1 00:00:02,520 --> 00:00:07,040 Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. 2 00:00:07,800 --> 00:00:11,119 Speaker 2: Joining us now to talk about all that's going on 3 00:00:11,440 --> 00:00:15,000 Speaker 2: in the markets right now is black Global, Chief Investment 4 00:00:15,040 --> 00:00:18,159 Speaker 2: Officer of Global Fixed Income, Rick Reader. And Rick, we 5 00:00:18,200 --> 00:00:21,239 Speaker 2: book you on every Job's Day, but this is yet 6 00:00:21,239 --> 00:00:24,560 Speaker 2: another Friday when we don't get the jobs report because 7 00:00:24,600 --> 00:00:26,799 Speaker 2: of a short government shutdown. It looks like we could 8 00:00:26,800 --> 00:00:31,040 Speaker 2: have another one partial shutdown at the end of next week. 9 00:00:31,240 --> 00:00:34,760 Speaker 2: What do you make of this sort of muddy data 10 00:00:34,840 --> 00:00:37,640 Speaker 2: picture when we don't get the things we need in time. 11 00:00:38,840 --> 00:00:42,120 Speaker 3: Well, so, first of all, it hasn't been jobs Day 12 00:00:42,120 --> 00:00:44,440 Speaker 3: in a number of months anyway, because we're not getting 13 00:00:44,440 --> 00:00:46,960 Speaker 3: any of those. So I think the last three months 14 00:00:46,960 --> 00:00:49,199 Speaker 3: we've had negative people. We had a government shutdown, but 15 00:00:49,240 --> 00:00:51,920 Speaker 3: you've still have negative negative jobs. 16 00:00:52,440 --> 00:00:52,680 Speaker 1: Listen. 17 00:00:52,720 --> 00:00:55,560 Speaker 3: I mean it's a little trickier when you don't get 18 00:00:55,600 --> 00:00:58,000 Speaker 3: the actual published reports and markets pivot off and by 19 00:00:58,000 --> 00:01:00,080 Speaker 3: the way, the volatility markets, you strike a lot of 20 00:01:00,080 --> 00:01:03,160 Speaker 3: options in and around those dates. So I tells you 21 00:01:03,240 --> 00:01:05,840 Speaker 3: this creates a little bit of trickiness that being sad. 22 00:01:05,920 --> 00:01:08,480 Speaker 3: I mean, particularly for jobs, and we've talked about a 23 00:01:08,560 --> 00:01:11,160 Speaker 3: number of months on your show. You look at what 24 00:01:11,200 --> 00:01:13,080 Speaker 3: we got yesterday. Look at the Jolt support, look at 25 00:01:13,080 --> 00:01:15,360 Speaker 3: the Challenger job counts, you look at the claims data, 26 00:01:15,600 --> 00:01:18,960 Speaker 3: you look at the ISM services. In terms of jobs, like, 27 00:01:19,640 --> 00:01:23,160 Speaker 3: there's no ambiguity around where we are in the job market. 28 00:01:23,200 --> 00:01:27,680 Speaker 3: We're having a really tough time. We're watching productivity explode 29 00:01:27,760 --> 00:01:31,200 Speaker 3: higher in terms of growth being really. 30 00:01:31,000 --> 00:01:33,200 Speaker 1: Good, but at job market, that's that's really tricky. 31 00:01:33,720 --> 00:01:37,000 Speaker 4: That dichotomy, Rick is the most fascinating. Well, there's a 32 00:01:37,000 --> 00:01:38,560 Speaker 4: lot of interesting stuff going on, but as one of 33 00:01:38,600 --> 00:01:41,600 Speaker 4: the most fascinating things about this economy because it's difficult 34 00:01:41,600 --> 00:01:44,800 Speaker 4: for anyone to say, even with jobs looking very challenging, 35 00:01:44,840 --> 00:01:47,480 Speaker 4: that we're heading anywhere near a recession. As long as 36 00:01:47,520 --> 00:01:49,480 Speaker 4: the mag seven is spending what like two point one 37 00:01:49,560 --> 00:01:52,920 Speaker 4: percent of GDP on capex, as long as a government's 38 00:01:53,000 --> 00:01:56,880 Speaker 4: running a six percent plus deficit deficit, is this economy 39 00:01:56,960 --> 00:01:59,840 Speaker 4: going to be okay even if the jobs market starts 40 00:01:59,840 --> 00:02:01,080 Speaker 4: to have some cracks in it. 41 00:02:02,400 --> 00:02:03,880 Speaker 1: Yeah, the answer is yes. 42 00:02:04,080 --> 00:02:06,840 Speaker 3: And the you know, I think I think people don't 43 00:02:06,880 --> 00:02:09,720 Speaker 3: you know, look at jobs and look at this economy 44 00:02:09,800 --> 00:02:11,880 Speaker 3: like it was twenty thirty years ago. You have an 45 00:02:11,960 --> 00:02:16,880 Speaker 3: extraordinarily different economy service oriented versus goods oriented. But you've 46 00:02:16,880 --> 00:02:19,680 Speaker 3: got an economy that's operating incredibly well, but only on 47 00:02:19,720 --> 00:02:21,440 Speaker 3: a couple or three cylinders. 48 00:02:21,919 --> 00:02:22,280 Speaker 1: Today. 49 00:02:22,320 --> 00:02:24,560 Speaker 3: You've got, like you pointed out, you've got cap X 50 00:02:24,560 --> 00:02:27,720 Speaker 3: that is robust and will continue. You've got consumption that 51 00:02:27,840 --> 00:02:33,160 Speaker 3: is robust, but it's driven by wealthier, older savers. And 52 00:02:33,160 --> 00:02:34,919 Speaker 3: it's part of why the you know, the interest rate 53 00:02:34,960 --> 00:02:37,480 Speaker 3: tool is is not nearly as effective as it used 54 00:02:37,480 --> 00:02:40,200 Speaker 3: to be because that cohort is doing extremely well. Where 55 00:02:40,240 --> 00:02:43,800 Speaker 3: the burden today is is in terms of low income, 56 00:02:44,360 --> 00:02:47,640 Speaker 3: small business, younger people and so. 57 00:02:47,880 --> 00:02:48,760 Speaker 1: But if when you. 58 00:02:48,680 --> 00:02:50,320 Speaker 3: Aggregate the data, and I hear a lot of people 59 00:02:50,360 --> 00:02:52,079 Speaker 3: talking about when my god, the jobs market is softening, 60 00:02:52,120 --> 00:02:53,079 Speaker 3: the economy. 61 00:02:52,720 --> 00:02:54,000 Speaker 1: Is going to come under pressure. 62 00:02:54,440 --> 00:02:56,840 Speaker 3: It's actually this is an economy that's more acid oriented 63 00:02:56,840 --> 00:03:02,160 Speaker 3: than labor oriented, and that cohort I don't want to 64 00:03:02,280 --> 00:03:02,880 Speaker 3: understate this. 65 00:03:03,080 --> 00:03:04,600 Speaker 1: We have a problem too, is we need to employ 66 00:03:04,680 --> 00:03:05,200 Speaker 1: more people. 67 00:03:05,600 --> 00:03:09,040 Speaker 3: But that cohort isn't that much in terms of aggregate spend, 68 00:03:09,600 --> 00:03:13,399 Speaker 3: so the economy can continue to motor along. And productivity, 69 00:03:13,840 --> 00:03:16,120 Speaker 3: I mean you watch it play out every day. I 70 00:03:16,120 --> 00:03:18,560 Speaker 3: mean the equity market has taken it on. About where 71 00:03:18,680 --> 00:03:23,119 Speaker 3: is productivity manifesting itself effectively some spaces. 72 00:03:22,840 --> 00:03:24,880 Speaker 1: Not other Who are the winners? Who's building a moat? 73 00:03:25,280 --> 00:03:26,720 Speaker 1: Who's not going to be a winner in this? 74 00:03:27,440 --> 00:03:30,399 Speaker 3: But I mean, at the core, you're watching something play 75 00:03:30,400 --> 00:03:31,600 Speaker 3: out that's pretty historic. 76 00:03:32,040 --> 00:03:37,600 Speaker 2: Anthropic putting out another AI tool, this time for financial analysis. 77 00:03:37,640 --> 00:03:40,640 Speaker 2: They did earlier this week for legal services. Both of 78 00:03:40,680 --> 00:03:46,000 Speaker 2: them kind of rocking the market. That will affect sales 79 00:03:46,040 --> 00:03:48,720 Speaker 2: at big companies I imagine, big and small, as well 80 00:03:48,760 --> 00:03:52,160 Speaker 2: as the jobs picture. Right, we're talking to a lot 81 00:03:52,160 --> 00:03:55,760 Speaker 2: of people. Yesterday we're talking Mike Arraghetti from Aries, who 82 00:03:55,800 --> 00:03:59,080 Speaker 2: pointed out that, you know, the younger talent, the new 83 00:03:59,160 --> 00:04:01,000 Speaker 2: hires aren't going to be doing the same work and 84 00:04:01,280 --> 00:04:04,160 Speaker 2: may not be as plentiful as they once were in 85 00:04:04,440 --> 00:04:09,040 Speaker 2: that industry. What do you make of AI changing the 86 00:04:09,040 --> 00:04:10,880 Speaker 2: way we work or the fact that we work at all. 87 00:04:13,560 --> 00:04:16,400 Speaker 3: Well, Mike's a very smart guy. I would say, I 88 00:04:16,400 --> 00:04:18,800 Speaker 3: would say a couple of things. You know, I chair 89 00:04:18,880 --> 00:04:21,119 Speaker 3: the board of we have fourteen charter schools in Newark, 90 00:04:21,120 --> 00:04:23,040 Speaker 3: New Jersey, and we just had a discussion this week 91 00:04:23,040 --> 00:04:26,359 Speaker 3: at our board meeting about what is our curriculum going forward? 92 00:04:26,400 --> 00:04:31,040 Speaker 3: How does AI evolve how we teach kids. How do 93 00:04:31,040 --> 00:04:33,479 Speaker 3: we what are the disciplines we're teaching our kids for 94 00:04:33,680 --> 00:04:36,200 Speaker 3: going forward? How do we use AI to augment a 95 00:04:36,279 --> 00:04:40,240 Speaker 3: traditional teaching process? This is all new territory, and this 96 00:04:40,279 --> 00:04:43,680 Speaker 3: is all new land in terms of where we're going. Listen, 97 00:04:43,720 --> 00:04:46,279 Speaker 3: I think there's a bunch of things that are you know, 98 00:04:46,480 --> 00:04:50,760 Speaker 3: that have been standard operating procedure that you know that 99 00:04:50,839 --> 00:04:52,760 Speaker 3: we used to teach people for and quite frankly, AI 100 00:04:52,920 --> 00:04:55,559 Speaker 3: is going to fulfill that function going forward. I still 101 00:04:55,560 --> 00:04:59,120 Speaker 3: think learning and interacting with people and the core of 102 00:04:59,240 --> 00:05:01,599 Speaker 3: education will will be sincere to what it was. 103 00:05:01,960 --> 00:05:03,800 Speaker 1: But gosh, there's so many things we got to. 104 00:05:03,720 --> 00:05:06,440 Speaker 3: Think about about what can AI do that can make 105 00:05:06,440 --> 00:05:09,200 Speaker 3: the economy more efficient, make people more efficient, and then 106 00:05:09,240 --> 00:05:12,000 Speaker 3: move people into the zones that are going to be 107 00:05:12,040 --> 00:05:14,760 Speaker 3: fulfilling going forward. But that is I'll tell you'm out there. 108 00:05:14,880 --> 00:05:16,320 Speaker 3: There is no roadmap for this. 109 00:05:16,520 --> 00:05:18,600 Speaker 2: Well what do you make of I mean, I look 110 00:05:18,640 --> 00:05:22,800 Speaker 2: at Bink, the ETF that you manage very well, and 111 00:05:22,839 --> 00:05:24,960 Speaker 2: we'll show in a second how you've beaten returns of 112 00:05:25,480 --> 00:05:29,320 Speaker 2: the benchmarks by a lot. But there's some corporate assets 113 00:05:29,320 --> 00:05:34,279 Speaker 2: there right forty five percent, And I wonder how you 114 00:05:34,640 --> 00:05:38,400 Speaker 2: judge whether or not a company has a moat, what 115 00:05:38,440 --> 00:05:40,679 Speaker 2: that moat would look like so that it can defend 116 00:05:40,720 --> 00:05:42,599 Speaker 2: itself against AI disruption. 117 00:05:44,760 --> 00:05:47,200 Speaker 3: So mat there is how do I describe this by 118 00:05:47,240 --> 00:05:48,920 Speaker 3: the way, you know, we'll take it in a couple 119 00:05:48,920 --> 00:05:49,520 Speaker 3: of different rections. 120 00:05:49,560 --> 00:05:51,760 Speaker 1: One that's interesting. You know, you hear the. 121 00:05:51,680 --> 00:05:55,039 Speaker 3: Discussion about capex and the cap X was too high, 122 00:05:55,279 --> 00:05:57,000 Speaker 3: and you know, I would argue, there's some other things 123 00:05:57,000 --> 00:05:57,680 Speaker 3: that play there. 124 00:05:57,960 --> 00:05:59,080 Speaker 1: Cap X is your moat. 125 00:05:59,440 --> 00:06:01,640 Speaker 3: Cap X and R and D spend are the way 126 00:06:01,680 --> 00:06:05,000 Speaker 3: companies can build their moat. And it's actually data utilization 127 00:06:05,240 --> 00:06:09,200 Speaker 3: and the companies that are exploiting data effectively that are 128 00:06:09,200 --> 00:06:10,120 Speaker 3: building bigger moats. 129 00:06:10,200 --> 00:06:11,800 Speaker 1: That is at the core of what is happening. 130 00:06:11,839 --> 00:06:15,120 Speaker 3: You know, there's something also that's different today some companies, 131 00:06:15,120 --> 00:06:18,200 Speaker 3: the free cash flow generation that's been so robust the last. 132 00:06:18,000 --> 00:06:18,560 Speaker 1: Couple of years. 133 00:06:18,560 --> 00:06:20,680 Speaker 3: You see some of these big companies buying back a 134 00:06:20,720 --> 00:06:23,479 Speaker 3: huge amount of stock. Now they're spending more on capex 135 00:06:23,520 --> 00:06:26,120 Speaker 3: that has real ratifications for the technicals in the equity 136 00:06:26,160 --> 00:06:27,200 Speaker 3: market that we got to think through. 137 00:06:28,080 --> 00:06:30,000 Speaker 1: It's a lot of hard work, YEA. 138 00:06:30,160 --> 00:06:31,800 Speaker 4: Well, I just want to jump in about the other 139 00:06:31,800 --> 00:06:33,680 Speaker 4: hard work you do at BINK and how you're thinking 140 00:06:33,760 --> 00:06:36,359 Speaker 4: about positioning the fund and where on the curve. Yield 141 00:06:36,440 --> 00:06:39,800 Speaker 4: curve just shy of its twenty twenty two highs, somewhat 142 00:06:39,800 --> 00:06:42,720 Speaker 4: reverse a little bit yesterday, but some of that steepening continues. 143 00:06:43,320 --> 00:06:46,520 Speaker 4: We have an incoming FED chief who's been talking about 144 00:06:47,160 --> 00:06:49,800 Speaker 4: trying to shrink the balance sheet over at the FED. 145 00:06:50,200 --> 00:06:52,440 Speaker 4: When you think about the rest of this year, are 146 00:06:52,480 --> 00:06:54,680 Speaker 4: you thinking about changes to bank it all? Where do 147 00:06:54,720 --> 00:06:57,080 Speaker 4: you want to be positioned for the road ahead? And 148 00:06:57,080 --> 00:06:57,719 Speaker 4: fixed income? 149 00:07:00,680 --> 00:07:03,440 Speaker 3: Bunch of changes your point about credit. We've reduced some credit, 150 00:07:03,520 --> 00:07:07,160 Speaker 3: We've reduced some ig because quite frankly, it's not that fulfilling. 151 00:07:07,200 --> 00:07:09,240 Speaker 3: We're gonna get a lot of supply. The spread's not 152 00:07:09,279 --> 00:07:11,720 Speaker 3: that interesting, you know. We've cut a little bit of 153 00:07:11,720 --> 00:07:14,880 Speaker 3: the low quality high yield, and by the way, we're 154 00:07:14,920 --> 00:07:17,360 Speaker 3: running a bit less high yield than we're running overall. 155 00:07:18,120 --> 00:07:20,680 Speaker 3: We've added to mortgages, although recent the last couple of 156 00:07:20,680 --> 00:07:22,880 Speaker 3: months or there's no last couple months, last few days, 157 00:07:22,920 --> 00:07:25,280 Speaker 3: maybe we've cut a little bit of mortgages because the 158 00:07:25,320 --> 00:07:30,080 Speaker 3: balance sheet discussion becomes a little less enthusiastic than than 159 00:07:30,120 --> 00:07:30,880 Speaker 3: it was before. 160 00:07:31,040 --> 00:07:32,440 Speaker 1: But we still like mortgages. 161 00:07:32,880 --> 00:07:35,800 Speaker 3: We like EM a lot, and the dollar will stay 162 00:07:35,840 --> 00:07:39,600 Speaker 3: contained and so EM. The yield differential between EM and 163 00:07:39,680 --> 00:07:42,720 Speaker 3: high yield is as good as it's ever been. And 164 00:07:42,760 --> 00:07:45,960 Speaker 3: then the key one for us is and is securitization 165 00:07:46,120 --> 00:07:50,120 Speaker 3: markets that I'll allow you to structure the collateral, the covenants, 166 00:07:50,160 --> 00:07:52,720 Speaker 3: the you know, what's your attachment point is. So we 167 00:07:52,800 --> 00:07:56,120 Speaker 3: love the securitization market, but you're right, it's a different expression, 168 00:07:56,120 --> 00:07:59,240 Speaker 3: a little less credit, a little more EM, a little 169 00:07:59,280 --> 00:08:02,880 Speaker 3: more sicking the securitization zone. By the way, Europe killed 170 00:08:02,880 --> 00:08:06,200 Speaker 3: it last year, and now the benefit you're getting from 171 00:08:06,200 --> 00:08:08,120 Speaker 3: Europe is not nearly as robust as it was. So 172 00:08:08,120 --> 00:08:10,000 Speaker 3: we've dulled down a little bit of that and more 173 00:08:10,160 --> 00:08:13,040 Speaker 3: actually more Asia in the portfolio. So yeah, we've been 174 00:08:13,040 --> 00:08:16,000 Speaker 3: moving around a fair amount to keep a dynamic and 175 00:08:16,040 --> 00:08:18,000 Speaker 3: where the best we think the best opportunity is