1 00:00:00,280 --> 00:00:11,200 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. This is Bloomberg Intelligence 2 00:00:11,320 --> 00:00:13,400 Speaker 1: with Alex Steel and Paul Sweeney. 3 00:00:13,520 --> 00:00:16,720 Speaker 2: The real AP performance has been in US corporate high yield. 4 00:00:16,920 --> 00:00:19,280 Speaker 3: Are the companies lean enough? Have they trimmed all the fats? 5 00:00:19,320 --> 00:00:22,959 Speaker 2: The semiconductor business is a really cyclical business. 6 00:00:22,600 --> 00:00:26,320 Speaker 1: Breaking market headlines and corporate news from across the globe. 7 00:00:26,360 --> 00:00:28,800 Speaker 3: Do investors like the M and A that we've seen? 8 00:00:29,000 --> 00:00:31,960 Speaker 2: These are two big time blue chip companies. 9 00:00:32,240 --> 00:00:35,640 Speaker 3: Window between the peak and cunt changing super fast. 10 00:00:35,880 --> 00:00:40,920 Speaker 1: Bloomberg Intelligence with Alex Steele and Paul Sweeney on Bloomberg Radio. 11 00:00:42,920 --> 00:00:45,480 Speaker 2: Today's Bloomberg Intelligence Show, we dig inside the big business 12 00:00:45,520 --> 00:00:47,600 Speaker 2: stories impacting Wall Street and the global markets. 13 00:00:47,680 --> 00:00:49,880 Speaker 3: Each and every week we provide dep research and data 14 00:00:49,880 --> 00:00:51,680 Speaker 3: on some of the two thousand companies and one hundred 15 00:00:51,680 --> 00:00:54,080 Speaker 3: and thirty industries our analysts cover worldwide. 16 00:00:54,200 --> 00:00:56,600 Speaker 2: Today, we'll look at the growing dominance of private credit 17 00:00:56,600 --> 00:00:58,920 Speaker 2: as traditional banks face stricter regulations. 18 00:00:58,960 --> 00:01:01,800 Speaker 3: Plus we'll discuss the ball role of quantitative finance and 19 00:01:01,920 --> 00:01:04,120 Speaker 3: artificial intelligence and asset management. 20 00:01:04,440 --> 00:01:06,440 Speaker 2: And we begin with some of the best interviews from 21 00:01:06,440 --> 00:01:09,280 Speaker 2: our live broadcast this week at Bloomberg invest There, we 22 00:01:09,360 --> 00:01:12,520 Speaker 2: talked with leaders in asset management, banking, wealth and private 23 00:01:12,520 --> 00:01:14,760 Speaker 2: markets in the heart of New York's Financial district. 24 00:01:14,920 --> 00:01:17,200 Speaker 3: For our first conversation, we are joined by Mark Mahaney, 25 00:01:17,240 --> 00:01:20,479 Speaker 3: Senior Managing director at Evercore ISI. We discussed the state 26 00:01:20,480 --> 00:01:23,280 Speaker 3: of the tech sector and how artificial intelligence is reshaping 27 00:01:23,319 --> 00:01:26,679 Speaker 3: the industry. We first asked Mark about how AI compares 28 00:01:26,840 --> 00:01:28,080 Speaker 3: to the launch of the Internet. 29 00:01:28,520 --> 00:01:31,720 Speaker 4: I don't know if it will be that transformative, but 30 00:01:32,720 --> 00:01:37,360 Speaker 4: the amount of money that's going into them, paid by companies, 31 00:01:37,440 --> 00:01:41,479 Speaker 4: put in by companies that have plenty of cash is 32 00:01:41,520 --> 00:01:43,640 Speaker 4: something of a tell. And then we've seen a lot 33 00:01:43,680 --> 00:01:46,399 Speaker 4: of examples of what I call OURAI, you know ROI 34 00:01:46,520 --> 00:01:50,240 Speaker 4: return on investment ROAI. So you know, we're staring at 35 00:01:50,280 --> 00:01:52,480 Speaker 4: it right now. Look at what's happened to Meta in 36 00:01:52,520 --> 00:01:54,760 Speaker 4: the last two and a half years. How they've turned 37 00:01:54,760 --> 00:02:00,360 Speaker 4: around their business both and they've dramatically improved their services 38 00:02:00,400 --> 00:02:02,880 Speaker 4: for customers that's you and me as consumers. Our news 39 00:02:02,880 --> 00:02:05,280 Speaker 4: feed has gotten to become more relevant because they've used 40 00:02:05,280 --> 00:02:09,600 Speaker 4: AI to do better targeting, better recommendations. But also for advertisers, 41 00:02:09,639 --> 00:02:12,960 Speaker 4: their return on ads ben ROAs has risen because the 42 00:02:13,000 --> 00:02:16,640 Speaker 4: campaigns have become better targeted, better management, better managed. So 43 00:02:16,840 --> 00:02:20,840 Speaker 4: I've seen a couple of really great ROAI examples and 44 00:02:20,880 --> 00:02:23,919 Speaker 4: so I'm not sure it's transformative, but it's definitely improving 45 00:02:23,960 --> 00:02:25,959 Speaker 4: the performance of these companies, and it shows up in 46 00:02:26,000 --> 00:02:26,480 Speaker 4: the P and L. 47 00:02:26,520 --> 00:02:26,720 Speaker 5: Two. 48 00:02:26,880 --> 00:02:28,639 Speaker 4: I think you can also look at Google, twenty five 49 00:02:28,639 --> 00:02:31,280 Speaker 4: percent of their code is now written by AI. Imagine 50 00:02:31,320 --> 00:02:34,079 Speaker 4: the productivity improvement associated with that. And then Amazon is 51 00:02:34,120 --> 00:02:37,280 Speaker 4: talking about twenty five percent lower cost to serve in 52 00:02:37,320 --> 00:02:40,120 Speaker 4: its most advanced distribution centers. I mean, that's why their 53 00:02:40,120 --> 00:02:41,600 Speaker 4: margins are going to continue to go up. So you're 54 00:02:41,600 --> 00:02:43,280 Speaker 4: seeing it in a P and L. So I think 55 00:02:43,280 --> 00:02:45,920 Speaker 4: it's actually a major productivity improvement, and I think this 56 00:02:45,960 --> 00:02:47,120 Speaker 4: is going to play out for years. 57 00:02:47,840 --> 00:02:51,320 Speaker 3: When do you think we're going to really understand how 58 00:02:51,560 --> 00:02:55,359 Speaker 3: inferencing is going to impact us and companies? And like, 59 00:02:55,400 --> 00:02:57,000 Speaker 3: when are you going to get me to buy in 60 00:02:57,000 --> 00:02:58,040 Speaker 3: to an AI story? 61 00:02:59,040 --> 00:03:01,320 Speaker 4: Well, I tried to lay out couple of examples already 62 00:03:01,480 --> 00:03:03,960 Speaker 4: of where these companies are deploying AI and machine learning, 63 00:03:03,960 --> 00:03:06,000 Speaker 4: and they have been for quite some time. We've just 64 00:03:06,080 --> 00:03:09,800 Speaker 4: had a step up, like a hockey stick improvement. You 65 00:03:09,880 --> 00:03:14,080 Speaker 4: just mentioned Kenda hockey stick inflection up in productivity gains 66 00:03:14,120 --> 00:03:16,600 Speaker 4: because with these companies. So I'm sorry, I think we're 67 00:03:16,600 --> 00:03:18,400 Speaker 4: already starting to see it, and I think we're seeing 68 00:03:18,400 --> 00:03:18,639 Speaker 4: it in it. 69 00:03:18,880 --> 00:03:20,760 Speaker 3: Why I see it, I mean maybe my news feed, 70 00:03:20,840 --> 00:03:23,600 Speaker 3: but well I pay for it. 71 00:03:24,360 --> 00:03:27,160 Speaker 4: Well, you want some really specific product examples, I got 72 00:03:27,160 --> 00:03:28,079 Speaker 4: a really fun one for you. 73 00:03:28,200 --> 00:03:29,079 Speaker 3: Okay, into it. 74 00:03:29,240 --> 00:03:31,720 Speaker 4: You want to learn languages, There's this wonderful app called 75 00:03:31,800 --> 00:03:34,040 Speaker 4: dual Lingo. You want to really learn a language, pay 76 00:03:34,120 --> 00:03:36,360 Speaker 4: up for dual Lingo Max, where you can use an 77 00:03:36,400 --> 00:03:39,520 Speaker 4: AI generated bot to actually practice your French, your Spanish, 78 00:03:39,600 --> 00:03:42,680 Speaker 4: your German, your Russian, whatever we need to learn these days. Anyway, 79 00:03:43,400 --> 00:03:44,640 Speaker 4: and I think you're going to see more of these 80 00:03:44,680 --> 00:03:47,080 Speaker 4: kind of little one off examples. But you know, from 81 00:03:47,120 --> 00:03:51,840 Speaker 4: a company's perspective, anything that produces internal productivity, improves relations 82 00:03:51,840 --> 00:03:54,480 Speaker 4: with suppliers or customers. I mean, all of that's I 83 00:03:54,520 --> 00:03:57,400 Speaker 4: don't think there's one. I don't think there's one AI 84 00:03:57,480 --> 00:03:59,240 Speaker 4: revenue build. But you'll see a couple of products that 85 00:03:59,280 --> 00:04:02,080 Speaker 4: wouldn't exist, And they do a Lingle example as one 86 00:04:02,200 --> 00:04:04,840 Speaker 4: that wouldn't simply wouldn't exist if you didn't have AI. 87 00:04:05,280 --> 00:04:09,200 Speaker 2: How about for Google and a traditional search business is 88 00:04:09,280 --> 00:04:11,720 Speaker 2: AI a threat to Google or not. 89 00:04:12,360 --> 00:04:15,320 Speaker 4: Google just put out a blog that said that because 90 00:04:15,400 --> 00:04:23,279 Speaker 4: of AI overviews that they're actually seeing more commercial search queries. Really, 91 00:04:23,560 --> 00:04:27,159 Speaker 4: that's that should raise all of our eyes. So, and 92 00:04:27,200 --> 00:04:28,640 Speaker 4: I guess I'm not at the end of the day, 93 00:04:28,720 --> 00:04:32,039 Speaker 4: not surprise. Google is a company that just consistently improved 94 00:04:32,040 --> 00:04:34,560 Speaker 4: the product, made the search results faster and faster and 95 00:04:34,600 --> 00:04:37,920 Speaker 4: more relevant. This just took that up a notch. And so, yeah, 96 00:04:37,960 --> 00:04:40,760 Speaker 4: if they can get you the result you want more quickly, 97 00:04:41,360 --> 00:04:44,240 Speaker 4: especially if it's leading to more commercial searches, Google is 98 00:04:44,240 --> 00:04:45,919 Speaker 4: the one company in the world that knows how to 99 00:04:45,960 --> 00:04:47,240 Speaker 4: monetize commercial searches. 100 00:04:47,520 --> 00:04:51,159 Speaker 3: What do you think is the biggest misconception about AI, 101 00:04:51,400 --> 00:04:54,880 Speaker 3: Whether it's like what investors thing, what's priced into the stock, 102 00:04:55,000 --> 00:04:55,960 Speaker 3: or justconceptually. 103 00:04:57,040 --> 00:04:59,920 Speaker 4: I think the biggest mistake misconception probably occurred when Deep 104 00:05:00,320 --> 00:05:02,760 Speaker 4: came out and there was concern that this would be 105 00:05:02,800 --> 00:05:06,680 Speaker 4: highly disruptive for the hyperscalers. I actually took the exact 106 00:05:06,760 --> 00:05:10,520 Speaker 4: opposite view, especially if you're at the application layer, and 107 00:05:10,880 --> 00:05:15,040 Speaker 4: because the infrastructure potentially just got a lot cheaper, So 108 00:05:15,080 --> 00:05:17,279 Speaker 4: you're going to all that money that you've spent on Capex, 109 00:05:17,279 --> 00:05:19,479 Speaker 4: You're going to get a better return. That money wasn't wasted, 110 00:05:19,520 --> 00:05:21,760 Speaker 4: You're going to get a better return than you would 111 00:05:21,760 --> 00:05:24,239 Speaker 4: have had in the past. So I think that's probably 112 00:05:24,240 --> 00:05:26,239 Speaker 4: the biggest recent misconception I've seen. 113 00:05:26,520 --> 00:05:29,839 Speaker 2: For Meta It's had a great turnaround. As you talked 114 00:05:29,839 --> 00:05:34,120 Speaker 2: about what percentage of that turnaround is simply cost cutting 115 00:05:34,640 --> 00:05:38,200 Speaker 2: versus maybe just stepping away from the metaverse discussion somewhat. 116 00:05:39,080 --> 00:05:41,520 Speaker 4: I think it's two or three things. Stepping away from metaverse, 117 00:05:41,800 --> 00:05:45,159 Speaker 4: focusing on the year of efficiency that Zuckerberg talked about 118 00:05:45,200 --> 00:05:47,080 Speaker 4: the beginning of twenty three and now it's become the 119 00:05:47,160 --> 00:05:50,520 Speaker 4: years of efficiency. There has been a mind shift at 120 00:05:50,520 --> 00:05:53,719 Speaker 4: Silicon Valley. It's not growth at all costs is much 121 00:05:53,760 --> 00:05:55,880 Speaker 4: more of a focus on So there's a cultural shift 122 00:05:55,920 --> 00:05:58,160 Speaker 4: I think is probably good. These companies are going through 123 00:05:58,160 --> 00:06:02,159 Speaker 4: their middle life stage is not crisis, but stages, and 124 00:06:02,200 --> 00:06:04,120 Speaker 4: as they do that, they shouldn't be They should be 125 00:06:04,120 --> 00:06:06,840 Speaker 4: spending much less aggressively on growth. They should be focused 126 00:06:06,839 --> 00:06:08,960 Speaker 4: more and profitability than they are. But then the tie 127 00:06:08,960 --> 00:06:14,000 Speaker 4: into AI is their developers can produce more code with 128 00:06:14,120 --> 00:06:16,400 Speaker 4: fewer developers. It's not like they need to cut people 129 00:06:16,440 --> 00:06:19,520 Speaker 4: from this point on, but they can grow, They can 130 00:06:19,520 --> 00:06:22,560 Speaker 4: sustain growth with less need to add headcount than they 131 00:06:22,560 --> 00:06:23,239 Speaker 4: did in the past. 132 00:06:23,680 --> 00:06:26,760 Speaker 2: Our thanks to Mark Mahaney, Senior managing director at Evercore, I. 133 00:06:26,920 --> 00:06:28,920 Speaker 3: S I saying with Bloomberg and Bez Paul and I 134 00:06:28,920 --> 00:06:31,480 Speaker 3: also spoke with Katie Fogerty, chief financial officer at the 135 00:06:31,480 --> 00:06:34,839 Speaker 3: Burger chain Shake Shack, and we discussed the company's growth strategy, 136 00:06:34,880 --> 00:06:36,840 Speaker 3: pricing dynamics, and expansion plans. 137 00:06:37,000 --> 00:06:39,440 Speaker 2: We're first to ask Katie about the company's strategy and 138 00:06:39,480 --> 00:06:42,080 Speaker 2: who the consumer is at shay Check these days. 139 00:06:42,400 --> 00:06:44,800 Speaker 6: We have this amazing real estate strategy, and what we've 140 00:06:44,800 --> 00:06:49,360 Speaker 6: done is we've put these great community gathering places in 141 00:06:49,440 --> 00:06:52,400 Speaker 6: a lot of these you know, great communities, and where 142 00:06:52,440 --> 00:06:54,600 Speaker 6: we have attracted is just really kind of more of 143 00:06:54,640 --> 00:06:57,880 Speaker 6: a I would say, you know, more a middle income 144 00:06:57,960 --> 00:07:00,640 Speaker 6: to higher income guests. And we've seen that guest be 145 00:07:00,720 --> 00:07:03,680 Speaker 6: able to weather a lot more of the economic headwinds 146 00:07:03,720 --> 00:07:06,440 Speaker 6: than other, you know, than the low income consumer has 147 00:07:06,960 --> 00:07:09,680 Speaker 6: been facing. And you know, what we continue to see 148 00:07:09,720 --> 00:07:12,520 Speaker 6: is by leaning into our strength, which is delivering a 149 00:07:12,560 --> 00:07:15,559 Speaker 6: fine casual experience. So we think about kind of bringing 150 00:07:15,600 --> 00:07:20,280 Speaker 6: all those great guts of fine dining elevated food, premium ingredients, 151 00:07:20,840 --> 00:07:23,239 Speaker 6: doing the things that you know, other you know, fast 152 00:07:23,240 --> 00:07:26,200 Speaker 6: casual and QSR just are not willing to do. Putting 153 00:07:26,200 --> 00:07:30,600 Speaker 6: that an amazing hospital or hospitable environment and getting great 154 00:07:30,680 --> 00:07:33,600 Speaker 6: guest service. That together has been a winning formula to 155 00:07:33,640 --> 00:07:37,480 Speaker 6: help us outpunch what has been you know, some consumer 156 00:07:37,520 --> 00:07:40,520 Speaker 6: headwinds that has been facing the industry, and we are 157 00:07:40,560 --> 00:07:43,119 Speaker 6: going to continue to lean into that. It's it's helping 158 00:07:43,200 --> 00:07:46,360 Speaker 6: us to differentiate and kind of pull apart from the pack. 159 00:07:47,400 --> 00:07:50,680 Speaker 6: And it's it's been our strength. Where are our samples? 160 00:07:50,960 --> 00:07:53,400 Speaker 3: I know, I mean what is this about? 161 00:07:53,840 --> 00:07:54,720 Speaker 2: So who are. 162 00:07:54,720 --> 00:07:56,800 Speaker 3: Your competitors then? So if you're a middle and high 163 00:07:56,880 --> 00:07:59,320 Speaker 3: end consumer, who would you say as a competitor, Yeah, 164 00:07:59,360 --> 00:08:02,640 Speaker 3: I mean we sell burgers, shakes, fries, I think the 165 00:08:02,640 --> 00:08:05,520 Speaker 3: best chicken sandwich out there in the business. We view 166 00:08:05,560 --> 00:08:08,800 Speaker 3: our competitors as being you know, anybody who you know 167 00:08:08,880 --> 00:08:11,840 Speaker 3: you might consider having lunch at or dinner at. So 168 00:08:11,920 --> 00:08:15,080 Speaker 3: that is a pretty wide array and it also can 169 00:08:15,120 --> 00:08:17,040 Speaker 3: be you know, food at home. I mean that can 170 00:08:17,120 --> 00:08:19,680 Speaker 3: also be in you know, in an area where you 171 00:08:19,680 --> 00:08:22,520 Speaker 3: would have some share of stomach. So you know, for 172 00:08:22,640 --> 00:08:26,440 Speaker 3: the vast amount of you know, of our restaurants out there. 173 00:08:26,480 --> 00:08:28,880 Speaker 3: We are competing with a lot of people. Now we 174 00:08:29,000 --> 00:08:31,760 Speaker 3: are differentiated and we are kind of in that category 175 00:08:31,800 --> 00:08:35,240 Speaker 3: of one in the fine casual sector. But at the 176 00:08:35,280 --> 00:08:37,480 Speaker 3: same time, we know that, you know, people have lots 177 00:08:37,480 --> 00:08:39,720 Speaker 3: of different options where they can go out to eat, Katy. 178 00:08:39,800 --> 00:08:42,080 Speaker 2: There's a lot of concern out there about inflation. If 179 00:08:42,080 --> 00:08:44,600 Speaker 2: inflation were to come into your business, where would you 180 00:08:44,600 --> 00:08:45,920 Speaker 2: see it and how do you plan for that? 181 00:08:46,200 --> 00:08:48,920 Speaker 6: So we actually have been navigating through inflationary pressures for 182 00:08:48,960 --> 00:08:52,199 Speaker 6: a number of years here and doing so quite successfully. 183 00:08:52,240 --> 00:08:55,720 Speaker 6: I'll say, you know, we've had wage inflationary pressures in COVID. 184 00:08:55,800 --> 00:08:59,240 Speaker 6: It was actually very hard to get restaurant talent in 185 00:08:59,320 --> 00:09:02,760 Speaker 6: our restaurants to staff and to deliver our food. It 186 00:09:02,840 --> 00:09:04,880 Speaker 6: was not a desirable job at the time. And we 187 00:09:04,960 --> 00:09:08,040 Speaker 6: had we raised wages and had a very competitive and 188 00:09:08,040 --> 00:09:11,800 Speaker 6: compelling opportunity for our team members. We also introduced tips 189 00:09:11,840 --> 00:09:14,920 Speaker 6: as a way to compensate our team members as well 190 00:09:14,920 --> 00:09:18,640 Speaker 6: and give them added benefit. And then last year with 191 00:09:18,720 --> 00:09:20,840 Speaker 6: you know, with California Fast Food Wage Act, you know, 192 00:09:20,840 --> 00:09:23,840 Speaker 6: we faced through that as well. We've also had on 193 00:09:23,880 --> 00:09:26,760 Speaker 6: the food side, you know, inflationary pressures that have been. 194 00:09:27,000 --> 00:09:29,640 Speaker 6: We've been navigating for a number of years as well. 195 00:09:30,440 --> 00:09:33,600 Speaker 6: But through all of this, through leaning in on our strength, 196 00:09:33,640 --> 00:09:36,560 Speaker 6: which is, you know, again delivering that elevated you know, 197 00:09:36,679 --> 00:09:39,160 Speaker 6: experience to guests, giving them that you know, twenty five 198 00:09:39,240 --> 00:09:42,600 Speaker 6: dollars uh, you know black truffle Burger that we were 199 00:09:42,600 --> 00:09:45,360 Speaker 6: actually selling for ten dollars and giving them that great value. 200 00:09:45,360 --> 00:09:48,959 Speaker 6: On that side, we've been able to both grow sales 201 00:09:49,000 --> 00:09:52,199 Speaker 6: and grow margins at a faster pace. Just even last year, 202 00:09:52,240 --> 00:09:55,000 Speaker 6: we expanded our margins in the fourth quarter by three 203 00:09:55,080 --> 00:09:57,880 Speaker 6: hundred basis points. So I've never had Shakeshack, but it 204 00:09:57,960 --> 00:09:59,520 Speaker 6: looked I know, I know, but it looks like I 205 00:09:59,559 --> 00:10:01,400 Speaker 6: may be ab to now in Delta. Yes. 206 00:10:01,559 --> 00:10:04,440 Speaker 3: So, and this really also goes to your expansion plans. 207 00:10:04,440 --> 00:10:07,280 Speaker 3: So Delta is going to offer Shakeshack Burgers on additional 208 00:10:07,280 --> 00:10:10,600 Speaker 3: domestic routs this year, and that could expand international flights 209 00:10:10,840 --> 00:10:12,840 Speaker 3: next year. Talk about these expansion kind of plans. 210 00:10:12,880 --> 00:10:15,040 Speaker 6: Yeah, I mean, if you look at Delta at its 211 00:10:15,040 --> 00:10:17,719 Speaker 6: core and what this does, you know, this is an 212 00:10:17,760 --> 00:10:21,559 Speaker 6: opportunity where we're able to surprise and delight our guests, 213 00:10:21,640 --> 00:10:24,040 Speaker 6: give them that thing that they weren't really expecting. You know, 214 00:10:24,080 --> 00:10:26,760 Speaker 6: you have your expectation for what airline food is like, 215 00:10:27,400 --> 00:10:30,440 Speaker 6: and you know, this this opportunity to get a shake 216 00:10:30,480 --> 00:10:33,920 Speaker 6: Shack Burger and are great. We have a special brownie 217 00:10:34,000 --> 00:10:37,640 Speaker 6: that we've made for for Delta as well. Through this program. 218 00:10:38,200 --> 00:10:41,080 Speaker 6: People are just absolutely elated at the opportunity to have 219 00:10:41,160 --> 00:10:43,640 Speaker 6: that on their flights, and so much so that it's 220 00:10:43,679 --> 00:10:47,200 Speaker 6: exceeded our internal expectations. We're rolling it out to more airports. 221 00:10:47,240 --> 00:10:49,800 Speaker 6: You're gonna be able to get it, you know, New York, Atlanta, 222 00:10:50,200 --> 00:10:52,600 Speaker 6: a number of airports, and that will just you know, 223 00:10:52,679 --> 00:10:55,800 Speaker 6: probably continue to grow. And you know, if you look 224 00:10:55,840 --> 00:10:58,720 Speaker 6: at that opportunity and I can make so many different 225 00:10:58,760 --> 00:11:03,400 Speaker 6: parallels to how we've gone into an area where the 226 00:11:03,440 --> 00:11:07,280 Speaker 6: consumer had a certain expectation and we just really raised 227 00:11:07,280 --> 00:11:09,800 Speaker 6: the bar on it and out punched above our weight 228 00:11:10,679 --> 00:11:14,079 Speaker 6: and transformed what people were expecting from you know, it's 229 00:11:14,120 --> 00:11:18,880 Speaker 6: airline food, if it's roadside food, and across the board. 230 00:11:19,520 --> 00:11:21,880 Speaker 2: Katie, in terms of growth, how many locations do you 231 00:11:21,920 --> 00:11:24,360 Speaker 2: have today and what's your outlook for the next year 232 00:11:24,400 --> 00:11:24,680 Speaker 2: or two. 233 00:11:24,880 --> 00:11:27,679 Speaker 6: Yeah, we have, you know, across both our company operated 234 00:11:28,120 --> 00:11:32,120 Speaker 6: and our license business. We're you know, about five hundred 235 00:11:32,160 --> 00:11:35,000 Speaker 6: and fifty five hundred and seventy locations, but we are 236 00:11:35,040 --> 00:11:38,760 Speaker 6: growing very fast. We're going to add another forty five 237 00:11:39,000 --> 00:11:42,880 Speaker 6: domestic company operated shacks this year, and we're going to 238 00:11:42,920 --> 00:11:46,280 Speaker 6: open about thirty five to forty licensed shacks as well. 239 00:11:46,840 --> 00:11:50,160 Speaker 6: Those license shacks are ones that we operate, that our 240 00:11:50,160 --> 00:11:54,600 Speaker 6: partners operate. We have locations in the US, but most 241 00:11:54,640 --> 00:11:57,160 Speaker 6: of that is kind of outside of the US and Asia, 242 00:11:57,360 --> 00:12:01,920 Speaker 6: and we have UK, the Middle East, Mexico, and most 243 00:12:01,960 --> 00:12:03,439 Speaker 6: recently we opened up in Canada. 244 00:12:03,800 --> 00:12:06,800 Speaker 3: Our thanks to Katie Fogerty, chief financial officer at Shakeshack. 245 00:12:07,040 --> 00:12:09,120 Speaker 2: Coming up, we'll break down how private credit is being 246 00:12:09,160 --> 00:12:11,319 Speaker 2: impacted as banks face stricter regulations. 247 00:12:11,520 --> 00:12:14,079 Speaker 3: You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in 248 00:12:14,160 --> 00:12:16,240 Speaker 3: depth research and data on two thousand companies and one 249 00:12:16,280 --> 00:12:19,240 Speaker 3: hundred and thirty industries. You can access Bloomberg Intelligence through 250 00:12:19,320 --> 00:12:20,600 Speaker 3: Bigo on the terminal. 251 00:12:20,600 --> 00:12:22,440 Speaker 2: I'm Alex Steele to Paul Sweeney. 252 00:12:22,559 --> 00:12:23,600 Speaker 4: This is Bloomberg. 253 00:12:28,559 --> 00:12:32,280 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 254 00:12:32,360 --> 00:12:35,439 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 255 00:12:35,440 --> 00:12:38,760 Speaker 1: Auto with the Bloomberg Business app. Listen on demand wherever 256 00:12:38,800 --> 00:12:43,040 Speaker 1: you get your podcasts or watch us live on YouTube. 257 00:12:43,080 --> 00:12:45,400 Speaker 3: We continue with some of our best interviews from our 258 00:12:45,440 --> 00:12:48,000 Speaker 3: live broadcast at Bloomberg invest We talk with leaders and 259 00:12:48,000 --> 00:12:50,720 Speaker 3: asset management, banking, wealth and private markets in the heart 260 00:12:50,760 --> 00:12:52,120 Speaker 3: of New York's financial district. 261 00:12:52,360 --> 00:12:55,720 Speaker 2: In this conversation, we spoke with Mark Lipschultz, co CEO 262 00:12:55,840 --> 00:12:58,599 Speaker 2: at Blue Out Capital. We discussed the growing dominance of 263 00:12:58,600 --> 00:13:02,280 Speaker 2: private credit as traditional banks face stricter regulations and reduced 264 00:13:02,360 --> 00:13:03,239 Speaker 2: lending capacity. 265 00:13:03,360 --> 00:13:05,160 Speaker 3: We first asked Mark to talk to us about Blue 266 00:13:05,200 --> 00:13:07,560 Speaker 3: Owl and how they fit into the private credit business. 267 00:13:08,120 --> 00:13:10,679 Speaker 5: Well, we've been very fortunate to be part of an 268 00:13:10,679 --> 00:13:13,280 Speaker 5: asset class and you know, I play our role in 269 00:13:13,360 --> 00:13:16,160 Speaker 5: helping evolve it. Look, private credit, to set the stage 270 00:13:16,240 --> 00:13:19,760 Speaker 5: right is about taking long term capital from investors, and 271 00:13:19,800 --> 00:13:22,040 Speaker 5: we've tried to broaden the range of people that have 272 00:13:22,120 --> 00:13:24,400 Speaker 5: access to it and to be able to provide that 273 00:13:24,480 --> 00:13:28,720 Speaker 5: capital to corporate users to support their growth with a 274 00:13:28,760 --> 00:13:30,559 Speaker 5: view to the long term. And to be here on 275 00:13:30,640 --> 00:13:33,640 Speaker 5: a day when you know the public market is so volatile, 276 00:13:34,080 --> 00:13:37,240 Speaker 5: you know, in some ways very much a reminder of 277 00:13:37,240 --> 00:13:41,080 Speaker 5: why private credit works for investors, but also why it's 278 00:13:41,120 --> 00:13:45,199 Speaker 5: important because look, we're doing business today. We're making loans today, 279 00:13:45,280 --> 00:13:47,520 Speaker 5: just like we were yesterday, just like we will tomorrow. 280 00:13:47,880 --> 00:13:52,240 Speaker 5: You know, screen rater screen blue screen green, prefer green. 281 00:13:52,800 --> 00:13:55,400 Speaker 3: I should disclose that to my money manager. I do 282 00:13:55,480 --> 00:13:58,319 Speaker 3: own shares in blue Owl private credit. Finally, I do 283 00:13:58,400 --> 00:13:59,800 Speaker 3: have some of that feel like I need to say that, 284 00:13:59,840 --> 00:14:03,120 Speaker 3: but not through me. It's through my money guy. So 285 00:14:03,600 --> 00:14:06,920 Speaker 3: help me understand the competitive landscape though, because it feels 286 00:14:06,920 --> 00:14:09,280 Speaker 3: like banks now want to get a slice of the 287 00:14:09,280 --> 00:14:11,280 Speaker 3: private credit market that they had to give up, and 288 00:14:11,280 --> 00:14:14,560 Speaker 3: now we're seeing some partnerships with private credit shops. How 289 00:14:14,559 --> 00:14:15,160 Speaker 3: do you look at it? 290 00:14:15,280 --> 00:14:18,160 Speaker 5: Yeah, the evolving landscape with the banks is pretty interesting. 291 00:14:18,240 --> 00:14:22,120 Speaker 5: Let's make a couple observations. The word like referencing the 292 00:14:22,240 --> 00:14:25,560 Speaker 5: bank market. I think it's worth unpacking a little bit because, 293 00:14:25,600 --> 00:14:28,480 Speaker 5: as obviously you will know, when we go back to 294 00:14:28,720 --> 00:14:31,400 Speaker 5: thirty years ago, I started in the private markets. The 295 00:14:31,440 --> 00:14:34,320 Speaker 5: alternative market wasn't called that at the time, and we 296 00:14:34,360 --> 00:14:37,520 Speaker 5: actually borrowed money from the banks when we were doing 297 00:14:37,600 --> 00:14:40,880 Speaker 5: an LBO as it was called then, literally from their 298 00:14:41,080 --> 00:14:44,760 Speaker 5: balance sheets. That over the last thirty years has been 299 00:14:44,800 --> 00:14:49,080 Speaker 5: on a long trajectory changing from being a lender to now, 300 00:14:49,280 --> 00:14:51,720 Speaker 5: the banks don't lend to these companies at all, and 301 00:14:51,760 --> 00:14:55,080 Speaker 5: that's been true for a while. They intermediate, right, They'll 302 00:14:55,080 --> 00:14:58,040 Speaker 5: go in and they'll underwrite a loan and then sell 303 00:14:58,080 --> 00:15:00,720 Speaker 5: it into the market, cut it into pieces, sell it 304 00:15:01,280 --> 00:15:04,880 Speaker 5: and so in that regard, of course, that's an alternative 305 00:15:04,920 --> 00:15:07,000 Speaker 5: way to finance a business. And we could talk about 306 00:15:07,040 --> 00:15:09,320 Speaker 5: the pluses and minuses of both. It's great to have 307 00:15:09,400 --> 00:15:12,360 Speaker 5: both markets. You want to have a good, vibrant bank 308 00:15:12,480 --> 00:15:15,960 Speaker 5: intermediated market. But remember what the bank cares about is 309 00:15:16,280 --> 00:15:18,200 Speaker 5: can I underwrite the loan and sell it in the 310 00:15:18,200 --> 00:15:21,480 Speaker 5: next sixty days. So the red screen is dramatic for 311 00:15:21,560 --> 00:15:24,360 Speaker 5: a decision for a bank to underwrite a loan. On 312 00:15:24,360 --> 00:15:26,560 Speaker 5: the other hand, word at the exact opposite, it doesn't 313 00:15:26,600 --> 00:15:28,560 Speaker 5: really matter to us what's happening in the market today. 314 00:15:28,560 --> 00:15:31,680 Speaker 5: What matters to us is do we get paid back five, six, 315 00:15:31,760 --> 00:15:34,320 Speaker 5: seven years from out. That's our decision, that's what we're 316 00:15:34,360 --> 00:15:37,280 Speaker 5: focused on. So in that sense, we really live in 317 00:15:37,560 --> 00:15:40,880 Speaker 5: kind of with different incentives and serve a different function. However, 318 00:15:41,040 --> 00:15:43,440 Speaker 5: to the good point, the banks are saying, okay, but 319 00:15:43,800 --> 00:15:46,040 Speaker 5: turns out private credit really does work, right. They spent 320 00:15:46,120 --> 00:15:48,960 Speaker 5: a lot of time criticizing the market and trying different 321 00:15:48,960 --> 00:15:52,240 Speaker 5: ways to maybe scare up the boogeyman. But now they 322 00:15:52,280 --> 00:15:55,840 Speaker 5: in fact are actually launching funds to do private credit. 323 00:15:56,240 --> 00:15:58,680 Speaker 5: So I'd start with, look, if you can't beat them, 324 00:15:58,720 --> 00:16:01,760 Speaker 5: join them, and we that's right, We'll take the endorsement 325 00:16:01,760 --> 00:16:04,880 Speaker 5: of the market. It's a big world credit. It's a 326 00:16:04,960 --> 00:16:08,560 Speaker 5: multi trillion dollar asset class, multi trillion dollar marketplace. We 327 00:16:08,720 --> 00:16:12,800 Speaker 5: need vibrant available capital. And having bank launch a fund, 328 00:16:12,920 --> 00:16:14,600 Speaker 5: you know great. There's a lot of funds in the world, 329 00:16:15,000 --> 00:16:16,960 Speaker 5: and some of those will be done in partnerships as 330 00:16:16,960 --> 00:16:20,000 Speaker 5: you noted, and someone just be standalone efforts, and some 331 00:16:20,080 --> 00:16:22,120 Speaker 5: will just continue to stay the course and do their 332 00:16:22,160 --> 00:16:23,120 Speaker 5: traditional underwriting. 333 00:16:23,360 --> 00:16:26,040 Speaker 2: What's a typical deal for blue out these days? 334 00:16:26,320 --> 00:16:28,720 Speaker 5: So a typical deal for us. And this has been 335 00:16:28,720 --> 00:16:30,960 Speaker 5: true for us from the beginning. Now, obviously the attributes 336 00:16:30,960 --> 00:16:33,640 Speaker 5: and the size have changed, but over the last roughly 337 00:16:33,680 --> 00:16:36,320 Speaker 5: ten years that we've built Blue Owl, our reason to 338 00:16:36,360 --> 00:16:38,280 Speaker 5: be was to come in and say, look, we want 339 00:16:38,320 --> 00:16:41,680 Speaker 5: private credit to become the lender of first choice as 340 00:16:41,680 --> 00:16:44,120 Speaker 5: opposed to the lender of last resort, and private credit, 341 00:16:44,200 --> 00:16:47,280 Speaker 5: if you go back before that time was really a 342 00:16:47,400 --> 00:16:50,200 Speaker 5: lender of last resort. It's where you went if you 343 00:16:50,240 --> 00:16:53,000 Speaker 5: couldn't get money from a mainstream source. As I said, 344 00:16:53,040 --> 00:16:55,840 Speaker 5: I was at KKR for twenty one years, and during 345 00:16:55,880 --> 00:16:59,440 Speaker 5: that time I don't recall ever working with a private 346 00:16:59,520 --> 00:17:01,720 Speaker 5: lender that this wasn't what you did if you were 347 00:17:01,720 --> 00:17:05,679 Speaker 5: a mainstream borrower. But the idea for Blualla and today, 348 00:17:05,760 --> 00:17:08,800 Speaker 5: so to answer this question has been to create actually 349 00:17:08,840 --> 00:17:13,080 Speaker 5: a real value proposition in having a partner to really 350 00:17:13,119 --> 00:17:15,919 Speaker 5: work with a long dated capital pool for someone who 351 00:17:16,000 --> 00:17:19,199 Speaker 5: has long dated needs and long dated ambitions with their business. 352 00:17:19,240 --> 00:17:22,960 Speaker 5: So our typical company today often backed by a private 353 00:17:22,960 --> 00:17:26,680 Speaker 5: equity firm, a sponsor. Sometimes it's just private family owned 354 00:17:26,680 --> 00:17:30,679 Speaker 5: businesses or other corporate enterprises, but typically a private equity 355 00:17:30,720 --> 00:17:34,199 Speaker 5: backed business and they're buying a very large company and 356 00:17:34,280 --> 00:17:36,719 Speaker 5: they're looking for a long term partner to buy it. 357 00:17:37,000 --> 00:17:40,560 Speaker 5: So typically when we do a transaction, we're lending maybe 358 00:17:41,119 --> 00:17:44,159 Speaker 5: forty percent of the purchase price and the buyer is 359 00:17:44,160 --> 00:17:47,040 Speaker 5: putting up sixty percent of the capital. So that's a 360 00:17:47,160 --> 00:17:50,160 Speaker 5: very very low leverage structure compared to what people are 361 00:17:50,240 --> 00:17:52,440 Speaker 5: used to. If you go back again ten years and 362 00:17:52,600 --> 00:17:56,040 Speaker 5: twenty years and the company today Our average company in 363 00:17:56,080 --> 00:17:59,840 Speaker 5: our portfolio has over two hundred million dollars of even 364 00:18:00,200 --> 00:18:03,000 Speaker 5: I mean, these are big companies today, and that's been 365 00:18:03,000 --> 00:18:05,119 Speaker 5: a dramatic shift from ten years ago when it was 366 00:18:05,160 --> 00:18:07,520 Speaker 5: really a market for smaller businesses. 367 00:18:07,760 --> 00:18:10,040 Speaker 3: So let's get to that five to seven year time horizon, 368 00:18:10,119 --> 00:18:13,320 Speaker 3: because ten years ago that's the exact same conversation I'd 369 00:18:13,320 --> 00:18:15,800 Speaker 3: be having with private equity, right, and then we see 370 00:18:15,800 --> 00:18:18,919 Speaker 3: where things get tough and things get stickier, when vintages 371 00:18:18,960 --> 00:18:21,919 Speaker 3: don't work out or there come under different times of 372 00:18:22,000 --> 00:18:25,959 Speaker 3: market stress. How does that apply to the credit space? 373 00:18:26,320 --> 00:18:28,640 Speaker 5: So I think it applies for sure in the sense 374 00:18:28,680 --> 00:18:32,280 Speaker 5: that every market evolves, and every market we'll have it's 375 00:18:32,400 --> 00:18:35,720 Speaker 5: maybe slightly higher and lower moments, But there's an important distinction. Okay, 376 00:18:36,200 --> 00:18:38,159 Speaker 5: at the end of the day, Private equity, if I 377 00:18:38,320 --> 00:18:40,600 Speaker 5: kind of use this metaphor, private equity, which is a 378 00:18:40,600 --> 00:18:46,119 Speaker 5: business I personally participated in for decades, is about mining 379 00:18:46,160 --> 00:18:48,719 Speaker 5: for gold. Right, It's about going out and maybe in 380 00:18:48,720 --> 00:18:52,119 Speaker 5: our simplified parlance, might call and to get rich strategies, 381 00:18:52,280 --> 00:18:54,520 Speaker 5: how do you out there and shoot the moon on 382 00:18:54,840 --> 00:18:58,520 Speaker 5: great returns? So they're mining for gold. Our business in 383 00:18:58,720 --> 00:19:01,400 Speaker 5: private credit is to be the picks and shovels provider 384 00:19:01,600 --> 00:19:05,119 Speaker 5: to those miners. So we're not trying to find a 385 00:19:05,160 --> 00:19:08,160 Speaker 5: big gold vein. We're not betting on the price of gold. 386 00:19:08,359 --> 00:19:10,399 Speaker 5: What we're saying is if the miners are active, and 387 00:19:10,720 --> 00:19:13,719 Speaker 5: miners in this case would be any corporate user of capital, 388 00:19:13,760 --> 00:19:16,320 Speaker 5: so they are always active, we want to supply them 389 00:19:16,480 --> 00:19:19,159 Speaker 5: and we take a less risky position and we expect 390 00:19:19,160 --> 00:19:23,399 Speaker 5: a corollary attractive return. So on the one hand, of course, 391 00:19:23,400 --> 00:19:25,840 Speaker 5: every market evolves, and I want to suggest anybody that 392 00:19:25,840 --> 00:19:28,760 Speaker 5: lives in a vacuum. But the purpose of our strategies 393 00:19:28,960 --> 00:19:31,520 Speaker 5: and the purpose of Crivate credit from an investor's point 394 00:19:31,560 --> 00:19:33,800 Speaker 5: of view, is to have something that's much more about 395 00:19:33,840 --> 00:19:39,280 Speaker 5: downside protection, stability, and income generation through times of uncertainty, 396 00:19:39,520 --> 00:19:41,439 Speaker 5: which is a bit why I say this sort of 397 00:19:41,480 --> 00:19:43,560 Speaker 5: red environment today is actually a good time to have 398 00:19:43,560 --> 00:19:47,200 Speaker 5: the conversation because what we're trying to build our portfolios 399 00:19:47,240 --> 00:19:50,640 Speaker 5: and successfully have down over one hundred billion dollars of loans, 400 00:19:50,920 --> 00:19:53,760 Speaker 5: and our running loss rates have been eleven basis points, 401 00:19:54,119 --> 00:19:55,639 Speaker 5: and I think it speaks to the idea that this 402 00:19:55,680 --> 00:19:59,600 Speaker 5: is about durability and predictability when times are uncertain, and 403 00:19:59,640 --> 00:20:02,320 Speaker 5: I think probably safe to say everyone's looking around saying, gosh, 404 00:20:02,359 --> 00:20:03,720 Speaker 5: it feels uncertain out there. 405 00:20:04,119 --> 00:20:06,040 Speaker 2: Mark, we've got about a minute left. What do you 406 00:20:06,080 --> 00:20:08,640 Speaker 2: say to those folks who say, as the business evolves, 407 00:20:08,720 --> 00:20:11,080 Speaker 2: the dollars get bigger, regulation is needed. 408 00:20:11,119 --> 00:20:12,440 Speaker 4: What do you say to those folks. 409 00:20:12,480 --> 00:20:15,560 Speaker 5: Well, we're a highly regulated business as is, so you 410 00:20:15,560 --> 00:20:19,399 Speaker 5: know today. Look, we're regulated by the SEC, where public 411 00:20:19,400 --> 00:20:21,440 Speaker 5: company as a manager, we have public vehicles, We have 412 00:20:22,119 --> 00:20:25,639 Speaker 5: a lot of regulators we work with, constructively, happy to 413 00:20:25,680 --> 00:20:28,000 Speaker 5: do it. I don't think if what we mean by 414 00:20:28,440 --> 00:20:32,360 Speaker 5: more regulation is more direction from sort of a central 415 00:20:32,440 --> 00:20:35,280 Speaker 5: source as to what you should or shouldn't lend money 416 00:20:35,320 --> 00:20:37,879 Speaker 5: to Remember, when we look back where the sources of 417 00:20:37,920 --> 00:20:40,919 Speaker 5: problems have been, they actually tend to be in the 418 00:20:40,960 --> 00:20:45,080 Speaker 5: regulated institutions, not outside. Even recently. Of course, everyone remembers 419 00:20:45,080 --> 00:20:47,560 Speaker 5: the financial crisis, but don't forget over the last few 420 00:20:47,600 --> 00:20:50,080 Speaker 5: years as private credit is thrived. One of the moments 421 00:20:50,119 --> 00:20:52,879 Speaker 5: we worked through was the run on the bank at 422 00:20:52,880 --> 00:20:56,360 Speaker 5: Silicon Valley Bank. Ye, so you know, what's old is new. 423 00:20:56,680 --> 00:20:58,399 Speaker 5: If you have one day capital and you do long 424 00:20:58,520 --> 00:21:00,920 Speaker 5: term things with it, that's challenging. We have long term 425 00:21:00,960 --> 00:21:03,800 Speaker 5: capital to do long term things. So I think at 426 00:21:03,840 --> 00:21:05,679 Speaker 5: the end of the day, look, we don't touch depositors. 427 00:21:05,680 --> 00:21:08,800 Speaker 5: We're not systemic. So it's a nice compliment to a 428 00:21:08,840 --> 00:21:11,320 Speaker 5: traditional banking market and a public marketplace. 429 00:21:11,720 --> 00:21:14,480 Speaker 2: All right, thanks to market Lipscheltz, co CEO at Blue 430 00:21:14,480 --> 00:21:15,160 Speaker 2: Oul Capital. 431 00:21:15,440 --> 00:21:18,320 Speaker 3: Staying with Bloomberg invest Paul and I also spoke with Yupkim, 432 00:21:18,520 --> 00:21:21,880 Speaker 3: chief investment officer at the Texas Municipal Retirement System. Now 433 00:21:21,880 --> 00:21:23,959 Speaker 3: he discussed how the firm is managing a more than 434 00:21:24,040 --> 00:21:28,160 Speaker 3: forty billion plus pension fund in today's complex economic landscape. 435 00:21:28,359 --> 00:21:31,280 Speaker 2: You first asked, Yep, what he thinks the best allocation 436 00:21:31,400 --> 00:21:34,320 Speaker 2: is right now in what can be considered very strange, 437 00:21:34,440 --> 00:21:35,880 Speaker 2: difficult economic environment. 438 00:21:36,200 --> 00:21:39,560 Speaker 7: I think, on a very holistic basis, we are long 439 00:21:39,640 --> 00:21:43,879 Speaker 7: term investors, and so our long term strategy remains unchanged. 440 00:21:44,040 --> 00:21:46,960 Speaker 7: You know, it's really predicated upon three pillars. Number one, 441 00:21:47,720 --> 00:21:51,520 Speaker 7: attract higher and retain the best talent possible and also 442 00:21:51,560 --> 00:21:54,920 Speaker 7: attracted and partner with the world class investment managers around 443 00:21:54,960 --> 00:22:00,399 Speaker 7: the globe. Secondly, it's really about taking a low cost, 444 00:22:00,720 --> 00:22:04,359 Speaker 7: public markets benchmark aligned approach to to investing. I do 445 00:22:04,440 --> 00:22:08,879 Speaker 7: think we all recognize going forward there are more alph opportunities, 446 00:22:09,119 --> 00:22:10,840 Speaker 7: and beta might be you know, there might be some 447 00:22:11,160 --> 00:22:14,560 Speaker 7: headwinds to beta going forward. So I do think increasing 448 00:22:14,720 --> 00:22:17,240 Speaker 7: the share of active management and public markets will be 449 00:22:17,280 --> 00:22:21,000 Speaker 7: a critical a critical approach. And lastly, really endeavoring to 450 00:22:21,200 --> 00:22:24,639 Speaker 7: generate a lot of the outperformance going forward in private 451 00:22:24,680 --> 00:22:28,360 Speaker 7: markets will be absolutely critical. And you know, and so 452 00:22:28,600 --> 00:22:30,600 Speaker 7: I do think kind of with the you know, with 453 00:22:30,640 --> 00:22:33,240 Speaker 7: the confluence of a lot of market volatility, it's it's 454 00:22:33,280 --> 00:22:35,359 Speaker 7: easy to be swayed left and right. But I do 455 00:22:35,440 --> 00:22:39,000 Speaker 7: think kind of sticking to your core long term strategy 456 00:22:39,200 --> 00:22:41,200 Speaker 7: is you know, very important in this environment. 457 00:22:41,400 --> 00:22:43,880 Speaker 2: How does an asset allocation work for you guys down 458 00:22:43,920 --> 00:22:48,679 Speaker 2: in Austin stocks, bonds, alternatives, Let's hold it with alternatives playing. 459 00:22:48,840 --> 00:22:53,919 Speaker 7: Absolutely Look, I think when you think about alternatives, the 460 00:22:53,960 --> 00:22:57,400 Speaker 7: delta between a media and manager and a top five 461 00:22:57,440 --> 00:23:01,560 Speaker 7: percentile manager in alternatives and privates can be upwards of 462 00:23:01,600 --> 00:23:05,200 Speaker 7: fifteen hundred to eighteen hundred basis points. That equivalent number 463 00:23:05,200 --> 00:23:07,480 Speaker 7: in public markets is two hundred and fifty to three hundred 464 00:23:07,480 --> 00:23:11,359 Speaker 7: basis points. And so you are really compensated for good 465 00:23:11,400 --> 00:23:14,399 Speaker 7: manager selection but also a good deal selection. And so 466 00:23:14,600 --> 00:23:16,840 Speaker 7: I do think there's still you know, when you think 467 00:23:16,880 --> 00:23:18,679 Speaker 7: about the next ten years, there's a lot of equity 468 00:23:18,760 --> 00:23:21,320 Speaker 7: value creation that will occur in the private markets, and 469 00:23:21,400 --> 00:23:24,400 Speaker 7: so it really you know, kind of provides that long 470 00:23:24,480 --> 00:23:27,040 Speaker 7: term you know, kind of alp engine to the overall portfolio. 471 00:23:27,160 --> 00:23:29,560 Speaker 3: I mean, so surprised that you did private equity in 472 00:23:29,640 --> 00:23:31,439 Speaker 3: your last job and then now we're taking over at 473 00:23:31,440 --> 00:23:35,560 Speaker 3: the Texas Pension Fund. How well funded or pensions right now? 474 00:23:36,000 --> 00:23:40,560 Speaker 7: Yes, and so pension funds are definitely better funded kind 475 00:23:40,560 --> 00:23:44,400 Speaker 7: of really on the backs of two incredible years in 476 00:23:44,560 --> 00:23:47,040 Speaker 7: you know, the equity public markets, and I do think 477 00:23:47,080 --> 00:23:51,720 Speaker 7: public pensions typically have higher allocations to public equities since 478 00:23:51,800 --> 00:23:55,560 Speaker 7: that's that's certainly helped. At Texas, we're you know, above 479 00:23:55,640 --> 00:23:59,320 Speaker 7: ninety percent funded and so and just given that we 480 00:23:59,359 --> 00:24:02,560 Speaker 7: serve cities that are growing, you know, you know, our 481 00:24:03,000 --> 00:24:05,239 Speaker 7: net cash outflow for the past two years has been 482 00:24:05,320 --> 00:24:08,200 Speaker 7: less than a percent, and so that really empowers us 483 00:24:08,240 --> 00:24:11,920 Speaker 7: to harvest, you know, thelquided premium of our private market book, 484 00:24:11,960 --> 00:24:15,560 Speaker 7: but also really helps us risk manage on the liquidity side. 485 00:24:16,280 --> 00:24:19,640 Speaker 2: How do you feel about just the opportunities today? Where 486 00:24:19,640 --> 00:24:22,000 Speaker 2: do you guys see the best opportunities? 487 00:24:22,080 --> 00:24:25,160 Speaker 7: Sure, sure, you know, like I think, maybe three things 488 00:24:25,200 --> 00:24:28,480 Speaker 7: I'll share there is, you know, number one, the core 489 00:24:28,520 --> 00:24:33,880 Speaker 7: building blocks on why people were excited about this US exceptionalism. 490 00:24:34,280 --> 00:24:37,399 Speaker 7: The core building blocks have not changed. Right when I 491 00:24:37,440 --> 00:24:40,159 Speaker 7: talk to my peers in Asia and Europe and the 492 00:24:40,200 --> 00:24:44,280 Speaker 7: Middle East, the US continues to be the top destination, 493 00:24:44,560 --> 00:24:47,400 Speaker 7: you know, for their investment capital. You have the top 494 00:24:47,440 --> 00:24:52,560 Speaker 7: academic institutions in the United States, presumably with the greatest founders, 495 00:24:52,720 --> 00:24:55,919 Speaker 7: the most tenured management teams. You have access to cheap energy. 496 00:24:56,400 --> 00:24:59,880 Speaker 7: You have a risk taking culture that's celebrated that's really 497 00:24:59,880 --> 00:25:02,159 Speaker 7: not found in many parts of the world. And the 498 00:25:02,240 --> 00:25:04,080 Speaker 7: question we ask is not how do we generate our 499 00:25:04,119 --> 00:25:06,919 Speaker 7: performs in twenty twenty five, but how do we generate 500 00:25:06,920 --> 00:25:10,359 Speaker 7: outperforms in the next decade. And we do view the 501 00:25:10,480 --> 00:25:13,880 Speaker 7: US to continue to take an asymantic share of that equity. 502 00:25:14,119 --> 00:25:17,000 Speaker 7: You value creation in our total portfolio. 503 00:25:16,600 --> 00:25:19,199 Speaker 2: Our thanks to Yup Kim, chief investment officer at the 504 00:25:19,240 --> 00:25:20,879 Speaker 2: Texas Municipal Retirement System. 505 00:25:20,960 --> 00:25:22,600 Speaker 3: Coming up on the program, we're going to break down 506 00:25:22,640 --> 00:25:25,879 Speaker 3: the evolving role of quantitative finance and artificial intelligence in 507 00:25:26,160 --> 00:25:27,160 Speaker 3: asset management. 508 00:25:27,440 --> 00:25:30,480 Speaker 2: You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in 509 00:25:30,520 --> 00:25:32,679 Speaker 2: depth research and data on two thousand companies and one 510 00:25:32,720 --> 00:25:35,720 Speaker 2: hundred and thirty industries. You can access Bloomberg Intelligence via 511 00:25:35,760 --> 00:25:37,920 Speaker 2: b I go on the terminal. I'm Paul Sweeney and. 512 00:25:37,880 --> 00:25:39,920 Speaker 3: I'm Alex Steele, and this is Bloomberg. 513 00:25:45,440 --> 00:25:49,360 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch the program 514 00:25:49,440 --> 00:25:52,479 Speaker 1: live weekdays at ten am Eastern on Apple Coarclay, and 515 00:25:52,480 --> 00:25:55,480 Speaker 1: Android Auto with the Bloomberg Business app. You can also 516 00:25:55,600 --> 00:25:58,920 Speaker 1: listen live on Amazon Alexa from our flagship New York 517 00:25:58,960 --> 00:26:02,440 Speaker 1: station Alexa Play Bloomberg eleven thirty. 518 00:26:03,400 --> 00:26:05,520 Speaker 3: We continue with some of our best interviews from our 519 00:26:05,560 --> 00:26:08,040 Speaker 3: live broadcast at Bloomberg and Best. We talk with leaders 520 00:26:08,080 --> 00:26:10,760 Speaker 3: in asset management, banking, wealth and private markets in the 521 00:26:10,800 --> 00:26:12,360 Speaker 3: heart of New York's Financial district. 522 00:26:12,600 --> 00:26:16,040 Speaker 2: In this conversation, we spoke with Ben Wren, CEO of 523 00:26:16,040 --> 00:26:19,760 Speaker 2: the London based fintech company tech. Ben discusses the evolving 524 00:26:19,800 --> 00:26:23,120 Speaker 2: role of quantitative finance and artificial intelligence in asset management. 525 00:26:23,160 --> 00:26:25,000 Speaker 3: We first asked Ben to give us his quick pitch 526 00:26:25,080 --> 00:26:26,480 Speaker 3: on what sigtech actually does. 527 00:26:26,840 --> 00:26:32,119 Speaker 8: Sigtag we build specialist agents these days to help people 528 00:26:32,160 --> 00:26:35,080 Speaker 8: make better decisions in cup to markets, but also to 529 00:26:35,200 --> 00:26:38,520 Speaker 8: ultimate a lot of the very high value intellectual but 530 00:26:38,640 --> 00:26:42,520 Speaker 8: not very creative workflows. You know, we can reduce a 531 00:26:42,520 --> 00:26:45,159 Speaker 8: lot of the things people do today, which a bit boring, 532 00:26:45,359 --> 00:26:48,679 Speaker 8: you know, down from many hours to thirty seconds. I 533 00:26:48,720 --> 00:26:51,359 Speaker 8: think that makes a big difference in terms of productivities. 534 00:26:51,560 --> 00:26:53,680 Speaker 2: All Right, here's here's an example that I can think 535 00:26:53,680 --> 00:26:55,639 Speaker 2: of for my Okay, tell me being at the printer 536 00:26:56,560 --> 00:26:58,560 Speaker 2: not far from here, a couple of blocks from here, 537 00:26:58,640 --> 00:27:01,119 Speaker 2: don Linny at the two three o'clock in the morning, 538 00:27:01,119 --> 00:27:05,800 Speaker 2: going over a bond perspectives, that's probably something that AI 539 00:27:05,880 --> 00:27:10,080 Speaker 2: can help with. So been, how much our asset managers 540 00:27:10,200 --> 00:27:13,680 Speaker 2: generally speaking, how much are they using technology today help 541 00:27:13,880 --> 00:27:14,679 Speaker 2: computerize this? 542 00:27:14,720 --> 00:27:15,320 Speaker 8: Is it? 543 00:27:15,359 --> 00:27:16,359 Speaker 2: How quantitative is it? 544 00:27:16,920 --> 00:27:19,760 Speaker 8: I think in the last fifteen years there's a big 545 00:27:19,800 --> 00:27:24,080 Speaker 8: trend in asset management to to adopt more and more technology. 546 00:27:24,400 --> 00:27:26,520 Speaker 8: And we can see this shift in terms of, you know, 547 00:27:26,560 --> 00:27:30,440 Speaker 8: people using more data driven investment processes and people hire 548 00:27:30,520 --> 00:27:34,680 Speaker 8: data analysts and but Jenney and I jenei in the 549 00:27:34,760 --> 00:27:37,320 Speaker 8: last few years is a big step change. It's I 550 00:27:37,359 --> 00:27:42,119 Speaker 8: would say, it's it's an unprecedented, unprecedented change in you know, 551 00:27:42,400 --> 00:27:46,240 Speaker 8: in this trend just in terms of it's no longer incremental. 552 00:27:47,880 --> 00:27:50,840 Speaker 8: There's a before and after. And you know, when we 553 00:27:50,920 --> 00:27:54,600 Speaker 8: when we think about previous technologies, you know, we mainly 554 00:27:54,600 --> 00:27:58,159 Speaker 8: focus on what we call explicit knowledge, knowledge that we 555 00:27:58,200 --> 00:28:02,360 Speaker 8: can codify, describe, and there for use programming language to automate. 556 00:28:02,680 --> 00:28:06,640 Speaker 8: But only until now we're able to distill and automate 557 00:28:07,240 --> 00:28:11,000 Speaker 8: so called tested knowledge, the knowledge that resides in our head, 558 00:28:11,440 --> 00:28:14,359 Speaker 8: but we can't really so easily write it down and 559 00:28:14,440 --> 00:28:17,800 Speaker 8: describe and codify. But now we can actually automate those 560 00:28:18,040 --> 00:28:21,359 Speaker 8: and there are plenty of those workflows and processes, especially 561 00:28:21,440 --> 00:28:22,720 Speaker 8: in financial services. 562 00:28:23,000 --> 00:28:27,280 Speaker 3: So how would you help, Like a regular quant manager, 563 00:28:28,760 --> 00:28:30,720 Speaker 3: like I go to you and I'm like, hey, I 564 00:28:30,760 --> 00:28:33,359 Speaker 3: need your product to help me get better faster, find 565 00:28:33,400 --> 00:28:35,440 Speaker 3: better trends in the market. 566 00:28:35,920 --> 00:28:41,800 Speaker 8: Yeah, for quants, I think quants started with more number driven. 567 00:28:42,640 --> 00:28:44,880 Speaker 8: You know, trend following is if you do it like 568 00:28:44,920 --> 00:28:47,800 Speaker 8: in a very simple way, it's entirely number driven. But 569 00:28:47,920 --> 00:28:51,520 Speaker 8: these days we are moving to a world where we 570 00:28:51,600 --> 00:28:55,080 Speaker 8: have to deal with numbers and text as too, modalities. 571 00:28:55,120 --> 00:28:58,520 Speaker 8: At the same time, it's no longer just about technical analysis, 572 00:28:58,520 --> 00:29:02,560 Speaker 8: but it's also about all been new information and turn 573 00:29:03,120 --> 00:29:06,480 Speaker 8: you know, non numerical information into numerical information. And that's 574 00:29:06,520 --> 00:29:09,920 Speaker 8: something that Jen and I does really well because fundamentally, 575 00:29:09,920 --> 00:29:12,360 Speaker 8: if you think about how it's trained, it has been 576 00:29:12,400 --> 00:29:16,560 Speaker 8: trained on trillions of tokens of textual data and a 577 00:29:16,600 --> 00:29:19,840 Speaker 8: lot of things we used to do either bespoke or 578 00:29:20,200 --> 00:29:23,640 Speaker 8: preparatory fashion. This day we get autobox such as sentiment 579 00:29:23,680 --> 00:29:27,560 Speaker 8: analysis or extracting relative and information from very long pieces 580 00:29:27,600 --> 00:29:30,600 Speaker 8: of text. These sort of things actually change how qualms, 581 00:29:30,640 --> 00:29:33,240 Speaker 8: even how qualms approach their daily jobs. 582 00:29:33,520 --> 00:29:37,800 Speaker 2: Are the big Wall Street firms making these investments or 583 00:29:37,840 --> 00:29:41,200 Speaker 2: is it more of the hedge fund community that is 584 00:29:41,280 --> 00:29:43,120 Speaker 2: more receptive. Who are your customers? 585 00:29:43,160 --> 00:29:46,720 Speaker 8: Typically these days we mainly focus on byside, okay, but 586 00:29:46,800 --> 00:29:49,360 Speaker 8: we also have very big clients in terms of in 587 00:29:49,440 --> 00:29:52,320 Speaker 8: terms of like commercial banks, you know, using our technology 588 00:29:52,360 --> 00:29:57,520 Speaker 8: to completely change how they underwrite commercial loans. I think 589 00:29:57,560 --> 00:30:01,320 Speaker 8: so I wouldn't say it's a cell side or buyside 590 00:30:01,440 --> 00:30:05,240 Speaker 8: or big firm or small firm. I don't think that's 591 00:30:05,240 --> 00:30:08,000 Speaker 8: the main reason in terms of adoption. I would say 592 00:30:08,080 --> 00:30:12,000 Speaker 8: the main reason is is the leadership. You know, when 593 00:30:12,280 --> 00:30:16,280 Speaker 8: when when you approach something so unprecedented, it takes some 594 00:30:16,360 --> 00:30:19,760 Speaker 8: time to build a consensus inside the organization about you know, 595 00:30:19,800 --> 00:30:22,160 Speaker 8: what's the strategy, what do we do? But you know 596 00:30:22,400 --> 00:30:24,720 Speaker 8: that may take two months, three months, and given how 597 00:30:24,880 --> 00:30:29,040 Speaker 8: fast things change after three months is a different world. Yeah, right, 598 00:30:29,080 --> 00:30:31,560 Speaker 8: So it really takes some kind of conviction from a 599 00:30:31,600 --> 00:30:35,680 Speaker 8: visionary leadership team to adopt this technology very confidently. 600 00:30:35,800 --> 00:30:37,440 Speaker 3: Yeah, af for twenty four hours, it can be a 601 00:30:37,440 --> 00:30:42,680 Speaker 3: different investing landscape. So what's the best partnership between AI 602 00:30:42,760 --> 00:30:46,400 Speaker 3: and humans? Fifty to fifty? Is it AI seventy five 603 00:30:46,440 --> 00:30:48,920 Speaker 3: percent of the decision making process twenty five percent for 604 00:30:49,000 --> 00:30:50,160 Speaker 3: human How do you think about that? 605 00:30:50,400 --> 00:30:53,960 Speaker 8: Yeah, I think if I think about the knowledge work 606 00:30:54,040 --> 00:30:58,040 Speaker 8: we do every day, I would describe them as most 607 00:30:58,040 --> 00:31:03,920 Speaker 8: of them may be not creative but intellectual. Right, analyze 608 00:31:03,960 --> 00:31:08,560 Speaker 8: a lot of documents picking out the right information is intellectual, 609 00:31:08,600 --> 00:31:13,680 Speaker 8: but it's not creative. So in the future, humans should 610 00:31:13,800 --> 00:31:16,720 Speaker 8: devote almost all the time to creative stuff what makes 611 00:31:16,800 --> 00:31:21,520 Speaker 8: us different, whereas the boring intellectual stuff can be automated 612 00:31:21,560 --> 00:31:25,960 Speaker 8: by AI agents. On the other hand, we are certainly 613 00:31:26,040 --> 00:31:29,600 Speaker 8: seeing a big change in the user experience, the user 614 00:31:29,640 --> 00:31:32,240 Speaker 8: interface because you know, up to on to this point, 615 00:31:32,320 --> 00:31:35,800 Speaker 8: people approach GENI mainly through a chetbot. You know, there's 616 00:31:35,840 --> 00:31:38,000 Speaker 8: a chet box. You're typing into it to gets some response. 617 00:31:38,400 --> 00:31:41,240 Speaker 8: It's very nice and it's really started the error. But 618 00:31:41,560 --> 00:31:44,760 Speaker 8: going forward, we are looking at a user user interface 619 00:31:45,280 --> 00:31:49,240 Speaker 8: that allow human to essentially collaborate with a large number 620 00:31:49,280 --> 00:31:52,480 Speaker 8: of AI agents who specialize in different things. So how 621 00:31:52,520 --> 00:31:55,760 Speaker 8: does that user interface look like? And how does that 622 00:31:56,040 --> 00:32:01,360 Speaker 8: AI human fusion, intelligence and CLI like. It's it's a 623 00:32:01,480 --> 00:32:05,200 Speaker 8: very active, a feld of research, trial and errors. 624 00:32:05,600 --> 00:32:09,120 Speaker 2: So this sounds like from what I understand of AI, 625 00:32:09,560 --> 00:32:13,040 Speaker 2: a lot of computing power requirements. Talk about the investments 626 00:32:13,080 --> 00:32:16,719 Speaker 2: that you think these financial firms need to make are 627 00:32:16,840 --> 00:32:19,239 Speaker 2: making or you know, maybe need to step up. 628 00:32:19,480 --> 00:32:22,400 Speaker 8: Yeah, in terms of intelligence and the way I think 629 00:32:22,400 --> 00:32:25,120 Speaker 8: about it is and so it's very similar to electricity. 630 00:32:25,280 --> 00:32:27,640 Speaker 8: You know that we are currently in the in the 631 00:32:27,680 --> 00:32:31,760 Speaker 8: first stage of investing in the infrastructure, right and if 632 00:32:31,760 --> 00:32:34,040 Speaker 8: you're going back in history in the last two hundred 633 00:32:34,080 --> 00:32:37,240 Speaker 8: years and then the way we started building electric electricity grid, 634 00:32:37,720 --> 00:32:40,320 Speaker 8: there's one magical number, which is one percent. You know, 635 00:32:40,440 --> 00:32:42,800 Speaker 8: the countries throughout the history spent about one percent of 636 00:32:42,880 --> 00:32:46,400 Speaker 8: nominal GDP on building power grid from two hundred years 637 00:32:46,440 --> 00:32:49,560 Speaker 8: ago in Britain all the way to today. So the 638 00:32:49,600 --> 00:32:52,440 Speaker 8: Big Tech this year announced three hundred billion dollars of 639 00:32:52,480 --> 00:32:56,760 Speaker 8: investment into Genini data centers. That's almost exactly one percent 640 00:32:56,800 --> 00:32:59,720 Speaker 8: of the US GDP today it's about thirty trillions. So 641 00:32:59,880 --> 00:33:03,040 Speaker 8: in terms of infrastructure investment, we are there and people 642 00:33:03,080 --> 00:33:10,840 Speaker 8: are building incredibly big mega AI clusters across the country now. 643 00:33:11,480 --> 00:33:14,680 Speaker 8: But we are shifting toward the application later right because 644 00:33:14,720 --> 00:33:17,120 Speaker 8: once you have electricity, it's not about the electricity per se, 645 00:33:17,160 --> 00:33:20,880 Speaker 8: it's about what kind of appliances you can build powered 646 00:33:20,920 --> 00:33:23,600 Speaker 8: by electricity. So we are moving into that stage too, 647 00:33:23,640 --> 00:33:26,000 Speaker 8: where there are a lot of investment both in terms 648 00:33:26,000 --> 00:33:29,520 Speaker 8: of talent and capital into building the right applications that 649 00:33:29,560 --> 00:33:32,520 Speaker 8: they actually make a big difference to the knowledge workers 650 00:33:33,440 --> 00:33:36,400 Speaker 8: in terms of productivity. So we are starting that phase. 651 00:33:37,560 --> 00:33:40,280 Speaker 3: Last question here for us is what's the biggest misconsumption 652 00:33:40,880 --> 00:33:44,320 Speaker 3: right now when it comes to AI and using it. 653 00:33:47,360 --> 00:33:50,640 Speaker 8: I think the biggest conception is I think people tend 654 00:33:50,680 --> 00:33:57,920 Speaker 8: to either underappreciate its capabilities or sometimes getting over optimistic, 655 00:33:57,920 --> 00:33:59,840 Speaker 8: and it's quite hard to get it right. 656 00:34:00,800 --> 00:34:03,120 Speaker 3: So it's like too much or too much or too little. 657 00:34:03,200 --> 00:34:05,480 Speaker 8: So I mean I think most people are either under 658 00:34:06,120 --> 00:34:08,759 Speaker 8: you know, under hyping it or over hyping. It's very 659 00:34:08,760 --> 00:34:12,279 Speaker 8: hard to get it right. But one thing is very 660 00:34:12,320 --> 00:34:15,280 Speaker 8: obvious to us is that the pace of the change 661 00:34:15,400 --> 00:34:18,760 Speaker 8: is unprecedented and it's getting better. Like the Deep Seak 662 00:34:18,920 --> 00:34:23,719 Speaker 8: just introduced open sourced all their efficiency engineering tricks to 663 00:34:23,800 --> 00:34:26,359 Speaker 8: the whole world and then everybody is going to adopt it. 664 00:34:26,600 --> 00:34:30,840 Speaker 8: So all of this is pushing the efficiency frontier. So 665 00:34:30,880 --> 00:34:34,200 Speaker 8: we're getting better and faster every day, so people should 666 00:34:34,239 --> 00:34:36,760 Speaker 8: be prepared for the big change. 667 00:34:37,280 --> 00:34:40,400 Speaker 3: Our thanks to Bin ren CEO of sick Pech staying 668 00:34:40,400 --> 00:34:42,360 Speaker 3: with Bloomberg and Best. Paul and I also spoke with 669 00:34:42,400 --> 00:34:45,560 Speaker 3: Stephen Meyer, chief investment Officer and Deputy Comptroller for asset 670 00:34:45,600 --> 00:34:47,800 Speaker 3: management at New York City Retirement Systems. 671 00:34:48,200 --> 00:34:51,960 Speaker 2: Stephen discussed how his group is approaching market volatility, rising 672 00:34:52,000 --> 00:34:54,160 Speaker 2: interest rates, and long term pension obligations. 673 00:34:54,239 --> 00:34:56,919 Speaker 3: We first asked Steven how he's been navigating recent months 674 00:34:57,000 --> 00:34:58,319 Speaker 3: during economic uncertainty. 675 00:34:58,680 --> 00:35:02,680 Speaker 9: It's certainly been interesting, and we try to do those 676 00:35:02,760 --> 00:35:05,680 Speaker 9: adhere to a long term strategic plan. So a lot 677 00:35:05,760 --> 00:35:08,279 Speaker 9: for us, a lot of this is noise in terms 678 00:35:08,280 --> 00:35:11,000 Speaker 9: of what's going on in the change of policy in Washington, 679 00:35:11,440 --> 00:35:13,200 Speaker 9: so we're really trying to stick to our north star, 680 00:35:13,280 --> 00:35:16,720 Speaker 9: which is our strategic ass allocation. Again, we have multi 681 00:35:16,760 --> 00:35:20,680 Speaker 9: generational liabilities that we're trying to satisfy. So again a 682 00:35:20,719 --> 00:35:23,680 Speaker 9: long term investment horizon and a long term discipline. Now, 683 00:35:23,680 --> 00:35:26,960 Speaker 9: having said that, our trustees and our beneficiaries and our 684 00:35:27,000 --> 00:35:29,920 Speaker 9: participants do call. We have the privilege of servicing eight 685 00:35:29,960 --> 00:35:33,800 Speaker 9: hundred thousand public workers here in the City of New York, 686 00:35:34,400 --> 00:35:36,080 Speaker 9: so they are concerned. So we need to stay on 687 00:35:36,080 --> 00:35:38,600 Speaker 9: top of it in terms of just increasing the information 688 00:35:38,680 --> 00:35:41,480 Speaker 9: flow of how our assets are diversified and they continue 689 00:35:41,520 --> 00:35:42,200 Speaker 9: to perform as. 690 00:35:42,160 --> 00:35:45,240 Speaker 3: Expected, So how are they like forty sixty or sixty 691 00:35:45,360 --> 00:35:47,399 Speaker 3: forty maybe a thing of the past. There's different mix 692 00:35:47,440 --> 00:35:49,759 Speaker 3: in there, especially when it comes to alternative assets. What's 693 00:35:49,800 --> 00:35:50,319 Speaker 3: the best mix. 694 00:35:50,520 --> 00:35:53,279 Speaker 9: We're about thirty five percent in alternative assets at this point. 695 00:35:53,480 --> 00:35:56,400 Speaker 9: That's a lot, yeah, yeah, yeah, And that includes you know, 696 00:35:56,440 --> 00:36:00,719 Speaker 9: private equity, infrastructure, private credit, some small all exposure to 697 00:36:00,760 --> 00:36:04,480 Speaker 9: hedge funds in real estate. Of this other sixty five percent, 698 00:36:04,600 --> 00:36:08,000 Speaker 9: we're about almost forty percent of that is in equity, 699 00:36:08,680 --> 00:36:12,640 Speaker 9: dominated by US equity, about eighty five percent US large 700 00:36:12,640 --> 00:36:15,799 Speaker 9: cap in particular. And then an allocation to develop market 701 00:36:15,760 --> 00:36:18,680 Speaker 9: actually US and emerging market. So we're balanced. We're balanced 702 00:36:18,680 --> 00:36:21,400 Speaker 9: from a private perspective, we're balanced from a public perspective, 703 00:36:22,360 --> 00:36:25,000 Speaker 9: and again, I think that's going to benefit us over time. 704 00:36:25,200 --> 00:36:27,080 Speaker 9: With the increase in volatility, have. 705 00:36:27,120 --> 00:36:30,080 Speaker 2: You changed your views on the economy out of the 706 00:36:30,200 --> 00:36:32,680 Speaker 2: US economy or global economy given some of these trade 707 00:36:32,680 --> 00:36:34,200 Speaker 2: tensions that are coming into the marketplace. 708 00:36:34,360 --> 00:36:37,120 Speaker 9: Well, we're concerned about inflation, and we do think we 709 00:36:37,200 --> 00:36:40,680 Speaker 9: have some natural hedges against inflation and a portfolio terms 710 00:36:40,680 --> 00:36:44,200 Speaker 9: of a real asset allocation, real estate, infrastructure. I think 711 00:36:44,200 --> 00:36:46,759 Speaker 9: our public equities will actually perform well over time in 712 00:36:46,800 --> 00:36:51,680 Speaker 9: a higher inflationary environment. So we're not necessarily overly concerned. 713 00:36:52,239 --> 00:36:56,240 Speaker 9: We did expect to see some uplift in inflation expectations 714 00:36:56,360 --> 00:37:01,680 Speaker 9: given concerns about you know, the imposition riffs, the mass 715 00:37:01,960 --> 00:37:04,880 Speaker 9: deportations that we're talked about anyway in terms of potentially 716 00:37:05,440 --> 00:37:08,680 Speaker 9: impacting the price of labor. So again, haven't really changed 717 00:37:08,719 --> 00:37:10,239 Speaker 9: what we're doing or how we're doing it, but we're 718 00:37:10,480 --> 00:37:13,239 Speaker 9: certainly mindful and we continue to monitor the situations. 719 00:37:13,520 --> 00:37:16,080 Speaker 3: Before we let you go, you mentioned thirty five percent 720 00:37:16,280 --> 00:37:17,000 Speaker 3: in alternatives. 721 00:37:17,040 --> 00:37:17,680 Speaker 2: Seems like a lot. 722 00:37:17,760 --> 00:37:19,320 Speaker 3: Is there a liquidity issue there? 723 00:37:19,640 --> 00:37:22,200 Speaker 9: Not really compared to some of our peers, and I know, 724 00:37:22,520 --> 00:37:25,920 Speaker 9: you know, other institutional investors were just under three hundred 725 00:37:25,920 --> 00:37:28,440 Speaker 9: billion dollars in assets, So I understand that there are 726 00:37:28,440 --> 00:37:31,640 Speaker 9: other managers out there that have forty forty five fifty 727 00:37:31,640 --> 00:37:34,560 Speaker 9: percent allocation to alternatives. We have ample liquidity through the 728 00:37:34,600 --> 00:37:38,120 Speaker 9: sixty five percent in public markets. Again, we're disciplined in 729 00:37:38,160 --> 00:37:41,320 Speaker 9: terms of putting money to work. Over time, we're benefiting 730 00:37:41,320 --> 00:37:44,960 Speaker 9: from vintage your diversification. We've actually been putting more money 731 00:37:44,960 --> 00:37:47,479 Speaker 9: to work in private assets over the last two years 732 00:37:47,480 --> 00:37:50,400 Speaker 9: with a change of our strategic as allocation, which has 733 00:37:50,440 --> 00:37:52,760 Speaker 9: been beneficial as others have pulled away from the markets. 734 00:37:52,800 --> 00:37:55,719 Speaker 9: We've been actually putting money to work, getting better economics, 735 00:37:55,719 --> 00:37:59,080 Speaker 9: better access to the top managers co investment, as well 736 00:37:59,120 --> 00:38:00,720 Speaker 9: to average down the feed expense. 737 00:38:01,120 --> 00:38:01,400 Speaker 5: All right. 738 00:38:01,400 --> 00:38:04,240 Speaker 3: Thanks to Stephen Meyer, chief Investment Officer and Deputy Comptroller 739 00:38:04,280 --> 00:38:06,960 Speaker 3: for Asset Management at New York City Retirement Systems. 740 00:38:08,160 --> 00:38:12,840 Speaker 1: This is the Bloomberg Intelligence podcast, available on Apple, Spotify 741 00:38:13,040 --> 00:38:16,520 Speaker 1: and anywhere else you get your podcasts. Listen live each 742 00:38:16,520 --> 00:38:20,280 Speaker 1: weekday ten am to noon Eastern on Bloomberg dot com. 743 00:38:20,400 --> 00:38:23,960 Speaker 1: The iHeartRadio app tune In, and the Bloomberg Business app. 744 00:38:24,360 --> 00:38:27,320 Speaker 1: You can also watch us live every weekday on YouTube 745 00:38:27,680 --> 00:38:29,960 Speaker 1: and always on the Bloomberg terminal