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 --> 00:00:21,400 Speaker 1: at Bloomberg dot com slash podcast. All right, we get 7 00:00:21,400 --> 00:00:24,520 Speaker 1: some inflation data tomorrow c p I. The year of 8 00:00:24,600 --> 00:00:29,200 Speaker 1: year consensus is eight point four UM. I don't think 9 00:00:29,200 --> 00:00:31,120 Speaker 1: wages are going up eight point four percent, so that's 10 00:00:31,120 --> 00:00:33,879 Speaker 1: a challenge for many folks out there. Let's check in 11 00:00:33,920 --> 00:00:40,159 Speaker 1: with Robert Rosener, executive director, senior US economist at Morgan Stanley. Robert, 12 00:00:40,280 --> 00:00:43,760 Speaker 1: what are you can? Award winning economists? Award winning economist, 13 00:00:43,840 --> 00:00:47,320 Speaker 1: aren't they all? No, that's the point. He won the 14 00:00:47,440 --> 00:00:51,000 Speaker 1: n A B Outlook Award for the most accurate economic 15 00:00:51,120 --> 00:00:56,920 Speaker 1: forecasts over the past four quarters. So who yeah, So 16 00:00:57,000 --> 00:00:58,440 Speaker 1: he knows what he's talking about. So you we're gonna 17 00:00:58,440 --> 00:01:01,480 Speaker 1: ask about inflation. This sperfect. Let's do it. Robert, thanks 18 00:01:01,480 --> 00:01:03,200 Speaker 1: so much for joining us. Really appreciate you taking the 19 00:01:03,280 --> 00:01:05,840 Speaker 1: time here. What are you going to be looking for tomorrow, Robert, 20 00:01:05,840 --> 00:01:09,679 Speaker 1: and that inflation data. Yeah, well, thanks guys, thanks for 21 00:01:09,680 --> 00:01:12,440 Speaker 1: having me on and you're two nice um. But when 22 00:01:12,440 --> 00:01:14,880 Speaker 1: it comes to the inflation data tomorrow, we're certainly going 23 00:01:14,920 --> 00:01:17,600 Speaker 1: to see a lot of heat. Um. We're looking for 24 00:01:17,640 --> 00:01:20,360 Speaker 1: a high headline inflation reading driven by the upside and 25 00:01:20,440 --> 00:01:24,000 Speaker 1: energy prices as well as food prices, and underneath the surface, 26 00:01:24,080 --> 00:01:27,120 Speaker 1: the core should remain elevated as well. We're seeing a 27 00:01:27,160 --> 00:01:29,760 Speaker 1: little bit of give back in terms of goods inflation. 28 00:01:29,880 --> 00:01:32,320 Speaker 1: Some of the areas that we're leading the high inflation 29 00:01:32,360 --> 00:01:35,560 Speaker 1: prints that we saw last year, areas like used car prices, 30 00:01:35,600 --> 00:01:38,800 Speaker 1: appear that they've pulled back a little bit. But on 31 00:01:38,840 --> 00:01:40,760 Speaker 1: the surfaces side of the picture, where we've seen that 32 00:01:40,840 --> 00:01:44,240 Speaker 1: broadening out of inflationary pressures in recent months, we actually 33 00:01:44,240 --> 00:01:47,600 Speaker 1: look for some acceleration there in things like rents owner's 34 00:01:47,640 --> 00:01:49,920 Speaker 1: equivalent rents as well as some of the COVID sensitive 35 00:01:49,920 --> 00:01:53,280 Speaker 1: categories like air fairs and hotels all look like they're 36 00:01:53,320 --> 00:01:56,200 Speaker 1: set up for high readings. And all of that's important 37 00:01:56,520 --> 00:01:59,680 Speaker 1: as we think about how to read this print, because 38 00:01:59,840 --> 00:02:01,720 Speaker 1: we know the top line is going to be high 39 00:02:01,800 --> 00:02:04,520 Speaker 1: driven by energy prices. The internals are going to tell 40 00:02:04,560 --> 00:02:06,840 Speaker 1: us a lot more about where inflation is likely to 41 00:02:06,920 --> 00:02:09,120 Speaker 1: trend over the month ahead and if we are going 42 00:02:09,160 --> 00:02:12,960 Speaker 1: to see any sequential deceleration. So um, but where do 43 00:02:13,000 --> 00:02:15,120 Speaker 1: you think now it's likely a trend over there. You 44 00:02:15,160 --> 00:02:16,760 Speaker 1: know a lot of people are saying it's going to 45 00:02:16,880 --> 00:02:21,559 Speaker 1: peak with this reading. Our Abigail Doolittle, who is a chartist, disagrees. 46 00:02:21,840 --> 00:02:25,480 Speaker 1: What's your view? Well, that's the key question. You know, 47 00:02:25,520 --> 00:02:28,400 Speaker 1: on a twelve month basis, we do expect that inflation 48 00:02:28,440 --> 00:02:30,720 Speaker 1: is going to peak. We're expecting that this peak reading 49 00:02:30,800 --> 00:02:33,000 Speaker 1: for headline CPI is going to come in at eight 50 00:02:33,000 --> 00:02:37,119 Speaker 1: point six percent, so again that multidecade high, and as 51 00:02:37,120 --> 00:02:39,600 Speaker 1: we make the lap around those tough base effects from 52 00:02:39,639 --> 00:02:42,680 Speaker 1: the spring, we should see inflation coming off of those peaks. 53 00:02:42,720 --> 00:02:45,160 Speaker 1: I think the key question here is what's going on 54 00:02:45,200 --> 00:02:47,640 Speaker 1: with those core internals and how quickly are we going 55 00:02:47,680 --> 00:02:50,519 Speaker 1: to roll off of those peaks and to where our 56 00:02:50,560 --> 00:02:52,760 Speaker 1: forecast would say, yes, we're going to come off of 57 00:02:52,800 --> 00:02:55,079 Speaker 1: those peaks. It's going to be a slow grind off 58 00:02:55,080 --> 00:02:58,120 Speaker 1: of that peak for inflation, though year over year inflation 59 00:02:58,160 --> 00:03:00,919 Speaker 1: is going to remain elevated. It's likely in our forecast 60 00:03:01,000 --> 00:03:03,600 Speaker 1: to remain above seven per cent until we get into 61 00:03:03,680 --> 00:03:06,680 Speaker 1: the second half of the year, so those pressures are 62 00:03:06,680 --> 00:03:09,440 Speaker 1: still going to be there. Um, what we need to 63 00:03:09,440 --> 00:03:11,560 Speaker 1: see is if the core is going to start decelerating 64 00:03:11,560 --> 00:03:14,320 Speaker 1: a material way that can give us more confidence that 65 00:03:14,360 --> 00:03:18,079 Speaker 1: we will see inflation slow further or more materially when 66 00:03:18,080 --> 00:03:20,880 Speaker 1: we're getting into the end of next year early sorry, 67 00:03:20,960 --> 00:03:23,760 Speaker 1: end of this year, early next year. But that evans 68 00:03:24,040 --> 00:03:26,240 Speaker 1: is not there yet, and what we're seeing is that 69 00:03:26,360 --> 00:03:29,480 Speaker 1: a trend is warming that suggests them for their support. 70 00:03:30,440 --> 00:03:35,120 Speaker 1: All right, So, Robert, given that inflationary backdrop, give us 71 00:03:35,120 --> 00:03:37,480 Speaker 1: your assessment of kind of where the FED is right 72 00:03:37,520 --> 00:03:40,560 Speaker 1: now in terms of their actions and kind of how 73 00:03:40,600 --> 00:03:42,000 Speaker 1: you think that might play off for the remainder of 74 00:03:42,040 --> 00:03:45,800 Speaker 1: the year. Yeah. Well, this is clearly a FED that 75 00:03:45,960 --> 00:03:49,520 Speaker 1: is taking inflation much more seriously and has undergone a 76 00:03:49,640 --> 00:03:52,200 Speaker 1: very hawkers shift in recent months as a result, and 77 00:03:52,240 --> 00:03:56,480 Speaker 1: we're expecting the Fed to deliver on more hawk is expectations. 78 00:03:56,520 --> 00:03:58,840 Speaker 1: We're expecting a fifty basis point rate hike from the 79 00:03:58,880 --> 00:04:01,960 Speaker 1: Fed at them May meeting. We're expecting another fifty basis 80 00:04:02,000 --> 00:04:04,800 Speaker 1: point rate hike at the June meeting. All the while 81 00:04:05,200 --> 00:04:07,880 Speaker 1: policymakers have given us an indication that the balance sheet 82 00:04:07,920 --> 00:04:10,320 Speaker 1: runoff is likely to begin. We think that announcement comes 83 00:04:10,440 --> 00:04:13,560 Speaker 1: in May. We just learned in the minutes last week 84 00:04:13,600 --> 00:04:16,520 Speaker 1: that will likely occur at a pace of a billion 85 00:04:16,560 --> 00:04:19,360 Speaker 1: dollars per month. So that's a lot of policy tightening 86 00:04:19,560 --> 00:04:22,000 Speaker 1: coming in the pipeline. And there are a number of 87 00:04:22,080 --> 00:04:25,119 Speaker 1: important things that we learned in the FMC minutes last week, 88 00:04:25,720 --> 00:04:31,280 Speaker 1: particularly around policymakers preferences for tightening policy expeditiously more our 89 00:04:31,360 --> 00:04:34,279 Speaker 1: favoring fifty basis point rate hikes, and coming back to 90 00:04:34,320 --> 00:04:36,719 Speaker 1: the inflation data, that's going to be the key guide. 91 00:04:37,000 --> 00:04:39,560 Speaker 1: We do think it will get to in May and June. 92 00:04:39,880 --> 00:04:42,840 Speaker 1: What does the policy path look like thereafter? It remains 93 00:04:42,880 --> 00:04:45,720 Speaker 1: data dependent, and so if inflation does not pull back materially, 94 00:04:45,720 --> 00:04:47,760 Speaker 1: we should expect the Fed to continue to pursue a 95 00:04:47,839 --> 00:04:50,120 Speaker 1: more hawkish policies down all right, So back to back 96 00:04:50,160 --> 00:04:53,320 Speaker 1: fifty basis point hikes. And for those wondering, there's no 97 00:04:53,400 --> 00:04:57,000 Speaker 1: April meeting for the Fed. They skip it maybe because 98 00:04:57,000 --> 00:04:59,800 Speaker 1: of Easter, I don't know, but their next meeting is May. 99 00:04:59,800 --> 00:05:02,800 Speaker 1: F earth Um Robert talked to me about, you know, 100 00:05:03,440 --> 00:05:06,359 Speaker 1: Paul said, isn't everyone but no, Um, Wall Street is 101 00:05:06,400 --> 00:05:09,000 Speaker 1: one example of a place where everyone doesn't get a trophy. 102 00:05:09,040 --> 00:05:13,320 Speaker 1: There's one winner. You are in participation, UM, So talk 103 00:05:13,360 --> 00:05:16,400 Speaker 1: to us about your process. You know what, what do 104 00:05:16,440 --> 00:05:18,919 Speaker 1: you think is different about your process that allows you 105 00:05:18,960 --> 00:05:25,080 Speaker 1: to forecast more accurately. Well, I think it's been continuously 106 00:05:25,120 --> 00:05:28,200 Speaker 1: the case as we moved through UH this recovery and 107 00:05:28,240 --> 00:05:30,840 Speaker 1: as we're moving for this expansion. We really have to 108 00:05:30,880 --> 00:05:33,640 Speaker 1: get into the leads. There's a lot of specific drivers 109 00:05:33,720 --> 00:05:37,040 Speaker 1: moving at the sector level. So for Morgan Stanley research 110 00:05:37,200 --> 00:05:40,719 Speaker 1: about the collaborative process, we get to hear very smart 111 00:05:40,800 --> 00:05:43,520 Speaker 1: things from analysts who are experts in the oil sector 112 00:05:43,560 --> 00:05:46,320 Speaker 1: who know what's going on with cathex, same thing with 113 00:05:46,360 --> 00:05:49,960 Speaker 1: the auto sector and so on. So that collaboration really 114 00:05:49,960 --> 00:05:52,760 Speaker 1: plays a big role in the forecasting process. And then 115 00:05:52,839 --> 00:05:57,000 Speaker 1: also you know, keeping a very close eye on the models. UH, 116 00:05:57,320 --> 00:06:00,360 Speaker 1: there have been a lot of surprises. That is clearly 117 00:06:00,360 --> 00:06:02,920 Speaker 1: what Kapta fed by surprise coming into this year is 118 00:06:03,040 --> 00:06:06,599 Speaker 1: the models would have predicted transitory inflation. We have to 119 00:06:06,600 --> 00:06:10,360 Speaker 1: be constantly questioning what the models are saying and understanding 120 00:06:10,400 --> 00:06:13,039 Speaker 1: what the output means in the context of a very 121 00:06:13,040 --> 00:06:17,320 Speaker 1: fast moving economic backdrop. So this is a real interesting 122 00:06:17,400 --> 00:06:20,080 Speaker 1: point for me. Robert, is Morgan Stanley back in your office. 123 00:06:20,120 --> 00:06:23,800 Speaker 1: Now we are back in the office, and you know, 124 00:06:23,880 --> 00:06:26,920 Speaker 1: talk about collaboration. Nothing like seeing people face to face 125 00:06:27,040 --> 00:06:30,360 Speaker 1: feels really good. That's interesting. So yeah, it's intertionally a 126 00:06:30,400 --> 00:06:32,800 Speaker 1: lot of different companies trying to come to grip soths. 127 00:06:32,839 --> 00:06:34,480 Speaker 1: I always like that, let me get somebody on and see, hey, 128 00:06:34,480 --> 00:06:36,920 Speaker 1: are you guys actually in the office. Are you working remotely? 129 00:06:36,960 --> 00:06:38,960 Speaker 1: And Matt and I are here in your office. Yeah, 130 00:06:38,960 --> 00:06:41,880 Speaker 1: but Robert won the trophy when people were home. The 131 00:06:41,880 --> 00:06:45,120 Speaker 1: only trophy HEAT cares about his Institutional Investor magazine. That 132 00:06:45,240 --> 00:06:48,360 Speaker 1: is the one that South Side really cares about. Not 133 00:06:48,400 --> 00:06:49,920 Speaker 1: as much as in the old days, but still I 134 00:06:49,920 --> 00:06:53,520 Speaker 1: think it's pretty important. Robert Rosener, executive Director, Senior us 135 00:06:53,560 --> 00:06:57,560 Speaker 1: E commers from Morgan Stanley, working from the office, expecting 136 00:06:57,720 --> 00:07:01,360 Speaker 1: fifty basis points rise from Federal Reserve over the next 137 00:07:01,400 --> 00:07:09,200 Speaker 1: two meetings. Tracy mcmillians she's had of a global asset 138 00:07:09,200 --> 00:07:13,200 Speaker 1: allocation strategy Wells Fargo and co graduate of William and 139 00:07:13,240 --> 00:07:15,280 Speaker 1: Mary Rick. Down the road from my University of Richmond, 140 00:07:15,640 --> 00:07:18,600 Speaker 1: UH Spider's nice little rivalry going there. Tracy, We're gonna 141 00:07:18,640 --> 00:07:21,120 Speaker 1: have some CPI data tomorrow. It's going to be an 142 00:07:21,240 --> 00:07:27,680 Speaker 1: ugly read. What's your inflation call? Yeah, so we're definitely 143 00:07:27,720 --> 00:07:32,080 Speaker 1: seeing a perfect storm of inflationary pressures, and you know, 144 00:07:32,160 --> 00:07:34,400 Speaker 1: we do think we're going to see an AID handle 145 00:07:34,520 --> 00:07:38,440 Speaker 1: on this CPI headline number tomorrow. So as you said, 146 00:07:38,480 --> 00:07:40,640 Speaker 1: the numbers are going to be ugly this week. We've 147 00:07:40,640 --> 00:07:44,840 Speaker 1: got CPI, we've got PPI coming out. But inflation we 148 00:07:45,080 --> 00:07:49,080 Speaker 1: think is probably near its high for the cycle. Our 149 00:07:49,120 --> 00:07:53,520 Speaker 1: commodities analysts always says that the cure for high prices 150 00:07:53,560 --> 00:07:57,960 Speaker 1: as high prices, and you know, we don't see things 151 00:07:58,000 --> 00:08:01,840 Speaker 1: like oil spiking higher at this point, but trading in 152 00:08:01,920 --> 00:08:06,200 Speaker 1: a really broad range with some potential upside as we 153 00:08:06,240 --> 00:08:09,200 Speaker 1: go into the end of the year, and you know, 154 00:08:09,240 --> 00:08:13,720 Speaker 1: other commodities probably choppy too, so they really impact headline 155 00:08:13,760 --> 00:08:17,120 Speaker 1: inflation um. But we're also seeing you know, at this 156 00:08:17,200 --> 00:08:21,080 Speaker 1: point shut downs in China and by shortages from that 157 00:08:21,680 --> 00:08:28,280 Speaker 1: and all of that we think keeps inflation elevated. But again, 158 00:08:28,440 --> 00:08:32,160 Speaker 1: you know, here in the eight um we're probably towards 159 00:08:32,200 --> 00:08:35,560 Speaker 1: the top for this cycle. How difficult is it to 160 00:08:35,679 --> 00:08:39,840 Speaker 1: factor in geopolitical risk and issues when you're looking at 161 00:08:39,840 --> 00:08:42,800 Speaker 1: these markets, Tracy, because of course, you know, last year 162 00:08:42,840 --> 00:08:44,760 Speaker 1: this time, you wouldn't have known that we're going to 163 00:08:44,880 --> 00:08:48,800 Speaker 1: have this sort of extra crimp in the supply chain, 164 00:08:49,440 --> 00:08:53,560 Speaker 1: extra boost to inflation of Russia invading Ukraine, and for 165 00:08:53,640 --> 00:08:55,720 Speaker 1: all we know, you know, next year we could be 166 00:08:55,720 --> 00:09:01,679 Speaker 1: looking at a bigger problem around China. Yeah, absolutely, And 167 00:09:01,800 --> 00:09:05,800 Speaker 1: you know it's it's really um, these unexpected events that 168 00:09:05,960 --> 00:09:10,679 Speaker 1: happened to market that cause the kind of uh, you know, 169 00:09:10,760 --> 00:09:15,400 Speaker 1: volatility that we tend to see uh in market cycles. 170 00:09:15,600 --> 00:09:19,560 Speaker 1: And you know, this time around, um, we not only 171 00:09:19,679 --> 00:09:23,480 Speaker 1: had COVID kind of ending and instella. Instead of you know, 172 00:09:23,600 --> 00:09:28,880 Speaker 1: celebrating the reopening from COVID, now we are lamenting a 173 00:09:28,960 --> 00:09:32,880 Speaker 1: war in Europe and looking at the market impacts of 174 00:09:32,920 --> 00:09:38,520 Speaker 1: that conflict because exports from Russia and Ukraine have caused 175 00:09:38,559 --> 00:09:41,520 Speaker 1: additional supply shocks in addition to the ones that we 176 00:09:41,520 --> 00:09:45,079 Speaker 1: were already seeing. So we had to you know, increase 177 00:09:45,200 --> 00:09:48,440 Speaker 1: our inflation expectation, we had to pull back on our 178 00:09:48,440 --> 00:09:54,800 Speaker 1: growth numbers, and you know, unfortunately commodities don't really clear quickly. 179 00:09:55,120 --> 00:09:59,760 Speaker 1: And this war is you know adding additional supply talks, 180 00:10:00,040 --> 00:10:04,400 Speaker 1: shocks to commodities, so they all ramp nail to inflation. 181 00:10:04,720 --> 00:10:08,280 Speaker 1: UM has been lengthened, and the Federal Reserve is ramping 182 00:10:08,360 --> 00:10:12,600 Speaker 1: up its policy response. So all of that is something 183 00:10:12,640 --> 00:10:15,720 Speaker 1: that markets have had to recalibrate really and just the 184 00:10:15,840 --> 00:10:20,800 Speaker 1: last three months. So do you expect tracy that this 185 00:10:20,920 --> 00:10:24,600 Speaker 1: Fed Reserve will raise interestrates fifty basis points maybe over 186 00:10:24,640 --> 00:10:29,239 Speaker 1: the next two meetings. Do you think they'll be that aggressive? Yeah, 187 00:10:29,400 --> 00:10:32,160 Speaker 1: we do. We think they're preparing markets for a really 188 00:10:32,280 --> 00:10:35,600 Speaker 1: tough inflation fight. And they told us that they're going 189 00:10:35,640 --> 00:10:39,120 Speaker 1: to do what it takes UM to you know, quell inflation, 190 00:10:39,440 --> 00:10:42,560 Speaker 1: and their frontloading these hikes. So we do think that 191 00:10:42,600 --> 00:10:46,400 Speaker 1: means probably fifty basis points in May, probably another fifty 192 00:10:46,440 --> 00:10:49,880 Speaker 1: basis points in June. And they're also going to be 193 00:10:49,960 --> 00:10:53,840 Speaker 1: implementing quantitative typening. That's another tool in their tool kit. 194 00:10:53,920 --> 00:10:57,080 Speaker 1: They're they're using UM and they're bringing that to the 195 00:10:57,120 --> 00:11:00,679 Speaker 1: four very quickly as well. UM. So a job of 196 00:11:01,120 --> 00:11:04,360 Speaker 1: orchestrating a soft landing is going to be really tough. 197 00:11:04,480 --> 00:11:09,200 Speaker 1: We've only utilized quantitative tightening once before, and it was 198 00:11:09,240 --> 00:11:13,640 Speaker 1: to a much lesser degree. And it ended shortly after 199 00:11:13,720 --> 00:11:16,880 Speaker 1: it started. So you know, the set is now using 200 00:11:17,440 --> 00:11:22,840 Speaker 1: both rate increases and quantitative tightening to get inflation under control, 201 00:11:23,320 --> 00:11:25,440 Speaker 1: and we think that's going to be a headwind market. 202 00:11:25,960 --> 00:11:31,600 Speaker 1: So where do you hide? Yeah, yeah, yeah, it's so 203 00:11:31,960 --> 00:11:37,160 Speaker 1: really investors are are asking that question, and you know, 204 00:11:37,240 --> 00:11:41,560 Speaker 1: looking across different outset classes, we're seeing a fairly steady 205 00:11:41,880 --> 00:11:46,080 Speaker 1: move out of equities, but not a run for the adfits. 206 00:11:46,200 --> 00:11:50,120 Speaker 1: And we're not suggesting running for the exits and equities, um. 207 00:11:50,200 --> 00:11:55,360 Speaker 1: We are suggesting moving back towards neutral strategic allocations. So 208 00:11:55,480 --> 00:11:58,920 Speaker 1: that means holding some equities but not being over risked. 209 00:11:59,400 --> 00:12:03,120 Speaker 1: It means being diversified inequities and moving away from higher 210 00:12:03,200 --> 00:12:07,320 Speaker 1: beta equities like emerging markets and small caps and adding 211 00:12:07,440 --> 00:12:11,559 Speaker 1: to UH fixed income from maybe you know, the higher 212 00:12:11,600 --> 00:12:15,120 Speaker 1: beta equities. And for there we would say, look at 213 00:12:15,160 --> 00:12:18,200 Speaker 1: the intermediate part of the curve. With ten years at 214 00:12:18,640 --> 00:12:22,240 Speaker 1: two point seven percent, that's starting to look more attractive, 215 00:12:22,320 --> 00:12:24,640 Speaker 1: certainly more so than we've seen in a couple of years. 216 00:12:25,200 --> 00:12:28,520 Speaker 1: All Right, Tracy, great stuff, as always, Tracy McMillian, head 217 00:12:28,520 --> 00:12:32,000 Speaker 1: of Global asset Allocation Strategy for Wells Fargo. I think 218 00:12:32,280 --> 00:12:36,920 Speaker 1: Tracy's based in Winston Salem, the home of wake Forest University. UM, 219 00:12:37,040 --> 00:12:39,680 Speaker 1: part of all those great colleges down in the great 220 00:12:39,720 --> 00:12:41,839 Speaker 1: state of North Carolina. So we have U n C. 221 00:12:42,080 --> 00:12:45,319 Speaker 1: We have a little place called Duke, NC State, you 222 00:12:45,440 --> 00:12:49,079 Speaker 1: got Wake Forest, you got basically the Atlantic Coast Conference, 223 00:12:49,120 --> 00:12:52,040 Speaker 1: basically all located within an hour of each other. But 224 00:12:52,040 --> 00:12:54,120 Speaker 1: you've got to go to the Midwest to find a 225 00:12:54,160 --> 00:13:00,720 Speaker 1: basketball champion. Will please? All right, Let's bring in a 226 00:13:00,720 --> 00:13:03,079 Speaker 1: professional here because we want to talk cyber security here. 227 00:13:03,600 --> 00:13:07,320 Speaker 1: Bob Kulaski, Senior VP for Exeter. Bob, we have a 228 00:13:07,360 --> 00:13:12,760 Speaker 1: hot war in Ukraine. I think about cyber aspects to that. 229 00:13:12,960 --> 00:13:15,320 Speaker 1: What have you noticed in terms of maybe some of 230 00:13:15,320 --> 00:13:18,240 Speaker 1: the activity over there and what risk it may pose 231 00:13:18,320 --> 00:13:23,000 Speaker 1: to some Western countries? Sure? Great to be with you, UM, 232 00:13:23,040 --> 00:13:24,640 Speaker 1: I mean I think the first thing I would take 233 00:13:24,679 --> 00:13:28,720 Speaker 1: away is cyber that fully integrated into a war plan here. 234 00:13:29,000 --> 00:13:32,920 Speaker 1: And for Russia, UM, we've seen their attacks not be 235 00:13:33,040 --> 00:13:36,400 Speaker 1: cyber specifics as much as cyber being part of their 236 00:13:36,480 --> 00:13:40,800 Speaker 1: overall campaign too. You know, you legitimately go after Ukraine 237 00:13:41,000 --> 00:13:43,520 Speaker 1: and the Ukrainian people, and so that means their attacks 238 00:13:43,520 --> 00:13:48,120 Speaker 1: have been somewhat strategic just going after communications infrastructure, um 239 00:13:48,120 --> 00:13:52,120 Speaker 1: which is intentional to hurt the Ukrainian military commander control 240 00:13:52,520 --> 00:13:56,480 Speaker 1: things like that, as well as things against the electric 241 00:13:56,520 --> 00:14:02,040 Speaker 1: gride in the financial sector, which just cause more inconvenient 242 00:14:02,440 --> 00:14:06,680 Speaker 1: for you know, the people, and you know, to help 243 00:14:06,760 --> 00:14:09,040 Speaker 1: the Russians achieve their war rings. And then you throw 244 00:14:09,080 --> 00:14:11,839 Speaker 1: that in with some disinformation and using cyber to get 245 00:14:11,920 --> 00:14:17,640 Speaker 1: access to credentials for Ukrainian military leaders, people involved in 246 00:14:18,040 --> 00:14:21,600 Speaker 1: creating military and um post i legitimate things on social 247 00:14:21,640 --> 00:14:25,160 Speaker 1: media sites. So it's an attack on credential spear fishy 248 00:14:25,240 --> 00:14:29,520 Speaker 1: to then get access to so confusion. So you know, 249 00:14:29,680 --> 00:14:33,160 Speaker 1: unfortunately the cyber's part of an overall hybrid effort the 250 00:14:33,200 --> 00:14:36,920 Speaker 1: Russian government. But Bob, what can we do in terms 251 00:14:36,920 --> 00:14:40,400 Speaker 1: of retaliatory attacks? Does the US engage in that sort 252 00:14:40,440 --> 00:14:45,160 Speaker 1: of um, I guess warfare? Do we engage in cyber warfare? 253 00:14:45,240 --> 00:14:49,400 Speaker 1: Will we hit back that way? So, I mean, when 254 00:14:49,440 --> 00:14:52,120 Speaker 1: you put in the contents of warfare, you know, we're 255 00:14:52,200 --> 00:14:57,120 Speaker 1: still largely following our own strategic participation in conflicts, so 256 00:14:57,400 --> 00:15:03,160 Speaker 1: you're not going to see US actively attacking. It's committing 257 00:15:03,200 --> 00:15:06,480 Speaker 1: an offensive cyber operations that would be thought of as warfare. 258 00:15:06,840 --> 00:15:10,960 Speaker 1: But do we have a setup like that we have 259 00:15:11,000 --> 00:15:14,680 Speaker 1: ability to cause harm in Russia and particularly to cause 260 00:15:14,760 --> 00:15:19,479 Speaker 1: harm and introduce friction into the operation to cyber operational 261 00:15:19,520 --> 00:15:24,480 Speaker 1: system of parts of the Russian government. And uh, you know, 262 00:15:25,640 --> 00:15:29,240 Speaker 1: obviously the administration is somewhat the circumspect of when that's used. 263 00:15:29,640 --> 00:15:32,720 Speaker 1: You know that that authority has been given to the 264 00:15:32,720 --> 00:15:36,160 Speaker 1: Secretary Defense and been been to cyber calm to go 265 00:15:36,320 --> 00:15:40,880 Speaker 1: offensive if it's part of our overall strategic efforts. So 266 00:15:40,920 --> 00:15:45,240 Speaker 1: who Bob, who who kind of runs our cyber I 267 00:15:45,240 --> 00:15:48,280 Speaker 1: guess security issues from a military perspective is that part 268 00:15:48,320 --> 00:15:50,360 Speaker 1: of the Department of Defense is at the n s A. 269 00:15:50,520 --> 00:15:54,360 Speaker 1: Where does it really lie that responsibility? So, you know, 270 00:15:55,280 --> 00:15:58,600 Speaker 1: the administration under the Trump administration gave authorities to the 271 00:15:58,640 --> 00:16:01,400 Speaker 1: Secretary of Defense, which in the operational command is the 272 00:16:01,440 --> 00:16:04,520 Speaker 1: cyber Command, which is a link with the National Security Agency. 273 00:16:05,080 --> 00:16:07,840 Speaker 1: And actually the White House right now is undertaking a 274 00:16:07,920 --> 00:16:11,160 Speaker 1: policy review about you know, what authorities should lie with 275 00:16:11,200 --> 00:16:13,840 Speaker 1: the Secretary of Defense and where the where the White 276 00:16:13,840 --> 00:16:16,480 Speaker 1: House its health the National Security Council should be um 277 00:16:16,520 --> 00:16:19,120 Speaker 1: involved in making off at the cyber decisions. And you 278 00:16:19,160 --> 00:16:21,400 Speaker 1: know that's the question that the show she's going to 279 00:16:21,480 --> 00:16:24,320 Speaker 1: be looking at is Yeah, are you giving too many 280 00:16:24,320 --> 00:16:27,000 Speaker 1: authorities to the commission closer to the command and you 281 00:16:27,040 --> 00:16:31,240 Speaker 1: know that a personal argument that happens in military operations. Interesting. Interesting, 282 00:16:31,240 --> 00:16:33,160 Speaker 1: all right, Bob Colaski, thanks so much for joining us. 283 00:16:33,160 --> 00:16:36,760 Speaker 1: Bob Carloski, Senior VP for Exeter. I'm talking about cybersecurity 284 00:16:36,760 --> 00:16:38,840 Speaker 1: in a time of you know, a hot war in 285 00:16:39,040 --> 00:16:43,320 Speaker 1: your has to raise um, you know, the awareness presumably 286 00:16:43,320 --> 00:16:49,800 Speaker 1: of Western countries. All right, let's talk about supply chains. 287 00:16:49,800 --> 00:16:52,840 Speaker 1: I'm gonna talk about supply chains as it relates to food. 288 00:16:52,880 --> 00:16:55,920 Speaker 1: We're definitely seeing issues there that includes the in the 289 00:16:56,040 --> 00:16:58,720 Speaker 1: seafood business. Our next guest is doing something about it, 290 00:16:58,720 --> 00:17:02,080 Speaker 1: Sylvia Wolf exactly of director, president and CEO of Aqua 291 00:17:02,160 --> 00:17:06,080 Speaker 1: Bounty Technologies. It's kind of like a it's a public 292 00:17:06,200 --> 00:17:07,960 Speaker 1: trade of stock on and now that kind of a 293 00:17:08,000 --> 00:17:10,200 Speaker 1: biotechnology company. So if you thanks so much for joining 294 00:17:10,240 --> 00:17:11,920 Speaker 1: us here. What if you could just start us off 295 00:17:11,960 --> 00:17:15,919 Speaker 1: by just describing what Aqua Bounties is and kind of 296 00:17:15,920 --> 00:17:19,240 Speaker 1: what what what what your strategy is? Thanks for having 297 00:17:19,280 --> 00:17:24,000 Speaker 1: me absolutely. Aquabunty Technologies has two facets to our business. 298 00:17:24,040 --> 00:17:27,560 Speaker 1: The first is we are the first genetically engineered animal 299 00:17:27,600 --> 00:17:30,280 Speaker 1: that was approved for food use, and it's our genetically 300 00:17:30,320 --> 00:17:33,919 Speaker 1: engineered salmon. And so the two components to our business 301 00:17:34,040 --> 00:17:37,440 Speaker 1: are the fact that we actually farm in a land based, 302 00:17:37,560 --> 00:17:42,760 Speaker 1: recirculating aquaculture system, which means we are under roof bio secure. 303 00:17:43,240 --> 00:17:45,080 Speaker 1: And then the other part of our business that we 304 00:17:45,160 --> 00:17:48,280 Speaker 1: think is unique is the fact that we have a 305 00:17:48,320 --> 00:17:52,479 Speaker 1: significant expertise in biotechnology. And what I mean by that 306 00:17:52,640 --> 00:17:57,320 Speaker 1: is selective breeding, gene editing, genetic engineering, as well as 307 00:17:57,320 --> 00:18:00,960 Speaker 1: thinking about fish health and nutrition. So that's what we do. 308 00:18:01,880 --> 00:18:04,399 Speaker 1: So I was about to say I love salmon, but 309 00:18:04,440 --> 00:18:07,040 Speaker 1: then I realized that everyone loves I don't love salmon. 310 00:18:07,119 --> 00:18:09,320 Speaker 1: I'm really yeah, no salmon here. I see, I'm not. 311 00:18:09,359 --> 00:18:12,000 Speaker 1: I'm not even a fish guy, but I love salmon. 312 00:18:12,040 --> 00:18:15,879 Speaker 1: And I always wonder about, um, you know, should I 313 00:18:15,920 --> 00:18:18,960 Speaker 1: buy the farm stuff? Should I go? I feel like 314 00:18:19,000 --> 00:18:23,880 Speaker 1: I'm splurging if I go for a freshwater uh salmon um? 315 00:18:24,080 --> 00:18:27,359 Speaker 1: Is it as good? Sylvia? I know you're biased, but 316 00:18:27,359 --> 00:18:29,959 Speaker 1: I'm gonna go and eat your product, and then I'm 317 00:18:29,960 --> 00:18:32,600 Speaker 1: gonna come back and give my verdict. Is it does 318 00:18:32,640 --> 00:18:36,679 Speaker 1: it taste as good as the wild stuff? It tastes. 319 00:18:36,920 --> 00:18:39,760 Speaker 1: It depends on what how you define good. And what 320 00:18:39,840 --> 00:18:43,240 Speaker 1: I mean by that is we have a slightly milder 321 00:18:43,359 --> 00:18:46,520 Speaker 1: flavor than a wild caught salmon, which is what you're describing. 322 00:18:46,800 --> 00:18:48,840 Speaker 1: But the majority of the salmon that we eat in 323 00:18:48,880 --> 00:18:53,159 Speaker 1: this country is quite frankly um farms. You know of 324 00:18:53,160 --> 00:18:56,520 Speaker 1: the salmon that's available in the US as farm salmon, 325 00:18:56,600 --> 00:19:00,240 Speaker 1: and it's all imported until we build farm is like 326 00:19:00,280 --> 00:19:03,879 Speaker 1: the one that we're currently operating in Indiana are constructing 327 00:19:03,880 --> 00:19:08,760 Speaker 1: in Ohio. Your choices are imports, and so wild cod 328 00:19:08,880 --> 00:19:11,480 Speaker 1: is seasonal. You know, there are quotas involved, but it's 329 00:19:11,560 --> 00:19:14,560 Speaker 1: it does taste slightly different than a farm variety. I mean, 330 00:19:14,600 --> 00:19:16,960 Speaker 1: I think I probably, now that I think about it, 331 00:19:16,960 --> 00:19:20,720 Speaker 1: I tend to eat farmed salmon from Scotland. Farmed in 332 00:19:20,720 --> 00:19:24,000 Speaker 1: in Scotland. If I'm Glenlocks, I think is what it's called. 333 00:19:24,359 --> 00:19:27,200 Speaker 1: But I would much prefer to eat a salmon from 334 00:19:27,200 --> 00:19:30,520 Speaker 1: the Great State of Ohio. Everything tastes better when it 335 00:19:30,560 --> 00:19:33,280 Speaker 1: comes from Ohio. What do you feed them? Do you 336 00:19:33,280 --> 00:19:37,679 Speaker 1: feed them corn? We feed them a very strict diet 337 00:19:37,800 --> 00:19:41,880 Speaker 1: that's been constructed for their life stage, and we buy 338 00:19:41,880 --> 00:19:45,520 Speaker 1: our feet, our salmon feed from the largest feed producers 339 00:19:45,520 --> 00:19:48,439 Speaker 1: in the world, and they feed all farm salmon, but 340 00:19:48,760 --> 00:19:52,120 Speaker 1: they've constructed a feed that is specific to the environment 341 00:19:52,160 --> 00:19:54,720 Speaker 1: where we raise our salmon, which is under as I said, 342 00:19:54,760 --> 00:19:58,560 Speaker 1: and there's a big tank farm um. And so you 343 00:19:58,560 --> 00:20:01,600 Speaker 1: know salmon are curnivorous, so there's fish meal, fish oil, 344 00:20:02,040 --> 00:20:05,240 Speaker 1: and a lot of protein which typically comes from soy 345 00:20:05,359 --> 00:20:10,320 Speaker 1: in their feed formulation. So we've seen inflation, uh, Sylvia 346 00:20:10,440 --> 00:20:13,639 Speaker 1: all over this economy. How has it affected your business? 347 00:20:14,720 --> 00:20:19,280 Speaker 1: You know it's affected us because obviously feed prices are rising. Um, 348 00:20:19,359 --> 00:20:22,880 Speaker 1: we've all seen what happened with agricultural commodities, soy being 349 00:20:23,440 --> 00:20:26,680 Speaker 1: no different than any other agricultural commodity. So we've seen 350 00:20:26,720 --> 00:20:30,159 Speaker 1: increases in feed pricing. But the I think one of 351 00:20:30,200 --> 00:20:33,520 Speaker 1: the benefits of the way that we farm is we 352 00:20:33,600 --> 00:20:36,480 Speaker 1: are not subject to a lot of the variability that 353 00:20:36,800 --> 00:20:42,200 Speaker 1: say netpen farmers are subject to because we farm near consumption. 354 00:20:42,240 --> 00:20:45,359 Speaker 1: So we don't have the inflation with air freight. So 355 00:20:45,440 --> 00:20:48,800 Speaker 1: you're salmon, for example, from salmon is air freighted into 356 00:20:48,840 --> 00:20:51,480 Speaker 1: the country, and we know that there's now limited capacity, 357 00:20:51,560 --> 00:20:55,080 Speaker 1: fuel prices are increasing, etcetera. So UM, the way that 358 00:20:55,119 --> 00:20:58,119 Speaker 1: we farm allows us to control those costs and actually 359 00:20:58,160 --> 00:21:01,639 Speaker 1: produce close to consumption. So where we've seen inflation is 360 00:21:01,680 --> 00:21:06,600 Speaker 1: primarily in feed. UM we're talking to Sylvia Wolf, I'll 361 00:21:06,640 --> 00:21:08,960 Speaker 1: just bring anyone up to speed. Is just tuning in 362 00:21:08,960 --> 00:21:13,240 Speaker 1: from Aqua Bounty technologies. They have genetically engineered salmon that 363 00:21:13,240 --> 00:21:16,200 Speaker 1: they're going to be growing in Ohio and some other state. 364 00:21:16,680 --> 00:21:24,160 Speaker 1: UM and you have tremendous experience in this UM industry. 365 00:21:24,280 --> 00:21:27,080 Speaker 1: You've been at Sarah Lee and Pillsbury, You've been at 366 00:21:27,520 --> 00:21:31,280 Speaker 1: UM Tyson Foods and a number of for example, the 367 00:21:31,359 --> 00:21:37,959 Speaker 1: National Fisheries Institute where you're UH committee member. UM is 368 00:21:38,040 --> 00:21:42,640 Speaker 1: this is Aqua Bounty like a big E. S G move. 369 00:21:42,880 --> 00:21:45,119 Speaker 1: Are you doing kind of the right thing for the 370 00:21:45,160 --> 00:21:50,000 Speaker 1: climate for the world at Aqua Bounty? We believe so, 371 00:21:50,400 --> 00:21:54,240 Speaker 1: and and we think about it from two perspectives. Salmon 372 00:21:54,359 --> 00:21:58,960 Speaker 1: is a very healthy, nutritious protein and providing that and 373 00:21:59,560 --> 00:22:03,200 Speaker 1: to a road are part of our population and actually 374 00:22:03,240 --> 00:22:05,840 Speaker 1: looking to feed the world globally, We're gonna need new 375 00:22:05,840 --> 00:22:09,480 Speaker 1: protein sources. So we think that feeding the world is 376 00:22:09,560 --> 00:22:12,480 Speaker 1: definitely something that we want to do, but we want 377 00:22:12,480 --> 00:22:14,960 Speaker 1: to do it in a safe, secure, and sustainable way. 378 00:22:15,359 --> 00:22:17,520 Speaker 1: So if you think about the way we farm, there's 379 00:22:17,560 --> 00:22:21,560 Speaker 1: two aspects to our fish and the way that we farm. First, 380 00:22:21,880 --> 00:22:26,040 Speaker 1: we recirculate the water um, so we think that we 381 00:22:26,160 --> 00:22:28,480 Speaker 1: use you know, we're judicious about our use of a 382 00:22:28,600 --> 00:22:32,320 Speaker 1: natural resource. And then our fish, the benefit of the 383 00:22:32,320 --> 00:22:36,359 Speaker 1: genetic engineering is twofold. The first is that they grow 384 00:22:36,480 --> 00:22:39,000 Speaker 1: faster than a conventional salm, and so we're able to 385 00:22:39,040 --> 00:22:42,880 Speaker 1: put more throughput through the farm um with that, so 386 00:22:42,960 --> 00:22:46,159 Speaker 1: for less resources in the same capital investment. But just 387 00:22:46,280 --> 00:22:50,439 Speaker 1: as importantly, our fish are actually incredibly efficient in the 388 00:22:50,440 --> 00:22:53,520 Speaker 1: way that they turn feed into biomass, so they actually 389 00:22:53,600 --> 00:22:56,280 Speaker 1: require less than a pound of feed to put on 390 00:22:56,320 --> 00:22:59,719 Speaker 1: a pound of weight. And that's another way of looking 391 00:22:59,800 --> 00:23:02,960 Speaker 1: at how we use our natural resources. So we think 392 00:23:02,960 --> 00:23:06,160 Speaker 1: that we're positioned very well for what's going on around 393 00:23:06,200 --> 00:23:09,119 Speaker 1: me right now. And I was just thinking of over fishing, 394 00:23:09,160 --> 00:23:10,960 Speaker 1: which is one of the biggest problems. I was throwing 395 00:23:10,960 --> 00:23:15,280 Speaker 1: you an alley oop, you know, dunk it, Yes, okay, 396 00:23:15,359 --> 00:23:18,440 Speaker 1: So we again you know, takes the pressure off the oceans, 397 00:23:18,920 --> 00:23:22,320 Speaker 1: um net pen farming, you know, there's environmental impact with that. 398 00:23:22,680 --> 00:23:26,359 Speaker 1: And then when you think about wild salmon, that's really 399 00:23:26,359 --> 00:23:30,240 Speaker 1: about quotas and protecting wild coop populations and so land 400 00:23:30,240 --> 00:23:33,240 Speaker 1: based farming we believe is going to be a significant 401 00:23:33,320 --> 00:23:37,040 Speaker 1: part of filling the gap for for our healthy, nutritious 402 00:23:37,080 --> 00:23:41,000 Speaker 1: protein because it's good stuff there so Via Wolf, Executive Director, 403 00:23:41,040 --> 00:23:44,920 Speaker 1: president CEO of Aqua Bounties Technology. Thanks for listening to 404 00:23:44,960 --> 00:23:48,480 Speaker 1: the Bloomberg Markets podcast. You can subscribe and listen to 405 00:23:48,520 --> 00:23:52,679 Speaker 1: interviews with Apple Podcasts or whatever podcast platform you prefer. 406 00:23:53,080 --> 00:23:57,600 Speaker 1: I'm Matt Miller. I'm on Twitter at Matt Miller, pen 407 00:23:57,680 --> 00:24:00,280 Speaker 1: on false swheey, I'm on Twitter at pt Sweeney. Before 408 00:24:00,280 --> 00:24:03,440 Speaker 1: the podcast, you can always catch us worldwide at Bloomberg Radio. 409 00:24:05,320 --> 00:24:05,359 Speaker 1: M