WEBVTT - BONUS: Muddy Waters Capital Founder Carson Block

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<v Speaker 1>Bloomberg Audio Studios, Podcasts, radio news. This is Masters in

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<v Speaker 1>Business with Barry Ritholts on Bloomberg Radio.

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<v Speaker 2>This week we have an extra special bonus episode live

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<v Speaker 2>from future Proof. My conversation with Muddy Waters Carson Block

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<v Speaker 2>really a fascinating conversation, not only about how he developed

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<v Speaker 2>an interest in shorting fraudulent equities and companies, but how

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<v Speaker 2>his firm has evolved into a comprehensive research shop and

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<v Speaker 2>a long short hedge fund. I thought the conversation was fascinating,

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<v Speaker 2>and I think you will also, with no further ado.

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<v Speaker 2>My conversation with Muddy Waters Carson Block live at Citywide

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<v Speaker 2>future Proof Miami. I'm so fascinated by your career, what

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<v Speaker 2>you've done, what you've built.

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<v Speaker 3>I first kind of became aware of you. I don't know.

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<v Speaker 2>It seems like it was a long time ago with

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<v Speaker 2>the reverse Chinese mergers and Sino Forrest. Then wait, China

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<v Speaker 2>is doing what. I don't understand any of this. Tell

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<v Speaker 2>us how you kind of fell into that aspect of

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<v Speaker 2>markets and how you ended up becoming an activist short seller.

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<v Speaker 4>I will try to nutshell this, but I grew up

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<v Speaker 4>in investing. My father was an equity analyst and was

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<v Speaker 4>working with him from ninety nine to two alongside covering microcaps.

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<v Speaker 4>And we were just getting lied to incessantly by these managements.

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<v Speaker 4>And back then they had forty five days to file

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<v Speaker 4>their forms for so let me take them on non

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<v Speaker 4>deal roadshow to meet institutions. Stock would go up and

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<v Speaker 4>let me'd find out later that hit the bid. So

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<v Speaker 4>this is the same time that you had the largest

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<v Speaker 4>companies in the world like Enron, WorldCom Health South Hidelphia

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<v Speaker 4>blowing up an accounting scandals. So my my realization around

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<v Speaker 4>two thousand and two, I was really demoralized. It's like, look,

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<v Speaker 4>I want to be an investor, but this is this

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<v Speaker 4>market is riddled with financial predators from top to bottom.

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<v Speaker 4>How do I protect myself against that? So I went

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<v Speaker 4>to law school with just this amorphous idea that that

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<v Speaker 4>would give me some tools, and you know, fast forward,

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<v Speaker 4>decided to practice law, ended up in China. Jones Day

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<v Speaker 4>left to start the first self storage business in mainland China.

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<v Speaker 4>I don't recommend it, and anyway, I was just sort of,

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<v Speaker 4>you know, keep trying to keep that business from failing.

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<v Speaker 4>In two thousand and nine, when my father got really

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<v Speaker 4>excited about a bunch of these Chinese companies that had

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<v Speaker 4>had gone public in the US via reverse merger, and

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<v Speaker 4>like I had my own problems, I wasn't really that interested.

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<v Speaker 4>But he asked me to look and he asked me

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<v Speaker 4>to look at this first one called Orient Paper. And

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<v Speaker 4>the first thing he told me he'd been at a

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<v Speaker 4>conference that these guys had gone to, and you know

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<v Speaker 4>what he's hearing is, oh, you know, chairman Leo, he's

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<v Speaker 4>different from other Chinese company chairmen. He doesn't smoke, and

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<v Speaker 4>he doesn't chase women. And you know, my father's telling

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<v Speaker 4>me this woman, you know, late night in Shanghai, and

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<v Speaker 4>I'm like, I'm sure neither of those things is actually true.

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<v Speaker 4>But the fact that this is making its rounds at

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<v Speaker 4>the conference, somebody is trying to game Western investor psychology.

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<v Speaker 4>So that got my attention. Early twenty ten, went up

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<v Speaker 4>to see the company and it was a Potemkin factory,

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<v Speaker 4>Like I never believed that such a thing could exist,

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<v Speaker 4>where at the time it's market cap is one hundred

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<v Speaker 4>and fifty million, had just reported one hundred three million

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<v Speaker 4>dollars in revenue and the real revenue two to five

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<v Speaker 4>million dollars that it was these empty box So I

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<v Speaker 4>exposed that with the thirty some ond page report. And

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<v Speaker 4>the only reason I did that was I felt like

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<v Speaker 4>I was stuck in my business in Shanghai, like a

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<v Speaker 4>few hundred people who are leaving their stuff.

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<v Speaker 3>In my facility.

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<v Speaker 4>The industry did not exist because it's a bad industry

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<v Speaker 4>to be in in China, and I don't know, there's

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<v Speaker 4>like a power and feeling like you have nothing to lose.

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<v Speaker 4>So I just threw the ball as far down the

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<v Speaker 4>field as I could wrote that report.

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<v Speaker 3>It went viral.

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<v Speaker 4>Quickly found out this was systemic, and one year later

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<v Speaker 4>Bloomberg's like, oh, he's one of the fifty most influential

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<v Speaker 4>in global finance with Ben Bernanki and Warren Buffett, and

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<v Speaker 4>it was like, well, yes, of course that's the natural

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<v Speaker 4>path from self storage.

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<v Speaker 2>That's every thirty page analyst report tends to lead to that.

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<v Speaker 2>So it's funny because you and I kind of came

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<v Speaker 2>of age in the markets similar period. The dot com

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<v Speaker 2>implosion was certainly fundamental to my view of both markets

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<v Speaker 2>and short sellers, and then the financial crisis. How do

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<v Speaker 2>you look at how the markets have changed over the

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<v Speaker 2>ensuing decade, as between QE and zero interest rate policy,

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<v Speaker 2>and more recently the Cares Act and the mascul fiscal stimulus.

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<v Speaker 2>I grew up thinking short sellers were the ones who

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<v Speaker 2>kept the market honest and responsible. That seems to be

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<v Speaker 2>a minority of you these days.

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<v Speaker 4>Yeah, well, I've come to the view that there's an

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<v Speaker 4>inverse relationship between interest rates and the amount of dishonesty

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<v Speaker 4>in society. So the lower your rates, the more easy

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<v Speaker 4>money is, the more dishonesty you get in society. And

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<v Speaker 4>so the emergency monetary policy outlived the emergency. And you

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<v Speaker 4>know what I felt is that just each year I've

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<v Speaker 4>been doing this, that investors are more and more anesthetized

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<v Speaker 4>to Now. The flip side of that is that behaviors

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<v Speaker 4>that were once really only present in microcap land will

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<v Speaker 4>those bubble up to MidCap land because of the inflation

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<v Speaker 4>of market caps. So on one hand, my business has

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<v Speaker 4>gotten harder because unless it's something really really egregious, like

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<v Speaker 4>people don't care. But then yes, you'll find that type

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<v Speaker 4>of behavior now even in mid cap companies, and you

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<v Speaker 4>know an environment where and just to be clear, it's

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<v Speaker 4>a small minority of companies that are frauds the world's

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<v Speaker 4>bigger problem is the gray zone, right, the things where yeah,

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<v Speaker 4>nobody's gonna get convicted. Tech you know, lawyers have signed off,

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<v Speaker 4>the auditor is okay with it, and that gray zone

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<v Speaker 4>behavior whereby you can significantly misrepresent economic reality that is

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<v Speaker 4>almost maybe the norm in many respects.

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<v Speaker 2>So this secret is to corrupt the attorneys and the

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<v Speaker 2>orderers and then it's home free.

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<v Speaker 3>Wait, corrupt the attorneys.

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<v Speaker 2>Right, So you mentioned microcaps, small cap mid caps. I

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<v Speaker 2>read a note of yours not too long ago talking

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<v Speaker 2>about the big caps and the megacaps, where so many

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<v Speaker 2>people have been calling this a bubble, and so many

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<v Speaker 2>people have saying, gee, I'd like to shorten video.

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<v Speaker 3>You kind of went out of your way.

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<v Speaker 2>To say, hey, maybe one day there's a downside play here,

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<v Speaker 2>but this freight train is really difficult to step in

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<v Speaker 2>front of. What are your thoughts on on the hyperscalers,

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<v Speaker 2>the megacap tech companies?

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<v Speaker 3>Three things?

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<v Speaker 4>Number one, there are easier better shorts out there than

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<v Speaker 4>in video. Number two. The reason why I was making

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<v Speaker 4>those comments is that flows have driven so much of this,

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<v Speaker 4>Like you have obviously the passive bid, and it squeezes

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<v Speaker 4>floats and by squeezing floats. It's not a linear impact

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<v Speaker 4>on stock prices. It's a parabolic impact on stock prices

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<v Speaker 4>at least of the winners. So the idea that something

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<v Speaker 4>is overvalued, that's a reference to its fundamental value. But

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<v Speaker 4>I think you have to consider its technical value. And

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<v Speaker 4>that's what everybody fails to say when they're criticizing these

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<v Speaker 4>things on a fundamental basis.

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<v Speaker 3>It's like, well what are the technicals of this? Now?

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<v Speaker 3>That's my second point.

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<v Speaker 4>My third point is up till one month ago, I

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<v Speaker 4>was completely sanguine on the on SMP and markets in

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<v Speaker 4>general and the economy. And my view has one eight

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<v Speaker 4>And I think the wrong question is well what do

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<v Speaker 4>you think of the valuations or stock prices of XYZ

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<v Speaker 4>of these AI companies? And the right question is what

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<v Speaker 4>is about to happen to society and to the market

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<v Speaker 4>as a result of AI. And I and like I

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<v Speaker 4>said on this like a month ago, I wouldn't even

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<v Speaker 4>refer to these models as a I had this rule.

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<v Speaker 4>These are large language models. They are not going to

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<v Speaker 4>create new information. They merely process information that's already out there.

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<v Speaker 4>Don't call it AI, they're lllms. But I call it

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<v Speaker 4>AI now.

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<v Speaker 2>Right, they're neither artificial nor intelligence. They're something else. But

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<v Speaker 2>given that, and given this one eighty but we're going

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<v Speaker 2>to dive right into AI in a minute. But since

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<v Speaker 2>you built your reputation before the firm is pivoted into

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<v Speaker 2>a full service research shop, both long and short, you've

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<v Speaker 2>criticized SPACs, crypto thematic ETFs, NFTs. Where has there been

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<v Speaker 2>the biggest destruction of investor wealth in that group?

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<v Speaker 4>Well in that group, Okay, so it's a little bit

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<v Speaker 4>in vogue. I think to point toward private credit right now,

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<v Speaker 4>and the reality is like who knows, right, there's there's

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<v Speaker 4>no data.

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<v Speaker 3>It's really opaque.

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<v Speaker 4>My concerns there, and I recognize that data is not

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<v Speaker 4>the plural of anecdote. But in the past few months,

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<v Speaker 4>some of the research we've done, I've looked at some

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<v Speaker 4>abs issuers and this is not private credit, but I

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<v Speaker 4>was really surprised to see as I went down the

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<v Speaker 4>rabbit hole of abs issuances that a lot of the

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<v Speaker 4>paperwork that should be done to basically show release of

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<v Speaker 4>lians of loans that are being securitized and filed publicly,

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<v Speaker 4>that paperwork is not being filed publicly and at first,

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<v Speaker 4>I thought, oh my god, we've got these guys on fraud.

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<v Speaker 4>They're selling off loans that are still encumbered. And I

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<v Speaker 4>spoke with a couple of securitization attorneys and they said, no, no, no,

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<v Speaker 4>that's market practice. The warehouse lender just provides a letter

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<v Speaker 4>saying that the lians are released. It doesn't get filed publicly.

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<v Speaker 4>And so I asked each of them, well, what's to

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<v Speaker 4>stop the sponsor of the securitization from forging the letter

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<v Speaker 4>because he thinks, like, look, the loans are, the ABSs

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<v Speaker 4>are already over collateralized. I can double pledge these, you know,

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<v Speaker 4>because if the warehouse lender, if it's not public, the

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<v Speaker 4>warehouse lender wouldn't know if somebody forged it.

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<v Speaker 3>Huh yeah, that's a good point.

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<v Speaker 4>And so I when I see that the largest financial

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<v Speaker 4>institutions are not dotting eyes and crossing t's.

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<v Speaker 3>You know.

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<v Speaker 4>I've a conversation with somebody recently who gave me data

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<v Speaker 4>point from a private equity firm that's doing a lot

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<v Speaker 4>of clos The conversation from somebody who's on the p

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<v Speaker 4>side going to the CLO guys is like, hey, so

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<v Speaker 4>what do we know about the performance of the underlying loans,

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<v Speaker 4>like how are they performing?

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<v Speaker 3>Huh? Why did we track that we don't service them?

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<v Speaker 3>Like this is.

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<v Speaker 4>Reminiscent of right out of the Yeah, this is reminiscent

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<v Speaker 4>of some of the behaviors and credit. So then okay,

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<v Speaker 4>I combined again, it's not data, these are anecdotes, but

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<v Speaker 4>I combine that with also what I noticed starting a

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<v Speaker 4>few years ago. You know, every time I talk to

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<v Speaker 4>an allocator, you know, because we're actually we run a fund.

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<v Speaker 4>We're a hedge fund, so you know, we're talking to

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<v Speaker 4>allocators all the time. And you know what do you

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<v Speaker 4>guys investing in everybody all of a sudden starts saying

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<v Speaker 4>private credit, private credit, private credit.

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<v Speaker 3>You know.

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<v Speaker 4>That also reminds me of the Internet bubble, because the

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<v Speaker 4>way I used to think about that as it was

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<v Speaker 4>happening is there's too much money chasing too few investable companies.

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<v Speaker 4>So I don't think if there are problems in private credit,

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<v Speaker 4>Like my first bet is not that it's at Apollo,

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<v Speaker 4>But I also know we have looked at the insurance industry,

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<v Speaker 4>and so I know a lot of these insurers have

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<v Speaker 4>been bought by smaller pe firms. I mean they're basically

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<v Speaker 4>using these things to finance their deals. The Ft did

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<v Speaker 4>a great article a few Alphaville a few months ago

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<v Speaker 4>on the credit ratings agencies. I mean, it's not even

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<v Speaker 4>SMP in Moody's. The number one is Egan Jones. So

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<v Speaker 4>corporate headquarters is like an eight bedroom house in suburban

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<v Speaker 4>Boston literally, and I think they did like two thousand

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<v Speaker 4>deals last year that they raided. I mean, if you

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<v Speaker 4>lived through the GFC and we're paying attention, you know,

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<v Speaker 4>like starting to see some dots connect. So that does

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<v Speaker 4>have me worried also, and if that does intersect with

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<v Speaker 4>what I think could happen in the labor markets from

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<v Speaker 4>AI job displacement, you know, like I know you want

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<v Speaker 4>to pivot back to it, but I'm just going to

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<v Speaker 4>put it out there. I think it's not unrealistic to

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<v Speaker 4>say fifteen percent of knowledge work jobs in the US

0:13:22.440 --> 0:13:24.560
<v Speaker 4>in three years are gone. And if it's not three,

0:13:24.600 --> 0:13:26.959
<v Speaker 4>it's going to be five. But it might not be fifteen,

0:13:27.000 --> 0:13:30.040
<v Speaker 4>it could be twenty twenty five percent. I mean, that's

0:13:30.360 --> 0:13:32.000
<v Speaker 4>and I can work through how I got there.

0:13:32.320 --> 0:13:37.680
<v Speaker 2>Let's dive deeper into AI. It's both an investible asset

0:13:37.880 --> 0:13:42.400
<v Speaker 2>a shortable asset, and a tool that you're using to

0:13:42.520 --> 0:13:44.480
<v Speaker 2>run a business. So I want to hit each of

0:13:44.520 --> 0:13:48.400
<v Speaker 2>those things, starting with how are you using AI as

0:13:48.440 --> 0:13:54.520
<v Speaker 2>a tool to manage a business to identify long and

0:13:54.559 --> 0:13:59.839
<v Speaker 2>short opportunities? What is true AI not just lms me

0:14:00.280 --> 0:14:01.840
<v Speaker 2>for your daily work?

0:14:02.240 --> 0:14:05.320
<v Speaker 4>Well, I mean in the past again, since finding religion

0:14:05.440 --> 0:14:08.360
<v Speaker 4>just a few weeks ago. I mean, this is something

0:14:08.400 --> 0:14:11.160
<v Speaker 4>I've been hammering. Most of my employees have worked for

0:14:11.200 --> 0:14:15.040
<v Speaker 4>me for over ten years. We're an old firm for

0:14:15.080 --> 0:14:16.840
<v Speaker 4>a hedge fund. I mean I used to joke that

0:14:17.280 --> 0:14:20.080
<v Speaker 4>this is probably true that if you look at trips

0:14:20.080 --> 0:14:23.560
<v Speaker 4>and falls per dollar of AUM, we maybe are the

0:14:23.600 --> 0:14:26.640
<v Speaker 4>highest in the world. And that was kind of funny

0:14:26.640 --> 0:14:30.160
<v Speaker 4>to say until I started saying, guys, why are you

0:14:30.360 --> 0:14:33.680
<v Speaker 4>literally taking months to put together one hundred and fifty

0:14:33.840 --> 0:14:38.160
<v Speaker 4>page slide decks to discuss something internally? Stick it in

0:14:38.560 --> 0:14:42.280
<v Speaker 4>the machine. And so one of my analysts, my longest

0:14:42.280 --> 0:14:49.880
<v Speaker 4>serving employee, ex ex auditor, super bright, but al we

0:14:50.000 --> 0:14:53.360
<v Speaker 4>struggled with communication. I mean one of my skills was

0:14:54.200 --> 0:14:58.880
<v Speaker 4>over months, weeks or months, many many hours trying to

0:14:59.000 --> 0:15:02.560
<v Speaker 4>draw out of her the patterns that she sees. But

0:15:02.680 --> 0:15:06.680
<v Speaker 4>she's just unable to elucidate. Now she's just pumping out

0:15:06.680 --> 0:15:09.800
<v Speaker 4>the memoranda from Claude, and I'm like, wow, this is

0:15:09.960 --> 0:15:12.480
<v Speaker 4>I mean, Cindy, this has saved us, like, you know,

0:15:12.560 --> 0:15:16.120
<v Speaker 4>probably five weeks of you know, like frustrated conversations in

0:15:16.160 --> 0:15:20.240
<v Speaker 4>the conference room like this. So from that perspective, it's helping,

0:15:20.760 --> 0:15:24.640
<v Speaker 4>I think hurting a little bit. You know. I've always

0:15:24.640 --> 0:15:27.600
<v Speaker 4>felt that we have an edge as active as short

0:15:27.640 --> 0:15:31.160
<v Speaker 4>sellers over our competition in terms of how I write

0:15:31.240 --> 0:15:32.000
<v Speaker 4>and communicate.

0:15:32.440 --> 0:15:33.480
<v Speaker 3>Like that edge has gone.

0:15:33.520 --> 0:15:35.760
<v Speaker 4>I mean, you can go to Claude and say, hey,

0:15:36.080 --> 0:15:39.080
<v Speaker 4>you know, write this up as a short report in

0:15:39.120 --> 0:15:39.960
<v Speaker 4>the voice of.

0:15:39.920 --> 0:15:43.160
<v Speaker 3>Carson Block, and you know it's not bad. I mean,

0:15:43.200 --> 0:15:46.280
<v Speaker 3>i it gets you a lot of the way there.

0:15:46.520 --> 0:15:49.160
<v Speaker 2>So so let me flip the question on you and

0:15:49.240 --> 0:15:56.080
<v Speaker 2>ask how has AI changed the fraudster's toolkit? What can

0:15:56.160 --> 0:16:00.680
<v Speaker 2>Claude do for a fabricated document, deep fakes, fake video,

0:16:00.800 --> 0:16:05.440
<v Speaker 2>fake voice, fake docs, fake everything. Has it just become

0:16:05.480 --> 0:16:08.320
<v Speaker 2>an arms race between the good guys and the bad guys?

0:16:10.360 --> 0:16:14.240
<v Speaker 4>Well, look, I mean the tools for forgery never really

0:16:14.280 --> 0:16:16.320
<v Speaker 4>needed to be that sophisticated. I Mean one of my

0:16:16.360 --> 0:16:20.400
<v Speaker 4>favorite examples of that was the Peregrine Financial That guy

0:16:20.520 --> 0:16:24.760
<v Speaker 4>had a post office box and an ink chat and

0:16:24.800 --> 0:16:27.640
<v Speaker 4>that's how he forged his auditor letters. And you know

0:16:27.680 --> 0:16:28.840
<v Speaker 4>that was a few hundred million.

0:16:28.880 --> 0:16:33.200
<v Speaker 2>But Bernie Madoff did not exactly use the most sophisticated technology.

0:16:33.360 --> 0:16:36.720
<v Speaker 4>Yeah, I think the thing that will get to be

0:16:36.800 --> 0:16:40.800
<v Speaker 4>more interesting is if you're a company CEO and you

0:16:40.840 --> 0:16:43.000
<v Speaker 4>know you're kind of you know, like you're pumping your

0:16:43.000 --> 0:16:46.520
<v Speaker 4>stock price, you're monetizing it and hitting the bid. I

0:16:46.520 --> 0:16:49.280
<v Speaker 4>think the more interesting thing is querying it. You know,

0:16:50.000 --> 0:16:53.520
<v Speaker 4>if I were the CEO of XYZ company, what would

0:16:53.560 --> 0:16:55.080
<v Speaker 4>a short sellar focus on?

0:16:55.560 --> 0:16:57.520
<v Speaker 3>You know, like what should I do about that?

0:16:57.840 --> 0:16:59.960
<v Speaker 4>So I think that we're going to get in this

0:17:00.080 --> 0:17:05.159
<v Speaker 4>cat and mouse game of preemption and reaction. But I mean,

0:17:05.200 --> 0:17:06.560
<v Speaker 4>at the end of the day, I mean, if you're

0:17:07.040 --> 0:17:09.240
<v Speaker 4>you know, if you're just ramping your stock price and

0:17:09.359 --> 0:17:12.160
<v Speaker 4>mortgaging your future, and I think as active as short

0:17:12.160 --> 0:17:15.040
<v Speaker 4>sellers will still get there, but you could at least

0:17:15.119 --> 0:17:19.520
<v Speaker 4>dig a wider moat around your you know, around what

0:17:19.560 --> 0:17:22.560
<v Speaker 4>you're doing if you use these AI tools.

0:17:23.240 --> 0:17:27.800
<v Speaker 2>So I always think of short sellers like Jim Chainos

0:17:27.880 --> 0:17:32.879
<v Speaker 2>and the original guys who who really pioneered forensic accounting

0:17:33.280 --> 0:17:37.560
<v Speaker 2>as being so deep into the documents. How useful are

0:17:37.600 --> 0:17:43.119
<v Speaker 2>tools like Claude Cowork as a forensic accountant to help

0:17:43.480 --> 0:17:50.080
<v Speaker 2>either identify patterns in every SEC filing or honing in

0:17:50.119 --> 0:17:54.040
<v Speaker 2>on a specific company's filings and seeing what doesn't smell

0:17:54.119 --> 0:17:55.040
<v Speaker 2>right for me.

0:17:55.200 --> 0:17:57.720
<v Speaker 3>That's a little TBD. I don't know yet.

0:17:57.760 --> 0:17:59.680
<v Speaker 4>I mean, I'm not sure that you can just upload

0:17:59.680 --> 0:18:02.919
<v Speaker 4>a ten and say, oh, you know, what's dodgy about this?

0:18:03.000 --> 0:18:06.320
<v Speaker 4>I mean, first of all, one of the one of

0:18:06.359 --> 0:18:09.040
<v Speaker 4>the secrets. It's not a secret, but of what we

0:18:09.119 --> 0:18:13.760
<v Speaker 4>do is we obtain documents from places people never look.

0:18:14.240 --> 0:18:17.960
<v Speaker 4>So again, like we're you know, we're pulling UCC files

0:18:18.200 --> 0:18:22.239
<v Speaker 4>to look at asset securitizations. We love companies that have

0:18:22.320 --> 0:18:27.720
<v Speaker 4>overseas subsidiaries because most overseas jurisdictions there are publicly filed

0:18:27.760 --> 0:18:28.800
<v Speaker 4>financial statements.

0:18:29.119 --> 0:18:31.240
<v Speaker 3>So we'll pull those and upload them.

0:18:31.520 --> 0:18:33.800
<v Speaker 4>And then also, I'm sure it could really help connect

0:18:33.800 --> 0:18:35.800
<v Speaker 4>the dots with people. I mean right now or up

0:18:35.880 --> 0:18:39.360
<v Speaker 4>till now, we've had to rely on memory, like oh wait, yeah,

0:18:39.400 --> 0:18:41.920
<v Speaker 4>this dude. You know, we've looked at fifty eight entities.

0:18:42.359 --> 0:18:45.480
<v Speaker 4>This dude was in that entity. Oh interesting. So the

0:18:45.520 --> 0:18:48.040
<v Speaker 4>AI is going to get rid of it's going to

0:18:48.240 --> 0:18:50.399
<v Speaker 4>make that part easy. But you still have to go

0:18:50.480 --> 0:18:52.679
<v Speaker 4>out and do the legwork. And you know, a lot

0:18:52.720 --> 0:18:54.639
<v Speaker 4>of times you have to send people in person to

0:18:54.720 --> 0:18:58.399
<v Speaker 4>do document retrieval. So I don't think it's as simple

0:18:58.440 --> 0:19:00.600
<v Speaker 4>as you know, Hey, I woke up today and I

0:19:00.600 --> 0:19:02.840
<v Speaker 4>want to be an activist short seller, like you know,

0:19:03.080 --> 0:19:05.760
<v Speaker 4>which you know, claude, which company should I write about?

0:19:05.800 --> 0:19:08.359
<v Speaker 4>And you know, what's my thesis? Like, you have to

0:19:08.359 --> 0:19:10.960
<v Speaker 4>still do a lot of leg work. But the accounting

0:19:10.960 --> 0:19:16.280
<v Speaker 4>stuff your claude has demonstrated internally again, turning my you know,

0:19:16.280 --> 0:19:21.639
<v Speaker 4>my accounting analysts, the former auditor, turning her poorly expressed

0:19:21.760 --> 0:19:25.760
<v Speaker 4>thoughts into actual words, you know. And of course she's

0:19:25.840 --> 0:19:27.840
<v Speaker 4>iterating with it. No, no, no, that's not what I mean.

0:19:28.160 --> 0:19:30.679
<v Speaker 4>But it's got real accounting knowledge. Oh well, according to

0:19:30.720 --> 0:19:32.480
<v Speaker 4>ASC blah blah blah, and this does not meet the

0:19:32.520 --> 0:19:34.560
<v Speaker 4>definition of the da da da N wow.

0:19:34.720 --> 0:19:36.560
<v Speaker 3>I mean, that's it's really interesting.

0:19:36.640 --> 0:19:38.120
<v Speaker 4>I mean, look, I think at the end of the day,

0:19:38.920 --> 0:19:40.800
<v Speaker 4>part of the edge of being an active as short

0:19:40.800 --> 0:19:44.200
<v Speaker 4>seller is the willingness to be sued, or the tolerance

0:19:44.240 --> 0:19:46.640
<v Speaker 4>for being sued. So I'm not worried that a bunch

0:19:46.680 --> 0:19:49.119
<v Speaker 4>of people are going to run out and like commoditize this.

0:19:49.320 --> 0:19:50.800
<v Speaker 4>And and I think at the end of the day,

0:19:50.920 --> 0:19:55.520
<v Speaker 4>also having a brand where if everybody can produce skeptical

0:19:56.200 --> 0:20:00.240
<v Speaker 4>you know pieces, it's also knowing when the model is

0:20:00.320 --> 0:20:02.960
<v Speaker 4>kind of bullying you, right, like no, no, because that

0:20:03.040 --> 0:20:06.000
<v Speaker 4>happens too. I mean, these things are sickophantic, like wow,

0:20:06.040 --> 0:20:09.960
<v Speaker 4>that's brilliant. Of course it's a fraud person, you know, no.

0:20:10.520 --> 0:20:15.439
<v Speaker 2>To say nothing of double checking for hallucinations. And a

0:20:15.480 --> 0:20:18.320
<v Speaker 2>bunch of lawyers who have been using AI keep getting

0:20:18.320 --> 0:20:21.879
<v Speaker 2>into trouble because it's citing cases that don't really exist,

0:20:22.400 --> 0:20:26.240
<v Speaker 2>and the judge's clerk, also using AI, discovers these cases

0:20:26.240 --> 0:20:30.240
<v Speaker 2>don't exist. But you mentioned a word that's really fascinating.

0:20:30.800 --> 0:20:36.920
<v Speaker 2>You mentioned edge. If all the participants in the markets

0:20:37.000 --> 0:20:41.160
<v Speaker 2>long and short are using the same tools, is there

0:20:41.200 --> 0:20:43.760
<v Speaker 2>any edge to be found that had there or is

0:20:43.800 --> 0:20:46.560
<v Speaker 2>it really about how you're applying these tools where the

0:20:46.640 --> 0:20:47.400
<v Speaker 2>edge comes from.

0:20:47.640 --> 0:20:48.720
<v Speaker 3>That's an interesting question.

0:20:48.840 --> 0:20:50.879
<v Speaker 4>I mean, look, on the on the short side, you

0:20:50.960 --> 0:20:53.480
<v Speaker 4>only make money if people care, right, And so I

0:20:53.480 --> 0:20:58.639
<v Speaker 4>think that's been the problem that most so since the GFC.

0:20:59.640 --> 0:21:03.280
<v Speaker 4>Almost everybody who is running money principally focused on short

0:21:03.280 --> 0:21:06.840
<v Speaker 4>strategies has gone out of business. I mean some you know,

0:21:06.920 --> 0:21:08.920
<v Speaker 4>they rode off into the sunset. You know, I made

0:21:08.920 --> 0:21:12.399
<v Speaker 4>a bunch of money, most carried out, you know. I

0:21:12.400 --> 0:21:15.040
<v Speaker 4>think the problem that a lot of the short sellers

0:21:15.160 --> 0:21:18.600
<v Speaker 4>have had and I had this too, you know, and

0:21:18.680 --> 0:21:20.960
<v Speaker 4>have if I have to actively correct for it is

0:21:21.800 --> 0:21:23.800
<v Speaker 4>you try. You tend to view the world the way

0:21:23.840 --> 0:21:26.320
<v Speaker 4>it should be, not the way it is. And so

0:21:26.480 --> 0:21:29.920
<v Speaker 4>that's the problem. Like when people short you know, Tesla

0:21:30.000 --> 0:21:33.400
<v Speaker 4>because you know Elon Musk this and that, like nobody

0:21:33.440 --> 0:21:36.800
<v Speaker 4>cares right and that that's that's the thing. So I

0:21:37.520 --> 0:21:40.960
<v Speaker 4>think you to be good on the short side, you

0:21:41.080 --> 0:21:44.719
<v Speaker 4>have to understand why people are buying the stock, and

0:21:44.760 --> 0:21:48.240
<v Speaker 4>you have to have a view that goes directly against

0:21:48.240 --> 0:21:50.840
<v Speaker 4>that or that undermines that thesis. And I think so

0:21:50.960 --> 0:21:54.240
<v Speaker 4>much of the time that doesn't happen. So I don't know.

0:21:54.280 --> 0:21:57.480
<v Speaker 4>I think the I don't know that this erodes the

0:21:57.720 --> 0:22:01.000
<v Speaker 4>edge of just of judgment when it comes the longside

0:22:01.240 --> 0:22:03.320
<v Speaker 4>or short side. And then on the long side, I

0:22:03.359 --> 0:22:05.879
<v Speaker 4>mean kind of buy what the smart money is buying

0:22:05.920 --> 0:22:07.919
<v Speaker 4>seems to have worked like I hate to say it,

0:22:07.960 --> 0:22:11.680
<v Speaker 4>but you know, again, technicals versus fundamental value, the technical

0:22:11.760 --> 0:22:14.880
<v Speaker 4>value of something. You know, I don't know that AI

0:22:15.240 --> 0:22:17.960
<v Speaker 4>helps tongue with that right now, but it certainly can.

0:22:18.480 --> 0:22:22.320
<v Speaker 2>Let's talk about AI pretenders, and I'm pulling something else

0:22:22.359 --> 0:22:25.320
<v Speaker 2>you had written a while ago, and there's a little

0:22:25.320 --> 0:22:29.000
<v Speaker 2>bit of a rhyme with late nineties every company edit

0:22:29.040 --> 0:22:31.800
<v Speaker 2>a dot com and their stock would see a pop.

0:22:32.520 --> 0:22:36.000
<v Speaker 2>What are you noticing amongst the fake AI stories, the

0:22:36.040 --> 0:22:39.919
<v Speaker 2>fake pivots, the companies that really have nothing whatsoever to

0:22:40.040 --> 0:22:43.320
<v Speaker 2>use to do with AI other than two or three

0:22:43.320 --> 0:22:45.960
<v Speaker 2>people who work for the company have a Perplexity app

0:22:46.000 --> 0:22:50.520
<v Speaker 2>on their phone. Tell us about the narrative of AI pretenders.

0:22:50.840 --> 0:22:52.959
<v Speaker 4>Well, I look, I think if all of a sudden

0:22:52.960 --> 0:22:56.480
<v Speaker 4>the company has started talking. So I first did this

0:22:57.040 --> 0:23:01.760
<v Speaker 4>shortly after I started on the short side. Cloud became

0:23:01.800 --> 0:23:05.119
<v Speaker 4>the thing, right, and so then I saw some companies

0:23:05.119 --> 0:23:08.359
<v Speaker 4>that had just done a global find and replaced, like,

0:23:08.480 --> 0:23:11.600
<v Speaker 4>you know, find this, replace it with cloud. And so

0:23:11.640 --> 0:23:14.919
<v Speaker 4>if you see that with AI in a company's filings

0:23:15.200 --> 0:23:18.080
<v Speaker 4>and in their statements, then yeah, I mean they're they're

0:23:18.080 --> 0:23:21.359
<v Speaker 4>probably a pretender. I mean, I think it's pretty clear.

0:23:22.160 --> 0:23:25.600
<v Speaker 4>You know, AI, real AI requires scale. I mean, whether

0:23:25.680 --> 0:23:28.840
<v Speaker 4>you're on the process on the hardware side, or you're

0:23:29.080 --> 0:23:32.080
<v Speaker 4>you know, or you're actually producing the AI models. So

0:23:32.920 --> 0:23:36.280
<v Speaker 4>I don't know everybody who's like AI enabled it, And look,

0:23:36.320 --> 0:23:38.320
<v Speaker 4>I'm out over my skis here because I don't really

0:23:38.400 --> 0:23:41.919
<v Speaker 4>understand the technology. But everybody who's AI enabled, it's like, well,

0:23:41.960 --> 0:23:44.159
<v Speaker 4>what's what's the foundation? You know, if you are an

0:23:44.200 --> 0:23:47.240
<v Speaker 4>AI enabled this, what are you running? Are you running perplexity,

0:23:47.359 --> 0:23:50.240
<v Speaker 4>Claude chat GPT? And if you're like, well I made

0:23:50.240 --> 0:23:53.800
<v Speaker 4>it myself, like no, man, like I'm not going to

0:23:53.840 --> 0:23:56.040
<v Speaker 4>buy that, you know, like these things have cost way

0:23:56.119 --> 0:23:58.840
<v Speaker 4>too many billions of dollars to develop for you to

0:23:58.840 --> 0:23:59.760
<v Speaker 4>be able to vibe code.

0:23:59.800 --> 0:24:04.480
<v Speaker 2>You're short Sellers are always looking for a downside catalyst

0:24:05.000 --> 0:24:09.520
<v Speaker 2>when you start thinking about the megacaps, the hyperscalers, or

0:24:09.560 --> 0:24:13.280
<v Speaker 2>anybody else that's really blown up in value and in

0:24:13.400 --> 0:24:16.320
<v Speaker 2>price that's created a little bit of an air pocket.

0:24:16.760 --> 0:24:20.240
<v Speaker 2>Has that catalyst come in yet or is there something

0:24:20.280 --> 0:24:24.720
<v Speaker 2>off in the future that's gonna lead people to say, hey,

0:24:24.760 --> 0:24:26.720
<v Speaker 2>this has gone too far, we need to take something

0:24:26.760 --> 0:24:27.399
<v Speaker 2>off the table.

0:24:27.680 --> 0:24:30.760
<v Speaker 4>Well, if you take my view that a lot of

0:24:30.800 --> 0:24:34.240
<v Speaker 4>these names have traded based on their technical values as

0:24:34.240 --> 0:24:38.639
<v Speaker 4>opposed to fundamental. Then you need to get into okay,

0:24:38.760 --> 0:24:42.760
<v Speaker 4>like what are the underlying technicals here. So I'm a

0:24:42.800 --> 0:24:45.600
<v Speaker 4>fan of a guy named Mike Green, So I think

0:24:45.680 --> 0:24:48.679
<v Speaker 4>Mike is going to prove to be really prophetic. And

0:24:48.720 --> 0:24:52.160
<v Speaker 4>so what he's been saying since maybe eighteen or nineteen

0:24:52.800 --> 0:24:55.959
<v Speaker 4>is that so passive has broken the market. You know,

0:24:56.200 --> 0:25:01.120
<v Speaker 4>don't disagree, but that when the flows, actually the buying

0:25:01.320 --> 0:25:04.960
<v Speaker 4>from the target date funds tapers off and then you

0:25:05.040 --> 0:25:09.800
<v Speaker 4>get net outflows, that's when you get as he calls it,

0:25:10.119 --> 0:25:13.600
<v Speaker 4>or was calling it nineteen twenty nine magnitude crash at

0:25:13.880 --> 0:25:15.960
<v Speaker 4>you know, filling the year, you know, filling the blank

0:25:16.000 --> 0:25:20.520
<v Speaker 4>with the year speed. And that's what scares me about

0:25:20.880 --> 0:25:24.840
<v Speaker 4>AI because you know, like I said, if I if

0:25:24.840 --> 0:25:28.600
<v Speaker 4>this thesis is correct, that then three years or a

0:25:28.640 --> 0:25:31.880
<v Speaker 4>few years, fifteen percent of knowledge workers have lost their jobs.

0:25:32.320 --> 0:25:34.360
<v Speaker 4>It's not like they're going to find new jobs. It's

0:25:34.400 --> 0:25:37.920
<v Speaker 4>not like you know, fiscal or monetary stimulus creates new

0:25:37.960 --> 0:25:41.160
<v Speaker 4>knowledge work jobs. They are going to and they all

0:25:41.200 --> 0:25:47.000
<v Speaker 4>have college debt, mortgages, car leases. Eventually they're going to

0:25:47.040 --> 0:25:50.000
<v Speaker 4>start hitting up their four oh one k's and so

0:25:50.160 --> 0:25:53.760
<v Speaker 4>first they stop contributing as they're laid off. Then they

0:25:53.760 --> 0:25:57.479
<v Speaker 4>need that money and they start taking early redemptions. And

0:25:57.560 --> 0:26:02.000
<v Speaker 4>so if Mike Green is correct, when that happens, there's

0:26:02.040 --> 0:26:05.719
<v Speaker 4>nobody there to catch the falling knife, and the technicals

0:26:05.760 --> 0:26:10.000
<v Speaker 4>have basically for you know better, since the GFC just

0:26:10.160 --> 0:26:15.879
<v Speaker 4>created this tremendous amount of air, that's when it's really

0:26:15.920 --> 0:26:19.160
<v Speaker 4>time to panic, because that that's what I think, that's

0:26:19.240 --> 0:26:21.760
<v Speaker 4>what's going to make his thesis. That's what's going to

0:26:21.800 --> 0:26:25.200
<v Speaker 4>test his thesis. And if you asked me five weeks ago,

0:26:26.359 --> 0:26:29.040
<v Speaker 4>you know, did I think that we're in any danger

0:26:29.160 --> 0:26:32.560
<v Speaker 4>anything on the horizon in terms of seeing you know,

0:26:32.600 --> 0:26:36.080
<v Speaker 4>reversal of four oh one K flows and rise significant

0:26:36.160 --> 0:26:37.960
<v Speaker 4>rise in unemployment, I would have said no.

0:26:38.600 --> 0:26:38.959
<v Speaker 3>I was.

0:26:39.119 --> 0:26:43.240
<v Speaker 4>I was completely sanguine five weeks ago, and I've, like

0:26:43.280 --> 0:26:44.920
<v Speaker 4>I said, I've won eight So.

0:26:45.119 --> 0:26:48.160
<v Speaker 2>I can't leave on that much of a downbeat note.

0:26:48.600 --> 0:26:52.800
<v Speaker 2>So for the last question, you run along short funds.

0:26:53.520 --> 0:26:57.560
<v Speaker 2>If that's the downside of AI, if that's the negative

0:26:57.600 --> 0:27:02.320
<v Speaker 2>we're seeing in the world of why collar work, what's

0:27:02.520 --> 0:27:07.280
<v Speaker 2>the long side of the portfolio, What looks attractive through

0:27:07.359 --> 0:27:10.680
<v Speaker 2>and on the other side of whatever happens with either

0:27:10.840 --> 0:27:13.160
<v Speaker 2>the AI thesis or Green's thesis.

0:27:13.320 --> 0:27:17.080
<v Speaker 4>Well, okay, the tough thing is there obviously are going

0:27:17.119 --> 0:27:20.639
<v Speaker 4>to be companies that benefit from AI, right, and so

0:27:20.680 --> 0:27:23.840
<v Speaker 4>they're the hyperscalers. But if you have but if they're

0:27:23.880 --> 0:27:25.840
<v Speaker 4>in the index, which they all are, and they're major

0:27:25.880 --> 0:27:28.320
<v Speaker 4>parts of the index, and you have index fund flows,

0:27:29.200 --> 0:27:31.640
<v Speaker 4>well the bull cases that over the long term they're

0:27:31.680 --> 0:27:33.560
<v Speaker 4>going to be you know, there's gonna be a great

0:27:33.600 --> 0:27:36.760
<v Speaker 4>buying opportunity. So I'm not sure that's where you hide out.

0:27:36.800 --> 0:27:40.240
<v Speaker 4>I mean, what we've been doing for the past month

0:27:40.640 --> 0:27:43.240
<v Speaker 4>is creating a set of what I think are highly

0:27:43.280 --> 0:27:49.080
<v Speaker 4>convexed trades in the book, especially basically shorten credit. So

0:27:49.119 --> 0:27:51.119
<v Speaker 4>it's not like the lead up to the GFC there's

0:27:51.119 --> 0:27:55.480
<v Speaker 4>not you know, deep CDs market, but I think, I mean,

0:27:55.520 --> 0:27:59.960
<v Speaker 4>credit spreads are stupidly tight and credit ball is stupid

0:28:00.119 --> 0:28:04.159
<v Speaker 4>Lee Love. So to me, you want convexity and there

0:28:04.160 --> 0:28:06.120
<v Speaker 4>are lots of ways to pay it where you're capping

0:28:06.200 --> 0:28:09.520
<v Speaker 4>your potential loss. That's how we're that's how we're approaching it.

0:28:09.760 --> 0:28:11.720
<v Speaker 4>So like and look, I hope this doesn't play out.

0:28:11.760 --> 0:28:13.879
<v Speaker 4>I mean, I be cause I don't have like a

0:28:13.920 --> 0:28:17.399
<v Speaker 4>plan B or C after AI takes, you know, like

0:28:17.520 --> 0:28:20.320
<v Speaker 4>my job. But you know, at least as it does

0:28:20.359 --> 0:28:22.080
<v Speaker 4>play out, we're we're positioning for it.

0:28:22.359 --> 0:28:26.560
<v Speaker 2>That was my conversation live at future Proof Citywide, Miami

0:28:27.080 --> 0:28:31.320
<v Speaker 2>with Muddy Waters Carson Block. If you enjoy this conversation,

0:28:31.840 --> 0:28:34.480
<v Speaker 2>well check out any of the six hundred we've done

0:28:34.520 --> 0:28:38.800
<v Speaker 2>over the past almost fourteen years. You can find those

0:28:38.840 --> 0:28:44.640
<v Speaker 2>at iTunes, YouTube, Spotify, Bloomberg, wherever you get your favorite

0:28:44.680 --> 0:28:47.560
<v Speaker 2>podcasts from. I would be remiss if I didn't thank

0:28:47.640 --> 0:28:51.160
<v Speaker 2>the crack team that helps put these conversations.

0:28:50.680 --> 0:28:52.800
<v Speaker 3>Together each week.

0:28:53.080 --> 0:28:57.080
<v Speaker 2>Alexis Noriega is my video producer. Anna Luke is my

0:28:57.200 --> 0:29:00.680
<v Speaker 2>regular producer. Sean Russo is my head of research. I'm

0:29:00.720 --> 0:29:04.800
<v Speaker 2>Barry Ritolts. You've been listening to Masters in Business on

0:29:04.920 --> 0:29:10.280
<v Speaker 2>Bloomberg Radio.