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