Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. Hello and welcome to
Speaker 1: the Money Stuff Podcast. You're a weekly podcast where we
Speaker 1: talk about stuff related to money. I'm Matt Levian and
Speaker 1: I write the Money Stuff column for Bloomberg Opinion.
Speaker 2: And I'm Katie Greifeld, a reporter for Bloomberg News and
Speaker 2: an anchor for Bloomberg Television.
Speaker 1: What are we talking about today, Katie?
Speaker 2: We're going to talk about farmers markets, We're going to
Speaker 2: talk about private credit, and then we're going to talk
Speaker 2: about stealing some trade secrets and moving to China.
Speaker 1: That sounds good.
Speaker 2: I printed out the pricing charts for like beef, so
Speaker 2: we have a meaty section.
Speaker 1: I was at the one of the farmer's markets near me.
Speaker 1: I go to two farmers' markets per weekend. I was
Speaker 1: recognized by a person working at one of the stands. Wow,
Speaker 1: it works in financial media and also works at the
Speaker 1: farmer's market to get her mind off things, and she's
Speaker 1: apparently a fan of mine, and offered me free garlic.
Speaker 2: Did you take it? So you took the free garlic,
Speaker 2: and then you undercut some farm stands. Some farmer who
Speaker 2: like put in the labor, and you knew what to charge.
Speaker 1: Because this is before I knew anything about farmer's market pricing.
Speaker 1: I was a babe in the woods in terms.
Speaker 2: Of oh, I thought this was like last weekend.
Speaker 1: No, it was like three weekends.
Speaker 2: Okay, if only you had known.
Speaker 1: But I do not honestly pay that much attention to
Speaker 1: pricing at the farmer's markets. But I am aware of
Speaker 1: the disparity in garlic pricing at the different stands. There's
Speaker 1: a stand where I have seen but not purchased garlic
Speaker 1: for three dollars ahead. Seems really high for garlic. But
Speaker 1: also the farmers garlic is so good, Like I now
Speaker 1: they got farmer's market garlic can probably pay five x
Speaker 1: what i'd pat agressory store. Me.
Speaker 2: Trying to think of something relatable to say reminds me
Speaker 2: of the Arrested development scene or Luciel's like it's a banana, Michael,
Speaker 2: how much could it cost? Or something like that. Yeah,
Speaker 2: I feel like if you're at a farmer's market, you're
Speaker 2: kind of a price and sensitive buyer of produce.
Speaker 1: I'm pretty close to the ideal of price and sensitive
Speaker 1: buyer of produce. But even I was like three dollars garlic, hold.
Speaker 2: On whoa, it's too rich for my blood. Well, what
Speaker 2: a timely conversation that we're organically having about pricing at
Speaker 2: farmers markets.
Speaker 1: It's all I think about. Yeah, sorry, I just said
Speaker 1: if not anything, I think about it at all, and
Speaker 1: I'm totally which is closer to the truth. But now
Speaker 1: I'm thinking about pricing at farmer's markets.
Speaker 2: Yeah, so is Cornell University question mark great transition. Yeah,
Speaker 2: why don't you tell me about what they're doing.
Speaker 1: They're aggregating prices for farmers. They have like a website
Speaker 1: that publishes free information on prices of various agricultural goods
Speaker 1: for farmers at farmers' markets to basically help them set
Speaker 1: their prices. Because if you're a farmer at a farmer's market,
Speaker 1: you you know, are in the business of working the land,
Speaker 1: ground the produce, and you're maybe not like a savvy
Speaker 1: pricer of produce at farmers markets, and you know, the
Speaker 1: buyers at farmer's markets are not necessarily savvy pricers of
Speaker 1: produce either, so you could probably charge them a lot
Speaker 1: more than you do, and Cornell is helping you charge
Speaker 1: them more than you do by telling you what the
Speaker 1: actual price of garlic is.
Speaker 2: Seems like a real antitrust concern potentially, you know, you.
Speaker 1: Know, I sort of have jokingly suggested that if you
Speaker 1: have got kind of mad at me, like from your perspectives,
Speaker 1: one is like, no, it's not a farmer's no, no, no,
Speaker 1: like just my regular road. So it was like, no,
Speaker 1: it's not an antrost concern, which it is not really
Speaker 1: an intro trust concern. But the other thing is, like
Speaker 1: I made that suggestion because the Justice Department a couple
Speaker 1: of months ago sued Real Page, which is like, I'm
Speaker 1: gonna exaggerate and say this, but for landlords, right, it's
Speaker 1: like a software product that tells landlords how much other
Speaker 1: landlords are charging for rent so they know how to
Speaker 1: set the rent on their apartments. And the Justice Department
Speaker 1: said that Real Page is fostering collusion among landlords and
Speaker 1: reducing competition in the rental space and raising prices for tenants.
Speaker 1: And I sort of tongue in cheek compared this Farmer's
Speaker 1: Market stuff to Real Page, and people got mad because
Speaker 1: they're like, but the Real Page case is real. There's
Speaker 1: more stuff there, right, like the right page case the
Speaker 1: Farmer's Market stuff they're essentially using fairly straightforward technology to
Speaker 1: aggregate prices at a bunch of farmers' markets and also supermarkets.
Speaker 1: Real page is getting private information from landlords, so it's
Speaker 1: like they get more information than just like what's available
Speaker 1: to the public. And they're also using it to suggest
Speaker 1: the landlords or this is what the Justice Department alledge is.
Speaker 1: They're using it to suggest that landlords raise their prices,
Speaker 1: and like they've explicitly said things like a rising tide
Speaker 1: lifts all butts. It's like they're like, you know, in
Speaker 1: the business of trying to make landlords try to high rents.
Speaker 1: This one is, you know, based on publicly available prices.
Speaker 1: It's harder to get mad at it. It seems to
Speaker 1: me that there is a real continuum and that it
Speaker 1: just used to be the case that it was hard
Speaker 1: to be sophisticated about knowing your competitors' prices in like
Speaker 1: all sorts of areas, because yeah, your competitors' prices weren't
Speaker 1: like easily available on the internet. And now it is
Speaker 1: so much easier to like aggregate public data about prices,
Speaker 1: and so now you can anyone can be more sensitive
Speaker 1: to like what their competitors are charging. And the just
Speaker 1: this department gets nervous about that. Not the farmers, but
Speaker 1: in general.
Speaker 2: The goal here for the farmers is explicitly to raise prices.
Speaker 1: Yeah, that's true.
Speaker 2: Like there's there's a quote from someone involved in other words,
Speaker 2: to give them a better day at the farmers market,
Speaker 2: because they're going to be there for eight or six hours,
Speaker 2: whether they make four hundred dollars or eight hundred dollars.
Speaker 2: So we're looking for how we can help them earn
Speaker 2: more in those hours. So that's the goal.
Speaker 1: That's the goal.
Speaker 2: They want the farmers to charge more. We should say
Speaker 2: this is from a Marketplace article. It was a really
Speaker 2: fun read, I realized. So I was reading your real
Speaker 2: page column and it occurred to me that perhaps I'm
Speaker 2: being naive. I just don't see any situation where there
Speaker 2: wouldn't be a race to the bottom.
Speaker 1: What do you mean a race to the bottom line,
Speaker 1: like in.
Speaker 2: Terms of like, okay, we're all only going to charge
Speaker 2: three thousand dollars per month, guys, that's the bottom. I
Speaker 2: feel like, why wouldn't you just undercut that?
Speaker 1: Right? I mean, these cases are weird, right, This notion
Speaker 1: of like tacit collusion or algorithmic collusion is different from
Speaker 1: a classic cartel where you get together in a room
Speaker 1: and you're like, none of us are going to charge
Speaker 1: less than three thousand dollars and if you do break
Speaker 1: your legs, right, there's no suggestion of breaking your legs here, right, this.
Speaker 2: Is just not written down.
Speaker 1: No, I don't think at all.
Speaker 2: Maybe choking. They're not going to break your legs, Matt.
Speaker 1: We'll get to a story about that. But there's no
Speaker 1: like explicit cartel. Right, It's just like everyone wants to
Speaker 1: charge as much as they can, and like they're limited
Speaker 1: by competitive pressures where they have to charge less. And
Speaker 1: there is this suggestion that if you know, oh, your competitors' prices,
Speaker 1: it is easier to not undercut them or to like
Speaker 1: undercut them less. Right, Like if you don't, like, if
Speaker 1: you don't know what everyone else is charging, you might
Speaker 1: be like, I want to be the low cost provider,
Speaker 1: and so I'll charge twenty seven hundred. But if you
Speaker 1: know what everyone else is charging, you can be like, oh,
Speaker 1: charge twenty nine ninety nine, right, Like you can it's
Speaker 1: a little bit easier to coordinate on the same price
Speaker 1: if you have complete information. This is the theory. It's
Speaker 1: not necessarily true, And the Justice Department has been interested
Speaker 1: in the idea of like price sharing because like there's
Speaker 1: this theory that if like competitors in an industry are
Speaker 1: getting together and sharing prices with each other, it's because
Speaker 1: it's anti competitive, right, you don't have to know exactly
Speaker 1: what they're doing at the price. You have to be like, well,
Speaker 1: if they're sharing prices with each other, that's probably not
Speaker 1: good for consumers, Like they're probably doing it for a
Speaker 1: reason that involves maximizing their profits. And the Justice Department
Speaker 1: has like long been interested in that, and they had
Speaker 1: guidelines that were like certain kinds of price sharing are okay,
Speaker 1: including like if it's aggregated and not like broken down
Speaker 1: by competitor. If you know what each of your competitors charges,
Speaker 1: then like you can break the legs of the one
Speaker 1: who charge with the least, right, Whereas if it's just aggregated,
Speaker 1: it's like a little bit more just informational. But you know,
Speaker 1: they say, like aggregated data is okay, and data published
Speaker 1: by a third party, so like a trade magazine publishing
Speaker 1: prices rather than the competitors getting together and sharing prices.
Speaker 1: They said that stuff was okay and recently, there's been
Speaker 1: a change in their guidance where they're like, we're gonna
Speaker 1: actually look at that stuff more closely. And I think
Speaker 1: the impression is that they are worried that machine learning
Speaker 1: algorithms are going to make companies better at using this
Speaker 1: data to price at the maximum level to extract profits,
Speaker 1: and like the sharing of data is going to make
Speaker 1: industries less competitive. So there's also this interesting paper from
Speaker 1: a couple of months ago by John Jung Jong of
Speaker 1: University of North Carolina called Salaries on Display Unintended Consequences
Speaker 1: of Wage Disclosure, or there's a paper about you know,
Speaker 1: there's a lot of states have wage transparency laws where
Speaker 1: like when you advertise a position, you have to say yeah, exactly.
Speaker 1: And Jong finds that though, seem to lead to lower
Speaker 1: wages because if you don't have information, like the market
Speaker 1: is going to have disparities, right, and like some people
Speaker 1: are going to pay more than others because they're ignorant, right,
Speaker 1: Whereas like, if you know what everyone else is paying,
Speaker 1: you're not gonna pay anymore, like a dollar more, or
Speaker 1: you'll like be a little competitive, but there will be
Speaker 1: no outliers. And so I think that's the same intuition
Speaker 1: with pricing stuff, where if everyone is sharing information, you
Speaker 1: won't have any outlier cheap providers because everyone knows, like
Speaker 1: you know, the market price is this, Like I shouldn't
Speaker 1: charge less.
Speaker 2: That's interesting. The thing that I think the wage dis
Speaker 2: goes your laws lead to is just super wide salary
Speaker 2: ranges that make no sense.
Speaker 1: But that's I agree with that, Like they don't seem
Speaker 1: to yeah, tell you that much, but.
Speaker 2: Yeah, do you want to talk about some meat prices?
Speaker 1: Sure?
Speaker 2: I actually looked at the website from Cornell. This is
Speaker 2: monthly data, so I don't think it's the weekly days.
Speaker 1: I don't going to be a long podcast where you
Speaker 1: read out the price.
Speaker 2: Well, I think it's interesting. So at the farmers market
Speaker 2: in September, we're looking at price summary statistics across multiple
Speaker 2: meat products collected from ten farms selling in twenty one
Speaker 2: different farmers' markets in New York State. For chuck roast
Speaker 2: in September, your weighted average price per pound was nine
Speaker 2: dollars and sixty cents. Can you guess what it was
Speaker 2: from the grocery store?
Speaker 1: Seven dollars and twenty cents.
Speaker 2: Eight dollars and twenty five.
Speaker 1: Cents I don't know if I was close.
Speaker 2: I think you're doing it. But that's the average price
Speaker 2: per pound versus the weighted average price.
Speaker 1: So farmer's market's barely charging more than the gross well,
Speaker 1: and like your experience can't be beat.
Speaker 2: Hold your horses there, my friends, a big farmer's market.
Speaker 2: Propose non organic bacon from the farmer's market in September
Speaker 2: according to this data, seventeen dollars and twenty one cents
Speaker 2: per pound. What do you think it was from the
Speaker 2: grocery store?
Speaker 1: Seven dollars per pound?
Speaker 2: So close, seven dollars and ninety eight cents per pounds.
Speaker 2: I said, eight, Quite a mark up, your baby.
Speaker 1: That farmer's market bacon. It's going to be delicious, is it.
Speaker 2: I don't know. I'm not a bacon person on.
Speaker 1: The big farmer's market. Great experience, great food. Yeah, garlic
Speaker 1: cannot be beat. The ginger I got up my local
Speaker 1: farmer's market astonishingly expensive, so good.
Speaker 2: We were driving back from Albany this past weekend and
Speaker 2: we went to a rest stop and there was a
Speaker 2: farmer's market outside, like on the highway.
Speaker 1: I'm sure that was great.
Speaker 2: I got some dried beat chips and.
Speaker 1: I got I know that stand but okay.
Speaker 2: Yeah it was on the cusp of New Jersey.
Speaker 1: No, I just mean, like, oh, there's like stands that
Speaker 1: you see a lot of.
Speaker 2: You also at the rest stop on the highway. Yeah,
Speaker 2: but I don't think I'm a farmer's market person. I
Speaker 2: don't think I have the patience. Anyway, that was a
Speaker 2: robust discussion.
Speaker 1: I want to add one more thing, which I did
Speaker 1: write about, but I love it so much. Yeah, I
Speaker 1: got an email from a reader about the Ottawa Farmer's
Speaker 1: market where this reader sold strawberries for a while. Yeah,
Speaker 1: and like out of those farmer's market had explicit price fixing,
Speaker 1: where like the rules of the farmer's market said you
Speaker 1: couldn't undercut the prices that they that were agreed on,
Speaker 1: and you didn't say that legs were broken. But a
Speaker 1: little bit of ploot. He found a loophole where it
Speaker 1: was like, you know, a four liter container of strawberries
Speaker 1: had to cost this much, and he realized that if
Speaker 1: he sold the two and a half liter container, non
Speaker 1: standard size container, he could undercut because there was no
Speaker 1: rule about selling that size container. Wow, so he would
Speaker 1: sell two and a half leaders for half the price
Speaker 1: of four leaders and get more business. The kicker to
Speaker 1: the story is that he's now a data scientist at
Speaker 1: a tech fron because because I assumed that like a
Speaker 1: tech FIM recruiter is like walking through the market and
Speaker 1: be like this guy, yeah knows how to price ad auctions.
Speaker 2: I wouldn't have guessed that the pipeline worked in that direction.
Speaker 2: But that's pretty cool. You're right.
Speaker 1: It would normally go and like, I don't know if
Speaker 1: he was a data scientist taking a break but strawberries, but.
Speaker 2: Maybe he was on gardening leaves. So private credit, in
Speaker 2: the sofer world of private credit, there's a lot going on,
Speaker 2: is there or are there just a lot of headlines?
Speaker 1: I don't know. There's a really interesting Financial Time story
Speaker 1: the title something like State Street is shopping for a
Speaker 1: private credit man.
Speaker 2: That's exactly what it is.
Speaker 1: Photographic memory. The thing that I thought was interesting is
Speaker 1: that the C States trade is like, yes, we're desperate
Speaker 1: for a private credit manager. Do you know any I
Speaker 1: need to I need to buy one right away. It's
Speaker 1: just like the like intensity of the search for like
Speaker 1: every big asset manager, Yeah really wants to buy a
Speaker 1: private credit manager, which is just like a great position
Speaker 1: to be in a few a few years ago launched
Speaker 1: your private credit for people are like, yeah, that's weird.
Speaker 1: Does that do? It was like a little bit of
Speaker 1: time where private credit was like, you know, like a
Speaker 1: little bit in the wilderness, like a little bit of
Speaker 1: a niche strategy. And now it's like all these managers
Speaker 1: are like State Street is kicking down their door.
Speaker 2: Yeah, I wish that that's how I had spent my pandemic.
Speaker 2: But here I am recording this podcast. But i's great.
Speaker 2: I kind of like the honesty and the aggression. So
Speaker 2: this is a CEO of State Street Global Advisors. It's
Speaker 2: their asset management arm. She said, this area is so
Speaker 2: well established, and given the size of our clients and
Speaker 2: their need to build and invest in a meaningful size,
Speaker 2: I think it just makes more sense for us to
Speaker 2: either partner or take a stake in a much more
Speaker 2: established firm where it's one plus one equals three. That's interesting,
Speaker 2: rather than trying to do it organically. They're like, we're
Speaker 2: behind already, let's go by the way.
Speaker 1: Do it organically isn't even a thing like do it
Speaker 1: organically means like, hey, huge guarantee is to the people
Speaker 1: you hire, right, there's no like the market for people
Speaker 1: in private credit is just really a pricey whether you're
Speaker 1: hiring them or buying their firms.
Speaker 2: Yeah, I started thinking about Apollo because she also said
Speaker 2: we're shopping for either a full acquisition or a minority
Speaker 2: state combined with product partnerships. And they have a planned
Speaker 2: product partnership with Apollo. That ETF filing heard around the
Speaker 2: world between Apollo and State Street for private credit ETF
Speaker 2: which I don't know if that one is going to launch.
Speaker 2: There's a lot of skepticism over that. But that's interesting.
Speaker 1: Oh sure, but like they want a private credit offering
Speaker 1: for their clients, right, Like they want to be able
Speaker 1: to chuck billions of dollars institutional money into a private
Speaker 1: credit offering, and everyone wants to that. Yeah, you know,
Speaker 1: if you are running a private credit firm, you're raising
Speaker 1: funds and like you're getting all these offers from all
Speaker 1: these traditional firms. Yeah, you know. There's another article in
Speaker 1: the Wall Street Journal about black Rock looking for alts
Speaker 1: managers like private credit or other like alternatives, and the
Speaker 1: reason for it is so clear, Like you can charge
Speaker 1: like roughly one order of magnitude more n fees for
Speaker 1: running alternatives than for running you know, traditional long only money.
Speaker 2: Well to the point that State Street be shopping, Blackrock
Speaker 2: has been shopping in a big way. I mean they
Speaker 2: bought Prequin for example, that was you know, for data
Speaker 2: Global Infrastructure Partners that finally closed.
Speaker 1: Yeah, by the way, I think I forget it was
Speaker 1: the State Street or something else. But like one of
Speaker 1: the articles is like they're shopping for a private credit
Speaker 1: or infrastructure, but it's like anything at all.
Speaker 2: Yeah, yeah, as long as it's alts. And also maybe
Speaker 2: Blackrock is going to buy HPS. I don't know.
Speaker 1: There's a fascinating story about HBS a while back. Hs
Speaker 1: is like nominally preparing an IPO, but like also shopping
Speaker 1: themselves hard to probably Blackrock. But also like there's talks
Speaker 1: of talk of like JP Morgan is like maybe like yeah,
Speaker 1: like Jamie Diamond, like I think was asked about buying
Speaker 1: a private credit for him and he's like, no, we
Speaker 1: would never do that, and then like came back later
Speaker 1: and it's like my team tells.
Speaker 2: Me we might Yeah, I've been in form Yeah.
Speaker 1: Yeah, Like they're like they're like pulled them back. But
Speaker 1: a lot of ways that HPS could go but one
Speaker 1: of those ways is selling themselves the black Rock for
Speaker 1: an enormous premium.
Speaker 2: This strategy has worked out for black Rock. They have
Speaker 2: like four hundred and fifty billion dollars in alts. At
Speaker 2: least one hundred and sixteen billion dollars is coming from
Speaker 2: GIP for example. So it's a really easy way to
Speaker 2: just scale up.
Speaker 1: Yeah, I mean like scale up, Like you know, it's
Speaker 1: like what like four percent of black Rocks assets, right,
Speaker 1: but it's like the very juicy four percent, right, It's
Speaker 1: like the.
Speaker 2: Four percent that makes a lot of money.
Speaker 1: Yeah, you charge, it makes a lot of the money,
Speaker 1: and it gets a higher multiple, and it's like, yeah,
Speaker 1: it's just like really attractive. And like, you know, saying
Speaker 1: we're a giant index fund provider is just less appealing
Speaker 1: to investors now than saying we're a giant ults provider.
Speaker 2: I have some numbers in your column. You reference this
Speaker 2: Wall Street Journal article that pointed out that Blackrocks market
Speaker 2: cap is similar to those of Blackstone, Apollo, KKR, et cetera,
Speaker 2: even though Blackrock manages like eleven and a half trillion
Speaker 2: and they manage a fraction of that. I wrote about
Speaker 2: this in mid October following BlackRock's earnings, just about how
Speaker 2: much money they make per dollar of AUM. And for Blackrock,
Speaker 2: it's like, according to Bloomberg Intelligence, they have an annualized
Speaker 2: fee rate of fourteen point six basis points. You compare
Speaker 2: that to Apollo, and it's something like fifty two basis points.
Speaker 2: So I would have guessed the higher number for Apollo. Well,
Speaker 2: apparently for Blackstone and KKR and Ares, that figure ranges
Speaker 2: from fifty basis points to like one hundred basis points, right, So.
Speaker 1: Yeah, classically two and twenty right, Yeah, but like it's
Speaker 1: a much, much, much richer fee product. And like a
Speaker 1: lot of the stories about private credit are like, wow,
Speaker 1: there's so much more money in this.
Speaker 2: Oh my gosh.
Speaker 1: This is a Bloomberg article from September Bonus starved bankers
Speaker 1: are a jumping ship for private credit riches. Yeah, why
Speaker 1: wouldn't you do that?
Speaker 2: That makes sense?
Speaker 1: You know, all these like private credit funds are started
Speaker 1: by people who are like you know, lib fin bankers
Speaker 1: at Coldman and like went to start their own funds
Speaker 1: when that was like a somewhat contrariy and move, and
Speaker 1: now they can sell their firms for billions of dollars
Speaker 1: to Blackrock.
Speaker 2: If I could do it, I would.
Speaker 1: It's just like, you know, one thing I write about
Speaker 1: this is like it seems hard to run a private
Speaker 1: credit fund now from the perspective of like being an investor.
Speaker 1: Josh Harris said to David Rubinston the other day that
Speaker 1: like a lot of these alts funds are like the
Speaker 1: beata of aults. Right, private credit like its core is
Speaker 1: like direct lending to leverage biots, And so you are
Speaker 1: in a business of like being friends with twenty private
Speaker 1: equity sponsors, and when they do a biot, they call
Speaker 1: you and they say, would you like to lend us
Speaker 1: the money? And you say yes? Because you say no,
Speaker 1: and they stop calling you, and then you don't have
Speaker 1: the paper to feed your hungry investors. And so there's
Speaker 1: this sense in prior credit that, like, it is hard
Speaker 1: to be a disciplined investor, and it's hard to look
Speaker 1: for value and make do really careful credit work because
Speaker 1: you're essentially in the business of saying yes to every
Speaker 1: buyout that gets offered to you because you just have
Speaker 1: to do deals. But it's a great time to be
Speaker 1: selling your private credit front, right, Yeah, you know, it's
Speaker 1: a huge boom that like any huge room makes it
Speaker 1: hard to be like a careful investor because like you
Speaker 1: have to deploy a lot of money, but like it's
Speaker 1: a great time to be a seller.
Speaker 2: Yeah. I was actually just having this conversation with a
Speaker 2: private credit person, and this person was talking about how
Speaker 2: there's private credit beta right now, and you know you
Speaker 2: have to get more esoteric to find the alpha, et cetera.
Speaker 1: You don't have to find the alpha. You charged two
Speaker 1: percent and you know you judge, you judge fifty vasis points.
Speaker 2: And you can at least this person would like to.
Speaker 1: That's why I'm saying it's hard because like everyone is
Speaker 1: like constitutionally like wants to be doing good deals and
Speaker 1: not doing bad deals. But there's a lot of money
Speaker 1: in doing like private credit paida.
Speaker 2: Let's talk about some trade secrets.
Speaker 1: So there's a Bloomberg story about Shao Xiang, who's the
Speaker 1: founder of Pinestone, which is a big and very successful
Speaker 1: quant fund in China. He was charged criminally in Boston
Speaker 1: Federal Court in Boston for allegedly he had a former
Speaker 1: job at an American asset manager and he like allegedly
Speaker 1: they downloaded all the models. It's like left for Actually
Speaker 1: he left for China and downloaded all the models.
Speaker 2: He was out of the country first, out of the country.
Speaker 1: First, which is smart. There's another story a while back
Speaker 1: about a guy who did the reverse, Like he downloaded
Speaker 1: the models and then he left the country like that night,
Speaker 1: and like by the time he landed, they have them
Speaker 1: to tand and like it. It didn't work out for him.
Speaker 1: But this guy left the country first, wasn't supposed to
Speaker 1: be able to get into his corporate hard drive, but
Speaker 1: right used the VP and to somehow log into work
Speaker 1: from China, which I think is probably not technically feasible
Speaker 1: anymore at most quant firms. But he allegedly did it,
Speaker 1: and he allegedly downloaded all the models, and it's an indictment.
Speaker 1: It's not full of detail. There's a suggestion that he
Speaker 1: used these models to set up his now very successful
Speaker 1: Chinese quand fundt. I don't know if that's even what
Speaker 1: they're charging, but like there's a hint that like these
Speaker 1: things were useful in his subsequent career.
Speaker 2: So well, I would like to know his returns.
Speaker 1: Well, they're great.
Speaker 2: Well, you point out on your column that the US
Speaker 2: market is different than the Chinese market.
Speaker 1: It's very different. You know, there's been a lot of
Speaker 1: stories about like Chinese quand funds getting wrecked in like
Speaker 1: regime changes, where yes, the Chinese governments like oh, you
Speaker 1: like can't bet again stocks or whatever, and like you know,
Speaker 1: your long short fund just that you know, explodes because
Speaker 1: you can't be short anymore. You know. You think of
Speaker 1: like a quant fund stereotypically being trained on some relatively
Speaker 1: recent history and being bad at like adapting to sharp
Speaker 1: changes and like how the world works. Yeah, it's like
Speaker 1: probably an overly simplified stereotype. And like some quant algorithms
Speaker 1: are really good at adjusting to new information, but like
Speaker 1: you know, that's the stereotype, and like it does seem
Speaker 1: hard to run a quant fund that is, like these
Speaker 1: are the returns of going along this basket of stocks
Speaker 1: and going short that basket of stocks, and then like
Speaker 1: you updated for you can't short stocks anymore.
Speaker 2: Like this seems hard, yeah, Or the government comes in
Speaker 2: with like a ton of stimulus and just completely changes
Speaker 2: the narrative, right exactly right, they develop it, which we
Speaker 2: saw a couple of weeks ago.
Speaker 1: It's not necessarily that's right, Like the economic environment can
Speaker 1: change rapidly, and it does seem very hard to deal
Speaker 1: with that, and like there were a lot of quant
Speaker 1: funds that blew up, And as a sort of like
Speaker 1: amateur tourist reading those stories, I'm like the lessons of
Speaker 1: like the sort of classical development of like quantu investing
Speaker 1: in the US might not apply perfectly to China, but
Speaker 1: presumably people know that, right, But it's like, well, they
Speaker 1: stole the code, but like, by the way, his firm
Speaker 1: is doing great if you just stole the card and
Speaker 1: like plugged in like us trading into Chinese markets, Like
Speaker 1: either that worked really well or like there's something we're
Speaker 1: missing there.
Speaker 2: Perhaps he tweaked it a little bit. You could draw
Speaker 2: parallels to another case we've talked about that was Jane
Speaker 2: Street and Millennium's trade secrets. Tell us about the nuances here.
Speaker 1: Well, I mean one thing is like there's actually a
Speaker 1: lot of these cases where the person gets charged criminally.
Speaker 1: I was going to say arrested, but this guy's not
Speaker 1: been arrested because he was out of the country. But
Speaker 1: like the number of them get arrested, you know, like
Speaker 1: the one that is famous as Sergei Atlanikov, who allegedly
Speaker 1: stole code from Goldman Sachs and got arrested and so
Speaker 1: quite a long time in jail before It's like, I
Speaker 1: think his convictions are ultimately overturned, and he was like
Speaker 1: he had kind of a rough go of it. He
Speaker 1: was arrested roughly the time that I left Goldman, And
Speaker 1: although I did not steal any.
Speaker 2: Code, I like, do you want to say that again?
Speaker 1: I did not steal any code, to be clear, but
Speaker 1: I was worried because I was going into media and
Speaker 1: I was like, what if they get mad at me
Speaker 1: and say that I stole code. It's a real time
Speaker 1: of like looked like Goldman could have you put in
Speaker 1: prison if they didn't like you, right, look to me
Speaker 1: like that because I was a parent. Anyway, they put
Speaker 1: him in prison. But like you know, the Jane Street stuff,
Speaker 1: no one's going to get put in prison for a
Speaker 1: variety of reasons, but a big one is like, there's
Speaker 1: no allegation of code stealing, right, There's a difference between
Speaker 1: stealing ideas, which is like a really fuzzy area, right,
Speaker 1: Like Jane Street is like convinced that these traders stole
Speaker 1: a proprietary, complicated trading strategy that was developed with like
Speaker 1: much work and investment at Jane Street and belongs to
Speaker 1: Jane Street, and like Millennium is like, no, these guys
Speaker 1: like you know, they how to trade options and now
Speaker 1: they're trading options for us. There's nothing proprietary about that.
Speaker 1: I think probably the truth of somewhere in between. But
Speaker 1: like even if Chain Street is right, that kind of
Speaker 1: like know how you can get mad, you can get sued,
Speaker 1: you can be like stopped from working at the new firm.
Speaker 1: You like have to pay them back, but you're not
Speaker 1: gonna go to jail for that, probably not legal advice,
Speaker 1: whereas like if you like download code from a VPN, like, yeah,
Speaker 1: you can go to jail.
Speaker 2: Yeah if you're caught, Well, this guy, what's gonna happen
Speaker 2: to him? Because he isn't trya nothing.
Speaker 1: So this is interesting take it back to the US.
Speaker 1: It's like it's like a real consequence.
Speaker 2: Yeah, that is a consequence. Does his firm get to
Speaker 2: keep doing great and using these models?
Speaker 1: There's a widespread assumption that like this stuff decays. Yeah,
Speaker 1: maybe he downloaded like the whole like framework for how
Speaker 1: to build you know, a quantitative trading firm. But like
Speaker 1: that stuff is kind of public domain, you know, to
Speaker 1: the extent he downloaded, like signals, those decay, Like no one,
Speaker 1: no one thinks that like three years after you're stolen
Speaker 1: stuff from your firm, it's still I mean maybe if
Speaker 1: it was renaissance, but like yeah, for the most part,
Speaker 1: like the Stuffycays and so there's like there's this notion
Speaker 1: that like you have to be stopped from using it
Speaker 1: for some period of time, but then after that it's
Speaker 1: probably not worth worrying about. Yeah, Like you see that
Speaker 1: in the Jane Street case where it's like whatever secret
Speaker 1: trade they're doing options in India, but Options in India
Speaker 1: doesn't tell you very much about the trade. Like Jane
Speaker 1: secretal sides out like some very complicated, you know, clever implementation,
Speaker 1: but uh, no one thinks that's going to make one
Speaker 1: hundred million dollars a year forever. You know. Like it's
Speaker 1: like Jane Street had some window in which to use
Speaker 1: that in which to do that trade, and then like
Speaker 1: Millennium butted in and now they you know, have to
Speaker 1: put the profits where the profits go away. Probably that's
Speaker 1: what's happening here. But also I can't be like shooting
Speaker 1: the lights out trading Quantu and China solely with stolen models.
Speaker 2: He's only thirty three, yeah, yeah, and he stole these
Speaker 2: secrets allegedly in twenty twenty one.
Speaker 1: That's the other cool thing is like the indictment says
Speaker 1: that he was an associate and was not responsible for
Speaker 1: these models. Like often you have some dispute about like
Speaker 1: whether the person was like downloading their own work, yeah,
Speaker 1: or but here the implication is kind of like you
Speaker 1: like shut up as an associate, did the training and
Speaker 1: then like downloaded all the models and left. You know,
Speaker 1: there's like your implication that like he was he was
Speaker 1: just taking other people's work.
Speaker 2: This did prompt a response from your readers, as I
Speaker 2: understand it.
Speaker 1: Oh yeah, so I wrote about like the high level
Speaker 1: problems with doing this, right, like if you just download
Speaker 1: code and then go start your own firm, like the
Speaker 1: big problem is that you get arrested. Yeah, it was
Speaker 1: like you know, moving to China like solves that problem.
Speaker 1: But then like a secondary problem is like you're crowding
Speaker 1: a trade that is there's not that much profit in
Speaker 1: it necessarily, so like if you and your your old
Speaker 1: firm are both doing it, like you're both make less money.
Speaker 1: One reader pointed out that actually the biggest problem with
Speaker 1: this because of getting arrested is raising money clients. Yeah,
Speaker 1: because like if you work at a hedge fund and
Speaker 1: you download their code, then like how do you raise money?
Speaker 1: You're like I still could from my old hedge fund,
Speaker 1: Like no one's gonna invest with you that. Or you
Speaker 1: can be like I'm just really smart, I have some
Speaker 1: great ideas, but it's like or you should be.
Speaker 2: Like I'm gonna undercut that hedge fund and I'm going
Speaker 2: to give it to you at a cheaper price, which
Speaker 2: gets us neatly back to farmers' markets.
Speaker 1: It does, but I do think that that pitch, well,
Speaker 1: it might work for garlic, is very bad for a
Speaker 1: hedge fund client, Yeah, because you're just like you're taking
Speaker 1: out a lot of like operational and regulatory and reputational
Speaker 1: risk for like saving some money because like you know,
Speaker 1: like this hedgehund strategy fell off the back of a
Speaker 1: truck and I'll give it to you for cheap. Like
Speaker 1: that thought that's not a good like long term strategy
Speaker 1: for like an endowment. But moving to China and saying, hey,
Speaker 1: we've developed our skills at like a leading US institution
Speaker 1: and now we can apply them to this. It's somewhat
Speaker 1: like less fully efficient market. That's a good pitch. And
Speaker 1: if you're like nudge, nudge, wink wink. Also we stole
Speaker 1: the models like maybe that's a fine touch too, don't Yeah,
Speaker 1: And that was the Money Stuff Podcast.
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