1 00:00:00,840 --> 00:00:04,000 Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney, alongside 2 00:00:04,080 --> 00:00:05,240 Speaker 1: my co host Matt Miller. 3 00:00:05,640 --> 00:00:09,600 Speaker 2: Every business day, we bring you interviews from CEOs, market pros, 4 00:00:09,720 --> 00:00:13,680 Speaker 2: and Bloomberg experts, along with essential market moving news. 5 00:00:14,160 --> 00:00:17,279 Speaker 1: Find the Bloomberg Markets Podcast on Apple Podcasts or wherever 6 00:00:17,360 --> 00:00:20,520 Speaker 1: you listen to podcasts, and at Bloomberg dot com slash podcast. 7 00:00:21,120 --> 00:00:23,239 Speaker 1: Let's talk to John Murphy. He does this stuff for 8 00:00:23,239 --> 00:00:27,000 Speaker 1: a living. He's Bloomberg Intelligence analysts. He's based in London. 9 00:00:27,280 --> 00:00:29,639 Speaker 1: He's trying to help poor Sam Fazelli, you know, with 10 00:00:29,720 --> 00:00:32,479 Speaker 1: his research. We appreciate John joining the team a few 11 00:00:32,560 --> 00:00:35,960 Speaker 1: years ago. John, talk to us about Prometheus. Here, what 12 00:00:36,360 --> 00:00:39,120 Speaker 1: is MERK buying for ten point eight billion dollars? 13 00:00:39,640 --> 00:00:43,160 Speaker 3: Yeah, sure, nice to join you. Yeah, what are they buying. 14 00:00:43,200 --> 00:00:46,120 Speaker 3: They're essentially buying one product, and it's a bit of 15 00:00:46,159 --> 00:00:48,600 Speaker 3: a gamble, some people might might suggest. But what we've 16 00:00:48,640 --> 00:00:52,040 Speaker 3: seen is we've seen phase two data in two indications 17 00:00:52,080 --> 00:00:56,600 Speaker 3: that both ritable bow disease indications Crone's disease and ultrative colitis. 18 00:00:57,200 --> 00:00:59,760 Speaker 3: Those data look very interesting, they look very competitive for 19 00:00:59,840 --> 00:01:03,360 Speaker 3: an see viewpoint. If and this is the key thing, 20 00:01:03,760 --> 00:01:06,319 Speaker 3: if they were to repeat those data in phase three. 21 00:01:06,520 --> 00:01:08,119 Speaker 3: Were probably not going to see that data till mid 22 00:01:08,160 --> 00:01:11,759 Speaker 3: twenty twenty five. And assuming there's a good safety profile, 23 00:01:12,040 --> 00:01:14,479 Speaker 3: then you're going to start seeing analysts put multi billion 24 00:01:14,480 --> 00:01:17,000 Speaker 3: dollar numbers in there in their spreadsheets. You're going to 25 00:01:17,080 --> 00:01:20,440 Speaker 3: start seeing high single digit billion dollars in their spreadsheets, 26 00:01:20,440 --> 00:01:23,280 Speaker 3: on which basis, ten point eight billion dollars will look 27 00:01:23,319 --> 00:01:26,560 Speaker 3: like a great, great deal. The converse is clearly true here. 28 00:01:27,040 --> 00:01:29,560 Speaker 1: Hey, John, just give me kind of the broad strokes. 29 00:01:29,560 --> 00:01:33,959 Speaker 1: How does a biotech analyst value a company like Prometheus? 30 00:01:33,959 --> 00:01:36,520 Speaker 1: I mean, before you know, like your close Friday with 31 00:01:36,560 --> 00:01:39,760 Speaker 1: an equity value a little over five billion dollars, do 32 00:01:39,840 --> 00:01:41,440 Speaker 1: you guys just go out there and say, hey, I 33 00:01:41,480 --> 00:01:45,039 Speaker 1: think the size of the market potentially is this, and 34 00:01:45,120 --> 00:01:47,840 Speaker 1: I think this drug could get X percent of this market, 35 00:01:47,880 --> 00:01:49,680 Speaker 1: and therefore I sign a multiple that way? 36 00:01:49,760 --> 00:01:50,840 Speaker 4: I mean, how do you guys do that? 37 00:01:51,560 --> 00:01:51,760 Speaker 5: Yeah? 38 00:01:51,800 --> 00:01:53,280 Speaker 3: I mean I think early on, a lot of this 39 00:01:53,400 --> 00:01:55,240 Speaker 3: is finger and the air stuff, right, and early on, 40 00:01:55,280 --> 00:01:57,880 Speaker 3: you're you're looking at the management team, you're looking at 41 00:01:57,880 --> 00:01:59,960 Speaker 3: the mechanism action, and you look at the disease air 42 00:02:00,600 --> 00:02:02,920 Speaker 3: Later on, and this is where these guys are now. 43 00:02:03,000 --> 00:02:05,520 Speaker 3: Later on you're looking at the clinical data and you're 44 00:02:05,520 --> 00:02:08,560 Speaker 3: comparing it with other products out there in the marketplace. 45 00:02:08,639 --> 00:02:10,440 Speaker 3: So we know in IBD there's a lot of big 46 00:02:10,520 --> 00:02:13,160 Speaker 3: drugs out there, Humera right nor to twenty billion dollars 47 00:02:13,160 --> 00:02:16,480 Speaker 3: for example. So you look at the data and you 48 00:02:16,560 --> 00:02:20,040 Speaker 3: compare and contrast there and versus those products. At the moment, 49 00:02:20,320 --> 00:02:23,160 Speaker 3: this looks pretty competitive. So that's kind of where you 50 00:02:23,200 --> 00:02:25,880 Speaker 3: are now. The next step then, of course, is a 51 00:02:25,919 --> 00:02:27,959 Speaker 3: company like Prometheus is going to be able to get out, 52 00:02:28,080 --> 00:02:29,960 Speaker 3: going to be able to do the Phase three itself, 53 00:02:29,960 --> 00:02:32,200 Speaker 3: it's going to be able to market the drug. Now 54 00:02:32,200 --> 00:02:34,280 Speaker 3: they've got a big guy on board putting their arm around, 55 00:02:34,280 --> 00:02:36,720 Speaker 3: and they've got Merk on board, and so again people 56 00:02:36,760 --> 00:02:40,120 Speaker 3: are going to start allocating greater value to the products 57 00:02:40,120 --> 00:02:41,480 Speaker 3: and to the company on the back of that. 58 00:02:41,880 --> 00:02:44,680 Speaker 6: Well, can we talk about the Merk side of this 59 00:02:44,760 --> 00:02:47,560 Speaker 6: deal here, because we're coming off I think a couple 60 00:02:47,600 --> 00:02:50,240 Speaker 6: of months ago Pfizer and Ciegen was the big biotech 61 00:02:50,280 --> 00:02:52,680 Speaker 6: deal that everyone was talking about. From when it comes 62 00:02:52,680 --> 00:02:56,080 Speaker 6: from Merks perspective, this is not probably going to be 63 00:02:56,160 --> 00:02:58,519 Speaker 6: the last acquisition that they make. How much cash do 64 00:02:58,600 --> 00:03:00,440 Speaker 6: they have on their balery. How much root do they 65 00:03:00,440 --> 00:03:03,560 Speaker 6: have to work with to diversify their pipeline. 66 00:03:03,600 --> 00:03:06,920 Speaker 3: Right, that's a great question, that's absolutely spot on In 67 00:03:07,000 --> 00:03:09,240 Speaker 3: terms of the commentary, I think, first for context here, 68 00:03:09,280 --> 00:03:11,520 Speaker 3: the key thing is Mert this year is going to 69 00:03:11,520 --> 00:03:14,320 Speaker 3: have the world's biggest selling drug, key Truder, a cancer 70 00:03:14,360 --> 00:03:17,280 Speaker 3: drug that goes off patent in twenty twenty eight when 71 00:03:17,280 --> 00:03:19,880 Speaker 3: it's going to be selling thirty three billion dollars. It's 72 00:03:19,880 --> 00:03:23,040 Speaker 3: about forty four percent of merk sales. So if MERK 73 00:03:23,120 --> 00:03:25,880 Speaker 3: doesn't have some products to replace that, it's going to 74 00:03:25,919 --> 00:03:27,959 Speaker 3: have a massive hole in its earnings. So we saw, 75 00:03:28,000 --> 00:03:30,320 Speaker 3: for example, MERK did a deal with acce on spent 76 00:03:30,400 --> 00:03:33,960 Speaker 3: eleven half billion dollars in twenty twenty one. You'll remember 77 00:03:34,000 --> 00:03:36,160 Speaker 3: they missed out and see gen Fires have taken siege 78 00:03:36,200 --> 00:03:38,520 Speaker 3: and now we've seen Prometheus today. There are going to 79 00:03:38,520 --> 00:03:41,640 Speaker 3: be more deals to follow from Merk because their strategy 80 00:03:41,720 --> 00:03:44,720 Speaker 3: or part of their strategy, is to make sure they 81 00:03:44,720 --> 00:03:48,440 Speaker 3: have additional growth legs when key Truder goes off. Pattern 82 00:03:48,920 --> 00:03:51,440 Speaker 3: in terms of how do they pay for these things, 83 00:03:51,520 --> 00:03:54,280 Speaker 3: what goes on in the balance sheet, Merk's throwing off 84 00:03:54,360 --> 00:03:58,320 Speaker 3: over twenty billion dollars of operating free cash flow annually. 85 00:03:58,640 --> 00:04:00,920 Speaker 3: So these sort of deals are deals they can very 86 00:04:00,960 --> 00:04:03,880 Speaker 3: straightforwardly do. They may pay cash, they may raise a 87 00:04:03,920 --> 00:04:05,840 Speaker 3: bit of a debt in the marketplace, but it's not 88 00:04:05,880 --> 00:04:08,200 Speaker 3: the sort of thing that's going to impact the credit 89 00:04:08,280 --> 00:04:09,440 Speaker 3: rating of a company like this. 90 00:04:10,600 --> 00:04:13,280 Speaker 1: John, you know what we've all been dealing with in 91 00:04:13,320 --> 00:04:17,000 Speaker 1: the macro over you know, the last you know, you know, 92 00:04:17,040 --> 00:04:19,280 Speaker 1: six months, maybe even more, is just a tightening of 93 00:04:19,360 --> 00:04:24,000 Speaker 1: credit out there, tough to raise capital, cost of capital 94 00:04:24,040 --> 00:04:26,280 Speaker 1: going higher for everybody in the marketplace. What does that 95 00:04:26,360 --> 00:04:29,120 Speaker 1: mean for the biotech space? If I've got a really 96 00:04:29,200 --> 00:04:33,160 Speaker 1: cool drug idea, or if I've got the science, can 97 00:04:33,200 --> 00:04:35,960 Speaker 1: I go out there and raise money for the early 98 00:04:36,040 --> 00:04:39,000 Speaker 1: early trials or is that a real tough go these days? 99 00:04:39,440 --> 00:04:42,240 Speaker 3: It really is a tough go these days. Absolutely, and 100 00:04:42,279 --> 00:04:44,120 Speaker 3: it's and it's tougher and tougher. And you can look 101 00:04:44,120 --> 00:04:45,720 Speaker 3: at it from two points of view. You can say, 102 00:04:45,720 --> 00:04:48,479 Speaker 3: if you're that biotech, what you really have to have, 103 00:04:48,640 --> 00:04:52,359 Speaker 3: ideally is you have to have hopefully some clinical data 104 00:04:52,520 --> 00:04:54,000 Speaker 3: at the very least, you have to have a very 105 00:04:54,000 --> 00:04:57,839 Speaker 3: good concept and a strong management and a credible management 106 00:04:57,839 --> 00:05:01,400 Speaker 3: management team in the absence of it becomes very, very tough, 107 00:05:01,440 --> 00:05:02,720 Speaker 3: and that's when you look at the other side of 108 00:05:02,760 --> 00:05:05,080 Speaker 3: the coin. Then big farmer starts looking down and they 109 00:05:05,080 --> 00:05:07,839 Speaker 3: can start to maybe cherry pick some of these better 110 00:05:07,920 --> 00:05:11,000 Speaker 3: assets because, as you rightly say, they're raising capital in 111 00:05:11,000 --> 00:05:13,520 Speaker 3: this market is a real tough ask. Of course, for 112 00:05:13,560 --> 00:05:17,279 Speaker 3: the farmer guys, they're so cash generative, it's something relatively 113 00:05:17,320 --> 00:05:18,880 Speaker 3: straightforward for them. 114 00:05:19,320 --> 00:05:22,000 Speaker 6: Well, when you're talking about just M and A activity 115 00:05:22,080 --> 00:05:24,679 Speaker 6: in general here, I mean, it feels like it's always 116 00:05:24,720 --> 00:05:28,320 Speaker 6: going to be in these bigger players' best interests to diversify. 117 00:05:28,320 --> 00:05:30,040 Speaker 6: We're hearing it from Mark, we're hearing it from Pfizer, 118 00:05:30,120 --> 00:05:34,320 Speaker 6: Maderna as well post COVID vaccine. But is the M 119 00:05:34,400 --> 00:05:37,640 Speaker 6: and A activity in any way indicative of kind of 120 00:05:37,680 --> 00:05:40,640 Speaker 6: the macroeconomic conditions that you're seeing or is this something 121 00:05:40,640 --> 00:05:42,320 Speaker 6: that's very specific to biotech. 122 00:05:43,400 --> 00:05:46,080 Speaker 3: Yeah, I don't think it relates to the macroeconomic side 123 00:05:46,080 --> 00:05:50,000 Speaker 3: of things. What I focus on really is the patent cycle. 124 00:05:50,080 --> 00:05:52,840 Speaker 3: Remember that drug companies are when they bring a drug 125 00:05:52,880 --> 00:05:55,600 Speaker 3: to market, a drug has a twenty year pattern life, 126 00:05:55,800 --> 00:05:57,880 Speaker 3: it's probably taking ten years to get to market. That 127 00:05:57,960 --> 00:06:00,440 Speaker 3: means every ten years, on average, half of them business 128 00:06:00,800 --> 00:06:03,800 Speaker 3: they have to regenerate or find from somewhere else. And 129 00:06:03,839 --> 00:06:07,160 Speaker 3: what we're seeing is between twenty twenty three and twenty 130 00:06:07,240 --> 00:06:11,479 Speaker 3: thirty there's nearly four hundred billion, four hundred billion of 131 00:06:11,560 --> 00:06:14,359 Speaker 3: annual sales potentially exposed to generics. So you've got a 132 00:06:14,360 --> 00:06:15,960 Speaker 3: lot of these players, some of the ones you just 133 00:06:16,040 --> 00:06:19,040 Speaker 3: mentioned there, you've got fiser merk of artists for example. 134 00:06:19,080 --> 00:06:22,400 Speaker 3: I being very very vocal indeed about having to do deals, 135 00:06:23,080 --> 00:06:25,000 Speaker 3: not huge deals, not like the ones that we saw 136 00:06:25,040 --> 00:06:28,240 Speaker 3: in the late eighties where that were buying other large companies, 137 00:06:28,279 --> 00:06:31,599 Speaker 3: but really deals that bring in product portfolio and late 138 00:06:31,640 --> 00:06:34,320 Speaker 3: stage assets and more lock on deals. But we would 139 00:06:34,360 --> 00:06:36,480 Speaker 3: expect to see a lot more deals in this kind 140 00:06:36,520 --> 00:06:40,159 Speaker 3: of high single digit billion dollars going forward. But we 141 00:06:40,240 --> 00:06:43,520 Speaker 3: don't think that today necessarily marks any sort of sea 142 00:06:43,600 --> 00:06:46,040 Speaker 3: change at all. This is very much in keeping with 143 00:06:46,640 --> 00:06:49,520 Speaker 3: the strategy the murk of an announced to the market already. 144 00:06:50,000 --> 00:06:52,080 Speaker 1: Hey, John, if I'm a merch shareholder, do I care 145 00:06:52,160 --> 00:06:54,680 Speaker 1: whether they come up with the next big drugs internally 146 00:06:54,720 --> 00:06:56,240 Speaker 1: through their R and D or they go out and 147 00:06:56,240 --> 00:06:56,560 Speaker 1: buy it. 148 00:06:56,600 --> 00:06:57,080 Speaker 7: Do I care? 149 00:06:58,200 --> 00:07:01,279 Speaker 3: No? Short short shop aren't, So no, I don't think so. 150 00:07:01,360 --> 00:07:04,400 Speaker 3: I think some investors like to see it coming through internally, 151 00:07:04,440 --> 00:07:06,520 Speaker 3: But at the end of the day, why does that matter. 152 00:07:07,200 --> 00:07:09,680 Speaker 3: If you're the smartest out there in terms of accessing 153 00:07:09,960 --> 00:07:12,720 Speaker 3: new technology or accessing new part line, that's as good 154 00:07:12,720 --> 00:07:14,040 Speaker 3: as doing it in the house yourself. 155 00:07:15,040 --> 00:07:17,120 Speaker 1: I mean it's interesting. I mean because there's Mark spending 156 00:07:17,120 --> 00:07:18,320 Speaker 1: thirteen billion on our R and D. 157 00:07:18,640 --> 00:07:22,400 Speaker 6: Yeah, thirty seconds, hear very quickly. What about the regulatory action. 158 00:07:22,440 --> 00:07:23,960 Speaker 6: It feels like the consensus here is that this is 159 00:07:24,000 --> 00:07:27,480 Speaker 6: going to have zero hurdles, So I. 160 00:07:27,400 --> 00:07:30,800 Speaker 3: Think, yeah, that's a very important point. Regulator in FTC 161 00:07:30,880 --> 00:07:33,160 Speaker 3: and FTC have clearly looked like they're going to be 162 00:07:33,400 --> 00:07:36,600 Speaker 3: more aggressive. However, there's no obvious overlap. Pier MERK doesn't 163 00:07:36,640 --> 00:07:39,320 Speaker 3: have a big presence in immunology. Slightly different to when 164 00:07:39,360 --> 00:07:41,400 Speaker 3: you looked at, for example, when we looked at fires 165 00:07:41,400 --> 00:07:43,720 Speaker 3: a siege and we did see some potential over that 166 00:07:43,880 --> 00:07:46,240 Speaker 3: learing bladder cancer. But this looks like it ought to 167 00:07:46,280 --> 00:07:49,080 Speaker 3: be clearing regulatory hurdles without any major issues. 168 00:07:49,360 --> 00:07:51,280 Speaker 1: All right, John, thank you so much for joining us. Really, 169 00:07:51,320 --> 00:07:55,040 Speaker 1: I really appreciate getting your insight. John Murphy, longtime pharmaceutical 170 00:07:55,080 --> 00:07:57,080 Speaker 1: analyst on the street, spent a lot of time in 171 00:07:57,120 --> 00:08:00,000 Speaker 1: Gold and Sachs. He joined Bloomberg Intelligence fore years ago. 172 00:08:00,400 --> 00:08:04,960 Speaker 1: So they've got a top notch healthcare team at Bloomberg Intelligence, 173 00:08:05,200 --> 00:08:08,480 Speaker 1: got folks in the US, in London with the Sam 174 00:08:08,520 --> 00:08:10,400 Speaker 1: Fazelli and John Murphy, and a good team in Asia 175 00:08:10,400 --> 00:08:13,000 Speaker 1: as well, So we got it covered all over the 176 00:08:13,000 --> 00:08:15,040 Speaker 1: place from every angle on the healthcare side. John Murphy 177 00:08:15,040 --> 00:08:19,600 Speaker 1: pharmaceutical anamals with Bloomberg Intelligence based in London. MRK buying 178 00:08:19,640 --> 00:08:24,640 Speaker 1: Prometheus biotech company ten point eight billion dollars. Nice little 179 00:08:24,680 --> 00:08:26,119 Speaker 1: trade for a Monday morning. 180 00:08:27,640 --> 00:08:31,520 Speaker 5: You're listening to the team ken'shar Live program Bloomberg Markets 181 00:08:31,520 --> 00:08:34,640 Speaker 5: weekdays at ten am Eastern on Bloomberg dot Com, the 182 00:08:34,720 --> 00:08:37,840 Speaker 5: iHeartRadio app, and the Bloomberg Business App, or listen on 183 00:08:37,920 --> 00:08:40,000 Speaker 5: demand wherever you get your podcasts. 184 00:08:42,200 --> 00:08:46,839 Speaker 1: Earnings are happening. Focus turns to earnings, folks, also turns 185 00:08:46,840 --> 00:08:48,360 Speaker 1: to dividends. A lot of folcus saying we need to 186 00:08:48,400 --> 00:08:50,680 Speaker 1: pay more attention to dividends and focus on them going 187 00:08:50,679 --> 00:08:53,760 Speaker 1: forward in this higher industrade environment. Austin Grath, founder and 188 00:08:53,880 --> 00:08:58,120 Speaker 1: CIO of Opal Capital, joins us. Austin talk to us 189 00:08:58,120 --> 00:09:02,600 Speaker 1: about kind of how you guys view dividends, How does 190 00:09:03,000 --> 00:09:05,679 Speaker 1: that factor into your investment thesis. 191 00:09:07,679 --> 00:09:12,199 Speaker 8: So we view dividends as a critical component to investor returns, 192 00:09:12,200 --> 00:09:15,360 Speaker 8: and we do that for a number of reasons, but 193 00:09:15,640 --> 00:09:19,319 Speaker 8: I think the biggest reason is just the dividends of contributed. 194 00:09:19,480 --> 00:09:22,480 Speaker 8: You know, depending on when you look back in the past, 195 00:09:22,480 --> 00:09:26,720 Speaker 8: it's contributed anywhere between kind of forty and sixty percent 196 00:09:26,720 --> 00:09:30,000 Speaker 8: of returns when you look at dividends and the reinvestment 197 00:09:30,040 --> 00:09:33,480 Speaker 8: of those dividends. So we think that investors that tend 198 00:09:33,559 --> 00:09:36,600 Speaker 8: to look to those parts of the market will end 199 00:09:36,679 --> 00:09:40,400 Speaker 8: up benefiting over time. We think the reason that that 200 00:09:40,559 --> 00:09:44,840 Speaker 8: exists is is because it's the good signaling mechanism for 201 00:09:44,960 --> 00:09:49,520 Speaker 8: management teams. Management teams that are willing to distribute some 202 00:09:49,640 --> 00:09:51,920 Speaker 8: of their cash fload to investors in the form of 203 00:09:51,920 --> 00:09:56,440 Speaker 8: dividends and grow that distribution over time tend to show 204 00:09:56,480 --> 00:09:59,440 Speaker 8: that they're confident and their business going forward. And the 205 00:09:59,520 --> 00:10:02,280 Speaker 8: business is that do this also happen to be a 206 00:10:02,360 --> 00:10:06,520 Speaker 8: relatively high quality company. So we think it puts investors 207 00:10:06,559 --> 00:10:08,640 Speaker 8: in a pretty good kind of section of the market 208 00:10:09,200 --> 00:10:11,400 Speaker 8: if they focus on dividend paying companies. 209 00:10:12,360 --> 00:10:14,800 Speaker 6: Talk to us a little bit about that phrase high 210 00:10:14,920 --> 00:10:18,400 Speaker 6: quality company. Are we looking at it from a kind 211 00:10:18,400 --> 00:10:20,800 Speaker 6: of cash perspective? How much cash do some of these 212 00:10:20,960 --> 00:10:22,920 Speaker 6: companies have on their balance sheet? For example, I think 213 00:10:22,920 --> 00:10:25,200 Speaker 6: in twenty twenty it was Techo was all the rage 214 00:10:25,280 --> 00:10:28,760 Speaker 6: because of that liquidity option. How do you value high 215 00:10:28,880 --> 00:10:31,559 Speaker 6: quality at a time when that cash is diminishing. 216 00:10:33,120 --> 00:10:37,280 Speaker 8: Yeah, so high quality is kind of subjective and everyone 217 00:10:37,480 --> 00:10:41,240 Speaker 8: has a different definition. Some people say high quality is 218 00:10:41,320 --> 00:10:44,199 Speaker 8: just high free cashual yield, and you know that that 219 00:10:44,840 --> 00:10:49,640 Speaker 8: can be true in some situations, but company pre castule 220 00:10:49,760 --> 00:10:52,880 Speaker 8: yield can vary over time, and so we really look 221 00:10:53,000 --> 00:10:56,960 Speaker 8: for companies that both have found balance sheet, they have 222 00:10:57,000 --> 00:11:01,880 Speaker 8: the ability to generate attractive free flows through the cycle. 223 00:11:02,000 --> 00:11:04,760 Speaker 8: So it's not just kind of commodities companies that have 224 00:11:04,880 --> 00:11:07,360 Speaker 8: a ton of free cash flow because they're in the 225 00:11:07,440 --> 00:11:10,640 Speaker 8: right part of the pricing cycles for the commodity. But 226 00:11:10,679 --> 00:11:13,800 Speaker 8: we want companies that have that balance sheet strength and 227 00:11:13,840 --> 00:11:17,480 Speaker 8: stability to pay a decent dividend through the cycle and 228 00:11:17,520 --> 00:11:20,400 Speaker 8: also grow the dividend. And then finally it comes down 229 00:11:20,440 --> 00:11:24,319 Speaker 8: to the really subjective measures is speaking with management and 230 00:11:24,400 --> 00:11:29,400 Speaker 8: understanding kind of what their ability and willingness to pay 231 00:11:29,440 --> 00:11:32,520 Speaker 8: dividends is so companies like some of these tech companies 232 00:11:32,559 --> 00:11:35,760 Speaker 8: that have a lot of cash, they may be considered 233 00:11:35,840 --> 00:11:38,880 Speaker 8: high quality, but then they end up putting that cash 234 00:11:38,920 --> 00:11:41,719 Speaker 8: into a bunch of kind of moonshot projects that may 235 00:11:41,760 --> 00:11:45,640 Speaker 8: not be that helpful for investors. And so we like 236 00:11:45,679 --> 00:11:50,200 Speaker 8: to focus on companies who are focused on investing for 237 00:11:50,280 --> 00:11:54,240 Speaker 8: the long term, but also focused on putting money towards 238 00:11:55,000 --> 00:11:58,120 Speaker 8: investments that have high returns on capital and aren't just 239 00:11:58,280 --> 00:12:01,240 Speaker 8: kind of kind of shooting for the moon hoping that 240 00:12:01,360 --> 00:12:03,760 Speaker 8: you know, whether whatever it is, kind of flying cars 241 00:12:03,880 --> 00:12:07,800 Speaker 8: or you know, space exploration or or whatever they're putting 242 00:12:07,840 --> 00:12:11,079 Speaker 8: money into, hoping it turns into a proper business at 243 00:12:11,080 --> 00:12:11,960 Speaker 8: some point in the future. 244 00:12:12,520 --> 00:12:16,520 Speaker 1: Austin, speaking of dividends, the banks have begun reporting earnings, 245 00:12:16,559 --> 00:12:18,240 Speaker 1: and you think about some of these big banks and 246 00:12:18,280 --> 00:12:21,280 Speaker 1: they have did with dividend yields of three to four percent. Here, 247 00:12:21,280 --> 00:12:23,160 Speaker 1: what did you see from some of the bank earnings 248 00:12:23,160 --> 00:12:26,960 Speaker 1: so far? And have you changed your view towards the banks? 249 00:12:28,440 --> 00:12:31,520 Speaker 8: Yeah, So the bank earnings is really interesting because it 250 00:12:31,600 --> 00:12:33,839 Speaker 8: kind of highlights what we think is going to be 251 00:12:34,160 --> 00:12:39,400 Speaker 8: a theme through the first quarter reporting cycle. So a 252 00:12:39,440 --> 00:12:42,839 Speaker 8: lot of banks didn't really so the economy or the 253 00:12:42,920 --> 00:12:46,880 Speaker 8: economic data was relatively positive for a little over two 254 00:12:46,960 --> 00:12:49,680 Speaker 8: thirds of the quarter, and so when you look back 255 00:12:49,920 --> 00:12:53,120 Speaker 8: at what banks are reporting, they're reporting on the first quarter, 256 00:12:53,160 --> 00:12:57,880 Speaker 8: which was a relatively positive economic environment. We think most 257 00:12:57,920 --> 00:13:03,479 Speaker 8: banks and most companies will actually turn in relatively acceptable 258 00:13:03,760 --> 00:13:07,040 Speaker 8: reports in the first quarter. We think investors should really 259 00:13:07,040 --> 00:13:11,800 Speaker 8: focus on what management teams are saying about the quarters 260 00:13:11,840 --> 00:13:16,160 Speaker 8: to come, as the dislocation in the market seem to 261 00:13:16,200 --> 00:13:20,280 Speaker 8: have started in March, and we think management teams will 262 00:13:20,280 --> 00:13:22,719 Speaker 8: start preparing for that and start preparing investors for that 263 00:13:22,880 --> 00:13:25,760 Speaker 8: with some of their commentary, and there will be kind 264 00:13:25,760 --> 00:13:29,480 Speaker 8: of winners and losers. We saw JP Morgan was one 265 00:13:29,520 --> 00:13:33,880 Speaker 8: of the big winners from the dislocation, and some of 266 00:13:33,320 --> 00:13:39,520 Speaker 8: the smaller banks are not necessarily reporting catastrophic results, but 267 00:13:39,600 --> 00:13:43,600 Speaker 8: they're alluding to less earning power going forward, and we 268 00:13:43,640 --> 00:13:46,679 Speaker 8: think that the risk at current valuation levels. 269 00:13:47,600 --> 00:13:49,920 Speaker 6: Can We talk a little bit about buybacks here, because 270 00:13:49,960 --> 00:13:52,960 Speaker 6: it feels like a lot of companies again who are 271 00:13:53,000 --> 00:13:56,800 Speaker 6: still sitting on cash and issue ins etc. That they 272 00:13:56,920 --> 00:14:00,800 Speaker 6: had from twenty twenty and twenty one, are actually still 273 00:14:00,840 --> 00:14:05,400 Speaker 6: buying back their stock despite talking about risks and layoffs 274 00:14:05,480 --> 00:14:10,560 Speaker 6: and kind of macroeconomic gloom and doom. What happens to buybacks. 275 00:14:12,679 --> 00:14:16,520 Speaker 8: It's an interesting question. Some of the biggest buyer backs 276 00:14:16,559 --> 00:14:20,680 Speaker 8: of shares for the large technology companies, and they tend 277 00:14:20,720 --> 00:14:23,119 Speaker 8: to buy back a lot of their shares to offset 278 00:14:23,920 --> 00:14:29,680 Speaker 8: dilution associated with compensation for employees. There's actually no we 279 00:14:29,680 --> 00:14:33,800 Speaker 8: could talk about the tax on buybacks. There's no tax 280 00:14:34,760 --> 00:14:40,560 Speaker 8: associated with the return of the buybacks for share for 281 00:14:40,800 --> 00:14:45,240 Speaker 8: management compensation. There will be a one percent tax on 282 00:14:45,440 --> 00:14:49,480 Speaker 8: buybacks that actually reduced share count. It's more of a 283 00:14:50,960 --> 00:14:55,000 Speaker 8: discretionary payment. So we think if if the economy really 284 00:14:55,080 --> 00:14:59,120 Speaker 8: does turn south, you might see those buybacks slow down 285 00:14:59,280 --> 00:15:02,760 Speaker 8: or even stop in many situations. But you do have 286 00:15:02,800 --> 00:15:05,440 Speaker 8: a lot of tech companies that are kind of forced 287 00:15:05,600 --> 00:15:09,000 Speaker 8: to buy back shares to make up for the dilution 288 00:15:09,920 --> 00:15:12,040 Speaker 8: that will take place if they don't buy back shares 289 00:15:12,080 --> 00:15:14,520 Speaker 8: just because of the way that they compensate their employees. 290 00:15:15,520 --> 00:15:18,160 Speaker 1: So also when you look at a company like Apple, 291 00:15:18,600 --> 00:15:21,120 Speaker 1: here's a company one hundred and sixty five billion dollars 292 00:15:21,120 --> 00:15:24,480 Speaker 1: of cash on its balance sheet, annual free cash flow 293 00:15:24,480 --> 00:15:26,560 Speaker 1: of about one hundred billion dollars a year for the 294 00:15:26,640 --> 00:15:29,640 Speaker 1: next couple of years, yet they pay no dividend. 295 00:15:29,720 --> 00:15:32,080 Speaker 7: Yes, they have a massive buyback, but no dividend. 296 00:15:32,560 --> 00:15:35,640 Speaker 1: I mean, does that surprise you because it seems like 297 00:15:35,680 --> 00:15:37,720 Speaker 1: they could put out a two or three percent dividend 298 00:15:37,800 --> 00:15:42,720 Speaker 1: yield and attract a whole new group of income seeking investors. 299 00:15:43,080 --> 00:15:45,520 Speaker 1: When you see a company like Apple, how do you 300 00:15:45,600 --> 00:15:46,160 Speaker 1: kind of view that? 301 00:15:47,720 --> 00:15:50,640 Speaker 8: Yeah, we look at that as management doesn't really value 302 00:15:51,320 --> 00:15:56,600 Speaker 8: a dividend. They value buybacks more than dividends. Over time, 303 00:15:56,920 --> 00:16:01,400 Speaker 8: we think that that might change. One of the changes 304 00:16:01,920 --> 00:16:05,480 Speaker 8: we see is potentially with the buy back tax that 305 00:16:05,640 --> 00:16:10,400 Speaker 8: was put in place. There has been talk about increasing that. 306 00:16:10,480 --> 00:16:14,040 Speaker 8: I think that President Biden mentioned it around the State 307 00:16:14,080 --> 00:16:17,440 Speaker 8: of the Union speech, to the extent that the government 308 00:16:17,560 --> 00:16:21,760 Speaker 8: starts to increase buy back taxes. We think that dividends 309 00:16:21,760 --> 00:16:27,160 Speaker 8: become relatively more attractive because you don't have the significant 310 00:16:27,560 --> 00:16:32,000 Speaker 8: difference in tax situation between dividends and buybacks, and we 311 00:16:32,080 --> 00:16:36,720 Speaker 8: think more companies will start distributing cash flows in the 312 00:16:36,720 --> 00:16:41,800 Speaker 8: form of dividends going forward. One thought on the Apple situation, 313 00:16:41,960 --> 00:16:45,760 Speaker 8: and actually many tech tech companies out there, is just 314 00:16:45,800 --> 00:16:49,880 Speaker 8: they haven't necessarily hit a point in their life cycle 315 00:16:49,920 --> 00:16:54,640 Speaker 8: where investors are expecting them to distribute that cash. We 316 00:16:54,680 --> 00:16:58,880 Speaker 8: think over time, if investors pressure for a higher dividend, 317 00:16:59,280 --> 00:17:03,360 Speaker 8: you will get more serious consideration for management teams. 318 00:17:03,560 --> 00:17:06,000 Speaker 1: All right, Austin, thanks so much for joining us. Always 319 00:17:06,000 --> 00:17:10,840 Speaker 1: love talking about stocks and dividends and companies dividend policies, 320 00:17:10,880 --> 00:17:13,280 Speaker 1: because a lot of folks are saying this next decade 321 00:17:13,359 --> 00:17:14,840 Speaker 1: is the decade of the dividend. 322 00:17:14,880 --> 00:17:15,480 Speaker 7: We've heard that a. 323 00:17:15,400 --> 00:17:17,960 Speaker 1: Couple of times from a couple investors. Austin Graff, He's 324 00:17:17,960 --> 00:17:21,359 Speaker 1: a founder and CIO of Opal Capital. Before that, he 325 00:17:21,440 --> 00:17:22,840 Speaker 1: was an equity analyst at PIMCO. 326 00:17:23,359 --> 00:17:26,480 Speaker 5: You're listening to the tape cats are live program Bloomberg 327 00:17:26,560 --> 00:17:30,119 Speaker 5: Markets weekdays at ten am Eastern on Bloomberg Radio, the 328 00:17:30,200 --> 00:17:33,440 Speaker 5: tune in app, Bloomberg dot com, and the Bloomberg Business App. 329 00:17:33,480 --> 00:17:36,280 Speaker 5: You can also listen live on Amazon Alexa from our 330 00:17:36,280 --> 00:17:41,360 Speaker 5: flagship New York station, Just say Alexa, play Bloomberg eleven thirty. 331 00:17:42,680 --> 00:17:44,560 Speaker 1: If you think about over the last year, year and 332 00:17:44,560 --> 00:17:47,399 Speaker 1: a half, at least, to me, the most widely used 333 00:17:47,480 --> 00:17:50,960 Speaker 1: term reference on Ernie's conference causes has been AI. Every 334 00:17:51,040 --> 00:17:55,720 Speaker 1: company's talking about AI, artificial intelligence, how it's impacting their business, 335 00:17:55,760 --> 00:17:58,160 Speaker 1: how they're using it, and I think most investors don't 336 00:17:58,160 --> 00:17:59,840 Speaker 1: even know what it is. They're trying to figure out 337 00:18:00,040 --> 00:18:01,800 Speaker 1: what is it? How does it impact the companies that 338 00:18:01,840 --> 00:18:04,520 Speaker 1: I invest in. We figured we go to a professional 339 00:18:04,520 --> 00:18:06,920 Speaker 1: here who does this stuff, Ashley Still. She's a senior 340 00:18:07,000 --> 00:18:10,520 Speaker 1: vice president and general manager for creative Cloud and document 341 00:18:10,560 --> 00:18:15,320 Speaker 1: Cloud at a little tech company out in California called Adobe. Ashley, 342 00:18:15,600 --> 00:18:16,960 Speaker 1: thank you so much for joining us. 343 00:18:18,280 --> 00:18:19,040 Speaker 4: Let's just start off. 344 00:18:19,080 --> 00:18:21,399 Speaker 1: I would love to get your definition of what is 345 00:18:21,480 --> 00:18:24,359 Speaker 1: AI and then how does it apply to some of 346 00:18:24,400 --> 00:18:26,120 Speaker 1: the businesses that Adobe is in. 347 00:18:28,280 --> 00:18:32,400 Speaker 9: Well, first, thanks for having me, and you know, at Adobe, 348 00:18:32,440 --> 00:18:35,480 Speaker 9: our mission is to help everyone bring their CreatiVision to life, 349 00:18:35,480 --> 00:18:40,240 Speaker 9: and we certainly believe that AI gives us a huge 350 00:18:40,240 --> 00:18:44,879 Speaker 9: opportunity to do that, for professionals and non professionals to like. So, 351 00:18:45,400 --> 00:18:51,000 Speaker 9: you know, AI simply for me, is when algorithms kind 352 00:18:51,000 --> 00:18:56,879 Speaker 9: of are aiding software to do tasks, and it often 353 00:18:57,400 --> 00:19:05,679 Speaker 9: helps automate repetitive, monotonous activities that traditionally humans have undertaken. 354 00:19:06,280 --> 00:19:08,480 Speaker 9: And one of the areas that we're really focused on 355 00:19:08,600 --> 00:19:11,760 Speaker 9: right now is an error of AI called generative AI, 356 00:19:12,119 --> 00:19:17,440 Speaker 9: and that enables people, you know, it's services like chat 357 00:19:17,440 --> 00:19:21,800 Speaker 9: GPT or Dolly, and Adobe just introduced a service called 358 00:19:21,800 --> 00:19:27,560 Speaker 9: Adobe Firefly that enables you to simply just enter text 359 00:19:28,440 --> 00:19:34,160 Speaker 9: and the models and algorithm produce images based on the 360 00:19:34,200 --> 00:19:38,560 Speaker 9: text that you've written. And so obviously this enables a 361 00:19:38,760 --> 00:19:44,160 Speaker 9: huge opportunity for people to express their ideas and create 362 00:19:44,240 --> 00:19:46,560 Speaker 9: content in new in different ways. 363 00:19:47,000 --> 00:19:50,400 Speaker 6: So how does that align with kind of just the 364 00:19:50,440 --> 00:19:52,679 Speaker 6: broader text space. I guess I mean, I'm thinking of 365 00:19:52,720 --> 00:19:56,440 Speaker 6: it as chat gpt is the easiest example of it. 366 00:19:56,560 --> 00:20:00,000 Speaker 6: It kind of makes sense that alphabet would hop into 367 00:20:00,160 --> 00:20:02,000 Speaker 6: what the Microsoft would happen to it because they have 368 00:20:02,040 --> 00:20:05,800 Speaker 6: search engines and that makes it kind of an easier alignment. 369 00:20:05,840 --> 00:20:08,520 Speaker 6: But then how do other companies within the tech space 370 00:20:09,760 --> 00:20:12,600 Speaker 6: adopt it? It feels like AI and chash ebt even 371 00:20:12,680 --> 00:20:14,600 Speaker 6: is a very wide umbrella. Can you give us some 372 00:20:14,600 --> 00:20:15,280 Speaker 6: more examples? 373 00:20:16,680 --> 00:20:21,040 Speaker 9: Absolutely? So, you know, for Adobe, we see this is 374 00:20:21,119 --> 00:20:25,000 Speaker 9: a huge opportunity to aid editing. If you think about 375 00:20:25,000 --> 00:20:28,480 Speaker 9: what our tools do, whether it's video or imaging or 376 00:20:28,480 --> 00:20:34,680 Speaker 9: photography or design, our tools enable creative professionals or marketers 377 00:20:35,160 --> 00:20:39,960 Speaker 9: to produce content. And they might do that with starting 378 00:20:40,040 --> 00:20:45,639 Speaker 9: with images or graphics that they've created themselves, or you know, 379 00:20:45,640 --> 00:20:48,960 Speaker 9: if you're a large company, you're probably licensing content as well. 380 00:20:49,560 --> 00:20:53,880 Speaker 9: This is a huge opportunities another source of content. Think 381 00:20:53,920 --> 00:20:57,639 Speaker 9: of it that way, where if you're in Photoshop and 382 00:20:58,320 --> 00:21:01,000 Speaker 9: you need to add an element to a design that 383 00:21:01,040 --> 00:21:05,320 Speaker 9: you're working on, instead of going and and you know 384 00:21:05,440 --> 00:21:09,000 Speaker 9: finding it in your files or from a colleague, you 385 00:21:09,040 --> 00:21:12,440 Speaker 9: can literally just produce it on the fly. So it 386 00:21:12,520 --> 00:21:17,359 Speaker 9: is again a powerful tool to help with editing. On 387 00:21:17,440 --> 00:21:22,119 Speaker 9: the marketing side, again, it enables marketers in more text 388 00:21:22,200 --> 00:21:27,520 Speaker 9: examples to create copy and and you know, one of 389 00:21:27,560 --> 00:21:32,120 Speaker 9: the big trends in digital and for companies is personalization 390 00:21:33,080 --> 00:21:36,600 Speaker 9: and a lot of content and experiences are being created 391 00:21:37,280 --> 00:21:42,080 Speaker 9: in order for businesses to have more relevant experiences for 392 00:21:42,160 --> 00:21:47,640 Speaker 9: their customers. And humans can't produce enough content to get 393 00:21:47,720 --> 00:21:51,159 Speaker 9: to true one to one personalization, and so AI is 394 00:21:51,200 --> 00:21:55,199 Speaker 9: going to be a really important again tool in the 395 00:21:55,440 --> 00:22:00,119 Speaker 9: in the tool chest to achieve true personalization and and 396 00:22:00,720 --> 00:22:02,040 Speaker 9: unlocks the power of digital. 397 00:22:02,560 --> 00:22:05,480 Speaker 1: Hey, Ashley, you know, as more and more companies and 398 00:22:05,520 --> 00:22:09,200 Speaker 1: individuals for that matter, embrace artificial intelligence, there's concerns out 399 00:22:09,200 --> 00:22:14,800 Speaker 1: there about control, having control over AI, what it can do. 400 00:22:15,720 --> 00:22:18,480 Speaker 1: How do you guys at Adobe think about that and 401 00:22:18,560 --> 00:22:19,280 Speaker 1: manage that risk. 402 00:22:21,240 --> 00:22:26,639 Speaker 9: Yes, So it is incredibly important as content is produced 403 00:22:26,680 --> 00:22:29,840 Speaker 9: in more and more ways, right by both humans as 404 00:22:29,880 --> 00:22:35,560 Speaker 9: well as algorithms and machines, for to have transparency. And 405 00:22:37,440 --> 00:22:41,920 Speaker 9: again I think there's whether you think of it as 406 00:22:41,960 --> 00:22:47,040 Speaker 9: control or transparency. Ultimately, consumers have to trust the content 407 00:22:47,080 --> 00:22:50,679 Speaker 9: that they're seeing, whether it's from a brand and a 408 00:22:50,720 --> 00:22:56,480 Speaker 9: marketing context, whether it's from news organizations. And Adobe founded 409 00:22:57,080 --> 00:23:01,560 Speaker 9: along with you now nine hundred partners an initiative called 410 00:23:01,560 --> 00:23:05,320 Speaker 9: the Content Authenticity Initiative, And what this really focuses on 411 00:23:05,600 --> 00:23:10,040 Speaker 9: is transparency for digital content. And we do that by 412 00:23:10,920 --> 00:23:15,960 Speaker 9: adding metadata to content as it's being edited and produced, 413 00:23:16,560 --> 00:23:22,439 Speaker 9: and that enables news site, businesses, et cetera to provide 414 00:23:22,480 --> 00:23:28,439 Speaker 9: that transparency to the consumer to just be clear, was 415 00:23:28,480 --> 00:23:33,160 Speaker 9: this content created with the help of generative AI, How 416 00:23:33,280 --> 00:23:34,840 Speaker 9: was this content edited? 417 00:23:35,320 --> 00:23:35,520 Speaker 5: Right? 418 00:23:35,640 --> 00:23:39,160 Speaker 9: Is it real or is it fake? So we're really 419 00:23:39,200 --> 00:23:43,760 Speaker 9: focused on transparency with both AI, but just in general 420 00:23:44,359 --> 00:23:46,760 Speaker 9: with digital content, are. 421 00:23:46,640 --> 00:23:51,200 Speaker 6: You all worried about regulatory pushback or scrutiny from Washington 422 00:23:51,320 --> 00:23:53,880 Speaker 6: or even scrutiny from kind of your demographic as well 423 00:23:53,920 --> 00:23:56,000 Speaker 6: as more and more people are talking about adopting AI, 424 00:23:56,359 --> 00:23:59,479 Speaker 6: it feels like there's privacy concerns associated with them. How 425 00:23:59,480 --> 00:24:00,320 Speaker 6: are you thinking out that? 426 00:24:02,840 --> 00:24:09,440 Speaker 9: Well, one of we believe very strongly that everybody participating 427 00:24:09,440 --> 00:24:12,600 Speaker 9: in I in AI needs to take a responsible approach 428 00:24:13,280 --> 00:24:16,399 Speaker 9: and so, for example, at Adobe, what we've done is 429 00:24:16,480 --> 00:24:21,359 Speaker 9: we only train our models on content that we have 430 00:24:21,440 --> 00:24:25,400 Speaker 9: a license to right or content that's on the Internet 431 00:24:25,480 --> 00:24:29,199 Speaker 9: where the license has expired. And we believe this is 432 00:24:29,320 --> 00:24:34,360 Speaker 9: really important because a lot of people don't want their 433 00:24:34,400 --> 00:24:37,480 Speaker 9: content to be used in training. You know, we represent 434 00:24:37,560 --> 00:24:40,919 Speaker 9: the creative community, and there are many people in the 435 00:24:40,920 --> 00:24:45,440 Speaker 9: creative community who don't want their style kind of quote 436 00:24:45,480 --> 00:24:50,080 Speaker 9: unquote stolen from them, and so we do believe it's 437 00:24:50,359 --> 00:24:54,200 Speaker 9: important to take a very responsible approach. And there's also 438 00:24:54,359 --> 00:24:57,479 Speaker 9: parts of the law that are very unclear right where 439 00:24:58,200 --> 00:25:02,240 Speaker 9: you know, copyright in the age your AI will evolve 440 00:25:02,400 --> 00:25:07,800 Speaker 9: right now, again with generative AI, if an artist produces 441 00:25:08,160 --> 00:25:15,119 Speaker 9: work through text prompts, there's no ability to copyright that work. 442 00:25:15,680 --> 00:25:20,600 Speaker 9: So there are definitely areas where the law will need 443 00:25:20,640 --> 00:25:23,679 Speaker 9: to evolve, and we think it's important as well that 444 00:25:23,920 --> 00:25:27,800 Speaker 9: companies are responsible and how they're sourcing data for AI. 445 00:25:28,240 --> 00:25:29,920 Speaker 1: Hey Ashley, Thank you so much for taking the time 446 00:25:29,960 --> 00:25:32,080 Speaker 1: to join us. We really appreciate kind of getting the 447 00:25:32,080 --> 00:25:35,680 Speaker 1: benefit of your wisdom on AI artificial intelligence. Actually still 448 00:25:36,000 --> 00:25:39,320 Speaker 1: senior vice president, General Manager Creative Cloud and document Cloud 449 00:25:39,440 --> 00:25:40,560 Speaker 1: at Adobe. 450 00:25:42,280 --> 00:25:45,720 Speaker 5: You're listening to the team Ken's are live program Bloomberg 451 00:25:45,760 --> 00:25:49,159 Speaker 5: Markets weekdays at ten am Eastern on Bloomberg dot com, 452 00:25:49,200 --> 00:25:52,359 Speaker 5: the iHeartRadio app and the Bloomberg Business app, or listen 453 00:25:52,400 --> 00:25:54,520 Speaker 5: on demand wherever you get your podcasts. 454 00:25:56,520 --> 00:25:59,960 Speaker 1: We're in a thick of bank earning season that means 455 00:26:00,119 --> 00:26:01,560 Speaker 1: talked to Hermit Chan. We talked to him a lot. 456 00:26:01,600 --> 00:26:03,200 Speaker 1: I'm kind of tired of this guy, but he covers 457 00:26:03,240 --> 00:26:05,040 Speaker 1: the regional banks. He's really really good at one of 458 00:26:05,080 --> 00:26:06,800 Speaker 1: the top guys on the street. But we're also joined 459 00:26:06,800 --> 00:26:10,400 Speaker 1: now by Neil SIPs, equity research analysts the Bloomberg Intelligence 460 00:26:10,440 --> 00:26:12,280 Speaker 1: He's a proud at University of Dayton flyer. 461 00:26:12,760 --> 00:26:13,040 Speaker 7: Neil. 462 00:26:13,119 --> 00:26:14,879 Speaker 1: The last time I saw you you were in Asso 463 00:26:14,960 --> 00:26:18,560 Speaker 1: shit working with Alison Williams. That they promoted you to analyst. 464 00:26:19,520 --> 00:26:22,600 Speaker 10: Yeah, that's right, that happened. Yeah, And you know, I 465 00:26:22,600 --> 00:26:25,600 Speaker 10: think many years of kind of getting into the details 466 00:26:25,600 --> 00:26:27,920 Speaker 10: of some of some of those bigger banks you get 467 00:26:27,920 --> 00:26:30,960 Speaker 10: a lot of experience and a lot of understanding, you 468 00:26:31,000 --> 00:26:33,240 Speaker 10: know what all these business lines are are driven by 469 00:26:33,240 --> 00:26:35,240 Speaker 10: and ultimately how these businesses are positioned. 470 00:26:35,240 --> 00:26:37,439 Speaker 4: All right, So what did you see from Schwab today? 471 00:26:37,480 --> 00:26:39,160 Speaker 1: And then you know, I'll ask you for your thoughts 472 00:26:39,200 --> 00:26:40,680 Speaker 1: later on kind of what we saw Friday from some 473 00:26:40,720 --> 00:26:41,360 Speaker 1: of the bigger banks. 474 00:26:41,400 --> 00:26:42,680 Speaker 4: Which would you see from Schwab today? 475 00:26:42,800 --> 00:26:43,040 Speaker 7: Yeah? 476 00:26:43,080 --> 00:26:46,040 Speaker 10: Sure, so I think from Schwab, you know, from the 477 00:26:46,440 --> 00:26:49,800 Speaker 10: from the start, you see the strength of their business. 478 00:26:49,840 --> 00:26:52,240 Speaker 10: You see return on equity and access to twenty percent, 479 00:26:52,640 --> 00:26:56,400 Speaker 10: you see pre tax margin above forty percent. Ultimately saw 480 00:26:56,400 --> 00:26:59,960 Speaker 10: the net interest margin decline this quarter sequentially, and that's 481 00:27:00,040 --> 00:27:03,280 Speaker 10: the biggest question for investors is what's going on with deposits. 482 00:27:04,040 --> 00:27:06,880 Speaker 10: Ultimately what we saw as deposits decline on the platform 483 00:27:06,920 --> 00:27:08,600 Speaker 10: by about forty billion this quarter. 484 00:27:09,400 --> 00:27:12,600 Speaker 4: That accelerated from the That's huge, right, Yeah, that's huge. 485 00:27:13,040 --> 00:27:16,520 Speaker 4: Of anything's big, but I mean when it's money, that's really. 486 00:27:16,640 --> 00:27:19,480 Speaker 10: Yeah, And for Schwab specifically, I mean that's that's sort 487 00:27:19,520 --> 00:27:22,000 Speaker 10: of the proposition of how they make money is ultimately 488 00:27:22,040 --> 00:27:26,160 Speaker 10: the uninvested cash in their clients accounts is what ultimately 489 00:27:26,160 --> 00:27:28,920 Speaker 10: gets reinvested. Into securities on the balance sheet, and that's 490 00:27:28,920 --> 00:27:32,200 Speaker 10: really the driver of net interest margin. When those deposits leave, 491 00:27:32,800 --> 00:27:36,080 Speaker 10: you start having issues on the liquidity front, and that's 492 00:27:36,160 --> 00:27:37,840 Speaker 10: kind of the question and what the you know what. 493 00:27:37,880 --> 00:27:40,280 Speaker 10: The CEO was trying to quell some of those concerns 494 00:27:40,320 --> 00:27:42,680 Speaker 10: today with of how they're going to provide funding going 495 00:27:42,680 --> 00:27:43,920 Speaker 10: forward as deposits leave. 496 00:27:44,520 --> 00:27:49,120 Speaker 6: Herman hop on into this conversation. Herman again, that guy 497 00:27:49,760 --> 00:27:51,680 Speaker 6: her Hobbins is the conversation talks to us a little 498 00:27:51,720 --> 00:27:53,639 Speaker 6: about what we can actually expect from these earnings. I 499 00:27:53,640 --> 00:27:55,679 Speaker 6: think Thursday is the big day where we're getting the 500 00:27:55,720 --> 00:27:59,760 Speaker 6: majority of the regional banker earnings. What is or is 501 00:27:59,800 --> 00:28:02,080 Speaker 6: there a kind of one bank or two or three 502 00:28:02,160 --> 00:28:04,520 Speaker 6: that you're really paying attention to. Last Friday it was 503 00:28:04,520 --> 00:28:07,679 Speaker 6: all about JP Morgan. Obviously, I think tomorrow it's going 504 00:28:07,720 --> 00:28:09,600 Speaker 6: to be off's a bit all the big three, But 505 00:28:09,960 --> 00:28:12,840 Speaker 6: on the regional basis, what's what's on your radar? Yeah? 506 00:28:12,920 --> 00:28:15,240 Speaker 11: Sure, So Wednesday and Thursdays are the big days for 507 00:28:15,280 --> 00:28:18,400 Speaker 11: the regional bank reporting for the first quarter. We had 508 00:28:18,520 --> 00:28:23,439 Speaker 11: mm T report today, PNC on Friday. The biggest issue 509 00:28:23,440 --> 00:28:25,800 Speaker 11: in the focus is going to be on deposits. As 510 00:28:25,800 --> 00:28:28,840 Speaker 11: Neil mentioned earlier, where are we on deposits? How do 511 00:28:28,960 --> 00:28:32,440 Speaker 11: they stack with the rest of the group. The best 512 00:28:32,480 --> 00:28:36,280 Speaker 11: so far has been JP Morgan and then M and 513 00:28:36,320 --> 00:28:38,920 Speaker 11: T was actually showing steady and stable deposits, which is 514 00:28:38,920 --> 00:28:42,160 Speaker 11: a great sign. We're still waiting on some of the 515 00:28:42,200 --> 00:28:46,000 Speaker 11: others that the numbers look maybe a bit poor on, 516 00:28:46,720 --> 00:28:50,320 Speaker 11: which would be somebody like Western Alliance and banks like 517 00:28:50,440 --> 00:28:54,280 Speaker 11: First Republic. But we're probably hoping to see pretty stable 518 00:28:54,360 --> 00:28:57,760 Speaker 11: the maybe down a little bit for deposits across the group. 519 00:28:58,240 --> 00:29:00,600 Speaker 1: Can you up on Friday some of the big banks 520 00:29:00,760 --> 00:29:03,240 Speaker 1: reported I was not here. I was driving all over 521 00:29:03,240 --> 00:29:06,640 Speaker 1: the central coast of California. I missed it. But it 522 00:29:06,760 --> 00:29:09,040 Speaker 1: was the story there for a lot of these bigger banks. 523 00:29:09,560 --> 00:29:12,120 Speaker 1: And will it continue to be this positive net interest 524 00:29:12,520 --> 00:29:14,760 Speaker 1: margin stories? That one of the key things that you're 525 00:29:14,800 --> 00:29:15,200 Speaker 1: looking at. 526 00:29:15,720 --> 00:29:19,280 Speaker 10: Yeah, and I think the question is still just surrounds deposits, 527 00:29:19,320 --> 00:29:21,600 Speaker 10: and particularly when you're looking at some of the some 528 00:29:21,680 --> 00:29:24,440 Speaker 10: of those larger players, the JP Morgan's Bank of Americas 529 00:29:24,480 --> 00:29:27,520 Speaker 10: of the World, they're the ones who are perhaps you know, 530 00:29:27,720 --> 00:29:30,400 Speaker 10: winning some of that share of deposits. As you see 531 00:29:30,400 --> 00:29:34,040 Speaker 10: things kind of reshuffle between institutions, and so ultimately the 532 00:29:34,120 --> 00:29:36,520 Speaker 10: question is that and obviously as we have you know, 533 00:29:36,840 --> 00:29:39,720 Speaker 10: objectively higher interest rates, now the question is what's going 534 00:29:39,800 --> 00:29:41,960 Speaker 10: to happen with loan growth as you you know, get 535 00:29:41,960 --> 00:29:45,840 Speaker 10: to these elevated levels on short term interest rates, and 536 00:29:45,840 --> 00:29:48,960 Speaker 10: then particularly when you look at investment banking, that continues 537 00:29:49,000 --> 00:29:52,440 Speaker 10: to remain slow, whereas trading was benefited by some of 538 00:29:52,440 --> 00:29:53,480 Speaker 10: that rate volatility. 539 00:29:54,000 --> 00:29:56,280 Speaker 6: Well, Neil a follow upon the loan growth story because 540 00:29:56,280 --> 00:29:59,239 Speaker 6: it feels like there's kind of this cash twenty two 541 00:29:59,320 --> 00:30:01,960 Speaker 6: on the one hand, and it's this big influx of 542 00:30:02,280 --> 00:30:05,360 Speaker 6: deposits that Jamie Diamond, I believe on Friday, Paul, you 543 00:30:05,360 --> 00:30:06,800 Speaker 6: missed this part. Jamie Diamond had. 544 00:30:06,680 --> 00:30:07,280 Speaker 4: A lot to say. 545 00:30:07,360 --> 00:30:10,680 Speaker 6: I'm sure on Friday, but Jamie Dimond said, look, by 546 00:30:10,720 --> 00:30:12,440 Speaker 6: the end of the year, that's going to reverse. This 547 00:30:12,520 --> 00:30:16,240 Speaker 6: is a temporary measure. But then on the other hand, 548 00:30:16,240 --> 00:30:18,480 Speaker 6: you have the loan growth, which is also song. So 549 00:30:18,640 --> 00:30:20,080 Speaker 6: that does that mean by the end of the year 550 00:30:20,200 --> 00:30:23,480 Speaker 6: everything that's being viewed as a major positive for the 551 00:30:23,480 --> 00:30:25,880 Speaker 6: big banks is just gonna fade away? 552 00:30:26,960 --> 00:30:29,760 Speaker 10: Yeah, Well, I think it's it's it's sort of difficult 553 00:30:29,760 --> 00:30:32,080 Speaker 10: to say. I think there's a lot of variables between 554 00:30:32,120 --> 00:30:33,720 Speaker 10: now and the end of the year, and a lot 555 00:30:33,720 --> 00:30:36,040 Speaker 10: of that's going to ultimately play out into what we 556 00:30:36,120 --> 00:30:38,640 Speaker 10: see in terms of loan growth, what the benefit of 557 00:30:38,640 --> 00:30:41,560 Speaker 10: interest rates is. And I even think you know, Herman 558 00:30:41,640 --> 00:30:44,960 Speaker 10: Chan may actually have you know, better insight on that 559 00:30:45,040 --> 00:30:47,080 Speaker 10: as it relates to kind of the loan growth that 560 00:30:47,120 --> 00:30:50,840 Speaker 10: you're seeing, perhaps more so at commercial versus consumer at 561 00:30:50,840 --> 00:30:51,840 Speaker 10: some of his banks. 562 00:30:52,080 --> 00:30:55,920 Speaker 11: Yeah, I would say that commercial lending is still fairly strong. 563 00:30:56,000 --> 00:30:58,240 Speaker 11: You saw some growth from M and C in terms 564 00:30:58,240 --> 00:31:00,440 Speaker 11: of C and I growth, so that's a positive sign. 565 00:31:01,240 --> 00:31:04,000 Speaker 11: We're still waiting on guidance furmenty the calls going on 566 00:31:04,080 --> 00:31:07,000 Speaker 11: right now, but that'll be the big driver a sentiment 567 00:31:07,080 --> 00:31:13,600 Speaker 11: going forward. Overall, it seems like credit availability could could 568 00:31:13,680 --> 00:31:16,600 Speaker 11: weaken a bit given the fact that we're seeing higher 569 00:31:16,640 --> 00:31:20,200 Speaker 11: deposit costs and banks needing to pay up for deposits 570 00:31:20,280 --> 00:31:26,120 Speaker 11: to retain those relationships. That probably could spur some weaker 571 00:31:26,160 --> 00:31:29,840 Speaker 11: demand going forward, and we've seen that across some consumer 572 00:31:30,040 --> 00:31:34,080 Speaker 11: lending types already with auto loans, those rates on the 573 00:31:34,120 --> 00:31:37,760 Speaker 11: auto loans are already driving something to the effect of 574 00:31:37,840 --> 00:31:41,320 Speaker 11: seven percent, which creates some sticker. Stock Shop for a 575 00:31:41,360 --> 00:31:44,640 Speaker 11: lot of the potential buyers of cars these days. So 576 00:31:44,960 --> 00:31:48,520 Speaker 11: that's something that we're looking into going ahead for the 577 00:31:48,560 --> 00:31:49,160 Speaker 11: rest of the year. 578 00:31:49,640 --> 00:31:52,040 Speaker 1: You know, what are the big banks saying about kind 579 00:31:52,040 --> 00:31:54,480 Speaker 1: of the capital markets business? Are they kind of saying, 580 00:31:54,920 --> 00:31:57,320 Speaker 1: you know, don't get your hopes up for twenty twenty three, 581 00:31:57,880 --> 00:31:58,880 Speaker 1: We'll think about twenty four. 582 00:31:59,200 --> 00:32:01,880 Speaker 10: Yeah. I think unfortunately, it's sort of been a kicking 583 00:32:01,920 --> 00:32:04,800 Speaker 10: the can down the road on you know, we expect 584 00:32:04,800 --> 00:32:06,880 Speaker 10: it to continue to get better at some point, but 585 00:32:07,000 --> 00:32:10,040 Speaker 10: when that's some point is you know, we're not too certain, 586 00:32:10,080 --> 00:32:12,560 Speaker 10: and you just look at kind of metrics of volatility, 587 00:32:13,080 --> 00:32:16,840 Speaker 10: where interest rates are, the uncertainty around interest rates the economy, 588 00:32:17,080 --> 00:32:20,040 Speaker 10: it's just challenging for capital raising to happen. It's challenging 589 00:32:20,080 --> 00:32:23,520 Speaker 10: for deals to take place when there's still not clarity 590 00:32:23,560 --> 00:32:27,120 Speaker 10: on ultimately where interest rates are going to be going forward. 591 00:32:27,160 --> 00:32:29,760 Speaker 10: And so I think, you know, twenty twenty four is 592 00:32:30,280 --> 00:32:33,560 Speaker 10: sort of where they're starting to push those you know, 593 00:32:33,600 --> 00:32:36,400 Speaker 10: those guidances of you know, potential for hope. 594 00:32:36,560 --> 00:32:38,760 Speaker 1: All right, Like many people, Neil, I'm I'm a fan 595 00:32:38,840 --> 00:32:41,480 Speaker 1: at Jamie Diamond, but his stock just went up another notch. 596 00:32:41,480 --> 00:32:43,800 Speaker 7: In my mind, telling his managing. 597 00:32:43,400 --> 00:32:45,160 Speaker 4: Directors to be back five days a week. 598 00:32:45,360 --> 00:32:47,760 Speaker 1: Has there been any what's the feedback that you've heard, 599 00:32:47,760 --> 00:32:50,400 Speaker 1: maybe even on the call Jamie Diamond's comments to it. 600 00:32:50,640 --> 00:32:51,840 Speaker 7: Have you heard any feedback there? 601 00:32:51,880 --> 00:32:55,280 Speaker 1: And we'll expect other banks to follow suit because a 602 00:32:55,280 --> 00:32:57,360 Speaker 1: lot of times Jamie kind of leads the pack. 603 00:32:57,520 --> 00:32:59,520 Speaker 10: Yeah. Yeah, he can tend to be a bell weather. 604 00:33:00,440 --> 00:33:03,320 Speaker 10: And I think you know, to that extent, perhaps it's 605 00:33:03,360 --> 00:33:06,080 Speaker 10: it's more focused on that senior talent, and you want 606 00:33:06,120 --> 00:33:09,120 Speaker 10: to have those people in the office, particularly for the 607 00:33:09,120 --> 00:33:12,600 Speaker 10: benefits of those that are junior below them, because ultimately 608 00:33:12,640 --> 00:33:15,320 Speaker 10: that's you know, that's how you're going to foster that culture, 609 00:33:15,360 --> 00:33:19,120 Speaker 10: which we know is incredibly important in investment banking, ultimately 610 00:33:19,200 --> 00:33:22,760 Speaker 10: driving relationships for the business. And so as you ultimately 611 00:33:22,800 --> 00:33:25,360 Speaker 10: see you know, work from home being phased out a 612 00:33:25,360 --> 00:33:27,640 Speaker 10: little bit, it may start at the higher ranks and 613 00:33:27,720 --> 00:33:31,040 Speaker 10: ultimately feed down into the lowers. And of course, you know, 614 00:33:31,080 --> 00:33:33,960 Speaker 10: we'll see if this does bleed into the other banks 615 00:33:33,960 --> 00:33:37,160 Speaker 10: and others, as ultimately that can sort of be a 616 00:33:37,200 --> 00:33:38,560 Speaker 10: competing factor for talent. 617 00:33:39,480 --> 00:33:42,160 Speaker 6: The only reason Paul Swen is a fan of Herman 618 00:33:42,240 --> 00:33:44,480 Speaker 6: Chan the only reason because he comes in five days 619 00:33:44,480 --> 00:33:44,720 Speaker 6: a week. 620 00:33:44,800 --> 00:33:46,560 Speaker 7: Yeah, he brings it. 621 00:33:47,200 --> 00:33:49,040 Speaker 11: The best ability is availability. 622 00:33:49,040 --> 00:33:53,080 Speaker 4: Oh well, the best ability is availability that one. 623 00:33:52,920 --> 00:33:56,760 Speaker 6: Put it on a shirt to it on Paul's forehead. Herman, 624 00:33:57,160 --> 00:33:59,560 Speaker 6: your take, then, I mean, let's just continue with that thing. 625 00:33:59,600 --> 00:34:01,200 Speaker 6: And that's the take from the big banks. Is it 626 00:34:01,280 --> 00:34:03,960 Speaker 6: that important for the regional banks in. 627 00:34:04,000 --> 00:34:07,040 Speaker 11: Terms of folks coming in? I think there's still a 628 00:34:07,120 --> 00:34:10,960 Speaker 11: lot of work from home mentality So well, we haven't 629 00:34:11,040 --> 00:34:15,640 Speaker 11: heard directive from the CEOs on down. So if the 630 00:34:15,719 --> 00:34:19,080 Speaker 11: Jamie Diamond issue of making folks coming in, at least 631 00:34:19,120 --> 00:34:22,000 Speaker 11: from the MD level, you could see some of the 632 00:34:22,040 --> 00:34:24,960 Speaker 11: regionals sort of follow suit, But we haven't heard of 633 00:34:25,000 --> 00:34:29,200 Speaker 11: any of the more mandated coming into the office, at 634 00:34:29,320 --> 00:34:30,000 Speaker 11: least not yet. 635 00:34:30,080 --> 00:34:32,880 Speaker 6: Herman, really quickly, I want to ask you about buybacks specifically. 636 00:34:32,880 --> 00:34:34,040 Speaker 6: I think I asked you this last week. I had 637 00:34:34,040 --> 00:34:37,319 Speaker 6: a fantastic answer. It's worth repeating. When you're looking at 638 00:34:37,360 --> 00:34:39,560 Speaker 6: some of the valuations of these regional stocks, they are 639 00:34:40,280 --> 00:34:42,960 Speaker 6: trading far below their kind of normal or average price 640 00:34:43,000 --> 00:34:45,920 Speaker 6: to book ratios. Isn't that a no brainer for these 641 00:34:45,960 --> 00:34:47,400 Speaker 6: regional banks to buy back their stock. 642 00:34:48,160 --> 00:34:52,480 Speaker 11: It makes it really enticing because our group, the regional 643 00:34:52,480 --> 00:34:55,920 Speaker 11: bank group that I cover, it's training about one times 644 00:34:56,040 --> 00:35:01,239 Speaker 11: tangible book value adjusted for the AOCI, so really low 645 00:35:01,360 --> 00:35:06,399 Speaker 11: levels attractive levels. We're still in a bit of uncertainty though. 646 00:35:06,480 --> 00:35:09,240 Speaker 11: PNC came out on Friday and said they were halting 647 00:35:09,480 --> 00:35:13,560 Speaker 11: buybacks until they get more clarity on maybe uncertainly from 648 00:35:13,600 --> 00:35:16,680 Speaker 11: the market and also from the regulators. So until we 649 00:35:17,080 --> 00:35:22,200 Speaker 11: see some of that clarity uppear, it seems like there 650 00:35:22,239 --> 00:35:26,239 Speaker 11: could be some less activity from a buyback standpoint. There 651 00:35:26,239 --> 00:35:30,080 Speaker 11: are others that have really strong capital ratios that we cover. 652 00:35:31,280 --> 00:35:33,840 Speaker 11: M and T is one. East Wests is another that 653 00:35:33,920 --> 00:35:37,160 Speaker 11: really have strong capital and operating really well that could 654 00:35:37,200 --> 00:35:39,600 Speaker 11: continue to do buybacks. So it'll be a mix, all. 655 00:35:39,600 --> 00:35:41,759 Speaker 1: Right, Gens, thanks so much for joining us. Herman Chan, 656 00:35:41,800 --> 00:35:45,160 Speaker 1: who has saved our bacon many times over the last month, 657 00:35:45,200 --> 00:35:46,960 Speaker 1: helping us get through what has been a stressful time 658 00:35:46,960 --> 00:35:49,480 Speaker 1: for some of these regional banks. Herman Chan, Bloomberg Intelligence 659 00:35:49,520 --> 00:35:52,719 Speaker 1: senior animals covering those regional banks, and Neil SIPs Man, 660 00:35:53,080 --> 00:35:55,440 Speaker 1: what a strong first show on my show, Neil Safe's 661 00:35:55,440 --> 00:35:59,080 Speaker 1: Equity Research Annals Bloomberg Intelligence. We trained him up and 662 00:35:59,160 --> 00:36:01,839 Speaker 1: here he is put out some great research and helping 663 00:36:01,920 --> 00:36:03,880 Speaker 1: us understand what's going on with the banks. 664 00:36:04,640 --> 00:36:07,759 Speaker 5: You're listening to the tape Cat's are live program Bloomberg 665 00:36:07,840 --> 00:36:11,400 Speaker 5: Markets weekdays at ten am Eastern on Bloomberg Radio, the 666 00:36:11,480 --> 00:36:14,680 Speaker 5: tune in app, Bloomberg dot Com, and the Bloomberg Business App. 667 00:36:14,760 --> 00:36:17,560 Speaker 5: You can also listen live on Amazon Alexa from our 668 00:36:17,600 --> 00:36:22,640 Speaker 5: flagship New York station, Just say Alexa play Bloomberg eleven thirty. 669 00:36:23,680 --> 00:36:26,160 Speaker 1: Looking at the Big Take story, you know, we're all 670 00:36:26,239 --> 00:36:28,400 Speaker 1: big fans of the Big Takes story because they are 671 00:36:28,800 --> 00:36:32,760 Speaker 1: really usually usually very very interesting topics, but always deeply, 672 00:36:32,840 --> 00:36:37,960 Speaker 1: deeply reported. In today's is no different, and it goes 673 00:36:38,040 --> 00:36:41,920 Speaker 1: to the headline interest only loans to Hampton's set in 674 00:36:42,080 --> 00:36:45,640 Speaker 1: pale First Republic. That does not sound good there, So 675 00:36:45,880 --> 00:36:50,120 Speaker 1: let's talk to Jenny surname surname Surrain. I'm sorry, Jase Shrain, 676 00:36:50,480 --> 00:36:52,759 Speaker 1: thank you for Bloomberg News. She was one of the 677 00:36:53,040 --> 00:36:57,240 Speaker 1: reporters on this story. And you think about these big Jenny, 678 00:36:57,239 --> 00:36:58,480 Speaker 1: you got to the ham Does not that I go 679 00:36:58,520 --> 00:37:00,600 Speaker 1: there because I'm a Jersey shore guy. You think about 680 00:37:00,600 --> 00:37:03,120 Speaker 1: the Hampton Is to see these big, big homes. 681 00:37:03,239 --> 00:37:04,280 Speaker 7: They're not all cash. 682 00:37:04,360 --> 00:37:07,600 Speaker 1: They're getting up some big mortgages associated with those and 683 00:37:07,920 --> 00:37:11,320 Speaker 1: I would think for a banker that would be good business. 684 00:37:11,680 --> 00:37:13,799 Speaker 1: Talk to us about First Republican and the business they 685 00:37:13,800 --> 00:37:14,920 Speaker 1: were doing out in the Hamptons. 686 00:37:15,239 --> 00:37:17,680 Speaker 12: Yeah, no, I think you're exactly right. You know, for 687 00:37:17,840 --> 00:37:21,759 Speaker 12: years and years, First Republicans really focused on banking more 688 00:37:21,760 --> 00:37:25,000 Speaker 12: of these wealthy consumers. And so in our reporting we 689 00:37:25,160 --> 00:37:27,640 Speaker 12: learned that a big chunk of the mortgage business that 690 00:37:27,680 --> 00:37:30,759 Speaker 12: they did with with wealthy individuals was actually comes in 691 00:37:30,800 --> 00:37:33,279 Speaker 12: the form of interest only mortgages. So that means that 692 00:37:33,320 --> 00:37:34,720 Speaker 12: for the first ten years of that lunch. 693 00:37:34,600 --> 00:37:36,880 Speaker 1: I'm still a thing I thought that was like banned 694 00:37:36,920 --> 00:37:38,360 Speaker 1: after the Great Financial Crisis. 695 00:37:38,400 --> 00:37:41,600 Speaker 12: So it's interesting because they kind of reached this level 696 00:37:41,600 --> 00:37:44,840 Speaker 12: of infamy because bankers were offering them to lower income 697 00:37:44,840 --> 00:37:47,240 Speaker 12: consumers who wouldn't be able to keep up with the payments, 698 00:37:47,239 --> 00:37:49,560 Speaker 12: you know, once that interest only period ended. And so 699 00:37:50,040 --> 00:37:52,279 Speaker 12: this was kind of a new take on maybe an 700 00:37:52,360 --> 00:37:56,000 Speaker 12: old foe, and it was really meant to, yeah, be 701 00:37:56,040 --> 00:37:58,920 Speaker 12: away to get their claws into these wealthy consumers and 702 00:37:59,080 --> 00:38:01,520 Speaker 12: hopefully get more of their banking business generally. So they 703 00:38:01,560 --> 00:38:04,040 Speaker 12: had this large wealth management arm and lots of other 704 00:38:04,080 --> 00:38:05,520 Speaker 12: things that they could offer them, and so This was 705 00:38:05,560 --> 00:38:08,000 Speaker 12: like the sweetheart deal that they could do to just 706 00:38:08,080 --> 00:38:10,400 Speaker 12: sort of sink their claws in early and beg more 707 00:38:10,400 --> 00:38:11,000 Speaker 12: of these folks. 708 00:38:11,160 --> 00:38:14,040 Speaker 6: Also, Jenny welcome back. By the way, she was just 709 00:38:14,080 --> 00:38:18,560 Speaker 6: in London for three months. I think, cool, very exciting stuff. Yeah, 710 00:38:18,600 --> 00:38:22,120 Speaker 6: great pictures on Instagram just saying very well, how was that? 711 00:38:22,160 --> 00:38:23,839 Speaker 12: By the way, it was awesome, It was really good. 712 00:38:23,880 --> 00:38:26,840 Speaker 12: I mean it was interesting because I was there for 713 00:38:26,960 --> 00:38:29,440 Speaker 12: the first three months of the year and so watching 714 00:38:29,520 --> 00:38:32,280 Speaker 12: the US banking crisis and then kind of being involved 715 00:38:32,320 --> 00:38:35,480 Speaker 12: in the European banking crisis with Credit Sweeze. It was 716 00:38:35,480 --> 00:38:37,480 Speaker 12: interesting to kind of have a different, different seat at 717 00:38:37,520 --> 00:38:37,920 Speaker 12: the table. 718 00:38:38,239 --> 00:38:41,200 Speaker 6: Very very cool. So bringing it back stateside though, we 719 00:38:41,200 --> 00:38:44,319 Speaker 6: were talking about First Republic, who fills that slot with 720 00:38:44,320 --> 00:38:46,880 Speaker 6: First Public? Are there other candidates here that could maybe 721 00:38:47,000 --> 00:38:48,239 Speaker 6: take some of that market share? 722 00:38:48,520 --> 00:38:51,839 Speaker 12: Yeah, you know, it's interesting. They're not pulling back as 723 00:38:51,880 --> 00:38:55,080 Speaker 12: far as we know. So these guys did this more 724 00:38:55,080 --> 00:38:57,800 Speaker 12: than anyone else. But other banks do offer these products, 725 00:38:57,840 --> 00:39:00,360 Speaker 12: So that should be one thing we're careful about is that, 726 00:39:00,440 --> 00:39:02,799 Speaker 12: you know, JP Morgan does this. Others do too. It's 727 00:39:02,840 --> 00:39:05,839 Speaker 12: a big business and I think the problem with these 728 00:39:05,840 --> 00:39:08,640 Speaker 12: loans now is that as First Republic looks to get 729 00:39:08,680 --> 00:39:11,080 Speaker 12: a capital in fusion or potentially looks for a buyer 730 00:39:11,200 --> 00:39:13,840 Speaker 12: to kind of help it shore up and get a 731 00:39:13,840 --> 00:39:16,200 Speaker 12: little bit better here. That's why this has become a 732 00:39:16,200 --> 00:39:18,359 Speaker 12: problem because these loans, while they perform great and they 733 00:39:18,360 --> 00:39:20,600 Speaker 12: have all these wealthy customers attached to them, carry a 734 00:39:20,600 --> 00:39:23,120 Speaker 12: lot of interest rate risk, and so as interest rates 735 00:39:23,120 --> 00:39:25,080 Speaker 12: go up, the value of these loans goes down, and 736 00:39:25,120 --> 00:39:26,959 Speaker 12: so for any buyer that would be a problem looking 737 00:39:26,960 --> 00:39:28,439 Speaker 12: to fill that balance sheet hole. 738 00:39:28,680 --> 00:39:32,480 Speaker 1: So is First repubably looking to kind of work its 739 00:39:32,520 --> 00:39:34,399 Speaker 1: way out of this? Is that kind of what they've 740 00:39:34,440 --> 00:39:37,480 Speaker 1: been telling people, because it seems like, I don't know, 741 00:39:37,560 --> 00:39:39,320 Speaker 1: if you're buying a house in Hampton's you're. 742 00:39:39,160 --> 00:39:43,279 Speaker 4: Probably a pretty good credit. Yeah, I wouldn't mind. I 743 00:39:43,320 --> 00:39:44,839 Speaker 4: could take all that risk at a certain price. 744 00:39:44,880 --> 00:39:45,200 Speaker 7: Maybe. 745 00:39:45,280 --> 00:39:47,520 Speaker 12: Well, the problem is that it's just become such a 746 00:39:47,560 --> 00:39:50,400 Speaker 12: big hole. So, you know, we're in the middle of 747 00:39:50,440 --> 00:39:52,279 Speaker 12: regional bank earning season, so you're hearing a lot of 748 00:39:52,280 --> 00:39:55,800 Speaker 12: these guys talk about the unrealized losses on the bonds 749 00:39:55,840 --> 00:39:58,000 Speaker 12: on their balance sheet, which has become a huge problem 750 00:39:58,280 --> 00:40:00,640 Speaker 12: at First Republic. That's a problem too, but it's not 751 00:40:00,760 --> 00:40:04,040 Speaker 12: nearly as big of a problem as the losses unrealized 752 00:40:04,040 --> 00:40:06,520 Speaker 12: to be sure, on these mortgages that they've made, and 753 00:40:06,520 --> 00:40:08,600 Speaker 12: so as they looked for a potential buyers, they look 754 00:40:08,640 --> 00:40:11,200 Speaker 12: at a M and A deal. What we've heard is 755 00:40:11,200 --> 00:40:12,759 Speaker 12: that this is the thing that's causing a lot of 756 00:40:12,760 --> 00:40:14,360 Speaker 12: folks to balk and say, you know, this is just 757 00:40:14,400 --> 00:40:16,880 Speaker 12: too big. You know, even if they paid zero dollars 758 00:40:16,880 --> 00:40:20,120 Speaker 12: a share, they'd still have thirteen billion dollars of a 759 00:40:20,160 --> 00:40:21,879 Speaker 12: hole that they would need to fill, and so it's 760 00:40:22,000 --> 00:40:23,200 Speaker 12: just an untenable deal. 761 00:40:23,640 --> 00:40:26,839 Speaker 6: Are there other regions that are seeing similar things? I mean, 762 00:40:26,880 --> 00:40:31,600 Speaker 6: we associate as New Yorkers, we associate and New Jersey first, yes, 763 00:40:31,960 --> 00:40:36,680 Speaker 6: on associate the Hamptons with that kind of obviously very 764 00:40:36,800 --> 00:40:40,160 Speaker 6: very wealthy share. But are we seeing similar stories coming 765 00:40:40,200 --> 00:40:45,040 Speaker 6: out of I don't know, Miami, San Francisco, other wealthier 766 00:40:45,040 --> 00:40:45,880 Speaker 6: parts of the country. 767 00:40:46,000 --> 00:40:48,760 Speaker 12: Yeah, no, we when we looked at the data underlying 768 00:40:48,800 --> 00:40:52,000 Speaker 12: these mortgages, we've figured out that they actually they had 769 00:40:52,040 --> 00:40:55,160 Speaker 12: a really big presence in the Hamptons and certain wealthy 770 00:40:55,200 --> 00:40:57,200 Speaker 12: neighborhoods in New York. You know, the Upper West Side 771 00:40:57,320 --> 00:41:01,440 Speaker 12: was a popular destination Tribeca another one. But then yeah, 772 00:41:01,440 --> 00:41:04,719 Speaker 12: beyond that, you know, we looked at southern California. There 773 00:41:04,760 --> 00:41:08,040 Speaker 12: was a lot in the Wine country of California, in 774 00:41:08,080 --> 00:41:10,120 Speaker 12: Silicon Valley, you know, where all these tech billionaires are 775 00:41:10,160 --> 00:41:12,600 Speaker 12: being minted. So this was definitely not just a New 776 00:41:12,680 --> 00:41:16,080 Speaker 12: York thing. But yes, obviously for the Bloomberg consumer that 777 00:41:16,200 --> 00:41:16,920 Speaker 12: was a popular one. 778 00:41:17,120 --> 00:41:18,719 Speaker 1: Yeah, because I'm looking at I mean, in this story 779 00:41:18,719 --> 00:41:20,680 Speaker 1: and people you can find the story at Bloomberg dot com, 780 00:41:20,719 --> 00:41:23,800 Speaker 1: slash Big Take or ni Space Big Take, go on 781 00:41:24,120 --> 00:41:25,640 Speaker 1: the terminal and you're going to take a look at 782 00:41:25,680 --> 00:41:27,560 Speaker 1: this because I got some great maps, like kind of 783 00:41:27,600 --> 00:41:32,759 Speaker 1: heat maps of northern California, southern California around La the 784 00:41:32,840 --> 00:41:36,000 Speaker 1: Hampton's Manhattan and you guys have it kind of heat 785 00:41:36,080 --> 00:41:38,600 Speaker 1: map this show kind of where the concentration is and 786 00:41:38,800 --> 00:41:41,319 Speaker 1: of some of these loans. And boy, you look at 787 00:41:41,320 --> 00:41:43,879 Speaker 1: the southern California and the one that shows up the 788 00:41:43,920 --> 00:41:45,919 Speaker 1: brightest on the heat map is Beverly Hills. 789 00:41:46,640 --> 00:41:49,560 Speaker 6: So I wonder who lives there and yeah, just a 790 00:41:49,560 --> 00:41:50,320 Speaker 6: few billionaires. 791 00:41:50,640 --> 00:41:53,399 Speaker 1: So all right, so what's next for this bank here? 792 00:41:53,440 --> 00:41:57,040 Speaker 1: I mean, is there a certain timeframe where you know 793 00:41:57,120 --> 00:42:00,880 Speaker 1: they've got to do something because the markets not really 794 00:42:00,960 --> 00:42:01,640 Speaker 1: buying in on it. 795 00:42:01,800 --> 00:42:03,680 Speaker 12: Yeah, no, I think you know, the big thing that 796 00:42:03,719 --> 00:42:06,399 Speaker 12: we're looking forward to is their earnings next week, because 797 00:42:06,400 --> 00:42:09,120 Speaker 12: that's when we'll really get the first look at just 798 00:42:09,840 --> 00:42:13,080 Speaker 12: how big the deposit outflows have been in the last month. 799 00:42:13,120 --> 00:42:14,759 Speaker 12: You know, you hear it anecdotally, and we talked to 800 00:42:14,760 --> 00:42:17,160 Speaker 12: lots of big customers who've said that they've pulled their funds. 801 00:42:17,320 --> 00:42:18,840 Speaker 12: But at the same time they had, you know, the 802 00:42:18,840 --> 00:42:22,640 Speaker 12: biggest US banks do a deposit infusion at thirty billion 803 00:42:22,680 --> 00:42:25,160 Speaker 12: dollars and so that was really meant to shore them up, 804 00:42:25,200 --> 00:42:27,680 Speaker 12: give them more time to eventually either have a capital 805 00:42:27,680 --> 00:42:31,720 Speaker 12: infusion or find a buyer. So yeah, I'm next Monday, 806 00:42:31,719 --> 00:42:32,960 Speaker 12: I think is. 807 00:42:32,440 --> 00:42:34,360 Speaker 1: Is that's when they read that's when first Republican that 808 00:42:34,400 --> 00:42:35,360 Speaker 1: they dance exactly. 809 00:42:35,480 --> 00:42:37,600 Speaker 12: Yeah, So that's our first that's our next real look 810 00:42:38,000 --> 00:42:39,799 Speaker 12: at under the hood and kind of what's going on 811 00:42:39,840 --> 00:42:42,319 Speaker 12: with these guys, because we really haven't gotten that many 812 00:42:42,360 --> 00:42:44,600 Speaker 12: on the record updates from them in the last month 813 00:42:44,640 --> 00:42:46,120 Speaker 12: or so that this has been a crisis. 814 00:42:46,640 --> 00:42:49,319 Speaker 4: All right, So what other I mean, it seems like 815 00:42:50,080 --> 00:42:52,759 Speaker 4: this and I really want to get your take. 816 00:42:52,840 --> 00:42:56,160 Speaker 1: It seems like the crisis aspect of this turmoil we've 817 00:42:56,160 --> 00:42:58,680 Speaker 1: been dealing with the banking space in the US, it's 818 00:42:58,960 --> 00:43:02,080 Speaker 1: passed or we've been to you know, too early on that. 819 00:43:03,000 --> 00:43:04,880 Speaker 12: I think it's I think it's early. I mean, I 820 00:43:04,920 --> 00:43:07,640 Speaker 12: think we So the biggest thing is that a lot 821 00:43:07,640 --> 00:43:09,560 Speaker 12: of the bank that we're most worried about haven't reported 822 00:43:09,600 --> 00:43:11,960 Speaker 12: earnings yet. And the big fear that I think folks 823 00:43:11,960 --> 00:43:16,040 Speaker 12: have is that they might miff on the disclosure aspect. 824 00:43:16,120 --> 00:43:17,799 Speaker 12: So we've seen that a few times already, where a 825 00:43:17,800 --> 00:43:20,920 Speaker 12: bank is even pre reported and maybe not given investors 826 00:43:20,960 --> 00:43:23,839 Speaker 12: exactly the data or information they wanted, and it's kind 827 00:43:23,840 --> 00:43:27,080 Speaker 12: of caused a whole new calamity. And so I think 828 00:43:27,680 --> 00:43:29,799 Speaker 12: that will be the big key test, especially I think 829 00:43:29,960 --> 00:43:31,879 Speaker 12: Innesday and Thursday. We have a lot coming up next 830 00:43:31,960 --> 00:43:35,400 Speaker 12: Monday obviously with the First Republic, it'll be a big 831 00:43:35,480 --> 00:43:38,000 Speaker 12: key test that really, you know, do they not only 832 00:43:38,040 --> 00:43:40,960 Speaker 12: do they say, you know, numbers that inspire confidence, but 833 00:43:41,000 --> 00:43:42,560 Speaker 12: do they say it in the right way? Do they 834 00:43:42,560 --> 00:43:44,680 Speaker 12: release the right numbers and right And so I think 835 00:43:44,719 --> 00:43:45,520 Speaker 12: that's the big question. 836 00:43:46,000 --> 00:43:47,920 Speaker 1: All right, you were the former editor in chief of 837 00:43:47,960 --> 00:43:49,480 Speaker 1: the Daily tar Herol, So I have to make sure, 838 00:43:49,520 --> 00:43:52,279 Speaker 1: I get my facts straight. Your basketball team started the 839 00:43:52,320 --> 00:43:56,560 Speaker 1: season preseason ranked number one in the country and they 840 00:43:56,640 --> 00:43:59,399 Speaker 1: didn't even go to the tournament. And I don't think 841 00:43:59,480 --> 00:44:03,200 Speaker 1: that's times has that happened? Oh, it had never happened before. Then, 842 00:44:03,640 --> 00:44:05,279 Speaker 1: So are you guys even gonna suit up a team 843 00:44:05,280 --> 00:44:05,600 Speaker 1: next year? 844 00:44:05,640 --> 00:44:07,680 Speaker 4: To face my duties or what we are? 845 00:44:07,719 --> 00:44:09,839 Speaker 12: We're gonna suit up a team. I mean, I hope 846 00:44:09,840 --> 00:44:12,840 Speaker 12: it goes better this year. I honestly think that for 847 00:44:12,960 --> 00:44:19,920 Speaker 12: most our Hills the season before when we will feel 848 00:44:19,960 --> 00:44:22,120 Speaker 12: good for kind of at least a few more So. 849 00:44:22,480 --> 00:44:24,279 Speaker 1: I am a big fan of Hubert Davis. I liked 850 00:44:24,320 --> 00:44:26,279 Speaker 1: him and when he played for Carolina, I liked it. 851 00:44:26,360 --> 00:44:30,399 Speaker 1: When he was with the Knicks. What's the feeling down 852 00:44:30,400 --> 00:44:33,960 Speaker 1: in Chapel Hill about Hubert Davis in terms of boy 853 00:44:34,000 --> 00:44:35,120 Speaker 1: that was kind of embarrassing. 854 00:44:35,239 --> 00:44:37,600 Speaker 12: Yeah, I mean that wasn't his team, so you know 855 00:44:37,680 --> 00:44:41,279 Speaker 12: that was still Roy's team. I think I think we 856 00:44:41,360 --> 00:44:43,200 Speaker 12: give him a few more seasons. I mean, we're not. 857 00:44:43,480 --> 00:44:45,239 Speaker 12: We don't throw babies out with the bathwater down in 858 00:44:45,280 --> 00:44:47,799 Speaker 12: job Well. We give people times to season up. 859 00:44:47,760 --> 00:44:49,719 Speaker 1: All right, So you're gonna they're gonna have a team. 860 00:44:49,760 --> 00:44:52,320 Speaker 1: We can confirm that. Will you go down to any games? 861 00:44:52,960 --> 00:44:54,400 Speaker 12: You know what, I don't have any plans to go 862 00:44:54,400 --> 00:44:55,160 Speaker 12: down to games this year. 863 00:44:55,160 --> 00:44:57,960 Speaker 4: I need to make some he needs to do tickets. 864 00:44:58,680 --> 00:44:59,200 Speaker 7: Just come to me. 865 00:44:59,239 --> 00:45:01,160 Speaker 4: I can set yup, be all set to go. We'll 866 00:45:01,160 --> 00:45:05,080 Speaker 4: put you right there, right in a defectory the Cameron crazy. 867 00:45:05,120 --> 00:45:06,480 Speaker 12: I don't think I would enjoy that. 868 00:45:06,560 --> 00:45:10,239 Speaker 1: And we have another with yeah, did you ever go 869 00:45:10,280 --> 00:45:11,120 Speaker 1: to a basketball game? 870 00:45:11,800 --> 00:45:14,479 Speaker 4: No? Did you go to a football game? 871 00:45:14,800 --> 00:45:14,960 Speaker 8: No? 872 00:45:15,440 --> 00:45:15,720 Speaker 7: Wow? 873 00:45:16,040 --> 00:45:18,080 Speaker 6: I just I'm not a sports coal not even. 874 00:45:20,440 --> 00:45:23,239 Speaker 1: I mean the little VA boys get their suit and 875 00:45:23,280 --> 00:45:25,080 Speaker 1: tis coats and ties on, they look. 876 00:45:24,920 --> 00:45:26,440 Speaker 6: All nice and so embarrassing. 877 00:45:28,480 --> 00:45:29,040 Speaker 12: I'm not. I'm not. 878 00:45:29,080 --> 00:45:31,920 Speaker 6: Look, I'm not a very kind of college spirit, kind 879 00:45:31,920 --> 00:45:32,239 Speaker 6: of gal. 880 00:45:32,520 --> 00:45:34,520 Speaker 4: So I just never never did. 881 00:45:34,719 --> 00:45:35,120 Speaker 7: All right. 882 00:45:35,719 --> 00:45:36,359 Speaker 4: I did go to. 883 00:45:36,320 --> 00:45:39,919 Speaker 6: Plenty of soccer games though, and swim meets, because you know, all. 884 00:45:39,880 --> 00:45:40,439 Speaker 4: Right, good stuff. 885 00:45:40,480 --> 00:45:44,120 Speaker 1: Jenny Serene, financial reporter for Bloomberg News. Uh, and I 886 00:45:44,160 --> 00:45:45,799 Speaker 1: think the feather in her cap is a former editor 887 00:45:45,840 --> 00:45:47,360 Speaker 1: in chief of the Daly Tar Hill. That is a 888 00:45:47,400 --> 00:45:49,800 Speaker 1: big job, not kidding, you know, for those college papers, 889 00:45:49,840 --> 00:45:50,680 Speaker 1: and the Deli Tar. 890 00:45:50,560 --> 00:45:51,640 Speaker 7: Hill is an excellent paper. 891 00:45:51,880 --> 00:45:54,120 Speaker 1: And be editor in chief there is pretty pretty cool too, 892 00:45:54,719 --> 00:45:57,399 Speaker 1: So that's good stuff. Jenny Serene big take story out 893 00:45:57,400 --> 00:46:01,480 Speaker 1: there with her team. Check it out bloomerked Slash Big tape. 894 00:46:01,600 --> 00:46:04,640 Speaker 5: You're listening to the tape. Catch are live program Bloomberg 895 00:46:04,760 --> 00:46:08,360 Speaker 5: Markets weekdays at ten am Eastern on Bloomberg Radio, the 896 00:46:08,400 --> 00:46:11,640 Speaker 5: tune in app, Bloomberg dot Com, and the Bloomberg Business App. 897 00:46:11,680 --> 00:46:14,480 Speaker 5: You can also listen live on Amazon Alexa from our 898 00:46:14,520 --> 00:46:19,560 Speaker 5: flagship New York station, Just say Alexa play Bloomberg eleven thirty. 899 00:46:20,360 --> 00:46:22,400 Speaker 7: All right, here's a headline that got my attention. 900 00:46:23,719 --> 00:46:27,799 Speaker 1: The pig still hasn't fully exited the python. And I think, 901 00:46:27,880 --> 00:46:31,479 Speaker 1: having read it, the pig in this case is the 902 00:46:31,520 --> 00:46:34,600 Speaker 1: pandemic and the you know, the economic hit from the pandemic. 903 00:46:34,680 --> 00:46:36,080 Speaker 7: So I don't know. 904 00:46:36,120 --> 00:46:38,160 Speaker 1: That's my best guest, John Authors, he's the author, He's 905 00:46:38,160 --> 00:46:39,839 Speaker 1: the one to blame for this. He's the senior editor 906 00:46:39,840 --> 00:46:43,319 Speaker 1: at Bloomberg Opinion. One of our favorite folks to chat with. John, 907 00:46:43,360 --> 00:46:45,800 Speaker 1: talk to us about this. The pig still hasn't fully 908 00:46:45,800 --> 00:46:47,879 Speaker 1: exited the python? What are you talking about? 909 00:46:48,840 --> 00:46:49,200 Speaker 3: Okay? 910 00:46:49,960 --> 00:46:51,760 Speaker 13: If you go down to I think it's the last 911 00:46:51,840 --> 00:46:55,560 Speaker 13: paragraph boy of the main peace before you get my 912 00:46:55,719 --> 00:47:01,479 Speaker 13: interesting piece about soccer refereeing in England in the spital Yes, 913 00:47:01,520 --> 00:47:07,920 Speaker 13: it's about It's about the pandemic and obviously it's created 914 00:47:08,680 --> 00:47:14,480 Speaker 13: a very big shock, big reaction, you know, like a 915 00:47:16,000 --> 00:47:18,680 Speaker 13: tsunami or something like that. The idea that that that 916 00:47:18,719 --> 00:47:25,640 Speaker 13: something has been hit very hard and it will create turbulence, 917 00:47:25,680 --> 00:47:28,600 Speaker 13: will create waves for a while afterwards. 918 00:47:29,040 --> 00:47:29,600 Speaker 6: Uh. 919 00:47:29,640 --> 00:47:33,040 Speaker 13: And because this is being reflected through human behavior, it's 920 00:47:33,040 --> 00:47:36,160 Speaker 13: that much harder to predict exactly how those waves are 921 00:47:36,160 --> 00:47:40,000 Speaker 13: going to work. But it's obvious we still haven't got 922 00:47:40,040 --> 00:47:44,440 Speaker 13: through that now. The particular point that I was making 923 00:47:44,520 --> 00:47:50,040 Speaker 13: their concerns and concerns tech where there was a lot 924 00:47:50,080 --> 00:47:55,520 Speaker 13: of spending brought forward during the worst days of the pandemic, 925 00:47:55,520 --> 00:47:59,600 Speaker 13: and that has raised some Varish people to suggest that 926 00:47:59,640 --> 00:48:05,160 Speaker 13: this we like the the Y two K incidents for 927 00:48:05,239 --> 00:48:10,399 Speaker 13: those who who remember it, that that when companies splurged 928 00:48:10,440 --> 00:48:12,920 Speaker 13: on it spending ahead of the millennium because they were 929 00:48:12,960 --> 00:48:15,799 Speaker 13: worried about what would happen when o'clock moved from ninety 930 00:48:15,920 --> 00:48:20,240 Speaker 13: nine to zero zero, and one of the one of 931 00:48:20,000 --> 00:48:23,680 Speaker 13: the consequences of that was that spending was much lower 932 00:48:23,719 --> 00:48:26,280 Speaker 13: on it than it had been expected several years thereafter. 933 00:48:26,440 --> 00:48:28,560 Speaker 13: But that's one of the concerns at the moment that 934 00:48:28,600 --> 00:48:32,839 Speaker 13: we'll find that that peak hasn't excited the python yet. 935 00:48:32,840 --> 00:48:37,680 Speaker 13: That but companies are still in fact able to reduce 936 00:48:37,719 --> 00:48:41,839 Speaker 13: their spending to where they were. Yeah, so that's that's 937 00:48:41,880 --> 00:48:42,880 Speaker 13: that's the python. 938 00:48:44,040 --> 00:48:46,319 Speaker 6: It's quite the image. Also, Paul, did you know that 939 00:48:46,440 --> 00:48:50,240 Speaker 6: when I first I think early early days of meeting 940 00:48:50,360 --> 00:48:55,560 Speaker 6: John Authors speaking of pythons, I was a producer on 941 00:48:55,600 --> 00:48:59,480 Speaker 6: television this is what four years ago maybe, and I 942 00:48:59,480 --> 00:49:02,920 Speaker 6: would reduce John author segments and he this was during 943 00:49:02,960 --> 00:49:05,759 Speaker 6: like Brexit or something, negotiations were happening or something along 944 00:49:05,800 --> 00:49:08,440 Speaker 6: those lines, and he explained Brexit to me through the 945 00:49:08,520 --> 00:49:12,640 Speaker 6: lens of Monty Python. And that is my earliest memory 946 00:49:12,719 --> 00:49:14,359 Speaker 6: of John Author's And then I went to go sit 947 00:49:14,400 --> 00:49:18,600 Speaker 6: by him and learned plenty about Monty Python and market. 948 00:49:19,640 --> 00:49:26,080 Speaker 13: I think it was the Ministry of again both either 949 00:49:26,160 --> 00:49:28,800 Speaker 13: that's all the black Knights who didn't know he was beaten. 950 00:49:30,040 --> 00:49:31,839 Speaker 6: All this rings bells for sure. 951 00:49:33,719 --> 00:49:37,000 Speaker 9: Anyway, John, listen, let's. 952 00:49:37,760 --> 00:49:41,160 Speaker 6: Let's talk about what's going on in France right now. Look, you, 953 00:49:41,520 --> 00:49:43,560 Speaker 6: I think one of the best parts about your columns 954 00:49:43,560 --> 00:49:45,719 Speaker 6: you kind of have a take on everything, and I 955 00:49:45,719 --> 00:49:48,000 Speaker 6: want to get your take on France in particular because 956 00:49:48,040 --> 00:49:51,960 Speaker 6: as I am getting more educated on the matter of 957 00:49:52,440 --> 00:49:55,120 Speaker 6: kind of pension reform and the labor strikes that I've 958 00:49:55,160 --> 00:50:00,239 Speaker 6: been told happen every year in France and around around 959 00:50:00,239 --> 00:50:02,840 Speaker 6: the country, talk to us a little bit about why 960 00:50:02,880 --> 00:50:05,600 Speaker 6: this time the pension reform is such a big deal. 961 00:50:07,160 --> 00:50:12,400 Speaker 13: Okay, the pension reform is such a big deal because, well, 962 00:50:12,440 --> 00:50:14,960 Speaker 13: there are a number of different layers to this. Obviously, 963 00:50:14,960 --> 00:50:19,960 Speaker 13: it's a very important test of Emmanuel MacColl who has 964 00:50:20,280 --> 00:50:28,400 Speaker 13: really been the only modern style technocrat who tries to 965 00:50:28,440 --> 00:50:33,000 Speaker 13: rescue ideology and certainly tries to rescue populism, who has 966 00:50:33,080 --> 00:50:37,000 Speaker 13: managed to stay successful within Europe, who got himself elected 967 00:50:37,040 --> 00:50:40,320 Speaker 13: the second time, and he has now staked an immense 968 00:50:40,440 --> 00:50:44,239 Speaker 13: amount on this. And it's a country where the far right, 969 00:50:44,600 --> 00:50:50,040 Speaker 13: the from Nacionale, is very strong. So that's one leg 970 00:50:50,080 --> 00:50:53,959 Speaker 13: of this, that is the political There's also the fact 971 00:50:54,000 --> 00:50:57,600 Speaker 13: that France has always been I could almost illustrate this 972 00:50:57,840 --> 00:51:01,560 Speaker 13: with you from Monty Pays. The thinking about this that 973 00:51:01,560 --> 00:51:07,320 Speaker 13: that that France has always been very much more prepared 974 00:51:07,480 --> 00:51:12,400 Speaker 13: to take to the streets than other Western European nations 975 00:51:12,480 --> 00:51:16,440 Speaker 13: that it's it's it's it's part of the culture. As 976 00:51:16,440 --> 00:51:18,319 Speaker 13: you were saying that that that that you might get 977 00:51:18,400 --> 00:51:23,480 Speaker 13: labor unrested, but they're also that much more prepared to 978 00:51:23,480 --> 00:51:28,360 Speaker 13: to demonstrate and to fight, and a little bit like 979 00:51:28,480 --> 00:51:32,680 Speaker 13: John Clees playing the extremely rude Frenchman addressing the knights 980 00:51:32,680 --> 00:51:34,759 Speaker 13: in Monty Python and the Holy Grail, which you can 981 00:51:34,840 --> 00:51:38,600 Speaker 13: look up later and then. But I think the most 982 00:51:38,640 --> 00:51:44,360 Speaker 13: important point is France has a very generous national pension scheme, 983 00:51:44,520 --> 00:51:48,880 Speaker 13: but the French are much less bothered about a nanny state, 984 00:51:48,920 --> 00:51:52,720 Speaker 13: about a strong state than most other of the big 985 00:51:52,840 --> 00:51:59,279 Speaker 13: western capitalist nations. And raising the retirement age by two 986 00:51:59,360 --> 00:52:03,680 Speaker 13: years is has really got them. And this is something 987 00:52:03,719 --> 00:52:09,000 Speaker 13: that is likely to be necessary across the world because 988 00:52:09,080 --> 00:52:13,560 Speaker 13: we're all subject to the same demographics. And this is 989 00:52:13,600 --> 00:52:17,320 Speaker 13: an interesting case study in what happens when you really 990 00:52:17,360 --> 00:52:23,040 Speaker 13: try to bite the metal and reduce retirement benefits retirement 991 00:52:23,080 --> 00:52:29,040 Speaker 13: costs in a big developed economy. That is the key 992 00:52:29,719 --> 00:52:33,520 Speaker 13: worrying point to this. That's what is what it could 993 00:52:33,600 --> 00:52:37,759 Speaker 13: portend for the rest that the Macon has said, and 994 00:52:37,920 --> 00:52:39,719 Speaker 13: I guess you have to say, it's the courage to 995 00:52:39,719 --> 00:52:42,040 Speaker 13: do what any good technocraft would say, you need to 996 00:52:42,080 --> 00:52:46,760 Speaker 13: do and try to grasp the issue of reducing pentry costs, 997 00:52:46,840 --> 00:52:48,239 Speaker 13: but let's see if he can do it. 998 00:52:48,440 --> 00:52:51,640 Speaker 6: So the retirement age now from sixty two to sixty four. 999 00:52:51,800 --> 00:52:57,080 Speaker 6: And initially when this was brought to attention, Aminel Macron 1000 00:52:57,280 --> 00:52:59,359 Speaker 6: was going to do this, you know laterally this wasn't 1001 00:52:59,400 --> 00:53:01,879 Speaker 6: going to be put to a vote until, of course, 1002 00:53:01,920 --> 00:53:05,040 Speaker 6: the protests first came on. John talked to us a 1003 00:53:05,080 --> 00:53:07,719 Speaker 6: little bit about any sort of market fall out here, 1004 00:53:07,760 --> 00:53:11,160 Speaker 6: because inevitably, if you've changed the pension reform, that has 1005 00:53:11,200 --> 00:53:14,719 Speaker 6: a very real impact on the French national budget, and 1006 00:53:14,760 --> 00:53:18,160 Speaker 6: therefore you would think on the sovereign debt as well. 1007 00:53:18,200 --> 00:53:20,080 Speaker 6: Are we seeing any kind of market reaction? 1008 00:53:20,200 --> 00:53:27,319 Speaker 13: What is the trade here? Not significantly, I think. I mean, 1009 00:53:27,320 --> 00:53:33,360 Speaker 13: what's easy interesting is that French bond spreads spreads compartments 1010 00:53:33,600 --> 00:53:37,800 Speaker 13: of French bonds have increased a little. But we're talking 1011 00:53:37,840 --> 00:53:42,160 Speaker 13: about compared to the kind of spreads we've seen it 1012 00:53:42,760 --> 00:53:46,600 Speaker 13: on Italian or Spanish debt at different times, countries that 1013 00:53:46,680 --> 00:53:51,440 Speaker 13: really did look as though they could conceivably leave the Eurozone. 1014 00:53:51,600 --> 00:53:55,880 Speaker 13: It's still nothing much too much to consider. You can 1015 00:53:56,000 --> 00:54:01,160 Speaker 13: see that it's a problem that markets are are taking 1016 00:54:01,440 --> 00:54:04,120 Speaker 13: notice of. But I would say that the markets are 1017 00:54:04,120 --> 00:54:09,560 Speaker 13: not at this point a critical player in the French 1018 00:54:09,640 --> 00:54:13,759 Speaker 13: drama in the way that they have been, says most 1019 00:54:14,040 --> 00:54:22,080 Speaker 13: noticeably in Italy. If you have, if you have a 1020 00:54:22,120 --> 00:54:26,480 Speaker 13: clear cut political defeat, which I'm not predicting, but if 1021 00:54:26,520 --> 00:54:31,400 Speaker 13: you did, if you had to, if the pension retirement 1022 00:54:31,440 --> 00:54:35,200 Speaker 13: age stays exactly where it is, a Macron admits he's 1023 00:54:35,239 --> 00:54:39,239 Speaker 13: beaten both on the political and army economics, and that's 1024 00:54:39,280 --> 00:54:44,000 Speaker 13: going to be pretty seriously bad for French debts. Yes, definitely, 1025 00:54:44,480 --> 00:54:45,479 Speaker 13: we haven't got there yet. 1026 00:54:45,800 --> 00:54:47,960 Speaker 1: Hey, John, just you got about it a minute left. 1027 00:54:48,239 --> 00:54:50,520 Speaker 1: I know you're on holiday last week from reading your columns, and. 1028 00:54:50,520 --> 00:54:54,000 Speaker 7: I believe you're in England. Yes, talk to us. 1029 00:54:54,120 --> 00:54:58,080 Speaker 1: What's your takeaway from talking to families and friends and 1030 00:54:58,160 --> 00:55:01,680 Speaker 1: hanging out at the pubs housing average Englishmen feeling? Are 1031 00:55:01,719 --> 00:55:05,880 Speaker 1: Englishman feeling these days? You know, will post Brexit, post COVID, 1032 00:55:05,920 --> 00:55:06,920 Speaker 1: post all that stuff. 1033 00:55:10,280 --> 00:55:15,680 Speaker 13: I mean, I've actually had sort of lots of cheerful 1034 00:55:15,719 --> 00:55:17,920 Speaker 13: conversations with people in the last week, which is nice 1035 00:55:17,960 --> 00:55:24,520 Speaker 13: to know. I think that Brexits as a whole, it's 1036 00:55:24,640 --> 00:55:29,560 Speaker 13: very difficult because obviously I was always against it. I 1037 00:55:29,600 --> 00:55:35,640 Speaker 13: think the country is very slowly but clearly coming around 1038 00:55:35,760 --> 00:55:39,800 Speaker 13: to the view that it was a mistake. And we'll 1039 00:55:39,840 --> 00:55:42,000 Speaker 13: see how long that will happen. And I think you're 1040 00:55:42,040 --> 00:55:46,320 Speaker 13: still talking about decades before there could be any attempt 1041 00:55:46,480 --> 00:55:51,640 Speaker 13: to rejoin. But there is a things have not improved. 1042 00:55:51,719 --> 00:55:57,360 Speaker 13: In fact, they've got worse since since Brexit, and that's 1043 00:55:57,680 --> 00:55:58,840 Speaker 13: becoming more apparent. 1044 00:55:59,280 --> 00:56:02,000 Speaker 1: All right, good stuff, John, Thanks so much for joining us. 1045 00:56:02,000 --> 00:56:05,720 Speaker 1: Always appreciate getting your perspective. John Authores. He's a senior 1046 00:56:05,800 --> 00:56:09,600 Speaker 1: editor at Bloomberg Opinion Scott. He writes a lot of stuff, 1047 00:56:09,640 --> 00:56:11,440 Speaker 1: a lot of really interesting stuff, so you can check 1048 00:56:11,520 --> 00:56:14,759 Speaker 1: that on Bloomberg dot com slash opinion John's work and 1049 00:56:14,760 --> 00:56:17,760 Speaker 1: plus all the other opinion writers as well, and also 1050 00:56:17,920 --> 00:56:21,279 Speaker 1: on OPI n go on the Bloomberg Ternel to get 1051 00:56:21,280 --> 00:56:23,879 Speaker 1: all that great Bloomberg opinion pieces out there. 1052 00:56:25,400 --> 00:56:28,520 Speaker 2: Thanks for listening to the Bloomberg Markets podcasts. You can 1053 00:56:28,560 --> 00:56:32,320 Speaker 2: subscribe and listen to interviews at Apple Podcasts or whatever 1054 00:56:32,400 --> 00:56:33,920 Speaker 2: podcast platform you prefer. 1055 00:56:34,280 --> 00:56:35,080 Speaker 4: I'm Matt Miller. 1056 00:56:35,360 --> 00:56:38,840 Speaker 2: I'm on Twitter at Matt Miller nineteen seventy three. 1057 00:56:38,719 --> 00:56:41,080 Speaker 1: And I'm Faull Sweeney. I'm on Twitter at pt Sweeney 1058 00:56:41,200 --> 00:56:43,880 Speaker 1: Before the podcast. You can always catch us worldwide at 1059 00:56:43,880 --> 00:56:45,640 Speaker 1: Bloomberg Radio.