1 00:00:02,720 --> 00:00:07,200 Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. 2 00:00:08,160 --> 00:00:12,160 Speaker 2: There was a comment on Spotify on our most recent podcast, 3 00:00:12,240 --> 00:00:14,120 Speaker 2: last week's We Just Find It. I thought it was 4 00:00:15,280 --> 00:00:17,640 Speaker 2: Hello and welcome to the bird Stuff Podcast, your weekly 5 00:00:17,680 --> 00:00:21,279 Speaker 2: podcast where we talk about stuff related to birds and 6 00:00:21,520 --> 00:00:24,000 Speaker 2: the European starling. He's doing quite well. He's perching, he 7 00:00:24,079 --> 00:00:25,200 Speaker 2: started to feed himself. 8 00:00:25,320 --> 00:00:27,520 Speaker 1: Oh great, two out of three exactly. 9 00:00:27,560 --> 00:00:30,680 Speaker 2: He's stopped screaming quite as loudly as my parents to 10 00:00:30,720 --> 00:00:33,400 Speaker 2: feed him like a baby. The flying we need to 11 00:00:33,440 --> 00:00:36,360 Speaker 2: work on though. He's really good at flapping, but you 12 00:00:36,360 --> 00:00:39,360 Speaker 2: know he's lacking some confidence when it comes to flight. 13 00:00:39,640 --> 00:00:42,519 Speaker 1: Do you have a training program ready for working on 14 00:00:42,560 --> 00:00:42,960 Speaker 1: the flying? 15 00:00:43,200 --> 00:00:44,800 Speaker 2: I think we just need to let him out of 16 00:00:44,800 --> 00:00:48,120 Speaker 2: the cage, similar to Wells Fargo, which we'll talk about. 17 00:00:48,400 --> 00:00:51,960 Speaker 1: Oh what a transition. Hello and welcome to the bird 18 00:00:51,960 --> 00:00:54,720 Speaker 1: Stuff Podcast, your weekly podcast where we talk about stuff 19 00:00:54,720 --> 00:00:59,480 Speaker 1: related to birds. I'm Matt Levine and I wrote the 20 00:00:59,480 --> 00:01:01,400 Speaker 1: Bunny Stuff column for Bloomberg Opinion. 21 00:01:01,920 --> 00:01:04,720 Speaker 2: And I'm Katie Greifeld, a reporter for Bloomberg News and 22 00:01:04,760 --> 00:01:07,080 Speaker 2: an anchor for Bloomberg Television and a bird owner. 23 00:01:07,400 --> 00:01:10,120 Speaker 1: It's actually the money Stuff podcast in case anyone has, 24 00:01:10,120 --> 00:01:11,640 Speaker 1: I mean dots. It's gonna be weird if this is 25 00:01:11,640 --> 00:01:15,120 Speaker 1: your first episode speaking of being let out of your cage. 26 00:01:15,280 --> 00:01:17,600 Speaker 1: Wells Fargo let out of its game. 27 00:01:18,600 --> 00:01:25,720 Speaker 2: Charlie Sharp playing offense. This was expected, but I think 28 00:01:25,760 --> 00:01:28,800 Speaker 2: it was still somewhat surprising to get this news this 29 00:01:28,840 --> 00:01:33,119 Speaker 2: past week that the asset cap the FED had imposed 30 00:01:33,120 --> 00:01:35,960 Speaker 2: on Wells Fargo back in twenty eighteen has been lifted. 31 00:01:36,840 --> 00:01:42,280 Speaker 1: So. The Bloomberg article about this reported that when Charlie Sharff, 32 00:01:42,360 --> 00:01:45,280 Speaker 1: the CEO of Wells Fargo, he joined the bank like 33 00:01:45,319 --> 00:01:48,240 Speaker 1: a year after the asset capitalism post, and when he 34 00:01:48,280 --> 00:01:50,640 Speaker 1: was like interviewing, he was aware of the asset cap 35 00:01:50,640 --> 00:01:55,080 Speaker 1: because it was a pretty high pye profile thing, but 36 00:01:55,120 --> 00:01:58,680 Speaker 1: according to the article, they couldn't tell him exactly how 37 00:01:59,360 --> 00:02:04,080 Speaker 1: they were doing with progressing to fix it because that 38 00:02:04,200 --> 00:02:07,160 Speaker 1: was confidential supervisory information and it would be illegal to 39 00:02:07,240 --> 00:02:10,240 Speaker 1: leak it to anyone, including the CEO candidate. So basically 40 00:02:10,280 --> 00:02:12,239 Speaker 1: he was like, so, how's it going with the FED? 41 00:02:12,240 --> 00:02:14,919 Speaker 1: And they're like, hey, I can't tell you. And then 42 00:02:14,960 --> 00:02:16,600 Speaker 1: they hired him and he came in and he's like, okay, 43 00:02:16,639 --> 00:02:17,880 Speaker 1: so how's it going with the Fed? And they're like, 44 00:02:17,960 --> 00:02:20,400 Speaker 1: really bad. Sorry we didn't tell you earlier. 45 00:02:20,919 --> 00:02:21,440 Speaker 2: Surprise. 46 00:02:22,200 --> 00:02:23,880 Speaker 1: I think he sort of came in expecting it to 47 00:02:23,880 --> 00:02:27,240 Speaker 1: be a one year process after he joined. It turned 48 00:02:27,240 --> 00:02:30,040 Speaker 1: out to be like a five year process after he gied. 49 00:02:30,280 --> 00:02:32,639 Speaker 1: But now now it's all better. Yeah. 50 00:02:32,680 --> 00:02:36,480 Speaker 2: Our reporting on the matter suggested the same. Well, fast 51 00:02:36,480 --> 00:02:40,799 Speaker 2: forward to twenty twenty five, and we're finally here. It's 52 00:02:41,720 --> 00:02:45,880 Speaker 2: again somewhat interesting that it happened this week. There had 53 00:02:45,919 --> 00:02:47,840 Speaker 2: been a lot of anticipation about this, if you just 54 00:02:47,919 --> 00:02:51,000 Speaker 2: look at the share price, for example, since President Trump's 55 00:02:51,000 --> 00:02:55,240 Speaker 2: election in November, I think Wells Fargo heading into this 56 00:02:55,320 --> 00:02:57,639 Speaker 2: week was up like twenty percent on a total repase 57 00:02:57,919 --> 00:03:02,000 Speaker 2: return basis, and the KVW Bank Index as a whole 58 00:03:02,160 --> 00:03:04,080 Speaker 2: was only up about seven percent in that time. So 59 00:03:04,120 --> 00:03:07,320 Speaker 2: there was the anticipation was there. But also according to 60 00:03:07,360 --> 00:03:11,120 Speaker 2: our reporting, it took some senior executives by surprise. 61 00:03:11,400 --> 00:03:13,160 Speaker 1: Oh yeah, one of them was like doing an intern 62 00:03:13,560 --> 00:03:14,400 Speaker 1: visitor or something. 63 00:03:14,760 --> 00:03:17,840 Speaker 2: I think the chairman was celebrating his seventy third birthday, 64 00:03:18,120 --> 00:03:20,720 Speaker 2: So this is a nice surprise. Before we talk about 65 00:03:20,840 --> 00:03:23,639 Speaker 2: what this means for Wells Fargo, the future of Wells Fargo, 66 00:03:24,520 --> 00:03:29,200 Speaker 2: Matt I wasn't really paying that close attention to Wells 67 00:03:29,200 --> 00:03:31,560 Speaker 2: Fargo when this cap went into place in twenty eighteen. 68 00:03:32,240 --> 00:03:34,480 Speaker 2: I'd love to hear your thoughts on the lead up 69 00:03:34,520 --> 00:03:37,400 Speaker 2: there and how unprecedented this was. 70 00:03:37,840 --> 00:03:40,760 Speaker 1: I feel like in twenty eighteen everyone was paying attention to. 71 00:03:40,800 --> 00:03:43,600 Speaker 2: Wellswere I was worried about currencies. 72 00:03:44,000 --> 00:03:46,520 Speaker 1: I have rarely seen a bank scandal get people so 73 00:03:46,640 --> 00:03:50,320 Speaker 1: angry as the Wells Fargo fake account scandal, which I'm 74 00:03:50,320 --> 00:03:52,280 Speaker 1: not sure was like the direct precipitator of this, but 75 00:03:52,320 --> 00:03:54,120 Speaker 1: it was like one of the big things they pointed 76 00:03:54,160 --> 00:03:56,400 Speaker 1: to to be like you can never grow again. Wells 77 00:03:56,480 --> 00:04:01,120 Speaker 1: Fargo opened millions of fake accounts because they had like 78 00:04:01,320 --> 00:04:06,720 Speaker 1: a culture of cross selling and also not a culture 79 00:04:06,760 --> 00:04:09,800 Speaker 1: of supervising people very closely, I guess, And so like 80 00:04:10,200 --> 00:04:13,640 Speaker 1: they told thousands of bankers, your job is to open 81 00:04:13,680 --> 00:04:16,920 Speaker 1: eight new financial products today, and so they're like, okay, fine, 82 00:04:16,920 --> 00:04:18,520 Speaker 1: everyone who signs up for a check account, we're gonna 83 00:04:18,520 --> 00:04:20,640 Speaker 1: give them a credit card too, and like didn't tell 84 00:04:20,640 --> 00:04:22,760 Speaker 1: the customers, and so people got all these credit cards 85 00:04:22,760 --> 00:04:26,560 Speaker 1: they didn't sign up for, and that got Wells Fargo 86 00:04:26,640 --> 00:04:29,320 Speaker 1: in trouble. And also many people are really mad because 87 00:04:29,320 --> 00:04:32,360 Speaker 1: it just sounds bad. I think it, like it sounded 88 00:04:32,360 --> 00:04:34,080 Speaker 1: a little worse than it was, but it was pretty bad. 89 00:04:34,480 --> 00:04:38,200 Speaker 1: And I thought it was an interesting scandal because people 90 00:04:38,240 --> 00:04:40,600 Speaker 1: disagree with me about this, but like it didn't help 91 00:04:40,640 --> 00:04:43,080 Speaker 1: Wells Farga to open these fake accounts. There were like 92 00:04:43,120 --> 00:04:45,000 Speaker 1: a few accounts where like you know, you open a 93 00:04:45,000 --> 00:04:46,560 Speaker 1: credit card and you charge your credit card fee, so 94 00:04:46,600 --> 00:04:48,040 Speaker 1: like Wells Fargo made a little bit of money from 95 00:04:48,040 --> 00:04:50,360 Speaker 1: the fake accounts, but it's like negligible. Almost all of 96 00:04:50,400 --> 00:04:52,840 Speaker 1: these fake accounts were like nothing happened in them. It 97 00:04:52,920 --> 00:04:57,080 Speaker 1: was truly just like the employees gaming the management right, 98 00:04:57,120 --> 00:04:58,599 Speaker 1: Like the employees were told you got to open eight 99 00:04:58,600 --> 00:05:00,400 Speaker 1: accounts to day. I'm like, fine, we'll do that. But 100 00:05:00,440 --> 00:05:02,800 Speaker 1: like it was just these meaningless accounts that didn't help 101 00:05:02,800 --> 00:05:06,719 Speaker 1: Paul's fago. But that like met quotas, and that is 102 00:05:06,760 --> 00:05:09,160 Speaker 1: not a problem of a bank with like evil intent 103 00:05:09,200 --> 00:05:11,240 Speaker 1: at the top. That is the problem of a bank 104 00:05:11,480 --> 00:05:16,640 Speaker 1: that has management troubles, and like trouble like supervising it's 105 00:05:16,680 --> 00:05:20,000 Speaker 1: thousands of employees, and trouble like designing incentives and designing 106 00:05:20,000 --> 00:05:22,200 Speaker 1: programs to make sure that people are operating the best 107 00:05:22,240 --> 00:05:25,400 Speaker 1: interests of the bank. And you know, you always used 108 00:05:25,440 --> 00:05:27,839 Speaker 1: to read like people talking about banks being too big 109 00:05:27,880 --> 00:05:30,359 Speaker 1: to manage, and you know, like you look at that 110 00:05:30,400 --> 00:05:33,080 Speaker 1: scandal and you're like, yeah, like this is maybe a 111 00:05:33,080 --> 00:05:34,840 Speaker 1: bank that doesn't have a handle on all of its 112 00:05:34,839 --> 00:05:36,720 Speaker 1: employees and all of what it's doing right. This is 113 00:05:36,760 --> 00:05:39,000 Speaker 1: a bank that has not figured out how to manage 114 00:05:39,040 --> 00:05:40,880 Speaker 1: its bigness. And so I always thought that there was 115 00:05:40,920 --> 00:05:43,200 Speaker 1: like a poet of justice to like the punishment for 116 00:05:43,240 --> 00:05:46,200 Speaker 1: some of these scandals being bank regulators saying you can't 117 00:05:46,200 --> 00:05:49,120 Speaker 1: grow your balance sheet anymore, because you know, that's like 118 00:05:49,160 --> 00:05:51,400 Speaker 1: a direct cap on bigness. It's not a cap on 119 00:05:51,440 --> 00:05:55,080 Speaker 1: like employee numbers, but it's a cap on size, and 120 00:05:55,160 --> 00:05:58,360 Speaker 1: it sort of focuses the mind on like, Okay, we 121 00:05:58,480 --> 00:06:00,479 Speaker 1: got to be able to manage the bank the size 122 00:06:00,480 --> 00:06:04,120 Speaker 1: that it is before we grow any bigger. The punishment 123 00:06:04,160 --> 00:06:06,479 Speaker 1: is like an asset cap and then like stays in 124 00:06:06,560 --> 00:06:11,240 Speaker 1: place basically until they convince their regulators that they have 125 00:06:11,920 --> 00:06:15,400 Speaker 1: improved their risk management and board processes such that you know, 126 00:06:15,480 --> 00:06:18,760 Speaker 1: they can run their business in a safe way. And 127 00:06:18,839 --> 00:06:21,480 Speaker 1: I don't know, they seemed like sort of a reasonable punishment. 128 00:06:21,760 --> 00:06:25,840 Speaker 2: I have two thoughts. One, I have a Wells Fargo account, 129 00:06:26,000 --> 00:06:28,520 Speaker 2: which is funny. So you know, the extent of me 130 00:06:28,560 --> 00:06:31,920 Speaker 2: thinking about this in twenty eighteen was I wonder if 131 00:06:31,920 --> 00:06:33,120 Speaker 2: they gave me a credit card too. 132 00:06:33,320 --> 00:06:34,800 Speaker 1: I don't have a well Swargo looking at I do 133 00:06:34,839 --> 00:06:38,200 Speaker 1: have a well Square credit card and I use it 134 00:06:38,279 --> 00:06:41,640 Speaker 1: almost never. It's just like a spare credit card. And 135 00:06:41,640 --> 00:06:43,640 Speaker 1: like once every like two years, I get a letter 136 00:06:43,680 --> 00:06:45,839 Speaker 1: from them being like, we're going to close your credit 137 00:06:45,880 --> 00:06:49,000 Speaker 1: card unless you tell us not to or use it. 138 00:06:49,040 --> 00:06:50,880 Speaker 1: And I'll like go to the store and buy a 139 00:06:50,880 --> 00:06:53,480 Speaker 1: pack of gums so that I give the credit card open. 140 00:06:53,680 --> 00:06:55,200 Speaker 2: Oh you want it, I don't care. 141 00:06:55,720 --> 00:06:58,320 Speaker 1: Okay, It's like sitting in my desk doesn't bother me, right. 142 00:06:58,320 --> 00:06:59,960 Speaker 1: I wonder if I get those letters because they're like, 143 00:07:00,560 --> 00:07:02,159 Speaker 1: you know, they're looking at my account. They're like, oh no, 144 00:07:02,200 --> 00:07:05,000 Speaker 1: what if this is a fake account, So they're making 145 00:07:05,040 --> 00:07:06,560 Speaker 1: sure that my credit card is not fake. 146 00:07:06,880 --> 00:07:10,119 Speaker 2: I will say I decided to specifically open a Wells 147 00:07:10,120 --> 00:07:12,600 Speaker 2: Fargo account right before I went to college because I 148 00:07:12,680 --> 00:07:15,280 Speaker 2: was going to Haverford College, which we'll actually get to 149 00:07:15,640 --> 00:07:19,120 Speaker 2: a little bit, but it was very close to campus 150 00:07:19,160 --> 00:07:23,800 Speaker 2: and they had horses on the card the stagecoach, which 151 00:07:23,840 --> 00:07:25,960 Speaker 2: is one of the things that Charlie Sharp did away with. 152 00:07:26,040 --> 00:07:26,760 Speaker 2: He did away with the. 153 00:07:26,720 --> 00:07:29,040 Speaker 1: Look to keep it, to keep them under the asset cap. 154 00:07:29,080 --> 00:07:30,320 Speaker 1: They fired the horses. 155 00:07:30,560 --> 00:07:33,880 Speaker 2: They actually they fired the horses. They also fired tens 156 00:07:33,880 --> 00:07:36,240 Speaker 2: of thousands of employees. The other thought that I had 157 00:07:36,320 --> 00:07:39,280 Speaker 2: was that it's interesting that it feels pretty binary, like 158 00:07:39,320 --> 00:07:42,040 Speaker 2: the cap was on and now it's off. There wasn't 159 00:07:42,880 --> 00:07:45,600 Speaker 2: any step like, oh, you can grow the balance sheet 160 00:07:45,640 --> 00:07:48,880 Speaker 2: by half a trillion one trillion because you're doing such 161 00:07:48,920 --> 00:07:49,480 Speaker 2: a good job. 162 00:07:49,600 --> 00:07:52,760 Speaker 1: Yeah, it's a super weird regulatory move. It's not a 163 00:07:52,760 --> 00:07:55,080 Speaker 1: common punishment. Would not be normal to say, okay, you 164 00:07:55,120 --> 00:07:57,640 Speaker 1: can grow by one hundred million dollars. Those be weird. 165 00:07:58,080 --> 00:08:01,280 Speaker 1: They're just like they've put this mary draconian punishment on 166 00:08:01,360 --> 00:08:03,840 Speaker 1: and now it's been fixed, and they're like, okay, fine 167 00:08:04,040 --> 00:08:06,280 Speaker 1: crow again. So it'd be funny if they doubled in 168 00:08:06,320 --> 00:08:08,960 Speaker 1: size next month, but I assume that they won't. 169 00:08:09,440 --> 00:08:12,400 Speaker 2: If you think about the last seven years for Wells Fargo, 170 00:08:12,640 --> 00:08:17,160 Speaker 2: I was obviously fiddling with the charts. JP Morgan's balance sheet, 171 00:08:17,200 --> 00:08:20,080 Speaker 2: one of our reporters sold me has grown by an 172 00:08:20,320 --> 00:08:24,000 Speaker 2: entire Wells Fargo since this cap went into place. You 173 00:08:24,040 --> 00:08:26,880 Speaker 2: take a look at Wells Fargo's shares since the start 174 00:08:26,880 --> 00:08:30,400 Speaker 2: of February and twenty eighteen, They're up forty three percent 175 00:08:30,440 --> 00:08:33,760 Speaker 2: in total return terms since that time. You compare that 176 00:08:33,800 --> 00:08:36,480 Speaker 2: to JP Morgan up one hundred and seventy eight percent, 177 00:08:37,040 --> 00:08:40,200 Speaker 2: Goldman up one hundred and sixty percent. This has been 178 00:08:40,640 --> 00:08:43,640 Speaker 2: crippling for the performance of this company. 179 00:08:44,200 --> 00:08:47,000 Speaker 1: Yeah, I mean, like the Bloomberg reporting suggests that there 180 00:08:47,080 --> 00:08:49,080 Speaker 1: was some amount of like, if you can't grow, you 181 00:08:49,120 --> 00:08:51,080 Speaker 1: have to focus on the businesses that you really like. 182 00:08:51,440 --> 00:08:55,000 Speaker 1: But yes, that only does so much for you in 183 00:08:55,040 --> 00:08:58,120 Speaker 1: an environment of Dellwin's for banks. 184 00:08:58,559 --> 00:09:01,800 Speaker 2: Yeah. Also, this one was kind of funny. I was 185 00:09:01,840 --> 00:09:04,360 Speaker 2: looking at his valuation as well. It's price to book. 186 00:09:04,440 --> 00:09:06,800 Speaker 2: Wells Fargo trades at a price to book of one 187 00:09:06,840 --> 00:09:10,440 Speaker 2: point five. You compare that to JP Morgan's JP Morgan 188 00:09:10,559 --> 00:09:14,199 Speaker 2: trades at like two point two. City City trades at 189 00:09:14,280 --> 00:09:17,679 Speaker 2: point seven, which I think says more about City than 190 00:09:17,720 --> 00:09:20,720 Speaker 2: it does about Wells Fargo. But that was kind of fun. 191 00:09:21,400 --> 00:09:41,480 Speaker 1: Okay, City catching astraight here speaking of Haverford, Pennsylvania. You 192 00:09:41,520 --> 00:09:44,040 Speaker 1: know what else is there besides Katie's College. 193 00:09:44,440 --> 00:09:47,480 Speaker 2: The Egan Jones rating company, No, it was. 194 00:09:47,520 --> 00:09:49,480 Speaker 1: The branch of Wells Fire that you bank on College 195 00:09:49,559 --> 00:09:54,360 Speaker 1: Yesty operates out of a house in Harford, Pennsylvania, where 196 00:09:54,400 --> 00:09:57,800 Speaker 1: they rate thousands of private credit deals. 197 00:09:58,800 --> 00:10:01,920 Speaker 2: They actually have since relocated to King of Prussia, which 198 00:10:01,920 --> 00:10:04,680 Speaker 2: is also in the suburbs of Philadelphia, but we'll get 199 00:10:04,679 --> 00:10:10,360 Speaker 2: to that. Yeah, this ratings company, which calls itself the 200 00:10:10,400 --> 00:10:13,800 Speaker 2: biggest rating company in the private credit space, operated out 201 00:10:13,800 --> 00:10:18,319 Speaker 2: of a four bedroom colonial in Haverford, Pennsylvania, on Haverford 202 00:10:18,400 --> 00:10:22,320 Speaker 2: Station Road, literally across the street from my college. And 203 00:10:22,880 --> 00:10:25,840 Speaker 2: it's a pretty interesting business model, pretty scrappy. 204 00:10:26,320 --> 00:10:28,400 Speaker 1: I love the ratings business model, right. I mean, like, 205 00:10:29,280 --> 00:10:31,079 Speaker 1: so you can join this fighter by Shawane Egan, who 206 00:10:32,400 --> 00:10:34,040 Speaker 1: kind of made a name for himself in the financial 207 00:10:34,080 --> 00:10:37,959 Speaker 1: crisis criticizing the big three ratings agencies for their conflicts 208 00:10:37,960 --> 00:10:41,480 Speaker 1: of interest. Right. People think of ratings agencies as organizations 209 00:10:41,520 --> 00:10:44,679 Speaker 1: that write reports saying whether an issuer is a good 210 00:10:44,720 --> 00:10:46,400 Speaker 1: credit risk? Right. I mean, like this came up a 211 00:10:46,400 --> 00:10:48,839 Speaker 1: lot recently when the Booty's is the last agency to 212 00:10:48,920 --> 00:10:52,280 Speaker 1: downgrade the US government, and I was like, oh, what 213 00:10:52,320 --> 00:10:52,800 Speaker 1: does it mean? 214 00:10:52,920 --> 00:10:53,120 Speaker 2: Right? 215 00:10:53,480 --> 00:10:55,760 Speaker 1: Because like these agencies are sort of seen as like 216 00:10:55,840 --> 00:10:58,679 Speaker 1: the arbiter of credit risk, and his criticism in two 217 00:10:58,720 --> 00:11:02,600 Speaker 1: thousand and eight was these agencies are paid by the 218 00:11:02,600 --> 00:11:07,800 Speaker 1: issuers of the bonds, and therefore the issuers want to 219 00:11:07,800 --> 00:11:10,280 Speaker 1: have high ratings, and so if a ratings agency gives 220 00:11:10,280 --> 00:11:13,360 Speaker 1: them a low rating, the issue is say, we won't 221 00:11:13,400 --> 00:11:15,079 Speaker 1: pay you anymore if you don't give us a high rating, 222 00:11:15,080 --> 00:11:16,760 Speaker 1: and the agency say, fine, fine, fine, we give your 223 00:11:16,800 --> 00:11:18,800 Speaker 1: high rating. And this is like the sort of conflict 224 00:11:18,800 --> 00:11:22,280 Speaker 1: of interest model. And it's particularly a concern in the 225 00:11:22,320 --> 00:11:25,080 Speaker 1: structured product rating, where you have a bank that gets 226 00:11:25,160 --> 00:11:28,400 Speaker 1: ratings on hundreds of products, and if it isn't satisfied 227 00:11:28,400 --> 00:11:31,000 Speaker 1: with the ratings it gets, it can take its enormous 228 00:11:31,000 --> 00:11:34,760 Speaker 1: book of business to another ratings agency. And the Egan 229 00:11:34,840 --> 00:11:37,480 Speaker 1: Jones model was, I think this is not entire one 230 00:11:37,520 --> 00:11:39,400 Speaker 1: hundred percent try now. But like the general idea of 231 00:11:39,400 --> 00:11:42,720 Speaker 1: the model was they would get paid by consumers, They 232 00:11:42,720 --> 00:11:45,680 Speaker 1: would get paid by people who wanted to buy the debt, 233 00:11:45,840 --> 00:11:48,200 Speaker 1: and therefore they would have fewer conflicts of interest because 234 00:11:48,480 --> 00:11:51,400 Speaker 1: they would be looking at for the interests of the 235 00:11:51,440 --> 00:11:54,240 Speaker 1: investors the lenders, rather than the interests of the issuers, 236 00:11:54,679 --> 00:11:56,720 Speaker 1: and so when they told you this is a good 237 00:11:56,720 --> 00:11:59,120 Speaker 1: credit risk, you would know they mean it because you 238 00:11:59,160 --> 00:12:04,000 Speaker 1: were paying them. And I don't think that's the right 239 00:12:04,040 --> 00:12:07,080 Speaker 1: way to understand a ratings agency. I think that, like 240 00:12:07,440 --> 00:12:10,520 Speaker 1: if you're a buyer of credit, if you're a lender 241 00:12:11,040 --> 00:12:13,920 Speaker 1: and you're getting a rating, you're not doing it for you. 242 00:12:13,920 --> 00:12:15,600 Speaker 1: You're not doing it to figure out if the company 243 00:12:15,640 --> 00:12:17,360 Speaker 1: is a good risk or not right, because, like you're 244 00:12:17,679 --> 00:12:19,640 Speaker 1: a lender, you're in the business of knowing whether it's 245 00:12:19,679 --> 00:12:21,520 Speaker 1: a good risk or not. You might be interested in 246 00:12:21,520 --> 00:12:23,560 Speaker 1: like the credit ratings. It might give you some sort 247 00:12:23,600 --> 00:12:26,320 Speaker 1: of baseline understanding of what the credit is like, but 248 00:12:26,520 --> 00:12:28,880 Speaker 1: you can probably do your own credit analysis. The reason 249 00:12:28,960 --> 00:12:31,920 Speaker 1: you're getting a rating is you have some constraint on 250 00:12:32,120 --> 00:12:34,199 Speaker 1: who you're allowed to lend to, or like what your 251 00:12:34,200 --> 00:12:36,200 Speaker 1: book is supposed to look like. So if you're an 252 00:12:36,200 --> 00:12:39,080 Speaker 1: insurance company and you make investment grade loans or you buy 253 00:12:39,080 --> 00:12:42,200 Speaker 1: investment grade bonds, then you don't have to hold very 254 00:12:42,280 --> 00:12:45,240 Speaker 1: much capital against them. And if you make non investment 255 00:12:45,240 --> 00:12:47,280 Speaker 1: grade loans, you have a lot of capital. You know, 256 00:12:47,280 --> 00:12:50,320 Speaker 1: you get the rating to satisfy your capital regulators that 257 00:12:50,360 --> 00:12:53,440 Speaker 1: you are running your business prudently, and so you have 258 00:12:53,480 --> 00:12:55,160 Speaker 1: the same incentives as an issue, right, you want a 259 00:12:55,200 --> 00:12:57,440 Speaker 1: high rating. You don't care. Like if the world worked 260 00:12:57,480 --> 00:12:59,840 Speaker 1: in such a way that like every bond could be 261 00:13:00,120 --> 00:13:02,280 Speaker 1: rated triple A, you'd be like, great, I can buy 262 00:13:02,440 --> 00:13:05,040 Speaker 1: every bond I want. You wouldn't buy like the worst bonds. 263 00:13:05,040 --> 00:13:07,160 Speaker 1: You do your own credit analysis, but you wouldn't have 264 00:13:07,160 --> 00:13:09,880 Speaker 1: to worry about regulation anymore, whereas regulators don't like that, right, 265 00:13:10,280 --> 00:13:14,000 Speaker 1: And so the ratings agency ultimately is not really working 266 00:13:14,040 --> 00:13:16,480 Speaker 1: on behalf of the issuer, and it's not really working 267 00:13:16,559 --> 00:13:18,959 Speaker 1: on behalf of the lender. It's working on behalf like 268 00:13:19,000 --> 00:13:21,960 Speaker 1: the lender's regulator or the lender's ultimate customer, right, like 269 00:13:21,960 --> 00:13:24,480 Speaker 1: the insurance company customer or the bank customer or whatever. 270 00:13:25,120 --> 00:13:28,760 Speaker 1: And so you know, you were read at Egan Jentes, 271 00:13:28,840 --> 00:13:32,280 Speaker 1: like you know, there's a big bloomber article about their 272 00:13:33,000 --> 00:13:35,560 Speaker 1: process and they're being run out of a four bedroom 273 00:13:35,600 --> 00:13:38,040 Speaker 1: house and also about like you know, there's a couple 274 00:13:38,040 --> 00:13:40,160 Speaker 1: of deals that they rated that kind of went bad, 275 00:13:40,200 --> 00:13:42,400 Speaker 1: and like there's some criticism of them, and there's some 276 00:13:42,480 --> 00:13:46,040 Speaker 1: like people are like other ratings firms issue twenty page 277 00:13:46,200 --> 00:13:48,839 Speaker 1: ratings reports and they issue one page rating reports. It's 278 00:13:48,840 --> 00:13:50,599 Speaker 1: like no one cares, no one reads that. Like the 279 00:13:51,000 --> 00:13:55,319 Speaker 1: goal is like a regulatory goal, and they are providing 280 00:13:55,840 --> 00:14:00,320 Speaker 1: a product that consumers in the market want, but you know, 281 00:14:00,520 --> 00:14:02,400 Speaker 1: you might not like why they want the product. 282 00:14:03,520 --> 00:14:06,120 Speaker 2: Yeah, So basically what you're saying is that it just 283 00:14:06,600 --> 00:14:10,960 Speaker 2: transfers the risk that is conflict of interest, and the 284 00:14:11,000 --> 00:14:14,160 Speaker 2: heavy insinuation in this article which you alluded to, is 285 00:14:14,200 --> 00:14:19,239 Speaker 2: that they're basically just rubber stamping these ratings on private investments. 286 00:14:19,440 --> 00:14:22,320 Speaker 1: I don't think that that's right. I don't think that. 287 00:14:22,160 --> 00:14:27,040 Speaker 2: They're One of the things the article describes is that, 288 00:14:27,480 --> 00:14:30,040 Speaker 2: I mean you mentioned that they have a small staff 289 00:14:30,080 --> 00:14:32,800 Speaker 2: and they have one page reports. Bloomberg News colleagues also 290 00:14:32,920 --> 00:14:36,960 Speaker 2: write that they offer their initial workups within twenty four hours, 291 00:14:37,040 --> 00:14:39,920 Speaker 2: a formal verdict in less than five days, whereas you 292 00:14:40,000 --> 00:14:42,000 Speaker 2: compare that to an S and P or a Fitch 293 00:14:42,520 --> 00:14:45,520 Speaker 2: and those rating decisions can take months at a time. 294 00:14:45,720 --> 00:14:49,520 Speaker 2: So they're working with a much smaller staff and in 295 00:14:49,760 --> 00:14:51,360 Speaker 2: very compressed timeframes. 296 00:14:52,040 --> 00:14:55,800 Speaker 1: Yeah. Right. They say their ratings generally perform well, right, 297 00:14:55,800 --> 00:14:57,760 Speaker 1: I mean, you can always like find someones that aren't 298 00:14:57,880 --> 00:15:00,400 Speaker 1: very good that you know, the default rate on like 299 00:15:00,480 --> 00:15:03,320 Speaker 1: a you know, triple B company is not supposed to 300 00:15:03,320 --> 00:15:04,880 Speaker 1: be zero, so you can always find some triple B 301 00:15:04,960 --> 00:15:06,800 Speaker 1: company that defaults and then it's like, you know, oh 302 00:15:06,800 --> 00:15:08,840 Speaker 1: that was wrong, right, But it's like, statistically you have 303 00:15:08,880 --> 00:15:11,080 Speaker 1: to have some of those. But if you ran a 304 00:15:11,120 --> 00:15:13,640 Speaker 1: ratings agency that gave everything in triple A, like there 305 00:15:13,640 --> 00:15:16,760 Speaker 1: would be demand for that, but like you wouldn't last long, 306 00:15:17,560 --> 00:15:19,760 Speaker 1: Like there wouldn't really be demand for that, or like 307 00:15:19,880 --> 00:15:22,360 Speaker 1: it'd be great to get everyone, every anything rated triple A, 308 00:15:22,400 --> 00:15:24,600 Speaker 1: but it wouldn't really satisfy your regulators, It wouldn't really 309 00:15:24,600 --> 00:15:26,960 Speaker 1: satisfy anyone. So I don't think that they are a 310 00:15:27,000 --> 00:15:29,960 Speaker 1: rubber stamp. I think that they're doing genuine credit work. 311 00:15:30,000 --> 00:15:33,520 Speaker 1: But I think, you know, there's some insinuation that they 312 00:15:33,720 --> 00:15:37,440 Speaker 1: have a tendency to rate stuff higher than other people 313 00:15:37,480 --> 00:15:40,400 Speaker 1: would rate it, and particularly they were working in the 314 00:15:40,400 --> 00:15:44,000 Speaker 1: private credit space where the ratings are not for broad 315 00:15:44,040 --> 00:15:46,880 Speaker 1: public consumption because it's a handful of lenders making the loans, 316 00:15:46,880 --> 00:15:50,400 Speaker 1: and those lenders can kind of pick their own rating agency, 317 00:15:50,520 --> 00:15:53,320 Speaker 1: and yeah, they're gonna want the one that works with 318 00:15:53,360 --> 00:15:55,000 Speaker 1: them nicely and is maybe a little bit. 319 00:15:54,920 --> 00:15:59,040 Speaker 2: Generous well to the point on generosity. There is a 320 00:15:59,080 --> 00:16:01,960 Speaker 2: description in this part of about the kerfuffle that was 321 00:16:02,080 --> 00:16:06,520 Speaker 2: raised by this report from the National Association of Insurance Commissioners. 322 00:16:06,960 --> 00:16:11,280 Speaker 2: Apparently they rescinded this report, but it showed that smaller 323 00:16:11,320 --> 00:16:14,760 Speaker 2: outfits such as Egan Jones tended to rate private investments 324 00:16:14,800 --> 00:16:18,840 Speaker 2: three notches higher on average than the association's in house 325 00:16:19,040 --> 00:16:23,000 Speaker 2: valuation office. This report was rescinded, but it was heard 326 00:16:23,040 --> 00:16:26,840 Speaker 2: around the industry. Apparently it was rescinded, according to people familiar, 327 00:16:26,840 --> 00:16:29,000 Speaker 2: because of backlash from insurers as well as some of 328 00:16:29,000 --> 00:16:31,720 Speaker 2: the ratings firms. But kind of, I mean there's some 329 00:16:31,760 --> 00:16:32,760 Speaker 2: evidence there. 330 00:16:32,840 --> 00:16:35,080 Speaker 1: Yeah, I've never fully understood it. Like there's there's some 331 00:16:35,160 --> 00:16:39,960 Speaker 1: real controversy going on at the National Association of Insurance Commissioners. Like, yeah, 332 00:16:40,160 --> 00:16:46,120 Speaker 1: there are a lot of insurers who really like private credit, 333 00:16:46,160 --> 00:16:49,440 Speaker 1: let's say, really like alternative asset managers. Some of these 334 00:16:49,480 --> 00:16:52,480 Speaker 1: insurers are big customers of those alternative asset managers. Some 335 00:16:52,520 --> 00:16:55,960 Speaker 1: of them are owned by those big asset managers, and 336 00:16:56,000 --> 00:16:58,040 Speaker 1: so all of those insurers are like basically like, we 337 00:16:58,080 --> 00:17:01,000 Speaker 1: would like to chuck a lot of our money into 338 00:17:01,000 --> 00:17:03,640 Speaker 1: private credit. We think getting paid for liquidity and like 339 00:17:03,720 --> 00:17:06,119 Speaker 1: it's a good investment and we should be doing this 340 00:17:06,359 --> 00:17:08,920 Speaker 1: and it's professionally managed, and like, you know, we're doing 341 00:17:08,960 --> 00:17:11,000 Speaker 1: a good job. And there's a lot of other insurance 342 00:17:11,000 --> 00:17:16,320 Speaker 1: companies who do more traditional bond investing and are really 343 00:17:16,359 --> 00:17:20,120 Speaker 1: mad at the private credit insurance companies and think that 344 00:17:20,600 --> 00:17:24,159 Speaker 1: they are taking wild risks with customer money. You know, 345 00:17:24,200 --> 00:17:27,199 Speaker 1: they think the asset manager owned insurance companies are like 346 00:17:27,240 --> 00:17:30,760 Speaker 1: making too much money. So there is like controversy within 347 00:17:30,800 --> 00:17:33,479 Speaker 1: the insurance world where like some insurers are trying to 348 00:17:33,560 --> 00:17:36,160 Speaker 1: basically stop people from investing in private credit, and other 349 00:17:36,200 --> 00:17:38,160 Speaker 1: insurers are saying, we want to back up the truck 350 00:17:38,200 --> 00:17:40,679 Speaker 1: for private credit. And so some of that controversy has 351 00:17:40,680 --> 00:17:43,520 Speaker 1: played out in like the issuing and rescinding of reports. 352 00:17:43,880 --> 00:17:48,439 Speaker 1: But it's a point of contention. And yeah, the report 353 00:17:48,440 --> 00:17:50,280 Speaker 1: about ratings is I think part of that. 354 00:17:50,600 --> 00:17:52,320 Speaker 2: I don't have it in front of me, but there 355 00:17:52,400 --> 00:17:54,800 Speaker 2: is a professor quoted in the piece I believe that 356 00:17:54,920 --> 00:17:58,880 Speaker 2: was talking about the performance of their rated companies, and 357 00:17:59,320 --> 00:18:02,520 Speaker 2: the professor make the point that the public investments that 358 00:18:02,560 --> 00:18:04,399 Speaker 2: they rate it tended to do okay. It's just that 359 00:18:05,080 --> 00:18:08,960 Speaker 2: it kind of deteriorated as it got into more private 360 00:18:09,200 --> 00:18:11,240 Speaker 2: sort of investments. It's kind of the whole point of 361 00:18:11,280 --> 00:18:14,240 Speaker 2: their business though, was to rate private investments, and you 362 00:18:14,320 --> 00:18:18,439 Speaker 2: can cherry pick examples and any rating agencies will have that, 363 00:18:18,720 --> 00:18:22,000 Speaker 2: but there were some great examples in this piece as well, 364 00:18:22,240 --> 00:18:24,399 Speaker 2: and most of them were triple BE rated, it seems 365 00:18:24,440 --> 00:18:25,520 Speaker 2: like before they blew up. 366 00:18:26,240 --> 00:18:29,920 Speaker 1: Then as a banker, we did this analysis for companies 367 00:18:30,160 --> 00:18:32,360 Speaker 1: that was like what is the optimal credit rating to have? 368 00:18:32,880 --> 00:18:36,639 Speaker 1: And I never fully understood that there was like some complicated, 369 00:18:36,760 --> 00:18:40,439 Speaker 1: you know, model that told you what the optimal credit 370 00:18:40,520 --> 00:18:43,760 Speaker 1: rating to have was based on your unique facts and circumstances. 371 00:18:43,760 --> 00:18:45,800 Speaker 1: But the answer was always triple to B minus, which 372 00:18:45,840 --> 00:18:49,359 Speaker 1: makes total intuitive sense because basically there's like a break 373 00:18:49,359 --> 00:18:53,240 Speaker 1: point where investors can buy anything grated triple B minus 374 00:18:53,359 --> 00:18:56,320 Speaker 1: or above and they can't buy anything graded w B 375 00:18:56,400 --> 00:18:59,359 Speaker 1: plus or below, and so you get access to the 376 00:18:59,359 --> 00:19:02,639 Speaker 1: investment grade buyers, which lowers your cost of debt if 377 00:19:02,640 --> 00:19:06,200 Speaker 1: you're a triple B minus or above, but anything better 378 00:19:06,240 --> 00:19:08,000 Speaker 1: than that you're leaving money on the table. You're like 379 00:19:08,119 --> 00:19:10,200 Speaker 1: under levered, right, Like you want to be as levered 380 00:19:10,200 --> 00:19:12,600 Speaker 1: as possible and still have access to investment grade credit. 381 00:19:13,880 --> 00:19:18,320 Speaker 1: And you know, like in the private credit wor old 382 00:19:18,320 --> 00:19:21,080 Speaker 1: same story, right, Like you want to lend money to 383 00:19:21,200 --> 00:19:25,399 Speaker 1: the most exciting, riskiest companies that will pay you the 384 00:19:25,440 --> 00:19:29,840 Speaker 1: most consistent with getting a triple B rating, and so yeah, 385 00:19:29,960 --> 00:19:32,639 Speaker 1: if you can push out the boundaries of risk on 386 00:19:32,680 --> 00:19:34,720 Speaker 1: triple B a little bit more, then that's a better 387 00:19:34,760 --> 00:19:36,959 Speaker 1: deal for you. Similarly, like you wouldn't get a lot 388 00:19:37,000 --> 00:19:40,359 Speaker 1: of A ratings because like if a company doing a 389 00:19:40,400 --> 00:19:44,120 Speaker 1: private credit deal would get an A rating, then you're 390 00:19:44,160 --> 00:19:46,600 Speaker 1: just like, well, let's borrow more then until we can 391 00:19:46,640 --> 00:19:48,840 Speaker 1: get down to triple B. But like below triple B 392 00:19:49,000 --> 00:19:51,280 Speaker 1: is bad. So there's a reason it's all triple B. 393 00:19:51,920 --> 00:19:54,399 Speaker 1: But yeah, there's a couple of examples in the story, 394 00:19:54,520 --> 00:19:58,240 Speaker 1: of which the funniest is probably Chicken Soup for the Soul, 395 00:19:58,280 --> 00:20:00,480 Speaker 1: which I think I wrote about in the day, Like 396 00:20:00,520 --> 00:20:02,720 Speaker 1: Chicken seap for this Soul had a weird slide into bankruptcy, 397 00:20:02,800 --> 00:20:05,359 Speaker 1: but it was triple B rated at Egan Jones until 398 00:20:05,400 --> 00:20:06,760 Speaker 1: like through like twenty twenty three. 399 00:20:07,080 --> 00:20:11,560 Speaker 2: Yeah, fourteen months after Egan Jones reiterated it's triple B 400 00:20:11,680 --> 00:20:15,160 Speaker 2: rating for the company, it filed for bankruptcy, and its 401 00:20:15,240 --> 00:20:17,560 Speaker 2: lawyer said at the time it only had twenty five 402 00:20:17,640 --> 00:20:21,119 Speaker 2: grand left in the bank, So that one was pretty funny. 403 00:20:21,240 --> 00:20:23,119 Speaker 2: Can I tell you what the most surprising thing in 404 00:20:23,160 --> 00:20:26,719 Speaker 2: this article was? Though, Yeah, okay, bring it back to Haverford. 405 00:20:27,000 --> 00:20:29,040 Speaker 1: I knew it was going to go back to Haverford. 406 00:20:28,640 --> 00:20:33,240 Speaker 2: A beautiful Philadelphia suburb. On the mainline. Apparently they sold 407 00:20:33,400 --> 00:20:38,600 Speaker 2: the four bedroom colonial on Haverford Station Road in late 408 00:20:38,680 --> 00:20:42,480 Speaker 2: twenty twenty four for eight hundred and sixty five thousand dollars, 409 00:20:42,840 --> 00:20:44,119 Speaker 2: which seems pretty cheap. 410 00:20:44,640 --> 00:20:46,159 Speaker 1: It's funny when you said, can I tell you the 411 00:20:46,160 --> 00:20:48,120 Speaker 1: most surprising thing, I was, like, this is probably gonna 412 00:20:48,280 --> 00:20:50,920 Speaker 1: have a preferred real estate thing. It does seem cheap. 413 00:20:51,000 --> 00:20:52,280 Speaker 1: On the main line, Yeah. 414 00:20:52,760 --> 00:20:54,520 Speaker 2: I wish I had bought it. I guess it was 415 00:20:54,600 --> 00:20:58,600 Speaker 2: zoned for commercial use though, because apparently a psychotherapy practice 416 00:20:58,800 --> 00:21:02,320 Speaker 2: took over the space. Egan Jones is now legally headquartered 417 00:21:02,560 --> 00:21:06,040 Speaker 2: in King of Prussia, So there you go. But very 418 00:21:06,040 --> 00:21:10,200 Speaker 2: close to Haverford College, beautiful, great nature trail which I've 419 00:21:10,280 --> 00:21:31,080 Speaker 2: run hundreds of miles on. I have to go in 420 00:21:31,200 --> 00:21:31,800 Speaker 2: nine minutes. 421 00:21:31,840 --> 00:21:34,919 Speaker 1: Matt, Well, then let's talk about whatever. The third thing was. 422 00:21:35,880 --> 00:21:41,399 Speaker 2: Let's talk about Paul Marshall and Ian wasce Yes, the 423 00:21:41,720 --> 00:21:44,840 Speaker 2: billionaire odd couple, as the Wall Street Journal called them 424 00:21:44,840 --> 00:21:48,879 Speaker 2: in a recent profile. This was so well written. I 425 00:21:48,920 --> 00:21:51,520 Speaker 2: really enjoyed reading this by Caitlin McCabe over at the 426 00:21:51,560 --> 00:21:52,280 Speaker 2: Wall Street Journal. 427 00:21:52,440 --> 00:21:54,959 Speaker 1: Right, there's a great anecdote at the end about you know, 428 00:21:55,080 --> 00:21:57,879 Speaker 1: like any hedge fund, they like give job applicants like 429 00:21:58,119 --> 00:22:01,200 Speaker 1: puzzles and challenges and stuff, as you know from our. 430 00:22:01,520 --> 00:22:04,720 Speaker 2: Special still recovering from that episode. 431 00:22:04,440 --> 00:22:08,520 Speaker 1: And they waste one's challenged a group of hires to 432 00:22:08,600 --> 00:22:11,000 Speaker 1: visit the most countries in Europe within twenty four hours, 433 00:22:11,320 --> 00:22:14,439 Speaker 1: and one guy went to every embassy in London, so 434 00:22:14,480 --> 00:22:18,879 Speaker 1: he like won on a technicality and they hired him. 435 00:22:19,200 --> 00:22:22,199 Speaker 1: Ways says it was a bit too cute. I was 436 00:22:22,240 --> 00:22:25,600 Speaker 1: really thinking about, like, you know, it's not like everyone 437 00:22:25,640 --> 00:22:27,879 Speaker 1: at a hedge fund needs to be like a person 438 00:22:27,920 --> 00:22:31,199 Speaker 1: who can find a game to you know, get around 439 00:22:31,320 --> 00:22:33,760 Speaker 1: the stated rules of a problem. But like you want 440 00:22:33,760 --> 00:22:35,720 Speaker 1: some of those people at your hedge fund. That's a 441 00:22:35,840 --> 00:22:39,040 Speaker 1: useful skill and like you know, if you like give 442 00:22:39,080 --> 00:22:40,639 Speaker 1: someone a challenge like that and they come back and 443 00:22:40,640 --> 00:22:44,679 Speaker 1: they're like, I cheated, gotcha? You're like, okay, fine, you 444 00:22:44,720 --> 00:22:45,440 Speaker 1: got a job. 445 00:22:45,320 --> 00:22:45,880 Speaker 2: Come in? 446 00:22:46,160 --> 00:22:49,640 Speaker 1: Yeah, right, that amused me. I Mean, the main thing 447 00:22:49,800 --> 00:22:52,120 Speaker 1: that is so interesting about Marshall Waste is like they 448 00:22:52,119 --> 00:22:57,560 Speaker 1: have found this way they call it tops to monetize 449 00:22:58,200 --> 00:23:00,479 Speaker 1: sell side research and sell sides doock to right, Like 450 00:23:00,720 --> 00:23:02,199 Speaker 1: you know, you run a hedge fund. Like people are 451 00:23:02,200 --> 00:23:04,200 Speaker 1: calling you all day from banks saying like, hey, you 452 00:23:04,200 --> 00:23:09,600 Speaker 1: should buy this stuck And conventionally the response is, well, 453 00:23:09,640 --> 00:23:12,199 Speaker 1: I run a hedge fund and you don't, So why 454 00:23:12,240 --> 00:23:13,760 Speaker 1: Like if you're telling me to bout the stuck, Like, 455 00:23:13,920 --> 00:23:15,760 Speaker 1: clearly I'm better at this than you are, so why 456 00:23:15,800 --> 00:23:17,800 Speaker 1: why would I listen to you? And Marshall Base is 457 00:23:17,800 --> 00:23:19,760 Speaker 1: like we're gonna write them all down and we're gonna 458 00:23:19,760 --> 00:23:22,680 Speaker 1: see if any of them provide useful signals. And now 459 00:23:22,680 --> 00:23:25,359 Speaker 1: they have this like very complicated quantitative system that like 460 00:23:25,440 --> 00:23:28,840 Speaker 1: extracts signals from what like their cell side coverage tells them. 461 00:23:29,320 --> 00:23:34,080 Speaker 1: And that is endlessly fascinating because like, like one thing 462 00:23:34,119 --> 00:23:35,919 Speaker 1: that is happening here is like the cell It's like 463 00:23:36,119 --> 00:23:39,040 Speaker 1: they can understand the cell side analysts like better than 464 00:23:39,080 --> 00:23:42,119 Speaker 1: those people understand themselves, because like they're you know, putting 465 00:23:42,160 --> 00:23:44,080 Speaker 1: it into a quantitative model, and the cell side guys 466 00:23:44,080 --> 00:23:46,840 Speaker 1: are just like you know, calling clients all day and 467 00:23:46,880 --> 00:23:49,000 Speaker 1: so like, yeah, you know, they have the anecdote of like, 468 00:23:49,840 --> 00:23:52,080 Speaker 1: you know a research analyst who has really good ideas 469 00:23:52,160 --> 00:23:55,080 Speaker 1: but tells you to take them off too soon. He 470 00:23:55,440 --> 00:23:58,960 Speaker 1: cuts his winners too soon, and they will analyze that 471 00:23:59,080 --> 00:24:00,880 Speaker 1: and see that he always it's his winners too soon, 472 00:24:00,920 --> 00:24:03,080 Speaker 1: so they'll just ignore him when he cuts his winners, 473 00:24:03,119 --> 00:24:05,560 Speaker 1: and like they will do better with his recommendations then 474 00:24:05,600 --> 00:24:07,960 Speaker 1: he will do with his recommendations. And so there's a 475 00:24:07,960 --> 00:24:09,399 Speaker 1: lot of stuff like that where like you know, if 476 00:24:09,400 --> 00:24:11,240 Speaker 1: you know that someone is really good in the morning 477 00:24:11,320 --> 00:24:12,880 Speaker 1: and really bad in the afternoon, then you only trade 478 00:24:12,920 --> 00:24:15,000 Speaker 1: on her ideas in the morning and you make more 479 00:24:15,000 --> 00:24:17,320 Speaker 1: money than like if you just naively took her ideas. 480 00:24:17,920 --> 00:24:20,119 Speaker 1: There's sort of two skills at a hedge fund, right 481 00:24:20,160 --> 00:24:23,639 Speaker 1: There's being an analyst, which is like understanding companies and 482 00:24:23,680 --> 00:24:26,159 Speaker 1: coming up with ideas, and there's being a portfolio manager, 483 00:24:26,160 --> 00:24:28,159 Speaker 1: which is like making like the last step of like 484 00:24:28,560 --> 00:24:30,480 Speaker 1: turning it into a trade and taking off the trade 485 00:24:30,480 --> 00:24:32,600 Speaker 1: and figure out how much risk to take. And they 486 00:24:32,680 --> 00:24:36,679 Speaker 1: are like being the portfolio manager with like thousands of 487 00:24:36,720 --> 00:24:39,680 Speaker 1: analysts who work for their cell side coverage, and they 488 00:24:39,720 --> 00:24:43,439 Speaker 1: are taking the like raw information of the analysts and 489 00:24:43,480 --> 00:24:46,480 Speaker 1: turning it into useful trades that make money for them. 490 00:24:46,800 --> 00:24:48,080 Speaker 1: Or that's like the basic idea. 491 00:24:48,280 --> 00:24:51,320 Speaker 2: Yeah, it very loosely reminded me as I was reading 492 00:24:51,320 --> 00:24:54,359 Speaker 2: this profile of something we've talked about before, which is 493 00:24:54,720 --> 00:24:58,320 Speaker 2: you have short sellers who write research reports and then 494 00:24:58,359 --> 00:25:01,880 Speaker 2: they sell them to hedge funds to actually do the trades. 495 00:25:02,200 --> 00:25:03,560 Speaker 1: Yeah, and they do some of that too. They do that, 496 00:25:03,640 --> 00:25:05,639 Speaker 1: Like there are some like other other hedge funds who 497 00:25:05,640 --> 00:25:07,879 Speaker 1: are like, we can't do this trade for whatever reason, 498 00:25:07,920 --> 00:25:10,000 Speaker 1: but like you run a giant multi strategy fund, you 499 00:25:10,080 --> 00:25:12,040 Speaker 1: could put this trade into your portfolio, and so they 500 00:25:12,080 --> 00:25:12,280 Speaker 1: do it. 501 00:25:12,560 --> 00:25:15,280 Speaker 2: Yeah. I also thought it was funny. I mean, the 502 00:25:15,880 --> 00:25:18,520 Speaker 2: article in the Wall Street Journal spent some time talking 503 00:25:18,520 --> 00:25:22,720 Speaker 2: about how they have many fewer employees than a Citadel, 504 00:25:22,760 --> 00:25:24,520 Speaker 2: for example, I think they have seven hundred and fifty 505 00:25:24,520 --> 00:25:29,360 Speaker 2: employees versus Citadel's hedge fund has somewhere in the ballpark 506 00:25:29,400 --> 00:25:32,760 Speaker 2: of three thousand. But it feels like, you know, they've 507 00:25:33,320 --> 00:25:36,400 Speaker 2: outsourced for a lot of their trade ideas, so that 508 00:25:36,920 --> 00:25:39,480 Speaker 2: potentially lightens the headcount needs. 509 00:25:39,920 --> 00:25:43,240 Speaker 1: Yeah, those headcounts comparisons always like I never understand them 510 00:25:43,240 --> 00:25:46,320 Speaker 1: because like you know, conventionally need less headcount to do 511 00:25:46,400 --> 00:25:48,800 Speaker 1: quantity things. Then you know, there are different kinds of 512 00:25:49,080 --> 00:25:50,840 Speaker 1: businesses and a hedgehund, and some of them require more 513 00:25:50,840 --> 00:25:53,920 Speaker 1: headcount than others. But yeah, like intuitively, if like instead 514 00:25:53,960 --> 00:25:55,919 Speaker 1: of employing a lot of analysts to find ideas, you 515 00:25:56,040 --> 00:25:58,879 Speaker 1: just like employ yourself side coverage to find the ideas, 516 00:25:58,920 --> 00:26:01,720 Speaker 1: then you need fewer analysts. I will say that when 517 00:26:01,720 --> 00:26:03,560 Speaker 1: I write about this, I get a lot of emails 518 00:26:03,560 --> 00:26:08,119 Speaker 1: from people who are cynical, and the cynical take on 519 00:26:08,160 --> 00:26:11,200 Speaker 1: this system, and like other funds have done this, and 520 00:26:11,280 --> 00:26:14,479 Speaker 1: like Blackrock Ages Ago got in trouble for doing something 521 00:26:14,720 --> 00:26:16,760 Speaker 1: not this, but like the somewhat related thing, which is 522 00:26:16,800 --> 00:26:19,640 Speaker 1: like sending out an analyst survey. People don't like this 523 00:26:20,359 --> 00:26:25,200 Speaker 1: because they worry about fairness. Right, Like, if you send 524 00:26:25,200 --> 00:26:27,879 Speaker 1: out a survey of analysts and you say, what do 525 00:26:27,880 --> 00:26:32,280 Speaker 1: you think about this stock? Some of the analysts might say, oh, 526 00:26:32,280 --> 00:26:34,399 Speaker 1: I think it's bad, while they still have a buy 527 00:26:34,520 --> 00:26:37,680 Speaker 1: recommendation on because they're going to later change their buy recommendation, right, 528 00:26:37,720 --> 00:26:40,240 Speaker 1: They're gonna like you might get like a more updated 529 00:26:40,320 --> 00:26:43,720 Speaker 1: view than like the published seal side research analysis. Similarly, 530 00:26:43,760 --> 00:26:48,320 Speaker 1: if you're like surveying your salespeople and you say, what's 531 00:26:48,320 --> 00:26:50,680 Speaker 1: a good trade idea? One worry that a lot of 532 00:26:50,680 --> 00:26:53,320 Speaker 1: people have is that your salespeople will say to you 533 00:26:54,080 --> 00:26:57,320 Speaker 1: not like the idea they just thought of, but rather 534 00:26:57,760 --> 00:27:01,399 Speaker 1: something that is predictive of like client. Right, Like, the 535 00:27:01,440 --> 00:27:03,920 Speaker 1: salespeople know a lot about what other people are doing, 536 00:27:04,320 --> 00:27:06,400 Speaker 1: and if you ask them for their best trade ideas, 537 00:27:06,560 --> 00:27:08,840 Speaker 1: they might be leaking information to you. This is a 538 00:27:08,840 --> 00:27:10,560 Speaker 1: worry that people have. I don't know if it's true. 539 00:27:10,560 --> 00:27:12,440 Speaker 1: And like in this in this journal article, they point 540 00:27:12,440 --> 00:27:14,760 Speaker 1: out that like because of the way that Martial Waste 541 00:27:14,840 --> 00:27:17,000 Speaker 1: does it, which is like with this automated system that 542 00:27:17,080 --> 00:27:19,360 Speaker 1: like there has lots of timestamps and a lot of data, 543 00:27:19,480 --> 00:27:22,040 Speaker 1: Like they have a better audit trail than like, you know, 544 00:27:22,119 --> 00:27:24,520 Speaker 1: the conventional hedge fund approach of like calling up your 545 00:27:25,119 --> 00:27:27,239 Speaker 1: salesperson and saying, hey, what are other people doing? Right, 546 00:27:27,280 --> 00:27:30,320 Speaker 1: Like it's it's arguably more transparent and like less risky 547 00:27:30,359 --> 00:27:34,040 Speaker 1: thing than like the normal fundamental manager model. But it 548 00:27:34,080 --> 00:27:35,400 Speaker 1: is a thing that a lot of people worry about 549 00:27:35,440 --> 00:27:39,679 Speaker 1: that like you're leaking other institutional flows because your salesperson 550 00:27:39,760 --> 00:27:41,639 Speaker 1: is like trying to compete to give martial waste the 551 00:27:41,640 --> 00:27:42,159 Speaker 1: best ideas. 552 00:27:42,240 --> 00:27:44,640 Speaker 2: Yeah, and the article does mention that when this started 553 00:27:44,680 --> 00:27:49,359 Speaker 2: in the late nineties, there's was some skepticism, some suspicion 554 00:27:49,440 --> 00:27:50,639 Speaker 2: that is this even legal. 555 00:27:50,840 --> 00:27:53,400 Speaker 1: I can report from my email that that skepticism remains. 556 00:27:54,160 --> 00:27:56,640 Speaker 2: It remains. Yeah. Well, something I always think about when 557 00:27:56,680 --> 00:27:59,840 Speaker 2: I read that is, you know, I try to imagine 558 00:28:00,040 --> 00:28:03,879 Speaker 2: hedge fund like this launching in twenty twenty five and 559 00:28:03,880 --> 00:28:05,640 Speaker 2: what the reception would be. Like It's easy to read 560 00:28:05,640 --> 00:28:07,080 Speaker 2: this and be like, oh, well, it's been around for 561 00:28:07,080 --> 00:28:08,919 Speaker 2: thirty years, so it much to be okay. But I 562 00:28:08,920 --> 00:28:12,040 Speaker 2: imagine something like this launching now, you know, there would 563 00:28:12,080 --> 00:28:14,840 Speaker 2: be endless ink spilled about that. 564 00:28:14,920 --> 00:28:16,840 Speaker 1: Yeah, I mean, you really do need scale to do this, 565 00:28:16,880 --> 00:28:19,680 Speaker 1: because like you need people to fill out your little form. 566 00:28:19,720 --> 00:28:22,520 Speaker 1: Like when you know, like the company that got in 567 00:28:22,520 --> 00:28:24,359 Speaker 1: trouble for doing this was ten years ago. They settled 568 00:28:24,359 --> 00:28:26,560 Speaker 1: with New York. It was black Rock because like, yeah, Blackrock, 569 00:28:26,640 --> 00:28:28,320 Speaker 1: they can do whatever they want. If they ask analysts 570 00:28:28,320 --> 00:28:29,840 Speaker 1: to like fill out forms, they'll fill out the form. 571 00:28:29,960 --> 00:28:30,120 Speaker 2: Right. 572 00:28:30,200 --> 00:28:31,840 Speaker 1: If you started a new hedge fun today and you 573 00:28:31,880 --> 00:28:33,679 Speaker 1: asked every research analyst to fill out a form, they 574 00:28:33,680 --> 00:28:36,920 Speaker 1: wouldn't do it. But yeah, there was also I forget 575 00:28:36,920 --> 00:28:39,040 Speaker 1: it was called, but like there was this startup Edgemhen 576 00:28:39,080 --> 00:28:40,960 Speaker 1: in the last year or two that was, like their 577 00:28:40,960 --> 00:28:43,440 Speaker 1: business model was, we're going to have analysts and we're 578 00:28:43,440 --> 00:28:45,560 Speaker 1: not going to have portfolio managers. We're gonna have like 579 00:28:45,600 --> 00:28:50,000 Speaker 1: an algorithmic thing that will aggregate the analyst's recommendations into 580 00:28:50,040 --> 00:28:53,440 Speaker 1: a portfolio. Basically, we were gonna keep having human analysts 581 00:28:53,480 --> 00:28:56,480 Speaker 1: because they're valuable, but we're going to automate the portfolio 582 00:28:56,560 --> 00:28:59,640 Speaker 1: manager job. That's not exactly this, but it's related, right, 583 00:28:59,680 --> 00:29:02,360 Speaker 1: like this one. You know, they do the portfolio manager job, 584 00:29:02,400 --> 00:29:05,120 Speaker 1: but it's it's very quanti, right, Like they're using algorithms 585 00:29:05,160 --> 00:29:08,520 Speaker 1: to aggregate the like investment ideas that they get from 586 00:29:08,760 --> 00:29:11,080 Speaker 1: from like the cell side, and also doing other stuff. 587 00:29:11,120 --> 00:29:12,520 Speaker 1: The I mean to suggest that's all they do, but 588 00:29:12,600 --> 00:29:14,320 Speaker 1: like that's you know, the thing they're kind of famous for. 589 00:29:14,720 --> 00:29:18,240 Speaker 1: But like the the no PM thing is a little 590 00:29:18,280 --> 00:29:18,960 Speaker 1: similar idea. 591 00:29:19,000 --> 00:29:22,520 Speaker 2: There's a quote from either Marshall or Waste in there 592 00:29:22,520 --> 00:29:25,920 Speaker 2: talking about how we're not just taking Joe Schmo's stock 593 00:29:25,960 --> 00:29:28,080 Speaker 2: ideas we do more than that they do have. In 594 00:29:28,120 --> 00:29:31,480 Speaker 2: addition to this, tops is about forty billion of their 595 00:29:31,680 --> 00:29:34,600 Speaker 2: seventy billion in assets. They do have a fundamental stock 596 00:29:34,640 --> 00:29:37,040 Speaker 2: picking side of the business as well. 597 00:29:37,480 --> 00:29:40,560 Speaker 1: Yeah, I assume that, by the way, like this is 598 00:29:40,560 --> 00:29:42,080 Speaker 1: not in the article, and I don't actually know how 599 00:29:42,120 --> 00:29:44,200 Speaker 1: true this is, but like, certainly, if you run a 600 00:29:44,200 --> 00:29:50,320 Speaker 1: business that rigorously analyzes the investment ideas of like hundreds 601 00:29:50,360 --> 00:29:52,480 Speaker 1: of seal side people, if you notice that one of 602 00:29:52,520 --> 00:29:55,400 Speaker 1: them is really good, you should probably hire that person, right, Like, 603 00:29:55,400 --> 00:29:57,280 Speaker 1: you should probably move them over to your fundamental stock 604 00:29:57,280 --> 00:29:59,480 Speaker 1: picking side rather than just let them, you know, give 605 00:29:59,480 --> 00:30:00,440 Speaker 1: their ideas everyone. 606 00:30:00,680 --> 00:30:02,480 Speaker 2: This whole Street Journal article spends a lot of time 607 00:30:02,480 --> 00:30:06,560 Speaker 2: talking about how different these two guys are, and it 608 00:30:06,560 --> 00:30:08,720 Speaker 2: was a lot of fun to read this. But it's 609 00:30:08,840 --> 00:30:12,800 Speaker 2: unique to see this hedge fund work so well. They 610 00:30:12,800 --> 00:30:15,400 Speaker 2: found it in nineteen ninety seven or something, and we 611 00:30:15,440 --> 00:30:19,080 Speaker 2: have the very recent example of two Sigma for example, 612 00:30:19,280 --> 00:30:21,920 Speaker 2: it's co founders getting in such a brawl that they 613 00:30:21,920 --> 00:30:23,560 Speaker 2: had to be separated. 614 00:30:23,760 --> 00:30:25,640 Speaker 1: So also worked quite well. 615 00:30:25,680 --> 00:30:28,520 Speaker 2: Though, Yeah, I know, but just in terms of the 616 00:30:28,560 --> 00:30:31,800 Speaker 2: relationship there at the very top, you know, there was 617 00:30:32,000 --> 00:30:36,520 Speaker 2: some intervention so that was a charming factor in this article. 618 00:30:36,800 --> 00:30:38,800 Speaker 1: I've had it refreshing when two people are like, yes, 619 00:30:38,880 --> 00:30:41,560 Speaker 1: we've worked together for thirty years. It's a really good 620 00:30:41,560 --> 00:30:46,760 Speaker 1: professional partnership. We don't socialize, it's just the job's cool 621 00:30:47,200 --> 00:30:51,360 Speaker 1: man like us exactly looks like our podcast. 622 00:30:51,520 --> 00:30:55,160 Speaker 2: It's all for the camera, you guys can't see, but 623 00:30:55,320 --> 00:30:58,120 Speaker 2: it's all I'm looking at is myself in the return. Okay, 624 00:30:58,240 --> 00:30:58,920 Speaker 2: I have to go now. 625 00:31:00,080 --> 00:31:20,280 Speaker 1: The the