1 00:00:00,800 --> 00:00:04,040 Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney, alongside 2 00:00:04,040 --> 00:00:06,920 Speaker 1: my co host Matt Miller. Every business day we bring 3 00:00:06,960 --> 00:00:11,520 Speaker 1: you interviews from CEOs, market pros, and Bloomberg experts, along 4 00:00:11,560 --> 00:00:15,520 Speaker 1: with essential market moving news. Find the Bloomberg Markets podcast 5 00:00:15,560 --> 00:00:18,479 Speaker 1: called Apple Podcasts or wherever you listen to podcasts, and 6 00:00:18,480 --> 00:00:23,119 Speaker 1: at Bloomberg dot com slash podcast. Danielle di Martino booth, 7 00:00:23,160 --> 00:00:25,160 Speaker 1: let's get right to her. She's a CEO and chief 8 00:00:25,160 --> 00:00:28,479 Speaker 1: strategist for Quill Intelligence, also a former advisor at the 9 00:00:28,480 --> 00:00:32,279 Speaker 1: Federal Reserve Bank of Dallas. So, Danielle, thanks so much 10 00:00:32,440 --> 00:00:34,159 Speaker 1: for taking the time. I guess where I want to 11 00:00:34,200 --> 00:00:36,960 Speaker 1: start with is you know, during the press conference from 12 00:00:37,000 --> 00:00:41,040 Speaker 1: FED Chairman Pal there's obviously questions about potentially a recession 13 00:00:41,200 --> 00:00:44,800 Speaker 1: slowing growth, and he took a pretty aggressive tact and 14 00:00:44,880 --> 00:00:47,280 Speaker 1: pushing back on that narrative. What's your take? What do 15 00:00:47,320 --> 00:00:50,319 Speaker 1: you think he's trying to do well. I think he's 16 00:00:50,320 --> 00:00:53,520 Speaker 1: trying to do his job, which is to use FED 17 00:00:53,600 --> 00:00:58,480 Speaker 1: speak to its fullest and to induce confidence in the 18 00:00:58,560 --> 00:01:02,120 Speaker 1: markets and induced confidence among those who are listening to him, 19 00:01:02,160 --> 00:01:05,160 Speaker 1: to say we've got this under control. We're going to 20 00:01:05,200 --> 00:01:08,600 Speaker 1: be able to to navigate a soft landing. And of 21 00:01:08,640 --> 00:01:12,680 Speaker 1: course today we've heard that from from Governor Waller. We've 22 00:01:12,720 --> 00:01:16,680 Speaker 1: heard the month July in terms of when they're looking 23 00:01:16,680 --> 00:01:20,040 Speaker 1: at starting that balance sheet runoff. That would explain why 24 00:01:20,120 --> 00:01:22,839 Speaker 1: they used the phrase coming months. So clearly they think 25 00:01:22,840 --> 00:01:27,040 Speaker 1: that this spate of inflation that's induced by Russia invading 26 00:01:27,120 --> 00:01:29,640 Speaker 1: Ukraine is going to be short lived and possibly be 27 00:01:29,720 --> 00:01:31,800 Speaker 1: coming off the time we get towards the end of summer. 28 00:01:31,959 --> 00:01:37,760 Speaker 1: Was he doing his job last year, Danielle, Oh gosh, no, heavens, no, no, no, no, no. 29 00:01:38,000 --> 00:01:42,760 Speaker 1: You just saw first time homebuyers decreased. The National Association 30 00:01:42,800 --> 00:01:45,600 Speaker 1: of Realtors at Laurence June said that that a payment 31 00:01:45,600 --> 00:01:48,920 Speaker 1: in February was higher than it was a year earlier. 32 00:01:49,120 --> 00:01:51,560 Speaker 1: At a minimum, you could say, you know what, we'll 33 00:01:51,600 --> 00:01:54,320 Speaker 1: hold off on treasury run off, but we'll go ahead 34 00:01:54,560 --> 00:01:58,280 Speaker 1: and be responsible to homebuyers who cannot buy homes because 35 00:01:58,280 --> 00:02:00,560 Speaker 1: they're too expensive. Will be respond will and let those 36 00:02:00,560 --> 00:02:04,280 Speaker 1: mortgage backs start to run off by themselves before treasuries. So, Daniel, 37 00:02:04,320 --> 00:02:06,800 Speaker 1: what do you take of this new wrinkle. I guess 38 00:02:06,840 --> 00:02:09,880 Speaker 1: it's just from an economic perspective into the equation, which 39 00:02:09,919 --> 00:02:13,320 Speaker 1: is a hot shooting war in Eastern Europe. If I'm 40 00:02:13,360 --> 00:02:16,320 Speaker 1: the Federal Reserve, I've got inflation, I've got slowing growth. 41 00:02:16,800 --> 00:02:19,600 Speaker 1: Now I've got this geopolitical risk at how do you 42 00:02:19,600 --> 00:02:24,840 Speaker 1: think that factors into the Fed's calculus. Well, it should 43 00:02:24,880 --> 00:02:27,520 Speaker 1: obviously be a factor, right, This is a this is 44 00:02:27,560 --> 00:02:31,799 Speaker 1: a new idiosyncrasy that's going to affect confidence. Bank of 45 00:02:31,840 --> 00:02:36,119 Speaker 1: America has a their own proprietary confidence gauge. It fell 46 00:02:36,160 --> 00:02:39,000 Speaker 1: to the lowest in history in the week through March thirteenth. 47 00:02:39,360 --> 00:02:42,920 Speaker 1: So there's clearly a dent being made. And people are 48 00:02:42,919 --> 00:02:46,000 Speaker 1: watching the headlines and they're disturbing. I get that. But 49 00:02:46,280 --> 00:02:50,760 Speaker 1: the primary source of economic new news out of this 50 00:02:50,880 --> 00:02:53,720 Speaker 1: situation is that it's pushing inflation higher. And I think 51 00:02:53,720 --> 00:02:55,639 Speaker 1: that that's a greater offset and that they should look 52 00:02:55,639 --> 00:02:58,440 Speaker 1: at it through that lens. Because of the high starting 53 00:02:58,440 --> 00:03:02,359 Speaker 1: point of gasoline prices rising year over year in Intebrary 54 00:03:02,440 --> 00:03:04,799 Speaker 1: CPI yeah, if it's just filled up on the way 55 00:03:04,800 --> 00:03:07,400 Speaker 1: to work today for well over five dollars a gallon, 56 00:03:07,440 --> 00:03:09,960 Speaker 1: which I guess I should consider myself lucky. Because the 57 00:03:10,000 --> 00:03:13,280 Speaker 1: Germans are hoping for legislation that lowers their gas bills 58 00:03:13,320 --> 00:03:16,200 Speaker 1: to eight dollars a gallon. They feel like that should Well, 59 00:03:16,280 --> 00:03:20,080 Speaker 1: I get concerned when we start throwing around price fixing 60 00:03:20,120 --> 00:03:23,160 Speaker 1: because central bankers all talk to each other, So I 61 00:03:23,160 --> 00:03:25,840 Speaker 1: don't don't want anybody getting any ideas here in the 62 00:03:25,919 --> 00:03:28,200 Speaker 1: United States about price fixing. You can look back and 63 00:03:28,280 --> 00:03:30,639 Speaker 1: google Nixon and price fixing and see how that ended. No, 64 00:03:31,040 --> 00:03:35,040 Speaker 1: agree one percent. The thing is the price is already 65 00:03:35,080 --> 00:03:38,840 Speaker 1: fixed in Germany because like cent of what you pay 66 00:03:38,880 --> 00:03:41,440 Speaker 1: at the pump is taxes, you know, so all they 67 00:03:41,480 --> 00:03:43,200 Speaker 1: need to do is reduce some of that burden. And 68 00:03:43,240 --> 00:03:46,880 Speaker 1: I'm sure we have a similar, uh not nearly as bad, 69 00:03:46,920 --> 00:03:50,360 Speaker 1: but um similar tax burden here. What I was going 70 00:03:50,400 --> 00:03:55,120 Speaker 1: to ask about is um the growth, the slowing growth? 71 00:03:55,240 --> 00:03:58,760 Speaker 1: I guess is it the bigger concern. And it looks 72 00:03:58,800 --> 00:04:01,920 Speaker 1: like when you have a Moody shock, which we have had, 73 00:04:02,040 --> 00:04:05,120 Speaker 1: or when you have the fed um starting to raise rates, 74 00:04:05,160 --> 00:04:07,880 Speaker 1: which we have, or when you have yield curves invert, 75 00:04:07,920 --> 00:04:12,360 Speaker 1: which we saw yesterday. Um, these things all tend to 76 00:04:12,440 --> 00:04:16,080 Speaker 1: lead to recessions. Not necessarily you're gonna have a recession 77 00:04:16,080 --> 00:04:18,120 Speaker 1: after that, but you know, all three of them at once. 78 00:04:18,320 --> 00:04:22,080 Speaker 1: Do we have a recession next year. I'm not so sure. 79 00:04:22,600 --> 00:04:25,280 Speaker 1: My good friend Peter Jucchini said this morning that his 80 00:04:25,360 --> 00:04:29,000 Speaker 1: base cases is a recession in two based purely on 81 00:04:29,040 --> 00:04:32,279 Speaker 1: what he seen in the rapidity of the cycle compression. 82 00:04:32,800 --> 00:04:36,240 Speaker 1: We we got accustomed to ten years of expansion, and 83 00:04:36,240 --> 00:04:38,720 Speaker 1: now we're talking about things happening inside of a two 84 00:04:38,720 --> 00:04:42,200 Speaker 1: to three year vacuum. So there's no reason to go 85 00:04:42,320 --> 00:04:45,119 Speaker 1: by the old playbook that suggests that once we see 86 00:04:45,360 --> 00:04:48,320 Speaker 1: yield curves flirting with inversion, that it shouldn't be a 87 00:04:48,320 --> 00:04:51,640 Speaker 1: faster runway between that moment and when we go into 88 00:04:51,720 --> 00:04:55,000 Speaker 1: an actual contraction. And again, this is a byproduct of 89 00:04:55,040 --> 00:04:57,960 Speaker 1: the Fed waiting too long last year to take the 90 00:04:57,960 --> 00:05:02,320 Speaker 1: opportunity of beginning to normalize. Then were you surprised at all, 91 00:05:02,360 --> 00:05:04,440 Speaker 1: at Danielle, that they did not raised by fifty basis 92 00:05:04,520 --> 00:05:08,280 Speaker 1: points this week. I was not surprised at all that 93 00:05:08,279 --> 00:05:10,839 Speaker 1: that did not surprise me in the least. I was 94 00:05:10,920 --> 00:05:13,520 Speaker 1: shocked that they said in coming months about the balance sheet. 95 00:05:13,880 --> 00:05:15,680 Speaker 1: And I'm even more shocked because now that we have 96 00:05:15,720 --> 00:05:18,159 Speaker 1: Waller out on the wires, you know what was what's 97 00:05:18,200 --> 00:05:21,400 Speaker 1: being contemplated among those on the Federal Open Market Committee 98 00:05:21,440 --> 00:05:23,640 Speaker 1: and that right now appears to be July. So I 99 00:05:23,680 --> 00:05:26,400 Speaker 1: was expecting there to there to be an indication that 100 00:05:26,480 --> 00:05:28,680 Speaker 1: the balance sheet run up would start in May. And 101 00:05:28,760 --> 00:05:30,920 Speaker 1: even is it going to be eighty billion dollars a 102 00:05:30,960 --> 00:05:32,960 Speaker 1: month or a hundred billion dollars a month. Lorie Logan 103 00:05:33,040 --> 00:05:35,480 Speaker 1: of the New York Fed Markets Desk and John Williams, 104 00:05:35,520 --> 00:05:37,640 Speaker 1: the President of the New York Fits, they've been fairly 105 00:05:38,560 --> 00:05:42,240 Speaker 1: explicit in terms of where they saw that balance sheet 106 00:05:42,279 --> 00:05:45,440 Speaker 1: run up beginning, at what levels, and how aggressively they 107 00:05:45,440 --> 00:05:47,560 Speaker 1: would they would have it run, which would be more 108 00:05:47,600 --> 00:05:50,320 Speaker 1: aggressively than the last time they attempted this. And yet 109 00:05:50,720 --> 00:05:53,280 Speaker 1: they appeared to be extremely hesitant on this tack. And 110 00:05:53,320 --> 00:05:55,480 Speaker 1: that was what surprised me the most. Okay, Daniel D. 111 00:05:55,560 --> 00:05:58,320 Speaker 1: Martino Booth, we knew we'd get the clean skinny on 112 00:05:58,440 --> 00:06:00,880 Speaker 1: what's going on with our federal reserve. Daniel D. Martino Booth, 113 00:06:01,000 --> 00:06:05,840 Speaker 1: CEO and chief strategist A Quill Intelligence still concerned that 114 00:06:06,240 --> 00:06:09,520 Speaker 1: the photo Reserve is behind the curve here. Yeah, and 115 00:06:09,520 --> 00:06:11,560 Speaker 1: and the risk is that they get a little too 116 00:06:11,600 --> 00:06:13,640 Speaker 1: aggressive to try and catch up, and and that's what 117 00:06:13,680 --> 00:06:16,359 Speaker 1: could push you into It's unlikely they'll do that with 118 00:06:16,400 --> 00:06:18,159 Speaker 1: the balance sheet, right, I mean, remember when they wanted 119 00:06:18,200 --> 00:06:20,599 Speaker 1: to reduce the four trillion dollar balance sheet, which was 120 00:06:20,600 --> 00:06:25,080 Speaker 1: already i poppingly large. Um, just a couple of years later, 121 00:06:25,480 --> 00:06:30,880 Speaker 1: we're looking at nine trillions son nine times nine times 122 00:06:31,200 --> 00:06:37,680 Speaker 1: for those that get the reference. We've got some ECO 123 00:06:37,760 --> 00:06:40,919 Speaker 1: data out. Got the Leading Economic Indicator came out today 124 00:06:41,080 --> 00:06:42,720 Speaker 1: pretty decent. I'm gonna say I'm not you know, I 125 00:06:42,760 --> 00:06:44,920 Speaker 1: think our economy hanging in there, but let's get the details. 126 00:06:44,960 --> 00:06:48,960 Speaker 1: Automan Azoldrum, Senior director of Economic Research at the conference Board. 127 00:06:48,960 --> 00:06:51,920 Speaker 1: Ottoman talked to us about the Leading Economic Indicator data 128 00:06:52,000 --> 00:06:55,040 Speaker 1: that just came out this morning. Yeah, good morning to 129 00:06:55,080 --> 00:06:58,400 Speaker 1: be here. So, yes, the Leading Economic Index came out 130 00:06:58,480 --> 00:07:02,960 Speaker 1: this morning. It increased about zero point three percent in February. 131 00:07:03,680 --> 00:07:09,440 Speaker 1: That's reversing the revised decline from January, and overall, the 132 00:07:09,680 --> 00:07:15,560 Speaker 1: Leading Economic Index remains on a moderately rising trajectory, pointing 133 00:07:15,640 --> 00:07:20,040 Speaker 1: to continuing expansion for the US economy. So, after after 134 00:07:20,160 --> 00:07:23,440 Speaker 1: weathering the omicrond wave in the beginning of the year, 135 00:07:23,880 --> 00:07:27,200 Speaker 1: the US economy UM is in fairly good shape in 136 00:07:27,240 --> 00:07:30,920 Speaker 1: the first quarter. But what can you see about UM? 137 00:07:30,960 --> 00:07:35,880 Speaker 1: What's to come? Right? So there are some clouds in 138 00:07:35,880 --> 00:07:39,800 Speaker 1: the horizon UM. And we've been uh, you know, looking 139 00:07:39,920 --> 00:07:46,040 Speaker 1: at what inflation means for household budgets, UH, consumer spending. 140 00:07:46,880 --> 00:07:51,080 Speaker 1: We look at the volatility in stock prices UM and 141 00:07:51,400 --> 00:07:55,400 Speaker 1: one of the negative contributors this month was a building 142 00:07:55,440 --> 00:08:00,840 Speaker 1: permit spell and the housing construction sector is likely to 143 00:08:00,880 --> 00:08:04,240 Speaker 1: be negatively affected, you know, as the Fed continues to 144 00:08:04,600 --> 00:08:07,800 Speaker 1: raise rates for the rest of the year. So you know, 145 00:08:07,840 --> 00:08:11,360 Speaker 1: there are some clouds that will slow growth UM. And 146 00:08:11,600 --> 00:08:14,440 Speaker 1: we've seen that in you know, some of the UH 147 00:08:14,640 --> 00:08:19,680 Speaker 1: growth numbers getting revised for two UM. And unfortunately, on 148 00:08:19,760 --> 00:08:24,800 Speaker 1: top of that, we have the Russian invasion of Ukraine 149 00:08:25,240 --> 00:08:29,800 Speaker 1: that is creating made a major shock for the global economy. UH. 150 00:08:29,840 --> 00:08:33,920 Speaker 1: So it's it could also lower the trajectory and lower 151 00:08:33,960 --> 00:08:37,240 Speaker 1: growth rates further for two It's kind of where I 152 00:08:37,240 --> 00:08:40,400 Speaker 1: wanted to go Outoman. I think some folks are saying, hey, 153 00:08:40,400 --> 00:08:44,640 Speaker 1: when you put these rapid and significant rate increases along 154 00:08:44,720 --> 00:08:48,400 Speaker 1: with a shooting war in Europe, that might be enough 155 00:08:48,440 --> 00:08:52,080 Speaker 1: to push you know, some economies into a recession. Is 156 00:08:52,080 --> 00:08:54,520 Speaker 1: the R word in your vocabulary for the next year 157 00:08:54,559 --> 00:08:59,120 Speaker 1: or two? Uh not yet. So you know, the leading 158 00:08:59,160 --> 00:09:02,840 Speaker 1: economic indey is a gauge of recessions. It's used for 159 00:09:02,920 --> 00:09:08,080 Speaker 1: predicting recessions, and so far it hasn't been signaling anything 160 00:09:08,160 --> 00:09:11,040 Speaker 1: like that. And looking ahead, we have to watch that 161 00:09:11,880 --> 00:09:16,360 Speaker 1: very carefully. But the you know, underlying trend trajectory for 162 00:09:16,440 --> 00:09:21,680 Speaker 1: the US economy has been fairly healthy. UM and um. 163 00:09:21,679 --> 00:09:25,200 Speaker 1: You know, even though revising growth rates down to around 164 00:09:25,200 --> 00:09:30,240 Speaker 1: three percent for UM, we we are still looking at 165 00:09:30,760 --> 00:09:37,840 Speaker 1: pretty robust above average growth rates in terms of what 166 00:09:37,960 --> 00:09:41,480 Speaker 1: the Fed does here. Um. Do you get the idea 167 00:09:41,559 --> 00:09:47,120 Speaker 1: that this is hurting the leading indicators? Uh, it does 168 00:09:47,520 --> 00:09:52,640 Speaker 1: create a potential downward risk for many leading indicators as 169 00:09:52,640 --> 00:09:55,120 Speaker 1: well as for the economy. Of course, that's what we're 170 00:09:55,160 --> 00:09:59,079 Speaker 1: trying to measure here. UM. So as those rates start 171 00:09:59,160 --> 00:10:02,480 Speaker 1: to go up to find inflation, we're going to begin 172 00:10:02,559 --> 00:10:06,480 Speaker 1: to see the impact starting out, you know, spilling over 173 00:10:06,559 --> 00:10:09,679 Speaker 1: into mortgage rates and credit card rates, and those are 174 00:10:09,720 --> 00:10:13,839 Speaker 1: the channels or mechanisms that work to slow the economy 175 00:10:14,360 --> 00:10:19,199 Speaker 1: and attempt to control inflation. So, UM, we will begin 176 00:10:19,280 --> 00:10:23,880 Speaker 1: to see some of that. But compared to the negative 177 00:10:23,920 --> 00:10:29,600 Speaker 1: effect of uncontrolled inflation on consumers purchasing power, it's uh, 178 00:10:29,640 --> 00:10:32,760 Speaker 1: it's not de preferable. All right, olduman, thank you so 179 00:10:32,880 --> 00:10:34,920 Speaker 1: much for joining us and breaking down some of this 180 00:10:35,200 --> 00:10:39,160 Speaker 1: leading economic indicator data. Otoman also Drum, Senior director of 181 00:10:39,240 --> 00:10:44,640 Speaker 1: Economic Research at the Conference Board. All Right, Matt, here 182 00:10:44,679 --> 00:10:47,280 Speaker 1: you go. You go get your bachelor's of Science and 183 00:10:47,280 --> 00:10:52,400 Speaker 1: mechanical engineering from Berkeley, and then you cross the metaphorical 184 00:10:52,440 --> 00:10:55,520 Speaker 1: street and get your pH d in material science and 185 00:10:55,600 --> 00:10:58,559 Speaker 1: engineering from Stanford. Then what do you do? You go 186 00:10:58,640 --> 00:11:01,439 Speaker 1: to Wall Street. That's what our next guested Interesting Play 187 00:11:01,679 --> 00:11:05,960 Speaker 1: Anchor Crawford, Executive vice president portfolio manager, Fred Alger Asset 188 00:11:06,000 --> 00:11:08,800 Speaker 1: Management Anchored. Thanks so much for joining us. You appreciate 189 00:11:08,880 --> 00:11:11,800 Speaker 1: you taking the time. All right, you've got all these 190 00:11:12,040 --> 00:11:17,440 Speaker 1: engineering degrees. How do you apply that stuff to the markets? Actually, 191 00:11:17,480 --> 00:11:22,240 Speaker 1: I don't. Parents are saying, Oh my goodness, I know 192 00:11:22,360 --> 00:11:25,440 Speaker 1: that is actually what they said. But um, you know, 193 00:11:25,520 --> 00:11:29,000 Speaker 1: I think with engineering, all it is is pattern recognition. 194 00:11:29,040 --> 00:11:30,880 Speaker 1: At the end of the day, what we look for, 195 00:11:31,000 --> 00:11:33,920 Speaker 1: even as investors, is different patterns in the market, different 196 00:11:33,920 --> 00:11:37,600 Speaker 1: patterns and companies and stocks in the numbers. And so 197 00:11:38,120 --> 00:11:40,880 Speaker 1: you really take that learning as an engineer and I'm 198 00:11:40,920 --> 00:11:44,240 Speaker 1: able to apply it to the markets. What are you 199 00:11:44,240 --> 00:11:45,960 Speaker 1: seeing in those markets? Right now. What are the patterns 200 00:11:45,960 --> 00:11:48,440 Speaker 1: you're seeing, because boy, you've got a lot of cross 201 00:11:48,440 --> 00:11:50,200 Speaker 1: currents on there that you have a lot of bricks 202 00:11:50,200 --> 00:11:51,920 Speaker 1: in that wall of worry. Now you get to add 203 00:11:52,160 --> 00:11:54,880 Speaker 1: geopolitical risks. How are you viewing the market right now? 204 00:11:55,760 --> 00:11:58,240 Speaker 1: You know it is the market is actually quite fascinating 205 00:11:58,320 --> 00:12:00,480 Speaker 1: right now in um. You know, we the end of 206 00:12:00,520 --> 00:12:03,320 Speaker 1: COVID and the return of normalism and a return to 207 00:12:03,360 --> 00:12:07,000 Speaker 1: normalization of COVID, at least in the US. We have 208 00:12:07,160 --> 00:12:12,480 Speaker 1: this geopolitical risk that we haven't experienced in three generations. UM. 209 00:12:12,559 --> 00:12:16,400 Speaker 1: We have reverberations of all of these effects on the 210 00:12:16,400 --> 00:12:19,160 Speaker 1: supply chains causing inflation readings that we haven't seen in 211 00:12:19,240 --> 00:12:23,600 Speaker 1: four decades. UM. So there's a lot of different cross currents, 212 00:12:23,600 --> 00:12:26,760 Speaker 1: as you mentioned, in the market right now. However, what 213 00:12:26,800 --> 00:12:30,240 Speaker 1: we're focused on is really understanding what's getting baked in 214 00:12:30,840 --> 00:12:33,360 Speaker 1: and so we are very deep in the numbers for 215 00:12:33,520 --> 00:12:36,880 Speaker 1: each of the businesses that we own, and we we 216 00:12:37,000 --> 00:12:41,040 Speaker 1: probability weight the the effect of our recession for example, 217 00:12:41,240 --> 00:12:44,200 Speaker 1: and UM, well sorry, what was that? What what what's 218 00:12:44,240 --> 00:12:47,840 Speaker 1: your probability of recession? Oh, we don't, we don't. We 219 00:12:47,880 --> 00:12:50,520 Speaker 1: just probability weighted, so we say, if there's a five 220 00:12:50,520 --> 00:12:52,800 Speaker 1: percent probability of a recession, this is where we think 221 00:12:52,840 --> 00:12:55,600 Speaker 1: the bare case will be, or the numbers should go 222 00:12:55,640 --> 00:13:00,160 Speaker 1: to if there's um probability of a recession, and the 223 00:13:00,200 --> 00:13:03,160 Speaker 1: numbers will toggle down right, So we basically can tuggle 224 00:13:03,280 --> 00:13:06,400 Speaker 1: the probability of recession up and down in the numbers. 225 00:13:06,480 --> 00:13:09,600 Speaker 1: And what we found is that really there's some of 226 00:13:09,600 --> 00:13:12,800 Speaker 1: these businesses that we're looking at, especially in the growth sector, 227 00:13:13,200 --> 00:13:18,160 Speaker 1: that have gotten completely sold off over the last three months, 228 00:13:18,679 --> 00:13:21,199 Speaker 1: are trading at free cash flow yields even in a 229 00:13:21,200 --> 00:13:25,200 Speaker 1: more recessionary case, that are quite compelling, especially relative to 230 00:13:25,240 --> 00:13:27,720 Speaker 1: the cash flow yield of the S and P. So 231 00:13:27,960 --> 00:13:31,200 Speaker 1: it is interesting because the market is has very quickly 232 00:13:31,320 --> 00:13:35,160 Speaker 1: baked in a much higher probability of a recessionary case 233 00:13:35,160 --> 00:13:37,400 Speaker 1: scenario because of all these cross currents that we had 234 00:13:37,400 --> 00:13:40,160 Speaker 1: talked about. So, which companies do you think anchor do 235 00:13:40,280 --> 00:13:43,000 Speaker 1: well and even in a recession case, not saying that 236 00:13:43,040 --> 00:13:46,800 Speaker 1: we're having a recession, but if we do, where do 237 00:13:46,800 --> 00:13:50,680 Speaker 1: you want to be? So look, I think I think 238 00:13:50,679 --> 00:13:52,720 Speaker 1: the recession is going to at least in the US 239 00:13:52,960 --> 00:13:55,600 Speaker 1: if if we do have a recession, which I am. 240 00:13:55,640 --> 00:13:57,920 Speaker 1: I am very much on a fense about if we 241 00:13:58,040 --> 00:14:00,240 Speaker 1: see a recession in the US. In part, they because 242 00:14:00,240 --> 00:14:03,280 Speaker 1: the consumer is so incredibly resilient, they have two point 243 00:14:03,320 --> 00:14:06,439 Speaker 1: five trillion dollars of express savings that can be used 244 00:14:06,480 --> 00:14:09,520 Speaker 1: to thwart off the effects of a recession. UM they 245 00:14:09,520 --> 00:14:12,120 Speaker 1: have under leveraged balance sheets still that they can the 246 00:14:12,160 --> 00:14:16,120 Speaker 1: consumer can still lever up. However, if UM, you know, 247 00:14:16,160 --> 00:14:19,120 Speaker 1: there are several very interesting themes in the market right 248 00:14:19,160 --> 00:14:23,600 Speaker 1: now that have duration and have growth aspects that that 249 00:14:23,640 --> 00:14:26,920 Speaker 1: are almost uh not related to the economy and so 250 00:14:27,160 --> 00:14:29,120 Speaker 1: in in big tech, if you look at a company 251 00:14:29,160 --> 00:14:34,000 Speaker 1: like Microsoft, UM you know of that business is they 252 00:14:34,040 --> 00:14:37,080 Speaker 1: have visibility over the next year into the into the revenues, 253 00:14:37,160 --> 00:14:41,080 Speaker 1: and so you know, even in a recessionary case scenario, 254 00:14:41,160 --> 00:14:42,760 Speaker 1: the number is on the on the top and the 255 00:14:42,760 --> 00:14:44,880 Speaker 1: bottom line. I am not going to flex up and 256 00:14:44,920 --> 00:14:47,760 Speaker 1: down all that much, in part because they're really the 257 00:14:47,840 --> 00:14:52,000 Speaker 1: hub of this digital transformation and industrial revolution that we 258 00:14:52,040 --> 00:14:55,200 Speaker 1: are experiencing right now. UM. On the other hand, if 259 00:14:55,200 --> 00:14:57,400 Speaker 1: you look at consumer, we believe that the higher end 260 00:14:57,440 --> 00:15:01,880 Speaker 1: consumer will be also quite resilient and they have a 261 00:15:02,240 --> 00:15:05,240 Speaker 1: great wealth effect that they've experienced from both the market, 262 00:15:05,240 --> 00:15:07,680 Speaker 1: home prices both going up over the last few years, 263 00:15:08,280 --> 00:15:12,720 Speaker 1: and their businesses like Veil Mountain resorts that are trading 264 00:15:12,720 --> 00:15:14,760 Speaker 1: at five and six percent free cash full yields as 265 00:15:15,000 --> 00:15:17,760 Speaker 1: you look out a couple of years, and we think 266 00:15:17,800 --> 00:15:21,800 Speaker 1: that they will be relatively resilient through through UM a 267 00:15:21,920 --> 00:15:25,440 Speaker 1: slowdown in the economy. Anchor energy has had a nice 268 00:15:25,520 --> 00:15:27,840 Speaker 1: run here got oil north of a hundred dollars a 269 00:15:27,880 --> 00:15:32,040 Speaker 1: barrel w T I has that trade played out? Has 270 00:15:32,080 --> 00:15:33,960 Speaker 1: which trade played out? Kind of the energy trade just 271 00:15:34,040 --> 00:15:37,160 Speaker 1: kind of being long energy? You know what? I think? 272 00:15:37,920 --> 00:15:41,800 Speaker 1: I think we're not going back to energy and stock 273 00:15:41,880 --> 00:15:45,520 Speaker 1: prices where they were at thirty dollars of barrel um 274 00:15:45,560 --> 00:15:49,480 Speaker 1: in part because of like people are realizing that the 275 00:15:49,480 --> 00:15:54,640 Speaker 1: there's this very strategic aspect to oil and UM. But 276 00:15:54,800 --> 00:15:57,080 Speaker 1: has it played out? I think I think it has 277 00:15:57,400 --> 00:15:59,960 Speaker 1: and in part the global economies will start to slow 278 00:16:00,800 --> 00:16:03,960 Speaker 1: UM and demand for for oil will will decline and 279 00:16:04,040 --> 00:16:07,640 Speaker 1: so UM. You know, I do I do think that 280 00:16:07,680 --> 00:16:11,440 Speaker 1: it has mostly played out. That said, I do think 281 00:16:11,480 --> 00:16:16,280 Speaker 1: that oil stays higher for longer UM and maybe not 282 00:16:16,360 --> 00:16:19,320 Speaker 1: at one forty where it got to at its peak, 283 00:16:20,040 --> 00:16:22,360 Speaker 1: but could it could it stay at eighty bucks for 284 00:16:22,400 --> 00:16:24,840 Speaker 1: a long time it could. All right, uncle, thank you 285 00:16:24,880 --> 00:16:27,920 Speaker 1: so much for joining us. Really appreciate you taking the time. 286 00:16:27,920 --> 00:16:31,040 Speaker 1: And Court Crawford, e v P and portfolio manager for 287 00:16:31,040 --> 00:16:39,320 Speaker 1: Fred Alger Management. Let's talk space. Let's talk satellites. I 288 00:16:39,320 --> 00:16:41,400 Speaker 1: mean you can see basically what the satellites we have 289 00:16:41,440 --> 00:16:44,920 Speaker 1: in the air these days. You can see just about anything. 290 00:16:44,920 --> 00:16:47,680 Speaker 1: You can get a picture of just about anything. Peter Platts, 291 00:16:47,760 --> 00:16:51,840 Speaker 1: or CEO of Spire, joins us. Spire is a publicly 292 00:16:51,880 --> 00:16:54,800 Speaker 1: traded company went public via a spack it looks like 293 00:16:54,880 --> 00:17:00,160 Speaker 1: back in UM. Yeah, they offered twenty three million is 294 00:17:00,200 --> 00:17:02,440 Speaker 1: at ten dollars via my good friends of credits. Sweet. 295 00:17:02,560 --> 00:17:04,840 Speaker 1: All right, Peter, talk to us about Spire. Give us 296 00:17:04,840 --> 00:17:07,520 Speaker 1: the thirty second elevator pitch. What inspire? What are you 297 00:17:07,520 --> 00:17:11,560 Speaker 1: guys up to these days? Absolutely appitude. We are a 298 00:17:11,680 --> 00:17:15,800 Speaker 1: data and analytics company and we're leveraging space to solve 299 00:17:15,960 --> 00:17:20,080 Speaker 1: business and e s G challenges for companies, countries and 300 00:17:20,160 --> 00:17:24,320 Speaker 1: communities all across the world. We are We designed and 301 00:17:24,480 --> 00:17:28,840 Speaker 1: launched and owned and operate the world's largest radio frequency 302 00:17:28,880 --> 00:17:32,960 Speaker 1: based UM satellite constellation to observe the Earth. You know, 303 00:17:33,040 --> 00:17:36,760 Speaker 1: we track some seventeen trillion dollars of global trade, the 304 00:17:37,240 --> 00:17:41,120 Speaker 1: two trillion dollar aviation industry, and the weather all across 305 00:17:41,160 --> 00:17:45,560 Speaker 1: the globe, which you also predict up to ten days out. Um. 306 00:17:45,880 --> 00:17:47,679 Speaker 1: And as you as well know that whether it is 307 00:17:47,720 --> 00:17:50,679 Speaker 1: impacting you know, at least twenty five trillion of global 308 00:17:50,720 --> 00:17:54,600 Speaker 1: GDP in with climate change that is just getting more extreme, 309 00:17:54,680 --> 00:17:57,680 Speaker 1: you know, almost every single week. I want to say, um, 310 00:17:58,359 --> 00:18:06,080 Speaker 1: we serve do you watch this war? Yes, we do, UM. 311 00:18:06,320 --> 00:18:08,520 Speaker 1: And you know it is with data and insights from 312 00:18:08,600 --> 00:18:13,439 Speaker 1: space that the truth and transparency can be shed on 313 00:18:13,600 --> 00:18:15,920 Speaker 1: on such a global conflict. And I think we have 314 00:18:16,040 --> 00:18:19,879 Speaker 1: been witnessing this really firsthand um as it relates to 315 00:18:19,920 --> 00:18:23,280 Speaker 1: the situation in the Ukraine right now, UM, with with 316 00:18:23,359 --> 00:18:27,399 Speaker 1: commercial companies like a spire really bringing that data and 317 00:18:27,480 --> 00:18:31,520 Speaker 1: transparency to the world. UM. You know, our data has 318 00:18:31,560 --> 00:18:34,719 Speaker 1: been used by humanitarian efforts, you know, by the media 319 00:18:34,840 --> 00:18:38,960 Speaker 1: to bring that that knowledge and transparency as well as 320 00:18:38,960 --> 00:18:40,920 Speaker 1: some other areas as I'm sure you can you can 321 00:18:40,960 --> 00:18:46,440 Speaker 1: probably imagine and really being able to participate, um, helping 322 00:18:46,600 --> 00:18:50,640 Speaker 1: people and humanity in you know, this particular situation as 323 00:18:50,640 --> 00:18:54,520 Speaker 1: a European is uh, like I'm I'm from Austria is 324 00:18:54,520 --> 00:18:58,080 Speaker 1: something that is very very meaningful to me personally, so Peter. 325 00:18:58,280 --> 00:19:00,680 Speaker 1: The supply chain, global supply chains, but a big, big 326 00:19:00,720 --> 00:19:04,240 Speaker 1: issue for the world's economies. It's a global story. People 327 00:19:04,240 --> 00:19:06,000 Speaker 1: are always trying to figure out where are the ships, 328 00:19:06,040 --> 00:19:09,600 Speaker 1: where the trucks, where the trains? Um, how have you 329 00:19:09,680 --> 00:19:13,160 Speaker 1: kind of taken a look at that side of the business. 330 00:19:13,160 --> 00:19:15,400 Speaker 1: So supply chain is a is a very very nice 331 00:19:15,440 --> 00:19:19,800 Speaker 1: industry for us UM from a customer perspective. UM we 332 00:19:20,080 --> 00:19:23,680 Speaker 1: track all of the world ships, where they are, where 333 00:19:23,680 --> 00:19:26,240 Speaker 1: they're going, what they're doing, how fast they are, where 334 00:19:26,240 --> 00:19:29,800 Speaker 1: they will arrive, why they will arrive, as well as 335 00:19:30,359 --> 00:19:34,000 Speaker 1: the planes. And then as you imagine, once you are 336 00:19:34,119 --> 00:19:38,800 Speaker 1: on land and transportation happens in trucks, then whether it 337 00:19:38,880 --> 00:19:42,520 Speaker 1: has a massive impact on on potential disruptions there and 338 00:19:42,560 --> 00:19:45,560 Speaker 1: so everything from uh you know, the blocking of the 339 00:19:45,600 --> 00:19:48,560 Speaker 1: Suez Canal and the and the ripple effects all across 340 00:19:48,600 --> 00:19:51,399 Speaker 1: the world on the ports um to you know, just 341 00:19:51,440 --> 00:19:54,880 Speaker 1: today we put out a little story about the shutting 342 00:19:54,880 --> 00:19:57,560 Speaker 1: down of of Shenzen. You know, we have been able 343 00:19:57,640 --> 00:20:01,639 Speaker 1: to to monitor those activities and then help our customers, 344 00:20:01,960 --> 00:20:06,159 Speaker 1: uh preempt them and know what to do based on 345 00:20:06,240 --> 00:20:08,320 Speaker 1: what is happening and how they can get a bit 346 00:20:08,359 --> 00:20:11,320 Speaker 1: of a leg up in their own supply chain management, 347 00:20:11,680 --> 00:20:13,880 Speaker 1: and then their understanding of what is happening to their 348 00:20:13,920 --> 00:20:16,760 Speaker 1: own supply chain based on the data and analytics that 349 00:20:16,800 --> 00:20:21,720 Speaker 1: we can provide them. In terms of UM, your company, 350 00:20:21,800 --> 00:20:27,240 Speaker 1: your stock has come down pretty substantially over the last 351 00:20:27,720 --> 00:20:32,600 Speaker 1: I guess six months. What's going on there? You know, honestly, 352 00:20:32,640 --> 00:20:35,240 Speaker 1: if if if I could predict the understand the market 353 00:20:35,280 --> 00:20:38,199 Speaker 1: with great certainty, I'll probably spent more time in Vegas 354 00:20:38,200 --> 00:20:41,280 Speaker 1: and rather than helping our customers. But I think I 355 00:20:41,320 --> 00:20:43,600 Speaker 1: think there's there's probably a number of elements. You know. 356 00:20:43,680 --> 00:20:45,760 Speaker 1: One of them is certainly that we are in a 357 00:20:45,880 --> 00:20:49,879 Speaker 1: in a very very risk off environment. I spent I 358 00:20:49,960 --> 00:20:52,639 Speaker 1: spent ten years and LASS so there's a quantitative investment 359 00:20:52,680 --> 00:20:57,480 Speaker 1: manager UMH in longer term trading. And certainly when you 360 00:20:57,600 --> 00:21:02,880 Speaker 1: have situations like uh a geopolitical crisis in Europe, when 361 00:21:02,920 --> 00:21:06,480 Speaker 1: you have a situation like a pandemic UM but then 362 00:21:06,640 --> 00:21:09,679 Speaker 1: at risk of indust rates rising, UM, you know, you 363 00:21:09,760 --> 00:21:12,280 Speaker 1: have a you have a very risk off environment that 364 00:21:12,440 --> 00:21:16,960 Speaker 1: has been you know, very negative for high growth companies UM. 365 00:21:17,000 --> 00:21:19,480 Speaker 1: I think additionally you know, the the products that we 366 00:21:19,600 --> 00:21:23,680 Speaker 1: have serve industries that are vast and large, but they're 367 00:21:23,760 --> 00:21:26,640 Speaker 1: not you know, top of mind for people. I mean 368 00:21:26,680 --> 00:21:29,600 Speaker 1: you started off by talking about the pictures that you 369 00:21:29,600 --> 00:21:32,680 Speaker 1: can get from satellites, but the data that we do 370 00:21:32,800 --> 00:21:36,720 Speaker 1: that cover, for example, you know, four hundred billion dollar 371 00:21:37,040 --> 00:21:40,560 Speaker 1: fishing industry, that's just not as much top of mind, 372 00:21:41,000 --> 00:21:42,520 Speaker 1: and I think I need to do a better job 373 00:21:42,600 --> 00:21:45,360 Speaker 1: in bringing that to life with people. Well, and what's 374 00:21:45,400 --> 00:21:48,119 Speaker 1: the growth outlook, I mean, what kind of revenues are 375 00:21:48,119 --> 00:21:50,760 Speaker 1: you expecting, say this year, and and what the margins 376 00:21:50,760 --> 00:21:53,560 Speaker 1: look like. Yes, so we you know, we had a 377 00:21:54,520 --> 00:21:57,720 Speaker 1: very very strong finish to the year. We exceeded guidance 378 00:21:58,240 --> 00:22:01,560 Speaker 1: both on the UH hop line and bottom line elements 379 00:22:01,600 --> 00:22:04,080 Speaker 1: a region, the very top of it UM fourth quote 380 00:22:04,119 --> 00:22:07,000 Speaker 1: of revenue was fifteen million, up a hundred and six 381 00:22:07,040 --> 00:22:10,840 Speaker 1: percent year of a year UM. We reached seventy one 382 00:22:10,880 --> 00:22:14,320 Speaker 1: million almost of annually recurring revenue, which was in ninety 383 00:22:14,400 --> 00:22:17,800 Speaker 1: six percent year of a year increase. UM guidance for 384 00:22:17,880 --> 00:22:20,320 Speaker 1: this year on the revenue side is eighty five to 385 00:22:20,440 --> 00:22:22,879 Speaker 1: ninety million of revenue, which is a year of a 386 00:22:22,960 --> 00:22:26,560 Speaker 1: year growth rate of over a hundred percent at the midpoint, 387 00:22:26,960 --> 00:22:31,600 Speaker 1: so growth is really really phenomenal. Um, we see the 388 00:22:31,680 --> 00:22:35,440 Speaker 1: demand in every single one off our segments. We see 389 00:22:35,440 --> 00:22:38,560 Speaker 1: it in the h the maritime, the aviation, the weather, 390 00:22:38,920 --> 00:22:41,920 Speaker 1: as well as the space services segment, and we continue 391 00:22:41,960 --> 00:22:46,840 Speaker 1: to drive, you know, very very aggressively to profitability despite 392 00:22:47,000 --> 00:22:49,639 Speaker 1: that high growth rate. He Peter, thanks so much for 393 00:22:49,680 --> 00:22:52,560 Speaker 1: joining us. Really interesting company. Peter Platts or CEO of 394 00:22:52,680 --> 00:22:55,320 Speaker 1: Spire again that trades on the New York Sock Exchange 395 00:22:55,520 --> 00:23:01,320 Speaker 1: sp i R. Thanks for listening to the bloom Markets podcast. 396 00:23:01,720 --> 00:23:04,920 Speaker 1: You can subscribe and listen to interviews with Apple Podcasts 397 00:23:05,080 --> 00:23:08,960 Speaker 1: or whatever podcast platform you prefer. I'm Matt Miller. I'm 398 00:23:09,000 --> 00:23:13,200 Speaker 1: on Twitter at Matt Miller and on Fall Sweeney I'm 399 00:23:13,200 --> 00:23:15,840 Speaker 1: on Twitter at pt Sweeney. Before the podcast. You can 400 00:23:15,880 --> 00:23:18,120 Speaker 1: always catch us worldwide at Bloomberg Radio.