1 00:00:04,760 --> 00:00:07,720 Speaker 1: Welcome to the Bloomberg P and L Podcast. I'm Pim 2 00:00:07,800 --> 00:00:11,080 Speaker 1: Fox along with my co host Lisa Abramowitz. Each day 3 00:00:11,119 --> 00:00:14,360 Speaker 1: we bring you the most important, noteworthy, and useful interviews 4 00:00:14,400 --> 00:00:16,560 Speaker 1: for you and your money, whether at the grocery store 5 00:00:16,800 --> 00:00:19,960 Speaker 1: or the trading floor. Find the Bloomberg P L Podcast 6 00:00:20,000 --> 00:00:29,560 Speaker 1: on iTunes, SoundCloud and at Bloomberg dot com. I want 7 00:00:29,600 --> 00:00:32,720 Speaker 1: to take a deeper look at what the potential on 8 00:00:33,000 --> 00:00:38,080 Speaker 1: the ground implications are regardless of who wins this election. 9 00:00:38,120 --> 00:00:40,560 Speaker 1: It is my honor to bring in Jonathan Seagal, founder 10 00:00:40,560 --> 00:00:44,199 Speaker 1: and CEO of the One Groom and St. K restaurants. Um, 11 00:00:44,200 --> 00:00:46,880 Speaker 1: this is you can find them uh in the meatpacking 12 00:00:47,000 --> 00:00:50,839 Speaker 1: district and uh, you know, across the country. Uh. Jonathan, 13 00:00:50,880 --> 00:00:55,240 Speaker 1: are you expecting to see any kind of meaningful change 14 00:00:55,480 --> 00:00:58,840 Speaker 1: either in your customers or the amount of money people 15 00:00:58,840 --> 00:01:02,440 Speaker 1: are willing to spend um in your restaurants or other Well, 16 00:01:02,720 --> 00:01:04,880 Speaker 1: good morning to you, good money. I certainly think there's 17 00:01:04,920 --> 00:01:09,000 Speaker 1: been a change up until now with the election, people 18 00:01:09,040 --> 00:01:10,840 Speaker 1: tend to be a little bit more cautious about going 19 00:01:10,880 --> 00:01:14,000 Speaker 1: out and spending money, and I think, I think, to 20 00:01:14,000 --> 00:01:15,880 Speaker 1: be honest, people are going to wait and see what happens. 21 00:01:16,760 --> 00:01:18,080 Speaker 1: Can you back up because a lot of people have 22 00:01:18,120 --> 00:01:20,120 Speaker 1: said this, A lot of companies have said that people 23 00:01:20,120 --> 00:01:22,840 Speaker 1: have been more cautious. Really, people don't go out to 24 00:01:22,880 --> 00:01:25,600 Speaker 1: eat because of the election. I think people it becomes 25 00:01:25,760 --> 00:01:28,280 Speaker 1: it becomes a mainstream event that people are focused on 26 00:01:28,280 --> 00:01:31,240 Speaker 1: amongst themselves, and they tend to become more isolated, and 27 00:01:31,240 --> 00:01:33,880 Speaker 1: they're more focused on what's going on. And whenever any 28 00:01:33,959 --> 00:01:37,760 Speaker 1: major event happens, whether it's a sport event and the Olympics, 29 00:01:38,000 --> 00:01:43,560 Speaker 1: World Series, anything that's major that really embraces the a 30 00:01:43,600 --> 00:01:46,320 Speaker 1: great many people, it has an impact on people's expenditure 31 00:01:46,440 --> 00:01:49,200 Speaker 1: because they also become aware of the implications of the results. 32 00:01:49,640 --> 00:01:52,640 Speaker 1: And that's also part of what affects their decision to 33 00:01:52,680 --> 00:01:55,120 Speaker 1: spend money. Do they think the economy is going to boom, 34 00:01:55,160 --> 00:01:56,560 Speaker 1: they think it's not going to boom. Do they need 35 00:01:56,600 --> 00:01:59,000 Speaker 1: to save more money? Is look what's happened this morning. 36 00:01:59,160 --> 00:02:01,480 Speaker 1: Obviously the small in the market things that Clinton is 37 00:02:01,520 --> 00:02:03,520 Speaker 1: gonna win, and and the markets up two hundred fifty 38 00:02:03,520 --> 00:02:07,760 Speaker 1: seven points. So there's absolutely a correlation between economics and 39 00:02:07,840 --> 00:02:12,800 Speaker 1: spenditure and investment and and and obviously uh election results. 40 00:02:13,200 --> 00:02:15,120 Speaker 1: You know, I can tell by your accent that you 41 00:02:15,240 --> 00:02:18,720 Speaker 1: come from the heartland of America in the center. How 42 00:02:18,840 --> 00:02:21,240 Speaker 1: how did you did you call the brexit? I mean, 43 00:02:21,760 --> 00:02:25,000 Speaker 1: you know, so I have connected the completely got the 44 00:02:25,040 --> 00:02:29,359 Speaker 1: Brexit wrong. I thought that we would stay um And 45 00:02:29,400 --> 00:02:32,440 Speaker 1: what is unbelievably interesting now that seems to have been 46 00:02:32,480 --> 00:02:36,000 Speaker 1: washed over is what occurred last Friday in London where 47 00:02:36,040 --> 00:02:39,200 Speaker 1: the part of the High Court ruled that there has 48 00:02:39,280 --> 00:02:42,160 Speaker 1: to be an Act of Parliament in order to exit 49 00:02:42,240 --> 00:02:45,480 Speaker 1: to enforce Article forty. You think that we washed over 50 00:02:45,520 --> 00:02:51,680 Speaker 1: that were bloomberg. So this is an unbelievable constitutional will 51 00:02:51,720 --> 00:02:53,960 Speaker 1: that affect your business? With that affect you because I know, 52 00:02:54,080 --> 00:02:56,799 Speaker 1: for example, you've got projects in the lands. You've got 53 00:02:56,880 --> 00:03:00,520 Speaker 1: business in London, Toronto, or land on Miami, Chica. I mean, 54 00:03:00,560 --> 00:03:02,760 Speaker 1: I want you to tell people about some of these places. 55 00:03:02,760 --> 00:03:04,359 Speaker 1: So let's just talk about that for a minute, because 56 00:03:04,360 --> 00:03:06,320 Speaker 1: this is a great question in the Again, in the 57 00:03:06,440 --> 00:03:10,480 Speaker 1: lead up to the Brexit, our business was impacted. Following 58 00:03:10,480 --> 00:03:13,799 Speaker 1: the Brexit, our business returned to where it was. It's 59 00:03:14,000 --> 00:03:18,440 Speaker 1: uncertainty that creates cautiousness. Once that uncertainty has gone, it 60 00:03:18,480 --> 00:03:20,680 Speaker 1: doesn't necessarily have to gone the way you wanted it. 61 00:03:20,760 --> 00:03:24,120 Speaker 1: To go. But once that uncertainty has past us, people 62 00:03:24,160 --> 00:03:25,920 Speaker 1: become a little bit more relaxed. If you look at 63 00:03:25,919 --> 00:03:29,440 Speaker 1: our businesses, particularly in the United Kingdom where we operate 64 00:03:29,520 --> 00:03:33,400 Speaker 1: seven facilities, seven venues in two facilities. In the lead 65 00:03:33,480 --> 00:03:36,600 Speaker 1: up to Brexit, we were impacted and post Brexit business 66 00:03:36,680 --> 00:03:38,440 Speaker 1: to kind of return and in fact is up and 67 00:03:38,520 --> 00:03:41,080 Speaker 1: where it was at this time last year. Restaurant, we 68 00:03:41,160 --> 00:03:45,160 Speaker 1: just gotta make sure food restaurant hospitality, right, I just 69 00:03:45,200 --> 00:03:48,440 Speaker 1: giving example some people understand. So so we have a 70 00:03:48,520 --> 00:03:51,120 Speaker 1: number of venues in England we operate as part of 71 00:03:51,120 --> 00:03:53,480 Speaker 1: our business we go into hotels and run their entire 72 00:03:53,520 --> 00:03:55,800 Speaker 1: food and beverage. So we do that in the Mere 73 00:03:55,880 --> 00:03:58,600 Speaker 1: Hotel in London. We also have an STK restaurant. We 74 00:03:58,640 --> 00:04:00,960 Speaker 1: also have a rooftop bar, and then we have a 75 00:04:01,000 --> 00:04:04,520 Speaker 1: facility in the Hippodrome casino. So really in our London 76 00:04:05,160 --> 00:04:07,720 Speaker 1: is a snapshot of what we do globally as a company. 77 00:04:07,840 --> 00:04:10,160 Speaker 1: And it's also training across the board of people that 78 00:04:10,200 --> 00:04:13,520 Speaker 1: are at all different levels of disposable income. We're sitting 79 00:04:13,560 --> 00:04:15,360 Speaker 1: with someone who lives much better than I do. I 80 00:04:15,440 --> 00:04:18,440 Speaker 1: am sure with all of the food and the entertainment 81 00:04:18,520 --> 00:04:21,760 Speaker 1: and the beautiful hotels that you can go visit. One 82 00:04:21,800 --> 00:04:27,279 Speaker 1: thing I am wondering once the uncertainty settles, there are 83 00:04:27,360 --> 00:04:30,640 Speaker 1: some policies that could make a big difference. Another word 84 00:04:30,640 --> 00:04:33,720 Speaker 1: for one, in particular minimum wage. Do you think that 85 00:04:33,800 --> 00:04:36,960 Speaker 1: if a minimum wage was lifted in the US that 86 00:04:37,000 --> 00:04:39,320 Speaker 1: would affect your business at all? So it definitely affects 87 00:04:39,320 --> 00:04:41,600 Speaker 1: our business, and and part of the problem that's driving 88 00:04:42,120 --> 00:04:46,280 Speaker 1: this minimum wage issue is a very complex arena. Part 89 00:04:46,360 --> 00:04:48,920 Speaker 1: of the problem. For first, you have to split out 90 00:04:48,920 --> 00:04:52,000 Speaker 1: the beneficiaries of it. People that earn money in fast 91 00:04:52,000 --> 00:04:55,400 Speaker 1: casual or in fast food restaurants are not benefits of 92 00:04:55,720 --> 00:04:58,479 Speaker 1: the tip structure, so minimum wage is a really important 93 00:04:58,520 --> 00:05:01,720 Speaker 1: asset for them. The people that work in in casual 94 00:05:01,800 --> 00:05:04,480 Speaker 1: or in fine dining our benefit from the tip structure. 95 00:05:05,000 --> 00:05:09,880 Speaker 1: So you have situations where as you systematically increase minimum wage, 96 00:05:10,600 --> 00:05:13,200 Speaker 1: you're still you're paying your waste weight staff more. And 97 00:05:13,200 --> 00:05:16,440 Speaker 1: whilst tipping still exists, they're still going to twenty percent tipping. 98 00:05:16,480 --> 00:05:19,320 Speaker 1: Do you think that the tipping structure should go away? Well, 99 00:05:19,360 --> 00:05:21,800 Speaker 1: tipping needs to change. One of the ways. It either 100 00:05:21,920 --> 00:05:24,600 Speaker 1: needs to change or the laws that impact it need 101 00:05:24,680 --> 00:05:26,920 Speaker 1: to change. The biggest problem with the tipping sits and 102 00:05:26,960 --> 00:05:29,800 Speaker 1: which is I don't understand why the authorities haven't really 103 00:05:29,839 --> 00:05:32,320 Speaker 1: worked out because it doesn't take a brain surgeon to 104 00:05:32,360 --> 00:05:35,440 Speaker 1: work it out. The rules require that the only people 105 00:05:35,480 --> 00:05:37,040 Speaker 1: that can benefit from the tips and the people that 106 00:05:37,160 --> 00:05:41,839 Speaker 1: actually touched the consumer, So the the the servers, the 107 00:05:41,880 --> 00:05:44,120 Speaker 1: bar staff, et cetera. But if you work in the kitchen, 108 00:05:44,520 --> 00:05:46,040 Speaker 1: or if you work in the back of house, or 109 00:05:46,080 --> 00:05:48,080 Speaker 1: if you work at any other areas where you don't 110 00:05:48,120 --> 00:05:50,360 Speaker 1: impact the guest, you don't actually get to share in 111 00:05:50,360 --> 00:05:52,600 Speaker 1: the tip pole. Now, the truth is you can't sit 112 00:05:52,600 --> 00:05:54,040 Speaker 1: and arrest on and have a meal and this there's 113 00:05:54,040 --> 00:05:56,600 Speaker 1: a kitchen cook in it. But because we can't share 114 00:05:56,640 --> 00:05:59,960 Speaker 1: the tips round amongst everybody, you have this terrible imbalance. 115 00:06:00,320 --> 00:06:02,839 Speaker 1: So certainly at the fine dining and the casual dining 116 00:06:02,880 --> 00:06:05,640 Speaker 1: in arena, one of the areas to fix the the 117 00:06:05,839 --> 00:06:08,200 Speaker 1: split or the or the differential between the back of 118 00:06:08,200 --> 00:06:11,159 Speaker 1: house and front house is just enable everybody down for 119 00:06:11,279 --> 00:06:13,839 Speaker 1: managers to share in the tip pole. That one little 120 00:06:13,920 --> 00:06:17,840 Speaker 1: fix will change that whole category of income, and then 121 00:06:17,880 --> 00:06:20,280 Speaker 1: you can really start to focus on people that are 122 00:06:20,279 --> 00:06:22,240 Speaker 1: not necessarily in a tip pool in the in the 123 00:06:22,279 --> 00:06:25,479 Speaker 1: in the fast food restaurant, where obviously people are entitled 124 00:06:25,520 --> 00:06:29,080 Speaker 1: and should should earn a living wage. The cost of 125 00:06:29,120 --> 00:06:31,880 Speaker 1: doing business. Maybe speak a little bit about that, whether 126 00:06:31,920 --> 00:06:34,320 Speaker 1: it's the input costs, or the real estate costs, or 127 00:06:34,400 --> 00:06:36,920 Speaker 1: just the cost and the risk of going bus Because 128 00:06:36,920 --> 00:06:39,800 Speaker 1: the restaurant industry, as I heard, well not a short thing. No, no, 129 00:06:39,920 --> 00:06:42,600 Speaker 1: Well listen, the restaurant industries in recession at the moment. 130 00:06:42,600 --> 00:06:45,039 Speaker 1: There's no question of doubt about that. And it's it's 131 00:06:45,080 --> 00:06:47,680 Speaker 1: based on all that. It's we're in the perfect storm. 132 00:06:47,760 --> 00:06:50,159 Speaker 1: We have rising rents. You know, every year our rent 133 00:06:50,160 --> 00:06:52,520 Speaker 1: to go up three five, the landlords do not put 134 00:06:52,560 --> 00:06:55,600 Speaker 1: them up. We have increased food costs and we now 135 00:06:55,640 --> 00:07:00,360 Speaker 1: have increased labor costs. We have uncertainty, we have increased petition, 136 00:07:00,400 --> 00:07:03,520 Speaker 1: We have competition from disruptors. You know, you have situations 137 00:07:03,520 --> 00:07:05,960 Speaker 1: with the seamless and the internet food delivery service that 138 00:07:06,040 --> 00:07:08,440 Speaker 1: impact what's going on in the actual restaurant. Sure that 139 00:07:08,520 --> 00:07:10,480 Speaker 1: those that will argue to say, well, you're still getting 140 00:07:10,560 --> 00:07:13,000 Speaker 1: you're selling a meal if you sell it through seamless, 141 00:07:13,040 --> 00:07:15,000 Speaker 1: if you sell it in store. But the truth is 142 00:07:15,040 --> 00:07:17,240 Speaker 1: you're not getting the liquor sales that help to add 143 00:07:17,280 --> 00:07:19,800 Speaker 1: to the profitability of the company, of the of the business, 144 00:07:20,040 --> 00:07:22,239 Speaker 1: and therefore, as a result, we're in a perfect storm, 145 00:07:22,320 --> 00:07:25,200 Speaker 1: in a perfect storm of problems. And the and the 146 00:07:25,200 --> 00:07:27,200 Speaker 1: authorities need to wake up to this because if you 147 00:07:27,240 --> 00:07:32,560 Speaker 1: start to to marginalize the restaurant industry that has overwhelming 148 00:07:32,560 --> 00:07:37,000 Speaker 1: imployments are mostly self inflicted. Yes and no, the rents 149 00:07:37,040 --> 00:07:40,840 Speaker 1: certainly are not. Food costs are certainly not. Um I 150 00:07:40,840 --> 00:07:43,560 Speaker 1: think you know, the let the register, the the legislation 151 00:07:43,600 --> 00:07:45,960 Speaker 1: that we work under, and the and all the enforcement 152 00:07:46,000 --> 00:07:48,160 Speaker 1: rules are crazy. I mean, if you're sitting and understand, 153 00:07:48,320 --> 00:07:50,440 Speaker 1: here's a crazy enforcement law. How about this, It's going 154 00:07:50,480 --> 00:07:52,600 Speaker 1: to give you a five seconds. Okay, if you don't 155 00:07:52,640 --> 00:07:54,960 Speaker 1: see your patios the way they're supposed to be seen, 156 00:07:55,000 --> 00:07:57,559 Speaker 1: but move them to put two fours together, you're breaking 157 00:07:57,560 --> 00:08:00,840 Speaker 1: the law. Charlathan Siegal, thank you very much, Founder, chief 158 00:08:00,880 --> 00:08:04,120 Speaker 1: executive the One Group and S t K Restaurants. This 159 00:08:04,240 --> 00:08:19,840 Speaker 1: is Bloomberg, all right. Thirteen hours, seven minutes and fifty 160 00:08:19,960 --> 00:08:25,360 Speaker 1: six seconds until the first poles open in the clearly 161 00:08:25,840 --> 00:08:30,000 Speaker 1: three towns in New Hampshire are set to vote at midnight. 162 00:08:30,840 --> 00:08:33,240 Speaker 1: So Lisa Brahmins, I think he'll be staying up quite 163 00:08:33,320 --> 00:08:36,320 Speaker 1: a late night, and I think that Mark Niquett also 164 00:08:36,440 --> 00:08:38,720 Speaker 1: better it gets some sleep in the afternoon because he'll 165 00:08:38,760 --> 00:08:41,959 Speaker 1: be spending the night watching. He's our politics and national 166 00:08:42,040 --> 00:08:45,440 Speaker 1: government reporter. Normally he joins us from Columbus, Ohio, but 167 00:08:45,440 --> 00:08:47,959 Speaker 1: he joins us here in our studios in our global 168 00:08:48,000 --> 00:08:50,360 Speaker 1: headquarters in New York. Thank you very much for being here. Mark. 169 00:08:51,120 --> 00:08:53,199 Speaker 1: So what are we supposed to take What's going to 170 00:08:53,280 --> 00:08:55,920 Speaker 1: happen in the next thirteen hours that is going to 171 00:08:56,080 --> 00:08:58,520 Speaker 1: matter to the outcome of the election. Well, we're gonna 172 00:08:58,520 --> 00:09:00,880 Speaker 1: see sort of the final push by the campaigns. We 173 00:09:00,960 --> 00:09:03,920 Speaker 1: have Hillary Clinton with rallies all the way up to midnight, 174 00:09:04,480 --> 00:09:08,760 Speaker 1: her last rallies in Raleigh, North Carolina at midnight. Donald 175 00:09:08,760 --> 00:09:10,280 Speaker 1: Trump will be doing the same and this is sort 176 00:09:10,280 --> 00:09:13,400 Speaker 1: of the last push to get you know, the final late, late, 177 00:09:13,480 --> 00:09:15,640 Speaker 1: late deciders, the people who are actually going to the 178 00:09:15,640 --> 00:09:18,880 Speaker 1: polls tomorrow who haven't already early voted, you know, maybe 179 00:09:18,920 --> 00:09:21,439 Speaker 1: sway just the last few folks that could make a 180 00:09:21,480 --> 00:09:23,600 Speaker 1: difference in some of these key battleground states that could 181 00:09:23,600 --> 00:09:27,080 Speaker 1: decide the election. So you wrote a story basically saying 182 00:09:27,200 --> 00:09:31,120 Speaker 1: that even though James Comey, the FBI director, came out 183 00:09:31,280 --> 00:09:35,200 Speaker 1: and said that he wasn't going to charge any charge 184 00:09:35,280 --> 00:09:38,560 Speaker 1: Hillary Clinton with any crime and that the new review 185 00:09:38,600 --> 00:09:42,040 Speaker 1: of emails did not change the FBI's deliberations. This clears 186 00:09:42,080 --> 00:09:44,600 Speaker 1: the cloud. But you're saying the damage is done. Yeah, 187 00:09:44,600 --> 00:09:46,840 Speaker 1: on a couple of levels. I mean, one, you've had 188 00:09:46,960 --> 00:09:50,200 Speaker 1: millions of people casting early votes at a time this 189 00:09:50,240 --> 00:09:51,960 Speaker 1: cloud was sort of hanging over her head, and to 190 00:09:52,000 --> 00:09:54,960 Speaker 1: the extent that it affected votes, you know, there's no 191 00:09:55,000 --> 00:09:57,480 Speaker 1: way to change those, of course, but I think fundamentally 192 00:09:57,600 --> 00:09:59,920 Speaker 1: it really did change that, you know, the trajectory of 193 00:09:59,920 --> 00:10:02,959 Speaker 1: the race. You know, think about before the first um 194 00:10:03,120 --> 00:10:06,719 Speaker 1: FBI letter came out from Director came Um, I was 195 00:10:06,760 --> 00:10:09,959 Speaker 1: actually was aboard the Clinton campaign plane, you know, when 196 00:10:10,000 --> 00:10:11,840 Speaker 1: that news broke. We were in mid air and they 197 00:10:11,840 --> 00:10:14,080 Speaker 1: were doing a press conference on the plane talking about 198 00:10:14,080 --> 00:10:17,319 Speaker 1: how we can't be complacent, you know, complacencies our enemy. 199 00:10:17,360 --> 00:10:19,240 Speaker 1: Because the polls at that time looked like she was 200 00:10:19,480 --> 00:10:22,280 Speaker 1: headed toward victory and maybe a decisive victory, and that 201 00:10:22,400 --> 00:10:24,600 Speaker 1: you know, letters just sort of reset the race where 202 00:10:24,600 --> 00:10:27,760 Speaker 1: it reinforced you know, questions that people might have had 203 00:10:27,800 --> 00:10:31,120 Speaker 1: about her use of emails. It gave Donald Trump, you know, 204 00:10:31,200 --> 00:10:34,600 Speaker 1: something to to talk about on his campaign rallies. And 205 00:10:34,600 --> 00:10:37,320 Speaker 1: it also you know, what we're seeing is maybe affected 206 00:10:37,960 --> 00:10:42,720 Speaker 1: independence or you know, even Republican leaning independence or um 207 00:10:42,720 --> 00:10:45,600 Speaker 1: suburban women who you know, maybe weren't enamored of Trump, 208 00:10:45,679 --> 00:10:48,040 Speaker 1: but we're you know, unsure about Hillary Clinton, and this 209 00:10:48,160 --> 00:10:50,360 Speaker 1: sort of made them pause about supporting her. So it 210 00:10:50,400 --> 00:10:52,480 Speaker 1: made the race tighten, no question. But why wouldn't they 211 00:10:52,480 --> 00:10:54,079 Speaker 1: reverse that. I mean, if it had such a big 212 00:10:54,080 --> 00:10:56,559 Speaker 1: effect in the other way, why wouldn't people say, all right, this, 213 00:10:56,640 --> 00:10:58,680 Speaker 1: there's nothing to see here. Well, I think the people 214 00:10:58,679 --> 00:11:00,480 Speaker 1: were talking to say it will have some of that 215 00:11:00,520 --> 00:11:03,520 Speaker 1: effect that Again, these are late, late deciders, you know, 216 00:11:03,559 --> 00:11:06,000 Speaker 1: who may have had concerns about Clinton. Maybe this removes 217 00:11:06,000 --> 00:11:07,760 Speaker 1: that cloud and they go ahead and vote for her. 218 00:11:07,920 --> 00:11:09,840 Speaker 1: But I think the feeling was the race was already 219 00:11:09,880 --> 00:11:12,640 Speaker 1: tightening with Republicans coming home is what they say. You know, 220 00:11:12,679 --> 00:11:14,920 Speaker 1: if you're a Republican and maybe you're not sure about 221 00:11:15,000 --> 00:11:16,880 Speaker 1: Donald Trump, but you're not sure about her either, you 222 00:11:16,920 --> 00:11:20,000 Speaker 1: still vote Republican. So this could help on the margins 223 00:11:20,080 --> 00:11:22,920 Speaker 1: with you know, a really really close race, but you know, 224 00:11:22,960 --> 00:11:24,800 Speaker 1: the feeling is a lot of it's already baked in. 225 00:11:24,840 --> 00:11:27,480 Speaker 1: If you cared about this issue or didn't care about 226 00:11:27,480 --> 00:11:29,800 Speaker 1: this issue, you know this isn't gonna change your opinion. 227 00:11:30,360 --> 00:11:35,160 Speaker 1: Mark Niquette, the use of polling data and projections. Uh. 228 00:11:35,360 --> 00:11:39,520 Speaker 1: Major news organizations do not call elections until after the 229 00:11:39,600 --> 00:11:44,920 Speaker 1: polls have closed, but using projections during the election day 230 00:11:45,120 --> 00:11:47,959 Speaker 1: is something that apparently is gonna gonna happen. There's a 231 00:11:48,280 --> 00:11:51,560 Speaker 1: something called vote Caster, and they're going to team up 232 00:11:51,559 --> 00:11:54,480 Speaker 1: with Slate and Vice, I believe, and they're gonna be 233 00:11:54,600 --> 00:11:59,200 Speaker 1: giving information out about the polling while the election is 234 00:11:59,240 --> 00:12:03,760 Speaker 1: still taking place. Right, And traditionally we've also had exit polling. 235 00:12:03,800 --> 00:12:06,120 Speaker 1: This is somewhat similar to that, where you know, they 236 00:12:06,160 --> 00:12:08,920 Speaker 1: take a slice of the electorate coming off the you know, 237 00:12:09,040 --> 00:12:11,360 Speaker 1: from from voting and get a sense of, wow, the 238 00:12:11,400 --> 00:12:13,679 Speaker 1: vote's going to break down. Uh. And it is always 239 00:12:13,720 --> 00:12:15,880 Speaker 1: a little bit you know, dicey, from the standpoint of 240 00:12:15,920 --> 00:12:18,120 Speaker 1: people are still voting, and like you say, there's sort 241 00:12:18,120 --> 00:12:20,600 Speaker 1: of a tradition it might discourage people. It might discourage 242 00:12:20,640 --> 00:12:22,679 Speaker 1: people from actually going to the polls if they think 243 00:12:22,720 --> 00:12:26,360 Speaker 1: that their vote doesn't matter because of these early estimates. 244 00:12:26,360 --> 00:12:28,120 Speaker 1: For example, Right, and you've got people on the West 245 00:12:28,160 --> 00:12:30,480 Speaker 1: Coast voting after you know the race has been called 246 00:12:30,600 --> 00:12:32,840 Speaker 1: or some states have already come in, And you know 247 00:12:32,880 --> 00:12:35,360 Speaker 1: that that's always been a sort of attention in terms of, 248 00:12:35,520 --> 00:12:37,800 Speaker 1: you know, we want to get the information as quickly 249 00:12:37,800 --> 00:12:39,079 Speaker 1: as we can, and we want to see what the 250 00:12:39,120 --> 00:12:42,400 Speaker 1: trends are. But you know, ultimately all that matters is 251 00:12:42,440 --> 00:12:45,080 Speaker 1: what's the final vote count when you know when all 252 00:12:45,080 --> 00:12:47,080 Speaker 1: the ballots are counted. So since I want to get 253 00:12:47,240 --> 00:12:49,480 Speaker 1: a sense of who's winning and I wanted the information, Now, 254 00:12:49,760 --> 00:12:52,960 Speaker 1: what are the early polls saying, Well, the polls suggests 255 00:12:53,000 --> 00:12:55,960 Speaker 1: that the race has stabilized, that you know, Hillary Clinton 256 00:12:56,080 --> 00:12:59,560 Speaker 1: still has a structural advantage. What about the actual early voting, Well, 257 00:12:59,559 --> 00:13:01,520 Speaker 1: the early vot voting. Again, I think the the early 258 00:13:01,640 --> 00:13:04,520 Speaker 1: voting suggests that you know, Clinton had an advantage there, 259 00:13:04,520 --> 00:13:05,959 Speaker 1: but she had to have an advantage, I mean the 260 00:13:06,000 --> 00:13:09,400 Speaker 1: way that traditionally works, as Republicans are better at election 261 00:13:09,480 --> 00:13:12,679 Speaker 1: day turnout. You know, even if you know Republican like 262 00:13:12,720 --> 00:13:16,080 Speaker 1: Mitt Romney and twelve loses the election, he'll often win 263 00:13:16,160 --> 00:13:17,920 Speaker 1: in terms of the vote that actually comes out on 264 00:13:17,960 --> 00:13:20,679 Speaker 1: election day. So the idea for Democrats has been and 265 00:13:20,920 --> 00:13:23,719 Speaker 1: certainly the last three cycles. Bank your votes early, get 266 00:13:23,720 --> 00:13:26,120 Speaker 1: your supporters to cast their ballots early, and sort of 267 00:13:26,120 --> 00:13:29,439 Speaker 1: build up a lead that can't be overcome on election day. 268 00:13:29,440 --> 00:13:31,440 Speaker 1: And that's what you're seeing in states like Nevada, where 269 00:13:31,559 --> 00:13:34,920 Speaker 1: the Clinton campaign, for example, estimates Donald Trump would have 270 00:13:34,920 --> 00:13:38,400 Speaker 1: to get ten percent of all of the ten percentage 271 00:13:38,400 --> 00:13:40,640 Speaker 1: points of all the election day votes to overcome the 272 00:13:40,720 --> 00:13:44,200 Speaker 1: lead that Clinton has built with early voting. Mark Niquette, 273 00:13:44,360 --> 00:13:47,600 Speaker 1: thank you so much for joining. I just ask, where's Hill? 274 00:13:47,640 --> 00:13:50,280 Speaker 1: Where's Hillary Clinton going to vote? Yeah, that's a good question. 275 00:13:50,320 --> 00:13:53,680 Speaker 1: I haven't seen any announcement. I'm assuming it's New York, 276 00:13:53,760 --> 00:13:58,280 Speaker 1: but also Donald Trump obviously New Yorkers. Mark Niquette, Limberg 277 00:13:58,320 --> 00:14:00,560 Speaker 1: Politics reporter, thank you so much for joining us. Market 278 00:14:00,559 --> 00:14:03,320 Speaker 1: cat has a full party ready to go just to 279 00:14:03,360 --> 00:14:06,000 Speaker 1: celebrate the end of the election season. He cannot wait. 280 00:14:06,040 --> 00:14:08,960 Speaker 1: An Lisa bram Waits. I am here with Tim Fox. 281 00:14:09,080 --> 00:14:24,400 Speaker 1: This is Bloomberg. You know who we call on when 282 00:14:24,400 --> 00:14:26,880 Speaker 1: we want to know everything about the retail industry, our 283 00:14:26,960 --> 00:14:31,720 Speaker 1: own pun. I'm Goyal, senior US retail analyst for Bloomberg Intelligence. 284 00:14:32,080 --> 00:14:34,600 Speaker 1: Great to have you with us. Tell us about the 285 00:14:34,640 --> 00:14:40,040 Speaker 1: big department stores and they're upcoming all important holiday selling season. 286 00:14:40,640 --> 00:14:43,360 Speaker 1: So the department stores have been struggling, as you know, 287 00:14:43,400 --> 00:14:45,200 Speaker 1: at least to most of them, are many of them, 288 00:14:45,280 --> 00:14:47,240 Speaker 1: and I don't think there will be any different this 289 00:14:47,320 --> 00:14:50,840 Speaker 1: holiday season. Um. They're all slated to report earnings this week, 290 00:14:50,960 --> 00:14:55,440 Speaker 1: beginning Thursday with Macy's North German Cold and then UM 291 00:14:55,560 --> 00:14:58,640 Speaker 1: we have DC Penny reporting on Friday. Now, what I 292 00:14:58,640 --> 00:15:02,400 Speaker 1: can tell you here is that sales likely suffered for 293 00:15:02,480 --> 00:15:05,120 Speaker 1: many of them UM in third quarter, and that's not 294 00:15:05,240 --> 00:15:08,360 Speaker 1: a good sign heading into holidays because it shows the 295 00:15:08,440 --> 00:15:12,720 Speaker 1: lack of customer interest in big box retailing and the 296 00:15:12,800 --> 00:15:15,920 Speaker 1: lack of desire to go to a mall. That said, 297 00:15:16,200 --> 00:15:19,720 Speaker 1: we think margins will likely hold up better because they 298 00:15:19,760 --> 00:15:22,680 Speaker 1: are managing their inventory well, and from what I can 299 00:15:22,720 --> 00:15:27,200 Speaker 1: see in the space, the promotional cadence has somewhat moderated. 300 00:15:27,440 --> 00:15:30,200 Speaker 1: Now that doesn't mean that there aren't any more promotions, 301 00:15:30,440 --> 00:15:34,040 Speaker 1: but they're being very strategic with them and they're more planned. Held. 302 00:15:34,080 --> 00:15:36,240 Speaker 1: One second, when you say that you're talking about how 303 00:15:36,320 --> 00:15:39,920 Speaker 1: much discounts they're giving. That is right. So you know, 304 00:15:40,000 --> 00:15:43,840 Speaker 1: typically you've seen sixty seventy percent clearance racks and many 305 00:15:43,880 --> 00:15:47,400 Speaker 1: of these retailers, and that's largely because of lots of 306 00:15:47,440 --> 00:15:51,400 Speaker 1: inventory left over. So they're watching their inventory, they're keeping 307 00:15:51,440 --> 00:15:53,880 Speaker 1: an eye on how much they're selling, and they're cutting 308 00:15:53,880 --> 00:15:56,440 Speaker 1: back orders just to make sure that they don't get 309 00:15:56,440 --> 00:15:59,160 Speaker 1: into that position they did last year where they had 310 00:15:59,200 --> 00:16:02,320 Speaker 1: way too much, couldn't sell it and had to discount 311 00:16:02,320 --> 00:16:06,000 Speaker 1: it aggressively to make room for new merchandise. Right. Well, 312 00:16:06,080 --> 00:16:08,640 Speaker 1: these are not all the same either. I mean, Nordstrom 313 00:16:08,720 --> 00:16:12,080 Speaker 1: usually caters to a higher end UH clients help were 314 00:16:12,240 --> 00:16:15,400 Speaker 1: whereas Coals is more um of sort of middle or 315 00:16:15,520 --> 00:16:20,040 Speaker 1: lower h tier of shoppers. Correct, I mean there's there 316 00:16:20,080 --> 00:16:22,120 Speaker 1: there is a split here. So which do you which 317 00:16:22,120 --> 00:16:24,520 Speaker 1: do you expect to do better? So for a third quarter, 318 00:16:24,560 --> 00:16:27,040 Speaker 1: I think nord Storm will do, but better only because 319 00:16:27,080 --> 00:16:29,800 Speaker 1: they have that one week of their anniversary sale moving 320 00:16:29,840 --> 00:16:32,440 Speaker 1: into the third quarter, and even in general. You know, 321 00:16:32,560 --> 00:16:35,680 Speaker 1: the problem that Nordstrom has right now is tourism and 322 00:16:35,760 --> 00:16:39,120 Speaker 1: just that the luxury consumer that's coming from abroad isn't 323 00:16:39,200 --> 00:16:42,320 Speaker 1: hitting those key tourist areas, whether it's Miami, New York City, 324 00:16:42,720 --> 00:16:46,520 Speaker 1: Los Angeles, or so forth. If that starts to come back, 325 00:16:46,600 --> 00:16:48,480 Speaker 1: I think they'll do better. But when you look at 326 00:16:48,480 --> 00:16:50,920 Speaker 1: the Macy's, the Colds, the Dillards, the more mid tier 327 00:16:51,080 --> 00:16:54,200 Speaker 1: retailers that are essentially overstored. I mean I feel like 328 00:16:54,200 --> 00:16:57,240 Speaker 1: a Macy's they have a hundred stores. Coals has over 329 00:16:57,280 --> 00:17:01,480 Speaker 1: a thousand. Too many stores. Uh, no real place of 330 00:17:01,640 --> 00:17:05,040 Speaker 1: why I should come here. I mean, there's little differentiation, 331 00:17:05,640 --> 00:17:10,720 Speaker 1: so consumers are just opting to go elsewhere. T j X, 332 00:17:10,800 --> 00:17:17,600 Speaker 1: Ross Stores, Burlington's stores, these are the thrifty retailers. Fort 333 00:17:18,119 --> 00:17:22,280 Speaker 1: off retail prices. Are they going to benefit Absolutely, They've 334 00:17:22,320 --> 00:17:25,040 Speaker 1: been benefiting for the last at say seven eight years, 335 00:17:25,040 --> 00:17:27,359 Speaker 1: and they continue to do so. And it's not so 336 00:17:27,440 --> 00:17:30,119 Speaker 1: much about the discount Well, the discounts great, it's not 337 00:17:30,200 --> 00:17:32,760 Speaker 1: when you walk in there, you'll always find something new. 338 00:17:33,119 --> 00:17:36,920 Speaker 1: So customers like that element of surprise when I walk in, 339 00:17:37,240 --> 00:17:39,120 Speaker 1: I grab it. If I don't get it, it may 340 00:17:39,119 --> 00:17:42,320 Speaker 1: not be here. And that's really what's been helping these retailers. 341 00:17:42,359 --> 00:17:45,280 Speaker 1: These retailers don't have an online presence. T j X 342 00:17:45,280 --> 00:17:48,160 Speaker 1: is very small, so all the business that they're doing 343 00:17:48,240 --> 00:17:50,920 Speaker 1: is in the store and they're getting customers to come 344 00:17:50,960 --> 00:17:53,360 Speaker 1: to that store. So we've heard a lot of excuses 345 00:17:53,520 --> 00:17:56,720 Speaker 1: over the quarter as We've heard about whether that was 346 00:17:56,800 --> 00:17:58,800 Speaker 1: too warm, We've heard about whether that was too cold. 347 00:17:59,040 --> 00:18:01,880 Speaker 1: We've heard recently about the election and how that's crimping 348 00:18:01,920 --> 00:18:05,240 Speaker 1: people's expenditures. What do you expect to be the excuse 349 00:18:05,320 --> 00:18:08,600 Speaker 1: this time around and maybe whether again, um, you know, 350 00:18:08,720 --> 00:18:11,080 Speaker 1: it's it's very important, as much as we'd like to 351 00:18:11,119 --> 00:18:14,000 Speaker 1: call it an excuse, but apparel retailers needed to get 352 00:18:14,000 --> 00:18:17,040 Speaker 1: cold and for key to self sweaters and cold weather accessories. 353 00:18:17,359 --> 00:18:20,760 Speaker 1: So as of right now, temperatures are i'd say, you know, 354 00:18:21,080 --> 00:18:23,080 Speaker 1: have so many degrees here last week, so they're not 355 00:18:23,320 --> 00:18:24,960 Speaker 1: that cold where it would prompt you to get a 356 00:18:24,960 --> 00:18:27,840 Speaker 1: coat or a sweater. But if they don't turn cold, 357 00:18:28,160 --> 00:18:30,560 Speaker 1: we will have another excuse, and it will be whether 358 00:18:30,840 --> 00:18:33,399 Speaker 1: if temperatures do cool, though, I think they'll all be 359 00:18:33,480 --> 00:18:36,400 Speaker 1: positioned for a very good fourth quarter because last year 360 00:18:36,480 --> 00:18:40,760 Speaker 1: November was just very bleak. I don't think that the 361 00:18:40,800 --> 00:18:44,199 Speaker 1: weather really affects anything in the cosmetic industry, or am 362 00:18:44,200 --> 00:18:46,359 Speaker 1: I wrong? Maybe I'm wrong there. You know that's the 363 00:18:46,359 --> 00:18:48,720 Speaker 1: one industry that's on fire. Okay, I want you to 364 00:18:48,760 --> 00:18:50,560 Speaker 1: tell me about Alta salon. I want you to tell 365 00:18:50,560 --> 00:18:53,439 Speaker 1: me about the details because there are all new ways 366 00:18:53,520 --> 00:18:57,440 Speaker 1: that cosmetics are now being introduced into the marketplace, whether 367 00:18:57,520 --> 00:19:00,119 Speaker 1: it is dry bars, whether it is all kinds of 368 00:19:00,440 --> 00:19:04,159 Speaker 1: services combined with products. So I don't cover cosmetics closely 369 00:19:04,200 --> 00:19:06,159 Speaker 1: outside of Sapphora, which is in J. C. Penny, but 370 00:19:06,200 --> 00:19:08,400 Speaker 1: I can tell you our hardlines there. Analyst that does 371 00:19:08,880 --> 00:19:11,480 Speaker 1: UM had just mentioned in our holiday preview that Alta 372 00:19:11,560 --> 00:19:14,960 Speaker 1: us on fire growing um double digits for the last 373 00:19:15,000 --> 00:19:17,560 Speaker 1: few years and will continue to do so. And that's 374 00:19:17,680 --> 00:19:21,200 Speaker 1: largely because it kind of fits back into the experience. 375 00:19:21,320 --> 00:19:23,399 Speaker 1: And you know, you want to dress up because you 376 00:19:23,440 --> 00:19:25,800 Speaker 1: want to go out, you want to have nice makeup, 377 00:19:25,840 --> 00:19:27,760 Speaker 1: you want to have your hair done, and you want 378 00:19:27,760 --> 00:19:29,560 Speaker 1: to have the right products to do so. So the 379 00:19:29,600 --> 00:19:32,879 Speaker 1: whole shift that we're seeing from buying things to spending 380 00:19:32,880 --> 00:19:36,400 Speaker 1: money on experiences beauty just sits right into that. Well. 381 00:19:36,400 --> 00:19:39,600 Speaker 1: They talk about things like salon services including hair, brow 382 00:19:39,840 --> 00:19:44,080 Speaker 1: and skin bars, as well as prestige boutiques, and also 383 00:19:44,160 --> 00:19:48,159 Speaker 1: the point is made that their share of the wallet 384 00:19:48,200 --> 00:19:51,040 Speaker 1: and the shopping frequency at an ALTA salon sets them 385 00:19:51,080 --> 00:19:55,359 Speaker 1: apart from their rivals. Yeah, I mean, speaking to ALTA, 386 00:19:55,600 --> 00:19:57,399 Speaker 1: I don't follow it. Once again, I was closely, but 387 00:19:57,480 --> 00:19:59,800 Speaker 1: I can tell you that, you know, it's cheaper right 388 00:20:00,000 --> 00:20:01,680 Speaker 1: to go there, So it kind of fits into the 389 00:20:01,720 --> 00:20:04,960 Speaker 1: discount the value chain, and that's something that the customer 390 00:20:05,040 --> 00:20:07,760 Speaker 1: is looking for right now. So the more expansion that 391 00:20:07,840 --> 00:20:09,520 Speaker 1: they can have, or the more bread that they can 392 00:20:09,520 --> 00:20:12,480 Speaker 1: have in the types of seauty services they offer should 393 00:20:12,520 --> 00:20:15,800 Speaker 1: continue to help them. So what about currency? Does the dollar? 394 00:20:16,040 --> 00:20:18,359 Speaker 1: Are we going to hear anything about the dollar strengthening 395 00:20:18,359 --> 00:20:20,480 Speaker 1: and the potential for that, especially as the Federal reserve 396 00:20:20,600 --> 00:20:23,960 Speaker 1: hikes or is that sort of over? It's not over, 397 00:20:24,040 --> 00:20:26,880 Speaker 1: it's still there. But given that we've seen a lot 398 00:20:26,920 --> 00:20:29,080 Speaker 1: of the surge already with the dollar strengthing in the 399 00:20:29,119 --> 00:20:32,199 Speaker 1: past twelve d eighteen months, I think the pressure is 400 00:20:32,240 --> 00:20:35,520 Speaker 1: somewhat abate heading into four Q and next year. That said, 401 00:20:35,560 --> 00:20:38,760 Speaker 1: if the dollar materially strengthens again, it's it's definitely a 402 00:20:38,800 --> 00:20:43,240 Speaker 1: headwind at least for the retailers with international presence. What 403 00:20:43,520 --> 00:20:45,840 Speaker 1: is your most contrarian belief Who do you think is 404 00:20:45,840 --> 00:20:48,560 Speaker 1: going to outperform who everybody else is discounted or the 405 00:20:48,600 --> 00:20:52,040 Speaker 1: other way around. You know, um, we don't give recommendations 406 00:20:52,040 --> 00:20:53,720 Speaker 1: that I can tell you that J. C. Penny, which 407 00:20:53,720 --> 00:20:56,560 Speaker 1: has been a turnaround story for some time has had 408 00:20:56,680 --> 00:20:59,639 Speaker 1: mixed reviews on you know, whether they'll fall at prey 409 00:20:59,720 --> 00:21:02,240 Speaker 1: to the h broader trends ever seeing in the department 410 00:21:02,280 --> 00:21:05,480 Speaker 1: store space, which is lack of traffic, lack of disinterest 411 00:21:05,560 --> 00:21:08,520 Speaker 1: in buying apparel, and I think they're doing interesting things 412 00:21:08,560 --> 00:21:10,680 Speaker 1: up their stories, like adding appliance so as they are 413 00:21:10,720 --> 00:21:14,200 Speaker 1: also focusing in on their InStyle boutiques, the centered core 414 00:21:14,720 --> 00:21:18,600 Speaker 1: and differentiating themselves from the rust. So while still a 415 00:21:18,680 --> 00:21:22,240 Speaker 1: department store, they're making a lot of headwind headway into 416 00:21:23,240 --> 00:21:26,760 Speaker 1: getting the consumer back into their doors. Punamgoyle, thank you 417 00:21:26,840 --> 00:21:30,400 Speaker 1: so much for joining us. Punamgoyle, senior US retail analyst 418 00:21:30,520 --> 00:21:34,440 Speaker 1: breaking down earnings from Macy's, coals Nords from j C. Penny. 419 00:21:34,440 --> 00:21:36,480 Speaker 1: We're gonna get them all this week and we will 420 00:21:36,480 --> 00:21:41,159 Speaker 1: be keeping track of the uh frankly somewhat beliegaled, beliaguered 421 00:21:41,320 --> 00:21:44,680 Speaker 1: retail industry that has really been uh bearing the brunt 422 00:21:44,920 --> 00:21:48,560 Speaker 1: of the lack of wage increase set is finally starting 423 00:21:48,600 --> 00:21:50,480 Speaker 1: to take ups or perhaps we'll see some better earnings 424 00:21:50,520 --> 00:21:53,600 Speaker 1: there coming from there. And Lisa Brahmoys, I'm here with 425 00:21:53,640 --> 00:22:09,120 Speaker 1: my co host Pim Fox. This is Bloomberg. I want 426 00:22:09,119 --> 00:22:11,120 Speaker 1: to take a look at what I think is probably 427 00:22:11,119 --> 00:22:14,240 Speaker 1: the biggest casino UH in the past three days, and 428 00:22:14,280 --> 00:22:16,560 Speaker 1: that is gold. I mean, gold has been bouncing around. 429 00:22:16,600 --> 00:22:19,720 Speaker 1: First touch funds were piling in putting long bets on gold, 430 00:22:20,119 --> 00:22:24,840 Speaker 1: UH to sort of offset the chance of a Trump victory. 431 00:22:24,960 --> 00:22:27,639 Speaker 1: Now gold is falling the most in a month. I 432 00:22:27,680 --> 00:22:30,120 Speaker 1: want to get some more insight on this, UH. Mike 433 00:22:30,200 --> 00:22:33,119 Speaker 1: mclaughn commodity strategies from Bloomberg Intelligence. What's your take on 434 00:22:33,160 --> 00:22:35,640 Speaker 1: all this? Well, I think today is a good example. 435 00:22:35,680 --> 00:22:38,879 Speaker 1: It's with you know, the highest probability of events with 436 00:22:39,280 --> 00:22:41,719 Speaker 1: a Trump election would be gold going up. So obviously 437 00:22:41,760 --> 00:22:44,879 Speaker 1: we're seeing the opposite today with gold going down. You know, 438 00:22:44,920 --> 00:22:47,239 Speaker 1: it seems unlikely it will happen. But the key thing 439 00:22:47,240 --> 00:22:49,800 Speaker 1: to remember for gold is still on the year and 440 00:22:49,880 --> 00:22:53,400 Speaker 1: why global interest rates negative interest rates US might be tightening. 441 00:22:53,400 --> 00:22:56,199 Speaker 1: The dollar hasn't increased as much. So as far as 442 00:22:56,200 --> 00:22:58,960 Speaker 1: an election relation, I think it's the highest probability in 443 00:22:58,960 --> 00:23:01,520 Speaker 1: commodities that gold would go. But you know, knocking around today, 444 00:23:01,520 --> 00:23:03,280 Speaker 1: I mean the news was pretty significant. Look at the 445 00:23:03,280 --> 00:23:05,960 Speaker 1: stock markets up, it's up, the opposite of gold being down. Today. 446 00:23:06,040 --> 00:23:08,439 Speaker 1: So it's kind of like are you Are you a 447 00:23:08,480 --> 00:23:11,000 Speaker 1: popular guy now, because I mean, boy, you were not 448 00:23:11,119 --> 00:23:13,159 Speaker 1: popular at the beginning of the year anything to do 449 00:23:13,200 --> 00:23:15,600 Speaker 1: with commodities. Everyone wanted to stay about a hundred and 450 00:23:15,640 --> 00:23:18,280 Speaker 1: fifty feet away if we wanted to be in your neighborhood. 451 00:23:18,359 --> 00:23:20,080 Speaker 1: That is very true. And that's part of the reason 452 00:23:20,080 --> 00:23:22,280 Speaker 1: I'm a Bloomberg is because I was at a firm 453 00:23:22,359 --> 00:23:24,960 Speaker 1: name for the last three years and the commodity aum 454 00:23:25,000 --> 00:23:26,720 Speaker 1: just went straight down and finally they hit their stop 455 00:23:26,760 --> 00:23:28,560 Speaker 1: and I ended up in a better place. But I'm 456 00:23:28,560 --> 00:23:30,840 Speaker 1: becoming more popular, I guess. And it's a discussion we 457 00:23:30,880 --> 00:23:33,199 Speaker 1: had earlier. But you know, you look at gold a 458 00:23:33,240 --> 00:23:34,800 Speaker 1: few years from now, and I you know, we all 459 00:23:34,800 --> 00:23:37,520 Speaker 1: hope gold would be down because everything is doing better. Commanities, 460 00:23:37,600 --> 00:23:39,880 Speaker 1: the commanity, the economy is doing better, and the Fed 461 00:23:39,960 --> 00:23:41,320 Speaker 1: doesn't have to you know, we don't have to, like 462 00:23:41,400 --> 00:23:44,199 Speaker 1: stock markets doing better. But gold is still the the 463 00:23:44,359 --> 00:23:47,560 Speaker 1: attractive hedge, and partly you see it in negative interest rates. 464 00:23:47,560 --> 00:23:49,800 Speaker 1: Now we can move on the other commodities for instance, Like, 465 00:23:49,880 --> 00:23:52,480 Speaker 1: what's really would be a big problem I think if 466 00:23:52,520 --> 00:23:55,959 Speaker 1: Trump were to be elected, is his anti trade status 467 00:23:56,000 --> 00:24:00,520 Speaker 1: so you think of commandities that US really exports corn, wheat, soybeans, 468 00:24:00,720 --> 00:24:02,639 Speaker 1: that would be a problem there because that extra it 469 00:24:02,640 --> 00:24:04,720 Speaker 1: would kind of hurt that export market. Well, but wouldn't 470 00:24:04,720 --> 00:24:06,560 Speaker 1: it be the same for Clinton because she's sort of 471 00:24:06,600 --> 00:24:10,680 Speaker 1: taken an anti TPP stance as well. I think so, 472 00:24:10,840 --> 00:24:14,080 Speaker 1: But it's already kind of factored in. Any Any type 473 00:24:14,080 --> 00:24:16,400 Speaker 1: of anti trade for things we export will be bad, 474 00:24:16,400 --> 00:24:19,560 Speaker 1: but Trump more so. Um well, okay, So going back 475 00:24:19,600 --> 00:24:21,199 Speaker 1: to gold, I mean you said, you know it's up 476 00:24:21,920 --> 00:24:24,879 Speaker 1: the year regardless of who wins. Do you think that 477 00:24:24,920 --> 00:24:28,399 Speaker 1: there's a direction for gold? Uh, it's really independent of 478 00:24:28,440 --> 00:24:34,000 Speaker 1: this latest bout of volatility, Yes, exactly, And um it's up. Well, good, 479 00:24:34,359 --> 00:24:37,680 Speaker 1: it's up for now. But it's all commondities and gold 480 00:24:37,720 --> 00:24:39,239 Speaker 1: has just been one of the leaders. It just got 481 00:24:39,280 --> 00:24:41,520 Speaker 1: a little expensive relative of the commanities. But it's also 482 00:24:41,880 --> 00:24:44,600 Speaker 1: look at the environment. Their interest rates are near negative 483 00:24:44,640 --> 00:24:47,160 Speaker 1: and what's the next step If the central banks are 484 00:24:47,240 --> 00:24:52,080 Speaker 1: successful in creating inflation, that's traditionally the best thing for gold. 485 00:24:51,720 --> 00:24:54,080 Speaker 1: So so in other words, I didn't mean stay glad 486 00:24:54,080 --> 00:24:56,720 Speaker 1: to hear it because I have one a bet one way. 487 00:24:58,000 --> 00:25:01,040 Speaker 1: Um No, it's more just you know, generally up is 488 00:25:01,040 --> 00:25:02,639 Speaker 1: a positive, but in this case it actually might be 489 00:25:02,640 --> 00:25:05,240 Speaker 1: a negative with respect to the global economy. I mean, 490 00:25:05,240 --> 00:25:07,960 Speaker 1: do you think that that the bets on gold and 491 00:25:08,000 --> 00:25:11,240 Speaker 1: the and the gains that gold has has experienced really 492 00:25:11,440 --> 00:25:16,400 Speaker 1: is a vote of of lack of confidence in the economy. Yeah, exactly. 493 00:25:16,400 --> 00:25:18,880 Speaker 1: Gold is generally the inversion of the U. S. Dow. 494 00:25:19,200 --> 00:25:22,040 Speaker 1: It's it's the inversion of the stock market. Gold really 495 00:25:22,080 --> 00:25:24,680 Speaker 1: stopped going up and started going down in two thousand 496 00:25:24,680 --> 00:25:27,200 Speaker 1: and fourteen when the stock market started making new highs, 497 00:25:27,200 --> 00:25:29,840 Speaker 1: and you know, and it's it's done the opposite there. 498 00:25:29,960 --> 00:25:32,080 Speaker 1: This year it's done well even though the stock market 499 00:25:32,119 --> 00:25:35,120 Speaker 1: has gone up. So it's still it's the ultimate quintus. 500 00:25:35,160 --> 00:25:39,479 Speaker 1: I guess you could say the diversified acid, you know, 501 00:25:39,560 --> 00:25:44,399 Speaker 1: the the free, the the the clear asset that you 502 00:25:44,440 --> 00:25:47,280 Speaker 1: can use to diverse it your but your other your 503 00:25:47,320 --> 00:25:51,080 Speaker 1: other other other investments. Still is I want to just 504 00:25:51,119 --> 00:25:53,280 Speaker 1: go through a bunch of commodities. Give me the bullet 505 00:25:53,280 --> 00:25:55,280 Speaker 1: bear case and that, you know, give you five seconds, 506 00:25:55,440 --> 00:25:56,960 Speaker 1: because I want to get through a bunch of them. 507 00:25:57,000 --> 00:26:00,080 Speaker 1: Silver best performing assets so far this year thirty one 508 00:26:00,160 --> 00:26:04,880 Speaker 1: percent gain year today, Silver bullish bush bullish. Why it's 509 00:26:05,000 --> 00:26:07,560 Speaker 1: um down from the highest and the supply demand turns 510 00:26:07,600 --> 00:26:09,479 Speaker 1: are very positive. All right, we did go that's up 511 00:26:09,520 --> 00:26:11,919 Speaker 1: more than Tell me what's going on with things like 512 00:26:12,000 --> 00:26:15,280 Speaker 1: palladium and platinum. I always here that they're tied to 513 00:26:15,280 --> 00:26:18,480 Speaker 1: the auto somewhat different. Palladium definitely much more tied to 514 00:26:18,600 --> 00:26:21,920 Speaker 1: gasoline vehicles. Demand is still picking up, most notably from China, 515 00:26:22,400 --> 00:26:26,160 Speaker 1: So still somewhat bullish. Platinum a little different, more focused 516 00:26:26,160 --> 00:26:29,000 Speaker 1: on diesel vehicles and what happened with Volkswagen is pressuring it. 517 00:26:29,040 --> 00:26:32,040 Speaker 1: But although platinum is still three still less than gold 518 00:26:32,040 --> 00:26:35,520 Speaker 1: historically it's very cheap. Tell me about soft commodities, things 519 00:26:35,600 --> 00:26:38,520 Speaker 1: like corn weed. I know we've got a big ethanol 520 00:26:38,600 --> 00:26:41,199 Speaker 1: issue having to do with corn, and we've got a 521 00:26:41,240 --> 00:26:44,960 Speaker 1: lot of well, we had a good harvest corn and 522 00:26:45,640 --> 00:26:48,439 Speaker 1: wheat just made ten year lows and because of that, 523 00:26:48,520 --> 00:26:50,800 Speaker 1: demand is really picking up. So they've been down for 524 00:26:50,880 --> 00:26:53,320 Speaker 1: quite a while. It's just how sustainable are these trends. 525 00:26:53,440 --> 00:26:58,720 Speaker 1: Demand is quite strung, specifically in wheat, corn, soybeans. Soft commodities, 526 00:26:58,720 --> 00:27:00,919 Speaker 1: if you want a specific soft command to speak of, sugar, 527 00:27:01,000 --> 00:27:04,840 Speaker 1: and sugar is up in the air, coffee, also coffee 528 00:27:04,840 --> 00:27:06,840 Speaker 1: to which we have to drink. But the thing about sugar, 529 00:27:06,880 --> 00:27:09,280 Speaker 1: it's a direct relationship to corn because of ethanol, so 530 00:27:09,320 --> 00:27:12,280 Speaker 1: it might pull corn prices up. Anything that you want 531 00:27:12,280 --> 00:27:14,199 Speaker 1: to tell us about the energy complex that we need 532 00:27:14,240 --> 00:27:19,520 Speaker 1: to know, natural gas, heating oil, gasoline, overall glut. We 533 00:27:19,520 --> 00:27:22,760 Speaker 1: still have a glut. Range trading. It got a little expensive, 534 00:27:22,800 --> 00:27:25,000 Speaker 1: little bit, a little bit overweight above fifty when crude 535 00:27:25,000 --> 00:27:27,800 Speaker 1: oil is fifty recently, but getting near forty it might 536 00:27:27,840 --> 00:27:30,400 Speaker 1: do the opposite. Was stuck in a range, still a glut, 537 00:27:30,640 --> 00:27:32,240 Speaker 1: and at some point that was going to change. But 538 00:27:32,320 --> 00:27:34,399 Speaker 1: you talked about technology earlier, and that's the key thing 539 00:27:34,400 --> 00:27:38,520 Speaker 1: that's impacting energy conservation more supply, and it's the opposite, 540 00:27:38,560 --> 00:27:41,439 Speaker 1: and things like silver word technology is creating more demand 541 00:27:41,440 --> 00:27:43,280 Speaker 1: and not increase in supply. I was going to get 542 00:27:43,280 --> 00:27:45,399 Speaker 1: that for Lisa. I was going to get it as 543 00:27:45,440 --> 00:27:49,040 Speaker 1: a gift. Always just gonna ask real quick, what is 544 00:27:49,040 --> 00:27:50,880 Speaker 1: the one commodity that we're gonna be talking about most 545 00:27:50,920 --> 00:27:55,199 Speaker 1: next year? Good question. I still I still think it's silver, 546 00:27:55,560 --> 00:27:59,120 Speaker 1: partly because it's not really widely watched and this supplied 547 00:27:59,160 --> 00:28:03,480 Speaker 1: to mentor the supply demand trends are very positive. Mike McLoone, 548 00:28:03,760 --> 00:28:06,840 Speaker 1: thank you so much for joining us. Mike McLoone, Commodity 549 00:28:06,880 --> 00:28:11,040 Speaker 1: strategist for Bloomberg Intelligence and All Things Commodities. We got 550 00:28:11,080 --> 00:28:13,320 Speaker 1: a lots, We got a lot there, Pim, I like that, 551 00:28:13,400 --> 00:28:23,720 Speaker 1: I like the list. This is Bloomberg. Thanks for listening 552 00:28:23,760 --> 00:28:26,879 Speaker 1: to the Bloomberg pen L podcast. You can subscribe and 553 00:28:26,920 --> 00:28:31,880 Speaker 1: listen to interviews at iTunes, SoundCloud, or whatever podcast platform 554 00:28:32,040 --> 00:28:34,760 Speaker 1: you prefer. I'm Pim Fox. I'm out there on Twitter 555 00:28:34,920 --> 00:28:38,600 Speaker 1: at pim Fox. I'm out there on Twitter at Lisa Abramo. 556 00:28:38,680 --> 00:28:41,320 Speaker 1: It's one before the podcast. You can always catch us 557 00:28:41,400 --> 00:28:48,520 Speaker 1: worldwide on Bloomberg Radio. Thank