1 00:00:02,640 --> 00:00:05,320 Speaker 1: Welcome to the Bloomberg Penel Podcast. I'm Paul Swinge. You, 2 00:00:05,360 --> 00:00:07,680 Speaker 1: along with my co host Lisa Brahma wits each day 3 00:00:07,720 --> 00:00:10,240 Speaker 1: we bring you the most noteworthy and useful interviews for 4 00:00:10,280 --> 00:00:12,520 Speaker 1: you and your money. Whether at the grocery store or 5 00:00:12,560 --> 00:00:15,480 Speaker 1: the trading floor. Find a Bloomberg penl podcast on Apple 6 00:00:15,520 --> 00:00:17,960 Speaker 1: podcast or wherever you listen to podcasts, as well as 7 00:00:17,960 --> 00:00:23,599 Speaker 1: at Bloomberg dot com. If you have an Alexa right now, 8 00:00:23,880 --> 00:00:26,520 Speaker 1: they're probably listening to everything that you're saying. Certainly everything 9 00:00:26,560 --> 00:00:30,280 Speaker 1: that I'm saying, and UH is getting data from you 10 00:00:30,400 --> 00:00:33,320 Speaker 1: and is collecting it and storing it, and the storage 11 00:00:33,320 --> 00:00:36,760 Speaker 1: and the collection of this data and other similar activities 12 00:00:36,800 --> 00:00:40,400 Speaker 1: by other companies is changing the fabric of our society. 13 00:00:40,440 --> 00:00:44,199 Speaker 1: That is the argument put forward by Shoshanna Zubof, Professor 14 00:00:44,240 --> 00:00:46,479 Speaker 1: Amerda at Harvard Business School. She joins us here in 15 00:00:46,520 --> 00:00:49,320 Speaker 1: our Bloomberg Interactive Broker's studio. She is the author of 16 00:00:49,360 --> 00:00:52,080 Speaker 1: a new book which will scare you. It was scary 17 00:00:52,120 --> 00:00:55,960 Speaker 1: to me, but really really interesting. The age of surveillance, capitalism, 18 00:00:55,960 --> 00:00:59,000 Speaker 1: the fight for a human future at the new frontier 19 00:00:59,400 --> 00:01:03,080 Speaker 1: of power are so so Shauna, What prompted you to 20 00:01:03,120 --> 00:01:06,320 Speaker 1: write this story. How does it differ from what people 21 00:01:06,319 --> 00:01:09,240 Speaker 1: have been arguing, which is that you know, these companies 22 00:01:09,280 --> 00:01:11,319 Speaker 1: have too much of a grip on what we do 23 00:01:11,400 --> 00:01:14,479 Speaker 1: every day and can market our daily routines to uh 24 00:01:15,040 --> 00:01:23,200 Speaker 1: two potential companies. Well, you know, surveillance capitalism is a 25 00:01:23,319 --> 00:01:26,840 Speaker 1: very specific logic of capitalism that differs from what we've 26 00:01:26,880 --> 00:01:30,800 Speaker 1: seen in the past. And while it began in the 27 00:01:30,959 --> 00:01:34,679 Speaker 1: big internet companies, first Google, then Facebook, then the tech sector, 28 00:01:35,200 --> 00:01:39,759 Speaker 1: it is now spreading across across the normal economy into 29 00:01:39,840 --> 00:01:44,160 Speaker 1: literally every economic sector. So we're talking about something now 30 00:01:44,200 --> 00:01:46,880 Speaker 1: that is becoming the dominant form of capitalism in our time. 31 00:01:47,520 --> 00:01:53,400 Speaker 1: It has very specific consequences for individuals and for democracy, 32 00:01:53,920 --> 00:01:59,200 Speaker 1: consequences that are in their own way, violent and destructive. 33 00:01:59,600 --> 00:02:02,200 Speaker 1: And that it's what drove me to spend seven years 34 00:02:02,200 --> 00:02:05,320 Speaker 1: working on this book. All right, can you um shna, 35 00:02:05,360 --> 00:02:09,760 Speaker 1: can you give us some examples of surveillance capitalism from 36 00:02:09,800 --> 00:02:14,359 Speaker 1: your perspective? Yes, of course, So let me go back 37 00:02:14,400 --> 00:02:17,840 Speaker 1: and define surveillance capitalism if I might, just quite briefly, 38 00:02:18,320 --> 00:02:20,600 Speaker 1: and then we can we can look at some examples. 39 00:02:21,280 --> 00:02:26,040 Speaker 1: So it has long been understood that capitalism evolved by 40 00:02:26,200 --> 00:02:30,240 Speaker 1: taking things that exist outside the marketplace, bringing them into 41 00:02:30,240 --> 00:02:33,280 Speaker 1: the market dynamic so that they can be sold as 42 00:02:33,280 --> 00:02:38,680 Speaker 1: commodities and purchased. Industrial capitalism claim nature for the market 43 00:02:38,760 --> 00:02:42,680 Speaker 1: dynamic reborn as real estate, as land that could be 44 00:02:42,840 --> 00:02:47,880 Speaker 1: sold and purchased. In the case of surveillance capitalism, it 45 00:02:48,040 --> 00:02:51,280 Speaker 1: seems to emulate this pattern, but it does so with 46 00:02:51,320 --> 00:02:57,440 Speaker 1: a dark and unexpected twist. Surveillance capitalism goes after the 47 00:02:57,560 --> 00:03:03,120 Speaker 1: last virgin would to turn into commodities, and it turns 48 00:03:03,160 --> 00:03:08,400 Speaker 1: out that this last virgin wood is our private human experience. 49 00:03:09,400 --> 00:03:14,400 Speaker 1: It unilaterally claims our experience as a free source of 50 00:03:14,520 --> 00:03:20,280 Speaker 1: raw material to be translated into behavioral data, which are 51 00:03:20,320 --> 00:03:25,160 Speaker 1: then shunted into its manufacturing processes, which we call artificial 52 00:03:25,160 --> 00:03:33,000 Speaker 1: intelligence machine intelligence. From those black boxes are produced surveillance 53 00:03:33,080 --> 00:03:38,440 Speaker 1: capitalism's products. These products are actually predictions of our future behavior, 54 00:03:38,960 --> 00:03:42,560 Speaker 1: predictions of what we will do now soon and later. 55 00:03:43,360 --> 00:03:45,960 Speaker 1: Turns out there are a lot of businesses who are 56 00:03:46,080 --> 00:03:51,360 Speaker 1: interested in knowing our futures, and these businesses constitute new 57 00:03:51,400 --> 00:03:56,560 Speaker 1: prediction markets where these new prediction products are sold to 58 00:03:56,680 --> 00:03:59,680 Speaker 1: businesses who have an interest in knowing what we're about 59 00:03:59,680 --> 00:04:02,800 Speaker 1: to do. This logic that I've just described to you 60 00:04:03,720 --> 00:04:07,320 Speaker 1: was first invented in the context of online targeted advertising, 61 00:04:08,240 --> 00:04:11,040 Speaker 1: and the bit of future behavior that was being predicted 62 00:04:11,680 --> 00:04:16,960 Speaker 1: is what the folks called click through rates. And the 63 00:04:17,000 --> 00:04:20,760 Speaker 1: business customers who came into these markets to bet on 64 00:04:20,960 --> 00:04:25,800 Speaker 1: click through rates are people that we call advertisers, specifically 65 00:04:25,839 --> 00:04:29,840 Speaker 1: online advertisers. And what they did was they gave up 66 00:04:30,320 --> 00:04:34,120 Speaker 1: all of the old premises of advertising in order to 67 00:04:34,320 --> 00:04:39,600 Speaker 1: buy into Google's black box. And Google's black box said 68 00:04:39,680 --> 00:04:41,920 Speaker 1: We're not going to let you know what is the 69 00:04:42,000 --> 00:04:44,120 Speaker 1: data that goes into the box, or what are the 70 00:04:44,160 --> 00:04:47,400 Speaker 1: computations we make. There's gonna it's gonna spit out a result, 71 00:04:47,720 --> 00:04:50,040 Speaker 1: and if you put your add down where it tells 72 00:04:50,040 --> 00:04:52,400 Speaker 1: you to, you will make a lot of money. And 73 00:04:52,520 --> 00:04:56,680 Speaker 1: indeed that is exactly what happened. The final point on 74 00:04:56,720 --> 00:05:01,720 Speaker 1: this is that while surveillance capitalism originated in this context 75 00:05:01,720 --> 00:05:06,359 Speaker 1: of online targeted advertising, it is no more confined to 76 00:05:06,480 --> 00:05:10,839 Speaker 1: that context. We have learned then, let's say mass production 77 00:05:11,400 --> 00:05:15,640 Speaker 1: is confined to the original production of Ford model t s, 78 00:05:16,200 --> 00:05:18,720 Speaker 1: you know, back in early twentieth century. So so I 79 00:05:18,760 --> 00:05:22,200 Speaker 1: guess then the question becomes, you know, would people use 80 00:05:22,360 --> 00:05:24,880 Speaker 1: this data and the sort of predictive power that it 81 00:05:24,960 --> 00:05:28,920 Speaker 1: has when paired with artificial intelligence and machine learning to 82 00:05:29,240 --> 00:05:34,520 Speaker 1: manipulate behaviors aside from by my product. And you know, 83 00:05:34,680 --> 00:05:37,560 Speaker 1: how do you see that being born out? Okay, that's 84 00:05:37,600 --> 00:05:41,440 Speaker 1: such a good question, Lisa, because that brings us to 85 00:05:41,480 --> 00:05:44,640 Speaker 1: the heart of the economic imperatives. That may sound like 86 00:05:44,680 --> 00:05:47,400 Speaker 1: a bit of jargon, but the idea here is that 87 00:05:47,839 --> 00:05:51,520 Speaker 1: once you understand that this is an economic logic, it's 88 00:05:51,600 --> 00:05:56,160 Speaker 1: not the same as technology. It's not the same as 89 00:05:56,279 --> 00:06:01,359 Speaker 1: digital technology. This economic logic require there's digital technology to 90 00:06:01,400 --> 00:06:06,160 Speaker 1: express itself. But we can easily imagine digital technology without 91 00:06:06,200 --> 00:06:09,640 Speaker 1: surveillance capitalism. We can, and we have, and I can 92 00:06:09,680 --> 00:06:12,920 Speaker 1: give you examples of that. But at this point what 93 00:06:12,960 --> 00:06:19,400 Speaker 1: we see is surveillance capitalism is the puppet master. The 94 00:06:19,480 --> 00:06:22,960 Speaker 1: digital technology is simply the puppet. So we have this 95 00:06:23,160 --> 00:06:29,160 Speaker 1: hijacking of the digital for these specific commercial goals. And 96 00:06:29,240 --> 00:06:33,040 Speaker 1: within this logic, um, longer I've studied it, the more 97 00:06:33,080 --> 00:06:37,159 Speaker 1: I've come to understand there are very specific and imperative, 98 00:06:37,520 --> 00:06:42,760 Speaker 1: sorry specific and predictable and um economic imperatives. That's part 99 00:06:42,800 --> 00:06:49,200 Speaker 1: of the logic. As they follow these economic imperatives, where 100 00:06:49,200 --> 00:06:52,040 Speaker 1: do the economic comparatives come from They come from competition. 101 00:06:52,760 --> 00:06:55,480 Speaker 1: What are they competing over? They're competing over who has 102 00:06:55,520 --> 00:06:58,360 Speaker 1: the best predictions. How do you get the best predictions? 103 00:06:59,279 --> 00:07:02,480 Speaker 1: First of all, you must have a lot of data, 104 00:07:02,600 --> 00:07:07,120 Speaker 1: So that's imperative number one. You need scale, you need volume, alright, 105 00:07:07,160 --> 00:07:12,160 Speaker 1: they're competing on volume. New competitive demands arise. We need 106 00:07:12,240 --> 00:07:14,880 Speaker 1: not only a lot of data, we need different kinds 107 00:07:14,880 --> 00:07:18,040 Speaker 1: of data, varied data. So we need scale and we 108 00:07:18,120 --> 00:07:23,000 Speaker 1: need scope. We're competing. New competitive demands arise. Then they 109 00:07:23,080 --> 00:07:28,720 Speaker 1: discover that the very best, the choicest predictive data comes 110 00:07:28,720 --> 00:07:34,080 Speaker 1: from actually being able to intervene in the state of play, 111 00:07:34,120 --> 00:07:38,520 Speaker 1: intervene in your behavior, to subtly and outside of your awareness, 112 00:07:39,440 --> 00:07:45,280 Speaker 1: shape and herd and tune your behavior towards their commercial outcomes. Wow, 113 00:07:45,440 --> 00:07:47,800 Speaker 1: that is externally interesting. We could have a whole show 114 00:07:47,840 --> 00:07:51,880 Speaker 1: on this. Uh. Shoshanna Zuba, Professor Amerita Harvard Business School, 115 00:07:52,160 --> 00:07:55,120 Speaker 1: author of the book The Age of Surveillance Capitalism, The 116 00:07:55,280 --> 00:07:58,880 Speaker 1: fight part fascinating. Yeah, yeah, the fight for a human 117 00:07:58,920 --> 00:08:01,600 Speaker 1: future at that new frontier of power. Thank you very 118 00:08:01,680 --> 00:08:04,679 Speaker 1: much for joining us in our Bloomberg Interactive Broker studio. 119 00:08:05,120 --> 00:08:07,280 Speaker 1: We will certainly love to follow up on that. I'm 120 00:08:07,280 --> 00:08:22,360 Speaker 1: sure that will spur a lot of discussions. Well, it 121 00:08:22,400 --> 00:08:25,680 Speaker 1: looks like ride sharing company Lift is going to beat 122 00:08:25,760 --> 00:08:29,160 Speaker 1: its Uber competitor Uber to the I p O market. 123 00:08:29,480 --> 00:08:32,400 Speaker 1: We're expecting a filing and IPO filing from Lift sometime 124 00:08:32,480 --> 00:08:37,760 Speaker 1: today seeking evaluation up to twenty billion dollars for the 125 00:08:37,880 --> 00:08:40,920 Speaker 1: ride sharing company. Help us dig into this pending I 126 00:08:41,000 --> 00:08:42,920 Speaker 1: p O. As Man Deep seeing, Man Deep is a 127 00:08:43,000 --> 00:08:47,719 Speaker 1: senior technology industry analysts Bloomberg Intelligence covering all things software. 128 00:08:48,040 --> 00:08:50,480 Speaker 1: He joins us on a Bloomberg Interact to Broker Studio 129 00:08:50,760 --> 00:08:53,280 Speaker 1: here in New York. Man Deep, thanks for joining us. So, 130 00:08:53,520 --> 00:08:56,720 Speaker 1: first of all, how important is it for Lift to 131 00:08:57,400 --> 00:09:01,360 Speaker 1: be first to market visa the Uber? Sure? So we 132 00:09:01,440 --> 00:09:04,840 Speaker 1: think since Lift is the smaller guy, and you know, 133 00:09:05,000 --> 00:09:08,520 Speaker 1: they don't have the same branding as Uber has, you 134 00:09:08,559 --> 00:09:11,840 Speaker 1: know globally, it makes sense for them to go first 135 00:09:12,240 --> 00:09:15,920 Speaker 1: simply because they can generate some excitement around the numbers. 136 00:09:16,080 --> 00:09:18,600 Speaker 1: You know, the fact that this is a large market. 137 00:09:18,720 --> 00:09:21,360 Speaker 1: We think it could be a trillion dollar market in 138 00:09:21,400 --> 00:09:25,000 Speaker 1: the next five years. I think it makes sense for 139 00:09:25,040 --> 00:09:27,520 Speaker 1: them to go first just because of you know the 140 00:09:27,559 --> 00:09:30,199 Speaker 1: fact that they are the smaller guy and and they 141 00:09:30,240 --> 00:09:33,240 Speaker 1: can garner a higher evaluation if they were to go first. 142 00:09:33,360 --> 00:09:36,720 Speaker 1: So let's say Lift does get evaluation between twenty and 143 00:09:37,280 --> 00:09:40,120 Speaker 1: billion dollars, which I believe is the target. Correct. What 144 00:09:40,240 --> 00:09:43,480 Speaker 1: does that say about the valuation of Uber? Yeah, so 145 00:09:43,600 --> 00:09:46,480 Speaker 1: we value the company based on its sales right now. 146 00:09:46,520 --> 00:09:49,240 Speaker 1: So from what we know, the trailing twelve month sales 147 00:09:49,400 --> 00:09:53,240 Speaker 1: for Lift with is somewhere around two billion dollars. And 148 00:09:53,440 --> 00:09:57,040 Speaker 1: if they do if they're doing like about fifty growth 149 00:09:57,080 --> 00:10:01,800 Speaker 1: next year, so based on afford multiple, they around twenty five. 150 00:10:01,920 --> 00:10:05,360 Speaker 1: Like you said, so Uber is five times left. Uber 151 00:10:05,520 --> 00:10:09,679 Speaker 1: is revenue somewhere around eleven to twelve billion dollars. If 152 00:10:09,720 --> 00:10:12,480 Speaker 1: you value them, you know, based on the fact that 153 00:10:12,520 --> 00:10:16,920 Speaker 1: they could grow thirty next couple of years, We're talking 154 00:10:16,920 --> 00:10:19,640 Speaker 1: about at least a hundred billion dollar evaluation for Uber. 155 00:10:20,120 --> 00:10:22,040 Speaker 1: So I'd like to say a lot of men deeps 156 00:10:22,040 --> 00:10:25,760 Speaker 1: companies you have to value on revenue because there's little 157 00:10:25,800 --> 00:10:28,240 Speaker 1: to no cash load, there's little to no earnings. So 158 00:10:28,320 --> 00:10:31,360 Speaker 1: let's go down the income statement here for Uber, is 159 00:10:31,360 --> 00:10:33,880 Speaker 1: a company profitable? If not, when do you think it 160 00:10:33,960 --> 00:10:38,400 Speaker 1: becomes profitable? Yeah, So that's the uncertainty around the business 161 00:10:38,400 --> 00:10:42,360 Speaker 1: model for these companies, the fact that it's a large market, 162 00:10:42,480 --> 00:10:45,320 Speaker 1: the fact that these guys are have a duopoli uber 163 00:10:45,360 --> 00:10:48,920 Speaker 1: on Lift is great, but when it comes to gross margins, 164 00:10:49,080 --> 00:10:51,880 Speaker 1: we still don't know if their gross margins are as 165 00:10:51,920 --> 00:10:55,000 Speaker 1: high as other tech companies, that it could happen that 166 00:10:55,040 --> 00:10:58,320 Speaker 1: they are subsidizing their rides and drivers so much that 167 00:10:58,400 --> 00:11:03,080 Speaker 1: their gross margins are sub which we think could be 168 00:11:03,120 --> 00:11:06,360 Speaker 1: a headwind for profitability in the next three or four years. 169 00:11:06,679 --> 00:11:09,240 Speaker 1: And that's the biggest concern that the fact that they're 170 00:11:09,280 --> 00:11:12,600 Speaker 1: not cash flow positive, the fact that if their growth 171 00:11:12,679 --> 00:11:15,480 Speaker 1: margins are lower than other tech companies, then what's the 172 00:11:15,520 --> 00:11:19,199 Speaker 1: path to profitability? And that's an unanswered question. So Lift, 173 00:11:19,400 --> 00:11:22,959 Speaker 1: like Uber and other tech companies, have relied on private 174 00:11:22,960 --> 00:11:26,840 Speaker 1: markets and debt markets until this point to finance themselves 175 00:11:26,920 --> 00:11:30,160 Speaker 1: and have leaned heavily on those markets. And I'm just wondering, 176 00:11:30,480 --> 00:11:33,040 Speaker 1: at this point in the life cycle of Lift and 177 00:11:33,120 --> 00:11:37,360 Speaker 1: soon to be Uber, how much upside could there potentially 178 00:11:37,360 --> 00:11:40,000 Speaker 1: be for equity investors. In other words, is this still 179 00:11:40,679 --> 00:11:43,400 Speaker 1: very much a growth story that they're peddling, or is 180 00:11:43,440 --> 00:11:46,440 Speaker 1: this a mature company that is going to try to 181 00:11:46,440 --> 00:11:50,480 Speaker 1: solidify their market share. Oh, it is definitely a growth story. 182 00:11:50,640 --> 00:11:52,800 Speaker 1: I mean, I go back to the fact that no 183 00:11:52,840 --> 00:11:55,880 Speaker 1: matter how you slice this market based on the total 184 00:11:55,960 --> 00:11:59,720 Speaker 1: number of milds travel globally, which is close to eight 185 00:12:00,000 --> 00:12:03,200 Speaker 1: million miles, so you know, right, sharing is still sup 186 00:12:03,280 --> 00:12:06,800 Speaker 1: five percent of the total miles travel. And the fact 187 00:12:06,840 --> 00:12:11,840 Speaker 1: that everyone has a smartphone. Now you can track their location, 188 00:12:11,960 --> 00:12:15,040 Speaker 1: you can offer them mobility services. These guys can expand 189 00:12:15,040 --> 00:12:19,280 Speaker 1: into food delivery. But but what's the barrier to entry here? Well, 190 00:12:19,320 --> 00:12:22,320 Speaker 1: the barrier to entry is the scale. So the fact 191 00:12:22,360 --> 00:12:24,840 Speaker 1: that Uber has a scale, d D has a scale 192 00:12:24,880 --> 00:12:27,520 Speaker 1: in China, Lift to an extent is the number two 193 00:12:27,559 --> 00:12:31,479 Speaker 1: in the US. Once you have scale, you have network effects, 194 00:12:31,559 --> 00:12:33,960 Speaker 1: and this is a mode that keeps growing because you 195 00:12:34,000 --> 00:12:38,600 Speaker 1: are constantly acquiring more data about the rides, about you know, people, 196 00:12:39,160 --> 00:12:42,800 Speaker 1: and over time, this is a mode that's hard to crack. So, 197 00:12:43,400 --> 00:12:45,360 Speaker 1: being first out to the marketplace, what do you think 198 00:12:45,440 --> 00:12:47,320 Speaker 1: Lift is going to do or say to try to 199 00:12:47,320 --> 00:12:51,920 Speaker 1: differentiate itself from Uber. Yeah, so we think the fact 200 00:12:52,000 --> 00:12:54,800 Speaker 1: that Lift focuses more on the US market, which has 201 00:12:54,880 --> 00:12:58,920 Speaker 1: higher a SPS in terms of the average ride. You know, 202 00:12:59,040 --> 00:13:02,880 Speaker 1: compare them to globally, the average costs provide is much lower, 203 00:13:03,040 --> 00:13:06,360 Speaker 1: so US is a much more attractive market from a 204 00:13:06,400 --> 00:13:10,560 Speaker 1: profitability perspective. And now they have expanded into China and 205 00:13:10,559 --> 00:13:13,480 Speaker 1: and lifts market share is growing in the US. So 206 00:13:13,679 --> 00:13:17,640 Speaker 1: Uber previously had eight percent share, now it's seventy and 207 00:13:17,760 --> 00:13:21,320 Speaker 1: Lift is closed to so we think the fact that 208 00:13:21,360 --> 00:13:24,840 Speaker 1: they are more domestically focused, which is a more attractive market, 209 00:13:25,000 --> 00:13:26,800 Speaker 1: is good for a LIFT. Thank you so much for 210 00:13:26,840 --> 00:13:28,600 Speaker 1: being with us. We know you've got a busy few 211 00:13:28,640 --> 00:13:30,560 Speaker 1: weeks ahead of you, but deep saying it. Is a 212 00:13:30,559 --> 00:13:49,400 Speaker 1: senior tech industry analyst for Bloomberg Intelligence, we hear a 213 00:13:49,400 --> 00:13:52,280 Speaker 1: lot about trade. The question now is what will be 214 00:13:52,320 --> 00:13:55,120 Speaker 1: the impact on the global economy. And there is no 215 00:13:55,440 --> 00:13:58,600 Speaker 1: better industry to have a good window into this than 216 00:13:58,679 --> 00:14:01,679 Speaker 1: the shipping industry. Enjoying us here is Victor Garcia, chief 217 00:14:01,679 --> 00:14:05,280 Speaker 1: executive officer of c AI International, based in San Francisco, 218 00:14:05,280 --> 00:14:08,360 Speaker 1: but he enjoins is here in our Bloomberg Interactive Brokers studios. 219 00:14:08,360 --> 00:14:10,839 Speaker 1: So Victor, before we get started, watch tell us just 220 00:14:10,920 --> 00:14:13,280 Speaker 1: a little bit about your business and and how much 221 00:14:13,320 --> 00:14:16,080 Speaker 1: it gives you a sense of the global economy. Sure, 222 00:14:16,120 --> 00:14:18,599 Speaker 1: thank you for having me. Our business. We're in the 223 00:14:19,240 --> 00:14:21,480 Speaker 1: marine container re leasing business. It's a global business. We 224 00:14:21,480 --> 00:14:23,640 Speaker 1: have about a million containers that go around and we 225 00:14:23,760 --> 00:14:27,800 Speaker 1: ship uh we leased containers to the global shipping lines. 226 00:14:27,840 --> 00:14:31,760 Speaker 1: And so we've been were thirty year company, publicly traded um. 227 00:14:31,840 --> 00:14:34,640 Speaker 1: We we have about two billion dollars in assets. We 228 00:14:34,720 --> 00:14:36,440 Speaker 1: continue to grow. We had a big year last year. 229 00:14:36,480 --> 00:14:39,400 Speaker 1: We grew. We also have two other businesses of rail 230 00:14:39,440 --> 00:14:41,880 Speaker 1: car leasing business to you know, based in the United States, 231 00:14:42,280 --> 00:14:45,920 Speaker 1: basic commodities that we move around, energy, agriculture and things 232 00:14:45,920 --> 00:14:47,880 Speaker 1: like that. And then we in the United States, we 233 00:14:47,880 --> 00:14:51,960 Speaker 1: also have a global logistics business, so we do brokerage 234 00:14:51,960 --> 00:14:55,160 Speaker 1: and and intermortal movements. So with a million containers all 235 00:14:55,200 --> 00:14:57,600 Speaker 1: around the world, obviously you get a great sense of 236 00:14:57,840 --> 00:15:00,440 Speaker 1: you know, global trade in general. So what kind of 237 00:15:00,440 --> 00:15:01,920 Speaker 1: what are you feeling right now? I know there's a 238 00:15:01,960 --> 00:15:04,280 Speaker 1: lot of trade uncertainty out there right now, but kind 239 00:15:04,280 --> 00:15:06,040 Speaker 1: of what is your business? What are your customers telling 240 00:15:06,040 --> 00:15:08,880 Speaker 1: you now about their prospects for global trade? Okay, So 241 00:15:08,920 --> 00:15:11,800 Speaker 1: what I would say is almost uniformally, particularly on the 242 00:15:11,840 --> 00:15:16,720 Speaker 1: international side, there is a cautious optimism. There's a there's 243 00:15:16,720 --> 00:15:19,720 Speaker 1: a feeling that there's an underlying strength to the to 244 00:15:19,800 --> 00:15:23,040 Speaker 1: the economy, even the global economy that is buttressing some 245 00:15:23,080 --> 00:15:26,200 Speaker 1: of these concerns. But as they look forward, UH, they 246 00:15:26,240 --> 00:15:29,160 Speaker 1: are concerned about what the implications could be of if 247 00:15:29,160 --> 00:15:32,760 Speaker 1: the tariffs continue to be escalated. But what they're seeing 248 00:15:32,800 --> 00:15:36,560 Speaker 1: today is still good underlying demand. The U s economy 249 00:15:36,600 --> 00:15:40,000 Speaker 1: continues to be the strength of the global economy. UH. 250 00:15:40,040 --> 00:15:42,880 Speaker 1: There is concern about the amount of slippage that we're 251 00:15:42,880 --> 00:15:46,400 Speaker 1: seeing in China. Southeast Asia starting to get a little 252 00:15:46,400 --> 00:15:48,160 Speaker 1: bit affected by that because they do a lot of 253 00:15:48,160 --> 00:15:51,760 Speaker 1: trade with China, but but it's a moderate degree at 254 00:15:51,760 --> 00:15:55,400 Speaker 1: this point. So I'm trying to reconcile the strength that 255 00:15:55,440 --> 00:15:58,160 Speaker 1: you're talking about. With the dry bulk index, which a 256 00:15:58,200 --> 00:16:00,840 Speaker 1: lot of people use, is sort of engage of the economy. 257 00:16:00,880 --> 00:16:02,440 Speaker 1: It sort of gives you a sense of the cost 258 00:16:02,480 --> 00:16:05,440 Speaker 1: of some of these containers to to ship goods. I'm 259 00:16:05,480 --> 00:16:08,440 Speaker 1: just wondering, it's near it's all time lows. That doesn't 260 00:16:08,480 --> 00:16:11,120 Speaker 1: give a very positive outlook on the economy. What are 261 00:16:11,200 --> 00:16:14,720 Speaker 1: you seeing that gives you, that gives your customers a 262 00:16:14,760 --> 00:16:19,280 Speaker 1: sense of confidence here, So the dry bulk Industry index 263 00:16:19,560 --> 00:16:22,560 Speaker 1: tends to focus more on basic commodities. So so those 264 00:16:23,080 --> 00:16:25,400 Speaker 1: basic commodities have been on a decline, and I think 265 00:16:25,440 --> 00:16:28,560 Speaker 1: that's reflective of of what's going on in China's concern 266 00:16:28,640 --> 00:16:31,040 Speaker 1: about China itself. A lot of the stuff that moves 267 00:16:31,040 --> 00:16:34,040 Speaker 1: in our containers tends to be consumer driven, and the 268 00:16:34,080 --> 00:16:36,960 Speaker 1: consumer globally, for the most part, is doing pretty well. 269 00:16:37,080 --> 00:16:39,000 Speaker 1: So what's hot right now that you see a lot 270 00:16:39,040 --> 00:16:41,720 Speaker 1: of you know, getting shipped more frequently, Well, we don't 271 00:16:41,760 --> 00:16:43,680 Speaker 1: We don't know exactly what's in the containers, but I 272 00:16:43,680 --> 00:16:46,720 Speaker 1: would say most most commodities that would you would be 273 00:16:46,720 --> 00:16:50,680 Speaker 1: finding an Amazon or or in a Walmart. Um, those 274 00:16:50,720 --> 00:16:53,720 Speaker 1: are the kind of things electronics we're seeing a lot of. So, 275 00:16:53,800 --> 00:16:55,440 Speaker 1: you know, that's one of the things we talked about 276 00:16:55,440 --> 00:16:59,520 Speaker 1: little bit earlier with this incredible growth of just you know, 277 00:16:59,560 --> 00:17:04,280 Speaker 1: Amazon on you know, free shipping just in time to delivery. Um, 278 00:17:04,400 --> 00:17:06,399 Speaker 1: how has that changed your business in the shipping business 279 00:17:06,400 --> 00:17:09,760 Speaker 1: in general, Well, everybody's expecting just in time, So supply 280 00:17:09,840 --> 00:17:13,119 Speaker 1: chains are getting tighter, Uh, inventories are more limited than 281 00:17:13,119 --> 00:17:16,720 Speaker 1: they used to be. Responsiveness is important. Um. One of 282 00:17:16,720 --> 00:17:18,560 Speaker 1: the things that the supply chains are all dealing with 283 00:17:18,680 --> 00:17:22,119 Speaker 1: is a capacity shortage, particularly United States. You know, labor 284 00:17:22,320 --> 00:17:26,119 Speaker 1: and UH equipment capacity is limited, which means everybody has 285 00:17:26,119 --> 00:17:28,040 Speaker 1: to even be more focused to be able to deliver 286 00:17:28,119 --> 00:17:32,520 Speaker 1: on time. So I'm I'm struggling to understand this sort 287 00:17:32,520 --> 00:17:34,679 Speaker 1: of strength that you're talking about. You're saying that it 288 00:17:34,760 --> 00:17:37,160 Speaker 1: is being driven by the United States, which makes sense 289 00:17:37,200 --> 00:17:39,840 Speaker 1: to me. Are there other regions in the world that 290 00:17:39,920 --> 00:17:44,439 Speaker 1: you think are stronger economically than many give credit to? Well, 291 00:17:44,480 --> 00:17:46,879 Speaker 1: I'd say if you look down in Latin America, that's recovering. 292 00:17:47,119 --> 00:17:49,960 Speaker 1: It's Uh. Latin America has been a brazili in particular 293 00:17:50,000 --> 00:17:53,040 Speaker 1: has been a soft spot, but that's coming back. UM. 294 00:17:53,240 --> 00:17:58,040 Speaker 1: I think confidence back in Brazil. Um. Europe has been um, 295 00:17:58,119 --> 00:18:01,000 Speaker 1: not as strong, but it was still seeing some strength 296 00:18:01,040 --> 00:18:04,080 Speaker 1: out of Europe. We haven't seen any effects from Brexit. Um, 297 00:18:04,080 --> 00:18:06,560 Speaker 1: we're not seeing any disruptions. I think everybody's expecting that 298 00:18:06,640 --> 00:18:11,399 Speaker 1: something will get resolved. UM. So Europe continues to move along, 299 00:18:11,440 --> 00:18:14,159 Speaker 1: although it slowed a little bit, but everything has been 300 00:18:14,200 --> 00:18:16,480 Speaker 1: pretty tight. So for your business, what's I know you 301 00:18:16,560 --> 00:18:19,520 Speaker 1: just reported uh earning a couple of weeks ago. What's 302 00:18:19,600 --> 00:18:21,960 Speaker 1: driving your business here over the next you know, over 303 00:18:22,000 --> 00:18:24,560 Speaker 1: the twenty nineteen what are the key drivers for your company, 304 00:18:24,680 --> 00:18:28,199 Speaker 1: It's gonna be volume we have our Our business is 305 00:18:28,200 --> 00:18:30,800 Speaker 1: contractual nature, so we build off every year. So we 306 00:18:30,800 --> 00:18:34,000 Speaker 1: we've built a lot of investment over the last couple 307 00:18:34,040 --> 00:18:37,679 Speaker 1: of years. About of our overall investment has been over 308 00:18:37,680 --> 00:18:40,080 Speaker 1: the last couple of years, and so we continue to 309 00:18:40,119 --> 00:18:42,640 Speaker 1: do that, and we see and we are are people 310 00:18:42,640 --> 00:18:45,040 Speaker 1: are talking to our customers and it's a good situation 311 00:18:45,119 --> 00:18:47,119 Speaker 1: for us because of the uncertainty. They tend not to 312 00:18:47,160 --> 00:18:50,239 Speaker 1: make our own purchasing decisions and they're depending on us 313 00:18:50,240 --> 00:18:52,680 Speaker 1: to be able to supply them. So I think we 314 00:18:52,680 --> 00:18:55,040 Speaker 1: we have the opportunity to actually have a pretty strong 315 00:18:55,040 --> 00:18:57,159 Speaker 1: two thousand nineteen. What keeps you up at night? What 316 00:18:57,200 --> 00:18:59,200 Speaker 1: do you worry about? Worry about? As far as a 317 00:18:59,280 --> 00:19:02,040 Speaker 1: sort of win to this whole scenario, I think it 318 00:19:02,040 --> 00:19:04,000 Speaker 1: would be one of the, you know, an economic shock. 319 00:19:04,040 --> 00:19:05,520 Speaker 1: I think we were worried that the FED was going 320 00:19:05,560 --> 00:19:08,120 Speaker 1: to be increasing rates too aggressively and that would put 321 00:19:08,160 --> 00:19:10,920 Speaker 1: a stall in the economy. I think that's been taken 322 00:19:10,960 --> 00:19:13,120 Speaker 1: off the table. I think most people feel better about that. 323 00:19:13,520 --> 00:19:16,280 Speaker 1: The other would be some kind of systemic risk related 324 00:19:16,320 --> 00:19:18,680 Speaker 1: to the slowdown in China. I think that's that would 325 00:19:18,680 --> 00:19:20,880 Speaker 1: be a concern. You know, we don't see anything right now, 326 00:19:20,920 --> 00:19:22,680 Speaker 1: but that's you know, those are the kind of things 327 00:19:22,680 --> 00:19:26,320 Speaker 1: that could could really disrupt the outlook. Interesting. Thank you 328 00:19:26,400 --> 00:19:28,919 Speaker 1: so very much for a great overview on the global 329 00:19:28,960 --> 00:19:31,639 Speaker 1: shipping business and kind of some of the UM I 330 00:19:31,640 --> 00:19:36,359 Speaker 1: think takeaways. We can you know, glean about global um GDP, 331 00:19:36,480 --> 00:19:38,960 Speaker 1: global economy, gold, global trade. And people like stuff and 332 00:19:39,000 --> 00:19:41,000 Speaker 1: they want their stuff now, and they want their stuff now, 333 00:19:41,000 --> 00:19:42,760 Speaker 1: and they and it comes in containers. You see the 334 00:19:42,840 --> 00:19:46,879 Speaker 1: ships going and port with these monsters containers. That's Victor's company. 335 00:19:46,840 --> 00:19:50,879 Speaker 1: And how about the rail cars with all of those containers. 336 00:19:50,960 --> 00:19:53,359 Speaker 1: I love watching those. Yes, that's very cool the shipping business. 337 00:19:53,760 --> 00:19:55,160 Speaker 1: Victor has to get us on one of those big 338 00:19:55,160 --> 00:19:56,879 Speaker 1: ships one day so we can go out out to 339 00:19:56,920 --> 00:19:59,120 Speaker 1: sea with the big container ships. That'll be our next one, 340 00:19:59,240 --> 00:20:02,680 Speaker 1: our next trip remote. Thank you Victor. We appreciate its 341 00:20:02,720 --> 00:20:05,600 Speaker 1: CEO of c AI internationally in our Bloomberg eleven three 342 00:20:05,600 --> 00:20:23,760 Speaker 1: oh studios. Well, markets have been relatively range bound this week. 343 00:20:23,800 --> 00:20:26,840 Speaker 1: I'm talking about US equities as well as bonds, where 344 00:20:26,840 --> 00:20:30,000 Speaker 1: you can see volatility and implied volatility and treasury yields 345 00:20:30,000 --> 00:20:34,119 Speaker 1: has fallen to nearly all time loads with the smallest 346 00:20:34,359 --> 00:20:37,639 Speaker 1: range of price swings in years. Joining us now as 347 00:20:37,680 --> 00:20:42,080 Speaker 1: Phil Orlando, chief equity market strategist at Federated Investors. Phil, 348 00:20:42,080 --> 00:20:44,800 Speaker 1: has this been an incredibly exciting week for you? It's 349 00:20:44,840 --> 00:20:48,840 Speaker 1: been an incredibly inciting year. This week has been a 350 00:20:48,880 --> 00:20:53,080 Speaker 1: little more, as you said, sort of going sideways. So 351 00:20:53,320 --> 00:20:57,280 Speaker 1: we're Lisa, We're up twenty since Christmas Eve. I mean, 352 00:20:57,320 --> 00:21:00,960 Speaker 1: this is one of the strongest periods of stock market 353 00:21:01,040 --> 00:21:06,560 Speaker 1: performance we've seen, I think since so, you know, roughly 354 00:21:06,600 --> 00:21:10,240 Speaker 1: thirty years. But so then my question is have we 355 00:21:10,280 --> 00:21:13,720 Speaker 1: already gotten all the games or are we just heading 356 00:21:13,720 --> 00:21:17,479 Speaker 1: straight up as the next catalyst gonna send markets shooting higher. 357 00:21:17,960 --> 00:21:20,920 Speaker 1: So we haven't gotten all of the games for the year, 358 00:21:21,000 --> 00:21:25,840 Speaker 1: but we've had a phenomenal run, and frankly, we've been 359 00:21:25,880 --> 00:21:29,000 Speaker 1: looking for the spot where the market was going to 360 00:21:29,119 --> 00:21:32,159 Speaker 1: consolidate and at least take a deep breath. Now. You 361 00:21:32,200 --> 00:21:34,119 Speaker 1: and I talked about earlier in the year that the 362 00:21:34,160 --> 00:21:36,240 Speaker 1: month of March was going to be sort of a 363 00:21:36,280 --> 00:21:39,480 Speaker 1: critical month because there were sort of a couple of 364 00:21:39,520 --> 00:21:42,080 Speaker 1: things that we thought were important coming up. We had 365 00:21:42,080 --> 00:21:45,040 Speaker 1: this trade deal with China in the US. We had 366 00:21:45,040 --> 00:21:48,240 Speaker 1: a deadline set for today that's been sort of extended, 367 00:21:48,280 --> 00:21:50,959 Speaker 1: but the stuff is moving in the right direction. Then 368 00:21:51,000 --> 00:21:52,320 Speaker 1: you've got what I think is going to be a 369 00:21:52,320 --> 00:21:54,639 Speaker 1: critical fo MC meeting in the middle of the month. 370 00:21:54,680 --> 00:21:57,040 Speaker 1: I think it's March twenty, and then you've got this 371 00:21:57,160 --> 00:21:59,280 Speaker 1: Brexit mess at the end of the month. I think 372 00:21:59,320 --> 00:22:02,600 Speaker 1: that's March nine. And so our view is that you know, 373 00:22:02,640 --> 00:22:04,720 Speaker 1: we we'd have a nice bounce to start the year, 374 00:22:04,760 --> 00:22:07,359 Speaker 1: and then you know there might be a little you know, 375 00:22:07,440 --> 00:22:13,720 Speaker 1: consolidation ahead of uh, these three critical signposts in March, 376 00:22:13,800 --> 00:22:17,160 Speaker 1: and then depending upon how well they go, then then 377 00:22:17,320 --> 00:22:20,400 Speaker 1: we sort of continue the rally from there. So I mean, 378 00:22:20,480 --> 00:22:22,359 Speaker 1: it's you bring up a good point because you know, 379 00:22:22,400 --> 00:22:25,360 Speaker 1: we're we're the feed is on the sidelines, we're through earnings, 380 00:22:25,400 --> 00:22:27,480 Speaker 1: and so it seems like the market will be looking 381 00:22:27,560 --> 00:22:31,040 Speaker 1: maybe more than it should towards some of these geopolitical issues. 382 00:22:31,080 --> 00:22:33,320 Speaker 1: But there's always a risk that these things turned the 383 00:22:33,320 --> 00:22:35,760 Speaker 1: wrong way. I mean, Brexit looks as much as up 384 00:22:35,760 --> 00:22:37,800 Speaker 1: in air as it's ever been, and who knows about China, 385 00:22:37,880 --> 00:22:40,120 Speaker 1: So is that more of a risk do you think 386 00:22:40,160 --> 00:22:44,119 Speaker 1: to this market, or certainly with stalks up in the 387 00:22:44,200 --> 00:22:47,240 Speaker 1: last nine weeks. You're You're absolutely right, Paul. But let's 388 00:22:47,280 --> 00:22:49,000 Speaker 1: let's take a look at each of these. Okay, you've 389 00:22:49,000 --> 00:22:52,600 Speaker 1: got China US first. Our view is that China US 390 00:22:52,680 --> 00:22:55,080 Speaker 1: this trade deal is going to go well, but both 391 00:22:55,119 --> 00:22:59,639 Speaker 1: countries are significantly motivated to get a deal. I think 392 00:22:59,720 --> 00:23:01,639 Speaker 1: the thing is moving in the right direction. So of 393 00:23:01,760 --> 00:23:05,480 Speaker 1: the you know, of the three, I feel really comfortable 394 00:23:06,200 --> 00:23:09,240 Speaker 1: that we're going to get a Chinese US trade deal soon, 395 00:23:09,800 --> 00:23:12,000 Speaker 1: and and it's gonna be uh, it's gonna be to 396 00:23:12,080 --> 00:23:14,320 Speaker 1: the U. S A is liking the FED meeting in 397 00:23:14,359 --> 00:23:16,520 Speaker 1: the middle of the month, I'm gonna also put that 398 00:23:16,640 --> 00:23:20,159 Speaker 1: in the wind column. I think that the FED uh, 399 00:23:20,240 --> 00:23:23,720 Speaker 1: you know, if you look at um some of the 400 00:23:23,760 --> 00:23:26,200 Speaker 1: flip flops that we saw over the course of last 401 00:23:26,320 --> 00:23:29,159 Speaker 1: year versus what we've seen this year. You know, the 402 00:23:29,200 --> 00:23:33,199 Speaker 1: Atlanta UH speech in the beginning of January, in a 403 00:23:33,240 --> 00:23:36,040 Speaker 1: c meeting at the end of January, you've had some 404 00:23:36,119 --> 00:23:40,560 Speaker 1: interim comments. I think the FED is has telegraphed that 405 00:23:40,760 --> 00:23:44,800 Speaker 1: at this March twentieth meeting, we're gonna see the FED 406 00:23:44,880 --> 00:23:47,560 Speaker 1: pulling their horns on a couple of dot plots and 407 00:23:47,560 --> 00:23:51,159 Speaker 1: we're gonna see them announce that the wind down of 408 00:23:51,240 --> 00:23:54,200 Speaker 1: the balance sheet is going to be a lot is 409 00:23:54,240 --> 00:23:56,800 Speaker 1: going to end quicker than the market had expected, that 410 00:23:56,800 --> 00:23:58,360 Speaker 1: that maybe to end by the end of the year 411 00:23:58,520 --> 00:24:02,320 Speaker 1: around three and a half trillion dollars. The Brexit situation 412 00:24:02,440 --> 00:24:04,760 Speaker 1: is the biggest wild card at the end of the 413 00:24:04,800 --> 00:24:07,400 Speaker 1: month because we literally have no control over that here 414 00:24:07,400 --> 00:24:10,880 Speaker 1: in the United States, and I don't think uh May 415 00:24:11,080 --> 00:24:13,600 Speaker 1: and the Brits and the Europeans have any idea what 416 00:24:13,640 --> 00:24:16,400 Speaker 1: they're doing on this, so they're gonna be as surprised 417 00:24:16,440 --> 00:24:20,200 Speaker 1: as we are as to how this thing turns out. Um, 418 00:24:20,400 --> 00:24:23,720 Speaker 1: I can I can paint multiple scenarios as to what 419 00:24:23,760 --> 00:24:26,560 Speaker 1: direction this thing goes. I don't have any sense of 420 00:24:26,600 --> 00:24:29,919 Speaker 1: confidence and can't put any probability on what any of 421 00:24:29,920 --> 00:24:32,919 Speaker 1: these scenarios are gonna be. So that could be the 422 00:24:33,000 --> 00:24:36,440 Speaker 1: ultimately wild card that either gives us a correction near 423 00:24:36,600 --> 00:24:39,359 Speaker 1: term or allows the market to say, all right, we've 424 00:24:39,440 --> 00:24:42,560 Speaker 1: checked the Brexit box and now we can keep plowing ahead. 425 00:24:42,680 --> 00:24:45,000 Speaker 1: I gotta say, when I say Brexit, I just see 426 00:24:45,040 --> 00:24:47,800 Speaker 1: people immediately fall asleep. So it would be really interesting 427 00:24:47,800 --> 00:24:50,600 Speaker 1: if that's the catalyst that actually shakes this market, uh, 428 00:24:50,720 --> 00:24:53,880 Speaker 1: and gives it some direct direction one way or another. 429 00:24:54,040 --> 00:24:56,000 Speaker 1: I am wondering, so I want to change gears a 430 00:24:56,000 --> 00:24:58,760 Speaker 1: little bit because going from the macro to the micro. 431 00:24:58,960 --> 00:25:01,679 Speaker 1: We're getting news today our own Dave Wilson called it 432 00:25:01,760 --> 00:25:05,840 Speaker 1: fracture Friday, with the breakups and firms such as Gap, 433 00:25:06,040 --> 00:25:10,560 Speaker 1: Gap shares up, now L Brands and sympathy rising about 434 00:25:10,640 --> 00:25:13,119 Speaker 1: nine percent. Do you think that this will be the 435 00:25:13,200 --> 00:25:15,320 Speaker 1: year of corporate breakups and that it will be a 436 00:25:15,480 --> 00:25:19,560 Speaker 1: very positive thing for equity valuations? So so the short 437 00:25:19,600 --> 00:25:22,960 Speaker 1: answers yes, and and well, I haven't spent a lot 438 00:25:22,960 --> 00:25:25,600 Speaker 1: of time on either of those companies, that the Gap 439 00:25:26,080 --> 00:25:29,320 Speaker 1: breakup makes a tremendous amount of sense because Old Navy 440 00:25:29,359 --> 00:25:31,760 Speaker 1: has been doing really really well over the years, and 441 00:25:32,320 --> 00:25:37,159 Speaker 1: their value was probably clouded in sort of the conglomerate 442 00:25:37,240 --> 00:25:40,160 Speaker 1: of what had become Gap. So I'm sure their investment 443 00:25:40,200 --> 00:25:43,120 Speaker 1: bankers explained to them, if you split Old Navy out 444 00:25:43,200 --> 00:25:47,520 Speaker 1: as its own company and that gets valued appropriately, that's 445 00:25:47,520 --> 00:25:50,800 Speaker 1: going to enhance the consolidated value of the company. Um 446 00:25:51,080 --> 00:25:55,120 Speaker 1: L Brands, Uh, They've got they've got some they've got 447 00:25:55,119 --> 00:25:59,320 Speaker 1: some bigger issues. The lingerie business hasn't been going great 448 00:25:59,320 --> 00:26:02,480 Speaker 1: guns here, there's a lot more competition. Bath and Body 449 00:26:02,560 --> 00:26:05,640 Speaker 1: Works looks like it's great. I don't know if there 450 00:26:06,400 --> 00:26:09,320 Speaker 1: you know the thought processes, let's strip you know Bath 451 00:26:09,400 --> 00:26:12,960 Speaker 1: and Body Works out uh and and and that you 452 00:26:13,000 --> 00:26:14,639 Speaker 1: know might be a home run. And then you know, 453 00:26:14,760 --> 00:26:18,280 Speaker 1: concentrate on fixing the parts of the lingerie business that 454 00:26:18,440 --> 00:26:21,200 Speaker 1: that that aren't working. So maybe the thought process there. 455 00:26:21,200 --> 00:26:23,960 Speaker 1: If gaps doing this, then than l brands will as well. 456 00:26:24,680 --> 00:26:27,080 Speaker 1: So Phil, given the fact that we have had this big, 457 00:26:27,080 --> 00:26:31,520 Speaker 1: big run off of the December low. Uh and given 458 00:26:31,560 --> 00:26:34,440 Speaker 1: your it's called a March catalyst calendar that you're looking at, 459 00:26:34,760 --> 00:26:37,919 Speaker 1: where are you putting fresh capital to work today? So 460 00:26:37,960 --> 00:26:42,119 Speaker 1: the areas that look most attractive to us are domestically 461 00:26:42,280 --> 00:26:48,159 Speaker 1: value versus growth, and specifically the the energy, industrial and 462 00:26:48,200 --> 00:26:51,240 Speaker 1: financial service areas are the ones that appear to be 463 00:26:51,760 --> 00:26:55,240 Speaker 1: offering the most attractiveness in terms of value. Uh. We 464 00:26:55,320 --> 00:26:59,720 Speaker 1: still love small cap that that's a category that's done 465 00:26:59,720 --> 00:27:02,679 Speaker 1: well since Christmas eve and we think continues to do well. 466 00:27:03,160 --> 00:27:05,919 Speaker 1: And and uh for those that need to put some 467 00:27:05,960 --> 00:27:10,080 Speaker 1: money internationally, were concerned about what's going on in the 468 00:27:10,119 --> 00:27:13,000 Speaker 1: developed markets. We talked about Europe. Japan is sort of 469 00:27:13,480 --> 00:27:16,480 Speaker 1: sort of chugging away here, but but emerging markets look 470 00:27:16,600 --> 00:27:18,800 Speaker 1: very attractive to us as well. So those would be 471 00:27:18,800 --> 00:27:21,760 Speaker 1: the ways we play real quick here, Phil, Was this 472 00:27:21,800 --> 00:27:23,639 Speaker 1: a year that you should take your cash and spend 473 00:27:23,640 --> 00:27:32,040 Speaker 1: it as a consumer? No, as a as an investor, Well, no, 474 00:27:32,240 --> 00:27:34,640 Speaker 1: we're we're gonna We're gonna take a polo the money 475 00:27:34,680 --> 00:27:38,199 Speaker 1: this year. Stock market. If we're right, and and you know, 476 00:27:38,280 --> 00:27:40,399 Speaker 1: we talked about this a couple of months ago, Lisa, 477 00:27:40,840 --> 00:27:44,879 Speaker 1: our forecast off of that Christmas Eve bottom is stock 478 00:27:44,920 --> 00:27:47,000 Speaker 1: market is going to be up thirty two over the 479 00:27:47,040 --> 00:27:48,960 Speaker 1: course of this year. We think the S and P 480 00:27:49,119 --> 00:27:53,840 Speaker 1: gets and that looked like a ridiculous forecast nine weeks ago. 481 00:27:54,200 --> 00:27:58,200 Speaker 1: We're halfway home to that and we're still feeling very 482 00:27:58,240 --> 00:28:01,400 Speaker 1: comfortable about that. We think the corporate earnings will be up, 483 00:28:01,520 --> 00:28:03,760 Speaker 1: you know, maybe five next year to a hundred and 484 00:28:03,760 --> 00:28:09,240 Speaker 1: seventy dollars. The multiple that was eighteen times last stepemper 485 00:28:09,240 --> 00:28:12,040 Speaker 1: which collapsed down to fourteen. We think we're on our 486 00:28:12,040 --> 00:28:14,639 Speaker 1: way back to eighteen. If all of those hit we 487 00:28:14,680 --> 00:28:17,200 Speaker 1: believe they will, We've got a thirty one hundred. That's 488 00:28:17,200 --> 00:28:20,400 Speaker 1: a bullish call. That's a bullish called Philo Landos. Thank 489 00:28:20,400 --> 00:28:24,120 Speaker 1: you very much. Philo Lando's chief executive. Equity strategies are federated. 490 00:28:24,480 --> 00:28:26,720 Speaker 1: Thanks for listening to the Bloomberg P and L podcast. 491 00:28:26,880 --> 00:28:29,480 Speaker 1: You can subscribe and listen to interviews at Apple Podcasts 492 00:28:29,560 --> 00:28:32,639 Speaker 1: or whatever podcast platform you prefer. Paul Sweeney, I'm on 493 00:28:32,680 --> 00:28:35,320 Speaker 1: Twitter at pt Sweeney. I'm Lisa Bramwoy. It's I'm on 494 00:28:35,359 --> 00:28:38,360 Speaker 1: Twitter at Lisa Bramwoyit's one before the podcast. You can 495 00:28:38,400 --> 00:28:40,800 Speaker 1: always catch us worldwide. I'm Bloomberg Radio