1 00:00:00,800 --> 00:00:04,040 Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney, alongside 2 00:00:04,040 --> 00:00:06,920 Speaker 1: my co host Matt Miller. Every business day we bring 3 00:00:06,960 --> 00:00:11,520 Speaker 1: you interviews from CEOs, market pros, and Bloomberg experts, along 4 00:00:11,560 --> 00:00:15,560 Speaker 1: with essential market moving news. Find the Bloomberg Markets podcast 5 00:00:15,560 --> 00:00:18,479 Speaker 1: called Apple Podcasts or wherever you listen to podcasts, and 6 00:00:18,480 --> 00:00:22,800 Speaker 1: at Bloomberg dot com slash podcast. Just get over to 7 00:00:22,880 --> 00:00:25,160 Speaker 1: David Kats right now. He is the president and c 8 00:00:25,480 --> 00:00:30,280 Speaker 1: i O at Matrix Asset Advisers affirmed that he uh 9 00:00:30,320 --> 00:00:33,800 Speaker 1: co founded as well. Um, David, I wonder what you 10 00:00:33,840 --> 00:00:36,880 Speaker 1: think about the inflation number. Obviously that's probably our top 11 00:00:36,920 --> 00:00:39,720 Speaker 1: headline today. Six point eight percent year over year is 12 00:00:39,760 --> 00:00:42,680 Speaker 1: a big, hefty number. But as I can't remember his 13 00:00:42,680 --> 00:00:44,600 Speaker 1: Critty or Chinale, one of them was telling us earlier 14 00:00:44,600 --> 00:00:48,120 Speaker 1: the month over month number was a little softer than 15 00:00:48,200 --> 00:00:50,800 Speaker 1: maybe we expected. And also bad news. Looks like it's 16 00:00:50,800 --> 00:00:54,640 Speaker 1: pretty good news for this market. Well, right now, all 17 00:00:54,760 --> 00:00:57,920 Speaker 1: the news is good for this market. It's looking through 18 00:00:57,960 --> 00:01:00,320 Speaker 1: a lot of things. You know, today's action a little 19 00:01:00,360 --> 00:01:03,120 Speaker 1: bit surprising in terms of yields going lower, in stocks 20 00:01:03,120 --> 00:01:07,800 Speaker 1: going higher on the worst inflation numbers since nine two. Um, 21 00:01:07,920 --> 00:01:10,240 Speaker 1: we think what's happening is the market is looking through 22 00:01:10,280 --> 00:01:14,920 Speaker 1: the current higher inflation. It was not worse than expectations, 23 00:01:15,000 --> 00:01:17,399 Speaker 1: so people don't think it's going to cause the FED 24 00:01:17,440 --> 00:01:21,000 Speaker 1: to change course. And from our perspective, while we do 25 00:01:21,160 --> 00:01:23,640 Speaker 1: worry a lot about inflation, we think that it is 26 00:01:23,680 --> 00:01:27,600 Speaker 1: going to calm down by next spring or summer under 27 00:01:27,640 --> 00:01:29,720 Speaker 1: the three and a half percent level, so we don't 28 00:01:29,760 --> 00:01:33,400 Speaker 1: think it derails the economy. Uh and interest rates will 29 00:01:33,440 --> 00:01:36,640 Speaker 1: still say relatively low, so that's an okay environment for stocks. 30 00:01:36,680 --> 00:01:39,280 Speaker 1: It's interesting that you say that any news is good 31 00:01:39,280 --> 00:01:42,000 Speaker 1: news because I'm wondering if you could speak to the 32 00:01:42,080 --> 00:01:47,319 Speaker 1: fear and the caution that still underpins this market. Well, 33 00:01:47,400 --> 00:01:50,120 Speaker 1: you know, the market has been more volatile since September. 34 00:01:50,160 --> 00:01:52,680 Speaker 1: You've had to five percent corrections, and that's more normal, 35 00:01:52,720 --> 00:01:54,720 Speaker 1: and we think that's going to continue for some time. 36 00:01:55,080 --> 00:01:57,440 Speaker 1: But at the moment, the market is looking through the 37 00:01:57,480 --> 00:02:00,640 Speaker 1: negatives and focusing on the positives, and and the positives 38 00:02:00,640 --> 00:02:03,160 Speaker 1: are pretty good. The economy is in very good shape, 39 00:02:03,840 --> 00:02:06,560 Speaker 1: businesses are doing very well, Corporate earnings are coming in 40 00:02:06,720 --> 00:02:10,560 Speaker 1: very nicely, and we think a significant driver of the 41 00:02:10,600 --> 00:02:13,919 Speaker 1: stock market is there's just this enormous liquidity out there. 42 00:02:13,919 --> 00:02:16,680 Speaker 1: There's just so much cash floating around, and as people 43 00:02:16,760 --> 00:02:19,720 Speaker 1: throw that into stocks, that's just driving prices higher. So 44 00:02:20,080 --> 00:02:22,920 Speaker 1: the key here from an investment perspective is not to 45 00:02:23,040 --> 00:02:26,400 Speaker 1: chase the rallies. You know, we suggest putting money to 46 00:02:26,440 --> 00:02:28,440 Speaker 1: work when you have these sell offs like you had 47 00:02:28,480 --> 00:02:31,440 Speaker 1: in September or in the last month, rather than trying 48 00:02:31,520 --> 00:02:36,160 Speaker 1: to throw money in after things have risen. Is do 49 00:02:36,360 --> 00:02:39,320 Speaker 1: valuations not concern you here? Because we seem to be 50 00:02:39,960 --> 00:02:43,799 Speaker 1: at a level where any little thing. For example, um, 51 00:02:44,280 --> 00:02:46,600 Speaker 1: I think it was last Monday, we got a headline 52 00:02:46,680 --> 00:02:50,000 Speaker 1: saying that an omicron case have been found in California, 53 00:02:50,120 --> 00:02:53,000 Speaker 1: after we all knew that, oh Macron was out in 54 00:02:53,040 --> 00:02:55,160 Speaker 1: the US. It wasn't a surprised and yet the market 55 00:02:55,200 --> 00:02:58,960 Speaker 1: sold off. Right. The market is going to be pretty volatile. 56 00:02:59,000 --> 00:03:02,560 Speaker 1: It's taking its cuse whether it's COVID news or FED 57 00:03:02,639 --> 00:03:06,120 Speaker 1: news or government news. Either the market loves things or 58 00:03:06,160 --> 00:03:08,840 Speaker 1: it hates things. So the key to being investor is 59 00:03:08,880 --> 00:03:12,160 Speaker 1: just look beyond the day to day fluctuations. In terms 60 00:03:12,160 --> 00:03:15,680 Speaker 1: of valuation, we think the overall market is modestly overvalued. 61 00:03:16,200 --> 00:03:20,040 Speaker 1: We think many growth stocks are very significantly overvalued, and 62 00:03:20,120 --> 00:03:22,440 Speaker 1: that's the area that we worry a lot about. The 63 00:03:22,480 --> 00:03:24,000 Speaker 1: flip side is we think there are a lot of 64 00:03:24,040 --> 00:03:26,800 Speaker 1: places that you can buy now and you should do 65 00:03:26,840 --> 00:03:28,640 Speaker 1: well over the next twelve months, or a lot of 66 00:03:28,720 --> 00:03:33,280 Speaker 1: areas like media, telecom, healthcare that have not done a lot. 67 00:03:33,400 --> 00:03:37,120 Speaker 1: The businesses are doing well. Stocks are twelve thirteen times earnings. 68 00:03:37,360 --> 00:03:39,040 Speaker 1: We think that's going to be the next place to 69 00:03:39,080 --> 00:03:41,880 Speaker 1: make good money and do it in a lower risk way. 70 00:03:42,000 --> 00:03:44,760 Speaker 1: You know, it's interesting. I was with Scott Minor yesterday 71 00:03:45,000 --> 00:03:48,320 Speaker 1: who is the CEO of Guggenheim big bond investor, and 72 00:03:48,360 --> 00:03:50,600 Speaker 1: he was saying that I need to brag about it. 73 00:03:50,680 --> 00:03:53,040 Speaker 1: We know who Scott Minor. It is. Well, you know 74 00:03:53,240 --> 00:03:55,360 Speaker 1: one interesting thing he said to me, and we'll hear 75 00:03:55,400 --> 00:03:57,760 Speaker 1: more about this next week, is that he thinks that 76 00:03:57,840 --> 00:04:00,920 Speaker 1: the market is telling us that there are afraid of 77 00:04:00,960 --> 00:04:03,640 Speaker 1: a policy mistake when it comes to the Federal Reserve. 78 00:04:04,120 --> 00:04:07,160 Speaker 1: What do you think that really means, David? And do 79 00:04:07,240 --> 00:04:11,520 Speaker 1: you agree with that? Well, I think the market, while 80 00:04:11,560 --> 00:04:14,240 Speaker 1: it might be afraid, it's truly not acting that way 81 00:04:14,280 --> 00:04:17,400 Speaker 1: in terms of bonds or stock. So I think the 82 00:04:17,400 --> 00:04:20,800 Speaker 1: fet has actually done a very good job inflation is 83 00:04:20,920 --> 00:04:23,760 Speaker 1: much hotter than they had originally anticipated. We think a 84 00:04:23,760 --> 00:04:26,200 Speaker 1: lot of that is coming from the labor market and 85 00:04:26,240 --> 00:04:29,279 Speaker 1: from the logistics problems caused by COVID, and we think 86 00:04:29,320 --> 00:04:31,520 Speaker 1: both of those are going to come under better control 87 00:04:32,160 --> 00:04:35,120 Speaker 1: in the next six months or so. So you know, 88 00:04:35,520 --> 00:04:37,680 Speaker 1: we're in the camp where we really like what the 89 00:04:37,720 --> 00:04:40,040 Speaker 1: FET is doing. Yes, they probably are a little bit 90 00:04:40,120 --> 00:04:43,280 Speaker 1: late to starting to taper um, but we don't think 91 00:04:43,279 --> 00:04:45,680 Speaker 1: it's going to derail the economy, and we think they 92 00:04:45,680 --> 00:04:48,080 Speaker 1: should be given a lot of credit for navigating a 93 00:04:48,240 --> 00:04:52,359 Speaker 1: really difficult economic environment over the last two years. Almost 94 00:04:52,400 --> 00:04:54,880 Speaker 1: seemed like they had to be right. Pal was super 95 00:04:55,000 --> 00:05:00,440 Speaker 1: devish until he was reconfirmed and and then he and 96 00:05:00,480 --> 00:05:02,440 Speaker 1: then he was like, actually, you know what, I don't 97 00:05:02,440 --> 00:05:06,200 Speaker 1: think it's going to be transits all right, Um, all right, 98 00:05:06,240 --> 00:05:08,280 Speaker 1: So what do you like here, David? I mean, if 99 00:05:08,520 --> 00:05:09,960 Speaker 1: when you wake up in the morning, what do you 100 00:05:10,000 --> 00:05:12,400 Speaker 1: get pumped about? Or if you're if your best friend 101 00:05:12,440 --> 00:05:14,800 Speaker 1: asked you at the bar, um you know where he 102 00:05:14,800 --> 00:05:18,440 Speaker 1: should be investing? What do you tell him? So we like, 103 00:05:18,560 --> 00:05:22,600 Speaker 1: as I'd mentioned, the media, telecom, healthcare financials. Probably our 104 00:05:22,680 --> 00:05:26,320 Speaker 1: favorite two stocks right now would be Comcast, which was 105 00:05:26,360 --> 00:05:30,040 Speaker 1: off this week on what we think was a misunderstanding 106 00:05:30,040 --> 00:05:32,960 Speaker 1: of the company communications. Uh, it's gonna have very nice 107 00:05:33,000 --> 00:05:34,840 Speaker 1: earnings in the next year. It sells a thirteen and 108 00:05:34,880 --> 00:05:37,960 Speaker 1: a half times earnings, great long term business, so we 109 00:05:38,040 --> 00:05:41,839 Speaker 1: like that here Viacom is doing all of the right things. 110 00:05:41,880 --> 00:05:44,280 Speaker 1: They are going to become a streaming force of stock 111 00:05:44,360 --> 00:05:47,440 Speaker 1: sales at under nine times earnings. The CEO and the 112 00:05:47,520 --> 00:05:50,440 Speaker 1: chairwoman just bought a great deal of stock, yet it 113 00:05:50,520 --> 00:05:54,599 Speaker 1: sells at year lows at a great price, three percent yield, 114 00:05:54,839 --> 00:05:57,440 Speaker 1: So things like that are pretty interesting. On the banking side, 115 00:05:57,480 --> 00:06:01,159 Speaker 1: we like MMT Bank in US Bank Corps. In the 116 00:06:01,240 --> 00:06:04,799 Speaker 1: healthcare side, we like Amgen and zimmer which makes knee 117 00:06:04,800 --> 00:06:08,160 Speaker 1: and him replacements, has done pretty poorly of late. We 118 00:06:08,200 --> 00:06:12,200 Speaker 1: think as COVID normalizes, as the world gets back to normal, 119 00:06:12,279 --> 00:06:15,960 Speaker 1: that stock easily is sixty company. You're buying it at 120 00:06:16,000 --> 00:06:18,839 Speaker 1: a hundred twenty five today. All those companies that I 121 00:06:18,880 --> 00:06:22,120 Speaker 1: mentioned are selling well below market multiple, so you're not 122 00:06:22,240 --> 00:06:25,560 Speaker 1: paying twenty and twenty five times earnings for these good businesses. 123 00:06:25,920 --> 00:06:28,600 Speaker 1: All right, David Um, great to get some time with you. 124 00:06:28,640 --> 00:06:32,280 Speaker 1: Really appreciate your insight. Thanks very much. David Kax As 125 00:06:32,279 --> 00:06:36,920 Speaker 1: the President and chief investment officer at Matrix Asset Advisers 126 00:06:36,960 --> 00:06:41,400 Speaker 1: talking to us about the markets, the Fed, and inflation. 127 00:06:45,480 --> 00:06:47,920 Speaker 1: Jeffrey Cleveland coming up now. We promised that we would 128 00:06:47,960 --> 00:06:52,400 Speaker 1: talk about inflation again and he is the director and 129 00:06:52,480 --> 00:06:54,719 Speaker 1: chief economist for Peyton and Right, Gal, Jeffrey, thank you 130 00:06:54,720 --> 00:06:59,080 Speaker 1: so much for joining us. What is your expectation for 131 00:06:59,279 --> 00:07:02,919 Speaker 1: next week given this elevated inflation number we have, I 132 00:07:02,960 --> 00:07:05,000 Speaker 1: know it is in line with estimates, but it is 133 00:07:05,000 --> 00:07:09,560 Speaker 1: still high. Yeah, it's the tricky it's a very tricky 134 00:07:09,560 --> 00:07:12,920 Speaker 1: situation for the fom C. I think very high inflation, 135 00:07:13,680 --> 00:07:17,360 Speaker 1: higher than you know, policy makers they expected for the year. Also, 136 00:07:17,400 --> 00:07:19,400 Speaker 1: I have to issue a medical book much higher than 137 00:07:19,440 --> 00:07:21,960 Speaker 1: I had anticipated for the year. So we were also 138 00:07:22,080 --> 00:07:25,680 Speaker 1: wrong in our forecast. Um, But in recent months looks 139 00:07:25,720 --> 00:07:28,480 Speaker 1: like the market you know, expected higher inflation, was set 140 00:07:28,520 --> 00:07:30,320 Speaker 1: up for that. So perhaps that's why you see the 141 00:07:30,360 --> 00:07:32,720 Speaker 1: rally today. The taff for the Fed though, which is 142 00:07:32,760 --> 00:07:36,960 Speaker 1: your question? They you know, they've delivered very explicit guidance 143 00:07:37,240 --> 00:07:41,600 Speaker 1: on when they might lift off, right they say maximum employment, 144 00:07:42,080 --> 00:07:46,680 Speaker 1: so um, with inflation very very high. Question is are 145 00:07:46,720 --> 00:07:50,760 Speaker 1: they going to relax or somehow alter how they define 146 00:07:51,200 --> 00:07:53,880 Speaker 1: maximum employment to say that, you know, we are much 147 00:07:53,880 --> 00:07:56,640 Speaker 1: closer to it with you know, quit rates very high, 148 00:07:56,640 --> 00:07:58,560 Speaker 1: with job opening is very high, with the unemployment rate 149 00:07:58,560 --> 00:08:02,560 Speaker 1: at four? Is that close enough to open the door 150 00:08:02,680 --> 00:08:06,040 Speaker 1: for liftoff? Um. That's that's the thing that they have 151 00:08:06,080 --> 00:08:08,680 Speaker 1: to wrestle with. It's the key thing in my mind. Um. 152 00:08:08,800 --> 00:08:11,240 Speaker 1: I I still think we're not at full employment or 153 00:08:11,320 --> 00:08:15,040 Speaker 1: close to maximum employment in my view, what given where 154 00:08:15,040 --> 00:08:17,800 Speaker 1: inflation is, maybe they adjust that their their take. I mean, 155 00:08:17,800 --> 00:08:21,000 Speaker 1: if we're not at maximum employment, how is it that 156 00:08:21,080 --> 00:08:25,720 Speaker 1: we saw fewer jobless claims UM this week than any 157 00:08:25,760 --> 00:08:30,920 Speaker 1: time since Richard Nixon was president? Yeah? I think it 158 00:08:30,960 --> 00:08:32,920 Speaker 1: all depends on how you define maximum right, which they 159 00:08:33,160 --> 00:08:37,000 Speaker 1: did not give us an explicit, uh no numerical definition. 160 00:08:37,360 --> 00:08:38,800 Speaker 1: But for me, you know, I look at I look 161 00:08:38,840 --> 00:08:40,959 Speaker 1: at that, and it's great. We have very few layoffs, 162 00:08:40,960 --> 00:08:44,440 Speaker 1: so that's good news. We have a labor force participation, 163 00:08:44,520 --> 00:08:47,920 Speaker 1: right though, Matt, that's sixty one eight. We were on 164 00:08:48,040 --> 00:08:53,760 Speaker 1: labor force participation over sixty three UM pre COVID. So yeah, 165 00:08:53,800 --> 00:08:56,240 Speaker 1: some of those people probably retired early, but not all 166 00:08:56,280 --> 00:08:57,800 Speaker 1: of those folks. You know, when you look at that 167 00:08:57,880 --> 00:09:00,560 Speaker 1: chart of labor force. What is your view, Jeffrey of 168 00:09:00,640 --> 00:09:05,800 Speaker 1: the great resignation? Um, I've We've written a story about it. 169 00:09:06,240 --> 00:09:09,400 Speaker 1: Every major media outlet has has tried to figure out 170 00:09:09,480 --> 00:09:12,440 Speaker 1: what's going on here. So many people are telling me, 171 00:09:12,520 --> 00:09:15,600 Speaker 1: you know what, the kids are just uh fed up. 172 00:09:16,280 --> 00:09:18,440 Speaker 1: They're just not getting paid enough to keep up with 173 00:09:18,559 --> 00:09:21,800 Speaker 1: rising prices and they just are quitting. Is that how 174 00:09:21,880 --> 00:09:24,760 Speaker 1: you see it? Too? Well? Where do you see a 175 00:09:24,760 --> 00:09:27,200 Speaker 1: lot of the quicks in the data? Okay, it's it 176 00:09:27,280 --> 00:09:30,400 Speaker 1: tends to be in some of the lower wage industries, 177 00:09:30,960 --> 00:09:34,720 Speaker 1: so things like food service, bars and restaurants. So that 178 00:09:34,960 --> 00:09:37,880 Speaker 1: could be just a situation where there are some better 179 00:09:37,920 --> 00:09:40,920 Speaker 1: wage options that um, you know different employers and people 180 00:09:40,960 --> 00:09:43,160 Speaker 1: are making the jump, like to be something like that. 181 00:09:43,559 --> 00:09:46,400 Speaker 1: We looked yesterday, you know at the job openings data. 182 00:09:46,559 --> 00:09:48,800 Speaker 1: Where are all the job openings available that that people 183 00:09:48,840 --> 00:09:52,920 Speaker 1: can jump to the biggest increase in job openings since 184 00:09:53,040 --> 00:09:57,040 Speaker 1: COVID began. You've got you know the reason on hospitality, 185 00:09:57,360 --> 00:09:59,400 Speaker 1: which is of course where we saw the most job losses. 186 00:09:59,440 --> 00:10:01,600 Speaker 1: So if we are coming out of this pandemic, it's 187 00:10:01,640 --> 00:10:05,000 Speaker 1: not that unusual to see those job openings rise, but 188 00:10:05,040 --> 00:10:09,920 Speaker 1: then also matt, manufacturing, trade, warehouse, all those areas that 189 00:10:09,920 --> 00:10:13,200 Speaker 1: are tied in very closely to meeting the demand for 190 00:10:13,280 --> 00:10:16,679 Speaker 1: goods that we've seen. We've seen this huge surge from 191 00:10:16,720 --> 00:10:19,200 Speaker 1: consumers in the last eighteen months in demand for goods, 192 00:10:19,480 --> 00:10:21,480 Speaker 1: and there's there's been a lot of job openings and 193 00:10:21,559 --> 00:10:25,079 Speaker 1: hiring in that area. To me, though, that's really pandemic, 194 00:10:25,200 --> 00:10:29,760 Speaker 1: unique to the pandemic. Once consumer spending normalizes, people go 195 00:10:29,800 --> 00:10:32,120 Speaker 1: back to spending more on services less on goods. I mean, 196 00:10:32,480 --> 00:10:35,120 Speaker 1: how many how many home jims do you need? Matt, 197 00:10:35,720 --> 00:10:39,719 Speaker 1: The spending patterns will change, and then maybe demanding those 198 00:10:39,720 --> 00:10:42,360 Speaker 1: industries will change, job openings will come down, So it 199 00:10:42,360 --> 00:10:45,080 Speaker 1: could be some noise in the quits data and also 200 00:10:45,120 --> 00:10:48,040 Speaker 1: in the job opening to right. I'm really curious here 201 00:10:48,080 --> 00:10:51,400 Speaker 1: about labor as well, because we did see that news 202 00:10:51,440 --> 00:10:54,360 Speaker 1: coming out of Starbucks and the union vote, and I'm 203 00:10:54,400 --> 00:10:58,120 Speaker 1: wondering if we're going to see more like this. Are 204 00:10:58,120 --> 00:11:01,360 Speaker 1: we going to see more unionization, more strikes, more people 205 00:11:01,400 --> 00:11:08,760 Speaker 1: that are asking for more um as this labor market changes. Yeah. 206 00:11:08,800 --> 00:11:10,600 Speaker 1: I mean, one thing we've learned over the years is 207 00:11:10,600 --> 00:11:13,079 Speaker 1: when when the labor market gets hotter, Right, when you 208 00:11:13,080 --> 00:11:15,760 Speaker 1: get the unemployment rate falls below five down to four. 209 00:11:16,080 --> 00:11:18,400 Speaker 1: We think the unemployment rate will get to three point 210 00:11:18,520 --> 00:11:22,600 Speaker 1: five next year. That's great for labor. That is usually 211 00:11:22,640 --> 00:11:26,720 Speaker 1: great for the broad swath labor market. Um, so it 212 00:11:26,800 --> 00:11:29,520 Speaker 1: does tip the scales if you will more in in 213 00:11:29,760 --> 00:11:33,160 Speaker 1: favor of labor over over capital, which which as an 214 00:11:33,160 --> 00:11:37,200 Speaker 1: employee I won't complain about. It just dawned on me that, 215 00:11:38,440 --> 00:11:40,720 Speaker 1: I mean, mindset matters, right, You're the kind of person, 216 00:11:40,800 --> 00:11:44,520 Speaker 1: Jeffrey who doesn't quit. You don't ever give up, as 217 00:11:45,120 --> 00:11:47,320 Speaker 1: is obvious by the fact that you swam across the 218 00:11:47,360 --> 00:11:50,840 Speaker 1: English Channel, the Catalina Channel, and around the island of Manhattan. 219 00:11:51,320 --> 00:11:54,280 Speaker 1: But I wonder if there's a generation of kids now 220 00:11:54,320 --> 00:11:57,400 Speaker 1: that has just said I can't I have had enough, 221 00:11:57,520 --> 00:12:01,080 Speaker 1: I can't keep up. Yeah, or know there's there are 222 00:12:01,080 --> 00:12:04,920 Speaker 1: other options available. So I think one interesting data series 223 00:12:05,000 --> 00:12:07,200 Speaker 1: worth taking a look at, you know, of late is 224 00:12:07,880 --> 00:12:10,920 Speaker 1: new business applications. So one of the predictions I think 225 00:12:11,000 --> 00:12:15,560 Speaker 1: pre COVID was that capital wouldn't be available and then businesses, 226 00:12:15,720 --> 00:12:17,760 Speaker 1: you know, would really suffer. But we've seen sort of 227 00:12:17,760 --> 00:12:21,600 Speaker 1: a flourishing in new business applications through the COVID period. 228 00:12:21,600 --> 00:12:24,920 Speaker 1: And even after here, So it could be that the 229 00:12:25,160 --> 00:12:28,240 Speaker 1: entrepreneurial spirit in the US is alive and well and 230 00:12:28,559 --> 00:12:32,480 Speaker 1: instead of working for the firm, you know, people can 231 00:12:32,520 --> 00:12:34,839 Speaker 1: branch out and start their own operations, So that that 232 00:12:34,880 --> 00:12:36,720 Speaker 1: could be a positive spin on this whole development. It's 233 00:12:36,720 --> 00:12:40,240 Speaker 1: not necessarily a bad thing. Also a great point, Jeffrey, 234 00:12:40,240 --> 00:12:42,160 Speaker 1: I love having you on. Thanks so much for joining us. 235 00:12:42,480 --> 00:12:45,520 Speaker 1: Jeff Cleveland there is the director and chief economist over 236 00:12:45,559 --> 00:12:52,439 Speaker 1: at Paydon and Regal. Next up, we have Marianne Miller. 237 00:12:52,640 --> 00:12:55,920 Speaker 1: She's the vice president of Client Experience, vice president over 238 00:12:55,960 --> 00:13:00,840 Speaker 1: Approve and she has the latest on cyber secure already 239 00:13:00,880 --> 00:13:04,200 Speaker 1: amid this holiday shopping season, as we know that a 240 00:13:04,240 --> 00:13:07,080 Speaker 1: lot of it is being done online. Marianne, thank you 241 00:13:07,160 --> 00:13:09,400 Speaker 1: so much for joining us. What are some of the 242 00:13:09,520 --> 00:13:13,480 Speaker 1: issues that you're most concerned about the season, Yes, a 243 00:13:13,600 --> 00:13:15,480 Speaker 1: great UM, thank you, and it's great to be here 244 00:13:15,520 --> 00:13:18,920 Speaker 1: with you and your audience today. UM. This holiday season 245 00:13:19,080 --> 00:13:23,000 Speaker 1: is proving to be challenging for retailers, and I predict 246 00:13:23,040 --> 00:13:25,320 Speaker 1: that I'm going to go on record here on your show, 247 00:13:25,760 --> 00:13:28,000 Speaker 1: it's going to be the toughest here in history for 248 00:13:28,080 --> 00:13:33,319 Speaker 1: retail loss prevention. UM. The pandemic really moved consumers to 249 00:13:33,480 --> 00:13:38,400 Speaker 1: online retailers. We see continued other factors that are kind 250 00:13:38,400 --> 00:13:41,440 Speaker 1: of continuing this trend this year. As this year closes 251 00:13:41,760 --> 00:13:45,240 Speaker 1: and we're moving into um many of the factors that 252 00:13:45,320 --> 00:13:50,160 Speaker 1: contributed to fraud during the pandemic. Importantly, the challenge of 253 00:13:50,640 --> 00:13:55,440 Speaker 1: digital identity proofing are affecting re killers as well. But 254 00:13:55,559 --> 00:13:58,520 Speaker 1: we also have some top headline fraud issues as well. 255 00:13:59,160 --> 00:14:03,320 Speaker 1: And I'll yeah, I actually just got an email. I'm 256 00:14:03,320 --> 00:14:04,640 Speaker 1: trying to sell a car here, and it's got an 257 00:14:04,679 --> 00:14:08,360 Speaker 1: email from a captain in the U. S. Military. He's 258 00:14:08,400 --> 00:14:10,640 Speaker 1: serving in Syria right now. He and his buddies just 259 00:14:10,640 --> 00:14:14,240 Speaker 1: found six point two million dollars that they decided to 260 00:14:14,320 --> 00:14:16,000 Speaker 1: keep instead, and now they're going to put it in 261 00:14:16,000 --> 00:14:19,640 Speaker 1: a red cross box and send it to me. In return, 262 00:14:19,840 --> 00:14:22,200 Speaker 1: I get fifteen percent, and all I need to do 263 00:14:22,240 --> 00:14:24,160 Speaker 1: is send them a copy of my I D and 264 00:14:24,200 --> 00:14:27,440 Speaker 1: my bank account details. It seems like a great deal. 265 00:14:27,440 --> 00:14:28,960 Speaker 1: I don't want to miss out on it. Is there 266 00:14:28,960 --> 00:14:32,600 Speaker 1: anything I should be concerned about? Yes, there's definitely things 267 00:14:32,600 --> 00:14:35,000 Speaker 1: you should be concerned about. And that definitely sounds like 268 00:14:35,040 --> 00:14:37,840 Speaker 1: a scam, and we know I gotta tell you Marian, 269 00:14:38,040 --> 00:14:41,840 Speaker 1: I've had two two people saying that they found millions 270 00:14:41,840 --> 00:14:43,680 Speaker 1: of dollars in boxes and wanted to send it to 271 00:14:43,720 --> 00:14:45,560 Speaker 1: me by a Red Cross. This isn't the new like 272 00:14:45,760 --> 00:14:49,240 Speaker 1: African Prince scam. I think, right, well, you know, when 273 00:14:49,280 --> 00:14:51,080 Speaker 1: it's too good to be true, it's too good to 274 00:14:51,080 --> 00:14:53,600 Speaker 1: be true. And and you know, if you look at 275 00:14:53,680 --> 00:14:55,560 Speaker 1: some of the challenges that you see out there for 276 00:14:55,600 --> 00:14:58,680 Speaker 1: consumers as well as retailers UM and you know a 277 00:14:58,720 --> 00:15:01,120 Speaker 1: couple of things that we really want to focus on 278 00:15:01,280 --> 00:15:03,920 Speaker 1: is UM. You know, the supply chain shortages are going 279 00:15:03,960 --> 00:15:07,560 Speaker 1: to make fraud more prevalent. So fraudsters like to take 280 00:15:07,600 --> 00:15:11,200 Speaker 1: advantage of you know, panicked online buying and setting up 281 00:15:11,280 --> 00:15:16,240 Speaker 1: bake fishing sites to collect customers personal information and credit 282 00:15:16,280 --> 00:15:19,440 Speaker 1: and debit card information. So just like you're experiencing Matt, 283 00:15:19,680 --> 00:15:23,040 Speaker 1: there's just these you know, constant fishing attacks and these 284 00:15:23,080 --> 00:15:26,680 Speaker 1: attacks of scamming are are are bringing consumers into the 285 00:15:26,760 --> 00:15:30,520 Speaker 1: into the mix. And second, UM, the retailers have always 286 00:15:30,520 --> 00:15:35,200 Speaker 1: had an element of shoplifting increased during the holiday, but recently, 287 00:15:35,400 --> 00:15:38,280 Speaker 1: you know, the highly publicized sharp spikes and organized retail 288 00:15:38,360 --> 00:15:42,440 Speaker 1: depth is putting stress on businesses. So this is increasing 289 00:15:42,480 --> 00:15:46,000 Speaker 1: the cost of physical security insurance and and moves more 290 00:15:46,040 --> 00:15:50,400 Speaker 1: shopping online and as retailers UM, you know, move more 291 00:15:50,440 --> 00:15:53,360 Speaker 1: things off the shelves and in certain locations and move 292 00:15:53,440 --> 00:15:55,800 Speaker 1: things online. And that's when we start to see the scams, 293 00:15:55,840 --> 00:15:59,200 Speaker 1: Like you're starting to see an experience so and some 294 00:15:59,440 --> 00:16:02,680 Speaker 1: so these UM law Enforcement task force have been set up, 295 00:16:02,760 --> 00:16:06,080 Speaker 1: just a set up and retaining these activities. You know, Mary, 296 00:16:06,160 --> 00:16:07,920 Speaker 1: unless look a couple of years into the future here 297 00:16:07,960 --> 00:16:11,560 Speaker 1: real quick, because I'm wondering, if crypto continues to take off, 298 00:16:12,200 --> 00:16:19,120 Speaker 1: does that make cybercrime easier or harder? Because in theory, yeah, 299 00:16:19,240 --> 00:16:21,360 Speaker 1: I mean you know, how does that really end up 300 00:16:21,360 --> 00:16:25,560 Speaker 1: playing out? Well, you know, any time that there's something 301 00:16:25,640 --> 00:16:28,440 Speaker 1: and you know, in the fraud community, we always look 302 00:16:28,480 --> 00:16:32,200 Speaker 1: at any time there's something new UM and and fraudsters 303 00:16:32,320 --> 00:16:35,680 Speaker 1: love that. Actors love a new product or something new, 304 00:16:35,760 --> 00:16:39,920 Speaker 1: and they're definitely taking advantage of the crypto environment and 305 00:16:40,000 --> 00:16:43,800 Speaker 1: you know, the the crypto exchanges and we know that 306 00:16:43,960 --> 00:16:47,200 Speaker 1: UM there's a lot of focus on getting new signals 307 00:16:47,560 --> 00:16:51,280 Speaker 1: in those environments to make them safer. UM like device 308 00:16:51,360 --> 00:16:56,360 Speaker 1: intelligence and phone identity signals, biometrics, machine learning, all of 309 00:16:56,400 --> 00:16:59,480 Speaker 1: that's really important, you know, to make you known environment 310 00:16:59,480 --> 00:17:03,200 Speaker 1: where it's better lost controls. Marianne, thank you so much 311 00:17:03,240 --> 00:17:04,760 Speaker 1: for joining us on this. It's going to be a 312 00:17:04,760 --> 00:17:11,120 Speaker 1: scary holiday season in some regards. This is the Big Take, 313 00:17:11,280 --> 00:17:15,080 Speaker 1: the best of Bloomberg's in depth, original reporting from around 314 00:17:15,119 --> 00:17:17,760 Speaker 1: the globe. We're running on a financial system that's running 315 00:17:17,760 --> 00:17:22,159 Speaker 1: on old technology. We're seeing prices reach fresh recordized. What 316 00:17:22,320 --> 00:17:24,600 Speaker 1: unfolds in mid terms, we will no doubt see again 317 00:17:25,040 --> 00:17:29,240 Speaker 1: in the next presidential election. The Big Take on Bloomberg Radio. 318 00:17:31,119 --> 00:17:33,679 Speaker 1: All right, let's get to our Big Take story of 319 00:17:33,800 --> 00:17:36,080 Speaker 1: the day. Paul and I love these stories, but I'm 320 00:17:36,080 --> 00:17:41,119 Speaker 1: sure Sheinali does as well. They are deeply reported long 321 00:17:41,240 --> 00:17:44,359 Speaker 1: reads that we have for you on the Bloomberg terminal, 322 00:17:44,400 --> 00:17:48,080 Speaker 1: but are also available often in Bloomberg Business Week. Today. 323 00:17:48,160 --> 00:17:50,880 Speaker 1: Cam Simpson joins us. He wrote a story about well, 324 00:17:50,920 --> 00:17:53,760 Speaker 1: the title is the E. S. G Mirage, and it's 325 00:17:53,800 --> 00:17:55,879 Speaker 1: about M S C. I can you say it's a 326 00:17:55,920 --> 00:18:00,200 Speaker 1: bland Wall Street company, But I have always uh loved 327 00:18:00,320 --> 00:18:03,480 Speaker 1: MSDU because they helped me um so easily sort through 328 00:18:03,520 --> 00:18:07,080 Speaker 1: a number of different verticals in the market. Of course, 329 00:18:07,119 --> 00:18:09,600 Speaker 1: I've been reporting on markets for twenty years. I've been 330 00:18:09,680 --> 00:18:12,840 Speaker 1: using it for a long time. What's the link between 331 00:18:12,880 --> 00:18:16,520 Speaker 1: this company and E s G. Yeah, that's that's right. Thanks, 332 00:18:16,680 --> 00:18:19,159 Speaker 1: it's you know, but this is kind of like a 333 00:18:19,200 --> 00:18:21,719 Speaker 1: back office function on Wall Street that nobody it's not 334 00:18:21,800 --> 00:18:25,320 Speaker 1: like a really terribly sexy stock That's what we've and 335 00:18:25,400 --> 00:18:28,960 Speaker 1: then the CEO of the company rebranded it around their 336 00:18:29,080 --> 00:18:33,480 Speaker 1: E s G business. They aren't by far the dominant 337 00:18:34,320 --> 00:18:38,359 Speaker 1: ratings provided for E s G investing, which as you know, 338 00:18:38,440 --> 00:18:44,800 Speaker 1: has become a multi trillion dollar excuse me business and 339 00:18:44,840 --> 00:18:47,720 Speaker 1: the and the fastest growing segment of the global financial 340 00:18:47,760 --> 00:18:50,880 Speaker 1: services industry in just the past few years. And these 341 00:18:50,880 --> 00:18:53,720 Speaker 1: guys in terms of retail funds that people are able 342 00:18:53,720 --> 00:18:59,560 Speaker 1: to invest in their ratings probably or underneath at least 343 00:19:00,000 --> 00:19:01,760 Speaker 1: and the money and retail funds. I mean, it's not 344 00:19:01,800 --> 00:19:06,040 Speaker 1: even close between them and their next competitor. They just 345 00:19:06,119 --> 00:19:08,960 Speaker 1: completely dominate the space. So he rebranded the company in 346 00:19:09,000 --> 00:19:11,400 Speaker 1: two thousand nineteen, at the beginning of two nineteen when 347 00:19:11,440 --> 00:19:15,159 Speaker 1: he saw this taking off under you know, a new motto, 348 00:19:15,240 --> 00:19:18,160 Speaker 1: which was either better investments for a better world are 349 00:19:18,200 --> 00:19:21,199 Speaker 1: better portfolios for a better world? Really trying to hammer 350 00:19:21,240 --> 00:19:25,840 Speaker 1: on this idea that investing in the SG funds is 351 00:19:25,880 --> 00:19:29,400 Speaker 1: going to help save the planet from climate change. And 352 00:19:29,480 --> 00:19:34,240 Speaker 1: you know, this really took off when you know, it 353 00:19:34,280 --> 00:19:38,639 Speaker 1: was marketed around the social justice movement and that was 354 00:19:38,680 --> 00:19:41,879 Speaker 1: happening in America on the streets and also the pandemic 355 00:19:42,000 --> 00:19:46,120 Speaker 1: and dire warnings about the climate crisis, and so uh, 356 00:19:46,160 --> 00:19:50,680 Speaker 1: they're they're really MSCI is at the foundation of this 357 00:19:50,760 --> 00:19:55,879 Speaker 1: whole boom in in in sustainable funds in America through 358 00:19:56,080 --> 00:19:59,480 Speaker 1: and globally through through their ratings. Yeam, it's so interesting. 359 00:19:59,480 --> 00:20:01,240 Speaker 1: And you know one fact, m sc I used to 360 00:20:01,280 --> 00:20:03,680 Speaker 1: be a part of Morgan Stanley back in the day. 361 00:20:03,720 --> 00:20:06,080 Speaker 1: They have gotten a lot of heat from fund managers 362 00:20:06,520 --> 00:20:11,080 Speaker 1: for not doing more. What is the issue at play 363 00:20:11,200 --> 00:20:14,560 Speaker 1: here between M s c I and it's E s 364 00:20:14,640 --> 00:20:19,960 Speaker 1: G push or you know the lack thereof in summers regards. Well, 365 00:20:20,000 --> 00:20:21,520 Speaker 1: I think I think you know the issue is that 366 00:20:21,720 --> 00:20:26,240 Speaker 1: that E s G is pretty much exactly the opposite 367 00:20:26,240 --> 00:20:28,520 Speaker 1: of what Wall Street marketing has led people to believe 368 00:20:28,560 --> 00:20:30,920 Speaker 1: that it is right. So E s G ratings, M 369 00:20:31,000 --> 00:20:32,920 Speaker 1: s c I, G s G ratings are particular, They're 370 00:20:32,920 --> 00:20:36,960 Speaker 1: all different, they're all different brands of magic and they're 371 00:20:36,960 --> 00:20:39,880 Speaker 1: not regulated, and they all every s g rader produces 372 00:20:39,920 --> 00:20:43,240 Speaker 1: completely different results on like a credit rating. You know, 373 00:20:43,440 --> 00:20:46,159 Speaker 1: m SCI uses the credit rating standards of triple A, a 374 00:20:46,040 --> 00:20:49,120 Speaker 1: a trouble bb junk, the stuff that Wall Street knows 375 00:20:49,160 --> 00:20:51,520 Speaker 1: and recognizes the only ones to keep that and they 376 00:20:51,600 --> 00:20:55,000 Speaker 1: get in order of credibility from that um that that 377 00:20:55,040 --> 00:20:59,080 Speaker 1: nobody else gets. But instead they're looking at is not 378 00:20:59,280 --> 00:21:01,439 Speaker 1: like what it's going to make a better world. The 379 00:21:01,520 --> 00:21:04,199 Speaker 1: lens that they're looking at specifically is what matters to 380 00:21:04,240 --> 00:21:06,800 Speaker 1: the bottom line. It's not the impact of the company 381 00:21:06,800 --> 00:21:09,520 Speaker 1: on the world, it's the impact of the world on 382 00:21:09,560 --> 00:21:12,399 Speaker 1: the company. So when you look at climate change, you 383 00:21:12,400 --> 00:21:15,840 Speaker 1: could be a massive producer of greenhouse gases, and unless 384 00:21:15,880 --> 00:21:18,760 Speaker 1: you're in a business that's going to be regulated for 385 00:21:18,840 --> 00:21:21,880 Speaker 1: greenhouse gases, which is pretty much just the utility industry, 386 00:21:21,960 --> 00:21:25,600 Speaker 1: these won't even really impact your your bottom line in 387 00:21:25,680 --> 00:21:27,840 Speaker 1: any in any near kind of way, and so they're 388 00:21:27,880 --> 00:21:32,040 Speaker 1: not even considered your rating. McDonald's had greenhouse gas emissions 389 00:21:32,359 --> 00:21:35,400 Speaker 1: equal to Portugal or Hungary and its supply chain, which 390 00:21:35,440 --> 00:21:37,280 Speaker 1: is where most of that comes from, because it's one 391 00:21:37,320 --> 00:21:41,160 Speaker 1: of the biggest beef purchasers in the world, and it 392 00:21:41,320 --> 00:21:44,119 Speaker 1: weighs zero percent in in M s c I E 393 00:21:44,280 --> 00:21:46,600 Speaker 1: s G rating of them, they got into s G rating. 394 00:21:46,840 --> 00:21:48,760 Speaker 1: They're going in the s G upgrade when there are 395 00:21:48,760 --> 00:21:53,440 Speaker 1: emissions going up significantly and and M s c I 396 00:21:53,520 --> 00:21:57,119 Speaker 1: recalculated its environment scored to remove emissions completely. So what 397 00:21:57,160 --> 00:21:59,800 Speaker 1: we did was we went through like all the upgrades 398 00:21:59,800 --> 00:22:02,679 Speaker 1: in the S and P during this heery period of 399 00:22:02,800 --> 00:22:05,879 Speaker 1: record growth for sustainable industy, and we looked at what 400 00:22:05,960 --> 00:22:10,119 Speaker 1: was actually underneathy upgrades. We both bespoke database to really 401 00:22:10,160 --> 00:22:12,000 Speaker 1: get under the hood of these ratings and see what 402 00:22:12,040 --> 00:22:14,320 Speaker 1: they were. And we were pretty surprised. I mean, we 403 00:22:14,359 --> 00:22:18,359 Speaker 1: didn't know this was a pure exercise like where is 404 00:22:18,359 --> 00:22:20,800 Speaker 1: it actually coming from, what does it actually mean? So 405 00:22:20,840 --> 00:22:23,360 Speaker 1: to discover that it was kind of the opposite of 406 00:22:23,400 --> 00:22:27,119 Speaker 1: what was being what investors are being pitched on, what 407 00:22:27,240 --> 00:22:30,280 Speaker 1: the world is being pitched on, it was really, really, 408 00:22:30,320 --> 00:22:33,879 Speaker 1: really surprising to us, and hopefully we were able to 409 00:22:34,000 --> 00:22:37,280 Speaker 1: show that in a way that is meaningful for people. 410 00:22:37,280 --> 00:22:39,159 Speaker 1: And the interesting thing cam is when we talked to 411 00:22:39,200 --> 00:22:42,440 Speaker 1: E s G investors, they say, you can't separate E 412 00:22:42,600 --> 00:22:45,800 Speaker 1: s G from the bottom line because things like, um, 413 00:22:45,840 --> 00:22:48,080 Speaker 1: you know, the diversity that you have in terms of 414 00:22:48,240 --> 00:22:52,840 Speaker 1: management effect how well you do financially. If you have 415 00:22:52,920 --> 00:22:55,560 Speaker 1: a more diverse board, you're likely to sell your stuff 416 00:22:55,600 --> 00:22:58,720 Speaker 1: to a more diverse and a bigger group of people. 417 00:22:59,080 --> 00:23:01,119 Speaker 1: I guess what you're saying is that it's not always 418 00:23:01,200 --> 00:23:03,760 Speaker 1: the case that E s G leads to a better 419 00:23:03,800 --> 00:23:07,919 Speaker 1: bottom line. No. I think that the problem is the 420 00:23:08,000 --> 00:23:10,040 Speaker 1: problem is the way that E s G is marketed, 421 00:23:10,119 --> 00:23:13,520 Speaker 1: especially to ordinary retail investors, the idea that you're doing 422 00:23:13,600 --> 00:23:17,000 Speaker 1: something to make the world better, right like climate change. 423 00:23:17,320 --> 00:23:20,920 Speaker 1: I think especially for millennials who have really been driving 424 00:23:20,920 --> 00:23:24,040 Speaker 1: this boom, you know, that's what matters to them the most, 425 00:23:24,119 --> 00:23:26,840 Speaker 1: and the biggest chasm between the marketing of E s 426 00:23:26,880 --> 00:23:32,679 Speaker 1: G and what the ratings actually represent change. We have 427 00:23:32,720 --> 00:23:35,280 Speaker 1: to leave it there, but we'll Devin be following this more. 428 00:23:35,480 --> 00:23:37,280 Speaker 1: Thank you so much. That's Camp Simpson, who's part of 429 00:23:37,280 --> 00:23:39,800 Speaker 1: the big take of the day regarding the E s 430 00:23:39,840 --> 00:23:45,280 Speaker 1: G mirage. Thanks for listening to the Bloomberg Markets podcast. 431 00:23:45,680 --> 00:23:48,879 Speaker 1: You can subscribe and listen to interviews with Apple Podcasts 432 00:23:49,040 --> 00:23:52,920 Speaker 1: or whatever podcast platform you prefer. I'm Matt Miller. I'm 433 00:23:52,960 --> 00:23:57,000 Speaker 1: on Twitter at Matt Miller three pt on fal Sweeney. 434 00:23:57,000 --> 00:23:59,639 Speaker 1: I'm on Twitter at pt sweeney before the podcast. You 435 00:23:59,640 --> 00:24:02,080 Speaker 1: can always catch us worldwide at Bloomberg Gradient