaker 1: also mean decrepit, it can meet out of touch. And

1093
01:07:46,960 --> 01:07:51,440
Speaker 1: if you think about Joe Biden's career, he came into

1094
01:07:51,520 --> 01:07:58,360
Speaker 1: office as the young buck against an aging group of

1095
01:07:59,400 --> 01:08:01,960
Speaker 1: politicians on a national level.

1096
01:08:02,440 --> 01:08:04,640
Speaker 2: On a national level, we have once.

1097
01:08:04,440 --> 01:08:08,000
Speaker 1: Again and we are back to that, both parties, House, Senate,

1098
01:08:08,760 --> 01:08:11,520
Speaker 1: even the Supreme Court. We have a lot of people

1099
01:08:11,560 --> 01:08:16,880
Speaker 1: who are, let's just politely say, AARP members. Yeah, and

1100
01:08:16,880 --> 01:08:20,280
Speaker 1: I don't I don't think we have seen yet the

1101
01:08:20,600 --> 01:08:29,200
Speaker 1: kind of grassroots political leader who rises from within, and

1102
01:08:29,200 --> 01:08:33,280
Speaker 1: and I think that that is a real possibility. What's

1103
01:08:33,400 --> 01:08:36,840
Speaker 1: what's interesting with both parties is that we have these

1104
01:08:36,880 --> 01:08:40,719
Speaker 1: figures who are seeking to control from above.

1105
01:08:41,160 --> 01:08:41,280
Speaker 2: Right.

1106
01:08:42,200 --> 01:08:48,000
Speaker 1: History suggests that in times of turmoil we choose from within,

1107
01:08:48,720 --> 01:08:54,080
Speaker 1: that leaders that come sort of unexpectedly from below and

1108
01:08:54,479 --> 01:08:57,840
Speaker 1: not the ones that we expect. I mean, I look

1109
01:08:57,880 --> 01:09:01,640
Speaker 1: at somebody like Zelensky, who no one believed would be

1110
01:09:01,720 --> 01:09:06,040
Speaker 1: a credible leader, and yet from my perspective, had all

1111
01:09:06,120 --> 01:09:10,080
Speaker 1: the traits of a great crisis leader. You know, can

1112
01:09:10,120 --> 01:09:11,599
Speaker 1: read the room, is you know.

1113
01:09:12,000 --> 01:09:15,640
Speaker 2: Just on his feet, relatively intelligent.

1114
01:09:15,439 --> 01:09:17,840
Speaker 1: And and I don't know if it's the case for him,

1115
01:09:17,840 --> 01:09:22,000
Speaker 1: but you know a lot of comedians suffer from depression,

1116
01:09:22,000 --> 01:09:24,840
Speaker 1: and you know, if you're in a crisis, you know,

1117
01:09:25,000 --> 01:09:29,920
Speaker 1: uncertainty and powerlessness is called Tuesday. My friend Asergami has

1118
01:09:29,920 --> 01:09:34,360
Speaker 1: written a wonderful book on leader crises in the relationship

1119
01:09:34,439 --> 01:09:39,040
Speaker 1: to to mental illness. But it would not surprise me

1120
01:09:39,160 --> 01:09:47,439
Speaker 1: berry to see young local politicians, governors, mayors who upend

1121
01:09:47,960 --> 01:09:52,080
Speaker 1: the rhetoric and surprise on both sides of the party.

1122
01:09:52,280 --> 01:09:56,920
Speaker 2: Huh, that's interesting. We've touched very briefly on social media.

1123
01:09:57,720 --> 01:10:02,840
Speaker 2: Let's talk about media generally and social media on a

1124
01:10:02,880 --> 01:10:07,160
Speaker 2: related basis. There's been so much misinformation, there's been so

1125
01:10:07,360 --> 01:10:14,000
Speaker 2: much problems being able to have trustworthy sources. How can

1126
01:10:14,040 --> 01:10:17,840
Speaker 2: we look at centiment and confidence as a way to

1127
01:10:18,080 --> 01:10:19,120
Speaker 2: deal with these issues.

1128
01:10:19,320 --> 01:10:22,799
Speaker 1: Yeah, So when confidence is high, we go to the center.

1129
01:10:23,200 --> 01:10:26,599
Speaker 1: We watch three networks, you know, ABC, CBS, NBC.

1130
01:10:27,320 --> 01:10:28,280
Speaker 2: Still is that still no?

1131
01:10:28,560 --> 01:10:31,760
Speaker 1: But my point is that in the nineteen sixties, as

1132
01:10:31,800 --> 01:10:36,640
Speaker 1: confidence was peaking, we're all watching the same news stories

1133
01:10:36,680 --> 01:10:37,640
Speaker 1: from the same.

1134
01:10:38,000 --> 01:10:41,160
Speaker 2: We've been totally bulkanized since then, and there's a thousand channels.

1135
01:10:41,240 --> 01:10:46,560
Speaker 1: Yeah, and the Balkanization that takes place today can be instantaneous.

1136
01:10:47,360 --> 01:10:51,640
Speaker 1: So as your mood changes, very if I create a

1137
01:10:51,760 --> 01:10:55,720
Speaker 1: more resonant deliverer and you could watch this on the

1138
01:10:55,800 --> 01:11:00,000
Speaker 1: right with Fox the News Mix than on. As republic

1139
01:11:00,200 --> 01:11:05,519
Speaker 1: and confidence change, you will find the provider of news

1140
01:11:06,000 --> 01:11:10,640
Speaker 1: that is most me here now you and the Internet

1141
01:11:11,560 --> 01:11:16,840
Speaker 1: and social media enables that, like there's no tomorrow, and

1142
01:11:16,840 --> 01:11:25,200
Speaker 1: and we forget that familiarity and truthiness are much more

1143
01:11:25,240 --> 01:11:27,880
Speaker 1: appealing to us than the truth.

1144
01:11:28,640 --> 01:11:32,600
Speaker 2: We're all confirmation bias and less fact checking than we

1145
01:11:32,640 --> 01:11:33,640
Speaker 2: want to admit.

1146
01:11:33,360 --> 01:11:35,360
Speaker 1: To, particularly when confidence is low.

1147
01:11:35,479 --> 01:11:38,479
Speaker 2: But let let's stick with oh really, particularly.

1148
01:11:38,000 --> 01:11:40,679
Speaker 1: When because if I've if I've got all these other

1149
01:11:40,720 --> 01:11:44,560
Speaker 1: things to focus on, I don't have the cognitive bandwidth

1150
01:11:45,120 --> 01:11:47,439
Speaker 1: that's fair to do the fact checking.

1151
01:11:47,760 --> 01:11:52,120
Speaker 2: So let's apply the same left right analysis that we

1152
01:11:52,120 --> 01:11:55,519
Speaker 2: were talking about with economics before, and it's more up

1153
01:11:55,560 --> 01:11:58,799
Speaker 2: down than left right. When I look at both social

1154
01:11:58,840 --> 01:12:03,240
Speaker 2: media and and mainstream media, I often find people who

1155
01:12:03,240 --> 01:12:06,719
Speaker 2: are arguing left right or missing the point. It's usually

1156
01:12:06,760 --> 01:12:11,479
Speaker 2: more what's more sensationalistic, what's more clickbaity, what's more hair

1157
01:12:11,560 --> 01:12:15,840
Speaker 2: on fire, and what's more structurally here's the horse race,

1158
01:12:15,880 --> 01:12:18,599
Speaker 2: So let's not talk about policy. Who's ahead right now?

1159
01:12:19,439 --> 01:12:23,720
Speaker 2: It's always what's the easiest way to generate eyeballs than

1160
01:12:23,760 --> 01:12:27,320
Speaker 2: it is to provide more heat than light, so to speak.

1161
01:12:27,479 --> 01:12:32,520
Speaker 1: Yeah, So to our media focus is intensely about resonance, relevance,

1162
01:12:33,320 --> 01:12:37,479
Speaker 1: and that creates several problems. One is the media has

1163
01:12:37,560 --> 01:12:40,639
Speaker 1: to follow its audience as opposed to lead its audience.

1164
01:12:41,000 --> 01:12:46,559
Speaker 1: The media also has to create even greater excitement. So

1165
01:12:47,200 --> 01:12:50,760
Speaker 1: I joke often that we've gone from the circus Barker's

1166
01:12:51,320 --> 01:12:54,120
Speaker 1: promoting a two headed lady. You know, the lady now

1167
01:12:54,120 --> 01:12:58,040
Speaker 1: has to have about fifteen heads to capture attention, and

1168
01:12:58,080 --> 01:13:01,479
Speaker 1: that becomes unsustainable. One of the things if you think

1169
01:13:01,520 --> 01:13:06,880
Speaker 1: about our culture of followership, the goal is dependence. And

1170
01:13:07,000 --> 01:13:10,160
Speaker 1: so whether I'm a politician, a member of the media,

1171
01:13:10,360 --> 01:13:16,160
Speaker 1: a pundit at large, the goal is permanent dependence. You

1172
01:13:16,560 --> 01:13:21,080
Speaker 1: have to keep coming back to me. And what I'm

1173
01:13:21,120 --> 01:13:25,960
Speaker 1: looking for, Barry, are leaders who are talking about empowerment

1174
01:13:26,320 --> 01:13:29,679
Speaker 1: that send a message. And again this could be. This

1175
01:13:29,760 --> 01:13:33,120
Speaker 1: is where I think up down may matter. Is if

1176
01:13:33,200 --> 01:13:36,719
Speaker 1: I send a message of empowerment to those at the bottom,

1177
01:13:37,680 --> 01:13:41,720
Speaker 1: you could easily draw together a court from both the

1178
01:13:41,800 --> 01:13:46,200
Speaker 1: left and the right that generates this grassroots movement.

1179
01:13:46,360 --> 01:13:50,640
Speaker 2: Pardon me for personalizing this, but you seem fairly optimistic

1180
01:13:51,160 --> 01:13:58,160
Speaker 2: that in this time of uncertainty and partisanship and negative

1181
01:13:58,160 --> 01:14:02,960
Speaker 2: sentiment and just general disarray, you seem fairly optimistic that

1182
01:14:03,000 --> 01:14:04,000
Speaker 2: we're going to come out of this.

1183
01:14:04,160 --> 01:14:07,840
Speaker 1: Okay, I guess I would say I am optimistic that

1184
01:14:08,000 --> 01:14:11,200
Speaker 1: we will tire of the uncertainty. We will tire of

1185
01:14:11,240 --> 01:14:18,080
Speaker 1: the powerlessness, and groups will seek to regain or gain

1186
01:14:18,640 --> 01:14:22,559
Speaker 1: in depending on the situation, certainty and control in their lives.

1187
01:14:23,240 --> 01:14:26,880
Speaker 1: How that struggle plays out, I don't know, but there

1188
01:14:26,920 --> 01:14:31,760
Speaker 1: is no question in my mind that the uncertainty will end.

1189
01:14:32,080 --> 01:14:34,880
Speaker 1: It may be chaotic, you know, it could be civil

1190
01:14:34,920 --> 01:14:37,879
Speaker 1: war as groups fight for what is what does certainty

1191
01:14:37,920 --> 01:14:40,040
Speaker 1: mean for you versus what it means for me? But

1192
01:14:40,800 --> 01:14:43,240
Speaker 1: we don't endure this, well, the.

1193
01:14:43,200 --> 01:14:46,439
Speaker 2: One hundred years War doesn't. The reason we haven't had

1194
01:14:46,479 --> 01:14:48,120
Speaker 2: one sense is who wants to be at war for

1195
01:14:48,120 --> 01:14:51,320
Speaker 2: one hundred years? Yeah? Huh? Really quite interesting. And let's

1196
01:14:51,360 --> 01:14:54,080
Speaker 2: jump to our favorite question, starting with what are you

1197
01:14:54,080 --> 01:14:56,840
Speaker 2: streaming these days? Tell us what you're either watching or

1198
01:14:56,880 --> 01:14:57,400
Speaker 2: listening to.

1199
01:14:57,640 --> 01:15:03,440
Speaker 1: So we're streaming murders in the building. My wife assesses

1200
01:15:03,439 --> 01:15:07,320
Speaker 1: and trains autistic adults, and so we've been watching Love

1201
01:15:07,360 --> 01:15:11,760
Speaker 1: on the Spectrum, which is a really heart warmings you know,

1202
01:15:11,800 --> 01:15:17,120
Speaker 1: I watch what my wife's organization does to transform autistic

1203
01:15:17,160 --> 01:15:20,600
Speaker 1: adults lives and even more their parents' lives, and so

1204
01:15:20,640 --> 01:15:25,320
Speaker 1: it's really heartwarming to see that there's there are so

1205
01:15:25,439 --> 01:15:28,519
Speaker 1: many opportunities that we ignore otherwise.

1206
01:15:28,920 --> 01:15:32,080
Speaker 2: Huh, really really interesting. Tell us about some of your

1207
01:15:32,120 --> 01:15:34,960
Speaker 2: early mentors who helped to shape your career.

1208
01:15:35,720 --> 01:15:37,840
Speaker 1: I think of some of the mentors I had at

1209
01:15:37,920 --> 01:15:42,080
Speaker 1: JP Morgan, particularly a guy named Dave Wakefield. You know,

1210
01:15:42,680 --> 01:15:45,880
Speaker 1: going into an organization like JP Morgan when I did,

1211
01:15:46,760 --> 01:15:51,680
Speaker 1: it was an organization that was about to undergo mammoth transformation,

1212
01:15:52,840 --> 01:15:58,120
Speaker 1: and what I sow value was the wisdom of what

1213
01:15:58,200 --> 01:16:01,960
Speaker 1: we might refer to now as old heads. You know,

1214
01:16:02,080 --> 01:16:05,880
Speaker 1: the world of finance is typically filled with young, aggressive

1215
01:16:06,720 --> 01:16:10,920
Speaker 1: You had these folks who would like yes, and you know,

1216
01:16:11,000 --> 01:16:13,719
Speaker 1: to your point, they'd seen it before. There was nothing

1217
01:16:13,760 --> 01:16:17,320
Speaker 1: new under the sun. And I really feel like a

1218
01:16:17,360 --> 01:16:21,680
Speaker 1: lot of organizations miss that sense of judgment, and so

1219
01:16:21,720 --> 01:16:23,400
Speaker 1: I feel really blessed to have had that.

1220
01:16:23,560 --> 01:16:26,720
Speaker 2: Huh, very interesting. Let's let's talk about books. What are

1221
01:16:26,720 --> 01:16:28,360
Speaker 2: some of your favorites. What are you reading now?

1222
01:16:28,560 --> 01:16:31,840
Speaker 1: Yeah, so interestingly very one. Reading is very difficult for me,

1223
01:16:32,479 --> 01:16:36,880
Speaker 1: But I spend so much of my day reading because

1224
01:16:36,920 --> 01:16:40,760
Speaker 1: I'm trying to capture what's going on in politics and

1225
01:16:40,800 --> 01:16:43,479
Speaker 1: economics and finance all at the same time that by

1226
01:16:43,479 --> 01:16:45,760
Speaker 1: the end of the day I want to go pull

1227
01:16:45,840 --> 01:16:49,759
Speaker 1: weeds in vegetable garden. I want to you know, reading

1228
01:16:49,840 --> 01:16:53,680
Speaker 1: is I'm embarrassed to say it, but it just it

1229
01:16:53,720 --> 01:16:55,960
Speaker 1: takes me a couple of days on vacation before I can.

1230
01:16:55,880 --> 01:16:57,720
Speaker 2: Crack a b That's my favorite place to read is

1231
01:16:57,760 --> 01:17:00,840
Speaker 2: on vacation, read a book on vacation, or when I'm

1232
01:17:00,880 --> 01:17:04,000
Speaker 2: prepping for a podcast. So let's go to our final

1233
01:17:04,040 --> 01:17:07,240
Speaker 2: two questions. What advice would you give to a recent

1234
01:17:07,320 --> 01:17:10,840
Speaker 2: college grad who is interested in a career in either

1235
01:17:11,280 --> 01:17:15,160
Speaker 2: finance or studying sentiment, So in.

1236
01:17:15,120 --> 01:17:18,760
Speaker 1: The in the world of finance, I would say, don't

1237
01:17:18,800 --> 01:17:23,599
Speaker 1: feel beholden to New York. I think there's a lot

1238
01:17:23,640 --> 01:17:25,880
Speaker 1: of folks who come out of college with that. You know,

1239
01:17:25,920 --> 01:17:28,240
Speaker 1: if I don't make it in New York, you know.

1240
01:17:28,720 --> 01:17:31,439
Speaker 1: And what I love so much about finance today is

1241
01:17:31,439 --> 01:17:35,160
Speaker 1: that there are opportunities in so many different angles of

1242
01:17:35,200 --> 01:17:36,759
Speaker 1: it in so many different places.

1243
01:17:37,400 --> 01:17:42,560
Speaker 2: Boston, Charlotte, Chicago, San Francisco, the number of Atlanta, the

1244
01:17:42,680 --> 01:17:47,920
Speaker 2: number of financial hubs have expanded dramatically, and there is

1245
01:17:48,600 --> 01:17:51,559
Speaker 2: pretty active. You know, venture capital used to be just

1246
01:17:51,600 --> 01:17:55,720
Speaker 2: San Francisco. There are a number of venture hubs all

1247
01:17:55,760 --> 01:17:56,600
Speaker 2: over the country.

1248
01:17:57,040 --> 01:17:59,760
Speaker 1: And to your question about sentiment, I think a lot

1249
01:17:59,800 --> 01:18:05,160
Speaker 1: of economists and finance professionals focus a lot of energy

1250
01:18:05,160 --> 01:18:08,200
Speaker 1: on what we do poorly, what we do wrong, and

1251
01:18:08,280 --> 01:18:10,800
Speaker 1: I think we need more attention on what do we

1252
01:18:10,920 --> 01:18:14,400
Speaker 1: just do? You know, if our objective is to change

1253
01:18:14,520 --> 01:18:19,040
Speaker 1: people's behavior, we need to understand what do we do

1254
01:18:19,640 --> 01:18:24,080
Speaker 1: that's unscripted. And I feel like the reason I wrote

1255
01:18:24,120 --> 01:18:26,400
Speaker 1: this book is to say this is what we just do.

1256
01:18:27,280 --> 01:18:30,960
Speaker 1: And if I understand that better, then I can start

1257
01:18:31,000 --> 01:18:32,160
Speaker 1: to make better decisions.

1258
01:18:32,680 --> 01:18:35,240
Speaker 2: And our final question, what do you know about the

1259
01:18:35,280 --> 01:18:41,160
Speaker 2: world of finance, investing sentiment confidence today? You wish you

1260
01:18:41,240 --> 01:18:43,559
Speaker 2: knew thirty or so years ago when you were first

1261
01:18:43,600 --> 01:18:44,720
Speaker 2: getting started.

1262
01:18:45,280 --> 01:18:51,240
Speaker 1: That what I think doesn't matter. To be successful, I

1263
01:18:51,439 --> 01:18:56,320
Speaker 1: need to understand how others think and feel because at

1264
01:18:56,320 --> 01:18:59,040
Speaker 1: the end of the day, my price is a function

1265
01:18:59,160 --> 01:19:00,120
Speaker 1: of their behavior.

1266
01:19:00,479 --> 01:19:04,240
Speaker 2: In other words, the crowd determines market price, the crowd

1267
01:19:04,240 --> 01:19:07,800
Speaker 2: determined sentiment. It's all about the wei, not the me.

1268
01:19:08,479 --> 01:19:12,439
Speaker 2: Absolutely huh, really fascinating, Peter, Thank you for being so

1269
01:19:12,560 --> 01:19:16,400
Speaker 2: generous with your time. We have been speaking with Peter Atwater,

1270
01:19:16,960 --> 01:19:21,040
Speaker 2: author of the Confidence Map, charting a path from Chaos

1271
01:19:21,080 --> 01:19:24,920
Speaker 2: to Clarity. If you enjoy this conversation, well, be sure

1272
01:19:24,960 --> 01:19:27,719
Speaker 2: and check out any of the previous five hundred such

1273
01:19:27,760 --> 01:19:31,400
Speaker 2: discussions we've had over the past nine years. You can

1274
01:19:31,439 --> 01:19:36,719
Speaker 2: find those at Apple Podcasts, Spotify, YouTube, wherever you get

1275
01:19:36,760 --> 01:19:40,400
Speaker 2: your favorite podcasts. Sign up for my daily reading list

1276
01:19:40,479 --> 01:19:43,439
Speaker 2: at rid Halts dot com. Follow me on Twitter at

1277
01:19:43,560 --> 01:19:47,759
Speaker 2: Rid Halts or on X at Barry Underscore Rid Halts.

1278
01:19:48,160 --> 01:19:52,160
Speaker 2: Follow all of the Bloomberg Family of podcasts at podcast

1279
01:19:52,800 --> 01:19:54,519
Speaker 2: I would be remiss if I did not thank our

1280
01:19:54,560 --> 01:19:58,479
Speaker 2: crack team that helps put these conversations together each week.

1281
01:19:58,800 --> 01:20:02,400
Speaker 2: Sarah Livesey is my my audio engineer. Anna Luke is

1282
01:20:02,520 --> 01:20:05,639
Speaker 2: my producer. A Teak of Albron is our project manager.

1283
01:20:05,720 --> 01:20:10,040
Speaker 2: Sean Russo is my researcher. I'm Barry Uholtz. You've been

1284
01:20:10,040 --> 01:20:14,400
Speaker 2: listening to Masters in Business on Bloomberg Radio.