1 00:00:03,120 --> 00:00:12,799 Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. Hello and welcome to 2 00:00:12,800 --> 00:00:15,640 Speaker 1: the Money Stuff Podcast. You're a weekly podcast where we 3 00:00:15,680 --> 00:00:20,079 Speaker 1: talk about stuff related to money. I'm Matt Levian and 4 00:00:20,120 --> 00:00:22,239 Speaker 1: I write the Money Stuff column for Bloomberg Opinion. 5 00:00:22,400 --> 00:00:25,040 Speaker 2: And I'm Katie Greifeld, a reporter for Bloomberg News and 6 00:00:25,079 --> 00:00:26,680 Speaker 2: an anchor for Bloomberg Television. 7 00:00:28,000 --> 00:00:29,639 Speaker 1: What are we talking about today, Katie? 8 00:00:29,760 --> 00:00:32,120 Speaker 2: We're going to talk about farmers markets, We're going to 9 00:00:32,159 --> 00:00:34,920 Speaker 2: talk about private credit, and then we're going to talk 10 00:00:34,960 --> 00:00:38,080 Speaker 2: about stealing some trade secrets and moving to China. 11 00:00:38,680 --> 00:00:39,360 Speaker 1: That sounds good. 12 00:00:45,720 --> 00:00:49,600 Speaker 2: I printed out the pricing charts for like beef, so 13 00:00:50,280 --> 00:00:51,360 Speaker 2: we have a meaty section. 14 00:00:51,640 --> 00:00:53,760 Speaker 1: I was at the one of the farmer's markets near me. 15 00:00:53,840 --> 00:00:57,000 Speaker 1: I go to two farmers' markets per weekend. I was 16 00:00:57,080 --> 00:01:02,720 Speaker 1: recognized by a person working at one of the stands. Wow, 17 00:01:02,840 --> 00:01:07,920 Speaker 1: it works in financial media and also works at the 18 00:01:07,959 --> 00:01:10,440 Speaker 1: farmer's market to get her mind off things, and she's 19 00:01:10,480 --> 00:01:13,480 Speaker 1: apparently a fan of mine, and offered me free garlic. 20 00:01:13,880 --> 00:01:18,720 Speaker 2: Did you take it? So you took the free garlic, 21 00:01:18,800 --> 00:01:22,320 Speaker 2: and then you undercut some farm stands. Some farmer who 22 00:01:22,400 --> 00:01:25,640 Speaker 2: like put in the labor, and you knew what to charge. 23 00:01:26,040 --> 00:01:29,200 Speaker 1: Because this is before I knew anything about farmer's market pricing. 24 00:01:29,240 --> 00:01:31,280 Speaker 1: I was a babe in the woods in terms. 25 00:01:31,120 --> 00:01:33,000 Speaker 2: Of oh, I thought this was like last weekend. 26 00:01:33,400 --> 00:01:35,679 Speaker 1: No, it was like three weekends. 27 00:01:36,560 --> 00:01:39,280 Speaker 2: Okay, if only you had known. 28 00:01:39,560 --> 00:01:41,959 Speaker 1: But I do not honestly pay that much attention to 29 00:01:42,040 --> 00:01:45,320 Speaker 1: pricing at the farmer's markets. But I am aware of 30 00:01:45,360 --> 00:01:48,520 Speaker 1: the disparity in garlic pricing at the different stands. There's 31 00:01:48,880 --> 00:01:52,880 Speaker 1: a stand where I have seen but not purchased garlic 32 00:01:52,960 --> 00:01:56,640 Speaker 1: for three dollars ahead. Seems really high for garlic. But 33 00:01:56,760 --> 00:01:59,720 Speaker 1: also the farmers garlic is so good, Like I now 34 00:02:00,080 --> 00:02:02,800 Speaker 1: they got farmer's market garlic can probably pay five x 35 00:02:02,880 --> 00:02:05,280 Speaker 1: what i'd pat agressory store. Me. 36 00:02:05,400 --> 00:02:08,360 Speaker 2: Trying to think of something relatable to say reminds me 37 00:02:08,600 --> 00:02:12,640 Speaker 2: of the Arrested development scene or Luciel's like it's a banana, Michael, 38 00:02:12,680 --> 00:02:15,160 Speaker 2: how much could it cost? Or something like that. Yeah, 39 00:02:15,200 --> 00:02:16,840 Speaker 2: I feel like if you're at a farmer's market, you're 40 00:02:16,880 --> 00:02:18,840 Speaker 2: kind of a price and sensitive buyer of produce. 41 00:02:18,960 --> 00:02:21,040 Speaker 1: I'm pretty close to the ideal of price and sensitive 42 00:02:21,080 --> 00:02:24,160 Speaker 1: buyer of produce. But even I was like three dollars garlic, hold. 43 00:02:24,040 --> 00:02:27,360 Speaker 2: On whoa, it's too rich for my blood. Well, what 44 00:02:27,480 --> 00:02:30,560 Speaker 2: a timely conversation that we're organically having about pricing at 45 00:02:30,560 --> 00:02:31,440 Speaker 2: farmers markets. 46 00:02:31,760 --> 00:02:34,160 Speaker 1: It's all I think about. Yeah, sorry, I just said 47 00:02:34,160 --> 00:02:35,600 Speaker 1: if not anything, I think about it at all, and 48 00:02:35,600 --> 00:02:38,560 Speaker 1: I'm totally which is closer to the truth. But now 49 00:02:38,600 --> 00:02:40,160 Speaker 1: I'm thinking about pricing at farmer's markets. 50 00:02:40,240 --> 00:02:43,960 Speaker 2: Yeah, so is Cornell University question mark great transition. Yeah, 51 00:02:44,160 --> 00:02:46,320 Speaker 2: why don't you tell me about what they're doing. 52 00:02:46,720 --> 00:02:50,240 Speaker 1: They're aggregating prices for farmers. They have like a website 53 00:02:50,280 --> 00:02:54,239 Speaker 1: that publishes free information on prices of various agricultural goods 54 00:02:54,880 --> 00:02:59,040 Speaker 1: for farmers at farmers' markets to basically help them set 55 00:02:59,080 --> 00:03:01,720 Speaker 1: their prices. Because if you're a farmer at a farmer's market, 56 00:03:01,760 --> 00:03:04,840 Speaker 1: you you know, are in the business of working the land, 57 00:03:05,000 --> 00:03:07,840 Speaker 1: ground the produce, and you're maybe not like a savvy 58 00:03:08,080 --> 00:03:12,160 Speaker 1: pricer of produce at farmers markets, and you know, the 59 00:03:12,200 --> 00:03:15,040 Speaker 1: buyers at farmer's markets are not necessarily savvy pricers of 60 00:03:15,080 --> 00:03:17,120 Speaker 1: produce either, so you could probably charge them a lot 61 00:03:17,120 --> 00:03:19,320 Speaker 1: more than you do, and Cornell is helping you charge 62 00:03:19,360 --> 00:03:20,880 Speaker 1: them more than you do by telling you what the 63 00:03:20,960 --> 00:03:22,440 Speaker 1: actual price of garlic is. 64 00:03:22,600 --> 00:03:26,639 Speaker 2: Seems like a real antitrust concern potentially, you know, you. 65 00:03:26,720 --> 00:03:29,679 Speaker 1: Know, I sort of have jokingly suggested that if you 66 00:03:29,760 --> 00:03:32,440 Speaker 1: have got kind of mad at me, like from your perspectives, 67 00:03:32,440 --> 00:03:34,840 Speaker 1: one is like, no, it's not a farmer's no, no, no, 68 00:03:34,880 --> 00:03:37,440 Speaker 1: like just my regular road. So it was like, no, 69 00:03:37,520 --> 00:03:39,760 Speaker 1: it's not an antrost concern, which it is not really 70 00:03:39,800 --> 00:03:42,000 Speaker 1: an intro trust concern. But the other thing is, like 71 00:03:42,520 --> 00:03:45,320 Speaker 1: I made that suggestion because the Justice Department a couple 72 00:03:45,360 --> 00:03:49,080 Speaker 1: of months ago sued Real Page, which is like, I'm 73 00:03:49,080 --> 00:03:53,160 Speaker 1: gonna exaggerate and say this, but for landlords, right, it's 74 00:03:53,240 --> 00:03:56,920 Speaker 1: like a software product that tells landlords how much other 75 00:03:57,000 --> 00:03:59,360 Speaker 1: landlords are charging for rent so they know how to 76 00:03:59,400 --> 00:04:01,920 Speaker 1: set the rent on their apartments. And the Justice Department 77 00:04:02,000 --> 00:04:05,839 Speaker 1: said that Real Page is fostering collusion among landlords and 78 00:04:05,920 --> 00:04:11,120 Speaker 1: reducing competition in the rental space and raising prices for tenants. 79 00:04:11,680 --> 00:04:15,280 Speaker 1: And I sort of tongue in cheek compared this Farmer's 80 00:04:15,320 --> 00:04:17,720 Speaker 1: Market stuff to Real Page, and people got mad because 81 00:04:17,720 --> 00:04:20,320 Speaker 1: they're like, but the Real Page case is real. There's 82 00:04:20,440 --> 00:04:22,880 Speaker 1: more stuff there, right, like the right page case the 83 00:04:22,920 --> 00:04:28,080 Speaker 1: Farmer's Market stuff they're essentially using fairly straightforward technology to 84 00:04:28,160 --> 00:04:31,480 Speaker 1: aggregate prices at a bunch of farmers' markets and also supermarkets. 85 00:04:32,040 --> 00:04:36,640 Speaker 1: Real page is getting private information from landlords, so it's 86 00:04:36,680 --> 00:04:39,200 Speaker 1: like they get more information than just like what's available 87 00:04:39,240 --> 00:04:41,719 Speaker 1: to the public. And they're also using it to suggest 88 00:04:41,720 --> 00:04:44,039 Speaker 1: the landlords or this is what the Justice Department alledge is. 89 00:04:44,160 --> 00:04:47,240 Speaker 1: They're using it to suggest that landlords raise their prices, 90 00:04:47,560 --> 00:04:49,800 Speaker 1: and like they've explicitly said things like a rising tide 91 00:04:49,839 --> 00:04:52,040 Speaker 1: lifts all butts. It's like they're like, you know, in 92 00:04:52,080 --> 00:04:54,880 Speaker 1: the business of trying to make landlords try to high rents. 93 00:04:55,040 --> 00:04:58,359 Speaker 1: This one is, you know, based on publicly available prices. 94 00:04:58,520 --> 00:05:00,839 Speaker 1: It's harder to get mad at it. It seems to 95 00:05:00,880 --> 00:05:03,440 Speaker 1: me that there is a real continuum and that it 96 00:05:03,560 --> 00:05:06,719 Speaker 1: just used to be the case that it was hard 97 00:05:07,040 --> 00:05:11,240 Speaker 1: to be sophisticated about knowing your competitors' prices in like 98 00:05:11,320 --> 00:05:14,120 Speaker 1: all sorts of areas, because yeah, your competitors' prices weren't 99 00:05:14,160 --> 00:05:17,359 Speaker 1: like easily available on the internet. And now it is 100 00:05:17,400 --> 00:05:19,880 Speaker 1: so much easier to like aggregate public data about prices, 101 00:05:19,920 --> 00:05:23,560 Speaker 1: and so now you can anyone can be more sensitive 102 00:05:23,560 --> 00:05:26,520 Speaker 1: to like what their competitors are charging. And the just 103 00:05:26,600 --> 00:05:28,960 Speaker 1: this department gets nervous about that. Not the farmers, but 104 00:05:29,000 --> 00:05:29,480 Speaker 1: in general. 105 00:05:29,600 --> 00:05:33,960 Speaker 2: The goal here for the farmers is explicitly to raise prices. 106 00:05:34,040 --> 00:05:34,799 Speaker 1: Yeah, that's true. 107 00:05:35,040 --> 00:05:38,599 Speaker 2: Like there's there's a quote from someone involved in other words, 108 00:05:38,640 --> 00:05:40,360 Speaker 2: to give them a better day at the farmers market, 109 00:05:40,440 --> 00:05:42,760 Speaker 2: because they're going to be there for eight or six hours, 110 00:05:42,760 --> 00:05:45,360 Speaker 2: whether they make four hundred dollars or eight hundred dollars. 111 00:05:45,680 --> 00:05:47,560 Speaker 2: So we're looking for how we can help them earn 112 00:05:47,640 --> 00:05:51,359 Speaker 2: more in those hours. So that's the goal. 113 00:05:51,720 --> 00:05:52,440 Speaker 1: That's the goal. 114 00:05:52,560 --> 00:05:54,840 Speaker 2: They want the farmers to charge more. We should say 115 00:05:54,880 --> 00:05:57,320 Speaker 2: this is from a Marketplace article. It was a really 116 00:05:57,320 --> 00:06:01,600 Speaker 2: fun read, I realized. So I was reading your real 117 00:06:01,640 --> 00:06:05,840 Speaker 2: page column and it occurred to me that perhaps I'm 118 00:06:05,839 --> 00:06:09,280 Speaker 2: being naive. I just don't see any situation where there 119 00:06:09,279 --> 00:06:10,599 Speaker 2: wouldn't be a race to the bottom. 120 00:06:10,720 --> 00:06:11,960 Speaker 1: What do you mean a race to the bottom line, 121 00:06:12,040 --> 00:06:12,280 Speaker 1: like in. 122 00:06:12,240 --> 00:06:14,440 Speaker 2: Terms of like, okay, we're all only going to charge 123 00:06:14,440 --> 00:06:18,400 Speaker 2: three thousand dollars per month, guys, that's the bottom. I 124 00:06:18,440 --> 00:06:21,000 Speaker 2: feel like, why wouldn't you just undercut that? 125 00:06:21,360 --> 00:06:24,719 Speaker 1: Right? I mean, these cases are weird, right, This notion 126 00:06:24,800 --> 00:06:29,400 Speaker 1: of like tacit collusion or algorithmic collusion is different from 127 00:06:29,560 --> 00:06:31,760 Speaker 1: a classic cartel where you get together in a room 128 00:06:31,800 --> 00:06:33,520 Speaker 1: and you're like, none of us are going to charge 129 00:06:33,560 --> 00:06:35,240 Speaker 1: less than three thousand dollars and if you do break 130 00:06:35,240 --> 00:06:38,680 Speaker 1: your legs, right, there's no suggestion of breaking your legs here, right, this. 131 00:06:38,600 --> 00:06:39,839 Speaker 2: Is just not written down. 132 00:06:39,920 --> 00:06:41,800 Speaker 1: No, I don't think at all. 133 00:06:41,960 --> 00:06:44,600 Speaker 2: Maybe choking. They're not going to break your legs, Matt. 134 00:06:46,400 --> 00:06:48,880 Speaker 1: We'll get to a story about that. But there's no 135 00:06:48,960 --> 00:06:51,719 Speaker 1: like explicit cartel. Right, It's just like everyone wants to 136 00:06:51,760 --> 00:06:53,560 Speaker 1: charge as much as they can, and like they're limited 137 00:06:53,560 --> 00:06:56,280 Speaker 1: by competitive pressures where they have to charge less. And 138 00:06:56,800 --> 00:07:01,719 Speaker 1: there is this suggestion that if you know, oh, your competitors' prices, 139 00:07:01,760 --> 00:07:05,560 Speaker 1: it is easier to not undercut them or to like 140 00:07:05,680 --> 00:07:08,400 Speaker 1: undercut them less. Right, Like if you don't, like, if 141 00:07:08,440 --> 00:07:11,720 Speaker 1: you don't know what everyone else is charging, you might 142 00:07:11,920 --> 00:07:13,640 Speaker 1: be like, I want to be the low cost provider, 143 00:07:13,680 --> 00:07:15,720 Speaker 1: and so I'll charge twenty seven hundred. But if you 144 00:07:15,760 --> 00:07:17,120 Speaker 1: know what everyone else is charging, you can be like, oh, 145 00:07:17,240 --> 00:07:19,560 Speaker 1: charge twenty nine ninety nine, right, Like you can it's 146 00:07:19,600 --> 00:07:23,000 Speaker 1: a little bit easier to coordinate on the same price 147 00:07:23,240 --> 00:07:25,960 Speaker 1: if you have complete information. This is the theory. It's 148 00:07:26,000 --> 00:07:29,840 Speaker 1: not necessarily true, And the Justice Department has been interested 149 00:07:29,880 --> 00:07:33,360 Speaker 1: in the idea of like price sharing because like there's 150 00:07:33,400 --> 00:07:35,440 Speaker 1: this theory that if like competitors in an industry are 151 00:07:35,480 --> 00:07:38,400 Speaker 1: getting together and sharing prices with each other, it's because 152 00:07:38,400 --> 00:07:41,120 Speaker 1: it's anti competitive, right, you don't have to know exactly 153 00:07:41,120 --> 00:07:42,440 Speaker 1: what they're doing at the price. You have to be like, well, 154 00:07:42,440 --> 00:07:44,560 Speaker 1: if they're sharing prices with each other, that's probably not 155 00:07:44,600 --> 00:07:46,600 Speaker 1: good for consumers, Like they're probably doing it for a 156 00:07:46,680 --> 00:07:50,200 Speaker 1: reason that involves maximizing their profits. And the Justice Department 157 00:07:50,200 --> 00:07:52,960 Speaker 1: has like long been interested in that, and they had 158 00:07:53,000 --> 00:07:55,840 Speaker 1: guidelines that were like certain kinds of price sharing are okay, 159 00:07:55,880 --> 00:07:58,760 Speaker 1: including like if it's aggregated and not like broken down 160 00:07:58,760 --> 00:08:02,000 Speaker 1: by competitor. If you know what each of your competitors charges, 161 00:08:02,040 --> 00:08:03,640 Speaker 1: then like you can break the legs of the one 162 00:08:03,640 --> 00:08:06,000 Speaker 1: who charge with the least, right, Whereas if it's just aggregated, 163 00:08:06,000 --> 00:08:08,800 Speaker 1: it's like a little bit more just informational. But you know, 164 00:08:08,800 --> 00:08:11,760 Speaker 1: they say, like aggregated data is okay, and data published 165 00:08:11,760 --> 00:08:14,040 Speaker 1: by a third party, so like a trade magazine publishing 166 00:08:14,080 --> 00:08:17,520 Speaker 1: prices rather than the competitors getting together and sharing prices. 167 00:08:17,920 --> 00:08:20,600 Speaker 1: They said that stuff was okay and recently, there's been 168 00:08:20,600 --> 00:08:22,120 Speaker 1: a change in their guidance where they're like, we're gonna 169 00:08:22,120 --> 00:08:23,880 Speaker 1: actually look at that stuff more closely. And I think 170 00:08:23,920 --> 00:08:27,440 Speaker 1: the impression is that they are worried that machine learning 171 00:08:27,480 --> 00:08:31,000 Speaker 1: algorithms are going to make companies better at using this 172 00:08:31,160 --> 00:08:35,079 Speaker 1: data to price at the maximum level to extract profits, 173 00:08:35,120 --> 00:08:37,400 Speaker 1: and like the sharing of data is going to make 174 00:08:37,480 --> 00:08:41,240 Speaker 1: industries less competitive. So there's also this interesting paper from 175 00:08:41,280 --> 00:08:43,640 Speaker 1: a couple of months ago by John Jung Jong of 176 00:08:43,920 --> 00:08:48,959 Speaker 1: University of North Carolina called Salaries on Display Unintended Consequences 177 00:08:49,000 --> 00:08:51,800 Speaker 1: of Wage Disclosure, or there's a paper about you know, 178 00:08:52,080 --> 00:08:54,199 Speaker 1: there's a lot of states have wage transparency laws where 179 00:08:54,240 --> 00:08:57,559 Speaker 1: like when you advertise a position, you have to say yeah, exactly. 180 00:08:58,160 --> 00:09:02,480 Speaker 1: And Jong finds that though, seem to lead to lower 181 00:09:02,520 --> 00:09:06,520 Speaker 1: wages because if you don't have information, like the market 182 00:09:06,559 --> 00:09:08,920 Speaker 1: is going to have disparities, right, and like some people 183 00:09:08,960 --> 00:09:11,160 Speaker 1: are going to pay more than others because they're ignorant, right, 184 00:09:11,240 --> 00:09:12,920 Speaker 1: Whereas like, if you know what everyone else is paying, 185 00:09:12,920 --> 00:09:15,480 Speaker 1: you're not gonna pay anymore, like a dollar more, or 186 00:09:15,520 --> 00:09:17,840 Speaker 1: you'll like be a little competitive, but there will be 187 00:09:17,840 --> 00:09:20,480 Speaker 1: no outliers. And so I think that's the same intuition 188 00:09:20,559 --> 00:09:23,400 Speaker 1: with pricing stuff, where if everyone is sharing information, you 189 00:09:23,440 --> 00:09:28,080 Speaker 1: won't have any outlier cheap providers because everyone knows, like 190 00:09:28,280 --> 00:09:30,080 Speaker 1: you know, the market price is this, Like I shouldn't 191 00:09:30,120 --> 00:09:30,679 Speaker 1: charge less. 192 00:09:31,200 --> 00:09:34,120 Speaker 2: That's interesting. The thing that I think the wage dis 193 00:09:34,160 --> 00:09:36,560 Speaker 2: goes your laws lead to is just super wide salary 194 00:09:36,679 --> 00:09:37,680 Speaker 2: ranges that make no sense. 195 00:09:37,679 --> 00:09:39,560 Speaker 1: But that's I agree with that, Like they don't seem 196 00:09:39,600 --> 00:09:41,160 Speaker 1: to yeah, tell you that much, but. 197 00:09:41,280 --> 00:09:43,280 Speaker 2: Yeah, do you want to talk about some meat prices? 198 00:09:43,520 --> 00:09:43,720 Speaker 1: Sure? 199 00:09:43,760 --> 00:09:47,640 Speaker 2: I actually looked at the website from Cornell. This is 200 00:09:48,200 --> 00:09:50,880 Speaker 2: monthly data, so I don't think it's the weekly days. 201 00:09:50,920 --> 00:09:52,520 Speaker 1: I don't going to be a long podcast where you 202 00:09:52,559 --> 00:09:53,400 Speaker 1: read out the price. 203 00:09:53,600 --> 00:09:56,640 Speaker 2: Well, I think it's interesting. So at the farmers market 204 00:09:56,760 --> 00:10:00,480 Speaker 2: in September, we're looking at price summary statistics across multiple 205 00:10:00,480 --> 00:10:03,080 Speaker 2: meat products collected from ten farms selling in twenty one 206 00:10:03,240 --> 00:10:07,120 Speaker 2: different farmers' markets in New York State. For chuck roast 207 00:10:07,200 --> 00:10:10,960 Speaker 2: in September, your weighted average price per pound was nine 208 00:10:11,000 --> 00:10:13,640 Speaker 2: dollars and sixty cents. Can you guess what it was 209 00:10:13,720 --> 00:10:14,760 Speaker 2: from the grocery store? 210 00:10:15,320 --> 00:10:16,720 Speaker 1: Seven dollars and twenty cents. 211 00:10:16,960 --> 00:10:18,160 Speaker 2: Eight dollars and twenty five. 212 00:10:18,040 --> 00:10:19,880 Speaker 1: Cents I don't know if I was close. 213 00:10:20,200 --> 00:10:22,480 Speaker 2: I think you're doing it. But that's the average price 214 00:10:22,520 --> 00:10:25,280 Speaker 2: per pound versus the weighted average price. 215 00:10:25,480 --> 00:10:27,880 Speaker 1: So farmer's market's barely charging more than the gross well, 216 00:10:28,040 --> 00:10:29,680 Speaker 1: and like your experience can't be beat. 217 00:10:29,880 --> 00:10:32,360 Speaker 2: Hold your horses there, my friends, a big farmer's market. 218 00:10:32,360 --> 00:10:37,880 Speaker 2: Propose non organic bacon from the farmer's market in September 219 00:10:38,040 --> 00:10:41,800 Speaker 2: according to this data, seventeen dollars and twenty one cents 220 00:10:41,800 --> 00:10:44,560 Speaker 2: per pound. What do you think it was from the 221 00:10:44,559 --> 00:10:45,319 Speaker 2: grocery store? 222 00:10:46,120 --> 00:10:47,240 Speaker 1: Seven dollars per pound? 223 00:10:48,000 --> 00:10:50,400 Speaker 2: So close, seven dollars and ninety eight cents per pounds. 224 00:10:51,160 --> 00:10:55,319 Speaker 2: I said, eight, Quite a mark up, your baby. 225 00:10:55,840 --> 00:10:58,480 Speaker 1: That farmer's market bacon. It's going to be delicious, is it. 226 00:10:58,720 --> 00:11:00,240 Speaker 2: I don't know. I'm not a bacon person on. 227 00:11:00,280 --> 00:11:04,320 Speaker 1: The big farmer's market. Great experience, great food. Yeah, garlic 228 00:11:04,440 --> 00:11:06,280 Speaker 1: cannot be beat. The ginger I got up my local 229 00:11:06,280 --> 00:11:09,560 Speaker 1: farmer's market astonishingly expensive, so good. 230 00:11:09,640 --> 00:11:12,240 Speaker 2: We were driving back from Albany this past weekend and 231 00:11:12,280 --> 00:11:14,960 Speaker 2: we went to a rest stop and there was a 232 00:11:15,000 --> 00:11:19,280 Speaker 2: farmer's market outside, like on the highway. 233 00:11:19,400 --> 00:11:20,480 Speaker 1: I'm sure that was great. 234 00:11:20,640 --> 00:11:23,480 Speaker 2: I got some dried beat chips and. 235 00:11:23,600 --> 00:11:25,840 Speaker 1: I got I know that stand but okay. 236 00:11:25,720 --> 00:11:27,640 Speaker 2: Yeah it was on the cusp of New Jersey. 237 00:11:28,000 --> 00:11:30,520 Speaker 1: No, I just mean, like, oh, there's like stands that 238 00:11:30,520 --> 00:11:31,120 Speaker 1: you see a lot of. 239 00:11:31,280 --> 00:11:34,720 Speaker 2: You also at the rest stop on the highway. Yeah, 240 00:11:34,760 --> 00:11:36,720 Speaker 2: but I don't think I'm a farmer's market person. I 241 00:11:36,720 --> 00:11:39,240 Speaker 2: don't think I have the patience. Anyway, that was a 242 00:11:39,320 --> 00:11:40,160 Speaker 2: robust discussion. 243 00:11:40,280 --> 00:11:41,800 Speaker 1: I want to add one more thing, which I did 244 00:11:41,840 --> 00:11:44,320 Speaker 1: write about, but I love it so much. Yeah, I 245 00:11:44,360 --> 00:11:46,600 Speaker 1: got an email from a reader about the Ottawa Farmer's 246 00:11:46,600 --> 00:11:49,720 Speaker 1: market where this reader sold strawberries for a while. Yeah, 247 00:11:49,720 --> 00:11:52,440 Speaker 1: and like out of those farmer's market had explicit price fixing, 248 00:11:52,440 --> 00:11:54,280 Speaker 1: where like the rules of the farmer's market said you 249 00:11:54,400 --> 00:11:57,440 Speaker 1: couldn't undercut the prices that they that were agreed on, 250 00:11:57,600 --> 00:12:00,400 Speaker 1: and you didn't say that legs were broken. But a 251 00:12:00,400 --> 00:12:05,440 Speaker 1: little bit of ploot. He found a loophole where it 252 00:12:05,600 --> 00:12:07,880 Speaker 1: was like, you know, a four liter container of strawberries 253 00:12:07,880 --> 00:12:09,840 Speaker 1: had to cost this much, and he realized that if 254 00:12:09,840 --> 00:12:12,000 Speaker 1: he sold the two and a half liter container, non 255 00:12:12,040 --> 00:12:15,480 Speaker 1: standard size container, he could undercut because there was no 256 00:12:15,600 --> 00:12:18,960 Speaker 1: rule about selling that size container. Wow, so he would 257 00:12:18,960 --> 00:12:21,520 Speaker 1: sell two and a half leaders for half the price 258 00:12:21,559 --> 00:12:25,080 Speaker 1: of four leaders and get more business. The kicker to 259 00:12:25,120 --> 00:12:26,800 Speaker 1: the story is that he's now a data scientist at 260 00:12:26,800 --> 00:12:28,959 Speaker 1: a tech fron because because I assumed that like a 261 00:12:29,000 --> 00:12:31,240 Speaker 1: tech FIM recruiter is like walking through the market and 262 00:12:31,280 --> 00:12:34,560 Speaker 1: be like this guy, yeah knows how to price ad auctions. 263 00:12:34,600 --> 00:12:37,040 Speaker 2: I wouldn't have guessed that the pipeline worked in that direction. 264 00:12:37,360 --> 00:12:38,600 Speaker 2: But that's pretty cool. You're right. 265 00:12:38,640 --> 00:12:40,960 Speaker 1: It would normally go and like, I don't know if 266 00:12:40,960 --> 00:12:44,320 Speaker 1: he was a data scientist taking a break but strawberries, but. 267 00:12:44,520 --> 00:13:02,000 Speaker 2: Maybe he was on gardening leaves. So private credit, in 268 00:13:02,080 --> 00:13:06,880 Speaker 2: the sofer world of private credit, there's a lot going on, 269 00:13:07,240 --> 00:13:09,120 Speaker 2: is there or are there just a lot of headlines? 270 00:13:09,320 --> 00:13:12,160 Speaker 1: I don't know. There's a really interesting Financial Time story 271 00:13:12,480 --> 00:13:14,520 Speaker 1: the title something like State Street is shopping for a 272 00:13:14,559 --> 00:13:15,240 Speaker 1: private credit man. 273 00:13:15,360 --> 00:13:16,560 Speaker 2: That's exactly what it is. 274 00:13:16,840 --> 00:13:20,319 Speaker 1: Photographic memory. The thing that I thought was interesting is 275 00:13:20,320 --> 00:13:22,360 Speaker 1: that the C States trade is like, yes, we're desperate 276 00:13:22,360 --> 00:13:24,360 Speaker 1: for a private credit manager. Do you know any I 277 00:13:24,400 --> 00:13:26,360 Speaker 1: need to I need to buy one right away. It's 278 00:13:26,400 --> 00:13:29,200 Speaker 1: just like the like intensity of the search for like 279 00:13:29,280 --> 00:13:31,800 Speaker 1: every big asset manager, Yeah really wants to buy a 280 00:13:31,840 --> 00:13:35,480 Speaker 1: private credit manager, which is just like a great position 281 00:13:35,559 --> 00:13:38,199 Speaker 1: to be in a few a few years ago launched 282 00:13:38,200 --> 00:13:40,520 Speaker 1: your private credit for people are like, yeah, that's weird. 283 00:13:40,559 --> 00:13:42,640 Speaker 1: Does that do? It was like a little bit of 284 00:13:42,640 --> 00:13:44,319 Speaker 1: time where private credit was like, you know, like a 285 00:13:44,320 --> 00:13:45,719 Speaker 1: little bit in the wilderness, like a little bit of 286 00:13:45,760 --> 00:13:48,520 Speaker 1: a niche strategy. And now it's like all these managers 287 00:13:48,559 --> 00:13:50,720 Speaker 1: are like State Street is kicking down their door. 288 00:13:50,880 --> 00:13:53,400 Speaker 2: Yeah, I wish that that's how I had spent my pandemic. 289 00:13:53,440 --> 00:13:56,800 Speaker 2: But here I am recording this podcast. But i's great. 290 00:13:56,960 --> 00:13:59,280 Speaker 2: I kind of like the honesty and the aggression. So 291 00:13:59,320 --> 00:14:01,640 Speaker 2: this is a CEO of State Street Global Advisors. It's 292 00:14:01,679 --> 00:14:04,560 Speaker 2: their asset management arm. She said, this area is so 293 00:14:04,600 --> 00:14:06,880 Speaker 2: well established, and given the size of our clients and 294 00:14:06,920 --> 00:14:09,280 Speaker 2: their need to build and invest in a meaningful size, 295 00:14:09,920 --> 00:14:12,120 Speaker 2: I think it just makes more sense for us to 296 00:14:12,160 --> 00:14:14,679 Speaker 2: either partner or take a stake in a much more 297 00:14:14,760 --> 00:14:18,960 Speaker 2: established firm where it's one plus one equals three. That's interesting, 298 00:14:19,040 --> 00:14:22,360 Speaker 2: rather than trying to do it organically. They're like, we're 299 00:14:22,480 --> 00:14:24,360 Speaker 2: behind already, let's go by the way. 300 00:14:24,360 --> 00:14:26,240 Speaker 1: Do it organically isn't even a thing like do it 301 00:14:26,320 --> 00:14:29,600 Speaker 1: organically means like, hey, huge guarantee is to the people 302 00:14:29,640 --> 00:14:33,040 Speaker 1: you hire, right, there's no like the market for people 303 00:14:33,040 --> 00:14:35,160 Speaker 1: in private credit is just really a pricey whether you're 304 00:14:35,320 --> 00:14:36,880 Speaker 1: hiring them or buying their firms. 305 00:14:37,000 --> 00:14:39,840 Speaker 2: Yeah, I started thinking about Apollo because she also said 306 00:14:39,840 --> 00:14:42,920 Speaker 2: we're shopping for either a full acquisition or a minority 307 00:14:42,920 --> 00:14:47,280 Speaker 2: state combined with product partnerships. And they have a planned 308 00:14:47,320 --> 00:14:51,480 Speaker 2: product partnership with Apollo. That ETF filing heard around the 309 00:14:51,480 --> 00:14:54,920 Speaker 2: world between Apollo and State Street for private credit ETF 310 00:14:54,960 --> 00:14:56,720 Speaker 2: which I don't know if that one is going to launch. 311 00:14:56,760 --> 00:14:59,960 Speaker 2: There's a lot of skepticism over that. But that's interesting. 312 00:15:00,680 --> 00:15:03,040 Speaker 1: Oh sure, but like they want a private credit offering 313 00:15:03,080 --> 00:15:05,480 Speaker 1: for their clients, right, Like they want to be able 314 00:15:05,520 --> 00:15:09,920 Speaker 1: to chuck billions of dollars institutional money into a private 315 00:15:09,960 --> 00:15:12,680 Speaker 1: credit offering, and everyone wants to that. Yeah, you know, 316 00:15:12,800 --> 00:15:15,400 Speaker 1: if you are running a private credit firm, you're raising 317 00:15:15,400 --> 00:15:18,040 Speaker 1: funds and like you're getting all these offers from all 318 00:15:18,080 --> 00:15:20,560 Speaker 1: these traditional firms. Yeah, you know. There's another article in 319 00:15:20,560 --> 00:15:23,000 Speaker 1: the Wall Street Journal about black Rock looking for alts 320 00:15:23,080 --> 00:15:26,760 Speaker 1: managers like private credit or other like alternatives, and the 321 00:15:26,800 --> 00:15:28,760 Speaker 1: reason for it is so clear, Like you can charge 322 00:15:28,760 --> 00:15:31,560 Speaker 1: like roughly one order of magnitude more n fees for 323 00:15:31,680 --> 00:15:35,480 Speaker 1: running alternatives than for running you know, traditional long only money. 324 00:15:35,520 --> 00:15:39,280 Speaker 2: Well to the point that State Street be shopping, Blackrock 325 00:15:39,800 --> 00:15:42,400 Speaker 2: has been shopping in a big way. I mean they 326 00:15:42,440 --> 00:15:46,120 Speaker 2: bought Prequin for example, that was you know, for data 327 00:15:46,360 --> 00:15:49,000 Speaker 2: Global Infrastructure Partners that finally closed. 328 00:15:49,160 --> 00:15:50,760 Speaker 1: Yeah, by the way, I think I forget it was 329 00:15:50,800 --> 00:15:52,240 Speaker 1: the State Street or something else. But like one of 330 00:15:52,280 --> 00:15:54,720 Speaker 1: the articles is like they're shopping for a private credit 331 00:15:54,840 --> 00:15:57,640 Speaker 1: or infrastructure, but it's like anything at all. 332 00:15:57,800 --> 00:16:02,120 Speaker 2: Yeah, yeah, as long as it's alts. And also maybe 333 00:16:02,280 --> 00:16:05,040 Speaker 2: Blackrock is going to buy HPS. I don't know. 334 00:16:05,920 --> 00:16:09,400 Speaker 1: There's a fascinating story about HBS a while back. Hs 335 00:16:09,480 --> 00:16:12,160 Speaker 1: is like nominally preparing an IPO, but like also shopping 336 00:16:12,200 --> 00:16:17,160 Speaker 1: themselves hard to probably Blackrock. But also like there's talks 337 00:16:17,200 --> 00:16:20,280 Speaker 1: of talk of like JP Morgan is like maybe like yeah, 338 00:16:20,400 --> 00:16:22,600 Speaker 1: like Jamie Diamond, like I think was asked about buying 339 00:16:22,600 --> 00:16:23,840 Speaker 1: a private credit for him and he's like, no, we 340 00:16:23,880 --> 00:16:25,720 Speaker 1: would never do that, and then like came back later 341 00:16:25,760 --> 00:16:26,840 Speaker 1: and it's like my team tells. 342 00:16:26,600 --> 00:16:30,200 Speaker 2: Me we might Yeah, I've been in form Yeah. 343 00:16:30,240 --> 00:16:32,120 Speaker 1: Yeah, Like they're like they're like pulled them back. But 344 00:16:32,400 --> 00:16:34,120 Speaker 1: a lot of ways that HPS could go but one 345 00:16:34,120 --> 00:16:36,240 Speaker 1: of those ways is selling themselves the black Rock for 346 00:16:36,560 --> 00:16:37,760 Speaker 1: an enormous premium. 347 00:16:37,800 --> 00:16:39,920 Speaker 2: This strategy has worked out for black Rock. They have 348 00:16:40,000 --> 00:16:42,880 Speaker 2: like four hundred and fifty billion dollars in alts. At 349 00:16:42,960 --> 00:16:46,120 Speaker 2: least one hundred and sixteen billion dollars is coming from 350 00:16:46,440 --> 00:16:48,800 Speaker 2: GIP for example. So it's a really easy way to 351 00:16:48,840 --> 00:16:49,400 Speaker 2: just scale up. 352 00:16:50,200 --> 00:16:52,600 Speaker 1: Yeah, I mean like scale up, Like you know, it's 353 00:16:52,680 --> 00:16:55,000 Speaker 1: like what like four percent of black Rocks assets, right, 354 00:16:55,000 --> 00:16:57,920 Speaker 1: but it's like the very juicy four percent, right, It's 355 00:16:57,960 --> 00:16:59,840 Speaker 1: like the. 356 00:16:59,040 --> 00:17:00,800 Speaker 2: Four percent that makes a lot of money. 357 00:17:00,920 --> 00:17:03,160 Speaker 1: Yeah, you charge, it makes a lot of the money, 358 00:17:03,240 --> 00:17:06,119 Speaker 1: and it gets a higher multiple, and it's like, yeah, 359 00:17:06,160 --> 00:17:08,840 Speaker 1: it's just like really attractive. And like, you know, saying 360 00:17:08,840 --> 00:17:11,679 Speaker 1: we're a giant index fund provider is just less appealing 361 00:17:11,720 --> 00:17:13,840 Speaker 1: to investors now than saying we're a giant ults provider. 362 00:17:13,880 --> 00:17:16,560 Speaker 2: I have some numbers in your column. You reference this 363 00:17:16,560 --> 00:17:20,800 Speaker 2: Wall Street Journal article that pointed out that Blackrocks market 364 00:17:20,840 --> 00:17:24,800 Speaker 2: cap is similar to those of Blackstone, Apollo, KKR, et cetera, 365 00:17:24,920 --> 00:17:28,240 Speaker 2: even though Blackrock manages like eleven and a half trillion 366 00:17:29,080 --> 00:17:32,120 Speaker 2: and they manage a fraction of that. I wrote about 367 00:17:32,160 --> 00:17:37,560 Speaker 2: this in mid October following BlackRock's earnings, just about how 368 00:17:37,640 --> 00:17:41,879 Speaker 2: much money they make per dollar of AUM. And for Blackrock, 369 00:17:42,240 --> 00:17:47,760 Speaker 2: it's like, according to Bloomberg Intelligence, they have an annualized 370 00:17:47,800 --> 00:17:52,280 Speaker 2: fee rate of fourteen point six basis points. You compare 371 00:17:52,320 --> 00:17:56,840 Speaker 2: that to Apollo, and it's something like fifty two basis points. 372 00:17:57,320 --> 00:18:01,600 Speaker 2: So I would have guessed the higher number for Apollo. Well, 373 00:18:01,600 --> 00:18:05,720 Speaker 2: apparently for Blackstone and KKR and Ares, that figure ranges 374 00:18:05,720 --> 00:18:09,000 Speaker 2: from fifty basis points to like one hundred basis points, right, So. 375 00:18:09,560 --> 00:18:12,440 Speaker 1: Yeah, classically two and twenty right, Yeah, but like it's 376 00:18:12,480 --> 00:18:17,000 Speaker 1: a much, much, much richer fee product. And like a 377 00:18:17,000 --> 00:18:18,840 Speaker 1: lot of the stories about private credit are like, wow, 378 00:18:18,840 --> 00:18:20,000 Speaker 1: there's so much more money in this. 379 00:18:20,600 --> 00:18:22,080 Speaker 2: Oh my gosh. 380 00:18:22,240 --> 00:18:25,639 Speaker 1: This is a Bloomberg article from September Bonus starved bankers 381 00:18:25,680 --> 00:18:29,120 Speaker 1: are a jumping ship for private credit riches. Yeah, why 382 00:18:29,160 --> 00:18:30,160 Speaker 1: wouldn't you do that? 383 00:18:30,160 --> 00:18:30,840 Speaker 2: That makes sense? 384 00:18:31,080 --> 00:18:33,200 Speaker 1: You know, all these like private credit funds are started 385 00:18:33,200 --> 00:18:35,159 Speaker 1: by people who are like you know, lib fin bankers 386 00:18:35,200 --> 00:18:37,240 Speaker 1: at Coldman and like went to start their own funds 387 00:18:37,400 --> 00:18:39,919 Speaker 1: when that was like a somewhat contrariy and move, and 388 00:18:40,000 --> 00:18:42,879 Speaker 1: now they can sell their firms for billions of dollars 389 00:18:42,680 --> 00:18:43,640 Speaker 1: to Blackrock. 390 00:18:43,840 --> 00:18:45,000 Speaker 2: If I could do it, I would. 391 00:18:45,560 --> 00:18:47,800 Speaker 1: It's just like, you know, one thing I write about 392 00:18:47,800 --> 00:18:51,280 Speaker 1: this is like it seems hard to run a private 393 00:18:51,320 --> 00:18:55,320 Speaker 1: credit fund now from the perspective of like being an investor. 394 00:18:55,560 --> 00:18:57,600 Speaker 1: Josh Harris said to David Rubinston the other day that 395 00:18:57,680 --> 00:18:59,200 Speaker 1: like a lot of these alts funds are like the 396 00:18:59,680 --> 00:19:02,159 Speaker 1: beata of aults. Right, private credit like its core is 397 00:19:02,160 --> 00:19:05,719 Speaker 1: like direct lending to leverage biots, And so you are 398 00:19:05,720 --> 00:19:09,159 Speaker 1: in a business of like being friends with twenty private 399 00:19:09,160 --> 00:19:11,760 Speaker 1: equity sponsors, and when they do a biot, they call 400 00:19:11,840 --> 00:19:13,399 Speaker 1: you and they say, would you like to lend us 401 00:19:13,400 --> 00:19:15,960 Speaker 1: the money? And you say yes? Because you say no, 402 00:19:16,560 --> 00:19:18,760 Speaker 1: and they stop calling you, and then you don't have 403 00:19:19,440 --> 00:19:23,760 Speaker 1: the paper to feed your hungry investors. And so there's 404 00:19:23,800 --> 00:19:26,240 Speaker 1: this sense in prior credit that, like, it is hard 405 00:19:26,240 --> 00:19:29,400 Speaker 1: to be a disciplined investor, and it's hard to look 406 00:19:29,400 --> 00:19:32,600 Speaker 1: for value and make do really careful credit work because 407 00:19:32,600 --> 00:19:34,880 Speaker 1: you're essentially in the business of saying yes to every 408 00:19:34,960 --> 00:19:37,040 Speaker 1: buyout that gets offered to you because you just have 409 00:19:37,080 --> 00:19:39,280 Speaker 1: to do deals. But it's a great time to be 410 00:19:40,200 --> 00:19:42,840 Speaker 1: selling your private credit front, right, Yeah, you know, it's 411 00:19:42,840 --> 00:19:45,119 Speaker 1: a huge boom that like any huge room makes it 412 00:19:45,160 --> 00:19:47,199 Speaker 1: hard to be like a careful investor because like you 413 00:19:47,240 --> 00:19:48,680 Speaker 1: have to deploy a lot of money, but like it's 414 00:19:48,680 --> 00:19:49,800 Speaker 1: a great time to be a seller. 415 00:19:50,000 --> 00:19:53,159 Speaker 2: Yeah. I was actually just having this conversation with a 416 00:19:53,200 --> 00:19:57,520 Speaker 2: private credit person, and this person was talking about how 417 00:19:57,800 --> 00:20:00,679 Speaker 2: there's private credit beta right now, and you know you 418 00:20:00,680 --> 00:20:03,119 Speaker 2: have to get more esoteric to find the alpha, et cetera. 419 00:20:03,280 --> 00:20:05,520 Speaker 1: You don't have to find the alpha. You charged two 420 00:20:05,560 --> 00:20:09,040 Speaker 1: percent and you know you judge, you judge fifty vasis points. 421 00:20:08,840 --> 00:20:10,960 Speaker 2: And you can at least this person would like to. 422 00:20:11,160 --> 00:20:13,919 Speaker 1: That's why I'm saying it's hard because like everyone is 423 00:20:13,960 --> 00:20:17,680 Speaker 1: like constitutionally like wants to be doing good deals and 424 00:20:17,680 --> 00:20:19,840 Speaker 1: not doing bad deals. But there's a lot of money 425 00:20:20,080 --> 00:20:21,520 Speaker 1: in doing like private credit paida. 426 00:20:36,080 --> 00:20:37,760 Speaker 2: Let's talk about some trade secrets. 427 00:20:38,240 --> 00:20:42,240 Speaker 1: So there's a Bloomberg story about Shao Xiang, who's the 428 00:20:42,240 --> 00:20:45,720 Speaker 1: founder of Pinestone, which is a big and very successful 429 00:20:46,000 --> 00:20:49,800 Speaker 1: quant fund in China. He was charged criminally in Boston 430 00:20:50,000 --> 00:20:53,160 Speaker 1: Federal Court in Boston for allegedly he had a former 431 00:20:53,240 --> 00:20:56,080 Speaker 1: job at an American asset manager and he like allegedly 432 00:20:56,119 --> 00:20:58,959 Speaker 1: they downloaded all the models. It's like left for Actually 433 00:20:59,000 --> 00:21:01,119 Speaker 1: he left for China and downloaded all the models. 434 00:21:01,160 --> 00:21:03,240 Speaker 2: He was out of the country first, out of the country. 435 00:21:02,920 --> 00:21:05,239 Speaker 1: First, which is smart. There's another story a while back 436 00:21:05,280 --> 00:21:07,120 Speaker 1: about a guy who did the reverse, Like he downloaded 437 00:21:07,160 --> 00:21:09,680 Speaker 1: the models and then he left the country like that night, 438 00:21:09,960 --> 00:21:11,520 Speaker 1: and like by the time he landed, they have them 439 00:21:11,560 --> 00:21:14,040 Speaker 1: to tand and like it. It didn't work out for him. 440 00:21:14,200 --> 00:21:17,080 Speaker 1: But this guy left the country first, wasn't supposed to 441 00:21:17,080 --> 00:21:19,520 Speaker 1: be able to get into his corporate hard drive, but 442 00:21:19,960 --> 00:21:23,320 Speaker 1: right used the VP and to somehow log into work 443 00:21:23,320 --> 00:21:26,280 Speaker 1: from China, which I think is probably not technically feasible 444 00:21:26,320 --> 00:21:29,080 Speaker 1: anymore at most quant firms. But he allegedly did it, 445 00:21:29,119 --> 00:21:33,159 Speaker 1: and he allegedly downloaded all the models, and it's an indictment. 446 00:21:33,359 --> 00:21:36,680 Speaker 1: It's not full of detail. There's a suggestion that he 447 00:21:36,800 --> 00:21:39,240 Speaker 1: used these models to set up his now very successful 448 00:21:39,320 --> 00:21:41,159 Speaker 1: Chinese quand fundt. I don't know if that's even what 449 00:21:41,160 --> 00:21:43,480 Speaker 1: they're charging, but like there's a hint that like these 450 00:21:43,520 --> 00:21:45,240 Speaker 1: things were useful in his subsequent career. 451 00:21:45,680 --> 00:21:48,760 Speaker 2: So well, I would like to know his returns. 452 00:21:49,520 --> 00:21:50,080 Speaker 1: Well, they're great. 453 00:21:50,600 --> 00:21:53,160 Speaker 2: Well, you point out on your column that the US 454 00:21:53,280 --> 00:21:55,119 Speaker 2: market is different than the Chinese market. 455 00:21:55,480 --> 00:21:57,280 Speaker 1: It's very different. You know, there's been a lot of 456 00:21:57,320 --> 00:22:01,040 Speaker 1: stories about like Chinese quand funds getting wrecked in like 457 00:22:01,520 --> 00:22:04,280 Speaker 1: regime changes, where yes, the Chinese governments like oh, you 458 00:22:04,359 --> 00:22:06,520 Speaker 1: like can't bet again stocks or whatever, and like you know, 459 00:22:06,560 --> 00:22:09,320 Speaker 1: your long short fund just that you know, explodes because 460 00:22:09,359 --> 00:22:11,520 Speaker 1: you can't be short anymore. You know. You think of 461 00:22:11,600 --> 00:22:18,439 Speaker 1: like a quant fund stereotypically being trained on some relatively 462 00:22:18,480 --> 00:22:22,159 Speaker 1: recent history and being bad at like adapting to sharp 463 00:22:22,280 --> 00:22:26,199 Speaker 1: changes and like how the world works. Yeah, it's like 464 00:22:26,200 --> 00:22:30,360 Speaker 1: probably an overly simplified stereotype. And like some quant algorithms 465 00:22:30,359 --> 00:22:32,800 Speaker 1: are really good at adjusting to new information, but like 466 00:22:33,119 --> 00:22:35,120 Speaker 1: you know, that's the stereotype, and like it does seem 467 00:22:35,160 --> 00:22:37,360 Speaker 1: hard to run a quant fund that is, like these 468 00:22:37,400 --> 00:22:39,600 Speaker 1: are the returns of going along this basket of stocks 469 00:22:39,600 --> 00:22:42,000 Speaker 1: and going short that basket of stocks, and then like 470 00:22:42,520 --> 00:22:44,479 Speaker 1: you updated for you can't short stocks anymore. 471 00:22:44,480 --> 00:22:46,840 Speaker 2: Like this seems hard, yeah, Or the government comes in 472 00:22:46,880 --> 00:22:49,200 Speaker 2: with like a ton of stimulus and just completely changes 473 00:22:49,240 --> 00:22:51,720 Speaker 2: the narrative, right exactly right, they develop it, which we 474 00:22:51,760 --> 00:22:52,760 Speaker 2: saw a couple of weeks ago. 475 00:22:53,040 --> 00:22:56,560 Speaker 1: It's not necessarily that's right, Like the economic environment can 476 00:22:56,600 --> 00:23:01,240 Speaker 1: change rapidly, and it does seem very hard to deal 477 00:23:01,280 --> 00:23:02,480 Speaker 1: with that, and like there were a lot of quant 478 00:23:02,480 --> 00:23:05,080 Speaker 1: funds that blew up, And as a sort of like 479 00:23:05,119 --> 00:23:09,639 Speaker 1: amateur tourist reading those stories, I'm like the lessons of 480 00:23:09,640 --> 00:23:12,480 Speaker 1: like the sort of classical development of like quantu investing 481 00:23:12,480 --> 00:23:15,000 Speaker 1: in the US might not apply perfectly to China, but 482 00:23:15,040 --> 00:23:17,679 Speaker 1: presumably people know that, right, But it's like, well, they 483 00:23:17,680 --> 00:23:19,400 Speaker 1: stole the code, but like, by the way, his firm 484 00:23:19,440 --> 00:23:21,080 Speaker 1: is doing great if you just stole the card and 485 00:23:21,080 --> 00:23:23,760 Speaker 1: like plugged in like us trading into Chinese markets, Like 486 00:23:24,400 --> 00:23:26,360 Speaker 1: either that worked really well or like there's something we're 487 00:23:26,400 --> 00:23:26,880 Speaker 1: missing there. 488 00:23:26,920 --> 00:23:29,240 Speaker 2: Perhaps he tweaked it a little bit. You could draw 489 00:23:29,359 --> 00:23:32,240 Speaker 2: parallels to another case we've talked about that was Jane 490 00:23:32,240 --> 00:23:36,400 Speaker 2: Street and Millennium's trade secrets. Tell us about the nuances here. 491 00:23:36,440 --> 00:23:38,399 Speaker 1: Well, I mean one thing is like there's actually a 492 00:23:38,480 --> 00:23:42,800 Speaker 1: lot of these cases where the person gets charged criminally. 493 00:23:43,040 --> 00:23:44,520 Speaker 1: I was going to say arrested, but this guy's not 494 00:23:44,560 --> 00:23:46,320 Speaker 1: been arrested because he was out of the country. But 495 00:23:46,400 --> 00:23:48,800 Speaker 1: like the number of them get arrested, you know, like 496 00:23:48,840 --> 00:23:52,480 Speaker 1: the one that is famous as Sergei Atlanikov, who allegedly 497 00:23:52,520 --> 00:23:56,560 Speaker 1: stole code from Goldman Sachs and got arrested and so 498 00:23:56,840 --> 00:23:59,800 Speaker 1: quite a long time in jail before It's like, I 499 00:23:59,800 --> 00:24:01,959 Speaker 1: think his convictions are ultimately overturned, and he was like 500 00:24:02,200 --> 00:24:03,719 Speaker 1: he had kind of a rough go of it. He 501 00:24:03,760 --> 00:24:07,160 Speaker 1: was arrested roughly the time that I left Goldman, And 502 00:24:07,359 --> 00:24:08,760 Speaker 1: although I did not steal any. 503 00:24:08,600 --> 00:24:11,119 Speaker 2: Code, I like, do you want to say that again? 504 00:24:12,200 --> 00:24:16,080 Speaker 1: I did not steal any code, to be clear, but 505 00:24:16,160 --> 00:24:18,439 Speaker 1: I was worried because I was going into media and 506 00:24:18,480 --> 00:24:19,879 Speaker 1: I was like, what if they get mad at me 507 00:24:19,920 --> 00:24:23,160 Speaker 1: and say that I stole code. It's a real time 508 00:24:23,240 --> 00:24:26,240 Speaker 1: of like looked like Goldman could have you put in 509 00:24:26,280 --> 00:24:27,960 Speaker 1: prison if they didn't like you, right, look to me 510 00:24:28,040 --> 00:24:30,400 Speaker 1: like that because I was a parent. Anyway, they put 511 00:24:30,480 --> 00:24:32,760 Speaker 1: him in prison. But like you know, the Jane Street stuff, 512 00:24:32,760 --> 00:24:34,199 Speaker 1: no one's going to get put in prison for a 513 00:24:34,240 --> 00:24:36,240 Speaker 1: variety of reasons, but a big one is like, there's 514 00:24:36,240 --> 00:24:39,080 Speaker 1: no allegation of code stealing, right, There's a difference between 515 00:24:39,520 --> 00:24:42,959 Speaker 1: stealing ideas, which is like a really fuzzy area, right, 516 00:24:42,960 --> 00:24:47,280 Speaker 1: Like Jane Street is like convinced that these traders stole 517 00:24:47,680 --> 00:24:51,800 Speaker 1: a proprietary, complicated trading strategy that was developed with like 518 00:24:51,920 --> 00:24:55,600 Speaker 1: much work and investment at Jane Street and belongs to 519 00:24:55,680 --> 00:24:59,040 Speaker 1: Jane Street, and like Millennium is like, no, these guys 520 00:24:59,080 --> 00:25:01,000 Speaker 1: like you know, they how to trade options and now 521 00:25:01,040 --> 00:25:03,360 Speaker 1: they're trading options for us. There's nothing proprietary about that. 522 00:25:03,640 --> 00:25:05,520 Speaker 1: I think probably the truth of somewhere in between. But 523 00:25:05,520 --> 00:25:07,840 Speaker 1: like even if Chain Street is right, that kind of 524 00:25:07,880 --> 00:25:10,399 Speaker 1: like know how you can get mad, you can get sued, 525 00:25:10,600 --> 00:25:12,560 Speaker 1: you can be like stopped from working at the new firm. 526 00:25:12,760 --> 00:25:14,520 Speaker 1: You like have to pay them back, but you're not 527 00:25:14,520 --> 00:25:17,040 Speaker 1: gonna go to jail for that, probably not legal advice, 528 00:25:17,440 --> 00:25:20,280 Speaker 1: whereas like if you like download code from a VPN, like, yeah, 529 00:25:20,480 --> 00:25:21,200 Speaker 1: you can go to jail. 530 00:25:21,440 --> 00:25:25,360 Speaker 2: Yeah if you're caught, Well, this guy, what's gonna happen 531 00:25:25,359 --> 00:25:26,840 Speaker 2: to him? Because he isn't trya nothing. 532 00:25:27,400 --> 00:25:30,359 Speaker 1: So this is interesting take it back to the US. 533 00:25:30,359 --> 00:25:31,920 Speaker 1: It's like it's like a real consequence. 534 00:25:32,040 --> 00:25:34,639 Speaker 2: Yeah, that is a consequence. Does his firm get to 535 00:25:34,720 --> 00:25:36,800 Speaker 2: keep doing great and using these models? 536 00:25:37,359 --> 00:25:41,160 Speaker 1: There's a widespread assumption that like this stuff decays. Yeah, 537 00:25:41,520 --> 00:25:43,800 Speaker 1: maybe he downloaded like the whole like framework for how 538 00:25:43,840 --> 00:25:46,119 Speaker 1: to build you know, a quantitative trading firm. But like 539 00:25:46,119 --> 00:25:48,199 Speaker 1: that stuff is kind of public domain, you know, to 540 00:25:48,240 --> 00:25:52,400 Speaker 1: the extent he downloaded, like signals, those decay, Like no one, 541 00:25:52,480 --> 00:25:54,800 Speaker 1: no one thinks that like three years after you're stolen 542 00:25:54,840 --> 00:25:57,080 Speaker 1: stuff from your firm, it's still I mean maybe if 543 00:25:57,119 --> 00:25:59,520 Speaker 1: it was renaissance, but like yeah, for the most part, 544 00:25:59,560 --> 00:26:02,520 Speaker 1: like the Stuffycays and so there's like there's this notion 545 00:26:02,600 --> 00:26:04,679 Speaker 1: that like you have to be stopped from using it 546 00:26:04,720 --> 00:26:06,360 Speaker 1: for some period of time, but then after that it's 547 00:26:06,359 --> 00:26:08,520 Speaker 1: probably not worth worrying about. Yeah, Like you see that 548 00:26:08,560 --> 00:26:11,840 Speaker 1: in the Jane Street case where it's like whatever secret 549 00:26:11,840 --> 00:26:15,880 Speaker 1: trade they're doing options in India, but Options in India 550 00:26:15,920 --> 00:26:17,720 Speaker 1: doesn't tell you very much about the trade. Like Jane 551 00:26:17,720 --> 00:26:21,360 Speaker 1: secretal sides out like some very complicated, you know, clever implementation, 552 00:26:21,920 --> 00:26:24,280 Speaker 1: but uh, no one thinks that's going to make one 553 00:26:24,359 --> 00:26:26,320 Speaker 1: hundred million dollars a year forever. You know. Like it's 554 00:26:26,359 --> 00:26:28,720 Speaker 1: like Jane Street had some window in which to use 555 00:26:28,720 --> 00:26:30,879 Speaker 1: that in which to do that trade, and then like 556 00:26:31,000 --> 00:26:33,119 Speaker 1: Millennium butted in and now they you know, have to 557 00:26:33,160 --> 00:26:36,280 Speaker 1: put the profits where the profits go away. Probably that's 558 00:26:36,280 --> 00:26:39,960 Speaker 1: what's happening here. But also I can't be like shooting 559 00:26:40,000 --> 00:26:44,400 Speaker 1: the lights out trading Quantu and China solely with stolen models. 560 00:26:44,440 --> 00:26:48,040 Speaker 2: He's only thirty three, yeah, yeah, and he stole these 561 00:26:48,040 --> 00:26:51,200 Speaker 2: secrets allegedly in twenty twenty one. 562 00:26:51,560 --> 00:26:53,840 Speaker 1: That's the other cool thing is like the indictment says 563 00:26:53,840 --> 00:26:55,919 Speaker 1: that he was an associate and was not responsible for 564 00:26:55,960 --> 00:27:00,399 Speaker 1: these models. Like often you have some dispute about like 565 00:27:00,440 --> 00:27:05,760 Speaker 1: whether the person was like downloading their own work, yeah, 566 00:27:05,880 --> 00:27:09,080 Speaker 1: or but here the implication is kind of like you 567 00:27:09,160 --> 00:27:11,679 Speaker 1: like shut up as an associate, did the training and 568 00:27:11,680 --> 00:27:13,399 Speaker 1: then like downloaded all the models and left. You know, 569 00:27:13,400 --> 00:27:15,639 Speaker 1: there's like your implication that like he was he was 570 00:27:15,760 --> 00:27:16,960 Speaker 1: just taking other people's work. 571 00:27:17,200 --> 00:27:19,520 Speaker 2: This did prompt a response from your readers, as I 572 00:27:19,600 --> 00:27:20,280 Speaker 2: understand it. 573 00:27:20,520 --> 00:27:23,480 Speaker 1: Oh yeah, so I wrote about like the high level 574 00:27:23,560 --> 00:27:25,439 Speaker 1: problems with doing this, right, like if you just download 575 00:27:25,480 --> 00:27:27,840 Speaker 1: code and then go start your own firm, like the 576 00:27:27,840 --> 00:27:30,399 Speaker 1: big problem is that you get arrested. Yeah, it was 577 00:27:30,440 --> 00:27:32,520 Speaker 1: like you know, moving to China like solves that problem. 578 00:27:32,680 --> 00:27:35,400 Speaker 1: But then like a secondary problem is like you're crowding 579 00:27:35,440 --> 00:27:37,680 Speaker 1: a trade that is there's not that much profit in 580 00:27:37,720 --> 00:27:39,800 Speaker 1: it necessarily, so like if you and your your old 581 00:27:39,800 --> 00:27:42,040 Speaker 1: firm are both doing it, like you're both make less money. 582 00:27:42,640 --> 00:27:44,639 Speaker 1: One reader pointed out that actually the biggest problem with 583 00:27:44,680 --> 00:27:48,760 Speaker 1: this because of getting arrested is raising money clients. Yeah, 584 00:27:48,800 --> 00:27:51,359 Speaker 1: because like if you work at a hedge fund and 585 00:27:51,400 --> 00:27:55,960 Speaker 1: you download their code, then like how do you raise money? 586 00:27:56,080 --> 00:27:58,320 Speaker 1: You're like I still could from my old hedge fund, 587 00:27:58,320 --> 00:28:00,119 Speaker 1: Like no one's gonna invest with you that. Or you 588 00:28:00,119 --> 00:28:01,520 Speaker 1: can be like I'm just really smart, I have some 589 00:28:01,560 --> 00:28:04,000 Speaker 1: great ideas, but it's like or you should be. 590 00:28:03,920 --> 00:28:07,399 Speaker 2: Like I'm gonna undercut that hedge fund and I'm going 591 00:28:07,480 --> 00:28:09,440 Speaker 2: to give it to you at a cheaper price, which 592 00:28:09,520 --> 00:28:11,960 Speaker 2: gets us neatly back to farmers' markets. 593 00:28:12,480 --> 00:28:16,160 Speaker 1: It does, but I do think that that pitch, well, 594 00:28:16,200 --> 00:28:19,879 Speaker 1: it might work for garlic, is very bad for a 595 00:28:19,920 --> 00:28:23,119 Speaker 1: hedge fund client, Yeah, because you're just like you're taking 596 00:28:23,160 --> 00:28:26,919 Speaker 1: out a lot of like operational and regulatory and reputational 597 00:28:27,000 --> 00:28:29,679 Speaker 1: risk for like saving some money because like you know, 598 00:28:30,000 --> 00:28:32,200 Speaker 1: like this hedgehund strategy fell off the back of a 599 00:28:32,200 --> 00:28:33,439 Speaker 1: truck and I'll give it to you for cheap. Like 600 00:28:33,480 --> 00:28:35,400 Speaker 1: that thought that's not a good like long term strategy 601 00:28:35,400 --> 00:28:38,480 Speaker 1: for like an endowment. But moving to China and saying, hey, 602 00:28:38,480 --> 00:28:41,360 Speaker 1: we've developed our skills at like a leading US institution 603 00:28:41,720 --> 00:28:43,560 Speaker 1: and now we can apply them to this. It's somewhat 604 00:28:43,600 --> 00:28:47,640 Speaker 1: like less fully efficient market. That's a good pitch. And 605 00:28:47,680 --> 00:28:49,880 Speaker 1: if you're like nudge, nudge, wink wink. Also we stole 606 00:28:49,920 --> 00:28:54,480 Speaker 1: the models like maybe that's a fine touch too, don't Yeah, 607 00:28:55,280 --> 00:28:56,720 Speaker 1: And that was the Money Stuff Podcast. 608 00:28:56,880 --> 00:28:59,040 Speaker 2: I'm Matt Livian and I'm Katie for myself. 609 00:28:59,240 --> 00:29:01,320 Speaker 1: You can find my work by subscribing to The Money 610 00:29:01,320 --> 00:29:03,880 Speaker 1: Stuff newsletter on Bloomberg dot com. 611 00:29:03,680 --> 00:29:06,200 Speaker 2: And you can find me on Bloomberg TV every day 612 00:29:06,240 --> 00:29:09,360 Speaker 2: on Open Interest between nine to eleven am Eastern. 613 00:29:09,640 --> 00:29:11,320 Speaker 1: We'd love to hear from you. You can send an 614 00:29:11,360 --> 00:29:14,560 Speaker 1: email to Moneypod at Bloomberg dot net, ask us a 615 00:29:14,640 --> 00:29:16,000 Speaker 1: question and we might answer it on air. 616 00:29:16,400 --> 00:29:18,600 Speaker 2: You can also subscribe to our show wherever you're listening 617 00:29:18,680 --> 00:29:20,680 Speaker 2: right now and leave us a review. It helps more 618 00:29:20,720 --> 00:29:21,560 Speaker 2: people find the show. 619 00:29:22,120 --> 00:29:25,400 Speaker 1: The Money Stuff Podcast is produced by Anamasarakis and Moses On. 620 00:29:26,160 --> 00:29:27,960 Speaker 2: Our theme music was composed by Blake. 621 00:29:27,840 --> 00:29:29,840 Speaker 1: Maples, Brandon Francis munim As, our. 622 00:29:29,760 --> 00:29:33,160 Speaker 2: Executive producer, and Stage Bauman is Bloomberg's head of Podcasts. 623 00:29:33,240 --> 00:29:35,560 Speaker 1: Thanks for listening to The Money Stuff Podcasts. 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