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 --> 00:00:21,240 Speaker 1: on Apple car Play or Android Auto with the Bloomberg 4 00:00:21,320 --> 00:00:24,880 Speaker 1: Business App. Listen on demand wherever you get your podcasts, 5 00:00:25,280 --> 00:00:27,040 Speaker 1: or watch us live on YouTube. 6 00:00:27,480 --> 00:00:30,120 Speaker 2: Our next guest, Sarah Hunt joins is chief market strategist 7 00:00:30,160 --> 00:00:32,320 Speaker 2: for Alpine Saxon, which he joins us here in our studio. 8 00:00:32,360 --> 00:00:34,839 Speaker 2: Thank you so much for joining us. Sarah, You've got 9 00:00:34,840 --> 00:00:37,159 Speaker 2: a nice note in your line in your notes that 10 00:00:37,200 --> 00:00:40,800 Speaker 2: I really like from quote you're not spending enough too. Wow, 11 00:00:40,840 --> 00:00:43,559 Speaker 2: that's a lot of Capex. Was a short trip. We 12 00:00:43,640 --> 00:00:47,880 Speaker 2: did see a little bit of, I guess concern this week. 13 00:00:47,920 --> 00:00:52,280 Speaker 2: We had Google up their Capex stock trades up. Meta 14 00:00:52,360 --> 00:00:56,400 Speaker 2: ups their Capex stock trades down dramatically, So not all 15 00:00:56,440 --> 00:00:58,639 Speaker 2: Capex is the same. What are we learning here? 16 00:00:58,960 --> 00:01:01,360 Speaker 3: I think it's showing you that there's a question really 17 00:01:01,440 --> 00:01:03,720 Speaker 3: about who's going to be able to put that Capex 18 00:01:03,760 --> 00:01:06,039 Speaker 3: to most effective use. And I think unfortunately for Meta, 19 00:01:06,080 --> 00:01:08,760 Speaker 3: because they've had some issues in the past spending a 20 00:01:08,760 --> 00:01:11,160 Speaker 3: lot of money where it didn't always come to fruition, 21 00:01:11,600 --> 00:01:13,600 Speaker 3: I think they have more of a penalty box than 22 00:01:13,600 --> 00:01:16,399 Speaker 3: some of the other players in the space. And I think, 23 00:01:16,720 --> 00:01:22,119 Speaker 3: I mean, the Capex boom has been so dramatic that 24 00:01:22,240 --> 00:01:24,840 Speaker 3: the fear then becomes what happens when the second derivative 25 00:01:24,959 --> 00:01:26,959 Speaker 3: goes negative. Right, it's up, but it's not up as 26 00:01:27,040 --> 00:01:29,759 Speaker 3: much as it was last year, and right now that's 27 00:01:29,920 --> 00:01:32,119 Speaker 3: not as much of a problem, but it's coming as 28 00:01:32,120 --> 00:01:34,840 Speaker 3: the law of large numbers gets larger and larger, and 29 00:01:34,880 --> 00:01:36,840 Speaker 3: the question is going to start to become what are 30 00:01:36,880 --> 00:01:38,360 Speaker 3: you getting for that Capex? 31 00:01:38,440 --> 00:01:39,520 Speaker 2: And if margins are. 32 00:01:39,440 --> 00:01:41,200 Speaker 3: Going to be affected, then people are going to be 33 00:01:41,200 --> 00:01:43,480 Speaker 3: a little less excited than they were when it looked 34 00:01:43,520 --> 00:01:45,760 Speaker 3: like that Capex was going to drive margins. So I 35 00:01:45,760 --> 00:01:48,040 Speaker 3: think that's the tension right now, that's what people are 36 00:01:48,040 --> 00:01:48,680 Speaker 3: trying to figure out. 37 00:01:48,760 --> 00:01:50,160 Speaker 4: Yeah, and in your note, I liked how you said 38 00:01:50,200 --> 00:01:52,400 Speaker 4: it's going to be about show me the money right 39 00:01:52,440 --> 00:01:55,880 Speaker 4: when it comes to Capex spending on AI, let's talk 40 00:01:55,880 --> 00:01:58,000 Speaker 4: about the names that are not beating. Some of the 41 00:01:58,040 --> 00:02:02,360 Speaker 4: companies that are not Wall Street disappointing on either the top, 42 00:02:02,360 --> 00:02:07,120 Speaker 4: bottom or both lines. They're really getting beaten up. Do 43 00:02:07,160 --> 00:02:09,240 Speaker 4: you think it's being a little overdone when you look 44 00:02:09,240 --> 00:02:10,440 Speaker 4: at those individual names. 45 00:02:10,639 --> 00:02:12,560 Speaker 3: If I want to add to the things that go 46 00:02:12,639 --> 00:02:14,720 Speaker 3: on the wall of worry, the fact that stocks can 47 00:02:14,720 --> 00:02:17,120 Speaker 3: get cut in half for bad news as opposed to 48 00:02:17,160 --> 00:02:19,799 Speaker 3: down ten or fifteen percent. It seems to me one 49 00:02:19,840 --> 00:02:22,400 Speaker 3: of those things where there's very much of a knee 50 00:02:22,480 --> 00:02:25,040 Speaker 3: jerk reaction and there's a wholesale selling and there's not 51 00:02:25,200 --> 00:02:27,440 Speaker 3: a lot of looking into what's wrong. Now, in some 52 00:02:27,520 --> 00:02:30,120 Speaker 3: cases there were things that were wrong, people have cut guidance. 53 00:02:30,120 --> 00:02:32,680 Speaker 3: I mean, I'm looking at companies like FMC or five 54 00:02:32,720 --> 00:02:35,079 Speaker 3: Serve where there were big issues going on, but those 55 00:02:35,120 --> 00:02:37,480 Speaker 3: are really big moves, and those kind of moves I 56 00:02:37,520 --> 00:02:40,040 Speaker 3: think are a little bit should warn you that there 57 00:02:40,040 --> 00:02:42,840 Speaker 3: could be more volatility ahead, because that is more than 58 00:02:42,880 --> 00:02:45,880 Speaker 3: you usually get even for problems within an earning season. 59 00:02:45,960 --> 00:02:48,880 Speaker 4: So does that tell you that investors are just looking 60 00:02:48,880 --> 00:02:50,480 Speaker 4: for a reason to get out. 61 00:02:51,160 --> 00:02:54,399 Speaker 3: I think it's almost like there's either either it's over 62 00:02:54,480 --> 00:02:56,720 Speaker 3: owned for some reason or people are just getting out 63 00:02:56,760 --> 00:02:58,240 Speaker 3: to say I want to go back to this, or 64 00:02:58,280 --> 00:03:00,080 Speaker 3: I just want to get out of that. But some 65 00:03:00,120 --> 00:03:01,800 Speaker 3: of them are not the big tech companies. I mean, 66 00:03:01,840 --> 00:03:04,359 Speaker 3: met as the exception for this earning season so far. 67 00:03:04,680 --> 00:03:06,480 Speaker 3: But I think that that is a little bit worrying 68 00:03:06,480 --> 00:03:09,359 Speaker 3: to see that much volatility in names where you shouldn't 69 00:03:09,360 --> 00:03:10,920 Speaker 3: expect to see that much volatility. 70 00:03:11,080 --> 00:03:12,760 Speaker 2: And one of the ones yesterday that kind of got 71 00:03:12,800 --> 00:03:14,560 Speaker 2: my attention was because it's near and dear to my 72 00:03:14,600 --> 00:03:18,360 Speaker 2: heart is Chipotle. Actually, I stock got crushed yesterday on 73 00:03:18,440 --> 00:03:21,959 Speaker 2: some bad numbers, and that's my Wednesday go to right. 74 00:03:22,040 --> 00:03:23,640 Speaker 2: I mean, you go to the one on Third Avenue 75 00:03:23,639 --> 00:03:25,960 Speaker 2: and they do a great job. So I was little well, 76 00:03:25,960 --> 00:03:26,480 Speaker 2: and that's the. 77 00:03:26,440 --> 00:03:29,040 Speaker 3: Concern about you know, you've got to cut earnings three 78 00:03:29,080 --> 00:03:31,359 Speaker 3: times in a row, and or those prices and those 79 00:03:31,400 --> 00:03:33,919 Speaker 3: costs are going up faster than you anticipated that they were. 80 00:03:34,080 --> 00:03:36,160 Speaker 3: I mean, I don't know if that is individual to 81 00:03:36,200 --> 00:03:37,920 Speaker 3: them where they didn't have a handle on it, or 82 00:03:37,920 --> 00:03:39,880 Speaker 3: if it just kept the bad news just kept coming. 83 00:03:40,120 --> 00:03:41,400 Speaker 2: But that's that's. 84 00:03:41,160 --> 00:03:43,600 Speaker 3: Also something where the underlying is Peter Cheer was just 85 00:03:43,600 --> 00:03:46,480 Speaker 3: saying before some of those tariffs, some of those impacts 86 00:03:46,480 --> 00:03:48,680 Speaker 3: are coming next year. They're not here yet, and we 87 00:03:48,760 --> 00:03:51,120 Speaker 3: have this sort of feeling that it's all okay, and 88 00:03:51,200 --> 00:03:53,280 Speaker 3: I have concerns that going into next year you're going 89 00:03:53,320 --> 00:03:53,640 Speaker 3: to see some. 90 00:03:53,640 --> 00:03:55,800 Speaker 2: More of that. We had Michael Halen on yesterday. He's 91 00:03:55,840 --> 00:03:58,520 Speaker 2: the restaurant analyst or of Bloomberg Intelligence, and he called 92 00:03:58,520 --> 00:04:01,400 Speaker 2: out the company big time. He says, for them to 93 00:04:01,440 --> 00:04:05,000 Speaker 2: blame the economy is not accurate because all their peers 94 00:04:05,040 --> 00:04:07,440 Speaker 2: are doing pretty darn well. So he called it out 95 00:04:07,440 --> 00:04:10,559 Speaker 2: as a company thing, and he heard from the company yesterday. 96 00:04:10,360 --> 00:04:14,960 Speaker 2: So where are we going here as we think about 97 00:04:14,960 --> 00:04:18,680 Speaker 2: twenty twenty six, Sarah Boom. We're turning in the calendar 98 00:04:18,720 --> 00:04:21,880 Speaker 2: on November tomorrow. What are we thinking for twenty twenty 99 00:04:21,880 --> 00:04:22,400 Speaker 2: six here? 100 00:04:22,880 --> 00:04:23,040 Speaker 5: Well? 101 00:04:23,080 --> 00:04:25,679 Speaker 3: I think that. So there's the plus side for twenty 102 00:04:25,680 --> 00:04:29,080 Speaker 3: twenty six is you've got some fiscal stimulus, arguably with 103 00:04:29,200 --> 00:04:31,760 Speaker 3: what happened with the legislation that was try asked, you've 104 00:04:31,800 --> 00:04:34,800 Speaker 3: got and the tension is that you've got the trade 105 00:04:35,160 --> 00:04:37,760 Speaker 3: situation where you're finally going to start seeing some of that. 106 00:04:37,880 --> 00:04:39,720 Speaker 3: It's going to be about earnings. It's going to be 107 00:04:39,760 --> 00:04:41,960 Speaker 3: about margins. You're already seeing some of the big tech 108 00:04:41,960 --> 00:04:44,839 Speaker 3: companies lay people off, so that's also I think about margins. 109 00:04:44,839 --> 00:04:47,080 Speaker 3: No matter how you want to slice that. If Amazon 110 00:04:47,120 --> 00:04:49,200 Speaker 3: is saying, well we have too much, well you didn't 111 00:04:49,200 --> 00:04:51,599 Speaker 3: have too much last year. So it's going to be 112 00:04:51,640 --> 00:04:52,359 Speaker 3: a margin issue. 113 00:04:52,400 --> 00:04:54,160 Speaker 2: If you know what's interesting about Amazon edged I just 114 00:04:54,360 --> 00:04:56,760 Speaker 2: was just reading they had about seven hundred and fifty 115 00:04:56,760 --> 00:04:59,760 Speaker 2: thousand employees in twenty nineteen. They came out of twenty 116 00:05:00,240 --> 00:05:02,280 Speaker 2: and they have one point five million now. So they 117 00:05:02,480 --> 00:05:06,440 Speaker 2: edited during the pandemic, a pandemic as we all did 118 00:05:06,520 --> 00:05:09,720 Speaker 2: much more e shopping, And so I guess are they 119 00:05:09,839 --> 00:05:12,919 Speaker 2: liking a couple two, three, four hundred thousand people out? Maybe? 120 00:05:13,080 --> 00:05:13,520 Speaker 2: I don't know. 121 00:05:13,800 --> 00:05:17,239 Speaker 3: Well, I just think it speaks to markets are driven 122 00:05:17,240 --> 00:05:21,160 Speaker 3: by earnings, ns are driven by margins. The AI revolution 123 00:05:21,240 --> 00:05:23,560 Speaker 3: that is supposed to add productivity, what does that really mean, Well, 124 00:05:23,560 --> 00:05:26,279 Speaker 3: it generally means that there's less people working, so there's 125 00:05:26,279 --> 00:05:28,960 Speaker 3: an issue. There's another tension there. How that all plays 126 00:05:29,000 --> 00:05:30,159 Speaker 3: out through twenty twenty six. 127 00:05:30,080 --> 00:05:31,800 Speaker 2: Is going to matter a lot. Night, Sarah, thank you 128 00:05:31,800 --> 00:05:34,240 Speaker 2: so much for joining us. We always appreciate having you 129 00:05:34,240 --> 00:05:36,520 Speaker 2: come in our studios here. Sarah Hunt, chief market strategists 130 00:05:36,520 --> 00:05:39,040 Speaker 2: for Alpine Saxon Woods, stay with us. More from Bloomberg 131 00:05:39,080 --> 00:05:40,760 Speaker 2: Surveillance coming up after this. 132 00:05:46,960 --> 00:05:50,560 Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us live 133 00:05:50,640 --> 00:05:53,800 Speaker 1: weekday afternoons from seven to ten am. Eastern Listen on 134 00:05:53,880 --> 00:05:57,520 Speaker 1: Applecarplay and Android Auto with the Bloomberg Business app, or 135 00:05:57,680 --> 00:05:59,200 Speaker 1: watch us live on YouTube. 136 00:05:59,279 --> 00:06:01,760 Speaker 2: This is how you when you're a gentleman on a 137 00:06:01,760 --> 00:06:06,279 Speaker 2: certain agent Wall Street Friday, blue jeans, popper shirt, blue 138 00:06:06,320 --> 00:06:10,279 Speaker 2: blazer solid. I love it. This guy comes in and 139 00:06:10,320 --> 00:06:13,279 Speaker 2: blows up the entire studio. I mean there were clashing 140 00:06:13,320 --> 00:06:15,320 Speaker 2: in so many different directions. I don't even know where 141 00:06:15,360 --> 00:06:17,480 Speaker 2: to go. But Dan Ives is here. He does all 142 00:06:17,520 --> 00:06:19,920 Speaker 2: the tech stuff for wet Bush Securities. Dan, you've been 143 00:06:19,920 --> 00:06:22,400 Speaker 2: busy this week. We've had a ton of tech earnings. 144 00:06:22,600 --> 00:06:25,359 Speaker 2: I just want to start with Apple last night. The 145 00:06:25,400 --> 00:06:27,480 Speaker 2: iPhone seventeen is a thing, isn't it. 146 00:06:27,520 --> 00:06:30,560 Speaker 6: Look it's a surprise upgrade cycle. I mean that's the reality. 147 00:06:30,640 --> 00:06:32,880 Speaker 6: And for so long we've always talked about, you know, 148 00:06:33,120 --> 00:06:36,719 Speaker 6: these upgrade cycles, a potential supercycle, and this is a 149 00:06:36,760 --> 00:06:39,400 Speaker 6: surprise upgrade cycle. And I think especially what we're seeing 150 00:06:39,440 --> 00:06:43,160 Speaker 6: in China, well, China was a decliner. Now you start 151 00:06:43,200 --> 00:06:46,279 Speaker 6: to see that increasing year of a year. That's something 152 00:06:46,360 --> 00:06:49,520 Speaker 6: streets coming up in terms of numbers. The New York 153 00:06:49,600 --> 00:06:52,760 Speaker 6: City cab driver's embarrassment Apple last six nine months, so 154 00:06:52,800 --> 00:06:56,440 Speaker 6: that's this is a bullish scenario, especially leading into what 155 00:06:56,520 --> 00:06:59,120 Speaker 6: I believe now will be the year of AI. Ultimately 156 00:06:59,200 --> 00:07:03,680 Speaker 6: Google partners for Apple seventy five hundred dollars. 157 00:07:01,800 --> 00:07:05,839 Speaker 2: To go back to that, What is Apple's AI strategy 158 00:07:06,000 --> 00:07:08,200 Speaker 2: going to be or should be? Do you think today? 159 00:07:08,400 --> 00:07:09,800 Speaker 2: It's invisible? Right today? 160 00:07:09,800 --> 00:07:12,640 Speaker 6: In the AI party that started at nine pm, it's 161 00:07:12,680 --> 00:07:15,640 Speaker 6: now ten thirty pm. That party goes to four am, 162 00:07:16,160 --> 00:07:18,480 Speaker 6: cook an Apple. They're on the outside, looking behind the 163 00:07:18,560 --> 00:07:20,880 Speaker 6: velvet ropes. They're looking through the party through the window. 164 00:07:21,360 --> 00:07:24,160 Speaker 6: But what I believe they're going to do now once 165 00:07:24,240 --> 00:07:27,920 Speaker 6: Google won that DOJ suit, that clears the road for 166 00:07:28,000 --> 00:07:31,800 Speaker 6: them to do a significant Gemini partnership where ultimately the 167 00:07:31,920 --> 00:07:35,119 Speaker 6: consumer AI revolution goes through Cooper Tino. 168 00:07:35,680 --> 00:07:38,120 Speaker 4: Well, look, we're talking AI spend. We've got to talk 169 00:07:38,200 --> 00:07:40,760 Speaker 4: Meta because they're the complete opposite of Apple. Right, they're 170 00:07:40,800 --> 00:07:43,480 Speaker 4: just throwing the kitchen sink at AI right now. But 171 00:07:43,560 --> 00:07:46,720 Speaker 4: Wall Street are they approving of the spending Meta is 172 00:07:46,880 --> 00:07:47,880 Speaker 4: doing in that space? 173 00:07:48,080 --> 00:07:50,720 Speaker 6: Look, in my opinion, it's a table pounder when that 174 00:07:50,840 --> 00:07:53,800 Speaker 6: stocks sold off Yestad, because my whole view is this 175 00:07:53,840 --> 00:07:57,360 Speaker 6: is an AI arms race. You want companies to spend now, Look, 176 00:07:57,440 --> 00:08:00,560 Speaker 6: free cash for earnings obviously gets hit. But the reality 177 00:08:00,680 --> 00:08:03,600 Speaker 6: is is that this is a fourth Industrial Revolution, and 178 00:08:03,680 --> 00:08:06,680 Speaker 6: you want all these coming from Microsoft to Google to 179 00:08:06,880 --> 00:08:08,680 Speaker 6: Meta to what we see with Amazon. 180 00:08:09,000 --> 00:08:10,160 Speaker 2: But guess what they're. 181 00:08:10,040 --> 00:08:14,120 Speaker 6: Fueling the AI revolution. That's obviously bullish for Nvidia, AMD 182 00:08:14,200 --> 00:08:16,960 Speaker 6: and others. I love what Meta's doing. I think it's 183 00:08:16,960 --> 00:08:19,280 Speaker 6: a four digit stock, and I think what you're seeing 184 00:08:19,320 --> 00:08:23,640 Speaker 6: now it's spreading. Look at Amazon. Finally, Jassey saying, don't 185 00:08:23,680 --> 00:08:27,880 Speaker 6: forget about us. It just shows in streak continues to 186 00:08:27,960 --> 00:08:32,280 Speaker 6: underestimate the scope and scale of this fourth Industrial Revolution. 187 00:08:33,400 --> 00:08:36,800 Speaker 2: So and Alexi saw yesterday Meta the stock did sell off. 188 00:08:36,840 --> 00:08:39,560 Speaker 2: They went out and I sold thirty billion dollars worth 189 00:08:39,600 --> 00:08:42,000 Speaker 2: of bonds one hundred and twenty five billion dollars Demand one. 190 00:08:42,120 --> 00:08:46,040 Speaker 2: I was doing that business a five or ten billion 191 00:08:46,040 --> 00:08:49,200 Speaker 2: dollar deals were monster, right, thirty billion and I bet 192 00:08:49,280 --> 00:08:51,240 Speaker 2: you had made five phone calls LA last night and 193 00:08:51,240 --> 00:08:53,400 Speaker 2: sold that deal. Believe I bet you that's what happened. Dan, 194 00:08:53,440 --> 00:08:55,720 Speaker 2: talk to us about Amazon, boy that the stocks up 195 00:08:55,760 --> 00:08:58,560 Speaker 2: twelve percent pre market trading. Here, talk to us about 196 00:08:58,720 --> 00:09:03,120 Speaker 2: where they are with their cloud business. Visa v Microsoft, 197 00:09:03,200 --> 00:09:07,520 Speaker 2: Visa v Google. Where's the cloud horizon for Amazon for 198 00:09:07,559 --> 00:09:08,640 Speaker 2: the last few years. 199 00:09:08,760 --> 00:09:10,920 Speaker 6: Right, if you look at the top of that mountain, 200 00:09:11,120 --> 00:09:13,800 Speaker 6: it's Microsoft in the della and then of course Google 201 00:09:13,800 --> 00:09:15,920 Speaker 6: what they've been done with GCP, and that's been huge, 202 00:09:15,960 --> 00:09:18,480 Speaker 6: the rerating that we've seen with Google. But if you 203 00:09:18,480 --> 00:09:21,400 Speaker 6: look at Amazon outside, looking at right, I mean Jase, 204 00:09:21,480 --> 00:09:24,959 Speaker 6: even though he's in AWSK, really anthropics been the opportunity 205 00:09:25,559 --> 00:09:28,800 Speaker 6: underwhelming last night. I think it's an inflection point quarter 206 00:09:28,840 --> 00:09:31,600 Speaker 6: for Amazon. I think this now is going to change 207 00:09:31,640 --> 00:09:33,920 Speaker 6: the view of Amazon when it comes to the. 208 00:09:33,840 --> 00:09:35,560 Speaker 2: Cloudiest cool some of the parts. 209 00:09:35,600 --> 00:09:37,880 Speaker 6: That's how you get the three forty three and fifty 210 00:09:37,880 --> 00:09:41,040 Speaker 6: dollars stock And this is a very very important quarter 211 00:09:41,280 --> 00:09:44,440 Speaker 6: for the two mag seventy. If you the Apple and 212 00:09:44,520 --> 00:09:47,600 Speaker 6: Amazon both sort of like they're sitting at the table 213 00:09:47,640 --> 00:09:50,280 Speaker 6: by the kitchen, like at the wedding, like with the 214 00:09:50,400 --> 00:09:52,960 Speaker 6: random friends they get put that random table. 215 00:09:53,400 --> 00:09:56,760 Speaker 2: They want to be at the cool table. Now they're there. 216 00:09:57,240 --> 00:09:59,400 Speaker 4: Look, there's so much to talk about with Dan ives, right, 217 00:09:59,440 --> 00:10:00,880 Speaker 4: because you just I just I want to tick through 218 00:10:01,120 --> 00:10:03,560 Speaker 4: some of these things we have you here in studio Tesla. 219 00:10:04,520 --> 00:10:08,199 Speaker 4: Are these shareholders going to vote for this huge compensation package? 220 00:10:08,240 --> 00:10:09,480 Speaker 4: November six or elon Musk. 221 00:10:09,559 --> 00:10:12,880 Speaker 6: There's a better chance to me not eating chocolate sour 222 00:10:12,960 --> 00:10:15,840 Speaker 6: Patch kids tonight. Then this thing actually getting voted down. 223 00:10:15,880 --> 00:10:17,480 Speaker 6: I mean, the point is this thing is getting one 224 00:10:17,559 --> 00:10:21,760 Speaker 6: hundred percent getting voted for. The reality is that Musk 225 00:10:21,880 --> 00:10:25,800 Speaker 6: is Tesla. Tesla is Musk. He's a wartime CEO right now. 226 00:10:25,880 --> 00:10:27,880 Speaker 2: You need him in this AI chapter. 227 00:10:28,559 --> 00:10:31,160 Speaker 6: And then also I think they'll they're gonna vote for 228 00:10:31,200 --> 00:10:35,960 Speaker 6: the XAI ownership piece, which speaks to Tesla isn't a 229 00:10:36,120 --> 00:10:39,080 Speaker 6: on it. It is an autonomous and robotics play. It 230 00:10:39,200 --> 00:10:41,800 Speaker 6: is not about deliveries. In my opinion, I think that's 231 00:10:41,840 --> 00:10:44,680 Speaker 6: why this is so important for shareholders when it comes 232 00:10:44,679 --> 00:10:45,120 Speaker 6: to Musk. 233 00:10:45,440 --> 00:10:47,240 Speaker 2: All Right, we got it before, we let you go, 234 00:10:48,400 --> 00:10:52,000 Speaker 2: Happy Valley. Turbulent times in Happy Valley, Penn State, we 235 00:10:52,640 --> 00:10:55,720 Speaker 2: don't have a coach, but boy, is that a good seat. 236 00:10:55,960 --> 00:10:57,400 Speaker 2: What do you think Penn State's going to do in 237 00:10:57,480 --> 00:10:58,080 Speaker 2: terms of hiring it. 238 00:10:58,120 --> 00:11:00,559 Speaker 6: Look, in my opinion, it's the number Obviously you could 239 00:11:00,600 --> 00:11:03,400 Speaker 6: say bias. I think, especially after the LSU Governors team, 240 00:11:03,640 --> 00:11:06,040 Speaker 6: I think it's the number one coaching spine all of 241 00:11:06,080 --> 00:11:11,480 Speaker 6: college football above Florida to me, you know, Paccraft there's 242 00:11:11,559 --> 00:11:13,880 Speaker 6: no better athletic director I think right now in the 243 00:11:13,920 --> 00:11:16,120 Speaker 6: world than him, And I think they're going to go 244 00:11:16,200 --> 00:11:18,920 Speaker 6: for Elka at Texas A and M I think you go 245 00:11:19,000 --> 00:11:22,720 Speaker 6: for Clark Lee at Vanderbilt, manny DA, potentially Brahm and 246 00:11:22,760 --> 00:11:25,920 Speaker 6: others there. Look, this is it's obviously been a very 247 00:11:26,040 --> 00:11:29,440 Speaker 6: very you know, disaster year, but it's our view we 248 00:11:29,600 --> 00:11:31,880 Speaker 6: need the right person to ultimately take us to the 249 00:11:31,920 --> 00:11:32,520 Speaker 6: next level. 250 00:11:32,800 --> 00:11:34,440 Speaker 2: There you go. Dan, I is very He's a proud 251 00:11:34,480 --> 00:11:37,720 Speaker 2: Penn State alum, very involved in the athletic department there 252 00:11:37,760 --> 00:11:40,480 Speaker 2: at Penn State. And I think he also does some 253 00:11:40,559 --> 00:11:42,560 Speaker 2: tech research on and he looks. 254 00:11:42,360 --> 00:11:44,880 Speaker 4: Like Florida, the state of Florida walking. 255 00:11:44,800 --> 00:11:47,440 Speaker 2: Badly, badly. It's a total sign there. 256 00:11:47,840 --> 00:11:50,360 Speaker 6: Guys like Sweeney, they're the ones that give out the 257 00:11:50,520 --> 00:11:55,800 Speaker 6: full chocolate bar for Halloween. So that remember that continues 258 00:11:55,840 --> 00:11:57,920 Speaker 6: to be you know, obviously someone. 259 00:11:57,600 --> 00:12:00,360 Speaker 2: That are many, none of the many, and we can't 260 00:12:00,360 --> 00:12:02,880 Speaker 2: see you can't do. Dan, thanks so much for joining us. 261 00:12:02,880 --> 00:12:04,760 Speaker 2: We really appreciate it. Dan Ive's global head of tech 262 00:12:04,800 --> 00:12:07,600 Speaker 2: research and Webush Securities. Stay with us. More from Bloomberg 263 00:12:07,600 --> 00:12:09,319 Speaker 2: Surveillance coming up after this. 264 00:12:15,520 --> 00:12:19,120 Speaker 1: You're listening to the Bloomberg Surveillance Podcast. Catch us live 265 00:12:19,160 --> 00:12:22,320 Speaker 1: weekday afternoons from seven to ten am Eastern. Listen on 266 00:12:22,400 --> 00:12:26,080 Speaker 1: Applecarplay and Android Auto with the Bloomberg Business app, or 267 00:12:26,240 --> 00:12:27,679 Speaker 1: watch us live on YouTube. 268 00:12:27,840 --> 00:12:29,880 Speaker 2: That brings us to Peter Cheer. We want to get 269 00:12:29,920 --> 00:12:31,480 Speaker 2: a sense of what we're doing with this Marketer. He's 270 00:12:31,480 --> 00:12:34,480 Speaker 2: had a macro strategy at Academy Securities, and I'm guessing 271 00:12:34,600 --> 00:12:39,560 Speaker 2: he is a Patriots fan. Yeah, okay, and they're back 272 00:12:39,640 --> 00:12:41,760 Speaker 2: by the way for what it's true, you know, and 273 00:12:41,760 --> 00:12:43,360 Speaker 2: not being a Patriots fan. If Peter, what do you 274 00:12:43,400 --> 00:12:45,200 Speaker 2: make of this market? We were just talking to Dan 275 00:12:45,280 --> 00:12:48,120 Speaker 2: Ives and web bullshavette all the spending that we're seeing 276 00:12:48,160 --> 00:12:50,960 Speaker 2: a lot of these tech companies do on artificial intelligence, 277 00:12:51,000 --> 00:12:54,800 Speaker 2: and I think people are supportive of it, but at 278 00:12:54,800 --> 00:12:57,120 Speaker 2: the same time a little bit wary because these numbers 279 00:12:57,120 --> 00:13:00,400 Speaker 2: are numbers we've never seen before from any industry. 280 00:13:00,640 --> 00:13:03,000 Speaker 5: So that basically describes me to a t so, which 281 00:13:03,040 --> 00:13:05,000 Speaker 5: is why we've been really focusing our investment on what 282 00:13:05,000 --> 00:13:08,280 Speaker 5: we've been calling production for security, and we're really looking 283 00:13:08,400 --> 00:13:11,640 Speaker 5: at areas that are going to benefit from a real 284 00:13:11,760 --> 00:13:14,720 Speaker 5: focus on growth of domestic business. 285 00:13:14,800 --> 00:13:17,200 Speaker 2: I think electricity production is a huge part of that. 286 00:13:17,280 --> 00:13:20,640 Speaker 5: Right, if you look wherever the AI winners are, losers are, 287 00:13:20,760 --> 00:13:23,240 Speaker 5: whatever the valuations are, we're going to need a lot 288 00:13:23,280 --> 00:13:26,040 Speaker 5: more electricity coming online in the next three, five, ten 289 00:13:26,120 --> 00:13:29,400 Speaker 5: years than it's currently scheduled. So we're huge believers in that. 290 00:13:29,760 --> 00:13:32,120 Speaker 5: I really think the rarest and critical minerals, the processing 291 00:13:32,120 --> 00:13:34,040 Speaker 5: and refining of those, is going to be brought domestically. 292 00:13:34,040 --> 00:13:36,040 Speaker 5: You're going to see chip industry, You're going to see space. 293 00:13:36,360 --> 00:13:38,120 Speaker 5: So I kind of like this what we've been calling 294 00:13:38,160 --> 00:13:40,680 Speaker 5: pro sac or production for security, that is going to 295 00:13:40,679 --> 00:13:42,440 Speaker 5: be the investment thesis. And I think it's actually going 296 00:13:42,480 --> 00:13:44,920 Speaker 5: to replace ESG as a driving force for the next 297 00:13:44,960 --> 00:13:45,800 Speaker 5: five to ten years. 298 00:13:45,880 --> 00:13:48,079 Speaker 2: Yeah. Yes, gene boy, that took a turn. 299 00:13:48,080 --> 00:13:48,920 Speaker 4: Came and went right. 300 00:13:49,200 --> 00:13:49,440 Speaker 2: Yeah. 301 00:13:49,480 --> 00:13:51,079 Speaker 5: And I think it's and I think this is almost 302 00:13:51,080 --> 00:13:53,640 Speaker 5: an evolution. I think we're just rethinking sustainability. 303 00:13:53,679 --> 00:13:53,760 Speaker 2: Right. 304 00:13:53,800 --> 00:13:56,600 Speaker 5: Sustainability meant one thing, and I think now it's much 305 00:13:56,640 --> 00:13:58,400 Speaker 5: more of a hard look. If we want to be 306 00:13:58,440 --> 00:14:00,880 Speaker 5: sustainable as a country or as a company, you need 307 00:14:00,920 --> 00:14:03,120 Speaker 5: to be in control of certain things. So I think 308 00:14:03,160 --> 00:14:05,520 Speaker 5: when I look at this, we're going to produce x 309 00:14:05,559 --> 00:14:08,440 Speaker 5: amount domestically then you're going to want to produce some 310 00:14:08,520 --> 00:14:11,280 Speaker 5: amount with your close allies and friends, and then sure 311 00:14:11,280 --> 00:14:13,320 Speaker 5: you can buy some on the open market because who cares, 312 00:14:13,360 --> 00:14:15,640 Speaker 5: but you can adjust that, but you need this core 313 00:14:16,000 --> 00:14:19,200 Speaker 5: base to be truly secure and sustainable as a nation. 314 00:14:19,520 --> 00:14:21,200 Speaker 5: I think that's going to go to the corporate level, 315 00:14:21,280 --> 00:14:23,080 Speaker 5: and I think it's going to spread globally as every 316 00:14:23,080 --> 00:14:24,560 Speaker 5: country across the globe realizes this. 317 00:14:24,640 --> 00:14:27,400 Speaker 2: So I think this is not a but I grew 318 00:14:27,440 --> 00:14:29,120 Speaker 2: up in and you grew up in a world where 319 00:14:29,120 --> 00:14:33,080 Speaker 2: it was globalization and the net result are One of 320 00:14:33,120 --> 00:14:37,080 Speaker 2: the net results is low costs, low levels of inflation. 321 00:14:37,640 --> 00:14:39,920 Speaker 2: We're buying stuff because we're making it where it's the 322 00:14:40,000 --> 00:14:43,200 Speaker 2: most efficient slash cheapest. Then I guess the pandemic said, 323 00:14:43,280 --> 00:14:46,760 Speaker 2: uh oh, there's some weaknesses there in terms of, you know, 324 00:14:47,760 --> 00:14:50,200 Speaker 2: getting supply chain reliability, And I guess that's kind of 325 00:14:50,200 --> 00:14:51,640 Speaker 2: where we're trying to figure out, now what that miss? 326 00:14:51,720 --> 00:14:53,080 Speaker 5: Yeah, And I think first it was COVID where we 327 00:14:53,080 --> 00:14:55,280 Speaker 5: realized supply chains were kind of broken for a variety 328 00:14:55,280 --> 00:14:57,680 Speaker 5: of reasons, not necessarily in affarias. Then you saw Russian 329 00:14:57,680 --> 00:15:00,120 Speaker 5: invade Ukraine, where you saw a really bad actor the 330 00:15:00,120 --> 00:15:02,920 Speaker 5: first time in our lives behave badly, and now I 331 00:15:02,960 --> 00:15:04,960 Speaker 5: think you have this ongoing friction with where we're want 332 00:15:05,040 --> 00:15:07,480 Speaker 5: and it's clear China as a bottleneck. And you know, 333 00:15:07,560 --> 00:15:09,600 Speaker 5: one of our general's work with Spider Marks is great. 334 00:15:09,880 --> 00:15:12,480 Speaker 5: He's been talking about us moving to a pre war world, 335 00:15:13,480 --> 00:15:15,080 Speaker 5: and I've never really thought about it that way, but 336 00:15:15,120 --> 00:15:16,640 Speaker 5: we've kind of since World War Two lived in a 337 00:15:16,640 --> 00:15:18,840 Speaker 5: post war world. We had this luxury, then the Soviet 338 00:15:18,960 --> 00:15:22,040 Speaker 5: Union crashed and we have the true we're basking the 339 00:15:22,080 --> 00:15:24,040 Speaker 5: peace divid end, and now we're moving to a pre 340 00:15:24,120 --> 00:15:26,080 Speaker 5: war mentality. And I think there's three things that are 341 00:15:26,240 --> 00:15:28,680 Speaker 5: good and important about that. One is it creates a 342 00:15:28,720 --> 00:15:30,920 Speaker 5: sense of urgency. So some of these problems that we've 343 00:15:30,920 --> 00:15:32,960 Speaker 5: been talking about five ten years and no one did anything, 344 00:15:33,000 --> 00:15:35,640 Speaker 5: now we do it. It creates a sense of sacrifice, 345 00:15:35,720 --> 00:15:37,520 Speaker 5: So I think people are maybe willing to do things, 346 00:15:37,520 --> 00:15:39,680 Speaker 5: maybe give up on some regulatory things that they were 347 00:15:39,760 --> 00:15:43,440 Speaker 5: really wanted to let this occur. And if it's successful, 348 00:15:43,520 --> 00:15:45,800 Speaker 5: pre war leads to no war. And I think that's 349 00:15:45,800 --> 00:15:48,120 Speaker 5: the key, right, It's kind of like deterrence. If we 350 00:15:48,200 --> 00:15:50,480 Speaker 5: now realize we need to protect ourselves and make sure 351 00:15:50,480 --> 00:15:52,080 Speaker 5: that China doesn't want to mess with us. 352 00:15:52,320 --> 00:15:53,720 Speaker 2: We have to do these things, and I think we're 353 00:15:53,720 --> 00:15:55,480 Speaker 2: on those stages, you know. 354 00:15:55,760 --> 00:15:58,880 Speaker 4: Speaking of trends during this earning season, certainly AI spend 355 00:15:58,920 --> 00:16:00,800 Speaker 4: is one of them. But something I'm not hearing a 356 00:16:00,840 --> 00:16:04,080 Speaker 4: lot of is companies talking about the impact of tariffs. 357 00:16:04,120 --> 00:16:06,600 Speaker 4: It's sort of been a non event. Why do you 358 00:16:06,640 --> 00:16:08,800 Speaker 4: think that is? And do you think that's going to continue? 359 00:16:09,040 --> 00:16:11,320 Speaker 5: So I think it's kind of natural if you look 360 00:16:11,360 --> 00:16:13,400 Speaker 5: at it. We've only been paying an extra twenty five 361 00:16:13,400 --> 00:16:15,440 Speaker 5: to thirty billion a month since kind of April, so 362 00:16:15,520 --> 00:16:17,520 Speaker 5: cumulative it's been about one hundred and eighty billion, So 363 00:16:17,560 --> 00:16:20,040 Speaker 5: it's not a big deal in the state of the economy. 364 00:16:20,400 --> 00:16:21,640 Speaker 2: Two, I think. 365 00:16:21,480 --> 00:16:24,400 Speaker 5: The large corporations had the working capital and the clout 366 00:16:24,480 --> 00:16:26,440 Speaker 5: to get a lot of products brought in before tariff. 367 00:16:26,480 --> 00:16:28,960 Speaker 5: So I think it's only going to start slowly affecting, 368 00:16:29,280 --> 00:16:31,200 Speaker 5: you know, the large companies who that's who we tend 369 00:16:31,240 --> 00:16:32,640 Speaker 5: to get the data from. That's who we tend to 370 00:16:32,680 --> 00:16:35,400 Speaker 5: see going, you know, in the coming quarters. I think 371 00:16:35,480 --> 00:16:38,240 Speaker 5: from the you know, smaller companies, it's already hitting, but 372 00:16:38,280 --> 00:16:40,680 Speaker 5: we don't see that right. It's you know, the individual companies, 373 00:16:40,720 --> 00:16:43,920 Speaker 5: small LLCs got hit, So I think it's there. We're 374 00:16:43,920 --> 00:16:45,520 Speaker 5: going to start seeing I think creep into the data 375 00:16:45,520 --> 00:16:47,480 Speaker 5: in Q one and Q two, And the other thing is, 376 00:16:47,560 --> 00:16:50,040 Speaker 5: let's be you know, I think fairly honest here is 377 00:16:50,040 --> 00:16:53,080 Speaker 5: that companies are very reluctant to attract attention to themselves 378 00:16:53,080 --> 00:16:55,080 Speaker 5: on tariffs because the administration doesn't like that. 379 00:16:55,160 --> 00:16:57,440 Speaker 2: So I think it's a Q one Q two story 380 00:16:57,480 --> 00:16:57,840 Speaker 2: next year. 381 00:16:57,840 --> 00:17:00,360 Speaker 5: I think it's there, but it's kind of being suppress 382 00:17:00,600 --> 00:17:02,720 Speaker 5: and as we roll into the new year. 383 00:17:02,600 --> 00:17:04,119 Speaker 2: That's when it's going to be harder to hold back. 384 00:17:04,240 --> 00:17:06,680 Speaker 2: Is that a headwind for the markets if we start 385 00:17:06,720 --> 00:17:09,400 Speaker 2: seeing more inflation data coming out? Yeah, I think it's 386 00:17:09,400 --> 00:17:10,440 Speaker 2: a headwind for markets. 387 00:17:10,480 --> 00:17:12,600 Speaker 5: And again I think this transition, as you pointed out, 388 00:17:12,640 --> 00:17:15,560 Speaker 5: we benefit from globalization, made everything cheaper. I think it 389 00:17:15,560 --> 00:17:18,800 Speaker 5: made things cheaper at the suspense of true sustainability and security. 390 00:17:19,119 --> 00:17:20,480 Speaker 5: That I think is going to be the trade off 391 00:17:20,480 --> 00:17:22,320 Speaker 5: that we're going to have better job security, but there 392 00:17:22,400 --> 00:17:23,560 Speaker 5: is going to be this higher cost. 393 00:17:23,800 --> 00:17:24,879 Speaker 2: I don't see a way around that. 394 00:17:24,960 --> 00:17:27,040 Speaker 4: And is it a headwind for the Fed come December? 395 00:17:27,880 --> 00:17:29,639 Speaker 5: You know, I think that's a tough one because I 396 00:17:29,680 --> 00:17:31,600 Speaker 5: do think you know, we are going to get to 397 00:17:31,680 --> 00:17:33,320 Speaker 5: something more neutral rates. So I think we get to 398 00:17:33,359 --> 00:17:36,720 Speaker 5: three percent, come hell or high water on FED funds, 399 00:17:36,760 --> 00:17:39,480 Speaker 5: and I think the ten year stays below four percent. 400 00:17:39,480 --> 00:17:41,640 Speaker 5: Maybe it's in that three sixty to three eighty sort 401 00:17:41,680 --> 00:17:43,640 Speaker 5: of range, and I think that's enough. And I think 402 00:17:43,680 --> 00:17:46,159 Speaker 5: the one big tailwind that if I'm right and we 403 00:17:46,200 --> 00:17:48,720 Speaker 5: really get this production for security, the big beautiful Bill 404 00:17:48,720 --> 00:17:52,440 Speaker 5: had accelerated depreciation, so that really encourages that aggressive growth. 405 00:17:52,520 --> 00:17:54,800 Speaker 5: So I think we've got some headwinds on one side, 406 00:17:55,000 --> 00:17:57,159 Speaker 5: tailwinds on the other. But that's why my portfolio. I 407 00:17:57,240 --> 00:17:59,919 Speaker 5: just see the need to produce electrons or electricity being 408 00:18:00,280 --> 00:18:02,560 Speaker 5: such a high thing. No matter who wins on the AI, 409 00:18:02,960 --> 00:18:05,040 Speaker 5: I want to own that. I want to own energy production. 410 00:18:05,160 --> 00:18:08,600 Speaker 5: I want to own the chip manufacturers. Domestic, domestic, domestic 411 00:18:08,720 --> 00:18:10,520 Speaker 5: is kind of the focus. So I think there's going 412 00:18:10,560 --> 00:18:13,440 Speaker 5: to be opportunities, less downside, decent amount of upside. 413 00:18:13,480 --> 00:18:15,080 Speaker 2: All right, Peter, thank you so much for We appreciate 414 00:18:15,119 --> 00:18:17,280 Speaker 2: it as always. Peter Chuer, head of macro strategy at 415 00:18:17,280 --> 00:18:19,600 Speaker 2: Academy Securities during this year and wearing a blue jay's 416 00:18:19,600 --> 00:18:21,560 Speaker 2: hat and we're in a blue Jay's hat exactly right. 417 00:18:21,600 --> 00:18:24,760 Speaker 2: So again again lat tonight here to see you. But 418 00:18:24,920 --> 00:18:30,280 Speaker 2: exactly where is Waterloo? It's about an hour southwest of Toronto, 419 00:18:30,400 --> 00:18:32,560 Speaker 2: right towards Detroit. Okay, very good, So there we go, 420 00:18:32,680 --> 00:18:35,760 Speaker 2: So Waterloo, Canada. That's from mister Cheer hung his hat 421 00:18:35,800 --> 00:18:37,240 Speaker 2: there for a while. All right, Peter Cheer had a 422 00:18:37,240 --> 00:18:40,080 Speaker 2: Macro Strategy Academy security. Stay with us. More from Bloomberg 423 00:18:40,119 --> 00:18:41,800 Speaker 2: Surveillance coming up after this. 424 00:18:48,000 --> 00:18:51,600 Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us Live 425 00:18:51,680 --> 00:18:54,800 Speaker 1: weekday afternoons from seven to ten am Eastern. Listen on 426 00:18:54,920 --> 00:18:58,600 Speaker 1: Applecarplay and Android Auto with the Bloomberg Business app, or 427 00:18:58,720 --> 00:18:59,720 Speaker 1: watch us Live on. 428 00:18:59,680 --> 00:19:03,359 Speaker 2: YouTube back by popular demand. This is Lisa Matteo. And 429 00:19:03,400 --> 00:19:05,520 Speaker 2: they'll look at the newspapers. What do you have today these? Okay? 430 00:19:05,560 --> 00:19:07,600 Speaker 7: This has to do with the pending cuts to the 431 00:19:07,600 --> 00:19:10,720 Speaker 7: SNAP program because of the government shutdown. It's actually changing 432 00:19:10,760 --> 00:19:13,640 Speaker 7: what people are handing out to tricker treaters today. 433 00:19:13,840 --> 00:19:15,960 Speaker 2: So this was in the Associated Press. Kind of interesting. 434 00:19:15,960 --> 00:19:18,960 Speaker 7: It's happening in like working class neighborhoods where people are 435 00:19:18,960 --> 00:19:23,240 Speaker 7: giving out shelf stable food instead of candy sometimes so 436 00:19:23,480 --> 00:19:27,280 Speaker 7: like ramen instead of Reese's or Mac of cheese boxes, okay, 437 00:19:27,280 --> 00:19:29,840 Speaker 7: because they're worried, like their neighbors are losing some of 438 00:19:29,880 --> 00:19:31,239 Speaker 7: the food that they rely on. 439 00:19:31,880 --> 00:19:34,200 Speaker 2: So I see, yeah, he's yes. 440 00:19:34,560 --> 00:19:37,080 Speaker 7: So sometimes they're doing it instead of but other times 441 00:19:37,080 --> 00:19:39,520 Speaker 7: they're giving the kids the candy. But on a side 442 00:19:39,560 --> 00:19:42,280 Speaker 7: table they have out things like the mac and cheese 443 00:19:42,520 --> 00:19:44,560 Speaker 7: or diapers or wipes. 444 00:19:44,520 --> 00:19:45,879 Speaker 2: Or things like that. I like this stuff. 445 00:19:46,200 --> 00:19:49,359 Speaker 4: Imagine the kid's face they throw a diaper in there. Yeah, 446 00:19:50,320 --> 00:19:51,800 Speaker 4: I was hoping for a Reese's peanut butter. 447 00:19:51,960 --> 00:19:52,360 Speaker 2: Correct. 448 00:19:52,440 --> 00:19:54,000 Speaker 7: So now they have like kind of a table on 449 00:19:54,040 --> 00:19:56,359 Speaker 7: the side so that parents, if they need it, they 450 00:19:56,359 --> 00:19:57,280 Speaker 7: can kind of take it. 451 00:19:57,520 --> 00:19:59,000 Speaker 4: That's community coming together. 452 00:19:59,080 --> 00:20:02,240 Speaker 7: That's awesome, exactly, exactly, especially in a lot of the 453 00:20:02,240 --> 00:20:03,359 Speaker 7: middle class neighborhoods. 454 00:20:03,359 --> 00:20:05,480 Speaker 2: So I love, love, love that story. Yeah, I'm looking 455 00:20:05,520 --> 00:20:08,040 Speaker 2: at the price of coco just because it's gone up 456 00:20:08,080 --> 00:20:09,959 Speaker 2: over the last several years so much. But it is 457 00:20:10,000 --> 00:20:11,880 Speaker 2: down forty five percent year to date, so a little 458 00:20:11,880 --> 00:20:13,600 Speaker 2: bit of a pull back in there, the price of 459 00:20:13,600 --> 00:20:15,600 Speaker 2: cocoa and chocolate and things like that. So there you go. 460 00:20:15,840 --> 00:20:17,440 Speaker 7: I know, I haven't gotten my chocolate yet, but I 461 00:20:17,440 --> 00:20:21,080 Speaker 7: don't get many trigger treaders. Yeah, yeah, no, okay, this 462 00:20:21,160 --> 00:20:23,880 Speaker 7: one's in the New York Times. The bidding is open 463 00:20:23,960 --> 00:20:27,240 Speaker 7: for New York Penn Station, right, the transformation Okay, yes, no, 464 00:20:27,640 --> 00:20:28,679 Speaker 7: it's still going up. 465 00:20:29,080 --> 00:20:31,639 Speaker 2: I'm sixty one years old and I've heard this every 466 00:20:31,680 --> 00:20:32,479 Speaker 2: year of my life. 467 00:20:32,800 --> 00:20:34,600 Speaker 7: Well, the problem is that six months ago, right, the 468 00:20:34,600 --> 00:20:38,080 Speaker 7: Trump administration took over control of it. So now the 469 00:20:38,080 --> 00:20:41,600 Speaker 7: Federal Department translation, they're looking for proposals to transform it 470 00:20:41,680 --> 00:20:42,879 Speaker 7: in about two years. 471 00:20:42,920 --> 00:20:44,920 Speaker 2: That's what they're saying. Two years that's going to happen. 472 00:20:45,840 --> 00:20:48,280 Speaker 7: And I didn't even realize Amtrak owns Penn Station. 473 00:20:48,720 --> 00:20:52,000 Speaker 2: I didn't realize that. So because every time you get delayed, yeah, 474 00:20:52,080 --> 00:20:54,720 Speaker 2: it's because of your second class citizen in New Jersey transits. 475 00:20:54,800 --> 00:20:57,480 Speaker 2: They get there right away, they get that's there, you go. 476 00:20:58,000 --> 00:20:59,919 Speaker 7: So Amchak was kind of official, was talking to the 477 00:21:00,000 --> 00:21:02,480 Speaker 7: New York Times about it and even saying for the 478 00:21:02,480 --> 00:21:05,240 Speaker 7: fate of Madison Square Garden because. 479 00:21:04,960 --> 00:21:06,560 Speaker 2: It sits on top of the station. 480 00:21:06,960 --> 00:21:08,960 Speaker 7: You know what happens you know with that too, So 481 00:21:09,040 --> 00:21:09,879 Speaker 7: that's under question. 482 00:21:10,320 --> 00:21:12,960 Speaker 2: But I'll tell you the Moynihan station across the street 483 00:21:13,240 --> 00:21:16,520 Speaker 2: is awesome. They did what they did renovate so far 484 00:21:17,200 --> 00:21:20,680 Speaker 2: is really good. Unfortunately that's not me New Jersey Transit's 485 00:21:20,680 --> 00:21:21,960 Speaker 2: still in the in the dump, in. 486 00:21:21,960 --> 00:21:23,840 Speaker 4: The duck, you know, I mean dark Dolans will want 487 00:21:23,880 --> 00:21:25,320 Speaker 4: to redo MSG now. 488 00:21:25,400 --> 00:21:27,440 Speaker 2: They had the opportunity to go to the West Side. 489 00:21:27,520 --> 00:21:29,080 Speaker 2: They had the opportunity to go to the West Side 490 00:21:29,720 --> 00:21:33,560 Speaker 2: as part of a big project to build a football 491 00:21:33,560 --> 00:21:35,479 Speaker 2: stadium and things like that. Was gonna be awesome day 492 00:21:35,560 --> 00:21:38,919 Speaker 2: to move so and so that's not happening. But anyway, 493 00:21:39,200 --> 00:21:42,199 Speaker 2: if President trumpets again and put his weight behind it, 494 00:21:42,960 --> 00:21:43,399 Speaker 2: go for it. 495 00:21:43,440 --> 00:21:46,480 Speaker 7: So maybe it looks bigger push we'll see, okay. And 496 00:21:46,560 --> 00:21:48,720 Speaker 7: this last one is actually on the terminal. It's a 497 00:21:48,760 --> 00:21:51,760 Speaker 7: deep look into the world of travel baseball for kids. 498 00:21:52,640 --> 00:21:56,760 Speaker 7: How much parents are spending thousand dollars. They got bats, gloves, 499 00:21:56,760 --> 00:21:59,520 Speaker 7: clea showcases, camps, travel team itself. Then you have to 500 00:21:59,640 --> 00:22:02,520 Speaker 7: dry and fly to the games and tournaments, hotel stays, 501 00:22:02,640 --> 00:22:03,440 Speaker 7: rental cars. 502 00:22:04,520 --> 00:22:07,040 Speaker 2: I understand this, I live it. 503 00:22:07,200 --> 00:22:08,879 Speaker 7: And then you have the drip, right, you gotta have 504 00:22:08,880 --> 00:22:11,199 Speaker 7: one hundred and twenty five dollars batting gloves, right, the 505 00:22:11,240 --> 00:22:15,280 Speaker 7: eighty five dollars sliding miss It's ridiculous, but it does 506 00:22:15,359 --> 00:22:17,440 Speaker 7: point out this one story. There is a sixteen year 507 00:22:17,440 --> 00:22:19,600 Speaker 7: old kid, his name Miss Striker Pence. He's about six 508 00:22:19,720 --> 00:22:23,520 Speaker 7: foot six. He throws one hundred mile per hour fastball. Okay, 509 00:22:23,800 --> 00:22:26,600 Speaker 7: but he's seen as like the MLB's next top pick. 510 00:22:26,640 --> 00:22:30,200 Speaker 7: He's sixteen, and his parents are saying they've spent about 511 00:22:30,200 --> 00:22:33,320 Speaker 7: one hundred thousand dollars between him and his He has 512 00:22:33,320 --> 00:22:36,080 Speaker 7: two younger brothers too, taking them to all these things 513 00:22:36,119 --> 00:22:37,920 Speaker 7: and showcasing them and putting them off, and they have 514 00:22:37,960 --> 00:22:39,959 Speaker 7: a batting cage in the backyard and all this stuff. 515 00:22:40,160 --> 00:22:42,760 Speaker 7: But they say it's going to pay off because hopefully 516 00:22:42,760 --> 00:22:43,360 Speaker 7: their son. 517 00:22:43,280 --> 00:22:45,440 Speaker 4: Is going to Maybe that ROI is going to pay 518 00:22:45,480 --> 00:22:47,120 Speaker 4: off better than sending them to college. 519 00:22:47,200 --> 00:22:49,400 Speaker 2: I don't know all he says. He's basically that said, 520 00:22:49,440 --> 00:22:50,520 Speaker 2: he's spent just about. 521 00:22:50,280 --> 00:22:54,280 Speaker 7: As much as a college education already, so we'll see. 522 00:22:54,280 --> 00:22:57,320 Speaker 2: But it's like this huge, huge, big business. I mean, 523 00:22:58,280 --> 00:23:00,320 Speaker 2: the one I think is the most egregious is high hockey. 524 00:23:00,920 --> 00:23:03,480 Speaker 2: What hockey parents do for their kids. And they drive. 525 00:23:03,560 --> 00:23:05,359 Speaker 2: So where are you going this weekend? They're going to 526 00:23:05,440 --> 00:23:08,520 Speaker 2: like eerie Pennsylvania. Where I'm going to Toronto. You live 527 00:23:08,520 --> 00:23:10,560 Speaker 2: in New Jersey, You're going to Toronto for ten year 528 00:23:10,600 --> 00:23:11,680 Speaker 2: old hockey tournament. 529 00:23:12,400 --> 00:23:14,239 Speaker 7: That is when you fly to these places and then 530 00:23:14,240 --> 00:23:17,199 Speaker 7: you play a team from New Jersey. Yes, like, if 531 00:23:17,200 --> 00:23:19,560 Speaker 7: you're kidding me, I'm flowing to Florida to play in 532 00:23:19,560 --> 00:23:20,720 Speaker 7: New Jersey to team No. 533 00:23:21,440 --> 00:23:24,119 Speaker 2: It's a scam, but time expensive. All right, there you go. 534 00:23:24,160 --> 00:23:28,160 Speaker 2: That's Lisa Matteo and her and newspapers. It never fails 535 00:23:28,359 --> 00:23:29,000 Speaker 2: to impress. 536 00:23:29,440 --> 00:23:34,320 Speaker 1: This is the Bloomberg Surveillance podcast, available on Apple, Spotify, 537 00:23:34,440 --> 00:23:38,720 Speaker 1: and anywhere else you get your podcasts. Listen live each weekday, 538 00:23:38,840 --> 00:23:42,360 Speaker 1: seven to ten am Eastern on Bloomberg dot Com, the 539 00:23:42,400 --> 00:23:46,399 Speaker 1: iHeartRadio app, tune In, and the Bloomberg Business app. You 540 00:23:46,440 --> 00:23:49,800 Speaker 1: can also watch us live every weekday on YouTube and 541 00:23:50,000 --> 00:23:51,760 Speaker 1: always on the Bloomberg terminal