1 00:00:05,800 --> 00:00:08,720 Speaker 1: Welcome to the Bloomberg pim L Podcast. I'm pim Fox. 2 00:00:08,760 --> 00:00:11,520 Speaker 1: Along with my co host Lisa Abramowitz. Each day we 3 00:00:11,640 --> 00:00:15,120 Speaker 1: bring you the most important, noteworthy, and useful interviews for 4 00:00:15,200 --> 00:00:17,840 Speaker 1: you and your money, whether you're at the grocery store 5 00:00:17,960 --> 00:00:20,720 Speaker 1: or the trading floor. Find the Bloomberg p and L 6 00:00:20,840 --> 00:00:33,240 Speaker 1: Podcast on Apple Podcasts, SoundCloud and Bloomberg dot com. What 7 00:00:33,360 --> 00:00:37,440 Speaker 1: does what does India's Prime Minister Narendra Modi have in 8 00:00:37,600 --> 00:00:41,159 Speaker 1: common with the President of the Philippines, Rodrigo du Terte, 9 00:00:41,360 --> 00:00:44,199 Speaker 1: as well as the Scottish National Party, an alternative for 10 00:00:44,360 --> 00:00:47,519 Speaker 1: Germany another party that is based in Germany. Well, here 11 00:00:47,560 --> 00:00:51,040 Speaker 1: to tell us is Vernon Silver Projects, an investigations reporter 12 00:00:51,280 --> 00:00:55,480 Speaker 1: for Bloomberg. He joins us from Rome, Vernon, I'm gonna 13 00:00:55,560 --> 00:00:57,880 Speaker 1: let you tell people what do what do all four 14 00:00:57,920 --> 00:01:03,200 Speaker 1: of these different political connections have in common? They've all 15 00:01:03,280 --> 00:01:08,040 Speaker 1: gotten advice in elections from Facebook, from a special unit 16 00:01:08,480 --> 00:01:12,920 Speaker 1: within the company that focuses on politics and governments and 17 00:01:13,360 --> 00:01:18,880 Speaker 1: has apparently increasingly participated in helping in electioneering. This is 18 00:01:18,920 --> 00:01:21,520 Speaker 1: an amazing story. I highly recommend everyone read it. This 19 00:01:21,560 --> 00:01:26,559 Speaker 1: Facebook team helps regimes that reach out and cracked down um, Vernon, 20 00:01:26,880 --> 00:01:29,319 Speaker 1: do we have a sense of the financials here of 21 00:01:29,360 --> 00:01:33,440 Speaker 1: how much Facebook earns from helping these campaigns to disseminate 22 00:01:33,480 --> 00:01:37,920 Speaker 1: their message as widely as possible on social media. What's 23 00:01:38,000 --> 00:01:41,520 Speaker 1: what's interesting about this is how small the direct numbers are. 24 00:01:41,640 --> 00:01:43,920 Speaker 1: You know, in some of these campaigns. Uh, they were 25 00:01:43,959 --> 00:01:48,000 Speaker 1: only spending hundreds of thousands of dollars on these campaigns. 26 00:01:48,040 --> 00:01:53,000 Speaker 1: But as Facebook has learned through the last few election cycles, UM, 27 00:01:53,120 --> 00:01:55,720 Speaker 1: these are big events. Elections are big events that rank 28 00:01:55,760 --> 00:01:58,760 Speaker 1: alongside the Super Bowl in the Olympics in terms of 29 00:01:58,840 --> 00:02:03,120 Speaker 1: drawing black block blockbuster ad dollars from elsewhere, you know, 30 00:02:03,160 --> 00:02:06,640 Speaker 1: stuff that other participants are bringing into the conversation and 31 00:02:06,720 --> 00:02:09,760 Speaker 1: more importantly, boost engagement, which is sort of the key 32 00:02:09,800 --> 00:02:12,680 Speaker 1: metric at Facebook. That includes you know, how many people 33 00:02:12,720 --> 00:02:15,680 Speaker 1: are clicking how many times and sharing how many times? 34 00:02:15,760 --> 00:02:19,040 Speaker 1: And so if you get a party in Germany or 35 00:02:19,080 --> 00:02:23,000 Speaker 1: the Philippines that's spending hundreds of thousands, um, you might 36 00:02:23,160 --> 00:02:26,040 Speaker 1: end up seeing a multiplier effect, and that's what they've 37 00:02:26,120 --> 00:02:29,840 Speaker 1: really tuned into. So Vernon, can you give us some 38 00:02:29,960 --> 00:02:34,680 Speaker 1: details about what encouraging engagement means, What does it mean 39 00:02:34,720 --> 00:02:38,880 Speaker 1: to help these campaigns, what did this unit actually do well? 40 00:02:38,919 --> 00:02:42,720 Speaker 1: It started out, this unit started in Europe servicing the 41 00:02:42,720 --> 00:02:46,440 Speaker 1: Middle East after the Arab Spring, talking to new leaders 42 00:02:46,480 --> 00:02:49,160 Speaker 1: transitional governments, trying to let them know what this new 43 00:02:49,200 --> 00:02:51,280 Speaker 1: tool was Facebook. I mean, this is just a few 44 00:02:51,320 --> 00:02:54,400 Speaker 1: years ago. Facebook did not have the two billion users 45 00:02:54,440 --> 00:02:57,519 Speaker 1: that it had. And then a few years ago they 46 00:02:57,560 --> 00:03:00,960 Speaker 1: started staffing up in Washington, and they did so with 47 00:03:01,040 --> 00:03:05,480 Speaker 1: people who came from political campaign backgrounds. And what they 48 00:03:05,520 --> 00:03:09,120 Speaker 1: started doing was taking the traditional pitch, like you know, hey, 49 00:03:09,520 --> 00:03:12,800 Speaker 1: campaign X and Y, because they were helping everybody in 50 00:03:12,800 --> 00:03:15,240 Speaker 1: every race that they went to deal with UM in 51 00:03:15,280 --> 00:03:19,560 Speaker 1: addition to verifying you as an authentic Facebook user, helping 52 00:03:19,600 --> 00:03:21,520 Speaker 1: you figure out how to use the basic tools and 53 00:03:21,600 --> 00:03:24,560 Speaker 1: leaving you the campaign to do it. They started getting 54 00:03:24,600 --> 00:03:27,360 Speaker 1: more engaged to the point where in the last election 55 00:03:27,400 --> 00:03:31,640 Speaker 1: in the US there were Facebook employees embedded with the 56 00:03:31,720 --> 00:03:35,720 Speaker 1: Trump campaign and you know, even in local elections, we 57 00:03:35,760 --> 00:03:39,880 Speaker 1: saw that some in the US were being offered collaboration 58 00:03:39,920 --> 00:03:43,880 Speaker 1: on testing different video formats with Facebook. So the collaborative 59 00:03:44,000 --> 00:03:47,440 Speaker 1: nature grew. And that's what the issue is that some 60 00:03:47,480 --> 00:03:51,000 Speaker 1: of the critics are having. Can you explain or maybe 61 00:03:51,000 --> 00:03:54,760 Speaker 1: just give a little uh sort of story about Katie 62 00:03:54,960 --> 00:03:59,800 Speaker 1: Harbath and Elizabeth Linder who are these two individuals. There's 63 00:04:00,120 --> 00:04:04,520 Speaker 1: interesting Elizabeth Linder Um started the unit. She was based 64 00:04:04,560 --> 00:04:07,720 Speaker 1: in London for Facebook. She was very early Facebook employee 65 00:04:08,160 --> 00:04:11,960 Speaker 1: and she started sort of as an ambassadorial figure making 66 00:04:12,000 --> 00:04:14,320 Speaker 1: the rounds in Europe and the Middle East and Africa, 67 00:04:15,080 --> 00:04:18,040 Speaker 1: helping introduce people to the tools, and she would just 68 00:04:18,040 --> 00:04:19,920 Speaker 1: sort of leave them there with them and she would 69 00:04:19,960 --> 00:04:22,080 Speaker 1: make a presentation to the candidates on the right and 70 00:04:22,120 --> 00:04:25,000 Speaker 1: the candidates on the left, and that was it. But 71 00:04:25,160 --> 00:04:28,400 Speaker 1: then a few years in UM Katie Harbath is hired 72 00:04:28,440 --> 00:04:31,760 Speaker 1: and she's a former Republican strategist who worked at Rudy 73 00:04:31,800 --> 00:04:36,679 Speaker 1: Giuliani's two thousand and eight presidential campaign. And things started changing. 74 00:04:36,720 --> 00:04:40,560 Speaker 1: Among other things, that Katie became the the global leader 75 00:04:40,600 --> 00:04:44,240 Speaker 1: of this politics and government unit within Facebook, which is 76 00:04:44,240 --> 00:04:46,159 Speaker 1: a small unit at most, you know, maybe a hundred 77 00:04:46,240 --> 00:04:50,400 Speaker 1: or something people during a pea collection time. And according 78 00:04:50,440 --> 00:04:53,360 Speaker 1: to what Elizabeth Linder, who is no longer with Facebook, 79 00:04:53,400 --> 00:04:56,040 Speaker 1: she left because of a different opinion about the direction 80 00:04:56,080 --> 00:05:00,680 Speaker 1: they were going. UM they started tailoring the advice that 81 00:05:00,760 --> 00:05:03,640 Speaker 1: they had to each of the parties that were involved 82 00:05:03,640 --> 00:05:07,160 Speaker 1: in getting more and more involved. So it went from 83 00:05:07,240 --> 00:05:11,280 Speaker 1: sort of a think tanking NGO vibe to one where like, 84 00:05:11,400 --> 00:05:13,880 Speaker 1: we will bring in democrats to work with the democratic 85 00:05:13,960 --> 00:05:16,479 Speaker 1: side and Republican support with the work with the other side, 86 00:05:17,000 --> 00:05:20,000 Speaker 1: and you know, we're going to help you use as 87 00:05:20,080 --> 00:05:23,520 Speaker 1: many of the Facebook tools as possible to know, in 88 00:05:23,560 --> 00:05:27,320 Speaker 1: the end boosting engagement and controversy also is really great 89 00:05:27,400 --> 00:05:30,320 Speaker 1: for for boosting engagement during election time. And you know, 90 00:05:30,360 --> 00:05:33,279 Speaker 1: in all these countries, whether it's Poland or Germany or 91 00:05:33,320 --> 00:05:37,280 Speaker 1: the Philippines, are India, which is essentially, in a lot 92 00:05:37,279 --> 00:05:40,880 Speaker 1: of measures, the biggest market for the company right vernon, 93 00:05:40,920 --> 00:05:43,520 Speaker 1: A lot of people will read this story and think, wow, 94 00:05:43,560 --> 00:05:47,560 Speaker 1: how can Facebook allow this? It basically is helping fuel 95 00:05:47,640 --> 00:05:53,440 Speaker 1: the rise of some misinformation or certainly higherly or more 96 00:05:53,800 --> 00:05:58,800 Speaker 1: highly politicized types of rhetoric. At the same time, Facebook 97 00:05:58,800 --> 00:06:01,159 Speaker 1: isn't doing anything wrong, is it, I mean, is it 98 00:06:01,400 --> 00:06:05,200 Speaker 1: disseminating bad information on purpose? Or you know, some people 99 00:06:05,200 --> 00:06:07,279 Speaker 1: could say, well, it's just doing its job. It's helping 100 00:06:07,320 --> 00:06:10,720 Speaker 1: clients use the platform as well as they possibly can. Yeah, 101 00:06:10,720 --> 00:06:13,599 Speaker 1: I mean, that's a really interesting question because what you 102 00:06:13,720 --> 00:06:16,120 Speaker 1: have is and let's say, a face like a place 103 00:06:16,160 --> 00:06:19,360 Speaker 1: like the Philippines where they came in and they offered 104 00:06:19,400 --> 00:06:23,040 Speaker 1: their services to all the candidates. UM. But there was 105 00:06:23,120 --> 00:06:27,640 Speaker 1: one candidate who really embraced the technology and once he 106 00:06:27,760 --> 00:06:31,440 Speaker 1: was in power, um, Facebook again helped, you know, sort 107 00:06:31,440 --> 00:06:35,720 Speaker 1: of writing the cotails into the presidential palace, so to speak. UM. 108 00:06:35,800 --> 00:06:40,960 Speaker 1: And they started broadcasting through Facebook channels official events and 109 00:06:41,680 --> 00:06:43,560 Speaker 1: in a lot of countries. And we see this in 110 00:06:43,600 --> 00:06:48,200 Speaker 1: India also. The campaign work then becomes this door into 111 00:06:48,240 --> 00:06:52,120 Speaker 1: being part of the power structure in the country. And 112 00:06:52,120 --> 00:06:55,160 Speaker 1: what this is really a contrast to what Mark Zuckerberg 113 00:06:55,240 --> 00:06:59,719 Speaker 1: has said in saying that the company is agnostic politically. Yeah, 114 00:07:00,000 --> 00:07:02,039 Speaker 1: we we're gonna have to leave it. They're fascinating a story. 115 00:07:02,040 --> 00:07:04,880 Speaker 1: Thank you so much for joining us. Vernon Silver Projects 116 00:07:04,920 --> 00:07:09,960 Speaker 1: and Investigations reporter for Bloomberg News. Facebook team helps regimes 117 00:07:09,960 --> 00:07:26,840 Speaker 1: that reach out in cracktown. This is Bluemberg. Will Big 118 00:07:26,880 --> 00:07:29,760 Speaker 1: Tech keep on rallying to the degree that they did 119 00:07:29,960 --> 00:07:33,400 Speaker 1: this year? That is the question and the answer, according 120 00:07:33,440 --> 00:07:36,720 Speaker 1: to John Patritis, is no. He is managing director and 121 00:07:36,760 --> 00:07:41,280 Speaker 1: portfolio manager for Point View Wealth Management in Summit, New Jersey, 122 00:07:41,280 --> 00:07:44,160 Speaker 1: and he joins US now. John, thanks so much for 123 00:07:44,240 --> 00:07:46,800 Speaker 1: being with us. So what's going on here? Why do 124 00:07:46,840 --> 00:07:50,800 Speaker 1: you think that the fang stacks, the Facebook, Amazon, Netflix, 125 00:07:50,840 --> 00:07:53,840 Speaker 1: and Google shares are not going to have such a 126 00:07:53,880 --> 00:07:57,120 Speaker 1: great year next year? Well, thanks for having me on. 127 00:07:57,200 --> 00:08:00,000 Speaker 1: I think that investors love to rally around us store 128 00:08:00,000 --> 00:08:02,760 Speaker 1: worry stock. You know, in the late sixties, early seventies, 129 00:08:02,760 --> 00:08:06,160 Speaker 1: it was the fifty fifty, and the eighties it was 130 00:08:06,200 --> 00:08:09,440 Speaker 1: the Go Go Stox, and then nineties it was dot com. Uh. 131 00:08:09,440 --> 00:08:11,960 Speaker 1: In the early part of the turn of the century, 132 00:08:11,960 --> 00:08:14,360 Speaker 1: it was the brick stocks, you know, the International StockX 133 00:08:14,400 --> 00:08:16,480 Speaker 1: and now you know fangs all our age. I mean, 134 00:08:16,840 --> 00:08:19,000 Speaker 1: is there anything else we've spoken about more this year 135 00:08:19,080 --> 00:08:21,960 Speaker 1: outside of bitcoin than the fang Stox. So I think 136 00:08:22,000 --> 00:08:26,160 Speaker 1: investors have piled into these, uh, these companies, and I 137 00:08:26,200 --> 00:08:28,680 Speaker 1: think valuations are starting to get stretched, and I don't 138 00:08:28,720 --> 00:08:33,560 Speaker 1: think the downside risks are priced into the stocks at all. Well, John, 139 00:08:34,480 --> 00:08:37,760 Speaker 1: I'm looking at you know, their sales annual sales for 140 00:08:37,840 --> 00:08:43,079 Speaker 1: Facebook thirty six and a half billion, and they got 141 00:08:43,120 --> 00:08:47,800 Speaker 1: net income of fifteen billion. You know any other company 142 00:08:47,840 --> 00:08:51,720 Speaker 1: that does that kind of business? Right? Maybe Amazon? How 143 00:08:51,720 --> 00:08:53,440 Speaker 1: about still look at some of the other fangs dots. 144 00:08:53,440 --> 00:08:56,440 Speaker 1: How about Amazon does so the uh no, no, no, 145 00:08:56,440 --> 00:08:58,800 Speaker 1: no no, but Amazon doesn't. I mean you're talking a 146 00:08:58,880 --> 00:09:01,439 Speaker 1: company does thirty six and a half billion in sales 147 00:09:01,600 --> 00:09:06,680 Speaker 1: and puts fifteen of it in their pocket. Said and done, right, 148 00:09:06,760 --> 00:09:10,040 Speaker 1: So let me clarify all five of the FANG stocks 149 00:09:10,040 --> 00:09:12,080 Speaker 1: and if you want to add Microsoft into that as well, 150 00:09:12,080 --> 00:09:14,440 Speaker 1: they don't fit nice into the acronym. But Microsoft has 151 00:09:14,440 --> 00:09:18,360 Speaker 1: boosted the tech sector as well. Are fantastic companies. What 152 00:09:18,400 --> 00:09:20,480 Speaker 1: I'm saying is I think the market is pricing these 153 00:09:20,480 --> 00:09:23,000 Speaker 1: companies that they could do no wrong. And that's where 154 00:09:23,000 --> 00:09:25,559 Speaker 1: investors have to be careful of because every great investment 155 00:09:25,600 --> 00:09:27,400 Speaker 1: is always a function of the price you pay for it. 156 00:09:27,640 --> 00:09:30,280 Speaker 1: So I think Facebook and Google can be under significant 157 00:09:30,280 --> 00:09:33,160 Speaker 1: regulatory pressure in two thousand eighteen. I think the whole 158 00:09:33,200 --> 00:09:37,120 Speaker 1: Russian interference with Facebook is a big red flag. And 159 00:09:37,160 --> 00:09:40,720 Speaker 1: I don't think any political risk or regulatory risk or 160 00:09:40,720 --> 00:09:44,120 Speaker 1: price into those stocks at all. So the companies are fantastic, 161 00:09:44,200 --> 00:09:47,200 Speaker 1: but I think you could see discounts priced into the 162 00:09:47,200 --> 00:09:51,880 Speaker 1: stocks because of regulatory issues. You know, everyone is excited 163 00:09:51,920 --> 00:09:54,959 Speaker 1: about Apple because of the new iPhone, but Apple is 164 00:09:55,000 --> 00:09:58,520 Speaker 1: now a hundred, eight hundred and fifty billion dollar company. 165 00:09:58,800 --> 00:10:00,840 Speaker 1: You know, if you want a dent return on Apple 166 00:10:00,880 --> 00:10:02,960 Speaker 1: from here, you're gonna have a one point six trillion 167 00:10:03,000 --> 00:10:05,599 Speaker 1: dollar company. They have to sell a lot of iPhones 168 00:10:05,640 --> 00:10:07,319 Speaker 1: to do that, right, So you're getting up, but you're 169 00:10:07,320 --> 00:10:09,920 Speaker 1: pushing up against law of large numbers. Some people do 170 00:10:10,040 --> 00:10:12,440 Speaker 1: think that it will be a trillion dollar country company. 171 00:10:12,480 --> 00:10:15,599 Speaker 1: Actually almost said country pretty soon. But but John, you know, 172 00:10:15,640 --> 00:10:18,920 Speaker 1: I want to talk specifically about the regulatory issues you 173 00:10:19,200 --> 00:10:23,120 Speaker 1: pinpointed Amazon and Google in particular. Uh, can you just 174 00:10:23,200 --> 00:10:26,920 Speaker 1: play out what some of those regulatory pressures would look 175 00:10:26,960 --> 00:10:29,280 Speaker 1: like that would cause a stock swoon because we hear 176 00:10:29,320 --> 00:10:31,680 Speaker 1: a lot about it, but I don't hear of any 177 00:10:31,720 --> 00:10:35,680 Speaker 1: regulatory efforts that are currently being discussed in concrete terms 178 00:10:35,720 --> 00:10:38,160 Speaker 1: on the hill, And I'm not sure what would do 179 00:10:38,200 --> 00:10:40,600 Speaker 1: it to these two. So yeah, I think so the 180 00:10:40,600 --> 00:10:43,640 Speaker 1: regular issues I think you for Facebook and Google specifically 181 00:10:43,679 --> 00:10:46,440 Speaker 1: because of the massive amount of data that they have 182 00:10:46,679 --> 00:10:50,920 Speaker 1: on all of their users. And I think the fact 183 00:10:50,960 --> 00:10:54,720 Speaker 1: that it was disposed that Russia was buying uh ads 184 00:10:54,840 --> 00:10:59,720 Speaker 1: on Facebook and using that uh along with it too 185 00:10:59,800 --> 00:11:03,240 Speaker 1: many pilate to a degree the uh the election results 186 00:11:03,360 --> 00:11:06,640 Speaker 1: I think is um uh you know, could within the 187 00:11:06,720 --> 00:11:08,520 Speaker 1: argument can we make within Congress to that as a 188 00:11:08,640 --> 00:11:12,800 Speaker 1: national security issue? So I think that if that's the case, 189 00:11:12,840 --> 00:11:15,280 Speaker 1: what that does is it forces Google and Facebook to 190 00:11:15,320 --> 00:11:18,960 Speaker 1: go back to the drawing board and tighten up UH 191 00:11:19,120 --> 00:11:21,880 Speaker 1: their own practices, which will add to their own to 192 00:11:21,960 --> 00:11:24,559 Speaker 1: their expenses and their costs. So my point behind all 193 00:11:24,640 --> 00:11:26,920 Speaker 1: that is, I don't think that Google and Facebook go 194 00:11:26,960 --> 00:11:29,000 Speaker 1: out of business. All I'm saying is that I think 195 00:11:29,000 --> 00:11:32,080 Speaker 1: their stocks are overvalued at current levels and they're not 196 00:11:32,160 --> 00:11:35,679 Speaker 1: pricing in any potential downside risk, And I think investors 197 00:11:35,679 --> 00:11:39,160 Speaker 1: fall in love with stocks like that. Who's chart what's fantastic? 198 00:11:39,400 --> 00:11:42,400 Speaker 1: If you're looking backward, UH could become a risky place 199 00:11:42,400 --> 00:11:44,679 Speaker 1: in two thousand eighteen, all right, So where is their 200 00:11:44,800 --> 00:11:47,720 Speaker 1: value to be had? So I still like the financials 201 00:11:47,960 --> 00:11:50,840 Speaker 1: despite the fact, again looking backward over the last eighteen months, 202 00:11:50,840 --> 00:11:54,079 Speaker 1: the banks have done a fantastic job from a performance standpoint. 203 00:11:54,320 --> 00:11:57,960 Speaker 1: You nowhere near valuation stamp valuation levels of where we 204 00:11:57,960 --> 00:12:01,240 Speaker 1: were in two thousand five, six seven during the apex 205 00:12:01,280 --> 00:12:03,560 Speaker 1: of the dot com bubble, and the fundamentals of the 206 00:12:03,559 --> 00:12:06,680 Speaker 1: financials are fantastic. Right. Interest rates continue to creep higher. 207 00:12:07,080 --> 00:12:10,200 Speaker 1: You're in a government to a regulatory situation where there's 208 00:12:10,200 --> 00:12:13,680 Speaker 1: deregulation going on. The bank's balance sheets are as healthy 209 00:12:13,679 --> 00:12:17,800 Speaker 1: as they've been so um since World War Two. So 210 00:12:18,240 --> 00:12:20,040 Speaker 1: you know, I still still think there's room to run 211 00:12:20,040 --> 00:12:22,400 Speaker 1: on the financial sector. I also think, you know, the 212 00:12:22,480 --> 00:12:26,320 Speaker 1: selloff and healthcare that we saw in October and September 213 00:12:26,320 --> 00:12:28,520 Speaker 1: and even a little bit in November provides an opportunity 214 00:12:28,679 --> 00:12:33,520 Speaker 1: healthcare insurers, how medical devices, pharmacy. I like big farmer 215 00:12:33,960 --> 00:12:37,840 Speaker 1: um particularly. Uh So if you look at where you know, 216 00:12:37,880 --> 00:12:41,520 Speaker 1: globally again thinking long term, where investors not traders, so 217 00:12:41,520 --> 00:12:43,559 Speaker 1: we're not thinking about next quarter. You know, as the 218 00:12:43,600 --> 00:12:47,600 Speaker 1: global population grows and ages, the utilization of the healthcare 219 00:12:47,640 --> 00:12:51,040 Speaker 1: system was only going to increase. So big farmer companies 220 00:12:51,080 --> 00:12:54,040 Speaker 1: are sitting with a ton of cash um. They have 221 00:12:54,120 --> 00:12:57,280 Speaker 1: the ability to reinvest in their pipeline and or do 222 00:12:57,400 --> 00:13:01,200 Speaker 1: acquisitions to bolster their own pipeline. They usually pay at 223 00:13:01,240 --> 00:13:03,760 Speaker 1: a big dividend and they buyback spots do so I 224 00:13:03,800 --> 00:13:06,839 Speaker 1: think it's a long term story out there that is 225 00:13:06,880 --> 00:13:10,520 Speaker 1: being overly discounted by investors because this fear of regulation 226 00:13:10,640 --> 00:13:13,360 Speaker 1: or drug prices. We're gonna have to leave it there 227 00:13:13,360 --> 00:13:16,480 Speaker 1: but thanks very much for enlightening us. John Patries is 228 00:13:16,520 --> 00:13:21,000 Speaker 1: Managing director portfolio manager for point View Wealth Management. They 229 00:13:21,000 --> 00:13:24,040 Speaker 1: are based in some New Jersey, and he was making 230 00:13:24,040 --> 00:13:42,400 Speaker 1: the bear case for those fang stocks. He watches all 231 00:13:42,520 --> 00:13:46,560 Speaker 1: of the information, whether it's the average private work week, 232 00:13:46,600 --> 00:13:49,640 Speaker 1: whether it's wage growth or even the conference board leading 233 00:13:49,640 --> 00:13:53,600 Speaker 1: indicators which we receive today, but he also follows Christmas trees. 234 00:13:53,920 --> 00:13:57,320 Speaker 1: Phil Orlando is the chief equity market strategist and head 235 00:13:57,320 --> 00:14:01,080 Speaker 1: of client portfolio Management at Federated. He thought you were 236 00:14:01,160 --> 00:14:02,560 Speaker 1: joking when you said we were going to talk about 237 00:14:02,600 --> 00:14:05,840 Speaker 1: Christmas trees. I'm not gonna choking. It's a big business. 238 00:14:05,920 --> 00:14:08,120 Speaker 1: It is a big business. And and thank you for 239 00:14:08,200 --> 00:14:11,199 Speaker 1: having me back on again. Merry Christmas, Happy Honkkah, and 240 00:14:11,200 --> 00:14:13,839 Speaker 1: and let's talk Christmas trees. Then that's my point. I 241 00:14:13,920 --> 00:14:15,840 Speaker 1: wanted to ask you about Christmas trees because I know 242 00:14:15,880 --> 00:14:18,560 Speaker 1: I heard about the shortage, because this has to do 243 00:14:18,679 --> 00:14:22,200 Speaker 1: with the economy in two thousand seven and eight. But 244 00:14:22,280 --> 00:14:24,600 Speaker 1: you've done some work, so let me So. I've got 245 00:14:24,600 --> 00:14:27,240 Speaker 1: to give props to my buddies at ever Core I 246 00:14:27,440 --> 00:14:29,800 Speaker 1: s I. Oscar slaughter Back is the guy that runs 247 00:14:30,280 --> 00:14:33,120 Speaker 1: this regular survey for them for the last fifteen years. 248 00:14:33,160 --> 00:14:36,160 Speaker 1: And the issue. The problem here is that it takes 249 00:14:36,200 --> 00:14:39,360 Speaker 1: about eight to ten years for a seedling to sort 250 00:14:39,360 --> 00:14:42,080 Speaker 1: of grow into a mature tree. But think about ten 251 00:14:42,160 --> 00:14:44,760 Speaker 1: years ago, we were starting, we were growing into the 252 00:14:44,760 --> 00:14:48,600 Speaker 1: Great Recession. So a lot of these smaller independent tree 253 00:14:48,640 --> 00:14:51,840 Speaker 1: farms around the country Canada whatever, they said, we don't 254 00:14:51,840 --> 00:14:54,640 Speaker 1: have the money were we were, we cut back our planning, 255 00:14:54,720 --> 00:14:57,440 Speaker 1: we went out of business. And so now ten years later, 256 00:14:57,760 --> 00:15:01,400 Speaker 1: we've got a shortage of trees. So uh, when I 257 00:15:01,600 --> 00:15:04,000 Speaker 1: s I put out the you know, they do this 258 00:15:04,080 --> 00:15:07,520 Speaker 1: survey over the four weeks of Christmas, the numbers, frankly 259 00:15:07,520 --> 00:15:09,800 Speaker 1: on a year of year basis, didn't look particularly good. 260 00:15:09,880 --> 00:15:14,120 Speaker 1: Yet we've got a very bullish forecast for Christmas. So 261 00:15:14,240 --> 00:15:16,160 Speaker 1: in my mind, I'm trying to say, okay, wait a second, 262 00:15:16,200 --> 00:15:18,000 Speaker 1: one of the key things we look at not working 263 00:15:18,240 --> 00:15:20,480 Speaker 1: yet I think Christmas is gonna be really good. And 264 00:15:20,520 --> 00:15:23,600 Speaker 1: then I sort of stumbled upon this, this this Great 265 00:15:23,600 --> 00:15:26,640 Speaker 1: Recession thing that I think that the shortage of trees 266 00:15:27,080 --> 00:15:29,560 Speaker 1: and the fact that prices have gone up, I think 267 00:15:29,600 --> 00:15:32,640 Speaker 1: people are either doing without or they're they're shifting over 268 00:15:32,800 --> 00:15:36,600 Speaker 1: artificial Now I s I survey doesn't capture artificial sales, 269 00:15:36,880 --> 00:15:40,360 Speaker 1: so we don't know how much of that mix shift occurred. 270 00:15:40,640 --> 00:15:42,840 Speaker 1: So I'm still sticking in my forecast that we're gonna 271 00:15:42,880 --> 00:15:45,080 Speaker 1: have a great Christmas. You know, based upon some of 272 00:15:45,120 --> 00:15:47,320 Speaker 1: the indicators we're looking at, this could be the best 273 00:15:47,360 --> 00:15:51,280 Speaker 1: Christmas since eleven when year of your Christmas sales were 274 00:15:51,360 --> 00:15:53,880 Speaker 1: up like six percent. So we're we're you know, we're 275 00:15:53,880 --> 00:15:56,640 Speaker 1: gonna have I think a pretty good year. Three hundred 276 00:15:56,720 --> 00:16:01,600 Speaker 1: and fifty million real Christmas trees currently growing on Christmas 277 00:16:01,640 --> 00:16:04,880 Speaker 1: tree farms in the US alone, so this isn't a 278 00:16:04,880 --> 00:16:08,720 Speaker 1: tiny business. This is. But again, because it takes about 279 00:16:08,760 --> 00:16:12,240 Speaker 1: ten years that million, you're going to chop down maybe 280 00:16:12,400 --> 00:16:14,680 Speaker 1: thirty million of them in a given year, al right, 281 00:16:14,720 --> 00:16:16,880 Speaker 1: So as people chop down their trees and get ready 282 00:16:16,880 --> 00:16:20,040 Speaker 1: for for the holidays, I'm just wondering. You know, we 283 00:16:20,120 --> 00:16:22,200 Speaker 1: talked to a lot of people. There seems to be 284 00:16:22,480 --> 00:16:25,560 Speaker 1: some consensus forming, not as much as going into going 285 00:16:25,600 --> 00:16:29,280 Speaker 1: into this year, but the consensus seems to be growth 286 00:16:29,360 --> 00:16:31,680 Speaker 1: is pretty good. We're going to get a modest boost 287 00:16:31,680 --> 00:16:34,400 Speaker 1: from the tax plan, not anything to write home about. 288 00:16:34,720 --> 00:16:38,400 Speaker 1: The dollar will remain range bound, possibly go down. Uh, 289 00:16:38,600 --> 00:16:41,360 Speaker 1: Stocks in the US will continue to do well, maybe 290 00:16:41,360 --> 00:16:43,080 Speaker 1: not as well as this year, but we'll continue to 291 00:16:43,120 --> 00:16:46,040 Speaker 1: do well, and bonds might sell off, but it won't 292 00:16:46,080 --> 00:16:50,320 Speaker 1: be a disorderedly unwind. What's wrong about those consensus ideas. 293 00:16:50,360 --> 00:16:53,000 Speaker 1: There's nothing wrong with them. I mean, basically your point 294 00:16:53,000 --> 00:16:56,119 Speaker 1: painting by and large, a goldilocks kind of an environment 295 00:16:56,640 --> 00:17:00,000 Speaker 1: where we think treasure yields will sort of grind up 296 00:17:00,040 --> 00:17:02,640 Speaker 1: to three percent over the next year year and a half, 297 00:17:03,040 --> 00:17:05,600 Speaker 1: stocks will grind up to three thousand over the course 298 00:17:05,600 --> 00:17:09,840 Speaker 1: of the next year or so. Uh GDP growth is 299 00:17:10,240 --> 00:17:12,000 Speaker 1: you know, we've been at a three percent run right 300 00:17:12,040 --> 00:17:14,360 Speaker 1: the last couple of quarters. We've got a three point 301 00:17:14,440 --> 00:17:17,280 Speaker 1: two percent estimate for the fourth quarter, We've got a 302 00:17:17,280 --> 00:17:19,680 Speaker 1: three percent estimate for next year. We're sort of back 303 00:17:19,720 --> 00:17:23,200 Speaker 1: to trendline. It's all good as far as we can tell. Okay, 304 00:17:23,240 --> 00:17:26,840 Speaker 1: So given that backdrop, what do you tell your clients 305 00:17:26,880 --> 00:17:31,800 Speaker 1: with respect to active management, Because this goldilocks scenario is 306 00:17:31,840 --> 00:17:37,320 Speaker 1: great for indexing well, not necessarily, because there are aspects 307 00:17:37,400 --> 00:17:41,240 Speaker 1: of this market that active management will be able to 308 00:17:41,320 --> 00:17:44,639 Speaker 1: do a better job. For example, UM, I'm going to 309 00:17:44,760 --> 00:17:47,920 Speaker 1: disagree with one of the elements of your analysis, which 310 00:17:48,000 --> 00:17:52,040 Speaker 1: was the dollar. If the economy, which was growing at 311 00:17:52,080 --> 00:17:54,360 Speaker 1: one and a half percent last year and is now 312 00:17:54,400 --> 00:17:57,520 Speaker 1: sort of at a three percent run right now, continues 313 00:17:57,560 --> 00:18:00,359 Speaker 1: at that pace, and that's our call, uh, and the 314 00:18:00,400 --> 00:18:03,919 Speaker 1: transition from from yelling at Powell is successful, and and 315 00:18:04,320 --> 00:18:09,800 Speaker 1: the Fed continues to gradually remove accommodation. UH. That combination 316 00:18:09,840 --> 00:18:13,479 Speaker 1: of better economic growth, better corporate earnings growth, UH, tighter 317 00:18:13,520 --> 00:18:16,119 Speaker 1: monetary policy out of the Fed should result in a 318 00:18:16,160 --> 00:18:19,800 Speaker 1: stronger dollar over time. So we went from dollar euro 319 00:18:19,960 --> 00:18:21,560 Speaker 1: I think we were one oh three or so at 320 00:18:21,600 --> 00:18:24,200 Speaker 1: the beginning of the year, topped down at about one two. 321 00:18:24,880 --> 00:18:28,119 Speaker 1: We started to strengthen down about one s eighteen. We 322 00:18:28,200 --> 00:18:30,719 Speaker 1: seem to be temporarily going back the other way. I 323 00:18:30,760 --> 00:18:33,480 Speaker 1: think we're gonna we're gonna catch a bid here, uh, 324 00:18:33,520 --> 00:18:35,920 Speaker 1: and we're gonna get the dollar euro back into that 325 00:18:36,080 --> 00:18:39,199 Speaker 1: you know, one one fifteen neighborhood over the course of 326 00:18:39,200 --> 00:18:43,920 Speaker 1: the next year. In that scenario, small cap stocks UM, 327 00:18:44,080 --> 00:18:47,680 Speaker 1: stronger economic growth, UH, the tax cuts, Remember small cap 328 00:18:47,720 --> 00:18:51,239 Speaker 1: companies pay very high taxes. UH, stronger dollar, So that 329 00:18:51,280 --> 00:18:55,640 Speaker 1: benefits UH more of the domestic oriented smaller cap companies 330 00:18:55,680 --> 00:18:58,640 Speaker 1: as opposed to the international companies. Small cap stocks ought 331 00:18:58,720 --> 00:19:01,320 Speaker 1: to do well in that environment. That's an environment that 332 00:19:01,440 --> 00:19:05,040 Speaker 1: active management really has an advantage in the indexers not 333 00:19:05,160 --> 00:19:09,560 Speaker 1: so much. Also, growth stocks, Remember large cap growth did 334 00:19:09,640 --> 00:19:12,560 Speaker 1: much better than large cap value and the first part 335 00:19:12,600 --> 00:19:16,080 Speaker 1: of the year we've rotated right around Labor Day to 336 00:19:16,160 --> 00:19:19,920 Speaker 1: a value trade. So we think the financials, the energies, 337 00:19:19,960 --> 00:19:22,600 Speaker 1: the industrials, et cetera. Those companies ought to catch a 338 00:19:22,680 --> 00:19:25,640 Speaker 1: bid relative to some of the growth stocks that did 339 00:19:25,680 --> 00:19:27,439 Speaker 1: really well of the first seven or eight months of 340 00:19:27,440 --> 00:19:30,160 Speaker 1: the year. So there are parts of the market that 341 00:19:30,160 --> 00:19:32,640 Speaker 1: that ought to do well here given the environment we've 342 00:19:32,720 --> 00:19:36,680 Speaker 1: laid out that that in our view, should benefit active 343 00:19:36,720 --> 00:19:40,440 Speaker 1: management rather than passive management. Phil, I would imagine you've 344 00:19:40,480 --> 00:19:42,840 Speaker 1: racked up a number of miles this year, traveling all 345 00:19:42,840 --> 00:19:46,560 Speaker 1: over the country talking to various investor groups. Has the 346 00:19:46,680 --> 00:19:50,399 Speaker 1: investor changed in the last decade we've talked about Christmas Trees. 347 00:19:50,440 --> 00:19:55,560 Speaker 1: Has investors mature to the point where they better understand 348 00:19:55,640 --> 00:19:58,600 Speaker 1: the investing environment that you're in today. I thought you 349 00:19:58,640 --> 00:20:00,000 Speaker 1: were going to say that they're gonna be chopped out. 350 00:20:00,960 --> 00:20:03,639 Speaker 1: I don't think so. I travel You're right, I travel 351 00:20:03,680 --> 00:20:06,119 Speaker 1: around the country talking to client groups all over the place, 352 00:20:06,400 --> 00:20:10,760 Speaker 1: and people are still scared to death because they they uh, 353 00:20:10,800 --> 00:20:14,320 Speaker 1: they're they're they're furious with the nonsense that's going on 354 00:20:14,359 --> 00:20:17,600 Speaker 1: in Washington, the stupidity in Washington. I think the single 355 00:20:17,600 --> 00:20:20,119 Speaker 1: biggest mistake a lot of investors have made over the 356 00:20:20,200 --> 00:20:24,600 Speaker 1: last year is allowing their political biases to influence their 357 00:20:24,640 --> 00:20:27,320 Speaker 1: investment judgment. I mean, that's a huge deal. And then 358 00:20:27,600 --> 00:20:29,800 Speaker 1: you know, you flip on the TV and and you've 359 00:20:29,840 --> 00:20:34,160 Speaker 1: got any number of of theoretically credible people saying Trump's 360 00:20:34,160 --> 00:20:37,920 Speaker 1: an idiot, This tax plans a disaster, it's not gonna work. Uh, 361 00:20:38,080 --> 00:20:40,600 Speaker 1: the stock markets are overvalued. You know, we're going to 362 00:20:40,680 --> 00:20:43,800 Speaker 1: hell in a handbasket. The average person doesn't know that 363 00:20:43,800 --> 00:20:47,080 Speaker 1: that's bad information and and that that we're in pretty 364 00:20:47,080 --> 00:20:49,760 Speaker 1: good shape right now. Is Lisa just articulated a moment 365 00:20:49,800 --> 00:20:53,080 Speaker 1: ago beautifully and that we're grinding up towards the three 366 00:20:53,080 --> 00:20:55,919 Speaker 1: thousand SMP over the next year or so, so we 367 00:20:56,000 --> 00:20:58,479 Speaker 1: think you gotta stick with it. That's a tough message 368 00:20:58,480 --> 00:21:01,000 Speaker 1: to get across, phil Or And oh, thank you so 369 00:21:01,080 --> 00:21:03,879 Speaker 1: much for being with us, and good luck with your Christmas. 370 00:21:03,920 --> 00:21:08,160 Speaker 1: Tree Business Analytics and Merry Christmas too, Merry Christmas. Tick 371 00:21:08,160 --> 00:21:10,720 Speaker 1: to Fill Orlando, chief equity markets strategist and head of 372 00:21:10,800 --> 00:21:16,000 Speaker 1: client portfolio management for Federated Investors. We always love having 373 00:21:16,080 --> 00:21:18,240 Speaker 1: him and UH, you know, I never realized that it 374 00:21:18,320 --> 00:21:19,920 Speaker 1: was that big of a business, to be honest, the 375 00:21:19,920 --> 00:21:35,560 Speaker 1: whole Christmas Tree business. UH. Here to help us understand 376 00:21:35,560 --> 00:21:38,240 Speaker 1: a little bit about the risks that perhaps are in 377 00:21:38,440 --> 00:21:41,800 Speaker 1: the financial world is Mike Bodson. He is the chief 378 00:21:41,840 --> 00:21:46,000 Speaker 1: executive of the Depository Trust and Clearing Corporation. Mike, thank 379 00:21:46,040 --> 00:21:48,360 Speaker 1: you very much for being with us. Tell people what 380 00:21:48,440 --> 00:21:52,000 Speaker 1: does the d t c C do and then explain 381 00:21:52,119 --> 00:21:56,680 Speaker 1: what is your systemic risk barometer? Thank you, good morning. UH. 382 00:21:57,240 --> 00:22:01,240 Speaker 1: Dt c C is basically the central counterparty for the 383 00:22:01,320 --> 00:22:04,600 Speaker 1: US cash securities market, and we're also the central securities 384 00:22:04,720 --> 00:22:08,800 Speaker 1: the depository for cast security markets. So in a nutshell, 385 00:22:08,920 --> 00:22:11,640 Speaker 1: we process every cast trade done in the United States, 386 00:22:11,680 --> 00:22:15,800 Speaker 1: every bond, stock, treasury security, mortgage backed security. So we 387 00:22:15,840 --> 00:22:18,199 Speaker 1: do about a hundred million transactions to day. We do 388 00:22:18,320 --> 00:22:21,880 Speaker 1: about one point five quadrillion dollars a year flows through us. 389 00:22:22,240 --> 00:22:25,960 Speaker 1: So we're basically the uh, the processors of all transactions 390 00:22:25,960 --> 00:22:28,680 Speaker 1: in the US markets as well as some other ancillary businesses. 391 00:22:29,600 --> 00:22:33,560 Speaker 1: Our Systemic Risk Barometer is just something we started a 392 00:22:33,640 --> 00:22:36,800 Speaker 1: few years ago where we go out and survey our 393 00:22:36,840 --> 00:22:41,280 Speaker 1: membership primarily US but internationally as well, UH to get 394 00:22:41,280 --> 00:22:43,320 Speaker 1: a gauge of where people are focused on from a 395 00:22:43,440 --> 00:22:47,120 Speaker 1: systemic risk basis, where the leading issues, and from there 396 00:22:47,160 --> 00:22:50,040 Speaker 1: we build the thought leadership pieces. We've done thought leaderships 397 00:22:50,040 --> 00:22:53,720 Speaker 1: on fintech, on cloud, on interconnectedness, risk, and things along 398 00:22:53,760 --> 00:22:58,959 Speaker 1: that deadline. I found it interesting that an emerging worry 399 00:22:59,160 --> 00:23:01,640 Speaker 1: among the people who you spoke with and with respect 400 00:23:01,720 --> 00:23:06,080 Speaker 1: to financial stability with fintech financial technology in particular, it's 401 00:23:06,160 --> 00:23:11,600 Speaker 1: lack of regulation with this idea that advancements have outpaced governance. 402 00:23:11,840 --> 00:23:15,600 Speaker 1: Please explain, Yeah, I think, um, you know, obviously, fintech 403 00:23:15,720 --> 00:23:18,000 Speaker 1: is something that's gotten a lot of focus on in 404 00:23:18,040 --> 00:23:21,480 Speaker 1: the last few years as a disruptive technology and competitive 405 00:23:21,480 --> 00:23:27,200 Speaker 1: force to financial market participants. But as the competitive threat 406 00:23:27,280 --> 00:23:31,280 Speaker 1: and competitive risk has been better understood, I think people 407 00:23:31,280 --> 00:23:33,560 Speaker 1: now are focused on, well, what does it mean to 408 00:23:33,600 --> 00:23:36,800 Speaker 1: the system itself and what type of risk doesn't introduce 409 00:23:36,920 --> 00:23:40,119 Speaker 1: and that will vary from fragmentation and changing the basic 410 00:23:40,160 --> 00:23:44,000 Speaker 1: economic model to things like cyber security, having you know, 411 00:23:44,119 --> 00:23:47,439 Speaker 1: small fintech companies who may not have the rigor UH 412 00:23:47,480 --> 00:23:50,080 Speaker 1: in terms of cyber over their product that you know, 413 00:23:50,200 --> 00:23:53,240 Speaker 1: the more established players may have that could bring obviously 414 00:23:53,240 --> 00:23:56,440 Speaker 1: a major risk if they're connected to the ecosystem. So 415 00:23:56,720 --> 00:23:58,720 Speaker 1: I think, you know, there's a variety of different ways 416 00:23:58,800 --> 00:24:01,840 Speaker 1: to look at it. But I think people have gotten 417 00:24:01,880 --> 00:24:04,640 Speaker 1: comfortable with the thought of fintech can be a real 418 00:24:04,720 --> 00:24:07,879 Speaker 1: positive force and don't want to stop innovation, but they 419 00:24:07,880 --> 00:24:09,919 Speaker 1: don't want to open up the system too unknown or 420 00:24:10,280 --> 00:24:12,679 Speaker 1: anticipated risk that could bring down the entirety of the 421 00:24:13,320 --> 00:24:16,560 Speaker 1: the financial markets. Mike, I'd be remiss if I didn't 422 00:24:16,640 --> 00:24:20,240 Speaker 1: use the word blockchain and just about every conversation, but 423 00:24:20,400 --> 00:24:25,760 Speaker 1: you are using the blockchain system for derivatives processing. Explain this. Sure, 424 00:24:25,800 --> 00:24:28,600 Speaker 1: we have a prototype being built. We hope to go 425 00:24:28,720 --> 00:24:32,000 Speaker 1: live with it UH next year where we're working with 426 00:24:32,119 --> 00:24:37,399 Speaker 1: IBM x only and R three UH to re platform 427 00:24:37,600 --> 00:24:40,600 Speaker 1: a product onto a distributed ledger to TO TO platform or 428 00:24:40,640 --> 00:24:44,080 Speaker 1: something called the trade Information warehouse. It is a central 429 00:24:44,119 --> 00:24:48,960 Speaker 1: repository of information primarily about credit to false swaps UH. 430 00:24:48,960 --> 00:24:51,840 Speaker 1: It's used by regulators to monitor the market. It's used 431 00:24:51,840 --> 00:24:56,880 Speaker 1: by market participants for payments and reconciliation purposes. But it's 432 00:24:56,920 --> 00:25:00,919 Speaker 1: built on mainframe technology. Uh. Give in the nature of 433 00:25:01,119 --> 00:25:04,800 Speaker 1: distributed ledger blockchain uh and its ability to have one 434 00:25:04,880 --> 00:25:07,320 Speaker 1: version of the truth that shared amongst all participants, that 435 00:25:07,400 --> 00:25:11,199 Speaker 1: seem to be a natural uh usage for blockchain. So 436 00:25:11,280 --> 00:25:14,200 Speaker 1: we started this project this year and as I said, 437 00:25:14,200 --> 00:25:17,400 Speaker 1: we hope to roll it out sometime next year. It's 438 00:25:17,480 --> 00:25:20,720 Speaker 1: very exciting to see an actual application on a wide 439 00:25:21,040 --> 00:25:23,640 Speaker 1: scale basis. Uh. We you know, it'll be pretty much 440 00:25:23,680 --> 00:25:27,040 Speaker 1: the first one in the US securities market. Mike, how 441 00:25:27,080 --> 00:25:30,840 Speaker 1: concerned are you about the blockchain or just in general 442 00:25:31,000 --> 00:25:35,720 Speaker 1: about increases in financial technology and frankly a potential issuance 443 00:25:35,720 --> 00:25:39,600 Speaker 1: of digital currency undermining the dt c c S business 444 00:25:39,640 --> 00:25:42,920 Speaker 1: model as a processor. Yeah. You know. Look, and when 445 00:25:42,920 --> 00:25:48,159 Speaker 1: the blockchain first became widely under steward or widely discussed, 446 00:25:48,880 --> 00:25:50,639 Speaker 1: we read a lot about how, you know, all of 447 00:25:50,640 --> 00:25:53,600 Speaker 1: a sudden, we would go to a blockchain based settlement 448 00:25:53,640 --> 00:25:56,439 Speaker 1: system and uh, there will be no need for clearing 449 00:25:56,440 --> 00:25:58,480 Speaker 1: and settlement. Then the biggest clear and settler in the 450 00:25:58,520 --> 00:26:01,439 Speaker 1: world is dtc C and we would disappear, And you know, 451 00:26:01,480 --> 00:26:03,960 Speaker 1: we kind of said, look, our business model will always 452 00:26:04,000 --> 00:26:07,680 Speaker 1: evolve and even using blockchain, there still is a role 453 00:26:07,720 --> 00:26:10,040 Speaker 1: to be played by somebody who's gonna be the central authority. 454 00:26:10,400 --> 00:26:13,480 Speaker 1: They're not gonna be open systems, they'll be closed systems. Uh. 455 00:26:13,520 --> 00:26:16,080 Speaker 1: You still have governance needs and processing needs over things 456 00:26:16,160 --> 00:26:19,880 Speaker 1: like smart contracts and nodes. How do you change uh, 457 00:26:20,080 --> 00:26:24,800 Speaker 1: the programs, etcetera. So you know, we're not immune to competition, 458 00:26:24,800 --> 00:26:27,280 Speaker 1: we're not immune to the world moving on. But rather 459 00:26:27,320 --> 00:26:29,359 Speaker 1: than you know, being scared of it, we've embraced it 460 00:26:29,400 --> 00:26:31,600 Speaker 1: and become where we believe our thought leaders in the space. 461 00:26:32,080 --> 00:26:34,320 Speaker 1: And you know, it'll take a while for blockchain to 462 00:26:34,440 --> 00:26:36,800 Speaker 1: be able to handle the volume as we do. Um. 463 00:26:36,840 --> 00:26:39,080 Speaker 1: You know, one of the things that we manage, as 464 00:26:39,080 --> 00:26:41,240 Speaker 1: I said, we do a hundred million transactions a day 465 00:26:41,240 --> 00:26:43,960 Speaker 1: come in from the stock exchanges, for instance. We net 466 00:26:43,960 --> 00:26:46,960 Speaker 1: that down to three million net movements of securities in cash, 467 00:26:46,960 --> 00:26:49,080 Speaker 1: which is highly efficient and saves a lot of money 468 00:26:49,119 --> 00:26:52,080 Speaker 1: and operational risk. Alston, if you went back to a 469 00:26:52,119 --> 00:26:54,800 Speaker 1: process where a hundred million cash movements would happen to 470 00:26:55,000 --> 00:26:57,560 Speaker 1: every day, that would not be anywhere near as efficient 471 00:26:57,560 --> 00:26:59,560 Speaker 1: and be a lot risk here. So I think as 472 00:26:59,600 --> 00:27:03,159 Speaker 1: the hype has the simmered down and people understand the 473 00:27:03,200 --> 00:27:06,600 Speaker 1: benefits of blockchain, but also the costs. You know, you're 474 00:27:06,640 --> 00:27:09,200 Speaker 1: having much more rational discussions as to you know, how 475 00:27:09,240 --> 00:27:11,360 Speaker 1: does it, how is it going to roll out, how 476 00:27:11,400 --> 00:27:13,120 Speaker 1: is it going to impact the market, and what benefits 477 00:27:13,119 --> 00:27:16,520 Speaker 1: will to bring Mike, we also have heard a lot 478 00:27:16,640 --> 00:27:21,800 Speaker 1: about the cleared derivatives and how essentially cleared derivatives have 479 00:27:21,880 --> 00:27:24,159 Speaker 1: eliminated a lot of the risk to the financial system. 480 00:27:24,680 --> 00:27:27,600 Speaker 1: Did your survey touch on that at all? And have 481 00:27:27,800 --> 00:27:31,200 Speaker 1: risks migrated to the central clearing houses themselves? The survey 482 00:27:31,200 --> 00:27:33,160 Speaker 1: didn't touch on that per se. I mean, I think 483 00:27:33,200 --> 00:27:36,600 Speaker 1: we we looked at things like interconnectedness risk UH and 484 00:27:36,760 --> 00:27:41,280 Speaker 1: failure market participant um. I mean, and the risk hasn't disappeared. 485 00:27:41,280 --> 00:27:43,800 Speaker 1: I mean what happens with a CCP as you're concentrating 486 00:27:43,840 --> 00:27:46,399 Speaker 1: the risk and managing it at a central point. So 487 00:27:46,480 --> 00:27:48,320 Speaker 1: it's not like the risk of disappeared. But it went 488 00:27:48,400 --> 00:27:51,920 Speaker 1: from a very bilateral basis I firm may exposed the 489 00:27:51,960 --> 00:27:55,399 Speaker 1: firm b uh and in some ways very opaid because 490 00:27:55,400 --> 00:27:59,080 Speaker 1: there was not transparency over those positions before two now 491 00:27:59,240 --> 00:28:02,800 Speaker 1: through both the cleared o tcs as well as the 492 00:28:02,840 --> 00:28:06,280 Speaker 1: business we do in terms of a trade repository which 493 00:28:06,320 --> 00:28:09,280 Speaker 1: gathers all the information about these transactions. You know, the 494 00:28:09,280 --> 00:28:12,600 Speaker 1: transparencies increase the concentration, and therefore the central management of 495 00:28:12,600 --> 00:28:15,159 Speaker 1: the risk has increased, and you know, it's made the 496 00:28:15,160 --> 00:28:17,960 Speaker 1: system that much stronger. Mike Bodson, thank you so much 497 00:28:17,960 --> 00:28:21,879 Speaker 1: for joining us a truly fascinating discussion. Mike Bodson, Chief 498 00:28:21,960 --> 00:28:26,119 Speaker 1: Executive Officer of the Depository Trust and Clearing Corp DTCC. 499 00:28:30,160 --> 00:28:32,720 Speaker 1: Thanks for listening to the Bloomberg P and L podcast. 500 00:28:33,040 --> 00:28:36,959 Speaker 1: You can subscribe and listen to interviews at Apple Podcasts, SoundCloud, 501 00:28:37,080 --> 00:28:40,520 Speaker 1: or whatever podcast platform you prefer. I'm pim Fox. I'm 502 00:28:40,560 --> 00:28:44,560 Speaker 1: on Twitter at pim Fox. I'm on Twitter at Lisa Abramo. 503 00:28:44,680 --> 00:28:47,280 Speaker 1: It's one before the podcast. You can always catch us 504 00:28:47,320 --> 00:28:48,880 Speaker 1: worldwide on Bloomberg Radio.