1 00:00:02,640 --> 00:00:05,320 Speaker 1: Welcome to the Bloomberg Penl Podcast. I'm Paul swing you, 2 00:00:05,360 --> 00:00:07,680 Speaker 1: along with my co host Lisa Brahma wits. Each day 3 00:00:07,720 --> 00:00:10,240 Speaker 1: we bring you the most noteworthy and useful interviews for 4 00:00:10,280 --> 00:00:12,520 Speaker 1: you and your money, whether at the grocery store or 5 00:00:12,560 --> 00:00:15,480 Speaker 1: the trading floor. Find a Bloomberg Penl podcast on Apple 6 00:00:15,520 --> 00:00:17,960 Speaker 1: podcast or wherever you listen to podcasts, as well as 7 00:00:17,960 --> 00:00:24,080 Speaker 1: at Bloomberg dot com. One big question heading into since 8 00:00:24,120 --> 00:00:27,200 Speaker 1: we are now there has been how much has the 9 00:00:27,200 --> 00:00:30,320 Speaker 1: FED bolstered stock prices and how much will they continue 10 00:00:30,360 --> 00:00:32,400 Speaker 1: to do? So we're so lucky to have tourist in 11 00:00:32,479 --> 00:00:35,120 Speaker 1: stock with US chief economists and managing director at totter 12 00:00:35,200 --> 00:00:39,040 Speaker 1: Bag Securities here in our interactive broker studios, Touristen puts 13 00:00:39,040 --> 00:00:43,080 Speaker 1: out some of the most interesting and provocative charts that 14 00:00:43,159 --> 00:00:45,600 Speaker 1: I get in my inbox. I'm very excited to have 15 00:00:45,680 --> 00:00:48,240 Speaker 1: you on. Let's just first talk about how much you've 16 00:00:48,240 --> 00:00:52,800 Speaker 1: found that the FED stimulus last year actually bolstered stock valuations. 17 00:00:53,000 --> 00:00:55,120 Speaker 1: So what we try to do was to ask the question, 18 00:00:56,800 --> 00:00:59,440 Speaker 1: when the fit basically expands that balance sheet, there various 19 00:00:59,480 --> 00:01:01,440 Speaker 1: reasons why banishing could go up, and we can discuss 20 00:01:01,440 --> 00:01:03,120 Speaker 1: for a long time, whether it's called qui or not. 21 00:01:03,480 --> 00:01:05,800 Speaker 1: But the bottom line is when the Fed expanses balance sheet, 22 00:01:05,959 --> 00:01:08,520 Speaker 1: then you can measure that on a weekly basis when 23 00:01:08,560 --> 00:01:10,440 Speaker 1: the balance sheet data comes out, and then you can 24 00:01:10,480 --> 00:01:12,240 Speaker 1: try to ask the question, let's try to go back 25 00:01:12,280 --> 00:01:14,640 Speaker 1: since October when they started expanding the balance sheet and 26 00:01:14,680 --> 00:01:18,039 Speaker 1: say for every one percent that the balance sheet expanded, 27 00:01:18,160 --> 00:01:20,199 Speaker 1: how much did the stock market go up or down? 28 00:01:20,280 --> 00:01:22,440 Speaker 1: And what we found in our very simple scatter diagram 29 00:01:22,560 --> 00:01:24,560 Speaker 1: is that for every one percent increase in the fifth 30 00:01:24,560 --> 00:01:26,759 Speaker 1: balance sheet, this in p. Five hundred has actually gone 31 00:01:26,800 --> 00:01:29,119 Speaker 1: up by roughly one percent. Also, so in that sense, 32 00:01:29,319 --> 00:01:32,800 Speaker 1: fit banasheat expansion has at least been correlated with the 33 00:01:32,840 --> 00:01:35,399 Speaker 1: increase in the stock marget that we have seen since October. 34 00:01:35,480 --> 00:01:37,560 Speaker 1: Now you can ask, looking ahead, of course, if this 35 00:01:37,600 --> 00:01:39,840 Speaker 1: will continue, if the fIF balant sheat expansion is continuing, 36 00:01:39,840 --> 00:01:41,800 Speaker 1: but at least for now, that has been a very 37 00:01:41,840 --> 00:01:44,679 Speaker 1: tight relationship for the last several months. Has the FEDS 38 00:01:44,720 --> 00:01:46,760 Speaker 1: activity as it relates to the balance sheet and growing 39 00:01:46,800 --> 00:01:50,520 Speaker 1: its balance sheet? How unusual is that? You know? Kind 40 00:01:50,520 --> 00:01:53,480 Speaker 1: of activity? Is it something that we should consider for 41 00:01:54,480 --> 00:01:58,000 Speaker 1: so a very important part of that question is that Traditionally, 42 00:01:58,000 --> 00:02:00,400 Speaker 1: when the fit has done que or quantity V saying 43 00:02:00,480 --> 00:02:02,920 Speaker 1: they've been buying the long end of the yield curve 44 00:02:03,000 --> 00:02:04,920 Speaker 1: with the whole intention of trying to lower long term 45 00:02:04,920 --> 00:02:07,560 Speaker 1: interst rates. What's really unusual about what they're doing today 46 00:02:07,880 --> 00:02:09,640 Speaker 1: is that they're buying T bills, meaning the short end 47 00:02:09,639 --> 00:02:11,640 Speaker 1: of the yeld curve, And therefore we're getting a lot 48 00:02:11,639 --> 00:02:13,360 Speaker 1: of questions from clients about, well, why should that be 49 00:02:13,400 --> 00:02:15,560 Speaker 1: helping the stock market. It makes sense that when you 50 00:02:15,639 --> 00:02:18,000 Speaker 1: shift long bunds that you could begin to buy long 51 00:02:18,080 --> 00:02:20,280 Speaker 1: duration assets. But if you buy a T bill, why 52 00:02:20,280 --> 00:02:22,639 Speaker 1: would that be substituted with the S and P. That's 53 00:02:22,639 --> 00:02:25,800 Speaker 1: probably not many who on their own just substitute directly 54 00:02:25,840 --> 00:02:28,240 Speaker 1: a four week th bill with a long term asses 55 00:02:28,280 --> 00:02:31,399 Speaker 1: by S and P five. But remember money is much fungible, 56 00:02:31,440 --> 00:02:34,440 Speaker 1: so in that sense, if there is a portfolio induced 57 00:02:34,600 --> 00:02:37,360 Speaker 1: re balancing, you could easily to see that someone at 58 00:02:37,360 --> 00:02:39,399 Speaker 1: the end of a long process would end up allocating 59 00:02:39,400 --> 00:02:42,600 Speaker 1: more money to risky assets. Therefore, this in the long 60 00:02:42,600 --> 00:02:45,119 Speaker 1: answer to a question Paul, is that I still think 61 00:02:45,160 --> 00:02:46,960 Speaker 1: that as we look into this year, the more the 62 00:02:47,000 --> 00:02:49,880 Speaker 1: fat penalty is going to expand, it will be still 63 00:02:50,080 --> 00:02:53,480 Speaker 1: something that provides support to the stock market. So that's 64 00:02:53,600 --> 00:02:57,960 Speaker 1: fantastic perspective as to what potentially could drive stock gains 65 00:02:58,120 --> 00:03:01,079 Speaker 1: further in te thing that I love about your research 66 00:03:01,160 --> 00:03:04,440 Speaker 1: is you take a more holistic approach, not just stock valuations, 67 00:03:04,600 --> 00:03:07,000 Speaker 1: diving deeper into the economy. And one thing that you've 68 00:03:07,040 --> 00:03:10,200 Speaker 1: highlighted increasingly is that there is a whole swath of 69 00:03:10,280 --> 00:03:12,920 Speaker 1: Americans that have been left behind in the rally, whether 70 00:03:12,960 --> 00:03:15,240 Speaker 1: it comes whether whether it comes to income gains, whether 71 00:03:15,280 --> 00:03:18,079 Speaker 1: it comes to spending more than their bringing in every month, 72 00:03:18,120 --> 00:03:20,440 Speaker 1: whether it comes to healthcare costs. Can you give us 73 00:03:20,440 --> 00:03:23,760 Speaker 1: a sense of just your overarching thesis when it comes 74 00:03:23,760 --> 00:03:26,280 Speaker 1: to the widening gap and what that could potentially do 75 00:03:27,040 --> 00:03:30,919 Speaker 1: economically and frankly as as surprise wise, absolutely, we think 76 00:03:30,960 --> 00:03:34,800 Speaker 1: a very important issue going into two thousand twenty, and 77 00:03:34,880 --> 00:03:38,080 Speaker 1: of course, particularly with the election in November, continues to 78 00:03:38,120 --> 00:03:40,920 Speaker 1: be inequality in all dimensions. The way we look at 79 00:03:40,920 --> 00:03:42,960 Speaker 1: it is that there are four different dimensions to an equality. 80 00:03:43,000 --> 00:03:46,680 Speaker 1: There's income inequality, there's wealth inequality, but there also two 81 00:03:46,720 --> 00:03:50,360 Speaker 1: other very important dimensions that are often ignored, namely health inequality. 82 00:03:50,400 --> 00:03:53,360 Speaker 1: Different people have different access to healthcare and finally education 83 00:03:53,400 --> 00:03:56,160 Speaker 1: in equality, that education has become very expensive, which also 84 00:03:56,240 --> 00:03:58,680 Speaker 1: means that different people have different access And if look 85 00:03:58,720 --> 00:04:01,880 Speaker 1: at these different dimensions, it is basically things that are 86 00:04:01,880 --> 00:04:05,200 Speaker 1: dominating the political conversations. So we're trying to think about 87 00:04:05,320 --> 00:04:07,080 Speaker 1: and trying to figure out, as hard as it is, 88 00:04:07,320 --> 00:04:09,680 Speaker 1: should we just ignore this and say, hey, I just 89 00:04:09,680 --> 00:04:11,200 Speaker 1: look at the stock market, this is what I do. 90 00:04:11,480 --> 00:04:14,760 Speaker 1: Or should we say, well, these are actually now indicators 91 00:04:14,800 --> 00:04:17,719 Speaker 1: and data points that have become so important in the 92 00:04:17,760 --> 00:04:21,000 Speaker 1: conversation politically that maybe we need to take into account. 93 00:04:21,160 --> 00:04:23,400 Speaker 1: How should I think about as an investor? Should I 94 00:04:23,480 --> 00:04:25,440 Speaker 1: take it into account and see this could apply something 95 00:04:25,480 --> 00:04:30,040 Speaker 1: in terms of policy changes on education, healthcare, student loans, taxes. 96 00:04:30,279 --> 00:04:32,280 Speaker 1: There's a lot of time mentions that become very important 97 00:04:32,279 --> 00:04:34,960 Speaker 1: for the overall business environment and therefore also for the 98 00:04:35,000 --> 00:04:36,839 Speaker 1: out there, for the stock market, and ultimately also for 99 00:04:36,839 --> 00:04:40,080 Speaker 1: the fit and rates. So in short, this agenda is 100 00:04:40,160 --> 00:04:43,400 Speaker 1: very confusing and fluffy in the sense of there's a 101 00:04:43,400 --> 00:04:45,719 Speaker 1: lot of arm waving around a lot of these data points, 102 00:04:45,760 --> 00:04:48,440 Speaker 1: but it still turns out in almost all our conversations 103 00:04:48,480 --> 00:04:50,400 Speaker 1: to be at the end of the day, a very 104 00:04:50,480 --> 00:04:53,480 Speaker 1: very critical input to how will markets actually do as 105 00:04:53,480 --> 00:04:55,760 Speaker 1: we sit here on the first days of two thousand twenty, 106 00:04:55,760 --> 00:04:57,799 Speaker 1: do you think some of those inequalities that you identified 107 00:04:57,920 --> 00:05:00,240 Speaker 1: have had an economic impact in the US? Has it 108 00:05:00,279 --> 00:05:02,160 Speaker 1: impacted g d P? There's a lot of folks, a 109 00:05:02,200 --> 00:05:04,600 Speaker 1: lot of economists are saying we're gonna be slower growth 110 00:05:04,920 --> 00:05:07,360 Speaker 1: for a longer, you know, kind of two percent GDP. 111 00:05:07,440 --> 00:05:09,120 Speaker 1: Do you think one of the contributors of that could 112 00:05:09,160 --> 00:05:11,359 Speaker 1: be some of these inequalities were seeing. Absolutely, we do 113 00:05:11,400 --> 00:05:13,440 Speaker 1: think that a very important reason why this expansion was 114 00:05:13,480 --> 00:05:16,559 Speaker 1: so weak for the last ten years was probably that 115 00:05:16,760 --> 00:05:19,560 Speaker 1: the main boost from policy makers. Remember policy in two 116 00:05:19,600 --> 00:05:23,040 Speaker 1: thousand nine and ten basically responded less with fiscal policy 117 00:05:23,040 --> 00:05:24,920 Speaker 1: and mold with monetary policy. And what did mind story 118 00:05:24,920 --> 00:05:27,760 Speaker 1: opposed to do. It lifted stock prices and home prices. 119 00:05:27,800 --> 00:05:30,200 Speaker 1: Who benefits on that people who own stocks, people who 120 00:05:30,279 --> 00:05:33,400 Speaker 1: own homes. And because there were fewer people who own homes, 121 00:05:33,400 --> 00:05:36,320 Speaker 1: the home ownership rate was going down. Fewer people owning stocks. 122 00:05:36,440 --> 00:05:39,120 Speaker 1: That meant that the benefits in this expansion were concentrated 123 00:05:39,120 --> 00:05:41,520 Speaker 1: on a fewer hands. So in that sense, the benefits 124 00:05:41,560 --> 00:05:44,159 Speaker 1: of highest stock price and high home prices were basically 125 00:05:44,320 --> 00:05:47,719 Speaker 1: more concentrated in a smaller group of the population. That 126 00:05:47,800 --> 00:05:51,040 Speaker 1: meant that the impact on consumer spending, the wealth effect, 127 00:05:51,160 --> 00:05:53,400 Speaker 1: the impact overall on the economy turned out to be 128 00:05:53,480 --> 00:05:56,159 Speaker 1: driven a lot by asset prices going up in some 129 00:05:56,240 --> 00:05:59,280 Speaker 1: sexes and some people benefiting, but a significant part of 130 00:05:59,279 --> 00:06:01,360 Speaker 1: the population not efiting. So we do believe that one 131 00:06:01,400 --> 00:06:04,120 Speaker 1: critical reason why these expanion has been so weak is 132 00:06:04,320 --> 00:06:07,960 Speaker 1: because of inequality that has continued to widen Torsen's law. 133 00:06:08,000 --> 00:06:09,760 Speaker 1: Thank you so much for joining us. We really appreciate 134 00:06:09,800 --> 00:06:12,240 Speaker 1: you coming into our Bloomberg Interactive Broker studio. Torsen's and 135 00:06:12,320 --> 00:06:30,400 Speaker 1: chief economist at Deutsche Bank Securities hockey stick growth. That 136 00:06:30,480 --> 00:06:32,640 Speaker 1: is what people are expecting for the first quarter of 137 00:06:32,720 --> 00:06:35,719 Speaker 1: the first half of joining us here in our interactive 138 00:06:35,720 --> 00:06:39,599 Speaker 1: broker studios. Nick Cholis, co founder of Data Track Research, 139 00:06:39,760 --> 00:06:42,120 Speaker 1: and I want to talk about the consensus idea that 140 00:06:42,160 --> 00:06:45,160 Speaker 1: we have here, which is that the first half of 141 00:06:45,200 --> 00:06:48,080 Speaker 1: the year will be frontloaded in terms of gains in 142 00:06:48,120 --> 00:06:51,360 Speaker 1: the SMP and beyond as companies report earnings that are 143 00:06:51,440 --> 00:06:54,360 Speaker 1: solid and show study growth in the U S economy. 144 00:06:54,760 --> 00:06:57,280 Speaker 1: Do you agree with that consensus call. I think it's 145 00:06:57,320 --> 00:06:59,200 Speaker 1: a bit tough and I'll tell you why. If you 146 00:06:59,240 --> 00:07:01,400 Speaker 1: look at the first half of last year, you saw 147 00:07:01,440 --> 00:07:05,040 Speaker 1: that SMP five companies registered revenue growth of five percent 148 00:07:05,080 --> 00:07:07,440 Speaker 1: in Q one and four percent in Q two, and 149 00:07:07,480 --> 00:07:09,640 Speaker 1: that's trailed off to three and then two percent what 150 00:07:09,640 --> 00:07:12,200 Speaker 1: we're expecting for the fourth quarter. And those are tough 151 00:07:12,240 --> 00:07:14,880 Speaker 1: comps because the U. S economy and global economy is 152 00:07:14,920 --> 00:07:18,040 Speaker 1: still growing only fairly slowly. And even though the effect 153 00:07:18,120 --> 00:07:21,160 Speaker 1: of FED rate cuts and perhaps the trade US UM 154 00:07:21,320 --> 00:07:24,440 Speaker 1: trade war settlements will spur business spending, it'll be in 155 00:07:24,480 --> 00:07:26,080 Speaker 1: the back half of the year. So I'm not as 156 00:07:26,120 --> 00:07:28,920 Speaker 1: optimistic that we'll see those really healthy comps in Q 157 00:07:29,120 --> 00:07:31,680 Speaker 1: one and Q two. So Nick, I'm looking at your research, 158 00:07:31,800 --> 00:07:35,320 Speaker 1: and I love your your theme here, six word market narratives. 159 00:07:35,320 --> 00:07:38,760 Speaker 1: Give us your six word market narratives for nineteen and 160 00:07:38,800 --> 00:07:41,840 Speaker 1: maybe how we should think about You know, the six 161 00:07:41,920 --> 00:07:43,880 Speaker 1: word narrative is an exercise to try to just to 162 00:07:43,960 --> 00:07:47,560 Speaker 1: steal down what happened in twenty nineteen, then what could 163 00:07:47,600 --> 00:07:50,960 Speaker 1: happen this year. The summary of it was that eighteen 164 00:07:51,120 --> 00:07:54,000 Speaker 1: was a year of a huge policy mistake. The FED 165 00:07:54,040 --> 00:07:55,840 Speaker 1: thought that neutral rates were much higher than they were. 166 00:07:56,200 --> 00:07:58,920 Speaker 1: You know, if J don't touch that. Dial's kind of 167 00:07:58,960 --> 00:08:02,720 Speaker 1: the six word market narrative in we had a reversal 168 00:08:02,760 --> 00:08:05,080 Speaker 1: of that. Basically, the FED came out on January four, 169 00:08:05,520 --> 00:08:08,080 Speaker 1: apologize for getting it wrong, and spent the rest of 170 00:08:08,080 --> 00:08:11,320 Speaker 1: the year cutting So it was okay, we know, you're sorry, 171 00:08:11,520 --> 00:08:15,440 Speaker 1: it's okay. Is going to be this issue of look, 172 00:08:15,440 --> 00:08:17,720 Speaker 1: there's a hundred different ways to cut this market and 173 00:08:17,800 --> 00:08:20,840 Speaker 1: say you shouldn't be involved. Valuations are very high. Corporate 174 00:08:20,880 --> 00:08:23,800 Speaker 1: that's very high. We talked about the earnings cops, all 175 00:08:23,920 --> 00:08:26,160 Speaker 1: very real issues. But at the same time, we still 176 00:08:26,200 --> 00:08:28,600 Speaker 1: have the flow through of these policy makers, both at 177 00:08:28,600 --> 00:08:30,720 Speaker 1: the FED now saying they're not going to raise rates 178 00:08:31,000 --> 00:08:32,760 Speaker 1: and in the White House saying, you know what, the 179 00:08:32,880 --> 00:08:35,480 Speaker 1: trade war probably should be over because President Trump wants 180 00:08:35,520 --> 00:08:38,040 Speaker 1: to get reelected. And it's a flow through of those 181 00:08:38,040 --> 00:08:40,760 Speaker 1: two narratives that says this year might be okay. All right, 182 00:08:40,880 --> 00:08:43,079 Speaker 1: let's talk about where it's going to be most okay. 183 00:08:43,240 --> 00:08:45,719 Speaker 1: I was looking at the City Economic Surprise Index for 184 00:08:45,760 --> 00:08:48,880 Speaker 1: both the US and Europe this morning. In the US 185 00:08:48,960 --> 00:08:51,680 Speaker 1: it's going down and it is negative. In Europe, it's 186 00:08:51,679 --> 00:08:56,640 Speaker 1: the highest level UH since February, basically meaning that the 187 00:08:56,679 --> 00:08:59,760 Speaker 1: economic data coming out was beating expectations by the most 188 00:09:00,080 --> 00:09:03,080 Speaker 1: since then, do you agree that this sort of supports 189 00:09:03,080 --> 00:09:05,840 Speaker 1: the narrative that Europe will perform the US at an 190 00:09:05,920 --> 00:09:08,480 Speaker 1: economic basis on a relative basis, meaning they're going to 191 00:09:08,559 --> 00:09:10,640 Speaker 1: grow a little faster on a quarter of a quarters 192 00:09:10,720 --> 00:09:14,040 Speaker 1: quantial basis. Absolutely. The issue with Europe as a stock 193 00:09:14,080 --> 00:09:17,000 Speaker 1: market is it's so little exposed to technology. The IFA 194 00:09:17,040 --> 00:09:20,640 Speaker 1: index is only seven percent technology, and that includes Japan obviously, 195 00:09:20,679 --> 00:09:25,959 Speaker 1: but developed non US US. Here we're tech between tech, Amazon, Google, 196 00:09:26,000 --> 00:09:28,760 Speaker 1: and Facebook. So you really have to make a very 197 00:09:28,760 --> 00:09:31,160 Speaker 1: big bet on financials, which is fine. European financial has 198 00:09:31,160 --> 00:09:33,880 Speaker 1: done really well in the fourth quarter and should continue 199 00:09:33,920 --> 00:09:36,160 Speaker 1: to do well as bodon rates continue to rise. So 200 00:09:36,240 --> 00:09:38,840 Speaker 1: it's a good story. It's just not the same kind 201 00:09:38,920 --> 00:09:40,680 Speaker 1: of story as the US market. I still like the 202 00:09:40,720 --> 00:09:43,920 Speaker 1: US market better, but it's for that tech exposure. So 203 00:09:43,960 --> 00:09:48,640 Speaker 1: typically after a very strong year like we had in 204 00:09:48,640 --> 00:09:51,040 Speaker 1: in the SMP, what is your research show to what 205 00:09:51,080 --> 00:09:54,120 Speaker 1: the markets tend to do in the year after. Well, 206 00:09:54,160 --> 00:09:57,280 Speaker 1: here's the good news, let's star. The good news is. 207 00:09:59,559 --> 00:10:02,280 Speaker 1: The good news is you don't see markets puke the 208 00:10:02,320 --> 00:10:05,520 Speaker 1: next year. The market is pretty efficient and it tends 209 00:10:05,559 --> 00:10:07,920 Speaker 1: to see through. The only time we had a really 210 00:10:07,920 --> 00:10:10,959 Speaker 1: bad sequential year after a bat after a great year 211 00:10:11,040 --> 00:10:14,200 Speaker 1: was thirty seven. Uh yeah, nineteen thirty seven market was 212 00:10:14,240 --> 00:10:18,880 Speaker 1: down thirty eight percent thirty eight um and then but 213 00:10:19,040 --> 00:10:21,360 Speaker 1: on average you do about ten percent. Is a short 214 00:10:21,400 --> 00:10:23,200 Speaker 1: answer to your question. You know do as well as 215 00:10:23,240 --> 00:10:25,720 Speaker 1: average because there is a little bit of pull forward, 216 00:10:26,080 --> 00:10:28,400 Speaker 1: but you tend to have another good year. The problem 217 00:10:28,440 --> 00:10:30,760 Speaker 1: is the wind rates not as good on average S 218 00:10:30,800 --> 00:10:35,400 Speaker 1: ANDP win rate since night against these years, it's more 219 00:10:35,440 --> 00:10:38,280 Speaker 1: like sixt so a little bit closer to a coin toss. 220 00:10:38,840 --> 00:10:41,080 Speaker 1: We had tour sence lock On earlier from Deutsche Bank 221 00:10:41,080 --> 00:10:43,280 Speaker 1: and he was talking about something that you mentioned, the 222 00:10:43,320 --> 00:10:48,360 Speaker 1: FED support of markets, and talking about the correlation between 223 00:10:48,520 --> 00:10:51,880 Speaker 1: the increase in the Fed's balance sheet and increases in 224 00:10:51,880 --> 00:10:54,280 Speaker 1: the SMP five hundred. Granted it's not a long time 225 00:10:54,760 --> 00:10:58,000 Speaker 1: time set. Do you, though, believe that the expansion of 226 00:10:58,000 --> 00:11:00,520 Speaker 1: the balance sheet, call it whatever you will, perhaps don't 227 00:11:00,559 --> 00:11:03,720 Speaker 1: use quantitivities because it is controversial. Do you think that 228 00:11:03,720 --> 00:11:06,240 Speaker 1: that is supporting a rally much more than some people 229 00:11:06,320 --> 00:11:10,480 Speaker 1: are allowing. I think it is absolutely helpful. It does 230 00:11:10,559 --> 00:11:13,480 Speaker 1: show that the FED put and we all hate that phrase, 231 00:11:13,559 --> 00:11:16,400 Speaker 1: but it's real. The FED put applies to a whole 232 00:11:16,520 --> 00:11:18,960 Speaker 1: range of things, including things like the repo market, and 233 00:11:19,000 --> 00:11:20,839 Speaker 1: they want to make sure that the system can use 234 00:11:20,920 --> 00:11:23,280 Speaker 1: to work as it should. So I think it's a 235 00:11:23,320 --> 00:11:25,840 Speaker 1: comforting notion. I don't know how much it directly affects 236 00:11:25,840 --> 00:11:28,439 Speaker 1: stock prices, but let's put it this way. It helps 237 00:11:28,440 --> 00:11:31,400 Speaker 1: more than it hurts. So again, are you in the 238 00:11:31,480 --> 00:11:34,560 Speaker 1: camp that like I? This is where at least And 239 00:11:34,559 --> 00:11:36,720 Speaker 1: I had a little bit bund of contention before the holidays. 240 00:11:36,760 --> 00:11:40,080 Speaker 1: I said, if the data was to come in, you know, 241 00:11:40,240 --> 00:11:43,160 Speaker 1: strong economic data, that is there a scenario where the 242 00:11:43,160 --> 00:11:46,000 Speaker 1: FED could hike raise And she quote unquote rejected that. 243 00:11:46,880 --> 00:11:49,559 Speaker 1: She rejected that assertion. Is there any scenario where in 244 00:11:49,600 --> 00:11:52,240 Speaker 1: an election year the FED would even consider if the 245 00:11:52,320 --> 00:11:54,760 Speaker 1: data lead them there to be raised rates? Absolutely? No. 246 00:11:55,720 --> 00:11:57,800 Speaker 1: It doesn't feel like if I'll tell you why, we do. 247 00:11:57,960 --> 00:11:59,839 Speaker 1: Every time we see a new set of dot plots 248 00:11:59,840 --> 00:12:01,760 Speaker 1: from the FED would do a standard deviation of all 249 00:12:01,760 --> 00:12:05,360 Speaker 1: them participants and look at how certain they are about 250 00:12:05,400 --> 00:12:09,600 Speaker 1: their future expectations. The FED is more certain now, right 251 00:12:09,600 --> 00:12:13,000 Speaker 1: now about than it has ever been since the dot 252 00:12:13,000 --> 00:12:16,680 Speaker 1: plots started for a future year. They are signaling very 253 00:12:16,760 --> 00:12:19,640 Speaker 1: strongly that they are not going to raise rates. It's 254 00:12:19,720 --> 00:12:21,920 Speaker 1: really unusual. Standard deviation is like a third of what 255 00:12:22,000 --> 00:12:24,400 Speaker 1: it usually is from an end of year forward year. Look, 256 00:12:25,840 --> 00:12:29,960 Speaker 1: that sounds like a rejection. He didn't reject lightly helitely 257 00:12:30,040 --> 00:12:33,400 Speaker 1: rejected your assertion. I I very impolitely rejected your just 258 00:12:33,520 --> 00:12:36,280 Speaker 1: we just follow the numbers. Yeah, right, I just reject 259 00:12:36,280 --> 00:12:38,120 Speaker 1: things out right. I do think when you say, Jay, 260 00:12:38,120 --> 00:12:40,040 Speaker 1: don't touch that dial, the idea that they will be 261 00:12:40,080 --> 00:12:43,240 Speaker 1: on hold at best, uh, you know, at worst, if 262 00:12:43,240 --> 00:12:47,360 Speaker 1: things do deteriorate, they will cut rates and support the 263 00:12:47,440 --> 00:12:50,360 Speaker 1: economic and asset price expansion. One thing I noticed is 264 00:12:50,400 --> 00:12:52,760 Speaker 1: that you came in with a prop today. Yes, the 265 00:12:52,800 --> 00:12:54,760 Speaker 1: prop has to do with the fact that a hundred 266 00:12:54,880 --> 00:12:58,480 Speaker 1: years ago today was the liftoff point for radio as 267 00:12:58,520 --> 00:13:03,400 Speaker 1: a medium. The first broadcast news was Warren Harding winning 268 00:13:03,400 --> 00:13:05,800 Speaker 1: the nineteen twenty election, and it was really what spurred 269 00:13:05,920 --> 00:13:09,679 Speaker 1: radio into popular use. You know, the at the being 270 00:13:09,720 --> 00:13:11,800 Speaker 1: in eighteen twenties, one percent of the population I had 271 00:13:11,840 --> 00:13:15,920 Speaker 1: a radio. By nineteen thirty, it was closer. He has this, uh, 272 00:13:16,280 --> 00:13:21,400 Speaker 1: the wireless age issue from April nineteen twenty two, Uh, 273 00:13:21,520 --> 00:13:27,120 Speaker 1: it's got wow. It was Amazon eBay five five bucks 274 00:13:27,160 --> 00:13:30,240 Speaker 1: on eBay. Wireless Age was the hobbyist magazine of the 275 00:13:30,360 --> 00:13:33,600 Speaker 1: radio age in the nineteen twenties. Uh, and it looks 276 00:13:33,640 --> 00:13:36,840 Speaker 1: exactly like a computer nerd magazine from the nineteen eighties 277 00:13:36,840 --> 00:13:39,240 Speaker 1: and nineties. It was really you know, the industry was 278 00:13:39,280 --> 00:13:42,600 Speaker 1: built by enthusiasts and only slowly commercialized. It's funny. We're 279 00:13:42,600 --> 00:13:44,920 Speaker 1: just talking to Justin Fox of Bloomer talking about the 280 00:13:44,960 --> 00:13:48,360 Speaker 1: evolution of media, and primarily from a news perspective, about 281 00:13:48,400 --> 00:13:50,720 Speaker 1: the obviously the decline in the local newspaper and local 282 00:13:50,760 --> 00:13:54,439 Speaker 1: media and how that may be contributing to the polarization 283 00:13:54,440 --> 00:13:56,760 Speaker 1: of the US and you know the left and the right, 284 00:13:56,800 --> 00:13:59,680 Speaker 1: and how cable television and you know, talk shows and 285 00:13:59,679 --> 00:14:01,920 Speaker 1: so on and so forth may have contributed to that. 286 00:14:02,040 --> 00:14:04,600 Speaker 1: So it kind of brings into context the one hundred 287 00:14:04,720 --> 00:14:07,160 Speaker 1: years of it and it all started with radio, and 288 00:14:07,160 --> 00:14:09,719 Speaker 1: it all started with radio. And yes, and here we are, 289 00:14:09,840 --> 00:14:12,800 Speaker 1: and here we are continuing to beat that drum exactly. 290 00:14:12,840 --> 00:14:15,320 Speaker 1: Thank you so much for going with us. Nick Nichole's 291 00:14:15,360 --> 00:14:17,840 Speaker 1: co founder Data Track Research, joining us here on our 292 00:14:17,880 --> 00:14:21,240 Speaker 1: Bloomberg Interactive Broker Studio giving us lots of perspective on 293 00:14:21,280 --> 00:14:27,840 Speaker 1: the markets coming from the disappointment extraordinary performance. The question 294 00:14:27,920 --> 00:14:31,160 Speaker 1: is what does what do the markets hold in store 295 00:14:31,280 --> 00:14:50,560 Speaker 1: for us? With a launch of Disney Plus in November 296 00:14:50,640 --> 00:14:53,640 Speaker 1: of last year, many expect to be the year that 297 00:14:53,680 --> 00:14:56,360 Speaker 1: the streaming wars really heat up. To get a sense 298 00:14:56,440 --> 00:14:57,880 Speaker 1: kind of where we are here in the early days, 299 00:14:57,920 --> 00:15:00,760 Speaker 1: we welcome Roman Crossing, He's said, of data analytics at 300 00:15:00,760 --> 00:15:04,720 Speaker 1: Eagle Alpha, joins us on the phone from Dublin, Ireland. Ronan, 301 00:15:04,720 --> 00:15:07,320 Speaker 1: thanks so much for joining us. It seems like, you know, 302 00:15:07,360 --> 00:15:09,560 Speaker 1: as we entered twenty nineteen, it was all pretty much 303 00:15:09,840 --> 00:15:13,200 Speaker 1: a Netflix story. But it's getting pretty competitive out there, 304 00:15:13,200 --> 00:15:16,640 Speaker 1: isn't it. It is absolutely yeah, no, it is getting 305 00:15:16,680 --> 00:15:20,160 Speaker 1: more competitive. But what we're actually seeing is that with 306 00:15:20,280 --> 00:15:22,400 Speaker 1: the launch of Disney Plus, what we've actually seen is 307 00:15:22,480 --> 00:15:26,320 Speaker 1: Disney Plus have grown the market um like we around 308 00:15:26,320 --> 00:15:30,160 Speaker 1: the time of the Netflix they're disappointing Q two earnings 309 00:15:30,240 --> 00:15:34,440 Speaker 1: last year, we started tracking Netflix using social media data, 310 00:15:34,480 --> 00:15:37,960 Speaker 1: particularly from Twitter, and what we noticed was that Netflix 311 00:15:38,040 --> 00:15:40,880 Speaker 1: was continuing to gain momentum and was continuing to get 312 00:15:40,880 --> 00:15:43,920 Speaker 1: stronger and stronger. Then around the time of the Disney 313 00:15:43,920 --> 00:15:46,960 Speaker 1: Plus launch, in November, we saw that actually that grew 314 00:15:47,040 --> 00:15:50,800 Speaker 1: the market, and Netflix continued to grow as Disney Plus did, 315 00:15:51,360 --> 00:15:54,120 Speaker 1: and so we're seeing, actually, it's it's not necessarily a 316 00:15:54,200 --> 00:15:57,640 Speaker 1: zero sum game. The market continues to grow overall. All Right, 317 00:15:57,680 --> 00:16:00,000 Speaker 1: This is a really interesting take because I think Netflix 318 00:16:00,120 --> 00:16:02,040 Speaker 1: x is one of the most compelling companies to watch 319 00:16:02,040 --> 00:16:06,320 Speaker 1: in because of Disney Plus, because of this consensus that 320 00:16:06,400 --> 00:16:09,720 Speaker 1: there can only be so many streaming services. What do 321 00:16:09,760 --> 00:16:12,480 Speaker 1: you think will drive their profitability the fact that they 322 00:16:12,560 --> 00:16:14,560 Speaker 1: might not just burn through cash. Is it going to 323 00:16:14,680 --> 00:16:17,960 Speaker 1: be uh, charging subscribers more, Is it going to be 324 00:16:18,000 --> 00:16:20,240 Speaker 1: expanding their subscriber base, or is it going to be 325 00:16:20,280 --> 00:16:25,040 Speaker 1: monetizing things like advertising or data streams? Well, I think 326 00:16:25,200 --> 00:16:27,360 Speaker 1: it always comes back to the content, right, and the 327 00:16:27,440 --> 00:16:30,160 Speaker 1: Netflix has consistently invested in their content, and we actually 328 00:16:30,200 --> 00:16:34,400 Speaker 1: saw that as we track the conversation online, it's the 329 00:16:34,440 --> 00:16:38,040 Speaker 1: top shows that are continuing to gain momentum. And actually, 330 00:16:38,080 --> 00:16:41,120 Speaker 1: what we saw in twenty eighteen was that there was 331 00:16:41,400 --> 00:16:44,080 Speaker 1: somewhat of a depth of news shows coming on that 332 00:16:44,120 --> 00:16:48,000 Speaker 1: we weren't seeing the same appetite and enthusiasm on one 333 00:16:48,080 --> 00:16:50,960 Speaker 1: on on online for those those shows at Netflix. But 334 00:16:50,960 --> 00:16:54,240 Speaker 1: actually nineteen. It feels like they got it right, particularly 335 00:16:54,240 --> 00:16:56,840 Speaker 1: towards the second half of the year, and so we 336 00:16:56,880 --> 00:17:02,240 Speaker 1: think they did take the higher subscription um Earlier last year, 337 00:17:02,280 --> 00:17:05,320 Speaker 1: they increased their subscription prices, and we think that that, 338 00:17:05,520 --> 00:17:08,480 Speaker 1: combined with the weaker content of teen was probably what 339 00:17:08,640 --> 00:17:11,760 Speaker 1: led to those leaker, weaker numbers in Q two. But 340 00:17:11,880 --> 00:17:13,960 Speaker 1: actually the content has got much stronger and we think 341 00:17:14,000 --> 00:17:16,800 Speaker 1: we can can absorb that pricing, and we we were 342 00:17:16,800 --> 00:17:19,240 Speaker 1: seeing that in terms of the momentum coming out of 343 00:17:19,240 --> 00:17:23,399 Speaker 1: the year. So running as you monitor and analyze social media, 344 00:17:24,280 --> 00:17:26,439 Speaker 1: you know, commentary as it relates to some of these 345 00:17:26,480 --> 00:17:28,720 Speaker 1: streaming companies, are you hearing anything about some of the 346 00:17:28,760 --> 00:17:30,560 Speaker 1: others out there? What are you hearing about some of 347 00:17:30,600 --> 00:17:33,879 Speaker 1: the others, whether it's a an existing streaming thing, a 348 00:17:33,920 --> 00:17:36,960 Speaker 1: brand like Hulu or something new like the you know, 349 00:17:37,119 --> 00:17:39,639 Speaker 1: HBO max is coming out, and then I think Comcast 350 00:17:39,720 --> 00:17:43,040 Speaker 1: has uh coming out with Peacock. Are you are they 351 00:17:43,200 --> 00:17:46,080 Speaker 1: registering at all on social media right now? Yeah, so 352 00:17:46,080 --> 00:17:48,160 Speaker 1: so no, it's a it's a great question, Paul. So 353 00:17:48,600 --> 00:17:52,320 Speaker 1: what we're seeing is not with Disney Plus was definitely 354 00:17:52,800 --> 00:17:56,080 Speaker 1: a breakthrough compared to see Apple TV Plus and what 355 00:17:56,119 --> 00:17:59,960 Speaker 1: we've seen is that, yes, Netflix has continued to perform well, 356 00:18:00,119 --> 00:18:03,240 Speaker 1: but Disney Plus is really showing strong momentum and has 357 00:18:03,280 --> 00:18:05,840 Speaker 1: gone straight in there at number two if you like, 358 00:18:06,720 --> 00:18:11,320 Speaker 1: within the streaming streaming universe, whereas we see someone like 359 00:18:11,400 --> 00:18:15,760 Speaker 1: Hulu and Roku are continuing continuing to to to tread 360 00:18:15,800 --> 00:18:18,400 Speaker 1: at a similar level, whereas Apple TV plus come out 361 00:18:18,400 --> 00:18:20,520 Speaker 1: and come in at a much lower level. So we 362 00:18:20,600 --> 00:18:24,520 Speaker 1: see certainly we see Disney or Netflix at number one, 363 00:18:24,560 --> 00:18:27,280 Speaker 1: but Disney Plus is doing really well and that continued 364 00:18:27,320 --> 00:18:30,560 Speaker 1: into the holiday season. We're seeing the Mandalorian in particular 365 00:18:30,600 --> 00:18:34,359 Speaker 1: has has proven to be particular, particularly popular. All the 366 00:18:34,400 --> 00:18:36,960 Speaker 1: people say that the real game changer will be live 367 00:18:37,040 --> 00:18:41,440 Speaker 1: sports and whether the cable networks will lose live sports 368 00:18:41,480 --> 00:18:45,720 Speaker 1: streaming to some of these services. Do you foresee that 369 00:18:45,960 --> 00:18:50,359 Speaker 1: being a significant game changer that potentially creates losers and 370 00:18:50,359 --> 00:18:55,359 Speaker 1: winners the results in either insolvencies or mergers. Yes, So 371 00:18:55,600 --> 00:18:58,719 Speaker 1: so as a firm, Eagle also we look right across 372 00:18:58,760 --> 00:19:01,080 Speaker 1: the alternative data spectrum. So we've talked a lot about 373 00:19:01,080 --> 00:19:05,360 Speaker 1: the Twitter social media analysis, but as a firm, we're 374 00:19:05,359 --> 00:19:07,480 Speaker 1: looking at many more data sets out there, and I 375 00:19:07,520 --> 00:19:10,840 Speaker 1: think they will be really crivotal in analyzing this trend, 376 00:19:10,880 --> 00:19:15,040 Speaker 1: because you're absolutely right, this is a very fluid market 377 00:19:15,320 --> 00:19:16,720 Speaker 1: and I think we're going to have to you know, 378 00:19:16,720 --> 00:19:18,920 Speaker 1: we're gonna have to monitor that date over time. Live 379 00:19:19,000 --> 00:19:23,119 Speaker 1: sports is absolutely a hot topic. We're seeing it in 380 00:19:23,240 --> 00:19:26,760 Speaker 1: terms of online conversation and there's definitely the appetite for 381 00:19:27,640 --> 00:19:32,119 Speaker 1: more live live sports via the streaming platforms, and I 382 00:19:32,160 --> 00:19:34,800 Speaker 1: think that it's something we're gonna have to monitor very closely, 383 00:19:34,800 --> 00:19:37,280 Speaker 1: and we will be monitoring very closely. Ronan, thank you 384 00:19:37,320 --> 00:19:39,640 Speaker 1: so much for being with us. Ronan Crossing, the head 385 00:19:39,640 --> 00:19:43,280 Speaker 1: of data analytics with Eagle Alpha, joining us on the 386 00:19:43,280 --> 00:19:46,960 Speaker 1: phone from Dublin, Ireland, talking about what I think will 387 00:19:47,000 --> 00:19:50,159 Speaker 1: be one of the most fascinating fields in which is 388 00:19:50,160 --> 00:20:07,440 Speaker 1: the streaming Paul. I love it when we talk about 389 00:20:07,480 --> 00:20:10,520 Speaker 1: cybersecurity because it's always some iteration of why we should 390 00:20:10,520 --> 00:20:12,600 Speaker 1: all be really scared and we're about to deal with 391 00:20:12,720 --> 00:20:17,320 Speaker 1: something really tragic and and regret regretful based on the 392 00:20:17,359 --> 00:20:19,360 Speaker 1: excess of our data out there in the mainstream. Joining 393 00:20:19,400 --> 00:20:21,640 Speaker 1: us now to talk about that. Steve Grogman, he's chief 394 00:20:21,640 --> 00:20:25,960 Speaker 1: technology officer at McAfee, joining us on the phone from Dallas. 395 00:20:26,200 --> 00:20:27,560 Speaker 1: I want to get your son, Steve. So when we 396 00:20:27,560 --> 00:20:29,800 Speaker 1: talk about why we should get scared with respect to 397 00:20:29,840 --> 00:20:32,200 Speaker 1: all of the cybersecurity threats, what are the main reasons 398 00:20:32,320 --> 00:20:36,000 Speaker 1: that we should be nervous right now? Sure you bet. 399 00:20:36,240 --> 00:20:38,639 Speaker 1: First off, Happy New year, Lisa and Paul, and you know, 400 00:20:38,800 --> 00:20:43,440 Speaker 1: cybersecurity is really one of these areas that impacts consumers, 401 00:20:43,480 --> 00:20:47,240 Speaker 1: It impacts business, it could even impact the upcoming election cycle, 402 00:20:47,280 --> 00:20:49,600 Speaker 1: and maybe just to kick us off, if we look 403 00:20:49,680 --> 00:20:53,480 Speaker 1: at it from a consumer standpoint, the thing that consumers 404 00:20:53,520 --> 00:20:56,560 Speaker 1: really need to worry about is having their accounts and 405 00:20:56,640 --> 00:21:00,359 Speaker 1: account data stolen. One of the things that we seen 406 00:21:00,560 --> 00:21:06,720 Speaker 1: is over two billion dollars of consumer account information with 407 00:21:06,880 --> 00:21:10,320 Speaker 1: up for sale on the black market. That's eventually going 408 00:21:10,400 --> 00:21:12,879 Speaker 1: to be sold to individuals that will use it for 409 00:21:12,920 --> 00:21:17,800 Speaker 1: identity theft or fraudulent purposes. What's really interesting for folks 410 00:21:17,840 --> 00:21:20,600 Speaker 1: to be on the lookout now is how they can 411 00:21:20,600 --> 00:21:24,359 Speaker 1: be targeted because it's not just through fitting emails. We 412 00:21:24,400 --> 00:21:28,840 Speaker 1: now see things like phishing texts or even robo calls, 413 00:21:28,880 --> 00:21:31,960 Speaker 1: and really having consumers understand that these are all things 414 00:21:31,960 --> 00:21:34,359 Speaker 1: they need to be aware of. His key, So, Steve, 415 00:21:34,960 --> 00:21:37,399 Speaker 1: give us a sense of where the regulatory environment is. 416 00:21:37,440 --> 00:21:41,600 Speaker 1: It just seems like they're the regulations cannot whether it's 417 00:21:41,600 --> 00:21:44,359 Speaker 1: you know, robo calls or whatever, cannot stay ahead of 418 00:21:44,359 --> 00:21:46,840 Speaker 1: the technology. What do you think is the best way, 419 00:21:46,920 --> 00:21:49,639 Speaker 1: assuming that you know, government regulation is not there to 420 00:21:49,640 --> 00:21:53,200 Speaker 1: protect us per se, what do you suggest for your 421 00:21:53,280 --> 00:21:57,200 Speaker 1: corporate clients that they do sure so, so, first off, 422 00:21:57,200 --> 00:22:01,720 Speaker 1: there's actually been a lot of great progress s against 423 00:22:01,840 --> 00:22:08,880 Speaker 1: robocalls in both on the regulatory and technology side. On 424 00:22:08,920 --> 00:22:13,520 Speaker 1: the regulatory side, the carriers have now received higher levels 425 00:22:13,560 --> 00:22:17,520 Speaker 1: of empowerment to go after and block some of these robocalls, 426 00:22:17,520 --> 00:22:21,320 Speaker 1: so monitor them. When they detect patterns that look like 427 00:22:21,400 --> 00:22:24,560 Speaker 1: it's not legitimate, they are now authorized to block them. 428 00:22:24,560 --> 00:22:27,360 Speaker 1: There's also some new technology. It has kind of an 429 00:22:27,359 --> 00:22:32,240 Speaker 1: interesting name. It's called Shaken and stir uh so either 430 00:22:32,520 --> 00:22:36,040 Speaker 1: Martini or James Bond reference. But a Stir is for 431 00:22:36,119 --> 00:22:39,800 Speaker 1: those business systems the void systems, and Shaken is for 432 00:22:39,960 --> 00:22:43,879 Speaker 1: cell and landline. And what these technologies will do is 433 00:22:43,920 --> 00:22:46,439 Speaker 1: it will make it so that when you get caller 434 00:22:46,560 --> 00:22:50,560 Speaker 1: I D information, it will be authenticated such that it's 435 00:22:50,560 --> 00:22:53,199 Speaker 1: going to be much harder to spoof. The challenges is 436 00:22:53,280 --> 00:22:57,360 Speaker 1: that it's gonna take some time to implement these new 437 00:22:57,359 --> 00:23:01,600 Speaker 1: technologies across the board and in the um consumers M 438 00:23:01,680 --> 00:23:04,560 Speaker 1: businesses really need to have a very heightened state of 439 00:23:04,600 --> 00:23:07,320 Speaker 1: alert anytime they get a text or a or a 440 00:23:07,359 --> 00:23:11,040 Speaker 1: phone call because it's very likely not coming from the 441 00:23:11,080 --> 00:23:13,160 Speaker 1: source that the caller I D says that it is. 442 00:23:13,600 --> 00:23:17,439 Speaker 1: So how is McAfee seeing the business spending when it 443 00:23:17,480 --> 00:23:21,640 Speaker 1: comes to cybersecurity? I mean, has it been steadily accelerating 444 00:23:21,760 --> 00:23:24,280 Speaker 1: at an exponential speed or they bring it back and 445 00:23:24,320 --> 00:23:28,120 Speaker 1: being more selective about how they invest. So what we've 446 00:23:28,119 --> 00:23:32,679 Speaker 1: seen is businesses now recognize that they need to protect 447 00:23:32,720 --> 00:23:35,439 Speaker 1: all of the technologies that they're using to run their 448 00:23:35,480 --> 00:23:40,520 Speaker 1: business in and we'll see the trend continue in there's 449 00:23:40,560 --> 00:23:46,120 Speaker 1: a significant movement and embracing of cloud technologies, and with 450 00:23:46,280 --> 00:23:49,679 Speaker 1: that move of business to the cloud, we see cyber 451 00:23:49,720 --> 00:23:53,160 Speaker 1: threats now starting to target the cloud environment. So one 452 00:23:53,200 --> 00:23:57,040 Speaker 1: of the things that McAfee has done is we've extended 453 00:23:57,200 --> 00:24:02,240 Speaker 1: our enterprise portfolio to include both traditional environments and cloud 454 00:24:02,320 --> 00:24:05,280 Speaker 1: and where we see a lot of the business investment 455 00:24:05,800 --> 00:24:08,200 Speaker 1: is making sure that as they moved to the cloud 456 00:24:08,520 --> 00:24:12,000 Speaker 1: to run their business, that they can protect those environments 457 00:24:12,320 --> 00:24:15,399 Speaker 1: as well as their traditional environments. Steve, give us a 458 00:24:15,440 --> 00:24:19,520 Speaker 1: sense of how much of the cybercrime or cymber, you know, 459 00:24:20,119 --> 00:24:22,960 Speaker 1: the issues that people are dealing with, the threats, are 460 00:24:23,080 --> 00:24:25,919 Speaker 1: how much of that a state sponsored versus maybe individual 461 00:24:26,040 --> 00:24:27,399 Speaker 1: or criminal. Do we have a sense of kind of 462 00:24:27,440 --> 00:24:32,360 Speaker 1: that breakdown these days, So we don't have very specific 463 00:24:32,560 --> 00:24:37,480 Speaker 1: quantitative breakdowns, but we do see some interesting patterns. For example, 464 00:24:37,600 --> 00:24:41,240 Speaker 1: last year we saw a major ransomware campaign. It was 465 00:24:41,280 --> 00:24:45,400 Speaker 1: called the Sodan the Kibi campaign, and what was interesting 466 00:24:45,440 --> 00:24:50,959 Speaker 1: about this was it very specifically targeted North America and 467 00:24:51,040 --> 00:24:54,400 Speaker 1: Western Europe. The way that it did that is part 468 00:24:54,440 --> 00:24:58,240 Speaker 1: of the code looked at what was the local language 469 00:24:58,240 --> 00:25:01,680 Speaker 1: that was installed on the computer it or that got infected, 470 00:25:02,000 --> 00:25:04,119 Speaker 1: and if it was one of those languages from the 471 00:25:04,160 --> 00:25:07,960 Speaker 1: former Soviet Union, it would basically not run. What that 472 00:25:08,080 --> 00:25:13,200 Speaker 1: essentially did is even if individuals or businesses in certain 473 00:25:13,240 --> 00:25:17,560 Speaker 1: parts of the world got targeted or or were exposed 474 00:25:17,960 --> 00:25:21,520 Speaker 1: to this ransomware, it was essentially benign on their environment 475 00:25:22,000 --> 00:25:26,120 Speaker 1: and only selectively impacted certain parts of the world. So 476 00:25:27,119 --> 00:25:31,560 Speaker 1: whether that was a cyber crime organization that was focusing 477 00:25:31,720 --> 00:25:36,400 Speaker 1: on areas that they won't be prosecuted or other reasons. 478 00:25:36,760 --> 00:25:38,720 Speaker 1: You know, those are typically some of the reasons we 479 00:25:38,760 --> 00:25:41,119 Speaker 1: see that that sort of behavior. Hey, Steve, thanks so 480 00:25:41,200 --> 00:25:44,080 Speaker 1: much for joining us. We appreciate your thoughts. Steve Groban, 481 00:25:44,160 --> 00:25:47,400 Speaker 1: chief technology officer for McAfee, joining us on the phone 482 00:25:47,400 --> 00:25:50,200 Speaker 1: from Dallas, Texas. Thanks for listening to the Bloomberg P 483 00:25:50,280 --> 00:25:52,840 Speaker 1: and L podcast. You can subscribe and listen to interviews 484 00:25:52,840 --> 00:25:56,639 Speaker 1: at Apple Podcasts or whatever podcast platform you prefer. Paul Sweeney, 485 00:25:56,720 --> 00:25:59,440 Speaker 1: I'm on Twitter at pt Sweeney. And Lisa bram Woids 486 00:25:59,440 --> 00:26:02,480 Speaker 1: I'm on Twitter at Lisa Abramo. It's one before the podcast. 487 00:26:02,520 --> 00:26:07,280 Speaker 1: You can always catch us worldwide on Bloomberg Radiom