1 00:00:05,800 --> 00:00:08,720 Speaker 1: Welcome to the Bloomberg p m L Podcast. I'm pim Fox. 2 00:00:08,760 --> 00:00:11,520 Speaker 1: Along with my co host Lisa Bramowitz. Each day we 3 00:00:11,640 --> 00:00:15,120 Speaker 1: bring you the most important, noteworthy, and useful interviews for 4 00:00:15,200 --> 00:00:17,840 Speaker 1: you and your money, whether you're at the grocery store 5 00:00:17,960 --> 00:00:20,720 Speaker 1: or the trading floor. Find the Bloomberg p m L 6 00:00:20,840 --> 00:00:33,920 Speaker 1: Podcast on Apple Podcasts, SoundCloud, and Bloomberg dot com. Just 7 00:00:34,159 --> 00:00:37,880 Speaker 1: how at risk are you of having a flood? Well? 8 00:00:38,040 --> 00:00:41,640 Speaker 1: When it came to Hurricane Harvey, about forty percent of 9 00:00:41,680 --> 00:00:45,479 Speaker 1: the people who suffered damages of homeowners were outside of 10 00:00:45,560 --> 00:00:49,520 Speaker 1: the flood zone and did not have insurance through the 11 00:00:49,640 --> 00:00:53,080 Speaker 1: National Flood Insurance Program. Here to talk about how to 12 00:00:53,159 --> 00:00:56,160 Speaker 1: assess your risk of flooding and why it is important 13 00:00:56,160 --> 00:00:59,720 Speaker 1: to consider private insurance is Mark Aunky Larry uh CEO 14 00:00:59,880 --> 00:01:02,400 Speaker 1: of Various Analytics and I enjoy us here in our 15 00:01:02,400 --> 00:01:04,440 Speaker 1: Bloombrick eleven three our studios. So, first of all, what 16 00:01:04,560 --> 00:01:07,959 Speaker 1: is Various Analytics. Well, Various Canalytics has some great data 17 00:01:08,040 --> 00:01:13,240 Speaker 1: which provides our customers, insurers, natural resources area as well 18 00:01:13,280 --> 00:01:16,000 Speaker 1: as financial services with great insights into the risk and 19 00:01:16,040 --> 00:01:18,120 Speaker 1: about the decisions they need to make. So how do 20 00:01:18,160 --> 00:01:21,200 Speaker 1: people determine truly their risk if they are not in 21 00:01:21,480 --> 00:01:25,000 Speaker 1: a flood zone and they are not on the coasts. 22 00:01:25,880 --> 00:01:27,920 Speaker 1: I mean, what goes into that? Sure? Well, I mean 23 00:01:27,920 --> 00:01:30,360 Speaker 1: the first thing you have to understand is long ago 24 00:01:30,560 --> 00:01:34,399 Speaker 1: the hundred year plane is really about lenders. Lenders want 25 00:01:34,400 --> 00:01:36,760 Speaker 1: to make sure that their assets, the mortgage that they're 26 00:01:36,760 --> 00:01:40,240 Speaker 1: putting on a home, had insurance. So over the course 27 00:01:40,240 --> 00:01:43,280 Speaker 1: of time, Um, there is a lot of floodplane prone 28 00:01:43,280 --> 00:01:46,040 Speaker 1: areas that aren't covered by those maps. So you're at 29 00:01:46,160 --> 00:01:48,840 Speaker 1: risk well outside those maps. And the fact you just 30 00:01:48,880 --> 00:01:55,120 Speaker 1: provided inside of Harvey of the loss was outside of 31 00:01:55,120 --> 00:01:59,560 Speaker 1: those traditional floodplanes. So risk is much bigger and much expected. 32 00:01:59,640 --> 00:02:02,400 Speaker 1: A lot of consumers have no idea, and at the 33 00:02:02,400 --> 00:02:06,440 Speaker 1: same time, the actual boundaries of flood are extending every day. 34 00:02:06,800 --> 00:02:09,520 Speaker 1: So I just have to wonder, when you start to 35 00:02:09,639 --> 00:02:12,880 Speaker 1: do analytics on this kind of thing, what are you 36 00:02:12,960 --> 00:02:17,960 Speaker 1: looking for? Are you looking for the elevation, the whether 37 00:02:18,000 --> 00:02:20,799 Speaker 1: they're hills, whether it's just a flat plane, whether it's 38 00:02:20,840 --> 00:02:23,040 Speaker 1: covered in concrete, the soil. I mean, what do you 39 00:02:23,040 --> 00:02:26,120 Speaker 1: look for? So great, great opening almost all those So 40 00:02:26,160 --> 00:02:28,120 Speaker 1: there's a lot of very advanced models that take a 41 00:02:28,120 --> 00:02:30,720 Speaker 1: look at all that. So if you price or understanding 42 00:02:30,919 --> 00:02:33,799 Speaker 1: homeowner's insurance policy. A lot of those perils are all 43 00:02:34,000 --> 00:02:36,959 Speaker 1: captured in that. So the models are very effective and 44 00:02:37,080 --> 00:02:40,080 Speaker 1: understanding both the floodplains. But what they do is they 45 00:02:40,120 --> 00:02:42,760 Speaker 1: go beyond to understand how rising water will effect an area, 46 00:02:43,440 --> 00:02:47,080 Speaker 1: whether it's paved or not paved. An example, distance to coast, 47 00:02:47,240 --> 00:02:52,120 Speaker 1: distance to you know, the various natural tributaries, tributaries. The 48 00:02:52,200 --> 00:02:55,160 Speaker 1: elements of risk are beyond just what has been a 49 00:02:55,919 --> 00:02:58,760 Speaker 1: UH map that's been around for a long time that 50 00:02:58,840 --> 00:03:02,560 Speaker 1: has been kind of altered for different legislative problems and issues. 51 00:03:02,720 --> 00:03:05,800 Speaker 1: So how who pays you? I mean do insurance companies basically, 52 00:03:05,840 --> 00:03:08,200 Speaker 1: So it's basically the insurers who are looking to write 53 00:03:08,240 --> 00:03:10,880 Speaker 1: those risks. So I think there's a great opportunity to 54 00:03:10,919 --> 00:03:14,359 Speaker 1: take some of what is you know, the flood insurance 55 00:03:14,400 --> 00:03:17,040 Speaker 1: and bring it to the private market so insurers can 56 00:03:17,040 --> 00:03:20,200 Speaker 1: provide that to consumers. And I think that's a very 57 00:03:20,320 --> 00:03:23,320 Speaker 1: viable and opportunity. I don't really see how they could 58 00:03:23,360 --> 00:03:26,240 Speaker 1: do that if they could compete with the National Flood 59 00:03:26,280 --> 00:03:28,680 Speaker 1: Insurance Program of the U S which is set to 60 00:03:28,720 --> 00:03:31,000 Speaker 1: expire later this year. But I'm sure we'll get pasted 61 00:03:31,040 --> 00:03:33,280 Speaker 1: again because politically it would be unviable for them to 62 00:03:33,280 --> 00:03:35,600 Speaker 1: say to all the people on the coast of Florida 63 00:03:35,880 --> 00:03:39,440 Speaker 1: and North Carolina, well, go go fish, go go figure 64 00:03:39,440 --> 00:03:41,000 Speaker 1: it out for yourselves, and we're not going to insure 65 00:03:41,000 --> 00:03:43,839 Speaker 1: you anymore. Um. But a lot of people have said 66 00:03:43,840 --> 00:03:47,280 Speaker 1: that that's not an economically viable program, that there will 67 00:03:47,320 --> 00:03:50,280 Speaker 1: be much bigger losses than the income that they bring in. 68 00:03:50,800 --> 00:03:54,480 Speaker 1: So any private insurance policy would be vastly more expensive. No, 69 00:03:55,160 --> 00:03:58,119 Speaker 1: So I think the answer is not necessarily to replace 70 00:03:58,400 --> 00:04:00,280 Speaker 1: uh the n f I paper. I think that needs 71 00:04:00,280 --> 00:04:03,240 Speaker 1: to continue. I'm not going to get into the politics 72 00:04:03,280 --> 00:04:06,040 Speaker 1: of that, but the reality is there should it needs 73 00:04:06,040 --> 00:04:09,600 Speaker 1: to be private insurance to augment it, to provide insurance 74 00:04:09,640 --> 00:04:12,720 Speaker 1: to those who are in a floodplaine that have risk. Um. 75 00:04:12,760 --> 00:04:14,720 Speaker 1: I think what we are looking to do is try 76 00:04:14,760 --> 00:04:17,120 Speaker 1: to provide the same type of options and flexibility that 77 00:04:17,160 --> 00:04:20,680 Speaker 1: are available from a homeowner's perspective, trying to provide things 78 00:04:20,720 --> 00:04:24,080 Speaker 1: that's affordable and available from a private perspective outside those 79 00:04:24,080 --> 00:04:25,880 Speaker 1: flood zones. And I think, you know, you need to 80 00:04:25,880 --> 00:04:28,919 Speaker 1: actually have some actual sound rating information so that the 81 00:04:28,920 --> 00:04:31,800 Speaker 1: pricing is accurate. Your point is valid there, it's been 82 00:04:31,800 --> 00:04:34,800 Speaker 1: a little bit subsidized, a little bit subsidized. It's a 83 00:04:34,880 --> 00:04:38,039 Speaker 1: very very diplomatic way of putting it, compared to some 84 00:04:38,120 --> 00:04:40,560 Speaker 1: of the language I've heard from other people. Uh, just 85 00:04:40,640 --> 00:04:42,640 Speaker 1: can you give us a sense of which insurance companies 86 00:04:42,680 --> 00:04:46,320 Speaker 1: are interested in underwriting this type of policy. So right now, 87 00:04:46,400 --> 00:04:48,840 Speaker 1: there's a group of very large insurers they're called write 88 00:04:48,839 --> 00:04:51,839 Speaker 1: your own um. Historically they have been kind of focused 89 00:04:51,880 --> 00:04:54,600 Speaker 1: on providing is a distribution channel to the n f 90 00:04:54,680 --> 00:04:57,120 Speaker 1: I pay um. I think under some of the more 91 00:04:57,160 --> 00:05:00,440 Speaker 1: recent legislation, they will now be allowed to both uh 92 00:05:00,600 --> 00:05:03,320 Speaker 1: distribute the n f I P insurance as well as 93 00:05:03,360 --> 00:05:05,479 Speaker 1: write your own I think many sharers, both on the 94 00:05:05,480 --> 00:05:09,520 Speaker 1: commercial and personal lines will write the program to get 95 00:05:09,520 --> 00:05:13,480 Speaker 1: the proper pricing and rates. And I'm sure that it's 96 00:05:13,520 --> 00:05:15,479 Speaker 1: not too hard to find investors who want to put 97 00:05:15,520 --> 00:05:17,520 Speaker 1: up the capital on the other side, because everyone's looking 98 00:05:17,520 --> 00:05:19,200 Speaker 1: for yields, and you can probably get a good yield 99 00:05:19,240 --> 00:05:21,320 Speaker 1: for this, right I would agree what kind of yields 100 00:05:21,320 --> 00:05:23,800 Speaker 1: are looking at? Well, I think you'd see that from 101 00:05:23,800 --> 00:05:26,320 Speaker 1: an insurance perspective, r O s IF in the industry 102 00:05:26,320 --> 00:05:28,880 Speaker 1: have historically been around seven percent, So I think most 103 00:05:28,880 --> 00:05:30,719 Speaker 1: people who are kind of coming in from an alternative 104 00:05:30,720 --> 00:05:33,599 Speaker 1: capital are going to look something that would be low 105 00:05:33,839 --> 00:05:36,480 Speaker 1: sick double digits. All right, thank you so much, low 106 00:05:36,480 --> 00:05:40,640 Speaker 1: double digits eleven twelve. In a time like this of 107 00:05:41,040 --> 00:05:44,160 Speaker 1: nine point seven trillion dollars of negative yielding debt, I'm 108 00:05:44,200 --> 00:05:46,200 Speaker 1: sure they could find some some takers for that mark. 109 00:05:46,279 --> 00:05:48,320 Speaker 1: Uncle Larry, thank you so much for joining us chief 110 00:05:48,360 --> 00:05:51,360 Speaker 1: operating Officer of various Analytics, which takes a look at 111 00:05:51,440 --> 00:05:56,640 Speaker 1: the risks that are implied when people take out flood insurance. Uh. 112 00:05:56,960 --> 00:05:58,839 Speaker 1: Of course, if you want to know the truth. I 113 00:05:58,839 --> 00:06:02,400 Speaker 1: actually bought my apartments specifically because it was an elevation 114 00:06:02,480 --> 00:06:04,240 Speaker 1: that would not get flooded. But now I'm going to 115 00:06:04,320 --> 00:06:05,960 Speaker 1: have to go back and this will be another thing 116 00:06:06,000 --> 00:06:07,800 Speaker 1: that I can worry about later to late at night 117 00:06:07,839 --> 00:06:25,680 Speaker 1: when I don't have anything else to worry about. Semi 118 00:06:26,040 --> 00:06:31,440 Speaker 1: followed Cebo opening up for bitcoin futures trading last night, 119 00:06:31,560 --> 00:06:33,960 Speaker 1: and the results have been pretty good. They have not 120 00:06:34,040 --> 00:06:38,480 Speaker 1: seen major hiccups, they have seen the trading volumes that 121 00:06:38,720 --> 00:06:42,839 Speaker 1: they have been good. All systems seem ago here to 122 00:06:43,120 --> 00:06:46,400 Speaker 1: put this into perspective and figure out whether this paves 123 00:06:46,440 --> 00:06:51,799 Speaker 1: the path for more institutional money flying into this cryptocurrency 124 00:06:51,839 --> 00:06:55,599 Speaker 1: as Ken Fisher, Founder, chairman and co chief investment officer 125 00:06:55,640 --> 00:06:59,160 Speaker 1: of Fisher Investments. Ken, thank you so much for joining us. 126 00:06:59,720 --> 00:07:02,359 Speaker 1: I want to start with I want to start with 127 00:07:02,400 --> 00:07:06,279 Speaker 1: bitcoin because it seems to be the rage right now, 128 00:07:06,440 --> 00:07:11,400 Speaker 1: and because it's sort of highlights the degree of desire 129 00:07:11,840 --> 00:07:15,840 Speaker 1: for volatility and bigger profits than you can get elsewhere. 130 00:07:16,280 --> 00:07:18,320 Speaker 1: What's your take on it? Are you investing in it? 131 00:07:18,360 --> 00:07:20,200 Speaker 1: Are you staying away from it? Do you see it 132 00:07:20,200 --> 00:07:24,840 Speaker 1: as a sign of a bubble? Uh? So I've got 133 00:07:24,840 --> 00:07:27,800 Speaker 1: to take on it that I haven't had until last week, 134 00:07:29,360 --> 00:07:33,440 Speaker 1: which is last week. I'm in Manhattan, and I'm appearing 135 00:07:33,440 --> 00:07:37,120 Speaker 1: in various places, and I'm commenting on bitcoin, and I 136 00:07:37,160 --> 00:07:42,800 Speaker 1: was routinely in print, taken out of context and misinterpreted 137 00:07:42,840 --> 00:07:46,040 Speaker 1: in almost everything that I said by people who seem 138 00:07:46,120 --> 00:07:49,040 Speaker 1: to have some other goal. And I've never seen that 139 00:07:49,080 --> 00:07:51,960 Speaker 1: happen before. So I've made a conscious decision as of 140 00:07:52,080 --> 00:07:55,200 Speaker 1: last week, I'm not talking about bitcoin ever or crypto ever, 141 00:07:55,360 --> 00:07:59,200 Speaker 1: because it's a crazy world. People just cannot keep themselves 142 00:07:59,240 --> 00:08:01,760 Speaker 1: to the facts. The things that I said, which was 143 00:08:01,920 --> 00:08:06,960 Speaker 1: all actually on TV, are clear because there's a clear 144 00:08:07,000 --> 00:08:08,840 Speaker 1: record off I didn't do any other interviews, and there's 145 00:08:08,880 --> 00:08:11,880 Speaker 1: all these other things that appeared online in print saying 146 00:08:11,920 --> 00:08:13,920 Speaker 1: things that I said, things that I never said. I 147 00:08:13,960 --> 00:08:15,680 Speaker 1: think that's crazy, and I think that's an awful lot 148 00:08:15,680 --> 00:08:19,600 Speaker 1: of what goes on with the rest of bitcoin. Oh. 149 00:08:20,600 --> 00:08:23,200 Speaker 1: You know, I'm to go back that stuff on CNBC 150 00:08:23,320 --> 00:08:26,400 Speaker 1: and on the street dot com. And you know, basically 151 00:08:26,640 --> 00:08:27,920 Speaker 1: all that I said was I don't know if the 152 00:08:27,920 --> 00:08:31,320 Speaker 1: bubble or not. I hate that term bubble, but the 153 00:08:31,360 --> 00:08:35,480 Speaker 1: price movement in trading days before and after where we 154 00:08:35,559 --> 00:08:39,840 Speaker 1: are as of last week is in percentage magnitude bigger 155 00:08:39,880 --> 00:08:42,960 Speaker 1: than any of the bubbles of history. That doesn't make 156 00:08:43,000 --> 00:08:45,960 Speaker 1: it a bubble. It just makes it a big price movement. Uh. 157 00:08:46,000 --> 00:08:47,920 Speaker 1: The other thing that I've said and that I'll say 158 00:08:47,920 --> 00:08:51,680 Speaker 1: about bitcoin is it in every long bull cycle, there 159 00:08:51,840 --> 00:08:56,560 Speaker 1: is some non stock market phenomena or close to stock 160 00:08:56,600 --> 00:09:00,160 Speaker 1: market phenomena that gives you a kind of a you 161 00:09:00,200 --> 00:09:03,199 Speaker 1: into a kind of a window pane into the coming 162 00:09:03,200 --> 00:09:07,040 Speaker 1: euphoria stocks. Coming back to John Templeton's line, the bull 163 00:09:07,080 --> 00:09:10,520 Speaker 1: markets are born on pessimism, growing skepticism, ature on optimism, 164 00:09:10,520 --> 00:09:15,560 Speaker 1: and die of euphoria, and that euphoria, which is normally 165 00:09:15,600 --> 00:09:18,640 Speaker 1: the end of a bull market unless something governmental comes 166 00:09:18,679 --> 00:09:21,920 Speaker 1: along and noxious under first is something it's always not 167 00:09:22,160 --> 00:09:24,880 Speaker 1: clear fully that we're going to get to. But I 168 00:09:24,920 --> 00:09:28,199 Speaker 1: think the crypto thing is the first real sign we're 169 00:09:28,240 --> 00:09:31,959 Speaker 1: seeing in this long cycle of the coming of euphoria. 170 00:09:32,080 --> 00:09:35,280 Speaker 1: It's the window pane into the coming of euphoria for stocks. 171 00:09:36,000 --> 00:09:39,000 Speaker 1: So what are you looking for to determine whether that 172 00:09:39,080 --> 00:09:41,480 Speaker 1: euphoria has started to bleed over? I mean, how do 173 00:09:41,520 --> 00:09:44,880 Speaker 1: you know that we aren't there yet? Oh, that's easy, 174 00:09:45,080 --> 00:09:48,880 Speaker 1: that's trivial. Look at all of the nonsense that people 175 00:09:48,960 --> 00:09:51,280 Speaker 1: worry about that they stop worrying about when you get 176 00:09:51,280 --> 00:09:54,200 Speaker 1: to euphoria. I mean, I've been doing this stuff, you know, 177 00:09:54,280 --> 00:09:57,640 Speaker 1: since the early seventies. And when you get to euphoria, 178 00:09:57,760 --> 00:09:59,960 Speaker 1: people stop worrying about things like are there too many 179 00:10:00,040 --> 00:10:03,240 Speaker 1: new highs? Uh? They stop worrying about things like as 180 00:10:03,280 --> 00:10:07,120 Speaker 1: the markets pe two high, they stop worrying about all 181 00:10:07,120 --> 00:10:11,400 Speaker 1: of the kinds of things like uh, the next said hike. 182 00:10:11,800 --> 00:10:14,240 Speaker 1: Because you actually get to that point when there's euphoria 183 00:10:14,280 --> 00:10:16,480 Speaker 1: where they invert the yel curve and nobody much pays 184 00:10:16,480 --> 00:10:18,920 Speaker 1: attention or notices because they conclude that it doesn't matter. 185 00:10:19,600 --> 00:10:24,800 Speaker 1: It's the worrying stopping about the things that people have 186 00:10:24,880 --> 00:10:28,360 Speaker 1: worried about over and over and over again wrongly, which 187 00:10:28,400 --> 00:10:31,400 Speaker 1: ironically is about the time to get worried. But we 188 00:10:31,480 --> 00:10:33,840 Speaker 1: still have those things. We still have people that have 189 00:10:33,880 --> 00:10:36,480 Speaker 1: a fear of heights, that think the market has been 190 00:10:36,520 --> 00:10:39,959 Speaker 1: too strong, particularly in America. That's true more so than 191 00:10:40,000 --> 00:10:43,160 Speaker 1: overseas because of the UH you know, if you look 192 00:10:43,240 --> 00:10:48,439 Speaker 1: overseas Britain, some continental Europe, more the equity returns have 193 00:10:48,480 --> 00:10:52,240 Speaker 1: been muted by currency strength, and so there's has been 194 00:10:52,280 --> 00:10:55,440 Speaker 1: so buoyant normally in the late stages of bowl markets. 195 00:10:55,480 --> 00:10:58,240 Speaker 1: As you move into that eusphoria phase, you get some 196 00:10:58,559 --> 00:11:02,679 Speaker 1: multiple big years this cycle, and we haven't really had 197 00:11:02,720 --> 00:11:05,160 Speaker 1: that normally. The first third of time of a ballmark 198 00:11:05,240 --> 00:11:08,000 Speaker 1: it's pretty steep, the middle thirds flatish in the back 199 00:11:08,080 --> 00:11:10,800 Speaker 1: their steep and of the return comes in the first 200 00:11:11,200 --> 00:11:14,400 Speaker 1: and last the ball market only about the middle third. 201 00:11:15,440 --> 00:11:17,800 Speaker 1: Before I came on, there was a comment that we've 202 00:11:17,840 --> 00:11:22,640 Speaker 1: had the most new high since nineteen which is true, um, 203 00:11:22,679 --> 00:11:27,360 Speaker 1: but also people forget that NT was at seven percent 204 00:11:27,480 --> 00:11:30,440 Speaker 1: year and still had years ahead of it in the 205 00:11:30,440 --> 00:11:33,520 Speaker 1: ball market. Uh, an interesting point that I think people 206 00:11:33,600 --> 00:11:36,640 Speaker 1: kind of miss in context. We still have a long 207 00:11:36,720 --> 00:11:40,360 Speaker 1: ways to go unless the government does something stupid, which 208 00:11:40,360 --> 00:11:43,320 Speaker 1: is so possible. Well, so if that's the case, it 209 00:11:43,360 --> 00:11:47,680 Speaker 1: sounds like, are you getting more heavily invested in risk 210 00:11:47,800 --> 00:11:49,920 Speaker 1: your stocks? I mean, is this time the time to 211 00:11:49,920 --> 00:11:51,920 Speaker 1: go all in if we still have the last third 212 00:11:51,920 --> 00:11:55,679 Speaker 1: of games to go? The time to get all in 213 00:11:55,920 --> 00:11:59,959 Speaker 1: was two thousand and nine, and I've been nearly endlessly bullish, 214 00:12:00,080 --> 00:12:03,319 Speaker 1: but not in what you think of as risk gier stocks. 215 00:12:03,320 --> 00:12:05,600 Speaker 1: In the back third of the time of the ball market, 216 00:12:05,920 --> 00:12:08,559 Speaker 1: the categories of stocks that typically do best are not 217 00:12:08,640 --> 00:12:11,680 Speaker 1: the ones that people think they will, because the market 218 00:12:11,880 --> 00:12:14,959 Speaker 1: is a function that works off surprise. The things that 219 00:12:15,040 --> 00:12:17,000 Speaker 1: do best in the last stage of a ball market 220 00:12:17,280 --> 00:12:21,720 Speaker 1: are categorically what you could call comfort stocks. They're big, 221 00:12:22,160 --> 00:12:27,520 Speaker 1: they're reputationally impeccable. There are things that are not thought 222 00:12:27,520 --> 00:12:31,199 Speaker 1: of as needles in the haystack, but as too obvious 223 00:12:31,240 --> 00:12:34,560 Speaker 1: to likely do well. They're perfectly the stocks that the 224 00:12:34,679 --> 00:12:37,480 Speaker 1: last greater fool who gets into the market that was 225 00:12:37,520 --> 00:12:40,400 Speaker 1: too afraid to buy a single thing one week before 226 00:12:40,960 --> 00:12:44,880 Speaker 1: is ready to dip his toe into because their comfort stocks. 227 00:12:44,920 --> 00:12:50,200 Speaker 1: So this would be big, global, high quality, well branded names. 228 00:12:50,679 --> 00:12:53,480 Speaker 1: This is why the Fangs are doing so well. Uh. 229 00:12:53,520 --> 00:12:58,600 Speaker 1: It's classically big pharma for the same reason. The person 230 00:12:58,679 --> 00:13:03,160 Speaker 1: with money, who is typically older, buys the drugs, knows 231 00:13:03,240 --> 00:13:07,760 Speaker 1: his friends would buy the drugs. Big global name, high quality, 232 00:13:08,080 --> 00:13:11,360 Speaker 1: easy to do. The last people to get into the 233 00:13:11,400 --> 00:13:13,720 Speaker 1: market to push it up the most. You keep pushing 234 00:13:13,720 --> 00:13:17,000 Speaker 1: it up even as it's starting to fall. Those people, 235 00:13:17,679 --> 00:13:19,560 Speaker 1: they were too afraid to buy anything before, so they 236 00:13:19,640 --> 00:13:21,560 Speaker 1: might buy the stock of the company they worked for. 237 00:13:21,840 --> 00:13:23,840 Speaker 1: They might buy the stock of the company their spouse 238 00:13:23,880 --> 00:13:26,360 Speaker 1: works for. They might buy the one that brother works for. 239 00:13:26,679 --> 00:13:28,480 Speaker 1: And when you get a little beyond that, they buy 240 00:13:28,640 --> 00:13:31,840 Speaker 1: big global, safe names. Ken Fisher, thank you so much 241 00:13:31,840 --> 00:13:34,640 Speaker 1: for joining us. Ken Fisher, Founder, chairman and co chief 242 00:13:34,720 --> 00:13:55,720 Speaker 1: investment officer of Fisher Investments. Shoppers spent a record seventy 243 00:13:55,920 --> 00:14:00,760 Speaker 1: seven point five billion dollars online. That's just since November 244 00:14:00,840 --> 00:14:04,400 Speaker 1: one through yesterday. Every single one of those forty four 245 00:14:04,480 --> 00:14:09,240 Speaker 1: days has been a billion dollar day. Some shocking statistics, 246 00:14:09,679 --> 00:14:13,480 Speaker 1: uh from Adobe Sense and I'd love to get some 247 00:14:13,559 --> 00:14:16,480 Speaker 1: insight on what we can expect in the remaining a 248 00:14:16,520 --> 00:14:19,000 Speaker 1: few months and weeks of the year to America. Affney 249 00:14:19,040 --> 00:14:22,960 Speaker 1: joins us now. She's senior director of Adobe Digital Insights, 250 00:14:23,000 --> 00:14:26,840 Speaker 1: which has been looking into some of the data from 251 00:14:27,040 --> 00:14:30,960 Speaker 1: the biggest online retailers and trying to project what we 252 00:14:31,000 --> 00:14:34,160 Speaker 1: can expect. Tamara, thank you so much for joining us. 253 00:14:35,280 --> 00:14:37,480 Speaker 1: Good morning. It's great to be here. Good morning. So 254 00:14:37,480 --> 00:14:40,960 Speaker 1: so let's just get us start with how much can 255 00:14:41,040 --> 00:14:46,240 Speaker 1: we see online sales accelerate before it becomes a logistics nightmare. Oh, 256 00:14:46,280 --> 00:14:49,360 Speaker 1: that's a really great question. We actually are seeing right 257 00:14:49,400 --> 00:14:53,400 Speaker 1: now about a thirteen point one percent growth in online 258 00:14:53,440 --> 00:14:56,760 Speaker 1: shopping versus last year. We're expecting that to end up 259 00:14:56,800 --> 00:14:59,160 Speaker 1: at thirteen point eight percent because the last couple of 260 00:14:59,200 --> 00:15:02,240 Speaker 1: weeks of of the month actually turned out to be 261 00:15:02,360 --> 00:15:06,080 Speaker 1: higher growth rate months weeks because of the fact that 262 00:15:06,120 --> 00:15:09,160 Speaker 1: people can ship later and later, Which brings me to 263 00:15:09,200 --> 00:15:11,200 Speaker 1: your question, which is how much more can we ship? 264 00:15:11,680 --> 00:15:14,360 Speaker 1: And Uh, I think that is we're just lucky that 265 00:15:14,400 --> 00:15:17,560 Speaker 1: we haven't had any big storms to slow down any 266 00:15:17,600 --> 00:15:20,840 Speaker 1: of those shipping and delivery services. Well, I mean we've 267 00:15:20,840 --> 00:15:25,160 Speaker 1: already heard about ups, for example, being worried about some 268 00:15:25,280 --> 00:15:30,000 Speaker 1: kind of logistic interruption. I'm sure that they're all racing 269 00:15:30,080 --> 00:15:32,440 Speaker 1: to make sure that their stations are up to speed. 270 00:15:32,920 --> 00:15:35,880 Speaker 1: We know that UPS and FedEx both are considering having 271 00:15:35,960 --> 00:15:39,920 Speaker 1: some kind of voluntary pick up at drug stores or 272 00:15:39,960 --> 00:15:45,800 Speaker 1: local businesses to try to expedite some of the the deliveries. 273 00:15:46,120 --> 00:15:50,040 Speaker 1: I'm just wondering, is the infrastructure okay with this growth? 274 00:15:50,040 --> 00:15:52,840 Speaker 1: At what point will it not be Well? At this 275 00:15:52,920 --> 00:15:55,240 Speaker 1: point seems to be okay, but you do see the 276 00:15:55,400 --> 00:16:00,320 Speaker 1: pure play online retailers investing in actual physical store look stations, 277 00:16:00,360 --> 00:16:02,240 Speaker 1: and part of the reason why they be doing that 278 00:16:02,680 --> 00:16:04,120 Speaker 1: is to make sure they do have a place to 279 00:16:04,200 --> 00:16:08,239 Speaker 1: drop off when the event happens that online shopping overcomes 280 00:16:08,280 --> 00:16:13,440 Speaker 1: our logistic capacity and trucking just becomes overloaded. Uh. The 281 00:16:13,480 --> 00:16:15,360 Speaker 1: other thing is going on right now is that the 282 00:16:15,440 --> 00:16:18,360 Speaker 1: average order value that's how much is put into a cart, 283 00:16:18,680 --> 00:16:21,280 Speaker 1: is a little bit down, but the amount of orders 284 00:16:21,360 --> 00:16:22,960 Speaker 1: is up, and that means there are more and more 285 00:16:23,000 --> 00:16:25,960 Speaker 1: boxes floating around. I was in Manhattan last year and 286 00:16:26,000 --> 00:16:28,040 Speaker 1: it was a sea of boxes. I'm sure it's like 287 00:16:28,080 --> 00:16:30,800 Speaker 1: that today. So it's so yes, this is going to 288 00:16:30,880 --> 00:16:34,600 Speaker 1: be a challenge. But Amazon Whole Foods now, so anywhere 289 00:16:34,640 --> 00:16:36,200 Speaker 1: there's a whole Foods. If they want to ship to 290 00:16:36,280 --> 00:16:38,440 Speaker 1: that location, they might be able to just have people 291 00:16:38,480 --> 00:16:42,520 Speaker 1: going to pick up stuff. So is the the sales profile? 292 00:16:42,600 --> 00:16:45,440 Speaker 1: Is it pretty much even across the retailers. Is it 293 00:16:45,600 --> 00:16:49,240 Speaker 1: mostly Amazon dot Com that's sucking up all the gains 294 00:16:49,320 --> 00:16:52,240 Speaker 1: here or were also seeing an increase in Walmart and 295 00:16:52,360 --> 00:16:56,560 Speaker 1: even in same Nordstrom. Well, you know, in my data set, 296 00:16:56,600 --> 00:16:58,920 Speaker 1: I need to give you more broad answer, so I 297 00:16:58,920 --> 00:17:01,480 Speaker 1: can tell you that the law are just retailers. The 298 00:17:01,560 --> 00:17:04,080 Speaker 1: ones who have a massive shopping catalog where it's a 299 00:17:04,119 --> 00:17:07,360 Speaker 1: one shop kind of deal are picking up much more 300 00:17:07,480 --> 00:17:11,840 Speaker 1: than average. The place where small retailers are winning is 301 00:17:11,880 --> 00:17:15,200 Speaker 1: in the mobile shopping category. They're actually with a more 302 00:17:15,240 --> 00:17:18,880 Speaker 1: targeted catalog and more specific items that you go there 303 00:17:18,920 --> 00:17:21,440 Speaker 1: to buy. It's much easier when you're under mobile phone. 304 00:17:21,640 --> 00:17:23,000 Speaker 1: I don't know about you, but if I want to 305 00:17:23,040 --> 00:17:27,080 Speaker 1: go find something like a silver bracelet, I don't want 306 00:17:27,080 --> 00:17:30,520 Speaker 1: to look at a thousand pages on my phone. So 307 00:17:30,760 --> 00:17:33,639 Speaker 1: that so there's a place for small retailers. There's obviously 308 00:17:34,000 --> 00:17:36,639 Speaker 1: the big places for the super large retailers. The middle 309 00:17:36,680 --> 00:17:40,960 Speaker 1: guys are not doing so hot. What about apparel? Apparel 310 00:17:41,080 --> 00:17:43,720 Speaker 1: is really interesting It's one of the only categories that 311 00:17:43,800 --> 00:17:48,360 Speaker 1: continues to see discounts even after Christmas is over. Right 312 00:17:48,359 --> 00:17:51,399 Speaker 1: now with discounts, we're still seeing some fairly good deals. 313 00:17:51,720 --> 00:17:55,160 Speaker 1: TVs are at about fifteen point three percent discount that's 314 00:17:55,200 --> 00:17:58,760 Speaker 1: coming off of though on Black Friday, So things are 315 00:17:58,760 --> 00:18:01,000 Speaker 1: starting to get more and more sensitive. But a perilous 316 00:18:01,040 --> 00:18:03,479 Speaker 1: one of those areas that doesn't get more expensive. It 317 00:18:03,480 --> 00:18:06,280 Speaker 1: actually gets cheaper as soon as you get into January. 318 00:18:06,320 --> 00:18:10,159 Speaker 1: Are we seeing tech really still being the hot spot? 319 00:18:10,240 --> 00:18:13,639 Speaker 1: And if so, is it all concentrated in one area 320 00:18:13,760 --> 00:18:16,840 Speaker 1: is it pretty much across the board with basically kids 321 00:18:16,880 --> 00:18:19,240 Speaker 1: across the world seeing what my children do, which is 322 00:18:19,280 --> 00:18:22,840 Speaker 1: just they want anything and all things tech. It's true, 323 00:18:22,920 --> 00:18:25,679 Speaker 1: tech is one of those categories that just keeps growing 324 00:18:25,720 --> 00:18:28,679 Speaker 1: and growing. In fact, it's almost hard to differentiate a 325 00:18:28,720 --> 00:18:32,119 Speaker 1: toy from tech at this point. Is the new video 326 00:18:32,160 --> 00:18:36,400 Speaker 1: game console the PlayStation for Pro with VR is that tech? 327 00:18:36,520 --> 00:18:39,200 Speaker 1: Or is that a game or toy? What is that now? 328 00:18:39,520 --> 00:18:43,040 Speaker 1: But yeah, the electronics category is seeing iPads and air 329 00:18:43,080 --> 00:18:47,040 Speaker 1: pods and Amazon Fire TVs and echo devices flying off 330 00:18:47,040 --> 00:18:50,200 Speaker 1: the shelves, and those discounts are pretty good right now 331 00:18:50,240 --> 00:18:55,200 Speaker 1: as well. Computers, for example, are at about seven percent down. 332 00:18:55,880 --> 00:18:59,840 Speaker 1: Black Friday saw six discounts, So again all of that 333 00:19:00,160 --> 00:19:02,879 Speaker 1: it's going to be under the Christmas tree and giving 334 00:19:03,280 --> 00:19:06,520 Speaker 1: gifts to all those from every category from kids to 335 00:19:07,000 --> 00:19:10,000 Speaker 1: two dads to moms and and and even grandparents are 336 00:19:10,000 --> 00:19:12,960 Speaker 1: getting in on the tech tech buying. To Mary Gaffney, 337 00:19:12,960 --> 00:19:14,880 Speaker 1: thank you so much for joining us to Mary Gaffney 338 00:19:15,000 --> 00:19:34,639 Speaker 1: is Senior director of Adobe Digital Insights. There's been a 339 00:19:34,680 --> 00:19:38,199 Speaker 1: lot of talk about retailers that have slowly been dying 340 00:19:38,480 --> 00:19:41,160 Speaker 1: for a number of years, and the question has been 341 00:19:41,480 --> 00:19:43,960 Speaker 1: when are they going to finally kick the bucket? You know? 342 00:19:44,080 --> 00:19:47,160 Speaker 1: And today I looked at a story at Bonton's Stories 343 00:19:47,200 --> 00:19:50,480 Speaker 1: to lead a December fifteenth payment on some of its debt. 344 00:19:51,359 --> 00:19:54,400 Speaker 1: Hasn't a fault yet. They still have a just grace period, 345 00:19:54,520 --> 00:19:58,000 Speaker 1: but it's sort of eching closer to that sort of 346 00:19:58,000 --> 00:20:01,359 Speaker 1: tipping point. Bert Flickinger here with us, managing director at 347 00:20:01,359 --> 00:20:06,520 Speaker 1: Strategic Resource Group UH Bonton is one of these stores 348 00:20:06,560 --> 00:20:08,960 Speaker 1: that has been on death watch. Is this the final nil? 349 00:20:09,800 --> 00:20:13,440 Speaker 1: It could be the final nil, Lisa for three reasons. One, 350 00:20:13,520 --> 00:20:18,119 Speaker 1: it's primarily a rust belt retailer, and the better economy 351 00:20:18,200 --> 00:20:21,359 Speaker 1: hasn't gotten to the regions where many of the retail 352 00:20:21,400 --> 00:20:25,040 Speaker 1: stores are to Uh, the off price retailers from Burlington 353 00:20:25,160 --> 00:20:28,920 Speaker 1: to t j X Max Marshalls have opened very aggressively 354 00:20:29,000 --> 00:20:33,080 Speaker 1: against them, So that's very problematic. And three, they've had 355 00:20:33,119 --> 00:20:36,640 Speaker 1: a lot of leadership changes. So when when they when 356 00:20:36,640 --> 00:20:39,920 Speaker 1: they lost a couple of good CEOs back to back. 357 00:20:40,040 --> 00:20:42,879 Speaker 1: The vendors had been supportive of the Bontan stores, but 358 00:20:42,920 --> 00:20:46,760 Speaker 1: the Herburger stores have been in recently in North Dakota, Minnesota, 359 00:20:47,359 --> 00:20:52,560 Speaker 1: upper Midwestern region, Carson's in Chicago. Uh, inventories a little light, 360 00:20:53,000 --> 00:20:56,120 Speaker 1: the circular pages, the ad pages a little light. Uh 361 00:20:56,160 --> 00:20:59,159 Speaker 1: So getting the cash in for Christmas, Hanukah, New Year's 362 00:20:59,480 --> 00:21:02,240 Speaker 1: is going to be concerning to your important point. Well, 363 00:21:02,280 --> 00:21:04,760 Speaker 1: I just have to wonder though, also whether we're reaching 364 00:21:04,760 --> 00:21:08,760 Speaker 1: a point given the increasing pressure from Amazon dot Com, 365 00:21:08,800 --> 00:21:11,760 Speaker 1: the fact that there have been so many years when 366 00:21:11,760 --> 00:21:15,600 Speaker 1: these struggling retailers have failed to turn themselves around. Dr J. C. Penney, 367 00:21:15,640 --> 00:21:19,119 Speaker 1: I'm talking Claire's, I'm talking uh years, I'm talking you know, 368 00:21:19,160 --> 00:21:22,800 Speaker 1: you're your sort of a list of laggards. I'm just wondering, 369 00:21:22,920 --> 00:21:24,879 Speaker 1: is next year going to be the one when we 370 00:21:24,960 --> 00:21:27,720 Speaker 1: actually start to see the fallout here. Next year is 371 00:21:27,760 --> 00:21:29,680 Speaker 1: going to be the one. And then uh t TM 372 00:21:29,760 --> 00:21:32,639 Speaker 1: or trailing twelve months is you You and your team 373 00:21:32,640 --> 00:21:35,600 Speaker 1: of Bloomberg News have reported well as well as the 374 00:21:35,600 --> 00:21:39,879 Speaker 1: Bloomberg terminal twenty retail chains of file for either bankruptcy 375 00:21:39,960 --> 00:21:43,520 Speaker 1: or liquidation this year, so in the last twelve months. 376 00:21:43,960 --> 00:21:47,560 Speaker 1: And but the key ones to your your key point 377 00:21:47,920 --> 00:21:52,680 Speaker 1: are going to be in and nineteen and primarily eighteen 378 00:21:53,160 --> 00:21:58,480 Speaker 1: where the vendors are seeing price deflation. Ors Tom Keane 379 00:21:58,800 --> 00:22:01,639 Speaker 1: always says, I want to know, ay, you are average 380 00:22:01,720 --> 00:22:05,200 Speaker 1: unit retail and the vendors are seeing average unit retailer. 381 00:22:05,400 --> 00:22:08,119 Speaker 1: The retailers are seeing average unit retail. And if you 382 00:22:08,160 --> 00:22:12,520 Speaker 1: can't drive higher sales like the well capitalized competitors, the Bonton's, 383 00:22:12,560 --> 00:22:16,000 Speaker 1: the Sears, the Claire's, all the key concerning change of 384 00:22:16,080 --> 00:22:21,119 Speaker 1: referenced are are brilliant for tough times. What's the what's 385 00:22:21,160 --> 00:22:25,000 Speaker 1: the catalyst here? Why now? Or why next year? Why now? 386 00:22:25,240 --> 00:22:28,880 Speaker 1: Is the toys r US bankruptcy really caught the vendor 387 00:22:28,960 --> 00:22:32,240 Speaker 1: community by surprise. We've met with the vendor community over 388 00:22:32,280 --> 00:22:35,520 Speaker 1: the summer. They've been fully supportive. UH two toys r 389 00:22:35,680 --> 00:22:38,199 Speaker 1: US and you could see it in the Toys her 390 00:22:38,320 --> 00:22:42,840 Speaker 1: US ads that ran last weekend and uh pre and 391 00:22:42,920 --> 00:22:46,480 Speaker 1: during Black Friday it's only four pages, while Target is 392 00:22:46,480 --> 00:22:49,359 Speaker 1: putting out a seventy two page full color toy book. 393 00:22:49,840 --> 00:22:53,160 Speaker 1: And so it is your referencing Amazon shifting the sales, 394 00:22:53,200 --> 00:22:57,080 Speaker 1: Target Walmart shifting the sales. The under capitalized retailers aren't 395 00:22:57,119 --> 00:23:01,960 Speaker 1: getting the extra money to advertise TV, radio, social, digital 396 00:23:02,280 --> 00:23:05,200 Speaker 1: connective and the key circulars that go to the homes 397 00:23:05,200 --> 00:23:08,199 Speaker 1: in the in the Sunday papers, and with that it 398 00:23:08,280 --> 00:23:12,600 Speaker 1: hurts customer count. And Bontan and the others don't benefit 399 00:23:12,680 --> 00:23:16,920 Speaker 1: from Star Wars setting box office records this weekend. They 400 00:23:16,960 --> 00:23:20,520 Speaker 1: have the FAO Schwartz toys, not the Star Wars license toys. 401 00:23:20,560 --> 00:23:23,600 Speaker 1: So sad. I'm looking at Bonton bonds. I mean, they've 402 00:23:23,600 --> 00:23:26,800 Speaker 1: been doing terribly for a long time, but they are 403 00:23:26,920 --> 00:23:30,520 Speaker 1: trading even lower right now. I'm looking uh less thirty 404 00:23:30,560 --> 00:23:33,440 Speaker 1: one cents on the dollar. I'm looking at. These are 405 00:23:33,440 --> 00:23:36,479 Speaker 1: the ones that come to one that is not a 406 00:23:36,560 --> 00:23:41,560 Speaker 1: very encouraging sign. Lowest in trading days. So I guess 407 00:23:41,560 --> 00:23:43,240 Speaker 1: that there was one lower, but it's it's close to 408 00:23:43,240 --> 00:23:45,600 Speaker 1: the lowest price on record. But it seems to be 409 00:23:45,920 --> 00:23:48,880 Speaker 1: uh that there also is a shift in debt markets. 410 00:23:49,200 --> 00:23:52,000 Speaker 1: There's a key shift in debt markets. You're referencing that 411 00:23:52,720 --> 00:23:55,600 Speaker 1: no one other than you and Bloomberg are reporting because 412 00:23:55,960 --> 00:24:00,360 Speaker 1: you're not able to refinance now the way you would 413 00:24:00,359 --> 00:24:02,679 Speaker 1: have been able to refinance even a quarter go. So 414 00:24:02,720 --> 00:24:06,080 Speaker 1: it's beyond toys or US. It's like you said, it's Bonton, 415 00:24:06,200 --> 00:24:09,720 Speaker 1: it's sears. Pet Smart bonds on the Bloomberg terminal have 416 00:24:09,800 --> 00:24:13,320 Speaker 1: traded way down. What happened there, It's it's a it's 417 00:24:13,359 --> 00:24:18,280 Speaker 1: a combination really good reverse category killing by Walmart and 418 00:24:18,480 --> 00:24:22,760 Speaker 1: b J's Wholesale Club and Albertson, Safeway, Windco, a number 419 00:24:22,800 --> 00:24:25,960 Speaker 1: of others because pet and all the way to pet 420 00:24:26,000 --> 00:24:29,960 Speaker 1: accessories is the fastest growing category and retail. But pet 421 00:24:30,040 --> 00:24:33,679 Speaker 1: Smart hired a lot of consultants that didn't know what 422 00:24:33,840 --> 00:24:36,400 Speaker 1: the devil they were doing, didn't know the detail of retail. 423 00:24:37,000 --> 00:24:41,080 Speaker 1: Bad releases, bad capex decisions, the new new stores are 424 00:24:41,119 --> 00:24:45,639 Speaker 1: losing money, and uh, the the stores really aren't aren't 425 00:24:45,640 --> 00:24:48,800 Speaker 1: built efficiently, so it should be best of times for 426 00:24:49,040 --> 00:24:51,439 Speaker 1: pet Smart, But it's dick and esque. It's worst of 427 00:24:51,520 --> 00:24:53,920 Speaker 1: times to your point on the Bloomberg terminal with the 428 00:24:53,960 --> 00:24:57,639 Speaker 1: bonds today on pet Smart, well, just to play devil's advocate, 429 00:24:57,680 --> 00:25:01,480 Speaker 1: I mean, these companies, these stores is have managed to 430 00:25:01,520 --> 00:25:04,760 Speaker 1: sort of limp along for a while, and perhaps they've 431 00:25:04,840 --> 00:25:08,000 Speaker 1: closed stores enough, and perhaps they'll close more stores next year. 432 00:25:08,040 --> 00:25:11,280 Speaker 1: What's not to say, you know, there is a place 433 00:25:11,359 --> 00:25:13,920 Speaker 1: for brick and mortar. We're seeing Amazon move more into 434 00:25:13,920 --> 00:25:17,520 Speaker 1: brick and mortar. You know, they can drag along for 435 00:25:17,520 --> 00:25:20,399 Speaker 1: a little long there. There they can drag along, and 436 00:25:20,440 --> 00:25:23,320 Speaker 1: there clearly is a place for brick and mortar. But 437 00:25:23,320 --> 00:25:25,360 Speaker 1: at the same time, we were going through the bontan 438 00:25:25,480 --> 00:25:28,879 Speaker 1: Herberger stores in the north central states between the Dakotas 439 00:25:28,920 --> 00:25:31,800 Speaker 1: and Minnesota, Wisconsin. We were also going through Chuck and 440 00:25:31,880 --> 00:25:36,560 Speaker 1: Don's super Pet stores, a local entrepreneur one shop now 441 00:25:36,640 --> 00:25:39,440 Speaker 1: has dozens of stores. It's just pounding pet smart into 442 00:25:39,480 --> 00:25:42,879 Speaker 1: the ground with a lot of natural and organic pet food. 443 00:25:42,920 --> 00:25:47,160 Speaker 1: Fleet Farms now owned by kkr I and Menard's and 444 00:25:47,320 --> 00:25:49,840 Speaker 1: a number of others are also doing really well with 445 00:25:49,960 --> 00:25:53,280 Speaker 1: pet and pet smart. By going to the big house 446 00:25:53,320 --> 00:25:56,919 Speaker 1: consulting firms lost a lot of the great leadership they 447 00:25:56,960 --> 00:25:59,520 Speaker 1: had that built the company up during the twentieth century 448 00:25:59,600 --> 00:26:02,800 Speaker 1: until about five six years ago. Uh. And and just 449 00:26:03,080 --> 00:26:06,159 Speaker 1: real quick, what are you expecting with uh with this 450 00:26:06,240 --> 00:26:09,000 Speaker 1: year's holiday sales. I mean, I've heard from some people 451 00:26:09,000 --> 00:26:11,119 Speaker 1: that it seems like it's pretty strong so far. Would 452 00:26:11,119 --> 00:26:13,480 Speaker 1: you say that that's what you're hearing? Very strong? We 453 00:26:13,560 --> 00:26:17,320 Speaker 1: also checked the post office. Is the FedEx deposts and 454 00:26:17,359 --> 00:26:22,359 Speaker 1: the UPS deposts. I've never seen the shipping deposts so packed, 455 00:26:22,400 --> 00:26:26,720 Speaker 1: with a record two million parcels to be shipped bet 456 00:26:26,920 --> 00:26:31,160 Speaker 1: between million between between the big three post office UPS, FedEx, 457 00:26:31,480 --> 00:26:34,560 Speaker 1: and Bloomberg terminals. Reporting FedEx near a fifty two week 458 00:26:34,640 --> 00:26:37,359 Speaker 1: high today. I think, thinking part that should should go 459 00:26:37,480 --> 00:26:41,760 Speaker 1: higher because the volumes just astounding. But the retail stores 460 00:26:42,480 --> 00:26:46,719 Speaker 1: with new leaders, good merchants are bouncing back, and Penny 461 00:26:46,760 --> 00:26:49,960 Speaker 1: On the Bloomberg terminals actually going up in terms of 462 00:26:49,960 --> 00:26:52,879 Speaker 1: the bonds that prefers and the the equity and sympathy 463 00:26:52,920 --> 00:26:56,359 Speaker 1: that they'll get. Ship shoppers who see out of stocks 464 00:26:56,359 --> 00:27:00,040 Speaker 1: at Bonton shift to Penny and seares the shoppers of 465 00:27:00,119 --> 00:27:03,480 Speaker 1: already safe save Penny during during the last two years too. 466 00:27:04,440 --> 00:27:06,639 Speaker 1: Bert Flickinger, thank you so much. The only one I 467 00:27:06,680 --> 00:27:09,679 Speaker 1: know is they're counting the boxes that are lined up 468 00:27:10,280 --> 00:27:12,480 Speaker 1: that are ready to get shipped out for the holidays. 469 00:27:12,480 --> 00:27:15,879 Speaker 1: Burt Flickinger, thank you as always, Managing director at Strategic 470 00:27:16,119 --> 00:27:22,760 Speaker 1: Resource Group. Thanks for listening to the Bloomberg P and 471 00:27:22,880 --> 00:27:25,920 Speaker 1: L podcast. You can subscribe and listen to interviews at 472 00:27:25,960 --> 00:27:30,400 Speaker 1: Apple Podcasts, SoundCloud, or whatever podcast platform you prefer. I'm 473 00:27:30,440 --> 00:27:33,879 Speaker 1: Pim Fox. I'm on Twitter at pim Fox. I'm on 474 00:27:33,920 --> 00:27:37,200 Speaker 1: Twitter at Lisa Abramo. It's one before the podcast. You 475 00:27:37,240 --> 00:27:39,760 Speaker 1: can always catch us worldwide on Bloomberg Radio