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Why have so many been so wrong with recession predictions? · The Financial Exchange Show

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Speaker 1: Corporation face. He's the Financial Exchange with Chuck Zada and
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Speaker 1: Mark Vandetti.
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Speaker 2: Chuck, Mark and Tucker with you here, and we've got
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Speaker 2: stocks mostly up for the major indices, but it is
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Speaker 2: kind of a narrow rally that is taking place. Actually,
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Speaker 2: it's broadened out a little bit in the last twenty
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Speaker 2: minutes or so, but still largely being led by big tech,
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Speaker 2: which again has kind of been the trend for the
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Speaker 2: last week, week and a half after most of the
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Speaker 2: second half of the year, Big tech was kind of
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Speaker 2: lagging for quite a while since the July fourth holiday.
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Speaker 2: But today we've got the Dow off fifty one points,
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Speaker 2: the S and P is up forty two, and the
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Speaker 2: NASDAK up two hundred and seventy six. Nasdak knocking on
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Speaker 2: the door of twenty thousand today. That's twenty thousand points
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Speaker 2: for those of you playing at home. We've got the
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Speaker 2: ten of US Treasury selling off just a little bit,
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Speaker 2: up to four point two five percent, three basis point
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Speaker 2: move upward today. Oil West Texas Intermediate up eighty six
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Speaker 2: cents a barrel to sixty nine to forty five. The
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Speaker 2: TRIPA national average four gas prices taking back up nine
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Speaker 2: tens of a cent as well, from three oh one
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Speaker 2: to one tenth back up to three zero two. So
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Speaker 2: still can't get that puppy below three dollars a gallon nationally.
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Speaker 2: We'll see if we can get there eventually, but no
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Speaker 2: luck to this point. And gold today is up thirty
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Speaker 2: seven to ninety announced to twenty seven, fifty six and
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Speaker 2: thirty cents. Market's talking about this piece from CNBC. There's
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Speaker 2: there's a lot in the headlines and the sub headlines
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Speaker 2: that I'm trying to figure out. And basically what it
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Speaker 2: seems is, really they interviewed the chief market strategies for
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Speaker 2: Jefferies and just asked them a whole bunch of questions,
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Speaker 2: and that's how you get this Schmorgsborg of different answers. Then,
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Speaker 2: but he throws out there the first question is, look,
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Speaker 2: why did everyone have it wrong about recession? Now, granted
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Speaker 2: not everyone did, but you had things two years ago.
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Speaker 2: You know, Bloomberg publishes, Hey, there's one hundred percent chance
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Speaker 2: of a recession coming. You've had Jamie Diamond for the
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Speaker 2: last couple of years talking about these hurricanes that are
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Speaker 2: brewing economically, and yet nothing has come of it recession.
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Speaker 2: This has been the most predicted non recession that I've
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Speaker 2: ever seen. Why did people have it wrong?
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Speaker 3: Those who did, the people you cited, they're not economist.
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Speaker 3: Zervos is. He's a serious guy PhD. So more qualified
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Speaker 3: than I am, and is published in big journals on
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Speaker 3: not necessarily related topics. But the first thing I always
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Speaker 3: do is I check somebody's credentials. You have to do it,
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Speaker 3: like should they be talking about this? Even he should.
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Speaker 3: The person who edited the article probably shouldn't have written
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Speaker 3: the headline that way, because most serious economists don't try
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Speaker 3: to predict recessions. The first thing you learn is as
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Speaker 3: an undergraduate is it's futile. The economy is too complicated
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Speaker 3: in short. But you all know that. So those who
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Speaker 3: were predicting recession, I don't know. Jamie Diamond he saw
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Speaker 3: something in JP Morgan's Yeah, and that's fine, but that's
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Speaker 3: not You can't necessarily generalize from that. It's like we
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Speaker 3: talk about when Walmart gives a bad forecast or something.
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Speaker 3: We say, well, they're a big retailer, but they're not everybody.
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Speaker 3: It might be specific, the problem might be specific to them.
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Speaker 3: That's not the case.
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Speaker 1: Here.
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Speaker 3: I'm just using that as an example, so I don't know,
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Speaker 3: Chuck to me, the lesson is, don't try to predict
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Speaker 3: outcomes when something is very complex, like a recession or
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Speaker 3: even in inflation. People are harping about the potential inflationary
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Speaker 3: impact of tariffs and deportation of undocumented folks and stuff
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Speaker 3: like that. Those are predicated on all lse equal assumptions
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Speaker 3: and might turn out to be wrong. So predictions about
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Speaker 3: any economic phenomenon. And again, I think professional econmoists largely
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Speaker 3: get this right. That make the headlines of the hysterical
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Speaker 3: executives and often non economists who don't have a framework
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Speaker 3: in mind. They're just kind of going with their gut,
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Speaker 3: and that's okay. It's a free country. I think the
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Speaker 3: Celtics gonna wear the next twenty games. Who cares what
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Speaker 3: I think. I'm not an expert, it's not my domain,
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Speaker 3: and it's a silly prediction anyway, bad analogy, but you
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Speaker 3: kind of get the point.
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Speaker 2: Let's talk a little bit about another quote from Zervos.
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Speaker 2: Then he's talking about inflation and says he thinks it's
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Speaker 2: going to decline next year. He says, quote, take the
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Speaker 2: tape rewind it, put it back in twenty nineteen, and
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Speaker 2: let's go from there, basically saying, yeah, I think we're
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Speaker 2: gonna see low inflation like we did in the first
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Speaker 2: Trump term.
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Speaker 3: This is his area I would respect. I'm looking at
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Speaker 3: who he's published with and what he's written about. Yeah,
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Speaker 3: he is no lightweight, So I think when he says
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Speaker 3: that that the I'll call it the secular stagnation to
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Speaker 3: steal a term from a different, slightly different context. The
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Speaker 3: forces that prevailed before COVID didn't go away, they've been
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Speaker 3: distorted by it is. I think you made the point
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Speaker 3: better than the article did. Tell me if this is
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Speaker 3: not what you were trying to get at, we're going
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Speaker 3: to jump back to the old trend lines for growth
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Speaker 3: and the resulting trend line for price increases and just
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Speaker 3: about everything else. The ECONA said differently, the economy's not
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Speaker 3: changed structurally since twenty nineteen. A bunch of weird things happened,
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Speaker 3: but we're going to get back on track, so to speak.
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Speaker 3: That track isn't necessarily desirable in every way, but I
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Speaker 3: think that's is larger point.
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Speaker 4: We get this.
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Speaker 2: Another piece that is from is this The Financial Times?
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Speaker 4: Yes, yes, it is.
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Speaker 2: I always try to identify it by the text and
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Speaker 2: the headline, like the font they use before checking the
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Speaker 2: last page, and it.
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Speaker 3: Says, ft on that where does it say that it's
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Speaker 3: in the sub I had the benefit of looking at
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Speaker 3: it for thirty seconds. It's buried. See you right here
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Speaker 3: in bold underneath the graphic.
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Speaker 4: I see it, and now it's not. I appreciate you
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Speaker 4: pointing that out. Thanks. I could have just said that
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Speaker 4: off air, but no, no, it's fine.
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Speaker 2: Half our shows are me either like ripping on Paul
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Speaker 2: or mark for something. So it's good that it comes
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Speaker 2: back to me occasionally, like if you dished out, you
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Speaker 2: got to be able to take it.
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Speaker 3: Was it a criticism of you? You have to poke
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Speaker 3: around for it. I had the benefit of it's okay,
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Speaker 3: like being calmly being able to look for it.
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Speaker 4: I know, and make me look dumb like it's fine.
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Speaker 3: You just read the headline and you said it's not.
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Speaker 4: I know what I meant it is. What did it say, gentlemen,
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Speaker 4: I don't know what did it say? Back off, Tucker,
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Speaker 4: were conversation here.
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Speaker 3: This is riveting.
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Speaker 2: It says accurately predicting the next crash is impossible, and
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Speaker 2: this gets it exactly what you were talking about. The
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Speaker 2: piece also references one of the great science fiction works
7:41
Speaker 2: of all time, which is the Foundation series written by
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Speaker 2: Isaac Asimov.
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Speaker 3: I have not read it.
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Speaker 4: You haven't read Foundation.
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Speaker 3: No, I don't read fiction.
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Speaker 4: You don't read fiction at all.
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Speaker 3: No, I can't stick with it. I read some a
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Speaker 3: little bit of history, which is so you're not more
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Speaker 3: it's a story. I mean, look, trust me, I think
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Speaker 3: a lot of people don't read fiction.
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Speaker 2: I would say eighty to nine ninety percent of what
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Speaker 2: I read is nonfiction.
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Speaker 3: Yeah, but.
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Speaker 4: Not reading fiction.
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Speaker 3: Nothing.
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Speaker 4: Oh that that hurts my soul.
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Speaker 3: What should I be What have you read lightly that
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Speaker 3: you thought was a good investment of your time? Fiction?
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Speaker 4: Well? I would start with Foundation.
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Speaker 2: It's it's actually okay, like as long as we're talking
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Speaker 2: about it, like fantastic.
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Speaker 3: What is there a movie I can watch?
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Speaker 2: There's a TV series from Apple that the first season
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Speaker 2: c minus the second a minus okay, rare show that
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Speaker 2: you know, has a big budget and gets noticeably better
8:32
Speaker 2: from the first season to the second. But in any case,
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Speaker 2: if you're familiar with the Foundation book or even the series,
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Speaker 2: the premise of it is that a man by the
8:42
Speaker 2: name of Harry Selden developed something called psychohistory that allows
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Speaker 2: him to analyze basically the large scale events that happened
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Speaker 2: throughout the universe and basically can predict large scale events,
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Speaker 2: but not small ones. And it's this whole predictive model
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Speaker 2: that he uses. And there's a small group of people
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Speaker 2: that actually can figure out what's going on. That's not
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Speaker 2: really feasible. It's not really a thing that you can
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Speaker 2: actually do. And the point on this is, look, you
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Speaker 2: listen to you know, CNBC long enough for Bloomberg long enough,
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Speaker 2: and by that I mean for about eight seconds, and
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Speaker 2: everyone's trying to predict exactly what's going to happen next.
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Speaker 2: And a there's no scoreboard that shows you how accurately
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Speaker 2: those people actually do what they're claiming to do, like
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Speaker 2: whether or not they're actually good at it or not. Yes,
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Speaker 2: And b CNBC and Bloomberg understand that, Hey, the way
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Speaker 2: that money is made in the finance world, at least
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Speaker 2: by the people who really make a lot of it,
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Speaker 2: it's not by predicting the next thing, but rather it's
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Speaker 2: by getting you to trade on it, and as such,
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Speaker 2: they get you know, commissions off the flows and this
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Speaker 2: and that, and that's where you know the money's actually made,
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Speaker 2: you know, on a pretty consistent basis.
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Speaker 4: So trying to you know, read the.
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Speaker 2: News and say, oh, this is gonna be like the
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Speaker 2: next thing and having any kind of certainty about it, man, Like,
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Speaker 2: it's a humbling business trying to predict what's coming next.
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Speaker 2: And it's hard, and you're going against people that have
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Speaker 2: huge budgets and huge resources. And if you think, oh, like,
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Speaker 2: I see this coming and I know exactly what's gonna happen. Man,
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Speaker 2: We've been wrong about so many things the last couple
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Speaker 2: of years based on oh, like this happened before and
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Speaker 2: recession came with it, or this happened before and we
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Speaker 2: avoided recession. Economics. I say this all the time. It's
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Speaker 2: not physics. It's social science with numbers attached to it,
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Speaker 2: which makes people think that it has hard and fast rules,
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Speaker 2: when in fact it's kind of like, hey, here's some
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Speaker 2: guidelines to follow, but things can deviate from them in
10:44
Speaker 2: ways that you may not anticipate.
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Speaker 4: Yeah.
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Speaker 3: I think people know that long term investors know they
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Speaker 3: have to stay invested to benefit from the return. Generally,
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Speaker 3: I don't.
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Speaker 4: Think the average person knows that mark.
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Speaker 3: You don't think they know to buy and hold.
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Speaker 4: I'm not saying buying.
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Speaker 2: I don't think the average person knows that what is
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Speaker 2: going to happen isn't predictable. I'm in markets in the economy.
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Speaker 3: I bet you they would. They may not act like
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Speaker 3: they know that, but they would say that. So maybe
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Speaker 3: I'm being naive. Most would say, well, you can't predict
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Speaker 3: these things. I think most people would agree with that.
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Speaker 2: I think if you gave him a little dose of
11:19
Speaker 2: truth serum or hooked them up to a uh, what's
11:23
Speaker 2: the machine that tells if you're lying holograph?
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Speaker 4: That's the one.
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Speaker 3: Well you knew that answer.
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Speaker 2: Tucker's been through a couple of Yeah, it was very
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Speaker 2: quick with that answer. You know, well, his father in
11:33
Speaker 2: law is Robert de Niro from The Parents, Meet the Parents.
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Speaker 3: All right, yeah, Jack.
11:39
Speaker 4: Jack Burns, Yeah, Jack Burns. Jack talked Tie very well.
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Speaker 4: But in any case, let's take a quick break here.
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Speaker 2: I want to have more on this conversation here talking
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Speaker 2: about Hey, what what is coming in the economy next year?
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Speaker 2: Because even though we don't know it's you try to say, hey,
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Speaker 2: what are some clues that we can piece together in
11:55
Speaker 2: possible paths, because having a few possible paths that you
11:58
Speaker 2: can take much which better approach, I think than saying
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Speaker 2: this is or is not going to happen. We'll also
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Speaker 2: do some trivia right after this.
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Speaker 5: to Ebenezer Scrooge in Charles Dickens at Christmas Carol?
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Speaker 5: How many ghosts appeer to Ebenezer Scrooge in Charles Dickens
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13:48
Speaker 2: Mark's looked at me like, I think this might be
13:51
Speaker 2: one of the few fiction books that Mark's actually read.
13:54
Speaker 3: Yeah, because I always sympathize with the Scrooge, which probably
13:57
Speaker 3: says a lot about me and why I'm alone. But
13:59
Speaker 3: I get off his back.
14:01
Speaker 4: Hold on hell, let's deal it on this all.
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Speaker 3: No, No, let's not. Let's don't look into it. Don't
14:06
Speaker 3: look into it. But I always thought get off his back.
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Speaker 3: He'll he'll mellow out when he's ready, and.
14:11
Speaker 4: He did well because of what happens.
14:14
Speaker 3: I know it was going to happen eventually, is my points,
14:16
Speaker 3: Just like, let er take his course either.
14:18
Speaker 4: If you happen to watch UH the UH.
14:20
Speaker 2: I think it came out two years ago, The UH,
14:23
Speaker 2: Will Ferrell and Ryan Reynolds UH Spirited.
14:26
Speaker 3: Now I heard it was bad shocker.
14:28
Speaker 5: It's okay, filmed in Boston.
14:32
Speaker 4: It was filmed in Boston.
14:33
Speaker 2: It's it's okay, It's it's got its moments, but overall,
14:37
Speaker 2: if okay, it's it's fine.
14:40
Speaker 4: You know, don't waste your time, don't waste your money
14:42
Speaker 4: on it. If you're you know, you probably wouldn't. At
14:44
Speaker 4: this point, I guess let's talk a little bit about
14:47
Speaker 4: UH next year.
14:48
Speaker 2: And there's a piece from Bloomberg here it says Trump
14:52
Speaker 2: agenda won't hurt global economy as much next year as
14:54
Speaker 2: in twenty twenty six. So this again is kind of
14:56
Speaker 2: getting it, like, hey, how does one try to figure
14:59
Speaker 2: out what's going to happen in the future economically? And
15:03
Speaker 2: I just I don't know how one can make concrete
15:06
Speaker 2: predictions about this or that in terms of what's going
15:10
Speaker 2: to happen when there are things that have been promised
15:12
Speaker 2: during this political campaign that are inherently contradictory or just
15:18
Speaker 2: like information that doesn't like click as far as hey,
15:22
Speaker 2: what terrif rates are we even talking about implementing around
15:24
Speaker 2: what timeline?
15:25
Speaker 4: And things like that.
15:26
Speaker 2: I don't know how you can then have a definitive
15:28
Speaker 2: piece that says, well, this won't hurt as much this
15:31
Speaker 2: year as it will the year after.
15:33
Speaker 3: Yeah. I think the larger point here, and it's one
15:35
Speaker 3: that we were getting at in the last segment, is
15:39
Speaker 3: that economic outcomes are not forecastable the way say whether
15:43
Speaker 3: it is in the short term and the reason for it.
15:46
Speaker 3: And you learn this if you go on to study economics,
15:49
Speaker 3: like after college. The first thing they teach you learn
15:52
Speaker 3: about something called time series forecasting. That's a fancy way
15:54
Speaker 3: of saying projecting the value of something into the future.
15:57
Speaker 3: There are various ways of doing it, but the first
15:59
Speaker 3: thing you learn is that the relationship between something in
16:02
Speaker 3: its own past values or two different things has to
16:06
Speaker 3: be steady in order to use it for forecasts. Sure,
16:09
Speaker 3: the reason is obvious. This doesn't even really need explanation.
16:12
Speaker 3: If the way say the unemployment rate reflects the same rule.
16:17
Speaker 3: You and Mike Armstrong talk a lot about the SAM rule,
16:20
Speaker 3: talked a lot about it. When it was triggered. It
16:22
Speaker 3: was triggered, there was no recession. Why is that Well,
16:25
Speaker 3: because the relationship between what unemployment measures and the larger
16:29
Speaker 3: economy is apparently different now than it was in the past.
16:33
Speaker 3: That's what makes economic variable so tricky to forecast.
16:39
Speaker 2: No, no, no, it's it's basically, look, what are you
16:42
Speaker 2: basing this conclusion on, and how do you know it
16:44
Speaker 2: continues to hold up. There are common things that we
16:46
Speaker 2: see in everyday life. If I go outside and there
16:49
Speaker 2: are no clouds in the sky, I could say with
16:51
Speaker 2: pretty strong confidence it's not going to be raining. Yes,
16:54
Speaker 2: we have like the occasional sunshower caused by rain falling
16:57
Speaker 2: from a cloud that has since past. But ninety nine
17:01
Speaker 2: point nine percent of the time, if you walk outside
17:03
Speaker 2: and it's bright sunshine, there's no rain, it's it's not
17:07
Speaker 2: raining on you at that point. That's a basic, you
17:10
Speaker 2: know algorithm that every person uses, which is hey, sunshining,
17:15
Speaker 2: no rain.
17:16
Speaker 4: Okay.
17:17
Speaker 2: When you look at economics again, they get more complicated
17:20
Speaker 2: as you look through this. The three month average of
17:23
Speaker 2: unemployment has risen half a percent from its previous low
17:27
Speaker 2: in the last year recession. Like that, That's what the
17:31
Speaker 2: sum indicator has basically said historically.
17:34
Speaker 4: But does it hold true in all cases?
17:37
Speaker 2: No, We've we only have what was it like, eleven
17:40
Speaker 2: instances where we have accurate enough data to have even
17:43
Speaker 2: been able to measure this in the past, and so
17:47
Speaker 2: unlike lived human history, which is hey, by the time
17:49
Speaker 2: you're you know, twenty years old, you've lived was it
17:53
Speaker 2: seven thousand days? Okay, you've got, you know, a pretty
17:56
Speaker 2: good track record of Hey, sunny sky, no rain. We
18:01
Speaker 2: have eleven examples of some indicator firing and recession. Who's
18:08
Speaker 2: to say that that is the normal, that that should
18:10
Speaker 2: be how it works. It's not as black and white
18:12
Speaker 2: as it's made out to be.
18:13
Speaker 3: Yeah, I think where it gets confusing for folks maybe
18:16
Speaker 3: is when you're asked, what is the distinction between economic
18:21
Speaker 3: forecasting and weather forecasting, because some of the techniques are
18:24
Speaker 3: similar mathematically, and I'll say it again, I think it's
18:28
Speaker 3: worth underscoring. It's that the relationships that weather forecasting depends
18:32
Speaker 3: on for accuracy, and that accuracy is not perfect. We
18:35
Speaker 3: all know that are far more stable than the relationships
18:40
Speaker 3: that an economic forecaster would use. So it's appropriate, as
18:44
Speaker 3: you suggested, I think in the last segment to talk
18:45
Speaker 3: about the uncertainty associated with your forecast. Just like weather
18:49
Speaker 3: forecasters do seventy percent chance of rain that ris in
18:53
Speaker 3: seventy percent of scenarios in which all these forces are
18:57
Speaker 3: lining up to produce the average that I'm sharing with you,
19:01
Speaker 3: in seventy percent they result in rain, but in thirty
19:03
Speaker 3: percent they don't. And we do an okay job of
19:06
Speaker 3: I think internalizing that and understanding what it means.
19:09
Speaker 2: Yeah, we don't do as much of that with the economy.
19:12
Speaker 2: The economy, when people talk about it, is recession or
19:16
Speaker 2: not is kind of where we end up, not Hey,
19:18
Speaker 2: what's the probability of growth accelerating or slowing down?
19:22
Speaker 3: Or this is It's not like those errors don't exist.
19:24
Speaker 3: They're called prediction intervals. You generate them with any prediction.
19:27
Speaker 2: Well, and there's quite a bit in between you. It
19:28
Speaker 2: would be like just saying there's either rainy or sunny weather,
19:30
Speaker 2: sometimes it's cloudy.
19:32
Speaker 4: Quick break here. When we come back, we get the
19:33
Speaker 4: trivia answer, and then we're talking.
19:35
Speaker 1: Macy's bringing the latest financial news straight to your radio.
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19:48
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20:00
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20:08
Speaker 5: I'm gonna go supere to Everneezer, Scrooge and Charles Dickens
20:12
Speaker 5: a Christmas Carol. That'll be four, which were Jacob Marley,
20:16
Speaker 5: The Ghost of Christmas Past, Christmas Present, and Christmas Future.
20:21
Speaker 5: Winner today of the Financial Change Show T shirt was
20:25
Speaker 5: Kevin from Standish, Maine. Congrats to Kevin there. And we
20:29
Speaker 5: played trivia every day here on the Financial Exchange. See
20:32
Speaker 5: complete contest rules at Financial Exchange Show dot com.
20:36
Speaker 2: The only version of a Christmas Carol that is worth
20:40
Speaker 2: anything beyond the original is Muppet Christmas Carol. I'll stand
20:45
Speaker 2: by that until the day I die.
20:47
Speaker 4: Mark. You familiar with Muppet.
20:49
Speaker 3: Christmas Carol the concept?
20:51
Speaker 2: Yeah, so, Michael Kaine, you're familiar with him. I Am
20:56
Speaker 2: took the role as Scrooge with the only reason he
21:00
Speaker 2: took it was because the whoever was producing and directing.
21:03
Speaker 2: I think it was one of like Jim Henson's brothers
21:05
Speaker 2: or cousins agreed to let him play the role completely straight,
21:10
Speaker 2: as if he was acting in a drama, not surrounded
21:14
Speaker 2: by a bunch of muppets, And and did he do that.
21:17
Speaker 4: It's fantastic.
21:18
Speaker 2: To this day, I think it is one of the
21:20
Speaker 2: best acting performances I have seen in any movie, because
21:24
Speaker 2: you're actually surrounded by live action muppets that are just
21:27
Speaker 2: like flipping out for the whole movie. And he plays
21:30
Speaker 2: it as Scrooge, you know, the Scroogiest. Fantastic, and it's
21:36
Speaker 2: got some good music.
21:37
Speaker 3: Probably on Disney. They Disney bought the Muppets, right, Oh, yeah,
21:40
Speaker 3: it's fun, probably on Disney. Plus.
21:42
Speaker 2: Yeah, it's quite fantastic. Actually some good musical number.
21:46
Speaker 3: But you like the George C. Scott. Everybody seems to
21:48
Speaker 3: like the George Scott, which actually was a TV movie.
21:51
Speaker 2: But no, you know, Muppet Christmas Carrol is the only
21:55
Speaker 2: Stewart that stands up in my Listen. I'm a big
21:57
Speaker 2: Patrick Stewart Stewart fan, but I know Muppet Christmas counter
22:02
Speaker 2: the one that holds up.
22:03
Speaker 4: Let's talk a little bit about Macy.
22:04
Speaker 2: So about a month ago they announced, Hey, one of
22:08
Speaker 2: our employees made a one hundred and fifty one million
22:10
Speaker 2: dollar accounting error. Basically, this was someone who was in
22:14
Speaker 2: charge of accounting for the cost of shipping small items
22:19
Speaker 2: and somehow this this happened. Now at the time, we said, look,
22:23
Speaker 2: it's gonna be one of two things. Either A it
22:25
Speaker 2: isn't an individual person or b they probably made a
22:27
Speaker 2: mistake at some point and then just kept making it
22:29
Speaker 2: over and over and over with a lack of oversight.
22:32
Speaker 2: And it appears that's what the case was that back
22:34
Speaker 2: in twenty twenty one, this person basically misstated the amount
22:40
Speaker 2: of cost for small parcel delivery and continued making the
22:45
Speaker 2: same mistake, either know fully and willingly or unknowingly, but
22:51
Speaker 2: it appears that it was pretty knowingly. I'll quote here
22:54
Speaker 2: from the Wall Street Journal to hide the air. The
22:55
Speaker 2: employee continued to intentionally make erroneous accounting entries and falsify
22:59
Speaker 2: underlying document until the misstatement was discovered this fall. So
23:03
Speaker 2: it's one of those where look, if they had if
23:06
Speaker 2: they had just said, hey, I made a mistake, they
23:09
Speaker 2: probably still have their job right now and there's no
23:11
Speaker 2: problem because everyone makes mistakes in their job. Unfortunately, they said,
23:17
Speaker 2: oh no, I'm nervous, this is going to be the
23:18
Speaker 2: end of my job, and intentionally made the same mistake
23:21
Speaker 2: for the next four years, which ended up costing them
23:24
Speaker 2: their job.
23:24
Speaker 3: And probably at what point they felt like they were
23:26
Speaker 3: in too deep and they weren't. For two hundred and
23:29
Speaker 3: fifty bucks or something, a small loss with the first error,
23:32
Speaker 3: and then they decided that that was intolerable.
23:36
Speaker 4: Yeah, I mean, that's that's how it broke.
23:37
Speaker 3: The million dollar mark, and they said, well, we're committed.
23:39
Speaker 2: That's how most of this usually ends up happening, when
23:42
Speaker 2: it's just someone who gets nervous and says, oh, like,
23:45
Speaker 2: I need to keep doing this. It's rare that you
23:47
Speaker 2: find someone who I didn't cover it with you. Last
23:50
Speaker 2: week was with Paul, the Miami couple that launched a
23:54
Speaker 2: ponzi scheme back in twenty twenty one, got caught by
23:57
Speaker 2: the SEC, and a month out after getting caught by
24:00
Speaker 2: the SEC, launched another ponzi scheme like that.
24:03
Speaker 4: That's kind of the exception.
24:05
Speaker 3: Usually it's wow, real one trick pony. At least mix
24:08
Speaker 3: it up a little.
24:10
Speaker 4: They have no diversification of fraud.
24:12
Speaker 3: Yeah, start a crypto firm or something.
24:15
Speaker 2: So yeah, this again just appears to be someone who
24:19
Speaker 2: made an honest mistake, decided that they were going to
24:22
Speaker 2: try to hide it, and then it became a very
24:24
Speaker 2: large dishonest mistake.
24:25
Speaker 3: It's almost hard to believe, isn't it. I'm not saying
24:28
Speaker 3: Macy's is lying. I have no basis one way or
24:30
Speaker 3: the other. It's not hard to believe this. The sums
24:32
Speaker 3: here are huge. Cumulatively, they're huge. At no point did
24:35
Speaker 3: this raise a red flag? Huh? Their manager never said, hey,
24:39
Speaker 3: that costs been constant for six years, Good job, Johnson.
24:42
Speaker 2: I do think it speaks to the fact that, hey,
24:44
Speaker 2: as long as no problems are coming up, Yeah, most
24:48
Speaker 2: managers are like okay, like fine, like this is what
24:50
Speaker 2: it is.
24:51
Speaker 3: And we don't need to audit. Smithers's he's a good egg.
24:55
Speaker 2: So uh yeah, this uh is uh now closed.
24:59
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26:02
Speaker 1: Mark.
26:02
Speaker 2: I want to hop ahead a little bit to this
26:04
Speaker 2: piece on Alphabet and their quantum computing news from yesterday,
26:10
Speaker 2: no Tuesday. So on Tuesday yesterday, Well, the Alphabet announced
26:15
Speaker 2: it on Tuesday.
26:15
Speaker 3: That was yesterday.
26:16
Speaker 2: Tuesday was yesterday, Today's Wednesday. This is totally the opposite
26:21
Speaker 2: of last week. Last week, I felt like we got
26:24
Speaker 2: to Thursday and I'm like, man, it's only Tuesday this week,
26:27
Speaker 2: It's Wednesday.
26:28
Speaker 4: It feels like it should be Friday already.
26:29
Speaker 2: I don't know what's going on in the space time continuum,
26:32
Speaker 2: but this piece might have the key to it. So
26:34
Speaker 2: Alphabet on Tuesday yesterday announced that they had a quantum
26:39
Speaker 2: computing breakthrough. Now, if you're sitting there listening wondering, Chuck,
26:44
Speaker 2: what is quantum computing? The best way I can explain
26:47
Speaker 2: it is this. A typical computer uses at this point
26:51
Speaker 2: billions of transistors within its chips in order to compute
26:56
Speaker 2: different data. The way it does so is by having
26:59
Speaker 2: each transition either open or closed at any particular point
27:03
Speaker 2: in time, which allows it to get, you know, with
27:05
Speaker 2: billions of transistors, different outcomes, and it can calculate.
27:09
Speaker 3: Based that's exactly one zero, one zero, correct.
27:15
Speaker 4: But a transistor can either be open or closed. With
27:19
Speaker 4: quantum computing, the premise of it is that a it's
27:23
Speaker 4: not really a transistor. What they call them are cubits.
27:26
Speaker 2: A cubit can both be open and closed at the
27:29
Speaker 2: exact same time, and so as opposed to having to
27:33
Speaker 2: go in sequence one zero zero one one one zero zero,
27:38
Speaker 2: it can do.
27:39
Speaker 3: All that at against ventriloquist mouth.
27:41
Speaker 4: These are the ventriloquists of computers.
27:46
Speaker 3: That was so stupid correct, We're gonna sorry, sorry, serious subject, but.
27:50
Speaker 4: The primary subject is that you can go through all
27:54
Speaker 4: of those states all at once, as opposed to having
27:57
Speaker 4: to go through them in sequence, so you can do
27:58
Speaker 4: things much more quickly.
28:00
Speaker 2: Now, the reason that this has been hard to actually
28:03
Speaker 2: do is twofold. The first is actually building the things
28:07
Speaker 2: that like if you actually google just images of quantum computers,
28:10
Speaker 2: they kind of have a very like steampunk aesthetic to them,
28:14
Speaker 2: Like it's a bunch of copper tubes wrapped in circles
28:17
Speaker 2: and stuff feeding into like a central mind. It's it's
28:20
Speaker 2: very much like if.
28:24
Speaker 3: Oh, yeah, that's what comes up, looks like a chandelier.
28:27
Speaker 3: It looks like a steam chandelier.
28:29
Speaker 4: So it's got that vibe to it.
28:31
Speaker 2: So actually, the other problem is that there's a huge
28:35
Speaker 2: error rate in the computing and so it's kind of like, well,
28:38
Speaker 2: are we actually getting anything meaningful or not because it's hard.
28:42
Speaker 3: To get well.
28:44
Speaker 4: It's hard to get something to be open and closed
28:46
Speaker 4: at the same time.
28:48
Speaker 3: Tell me about it.
28:49
Speaker 4: It's something that we've all struggled with.
28:52
Speaker 2: So Google announced yesterday that they have a chip called
28:56
Speaker 2: Willow that they said is much faster and has much
29:00
Speaker 2: better error detection capability than previous chips. The chip has
29:04
Speaker 2: one hundred cubits, but Google's plan to eventually build a
29:07
Speaker 2: system with a million cubits. Why not they then, And
29:11
Speaker 2: this is again just the fact that this is the
29:14
Speaker 2: fourth paragraph in the CNBC article that talk about burying
29:17
Speaker 2: the lead. Will brings us closer to running practical, commercially
29:21
Speaker 2: relevant algorithms that can't be replicated on conventional computers. Google
29:25
Speaker 2: wrote in a blog post, adding that the experiment is
29:29
Speaker 2: evidence that suggests that reality is comprised of parallel universes.
29:33
Speaker 4: Whoops, wow, talk.
29:34
Speaker 2: About totally highly Everyone's like, oh a, Google's stock is
29:39
Speaker 2: up six percent yesterday, by the way, not even like
29:41
Speaker 2: realizing that. Hey, Google said we might not be able
29:44
Speaker 2: to make any money off this for decades, so you know,
29:47
Speaker 2: talk about efficient market hypothesis. Good, Hey, We've got this
29:50
Speaker 2: great chip that might do something decades from now.
29:52
Speaker 4: Okay, at six percent to Google's market cap. But by
29:56
Speaker 4: the way, we might have also unlocked the fact that
29:58
Speaker 4: they are a parallel universe and the variant of Tucker
30:03
Speaker 4: that is you know, eight feet tall and has three noses,
30:07
Speaker 4: is gonna come through tomorrow?
30:09
Speaker 3: Is he wearing that shirt?
30:12
Speaker 2: I mean, I just think the fact that the parallel
30:14
Speaker 2: University is a little like.
30:16
Speaker 3: It's like the good news as we cracked it, bad
30:18
Speaker 3: news as we opened a portal to a parallel universe
30:20
Speaker 3: of evil being.
30:21
Speaker 4: Chuck with hair is coming and you're not gonna want
30:23
Speaker 4: to see that. It's just man'.
30:28
Speaker 3: That's it is pretty cool though, even though I understand
30:30
Speaker 3: none of it.
30:31
Speaker 2: It's I understand about one percent. I understand enough to
30:34
Speaker 2: be able to explain how it works. Basically, I have
30:37
Speaker 2: no idea how it works in practice, no idea how
30:40
Speaker 2: it works in practice.
30:42
Speaker 4: Yeah. This is also kind of the sad thing.
30:44
Speaker 2: About where we're going with really high tech stuff these
30:47
Speaker 2: days is look back in the nineteen eighties, Steve Jobs
30:51
Speaker 2: and Steve Wasney, like they got together in their garage.
30:52
Speaker 2: They're like, hey, let's build a computer. You can't get
30:55
Speaker 2: together in your garage and build a quantum computer. First
30:59
Speaker 2: of all, we're you're gonna the parts for it. Second,
31:02
Speaker 2: what if you opened that parallel universe door in your garage.
31:06
Speaker 2: In your garage, just unplug it and plug it back
31:08
Speaker 2: in I'm sure, though, well, what if you got a
31:11
Speaker 2: different one? Then it sounds like there's more than one
31:14
Speaker 2: of these, so I don't know. It's kind of wild
31:19
Speaker 2: that twenty twenty four, at the end of the two
31:21
Speaker 2: years ago, it was Hey, here's chat GPT.
31:23
Speaker 4: You can make it.
31:24
Speaker 2: You know, it can make cat memes for you. Twenty
31:27
Speaker 2: twenty four we made a computer that detected parallel universes. Oh,
31:32
Speaker 2: let's get to twenty five. Then quick break here, we'll
31:35
Speaker 2: have some stack roulette after.
31:36
Speaker 1: This breaking business and financial news first throughout the day.
31:41
Speaker 1: Only here on the Financial Exchange Radio Network, find daily
31:46
Speaker 1: interviews and full shows of the Financial Exchange on how
31:49
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31:52
Speaker 1: you might have missed. This is the Financial Exchange Radio Network.
32:08
Speaker 4: Mark, what do you got for stack roulet?
32:09
Speaker 3: I'll give you two quickies, Chuck. We talk about core
32:12
Speaker 3: inflation because it strips out the jumpy components that there
32:15
Speaker 3: are other ways to do that. One of them is median,
32:17
Speaker 3: which means you trim trim all the outlies. You take
32:19
Speaker 3: the one in the middle as also trim mean. We
32:22
Speaker 3: did get median and trim mean. One of the Fed
32:24
Speaker 3: banks calculates both of these, and they came in about
32:26
Speaker 3: where Core didn't, for that matter, where Headline did this month.
32:29
Speaker 3: I don't need to bore you with the details other
32:31
Speaker 3: than to say stability seems to be the status quo
32:35
Speaker 3: with respect to inflation. No real progress by these measures either, though,
32:39
Speaker 3: nothing alarming. Either. I could talk about Amazon and the
32:42
Speaker 3: car business, or you can do your thing.
32:44
Speaker 2: I could do my thing, do your thing. I'm gonna
32:46
Speaker 2: talk a little bit about jet Blues. So they, after
32:49
Speaker 2: not being able to buy what was it Spirit Airlines,
32:53
Speaker 2: are trying to figure out how to get back to profitability.
32:56
Speaker 2: They've had three billion dollars plus in losses since twenty twenty,
33:01
Speaker 2: and so what they have announced here is that they
33:05
Speaker 2: are trying to go up market, and so they're thinning
33:08
Speaker 2: out some of their routes and so you're seeing, you know,
33:10
Speaker 2: some cancelations of you know, routes that they previously operated on.
33:14
Speaker 2: But they are also adding more trips over to Europe,
33:18
Speaker 2: which obviously have you know, some high end seats that
33:20
Speaker 2: are on those with their lay flat mint seats and
33:23
Speaker 2: things like that. But they also announced today that on
33:27
Speaker 2: domestic flights they are going to begin having a more
33:30
Speaker 2: conventional domestic first class beginning in twenty twenty six, so
33:35
Speaker 2: being able to attract higher paying customers who want more space,
33:38
Speaker 2: more leg room, and things along those lines. So this
33:42
Speaker 2: to me is, you know, when combined with what we're
33:45
Speaker 2: seeing from Southwest Airlines, it's basically a concession from the
33:51
Speaker 2: airlines right now that hey, the budget airline is not
33:56
Speaker 2: working with today's economics. And that's a pretty stark viversal
34:00
Speaker 2: from where we were twenty years ago, where in the
34:03
Speaker 2: two thousands the whole trend was, hey, Jet Blue and
34:08
Speaker 2: Southwest and Spirit are eating the legacy players lunch. And
34:11
Speaker 2: I mean like you had the big guys after nine
34:13
Speaker 2: to eleven again that decade after Granted, part of it
34:16
Speaker 2: was nine to eleven, and part of it was, you know,
34:17
Speaker 2: these upstarts, but you had bankruptcies left and right that
34:20
Speaker 2: ended up resulting in this wave of consolidation that's gotten
34:23
Speaker 2: us to where we are because the big guys couldn't
34:25
Speaker 2: compete with the low cost carriers. And now you have
34:29
Speaker 2: the low cost carriers pretty much saying we got to
34:31
Speaker 2: turn into the big guys in order to compete.
34:33
Speaker 3: Today you're seeing this and you tell me if I'm
34:36
Speaker 3: wrong here in other industries too, where firms decide to
34:38
Speaker 3: focus on higher margin I'll just call it products or
34:41
Speaker 3: product lines. And part of that is a response to
34:45
Speaker 3: current conditions. Part of it might be the recognition that
34:49
Speaker 3: if austerity is the order of the day, big federal
34:51
Speaker 3: government spending cuts, for example, and perhaps slower economic growth
34:56
Speaker 3: over the next decade, you might have to focus on higher,
34:58
Speaker 3: more affluent, more profitable consumers, whether it's car manufacturers or
35:04
Speaker 3: airlines or maybe others that you've come across. As you
35:07
Speaker 3: I'm going with talk about these stories.
35:08
Speaker 4: Demographics being a key factor here as well. There's that, Yeah,
35:12
Speaker 4: you got all.
35:13
Speaker 2: These boomers and I know, I know boomers listening. Are
35:15
Speaker 2: you know of various different economic stripes. You got a
35:19
Speaker 2: lot of boomers with a lot of money, and they're retiring,
35:22
Speaker 2: and they have money to spend. They don't if they
35:26
Speaker 2: have the money, they don't want to be sitting jammed
35:30
Speaker 2: in back in economy class if they.
35:33
Speaker 4: Can avoid it, of course.
35:34
Speaker 2: And so if you have all this money that is
35:37
Speaker 2: now tied to the stock market and not tied to
35:41
Speaker 2: you know, how much income a person is making year
35:43
Speaker 2: to year? Okay, like these are boomers that are saying, hey,
35:48
Speaker 2: I got ten to fifteen years where I'm going to
35:50
Speaker 2: be able to spend this money enjoying like what I
35:52
Speaker 2: do before. I'm not able to do that anymore. Great,
35:57
Speaker 2: let's spend it. And I think that's a huge thing
35:59
Speaker 2: that we need to factor in in terms of not
36:03
Speaker 2: only just these business decisions, but also hey, how do
36:06
Speaker 2: things like monetary policy, how do their impact shift in
36:09
Speaker 2: today's economy compared to what it used to be, both
36:12
Speaker 2: in terms of where's the consumption coming from? And you know,
36:15
Speaker 2: we've talked at other times about hey, what are we
36:18
Speaker 2: producing and how is that, you know, impacted by monetary
36:20
Speaker 2: policy in different ways than it used to be.
36:23
Speaker 4: I think the.
36:24
Speaker 2: Rise of retired boomers is something that is absolutely a
36:27
Speaker 2: factor in both of these things.
36:29
Speaker 3: Yeah, makes sense.
36:30
Speaker 4: Okay, what else you got?
36:31
Speaker 3: Thank you? Would you buy a car from Amazon.
36:34
Speaker 4: Like a like with an Amazon logo on it?
36:38
Speaker 3: I'm sorry, through their website it could.
36:39
Speaker 4: Be made, Oh so not an Amazon car?
36:41
Speaker 3: So Hundai for examples. Part have you guys heard about
36:43
Speaker 3: this is I don't claim to be an expert.
36:46
Speaker 5: We've talked about here before, but the official launch was yesterday.
36:49
Speaker 3: Okay, so you can buy what a Hyundai now on
36:51
Speaker 3: Amazon in certain markets including Boston? Would you do it?
36:58
Speaker 3: Can you return it?
37:00
Speaker 4: Probably just ship it back on it and we don't
37:04
Speaker 4: accept return. Take it over to the Whole Foods and stick
37:06
Speaker 4: it in the way.
37:07
Speaker 3: What all the advantages of doing this versus going to
37:09
Speaker 3: a dealer's website and doing most of the transaction online
37:12
Speaker 3: with the sort of dedicated expert.
37:14
Speaker 5: Saves the nuisance of going to a car dealer.
37:17
Speaker 3: But they they've streamlined that process a lot. I'm just wondering,
37:20
Speaker 3: what are the advantages You're buying through a trusted seller Amazon,
37:24
Speaker 3: but if you buy through one of our local dealer networks,
37:27
Speaker 3: they're presumably a trusted as well. I just don't know
37:29
Speaker 3: what the what what need are they trying to meet?
37:30
Speaker 2: And ultimately, all they're doing is taking the dealer inventory
37:33
Speaker 2: and putting it on right their site, So it's just
37:36
Speaker 2: another way to aggregate.
37:37
Speaker 3: It, which dealers already do.
37:39
Speaker 2: So Yeah, I would have to really spend some time
37:44
Speaker 2: analyzing the pricing, you know, the service contracts, because a
37:48
Speaker 2: lot of new cars now come with service contracts that
37:50
Speaker 2: are built in. Is Amazon's better or worse than anywhere else?
37:55
Speaker 2: It's I'd have to spend some real time figuring out
37:58
Speaker 2: what you get from this.
38:00
Speaker 4: I I really don't know.
38:03
Speaker 2: I'm not saying I wouldn't buy a car from Amazon,
38:06
Speaker 2: but why from Amazon as opposed to any other dealer
38:09
Speaker 2: or a website.
38:11
Speaker 3: I don't know they're there. It's online. You can type
38:13
Speaker 3: in Hyundai and Amazon and.
38:15
Speaker 2: I'm getting I'm getting all the Herb Chambers listings right now.
38:19
Speaker 3: I just bought one.
38:20
Speaker 4: Oh congratulations. Quick break here. We've got to actually break
38:23
Speaker 4: for the rest of the day.
38:23
Speaker 2: We'll see you tomorrow on the Financial Exchange