Latest / Masters in Business / BONUS: Muddy Waters Capital Founder Carson Block

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BONUS: Muddy Waters Capital Founder Carson Block · Masters in Business

• 0:02
  Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. This is Masters in
• 0:11
  Speaker 1: Business with Barry Ritholts on Bloomberg Radio.
• 0:17
  Speaker 2: This week we have an extra special bonus episode live
• 0:22
  Speaker 2: from future Proof. My conversation with Muddy Waters Carson Block
• 0:28
  Speaker 2: really a fascinating conversation, not only about how he developed
• 0:34
  Speaker 2: an interest in shorting fraudulent equities and companies, but how
• 0:39
  Speaker 2: his firm has evolved into a comprehensive research shop and
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  Speaker 2: a long short hedge fund. I thought the conversation was fascinating,
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  Speaker 2: and I think you will also, with no further ado.
• 0:53
  Speaker 2: My conversation with Muddy Waters Carson Block live at Citywide
• 0:59
  Speaker 2: future Proof Miami. I'm so fascinated by your career, what
• 1:05
  Speaker 2: you've done, what you've built.
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  Speaker 3: I first kind of became aware of you. I don't know.
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  Speaker 2: It seems like it was a long time ago with
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  Speaker 2: the reverse Chinese mergers and Sino Forrest. Then wait, China
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  Speaker 2: is doing what. I don't understand any of this. Tell
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  Speaker 2: us how you kind of fell into that aspect of
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  Speaker 2: markets and how you ended up becoming an activist short seller.
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  Speaker 4: I will try to nutshell this, but I grew up
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  Speaker 4: in investing. My father was an equity analyst and was
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  Speaker 4: working with him from ninety nine to two alongside covering microcaps.
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  Speaker 4: And we were just getting lied to incessantly by these managements.
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  Speaker 4: And back then they had forty five days to file
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  Speaker 4: their forms for so let me take them on non
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  Speaker 4: deal roadshow to meet institutions. Stock would go up and
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  Speaker 4: let me'd find out later that hit the bid. So
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  Speaker 4: this is the same time that you had the largest
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  Speaker 4: companies in the world like Enron, WorldCom Health South Hidelphia
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  Speaker 4: blowing up an accounting scandals. So my my realization around
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  Speaker 4: two thousand and two, I was really demoralized. It's like, look,
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  Speaker 4: I want to be an investor, but this is this
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  Speaker 4: market is riddled with financial predators from top to bottom.
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  Speaker 4: How do I protect myself against that? So I went
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  Speaker 4: to law school with just this amorphous idea that that
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  Speaker 4: would give me some tools, and you know, fast forward,
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  Speaker 4: decided to practice law, ended up in China. Jones Day
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  Speaker 4: left to start the first self storage business in mainland China.
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  Speaker 4: I don't recommend it, and anyway, I was just sort of,
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  Speaker 4: you know, keep trying to keep that business from failing.
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  Speaker 4: In two thousand and nine, when my father got really
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  Speaker 4: excited about a bunch of these Chinese companies that had
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  Speaker 4: had gone public in the US via reverse merger, and
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  Speaker 4: like I had my own problems, I wasn't really that interested.
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  Speaker 4: But he asked me to look and he asked me
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  Speaker 4: to look at this first one called Orient Paper. And
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  Speaker 4: the first thing he told me he'd been at a
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  Speaker 4: conference that these guys had gone to, and you know
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  Speaker 4: what he's hearing is, oh, you know, chairman Leo, he's
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  Speaker 4: different from other Chinese company chairmen. He doesn't smoke, and
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  Speaker 4: he doesn't chase women. And you know, my father's telling
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  Speaker 4: me this woman, you know, late night in Shanghai, and
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  Speaker 4: I'm like, I'm sure neither of those things is actually true.
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  Speaker 4: But the fact that this is making its rounds at
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  Speaker 4: the conference, somebody is trying to game Western investor psychology.
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  Speaker 4: So that got my attention. Early twenty ten, went up
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  Speaker 4: to see the company and it was a Potemkin factory,
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  Speaker 4: Like I never believed that such a thing could exist,
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  Speaker 4: where at the time it's market cap is one hundred
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  Speaker 4: and fifty million, had just reported one hundred three million
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  Speaker 4: dollars in revenue and the real revenue two to five
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  Speaker 4: million dollars that it was these empty box So I
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  Speaker 4: exposed that with the thirty some ond page report. And
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  Speaker 4: the only reason I did that was I felt like
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  Speaker 4: I was stuck in my business in Shanghai, like a
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  Speaker 4: few hundred people who are leaving their stuff.
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  Speaker 3: In my facility.
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  Speaker 4: The industry did not exist because it's a bad industry
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  Speaker 4: to be in in China, and I don't know, there's
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  Speaker 4: like a power and feeling like you have nothing to lose.
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  Speaker 4: So I just threw the ball as far down the
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  Speaker 4: field as I could wrote that report.
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  Speaker 3: It went viral.
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  Speaker 4: Quickly found out this was systemic, and one year later
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  Speaker 4: Bloomberg's like, oh, he's one of the fifty most influential
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  Speaker 4: in global finance with Ben Bernanki and Warren Buffett, and
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  Speaker 4: it was like, well, yes, of course that's the natural
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  Speaker 4: path from self storage.
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  Speaker 2: That's every thirty page analyst report tends to lead to that.
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  Speaker 2: So it's funny because you and I kind of came
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  Speaker 2: of age in the markets similar period. The dot com
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  Speaker 2: implosion was certainly fundamental to my view of both markets
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  Speaker 2: and short sellers, and then the financial crisis. How do
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  Speaker 2: you look at how the markets have changed over the
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  Speaker 2: ensuing decade, as between QE and zero interest rate policy,
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  Speaker 2: and more recently the Cares Act and the mascul fiscal stimulus.
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  Speaker 2: I grew up thinking short sellers were the ones who
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  Speaker 2: kept the market honest and responsible. That seems to be
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  Speaker 2: a minority of you these days.
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  Speaker 4: Yeah, well, I've come to the view that there's an
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  Speaker 4: inverse relationship between interest rates and the amount of dishonesty
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  Speaker 4: in society. So the lower your rates, the more easy
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  Speaker 4: money is, the more dishonesty you get in society. And
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  Speaker 4: so the emergency monetary policy outlived the emergency. And you
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  Speaker 4: know what I felt is that just each year I've
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  Speaker 4: been doing this, that investors are more and more anesthetized
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  Speaker 4: to Now. The flip side of that is that behaviors
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  Speaker 4: that were once really only present in microcap land will
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  Speaker 4: those bubble up to MidCap land because of the inflation
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  Speaker 4: of market caps. So on one hand, my business has
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  Speaker 4: gotten harder because unless it's something really really egregious, like
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  Speaker 4: people don't care. But then yes, you'll find that type
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  Speaker 4: of behavior now even in mid cap companies, and you
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  Speaker 4: know an environment where and just to be clear, it's
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  Speaker 4: a small minority of companies that are frauds the world's
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  Speaker 4: bigger problem is the gray zone, right, the things where yeah,
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  Speaker 4: nobody's gonna get convicted. Tech you know, lawyers have signed off,
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  Speaker 4: the auditor is okay with it, and that gray zone
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  Speaker 4: behavior whereby you can significantly misrepresent economic reality that is
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  Speaker 4: almost maybe the norm in many respects.
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  Speaker 2: So this secret is to corrupt the attorneys and the
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  Speaker 2: orderers and then it's home free.
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  Speaker 3: Wait, corrupt the attorneys.
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  Speaker 2: Right, So you mentioned microcaps, small cap mid caps. I
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  Speaker 2: read a note of yours not too long ago talking
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  Speaker 2: about the big caps and the megacaps, where so many
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  Speaker 2: people have been calling this a bubble, and so many
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  Speaker 2: people have saying, gee, I'd like to shorten video.
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  Speaker 3: You kind of went out of your way.
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  Speaker 2: To say, hey, maybe one day there's a downside play here,
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  Speaker 2: but this freight train is really difficult to step in
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  Speaker 2: front of. What are your thoughts on on the hyperscalers,
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  Speaker 2: the megacap tech companies?
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  Speaker 3: Three things?
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  Speaker 4: Number one, there are easier better shorts out there than
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  Speaker 4: in video. Number two. The reason why I was making
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  Speaker 4: those comments is that flows have driven so much of this,
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  Speaker 4: Like you have obviously the passive bid, and it squeezes
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  Speaker 4: floats and by squeezing floats. It's not a linear impact
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  Speaker 4: on stock prices. It's a parabolic impact on stock prices
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  Speaker 4: at least of the winners. So the idea that something
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  Speaker 4: is overvalued, that's a reference to its fundamental value. But
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  Speaker 4: I think you have to consider its technical value. And
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  Speaker 4: that's what everybody fails to say when they're criticizing these
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  Speaker 4: things on a fundamental basis.
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  Speaker 3: It's like, well what are the technicals of this? Now?
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  Speaker 3: That's my second point.
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  Speaker 4: My third point is up till one month ago, I
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  Speaker 4: was completely sanguine on the on SMP and markets in
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  Speaker 4: general and the economy. And my view has one eight
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  Speaker 4: And I think the wrong question is well what do
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  Speaker 4: you think of the valuations or stock prices of XYZ
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  Speaker 4: of these AI companies? And the right question is what
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  Speaker 4: is about to happen to society and to the market
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  Speaker 4: as a result of AI. And I and like I
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  Speaker 4: said on this like a month ago, I wouldn't even
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  Speaker 4: refer to these models as a I had this rule.
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  Speaker 4: These are large language models. They are not going to
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  Speaker 4: create new information. They merely process information that's already out there.
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  Speaker 4: Don't call it AI, they're lllms. But I call it
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  Speaker 4: AI now.
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  Speaker 2: Right, they're neither artificial nor intelligence. They're something else. But
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  Speaker 2: given that, and given this one eighty but we're going
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  Speaker 2: to dive right into AI in a minute. But since
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  Speaker 2: you built your reputation before the firm is pivoted into
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  Speaker 2: a full service research shop, both long and short, you've
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  Speaker 2: criticized SPACs, crypto thematic ETFs, NFTs. Where has there been
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  Speaker 2: the biggest destruction of investor wealth in that group?
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  Speaker 4: Well in that group, Okay, so it's a little bit
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  Speaker 4: in vogue. I think to point toward private credit right now,
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  Speaker 4: and the reality is like who knows, right, there's there's
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  Speaker 4: no data.
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  Speaker 3: It's really opaque.
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  Speaker 4: My concerns there, and I recognize that data is not
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  Speaker 4: the plural of anecdote. But in the past few months,
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  Speaker 4: some of the research we've done, I've looked at some
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  Speaker 4: abs issuers and this is not private credit, but I
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  Speaker 4: was really surprised to see as I went down the
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  Speaker 4: rabbit hole of abs issuances that a lot of the
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  Speaker 4: paperwork that should be done to basically show release of
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  Speaker 4: lians of loans that are being securitized and filed publicly,
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  Speaker 4: that paperwork is not being filed publicly and at first,
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  Speaker 4: I thought, oh my god, we've got these guys on fraud.
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  Speaker 4: They're selling off loans that are still encumbered. And I
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  Speaker 4: spoke with a couple of securitization attorneys and they said, no, no, no,
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  Speaker 4: that's market practice. The warehouse lender just provides a letter
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  Speaker 4: saying that the lians are released. It doesn't get filed publicly.
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  Speaker 4: And so I asked each of them, well, what's to
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  Speaker 4: stop the sponsor of the securitization from forging the letter
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  Speaker 4: because he thinks, like, look, the loans are, the ABSs
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  Speaker 4: are already over collateralized. I can double pledge these, you know,
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  Speaker 4: because if the warehouse lender, if it's not public, the
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  Speaker 4: warehouse lender wouldn't know if somebody forged it.
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  Speaker 3: Huh yeah, that's a good point.
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  Speaker 4: And so I when I see that the largest financial
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  Speaker 4: institutions are not dotting eyes and crossing t's.
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  Speaker 3: You know.
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  Speaker 4: I've a conversation with somebody recently who gave me data
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  Speaker 4: point from a private equity firm that's doing a lot
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  Speaker 4: of clos The conversation from somebody who's on the p
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  Speaker 4: side going to the CLO guys is like, hey, so
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  Speaker 4: what do we know about the performance of the underlying loans,
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  Speaker 4: like how are they performing?
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  Speaker 3: Huh? Why did we track that we don't service them?
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  Speaker 3: Like this is.
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  Speaker 4: Reminiscent of right out of the Yeah, this is reminiscent
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  Speaker 4: of some of the behaviors and credit. So then okay,
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  Speaker 4: I combined again, it's not data, these are anecdotes, but
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  Speaker 4: I combine that with also what I noticed starting a
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  Speaker 4: few years ago. You know, every time I talk to
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  Speaker 4: an allocator, you know, because we're actually we run a fund.
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  Speaker 4: We're a hedge fund, so you know, we're talking to
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  Speaker 4: allocators all the time. And you know what do you
• 12:01
  Speaker 4: guys investing in everybody all of a sudden starts saying
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  Speaker 4: private credit, private credit, private credit.
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  Speaker 3: You know.
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  Speaker 4: That also reminds me of the Internet bubble, because the
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  Speaker 4: way I used to think about that as it was
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  Speaker 4: happening is there's too much money chasing too few investable companies.
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  Speaker 4: So I don't think if there are problems in private credit,
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  Speaker 4: Like my first bet is not that it's at Apollo,
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  Speaker 4: But I also know we have looked at the insurance industry,
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  Speaker 4: and so I know a lot of these insurers have
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  Speaker 4: been bought by smaller pe firms. I mean they're basically
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  Speaker 4: using these things to finance their deals. The Ft did
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  Speaker 4: a great article a few Alphaville a few months ago
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  Speaker 4: on the credit ratings agencies. I mean, it's not even
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  Speaker 4: SMP in Moody's. The number one is Egan Jones. So
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  Speaker 4: corporate headquarters is like an eight bedroom house in suburban
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  Speaker 4: Boston literally, and I think they did like two thousand
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  Speaker 4: deals last year that they raided. I mean, if you
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  Speaker 4: lived through the GFC and we're paying attention, you know,
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  Speaker 4: like starting to see some dots connect. So that does
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  Speaker 4: have me worried also, and if that does intersect with
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  Speaker 4: what I think could happen in the labor markets from
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  Speaker 4: AI job displacement, you know, like I know you want
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  Speaker 4: to pivot back to it, but I'm just going to
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  Speaker 4: put it out there. I think it's not unrealistic to
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  Speaker 4: say fifteen percent of knowledge work jobs in the US
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  Speaker 4: in three years are gone. And if it's not three,
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  Speaker 4: it's going to be five. But it might not be fifteen,
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  Speaker 4: it could be twenty twenty five percent. I mean, that's
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  Speaker 4: and I can work through how I got there.
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  Speaker 2: Let's dive deeper into AI. It's both an investible asset
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  Speaker 2: a shortable asset, and a tool that you're using to
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  Speaker 2: run a business. So I want to hit each of
• 13:44
  Speaker 2: those things, starting with how are you using AI as
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  Speaker 2: a tool to manage a business to identify long and
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  Speaker 2: short opportunities? What is true AI not just lms me
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  Speaker 2: for your daily work?
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  Speaker 4: Well, I mean in the past again, since finding religion
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  Speaker 4: just a few weeks ago. I mean, this is something
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  Speaker 4: I've been hammering. Most of my employees have worked for
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  Speaker 4: me for over ten years. We're an old firm for
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  Speaker 4: a hedge fund. I mean I used to joke that
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  Speaker 4: this is probably true that if you look at trips
• 14:20
  Speaker 4: and falls per dollar of AUM, we maybe are the
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  Speaker 4: highest in the world. And that was kind of funny
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  Speaker 4: to say until I started saying, guys, why are you
• 14:30
  Speaker 4: literally taking months to put together one hundred and fifty
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  Speaker 4: page slide decks to discuss something internally? Stick it in
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  Speaker 4: the machine. And so one of my analysts, my longest
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  Speaker 4: serving employee, ex ex auditor, super bright, but al we
• 14:50
  Speaker 4: struggled with communication. I mean one of my skills was
• 14:54
  Speaker 4: over months, weeks or months, many many hours trying to
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  Speaker 4: draw out of her the patterns that she sees. But
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  Speaker 4: she's just unable to elucidate. Now she's just pumping out
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  Speaker 4: the memoranda from Claude, and I'm like, wow, this is
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  Speaker 4: I mean, Cindy, this has saved us, like, you know,
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  Speaker 4: probably five weeks of you know, like frustrated conversations in
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  Speaker 4: the conference room like this. So from that perspective, it's helping,
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  Speaker 4: I think hurting a little bit. You know. I've always
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  Speaker 4: felt that we have an edge as active as short
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  Speaker 4: sellers over our competition in terms of how I write
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  Speaker 4: and communicate.
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  Speaker 3: Like that edge has gone.
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  Speaker 4: I mean, you can go to Claude and say, hey,
• 15:36
  Speaker 4: you know, write this up as a short report in
• 15:39
  Speaker 4: the voice of.
• 15:39
  Speaker 3: Carson Block, and you know it's not bad. I mean,
• 15:43
  Speaker 3: i it gets you a lot of the way there.
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  Speaker 2: So so let me flip the question on you and
• 15:49
  Speaker 2: ask how has AI changed the fraudster's toolkit? What can
• 15:56
  Speaker 2: Claude do for a fabricated document, deep fakes, fake video,
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  Speaker 2: fake voice, fake docs, fake everything. Has it just become
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  Speaker 2: an arms race between the good guys and the bad guys?
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  Speaker 4: Well, look, I mean the tools for forgery never really
• 16:14
  Speaker 4: needed to be that sophisticated. I Mean one of my
• 16:16
  Speaker 4: favorite examples of that was the Peregrine Financial That guy
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  Speaker 4: had a post office box and an ink chat and
• 16:24
  Speaker 4: that's how he forged his auditor letters. And you know
• 16:27
  Speaker 4: that was a few hundred million.
• 16:28
  Speaker 2: But Bernie Madoff did not exactly use the most sophisticated technology.
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  Speaker 4: Yeah, I think the thing that will get to be
• 16:36
  Speaker 4: more interesting is if you're a company CEO and you
• 16:40
  Speaker 4: know you're kind of you know, like you're pumping your
• 16:43
  Speaker 4: stock price, you're monetizing it and hitting the bid. I
• 16:46
  Speaker 4: think the more interesting thing is querying it. You know,
• 16:50
  Speaker 4: if I were the CEO of XYZ company, what would
• 16:53
  Speaker 4: a short sellar focus on?
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  Speaker 3: You know, like what should I do about that?
• 16:57
  Speaker 4: So I think that we're going to get in this
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  Speaker 4: cat and mouse game of preemption and reaction. But I mean,
• 17:05
  Speaker 4: at the end of the day, I mean, if you're
• 17:07
  Speaker 4: you know, if you're just ramping your stock price and
• 17:09
  Speaker 4: mortgaging your future, and I think as active as short
• 17:12
  Speaker 4: sellers will still get there, but you could at least
• 17:15
  Speaker 4: dig a wider moat around your you know, around what
• 17:19
  Speaker 4: you're doing if you use these AI tools.
• 17:23
  Speaker 2: So I always think of short sellers like Jim Chainos
• 17:27
  Speaker 2: and the original guys who who really pioneered forensic accounting
• 17:33
  Speaker 2: as being so deep into the documents. How useful are
• 17:37
  Speaker 2: tools like Claude Cowork as a forensic accountant to help
• 17:43
  Speaker 2: either identify patterns in every SEC filing or honing in
• 17:50
  Speaker 2: on a specific company's filings and seeing what doesn't smell
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  Speaker 2: right for me.
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  Speaker 3: That's a little TBD. I don't know yet.
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  Speaker 4: I mean, I'm not sure that you can just upload
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  Speaker 4: a ten and say, oh, you know, what's dodgy about this?
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  Speaker 4: I mean, first of all, one of the one of
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  Speaker 4: the secrets. It's not a secret, but of what we
• 18:09
  Speaker 4: do is we obtain documents from places people never look.
• 18:14
  Speaker 4: So again, like we're you know, we're pulling UCC files
• 18:18
  Speaker 4: to look at asset securitizations. We love companies that have
• 18:22
  Speaker 4: overseas subsidiaries because most overseas jurisdictions there are publicly filed
• 18:27
  Speaker 4: financial statements.
• 18:29
  Speaker 3: So we'll pull those and upload them.
• 18:31
  Speaker 4: And then also, I'm sure it could really help connect
• 18:33
  Speaker 4: the dots with people. I mean right now or up
• 18:35
  Speaker 4: till now, we've had to rely on memory, like oh wait, yeah,
• 18:39
  Speaker 4: this dude. You know, we've looked at fifty eight entities.
• 18:42
  Speaker 4: This dude was in that entity. Oh interesting. So the
• 18:45
  Speaker 4: AI is going to get rid of it's going to
• 18:48
  Speaker 4: make that part easy. But you still have to go
• 18:50
  Speaker 4: out and do the legwork. And you know, a lot
• 18:52
  Speaker 4: of times you have to send people in person to
• 18:54
  Speaker 4: do document retrieval. So I don't think it's as simple
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  Speaker 4: as you know, Hey, I woke up today and I
• 19:00
  Speaker 4: want to be an activist short seller, like you know,
• 19:03
  Speaker 4: which you know, claude, which company should I write about?
• 19:05
  Speaker 4: And you know, what's my thesis? Like, you have to
• 19:08
  Speaker 4: still do a lot of leg work. But the accounting
• 19:10
  Speaker 4: stuff your claude has demonstrated internally again, turning my you know,
• 19:16
  Speaker 4: my accounting analysts, the former auditor, turning her poorly expressed
• 19:21
  Speaker 4: thoughts into actual words, you know. And of course she's
• 19:25
  Speaker 4: iterating with it. No, no, no, that's not what I mean.
• 19:28
  Speaker 4: But it's got real accounting knowledge. Oh well, according to
• 19:30
  Speaker 4: ASC blah blah blah, and this does not meet the
• 19:32
  Speaker 4: definition of the da da da N wow.
• 19:34
  Speaker 3: I mean, that's it's really interesting.
• 19:36
  Speaker 4: I mean, look, I think at the end of the day,
• 19:38
  Speaker 4: part of the edge of being an active as short
• 19:40
  Speaker 4: seller is the willingness to be sued, or the tolerance
• 19:44
  Speaker 4: for being sued. So I'm not worried that a bunch
• 19:46
  Speaker 4: of people are going to run out and like commoditize this.
• 19:49
  Speaker 4: And and I think at the end of the day,
• 19:50
  Speaker 4: also having a brand where if everybody can produce skeptical
• 19:56
  Speaker 4: you know pieces, it's also knowing when the model is
• 20:00
  Speaker 4: kind of bullying you, right, like no, no, because that
• 20:03
  Speaker 4: happens too. I mean, these things are sickophantic, like wow,
• 20:06
  Speaker 4: that's brilliant. Of course it's a fraud person, you know, no.
• 20:10
  Speaker 2: To say nothing of double checking for hallucinations. And a
• 20:15
  Speaker 2: bunch of lawyers who have been using AI keep getting
• 20:18
  Speaker 2: into trouble because it's citing cases that don't really exist,
• 20:22
  Speaker 2: and the judge's clerk, also using AI, discovers these cases
• 20:26
  Speaker 2: don't exist. But you mentioned a word that's really fascinating.
• 20:30
  Speaker 2: You mentioned edge. If all the participants in the markets
• 20:37
  Speaker 2: long and short are using the same tools, is there
• 20:41
  Speaker 2: any edge to be found that had there or is
• 20:43
  Speaker 2: it really about how you're applying these tools where the
• 20:46
  Speaker 2: edge comes from.
• 20:47
  Speaker 3: That's an interesting question.
• 20:48
  Speaker 4: I mean, look, on the on the short side, you
• 20:50
  Speaker 4: only make money if people care, right, And so I
• 20:53
  Speaker 4: think that's been the problem that most so since the GFC.
• 20:59
  Speaker 4: Almost everybody who is running money principally focused on short
• 21:03
  Speaker 4: strategies has gone out of business. I mean some you know,
• 21:06
  Speaker 4: they rode off into the sunset. You know, I made
• 21:08
  Speaker 4: a bunch of money, most carried out, you know. I
• 21:12
  Speaker 4: think the problem that a lot of the short sellers
• 21:15
  Speaker 4: have had and I had this too, you know, and
• 21:18
  Speaker 4: have if I have to actively correct for it is
• 21:21
  Speaker 4: you try. You tend to view the world the way
• 21:23
  Speaker 4: it should be, not the way it is. And so
• 21:26
  Speaker 4: that's the problem. Like when people short you know, Tesla
• 21:30
  Speaker 4: because you know Elon Musk this and that, like nobody
• 21:33
  Speaker 4: cares right and that that's that's the thing. So I
• 21:37
  Speaker 4: think you to be good on the short side, you
• 21:41
  Speaker 4: have to understand why people are buying the stock, and
• 21:44
  Speaker 4: you have to have a view that goes directly against
• 21:48
  Speaker 4: that or that undermines that thesis. And I think so
• 21:50
  Speaker 4: much of the time that doesn't happen. So I don't know.
• 21:54
  Speaker 4: I think the I don't know that this erodes the
• 21:57
  Speaker 4: edge of just of judgment when it comes the longside
• 22:01
  Speaker 4: or short side. And then on the long side, I
• 22:03
  Speaker 4: mean kind of buy what the smart money is buying
• 22:05
  Speaker 4: seems to have worked like I hate to say it,
• 22:07
  Speaker 4: but you know, again, technicals versus fundamental value, the technical
• 22:11
  Speaker 4: value of something. You know, I don't know that AI
• 22:15
  Speaker 4: helps tongue with that right now, but it certainly can.
• 22:18
  Speaker 2: Let's talk about AI pretenders, and I'm pulling something else
• 22:22
  Speaker 2: you had written a while ago, and there's a little
• 22:25
  Speaker 2: bit of a rhyme with late nineties every company edit
• 22:29
  Speaker 2: a dot com and their stock would see a pop.
• 22:32
  Speaker 2: What are you noticing amongst the fake AI stories, the
• 22:36
  Speaker 2: fake pivots, the companies that really have nothing whatsoever to
• 22:40
  Speaker 2: use to do with AI other than two or three
• 22:43
  Speaker 2: people who work for the company have a Perplexity app
• 22:46
  Speaker 2: on their phone. Tell us about the narrative of AI pretenders.
• 22:50
  Speaker 4: Well, I look, I think if all of a sudden
• 22:52
  Speaker 4: the company has started talking. So I first did this
• 22:57
  Speaker 4: shortly after I started on the short side. Cloud became
• 23:01
  Speaker 4: the thing, right, and so then I saw some companies
• 23:05
  Speaker 4: that had just done a global find and replaced, like,
• 23:08
  Speaker 4: you know, find this, replace it with cloud. And so
• 23:11
  Speaker 4: if you see that with AI in a company's filings
• 23:15
  Speaker 4: and in their statements, then yeah, I mean they're they're
• 23:18
  Speaker 4: probably a pretender. I mean, I think it's pretty clear.
• 23:22
  Speaker 4: You know, AI, real AI requires scale. I mean, whether
• 23:25
  Speaker 4: you're on the process on the hardware side, or you're
• 23:29
  Speaker 4: you know, or you're actually producing the AI models. So
• 23:32
  Speaker 4: I don't know everybody who's like AI enabled it, And look,
• 23:36
  Speaker 4: I'm out over my skis here because I don't really
• 23:38
  Speaker 4: understand the technology. But everybody who's AI enabled, it's like, well,
• 23:41
  Speaker 4: what's what's the foundation? You know, if you are an
• 23:44
  Speaker 4: AI enabled this, what are you running? Are you running perplexity,
• 23:47
  Speaker 4: Claude chat GPT? And if you're like, well I made
• 23:50
  Speaker 4: it myself, like no, man, like I'm not going to
• 23:53
  Speaker 4: buy that, you know, like these things have cost way
• 23:56
  Speaker 4: too many billions of dollars to develop for you to
• 23:58
  Speaker 4: be able to vibe code.
• 23:59
  Speaker 2: You're short Sellers are always looking for a downside catalyst
• 24:05
  Speaker 2: when you start thinking about the megacaps, the hyperscalers, or
• 24:09
  Speaker 2: anybody else that's really blown up in value and in
• 24:13
  Speaker 2: price that's created a little bit of an air pocket.
• 24:16
  Speaker 2: Has that catalyst come in yet or is there something
• 24:20
  Speaker 2: off in the future that's gonna lead people to say, hey,
• 24:24
  Speaker 2: this has gone too far, we need to take something
• 24:26
  Speaker 2: off the table.
• 24:27
  Speaker 4: Well, if you take my view that a lot of
• 24:30
  Speaker 4: these names have traded based on their technical values as
• 24:34
  Speaker 4: opposed to fundamental. Then you need to get into okay,
• 24:38
  Speaker 4: like what are the underlying technicals here. So I'm a
• 24:42
  Speaker 4: fan of a guy named Mike Green, So I think
• 24:45
  Speaker 4: Mike is going to prove to be really prophetic. And
• 24:48
  Speaker 4: so what he's been saying since maybe eighteen or nineteen
• 24:52
  Speaker 4: is that so passive has broken the market. You know,
• 24:56
  Speaker 4: don't disagree, but that when the flows, actually the buying
• 25:01
  Speaker 4: from the target date funds tapers off and then you
• 25:05
  Speaker 4: get net outflows, that's when you get as he calls it,
• 25:10
  Speaker 4: or was calling it nineteen twenty nine magnitude crash at
• 25:13
  Speaker 4: you know, filling the year, you know, filling the blank
• 25:16
  Speaker 4: with the year speed. And that's what scares me about
• 25:20
  Speaker 4: AI because you know, like I said, if I if
• 25:24
  Speaker 4: this thesis is correct, that then three years or a
• 25:28
  Speaker 4: few years, fifteen percent of knowledge workers have lost their jobs.
• 25:32
  Speaker 4: It's not like they're going to find new jobs. It's
• 25:34
  Speaker 4: not like you know, fiscal or monetary stimulus creates new
• 25:37
  Speaker 4: knowledge work jobs. They are going to and they all
• 25:41
  Speaker 4: have college debt, mortgages, car leases. Eventually they're going to
• 25:47
  Speaker 4: start hitting up their four oh one k's and so
• 25:50
  Speaker 4: first they stop contributing as they're laid off. Then they
• 25:53
  Speaker 4: need that money and they start taking early redemptions. And
• 25:57
  Speaker 4: so if Mike Green is correct, when that happens, there's
• 26:02
  Speaker 4: nobody there to catch the falling knife, and the technicals
• 26:05
  Speaker 4: have basically for you know better, since the GFC just
• 26:10
  Speaker 4: created this tremendous amount of air, that's when it's really
• 26:15
  Speaker 4: time to panic, because that that's what I think, that's
• 26:19
  Speaker 4: what's going to make his thesis. That's what's going to
• 26:21
  Speaker 4: test his thesis. And if you asked me five weeks ago,
• 26:26
  Speaker 4: you know, did I think that we're in any danger
• 26:29
  Speaker 4: anything on the horizon in terms of seeing you know,
• 26:32
  Speaker 4: reversal of four oh one K flows and rise significant
• 26:36
  Speaker 4: rise in unemployment, I would have said no.
• 26:38
  Speaker 3: I was.
• 26:39
  Speaker 4: I was completely sanguine five weeks ago, and I've, like
• 26:43
  Speaker 4: I said, I've won eight So.
• 26:45
  Speaker 2: I can't leave on that much of a downbeat note.
• 26:48
  Speaker 2: So for the last question, you run along short funds.
• 26:53
  Speaker 2: If that's the downside of AI, if that's the negative
• 26:57
  Speaker 2: we're seeing in the world of why collar work, what's
• 27:02
  Speaker 2: the long side of the portfolio, What looks attractive through
• 27:07
  Speaker 2: and on the other side of whatever happens with either
• 27:10
  Speaker 2: the AI thesis or Green's thesis.
• 27:13
  Speaker 4: Well, okay, the tough thing is there obviously are going
• 27:17
  Speaker 4: to be companies that benefit from AI, right, and so
• 27:20
  Speaker 4: they're the hyperscalers. But if you have but if they're
• 27:23
  Speaker 4: in the index, which they all are, and they're major
• 27:25
  Speaker 4: parts of the index, and you have index fund flows,
• 27:29
  Speaker 4: well the bull cases that over the long term they're
• 27:31
  Speaker 4: going to be you know, there's gonna be a great
• 27:33
  Speaker 4: buying opportunity. So I'm not sure that's where you hide out.
• 27:36
  Speaker 4: I mean, what we've been doing for the past month
• 27:40
  Speaker 4: is creating a set of what I think are highly
• 27:43
  Speaker 4: convexed trades in the book, especially basically shorten credit. So
• 27:49
  Speaker 4: it's not like the lead up to the GFC there's
• 27:51
  Speaker 4: not you know, deep CDs market, but I think, I mean,
• 27:55
  Speaker 4: credit spreads are stupidly tight and credit ball is stupid
• 28:00
  Speaker 4: Lee Love. So to me, you want convexity and there
• 28:04
  Speaker 4: are lots of ways to pay it where you're capping
• 28:06
  Speaker 4: your potential loss. That's how we're that's how we're approaching it.
• 28:09
  Speaker 4: So like and look, I hope this doesn't play out.
• 28:11
  Speaker 4: I mean, I be cause I don't have like a
• 28:13
  Speaker 4: plan B or C after AI takes, you know, like
• 28:17
  Speaker 4: my job. But you know, at least as it does
• 28:20
  Speaker 4: play out, we're we're positioning for it.
• 28:22
  Speaker 2: That was my conversation live at future Proof Citywide, Miami
• 28:27
  Speaker 2: with Muddy Waters Carson Block. If you enjoy this conversation,
• 28:31
  Speaker 2: well check out any of the six hundred we've done
• 28:34
  Speaker 2: over the past almost fourteen years. You can find those
• 28:38
  Speaker 2: at iTunes, YouTube, Spotify, Bloomberg, wherever you get your favorite
• 28:44
  Speaker 2: podcasts from. I would be remiss if I didn't thank
• 28:47
  Speaker 2: the crack team that helps put these conversations.
• 28:50
  Speaker 3: Together each week.
• 28:53
  Speaker 2: Alexis Noriega is my video producer. Anna Luke is my
• 28:57
  Speaker 2: regular producer. Sean Russo is my head of research. I'm
• 29:00
  Speaker 2: Barry Ritolts. You've been listening to Masters in Business on
• 29:04
  Speaker 2: Bloomberg Radio.