1 00:00:02,520 --> 00:00:13,760 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is the Bloomberg 2 00:00:13,840 --> 00:00:17,920 Speaker 1: Surveillance Podcast. Catch us live weekdays at seven am Eastern 3 00:00:18,200 --> 00:00:22,000 Speaker 1: on Apple CarPlay or Android Auto with the Bloomberg Business App. 4 00:00:22,360 --> 00:00:25,680 Speaker 1: Listen on demand wherever you get your podcasts, or watch 5 00:00:25,760 --> 00:00:27,040 Speaker 1: us live on YouTube. 6 00:00:27,320 --> 00:00:30,280 Speaker 2: Claudia Sam on Fire with us a few days ago, 7 00:00:30,880 --> 00:00:34,000 Speaker 2: and she has written up a storm of brilliance. We're 8 00:00:34,040 --> 00:00:36,880 Speaker 2: thrilled that she could join us. Some new century advisors 9 00:00:37,000 --> 00:00:41,879 Speaker 2: or definitive work at the FED and at Michigan as well. Claudia, 10 00:00:41,960 --> 00:00:45,199 Speaker 2: of all your charts, to me, the most emotional one is, 11 00:00:45,320 --> 00:00:49,839 Speaker 2: unlike past expansions, the unemployment rate is rising. Are we 12 00:00:49,920 --> 00:00:53,680 Speaker 2: in an expansion? Are you on the acclaimed some recession? 13 00:00:53,760 --> 00:00:55,840 Speaker 2: Watch now? 14 00:00:55,880 --> 00:00:57,480 Speaker 3: I mean we are in an expansion. 15 00:00:57,600 --> 00:01:01,600 Speaker 4: It is very unusual to have a jobless expansion at 16 00:01:01,600 --> 00:01:03,920 Speaker 4: this point, you know, on a gradual rising. 17 00:01:03,920 --> 00:01:05,160 Speaker 3: The unemployment rate is still a rising. 18 00:01:05,160 --> 00:01:07,720 Speaker 4: The unemployment rate, it is a problem for some workers, 19 00:01:07,760 --> 00:01:11,080 Speaker 4: but it doesn't the economy does not have right now 20 00:01:11,120 --> 00:01:14,480 Speaker 4: that kind of recessionary dynamic, those rapid increases in the 21 00:01:15,360 --> 00:01:18,319 Speaker 4: unemployment rate, and it's been a feature of the economy 22 00:01:18,360 --> 00:01:20,600 Speaker 4: for two and a half years now that we've seen this, 23 00:01:20,720 --> 00:01:22,480 Speaker 4: so it's very unusual. 24 00:01:22,800 --> 00:01:25,639 Speaker 5: So cloudy. If we do have an economy that is growing, 25 00:01:25,800 --> 00:01:29,200 Speaker 5: but a workforce that is not necessarily growing along with it, 26 00:01:29,240 --> 00:01:31,200 Speaker 5: does that mean we're more productive? 27 00:01:33,600 --> 00:01:35,240 Speaker 3: Not necessarily I mean the. 28 00:01:36,880 --> 00:01:40,160 Speaker 4: Low higher or maybe we'll see today no higher economy 29 00:01:40,400 --> 00:01:43,000 Speaker 4: that is really rough on people coming into the labor 30 00:01:43,040 --> 00:01:45,160 Speaker 4: market for the first time or maybe coming back into 31 00:01:45,200 --> 00:01:47,920 Speaker 4: the labor market like this is. They are really facing 32 00:01:47,960 --> 00:01:51,600 Speaker 4: a tough labor market and that loses all kinds of potential, 33 00:01:51,680 --> 00:01:53,960 Speaker 4: particularly for people at the beginning of their career, to 34 00:01:54,000 --> 00:01:56,760 Speaker 4: get off on the wrong foot. We're seeing a lot 35 00:01:56,840 --> 00:01:59,440 Speaker 4: less movement of people from jobs to jobs, So maybe 36 00:01:59,440 --> 00:02:01,880 Speaker 4: that makes it productive because they've been on the job longer. 37 00:02:02,000 --> 00:02:04,920 Speaker 3: But I wouldn't you know, maybe frame it quite that way. 38 00:02:05,080 --> 00:02:07,520 Speaker 2: Doctor somillby with us after the report. Let me squeeze 39 00:02:07,520 --> 00:02:10,240 Speaker 2: this in, Claudia if I could. You've got a brilliant 40 00:02:10,320 --> 00:02:12,960 Speaker 2: three month moving average chart, which is the way I 41 00:02:13,120 --> 00:02:17,480 Speaker 2: roll in the negative intigran This is calculus talk, Paul, 42 00:02:17,600 --> 00:02:21,040 Speaker 2: Stay with me here. The negative into grand is late 43 00:02:21,400 --> 00:02:27,959 Speaker 2: spring last year. We're basically on revision potentially into negative 44 00:02:28,000 --> 00:02:30,400 Speaker 2: non farm payrolls back to when the Red Sox were 45 00:02:30,440 --> 00:02:34,000 Speaker 2: gonna win last year. Is it that grim? We've really 46 00:02:34,040 --> 00:02:37,720 Speaker 2: been that saggy since April of last year. 47 00:02:39,360 --> 00:02:41,760 Speaker 3: Yeah, I mean, job creation really hit a wall. 48 00:02:41,960 --> 00:02:45,160 Speaker 4: Now we can argue about whether it's grim in terms 49 00:02:45,160 --> 00:02:46,919 Speaker 4: of how worried we should be about this, because again 50 00:02:47,000 --> 00:02:50,559 Speaker 4: the unemployment rate has been rising only gradually, not dramatically. 51 00:02:51,480 --> 00:02:53,920 Speaker 4: But yeah, no, I mean, and we could see the 52 00:02:54,240 --> 00:02:56,679 Speaker 4: last year when all the dust settles with the revisions, 53 00:02:56,680 --> 00:02:58,960 Speaker 4: that no jobs were on net created in the US, 54 00:02:59,080 --> 00:03:01,440 Speaker 4: and that is very usual outside of a recession. 55 00:03:01,760 --> 00:03:03,760 Speaker 5: So we're going to have that one time kind of 56 00:03:04,240 --> 00:03:05,959 Speaker 5: I guess payrolls revision here. 57 00:03:06,200 --> 00:03:09,400 Speaker 6: Explain to us what that means, right. 58 00:03:09,280 --> 00:03:11,919 Speaker 4: Well, every month when we get the job's day numbers, 59 00:03:11,960 --> 00:03:14,760 Speaker 4: these are based on a survey of a stab of businesses. 60 00:03:14,800 --> 00:03:17,160 Speaker 4: I mean, it's a large survey, but it's not all 61 00:03:17,200 --> 00:03:19,800 Speaker 4: the businesses in the country. So once you're at the 62 00:03:19,840 --> 00:03:25,320 Speaker 4: benchmark revision, the buyer of labor statistics uses what's administrative 63 00:03:25,400 --> 00:03:29,000 Speaker 4: data Unemployment Insurance System, which is basically a census of 64 00:03:29,040 --> 00:03:32,760 Speaker 4: the eleven million establishments in the country, and so then 65 00:03:32,840 --> 00:03:35,920 Speaker 4: we true up the level of employment because the survey 66 00:03:36,040 --> 00:03:38,160 Speaker 4: just isn't you know it can miss things the first 67 00:03:38,160 --> 00:03:39,880 Speaker 4: time around. I mean, there's a lot one can say 68 00:03:39,880 --> 00:03:43,400 Speaker 4: about this, but really these revisions, they're probably going to 69 00:03:43,400 --> 00:03:45,360 Speaker 4: be big today, but it's a sign of us getting 70 00:03:45,520 --> 00:03:48,320 Speaker 4: better quality data so we can have this conversation about 71 00:03:48,320 --> 00:03:50,160 Speaker 4: what is going on in this labor market. 72 00:03:50,280 --> 00:03:52,800 Speaker 2: Claudia Sam stay with us again, commercial free for you 73 00:03:52,880 --> 00:03:56,880 Speaker 2: across this nation. Diane Swack and Eric Winnigrad later Carl 74 00:03:56,920 --> 00:03:59,920 Speaker 2: Weinberg in the nine o'clock hour. You're in timor of Fidelity. 75 00:04:00,480 --> 00:04:02,960 Speaker 2: We'll join us in the nine o'clock cover is, well, 76 00:04:03,000 --> 00:04:05,320 Speaker 2: where are we in the last five minutes? Futures lift 77 00:04:05,320 --> 00:04:08,040 Speaker 2: a little bit? Up three, now up eleven. Don't want 78 00:04:08,040 --> 00:04:09,960 Speaker 2: to make a big deal about it. Vix comes in 79 00:04:10,040 --> 00:04:15,040 Speaker 2: nicety seventeen point eighty five. The yields for those keeping score, 80 00:04:15,160 --> 00:04:17,880 Speaker 2: keep your hands on the wheel for those driving four 81 00:04:17,880 --> 00:04:20,680 Speaker 2: point one two percent. Yields are in a solid two 82 00:04:20,760 --> 00:04:25,280 Speaker 2: basis points price up, yield down. Into this jobs report 83 00:04:25,320 --> 00:04:28,880 Speaker 2: and the dollar fractionally weaker, it is time to look 84 00:04:28,920 --> 00:04:30,280 Speaker 2: at the labor economy. 85 00:04:31,080 --> 00:04:34,080 Speaker 7: This is what we've been waiting for. January jobs figures 86 00:04:34,120 --> 00:04:37,880 Speaker 7: and the change in non farm payrolls much stronger than expected. 87 00:04:38,320 --> 00:04:41,760 Speaker 7: One hundred and thirty thousand jobs added to the economy 88 00:04:41,839 --> 00:04:45,000 Speaker 7: last month. The whisper number was for thirty five thousand. 89 00:04:45,240 --> 00:04:48,320 Speaker 7: We've got the unemployment rate ticking down to four point 90 00:04:48,320 --> 00:04:51,440 Speaker 7: three percent. Four point four percent was expected. And the 91 00:04:51,440 --> 00:04:55,040 Speaker 7: big one, the final benchmark payrolls revision. We're still waiting 92 00:04:55,080 --> 00:04:58,359 Speaker 7: on that. There was an expectation for a loss of 93 00:04:58,400 --> 00:05:00,520 Speaker 7: eight hundred and twenty five thousand jobs. Want to look 94 00:05:00,520 --> 00:05:03,920 Speaker 7: at average hourly earnings month over month, up four tenths 95 00:05:03,920 --> 00:05:06,880 Speaker 7: of a percent year over year, right in line with 96 00:05:07,040 --> 00:05:11,960 Speaker 7: estimates three point seven percent. The market reaction not much. 97 00:05:12,160 --> 00:05:14,600 Speaker 7: We've got S and p DAL and Nasdaq futures a 98 00:05:14,600 --> 00:05:18,479 Speaker 7: little changed following this report. Again the economy adding many 99 00:05:18,520 --> 00:05:21,400 Speaker 7: more jobs than expected last month, one hundred and thirty thousand. 100 00:05:21,640 --> 00:05:24,120 Speaker 7: The expectation was for sixty five thousand. 101 00:05:24,160 --> 00:05:27,400 Speaker 2: Guys, Thanks so much, Alex. I really appreciate that we 102 00:05:27,440 --> 00:05:30,400 Speaker 2: were up eleven on futures now up twenty as well. 103 00:05:30,480 --> 00:05:33,080 Speaker 2: A nice lift to the market. NASDAK up six tens 104 00:05:33,080 --> 00:05:35,680 Speaker 2: of a percent. VIX comes in as you'd expect, Paul, 105 00:05:35,720 --> 00:05:37,839 Speaker 2: the yield space, what do you see. 106 00:05:37,760 --> 00:05:41,520 Speaker 5: I'm seeing a big movement in trash exactly right. Look 107 00:05:41,560 --> 00:05:43,240 Speaker 5: at the short end of the curve of the two 108 00:05:43,279 --> 00:05:46,400 Speaker 5: years up nine basis points three spot five to four percent, 109 00:05:46,480 --> 00:05:48,920 Speaker 5: so a big, big move there. The ten year up 110 00:05:48,960 --> 00:05:50,800 Speaker 5: about four and a half basis points four point one 111 00:05:50,920 --> 00:05:52,920 Speaker 5: nine percent, So the short end of the curve tome 112 00:05:53,560 --> 00:05:57,040 Speaker 5: really reflecting this better than expected nonfarm pay well. 113 00:05:56,960 --> 00:06:01,080 Speaker 2: Higher yields and priced down across the entire spectrum of death. 114 00:06:01,160 --> 00:06:03,080 Speaker 2: The ten year real yield was a one point eight 115 00:06:03,200 --> 00:06:06,000 Speaker 2: zero now out at one point eight five. I wanted 116 00:06:06,080 --> 00:06:10,000 Speaker 2: two part this discussion to go back to doctor major 117 00:06:10,040 --> 00:06:13,560 Speaker 2: shoutout Andrew Hollendhorse City Group just just nailed this thing. 118 00:06:14,160 --> 00:06:17,440 Speaker 2: We're going to try to get doctor Hollandhorst on the phone. 119 00:06:17,720 --> 00:06:21,440 Speaker 2: You know, I look, Claudia a one thirty number, but 120 00:06:21,520 --> 00:06:24,719 Speaker 2: with a negative revision. I don't want to oversell it. 121 00:06:24,800 --> 00:06:26,960 Speaker 2: You need a three month moving average, as you say, 122 00:06:27,200 --> 00:06:31,240 Speaker 2: non farm payrolls three month moving average seventy three thousand 123 00:06:31,320 --> 00:06:34,400 Speaker 2: is our first quick look at Bloomberg. But then I 124 00:06:34,520 --> 00:06:40,799 Speaker 2: got the actual final benchmark revisions rounded up almost negative 125 00:06:40,920 --> 00:06:45,839 Speaker 2: nine hundred thousand translate a negative eight hundred and sixty 126 00:06:45,880 --> 00:06:47,960 Speaker 2: two thousand revision. 127 00:06:49,279 --> 00:06:52,240 Speaker 4: Well, and I'll say the benchmark revision that goes to 128 00:06:52,320 --> 00:06:56,200 Speaker 4: last March was almost nine hundred thousand down There are 129 00:06:56,240 --> 00:06:59,159 Speaker 4: other revisions from the birth death model that come in 130 00:06:59,200 --> 00:07:02,200 Speaker 4: the months after that. By December of last year, the 131 00:07:02,240 --> 00:07:06,880 Speaker 4: downward revision was over a million jobs. Yeah, so now 132 00:07:07,279 --> 00:07:09,840 Speaker 4: we got the best possible outcome today. We knew these 133 00:07:09,880 --> 00:07:12,960 Speaker 4: revisions were coming, and again we can talk about what's 134 00:07:12,960 --> 00:07:16,400 Speaker 4: behind them. But to see the most recent readings, we've 135 00:07:16,440 --> 00:07:19,240 Speaker 4: got some lift in the payrolls in January. It's just 136 00:07:19,240 --> 00:07:22,560 Speaker 4: one month, but we got some lyft and the unemployment 137 00:07:22,600 --> 00:07:25,280 Speaker 4: rate ticked down. So like we want to say a 138 00:07:25,360 --> 00:07:28,280 Speaker 4: labor market that's stabilizing and coming out of this, but like, 139 00:07:28,520 --> 00:07:33,320 Speaker 4: these are huge revisions. 140 00:07:32,360 --> 00:07:34,679 Speaker 2: Doctors, Thom, I'm sitting in the back of the class 141 00:07:34,720 --> 00:07:38,360 Speaker 2: at Michigan hiding you and the smart people are up front. Okay, 142 00:07:38,560 --> 00:07:41,880 Speaker 2: my fancy math is one million jobs lost for whatever, 143 00:07:42,240 --> 00:07:47,200 Speaker 2: Claudia Sam Diane Swank reason divided by twelve is eighty 144 00:07:47,240 --> 00:07:51,440 Speaker 2: three thousand and three hundred and thirty three jobs evaporated 145 00:07:51,600 --> 00:07:56,080 Speaker 2: every thirty days out of our belief our fabric of 146 00:07:56,120 --> 00:07:58,640 Speaker 2: the American labor economy. Do I have that right? 147 00:08:00,000 --> 00:08:00,120 Speaker 8: So? 148 00:08:00,320 --> 00:08:02,119 Speaker 3: The revisions actually go back further. 149 00:08:02,360 --> 00:08:04,600 Speaker 4: The first month that will be revised down because the 150 00:08:04,600 --> 00:08:08,800 Speaker 4: benchmark was April of twenty twenty four, right, they take 151 00:08:08,840 --> 00:08:11,960 Speaker 4: the annual benchmark revision is wedged in over the prior 152 00:08:12,040 --> 00:08:15,720 Speaker 4: twelve months, so we're that million down. That's happening over 153 00:08:15,880 --> 00:08:18,440 Speaker 4: a span of time. But if you look at the 154 00:08:18,480 --> 00:08:22,560 Speaker 4: monthly changes last year the new estimates, there's a lot 155 00:08:22,560 --> 00:08:24,640 Speaker 4: of red I mean, there's a lot of months where 156 00:08:24,640 --> 00:08:27,480 Speaker 4: we were dipping, you know, into the not you know, 157 00:08:27,560 --> 00:08:28,280 Speaker 4: destroying jobs. 158 00:08:28,360 --> 00:08:29,760 Speaker 3: So these are big numbers. 159 00:08:29,800 --> 00:08:33,240 Speaker 4: It is spread out over a period of time, but 160 00:08:34,240 --> 00:08:37,240 Speaker 4: there's something here for us to understand about what exactly 161 00:08:37,320 --> 00:08:40,440 Speaker 4: is happening with job creation and how comforted should we 162 00:08:40,480 --> 00:08:44,280 Speaker 4: be by the latest numbers. Have we turned the corner 163 00:08:44,400 --> 00:08:46,240 Speaker 4: or is that just an aberration and we're going to 164 00:08:46,280 --> 00:08:49,520 Speaker 4: get back into these really low low numbers. 165 00:08:49,679 --> 00:08:51,360 Speaker 5: How do you think the Fed is going to react 166 00:08:51,400 --> 00:08:54,640 Speaker 5: to these numbers? Claudia, Again, they change non farm perils 167 00:08:54,679 --> 00:08:56,600 Speaker 5: coming in for the month of January much much better 168 00:08:56,600 --> 00:08:57,160 Speaker 5: than expected. 169 00:08:58,160 --> 00:08:59,600 Speaker 3: Yeah, so the FED knew about this. 170 00:09:00,280 --> 00:09:03,720 Speaker 4: We you know, your Labor Statistics published its preliminary estimate 171 00:09:03,760 --> 00:09:06,440 Speaker 4: of the benchmark revision back in September it was for 172 00:09:06,520 --> 00:09:08,040 Speaker 4: a negative nine hundred thousand. 173 00:09:08,080 --> 00:09:10,400 Speaker 3: My goodness, it was almost you know, right on the money. 174 00:09:10,880 --> 00:09:15,120 Speaker 4: And this is certainly you've heard FED Governor Waller mentioned 175 00:09:15,120 --> 00:09:17,960 Speaker 4: this in his descent, but also FED cher Powell talked about, 176 00:09:18,200 --> 00:09:22,200 Speaker 4: you know, revision. So these numbers aren't surprising. I mean, really, 177 00:09:22,240 --> 00:09:25,920 Speaker 4: the news today maybe the most recent months. 178 00:09:26,480 --> 00:09:27,679 Speaker 3: This you know, the January. 179 00:09:27,760 --> 00:09:30,040 Speaker 4: Again, not to overplay it, but you know it's good 180 00:09:30,040 --> 00:09:32,040 Speaker 4: news to see that kind of number and the unemployment 181 00:09:32,080 --> 00:09:34,760 Speaker 4: rate taking down. So this is not a surprise to 182 00:09:34,800 --> 00:09:36,360 Speaker 4: the FED. Right, we knew this was going. 183 00:09:36,240 --> 00:09:36,920 Speaker 8: To be in the data. 184 00:09:37,000 --> 00:09:39,880 Speaker 2: But you published a chart last night, folks that was 185 00:09:39,920 --> 00:09:43,439 Speaker 2: in English, unlike anything I would do. And Claudia Sam, 186 00:09:43,840 --> 00:09:46,560 Speaker 2: I mean you said within the dynamics of the labor 187 00:09:46,640 --> 00:09:50,960 Speaker 2: economy that the dearth of immigration plays into this. I 188 00:09:50,960 --> 00:09:54,000 Speaker 2: mean your chart's a little spike up, a little line up. 189 00:09:54,080 --> 00:09:57,479 Speaker 2: Are we at four point three percent because if immigration 190 00:09:57,640 --> 00:10:01,040 Speaker 2: dynamics where we ought to be at say five point percent? 191 00:10:03,000 --> 00:10:06,679 Speaker 4: So I think the immigration dynamics and we've seen a 192 00:10:06,720 --> 00:10:09,680 Speaker 4: big swing, a lot more immigration than had been. 193 00:10:09,640 --> 00:10:11,920 Speaker 3: Typical, and then a big slow immigration. 194 00:10:12,400 --> 00:10:16,120 Speaker 4: That certainly is important and understanding what is with these 195 00:10:16,240 --> 00:10:19,040 Speaker 4: jobs numbers that just really hit a wall. So that's 196 00:10:19,200 --> 00:10:21,480 Speaker 4: but it is not the only factor behind it. Like 197 00:10:21,520 --> 00:10:24,480 Speaker 4: we have still seen the unemployment rate drift up. We 198 00:10:24,840 --> 00:10:29,400 Speaker 4: are not like labor demand for workers is not keeping 199 00:10:29,480 --> 00:10:31,959 Speaker 4: up with the supply of workers, right, But so the 200 00:10:32,040 --> 00:10:34,080 Speaker 4: unemployed rate is giving us a much better picture of 201 00:10:34,120 --> 00:10:38,520 Speaker 4: this kind of gradual problem that's building the payrolls because 202 00:10:38,520 --> 00:10:42,880 Speaker 4: it has the supply of workers has just shifted so abruptly. 203 00:10:43,520 --> 00:10:47,000 Speaker 4: The message from the payrolls looks a lot scarier than 204 00:10:47,080 --> 00:10:49,360 Speaker 4: it is. But I don't want to write it off, right, 205 00:10:49,440 --> 00:10:52,640 Speaker 4: Like we still see wage growth slowing, unemployment rate drifting up, 206 00:10:52,840 --> 00:10:55,960 Speaker 4: and certainly for groups like you know, people new to 207 00:10:56,000 --> 00:10:59,200 Speaker 4: the labor market, this is a very tough job market. 208 00:11:00,080 --> 00:11:00,760 Speaker 6: Tough job market. 209 00:11:00,840 --> 00:11:03,520 Speaker 5: Just real quickly that eight hundred and sixty two thousand 210 00:11:03,600 --> 00:11:06,160 Speaker 5: final benchmark revision just put that into context for us. 211 00:11:07,440 --> 00:11:13,120 Speaker 4: It's big, Like no, it's it should be about six 212 00:11:13,360 --> 00:11:16,640 Speaker 4: tenths of total payroll employment something like that, five to 213 00:11:16,679 --> 00:11:20,920 Speaker 4: six tenths, and a typical before last year typical had 214 00:11:20,920 --> 00:11:22,840 Speaker 4: been more like a tenth of the level. Last year's 215 00:11:22,880 --> 00:11:25,600 Speaker 4: was pretty big too, So you know, the average over 216 00:11:25,600 --> 00:11:27,560 Speaker 4: the last ten years hasn't been about two tents, so 217 00:11:27,600 --> 00:11:30,400 Speaker 4: this is like three times larger, and we've had two 218 00:11:30,440 --> 00:11:31,920 Speaker 4: of these in a row. And again I want to 219 00:11:31,960 --> 00:11:33,880 Speaker 4: stress this is not a signed the Bureau of Labor 220 00:11:33,920 --> 00:11:36,400 Speaker 4: Statistics is asleep at the wheel. This is just we 221 00:11:36,520 --> 00:11:39,800 Speaker 4: have some major dynamics happening in the economy and it's 222 00:11:39,840 --> 00:11:42,360 Speaker 4: really tough to measure them in real time, and so 223 00:11:42,400 --> 00:11:44,720 Speaker 4: we're kind of catching up and it should help them 224 00:11:45,200 --> 00:11:47,960 Speaker 4: with you know, people try and understand the labor market. 225 00:11:48,120 --> 00:11:50,120 Speaker 4: Still a lot of puzzles, but we've got better data 226 00:11:50,160 --> 00:11:52,200 Speaker 4: today and that is a really good starting point for 227 00:11:52,320 --> 00:11:55,720 Speaker 4: understanding where we're going and what policy makers might want 228 00:11:55,760 --> 00:11:55,920 Speaker 4: to do. 229 00:11:56,200 --> 00:11:58,680 Speaker 2: So Claudia helping are for folks studying SWAT coming up 230 00:11:58,679 --> 00:12:01,600 Speaker 2: and Eric Winnegretti in a moment with Alliance burnsting. So 231 00:12:01,800 --> 00:12:05,240 Speaker 2: Eric Winnigrad's up in darkness freezing. I'l like the cushy 232 00:12:05,240 --> 00:12:09,320 Speaker 2: ann arbor weather. Claudia sam he's taken the sevens. He's 233 00:12:09,360 --> 00:12:14,240 Speaker 2: taken labor economics. Is this you're brilliance Claudia out on 234 00:12:14,280 --> 00:12:18,120 Speaker 2: Twitter last night. The academics right now of our labor 235 00:12:18,320 --> 00:12:22,320 Speaker 2: economics is this in the textbooks, Eric Winnigrad. 236 00:12:21,920 --> 00:12:26,640 Speaker 4: Studied, I mean, every session has its own dynamics. But 237 00:12:26,679 --> 00:12:29,360 Speaker 4: ever since the pandemics showed up, the labor market has 238 00:12:29,360 --> 00:12:33,000 Speaker 4: been doing things that are just unusual, if nothing else 239 00:12:33,040 --> 00:12:37,800 Speaker 4: in their magnitudes. We've just had some really abrupt swings. 240 00:12:38,000 --> 00:12:42,840 Speaker 4: And so like, I think this cycle, this business cycle 241 00:12:42,880 --> 00:12:45,840 Speaker 4: really does stand out right, and it may. 242 00:12:45,720 --> 00:12:46,720 Speaker 3: Stand out in good ways. 243 00:12:46,840 --> 00:12:50,319 Speaker 4: Maybe that gradual rising unemployment rate without a recession, maybe 244 00:12:50,360 --> 00:12:53,160 Speaker 4: that's what a soft landing actually looks like. Like we 245 00:12:53,160 --> 00:12:55,040 Speaker 4: don't ever get those, So this doesn't have to be 246 00:12:55,080 --> 00:12:58,640 Speaker 4: a bad news story. But there's certainly tensions, and I 247 00:12:58,760 --> 00:13:01,080 Speaker 4: just want people to do just because we avoid a 248 00:13:01,120 --> 00:13:02,840 Speaker 4: recession doesn't mean it's good enough. 249 00:13:02,920 --> 00:13:05,120 Speaker 2: She's you know, I mean, we lost a million jobs 250 00:13:05,160 --> 00:13:07,840 Speaker 2: in summary vider stand and she's telling us it's not 251 00:13:07,880 --> 00:13:10,560 Speaker 2: a bad news. Sorry, Claudia, can you stay for five 252 00:13:10,640 --> 00:13:11,200 Speaker 2: more minutes? 253 00:13:12,200 --> 00:13:12,640 Speaker 3: Of course? 254 00:13:12,800 --> 00:13:15,199 Speaker 2: Okay, thank you so much. Joining us now, Eric Winigrad 255 00:13:15,240 --> 00:13:18,240 Speaker 2: with Claudia. Some I think that the two of them, 256 00:13:18,520 --> 00:13:21,520 Speaker 2: Eric has a much more international feel, maybe, but the 257 00:13:21,559 --> 00:13:24,200 Speaker 2: two of them are the market economics at Alliance Bernstein 258 00:13:24,240 --> 00:13:27,320 Speaker 2: of Eric winnigred with the academics of doctor, some I 259 00:13:27,320 --> 00:13:31,280 Speaker 2: think it really dovetails here. Eric, how do you translate 260 00:13:31,400 --> 00:13:36,160 Speaker 2: Claudia SOM's brilliant work on the labor economy, not on recession. 261 00:13:36,600 --> 00:13:39,440 Speaker 2: But she's been on fire the last twenty four hours 262 00:13:39,840 --> 00:13:43,800 Speaker 2: about these odd Newtonian dynamics of our labor economy. 263 00:13:44,120 --> 00:13:45,960 Speaker 9: It is a very strange economy. And to answer the 264 00:13:46,000 --> 00:13:47,560 Speaker 9: question that you asked, No, none of this was in 265 00:13:47,600 --> 00:13:49,880 Speaker 9: the textbooks that I was looking at a dartmouth. But 266 00:13:50,080 --> 00:13:51,640 Speaker 9: I think you want to put this in perspective. You 267 00:13:51,679 --> 00:13:53,480 Speaker 9: just said a minute ago, Tom, we've lost eight hundred 268 00:13:53,480 --> 00:13:56,000 Speaker 9: and sixty two thousand jobs as a result of this revision. 269 00:13:56,120 --> 00:13:59,160 Speaker 9: That's not true. Nobody has lost a job. We're just 270 00:13:59,280 --> 00:14:01,560 Speaker 9: counting it better, right, So so that is not the 271 00:14:01,559 --> 00:14:03,840 Speaker 9: case that people lost jobs. 272 00:14:04,280 --> 00:14:05,280 Speaker 6: It's just that the data. 273 00:14:05,120 --> 00:14:07,680 Speaker 2: Helps we counted weren't there. 274 00:14:07,880 --> 00:14:10,720 Speaker 9: That's correct. But again, what are we really interested in? 275 00:14:10,760 --> 00:14:13,080 Speaker 9: Are we interested in the statistical minutia or are we 276 00:14:13,120 --> 00:14:15,920 Speaker 9: interested in the way that people in the economy experienced this. 277 00:14:16,880 --> 00:14:19,440 Speaker 9: We're more interested in the way people experience this, and 278 00:14:19,480 --> 00:14:22,960 Speaker 9: nobody actually lost their job. I agree with Claudia one 279 00:14:23,040 --> 00:14:26,480 Speaker 9: hundred percent that the true signal in today's report is 280 00:14:26,520 --> 00:14:30,000 Speaker 9: the unemployment rate. Because the revisions to the headline series 281 00:14:30,040 --> 00:14:34,400 Speaker 9: are so complicated, there is statistical artifact the unemployment rate 282 00:14:34,520 --> 00:14:37,880 Speaker 9: is balancing supply and demand in the economy, and it's 283 00:14:37,880 --> 00:14:40,920 Speaker 9: telling us that things are okay, not great, right, but okay. 284 00:14:41,040 --> 00:14:44,240 Speaker 2: Does it reaffirm doctor some the idea of two rate cuts? 285 00:14:44,240 --> 00:14:46,040 Speaker 2: I mean, how do you go to four rate cuts 286 00:14:46,040 --> 00:14:48,680 Speaker 2: with a four point three percent unemployment rate? 287 00:14:51,560 --> 00:14:53,800 Speaker 4: My base case is still two rate cuts this year, 288 00:14:53,840 --> 00:14:56,200 Speaker 4: But we're going to get a lot more information and 289 00:14:56,280 --> 00:14:58,880 Speaker 4: the Fed is going to watch the labor market extremely 290 00:14:58,960 --> 00:15:02,680 Speaker 4: carefully in terms of how they adjusted going forward. 291 00:15:03,280 --> 00:15:05,920 Speaker 5: Eric, how do you think AI is impacting this labor 292 00:15:05,960 --> 00:15:08,680 Speaker 5: force here? Because people say it's really tough to get 293 00:15:08,680 --> 00:15:11,040 Speaker 5: a job, and maybe that's the entry level job, and 294 00:15:11,080 --> 00:15:14,280 Speaker 5: maybe that's the job that's being impacted by AI at 295 00:15:14,320 --> 00:15:15,160 Speaker 5: least initially. 296 00:15:15,200 --> 00:15:16,600 Speaker 6: Does that factor into your work at all? 297 00:15:16,640 --> 00:15:18,120 Speaker 9: So it's just one of the ways in which this 298 00:15:18,200 --> 00:15:20,840 Speaker 9: labor market is confusing and complicated. And I would actually 299 00:15:20,920 --> 00:15:22,480 Speaker 9: refer you to a speech that the Governor of the 300 00:15:22,520 --> 00:15:25,120 Speaker 9: Bank of Canada made last week, Tiff Macklin, where he 301 00:15:25,160 --> 00:15:27,640 Speaker 9: said that if part of the reason the labor market 302 00:15:27,680 --> 00:15:30,440 Speaker 9: is so tough is because of these structural changes, because 303 00:15:30,440 --> 00:15:34,000 Speaker 9: of artificial intelligence, for example, it isn't appropriate for central 304 00:15:34,000 --> 00:15:36,880 Speaker 9: banks to respond to that by cutting interest rates. You 305 00:15:36,920 --> 00:15:39,360 Speaker 9: can't boost labor and demand with interest rates if the 306 00:15:39,400 --> 00:15:43,200 Speaker 9: problem is AI. I think it's premature to draw that conclusion. 307 00:15:43,520 --> 00:15:45,440 Speaker 9: Claudia has said, and she's right that there is some 308 00:15:45,480 --> 00:15:48,840 Speaker 9: evidence that entry level workers in particular are struggling. But 309 00:15:48,880 --> 00:15:51,000 Speaker 9: we're still very very early days on this. 310 00:15:51,160 --> 00:15:53,520 Speaker 2: One final question, Claudia SAMs, I know you have to 311 00:15:53,560 --> 00:15:56,320 Speaker 2: publish for a new century. Claudia, I want you to 312 00:15:56,400 --> 00:16:00,160 Speaker 2: speak to the huge body of the nation that's not 313 00:16:00,280 --> 00:16:04,760 Speaker 2: worried about their stock options on a mag seven equity holding. 314 00:16:04,920 --> 00:16:09,239 Speaker 2: They're not part of the profit machine of technology in America. 315 00:16:09,560 --> 00:16:13,320 Speaker 2: How flat on their back is the rest of America. 316 00:16:13,160 --> 00:16:15,800 Speaker 4: Right Well, for that group of Americans, I mean, their 317 00:16:15,880 --> 00:16:20,120 Speaker 4: jobs are so critical to their well being. And for 318 00:16:20,200 --> 00:16:22,440 Speaker 4: people who have a job and like their job. Right now, 319 00:16:22,440 --> 00:16:25,440 Speaker 4: things are really pretty good, right Wages aren't, you know, 320 00:16:25,560 --> 00:16:28,160 Speaker 4: going gangbusters. Workers are not sharing in all of this 321 00:16:28,240 --> 00:16:31,680 Speaker 4: productivity that it seems to be out there necessarily, but 322 00:16:31,960 --> 00:16:32,840 Speaker 4: it's pretty okay. 323 00:16:32,880 --> 00:16:33,800 Speaker 6: But it's the. 324 00:16:33,680 --> 00:16:36,640 Speaker 4: Ones who are on the margins who don't have the 325 00:16:36,720 --> 00:16:39,520 Speaker 4: job or want to switch job like, they are a 326 00:16:39,520 --> 00:16:41,560 Speaker 4: lot more stuck right now. And so I think, really 327 00:16:41,600 --> 00:16:44,560 Speaker 4: the labor market it has always been and will continue 328 00:16:44,560 --> 00:16:46,760 Speaker 4: to be central to people, particularly those who are not 329 00:16:46,920 --> 00:16:48,880 Speaker 4: plugged into the asset markets. 330 00:16:49,000 --> 00:16:52,160 Speaker 2: Claudia, So I'm thank you for your commitment to Bloomberg Surveillance. 331 00:16:52,240 --> 00:16:55,400 Speaker 2: Doctor Simus of the New Century advises, I can't say enough 332 00:16:55,480 --> 00:16:59,720 Speaker 2: about a workout on Twitter and LinkedIn, just hugely informed. 333 00:17:01,560 --> 00:17:05,760 Speaker 2: Stay with us more from Bloomberg Surveillance coming up after this. 334 00:17:13,000 --> 00:17:16,560 Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us Live 335 00:17:16,640 --> 00:17:19,800 Speaker 1: weekday afternoons from seven to ten am Eastern Listen on 336 00:17:19,880 --> 00:17:23,520 Speaker 1: Applecarplay and Android Auto with the Bloomberg Business app, or 337 00:17:23,680 --> 00:17:25,160 Speaker 1: watch us live on YouTube. 338 00:17:25,440 --> 00:17:27,560 Speaker 2: So when you get this huge report coming up and 339 00:17:27,600 --> 00:17:29,119 Speaker 2: you get the data, what do you do well to 340 00:17:29,160 --> 00:17:31,720 Speaker 2: impress Lisa Shallat, I go to the ten year real yield, 341 00:17:31,960 --> 00:17:34,440 Speaker 2: which is sitting at two standard dv sits under one 342 00:17:34,440 --> 00:17:36,880 Speaker 2: point eight one percent of breakdown there in the ten 343 00:17:36,920 --> 00:17:39,200 Speaker 2: year real yield would be a big deal. And then 344 00:17:39,280 --> 00:17:42,040 Speaker 2: she knows, I go to Swiss Frank That's what you 345 00:17:42,119 --> 00:17:44,920 Speaker 2: do with Morgan Stanley and I'm sorry. I got a 346 00:17:45,000 --> 00:17:48,160 Speaker 2: Swiss Frank at the CUSP along with Yeana one fifty 347 00:17:48,240 --> 00:17:51,879 Speaker 2: three fifty nine joining us on Lisa Schellet at Morgan Stanley, 348 00:17:51,880 --> 00:17:54,399 Speaker 2: probably on a plane heading for Tokyo here at some 349 00:17:54,440 --> 00:17:57,600 Speaker 2: point chief investment officer at Morgan Stanley, let me cut 350 00:17:57,640 --> 00:17:58,399 Speaker 2: to the chase. 351 00:17:58,840 --> 00:18:02,200 Speaker 10: Yes, sir, Brad hints my old buddy, is. 352 00:18:02,280 --> 00:18:05,119 Speaker 2: AI going to replace Brandigins? 353 00:18:08,400 --> 00:18:12,160 Speaker 10: So look absolutely not. You Know, what I can tell 354 00:18:12,200 --> 00:18:17,320 Speaker 10: you is that, like every other technology, we fundamentally believe 355 00:18:17,440 --> 00:18:22,320 Speaker 10: that AI is an enabling tool. It is an enabling 356 00:18:22,400 --> 00:18:26,760 Speaker 10: tool for expertise. While there are many things that we 357 00:18:26,880 --> 00:18:31,240 Speaker 10: do that can be automated in terms of a process 358 00:18:31,320 --> 00:18:34,800 Speaker 10: that are repetitive, that require us to capture and intake 359 00:18:34,920 --> 00:18:40,679 Speaker 10: information and summarize it, the real beauty of expertise is 360 00:18:40,760 --> 00:18:43,959 Speaker 10: creativity and interpretation. And as far as I can tell, 361 00:18:44,200 --> 00:18:48,520 Speaker 10: at least thus far my interactions with the technology, is 362 00:18:48,520 --> 00:18:51,639 Speaker 10: that we're far, far, far away from being able to 363 00:18:51,760 --> 00:18:57,000 Speaker 10: rival America. You know, an analyst, a human beings. 364 00:18:57,200 --> 00:18:59,119 Speaker 5: It's tough to see you because we saw in just 365 00:18:59,280 --> 00:19:02,000 Speaker 5: this year, let's several weeks, last couple of months, this 366 00:19:02,160 --> 00:19:04,760 Speaker 5: AI story's evolved a little bit from how much can 367 00:19:04,800 --> 00:19:07,400 Speaker 5: we spend, how big can it get to be? Who's 368 00:19:07,400 --> 00:19:10,719 Speaker 5: at risk from the deployment of AI technology, and then 369 00:19:10,720 --> 00:19:12,080 Speaker 5: over the less several weeks, we really hit a lot 370 00:19:12,080 --> 00:19:13,120 Speaker 5: of these software companies. 371 00:19:13,240 --> 00:19:17,320 Speaker 10: Yeah, so the software sell off on one level doesn't 372 00:19:17,520 --> 00:19:21,440 Speaker 10: surprise me in the sense that some of these business 373 00:19:21,480 --> 00:19:26,239 Speaker 10: models are ultimately you know, going to be disrupted. But 374 00:19:26,359 --> 00:19:29,600 Speaker 10: what I think people have to remember is a lot 375 00:19:29,640 --> 00:19:33,840 Speaker 10: of the enterprise software companies in particular, what they have 376 00:19:34,240 --> 00:19:39,639 Speaker 10: done with companies is they've come to dominate, organize, optimize data. 377 00:19:40,320 --> 00:19:43,879 Speaker 10: And you know where we are in terms of AI 378 00:19:44,000 --> 00:19:48,080 Speaker 10: implementation in most companies is you need the data. You 379 00:19:48,160 --> 00:19:52,480 Speaker 10: can't train these tools to do anything without the data. 380 00:19:52,600 --> 00:19:54,600 Speaker 10: And I think it's going to be really hard to 381 00:19:54,640 --> 00:19:58,320 Speaker 10: do it without some of these enterprise software companies participating 382 00:19:58,320 --> 00:19:59,120 Speaker 10: in a major way. 383 00:19:59,359 --> 00:20:02,640 Speaker 5: So twenty two was a solid year for US equity investors, 384 00:20:02,720 --> 00:20:06,200 Speaker 5: solid returns, solid returns in the fixed income market. Here, 385 00:20:07,880 --> 00:20:10,359 Speaker 5: I don't know what's the call here for twenty six 386 00:20:10,440 --> 00:20:12,360 Speaker 5: that we more the same? 387 00:20:13,080 --> 00:20:13,800 Speaker 6: What are you looking for? 388 00:20:14,080 --> 00:20:17,160 Speaker 10: So look, I think our tagline for twenty twenty six 389 00:20:17,280 --> 00:20:22,360 Speaker 10: was simply, you know, price to perfection, which means the 390 00:20:22,400 --> 00:20:25,960 Speaker 10: window for upside surprise is narrower. So our view is, 391 00:20:26,200 --> 00:20:29,320 Speaker 10: you know, this will be a good, solid average year 392 00:20:29,440 --> 00:20:33,240 Speaker 10: in stock markets that means seven to ten percent total returns. 393 00:20:34,000 --> 00:20:36,080 Speaker 10: But it's going to be a little bit more of all. 394 00:20:36,320 --> 00:20:38,800 Speaker 10: It's going to be a little bit more idiosyncratic. It's 395 00:20:38,800 --> 00:20:41,240 Speaker 10: going to be about fundamentals. It's going to be about earnings, 396 00:20:41,280 --> 00:20:44,040 Speaker 10: achievement and surprise, and that stuff's hard. 397 00:20:44,560 --> 00:20:47,000 Speaker 2: Lisa show it with us with Morgan Stanley, and this 398 00:20:47,119 --> 00:20:50,720 Speaker 2: is breaking news, and it's absolutely perfect for mischell with 399 00:20:50,800 --> 00:20:54,000 Speaker 2: all over decades of work of working out companies, of 400 00:20:54,040 --> 00:20:57,600 Speaker 2: deciding what not to own, all the focus. And I'm 401 00:20:57,640 --> 00:20:59,760 Speaker 2: as guilty of this lease as anyone else is. On 402 00:20:59,800 --> 00:21:04,520 Speaker 2: two stocks. I'm an idiot. And what I'm fascinated by 403 00:21:04,760 --> 00:21:08,560 Speaker 2: is the rest of corporate America left behind that's not 404 00:21:08,720 --> 00:21:14,600 Speaker 2: getting it done. Craft, Hinds, kool Aid, Cello, I think 405 00:21:14,640 --> 00:21:17,800 Speaker 2: they owned Vilvida, I can't remember. They're going to stop 406 00:21:17,920 --> 00:21:22,360 Speaker 2: with They're split into two publicly traded companies. Organic revenue 407 00:21:22,440 --> 00:21:26,399 Speaker 2: last quarter was a stunning negative four percent. I'm going 408 00:21:26,480 --> 00:21:30,000 Speaker 2: to put that seven hundred beeps, eight hundred beeps by 409 00:21:30,119 --> 00:21:35,200 Speaker 2: nominal GDP well, how should our how should our listeners 410 00:21:35,200 --> 00:21:40,760 Speaker 2: and viewers interpret companies, big blue chip companies that just 411 00:21:40,880 --> 00:21:42,399 Speaker 2: aren't getting it done? 412 00:21:42,800 --> 00:21:46,399 Speaker 10: Yeah, look, I think that you've got to be come 413 00:21:46,440 --> 00:21:49,600 Speaker 10: to them with an extraordinarily critical eye and ask yourself 414 00:21:49,680 --> 00:21:53,680 Speaker 10: why for a lot of the consumer staples companies, they 415 00:21:53,720 --> 00:21:59,080 Speaker 10: have been, you know, the victims of you know, currency movements, 416 00:21:59,119 --> 00:22:01,520 Speaker 10: they've been a vic of some of the you know, 417 00:22:01,600 --> 00:22:06,399 Speaker 10: consumer impacted tariff related issues, and they've been you know, 418 00:22:06,560 --> 00:22:11,000 Speaker 10: victims of demographic and behavioral shifts in terms of how 419 00:22:11,119 --> 00:22:14,400 Speaker 10: much staples are actually consumed at home. 420 00:22:14,280 --> 00:22:17,000 Speaker 2: And in a portfolio. You say, just say no, right, 421 00:22:17,160 --> 00:22:19,640 Speaker 2: you just don't own it exactly. 422 00:22:19,680 --> 00:22:21,800 Speaker 10: You got to go go through name by name by 423 00:22:21,880 --> 00:22:25,360 Speaker 10: name and make an active decision. Am I overweight, underweight 424 00:22:25,440 --> 00:22:25,960 Speaker 10: or no weight? 425 00:22:26,080 --> 00:22:30,679 Speaker 2: Brilliant Paul Pe of Craft Times nine. Yep, it's traded 426 00:22:30,760 --> 00:22:34,200 Speaker 2: like international paper years ago. The dividend, we'll talk about 427 00:22:34,200 --> 00:22:36,080 Speaker 2: a broken dividend on the Bloomberg. 428 00:22:36,119 --> 00:22:39,479 Speaker 6: You got six di you're living for the dividend. 429 00:22:39,520 --> 00:22:44,760 Speaker 5: I guess, yeah, Lisa, were constantly wealth management. How much 430 00:22:45,119 --> 00:22:47,720 Speaker 5: alternative assets to your clients want to own? What's the 431 00:22:47,960 --> 00:22:51,080 Speaker 5: what's an allocation there? Because I'm always shocked that it's 432 00:22:51,200 --> 00:22:52,480 Speaker 5: much higher than I would have thought. 433 00:22:52,760 --> 00:22:56,840 Speaker 10: You know, yeah, so our recommendations, and I h sit 434 00:22:56,920 --> 00:23:01,160 Speaker 10: atop our Global Investment Committee, which derives this set allocation advice. 435 00:23:01,560 --> 00:23:05,719 Speaker 10: We've routinely, you know, talked about truly private liquids at 436 00:23:06,040 --> 00:23:09,160 Speaker 10: roughly you know, ten to fifteen percent of your portfolio, 437 00:23:09,680 --> 00:23:12,800 Speaker 10: Hedge funds maybe at ten. So you think about just 438 00:23:12,880 --> 00:23:15,520 Speaker 10: those two categories, you could get as high as twenty 439 00:23:15,520 --> 00:23:20,360 Speaker 10: five for an ultra high networth client. Now that's very aspirational, 440 00:23:20,359 --> 00:23:24,080 Speaker 10: it's very theoretical, you know, it's Harry Markowitz an efficient, 441 00:23:24,280 --> 00:23:29,320 Speaker 10: you know, frontiers and the like. The reality is is 442 00:23:29,359 --> 00:23:32,959 Speaker 10: that today, within you know, the Morgan Stanlely Wealth Management book, 443 00:23:33,680 --> 00:23:39,880 Speaker 10: the penetration, the actual average allocation to alternatives is much 444 00:23:39,920 --> 00:23:43,040 Speaker 10: closer to five or six percent than that twenty five 445 00:23:43,119 --> 00:23:44,160 Speaker 10: percent recommendation. 446 00:23:44,520 --> 00:23:45,680 Speaker 2: How about a long way to go? 447 00:23:45,800 --> 00:23:47,960 Speaker 5: How about fixed income? I mean, you know, now you 448 00:23:47,960 --> 00:23:49,800 Speaker 5: can be clipping some nice coupons. I'm not sure we're 449 00:23:49,800 --> 00:23:51,600 Speaker 5: going to get price appreciate like we did last year, 450 00:23:51,640 --> 00:23:53,560 Speaker 5: but is it okay to just sit there with a 451 00:23:54,560 --> 00:23:57,280 Speaker 5: nice diversified fixing come portfolio and clip coupons. 452 00:23:56,920 --> 00:23:59,760 Speaker 10: Saying yes, We yes, absolutely, but you want to be 453 00:23:59,880 --> 00:24:02,400 Speaker 10: very very careful about where on the curve you are. 454 00:24:03,080 --> 00:24:06,040 Speaker 10: We expect there to still be some front end volatility 455 00:24:06,119 --> 00:24:09,880 Speaker 10: and those rates to come down, and on the long end, 456 00:24:09,960 --> 00:24:12,760 Speaker 10: we think that there's still a bias higher to rates, 457 00:24:13,040 --> 00:24:16,320 Speaker 10: and because of the long duration, that could produce some volatility. 458 00:24:16,640 --> 00:24:20,399 Speaker 10: So we're focusing on the the what we call the 459 00:24:20,400 --> 00:24:23,439 Speaker 10: belly of the curve, or somewhere between four and seven 460 00:24:23,560 --> 00:24:28,800 Speaker 10: years of duration to truly have just clip coupon, don't 461 00:24:28,920 --> 00:24:32,120 Speaker 10: don't get too aspirational about what you're going to make 462 00:24:32,160 --> 00:24:35,280 Speaker 10: on price. Just try to try to try to focus 463 00:24:35,320 --> 00:24:36,000 Speaker 10: on the coupon. 464 00:24:36,160 --> 00:24:36,520 Speaker 8: Clip. 465 00:24:37,280 --> 00:24:40,640 Speaker 10: But in the rest of fixed income, you know, credit 466 00:24:41,400 --> 00:24:44,280 Speaker 10: has become extraordinarily. 467 00:24:43,280 --> 00:24:45,560 Speaker 6: Richly value and so there. 468 00:24:45,400 --> 00:24:48,120 Speaker 10: We're applying a similar lens to the one we're applying 469 00:24:48,160 --> 00:24:51,280 Speaker 10: to stocks, which is, let's start being a little bit 470 00:24:51,280 --> 00:24:55,520 Speaker 10: more discriminatory and decide to all to all of these 471 00:24:56,040 --> 00:24:58,600 Speaker 10: bonds you know deserve these tight spreads. 472 00:24:58,760 --> 00:25:01,920 Speaker 2: Lucky you. I got twenty seconds. Did we place the 473 00:25:01,960 --> 00:25:06,720 Speaker 2: one hundred year Google yesterday into Morgan Stanley portfolios? 474 00:25:07,359 --> 00:25:10,520 Speaker 10: That I don't know, I don't know where we were 475 00:25:10,640 --> 00:25:12,880 Speaker 10: on the tear sheet when all is said and done. 476 00:25:12,920 --> 00:25:16,239 Speaker 10: But look, it's an extraordinary moment. And you know this 477 00:25:16,359 --> 00:25:19,240 Speaker 10: from prior bull market cycles. 478 00:25:19,680 --> 00:25:20,920 Speaker 6: When you see these one. 479 00:25:20,960 --> 00:25:25,520 Speaker 10: Hundred year type of events, they tend to get you know, 480 00:25:25,680 --> 00:25:26,840 Speaker 10: marked on it. 481 00:25:26,880 --> 00:25:31,040 Speaker 2: On the walking into the interns at Morgan Stanley, the 482 00:25:31,640 --> 00:25:34,240 Speaker 2: gifted few chosen to sit in the class. You going 483 00:25:34,320 --> 00:25:37,199 Speaker 2: to the piece of chalk and you put perpetuity up 484 00:25:37,240 --> 00:25:40,840 Speaker 2: on the chalkboard and say read it and weep. Lisa, 485 00:25:40,880 --> 00:25:44,320 Speaker 2: Thank you. Lisa Shallotte with us Morgan Stanley Wealth Management. 486 00:25:44,359 --> 00:25:49,640 Speaker 2: Your stay with us. More from Bloomberg Surveillance coming up 487 00:25:49,880 --> 00:25:50,480 Speaker 2: after this. 488 00:25:57,680 --> 00:26:01,280 Speaker 1: You're listening to the Bloomberg Surveillance Pod. Catch us live 489 00:26:01,359 --> 00:26:04,480 Speaker 1: weekday afternoons from seven to ten am Eastern Listen on 490 00:26:04,600 --> 00:26:08,280 Speaker 1: Applecarplay and Android Otto with the Bloomberg Business app, or 491 00:26:08,400 --> 00:26:09,880 Speaker 1: watch us live on YouTube. 492 00:26:10,000 --> 00:26:13,359 Speaker 2: Your leadership of the National Association for Business Economics is 493 00:26:13,400 --> 00:26:17,440 Speaker 2: noted with KPMG. Diane Swank joins us right now. Diane, 494 00:26:17,520 --> 00:26:20,720 Speaker 2: just a sixty thousand foot question for our listeners, those 495 00:26:20,800 --> 00:26:23,520 Speaker 2: with the job, those with Google stock options and the 496 00:26:23,560 --> 00:26:26,040 Speaker 2: Google one hundred year piece, and those flat on their 497 00:26:26,119 --> 00:26:30,040 Speaker 2: back across America. How case shaped are we this morning? 498 00:26:32,280 --> 00:26:35,040 Speaker 11: Well, we are as much as we've been since the 499 00:26:35,119 --> 00:26:38,399 Speaker 11: data started on corporate profit share versus wade share in 500 00:26:38,440 --> 00:26:41,520 Speaker 11: the economy going back to the nineteen seventies. What we're 501 00:26:41,520 --> 00:26:45,520 Speaker 11: seeing is a record break between the share of profits 502 00:26:45,560 --> 00:26:51,200 Speaker 11: going to wealthholders versus the amount of going to wages. 503 00:26:51,240 --> 00:26:54,000 Speaker 11: And I think that's where the bulk of this is. 504 00:26:54,000 --> 00:26:56,880 Speaker 11: You're seeing the productivity gains a crew to the owners 505 00:26:56,880 --> 00:26:59,960 Speaker 11: of capital as opposed to workers, and that's why we're 506 00:27:00,600 --> 00:27:03,400 Speaker 11: are not very happy about where things are. Also, when 507 00:27:03,440 --> 00:27:05,720 Speaker 11: you think about wages, I think it's very important to 508 00:27:05,840 --> 00:27:09,240 Speaker 11: understand that we are seeing this labor market looks like 509 00:27:09,280 --> 00:27:14,160 Speaker 11: it's now healing after getting cratered last year. That's important, 510 00:27:14,400 --> 00:27:17,600 Speaker 11: but it's healing at a pace as Claudia and Eric 511 00:27:17,640 --> 00:27:20,120 Speaker 11: pointed out, where we just don't need to generate many 512 00:27:20,240 --> 00:27:23,400 Speaker 11: jobs be able to bring the unemployment rate down, which 513 00:27:23,480 --> 00:27:26,639 Speaker 11: could push wages higher. That's great if it does not 514 00:27:27,280 --> 00:27:30,200 Speaker 11: also be accompanied by information and we know that much 515 00:27:30,280 --> 00:27:35,600 Speaker 11: like stock returns compound, also inflation compounded over the last 516 00:27:35,600 --> 00:27:38,359 Speaker 11: five years, leaving too many prices out of reach for 517 00:27:38,440 --> 00:27:40,120 Speaker 11: too many Paul I was just going. 518 00:27:40,119 --> 00:27:43,920 Speaker 2: To say for your weekend reading, it's not Friday it's when. 519 00:27:43,760 --> 00:27:45,359 Speaker 5: I am I know we've got a waste to go 520 00:27:45,640 --> 00:27:48,919 Speaker 5: tom or red headline crossing the Bloomberg terminal traders fully 521 00:27:48,960 --> 00:27:52,840 Speaker 5: priced in FED rate cut by July versus June previously. 522 00:27:52,920 --> 00:27:55,840 Speaker 5: So the WORP function kind of we're seeing it right 523 00:27:55,880 --> 00:27:59,159 Speaker 5: there here on this strong labor print, Diane. We know 524 00:27:59,240 --> 00:28:02,200 Speaker 5: that FED like to look at this unemployment right and boy, 525 00:28:02,240 --> 00:28:04,920 Speaker 5: you ticked down from four point four percent to four 526 00:28:04,920 --> 00:28:11,520 Speaker 5: point three percent. That's full, full, fully employed America, isn't it. 527 00:28:11,560 --> 00:28:12,400 Speaker 3: Actually it is. 528 00:28:12,440 --> 00:28:14,880 Speaker 11: It is even better under the hood. What we saw 529 00:28:15,040 --> 00:28:17,560 Speaker 11: was the U six rate, which is that sort of 530 00:28:17,720 --> 00:28:20,920 Speaker 11: underemployment rate where you get discouraged workers and those having 531 00:28:20,960 --> 00:28:24,480 Speaker 11: just cut part time for economic reasons. That fell to 532 00:28:24,560 --> 00:28:27,440 Speaker 11: eight percent from eight point four percent in December. 533 00:28:27,760 --> 00:28:29,000 Speaker 3: That's an important move. 534 00:28:29,040 --> 00:28:31,639 Speaker 11: It's still well above the six point two percent we 535 00:28:31,680 --> 00:28:35,000 Speaker 11: saw back in twenty nineteen, but it is a move 536 00:28:35,119 --> 00:28:38,040 Speaker 11: down and an important move down for those who were 537 00:28:38,040 --> 00:28:40,480 Speaker 11: really struggling to get a job. What we're starting to 538 00:28:40,520 --> 00:28:44,400 Speaker 11: see is some of the ice melt in the labor 539 00:28:44,440 --> 00:28:47,040 Speaker 11: market now and things beginning to shift a bit. We 540 00:28:47,080 --> 00:28:50,360 Speaker 11: need to keep up that momentum for workers on the 541 00:28:50,360 --> 00:28:52,479 Speaker 11: flip side of it, it keeps the fed on the 542 00:28:52,480 --> 00:28:53,760 Speaker 11: sidelines longer. 543 00:28:54,440 --> 00:28:56,880 Speaker 5: We're not seeing, you know, what does economy, This labor 544 00:28:56,880 --> 00:28:59,959 Speaker 5: economy has been described as a kind of a low higher, 545 00:29:00,200 --> 00:29:03,320 Speaker 5: low fire type of environment. How about some of the 546 00:29:03,320 --> 00:29:08,400 Speaker 5: industries that rely historically upon immigration, such as housing, agriculture. 547 00:29:08,440 --> 00:29:10,440 Speaker 6: Are we seeing any problems there? 548 00:29:12,440 --> 00:29:14,880 Speaker 11: Well, we are seeing a major shift in things like 549 00:29:14,960 --> 00:29:17,960 Speaker 11: leisure and hospitality in terms of quit rates. Quit rates 550 00:29:18,000 --> 00:29:21,880 Speaker 11: in that sector have soared even as they've cooled and 551 00:29:22,000 --> 00:29:25,080 Speaker 11: sort of come to a near standstill across the economy, 552 00:29:25,280 --> 00:29:28,280 Speaker 11: and the job openings and labor turnover survey, we saw 553 00:29:28,560 --> 00:29:31,480 Speaker 11: those quit rates really soar. That has not been accompanied 554 00:29:31,520 --> 00:29:34,240 Speaker 11: by a lot of wage pressures in the economy that 555 00:29:34,400 --> 00:29:37,880 Speaker 11: was very weak last year, and in fact, vacations actually 556 00:29:37,920 --> 00:29:40,320 Speaker 11: went down a bit over the course of the year. 557 00:29:40,400 --> 00:29:44,280 Speaker 11: We saw only the affluent households continuing to spend heavily 558 00:29:44,320 --> 00:29:46,960 Speaker 11: on vacations, and that showed up in the breakdown in 559 00:29:47,040 --> 00:29:48,800 Speaker 11: terms of people paying to go to the front of 560 00:29:48,800 --> 00:29:52,760 Speaker 11: the bus in terms of the planes and luxury hotels 561 00:29:53,160 --> 00:29:55,719 Speaker 11: continue to do extremely well, but the rest of the 562 00:29:55,760 --> 00:30:01,000 Speaker 11: economy side of vacations did not. In twenty twenty five. 563 00:30:01,520 --> 00:30:04,520 Speaker 2: That bringing you here, folks, I believe is doctor Swank. 564 00:30:04,600 --> 00:30:09,320 Speaker 2: That's that's Kevin Worshy seeing Diane swanking right now, Like 565 00:30:09,880 --> 00:30:11,760 Speaker 2: Kevin Warsh is saying to Dan, we need to talk 566 00:30:11,880 --> 00:30:15,400 Speaker 2: right now, Diane. One of the things here, and you know, 567 00:30:15,440 --> 00:30:17,760 Speaker 2: I'll pick on. You know a city that I know 568 00:30:17,880 --> 00:30:22,280 Speaker 2: is really having trouble Alexander County, Illinois. Six percent unemployment right, 569 00:30:22,320 --> 00:30:25,760 Speaker 2: this is kro It's you know, southern Southern Illinois has 570 00:30:25,840 --> 00:30:29,760 Speaker 2: really struggled. How do you synthesize, Diane with all your 571 00:30:29,800 --> 00:30:35,760 Speaker 2: decades of work the easy gloom path versus observing the 572 00:30:35,880 --> 00:30:39,479 Speaker 2: vibrancy of the American economy. I mean, the media and 573 00:30:39,560 --> 00:30:43,200 Speaker 2: Tom Keen are really really good at going out and 574 00:30:43,240 --> 00:30:46,640 Speaker 2: finding a six percent unemployment rate and saying, OMG, the 575 00:30:46,680 --> 00:30:49,840 Speaker 2: world's going to end. But there's an America that's vital 576 00:30:49,880 --> 00:30:53,320 Speaker 2: out there. How do you balance that? After this report? 577 00:30:54,960 --> 00:30:57,080 Speaker 11: Well, I think the important issue is is that we 578 00:30:57,240 --> 00:31:01,120 Speaker 11: know that fewer firms and fewer households accounting for more 579 00:31:01,520 --> 00:31:04,400 Speaker 11: of the economic gains in the US economy. And that's 580 00:31:04,400 --> 00:31:06,600 Speaker 11: where you get to the k shaped economy. We've talked 581 00:31:06,640 --> 00:31:08,720 Speaker 11: about it a lot, but it's showing up and just 582 00:31:08,800 --> 00:31:13,040 Speaker 11: about everywhere and every strata, even with higher income households 583 00:31:13,080 --> 00:31:16,520 Speaker 11: now trading down and going to big box discounters trying 584 00:31:16,520 --> 00:31:19,960 Speaker 11: to get more value because they're feeling strained as well 585 00:31:20,080 --> 00:31:23,440 Speaker 11: unless they have a large stock portfolio. So there really 586 00:31:23,520 --> 00:31:27,120 Speaker 11: is this delineating thread that goes through the US economy 587 00:31:27,120 --> 00:31:30,240 Speaker 11: in terms of wealth versus non wealth, and it's not 588 00:31:30,360 --> 00:31:33,640 Speaker 11: just housing market wealth. Equity in your home cannot be 589 00:31:33,680 --> 00:31:36,520 Speaker 11: as easily tapped, but wealth in the stock market has 590 00:31:36,560 --> 00:31:40,520 Speaker 11: moved up dramatically, and that is important because it's not 591 00:31:40,560 --> 00:31:44,360 Speaker 11: filtering down to workers and the dichotomy of those two 592 00:31:44,400 --> 00:31:47,479 Speaker 11: things happening at the same time. The hard part is 593 00:31:47,520 --> 00:31:50,960 Speaker 11: that it keeps inflation void as well, and I think 594 00:31:51,160 --> 00:31:53,560 Speaker 11: that's something that the FED is going to be watching for, 595 00:31:53,920 --> 00:31:57,200 Speaker 11: and we know that as you heard earlier. I think 596 00:31:57,320 --> 00:31:59,840 Speaker 11: Eric pointed it out. If these losses that we saw 597 00:31:59,840 --> 00:32:03,640 Speaker 11: in jobs last year were more structural than cyclical in nature, 598 00:32:03,960 --> 00:32:06,960 Speaker 11: than rate cuts don't help them. If they are more 599 00:32:07,000 --> 00:32:11,840 Speaker 11: demand driven and the rate cuts actually helped to reignite employment, 600 00:32:11,960 --> 00:32:15,360 Speaker 11: that's great, although they don't usually work quite this quickly, 601 00:32:15,680 --> 00:32:17,720 Speaker 11: so I have my doubts about that. I think you 602 00:32:17,800 --> 00:32:22,200 Speaker 11: are working through some big uncertainty issues that finally abated 603 00:32:22,240 --> 00:32:25,800 Speaker 11: a bit, but measures of uncertainty move back up again 604 00:32:25,960 --> 00:32:27,120 Speaker 11: in the month of January. 605 00:32:27,320 --> 00:32:30,480 Speaker 2: Dayane Swack, thank you for your work Dayan Swanck is KPMG. 606 00:32:30,640 --> 00:32:36,320 Speaker 2: Here stay with us. More from Bloomberg Surveillance coming up 607 00:32:36,560 --> 00:32:37,120 Speaker 2: after this. 608 00:32:44,360 --> 00:32:47,960 Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us live 609 00:32:48,040 --> 00:32:51,160 Speaker 1: weekday afternoons from seven to ten am Eastern Listen on 610 00:32:51,280 --> 00:32:54,920 Speaker 1: Applecarplay and Android Atto with the Bloomberg Business app, or 611 00:32:55,080 --> 00:32:56,680 Speaker 1: watch us live on YouTube. 612 00:32:57,000 --> 00:32:59,040 Speaker 2: This is an honor. I'm going to explain this as 613 00:32:59,080 --> 00:33:02,880 Speaker 2: carefully as I can, and Fidelity was very very kind 614 00:33:02,920 --> 00:33:05,680 Speaker 2: to me over the years. And one day I was 615 00:33:05,840 --> 00:33:09,480 Speaker 2: at the old building up a number of floors just 616 00:33:09,520 --> 00:33:12,560 Speaker 2: pass where they keep the Red Sox tickets, and there's 617 00:33:12,600 --> 00:33:16,120 Speaker 2: a circular room with cloth walls and on it with 618 00:33:16,240 --> 00:33:22,000 Speaker 2: perfect mit pins is the chart room. Urine Timer this 619 00:33:22,040 --> 00:33:26,160 Speaker 2: week put out the chart of the Dow Jones Industrial 620 00:33:26,280 --> 00:33:29,800 Speaker 2: Average at fifty thousand. I've been waiting to talk about 621 00:33:29,800 --> 00:33:32,800 Speaker 2: this to get the Urine Timmer, director of Global Macro 622 00:33:32,920 --> 00:33:38,840 Speaker 2: at Fidelity. Urine is irresponsible to extrapolate the bullmark, a 623 00:33:38,960 --> 00:33:42,400 Speaker 2: trend that we are in out to sixty thousand or 624 00:33:42,480 --> 00:33:45,920 Speaker 2: dare I say out to one hundred thousand down points? 625 00:33:47,760 --> 00:33:51,440 Speaker 8: Well, good morning. Well certainly that chart will show you 626 00:33:51,520 --> 00:33:54,640 Speaker 8: that it is safe to extrapolate, because you know, just 627 00:33:54,720 --> 00:33:59,400 Speaker 8: like life, growth is it happens, but sometimes it happens slowly, 628 00:33:59,480 --> 00:34:03,760 Speaker 8: sometimes happens quickly. So we will get there eventually. But 629 00:34:04,120 --> 00:34:07,480 Speaker 8: you know, the dial can spend many years at one 630 00:34:07,480 --> 00:34:11,000 Speaker 8: of these milestones, or it could spend literally a minute 631 00:34:11,280 --> 00:34:14,680 Speaker 8: before it goes to the next one. And this one, 632 00:34:14,760 --> 00:34:17,160 Speaker 8: of course, you know, we are in year at least 633 00:34:17,160 --> 00:34:20,759 Speaker 8: by my estimation, we are in year seventeen of a 634 00:34:20,760 --> 00:34:24,960 Speaker 8: secular bull market. And the milestones come fast and furious 635 00:34:25,040 --> 00:34:28,799 Speaker 8: during secular bull markets, and they come very slowly during 636 00:34:28,840 --> 00:34:32,120 Speaker 8: secular bear markets. And so I think the drivers of 637 00:34:32,160 --> 00:34:35,279 Speaker 8: this secular bull are still intact. But it is long 638 00:34:35,320 --> 00:34:37,839 Speaker 8: into tooths. You know, they generally don't last more than 639 00:34:38,320 --> 00:34:40,719 Speaker 8: eighteen nineteen years or so, so we do have to 640 00:34:40,800 --> 00:34:42,719 Speaker 8: keep an eye on the clock in that sense. But 641 00:34:43,800 --> 00:34:47,319 Speaker 8: it's you know, I found it very pleasing last week 642 00:34:47,320 --> 00:34:51,600 Speaker 8: that when we're worried about the SaaS stocks getting commoditized 643 00:34:51,640 --> 00:34:56,840 Speaker 8: because of AI programs, and you know, are the hyperscalers 644 00:34:56,960 --> 00:35:01,840 Speaker 8: overspending on capex that very quietly the Dow just in 645 00:35:02,080 --> 00:35:06,000 Speaker 8: the week at a very major milestone. So it's nice 646 00:35:06,000 --> 00:35:09,680 Speaker 8: to see that the market is broadening, and it's doing 647 00:35:09,760 --> 00:35:13,080 Speaker 8: so in the best way possible, which is not as 648 00:35:13,080 --> 00:35:17,120 Speaker 8: a zero sum where the max seven you'll fall from 649 00:35:17,200 --> 00:35:20,840 Speaker 8: grace and drag the index down even though most stocks 650 00:35:20,840 --> 00:35:22,959 Speaker 8: are going up, but in a way where the pie 651 00:35:23,080 --> 00:35:25,200 Speaker 8: actually gets bigger. And now we'll have to see if 652 00:35:25,200 --> 00:35:27,719 Speaker 8: it blasts, but it's a win for. 653 00:35:27,719 --> 00:35:29,040 Speaker 6: Now you're in. 654 00:35:29,480 --> 00:35:33,480 Speaker 5: We've seen I guess a rotation over the last three 655 00:35:33,560 --> 00:35:35,919 Speaker 5: four five months, maybe a little bit of rotation out 656 00:35:36,000 --> 00:35:39,320 Speaker 5: of some of those high growth, high multiple tech stocks, 657 00:35:39,320 --> 00:35:42,440 Speaker 5: maybe a little max seven into or cyclical sectors, maybe 658 00:35:42,480 --> 00:35:46,160 Speaker 5: in some small and MidCap Is that a longer term trade? 659 00:35:46,200 --> 00:35:47,680 Speaker 6: Is that a short term trade? How do you think 660 00:35:47,760 --> 00:35:48,160 Speaker 6: about that? 661 00:35:49,480 --> 00:35:51,200 Speaker 8: I think it's a longer term trade. Right, So, if 662 00:35:51,239 --> 00:35:55,960 Speaker 8: you line up a bunch of Paris trades, growth versus value, large, 663 00:35:56,600 --> 00:36:03,719 Speaker 8: small US versus international, financial versus hard assets, the commodities 664 00:36:03,760 --> 00:36:07,520 Speaker 8: in general, they all follow like a thirty year cycle, 665 00:36:07,560 --> 00:36:10,680 Speaker 8: like a very long wave, almost like a condatif wave 666 00:36:10,800 --> 00:36:15,000 Speaker 8: type of formation and on a ten year rate of 667 00:36:15,120 --> 00:36:19,160 Speaker 8: change basis, a cager basis, all of those paris trades 668 00:36:19,239 --> 00:36:21,520 Speaker 8: have been sort of waiting in the wings from a 669 00:36:22,040 --> 00:36:26,080 Speaker 8: duration and a magnitude perspective, and we're just waiting for 670 00:36:26,160 --> 00:36:28,440 Speaker 8: the catalyst, right, So as long as the Max seven 671 00:36:28,480 --> 00:36:32,000 Speaker 8: are dominating, all those para trades have to sort of wait. 672 00:36:32,520 --> 00:36:35,600 Speaker 8: But one by one they're springing to life. Right. International 673 00:36:35,719 --> 00:36:39,280 Speaker 8: is now outperforming US, which is very nice to see 674 00:36:39,320 --> 00:36:43,319 Speaker 8: because we want the market to be as broad as possible, right, 675 00:36:43,360 --> 00:36:47,080 Speaker 8: we want to fish from the biggest pond possible. Commodities 676 00:36:47,480 --> 00:36:51,239 Speaker 8: are moving and like you said, even small and midcaps 677 00:36:51,280 --> 00:36:54,839 Speaker 8: are now starting to wake up, and so I do 678 00:36:54,920 --> 00:36:58,440 Speaker 8: think that once that happens, it's a long term trend. 679 00:36:58,560 --> 00:37:04,160 Speaker 8: That's like a five year plus strategic allocation type of plan. 680 00:37:04,560 --> 00:37:06,879 Speaker 8: The question is, you know, again, does it come at 681 00:37:06,880 --> 00:37:09,399 Speaker 8: the It always comes at the expensive growth, But does 682 00:37:09,440 --> 00:37:12,040 Speaker 8: it come at the expense of the beta that the 683 00:37:12,080 --> 00:37:15,680 Speaker 8: growth sector produces? And if that's the case, we're going 684 00:37:15,719 --> 00:37:18,520 Speaker 8: to have less beta but more alpha. But that's to 685 00:37:18,560 --> 00:37:19,480 Speaker 8: me is the big question. 686 00:37:19,760 --> 00:37:21,719 Speaker 2: You're in timor with us folks, to help us get 687 00:37:21,719 --> 00:37:25,319 Speaker 2: smarter with Fidelity or Carol Weinberg later on in the hour, 688 00:37:25,400 --> 00:37:27,960 Speaker 2: we welcome all of you around the world on YouTube. 689 00:37:28,000 --> 00:37:31,239 Speaker 2: Subscribe to Bloomberg Podcast, Sweete and I Shaking down the 690 00:37:31,239 --> 00:37:34,520 Speaker 2: new Bloomberg Hub a set of videos here out at 691 00:37:34,560 --> 00:37:37,640 Speaker 2: Bloomberg dot com. Look for that building out each and 692 00:37:37,680 --> 00:37:39,600 Speaker 2: every day. And of course the way you listen to us, 693 00:37:39,800 --> 00:37:42,680 Speaker 2: especially good morning to ninety to nine FM in Boston, 694 00:37:43,160 --> 00:37:46,759 Speaker 2: Land of Fidelity, and you're in Timber, you're in which 695 00:37:46,800 --> 00:37:49,280 Speaker 2: of your wonderful charts that you give us on LinkedIn 696 00:37:49,719 --> 00:37:53,840 Speaker 2: and all of Fidelity? Which charts the most informative for 697 00:37:53,960 --> 00:37:58,040 Speaker 2: people in their fe own case. They're inequities. They believe 698 00:37:58,080 --> 00:38:02,240 Speaker 2: in the American experiment, which is the chart that matters most. 699 00:38:03,480 --> 00:38:07,120 Speaker 8: I think, well, there's so many, but the one that 700 00:38:07,320 --> 00:38:12,120 Speaker 8: explains the market's lofty valuations. Right, So we all spend 701 00:38:12,160 --> 00:38:14,080 Speaker 8: a lot of time on like, Okay, the US stocks 702 00:38:14,080 --> 00:38:18,120 Speaker 8: are so expensive, you know, thirty two x five year 703 00:38:18,760 --> 00:38:22,799 Speaker 8: cape ratio, twenty five times trailing earnings. But you have 704 00:38:22,880 --> 00:38:25,799 Speaker 8: to take that into context, right, if you regress those 705 00:38:25,840 --> 00:38:31,279 Speaker 8: pes or equity risk premia against where investment grade or 706 00:38:31,400 --> 00:38:34,879 Speaker 8: high yield credit spreads are and where operating margins are 707 00:38:34,960 --> 00:38:38,879 Speaker 8: for the s and P five hundred, they actually make sense, right, 708 00:38:38,960 --> 00:38:41,440 Speaker 8: So you know, the market's not stupid. It's not going 709 00:38:41,520 --> 00:38:45,120 Speaker 8: to price itself at a at a level that doesn't 710 00:38:45,160 --> 00:38:49,799 Speaker 8: make sense. It's very efficient. And so if you think 711 00:38:49,920 --> 00:38:53,839 Speaker 8: equities are very expensive or too expensive, or even in 712 00:38:53,840 --> 00:38:56,640 Speaker 8: a bubble, which I don't think they are, then by 713 00:38:56,719 --> 00:39:00,239 Speaker 8: definition you have to think, in my view, that credit 714 00:39:00,320 --> 00:39:02,759 Speaker 8: spreads are too low and are going to rise, and 715 00:39:02,960 --> 00:39:06,239 Speaker 8: margins are too high and are going to fall. Otherwise, 716 00:39:06,680 --> 00:39:12,040 Speaker 8: equities are just pricing in in the same fundamental scenario 717 00:39:12,160 --> 00:39:15,120 Speaker 8: that all the other markets are pricing in. And so 718 00:39:15,600 --> 00:39:18,360 Speaker 8: I think that's an important thing to keep in mind, 719 00:39:18,440 --> 00:39:21,520 Speaker 8: because it's easy after a long up trend, you know, 720 00:39:21,800 --> 00:39:24,640 Speaker 8: and the cyclical bull is now forty months old, the 721 00:39:24,680 --> 00:39:28,360 Speaker 8: secular bull is now seventeen years old to say, you know, 722 00:39:28,640 --> 00:39:30,640 Speaker 8: I'm afraid of what comes next, so I'm going to 723 00:39:30,719 --> 00:39:32,799 Speaker 8: get out. But if you get out, you're not going 724 00:39:32,880 --> 00:39:37,879 Speaker 8: to compound, and that's a major drawback. So looking at 725 00:39:37,960 --> 00:39:42,399 Speaker 8: the market holistically and look at why valuations are where 726 00:39:42,440 --> 00:39:44,920 Speaker 8: they are, what do they assume, I think is an 727 00:39:44,960 --> 00:39:48,000 Speaker 8: important piece of context. Otherwise it's easy just to say 728 00:39:48,000 --> 00:39:49,680 Speaker 8: Oh my god, we're in a bubble. I'm going to 729 00:39:49,760 --> 00:39:50,640 Speaker 8: run for the hills. 730 00:39:51,080 --> 00:39:54,040 Speaker 5: You're in twenty twenty five and in year to date 731 00:39:54,360 --> 00:39:56,680 Speaker 5: so far in twenty twenty six, the US equity markets 732 00:39:56,719 --> 00:39:59,680 Speaker 5: doing just fine, but rest of the world doing a 733 00:39:59,680 --> 00:40:02,320 Speaker 5: lot better than fine, outperforming the US. 734 00:40:02,520 --> 00:40:04,399 Speaker 6: Talk to us about US versus rest of the world 735 00:40:04,440 --> 00:40:05,359 Speaker 6: these days. What's your view? 736 00:40:06,480 --> 00:40:09,240 Speaker 8: Yeah, it's a it's a really great story. It happened 737 00:40:09,360 --> 00:40:12,319 Speaker 8: last year, of course during sort of the tariff tantrum. 738 00:40:13,560 --> 00:40:17,520 Speaker 8: But what's happening is that the global economy is waking up. 739 00:40:17,560 --> 00:40:20,120 Speaker 8: You know, we all know the story from a year 740 00:40:20,160 --> 00:40:23,440 Speaker 8: ago with NATO having to pull its own weight and 741 00:40:23,560 --> 00:40:26,520 Speaker 8: seeing more of a fiscal impulse in Europe, and of 742 00:40:26,560 --> 00:40:31,160 Speaker 8: course in Japan we're seeing that, you know, commodities are 743 00:40:31,200 --> 00:40:37,960 Speaker 8: becoming a national security type of resource. So in a fragmented, 744 00:40:38,040 --> 00:40:42,040 Speaker 8: multipolar world, I think commodities become a strategic asset. And 745 00:40:42,120 --> 00:40:45,520 Speaker 8: so then you have you look at commodity centric countries, 746 00:40:45,560 --> 00:40:50,160 Speaker 8: mostly in emerging markets that are now you know, being competitive. 747 00:40:50,280 --> 00:40:53,640 Speaker 8: So when I divide the world into developed and emerging 748 00:40:53,719 --> 00:40:58,600 Speaker 8: so versus e M, they both have interesting stories. Right. 749 00:41:01,200 --> 00:41:04,120 Speaker 8: The companies in Japan and Europe are becoming much more 750 00:41:04,200 --> 00:41:09,600 Speaker 8: shareholder savvy. They're unlocking or monetizing their balance sheets in 751 00:41:09,719 --> 00:41:12,840 Speaker 8: order and by buying back shares in order to reward 752 00:41:12,880 --> 00:41:16,719 Speaker 8: shareholders with a higher payout ratio. And it's interesting that 753 00:41:16,760 --> 00:41:20,759 Speaker 8: the payouts, so dividends plus buybacks, is rising faster on 754 00:41:20,800 --> 00:41:24,200 Speaker 8: a five year basis in both Europe and em than 755 00:41:24,239 --> 00:41:26,960 Speaker 8: it is in US, which is maybe counterintuitive because in 756 00:41:26,960 --> 00:41:30,040 Speaker 8: the US you figure max seven art are the engines 757 00:41:30,120 --> 00:41:34,800 Speaker 8: for that story. But the payouts are competitive, the payout 758 00:41:34,880 --> 00:41:38,440 Speaker 8: ratios are competitive. Yet they trade at a fifteen PE 759 00:41:38,480 --> 00:41:41,040 Speaker 8: as opposed to a twenty two PE. And that's so 760 00:41:41,160 --> 00:41:43,160 Speaker 8: you know, it's easy to fall into a value trap, 761 00:41:43,200 --> 00:41:47,680 Speaker 8: but you have the value plus a fundamental catalyst. Boy, 762 00:41:47,719 --> 00:41:50,120 Speaker 8: you got some magic and that's what we're seeing over there. 763 00:41:50,239 --> 00:41:52,400 Speaker 2: Okay, I got to ask Paul was just on a 764 00:41:52,480 --> 00:41:54,720 Speaker 2: rube and he's decided to move there. You're in Timor 765 00:41:55,480 --> 00:41:58,320 Speaker 2: I'm there right now? 766 00:41:58,320 --> 00:41:59,879 Speaker 6: Why did we know that? 767 00:41:59,440 --> 00:42:02,759 Speaker 2: I I mean, I mean Urian Should we slide into 768 00:42:02,800 --> 00:42:08,120 Speaker 2: the Dutch Caribbean Securities Exchange? I mean, is Will Danoff 769 00:42:08,239 --> 00:42:11,160 Speaker 2: looking at every stock in there? Yeah? 770 00:42:11,320 --> 00:42:13,360 Speaker 8: Well you know it's Carnival a week in a rubab 771 00:42:13,719 --> 00:42:15,719 Speaker 8: and that can only mean one thing, and that is 772 00:42:15,760 --> 00:42:19,680 Speaker 8: that I've got about a dozen extended Timmor family and 773 00:42:19,719 --> 00:42:22,640 Speaker 8: friends right at my brother's house, and that means I 774 00:42:22,640 --> 00:42:24,680 Speaker 8: get to cook. So I cooked the great twelve people 775 00:42:24,760 --> 00:42:27,560 Speaker 8: last night. I'm cooking for fifteen tonight. So this is 776 00:42:27,600 --> 00:42:29,640 Speaker 8: our annual tradition and. 777 00:42:30,040 --> 00:42:30,480 Speaker 6: Good for you. 778 00:42:30,600 --> 00:42:32,040 Speaker 8: And you know this is my ole king. 779 00:42:32,360 --> 00:42:33,560 Speaker 6: We got enough Carnival. 780 00:42:33,800 --> 00:42:36,799 Speaker 2: Is Abby Johnson ever Grace a Timmer household in her 781 00:42:36,840 --> 00:42:39,160 Speaker 2: room but for this festivities. 782 00:42:39,000 --> 00:42:41,200 Speaker 8: Uh, not that I know of, but if she, if 783 00:42:41,200 --> 00:42:43,080 Speaker 8: she calls me, I would certainly makes some room. 784 00:42:43,400 --> 00:42:47,640 Speaker 2: Very good, Urian. We appreciate your work. I can't say enough, folks. Literally. 785 00:42:47,840 --> 00:42:50,319 Speaker 2: A reason to get on LinkedIn is to see the 786 00:42:50,320 --> 00:42:54,240 Speaker 2: brilliance of fidelity in Urine Timmer. There as well Twitter 787 00:42:54,320 --> 00:42:58,480 Speaker 2: as well. Urine Timmor driving everything in charts, technical analysis 788 00:42:58,480 --> 00:43:01,840 Speaker 2: and macro analysis at Fidelity. 789 00:43:02,080 --> 00:43:06,920 Speaker 1: This is the Bloomberg Surveillance podcast, available on Apple, Spotify, 790 00:43:07,040 --> 00:43:10,799 Speaker 1: and anywhere else you get your podcasts. Listen live each 791 00:43:10,840 --> 00:43:14,680 Speaker 1: weekday seven to ten am Eastern on Bloomberg dot com, 792 00:43:14,800 --> 00:43:18,640 Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business app. 793 00:43:18,920 --> 00:43:22,040 Speaker 1: You can also Watch US live every weekday on YouTube 794 00:43:22,320 --> 00:43:24,360 Speaker 1: and always on the Bloomberg terminal