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Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney alongside

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Speaker 1: my co host Matt Miller. Every business day we bring

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Speaker 1: you interviews from CEOs, market pros, and Bloomberg experts, along

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Speaker 1: with essential market moving news. Find the Bloomberg Markets Podcast

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Speaker 1: on Apple Podcasts or wherever you listen to podcasts, and

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Speaker 1: at Bloomberg dot com slash podcast. I don't know I

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Speaker 1: got my Paul Sweeney personal inflation meter, otherwise known as

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Speaker 1: unletted gas. It's continues to roll over. There's students, especially

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Speaker 1: if you're at sheets in Newark, Ohio. First exactly, they're

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Speaker 1: giving it away. Practically, we're seeing in other parts of

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Speaker 1: the economy inflation A lot of people tell me has peaked.

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Speaker 1: If that's in fact the case, why doesn't Ira Jersey's

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Speaker 1: feed to reserve just put the brakes on it. Let's ask, right,

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Speaker 1: he's chief US interest rate strategist for Bloomberg Intelligence, and

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Speaker 1: we need to save some time to talk about World

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Speaker 1: Cup here. Matt remind me on that. I know, but

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Speaker 1: we're not going to talk about Amazon because Ira has

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Speaker 1: such a cushy job. All he focuses on in sector, Ira,

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Speaker 1: why don't you broaden your remit a little bit. I mean,

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Speaker 1: the whole rate space is there for you. Well, my, well,

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Speaker 1: so we have a credit strategist named Noel Hebert who

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Speaker 1: covers corporates, so you can talk to him about what's

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Speaker 1: going on in the text space and all the other

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Speaker 1: sectors within within the corporate landscape. So also, I think

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Speaker 1: it's fair actually, now that I think about it, considering

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Speaker 1: the amount of FED speak out there, we need one

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Speaker 1: guy that's just focused on that. Like, why did they

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Speaker 1: come out and talk so much? Doesn't that annoy J? Powell? Uh, yeah,

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Speaker 1: it would have annoyed down in Greenspan for sure. Um. Yeah.

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Speaker 1: You know, the FED over the last twenty years has

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Speaker 1: gotten very democratized and and there's just I think there's

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Speaker 1: just been this push that all the members are um,

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Speaker 1: you know, wanted to say things, and then they when

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Speaker 1: they once they started too, it was hard to kind

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Speaker 1: of put the genie back in the bottle. J. Powell. Certainly,

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Speaker 1: it's still the mouthpiece for the entire Federal Reserve, and

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Speaker 1: I think that his what he says matters obviously the most.

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Speaker 1: And then um, but every member you know, wants to

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Speaker 1: have their say, and you know from from an analysis perspective,

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Speaker 1: it's a little bit easier for us too to determine

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Speaker 1: things like where the dots are and and maybe who's

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Speaker 1: who's really hawkish and dobbish visa be what you could

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Speaker 1: do before Alan Greenspan or you know, left the Fed Reserve,

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Speaker 1: because back then it was like, okay, it's whatever Alan

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Speaker 1: Greenspan says. And but every once in a while you

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Speaker 1: had some members that were more hawkish or dovish than him,

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Speaker 1: and they would dissent and we didn't necessarily know in

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Speaker 1: advance if they would. And now it's it's a little

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Speaker 1: bit easier to determine, you know what, what the leaning

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Speaker 1: of a majority or of the or or a significant

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Speaker 1: minority of the Fed Reserve is going to be. Well.

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Speaker 1: And now then to Paul's point, um, it does seem

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Speaker 1: it's not just him, right. A lot of people think

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Speaker 1: inflation has peaked now, even though we've only gotten a

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Speaker 1: very small set of numbers to corroborate that. But the

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Speaker 1: speakers for the most part are talking about a step down,

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Speaker 1: a reduction in the rate hike increases that we've seen.

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Speaker 1: So have we reached that point? I mean, are we

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Speaker 1: looking at something of a pivot. Yeah, so you know,

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Speaker 1: this is something that actually that J. Powell has been

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Speaker 1: mentioning since uh since July. Right, So it's not this

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Speaker 1: isn't a new concept, and that this step down in

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Speaker 1: the pace of hikes. They weren't going to hike at

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Speaker 1: seventy five basis points every single meeting forever, right, So

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Speaker 1: at some point they were going to have to slow

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Speaker 1: the pace or just stop. And and I think in

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Speaker 1: December they're only going to go fifty. I think they'll

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Speaker 1: go then after that, And and I mentioned to you

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Speaker 1: guys before you know, they're going to go to the

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Speaker 1: basis point. UM moved again, probably starting in at the

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Speaker 1: February meeting, the February first meeting, because it allows them

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Speaker 1: just to calibrate just a little bit more like should

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Speaker 1: they go to five on the upper round of the

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Speaker 1: Fed funds target? Should they go to five and a

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Speaker 1: quarter like some people, UM think they should go. So

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Speaker 1: by by going in twenty five, they can just calibrate

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Speaker 1: towards the end of hikes. But but I think the

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Speaker 1: important point there is that to paulse question is that, yes,

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Speaker 1: inflation seems like it's rolled over, the economy is slowing

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Speaker 1: a bit and because of that that the FED is

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Speaker 1: nearing the end of their hikes. Whether or not they

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Speaker 1: go another another fifty seventy five hundred basis points, it's

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Speaker 1: still the end is still in sight. And I think

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Speaker 1: that that's the important part point for the markets right now.

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Speaker 1: All right, that's enough on the rates market. Let's get

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Speaker 1: the important stuff. Two pm. Wall Street Time today, US Iran.

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Speaker 1: How do you think this is going to go? Especially

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Speaker 1: in a World Cup where literally anyone can win. Yes,

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Speaker 1: it seems like it. So I think for Iran, given

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Speaker 1: that they they beat Whales, they're gonna probably play pretty

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Speaker 1: defensively against US and try to put you know, nine

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Speaker 1: or ten guys behind the ball and just trying and

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Speaker 1: try to beat us on on a counter attack. And

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Speaker 1: and historically, if you go look at what the US

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Speaker 1: has done against other countries in North and Central America

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Speaker 1: that they play that that we play in the Gold Cup,

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Speaker 1: we we tend to have a pretty hard time breaking

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Speaker 1: down very what we call bunker defenses. So um so

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Speaker 1: I think that that you know, I hate to say this,

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Speaker 1: but this is gonna be probably a one goal game,

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Speaker 1: and I think it will be, you know, maybe one

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Speaker 1: nail to the US and in the end, um, but

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Speaker 1: and and if we do score early, I think that

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Speaker 1: that will get that will get I ran out of

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Speaker 1: their bunker, because they're in order for them to continue

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Speaker 1: and actually make it to the next round, they're going

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Speaker 1: to have to then play to to at least draw

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Speaker 1: the US. And how much does historically matter? I mean,

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Speaker 1: in a in a contest where Saudi Arabia beats Argentina,

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Speaker 1: is that because Saudi Arabia historically is great at soccer

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Speaker 1: and Argentina is horrible? No? Not, not not at all,

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Speaker 1: I think I Well, in rewatching, that's the percentage history,

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Speaker 1: you know, I mean, um, compared to chance. Well, well,

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Speaker 1: let me say this firstly, I think any of these

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Speaker 1: teams could be any any other team on a on

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Speaker 1: any given day. I mean, that's one of the that's

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Speaker 1: like almost every sport, right, especially when you're talking about

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Speaker 1: high level professional athletes. I think in that Argentina Sordi

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Speaker 1: Arabia game, I think Argentina came out a bit flat.

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Speaker 1: I think that their defense has some holes in it.

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Speaker 1: That um that you know, Saudi Arabia certainly exploited and um,

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Speaker 1: so you know, but that's a one off game. I think,

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Speaker 1: you know, taking the games the afternoon, um as in

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Speaker 1: a bubble. I think the US has the more talented players,

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Speaker 1: but I Ran does play very compact. They are very

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Speaker 1: organized defensively, and and that's going to create problems for

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Speaker 1: the US. All Right, it's good stuff. I think it's

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Speaker 1: gonna be musty TV for a lot of sports fans today,

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Speaker 1: even if you're not a Soccer World Cup fan. Our

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Speaker 1: Jersey chief US Interest rate strategist and Chief Soccer strategists

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Speaker 1: slash football strategist for Bloomberg Intelligence. Over the last few days,

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Speaker 1: you know, surprised me. To me, I guess it's just

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Speaker 1: I've really been kind of moving in response to kind

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Speaker 1: of some of the news we're getting out of China,

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Speaker 1: and I guess that goes to the whole global economic

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Speaker 1: you know, reopening, recession risk, all those types of things

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Speaker 1: on global scale is obviously economy. So we wait to

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Speaker 1: talk to people who have got some experience thinking about

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Speaker 1: investing in that part of the world. Uh Hans Dout

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Speaker 1: is one of those people who's the CEO of Mitchell

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Speaker 1: Madison Group, and I think that his claim to fame

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Speaker 1: as he is an undergraduate from the University of Michigan,

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Speaker 1: who have had a an extraordinarily successful weekend. So Hans,

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Speaker 1: let me get your your thoughts here on the Higher

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Speaker 1: State Michigan game. You guys know what went to Dartmouth, right, Yes,

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Speaker 1: you got your m right, but I thought you got

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Speaker 1: your b A from the university. I did not. I

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Speaker 1: did not about that, thank god. Okay, so you know

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Speaker 1: we had a Michigan guy coming on, and I will

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Speaker 1: say you know that Michigan played an incredible game on Saturday,

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Speaker 1: and Ohio State simply did not show up. I don't

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Speaker 1: know where our defensive coordinator was. He didn't seem to

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Speaker 1: be working that day, even though I thought that's why

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Speaker 1: we hired him. All of this means nothing to Hans

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Speaker 1: Doll because he didn't go to Michigan. No, but he

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Speaker 1: got his NBA qualified. Alright, let's let's pivot to the

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Speaker 1: China first. Let's talk about your China bona fides then,

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Speaker 1: because I know that you have made uh substantial contributions

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Speaker 1: to the tang In Song law and um you have

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Speaker 1: helped US government officials understand China and Chinese legal history.

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Speaker 1: How did you get into China going to school in Germany?

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Speaker 1: And then UM in Vermont. Well, well, we basically a

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Speaker 1: consulting firm, right, so we most of what we did

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Speaker 1: over the last decade or so, it's help American companies

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Speaker 1: established UM production of China, sourcing from China, right, So

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Speaker 1: my main business has been strategic sourcing, helping Western companies

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Speaker 1: established you know, production and uh, you know sourcing agreement

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Speaker 1: all over the world. Of course in China in particular lately,

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Speaker 1: we've actually helped a lot of Chinese companies be more

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Speaker 1: efficient within China. And of course since COVID, that whole

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Speaker 1: business does nothing going on. I mean, you and I

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Speaker 1: spent a lot of time going to China before COVID.

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Speaker 1: I was actually part of the UM. I was in

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Speaker 1: Hong Kong doing the protests and everything, and I thought

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Speaker 1: that was going to actually result in something, but it didn't.

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Speaker 1: Right in, the Chinese clearly clamped down on this, And

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Speaker 1: I think we're just living in the world that looks

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Speaker 1: quite different from from the world that you know existed

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Speaker 1: before COVID, because you know, China is on number one

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Speaker 1: too political rival, there's no doubt about that. And you're

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Speaker 1: looking at the zero COVID policies causing you know, lots

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Speaker 1: of issues politically, and you know, the staw, the protests,

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Speaker 1: the markets up a little bit. I guess people are

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Speaker 1: more optimistic, but still um. You know, you look at

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Speaker 1: at the policy response and it seems to me that

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Speaker 1: they are. There's an element of political obsession, you know,

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Speaker 1: with zero COVID policy, of course, but there's also maybe

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Speaker 1: an element of the fact that China has to flatten

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Speaker 1: the curve more than we had to do, right, because

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Speaker 1: the vaccination rates aren't very good, especially among people, and

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Speaker 1: maybe the hospital capacity and the medical system isn't as

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Speaker 1: good as as they make us believe, right, So that's

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Speaker 1: going going to continue a thing. Can you help us

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Speaker 1: understand why j and ping Um continues to stick to

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Speaker 1: this COVID zero policy. Why not you know, mass vaccinations.

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Speaker 1: They have the supply chains to make stuff, right, they

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Speaker 1: have the authority to order people to take stuff. Why

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Speaker 1: not deal with it that way rather than this way.

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Speaker 1: I mean they have done to certain extent, right, So

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Speaker 1: you have about ninety ciment population is vaccine it twice

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Speaker 1: the lowest vaccination rates are among people over eighty, which

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Speaker 1: is very concerning. I think they're old enough to remember

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Speaker 1: the good old base and they don't trust the government. Uh.

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Speaker 1: And and you have the vaccine is you know, far

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Speaker 1: less effective than than than MR and A technology. It's

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Speaker 1: not style vaccine. Um. And I think you have the

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Speaker 1: I mean, you can't really trust the numbers are China, right,

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Speaker 1: I mean, I do not believe that the hospital capacity

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Speaker 1: is as good as they claim it would be. And

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Speaker 1: if they have a major outbreak with the with the

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Speaker 1: more you infectious variants, um, you know, one to two

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Speaker 1: million people would die and would make the leadership look

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Speaker 1: really bad, right, And I think that's why they're not

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Speaker 1: doing it. They're they're easing us a little bit. I

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Speaker 1: think they're walking this fine line between you know, protests

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Speaker 1: and and and people you know, sense of complaining and

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Speaker 1: and and all that. But it's the old flatan in

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Speaker 1: the curve that you're going to get it right eventually.

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Speaker 1: So over the long haul, you're gonna get it. Yeah,

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Speaker 1: of course. Well look Miracle said that right at the

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Speaker 1: very beginning of the pandemic before when we all thought

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Speaker 1: it was crazy. She said, I think sixty people are

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Speaker 1: going to end up getting COVID and we thought this

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Speaker 1: is in March of that's nuts. And she turned out there. So, Hans,

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Speaker 1: how do you we we've all recognized that the Chinese

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Speaker 1: governments in a very difficult position here. How do you

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Speaker 1: actually think this ultimately plays out? It's hard to say.

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Speaker 1: I think we have to understand that China is this

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Speaker 1: ultimate surveillance state, right and with enormous powers, right, and

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Speaker 1: so drawing any parallels from the past, I think it

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Speaker 1: is very dangerous because that's just that's just not how

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Speaker 1: it was. Right. You might have protests, but the degree

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Speaker 1: to which China is monitoring its population, you know, through

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Speaker 1: the phones and through cameras and all this stuff, makes

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Speaker 1: it pretty very effective at putting any kind of protests down.

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Speaker 1: And I think, you know, you the models we've me

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Speaker 1: have used in the past, and you know, in terms

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Speaker 1: of like German square and even Hong Kong and to

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Speaker 1: US nineteen may not apply, I think that will be

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Speaker 1: quite successful in keeping the population under control. It's very interesting, indeed,

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Speaker 1: what do you think in terms of you know, Apple,

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Speaker 1: for example, is now UM accelerating its quest to produce

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Speaker 1: more iPhones elsewhere UM. A lot of companies have, as

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Speaker 1: you know at Mitchell Madison UM looked for ways to

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Speaker 1: untangle themselves from the Chinese supply chain web. Is that

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Speaker 1: going to happen or are we gonna all chill out

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Speaker 1: and they're gonna keep making all this stuff by well,

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Speaker 1: I certainly hope not right. I mean, I think you've

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Speaker 1: seen some some elements of this. You saw you guys

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Speaker 1: reported that Mexico had the absolute largest monthly export to

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Speaker 1: the United States and there were some pretty sophisticated you know,

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Speaker 1: product automotive parts and so forth. I think it's happening.

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Speaker 1: The private sector as usual will drive this shift away

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Speaker 1: from China. This is not going to be a top

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Speaker 1: down thing, um, And I think there's alternatives, right, Obviously,

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Speaker 1: there's huge capital investment in the country that have to

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Speaker 1: be replicated. I think, you know, Taiwan was probably the

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Speaker 1: most dangerous situation that from the private sector of perspective

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Speaker 1: that could happen. What a dangerous for both parties. I

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Speaker 1: think people will be hopefully be be cool about it, right,

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Speaker 1: cool aheads. But I think the private sector has taken

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Speaker 1: lead on this, and the name of the game is diversification. Diversisification, diversification.

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Speaker 1: You cannot relye when this thing that's even Apple like

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Speaker 1: the most sophisticated supply Cheam company on the in the

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Speaker 1: history of humanity, you got hit pretty hard, right, Yea,

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Speaker 1: it's a it's an extraordinary situation, seemingly fluid changing by

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Speaker 1: the day there in China, with as you mentioned, Hans,

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Speaker 1: this broad broad implications for the global economy, hansdo CEO

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Speaker 1: of Weight, Hans Dow. Where did you study? Which university

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Speaker 1: in Germany? You know? I think I studied in Mannheim,

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Speaker 1: which sounded a little bit like Michigan. Maybe that's that's

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Speaker 1: what happened. Oh, that's like a Weinheimer. That's like an

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Speaker 1: engineering school. Right, it's a cool place, you know. Yeah.

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Speaker 1: I love Monheim and we use their used car indexes.

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Speaker 1: Oh we do. That's right, good stuff, all right, exactly.

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Speaker 1: We're gonna round table a little bit right now. Our

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Speaker 1: topic is going to be this railroad potential strike that's

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Speaker 1: out there. I've got a couple of weeks kind of

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Speaker 1: deal with that. Now, I would have big implications for

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Speaker 1: this economy. So we need to get a couple of

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Speaker 1: smart people on here. Bloomberg Intelligence Senior Transportation analyst Lead

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Speaker 1: class now who joins us on the phone, and Jody

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Speaker 1: Schneider here on O Bloomberg inter actor Broker Studio. She's

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Speaker 1: a political news director for Bloomberg TV and Radio. So

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Speaker 1: let's start with you. I'd love to get a sense

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Speaker 1: of what you're hearing from the big railroad companies that

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Speaker 1: you talked to. What are they saying here, Hey, Paul,

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Speaker 1: thanks for having me. Um. You know, I think that

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Speaker 1: you know, I think they remain relatively optimistic that that

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Speaker 1: our agreement can can come before the December ninth deadline. Obviously,

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Speaker 1: the closer you get to that deadline, the rails will

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Speaker 1: have to start shutting down their networks to ensure that um,

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Speaker 1: you know, fraid it's not going to get lost in

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Speaker 1: the system. Uh and also to make sure that their

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Speaker 1: employees are home, um, you know when when the strike happens. Um,

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Speaker 1: So you know, you could see a disruption before the

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Speaker 1: December and ninth deadline. Uh, as as we get closer

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Speaker 1: to that deadline. If in fact, um, you know, the companies,

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Speaker 1: the railroads feel that they can't get to an agreement.

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Speaker 1: But but obviously noise out of Washington looks like, you know,

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Speaker 1: the federal government, the administration and Congress is working pretty

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Speaker 1: hard to make sure that doesn't happen. Just because of

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Speaker 1: the you know, the impact the economy which the American

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Speaker 1: trucking or is to start the Association of American Railroads

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Speaker 1: are putting out around two billion dollars a day. Are

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Speaker 1: we still looking at the same problems we were back

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Speaker 1: in August September, where you know, railroad employees can't get

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Speaker 1: a day off to go to the doctor, or where

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Speaker 1: you know one woman or man is in charge of

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Speaker 1: an entire freight train along a route. Yeah, you know,

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Speaker 1: it's it's really not about pay. Uh, you know, the

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Speaker 1: pay aspect, they're getting a pretty nice bump. They're getting

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Speaker 1: raises over a four or four or five year period. Um.

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Speaker 1: It's really about to your point to work rules. You know,

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Speaker 1: how easy or difficult is it for a rail employee

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Speaker 1: to you know, call and sick to go to a

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Speaker 1: doctor's appointment? You know, are they going to be penalized

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Speaker 1: for that? You know, there's about thirteen groups that are

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Speaker 1: negotiating as part of this National Railway Railway Labor Conference.

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Speaker 1: Four of them have not ratified the agreement. The others, uh,

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Speaker 1: seven have ratified the agreement. Um. And so it's really

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Speaker 1: those those score holdouts that could really snag things up. Now,

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Speaker 1: what's what's the problem here on the side of the

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Speaker 1: railroad operators. I mean, why not give your employees um

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Speaker 1: days off to deal with healthcare issues. I mean, you

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Speaker 1: wouldn't insist that a locomotive work every day. If it's

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Speaker 1: broken down, you're not gonna put it in service, right right.

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Speaker 1: And I'm not definitely here to defend the railroads any

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Speaker 1: stretch of imagination, but you know, this is something that's

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Speaker 1: typically negotiated at the local level. That's what the rails

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Speaker 1: are saying. So they're not necessarily saying that we're mean

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Speaker 1: and we don't want our employees to take off. We're

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Speaker 1: saying that this is typically dealt at the local level,

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Speaker 1: and that's where it should be a negotiated opposed to

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Speaker 1: this national broad contract for all the railroads. Um, you know.

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Speaker 1: And the problem also becomes, you know a lot of

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Speaker 1: railroads are operating a lot more efficiently because they've implemented

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Speaker 1: precision scheduling railroading, which is pretty much six stigma for

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Speaker 1: the rail industry. Uh. And you know they're trying to

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Speaker 1: operate lean and mean, and you know, when if if if,

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Speaker 1: if you're scheduled to work and someone's calling out, that

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Speaker 1: put a wrench in the whole system. Uh. But the

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Speaker 1: rails need to probably realize, well, maybe we need to

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Speaker 1: resource our systems a little more. Uh. And you know,

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Speaker 1: if that's going to cost tend basis in operating ratio,

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Speaker 1: so be it. But you know, that's that's an argument

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Speaker 1: that the railroads will have to have, uh, not only

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Speaker 1: you know, discussion with the unions, but also discussions with

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Speaker 1: the shareholder as well, because you know, because rail investors

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Speaker 1: are probably myopically focused on the operating ratio, which is

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Speaker 1: an inverse of an EVA margin, So lower the better. Hey, Jody,

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Speaker 1: want to bring you in here. What can this administration do?

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Speaker 1: What should they do? What do you think they can

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Speaker 1: get done? Well? President Biden says, now he was going

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Speaker 1: to go to Congress. Uh, and yesterday in his statement

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Speaker 1: expressing concern about this potential strike now that it's coming closer,

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Speaker 1: that he said lawmakers should immediately codify the agreement that

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Speaker 1: he helped of course broker in September between the unions

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Speaker 1: and the railroads. Uh. It looks like then the House

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Speaker 1: they're getting ready to do that, outgoing Speaker Nancy Pelosi,

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Speaker 1: so she will move to do that to codify that

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Speaker 1: this week. The Senate is a little trickier because they

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Speaker 1: have other things on the agenda, and the Senate always

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Speaker 1: takes longer to do things. Things like the intervening day

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Speaker 1: pop up, so it's unclear whether that will happen. There

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Speaker 1: By the way Congress has acted, we went and looked.

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Speaker 1: They've acted eighteen times to prevent strikes. Um. They but

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Speaker 1: the last time they did this was so Um, it's

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Speaker 1: been a while. You could say that again. Yes, it's

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Speaker 1: been twenty six years, eight years. Um. So hey, while

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Speaker 1: we have you here, Jody, when are we gonna know

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Speaker 1: the full composition of the Senate? Yeah? So next Tuesday

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Speaker 1: we have a big runoff between Herchel Walker and the

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Speaker 1: Republican side and sitting Senator Raphael Warnock on the Democratic side.

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Speaker 1: Early voting has been a record in that so a

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Speaker 1: lot of people have already gotten out there. Uh, it's

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Speaker 1: still polls and there are a ton of polls, but

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Speaker 1: the polls are showing them pretty neck and neck. Uh.

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Speaker 1: It won't determine obviously, the majority in the Senate, because

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Speaker 1: we already knew that. Um, the Democrats have picked that up.

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Speaker 1: But it will give them a little bit of breathing

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Speaker 1: room the Democrats if they do win that seat. And

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Speaker 1: so it looks neck and neck. Lots of you know

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Speaker 1: issues there, And of course herschel Walker was somebody who

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Speaker 1: Donald Trump had supported. Brian Kemp, the governor who just

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Speaker 1: was reelected, is now supporting uh Walker. He hadn't done

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Speaker 1: a whole lot for him in the general campaign, but

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Speaker 1: is now appearing on the stage with him. Interesting fact

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Speaker 1: and another fun fact here, two hundred thousand voters voted

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Speaker 1: for Kemp who did not vote for Walker in the

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Speaker 1: general election. So the question is are they are those

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Speaker 1: people likely to show up or some who voted for

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Speaker 1: him likely to show up. It's all going to be

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Speaker 1: about turn out, all right, Jody, great stuff, Thanks so

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Speaker 1: much for joining us here in our Bloomberg and Director

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Speaker 1: Broker studio, Lee Glasgow. He's a senior transportation analyst focusing

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Speaker 1: on the rails and the trucks and all that logistics stuff,

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Speaker 1: so certainly the perfect guy to get on the phone

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Speaker 1: here and talk to us about what could be a

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Speaker 1: strike for the nation's railroads beginning December ninth. So that's

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Speaker 1: a big issue. We will keep on top of that.

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Speaker 1: I got the argument why the Amazons and the Microsoft

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Speaker 1: would come to the debt market to race that even

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Speaker 1: though they don't need it because interest rates are zero.

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Speaker 1: But interest rates aren't zero anymore yet, Amazon coming to

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Speaker 1: the market with maybe a seven billion dollar deal. Matt

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Speaker 1: Miller's deal. It's a big deal, Matt. It's like a

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Speaker 1: huge deal in a year where there's nothing going on

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Speaker 1: for a lot of these investment banks. So we got

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Speaker 1: to bring in, Matt says, we gotta get the uh

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Speaker 1: somebody in here, and we do. We have our friend

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Speaker 1: here to talk to us about what is going on

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Speaker 1: here from Bloomberg Intelligence. What is going on here? Why

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Speaker 1: is Amazon rob Why are they coming to market? Now? Well, listen,

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Speaker 1: others might take credit for this phrase, but I think

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Speaker 1: I created it. You borrow when you can, not when

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Speaker 1: you need to. It sounds like Jack Reacher. I think

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Speaker 1: Jack Reacher said that. So listen. The ten years rallied

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Speaker 1: fifty basis points. In the last two months, spreads are just,

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Speaker 1: you know, really haven't moved that much. The cost of

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Speaker 1: capital for Amazon isn't that much. And by the way,

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Speaker 1: they've spent a lot of money over the last couple years.

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Speaker 1: Their cash numbers are down thirty odd billion dollars, their

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Speaker 1: free cash flow negative for the year UM, so they're

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Speaker 1: just fortifying their balance sheet. I think it could be

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Speaker 1: two things. UM. One is there could be more M

427
00:23:10,560 --> 00:23:12,840
Speaker 1: and A coming or two as they could be joining

428
00:23:13,000 --> 00:23:18,400
Speaker 1: their large cap brethren UM and start start to participating

429
00:23:18,400 --> 00:23:21,280
Speaker 1: in this capitol return game and start buying a back

430
00:23:21,320 --> 00:23:23,600
Speaker 1: a lot more stock. You know, they've pretty much stayed

431
00:23:23,600 --> 00:23:27,040
Speaker 1: out of the capital return market. So all right, rob

432
00:23:27,080 --> 00:23:30,679
Speaker 1: Shift and bloomber Intelligence. My question is, is this just

433
00:23:30,800 --> 00:23:34,560
Speaker 1: like I don't know on the M and A front,

434
00:23:34,680 --> 00:23:37,199
Speaker 1: It feels like there's a lot of places they could go,

435
00:23:38,040 --> 00:23:41,280
Speaker 1: but and they do do some smaller deals, but is

436
00:23:41,280 --> 00:23:44,640
Speaker 1: there any call out there that they could do a big, big,

437
00:23:44,680 --> 00:23:48,920
Speaker 1: big deal. You know, it's pretty hard to make transformation

438
00:23:49,000 --> 00:23:52,480
Speaker 1: on trades these days. One is Amazon is so big,

439
00:23:52,880 --> 00:23:55,479
Speaker 1: there's nothing that they could actually buy that would they

440
00:23:55,480 --> 00:23:58,680
Speaker 1: would meaningfully change their their top or bottom line. It's

441
00:23:58,680 --> 00:24:01,440
Speaker 1: like regulatory issues. And the secondly, listen, you've got guys

442
00:24:01,480 --> 00:24:05,560
Speaker 1: like Microsoft going after activision UM and they might not

443
00:24:05,600 --> 00:24:07,240
Speaker 1: be able to get get away with it, and they're

444
00:24:07,240 --> 00:24:09,480
Speaker 1: willing to spend you know, close to seventy billion dollars

445
00:24:09,480 --> 00:24:11,840
Speaker 1: in cash, So Listen, there's a lot of things Amazon

446
00:24:12,000 --> 00:24:17,040
Speaker 1: can buy. Um, they can get much deeper into the movie, uh,

447
00:24:17,160 --> 00:24:20,960
Speaker 1: TV production, theatrical businesses. You know, there could be more

448
00:24:21,000 --> 00:24:25,160
Speaker 1: in terms of of um, you know, health and healthcare.

449
00:24:25,240 --> 00:24:27,600
Speaker 1: You know, there's always a peloton sitting out there. Listen.

450
00:24:27,600 --> 00:24:29,919
Speaker 1: In theory, maybe they want to buy a Netflix, but

451
00:24:30,040 --> 00:24:32,879
Speaker 1: it's it's probably unlikely. I think, you know, M and

452
00:24:32,920 --> 00:24:34,840
Speaker 1: A for a name like this is really around the edges.

453
00:24:34,840 --> 00:24:38,320
Speaker 1: What matters to Amazon is growth in aws and people

454
00:24:38,359 --> 00:24:41,200
Speaker 1: buying a lot of stuff online, and that's ultimately what's

455
00:24:41,200 --> 00:24:43,920
Speaker 1: going to drive the business. And they have the might

456
00:24:44,400 --> 00:24:48,160
Speaker 1: to command a decent rate in markets, right, I mean

457
00:24:48,480 --> 00:24:50,440
Speaker 1: I was looking at the story. It said they're going

458
00:24:50,840 --> 00:24:54,320
Speaker 1: for a hundred fifteen basis points over treasuries. That's pretty good.

459
00:24:54,680 --> 00:24:58,040
Speaker 1: Is that good for Amazon? Listen? They actually trade meaningfully

460
00:24:58,080 --> 00:25:02,480
Speaker 1: tighter than their and above tech comparables. But they do

461
00:25:02,600 --> 00:25:10,240
Speaker 1: trade wider, uh than they're real they're the biggest comps Apple, Microsoft, Alphabet,

462
00:25:10,640 --> 00:25:14,200
Speaker 1: so they surely not wider than Netflix, Disney, no Or

463
00:25:14,400 --> 00:25:17,640
Speaker 1: or Meta. UM. But are are they? Are they attractive

464
00:25:17,680 --> 00:25:21,760
Speaker 1: to people because one, they offer incremental yield versus the

465
00:25:21,920 --> 00:25:25,480
Speaker 1: super high quality names, and because credit quality is still

466
00:25:25,760 --> 00:25:28,320
Speaker 1: actually on the rise. I mean, even though this is

467
00:25:28,440 --> 00:25:31,000
Speaker 1: a double A name, they could be high double A.

468
00:25:31,320 --> 00:25:34,400
Speaker 1: I don't think anyone really is concerned about Amazon's credit

469
00:25:34,480 --> 00:25:36,919
Speaker 1: quality going forward. And in fact, sort of all the

470
00:25:37,000 --> 00:25:39,359
Speaker 1: noise that you've seen in the equity market really hasn't

471
00:25:39,359 --> 00:25:42,840
Speaker 1: played into Amazon. You know, when I talked to clients

472
00:25:43,040 --> 00:25:45,159
Speaker 1: and most of them say to me, I'm surprised they

473
00:25:45,160 --> 00:25:47,160
Speaker 1: haven't widened out a lot more. And and the reason

474
00:25:47,240 --> 00:25:49,720
Speaker 1: why they haven't is that, you know, most people know

475
00:25:49,760 --> 00:25:52,320
Speaker 1: what Amazon is. It's very easy to pick through this

476
00:25:52,400 --> 00:25:54,679
Speaker 1: bouncy and think, you know, over the long term, the

477
00:25:54,720 --> 00:25:58,280
Speaker 1: cash flow trajectory for this name is going to be enormous.

478
00:25:58,520 --> 00:26:01,720
Speaker 1: They have also the ability to control what their free

479
00:26:01,720 --> 00:26:03,679
Speaker 1: cash flow. It looks like we pretty much know what

480
00:26:03,760 --> 00:26:06,119
Speaker 1: the man is going to be plus or minus certain

481
00:26:06,119 --> 00:26:09,080
Speaker 1: amounts regardless of a recession. So what's gonna drive free

482
00:26:09,080 --> 00:26:11,560
Speaker 1: cash flow is going to be spending. And what you've

483
00:26:11,560 --> 00:26:14,040
Speaker 1: heard them say recently is, hey, you know what, we're

484
00:26:14,040 --> 00:26:17,120
Speaker 1: taking the pedal off of our spending. We're gonna fire

485
00:26:17,160 --> 00:26:19,240
Speaker 1: a bunch of people ten thousand. It's not it's not

486
00:26:19,320 --> 00:26:21,440
Speaker 1: that much relative to a million and a half employs

487
00:26:21,440 --> 00:26:23,520
Speaker 1: that they have. But they if they if they take

488
00:26:23,560 --> 00:26:26,600
Speaker 1: the pedal off and they spend ten or fifteen billion

489
00:26:26,640 --> 00:26:29,439
Speaker 1: dollars less next year, that'll go right to the to

490
00:26:29,480 --> 00:26:32,440
Speaker 1: the bottom line and free cash. Unlike Meta who constantly

491
00:26:32,440 --> 00:26:34,600
Speaker 1: said we're just gonna spend more, We're gonna blow another

492
00:26:34,600 --> 00:26:36,720
Speaker 1: ten or fifteen billion dollars on the metals because because

493
00:26:36,800 --> 00:26:39,400
Speaker 1: Zuckerberg can do that, Amazon is not acting that way.

494
00:26:39,440 --> 00:26:42,680
Speaker 1: So they have in the past. But but Bezos has

495
00:26:42,680 --> 00:26:47,040
Speaker 1: in the past, right they can turn off. Yeah, well, listen,

496
00:26:47,119 --> 00:26:48,680
Speaker 1: they haven't had to turn it off in the past.

497
00:26:48,720 --> 00:26:52,000
Speaker 1: You know, they've they've only spent money. And as we

498
00:26:52,040 --> 00:26:55,040
Speaker 1: went both as we went into COVID for instance, you know,

499
00:26:55,200 --> 00:26:58,480
Speaker 1: they spent a lot more. The demand for Amazon products

500
00:26:58,720 --> 00:27:01,160
Speaker 1: went way up eight h asked was still was still

501
00:27:01,240 --> 00:27:04,480
Speaker 1: printing cash, but the demand for for delivery of products

502
00:27:04,520 --> 00:27:07,280
Speaker 1: went way way up. So they build out a ton

503
00:27:07,600 --> 00:27:12,119
Speaker 1: more in terms of distribution facilities um uh, the the

504
00:27:12,200 --> 00:27:16,600
Speaker 1: actual distribution and buying more trucks um and they hired

505
00:27:16,640 --> 00:27:18,600
Speaker 1: a ton more people. So they're just slowing down as

506
00:27:18,600 --> 00:27:21,160
Speaker 1: the economy slows down a little bit. So they really

507
00:27:21,200 --> 00:27:22,640
Speaker 1: haven't had to take their foot off the pedal. They're

508
00:27:22,640 --> 00:27:24,600
Speaker 1: gonna do it now for a little bit. They'll protect

509
00:27:24,600 --> 00:27:27,120
Speaker 1: their bountet, and then as soon as things picked up again,

510
00:27:27,160 --> 00:27:28,800
Speaker 1: I think that they could, They'll be able to meet

511
00:27:28,840 --> 00:27:31,399
Speaker 1: demand whenever they right, I'm a salesperson. Isn't Barclays or

512
00:27:31,440 --> 00:27:34,600
Speaker 1: Bank of America one of the other underwriters who am

513
00:27:34,600 --> 00:27:39,159
Speaker 1: I calling today to buy this issue? Well, listen, he

514
00:27:39,240 --> 00:27:42,480
Speaker 1: really wants to know. Yeah, you know, listen, Mom and

515
00:27:42,480 --> 00:27:45,600
Speaker 1: pops are not the ones who are buying seventy billion

516
00:27:45,600 --> 00:27:50,920
Speaker 1: dollars worth Amazon. Pension funds, mutual funds, and insurance companies.

517
00:27:50,960 --> 00:27:55,760
Speaker 1: Those those who have you know, long want long lived assets.

518
00:27:55,760 --> 00:27:58,280
Speaker 1: They've got long lived obligation. You know. This bond deal,

519
00:27:58,440 --> 00:28:01,520
Speaker 1: in fact, is actually reasonably short duration. It's two to

520
00:28:01,600 --> 00:28:04,080
Speaker 1: ten years, and it sort of goes to show that. Listen,

521
00:28:04,560 --> 00:28:07,879
Speaker 1: Amazon's much more comfortable about short dated rates than they

522
00:28:07,880 --> 00:28:11,000
Speaker 1: are necessarily about long dated rates. But this is an

523
00:28:11,040 --> 00:28:14,840
Speaker 1: institutional bond. You know, if if for those who are

524
00:28:14,840 --> 00:28:17,920
Speaker 1: looking for yield, you're not necessarily buying Amazon. So it's

525
00:28:18,000 --> 00:28:20,159
Speaker 1: all the largest buyers that buy all this, All the

526
00:28:20,160 --> 00:28:24,120
Speaker 1: rest of these high quality buys good stuff. Rob Schiffman. Uh.

527
00:28:24,160 --> 00:28:28,000
Speaker 1: He covers all things technology from the credit perspective, and

528
00:28:28,080 --> 00:28:30,280
Speaker 1: he's in the office, and he's in the Bloomberg Interactive

529
00:28:30,280 --> 00:28:32,640
Speaker 1: Brooker studio in the office. So that means you get

530
00:28:32,680 --> 00:28:35,159
Speaker 1: a gold star. I know that's big for you. Uh,

531
00:28:35,200 --> 00:28:37,720
Speaker 1: it's big for us here to get folks in the studio.

532
00:28:40,000 --> 00:28:42,280
Speaker 1: I want to bring into Vek Rama Swamy. You know

533
00:28:42,440 --> 00:28:45,560
Speaker 1: him as the co founder and executive chairman of Strive

534
00:28:45,680 --> 00:28:49,520
Speaker 1: Asset Management. He's also the author of the book Woke Inc.

535
00:28:49,880 --> 00:28:54,880
Speaker 1: Inside Corporate America's Social Justice Scam. But he also has

536
00:28:55,040 --> 00:28:57,960
Speaker 1: recently penned an op ed in The Wall Street Journal

537
00:28:57,960 --> 00:29:02,400
Speaker 1: with Mark Lury about the fall the actacular collapse of

538
00:29:02,640 --> 00:29:05,120
Speaker 1: f t X, and so we wanted to get his

539
00:29:05,240 --> 00:29:08,520
Speaker 1: thoughts on this story. Um, that seems to just keep

540
00:29:08,560 --> 00:29:11,200
Speaker 1: on giving. Vek you know that Block five has just

541
00:29:11,280 --> 00:29:13,960
Speaker 1: filed for bankruptcy. We're all watching to see what happens

542
00:29:13,960 --> 00:29:17,800
Speaker 1: with Genesis and Gemini. Anyone who knows about this space

543
00:29:18,480 --> 00:29:22,480
Speaker 1: realizes that other shoes were waiting for other shoes to drop.

544
00:29:22,520 --> 00:29:26,280
Speaker 1: I guess, um, what do you think about the root

545
00:29:26,400 --> 00:29:29,160
Speaker 1: of the problem. Why did we all trust Sam Bankman Freed?

546
00:29:29,200 --> 00:29:32,400
Speaker 1: And what went wrong. Well, I think that there are

547
00:29:32,440 --> 00:29:35,000
Speaker 1: a lot of parallels to the two thousand eight financial crisis,

548
00:29:35,000 --> 00:29:37,320
Speaker 1: which I, um, you know, had the privilege of seeing

549
00:29:37,320 --> 00:29:39,560
Speaker 1: from a front row seat when I graduated from from

550
00:29:39,560 --> 00:29:44,200
Speaker 1: college in two thousand and seven college crisis. I graduate

551
00:29:44,200 --> 00:29:46,040
Speaker 1: from college, I went from Harvard for college, and then

552
00:29:46,040 --> 00:29:48,320
Speaker 1: I worked at a hedge fund in that fall. That

553
00:29:48,560 --> 00:29:51,520
Speaker 1: actually got an honorable mention just say I graduated from college.

554
00:29:51,520 --> 00:29:53,760
Speaker 1: If you went to Harvard, you should say I graduated

555
00:29:53,800 --> 00:29:57,080
Speaker 1: from Harvard, or I went to school in Cambridge. You know,

556
00:29:57,240 --> 00:29:59,560
Speaker 1: I think I got over that around my sophomore year.

557
00:29:59,680 --> 00:30:02,560
Speaker 1: That's that was my experience of that. But you know,

558
00:30:02,880 --> 00:30:05,600
Speaker 1: there's it turns out that it is a separate discussion

559
00:30:05,600 --> 00:30:08,120
Speaker 1: another day. I'm a little bit disappointed that Harvard isn't

560
00:30:08,120 --> 00:30:10,240
Speaker 1: really the place it was when I went there, But

561
00:30:10,320 --> 00:30:12,640
Speaker 1: that's a that's a topic for now. F TX certainly

562
00:30:12,680 --> 00:30:16,360
Speaker 1: isn't the place it was two months ago. What happened exactly.

563
00:30:16,720 --> 00:30:19,880
Speaker 1: So so look, I think that it's worth separating what's

564
00:30:20,240 --> 00:30:23,600
Speaker 1: specific to this being a crypto exchange versus what's actually

565
00:30:23,600 --> 00:30:25,560
Speaker 1: not at all specific to this being a crypto exchange,

566
00:30:25,600 --> 00:30:28,360
Speaker 1: but just a centralized exchange at all. And this is

567
00:30:28,360 --> 00:30:29,600
Speaker 1: the point I made in the piece in the Wall

568
00:30:29,600 --> 00:30:32,520
Speaker 1: Street Journal that I co authored, which is that this

569
00:30:32,560 --> 00:30:35,080
Speaker 1: was a centralized exchange, and a fundamental feature of a

570
00:30:35,120 --> 00:30:37,680
Speaker 1: centralized exchange is that you have to trust someone else,

571
00:30:37,720 --> 00:30:41,200
Speaker 1: another human being, with your money, to take custody over

572
00:30:41,240 --> 00:30:44,960
Speaker 1: your funds. A centralized exchange cannot work unless someone, someone else,

573
00:30:44,960 --> 00:30:47,600
Speaker 1: a human being, take control of your funds. That lends

574
00:30:47,640 --> 00:30:50,480
Speaker 1: itself to fraud. That fraud is illegal, whether or not

575
00:30:50,560 --> 00:30:53,560
Speaker 1: you're operating a cryptocurrency exchange or an exchange that trades

576
00:30:53,600 --> 00:30:57,880
Speaker 1: different securities. Fraud is illegal. Taking someone else's money, customers funds,

577
00:30:57,880 --> 00:30:59,960
Speaker 1: and using it for a different purpose without the permission

578
00:31:00,080 --> 00:31:02,520
Speaker 1: is fraud. I will note that's exactly what happened about

579
00:31:02,520 --> 00:31:05,480
Speaker 1: a decade ago in the MF Global scandal. People lost

580
00:31:05,520 --> 00:31:07,720
Speaker 1: their money because someone broke the law and committed fraud

581
00:31:09,480 --> 00:31:13,920
Speaker 1: gold New Jersey Governor John Corzine exactly. And so it's

582
00:31:13,920 --> 00:31:17,640
Speaker 1: worth seeing with clear eyes that this wasn't that feature

583
00:31:17,640 --> 00:31:21,200
Speaker 1: of this wasn't necessarily specific to cryptocurrencies. It was specific

584
00:31:21,240 --> 00:31:23,920
Speaker 1: to a fraudulent bad actor who used customer funds to

585
00:31:23,960 --> 00:31:26,560
Speaker 1: advance his own hands. Now you ask why wasn't this

586
00:31:26,600 --> 00:31:29,280
Speaker 1: detected earlier? And I think a big underappreciated part of

587
00:31:29,280 --> 00:31:32,920
Speaker 1: the story is that he presented himself to the public effectively,

588
00:31:33,000 --> 00:31:35,720
Speaker 1: quite effectively, I may say, as one of the good guys,

589
00:31:36,040 --> 00:31:39,080
Speaker 1: as the guy who was calling for so called responsible

590
00:31:39,120 --> 00:31:43,120
Speaker 1: regulation of cryptocurrencies, as the guy who was winning good

591
00:31:43,120 --> 00:31:45,440
Speaker 1: E s G scores and saying things that the E

592
00:31:45,640 --> 00:31:49,200
Speaker 1: s G Friendly crowd wanted him to say, making tens

593
00:31:49,200 --> 00:31:51,640
Speaker 1: of millions of dollars I think thirty million dollars plus

594
00:31:51,680 --> 00:31:55,520
Speaker 1: in this cycle alone to Democratic candidates doing the kinds

595
00:31:55,560 --> 00:31:57,560
Speaker 1: of things that the good guys are supposed to do,

596
00:31:58,080 --> 00:32:01,120
Speaker 1: just like by the way, Ralph Wintercoorts or CEO winter Corn,

597
00:32:01,160 --> 00:32:02,920
Speaker 1: I think his name is Ralph Wintercorn Winter Corners, the

598
00:32:03,000 --> 00:32:05,920
Speaker 1: last name the CEO Volkswagen who was caught in the

599
00:32:05,960 --> 00:32:10,320
Speaker 1: emissions cheating only after exactly Martin winter Corn excuse me, is,

600
00:32:10,360 --> 00:32:15,000
Speaker 1: shortly after they had actually won multiple E s G awards,

601
00:32:15,040 --> 00:32:17,880
Speaker 1: Shortly after he had spent years waxing eloquent about the

602
00:32:17,880 --> 00:32:20,560
Speaker 1: climate transition. Guess who turns out to be the bad,

603
00:32:20,640 --> 00:32:23,280
Speaker 1: the worst of the actors of all. It's actually the

604
00:32:23,320 --> 00:32:25,640
Speaker 1: company that pretended to be one of the good guys,

605
00:32:26,160 --> 00:32:28,440
Speaker 1: and so I think we learned this lesson time and

606
00:32:28,520 --> 00:32:32,760
Speaker 1: again that human beings and markets and customers and citizens

607
00:32:33,280 --> 00:32:38,600
Speaker 1: are pretty good at holding bad actors accountable as long

608
00:32:38,600 --> 00:32:41,280
Speaker 1: as you don't throw a trip wire in the system,

609
00:32:41,320 --> 00:32:44,320
Speaker 1: as long as you don't tamper with the smoke detector. Okay,

610
00:32:44,320 --> 00:32:46,160
Speaker 1: but one of the ways some of these guys, be

611
00:32:46,320 --> 00:32:49,760
Speaker 1: from from winter Corn to SBF now, managed to tamper

612
00:32:49,840 --> 00:32:53,360
Speaker 1: with the smoke detector is that they presented this smoke

613
00:32:53,440 --> 00:32:56,840
Speaker 1: screen of virtue that I think otherwise turned off the

614
00:32:56,880 --> 00:33:00,880
Speaker 1: public's radar to picking up on the signal that otherwise

615
00:33:00,880 --> 00:33:03,000
Speaker 1: would have caused them to pick up on on the

616
00:33:03,000 --> 00:33:06,680
Speaker 1: fraud much sooner the vect does crypto broadly defined need

617
00:33:06,760 --> 00:33:12,360
Speaker 1: to be regulated. So I think that a knee jerk

618
00:33:12,560 --> 00:33:16,040
Speaker 1: regulatory response on the back of this, and a catch

619
00:33:16,080 --> 00:33:20,840
Speaker 1: all regulatory approach that did not draw distinctions between centralized

620
00:33:20,880 --> 00:33:25,520
Speaker 1: and decentralized exchanges would be a bad idea. That being said,

621
00:33:25,640 --> 00:33:29,040
Speaker 1: I think the legal regime as it exists in ways

622
00:33:29,120 --> 00:33:34,800
Speaker 1: that prevent fraud for non cryptocurrency based securities non cryptocurrency

623
00:33:34,840 --> 00:33:40,440
Speaker 1: based assets absolutely should and does already apply to cryptocurrency

624
00:33:40,480 --> 00:33:42,520
Speaker 1: as well, it just is a question of the ability

625
00:33:42,560 --> 00:33:46,600
Speaker 1: to enforce those standards evenly. You can't steal someone else's funds,

626
00:33:46,600 --> 00:33:49,400
Speaker 1: that's illegal. If you're a fiduciary, or if you're a

627
00:33:49,440 --> 00:33:52,800
Speaker 1: custodian of someone else's funds, you cannot misuse those for

628
00:33:52,880 --> 00:33:55,360
Speaker 1: your own purposes. So in a certain sense, that's not

629
00:33:55,480 --> 00:34:00,120
Speaker 1: new regulation. That's just the application of basic legal principles

630
00:34:00,160 --> 00:34:04,720
Speaker 1: of trust, principles of fiduciary, principles of non theft, principles

631
00:34:04,720 --> 00:34:08,520
Speaker 1: of non misappropriation, principles that exist in the law for assets,

632
00:34:08,520 --> 00:34:11,320
Speaker 1: have existed in the common law for hundreds of years

633
00:34:11,360 --> 00:34:13,239
Speaker 1: that need to be applied in the same way to

634
00:34:13,280 --> 00:34:16,040
Speaker 1: cryptocurrencies as they are to any other assets. And so

635
00:34:16,120 --> 00:34:19,200
Speaker 1: my view is that crypto doesn't get a special pass

636
00:34:19,280 --> 00:34:22,400
Speaker 1: from those rules just because people call it crypto, But

637
00:34:22,560 --> 00:34:26,560
Speaker 1: nor should we overreact to create a crypto specific regime.

638
00:34:26,960 --> 00:34:30,080
Speaker 1: That's it. That's actually, ironically what SPF was exactly calling for.

639
00:34:30,520 --> 00:34:32,479
Speaker 1: He might make his own wish come true. All right, vac,

640
00:34:32,560 --> 00:34:34,240
Speaker 1: thank you so much once again for joining has always

641
00:34:34,320 --> 00:34:37,520
Speaker 1: learned something there. Ramaswanna, co founder and executive chairman of

642
00:34:37,560 --> 00:34:43,080
Speaker 1: Strive Asset Management, you know that it is Giving Tuesday,

643
00:34:43,120 --> 00:34:45,239
Speaker 1: although I know for you every day is giving twos

644
00:34:45,280 --> 00:34:49,600
Speaker 1: a giar a giver. But we want to talk about education, UM,

645
00:34:49,719 --> 00:34:53,960
Speaker 1: nonprofits things like that, because the pandemic has really done

646
00:34:53,960 --> 00:34:58,040
Speaker 1: a job on the educational UH environment out there and

647
00:34:58,160 --> 00:35:00,600
Speaker 1: particularly for for younger children. So we want to kind

648
00:35:00,600 --> 00:35:02,040
Speaker 1: of break that down and get a little sense of

649
00:35:02,040 --> 00:35:03,200
Speaker 1: what's going on out there. What are some of the

650
00:35:03,239 --> 00:35:05,319
Speaker 1: good stories, what are some of the challenges for that.

651
00:35:05,360 --> 00:35:07,880
Speaker 1: We can get an excellent roundtable here in our Bloomberg

652
00:35:07,880 --> 00:35:11,200
Speaker 1: Interactive Broker studio. Angela Williams c you have Common Denominator

653
00:35:11,840 --> 00:35:16,200
Speaker 1: joins us as well as Marian Scordell with Bourgeville Consulting.

654
00:35:16,400 --> 00:35:19,319
Speaker 1: Close enough, good, awesome, Awesome, I did that again, two

655
00:35:19,320 --> 00:35:22,680
Speaker 1: for two UM. Alright, so angel let's start with you.

656
00:35:22,760 --> 00:35:24,920
Speaker 1: Just talk to us about Common Denominator. What are you

657
00:35:24,960 --> 00:35:27,720
Speaker 1: guys doing at Common Denominator. Well, I think a Common

658
00:35:27,760 --> 00:35:31,319
Speaker 1: Denominator we give the gift that keeps on giving UM,

659
00:35:31,400 --> 00:35:35,000
Speaker 1: and that's the gift of of of math numeracy UH.

660
00:35:35,080 --> 00:35:39,239
Speaker 1: Common Denominator is a nonprofit organization that provides free, holistic

661
00:35:39,360 --> 00:35:42,799
Speaker 1: math tutoring to middle school students who are really struggling

662
00:35:42,840 --> 00:35:47,120
Speaker 1: with basic numeracy, math numeracy UM and and really struggling

663
00:35:47,560 --> 00:35:51,160
Speaker 1: UM in their maths class. You know, our mission is

664
00:35:51,200 --> 00:35:54,120
Speaker 1: to help underserved middle school students improve their math skills,

665
00:35:54,160 --> 00:35:58,200
Speaker 1: build confidence, and enjoy doing So how did it evolve

666
00:35:58,480 --> 00:36:02,719
Speaker 1: devolve during the past two and a half three years? Okay, Well,

667
00:36:02,760 --> 00:36:05,960
Speaker 1: you know, prior to the pandemic, we knew that our

668
00:36:05,960 --> 00:36:10,320
Speaker 1: middle school students were having a significant problem in in math,

669
00:36:10,400 --> 00:36:13,200
Speaker 1: and we knew the causes, and so we were diligent

670
00:36:13,280 --> 00:36:16,400
Speaker 1: about providing a place where we were going to provide

671
00:36:16,400 --> 00:36:20,239
Speaker 1: the resources and tools for them. Of course, unfortunately, the

672
00:36:20,520 --> 00:36:24,880
Speaker 1: COVID nineteen pandemic landed more underserved students on the vulnerable

673
00:36:24,880 --> 00:36:28,600
Speaker 1: side of an even larger achievement gap. So, you know,

674
00:36:28,760 --> 00:36:32,480
Speaker 1: it has been incredible for our organization because as we

675
00:36:32,640 --> 00:36:36,480
Speaker 1: pivoted from in person to online, we've been able to

676
00:36:36,560 --> 00:36:41,040
Speaker 1: open up our program to a wider uh swath of

677
00:36:41,160 --> 00:36:45,040
Speaker 1: students across New York City um and and it has

678
00:36:45,120 --> 00:36:47,880
Speaker 1: been very effective for our students as well as for

679
00:36:47,920 --> 00:36:51,680
Speaker 1: our organization. So, Marian, how do you come into this discussion?

680
00:36:51,800 --> 00:36:55,520
Speaker 1: How did you and Angela meet? How have you got involved? Well,

681
00:36:55,560 --> 00:36:58,080
Speaker 1: we I we met through my neighbors really, but it

682
00:36:58,239 --> 00:37:00,920
Speaker 1: was probably listening to us actually, but I hope so,

683
00:37:01,000 --> 00:37:06,560
Speaker 1: but I shout out your neighbor Andrew, Thanks Andrew. So

684
00:37:06,680 --> 00:37:09,000
Speaker 1: no I came. I came to comment the dominator because

685
00:37:09,040 --> 00:37:11,120
Speaker 1: I have a background in financial services. I worked in

686
00:37:11,200 --> 00:37:14,400
Speaker 1: investment bank. I'm running my own business, and I know

687
00:37:14,440 --> 00:37:17,319
Speaker 1: what education did for me. So I don't come from

688
00:37:17,320 --> 00:37:19,840
Speaker 1: from a private edge background at all, and yet I

689
00:37:19,880 --> 00:37:21,479
Speaker 1: was able to go talk so that I I was able

690
00:37:21,520 --> 00:37:23,399
Speaker 1: to now that I teach sometimes at Yale and at

691
00:37:23,400 --> 00:37:26,839
Speaker 1: other universities, and I know what education can do for you.

692
00:37:26,920 --> 00:37:29,160
Speaker 1: I know how it can get you out of you know,

693
00:37:29,200 --> 00:37:31,960
Speaker 1: it can brought on your horizons, it can open up careers,

694
00:37:32,000 --> 00:37:33,959
Speaker 1: it can open up a future, and then in turn

695
00:37:34,360 --> 00:37:36,640
Speaker 1: you have to help others. So that's that's where I

696
00:37:36,680 --> 00:37:39,600
Speaker 1: fit in. And can I also point out, um, I

697
00:37:39,640 --> 00:37:42,600
Speaker 1: don't want it to be overlooked that it can be

698
00:37:42,760 --> 00:37:45,799
Speaker 1: very helpful for the bank or the organization to have

699
00:37:46,000 --> 00:37:50,960
Speaker 1: a more diverse group of mimes working on problem. Absolutely

700
00:37:51,200 --> 00:37:53,279
Speaker 1: when I was in bank, and even now when I

701
00:37:53,360 --> 00:37:55,440
Speaker 1: we know if I have to recruit, I'm like all

702
00:37:55,440 --> 00:37:57,920
Speaker 1: the candidates come from exactly the same background that or

703
00:37:57,960 --> 00:38:00,640
Speaker 1: exactly all the same, and we're you know, we are

704
00:38:00,640 --> 00:38:04,120
Speaker 1: pushed to bring more diversity into organizations. But the thing is,

705
00:38:04,440 --> 00:38:06,560
Speaker 1: if all the candidates come from the same place, there's

706
00:38:06,600 --> 00:38:09,319
Speaker 1: a very narrow pool of candidates to choose from. So

707
00:38:09,360 --> 00:38:11,680
Speaker 1: I think the problem has to be addressed a lot earlier,

708
00:38:11,800 --> 00:38:14,399
Speaker 1: by the time you know, the past middle school. I'm

709
00:38:14,440 --> 00:38:16,439
Speaker 1: not saying it's too late, because it's never too late,

710
00:38:16,920 --> 00:38:19,440
Speaker 1: but it would help you at an earlier stage. We

711
00:38:19,480 --> 00:38:22,640
Speaker 1: would help students instead of helping them just at university stage.

712
00:38:22,880 --> 00:38:25,160
Speaker 1: So Angela, when when you get these students at a

713
00:38:25,200 --> 00:38:27,719
Speaker 1: young age and you're focusing on maths, it's all part

714
00:38:27,719 --> 00:38:30,200
Speaker 1: of this the stem focus that we hear so much

715
00:38:30,280 --> 00:38:34,040
Speaker 1: about in education. What are some of the key challenges

716
00:38:34,560 --> 00:38:38,200
Speaker 1: for math? Is math just harder for some students than

717
00:38:38,280 --> 00:38:42,000
Speaker 1: others uh skills or other subjects, or is it more

718
00:38:42,040 --> 00:38:44,320
Speaker 1: on the on the instruction side. What's kind of some

719
00:38:44,400 --> 00:38:46,879
Speaker 1: of the challenges. I think the key challenge is that,

720
00:38:46,960 --> 00:38:49,040
Speaker 1: you know, we are all math people, and if we

721
00:38:49,080 --> 00:38:52,479
Speaker 1: start to understand that and gravitate towards that, we won't

722
00:38:52,480 --> 00:38:55,399
Speaker 1: have the challenges that we do imagine being seen as

723
00:38:55,440 --> 00:38:57,720
Speaker 1: part of a group taught to believe that they could

724
00:38:57,800 --> 00:39:02,080
Speaker 1: not excel in math. Uh, imagine the repercussions of believing

725
00:39:02,200 --> 00:39:05,680
Speaker 1: that false notion your entire life, um and and really

726
00:39:05,760 --> 00:39:09,960
Speaker 1: imagine having an additional impediment, you know, to your own

727
00:39:10,040 --> 00:39:13,920
Speaker 1: upward mobility. You're you know, we're potentially from middle school

728
00:39:13,960 --> 00:39:18,560
Speaker 1: students who prior to the pandemic only about thirty six

729
00:39:18,640 --> 00:39:21,440
Speaker 1: percent of them were even fluent in math by eighth grade.

730
00:39:21,960 --> 00:39:25,439
Speaker 1: Now add on the troubles of the pandemic, and we're

731
00:39:25,440 --> 00:39:28,400
Speaker 1: talking about you know, students of color and those in

732
00:39:28,480 --> 00:39:31,840
Speaker 1: low income brackets who are suffering even more from the

733
00:39:32,000 --> 00:39:36,840
Speaker 1: from the inequities and the education gap. So potentially, according

734
00:39:36,880 --> 00:39:40,720
Speaker 1: to to what Mary Anne said, they are not identifying

735
00:39:40,760 --> 00:39:44,120
Speaker 1: with math, and therefore they're cutting off an entire industry

736
00:39:44,560 --> 00:39:48,080
Speaker 1: that could really allow them to become upwardly mobile jobs

737
00:39:48,160 --> 00:39:52,480
Speaker 1: like you know, medical scientists, financial and analysts, the statisticians,

738
00:39:52,760 --> 00:39:57,520
Speaker 1: actuary economists, not even considering them, not considering banking um

739
00:39:57,560 --> 00:40:00,239
Speaker 1: and that is critical, that's critical and some thing that

740
00:40:00,280 --> 00:40:03,680
Speaker 1: we have to really work towards so that our students

741
00:40:03,680 --> 00:40:07,680
Speaker 1: can understand and hoards and sometimes the barriers are really psychological.

742
00:40:07,760 --> 00:40:09,920
Speaker 1: So sometimes they wouldn't even think of an industry that

743
00:40:10,000 --> 00:40:12,400
Speaker 1: is so remote that nobody in their families work in.

744
00:40:12,600 --> 00:40:15,399
Speaker 1: So we are also as part of common denominator, we're

745
00:40:15,480 --> 00:40:19,440
Speaker 1: organizing bank visits. So we're bringing small groups of middle

746
00:40:19,440 --> 00:40:21,960
Speaker 1: school children. We're bringing them to see what the trading

747
00:40:22,000 --> 00:40:24,800
Speaker 1: floor is, you know what. So because in their minds,

748
00:40:24,840 --> 00:40:26,759
Speaker 1: this is just not for them. So that's why they

749
00:40:26,760 --> 00:40:30,960
Speaker 1: wouldn't consider these careers that they feel from the start excluded. Um,

750
00:40:31,000 --> 00:40:32,839
Speaker 1: So that that's one of one of the things we're doing.

751
00:40:32,880 --> 00:40:35,640
Speaker 1: It's not just the education, is also the psychological barriers.

752
00:40:35,719 --> 00:40:38,160
Speaker 1: And I mean I imagine that mentoring would be important

753
00:40:38,160 --> 00:40:40,600
Speaker 1: as well. Right, a lot of these kids, you know,

754
00:40:41,160 --> 00:40:44,120
Speaker 1: their parents are unlikely to be involved in the financial industry.

755
00:40:44,200 --> 00:40:46,239
Speaker 1: Maybe they don't even know anybody in the neighborhood who's

756
00:40:46,239 --> 00:40:48,520
Speaker 1: involved in the financial industry. So I'm sure it would

757
00:40:48,520 --> 00:40:52,200
Speaker 1: help to connect them with Angela was someone like Mary Anne. Absolutely,

758
00:40:52,239 --> 00:40:57,279
Speaker 1: that's exactly what we're doing. So what's what's it like

759
00:40:57,360 --> 00:40:59,799
Speaker 1: in a a New York City public school today? From

760
00:40:59,840 --> 00:41:04,600
Speaker 1: a math perspective? I mean, what are I know when

761
00:41:05,000 --> 00:41:09,560
Speaker 1: other schools, maybe some you know, math is really a focus?

762
00:41:09,719 --> 00:41:12,200
Speaker 1: Is it focus? Does it get the proper you know

763
00:41:12,360 --> 00:41:15,520
Speaker 1: weight do you think you know? That's a great question. UM.

764
00:41:15,960 --> 00:41:18,160
Speaker 1: I actually have the results from the New York State

765
00:41:18,200 --> 00:41:22,319
Speaker 1: Department of Education recently released assessment, and some of their

766
00:41:22,400 --> 00:41:25,359
Speaker 1: key findings UH state that less than half of all

767
00:41:25,360 --> 00:41:29,560
Speaker 1: students in grades three through eight are proficient in math proficiency.

768
00:41:29,640 --> 00:41:32,439
Speaker 1: Rates for students from low income backgrounds continue to lack

769
00:41:32,520 --> 00:41:36,040
Speaker 1: the rates of their more affluent peers. UM. Across all

770
00:41:36,080 --> 00:41:40,400
Speaker 1: the racial groups, there were losses in math proficiency. However,

771
00:41:40,440 --> 00:41:45,399
Speaker 1: the proficiency gaps between racial groups were alarmingly wide. UM.

772
00:41:45,480 --> 00:41:48,160
Speaker 1: And and you know there there's there's year to year

773
00:41:48,239 --> 00:41:53,080
Speaker 1: decline in math preferences proficiency for all students including eighth grade. Yeah,

774
00:41:53,200 --> 00:41:56,719
Speaker 1: so the data is not too supportive at the moment.

775
00:41:56,760 --> 00:41:59,360
Speaker 1: I'm sure the pandemic just made the challenge is more pronounced.

776
00:41:59,360 --> 00:42:02,200
Speaker 1: But four trained. There's good folks out there like YouTube

777
00:42:02,239 --> 00:42:04,279
Speaker 1: kind of doing your best to kind of help out.

778
00:42:04,320 --> 00:42:08,400
Speaker 1: Angela Williams, CEO of Common Denominator and Mary Anne Scoordell

779
00:42:08,840 --> 00:42:11,600
Speaker 1: with Bougeville Consulting, both joining us here boats kind of

780
00:42:11,680 --> 00:42:14,759
Speaker 1: joining powers, if you will, joining resources and trying to

781
00:42:14,760 --> 00:42:19,359
Speaker 1: make a big impact on this issue and about ten

782
00:42:19,360 --> 00:42:22,120
Speaker 1: seconds left. Yeah. Absolutely, this Giving Tuesday, give the gift

783
00:42:22,160 --> 00:42:26,239
Speaker 1: that keeps on giving. Absolutely, thank you very much. Matthcy

784
00:42:26,440 --> 00:42:30,680
Speaker 1: absolutely good, absolutely correct and financial literacy right also very

785
00:42:30,760 --> 00:42:37,200
Speaker 1: key at a young age. Yep, very good stuff. Thanks

786
00:42:37,239 --> 00:42:40,680
Speaker 1: for listening to the Bloomberg Markets podcast. You can subscribe

787
00:42:40,719 --> 00:42:44,400
Speaker 1: and listen to interviews with Apple Podcasts or whatever podcast

788
00:42:44,480 --> 00:42:48,040
Speaker 1: platform you prefer. I'm Matt Miller. I'm on Twitter at

789
00:42:48,080 --> 00:42:51,680
Speaker 1: Matt Miller, three pen on Fall Sweeney I'm on Twitter

790
00:42:51,760 --> 00:42:54,600
Speaker 1: at pt Sweeney before the podcast. You can always catch

791
00:42:54,640 --> 00:42:56,200
Speaker 1: us worldwide at Bloomberg Radio