1 00:00:00,080 --> 00:00:06,760 Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. 2 00:00:11,960 --> 00:00:15,560 Speaker 2: This is the Bloomberg Surveillance Podcast. I'm Tom Keene along 3 00:00:15,600 --> 00:00:18,960 Speaker 2: with Paul Sweeney. Join us each day for insight from 4 00:00:18,960 --> 00:00:23,160 Speaker 2: the best in economics, finance, investment, and international relations. You 5 00:00:23,160 --> 00:00:26,520 Speaker 2: can also watch the show live on YouTube. Visit the 6 00:00:26,520 --> 00:00:31,280 Speaker 2: Bloomberg Podcast channel on YouTube to see the show weekday 7 00:00:31,280 --> 00:00:34,320 Speaker 2: mornings from seven to ten am Eastern from our global 8 00:00:34,360 --> 00:00:39,000 Speaker 2: headquarters in New York City. Subscribe to the podcast on Apple, Spotify, 9 00:00:39,360 --> 00:00:42,920 Speaker 2: or anywhere else you listen, and always I'm Bloomberg Radio, 10 00:00:43,080 --> 00:00:47,639 Speaker 2: the Bloomberg Terminal, and the Bloomberg Business App. Joining us 11 00:00:47,720 --> 00:00:51,440 Speaker 2: now on what we have witnessed from the former President 12 00:00:51,560 --> 00:00:54,320 Speaker 2: of the United States and what we may witness forward 13 00:00:54,400 --> 00:00:58,880 Speaker 2: from the president President of the United States. Greg Reveillier. Greg, 14 00:00:58,960 --> 00:01:01,160 Speaker 2: I've got to go to your note of two days ago, 15 00:01:01,720 --> 00:01:06,280 Speaker 2: mister Biden. It's the strongest, most blistering note I've ever 16 00:01:06,360 --> 00:01:09,520 Speaker 2: seen from Gregory Valier and ever, folks, is a long 17 00:01:09,600 --> 00:01:15,759 Speaker 2: time you said this is elder abuse discuss Greg, Could 18 00:01:15,800 --> 00:01:16,200 Speaker 2: you hear me? 19 00:01:17,000 --> 00:01:18,479 Speaker 3: Oh right, Tom, good morning. 20 00:01:19,360 --> 00:01:19,640 Speaker 4: Yeah. 21 00:01:19,760 --> 00:01:21,560 Speaker 3: I think it is. I think there are people in 22 00:01:21,600 --> 00:01:26,600 Speaker 3: the inner circle in the Biden camp who have been 23 00:01:26,640 --> 00:01:29,800 Speaker 3: disingenuous with him, have not told him what is really 24 00:01:29,840 --> 00:01:35,039 Speaker 3: going on. And I think that at some point these 25 00:01:35,080 --> 00:01:38,480 Speaker 3: people are going to have to answer for their behavior 26 00:01:38,560 --> 00:01:41,399 Speaker 3: toward this very very frail old man. 27 00:01:41,560 --> 00:01:44,280 Speaker 2: What is the best outcome for the Democrats to stagger 28 00:01:44,360 --> 00:01:44,959 Speaker 2: to Sunday? 29 00:01:47,480 --> 00:01:51,000 Speaker 3: Well, I think that they're getting closer to ousting him. 30 00:01:51,160 --> 00:01:53,200 Speaker 3: I think it's going to happen. I think, frankly, Tom, 31 00:01:53,240 --> 00:01:57,000 Speaker 3: the only issue was when, not whether, and then they'll 32 00:01:57,080 --> 00:01:59,720 Speaker 3: move on. I think they'll try to create some excitement 33 00:02:00,080 --> 00:02:04,840 Speaker 3: over Kamala Harrison, and they may get some excitement over her. 34 00:02:05,520 --> 00:02:07,680 Speaker 3: It can only be her as the replacement. I do 35 00:02:07,800 --> 00:02:11,880 Speaker 3: not see any of these very intriguing young governors being 36 00:02:11,960 --> 00:02:12,920 Speaker 3: quite ready yet. 37 00:02:13,280 --> 00:02:15,280 Speaker 5: Greg. What'd you think of Donald Trump's speech last night? 38 00:02:16,480 --> 00:02:18,400 Speaker 3: It was too First of all, it was too long. 39 00:02:18,600 --> 00:02:23,320 Speaker 3: It ended at twelve nine. I don't think a lot 40 00:02:23,360 --> 00:02:26,080 Speaker 3: of people in the East were awake at twelve oh nine. 41 00:02:26,960 --> 00:02:31,160 Speaker 3: It was the longest convention speech ever and he should 42 00:02:31,160 --> 00:02:34,480 Speaker 3: have reduced it. Also, I thought that there were parts 43 00:02:34,520 --> 00:02:36,520 Speaker 3: of the speech where he didn't have a lot of energy, 44 00:02:36,840 --> 00:02:43,280 Speaker 3: where he was rambling. It didn't really impress me. 45 00:02:43,919 --> 00:02:46,320 Speaker 6: What'd you think of Larry Trump and you know her, 46 00:02:46,400 --> 00:02:48,359 Speaker 6: you know, Trump's grandchildren on her lap and the role 47 00:02:48,400 --> 00:02:50,560 Speaker 6: that she played. I mean, she's co chair of the RNC, 48 00:02:50,720 --> 00:02:52,800 Speaker 6: and obviously you know there was a lot of camera 49 00:02:52,800 --> 00:02:54,320 Speaker 6: footage on her if you watched it. I mean, talk 50 00:02:54,360 --> 00:02:56,560 Speaker 6: to me a little bit about his family. They're finally 51 00:02:56,600 --> 00:02:59,440 Speaker 6: showing up. What kind of role does Trump's character play 52 00:02:59,440 --> 00:02:59,880 Speaker 6: in this race? 53 00:03:01,040 --> 00:03:04,040 Speaker 3: Yeah, I mean I think they're trying to present a 54 00:03:04,160 --> 00:03:08,080 Speaker 3: more mellow Donald Trump. I focusing on his family and 55 00:03:08,240 --> 00:03:10,680 Speaker 3: that may work. But let me just make this quick 56 00:03:10,720 --> 00:03:13,560 Speaker 3: point please. I think the key here is not energizing 57 00:03:13,600 --> 00:03:16,120 Speaker 3: the base. The base is really energized right now. The 58 00:03:16,200 --> 00:03:19,440 Speaker 3: key is did they win many moderate and centrist voters 59 00:03:19,760 --> 00:03:23,560 Speaker 3: with the convention? I'm not sure the center was all 60 00:03:23,600 --> 00:03:24,280 Speaker 3: that impressed. 61 00:03:24,320 --> 00:03:26,320 Speaker 2: Oh let's go there. When the time we got left 62 00:03:26,360 --> 00:03:29,519 Speaker 2: to you this morning, Greg, We've got the appointment of 63 00:03:29,560 --> 00:03:32,960 Speaker 2: a vice president who a lot of people pushed against 64 00:03:33,000 --> 00:03:36,640 Speaker 2: insiders in the Republican Party, and then we had this 65 00:03:36,840 --> 00:03:41,120 Speaker 2: original speech by the former president. Do you detect in 66 00:03:41,160 --> 00:03:44,040 Speaker 2: any way a new Donald Trump. 67 00:03:45,720 --> 00:03:49,000 Speaker 3: Would be It could be the advance will influence him, 68 00:03:49,640 --> 00:03:53,800 Speaker 3: and a lot about vance is in encountered opposition he's 69 00:03:53,800 --> 00:03:56,480 Speaker 3: not that crazy about Wall Street, he's not that crazy 70 00:03:56,480 --> 00:04:00,800 Speaker 3: about big big business. His views on abortion are quite radical, 71 00:04:01,360 --> 00:04:05,080 Speaker 3: so I think Vance may actually drag Trump into a 72 00:04:05,080 --> 00:04:06,240 Speaker 3: more radical stance. 73 00:04:06,600 --> 00:04:09,800 Speaker 2: Is there polling now for all of our listeners across 74 00:04:09,840 --> 00:04:14,559 Speaker 2: the station, whatever their politics. Is there polling that informs 75 00:04:14,640 --> 00:04:20,080 Speaker 2: Greg Valier? Now about the set of outcomes past Sunday. 76 00:04:20,680 --> 00:04:22,760 Speaker 3: Well, let's see this weekend. All the big polls will 77 00:04:22,800 --> 00:04:25,800 Speaker 3: be out on Saturday or Sunday, so the Sunday talk 78 00:04:25,839 --> 00:04:29,600 Speaker 3: shows will be very interesting. But the only one I've 79 00:04:29,640 --> 00:04:31,960 Speaker 3: seen that impressed me in the last few days I 80 00:04:32,000 --> 00:04:37,520 Speaker 3: think was CBS. I mean, obviously Trump is ahead, but 81 00:04:37,600 --> 00:04:41,200 Speaker 3: I don't think he's ahead by an insurmountable margin. 82 00:04:41,680 --> 00:04:44,200 Speaker 2: Greg. Thank you so much for the time and apologies 83 00:04:44,240 --> 00:04:49,240 Speaker 2: for the airline upset in cyber stuff that we see 84 00:04:49,839 --> 00:04:52,400 Speaker 2: this morning, Gregory Valier helping us out, and with an 85 00:04:52,400 --> 00:04:55,680 Speaker 2: important note. See that note. Read that note from AGF 86 00:04:56,440 --> 00:05:11,720 Speaker 2: in Investments. So there's a snippet of c code which 87 00:05:11,760 --> 00:05:16,560 Speaker 2: is part of an sloc fo R space parentheses I 88 00:05:16,839 --> 00:05:22,640 Speaker 2: space equal space zero semi colon space. I space is 89 00:05:22,720 --> 00:05:25,840 Speaker 2: less than one hundred semi colon in on and on 90 00:05:26,680 --> 00:05:32,440 Speaker 2: good morning Manjiep. Sink, is it one line of SLOC 91 00:05:32,720 --> 00:05:35,599 Speaker 2: that is causing this agony worldwide this morning? 92 00:05:35,839 --> 00:05:39,200 Speaker 7: I mean, clearly they shipped something last night crowd Strike 93 00:05:39,279 --> 00:05:43,760 Speaker 7: Dead and it was meant for a Windows update, and 94 00:05:43,839 --> 00:05:45,800 Speaker 7: that is what it's saying now they have rolled out. 95 00:05:45,839 --> 00:05:49,000 Speaker 2: But what is the what the causes a bungled project? 96 00:05:49,560 --> 00:05:55,120 Speaker 2: It couldn't be one little typo in pri n TF 97 00:05:55,320 --> 00:05:58,080 Speaker 2: parentheses quote l quote. 98 00:05:57,839 --> 00:06:01,479 Speaker 7: And in time you make changes at the operating system level. 99 00:06:02,160 --> 00:06:04,680 Speaker 7: I mean it hits you right there in terms of, 100 00:06:04,720 --> 00:06:07,400 Speaker 7: you know, bringing down all your critical systems. And we've 101 00:06:07,440 --> 00:06:10,080 Speaker 7: seen all kinds of breaches, you know, over the past 102 00:06:10,080 --> 00:06:13,560 Speaker 7: twelve months and longer, but the OS, the operating system 103 00:06:13,600 --> 00:06:17,120 Speaker 7: breaches are the worst because they just bring the system down. 104 00:06:17,160 --> 00:06:20,000 Speaker 7: And I stand corrected. It's not a breach, it's an outage. 105 00:06:20,040 --> 00:06:24,080 Speaker 7: So nobody actually hacked the system. It was a code 106 00:06:24,120 --> 00:06:27,400 Speaker 7: that was shipped by CrowdStrike, and that is what caused 107 00:06:27,440 --> 00:06:31,400 Speaker 7: a kernel to malfunction and the operating system couldn't start. 108 00:06:31,320 --> 00:06:34,440 Speaker 2: The Colonel malfunction. But the major came to the rescue. 109 00:06:34,200 --> 00:06:37,120 Speaker 6: Many but that Tom Keen, I'm not going to ask 110 00:06:37,160 --> 00:06:39,640 Speaker 6: you to answer a question with a zero or a one, 111 00:06:39,800 --> 00:06:41,320 Speaker 6: you know, but I do need to know this. 112 00:06:41,480 --> 00:06:43,120 Speaker 5: Who benefits here? I mean CrowdStrike? 113 00:06:43,160 --> 00:06:45,520 Speaker 6: This outage is pretty significant, right Who Who are the 114 00:06:45,560 --> 00:06:49,400 Speaker 6: companies that are best positioned to advance their own agenda 115 00:06:49,520 --> 00:06:50,600 Speaker 6: at the expensive CrowdStrike? 116 00:06:50,640 --> 00:06:50,800 Speaker 2: Here? 117 00:06:51,040 --> 00:06:53,520 Speaker 7: I mean one of the issues that the industry was 118 00:06:53,560 --> 00:06:57,320 Speaker 7: dealing with is do we need agent based solutions when 119 00:06:57,320 --> 00:07:01,000 Speaker 7: it comes to cybersecurity? And the answer here is agent 120 00:07:01,040 --> 00:07:04,400 Speaker 7: based solutions put at risk a Microsoft whose operating system 121 00:07:04,440 --> 00:07:08,279 Speaker 7: goes down. So why can't we have agent less solutions? 122 00:07:08,320 --> 00:07:11,040 Speaker 7: And there are plenty of vendors that have agent less 123 00:07:11,240 --> 00:07:13,640 Speaker 7: based approach. Now there are pros and cons to both 124 00:07:13,640 --> 00:07:16,200 Speaker 7: of them, so not that agent less will solve all 125 00:07:16,240 --> 00:07:20,480 Speaker 7: your problems, but clearly I think this benefits the agent 126 00:07:20,600 --> 00:07:23,640 Speaker 7: less vendors, and in fact, Google is looking to buy 127 00:07:23,680 --> 00:07:27,240 Speaker 7: one of them with security that was rumored and everyone 128 00:07:27,240 --> 00:07:29,840 Speaker 7: thought twenty three billion was so expensive. Well guess what, 129 00:07:30,120 --> 00:07:31,840 Speaker 7: it's not anymore. 130 00:07:32,200 --> 00:07:37,000 Speaker 2: Wiz Wiz Quiz what's the difference between Whiz and cloud strike. 131 00:07:37,320 --> 00:07:40,320 Speaker 7: Wiz doesn't have an agent that needs to be installed 132 00:07:40,480 --> 00:07:42,960 Speaker 7: at the operating system level, so you don't need to 133 00:07:43,000 --> 00:07:47,400 Speaker 7: install Viz agent within Windows. It will still work because 134 00:07:47,440 --> 00:07:53,160 Speaker 7: it's monitoring your workloads outside of the operating system. Nothing 135 00:07:53,200 --> 00:07:55,560 Speaker 7: needs to be installed. It's a solution that is agent 136 00:07:55,640 --> 00:07:58,440 Speaker 7: less and that's why, you know, if it can be 137 00:07:58,680 --> 00:08:02,560 Speaker 7: same in terms of, you know, the efficacy, then companies 138 00:08:02,800 --> 00:08:06,040 Speaker 7: would rather prefer that as opposed to changing the you know, 139 00:08:06,080 --> 00:08:07,320 Speaker 7: the structure of Windows. 140 00:08:07,360 --> 00:08:11,680 Speaker 6: Man the pow is AI affecting the enterprise security sector, Well. 141 00:08:11,440 --> 00:08:15,560 Speaker 7: AI opens more doors where you could be vulnerable. So 142 00:08:15,680 --> 00:08:18,720 Speaker 7: if you are using a lot of network traffic to 143 00:08:18,840 --> 00:08:21,760 Speaker 7: train your AI, well, guess what, somebody needs to inspect 144 00:08:21,760 --> 00:08:26,119 Speaker 7: that traffic. And so you know, if you're personalizing based 145 00:08:26,160 --> 00:08:29,600 Speaker 7: on AI, that personalized data can be hacked. So there 146 00:08:29,600 --> 00:08:32,679 Speaker 7: are so many different vectors when it comes to cybersecurity, 147 00:08:32,960 --> 00:08:36,199 Speaker 7: but nothing hits you as badly as an out as 148 00:08:36,200 --> 00:08:39,280 Speaker 7: a system wise outage where you can't even access your systems. 149 00:08:39,320 --> 00:08:41,640 Speaker 7: I mean, think about the repercussions you have to roll 150 00:08:41,679 --> 00:08:46,320 Speaker 7: back transactions, you have lost business because your systems weren't live. 151 00:08:46,640 --> 00:08:47,160 Speaker 2: It's huge. 152 00:08:47,240 --> 00:08:49,080 Speaker 5: What's the impact on Microsoft. 153 00:08:48,640 --> 00:08:50,080 Speaker 2: Exactly what's Microsoft doing? 154 00:08:50,200 --> 00:08:52,760 Speaker 7: I mean the fact that it was Microsoft and not 155 00:08:53,000 --> 00:08:56,320 Speaker 7: other operating system companies like Apple or you know, we 156 00:08:56,360 --> 00:08:59,559 Speaker 7: didn't hear anything about Google Cloud being down, so clearly 157 00:08:59,600 --> 00:09:03,800 Speaker 7: that puts tend to focus why Microsoft couldn't pick you know, 158 00:09:04,240 --> 00:09:08,439 Speaker 7: a malicious update like this, where I shouldn't call it malicious. 159 00:09:08,040 --> 00:09:11,199 Speaker 2: It could be at least just takeing notes. Leasa's daughter 160 00:09:11,480 --> 00:09:13,480 Speaker 2: is like number one in the world in softball and 161 00:09:13,480 --> 00:09:18,199 Speaker 2: they're working off a Mac platform. What's the Mac Microsoft 162 00:09:18,360 --> 00:09:21,920 Speaker 2: distinction here in this outage of Microsoft. 163 00:09:22,280 --> 00:09:25,800 Speaker 7: Well, so Mac has traditionally been more secure, Like you 164 00:09:25,960 --> 00:09:30,720 Speaker 7: don't hear about as many hacks or vulnerabilities for macOS 165 00:09:30,800 --> 00:09:33,440 Speaker 7: compared to a Windows operating system, and that has been 166 00:09:33,480 --> 00:09:36,199 Speaker 7: the case throughout. It's just when you do things at 167 00:09:36,200 --> 00:09:39,360 Speaker 7: the server level, it brings down an entire system. As 168 00:09:39,360 --> 00:09:42,480 Speaker 7: opposed to somebody having to pay ransomware because they can't 169 00:09:42,520 --> 00:09:45,480 Speaker 7: access their laptop. This is huge. This is system wide. 170 00:09:45,559 --> 00:09:48,880 Speaker 7: Your whole system is down. It's not about paying ransomware 171 00:09:48,920 --> 00:09:49,960 Speaker 7: and bringing it live up. 172 00:09:50,360 --> 00:09:51,560 Speaker 5: Tom, look at man Deep over here. 173 00:09:51,600 --> 00:09:53,120 Speaker 6: I mean, I thought we weren't going to hear or 174 00:09:53,160 --> 00:09:55,480 Speaker 6: see man Deep until the thirtieth of this month, when 175 00:09:55,520 --> 00:09:59,120 Speaker 6: Amazon and Apple and everybody report Microsoft is on the thirtieth. 176 00:09:59,160 --> 00:10:00,719 Speaker 5: I mean, look at you. Did you have to come 177 00:10:00,760 --> 00:10:02,720 Speaker 5: in special today just because of this adage. 178 00:10:02,760 --> 00:10:05,240 Speaker 7: I mean, what do you plan? I come to work 179 00:10:05,280 --> 00:10:07,120 Speaker 7: every day and I love my work. 180 00:10:07,920 --> 00:10:11,600 Speaker 2: What are they doing at Microsoft? Now? I think you know, 181 00:10:11,679 --> 00:10:14,360 Speaker 2: people may own crowd Striker, they want to buy it 182 00:10:14,400 --> 00:10:16,960 Speaker 2: down sixteen percent or whatever. Give me that, Bob, as 183 00:10:17,000 --> 00:10:19,280 Speaker 2: you can where a crowd strike is. But a lot 184 00:10:19,320 --> 00:10:22,520 Speaker 2: of people own Microsoft, even within their pension plans as well, 185 00:10:23,120 --> 00:10:26,559 Speaker 2: Like like Sacha Nadella gets a phone call three am, 186 00:10:26,880 --> 00:10:30,480 Speaker 2: we got a problem. Then what happens among people like 187 00:10:30,640 --> 00:10:32,479 Speaker 2: you at Microsoft? 188 00:10:32,800 --> 00:10:37,520 Speaker 7: I think Microsoft, being a big security player themselves, this 189 00:10:37,640 --> 00:10:41,160 Speaker 7: puts into question why can't they protect their cloud for 190 00:10:41,400 --> 00:10:44,360 Speaker 7: any sorts of things that could impact the runtime of 191 00:10:44,400 --> 00:10:45,920 Speaker 7: the cloud. I mean, this is a twenty four to 192 00:10:45,960 --> 00:10:49,880 Speaker 7: seven business and because all the systems are concentrated with 193 00:10:49,960 --> 00:10:54,880 Speaker 7: the cloud, hyperscalers like Amazon, Microsoft, Google systems being down 194 00:10:55,160 --> 00:10:56,600 Speaker 7: brings the whole Internet down. 195 00:10:56,760 --> 00:10:59,160 Speaker 2: Do we have reporting that the cloud is down? 196 00:10:59,400 --> 00:11:01,320 Speaker 5: No, cause it never dies. 197 00:11:01,600 --> 00:11:03,360 Speaker 6: You know, man, I have one last question for you, really, 198 00:11:03,400 --> 00:11:05,320 Speaker 6: I mean, last night we had the Trump you know, 199 00:11:05,360 --> 00:11:07,800 Speaker 6: the RNC. I just got to ask you what I mean, 200 00:11:07,960 --> 00:11:09,880 Speaker 6: just you know, off top of your head here, what 201 00:11:09,960 --> 00:11:13,600 Speaker 6: does your gut tell you regulation for big tech do 202 00:11:13,640 --> 00:11:15,959 Speaker 6: you expect that to increase under a Trump administration. 203 00:11:16,800 --> 00:11:19,800 Speaker 7: Well so, I mean, it's so uncertain that it comes 204 00:11:19,840 --> 00:11:22,560 Speaker 7: to the views coming from former President Trump that you 205 00:11:22,600 --> 00:11:25,320 Speaker 7: can't really make a lot out of what he's gonna 206 00:11:25,360 --> 00:11:28,840 Speaker 7: do actually versus what the election rhetoric is. And at 207 00:11:28,840 --> 00:11:31,320 Speaker 7: this point of time, one thing is sure, they're gonna 208 00:11:31,320 --> 00:11:34,040 Speaker 7: look to break up Meta. They are not looking to 209 00:11:34,160 --> 00:11:37,079 Speaker 7: ban TikTok, and you know, those are the things that 210 00:11:37,120 --> 00:11:38,640 Speaker 7: are becoming obvious with the election. 211 00:11:38,840 --> 00:11:40,360 Speaker 5: Zuckerberg was on the tape. Did you know what he 212 00:11:40,400 --> 00:11:40,920 Speaker 5: said about you? 213 00:11:41,200 --> 00:11:43,320 Speaker 6: I mean he was impressed by the reaction after the 214 00:11:43,320 --> 00:11:44,319 Speaker 6: assassination attempts. 215 00:11:44,320 --> 00:11:46,800 Speaker 2: So yeah, I mean, so, Mandy, what will you study 216 00:11:46,840 --> 00:11:49,760 Speaker 2: in the next six hours? You're here at Bloomberg. We're 217 00:11:50,120 --> 00:11:53,080 Speaker 2: humbled that people like you have made the Bloomberg system work. 218 00:11:53,120 --> 00:11:56,160 Speaker 2: Good morning to the three four thousand people that do 219 00:11:56,240 --> 00:11:59,280 Speaker 2: this worldwide every day. So then what you're gonna sit 220 00:11:59,320 --> 00:12:03,360 Speaker 2: at your desk for to attempt to observe out in 221 00:12:03,400 --> 00:12:06,040 Speaker 2: the zeitgeist to assist our listeners Like this. 222 00:12:05,960 --> 00:12:09,160 Speaker 7: Is not the first time CrowdStrike has shipped an update 223 00:12:09,200 --> 00:12:12,400 Speaker 7: to their software. So why did it happen? Because I 224 00:12:12,480 --> 00:12:16,400 Speaker 7: remember all these companies have made a lot of talking acquisitions. Now, 225 00:12:16,520 --> 00:12:20,360 Speaker 7: if this vulnerability arose because they made an acquisition and 226 00:12:20,520 --> 00:12:23,079 Speaker 7: embedded it in their product, that would be interesting to 227 00:12:23,120 --> 00:12:26,200 Speaker 7: look at as well, because, as we know, all these 228 00:12:26,200 --> 00:12:28,520 Speaker 7: things need to be tested properly, and in this case, 229 00:12:28,920 --> 00:12:29,880 Speaker 7: obviously it wasn't. 230 00:12:30,920 --> 00:12:44,240 Speaker 2: Man deep saying thank you so much. Believe it's a 231 00:12:44,320 --> 00:12:48,440 Speaker 2: perfect day to enjoy. Short thirty minutes too short thirty 232 00:12:48,480 --> 00:12:52,560 Speaker 2: minutes with Abby Joseph Cohen. The office at Columbia Business 233 00:12:52,559 --> 00:12:57,280 Speaker 2: School is five point seventy four cravice. When the students 234 00:12:57,320 --> 00:13:02,079 Speaker 2: walk through the door, do they shake? They do they 235 00:13:02,120 --> 00:13:03,320 Speaker 2: bow down? 236 00:13:04,640 --> 00:13:07,040 Speaker 8: You know, I have so much enjoyed working with the 237 00:13:07,080 --> 00:13:10,880 Speaker 8: students but also the faculty members. It's a pleasure to 238 00:13:10,920 --> 00:13:13,319 Speaker 8: be working with a number of people whose names you 239 00:13:13,360 --> 00:13:16,079 Speaker 8: would recognize, but also a lot of the up and comers. 240 00:13:16,080 --> 00:13:20,120 Speaker 2: Two years into the game. Do the underlying theories that 241 00:13:20,160 --> 00:13:23,520 Speaker 2: you owned and I was weaned on do they still work? 242 00:13:24,160 --> 00:13:29,920 Speaker 2: Dear Sharp, does uh Fama of Chicago the other giants? 243 00:13:30,200 --> 00:13:33,960 Speaker 2: Do those theories still work in this market? Uh? 244 00:13:34,000 --> 00:13:37,600 Speaker 8: This is a market clearly that is breaking a lot 245 00:13:37,600 --> 00:13:40,720 Speaker 8: of rules. The question is do we get back to 246 00:13:40,800 --> 00:13:44,200 Speaker 8: those rules and as you know, my own personal rule 247 00:13:44,240 --> 00:13:47,600 Speaker 8: of a TOM has always been that one must pay 248 00:13:47,640 --> 00:13:51,720 Speaker 8: attention to things like valuation models based on fundamentals. But 249 00:13:51,880 --> 00:13:54,960 Speaker 8: that doesn't mean that the market is always an equilibrium. 250 00:13:55,040 --> 00:13:56,520 Speaker 2: Damien's dying to get in here. 251 00:13:56,760 --> 00:13:58,640 Speaker 8: But let me make one other comment, if I may, 252 00:13:58,920 --> 00:14:04,360 Speaker 8: and that is we swing from one level of disequilibrium 253 00:14:04,400 --> 00:14:08,719 Speaker 8: to another. So market cycles are typically going from undervaluation 254 00:14:09,600 --> 00:14:13,840 Speaker 8: through fair value to overvaluation. And the question I think 255 00:14:13,880 --> 00:14:17,920 Speaker 8: for today is as we swing back down right we stop. 256 00:14:18,040 --> 00:14:20,120 Speaker 2: Okay, I'm going to rip up the script here right now, 257 00:14:20,280 --> 00:14:22,480 Speaker 2: and we got again. We've got abby for the entire 258 00:14:22,960 --> 00:14:26,600 Speaker 2: half hour. Megdum decaiah that let's say, wrote a book 259 00:14:26,640 --> 00:14:30,360 Speaker 2: in fury out of their financial crisis. Goldensach caused the 260 00:14:30,360 --> 00:14:34,360 Speaker 2: financial crisis case you didn't know on volacity in general 261 00:14:34,400 --> 00:14:38,440 Speaker 2: equilibrium theory, and he said it's flawed, but it's the 262 00:14:38,480 --> 00:14:43,640 Speaker 2: best tool we have. Is our global volcan equilibrium in 263 00:14:43,760 --> 00:14:47,480 Speaker 2: finance and an investment. Is it still in place? 264 00:14:48,200 --> 00:14:50,760 Speaker 8: It seems to me that it's always something we need 265 00:14:50,800 --> 00:14:53,320 Speaker 8: to keep in mind. But I think that some of 266 00:14:53,360 --> 00:14:56,880 Speaker 8: the best calls that get made by strategists, for example, 267 00:14:57,320 --> 00:15:00,920 Speaker 8: is identifying the situations that can keep you off of 268 00:15:01,040 --> 00:15:05,160 Speaker 8: equilibrium number one, and number two, identifying the catalysts that 269 00:15:05,200 --> 00:15:07,640 Speaker 8: will do that. So, for example, there have been many 270 00:15:07,680 --> 00:15:12,480 Speaker 8: people talking about the peculiarity of the US equity market 271 00:15:12,760 --> 00:15:16,520 Speaker 8: recently with the over concentration in a very small number 272 00:15:16,600 --> 00:15:21,520 Speaker 8: of names. But the magic, of course is identifying the 273 00:15:21,560 --> 00:15:27,600 Speaker 8: catalyst that would move that away and also figuring out 274 00:15:27,720 --> 00:15:31,200 Speaker 8: what the ultimate target might be. Doesn't mean you get there, 275 00:15:31,240 --> 00:15:32,680 Speaker 8: but it gives you a sense of direction. 276 00:15:33,200 --> 00:15:35,760 Speaker 6: Abbie, you mentioned catalysts, and so that takes me to 277 00:15:35,840 --> 00:15:38,000 Speaker 6: the concept of factor investing in equities and how it's 278 00:15:38,080 --> 00:15:38,960 Speaker 6: changed so very much. 279 00:15:38,960 --> 00:15:40,520 Speaker 5: And I'm a big fan of g SAM. 280 00:15:40,600 --> 00:15:42,920 Speaker 6: You know, Cliff Asness, this g SAM factor in disease, 281 00:15:42,960 --> 00:15:46,040 Speaker 6: the long short value, the growth. But there's quality, there's 282 00:15:46,080 --> 00:15:49,160 Speaker 6: low volatility, there's I mean, there's all these different factors 283 00:15:49,200 --> 00:15:52,320 Speaker 6: that are driving equities. What beta regime are we in 284 00:15:52,400 --> 00:15:54,760 Speaker 6: now and what beta regime do you think we're going 285 00:15:54,760 --> 00:15:56,040 Speaker 6: into through the end of this year. 286 00:15:56,280 --> 00:16:00,520 Speaker 8: Well, that is a very good question and the highly 287 00:16:00,560 --> 00:16:03,480 Speaker 8: technical one, but let me answer it in a somewhat 288 00:16:03,480 --> 00:16:06,880 Speaker 8: different way, and that has to do with the level 289 00:16:06,920 --> 00:16:10,880 Speaker 8: of concentration that we're seeing in markets, and the focus 290 00:16:11,000 --> 00:16:17,360 Speaker 8: that we have on indexation, both implicit and explicit, seems 291 00:16:17,400 --> 00:16:20,480 Speaker 8: to me to be driving a lot of the very 292 00:16:21,160 --> 00:16:25,680 Speaker 8: extraordinarily well developed quantitative models. It's just driving them in 293 00:16:25,720 --> 00:16:29,320 Speaker 8: the wrong direction. That doesn't mean they're wrong intermediate to 294 00:16:29,400 --> 00:16:32,320 Speaker 8: long term, but it doesn't really help on a trading basis. 295 00:16:32,320 --> 00:16:35,400 Speaker 8: And by the way, we have seen this before. Right 296 00:16:36,240 --> 00:16:38,760 Speaker 8: years ago, there was something called the nifty to fifty. 297 00:16:38,960 --> 00:16:44,080 Speaker 8: No really, and many people listening to us may not 298 00:16:44,280 --> 00:16:46,440 Speaker 8: remember that, or they may not have read about it, 299 00:16:46,720 --> 00:16:50,320 Speaker 8: but there were fifty sauce stocks that dominated the markets 300 00:16:50,800 --> 00:16:55,880 Speaker 8: decades ago, and basically the question was would it continue. 301 00:16:56,280 --> 00:16:59,160 Speaker 8: And many of the companies that were included in this, 302 00:16:59,240 --> 00:17:04,280 Speaker 8: including ib if you did the extrapolation, they were going 303 00:17:04,359 --> 00:17:09,400 Speaker 8: to be twenty to fifty percent of US GDPAI. Obviously, 304 00:17:09,600 --> 00:17:13,440 Speaker 8: that is not sustainable. And then we have an even 305 00:17:13,520 --> 00:17:17,000 Speaker 8: more extreme version of that now with a magnificent five, 306 00:17:17,119 --> 00:17:19,760 Speaker 8: with a mag seven, depending upon which ones you like, 307 00:17:20,200 --> 00:17:24,080 Speaker 8: and it is driven in large part by the self 308 00:17:24,080 --> 00:17:29,639 Speaker 8: fulfilling prophecy of people using indexed approaches, particularly market cap 309 00:17:29,840 --> 00:17:32,720 Speaker 8: indexed approaches. And you guys have talked about this before, 310 00:17:32,800 --> 00:17:34,760 Speaker 8: so I'm not going to belabor it. 311 00:17:34,800 --> 00:17:37,760 Speaker 5: To me, Abby is blaming Larry Fink and Blackrot. No, 312 00:17:37,800 --> 00:17:40,000 Speaker 5: I'm not a concentration risk in the equity market. 313 00:17:40,960 --> 00:17:44,880 Speaker 8: I am focusing on the idea that everyone has been 314 00:17:45,040 --> 00:17:49,359 Speaker 8: emphasizing relative performance visa VI the index and doing it 315 00:17:49,400 --> 00:17:52,679 Speaker 8: on a very short term basis. And there are some 316 00:17:52,720 --> 00:17:55,439 Speaker 8: great companies out there that have been facilitating that for 317 00:17:55,520 --> 00:17:58,680 Speaker 8: investors who wanted to get it done because it's low 318 00:17:58,760 --> 00:18:02,560 Speaker 8: cost and so on, and if you are a professional investor, 319 00:18:03,200 --> 00:18:05,320 Speaker 8: many of them don't want to veer too far from 320 00:18:05,359 --> 00:18:08,440 Speaker 8: the index because if you're wrong, better to be wrong 321 00:18:08,600 --> 00:18:10,120 Speaker 8: with lots of companies. 322 00:18:09,720 --> 00:18:12,520 Speaker 5: Right, And the thing the behavioral component there. 323 00:18:12,359 --> 00:18:15,600 Speaker 8: Absolutely and one of the things that intrigues me, of course, 324 00:18:16,000 --> 00:18:18,240 Speaker 8: are those people who are willing to kind of stick 325 00:18:18,280 --> 00:18:21,440 Speaker 8: their necks out and say, you know, maybe the consensus 326 00:18:22,000 --> 00:18:25,439 Speaker 8: will prove to be wrong. The problem this time around, 327 00:18:25,480 --> 00:18:29,359 Speaker 8: of course, has been that the movement towards five or 328 00:18:29,440 --> 00:18:33,600 Speaker 8: seven stocks, that level of concentration is really unparalleled. 329 00:18:33,640 --> 00:18:36,399 Speaker 2: I want to spend the entire next section on the 330 00:18:36,440 --> 00:18:39,800 Speaker 2: concentration of the mag seven. There's a small shop downtown 331 00:18:39,840 --> 00:18:43,120 Speaker 2: that put out a blistering essay about six days ago 332 00:18:43,200 --> 00:18:46,600 Speaker 2: that will. Did you hire Jim Cavello? You the one? 333 00:18:46,640 --> 00:18:47,280 Speaker 2: Is it your fault? 334 00:18:47,560 --> 00:18:48,159 Speaker 5: I was insolved. 335 00:18:49,880 --> 00:18:50,560 Speaker 2: It's going to be great. 336 00:18:50,560 --> 00:18:51,119 Speaker 7: We're going to do that. 337 00:18:51,160 --> 00:18:53,640 Speaker 2: In the next section for Global Wall Street, I want 338 00:18:53,640 --> 00:18:55,960 Speaker 2: to talk about courage to be in the market. And 339 00:18:56,000 --> 00:18:58,359 Speaker 2: the word in this room that we get from many 340 00:18:58,480 --> 00:19:02,680 Speaker 2: strategies is an abby Joe Cone word which is solid. 341 00:19:02,920 --> 00:19:06,119 Speaker 2: And what you say is if the American economy is 342 00:19:06,240 --> 00:19:12,200 Speaker 2: solid and business is solid, you have to participate. Talk 343 00:19:12,240 --> 00:19:16,879 Speaker 2: about the gloom crew that says go to cash. 344 00:19:16,960 --> 00:19:22,159 Speaker 8: That is a fascinating question, Tom, and it seems to 345 00:19:22,200 --> 00:19:24,520 Speaker 8: me that we do have an economy right now that 346 00:19:24,720 --> 00:19:29,800 Speaker 8: is extremely solid. We have never seen in recent decades 347 00:19:30,080 --> 00:19:33,240 Speaker 8: as strong a labor market as we have now. Wages 348 00:19:33,359 --> 00:19:37,480 Speaker 8: are rising at a rate that now exceeds inflation, which 349 00:19:37,520 --> 00:19:40,680 Speaker 8: is helpful, particularly for middle income and lower middle income 350 00:19:40,760 --> 00:19:46,160 Speaker 8: families that have been having trouble. We have enormously strong profits. 351 00:19:46,240 --> 00:19:48,800 Speaker 8: Return on equity for the S and P five hundred 352 00:19:49,280 --> 00:19:52,120 Speaker 8: is at an extremely high level. In fact, it might 353 00:19:52,160 --> 00:19:55,760 Speaker 8: be the highest ever. So things are in fact solid. 354 00:19:56,200 --> 00:19:59,960 Speaker 8: What I worry about always is is that already priced 355 00:20:00,200 --> 00:20:04,600 Speaker 8: into the market. Number one and number two the policies 356 00:20:04,920 --> 00:20:09,200 Speaker 8: that helped get us to this are they potentially in danger. 357 00:20:09,760 --> 00:20:14,359 Speaker 8: So this is obviously a big political point in the 358 00:20:14,480 --> 00:20:18,680 Speaker 8: United States right now. Policies may be changing, and among 359 00:20:18,760 --> 00:20:22,119 Speaker 8: the things that I worry about, for example, would be 360 00:20:22,160 --> 00:20:27,639 Speaker 8: a movement towards more significant tariffs which are inflationary. It 361 00:20:27,760 --> 00:20:31,240 Speaker 8: damages not just the economies of our trading partners, but 362 00:20:31,400 --> 00:20:35,800 Speaker 8: our economy as well. I worry about whether we would 363 00:20:35,880 --> 00:20:39,320 Speaker 8: step away from some of the good long term policies 364 00:20:39,359 --> 00:20:43,520 Speaker 8: implemented during the Biden administration to encourage long term investment 365 00:20:43,640 --> 00:20:49,120 Speaker 8: in public infrastructure, in technology through the Chips Act, basically 366 00:20:49,200 --> 00:20:52,520 Speaker 8: making things here, and then of course the investments that 367 00:20:52,560 --> 00:20:55,360 Speaker 8: are being made in alternative energy. One more point time, 368 00:20:55,440 --> 00:20:58,040 Speaker 8: if I may, if we're looking at where there's a 369 00:20:58,080 --> 00:21:01,879 Speaker 8: shortage of something in this country, its power, right with 370 00:21:02,119 --> 00:21:06,160 Speaker 8: all of the focus on technology, and clearly people are 371 00:21:06,160 --> 00:21:09,480 Speaker 8: talking about it this morning with the outage, if we're 372 00:21:09,520 --> 00:21:14,360 Speaker 8: going to be moving towards an even more tech concentrated economy, 373 00:21:15,240 --> 00:21:18,760 Speaker 8: one that is using AI, cloud services and so on, 374 00:21:19,040 --> 00:21:23,560 Speaker 8: we need a dependable grid. And one of the things 375 00:21:23,720 --> 00:21:28,280 Speaker 8: under the legislation, bipartisan legislation that was passed over the 376 00:21:28,320 --> 00:21:32,000 Speaker 8: last couple of years is a development of more power sources, 377 00:21:32,000 --> 00:21:33,240 Speaker 8: including alternatives. 378 00:21:33,640 --> 00:21:41,400 Speaker 2: Somebody really competent. James Cavello Georgetown Talk Goldben Sachs has said, 379 00:21:41,440 --> 00:21:44,800 Speaker 2: we got a problem. We're going opposite of the way 380 00:21:45,400 --> 00:21:49,200 Speaker 2: it worked at Intel and everywhere else. You have technology 381 00:21:49,240 --> 00:21:53,960 Speaker 2: that comes in that's cheaper, that drives the dialogue forward. 382 00:21:54,720 --> 00:22:00,800 Speaker 2: AI seems to be more expensive, polar, opposite of the 383 00:22:00,840 --> 00:22:04,520 Speaker 2: norm we have lived. Is there substance there to James 384 00:22:04,520 --> 00:22:06,520 Speaker 2: Cavello's questioning AI? 385 00:22:07,080 --> 00:22:10,960 Speaker 8: Yeah, I think Jim is a very thoughtful guy who 386 00:22:11,000 --> 00:22:16,000 Speaker 8: also has access to lots of information being pulled together 387 00:22:16,080 --> 00:22:19,719 Speaker 8: by analysts. And what many have been hearing for the 388 00:22:19,760 --> 00:22:23,560 Speaker 8: past six months in particular, has been that companies that 389 00:22:23,640 --> 00:22:27,359 Speaker 8: have been investing heavily in AI are saying they're not 390 00:22:27,440 --> 00:22:32,320 Speaker 8: yet seeing the return. Economists throughout the country are saying 391 00:22:32,640 --> 00:22:36,520 Speaker 8: they're not really seeing the productivity enhancements yet from AI. Now. 392 00:22:36,840 --> 00:22:40,200 Speaker 8: It could be that the analyses are looking at data 393 00:22:40,480 --> 00:22:45,520 Speaker 8: in a premature stage. Maybe things will improve, but clearly 394 00:22:45,960 --> 00:22:49,159 Speaker 8: AI has been quite expensive at this point. There was 395 00:22:49,560 --> 00:22:53,760 Speaker 8: a race in many industries to take on as much 396 00:22:53,880 --> 00:22:57,880 Speaker 8: AI investment as possible, and it might take a little 397 00:22:57,880 --> 00:22:58,840 Speaker 8: while to digest. 398 00:22:59,000 --> 00:23:02,320 Speaker 2: Do you believe I'm thinking of the railroads from eighteen 399 00:23:02,480 --> 00:23:05,840 Speaker 2: eighty out to nineteen thirty nineteen forty, that you can 400 00:23:05,920 --> 00:23:10,920 Speaker 2: partition parts of AI where there will be AI failures, 401 00:23:11,320 --> 00:23:16,080 Speaker 2: but there will be AI successes, and we've already identified them, 402 00:23:16,440 --> 00:23:18,679 Speaker 2: taking in Nvidia as the trophy child. 403 00:23:19,680 --> 00:23:23,120 Speaker 8: Tom, your point is very well made. Clearly, the success 404 00:23:23,320 --> 00:23:27,400 Speaker 8: thus far has been in those companies providing the infrastructure, right, 405 00:23:27,440 --> 00:23:31,480 Speaker 8: the ones who are providing the basic support for future 406 00:23:31,520 --> 00:23:35,359 Speaker 8: investment in AI. Where we've not yet seen the full 407 00:23:35,440 --> 00:23:39,560 Speaker 8: payback and maybe we won't in some companies has to 408 00:23:39,560 --> 00:23:43,280 Speaker 8: do with the application of AI. We also need to 409 00:23:43,320 --> 00:23:47,520 Speaker 8: train people, just the way everybody who's been trained in 410 00:23:47,800 --> 00:23:51,160 Speaker 8: the Microsoft three sixty five products are feeling a little 411 00:23:51,160 --> 00:23:54,639 Speaker 8: bit of pain today that worked out. Sure, it'll be 412 00:23:54,720 --> 00:23:55,360 Speaker 8: straightened out. 413 00:23:56,080 --> 00:23:56,280 Speaker 7: You know. 414 00:23:56,359 --> 00:24:00,560 Speaker 8: People are not yet fully familiar with many the AI 415 00:24:00,680 --> 00:24:06,200 Speaker 8: product and I believe based upon my background in computer science. 416 00:24:06,600 --> 00:24:09,400 Speaker 8: I do have an undergraduate degree in computer science. It's 417 00:24:09,520 --> 00:24:14,040 Speaker 8: ancient at this point talking about dinosaurs fort dinosaur, Yes, 418 00:24:14,160 --> 00:24:20,560 Speaker 8: for trand Pascal Pascal and cobol Oh my gosh. But 419 00:24:20,840 --> 00:24:23,919 Speaker 8: what I have seen over the years is that it 420 00:24:24,000 --> 00:24:29,280 Speaker 8: takes a while for users to understand the capabilities of 421 00:24:29,600 --> 00:24:32,120 Speaker 8: what they have, and I think that we're still in 422 00:24:32,160 --> 00:24:37,280 Speaker 8: that gestation period for AI. What I also think, however, 423 00:24:37,800 --> 00:24:40,840 Speaker 8: is that many investors in the market, because of this 424 00:24:40,920 --> 00:24:46,960 Speaker 8: heavy concentration, perhaps became very enthusiastic a little bit too soon, 425 00:24:47,560 --> 00:24:50,080 Speaker 8: and so we're going to need to see some digestion 426 00:24:51,040 --> 00:24:51,840 Speaker 8: of that as well. 427 00:24:52,000 --> 00:24:53,520 Speaker 6: Abby, I have to ask you something that I know 428 00:24:53,560 --> 00:24:58,400 Speaker 6: you're an expert about Meme stocks, Robinhood AMC, I mean 429 00:24:58,520 --> 00:25:01,800 Speaker 6: game stop. I mean these names ever come up in 430 00:25:01,840 --> 00:25:05,320 Speaker 6: your classrooms. I mean are students actually investing in or 431 00:25:05,400 --> 00:25:06,480 Speaker 6: asking about them? 432 00:25:07,200 --> 00:25:10,720 Speaker 8: Students are asking about them, and the response is always 433 00:25:10,720 --> 00:25:16,600 Speaker 8: one of momentum investing. And what we always do is 434 00:25:16,640 --> 00:25:19,199 Speaker 8: to encourage students to think about the fundamentals. What's the 435 00:25:19,240 --> 00:25:22,240 Speaker 8: business plan, what's the business model, what it does matter, 436 00:25:22,359 --> 00:25:25,520 Speaker 8: what do the financials look like? And if you can't 437 00:25:25,520 --> 00:25:30,640 Speaker 8: make a case based on that, it's only momentum. And 438 00:25:30,720 --> 00:25:34,280 Speaker 8: that to me, you know, in my history in the 439 00:25:34,320 --> 00:25:37,800 Speaker 8: market can take you only so far, but more importantly, 440 00:25:37,880 --> 00:25:40,639 Speaker 8: only for so long, because at some point there's a 441 00:25:40,680 --> 00:25:44,280 Speaker 8: catalyst that basically makes you stand up and say, emperor 442 00:25:44,320 --> 00:25:45,120 Speaker 8: has no clothes. 443 00:25:45,200 --> 00:25:47,520 Speaker 6: Well, I mean, let's just talk about momentum as a factor, right, 444 00:25:47,560 --> 00:25:49,239 Speaker 6: I mean, look back windows and all that. I mean, 445 00:25:49,240 --> 00:25:51,199 Speaker 6: there's a lot of momentum based strategies, but you know, 446 00:25:51,280 --> 00:25:52,800 Speaker 6: my understanding and I don't know if it works for 447 00:25:52,800 --> 00:25:56,080 Speaker 6: equity certainly doesn't have facts. It's a volatility dampener, you know, 448 00:25:56,160 --> 00:25:58,359 Speaker 6: so when you used with other factors, it kind of 449 00:25:58,400 --> 00:26:00,280 Speaker 6: does a little bit. It improves your risk just to 450 00:26:00,320 --> 00:26:01,680 Speaker 6: return your sharp base you as it were. 451 00:26:02,000 --> 00:26:02,639 Speaker 5: Do you agree with that? 452 00:26:03,760 --> 00:26:06,520 Speaker 8: You know, momentum is something that you need to pay 453 00:26:06,520 --> 00:26:10,359 Speaker 8: attention to. Part of my own fundamental analysis has always 454 00:26:10,400 --> 00:26:14,000 Speaker 8: been flow of funds, because you need to say, Okay, 455 00:26:14,040 --> 00:26:17,040 Speaker 8: what will corporates be doing with their cash? What will 456 00:26:17,200 --> 00:26:20,800 Speaker 8: individual investors, what will institutional investors be doing? And so on. 457 00:26:21,160 --> 00:26:24,560 Speaker 8: And one of the things that distinguishes this period has 458 00:26:24,640 --> 00:26:28,600 Speaker 8: been that those investors have all kind of coalesced around 459 00:26:28,680 --> 00:26:31,119 Speaker 8: the same thing because many of them are using the 460 00:26:31,119 --> 00:26:34,200 Speaker 8: same benchmarks for performance. And that's one of the big 461 00:26:34,200 --> 00:26:35,520 Speaker 8: differences this time around. 462 00:26:35,680 --> 00:26:38,800 Speaker 2: I'm going back in this insane period and it's someone 463 00:26:38,960 --> 00:26:41,359 Speaker 2: abby you and I know, well Michael Moisson now with 464 00:26:41,440 --> 00:26:44,400 Speaker 2: a shingle out at Morgan Stanley. That's a firm across 465 00:26:44,440 --> 00:26:48,520 Speaker 2: the street. Michael has been writing since nineteen ninety five 466 00:26:48,600 --> 00:26:52,680 Speaker 2: brilliantly for the CFA Institute and others about the new 467 00:26:53,080 --> 00:26:56,720 Speaker 2: capital allocation we're under and the traditional Graham, Dot and 468 00:26:56,840 --> 00:27:01,600 Speaker 2: hot Coddle capital intensive businesses have given way to an 469 00:27:01,640 --> 00:27:07,800 Speaker 2: intellectually intensive, innovation intensive work that needs less capital and 470 00:27:07,920 --> 00:27:13,800 Speaker 2: provides greater return ROIC in greater return and bigger cashlows. 471 00:27:14,160 --> 00:27:15,360 Speaker 2: Do you buy the kool aid? 472 00:27:16,359 --> 00:27:18,919 Speaker 8: I buy that to a very large extent, because it 473 00:27:19,000 --> 00:27:22,720 Speaker 8: also helps explain why the US economy and the US 474 00:27:22,800 --> 00:27:27,159 Speaker 8: equity market has so dramatically outperformed economies and markets in 475 00:27:27,240 --> 00:27:28,240 Speaker 8: other parts of the world. 476 00:27:28,280 --> 00:27:29,159 Speaker 2: Can we sustain that? 477 00:27:29,880 --> 00:27:33,520 Speaker 8: I think that there are very active decisions that have 478 00:27:33,600 --> 00:27:36,800 Speaker 8: already been taken in other countries to try to catch 479 00:27:36,880 --> 00:27:39,720 Speaker 8: up with us, and we're not keeping our eye on 480 00:27:39,760 --> 00:27:44,520 Speaker 8: the ball sufficiently. So, for example, there are industrial policies 481 00:27:44,560 --> 00:27:48,920 Speaker 8: that are underway in Asia and in Europe to try 482 00:27:48,920 --> 00:27:52,000 Speaker 8: to catch up with the United States in this regard. 483 00:27:52,280 --> 00:27:55,040 Speaker 8: And I'm not a huge fan of industrial policies because 484 00:27:55,119 --> 00:27:58,679 Speaker 8: mistakes can be made. But if you can provide a 485 00:27:58,760 --> 00:28:02,399 Speaker 8: capital incentive for the right sort of investment that to 486 00:28:02,440 --> 00:28:04,760 Speaker 8: me makes a great deal of sense. There's one other 487 00:28:04,800 --> 00:28:06,919 Speaker 8: piece of this time that I think we need to 488 00:28:06,920 --> 00:28:09,360 Speaker 8: touch on, and that is we are in a new 489 00:28:09,400 --> 00:28:13,320 Speaker 8: era in which capital is no longer free, right. We're 490 00:28:13,320 --> 00:28:16,800 Speaker 8: paying for capital now. And when there was an environment 491 00:28:16,840 --> 00:28:19,800 Speaker 8: in which it was free to borrow money, you can 492 00:28:19,800 --> 00:28:23,919 Speaker 8: make all kinds of interesting decisions. Now you really have 493 00:28:24,000 --> 00:28:26,960 Speaker 8: to sharpen the pencil in so many areas. And it's 494 00:28:27,000 --> 00:28:29,399 Speaker 8: not just what companies are doing, and it's not just 495 00:28:29,440 --> 00:28:33,040 Speaker 8: what active investors are doing. It's also the use of 496 00:28:33,160 --> 00:28:36,080 Speaker 8: leverage in many other investment vehicles. 497 00:28:36,160 --> 00:28:39,600 Speaker 2: Please visit with these when you stop giving out C's 498 00:28:39,880 --> 00:28:44,360 Speaker 2: Columbia Business School professor Joseph Cohen with this year on 499 00:28:44,520 --> 00:28:58,880 Speaker 2: the New New This is an incredible privilege. At least 500 00:28:58,880 --> 00:29:02,480 Speaker 2: your reasons were this with superlative academics out of UCLA 501 00:29:03,040 --> 00:29:06,880 Speaker 2: and Damien. It's great when you're doing securities analysis and 502 00:29:06,920 --> 00:29:09,080 Speaker 2: you get to wake up with a giant. She gets 503 00:29:09,160 --> 00:29:12,320 Speaker 2: to work with Michael Pact every day, which is like 504 00:29:12,520 --> 00:29:16,400 Speaker 2: really really cool. Michael Packer. You know, I think they 505 00:29:16,400 --> 00:29:19,360 Speaker 2: were making the first chip and there was no nano. 506 00:29:20,120 --> 00:29:22,760 Speaker 2: There was no nano, Nano Alicia Rees joins us now 507 00:29:23,040 --> 00:29:25,760 Speaker 2: with the technology excellence of webbersh. There's some other guy 508 00:29:25,800 --> 00:29:27,840 Speaker 2: that works as well. I can't remember who it is. 509 00:29:27,880 --> 00:29:31,600 Speaker 2: Alicia on Netflix, they own the high ground. I just 510 00:29:31,760 --> 00:29:36,400 Speaker 2: did a log regression back to two thousand and four 511 00:29:37,120 --> 00:29:39,880 Speaker 2: on Netflix, and boy are they catching up to the 512 00:29:39,960 --> 00:29:44,000 Speaker 2: long term trend. I mean, you have an optimistic tonier. 513 00:29:44,360 --> 00:29:48,120 Speaker 2: Can Netflix revert to the growthiness that we've seen the 514 00:29:48,160 --> 00:29:50,120 Speaker 2: last fifteen twenty years. 515 00:29:51,160 --> 00:29:55,200 Speaker 1: Well, last year we had added Netflix to our Best 516 00:29:55,240 --> 00:29:59,880 Speaker 1: Ideas list and shares pretty much doubled over that time. 517 00:30:00,480 --> 00:30:03,680 Speaker 1: Last quarter we removed it from our best Ideas list 518 00:30:03,800 --> 00:30:08,440 Speaker 1: because while we expect continued growth, it's going to be 519 00:30:08,440 --> 00:30:13,400 Speaker 1: harder and harder to impress investors. It's not going to 520 00:30:13,440 --> 00:30:15,400 Speaker 1: be the outsized growth that they saw when they had 521 00:30:15,520 --> 00:30:20,080 Speaker 1: multiple growth fronts occurring at the same time that we're 522 00:30:20,120 --> 00:30:20,920 Speaker 1: still seeing to. 523 00:30:21,560 --> 00:30:22,520 Speaker 4: Some degree or another. 524 00:30:22,600 --> 00:30:25,479 Speaker 1: But we have the password sharing crackdown that really added 525 00:30:25,880 --> 00:30:30,280 Speaker 1: a lot of subscribers. The ad tier has limited churn, 526 00:30:30,520 --> 00:30:34,240 Speaker 1: so instead of you know, just dropping your subscription for 527 00:30:34,280 --> 00:30:36,160 Speaker 1: a little while, you'll go try the ad here for 528 00:30:36,200 --> 00:30:36,680 Speaker 1: a little bit. 529 00:30:36,720 --> 00:30:40,200 Speaker 4: Maybe you won't watch as much content. That's what we thought. 530 00:30:40,640 --> 00:30:41,880 Speaker 4: Turns out people are. 531 00:30:41,800 --> 00:30:44,720 Speaker 1: Watching just as much content two hours per day permember 532 00:30:45,960 --> 00:30:48,640 Speaker 1: on the service on average, on both the ad tier 533 00:30:48,680 --> 00:30:51,040 Speaker 1: and the premium tiers, and so they have, you know, 534 00:30:51,120 --> 00:30:53,640 Speaker 1: just a lot going for them, but a lot of 535 00:30:53,680 --> 00:30:55,520 Speaker 1: that is priced into shares at this point. 536 00:30:56,480 --> 00:30:58,560 Speaker 6: Well at least let me let me just cut in 537 00:30:58,640 --> 00:31:01,320 Speaker 6: right there. I mean, you know, I understand that this 538 00:31:01,400 --> 00:31:04,400 Speaker 6: recent earnings release from Netflix was a margin story. Talk 539 00:31:04,440 --> 00:31:07,520 Speaker 6: to us about the right mix, determining that mix between 540 00:31:07,560 --> 00:31:11,240 Speaker 6: content and actually making money. Have they found that nirvana 541 00:31:11,280 --> 00:31:12,040 Speaker 6: that happy place? 542 00:31:12,720 --> 00:31:13,400 Speaker 4: Absolutely? 543 00:31:13,600 --> 00:31:17,120 Speaker 1: Yeah, this is the point where Netflix has really been 544 00:31:17,160 --> 00:31:19,840 Speaker 1: striving towards for a long time. They spent so much 545 00:31:19,880 --> 00:31:22,440 Speaker 1: money on content, really wracked up a lot of debt 546 00:31:23,280 --> 00:31:25,760 Speaker 1: to get those subscriber numbers as high as possible for 547 00:31:25,800 --> 00:31:29,160 Speaker 1: a long time because that was investor's primary focus was 548 00:31:29,200 --> 00:31:32,239 Speaker 1: that subscriber growth. It still is to some extent, but 549 00:31:32,280 --> 00:31:35,560 Speaker 1: that focus has largely shifted over to profitability, and Netflix 550 00:31:35,640 --> 00:31:40,160 Speaker 1: has has really soared on that note. A lot of 551 00:31:40,160 --> 00:31:45,080 Speaker 1: their competitors, or most of their competitors, couldn't find profitability 552 00:31:45,960 --> 00:31:50,360 Speaker 1: to save their lives really technically, So you know, a 553 00:31:50,400 --> 00:31:53,040 Speaker 1: couple are I think Disney is you know, turning the 554 00:31:53,080 --> 00:31:56,080 Speaker 1: corner there, but a lot of the competitors it's really 555 00:31:56,160 --> 00:31:58,400 Speaker 1: hard in the streaming world to get that profitability. 556 00:31:58,480 --> 00:32:02,600 Speaker 4: Netflix is wildly profitable and one of the things what. 557 00:32:02,520 --> 00:32:03,920 Speaker 5: Are their competitors is Roku? 558 00:32:04,040 --> 00:32:05,400 Speaker 6: And I just have to ask you, you know, you 559 00:32:05,440 --> 00:32:08,120 Speaker 6: think about these other streaming companies, Fubo, Roku, you know 560 00:32:08,200 --> 00:32:12,040 Speaker 6: Roku for example, I mean they are highly highly you know, 561 00:32:12,080 --> 00:32:15,160 Speaker 6: contingent on sports content right on the package they have 562 00:32:15,200 --> 00:32:18,200 Speaker 6: with MLB. You know, talk to us about sports and 563 00:32:18,360 --> 00:32:19,960 Speaker 6: sports is content for some bust? 564 00:32:20,200 --> 00:32:21,240 Speaker 5: Can that really last? 565 00:32:21,320 --> 00:32:23,880 Speaker 6: I mean, do you really expect these companies who are 566 00:32:24,200 --> 00:32:27,000 Speaker 6: kind of relying on the NFL, these NBA deals, these 567 00:32:27,320 --> 00:32:30,800 Speaker 6: eleven years, seventy whatever billion dollar deals, talk to us 568 00:32:30,840 --> 00:32:31,280 Speaker 6: about that. 569 00:32:31,320 --> 00:32:33,840 Speaker 5: What role did the streamers have in that end of 570 00:32:33,840 --> 00:32:34,280 Speaker 5: the market. 571 00:32:35,360 --> 00:32:38,840 Speaker 1: Sure, I mean sports is definitely shifting over to streaming, 572 00:32:38,920 --> 00:32:40,040 Speaker 1: and we've done. 573 00:32:39,920 --> 00:32:41,320 Speaker 4: A lot of work around that recently. 574 00:32:41,520 --> 00:32:43,880 Speaker 1: What I'd say about Roku is that there they don't 575 00:32:43,880 --> 00:32:47,280 Speaker 1: have to spend much at all on sports to really 576 00:32:48,000 --> 00:32:50,719 Speaker 1: you know, drive that growth for them. They have to 577 00:32:50,800 --> 00:32:55,200 Speaker 1: host the services that that have all that sports content. 578 00:32:55,560 --> 00:32:58,160 Speaker 1: And so what Roku's doing is actually really smart they're 579 00:32:58,200 --> 00:33:00,080 Speaker 1: they're not spending much money on this, but they have 580 00:33:00,120 --> 00:33:04,280 Speaker 1: a landing page within near search where you just go 581 00:33:04,320 --> 00:33:06,880 Speaker 1: and you look under sports and you can find where 582 00:33:06,880 --> 00:33:08,840 Speaker 1: all the sports are that you're looking for, because it's 583 00:33:08,920 --> 00:33:11,680 Speaker 1: so hard to figure out where your sports are playing. 584 00:33:11,720 --> 00:33:14,520 Speaker 4: Now, you know, where do you find this game? It 585 00:33:14,560 --> 00:33:15,480 Speaker 4: could be anywhere, and. 586 00:33:15,400 --> 00:33:18,160 Speaker 1: They have you know, just one game or one night 587 00:33:18,200 --> 00:33:22,000 Speaker 1: of football on Amazon or YouTube or wherever it might be. 588 00:33:22,600 --> 00:33:24,440 Speaker 4: And so Roku's actually. 589 00:33:25,280 --> 00:33:28,560 Speaker 1: Using that pain point for people without having to spend 590 00:33:28,560 --> 00:33:30,720 Speaker 1: the money on the content itself. They're spending a little 591 00:33:30,720 --> 00:33:33,640 Speaker 1: bit on content, but more than anything, they're just that 592 00:33:33,720 --> 00:33:37,560 Speaker 1: landing page and they can make a lot on revenue 593 00:33:37,560 --> 00:33:40,240 Speaker 1: shares if people sign up for those you know, for 594 00:33:40,400 --> 00:33:43,640 Speaker 1: those subscriptions on their service, and they can also advertise 595 00:33:43,680 --> 00:33:44,480 Speaker 1: on there, and so. 596 00:33:44,440 --> 00:33:45,800 Speaker 4: They have a lot of potential there. 597 00:33:45,840 --> 00:33:46,000 Speaker 2: Well. 598 00:33:46,040 --> 00:33:48,120 Speaker 4: Google, on the other hand, has to spend a lot 599 00:33:48,160 --> 00:33:48,680 Speaker 4: on content. 600 00:33:49,280 --> 00:33:51,200 Speaker 2: Get I got to get two questions in you know 601 00:33:51,240 --> 00:33:54,760 Speaker 2: the important You're lighting up YouTube live chat like nobody. 602 00:33:54,840 --> 00:33:58,480 Speaker 2: You have a chart which is the absolute definitive chart 603 00:33:58,560 --> 00:34:01,560 Speaker 2: of the future. Full disclosure, folks. We're on YouTube and 604 00:34:01,640 --> 00:34:05,160 Speaker 2: I subscribe with my own money to YouTube premium. You've 605 00:34:05,200 --> 00:34:09,000 Speaker 2: got a chart I plan to change to ads from 606 00:34:09,120 --> 00:34:12,960 Speaker 2: no ads. What's the trend you see of what Lisa 607 00:34:13,000 --> 00:34:15,719 Speaker 2: Mateo's going to do at her house when she's sick 608 00:34:15,760 --> 00:34:18,080 Speaker 2: of the ads? Are we going to switch to a 609 00:34:18,120 --> 00:34:19,080 Speaker 2: premium service? 610 00:34:20,840 --> 00:34:24,840 Speaker 1: So what we've seen through our survey work over the 611 00:34:24,880 --> 00:34:29,080 Speaker 1: quarters is that people instead of you know, they'll have 612 00:34:29,120 --> 00:34:32,359 Speaker 1: the premium service, they're not planning on watching a ton 613 00:34:32,520 --> 00:34:35,759 Speaker 1: over the next few months maybe, and so instead of 614 00:34:36,360 --> 00:34:38,600 Speaker 1: getting it, hopping off the service for that period of 615 00:34:38,600 --> 00:34:41,960 Speaker 1: time and choosing something else, they'll go to the ads here. 616 00:34:42,239 --> 00:34:44,279 Speaker 1: But they're also coming back from that ad here and 617 00:34:44,320 --> 00:34:46,799 Speaker 1: going back to premium. It just depends on, you know, 618 00:34:46,840 --> 00:34:50,160 Speaker 1: what their plans are for their content consumption over that time, 619 00:34:50,360 --> 00:34:53,040 Speaker 1: or maybe they're just trying it out right. But you know, 620 00:34:53,440 --> 00:34:57,759 Speaker 1: people are leaving Netflix less, and I dare say the 621 00:34:57,800 --> 00:35:02,640 Speaker 1: same with YouTube. People areably pretty happy with our premium subscriptions. 622 00:35:04,080 --> 00:35:07,919 Speaker 1: YouTube does deliver a lot of ads, Netflix far far fewer. 623 00:35:08,040 --> 00:35:11,840 Speaker 2: Okay, I got one other question, Alicia. I wasn't going 624 00:35:11,920 --> 00:35:14,960 Speaker 2: to ask it, and then a second person asked it, 625 00:35:15,560 --> 00:35:18,000 Speaker 2: and then a third person asked us. Now you look 626 00:35:18,440 --> 00:35:21,640 Speaker 2: on the edge of normal dan Ives is a life 627 00:35:21,680 --> 00:35:26,839 Speaker 2: force at Webbush traveling worldwide. He's absolutely killed it on 628 00:35:27,000 --> 00:35:29,919 Speaker 2: Apple just in the last number of months for all 629 00:35:29,960 --> 00:35:33,759 Speaker 2: of our listeners and viewers. Alicia Rees, what is it 630 00:35:34,080 --> 00:35:36,160 Speaker 2: like to work with dan Ives? 631 00:35:37,960 --> 00:35:41,040 Speaker 1: Well, we certainly do get a kick out of his outfits. 632 00:35:41,520 --> 00:35:43,440 Speaker 4: I mean, he goes. 633 00:35:43,600 --> 00:35:47,320 Speaker 1: He's very bright and colorful, and it's and it's exciting, 634 00:35:47,360 --> 00:35:48,600 Speaker 1: and he's just the nicest guy. 635 00:35:48,640 --> 00:35:52,600 Speaker 4: He's really really sweet and fun and lively. 636 00:35:52,760 --> 00:35:56,719 Speaker 1: So he's his personality is genuine as you see him 637 00:35:56,719 --> 00:35:57,120 Speaker 1: on TV. 638 00:35:57,560 --> 00:36:00,239 Speaker 2: Can you tell him he's so late? He's spent all 639 00:36:00,320 --> 00:36:02,759 Speaker 2: his time in Nike stores. Can you tell them? I 640 00:36:02,960 --> 00:36:06,560 Speaker 2: demand some of the parts all the stocks he follows. 641 00:36:06,800 --> 00:36:10,040 Speaker 2: I need some sensitivity analysis and some of the parts. 642 00:36:10,080 --> 00:36:11,399 Speaker 2: Damiens get in here with one more. 643 00:36:11,440 --> 00:36:13,360 Speaker 6: Can I just ask one last question? Have you cut 644 00:36:13,400 --> 00:36:14,959 Speaker 6: the cord yet in your own house? 645 00:36:15,800 --> 00:36:17,080 Speaker 4: Oh? Yeah? Years ago? 646 00:36:17,239 --> 00:36:17,759 Speaker 5: Years ago? 647 00:36:18,280 --> 00:36:19,000 Speaker 2: Wow, years ago. 648 00:36:19,040 --> 00:36:20,040 Speaker 5: She's obviously that sports. 649 00:36:20,640 --> 00:36:22,839 Speaker 1: I'm not the biggest sports fan, and I found most 650 00:36:22,840 --> 00:36:26,160 Speaker 1: of my sports on streaming, so that was that was 651 00:36:26,200 --> 00:36:27,040 Speaker 1: the ticket. 652 00:36:26,719 --> 00:36:30,040 Speaker 2: Really very valuable on Netflix. Alesha Reese, don't be a stranger. 653 00:36:30,040 --> 00:36:33,440 Speaker 2: Thank you so much. She is with pleasure. This is 654 00:36:33,440 --> 00:36:38,520 Speaker 2: a Bloomberg surveillance podcast, bringing you the best in economics, finance, investment, 655 00:36:38,719 --> 00:36:42,320 Speaker 2: and international relations. You can also watch the show live 656 00:36:42,560 --> 00:36:46,880 Speaker 2: on YouTube. Visit the Bloomberg Podcast channel on YouTube to 657 00:36:47,000 --> 00:36:50,400 Speaker 2: see the show weekday mornings from seven to ten am 658 00:36:50,440 --> 00:36:54,480 Speaker 2: Eastern from our global headquarters in New York City. Subscribe 659 00:36:54,480 --> 00:36:58,240 Speaker 2: to the podcast on Apple, Spotify, or anywhere else you listen, 660 00:36:58,560 --> 00:37:02,200 Speaker 2: and always I'm Bloomberg Radio, the Bloomberg Terminal, and the 661 00:37:02,239 --> 00:37:03,719 Speaker 2: Bloomberg Business App.