1 00:00:00,440 --> 00:00:03,840 Speaker 1: Strap on your parachute. Is time for What Goes Up 2 00:00:04,120 --> 00:00:14,200 Speaker 1: with Sarah Ponzick and Mike Reagan. Hello and welcome to 3 00:00:14,280 --> 00:00:18,280 Speaker 1: What goes Up, a Bloomberg Weekly Markets podcast. I'm Sarah Ponzek, 4 00:00:18,400 --> 00:00:21,560 Speaker 1: a reporter on the Cross Asset team, and I'm Mike Reagan, 5 00:00:21,720 --> 00:00:24,520 Speaker 1: a senior editor at Bloomberg. And you can think of 6 00:00:24,560 --> 00:00:28,480 Speaker 1: me as the Polly Walnuts to Sarah's Tony Soprano. Let's 7 00:00:28,560 --> 00:00:30,760 Speaker 1: keep it going, Mike, keep it going. You like you 8 00:00:30,800 --> 00:00:32,879 Speaker 1: like that one that makes you the boss? You know 9 00:00:32,880 --> 00:00:34,760 Speaker 1: I am the boss here. You know that that's a 10 00:00:34,800 --> 00:00:37,760 Speaker 1: big compliment in Jersey here, so I hope you like 11 00:00:37,840 --> 00:00:39,760 Speaker 1: that one down in North Carolina. I don't know if 12 00:00:39,760 --> 00:00:42,040 Speaker 1: they take Tony Soprano as as big as a compliment 13 00:00:42,240 --> 00:00:45,360 Speaker 1: as with you in Jersey, but I'm gonna take it 14 00:00:45,479 --> 00:00:48,440 Speaker 1: and run with it. Alright. Good a big week on 15 00:00:48,479 --> 00:00:51,159 Speaker 1: the show. So the breakneck rally in the stock market, 16 00:00:51,200 --> 00:00:55,240 Speaker 1: even amid the economic uncertainty surrounding the coronavirus, has many 17 00:00:55,360 --> 00:00:59,440 Speaker 1: market observers wondering if a bubble is forming. Our guest 18 00:00:59,560 --> 00:01:02,800 Speaker 1: is the absolute perfect person to discuss this, and for 19 00:01:02,960 --> 00:01:06,840 Speaker 1: years has analyzed the nature of bubbles across financial markets, 20 00:01:07,319 --> 00:01:09,759 Speaker 1: and as always, will close out the episode with our 21 00:01:09,800 --> 00:01:13,199 Speaker 1: tradition the craziest thing I saw in markets this week, 22 00:01:13,640 --> 00:01:16,000 Speaker 1: And remember, if you saw anything crazy, give us a 23 00:01:16,040 --> 00:01:19,440 Speaker 1: call on the Bloomberg Podcast hotline at six four six 24 00:01:19,959 --> 00:01:23,960 Speaker 1: three to four three four nine zero, or tweet to 25 00:01:24,080 --> 00:01:27,679 Speaker 1: us at Podcasts and maybe we'll read your tweet or 26 00:01:27,760 --> 00:01:31,080 Speaker 1: play your voicemail on the show. And Sarah, as you said, 27 00:01:31,240 --> 00:01:33,840 Speaker 1: very very excited to welcome back this week's guest. But 28 00:01:33,920 --> 00:01:36,080 Speaker 1: before I introduce him, I do want to point out 29 00:01:36,160 --> 00:01:40,119 Speaker 1: one thing to listeners. You know how the big thing 30 00:01:40,200 --> 00:01:43,120 Speaker 1: on Wall Street now, the big trend is to look 31 00:01:43,160 --> 00:01:47,360 Speaker 1: at all the alternative data, the Apple Maps mobility data 32 00:01:47,480 --> 00:01:50,200 Speaker 1: open table, that sort of thing. I want to warn people. 33 00:01:50,240 --> 00:01:52,640 Speaker 1: I think there's a problem with the Apple mobility data 34 00:01:52,680 --> 00:01:54,520 Speaker 1: and sorry, you know what that is. I'm waiting for 35 00:01:54,520 --> 00:01:56,840 Speaker 1: this explanation. Let's hear it. The upticking that data is 36 00:01:56,840 --> 00:02:00,160 Speaker 1: all because of Sarah. I think, truly I did. I'd 37 00:02:00,240 --> 00:02:03,480 Speaker 1: use Apple Maps a very fair amount over the past 38 00:02:03,520 --> 00:02:05,920 Speaker 1: week or so planning out how I was going to 39 00:02:05,960 --> 00:02:09,080 Speaker 1: get up here. Um I will say, though, service is 40 00:02:09,280 --> 00:02:13,840 Speaker 1: very rocky, so the Apple Mobility data probably hasn't been 41 00:02:13,840 --> 00:02:16,880 Speaker 1: able to send through a decent amounts of time. I'm 42 00:02:16,960 --> 00:02:19,960 Speaker 1: hiding out. It's pretty cool hiding out Florida. Now I'm 43 00:02:20,000 --> 00:02:23,760 Speaker 1: hiding out in the woods. You look like you're in 44 00:02:23,760 --> 00:02:26,280 Speaker 1: a giant sauna right now. We're we're you can't see 45 00:02:26,320 --> 00:02:28,160 Speaker 1: this at home, but we're all on a zoom calls. 46 00:02:28,160 --> 00:02:31,480 Speaker 1: How we do our podcasts in the age of COVID 47 00:02:31,520 --> 00:02:34,560 Speaker 1: and Sarah. Sarah fled New York because the virus got 48 00:02:34,600 --> 00:02:38,919 Speaker 1: really bad to her family home in Florida. It got 49 00:02:38,919 --> 00:02:41,400 Speaker 1: bad in Florida. Now she's fled to North Carolina. So 50 00:02:41,520 --> 00:02:44,239 Speaker 1: if you're listening from North Carolina, I mean, I'm no doctor, 51 00:02:44,440 --> 00:02:48,120 Speaker 1: but I'm gonna say, maybe shelter in place because this 52 00:02:48,200 --> 00:02:52,240 Speaker 1: virus is following side. I've really timed COVID nineteen very 53 00:02:52,240 --> 00:02:54,600 Speaker 1: well with my travels across the country, and I have 54 00:02:54,680 --> 00:02:58,120 Speaker 1: been driving everywhere too and keeping to myself. Um, but yes, 55 00:02:58,200 --> 00:03:01,400 Speaker 1: fingers crossed, that doesn't happen obviously, I would hate for 56 00:03:01,440 --> 00:03:04,720 Speaker 1: that to happen in North Carolina. There's an alternative explanation. 57 00:03:04,800 --> 00:03:07,360 Speaker 1: Maybe she's bringing it wherever she had never had it. 58 00:03:07,400 --> 00:03:12,079 Speaker 1: I promise I've been tested nothing this this is one 59 00:03:12,080 --> 00:03:14,680 Speaker 1: more reason why I'm glad we're doing this, uh these 60 00:03:14,720 --> 00:03:18,280 Speaker 1: podcasts remotely these days. But that other voice you here, 61 00:03:18,320 --> 00:03:20,520 Speaker 1: that's our guest this week. Very very excited to have 62 00:03:20,600 --> 00:03:23,760 Speaker 1: him back on the show. His name is Rob or Not. 63 00:03:24,000 --> 00:03:27,640 Speaker 1: He's the co founder of Research Affiliates. Rob, welcome back 64 00:03:27,680 --> 00:03:30,120 Speaker 1: to the show. Thank you so much. It's a pleasure. 65 00:03:30,680 --> 00:03:33,080 Speaker 1: And Rob, where are you? You're in California? I presume right. 66 00:03:33,480 --> 00:03:37,120 Speaker 1: I live mostly in Miami Beach, but I flee Miami 67 00:03:37,160 --> 00:03:40,600 Speaker 1: Beach during the summer months and returned to Newport Beach, 68 00:03:40,600 --> 00:03:44,520 Speaker 1: where I used to live. So I'm I'm hunkered down 69 00:03:44,600 --> 00:03:49,840 Speaker 1: here at home until end of September, roughly Florida, California. 70 00:03:49,920 --> 00:03:54,520 Speaker 1: Rob can't escape it either. Yeah, well, Rob, as Sarah 71 00:03:54,520 --> 00:03:56,560 Speaker 1: pointed out in the in the introduction, You've thought a 72 00:03:56,600 --> 00:04:00,360 Speaker 1: lot of really fascinating research over the years on bubbles, 73 00:04:00,560 --> 00:04:04,040 Speaker 1: and boy, I think that one of the craziest things 74 00:04:04,080 --> 00:04:07,280 Speaker 1: I've seen this year is this notion of the valuation 75 00:04:07,320 --> 00:04:11,440 Speaker 1: expansion that we've seen in a market that already seemed 76 00:04:11,840 --> 00:04:14,440 Speaker 1: very frothy before the recession hit. You know, of course, 77 00:04:14,480 --> 00:04:17,040 Speaker 1: we had the the big correction, the bear market that 78 00:04:17,120 --> 00:04:22,000 Speaker 1: was very quickly almost completely reversed. How shocking is it 79 00:04:22,040 --> 00:04:25,200 Speaker 1: to you to see this valuation expansion we're seeing right now, 80 00:04:25,360 --> 00:04:28,839 Speaker 1: and you know, based on on your studies of past bubbles, 81 00:04:29,520 --> 00:04:31,400 Speaker 1: is there any way to sort of expect how far 82 00:04:31,440 --> 00:04:34,320 Speaker 1: it goes or or when the sort of the music 83 00:04:34,360 --> 00:04:36,919 Speaker 1: stops playing and we all have to come back to 84 00:04:36,960 --> 00:04:40,880 Speaker 1: earth sort of mean reverting valuations, if ever, I'll take 85 00:04:40,920 --> 00:04:43,680 Speaker 1: the last part of your question. First. Short answer is no, 86 00:04:43,800 --> 00:04:45,760 Speaker 1: there's no way of knowing when it's when the bubbles 87 00:04:45,800 --> 00:04:49,000 Speaker 1: going to peter her out. We just know that it will. Um. 88 00:04:49,120 --> 00:04:54,360 Speaker 1: We also know that people buying bubble assets will make 89 00:04:54,400 --> 00:04:57,600 Speaker 1: money until they don't. And if they're buying on the 90 00:04:57,600 --> 00:05:00,920 Speaker 1: presumption that hey, it's soaring, I want to get on 91 00:05:00,960 --> 00:05:05,240 Speaker 1: this and uh right at the next leg up. Um, 92 00:05:05,279 --> 00:05:08,760 Speaker 1: if they don't have a cell discipline, if they don't 93 00:05:08,839 --> 00:05:13,039 Speaker 1: have a view of what will it take for me 94 00:05:13,200 --> 00:05:17,760 Speaker 1: to say, okay, enough already, I'm going to get out, Um, 95 00:05:17,920 --> 00:05:21,200 Speaker 1: then they are doomed to ride the roller coaster over 96 00:05:21,240 --> 00:05:26,680 Speaker 1: the top and down. And uh so, without a cell discipline, 97 00:05:26,680 --> 00:05:35,599 Speaker 1: buying bubble assets is insanely stupid. Bubbles. Jeremy Grantham went 98 00:05:35,640 --> 00:05:38,400 Speaker 1: on record saying this is the third bubble of his lifetime. 99 00:05:39,000 --> 00:05:45,880 Speaker 1: I view bubbles on a more uh scaled approach. There's 100 00:05:45,920 --> 00:05:48,599 Speaker 1: always bubbles. There's a little micro bubbles at work in 101 00:05:48,600 --> 00:05:52,640 Speaker 1: the market all the time, bits of irrationality all the time. 102 00:05:53,200 --> 00:05:56,000 Speaker 1: What we think of as a bubble is really when 103 00:05:56,480 --> 00:06:00,520 Speaker 1: a market as a whole goes to irrational levels, or 104 00:06:00,560 --> 00:06:02,479 Speaker 1: when a segment of the market as a whole goes 105 00:06:02,520 --> 00:06:06,440 Speaker 1: to irrational levels. One of the things that I've done 106 00:06:06,520 --> 00:06:10,120 Speaker 1: that I think is relatively important is to come up 107 00:06:10,160 --> 00:06:13,599 Speaker 1: with a workable definition of the term bubble. People bandy 108 00:06:13,600 --> 00:06:17,520 Speaker 1: around the term, and all it means is, well, it's frothy. Okay, 109 00:06:17,600 --> 00:06:20,560 Speaker 1: froth is a characteristic of bubbles and vice versa. But 110 00:06:21,360 --> 00:06:23,320 Speaker 1: that doesn't define it in a way you can use 111 00:06:23,360 --> 00:06:27,000 Speaker 1: it in real time. Uh. My definition that you can 112 00:06:27,160 --> 00:06:30,200 Speaker 1: use in real time is if you wanted to value 113 00:06:30,279 --> 00:06:35,240 Speaker 1: an asset using discounted cash flow or some other accepted 114 00:06:35,320 --> 00:06:40,080 Speaker 1: valuation method, you would have to use implausible assumptions to 115 00:06:40,240 --> 00:06:44,720 Speaker 1: justify the current multiple second part of the definition, and 116 00:06:44,839 --> 00:06:49,520 Speaker 1: no less important. The marginal buyer, the person who's buying 117 00:06:49,520 --> 00:06:55,560 Speaker 1: it today's prices, doesn't care about valuation models. At all. 118 00:06:56,440 --> 00:06:59,520 Speaker 1: If those two definitions are in place, you've got a 119 00:06:59,600 --> 00:07:02,400 Speaker 1: bubble and you can identify it when it's happening. Now, 120 00:07:02,400 --> 00:07:05,159 Speaker 1: the right answer is not to short short all of 121 00:07:05,160 --> 00:07:08,839 Speaker 1: the bubble assets, because bubbles can continue farther than you 122 00:07:08,839 --> 00:07:11,600 Speaker 1: can imagine. The The old adage the market can be 123 00:07:11,640 --> 00:07:16,160 Speaker 1: irrational longer than you can remain solvent is absolutely true, 124 00:07:16,200 --> 00:07:33,360 Speaker 1: and there's there's myriad examples of that. I love the 125 00:07:33,400 --> 00:07:36,280 Speaker 1: title of one of the papers that Research Affiliates put 126 00:07:36,320 --> 00:07:39,760 Speaker 1: out back in April, and it's yes, it's a bubble, 127 00:07:40,200 --> 00:07:42,920 Speaker 1: so what And you mentioned micro bubbles and at the time, 128 00:07:43,360 --> 00:07:46,440 Speaker 1: one of those micro bubbles that you mentioned was Tesla, 129 00:07:46,520 --> 00:07:49,520 Speaker 1: And of course look at where we are now with Tesla. 130 00:07:49,600 --> 00:07:53,920 Speaker 1: But we hear the word bubble being thrown out almost 131 00:07:54,000 --> 00:07:57,160 Speaker 1: constantly these days, whether or not it relates to tech 132 00:07:57,360 --> 00:08:00,280 Speaker 1: or the fame names or Tesla for example. Well, we 133 00:08:00,320 --> 00:08:02,440 Speaker 1: had a recent guest on the podcast we talked about 134 00:08:02,440 --> 00:08:04,960 Speaker 1: the concept of a melt up and said that hold 135 00:08:05,000 --> 00:08:08,240 Speaker 1: on a second. Sure, it's scary because eventually will end 136 00:08:08,240 --> 00:08:11,200 Speaker 1: and roll over, but you can enjoy it while it's 137 00:08:11,280 --> 00:08:14,160 Speaker 1: happening well from your perspective, because it's so difficult to 138 00:08:14,200 --> 00:08:19,000 Speaker 1: time these things. What advice can you give on how 139 00:08:19,040 --> 00:08:24,040 Speaker 1: to possibly approach what maybe a bubble? Well, you can 140 00:08:24,160 --> 00:08:27,360 Speaker 1: enjoy it as long as it keeps going, for sure. 141 00:08:28,480 --> 00:08:31,080 Speaker 1: The question is do you have a cell discipline? So 142 00:08:31,160 --> 00:08:34,840 Speaker 1: whoever said enjoy it while it's running, the question to 143 00:08:34,960 --> 00:08:37,320 Speaker 1: them would be a very simple one. Okay, So what 144 00:08:37,400 --> 00:08:41,400 Speaker 1: will it take for you to sell? Tesla is currently 145 00:08:41,520 --> 00:08:45,960 Speaker 1: valued larger than the entire US auto industry x Tesla. 146 00:08:46,720 --> 00:08:49,840 Speaker 1: It's valued at more than twice the value of Toyota, 147 00:08:50,080 --> 00:08:54,760 Speaker 1: which has remained profitable through the COVID crisis, remained profitable 148 00:08:54,800 --> 00:08:58,360 Speaker 1: through the global financial crisis, and produces thirty times as 149 00:08:58,400 --> 00:09:01,120 Speaker 1: many cars as Tesla. Now, Tesla is not just an 150 00:09:01,120 --> 00:09:04,600 Speaker 1: auto company. It's also a technology company and a patents company, 151 00:09:04,600 --> 00:09:07,280 Speaker 1: and an energy company and so forth. But what they 152 00:09:07,320 --> 00:09:10,360 Speaker 1: purport to make money on at the moment is cars, 153 00:09:11,000 --> 00:09:14,600 Speaker 1: and what they hope aspirationally to make money on is 154 00:09:14,880 --> 00:09:18,280 Speaker 1: some of these other things too. The bottom line is 155 00:09:18,840 --> 00:09:25,000 Speaker 1: to justify a valuation larger than Test than Toyota plus 156 00:09:25,120 --> 00:09:29,280 Speaker 1: the entire US auto industry the combination of all of that, 157 00:09:29,800 --> 00:09:34,400 Speaker 1: you'd have to paint a scenario in which Tesla's revenues 158 00:09:34,640 --> 00:09:41,080 Speaker 1: are comparable to all of those companies combined in let's 159 00:09:41,120 --> 00:09:47,120 Speaker 1: say ten years. Is that possible. Yes, That's why I 160 00:09:47,200 --> 00:09:52,760 Speaker 1: use the word plausible. Is it plausible? No? It would 161 00:09:52,760 --> 00:09:56,400 Speaker 1: have to see thirty or forty growth per annum for 162 00:09:56,440 --> 00:10:00,560 Speaker 1: the next ten years in order to have that uh 163 00:10:00,800 --> 00:10:05,040 Speaker 1: thirty full fortyfold fiftyfold growth in business in just ten years. 164 00:10:05,160 --> 00:10:09,520 Speaker 1: In fact, in its last ten years, it hasn't grown fiftyfold. Sir, 165 00:10:09,640 --> 00:10:12,480 Speaker 1: I think Ellen needs to restock those short shorts he 166 00:10:12,559 --> 00:10:16,320 Speaker 1: was selling to justify this valuation. Summer is not gonna 167 00:10:16,400 --> 00:10:21,480 Speaker 1: last forever. I would note that I have never shortened Tesla. 168 00:10:21,840 --> 00:10:24,319 Speaker 1: I've thought it was overpriced since it was a lot 169 00:10:24,400 --> 00:10:27,520 Speaker 1: cheaper than than current levels. At level, I was thinking 170 00:10:27,559 --> 00:10:31,480 Speaker 1: it's a short, but I've never shorted it for the 171 00:10:31,679 --> 00:10:34,480 Speaker 1: very simple reason that bubbles can continue longer than you 172 00:10:34,520 --> 00:10:37,120 Speaker 1: can possibly imagine, and can go further than you can 173 00:10:37,160 --> 00:10:41,120 Speaker 1: possibly imagine. They don't last forever. When I use the 174 00:10:41,160 --> 00:10:46,679 Speaker 1: word plausible, it's important because you do have bubble stocks 175 00:10:47,000 --> 00:10:51,679 Speaker 1: that that simple definition would identify as a bubble, and 176 00:10:51,840 --> 00:10:57,080 Speaker 1: correctly identify as a bubble that subsequently proved to have 177 00:10:57,840 --> 00:11:03,200 Speaker 1: results that that exceed plausible and that actually justify those prices. 178 00:11:03,600 --> 00:11:07,000 Speaker 1: The vivid example that comes to mind from the earlier 179 00:11:07,080 --> 00:11:10,720 Speaker 1: tech bubble of two thousand is Amazon. Amazon and ninety 180 00:11:10,800 --> 00:11:14,240 Speaker 1: nine was priced at levels that it would have had 181 00:11:14,240 --> 00:11:18,839 Speaker 1: to achieve implausible growth to justify the prices at that time. 182 00:11:19,240 --> 00:11:22,240 Speaker 1: Well over the next ten years, it underperformed the market 183 00:11:22,559 --> 00:11:25,840 Speaker 1: in a big way over the next ten years. It's 184 00:11:25,880 --> 00:11:29,920 Speaker 1: in that second decade that they finally hit their stride 185 00:11:30,000 --> 00:11:32,800 Speaker 1: and achieved the kind of growth that would have justified 186 00:11:33,280 --> 00:11:37,760 Speaker 1: the price. That's a long time to wait, so bubbles 187 00:11:38,480 --> 00:11:44,200 Speaker 1: usually burst. There's just enough exceptions to the rule that 188 00:11:44,320 --> 00:11:49,640 Speaker 1: do achieve implausible growth, and then some that it draws 189 00:11:50,000 --> 00:11:53,360 Speaker 1: suckers in to say, Okay, this time is different. I 190 00:11:53,400 --> 00:11:56,320 Speaker 1: wonder if there is an element of people trying to 191 00:11:56,360 --> 00:11:59,320 Speaker 1: put a book value on on Elon Musk's brain, you know, 192 00:11:59,400 --> 00:12:02,360 Speaker 1: and look looking, and it's the Amazon example is a 193 00:12:02,400 --> 00:12:06,840 Speaker 1: great example. You know that valuation for an online bookseller 194 00:12:07,440 --> 00:12:09,640 Speaker 1: was one thing, but of course we saw, you know, 195 00:12:09,760 --> 00:12:12,360 Speaker 1: Amazon turn into something much more than that. I wonder 196 00:12:12,360 --> 00:12:15,000 Speaker 1: if people are thinking, Nielon will will turn this into 197 00:12:15,040 --> 00:12:17,200 Speaker 1: something bigger than just a car company, you know, a 198 00:12:17,280 --> 00:12:20,760 Speaker 1: battery company that you know whatever. I don't know, but 199 00:12:21,120 --> 00:12:23,000 Speaker 1: it's hard to get into the brains of people that 200 00:12:23,040 --> 00:12:26,720 Speaker 1: are buying uh Tesla at ten thousand times trailing earnings 201 00:12:28,640 --> 00:12:32,720 Speaker 1: or or twelve times annual run rate revenues to make 202 00:12:32,760 --> 00:12:36,640 Speaker 1: money at ten times revenues, if you assume maybe the 203 00:12:36,679 --> 00:12:39,520 Speaker 1: company will have a twenty or thirty percent profit margin 204 00:12:39,600 --> 00:12:42,679 Speaker 1: down the road, how how big would those revenues have 205 00:12:42,800 --> 00:12:46,360 Speaker 1: to grow to justify ten times revenues. Well, you'd have 206 00:12:46,440 --> 00:12:49,280 Speaker 1: to have the revenues grow to thirty to fifty times 207 00:12:49,360 --> 00:12:55,000 Speaker 1: current levels to justify ten times revenues today, and thirty 208 00:12:55,000 --> 00:13:02,160 Speaker 1: to fifty times growth, My goodness, that is an extravagant expectation. 209 00:13:03,280 --> 00:13:05,719 Speaker 1: I would also say that Amazon has entered what I 210 00:13:05,720 --> 00:13:09,520 Speaker 1: would call bubble territory um. When it announced its first 211 00:13:09,600 --> 00:13:14,679 Speaker 1: quarter earnings at the end of April, it was priced 212 00:13:14,679 --> 00:13:16,319 Speaker 1: at the end of that day at a hundred eleven 213 00:13:16,360 --> 00:13:19,760 Speaker 1: times trailing. When you're earnings now, I use trailing earnings, 214 00:13:19,760 --> 00:13:22,600 Speaker 1: not expected earnings, because expected earnings haven't happened yet and 215 00:13:22,640 --> 00:13:26,199 Speaker 1: they often don't. But in any event, they were selling 216 00:13:26,200 --> 00:13:30,040 Speaker 1: at a hundred eleven times the trailing earnings. My chief 217 00:13:30,080 --> 00:13:33,840 Speaker 1: investment officer Chris Brightman did a very simple analysis. He said, 218 00:13:34,120 --> 00:13:37,000 Speaker 1: what if Amazon grows tenfold in the next ten years, 219 00:13:37,480 --> 00:13:42,600 Speaker 1: grows tenfold and at that stage is bigger than the 220 00:13:42,840 --> 00:13:47,200 Speaker 1: entire US retailing community in terms of its sales, bigger 221 00:13:47,240 --> 00:13:50,600 Speaker 1: than all of US retailing in the space of ten years, 222 00:13:50,640 --> 00:13:52,920 Speaker 1: what would it be worth And he came up with 223 00:13:52,960 --> 00:13:55,400 Speaker 1: an answer of seventy times earnings. It would be worth 224 00:13:55,440 --> 00:13:58,199 Speaker 1: a massive premium to the market. Seventy times earnings is 225 00:13:58,240 --> 00:14:00,719 Speaker 1: a big premium. It's not a hundred times, and it's 226 00:14:00,760 --> 00:14:04,000 Speaker 1: not today's hundred sixty times. Right. It's a good point 227 00:14:04,000 --> 00:14:07,160 Speaker 1: about trailing earnings, especially in this environment when boy, who's 228 00:14:07,200 --> 00:14:10,040 Speaker 1: even given a forecast anymore, it's it's almost impossible to know. 229 00:14:10,679 --> 00:14:13,440 Speaker 1: But rap I think what a lot of from the map, 230 00:14:13,480 --> 00:14:16,640 Speaker 1: from sort of the macro angle, um, I think what 231 00:14:16,760 --> 00:14:19,080 Speaker 1: a lot of people are struggling with when they try 232 00:14:19,120 --> 00:14:23,880 Speaker 1: to do valuation models is the notion that real yields 233 00:14:23,880 --> 00:14:26,440 Speaker 1: are negative right now. In other words, you know, treasury yields, 234 00:14:26,480 --> 00:14:30,600 Speaker 1: the safest assets are paying a yield uh that's less 235 00:14:30,600 --> 00:14:33,280 Speaker 1: than the inflation rate. Even out I think all the 236 00:14:33,280 --> 00:14:35,080 Speaker 1: way to thirty years, I'd have to double check that. 237 00:14:35,120 --> 00:14:38,680 Speaker 1: But the whole curve pretty much is negative on a 238 00:14:38,720 --> 00:14:42,560 Speaker 1: real basis. How much does that gum up your attempt 239 00:14:42,600 --> 00:14:47,000 Speaker 1: to to find a fair valuation. You know, our colleague 240 00:14:47,000 --> 00:14:49,600 Speaker 1: of mine who writes a colum at Bloomberg, Cameron Christ, 241 00:14:50,040 --> 00:14:53,520 Speaker 1: keeps joking that, you know, people think this justifies sort 242 00:14:53,520 --> 00:14:57,040 Speaker 1: of an infinity valuation on tech stocks. But there is 243 00:14:57,080 --> 00:14:59,600 Speaker 1: some truth to the fact that when the you know, 244 00:14:59,640 --> 00:15:02,560 Speaker 1: when the ascount rate is solo, when real yields are negative, 245 00:15:02,960 --> 00:15:07,720 Speaker 1: we should be able to sort of expect some valuation expansion. 246 00:15:07,800 --> 00:15:10,920 Speaker 1: But how do you wrap your head around an equity 247 00:15:11,000 --> 00:15:14,960 Speaker 1: valuation from a macro level when when real yields are negative. Well, firstly, 248 00:15:15,400 --> 00:15:20,600 Speaker 1: low real yields do justify higher evaluation, So let's stipulate 249 00:15:20,680 --> 00:15:23,160 Speaker 1: that and move that out of the way. The question 250 00:15:23,240 --> 00:15:27,760 Speaker 1: is how much higher? Now one of the nuances, there's 251 00:15:27,800 --> 00:15:32,440 Speaker 1: a Gordon equation, which is uh dividends over a discount 252 00:15:32,520 --> 00:15:37,640 Speaker 1: rate being a valuation metric for companies, which means that 253 00:15:37,680 --> 00:15:40,440 Speaker 1: if the if the discount rate is zero, that the 254 00:15:40,440 --> 00:15:45,640 Speaker 1: evaluation is infinity. Okay, Well, that is tacitly the argument 255 00:15:45,680 --> 00:15:50,640 Speaker 1: that negative rates justify any evaluation. You choose. My pushback 256 00:15:50,720 --> 00:15:54,640 Speaker 1: on that is, we had negligible real rates in the 257 00:15:54,680 --> 00:15:59,240 Speaker 1: mid fifties and stocks were trading at ten twelve times earnings, 258 00:15:59,400 --> 00:16:02,800 Speaker 1: so it didn't work. Then we have negative rate real 259 00:16:02,880 --> 00:16:07,400 Speaker 1: rates in Japan and Europe. They're trading at half to 260 00:16:07,480 --> 00:16:11,720 Speaker 1: two thirds are multiples, so it's not working there. So 261 00:16:12,000 --> 00:16:16,120 Speaker 1: if it doesn't work in other locations or at other times, 262 00:16:16,760 --> 00:16:21,360 Speaker 1: then why not? And I think the reason is very 263 00:16:21,440 --> 00:16:26,280 Speaker 1: very simple. Your your growth rate is also linked to 264 00:16:26,440 --> 00:16:29,680 Speaker 1: real interest rates. Real interest rates being low can mean 265 00:16:29,760 --> 00:16:33,800 Speaker 1: money is cheap and the discount rate is way down. Uh, 266 00:16:33,840 --> 00:16:37,800 Speaker 1: And it can mean that growth expectations are anemic, and 267 00:16:37,960 --> 00:16:40,640 Speaker 1: you have to take that into account. If growth expectations 268 00:16:40,680 --> 00:16:43,560 Speaker 1: dropped just as much as the interest rates, they cancel 269 00:16:44,120 --> 00:16:46,360 Speaker 1: and the low rates don't help your valuations at all. 270 00:16:46,920 --> 00:16:49,040 Speaker 1: So what does research affiliates do in that environment? I 271 00:16:49,040 --> 00:16:51,120 Speaker 1: spoke with Chris Brightman back in April, so just a 272 00:16:51,160 --> 00:16:53,320 Speaker 1: couple of months ago, early on in a month, and 273 00:16:53,360 --> 00:16:55,120 Speaker 1: he explained to me how you are moving from a 274 00:16:55,160 --> 00:17:00,000 Speaker 1: more defensive posture to more so riskon moving into small 275 00:17:00,080 --> 00:17:05,240 Speaker 1: tap us stocks, moving further more so into value. Obviously 276 00:17:05,640 --> 00:17:08,320 Speaker 1: that's worked out well as that was early April, but 277 00:17:08,440 --> 00:17:11,760 Speaker 1: it does feel like a good amount has changed since 278 00:17:11,800 --> 00:17:14,680 Speaker 1: that point in time. Is that still where you stand. 279 00:17:15,160 --> 00:17:20,399 Speaker 1: We've been moving back towards a defensive posture recently, and um, 280 00:17:20,920 --> 00:17:24,840 Speaker 1: we're reluctant to go fully to a defensive posture until 281 00:17:24,920 --> 00:17:29,879 Speaker 1: this next stimulus bill gets negotiated and passed and starts 282 00:17:29,880 --> 00:17:32,520 Speaker 1: to work its way into the economy. In the last 283 00:17:32,560 --> 00:17:35,680 Speaker 1: two weeks, the rumored size of the stimulus has risen 284 00:17:35,680 --> 00:17:39,760 Speaker 1: from one trillion to two trillion. Uh. That's a big delta. 285 00:17:40,000 --> 00:17:44,160 Speaker 1: And we know, we know from the past that stimulus 286 00:17:44,440 --> 00:17:48,840 Speaker 1: doesn't just drop into consumer pockets and drop into their 287 00:17:48,880 --> 00:17:52,320 Speaker 1: spending and stimulate the economy. What it does is stimulate 288 00:17:52,400 --> 00:17:57,040 Speaker 1: asset bubbles, and so to the extent that it drops 289 00:17:57,080 --> 00:18:00,600 Speaker 1: into people's pockets and people aren't working, so there's less 290 00:18:00,640 --> 00:18:05,040 Speaker 1: goods and services to buy, then you're either going to 291 00:18:05,160 --> 00:18:10,080 Speaker 1: get asset inflation or consumer price inflation, or a bit 292 00:18:10,080 --> 00:18:13,639 Speaker 1: of both. We didn't get the consumer price inflation after 293 00:18:13,680 --> 00:18:16,639 Speaker 1: the global financial crisis because the money may remainstalled on 294 00:18:16,680 --> 00:18:20,760 Speaker 1: the Fed's balance sheet and in rebuilding the balance sheets 295 00:18:20,800 --> 00:18:23,640 Speaker 1: of banks, and didn't get out into the macro economy. 296 00:18:23,680 --> 00:18:27,399 Speaker 1: To be spent to create the demand. Now, if it 297 00:18:27,440 --> 00:18:29,399 Speaker 1: gets out in the economy to create the demand and 298 00:18:29,440 --> 00:18:32,880 Speaker 1: there's no supply, there's elements of truth in both Keynesianism 299 00:18:32,960 --> 00:18:36,479 Speaker 1: and supply side economics. If there's no supply, you're going 300 00:18:36,520 --> 00:18:40,240 Speaker 1: to create inflation, and so there in lies the challenge. 301 00:18:41,040 --> 00:18:43,160 Speaker 1: Do I think some of the stimulus will make its 302 00:18:43,200 --> 00:18:48,000 Speaker 1: way into the capital markets? Of course yes, And so 303 00:18:48,200 --> 00:18:53,560 Speaker 1: does that push the market higher very possibly yes, um, 304 00:18:53,680 --> 00:18:57,280 Speaker 1: or at least it props it up at levels that 305 00:18:57,640 --> 00:19:03,400 Speaker 1: don't make economic sense. Um. I never thought after the 306 00:19:03,520 --> 00:19:07,119 Speaker 1: tech bubble that I would ever see dispersion and valuation 307 00:19:07,240 --> 00:19:10,800 Speaker 1: between growth and value stocks as wide as we saw then. 308 00:19:11,040 --> 00:19:17,240 Speaker 1: It was insane, and we're there again. The spread between 309 00:19:17,280 --> 00:19:20,680 Speaker 1: growth and value stocks using price to book value, which 310 00:19:20,680 --> 00:19:25,800 Speaker 1: is a very flawed measure, reached a point of nine 311 00:19:25,840 --> 00:19:29,679 Speaker 1: to one ratio, growth being nine times as expensive as 312 00:19:29,720 --> 00:19:33,239 Speaker 1: value during the tech bubble. That's an astonishing ratio. Well, 313 00:19:33,280 --> 00:19:38,000 Speaker 1: it's now eleven to one, eleven to one. Using price 314 00:19:38,080 --> 00:19:41,480 Speaker 1: to sales, it reached a point of sixteen or seventeen 315 00:19:41,520 --> 00:19:45,919 Speaker 1: to one. It's now nineteen to one between growth and value. 316 00:19:46,720 --> 00:19:52,160 Speaker 1: Some valuation metrics you mentioned Elon Musk and the negligible 317 00:19:52,200 --> 00:19:56,840 Speaker 1: book value of Tesla. Some valuation metrics like price to 318 00:19:56,920 --> 00:20:00,520 Speaker 1: book are actually pretty deeply flawed. We have a paper 319 00:20:00,600 --> 00:20:05,840 Speaker 1: coming out shortly the demonstrates that intangibles are a huge 320 00:20:05,880 --> 00:20:10,400 Speaker 1: missing component of book value and that if you incorporate 321 00:20:10,440 --> 00:20:14,840 Speaker 1: intangible as you get a better valuation metric. And that 322 00:20:14,960 --> 00:20:18,119 Speaker 1: I think is exciting work because it actually makes the 323 00:20:18,280 --> 00:20:24,400 Speaker 1: FAMA French price to book based value factor about thirty 324 00:20:24,800 --> 00:20:31,200 Speaker 1: more powerful. That's cool, That's that's pretty interesting, you know. Rob. 325 00:20:31,240 --> 00:20:34,520 Speaker 1: That brings us to another really interesting report that you 326 00:20:34,520 --> 00:20:37,240 Speaker 1: guys have out recently about the sort of the notion 327 00:20:37,280 --> 00:20:41,240 Speaker 1: of when that turn to value uh might happen? Uh. 328 00:20:41,280 --> 00:20:44,520 Speaker 1: And you point out that value tends to underperform in 329 00:20:44,560 --> 00:20:46,679 Speaker 1: a in a downturn in a market like like we 330 00:20:46,720 --> 00:20:50,679 Speaker 1: saw this year, and then outperformed during the recovery. The 331 00:20:50,800 --> 00:20:53,720 Speaker 1: question I always have with this is, you know, when 332 00:20:53,720 --> 00:20:55,920 Speaker 1: you look at sort of what the cohort of value 333 00:20:55,920 --> 00:20:59,200 Speaker 1: stocks is right now, Um, you know a lot of banks, 334 00:20:59,240 --> 00:21:03,400 Speaker 1: a lot of energy companies, um, that would clearly benefit 335 00:21:03,440 --> 00:21:07,120 Speaker 1: from higher interest rates, higher energy prices, that sort of thing. 336 00:21:08,040 --> 00:21:12,320 Speaker 1: So how much of of the phenomenon is actually the factor, 337 00:21:12,359 --> 00:21:15,000 Speaker 1: and how much does it depend on sort of what 338 00:21:15,119 --> 00:21:18,600 Speaker 1: sectors are in that factor at any given time, or 339 00:21:18,640 --> 00:21:22,400 Speaker 1: does it just so happen that cyclical stocks like that 340 00:21:22,440 --> 00:21:27,000 Speaker 1: tend to be in the value factor a lot more often, 341 00:21:27,119 --> 00:21:30,080 Speaker 1: especially at these sort of inflection points in the economy 342 00:21:30,160 --> 00:21:33,920 Speaker 1: like this. That's a lot of questions rolled into one. Firstly, 343 00:21:34,760 --> 00:21:40,399 Speaker 1: the notion that value loses during bearer markets. Actually, what 344 00:21:40,480 --> 00:21:44,440 Speaker 1: our research showed is that it's a coin toss um. 345 00:21:44,680 --> 00:21:48,959 Speaker 1: People buy value thinking it's going to help cushion the downside. Uh, 346 00:21:49,080 --> 00:21:51,920 Speaker 1: it sometimes does, and it sometimes doesn't. If you buy 347 00:21:52,000 --> 00:21:56,680 Speaker 1: furcate bear markets into those that are driven by the 348 00:21:56,760 --> 00:22:03,520 Speaker 1: bursting of a bubble, value when is big big the 349 00:22:03,960 --> 00:22:09,800 Speaker 1: end of the tech bubble, value stocks actually were up 350 00:22:10,000 --> 00:22:13,879 Speaker 1: about thirty percent in the first two years of that 351 00:22:13,920 --> 00:22:20,480 Speaker 1: bear market up, all right, that's interesting. When the nifty 352 00:22:20,520 --> 00:22:24,200 Speaker 1: fifty burst in seventy three and four, value outperformed handily. 353 00:22:24,920 --> 00:22:30,400 Speaker 1: When you have a macroeconomic shock where the economy itself 354 00:22:30,480 --> 00:22:34,960 Speaker 1: is getting hit hard, value tends to perform as badly 355 00:22:35,000 --> 00:22:39,560 Speaker 1: as the market or worse. Global financial crisis, it performed worse, 356 00:22:39,680 --> 00:22:43,040 Speaker 1: not drastically worse, but worse enough. To get people's attention 357 00:22:43,080 --> 00:22:44,600 Speaker 1: because they thought it was going to protect them on 358 00:22:44,600 --> 00:22:49,040 Speaker 1: the downside, which it doesn't. Where value really shines is 359 00:22:49,080 --> 00:22:51,680 Speaker 1: in the first two years after a bear market peters out, 360 00:22:51,720 --> 00:22:54,320 Speaker 1: and it makes very little difference whether the bear market 361 00:22:54,480 --> 00:23:00,840 Speaker 1: was fundamentals related or bubble related. The recovery um of 362 00:23:01,000 --> 00:23:05,800 Speaker 1: value tends to beat the market as a whole by 363 00:23:05,920 --> 00:23:10,200 Speaker 1: ten to twenty percentage points over the next two years, 364 00:23:11,400 --> 00:23:15,720 Speaker 1: and taken together, the bear market and the recovery value 365 00:23:15,720 --> 00:23:20,119 Speaker 1: on average winds by about ten percent in cases where 366 00:23:20,840 --> 00:23:25,960 Speaker 1: it's it's economic dislocation and uh forty or fifty percent 367 00:23:26,080 --> 00:23:28,080 Speaker 1: in times when it's bursting in bubble. What do we 368 00:23:28,119 --> 00:23:31,080 Speaker 1: have now? We have kind of both, right, yeah, kind 369 00:23:31,080 --> 00:23:33,920 Speaker 1: of economic driven bearer market, and the bubble has not 370 00:23:34,000 --> 00:23:37,800 Speaker 1: yet burst. So if we have a second leg to 371 00:23:37,800 --> 00:23:39,960 Speaker 1: the bearer market, my prediction would be that it will 372 00:23:40,000 --> 00:23:43,679 Speaker 1: be a bubble bursting portion of the bearer market. I 373 00:23:43,800 --> 00:23:47,480 Speaker 1: have no idea when is the right time to pivot 374 00:23:47,600 --> 00:23:52,160 Speaker 1: into value. I have a very strong view that value 375 00:23:52,200 --> 00:23:55,680 Speaker 1: over the next five years will beat growth handily by 376 00:23:55,680 --> 00:23:58,520 Speaker 1: a wide margin. But if you want to pick the 377 00:23:58,600 --> 00:24:01,320 Speaker 1: entry point, I have no clue. I would say average 378 00:24:01,320 --> 00:24:02,920 Speaker 1: in over the course of the next year or two. 379 00:24:03,800 --> 00:24:08,000 Speaker 1: Do not do not cut your value exposure just because 380 00:24:08,040 --> 00:24:10,560 Speaker 1: it's hurt. You have laid now. The other part of 381 00:24:10,600 --> 00:24:14,720 Speaker 1: your question is what about those sectors that comprise value, 382 00:24:15,200 --> 00:24:20,160 Speaker 1: aren't they Let me rephrase your question and put words 383 00:24:20,200 --> 00:24:24,040 Speaker 1: in your mouth. This time is different, People say this 384 00:24:24,119 --> 00:24:30,240 Speaker 1: time is different lots of times and usually always things 385 00:24:30,280 --> 00:24:33,400 Speaker 1: are different. Things are always a little different. Rarely are 386 00:24:33,400 --> 00:24:39,160 Speaker 1: they different enough to matter this particular economic meltdown. Things 387 00:24:39,160 --> 00:24:42,719 Speaker 1: are different enough that they do matter. And the question 388 00:24:42,880 --> 00:24:45,040 Speaker 1: is by how much there are going to be a 389 00:24:45,080 --> 00:24:49,760 Speaker 1: ton of bankruptcies. Those bankruptcies will be overwhelmingly on the 390 00:24:49,840 --> 00:24:53,199 Speaker 1: value side of the spectrum. So to the extent you 391 00:24:53,240 --> 00:24:57,080 Speaker 1: can invest in value and avoid value traps that are 392 00:24:57,080 --> 00:25:02,160 Speaker 1: headed to zero, that is wonderful. It's a tough thing 393 00:25:02,200 --> 00:25:06,920 Speaker 1: to do, but that is a wonderful aspirational goal. Then 394 00:25:06,960 --> 00:25:10,040 Speaker 1: the question is how much of the value segment would 395 00:25:10,080 --> 00:25:13,520 Speaker 1: have to go bust to justify that current eleven to 396 00:25:13,600 --> 00:25:19,000 Speaker 1: one spread. That spread is absolutely enormous. Growth stocks eleven 397 00:25:19,080 --> 00:25:22,399 Speaker 1: times as expensive as value using price to book and 398 00:25:22,640 --> 00:25:27,920 Speaker 1: different ratios using earnings or sales eleven to one spread. 399 00:25:28,400 --> 00:25:32,199 Speaker 1: What's the normal spread, it's about five to one. So 400 00:25:32,280 --> 00:25:34,200 Speaker 1: what would it take for the eleven to one spread 401 00:25:34,240 --> 00:25:37,000 Speaker 1: to go to five to one without value doubling or 402 00:25:37,000 --> 00:25:39,760 Speaker 1: relative to growth. Well, the easy way to do that 403 00:25:39,880 --> 00:25:41,879 Speaker 1: is for half of the value stocks to go bust. 404 00:25:43,280 --> 00:25:46,400 Speaker 1: So I would say, if you look at the current situation, 405 00:25:46,680 --> 00:25:49,320 Speaker 1: and if you come away with a view that half 406 00:25:49,359 --> 00:25:52,680 Speaker 1: of the publicly traded value stocks in the market are 407 00:25:52,760 --> 00:25:56,159 Speaker 1: likely to go bust in the coming year, then I 408 00:25:56,160 --> 00:26:00,919 Speaker 1: would say, don't pivot into value. My personal view is 409 00:26:01,119 --> 00:26:03,399 Speaker 1: ten or of them are going bust. I don't know 410 00:26:03,400 --> 00:26:08,440 Speaker 1: which ones, although I think deck coverage ratios and things 411 00:26:08,480 --> 00:26:11,680 Speaker 1: like that can help avoid some of the falling knives. 412 00:26:12,320 --> 00:26:16,480 Speaker 1: But uh, in any event, um, if you have the 413 00:26:16,560 --> 00:26:22,000 Speaker 1: view that this cycle is different, but not so radically 414 00:26:22,080 --> 00:26:26,440 Speaker 1: different as to kill half of the value stocks, then 415 00:26:26,480 --> 00:26:45,800 Speaker 1: it's a phenomenal time to buy value. I believe Rob 416 00:26:46,000 --> 00:26:49,359 Speaker 1: gets some special award for actually answering all parts to 417 00:26:49,440 --> 00:26:53,800 Speaker 1: Mike's question. I think I think he got every one 418 00:26:53,840 --> 00:26:57,200 Speaker 1: of them. It's like when you know, well, you when 419 00:26:57,200 --> 00:27:00,000 Speaker 1: you watch the you know, the Federal Reserve press conference, 420 00:27:00,080 --> 00:27:01,920 Speaker 1: you know you've got your one shots. You're you're throwing 421 00:27:02,000 --> 00:27:05,800 Speaker 1: like five questions I thought, I've I've seen my friend 422 00:27:05,880 --> 00:27:09,000 Speaker 1: Jeff Kern's ask questions that those things, and I keep 423 00:27:09,000 --> 00:27:11,720 Speaker 1: expecting like that music they play at the Oscars, you know, 424 00:27:11,800 --> 00:27:20,560 Speaker 1: halfway through his questions exactly. But never mind, never mind, 425 00:27:23,000 --> 00:27:24,879 Speaker 1: I've been in our comment on that one. Rob, I 426 00:27:24,880 --> 00:27:32,880 Speaker 1: don't know no emergency rate cut. I think that leads 427 00:27:32,960 --> 00:27:35,560 Speaker 1: us to uh, that time of the week, Sarah, I 428 00:27:35,600 --> 00:27:39,159 Speaker 1: believe it does stand clear of the craziest things we 429 00:27:39,200 --> 00:27:43,000 Speaker 1: saw in markets this week. So Rob, this is our week, 430 00:27:43,240 --> 00:27:45,840 Speaker 1: our weekly gimmick, the craziest thing we saw in markets 431 00:27:45,880 --> 00:27:49,240 Speaker 1: this week. I'm gonna let Sarah go first, because I 432 00:27:49,280 --> 00:27:51,480 Speaker 1: feel like in North Carolina there's got to be something 433 00:27:51,520 --> 00:27:54,840 Speaker 1: crazy going on that we don't know about. Uh, not 434 00:27:54,920 --> 00:27:57,960 Speaker 1: too much. I really have been confined to where I'm 435 00:27:57,960 --> 00:27:59,960 Speaker 1: staying right now. I haven't been able to get out 436 00:28:00,000 --> 00:28:05,960 Speaker 1: and about and explore. Unfortunately, hopefully soon, UM, so I 437 00:28:06,240 --> 00:28:09,479 Speaker 1: might disappoint you. Not as crazy as it is, I 438 00:28:09,520 --> 00:28:12,800 Speaker 1: think interesting. Um to the point that we are in 439 00:28:13,040 --> 00:28:16,680 Speaker 1: right now, I was able to see so far, eleven 440 00:28:17,400 --> 00:28:21,119 Speaker 1: SMP five hundred technology companies have reported earnings, and every 441 00:28:21,160 --> 00:28:24,639 Speaker 1: single one of them have beat in earnings expectations. Now, 442 00:28:24,680 --> 00:28:26,600 Speaker 1: of course there are plenty of other metrics that people 443 00:28:26,600 --> 00:28:30,440 Speaker 1: are watching and that go into this um, but since 444 00:28:30,440 --> 00:28:34,520 Speaker 1: the earning season began, check is actually the worst performing 445 00:28:34,520 --> 00:28:38,080 Speaker 1: sector along with communication services. So you you bring in 446 00:28:38,160 --> 00:28:40,920 Speaker 1: some of the other fang names as well, and it 447 00:28:41,040 --> 00:28:43,080 Speaker 1: just shows you the point that we are at right 448 00:28:43,120 --> 00:28:46,640 Speaker 1: now with some of these mega cap very popular tech 449 00:28:46,760 --> 00:28:49,320 Speaker 1: names where they can beat on earnings, but it doesn't 450 00:28:49,360 --> 00:28:52,640 Speaker 1: matter because they already are trading at very high valuations 451 00:28:52,960 --> 00:28:56,640 Speaker 1: and expectations are them or just just sky high? Yeah, 452 00:28:56,840 --> 00:28:58,960 Speaker 1: that's that's pretty good. That's tells you a lot about 453 00:28:59,000 --> 00:29:00,960 Speaker 1: sort of the climate right now. Not only do you 454 00:29:01,040 --> 00:29:03,640 Speaker 1: have to beat I guess you have to you know, uh, 455 00:29:04,120 --> 00:29:07,560 Speaker 1: cure cancer and land on the moon and who knows 456 00:29:07,600 --> 00:29:10,360 Speaker 1: what else, but every single one of these tech companies 457 00:29:10,440 --> 00:29:14,680 Speaker 1: is going to do that, right right, they'll all go 458 00:29:14,720 --> 00:29:18,040 Speaker 1: to the moon. Maybe Tesla. So I'm gonna I'm gonna 459 00:29:18,080 --> 00:29:20,160 Speaker 1: break your rules a little bit. I'm gonna go back 460 00:29:20,200 --> 00:29:25,400 Speaker 1: a week. Um. The craziest thing I've seen, uh this 461 00:29:25,600 --> 00:29:31,400 Speaker 1: month was a week ago Monday, when Tesla rose uh 462 00:29:31,680 --> 00:29:35,440 Speaker 1: two hundred fifty points and then fell three hundred points 463 00:29:35,440 --> 00:29:41,840 Speaker 1: basically a fifteen percent up down move based on precisely 464 00:29:42,040 --> 00:29:46,239 Speaker 1: zero news about Tesla. Now you can think about that 465 00:29:46,320 --> 00:29:52,440 Speaker 1: and come up with possible rationals. Um Uh. If they 466 00:29:52,480 --> 00:29:57,400 Speaker 1: have a trailing twelve month profitability net profitability, S and 467 00:29:57,440 --> 00:29:59,560 Speaker 1: P will finally have to add them to the index. 468 00:30:00,120 --> 00:30:03,840 Speaker 1: The index funds like to say, we don't move stock prices. 469 00:30:04,200 --> 00:30:07,320 Speaker 1: Oh my god, is that a lie? Uh. It doesn't 470 00:30:07,480 --> 00:30:10,000 Speaker 1: move on the day they add the stocks because it 471 00:30:10,040 --> 00:30:13,080 Speaker 1: moves in the weeks ahead as arbit treasures and hedge 472 00:30:13,080 --> 00:30:16,080 Speaker 1: funds load up on the company in order to fulfill 473 00:30:16,160 --> 00:30:19,680 Speaker 1: the one day immediate demand. But Tesla would come in 474 00:30:19,720 --> 00:30:22,680 Speaker 1: at about a one percent weight. There's about six trillion 475 00:30:22,720 --> 00:30:26,160 Speaker 1: index to the S and P. Uh. That means that 476 00:30:27,000 --> 00:30:29,280 Speaker 1: when it's added to the S and P, there will 477 00:30:29,280 --> 00:30:33,000 Speaker 1: be a sixty billion dollar buy ticket for Tesla stock 478 00:30:33,040 --> 00:30:37,880 Speaker 1: in a single day. People looking ahead to that will say, okay, 479 00:30:38,000 --> 00:30:41,800 Speaker 1: I wanted to front run that, put that on my books, 480 00:30:41,800 --> 00:30:44,040 Speaker 1: and then flip it over to the index funds when 481 00:30:44,120 --> 00:30:46,760 Speaker 1: it gets added. We saw it on Twitter that went 482 00:30:46,800 --> 00:30:50,360 Speaker 1: up in the space of ten days. Uh, and the 483 00:30:50,400 --> 00:30:52,920 Speaker 1: index funds were able to say we didn't move Twitter's price. 484 00:30:53,000 --> 00:30:56,600 Speaker 1: It closed more or less unchanged, same thing will happen 485 00:30:56,600 --> 00:31:01,160 Speaker 1: this go around. Um, but that swing up three hundred, 486 00:31:01,360 --> 00:31:03,680 Speaker 1: up to fifty and down three hundred in a single 487 00:31:03,760 --> 00:31:10,280 Speaker 1: day based on no news was to me the wackiest 488 00:31:10,320 --> 00:31:12,880 Speaker 1: thing I've seen this month. That was a good one. Yeah, 489 00:31:12,920 --> 00:31:15,320 Speaker 1: it's amazing. I think it's because they ran out of 490 00:31:15,320 --> 00:31:17,800 Speaker 1: those short shorts. It is why everything is because they 491 00:31:17,880 --> 00:31:20,160 Speaker 1: ran out of those short shorts. The reason that they 492 00:31:20,160 --> 00:31:23,480 Speaker 1: posted twelve month profitability, Mike was because of those short 493 00:31:23,480 --> 00:31:27,200 Speaker 1: shorts as well. I really don't want to see Elon 494 00:31:27,320 --> 00:31:30,000 Speaker 1: Muskin short shorts. Maybe that'll be what finally brings the 495 00:31:30,040 --> 00:31:33,720 Speaker 1: stock downhill. He'll tweet out I think Tesla stock is 496 00:31:33,760 --> 00:31:36,480 Speaker 1: too expensive, and then will also include a picture of 497 00:31:36,520 --> 00:31:39,800 Speaker 1: him in Tesla short shorts. Well, it's it's interesting to 498 00:31:39,840 --> 00:31:42,280 Speaker 1: think of what, you know, how much is gonna have 499 00:31:42,320 --> 00:31:43,840 Speaker 1: to get sold of all the other stocks in the 500 00:31:43,840 --> 00:31:46,120 Speaker 1: index funds to make to make some room for Tesla. 501 00:31:46,120 --> 00:31:48,160 Speaker 1: I guess they. I guess they buy it ahead of time. 502 00:31:48,160 --> 00:31:50,560 Speaker 1: And just that's a nuance that a lot of people overlook. 503 00:31:50,640 --> 00:31:53,840 Speaker 1: You're gonna have to see to buy sixty billion in 504 00:31:54,000 --> 00:31:58,520 Speaker 1: Tesla that day, you're gonna have to uh sell about 505 00:31:58,600 --> 00:32:02,880 Speaker 1: three billion of uh Apple and a like amount of 506 00:32:03,000 --> 00:32:05,959 Speaker 1: Microsoft that same day in order to make that trade, 507 00:32:06,200 --> 00:32:09,840 Speaker 1: and people aren't paying attention to that. Right, You're not 508 00:32:09,880 --> 00:32:11,640 Speaker 1: making room for a little guy, You're make You're making 509 00:32:11,720 --> 00:32:14,760 Speaker 1: room for a very large stack. When it gets at it, 510 00:32:14,760 --> 00:32:18,320 Speaker 1: it will be the biggest addition to the SMP ever ever. 511 00:32:18,480 --> 00:32:20,520 Speaker 1: Right as far as a waiting, I guess. And of 512 00:32:20,520 --> 00:32:23,200 Speaker 1: course the share price hasn't budged in the least based 513 00:32:23,200 --> 00:32:30,640 Speaker 1: on that speculation, just trading sideways lately. Right, alright, that's 514 00:32:30,680 --> 00:32:32,840 Speaker 1: pretty good. Well in the spirit of bubbles, you know, Sarah, 515 00:32:32,880 --> 00:32:36,240 Speaker 1: a lot of our Twitter friends complain that we don't 516 00:32:36,480 --> 00:32:40,320 Speaker 1: cover bitcoin and crypto enough, So I'm gonna delve into 517 00:32:40,360 --> 00:32:42,760 Speaker 1: that world a little bit through the back door, so 518 00:32:42,800 --> 00:32:46,040 Speaker 1: to speak, um and talk about sort of what I 519 00:32:46,080 --> 00:32:50,000 Speaker 1: think is the most important uh real world use case 520 00:32:50,120 --> 00:32:53,640 Speaker 1: for bitcoin, and that is committing crimes, you know, and 521 00:32:53,720 --> 00:33:00,720 Speaker 1: another another shadiness general shadin. I know, I know, I'm 522 00:33:00,760 --> 00:33:03,040 Speaker 1: I'm bound to get some more similar tweets at me 523 00:33:03,040 --> 00:33:05,719 Speaker 1: about this, but all in good fun. I'm just joking 524 00:33:05,840 --> 00:33:08,200 Speaker 1: sort of. But anyway, there's a great story in this 525 00:33:08,280 --> 00:33:12,080 Speaker 1: week's Business Week about this company, Norse Chidro. It's a 526 00:33:12,200 --> 00:33:18,280 Speaker 1: it's a big aluminum manufacturer based in Norway, and they 527 00:33:18,320 --> 00:33:22,239 Speaker 1: got hit with one of these ransomware attacks where you know, 528 00:33:22,520 --> 00:33:26,520 Speaker 1: a hacker basically freezes is up your computer systems and 529 00:33:26,560 --> 00:33:29,160 Speaker 1: demands bitcoin and payment, and then they send you the 530 00:33:29,240 --> 00:33:33,600 Speaker 1: decode to unlock your computers again. And you know, companies 531 00:33:33,640 --> 00:33:37,080 Speaker 1: have a variety of strategies for dealing with this. Norse 532 00:33:37,200 --> 00:33:41,120 Speaker 1: Chidros was was really interesting. They're like, no way, we're 533 00:33:41,240 --> 00:33:45,600 Speaker 1: unplugging all of our computers. They took the entire company offline, 534 00:33:46,280 --> 00:33:49,120 Speaker 1: and then the story is all about how they tried 535 00:33:49,160 --> 00:33:52,160 Speaker 1: to operate in sort of an analog world without being 536 00:33:52,200 --> 00:33:54,840 Speaker 1: connected to the Internet, and they had to do all 537 00:33:54,920 --> 00:33:59,360 Speaker 1: sorts of things, uh, including um, they went to Staples 538 00:33:59,720 --> 00:34:03,360 Speaker 1: and bought a bunch of printers and paper and ink 539 00:34:03,360 --> 00:34:07,160 Speaker 1: car cartridges. They said, they cleaned out the local staples basically, 540 00:34:07,840 --> 00:34:11,360 Speaker 1: and they had these old PCs somewhere in storage that 541 00:34:11,480 --> 00:34:13,840 Speaker 1: don't connect to the Internet. So they broke them out 542 00:34:14,200 --> 00:34:17,880 Speaker 1: and they started printing out orders. Now the salesman, you know, 543 00:34:18,360 --> 00:34:21,279 Speaker 1: because they couldn't communicate on the Internet, had not much 544 00:34:21,320 --> 00:34:23,759 Speaker 1: to do, so they they made the salesman go to 545 00:34:23,800 --> 00:34:27,440 Speaker 1: the factory floor and start running these instructions on paper 546 00:34:27,560 --> 00:34:31,040 Speaker 1: back and forth between the guys on the floor, the 547 00:34:31,040 --> 00:34:35,120 Speaker 1: workers on the floor. But my favorite part, Sarah, is well, 548 00:34:35,520 --> 00:34:38,160 Speaker 1: one other thing they in order to meet payroll, they 549 00:34:38,160 --> 00:34:42,160 Speaker 1: basically just copied all of the previous week's paychecks from 550 00:34:42,200 --> 00:34:45,000 Speaker 1: their third party supplier and set them all out again. 551 00:34:45,040 --> 00:34:46,759 Speaker 1: And they tried to weed out the people who had 552 00:34:46,840 --> 00:34:49,759 Speaker 1: retired and gotten fired and that sort of thing. But 553 00:34:49,840 --> 00:34:53,680 Speaker 1: to communicate with suppliers, they broke out the old fax machine, 554 00:34:54,280 --> 00:34:58,000 Speaker 1: which I think is amazing because, Sarah, if this happened 555 00:34:58,000 --> 00:35:00,160 Speaker 1: to Bloomberg, I think I might be running the I 556 00:35:00,239 --> 00:35:02,000 Speaker 1: might be one of the only guys old enough who 557 00:35:02,000 --> 00:35:04,640 Speaker 1: still knew how to work a fax machine. I would 558 00:35:04,680 --> 00:35:07,080 Speaker 1: be I'd be like, I'd be facts in your stories. 559 00:35:08,880 --> 00:35:12,000 Speaker 1: That is my When I started in my newspaper career 560 00:35:12,000 --> 00:35:14,120 Speaker 1: in the early nineties, I used to go to the 561 00:35:14,120 --> 00:35:15,880 Speaker 1: fax machine every day and I'd have to check for 562 00:35:15,920 --> 00:35:19,760 Speaker 1: oh bits, you know, obituaries and police reports, and tucked 563 00:35:19,760 --> 00:35:22,600 Speaker 1: in among all of that would be news from from 564 00:35:22,640 --> 00:35:27,000 Speaker 1: this new, young, upstart news company called Bloomberg News, and 565 00:35:27,040 --> 00:35:30,000 Speaker 1: I and they would just facts. It's too newspapers. Uh. 566 00:35:30,120 --> 00:35:32,800 Speaker 1: That's how we started, was was faxing out the stories 567 00:35:33,360 --> 00:35:35,759 Speaker 1: and hoping that newspapers would say, it's pretty good. We're 568 00:35:35,760 --> 00:35:37,960 Speaker 1: gonna we're gonna take this service. You know, we're gonna 569 00:35:37,960 --> 00:35:40,920 Speaker 1: start running this stuff. Um so I'm I'm an old 570 00:35:40,960 --> 00:35:42,879 Speaker 1: hand with a fax machine. Rob. I imagine you worked 571 00:35:42,880 --> 00:35:45,400 Speaker 1: a fax machine or two in your day. Oh I have, 572 00:35:45,640 --> 00:35:50,680 Speaker 1: I have. I still get some every now and then 573 00:35:51,120 --> 00:35:54,399 Speaker 1: if you facts to us. There's some facts number we're 574 00:35:54,400 --> 00:35:57,759 Speaker 1: all associated with, and it'll show up in my email. Uh, 575 00:35:57,840 --> 00:36:00,520 Speaker 1: sort of a scan of the facts, and it's always like, 576 00:36:00,600 --> 00:36:05,080 Speaker 1: you know, some sort of Caribbean vacation or I don't know. 577 00:36:05,640 --> 00:36:08,840 Speaker 1: You get you get the weirdest stuff, fascinating story. But 578 00:36:08,840 --> 00:36:10,800 Speaker 1: I still think Rob gets the win with Tesla. You 579 00:36:11,000 --> 00:36:14,239 Speaker 1: you almost can't lose with Tesla these days. Yeah, yeah, 580 00:36:15,239 --> 00:36:20,279 Speaker 1: especially the short shorts head on the back. But where 581 00:36:20,360 --> 00:36:22,400 Speaker 1: are going to have to leave it there? Rob or not? 582 00:36:22,440 --> 00:36:24,840 Speaker 1: Thank you so much for coming on the podcast this week. 583 00:36:25,239 --> 00:36:36,080 Speaker 1: This was great fun. Thank you so much. What goes up? 584 00:36:36,160 --> 00:36:39,239 Speaker 1: We'll be back next week. Until then, you can find 585 00:36:39,320 --> 00:36:42,520 Speaker 1: us on the Bloomberg Terminal website and app or wherever 586 00:36:42,640 --> 00:36:45,279 Speaker 1: you get your podcasts. We love it if you took 587 00:36:45,280 --> 00:36:47,400 Speaker 1: the time to rate and read the show on Apple 588 00:36:47,440 --> 00:36:50,799 Speaker 1: Podcasts so more listeners can find us. And you can 589 00:36:50,840 --> 00:36:54,799 Speaker 1: find us on Twitter, follow me at Sara Pantzack. Mike 590 00:36:55,080 --> 00:36:58,760 Speaker 1: is a reaganonymous and you can also follow Bloomberg Podcasts 591 00:36:58,800 --> 00:37:02,040 Speaker 1: at podcasts And a very special thank you to Charlie 592 00:37:02,040 --> 00:37:04,359 Speaker 1: Pellett of Bloomberg Radio and the voice of the New 593 00:37:04,440 --> 00:37:07,600 Speaker 1: York City Subway System. What Goes Up is produced by 594 00:37:07,680 --> 00:37:11,320 Speaker 1: Jordan Gospore. The head of Bloomberg podcast is francesco Leavie. 595 00:37:11,520 --> 00:37:13,239 Speaker 1: Thanks for listening, See you next time.