1 00:00:05,800 --> 00:00:08,720 Speaker 1: Welcome to the Bloomberg p m L Podcast. I'm pim Fox. 2 00:00:08,760 --> 00:00:11,520 Speaker 1: Along with my co host Lisa Abramowitz. Each day we 3 00:00:11,640 --> 00:00:15,120 Speaker 1: bring you the most important, noteworthy, and useful interviews for 4 00:00:15,200 --> 00:00:17,840 Speaker 1: you and your money, whether you're at the grocery store 5 00:00:17,960 --> 00:00:20,720 Speaker 1: or the trading floor. Find the Bloomberg p m L 6 00:00:20,840 --> 00:00:33,120 Speaker 1: Podcast on Apple Podcasts, SoundCloud, and Bloomberg dot com. Let's 7 00:00:33,120 --> 00:00:35,880 Speaker 1: find out what's real when it comes to markets. Ben 8 00:00:35,960 --> 00:00:39,040 Speaker 1: Hunt is chief investment strategist for Salient. They are based 9 00:00:39,080 --> 00:00:43,640 Speaker 1: in Houston, and he is also one of the bloggers 10 00:00:43,920 --> 00:00:48,240 Speaker 1: for a website it's called the Epsilon Theory and you 11 00:00:48,280 --> 00:00:51,880 Speaker 1: can follow them also on Twitter at Epsilon Theory. Ben Hunt, 12 00:00:51,920 --> 00:00:55,480 Speaker 1: maybe just tell people why is it called epsilon theory. 13 00:00:56,280 --> 00:00:58,080 Speaker 1: That's a great question. Tim, It's great to be here, 14 00:00:58,080 --> 00:01:00,760 Speaker 1: by the way, Thanks you and Lisa for having so. 15 00:01:00,880 --> 00:01:06,000 Speaker 1: It's called Epsilon theory after the standard formula that you 16 00:01:06,160 --> 00:01:08,880 Speaker 1: learned about. Well, what goes into a portfolio? Right? We 17 00:01:08,920 --> 00:01:11,800 Speaker 1: talked about a portfolio and its returns being a combination 18 00:01:11,800 --> 00:01:14,679 Speaker 1: of alpha. Everybody knows what alpha is, right, That's that 19 00:01:15,200 --> 00:01:20,440 Speaker 1: special sauce that you bring to to get better. It 20 00:01:20,520 --> 00:01:27,440 Speaker 1: is to be honest, and the execution is a unicorn. 21 00:01:27,520 --> 00:01:30,280 Speaker 1: That's that's that's well put, Lisa. And also everyone knows 22 00:01:30,280 --> 00:01:33,040 Speaker 1: what beta is, which is, okay, I want to get 23 00:01:33,240 --> 00:01:35,080 Speaker 1: the market. I want to get the returns of the 24 00:01:35,360 --> 00:01:37,480 Speaker 1: world or the market gives to you. But if you 25 00:01:37,520 --> 00:01:39,920 Speaker 1: if you look at that equation, right, and it's always 26 00:01:39,920 --> 00:01:42,560 Speaker 1: set up as an equation in your textbooks and the like, 27 00:01:42,640 --> 00:01:44,800 Speaker 1: which is a whole another thing. Yeah, yeah, well the 28 00:01:45,040 --> 00:01:50,160 Speaker 1: equation is absolutely actually alpha plus beta plus this E 29 00:01:50,560 --> 00:01:55,520 Speaker 1: term out there E for epsilon, which is E for error. Right, 30 00:01:55,600 --> 00:01:57,960 Speaker 1: that that in all of econometrics, you've always got that 31 00:01:58,120 --> 00:02:01,040 Speaker 1: error term that's sitting out there. And the point about 32 00:02:01,040 --> 00:02:05,600 Speaker 1: epsilon theory is that, well, actually, let's unpack that error 33 00:02:05,680 --> 00:02:08,640 Speaker 1: term a bit, because it's not just all randomness and 34 00:02:08,639 --> 00:02:14,880 Speaker 1: and um what they call stochastic error in statistics. That's 35 00:02:14,919 --> 00:02:20,400 Speaker 1: where market behavior lives. That's that's where game theory lives, 36 00:02:20,440 --> 00:02:24,120 Speaker 1: that's where history lives, that's where market behavior lives, and 37 00:02:24,160 --> 00:02:28,200 Speaker 1: there are patterns to that. It's not just random their patterns. 38 00:02:28,240 --> 00:02:32,960 Speaker 1: There's a way to get real market information out of that. 39 00:02:33,280 --> 00:02:35,440 Speaker 1: So that's what I'm trying to explore all right. So 40 00:02:35,520 --> 00:02:41,239 Speaker 1: that's a great place to start with understanding market behavior. 41 00:02:41,639 --> 00:02:44,280 Speaker 1: In the past few weeks, a lot of people say 42 00:02:44,320 --> 00:02:46,960 Speaker 1: that it was the market behavior of computers, and that 43 00:02:47,000 --> 00:02:49,200 Speaker 1: they took over everything and created a big mass, and 44 00:02:49,200 --> 00:02:52,119 Speaker 1: then humans were left to try to darn these darn machines. 45 00:02:52,240 --> 00:02:55,040 Speaker 1: Why were they? Why were they so complicated? H and 46 00:02:55,160 --> 00:02:58,919 Speaker 1: other people were saying, well, people were just nervous, and uh, 47 00:02:59,040 --> 00:03:01,200 Speaker 1: stocks are a good And then we had a ton 48 00:03:01,400 --> 00:03:04,520 Speaker 1: of investment managers come on and we would ask them, 49 00:03:04,960 --> 00:03:06,560 Speaker 1: all right, so are you buying and they said, well, 50 00:03:06,600 --> 00:03:11,000 Speaker 1: not yet. What was The fundamentals are sound? Correct, correct, 51 00:03:11,240 --> 00:03:14,560 Speaker 1: the fundamentals are sound? Are you buying? Not so much? 52 00:03:14,600 --> 00:03:17,399 Speaker 1: Exactly every single one? So what's going on here? Well, 53 00:03:17,520 --> 00:03:19,920 Speaker 1: I'll say this first, a couple of points to quit. First, 54 00:03:20,200 --> 00:03:23,880 Speaker 1: it ain't the machines, right, it really isn't. And I 55 00:03:23,960 --> 00:03:28,760 Speaker 1: say that from a perspective of well, it's only we 56 00:03:28,800 --> 00:03:31,079 Speaker 1: managed about thirteen billion, right, so you know, not a 57 00:03:31,160 --> 00:03:33,240 Speaker 1: huge fish. But we know what we're doing and we've 58 00:03:33,240 --> 00:03:35,480 Speaker 1: got a wide range of strategies. A chunk of those 59 00:03:35,480 --> 00:03:40,120 Speaker 1: strategies are these systematic strategies, including the boogeyman du jour 60 00:03:40,480 --> 00:03:42,760 Speaker 1: risk parity. Right. So we've been in this for a lot. 61 00:03:43,320 --> 00:03:46,760 Speaker 1: I know I know right, right, and and what I 62 00:03:46,760 --> 00:03:51,840 Speaker 1: think is important to tell everyone about risk parity. I'll 63 00:03:51,920 --> 00:03:56,000 Speaker 1: use that as the example here. These strategies are barges. 64 00:03:56,560 --> 00:03:59,760 Speaker 1: They're not speedboats, right, and they and they react, they 65 00:03:59,840 --> 00:04:03,320 Speaker 1: do react, and they react to volatility, but it's historical 66 00:04:03,440 --> 00:04:06,520 Speaker 1: volatility they look at. And so I will tell you 67 00:04:07,240 --> 00:04:09,560 Speaker 1: from our strategy and they say, we're not one of 68 00:04:09,560 --> 00:04:12,280 Speaker 1: the giants here like in a q R or a Bridgewater, 69 00:04:12,360 --> 00:04:16,000 Speaker 1: but the bones of all of these strategies are very similar. 70 00:04:16,279 --> 00:04:18,880 Speaker 1: So I know what we're doing. I'm highly confident that 71 00:04:18,960 --> 00:04:21,200 Speaker 1: I've got a strong sense of what those other risk 72 00:04:21,240 --> 00:04:25,400 Speaker 1: parity strategies are doing. We're not selling on a on 73 00:04:25,440 --> 00:04:28,720 Speaker 1: a Monday when the markets declining. We don't even take 74 00:04:28,760 --> 00:04:31,360 Speaker 1: the VIX, which is what most people think of when 75 00:04:31,360 --> 00:04:34,760 Speaker 1: they think of volatility. That's a forward looking thing. We 76 00:04:34,800 --> 00:04:37,919 Speaker 1: don't even use that. We don't even use that. These 77 00:04:37,960 --> 00:04:43,600 Speaker 1: strategies are barges. And that ain't it. What is it? 78 00:04:43,680 --> 00:04:45,200 Speaker 1: What is it? What is it? What was it? I'll 79 00:04:45,200 --> 00:04:46,760 Speaker 1: tell you what I think what I what I think 80 00:04:46,760 --> 00:04:48,760 Speaker 1: it is, because this is what we're wrestling with with 81 00:04:48,800 --> 00:04:54,279 Speaker 1: our own strategies and and asset management. In my conversations, 82 00:04:54,320 --> 00:04:58,520 Speaker 1: I think this is what everyone is wrestling with. How 83 00:04:58,800 --> 00:05:03,160 Speaker 1: how do you invest best in a world where inflation 84 00:05:03,560 --> 00:05:06,880 Speaker 1: isn't going down, but it's starting to go up? How 85 00:05:06,920 --> 00:05:10,880 Speaker 1: do you invest our our portfolios off sides for a 86 00:05:10,960 --> 00:05:17,200 Speaker 1: world where inflation is increasing, not decreasing. That's a big change. Look, 87 00:05:18,080 --> 00:05:21,200 Speaker 1: you don't have to go back thirty years to really 88 00:05:21,200 --> 00:05:23,560 Speaker 1: be in in an inflationary environment. And even if you 89 00:05:23,600 --> 00:05:26,560 Speaker 1: were investing thirty years ago, and I certainly was, and 90 00:05:26,600 --> 00:05:28,720 Speaker 1: I don't know a many people who were. Even if 91 00:05:28,760 --> 00:05:33,720 Speaker 1: you were, those muscles they've atrophied a lot. So so 92 00:05:33,880 --> 00:05:40,000 Speaker 1: I believe so strongly that every asset owner in the 93 00:05:40,000 --> 00:05:43,000 Speaker 1: world is wrestling with these questions. And when you get 94 00:05:43,000 --> 00:05:46,279 Speaker 1: an event like that kind of hot wage number we 95 00:05:46,360 --> 00:05:50,960 Speaker 1: had on Friday, February of the two, those wheels start turning. 96 00:05:51,640 --> 00:05:54,520 Speaker 1: You start thinking, well, am I off sides? Is my 97 00:05:54,600 --> 00:05:57,760 Speaker 1: portfolio right here? And when you've got a market that 98 00:05:57,920 --> 00:06:01,760 Speaker 1: has very low i'll call it volume to it, that 99 00:06:02,040 --> 00:06:06,000 Speaker 1: it has really quite thin liquidity to it. It doesn't 100 00:06:06,040 --> 00:06:09,520 Speaker 1: take a lot of people changing their minds about where 101 00:06:09,560 --> 00:06:13,360 Speaker 1: their portfolio sits to have an outsized impact in the market. 102 00:06:14,880 --> 00:06:17,760 Speaker 1: All Right, I'm gonna make you dig a little deeper. Good. 103 00:06:18,560 --> 00:06:23,840 Speaker 1: What is coyote math? Alright, that's something I've written about recently, 104 00:06:24,080 --> 00:06:26,920 Speaker 1: and it's I like to use these kind of examples 105 00:06:26,960 --> 00:06:30,560 Speaker 1: from Yeah, I'm this dilettante farmer out in the wilds 106 00:06:30,600 --> 00:06:34,120 Speaker 1: of Connecticut, right, So we have coyotes out there, and 107 00:06:34,240 --> 00:06:37,919 Speaker 1: you are, well, I am, I am, and and the 108 00:06:39,160 --> 00:06:43,400 Speaker 1: I admire the coyotes, right because they're smart, they're clever, 109 00:06:44,320 --> 00:06:47,279 Speaker 1: they're they're much smarter than my dogs, for example, My my, 110 00:06:47,279 --> 00:06:50,960 Speaker 1: my dogs don't even know they exist. But they're too 111 00:06:51,000 --> 00:06:54,400 Speaker 1: clever by half. They're too clever by half. And what 112 00:06:54,480 --> 00:06:56,240 Speaker 1: I mean by that it's the same thing with Wiley 113 00:06:56,320 --> 00:07:00,279 Speaker 1: coyote from the Looney Tunes, always scheming and planning. And 114 00:07:00,440 --> 00:07:03,480 Speaker 1: that's the case with with real world coyotes. But it's 115 00:07:03,560 --> 00:07:07,920 Speaker 1: also true for the coyotes in our business, because this 116 00:07:08,040 --> 00:07:12,160 Speaker 1: business of financial advice and financial management attracts people who 117 00:07:12,200 --> 00:07:15,640 Speaker 1: are frankly too clever by half. All right, So real quick, 118 00:07:15,840 --> 00:07:21,360 Speaker 1: thirty seconds, what has been your biggest allocation shift concept 119 00:07:21,440 --> 00:07:24,360 Speaker 1: shift that you think investors should know based on the 120 00:07:24,480 --> 00:07:28,320 Speaker 1: signs of nascent inflation. So what you have to distinguish 121 00:07:28,360 --> 00:07:33,240 Speaker 1: between is inflation going up and interest rates going up. 122 00:07:33,280 --> 00:07:36,720 Speaker 1: There are two different things. They follow each other, but 123 00:07:37,160 --> 00:07:41,840 Speaker 1: that connection between inflation going up and interest rates going 124 00:07:41,920 --> 00:07:44,520 Speaker 1: up is the thing that everyone needs to be focused on. 125 00:07:44,840 --> 00:07:47,320 Speaker 1: And this is why, Lisa, to your question, people say, oh, 126 00:07:47,360 --> 00:07:51,320 Speaker 1: the fundamentals are sound, but I'm not investing. It's because 127 00:07:51,400 --> 00:07:55,280 Speaker 1: the fundamentals have not been a sufficient condition to invest 128 00:07:55,720 --> 00:07:58,440 Speaker 1: for eight or nine years. Now. What you have to 129 00:07:58,520 --> 00:08:01,280 Speaker 1: have is some notion of Okay, I like the fundamentals, 130 00:08:01,680 --> 00:08:03,920 Speaker 1: but what are the central banks going to do? What 131 00:08:03,960 --> 00:08:07,240 Speaker 1: are they going to do about interest rates? So we 132 00:08:07,280 --> 00:08:09,880 Speaker 1: can talk about inflation going up, but it's thinking about 133 00:08:09,880 --> 00:08:12,680 Speaker 1: interest rates as well. Ben Hunt, a pleasure having you on. 134 00:08:12,720 --> 00:08:14,280 Speaker 1: Thank you so much. Thank You'll let you go back 135 00:08:14,280 --> 00:08:17,480 Speaker 1: to your coyotes. Ben Hunt, chief investment strategist at Salient, 136 00:08:17,560 --> 00:08:21,600 Speaker 1: which is based in Houston, Texas and overseeing about thirteen 137 00:08:21,680 --> 00:08:39,640 Speaker 1: billion dollars of bassets. There has been so much focus 138 00:08:39,760 --> 00:08:43,839 Speaker 1: in the past few weeks on Russian interference in US 139 00:08:43,880 --> 00:08:48,560 Speaker 1: elections and UH their encroachments in the cyber world of 140 00:08:48,760 --> 00:08:52,240 Speaker 1: the US, but there are many other states sponsored actors 141 00:08:52,240 --> 00:08:57,240 Speaker 1: out there trying to infiltrate UH the technological ecosystem of 142 00:08:57,280 --> 00:08:58,719 Speaker 1: the U S. And here to talk about that is 143 00:08:58,840 --> 00:09:02,800 Speaker 1: John halt Quist, director of intelligence analysis for fire Eye 144 00:09:02,920 --> 00:09:06,160 Speaker 1: based in Washington, d C. He joins US Now, John, 145 00:09:06,280 --> 00:09:08,400 Speaker 1: thank you so much for being with US. I wanted 146 00:09:08,440 --> 00:09:13,080 Speaker 1: to start with North Korea. Fire Eye has identified them 147 00:09:13,120 --> 00:09:17,800 Speaker 1: as behind a very sophisticated state sponsored cyber attacker. Can 148 00:09:17,840 --> 00:09:20,480 Speaker 1: you give us a sense of what that effort looks 149 00:09:20,559 --> 00:09:24,080 Speaker 1: like and what they would or have or will target 150 00:09:24,200 --> 00:09:29,520 Speaker 1: in the US. So, we released recently released a report 151 00:09:29,520 --> 00:09:32,720 Speaker 1: on a group that we call APT thirty seven. They're 152 00:09:32,840 --> 00:09:37,520 Speaker 1: a North Korean hacking group that's been primarily focused on 153 00:09:37,720 --> 00:09:42,120 Speaker 1: South Korea carrying out espionage sort of a classic mission 154 00:09:42,240 --> 00:09:46,080 Speaker 1: for quite a long time. But we've seen them since 155 00:09:46,240 --> 00:09:50,280 Speaker 1: actually UH start developing missions outside of South Korea. They've 156 00:09:50,280 --> 00:09:53,800 Speaker 1: shown up in Japan, Vietnam, in the Middle East. UH, 157 00:09:53,800 --> 00:09:56,160 Speaker 1: and our concern is that this is another tool that 158 00:09:56,200 --> 00:10:01,040 Speaker 1: could be used by the North Korean regime to project power. UM. 159 00:10:01,120 --> 00:10:03,760 Speaker 1: They a lot of the activity that we hear about 160 00:10:03,920 --> 00:10:06,920 Speaker 1: North three and hacking activity has actually been attributed to 161 00:10:07,000 --> 00:10:10,920 Speaker 1: another group UH. This team has been able to remain 162 00:10:11,120 --> 00:10:16,319 Speaker 1: relatively obscure, which makes them an ideal choice for attack 163 00:10:16,400 --> 00:10:19,560 Speaker 1: operations or even crime because they're not as well known. 164 00:10:20,640 --> 00:10:23,080 Speaker 1: What have they attacked so far that you've been able 165 00:10:23,120 --> 00:10:27,320 Speaker 1: to trace? So most of their operations now appear to 166 00:10:27,360 --> 00:10:32,280 Speaker 1: be uh focused on sort of classic intelligence operations, are 167 00:10:32,400 --> 00:10:38,280 Speaker 1: classic intelligence collections, so uh things like defectors or sanctions 168 00:10:38,360 --> 00:10:43,040 Speaker 1: or unification efforts. Even the Olympics have been have they've 169 00:10:43,160 --> 00:10:47,280 Speaker 1: targeted individuals associated with the Olympics? Um, So they're right 170 00:10:47,320 --> 00:10:50,760 Speaker 1: now doing a lot of the low and quiet activity, 171 00:10:51,200 --> 00:10:53,800 Speaker 1: which is precisely the side type of activity we see 172 00:10:53,960 --> 00:10:59,840 Speaker 1: most nascent capabilities first focus on. For instance, the other 173 00:11:00,000 --> 00:11:02,240 Speaker 1: acting groups that have been that are out of North 174 00:11:02,280 --> 00:11:06,040 Speaker 1: three that they are very well known, first appeared to 175 00:11:06,160 --> 00:11:11,920 Speaker 1: US as espionage operations mostly focused in South Korea. So John, 176 00:11:12,080 --> 00:11:15,520 Speaker 1: I know, perhaps it's premature to talk about whether North 177 00:11:15,600 --> 00:11:20,359 Speaker 1: Korea will be able to infiltrate the US cyber ecosystem, 178 00:11:20,440 --> 00:11:24,520 Speaker 1: but I'm wondering, from your perspective, what areas are the 179 00:11:24,559 --> 00:11:29,040 Speaker 1: most vulnerable in the US. And uh do any of 180 00:11:29,040 --> 00:11:33,960 Speaker 1: these sort of state sponsored actors work together? Do they? Uh? 181 00:11:34,000 --> 00:11:35,400 Speaker 1: You know, do you have a sense of how many 182 00:11:35,480 --> 00:11:38,600 Speaker 1: there are trying to infiltrate a system at any given time. 183 00:11:40,240 --> 00:11:44,360 Speaker 1: So UH, as far as working together, we're always concerned 184 00:11:44,360 --> 00:11:48,560 Speaker 1: that lessons are being passed between some of these countries 185 00:11:48,600 --> 00:11:52,400 Speaker 1: that have longs like Russia, uh Iran and North three. 186 00:11:52,520 --> 00:11:56,880 Speaker 1: They have long standing relationships in military and move military 187 00:11:57,559 --> 00:12:01,640 Speaker 1: armaments and the training which sween them. We haven't necessarily 188 00:12:01,679 --> 00:12:05,880 Speaker 1: seen that play out from our visibility. Um our biggest 189 00:12:05,880 --> 00:12:08,600 Speaker 1: concern is that they're actually learning from each other though 190 00:12:08,640 --> 00:12:11,880 Speaker 1: as far as their offensive actions go. So each time 191 00:12:11,960 --> 00:12:16,600 Speaker 1: one of these actors carries out a major attack, a 192 00:12:16,679 --> 00:12:20,880 Speaker 1: disruptive attack, or um more of an influenced type of 193 00:12:20,920 --> 00:12:24,280 Speaker 1: attack that we saw during the elections, there each each 194 00:12:24,280 --> 00:12:26,240 Speaker 1: one of them is sort of pushing the edge for 195 00:12:26,280 --> 00:12:29,120 Speaker 1: the other and pushing the norms and the red lines 196 00:12:29,160 --> 00:12:32,440 Speaker 1: that the other other actor feels now more comfortable operating within. 197 00:12:33,120 --> 00:12:35,720 Speaker 1: So UH, in that in that regard, they are sort 198 00:12:35,760 --> 00:12:39,840 Speaker 1: of learning from each other. Would you would you say 199 00:12:39,880 --> 00:12:44,480 Speaker 1: that all heads of information technology or even the boards 200 00:12:44,600 --> 00:12:48,720 Speaker 1: of major corporations need to ask themselves are you happy? 201 00:12:48,920 --> 00:12:51,840 Speaker 1: And I use that term because that's what you describe 202 00:12:51,920 --> 00:12:54,320 Speaker 1: something tell people about are you happy? And why they 203 00:12:54,400 --> 00:12:59,120 Speaker 1: need to be particularly wary. So one of one of 204 00:12:59,120 --> 00:13:02,920 Speaker 1: the concerns that we've had with any North Korean actor is, um, 205 00:13:03,000 --> 00:13:06,319 Speaker 1: are they are they going to carry out some sort 206 00:13:06,360 --> 00:13:09,400 Speaker 1: of disruptive and destructive attack And uh, that's one of 207 00:13:09,440 --> 00:13:12,400 Speaker 1: the tools that we came across with regards to this actor. 208 00:13:12,480 --> 00:13:15,280 Speaker 1: They do have a destructive tool that could be used 209 00:13:15,840 --> 00:13:20,080 Speaker 1: in a wiper type attack. It's a fairly simplistic attack, 210 00:13:20,720 --> 00:13:25,800 Speaker 1: um and that's the name of the tool, and uh, 211 00:13:26,160 --> 00:13:28,400 Speaker 1: it's a fairly simplistic attack, but it can have a 212 00:13:28,520 --> 00:13:31,880 Speaker 1: lot of pretty strong effect on a on an organization 213 00:13:31,960 --> 00:13:37,520 Speaker 1: if they can wipe uh, you know, wipe important systems simultaneously. 214 00:13:37,960 --> 00:13:41,360 Speaker 1: And that's happened on several occasions already. From a lot 215 00:13:41,440 --> 00:13:44,880 Speaker 1: of that is the Russians, Russian actors that have done 216 00:13:44,920 --> 00:13:49,040 Speaker 1: that quite recently with a with a ransomware attack and 217 00:13:49,280 --> 00:13:53,120 Speaker 1: it actually caused billions of dollars and damages to the economy. 218 00:13:53,240 --> 00:13:56,640 Speaker 1: So it's a very real concern. So John, just real 219 00:13:56,720 --> 00:14:01,280 Speaker 1: quick here, which organization in the US is most vulnerable 220 00:14:01,280 --> 00:14:06,920 Speaker 1: at this point? Well, it's because they because a lot 221 00:14:06,960 --> 00:14:12,400 Speaker 1: of their it's of the incidents focus on critical infrastructure. Uh, 222 00:14:12,400 --> 00:14:16,760 Speaker 1: there's record that that recognized that represents often the biggest opportunity. 223 00:14:17,600 --> 00:14:21,960 Speaker 1: We anticipate that any sort of major disruptive or destructive 224 00:14:21,960 --> 00:14:24,440 Speaker 1: attack would focus on an area like that, and there's 225 00:14:24,480 --> 00:14:28,400 Speaker 1: been a lot of other incidents UM that have that 226 00:14:28,480 --> 00:14:31,400 Speaker 1: have played out like that. Uh. It's important to also 227 00:14:31,440 --> 00:14:35,440 Speaker 1: remember that critical infrastructure is not just utilities. I think 228 00:14:35,480 --> 00:14:37,960 Speaker 1: there's a lot of people to often focus on utilities, 229 00:14:38,000 --> 00:14:43,880 Speaker 1: but UM logistics and finance. UM. I want to thank 230 00:14:43,920 --> 00:14:47,880 Speaker 1: you John hould Quist, director of Intelligence Analysis or fire 231 00:14:47,920 --> 00:15:09,640 Speaker 1: Eyed talking about cyber attacks. Everybody wants it, but now 232 00:15:09,760 --> 00:15:12,560 Speaker 1: Apple wants to get it even more directly. Jack Farchie 233 00:15:12,680 --> 00:15:15,840 Speaker 1: is the senior Energy and Commodities reporter for Bloomberg is 234 00:15:15,880 --> 00:15:19,240 Speaker 1: based in London. Jack tell us the story about Apple 235 00:15:19,440 --> 00:15:25,320 Speaker 1: and why does it want its own direct supply of cobalt. Yes, 236 00:15:25,400 --> 00:15:28,360 Speaker 1: we've had this amazing shift in the cobalt market really 237 00:15:28,360 --> 00:15:32,040 Speaker 1: in a matter of a little over a year, where 238 00:15:32,080 --> 00:15:37,000 Speaker 1: the change in expectations for electric vehicles. You've seen almost 239 00:15:37,000 --> 00:15:40,520 Speaker 1: every major automaker come out with with forecasts for how 240 00:15:40,520 --> 00:15:42,240 Speaker 1: many electric vehicles they're going to build in the next 241 00:15:42,280 --> 00:15:45,240 Speaker 1: few years. Glen Core, who reported results today, had a 242 00:15:45,320 --> 00:15:46,760 Speaker 1: nice little toss up. They said it's going to be 243 00:15:47,000 --> 00:15:49,920 Speaker 1: there's a ninety billion dollars of investments announced by the 244 00:15:49,920 --> 00:15:52,880 Speaker 1: auto industry in electric vehicles, and that's had a huge 245 00:15:52,920 --> 00:15:56,120 Speaker 1: impact on the cobalt market because cobalt is an essential 246 00:15:56,120 --> 00:15:59,120 Speaker 1: commodity in the in most lithium ion batteries which are 247 00:15:59,200 --> 00:16:03,200 Speaker 1: used in electric vehicles, where cobalts also uses in licking 248 00:16:03,400 --> 00:16:07,880 Speaker 1: iron batteries in gadgets like smartphones and tablets and laptops 249 00:16:08,400 --> 00:16:11,600 Speaker 1: until now, in fact still now, Apple is probably one 250 00:16:11,680 --> 00:16:14,840 Speaker 1: of the largest end users of cobalt in the world. 251 00:16:14,920 --> 00:16:18,360 Speaker 1: Apple gadgets along with things companies like Samsung UH some 252 00:16:18,440 --> 00:16:22,240 Speaker 1: of the largest users of cobalt um As these car 253 00:16:22,280 --> 00:16:25,760 Speaker 1: companies are beginning to come out with huge forecasts for 254 00:16:26,040 --> 00:16:27,800 Speaker 1: how many electric vehicles are going to build over the 255 00:16:27,840 --> 00:16:30,240 Speaker 1: next five or ten years, they are going out into 256 00:16:30,240 --> 00:16:35,200 Speaker 1: the market, people like VW BMW going into the market 257 00:16:35,280 --> 00:16:39,880 Speaker 1: and seeking to sign big long term deals to buy 258 00:16:39,960 --> 00:16:41,840 Speaker 1: up supplies of cobalt to ensure they're gonna have enough 259 00:16:41,840 --> 00:16:44,560 Speaker 1: cobalt to build all the electric vehicles they want to 260 00:16:45,240 --> 00:16:48,880 Speaker 1: UH and now we're seeing Apple doing the same thing, essentially, 261 00:16:48,880 --> 00:16:52,120 Speaker 1: looking at what's happening in the in the car market 262 00:16:52,200 --> 00:16:56,160 Speaker 1: and what some of the car companies are doing, and 263 00:16:56,360 --> 00:16:58,440 Speaker 1: in our in our understanding, wanting to make sure that 264 00:16:58,480 --> 00:17:00,760 Speaker 1: they are going to have enough cobalt to UH to 265 00:17:00,840 --> 00:17:03,720 Speaker 1: build to carry on building iPhones and iPads into the future. 266 00:17:03,840 --> 00:17:07,639 Speaker 1: All right, So who does Apple currently buy cobalt from? 267 00:17:07,720 --> 00:17:11,000 Speaker 1: And basically who's going to be losing business as Apple 268 00:17:11,280 --> 00:17:13,760 Speaker 1: cuts out the middleman and goes direct to the miners. 269 00:17:14,359 --> 00:17:16,640 Speaker 1: It's not so much a question of Apple losing business 270 00:17:16,920 --> 00:17:19,879 Speaker 1: at the moment. Apple would go and buy batteries from 271 00:17:19,920 --> 00:17:23,520 Speaker 1: battery producers, who in turn are buying components of batteries 272 00:17:23,520 --> 00:17:25,240 Speaker 1: from people who produced those who in turn are buying 273 00:17:25,280 --> 00:17:27,879 Speaker 1: the WAW materials in a in a supply chain that 274 00:17:27,920 --> 00:17:30,040 Speaker 1: goes down the chain. So at the end of the day, 275 00:17:30,080 --> 00:17:34,479 Speaker 1: Apple is not gonna, we don't think, immediately start building 276 00:17:34,480 --> 00:17:37,119 Speaker 1: batteries of itself. They're just it's it's a question of 277 00:17:37,160 --> 00:17:39,919 Speaker 1: securing the supply of cobalt for their supply chain, for 278 00:17:39,960 --> 00:17:43,000 Speaker 1: the companies in their supply chain. Now, a cobalt is 279 00:17:43,600 --> 00:17:47,520 Speaker 1: a byproduct of mining for copper and nickel primarily, that's right, 280 00:17:48,040 --> 00:17:50,960 Speaker 1: Where does it come from? Well, that's one of the 281 00:17:50,960 --> 00:17:55,399 Speaker 1: main problems. The vast majority of it, about thirds uh, 282 00:17:55,560 --> 00:17:57,760 Speaker 1: and that's a number that's set to grow, comes from 283 00:17:57,760 --> 00:18:01,320 Speaker 1: the Democratic Republic of Congo, which is not the most 284 00:18:02,760 --> 00:18:05,040 Speaker 1: Even if it were the most stable country in the world, 285 00:18:05,440 --> 00:18:08,480 Speaker 1: that would be a pretty significant concentration risk for any 286 00:18:08,520 --> 00:18:13,560 Speaker 1: commodity UM. But uh, Democratic Republic of Congo is not 287 00:18:13,600 --> 00:18:16,440 Speaker 1: the most stable country in the world. They've just announced 288 00:18:16,440 --> 00:18:21,119 Speaker 1: a big planned increase in taxes on on minors uh, 289 00:18:21,240 --> 00:18:23,919 Speaker 1: and so that's a big concern. So I'm looking at 290 00:18:24,040 --> 00:18:29,160 Speaker 1: cobalt prices and they have skyrocketed in the past few years. 291 00:18:29,240 --> 00:18:31,360 Speaker 1: Wean just to give you a sense, from the end 292 00:18:31,440 --> 00:18:35,160 Speaker 1: of twenty sixteen, they've more than doubled uh. And I'm 293 00:18:35,200 --> 00:18:39,040 Speaker 1: just wondering it is the actual demand going to keep 294 00:18:39,119 --> 00:18:43,080 Speaker 1: up with the perceived demand that is driving prices now? 295 00:18:43,119 --> 00:18:44,800 Speaker 1: I mean, in other words, is applicant to lock in 296 00:18:45,080 --> 00:18:46,760 Speaker 1: prices that are much higher than which you might be 297 00:18:46,800 --> 00:18:49,960 Speaker 1: able to get later on. That's a very good question. 298 00:18:50,119 --> 00:18:53,160 Speaker 1: I think from what we have heard about the discussions 299 00:18:53,160 --> 00:18:55,840 Speaker 1: that are going on in the market, it's not so 300 00:18:55,920 --> 00:18:59,000 Speaker 1: much a question of locking in prices as locking in supply. 301 00:18:59,480 --> 00:19:01,800 Speaker 1: So probably believe the deals that have done. Not just 302 00:19:01,800 --> 00:19:04,720 Speaker 1: talking about Apple here, but v W, BMW, the big 303 00:19:04,760 --> 00:19:07,280 Speaker 1: car companies, some of the battery makers like Samsung, SDI 304 00:19:07,359 --> 00:19:10,639 Speaker 1: are also saying that they're seeking long term cobalt deals. 305 00:19:10,800 --> 00:19:12,920 Speaker 1: They're probably gonna have a floating price, so it will 306 00:19:12,960 --> 00:19:15,200 Speaker 1: be whatever the market price is. It's more a question 307 00:19:15,240 --> 00:19:18,199 Speaker 1: of of locking in supply. Whether the price stays at 308 00:19:18,240 --> 00:19:22,040 Speaker 1: this very high level is another question. If the shortage 309 00:19:22,040 --> 00:19:24,240 Speaker 1: that some people are looking at and fearing for the 310 00:19:24,280 --> 00:19:27,480 Speaker 1: future does materialize, then you'd have to say that prices 311 00:19:27,480 --> 00:19:30,160 Speaker 1: would go higher. But that's several years down the line. 312 00:19:30,240 --> 00:19:32,760 Speaker 1: I'm surprised that they're not lacking in a price for 313 00:19:32,840 --> 00:19:35,480 Speaker 1: a long term contract. It's very hard to lock in 314 00:19:35,520 --> 00:19:39,080 Speaker 1: a price in in the cobalt market where it's going. 315 00:19:39,280 --> 00:19:43,919 Speaker 1: It's gone through this kind of um real complete paradigm 316 00:19:43,960 --> 00:19:47,040 Speaker 1: shift because of electric vehicles. So the price has tripled, 317 00:19:47,080 --> 00:19:49,960 Speaker 1: as you said, in the past eighteen months. Who knows 318 00:19:50,000 --> 00:19:52,560 Speaker 1: what the right price is? Yeah, it's it's very it's 319 00:19:52,640 --> 00:19:54,000 Speaker 1: very hard to say, you know, you do you you take 320 00:19:54,040 --> 00:19:59,600 Speaker 1: five different forecasts for what electric vehicle production UH and 321 00:20:00,160 --> 00:20:04,399 Speaker 1: UH and and sales are going to be in UH, 322 00:20:04,400 --> 00:20:07,240 Speaker 1: and they're wildly different. UH so who can tell you 323 00:20:07,280 --> 00:20:08,959 Speaker 1: what the correct price for cobalt in five or ten 324 00:20:09,000 --> 00:20:11,119 Speaker 1: years time. Nobody can. Jack Fartie, thank you so much 325 00:20:11,160 --> 00:20:14,119 Speaker 1: for joining us. Jack Farchie, senior Energy and Commodities reporter 326 00:20:14,200 --> 00:20:17,960 Speaker 1: for a Bloomberg News coming to us from our London bureau. 327 00:20:18,040 --> 00:20:21,360 Speaker 1: You can find his story on the website Bloomberg dot 328 00:20:21,440 --> 00:20:37,960 Speaker 1: com or the terminal itself. Yes, let's talk about housing. 329 00:20:38,160 --> 00:20:40,960 Speaker 1: US existing home sales in the month of January falling 330 00:20:41,000 --> 00:20:42,919 Speaker 1: a little bit more than three percent. Here to help 331 00:20:43,000 --> 00:20:45,600 Speaker 1: us understand what's going on is Brad Hunter. He is 332 00:20:45,600 --> 00:20:49,000 Speaker 1: the chief economist of Home Adviser. They're based in West 333 00:20:49,040 --> 00:20:52,480 Speaker 1: Palm Beach, Florida. He can be followed on Twitter at 334 00:20:52,720 --> 00:20:57,360 Speaker 1: Bradley Hunter. Alright, at Bradley Hunter. What what's your view 335 00:20:57,400 --> 00:21:00,359 Speaker 1: of the of the housing market and this time that 336 00:21:00,440 --> 00:21:02,480 Speaker 1: we saw on the run rate of about five point 337 00:21:02,520 --> 00:21:06,320 Speaker 1: four million units morning, Pim. Well, Yeah, I think that 338 00:21:07,040 --> 00:21:10,480 Speaker 1: clearly the housing number was lower than expected, and I 339 00:21:10,520 --> 00:21:13,320 Speaker 1: think there are three different things that play. Number one 340 00:21:13,880 --> 00:21:17,360 Speaker 1: is the inventory and that's what everybody's talking about right now, 341 00:21:17,400 --> 00:21:21,760 Speaker 1: three point four months of supply of unsold inventory. And secondly, 342 00:21:22,240 --> 00:21:25,280 Speaker 1: uh in January mortgage rates were starting to edge up, 343 00:21:25,320 --> 00:21:28,000 Speaker 1: and of course they've gone up a lot more since then, 344 00:21:28,040 --> 00:21:29,920 Speaker 1: and I think they will go up a lot more 345 00:21:30,080 --> 00:21:34,680 Speaker 1: going forward. And the third factor is that prices were 346 00:21:34,760 --> 00:21:37,560 Speaker 1: up also in this reading, and uh, I think that 347 00:21:37,640 --> 00:21:41,280 Speaker 1: the rate of home price appreciation is going to slow. 348 00:21:42,280 --> 00:21:47,200 Speaker 1: So Brad Home Advisor helps homeowners figure out how to 349 00:21:47,240 --> 00:21:51,119 Speaker 1: renovate their homes in an effective manner. Correct. Yeah, we 350 00:21:51,200 --> 00:21:55,080 Speaker 1: connect where the marketplace that connects homeowners with the pros 351 00:21:55,119 --> 00:21:58,200 Speaker 1: that they need to get their projects done. So, just 352 00:21:58,280 --> 00:22:00,720 Speaker 1: can you give me a sense of what you're seeing 353 00:22:00,800 --> 00:22:04,520 Speaker 1: from that perspective and what it tells you about the 354 00:22:04,560 --> 00:22:07,200 Speaker 1: sort of mental state of homeowners? In other words, are 355 00:22:07,200 --> 00:22:09,880 Speaker 1: they looking to invest in their homes and expand them 356 00:22:09,920 --> 00:22:12,760 Speaker 1: because they don't want to move out? Or are they 357 00:22:12,800 --> 00:22:15,760 Speaker 1: investing in their homes in order to sell them at 358 00:22:15,760 --> 00:22:20,000 Speaker 1: a higher price. Can you get a sense of that? Yeah? Sure, Well, uh, 359 00:22:20,280 --> 00:22:23,480 Speaker 1: we just talked about the low inventory situation and it's 360 00:22:23,480 --> 00:22:26,800 Speaker 1: actually part of a vicious cycle. Um. Low supply of 361 00:22:26,920 --> 00:22:31,560 Speaker 1: homes for sale causes people to stay frustrated and I 362 00:22:32,280 --> 00:22:34,719 Speaker 1: have trouble getting the home that they want, So some 363 00:22:34,800 --> 00:22:36,760 Speaker 1: of them say, you know, I'm just gonna stay put 364 00:22:36,840 --> 00:22:39,960 Speaker 1: and remodel the house that I have. A lot more 365 00:22:40,040 --> 00:22:42,879 Speaker 1: people are looking to move because they are tired of 366 00:22:42,920 --> 00:22:45,280 Speaker 1: their current home, according to research from n A are 367 00:22:45,760 --> 00:22:48,800 Speaker 1: than people who are moving for a job that's in 368 00:22:48,800 --> 00:22:51,840 Speaker 1: a different area or what have you. So that further 369 00:22:52,119 --> 00:22:55,639 Speaker 1: reduces inventory because people stay put and then the cycle 370 00:22:55,800 --> 00:22:59,159 Speaker 1: just lather, rense, repeat, right. Um. The other thing that 371 00:22:59,200 --> 00:23:04,000 Speaker 1: I'm noticing is trend I'm calling nesting is investing. There's 372 00:23:04,040 --> 00:23:06,560 Speaker 1: all this stock market volatility, and I think it's going 373 00:23:06,640 --> 00:23:10,159 Speaker 1: to drive some people to say, you know what, instead 374 00:23:10,200 --> 00:23:13,280 Speaker 1: of staying fully invested in the stock market, up all 375 00:23:13,400 --> 00:23:15,399 Speaker 1: some of my chips off the table, and maybe go 376 00:23:15,480 --> 00:23:19,320 Speaker 1: ahead and reinvest in my home and you know, expand 377 00:23:19,560 --> 00:23:22,879 Speaker 1: or improve the property. And you know, that's a pretty 378 00:23:22,880 --> 00:23:27,520 Speaker 1: safe investment in terms of any risk. On the downside, Brad, 379 00:23:27,600 --> 00:23:31,440 Speaker 1: you note that the size of home improvement or renovation 380 00:23:31,520 --> 00:23:35,920 Speaker 1: projects is increasing. Expand on that, sure, we're seeing more 381 00:23:36,080 --> 00:23:40,240 Speaker 1: what we call major renovation projects. Our year end survey 382 00:23:40,280 --> 00:23:44,680 Speaker 1: actually showed that most home improvement companies and professionals saw 383 00:23:44,720 --> 00:23:47,720 Speaker 1: an increase in the size of their average job, whereas 384 00:23:47,760 --> 00:23:50,280 Speaker 1: only five point eight percent reported a decrease in the 385 00:23:50,280 --> 00:23:52,639 Speaker 1: average size of the job. So people are taking on 386 00:23:52,800 --> 00:23:57,600 Speaker 1: projects that they had deferred years ago. Now that the 387 00:23:57,640 --> 00:24:00,640 Speaker 1: economy is stronger, and more importantly, either equity in their 388 00:24:00,640 --> 00:24:04,399 Speaker 1: home is much higher. They're saying, Okay, you know what, 389 00:24:04,600 --> 00:24:07,040 Speaker 1: it's time to do that kitchen update that I've been 390 00:24:07,080 --> 00:24:10,560 Speaker 1: wanting to do, Or it's time to turn that basement 391 00:24:10,600 --> 00:24:13,760 Speaker 1: into a man cave or into a rental unit, or 392 00:24:14,000 --> 00:24:16,439 Speaker 1: redo the garage or the tile or whatever it is 393 00:24:16,480 --> 00:24:21,040 Speaker 1: that they've been wanting. So they're taking on more discretionary projects, 394 00:24:21,040 --> 00:24:25,240 Speaker 1: more of what I called lifestyle projects. I'm wondering bread 395 00:24:25,520 --> 00:24:29,399 Speaker 1: which parts of the country are seeing the fastest rates 396 00:24:29,600 --> 00:24:34,359 Speaker 1: of spending on home improvement. For the past few years, 397 00:24:34,720 --> 00:24:38,920 Speaker 1: it was the markets that we're seeing the greatest increases 398 00:24:39,240 --> 00:24:45,840 Speaker 1: in home prices and therefore homeowner equity, So San Francisco, 399 00:24:46,520 --> 00:24:52,200 Speaker 1: San Diego, New York, Miami, Seattle, Portland's and now it's 400 00:24:52,240 --> 00:24:55,960 Speaker 1: starting to shift. Those markets are starting to um kind 401 00:24:56,000 --> 00:24:59,359 Speaker 1: of slow down because they've had these very, very rapid 402 00:24:59,400 --> 00:25:02,520 Speaker 1: increases during the slowdown, and so now that some of 403 00:25:02,520 --> 00:25:06,680 Speaker 1: the interior markets and second tier markets are starting to 404 00:25:07,000 --> 00:25:12,360 Speaker 1: take off in a big way. So Milwaukee Columbus, Tampa, 405 00:25:12,680 --> 00:25:17,080 Speaker 1: markets like that are starting to see um very strong growth. 406 00:25:17,240 --> 00:25:20,000 Speaker 1: And uh I've been working with the Harvard Joint Center 407 00:25:20,440 --> 00:25:25,199 Speaker 1: on Housing studies and they are predicting strong growth in 408 00:25:25,240 --> 00:25:27,280 Speaker 1: those kinds of markets and and uh I can to 409 00:25:27,320 --> 00:25:29,600 Speaker 1: continue to watch those with them. So, Brad, does that 410 00:25:29,680 --> 00:25:32,919 Speaker 1: imply to you the prices in the big cities that 411 00:25:32,960 --> 00:25:36,639 Speaker 1: you mentioned are going to stagnate while they continue to 412 00:25:36,680 --> 00:25:42,159 Speaker 1: accelerate in the more central parts of the country. Right, So, 413 00:25:42,280 --> 00:25:46,000 Speaker 1: I think what we're going to see is um these 414 00:25:46,160 --> 00:25:49,680 Speaker 1: continued increases in homeowner equity. We've seen already at doubling 415 00:25:50,040 --> 00:25:52,639 Speaker 1: in equity in the country in the past five years. 416 00:25:52,760 --> 00:25:57,360 Speaker 1: That's huge, and so the markets that have already experienced 417 00:25:57,359 --> 00:25:59,480 Speaker 1: a big boom are going to just taper down. But 418 00:25:59,640 --> 00:26:02,840 Speaker 1: the the the rest of the country is now just 419 00:26:02,920 --> 00:26:06,920 Speaker 1: playing catch up and just quickly bred Any any change 420 00:26:06,920 --> 00:26:08,879 Speaker 1: in where people are going to be buying homes because 421 00:26:08,880 --> 00:26:14,120 Speaker 1: of changes in tax laws and the deductability of interest payments, Yeah, 422 00:26:14,119 --> 00:26:17,159 Speaker 1: I actually don't think that the tax law change is 423 00:26:17,160 --> 00:26:19,920 Speaker 1: going to have a huge impact on the aggregates home 424 00:26:19,960 --> 00:26:24,080 Speaker 1: sales numbers. It could shift the mix geographically or even 425 00:26:24,600 --> 00:26:28,879 Speaker 1: um across the different strata, for example, luxury home buying. 426 00:26:29,040 --> 00:26:31,720 Speaker 1: The luxury home buying population, if you will, will start 427 00:26:31,720 --> 00:26:35,000 Speaker 1: to enjoy higher after tax income, which will help home 428 00:26:35,040 --> 00:26:37,280 Speaker 1: buying and remodeling at the high end and in the 429 00:26:37,320 --> 00:26:40,760 Speaker 1: expensive markets, and the rest of the housing market won't 430 00:26:40,800 --> 00:26:43,480 Speaker 1: be affected very much either way in my opinion. Brad Hunter, 431 00:26:43,560 --> 00:26:45,800 Speaker 1: thank you so much for joining us. Bread Hunter chief 432 00:26:45,840 --> 00:26:50,200 Speaker 1: economist for Home Advisor, which is based in West Palm Beach. 433 00:26:50,720 --> 00:26:54,920 Speaker 1: We will continue attracking the housing data that we just received, 434 00:26:55,119 --> 00:26:58,800 Speaker 1: as well as the auctions later today of US Treasury. 435 00:27:00,920 --> 00:27:03,480 Speaker 1: Thanks for listening to the Bloomberg P and L podcast. 436 00:27:03,800 --> 00:27:07,679 Speaker 1: You can subscribe and listen to interviews at Apple Podcasts, SoundCloud, 437 00:27:07,800 --> 00:27:11,280 Speaker 1: or whatever podcast platform you prefer. I'm pim Fox. I'm 438 00:27:11,320 --> 00:27:14,840 Speaker 1: on Twitter at pim Fox. I'm on Twitter at Lisa 439 00:27:14,880 --> 00:27:17,800 Speaker 1: Abramo wits one. Before the podcast, you can always catch 440 00:27:17,920 --> 00:27:19,639 Speaker 1: us worldwide on Bloomberg Radio.