1 00:00:02,520 --> 00:00:13,760 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is the Bloomberg 2 00:00:13,840 --> 00:00:17,920 Speaker 1: Surveillance Podcast. Catch us live weekdays at seven am Eastern 3 00:00:18,200 --> 00:00:22,000 Speaker 1: on Apple CarPlay or Android Auto with the Bloomberg Business App. 4 00:00:22,360 --> 00:00:25,680 Speaker 1: Listen on demand wherever you get your podcasts, or watch 5 00:00:25,760 --> 00:00:27,040 Speaker 1: us live on YouTube. 6 00:00:27,360 --> 00:00:30,800 Speaker 2: This is Daniel Ives of Webb Bush. First of all, 7 00:00:31,120 --> 00:00:33,879 Speaker 2: rocket It out of Las Vegas with Aston Martin. For 8 00:00:33,920 --> 00:00:36,720 Speaker 2: those of you in radio, he's got the real jacket on, 9 00:00:36,880 --> 00:00:39,559 Speaker 2: like the kind net Lance Alonzo. We're in all that. 10 00:00:39,720 --> 00:00:43,000 Speaker 2: What in Formula one with all the excitement Apple taking 11 00:00:43,080 --> 00:00:46,920 Speaker 2: over the broadcast, Cadillac coming in next year. When you're 12 00:00:47,000 --> 00:00:50,720 Speaker 2: in the pit like you were, What's what's the thing 13 00:00:50,840 --> 00:00:52,880 Speaker 2: that you don't know when you watch on TV? 14 00:00:53,400 --> 00:00:55,240 Speaker 3: I think, I mean my experience at that point. 15 00:00:55,280 --> 00:00:57,680 Speaker 4: I think the thing that people realizes not just how 16 00:00:57,720 --> 00:01:00,440 Speaker 4: loud it is, but especially when you're in and you 17 00:01:00,520 --> 00:01:03,600 Speaker 4: actually have like the headphones on and you hear them 18 00:01:03,640 --> 00:01:07,119 Speaker 4: talking to the drivers. Just a complexity. I mean, that's 19 00:01:07,120 --> 00:01:09,080 Speaker 4: the thing. It's like, it's it's really amazing. 20 00:01:09,280 --> 00:01:10,319 Speaker 2: Did you change a tire? 21 00:01:11,120 --> 00:01:14,160 Speaker 4: I did, but I will tell you at at indy 22 00:01:14,280 --> 00:01:18,120 Speaker 4: five hundred I came close to almost change the entire. 23 00:01:18,120 --> 00:01:23,119 Speaker 3: Okay, to secure liberty media, you can own Formula one 24 00:01:23,319 --> 00:01:26,320 Speaker 3: fw O. NK is the ticker for Liberty Media. You 25 00:01:26,360 --> 00:01:27,400 Speaker 3: can own it as a publican. 26 00:01:27,600 --> 00:01:30,319 Speaker 2: Why is Apple doing that? Explaining just go to Jesse 27 00:01:30,440 --> 00:01:33,200 Speaker 2: Paul's dying to get to Nvidia and you know the 28 00:01:33,400 --> 00:01:37,800 Speaker 2: Google thing and all that. Why is Apple doing Apple TV? 29 00:01:37,959 --> 00:01:40,319 Speaker 2: It's called dad TV because no one watches it. They 30 00:01:40,400 --> 00:01:43,920 Speaker 2: got some product out, they've had some successes, but why 31 00:01:43,959 --> 00:01:45,160 Speaker 2: waste their time on that? 32 00:01:45,440 --> 00:01:45,600 Speaker 3: Yeah? 33 00:01:45,600 --> 00:01:48,920 Speaker 4: I mean to me, it's really it's all about where 34 00:01:49,240 --> 00:01:51,880 Speaker 4: they're ultimately going to take this. I mean in the future. 35 00:01:52,520 --> 00:01:55,200 Speaker 4: And we'll see as Apple ultimately goes down the past 36 00:01:55,240 --> 00:01:58,160 Speaker 4: with Gemini, and in terms of the AI future, they 37 00:01:58,200 --> 00:02:01,360 Speaker 4: need to have as wide of a con ten lenses possible. 38 00:02:01,520 --> 00:02:04,120 Speaker 4: And I think when you look at Apple TV, it's 39 00:02:04,160 --> 00:02:08,320 Speaker 4: all part of Look, the quality speaks for itself. Quantity 40 00:02:08,360 --> 00:02:10,520 Speaker 4: has been the issue, but for them, it's just they're 41 00:02:10,520 --> 00:02:11,400 Speaker 4: going to continue to. 42 00:02:11,280 --> 00:02:13,160 Speaker 3: Have irons in the fire. That's what they're going to do. 43 00:02:13,320 --> 00:02:16,360 Speaker 2: The TV show Pluribus, it's a sci fi thing. She's 44 00:02:16,400 --> 00:02:18,680 Speaker 2: home all alone. Everybody around her is like a droid. 45 00:02:19,160 --> 00:02:21,880 Speaker 2: She's watching surveillance. It was great, why don't you get 46 00:02:21,880 --> 00:02:22,920 Speaker 2: to a video right example? 47 00:02:23,360 --> 00:02:25,400 Speaker 3: So Dan, the AI story here took a little bit 48 00:02:25,400 --> 00:02:27,359 Speaker 3: of return over the last a couple of days. Here 49 00:02:27,639 --> 00:02:32,240 Speaker 3: Meta placing a big chip order with Google, further calling 50 00:02:32,320 --> 00:02:35,919 Speaker 3: to question the position or the dominance position of Nvidiot. 51 00:02:35,960 --> 00:02:37,840 Speaker 3: Give us your thoughts about that on I mean, look. 52 00:02:38,080 --> 00:02:42,280 Speaker 4: Google TPU if especially with with Broadcomm and TSMC is 53 00:02:42,320 --> 00:02:45,919 Speaker 4: the is the builder that's been around for over a decade, right, 54 00:02:45,960 --> 00:02:48,960 Speaker 4: So it's not that it's new per se. I think 55 00:02:49,040 --> 00:02:51,960 Speaker 4: the issue comes down to demand the spy from video 56 00:02:52,040 --> 00:02:53,040 Speaker 4: chips to twelve to one. 57 00:02:53,560 --> 00:02:56,480 Speaker 3: So the reality is the supply of Nvidio chips twelve 58 00:02:56,520 --> 00:02:57,000 Speaker 3: to one watch. 59 00:02:57,040 --> 00:02:59,440 Speaker 4: So look, when you look at Meta like they're not 60 00:02:59,520 --> 00:03:02,640 Speaker 4: going to be able to get everything they need from 61 00:03:02,639 --> 00:03:05,760 Speaker 4: in video, so they got to look outside. When you 62 00:03:05,760 --> 00:03:09,360 Speaker 4: look with googleized, I'd say it's really it's probut three 63 00:03:09,400 --> 00:03:12,880 Speaker 4: to four years behind where Nvidio is. But again on 64 00:03:13,240 --> 00:03:17,079 Speaker 4: some certain instances it could be good enough. And look 65 00:03:17,240 --> 00:03:19,440 Speaker 4: that's where we're going. I mean, the reality is when 66 00:03:19,480 --> 00:03:21,720 Speaker 4: it comes to AMD, when it comes to big tech, 67 00:03:22,000 --> 00:03:24,079 Speaker 4: eventually you need to see Apple, you know, to see Meta, 68 00:03:24,440 --> 00:03:26,440 Speaker 4: you can to see Microsoft. They'll build their own chips 69 00:03:26,480 --> 00:03:28,440 Speaker 4: as well, but there's one chip in the world fuel 70 00:03:28,440 --> 00:03:30,120 Speaker 4: in the AI revolution that's in video. 71 00:03:30,720 --> 00:03:32,359 Speaker 3: So that's kind of how I thought about yesday. I 72 00:03:32,360 --> 00:03:34,040 Speaker 3: was kind of surprised to see the cell off in 73 00:03:34,160 --> 00:03:36,880 Speaker 3: video because my thought was all I hear from guys 74 00:03:36,960 --> 00:03:39,320 Speaker 3: like you and technology folks coming in here is that 75 00:03:39,360 --> 00:03:42,640 Speaker 3: the demand for AI is just I'm not saying satial, 76 00:03:42,720 --> 00:03:45,600 Speaker 3: but boy, it's outstripping supply for sure, and you got 77 00:03:45,600 --> 00:03:47,480 Speaker 3: to get what you can get when you can get it. 78 00:03:47,520 --> 00:03:51,440 Speaker 4: Look, just spending three weeks in Asia, I mean, we've 79 00:03:51,480 --> 00:03:55,440 Speaker 4: seen demand accelerate thirty percent in the last six months 80 00:03:55,440 --> 00:03:58,080 Speaker 4: for AI. So it comes down to like it's easy 81 00:03:58,160 --> 00:04:02,240 Speaker 4: to call say AIS bubble in the spreadsheet and twenty 82 00:04:02,200 --> 00:04:04,280 Speaker 4: fifty four of New York City office building, but when 83 00:04:04,320 --> 00:04:07,960 Speaker 4: you actually see what's happening there. Look, only three percent 84 00:04:07,960 --> 00:04:10,360 Speaker 4: of enterprise in the US have gone down the AI path, 85 00:04:10,800 --> 00:04:14,960 Speaker 4: none in Europe, ajax, China, and now you've seen sovereigns 86 00:04:14,960 --> 00:04:16,880 Speaker 4: in Middle East, and for the first time in thirty years, 87 00:04:16,880 --> 00:04:17,920 Speaker 4: the US has headed China. 88 00:04:17,960 --> 00:04:18,960 Speaker 3: When it comes tack. 89 00:04:19,080 --> 00:04:22,080 Speaker 2: Your piniata on Wall Street, people love to go after 90 00:04:22,080 --> 00:04:24,680 Speaker 2: you on Twitter. It's the close. It's the act and 91 00:04:24,760 --> 00:04:27,640 Speaker 2: all that underneath it. We know, folks, not only Dan Eyes, 92 00:04:27,680 --> 00:04:31,640 Speaker 2: but webbush, there's some prodigious tech chips, like going to Asia, 93 00:04:31,800 --> 00:04:35,160 Speaker 2: like actually walking in a factory, find out what's going on. 94 00:04:35,520 --> 00:04:40,960 Speaker 2: Here's the reality for our listeners, our viewers worldwide. April three, 95 00:04:41,720 --> 00:04:46,080 Speaker 2: a leading newspaper just reporting the news. Apple Shell's shares 96 00:04:46,120 --> 00:04:49,279 Speaker 2: fell more than nine percent in response to the President's 97 00:04:49,320 --> 00:04:53,880 Speaker 2: plan for steep tariffs on products made a broad let 98 00:04:53,960 --> 00:04:56,920 Speaker 2: as sharp set off in tech stocks, which is loaded 99 00:04:56,960 --> 00:05:02,000 Speaker 2: with technology. OMG April thirds sink near six percent. Apple 100 00:05:02,200 --> 00:05:07,120 Speaker 2: is up sixty five percent, printing two to eighty yesterday. 101 00:05:07,640 --> 00:05:12,479 Speaker 2: How do our listeners in viewers digest the news and 102 00:05:12,520 --> 00:05:15,960 Speaker 2: the day to day panic and yet stay on board 103 00:05:16,200 --> 00:05:18,120 Speaker 2: this historic American path. 104 00:05:18,279 --> 00:05:20,640 Speaker 3: Look, and we've talked about so much on the show. 105 00:05:20,440 --> 00:05:22,960 Speaker 4: Over the years, right, I mean, the reality is is 106 00:05:23,000 --> 00:05:26,560 Speaker 4: that there's no bigger consumer install based in the world 107 00:05:26,600 --> 00:05:29,760 Speaker 4: than Apple two point four billion iOS devices, one point 108 00:05:29,800 --> 00:05:32,440 Speaker 4: five billion iPhones. And it comes down besides just the 109 00:05:32,520 --> 00:05:36,440 Speaker 4: cash generating machine, everything we see in services. When you 110 00:05:36,440 --> 00:05:39,360 Speaker 4: look at the AI revolution, Okay, they've looked, they've watched 111 00:05:39,400 --> 00:05:42,440 Speaker 4: it from the stands so far, but now they're about 112 00:05:42,480 --> 00:05:45,000 Speaker 4: to get into the field and actually do it and 113 00:05:45,080 --> 00:05:49,040 Speaker 4: monetize the install based the consumer AI revolution comes to Apple, 114 00:05:49,720 --> 00:05:51,360 Speaker 4: and I think that's something that we're going to see 115 00:05:51,400 --> 00:05:54,239 Speaker 4: with Google partnership and others and Tom I just continue 116 00:05:54,320 --> 00:05:57,479 Speaker 4: view it as like seventy five to one hundred hours 117 00:05:57,520 --> 00:06:00,320 Speaker 4: per share incremental will be. 118 00:06:00,320 --> 00:06:02,719 Speaker 3: Added to Apple for AI And. 119 00:06:02,560 --> 00:06:04,839 Speaker 4: That's my view, Dave David and also look at this 120 00:06:04,880 --> 00:06:07,560 Speaker 4: iPhone seventeen. It's been a surprise upgrade cycle that no 121 00:06:07,640 --> 00:06:10,600 Speaker 4: one expected with Gemini. 122 00:06:11,279 --> 00:06:14,919 Speaker 2: Is Apple under less pressure to do something this whole 123 00:06:15,200 --> 00:06:16,479 Speaker 2: do something, do something? 124 00:06:16,720 --> 00:06:20,080 Speaker 4: I'd say more pressure, but they couldn't do it till 125 00:06:20,200 --> 00:06:24,839 Speaker 4: Google ultimately won the dojsuit. Once they won the dojsuit, 126 00:06:24,920 --> 00:06:27,240 Speaker 4: that's where the candle ideenter between sun Dar and the 127 00:06:27,360 --> 00:06:31,640 Speaker 4: cook start. And I think that's that ultimately is now 128 00:06:31,720 --> 00:06:35,880 Speaker 4: where that's tracking to what can be a deal that 129 00:06:36,000 --> 00:06:38,880 Speaker 4: couldn't have been until they won that deal. And I 130 00:06:38,880 --> 00:06:41,800 Speaker 4: think that's where they're going to go. They're not buying purplexity, 131 00:06:42,120 --> 00:06:44,479 Speaker 4: They're going with Google. They're going to go down bet 132 00:06:44,560 --> 00:06:45,240 Speaker 4: heavily on them. 133 00:06:45,400 --> 00:06:47,520 Speaker 2: Then I was with Wedbush with us here on Wednesday 134 00:06:47,560 --> 00:06:50,680 Speaker 2: before Thanksgiving, is you get ready to travel, the Horde 135 00:06:50,760 --> 00:06:53,480 Speaker 2: comes over to the house. We say good morning all 136 00:06:53,520 --> 00:06:55,720 Speaker 2: the different ways you listen to us. Thank you for 137 00:06:55,839 --> 00:07:00,640 Speaker 2: discovering Bloomberg's surveillance in two thousand and twenty. Will be 138 00:07:00,640 --> 00:07:04,760 Speaker 2: your Friday, Paul Sweeney, your people. It was a big arguments. 139 00:07:04,960 --> 00:07:07,479 Speaker 2: People went back and forth. Yes, yeah, it will be 140 00:07:07,520 --> 00:07:10,360 Speaker 2: your Friday after Thanksgiving, Paul, and talk. 141 00:07:10,200 --> 00:07:11,800 Speaker 3: To us about Meta a little bit. I think that's 142 00:07:11,840 --> 00:07:14,000 Speaker 3: one of the ones the market is unsure of as 143 00:07:14,000 --> 00:07:17,200 Speaker 3: it relates to the AI play there. Stocks down about 144 00:07:17,200 --> 00:07:20,120 Speaker 3: twenty percent from its recent high, so some concerns there. 145 00:07:20,160 --> 00:07:21,160 Speaker 3: How do you position that? 146 00:07:21,400 --> 00:07:25,720 Speaker 4: I think, I mean it's a table pounder by because 147 00:07:25,760 --> 00:07:28,360 Speaker 4: the reason that stocks off is because Zuk right now 148 00:07:28,400 --> 00:07:33,000 Speaker 4: wartime CEO, focus on increasing cap backs over the next 149 00:07:33,080 --> 00:07:36,160 Speaker 4: year in his arms race, and you're and you're seeing 150 00:07:36,240 --> 00:07:39,400 Speaker 4: obviously pressure in terms of earnings and cashle but that's 151 00:07:39,800 --> 00:07:41,840 Speaker 4: that's what you want to see them do. You were 152 00:07:41,880 --> 00:07:45,280 Speaker 4: talking about monetizing the AI revolution over the coming years, 153 00:07:45,320 --> 00:07:48,720 Speaker 4: the three billion users that they basically have when it 154 00:07:48,760 --> 00:07:51,480 Speaker 4: comes to their consumer ecosism, and that's the smart move 155 00:07:51,920 --> 00:07:55,440 Speaker 4: I think right now, investors, it's very easy knee jerk 156 00:07:55,680 --> 00:07:58,560 Speaker 4: with the bury, the AI bubble, all the worries. 157 00:07:58,880 --> 00:07:59,840 Speaker 3: The reality is. 158 00:07:59,760 --> 00:08:02,080 Speaker 4: That there's two more years and weise left in this 159 00:08:02,200 --> 00:08:04,720 Speaker 4: tech ball market. You're in year three of an eight 160 00:08:04,760 --> 00:08:06,480 Speaker 4: to ten year build and it is truly a fourth 161 00:08:06,520 --> 00:08:08,840 Speaker 4: in dustrial revolution. I think Meta is going to be 162 00:08:08,880 --> 00:08:12,280 Speaker 4: proven that this is the right move what they're doing in. 163 00:08:12,200 --> 00:08:16,480 Speaker 2: The ZEITGEISTI this weekend is the partition that yes, we 164 00:08:16,560 --> 00:08:21,120 Speaker 2: appear to be using AI for search stuff In Paul 165 00:08:21,200 --> 00:08:23,040 Speaker 2: Sweeney the other day goes, should I go with the 166 00:08:23,080 --> 00:08:26,520 Speaker 2: ocean space cranberry or something homemade, you know that kind 167 00:08:26,520 --> 00:08:30,800 Speaker 2: of stuff, or like task driven AI? When do you 168 00:08:30,920 --> 00:08:36,040 Speaker 2: perceive America makes the shift to a more sophisticated use 169 00:08:36,240 --> 00:08:36,720 Speaker 2: of AI. 170 00:08:36,840 --> 00:08:39,240 Speaker 3: Yeah, it's a great qub. But today it's enterprise. 171 00:08:39,400 --> 00:08:42,680 Speaker 4: I mean, the reality is the consumer AI revolution hasn't started. 172 00:08:43,040 --> 00:08:46,320 Speaker 4: Chat GPTAM, we see that, but it's all enterprise. I mean, 173 00:08:46,640 --> 00:08:50,040 Speaker 4: this spending we're talking about called next two to three trillion, 174 00:08:50,040 --> 00:08:53,120 Speaker 4: it's just the enterprise. When it talks about consumer, it's 175 00:08:53,120 --> 00:08:56,200 Speaker 4: our autonomous humanoid robotics. 176 00:08:56,559 --> 00:08:58,800 Speaker 3: It's the future, the consum. 177 00:08:59,280 --> 00:09:03,120 Speaker 4: Goddamn robot to make my cranberry Sauce Switten, you're what's 178 00:09:03,160 --> 00:09:06,720 Speaker 4: happening again? And I continue to meet the call. Keen 179 00:09:06,880 --> 00:09:11,920 Speaker 4: will be in a rubotaxi in your the other day 180 00:09:11,720 --> 00:09:15,680 Speaker 4: that I thought Ludlow and again you never know, it 181 00:09:15,720 --> 00:09:16,480 Speaker 4: could be Ludlow. 182 00:09:16,840 --> 00:09:18,840 Speaker 3: So all right, let's go to that robotics and all 183 00:09:18,840 --> 00:09:20,480 Speaker 3: that kind of stuff, because that's kind of the story 184 00:09:20,520 --> 00:09:24,200 Speaker 3: behind teslaly these days it's not about bending steel and 185 00:09:24,200 --> 00:09:27,240 Speaker 3: making cars and things like that. So the stocks up 186 00:09:27,280 --> 00:09:29,920 Speaker 3: four percent year today, so it's really lagging the market. 187 00:09:30,480 --> 00:09:34,160 Speaker 3: It's come back from I guess the biggest concerns where 188 00:09:34,160 --> 00:09:36,719 Speaker 3: we were several months ago. But when you talk to 189 00:09:36,720 --> 00:09:38,560 Speaker 3: your institutions, our clients, what are they telling you. 190 00:09:38,760 --> 00:09:42,400 Speaker 4: I mean, it's it's all about the future. I believe 191 00:09:42,440 --> 00:09:46,480 Speaker 4: autonomous and ultimately optimists about will be the most important 192 00:09:46,559 --> 00:09:49,960 Speaker 4: chapter ever in Tesla's growth story. And I think now 193 00:09:50,400 --> 00:09:53,960 Speaker 4: must being wartime CEO have in the compackage, you know, 194 00:09:54,000 --> 00:09:59,120 Speaker 4: potentially trillion dollar men. This will now define Tesla. And 195 00:09:59,160 --> 00:10:01,600 Speaker 4: I also think you're gonn see a regulatory road map 196 00:10:01,640 --> 00:10:05,640 Speaker 4: that's going to ease when it comes to autonomous, specifically 197 00:10:05,679 --> 00:10:08,200 Speaker 4: on the robotaxi build out. You're gonna have thirty thirty 198 00:10:08,200 --> 00:10:11,000 Speaker 4: five cities, and I think WIMA is basically going to 199 00:10:11,040 --> 00:10:13,440 Speaker 4: be around the are a relative to where I see Tesla. 200 00:10:13,840 --> 00:10:16,280 Speaker 2: Let's go to our three radio stations. Good Morning ninety 201 00:10:16,320 --> 00:10:19,200 Speaker 2: two nine FM, Boston ninety nine one FM, Nathan Hager 202 00:10:19,559 --> 00:10:23,000 Speaker 2: Radio in Washington, here Bloomberg eleven three zero. How is 203 00:10:23,040 --> 00:10:27,640 Speaker 2: a robotaxi get across the Charles River right by MI 204 00:10:27,880 --> 00:10:31,000 Speaker 2: T How does a robot get turn left there and support? 205 00:10:31,520 --> 00:10:35,360 Speaker 2: How does a robotaxi get around DuPont Circle? How does 206 00:10:35,360 --> 00:10:40,400 Speaker 2: a robotaxi get down Fifth Avenue right outside the Trump Tower? 207 00:10:40,520 --> 00:10:41,280 Speaker 2: I don't get it. 208 00:10:41,640 --> 00:10:44,320 Speaker 4: Look, I mean, do you look at it? It's data driven. 209 00:10:44,360 --> 00:10:46,800 Speaker 4: I mean the reality is is that is. 210 00:10:46,760 --> 00:10:52,920 Speaker 2: Your proof of concept that they can handle normal urban traffic. 211 00:10:53,360 --> 00:10:56,600 Speaker 4: What everything I've seen, and obviously we've been there in Austin, 212 00:10:57,080 --> 00:10:59,040 Speaker 4: You're going to continue to see to expand you know, 213 00:10:59,400 --> 00:11:02,720 Speaker 4: across you know, many cities over the next few months. 214 00:11:03,120 --> 00:11:05,000 Speaker 3: I believe we're there now. 215 00:11:05,000 --> 00:11:07,400 Speaker 4: I'm not saying that there's you're gonna see the GEO 216 00:11:07,440 --> 00:11:12,000 Speaker 4: offense area continued expand, but it's my view next few years, 217 00:11:12,480 --> 00:11:15,640 Speaker 4: twenty percent of cars on the road when you're whether 218 00:11:15,679 --> 00:11:18,280 Speaker 4: it's New York City, whether it's Boston, whether scot you're 219 00:11:18,280 --> 00:11:20,640 Speaker 4: gonna look around and you're gonna and you're not gonna 220 00:11:20,679 --> 00:11:21,360 Speaker 4: see a driver. 221 00:11:21,360 --> 00:11:23,719 Speaker 2: Enough check what's your single best buy right now? Is 222 00:11:23,760 --> 00:11:25,240 Speaker 2: it matter or is something different? 223 00:11:25,360 --> 00:11:27,400 Speaker 4: I mean to me single best buy writ or is 224 00:11:27,480 --> 00:11:29,959 Speaker 4: Microsoft the relative to what we see in terms of 225 00:11:29,960 --> 00:11:30,280 Speaker 4: the stock. 226 00:11:30,440 --> 00:11:33,920 Speaker 3: I sit down because the view that. 227 00:11:34,320 --> 00:11:38,160 Speaker 4: Now Google, now Amazon and others on the hyperscale are 228 00:11:38,160 --> 00:11:40,400 Speaker 4: going to sort of eat their lunch. Gook, what's happening 229 00:11:40,480 --> 00:11:43,480 Speaker 4: Oracle as well? It just look New York City cab 230 00:11:43,600 --> 00:11:47,880 Speaker 4: driver was bearish on Alphabet Google start the year. Today 231 00:11:48,240 --> 00:11:50,920 Speaker 4: they're barish on Microsoft. And I think that's why that 232 00:11:50,960 --> 00:11:52,160 Speaker 4: has one hundred hour upside. 233 00:11:52,600 --> 00:11:59,440 Speaker 2: Okay on Microsoft just is one example. Are they open Ai? 234 00:11:59,640 --> 00:12:01,199 Speaker 2: Sam what's his name, Sam Altman? 235 00:12:01,320 --> 00:12:01,720 Speaker 3: Sam Almon? 236 00:12:02,480 --> 00:12:05,440 Speaker 2: Are they down because they're affiliated with Sam Altman? 237 00:12:05,840 --> 00:12:09,320 Speaker 4: I think, just like just like Oracle, there's that too 238 00:12:09,360 --> 00:12:13,160 Speaker 4: big to fail concept right where anyone that touches open 239 00:12:13,200 --> 00:12:16,959 Speaker 4: AI that's ultimately been an overhang. But it comes down 240 00:12:17,080 --> 00:12:19,960 Speaker 4: to like that would be like me being like, okay, 241 00:12:20,040 --> 00:12:22,920 Speaker 4: if I could have more Peter luger Steak, would I 242 00:12:23,040 --> 00:12:23,480 Speaker 4: have it? 243 00:12:23,720 --> 00:12:25,400 Speaker 3: Or would I rather own white Castle. 244 00:12:25,520 --> 00:12:28,240 Speaker 2: Actually at Bush you gotta be going pay. 245 00:12:28,200 --> 00:12:30,719 Speaker 3: Yeah again, you gotta go Lugers. But the reality is 246 00:12:30,760 --> 00:12:34,199 Speaker 3: that open AI. It's the Peter Lugers of technology. 247 00:12:34,280 --> 00:12:37,160 Speaker 4: You want to be associated with it, not not associated 248 00:12:37,240 --> 00:12:38,160 Speaker 4: those are you on YouTube? 249 00:12:38,200 --> 00:12:40,440 Speaker 2: The interns are in her ears. We got these holiday 250 00:12:40,480 --> 00:12:43,280 Speaker 2: interns and Sweeney's intern It's from Penn State. 251 00:12:43,320 --> 00:12:45,720 Speaker 3: I'm shocked we are. Nobody cares we are. 252 00:12:45,880 --> 00:12:48,200 Speaker 2: Paul Damn Penn State. Go Paul. 253 00:12:48,679 --> 00:12:49,600 Speaker 3: Who's going to be the coach? 254 00:12:49,679 --> 00:12:50,480 Speaker 5: Do you think? I mean? 255 00:12:50,520 --> 00:12:53,439 Speaker 3: Look, I think we'll see it probably Monday. Oh okay, 256 00:12:53,920 --> 00:12:54,720 Speaker 3: that was actual. 257 00:12:55,679 --> 00:12:58,280 Speaker 4: I continue to think it's you know, it's either Chesney 258 00:12:58,320 --> 00:13:02,760 Speaker 4: from JMU did that you know? Or there could be 259 00:13:02,800 --> 00:13:05,839 Speaker 4: a mystery candidate that will see how that emerged over 260 00:13:05,880 --> 00:13:06,760 Speaker 4: the coming days. 261 00:13:07,120 --> 00:13:10,199 Speaker 3: So I think a mystery candle. 262 00:13:11,880 --> 00:13:17,000 Speaker 4: Not no, not no, please, and we better days are 263 00:13:17,040 --> 00:13:19,040 Speaker 4: ahead for Pensate after a dark year. 264 00:13:19,120 --> 00:13:22,439 Speaker 2: Okay, all I asked, you're such a hitter and you're 265 00:13:22,480 --> 00:13:24,600 Speaker 2: so f one. Next time you go to F one, 266 00:13:25,080 --> 00:13:29,960 Speaker 2: take young John Farroll with you, like playing. 267 00:13:31,320 --> 00:13:34,600 Speaker 4: The reason I got into F one it was Netflix 268 00:13:34,920 --> 00:13:36,280 Speaker 4: and Farah. 269 00:13:36,000 --> 00:13:40,559 Speaker 2: Yeah yeah, yeah, I mean he he's like head to 270 00:13:40,559 --> 00:13:41,320 Speaker 2: Toad Ferrari. 271 00:13:41,520 --> 00:13:43,640 Speaker 3: Sure, I mean you know, I mean, you know that's 272 00:13:43,679 --> 00:13:44,320 Speaker 3: how you roll. 273 00:13:44,320 --> 00:13:47,240 Speaker 2: The whole Thing's where's your next f one you're going to? 274 00:13:47,520 --> 00:13:50,720 Speaker 4: I mean I have a few, but uh a few 275 00:13:50,800 --> 00:13:52,720 Speaker 4: on the docket, you know, Mid Middle. 276 00:13:52,559 --> 00:13:54,480 Speaker 3: East and and some other ones. 277 00:13:55,160 --> 00:13:57,720 Speaker 2: Dan, I thank you to extended a conversation, a lot 278 00:13:57,720 --> 00:14:00,800 Speaker 2: of good information there with his single best by the 279 00:14:00,880 --> 00:14:05,880 Speaker 2: gentleman from Microsoft. Stay with us. More from Bloomberg Surveillance 280 00:14:05,920 --> 00:14:07,280 Speaker 2: coming up after this. 281 00:14:14,520 --> 00:14:18,080 Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us live 282 00:14:18,160 --> 00:14:21,360 Speaker 1: weekday afternoons from seven to ten am Eastern. Listen on 283 00:14:21,400 --> 00:14:25,080 Speaker 1: Applecarplay and Android Auto with the Bloomberg Business app, or 284 00:14:25,200 --> 00:14:26,680 Speaker 1: watch us live on YouTube. 285 00:14:26,720 --> 00:14:29,960 Speaker 2: We got people out there, really in the trenches about 286 00:14:30,040 --> 00:14:34,320 Speaker 2: thinking of the future of retail. Tiffany joins us right 287 00:14:34,360 --> 00:14:39,120 Speaker 2: now out of pen out of Northwestern their fabulous NBA program. 288 00:14:39,520 --> 00:14:43,200 Speaker 2: She's a Boston consulting group and most she's like not 289 00:14:43,320 --> 00:14:47,000 Speaker 2: every day, but every third day at Highland Park in Dallas. Yeah, 290 00:14:47,000 --> 00:14:49,520 Speaker 2: I mean that's the way she will. Tiffany, thank you 291 00:14:49,560 --> 00:14:53,920 Speaker 2: for joining Surveillance this morning. Let's start. There is Luxury fixed, 292 00:14:54,160 --> 00:14:57,760 Speaker 2: I mean, there's this China. OMG, China is terrible, but 293 00:14:57,840 --> 00:15:01,400 Speaker 2: America is doing great double digit growth. Where does luxury 294 00:15:01,480 --> 00:15:03,120 Speaker 2: fit in for the holiday season? 295 00:15:04,640 --> 00:15:08,160 Speaker 6: Sure, luxury is one of those categories where based on 296 00:15:08,200 --> 00:15:11,400 Speaker 6: our recent survey, we are planning on seeing some recovery 297 00:15:11,520 --> 00:15:13,640 Speaker 6: during the Black Friday season. It was one of the 298 00:15:13,640 --> 00:15:17,200 Speaker 6: categories that when we surveyed across we saw increase and spend. 299 00:15:17,800 --> 00:15:19,800 Speaker 2: Black Friday used to be one hour in front of 300 00:15:19,880 --> 00:15:24,480 Speaker 2: Walmart exact thousand people and Tiffany says, it's a season helpul. 301 00:15:24,240 --> 00:15:27,720 Speaker 3: Yeah, And here's something that surprised me, Tom. In store 302 00:15:27,760 --> 00:15:32,000 Speaker 3: shopping is making a big comeback as fewer only shop online. 303 00:15:32,040 --> 00:15:34,720 Speaker 3: Tiffy talk us about that if I had never gone 304 00:15:34,720 --> 00:15:35,920 Speaker 3: to a store again, I'll be happy. 305 00:15:37,640 --> 00:15:40,400 Speaker 6: Well, what we're actually seeing is that most shoppers are 306 00:15:40,440 --> 00:15:44,000 Speaker 6: planning on shopping both in store and online this holiday season, 307 00:15:44,200 --> 00:15:45,840 Speaker 6: and the reason that they want to go back and 308 00:15:45,960 --> 00:15:49,440 Speaker 6: store is they want to touch and feel the products right, 309 00:15:49,480 --> 00:15:52,040 Speaker 6: they want to be a part of experiential retail. They 310 00:15:52,080 --> 00:15:55,200 Speaker 6: want personalized help as they shop. And it's really in 311 00:15:55,240 --> 00:15:57,320 Speaker 6: line with what we've been seeing all year long with 312 00:15:57,440 --> 00:16:00,200 Speaker 6: mall traffic continuing to come back and store per just 313 00:16:00,320 --> 00:16:04,080 Speaker 6: is coming back as well as the hybrid shopping channel, 314 00:16:04,080 --> 00:16:05,920 Speaker 6: if you will, becomes the norm. And I want to 315 00:16:05,920 --> 00:16:08,720 Speaker 6: emphasize that point on hybrid because we are really seeing 316 00:16:08,760 --> 00:16:12,800 Speaker 6: consumers grow across channels during their shopping journeys, including how 317 00:16:12,840 --> 00:16:13,680 Speaker 6: they're using AI. 318 00:16:14,280 --> 00:16:16,280 Speaker 3: All right, so talk to us about AI. Can AI 319 00:16:16,440 --> 00:16:18,720 Speaker 3: like kind of make my shopping list for me and 320 00:16:18,880 --> 00:16:20,960 Speaker 3: kind of go and buy the stuff for me. 321 00:16:22,400 --> 00:16:24,000 Speaker 2: AI can definitely do both. 322 00:16:24,080 --> 00:16:27,840 Speaker 6: Now that being said, I would say most consumers are 323 00:16:27,920 --> 00:16:32,720 Speaker 6: still using AI more in their initial shopping research and inspiration, 324 00:16:33,440 --> 00:16:37,080 Speaker 6: and we actually found that about fifty percent of consumers 325 00:16:37,160 --> 00:16:39,440 Speaker 6: plan on using AI in this holiday season. 326 00:16:39,800 --> 00:16:41,640 Speaker 2: I'm addicted to it. I did have to do a 327 00:16:41,640 --> 00:16:43,920 Speaker 2: search gyst today. You ready dark chocolate? 328 00:16:44,080 --> 00:16:44,400 Speaker 3: Okay? 329 00:16:44,520 --> 00:16:48,520 Speaker 2: I know nothing about dark chocolate. I grew up with Bosco. Yes, okay, 330 00:16:48,920 --> 00:16:53,280 Speaker 2: dark chocolate. I go to Perplexity, Tiffany, dark chocolate, Boom. 331 00:16:53,280 --> 00:16:56,880 Speaker 2: There's like three types to buy, just like that, Okay, Tiffany. 332 00:16:56,920 --> 00:17:00,600 Speaker 2: The basic BCG question and Paul brought this up yesterday. 333 00:17:00,920 --> 00:17:05,000 Speaker 2: What inning are we in for the growth of online, 334 00:17:05,119 --> 00:17:08,199 Speaker 2: for the growth of Amazon in Walmart. If it's a 335 00:17:08,200 --> 00:17:11,280 Speaker 2: baseball game Della's, does Dallas have a baseball day in 336 00:17:11,320 --> 00:17:14,840 Speaker 2: the Texas range. Oh they did, sure, Yeah, yeah, But Tiffany, 337 00:17:14,920 --> 00:17:19,480 Speaker 2: what inning are we in with our online experience? 338 00:17:21,440 --> 00:17:21,840 Speaker 7: I think it. 339 00:17:21,800 --> 00:17:23,800 Speaker 6: Depends a little bit on what angle you're looking at 340 00:17:23,840 --> 00:17:26,440 Speaker 6: it from. But if you think about where we are, 341 00:17:27,000 --> 00:17:29,080 Speaker 6: I would say we're still in the middle of the game. 342 00:17:29,400 --> 00:17:32,720 Speaker 6: Because you know, you mentioned perplexity, right, large language models 343 00:17:32,760 --> 00:17:36,320 Speaker 6: like chat GBT, they are really changing what the potential 344 00:17:36,359 --> 00:17:39,560 Speaker 6: shopping journey is and that you know, retailers have to 345 00:17:39,560 --> 00:17:42,159 Speaker 6: think about what their strategy is within that it's not 346 00:17:42,200 --> 00:17:44,920 Speaker 6: an all or nothing game, and so how they think 347 00:17:44,960 --> 00:17:47,680 Speaker 6: about you know, showing up in AI search becomes more 348 00:17:47,680 --> 00:17:48,480 Speaker 6: important than ever. 349 00:17:48,560 --> 00:17:51,760 Speaker 3: Now, how are the how are the retailers dealing with 350 00:17:52,040 --> 00:17:56,359 Speaker 3: UH tariffs here and passing along whatever cost increases they 351 00:17:56,440 --> 00:17:59,359 Speaker 3: might be bearing. Are they taking it in their margin? 352 00:17:59,400 --> 00:18:02,160 Speaker 3: Are they trying to pass along customers? How's that playing 353 00:18:02,160 --> 00:18:06,040 Speaker 3: out here? Because we don't hear as much about teriffs 354 00:18:06,080 --> 00:18:07,640 Speaker 3: as we did, you know, maybe the beginning of the year. 355 00:18:08,960 --> 00:18:12,000 Speaker 6: Yeah, I think everyone's settled into sort of this new 356 00:18:12,080 --> 00:18:14,479 Speaker 6: norm when it comes to tariffs, if you will, And 357 00:18:14,880 --> 00:18:17,560 Speaker 6: it's a mixture both definitely, right, They've taken some in 358 00:18:17,600 --> 00:18:20,760 Speaker 6: their margins, they have passed them along through and for. 359 00:18:20,680 --> 00:18:21,720 Speaker 2: This holiday season. 360 00:18:21,840 --> 00:18:24,960 Speaker 6: They know that consumers right still have expectations when it 361 00:18:25,000 --> 00:18:28,120 Speaker 6: comes to discounting promotions, right, and so they're making sure 362 00:18:28,160 --> 00:18:30,000 Speaker 6: that they can meet those expectations pretty quickly. 363 00:18:30,040 --> 00:18:32,640 Speaker 2: Or one final question. Okay, so all of us are 364 00:18:32,680 --> 00:18:36,400 Speaker 2: buying off this affirm kind of thing where it's set 365 00:18:36,400 --> 00:18:38,639 Speaker 2: out in payments. I don't know what you call it, 366 00:18:38,680 --> 00:18:41,080 Speaker 2: like a firm and you know all the others folks. 367 00:18:41,320 --> 00:18:43,560 Speaker 2: If I go into a given store, they want all 368 00:18:43,600 --> 00:18:46,199 Speaker 2: my money now or a charge card. But if I 369 00:18:46,240 --> 00:18:49,240 Speaker 2: buy online, I can spread out the payments. How is it? 370 00:18:49,240 --> 00:18:52,240 Speaker 2: Where do you see that dynamic in two years? 371 00:18:52,240 --> 00:18:56,520 Speaker 6: In five years, sure, we've seen actually a stabilization in 372 00:18:56,520 --> 00:18:59,720 Speaker 6: the buy now, pay later trend. So while there's still 373 00:18:59,720 --> 00:19:02,400 Speaker 6: a consumer and still categories that that's going to play 374 00:19:02,400 --> 00:19:05,320 Speaker 6: a meaningful role. I think we're seeing it balanced with 375 00:19:05,720 --> 00:19:07,480 Speaker 6: those desires to go in the store that I was 376 00:19:07,520 --> 00:19:09,399 Speaker 6: talking about and the benefits that you get when you 377 00:19:09,440 --> 00:19:10,040 Speaker 6: go in store. 378 00:19:10,920 --> 00:19:14,880 Speaker 2: Is Highland Park. I've never been Tiffany in Dallas. Highland 379 00:19:14,920 --> 00:19:17,920 Speaker 2: Park is like that's sort of like where they invented 380 00:19:18,320 --> 00:19:20,159 Speaker 2: one stop luxury. 381 00:19:19,680 --> 00:19:23,720 Speaker 6: Right there, we do have a really lovely shopping center 382 00:19:23,720 --> 00:19:26,159 Speaker 6: in Highland Park that has a lot of great luxury stores. 383 00:19:26,520 --> 00:19:29,720 Speaker 2: Give us one experience. Come on, come on, not using 384 00:19:29,800 --> 00:19:34,119 Speaker 2: the BCG MX, I mean, what's your favorite store? 385 00:19:35,640 --> 00:19:38,480 Speaker 6: Well, I must admit my favorite store in Highland Park 386 00:19:38,560 --> 00:19:42,720 Speaker 6: is actually a bakery. It's called Bakery, and I love 387 00:19:42,840 --> 00:19:44,520 Speaker 6: the I love the bakers there. 388 00:19:44,520 --> 00:19:45,920 Speaker 2: They make an excellent scone. 389 00:19:46,119 --> 00:19:48,240 Speaker 8: Great you get to come back in the show, Michael 390 00:19:48,240 --> 00:19:51,520 Speaker 8: Barr says, bring her back, Tiffany, thank you so much 391 00:19:51,520 --> 00:19:54,359 Speaker 8: with BCG Dallas here to get a sense of where 392 00:19:54,359 --> 00:19:56,840 Speaker 8: we are in this retail season. 393 00:19:56,920 --> 00:20:00,399 Speaker 2: It's a journey, she said, Stay with us. More Fromloomberg 394 00:20:00,520 --> 00:20:09,600 Speaker 2: Surveillance coming up after this. 395 00:20:09,600 --> 00:20:13,520 Speaker 1: This is the Bloomberg Surveillance Podcast. Listen live each weekday 396 00:20:13,520 --> 00:20:16,840 Speaker 1: starting at seven am Eastern on Applecarplay and Android Auto 397 00:20:16,960 --> 00:20:19,920 Speaker 1: with the Bloomberg Business App. You can also listen live 398 00:20:20,000 --> 00:20:23,600 Speaker 1: on Amazon Alexa from our flagship New York station, Just 399 00:20:23,640 --> 00:20:26,200 Speaker 1: say Alexa play Bloomberg eleven thirty. 400 00:20:26,640 --> 00:20:30,840 Speaker 2: For the arguments in the kitchen, out in the back porch, 401 00:20:31,720 --> 00:20:35,000 Speaker 2: at the Thanksgiving table, Sure where you're getting an evil 402 00:20:35,040 --> 00:20:40,919 Speaker 2: lie from Grandma about the market. You just wish you 403 00:20:41,000 --> 00:20:46,400 Speaker 2: were sitting at Thanksgiving with Andrew Slimman, Morgan Stanley investment manager. 404 00:20:46,840 --> 00:20:49,760 Speaker 2: He writes one of the most intelligent notes on the street. 405 00:20:49,840 --> 00:20:53,040 Speaker 2: Get it from Morgan Stanley and protect the copyright of 406 00:20:53,080 --> 00:20:57,160 Speaker 2: all our guests. And he's basically saying, forget market timing. 407 00:20:57,880 --> 00:21:02,800 Speaker 2: You have to participate in the American experiment. Andrew skrilled 408 00:21:02,840 --> 00:21:06,600 Speaker 2: to have you on the day before Thanksgiving. How do 409 00:21:06,640 --> 00:21:11,359 Speaker 2: you develop the faith and belief the conviction to own 410 00:21:11,560 --> 00:21:14,000 Speaker 2: equities after this great bull run? 411 00:21:15,920 --> 00:21:18,159 Speaker 9: Well, Tom, Before I begin, I got to say that 412 00:21:18,240 --> 00:21:20,960 Speaker 9: was the most unique introduction I've ever sived. 413 00:21:21,040 --> 00:21:24,760 Speaker 2: So congratulates worst has given me the beverage of her 414 00:21:24,840 --> 00:21:28,760 Speaker 2: choice before she's trying the mold whatever it is. I'm 415 00:21:28,880 --> 00:21:30,199 Speaker 2: here continue, Andrew. 416 00:21:30,920 --> 00:21:33,760 Speaker 9: So I'll give you the answer if I go to 417 00:21:33,800 --> 00:21:38,520 Speaker 9: my Bloomberg terminal and I look at what has worked 418 00:21:38,640 --> 00:21:44,800 Speaker 9: from a style standpoint the last ten years, value growth, dividends. 419 00:21:45,240 --> 00:21:48,840 Speaker 9: What's worked according to your bloom work, It is momentum 420 00:21:48,960 --> 00:21:52,919 Speaker 9: number one and revisions number two. Long down the list 421 00:21:53,080 --> 00:21:57,760 Speaker 9: is things like dividends, quality, value growth. It is momentum 422 00:21:57,840 --> 00:22:02,560 Speaker 9: and revisions. And the reality of the market is that 423 00:22:03,000 --> 00:22:07,640 Speaker 9: earnings i e. Revisions are very strong right now because 424 00:22:07,760 --> 00:22:12,560 Speaker 9: the economy, for all the talk, earnings have come in 425 00:22:12,720 --> 00:22:17,280 Speaker 9: better than what really Wall Street thought, certainly since April, 426 00:22:17,359 --> 00:22:20,280 Speaker 9: but even since the beginning of the year, and. 427 00:22:20,400 --> 00:22:22,000 Speaker 5: So that's the end of day. 428 00:22:22,040 --> 00:22:25,760 Speaker 9: It's a long winded way of saying stocks move with 429 00:22:26,280 --> 00:22:31,919 Speaker 9: the second derivative, which is earnings revisions, because stock prices 430 00:22:32,000 --> 00:22:35,680 Speaker 9: in bed today expectations of the future. You don't buy 431 00:22:35,720 --> 00:22:38,080 Speaker 9: a stock based on what's happened in the past. You 432 00:22:38,160 --> 00:22:41,160 Speaker 9: buy it based in the future. And if the future 433 00:22:41,359 --> 00:22:44,960 Speaker 9: looks better than what is expected, stock prices go up. 434 00:22:45,000 --> 00:22:48,399 Speaker 9: And if it's worse, Tom you know, in other words, 435 00:22:48,440 --> 00:22:51,440 Speaker 9: I've not since I've been in this business, or stocks. 436 00:22:51,080 --> 00:22:53,080 Speaker 5: Don't go up for long when. 437 00:22:52,880 --> 00:22:54,640 Speaker 9: Companies are telling you businesses is as. 438 00:22:54,560 --> 00:22:55,360 Speaker 5: Good as expected. 439 00:22:55,480 --> 00:22:59,760 Speaker 9: So what gives me faith is I see a positive 440 00:23:00,520 --> 00:23:02,000 Speaker 9: for earnings. 441 00:23:02,720 --> 00:23:05,320 Speaker 2: Bottle it. That's the single best idea today. 442 00:23:05,400 --> 00:23:08,320 Speaker 3: Just wonderfully, Andrew, Andrew, I guess we're entering I guess 443 00:23:08,359 --> 00:23:11,320 Speaker 3: what is the fourth year of this current bull market here? 444 00:23:11,520 --> 00:23:14,240 Speaker 3: So I'm sure you get the questions, how much longer 445 00:23:14,320 --> 00:23:16,320 Speaker 3: does this thing go? What do we what needs to 446 00:23:16,359 --> 00:23:18,360 Speaker 3: work to continue this bull market? What do you tell 447 00:23:18,400 --> 00:23:19,160 Speaker 3: folks these days. 448 00:23:20,080 --> 00:23:23,199 Speaker 9: Well, I certainly, certainly earnings have to keep going. The 449 00:23:23,200 --> 00:23:26,760 Speaker 9: market's not cheap at you know, twenty two times earnings. 450 00:23:26,800 --> 00:23:29,359 Speaker 9: But you know, I pushed back a little bit on 451 00:23:29,440 --> 00:23:33,240 Speaker 9: that for two reasons. Number one is, you know, the 452 00:23:33,720 --> 00:23:38,320 Speaker 9: dynamics of what comprised the S and P today is 453 00:23:38,440 --> 00:23:41,040 Speaker 9: far more profitable. Companies are far more profitful than in 454 00:23:41,119 --> 00:23:43,720 Speaker 9: the past, so versus average is a. 455 00:23:43,640 --> 00:23:46,040 Speaker 5: Little misleading, uh, you know. 456 00:23:46,080 --> 00:23:51,159 Speaker 9: And number two is again, valuations are only as powerful 457 00:23:51,359 --> 00:23:55,600 Speaker 9: as the denominated which is the estimate, and that's turned 458 00:23:55,640 --> 00:23:56,520 Speaker 9: out to be too low. 459 00:23:56,920 --> 00:23:58,040 Speaker 5: So I think. 460 00:23:57,960 --> 00:24:01,560 Speaker 9: There's a good backdrop for equities in the fourth year. 461 00:24:01,600 --> 00:24:06,399 Speaker 9: You know what's fascinating is when if a bull market 462 00:24:06,560 --> 00:24:08,720 Speaker 9: makes it to the fourth year. Now, a bull market 463 00:24:08,840 --> 00:24:10,879 Speaker 9: ends when you have a twenty percent pullback, which we 464 00:24:10,960 --> 00:24:14,680 Speaker 9: haven't had. Every time the S and P has made 465 00:24:14,680 --> 00:24:17,159 Speaker 9: it to the fourth year, it's gone up in the 466 00:24:17,160 --> 00:24:17,720 Speaker 9: fourth year. 467 00:24:17,840 --> 00:24:20,160 Speaker 5: It's never had it down year. So that's that's pretty 468 00:24:20,200 --> 00:24:24,800 Speaker 5: powerful perspective. Four equities Andrew two years ago. 469 00:24:24,920 --> 00:24:27,200 Speaker 2: Nice quote from you here, quote Why should I buy 470 00:24:27,280 --> 00:24:30,040 Speaker 2: equities when I can lock in a five percent risk 471 00:24:30,119 --> 00:24:31,400 Speaker 2: fee yield? Discuss? 472 00:24:33,200 --> 00:24:33,400 Speaker 4: Oh? 473 00:24:34,000 --> 00:24:38,639 Speaker 9: I My argument, Tom is the stock market is following 474 00:24:38,800 --> 00:24:44,520 Speaker 9: a classic behavioral path, which is unfortunately, you know that 475 00:24:44,600 --> 00:24:47,320 Speaker 9: the only consistency of this business, and you know this 476 00:24:47,680 --> 00:24:50,600 Speaker 9: bomb as well as I do, is people sell low 477 00:24:50,680 --> 00:24:54,199 Speaker 9: and they buy high. It's the only only market I 478 00:24:54,320 --> 00:24:56,720 Speaker 9: know where when prices go down people want to sell. 479 00:24:56,800 --> 00:24:59,320 Speaker 2: Well, it's just described by the investment strategy. 480 00:25:00,480 --> 00:25:05,200 Speaker 9: Well, it's a triple log cast whatever you have. But look, 481 00:25:05,440 --> 00:25:07,960 Speaker 9: in twenty twenty three, we had just come off a 482 00:25:08,240 --> 00:25:13,840 Speaker 9: twenty five percent declining. Was a wonderful opportunity by stocks. 483 00:25:14,040 --> 00:25:16,720 Speaker 5: But the reason why we had twenty five percent the 484 00:25:16,720 --> 00:25:18,479 Speaker 5: climb was man was raising rates. 485 00:25:18,520 --> 00:25:23,520 Speaker 9: So suddenly now short term rates look attractive and we 486 00:25:23,720 --> 00:25:24,920 Speaker 9: didn't want to buy equity and. 487 00:25:24,960 --> 00:25:27,280 Speaker 2: We gotta go. Are the Chicago Bears for real? 488 00:25:28,280 --> 00:25:29,800 Speaker 5: We're gonna find out tomorrow. 489 00:25:30,160 --> 00:25:32,320 Speaker 9: I know my whole family wants to watch for the 490 00:25:32,359 --> 00:25:33,560 Speaker 9: first time a few years. 491 00:25:33,560 --> 00:25:35,120 Speaker 5: So that's that could because that's. 492 00:25:34,920 --> 00:25:36,600 Speaker 2: A good thing. And just slimon, thank you so much 493 00:25:36,640 --> 00:25:40,600 Speaker 2: as Morgan stanleyder just fabulous. Note again, get that note 494 00:25:40,640 --> 00:25:44,960 Speaker 2: from Morgan, Sandy Joe, stay with us. More from Bloomberg 495 00:25:45,080 --> 00:25:54,200 Speaker 2: Surveillance coming up after this. 496 00:25:54,200 --> 00:25:58,080 Speaker 1: This is the Bloomberg Surveillance Podcast. Listen live each weekday 497 00:25:58,119 --> 00:26:01,400 Speaker 1: starting at seven am Eastern well Cocklay and Android Auto 498 00:26:01,560 --> 00:26:04,520 Speaker 1: with the Bloomberg Business App. You can also listen live 499 00:26:04,600 --> 00:26:08,159 Speaker 1: on Amazon Alexa from our flagship New York station, Just 500 00:26:08,200 --> 00:26:10,760 Speaker 1: say Alexa play Bloomberg eleven thirty. 501 00:26:11,000 --> 00:26:15,320 Speaker 2: Stephanie Chen joins us right now. She's absolutely definitive on 502 00:26:15,359 --> 00:26:19,639 Speaker 2: this at Trinity Investments, Los Angeles, and I want to 503 00:26:19,800 --> 00:26:23,399 Speaker 2: really emphasize as folks, if you go to Michigan State 504 00:26:23,680 --> 00:26:26,919 Speaker 2: in a hospitality Paul, I don't know what that's like. 505 00:26:27,160 --> 00:26:30,480 Speaker 2: It's like, you know, religion at the Vaticates or something like. 506 00:26:30,600 --> 00:26:35,240 Speaker 2: It is the program in America for the hospitality business. 507 00:26:35,480 --> 00:26:39,399 Speaker 2: Stephanie in your racket, did everybody get the growth of 508 00:26:39,520 --> 00:26:42,720 Speaker 2: luxury wrong? Did you see it coming? Or is it 509 00:26:42,800 --> 00:26:44,800 Speaker 2: like OMG, now it's here. 510 00:26:46,240 --> 00:26:49,040 Speaker 7: Yeah, No, appreciate the time and thank you for having me. 511 00:26:49,520 --> 00:26:52,080 Speaker 7: You know. I think from a luxury perspective, the trends 512 00:26:52,080 --> 00:26:55,320 Speaker 7: were always very positive, right. I think pre COVID there 513 00:26:55,359 --> 00:26:57,639 Speaker 7: was always a sense of you know, that type of 514 00:26:57,680 --> 00:27:00,320 Speaker 7: demand being there. I think as you noticed, you know, 515 00:27:00,400 --> 00:27:03,880 Speaker 7: from a post COVID environment, the need for experiences has 516 00:27:03,920 --> 00:27:07,720 Speaker 7: definitely skyrocketed. And what we've seen is you know, discretionary 517 00:27:07,800 --> 00:27:11,200 Speaker 7: spending and the want and to really kind of focus 518 00:27:11,280 --> 00:27:14,880 Speaker 7: on travel and experiences has definitely increased significantly. 519 00:27:15,119 --> 00:27:17,720 Speaker 2: What does it mean? Like like Paul's the one I 520 00:27:17,760 --> 00:27:20,920 Speaker 2: don't have a life, Stephanie Sweeney's hit every golf course 521 00:27:20,960 --> 00:27:25,000 Speaker 2: like the jew Marriott Phoenix doesert Rich? Is that in 522 00:27:25,040 --> 00:27:28,520 Speaker 2: your scout steal? Right? I mean these places have become 523 00:27:28,640 --> 00:27:32,040 Speaker 2: ginormous destinations, right, yeah. 524 00:27:31,560 --> 00:27:34,400 Speaker 7: Yeah, no, correct, And I think there's you know, these 525 00:27:34,440 --> 00:27:37,720 Speaker 7: destination what we like to call destination markets, are really 526 00:27:37,760 --> 00:27:41,639 Speaker 7: where we focus our attention just because again, like you noted, 527 00:27:41,880 --> 00:27:45,800 Speaker 7: they're just such a diverse, diversified demand base. 528 00:27:45,960 --> 00:27:46,120 Speaker 9: Right. 529 00:27:46,119 --> 00:27:48,640 Speaker 7: You have the leisure component, you have the group component, 530 00:27:48,680 --> 00:27:51,639 Speaker 7: you have the corporate component, and so I think you know, 531 00:27:51,720 --> 00:27:55,760 Speaker 7: from a leisure perspective, what's really driving customers and consumers 532 00:27:55,800 --> 00:27:59,119 Speaker 7: to travel is the experiences and what you're offering, because 533 00:27:59,160 --> 00:28:02,600 Speaker 7: I think right now what's differentiating the product is what 534 00:28:02,640 --> 00:28:05,000 Speaker 7: you can offer from an experiential perspective. 535 00:28:05,720 --> 00:28:08,640 Speaker 3: Stephanie. So we're at Trinity Investments. Where are you guys 536 00:28:08,720 --> 00:28:12,800 Speaker 3: allocating your capital in the hospitality space these days? Yeah? 537 00:28:12,840 --> 00:28:15,400 Speaker 7: So, like I noted earlier, what we like to call 538 00:28:15,480 --> 00:28:19,960 Speaker 7: destination markets whereby you know, whether that be resort, urban, 539 00:28:20,440 --> 00:28:23,359 Speaker 7: really places where you can focus a lot of the 540 00:28:23,640 --> 00:28:26,080 Speaker 7: kind of group leisure in corporate demand. So a lot 541 00:28:26,080 --> 00:28:28,359 Speaker 7: of the hotels that we focus on are let's call 542 00:28:28,400 --> 00:28:31,199 Speaker 7: it three hundred or four hundred rooms and above. And 543 00:28:31,240 --> 00:28:34,400 Speaker 7: the reason for that is because you know, there's an 544 00:28:34,480 --> 00:28:38,280 Speaker 7: ability to yield, manage the properties and kind of you know, 545 00:28:38,360 --> 00:28:42,160 Speaker 7: when the leisure component is potentially on the lower side, 546 00:28:42,200 --> 00:28:45,040 Speaker 7: you can really drive the group demand. And so a 547 00:28:45,120 --> 00:28:47,200 Speaker 7: lot of the hotels that we focus on are kind 548 00:28:47,240 --> 00:28:50,200 Speaker 7: of larger in scale as a result, and they are 549 00:28:50,280 --> 00:28:53,560 Speaker 7: typically focused and let's call it these destination markets that 550 00:28:53,640 --> 00:28:55,880 Speaker 7: really drive a lot of this type of kind of 551 00:28:55,880 --> 00:28:56,520 Speaker 7: demand base. 552 00:28:57,440 --> 00:28:59,600 Speaker 3: In New York City, for exam, I'm wondering if it's 553 00:28:59,600 --> 00:29:04,320 Speaker 3: another a lot of boutique hotels coming here with names 554 00:29:04,360 --> 00:29:07,480 Speaker 3: like you know, the Delano for example, trying to rebrand 555 00:29:07,840 --> 00:29:10,479 Speaker 3: properties here in New York and maybe brands that are 556 00:29:10,520 --> 00:29:13,080 Speaker 3: working in other parts of the world trying to bring 557 00:29:13,120 --> 00:29:15,360 Speaker 3: their brands to New York and other urban markets. How 558 00:29:15,400 --> 00:29:17,120 Speaker 3: do you guys do you invest in that? 559 00:29:18,600 --> 00:29:21,520 Speaker 7: Yeah, I mean, look, the boutique segment is definitely one 560 00:29:21,560 --> 00:29:23,560 Speaker 7: that has been quite profe and I think a lot 561 00:29:23,560 --> 00:29:25,920 Speaker 7: of that it goes back to the whole experiences, right, 562 00:29:25,960 --> 00:29:28,280 Speaker 7: and I think what the boutique segment has done really 563 00:29:28,320 --> 00:29:31,720 Speaker 7: well is to provide this different experience relative to kind 564 00:29:31,760 --> 00:29:35,880 Speaker 7: of the different niche that they're able to offer. Unfortunately, 565 00:29:35,920 --> 00:29:38,440 Speaker 7: you know, because of the scale of what we like 566 00:29:38,520 --> 00:29:41,240 Speaker 7: to focus on, and because we are value add investors, 567 00:29:41,600 --> 00:29:44,200 Speaker 7: we tend to focus on these larger assets that aren't 568 00:29:44,240 --> 00:29:47,480 Speaker 7: necessarily boutique in nature. But you're right, I mean the 569 00:29:47,560 --> 00:29:51,320 Speaker 7: trend in this boutique style type of segment is definitely 570 00:29:51,400 --> 00:29:53,800 Speaker 7: one that has picked up. And again, I think it 571 00:29:53,840 --> 00:29:57,560 Speaker 7: all goes back to experiences and people wanting to have 572 00:29:57,640 --> 00:29:59,719 Speaker 7: that differentiative type experience. 573 00:30:00,000 --> 00:30:02,520 Speaker 2: Circle back to the airlines I mentioned ed Bastian and 574 00:30:02,560 --> 00:30:06,920 Speaker 2: Delta airlines. I mean, in your world of luxury boom, 575 00:30:07,600 --> 00:30:10,880 Speaker 2: does that filter right back into the airlines where there's 576 00:30:11,280 --> 00:30:15,520 Speaker 2: fewer and fewer economy seats and more and more fancy seats. 577 00:30:16,800 --> 00:30:19,240 Speaker 7: Yeah, I mean, look, there is, and there isn't. I 578 00:30:19,240 --> 00:30:23,080 Speaker 7: would say from a supply demand fundamental perspective in the 579 00:30:23,160 --> 00:30:26,440 Speaker 7: luxury space space, it's still quite favorable, right, And what 580 00:30:26,520 --> 00:30:28,680 Speaker 7: I mean by that is there's still not a lot 581 00:30:28,760 --> 00:30:32,280 Speaker 7: of new supply relative to that kind of let's call 582 00:30:32,320 --> 00:30:36,560 Speaker 7: it luxury sector, and so what that does is obviously 583 00:30:36,720 --> 00:30:39,920 Speaker 7: deem really well from a fundamentals perspective for the existing 584 00:30:39,960 --> 00:30:43,680 Speaker 7: hotels and kind of the segment. So I think the 585 00:30:43,720 --> 00:30:46,760 Speaker 7: supply demand fundamentals, there's still a demand for that, right, 586 00:30:46,800 --> 00:30:49,320 Speaker 7: and we see it from a RevPAR revenue per available 587 00:30:49,400 --> 00:30:52,920 Speaker 7: room performance standpoint, whereby it, you know, through your date 588 00:30:53,000 --> 00:30:57,320 Speaker 7: October of twenty twenty five, RevPAR continues to grow, particularly 589 00:30:57,360 --> 00:30:59,840 Speaker 7: in the luxury and upper up scale segment, and it's 590 00:31:00,240 --> 00:31:02,520 Speaker 7: really kind of like, let's call it the low twenty 591 00:31:02,560 --> 00:31:06,160 Speaker 7: percent improvement relative to where we were in twenty nineteen. 592 00:31:06,960 --> 00:31:09,720 Speaker 7: So I think what that suggests is that consumer is 593 00:31:09,760 --> 00:31:12,760 Speaker 7: still there and wanting to pay that price have that 594 00:31:12,880 --> 00:31:17,480 Speaker 7: type of experience and quality. So yeah, I think that 595 00:31:17,680 --> 00:31:21,760 Speaker 7: the supply and demand fundamentals, however, are still quite favorable 596 00:31:22,480 --> 00:31:26,320 Speaker 7: because there is not a ton of newsify within that sector. 597 00:31:26,400 --> 00:31:29,600 Speaker 2: Stephanie, thank you so much. Stephanie Chen with is Trinity Investments, 598 00:31:29,680 --> 00:31:30,440 Speaker 2: Los Angeles. 599 00:31:30,440 --> 00:31:35,800 Speaker 1: Here this is the Bloomberg Surveillance podcast, available on Apple, Spotify, 600 00:31:35,920 --> 00:31:39,680 Speaker 1: and anywhere else you get your podcasts. 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