1 00:00:00,800 --> 00:00:04,040 Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney, alongside 2 00:00:04,040 --> 00:00:06,920 Speaker 1: my co host Matt Miller. Every business day we bring 3 00:00:06,960 --> 00:00:11,520 Speaker 1: you interviews from CEOs, market pros, and Bloomberg experts, along 4 00:00:11,560 --> 00:00:15,600 Speaker 1: with essential market moving news. Find the Bloomberg Markets Podcast 5 00:00:15,600 --> 00:00:18,479 Speaker 1: on Apple Podcasts or wherever you listen to podcasts, and 6 00:00:18,480 --> 00:00:22,840 Speaker 1: at Bloomberg dot com slash podcast. Well, last week, I 7 00:00:22,840 --> 00:00:26,079 Speaker 1: guess you know, Thursday, Friday, Saturday down in Miami, there 8 00:00:26,239 --> 00:00:30,520 Speaker 1: was a crypto investor conference and very well attended, well 9 00:00:30,560 --> 00:00:34,280 Speaker 1: covered in the business media. And what's also notable is 10 00:00:34,360 --> 00:00:37,080 Speaker 1: that people actually went. It wasn't virtual, it was a 11 00:00:37,240 --> 00:00:41,040 Speaker 1: real conference where real people got together talking all things crypto. 12 00:00:41,000 --> 00:00:43,959 Speaker 1: I look at bitcoin today, it's pretty much unchanged here, 13 00:00:44,120 --> 00:00:47,320 Speaker 1: just over thirty six thousand dollars per coin, but there's 14 00:00:47,360 --> 00:00:50,040 Speaker 1: certainly been a lot of volatility in the crypto market. 15 00:00:50,080 --> 00:00:52,120 Speaker 1: Let's get the latest with Jeff Dorman. He's the c 16 00:00:52,400 --> 00:00:56,040 Speaker 1: i O of ARCA. Arc is a digital asset from Jeff. 17 00:00:56,040 --> 00:00:58,240 Speaker 1: Thanks so much for joining us here. I love to 18 00:00:58,280 --> 00:01:01,400 Speaker 1: get your thoughts. Just let's start with bitcoin, because that's 19 00:01:01,480 --> 00:01:05,520 Speaker 1: the cryptocurrency or the crypto asset class or asset that 20 00:01:05,600 --> 00:01:10,640 Speaker 1: people are most familiar with talk us about the volatility 21 00:01:10,640 --> 00:01:15,120 Speaker 1: of bitcoin. What does that tell you? Sure? Thanks for 22 00:01:15,120 --> 00:01:19,640 Speaker 1: having me. I mean, like, the volatility is happening because 23 00:01:19,720 --> 00:01:22,440 Speaker 1: this is a new asset class, and new asset classes 24 00:01:22,480 --> 00:01:25,200 Speaker 1: don't have the same structure, they don't have the same players. Uh, 25 00:01:25,240 --> 00:01:29,920 Speaker 1: And it's largely driven by momentum and algorithmic quantitative traders 26 00:01:29,959 --> 00:01:32,759 Speaker 1: to date um. You know, I think that will change 27 00:01:32,800 --> 00:01:34,880 Speaker 1: over time as it becomes of a larger and more 28 00:01:35,600 --> 00:01:38,200 Speaker 1: adopted asset. In fact, you're already seeing it's starting to 29 00:01:38,200 --> 00:01:40,720 Speaker 1: decline a little bit because this is touching so many people. 30 00:01:41,240 --> 00:01:43,720 Speaker 1: But you know, volatility happens when you have a lot 31 00:01:43,760 --> 00:01:47,880 Speaker 1: more retail traders and momentum traders than you do fundamental investors. 32 00:01:47,880 --> 00:01:49,760 Speaker 1: And that's natural for an asset that doesn't really have 33 00:01:49,800 --> 00:01:53,760 Speaker 1: any fundamental underpinning. Are we looking at a little bit 34 00:01:53,760 --> 00:01:59,040 Speaker 1: of stability here around thirty six thousand dollars right now? Sure? 35 00:01:59,520 --> 00:02:03,160 Speaker 1: Things as pretty quickly, Uh, you know, I think I think, Look, 36 00:02:02,880 --> 00:02:05,680 Speaker 1: there's a couple of things that drive bitcoins value, right 37 00:02:05,680 --> 00:02:09,880 Speaker 1: and it's obviously not traditional fundamental valuation technique. That's true 38 00:02:09,880 --> 00:02:12,360 Speaker 1: of other assets and digital assets, but not bitcoin. But 39 00:02:12,400 --> 00:02:14,560 Speaker 1: what we know about bitcoin specifically is there's a couple 40 00:02:14,600 --> 00:02:16,560 Speaker 1: of factors that have driven you have low rates and 41 00:02:16,600 --> 00:02:19,360 Speaker 1: the declining dollar that's still very much in play. Nothing's 42 00:02:19,400 --> 00:02:22,720 Speaker 1: changing there. Therefore, this should still be a pretty strong 43 00:02:22,760 --> 00:02:26,280 Speaker 1: macro asset. You have institutional money entering the space. Nothing's 44 00:02:26,360 --> 00:02:28,600 Speaker 1: changed there. We have, you know, tons of investors coming 45 00:02:28,600 --> 00:02:30,440 Speaker 1: into our funds. Other funds are saying the same thing. 46 00:02:30,800 --> 00:02:33,560 Speaker 1: Money is pouring in everywhere you look into this asset 47 00:02:33,600 --> 00:02:35,880 Speaker 1: class because of what I've said before, low rates and 48 00:02:35,919 --> 00:02:37,400 Speaker 1: a low dollar, right where else are you going to 49 00:02:37,480 --> 00:02:39,960 Speaker 1: go to invest your money? Um? You know, really the 50 00:02:39,960 --> 00:02:42,840 Speaker 1: only thing has changed is recent narratives. You know, if 51 00:02:42,880 --> 00:02:45,240 Speaker 1: you are going to watch bitcoin go up from ten 52 00:02:45,280 --> 00:02:48,799 Speaker 1: thousand to sixty thousand every time Elon Musk tweets positively, well, 53 00:02:48,840 --> 00:02:51,519 Speaker 1: then by definition when him and other corporations pull out, 54 00:02:51,800 --> 00:02:53,960 Speaker 1: that's going to have a negative effect as well. So 55 00:02:54,080 --> 00:02:56,320 Speaker 1: I think the volatility is based on you know, a 56 00:02:56,400 --> 00:03:01,040 Speaker 1: lack of UH conviction around UH the path that it 57 00:03:01,080 --> 00:03:03,520 Speaker 1: takes to get higher. But ultimately bitcoins of binary bet 58 00:03:03,520 --> 00:03:05,680 Speaker 1: it's either going to be worth a lot more if 59 00:03:05,680 --> 00:03:07,880 Speaker 1: this is adopted as a true store of value and currency, 60 00:03:08,120 --> 00:03:09,680 Speaker 1: or it's gonna be worth a lot less if it doesn't. 61 00:03:09,720 --> 00:03:12,320 Speaker 1: And everything in between is there's a lot of fun 62 00:03:12,360 --> 00:03:15,799 Speaker 1: to trade, but not necessarily indicative of the end result. Jeff, 63 00:03:15,800 --> 00:03:18,600 Speaker 1: you say money is pouring into this asset class, where's 64 00:03:18,639 --> 00:03:21,079 Speaker 1: the money coming from? Is a retail Are you seeing 65 00:03:21,120 --> 00:03:26,520 Speaker 1: institutional buy in? Where are you seeing it? Well, institutional buying, 66 00:03:26,840 --> 00:03:30,079 Speaker 1: you know, in the traditional investing world, typically means your 67 00:03:30,080 --> 00:03:33,280 Speaker 1: asset allocators, right, your pensions, your endowments, your sovereign wealth. 68 00:03:33,720 --> 00:03:36,080 Speaker 1: It's not really coming from there yet. I think there's 69 00:03:36,080 --> 00:03:39,000 Speaker 1: a lot of complating the word institutional here in the 70 00:03:39,000 --> 00:03:41,080 Speaker 1: market because all of a sudden hedge funds got involved, 71 00:03:41,120 --> 00:03:43,760 Speaker 1: and all of a sudden corporate treasurers got involved. The 72 00:03:43,800 --> 00:03:46,800 Speaker 1: reality is most of the buying power of bitcoin is 73 00:03:46,840 --> 00:03:50,960 Speaker 1: still family offices, high net worth, you know, not necessarily 74 00:03:51,000 --> 00:03:53,320 Speaker 1: in the hedge fund itself, but generally the owners of 75 00:03:53,320 --> 00:03:56,160 Speaker 1: a hedge fund in their own personal accounts. There is 76 00:03:56,160 --> 00:03:59,520 Speaker 1: definitely real money coming in from the institutional world, but 77 00:03:59,560 --> 00:04:03,839 Speaker 1: it's not the traditional institutional asset allocators yet. What what's 78 00:04:03,840 --> 00:04:07,800 Speaker 1: going to change that? Um? Quite frankly, I'm not sure 79 00:04:07,880 --> 00:04:10,960 Speaker 1: it ever does. Uh. You know, the institutional investors that 80 00:04:11,000 --> 00:04:13,200 Speaker 1: we speak to the pensions and down with sovereign walls, etcetera. 81 00:04:13,240 --> 00:04:15,280 Speaker 1: They're more interested in the rest of the asset class. Uh. 82 00:04:15,360 --> 00:04:17,560 Speaker 1: You know a lot of times I talk about digital 83 00:04:17,640 --> 00:04:19,680 Speaker 1: assets the same way I talk about et s. Right, 84 00:04:19,720 --> 00:04:22,039 Speaker 1: you would never say, hey, I'm an EPF investor. You say, well, 85 00:04:22,080 --> 00:04:24,520 Speaker 1: what kind of ETF investor? Are you invested in healthcare 86 00:04:24,560 --> 00:04:27,360 Speaker 1: stocks or you know, bond EPs, or are you invested 87 00:04:27,400 --> 00:04:29,800 Speaker 1: in gold ets? Right? The e t F itself is 88 00:04:29,839 --> 00:04:32,120 Speaker 1: just a structure, and what's in the structure is what's 89 00:04:32,160 --> 00:04:34,280 Speaker 1: relevant from an investing standpoint, And the same thing is 90 00:04:34,279 --> 00:04:36,839 Speaker 1: happening with digital assets. We have different types of digital assets. 91 00:04:36,880 --> 00:04:39,920 Speaker 1: Some are asset backed, some have revenue pass throughs, some 92 00:04:40,000 --> 00:04:42,800 Speaker 1: are more like technology protocols and platforms, and others are 93 00:04:42,800 --> 00:04:46,279 Speaker 1: cryptocurrency and money like bitcoins. I think the institutional investors 94 00:04:46,400 --> 00:04:50,080 Speaker 1: largely gravitate towards the ones that have real fundamental analysis 95 00:04:50,120 --> 00:04:52,360 Speaker 1: attached to them, which is the asset back tokens and 96 00:04:52,440 --> 00:04:56,320 Speaker 1: the companies with real revenue and cash flows. I get 97 00:04:56,440 --> 00:05:01,160 Speaker 1: asset back tokens, I get um, but bitcoin is the 98 00:05:01,200 --> 00:05:04,400 Speaker 1: only one where the token really has become a store 99 00:05:04,440 --> 00:05:08,880 Speaker 1: of value. Um. You know that's not asset backed. The 100 00:05:08,960 --> 00:05:15,080 Speaker 1: other interesting Uh, crypto plays like Athereum have a great platform, 101 00:05:15,320 --> 00:05:17,320 Speaker 1: but I don't see any reason to buy the token. 102 00:05:18,960 --> 00:05:20,640 Speaker 1: I think that was true historically, and I would have 103 00:05:20,640 --> 00:05:22,920 Speaker 1: agreed with you two years ago. But what's happening now 104 00:05:23,120 --> 00:05:28,039 Speaker 1: is Ethereum is an ecosystem that other applications are building upon. 105 00:05:28,160 --> 00:05:30,240 Speaker 1: Right in some way, thethereum is the app store, and 106 00:05:30,279 --> 00:05:32,200 Speaker 1: all the other tokens are the apps that are built 107 00:05:32,200 --> 00:05:34,640 Speaker 1: in the app store. Uh. You know how does the 108 00:05:34,680 --> 00:05:37,360 Speaker 1: app store make money? It makes money on the transactions 109 00:05:37,360 --> 00:05:39,520 Speaker 1: that are happening inside of that app store. And that's 110 00:05:39,560 --> 00:05:42,760 Speaker 1: basically what ethereum is doing. To date. Uh, the token 111 00:05:42,839 --> 00:05:45,279 Speaker 1: has accrued none of that economic value. But with a 112 00:05:45,320 --> 00:05:47,760 Speaker 1: new proposal that is going into place called e I 113 00:05:47,800 --> 00:05:51,280 Speaker 1: Pine and it's shipped from proof of work to proof mistake, 114 00:05:51,520 --> 00:05:53,479 Speaker 1: there actually are going to be real cash flows that 115 00:05:53,520 --> 00:05:56,039 Speaker 1: eventually a crew back to the token holders. So it 116 00:05:56,120 --> 00:05:57,839 Speaker 1: is changing a little bit. And that's what's so interesting 117 00:05:57,880 --> 00:06:00,880 Speaker 1: about this asset class is, Uh, these tokens can be 118 00:06:00,960 --> 00:06:03,960 Speaker 1: representative of one thing on day one and ultimately morphin 119 00:06:04,120 --> 00:06:09,400 Speaker 1: change throughout the evolution of of the investment um that 120 00:06:09,560 --> 00:06:11,960 Speaker 1: the you know, the theorium itself is still kind of 121 00:06:11,960 --> 00:06:14,360 Speaker 1: difficult for traditional investors to get their hands around because 122 00:06:14,400 --> 00:06:17,719 Speaker 1: it is this like broader GDP ecosystem thing. But the 123 00:06:17,720 --> 00:06:21,239 Speaker 1: applications that are built on top of ethereum are generally 124 00:06:21,240 --> 00:06:23,400 Speaker 1: real companies with real revenues and real cash flows, and 125 00:06:23,400 --> 00:06:25,720 Speaker 1: the tokens can be modeled using a DCF analysis or 126 00:06:25,760 --> 00:06:27,400 Speaker 1: a dividend field model, and that's what we focus on 127 00:06:27,400 --> 00:06:29,080 Speaker 1: an ARCA, and that's what a lot of institutional investors 128 00:06:29,080 --> 00:06:32,200 Speaker 1: are focused on as well. And that includes defy uh, 129 00:06:32,240 --> 00:06:34,719 Speaker 1: some gaming assets and a lot of other ones that 130 00:06:34,720 --> 00:06:36,400 Speaker 1: are that are coming down the pikes in the future 131 00:06:36,440 --> 00:06:39,320 Speaker 1: as well. All right, Jeff, just real quickly thirty seconds, 132 00:06:39,360 --> 00:06:42,240 Speaker 1: what's the next mile post that you're looking for? As 133 00:06:42,279 --> 00:06:47,920 Speaker 1: this market, this asset class continues to develop and evolved. Uh. 134 00:06:48,200 --> 00:06:51,720 Speaker 1: For min milestone is is education um doing more things 135 00:06:51,720 --> 00:06:54,640 Speaker 1: like what you're doing in others where investors can understand 136 00:06:54,640 --> 00:06:57,479 Speaker 1: that cryptocurrency is not the right term. Cryptocurrency is a 137 00:06:57,560 --> 00:07:00,880 Speaker 1: very small subset of the market, but these other assets 138 00:07:00,880 --> 00:07:03,440 Speaker 1: are really more like quasi equity, and ultimately, I think 139 00:07:03,480 --> 00:07:06,160 Speaker 1: digital assets will end up in every company's capital structure 140 00:07:06,240 --> 00:07:09,520 Speaker 1: from you know, Netflix, the Starbucks, see delta over time, 141 00:07:09,840 --> 00:07:12,320 Speaker 1: and once you start to see the companies adopted and 142 00:07:12,320 --> 00:07:15,440 Speaker 1: you see investors understand what these assets really are, you know, 143 00:07:15,480 --> 00:07:19,440 Speaker 1: being great coordination mechanisms and growth mechanisms for companies. I 144 00:07:19,520 --> 00:07:21,600 Speaker 1: think the Narratabile change, and we'll be talking less about 145 00:07:21,640 --> 00:07:24,520 Speaker 1: bitcoin and more about the cash flow producing entities that 146 00:07:24,600 --> 00:07:28,000 Speaker 1: use a digital asset to represent that growth. Alright, very 147 00:07:28,040 --> 00:07:30,320 Speaker 1: interesting stuff, Jeff, thanks very much for talking to us. 148 00:07:30,920 --> 00:07:34,440 Speaker 1: Always a pleasure. Jeff Dorman is the chief investment officer 149 00:07:34,720 --> 00:07:38,560 Speaker 1: ARCA talking to us about how was about to say cryptocurrency, 150 00:07:38,640 --> 00:07:42,560 Speaker 1: digital assets. I think digital digital assets. They're looking at 151 00:07:42,560 --> 00:07:45,360 Speaker 1: one of them. Bitcoin just slipping under thirty six thousand, 152 00:07:45,640 --> 00:07:49,240 Speaker 1: barely thirty five thousand, nine sixty four dollars and ninety 153 00:07:49,360 --> 00:07:52,960 Speaker 1: three cents Ether trading for two thousand, seven hundred seventy eight. 154 00:07:53,080 --> 00:08:00,640 Speaker 1: This is Bloomberg. Now we're bringing Scott Kimball Portia, manager 155 00:08:00,800 --> 00:08:03,800 Speaker 1: of the Strategic Income Fund and co head of US 156 00:08:03,840 --> 00:08:08,200 Speaker 1: fixed Income at BEMO Global Asset Management. Scott, let's talk 157 00:08:08,240 --> 00:08:10,440 Speaker 1: first about what we saw happen on Friday. It was 158 00:08:10,440 --> 00:08:13,400 Speaker 1: pretty interesting with the jobs number. It was a miss, 159 00:08:13,440 --> 00:08:15,200 Speaker 1: but still I guess a pretty good number. More than 160 00:08:15,200 --> 00:08:19,040 Speaker 1: five thousand people got jobs in this economy as we 161 00:08:19,120 --> 00:08:24,240 Speaker 1: as we reopened and we saw treasuries yields just dropped. 162 00:08:24,760 --> 00:08:27,480 Speaker 1: I think it was five six basis points down to seven. 163 00:08:27,520 --> 00:08:31,520 Speaker 1: We're trading there right now. M. Does that make sense 164 00:08:31,520 --> 00:08:35,640 Speaker 1: to you, Yeah, good morning. I think it does for 165 00:08:35,679 --> 00:08:39,319 Speaker 1: a few reasons. I think that's what the jobs report signals. 166 00:08:39,360 --> 00:08:42,160 Speaker 1: First and foremost is that we are transitioning out of 167 00:08:42,200 --> 00:08:46,600 Speaker 1: the you know, the post reopening boom into a uh 168 00:08:46,640 --> 00:08:50,200 Speaker 1: an economic environment where more and more of the US's 169 00:08:50,400 --> 00:08:53,320 Speaker 1: economies own inertia is gonna have to take over, and 170 00:08:53,320 --> 00:08:55,840 Speaker 1: that growth potential and growth output is going to have 171 00:08:55,960 --> 00:09:00,760 Speaker 1: to be really driven by the underlying economic fundamentals uh 172 00:09:00,800 --> 00:09:03,400 Speaker 1: post that that big boom in the recovery, which I 173 00:09:03,440 --> 00:09:05,880 Speaker 1: think is what you saw in the outcome of the 174 00:09:06,440 --> 00:09:09,760 Speaker 1: jobs report. Uh you know, the estimates versus the the 175 00:09:09,800 --> 00:09:13,000 Speaker 1: actual print. That's not a typical. That's pretty common as 176 00:09:13,000 --> 00:09:15,800 Speaker 1: you get, you know, through these these handoff cycles where 177 00:09:16,200 --> 00:09:18,439 Speaker 1: you may not be directly in line with the number, 178 00:09:18,480 --> 00:09:22,880 Speaker 1: but the directional trend still remains pretty favorable. Treasuries, however, 179 00:09:23,280 --> 00:09:26,040 Speaker 1: probably took that as a little bit of a uh 180 00:09:26,080 --> 00:09:27,559 Speaker 1: you know, if you've seen the U seal curb be 181 00:09:27,720 --> 00:09:30,400 Speaker 1: very steep, probably taking off a little bit of the 182 00:09:30,440 --> 00:09:33,400 Speaker 1: steepness to reflect the fact that, you know, things like 183 00:09:33,520 --> 00:09:36,880 Speaker 1: inflation still have some upside risk, but the ability to 184 00:09:36,880 --> 00:09:40,959 Speaker 1: really punch through into a an explosively higher inflationary environment 185 00:09:41,160 --> 00:09:44,680 Speaker 1: is probably being a little bit tempered by this, uh 186 00:09:44,760 --> 00:09:47,200 Speaker 1: you know, this this transition in the economy, if you will. 187 00:09:47,760 --> 00:09:49,800 Speaker 1: That's kind of where I wanted to go, Scott in 188 00:09:49,880 --> 00:09:53,400 Speaker 1: terms of the discussion about inflationary concerns into this market. 189 00:09:53,520 --> 00:09:55,640 Speaker 1: You know, obviously two camps, one being the Federal Reserve 190 00:09:55,720 --> 00:09:58,400 Speaker 1: camp where you know, the signs of inflation that we 191 00:09:58,440 --> 00:10:00,559 Speaker 1: are seeing or transitory, and the others, hey, it might 192 00:10:00,559 --> 00:10:04,839 Speaker 1: be more systemic than that. Where do you fall so 193 00:10:05,720 --> 00:10:08,199 Speaker 1: perfectly down the middle? Because I think the FED has 194 00:10:08,240 --> 00:10:12,080 Speaker 1: a lot of credibility on the inflationary front. They've they've 195 00:10:12,120 --> 00:10:15,040 Speaker 1: been telling us for over a decade that inflationary pressures 196 00:10:15,080 --> 00:10:18,079 Speaker 1: are transitory and they've been correct, and that's a long 197 00:10:18,200 --> 00:10:20,960 Speaker 1: enough streak to be more than random. So I think 198 00:10:20,960 --> 00:10:24,120 Speaker 1: that the FED has the pulse of the inflationary pressures 199 00:10:24,760 --> 00:10:27,560 Speaker 1: pretty well contained, are pretty well, pretty well contained and 200 00:10:27,559 --> 00:10:31,360 Speaker 1: pretty well figured out, except this last couple of rounds 201 00:10:31,400 --> 00:10:33,200 Speaker 1: there has been a little bit of a little bit 202 00:10:33,200 --> 00:10:36,880 Speaker 1: of whack a mole and that everywhere inflation has moved higher, 203 00:10:36,960 --> 00:10:39,320 Speaker 1: it's sort of popped up in different parts of the 204 00:10:39,320 --> 00:10:42,320 Speaker 1: CPI measures. So for instance, the most recent read on 205 00:10:42,480 --> 00:10:46,079 Speaker 1: you know, used autos. You know, that's something that historically 206 00:10:46,160 --> 00:10:49,120 Speaker 1: you look at used autos contribution to inflation, It tends 207 00:10:49,120 --> 00:10:54,040 Speaker 1: to attempts to spike and and dissipate pretty regularly. Uh. 208 00:10:54,120 --> 00:10:56,360 Speaker 1: And you can really explain why in our case, you know, 209 00:10:56,440 --> 00:10:59,120 Speaker 1: with the pandemic we had, you know, auto plants were 210 00:10:59,240 --> 00:11:02,720 Speaker 1: restricted or out put was was curtailed UM, and people 211 00:11:02,760 --> 00:11:05,080 Speaker 1: were being a little more conscious of where they where 212 00:11:05,080 --> 00:11:08,360 Speaker 1: they spent money, so replacement vehicles were driven more towards 213 00:11:08,360 --> 00:11:11,440 Speaker 1: the used market. So naturally we've seen some we saw 214 00:11:11,480 --> 00:11:15,319 Speaker 1: some some booming prices there in in uh in used autos. 215 00:11:15,360 --> 00:11:17,760 Speaker 1: But how sustainable is that going to be? That gets 216 00:11:17,800 --> 00:11:21,560 Speaker 1: back to the Fed's point. Uh. I think our position 217 00:11:21,600 --> 00:11:23,880 Speaker 1: has been that there is a directional case to be 218 00:11:23,960 --> 00:11:27,200 Speaker 1: made for inflation to continue to creve higher UM. But 219 00:11:27,720 --> 00:11:31,480 Speaker 1: it's bumping into some things that I think will constrain it. 220 00:11:31,559 --> 00:11:35,480 Speaker 1: So for instance, oil prices most prominently, Uh, you know, 221 00:11:35,480 --> 00:11:37,800 Speaker 1: we're coming up on seven dollars of barrel as we 222 00:11:37,880 --> 00:11:40,080 Speaker 1: model things out. If we break through that and you 223 00:11:40,080 --> 00:11:45,000 Speaker 1: start getting a barrel, you know, that does certainly put 224 00:11:45,080 --> 00:11:48,760 Speaker 1: upward price pressures, but the ability to pass through those 225 00:11:48,760 --> 00:11:51,640 Speaker 1: pressures starts to roll over and you start to see 226 00:11:51,679 --> 00:11:55,760 Speaker 1: that consumption will adjust downward. So there's indicator indicators like 227 00:11:55,800 --> 00:11:59,080 Speaker 1: that at that point to mechanisms where yes, inflation can 228 00:11:59,160 --> 00:12:02,040 Speaker 1: press higher, but the economic output starts to suffer, which 229 00:12:02,080 --> 00:12:05,840 Speaker 1: then can sort of constrains it from running away. Is it? 230 00:12:05,880 --> 00:12:09,320 Speaker 1: Is it consensus though, that we start to taper at 231 00:12:09,320 --> 00:12:12,199 Speaker 1: the end of this year, um beginning of next year, 232 00:12:12,240 --> 00:12:14,559 Speaker 1: then start to raise rates and twenty two beginning of 233 00:12:17,360 --> 00:12:20,440 Speaker 1: That's definitely the way the futures market has has has 234 00:12:20,720 --> 00:12:22,640 Speaker 1: that's definitely out the I guess the path of the 235 00:12:22,640 --> 00:12:26,360 Speaker 1: output the futures market has been favoring. UM. I think 236 00:12:26,400 --> 00:12:29,360 Speaker 1: it's probably going to be difficult to really address the 237 00:12:29,440 --> 00:12:32,840 Speaker 1: right front. Um. You know, the FED has you know, 238 00:12:33,280 --> 00:12:39,520 Speaker 1: between both tapering and transitioning interest rate policy in both cases, 239 00:12:39,520 --> 00:12:43,160 Speaker 1: between the taper tantrum and whatever occurred when Pal tried 240 00:12:43,160 --> 00:12:46,880 Speaker 1: to raise rates, whatever we want to label that UM. 241 00:12:46,920 --> 00:12:49,760 Speaker 1: In both cases, the market response, in the economic response 242 00:12:50,360 --> 00:12:52,920 Speaker 1: was pretty clear that this version of the U S 243 00:12:52,960 --> 00:12:55,640 Speaker 1: economy is going to be a little more difficult than 244 00:12:55,679 --> 00:12:59,760 Speaker 1: pass cycles to have those meaningful breakthroughs uh in in 245 00:13:00,360 --> 00:13:03,760 Speaker 1: in uh in monetary policy or so it's gonna be 246 00:13:04,640 --> 00:13:08,800 Speaker 1: our our expectation that uh capering is probably going to 247 00:13:08,880 --> 00:13:11,400 Speaker 1: take place. I think that there's definitely efficacy for that 248 00:13:11,440 --> 00:13:14,160 Speaker 1: in the economy. You're through the crisis period. As far 249 00:13:14,200 --> 00:13:18,760 Speaker 1: as transitioning monetary policy to let's say a rising rate environment. 250 00:13:19,200 --> 00:13:22,560 Speaker 1: UM wouldn't be surprised if that tail continues to push 251 00:13:22,600 --> 00:13:25,040 Speaker 1: its way down the road a little bit. Hey, Scott, 252 00:13:25,080 --> 00:13:27,480 Speaker 1: thanks so much for joining us. We really appreciate getting 253 00:13:27,520 --> 00:13:30,960 Speaker 1: your thoughts and perspective on the fixed income market. Scott Kimball, 254 00:13:31,240 --> 00:13:34,760 Speaker 1: portfolio manager of the Strategic Income Fund and co head 255 00:13:34,920 --> 00:13:38,800 Speaker 1: of US fixed Income for Bibo BIMO, a global asset 256 00:13:38,880 --> 00:13:41,480 Speaker 1: of management, getting his thoughts on fixed income market again. 257 00:13:41,520 --> 00:13:44,960 Speaker 1: The ten year Treasury remains down at one point five 258 00:13:45,040 --> 00:13:50,839 Speaker 1: seven percent. All right, the Bloomberg Big Take story today, 259 00:13:50,840 --> 00:13:53,920 Speaker 1: it's just fascinating people are finding those who took part 260 00:13:54,000 --> 00:13:57,280 Speaker 1: in the January six Capital siege via social media and 261 00:13:57,320 --> 00:13:59,840 Speaker 1: are helping federal officers arrest them. We're seeing it all 262 00:13:59,840 --> 00:14:02,880 Speaker 1: through about our social media feeds. David Yaffee Belny did 263 00:14:02,880 --> 00:14:06,439 Speaker 1: some work on this. He's a legal reporter for Bloomberg News. David, 264 00:14:06,480 --> 00:14:08,760 Speaker 1: it seems like, you know, everybody in the social media 265 00:14:08,840 --> 00:14:12,640 Speaker 1: feeds are seeing you know, stories and of of of 266 00:14:12,640 --> 00:14:15,719 Speaker 1: people that have been identified as taking part in the 267 00:14:15,920 --> 00:14:20,960 Speaker 1: Capital siege. How wide spread is that, um? So, you know, 268 00:14:21,040 --> 00:14:23,680 Speaker 1: right after the siege on January six, there was kind 269 00:14:23,720 --> 00:14:26,520 Speaker 1: of a wave of activism from people who just regular 270 00:14:26,560 --> 00:14:28,960 Speaker 1: people watching the footage at home who were outraged at 271 00:14:29,000 --> 00:14:31,520 Speaker 1: what had happened and wanted to do something about it, um, 272 00:14:31,720 --> 00:14:34,440 Speaker 1: find some way to bring the perpetrators to justice. And 273 00:14:34,480 --> 00:14:38,000 Speaker 1: so you had this kind of initial rush to identify 274 00:14:38,280 --> 00:14:41,240 Speaker 1: people who were there that was initially focused on some 275 00:14:41,320 --> 00:14:43,480 Speaker 1: of the kind of most most prominent people in the 276 00:14:43,560 --> 00:14:46,160 Speaker 1: in the photos and videos. Um, you know, the man 277 00:14:46,240 --> 00:14:49,000 Speaker 1: with his feet up on Nancy closy desk, or the 278 00:14:49,040 --> 00:14:52,160 Speaker 1: guy and the kind of animal head dress who's walking 279 00:14:52,160 --> 00:14:55,000 Speaker 1: through the capitol, and and and that you know, there 280 00:14:55,000 --> 00:14:57,200 Speaker 1: were you know, thousands of people all over social media 281 00:14:57,240 --> 00:15:00,240 Speaker 1: sort of participating in that in that effort, and it's 282 00:15:00,280 --> 00:15:03,080 Speaker 1: sort of evolved in an interesting way since then. We're 283 00:15:03,120 --> 00:15:06,560 Speaker 1: now kind of trying to track down, um, sort of 284 00:15:06,640 --> 00:15:09,280 Speaker 1: less well known participants in the riot and pulled and 285 00:15:09,320 --> 00:15:11,600 Speaker 1: sort of the background with some of those photos and 286 00:15:11,600 --> 00:15:13,960 Speaker 1: and and try to really get a comprehensive sense thats 287 00:15:13,960 --> 00:15:18,840 Speaker 1: who was involved. So you got one guy that the 288 00:15:18,960 --> 00:15:21,320 Speaker 1: lead guy. I love his picture. He looks kind of 289 00:15:21,320 --> 00:15:25,640 Speaker 1: like Indiana Jones. Um who's helping to find out who 290 00:15:25,680 --> 00:15:28,760 Speaker 1: these people are? Um. I guess he's a guy who 291 00:15:28,760 --> 00:15:31,120 Speaker 1: doesn't have a job, so he has the ability to 292 00:15:31,160 --> 00:15:34,200 Speaker 1: spend the time to spend forty hours a week on 293 00:15:34,240 --> 00:15:38,160 Speaker 1: the internet looking for for these dudes. Yeah. The way, 294 00:15:38,280 --> 00:15:39,800 Speaker 1: the way he put it to me is that he 295 00:15:39,880 --> 00:15:41,840 Speaker 1: was living at home with his girlfriend and and she 296 00:15:41,840 --> 00:15:44,280 Speaker 1: would log onto her computer to do her actual job, 297 00:15:44,320 --> 00:15:46,360 Speaker 1: and he would log onto his computer and do his 298 00:15:46,480 --> 00:15:49,320 Speaker 1: kind of sedition hunting gig for for a few months. 299 00:15:49,320 --> 00:15:51,960 Speaker 1: You know. Uh, Like so many people, he found it 300 00:15:52,280 --> 00:15:54,720 Speaker 1: difficult to get consistent work during the pandemic. He's an 301 00:15:54,720 --> 00:15:58,800 Speaker 1: actor in Canada, and those sorts of opportunities were drawing up. Um, 302 00:15:58,840 --> 00:16:00,960 Speaker 1: and so yeah, it was really a combination of kind 303 00:16:00,960 --> 00:16:04,800 Speaker 1: of curiosity and pandemic induced boredom that sort of motivated 304 00:16:04,880 --> 00:16:07,720 Speaker 1: him to get involved with this. And he just started 305 00:16:07,760 --> 00:16:10,480 Speaker 1: spending you know, hours and hours a day pouring through 306 00:16:10,600 --> 00:16:14,960 Speaker 1: photos and videos trying to kind of catalog images where 307 00:16:15,000 --> 00:16:17,400 Speaker 1: you can see the same person multiple times, to sort 308 00:16:17,400 --> 00:16:19,960 Speaker 1: of put together like a comprehensive account of all the 309 00:16:20,000 --> 00:16:24,760 Speaker 1: evidence of a particular individuals involvement. And eventually that allowed 310 00:16:24,840 --> 00:16:29,040 Speaker 1: him to identify somebody, um who's who was charged by 311 00:16:29,080 --> 00:16:32,760 Speaker 1: the FBI, UM and and his work was was cited 312 00:16:32,800 --> 00:16:37,440 Speaker 1: in the arrest affidavit, UM, sort of underlying that that charge, David, 313 00:16:37,440 --> 00:16:40,880 Speaker 1: don't we have a bunch of like n Essay blackbriar 314 00:16:41,080 --> 00:16:45,640 Speaker 1: nerds who can do this stuff in their sleep? Um, 315 00:16:45,680 --> 00:16:47,920 Speaker 1: you know, in in theory we do. And And look, 316 00:16:47,960 --> 00:16:51,000 Speaker 1: the federal investigation has made a lot of progress over 317 00:16:51,040 --> 00:16:53,520 Speaker 1: the past few months. Nearly five people have been arrested. 318 00:16:53,560 --> 00:16:55,520 Speaker 1: And that's not all because of the work of these 319 00:16:55,520 --> 00:16:58,360 Speaker 1: sort of online tradition hunters, but there was there was 320 00:16:58,440 --> 00:17:02,320 Speaker 1: just so much footage UM and so many people involved 321 00:17:02,360 --> 00:17:05,760 Speaker 1: in such pressure to move quickly on this um that 322 00:17:05,840 --> 00:17:07,840 Speaker 1: I think the government was appreciative of the of the 323 00:17:07,840 --> 00:17:10,080 Speaker 1: public's help. Um, you know, and I when I talked 324 00:17:10,119 --> 00:17:12,600 Speaker 1: to the FBI about this, you know, they they said, 325 00:17:12,600 --> 00:17:15,600 Speaker 1: you know, in dozens and dozens of cases, these sorts 326 00:17:15,600 --> 00:17:18,960 Speaker 1: of tips have proved helpful, um, and they're asking for 327 00:17:19,040 --> 00:17:21,320 Speaker 1: more help as they, you know, continue to try to 328 00:17:21,440 --> 00:17:24,040 Speaker 1: round up you know, hundreds more people who were involved 329 00:17:24,040 --> 00:17:27,760 Speaker 1: in the riot and haven't been brought to justice so far. So, 330 00:17:28,240 --> 00:17:30,640 Speaker 1: I know, David, the Senate Republicans recently blocked a bill 331 00:17:30,680 --> 00:17:34,879 Speaker 1: in Congress to create an independent September eleven style commissioned 332 00:17:34,880 --> 00:17:39,080 Speaker 1: to investigate the riots. So does that mean we're you know, 333 00:17:39,400 --> 00:17:43,040 Speaker 1: we're basically just relying on uh, the FBI and some 334 00:17:43,119 --> 00:17:46,240 Speaker 1: of these amateurs to kind of bring people to justice 335 00:17:46,280 --> 00:17:49,560 Speaker 1: as it were, UM to it to an extent, yes, 336 00:17:49,600 --> 00:17:52,800 Speaker 1: I mean, you know, the the the investigations presumably going 337 00:17:52,880 --> 00:17:56,000 Speaker 1: to succeed in putting some of these people in prison. 338 00:17:56,160 --> 00:17:59,160 Speaker 1: But there are broader questions about what happened on January six, 339 00:17:59,240 --> 00:18:01,840 Speaker 1: you know, the extent to which far right groups were 340 00:18:01,840 --> 00:18:05,680 Speaker 1: coordinating with each other, um, you know, public figures who 341 00:18:05,760 --> 00:18:08,200 Speaker 1: may have been present or may have helped people behind 342 00:18:08,240 --> 00:18:10,359 Speaker 1: the fiends and what they're role was there. There's these 343 00:18:10,400 --> 00:18:13,720 Speaker 1: sort of broader historical questions that the investigation might not 344 00:18:13,840 --> 00:18:17,240 Speaker 1: ultimately answer, in which you know, people had hoped some 345 00:18:17,280 --> 00:18:20,639 Speaker 1: sort of bipartisan report would explore. And so one of 346 00:18:20,680 --> 00:18:23,359 Speaker 1: the things that's motivating these sedition hunters now is to 347 00:18:23,400 --> 00:18:25,760 Speaker 1: try to kind of ship away at some of those, uh, 348 00:18:25,880 --> 00:18:29,080 Speaker 1: those questions using the sort of open source resources that 349 00:18:29,400 --> 00:18:32,240 Speaker 1: they have to hand, um and really kind of fill 350 00:18:32,320 --> 00:18:35,119 Speaker 1: in where we're sort of Congress is sort of not 351 00:18:35,160 --> 00:18:40,920 Speaker 1: taking action. It's ironic that both groups seem to use discord, right. 352 00:18:41,000 --> 00:18:43,520 Speaker 1: I Mean, you've got the Q and On people on 353 00:18:43,600 --> 00:18:45,800 Speaker 1: there as well as the sedition hunters. Is there a 354 00:18:45,920 --> 00:18:50,000 Speaker 1: risk that, you know, if the FBI keeps on begging 355 00:18:50,080 --> 00:18:52,479 Speaker 1: if you see something, say something, you know, watch your 356 00:18:52,520 --> 00:18:56,120 Speaker 1: neighbor and give us a call, do we risk some 357 00:18:56,240 --> 00:19:01,240 Speaker 1: kind of East German Stazi surveillance state culture. I mean, 358 00:19:01,240 --> 00:19:03,479 Speaker 1: I think that's definitely a concern. I mean, some of 359 00:19:03,520 --> 00:19:08,080 Speaker 1: these amateur fisition hunters are using facial recognition technology to 360 00:19:08,160 --> 00:19:10,359 Speaker 1: try to to try to target people who are at 361 00:19:10,400 --> 00:19:13,399 Speaker 1: the capital on January six, and the fact that that 362 00:19:13,480 --> 00:19:16,399 Speaker 1: sort of technology is freely available to members of the 363 00:19:16,400 --> 00:19:18,480 Speaker 1: public and that you know, anybody with you know, some 364 00:19:18,520 --> 00:19:21,720 Speaker 1: sort of software engineering background can kind of put together 365 00:19:21,800 --> 00:19:24,720 Speaker 1: relatively quickly a kind of facial recognition due to me 366 00:19:25,440 --> 00:19:28,960 Speaker 1: is definitely is definitely troubling. And these all sorts of 367 00:19:28,960 --> 00:19:32,440 Speaker 1: civil liberties concerns or they could make a mistake, David, 368 00:19:32,480 --> 00:19:36,840 Speaker 1: they could get someone innocent in hot water. Yeah. Absolutely, 369 00:19:36,880 --> 00:19:39,320 Speaker 1: and we've i mean, we've seen that in the aftermath 370 00:19:39,359 --> 00:19:42,040 Speaker 1: of January six, that people have been identified, you know, 371 00:19:42,080 --> 00:19:45,639 Speaker 1: and named publicly who weren't actually actually there. Now, to 372 00:19:45,720 --> 00:19:48,200 Speaker 1: their credit, a lot of the groups that are coordinating 373 00:19:48,240 --> 00:19:51,359 Speaker 1: some of the sedition hunting activity are going to great 374 00:19:51,440 --> 00:19:53,840 Speaker 1: lengths to prevent that sort of thing from happening. They're 375 00:19:53,920 --> 00:19:57,240 Speaker 1: urging their followers never to publicly identify somebody by name, 376 00:19:57,640 --> 00:20:00,280 Speaker 1: and always to submit that information to the FBI, which 377 00:20:00,320 --> 00:20:03,040 Speaker 1: can then go and verify those tips, you know, UM 378 00:20:03,240 --> 00:20:05,960 Speaker 1: through its sort of more sophisticated means. And you know, 379 00:20:06,000 --> 00:20:08,560 Speaker 1: you definitely see in some SBI RST after dated Oh 380 00:20:08,640 --> 00:20:10,840 Speaker 1: you know, we've got ten tips about this case, and 381 00:20:10,960 --> 00:20:12,919 Speaker 1: eight of them were wrong, but you know, you're the 382 00:20:12,960 --> 00:20:14,920 Speaker 1: two that turned out to be correct, and that's how 383 00:20:14,960 --> 00:20:19,000 Speaker 1: we arrested this person. UM, so you know, I think 384 00:20:19,040 --> 00:20:21,280 Speaker 1: I think that these groups are conscious of that risk 385 00:20:21,359 --> 00:20:23,760 Speaker 1: and are trying to avoid making mistakes. But of course 386 00:20:23,800 --> 00:20:26,000 Speaker 1: there's no way that you can control just thousands of 387 00:20:26,040 --> 00:20:31,800 Speaker 1: people on the Internet. Really interesting story. I love the 388 00:20:31,800 --> 00:20:36,800 Speaker 1: big take. Um it's such a cool uh new thing 389 00:20:36,840 --> 00:20:39,720 Speaker 1: that we have on the Bloomberg And David, your your 390 00:20:39,760 --> 00:20:41,960 Speaker 1: story is awesome. I love also the layout. It's really 391 00:20:41,960 --> 00:20:45,200 Speaker 1: well done. So thanks very much for joining us on 392 00:20:45,280 --> 00:20:48,480 Speaker 1: this one, David, Daffy Bellini talking to us about the 393 00:20:48,520 --> 00:20:53,480 Speaker 1: amateur Internet sleuths who are trying to take down, um, 394 00:20:53,560 --> 00:20:57,880 Speaker 1: the capital rioters who you know, did things like serious 395 00:20:58,240 --> 00:21:00,399 Speaker 1: bodily damage to a lot of the police. There's just 396 00:21:00,480 --> 00:21:08,479 Speaker 1: trying to defend our nation's capital. This is Bloomberg, all right. 397 00:21:08,560 --> 00:21:14,480 Speaker 1: Apparently I guess Jeff Bezos July is set to launch 398 00:21:14,680 --> 00:21:18,320 Speaker 1: into space on one of those Blue Origin flights. Let's 399 00:21:18,359 --> 00:21:20,320 Speaker 1: get the latest on this deal. Like, I think he's 400 00:21:20,320 --> 00:21:22,920 Speaker 1: not gonna be alone either. Ed Ludlow, he's an auto 401 00:21:22,960 --> 00:21:25,720 Speaker 1: reporter for Bloomberg News, joins us from the Bloomberg nine 402 00:21:25,720 --> 00:21:28,639 Speaker 1: sixties studio, and San Francis a rocket reporter. He's a 403 00:21:28,720 --> 00:21:31,800 Speaker 1: rocket reporter now, is what he is uh ed. So 404 00:21:32,119 --> 00:21:35,680 Speaker 1: Jeff Bezos going into space, This seems like a big 405 00:21:35,720 --> 00:21:37,760 Speaker 1: deal for me. But I guess if you're one of, 406 00:21:37,800 --> 00:21:39,959 Speaker 1: if not the richest person in the world, you can 407 00:21:40,000 --> 00:21:43,159 Speaker 1: do those things. Yeah, it's a pretty small group of 408 00:21:43,160 --> 00:21:45,320 Speaker 1: people that have the ability to do that, right. So 409 00:21:45,760 --> 00:21:49,959 Speaker 1: this is Blue Origins debut passenger. They call them astronauts, 410 00:21:50,000 --> 00:21:52,760 Speaker 1: you know, private astronauts, but their passengers because it's a 411 00:21:52,760 --> 00:21:55,479 Speaker 1: Philly autonomous craft. And he is going to go up 412 00:21:55,480 --> 00:21:59,640 Speaker 1: with his brother Mark Bezos and one lucky I suppose 413 00:22:00,520 --> 00:22:03,600 Speaker 1: auction winner. So right now, the highest bidder for the 414 00:22:03,680 --> 00:22:06,600 Speaker 1: third seat has put two point eight million dollars down. 415 00:22:07,040 --> 00:22:10,199 Speaker 1: That's it, you say, that's it. I mean, you know 416 00:22:10,560 --> 00:22:14,600 Speaker 1: top took him and somebody paid sixty nine million dollars 417 00:22:14,720 --> 00:22:18,720 Speaker 1: for an n f T of a people picture. Yeah, 418 00:22:18,760 --> 00:22:21,639 Speaker 1: I know, but the you know, the risks associated with 419 00:22:22,359 --> 00:22:25,159 Speaker 1: being launched into orbit and budding n f T s. 420 00:22:25,240 --> 00:22:27,840 Speaker 1: I don't think they're on par right, But you know, 421 00:22:28,080 --> 00:22:30,360 Speaker 1: they're going to continue this auction until mid June when 422 00:22:30,359 --> 00:22:32,760 Speaker 1: they'll close it. Highest bidder gets to go up with 423 00:22:32,760 --> 00:22:36,399 Speaker 1: the Bezos bros. Um it's an eleven minute journey, you know, 424 00:22:36,480 --> 00:22:39,480 Speaker 1: you go to the Carmen Line, which is about a 425 00:22:39,560 --> 00:22:42,320 Speaker 1: hundred kilometers above above Earth. You know, it's kind of 426 00:22:42,359 --> 00:22:46,160 Speaker 1: the internationally recognized boundary of space from Earth. And then 427 00:22:46,160 --> 00:22:48,159 Speaker 1: you come straight back down in the capsule. So when 428 00:22:48,160 --> 00:22:51,400 Speaker 1: the capsule separates from the booster, the new Shepherd booster, 429 00:22:51,680 --> 00:22:55,320 Speaker 1: it falls by itself with parachute, you know, very leisurely 430 00:22:55,440 --> 00:22:59,120 Speaker 1: ride is the booster. I mean, are we talking about 431 00:22:59,240 --> 00:23:01,800 Speaker 1: top check here? Is it going to land again on 432 00:23:01,880 --> 00:23:05,199 Speaker 1: some autonomous ship in the ocean or is it ghetto? No, 433 00:23:05,280 --> 00:23:08,000 Speaker 1: it's automous. I think what's interesting about Blue Origin is 434 00:23:08,040 --> 00:23:10,880 Speaker 1: that they you know, they clearly want to get some 435 00:23:11,000 --> 00:23:13,439 Speaker 1: kind of milestone win if you if you go all 436 00:23:13,480 --> 00:23:16,280 Speaker 1: the way back to two thousand and twelve, they were 437 00:23:16,320 --> 00:23:21,000 Speaker 1: the first actually land a booster autonomously, ahead of SpaceX 438 00:23:21,000 --> 00:23:23,679 Speaker 1: by about a month, one calendar month. But the thing is, 439 00:23:24,040 --> 00:23:27,679 Speaker 1: Blue Origin has only done fifteen consecutive test flights of 440 00:23:27,720 --> 00:23:31,280 Speaker 1: its technology by this point over a ten year period. 441 00:23:31,320 --> 00:23:33,800 Speaker 1: SpaceX has done more than a hundred and twenty five 442 00:23:33,840 --> 00:23:38,320 Speaker 1: successful flights. So, you know, Bezos is I don't know 443 00:23:38,320 --> 00:23:40,280 Speaker 1: if it's the right expression, putting his money where his 444 00:23:40,320 --> 00:23:42,719 Speaker 1: mouth is, but he you know, This is a company 445 00:23:42,760 --> 00:23:44,920 Speaker 1: that he has put one billion dollars into on an 446 00:23:44,960 --> 00:23:49,560 Speaker 1: annual basis um. He has spoken very competitively about it 447 00:23:49,720 --> 00:23:52,199 Speaker 1: about how his it's been his childhood dreams go to space, 448 00:23:52,640 --> 00:23:55,119 Speaker 1: and you know he's going to go up him, going 449 00:23:55,200 --> 00:23:58,800 Speaker 1: to put his mouth where his money is exactly the opposite, right, 450 00:23:59,280 --> 00:24:01,879 Speaker 1: What is the risk here? I mean, what are some 451 00:24:01,920 --> 00:24:05,360 Speaker 1: of the experts saying here? It's it seems to me 452 00:24:06,480 --> 00:24:10,160 Speaker 1: fairly risky, maybe more risk than you know you'd you'd 453 00:24:10,240 --> 00:24:13,160 Speaker 1: want to take. Um, what if you had a hundred 454 00:24:13,200 --> 00:24:18,800 Speaker 1: and eighty six point eight at a technical level, And 455 00:24:18,880 --> 00:24:22,159 Speaker 1: again I'm a reporter, I'm not a space engineer. But 456 00:24:22,560 --> 00:24:24,440 Speaker 1: the thing that the difference between the capsule that Blue 457 00:24:24,480 --> 00:24:30,800 Speaker 1: Origin has is that there's no onboard control. Imagine meditation 458 00:24:30,920 --> 00:24:34,680 Speaker 1: room with padding around the outside, six windows and six seats. 459 00:24:34,720 --> 00:24:37,119 Speaker 1: That's it. If you compare that to the Dragon capsule 460 00:24:37,200 --> 00:24:41,800 Speaker 1: the SpaceX um produces. The astronauts in the SpaceX capsule 461 00:24:41,880 --> 00:24:45,240 Speaker 1: have some limited ability to interact with the vessel, run checks, 462 00:24:45,280 --> 00:24:48,840 Speaker 1: run controls, do some manual takeover in worst case scenarios. 463 00:24:49,160 --> 00:24:52,360 Speaker 1: The Blue Origin capsule is truly autonomous. You sit there, 464 00:24:52,400 --> 00:24:55,240 Speaker 1: you belt in and that's it. It's out of your control. 465 00:24:55,359 --> 00:24:59,119 Speaker 1: I guess that's slightly disconcerting. And and the frequency of 466 00:24:59,160 --> 00:25:02,360 Speaker 1: tests and vol lume of tests is much less, far 467 00:25:02,440 --> 00:25:05,399 Speaker 1: fewer than SpaceX is done. But they have had fifteen 468 00:25:05,440 --> 00:25:09,919 Speaker 1: consecutive test flights. They've they've tested successfully. The abort features 469 00:25:09,960 --> 00:25:12,200 Speaker 1: what happens in the event and of emergency. The way 470 00:25:12,200 --> 00:25:15,160 Speaker 1: that it's designed is that not only does the capsule 471 00:25:15,240 --> 00:25:18,160 Speaker 1: carrying the humans separate from the booster, but it gets 472 00:25:18,160 --> 00:25:22,040 Speaker 1: basically a boost to change its trajectory away from the booster. 473 00:25:22,480 --> 00:25:25,040 Speaker 1: There's a hard separation, which means that they you know, 474 00:25:25,040 --> 00:25:27,160 Speaker 1: they wouldn't collide with each other, will come into contact 475 00:25:27,359 --> 00:25:30,520 Speaker 1: and at that point the parachutes would open. But yeah, 476 00:25:30,720 --> 00:25:33,000 Speaker 1: of course it's fraught with risk, you know. And I 477 00:25:33,000 --> 00:25:35,520 Speaker 1: think that less so from Bazos because we hear from 478 00:25:35,600 --> 00:25:38,520 Speaker 1: him less. But Elon Musk, for example, is pretty transparent 479 00:25:38,560 --> 00:25:41,560 Speaker 1: about what those risks are. Musk wants to go to 480 00:25:41,600 --> 00:25:45,600 Speaker 1: Mars too, so he's maybe not far behind Jeff in 481 00:25:45,880 --> 00:25:48,280 Speaker 1: Billionaires in space. Ed, thanks so much for joining us, 482 00:25:48,359 --> 00:25:52,080 Speaker 1: Ed Ludlow there, he's Bloomberg's well rocket reporter, but also 483 00:25:52,200 --> 00:25:54,639 Speaker 1: what covers cars for us out of California. Thanks for 484 00:25:54,680 --> 00:25:58,159 Speaker 1: listening to the Bloomberg Markets podcast. You can subscribe and 485 00:25:58,240 --> 00:26:01,800 Speaker 1: listen to interviews with Apple, pod Asks, or whatever podcast 486 00:26:01,840 --> 00:26:05,360 Speaker 1: platform you prefer. I'm Matt Miller, I'm on Twitter at 487 00:26:05,400 --> 00:26:09,040 Speaker 1: Matt Miller three. And I'm Fall Sweeney. I'm on Twitter 488 00:26:09,080 --> 00:26:11,920 Speaker 1: at pt Sweeney. Before the podcast, you can always catch 489 00:26:12,000 --> 00:26:13,560 Speaker 1: us worldwide at Bloomberg Radio