1 00:00:02,520 --> 00:00:16,640 Speaker 1: Bloomberg Audio Studios, podcasts, radio news, single best idea on 2 00:00:16,680 --> 00:00:20,040 Speaker 1: a lazy Friday in the summer, Except it wasn't. It 3 00:00:20,120 --> 00:00:24,720 Speaker 1: was really interesting conversations across a wide set of topics, 4 00:00:24,800 --> 00:00:27,160 Speaker 1: and of course one of them is the politics of 5 00:00:27,200 --> 00:00:29,160 Speaker 1: the morning. Thank you Margaret Brennan with Face the Nation 6 00:00:29,720 --> 00:00:32,199 Speaker 1: on CBS, because we do a whole host of the 7 00:00:32,240 --> 00:00:35,839 Speaker 1: Sunday talk shows. You hear that on Bloomberg Radio on 8 00:00:36,000 --> 00:00:39,479 Speaker 1: Sunday at two pm in Washington and Boston and New 9 00:00:39,560 --> 00:00:42,680 Speaker 1: York as well. And all that's interesting about Washington, But 10 00:00:42,720 --> 00:00:45,479 Speaker 1: as we slip into the summer, it is about a 11 00:00:45,560 --> 00:00:49,239 Speaker 1: resilient stock market. It is about trying to get a 12 00:00:49,360 --> 00:00:53,240 Speaker 1: measure of where we are in the continuum. For Wayley 13 00:00:53,280 --> 00:00:56,720 Speaker 1: of Black Rock, it's an analog back to two thousand 14 00:00:56,720 --> 00:00:57,160 Speaker 1: and seven. 15 00:00:57,480 --> 00:01:01,800 Speaker 2: If we think about the peerage after Mobal financial crisis, 16 00:01:01,920 --> 00:01:06,200 Speaker 2: with the injection of Emmas pool of liquidity, companies that 17 00:01:06,640 --> 00:01:11,240 Speaker 2: didn't have good fundamentals were rallying alongside companies with very 18 00:01:11,240 --> 00:01:14,319 Speaker 2: good fundamentals. And this is what I meant by rising 19 00:01:14,360 --> 00:01:17,920 Speaker 2: tight lifting all boats. But we're now in an environment 20 00:01:18,600 --> 00:01:24,960 Speaker 2: of greater dispersion. We're in an environment of secular transformations 21 00:01:25,040 --> 00:01:29,759 Speaker 2: like AI that is likely going to imply winners take hold. 22 00:01:30,040 --> 00:01:33,360 Speaker 2: So this is an environment where being active and selective 23 00:01:33,560 --> 00:01:37,160 Speaker 2: pays off more. And this is not a hypothesis. Our 24 00:01:37,240 --> 00:01:40,600 Speaker 2: study actually shows that in a period coming out of 25 00:01:40,640 --> 00:01:47,680 Speaker 2: the pandemic, actually the additional alpha generated by good active 26 00:01:47,720 --> 00:01:52,720 Speaker 2: managers is greater compared to the peerage when rising tight 27 00:01:52,920 --> 00:01:53,880 Speaker 2: was lifting all boats. 28 00:01:54,080 --> 00:01:56,040 Speaker 1: Really they are are black rec and this is a 29 00:01:56,080 --> 00:01:59,280 Speaker 1: side note, she writes brilliantly on LinkedIn. One of the 30 00:01:59,320 --> 00:02:02,040 Speaker 1: reasons to be on LinkedIn. I'm on LinkedIn. Thank you 31 00:02:02,040 --> 00:02:05,160 Speaker 1: Shaneli Bassk for pushing me that way is wayley. She 32 00:02:05,320 --> 00:02:10,239 Speaker 1: just this great, great short chart driven work for Blackrock 33 00:02:10,680 --> 00:02:14,720 Speaker 1: out on LinkedIn. Anna Wong. People say where is she? 34 00:02:14,840 --> 00:02:18,360 Speaker 1: I get emails, live chat on YouTube. Where is she? 35 00:02:18,360 --> 00:02:20,760 Speaker 1: She was on the Pacific RIM. Bloomberg is a global 36 00:02:20,800 --> 00:02:25,079 Speaker 1: country a company, I should say, And it's really important 37 00:02:25,120 --> 00:02:27,640 Speaker 1: to understand that every once in a while, the US 38 00:02:27,680 --> 00:02:30,679 Speaker 1: team has to go and sit on the Pacific RIM. 39 00:02:30,760 --> 00:02:33,360 Speaker 1: That's what doctor Wong has been doing for weeks on 40 00:02:33,520 --> 00:02:36,720 Speaker 1: any ear. She is back and she was spirited today 41 00:02:37,200 --> 00:02:40,000 Speaker 1: about looking at the American labor economy. 42 00:02:40,160 --> 00:02:43,919 Speaker 3: Recall that last year. The July jobs report was what 43 00:02:44,080 --> 00:02:49,000 Speaker 3: caused this flash crash in August. So what happens in 44 00:02:49,080 --> 00:02:52,560 Speaker 3: this coming jobs report is that on a non seasonally 45 00:02:52,639 --> 00:02:55,880 Speaker 3: adjusted basis, there should be over a million job losses 46 00:02:56,360 --> 00:03:02,440 Speaker 3: from yes, from local sector, from local government, from education sector. 47 00:03:03,400 --> 00:03:07,120 Speaker 3: So last month everybody was like, wow, the job of persurprise, 48 00:03:07,160 --> 00:03:09,840 Speaker 3: of the upside, But it's entirely due to the facade 49 00:03:09,960 --> 00:03:13,400 Speaker 3: of a seasonal adjustment in the local government sector. So 50 00:03:13,520 --> 00:03:16,799 Speaker 3: now that in July we're supposed to see this, you know, 51 00:03:16,919 --> 00:03:21,040 Speaker 3: a million job losses in the sector, plus you have 52 00:03:21,160 --> 00:03:26,040 Speaker 3: this rebound from the seasonal you overestimation in the last month, 53 00:03:26,400 --> 00:03:29,959 Speaker 3: I think that that's the place to watch weather, because 54 00:03:29,960 --> 00:03:33,240 Speaker 3: we do know that local government is not hiring. 55 00:03:34,000 --> 00:03:37,200 Speaker 1: Great damn annawe Back really can't say enough about it. 56 00:03:37,320 --> 00:03:41,880 Speaker 1: She was brilliant today in freshwater versus saltwater economics. That's 57 00:03:41,920 --> 00:03:45,920 Speaker 1: the East Coast, the ocean versus the Great Lakes of Carnegie, Mellon, 58 00:03:46,000 --> 00:03:50,000 Speaker 1: and Rochester of years ago, over to Chicago and out 59 00:03:50,080 --> 00:03:53,560 Speaker 1: to the Midwest. Thanks to John Farrell for a great conversation. 60 00:03:54,160 --> 00:03:58,400 Speaker 1: Christopher Waller today a really important conversation with a gentleman 61 00:03:58,440 --> 00:04:02,680 Speaker 1: from the Saint Louis FED now in Washington as a 62 00:04:02,720 --> 00:04:06,720 Speaker 1: Governor of the FED. On our podcast, we're on Spotify, 63 00:04:06,720 --> 00:04:10,280 Speaker 1: were on Apple as well, and on YouTube podcasts. It's 64 00:04:10,320 --> 00:04:17,120 Speaker 1: single best idea