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 00:00:11,520 --> 00:00:15,560 Speaker 1: with essential market moving news. Find the Bloomberg Markets Podcast 5 00:00:15,600 --> 00:00:18,439 Speaker 1: on Apple Podcasts or wherever you listen to podcasts, and 6 00:00:18,480 --> 00:00:23,239 Speaker 1: at Bloomberg dot com slash podcast. Matt was just calling 7 00:00:23,280 --> 00:00:26,360 Speaker 1: out here in an I end screen the Bloomberg Index 8 00:00:26,400 --> 00:00:32,000 Speaker 1: browser Bloomberg US corporate total return value year to date 9 00:00:32,720 --> 00:00:37,560 Speaker 1: minus fourteen points six treasuries to minus fourteen point eight. 10 00:00:37,880 --> 00:00:40,960 Speaker 1: I mean, what's going on? And that does inlets total 11 00:00:41,000 --> 00:00:44,080 Speaker 1: return So not that it would have mattered because the 12 00:00:44,080 --> 00:00:49,040 Speaker 1: coupons are so low. Yes, um, but it's harsh. And look, 13 00:00:49,080 --> 00:00:54,440 Speaker 1: my mom and dad just retired this like month, and uh, 14 00:00:54,480 --> 00:00:56,720 Speaker 1: I feel for them. I guess I'm gonna have to 15 00:00:56,760 --> 00:01:01,160 Speaker 1: step up because they're broke now, you know, all right, 16 00:01:01,160 --> 00:01:03,760 Speaker 1: Liz McCormick, Global Fixed Income and far In Exchange reporter 17 00:01:03,880 --> 00:01:06,280 Speaker 1: joins us live here in a Bloomberg and after Broker studio. 18 00:01:06,360 --> 00:01:10,640 Speaker 1: So Liz, again, these are numbers, these are performance numbers. 19 00:01:11,120 --> 00:01:13,200 Speaker 1: You know your friends in the fixed income market have 20 00:01:13,800 --> 00:01:16,600 Speaker 1: ever seen, never seen. Yeah, I mean some of the 21 00:01:16,680 --> 00:01:19,000 Speaker 1: data how you splice and dice it is like at 22 00:01:19,040 --> 00:01:21,920 Speaker 1: least the worst first half and kind of modern times 23 00:01:22,000 --> 00:01:24,280 Speaker 1: call it. I was mentioning to Matt that Deutsche Bank 24 00:01:24,400 --> 00:01:26,920 Speaker 1: had some great data back to the seventeen hundreds, like 25 00:01:26,959 --> 00:01:29,560 Speaker 1: how bad it was. I mean, people just aren't Most 26 00:01:29,640 --> 00:01:32,319 Speaker 1: people aren't used to this kind of beating up in bonds. 27 00:01:33,760 --> 00:01:36,000 Speaker 1: I mean, do people in fixtion come to they try 28 00:01:36,040 --> 00:01:40,080 Speaker 1: to call the bottom, like we hear equity trying to 29 00:01:40,120 --> 00:01:42,920 Speaker 1: call the Yeah. And this is where I feel like 30 00:01:43,880 --> 00:01:46,200 Speaker 1: I see the same dichotomy going on as you guys 31 00:01:46,240 --> 00:01:48,880 Speaker 1: are talking all about in stocks. You know, is this 32 00:01:49,000 --> 00:01:52,200 Speaker 1: like a bear rally? Is it over? The same thing 33 00:01:52,240 --> 00:01:55,640 Speaker 1: in bonds? People saying, oh, we've seen the peak and yields, 34 00:01:55,800 --> 00:01:59,640 Speaker 1: you know, all the FED pricing for hikes is in there. 35 00:01:59,760 --> 00:02:03,120 Speaker 1: The worst is over. And then other people saying, wait 36 00:02:03,160 --> 00:02:05,280 Speaker 1: a minute. You know, like three point five on the 37 00:02:05,320 --> 00:02:08,200 Speaker 1: tenure was the highest we've seen. But like listen, you know, 38 00:02:08,320 --> 00:02:10,079 Speaker 1: I've been around for a while. Like the folks of 39 00:02:10,120 --> 00:02:12,440 Speaker 1: Bridgewater said to me a few times, we think rates 40 00:02:12,440 --> 00:02:14,160 Speaker 1: can go a lot higher. Ten years, could go to 41 00:02:14,240 --> 00:02:16,520 Speaker 1: four percent or more. You know, FED has just got 42 00:02:16,520 --> 00:02:18,880 Speaker 1: a lot more tightening to do. So there is these battles, 43 00:02:18,919 --> 00:02:22,079 Speaker 1: I think in both asset classes. You know, we'll see 44 00:02:22,080 --> 00:02:24,600 Speaker 1: who wins in the end, right, maybe next year or sometime. 45 00:02:24,880 --> 00:02:28,400 Speaker 1: I met a guy over the weekend, eighty three years old, 46 00:02:28,400 --> 00:02:31,920 Speaker 1: fascinating guy, and he watches and listens to us every day. 47 00:02:32,240 --> 00:02:35,840 Speaker 1: He trades bonds every night. So at the end of 48 00:02:35,840 --> 00:02:37,880 Speaker 1: the day he'll make a trade, put on a position, 49 00:02:37,919 --> 00:02:41,720 Speaker 1: and then the next day. No one nobody does that, right, 50 00:02:42,000 --> 00:02:44,160 Speaker 1: nobody does that. My father, who I've been doing this 51 00:02:44,240 --> 00:02:46,560 Speaker 1: for so long, still says to me, can you explain 52 00:02:46,560 --> 00:02:48,360 Speaker 1: to me again what a bond is? You know what 53 00:02:48,400 --> 00:02:51,120 Speaker 1: I mean? All the bond traders I know, all the 54 00:02:51,160 --> 00:02:53,320 Speaker 1: guys I know who worked in firms on the street 55 00:02:53,400 --> 00:02:57,280 Speaker 1: have long since retired or quit, right exactly. I remember 56 00:02:57,360 --> 00:02:59,800 Speaker 1: my old boss, Ward McCarthy saying, years back when there 57 00:02:59,880 --> 00:03:03,239 Speaker 1: was yield, saying, I bought you know, zero coupons ages 58 00:03:03,280 --> 00:03:05,160 Speaker 1: ago and that put my kids through college, you know, 59 00:03:05,240 --> 00:03:07,160 Speaker 1: like it used to be such great rates and those 60 00:03:07,160 --> 00:03:10,000 Speaker 1: are just gone. Well. Actually, Scott Miner did say he's 61 00:03:10,040 --> 00:03:15,040 Speaker 1: buying the strips right twenty years, which is um kind 62 00:03:15,080 --> 00:03:17,800 Speaker 1: of jargony. But I guess that's when you strip out 63 00:03:17,960 --> 00:03:21,840 Speaker 1: the coupon, you can trade the maturities and then you 64 00:03:21,880 --> 00:03:24,520 Speaker 1: can also trade the each due date of the coupon. 65 00:03:24,560 --> 00:03:26,640 Speaker 1: It's like a bullet, you know, it's it's just like 66 00:03:26,680 --> 00:03:29,400 Speaker 1: a single coupon in a sense, just what you get 67 00:03:29,440 --> 00:03:31,600 Speaker 1: at the end. But yeah, they're stripping and I saw that, 68 00:03:31,680 --> 00:03:33,679 Speaker 1: and we'll see. I mean, if we're in this era 69 00:03:33,760 --> 00:03:35,800 Speaker 1: that we're never going to get rates too high again, 70 00:03:35,840 --> 00:03:38,840 Speaker 1: which I'm not sure I buy into yet. People who 71 00:03:39,080 --> 00:03:42,800 Speaker 1: bought strips are locked in tansit over three percent are 72 00:03:42,840 --> 00:03:45,080 Speaker 1: going to be pretty happy if you know here we are. 73 00:03:45,160 --> 00:03:46,920 Speaker 1: You know, in a couple of years, the Feds fighting 74 00:03:46,920 --> 00:03:50,040 Speaker 1: in a recession cutting rates again. Is that, by the way, 75 00:03:50,160 --> 00:03:53,360 Speaker 1: kind of a consensus that the Fed is gonna raise 76 00:03:53,480 --> 00:03:56,600 Speaker 1: rates high enough to fight inflation because they now they 77 00:03:56,680 --> 00:04:00,280 Speaker 1: have to. That's they're locked in. And not only is 78 00:04:00,280 --> 00:04:02,920 Speaker 1: it one of their actual mandates, but and then we're 79 00:04:02,920 --> 00:04:05,000 Speaker 1: gonna have a recession in three and they're gonna have 80 00:04:05,000 --> 00:04:07,119 Speaker 1: to cut right back down again. Well, I would say, 81 00:04:07,160 --> 00:04:09,880 Speaker 1: like the timing of the recession gets nebulous. A lot 82 00:04:09,880 --> 00:04:12,920 Speaker 1: of people say late I've heard a few say maybe 83 00:04:13,040 --> 00:04:16,760 Speaker 1: there's enough cash in the system. Corporations are much better 84 00:04:16,800 --> 00:04:19,920 Speaker 1: it could be. But I think in general, Matt, you're 85 00:04:20,040 --> 00:04:24,200 Speaker 1: right that it's fast, up front loaded quick, and then 86 00:04:24,440 --> 00:04:26,800 Speaker 1: the FED is going to have to eventually not too 87 00:04:26,839 --> 00:04:30,000 Speaker 1: long be cutting rates again because they're trying to manage. 88 00:04:30,480 --> 00:04:32,560 Speaker 1: And like Pal said, he's gone from you know, like 89 00:04:32,960 --> 00:04:35,840 Speaker 1: soft landing soft dish to saying, well, you know, we 90 00:04:36,160 --> 00:04:38,760 Speaker 1: could have a slowd You know, he's trying, but you know, 91 00:04:38,839 --> 00:04:40,920 Speaker 1: you raise rates this fast. And I know there's not 92 00:04:40,960 --> 00:04:43,359 Speaker 1: a lot of floating rate debt out there, but I 93 00:04:43,440 --> 00:04:45,840 Speaker 1: have a home equity line of credit and I was like, oh, 94 00:04:46,000 --> 00:04:48,400 Speaker 1: they raised that rate pretty darned fast, you know, to me. 95 00:04:48,520 --> 00:04:52,960 Speaker 1: So not only that, um Joel Levington wrote a piece 96 00:04:53,040 --> 00:04:56,720 Speaker 1: about the automakers. Now they're facing a one hundred and 97 00:04:56,760 --> 00:05:01,080 Speaker 1: forty five billion dollar wall of debt and it's not like, uh, 98 00:05:01,160 --> 00:05:04,320 Speaker 1: you know, they can just hold it right, They're they're 99 00:05:04,320 --> 00:05:07,080 Speaker 1: constantly rolling over. So now they're going to look at 100 00:05:07,160 --> 00:05:11,279 Speaker 1: two d fifty three hundred basis points of increased costs. This, 101 00:05:11,360 --> 00:05:13,640 Speaker 1: by the way, adds to inflation because they've got to 102 00:05:13,680 --> 00:05:17,159 Speaker 1: pass that along to the customer. But Uh, it's it's 103 00:05:17,200 --> 00:05:19,919 Speaker 1: tough for for companies as well. Yeah, I think everyone 104 00:05:19,960 --> 00:05:22,600 Speaker 1: you're going to feel this very quickly. Now. The Fed said, 105 00:05:22,600 --> 00:05:26,120 Speaker 1: we're really watching financial conditions, which is kind of nebulous. 106 00:05:26,279 --> 00:05:28,400 Speaker 1: You know, how tight do they have to get? You know, 107 00:05:28,480 --> 00:05:30,760 Speaker 1: not just what's the hard rate the Fed funds has 108 00:05:30,800 --> 00:05:32,680 Speaker 1: to get to, but that's what they're watching. How does 109 00:05:32,720 --> 00:05:35,360 Speaker 1: this filter through? Look at mortgage rates over six percent? 110 00:05:35,480 --> 00:05:37,560 Speaker 1: You know, they seem like so low for so long. 111 00:05:37,600 --> 00:05:40,440 Speaker 1: The housing market hasn't imploded yet, but for once, not 112 00:05:40,520 --> 00:05:42,559 Speaker 1: that I'm looking to buy, but you see on Zeala 113 00:05:42,640 --> 00:05:45,960 Speaker 1: finally price reduction. We didn't see that forever, So I 114 00:05:46,000 --> 00:05:48,520 Speaker 1: think it's gonna sale. I know people who wanted to 115 00:05:48,560 --> 00:05:51,360 Speaker 1: sell and now they can't, so they got to rent. Yeah, well, 116 00:05:51,800 --> 00:05:54,159 Speaker 1: you know what, rents are crazy right, going up in price, 117 00:05:54,240 --> 00:05:57,000 Speaker 1: the you know, leases up. I've heard so many people complaining, 118 00:05:57,000 --> 00:06:00,320 Speaker 1: oh the language putting up my rent is too damn high. 119 00:06:00,800 --> 00:06:02,640 Speaker 1: The rent is too damn hon So if you move, 120 00:06:02,800 --> 00:06:04,760 Speaker 1: is that another reason to move to Austin, Texas? Or 121 00:06:05,240 --> 00:06:07,640 Speaker 1: I don't think pricing is good in Austin time. I 122 00:06:07,680 --> 00:06:09,240 Speaker 1: don't think it is either, especially you don't get a 123 00:06:09,279 --> 00:06:11,080 Speaker 1: special rates because it's Texas. So where do you have 124 00:06:11,120 --> 00:06:13,719 Speaker 1: to go? What we could go Columbus, Ohio. It's a 125 00:06:13,760 --> 00:06:16,280 Speaker 1: great place to live in, very affordable and people are 126 00:06:16,320 --> 00:06:21,720 Speaker 1: just wonderful and no accent, so it's the only place 127 00:06:21,720 --> 00:06:24,400 Speaker 1: in the country where there's absolutely no regional accents. They 128 00:06:24,480 --> 00:06:26,400 Speaker 1: use people from the great state of Ohio often for 129 00:06:26,440 --> 00:06:31,320 Speaker 1: newscasters and Matt Miller case in point. All right, Liz McCormack, 130 00:06:31,320 --> 00:06:33,479 Speaker 1: thanks so much for joining us. Lis mccormer. She covers 131 00:06:33,560 --> 00:06:36,560 Speaker 1: all things global fixed income, foreign exchange reporter. She does 132 00:06:36,600 --> 00:06:40,800 Speaker 1: it all for Bloomberg News, and most important, she is 133 00:06:40,880 --> 00:06:44,040 Speaker 1: in the Bloomberg Interactor Broker studio today, So we appreciate that. 134 00:06:49,520 --> 00:06:53,720 Speaker 1: Matt Our next guest is all in the state of Wisconsin. 135 00:06:53,800 --> 00:06:57,080 Speaker 1: PhD in Economics from the University of Wisconsin Milwaukee, j 136 00:06:57,279 --> 00:07:00,760 Speaker 1: d from Marquette, and an undergrad and finance from the 137 00:07:00,839 --> 00:07:03,279 Speaker 1: University of Wisconsin and Madison. We're gonna get this guy 138 00:07:03,320 --> 00:07:05,000 Speaker 1: out of state once in a while. I mean, he's 139 00:07:05,080 --> 00:07:08,320 Speaker 1: all in. It's also part time instructor at Marquette. Uh 140 00:07:08,520 --> 00:07:12,760 Speaker 1: DR Brian Jakebison's senior investment strategist Offspring Global investments. So, Brian, 141 00:07:12,760 --> 00:07:16,280 Speaker 1: you don't mind the winters in Wisconsin, you know what 142 00:07:16,280 --> 00:07:19,280 Speaker 1: I mean? Life is all about trade off. I guess 143 00:07:19,280 --> 00:07:21,280 Speaker 1: that's just the tradeoff you have to make for living 144 00:07:21,280 --> 00:07:24,360 Speaker 1: in the land of milk and honey, or I guess 145 00:07:24,560 --> 00:07:28,760 Speaker 1: milk and sausage or milk and cheese. I wish this 146 00:07:28,880 --> 00:07:31,200 Speaker 1: market was all about trade offs. Yes, it seems like 147 00:07:31,280 --> 00:07:33,400 Speaker 1: no matter what you own, your down I mean, I 148 00:07:33,400 --> 00:07:35,720 Speaker 1: guess if you if you if you just had oil modity, 149 00:07:35,800 --> 00:07:39,640 Speaker 1: if you have some commodities, you're okay. So, Brian, you know, 150 00:07:39,720 --> 00:07:42,280 Speaker 1: one of the things that people start talking about, well, 151 00:07:42,320 --> 00:07:43,760 Speaker 1: maybe I'm we're just hearing a little bit more of 152 00:07:43,800 --> 00:07:46,600 Speaker 1: the last few weeks is trying to find a bottom, 153 00:07:47,200 --> 00:07:50,320 Speaker 1: uh in these markets? Is that an exercise you go through? 154 00:07:50,400 --> 00:07:52,000 Speaker 1: And if so, kind of what do you look for? 155 00:07:52,880 --> 00:07:56,200 Speaker 1: How are you trading this market here? Well? You know, 156 00:07:56,440 --> 00:07:59,160 Speaker 1: sometimes it feels like my workouts, you know, an exercise 157 00:07:59,200 --> 00:08:02,600 Speaker 1: and utility. Um. And I think that, you know, trying 158 00:08:02,600 --> 00:08:04,520 Speaker 1: to find the bottom is always going to be difficult 159 00:08:04,560 --> 00:08:08,040 Speaker 1: because the market seems to be there to frustrate the 160 00:08:08,160 --> 00:08:13,080 Speaker 1: expectations and ambitions of everybody. Um. But it does feel 161 00:08:13,080 --> 00:08:15,440 Speaker 1: like we're trying to find a bottom, and since you 162 00:08:15,480 --> 00:08:17,920 Speaker 1: know we can't pick one, we just have to I think, 163 00:08:18,000 --> 00:08:21,800 Speaker 1: take a look at the broad thrust of the market, 164 00:08:22,160 --> 00:08:25,160 Speaker 1: and it seems like some of the indicators are suggesting 165 00:08:25,200 --> 00:08:29,680 Speaker 1: we're trying to find one here. Now who knows is 166 00:08:27,160 --> 00:08:31,520 Speaker 1: it is it even lower than that? But all we 167 00:08:31,560 --> 00:08:34,440 Speaker 1: know is that things look cheaper now than what they 168 00:08:34,440 --> 00:08:37,400 Speaker 1: did back in u on January three, when we're at 169 00:08:37,400 --> 00:08:39,520 Speaker 1: the peak. And so I think for longer term investors, 170 00:08:39,559 --> 00:08:42,080 Speaker 1: for that kind of structural part of your portfolio, the 171 00:08:42,120 --> 00:08:45,000 Speaker 1: strategic part um, that does suggest to us that there's 172 00:08:45,000 --> 00:08:47,760 Speaker 1: some long term opportunities even if there could be some 173 00:08:47,840 --> 00:08:50,720 Speaker 1: short term pain here. It's all about those trade offs, right, 174 00:08:50,800 --> 00:08:53,160 Speaker 1: that long term gain maybe a little bit more short 175 00:08:53,280 --> 00:08:56,160 Speaker 1: term pain. Do you go h do you go in 176 00:08:56,200 --> 00:09:00,760 Speaker 1: for the traditional defensive um? You know, can't imagine you're 177 00:09:00,800 --> 00:09:09,520 Speaker 1: buying utilities but consumer staples or healthcare? Healthcare? Yeah? You know. 178 00:09:09,800 --> 00:09:13,319 Speaker 1: So we just published are the all Spring mid year 179 00:09:13,440 --> 00:09:16,600 Speaker 1: Outlook and the theme was rolling with change, and I 180 00:09:16,640 --> 00:09:19,600 Speaker 1: think that what is defensive now you need to really 181 00:09:19,640 --> 00:09:21,880 Speaker 1: kind of change the way you think about it because 182 00:09:21,880 --> 00:09:24,920 Speaker 1: of that interest rate sensitivity, Right, utilities do tend to 183 00:09:24,920 --> 00:09:27,840 Speaker 1: be much more interest rate sensitive than say, consumer staples. 184 00:09:28,200 --> 00:09:31,360 Speaker 1: Both are traditionally viewed as being more defensive. It's just 185 00:09:31,520 --> 00:09:35,680 Speaker 1: one has a higher loading on rate risk than the other. 186 00:09:35,720 --> 00:09:39,720 Speaker 1: And so actually we are overweight consumer staples as somewhat 187 00:09:39,760 --> 00:09:44,320 Speaker 1: of uh not necessarily a barish view, but as a 188 00:09:44,480 --> 00:09:47,520 Speaker 1: bit more of a defensive view on the markets, at 189 00:09:47,600 --> 00:09:49,680 Speaker 1: least here in the short term. I do have to say, though, 190 00:09:49,880 --> 00:09:53,760 Speaker 1: we are warming up to areas like financials or home builders, 191 00:09:53,800 --> 00:09:57,560 Speaker 1: those parts that have sold off pretty substantially here or 192 00:09:57,600 --> 00:10:01,840 Speaker 1: haven't performed as you would have expected just given the 193 00:10:01,840 --> 00:10:06,600 Speaker 1: FEDS change and stamps. You know, looking at this upcoming 194 00:10:06,679 --> 00:10:09,439 Speaker 1: earning season, so I think July fifteen fishes when it 195 00:10:09,520 --> 00:10:12,920 Speaker 1: kicks off. You know, we look at inflation x food 196 00:10:12,960 --> 00:10:17,320 Speaker 1: and energy, Well, what's earnings x energy um is possible 197 00:10:17,360 --> 00:10:19,600 Speaker 1: that it would be a negative three You're a year 198 00:10:19,760 --> 00:10:22,280 Speaker 1: just excluding that one sector. So you know that it 199 00:10:22,280 --> 00:10:24,400 Speaker 1: seems like there's a lot of areas that there's some 200 00:10:24,480 --> 00:10:28,640 Speaker 1: decent opportunities if you focus on looking for maybe the 201 00:10:28,640 --> 00:10:30,480 Speaker 1: parts that have been beaten down the most but still 202 00:10:30,520 --> 00:10:33,840 Speaker 1: have decent fundamentals that can pull you through this. Yeah, 203 00:10:33,840 --> 00:10:35,679 Speaker 1: Bron I'm glad you mentioned earnings because we're going to 204 00:10:35,760 --> 00:10:40,160 Speaker 1: switch into that earnings mode very soon. Give us a 205 00:10:40,200 --> 00:10:42,640 Speaker 1: sense of kind of how you're thinking about evaluation for 206 00:10:42,679 --> 00:10:46,079 Speaker 1: these markets. Some people are suggesting that it's obviously a 207 00:10:46,160 --> 00:10:48,200 Speaker 1: lot more tracted than it was at the beginning of 208 00:10:48,200 --> 00:10:51,600 Speaker 1: the year from evaluation perspective, But is it cheap? How 209 00:10:51,600 --> 00:10:53,240 Speaker 1: do you think about that? And no one's really pulled 210 00:10:53,320 --> 00:10:57,600 Speaker 1: earnings forecast down, at least not dramatically. Yeah, that's been 211 00:10:57,760 --> 00:10:59,760 Speaker 1: a puzzling thing as to why we haven't seen the 212 00:10:59,760 --> 00:11:02,360 Speaker 1: ear and forecasts come down. And I think that's why 213 00:11:02,360 --> 00:11:05,120 Speaker 1: people can make the argument that, well, just the price decline, 214 00:11:05,120 --> 00:11:08,319 Speaker 1: it's just that things are cheaper now. The problem is 215 00:11:08,320 --> 00:11:10,880 Speaker 1: is I think the market is saying that the fundamentals 216 00:11:10,880 --> 00:11:14,440 Speaker 1: has also declined. Right, So it's yes, things are cheaper 217 00:11:14,480 --> 00:11:17,160 Speaker 1: based on price, but maybe it's also cheaper based on 218 00:11:17,480 --> 00:11:21,000 Speaker 1: value if the value has declined in tandem. And when 219 00:11:21,000 --> 00:11:23,840 Speaker 1: we like interest rate in just some of your typical 220 00:11:24,080 --> 00:11:28,400 Speaker 1: market multiples, you know, we've seen the pe come down, 221 00:11:28,720 --> 00:11:31,480 Speaker 1: but at the same time, yields have gone up, and 222 00:11:31,520 --> 00:11:33,880 Speaker 1: so it's been almost a bit of a wash from 223 00:11:34,080 --> 00:11:38,440 Speaker 1: the pure market multiple perspective, and as a result, the 224 00:11:38,480 --> 00:11:40,360 Speaker 1: way that we're trying to position things is be a 225 00:11:40,360 --> 00:11:43,520 Speaker 1: little bit more just broadly diversified, and then within each 226 00:11:43,520 --> 00:11:45,920 Speaker 1: one of the sectors, work with some of our tremendous 227 00:11:46,000 --> 00:11:48,720 Speaker 1: teams like and Miletti. She's the head of our fundamental 228 00:11:48,760 --> 00:11:51,560 Speaker 1: equity teams. They're the ones who are trying to identify 229 00:11:51,760 --> 00:11:54,040 Speaker 1: value there. Yeah, and so here it all springs. You know, 230 00:11:54,040 --> 00:11:57,160 Speaker 1: We're very fortunate to have her and her teams here 231 00:11:57,240 --> 00:12:00,720 Speaker 1: to try to identify some of those areas within each 232 00:12:00,760 --> 00:12:04,720 Speaker 1: sector about who might have that quality of earnings to 233 00:12:05,040 --> 00:12:07,360 Speaker 1: kind of cut through some of these cyclical headwinds that 234 00:12:07,440 --> 00:12:09,760 Speaker 1: we might be facing. By the way, Uh, Brian just 235 00:12:09,800 --> 00:12:12,880 Speaker 1: got about thirty seconds here, But I see you like China, 236 00:12:13,040 --> 00:12:14,800 Speaker 1: and it strikes me that they're kind of going in 237 00:12:14,800 --> 00:12:17,080 Speaker 1: the other direction or they haven't, you know, been in 238 00:12:17,120 --> 00:12:20,000 Speaker 1: a situation where inflation is high and they're raising rates. 239 00:12:20,040 --> 00:12:21,880 Speaker 1: They've still got to come out of lockdown. Is that 240 00:12:21,960 --> 00:12:25,000 Speaker 1: kind of a reopening play? It really is. Yeah. I 241 00:12:25,160 --> 00:12:29,080 Speaker 1: think sentiments shifted so much so negatively against them. Who 242 00:12:29,120 --> 00:12:30,960 Speaker 1: knows how long will hold on to it. But we 243 00:12:31,040 --> 00:12:33,360 Speaker 1: do like China road to to the US. They got 244 00:12:33,360 --> 00:12:37,120 Speaker 1: the fiscal impulse, monetary stimulus, and now the reopening. We 245 00:12:37,200 --> 00:12:40,000 Speaker 1: think that could bode well for them. All right, Brian, 246 00:12:40,160 --> 00:12:42,880 Speaker 1: great great stuff. I always appreciate getting some of your 247 00:12:42,880 --> 00:12:46,880 Speaker 1: thoughts here. Dr Brian Jacobson's senior investment strategists off Spring 248 00:12:47,040 --> 00:12:51,120 Speaker 1: Global Investments. Uh, they are all in Wisconsin. I mean, 249 00:12:51,160 --> 00:12:54,560 Speaker 1: I'm talking about it, Marquette, that's a Milwaukee is an 250 00:12:54,679 --> 00:12:57,800 Speaker 1: in Wisconsin is Yeah. They they all started. A lot 251 00:12:57,840 --> 00:13:00,679 Speaker 1: of them started there at Strong Funds, which is a 252 00:13:00,679 --> 00:13:04,200 Speaker 1: big was a big mutual fund out there in suburban Milwaukee. 253 00:13:04,280 --> 00:13:06,720 Speaker 1: It was a must go to visit if you were 254 00:13:06,760 --> 00:13:08,560 Speaker 1: sell side equity analyst. He had to go out se 255 00:13:10,120 --> 00:13:12,240 Speaker 1: a million times, a million times. It's a it's a 256 00:13:12,280 --> 00:13:15,080 Speaker 1: great money town, great money market town. There's lots of 257 00:13:15,679 --> 00:13:21,360 Speaker 1: good folks. They're managing institutional money. Well. When you think 258 00:13:21,400 --> 00:13:25,040 Speaker 1: about one of the great success stories in the US 259 00:13:25,080 --> 00:13:27,560 Speaker 1: in terms of the growth of you know, certain cities, 260 00:13:27,559 --> 00:13:30,400 Speaker 1: certain metroplexes around the country, Atlanta's got to be at 261 00:13:30,400 --> 00:13:32,880 Speaker 1: the top of your list. It's just been such a 262 00:13:32,920 --> 00:13:36,320 Speaker 1: great growth story for so long. So many great companies 263 00:13:36,559 --> 00:13:39,160 Speaker 1: like Delta Airlines and home Depot and so on, and 264 00:13:39,160 --> 00:13:42,040 Speaker 1: so forth, they hosted the Olympics. UH, just a great 265 00:13:42,040 --> 00:13:44,040 Speaker 1: success story. And so of course we need to put 266 00:13:44,080 --> 00:13:46,320 Speaker 1: some numbers around that. And when you want to do that, 267 00:13:46,800 --> 00:13:49,280 Speaker 1: you go to Chinpey a Bloomberg News and Matt Winkler, 268 00:13:49,360 --> 00:13:53,480 Speaker 1: who is editor in chief emeritus and founder of Bloomberg News, 269 00:13:53,600 --> 00:13:55,440 Speaker 1: to kind of put some numbers around that, put some 270 00:13:55,480 --> 00:13:58,439 Speaker 1: context around that. And they certainly have Matt include joint 271 00:13:58,480 --> 00:14:02,319 Speaker 1: us here in our Bloomberg Interactive Brokers studio. So, Matt, Atlanta, Georgia, 272 00:14:02,559 --> 00:14:04,960 Speaker 1: what's the key one of the key takeaways from your 273 00:14:05,040 --> 00:14:08,439 Speaker 1: perspectives as you looked at the data as to why 274 00:14:08,600 --> 00:14:11,000 Speaker 1: Atlanta has been such a good success story. So it 275 00:14:11,040 --> 00:14:16,680 Speaker 1: goes back to Maynard Jackson became the first black mayor 276 00:14:17,000 --> 00:14:21,360 Speaker 1: of any city, major city in the South, and he 277 00:14:21,680 --> 00:14:27,000 Speaker 1: had two very big initiatives that stand the test of time. 278 00:14:27,160 --> 00:14:32,800 Speaker 1: One was massive public works, which included the renovation of 279 00:14:32,880 --> 00:14:36,440 Speaker 1: the airport that is the busiest in the world uh 280 00:14:36,480 --> 00:14:39,600 Speaker 1: and has been renamed with his name on it because 281 00:14:39,640 --> 00:14:43,240 Speaker 1: of that renovation. UH. He also initiated a rail line 282 00:14:43,280 --> 00:14:45,160 Speaker 1: that goes from one into the city to the other, 283 00:14:45,240 --> 00:14:49,280 Speaker 1: so everybody can get from here to there without any difficulty. 284 00:14:49,800 --> 00:14:52,160 Speaker 1: But the other major thing was he wanted to make 285 00:14:52,160 --> 00:14:57,880 Speaker 1: sure Atlanta would be forever diverse. And with Atlanta being 286 00:14:57,920 --> 00:15:03,840 Speaker 1: today uh the second largest black majority UM city in 287 00:15:03,880 --> 00:15:09,520 Speaker 1: the United States. UM, he initiated a it was persuasion 288 00:15:09,680 --> 00:15:15,000 Speaker 1: really requirement that everybody hire at least thirty of their 289 00:15:15,040 --> 00:15:19,960 Speaker 1: workforce from the black local community. And that also stood 290 00:15:19,960 --> 00:15:22,840 Speaker 1: the test of time. So today when you look at 291 00:15:22,880 --> 00:15:26,320 Speaker 1: business in Atlanta, it is diverse, UH. And in fact, 292 00:15:26,480 --> 00:15:30,160 Speaker 1: Atlanta is really more diverse than any other city that way. 293 00:15:30,240 --> 00:15:34,160 Speaker 1: And so those two things, if you like, UH, infrastructure, 294 00:15:34,240 --> 00:15:40,120 Speaker 1: public works, and diversity have combined to make Atlanta, UM 295 00:15:40,160 --> 00:15:43,600 Speaker 1: the best performing city right now in the United States. 296 00:15:43,600 --> 00:15:45,680 Speaker 1: And we know that because we have these credit measures 297 00:15:45,720 --> 00:15:51,400 Speaker 1: that show that Atlanta liabilities are falling, personal incomes going up, 298 00:15:51,680 --> 00:15:58,000 Speaker 1: and UH and so UM are so many other measures 299 00:15:58,160 --> 00:16:01,040 Speaker 1: of performance for the city. So it's going in the 300 00:16:01,120 --> 00:16:05,920 Speaker 1: right direction. Is anyone else UM taking note or other 301 00:16:06,040 --> 00:16:09,560 Speaker 1: mayors looking at this as a template for what they 302 00:16:09,600 --> 00:16:12,520 Speaker 1: can do in their cities, especially in you know, cities 303 00:16:12,520 --> 00:16:17,800 Speaker 1: that have historically have had problems like Chicago or Baltimore. Well, UM, 304 00:16:17,880 --> 00:16:20,680 Speaker 1: I can't say I've done the Grand City tour of 305 00:16:20,760 --> 00:16:27,160 Speaker 1: late partly because of covid um you know, impediments. But um, 306 00:16:27,240 --> 00:16:30,000 Speaker 1: you know, I was in Boston last week catching up 307 00:16:30,040 --> 00:16:36,560 Speaker 1: with another new mayor, uh Michelle wou and mentioned Atlanta, 308 00:16:36,640 --> 00:16:39,160 Speaker 1: and she got excited and she said, we like what 309 00:16:39,200 --> 00:16:42,120 Speaker 1: we see down there. So, um it is. It is 310 00:16:42,160 --> 00:16:45,160 Speaker 1: an exemplar, There's no question about it. It's interesting, Matt, 311 00:16:45,280 --> 00:16:47,720 Speaker 1: just thinking about the success story of Atlanta, which has 312 00:16:47,760 --> 00:16:51,040 Speaker 1: been generations into making you think about just in the pandemic, 313 00:16:51,400 --> 00:16:54,800 Speaker 1: how we've seen, you know, a migration of people in 314 00:16:54,880 --> 00:16:59,080 Speaker 1: this country to other similar type cities, whether it's a 315 00:16:59,200 --> 00:17:02,960 Speaker 1: Nashville or or Charlotte or certainly Miami in on a 316 00:17:03,000 --> 00:17:07,600 Speaker 1: greater scale. How did Atlanta deal with the pandemic That 317 00:17:07,680 --> 00:17:10,760 Speaker 1: does anything unique there? Or were they hit as well 318 00:17:10,800 --> 00:17:12,880 Speaker 1: as anybody and they're trying to recover as well as anybody. 319 00:17:12,880 --> 00:17:15,680 Speaker 1: They had the same issues of every other city. Um, 320 00:17:15,880 --> 00:17:19,800 Speaker 1: and they also had you know, the if you like 321 00:17:20,880 --> 00:17:26,159 Speaker 1: the polarized politics, because as you know, Georgia is in 322 00:17:26,200 --> 00:17:32,199 Speaker 1: fact politically led by Republican legislature and governor. In Atlanta, 323 00:17:32,760 --> 00:17:37,520 Speaker 1: um is as I said, it's been Democrats since uh well, 324 00:17:37,680 --> 00:17:39,600 Speaker 1: going all the way back in time. Really, but it's 325 00:17:39,600 --> 00:17:43,560 Speaker 1: been black Democrat and uh, they don't agree on a 326 00:17:43,560 --> 00:17:48,720 Speaker 1: lot of big issues. And they certainly had difficulty dealing 327 00:17:48,720 --> 00:17:51,760 Speaker 1: with the pandemic having to do with things like masking 328 00:17:51,880 --> 00:17:54,760 Speaker 1: and you know, when businesses were going to be open 329 00:17:54,880 --> 00:17:57,760 Speaker 1: in schools and everything else. So every city has had 330 00:17:57,800 --> 00:18:01,760 Speaker 1: those issues. Uh, probably Atlanta I had to contend with 331 00:18:01,800 --> 00:18:08,960 Speaker 1: a much more difficult political um agenda. But Atlanta being Atlanta, 332 00:18:09,240 --> 00:18:13,159 Speaker 1: it managed to, you know, deal with these difficulties and 333 00:18:13,200 --> 00:18:15,760 Speaker 1: deal with them successfully to the extent that you know, 334 00:18:16,080 --> 00:18:22,479 Speaker 1: it's a uh, a bastion of diversity and will probably 335 00:18:22,520 --> 00:18:25,399 Speaker 1: continue to be so. I couldn't believe it when, uh 336 00:18:25,680 --> 00:18:28,160 Speaker 1: they tried to make it illegal to pass out bottles 337 00:18:28,200 --> 00:18:31,000 Speaker 1: of water to like single mothers and lines to vote. 338 00:18:31,000 --> 00:18:35,440 Speaker 1: What what a mean spirited thing to do. Uh, they 339 00:18:35,520 --> 00:18:38,760 Speaker 1: generate I think you said two thirds of the GDP 340 00:18:38,960 --> 00:18:41,400 Speaker 1: for Georgia. Is it possible that Atlantic could pick two 341 00:18:41,400 --> 00:18:45,359 Speaker 1: thirds of the congressional representatives. No, we're not there yet. 342 00:18:46,680 --> 00:18:49,360 Speaker 1: We're not there yet. But look, Atlanta was the reason 343 00:18:49,880 --> 00:18:53,399 Speaker 1: that Georgia for the first time in thirty years went 344 00:18:53,720 --> 00:18:57,160 Speaker 1: for a Democrat in the White House. Um, that's Faulton 345 00:18:57,320 --> 00:19:01,040 Speaker 1: and Dekalp County, those two counties to account for Atlanta, 346 00:19:01,240 --> 00:19:05,040 Speaker 1: and uh, you know, it's the reason that the senators 347 00:19:05,440 --> 00:19:09,720 Speaker 1: from Georgia are also Democrat and it's the reason that 348 00:19:10,000 --> 00:19:12,120 Speaker 1: you know, we see all these stories of companies leaving 349 00:19:12,160 --> 00:19:17,560 Speaker 1: Illinois to go, um to Texas and other states. But 350 00:19:17,760 --> 00:19:21,240 Speaker 1: companies headquartered in Atlanta are very happy. I know from um, 351 00:19:21,280 --> 00:19:25,000 Speaker 1: you know the companies I cover. Porscha absolutely loves being there. 352 00:19:25,000 --> 00:19:29,080 Speaker 1: But then they have much bigger, famous corporations that are 353 00:19:29,119 --> 00:19:32,119 Speaker 1: happy and not leaving, right correct. Um. You know, In 354 00:19:32,200 --> 00:19:36,840 Speaker 1: fact you mentioned at the outset Delta and home Depot, 355 00:19:36,880 --> 00:19:39,720 Speaker 1: those are the two. Those two companies are the best 356 00:19:39,760 --> 00:19:43,120 Speaker 1: performing in their global industries. You know, if you look 357 00:19:43,160 --> 00:19:46,959 Speaker 1: at Delta every which way you look at it, Delta 358 00:19:47,200 --> 00:19:51,840 Speaker 1: is the best airline from a market perspective or investment 359 00:19:52,200 --> 00:19:56,240 Speaker 1: perspective in the world. And if you look at home Depot, uh, 360 00:19:56,320 --> 00:19:58,600 Speaker 1: you know, look at their sales performance, it's it's really 361 00:19:58,640 --> 00:20:02,080 Speaker 1: the same thing. Home Depot does better than any other company. 362 00:20:02,200 --> 00:20:07,399 Speaker 1: So yes, they're very happy. Where they are happy is 363 00:20:07,440 --> 00:20:11,400 Speaker 1: a relative term, but um, yeah, where they're situated is 364 00:20:11,400 --> 00:20:16,159 Speaker 1: is uh is good for them, particularly because the airport. Um. 365 00:20:16,200 --> 00:20:19,919 Speaker 1: And that's really probably the best part of this is 366 00:20:20,000 --> 00:20:23,680 Speaker 1: that the Atlanta Airport has come out of COVID nineteen 367 00:20:24,480 --> 00:20:28,240 Speaker 1: UM performing better than any other airport in the world. 368 00:20:29,400 --> 00:20:31,600 Speaker 1: It's and the biggest airport in the world. I didn't 369 00:20:31,600 --> 00:20:33,720 Speaker 1: know that before I read this. I figured in terms 370 00:20:33,760 --> 00:20:37,120 Speaker 1: of traffic. Yeah, oh, hair or Charles de gaul Um, 371 00:20:38,240 --> 00:20:40,200 Speaker 1: I just want to quickly get your take on or 372 00:20:40,880 --> 00:20:44,160 Speaker 1: point out that Georgia Shirley must be one of the 373 00:20:44,160 --> 00:20:49,159 Speaker 1: trigger states, right, and we had this the uh, you know, 374 00:20:49,240 --> 00:20:52,000 Speaker 1: to really emotional days I think for the whole country 375 00:20:52,080 --> 00:20:56,320 Speaker 1: on Thursday and Friday because of the Supreme Court. Um. 376 00:20:56,400 --> 00:20:58,240 Speaker 1: What are we hearing from companies about how they're going 377 00:20:58,280 --> 00:21:00,840 Speaker 1: to deal deal with this? Well, what you've heard so far, 378 00:21:01,080 --> 00:21:06,840 Speaker 1: and we've reported this at Bloomberg pretty extensively, which is that, uh, 379 00:21:07,000 --> 00:21:10,800 Speaker 1: while companies have not for the most part, been explicit 380 00:21:11,000 --> 00:21:15,000 Speaker 1: in condemning the Supreme Court decision, what they have done 381 00:21:15,200 --> 00:21:18,919 Speaker 1: instead is say publicly that they will do whatever it 382 00:21:19,000 --> 00:21:24,800 Speaker 1: takes to pay for the reproductive care of their employees. 383 00:21:24,840 --> 00:21:27,040 Speaker 1: In other words, they will do whatever it takes to 384 00:21:27,119 --> 00:21:30,119 Speaker 1: enable employees wherever they are in any of these states 385 00:21:30,200 --> 00:21:35,439 Speaker 1: where um, you know, abortion is suddenly impossible or legal 386 00:21:35,880 --> 00:21:38,440 Speaker 1: or both. Yep, they'll take care of it all right, Matt, 387 00:21:38,440 --> 00:21:45,720 Speaker 1: thanks so much. We appreciate Matt Winkler, Bloomberg News. Here's 388 00:21:45,720 --> 00:21:49,120 Speaker 1: some data for you. Since the US alone has sustained 389 00:21:49,160 --> 00:21:53,679 Speaker 1: three weather and climate disasters, and by the end of 390 00:21:53,720 --> 00:21:56,720 Speaker 1: this century, the US government predicts two trillion dollars per 391 00:21:56,840 --> 00:22:01,280 Speaker 1: year in damages from hurricanes, wildfire's, flood, drought, severe storms, 392 00:22:01,440 --> 00:22:04,560 Speaker 1: or earthquakes. Question is is there a way to take 393 00:22:04,560 --> 00:22:08,480 Speaker 1: advantage of the disaster recovery efforts out there where you 394 00:22:08,640 --> 00:22:10,840 Speaker 1: guessed it? There's an e t F for that. Andrew 395 00:22:10,880 --> 00:22:14,400 Speaker 1: Chain and CEO of procure A m joins us UH. 396 00:22:14,440 --> 00:22:16,680 Speaker 1: Andrew talked to us about an e t F that 397 00:22:16,840 --> 00:22:20,520 Speaker 1: may benefit from, you know, recovery efforts for our disasters. 398 00:22:21,800 --> 00:22:23,480 Speaker 1: First of all, thanks for having me. It's great to 399 00:22:23,520 --> 00:22:26,720 Speaker 1: be back. And yeah, we're thrilled to talk about FEMA. 400 00:22:26,840 --> 00:22:30,000 Speaker 1: It's our latest ETF from procure We launched this just 401 00:22:30,119 --> 00:22:34,440 Speaker 1: on June one, and realizing the various trends and climate 402 00:22:34,520 --> 00:22:39,840 Speaker 1: change and the devastating and financial devastation that many of 403 00:22:39,960 --> 00:22:44,280 Speaker 1: these natural disasters and even man made and man enhanced 404 00:22:44,280 --> 00:22:47,479 Speaker 1: disasters can cause. To us, it made sense to create 405 00:22:47,840 --> 00:22:50,280 Speaker 1: a fund that focused on these companies that are helping 406 00:22:50,400 --> 00:22:54,680 Speaker 1: us with recovery, mitigation, prevention, and the companies that help 407 00:22:54,760 --> 00:22:56,560 Speaker 1: us in our in our times when we need them 408 00:22:56,560 --> 00:22:59,199 Speaker 1: the most. It's one of those ideas where when you 409 00:22:59,280 --> 00:23:02,320 Speaker 1: hear you're like, yeah, yeah, of course about time. Why 410 00:23:02,359 --> 00:23:05,640 Speaker 1: did it take so long? So talk to us about 411 00:23:05,680 --> 00:23:08,439 Speaker 1: the holdings that are in it. Yeah. So it's it's 412 00:23:08,480 --> 00:23:11,040 Speaker 1: a wide range, it's a global basket. We have currently 413 00:23:11,119 --> 00:23:13,960 Speaker 1: sixty two companies from around the world. And the SPUND 414 00:23:14,400 --> 00:23:18,480 Speaker 1: So you look back at the Texas UH freeze that 415 00:23:18,520 --> 00:23:21,160 Speaker 1: we had a little over a year ago, and when 416 00:23:21,160 --> 00:23:24,600 Speaker 1: the system went down, people were scrambling for generators. So 417 00:23:24,640 --> 00:23:27,280 Speaker 1: a company like Jenerac is where respund and they help 418 00:23:27,400 --> 00:23:31,680 Speaker 1: with you know, remote power generation absolutely. And you look 419 00:23:31,720 --> 00:23:35,160 Speaker 1: at UH. You know, when you have Hurricane Sandy or 420 00:23:35,160 --> 00:23:38,840 Speaker 1: events like the Horizon oil spill down on the Gulf, 421 00:23:39,280 --> 00:23:42,800 Speaker 1: and you know, typically dredging or the rebuilding of dunes 422 00:23:42,960 --> 00:23:46,240 Speaker 1: and protective barriers are extremely important. You have a company 423 00:23:46,280 --> 00:23:49,199 Speaker 1: like Great Lake Dredging DOC that you know, repaired I 424 00:23:49,240 --> 00:23:52,600 Speaker 1: believe twelve or more miles of the New Jersey coastline 425 00:23:53,000 --> 00:23:56,560 Speaker 1: UM and helped build up sand level sands heights in 426 00:23:56,640 --> 00:23:59,440 Speaker 1: the Gulf during the oil spill. So you have companies 427 00:23:59,440 --> 00:24:02,159 Speaker 1: to help with that. You have construction of engineering firms, 428 00:24:02,160 --> 00:24:07,600 Speaker 1: you have waste management treatment, water management, water treatment, UM 429 00:24:07,640 --> 00:24:10,480 Speaker 1: and so many other influential companies that help us in 430 00:24:10,560 --> 00:24:15,359 Speaker 1: events like wildfires, floods, earthquakes, even droughts. And this is 431 00:24:15,400 --> 00:24:17,800 Speaker 1: something that is a global phenomenon. You mentioned that two 432 00:24:17,840 --> 00:24:21,000 Speaker 1: trillion dollar figure that the US government expects by the 433 00:24:21,160 --> 00:24:24,960 Speaker 1: end of this century to the US budget alone. That's 434 00:24:25,000 --> 00:24:28,320 Speaker 1: probably five and a half billion dollars per day from 435 00:24:28,320 --> 00:24:31,919 Speaker 1: the US budget alone. That doesn't include what global efforts 436 00:24:31,960 --> 00:24:35,960 Speaker 1: are occurring overseas. That doesn't include what companies and individuals 437 00:24:36,000 --> 00:24:38,600 Speaker 1: will have to pay to protect and recover. So this 438 00:24:38,680 --> 00:24:41,960 Speaker 1: is truly a remarkable industry and one that we believe 439 00:24:41,960 --> 00:24:45,719 Speaker 1: we helped quantify by developing FEMA. But by the way, 440 00:24:45,720 --> 00:24:47,240 Speaker 1: I don't want to take us too far off base. 441 00:24:47,280 --> 00:24:50,080 Speaker 1: But when you see like Generac is one of those 442 00:24:50,080 --> 00:24:52,320 Speaker 1: products when when a guy like looks over the fence 443 00:24:52,359 --> 00:24:54,600 Speaker 1: and sees that has never got one, you're like super jealous. 444 00:24:55,119 --> 00:24:58,600 Speaker 1: And the new GENERAC I think are these bi directional 445 00:24:58,720 --> 00:25:00,520 Speaker 1: e V s. You just test of the four F 446 00:25:00,680 --> 00:25:03,199 Speaker 1: one which will essentially do the same thing. Right, it's 447 00:25:03,200 --> 00:25:06,640 Speaker 1: gonna power your house if and when the power goes down. 448 00:25:06,680 --> 00:25:10,720 Speaker 1: We got our generact three weeks before Superstar Sandy Horse. 449 00:25:11,400 --> 00:25:13,840 Speaker 1: We had people in our house. I didn't even know 450 00:25:13,920 --> 00:25:15,960 Speaker 1: they were staying with us for days. I found myself 451 00:25:15,960 --> 00:25:18,080 Speaker 1: walking a crying baby at like three o'clock in the 452 00:25:18,080 --> 00:25:19,680 Speaker 1: morning around my house and try to comment. I'm like, 453 00:25:19,680 --> 00:25:21,239 Speaker 1: I don't even know who this who this kid is, 454 00:25:21,400 --> 00:25:24,520 Speaker 1: But they work those generat work. Andrew, Uh, talk to 455 00:25:24,520 --> 00:25:27,520 Speaker 1: me quickly about the E t F business At a 456 00:25:27,560 --> 00:25:31,040 Speaker 1: broader level, you offer other products obviously. I I usually 457 00:25:31,080 --> 00:25:34,160 Speaker 1: talk to you about space and stuff like that. Um, 458 00:25:34,200 --> 00:25:38,800 Speaker 1: as we see this market downturn, it has been brutal, Um, 459 00:25:38,840 --> 00:25:42,560 Speaker 1: how does that affect E t F trading? Yeah? You know, 460 00:25:42,800 --> 00:25:45,480 Speaker 1: you know sometimes volatility, you know, brings a lot of 461 00:25:45,600 --> 00:25:48,280 Speaker 1: volume to the market. Sometimes people are in a wait 462 00:25:48,280 --> 00:25:51,760 Speaker 1: and see position and aren't ready to allocate new capital 463 00:25:51,840 --> 00:25:54,680 Speaker 1: to either new ideas or existing ideas, and they're trying 464 00:25:54,680 --> 00:25:57,720 Speaker 1: to figure out, Um, you're where the next trade maybe 465 00:25:57,840 --> 00:26:01,439 Speaker 1: or where they want to be overweighted and so UM. 466 00:26:01,480 --> 00:26:03,479 Speaker 1: You know, we've had some pretty violent moves in the 467 00:26:03,480 --> 00:26:06,040 Speaker 1: market over these last you know, many weeks, and you know, 468 00:26:06,119 --> 00:26:09,480 Speaker 1: for for the bulk of UM. You know, sometimes you 469 00:26:09,520 --> 00:26:11,679 Speaker 1: see those big moves and people use those as times 470 00:26:11,720 --> 00:26:14,840 Speaker 1: to reposition or reallocate, and you see volumes you know, 471 00:26:14,960 --> 00:26:17,520 Speaker 1: really surge. Sometimes people say, you know what, I'm gonna 472 00:26:17,560 --> 00:26:19,840 Speaker 1: take a step back, and certainly in the summer the 473 00:26:19,840 --> 00:26:23,040 Speaker 1: old adage and sell them ay and go away. UM. 474 00:26:23,080 --> 00:26:26,159 Speaker 1: You know, not always the case, but you know, some 475 00:26:26,280 --> 00:26:29,520 Speaker 1: volumes have been have been depressed, but there's always some 476 00:26:29,600 --> 00:26:31,840 Speaker 1: interest in certain areas in the market where you'll see 477 00:26:31,840 --> 00:26:34,640 Speaker 1: those volumes pick up. So typically those could be good 478 00:26:34,640 --> 00:26:36,840 Speaker 1: indicators for for what people are looking at. So is 479 00:26:36,880 --> 00:26:39,679 Speaker 1: this Uh? Is this the second e t F you're launching? 480 00:26:39,880 --> 00:26:43,560 Speaker 1: You have UFO right? UM? Is FEMA the second one 481 00:26:44,320 --> 00:26:48,680 Speaker 1: under the procure brand? Exactly what's next? You know, it's 482 00:26:48,880 --> 00:26:51,520 Speaker 1: it's a question we we always receive, UM. You know, 483 00:26:51,600 --> 00:26:54,080 Speaker 1: lots of times it's industries or themes that are near 484 00:26:54,119 --> 00:26:56,159 Speaker 1: and dear to me. UM. You know, I I was 485 00:26:56,200 --> 00:27:00,000 Speaker 1: down in New Orleans at University during Hurricane Katrina. Uh. 486 00:27:00,040 --> 00:27:02,200 Speaker 1: How is uh? You know in New York city during 487 00:27:02,200 --> 00:27:05,560 Speaker 1: sandy and the storms that we just had last year. Um, 488 00:27:05,640 --> 00:27:07,120 Speaker 1: you know a lot of ideas that I bring out 489 00:27:07,119 --> 00:27:08,680 Speaker 1: are things that you've played to some of my own 490 00:27:08,720 --> 00:27:12,040 Speaker 1: fears and looking for exposures and ways to potentially protect myself. 491 00:27:12,160 --> 00:27:15,600 Speaker 1: So we're always looking for first to market concepts. Typically 492 00:27:15,680 --> 00:27:18,240 Speaker 1: thematic global equity is how we how we bring the 493 00:27:18,320 --> 00:27:21,439 Speaker 1: strategies out and FEMA was, uh, you know, an area 494 00:27:21,480 --> 00:27:24,240 Speaker 1: that seemed completely underserved and one that you know could 495 00:27:24,280 --> 00:27:27,600 Speaker 1: give interest to many investors. Totally makes sense. Net look 496 00:27:27,640 --> 00:27:32,040 Speaker 1: for innovation. Now, UFO, you've been I assume you've been 497 00:27:32,119 --> 00:27:35,600 Speaker 1: hit by the whole um. Well, the FED raising rates 498 00:27:35,640 --> 00:27:37,879 Speaker 1: take some frothiness out of the market. Everybody looks at 499 00:27:38,000 --> 00:27:39,760 Speaker 1: ARC and they're like, why did we ever buy that? 500 00:27:39,880 --> 00:27:44,119 Speaker 1: You know, Um, but but you're investing in space and 501 00:27:44,160 --> 00:27:47,240 Speaker 1: the things that we're gonna need to use in space, 502 00:27:47,359 --> 00:27:50,640 Speaker 1: make in space, get from space. I have to assume 503 00:27:50,720 --> 00:27:53,800 Speaker 1: that is not going away just because the FED starts 504 00:27:53,840 --> 00:27:56,720 Speaker 1: raising rates. Well, you can even look at just in 505 00:27:56,760 --> 00:27:59,720 Speaker 1: the last few weeks various government contracts that have been 506 00:27:59,760 --> 00:28:04,320 Speaker 1: a ordered to numerous space companies and you know, historically 507 00:28:04,320 --> 00:28:07,199 Speaker 1: in the early days, space is almost entirely funded by 508 00:28:07,200 --> 00:28:10,560 Speaker 1: governments and government agencies. That numbers dropped to roughly twenty 509 00:28:10,600 --> 00:28:14,679 Speaker 1: percent in recent years, with commercial space really being the driver. 510 00:28:15,119 --> 00:28:18,200 Speaker 1: So we're seeing a ton of demand with the Ukraine invasion, 511 00:28:18,280 --> 00:28:20,760 Speaker 1: we're learning how important space is and to be able 512 00:28:20,760 --> 00:28:25,159 Speaker 1: to have redundancies, capabilities, defensive and offensive capabilities from a 513 00:28:25,200 --> 00:28:28,119 Speaker 1: government from a military standpoint, And these are things that 514 00:28:28,160 --> 00:28:31,480 Speaker 1: are in real time driving the space industry. So while 515 00:28:31,640 --> 00:28:34,840 Speaker 1: maybe people not as many people can afford space tourism, 516 00:28:34,880 --> 00:28:37,639 Speaker 1: that's a really small part of the space economy. The 517 00:28:37,680 --> 00:28:43,479 Speaker 1: other parts, the main drivers like communications, draw band, internet, connectivity, um, 518 00:28:43,520 --> 00:28:45,640 Speaker 1: you know, the things that benefit our lives here on 519 00:28:45,720 --> 00:28:49,440 Speaker 1: Earth are things that are still seeing some tremendous demands. 520 00:28:49,480 --> 00:28:52,400 Speaker 1: So it's an unaccompanied by company basis. Not necessarily every 521 00:28:52,400 --> 00:28:54,880 Speaker 1: company is going to be a winner, but using diversification 522 00:28:54,920 --> 00:28:57,440 Speaker 1: can hopefully provide you to too many of those companies 523 00:28:57,440 --> 00:29:00,920 Speaker 1: that are generating space revenues from around the world. All right, Andrew, 524 00:29:00,960 --> 00:29:04,240 Speaker 1: good stuff as always entertained and CEO of procure a M. 525 00:29:04,320 --> 00:29:07,440 Speaker 1: They've got a new e T f out f e 526 00:29:07,640 --> 00:29:11,080 Speaker 1: M a FEMA. It's uh to try to invest to 527 00:29:11,120 --> 00:29:14,440 Speaker 1: take advantage of some opportunities in the disaster recovery effort. 528 00:29:14,720 --> 00:29:17,040 Speaker 1: That's their second e t F after the first one 529 00:29:17,240 --> 00:29:20,240 Speaker 1: was u f O as Andrews just explaining kind of 530 00:29:20,280 --> 00:29:22,440 Speaker 1: take advantage of all the investment that is going on 531 00:29:22,640 --> 00:29:25,840 Speaker 1: in space of some cool thematic e t f s 532 00:29:25,880 --> 00:29:30,719 Speaker 1: out there. Thanks for listening to the Bloomberg Markets podcast. 533 00:29:31,120 --> 00:29:34,320 Speaker 1: You can subscribe and listen to interviews with Apple Podcasts 534 00:29:34,440 --> 00:29:38,360 Speaker 1: or whatever podcast platform you prefer. I'm Matt Miller. I'm 535 00:29:38,400 --> 00:29:42,440 Speaker 1: on Twitter at Matt Miller three. Put on false Sweeney. 536 00:29:42,440 --> 00:29:45,080 Speaker 1: I'm on Twitter at pt Sweeney before the podcast. You 537 00:29:45,120 --> 00:29:47,520 Speaker 1: can always catch us worldwide at Bloomberg Radio