1 00:00:13,840 --> 00:00:17,439 Speaker 1: Hello, and welcome to What Goes Up, a weekly markets podcast. 2 00:00:17,560 --> 00:00:21,040 Speaker 1: My name is Mike Reagan. I'm a senior editor at Bloomberg, 3 00:00:21,720 --> 00:00:23,760 Speaker 1: and this week on the show, well, if you look 4 00:00:23,760 --> 00:00:26,160 Speaker 1: at the leadership of the stock market in the second 5 00:00:26,239 --> 00:00:34,599 Speaker 1: quarter so far, it's sort of a classic defensive leadership, healthcare, Utilities, Technology. Wait, technology, 6 00:00:35,080 --> 00:00:37,559 Speaker 1: has the delta variant gotten so bad that tech is 7 00:00:37,560 --> 00:00:41,120 Speaker 1: defensive again? Or were we crazy simply to ever think 8 00:00:41,200 --> 00:00:44,120 Speaker 1: that tech would fall off the market's leaderboard for very long. 9 00:00:44,159 --> 00:00:46,680 Speaker 1: To begin with, we'll get into it with a portfolio 10 00:00:46,760 --> 00:00:50,120 Speaker 1: manager and tech analyst, but first I want to welcome 11 00:00:50,479 --> 00:00:53,800 Speaker 1: back to the show a woman who there's a bit 12 00:00:53,840 --> 00:00:56,400 Speaker 1: of mystery to her, but she's no stranger to our 13 00:00:56,440 --> 00:00:59,680 Speaker 1: our listeners here on What Goes Up. She's coming back 14 00:00:59,720 --> 00:01:04,280 Speaker 1: for another co hosting gig. Her name is Vildonna Hirich. Vildonna, 15 00:01:04,400 --> 00:01:08,399 Speaker 1: welcome back. Thanks for having me. And since you are known, 16 00:01:08,400 --> 00:01:11,959 Speaker 1: you don't get the Charlie Pellett introduction treatment. I'm sorry 17 00:01:11,959 --> 00:01:15,039 Speaker 1: about that, but next time I'll definitely expect it. But 18 00:01:15,080 --> 00:01:17,440 Speaker 1: I'm glad to have you on, Vildona because as a 19 00:01:17,560 --> 00:01:20,640 Speaker 1: proud New Jersey native like yourself, it's a big week 20 00:01:20,680 --> 00:01:23,480 Speaker 1: for New Jersey women in the Olympics. Are you as 21 00:01:23,480 --> 00:01:25,960 Speaker 1: excited as I am about all these gold medals that 22 00:01:25,959 --> 00:01:28,160 Speaker 1: that the great state of New Jersey is winning. I'm 23 00:01:28,240 --> 00:01:31,200 Speaker 1: hugely excited. And my household was like cheering and so 24 00:01:31,240 --> 00:01:34,240 Speaker 1: excited all week. And a thing move is from Trenton. 25 00:01:34,520 --> 00:01:36,640 Speaker 1: I'm from Trenton, so I was really really excited to 26 00:01:36,640 --> 00:01:39,480 Speaker 1: see her win, right, I don't forget Sidney McLaughlin right 27 00:01:39,480 --> 00:01:43,040 Speaker 1: down the road for me. Yeah, very exciting. Vildona, if 28 00:01:43,080 --> 00:01:45,200 Speaker 1: you were in the Olympics, what would you be taking 29 00:01:45,200 --> 00:01:49,000 Speaker 1: gold medal in? Oh my gosh, that's I mean not 30 00:01:49,240 --> 00:01:52,520 Speaker 1: I'm like not athletic at all. I can't even picture 31 00:01:53,600 --> 00:01:55,680 Speaker 1: some of the things they do, Like hurdles. I can't 32 00:01:55,680 --> 00:01:58,440 Speaker 1: even picture anybody ever looking at one and thinking I'm 33 00:01:58,440 --> 00:02:01,160 Speaker 1: going to jump over that, let alone jump over it 34 00:02:01,320 --> 00:02:04,800 Speaker 1: very very quickly. So I'm a big fan. I'm a 35 00:02:04,800 --> 00:02:06,320 Speaker 1: big fan of the hurdles, and I'm a big fan 36 00:02:06,360 --> 00:02:09,280 Speaker 1: of the Jamaican team, even though not as big of 37 00:02:09,280 --> 00:02:11,200 Speaker 1: a fan as the New Jersey Condensed of the Olympic. 38 00:02:11,280 --> 00:02:14,560 Speaker 1: But the Jamaican track team is so so athletic. Well, Donna, 39 00:02:14,600 --> 00:02:17,240 Speaker 1: you would win gold in the Craziest Things of the Olympics, 40 00:02:17,240 --> 00:02:19,919 Speaker 1: though I will say the craziest things. If there was 41 00:02:19,960 --> 00:02:22,480 Speaker 1: an event for craziest things in the markets in a week, 42 00:02:22,560 --> 00:02:25,640 Speaker 1: you would win the gold. And I will say, anyone 43 00:02:25,639 --> 00:02:27,800 Speaker 1: else who out there has seen something crazy, by all means, 44 00:02:27,800 --> 00:02:30,720 Speaker 1: give us a call on the Bloomberg Podcast hotline. I've 45 00:02:30,720 --> 00:02:33,240 Speaker 1: been very negligent and not giving out the number for 46 00:02:33,320 --> 00:02:36,240 Speaker 1: several episodes, but by all means, call us up at 47 00:02:36,280 --> 00:02:40,320 Speaker 1: six four six three to four three four nine zero. 48 00:02:40,440 --> 00:02:43,399 Speaker 1: Again that's six four or six three two four three 49 00:02:43,480 --> 00:02:45,880 Speaker 1: four nine zero. Our lines are open. As they say 50 00:02:45,919 --> 00:02:47,720 Speaker 1: on radio, I think I don't know something like that, 51 00:02:48,040 --> 00:02:50,360 Speaker 1: but I leave us a voicemail on the hotline with 52 00:02:50,440 --> 00:02:52,919 Speaker 1: the craziest thing you saw on markets and maybe we'll 53 00:02:52,919 --> 00:02:56,240 Speaker 1: play it on the show. Well down, another proud New 54 00:02:56,280 --> 00:02:58,320 Speaker 1: Jersey and I believe at least his firm is located 55 00:02:58,440 --> 00:03:01,240 Speaker 1: in New Jersey is this week's guest. As I said, 56 00:03:01,280 --> 00:03:05,079 Speaker 1: he's a portfolio manager at Harding Lovener. His name is 57 00:03:05,160 --> 00:03:08,480 Speaker 1: Chris Mack. Chris, welcome to the show, Thanks Mike, and 58 00:03:08,600 --> 00:03:11,960 Speaker 1: yes you're right New Jersey born and raised, so absolutely 59 00:03:12,160 --> 00:03:15,000 Speaker 1: Jersey roots here and a leaf yet grad to boot 60 00:03:15,000 --> 00:03:18,400 Speaker 1: which is kind of like almost New Jersey esque in 61 00:03:18,440 --> 00:03:21,919 Speaker 1: Pennsylvania right over the river. Uh, kind of a rival 62 00:03:21,960 --> 00:03:23,880 Speaker 1: to my Delaware Blue Hens. But I'm not gonna I'm 63 00:03:23,880 --> 00:03:27,120 Speaker 1: not gonna get on your case about that. That's okay. 64 00:03:27,360 --> 00:03:29,360 Speaker 1: And movie Hi is the only rivalry that counts. B 65 00:03:30,040 --> 00:03:33,160 Speaker 1: That's that's true. I can't compete with you all in football, 66 00:03:33,240 --> 00:03:36,200 Speaker 1: but we've we've gotten uh so yeah, I'll pretend it's 67 00:03:36,200 --> 00:03:40,520 Speaker 1: a rivalry basketball. So it's a decent mashup sometimes. But 68 00:03:40,520 --> 00:03:42,160 Speaker 1: but Chris, let's get into it. I know you have 69 00:03:42,280 --> 00:03:45,880 Speaker 1: a pretty heavy tech focus at your firm and the 70 00:03:45,880 --> 00:03:49,280 Speaker 1: funds you helped manage um. What is going on with 71 00:03:49,360 --> 00:03:51,480 Speaker 1: tech being back in the leadership? I think the simple 72 00:03:51,920 --> 00:03:55,640 Speaker 1: explanation narrative is that everyone's worried about the virus again. 73 00:03:55,680 --> 00:03:58,080 Speaker 1: But as I said in the intro, I mean, did 74 00:03:58,120 --> 00:04:00,440 Speaker 1: it ever make sense to sort of bet again this tech? 75 00:04:00,600 --> 00:04:03,600 Speaker 1: I mean, is is it just a perennial leader that 76 00:04:03,640 --> 00:04:06,640 Speaker 1: we should kind of always look to an absence of 77 00:04:06,720 --> 00:04:10,120 Speaker 1: some other reason for say, the cyclical stop performed? How 78 00:04:10,160 --> 00:04:11,880 Speaker 1: are you thinking about just the sector as a whole 79 00:04:11,960 --> 00:04:14,600 Speaker 1: right now? Sure? Yeah, and you know, we could talk 80 00:04:14,640 --> 00:04:17,120 Speaker 1: about maybe since the pandemic or even some of the 81 00:04:17,120 --> 00:04:20,560 Speaker 1: trends that have been taking on a longer term perspective. 82 00:04:21,000 --> 00:04:23,720 Speaker 1: You know, it's interesting about technology, and I think you 83 00:04:23,880 --> 00:04:26,560 Speaker 1: mentioned in your comments earlier you start talking about cyclical 84 00:04:26,680 --> 00:04:29,200 Speaker 1: or defensive, right, And if you look at the how 85 00:04:29,360 --> 00:04:33,360 Speaker 1: the the the sector has evolved in terms of index representation, 86 00:04:33,880 --> 00:04:36,919 Speaker 1: software has become a much much larger percentage of the 87 00:04:36,920 --> 00:04:39,760 Speaker 1: index as opposed to go way back when it's much 88 00:04:39,800 --> 00:04:44,560 Speaker 1: more hardware. Semiconductor is pretty strong, so you know, and 89 00:04:44,640 --> 00:04:47,680 Speaker 1: even software as a whole has because their business model 90 00:04:47,680 --> 00:04:50,080 Speaker 1: has shifted, right, a little bit more of recurring revenue, 91 00:04:50,400 --> 00:04:54,440 Speaker 1: less counting on cyclical launches of versions of software, a 92 00:04:54,480 --> 00:04:57,839 Speaker 1: little bit less CAPEX intensive, right, and so it has 93 00:04:57,880 --> 00:05:00,080 Speaker 1: become a little bit more at the margin defense to 94 00:05:00,320 --> 00:05:03,680 Speaker 1: your point, But when you look back over the past year, 95 00:05:04,000 --> 00:05:06,719 Speaker 1: it's been different segments leading tech. There was a period 96 00:05:06,720 --> 00:05:08,840 Speaker 1: of time when it was all about the semiconductor shortage 97 00:05:09,120 --> 00:05:11,640 Speaker 1: and that cyclical rebound, and so semis were leading the 98 00:05:11,640 --> 00:05:14,719 Speaker 1: way you go back last year it was more about 99 00:05:14,760 --> 00:05:18,560 Speaker 1: software and digitalization of everything, um and then you know, 100 00:05:18,600 --> 00:05:22,279 Speaker 1: particularly smaller cap software where maybe these companies are not 101 00:05:22,360 --> 00:05:25,000 Speaker 1: yet profitable that they're growing really fast because they're acquiring 102 00:05:25,160 --> 00:05:28,200 Speaker 1: users and can come more profitable more quickly. Um. So 103 00:05:28,240 --> 00:05:32,440 Speaker 1: it's been different, different turns in leadership. One point, small 104 00:05:32,520 --> 00:05:36,320 Speaker 1: caps semiconductors, now back to the big tech, which, to 105 00:05:36,360 --> 00:05:39,880 Speaker 1: your points, a little bit more defensive. Chris, I remember 106 00:05:39,960 --> 00:05:44,080 Speaker 1: last year when people positioning in tech companies actually was 107 00:05:44,200 --> 00:05:47,800 Speaker 1: signaling that potentially we could be seeing a much longer 108 00:05:47,839 --> 00:05:51,279 Speaker 1: time period of the recovery from the pandemic. But I 109 00:05:51,320 --> 00:05:53,800 Speaker 1: also wanted to ask you if you could maybe tell 110 00:05:53,920 --> 00:05:57,839 Speaker 1: us a bit more about your top holdings, because I 111 00:05:57,880 --> 00:06:00,320 Speaker 1: think you guys owned some things, but then the same 112 00:06:00,320 --> 00:06:03,920 Speaker 1: time you also own some regional banks, which, uh is 113 00:06:04,040 --> 00:06:06,600 Speaker 1: an interesting play given what's going on with interest rates. 114 00:06:06,600 --> 00:06:08,200 Speaker 1: So maybe you can tell us a bit more about 115 00:06:08,200 --> 00:06:10,640 Speaker 1: how you guys are positioning. Sure, and it kind of 116 00:06:10,640 --> 00:06:12,920 Speaker 1: gets too I guess you would say, the debts. Okay, 117 00:06:12,920 --> 00:06:15,640 Speaker 1: what are we doing? Uh? You know, we we take 118 00:06:15,680 --> 00:06:19,000 Speaker 1: a look at businesses. We look at combination of quality 119 00:06:19,000 --> 00:06:22,200 Speaker 1: of the business, the profitability, growth, and then lastly valuation. 120 00:06:22,520 --> 00:06:25,520 Speaker 1: So evaluation tends to dictate where we move. So tech 121 00:06:25,560 --> 00:06:29,200 Speaker 1: has been a structural large weight for us health care 122 00:06:29,240 --> 00:06:31,640 Speaker 1: as well. Um, we'll touch on that a little bit later, 123 00:06:31,680 --> 00:06:34,120 Speaker 1: but I'll get to your point on banks. Uh, we 124 00:06:34,200 --> 00:06:37,120 Speaker 1: are relativity index overweight on banks has become a larger 125 00:06:37,480 --> 00:06:40,280 Speaker 1: position for US. But it's not been so much a 126 00:06:40,279 --> 00:06:43,520 Speaker 1: cyclical trade, if you will. It's been much more about 127 00:06:43,600 --> 00:06:46,400 Speaker 1: how are we finding under the radar growth financials that 128 00:06:46,440 --> 00:06:49,800 Speaker 1: are able to grow irrespective of what interest rates are 129 00:06:49,800 --> 00:06:51,800 Speaker 1: going to happen. Right. So example of that is a 130 00:06:51,839 --> 00:06:54,800 Speaker 1: company like First Republic, which is a big holding for US. 131 00:06:55,160 --> 00:06:59,840 Speaker 1: They're primarily growing a lot of relationship wise through refer 132 00:07:00,000 --> 00:07:05,080 Speaker 1: calls um fee based income from from wealth management advice. Uh, 133 00:07:05,200 --> 00:07:07,920 Speaker 1: So that is a little bit less dependent upon what's 134 00:07:07,920 --> 00:07:10,120 Speaker 1: happening with interest rates. It will certainly help them too, 135 00:07:10,960 --> 00:07:13,000 Speaker 1: but you know, if you look back, seventy percent of 136 00:07:13,040 --> 00:07:16,880 Speaker 1: their growth has been coming from existing customers uh and 137 00:07:16,960 --> 00:07:19,200 Speaker 1: just growing their wealth over time. So there's a certain 138 00:07:19,240 --> 00:07:21,800 Speaker 1: element here that that's not relying on any particular cycle. 139 00:07:23,520 --> 00:07:26,320 Speaker 1: Those are those are kind of financials that appeal to us. 140 00:07:26,400 --> 00:07:28,760 Speaker 1: I was looking at those holdings to it's it's fascinating 141 00:07:28,800 --> 00:07:32,680 Speaker 1: to me. So First Republic and SVB Financial what I 142 00:07:33,440 --> 00:07:35,600 Speaker 1: find I guess it's not funny. But I kind of 143 00:07:35,600 --> 00:07:37,640 Speaker 1: find it funny is that these are stocks that are 144 00:07:37,680 --> 00:07:40,360 Speaker 1: in both value and growth indexes. So it's kind of 145 00:07:40,360 --> 00:07:43,880 Speaker 1: like everyone's deciding to rotate from growth growth to value 146 00:07:43,880 --> 00:07:45,440 Speaker 1: A why not by the ones that are that are 147 00:07:45,440 --> 00:07:48,320 Speaker 1: in both indexes? But I mean, when you think about it, 148 00:07:48,360 --> 00:07:51,920 Speaker 1: is that almost a viable strategy? What? As you said, 149 00:07:51,920 --> 00:07:54,320 Speaker 1: what are the growth stocks that are that are priced 150 00:07:54,320 --> 00:07:56,800 Speaker 1: like value stocks in a way. I mean, it seems 151 00:07:57,280 --> 00:08:01,320 Speaker 1: you know, that's the conversation that doesn't get brought into 152 00:08:01,320 --> 00:08:04,840 Speaker 1: the growth value roots rotation. It seems like, yeah, no, 153 00:08:04,880 --> 00:08:06,680 Speaker 1: that's absolutely true. And I think that's so I think 154 00:08:06,680 --> 00:08:08,960 Speaker 1: this a lot of times it's framed there's this false 155 00:08:09,000 --> 00:08:11,400 Speaker 1: dichonomy is it growth or is it value? And there's 156 00:08:11,440 --> 00:08:13,480 Speaker 1: there could be quite a little overlap. You look at 157 00:08:13,840 --> 00:08:17,600 Speaker 1: historically companies like Apple that have been in both UH 158 00:08:17,680 --> 00:08:20,480 Speaker 1: and you so so there's this this false conception and 159 00:08:20,520 --> 00:08:22,280 Speaker 1: you have to pick more or the other. And so 160 00:08:22,360 --> 00:08:24,880 Speaker 1: we're looking for growth, but just reasonably price growth, and 161 00:08:24,920 --> 00:08:27,280 Speaker 1: sometimes that leads us into something that's more value esque. 162 00:08:28,120 --> 00:08:29,960 Speaker 1: But then you know, even think take the case for 163 00:08:30,080 --> 00:08:35,680 Speaker 1: value today, there it's it's about could value stock could 164 00:08:35,679 --> 00:08:38,520 Speaker 1: the underlying businesses grow more quickly coming out of the 165 00:08:38,520 --> 00:08:40,880 Speaker 1: pandemic then the growth businesses that are trading out of 166 00:08:40,920 --> 00:08:44,520 Speaker 1: premium right. Um So even even the value case has 167 00:08:44,559 --> 00:08:48,000 Speaker 1: got some element of growth to it. UM. So for us, 168 00:08:48,040 --> 00:08:50,160 Speaker 1: the lines blur. It's really looking at what are the 169 00:08:50,200 --> 00:08:54,400 Speaker 1: strongest position businesses within their industries, Uh, you know, where 170 00:08:54,400 --> 00:08:57,439 Speaker 1: the where the structure is the strongest um and then 171 00:08:57,480 --> 00:09:00,520 Speaker 1: less than looking at that valuation. So financials paired with 172 00:09:00,600 --> 00:09:03,480 Speaker 1: technology makes a lot of sense to us. Um even 173 00:09:03,480 --> 00:09:05,800 Speaker 1: if you know you could have a financial related technology 174 00:09:05,800 --> 00:09:08,400 Speaker 1: company like in payments, like PayPal, which is one of 175 00:09:08,400 --> 00:09:12,679 Speaker 1: our larger holdings. Um. You know, given digital payments and 176 00:09:12,679 --> 00:09:16,320 Speaker 1: and so on, um And so combining that with healthcare 177 00:09:16,360 --> 00:09:20,000 Speaker 1: for example, and a decent amount of industrials with some 178 00:09:20,040 --> 00:09:23,920 Speaker 1: cyclical exposure. That's the way we're navigating this current environment. 179 00:09:23,960 --> 00:09:26,960 Speaker 1: Because we can't predict what's happening with the delta variant. 180 00:09:27,640 --> 00:09:29,800 Speaker 1: We don't know what's going to happen with interest rates. 181 00:09:30,040 --> 00:09:32,080 Speaker 1: I could certainly give you my opinion, but I could 182 00:09:32,160 --> 00:09:35,080 Speaker 1: wouldn't put a whole lot of weight in that opinion. 183 00:09:35,160 --> 00:09:37,280 Speaker 1: So how do we manage those uncertainties is through a 184 00:09:37,280 --> 00:09:50,200 Speaker 1: globally diversified portfolio. I'm glad you brought up the delta 185 00:09:50,280 --> 00:09:52,080 Speaker 1: variant again because I wanted to ask you how you 186 00:09:52,120 --> 00:09:54,360 Speaker 1: and your team are thinking about what's been going on 187 00:09:54,520 --> 00:09:57,720 Speaker 1: and in terms of what the bond market is signaling. 188 00:09:57,960 --> 00:10:00,600 Speaker 1: That's it signal that potentially we could have a slower 189 00:10:00,640 --> 00:10:03,960 Speaker 1: growth environment or are some of the signals from the 190 00:10:03,960 --> 00:10:06,600 Speaker 1: bond market a bit more technical in nature. How are 191 00:10:06,640 --> 00:10:08,400 Speaker 1: you thinking about it? And how much of a threat 192 00:10:08,720 --> 00:10:14,439 Speaker 1: is the delta variant to growth and growth propects us? 193 00:10:14,480 --> 00:10:16,760 Speaker 1: Certainly a threat, and I think when it goes back 194 00:10:16,760 --> 00:10:22,760 Speaker 1: to thinking about the pandemic recovery and vaccinations globally and 195 00:10:23,160 --> 00:10:26,440 Speaker 1: just this notion that okay, certainly not every country is 196 00:10:26,480 --> 00:10:29,240 Speaker 1: able to get either access to the vaccinations, are able 197 00:10:29,280 --> 00:10:32,800 Speaker 1: to distribute them broadly enough that we have this uneven 198 00:10:32,840 --> 00:10:36,240 Speaker 1: recovery if it's all about just the pandemic, right, And 199 00:10:36,280 --> 00:10:38,520 Speaker 1: so that's already been coming into play. Now the delta 200 00:10:38,600 --> 00:10:40,560 Speaker 1: variant just brings it home to roost, and now it 201 00:10:40,559 --> 00:10:43,360 Speaker 1: comes home here in the US. That is threatening because 202 00:10:43,480 --> 00:10:45,360 Speaker 1: vaccinations didn't quite get to the level that we had 203 00:10:45,400 --> 00:10:47,920 Speaker 1: all been hoping for, and so now it just makes 204 00:10:47,960 --> 00:10:50,960 Speaker 1: everyone tap the brakes again. So if you think about 205 00:10:51,040 --> 00:10:54,200 Speaker 1: the whole case for you know, the higher interest rates, 206 00:10:54,440 --> 00:10:56,959 Speaker 1: it gets back to this, what's going to happen with inflation? Right? 207 00:10:57,000 --> 00:11:00,400 Speaker 1: And to what extent are Yeah, we have this stronger 208 00:11:00,440 --> 00:11:03,840 Speaker 1: demand coming out of the pandemic because fortunately it wasn't 209 00:11:03,880 --> 00:11:05,839 Speaker 1: as damaging as it could have been. You also had 210 00:11:05,880 --> 00:11:10,199 Speaker 1: some flancial you know, economic incentive packages that have helped 211 00:11:10,240 --> 00:11:13,760 Speaker 1: out there. Uh ease the blow if you will, um, 212 00:11:13,840 --> 00:11:17,079 Speaker 1: but you know, trying to get the supply up and running. 213 00:11:17,080 --> 00:11:19,079 Speaker 1: We see it in a semi connector sector for example, 214 00:11:19,200 --> 00:11:22,760 Speaker 1: right or semi connector industry or building look at the 215 00:11:22,760 --> 00:11:25,560 Speaker 1: price of you know, of building materials and what's happened. 216 00:11:25,880 --> 00:11:27,840 Speaker 1: So we had this period we're up until May, everyone 217 00:11:27,880 --> 00:11:31,160 Speaker 1: was anticipating inflation, and then that great CPI number comes 218 00:11:31,160 --> 00:11:32,920 Speaker 1: in and you could see some of these you know, 219 00:11:32,960 --> 00:11:36,200 Speaker 1: timber prices and everything just roll over right, And so 220 00:11:36,640 --> 00:11:39,560 Speaker 1: I think everything would point to the FED being on 221 00:11:39,600 --> 00:11:41,680 Speaker 1: the right path and saying that it is it will 222 00:11:41,720 --> 00:11:45,720 Speaker 1: be transient. If you ask me, um, question is how 223 00:11:45,760 --> 00:11:49,280 Speaker 1: long is transient? Because it's certainly these things are bottled 224 00:11:49,360 --> 00:11:51,800 Speaker 1: up and it's some haven't come down the Pike yet right, 225 00:11:52,360 --> 00:11:54,640 Speaker 1: it's gonna take some time for the semi connector shortage 226 00:11:54,920 --> 00:11:57,080 Speaker 1: to ease. You know that there's gonna be more demand 227 00:11:57,160 --> 00:11:59,920 Speaker 1: for sem reason things like autos and you know, tried 228 00:12:00,000 --> 00:12:04,440 Speaker 1: buying an auto, trying running a car right now, it's impossible. Um, 229 00:12:04,559 --> 00:12:06,080 Speaker 1: And so that's going to take some time for that 230 00:12:06,120 --> 00:12:09,559 Speaker 1: manufacturing supply chain to to to respond. And then if anything, 231 00:12:09,600 --> 00:12:11,680 Speaker 1: you go into next year, hey, maybe we are going 232 00:12:11,720 --> 00:12:14,880 Speaker 1: to swing on the other side over capacity and back 233 00:12:14,920 --> 00:12:18,480 Speaker 1: into the story of deflation and everything else that has 234 00:12:18,480 --> 00:12:22,760 Speaker 1: been such a technology lead thing through digitalization. So a 235 00:12:22,800 --> 00:12:27,360 Speaker 1: bit you know going on there. But um, to your point, Yeah, 236 00:12:27,360 --> 00:12:30,840 Speaker 1: if you look at the tenure yield on treasury that's 237 00:12:31,280 --> 00:12:33,040 Speaker 1: rolled up, you wouldn't have thought any of this has happened, 238 00:12:33,120 --> 00:12:37,880 Speaker 1: right back to the old big tech deflation type trade. Uh. 239 00:12:37,920 --> 00:12:40,600 Speaker 1: And you know, so there's no way of knowing exactly 240 00:12:40,600 --> 00:12:43,280 Speaker 1: what's gonna happen in the future. I would argue that 241 00:12:43,640 --> 00:12:47,120 Speaker 1: the longer term past is much more likely than the 242 00:12:47,200 --> 00:12:49,960 Speaker 1: more recent past that seems to be more temporary nature 243 00:12:50,040 --> 00:12:53,199 Speaker 1: due to pandemic related effects. Every time I hear the 244 00:12:53,240 --> 00:12:55,360 Speaker 1: word transy and I think of those old hoboes that 245 00:12:55,480 --> 00:12:57,480 Speaker 1: used to wander around with like the stick and the 246 00:12:57,600 --> 00:12:59,000 Speaker 1: and the bag on the end of the stick and 247 00:12:59,080 --> 00:13:00,760 Speaker 1: ride in the rails. Anyway, thats just me that that 248 00:13:00,880 --> 00:13:04,200 Speaker 1: that's neither that's neither here nor there. But Chris I 249 00:13:04,360 --> 00:13:06,920 Speaker 1: said something early on that I think is so important. 250 00:13:06,960 --> 00:13:12,200 Speaker 1: You know that there's so many different subsectors within technology UM. 251 00:13:12,240 --> 00:13:15,520 Speaker 1: You know, obviously they've tried to sort of break out, 252 00:13:15,559 --> 00:13:18,360 Speaker 1: you know, the the Amazons and the facebooks and the 253 00:13:18,360 --> 00:13:21,079 Speaker 1: Googles out of the main tech index and put them 254 00:13:21,080 --> 00:13:25,800 Speaker 1: in discretionary or communications. I think there's an argument to 255 00:13:25,840 --> 00:13:28,199 Speaker 1: be made that maybe the index providers could do that again, 256 00:13:28,480 --> 00:13:31,520 Speaker 1: maybe a couple of times, and break up hardware and whatever. 257 00:13:31,559 --> 00:13:37,440 Speaker 1: But specifically thinking about chip stocks, you know, the fascinating 258 00:13:37,440 --> 00:13:40,360 Speaker 1: thing to me is this shortage of chips this year 259 00:13:41,360 --> 00:13:45,120 Speaker 1: exposed the reality that basically every company, what company is 260 00:13:45,160 --> 00:13:48,240 Speaker 1: not at at its core somehow exposed the tech these days. 261 00:13:48,280 --> 00:13:50,840 Speaker 1: I mean, if you can't, if you can't build up 262 00:13:50,880 --> 00:13:54,600 Speaker 1: an automobile without the supply of chips, uh, you know, 263 00:13:55,400 --> 00:13:57,760 Speaker 1: it's just remarkable, and on up and down the line. 264 00:13:57,760 --> 00:14:02,480 Speaker 1: Financial companies UM are in large sense mostly technology companies. 265 00:14:02,520 --> 00:14:06,080 Speaker 1: These days, but specifically with chips. It's been such a 266 00:14:06,160 --> 00:14:10,080 Speaker 1: shocking year for the chip sector with these shortages and 267 00:14:10,120 --> 00:14:13,880 Speaker 1: the ripple effects caused by them. In your mind, does 268 00:14:13,920 --> 00:14:17,280 Speaker 1: it seem like like a sort of tipping point type 269 00:14:17,280 --> 00:14:19,960 Speaker 1: of event that will change the industry forever? In other words, 270 00:14:20,040 --> 00:14:22,560 Speaker 1: will we sort of get away from that just in 271 00:14:22,640 --> 00:14:25,920 Speaker 1: time type of manufacturing uh, that so many companies had 272 00:14:26,000 --> 00:14:30,840 Speaker 1: relied on. Uh? Can we actually expect some foundries in 273 00:14:30,880 --> 00:14:34,160 Speaker 1: the US at some point? I mean, and more companies 274 00:14:34,240 --> 00:14:37,280 Speaker 1: you know talking about you know, fabricating their own ships 275 00:14:37,360 --> 00:14:39,280 Speaker 1: or is that is that kind of a pipe dream? 276 00:14:39,320 --> 00:14:41,920 Speaker 1: I mean, it's so expensive to to to get into 277 00:14:41,960 --> 00:14:44,800 Speaker 1: that game. How do you see that all playing out? 278 00:14:44,960 --> 00:14:48,280 Speaker 1: Sort of as a long term effect of everything we've 279 00:14:48,280 --> 00:14:53,280 Speaker 1: seen in the past year. Yeah, on a longer term view, Um, 280 00:14:53,320 --> 00:14:56,280 Speaker 1: you know, I think over time there is that potential 281 00:14:56,960 --> 00:15:00,480 Speaker 1: that you do have a broader manufacturing footprint as it 282 00:15:00,520 --> 00:15:03,520 Speaker 1: becomes more strategic. But to your point, it's easier said 283 00:15:03,520 --> 00:15:06,400 Speaker 1: than done, right, It's very it's only becoming more and 284 00:15:06,480 --> 00:15:10,840 Speaker 1: more and more expensive to manufacturers smaller and smaller chips, uh, 285 00:15:10,880 --> 00:15:13,600 Speaker 1: and certain transistors, and so if you look at how 286 00:15:13,680 --> 00:15:17,640 Speaker 1: someone like Taiwan Semiconductor. It's also holding of ours has 287 00:15:17,720 --> 00:15:20,760 Speaker 1: become so dominant. Uh, it's in part because of these 288 00:15:20,760 --> 00:15:24,040 Speaker 1: economies of scale that a crew and the expertise for 289 00:15:24,080 --> 00:15:26,680 Speaker 1: them operating this foundry model, which if you go way 290 00:15:26,680 --> 00:15:30,440 Speaker 1: back when companies used to produce their own chips here 291 00:15:30,440 --> 00:15:32,840 Speaker 1: in the US for example, UH, and then they decided 292 00:15:32,880 --> 00:15:35,440 Speaker 1: to outsource them. Why they outsource them because of the 293 00:15:35,520 --> 00:15:40,560 Speaker 1: volatility in cycles made it very costly endeavor for them 294 00:15:40,600 --> 00:15:43,040 Speaker 1: to predict. So you you would bear the brunt of 295 00:15:43,080 --> 00:15:45,000 Speaker 1: all this capital expenditure and then a few time the 296 00:15:45,040 --> 00:15:47,720 Speaker 1: cycle wrong, you take the financial hit. So working with 297 00:15:47,760 --> 00:15:51,160 Speaker 1: someone like a Time one semiconductor outsourcing that manufacturing, that 298 00:15:51,240 --> 00:15:53,840 Speaker 1: company is able to now diversify across all the different 299 00:15:53,880 --> 00:15:56,440 Speaker 1: end markets and their customers that they have, and they 300 00:15:56,440 --> 00:15:59,760 Speaker 1: could soften the blow and run much more profitable model 301 00:15:59,760 --> 00:16:02,160 Speaker 1: over time that allows them to continue investing in cathotics 302 00:16:02,160 --> 00:16:04,920 Speaker 1: and so on and so forth. Um, So you know, 303 00:16:05,000 --> 00:16:07,200 Speaker 1: I think you're they're going to try to there's certainly 304 00:16:07,200 --> 00:16:09,640 Speaker 1: more government incentives to try to do for them to 305 00:16:10,160 --> 00:16:13,760 Speaker 1: manufacture elsewhere, whether it's in the US. Europe is also 306 00:16:13,840 --> 00:16:16,680 Speaker 1: talking the same type of thing. What does it change 307 00:16:16,760 --> 00:16:20,600 Speaker 1: longer term. I'm not sure it changes too much. Um. 308 00:16:20,640 --> 00:16:22,000 Speaker 1: I think at the end of the day comes back 309 00:16:22,080 --> 00:16:26,360 Speaker 1: to industry structure. Yeah, it comes back to you know, 310 00:16:26,400 --> 00:16:29,360 Speaker 1: who are the who. I think you're seeing more customization 311 00:16:29,760 --> 00:16:32,680 Speaker 1: and chips for things like artificial intelligence, Google design their 312 00:16:32,680 --> 00:16:36,400 Speaker 1: own ships, Amazon, Apple, and that only fragments the end market, 313 00:16:36,400 --> 00:16:39,840 Speaker 1: which gives more strength to the end manufacturer at the 314 00:16:39,920 --> 00:16:59,400 Speaker 1: end of the day. Yeah, Chris, I wanted to ask 315 00:16:59,400 --> 00:17:01,160 Speaker 1: you about small caps. I know one of the funds 316 00:17:01,160 --> 00:17:03,480 Speaker 1: you helped manage is A is a small cap fund, 317 00:17:03,640 --> 00:17:06,040 Speaker 1: and we talk about the rugs sort of getting pulled 318 00:17:06,040 --> 00:17:08,960 Speaker 1: out of that as an asset class. Um. You know, 319 00:17:08,960 --> 00:17:10,960 Speaker 1: it was supposed to be one of the big beneficiaries 320 00:17:11,200 --> 00:17:16,159 Speaker 1: of the reopening, the reflation trade, and that's kind of uh, 321 00:17:16,359 --> 00:17:19,200 Speaker 1: you know, the that's kind of turned around. I mean, 322 00:17:19,200 --> 00:17:24,320 Speaker 1: I guess, um, when you're an active manager, it's arguably 323 00:17:24,320 --> 00:17:27,560 Speaker 1: easier to to navigate than when you know you're buying 324 00:17:27,640 --> 00:17:31,400 Speaker 1: just the two thousand index, the Russell two thousand index. Um. 325 00:17:31,600 --> 00:17:34,960 Speaker 1: But what is your thinking about small caps as an 326 00:17:34,960 --> 00:17:37,119 Speaker 1: asset class right now? I mean where how are you 327 00:17:37,160 --> 00:17:41,200 Speaker 1: sort of sifting through everything and finding finding the best, 328 00:17:41,280 --> 00:17:45,600 Speaker 1: most promising companies given this turnaround we've seen in the 329 00:17:45,600 --> 00:17:51,480 Speaker 1: the index level small cap situation. Yeah, so if anything, so, yeah, 330 00:17:51,560 --> 00:17:54,520 Speaker 1: it's an interesting environment for us as being more growth 331 00:17:54,560 --> 00:18:00,440 Speaker 1: for focused Uh, the headwind that the effects value simpall 332 00:18:00,520 --> 00:18:03,840 Speaker 1: cap value in particular was outperforming growth by a wide 333 00:18:03,840 --> 00:18:08,480 Speaker 1: margin um and so we benefited from the growth tail 334 00:18:08,560 --> 00:18:10,479 Speaker 1: end last year and then we're suffering a little bit 335 00:18:10,480 --> 00:18:12,960 Speaker 1: from it this year. So the fact you know, seeing 336 00:18:13,000 --> 00:18:15,960 Speaker 1: somewhere all over, we're not complaining too much about that, 337 00:18:16,040 --> 00:18:19,480 Speaker 1: but as that's happened, it's given us opportunities to look at, 338 00:18:19,920 --> 00:18:22,560 Speaker 1: you know, smaller growth companies that have been left behind. 339 00:18:22,880 --> 00:18:25,399 Speaker 1: Like one of the areas that's kind of interesting is 340 00:18:26,200 --> 00:18:30,760 Speaker 1: us specialty retail. There's a lot of talk that you know, 341 00:18:30,800 --> 00:18:33,159 Speaker 1: it's just an Amazon world. It's all e commerce, right, 342 00:18:33,160 --> 00:18:36,479 Speaker 1: And there's some small companies or smaller companies that are 343 00:18:36,520 --> 00:18:39,080 Speaker 1: interesting that we own in the in the all cap fund, 344 00:18:39,720 --> 00:18:41,520 Speaker 1: like an Etsy for example, that used to be a 345 00:18:41,520 --> 00:18:44,080 Speaker 1: small cap and now it's no longer. But there are 346 00:18:44,119 --> 00:18:47,840 Speaker 1: brick and mortar retailers that are doing okay in this environment. 347 00:18:47,880 --> 00:18:51,000 Speaker 1: They're managing that, they're growing their stores, they are taking 348 00:18:51,040 --> 00:18:54,520 Speaker 1: advantage of the disruption from the pandemic and the weak 349 00:18:54,640 --> 00:18:59,359 Speaker 1: weaker financial strength of competitors to acquire more land and 350 00:18:59,440 --> 00:19:02,520 Speaker 1: real estate and build and so some examples companies that 351 00:19:02,560 --> 00:19:07,280 Speaker 1: are doing that. Company Ali's allis discount retail. They're growing 352 00:19:07,320 --> 00:19:10,800 Speaker 1: their stores year every year. UM. They've actually been able 353 00:19:10,800 --> 00:19:13,680 Speaker 1: to They have this discount model where you know, people 354 00:19:13,680 --> 00:19:15,359 Speaker 1: are always still there's a really there's a reason to 355 00:19:15,440 --> 00:19:19,760 Speaker 1: visit the store every day. They have a loyalty system UM, 356 00:19:19,800 --> 00:19:21,439 Speaker 1: and so they've been able to grow their customers in 357 00:19:21,480 --> 00:19:24,840 Speaker 1: part because through the pandemic they've were able to sell 358 00:19:24,960 --> 00:19:28,720 Speaker 1: more UM essential items, cleaning products and so on, but 359 00:19:28,760 --> 00:19:30,880 Speaker 1: they offer other things and so they have a good 360 00:19:30,880 --> 00:19:32,560 Speaker 1: buying that we're kind of like a small t J 361 00:19:32,760 --> 00:19:36,560 Speaker 1: mat Max if you will. UM. Another one is five below, 362 00:19:37,160 --> 00:19:42,480 Speaker 1: this little niche targeting that teenage tween type segment with 363 00:19:42,600 --> 00:19:46,040 Speaker 1: quirky different things at a reason you know, but at 364 00:19:46,280 --> 00:19:49,199 Speaker 1: they're occupying this niche that is something that people go 365 00:19:49,280 --> 00:19:52,879 Speaker 1: for that experience and it's not an Amazon type world. 366 00:19:53,280 --> 00:19:55,600 Speaker 1: It's a different type of buyer and people look forward 367 00:19:55,600 --> 00:19:57,679 Speaker 1: to going to that store. And they've been able to 368 00:19:57,680 --> 00:20:01,359 Speaker 1: survive and then thrive through it too, So you know 369 00:20:01,400 --> 00:20:04,280 Speaker 1: the answer to your question is just being very careful 370 00:20:04,400 --> 00:20:07,840 Speaker 1: looking for insisting very strongly on that financial strength because 371 00:20:07,880 --> 00:20:10,439 Speaker 1: we don't know when there's going to be cyclical changes, 372 00:20:10,800 --> 00:20:13,000 Speaker 1: but we want to make sure, particularly as a smaller company, 373 00:20:13,280 --> 00:20:15,120 Speaker 1: you've got that margin of safety that you know they're 374 00:20:15,160 --> 00:20:18,080 Speaker 1: going to come out from it stronger and take advantage. 375 00:20:18,080 --> 00:20:20,080 Speaker 1: And some of those retailers. I think that's an interesting 376 00:20:20,480 --> 00:20:22,760 Speaker 1: area that you know, in the world everyone just think 377 00:20:22,880 --> 00:20:25,119 Speaker 1: is about bigger and better in e commerce, there's some 378 00:20:25,160 --> 00:20:29,080 Speaker 1: companies that are growing with financial strength in retail. Yeah. 379 00:20:29,200 --> 00:20:31,520 Speaker 1: As a father of three daughters, well done, I'm very 380 00:20:31,560 --> 00:20:35,600 Speaker 1: familiar with five below. I uh, A lot of disposable 381 00:20:35,600 --> 00:20:38,680 Speaker 1: income gets dumped into that place. It's remarkable though, that 382 00:20:38,800 --> 00:20:41,879 Speaker 1: is talk about it. Impulse purchase Meca. You know, I 383 00:20:41,960 --> 00:20:44,159 Speaker 1: found myself buying, you know, going in there, taking a 384 00:20:44,200 --> 00:20:46,680 Speaker 1: kid there to get some art supplies or whatever, and 385 00:20:46,680 --> 00:20:50,480 Speaker 1: and finding myself some impulse fights some stuff that. Actually, 386 00:20:50,680 --> 00:20:52,800 Speaker 1: that's how I feel about t J Max, which you 387 00:20:52,880 --> 00:20:56,560 Speaker 1: just mentioned, and one of their other brands is Marshals, 388 00:20:56,600 --> 00:20:59,040 Speaker 1: which I feel like I could go there every day 389 00:20:59,080 --> 00:21:03,119 Speaker 1: and just buy like millions of things I have absolutely 390 00:21:03,160 --> 00:21:07,080 Speaker 1: no use for I'm one of those I'm one of 391 00:21:07,080 --> 00:21:09,680 Speaker 1: those consumers. I could tell you. I mean, you may 392 00:21:09,720 --> 00:21:12,320 Speaker 1: attest when you know things start to reopen. Last year, 393 00:21:12,600 --> 00:21:14,879 Speaker 1: there were lines out the door and around the corner 394 00:21:14,880 --> 00:21:16,600 Speaker 1: to get back into t J Max. And that just 395 00:21:17,000 --> 00:21:19,200 Speaker 1: we have this debate all the time about the pandemic 396 00:21:19,280 --> 00:21:21,879 Speaker 1: and where the lasting changes. Where are the new habits 397 00:21:21,920 --> 00:21:23,280 Speaker 1: that are going to be formed, and where are the 398 00:21:23,280 --> 00:21:25,399 Speaker 1: old ones? And it just goes to show you that 399 00:21:25,440 --> 00:21:27,600 Speaker 1: even though a lot of us are spending more on 400 00:21:27,640 --> 00:21:30,399 Speaker 1: e commerce, there's certain experiences that we want to have 401 00:21:30,440 --> 00:21:33,920 Speaker 1: in person that just come back, whether it's travel or 402 00:21:34,000 --> 00:21:36,040 Speaker 1: you know, or or or going to a t J 403 00:21:36,200 --> 00:21:39,639 Speaker 1: Max for example. It's it's a good point about Etsy 404 00:21:39,720 --> 00:21:42,000 Speaker 1: graduating out of the small cap space. It must be 405 00:21:42,119 --> 00:21:44,320 Speaker 1: a little frustrating when you when you run a small 406 00:21:44,359 --> 00:21:46,840 Speaker 1: cap fund too, to pick a great stock and then 407 00:21:46,880 --> 00:21:49,520 Speaker 1: watch it sort of graduate out of your out of 408 00:21:49,520 --> 00:21:53,240 Speaker 1: your benchmark, Like I did everything right? Stay, why can't 409 00:21:53,240 --> 00:21:54,960 Speaker 1: I keep this stock in the fun But I guess 410 00:21:55,040 --> 00:21:57,520 Speaker 1: that's how it works. Yeah, we have we try to 411 00:21:57,560 --> 00:21:59,639 Speaker 1: take into that into account. We we do give a 412 00:21:59,640 --> 00:22:02,440 Speaker 1: little bit a leeway so we could sell it intelligently, 413 00:22:02,560 --> 00:22:05,240 Speaker 1: and sometimes it helps us that discipline for something that 414 00:22:05,320 --> 00:22:07,760 Speaker 1: is overvalued too. So you know, we just have to 415 00:22:07,840 --> 00:22:10,720 Speaker 1: keep keep at it, and there's longer term opportunities, and 416 00:22:10,720 --> 00:22:14,639 Speaker 1: that smaller cap UH focus gives that opportunity for the 417 00:22:15,480 --> 00:22:18,439 Speaker 1: customers that are interested in that to diversify their portfolios. 418 00:22:18,680 --> 00:22:21,080 Speaker 1: So it's not just all things right, it's a way 419 00:22:21,080 --> 00:22:23,959 Speaker 1: to differentiate yourself and get diverse returns. I feel like 420 00:22:24,000 --> 00:22:26,560 Speaker 1: the through line here really is consumer behavior and what 421 00:22:26,600 --> 00:22:29,080 Speaker 1: the consumers thinking and doing. And one of the things 422 00:22:29,080 --> 00:22:31,560 Speaker 1: that I had noticed this week is a lot of 423 00:22:31,640 --> 00:22:34,000 Speaker 1: the research notes that that I was reading more mentioning 424 00:22:34,000 --> 00:22:38,200 Speaker 1: mobility data, and people are still going out to restaurants. 425 00:22:38,359 --> 00:22:42,040 Speaker 1: There's still foot traffic, you know, any of these measurements 426 00:22:42,080 --> 00:22:45,640 Speaker 1: Apple mobility data, people out on the road, and it's 427 00:22:45,680 --> 00:22:47,760 Speaker 1: actually holding up really well. And I'm wondering if you 428 00:22:47,880 --> 00:22:51,359 Speaker 1: and Chris, you and your team also look at some 429 00:22:51,400 --> 00:22:56,080 Speaker 1: of these so called real time data to UH to 430 00:22:56,680 --> 00:23:01,920 Speaker 1: inform your strategy. Yeah, because you know, it's information that's 431 00:23:01,960 --> 00:23:04,600 Speaker 1: out there, we look at it. UM. I think the 432 00:23:04,640 --> 00:23:06,439 Speaker 1: big thing here is I don't think we necessarily have 433 00:23:06,480 --> 00:23:09,000 Speaker 1: any particular edge from looking at that that's a that's 434 00:23:09,080 --> 00:23:11,280 Speaker 1: that's data that's out there. I think it's much more 435 00:23:11,320 --> 00:23:14,320 Speaker 1: about interpretation and what we're going to do. So it's 436 00:23:14,400 --> 00:23:17,480 Speaker 1: much more about understanding. To this extent, it can inform 437 00:23:17,560 --> 00:23:19,960 Speaker 1: us of longer term trends or longer term debates that 438 00:23:20,000 --> 00:23:23,480 Speaker 1: we could have. Okay, the mobility data says this, is 439 00:23:23,520 --> 00:23:26,560 Speaker 1: there anything here that that that pretends to something that 440 00:23:26,560 --> 00:23:28,359 Speaker 1: could be extrapolated in a longer term or is this 441 00:23:28,440 --> 00:23:31,240 Speaker 1: just a short term deal? Right? And so to extend 442 00:23:31,280 --> 00:23:33,920 Speaker 1: it could help you time things a little bit, sure, 443 00:23:34,080 --> 00:23:36,320 Speaker 1: but on a longer term three to five year view, 444 00:23:36,800 --> 00:23:39,280 Speaker 1: we're not doing too much of that. If the T 445 00:23:39,440 --> 00:23:42,199 Speaker 1: s A numbers go down, we're not, you know, going 446 00:23:42,240 --> 00:23:44,280 Speaker 1: to be dumping one way or another. I think it's 447 00:23:44,359 --> 00:23:47,800 Speaker 1: much more about, Okay, is there value in this sector? 448 00:23:47,920 --> 00:23:50,720 Speaker 1: Is there value in this industry? Okay? If there's a 449 00:23:50,760 --> 00:23:55,080 Speaker 1: short term transient effect, okay, that's an opportunity for us 450 00:23:55,080 --> 00:23:56,960 Speaker 1: to add on a longer term view, provide the company's 451 00:23:56,960 --> 00:24:01,800 Speaker 1: got financial strength, good management, longer term growth opportunities. So yeah, 452 00:24:01,840 --> 00:24:03,639 Speaker 1: we look at it, but it's not it doesn't inform 453 00:24:03,680 --> 00:24:07,119 Speaker 1: what we do. Stand clear of the craziest things we 454 00:24:07,200 --> 00:24:10,960 Speaker 1: saw in markets this week. All right, guys, you know 455 00:24:11,000 --> 00:24:14,199 Speaker 1: you both represented New Jersey very well this week. We 456 00:24:14,240 --> 00:24:17,720 Speaker 1: didn't even talk about what everyone's favorite boardwalk is yet, 457 00:24:17,760 --> 00:24:19,520 Speaker 1: but I think we'll have to save that for the 458 00:24:19,560 --> 00:24:22,320 Speaker 1: next time because we have to talk about the crazy 459 00:24:22,400 --> 00:24:25,040 Speaker 1: things Bill Donna. As you know well, Donna is our 460 00:24:25,119 --> 00:24:29,000 Speaker 1: chief crazy things correspondent, Chris Um. But I kind of 461 00:24:29,440 --> 00:24:32,000 Speaker 1: we'll talk after the show about the best boardwalks I've got, 462 00:24:32,160 --> 00:24:34,919 Speaker 1: I've got, I've got some serious thought on that. I 463 00:24:34,960 --> 00:24:37,639 Speaker 1: don't want to tell you my favorite because the beach 464 00:24:37,720 --> 00:24:40,520 Speaker 1: we go to is actually really quiet and not that 465 00:24:40,600 --> 00:24:42,480 Speaker 1: many people go to it, and I don't want to 466 00:24:42,560 --> 00:24:48,160 Speaker 1: ruin that you're hoarding it off yourself. That's uh, the 467 00:24:48,200 --> 00:24:50,960 Speaker 1: beach scarcity issue is is a big deal in New Jersey. 468 00:24:50,960 --> 00:24:53,359 Speaker 1: All Right. I can respect that, but you do have 469 00:24:53,400 --> 00:24:55,280 Speaker 1: to share your crazy thing, Bill don and I hyped 470 00:24:55,320 --> 00:24:57,000 Speaker 1: you up, so I want you to go first. What's 471 00:24:57,000 --> 00:24:59,359 Speaker 1: the craziest thing you saw in markets this week? Well, 472 00:24:59,400 --> 00:25:01,639 Speaker 1: I think a lot of listeners might remember that the 473 00:25:01,720 --> 00:25:03,520 Speaker 1: last time I was on the pod, we talked about 474 00:25:03,520 --> 00:25:07,359 Speaker 1: something that was happening in space in terms of astronauts 475 00:25:07,440 --> 00:25:10,320 Speaker 1: doing laundry. In space and so I'm revisiting that same 476 00:25:10,359 --> 00:25:14,040 Speaker 1: theme this week, and Bloomberg had a story that caught 477 00:25:14,080 --> 00:25:16,800 Speaker 1: my eye. It's a company called I Space. It's a 478 00:25:16,800 --> 00:25:20,679 Speaker 1: Tokyo based space startup, and it's planning its first trip 479 00:25:20,720 --> 00:25:23,440 Speaker 1: to the Moon next year. It raised forty six million 480 00:25:23,440 --> 00:25:27,280 Speaker 1: dollars from Japanese investors to help bancrol those missions. So 481 00:25:27,640 --> 00:25:30,080 Speaker 1: I feel like there's a lot happening with with space 482 00:25:30,160 --> 00:25:34,240 Speaker 1: and all of the billionaires visiting space, and uh, that 483 00:25:34,320 --> 00:25:37,040 Speaker 1: one was interesting to me. Are they going to put 484 00:25:37,080 --> 00:25:39,240 Speaker 1: an actual person on the Moon? Are they just going 485 00:25:39,320 --> 00:25:42,000 Speaker 1: to drop a little robot or something there? Oh, I'm 486 00:25:42,000 --> 00:25:44,600 Speaker 1: not sure. Actually that's a good question. Probably robot. I 487 00:25:44,600 --> 00:25:46,840 Speaker 1: think we would hear about it as a person. Look, 488 00:25:46,880 --> 00:25:48,760 Speaker 1: I'm not one of those people that says the moon 489 00:25:48,880 --> 00:25:51,560 Speaker 1: landing was staged, But I'm also like, how come no 490 00:25:51,600 --> 00:25:53,919 Speaker 1: one else has landed on the moon? Human? What's going on? 491 00:25:54,240 --> 00:25:56,320 Speaker 1: You know you're not one of those people, but yet 492 00:25:56,400 --> 00:25:58,560 Speaker 1: you are. Yah? Yeah, I guess I guess that's my 493 00:25:58,640 --> 00:26:02,600 Speaker 1: tough Maybe bezo us for uh where Richard Brents and 494 00:26:02,840 --> 00:26:05,800 Speaker 1: we'll be up there these as will drop like an 495 00:26:05,800 --> 00:26:09,440 Speaker 1: Amazon flag on the moon something. But all right, Chris, 496 00:26:09,440 --> 00:26:13,359 Speaker 1: that one's pretty good, But can you beat a moon landing? 497 00:26:13,800 --> 00:26:16,600 Speaker 1: As I don't know. I feel like this whole year 498 00:26:16,720 --> 00:26:19,480 Speaker 1: is just full of crazy things, right, whether it's n 499 00:26:19,520 --> 00:26:22,520 Speaker 1: f T S and crypto and everything else or set 500 00:26:22,560 --> 00:26:25,040 Speaker 1: you know, Bezos going to the moon or not the 501 00:26:25,080 --> 00:26:28,160 Speaker 1: moon going into our space on like this odd shaped 502 00:26:28,280 --> 00:26:32,440 Speaker 1: rocket that you know, is there's so much that's like fiction, 503 00:26:32,480 --> 00:26:36,800 Speaker 1: that's that's reality, that's true. Um so you know, or 504 00:26:36,880 --> 00:26:39,920 Speaker 1: like the spot and the special for Atlas special purpose 505 00:26:40,000 --> 00:26:42,240 Speaker 1: Entities and everything that's going on. But I'll go it's 506 00:26:42,280 --> 00:26:44,400 Speaker 1: something that's a little bit you know, maybe less crazy 507 00:26:44,480 --> 00:26:47,200 Speaker 1: and just more interesting to me, which is just I 508 00:26:47,200 --> 00:26:49,439 Speaker 1: think you alluded to at the beginning of the of 509 00:26:49,520 --> 00:26:53,360 Speaker 1: the show, which is just this the healthcare tech thing, 510 00:26:54,240 --> 00:26:57,440 Speaker 1: which is just the fact that, um, you know, I 511 00:26:57,480 --> 00:27:01,040 Speaker 1: think everyone thinks about them together in this environment. And 512 00:27:01,040 --> 00:27:02,880 Speaker 1: I would notice that if you go past the past 513 00:27:02,880 --> 00:27:05,919 Speaker 1: earning season, there's been a little bit of decoupling between 514 00:27:05,960 --> 00:27:09,000 Speaker 1: tech reaction and health care reaction. And maybe that's the 515 00:27:09,000 --> 00:27:11,240 Speaker 1: market trying to tell us that the pandemic this is 516 00:27:11,280 --> 00:27:13,239 Speaker 1: the crazy thing. You know, maybe we should be all 517 00:27:13,240 --> 00:27:15,000 Speaker 1: worried that the pandemic is going to get a lot 518 00:27:15,040 --> 00:27:17,800 Speaker 1: worse again, and I think you certainly put that through there. 519 00:27:17,840 --> 00:27:20,000 Speaker 1: And so it's interesting how the market tries to anticipate 520 00:27:20,080 --> 00:27:22,040 Speaker 1: these things and you go back and you say, yeah, 521 00:27:22,040 --> 00:27:23,840 Speaker 1: they really got it. And so now this makes me 522 00:27:23,880 --> 00:27:28,040 Speaker 1: nervous of it for the future just in general. But 523 00:27:28,080 --> 00:27:31,359 Speaker 1: it seems like there's no appetite for lockdowns, which is 524 00:27:31,400 --> 00:27:33,600 Speaker 1: why the tech companies aren't doing better. It's much more 525 00:27:33,640 --> 00:27:37,520 Speaker 1: about more tests and innovation there. So yeah, no, that 526 00:27:37,600 --> 00:27:39,160 Speaker 1: makes a lot of sense to read it that way. 527 00:27:39,200 --> 00:27:40,840 Speaker 1: You know, we're not gonna be stuck at home, but 528 00:27:40,960 --> 00:27:42,720 Speaker 1: we're still going to be dealing with this thing for 529 00:27:42,720 --> 00:27:46,679 Speaker 1: for a long time. That's pretty good. Um and and 530 00:27:46,760 --> 00:27:48,760 Speaker 1: sad and scary. That might be the scariest thing of 531 00:27:48,800 --> 00:27:52,240 Speaker 1: the week as well. Well done, Chris, crazy and scared, 532 00:27:53,720 --> 00:27:56,560 Speaker 1: crazy and scary is dangerous. Smikes. Sorry, I got I 533 00:27:56,560 --> 00:27:59,360 Speaker 1: got a good one for us to end on. Um 534 00:27:59,400 --> 00:28:02,719 Speaker 1: and it's from the the Pressure Precious Metals Asset class 535 00:28:02,920 --> 00:28:06,480 Speaker 1: And uh, well, Donna, you know there's a joke that 536 00:28:06,600 --> 00:28:08,600 Speaker 1: if someone if you're walking in New York and someone 537 00:28:08,680 --> 00:28:10,480 Speaker 1: comes up to you and says, hey, do you know 538 00:28:10,520 --> 00:28:12,919 Speaker 1: how I can get to Carnegie Hall. You know what 539 00:28:12,960 --> 00:28:18,600 Speaker 1: you're supposed to say, no practice, practice, practice, Do you 540 00:28:18,640 --> 00:28:21,639 Speaker 1: get it? Yeah? Yeah, I can tell you're dying with 541 00:28:21,720 --> 00:28:23,320 Speaker 1: laughter on that one. It's an old joke and you 542 00:28:23,400 --> 00:28:26,760 Speaker 1: got to know these jokes though, all right, so it's 543 00:28:26,760 --> 00:28:29,760 Speaker 1: so hilarious. But I would ask, how do you get 544 00:28:29,800 --> 00:28:34,400 Speaker 1: a gold medal in the Olympics? You take your phone 545 00:28:34,400 --> 00:28:39,160 Speaker 1: apart and you melt all the little pieceles. That's pretty good. 546 00:28:39,280 --> 00:28:41,400 Speaker 1: That is how they did it actually, Or you could 547 00:28:41,440 --> 00:28:44,960 Speaker 1: say practice, practice practice again. Another way you can get one. 548 00:28:45,320 --> 00:28:47,960 Speaker 1: Just buy one from an auction house, which I think 549 00:28:48,080 --> 00:28:50,240 Speaker 1: is almost a bigger flex like you, you know, you 550 00:28:50,280 --> 00:28:53,000 Speaker 1: wear that thing to work, you know, And people would 551 00:28:53,000 --> 00:28:54,400 Speaker 1: be like, well, Donna, did you did you win a 552 00:28:54,400 --> 00:28:55,880 Speaker 1: gold medal in the Olympics, and be like, no, I 553 00:28:56,000 --> 00:28:59,360 Speaker 1: bought one. I'm not. I'm that type of players. So 554 00:28:59,360 --> 00:29:01,680 Speaker 1: there's an auction in house that has been selling some 555 00:29:01,720 --> 00:29:05,920 Speaker 1: Olympic medals and Chris, this might catch you as a surprise, 556 00:29:05,960 --> 00:29:08,280 Speaker 1: but will Don will know it's now time to play 557 00:29:08,320 --> 00:29:11,200 Speaker 1: prices right with the craziest things. And this is courtesy 558 00:29:11,240 --> 00:29:14,640 Speaker 1: of the New York Times. Um they are writing about 559 00:29:14,760 --> 00:29:18,640 Speaker 1: the aftermarket for Olympic medals. Some of them are pretty cheap, 560 00:29:18,680 --> 00:29:21,920 Speaker 1: I gotta say, cheaper than you would expect. But I'm 561 00:29:21,920 --> 00:29:24,240 Speaker 1: want to give you one that is sort of the 562 00:29:24,240 --> 00:29:27,640 Speaker 1: the gold medal of Olympic aftermarket medals, if you will. 563 00:29:27,680 --> 00:29:32,160 Speaker 1: It's actually a silver medal um from the first modern 564 00:29:32,160 --> 00:29:36,720 Speaker 1: Olympic Games in Athens. In here's what you need to 565 00:29:36,720 --> 00:29:39,600 Speaker 1: know then. Back then, first place was a silver medal. 566 00:29:39,640 --> 00:29:41,800 Speaker 1: There was no gold medal yet if you wont you 567 00:29:41,840 --> 00:29:45,120 Speaker 1: got a silver. So this is first place silver medal 568 00:29:46,040 --> 00:29:53,600 Speaker 1: eight Athens Olympics. So two part question for each of you, will, Donna, 569 00:29:53,920 --> 00:29:57,040 Speaker 1: what's your bid for that medal? And two? Would you 570 00:29:57,080 --> 00:30:00,480 Speaker 1: wear it to work? I would not wear to work, 571 00:30:00,760 --> 00:30:04,560 Speaker 1: but I'm going to guess thirty six thousand dollars thirty 572 00:30:04,600 --> 00:30:07,600 Speaker 1: six thousand dollars. Sorry, I'm keeping a poker face. Chris, 573 00:30:07,960 --> 00:30:11,920 Speaker 1: what's your bid for an eighteen ninety six silver first 574 00:30:11,920 --> 00:30:17,240 Speaker 1: place medal Athens Olympics, very first Olympics. I'm not sure. 575 00:30:17,560 --> 00:30:19,440 Speaker 1: Let me figure out what what event it was. I'm 576 00:30:19,480 --> 00:30:21,560 Speaker 1: not even sure what event it was, but I guess 577 00:30:21,560 --> 00:30:24,560 Speaker 1: it doesn't matter. Yeah, I think she outbids me. I 578 00:30:24,560 --> 00:30:26,080 Speaker 1: was gonna I mean I would bid a lot, maybe 579 00:30:26,080 --> 00:30:29,080 Speaker 1: twenty thousand, but yeah, she outbids me, so I lose 580 00:30:29,120 --> 00:30:32,800 Speaker 1: that auction. You're you're taking the under taking. Yeah, I'm 581 00:30:32,800 --> 00:30:35,040 Speaker 1: taking a little bit under But maybe I don't know. 582 00:30:35,120 --> 00:30:38,760 Speaker 1: I think it depends at the size of this medal, right, 583 00:30:39,040 --> 00:30:41,440 Speaker 1: I can't think it was too gigantic, although there probably 584 00:30:41,480 --> 00:30:44,800 Speaker 1: was more silver content in today right into today. Stay, 585 00:30:44,840 --> 00:30:47,720 Speaker 1: today's medals barely have anything in it. Yeah, you're probably 586 00:30:47,760 --> 00:30:50,800 Speaker 1: some value to it. This is a true value investor here. 587 00:30:50,840 --> 00:30:53,360 Speaker 1: He wants to know the meltdown value of the Olympic 588 00:30:53,440 --> 00:30:58,920 Speaker 1: medal from no collectors mark up. For Chris, it's about 589 00:30:58,920 --> 00:31:00,920 Speaker 1: the bragging though. I do you have to have that collection? 590 00:31:00,960 --> 00:31:03,760 Speaker 1: I don't know, but I can't think it's gigantic though. Well, 591 00:31:03,800 --> 00:31:06,280 Speaker 1: and the one outside. It would be hard to trick 592 00:31:06,360 --> 00:31:10,360 Speaker 1: anyone into believing that you won a medal in the Olympics. 593 00:31:10,360 --> 00:31:13,400 Speaker 1: I mean maybe I might have a better Yeah that 594 00:31:13,440 --> 00:31:15,200 Speaker 1: thanks that. I know. I set you up for that one. 595 00:31:15,240 --> 00:31:20,080 Speaker 1: Thank you anyway. Boston based auction house are our auctions 596 00:31:20,320 --> 00:31:23,640 Speaker 1: one hundred and eighty thousand dollars one hundred and eleven 597 00:31:23,720 --> 00:31:29,800 Speaker 1: one eighty thousand, one hundred eleven dollars. Pretty good. Yeah, 598 00:31:30,080 --> 00:31:34,000 Speaker 1: I get the medal. Well, Mike, you didn't you didn't 599 00:31:34,000 --> 00:31:38,800 Speaker 1: tell us which Olympic event you'd be participating in. Oh, hoops, 600 00:31:38,840 --> 00:31:43,320 Speaker 1: come on, okay, hoops. Not that I would ever the 601 00:31:43,360 --> 00:31:45,800 Speaker 1: only sport, the only Olympic type of sport I really play, 602 00:31:45,800 --> 00:31:48,440 Speaker 1: although mountain bikings in now, I might be able to, uh, 603 00:31:48,720 --> 00:31:50,280 Speaker 1: I might be able to pry have a better shot 604 00:31:50,280 --> 00:31:52,560 Speaker 1: a qualifying for that than hoops at at this age 605 00:31:52,920 --> 00:31:55,440 Speaker 1: or at any age. But you're you're a hundred and 606 00:31:55,520 --> 00:32:01,320 Speaker 1: thirty year old age. Yes, exactly exactly, but some bargains 607 00:32:01,360 --> 00:32:03,880 Speaker 1: on some other medals. According to the Times, silver medal 608 00:32:04,000 --> 00:32:07,360 Speaker 1: and shooting from the nineteen hundred Olympics in Paris only 609 00:32:07,360 --> 00:32:15,440 Speaker 1: twelve bucks and uh nine winner games in Italy. Uh so, 610 00:32:15,480 --> 00:32:17,480 Speaker 1: but that I think it's the it's the value of 611 00:32:17,480 --> 00:32:21,320 Speaker 1: that first Olympics that that makes it. And they don't 612 00:32:21,320 --> 00:32:22,960 Speaker 1: talk about the ancient Olympics. I don't know if there's 613 00:32:22,960 --> 00:32:24,840 Speaker 1: any medals available for that that that would be the 614 00:32:24,880 --> 00:32:28,480 Speaker 1: big flex. I guess all right, pull down. Well, I 615 00:32:28,480 --> 00:32:30,160 Speaker 1: can't believe you wouldn't wear it's work though I would 616 00:32:30,200 --> 00:32:33,520 Speaker 1: totally wear that thing everywhere. I went, Really, I don't 617 00:32:33,520 --> 00:32:37,560 Speaker 1: see a reason to wear it though it's for the flex. Yeah, 618 00:32:37,600 --> 00:32:39,440 Speaker 1: I guess it depends on what state it's in, and 619 00:32:40,600 --> 00:32:43,560 Speaker 1: like Chris said, how large it is. Yeah, Chris would 620 00:32:43,560 --> 00:32:47,600 Speaker 1: wear if Laffiott ever wins a football championship, will where 621 00:32:47,840 --> 00:32:51,000 Speaker 1: he'll wear that around? I think? Yeah? No, I think 622 00:32:51,040 --> 00:32:52,720 Speaker 1: I probably least would wear or something like this for 623 00:32:52,760 --> 00:32:56,840 Speaker 1: a day. Yeah, just just for the effect, just for fun. Yeah, 624 00:32:56,920 --> 00:32:58,560 Speaker 1: you gotta show up to work for there, at least 625 00:32:58,560 --> 00:33:00,600 Speaker 1: on a zoom call. You know. I'd be wearing it 626 00:33:00,640 --> 00:33:03,560 Speaker 1: on a zoom call for sure. Oh what's that? Oh 627 00:33:03,600 --> 00:33:11,160 Speaker 1: that's my Olympic first place silver medal from anyway. Anyway, 628 00:33:11,240 --> 00:33:13,200 Speaker 1: great stuff this week, guys. I think that's all the 629 00:33:13,240 --> 00:33:16,800 Speaker 1: time we have really appreciated Chris mac Wildonna high Rich. 630 00:33:16,920 --> 00:33:19,920 Speaker 1: I hope we can do it again someday. Likewise, add fine, 631 00:33:20,000 --> 00:33:31,400 Speaker 1: thank you very much. What goes up, We'll be back 632 00:33:31,440 --> 00:33:33,640 Speaker 1: next week. That's so then you can find us on 633 00:33:33,680 --> 00:33:36,640 Speaker 1: the Bloomberg Terminal website and app or wherever you get 634 00:33:36,680 --> 00:33:39,320 Speaker 1: your podcasts. We'd love it if he took the time 635 00:33:39,360 --> 00:33:41,800 Speaker 1: to rate and review the show on Apple Podcasts so 636 00:33:41,880 --> 00:33:44,560 Speaker 1: more listeners can find us. And you can find us 637 00:33:44,600 --> 00:33:48,280 Speaker 1: on Twitter, follow me at Reaganonymous. Bildona high Rich is 638 00:33:48,360 --> 00:33:51,480 Speaker 1: at Bildona high Rich. You can also follow Bloomberg podcasts 639 00:33:51,520 --> 00:33:54,880 Speaker 1: at podcasts I Think You To, Charlie Pelletta, Bloomberg Radio, 640 00:33:54,920 --> 00:33:57,400 Speaker 1: and the voice of the New York City Subway System. 641 00:33:57,440 --> 00:33:59,760 Speaker 1: What Goes Up is produced by Toe for Foreheads. The 642 00:33:59,760 --> 00:34:03,680 Speaker 1: head Bloomberg podcast is Francesco Leady. Thanks for listening, See 643 00:34:03,680 --> 00:34:04,200 Speaker 1: you next time.