1 00:00:00,600 --> 00:00:08,600 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:09,960 --> 00:00:13,840 Speaker 2: You're listening to the Bloomberg Intelligence Podcast. Catch us live 3 00:00:13,920 --> 00:00:17,000 Speaker 2: weekdays at ten am Eastern on Affle Cardplay and Android 4 00:00:17,000 --> 00:00:20,120 Speaker 2: Auto with the Bloomberg Business App. Listen on demand wherever 5 00:00:20,160 --> 00:00:24,000 Speaker 2: you get your podcasts, or watch us live on YouTube. 6 00:00:24,920 --> 00:00:27,600 Speaker 3: Alex Delaul Sweeney live here in our Bloomberg Interactive Brokers 7 00:00:27,640 --> 00:00:29,040 Speaker 3: studio in New York City. 8 00:00:29,120 --> 00:00:30,520 Speaker 4: We're also streaming livel on Youtubes. 9 00:00:30,520 --> 00:00:32,920 Speaker 3: Ahead over to YouTube dot com and search Bloomberg Podcast 10 00:00:32,920 --> 00:00:36,000 Speaker 3: and that's where you'll find this. Eli Lilly stock's hitting 11 00:00:36,000 --> 00:00:40,479 Speaker 3: it up four percent today, all time high stocks up 12 00:00:40,520 --> 00:00:43,320 Speaker 3: like fifty eight percent year to date. Patients taking Eli 13 00:00:43,320 --> 00:00:46,760 Speaker 3: Lilli's blockbuster weight loss shot We're ninety four percent less 14 00:00:46,920 --> 00:00:49,440 Speaker 3: likely to develop diabetes in a three year study that 15 00:00:49,479 --> 00:00:53,280 Speaker 3: illuminates the long term health benefits of treating obesity and Alex. 16 00:00:53,320 --> 00:00:55,560 Speaker 3: As you mentioned, these are just like wonder drugs. 17 00:00:55,680 --> 00:00:57,800 Speaker 5: I mean, it definitely feels like they're all magical. 18 00:00:58,080 --> 00:01:00,720 Speaker 3: They're magical thing. Yeah, they cure everything. So I need 19 00:01:00,720 --> 00:01:03,240 Speaker 3: to figure out what's going on here. Sam Fazzelli he 20 00:01:03,320 --> 00:01:05,399 Speaker 3: joined to SEE as the director of Research for Global Industries. 21 00:01:05,480 --> 00:01:07,959 Speaker 3: He's a senior pharmaceutical analyst. That that's his day job 22 00:01:08,000 --> 00:01:10,920 Speaker 3: for Bloomberg Intelligence. And believe it or not, he's actually 23 00:01:11,000 --> 00:01:12,840 Speaker 3: at his desk in the London. 24 00:01:13,040 --> 00:01:15,520 Speaker 5: He was in Bordeaux on Friday, and I was gonna. 25 00:01:15,319 --> 00:01:18,280 Speaker 3: Say I expected him to be in some dialing from 26 00:01:18,360 --> 00:01:21,959 Speaker 3: some exotic locale in Europe somewhere, but he's actually this 27 00:01:22,040 --> 00:01:22,600 Speaker 3: is exotic. 28 00:01:22,720 --> 00:01:24,000 Speaker 4: Look yeah, exactly. 29 00:01:24,480 --> 00:01:26,240 Speaker 5: The ceiling looks pretty cool, all right. 30 00:01:26,080 --> 00:01:28,200 Speaker 3: So Sam, I mean, well, thank you for coming into 31 00:01:28,240 --> 00:01:31,479 Speaker 3: work as opposed to your peers there Bi Sam talk 32 00:01:31,520 --> 00:01:35,400 Speaker 3: to us about Eli Lilly, their drugs here and obese. 33 00:01:35,400 --> 00:01:37,440 Speaker 4: These numbers just jump out at you, don't. 34 00:01:37,240 --> 00:01:39,520 Speaker 6: They They do, they do. 35 00:01:39,680 --> 00:01:42,679 Speaker 7: But let me take you back a little bit where 36 00:01:42,680 --> 00:01:45,360 Speaker 7: we not always told we went to the doctor and 37 00:01:45,400 --> 00:01:48,680 Speaker 7: we started glucose was going up. Not not you guys, 38 00:01:48,680 --> 00:01:53,000 Speaker 7: obviously you're a fascinatingly amazingly healthy and fit, but those 39 00:01:53,040 --> 00:01:55,640 Speaker 7: who weren't and told you need to lose some weight 40 00:01:55,680 --> 00:01:58,520 Speaker 7: to my friend, because you have risk of developing diabetes. 41 00:01:59,040 --> 00:02:02,880 Speaker 7: So where is the if you reduce weight and manage 42 00:02:02,920 --> 00:02:06,800 Speaker 7: the obesity, you lose all these you know, I'll be 43 00:02:06,880 --> 00:02:11,600 Speaker 7: suppeating this thing, sleep APNA, risk of developing diabetes, everything 44 00:02:11,639 --> 00:02:13,760 Speaker 7: that we're talking about here. You eat less, you lose 45 00:02:13,760 --> 00:02:18,720 Speaker 7: weight less risk of developing diabetes, So not exactly a shock. Nevertheless, 46 00:02:18,760 --> 00:02:21,760 Speaker 7: it's great to see that it actually does what it 47 00:02:21,760 --> 00:02:25,600 Speaker 7: says under tin that by reducing weight you do manage 48 00:02:25,600 --> 00:02:28,840 Speaker 7: all these side effects. But before we get too excited, 49 00:02:28,880 --> 00:02:31,760 Speaker 7: I want to highlight one little wrinkle here. It's no 50 00:02:31,800 --> 00:02:34,360 Speaker 7: wrinkle with the data if you read the press release, 51 00:02:34,360 --> 00:02:36,079 Speaker 7: and I've got it right up here on my terminal 52 00:02:36,440 --> 00:02:40,160 Speaker 7: eli Leui coming announced today positive top line results from 53 00:02:40,200 --> 00:02:43,200 Speaker 7: this amount one a three year study, one hundred and 54 00:02:43,240 --> 00:02:48,440 Speaker 7: seventy six week treatment period. Find me somebody who stayed 55 00:02:48,520 --> 00:02:50,840 Speaker 7: in the real world on this drug for one hundred 56 00:02:50,880 --> 00:02:55,160 Speaker 7: and seventy six weeks, so we survey physicians. But if 57 00:02:55,200 --> 00:02:59,079 Speaker 7: we find forty weeks, I'm sure it's going to go up. 58 00:02:59,280 --> 00:03:02,760 Speaker 7: But that very different setting. So how much of a 59 00:03:02,840 --> 00:03:06,080 Speaker 7: real world will this actually translate into in terms of 60 00:03:06,320 --> 00:03:07,480 Speaker 7: preventing diabetes. 61 00:03:07,800 --> 00:03:08,359 Speaker 6: Time will tell. 62 00:03:08,520 --> 00:03:10,440 Speaker 8: So you're not saying that the study was bogus. You're 63 00:03:10,440 --> 00:03:13,480 Speaker 8: saying the study was real. But in reality, people don't 64 00:03:13,680 --> 00:03:16,200 Speaker 8: stay that long on the drug. Therefore the results won't 65 00:03:16,200 --> 00:03:17,800 Speaker 8: be as magical for them. 66 00:03:18,520 --> 00:03:21,360 Speaker 7: Right in clinical trials, you get the best possible data 67 00:03:21,360 --> 00:03:23,480 Speaker 7: basically because it's highly controlled. 68 00:03:23,520 --> 00:03:26,359 Speaker 6: People are followed, you make sure that they stay on. 69 00:03:27,040 --> 00:03:30,000 Speaker 7: There would probably have been people who have dropped off here, 70 00:03:30,040 --> 00:03:35,200 Speaker 7: so maybe the actual average treatment period wasn't exactly one 71 00:03:35,280 --> 00:03:38,240 Speaker 7: hundred and seventy six weeks for everybody, because people do 72 00:03:38,360 --> 00:03:41,240 Speaker 7: drop off. And I'm assuming in this trial the data 73 00:03:41,280 --> 00:03:43,400 Speaker 7: they're reporting to us is what's called intent to treat, 74 00:03:44,000 --> 00:03:44,320 Speaker 7: i e. 75 00:03:44,760 --> 00:03:46,240 Speaker 6: You've intended to treat that patience. 76 00:03:46,280 --> 00:03:49,200 Speaker 7: Whatever happens to them, you still count them, even if 77 00:03:49,240 --> 00:03:51,440 Speaker 7: they've fallen off the drug. Nevertheless, we need to see 78 00:03:51,480 --> 00:03:54,160 Speaker 7: the detail. But in a trial setting things always look 79 00:03:54,200 --> 00:03:57,320 Speaker 7: better than in real world. So here we have to remember. 80 00:03:57,760 --> 00:04:00,920 Speaker 7: Average stay time according to our is that Mike show 81 00:04:01,000 --> 00:04:04,600 Speaker 7: My colleague runs every six months. It's about forty weeks, 82 00:04:04,640 --> 00:04:07,560 Speaker 7: similar to what we get for we go VI and people, 83 00:04:07,640 --> 00:04:09,240 Speaker 7: and even the press release they say as soon as 84 00:04:09,280 --> 00:04:11,520 Speaker 7: they came off, weight went back up and the risks 85 00:04:11,520 --> 00:04:14,480 Speaker 7: started going up again of developing diabetes. So this is 86 00:04:14,520 --> 00:04:16,520 Speaker 7: not something that you've cleaned it all up. I can 87 00:04:16,640 --> 00:04:18,920 Speaker 7: stop now at one hundred and seventy six and I'm done. 88 00:04:19,040 --> 00:04:20,760 Speaker 7: It's the same story over again. 89 00:04:20,960 --> 00:04:21,680 Speaker 4: Right, exactly. 90 00:04:22,080 --> 00:04:24,640 Speaker 3: So I mean, so look at the stock for Eli 91 00:04:24,680 --> 00:04:26,720 Speaker 3: literly Sam, I say, it's up sixty four percent year 92 00:04:26,720 --> 00:04:27,920 Speaker 3: to date, all time high. 93 00:04:28,080 --> 00:04:32,440 Speaker 4: How much of this stock performance is these glps? 94 00:04:33,880 --> 00:04:37,839 Speaker 7: Oh gosh, if you know, if you look at the 95 00:04:37,920 --> 00:04:40,640 Speaker 7: chart and look at the flow of information and news 96 00:04:40,720 --> 00:04:44,160 Speaker 7: and the upgrades et cetera that are coming to quarterlies, 97 00:04:44,240 --> 00:04:47,479 Speaker 7: every quarterly result et cetera, to sales, I would say 98 00:04:47,520 --> 00:04:50,520 Speaker 7: a meaningful chunk of this. I can't quantify it exactly 99 00:04:50,520 --> 00:04:52,920 Speaker 7: because this is a company that's got other stuff going 100 00:04:52,960 --> 00:04:58,880 Speaker 7: on Alzheimer's disease, oncology, you know, the skin diseases, et cetera. 101 00:04:58,920 --> 00:05:02,240 Speaker 7: So this is not a one trick pony, but a 102 00:05:02,320 --> 00:05:04,640 Speaker 7: large amount of this story. And you can tell by 103 00:05:04,640 --> 00:05:07,960 Speaker 7: when somebody reports a positive result in a competitor setting. 104 00:05:07,720 --> 00:05:09,279 Speaker 6: These stocks sell off four or five percent. 105 00:05:09,880 --> 00:05:12,400 Speaker 7: Right, You remember the days with rash only three or 106 00:05:12,440 --> 00:05:15,240 Speaker 7: four weeks ago, I think, right, And let's not forget 107 00:05:15,760 --> 00:05:18,680 Speaker 7: in a few weeks time, we have the European Association 108 00:05:18,760 --> 00:05:21,800 Speaker 7: for the Study of Diabetes Russia's data is coming out. 109 00:05:22,120 --> 00:05:23,960 Speaker 7: Somebody is going to be up three or four percent 110 00:05:24,000 --> 00:05:26,040 Speaker 7: that day, and somebody's going to be down three or 111 00:05:26,040 --> 00:05:27,240 Speaker 7: four percent who it is. 112 00:05:27,400 --> 00:05:28,640 Speaker 6: We'll see what the data says. 113 00:05:29,200 --> 00:05:32,200 Speaker 8: So the point that you made that if people come 114 00:05:32,240 --> 00:05:34,040 Speaker 8: off it and they gain the weight back, so in 115 00:05:34,040 --> 00:05:37,080 Speaker 8: that sense, it's not like everlastingly magical. Will there be 116 00:05:37,160 --> 00:05:39,880 Speaker 8: iterations though where that won't be the case. 117 00:05:41,560 --> 00:05:43,320 Speaker 6: There's two ways of doing dealing with this. 118 00:05:43,440 --> 00:05:45,600 Speaker 7: So you go on the drug, you come off the drug, 119 00:05:45,680 --> 00:05:47,359 Speaker 7: you go back on the drug, you come off the drug, 120 00:05:47,360 --> 00:05:50,240 Speaker 7: and you just do your cycling every few years after 121 00:05:50,320 --> 00:05:52,640 Speaker 7: you've got to a point where you think, I don't 122 00:05:52,680 --> 00:05:55,080 Speaker 7: know why people come off the drug necessarily on an 123 00:05:55,080 --> 00:05:57,440 Speaker 7: average is it side effect tends to get a lot 124 00:05:57,480 --> 00:05:59,560 Speaker 7: better over time, and. 125 00:06:00,000 --> 00:06:00,679 Speaker 6: Maybe it's cost. 126 00:06:01,520 --> 00:06:03,680 Speaker 7: Maybe it's because they're fed up begin taking an injection 127 00:06:03,760 --> 00:06:05,960 Speaker 7: every week. So if you put all those things together, 128 00:06:06,000 --> 00:06:09,480 Speaker 7: as they get cheaper and injections become once a month, 129 00:06:09,520 --> 00:06:12,599 Speaker 7: maybe or they become oral for the maintenance phase of 130 00:06:12,600 --> 00:06:15,760 Speaker 7: the dose, and that oral doesn't make you feel ill, 131 00:06:15,960 --> 00:06:18,839 Speaker 7: feel ill every time you take it in terms of 132 00:06:18,839 --> 00:06:22,880 Speaker 7: gastric intestinal maybe that's the future. Maybe there are other modalities. 133 00:06:23,120 --> 00:06:27,880 Speaker 7: Amlin is one that Nova Notice and Zealand Farm are 134 00:06:27,920 --> 00:06:31,479 Speaker 7: developing as a target that seems to have less side 135 00:06:31,480 --> 00:06:36,920 Speaker 7: effect issues. Maybe you can maintain your weight loss by 136 00:06:36,920 --> 00:06:39,440 Speaker 7: those drugs which don't have the same side effect issue. 137 00:06:39,640 --> 00:06:42,880 Speaker 7: So that has to be the way that you see it. 138 00:06:42,880 --> 00:06:45,560 Speaker 7: But nobody ever complies with the drug forever. 139 00:06:46,160 --> 00:06:50,200 Speaker 3: Right When do the pharmaceutical companies SAM have a timetable 140 00:06:50,240 --> 00:06:53,080 Speaker 3: for when they will have a pill format as opposed 141 00:06:53,080 --> 00:06:53,680 Speaker 3: to an injection. 142 00:06:54,920 --> 00:06:57,240 Speaker 7: Yeah, so they're all trying to develop them. There are 143 00:06:57,240 --> 00:06:59,279 Speaker 7: a couple of companies Russia and Astros and a Covich. 144 00:06:59,279 --> 00:07:03,000 Speaker 7: I've got what we would call traditional potentially small molecules 145 00:07:03,040 --> 00:07:05,240 Speaker 7: that comes in a pill, so it's not the same 146 00:07:05,880 --> 00:07:10,160 Speaker 7: biologic that you're currently seeing. The folks who are developing 147 00:07:10,280 --> 00:07:14,360 Speaker 7: these same glpe GPS, et cetera. Are also trying to 148 00:07:14,440 --> 00:07:16,720 Speaker 7: formulate them so that they can be taken orally. The 149 00:07:16,800 --> 00:07:19,800 Speaker 7: trick there is if it starts releasing in the stomach, 150 00:07:19,840 --> 00:07:21,520 Speaker 7: you need to take them on an empty stomach so 151 00:07:21,520 --> 00:07:22,400 Speaker 7: that you get absorption. 152 00:07:22,520 --> 00:07:24,640 Speaker 6: If you take them on a full stomach, then they 153 00:07:24,680 --> 00:07:25,239 Speaker 6: have a problem. 154 00:07:25,520 --> 00:07:27,360 Speaker 7: So that becomes a bit of a headache for somebody 155 00:07:27,360 --> 00:07:30,160 Speaker 7: who gets up in the morning decides to eat or 156 00:07:30,200 --> 00:07:32,840 Speaker 7: not eat, and then they also get side effects. So 157 00:07:33,080 --> 00:07:36,560 Speaker 7: I would say three or four years there is already 158 00:07:36,600 --> 00:07:40,280 Speaker 7: a diabetes version, Robeltsi's on the market as an oral. 159 00:07:40,680 --> 00:07:41,960 Speaker 6: But let's say three or four years. 160 00:07:42,800 --> 00:07:45,640 Speaker 5: What about heart disease? Does it actually cure heart or 161 00:07:45,720 --> 00:07:47,760 Speaker 5: reduced death? I should say, and heart disease? 162 00:07:48,440 --> 00:07:50,040 Speaker 6: Yeah, yeah, we know that already. We do we do, 163 00:07:50,080 --> 00:07:50,760 Speaker 6: we do, we do that. 164 00:07:50,840 --> 00:07:54,240 Speaker 7: We know that already from the cardiovascular outcomes trials, the 165 00:07:54,280 --> 00:07:58,240 Speaker 7: sea VOTs that they've done, at least for Novo, I'd 166 00:07:58,240 --> 00:08:01,240 Speaker 7: be very shocked if, if, if Lily doesn't get the 167 00:08:01,240 --> 00:08:01,760 Speaker 7: same result. 168 00:08:02,680 --> 00:08:05,640 Speaker 3: So for those on YouTube, there is literally no one. 169 00:08:05,960 --> 00:08:07,760 Speaker 5: I tak two people, two people. 170 00:08:07,480 --> 00:08:11,360 Speaker 6: In Sam's guys. It's it's five, it's three thirty here, 171 00:08:11,400 --> 00:08:14,000 Speaker 6: it's tea time. We're in England. It's they're all up 172 00:08:14,000 --> 00:08:15,440 Speaker 6: there having their tea. 173 00:08:15,760 --> 00:08:18,480 Speaker 5: Tree thirty in the afternoon. Man pauls on the beach 174 00:08:18,480 --> 00:08:21,960 Speaker 5: at that. Yeah, you're on the beach at b there 175 00:08:22,000 --> 00:08:22,280 Speaker 5: you go. 176 00:08:22,800 --> 00:08:24,840 Speaker 6: All right, Hey, Sam, I turned my camera that way. 177 00:08:24,840 --> 00:08:25,680 Speaker 6: You see a lot more people. 178 00:08:25,720 --> 00:08:28,280 Speaker 4: Okay, give me, we got like thirty seconds left here. 179 00:08:28,800 --> 00:08:31,360 Speaker 3: What what's the exciting thing that you and your team 180 00:08:31,360 --> 00:08:33,320 Speaker 3: are working on in terms of, you know what some 181 00:08:33,360 --> 00:08:35,760 Speaker 3: of these treatments are out there that people need to 182 00:08:35,760 --> 00:08:36,600 Speaker 3: be paying attention to. 183 00:08:37,600 --> 00:08:40,480 Speaker 6: Yeah in general, I mean or we see the diabetes general. 184 00:08:40,520 --> 00:08:43,200 Speaker 7: Okay, So we've got three three conferences coming up that 185 00:08:43,240 --> 00:08:45,880 Speaker 7: we're all excited to buy. And as I said, the 186 00:08:46,120 --> 00:08:49,280 Speaker 7: European Diabetes Conference. There RASH will get the data and 187 00:08:49,280 --> 00:08:51,440 Speaker 7: we'll get some cuts of other data that would be 188 00:08:51,440 --> 00:08:55,760 Speaker 7: an interesting one to look at. For ASMO European Oncology Conference, 189 00:08:56,240 --> 00:08:59,160 Speaker 7: new data coming out, some press releases today for potentially 190 00:08:59,200 --> 00:09:02,920 Speaker 7: surprising data. And then the World Lung Conference where we 191 00:09:03,000 --> 00:09:06,079 Speaker 7: have some new modalities being presented. All of them will 192 00:09:06,120 --> 00:09:08,560 Speaker 7: have something funky going on. And for the cancer ones, 193 00:09:08,600 --> 00:09:12,600 Speaker 7: we have a webinar coming up hopefully for our clients. 194 00:09:12,720 --> 00:09:14,280 Speaker 4: Very good. Sam Fazzelli, thank you so much. 195 00:09:14,320 --> 00:09:17,520 Speaker 3: As always, director of Research for Global Industries. I'm not 196 00:09:17,520 --> 00:09:19,160 Speaker 3: sure what that means. You should just be head of 197 00:09:19,160 --> 00:09:20,960 Speaker 3: European Research when I was part of this thing, but 198 00:09:20,960 --> 00:09:24,440 Speaker 3: they've changed it all up here. Most importantly, he's one 199 00:09:24,480 --> 00:09:27,640 Speaker 3: of the top pharmaceutical and biotech analysts a city of London, 200 00:09:28,440 --> 00:09:31,120 Speaker 3: and we got him at Bloomberg Intelligence and Bordeaux, France 201 00:09:31,200 --> 00:09:34,120 Speaker 3: and Bordeaux friends exactly. I mean, you know again, I'm 202 00:09:34,160 --> 00:09:36,319 Speaker 3: waiting for the invite for us to go over there, 203 00:09:36,360 --> 00:09:36,800 Speaker 3: and I. 204 00:09:36,720 --> 00:09:37,280 Speaker 5: Got a picture. 205 00:09:37,760 --> 00:09:38,280 Speaker 4: You got pictures? 206 00:09:38,320 --> 00:09:40,560 Speaker 8: Yeah, I got a picture from Friday. Okay, it's an 207 00:09:40,559 --> 00:09:41,839 Speaker 8: old pick, but still it was something. 208 00:09:42,080 --> 00:09:44,120 Speaker 4: Yeah, he's got like a horse farm there or something. 209 00:09:44,440 --> 00:09:46,440 Speaker 5: I don't know whatever. Sam's just really cool, Okay, and 210 00:09:46,480 --> 00:09:47,439 Speaker 5: we just totally love him. 211 00:09:48,880 --> 00:09:52,760 Speaker 2: You're listening to the Bloomberg Intelligence Podcast. Catch us live 212 00:09:52,840 --> 00:09:55,920 Speaker 2: weekdays at ten am Eastern on Apple card Play and 213 00:09:55,920 --> 00:09:59,160 Speaker 2: Android Auto with the Bloomberg Business. You can also listen 214 00:09:59,280 --> 00:10:02,400 Speaker 2: live on was on Alexa from our flagship New York station, 215 00:10:02,760 --> 00:10:05,120 Speaker 2: Just say Alexa playing Bloomberg eleven. 216 00:10:06,640 --> 00:10:07,880 Speaker 4: Let's go to Tesla. 217 00:10:08,360 --> 00:10:11,079 Speaker 3: The stock's pretty much unchanged today. It's down about ten 218 00:10:11,120 --> 00:10:14,120 Speaker 3: percent year to date. It's flat over trailing twelve months. 219 00:10:14,920 --> 00:10:17,880 Speaker 3: Looks like the EU is looking to slap some terraffs 220 00:10:18,240 --> 00:10:20,880 Speaker 3: on some of these Tesla vehicles that are coming that 221 00:10:20,880 --> 00:10:22,479 Speaker 3: are made in China. 222 00:10:22,840 --> 00:10:24,640 Speaker 4: Is this a big deal? The market doesn't seem to 223 00:10:24,640 --> 00:10:26,199 Speaker 4: think so. The stock's not doing a whole lot. 224 00:10:26,200 --> 00:10:26,360 Speaker 6: Here. 225 00:10:26,360 --> 00:10:29,559 Speaker 3: Craig Trudell joins US Global Autos editor for Bloomberg News, 226 00:10:29,640 --> 00:10:31,760 Speaker 3: joining us from London via zoom. 227 00:10:31,880 --> 00:10:34,160 Speaker 4: Craig, what's the latest coming out of the EU. 228 00:10:34,200 --> 00:10:34,320 Speaker 6: Here? 229 00:10:34,360 --> 00:10:36,400 Speaker 4: As it relates to Tesla. 230 00:10:36,520 --> 00:10:39,640 Speaker 9: Yeah, this is a case of Tesla having a bit 231 00:10:39,679 --> 00:10:44,320 Speaker 9: of a special situation where other manufacturers are subject to 232 00:10:44,520 --> 00:10:48,719 Speaker 9: terraffs on the basis and part of whether or not 233 00:10:48,800 --> 00:10:51,720 Speaker 9: they cooperated with the EU's investigation of just how much 234 00:10:51,760 --> 00:10:56,400 Speaker 9: they were subsidized by the Chinese government. And what the 235 00:10:56,440 --> 00:10:59,559 Speaker 9: EU did here was they sampled a few companies and 236 00:11:00,040 --> 00:11:02,000 Speaker 9: sort of, you know, took a specific look at a 237 00:11:02,000 --> 00:11:05,560 Speaker 9: few manufacturers and made decisions based on what they found 238 00:11:05,679 --> 00:11:08,960 Speaker 9: and on whether or not those companies complied with those investigations. 239 00:11:09,480 --> 00:11:12,840 Speaker 9: And you know, some separate rates were going to be 240 00:11:12,920 --> 00:11:17,120 Speaker 9: applied to companies that were not sampled. What Tesla did 241 00:11:17,320 --> 00:11:21,280 Speaker 9: was go to Brussels and say, look, we don't think 242 00:11:21,320 --> 00:11:23,480 Speaker 9: that we were subsidized as much as some of the 243 00:11:23,480 --> 00:11:27,240 Speaker 9: other guys, so subject us to a lower duty rate. 244 00:11:27,280 --> 00:11:29,600 Speaker 9: And that's what happened here. So they're subject to a 245 00:11:29,679 --> 00:11:34,120 Speaker 9: nine percent tariff byd on the other hand, an additional 246 00:11:34,200 --> 00:11:37,360 Speaker 9: seventeen percent. All of these rates are on top of 247 00:11:37,400 --> 00:11:40,920 Speaker 9: the existing ten percent that cars coming in from China 248 00:11:40,960 --> 00:11:44,320 Speaker 9: face when they are shipped into the EU. And so 249 00:11:44,600 --> 00:11:46,880 Speaker 9: I guess, you know, if I'm an investor, I sort 250 00:11:46,920 --> 00:11:50,320 Speaker 9: of knew that this was coming, had a sense that Tesla, 251 00:11:50,520 --> 00:11:54,200 Speaker 9: you know, there was a potential for you know, a 252 00:11:54,240 --> 00:11:57,120 Speaker 9: slightly more lenient treatment. But in the end, am I 253 00:11:57,160 --> 00:12:01,560 Speaker 9: happy about Model three is being subject to nineteen duties 254 00:12:02,000 --> 00:12:03,160 Speaker 9: you know coming in from Shanghai? 255 00:12:03,240 --> 00:12:03,760 Speaker 6: Probably not. 256 00:12:04,920 --> 00:12:07,800 Speaker 8: Does this mean that Elon Musk will want to manufacture 257 00:12:07,920 --> 00:12:10,840 Speaker 8: more Tesla's in Germany then? Or is he just going 258 00:12:10,880 --> 00:12:11,480 Speaker 8: to cut bait? 259 00:12:12,840 --> 00:12:15,440 Speaker 9: I think it's a really interesting question. I mean, the 260 00:12:15,440 --> 00:12:18,760 Speaker 9: model why is far and away, you know, the model 261 00:12:19,040 --> 00:12:23,400 Speaker 9: for Tesla globally, and I think increasingly so. Even as 262 00:12:23,480 --> 00:12:25,640 Speaker 9: as the company has you know, given a little bit 263 00:12:25,640 --> 00:12:29,080 Speaker 9: of a facelift to the Model three, the why is 264 00:12:29,120 --> 00:12:31,480 Speaker 9: really you know, the volume play for them, and they 265 00:12:31,520 --> 00:12:35,080 Speaker 9: make those in Germany. It wouldn't be a cinch to 266 00:12:35,200 --> 00:12:38,120 Speaker 9: add Model three to the to the plant in Germany. 267 00:12:38,160 --> 00:12:40,480 Speaker 9: But you know, does it does it make a lot 268 00:12:40,520 --> 00:12:44,400 Speaker 9: more sense to build that vehicle there as opposed to 269 00:12:44,400 --> 00:12:47,760 Speaker 9: shipping it in from China. It may, you know, be 270 00:12:47,880 --> 00:12:50,880 Speaker 9: in their best interest to do so. The nineteen percent 271 00:12:51,520 --> 00:12:55,160 Speaker 9: duty is substantial enough to where it certainly has to 272 00:12:55,200 --> 00:12:58,320 Speaker 9: make the math much more interesting in terms of whether 273 00:12:58,400 --> 00:12:59,960 Speaker 9: or not they decide to pull that trigger. 274 00:13:01,000 --> 00:13:04,400 Speaker 3: So from the EU's perspective here, is this a Tesla 275 00:13:04,559 --> 00:13:07,480 Speaker 3: issue or is this just a China issue because I 276 00:13:07,520 --> 00:13:10,600 Speaker 3: know they've got tarifs on other Chinese manufacturers as well. 277 00:13:11,720 --> 00:13:11,960 Speaker 6: Yeah. 278 00:13:12,240 --> 00:13:14,800 Speaker 9: I think the reason that that you know, Tesla is 279 00:13:14,840 --> 00:13:16,760 Speaker 9: sort of being led with today and how this is 280 00:13:16,800 --> 00:13:20,000 Speaker 9: getting covered is is Tesla, you know, was was sort 281 00:13:20,040 --> 00:13:23,840 Speaker 9: of separate from everybody else looking to be assessed on 282 00:13:23,880 --> 00:13:24,280 Speaker 9: its own. 283 00:13:24,800 --> 00:13:25,000 Speaker 6: Uh. 284 00:13:25,240 --> 00:13:28,880 Speaker 9: Whereas all the other manufacturers, uh, you know, the duty 285 00:13:28,960 --> 00:13:31,720 Speaker 9: rates were known, Tesla was was still a little bit 286 00:13:31,720 --> 00:13:34,000 Speaker 9: of a mystery. So this is you know, sort of 287 00:13:34,080 --> 00:13:36,640 Speaker 9: one one more sort of checked box in terms of, 288 00:13:36,679 --> 00:13:39,040 Speaker 9: you know, what the particulars are going to be for 289 00:13:39,200 --> 00:13:41,640 Speaker 9: these duties that go into effect later this year. And 290 00:13:41,840 --> 00:13:43,560 Speaker 9: you know, I think this is very sort of par 291 00:13:43,679 --> 00:13:46,199 Speaker 9: for the course for anything that gets you know, decided 292 00:13:46,200 --> 00:13:49,360 Speaker 9: by the European Commission. Uh, it gets decided over and 293 00:13:49,400 --> 00:13:51,640 Speaker 9: over and over again. And so this is very much 294 00:13:52,080 --> 00:13:55,520 Speaker 9: a broader China story. Uh. And and not Tesla specific. 295 00:13:55,880 --> 00:13:58,839 Speaker 8: Did Tesla evs that are manufactured in China even make 296 00:13:58,880 --> 00:14:01,080 Speaker 8: it into the EU and that point into the US 297 00:14:01,200 --> 00:14:01,360 Speaker 8: or no? 298 00:14:02,760 --> 00:14:06,520 Speaker 9: Yeah, the model all the Model three's that that are 299 00:14:06,559 --> 00:14:09,199 Speaker 9: sold in Europe are coming from Shanghai at the moment, 300 00:14:09,280 --> 00:14:12,240 Speaker 9: and uh, you know, so whether or not the company 301 00:14:12,280 --> 00:14:16,920 Speaker 9: maybe uh perhaps they would potentially look at, you know, 302 00:14:17,000 --> 00:14:19,600 Speaker 9: exporting from the US. I don't think we have a 303 00:14:19,640 --> 00:14:22,760 Speaker 9: good enough sense of, you know, the particulars of their 304 00:14:22,800 --> 00:14:25,440 Speaker 9: cost base to really sort of you know, be able 305 00:14:25,480 --> 00:14:27,760 Speaker 9: to say what makes the most sense for them, uh, 306 00:14:28,000 --> 00:14:30,920 Speaker 9: you know, sort of immediately as a result of this 307 00:14:31,000 --> 00:14:33,480 Speaker 9: change in tariffs that will go into place. But it 308 00:14:34,000 --> 00:14:37,120 Speaker 9: has been interesting that we have seen the company, even 309 00:14:37,200 --> 00:14:40,840 Speaker 9: before these tariffs actually take effect, bump up their prices 310 00:14:40,840 --> 00:14:43,200 Speaker 9: in Europe a little bit, and you've maybe seen that 311 00:14:43,320 --> 00:14:46,560 Speaker 9: result in in some some challenges for them sales wise, 312 00:14:46,600 --> 00:14:50,000 Speaker 9: where they've not had a very good start to the year, 313 00:14:50,040 --> 00:14:53,280 Speaker 9: and that's even carried in into the second half where 314 00:14:53,360 --> 00:14:56,160 Speaker 9: you know, the initial sales results that we've seen for 315 00:14:56,240 --> 00:14:59,280 Speaker 9: Tesla have not been particularly good. I think the fact 316 00:14:59,280 --> 00:15:02,280 Speaker 9: that they've not and able to continue to bring prices 317 00:15:02,320 --> 00:15:05,960 Speaker 9: down and have sort of you know, been unsure whether 318 00:15:06,080 --> 00:15:08,680 Speaker 9: or not all of the model threes that they're they're 319 00:15:08,760 --> 00:15:13,280 Speaker 9: shipping into into the EU from China maybe subject to 320 00:15:13,320 --> 00:15:17,600 Speaker 9: these tariffs. It has been absolutely a headwind. 321 00:15:17,200 --> 00:15:19,400 Speaker 4: For them all right, Greig, thanks so much for joining us. 322 00:15:19,440 --> 00:15:20,040 Speaker 4: Really appreciate it. 323 00:15:20,080 --> 00:15:22,960 Speaker 3: Craig Trudell, a Global autos editor for Bloomberg News, joining 324 00:15:23,040 --> 00:15:26,040 Speaker 3: us from London Q headquarters. 325 00:15:26,080 --> 00:15:29,880 Speaker 4: There in London, you're listening. 326 00:15:29,480 --> 00:15:33,440 Speaker 2: To the Bloomberg Intelligence Podcast. Catch us live weekdays at 327 00:15:33,440 --> 00:15:36,280 Speaker 2: ten am Eastern on Focarplay and then brout Auto with 328 00:15:36,320 --> 00:15:39,360 Speaker 2: the Bloomberg Business app. Listen on demand wherever you get 329 00:15:39,400 --> 00:15:42,880 Speaker 2: your podcasts, or watch us live on YouTube. 330 00:15:44,160 --> 00:15:47,480 Speaker 8: Well, Alex you alongside Paul Sweeney, is a Bloomberg Intelligence Radio. 331 00:15:47,480 --> 00:15:50,320 Speaker 8: We are broadcasting to live from Interactive Broker Studio right 332 00:15:50,360 --> 00:15:53,320 Speaker 8: here in New York City. You can also check us 333 00:15:53,320 --> 00:15:56,240 Speaker 8: out on YouTube as well. So back to the markets. Yeah, 334 00:15:56,240 --> 00:15:59,240 Speaker 8: I appreciate nothing's really happening in the broader equity market. 335 00:15:59,240 --> 00:16:01,680 Speaker 8: You are seeing little bit buying coming into the bond market, 336 00:16:01,720 --> 00:16:04,000 Speaker 8: particularly in the front end. We all look towards Jackson Hole. 337 00:16:04,120 --> 00:16:06,920 Speaker 8: I'm really into that revision of the labor data that 338 00:16:06,960 --> 00:16:09,040 Speaker 8: we're going to get tomorrow. Is the FED going to 339 00:16:09,080 --> 00:16:11,640 Speaker 8: be particularly behind the curb, But we wanted to get 340 00:16:11,640 --> 00:16:13,360 Speaker 8: a professional to weigh in on all of this, and 341 00:16:13,440 --> 00:16:16,440 Speaker 8: Dryden Pence is Chief Investment Officer at Pence Wealth Management 342 00:16:16,800 --> 00:16:19,280 Speaker 8: and he joined us now in the studio Dryden. 343 00:16:19,320 --> 00:16:20,800 Speaker 5: What do you think, what do you think we're going 344 00:16:20,880 --> 00:16:21,920 Speaker 5: to learn this week. 345 00:16:22,320 --> 00:16:23,760 Speaker 10: I think we're going to learn this week that the 346 00:16:23,840 --> 00:16:28,440 Speaker 10: much predicted, you know, September rate cut is on the table, 347 00:16:29,080 --> 00:16:32,560 Speaker 10: that labor data is probably going to be revised a 348 00:16:32,600 --> 00:16:34,440 Speaker 10: little bit. I think people forgot that a lot of 349 00:16:34,440 --> 00:16:37,080 Speaker 10: the labor data was affected by weather, and so you 350 00:16:37,160 --> 00:16:39,440 Speaker 10: had people that were temporary or layoffs or things like that, 351 00:16:39,480 --> 00:16:41,840 Speaker 10: so you get these anomalies that are when we've all 352 00:16:41,920 --> 00:16:45,080 Speaker 10: witnessed weather here lately in New York City, so those 353 00:16:45,120 --> 00:16:46,720 Speaker 10: things have caused it to. 354 00:16:46,760 --> 00:16:47,400 Speaker 4: Change a little bit. 355 00:16:47,440 --> 00:16:49,720 Speaker 10: I think we'll find September's on the table. I think 356 00:16:49,720 --> 00:16:53,320 Speaker 10: that we'll find that the economy is still robust and 357 00:16:53,400 --> 00:16:56,080 Speaker 10: not as I mean, while it's slowing, it's not slowing 358 00:16:56,080 --> 00:16:57,800 Speaker 10: to the level that others were talking about. So I 359 00:16:57,840 --> 00:17:01,160 Speaker 10: think we're going to find a benign move to a 360 00:17:01,240 --> 00:17:04,199 Speaker 10: quarter cut in September, and then we're data dependent to 361 00:17:04,200 --> 00:17:05,440 Speaker 10: see what happens in December. 362 00:17:06,280 --> 00:17:08,399 Speaker 3: We're just finishing up I guess this week kind of 363 00:17:08,440 --> 00:17:10,680 Speaker 3: earnings here. We've got some retailers coming in as well 364 00:17:10,680 --> 00:17:13,240 Speaker 3: as in Nvidia coming up to kind of put a 365 00:17:13,240 --> 00:17:15,720 Speaker 3: punctuation mark on it next next week, What did you 366 00:17:15,720 --> 00:17:17,240 Speaker 3: make of the earnings season we just had. 367 00:17:17,400 --> 00:17:18,920 Speaker 4: I think it's been a robust earning season. 368 00:17:18,960 --> 00:17:20,479 Speaker 10: I mean, the point of the matter is is is 369 00:17:20,520 --> 00:17:22,800 Speaker 10: you know, you had this growth scare that freaked everybody 370 00:17:22,840 --> 00:17:24,440 Speaker 10: out a couple weeks ago. But I mean the point 371 00:17:24,480 --> 00:17:27,840 Speaker 10: of matter is is that we're seeing the broadening out 372 00:17:28,119 --> 00:17:31,480 Speaker 10: of earnings. The earning situation is that we've you know, 373 00:17:31,520 --> 00:17:35,600 Speaker 10: earning recessions, you know, rolling recessions turned into rolling recoveries, 374 00:17:35,640 --> 00:17:37,359 Speaker 10: and so you're seeing the earnings of the rest of 375 00:17:37,359 --> 00:17:39,160 Speaker 10: the four ninety three of the S and P five 376 00:17:39,240 --> 00:17:42,760 Speaker 10: hundred begin to move forward and come out. You're seeing 377 00:17:42,800 --> 00:17:45,879 Speaker 10: about seven eight percent to thirteen percent earnings growth there, 378 00:17:46,040 --> 00:17:48,720 Speaker 10: and that bodes well for the whole broader part of 379 00:17:48,760 --> 00:17:52,360 Speaker 10: the market. So we're moving from magnificent seven, where Nvidia 380 00:17:52,359 --> 00:17:55,240 Speaker 10: accounts for all the earnings growth, to the rest of 381 00:17:55,280 --> 00:17:58,159 Speaker 10: the market moving forward. So that does one of two things. 382 00:17:58,440 --> 00:18:00,760 Speaker 10: It either puts a floor on it by making it 383 00:18:00,840 --> 00:18:05,480 Speaker 10: stronger and stable, or it moves the market forward as 384 00:18:05,520 --> 00:18:07,080 Speaker 10: we go through the rest of the. 385 00:18:07,080 --> 00:18:10,399 Speaker 8: Year, but only for those that actually had that earnings growth, 386 00:18:10,400 --> 00:18:13,200 Speaker 8: So where did you see it? For example, like Bank 387 00:18:13,240 --> 00:18:16,120 Speaker 8: of America's had all their clients bought everything last week except. 388 00:18:15,800 --> 00:18:18,160 Speaker 5: For energy and industrials, Like, where do you see that growth? 389 00:18:18,160 --> 00:18:18,679 Speaker 5: Where do you not? 390 00:18:19,359 --> 00:18:19,479 Speaker 6: Well? 391 00:18:19,560 --> 00:18:22,920 Speaker 10: I think the issue is I begin to see as 392 00:18:22,960 --> 00:18:25,320 Speaker 10: we look at this later part of the cycle, we're 393 00:18:25,320 --> 00:18:28,159 Speaker 10: going to see industrials begin to do better. And we 394 00:18:28,680 --> 00:18:31,520 Speaker 10: think we're going to see industrials and small caps, and 395 00:18:31,560 --> 00:18:34,600 Speaker 10: you're beginning to see pieces of that. I mean, most 396 00:18:34,680 --> 00:18:37,679 Speaker 10: companies are beating their earnings growth estimates. As that's all 397 00:18:37,720 --> 00:18:39,679 Speaker 10: come out, we're almost all the way through earning the season. 398 00:18:39,840 --> 00:18:42,680 Speaker 10: But I think as you get into late third quarter 399 00:18:42,720 --> 00:18:44,760 Speaker 10: and fourth quarters, we're moving through this and you're going 400 00:18:44,800 --> 00:18:48,000 Speaker 10: to see companies begin to publish and begin to show 401 00:18:48,480 --> 00:18:50,520 Speaker 10: even better earnings going forward. So it's again it's the 402 00:18:50,600 --> 00:18:53,040 Speaker 10: broadening out of the S and P five hundred and 403 00:18:53,080 --> 00:18:56,119 Speaker 10: also small caps and industrials. We think that are going 404 00:18:56,160 --> 00:19:01,520 Speaker 10: to continue to see a regular cad of improvement. 405 00:19:02,320 --> 00:19:04,080 Speaker 3: One of the companies on your list was actually in 406 00:19:04,119 --> 00:19:06,720 Speaker 3: the news this week. A m D is a company 407 00:19:06,720 --> 00:19:09,360 Speaker 3: that's on your list. They made an acquisition of ZT Systems, 408 00:19:09,760 --> 00:19:13,840 Speaker 3: which is technology company based in the bustling technology hub 409 00:19:13,840 --> 00:19:15,000 Speaker 3: of Secaucus, New Jersey. 410 00:19:15,520 --> 00:19:17,600 Speaker 4: I know, what's your AMD call. 411 00:19:18,600 --> 00:19:20,679 Speaker 10: We have been We've liked a m D for a 412 00:19:20,880 --> 00:19:24,080 Speaker 10: very long time, and we've owned it from the when 413 00:19:24,080 --> 00:19:26,240 Speaker 10: it was in some of our portfolios since it was 414 00:19:26,280 --> 00:19:29,280 Speaker 10: a you know, a small cap and just out there. 415 00:19:29,359 --> 00:19:31,480 Speaker 10: Now it's all the way, it's you know, moved up tremendously. 416 00:19:31,800 --> 00:19:34,200 Speaker 10: So we liked it for a very long time. We 417 00:19:34,440 --> 00:19:37,439 Speaker 10: like a m D here too, in terms of what 418 00:19:37,480 --> 00:19:39,440 Speaker 10: they're doing with their company. You know, there's sort of 419 00:19:39,480 --> 00:19:41,480 Speaker 10: the number two in a lot of spaces, not only 420 00:19:41,480 --> 00:19:44,120 Speaker 10: the advanced stuff but just kind of the everyday chips. 421 00:19:44,320 --> 00:19:47,679 Speaker 10: We've always said by chips on dips uh. And so 422 00:19:48,040 --> 00:19:50,760 Speaker 10: we think that with with AI, with everything going on, 423 00:19:51,119 --> 00:19:54,679 Speaker 10: this is a this acquisition is a MD kind of 424 00:19:54,960 --> 00:19:58,480 Speaker 10: you know, getting really serious about going after Nvidiah and 425 00:19:58,520 --> 00:20:01,679 Speaker 10: so I like companies that are number two and hungry. 426 00:20:01,920 --> 00:20:04,840 Speaker 5: Okay, So it's like an AMD not and video story 427 00:20:04,880 --> 00:20:08,280 Speaker 5: for you, right, gotcha? You also like Chipotle? 428 00:20:08,840 --> 00:20:09,040 Speaker 6: I do? 429 00:20:09,880 --> 00:20:12,880 Speaker 5: And do you like it without the CEO Brian Nikol, Well. 430 00:20:12,920 --> 00:20:16,119 Speaker 10: The point that makes a big difference in Starbucks needed 431 00:20:16,119 --> 00:20:18,520 Speaker 10: to make a change. There's probably a good move there. 432 00:20:18,800 --> 00:20:20,080 Speaker 4: But when you think. 433 00:20:19,960 --> 00:20:23,520 Speaker 10: About the consumer, consumers are what we call it, have 434 00:20:23,560 --> 00:20:26,160 Speaker 10: now become more conscious. You know, at one point, coming 435 00:20:26,160 --> 00:20:28,000 Speaker 10: out of the pandemic, it was going to buy anything 436 00:20:28,000 --> 00:20:30,720 Speaker 10: at any price because everybody who had to all this liquidity. 437 00:20:31,119 --> 00:20:34,040 Speaker 10: Now we're seeing that the consumers being pickier. 438 00:20:34,520 --> 00:20:35,800 Speaker 4: They want value. 439 00:20:35,840 --> 00:20:38,800 Speaker 10: This is why if you contrast Chipotle and McDonald's, I mean, 440 00:20:39,160 --> 00:20:41,280 Speaker 10: fast food is supposed to be fast and cheap, and 441 00:20:41,320 --> 00:20:44,399 Speaker 10: one becomes neither, right, then people move away from it. 442 00:20:44,440 --> 00:20:45,639 Speaker 4: And you saw that with McDonald's. 443 00:20:45,680 --> 00:20:49,800 Speaker 10: With Chipotle, people are seeing value in what they're spending. 444 00:20:49,840 --> 00:20:52,560 Speaker 10: So you're continuing to see, Okay, it's worth the extra 445 00:20:52,640 --> 00:20:54,639 Speaker 10: money for what I'm getting, and I'm paying for that, 446 00:20:54,680 --> 00:20:57,280 Speaker 10: and so that becomes a more stable, stable move. So 447 00:20:57,520 --> 00:20:59,879 Speaker 10: we think that the whole story here is about a 448 00:21:00,400 --> 00:21:04,760 Speaker 10: conscious consumer. They're still spending money, more people are making 449 00:21:04,760 --> 00:21:06,960 Speaker 10: more money than ever before, and they're spending it, but 450 00:21:07,040 --> 00:21:10,840 Speaker 10: they're being more discerning about it and they're being a 451 00:21:10,880 --> 00:21:11,480 Speaker 10: little pickier. 452 00:21:11,720 --> 00:21:13,439 Speaker 3: What do you think about the consumer here? Does that 453 00:21:14,160 --> 00:21:16,440 Speaker 3: a lot of folks are saying there's really at least 454 00:21:16,480 --> 00:21:19,240 Speaker 3: two consumers out there, the ones I own risk assets, 455 00:21:19,240 --> 00:21:22,000 Speaker 3: whether stocks, bonds, real estate, and they're doing fine and 456 00:21:22,040 --> 00:21:24,480 Speaker 3: maybe even more fine if the indust rates come down, 457 00:21:24,920 --> 00:21:28,479 Speaker 3: and then there's everybody else who really feels the brunt 458 00:21:28,560 --> 00:21:30,159 Speaker 3: of inflation in their pocketbook. 459 00:21:31,280 --> 00:21:33,120 Speaker 4: Does that impact kind of the stocks you look at 460 00:21:33,640 --> 00:21:34,080 Speaker 4: it does? 461 00:21:34,240 --> 00:21:36,760 Speaker 10: I mean, we really do focus on We look for big, 462 00:21:36,760 --> 00:21:40,320 Speaker 10: noble themes driving consumer activity. We look for choke points 463 00:21:40,400 --> 00:21:42,520 Speaker 10: or companies that really you don't have a kind of 464 00:21:42,720 --> 00:21:46,040 Speaker 10: either monopolistic power. They're a key into that consumer behavior. 465 00:21:46,280 --> 00:21:49,679 Speaker 10: So what we're again, we're seeing this trend of consumers 466 00:21:49,720 --> 00:21:52,119 Speaker 10: being pickier. You have people at the lower end of 467 00:21:52,119 --> 00:21:57,360 Speaker 10: the economic spectrum are certainly becoming stretched. Inflation is changing 468 00:21:57,400 --> 00:22:00,400 Speaker 10: their behavior a little bit. But it's very interesting. Inflation 469 00:22:00,480 --> 00:22:03,640 Speaker 10: expectations have come down now people are beginning to make 470 00:22:03,680 --> 00:22:05,920 Speaker 10: some changes in that and you and you and you. 471 00:22:05,880 --> 00:22:07,359 Speaker 4: Did see some real wage growth. 472 00:22:07,600 --> 00:22:10,679 Speaker 10: So I think the big thing that the agenda, and 473 00:22:10,800 --> 00:22:13,560 Speaker 10: whether it's politicians or anybody else, it takes a little 474 00:22:13,600 --> 00:22:16,800 Speaker 10: time for these things to work their way through the economy, 475 00:22:17,000 --> 00:22:19,240 Speaker 10: and I think that we're seeing some stabilization of it. 476 00:22:19,359 --> 00:22:22,080 Speaker 10: Consumer confidence is probably beginning to get a little bit better, 477 00:22:22,280 --> 00:22:24,119 Speaker 10: not a little bit worse. So I think this is 478 00:22:24,240 --> 00:22:27,080 Speaker 10: an adjustment period that we're moving from a torrid pace 479 00:22:27,119 --> 00:22:30,120 Speaker 10: of economic growth to a sustainable one, right, like. 480 00:22:30,160 --> 00:22:32,320 Speaker 5: Just slowing, not slumping basically. 481 00:22:32,400 --> 00:22:34,359 Speaker 8: But you know, back to Chipotle for a second. So 482 00:22:34,640 --> 00:22:37,000 Speaker 8: this is what I've heard from Paul. You said three tacos. 483 00:22:37,160 --> 00:22:39,800 Speaker 3: Okay, there, we got caught out on social media for 484 00:22:40,000 --> 00:22:42,280 Speaker 3: under you know, skipping on some of the ingredients. So 485 00:22:42,280 --> 00:22:46,840 Speaker 3: they went overboard and now overstuff your orders to the 486 00:22:46,840 --> 00:22:49,080 Speaker 3: point now that I only get two tacos instead of three. 487 00:22:49,359 --> 00:22:50,600 Speaker 5: So how is that good for Chippotle? 488 00:22:50,760 --> 00:22:52,919 Speaker 8: Because it's good for Paul, it's good for but like 489 00:22:52,920 --> 00:22:54,680 Speaker 8: it is it good for them? Like their top line 490 00:22:54,680 --> 00:22:56,720 Speaker 8: doesn't grow as much and they have to put out 491 00:22:56,720 --> 00:22:57,359 Speaker 8: more in the food. 492 00:22:57,560 --> 00:22:58,520 Speaker 5: I think they have done. 493 00:22:59,160 --> 00:23:03,000 Speaker 10: This is where chip has a competitive advantage in that 494 00:23:03,080 --> 00:23:07,359 Speaker 10: they really do pay attention to their consumers and their customers, 495 00:23:07,560 --> 00:23:11,080 Speaker 10: and they really focus throughout their entire history as how 496 00:23:11,119 --> 00:23:14,240 Speaker 10: do I put these families, these people that are coming 497 00:23:14,280 --> 00:23:16,520 Speaker 10: into these stores. These people are that they have a 498 00:23:16,600 --> 00:23:21,400 Speaker 10: reliable product at a reasonable price, and they consumers see 499 00:23:21,440 --> 00:23:23,520 Speaker 10: value and if they see value, they show up. And 500 00:23:23,600 --> 00:23:25,720 Speaker 10: I think that that's what that's a that's a competitive 501 00:23:25,720 --> 00:23:29,159 Speaker 10: advantage that Chappotle has, uh maybe against some of the competitors. 502 00:23:29,160 --> 00:23:32,160 Speaker 10: And that's what you're saying, right, they listen, they react, 503 00:23:32,440 --> 00:23:35,560 Speaker 10: they really react, and everybody feels it. So that's that's 504 00:23:35,600 --> 00:23:38,920 Speaker 10: a good consumer products company and we like those. 505 00:23:39,320 --> 00:23:40,320 Speaker 4: Yep, it's good stuff. 506 00:23:40,359 --> 00:23:40,439 Speaker 6: All. 507 00:23:41,200 --> 00:23:43,440 Speaker 3: So much for journey us Dryden Pen's chief investment officer 508 00:23:43,480 --> 00:23:46,360 Speaker 3: Pence Wealth Management, based in Newport Beach, California. 509 00:23:46,400 --> 00:23:49,679 Speaker 4: We've covered that territory before. I'm not buying. I'm not 510 00:23:49,680 --> 00:23:51,480 Speaker 4: buying the whole Pimpco thing out there. 511 00:23:51,560 --> 00:23:55,280 Speaker 8: It's pretty out there, beautiful. That's something as long as 512 00:23:55,280 --> 00:23:57,480 Speaker 8: it lasts, right, mudslines. 513 00:23:59,240 --> 00:24:02,800 Speaker 4: Nice, someone's got it there. I'm glad I do exactly exactly. 514 00:24:03,160 --> 00:24:05,199 Speaker 8: All right, Well, coming up, I'm going to talk to 515 00:24:05,200 --> 00:24:07,240 Speaker 8: Paul about what he can expect at his next luxury 516 00:24:07,280 --> 00:24:08,119 Speaker 8: hotel trip. 517 00:24:08,320 --> 00:24:08,600 Speaker 4: Nice. 518 00:24:08,760 --> 00:24:12,360 Speaker 5: Uh huh okay, bunk beds. Oh no, yeah, yeah, he's 519 00:24:12,359 --> 00:24:13,040 Speaker 5: going to be into it. 520 00:24:14,520 --> 00:24:18,400 Speaker 2: You're listening to the Bloomberg Intelligence Podcast. Catch us live 521 00:24:18,480 --> 00:24:22,000 Speaker 2: weekdays at ten am Eastern on applecar Play and Android 522 00:24:22,040 --> 00:24:24,800 Speaker 2: Auto with the Bloomberg Business app. You can also listen 523 00:24:24,920 --> 00:24:28,040 Speaker 2: live on Amazon Alexa from our flagship New York station. 524 00:24:28,400 --> 00:24:31,160 Speaker 2: Just say Alexa playing Bloomberg eleven thirty. 525 00:24:32,560 --> 00:24:34,200 Speaker 8: Alex, you' here alongside Paul sw We need. This is 526 00:24:34,240 --> 00:24:36,919 Speaker 8: Bloomberg Intelligence Radio. We cover all the top news and business, 527 00:24:36,960 --> 00:24:39,919 Speaker 8: economic and finance. There are lens of our Bloomberg Intelligence folks. 528 00:24:39,960 --> 00:24:42,360 Speaker 8: They cover two thousand companies and one hundred and thirty 529 00:24:42,440 --> 00:24:45,919 Speaker 8: industries all around the world. For now that we're going 530 00:24:45,960 --> 00:24:48,399 Speaker 8: to go to Miami, Florida, because you know, why not, 531 00:24:49,000 --> 00:24:50,879 Speaker 8: We're going to speak to Henri Pierre Jacques. He's co 532 00:24:50,960 --> 00:24:54,640 Speaker 8: founder and managing partner at Harlem Capital Partners. He joins 533 00:24:54,720 --> 00:24:55,720 Speaker 8: us from Miami, Florida. 534 00:24:55,760 --> 00:24:56,000 Speaker 5: Now. 535 00:24:56,280 --> 00:24:59,320 Speaker 8: Harlem Capital Partners was founded back in twenty fifteen. Is 536 00:24:59,320 --> 00:25:01,919 Speaker 8: a venture cap firm based in New York, and it 537 00:25:01,960 --> 00:25:05,760 Speaker 8: prefers to make investments and things like AI, consumer technology, 538 00:25:05,840 --> 00:25:09,439 Speaker 8: E commerce, enterprise, human resource technology, all the stuff that 539 00:25:09,480 --> 00:25:14,520 Speaker 8: we talk about every single day. Henri Pierre walk me 540 00:25:14,520 --> 00:25:16,760 Speaker 8: through kind of how you guys think of the AI 541 00:25:16,880 --> 00:25:20,520 Speaker 8: landscape right now, the good investments and the risky investments. 542 00:25:22,119 --> 00:25:24,200 Speaker 11: Yeah, I mean, obviously there's a lot of hype around AI. 543 00:25:24,280 --> 00:25:25,760 Speaker 11: I mean, I think the way that we think about 544 00:25:25,760 --> 00:25:29,040 Speaker 11: it generally, as we want to invest in AI companies 545 00:25:29,040 --> 00:25:31,880 Speaker 11: that don't touch anything close to the large incumbents such 546 00:25:31,880 --> 00:25:36,120 Speaker 11: as Apple, Apple, Microsoft, Chat, TBT, and so we're really 547 00:25:36,160 --> 00:25:39,719 Speaker 11: focused on vertical AI applications, and so some of our 548 00:25:39,760 --> 00:25:43,680 Speaker 11: investments have been in super niche fields like accounting AI services, 549 00:25:44,680 --> 00:25:47,720 Speaker 11: insurance broker AI services, and so we're really trying to 550 00:25:47,720 --> 00:25:50,879 Speaker 11: not touch the consumer AI marketplace. So we think distribution 551 00:25:51,040 --> 00:25:53,040 Speaker 11: largely will win there for the large players. 552 00:25:53,720 --> 00:25:56,600 Speaker 3: So, Henri, how do you We're such in the early 553 00:25:56,680 --> 00:25:59,800 Speaker 3: innings of AI, A lot of people don't even know 554 00:25:59,840 --> 00:26:02,480 Speaker 3: what it is, can't really articulate what it is, how 555 00:26:02,480 --> 00:26:05,879 Speaker 3: it's used, what the applications are. Yeah, I'm thinking me, 556 00:26:05,960 --> 00:26:08,720 Speaker 3: I'm speaking my own book here. How do you guys? 557 00:26:09,640 --> 00:26:11,879 Speaker 3: How are you guys approaching AI right here? Because it 558 00:26:11,920 --> 00:26:14,679 Speaker 3: feels to me like AI today is what we were 559 00:26:14,720 --> 00:26:17,880 Speaker 3: calling big data five years ago and ten years ago 560 00:26:17,920 --> 00:26:21,000 Speaker 3: we're just calling tech. So I'm not sure what it is. 561 00:26:21,000 --> 00:26:23,119 Speaker 3: How are you guys approaching if from an investment perspective? 562 00:26:24,240 --> 00:26:27,320 Speaker 11: Yeah, I mean, ultimately, AI has been around for decade plus. 563 00:26:27,359 --> 00:26:30,080 Speaker 11: I think what this wave has seen as generitive AI, 564 00:26:30,640 --> 00:26:33,000 Speaker 11: which is more of the image and tool and video creation, 565 00:26:33,119 --> 00:26:35,680 Speaker 11: and people are kind of bucketing that for all of AI. 566 00:26:36,200 --> 00:26:37,760 Speaker 11: I mean largely for a lot of the companies we 567 00:26:37,800 --> 00:26:41,480 Speaker 11: invest in, like they're really just enterprise software companies that 568 00:26:41,560 --> 00:26:44,720 Speaker 11: are using AI in the background. Ultimately, you know, right 569 00:26:44,760 --> 00:26:47,760 Speaker 11: now there are more CFOs and CTOs who are getting 570 00:26:47,800 --> 00:26:50,840 Speaker 11: AI budget spinds, and so if the company says AI, 571 00:26:50,920 --> 00:26:53,040 Speaker 11: then their company will allow them to spend more. But 572 00:26:53,119 --> 00:26:54,560 Speaker 11: the end of the day and the next three to 573 00:26:54,640 --> 00:26:57,000 Speaker 11: five years, like the customer only cares about how you're 574 00:26:57,000 --> 00:26:59,560 Speaker 11: solving their problem, right, We've gone through the similar way 575 00:26:59,600 --> 00:27:02,359 Speaker 11: for what in blockchain. If you're solving my problem on 576 00:27:02,400 --> 00:27:06,720 Speaker 11: web two versus blockchain versus AI, autesome I don't really care, right, 577 00:27:06,760 --> 00:27:09,840 Speaker 11: But there are these cycles where you'll see spend get budgeted, 578 00:27:09,840 --> 00:27:11,399 Speaker 11: and that's why you're seeing a big pullback for a 579 00:27:11,440 --> 00:27:14,600 Speaker 11: lot of the SaaS public companies because the software spins 580 00:27:14,600 --> 00:27:16,919 Speaker 11: getting drive to the AI spin. But in three to 581 00:27:17,000 --> 00:27:19,760 Speaker 11: five years, you know, maybe even shorter, that word won't 582 00:27:19,760 --> 00:27:22,040 Speaker 11: be where spin is going. It's ultimately, are you solving 583 00:27:22,080 --> 00:27:24,600 Speaker 11: the problem that the customer has? And so we're less 584 00:27:24,640 --> 00:27:27,439 Speaker 11: focused on the technology and more about what problem are 585 00:27:27,480 --> 00:27:30,480 Speaker 11: you solving? If you're using I versus software doesn't really 586 00:27:30,520 --> 00:27:32,120 Speaker 11: matter in the day, but you will get these short 587 00:27:32,200 --> 00:27:35,080 Speaker 11: term cycles where people will have spin for certain you know, 588 00:27:35,119 --> 00:27:37,080 Speaker 11: technologies because it's hot in the market. 589 00:27:37,359 --> 00:27:38,800 Speaker 8: Can you give me some examples of some of your 590 00:27:38,840 --> 00:27:42,000 Speaker 8: recent investments in AI, like the companies and sort of 591 00:27:42,040 --> 00:27:44,200 Speaker 8: why them, but dumb it down for me for sure. 592 00:27:45,600 --> 00:27:48,359 Speaker 11: Yeah. So one that I did, it's called test Party. 593 00:27:48,800 --> 00:27:51,679 Speaker 11: So basically what they do is they help websites be 594 00:27:51,720 --> 00:27:54,360 Speaker 11: eighty A compliant. And so a lot of people are 595 00:27:54,400 --> 00:27:57,200 Speaker 11: either deaf or blind or have blurry vision. And there's 596 00:27:57,200 --> 00:27:59,840 Speaker 11: actually like betteral laws that require companies to have what 597 00:28:00,080 --> 00:28:03,880 Speaker 11: sites that are accessible to them, right, and traditionally speaking, 598 00:28:04,000 --> 00:28:05,880 Speaker 11: people are going through this you know, either you're paying 599 00:28:05,920 --> 00:28:08,760 Speaker 11: somebody in India or it's very manual. Right, And now 600 00:28:08,760 --> 00:28:10,760 Speaker 11: we can use AI to actually go through and scrub 601 00:28:10,800 --> 00:28:13,040 Speaker 11: these sites and tell you, hey, these parts of your 602 00:28:13,080 --> 00:28:15,480 Speaker 11: sites are broken. Here's the code that can do to 603 00:28:15,560 --> 00:28:18,040 Speaker 11: fix it until you're eighty eight complyiant and you know, 604 00:28:18,200 --> 00:28:21,440 Speaker 11: billions of dollars a year. You'll see lawsuits where people 605 00:28:21,440 --> 00:28:24,560 Speaker 11: are getting sued because their websites aren't compliant. And so 606 00:28:24,640 --> 00:28:27,080 Speaker 11: this is a tool. This has been like, these companies 607 00:28:27,080 --> 00:28:29,840 Speaker 11: have been around, but they largely were consulting services before, 608 00:28:30,280 --> 00:28:32,159 Speaker 11: but now it's instead of having to pay people to 609 00:28:32,200 --> 00:28:34,879 Speaker 11: do this, you can actually use technology to help, particularly 610 00:28:34,920 --> 00:28:39,000 Speaker 11: e commerce websites, be more accessible to people who maybe 611 00:28:39,080 --> 00:28:40,800 Speaker 11: not have you know, perfect vision or perfect hearing. 612 00:28:41,440 --> 00:28:45,360 Speaker 3: Henri, what's a what's a typical deal side? I guess 613 00:28:45,400 --> 00:28:47,480 Speaker 3: what's a typical investment look like for you guys? Maybe 614 00:28:47,480 --> 00:28:50,680 Speaker 3: in terms of size? How early do you guys like 615 00:28:50,720 --> 00:28:53,120 Speaker 3: to get into these companies? What's a what's something in 616 00:28:53,200 --> 00:28:53,760 Speaker 3: use Spot? 617 00:28:53,800 --> 00:28:56,280 Speaker 11: I mean we're super early, so I mean our bread 618 00:28:56,280 --> 00:28:58,480 Speaker 11: and butter is kind of pre seed seed, So I 619 00:28:58,520 --> 00:29:01,120 Speaker 11: would say typically these companies are between zero and a 620 00:29:01,120 --> 00:29:04,400 Speaker 11: million of revenue. Our sweet Spot check is a one 621 00:29:04,400 --> 00:29:07,080 Speaker 11: point five to three million dollar check usually for ten 622 00:29:07,120 --> 00:29:10,760 Speaker 11: to fifteen percent ownership. So we're really early. I would 623 00:29:10,760 --> 00:29:13,640 Speaker 11: say half our companies we're pre revenue. Half our companies 624 00:29:13,640 --> 00:29:16,320 Speaker 11: we're post revenue. But ultimately, you know the stage that 625 00:29:16,360 --> 00:29:19,120 Speaker 11: we're at. We're backing the founders, but like sometimes there 626 00:29:19,160 --> 00:29:22,360 Speaker 11: are our businesses and customers, but sometimes there's no product 627 00:29:22,440 --> 00:29:24,160 Speaker 11: or no customers yet, and we're really just making a 628 00:29:24,160 --> 00:29:26,960 Speaker 11: bet on the founder to kind of you know, go 629 00:29:27,000 --> 00:29:28,640 Speaker 11: and tackle their vision again. 630 00:29:28,800 --> 00:29:30,720 Speaker 5: That gives me so much anxiety just hearing about that. 631 00:29:30,840 --> 00:29:32,000 Speaker 4: What's a success ratio? 632 00:29:32,120 --> 00:29:34,240 Speaker 11: My wife says the same for. 633 00:29:34,560 --> 00:29:38,560 Speaker 3: Someone like you at Harlem Capital Partners, what's a typical 634 00:29:38,600 --> 00:29:41,240 Speaker 3: success ratio? Like you've started this in twenty fifteen, we're 635 00:29:41,320 --> 00:29:44,080 Speaker 3: nine ten years into it, So how's that run for 636 00:29:44,120 --> 00:29:44,480 Speaker 3: you guys? 637 00:29:45,920 --> 00:29:47,720 Speaker 11: Yeah, I mean so for context, we started as an 638 00:29:47,760 --> 00:29:50,640 Speaker 11: angel syndikit, so for three to four years we were 639 00:29:50,680 --> 00:29:53,320 Speaker 11: investing our own money into companies, and then we actually 640 00:29:53,440 --> 00:29:56,360 Speaker 11: raise a fund for our capital five years ago. So 641 00:29:56,400 --> 00:29:58,320 Speaker 11: we're on our second fund now, so really like five 642 00:29:58,400 --> 00:30:01,000 Speaker 11: years into the journey of like having a stitutional capital, 643 00:30:02,120 --> 00:30:04,160 Speaker 11: you know, typical like I can give you, like we're 644 00:30:04,160 --> 00:30:06,320 Speaker 11: early in the cycle, but we have kind of like 645 00:30:06,320 --> 00:30:08,680 Speaker 11: a forty percent Series A conversion. I would say that's 646 00:30:08,680 --> 00:30:11,160 Speaker 11: like really the target for seed stage funn is how 647 00:30:11,160 --> 00:30:13,280 Speaker 11: many of your companies get to the Series A because 648 00:30:13,320 --> 00:30:15,600 Speaker 11: from there you typically see a sixty percent conversion to 649 00:30:15,600 --> 00:30:18,760 Speaker 11: the Series B seriously et cetera, and beyond. So that's 650 00:30:18,800 --> 00:30:21,479 Speaker 11: like the near term measurement that we're focused on, but 651 00:30:21,520 --> 00:30:24,040 Speaker 11: like long term, yeah, it's really hard. Obviously early stage venture, 652 00:30:24,120 --> 00:30:27,000 Speaker 11: you know, three percent or startups become unicorns, and it's 653 00:30:27,040 --> 00:30:29,200 Speaker 11: a law of outliers, right, and so typically, you know, 654 00:30:29,240 --> 00:30:32,000 Speaker 11: if you invest in thirty companies, one to two companies 655 00:30:32,000 --> 00:30:34,200 Speaker 11: will drive your returns and like that's ultimately what you're 656 00:30:34,200 --> 00:30:37,040 Speaker 11: fighting for, and the other twenty eight will be you know, 657 00:30:37,080 --> 00:30:40,160 Speaker 11: call it zero to five exes. But the one winner 658 00:30:40,880 --> 00:30:42,880 Speaker 11: is the one that kind of drives your returns. So 659 00:30:42,920 --> 00:30:44,480 Speaker 11: it's not it's stressful. 660 00:30:45,440 --> 00:30:48,040 Speaker 5: Yeah, I mean, hey, it's not hard. No, No, this 661 00:30:48,160 --> 00:30:50,520 Speaker 5: is definitely not my risk profile. I needs steady job, 662 00:30:50,560 --> 00:30:52,560 Speaker 5: I need the whole thing before I let you go. 663 00:30:52,600 --> 00:30:54,560 Speaker 8: We have like a minute left here. Talk about some 664 00:30:54,600 --> 00:30:57,120 Speaker 8: recent investments in say, vertical software. 665 00:30:58,800 --> 00:31:03,280 Speaker 11: Yeah, so a company called Finterry. So it's a reconciliation 666 00:31:03,400 --> 00:31:07,479 Speaker 11: platform for insurance brokers. So oftentimes insurance companies are kind 667 00:31:07,480 --> 00:31:10,120 Speaker 11: of outsourcing who they're using for the sales process. You 668 00:31:10,160 --> 00:31:14,320 Speaker 11: have like ten different brokers, they're getting paid differently, different timetables. 669 00:31:14,640 --> 00:31:16,520 Speaker 11: And so now you can use AI to actually, like 670 00:31:16,720 --> 00:31:19,000 Speaker 11: it's vertical software, but you can use vertical software or 671 00:31:19,040 --> 00:31:23,160 Speaker 11: AI help those companies actually manage the process of paying 672 00:31:23,200 --> 00:31:26,360 Speaker 11: all those brokers. Traditionally speaking, those have been done in 673 00:31:26,480 --> 00:31:29,680 Speaker 11: excel files, word documents, and so we invest in this 674 00:31:29,720 --> 00:31:32,480 Speaker 11: company pre revenue. They've grown ten x in the last 675 00:31:32,560 --> 00:31:34,480 Speaker 11: nine months. They're going really quickly. And so what we're 676 00:31:34,520 --> 00:31:37,400 Speaker 11: seeing vertical software is a lot of these companies are 677 00:31:37,440 --> 00:31:40,680 Speaker 11: looking for very specific problems because everybody who has been 678 00:31:40,720 --> 00:31:43,280 Speaker 11: buying software for the past ten to twelve years, so like, 679 00:31:43,320 --> 00:31:47,160 Speaker 11: nobody really no longer needs this broad solution because Microsoft 680 00:31:47,320 --> 00:31:49,840 Speaker 11: or Salesforce or whoever is kind of solving that. But 681 00:31:49,840 --> 00:31:51,960 Speaker 11: if you have a very specific problem, I'm willing to 682 00:31:52,000 --> 00:31:54,920 Speaker 11: pay for the software. But people aren't generally buying horizontal 683 00:31:54,920 --> 00:31:57,120 Speaker 11: software anymore because that's kind of been done. There's already 684 00:31:57,360 --> 00:32:00,320 Speaker 11: a lot of incumbent who are solving massive problems, like 685 00:32:00,520 --> 00:32:02,520 Speaker 11: it's a very specific problem that a company has. 686 00:32:02,600 --> 00:32:04,320 Speaker 5: Hey, Henri, this has been a real pleasure. 687 00:32:04,560 --> 00:32:05,960 Speaker 8: I definitely want to hear more about how all of 688 00:32:05,960 --> 00:32:08,520 Speaker 8: this continues to unfold for you. On RePr, Jack co 689 00:32:08,600 --> 00:32:12,000 Speaker 8: founder and managing partner at Harlem Capital Partners, joining us 690 00:32:12,040 --> 00:32:14,520 Speaker 8: from Miami, Florida. 691 00:32:14,920 --> 00:32:18,800 Speaker 2: You're listening to the Bloomberg Intelligence Podcast. Catch us live 692 00:32:18,880 --> 00:32:22,400 Speaker 2: weekdays at ten am Eastern on applecar Play and Android 693 00:32:22,440 --> 00:32:25,600 Speaker 2: Auto with the Bloomberg Business. You can also listen live 694 00:32:25,680 --> 00:32:28,880 Speaker 2: on Amazon Alexa from our flagship New York station, Just 695 00:32:28,920 --> 00:32:31,560 Speaker 2: say Alexa play Bloomberg eleven thirty. 696 00:32:32,840 --> 00:32:35,120 Speaker 3: We are live here in our Bloomberg Interactive Brokers studio. 697 00:32:35,120 --> 00:32:37,040 Speaker 3: We're streaming live on YouTube as well, so they head 698 00:32:37,080 --> 00:32:39,760 Speaker 3: over to YouTube dot com and search Bloomberg Podcast and 699 00:32:39,800 --> 00:32:42,760 Speaker 3: that's where you can find us. Talk about some volatility. 700 00:32:43,160 --> 00:32:45,120 Speaker 3: You know, two weeks ago Monday, we had a VIX 701 00:32:45,240 --> 00:32:48,400 Speaker 3: that surged above sixty. I think I got about sixty 702 00:32:48,400 --> 00:32:51,440 Speaker 3: five intra day. The VIX right now for Tom Keen 703 00:32:51,520 --> 00:32:55,200 Speaker 3: is at fifteen spot for what a move there? 704 00:32:55,760 --> 00:32:56,920 Speaker 4: What's a money manager? 705 00:32:56,960 --> 00:32:58,800 Speaker 3: What's an investor to do with that kind of volatility? 706 00:32:59,280 --> 00:33:01,720 Speaker 3: Katarina Simi and then she joins us. She's a senior 707 00:33:01,800 --> 00:33:06,320 Speaker 3: vice president private wealth advisor for Morgan Stanley Private Wealth Management. So, 708 00:33:06,400 --> 00:33:09,560 Speaker 3: KATHERINEA talk to us. What kind of conversations have you 709 00:33:09,680 --> 00:33:12,600 Speaker 3: had with your clients over the last couple of weeks 710 00:33:12,600 --> 00:33:15,200 Speaker 3: as they dealt with that volatility From a couple of 711 00:33:15,200 --> 00:33:17,680 Speaker 3: weeks ago to weoiver right back where we started. 712 00:33:17,720 --> 00:33:20,160 Speaker 4: It seems like, well, and. 713 00:33:20,080 --> 00:33:22,760 Speaker 1: Alex, thank you for having me on. You are one 714 00:33:22,800 --> 00:33:25,920 Speaker 1: hundred percent right. This definitely is not a lazy summer 715 00:33:26,440 --> 00:33:27,959 Speaker 1: investors are concerned. 716 00:33:28,160 --> 00:33:28,360 Speaker 6: You know. 717 00:33:28,400 --> 00:33:31,960 Speaker 1: The questions that we get ranged from how sustainable is 718 00:33:32,040 --> 00:33:35,440 Speaker 1: this rally or how long the market decline is going 719 00:33:35,480 --> 00:33:38,840 Speaker 1: to last? Because we see these fluctuations that are making 720 00:33:38,920 --> 00:33:42,360 Speaker 1: investors very nervous. And one thing we know for sure 721 00:33:42,760 --> 00:33:45,240 Speaker 1: is this volatility is here to stay. If we look 722 00:33:45,280 --> 00:33:50,720 Speaker 1: back historically at these stretches eating two presidential elections, they 723 00:33:50,920 --> 00:33:54,480 Speaker 1: usually are known for this heightened volatility. And what we 724 00:33:54,560 --> 00:33:58,680 Speaker 1: tell our clients is really to expect it, to be 725 00:33:58,800 --> 00:34:01,480 Speaker 1: prepared for it, to take take advantage of the dips 726 00:34:01,480 --> 00:34:04,920 Speaker 1: in the market when it makes sense, to rebalance portfolio 727 00:34:05,240 --> 00:34:09,520 Speaker 1: to stay on the quality side, and definitely avoid making 728 00:34:09,600 --> 00:34:13,080 Speaker 1: any type portfolio changes based on what they think the 729 00:34:13,160 --> 00:34:16,319 Speaker 1: outcome of the election might be, because you know, as 730 00:34:16,320 --> 00:34:19,040 Speaker 1: we all know, there might be surprises, you know. So 731 00:34:19,200 --> 00:34:22,480 Speaker 1: we have the roadmap for either outcome, but we are 732 00:34:22,520 --> 00:34:25,480 Speaker 1: going to start implementing it after we have clarity on 733 00:34:25,560 --> 00:34:26,080 Speaker 1: the outcome. 734 00:34:26,600 --> 00:34:29,040 Speaker 8: Where would you buy market on dips right now and 735 00:34:29,080 --> 00:34:32,280 Speaker 8: where would you be selling any rip alex. 736 00:34:32,360 --> 00:34:37,080 Speaker 1: What we see right now is disproportionate over exposure to 737 00:34:37,239 --> 00:34:42,200 Speaker 1: technology in many portfolios, and we love technology. It is 738 00:34:42,280 --> 00:34:44,680 Speaker 1: definitely here to stay. But this is where you know, 739 00:34:44,760 --> 00:34:48,799 Speaker 1: sometimes it's skewed and off balance, and what we recommend 740 00:34:48,840 --> 00:34:51,680 Speaker 1: to do is go back and rebalance and buy on 741 00:34:51,760 --> 00:34:59,080 Speaker 1: dips into the sectors like financials, industrials, consumer staples, healthcare, energy, 742 00:34:59,480 --> 00:35:01,719 Speaker 1: and just to make sure that you know, we have 743 00:35:01,840 --> 00:35:06,600 Speaker 1: this strategically positioned portfolio, especially if we add the stocks 744 00:35:06,719 --> 00:35:10,120 Speaker 1: or emphasize the stocks that pay dividends. Now, in addition 745 00:35:10,239 --> 00:35:13,440 Speaker 1: to growth, we also have that income component that is 746 00:35:13,480 --> 00:35:17,680 Speaker 1: going to help investors get through this turbulent, highly volatile time. 747 00:35:18,239 --> 00:35:21,239 Speaker 3: How about in the bond market, Katerina, how are you 748 00:35:21,280 --> 00:35:23,360 Speaker 3: telling your clients to be positioned here? Should they just 749 00:35:23,400 --> 00:35:25,400 Speaker 3: go take it to your treasury and get four percent 750 00:35:25,600 --> 00:35:27,399 Speaker 3: or maybe take some credit risk. 751 00:35:28,719 --> 00:35:30,600 Speaker 1: Well, Paul, you know, this is where we have to 752 00:35:30,640 --> 00:35:32,759 Speaker 1: make some tough decisions. You know, we know that the 753 00:35:32,840 --> 00:35:35,920 Speaker 1: interest rate cuts on the horizon, and whether we are 754 00:35:35,960 --> 00:35:38,120 Speaker 1: going to get a quarter point cut or a half 755 00:35:38,160 --> 00:35:41,080 Speaker 1: point cut. We know rates are coming down and towards 756 00:35:41,160 --> 00:35:43,680 Speaker 1: the end of the year they're going to get most 757 00:35:43,800 --> 00:35:47,359 Speaker 1: likely lower than where they are today. So investor sav 758 00:35:47,360 --> 00:35:49,880 Speaker 1: a choice. They still have picks of the higher rates. 759 00:35:49,920 --> 00:35:52,920 Speaker 1: When we look back, you know, at last twenty twenty 760 00:35:52,960 --> 00:35:56,480 Speaker 1: five years. You know, I became financial advisor in ninety nine, 761 00:35:56,719 --> 00:35:58,880 Speaker 1: and this is the first time in my entire career 762 00:35:59,040 --> 00:36:01,880 Speaker 1: I'm seeing rates at these levels. So take your pick. 763 00:36:02,000 --> 00:36:05,400 Speaker 1: There are opportunities in high yield. There are opportunities in 764 00:36:05,520 --> 00:36:08,760 Speaker 1: high quality investment grade corporates. You know, there are still 765 00:36:08,920 --> 00:36:11,359 Speaker 1: you know, some buys that we can find in municipals. 766 00:36:11,560 --> 00:36:14,719 Speaker 1: We don't recommend going out on the far side of 767 00:36:14,760 --> 00:36:17,240 Speaker 1: the yield curf, you know, we are you know, really 768 00:36:17,280 --> 00:36:20,000 Speaker 1: trying to stay moderate in the middle. But we don't 769 00:36:20,080 --> 00:36:22,440 Speaker 1: want to go too short either because we're going to 770 00:36:22,560 --> 00:36:24,879 Speaker 1: run out of rates and then you know, most likely 771 00:36:24,920 --> 00:36:27,400 Speaker 1: default in default into much lower yields. 772 00:36:27,680 --> 00:36:29,520 Speaker 8: But in the corporate credit market, I was reading an 773 00:36:29,600 --> 00:36:32,040 Speaker 8: article today that talked about how there is so much 774 00:36:32,160 --> 00:36:35,279 Speaker 8: demand for precisely the scenario that you lay it out, 775 00:36:35,280 --> 00:36:37,280 Speaker 8: that you have to just go down the credit quality 776 00:36:37,320 --> 00:36:40,200 Speaker 8: to get yields even at five percent. So that kind 777 00:36:40,239 --> 00:36:42,360 Speaker 8: of upside that you're used to getting from the corporate 778 00:36:42,600 --> 00:36:45,640 Speaker 8: bond market really isn't there. So how much risk do 779 00:36:45,680 --> 00:36:47,040 Speaker 8: you want to be taking on right now? 780 00:36:47,960 --> 00:36:49,879 Speaker 1: Well, Alex, there are two sides to look at it. 781 00:36:50,000 --> 00:36:52,439 Speaker 1: You might need to take on a little bit more risk, 782 00:36:52,520 --> 00:36:54,959 Speaker 1: but still stay in the investment grade. The other side 783 00:36:55,000 --> 00:36:58,719 Speaker 1: of it is to look at patting somewhat higher premium. 784 00:36:58,760 --> 00:37:01,600 Speaker 1: And we're not talking, you know, like ten years ago 785 00:37:01,640 --> 00:37:04,719 Speaker 1: when we're paying ten ten percent over par. You know, yes, 786 00:37:04,880 --> 00:37:07,319 Speaker 1: prices or wants have moved, but there are still some 787 00:37:07,400 --> 00:37:10,200 Speaker 1: buying opportunities and there's still dips, just like in the 788 00:37:10,200 --> 00:37:13,920 Speaker 1: equity markets. You know, somebody is looking into building their 789 00:37:13,960 --> 00:37:17,200 Speaker 1: fixed income portfolio, you know, there has to be diversification, 790 00:37:17,640 --> 00:37:21,800 Speaker 1: exposure to various asset classes like high yield, investment grade, 791 00:37:21,880 --> 00:37:25,479 Speaker 1: municipal preferreds, you know, and just putting together this well 792 00:37:25,520 --> 00:37:29,279 Speaker 1: balanced portfolio and buying it gradually and strategically. But I 793 00:37:29,400 --> 00:37:32,040 Speaker 1: probably would not wait too long because once the rangers 794 00:37:32,120 --> 00:37:34,200 Speaker 1: are going to start coming down, you know that moved 795 00:37:34,280 --> 00:37:37,719 Speaker 1: to higher prices and lower quality is going to continue. 796 00:37:38,320 --> 00:37:42,080 Speaker 3: Katerina, how do you position alternative investments for your clients? 797 00:37:42,440 --> 00:37:46,080 Speaker 3: You know, I'm I'm always surprised that retail investors have 798 00:37:46,120 --> 00:37:48,880 Speaker 3: an appetite for alternative investments, whether it's hedge funds or 799 00:37:48,920 --> 00:37:51,960 Speaker 3: private equity or private debt. How do you guys position 800 00:37:52,040 --> 00:37:53,279 Speaker 3: that well? 801 00:37:53,320 --> 00:37:57,840 Speaker 1: Alternative investments definitely give us an opportunity to access parts 802 00:37:57,840 --> 00:38:00,839 Speaker 1: of the market with that we otherwise can not, and 803 00:38:01,440 --> 00:38:04,600 Speaker 1: we by doing that, we give ourselves, you know, the 804 00:38:04,640 --> 00:38:09,000 Speaker 1: access to potentially higher returns. But also alternatives can be 805 00:38:09,200 --> 00:38:12,680 Speaker 1: used as very effective hedge against the market risks where 806 00:38:12,840 --> 00:38:16,760 Speaker 1: we're looking to attain the market like returns with lower 807 00:38:16,760 --> 00:38:17,840 Speaker 1: than the market risks. 808 00:38:17,960 --> 00:38:18,160 Speaker 6: You know. 809 00:38:18,239 --> 00:38:21,000 Speaker 1: The trade of here, of course, the lack of liquidity, 810 00:38:21,320 --> 00:38:24,120 Speaker 1: and not all of them created equals. Some alternatives have 811 00:38:24,560 --> 00:38:28,160 Speaker 1: there are a little bit more liquid private equity investments, 812 00:38:28,160 --> 00:38:30,800 Speaker 1: for example, are not you know, so that's the trade 813 00:38:30,840 --> 00:38:33,360 Speaker 1: of for investors when they're making a decision to go 814 00:38:33,520 --> 00:38:38,560 Speaker 1: into this alternative space. We absolutely see opportunities distressed creddit, 815 00:38:38,840 --> 00:38:41,400 Speaker 1: you know, real estate. There are some you know, pockets 816 00:38:41,400 --> 00:38:44,160 Speaker 1: of the market that can be access there. But lack 817 00:38:44,200 --> 00:38:47,239 Speaker 1: of liquidity is something that is a very big consideration 818 00:38:47,360 --> 00:38:48,680 Speaker 1: for a lot of investors. 819 00:38:48,840 --> 00:38:51,040 Speaker 8: Oh yeah, I mean just check out the last couple weeks. 820 00:38:51,480 --> 00:38:53,720 Speaker 8: What about small caps? Can you give me the spiel 821 00:38:54,040 --> 00:38:56,160 Speaker 8: on small caps? It feels like these guys are definitely 822 00:38:56,200 --> 00:38:58,160 Speaker 8: hitting a binary world, like you either love them or 823 00:38:58,200 --> 00:38:59,400 Speaker 8: you hate them. 824 00:39:00,080 --> 00:39:03,240 Speaker 1: Well, absolutely, and Alex not that the history always repeats itself. 825 00:39:03,280 --> 00:39:05,919 Speaker 1: But when we look back at the past cycles, once 826 00:39:05,960 --> 00:39:08,839 Speaker 1: the rates are starting to come down, usually we first 827 00:39:08,880 --> 00:39:11,640 Speaker 1: see the optic in large cabs, but then it's followed 828 00:39:11,640 --> 00:39:14,880 Speaker 1: by the optics in small cabs and broader. On the 829 00:39:14,920 --> 00:39:18,000 Speaker 1: economic level, you know, we have the higher interest rate 830 00:39:18,120 --> 00:39:21,719 Speaker 1: environment which is affecting consumer confidence and also it is 831 00:39:21,760 --> 00:39:26,120 Speaker 1: effective expecting profitability of the companies and you know, on 832 00:39:26,200 --> 00:39:29,160 Speaker 1: one side, we're happy, then inflation is coming down. On 833 00:39:29,200 --> 00:39:31,640 Speaker 1: the other side, this is where you know, the profit 834 00:39:31,760 --> 00:39:34,640 Speaker 1: margins are being squeezed as well, more so for the 835 00:39:34,680 --> 00:39:37,319 Speaker 1: small caps than for the large cabs. But at the 836 00:39:37,400 --> 00:39:40,480 Speaker 1: same time, it might be a delayed reaction, but we 837 00:39:40,600 --> 00:39:44,759 Speaker 1: absolutely are positioning small caps in the portfolio. The returns 838 00:39:44,760 --> 00:39:47,160 Speaker 1: that we have seen recently is somewhat of a surprise 839 00:39:47,280 --> 00:39:49,960 Speaker 1: because for us is more of a long play, you know, 840 00:39:49,960 --> 00:39:52,640 Speaker 1: we're looking at the longer time horizon for that position. 841 00:39:53,480 --> 00:39:57,520 Speaker 3: Hey, Keterinea, we're just finishing up on earning seasons. What's 842 00:39:57,520 --> 00:39:59,319 Speaker 3: you been your takeaway for earning so far? 843 00:40:00,719 --> 00:40:03,400 Speaker 1: Well, we've seen you know, pretty good earnings so far 844 00:40:03,880 --> 00:40:06,960 Speaker 1: in the year, which was almost a pleasant surprise, you know, 845 00:40:07,000 --> 00:40:10,200 Speaker 1: they were better than expected. Our outlook for the remainder 846 00:40:10,239 --> 00:40:13,279 Speaker 1: of the year is not quite as optimistic, as we 847 00:40:13,360 --> 00:40:17,719 Speaker 1: see earnings being affected by consumer confidence, by higher rate, 848 00:40:17,840 --> 00:40:23,759 Speaker 1: by lack of liquidity, and also by just general economic slowdown. 849 00:40:24,120 --> 00:40:27,960 Speaker 1: And our base scenario is still that soft lending scenario 850 00:40:28,120 --> 00:40:31,400 Speaker 1: that is going to affect some parts of the market 851 00:40:31,520 --> 00:40:34,120 Speaker 1: and some parts of the economy. But we see the 852 00:40:34,960 --> 00:40:38,640 Speaker 1: earnings being not quite as good as we saw earlier 853 00:40:38,680 --> 00:40:41,360 Speaker 1: in the year. And the most important piece of data 854 00:40:41,400 --> 00:40:44,600 Speaker 1: for us are these forward looking estimates as companies are 855 00:40:44,600 --> 00:40:47,200 Speaker 1: posting their earnings, you know, for us to really see 856 00:40:47,239 --> 00:40:50,080 Speaker 1: how well they're positioned in the market. And that's why 857 00:40:50,120 --> 00:40:54,360 Speaker 1: in this particular time, we favor individual stock investing versus 858 00:40:54,400 --> 00:40:58,799 Speaker 1: index investing, where we can specifically focus on valuations, on 859 00:40:59,160 --> 00:41:02,680 Speaker 1: market position, and on the forward cooking out cooking earnings. 860 00:41:03,040 --> 00:41:05,040 Speaker 5: Before we let you go, Jackson Hall, what are you 861 00:41:05,040 --> 00:41:05,480 Speaker 5: looking for? 862 00:41:07,520 --> 00:41:08,120 Speaker 1: Who knows? 863 00:41:08,480 --> 00:41:09,800 Speaker 5: You know, that's a great answer. 864 00:41:11,239 --> 00:41:12,600 Speaker 7: Is it is really just. 865 00:41:13,080 --> 00:41:17,279 Speaker 1: So so difficult to you know, pinpoint and exactly you know, 866 00:41:17,680 --> 00:41:19,960 Speaker 1: exact data that should come out of it, you know, 867 00:41:20,080 --> 00:41:22,520 Speaker 1: for us to you know, to build the roadmap. But 868 00:41:22,800 --> 00:41:25,279 Speaker 1: we're looking for, you know, just just a little bit 869 00:41:25,320 --> 00:41:29,640 Speaker 1: of positivity to you know, give give investors some good news, 870 00:41:29,719 --> 00:41:32,120 Speaker 1: you know, during this time of market volatility prior to 871 00:41:32,160 --> 00:41:32,600 Speaker 1: the election. 872 00:41:33,000 --> 00:41:35,440 Speaker 8: Right, so like slowing economy, but not like a slump 873 00:41:35,440 --> 00:41:36,960 Speaker 8: economy like that kind of idea. 874 00:41:37,560 --> 00:41:40,560 Speaker 1: That's exactly right. Anything that leads us to soft lending, 875 00:41:40,920 --> 00:41:43,200 Speaker 1: you know, is good is good enough for us. 876 00:41:43,320 --> 00:41:45,080 Speaker 5: All Right, Well, I appreciate it, Thank you so much. 877 00:41:45,120 --> 00:41:48,560 Speaker 8: Katerina Semonetti joining US Senior vice president, private wealth advisor 878 00:41:48,760 --> 00:41:50,640 Speaker 8: of Morgan Stanley Private Wealth Management. 879 00:41:50,640 --> 00:41:52,320 Speaker 5: I feel like the Jacksonville conversation. 880 00:41:51,960 --> 00:41:54,520 Speaker 8: Would be really different like three weeks ago, like it 881 00:41:54,560 --> 00:41:56,640 Speaker 8: was right after that job's number, And I wonder if 882 00:41:57,000 --> 00:42:00,399 Speaker 8: Powell winds up changing or talk about the market action 883 00:42:00,560 --> 00:42:03,560 Speaker 8: in relation to jobs, like I wonder how he talks. 884 00:42:03,320 --> 00:42:05,680 Speaker 3: About that, because again, two weeks ago Monday, there was 885 00:42:05,880 --> 00:42:08,920 Speaker 3: particularly in the morning session, a real so weekenic exactly 886 00:42:09,280 --> 00:42:12,640 Speaker 3: in the marketplace, we stabilized kind of midday, kind of 887 00:42:12,960 --> 00:42:14,520 Speaker 3: rallied a little bit towards end of that day, and 888 00:42:14,560 --> 00:42:17,000 Speaker 3: then ever since then they're kind of moving up into 889 00:42:17,040 --> 00:42:17,239 Speaker 3: the right. 890 00:42:17,320 --> 00:42:19,160 Speaker 5: So you forgot that Friday because you're on the beach. 891 00:42:19,200 --> 00:42:23,759 Speaker 2: But yes, this is the Bloomberg Intelligence podcast, available on 892 00:42:23,800 --> 00:42:27,560 Speaker 2: Apples Spotify, and anywhere else you'll get your podcasts. Listen 893 00:42:27,680 --> 00:42:30,960 Speaker 2: live each weekday, ten am to noon Eastern on Bloomberg 894 00:42:31,000 --> 00:42:34,480 Speaker 2: dot Com, the iHeartRadio app, tune In, and the Bloomberg 895 00:42:34,520 --> 00:42:37,640 Speaker 2: Business app. You can also watch us live every weekday 896 00:42:37,680 --> 00:42:40,360 Speaker 2: on YouTube and always on the Bloomberg terminal