1 00:00:02,440 --> 00:00:06,760 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:11,960 --> 00:00:16,360 Speaker 2: This is the Bloomberg Surveillance Podcast. Catch us live weekdays 3 00:00:16,400 --> 00:00:19,880 Speaker 2: at seven am Eastern on applecar Player, Android Auto with 4 00:00:19,920 --> 00:00:23,360 Speaker 2: the Bloomberg Business App. Listen on demand wherever you get 5 00:00:23,360 --> 00:00:26,200 Speaker 2: your podcasts, or watch us live on YouTube. 6 00:00:26,400 --> 00:00:29,480 Speaker 3: Laura Rain joins it. She's the Chief ECONOMOCE at FS Investments. 7 00:00:29,760 --> 00:00:30,520 Speaker 1: Lare given some of. 8 00:00:30,520 --> 00:00:34,240 Speaker 3: The economic data we've seen recently. I guess most recently 9 00:00:34,320 --> 00:00:37,200 Speaker 3: was a strong retail sales. It seems like this economy's 10 00:00:37,240 --> 00:00:40,120 Speaker 3: doing fairly well, if not better than fairly well. How 11 00:00:40,120 --> 00:00:40,879 Speaker 3: do you think about it? 12 00:00:42,400 --> 00:00:44,199 Speaker 4: I think what we're seeing is a little bit of 13 00:00:44,200 --> 00:00:47,040 Speaker 4: a difference between the growth data that you alluded to 14 00:00:47,120 --> 00:00:50,520 Speaker 4: with the retail sales numbers, and the employment data, which 15 00:00:50,680 --> 00:00:55,880 Speaker 4: does seem like the trajectory is slowing more notably. I 16 00:00:55,880 --> 00:00:58,200 Speaker 4: think all of this adds up to a soft landing. 17 00:00:58,240 --> 00:01:00,480 Speaker 4: But I think you bring up something really important. If 18 00:01:00,520 --> 00:01:03,160 Speaker 4: you look at the GDP data, it still looks like 19 00:01:03,280 --> 00:01:06,200 Speaker 4: there's no landing. We're still growing at a pace that's 20 00:01:06,240 --> 00:01:10,319 Speaker 4: well above potential, and I think really reflects a consumer 21 00:01:10,360 --> 00:01:14,679 Speaker 4: that just is truly unstoppable when we look ahead. However, 22 00:01:15,080 --> 00:01:18,200 Speaker 4: I think we are in for an incremental slowdown in 23 00:01:18,319 --> 00:01:21,600 Speaker 4: GDP growth. We're probably going to see a business investment 24 00:01:21,640 --> 00:01:24,200 Speaker 4: take a pause, a lot of uncertainty right now about 25 00:01:24,200 --> 00:01:27,440 Speaker 4: regulation around the election, and I think we're going to 26 00:01:27,480 --> 00:01:31,000 Speaker 4: see government spending also downshift to neutral from being a 27 00:01:31,000 --> 00:01:33,840 Speaker 4: pretty powerful tailwind. But you add it all up, I 28 00:01:33,840 --> 00:01:36,880 Speaker 4: think today where you see the soft landing, more specifically 29 00:01:36,920 --> 00:01:39,520 Speaker 4: as in the labor market data, where we are starting 30 00:01:39,600 --> 00:01:43,080 Speaker 4: to see a cooling picture, not cold, a cooling. 31 00:01:43,560 --> 00:01:45,720 Speaker 5: Laurie, you walk us through sort of how you're thinking 32 00:01:45,720 --> 00:01:48,480 Speaker 5: about all of this as you listen to FED policymakers 33 00:01:49,160 --> 00:01:51,240 Speaker 5: walk us through the way that they were approaching this 34 00:01:51,320 --> 00:01:53,040 Speaker 5: next meeting, which is going to take place just a 35 00:01:53,280 --> 00:01:56,000 Speaker 5: day or two after the presidential election. What are you 36 00:01:56,040 --> 00:01:57,960 Speaker 5: listening for? I'll note that Chris Waller is speaking today. 37 00:01:57,960 --> 00:01:59,720 Speaker 5: I think in Vienna, Austria, we're gonna hear from Neil 38 00:01:59,760 --> 00:02:03,840 Speaker 5: kshk sorry as well. Is the is the commentary there? 39 00:02:04,000 --> 00:02:06,320 Speaker 5: Commentary that we're getting is a cacophonists. Are we hearing 40 00:02:06,480 --> 00:02:08,160 Speaker 5: some of that unanimity that a lot of people thought 41 00:02:08,200 --> 00:02:10,520 Speaker 5: was eroding after the last meeting? What stands out to you? 42 00:02:10,560 --> 00:02:12,840 Speaker 5: What are you listening for when when these policy makers. 43 00:02:12,560 --> 00:02:15,880 Speaker 4: Speak, I think the only thing that they're unanimous about 44 00:02:16,040 --> 00:02:19,120 Speaker 4: is that they're going to have to be data dependent 45 00:02:19,639 --> 00:02:23,480 Speaker 4: when they're looking ahead to twenty twenty five. Listen, the 46 00:02:23,720 --> 00:02:28,120 Speaker 4: inflation data has absolutely come down enough to open a 47 00:02:28,160 --> 00:02:32,639 Speaker 4: window of opportunity for the FED to correct rates down 48 00:02:33,560 --> 00:02:36,520 Speaker 4: and sort of keep them in line with real FED 49 00:02:36,560 --> 00:02:39,720 Speaker 4: funds rates. You know, when we see inflation coming down, 50 00:02:40,160 --> 00:02:42,560 Speaker 4: just the nominal FEDS funds rates starts to look a 51 00:02:42,560 --> 00:02:43,920 Speaker 4: little bit more restrictive. 52 00:02:44,320 --> 00:02:45,320 Speaker 1: So I think that's the. 53 00:02:45,280 --> 00:02:49,240 Speaker 4: Adjustment that they're making today, and to twenty five basis 54 00:02:49,240 --> 00:02:52,040 Speaker 4: point rate cuts at the next two meetings has always 55 00:02:52,040 --> 00:02:56,280 Speaker 4: been my forecast. I think where I deviate more significantly 56 00:02:56,440 --> 00:02:59,280 Speaker 4: is into next year because I think they're going to 57 00:02:59,400 --> 00:03:03,040 Speaker 4: really take a pause. They're going to wait and see 58 00:03:03,440 --> 00:03:06,000 Speaker 4: how the economy is evolving. And I feel like they 59 00:03:06,040 --> 00:03:09,120 Speaker 4: take flak for having this sort of data dependent view, 60 00:03:09,560 --> 00:03:12,280 Speaker 4: but I think they have to because I don't think 61 00:03:12,280 --> 00:03:14,960 Speaker 4: inflation's totally gone. I think it's you know. 62 00:03:14,880 --> 00:03:16,200 Speaker 3: I think the boogeyman's under the bed. 63 00:03:16,240 --> 00:03:18,120 Speaker 4: I don't think it's just gone for good. 64 00:03:19,200 --> 00:03:22,240 Speaker 3: Lauren, let's talk in the labor market here. You know, 65 00:03:22,280 --> 00:03:25,200 Speaker 3: from my perspective, this is a fully employed economy because 66 00:03:25,240 --> 00:03:28,360 Speaker 3: all of the Sweeney offspring are gainfully employed. So to me, 67 00:03:28,600 --> 00:03:32,000 Speaker 3: that's very good well employed economy. What does numbers tell 68 00:03:32,040 --> 00:03:34,680 Speaker 3: you about kind of where the labor market is today 69 00:03:34,680 --> 00:03:36,160 Speaker 3: and where there might be some risks. 70 00:03:37,360 --> 00:03:40,600 Speaker 4: You know, it's interesting that it's evolved into almost a 71 00:03:40,760 --> 00:03:44,360 Speaker 4: two speed labor market because when you look at the 72 00:03:44,560 --> 00:03:49,560 Speaker 4: hiring data, it's declined, it's looking weaker than it was 73 00:03:49,720 --> 00:03:54,440 Speaker 4: before the pandemic, and it's eroding somewhat. But when you 74 00:03:54,480 --> 00:03:57,640 Speaker 4: look at the layoffs data, it's also very low, so 75 00:03:58,080 --> 00:04:01,520 Speaker 4: you know, people aren't losing their job en mass, which 76 00:04:01,560 --> 00:04:05,400 Speaker 4: is really just what's so critical to keep household consumption 77 00:04:05,560 --> 00:04:09,600 Speaker 4: going and consumer confidence where it is. But when you 78 00:04:09,640 --> 00:04:12,920 Speaker 4: look at job opportunities, you know clearly that churn that 79 00:04:13,000 --> 00:04:16,880 Speaker 4: we saw after the pandemic is really gone now, and 80 00:04:16,920 --> 00:04:20,600 Speaker 4: you're seeing the hiring side of things looking cooler. 81 00:04:21,240 --> 00:04:23,200 Speaker 1: But you know, to me, the can area. 82 00:04:23,000 --> 00:04:26,800 Speaker 4: And the coal mine is always the weekly initial jobless claims. 83 00:04:27,080 --> 00:04:29,440 Speaker 4: You know, we are seeing some elevation there because of 84 00:04:29,520 --> 00:04:34,320 Speaker 4: the hurricanes that have devastated some local communities, but overall, 85 00:04:34,480 --> 00:04:37,520 Speaker 4: outside of that, they're still fairly low, and of course, 86 00:04:37,640 --> 00:04:40,279 Speaker 4: you know, nothing gets the market's attention like the monthly 87 00:04:40,320 --> 00:04:43,039 Speaker 4: payroll report, which I think is going to continue to 88 00:04:43,080 --> 00:04:47,200 Speaker 4: show a steady unemployment rate at round four four point 89 00:04:47,200 --> 00:04:52,440 Speaker 4: one percent and hiring that's strong enough to keep that 90 00:04:52,560 --> 00:04:54,440 Speaker 4: unemployment rate steady where it is. 91 00:04:55,200 --> 00:04:57,120 Speaker 5: You know, bearing in mind what you're saying about how 92 00:04:57,320 --> 00:04:58,880 Speaker 5: the Fed's going to be data driven and we have 93 00:04:58,960 --> 00:05:01,440 Speaker 5: to be as well. Let me just ask you about 94 00:05:01,520 --> 00:05:04,159 Speaker 5: some of the softer data. And we had that consumer 95 00:05:04,200 --> 00:05:06,279 Speaker 5: confidence number a few weeks back, which I think spooked 96 00:05:06,279 --> 00:05:08,760 Speaker 5: a lot of people. Consumers less confident in the economy 97 00:05:08,760 --> 00:05:11,240 Speaker 5: where it is now and where it's headed. How do 98 00:05:11,320 --> 00:05:14,160 Speaker 5: you factor that into the way that you were forecasting 99 00:05:14,200 --> 00:05:16,720 Speaker 5: and thinking about the economy. Just the sense that consumers 100 00:05:16,800 --> 00:05:19,960 Speaker 5: have about the US economy directionally, I noted in the 101 00:05:20,000 --> 00:05:24,880 Speaker 5: last Confidence Board Report conference report, this sort of heightened 102 00:05:24,880 --> 00:05:27,240 Speaker 5: interest in what the FED is doing and where interest 103 00:05:27,320 --> 00:05:27,880 Speaker 5: rates are going. 104 00:05:29,000 --> 00:05:30,839 Speaker 4: You know, you bring up to such an important point 105 00:05:30,880 --> 00:05:35,960 Speaker 4: because the consumer confidence data have been lackluster, have been 106 00:05:36,000 --> 00:05:40,840 Speaker 4: weak really since the pandemic. And that's despite you know, 107 00:05:41,040 --> 00:05:45,080 Speaker 4: a very strong on a labor market, and despite the 108 00:05:45,120 --> 00:05:48,640 Speaker 4: fact that while consumers say they're a little more downbeat 109 00:05:48,720 --> 00:05:53,400 Speaker 4: on the on the economy, they're still out spending like gangbusters. 110 00:05:53,760 --> 00:05:56,320 Speaker 4: So it's hard for me to connect those dots today 111 00:05:57,160 --> 00:05:59,920 Speaker 4: given that the data has just sent such mixed signal. 112 00:06:00,360 --> 00:06:03,000 Speaker 4: You know, we read the consumer confidence data closely because 113 00:06:03,000 --> 00:06:05,800 Speaker 4: it comes out early, But of course what really matters 114 00:06:05,839 --> 00:06:08,280 Speaker 4: for all of us is what their consumers are actually 115 00:06:08,320 --> 00:06:12,320 Speaker 4: doing now, what they say they're worried about. That said, 116 00:06:12,520 --> 00:06:16,000 Speaker 4: we cannot just ignore it. So it's something I think 117 00:06:16,000 --> 00:06:20,080 Speaker 4: that I'm hoping we'll get better after the election. I 118 00:06:20,120 --> 00:06:24,120 Speaker 4: think that's weighing on sentiment, just the uncertainty. And I 119 00:06:24,160 --> 00:06:27,040 Speaker 4: think that, you know, as consumers slowly get used to 120 00:06:27,160 --> 00:06:31,479 Speaker 4: interest rates at a higher for longer place, some of 121 00:06:31,520 --> 00:06:35,960 Speaker 4: that concern around what they're able to do afford and 122 00:06:36,000 --> 00:06:40,960 Speaker 4: what houses they're able to buy is going to normalize 123 00:06:41,000 --> 00:06:43,000 Speaker 4: a little bit. I just think a lot of people 124 00:06:43,040 --> 00:06:44,960 Speaker 4: are waiting for us to come back to a very 125 00:06:44,960 --> 00:06:47,800 Speaker 4: low rate environment that I don't think it's going to happen. 126 00:06:48,640 --> 00:06:50,800 Speaker 3: All right, because I'm not refinancing my mortgage, is what 127 00:06:50,800 --> 00:06:53,400 Speaker 3: you're telling me anytime soon. Lara Ram, thanks so much 128 00:06:53,400 --> 00:06:58,160 Speaker 3: for joining us loa Rain Chief economists at FS Investments. 129 00:07:02,920 --> 00:07:06,760 Speaker 2: You're listening to the Bloomberg Surveillance Podcast. Catch us live 130 00:07:06,880 --> 00:07:10,200 Speaker 2: weekday afternoons from seven to ten am Easter Listen on 131 00:07:10,240 --> 00:07:13,480 Speaker 2: Apple car Play and Androut Auto with a Bloomberg Business app, 132 00:07:13,600 --> 00:07:15,240 Speaker 2: or watch US live on YouTube. 133 00:07:15,320 --> 00:07:18,239 Speaker 3: I want to bring a Nancy Curtain, Partner, Global CIO, 134 00:07:18,560 --> 00:07:22,760 Speaker 3: head of Investment Advisory at alt It Tiedament Global. Hey, Nancy, 135 00:07:22,800 --> 00:07:25,520 Speaker 3: We're just kind of getting into the teeth of the earnings, 136 00:07:25,560 --> 00:07:28,920 Speaker 3: but we have some good numbers out of American Express today. 137 00:07:28,960 --> 00:07:31,560 Speaker 3: The big banks put up some really good numbers. I mean, 138 00:07:31,600 --> 00:07:34,480 Speaker 3: Morgan Stanley JP Morgan, What do you take away so 139 00:07:34,560 --> 00:07:36,600 Speaker 3: far from what we've seen coming out of Corporate America 140 00:07:36,640 --> 00:07:37,240 Speaker 3: earnings wise? 141 00:07:38,800 --> 00:07:42,480 Speaker 1: Okay, so we're early innings in the third quarter, but like, 142 00:07:42,560 --> 00:07:45,320 Speaker 1: so far, so good banks. As you said, we're pretty 143 00:07:45,400 --> 00:07:49,760 Speaker 1: strong trading, they're benefiting from the volatility and markets. We 144 00:07:49,800 --> 00:07:53,160 Speaker 1: think investment banking will probably pick up, and I think 145 00:07:53,200 --> 00:07:56,680 Speaker 1: they indicated quite nicely on improvement net interest margins. We 146 00:07:56,760 --> 00:08:01,520 Speaker 1: have Netflix Overnight TSMC rather just spelled the fact that 147 00:08:01,560 --> 00:08:04,560 Speaker 1: there's a problem in demand for jen Ai, So I 148 00:08:04,600 --> 00:08:08,880 Speaker 1: think that reads well into Nvidia earnings that's coming towards 149 00:08:08,880 --> 00:08:11,440 Speaker 1: the end of November. As you know, look, there's a 150 00:08:11,560 --> 00:08:15,360 Speaker 1: lull bar for the third quarter. Expectations are four percent, 151 00:08:15,720 --> 00:08:18,000 Speaker 1: and I think companies are going to leap right over it. 152 00:08:18,120 --> 00:08:21,640 Speaker 1: So we think this quarter will be strong. But really 153 00:08:21,640 --> 00:08:25,080 Speaker 1: what's important for our clients and our positioning is looking 154 00:08:25,120 --> 00:08:28,280 Speaker 1: ahead to the fourth quarter and twenty twenty five, where 155 00:08:28,280 --> 00:08:31,560 Speaker 1: we still expect earnings to continue to accelerate as Central 156 00:08:31,600 --> 00:08:32,200 Speaker 1: Bank's ease. 157 00:08:32,520 --> 00:08:34,240 Speaker 5: Well, Nas, let's talk about that as you try to 158 00:08:34,240 --> 00:08:36,160 Speaker 5: look ahead to the fourth quarter. And obviously there's an 159 00:08:36,200 --> 00:08:40,320 Speaker 5: election between now and then looming large, and I'm curious 160 00:08:40,360 --> 00:08:42,440 Speaker 5: just about kind of the panoply of risks that you 161 00:08:42,480 --> 00:08:44,640 Speaker 5: see here. Yes, there's the election results, there's this Federal 162 00:08:44,640 --> 00:08:46,800 Speaker 5: Reserve meeting that we were talking about just a few 163 00:08:46,800 --> 00:08:49,480 Speaker 5: moments ago. I'm looking at just sort of how much 164 00:08:49,640 --> 00:08:52,160 Speaker 5: gold has gone up in price here in recent days. 165 00:08:53,240 --> 00:08:55,199 Speaker 5: How are you thinking about risk and how is that 166 00:08:55,280 --> 00:08:57,040 Speaker 5: kind of shaping your perspective as you look ahead to 167 00:08:57,040 --> 00:08:57,640 Speaker 5: the fourth quarter. 168 00:08:59,040 --> 00:09:01,800 Speaker 1: Well, first of all, it's important to remain diversified, which 169 00:09:01,840 --> 00:09:04,720 Speaker 1: is what we do. We don't just have equities. We've 170 00:09:04,760 --> 00:09:08,400 Speaker 1: got things like private credit and infrastructure and gold, gold 171 00:09:08,440 --> 00:09:11,720 Speaker 1: as you mentioned, hit twenty seven hundred overnight. That's been 172 00:09:11,760 --> 00:09:15,880 Speaker 1: a really really nice diversifier and ballast in client portfolio. 173 00:09:15,920 --> 00:09:19,439 Speaker 1: So it's not just about equities. And I think given 174 00:09:19,480 --> 00:09:22,640 Speaker 1: the strength and market that we've seen already year today, 175 00:09:23,200 --> 00:09:26,440 Speaker 1: a pullback on any of those event type things and 176 00:09:26,520 --> 00:09:28,840 Speaker 1: data things that you said coming ahead. We've got a PCE, 177 00:09:29,200 --> 00:09:31,120 Speaker 1: we've got a jobs number that's going to be a 178 00:09:31,120 --> 00:09:33,880 Speaker 1: bit mixed up with the hurricane and bowing and so 179 00:09:33,960 --> 00:09:35,960 Speaker 1: on and so forth, and then we got the election, 180 00:09:36,040 --> 00:09:38,840 Speaker 1: and then we've got the FED. So you know, short term, 181 00:09:38,880 --> 00:09:41,400 Speaker 1: you never know with markets could easily pull back. They've 182 00:09:41,400 --> 00:09:46,040 Speaker 1: been super strong. But remember last Saturday we celebrated Happy Birthday, 183 00:09:46,160 --> 00:09:49,600 Speaker 1: two year anniversary. You know, typically when you make it 184 00:09:49,600 --> 00:09:52,280 Speaker 1: to two years, you make it to three years seventy 185 00:09:52,280 --> 00:09:54,680 Speaker 1: percent of the time, and data going back to like 186 00:09:54,800 --> 00:09:58,640 Speaker 1: nineteen forty nine, and remember the average length of a 187 00:09:58,679 --> 00:10:01,000 Speaker 1: bullmark in the United States is five years and one 188 00:10:01,080 --> 00:10:04,920 Speaker 1: hundred percent. We've done sixty and two years. So we 189 00:10:05,040 --> 00:10:08,079 Speaker 1: got to look forward to twenty twenty five at all 190 00:10:08,120 --> 00:10:12,360 Speaker 1: things being equal, unless there's some big resurgence of inflation, 191 00:10:13,160 --> 00:10:17,760 Speaker 1: Middle East upset, whatever, we are still constructive positive on 192 00:10:17,800 --> 00:10:18,400 Speaker 1: the outlook. 193 00:10:19,120 --> 00:10:21,680 Speaker 3: Hey, Nancy, we had some I guess some conflicting results 194 00:10:21,720 --> 00:10:23,600 Speaker 3: coming out of some of the big chip makers over 195 00:10:23,640 --> 00:10:25,360 Speaker 3: the last week. ASML had a little bit of a 196 00:10:25,400 --> 00:10:28,640 Speaker 3: warning there, actually a big warning, let's be honest. But 197 00:10:28,679 --> 00:10:32,199 Speaker 3: then Taiwan Semika doctor came back strong yesterday. As someone 198 00:10:32,200 --> 00:10:34,360 Speaker 3: who thinks of the chip business as kind of a 199 00:10:34,440 --> 00:10:37,880 Speaker 3: proxy for this whole AI trade here, I'm not sure 200 00:10:37,880 --> 00:10:40,959 Speaker 3: if it's a trader, it's a long term theme. How 201 00:10:40,960 --> 00:10:43,800 Speaker 3: did you kind of deal with those two earnings announcement? 202 00:10:43,880 --> 00:10:46,160 Speaker 3: How do you think about the tech space in AI 203 00:10:46,360 --> 00:10:47,760 Speaker 3: given what we've seen from the chip makers. 204 00:10:49,080 --> 00:10:51,560 Speaker 1: So look, ASML is a bit of a howler there, 205 00:10:51,600 --> 00:10:54,800 Speaker 1: that's for sure. But you know, and we haven't gotten 206 00:10:54,920 --> 00:10:58,320 Speaker 1: full clarification, but the press release from the company talked 207 00:10:58,320 --> 00:11:00,960 Speaker 1: about the fact that it's really not in the A side, 208 00:11:01,440 --> 00:11:05,160 Speaker 1: it's more in what I call you know doubt, you know, 209 00:11:05,240 --> 00:11:09,640 Speaker 1: easier electronics, et cetera, some weakness in end markets of 210 00:11:09,679 --> 00:11:13,280 Speaker 1: where they sell some of their less advanced so called 211 00:11:13,840 --> 00:11:16,679 Speaker 1: you know, chip equipment into. So we don't think that 212 00:11:16,720 --> 00:11:20,000 Speaker 1: plays into at all that there's going to be weakness 213 00:11:20,040 --> 00:11:23,080 Speaker 1: in nvideo. Jensen Wang has made it pretty clear demand 214 00:11:23,200 --> 00:11:28,080 Speaker 1: is on fire. TSMC is forecasting thirty percent growth and revenue, 215 00:11:28,320 --> 00:11:31,680 Speaker 1: So we think the gen Ai and demand for chips 216 00:11:32,360 --> 00:11:36,080 Speaker 1: is very much alive and well so much so, so 217 00:11:36,320 --> 00:11:39,800 Speaker 1: much so that there could be some near term shortages 218 00:11:39,840 --> 00:11:43,720 Speaker 1: as we head into twenty twenty five in components, chips, 219 00:11:43,720 --> 00:11:46,240 Speaker 1: et cetera. And funny enough, before we get to the 220 00:11:46,280 --> 00:11:49,000 Speaker 1: big productivity boom of jen Ai, we're gonna have a 221 00:11:49,040 --> 00:11:52,439 Speaker 1: bit of inflation that comes from these shortages, So something 222 00:11:52,480 --> 00:11:54,320 Speaker 1: we're keeping an eye on, Nancy. 223 00:11:54,320 --> 00:11:55,760 Speaker 5: I think the last time that you and I spoke, 224 00:11:55,880 --> 00:11:58,480 Speaker 5: China had unveiled maybe the first of these initiatives to 225 00:12:00,160 --> 00:12:03,920 Speaker 5: do fiscal stimulus monetary stimulus. There was great excitement about 226 00:12:03,920 --> 00:12:06,640 Speaker 5: that than that ebbed is. There is some skepticism about 227 00:12:06,679 --> 00:12:08,560 Speaker 5: what that actually meant and how China might implement it. 228 00:12:08,600 --> 00:12:10,400 Speaker 5: We got these new growth figures today, which I think 229 00:12:10,400 --> 00:12:12,600 Speaker 5: are on the low end for the last six quarters, 230 00:12:13,120 --> 00:12:16,000 Speaker 5: but some more clarity from the Chinese Central Bank this morning. 231 00:12:16,520 --> 00:12:18,720 Speaker 5: How are you looking at China as you kind of 232 00:12:18,720 --> 00:12:22,640 Speaker 5: look at the investment landscape globally and processing what we've 233 00:12:22,640 --> 00:12:25,079 Speaker 5: heard both from policymakers there on the fiscal side and 234 00:12:25,120 --> 00:12:26,320 Speaker 5: monetary policy side. 235 00:12:27,679 --> 00:12:30,559 Speaker 1: So the good news is in China it's kind of Houston. 236 00:12:30,600 --> 00:12:33,920 Speaker 1: We have a problem, right, So finally China is dealing 237 00:12:33,960 --> 00:12:37,240 Speaker 1: with both the deflation and slow down in the economy. 238 00:12:37,440 --> 00:12:41,200 Speaker 1: But we believe the fiscal and stimulus so far is 239 00:12:41,280 --> 00:12:44,040 Speaker 1: not kind of in the Dragy school of whatever it takes, right, 240 00:12:44,679 --> 00:12:47,920 Speaker 1: we think China probably needs a trillion and a half 241 00:12:48,000 --> 00:12:51,240 Speaker 1: of stimulus fiscal and monetary combined with an emphasis on 242 00:12:51,280 --> 00:12:53,760 Speaker 1: the fiscal. They've done about a third of that, or 243 00:12:53,760 --> 00:12:56,480 Speaker 1: at least hinted at something like that, so we don't 244 00:12:56,520 --> 00:13:00,880 Speaker 1: think it's enough. More importantly, China has some big strugruel issues, right. 245 00:13:00,920 --> 00:13:03,080 Speaker 1: It's got a very high savings rate, it's got an 246 00:13:03,160 --> 00:13:06,920 Speaker 1: aging demographic, unemployment and double digit and lack of the 247 00:13:06,960 --> 00:13:10,960 Speaker 1: social safety net. So that is really a problem for consumption, 248 00:13:11,320 --> 00:13:13,800 Speaker 1: particularly as a lot of those consumers but their money 249 00:13:13,840 --> 00:13:16,920 Speaker 1: and the property market which isn't doing too well. And 250 00:13:16,960 --> 00:13:20,960 Speaker 1: then they've got a strategy for export growth, right, let's 251 00:13:21,040 --> 00:13:26,000 Speaker 1: be manufacturer of a naissance, be the world's leader in manufacturing. 252 00:13:26,000 --> 00:13:28,600 Speaker 1: And the problem is if their domestic economy is weak, 253 00:13:29,000 --> 00:13:31,559 Speaker 1: that creates excess capacity that they want to ship to 254 00:13:31,600 --> 00:13:33,760 Speaker 1: the rest of the world. The rest of the world 255 00:13:33,760 --> 00:13:37,200 Speaker 1: doesn't want it, and so that brings tariffs and trade 256 00:13:37,280 --> 00:13:40,160 Speaker 1: tensions and the like. So look, we think there are 257 00:13:40,160 --> 00:13:44,600 Speaker 1: some cheap Chinese shares, there is some value in the market, 258 00:13:44,800 --> 00:13:48,079 Speaker 1: but overall we think the combination of structural and cyclical 259 00:13:49,000 --> 00:13:52,600 Speaker 1: not yet dealt with by the Chinese authorities. But the 260 00:13:52,640 --> 00:13:55,600 Speaker 1: good news is it's removed what I call the tail 261 00:13:55,720 --> 00:13:59,960 Speaker 1: risk of China kind of dragging the world lower width. 262 00:14:00,280 --> 00:14:04,000 Speaker 1: So in that sense, the monetary and fiscal stimulus is 263 00:14:04,040 --> 00:14:07,359 Speaker 1: a positive from an overall global growth perspective. 264 00:14:07,800 --> 00:14:09,839 Speaker 3: Nancy, thanks so much for joining us, as I always 265 00:14:09,840 --> 00:14:12,840 Speaker 3: appreciate getting your thoughts and your perspective. Nancy Curtin, Folks, 266 00:14:12,960 --> 00:14:15,640 Speaker 3: she's a partner, she's a global CIO. She's the head 267 00:14:15,640 --> 00:14:19,600 Speaker 3: of Investment advisory at alt Ittaman Global. Nancy's been on 268 00:14:19,880 --> 00:14:23,120 Speaker 3: Global Wall Street four decades and we appreciate getting hurt. 269 00:14:23,400 --> 00:14:27,680 Speaker 2: This is the Bloomberg Surveillance Podcast. Listen live each weekday 270 00:14:27,760 --> 00:14:30,960 Speaker 2: starting at seven am Eastern on applecar Play and Android 271 00:14:31,000 --> 00:14:33,880 Speaker 2: Auto with the Bloomberg Business app. You can also listen 272 00:14:33,960 --> 00:14:37,080 Speaker 2: live on Amazon Alexa from our flagship New York station. 273 00:14:37,480 --> 00:14:40,520 Speaker 2: Just say, Alexa playing Bloomberg eleven thirty. 274 00:14:40,840 --> 00:14:43,080 Speaker 3: Our next guest, we need to get right to Gatham Maconda. 275 00:14:43,120 --> 00:14:45,400 Speaker 3: He's a lecturer of management practice at the Yale School 276 00:14:45,400 --> 00:14:49,400 Speaker 3: of Management is also the author of Picking Presidents. Gatham, 277 00:14:49,440 --> 00:14:51,000 Speaker 3: thanks so much for joining us here on our studio. 278 00:14:52,000 --> 00:14:53,680 Speaker 3: I don't think anybody knows how we're going to pick 279 00:14:53,680 --> 00:14:57,720 Speaker 3: this president come three weeks time. What's your view of 280 00:14:57,720 --> 00:15:00,240 Speaker 3: this election? In these campaigns kind of where we are today. 281 00:15:00,440 --> 00:15:02,280 Speaker 6: Always a pleasure to be here. Anyone who tells you 282 00:15:02,320 --> 00:15:04,920 Speaker 6: they know what's going to happen is immediately demonstrating that 283 00:15:04,920 --> 00:15:08,200 Speaker 6: they do not know what is going to at So 284 00:15:08,520 --> 00:15:11,680 Speaker 6: when people say it's too close to call, that's basically true. 285 00:15:11,720 --> 00:15:14,480 Speaker 6: I think the Harris campaign seems to feel that they'd 286 00:15:14,560 --> 00:15:18,120 Speaker 6: rather be them than the other guy. I observed that 287 00:15:18,120 --> 00:15:21,080 Speaker 6: the Trump campaign seems to feel that the Harris campaign 288 00:15:21,120 --> 00:15:23,120 Speaker 6: is right because they're acting in a few ways that 289 00:15:23,160 --> 00:15:25,760 Speaker 6: don't seem like someone who thinks that they can tip it. 290 00:15:26,520 --> 00:15:29,520 Speaker 6: Trump has pulled out of four interviews Major interviews CNBC 291 00:15:29,680 --> 00:15:31,720 Speaker 6: sixteen minutes in the last few days. That's kind of 292 00:15:31,720 --> 00:15:34,120 Speaker 6: striking and surprising. For twenty some days to go to 293 00:15:34,160 --> 00:15:38,400 Speaker 6: an election. But the other thing that the big change 294 00:15:39,040 --> 00:15:40,760 Speaker 6: that has happened since Harris came in, and this is 295 00:15:40,760 --> 00:15:42,720 Speaker 6: incredibly static race since you came in, right all these 296 00:15:42,760 --> 00:15:44,280 Speaker 6: people the polls are swinging. No, they're not. 297 00:15:44,520 --> 00:15:45,720 Speaker 3: This is just stable. 298 00:15:46,320 --> 00:15:49,160 Speaker 6: The big changes there's been a convergence in the swing states. 299 00:15:49,520 --> 00:15:52,240 Speaker 6: When Biden was the candidate, he had a path through 300 00:15:52,280 --> 00:15:55,320 Speaker 6: the Midwest and that was it. What's happened since Harris 301 00:15:55,360 --> 00:15:58,200 Speaker 6: is that Arizona, North Carolina, They've all kind of converged. 302 00:15:58,600 --> 00:16:01,240 Speaker 6: And so you do have this odd prospect where what 303 00:16:01,360 --> 00:16:04,000 Speaker 6: is objectively a very close race could become not that 304 00:16:04,160 --> 00:16:07,120 Speaker 6: close in the electoral college on after election day, just 305 00:16:07,160 --> 00:16:10,600 Speaker 6: because all the swing states correlate, and so they carrelate 306 00:16:10,680 --> 00:16:12,800 Speaker 6: for whom That's what no one knows. 307 00:16:13,120 --> 00:16:15,720 Speaker 3: Yeah, that's make sure I was missing something there. 308 00:16:15,720 --> 00:16:18,280 Speaker 5: Okay, you know you bring up polling, and I wanted 309 00:16:18,320 --> 00:16:20,280 Speaker 5: to ask you about this because it's something Paul and 310 00:16:20,320 --> 00:16:22,920 Speaker 5: I have talked about off mic, and that is, there 311 00:16:22,920 --> 00:16:25,040 Speaker 5: are so many polls. We were getting so many of them. 312 00:16:25,480 --> 00:16:27,800 Speaker 5: You look at them in compliment, What did they tell you? 313 00:16:27,840 --> 00:16:29,200 Speaker 5: How do you approach them? I know that there's so 314 00:16:29,240 --> 00:16:31,320 Speaker 5: much skepticism about what they've said in the past, how 315 00:16:31,360 --> 00:16:33,480 Speaker 5: they've been right and wrong. Here we have them at 316 00:16:33,520 --> 00:16:35,160 Speaker 5: such a granular level. So much of what we know 317 00:16:35,160 --> 00:16:37,800 Speaker 5: about these swing states comes from them, and we know 318 00:16:37,880 --> 00:16:40,400 Speaker 5: kind of what issues are most important to voters, how 319 00:16:40,480 --> 00:16:42,280 Speaker 5: much faith do you put into them, and how do 320 00:16:42,320 --> 00:16:43,680 Speaker 5: you look at them kind of holistically. 321 00:16:43,960 --> 00:16:46,320 Speaker 6: Right, So, the polling data in twenty sixteen was actually 322 00:16:46,320 --> 00:16:48,360 Speaker 6: pretty good. The essumate of the popular vote was only 323 00:16:48,400 --> 00:16:50,320 Speaker 6: off by one percent. The polling data in twenty twenty 324 00:16:50,440 --> 00:16:52,120 Speaker 6: was really bad. The estimate of the popular vote was 325 00:16:52,120 --> 00:16:54,560 Speaker 6: off by four percent. What was bad in twenty sixteen 326 00:16:54,640 --> 00:16:57,240 Speaker 6: was the swing state polling, right, which is why the estimates. 327 00:16:56,880 --> 00:16:57,360 Speaker 3: Is two one. 328 00:16:57,400 --> 00:16:59,760 Speaker 6: We're so old, but caveat to that. 329 00:17:00,080 --> 00:17:00,360 Speaker 3: Right now. 330 00:17:00,600 --> 00:17:02,960 Speaker 6: The thing that makes me really question the polls right 331 00:17:02,960 --> 00:17:07,600 Speaker 6: now is how consistent they are. Interesting just polling our 332 00:17:07,640 --> 00:17:11,720 Speaker 6: statistical instruments, normal statistical variation, you should see numbers that 333 00:17:11,800 --> 00:17:14,680 Speaker 6: jump around all the time. Right if Harris is legitimately 334 00:17:14,840 --> 00:17:17,960 Speaker 6: up two percent, let's say she actually is up two percent, 335 00:17:18,440 --> 00:17:20,120 Speaker 6: you should expect to see a fair number of polls 336 00:17:20,119 --> 00:17:23,440 Speaker 6: where Donald Trump is up one We are not seeing that. 337 00:17:23,480 --> 00:17:25,760 Speaker 6: We are just seeing poll after poll after pole coming 338 00:17:25,800 --> 00:17:27,960 Speaker 6: in with roughly the same data over and over again. 339 00:17:28,359 --> 00:17:30,840 Speaker 6: To me, that suggests that the polling companies are hurting 340 00:17:30,960 --> 00:17:32,320 Speaker 6: that nobody wants to explain that. 341 00:17:32,359 --> 00:17:34,399 Speaker 5: What does that mean? When there's hurting polls. 342 00:17:34,480 --> 00:17:36,600 Speaker 6: There's a lot of judgment involved in how you weight 343 00:17:36,720 --> 00:17:39,439 Speaker 6: different populations, how you assess right, are you going to 344 00:17:39,680 --> 00:17:42,600 Speaker 6: use recollections of how people voted four years ago? For example? 345 00:17:42,600 --> 00:17:44,240 Speaker 6: A lot of polls will ask how did you vote 346 00:17:44,240 --> 00:17:46,520 Speaker 6: to four years ago and use that to assess, like, 347 00:17:46,880 --> 00:17:49,200 Speaker 6: you know, to wait the reweight their sample. The problem 348 00:17:49,240 --> 00:17:51,359 Speaker 6: is people don't actually remember that as well as you think. 349 00:17:51,480 --> 00:17:53,440 Speaker 6: If you ask people a few years after the race, 350 00:17:53,440 --> 00:17:55,800 Speaker 6: who did you vote for, on average, more than sixty 351 00:17:55,840 --> 00:17:57,840 Speaker 6: percent will say they voted for the winning side blocked 352 00:17:57,880 --> 00:18:01,880 Speaker 6: it out. This seems unlikely. Yeah, So when you add 353 00:18:01,880 --> 00:18:05,600 Speaker 6: in there are enough subjective factors into polling that it 354 00:18:05,760 --> 00:18:08,040 Speaker 6: just seems to me like the polling companies might be thinking, 355 00:18:08,080 --> 00:18:11,400 Speaker 6: but nobody wants to be embarrassingly wrong, and they're converging 356 00:18:11,480 --> 00:18:13,840 Speaker 6: on a number which you know, like, look, it might 357 00:18:13,880 --> 00:18:16,119 Speaker 6: be right, but it's not normal for it to be 358 00:18:16,160 --> 00:18:17,960 Speaker 6: this type. This consistent across. 359 00:18:17,640 --> 00:18:18,040 Speaker 4: All the polls. 360 00:18:18,240 --> 00:18:19,600 Speaker 3: One of the other shows that I think a lot 361 00:18:19,600 --> 00:18:22,960 Speaker 3: of people are concerned about is we may not know 362 00:18:23,040 --> 00:18:25,359 Speaker 3: the evening of election day who the winner is. We 363 00:18:25,400 --> 00:18:26,960 Speaker 3: may not know the next day or the day after, 364 00:18:27,080 --> 00:18:28,879 Speaker 3: and then oh boy, it could get messy and it's 365 00:18:28,880 --> 00:18:31,959 Speaker 3: two thousand and all over again. But on steroids. What 366 00:18:32,080 --> 00:18:35,040 Speaker 3: is the risk there of that type of scenario developing? 367 00:18:35,200 --> 00:18:38,880 Speaker 6: Quite significant, But it also depends on your definition of noe. 368 00:18:39,280 --> 00:18:41,639 Speaker 6: We did not get the networks who somehow we have 369 00:18:41,680 --> 00:18:44,400 Speaker 6: outsourced the job of calling who wins an election too. 370 00:18:44,760 --> 00:18:47,480 Speaker 6: We did not get the networks to declare until several 371 00:18:47,560 --> 00:18:50,040 Speaker 6: days after the election in twenty twenty. But by eleven 372 00:18:50,080 --> 00:18:52,720 Speaker 6: pm on election night, I was texting people saying one 373 00:18:52,760 --> 00:18:54,960 Speaker 6: hundred percent Biden is going to win, Like I am, 374 00:18:55,359 --> 00:18:57,960 Speaker 6: you know, I will bet my condo right now any 375 00:18:57,960 --> 00:19:00,840 Speaker 6: odds you want Biden's gonna win. So we knew, right, 376 00:19:00,880 --> 00:19:05,439 Speaker 6: we just didn't officially know. Okay, this election I suspect 377 00:19:05,640 --> 00:19:07,879 Speaker 6: will look more like twenty twenty, where we'll have a 378 00:19:07,920 --> 00:19:10,880 Speaker 6: really good sense just because I expect the swing states 379 00:19:10,880 --> 00:19:13,000 Speaker 6: to correlate. I expect you know where what we'd have 380 00:19:13,000 --> 00:19:14,439 Speaker 6: to say is, well, there have to be flips in 381 00:19:14,520 --> 00:19:17,040 Speaker 6: like multiple states to reverse it. That doesn't seem. 382 00:19:16,760 --> 00:19:17,199 Speaker 2: Likely to me. 383 00:19:17,760 --> 00:19:20,760 Speaker 6: But but that doesn't mean that we'll have official knowledge 384 00:19:20,760 --> 00:19:23,520 Speaker 6: because if look, if Harris loses, she's gonna she's gonna 385 00:19:23,520 --> 00:19:25,000 Speaker 6: say I lost them. That will be the end of it. 386 00:19:25,240 --> 00:19:27,320 Speaker 6: But if Trump loses, I don't think there's any chance 387 00:19:27,320 --> 00:19:29,159 Speaker 6: that he'll do anything other than claim it was stolen. 388 00:19:29,240 --> 00:19:31,600 Speaker 6: He'll legally he'll do that, and then we're off to 389 00:19:31,600 --> 00:19:33,640 Speaker 6: the races we really have We really don't have a race, son, 390 00:19:33,640 --> 00:19:34,520 Speaker 6: So what's going to happen after that? 391 00:19:34,840 --> 00:19:36,560 Speaker 5: We have been through this week when both of these 392 00:19:36,600 --> 00:19:39,000 Speaker 5: candidates had made overtures to populations you'd think would not 393 00:19:39,040 --> 00:19:41,600 Speaker 5: be natural supporters and them. So for Kamala Harris, it's 394 00:19:41,760 --> 00:19:44,879 Speaker 5: Republican Republican women voters in Pennsylvania. For Donald Trump, it 395 00:19:44,920 --> 00:19:46,600 Speaker 5: was going down to Miami to speak to this audience 396 00:19:46,600 --> 00:19:50,760 Speaker 5: of Latino voters from the Univision studios there. I'm curious 397 00:19:50,800 --> 00:19:52,760 Speaker 5: sort of what you make of that outreach that they're doing. 398 00:19:52,760 --> 00:19:54,680 Speaker 5: And so when you look at the game plan going 399 00:19:54,680 --> 00:19:57,480 Speaker 5: from here to November, the fifth is the should the 400 00:19:57,560 --> 00:19:59,959 Speaker 5: game be to reach out to those undecided voters, how 401 00:20:00,080 --> 00:20:02,040 Speaker 5: few of them there may be, or is it simply 402 00:20:02,080 --> 00:20:04,000 Speaker 5: to focus on that get out the vote effort to 403 00:20:04,000 --> 00:20:05,760 Speaker 5: make sure that those are committed to these candidates make 404 00:20:05,800 --> 00:20:07,280 Speaker 5: it to the polls on election day. 405 00:20:07,560 --> 00:20:09,600 Speaker 6: True undecided voters last time I was on I said 406 00:20:09,640 --> 00:20:12,119 Speaker 6: three percent true undercided voters is probably under two percent. Well, 407 00:20:12,119 --> 00:20:14,919 Speaker 6: at this point, we're talking about really tiny margins. A 408 00:20:15,000 --> 00:20:18,119 Speaker 6: lot of what people are looking at which seems like 409 00:20:18,119 --> 00:20:20,520 Speaker 6: going to undecided voters. I don't think it's actually about that. 410 00:20:21,000 --> 00:20:23,840 Speaker 6: Right If in North Carolina Harris is going to win 411 00:20:23,840 --> 00:20:26,000 Speaker 6: the cities and lose the rural areas, but if she 412 00:20:26,200 --> 00:20:29,280 Speaker 6: cuts into Trump's margin in the rural areas, the cities 413 00:20:29,280 --> 00:20:32,480 Speaker 6: will take her right in Pennsylvania's you know, it's the 414 00:20:32,480 --> 00:20:34,960 Speaker 6: same thing. So what we're seeing is what my code 415 00:20:34,960 --> 00:20:37,520 Speaker 6: as undecided voters actually to me looks a lot more 416 00:20:37,600 --> 00:20:40,399 Speaker 6: like we're trying to do essentially a covert turnout, get 417 00:20:40,440 --> 00:20:42,119 Speaker 6: out the vote margin in areas where we're going to 418 00:20:42,160 --> 00:20:43,640 Speaker 6: get blown out. We just don't want to get blown 419 00:20:43,640 --> 00:20:44,320 Speaker 6: out by that much. 420 00:20:45,280 --> 00:20:47,720 Speaker 3: So it is I've heard from folks get out the 421 00:20:47,800 --> 00:20:50,120 Speaker 3: vote kind of election. Does one side or the other 422 00:20:50,160 --> 00:20:50,960 Speaker 3: have an advantage in that? 423 00:20:51,760 --> 00:20:54,480 Speaker 6: So from people on the ground in Pennsylvania that I 424 00:20:54,520 --> 00:20:57,119 Speaker 6: talk to. That's where I've been focusing my attention. It 425 00:20:57,240 --> 00:20:59,520 Speaker 6: certainly feels like the Harris operation is a lot more 426 00:20:59,520 --> 00:21:03,840 Speaker 6: sophisticated it. What we've seen is is the Trump campaign 427 00:21:03,880 --> 00:21:06,760 Speaker 6: is essentially outsourced. There get out the vote operation essentially 428 00:21:06,760 --> 00:21:09,680 Speaker 6: with Elon Musk and his superpag. Obviously, that's lavishly funded. 429 00:21:09,720 --> 00:21:12,560 Speaker 6: He puts seventy five million dollars in just just recently there, 430 00:21:12,760 --> 00:21:15,760 Speaker 6: but we don't see them on the ground. I'm not 431 00:21:15,800 --> 00:21:18,840 Speaker 6: totally certain where this money is going. Frankly. The question 432 00:21:18,960 --> 00:21:20,920 Speaker 6: is that the Trump people have a theory of victory, 433 00:21:21,440 --> 00:21:23,600 Speaker 6: and it is not a dumb theory of victory, right. 434 00:21:23,600 --> 00:21:25,880 Speaker 6: This is not the amateur hour campaign we saw twenty 435 00:21:25,920 --> 00:21:27,840 Speaker 6: sixteen and twenty These people know what they're doing, okay, 436 00:21:27,960 --> 00:21:29,920 Speaker 6: And the theory of victory is that they can get 437 00:21:29,960 --> 00:21:32,960 Speaker 6: people who do not normally vote to vote for Donald Trump. 438 00:21:33,200 --> 00:21:34,399 Speaker 6: If they're right about that, then they win. 439 00:21:34,440 --> 00:21:37,240 Speaker 3: This lecture, okay, Gotham, thank you so much, back big 440 00:21:37,320 --> 00:21:39,760 Speaker 3: with you. Yeah, great stuff, Gotham, Maconda. He's a lecture 441 00:21:39,760 --> 00:21:43,159 Speaker 3: of the management practice. Now it's at the Yale School 442 00:21:43,160 --> 00:21:43,760 Speaker 3: of Management. 443 00:21:44,119 --> 00:21:44,239 Speaker 2: Now. 444 00:21:44,280 --> 00:21:46,600 Speaker 3: He walks into Gotham with a very nice three piece suit. 445 00:21:46,640 --> 00:21:48,119 Speaker 3: But he's got this pin on his lapel. It's got 446 00:21:48,160 --> 00:21:51,479 Speaker 3: the American flag, also the flag of Harvard, and you 447 00:21:51,520 --> 00:21:53,520 Speaker 3: walk into your classroom at Yale with that. 448 00:21:53,680 --> 00:21:56,680 Speaker 6: The only time in my life I ever wear Harvard 449 00:21:56,720 --> 00:21:57,720 Speaker 6: gear is when I'm on yellow. 450 00:21:57,760 --> 00:22:01,119 Speaker 3: YEA, All right, stuff there. We'd like to see that 451 00:22:01,240 --> 00:22:07,760 Speaker 3: rivalry still in full tech. That's good to see. 452 00:22:09,440 --> 00:22:13,760 Speaker 2: This is the Bloomberg Surveillance Podcast. Listen live each weekday 453 00:22:13,840 --> 00:22:17,040 Speaker 2: starting at seven am Eastern on applecar Play and Android 454 00:22:17,080 --> 00:22:20,000 Speaker 2: Auto with the Bloomberg Business app. You can also watch 455 00:22:20,080 --> 00:22:23,320 Speaker 2: us live every weekday on YouTube and always on the 456 00:22:23,320 --> 00:22:24,320 Speaker 2: Bloomberg terminal. 457 00:22:24,400 --> 00:22:25,800 Speaker 3: Well, let's get a sense of this M and A 458 00:22:25,960 --> 00:22:28,320 Speaker 3: business for the remainder this year and kind of what 459 00:22:28,359 --> 00:22:30,399 Speaker 3: the big banks you're looking for next year. Carol Striker 460 00:22:30,480 --> 00:22:33,800 Speaker 3: joins us. She is America's regional head of Deal Advisory 461 00:22:34,000 --> 00:22:36,440 Speaker 3: for KPMG. Carol, thanks so much for joining us here. 462 00:22:36,480 --> 00:22:39,880 Speaker 3: Talk to us about M and A in twenty twenty four, 463 00:22:39,920 --> 00:22:42,959 Speaker 3: how's the business been for Global Wall Street? And then 464 00:22:43,000 --> 00:22:44,840 Speaker 3: we'll talk about next year. But how's twenty four been? 465 00:22:46,240 --> 00:22:49,040 Speaker 7: Yeah, twenty four has been a better year than twenty three. 466 00:22:49,840 --> 00:22:52,840 Speaker 7: We are seeing deals increasing in twenty four. We've seen 467 00:22:52,880 --> 00:22:55,679 Speaker 7: them in preasing, but you know, twenty three with a 468 00:22:55,800 --> 00:23:00,919 Speaker 7: really low year, so it's it's not a robust twenty 469 00:23:00,920 --> 00:23:03,160 Speaker 7: four if you kind of look at the last year 470 00:23:03,200 --> 00:23:05,520 Speaker 7: that deal makers kind of look as the last year 471 00:23:05,560 --> 00:23:09,600 Speaker 7: of normality was twenty and nineteen, and twenty four is 472 00:23:09,640 --> 00:23:13,480 Speaker 7: still lower than twenty nineteen. So better than last year, 473 00:23:13,560 --> 00:23:16,280 Speaker 7: but still not a super robust deal market. 474 00:23:16,680 --> 00:23:18,639 Speaker 5: I'll take the follow up picking up on what Paul said. So, 475 00:23:18,680 --> 00:23:22,119 Speaker 5: looking ahead to twenty twenty five, what in gender's optimism 476 00:23:22,280 --> 00:23:25,320 Speaker 5: in bankers and lawyers in your clients about how the 477 00:23:25,359 --> 00:23:25,760 Speaker 5: market is. 478 00:23:25,760 --> 00:23:26,200 Speaker 3: Going to look. 479 00:23:27,359 --> 00:23:30,320 Speaker 7: Yeah, I think the sentiment around from everyone we're talking to. 480 00:23:30,560 --> 00:23:32,960 Speaker 7: I was with a one hundred and fifty deal maker 481 00:23:33,200 --> 00:23:36,919 Speaker 7: yesterday talking about the M and A market, and the 482 00:23:37,000 --> 00:23:39,720 Speaker 7: sentiment everywhere is that twenty five is going to be 483 00:23:39,760 --> 00:23:43,200 Speaker 7: a more robust year and twenty six. We're talking about 484 00:23:43,240 --> 00:23:43,879 Speaker 7: kind of the next. 485 00:23:43,800 --> 00:23:44,399 Speaker 1: Couple of years. 486 00:23:44,400 --> 00:23:47,080 Speaker 7: And you know, there's a few things that we're looking 487 00:23:47,119 --> 00:23:50,800 Speaker 7: at that are going to be you know, things that 488 00:23:50,800 --> 00:23:53,639 Speaker 7: are headwinds and tailwinds in the deal market. Some of 489 00:23:53,680 --> 00:23:55,800 Speaker 7: the things that are positive, it's interest rates that you 490 00:23:55,840 --> 00:23:58,680 Speaker 7: guys know are coming down and that is an important 491 00:23:58,720 --> 00:24:03,240 Speaker 7: factor in deal making. The election hopefully will be behind us, 492 00:24:03,320 --> 00:24:06,760 Speaker 7: and some certainty will be back into the market, and 493 00:24:06,840 --> 00:24:09,120 Speaker 7: I think that will be something that will also help 494 00:24:09,160 --> 00:24:12,280 Speaker 7: with the M and A market. I think this next quarter, 495 00:24:12,880 --> 00:24:14,359 Speaker 7: the remainder of the year is still going to be 496 00:24:14,440 --> 00:24:18,200 Speaker 7: on the light or side given the election. I think 497 00:24:18,320 --> 00:24:21,680 Speaker 7: what deal makers want is that certainty. And so those 498 00:24:21,720 --> 00:24:24,480 Speaker 7: are some of the things that we're looking at for twenty. 499 00:24:24,119 --> 00:24:29,240 Speaker 3: Five private equity where they in this deal market here? 500 00:24:29,520 --> 00:24:32,680 Speaker 3: I know there's just tons of capital on the sidelines 501 00:24:32,720 --> 00:24:35,880 Speaker 3: for these private equity folks. They're always in fundraising mode, 502 00:24:35,880 --> 00:24:38,439 Speaker 3: it seems, but we haven't seen them maybe back in 503 00:24:38,480 --> 00:24:40,879 Speaker 3: the market and the size. Maybe some of the bankers 504 00:24:40,880 --> 00:24:43,159 Speaker 3: would like to see. Where's the private equity sector as 505 00:24:43,200 --> 00:24:43,560 Speaker 3: a driver? 506 00:24:44,720 --> 00:24:47,359 Speaker 7: Yeah, you're exactly right. There is so much dry powder 507 00:24:47,359 --> 00:24:49,919 Speaker 7: out there. The private equity firms need to put that 508 00:24:49,960 --> 00:24:52,239 Speaker 7: money to work. And I think the thing that is 509 00:24:52,440 --> 00:24:56,200 Speaker 7: most impactful that we see from a private equity perspective 510 00:24:56,240 --> 00:24:59,160 Speaker 7: is the interest rates coming down. So especially those LBOs 511 00:24:59,200 --> 00:25:02,560 Speaker 7: as leveraged by interest rates needing to come down to 512 00:25:02,600 --> 00:25:05,160 Speaker 7: be able to make those deals. A little less costly 513 00:25:05,200 --> 00:25:08,080 Speaker 7: for that cost of capital. And so when we did 514 00:25:08,119 --> 00:25:12,160 Speaker 7: our M and A survey of deal makers, it came 515 00:25:12,160 --> 00:25:14,800 Speaker 7: out very clear that in the first half of twenty five, 516 00:25:14,880 --> 00:25:18,800 Speaker 7: PE is more bullish around having a more robust M 517 00:25:18,840 --> 00:25:22,359 Speaker 7: and A market, driven again by those interest rates. It 518 00:25:22,440 --> 00:25:25,840 Speaker 7: was interesting in our corporate clients in contrast, so that 519 00:25:25,840 --> 00:25:27,560 Speaker 7: they thought it would be the latter part of twenty 520 00:25:27,560 --> 00:25:30,960 Speaker 7: five where they'd be more robust deal market for them. 521 00:25:31,680 --> 00:25:34,320 Speaker 5: I wanted to ask you about regulatory clarity. So you 522 00:25:34,320 --> 00:25:36,080 Speaker 5: mentioned the election at this obstacle. I think for a 523 00:25:36,119 --> 00:25:38,200 Speaker 5: lot of CEOs as they look at the prospects of 524 00:25:38,560 --> 00:25:41,240 Speaker 5: M and A, and I wonder, as you listen to 525 00:25:41,280 --> 00:25:45,720 Speaker 5: these two candidates on the campaign trail, how throw their 526 00:25:45,760 --> 00:25:49,760 Speaker 5: policy on regulation seems to be. So Obviously, we've lived 527 00:25:49,800 --> 00:25:54,080 Speaker 5: through a Trump administration before, and even though Vice President 528 00:25:54,080 --> 00:25:56,280 Speaker 5: Harris has tried to draw a distinction between what her 529 00:25:56,440 --> 00:25:58,160 Speaker 5: presidency would be like compared to the one that she's 530 00:25:58,200 --> 00:26:01,199 Speaker 5: in now with under Joe Biden, do we have a 531 00:26:01,240 --> 00:26:03,560 Speaker 5: good sense of what the regulatory environment would be like 532 00:26:03,680 --> 00:26:04,760 Speaker 5: under each of these candidates. 533 00:26:06,359 --> 00:26:06,679 Speaker 1: Yeah. 534 00:26:06,720 --> 00:26:08,520 Speaker 7: So here's what I would say is that there has 535 00:26:08,600 --> 00:26:13,320 Speaker 7: been increased scrutinity from an antitrust perspective for several years. 536 00:26:13,320 --> 00:26:16,240 Speaker 7: That's not just been within this administration, and I think 537 00:26:16,480 --> 00:26:18,440 Speaker 7: that as we think about the future and what we're 538 00:26:18,480 --> 00:26:21,760 Speaker 7: hearing from our clients is that that scrutiny is not 539 00:26:21,840 --> 00:26:26,440 Speaker 7: going to go away in the next term of whoever's 540 00:26:26,440 --> 00:26:29,920 Speaker 7: in office. I think they're working closely with their lawyers 541 00:26:29,920 --> 00:26:33,919 Speaker 7: to assess what scrutiny might be there for that in 542 00:26:34,000 --> 00:26:37,800 Speaker 7: particular deal in working closely on that, and so that's 543 00:26:37,840 --> 00:26:40,520 Speaker 7: what I would You know, there's not a clear one 544 00:26:40,600 --> 00:26:43,600 Speaker 7: path leads one way and one one path leads another way. 545 00:26:44,520 --> 00:26:46,160 Speaker 3: Carol, If I want to go out and buy a company, 546 00:26:46,280 --> 00:26:47,800 Speaker 3: Who's going to lend me the money because I'm going 547 00:26:47,840 --> 00:26:50,480 Speaker 3: to want to use some leverage to leverage my equity returns. 548 00:26:51,280 --> 00:26:53,399 Speaker 3: Are the banks still there or where am I going 549 00:26:53,440 --> 00:26:54,040 Speaker 3: to get the money? 550 00:26:54,800 --> 00:26:55,159 Speaker 4: Yeah? 551 00:26:55,200 --> 00:26:58,160 Speaker 7: Absolutely, great question. You can only get deals done if 552 00:26:58,160 --> 00:27:01,200 Speaker 7: you've got the money. So a couple thingsly, for those 553 00:27:01,240 --> 00:27:06,159 Speaker 7: that are using debt to finance the acquisition, the banks 554 00:27:06,160 --> 00:27:09,440 Speaker 7: are open. You know, if you rewind gosh, around six 555 00:27:09,480 --> 00:27:11,560 Speaker 7: eight months ago, that was not the case. And so 556 00:27:11,640 --> 00:27:14,840 Speaker 7: there is money out there. It's a little bit more 557 00:27:14,880 --> 00:27:19,040 Speaker 7: expensive than it was, you know, several years ago, but 558 00:27:19,920 --> 00:27:23,520 Speaker 7: it is available, and there's also the opportunity for some 559 00:27:23,560 --> 00:27:27,880 Speaker 7: of our corporates to be using their stock as well 560 00:27:27,920 --> 00:27:30,360 Speaker 7: as they're flushed with cash on their balance sheets as well. 561 00:27:31,600 --> 00:27:32,320 Speaker 3: Let me just ask you. 562 00:27:32,320 --> 00:27:35,159 Speaker 5: You talked about the Federal Reserve and the path of 563 00:27:35,480 --> 00:27:37,760 Speaker 5: rate cutting, and I'm curious to sort of how catalytic 564 00:27:37,800 --> 00:27:39,640 Speaker 5: that's going to be. So we've you know, joked about 565 00:27:39,640 --> 00:27:42,040 Speaker 5: refinancing mortgages and the housing market and all of that 566 00:27:43,280 --> 00:27:47,200 Speaker 5: in this space in particular, how much of a catalyst 567 00:27:47,320 --> 00:27:50,199 Speaker 5: how much did the dam break when you saw the 568 00:27:50,240 --> 00:27:52,520 Speaker 5: FED cut by fifty basis points, just kind of when 569 00:27:52,520 --> 00:27:54,679 Speaker 5: we saw the start of what we anticipate to be 570 00:27:54,880 --> 00:27:56,200 Speaker 5: a cycle of rate cuts. 571 00:27:57,000 --> 00:28:01,000 Speaker 7: Yeah, it's really interesting because when that rate hit cut hit, 572 00:28:01,320 --> 00:28:05,520 Speaker 7: it's also all the election stuff is going on, and 573 00:28:05,560 --> 00:28:09,680 Speaker 7: so it's hard to biper kate, if you will, what's 574 00:28:09,720 --> 00:28:14,679 Speaker 7: happening with the different things interest rates and election because 575 00:28:14,720 --> 00:28:17,560 Speaker 7: oftentimes in election years we see a depressed m and 576 00:28:17,600 --> 00:28:19,920 Speaker 7: a market. That's what we've seen for the last several 577 00:28:20,480 --> 00:28:24,080 Speaker 7: election years. All that being said, your question is around 578 00:28:24,119 --> 00:28:26,399 Speaker 7: those interest rates, and it is a catalyst for M 579 00:28:26,400 --> 00:28:29,520 Speaker 7: and A we haven't seen the DM break if you will. 580 00:28:29,920 --> 00:28:33,679 Speaker 7: We at kpmgr our chief economist is predicting another fifty 581 00:28:33,720 --> 00:28:37,600 Speaker 7: basis points drop twenty five basis points in November twenty 582 00:28:37,600 --> 00:28:40,480 Speaker 7: five in December, and when we look at our M 583 00:28:40,520 --> 00:28:42,920 Speaker 7: and A survey, what our deal makers said is that 584 00:28:43,000 --> 00:28:46,520 Speaker 7: a fifty basis point drop would spur them into doing 585 00:28:46,600 --> 00:28:49,920 Speaker 7: activity like it was in twenty twenty one. Now this 586 00:28:50,000 --> 00:28:52,880 Speaker 7: is deal makers who that's what they do for a living, right, but. 587 00:28:52,840 --> 00:28:54,440 Speaker 5: It is to get back in the game. 588 00:28:54,600 --> 00:28:55,600 Speaker 6: Yes, absolutely. 589 00:28:55,680 --> 00:28:57,440 Speaker 7: I always say it's like a kid asking a kid 590 00:28:57,440 --> 00:28:59,560 Speaker 7: in a candy store if they want a candy, of 591 00:28:59,560 --> 00:29:02,800 Speaker 7: course going to say yes, let's go Carol. 592 00:29:02,840 --> 00:29:05,400 Speaker 3: Are there any sectors or what are the sectors that 593 00:29:05,440 --> 00:29:08,320 Speaker 3: you think might be your clients think might be active 594 00:29:08,360 --> 00:29:09,240 Speaker 3: over the next year or two. 595 00:29:10,600 --> 00:29:13,280 Speaker 7: Well, you know, what we've seen so far is that 596 00:29:13,400 --> 00:29:17,200 Speaker 7: TMT has been a sector that's been extremely busy. On 597 00:29:17,240 --> 00:29:21,600 Speaker 7: the contrast, healthcare has been significantly down. We're starting to 598 00:29:21,640 --> 00:29:25,760 Speaker 7: see that pop up a little bit from a sector perspective. 599 00:29:26,200 --> 00:29:29,680 Speaker 7: But you know, of course, I think there's things around 600 00:29:29,720 --> 00:29:34,560 Speaker 7: our energy, energy needs energy clean energy is another one 601 00:29:34,600 --> 00:29:38,400 Speaker 7: where we're seeing some uptick in the deal market as well. 602 00:29:39,880 --> 00:29:42,160 Speaker 3: Carol, thanks so much for joining us. I really appreciate 603 00:29:42,160 --> 00:29:46,240 Speaker 3: getting your perspective on the global M and A business. 604 00:29:46,280 --> 00:29:49,360 Speaker 3: Twenty four better than twenty three. Expectations twenty five might 605 00:29:49,400 --> 00:29:51,680 Speaker 3: be pretty solid as well. That's certainly what we hear 606 00:29:51,760 --> 00:29:55,120 Speaker 3: from the big investment banks that have reported their earnings 607 00:29:55,360 --> 00:29:58,920 Speaker 3: so far. Carol Striker, she's America's regional head of Deal 608 00:29:59,000 --> 00:30:02,880 Speaker 3: Advisory KPMG. Her clients are the big M and A 609 00:30:02,960 --> 00:30:05,480 Speaker 3: bankers around global Wall Street, so it's good to check 610 00:30:05,480 --> 00:30:06,880 Speaker 3: in with Carol and get a sense of kind of 611 00:30:06,880 --> 00:30:10,240 Speaker 3: where her clients think this business may go. 612 00:30:10,520 --> 00:30:15,000 Speaker 2: This is the Bloomberg Surveillance podcast, available on Apple, Spotify, 613 00:30:15,160 --> 00:30:19,240 Speaker 2: and anywhere else you get your podcasts. Listen live each weekday, 614 00:30:19,360 --> 00:30:22,440 Speaker 2: seven to ten am Eastern on Bloomberg dot com, the 615 00:30:22,520 --> 00:30:26,320 Speaker 2: iHeartRadio app, tune In, and the Bloomberg Business app. You 616 00:30:26,360 --> 00:30:29,680 Speaker 2: can also watch us live every weekday on YouTube and 617 00:30:29,800 --> 00:30:31,400 Speaker 2: always on the Bloomberg terminal.