1 00:00:02,440 --> 00:00:09,119 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the 2 00:00:09,160 --> 00:00:13,280 Speaker 1: Bloomberg Intelligence Podcast. Catch us live weekdays at ten am 3 00:00:13,360 --> 00:00:17,040 Speaker 1: Eastern on Effocarplay and Android Auto with the Bloomberg Business App. 4 00:00:17,079 --> 00:00:20,279 Speaker 1: Listen on demand wherever you get your podcasts, or watch 5 00:00:20,360 --> 00:00:22,320 Speaker 1: us live on YouTube. 6 00:00:23,440 --> 00:00:26,400 Speaker 2: Malex Steel alongside Paul Sweeney. Happy Friday. Everyone made it 7 00:00:26,600 --> 00:00:29,240 Speaker 2: the end of the week. Yes, we did that. Lots 8 00:00:29,280 --> 00:00:30,840 Speaker 2: to go through over the next couple hours. We want 9 00:00:30,880 --> 00:00:32,680 Speaker 2: to kick off with more on that you mished sentiment. 10 00:00:32,760 --> 00:00:34,880 Speaker 2: It is the final read for November, but I'm interested 11 00:00:34,920 --> 00:00:36,400 Speaker 2: to see sort of what that brings in when it 12 00:00:36,440 --> 00:00:39,479 Speaker 2: comes to the election result. So Joe Anshu, University of 13 00:00:39,560 --> 00:00:42,880 Speaker 2: Michigan Surveys of Consumer Director joins us sentiment coming in 14 00:00:42,960 --> 00:00:44,879 Speaker 2: at about seventy three point nine, a little bit better 15 00:00:45,000 --> 00:00:48,800 Speaker 2: current condition sixty four point four, also better expectations, also 16 00:00:48,920 --> 00:00:50,840 Speaker 2: a touch better. Does this encapsulate the election? 17 00:00:51,760 --> 00:00:52,479 Speaker 3: Yes it does so. 18 00:00:52,600 --> 00:00:56,040 Speaker 4: Our preliminary read that we released two weeks ago did 19 00:00:56,120 --> 00:00:59,600 Speaker 4: not encapsulate the election, but today's release includes two weeks, 20 00:01:00,080 --> 00:01:02,840 Speaker 4: four and two weeks after the election. Essentially, what we 21 00:01:03,000 --> 00:01:06,640 Speaker 4: saw was that after Trump was elected, sentiment lost about 22 00:01:06,680 --> 00:01:08,160 Speaker 4: half of the gains that it had seen in the 23 00:01:08,200 --> 00:01:11,640 Speaker 4: first two weeks of the month. But on net, we're 24 00:01:11,680 --> 00:01:13,840 Speaker 4: still a little bit better than we were in October, 25 00:01:14,000 --> 00:01:17,120 Speaker 4: and we are now at four straight months of incremental gains. 26 00:01:17,640 --> 00:01:20,040 Speaker 5: Johan, talk to us about inflation out look. I know 27 00:01:20,280 --> 00:01:22,000 Speaker 5: you guys at Michigan take a look at that in 28 00:01:22,080 --> 00:01:25,319 Speaker 5: your survey. How are people thinking about the inflation netlook? 29 00:01:26,480 --> 00:01:30,800 Speaker 4: In the short run, people are expecting inflation to continue stabilizing. 30 00:01:31,400 --> 00:01:34,759 Speaker 4: We saw the year ahead inflation expectations edged down by 31 00:01:34,840 --> 00:01:39,200 Speaker 4: one tenth of percent, likely supported by lower gas prices 32 00:01:39,240 --> 00:01:42,160 Speaker 4: at this time of year. That being said, we actually 33 00:01:42,240 --> 00:01:46,160 Speaker 4: saw long run inflation expectations go from three point zero 34 00:01:46,240 --> 00:01:48,200 Speaker 4: to three point two. That's kind of on the high 35 00:01:48,320 --> 00:01:50,440 Speaker 4: side of the range we've been seeing for the last 36 00:01:50,520 --> 00:01:53,680 Speaker 4: couple of years. Consumers are perceiving quite a bit of 37 00:01:53,760 --> 00:01:57,200 Speaker 4: uncertainty over long run inflation, which is consistent with the 38 00:01:57,280 --> 00:02:01,279 Speaker 4: fact that we don't really know exactly Trump's economic agenda 39 00:02:01,360 --> 00:02:03,080 Speaker 4: is going to look like over the next four years, 40 00:02:03,120 --> 00:02:05,160 Speaker 4: So that uncertainty seems quite reasonable. 41 00:02:05,480 --> 00:02:07,400 Speaker 5: All right, Joe, and thank you so much. We appreciate it. 42 00:02:07,720 --> 00:02:10,000 Speaker 5: I appreciating a couple of minutes of your time joined shoe. 43 00:02:10,160 --> 00:02:13,160 Speaker 5: She's at the University of Michigan Surveys of consumer She 44 00:02:13,280 --> 00:02:15,480 Speaker 5: directs to that whole business here and again the you 45 00:02:15,600 --> 00:02:18,079 Speaker 5: missurveyed numbers just a headline number. I'm gonna go with that. 46 00:02:18,200 --> 00:02:20,560 Speaker 5: It came in at seventy one point eight contentius seventy 47 00:02:20,560 --> 00:02:22,880 Speaker 5: three point nine and also is down a little bit 48 00:02:22,919 --> 00:02:24,120 Speaker 5: from last period as well. 49 00:02:25,560 --> 00:02:29,400 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 50 00:02:29,520 --> 00:02:33,040 Speaker 1: weekdays at ten am Eastern on applecar Play and Android 51 00:02:33,080 --> 00:02:35,800 Speaker 1: Auto with the Bloomberg Business app. You can also listen 52 00:02:35,960 --> 00:02:39,040 Speaker 1: live on Amazon Alexa from our flagship New York station. 53 00:02:39,440 --> 00:02:42,160 Speaker 1: Just say Alexa Play Bloomberg eleven thirty. 54 00:02:43,360 --> 00:02:45,000 Speaker 2: Let's get to the other big news of the day, 55 00:02:45,120 --> 00:02:48,359 Speaker 2: and that was European PMIS. They were terrible and you 56 00:02:48,480 --> 00:02:51,200 Speaker 2: definitely then saw rerating in terms of cuts, maybe a 57 00:02:51,240 --> 00:02:53,799 Speaker 2: fifty basis point cut from the ECB. So we wanted 58 00:02:53,840 --> 00:02:55,160 Speaker 2: to break it down a little bit more for you 59 00:02:55,200 --> 00:02:58,960 Speaker 2: with David Powell Senior. You're area economist for Bloomberg Economics. 60 00:02:59,440 --> 00:03:02,359 Speaker 2: David was so bad about these numbers. What stood out 61 00:03:02,400 --> 00:03:04,080 Speaker 2: to you, Well. 62 00:03:04,040 --> 00:03:06,400 Speaker 6: Actually they were bad all around, and that's really what 63 00:03:06,560 --> 00:03:09,840 Speaker 6: stood out. There was no bright spots here, so the 64 00:03:10,160 --> 00:03:13,960 Speaker 6: composite figure for the your area declined and the numbers 65 00:03:14,120 --> 00:03:17,400 Speaker 6: for both the services and manufacturing sectors were weak. In 66 00:03:17,480 --> 00:03:19,959 Speaker 6: addition to that, we get a national breakdown at the 67 00:03:20,000 --> 00:03:23,440 Speaker 6: first release which shows the numbers for France and Germany, 68 00:03:23,680 --> 00:03:26,120 Speaker 6: and it showed both of the your areas to largest 69 00:03:26,160 --> 00:03:30,040 Speaker 6: economies experience weakness. So it's not something that's just isolated 70 00:03:30,080 --> 00:03:33,160 Speaker 6: to one country or one sector. It's this broad based weakness. 71 00:03:34,160 --> 00:03:37,040 Speaker 5: Again, it's interesting that we woke up to this data 72 00:03:37,080 --> 00:03:39,360 Speaker 5: here in the States, David, and we kind of said 73 00:03:39,400 --> 00:03:41,720 Speaker 5: we knew there was you know, it was softer in 74 00:03:42,160 --> 00:03:44,200 Speaker 5: across Europe, but some of this data came in and 75 00:03:44,280 --> 00:03:47,880 Speaker 5: just really, I think, surprise the markets here. What's the 76 00:03:48,000 --> 00:03:50,920 Speaker 5: expectation for the next you know, six to twelve months 77 00:03:51,040 --> 00:03:53,320 Speaker 5: as reached in European economic activity. 78 00:03:54,360 --> 00:03:58,160 Speaker 6: Well, I think the market is bracing for deterioration in 79 00:03:58,280 --> 00:04:01,000 Speaker 6: the economic numbers coming out out of coming out of 80 00:04:01,080 --> 00:04:04,640 Speaker 6: the EUR area, and that's because of the electoral victory 81 00:04:04,680 --> 00:04:07,840 Speaker 6: of Donald Trump. One of his campaign promises was to 82 00:04:08,920 --> 00:04:13,600 Speaker 6: impose tariffs not only on China, but smaller tariffs on 83 00:04:13,720 --> 00:04:17,160 Speaker 6: other trading partners and one country that really stands out 84 00:04:17,200 --> 00:04:20,640 Speaker 6: in that list is Germany given its huge trade surplus 85 00:04:21,240 --> 00:04:24,320 Speaker 6: with the United States, and it's a country that Donald 86 00:04:24,360 --> 00:04:28,760 Speaker 6: Trump specifically referred to on many occasions during the campaign. 87 00:04:29,520 --> 00:04:33,360 Speaker 6: And we have run the numbers and our estimate is 88 00:04:33,480 --> 00:04:35,800 Speaker 6: if those tariffs turn out to be as high as 89 00:04:36,440 --> 00:04:39,120 Speaker 6: Trump promised during the campaign, that could knock in the 90 00:04:39,200 --> 00:04:42,560 Speaker 6: short term about one percent off of GDP in the 91 00:04:42,640 --> 00:04:46,760 Speaker 6: EU area. And we've also had estimates come from the 92 00:04:47,240 --> 00:04:50,640 Speaker 6: Bundesbank Germany Central Bank, and they have a similar estimate 93 00:04:50,680 --> 00:04:53,160 Speaker 6: for the German economy. And that's going to be a 94 00:04:53,240 --> 00:04:56,960 Speaker 6: big shock to demand in the your era, which will 95 00:04:57,040 --> 00:05:00,360 Speaker 6: require the ECB in all likelihood to respond the form 96 00:05:00,400 --> 00:05:04,320 Speaker 6: of lower interest rates. And that comes on top of 97 00:05:04,440 --> 00:05:07,240 Speaker 6: what was already a weak economy before any of this happened. 98 00:05:07,400 --> 00:05:09,719 Speaker 2: Okay, so do you think fifty basis points coming up? 99 00:05:12,440 --> 00:05:15,479 Speaker 6: I don't think they'll cut by fifty basis points in December. 100 00:05:15,480 --> 00:05:19,200 Speaker 6: It will certainly introduce that topic for discussion. I think 101 00:05:19,240 --> 00:05:22,280 Speaker 6: the more likely outcome is you just see a longer 102 00:05:22,400 --> 00:05:25,400 Speaker 6: period of twenty five basis point cuts. So we look 103 00:05:25,480 --> 00:05:29,000 Speaker 6: for a cut of twenty five basis points in December, 104 00:05:29,320 --> 00:05:32,080 Speaker 6: and we think the ECB will keep with these back 105 00:05:32,160 --> 00:05:36,080 Speaker 6: to back cuts being cut at every meeting until until 106 00:05:36,120 --> 00:05:39,160 Speaker 6: they reached neutral, which is about two percent. So we're 107 00:05:39,200 --> 00:05:43,680 Speaker 6: going to have numerous cuts coming up throughout the start 108 00:05:43,720 --> 00:05:48,200 Speaker 6: of twenty twenty five. And like I said, more frequent 109 00:05:48,279 --> 00:05:50,119 Speaker 6: cuts is more likely than larger cuts. 110 00:05:50,920 --> 00:05:52,600 Speaker 5: David, thank you so much for joining us. We appreciate 111 00:05:52,640 --> 00:05:54,400 Speaker 5: getting a few minutes of your time. David Powell, he's 112 00:05:54,440 --> 00:05:58,800 Speaker 5: a senior Euro Area economist for Bloomberg Economics. That joining 113 00:05:58,920 --> 00:06:01,560 Speaker 5: us from via zoom thing. 114 00:06:03,000 --> 00:06:06,800 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 115 00:06:06,920 --> 00:06:09,080 Speaker 1: weekdays at ten am Eastern on fo. 116 00:06:09,040 --> 00:06:11,719 Speaker 7: Cardplay and Android auto with the Bloomberg Business app. 117 00:06:11,800 --> 00:06:15,000 Speaker 1: Listen on demand wherever you get your podcasts, or watch 118 00:06:15,080 --> 00:06:16,320 Speaker 1: us live on YouTube. 119 00:06:18,000 --> 00:06:20,680 Speaker 2: So and video is built as like the biggest event 120 00:06:21,160 --> 00:06:22,680 Speaker 2: for the end of the year. And so my question 121 00:06:22,720 --> 00:06:24,360 Speaker 2: over the last twenty four hours has been, Okay, well 122 00:06:24,400 --> 00:06:26,320 Speaker 2: we're done with that, so then then what? And I 123 00:06:26,400 --> 00:06:29,159 Speaker 2: keep getting notes in my inbox about how the rally 124 00:06:29,240 --> 00:06:31,120 Speaker 2: is broadening out and then I hear, ooh, we might 125 00:06:31,160 --> 00:06:33,840 Speaker 2: be topping out in tech. Go diversify. So let's get 126 00:06:33,880 --> 00:06:36,280 Speaker 2: someone whose job is to actually understand all this. Grace Lee, 127 00:06:36,360 --> 00:06:40,520 Speaker 2: senior portfolio manager for Columbia thread Needle, joins us. Now, Grace, 128 00:06:40,600 --> 00:06:43,320 Speaker 2: what is the right strategy now that we're done with Nvidia? 129 00:06:43,640 --> 00:06:43,880 Speaker 6: Now? What? 130 00:06:45,560 --> 00:06:48,560 Speaker 8: Well? I think we always have to pay attention to 131 00:06:48,640 --> 00:06:52,080 Speaker 8: in video and I think what in videos earnings showed 132 00:06:52,120 --> 00:06:55,200 Speaker 8: us this week is that the AI theme is still 133 00:06:55,279 --> 00:06:59,280 Speaker 8: alive and well, and so I think we can't ignore that. 134 00:07:00,120 --> 00:07:03,080 Speaker 8: That said, there are plenty of other sectors and I 135 00:07:03,160 --> 00:07:05,839 Speaker 8: think we're starting to see DOT. You know, we've started 136 00:07:05,839 --> 00:07:08,440 Speaker 8: to see it all year. You know, you've seen a 137 00:07:08,600 --> 00:07:14,800 Speaker 8: stealth rally in utilities and banks, especially post elections. You know, 138 00:07:14,880 --> 00:07:18,560 Speaker 8: there has been definitely a people taking a second look 139 00:07:18,600 --> 00:07:22,760 Speaker 8: at financials and other sectors that might have been a 140 00:07:22,840 --> 00:07:26,840 Speaker 8: little bit more ignored during the year because of maybe 141 00:07:26,920 --> 00:07:30,920 Speaker 8: regulatory concerns and things which have certainly eased post elections. 142 00:07:32,600 --> 00:07:34,920 Speaker 5: Grace, what did the election mean to you and your 143 00:07:34,960 --> 00:07:37,400 Speaker 5: team when you woke up that Wednesday morning? Did it 144 00:07:38,120 --> 00:07:41,840 Speaker 5: alter your outlook or how you're thinking about allocation or sectors? 145 00:07:41,960 --> 00:07:42,840 Speaker 5: How did you think about that? 146 00:07:44,160 --> 00:07:46,960 Speaker 8: No, I think mostly it was a huge clearing event 147 00:07:47,120 --> 00:07:51,760 Speaker 8: that it was decisive. It didn't take days or weeks 148 00:07:51,840 --> 00:07:55,680 Speaker 8: to count the votes or anything, and then I think 149 00:07:55,960 --> 00:08:00,120 Speaker 8: that it really is probably more of a positive I 150 00:08:00,240 --> 00:08:04,000 Speaker 8: think for the for the markets. The one takeaway I 151 00:08:04,040 --> 00:08:08,160 Speaker 8: would say is that at this point I probably don't 152 00:08:08,200 --> 00:08:11,960 Speaker 8: want to be more defensive. You know, I think I 153 00:08:12,040 --> 00:08:16,120 Speaker 8: think business leaders, company managements that we've met with since 154 00:08:16,200 --> 00:08:20,400 Speaker 8: the elections, they are more optimistic about what might happen 155 00:08:20,560 --> 00:08:24,520 Speaker 8: under a Trump administration and with the Republican Congress. 156 00:08:25,920 --> 00:08:27,920 Speaker 2: What are your favorite top companies right now? Let's give 157 00:08:27,960 --> 00:08:29,800 Speaker 2: me a couple that really float your boat. 158 00:08:31,040 --> 00:08:35,040 Speaker 8: Well, I think in terms of I would broaden it 159 00:08:35,120 --> 00:08:38,240 Speaker 8: out to maybe some sectors I think, you know, I 160 00:08:38,280 --> 00:08:41,160 Speaker 8: would say utilities is actually an interesting one. As much 161 00:08:41,160 --> 00:08:43,920 Speaker 8: as I say, don't get more defensive, there are some 162 00:08:44,320 --> 00:08:49,680 Speaker 8: some actual secular themes going on in in the utility sector. 163 00:08:49,800 --> 00:08:53,600 Speaker 8: And by by utilities, I'm not talking certainly the power 164 00:08:53,679 --> 00:08:56,319 Speaker 8: producers have done very well this year. But you know, 165 00:08:56,400 --> 00:09:00,400 Speaker 8: when when you think of Plaine Vanilla regulated utilities, I 166 00:09:00,440 --> 00:09:02,640 Speaker 8: would say that if there's ever a time to get 167 00:09:02,720 --> 00:09:07,360 Speaker 8: excited about about these companies, now is that time. And 168 00:09:07,640 --> 00:09:10,720 Speaker 8: you know, these are companies like Excel Energy, Southern Company, 169 00:09:11,640 --> 00:09:14,079 Speaker 8: the ones that maybe your you know, grandmother might have 170 00:09:14,160 --> 00:09:17,600 Speaker 8: been clipping the dividends. But at this point, what we've 171 00:09:17,679 --> 00:09:21,400 Speaker 8: seen is that we've had flat power demand for probably 172 00:09:21,520 --> 00:09:24,679 Speaker 8: over twenty years, and that is now changing for the 173 00:09:24,840 --> 00:09:29,080 Speaker 8: next several years where it's not just AI data centers, 174 00:09:29,120 --> 00:09:34,480 Speaker 8: it's just broader electrification, these crypto mining and resuring. That's 175 00:09:34,520 --> 00:09:36,800 Speaker 8: going to drive a lot more power demand, which means 176 00:09:36,880 --> 00:09:40,240 Speaker 8: that the regulated utilities will have to invest, and that 177 00:09:40,400 --> 00:09:43,199 Speaker 8: means that their earnings growth takes up higher. And we've 178 00:09:43,280 --> 00:09:48,680 Speaker 8: started seeing that in reality this quarter, where you've seen 179 00:09:48,800 --> 00:09:53,360 Speaker 8: some really interesting stock reactions, you know, maybe even double 180 00:09:53,440 --> 00:09:57,000 Speaker 8: digit price gains in a day off of just slightly 181 00:09:57,120 --> 00:09:59,800 Speaker 8: higher long term earnings outlooks. And I think that can 182 00:10:00,000 --> 00:10:03,240 Speaker 8: continue within the c Hey grace. 183 00:10:03,559 --> 00:10:05,760 Speaker 5: As a former banker, when I woke up that Wednesday morning, 184 00:10:05,800 --> 00:10:08,360 Speaker 5: I said, uh, oh, M and A. I think that 185 00:10:08,440 --> 00:10:11,480 Speaker 5: could be back on the front burner here. The regulators 186 00:10:11,520 --> 00:10:13,880 Speaker 5: have been really really tough on M and A or 187 00:10:13,960 --> 00:10:16,960 Speaker 5: list several years. That might change. Does that factor into 188 00:10:17,000 --> 00:10:19,439 Speaker 5: how you think about what sectors to get exposure to. 189 00:10:21,480 --> 00:10:25,840 Speaker 8: I think broadly M and A should pick up. People 190 00:10:25,920 --> 00:10:27,760 Speaker 8: have been waiting for this for a long time. I 191 00:10:27,840 --> 00:10:31,480 Speaker 8: think you know, financials are obviously front and center there. 192 00:10:32,720 --> 00:10:34,760 Speaker 8: You know, we're we're certainly involved in some of the 193 00:10:34,800 --> 00:10:38,800 Speaker 8: capital market stocks, some of the alternative investment managers which 194 00:10:38,840 --> 00:10:43,439 Speaker 8: we think we will will certainly see benefits there. But 195 00:10:44,160 --> 00:10:47,319 Speaker 8: you know, I think broadly and possibly you know, we 196 00:10:47,400 --> 00:10:50,200 Speaker 8: don't traffic in small caps a ton, but I think 197 00:10:50,280 --> 00:10:53,480 Speaker 8: some of the smaller mid cap companies might might also 198 00:10:53,600 --> 00:10:56,719 Speaker 8: be a little bit more interesting in this environment as 199 00:10:56,800 --> 00:10:57,800 Speaker 8: potential targets. 200 00:10:58,280 --> 00:11:02,120 Speaker 2: Yeah, profitable small camp that's really been out performing. All right, 201 00:11:02,120 --> 00:11:04,160 Speaker 2: thanks so much, Grace, really appreciate it. Grace Lee, Senior 202 00:11:04,200 --> 00:11:07,040 Speaker 2: portfolio manager for Columbia Thread Needle. Joining us. 203 00:11:08,640 --> 00:11:12,480 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 204 00:11:12,600 --> 00:11:15,520 Speaker 1: weekdays at ten am Eastern on applecar. 205 00:11:15,120 --> 00:11:17,880 Speaker 7: Play and Android Auto with the Bloomberg Business app. 206 00:11:18,000 --> 00:11:20,840 Speaker 1: You can also listen live on Amazon Alexa from our 207 00:11:20,880 --> 00:11:25,240 Speaker 1: flagship New York station. Just say Alexa play Bloomberg eleven thirty. 208 00:11:26,280 --> 00:11:30,000 Speaker 2: Another story that we're following today concerns oil and JP 209 00:11:30,200 --> 00:11:33,319 Speaker 2: Morgan and Iran. So apparently the US Treasury Department is 210 00:11:33,360 --> 00:11:36,640 Speaker 2: examining JP Morgan's relationship with a hedge fund that is 211 00:11:36,679 --> 00:11:39,480 Speaker 2: said to be part of a network that's overseen by 212 00:11:39,520 --> 00:11:43,160 Speaker 2: Iranian oil trader hosting Chamkani. We want to understand sort 213 00:11:43,200 --> 00:11:46,080 Speaker 2: of more on this. What might this violate in terms 214 00:11:46,120 --> 00:11:47,960 Speaker 2: of sanctions or not. So we're here to break us 215 00:11:47,960 --> 00:11:51,200 Speaker 2: down for us as Elliott Stein Bloomberg intelligence litigation analyst. 216 00:11:51,400 --> 00:11:53,040 Speaker 2: Can you just give us the facts first? 217 00:11:53,800 --> 00:11:54,000 Speaker 3: Yeah? 218 00:11:54,160 --> 00:11:57,280 Speaker 9: So, I mean the investigations early, the reporting is early. 219 00:11:57,600 --> 00:12:00,680 Speaker 9: A lot of unknowns, both known and unknown at this point. 220 00:12:01,240 --> 00:12:05,400 Speaker 9: But it sounds like the Treasury Department is investigating JP 221 00:12:05,559 --> 00:12:09,480 Speaker 9: Morgan in relation to its connection to this hedge fund 222 00:12:09,520 --> 00:12:12,800 Speaker 9: that's based in London and Dubai and the hedge funds 223 00:12:12,840 --> 00:12:16,000 Speaker 9: connection to an oil trader, And it sounds like the 224 00:12:16,120 --> 00:12:20,079 Speaker 9: overall investigation is focused on the oil trader, but the 225 00:12:20,160 --> 00:12:22,920 Speaker 9: Treasury departments also looking at JP Morgan to make sure 226 00:12:23,000 --> 00:12:25,360 Speaker 9: that it followed its you know, due diligence and did 227 00:12:25,400 --> 00:12:28,800 Speaker 9: its KYC and know your customer and AML compliance processes. 228 00:12:29,440 --> 00:12:31,320 Speaker 5: And I guess I'm just looking at the Bloomberg reporting. 229 00:12:33,120 --> 00:12:35,800 Speaker 5: I guess folks there say JP Morgan feels like they 230 00:12:35,840 --> 00:12:39,040 Speaker 5: don't need to do anything here because neither the Shimkhani 231 00:12:39,120 --> 00:12:41,960 Speaker 5: guy nor the company appear in any sanctions list. 232 00:12:42,080 --> 00:12:44,679 Speaker 3: I guess, right, yeah, and this may be you know, 233 00:12:44,800 --> 00:12:46,920 Speaker 3: this may be a nothing burger. There may be nothing there. 234 00:12:47,800 --> 00:12:50,880 Speaker 9: And you know, best case scenario, or one possible scenario 235 00:12:50,880 --> 00:12:54,360 Speaker 9: where JP Morgan has no exposure, is that maybe it 236 00:12:54,480 --> 00:12:58,640 Speaker 9: did all its due diligence and it was misled by 237 00:12:59,160 --> 00:13:01,240 Speaker 9: you know, the the companies that was doing its due 238 00:13:01,240 --> 00:13:04,440 Speaker 9: diligence on That's just one possibility. But worst case scenario, 239 00:13:05,000 --> 00:13:08,000 Speaker 9: it didn't do it's due diligence or it ignored red 240 00:13:08,040 --> 00:13:11,080 Speaker 9: flags and we've seen, you know, recently with TD Bank 241 00:13:11,440 --> 00:13:12,439 Speaker 9: what that can amount to. 242 00:13:12,720 --> 00:13:15,880 Speaker 2: So if this oil trader did have a relationship with 243 00:13:16,000 --> 00:13:19,920 Speaker 2: this individual from Iran, what does that potentially violate? What 244 00:13:20,000 --> 00:13:22,160 Speaker 2: are the sanctions and the rules currently that would make 245 00:13:22,200 --> 00:13:23,800 Speaker 2: that a problem, right, So, you. 246 00:13:23,840 --> 00:13:28,439 Speaker 9: Know, banks should not be doing business with companies that 247 00:13:28,679 --> 00:13:33,599 Speaker 9: are under sanctions or on you know, special lists, you know, 248 00:13:33,800 --> 00:13:36,839 Speaker 9: And so it's unclear what the connection is though to 249 00:13:37,200 --> 00:13:38,200 Speaker 9: this oil trader. 250 00:13:39,160 --> 00:13:41,720 Speaker 3: Apparently he is the son of someone who was. 251 00:13:41,760 --> 00:13:44,959 Speaker 9: In the Ayatolla's like inner circle, so there may be 252 00:13:45,120 --> 00:13:47,880 Speaker 9: some connections. But we've seen in the past that banks 253 00:13:47,920 --> 00:13:51,120 Speaker 9: have paid billions of dollars for doing transactions with the 254 00:13:51,200 --> 00:13:55,320 Speaker 9: Iranian government or other Iranian entities that are on sanctions lists. 255 00:13:55,640 --> 00:13:58,480 Speaker 3: So it can be very costly. But it's not clear 256 00:13:58,559 --> 00:14:00,840 Speaker 3: that the investigation is even focused on that, and may 257 00:14:00,920 --> 00:14:03,120 Speaker 3: be sort of just to make sure that JP Morgan 258 00:14:03,320 --> 00:14:04,880 Speaker 3: was doing its due diligence. 259 00:14:05,200 --> 00:14:08,079 Speaker 5: And doing through that. The training here at Bloomberg about 260 00:14:08,120 --> 00:14:11,400 Speaker 5: this type of issues, yeah, the type of training that 261 00:14:11,840 --> 00:14:14,319 Speaker 5: the same thing we receive and I'm sure everybody across 262 00:14:14,400 --> 00:14:18,319 Speaker 5: the industry, to various degrees receives about Hey, if you're 263 00:14:18,400 --> 00:14:20,880 Speaker 5: doing business with somebody that may or may not be 264 00:14:20,960 --> 00:14:24,240 Speaker 5: on a list, just stop, call your boss, call complaints, 265 00:14:24,480 --> 00:14:26,520 Speaker 5: see what the gig is before you move forward. 266 00:14:26,520 --> 00:14:29,160 Speaker 2: Well, it sounds like this could be like a third derivative. 267 00:14:29,560 --> 00:14:31,760 Speaker 9: Exactly, And that's why there's a lot of unknowns here. 268 00:14:32,040 --> 00:14:36,120 Speaker 9: The bank may have no exposure, but anytime you're talking 269 00:14:36,120 --> 00:14:40,080 Speaker 9: about sanctions on Iran and you know banks doing transactions 270 00:14:40,680 --> 00:14:44,280 Speaker 9: you know indirectly as well, you know, your eyebrows get 271 00:14:44,360 --> 00:14:46,520 Speaker 9: raised and banks have paid. 272 00:14:46,360 --> 00:14:48,520 Speaker 3: A lot of money in the past for failures related 273 00:14:48,560 --> 00:14:48,720 Speaker 3: to this. 274 00:14:48,880 --> 00:14:51,520 Speaker 2: Do we feel that sanctions could get more strenuous under 275 00:14:51,600 --> 00:14:53,360 Speaker 2: President Trump? Like, what are you thinking about? 276 00:14:54,680 --> 00:14:57,560 Speaker 3: Certainly possible, right I mean, yeah, I would expect that. 277 00:14:57,760 --> 00:14:59,520 Speaker 5: I would expect it, all right, So I'm going to 278 00:14:59,520 --> 00:15:01,760 Speaker 5: a JP Moore stocks up one percent today, up forty 279 00:15:01,760 --> 00:15:04,200 Speaker 5: five percent year to date, so I'm assuming the market's 280 00:15:04,240 --> 00:15:06,680 Speaker 5: discounting this is a non risk issue. How about other 281 00:15:06,760 --> 00:15:09,080 Speaker 5: litigation that your work? What else are you working on? 282 00:15:09,120 --> 00:15:11,880 Speaker 5: Because you do the litigation that companies have the deal 283 00:15:11,960 --> 00:15:13,680 Speaker 5: with that can move stocks. 284 00:15:13,560 --> 00:15:17,560 Speaker 9: Absolutely and actually in this arena, there are several other 285 00:15:17,640 --> 00:15:21,000 Speaker 9: banks that are under investigation for either AML violations or 286 00:15:21,080 --> 00:15:26,800 Speaker 9: potentially sanctions violations. UBS is being investigated with in connection 287 00:15:26,920 --> 00:15:29,440 Speaker 9: with clients that have took over from Credit Sue who 288 00:15:29,680 --> 00:15:33,400 Speaker 9: may be in violation of sanctions on Russia. There's a 289 00:15:33,440 --> 00:15:37,400 Speaker 9: swedest Sweat Bank that has been under investigation for AML 290 00:15:37,920 --> 00:15:40,440 Speaker 9: violations for years now, so I'm waiting for a penalty there. 291 00:15:40,520 --> 00:15:44,240 Speaker 9: There's a Turkish bank, Hawkbank, that was indicted by the 292 00:15:44,320 --> 00:15:46,880 Speaker 9: US government for violating sanctions on Irun. 293 00:15:46,960 --> 00:15:49,040 Speaker 3: So that's one area I'm looking at. 294 00:15:49,440 --> 00:15:52,280 Speaker 9: Another big area right now is all these rules and 295 00:15:52,360 --> 00:15:55,880 Speaker 9: regulations that the SEC and other regulators have put into 296 00:15:55,920 --> 00:15:58,680 Speaker 9: place under the Biden administration. There's a lot of lawsuits 297 00:15:58,720 --> 00:16:00,120 Speaker 9: over them, and so we're waiting to see what is 298 00:16:00,120 --> 00:16:02,120 Speaker 9: going to happen with the rules and with the lawsuits. 299 00:16:02,840 --> 00:16:05,320 Speaker 2: What else would a Trump victory mean for your world? 300 00:16:06,200 --> 00:16:09,400 Speaker 9: Right, So, in connection with these rules and regulations that 301 00:16:09,760 --> 00:16:14,200 Speaker 9: the SEC has promulgated during the Biden administration and the 302 00:16:14,280 --> 00:16:17,120 Speaker 9: CFPB as well, we're expecting a lot of the rules 303 00:16:17,160 --> 00:16:20,680 Speaker 9: and regulations to maybe be paused in terms of enforcing them, 304 00:16:21,000 --> 00:16:23,760 Speaker 9: and then the regulators will probably go back and revisit 305 00:16:23,840 --> 00:16:27,440 Speaker 9: the rules, but that takes a while. I'm also you know, 306 00:16:27,720 --> 00:16:31,920 Speaker 9: I'm attuned to the courts as well, and I'm particularly 307 00:16:33,240 --> 00:16:34,640 Speaker 9: interested in seeing whether. 308 00:16:34,800 --> 00:16:36,920 Speaker 3: The two oldest justices on the Supreme Court. 309 00:16:36,760 --> 00:16:40,160 Speaker 9: Clarence Thomas and Sam Alito, retire, probably at some point 310 00:16:40,440 --> 00:16:43,200 Speaker 9: during this next Trump administrator life, in which case he 311 00:16:43,240 --> 00:16:47,000 Speaker 9: would name the replacements and you'll have a conservative majority 312 00:16:47,120 --> 00:16:49,240 Speaker 9: for at least another generation on the Supreme Court. 313 00:16:49,360 --> 00:16:49,760 Speaker 7: Interesting. 314 00:16:49,800 --> 00:16:53,240 Speaker 5: Wow, because you started off fine going to Stanford, then 315 00:16:53,280 --> 00:16:56,920 Speaker 5: you went to get a law degree. It all turns 316 00:16:56,960 --> 00:16:58,280 Speaker 5: south Man. What were you thinking? 317 00:17:00,080 --> 00:17:03,200 Speaker 3: Have you marked your calendar for the Stanford Duke basketball game? 318 00:17:03,280 --> 00:17:05,400 Speaker 5: No, because we're now in the same conference, right, Yeah, 319 00:17:05,520 --> 00:17:05,920 Speaker 5: when is that? 320 00:17:06,560 --> 00:17:08,280 Speaker 3: I don't have a car, but I think I think 321 00:17:08,280 --> 00:17:09,520 Speaker 3: it's in January, maybe February. 322 00:17:09,560 --> 00:17:11,240 Speaker 5: I want to check it outre Stanford is in the 323 00:17:11,280 --> 00:17:12,680 Speaker 5: Atlantic Coast Conference. That makes sense. 324 00:17:12,800 --> 00:17:13,879 Speaker 3: Yeah, big game this weekend. 325 00:17:13,960 --> 00:17:15,760 Speaker 5: My Duke Field hockey team had a little problem getting 326 00:17:15,760 --> 00:17:17,159 Speaker 5: out to the Bay Area for their games against it 327 00:17:17,280 --> 00:17:20,520 Speaker 5: because you have to Drham, you have to transfer and connect, 328 00:17:20,720 --> 00:17:23,480 Speaker 5: and I'm like, why are my kids going out to 329 00:17:23,600 --> 00:17:26,440 Speaker 5: San Francisco for It's just the whole thing's a mess. 330 00:17:26,520 --> 00:17:29,879 Speaker 5: Elliot Stein Bloomberg Intelligence litigation analysts joining us here in 331 00:17:29,920 --> 00:17:31,879 Speaker 5: our Bloomberg Interactive Brokers Studio. 332 00:17:33,640 --> 00:17:37,480 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 333 00:17:37,600 --> 00:17:40,520 Speaker 1: weekdays at ten am Eastern on applecar. 334 00:17:40,160 --> 00:17:42,880 Speaker 7: Play and Android Auto with the Bloomberg Business app. 335 00:17:43,040 --> 00:17:45,840 Speaker 1: You can also listen live on Amazon Alexa from our 336 00:17:45,880 --> 00:17:50,240 Speaker 1: flagship New York station Just say Alexa playing Bloomberg eleven thirty. 337 00:17:51,480 --> 00:17:53,200 Speaker 2: Happy for Friday. We made it to the end of 338 00:17:53,240 --> 00:17:55,119 Speaker 2: the week. I'm Alex d alongside Paul swe Need. This 339 00:17:55,160 --> 00:17:57,320 Speaker 2: is Bloomberg Intelligence Radio. We bring you all the top 340 00:17:57,400 --> 00:17:59,840 Speaker 2: news and business, economics and finance through our lens of 341 00:17:59,840 --> 00:18:03,159 Speaker 2: our Bloomberg Intelligence folks. We also tap an amazing network 342 00:18:03,200 --> 00:18:06,119 Speaker 2: of resources outside of Bloomberg Intelligence, and we're going to 343 00:18:06,160 --> 00:18:09,080 Speaker 2: tap one right now. Jessica Kriegel is chief strategy Officer 344 00:18:09,200 --> 00:18:12,960 Speaker 2: of Workforce and Labor at Culture Partner. She joins US 345 00:18:12,960 --> 00:18:16,680 Speaker 2: now from Sacramento, California. So the headline from this week 346 00:18:16,760 --> 00:18:19,040 Speaker 2: that we didn't really get to digest as much was 347 00:18:19,280 --> 00:18:23,119 Speaker 2: Elon Musk and Vivek Ramaswami outlining a plan for large 348 00:18:23,240 --> 00:18:26,480 Speaker 2: scale firings of the federal workforce, in part, guys, get 349 00:18:26,520 --> 00:18:28,400 Speaker 2: your butt backs in the office five days a week. 350 00:18:28,480 --> 00:18:29,719 Speaker 2: You don't want to do it, and then you're going 351 00:18:29,760 --> 00:18:33,840 Speaker 2: to quit. Is this realistic? What's your take on something 352 00:18:33,960 --> 00:18:34,119 Speaker 2: like this? 353 00:18:35,840 --> 00:18:39,160 Speaker 10: Well, they argue that it is absolutely realistic, and you've 354 00:18:39,200 --> 00:18:43,720 Speaker 10: already seen a precedent set in the corporate world where 355 00:18:43,840 --> 00:18:47,000 Speaker 10: people are forcing employees back into the office five days 356 00:18:47,000 --> 00:18:49,640 Speaker 10: a week. What is a little bit different or maybe 357 00:18:49,760 --> 00:18:52,400 Speaker 10: even refreshing, you could argue, is that they are being 358 00:18:52,760 --> 00:18:56,480 Speaker 10: straightforward about the fact that they anticipate by forcing people 359 00:18:56,560 --> 00:18:59,040 Speaker 10: back into the office five days a week, that people 360 00:18:59,080 --> 00:19:02,000 Speaker 10: will quit, and they welcome that. I think that's probably 361 00:19:02,119 --> 00:19:04,520 Speaker 10: true for a lot of CEOs who make that decision 362 00:19:04,680 --> 00:19:09,080 Speaker 10: because they know their workforce values flexibility, and yet they're 363 00:19:09,160 --> 00:19:12,119 Speaker 10: forcing them to go back into the office. So they 364 00:19:12,160 --> 00:19:15,400 Speaker 10: are being in some ways at least transparent that there 365 00:19:15,560 --> 00:19:19,840 Speaker 10: is an alternative motivation for forcing people back into the office. 366 00:19:19,960 --> 00:19:22,920 Speaker 10: It's not about quote unquote culture, it's not about quote 367 00:19:22,960 --> 00:19:26,280 Speaker 10: unquote collaboration. It's really about we want to reduce the workforce, 368 00:19:26,320 --> 00:19:27,840 Speaker 10: and this is one of the many tools that we 369 00:19:27,880 --> 00:19:28,320 Speaker 10: will use. 370 00:19:29,359 --> 00:19:32,400 Speaker 5: So I guess in the federal government again, Elon musk 371 00:19:32,480 --> 00:19:35,840 Speaker 5: vivek Ramaswani, what do you think they could do? 372 00:19:36,200 --> 00:19:36,720 Speaker 3: Should do? 373 00:19:36,960 --> 00:19:41,560 Speaker 5: When you think about I don't know, waste inefficiency bureaucracy. 374 00:19:42,320 --> 00:19:44,560 Speaker 5: Is there a preferred way to kind of go about 375 00:19:44,600 --> 00:19:47,320 Speaker 5: this or you just take a you know, a clever 376 00:19:47,480 --> 00:19:48,760 Speaker 5: and lop off ten percent? 377 00:19:50,760 --> 00:19:51,320 Speaker 3: Well, should do? 378 00:19:51,520 --> 00:19:53,760 Speaker 10: Can? I'll leave that up to the political analysts. But 379 00:19:53,840 --> 00:19:57,920 Speaker 10: what I will say is they're arguing that the bureaucracy 380 00:19:58,160 --> 00:20:00,840 Speaker 10: is wildly inefficient, and they're not wrong because if you 381 00:20:00,960 --> 00:20:05,040 Speaker 10: look at accountability in bureaucracies as compared to the free markets, 382 00:20:05,119 --> 00:20:09,280 Speaker 10: there is less accountability, right, There's less consequences for failure 383 00:20:09,400 --> 00:20:14,040 Speaker 10: in a bureaucracy. There's less competition, and so accountability necessarily 384 00:20:14,160 --> 00:20:16,320 Speaker 10: goes down. And they're saying we need to address that. 385 00:20:16,920 --> 00:20:20,359 Speaker 10: It's not necessarily a problem the size of the federal government. 386 00:20:20,440 --> 00:20:23,520 Speaker 10: The federal government is the largest employer in America with 387 00:20:23,640 --> 00:20:26,919 Speaker 10: three million employees. But size isn't in and of itself 388 00:20:27,000 --> 00:20:29,760 Speaker 10: the problem, right Look at Amazon. Amazon has one point 389 00:20:29,840 --> 00:20:32,720 Speaker 10: five million employees, and they could deliver a band book 390 00:20:32,760 --> 00:20:35,280 Speaker 10: to your doorstep in the next eight hours. Right. The 391 00:20:35,400 --> 00:20:37,879 Speaker 10: problem is the lack of accountability, and that is in 392 00:20:38,000 --> 00:20:41,159 Speaker 10: particular what they are wanting to address with. Yes, it 393 00:20:41,240 --> 00:20:44,399 Speaker 10: sounds like a cleaver, Uh, how do they do that if? 394 00:20:44,440 --> 00:20:46,760 Speaker 2: Okay, so let's say that they didn't just do the clever. 395 00:20:47,480 --> 00:20:51,240 Speaker 2: How do you transform culture and help productivity in a 396 00:20:51,280 --> 00:20:52,080 Speaker 2: government agency. 397 00:20:54,480 --> 00:20:57,720 Speaker 10: Well, what we know from helping companies transform culture is 398 00:20:57,760 --> 00:21:00,119 Speaker 10: that culture does not go down without a fight. So 399 00:21:00,240 --> 00:21:04,879 Speaker 10: this is going to be incredibly disruptive. And here's the 400 00:21:04,920 --> 00:21:08,600 Speaker 10: pros and cons of disruption. Innovation comes from disruption. You 401 00:21:08,720 --> 00:21:12,720 Speaker 10: cannot have innovation without disruption. But disruption does not in 402 00:21:12,800 --> 00:21:16,359 Speaker 10: and of itself create innovation, right, Disruption can simply be 403 00:21:16,560 --> 00:21:20,240 Speaker 10: catastrophic to culture. And so what they are doing is 404 00:21:20,320 --> 00:21:23,600 Speaker 10: they are creating an opportunity, but they are also creating 405 00:21:23,800 --> 00:21:27,320 Speaker 10: a potential massive headache. And I do believe from the 406 00:21:27,400 --> 00:21:30,359 Speaker 10: federal workers and also from the public, there will be 407 00:21:31,040 --> 00:21:34,840 Speaker 10: resistance to change. There's always resistance to massive change like this, 408 00:21:35,080 --> 00:21:38,040 Speaker 10: And what we've also seen is the best things come 409 00:21:38,320 --> 00:21:41,920 Speaker 10: from the organizations that embrace change. So the extent to 410 00:21:42,000 --> 00:21:44,320 Speaker 10: which the federal workers and the public are able to 411 00:21:44,400 --> 00:21:46,960 Speaker 10: embrace this change will probably have a lot to do 412 00:21:47,200 --> 00:21:49,359 Speaker 10: with how well this is going to end up. 413 00:21:50,560 --> 00:21:52,080 Speaker 5: I feel like I have to ask us for a 414 00:21:52,119 --> 00:21:53,960 Speaker 5: while there this was a big issue for me, but 415 00:21:54,640 --> 00:21:57,720 Speaker 5: where is the US private sector economy in terms of 416 00:21:58,840 --> 00:22:00,840 Speaker 5: work from home, hybrid that type of thing. Have we 417 00:22:00,960 --> 00:22:04,760 Speaker 5: settled into a new normal or are the sands still 418 00:22:04,800 --> 00:22:05,400 Speaker 5: shifting there? 419 00:22:06,680 --> 00:22:11,520 Speaker 10: They're still shifting, so we see various plateaus in what 420 00:22:11,760 --> 00:22:15,080 Speaker 10: normal is year over year. I believe I'm coming out 421 00:22:15,160 --> 00:22:17,640 Speaker 10: soon with an article on the workplace trends of twenty 422 00:22:17,680 --> 00:22:20,119 Speaker 10: twenty five. The year twenty twenty five is going to 423 00:22:20,160 --> 00:22:22,159 Speaker 10: be the year of forcing people back into the office 424 00:22:22,280 --> 00:22:24,960 Speaker 10: five days a week. Usually what happens is there's a 425 00:22:25,040 --> 00:22:28,840 Speaker 10: lot of press about one big deal CEO forcing people 426 00:22:28,920 --> 00:22:31,239 Speaker 10: back into the office, which has already happened, and now 427 00:22:31,280 --> 00:22:34,480 Speaker 10: it's happening again with this announcement from Bavek and elon. 428 00:22:34,600 --> 00:22:37,880 Speaker 10: And so next year that empowers other leaders who wish 429 00:22:37,960 --> 00:22:40,200 Speaker 10: their employees were back in the office to get back 430 00:22:40,240 --> 00:22:42,120 Speaker 10: into the office. And you're going to continue to see 431 00:22:42,440 --> 00:22:44,800 Speaker 10: a push. We had plateaued it around three days a week, 432 00:22:44,880 --> 00:22:47,639 Speaker 10: but it's going to go even more back into the 433 00:22:47,720 --> 00:22:48,520 Speaker 10: office next year. 434 00:22:48,680 --> 00:22:50,840 Speaker 2: Okay that this means then that my commute in on 435 00:22:50,960 --> 00:22:53,440 Speaker 2: Fridays and Mondays now will be more trafficked. I don't 436 00:22:53,480 --> 00:22:55,240 Speaker 2: love that. I don't love that for me, Like we're 437 00:22:55,240 --> 00:22:56,919 Speaker 2: already here five days a week, when I've been here 438 00:22:56,920 --> 00:22:58,600 Speaker 2: five days a week since June and twenty twenty, so 439 00:22:58,680 --> 00:23:01,040 Speaker 2: it's like, yeah, whatever, but don't make traffic back. That's 440 00:23:01,040 --> 00:23:03,560 Speaker 2: a bummer. Exactly all right, We really appreciate it. Thank 441 00:23:03,600 --> 00:23:06,639 Speaker 2: you so much for all your insight on this. Jessica 442 00:23:06,720 --> 00:23:10,119 Speaker 2: Kriegel as Chief Strategy Officer of Workforce and Labor for 443 00:23:10,480 --> 00:23:13,640 Speaker 2: Culture Partners, joining us on that, speaking of I don't 444 00:23:13,680 --> 00:23:15,080 Speaker 2: know nothing in culture. 445 00:23:14,760 --> 00:23:17,679 Speaker 5: But it's interesting, Like I talked to my twenty eight 446 00:23:17,720 --> 00:23:20,960 Speaker 5: year old daughter who has only worked really during the 447 00:23:21,119 --> 00:23:24,280 Speaker 5: started working kind of in a pandemic era. It's not 448 00:23:24,400 --> 00:23:27,240 Speaker 5: even I guess they can reprogram, but for a while there. 449 00:23:27,240 --> 00:23:30,440 Speaker 5: It wasn't even in her DNA to do that, to 450 00:23:30,520 --> 00:23:33,040 Speaker 5: come in five days a week, I mean, she feels crazy. Yeah. 451 00:23:33,080 --> 00:23:35,919 Speaker 5: So I think they're getting reprogrammed back because they're now 452 00:23:35,960 --> 00:23:37,840 Speaker 5: in four days a week at her employer, which will 453 00:23:37,920 --> 00:23:40,280 Speaker 5: likely go to five. But for a while, it just 454 00:23:40,400 --> 00:23:42,080 Speaker 5: wasn't in her DNA to think about that. 455 00:23:42,440 --> 00:23:45,080 Speaker 2: I mean, I understand having a flex day here and there, like, hey, 456 00:23:45,160 --> 00:23:47,200 Speaker 2: my kids said, I got to work from home. Okay, great, 457 00:23:47,440 --> 00:23:50,439 Speaker 2: but like that's that feels like an exceptions, right. 458 00:23:50,359 --> 00:23:50,600 Speaker 7: It does. 459 00:23:50,680 --> 00:23:54,640 Speaker 5: And I think Jessica was saying, it's slowly been going 460 00:23:54,680 --> 00:23:56,280 Speaker 5: back to work from home, but I mean work from 461 00:23:56,400 --> 00:23:58,680 Speaker 5: the office. But we'll see how that plays out. I 462 00:23:59,160 --> 00:24:02,080 Speaker 5: still see a lot of vacant commercial space here in 463 00:24:02,119 --> 00:24:03,040 Speaker 5: a city, oh my god. 464 00:24:03,160 --> 00:24:05,520 Speaker 2: Yeah, although across the street on Lex it looks like 465 00:24:05,560 --> 00:24:09,440 Speaker 2: they're doing some construction on that massive retail space. Yes, anyway, 466 00:24:09,640 --> 00:24:10,720 Speaker 2: that's just food for thought. 467 00:24:12,200 --> 00:24:16,040 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 468 00:24:16,160 --> 00:24:19,080 Speaker 1: weekdays at ten am Eastern on applecar. 469 00:24:18,680 --> 00:24:21,440 Speaker 7: Play and Android Auto with the Bloomberg Business app. 470 00:24:21,600 --> 00:24:24,399 Speaker 1: You can also listen live on Amazon Alexa from our 471 00:24:24,440 --> 00:24:28,800 Speaker 1: flagship New York station Just Say Alexa Play Bloomberg eleven thirty. 472 00:24:29,920 --> 00:24:31,480 Speaker 2: All right, let's get back to the market here and 473 00:24:31,560 --> 00:24:34,359 Speaker 2: sort of what's next. I'm getting all the research about 474 00:24:34,400 --> 00:24:37,880 Speaker 2: twenty twenty five and what to expect. Christina Hooper, chief 475 00:24:37,920 --> 00:24:41,120 Speaker 2: Global market strategist at Invesco, joins US now, I feel 476 00:24:41,119 --> 00:24:43,280 Speaker 2: like every strategist is now sixty five hundred and sixty 477 00:24:43,280 --> 00:24:45,359 Speaker 2: six hundred on the S ANDP for next year? Is 478 00:24:45,400 --> 00:24:47,239 Speaker 2: this the right metric for us to be looking at 479 00:24:47,320 --> 00:24:50,639 Speaker 2: right now? So, Alex, we. 480 00:24:50,800 --> 00:24:54,239 Speaker 11: Actually don't give a set target, but I do think 481 00:24:54,359 --> 00:24:58,399 Speaker 11: directionally it's appropriate to assume that we see stocks go 482 00:24:58,640 --> 00:25:01,240 Speaker 11: up next year. I think we shouldn't just be looking 483 00:25:01,280 --> 00:25:02,920 Speaker 11: at the S and P five hundred. We should be 484 00:25:03,040 --> 00:25:06,000 Speaker 11: looking at markets outside the US, and I think directionally 485 00:25:06,400 --> 00:25:08,760 Speaker 11: they're likely to move higher as well. And I actually 486 00:25:08,840 --> 00:25:13,440 Speaker 11: think we could see UK equities, for example, outperform US 487 00:25:13,560 --> 00:25:16,360 Speaker 11: equities next year. I think there are opportunities in emerging 488 00:25:16,520 --> 00:25:20,520 Speaker 11: markets equities, so there is a lot more out there 489 00:25:20,800 --> 00:25:24,120 Speaker 11: than just focusing on US large cap stocks. 490 00:25:24,280 --> 00:25:26,960 Speaker 2: I feel sacriligious, Christina, I thought it was the whole 491 00:25:27,040 --> 00:25:31,160 Speaker 2: US exceptionalism kind of thing. Well, I don't know if. 492 00:25:31,040 --> 00:25:34,520 Speaker 11: It's necessarily US exceptionalism. We had a few things going 493 00:25:34,560 --> 00:25:36,840 Speaker 11: in our favor over the last few years that made 494 00:25:36,880 --> 00:25:40,600 Speaker 11: the US economy more resilient. Namely, I think first and 495 00:25:40,680 --> 00:25:44,560 Speaker 11: foremost would be long term fixed rate mortgages. That meant 496 00:25:44,640 --> 00:25:48,920 Speaker 11: the transmission mechanism for monetary policy wasn't as strong in 497 00:25:49,080 --> 00:25:52,320 Speaker 11: the US. We just didn't have as negative an impact 498 00:25:52,359 --> 00:25:56,040 Speaker 11: from aggressive tightening as some other Western developed economies, and 499 00:25:56,119 --> 00:25:59,080 Speaker 11: that certainly was helpful. The other key factor I think 500 00:25:59,400 --> 00:26:02,480 Speaker 11: was the amount of fiscal stimulus thrown at the US 501 00:26:02,560 --> 00:26:05,960 Speaker 11: economy by the federal government. A lot of governments put 502 00:26:06,040 --> 00:26:08,800 Speaker 11: stimulus into their economies, but not at the level that 503 00:26:08,880 --> 00:26:09,479 Speaker 11: the US did. 504 00:26:10,560 --> 00:26:14,440 Speaker 5: Christina, When you woke up two weeks ago Wednesday and 505 00:26:14,600 --> 00:26:17,400 Speaker 5: we've got you know, we saw the new presidential election 506 00:26:17,520 --> 00:26:19,879 Speaker 5: results and now we know that Congress is firmly in 507 00:26:20,119 --> 00:26:22,600 Speaker 5: the hands of Republicans. Has that changed kind of how 508 00:26:22,640 --> 00:26:26,600 Speaker 5: you guys at investco think about asset allocation, how much 509 00:26:26,720 --> 00:26:28,960 Speaker 5: risk you want to take? Did the elections change anything 510 00:26:29,000 --> 00:26:29,360 Speaker 5: for you guys? 511 00:26:30,920 --> 00:26:33,760 Speaker 11: Not very much, because we think it's far more important. 512 00:26:35,160 --> 00:26:38,639 Speaker 11: The more important factor is who is sitting at the 513 00:26:38,800 --> 00:26:41,040 Speaker 11: helm of the Fed than who was sitting in the 514 00:26:41,080 --> 00:26:44,400 Speaker 11: White House. I think the reality is that monetary policy 515 00:26:44,640 --> 00:26:48,200 Speaker 11: matters more for markets. Now that doesn't mean that policy 516 00:26:48,400 --> 00:26:51,040 Speaker 11: coming out of the White House has no impact. We 517 00:26:51,119 --> 00:26:54,840 Speaker 11: think of it as something akin to swing factors. We 518 00:26:55,000 --> 00:26:57,920 Speaker 11: have to be concerned about tariffs that certainly the first 519 00:26:57,960 --> 00:27:02,480 Speaker 11: time around created more volatility and created some selloffs for 520 00:27:02,880 --> 00:27:06,959 Speaker 11: the stock market. We also have to think about, for example, 521 00:27:07,000 --> 00:27:10,480 Speaker 11: immigration policy and the potential for it to impact inflation. 522 00:27:11,440 --> 00:27:16,920 Speaker 11: But those are really eclipsed by monetary policy and by 523 00:27:17,200 --> 00:27:20,360 Speaker 11: all the factors that have gone into the US economy 524 00:27:20,480 --> 00:27:23,760 Speaker 11: thus far that have enabled it to have essentially a 525 00:27:23,880 --> 00:27:27,400 Speaker 11: soft landing and what I think prepares us for reacceleration 526 00:27:27,600 --> 00:27:27,959 Speaker 11: next year. 527 00:27:28,960 --> 00:27:32,240 Speaker 2: When we take a look at the central bank cutting cycle, 528 00:27:32,359 --> 00:27:35,000 Speaker 2: let's leave Japan out of it. Do you need to 529 00:27:35,080 --> 00:27:37,560 Speaker 2: think about the areas where you might see more cuts? 530 00:27:37,680 --> 00:27:40,200 Speaker 2: So I'm just looking at the data from Europe in 531 00:27:40,320 --> 00:27:43,199 Speaker 2: terms of the pmis, they were terrible. Now we're talking about, oh, 532 00:27:43,240 --> 00:27:45,359 Speaker 2: we're going to see a fifty basis point cut. Is 533 00:27:45,400 --> 00:27:47,000 Speaker 2: that a good indication of kind of where to go 534 00:27:47,240 --> 00:27:48,480 Speaker 2: by how much the bank can cut? 535 00:27:50,359 --> 00:27:50,479 Speaker 6: Well? 536 00:27:50,560 --> 00:27:54,280 Speaker 11: I certainly think that is one helpful factor to consider. 537 00:27:55,280 --> 00:27:58,399 Speaker 11: I think it certainly matters in terms of currencies, and 538 00:28:00,119 --> 00:28:04,560 Speaker 11: I do think that the more easing that comes, certainly 539 00:28:04,680 --> 00:28:08,680 Speaker 11: that can be a powerful catalyst for economies. We also 540 00:28:08,800 --> 00:28:13,080 Speaker 11: have to recognize that part of the equation for investing 541 00:28:13,600 --> 00:28:16,000 Speaker 11: is how much negative sentiment is priced in, and so 542 00:28:16,160 --> 00:28:19,800 Speaker 11: when we do have a scenario where there's some negative 543 00:28:19,880 --> 00:28:23,920 Speaker 11: data coming out, there is the potential for positive surprise, 544 00:28:24,119 --> 00:28:27,919 Speaker 11: especially if we have significant easing. So I am excited 545 00:28:27,920 --> 00:28:31,200 Speaker 11: about European equities. I also think the valuations are attractive. 546 00:28:31,520 --> 00:28:35,440 Speaker 11: I think dividend yields are solid, So that's certainly. Those 547 00:28:35,440 --> 00:28:39,160 Speaker 11: are all factors that I would consider that make for 548 00:28:40,040 --> 00:28:43,000 Speaker 11: investors make a compelling case for investors to at least 549 00:28:43,040 --> 00:28:46,760 Speaker 11: have some exposure to European equities fixed income space. 550 00:28:47,120 --> 00:28:49,440 Speaker 5: Christina, do I sit with my two year Treasury at 551 00:28:49,440 --> 00:28:51,080 Speaker 5: four point three six percent or do I take some 552 00:28:51,200 --> 00:28:51,959 Speaker 5: credit risk out there? 553 00:28:53,560 --> 00:28:55,880 Speaker 11: I think you need to take some credit risk. The 554 00:28:56,040 --> 00:28:59,720 Speaker 11: US economy is in rather good shape and there's the 555 00:28:59,760 --> 00:29:03,720 Speaker 11: potential for I think there's a very good likelihood that 556 00:29:03,800 --> 00:29:07,320 Speaker 11: we see a reacceleration in the US economy next year. 557 00:29:07,720 --> 00:29:10,640 Speaker 11: So in this environment, you want to take credit risk. 558 00:29:11,200 --> 00:29:14,440 Speaker 11: You want to have exposure to high quality, high yield, 559 00:29:14,840 --> 00:29:18,480 Speaker 11: investment grade bank loans. This is an environment where there 560 00:29:18,560 --> 00:29:22,120 Speaker 11: are many attractive asset classes within the fixed income space. 561 00:29:23,480 --> 00:29:25,280 Speaker 2: What happens to all the money and money market funds? 562 00:29:25,320 --> 00:29:27,280 Speaker 2: Do you think eventually that winds up taking on more risk? 563 00:29:27,400 --> 00:29:28,200 Speaker 2: How long does that take? 564 00:29:30,320 --> 00:29:30,360 Speaker 6: So? 565 00:29:30,440 --> 00:29:35,600 Speaker 11: I think it absolutely eventually goes into both equities and 566 00:29:35,680 --> 00:29:39,920 Speaker 11: fixed income. And I think that as we see continued 567 00:29:39,960 --> 00:29:43,640 Speaker 11: easing by the FED, that's certainly a helpful catalyst. As 568 00:29:43,720 --> 00:29:48,360 Speaker 11: well as the psychological impact of FOMO. I think we're 569 00:29:48,560 --> 00:29:51,600 Speaker 11: likely to see stocks move higher from here, and not 570 00:29:51,800 --> 00:29:54,120 Speaker 11: just stocks in the US elsewhere, and so I think 571 00:29:54,240 --> 00:29:59,840 Speaker 11: those are all reasons why and drivers for money start 572 00:30:00,240 --> 00:30:01,720 Speaker 11: to come out of cash. 573 00:30:02,360 --> 00:30:06,000 Speaker 2: I'm thinking about it, thinking about it, liad it. If 574 00:30:06,000 --> 00:30:08,600 Speaker 2: I'm thinking about it, that means stuff. I definitely have 575 00:30:08,720 --> 00:30:10,400 Speaker 2: some viewers that pin me all the time. You're like, 576 00:30:10,440 --> 00:30:12,800 Speaker 2: what are you doing? Get into high yeld ETFs? Come 577 00:30:12,840 --> 00:30:15,040 Speaker 2: on now, all right, Christina, thanks a lot, We really 578 00:30:15,040 --> 00:30:19,240 Speaker 2: appreciate it. Christina Hooper joining us from Investco. She's the 579 00:30:19,280 --> 00:30:22,400 Speaker 2: chief of Global market strategist over on that side. 580 00:30:22,760 --> 00:30:23,360 Speaker 5: This is the. 581 00:30:23,440 --> 00:30:28,280 Speaker 1: Bloomberg Intelligence podcast, available on Apples, Spotify, and anywhere else 582 00:30:28,320 --> 00:30:31,680 Speaker 1: you get your podcasts. Listen live each weekday, ten am 583 00:30:31,800 --> 00:30:35,400 Speaker 1: to noon Eastern on Bloomberg dot Com, the iHeartRadio app, 584 00:30:35,600 --> 00:30:38,200 Speaker 1: tune In, and the Bloomberg Business app. You can also 585 00:30:38,360 --> 00:30:41,680 Speaker 1: watch us live every weekday on YouTube and always on 586 00:30:41,720 --> 00:30:42,720 Speaker 1: the Bloomberg Terminal