1 00:00:00,280 --> 00:00:07,200 Speaker 1: Bloomberg Audio Studios, podcasts, radio News. 2 00:00:08,840 --> 00:00:11,600 Speaker 2: Twenty twenty four was a year full of twists and 3 00:00:11,680 --> 00:00:17,000 Speaker 2: turns and shakeups with huge global implications, the biggest global 4 00:00:17,040 --> 00:00:19,320 Speaker 2: election year in history. How much you think the vod's 5 00:00:19,360 --> 00:00:22,639 Speaker 2: going to have to cut rates? Has Balla confirming that 6 00:00:22,760 --> 00:00:26,040 Speaker 2: yet another senior military commander has also been killed. 7 00:00:26,280 --> 00:00:27,640 Speaker 3: Take a look at what happened. 8 00:00:29,880 --> 00:00:32,479 Speaker 1: The assassination attempts on the former US president. 9 00:00:32,520 --> 00:00:35,760 Speaker 2: Of course, this afternoon, President Joe Biden changing course, ending 10 00:00:35,800 --> 00:00:36,800 Speaker 2: its re election bid. 11 00:00:37,000 --> 00:00:39,479 Speaker 1: Donald Trump is the President of the United States of America. 12 00:00:39,800 --> 00:00:41,400 Speaker 3: Twenty twenty four. 13 00:00:41,640 --> 00:00:45,240 Speaker 2: Is bitcoin pierced one hundred thousand dollars right now? The 14 00:00:45,400 --> 00:00:48,880 Speaker 2: NYPD has identified a person of interest in the killing 15 00:00:49,280 --> 00:00:54,840 Speaker 2: of the United Healthcare CEO. News events can move markets 16 00:00:54,880 --> 00:00:57,560 Speaker 2: in real time, but they can also shift how Wall 17 00:00:57,560 --> 00:01:01,160 Speaker 2: Street thinks about the future, and for years, Sam Potter, 18 00:01:01,360 --> 00:01:04,120 Speaker 2: a senior editor on Bloomberg's Markets team, has led an 19 00:01:04,120 --> 00:01:07,520 Speaker 2: effort to burrow through piles of these outlooks and predictions 20 00:01:07,760 --> 00:01:08,760 Speaker 2: to surface trends. 21 00:01:09,160 --> 00:01:11,440 Speaker 1: This is what these people are talking about in house, 22 00:01:11,520 --> 00:01:14,319 Speaker 1: this is what they're talking about with clients. So for me, 23 00:01:14,880 --> 00:01:17,360 Speaker 1: I like to bring it all together. See what the 24 00:01:17,360 --> 00:01:20,720 Speaker 1: big picture is where the all the calls are falling. 25 00:01:24,800 --> 00:01:27,360 Speaker 2: This is the big take from Bloomberg News. I'm David Gerra. 26 00:01:27,880 --> 00:01:30,119 Speaker 2: Today on the show, we look back at what Wall 27 00:01:30,160 --> 00:01:33,840 Speaker 2: Street predicted for twenty twenty four and look ahead at 28 00:01:33,840 --> 00:01:41,360 Speaker 2: what it expects in twenty twenty five. Going into the 29 00:01:41,360 --> 00:01:44,639 Speaker 2: holiday season, when things were winding down a bit at work, 30 00:01:44,840 --> 00:01:48,120 Speaker 2: Bloomberg Sam Potter was burning the midnight oil sifting through 31 00:01:48,160 --> 00:01:50,960 Speaker 2: a tall stack of outlooks for the year ahead from 32 00:01:51,000 --> 00:01:53,960 Speaker 2: banks and financial services firms all over the world. 33 00:01:54,320 --> 00:01:58,000 Speaker 1: Yeah, it has become something that takes over my life 34 00:01:58,080 --> 00:02:00,440 Speaker 1: in December every year. It was never intense to be 35 00:02:00,520 --> 00:02:03,640 Speaker 1: that way. I started five or six years ago just 36 00:02:03,720 --> 00:02:06,320 Speaker 1: gathering what I felt with the most interesting calls, and 37 00:02:07,000 --> 00:02:09,400 Speaker 1: it kind of snowboard and has now become an annual 38 00:02:09,400 --> 00:02:13,000 Speaker 1: Bloomberg tradition that I works through them, and I harvest 39 00:02:13,400 --> 00:02:16,320 Speaker 1: the most interesting calls and put them all together in 40 00:02:16,360 --> 00:02:19,000 Speaker 1: one place so that people can analyze and compare them. 41 00:02:19,080 --> 00:02:21,320 Speaker 2: For folks who aren't in the city or on Wall Street. 42 00:02:21,560 --> 00:02:24,760 Speaker 2: What is the utility of these year ahead outlooks? How 43 00:02:24,760 --> 00:02:26,320 Speaker 2: are they used in finance? 44 00:02:26,800 --> 00:02:29,679 Speaker 1: I think chiefly we have to acknowledge that a lot 45 00:02:29,680 --> 00:02:32,720 Speaker 1: of this is about marketing. I think all of us 46 00:02:33,040 --> 00:02:36,120 Speaker 1: realistically who work in this industry know how difficult it 47 00:02:36,160 --> 00:02:39,680 Speaker 1: is to predict what's going to happen next week, next month, 48 00:02:39,840 --> 00:02:42,639 Speaker 1: let alone in the year to come. And you know, 49 00:02:42,800 --> 00:02:45,200 Speaker 1: repeatedly we see Wall Street calls turn out to be 50 00:02:45,240 --> 00:02:49,280 Speaker 1: way off. But still the institutions come forward, largely because 51 00:02:49,280 --> 00:02:52,840 Speaker 1: they're trying to communicate to clients the way they're approaching 52 00:02:52,880 --> 00:02:55,560 Speaker 1: the year, what they think a client should do with 53 00:02:55,600 --> 00:02:58,160 Speaker 1: their money, and try to demonstrate a little bit of 54 00:02:58,200 --> 00:03:02,680 Speaker 1: their expertise, experience and their read of what could happen. 55 00:03:02,880 --> 00:03:04,960 Speaker 1: I suppose there's always the long shot that they might 56 00:03:04,960 --> 00:03:06,520 Speaker 1: be proved right, and at the end of the year 57 00:03:06,560 --> 00:03:09,720 Speaker 1: they can crow about it. But really, I think it's 58 00:03:09,720 --> 00:03:11,680 Speaker 1: a natural, it's a human thing for us all to 59 00:03:11,680 --> 00:03:14,079 Speaker 1: be looking ahead when that day on the calendar comes 60 00:03:14,080 --> 00:03:16,480 Speaker 1: around and we have a fresh start, fresh year ahead 61 00:03:16,520 --> 00:03:16,760 Speaker 1: of us. 62 00:03:16,960 --> 00:03:19,560 Speaker 2: Before we look ahead, could we look back to what 63 00:03:19,680 --> 00:03:22,079 Speaker 2: was predicted for twenty twenty four And I'm just curious 64 00:03:22,120 --> 00:03:24,000 Speaker 2: sort of how much of those kind of broader predictions 65 00:03:24,080 --> 00:03:27,720 Speaker 2: that you surfaced from those outlooks actually came to pass. 66 00:03:27,960 --> 00:03:31,200 Speaker 1: There was a lot probably above average inaccuracy in the 67 00:03:31,240 --> 00:03:34,680 Speaker 1: outlooks for twenty twenty four. A lot of people felt 68 00:03:34,680 --> 00:03:37,800 Speaker 1: that as the FED was and other central banks have 69 00:03:37,920 --> 00:03:41,400 Speaker 1: been raising interest rates, that some kind of landing was 70 00:03:41,440 --> 00:03:43,839 Speaker 1: going to occur, in economic landing. By that, we mean 71 00:03:44,320 --> 00:03:47,040 Speaker 1: the business cycle was going to slow down. There were 72 00:03:47,480 --> 00:03:52,200 Speaker 1: lots of people fretting about recession and eventual recession. In 73 00:03:52,280 --> 00:03:54,960 Speaker 1: the event, what we got in twenty twenty four was 74 00:03:55,800 --> 00:03:59,080 Speaker 1: a kind of remarkable performance from the US in particular 75 00:03:59,160 --> 00:04:03,520 Speaker 1: US assets particular. We ended the year with stocks not 76 00:04:03,600 --> 00:04:07,680 Speaker 1: far from all time records. We ended with credit spreads 77 00:04:07,720 --> 00:04:13,720 Speaker 1: at incredibly high levels. We ended with even cryptocurrencies hitting records. 78 00:04:14,400 --> 00:04:19,599 Speaker 1: So that landing softer or otherwise never really materialized. And 79 00:04:19,640 --> 00:04:21,960 Speaker 1: I think that as I look back, as I think 80 00:04:22,000 --> 00:04:24,920 Speaker 1: back to twenty twenty four, not many people called that, 81 00:04:25,000 --> 00:04:27,480 Speaker 1: not many people expected that, And then, of course the election, 82 00:04:28,080 --> 00:04:31,640 Speaker 1: so the year proved anything but predictable last year. 83 00:04:32,080 --> 00:04:34,920 Speaker 2: So now let's look forward to twenty twenty five. What 84 00:04:35,000 --> 00:04:37,159 Speaker 2: are the trends that you found as you went through 85 00:04:37,200 --> 00:04:38,920 Speaker 2: these hundreds of predictions. 86 00:04:40,920 --> 00:04:44,279 Speaker 1: So the top line that really stood out was the 87 00:04:44,440 --> 00:04:49,240 Speaker 1: Trump factor. Essentially, the outlook for twenty twenty five everything 88 00:04:49,279 --> 00:04:55,280 Speaker 1: marked with the words unpredictable, unpredictability, uncertainty, largely stemming from 89 00:04:55,360 --> 00:04:58,840 Speaker 1: Donald Trump. Now, there is a lot of optimism as well. 90 00:04:58,920 --> 00:05:01,240 Speaker 1: It should be said, I've seen that in asset prices 91 00:05:01,279 --> 00:05:04,440 Speaker 1: since the election. He is seen as pro business generally, 92 00:05:04,560 --> 00:05:08,440 Speaker 1: despite being quite protectionist in terms of global trade. He's 93 00:05:08,480 --> 00:05:14,000 Speaker 1: expected to look at deregulation in various sectors. Lower taxes, 94 00:05:14,040 --> 00:05:16,960 Speaker 1: particularly corporate tax is what people are looking for. So 95 00:05:16,960 --> 00:05:18,720 Speaker 1: there's a lot of optimism, but also a lot of 96 00:05:18,800 --> 00:05:21,360 Speaker 1: unknown because he does tend to talk a very tough game. 97 00:05:22,080 --> 00:05:25,159 Speaker 1: Everyone expects tariffs to come, but no one's quite sure 98 00:05:25,200 --> 00:05:28,400 Speaker 1: at what level he will set them. Trump brings with 99 00:05:28,600 --> 00:05:32,839 Speaker 1: him this air of unpredictability, and it makes it extremely 100 00:05:32,839 --> 00:05:35,080 Speaker 1: difficult to say what's going to happen, what's he going 101 00:05:35,120 --> 00:05:36,680 Speaker 1: to do, and how's that going to play out. 102 00:05:36,760 --> 00:05:40,000 Speaker 3: That's what everyone's everyone's talking about. Am I right? 103 00:05:40,000 --> 00:05:43,320 Speaker 2: That there is this sense that uncertainty begets opportunity On 104 00:05:43,360 --> 00:05:43,839 Speaker 2: Wall Street? 105 00:05:44,360 --> 00:05:46,760 Speaker 1: Yeah, they always tend to say that. One of their 106 00:05:46,800 --> 00:05:50,240 Speaker 1: favorite things is always are investors this year will have 107 00:05:50,279 --> 00:05:54,520 Speaker 1: to be nimble, Active managers will be required, obviously, that 108 00:05:54,640 --> 00:05:58,919 Speaker 1: is most often that is Wall Street and associate firms 109 00:05:58,960 --> 00:06:01,120 Speaker 1: talking their own book. You know, they're in the business 110 00:06:01,120 --> 00:06:02,880 Speaker 1: of managing your money for you, so they're going to 111 00:06:02,880 --> 00:06:08,000 Speaker 1: talk up the need to. But certainly, I think those 112 00:06:08,120 --> 00:06:11,840 Speaker 1: institutions that enter twenty twenty four with quite a downbeat 113 00:06:12,000 --> 00:06:14,919 Speaker 1: or a cautious outlook, only to see the S and 114 00:06:14,960 --> 00:06:19,119 Speaker 1: P five hundred posts twenty plus percent gains, I think 115 00:06:19,720 --> 00:06:23,520 Speaker 1: on one level, the risk they see is being left out. 116 00:06:28,120 --> 00:06:31,159 Speaker 2: After the break in twenty twenty four, no one wanted 117 00:06:31,160 --> 00:06:33,960 Speaker 2: to be left out of the AI frenzy? Does Wall 118 00:06:33,960 --> 00:06:37,680 Speaker 2: Street think that'll continue? And analyst views on Trump's proposed 119 00:06:37,720 --> 00:06:50,520 Speaker 2: tariffs will be right back? Bloomberg. Sam Potter read hundreds 120 00:06:50,560 --> 00:06:53,839 Speaker 2: of pages of predictions from market strategists and Wall Street 121 00:06:53,880 --> 00:06:57,520 Speaker 2: economists to get their outlooks for twenty twenty five, and 122 00:06:57,680 --> 00:07:00,839 Speaker 2: a common thread in them is President elect Trump's promise 123 00:07:00,960 --> 00:07:04,520 Speaker 2: to impose more tariffs on imported goods. What is the 124 00:07:04,560 --> 00:07:08,279 Speaker 2: consensus from these outlooks on whether the President elect is 125 00:07:08,320 --> 00:07:11,040 Speaker 2: actually going to implement these teriffs when he becomes the president. 126 00:07:11,240 --> 00:07:14,040 Speaker 2: Are there enough folks kind of making bets on that 127 00:07:14,320 --> 00:07:15,360 Speaker 2: for it to be interesting to you? 128 00:07:15,920 --> 00:07:19,800 Speaker 1: Yeah, it stands out very clearly that pretty much all 129 00:07:19,840 --> 00:07:23,160 Speaker 1: the firms expect some form of tariffs to come in 130 00:07:23,240 --> 00:07:25,640 Speaker 1: He's going to do it. I can't think of one 131 00:07:26,360 --> 00:07:29,800 Speaker 1: institution who didn't think that tariffs would happen. The debate 132 00:07:29,960 --> 00:07:34,160 Speaker 1: is about to what extent they'll be applied. Overall, I 133 00:07:34,160 --> 00:07:38,440 Speaker 1: think the consensus is that, yes, tariff's are coming. They 134 00:07:38,480 --> 00:07:41,960 Speaker 1: may be implemented quite fast, but they won't be as 135 00:07:42,040 --> 00:07:46,680 Speaker 1: tough or necessarily as wide ranging as Trump has threatened. 136 00:07:47,080 --> 00:07:50,560 Speaker 1: A number of the firms suggested it's a negotiating tactic 137 00:07:51,120 --> 00:07:55,160 Speaker 1: and that if the likes of Europe are responsive, then 138 00:07:55,360 --> 00:07:58,040 Speaker 1: he won't go fully aggressive. The exception to that, I 139 00:07:58,080 --> 00:08:00,520 Speaker 1: have to say is China. Trump, you know, is no 140 00:08:00,600 --> 00:08:05,400 Speaker 1: friend of China, and everyone is expecting that China is 141 00:08:05,440 --> 00:08:07,280 Speaker 1: going to get hit with tariffs and there's not much 142 00:08:07,320 --> 00:08:08,360 Speaker 1: they can do about it. 143 00:08:08,440 --> 00:08:10,960 Speaker 2: So Sam, obviously what happens with tariffs and trade policy 144 00:08:11,200 --> 00:08:13,840 Speaker 2: is a big risk for markets. What else is on 145 00:08:13,880 --> 00:08:17,240 Speaker 2: Wall Street's mind that could potentially cause some trouble in 146 00:08:17,360 --> 00:08:17,760 Speaker 2: your head? 147 00:08:18,120 --> 00:08:20,040 Speaker 1: The thing that stood out to me that came up 148 00:08:20,080 --> 00:08:23,680 Speaker 1: time and again was the theme of bond vigilantes. We 149 00:08:23,800 --> 00:08:28,520 Speaker 1: have seen global governments running high deficits now for a while, 150 00:08:29,040 --> 00:08:32,880 Speaker 1: a lot of big fiscal spending. So far, the bond 151 00:08:33,000 --> 00:08:36,040 Speaker 1: markets have kind of gone along with that. They've been 152 00:08:36,040 --> 00:08:39,360 Speaker 1: okay with it. But one of the fears, one of 153 00:08:39,440 --> 00:08:43,720 Speaker 1: the significant fears, I would say, is that this tolerance 154 00:08:43,760 --> 00:08:46,920 Speaker 1: of the bond investor is not infinite. While there is 155 00:08:47,000 --> 00:08:51,000 Speaker 1: little appetite within governments for them to tighten their belts, 156 00:08:51,400 --> 00:08:54,280 Speaker 1: if they keep going like they are, the bond vigilantes 157 00:08:54,320 --> 00:08:58,960 Speaker 1: may appear. Yields could get considerably higher, and that would 158 00:08:59,040 --> 00:09:01,400 Speaker 1: be potentially interests for so many economies. 159 00:09:01,960 --> 00:09:05,120 Speaker 2: May maybe I can have you pivot from predictions about 160 00:09:05,200 --> 00:09:07,400 Speaker 2: the global macro environment to sort of what we're seeing 161 00:09:07,400 --> 00:09:11,360 Speaker 2: in terms of expectations for certain sectors. And I feel 162 00:09:11,360 --> 00:09:13,520 Speaker 2: like for a couple of years now, I've talked so 163 00:09:13,600 --> 00:09:17,440 Speaker 2: much about the prospects of artificial intelligence, and we've certainly 164 00:09:17,440 --> 00:09:19,600 Speaker 2: seen that minted out in sort of how well it's done. 165 00:09:20,120 --> 00:09:21,599 Speaker 2: Going into twenty twenty four, I think a lot of 166 00:09:21,640 --> 00:09:24,480 Speaker 2: people were wondering if the AI bubble was going to burst. 167 00:09:25,200 --> 00:09:25,959 Speaker 3: Lo it hasn't. 168 00:09:26,440 --> 00:09:28,559 Speaker 2: Yeah, what are the expectations for st of where artificial 169 00:09:28,600 --> 00:09:30,440 Speaker 2: intelligence goes from you're into twenty twenty five. 170 00:09:30,720 --> 00:09:33,400 Speaker 1: Yeah, AI is one of the one of the sort 171 00:09:33,400 --> 00:09:36,920 Speaker 1: of bigger themes as well. Beyond Trump, AI, as we know, 172 00:09:37,040 --> 00:09:39,560 Speaker 1: has been a major feature of the market now for 173 00:09:39,559 --> 00:09:43,880 Speaker 1: a couple of years. There is some debate still, as 174 00:09:43,920 --> 00:09:47,720 Speaker 1: we know, as we all know, about exactly how valuable. 175 00:09:47,440 --> 00:09:49,200 Speaker 3: The AI revolution is going to prove. 176 00:09:49,480 --> 00:09:52,439 Speaker 1: Is it going to justify these incredible run ups in 177 00:09:52,520 --> 00:09:56,240 Speaker 1: the valuations of the megacap text docs that we've seen. 178 00:09:56,040 --> 00:09:57,520 Speaker 3: In the US. 179 00:09:58,000 --> 00:10:01,320 Speaker 1: The view seems to be, well, there's two interesting things 180 00:10:01,320 --> 00:10:04,559 Speaker 1: about it. One is that AI has not yet reached 181 00:10:04,559 --> 00:10:07,720 Speaker 1: its full potential. So there is definitely a view emerging 182 00:10:07,800 --> 00:10:11,800 Speaker 1: that other parts of the market, other companies are going 183 00:10:11,840 --> 00:10:13,680 Speaker 1: to be able to adopt AI, and they're going to 184 00:10:13,679 --> 00:10:16,520 Speaker 1: get better at adopting AI in their own industries, so. 185 00:10:16,480 --> 00:10:17,200 Speaker 3: Away from tech. 186 00:10:17,679 --> 00:10:20,840 Speaker 1: So there's one school of thoughts sort of recommending look 187 00:10:20,920 --> 00:10:23,800 Speaker 1: for the places this is going to happen, the areas 188 00:10:23,800 --> 00:10:26,040 Speaker 1: of the market that can really benefit from AI. I 189 00:10:26,040 --> 00:10:29,000 Speaker 1: think healthcare is one that's mentioned. And then there's this 190 00:10:29,040 --> 00:10:31,679 Speaker 1: other school of thought that one thing we all know 191 00:10:31,720 --> 00:10:35,360 Speaker 1: about AI now is it's incredibly demanding in terms of 192 00:10:35,520 --> 00:10:39,959 Speaker 1: energy and in terms of processing power, and a lot 193 00:10:40,000 --> 00:10:44,240 Speaker 1: of the views from the outlooks suggest that the energy 194 00:10:44,240 --> 00:10:47,840 Speaker 1: and infrastructure needs and not yet being met. We need 195 00:10:47,880 --> 00:10:51,679 Speaker 1: power stations, we need data centers. Companies are going to 196 00:10:51,720 --> 00:10:55,200 Speaker 1: have to be paid to build this stuff. So there's 197 00:10:55,200 --> 00:10:58,880 Speaker 1: a real dual opportunity seen in AI. So definitely, the 198 00:10:58,920 --> 00:11:02,800 Speaker 1: takeaway I had was that the AI boom, the AI 199 00:11:02,920 --> 00:11:06,800 Speaker 1: revolution is still ongoing and has room to run. There 200 00:11:06,800 --> 00:11:09,640 Speaker 1: were one or two firms, it must be said, who 201 00:11:10,120 --> 00:11:13,840 Speaker 1: floated the idea that, rather than this being on the 202 00:11:13,840 --> 00:11:16,840 Speaker 1: cusp of a revolution, what if it's just nineteen ninety 203 00:11:16,920 --> 00:11:21,719 Speaker 1: nine and we're heading for another dot com style crash. 204 00:11:21,920 --> 00:11:24,120 Speaker 1: That was more a risk that they had in their 205 00:11:24,160 --> 00:11:26,480 Speaker 1: heads than something that they would predicted would happen. I 206 00:11:26,520 --> 00:11:28,360 Speaker 1: don't think anyone wants to stand in front of the 207 00:11:28,360 --> 00:11:30,120 Speaker 1: AI train at this point. 208 00:11:30,280 --> 00:11:32,800 Speaker 2: My last question is you talked about how this is 209 00:11:32,880 --> 00:11:34,959 Speaker 2: kind of a marketing exercise for a lot of these firms, 210 00:11:35,000 --> 00:11:37,120 Speaker 2: But what's the takeaway from looking at this kind of 211 00:11:37,120 --> 00:11:40,280 Speaker 2: constellation of outlooks for the area D What do you 212 00:11:40,320 --> 00:11:41,800 Speaker 2: take away from it? What do you think that readers 213 00:11:41,800 --> 00:11:45,240 Speaker 2: can take away from looking at these various predictions, sort 214 00:11:45,240 --> 00:11:47,400 Speaker 2: of seeing what the consensus is, general consensus is and 215 00:11:47,440 --> 00:11:48,839 Speaker 2: also seeing what those outliers are. 216 00:11:49,880 --> 00:11:53,199 Speaker 1: I think it's a good place to get a feel 217 00:11:53,320 --> 00:11:57,160 Speaker 1: for what might impact the year ahead. As mentioned, we 218 00:11:57,200 --> 00:12:01,120 Speaker 1: have seen time and again that the actual predictions can 219 00:12:01,320 --> 00:12:05,240 Speaker 1: prove very far from the reality. But it is always 220 00:12:05,240 --> 00:12:08,679 Speaker 1: interesting to see where consensus forms because this is also 221 00:12:08,760 --> 00:12:10,480 Speaker 1: where a lot of the money's going to be steered. 222 00:12:10,559 --> 00:12:12,680 Speaker 1: Right If we looked at it, I'm sure we would 223 00:12:12,720 --> 00:12:15,319 Speaker 1: see that a lot of the investment flows are following 224 00:12:15,320 --> 00:12:18,560 Speaker 1: the patterns that are laid out in these in these outlooks. 225 00:12:19,280 --> 00:12:22,559 Speaker 1: More broadly, I think of it's a way to connect 226 00:12:22,640 --> 00:12:25,320 Speaker 1: with the financial wealth. You know, this is what these 227 00:12:25,320 --> 00:12:27,840 Speaker 1: people are talking about in house, this is what they're 228 00:12:27,840 --> 00:12:30,600 Speaker 1: talking about with clients, and it gives me a. 229 00:12:30,559 --> 00:12:33,080 Speaker 3: Sense as we go into the new year that Okay, 230 00:12:33,360 --> 00:12:34,559 Speaker 3: I know life. 231 00:12:34,440 --> 00:12:37,480 Speaker 1: Is unpredictable, the world's going to be unpredictable, but I 232 00:12:37,559 --> 00:12:40,160 Speaker 1: have some starting point. We know where we are, we 233 00:12:40,200 --> 00:12:42,320 Speaker 1: know where we think we could go, and I find 234 00:12:42,320 --> 00:12:43,400 Speaker 1: that incredibly useful. 235 00:12:48,880 --> 00:12:51,200 Speaker 2: This is the Big Take from Bloomberg News. I'm David Gurra. 236 00:12:51,480 --> 00:12:53,800 Speaker 2: To read Sam's full report on the twenty twenty five 237 00:12:53,840 --> 00:12:56,880 Speaker 2: market outlook, heads to Bloomberg dot com or follow the 238 00:12:56,920 --> 00:12:59,760 Speaker 2: link in our episode notes. This episode is produced by 239 00:12:59,760 --> 00:13:02,800 Speaker 2: Alan Tie. It was edited by Aaron Edwards. It was 240 00:13:02,880 --> 00:13:05,520 Speaker 2: mixed and sound designed by Alex Sagura and fact checked 241 00:13:05,559 --> 00:13:08,840 Speaker 2: by our editorial team. Our senior producer is Naomi Shaven. 242 00:13:08,920 --> 00:13:12,480 Speaker 2: Our senior editor is Elizabeth Ponso. Our executive producer is 243 00:13:12,520 --> 00:13:16,040 Speaker 2: Nicole Beamster. Bor Sage Bauman is Bloomberg's head of podcasts. 244 00:13:16,520 --> 00:13:18,640 Speaker 2: If you liked this episode, make sure to subscribe and 245 00:13:18,679 --> 00:13:21,280 Speaker 2: review The Big Take wherever you listen to podcasts. It 246 00:13:21,320 --> 00:13:23,959 Speaker 2: helps people find the show. Thanks for listening. We'll be 247 00:13:24,000 --> 00:13:26,360 Speaker 2: back tomorrow with the third episode in our series on 248 00:13:26,400 --> 00:13:28,760 Speaker 2: the global fertility industry.