1 00:00:02,400 --> 00:00:06,760 Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. 2 00:00:11,680 --> 00:00:15,480 Speaker 2: This is the Bloomberg Surveillance Podcast. I'm Jonathan Ferrow, along 3 00:00:15,520 --> 00:00:18,720 Speaker 2: with Lisa Bromwitz and Amerie Hordern. Join us each day 4 00:00:18,760 --> 00:00:22,280 Speaker 2: for insight from the best in markets, economics, and geopolitics 5 00:00:22,440 --> 00:00:24,880 Speaker 2: from our global headquarters in New York City. We are 6 00:00:24,960 --> 00:00:27,680 Speaker 2: live on Bloomberg Television weekday mornings from six to nine 7 00:00:27,720 --> 00:00:31,319 Speaker 2: am Eastern. Subscribe to the podcast on Apple, Spotify, or 8 00:00:31,320 --> 00:00:33,960 Speaker 2: anywhere else you listen, and as always on the Bloomberg 9 00:00:34,040 --> 00:00:35,880 Speaker 2: Terminal and the Bloomberg Business app. 10 00:00:36,360 --> 00:00:38,760 Speaker 3: And we begin this hour with stocks rising as risk 11 00:00:38,800 --> 00:00:42,720 Speaker 3: appetite returns after a stretch of volatility. Amy Silverman of 12 00:00:42,840 --> 00:00:46,360 Speaker 3: RBC Capital Markets writing, there's actually a lot more hedging. 13 00:00:46,800 --> 00:00:48,840 Speaker 3: There's a lot more demand for hedging than is currently 14 00:00:48,880 --> 00:00:51,479 Speaker 3: priced into the market. The risk of missing out is 15 00:00:51,520 --> 00:00:54,240 Speaker 3: almost worse than the risk of a drawdown. And I'm 16 00:00:54,280 --> 00:00:56,760 Speaker 3: pleased to say that. Amy joins us now and Amy. 17 00:00:56,800 --> 00:00:58,600 Speaker 3: Matt and I were talking to you about a week ago, 18 00:00:58,840 --> 00:01:01,640 Speaker 3: in the midst of some of this downturn in the market. 19 00:01:01,760 --> 00:01:05,440 Speaker 3: You were talking about the shadow hedges, the desire for hedges, 20 00:01:05,720 --> 00:01:08,000 Speaker 3: and the places people were turning to get them. How 21 00:01:08,040 --> 00:01:10,880 Speaker 3: has that evolved over the past week as markets have recovered. 22 00:01:11,240 --> 00:01:15,120 Speaker 4: I think part of the problem that I had described 23 00:01:15,280 --> 00:01:17,800 Speaker 4: was this idea that there is actually a lot of 24 00:01:17,840 --> 00:01:21,280 Speaker 4: concern about the fragility of a lot of the trades 25 00:01:21,319 --> 00:01:23,880 Speaker 4: because they're not only related to AI, they're related to 26 00:01:23,920 --> 00:01:26,640 Speaker 4: the concentration risk that you see in the mag seven. 27 00:01:27,080 --> 00:01:30,240 Speaker 4: But obviously this year it's been much more about that 28 00:01:30,440 --> 00:01:33,560 Speaker 4: upcrash being something that investors have to be concerned about, 29 00:01:33,560 --> 00:01:35,720 Speaker 4: that fear of missing out, And so when you do 30 00:01:35,800 --> 00:01:37,720 Speaker 4: get the down days, you get a little bit more 31 00:01:37,760 --> 00:01:39,680 Speaker 4: pile on and you do see that in the SKW 32 00:01:39,720 --> 00:01:43,200 Speaker 4: in the market, meaning that downside demand remains quite sticky. 33 00:01:43,440 --> 00:01:46,560 Speaker 4: Even when you reverse the market moves and you have 34 00:01:46,680 --> 00:01:51,000 Speaker 4: more updates, that SKEW hasn't quite changed as much, because again, 35 00:01:51,040 --> 00:01:53,720 Speaker 4: that fragility is at top of investors' minds. 36 00:01:53,960 --> 00:01:56,720 Speaker 3: What about the treatment of tech amy because before it 37 00:01:56,800 --> 00:01:59,000 Speaker 3: was a market that was pricing in all the AI 38 00:01:59,120 --> 00:02:02,160 Speaker 3: winners all be that that they would all be winners. 39 00:02:02,280 --> 00:02:03,480 Speaker 5: Things have started to change. 40 00:02:03,480 --> 00:02:05,640 Speaker 3: We're looking at another day of Nvidia losing in the 41 00:02:05,640 --> 00:02:08,680 Speaker 3: pre market and Alphabet gaining. Has the treatment of these 42 00:02:08,680 --> 00:02:11,040 Speaker 3: stocks shifted? Has that narrative and the way we price 43 00:02:11,080 --> 00:02:12,520 Speaker 3: it in started to move. 44 00:02:13,040 --> 00:02:15,440 Speaker 4: Yeah, and I think to some degree that actually might 45 00:02:15,480 --> 00:02:18,320 Speaker 4: be a good thing. So one thing we look at 46 00:02:18,400 --> 00:02:22,360 Speaker 4: isn't just inter stock market dispersion, but obviously inter mag 47 00:02:22,440 --> 00:02:25,639 Speaker 4: seven dispersion. And so you know, on a day where 48 00:02:25,680 --> 00:02:28,280 Speaker 4: you have Nvidia going down but Google going up, and 49 00:02:28,320 --> 00:02:31,480 Speaker 4: obviously that story is tied to each other, then it 50 00:02:31,560 --> 00:02:35,440 Speaker 4: becomes maybe something that's also more diversified, because one of 51 00:02:35,440 --> 00:02:39,840 Speaker 4: the biggest concerns has been if correlation rises because it's 52 00:02:39,880 --> 00:02:43,640 Speaker 4: all one big trade, it's quite incestuous. That fragility is 53 00:02:43,680 --> 00:02:45,679 Speaker 4: not good for the market, even in a time when 54 00:02:45,720 --> 00:02:47,560 Speaker 4: things are going up. So if it is the case 55 00:02:47,600 --> 00:02:49,679 Speaker 4: that one is more of a diversifier for the other 56 00:02:50,080 --> 00:02:52,920 Speaker 4: and you don't get that spiking correlation, I know, for 57 00:02:53,040 --> 00:02:56,120 Speaker 4: our investor base when they're thinking about weltility and hedging, 58 00:02:56,200 --> 00:02:59,720 Speaker 4: that is a big component in the market market structure 59 00:02:59,760 --> 00:03:02,840 Speaker 4: that you know, it's very key for how they diversify 60 00:03:02,880 --> 00:03:03,520 Speaker 4: the portfolio. 61 00:03:03,680 --> 00:03:08,120 Speaker 6: Don't we necessarily have less correlation now among the mag seven? Right, 62 00:03:08,120 --> 00:03:11,480 Speaker 6: they were all working together, investing in each other. It 63 00:03:11,520 --> 00:03:13,680 Speaker 6: was a very incestuous circular. 64 00:03:15,240 --> 00:03:15,800 Speaker 5: Economy. 65 00:03:15,840 --> 00:03:20,799 Speaker 6: And now you've got one against the other. It seems 66 00:03:20,840 --> 00:03:25,040 Speaker 6: like it would reduce correlation and maybe even reduce concentration risk. 67 00:03:25,760 --> 00:03:30,000 Speaker 4: Yeah, exactly exactly, Matt. So it's that diversifier aspect that 68 00:03:30,120 --> 00:03:32,320 Speaker 4: is important. I mean, I think the thing is there's 69 00:03:32,320 --> 00:03:37,240 Speaker 4: still that incestuousness hasn't fully gone away, you know, and 70 00:03:37,240 --> 00:03:40,640 Speaker 4: that's not just in terms of what kapax investments are, 71 00:03:40,680 --> 00:03:44,080 Speaker 4: but obviously there's issues on the credit side as well 72 00:03:44,120 --> 00:03:47,480 Speaker 4: that investors are watching for. So I don't think, you know, 73 00:03:47,560 --> 00:03:50,720 Speaker 4: this alleviates the whole picture. But I actually think even 74 00:03:50,760 --> 00:03:53,440 Speaker 4: though it's like Google is going up in videos going down, 75 00:03:53,520 --> 00:03:56,160 Speaker 4: the way that investors are thinking about it is we 76 00:03:56,240 --> 00:03:59,360 Speaker 4: at least my implied correlation on the intermag seven is 77 00:03:59,400 --> 00:04:02,160 Speaker 4: something that could be a diversifier. So this whole market 78 00:04:02,480 --> 00:04:03,680 Speaker 4: isn't all reaching at once. 79 00:04:04,120 --> 00:04:04,400 Speaker 5: Amy. 80 00:04:04,400 --> 00:04:08,240 Speaker 6: How strong does the retail bid look to you right now? 81 00:04:08,240 --> 00:04:12,080 Speaker 6: Because we finally had more than five percent draw down, 82 00:04:12,160 --> 00:04:16,520 Speaker 6: just barely, but it happened from peak to trough last week. 83 00:04:17,000 --> 00:04:19,600 Speaker 6: Our retailer is going to continue to be buying the dip. 84 00:04:19,680 --> 00:04:21,599 Speaker 6: Is that still a huge presence in this market? 85 00:04:23,279 --> 00:04:25,320 Speaker 4: So it has wane and you've seen that in some 86 00:04:25,360 --> 00:04:28,839 Speaker 4: of the sentiment markers, Matt. But it is something that 87 00:04:29,080 --> 00:04:31,320 Speaker 4: you know, we're watching very closely because I think one 88 00:04:31,320 --> 00:04:33,919 Speaker 4: thing we've talked about is the reason that investors have 89 00:04:34,080 --> 00:04:38,120 Speaker 4: that institutional misters, just to be clear, have been afraid of, 90 00:04:38,200 --> 00:04:40,000 Speaker 4: you know, really piling it on hedges. That's why we 91 00:04:40,000 --> 00:04:43,000 Speaker 4: call it shadow hedging, is that retail bid has continued 92 00:04:43,000 --> 00:04:46,160 Speaker 4: to stay in the market. Now there are these extraneous forces, 93 00:04:46,200 --> 00:04:49,800 Speaker 4: so for instance, how cryptocurrency is doing, how other factors 94 00:04:49,839 --> 00:04:53,120 Speaker 4: are doing that are actually quite correlated to that retail bid. 95 00:04:53,240 --> 00:04:56,279 Speaker 4: So we are watching those extraneous factors closely as well, 96 00:04:56,560 --> 00:04:59,159 Speaker 4: because it is interesting to see when you you know, 97 00:04:59,240 --> 00:05:03,240 Speaker 4: like crypto is always supposed to be this hedge asset 98 00:05:03,279 --> 00:05:05,960 Speaker 4: that in reality is a risk asset, and then it's 99 00:05:06,000 --> 00:05:08,360 Speaker 4: also very correlated to that bit that you see in 100 00:05:08,400 --> 00:05:11,320 Speaker 4: n ASTEC. So I think those things, even though they're 101 00:05:11,360 --> 00:05:14,560 Speaker 4: not directly tied into the stock market, are very important 102 00:05:14,600 --> 00:05:16,599 Speaker 4: as factors for sentiment amy. 103 00:05:16,760 --> 00:05:18,720 Speaker 3: In terms of finding other places to hedge, there was 104 00:05:18,720 --> 00:05:21,640 Speaker 3: a goldmn Socks report about what hedge funds are shorting, 105 00:05:21,720 --> 00:05:24,800 Speaker 3: and one of them that's at historic levels, albeit at 106 00:05:24,839 --> 00:05:27,880 Speaker 3: a relatively low level, is utilities two point three percent 107 00:05:27,880 --> 00:05:30,680 Speaker 3: of free float. Again, that doesn't sound terribly exciting, but 108 00:05:30,880 --> 00:05:33,440 Speaker 3: that is the most in history. I wonder if that 109 00:05:33,800 --> 00:05:37,240 Speaker 3: could be interpreted as a hedge for AI given the 110 00:05:37,440 --> 00:05:40,440 Speaker 3: close proximity and the correlations we've been talking about, And 111 00:05:40,720 --> 00:05:43,039 Speaker 3: if it is a hedge, does that make sense as one? 112 00:05:43,400 --> 00:05:45,320 Speaker 4: Yeah, I think it does. You know, when you think 113 00:05:45,360 --> 00:05:48,479 Speaker 4: about what everything comes down to and what could be 114 00:05:48,520 --> 00:05:52,400 Speaker 4: the bottleneck for large parts of the AI trade, it's 115 00:05:52,560 --> 00:05:56,480 Speaker 4: just getting enough compute right, and that has implications not 116 00:05:56,640 --> 00:05:58,400 Speaker 4: just for the United States, but if you think kind 117 00:05:58,400 --> 00:06:03,240 Speaker 4: of bigger, it's also geo politically, the race that is 118 00:06:03,279 --> 00:06:06,080 Speaker 4: going on right now between China and the United States. Again, 119 00:06:06,120 --> 00:06:09,240 Speaker 4: it's that ability to do compute and what bottlenecks happen. 120 00:06:09,640 --> 00:06:11,800 Speaker 4: The only issue I see when you think about doing 121 00:06:11,800 --> 00:06:14,839 Speaker 4: it through utilities is one, there's just not that much 122 00:06:14,920 --> 00:06:18,560 Speaker 4: market cap relative to other sectors. And two you know 123 00:06:18,600 --> 00:06:22,719 Speaker 4: that liquidity is traditionally not as I guess free flowing 124 00:06:22,800 --> 00:06:25,440 Speaker 4: as other sectors. So if that you think about that 125 00:06:25,480 --> 00:06:27,240 Speaker 4: as your hedge, I don't know if that is the 126 00:06:27,279 --> 00:06:31,599 Speaker 4: cleanest that you could have versus you know, outright owning something. 127 00:06:31,320 --> 00:06:33,919 Speaker 5: As a hedge in AI underliars. 128 00:06:33,720 --> 00:06:37,240 Speaker 2: Stay with US multile impex savanas. Coming up off to this. 129 00:06:46,200 --> 00:06:48,960 Speaker 3: Joining US now is Wendy Schiller, directman of the Tomman 130 00:06:49,040 --> 00:06:53,520 Speaker 3: Institute for American Politics and Policy at Brown University. Wendy, 131 00:06:53,600 --> 00:06:57,400 Speaker 3: these negotiations as they're happening in the background, we're getting 132 00:06:57,680 --> 00:07:02,280 Speaker 3: deer earnings that look really poor because of suffering consumer confidence, 133 00:07:02,520 --> 00:07:06,920 Speaker 3: that plunging elections, That affordability was at the forefront. How 134 00:07:07,040 --> 00:07:10,240 Speaker 3: is this coloring the administration's approach as it talks to 135 00:07:10,280 --> 00:07:13,640 Speaker 3: President Sheet as it negotiates with Europe in trade deals? 136 00:07:14,800 --> 00:07:18,080 Speaker 7: Hello, Donnie, I think that the President's got to balance 137 00:07:18,160 --> 00:07:23,280 Speaker 7: his international clout in delivering for the domestic US political market, 138 00:07:23,360 --> 00:07:27,680 Speaker 7: economically and politically, and he's getting so much pressure on 139 00:07:27,880 --> 00:07:31,880 Speaker 7: all fronts, and it's now reflected in his poll numbers. 140 00:07:31,880 --> 00:07:35,520 Speaker 7: On the economy, Republicans typically have an advantage managing the economy. 141 00:07:35,640 --> 00:07:37,240 Speaker 8: They still have an advantage. 142 00:07:36,840 --> 00:07:40,600 Speaker 7: Over the Democrats on managing the economy, but the President 143 00:07:40,680 --> 00:07:42,600 Speaker 7: Trump's managing of the economy have flipped. 144 00:07:42,760 --> 00:07:44,960 Speaker 8: They were more confident now he's underwater. 145 00:07:45,600 --> 00:07:48,160 Speaker 7: In particular, there's also some dynamics of the midterms in 146 00:07:48,200 --> 00:07:53,120 Speaker 7: twenty six Iowa, for example, big farm state relies on exports. 147 00:07:53,280 --> 00:07:55,280 Speaker 8: They have a Senate race, and that. 148 00:07:55,200 --> 00:07:57,600 Speaker 7: Senate race looked you know, maybe i was gone red, 149 00:07:57,920 --> 00:07:59,239 Speaker 7: but now it looks like Iowa. 150 00:07:59,320 --> 00:08:00,840 Speaker 8: The winds are change a little bit there. 151 00:08:00,840 --> 00:08:03,240 Speaker 7: They've got a strong contender on the Democratic side, and 152 00:08:03,280 --> 00:08:05,480 Speaker 7: we'll see who emerges on the Republican side. 153 00:08:05,600 --> 00:08:07,520 Speaker 8: And that's something that's concerning the Senate. 154 00:08:07,600 --> 00:08:10,240 Speaker 7: John fun in particular, has really been in the President's 155 00:08:10,240 --> 00:08:14,440 Speaker 7: ear on agriculture, exports and China. An understanding that this 156 00:08:14,520 --> 00:08:18,120 Speaker 7: doesn't just affect President Trump now, it could affect the 157 00:08:18,240 --> 00:08:20,440 Speaker 7: standing of the Republicans in the Senate in twenty six. 158 00:08:20,440 --> 00:08:20,920 Speaker 5: Yeah, for sure. 159 00:08:20,960 --> 00:08:23,120 Speaker 6: I mean, we see that farmers don't have enough money 160 00:08:23,120 --> 00:08:26,560 Speaker 6: to order more John Deere equipment. They lowered their profit 161 00:08:26,640 --> 00:08:28,320 Speaker 6: forecasts for next year. 162 00:08:29,040 --> 00:08:30,640 Speaker 5: We have seen already. 163 00:08:30,360 --> 00:08:33,560 Speaker 6: Automakers that have had to put production on hold because 164 00:08:33,600 --> 00:08:37,520 Speaker 6: they're not getting enough rare earths. And then President Trump 165 00:08:37,520 --> 00:08:40,320 Speaker 6: has this call with si in which the Chinese call 166 00:08:40,360 --> 00:08:43,559 Speaker 6: out Taiwan as a major sticking point. It's not even 167 00:08:43,679 --> 00:08:48,559 Speaker 6: in the US President's readout, making it look like we're 168 00:08:48,600 --> 00:08:53,400 Speaker 6: downplaying the important Taiwan issue in order to appease the Chinese. 169 00:08:53,440 --> 00:08:54,960 Speaker 5: Are we losing this trade war. 170 00:08:56,520 --> 00:08:59,920 Speaker 7: Well, Matt, I mean at the moment the American peak, 171 00:09:01,040 --> 00:09:03,880 Speaker 7: as evidenced by a number of different polls across different 172 00:09:03,920 --> 00:09:07,160 Speaker 7: polling companies that sort of tilt one way or the 173 00:09:07,200 --> 00:09:11,319 Speaker 7: other politically, that the American public things we are that 174 00:09:11,400 --> 00:09:16,920 Speaker 7: the tariffs are now being blamed for affordability, high prices, layoffs. 175 00:09:17,160 --> 00:09:19,120 Speaker 7: And this is something I think the Jouman Institution did 176 00:09:19,120 --> 00:09:21,080 Speaker 7: not anticipate when. 177 00:09:20,960 --> 00:09:23,160 Speaker 8: He forged the sort of mantra that he was going. 178 00:09:23,080 --> 00:09:25,960 Speaker 7: To stick up for America, get a better deal, negotiate 179 00:09:26,000 --> 00:09:28,080 Speaker 7: a better deal, and bring manufacturing home. 180 00:09:28,160 --> 00:09:31,760 Speaker 6: But every economist with a pulse warned the president about this. 181 00:09:33,520 --> 00:09:36,800 Speaker 7: Well, Donald Trump marches to his own tune, his own drummer, 182 00:09:36,840 --> 00:09:40,640 Speaker 7: and he will emerge claiming credit for deals. China did 183 00:09:40,679 --> 00:09:44,080 Speaker 7: agree to buy more soybeans about a month ago after John. 184 00:09:43,880 --> 00:09:46,240 Speaker 8: Fune pleaded with the President on this, But it still 185 00:09:46,240 --> 00:09:47,959 Speaker 8: looks like we're gonna have to pay out subsidies to 186 00:09:48,000 --> 00:09:49,839 Speaker 8: the farmers from the US Treasury to. 187 00:09:49,840 --> 00:09:53,319 Speaker 7: Make up for these losses, and the President pivots, as 188 00:09:53,360 --> 00:09:54,560 Speaker 7: we know all the time. 189 00:09:54,960 --> 00:09:56,000 Speaker 8: The question is. 190 00:09:55,960 --> 00:09:59,880 Speaker 7: How will the Republicans in Congress treat this going into 191 00:09:59,880 --> 00:10:03,520 Speaker 7: the midterms in twenty six because American public is starting 192 00:10:03,559 --> 00:10:06,920 Speaker 7: to blame the Republican Party and that's bad for them. 193 00:10:07,280 --> 00:10:10,920 Speaker 7: So how effective are they in persuading Donald Trump to 194 00:10:11,000 --> 00:10:12,480 Speaker 7: maybe renegotiate deals. 195 00:10:12,520 --> 00:10:15,679 Speaker 8: But right now it looks like China is still driving 196 00:10:15,679 --> 00:10:17,480 Speaker 8: the bus on this and. 197 00:10:17,480 --> 00:10:20,719 Speaker 7: Affecting because of our geopolitics in the United States, how 198 00:10:20,720 --> 00:10:23,040 Speaker 7: we elect people, which states are important. 199 00:10:23,360 --> 00:10:24,400 Speaker 8: You know, they understand that. 200 00:10:24,480 --> 00:10:27,520 Speaker 7: In China, they understand which markets are ware and how 201 00:10:27,559 --> 00:10:28,840 Speaker 7: that affects our politics. 202 00:10:28,840 --> 00:10:31,040 Speaker 8: And twenty six looms really. 203 00:10:30,880 --> 00:10:36,840 Speaker 6: Large is is the president too focused on international relations 204 00:10:36,920 --> 00:10:39,480 Speaker 6: when you know, we need someone to deal with the 205 00:10:39,520 --> 00:10:42,800 Speaker 6: problem of skyrocketing health costs here. Apparently they're going to 206 00:10:42,880 --> 00:10:47,719 Speaker 6: lay out another two year extension to these really inefficient 207 00:10:48,120 --> 00:10:51,480 Speaker 6: ACA subsidies, which the Republicans really wanted to avoid, but 208 00:10:51,520 --> 00:10:54,080 Speaker 6: now it looks like we're just going to keep, you know, 209 00:10:54,120 --> 00:10:55,000 Speaker 6: paying these bills. 210 00:10:56,720 --> 00:10:59,520 Speaker 7: Well, Matt, I mean every president of this, you know, 211 00:10:59,520 --> 00:11:02,400 Speaker 7: when things are going a little bit south domestically, every 212 00:11:02,480 --> 00:11:04,960 Speaker 7: president turns the page towards foreign relations. 213 00:11:05,000 --> 00:11:07,360 Speaker 8: It's not a partisan thing, it's not a Trump thing. 214 00:11:07,960 --> 00:11:09,440 Speaker 8: But this is what I'm watching. I'm watching. 215 00:11:09,480 --> 00:11:12,240 Speaker 7: Will the Republicans, particularly in the House, come with the President. 216 00:11:12,520 --> 00:11:15,359 Speaker 7: He clearly wants to sign an extension of these tax subsidies. 217 00:11:15,440 --> 00:11:17,800 Speaker 7: He doesn't want to have millions of people who can't 218 00:11:17,800 --> 00:11:19,800 Speaker 7: afford health insurance on his watch next year. 219 00:11:20,120 --> 00:11:21,400 Speaker 8: That's what he wants to avoid. 220 00:11:21,640 --> 00:11:23,600 Speaker 7: But the House is making noises that they don't want 221 00:11:23,600 --> 00:11:26,760 Speaker 7: to do it, that they are uncomfortable doing it. Does 222 00:11:26,800 --> 00:11:29,360 Speaker 7: he still have the same sway with the House GOP 223 00:11:29,559 --> 00:11:31,480 Speaker 7: that he has appeared to have all year long. 224 00:11:31,840 --> 00:11:33,720 Speaker 8: That's what I'm watching over the next couple of weeks 225 00:11:33,720 --> 00:11:34,120 Speaker 8: in into. 226 00:11:34,040 --> 00:11:38,200 Speaker 2: January, stay with us multple imperg Savannah's coming up off 227 00:11:38,200 --> 00:11:38,440 Speaker 2: to this. 228 00:11:47,840 --> 00:11:51,520 Speaker 3: Barbara Duran of BD eight Capital Partners, writing for now, 229 00:11:51,679 --> 00:11:54,600 Speaker 3: the AI play is still the place to be. Avoid 230 00:11:54,679 --> 00:11:59,400 Speaker 3: small cap staples, stick to quality large cap secular growers 231 00:11:59,480 --> 00:12:02,400 Speaker 3: over six and Barbarrown please to say it joins us now. 232 00:12:02,440 --> 00:12:04,839 Speaker 5: Really wonderful to see you this morning. Nice to see you, Danny. 233 00:12:04,880 --> 00:12:08,240 Speaker 3: I'm interested by the fact you're not looking at cyclicals 234 00:12:08,320 --> 00:12:11,560 Speaker 3: right now or small caps, especially since there's this hope 235 00:12:11,559 --> 00:12:13,560 Speaker 3: that we're going to get fed cuts, maybe you add 236 00:12:13,559 --> 00:12:15,719 Speaker 3: in fiscal stimulus and there's this reignition. 237 00:12:15,840 --> 00:12:17,600 Speaker 5: Why are you still ignoring those sectors. 238 00:12:17,800 --> 00:12:19,600 Speaker 1: Well, I think the FED cut that we may have 239 00:12:19,720 --> 00:12:22,720 Speaker 1: one more now, but the economy has been doing fine 240 00:12:23,040 --> 00:12:26,080 Speaker 1: without aggressive FED cuts, so that we've had about one 241 00:12:26,120 --> 00:12:28,360 Speaker 1: and a half percentage points in the last fourteen months. 242 00:12:28,520 --> 00:12:30,360 Speaker 1: But we've seen a number of false starts in terms 243 00:12:30,400 --> 00:12:32,360 Speaker 1: of cyclicals and the small caps. And I see the 244 00:12:32,360 --> 00:12:34,800 Speaker 1: small caps really as a trade because even with rates 245 00:12:34,840 --> 00:12:37,160 Speaker 1: coming down a little bit, you still have forty percent 246 00:12:37,240 --> 00:12:39,360 Speaker 1: of the russel two thousand don't make money. 247 00:12:39,600 --> 00:12:42,520 Speaker 5: They have much higher cost of capital. 248 00:12:42,200 --> 00:12:45,240 Speaker 1: Than return on investment typically, and unless rates come down 249 00:12:45,280 --> 00:12:47,920 Speaker 1: significantly on the long end, I don't see them being helped. 250 00:12:47,920 --> 00:12:50,439 Speaker 1: So I see that a's continuing as a trade. And 251 00:12:50,440 --> 00:12:52,440 Speaker 1: in cyclicals, I think you have to be very selective. 252 00:12:52,480 --> 00:12:54,720 Speaker 1: And industrials, for instance, I mean you want to be 253 00:12:54,880 --> 00:12:57,520 Speaker 1: I think doing industrials that are play on the AI 254 00:12:57,600 --> 00:13:01,440 Speaker 1: build out and infrastructure, automation, robotics, that sort of thing. 255 00:13:01,840 --> 00:13:04,720 Speaker 1: But it's hard to see a big reignition here of 256 00:13:04,760 --> 00:13:07,640 Speaker 1: the economy. I think we're in for good growth, decent growth, 257 00:13:07,640 --> 00:13:10,120 Speaker 1: and certainly we've seen that with the forward earnings guidance 258 00:13:10,120 --> 00:13:12,760 Speaker 1: from the companies who just reported a great quarter and 259 00:13:12,840 --> 00:13:16,280 Speaker 1: certainly do have the big beautiful tax bill, you know, 260 00:13:16,320 --> 00:13:19,319 Speaker 1: the incentives coming there for CAPEX, and also bank de 261 00:13:19,400 --> 00:13:22,920 Speaker 1: regulation which should free up more capital to lend and spend. 262 00:13:23,320 --> 00:13:24,760 Speaker 5: So next year is setting up nicely. 263 00:13:24,920 --> 00:13:26,520 Speaker 3: I'm kind of confused why that's kind of like a 264 00:13:26,640 --> 00:13:30,000 Speaker 3: muddling along versus a growth reognition, because all of those 265 00:13:30,080 --> 00:13:31,480 Speaker 3: do seem like powerful forces. 266 00:13:31,480 --> 00:13:33,679 Speaker 5: Barbara, Yeah, well, I think it is muddling long. 267 00:13:33,720 --> 00:13:36,360 Speaker 1: And we've seen this, you know, this year, even with 268 00:13:36,600 --> 00:13:40,320 Speaker 1: high supposedly high interest rates that are quote restrictive. 269 00:13:39,920 --> 00:13:42,520 Speaker 5: You've seen the economy do okay. And the earnings. 270 00:13:42,600 --> 00:13:44,520 Speaker 1: We just had the ninth quarter in a row where 271 00:13:44,559 --> 00:13:47,280 Speaker 1: earnings were up. In fact, they were better than expected, 272 00:13:47,320 --> 00:13:50,760 Speaker 1: some thirteen plus percent versus eight percent expected, you know, 273 00:13:50,800 --> 00:13:53,160 Speaker 1: but it's still you know, we talked about AI. That 274 00:13:53,280 --> 00:13:55,120 Speaker 1: is still the driver. I mean, if you look at 275 00:13:55,120 --> 00:13:58,240 Speaker 1: what the MAG seven did in earnings x Meta, I 276 00:13:58,280 --> 00:13:59,760 Speaker 1: take Meta out of the mix because they had a 277 00:13:59,760 --> 00:14:02,800 Speaker 1: six team billion dollars one time charge, right, But looking 278 00:14:02,840 --> 00:14:05,720 Speaker 1: at that the overall MAGS seven, we're up thirty percent, 279 00:14:06,240 --> 00:14:08,959 Speaker 1: you know, in in aggregate earnings, and that's versus a 280 00:14:09,040 --> 00:14:11,480 Speaker 1: twenty eight plus percent for the last four quarters. 281 00:14:11,480 --> 00:14:12,880 Speaker 5: So that's still the driver here. 282 00:14:13,040 --> 00:14:16,560 Speaker 6: I wonder about the massive capex plans that these companies 283 00:14:16,559 --> 00:14:18,640 Speaker 6: have you mentioned meta right, they want to spend I 284 00:14:18,640 --> 00:14:25,280 Speaker 6: think one hundred billion dollars next year. Is that depreciation scary? 285 00:14:25,320 --> 00:14:27,520 Speaker 6: As Michael Burry warns us about the fact that they're 286 00:14:27,520 --> 00:14:29,760 Speaker 6: going to buy all these chips which may be worth 287 00:14:30,040 --> 00:14:32,040 Speaker 6: you know, twenty percent less the moment they drive them 288 00:14:32,080 --> 00:14:32,600 Speaker 6: off the lot. 289 00:14:33,040 --> 00:14:34,240 Speaker 5: Yeah, I mean the depreciation. 290 00:14:34,360 --> 00:14:36,880 Speaker 1: What's what I really keep my eye on is the demand, 291 00:14:37,000 --> 00:14:39,440 Speaker 1: you know, and if you're looking at very credible sources, 292 00:14:39,480 --> 00:14:43,080 Speaker 1: you know see this market data infrastructure, data center infrastructure 293 00:14:43,120 --> 00:14:45,920 Speaker 1: going five times what it is now, So that really 294 00:14:45,960 --> 00:14:48,360 Speaker 1: speaks to the demand that's out there. So I mean 295 00:14:48,360 --> 00:14:50,600 Speaker 1: he's arguing about what are the real earnings this and that, 296 00:14:50,640 --> 00:14:52,600 Speaker 1: But to me, it's really what's the demand, what's the 297 00:14:52,640 --> 00:14:55,320 Speaker 1: revenue potential? And that is very real. I mean, just 298 00:14:55,320 --> 00:14:57,880 Speaker 1: saw an acceleration there. I think that continues. We are 299 00:14:57,960 --> 00:15:00,640 Speaker 1: still in the early stages of this AI. So the 300 00:15:00,720 --> 00:15:03,920 Speaker 1: concern about you know, we're in a bubble, there's too 301 00:15:04,000 --> 00:15:05,000 Speaker 1: much money being spent. 302 00:15:05,600 --> 00:15:06,360 Speaker 5: I don't think at all. 303 00:15:06,360 --> 00:15:08,360 Speaker 1: You're going to see increasing usage of AI as it 304 00:15:08,360 --> 00:15:09,000 Speaker 1: gets developed. 305 00:15:10,400 --> 00:15:13,800 Speaker 6: When do we get that revenue because I you know, 306 00:15:13,960 --> 00:15:18,440 Speaker 6: started this job covering tech companies as Cisco was, you know, 307 00:15:18,520 --> 00:15:21,280 Speaker 6: the the darling of the market, and we were spending 308 00:15:21,320 --> 00:15:23,240 Speaker 6: as much as we could to lay fiber for the 309 00:15:23,280 --> 00:15:26,720 Speaker 6: Internet in the late nineties early two thousands, and lo 310 00:15:26,880 --> 00:15:30,680 Speaker 6: and behold, the revenue didn't come quickly enough. Cisco fell 311 00:15:30,840 --> 00:15:34,720 Speaker 6: and only now, like last week, have you made money 312 00:15:34,760 --> 00:15:37,240 Speaker 6: on Cisco if you bought it in nineteen ninety nine 313 00:15:37,280 --> 00:15:37,880 Speaker 6: or two thousand. 314 00:15:38,000 --> 00:15:38,520 Speaker 5: No, that's true. 315 00:15:38,520 --> 00:15:40,400 Speaker 1: And I think so much though, is about the timing, 316 00:15:40,760 --> 00:15:42,760 Speaker 1: you know, because some of the great tech companies in 317 00:15:42,760 --> 00:15:45,240 Speaker 1: the past you had great long runs and made a 318 00:15:45,240 --> 00:15:47,280 Speaker 1: lot of money. But all things do come to an end. 319 00:15:47,280 --> 00:15:50,800 Speaker 1: There's innovation, you know, there's markets mature. I think the 320 00:15:50,840 --> 00:15:53,640 Speaker 1: AI play this is so big and what we're seeing. 321 00:15:53,720 --> 00:15:56,240 Speaker 1: I always mentioned Meta as the poster child, you know 322 00:15:56,240 --> 00:15:58,520 Speaker 1: for what's happy in AI. They have been very early 323 00:15:58,560 --> 00:16:00,600 Speaker 1: on applying it to their own business. Then you've seen 324 00:16:00,600 --> 00:16:03,960 Speaker 1: the results very quickly. They even increase their user base, 325 00:16:04,040 --> 00:16:07,280 Speaker 1: the engagement is up. They've really increased their improved their 326 00:16:07,280 --> 00:16:10,000 Speaker 1: ad targeting, so they've improved more dollars and you've got 327 00:16:10,160 --> 00:16:13,160 Speaker 1: very early penetration. AI is still you've heard it from 328 00:16:13,200 --> 00:16:15,440 Speaker 1: Palo Alto last week. They talked about it in their 329 00:16:15,440 --> 00:16:19,200 Speaker 1: AI security. It's still scaling up because their customers and 330 00:16:19,240 --> 00:16:22,200 Speaker 1: big enterprises are still figuring out how they're going to 331 00:16:22,280 --> 00:16:24,640 Speaker 1: you know, what AI they need and how they're. 332 00:16:24,440 --> 00:16:25,080 Speaker 5: Going to apply it. 333 00:16:25,120 --> 00:16:26,480 Speaker 1: So this is going to be You're going to see 334 00:16:26,520 --> 00:16:28,920 Speaker 1: these increases in productivity over the next year or two. 335 00:16:29,440 --> 00:16:32,680 Speaker 1: Exact timing hard to know, but it will just increase. 336 00:16:32,720 --> 00:16:35,240 Speaker 1: I mean, look at chat GPT. I don't know about 337 00:16:35,320 --> 00:16:37,280 Speaker 1: you all, but I use it all the time, and 338 00:16:37,360 --> 00:16:39,760 Speaker 1: I increase my usage as I discover more things. And 339 00:16:39,800 --> 00:16:42,720 Speaker 1: they have six hundred million users a week, and so 340 00:16:43,080 --> 00:16:44,920 Speaker 1: this is really still and I talked to most of 341 00:16:44,960 --> 00:16:46,840 Speaker 1: my friends. They're like, yeah, I should try it. There's 342 00:16:46,840 --> 00:16:49,800 Speaker 1: still so much more to come, both consumer and enterprise. 343 00:16:50,240 --> 00:16:52,360 Speaker 3: It definitely feels like something we're waiting for, right Like, 344 00:16:52,400 --> 00:16:55,200 Speaker 3: when do the other companies benefit from productivity? I was 345 00:16:55,240 --> 00:16:58,160 Speaker 3: looking at a Brooking study that was published recently. We're 346 00:16:58,200 --> 00:17:01,080 Speaker 3: only nineteen percent of their respond in said that AI 347 00:17:01,480 --> 00:17:07,280 Speaker 3: increase their productivity. Only four percent said it significantly increased productivity. 348 00:17:07,480 --> 00:17:10,639 Speaker 3: Roberts your point, we're still trying to figure this out. 349 00:17:10,880 --> 00:17:13,239 Speaker 3: So as you're looking for who benefits from AI, who 350 00:17:13,320 --> 00:17:15,280 Speaker 3: can use it, where does productivity come from? 351 00:17:15,440 --> 00:17:17,840 Speaker 5: Is it just too early to say? I think it is. 352 00:17:18,200 --> 00:17:18,679 Speaker 5: I think it is. 353 00:17:18,720 --> 00:17:21,760 Speaker 1: I think we see different companies that are benefiting. But 354 00:17:21,880 --> 00:17:24,520 Speaker 1: I think over the next twelve to eighteen months there's 355 00:17:24,520 --> 00:17:27,240 Speaker 1: going to be some dramatic stories to be told about 356 00:17:27,240 --> 00:17:31,080 Speaker 1: the improvements. And you look at we're early on autonomous driving, 357 00:17:31,320 --> 00:17:34,400 Speaker 1: we're early on the deployment of robotics. I mean, for instance, 358 00:17:34,440 --> 00:17:37,600 Speaker 1: you know, you've got Amazon, you know has a million 359 00:17:37,720 --> 00:17:40,400 Speaker 1: robots out there, and so they're very early on the curve, 360 00:17:40,440 --> 00:17:42,920 Speaker 1: but a lot of people are not. And so those 361 00:17:42,920 --> 00:17:44,719 Speaker 1: are things that over the next year. And again it's 362 00:17:44,760 --> 00:17:47,200 Speaker 1: about competition. That's where we're seeing so much spending going 363 00:17:47,240 --> 00:17:49,520 Speaker 1: to this because people know, I've got to do that. 364 00:17:49,760 --> 00:17:52,280 Speaker 1: When you see people like Meta or Amazon who are 365 00:17:52,280 --> 00:17:55,639 Speaker 1: already early users of all this and the productivity gains 366 00:17:55,680 --> 00:17:58,840 Speaker 1: they are seeing. As a company management, we've got to 367 00:17:58,840 --> 00:18:00,880 Speaker 1: do it too, and that requires spending up front. 368 00:18:01,600 --> 00:18:03,240 Speaker 3: Isn't there a chance though, that they go too far 369 00:18:03,280 --> 00:18:05,960 Speaker 3: with that spending and at some point it no longer 370 00:18:05,960 --> 00:18:08,360 Speaker 3: gets rewarded by the market. You're already starting to see 371 00:18:08,359 --> 00:18:10,560 Speaker 3: that in some of the hyper scalers, right, does that 372 00:18:10,600 --> 00:18:11,119 Speaker 3: continue on? 373 00:18:11,960 --> 00:18:14,120 Speaker 1: There's always that concern, and I think it's a legitimate 374 00:18:14,119 --> 00:18:16,399 Speaker 1: concern because at some point you can and this is 375 00:18:16,720 --> 00:18:18,720 Speaker 1: think in a capitalist economy, you know, you don't have 376 00:18:18,760 --> 00:18:21,560 Speaker 1: central planning, so everybody's rushing, you know, to go up 377 00:18:21,600 --> 00:18:24,600 Speaker 1: to the profitability typical margins come down. But I think 378 00:18:24,640 --> 00:18:27,560 Speaker 1: where we are, the demand is so explosive. It's not 379 00:18:27,640 --> 00:18:31,240 Speaker 1: a six to nine month phenomenon. So at some point 380 00:18:31,560 --> 00:18:33,880 Speaker 1: that will be a factor. Right now, you know, as 381 00:18:33,920 --> 00:18:36,359 Speaker 1: far as the eye can see, you've just got this demand, 382 00:18:36,359 --> 00:18:38,800 Speaker 1: this virtuous circle that will just keep going and going. 383 00:18:39,000 --> 00:18:40,679 Speaker 1: But it is something you always have to watch. We 384 00:18:40,760 --> 00:18:43,920 Speaker 1: know that the lifespan of industry is what happens. You 385 00:18:43,960 --> 00:18:46,560 Speaker 1: attract players, they all want to make money, and eventually 386 00:18:46,560 --> 00:18:48,840 Speaker 1: you can overbuild. I don't think it's like fiber though, 387 00:18:48,920 --> 00:18:50,919 Speaker 1: you know, fiber was much more limited. That was a 388 00:18:51,040 --> 00:18:55,760 Speaker 1: very specific application and very prone to being overbuilt. 389 00:18:55,840 --> 00:18:57,040 Speaker 5: This is just yeah, so much. 390 00:18:57,040 --> 00:18:59,080 Speaker 3: At the end of the day, data centers are just 391 00:18:59,080 --> 00:19:01,840 Speaker 3: like empty boxes. Those can't really be used for anything 392 00:19:01,840 --> 00:19:04,399 Speaker 3: else besides data centers, at least on the infrastructure side, 393 00:19:04,520 --> 00:19:05,600 Speaker 3: there's a chance we overbuild. 394 00:19:05,640 --> 00:19:11,000 Speaker 6: Now you could mind bitcoin, Yes, so true, but. 395 00:19:11,000 --> 00:19:12,439 Speaker 3: That is that is a place that it feels like 396 00:19:12,480 --> 00:19:13,840 Speaker 3: we could go too far, and a lot of money 397 00:19:13,880 --> 00:19:14,760 Speaker 3: has been put into that. 398 00:19:15,119 --> 00:19:17,639 Speaker 1: Yeah, no, it is. It is real estate. In the end, 399 00:19:17,800 --> 00:19:20,480 Speaker 1: you know what's going on there. But at the moment, again, 400 00:19:20,840 --> 00:19:23,639 Speaker 1: well everybody's watching that. It's like we're watching private credit. 401 00:19:23,920 --> 00:19:26,399 Speaker 1: You know, in terms of possible systemic risk, it's not 402 00:19:26,480 --> 00:19:28,679 Speaker 1: there yet, you know, and so you just still make 403 00:19:28,680 --> 00:19:29,200 Speaker 1: a lot of money. 404 00:19:29,200 --> 00:19:31,360 Speaker 5: And that's what we're going to continue to have these frights. 405 00:19:31,440 --> 00:19:33,560 Speaker 1: Like you know, I remember the years when Amazon made 406 00:19:33,560 --> 00:19:36,000 Speaker 1: no money and they kept reinvesting, reinvesting, and at least 407 00:19:36,040 --> 00:19:38,240 Speaker 1: once a year investors will throw up their hands and 408 00:19:38,280 --> 00:19:40,399 Speaker 1: say they will never make money and they sell the 409 00:19:40,440 --> 00:19:43,280 Speaker 1: stock off. Well, we now know how that story has ended. 410 00:19:43,440 --> 00:19:45,000 Speaker 1: And I think we're going to continue to see these 411 00:19:45,000 --> 00:19:47,080 Speaker 1: concerns with AI and the legitimate concerns. 412 00:19:47,119 --> 00:19:48,760 Speaker 5: I just think it's way early, Barbara. 413 00:19:48,840 --> 00:19:52,119 Speaker 6: Where do you an investor who already has exposure to 414 00:19:52,200 --> 00:19:56,720 Speaker 6: the megacap hyperscalers, an investor who already has exposure to energy, 415 00:19:57,520 --> 00:19:59,040 Speaker 6: where do you put new money? 416 00:19:59,280 --> 00:20:01,520 Speaker 1: Yeah, it's a pro because you know, in terms of 417 00:20:02,040 --> 00:20:05,200 Speaker 1: because you will have new companies starting new applications and 418 00:20:05,240 --> 00:20:06,760 Speaker 1: all that sort of things. So a lot of people. 419 00:20:07,080 --> 00:20:09,040 Speaker 1: You can look at the food chain, you know, it 420 00:20:09,080 --> 00:20:10,919 Speaker 1: goes into energy. Like you look at a company like 421 00:20:10,960 --> 00:20:15,399 Speaker 1: g i Vernova, very expensive, they have great backlog, but 422 00:20:15,440 --> 00:20:16,720 Speaker 1: they can only build so fast. 423 00:20:17,080 --> 00:20:18,480 Speaker 5: So where do you put the money there? 424 00:20:18,480 --> 00:20:20,600 Speaker 1: You can look at the suppliers and the components and 425 00:20:20,640 --> 00:20:23,280 Speaker 1: all that sort of thing. But for now, you know, 426 00:20:23,320 --> 00:20:26,119 Speaker 1: it's not only the hyperscalers, it's the broad comes of 427 00:20:26,160 --> 00:20:27,639 Speaker 1: the world. I mean, you saw it Broadcome did with 428 00:20:27,680 --> 00:20:30,760 Speaker 1: the announcement that Alphabet, you know, is going to be 429 00:20:30,760 --> 00:20:33,359 Speaker 1: selling their TPUs, which are basically a six you know, 430 00:20:33,440 --> 00:20:37,480 Speaker 1: customer customer chips to their customers, and so you still 431 00:20:37,480 --> 00:20:39,080 Speaker 1: a lot more to go there, and you're going to 432 00:20:39,160 --> 00:20:41,679 Speaker 1: have these kinds of announcements you know, going on, and 433 00:20:41,720 --> 00:20:43,959 Speaker 1: so that will change. Look at Alphabet, you know it is, 434 00:20:44,080 --> 00:20:46,879 Speaker 1: you know, outperformed, and just earlier this year it was 435 00:20:46,880 --> 00:20:49,679 Speaker 1: a laggard. They had any trust problems. People are like, oh, 436 00:20:49,680 --> 00:20:51,879 Speaker 1: they're gonna be left behind in the AI And now 437 00:20:51,960 --> 00:20:54,320 Speaker 1: look at it, it's like, oh, the darling, the star 438 00:20:54,359 --> 00:20:54,760 Speaker 1: of the show. 439 00:20:56,119 --> 00:20:59,640 Speaker 2: This is the Bloomberg's Events podcast, bringing you the best 440 00:20:59,640 --> 00:21:02,800 Speaker 2: in my kids, economics, angio politics. You can watch the 441 00:21:02,800 --> 00:21:05,840 Speaker 2: show live on Bloomberg TV weekday mornings from six am 442 00:21:05,960 --> 00:21:09,920 Speaker 2: to nine am Eastern. Subscribe to the podcast on Apple, Spotify, 443 00:21:10,080 --> 00:21:12,280 Speaker 2: or anywhere else you listen, and as always, on the 444 00:21:12,280 --> 00:21:14,720 Speaker 2: Bloomberg Terminal and the Bloomberg Business app.