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 --> 00:00:15,520 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 --> 00:00:21,960 Speaker 1: at Bloomberg dot com slash podcast. All right, let's talk 7 00:00:22,000 --> 00:00:24,840 Speaker 1: to Phil Plumbo. He's a founder, CEO and CIO Plumbo 8 00:00:24,880 --> 00:00:28,560 Speaker 1: Wealth Management. Phil, do we have another leg down in 9 00:00:28,640 --> 00:00:31,040 Speaker 1: this market? I kind of. I'm just not sure how 10 00:00:31,120 --> 00:00:35,000 Speaker 1: much I should really buy into this bounce off the bottom. 11 00:00:35,000 --> 00:00:37,680 Speaker 1: What say you? Well, you took the words out of 12 00:00:37,720 --> 00:00:39,400 Speaker 1: my mouth, right, So we're still in the middle of 13 00:00:39,400 --> 00:00:41,360 Speaker 1: this storm. And the way I look at it is 14 00:00:41,479 --> 00:00:45,080 Speaker 1: the FED said that inflation was gonna be transitory. Were 15 00:00:45,120 --> 00:00:47,960 Speaker 1: the furthest thing from transitory? The FED says that we're 16 00:00:48,560 --> 00:00:51,680 Speaker 1: not in a recession. We had two back about quarters 17 00:00:51,720 --> 00:00:53,600 Speaker 1: of negative GDP. As long as I've been doing that, 18 00:00:53,640 --> 00:00:56,440 Speaker 1: it's always been the definition. I totally get the tight 19 00:00:56,560 --> 00:00:59,720 Speaker 1: label market. So technically probably when not in a recession. 20 00:00:59,760 --> 00:01:02,240 Speaker 1: Now it everything the FED is doing on and is 21 00:01:02,360 --> 00:01:05,560 Speaker 1: doing and is embarking on right. All of that still 22 00:01:05,600 --> 00:01:08,800 Speaker 1: needs to be absorbed into the economy, and it takes time. 23 00:01:09,319 --> 00:01:11,160 Speaker 1: It takes six months to take a year, to take 24 00:01:11,160 --> 00:01:13,280 Speaker 1: a year and a half. So at some point this 25 00:01:13,400 --> 00:01:15,640 Speaker 1: data will continue to worsen. When you think about p 26 00:01:15,840 --> 00:01:20,240 Speaker 1: WC survey firm said they're gonna they're anticipating layoffs. The 27 00:01:20,240 --> 00:01:24,000 Speaker 1: inverted yield curve, sentiment again is high. You look at 28 00:01:24,040 --> 00:01:27,280 Speaker 1: the multiples on Amazon and Apple. Forward on Amazon is 29 00:01:27,280 --> 00:01:30,640 Speaker 1: fifty six Apples twenty six times in both the growing 30 00:01:30,680 --> 00:01:35,920 Speaker 1: revenue one another one at seven percent. So valuations still 31 00:01:36,000 --> 00:01:37,800 Speaker 1: have to come in and there is going to be 32 00:01:37,840 --> 00:01:39,880 Speaker 1: another leg down that will retest the loads that we 33 00:01:39,959 --> 00:01:43,600 Speaker 1: saw back in June. But what's the what's the driver 34 00:01:43,720 --> 00:01:47,800 Speaker 1: of that retesting of the lows? Is it the FED hike? 35 00:01:48,080 --> 00:01:51,560 Speaker 1: Is it recession worries? Is it it slowed out in consumption. 36 00:01:51,680 --> 00:01:55,200 Speaker 1: I mean, I'm admittedly at faulty because I'm a journalist 37 00:01:55,200 --> 00:01:57,440 Speaker 1: and I was repeatedly told by traders not everything has 38 00:01:57,440 --> 00:01:59,800 Speaker 1: a fundamental narrative. But why do you sell out of 39 00:01:59,800 --> 00:02:03,280 Speaker 1: this market when capital flows from other countries and really 40 00:02:03,320 --> 00:02:05,880 Speaker 1: the rest of the world could actually provide some sort 41 00:02:05,880 --> 00:02:09,160 Speaker 1: of support and everything has a fundamental narrative if you're 42 00:02:09,160 --> 00:02:10,919 Speaker 1: a trader in the short term, but over the six 43 00:02:10,960 --> 00:02:13,400 Speaker 1: twelve month period, which is a long term period, with 44 00:02:13,520 --> 00:02:16,520 Speaker 1: everything that the FETE is doing, and because we're in 45 00:02:16,520 --> 00:02:19,200 Speaker 1: a tight labor market means inflation could be more persistent. 46 00:02:19,240 --> 00:02:21,480 Speaker 1: We means the FETE has to act even more aggressively 47 00:02:21,560 --> 00:02:24,480 Speaker 1: or continue to be aggressive, and all of that is 48 00:02:24,480 --> 00:02:28,040 Speaker 1: not a positive for stocks. And ultimately, what happens our 49 00:02:28,160 --> 00:02:31,840 Speaker 1: company's executives, they're making decisions to lay off, They're gonna 50 00:02:31,880 --> 00:02:36,880 Speaker 1: You're gonna see analysts revise earnings, revision of earnings of 51 00:02:36,919 --> 00:02:42,600 Speaker 1: ten to off of what prediction is that brings you 52 00:02:42,639 --> 00:02:45,799 Speaker 1: out of forward multiple today of y two times, which 53 00:02:45,840 --> 00:02:48,280 Speaker 1: is basically where we were in the middle of January. 54 00:02:48,320 --> 00:02:51,840 Speaker 1: So that's not attractive thinking about what the FETE is 55 00:02:51,840 --> 00:02:55,440 Speaker 1: embarking on and how inflation could be sticky. So so 56 00:02:55,560 --> 00:02:56,960 Speaker 1: what do you what do you tell your clients about? 57 00:02:57,000 --> 00:02:59,680 Speaker 1: You know, given that backdrop your call there for equities, 58 00:02:59,720 --> 00:03:01,760 Speaker 1: I mean, I see the in the first half of 59 00:03:01,760 --> 00:03:06,480 Speaker 1: the year, the terrible, terrible underperformance of fixed income across 60 00:03:06,560 --> 00:03:09,720 Speaker 1: the board, whether it's corporates or treasuries, investment created high yield, 61 00:03:09,720 --> 00:03:12,399 Speaker 1: there's nowhere to hide. So if we've got another leg 62 00:03:12,440 --> 00:03:16,040 Speaker 1: down here, what are you telling your clients these days 63 00:03:16,120 --> 00:03:17,799 Speaker 1: in terms of if they if they have some new 64 00:03:17,800 --> 00:03:20,280 Speaker 1: money to put the work. Maybe a couple of things right. 65 00:03:20,320 --> 00:03:22,200 Speaker 1: So I've been very consistent, whether it's on your show 66 00:03:22,280 --> 00:03:24,280 Speaker 1: or anywhere else, that we were in the tech bubble 67 00:03:24,320 --> 00:03:27,480 Speaker 1: that burst. We thought we the stock market as a whole, 68 00:03:28,080 --> 00:03:31,959 Speaker 1: was in a bubble, right. That came down to troll. 69 00:03:32,480 --> 00:03:36,920 Speaker 1: The technology got got killed as well. So coming into 70 00:03:36,960 --> 00:03:39,920 Speaker 1: this year, we're aggressive in cash and we still are today. 71 00:03:40,200 --> 00:03:43,240 Speaker 1: We're being we're being very patient like buffets all the time, 72 00:03:43,440 --> 00:03:44,960 Speaker 1: wait for the perfect pitch. You know, we're not out 73 00:03:44,960 --> 00:03:46,960 Speaker 1: of the situation where we're having a perfect pitch right now, 74 00:03:47,000 --> 00:03:50,280 Speaker 1: so we're being completely patient. Scenario, we had great returns, 75 00:03:50,280 --> 00:03:54,800 Speaker 1: everybody did right go in one, So being patient here 76 00:03:54,800 --> 00:03:58,040 Speaker 1: in twenty two with everything going on is perfectly fine 77 00:03:58,080 --> 00:04:02,920 Speaker 1: thing to do. I'm still I've got to say, I'm curious, though, 78 00:04:03,320 --> 00:04:05,200 Speaker 1: what else do you put your money in? I mean, 79 00:04:05,240 --> 00:04:07,840 Speaker 1: if you're pulling out of stocks and let's say going 80 00:04:08,040 --> 00:04:11,760 Speaker 1: to cash, for example, does that mean money markets? Does 81 00:04:11,800 --> 00:04:15,040 Speaker 1: that mean just blocking the dollars straight out. Where does 82 00:04:15,080 --> 00:04:17,400 Speaker 1: that money go? Yeah, for us, we put it in 83 00:04:17,480 --> 00:04:19,559 Speaker 1: money markets that can kneel between one and two percent. 84 00:04:19,680 --> 00:04:21,560 Speaker 1: It's not a great return, especially when you factor an 85 00:04:21,560 --> 00:04:24,920 Speaker 1: inflation completely. Get that. But if we do get a 86 00:04:25,000 --> 00:04:27,200 Speaker 1: great pitch thrown at us and it's a good time 87 00:04:27,240 --> 00:04:29,880 Speaker 1: to put capital to work where we can make great 88 00:04:29,920 --> 00:04:33,000 Speaker 1: returns over a three to five year period, then I 89 00:04:33,040 --> 00:04:34,880 Speaker 1: mean that could happen over the next two to three months. 90 00:04:34,880 --> 00:04:36,839 Speaker 1: So even though the return in cash is not great, 91 00:04:37,160 --> 00:04:39,559 Speaker 1: it's the opportunity that we're looking for that we believe 92 00:04:39,560 --> 00:04:43,240 Speaker 1: will will occur that will make up for any type 93 00:04:43,279 --> 00:04:46,080 Speaker 1: of low return you're getting in cash today. We also 94 00:04:46,120 --> 00:04:49,200 Speaker 1: are invest in gold. We're also in commodities as a diverse, 95 00:04:49,279 --> 00:04:52,280 Speaker 1: floid balanced portfolio, and obviously we have some exposure to 96 00:04:52,279 --> 00:04:55,200 Speaker 1: equities as well. How do your clients fill Did they 97 00:04:55,200 --> 00:04:59,560 Speaker 1: ask you about crypto bitcoin specifically? And if so, what 98 00:04:59,600 --> 00:05:01,680 Speaker 1: do you do you? What do you tell them? Yeah? 99 00:05:01,680 --> 00:05:03,520 Speaker 1: The answer is just like I think of growth socks. Right, 100 00:05:03,560 --> 00:05:05,280 Speaker 1: when you're investing in growth socks, you're trying to make 101 00:05:05,279 --> 00:05:06,880 Speaker 1: a prediction of how much a product is going to 102 00:05:06,960 --> 00:05:09,440 Speaker 1: be sold with that company over a long period of 103 00:05:09,440 --> 00:05:12,080 Speaker 1: time and and that prediction is just so speculative. Right, 104 00:05:12,160 --> 00:05:14,560 Speaker 1: So when you think about like bitcoin and ethereum and others, 105 00:05:14,800 --> 00:05:19,000 Speaker 1: you're talking about something that is complete speculation. So why 106 00:05:19,000 --> 00:05:22,039 Speaker 1: would I invest my client's hard own capital and something 107 00:05:22,080 --> 00:05:24,000 Speaker 1: that is speculative. Yeah, it could turn out great, but 108 00:05:24,040 --> 00:05:26,880 Speaker 1: also could turn out terrible. Right, So when it comes 109 00:05:26,880 --> 00:05:29,560 Speaker 1: to investing, I really believe it's about risk in return profile. 110 00:05:29,680 --> 00:05:32,440 Speaker 1: So I'd rather buy a great company like McDonald's or 111 00:05:32,480 --> 00:05:35,520 Speaker 1: Coca Cola or Fiser have free cast full yields of 112 00:05:35,560 --> 00:05:38,240 Speaker 1: north six seven percent or eight percent or more than that, 113 00:05:38,600 --> 00:05:40,600 Speaker 1: which is two to three times a ten year treasury, 114 00:05:41,279 --> 00:05:45,320 Speaker 1: with stable earnings, great management, great economic mode. For me, 115 00:05:45,560 --> 00:05:47,719 Speaker 1: that's how you invest capital and a little long term 116 00:05:47,800 --> 00:05:50,839 Speaker 1: you'll succeed, all right, Phel always great to get your thoughts, 117 00:05:50,920 --> 00:05:53,440 Speaker 1: your perspective. You've been in this game a long time. 118 00:05:53,440 --> 00:05:56,800 Speaker 1: You always appreciate your experience. Filth Plumbo founder, CEO and 119 00:05:56,839 --> 00:06:04,000 Speaker 1: c IO of Plumbo Wealth Management. There pretty I always 120 00:06:04,000 --> 00:06:05,600 Speaker 1: think about, like who would I not want to hang 121 00:06:05,600 --> 00:06:08,200 Speaker 1: out with at a cocktail party. Here's this person be 122 00:06:08,400 --> 00:06:12,000 Speaker 1: a in economics and statistics from Berkeley, and then she 123 00:06:12,040 --> 00:06:14,760 Speaker 1: goes and gets a PhD in economics from the University 124 00:06:14,800 --> 00:06:17,480 Speaker 1: of Chicago. I mean, you don't want to hang out 125 00:06:17,480 --> 00:06:19,080 Speaker 1: with her at a cocktail par I'm not sure, but 126 00:06:19,560 --> 00:06:21,160 Speaker 1: Anna Wong is a good buddy of ours. She's a 127 00:06:21,200 --> 00:06:24,000 Speaker 1: chief US economist for Bloomberg Economics, and I thanks so 128 00:06:24,080 --> 00:06:25,560 Speaker 1: much for joining us. I don't mean, I don't mean 129 00:06:25,600 --> 00:06:29,000 Speaker 1: to prejudge, but boy, that's some resume there. What are 130 00:06:29,040 --> 00:06:32,800 Speaker 1: you looking for tomorrow coming out of Jackson Hole, Wyomings? 131 00:06:33,080 --> 00:06:35,080 Speaker 1: You know, in addition to seeing what Tom King's gonna 132 00:06:35,120 --> 00:06:40,920 Speaker 1: wear tomorrow? Well, I, like everybody, I'm expecting a hawkish speech. 133 00:06:41,040 --> 00:06:44,560 Speaker 1: I expect that Power will ressert that the FED is 134 00:06:44,720 --> 00:06:49,440 Speaker 1: unconditionally committed to restoring inflation that to its price press target. 135 00:06:49,839 --> 00:06:52,760 Speaker 1: He is going to say that he will keep rates 136 00:06:52,760 --> 00:06:56,680 Speaker 1: in shift of territory until you see compelling evidence that 137 00:06:56,720 --> 00:06:59,160 Speaker 1: inflation is coming down. You know, the same same old 138 00:06:59,240 --> 00:07:02,880 Speaker 1: hawkish words. Um. But I think the interesting thing is 139 00:07:03,040 --> 00:07:06,400 Speaker 1: how whether the whether the speech would be hawkish enough 140 00:07:06,440 --> 00:07:10,960 Speaker 1: for the markets to kind of quash the thought that 141 00:07:11,080 --> 00:07:13,600 Speaker 1: you know that the FED is ready to cut rates 142 00:07:13,600 --> 00:07:17,200 Speaker 1: in three UM. And I think in order to do 143 00:07:17,240 --> 00:07:21,400 Speaker 1: that um, power will have to be extra hawkish, for example, 144 00:07:21,520 --> 00:07:25,320 Speaker 1: giving some numerical guidance saying that that the FED will 145 00:07:25,320 --> 00:07:28,520 Speaker 1: not cut until core inflation comes down to close to 146 00:07:28,560 --> 00:07:31,960 Speaker 1: two percent, something like very concrete like that. But I 147 00:07:32,280 --> 00:07:34,560 Speaker 1: just don't I see very little chance you will be 148 00:07:34,600 --> 00:07:37,400 Speaker 1: doing that though. Well, and I mean you got you 149 00:07:37,600 --> 00:07:40,400 Speaker 1: and your team at Bloomberg Economics came out I think 150 00:07:40,440 --> 00:07:42,960 Speaker 1: a couple of months ago, which what at the time 151 00:07:43,200 --> 00:07:46,000 Speaker 1: I thought was just way way way out of consensus 152 00:07:46,040 --> 00:07:49,400 Speaker 1: call that the FED might take the FED funds rates 153 00:07:49,480 --> 00:07:52,600 Speaker 1: up to five percent. Is that correct or is that 154 00:07:52,640 --> 00:07:56,040 Speaker 1: still your call? Yeah? That that is still our call, 155 00:07:56,080 --> 00:07:58,600 Speaker 1: and I think that by each day the chance of 156 00:07:58,720 --> 00:08:02,760 Speaker 1: that call is increasing. Um, we saw the student loan 157 00:08:02,840 --> 00:08:06,720 Speaker 1: proposal yesterday and we estimated that that will boost core 158 00:08:06,720 --> 00:08:10,720 Speaker 1: inflation by about point to percentage point, with a risk 159 00:08:10,800 --> 00:08:14,480 Speaker 1: of it being higher. And you know, just if you 160 00:08:14,520 --> 00:08:17,880 Speaker 1: think about the trade off between price and unemployment, that 161 00:08:18,000 --> 00:08:22,880 Speaker 1: little bit a point to percentage point extra inflation would 162 00:08:22,920 --> 00:08:26,280 Speaker 1: cost the said two tighten even more in order to 163 00:08:26,320 --> 00:08:30,200 Speaker 1: generate an eight hundred fifteen thousand job losses in order 164 00:08:30,240 --> 00:08:32,760 Speaker 1: to bring it, you know, to offer up those little 165 00:08:33,120 --> 00:08:36,000 Speaker 1: zero point two percentage points. So it's not even though 166 00:08:36,000 --> 00:08:38,640 Speaker 1: it sounds like a little just a little bit of inflation, 167 00:08:38,760 --> 00:08:42,120 Speaker 1: in fact, it's pretty like substantial from from a view 168 00:08:42,160 --> 00:08:45,920 Speaker 1: assume a flat Philip's curve. For the record, Anna, I 169 00:08:45,920 --> 00:08:48,160 Speaker 1: would love to be at a cocktail hard idea. Can 170 00:08:48,200 --> 00:08:50,320 Speaker 1: I just say that? I would? You know, you're invited 171 00:08:50,360 --> 00:08:52,920 Speaker 1: to the next one? I have um, step one, get 172 00:08:52,920 --> 00:08:56,320 Speaker 1: a bar card, step two, and long um. But but 173 00:08:56,440 --> 00:08:58,520 Speaker 1: you know what I'm curious about, and what I would 174 00:08:58,520 --> 00:09:01,160 Speaker 1: probably ask you at said cock party is how much 175 00:09:01,160 --> 00:09:02,920 Speaker 1: can the Federal Reserve really do here? I mean, you're 176 00:09:02,920 --> 00:09:05,560 Speaker 1: talking about them, I mean everyone's talking about them, looking 177 00:09:05,600 --> 00:09:08,760 Speaker 1: to be extra extra hawkish, But what more can they 178 00:09:08,800 --> 00:09:12,400 Speaker 1: really even say here? They've already said that a recession 179 00:09:12,480 --> 00:09:14,840 Speaker 1: is on the table. They're willing to make that that bet. 180 00:09:14,880 --> 00:09:16,800 Speaker 1: That's not their base case scenario, but they are willing 181 00:09:16,840 --> 00:09:19,319 Speaker 1: to do it at the tackle inflation at the expense 182 00:09:19,440 --> 00:09:23,040 Speaker 1: of a recession. The markets have a very high standard 183 00:09:23,080 --> 00:09:26,120 Speaker 1: for Chairman Powell tomorrow. What else can the Federal Reserve 184 00:09:26,240 --> 00:09:29,080 Speaker 1: really do here? When they're going meeting to meeting and 185 00:09:29,080 --> 00:09:33,200 Speaker 1: the data is literally all over the place. Yeah, Cretty, 186 00:09:33,240 --> 00:09:35,920 Speaker 1: that's that's a very good question. I think it will 187 00:09:35,960 --> 00:09:39,400 Speaker 1: be very hard for for him to to be more 188 00:09:39,480 --> 00:09:43,320 Speaker 1: hawkish than what the market is already expecting. Tomorrow, he 189 00:09:43,920 --> 00:09:47,080 Speaker 1: you know, he may be able to say that this 190 00:09:47,040 --> 00:09:50,760 Speaker 1: is the injection. The whole theme is about reassessing constraints 191 00:09:50,760 --> 00:09:54,120 Speaker 1: and the economy. It's all about examining what our star is, 192 00:09:54,280 --> 00:09:58,000 Speaker 1: what youth star is, what all the stars are. And 193 00:09:58,000 --> 00:10:00,840 Speaker 1: and I think that that if he is able to 194 00:10:00,880 --> 00:10:04,160 Speaker 1: say something like, oh, in fact, that our star um 195 00:10:04,280 --> 00:10:07,960 Speaker 1: or or tomorrow's research papers are arguing that our star 196 00:10:08,080 --> 00:10:11,080 Speaker 1: in fact substantially higher than two point five percent of 197 00:10:11,160 --> 00:10:15,000 Speaker 1: the median f MC participate participant thinks right now that 198 00:10:15,280 --> 00:10:18,800 Speaker 1: if he acknowledged that, that that's very hawkish. If he 199 00:10:19,000 --> 00:10:23,800 Speaker 1: acknowledged that the youth star is like six percent natural 200 00:10:23,880 --> 00:10:26,400 Speaker 1: rate of unemployment and that the FED will need to 201 00:10:26,480 --> 00:10:29,600 Speaker 1: generate an unemployment of up to six percent, well that 202 00:10:29,640 --> 00:10:32,600 Speaker 1: would be really hawkish. But that that's why I said 203 00:10:32,640 --> 00:10:36,800 Speaker 1: he would need to offer up some numerical something numerical 204 00:10:36,920 --> 00:10:40,559 Speaker 1: and something concrete to to come across is very convincing, 205 00:10:40,679 --> 00:10:43,720 Speaker 1: and and I just don't think that he would do 206 00:10:43,800 --> 00:10:46,360 Speaker 1: that tomorrow. However, I think they have a chance to 207 00:10:46,360 --> 00:10:50,079 Speaker 1: do in the September September flmc WH where they will 208 00:10:50,160 --> 00:10:53,400 Speaker 1: have an updated SEP at that point that UM, I 209 00:10:53,400 --> 00:10:57,000 Speaker 1: would expect that the neutral rate could be revised up 210 00:10:57,040 --> 00:11:00,640 Speaker 1: from the current two point five So you know, and 211 00:11:00,840 --> 00:11:02,520 Speaker 1: when you guys came out with that five percent number, 212 00:11:02,559 --> 00:11:04,640 Speaker 1: it was again way out of consensus. So kudos to 213 00:11:04,679 --> 00:11:07,160 Speaker 1: you and your team here. But one of the things 214 00:11:07,240 --> 00:11:11,040 Speaker 1: I look at the you know, the labor market, and 215 00:11:11,080 --> 00:11:14,520 Speaker 1: I still see a pretty strong labor market is is 216 00:11:14,559 --> 00:11:17,079 Speaker 1: that is it real? Do you think or do you 217 00:11:17,080 --> 00:11:19,120 Speaker 1: think there's some underlying week to say that the FETE 218 00:11:19,160 --> 00:11:20,839 Speaker 1: is paying attention to that we may not see in 219 00:11:20,880 --> 00:11:25,679 Speaker 1: the numbers. I think it's real. So if you look 220 00:11:25,720 --> 00:11:28,960 Speaker 1: at the direction of revisions, we just got to manage 221 00:11:29,000 --> 00:11:32,240 Speaker 1: your revisions on jobs yesterday. In fact, it turned out 222 00:11:32,280 --> 00:11:35,240 Speaker 1: that last year, up to earlier this year, the labor 223 00:11:35,280 --> 00:11:38,839 Speaker 1: market was half a million jobs hotter more than what 224 00:11:39,200 --> 00:11:42,640 Speaker 1: statistics actually show. That's on top of every month we 225 00:11:42,640 --> 00:11:46,240 Speaker 1: have been getting our revisions. I think the issue here, 226 00:11:46,800 --> 00:11:50,640 Speaker 1: UM is really productivity. UM. That's that explains to why 227 00:11:50,679 --> 00:11:55,120 Speaker 1: the g d I, the gross Domestic income measure of 228 00:11:55,200 --> 00:11:58,559 Speaker 1: GDP and GDP are telling you a different story. G 229 00:11:58,720 --> 00:12:02,080 Speaker 1: d P is saying the economic activity contracted g d I, 230 00:12:02,160 --> 00:12:06,920 Speaker 1: which is an income based measure that used hours, work times, wages, 231 00:12:07,280 --> 00:12:10,120 Speaker 1: and corporate profits. That's telling you that the economy is 232 00:12:10,160 --> 00:12:12,760 Speaker 1: doing pretty well. And I think that the thing to 233 00:12:12,840 --> 00:12:15,320 Speaker 1: bridge them all is that, in fact a lot of 234 00:12:15,320 --> 00:12:18,679 Speaker 1: people are being hired, but they're probably less productive than 235 00:12:18,720 --> 00:12:21,559 Speaker 1: before because people are calling sick and there are a 236 00:12:21,640 --> 00:12:24,280 Speaker 1: lot of sick leaves that that that's not being recorded. 237 00:12:24,559 --> 00:12:27,160 Speaker 1: So that's why we also have negative productivity. I think, 238 00:12:27,280 --> 00:12:30,440 Speaker 1: I I personally, that's my theory of what's going on. 239 00:12:30,800 --> 00:12:32,800 Speaker 1: And I'm gonna put you on the spot here thirty seconds. 240 00:12:32,960 --> 00:12:38,240 Speaker 1: How much unemployment is too much? Unemployment? Um, you know, 241 00:12:39,320 --> 00:12:42,160 Speaker 1: every kind of unemployment is if bad, even one extra 242 00:12:42,360 --> 00:12:45,880 Speaker 1: job lass is bad. So uh, you know. But however, 243 00:12:46,040 --> 00:12:50,000 Speaker 1: price stability will be important in it ensuring a long expansion. 244 00:12:50,160 --> 00:12:54,080 Speaker 1: As Power said, all right, Anna, good stuff again you guys, 245 00:12:54,400 --> 00:12:56,600 Speaker 1: you and your team. Ana, we're just really early and 246 00:12:56,720 --> 00:13:00,679 Speaker 1: looking increasingly correct with your call with where this you know, 247 00:13:00,679 --> 00:13:03,120 Speaker 1: this natural rate may go here and we'll hear more. 248 00:13:03,640 --> 00:13:06,760 Speaker 1: Fed Chairman Pale tomorrow from Jackson Hole Anna Wong. She's 249 00:13:06,760 --> 00:13:10,080 Speaker 1: the chief OS economist for bloomerk economics, and you know, creaty. 250 00:13:10,080 --> 00:13:11,760 Speaker 1: When she came out with that call, I was like, whoa, 251 00:13:11,840 --> 00:13:13,480 Speaker 1: because the street was at like two and a half 252 00:13:13,520 --> 00:13:15,520 Speaker 1: percent at the time, and she came out with this 253 00:13:15,559 --> 00:13:18,320 Speaker 1: five percent number. And she may be proven right. And 254 00:13:18,320 --> 00:13:19,559 Speaker 1: when all is said and done, you know, one of 255 00:13:19,559 --> 00:13:22,160 Speaker 1: the criticisms of the Federal Reserve right now in economics 256 00:13:22,160 --> 00:13:24,560 Speaker 1: at large simply that they're getting their forecasts wrong. Paul 257 00:13:24,600 --> 00:13:26,760 Speaker 1: I ad venture to say, I think the youth government 258 00:13:26,800 --> 00:13:30,280 Speaker 1: lost Annah Long and that's maybe why. Yes, exactly exactly, 259 00:13:30,320 --> 00:13:36,720 Speaker 1: so we're fortunate to have her there. All right, let's 260 00:13:36,720 --> 00:13:41,600 Speaker 1: go to Amber Fairbanks, portfolio manager for Mirova up in Boston, 261 00:13:42,000 --> 00:13:45,960 Speaker 1: and that makes sense. She's undergraduate from umss Amherston, an 262 00:13:46,040 --> 00:13:49,480 Speaker 1: NBA from Boston College. So all in Boston, go yankees, 263 00:13:49,880 --> 00:13:52,280 Speaker 1: uh Amber, thanks so much for joining us here. What's 264 00:13:52,320 --> 00:13:57,880 Speaker 1: the investment theology focused strategy at your firm? Rova and 265 00:13:58,160 --> 00:14:01,679 Speaker 1: some rather approach this stainable one. We're really looking at 266 00:14:01,720 --> 00:14:06,040 Speaker 1: exploiting market inefficiencies that we see around long term secular trends, 267 00:14:06,120 --> 00:14:08,360 Speaker 1: as well as the belief that the market is really 268 00:14:08,440 --> 00:14:11,280 Speaker 1: underestimating the risk coming from poor e s G practices. 269 00:14:13,080 --> 00:14:15,360 Speaker 1: So let's talk about those E s G practices. I mean, 270 00:14:15,920 --> 00:14:18,000 Speaker 1: to me, it feels like the s G was all 271 00:14:18,120 --> 00:14:21,480 Speaker 1: arraged maybe two years ago when the pandemic first struck, 272 00:14:21,520 --> 00:14:24,240 Speaker 1: for a variety of reasons, um, including how we want 273 00:14:24,240 --> 00:14:26,520 Speaker 1: to really deal with our our footprint. But I'm curious 274 00:14:26,520 --> 00:14:29,440 Speaker 1: about how that's evolved in light of I think the 275 00:14:29,520 --> 00:14:33,400 Speaker 1: recent criticism has gotten. Yeah, I think we've seen some 276 00:14:33,520 --> 00:14:36,240 Speaker 1: recent criticism starting really the beginning of this year. I 277 00:14:36,280 --> 00:14:38,680 Speaker 1: know with the Baron's article that came out. There's a 278 00:14:38,720 --> 00:14:42,840 Speaker 1: similar economists Economist article that came out as well. Um, 279 00:14:42,920 --> 00:14:45,680 Speaker 1: you know, I think that certainly there's there's reasons to 280 00:14:45,760 --> 00:14:48,800 Speaker 1: be looking a little bit closely at E s G 281 00:14:48,800 --> 00:14:51,479 Speaker 1: given the popularity, and I think, you know, the criticism 282 00:14:51,480 --> 00:14:56,160 Speaker 1: contains some brain of truth, particularly around the inconsistent implementation 283 00:14:56,360 --> 00:14:59,120 Speaker 1: of E s G frameworks by investors and kind of 284 00:14:59,160 --> 00:15:01,880 Speaker 1: E s G being used is virtue signaling as opposed 285 00:15:01,880 --> 00:15:04,720 Speaker 1: to really having real world impact. But you know, I 286 00:15:04,720 --> 00:15:08,280 Speaker 1: think really these are effective debating points, but really none 287 00:15:08,280 --> 00:15:12,080 Speaker 1: amounts to anything close to a disqualifying argument. I think, 288 00:15:12,120 --> 00:15:15,160 Speaker 1: really the attention to e FC issues becomes a biduciary 289 00:15:15,240 --> 00:15:19,520 Speaker 1: duty to investors and to company managers and directors because 290 00:15:19,520 --> 00:15:22,120 Speaker 1: of financial materiality. And I think that's the most important 291 00:15:22,240 --> 00:15:25,480 Speaker 1: point is that history has really shown that attention to 292 00:15:25,560 --> 00:15:29,160 Speaker 1: e sc issues it's really increasingly important in the creation 293 00:15:29,240 --> 00:15:31,440 Speaker 1: and preservation of value. And certainly there's done a lot 294 00:15:31,440 --> 00:15:35,560 Speaker 1: of examples like the VP Deepwater Horizon explosion, you know, 295 00:15:35,640 --> 00:15:39,239 Speaker 1: Facebook data privacy, that have really pointed to the importance 296 00:15:39,280 --> 00:15:42,200 Speaker 1: of considering e s G issues um serverally becomes a 297 00:15:42,240 --> 00:15:46,560 Speaker 1: management of intangible issues around brand and reputation, human capital, 298 00:15:46,640 --> 00:15:50,080 Speaker 1: for example. So I think that e s G and 299 00:15:50,120 --> 00:15:54,720 Speaker 1: shareholder capitalism are really fundamentally about good governance. The idea 300 00:15:54,800 --> 00:15:58,480 Speaker 1: that it's kind of about inconsistent implementation. It's certainly that's 301 00:15:58,480 --> 00:16:01,000 Speaker 1: a fair point across some managers, but it really about 302 00:16:01,000 --> 00:16:03,600 Speaker 1: politicizing e s G investing, which I think is what 303 00:16:03,640 --> 00:16:06,760 Speaker 1: we've seen in the media recently. You're kind of conflating 304 00:16:06,800 --> 00:16:10,320 Speaker 1: at virtue signaling and values based investing and really debate 305 00:16:10,360 --> 00:16:14,840 Speaker 1: about wokeism, where really it's just underestimating the changing nature 306 00:16:14,840 --> 00:16:17,960 Speaker 1: of business value creation. Amber give us an example of 307 00:16:18,160 --> 00:16:20,920 Speaker 1: a name that's in your portfolio or something you've recently added, 308 00:16:20,960 --> 00:16:25,120 Speaker 1: and how it might fit into your E s G framework. 309 00:16:26,320 --> 00:16:29,200 Speaker 1: So one of the companies we added UM in December 310 00:16:29,320 --> 00:16:31,800 Speaker 1: last year and then added to more recently is Macado Libre. 311 00:16:32,360 --> 00:16:35,480 Speaker 1: It's an e commerce and fintech company in Latin America, 312 00:16:35,840 --> 00:16:39,000 Speaker 1: especially a really interesting company that the largest e commerce company. 313 00:16:39,000 --> 00:16:40,880 Speaker 1: And I think if you look at the growth of 314 00:16:40,920 --> 00:16:43,400 Speaker 1: e commerce in Latin America, only about six percent of 315 00:16:43,440 --> 00:16:46,040 Speaker 1: retail sales in Latin America are coming from e commerce. 316 00:16:46,400 --> 00:16:49,320 Speaker 1: That compared globally to around eighteen percent. Such a tremendous 317 00:16:49,320 --> 00:16:52,040 Speaker 1: opportunity for growth there. The company has a really strong 318 00:16:52,080 --> 00:16:55,200 Speaker 1: competitive advantage as well. And then within fintech. You know, 319 00:16:55,200 --> 00:16:57,880 Speaker 1: if you look at Latin America, about fifty of adults 320 00:16:57,920 --> 00:17:01,240 Speaker 1: are unbanked. It's really to lead a poverty. To provide 321 00:17:01,240 --> 00:17:05,000 Speaker 1: for academic growth, these people need access to affordable financial 322 00:17:05,000 --> 00:17:07,800 Speaker 1: systems and that's something that Accatto leave I provide. So 323 00:17:07,880 --> 00:17:09,520 Speaker 1: a company that we were able to add to what 324 00:17:09,600 --> 00:17:12,440 Speaker 1: we think is a really attractive valuation. It's certainly a 325 00:17:12,520 --> 00:17:15,640 Speaker 1: growth company UM and I think, you know, it's been 326 00:17:15,720 --> 00:17:18,040 Speaker 1: such a sentiment driven market, particularly in the beginning of 327 00:17:18,119 --> 00:17:20,879 Speaker 1: the year, with growth selling officers sharply. But a company 328 00:17:20,880 --> 00:17:23,840 Speaker 1: that continues to put very very strong fundamental So we 329 00:17:23,960 --> 00:17:26,320 Speaker 1: kept our long term valuation approach and we're able to 330 00:17:26,320 --> 00:17:28,879 Speaker 1: exploit and the short termism that we're seeing in the 331 00:17:28,880 --> 00:17:31,880 Speaker 1: market today. So from an E s G perspective, I mean, 332 00:17:31,960 --> 00:17:34,720 Speaker 1: just shut some light for me on this Mercatto Libre story, 333 00:17:34,760 --> 00:17:37,439 Speaker 1: because for our international audience who aren't perhaps it's familiar. 334 00:17:37,480 --> 00:17:39,000 Speaker 1: The way I like to think about and Paul correct 335 00:17:39,000 --> 00:17:40,679 Speaker 1: me if I'm wrong here, is that it's kind of 336 00:17:40,680 --> 00:17:44,000 Speaker 1: the Amazon of Latin America to some extent the eBay 337 00:17:44,000 --> 00:17:47,760 Speaker 1: even if you will, I'm curious why the investing case 338 00:17:47,800 --> 00:17:50,440 Speaker 1: from Ricatto Libre differs from that on Amazon when it 339 00:17:50,480 --> 00:17:53,200 Speaker 1: comes to an E s G basis. So it was 340 00:17:53,280 --> 00:17:56,040 Speaker 1: Amazon has been a lot of socialities that have us concerns. 341 00:17:56,080 --> 00:17:59,000 Speaker 1: You have our treatment of workers, for example, as well 342 00:17:59,040 --> 00:18:02,439 Speaker 1: as their men Somemen, a third party manufacturing, and so 343 00:18:02,600 --> 00:18:05,640 Speaker 1: it's really those social issues that have us concerned around Amazon. 344 00:18:05,680 --> 00:18:09,240 Speaker 1: I think, you know, from a fundamental perspective, from a 345 00:18:09,280 --> 00:18:12,840 Speaker 1: secular trend perspectives, a company is certainly attractive, but it's 346 00:18:12,880 --> 00:18:17,240 Speaker 1: really the idea that eventually, over time, those issues, if 347 00:18:17,240 --> 00:18:19,960 Speaker 1: not managed to correctly, have a financial impact on the company, 348 00:18:20,240 --> 00:18:22,400 Speaker 1: and I think we've seen that with companies like Amazon 349 00:18:22,440 --> 00:18:25,360 Speaker 1: to a certain extent, but more companies like Facebook for example. 350 00:18:25,520 --> 00:18:30,480 Speaker 1: In the alphabet. So Mercedes Benz is also another name 351 00:18:30,640 --> 00:18:34,080 Speaker 1: here for you guys, give us the case there for 352 00:18:34,520 --> 00:18:38,560 Speaker 1: Mercedes Benz. So we add a Mercedes to the portfolio 353 00:18:38,680 --> 00:18:41,400 Speaker 1: in March's a company that has a really strong plan 354 00:18:41,520 --> 00:18:45,240 Speaker 1: orund the electrification of vehicles. They're targeting fifty of sales 355 00:18:45,280 --> 00:18:49,520 Speaker 1: from EPs by the year and then from ebes By 356 00:18:50,600 --> 00:18:53,240 Speaker 1: and they put forty billion euros and cappex to really 357 00:18:53,240 --> 00:18:56,440 Speaker 1: tool factories and step up software efforts and so really 358 00:18:56,480 --> 00:18:58,520 Speaker 1: a strong plan that we think is addressing that growth 359 00:18:58,560 --> 00:19:02,440 Speaker 1: towards electric vehicle. It's a company that we bought after 360 00:19:02,480 --> 00:19:05,280 Speaker 1: the rush of Ukraine conflicts a lot of concerns in 361 00:19:05,320 --> 00:19:08,320 Speaker 1: the short term around supply chain, but I think if 362 00:19:08,320 --> 00:19:10,439 Speaker 1: you look at the long term value of Mercedes, it's 363 00:19:10,520 --> 00:19:13,600 Speaker 1: very much intact stocks trading at a PETE multiple of 364 00:19:13,720 --> 00:19:16,040 Speaker 1: less than five times, has about a thirty percent great 365 00:19:16,040 --> 00:19:18,760 Speaker 1: cash flow yield. I think it's a very attractive stock 366 00:19:18,800 --> 00:19:23,960 Speaker 1: here today. So for your clients, do your clients, for 367 00:19:24,080 --> 00:19:27,080 Speaker 1: your funds to date? Is the E s G part 368 00:19:27,160 --> 00:19:30,600 Speaker 1: of your offering. The primary driver why they're with you 369 00:19:30,600 --> 00:19:34,960 Speaker 1: guys as opposed to somebody else, is that your typical client. 370 00:19:36,800 --> 00:19:38,679 Speaker 1: You know, I would say it really comes down to 371 00:19:38,760 --> 00:19:41,320 Speaker 1: performance over the long term, and I think that that's 372 00:19:41,440 --> 00:19:44,240 Speaker 1: really what's driving the growth of our assets, where you know, 373 00:19:44,240 --> 00:19:46,840 Speaker 1: they've grown tremendous new over the last several years. And 374 00:19:46,880 --> 00:19:48,800 Speaker 1: I think that that's at the end of the day, 375 00:19:48,800 --> 00:19:51,400 Speaker 1: what's going to continue to drive E s G fun 376 00:19:51,480 --> 00:19:54,280 Speaker 1: flu um. It's it's really that integration of E s 377 00:19:54,320 --> 00:19:57,440 Speaker 1: G to really help us understand company culture, for example, 378 00:19:57,880 --> 00:20:00,480 Speaker 1: help us understand the company management team in really how 379 00:20:00,520 --> 00:20:03,560 Speaker 1: companies are addressing both risks and opportunities around E s G, 380 00:20:03,880 --> 00:20:06,159 Speaker 1: which we think is very material in the creation or 381 00:20:06,160 --> 00:20:09,040 Speaker 1: destruction of a company value. And we're talking to us 382 00:20:09,080 --> 00:20:10,840 Speaker 1: about data because you know, when I go do my 383 00:20:10,880 --> 00:20:13,800 Speaker 1: financial analysis, uh, you know, I can look at income statements, 384 00:20:13,840 --> 00:20:17,400 Speaker 1: balance sheets, casual statements, they're all audited. I kind of 385 00:20:17,480 --> 00:20:19,280 Speaker 1: get a sense I can compare and do all that 386 00:20:19,359 --> 00:20:21,879 Speaker 1: kind of work. Uh. And Bloomberg actually one of the 387 00:20:21,880 --> 00:20:24,840 Speaker 1: most widely used functions on the Bloomber terminals FA for 388 00:20:24,880 --> 00:20:28,720 Speaker 1: financial analysis. Talk to us about the data that's available 389 00:20:28,760 --> 00:20:31,840 Speaker 1: to do e s G analysis. I've heard that it's 390 00:20:31,920 --> 00:20:36,919 Speaker 1: it's not nearly as robust as financial data is. Where's 391 00:20:36,920 --> 00:20:39,760 Speaker 1: the industry there and what could be done? Yeah, I 392 00:20:39,760 --> 00:20:42,480 Speaker 1: would definitely agree it's not as robust as you can 393 00:20:42,600 --> 00:20:45,320 Speaker 1: find in balance seats and income statements as well as 394 00:20:45,600 --> 00:20:48,879 Speaker 1: on Bloomberg. But I think you know it's really because 395 00:20:48,880 --> 00:20:52,240 Speaker 1: there's a subject subjective element right now still at the 396 00:20:52,240 --> 00:20:55,119 Speaker 1: e s G. There's also not a lot of transparency 397 00:20:55,160 --> 00:20:58,120 Speaker 1: when you're using a lot of these third party rating agencies. 398 00:20:58,400 --> 00:21:01,200 Speaker 1: They're relying a lot on the company to closures, which 399 00:21:01,200 --> 00:21:03,080 Speaker 1: can often lead to a large cat bias where you 400 00:21:03,119 --> 00:21:05,240 Speaker 1: have companies that are disclosing a lot around e s 401 00:21:05,280 --> 00:21:08,399 Speaker 1: G data. Um So, for us, it's really about digging deeper. 402 00:21:08,440 --> 00:21:10,320 Speaker 1: We've really built out our own e s G team 403 00:21:10,400 --> 00:21:12,400 Speaker 1: so we can take a much closer look at companies. 404 00:21:12,840 --> 00:21:15,240 Speaker 1: Um So. I think right now there's still an evolution 405 00:21:15,320 --> 00:21:18,919 Speaker 1: with regards to the third party data providers. Standardization of 406 00:21:18,920 --> 00:21:21,639 Speaker 1: that data I think will help over time. We're starting 407 00:21:21,640 --> 00:21:24,879 Speaker 1: to see that regulation, I think, which will be beneficial. Alright, 408 00:21:24,880 --> 00:21:28,560 Speaker 1: good stuff, Appreciate getting your thoughts. Amber Fairbanks, portfolio manager 409 00:21:28,640 --> 00:21:32,119 Speaker 1: for the firm Arrova talking about E S g uh investing. 410 00:21:35,840 --> 00:21:38,000 Speaker 1: All right, let's talk about the private credit business. This 411 00:21:38,080 --> 00:21:40,639 Speaker 1: is a business I like. I like the yields that 412 00:21:40,720 --> 00:21:43,680 Speaker 1: investors can get there. Um, and a lot of capitals 413 00:21:43,680 --> 00:21:46,080 Speaker 1: flowing to that biz. John Klein, he's a managing director 414 00:21:46,119 --> 00:21:49,760 Speaker 1: and co portfolio manager private credit at the firm New 415 00:21:49,760 --> 00:21:53,400 Speaker 1: Mountain Finance Corporation. John, thanks so much for joining us here. 416 00:21:53,800 --> 00:21:56,399 Speaker 1: Talk to us about the state year to date of 417 00:21:56,520 --> 00:21:59,840 Speaker 1: private credit. His boy, my equity portfolio has gotten crushed. 418 00:22:00,200 --> 00:22:03,960 Speaker 1: Even my corporate bond, my treasuries, they were crushed. Um 419 00:22:04,200 --> 00:22:07,960 Speaker 1: talked us about the private credit market. Sure, well, good 420 00:22:08,040 --> 00:22:09,760 Speaker 1: morning and thanks for having me on the show. I 421 00:22:09,840 --> 00:22:12,760 Speaker 1: appreciate it. And Um, when I think about the private 422 00:22:12,800 --> 00:22:15,080 Speaker 1: credit market, I really think it's one of the best 423 00:22:15,080 --> 00:22:18,159 Speaker 1: performing asset classes that that that we observe here at 424 00:22:18,160 --> 00:22:20,560 Speaker 1: New Mountain. And I think you're right. I mean, if 425 00:22:20,560 --> 00:22:24,160 Speaker 1: you own normal fixed income that has true fixed interest rates, 426 00:22:24,760 --> 00:22:27,960 Speaker 1: you've definitely gotten hurt this year. When you think about 427 00:22:27,960 --> 00:22:30,240 Speaker 1: every equity market index that I can think of, except 428 00:22:30,280 --> 00:22:34,520 Speaker 1: for maybe energy, it's down. Meanwhile, in private credit, we 429 00:22:34,560 --> 00:22:37,760 Speaker 1: really benefit from the fact that we have floating interest rates. 430 00:22:38,000 --> 00:22:41,119 Speaker 1: You know, good industry selection and uh and that's been 431 00:22:41,119 --> 00:22:43,360 Speaker 1: a real tail win for us. But the biggest drivers 432 00:22:43,400 --> 00:22:46,320 Speaker 1: floating interest rates. And when you have floating interest rates 433 00:22:46,320 --> 00:22:49,600 Speaker 1: in a rising rate environment, we pay coupons that rise 434 00:22:49,800 --> 00:22:51,840 Speaker 1: right in line with the FED increases and that's very 435 00:22:51,880 --> 00:22:56,080 Speaker 1: important for our investors. So simplify this for me a 436 00:22:56,119 --> 00:22:58,639 Speaker 1: little bit when it comes to perhaps some of the 437 00:22:58,640 --> 00:23:00,560 Speaker 1: things that the market is pricing in here a very 438 00:23:00,640 --> 00:23:05,080 Speaker 1: hawkish um standard, at least for Charman Powell tomorrow. How 439 00:23:05,080 --> 00:23:09,680 Speaker 1: does that affect you? So when we think about our portfolios, 440 00:23:09,720 --> 00:23:12,840 Speaker 1: and the most visible portfolio that we manage, his new 441 00:23:12,840 --> 00:23:16,240 Speaker 1: Mountain Finance Corporation, which is a publicly traded b DC 442 00:23:16,840 --> 00:23:19,199 Speaker 1: you can buy and sell shares every day. When we 443 00:23:19,240 --> 00:23:23,280 Speaker 1: think about that portfolio, you know, it's floating rate loans. 444 00:23:23,440 --> 00:23:25,800 Speaker 1: So our average loan is going to have a spread 445 00:23:25,800 --> 00:23:29,520 Speaker 1: of about uh lieb or or SOF plus six hundred 446 00:23:29,840 --> 00:23:33,919 Speaker 1: and essentially UM. As the FED raises rates, those loans 447 00:23:33,960 --> 00:23:37,240 Speaker 1: are tied to the rate increases in the base rate, 448 00:23:37,600 --> 00:23:40,280 Speaker 1: and so a loan that might have yielded six and 449 00:23:40,320 --> 00:23:42,399 Speaker 1: a half percent at the beginning of the beginning of 450 00:23:42,400 --> 00:23:44,919 Speaker 1: the year is now roughly eight and a half percent, 451 00:23:45,440 --> 00:23:47,439 Speaker 1: and and if and if if rates keep going up, 452 00:23:47,480 --> 00:23:49,840 Speaker 1: we could see we could see our loans yielding ten 453 00:23:50,000 --> 00:23:52,040 Speaker 1: ten percent by the end of the year. And so 454 00:23:52,080 --> 00:23:56,280 Speaker 1: that's very that's a very powerful tail wind for our investors. John, 455 00:23:56,280 --> 00:23:58,639 Speaker 1: what are some of the sectors that you guys are 456 00:23:58,640 --> 00:24:02,720 Speaker 1: favoring right now in your portfolio? So so, yeah, that's 457 00:24:02,720 --> 00:24:05,040 Speaker 1: a great question. You know, one thing we really like 458 00:24:05,119 --> 00:24:07,560 Speaker 1: about our strategy, and I think the strategy is mirrored 459 00:24:07,560 --> 00:24:10,760 Speaker 1: by some other good private credit funds, is that we 460 00:24:10,800 --> 00:24:15,280 Speaker 1: really focus on good, defensive growth industries. We want to 461 00:24:15,320 --> 00:24:19,919 Speaker 1: invest in businesses that have predictability, they have natural tail winds, 462 00:24:19,960 --> 00:24:23,840 Speaker 1: they have growth to their business models, and so we 463 00:24:23,880 --> 00:24:27,960 Speaker 1: really gear our portfolio towards those those sectors. And I 464 00:24:28,040 --> 00:24:30,480 Speaker 1: think that's very valuable because when you're in a difficult 465 00:24:30,480 --> 00:24:33,480 Speaker 1: economic environment, the last thing you want in your portfolio 466 00:24:34,160 --> 00:24:40,040 Speaker 1: is volatile industries, UH, cyclical industries or secularly challenged industries, 467 00:24:40,240 --> 00:24:42,919 Speaker 1: and those are the those are the types of companies 468 00:24:43,000 --> 00:24:45,520 Speaker 1: we really seek to avoid. John has a lot of 469 00:24:45,760 --> 00:24:48,760 Speaker 1: talk that if we're not intercession already, that we're pretty 470 00:24:48,840 --> 00:24:50,760 Speaker 1: darn close, and that's something that people need to put 471 00:24:50,800 --> 00:24:54,560 Speaker 1: into their models probably for next year. How do you 472 00:24:54,600 --> 00:25:00,679 Speaker 1: guys think about your portfolio in a recession scenario. So 473 00:25:00,720 --> 00:25:02,640 Speaker 1: in a recession scenario, I think it just ties into 474 00:25:02,640 --> 00:25:04,520 Speaker 1: a lot of the things that I just said, which 475 00:25:04,600 --> 00:25:08,440 Speaker 1: is we want businesses, uh that just have that great predictability. 476 00:25:08,520 --> 00:25:12,480 Speaker 1: So we focus on software businesses that sell software every 477 00:25:12,560 --> 00:25:15,320 Speaker 1: year to the same customers and have high retention. We 478 00:25:15,440 --> 00:25:18,960 Speaker 1: like database companies that provide much much must have data 479 00:25:19,160 --> 00:25:23,159 Speaker 1: to their customers, not unlike Bloomberg. And really what we 480 00:25:23,200 --> 00:25:26,640 Speaker 1: don't want to be doing intercessionary environment is we don't 481 00:25:26,680 --> 00:25:29,399 Speaker 1: want to be taking views on on how many f 482 00:25:29,520 --> 00:25:31,600 Speaker 1: one fifty pickup trucks are going to be built in 483 00:25:31,600 --> 00:25:34,560 Speaker 1: Detroit next year, or what housing starts are gonna look 484 00:25:34,560 --> 00:25:37,400 Speaker 1: like in Arizona. We just think that's very tough to predict. 485 00:25:37,600 --> 00:25:39,879 Speaker 1: And if you're a credit investor, we get paid for 486 00:25:39,960 --> 00:25:43,480 Speaker 1: delivering consistency of return, making sure that we were able 487 00:25:43,520 --> 00:25:46,879 Speaker 1: to pocket our coupons and get principal when the maturities do. 488 00:25:47,080 --> 00:25:50,000 Speaker 1: So those defensive industries are really where we like to stay. 489 00:25:51,760 --> 00:25:54,399 Speaker 1: So let's go back Macro here because that's my my 490 00:25:54,480 --> 00:25:57,280 Speaker 1: safe space. As Paul knows, I I like to do that, 491 00:25:57,359 --> 00:26:00,280 Speaker 1: I'm curious about simply the implication to you when comes 492 00:26:00,320 --> 00:26:02,879 Speaker 1: to liquidity and how that affects private credit, it kind 493 00:26:02,880 --> 00:26:05,600 Speaker 1: of feels like it's almost marching to the beat of 494 00:26:05,640 --> 00:26:08,320 Speaker 1: its own drum. But liquidity is an issue that is 495 00:26:08,359 --> 00:26:11,119 Speaker 1: hitting the public markets very well. If there's a lag 496 00:26:11,359 --> 00:26:17,400 Speaker 1: for private credit, walk us through the domino effect there. Well, 497 00:26:17,400 --> 00:26:19,560 Speaker 1: I guess you know, um, so my safe spade is 498 00:26:19,600 --> 00:26:22,560 Speaker 1: bondons up bottens up credit analysis. But but but when 499 00:26:22,560 --> 00:26:27,000 Speaker 1: I think about, you know, our overall our industry, essentially, 500 00:26:27,000 --> 00:26:29,320 Speaker 1: when I think about private credit and liquidity that we 501 00:26:29,400 --> 00:26:32,040 Speaker 1: have is we we just because of floating rates, we're 502 00:26:32,040 --> 00:26:35,040 Speaker 1: attracting a lot of investor interests, a lot of capital 503 00:26:35,080 --> 00:26:39,160 Speaker 1: flows that really are attracted to that floating rate secure 504 00:26:39,240 --> 00:26:42,880 Speaker 1: debt product, and so we basically take the investor inflows 505 00:26:42,920 --> 00:26:45,800 Speaker 1: that we get into that product and then we're able 506 00:26:45,840 --> 00:26:49,480 Speaker 1: to lend to our financial sponsor clients. So we feel 507 00:26:49,520 --> 00:26:52,520 Speaker 1: good about the overall liquidity in the market, and in general, 508 00:26:52,680 --> 00:26:55,800 Speaker 1: we see good demand for our loans because the syndicated 509 00:26:55,880 --> 00:26:59,320 Speaker 1: market does have liquidity challenges, and so we can really 510 00:26:59,359 --> 00:27:02,280 Speaker 1: prove to be a a good solution for um for 511 00:27:02,320 --> 00:27:06,080 Speaker 1: folks that want to buy high quality, defensive businesses. UM. 512 00:27:06,760 --> 00:27:09,080 Speaker 1: And then that's why we think about it. John, just 513 00:27:09,280 --> 00:27:12,280 Speaker 1: thirty seconds, Just how's the deal flow these days with 514 00:27:12,359 --> 00:27:16,160 Speaker 1: your sponsors? So so deal flow is good? I mean 515 00:27:16,200 --> 00:27:19,400 Speaker 1: when when when we think back to two one, deal 516 00:27:19,440 --> 00:27:21,600 Speaker 1: flow is at a record and I think, you know, 517 00:27:21,600 --> 00:27:24,359 Speaker 1: we're we've come off that record just because the overall 518 00:27:24,359 --> 00:27:27,480 Speaker 1: economic environment is less strong. But I think our sponsor 519 00:27:27,520 --> 00:27:30,919 Speaker 1: clients do see good bargains now that the stock market 520 00:27:30,960 --> 00:27:35,159 Speaker 1: has declined and valuations have settled, and so UM, If 521 00:27:35,280 --> 00:27:37,760 Speaker 1: if our clients see bargains and the ability to buy 522 00:27:37,800 --> 00:27:41,960 Speaker 1: good businesses at at better valuations, UM, we think there's 523 00:27:41,960 --> 00:27:44,919 Speaker 1: a good opportunity for for solid deal flow going forward, 524 00:27:45,160 --> 00:27:47,159 Speaker 1: even if we don't hit deal flow levels that we 525 00:27:47,200 --> 00:27:49,920 Speaker 1: saw in two thousand one. All right, John, thanks so 526 00:27:50,000 --> 00:27:52,520 Speaker 1: much for taking the time. Really appreciate getting your perspective here. 527 00:27:52,600 --> 00:27:55,480 Speaker 1: John Klein, He's a managing director and co portfolio manager 528 00:27:55,520 --> 00:28:02,399 Speaker 1: of Private Credit, the firm's new Mountain Finance Corporation. Thanks 529 00:28:02,440 --> 00:28:05,879 Speaker 1: for listening to the Bloomberg Markets podcast. You can subscribe 530 00:28:05,920 --> 00:28:09,680 Speaker 1: and listen to interviews with Apple Podcasts or whatever podcast 531 00:28:09,680 --> 00:28:13,240 Speaker 1: platform you prefer. I'm Matt Miller, I'm on Twitter at 532 00:28:13,280 --> 00:28:17,080 Speaker 1: Matt Miller three. On Fall Sweeney, I'm on Twitter at 533 00:28:17,119 --> 00:28:19,960 Speaker 1: pt Sweeney Before the podcast. You can always catch us 534 00:28:20,000 --> 00:28:21,400 Speaker 1: worldwide at Bloomberg Radio