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Speaker 1: Hello, and welcome to another episode of the Odd Thoughts Podcast.

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Speaker 1: I'm Tracy Allaway and I'm Joe. WI isn't all so, Joe?

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Speaker 1: I think equity markets have been um getting all the

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Speaker 1: attention lately. Yeah, for good reason. Um, you know, the

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Speaker 1: index level is extremely high, individual stocks all kinds of

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Speaker 1: wild stories. But I am aware that there's also some

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Speaker 1: interesting stuff in credit markets. I it's not getting as

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Speaker 1: much attention, but I've kind of I'm aware that there's

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Speaker 1: some stuff going on. Yeah, we're gonna try to fix

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Speaker 1: the imbalance of of attention. In this episode. We're going

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Speaker 1: to get very very um technical and a little bit

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Speaker 1: wonky and take a look at not just credit as

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Speaker 1: you mentioned, corporate bonds, but um, we'll also look at

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Speaker 1: things like US treasuries. Um, what's going on there? So

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Speaker 1: I should just say, as we're recording this episode, I

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Speaker 1: was just looking at the yield on the thirty year

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Speaker 1: and that's getting up to almost two per cent, which

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Speaker 1: is a nice round number that people like to focus on.

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Speaker 1: But the question, of course, is when we talk about

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Speaker 1: bond yields, when we talk about bond prices, what exactly

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Speaker 1: are we talking about. None of these trade on an exchange,

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Speaker 1: So where does that pricing information come from? Yeah, this

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Speaker 1: is always a fascinating question. We've discussed it in various

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Speaker 1: forms a few times with Chris White as as well

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Speaker 1: as others. Which is just this idea that Okay, everyone

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Speaker 1: can look up on their monitor and see a quote

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Speaker 1: for the say, um, you know, price of Microsoft shares,

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Speaker 1: and we know where that comes from, and there's sort

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Speaker 1: of like some sort of central repository for that. But

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Speaker 1: in the world of fixed income, whether it's a sort

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Speaker 1: of credit or rates, pricing is at a minimum much

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Speaker 1: more distributed across all different kinds of platforms, all different

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Speaker 1: kinds of players. In the idea that they're just sort

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Speaker 1: of like one agreed upon price is um, it's not

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Speaker 1: as much of a thing at all. Yeah, that's exactly right.

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Speaker 1: And it's the kind of thing that people don't tend

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Speaker 1: to talk about unless something bad is happening in the market,

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Speaker 1: at which point suddenly everyone starts talking about bond pricing

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Speaker 1: and what exactly, um, the process is there. And we

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Speaker 1: saw a little bit of that in during the big

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Speaker 1: market sell off. Of course, we had a lot of

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Speaker 1: turmoil in credit. We also had a lot of turmoil

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Speaker 1: in the U. S. Treasury market, and that's when people

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Speaker 1: started talking about discrepancies in bond prices, which is it's

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Speaker 1: never a good sign, is it. Uh No, it's like basically,

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Speaker 1: you know, with all these things, it's like, once you

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Speaker 1: have to start learning, by the time you're learning about

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Speaker 1: how something actually works, usually that means trouble him. Yeah, exactly.

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Speaker 1: So okay, yes, So today, um, we're going to be

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Speaker 1: diving into the topic of bond pricing and we're gonna

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Speaker 1: be talking to the authors of a paper that came

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Speaker 1: out in January, a really really interesting paper by morning Star.

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Speaker 1: It's called Bond Pricing Agreeing to Disagree and uh basically

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Speaker 1: the authors on that crunched a bunch of numbers to

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Speaker 1: really look at how different funds are pricing bonds and

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Speaker 1: the discrepancies that are going on. So really interesting. Um So,

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Speaker 1: without further ado, then let's bring on Eric Jacobson. He's

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Speaker 1: a fixed income strategist at morning Star, and we'll bring

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Speaker 1: on his co author as well, match Up Kawara. Thank

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Speaker 1: you both for coming on, glad to be with you,

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Speaker 1: thanks for having us. So, I guess first things first,

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Speaker 1: but you know, Joe and I were joking a bit

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Speaker 1: about how people don't tend to look at the technicals

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Speaker 1: of bond pricing unless things are going wrong. What prompted

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Speaker 1: you to do the paper? Well, there are a few

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Speaker 1: things I think, you know, I hate to use the

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Speaker 1: cliche that that crises are an opportunity, but when you're

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Speaker 1: in the when you when you look at bond bonds

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Speaker 1: and bond funds, the most exciting stuff always happens when

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Speaker 1: something goes wrong. And that's really what happened as usual

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Speaker 1: in in March, and we started thinking about what we

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Speaker 1: might see in the data at that period of time.

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Speaker 1: And there's a relatively new filing that is required by

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Speaker 1: the SEC called MPort, which is really an electronic version

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Speaker 1: of a portfolio filing, essentially almost the same as an

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Speaker 1: annual report UM, but for you know, reasons that most

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Speaker 1: people wouldn't really care about. Having it digitized makes a

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Speaker 1: huge difference in being able to deal with the data.

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Speaker 1: And so it gave us an opportunity, because obviously we

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Speaker 1: collect that stuff across the industry. UM, it gave us

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Speaker 1: an opportunity to pull some of the data that was

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Speaker 1: that we knew would be very clean or as clean

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Speaker 1: as we could imagine it to be given how it's

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Speaker 1: submitted to the SEC and look at how different firms

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Speaker 1: price their bonds at the end of a particular day,

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Speaker 1: which you know, it's been possible to do that in

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Speaker 1: the past, but as I just sort of alluded about

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Speaker 1: the filing issue, it would have been it was a

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Speaker 1: lot more difficult and a lot more difficult to do

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Speaker 1: knowing for sure that the that the data was going

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Speaker 1: to be filed consistently. So, uh, you know, unfortunately a

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Speaker 1: very bad time in the market for a lot of people,

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Speaker 1: third quarter at the end of the first quarter, but

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Speaker 1: not a terrible time to do research. So what was

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Speaker 1: your most striking finding in terms of the different prices

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Speaker 1: that can emerge on the same security, the same bond,

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Speaker 1: and the different approaches that a different holder took in

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Speaker 1: their prices. Sure, so, you know, the first thing I

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Speaker 1: would say is that we did not expect to see

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Speaker 1: prices sort of on top of each other perfectly aligned.

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Speaker 1: For some of the is I think that that you

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Speaker 1: guys alluded to, But you know, some of it is

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Speaker 1: just sort of structural in the sense of when when

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Speaker 1: bond portfolios are marked, they're marked at the end of

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Speaker 1: the day, and it's handled in slightly different ways depending

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Speaker 1: on the firm that's doing it and some of the

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Speaker 1: decisions that they make about pricing. So one of them

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Speaker 1: is simply what time of day, and you can price

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Speaker 1: bond portfolios that either three o'clock or flour o'clock. It

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Speaker 1: seems that there's a lot more consistently, and there used

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Speaker 1: to be a lot more firms are doing at three

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Speaker 1: o'clock hour, but there is some diversity in that they

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Speaker 1: also have the option of choosing to price either at

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Speaker 1: the bid or the ask or the mid and so

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Speaker 1: that's just another layer of difference there. And most firms

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Speaker 1: are also, well pretty much all the firms that we

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Speaker 1: know of a all use third party pricing services. And

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Speaker 1: so then you add to add to the fact that

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Speaker 1: there are a multitude, not not a huge number, but

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Speaker 1: there are different services. So once you get through all

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Speaker 1: three of those lenses, it's certainly posible for prices to

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Speaker 1: be somewhat different. And you know, I think that the

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Speaker 1: key issue here, I think you guys were talking before

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Speaker 1: about the end of day price for a stock. Part

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Speaker 1: of the reason for this that we have this issue

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Speaker 1: is that um even if you are able to observe

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Speaker 1: a price, you know, at two o'clock in the afternoon

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Speaker 1: for a particular bond, and it's recorded by FINNRA, that's

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Speaker 1: the regulator, and it's disseminated through trace, which is a

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Speaker 1: reporting system. If that's not the price, if if that

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Speaker 1: trade doesn't happen anywhere near the close of the market,

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Speaker 1: then the somebody has to look at what that bond

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Speaker 1: and say, well, this is what the price should have

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Speaker 1: been at the end of the day, because the market

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Speaker 1: shifted between the last trade and now, and we really

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Speaker 1: need to change the price to reflect that. And that's

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Speaker 1: part of you know, where you get all this difference.

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Speaker 1: Of course, as we mentioned in the paper, there are

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Speaker 1: lots of bonds that don't trade at all in a

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Speaker 1: single day either, so that complicates things as well. Finally,

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Speaker 1: I would say there's always a possibility that that the

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Speaker 1: asset amount you can challenge the price that comes from

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Speaker 1: from pricing service. So that's that as another layer of complexity.

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Speaker 1: You know that they they may think that they know

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Speaker 1: the real value of that bond better than the pricing agency,

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Speaker 1: which which is quite conceivably true. If one manager challenges

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Speaker 1: the bond and another firm doesn't, then you know, prices

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Speaker 1: might look different for that reason as well. Can you

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Speaker 1: talk a little bit more about the third party pricing services,

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Speaker 1: because I think this is sort of whenever people hear

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Speaker 1: about this UM for the first time, I think it's

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Speaker 1: difficult for a lot of people to get their heads

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Speaker 1: around that there are actually companies out there whose job

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Speaker 1: is to kind of triangulate the price of a corporate bond. Sure,

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Speaker 1: so it's interesting because you know, people will sometimes ask,

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Speaker 1: you know, why wouldn't you just price the bond yourself

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Speaker 1: if you're a manager, and as much it just eluded

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Speaker 1: maybe in some cases a bond that's not widely held,

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Speaker 1: maybe the manager it knows even more about it. The

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Speaker 1: pricing service. You know that the truth is is that

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Speaker 1: we've evolved into this system because the goal is to

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Speaker 1: have a third party or an arms length party, if

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Speaker 1: you will, UM making those pricing determinations, to sort of

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Speaker 1: remove the manager a step away from that decision. Since

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Speaker 1: the decision that the manager, the decision that's made on

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Speaker 1: that price can affect the performance of an account that

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Speaker 1: a manager is running, and so forth. And it's the

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Speaker 1: kind of thing that has evolved over the years. Um,

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Speaker 1: I haven't been involved in bond pricing directly, so it's uh,

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Speaker 1: you know, I don't have the full history of the

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Speaker 1: industry at my fingertips, but I can tell you that

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Speaker 1: pricing has historically a lot of that information has come

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Speaker 1: from broker dealers themselves, so uh, and even today, the

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Speaker 1: pricing services do talk to the broke dealers, and there

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Speaker 1: are pricing services that are associated on some cases with

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Speaker 1: broker dealers as well, so it's kind of a mix there.

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Speaker 1: But you know, the idea is that, um, when you

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Speaker 1: have a portfolio of you know, a hundred and fifty

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Speaker 1: different bonds or maybe a thousand when you're talking about

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Speaker 1: mortgages are a very large mutual fund, you need to

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Speaker 1: be able to gather market information very very quickly in

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Speaker 1: order to that kind of pricing. So it makes sense

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Speaker 1: to have a third party do it. And one of

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Speaker 1: the advantages of having an agency that's that's sort of

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Speaker 1: independent is that they can be in touch with multiple dealers,

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Speaker 1: they can take in all the data feeds, and they

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Speaker 1: also have systems in place so that, um, if there

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Speaker 1: isn't any really fresh information, but they have a signpost

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Speaker 1: of some kind to work off of for example, you

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Speaker 1: know that the bond has this level of maturity, you

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Speaker 1: know that it has this credit rating, it's in this sector,

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Speaker 1: and etcetera. You can sort of triangulate a prices. I

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Speaker 1: think someone said, um, they use a lot of different

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Speaker 1: tools for that. Some of them are now they're starting

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Speaker 1: to use AI for some of that stuff. But the

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Speaker 1: idea of fundamentally is to try and get that to

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Speaker 1: be as dispassionate as as decision as possible. UM. And

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Speaker 1: you know, one of the things that we talked about

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Speaker 1: in the paper is one of the reasons that you

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Speaker 1: have some differentiation aside from the other factors, is that

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Speaker 1: there are a good handful of pricing services, and some

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Speaker 1: firms may use a single service for everything, but most

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Speaker 1: of the larger mutual fund managers that most people are

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Speaker 1: invested with, UH pick and choose among the services depending

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Speaker 1: on the asset class that they're that they're using. And

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Speaker 1: then UH and so, for example, you know, if they

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Speaker 1: are looking at one particular kind of mortgage bond for

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Speaker 1: a private mortgage security, the kind that blew up during

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Speaker 1: a crisis, they may use a single pricing service just

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Speaker 1: for that and use somebody else for for all the

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Speaker 1: other sectors, So you know, this comes up every once

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Speaker 1: in a while. Obviously, Q one of last year was

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Speaker 1: one time, I forget, what is it, tracy, when were

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Speaker 1: we talking about like energy bonds in the junk bond

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Speaker 1: E t F like years ago. I feel like that

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Speaker 1: was late, I want to say, although, yeah, I think

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Speaker 1: it happened. No, I think, but I want so yeah, yeah,

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Speaker 1: I think it was late. And I know there's like

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Speaker 1: a bunch there's like an oil crash or a bunch

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Speaker 1: of junk bond E t F got dislocated. Hasn't really

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Speaker 1: been a problem yet, this question of ambiguous bond pricing

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Speaker 1: of instruments that don't trade, because I know there's all

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Speaker 1: these questions that emerge about the sort of liquidity mismatch

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Speaker 1: where the bonds don't really move, but the E t

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Speaker 1: F that or the funds that own the bonds have

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Speaker 1: to provide daily prices or even intramarket daily liquidity. How

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Speaker 1: big of an issue is this because so far it

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Speaker 1: seems like mostly the infrastructure has work. Yeah, I think.

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Speaker 1: You know, one of the benefits of the mutual fund

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Speaker 1: structure in particular is that you know a lot of

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Speaker 1: these differences get kind of washed out on a large portfolio.

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Speaker 1: So even in a mutual fund that you know that

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Speaker 1: has truly billions and billions of dollars, even if there

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Speaker 1: are a good handful of bonds where the pricing seems

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Speaker 1: to be all over the map, you know, when you

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Speaker 1: when you add all that up and average it out,

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Speaker 1: they turn out to be kind of rounding errors in

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Speaker 1: a lot of cases. UM we still have some research

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Speaker 1: to do on that, because we haven't gone through the

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Speaker 1: entire universe and done it at the fund by fund level,

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Speaker 1: but that seems to be the case for the most part.

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Speaker 1: You know. The big problem, as you alluded though, is

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Speaker 1: when you wind up in a big crisis situation, and

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Speaker 1: the more concentrated a portfolio, and the worst the crisis

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Speaker 1: and the longer at last, the bigger problem that can be.

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Speaker 1: And of course you know this isn't exclusive to bonds.

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Speaker 1: It doesn't happen, you don't notice it nearly as often

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Speaker 1: with equities, but that you alluded to earlier, you know,

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Speaker 1: if you have private placements in a mutual fund or

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Speaker 1: you know, very very large slugs of a of a

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Speaker 1: private company that's spread around UM, and and that happens

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Speaker 1: you know, often with with young uh startup companies, where

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Speaker 1: small cap funds get involved, why to put big tech names?

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Speaker 1: There can be disagreements about things like that too. Usually

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Speaker 1: it's not that big a deal to small investors when

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Speaker 1: you have diversified funds um But as I said, crisis

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Speaker 1: last lasts long enough, or you have a concentrated enough portfolio,

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Speaker 1: that's when it really starts to make a difference. So

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Speaker 1: can we talk about that a little bit more in

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Speaker 1: your paper? What exactly what was the difference in bond

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Speaker 1: pricing differences in normal times versus something like the first

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Speaker 1: quarter of twenty twenty, because I think your study looked

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Speaker 1: at late which was a relatively calm period in markets,

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Speaker 1: and then the end of March. So what was the

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Speaker 1: difference between those two periods? Sure, so, as you alluded,

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Speaker 1: we we started in September, and just to clarify, you know,

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Speaker 1: we used quarter end data and so this was essentially

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Speaker 1: data on the last day of the quarter, at the

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Speaker 1: end of the day and looked across funds and across

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Speaker 1: bonds that were appearing in more than one fund. Well,

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Speaker 1: this is kind of a nuanced in and of itself.

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Speaker 1: But when I say more than one. What I really

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Speaker 1: mean is more than one firms funds because each firm,

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Speaker 1: no matter how many funds they have, if they own

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Speaker 1: the same bond across multiple funds, the structure is to

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Speaker 1: price them all at the same price. So when we

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Speaker 1: talk about this, we talked about how many firms priced

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Speaker 1: the bond, and that appear in the portfolios we looked

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Speaker 1: at um. But when you go back to September, for example,

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Speaker 1: as you asked, if you take corporate high quality, corporate bronze,

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Speaker 1: but corporate brons in generalist, essentially, the differences in price

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Speaker 1: were fairly narrow. We use a term that we call

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Speaker 1: the price spread percentage, where we took the lowest price

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Speaker 1: and the highest price that we found, and then we

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Speaker 1: took that the difference between those two and we divided

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Speaker 1: it by the mean average, and that gave us this

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Speaker 1: price spread percentage. And so if you look at triple

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Speaker 1: A and double A bonds at the end of September

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Speaker 1: UM that number was very small. It was only about

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Speaker 1: thirty basis points for double and triple A and it

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Speaker 1: got you know, a triple B was point three seven,

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Speaker 1: so pretty small. Those numbers are still meaningful in the

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Speaker 1: in the framework of um. You know a market where

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Speaker 1: returns for a whole year, you know, the yield on

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Speaker 1: on bonds, as you just mentioned earlier, the thirty year

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Speaker 1: not quite even two. That's a meaningful number, but it's

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Speaker 1: it's within the realm of expectations given all the things

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Speaker 1: that we said earlier about prices, and then they do

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Speaker 1: tend to get a little bit wider. The the thinner

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Speaker 1: the market, lower the quality, the smaller the range of

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Speaker 1: values and the bonds part of me what I mean

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Speaker 1: to say is, you know, the high yield market is

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Speaker 1: many times smaller, for example, than the investment grade corporate market,

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Speaker 1: and so you expect more dispersion there, and that's what

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Speaker 1: you saw at that point. And then, of course, by contrast,

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Speaker 1: when we looked at the end of the first quarter,

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Speaker 1: of those numbers were in some cases multiples. So I

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Speaker 1: mentioned earlier thirty basis points for the price fred percentage

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Speaker 1: for triple A double A corporates at the end of

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Speaker 1: March was one, and then the number for triple B

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Speaker 1: bonds was two points seven two percent, so literally multiples

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Speaker 1: of what we saw at that point. Just another snapshot

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Speaker 1: in time. Your thoughts on this sort of significance of

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Speaker 1: these figures are what they imply. As Eric said, especially

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Speaker 1: in the in the in the crisis mode, these differences

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Speaker 1: were way bigger than we expected. One thing that I

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Speaker 1: would maybe want to mention is that, you know, I

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Speaker 1: remember this old paper that Fisher Black of the famous

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Speaker 1: um you know Black and shows formula. You wrote this

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Speaker 1: paper at some point, I forget what exact name of

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Speaker 1: seven is called noise, And this is kind of what

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Speaker 1: we're dealing with here a little bit. You know, the

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Speaker 1: bond prices are noisy. You know, they are not perfect.

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Speaker 1: We don't know for sure what a given bond is

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Speaker 1: it's worth, and that's what we see being here. So

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Speaker 1: on the plot positive side, um, you know. Fisher Black

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Speaker 1: asked the question, you know, when would you say that

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Speaker 1: the market is efficient? And as the answer was, if

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Speaker 1: if there is some kind of a true value which

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Speaker 1: we don't know about, but let's assume that it is there.

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Speaker 1: Fisher Black said that the market will be efficient if

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Speaker 1: if the the market is efficient if it will assign

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Speaker 1: a price within the factor of two of the real

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Speaker 1: unobservable true value. So if if something is something let's

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Speaker 1: say is is is there's an instrument who's true values

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Speaker 1: let's say a hundred then Fisher Black would say that

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Speaker 1: the market is efficient if if if it assigns at

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Speaker 1: the value of somewhere between fifty and two hundred um.

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Speaker 1: That was his definition. So what we see here, you

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Speaker 1: know this is these are these are fractions of of

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Speaker 1: what official Black thoughts might still constitute an efficient market.

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Speaker 1: So in that sense, we are not seeing anything critical here.

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Speaker 1: On the other hand, as I mentioned, if you see

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Speaker 1: attempt percentage point price differential between between bonds, that that

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Speaker 1: can well be like two years worth a yield for

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Speaker 1: some events, for high yield issue, right, so that is

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Speaker 1: a potential, uh, you know, point of concern. Um, I'm

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Speaker 1: not sure what solution to this problem might be. Nothing

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Speaker 1: obvious count comes to mind. If we don't want to

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Speaker 1: end up with just one pricing service, we don't probably

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Speaker 1: want the government to dictate what that price is. So

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Speaker 1: I think we are stuck with the system that that

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Speaker 1: we have here. Let's just hope it continues to function

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Speaker 1: reasonably well. One thing that Eric probably didn't highlight, so

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Speaker 1: our sample that we are dealing with, we are only

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Speaker 1: dealing with bonds that had at least two different firms

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Speaker 1: pricing it. Now, it turns out that this is in

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Speaker 1: many cases the minority of all the bonds. Most of

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Speaker 1: the bonds that we are dealing with in these sectors

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Speaker 1: and especially in the municipal market, they are owned only

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Speaker 1: by one firm. So we don't really know. We can't

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Speaker 1: you know, you have only one price that you can't

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Speaker 1: talk about how spread out that price is, right, but

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Speaker 1: that that seems to be that seems to be more

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Speaker 1: of a norm than one would expect. So we're kind

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Speaker 1: of dealing with these two issues. One is only one

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Speaker 1: one player owns a given bonds and secondly, what Eric mentions,

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Speaker 1: these bonds oftentimes go through long periods of not being

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Speaker 1: traded at all, So so how do you a sign

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Speaker 1: a price to what? Instruments like that? Though I don't remember,

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Speaker 1: we were talking to somebody from a who came from

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Speaker 1: a big firm, and he was telling us that this

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Speaker 1: was in the context of of some emerging market paper.

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Speaker 1: You know, they had to put a price on it.

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Speaker 1: Says this bond hasn't traded for seven years. Now, who

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Speaker 1: really knows what it's worth, So we're going to just

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Speaker 1: say that it's worth seventy dollars and it's going to

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Speaker 1: be done with it. Wow. So I know we're talking

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Speaker 1: about how especially when when you look at something like

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Speaker 1: new knees or something like corporate bonds where they really

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Speaker 1: aren't trading that regularly, there's a tendency to say, well,

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Speaker 1: this isn't the fact that there are pricing discrepancies, isn't

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Speaker 1: that worrying? And they tend to get sort of normalized

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Speaker 1: in the long term and everything kind of works out.

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Speaker 1: But one thing that was really surprising in your paper

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Speaker 1: was that you also found price discrepancies in treasuries during

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Speaker 1: the worst of the market sell off in And this

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Speaker 1: is supposed to be, you know, a huge and liquid

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Speaker 1: and standardized market, and yet in March of last year,

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Speaker 1: people seem to have difficulty agreeing what US government debt

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Speaker 1: was actually worth. Um, can you walk us through your findings?

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Speaker 1: And then also, I guess your thoughts around this, like,

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Speaker 1: how could that possibly have happened? Sure, so what you

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Speaker 1: said is right on. You know, we we when you

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Speaker 1: look at the data for the end of the third

396
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Speaker 1: quarter of UM, the differences were very very small. Um.

397
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Speaker 1: You know, anyone looking at our charts, we'll see that

398
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Speaker 1: there are cases where there are these outliers that show

399
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Speaker 1: up in the data, and you know, we've audited a

400
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Speaker 1: number them and found that it's the data. We the

401
00:23:58,800 --> 00:24:00,919
Speaker 1: representation that we came up with its accurate. But there

402
00:24:00,960 --> 00:24:03,639
Speaker 1: were certainly a handful of cases where we think that

403
00:24:03,720 --> 00:24:07,919
Speaker 1: firms were actually reporting the information incorrectly, but you know,

404
00:24:08,119 --> 00:24:10,040
Speaker 1: we didn't we didn't strip that out if we knew

405
00:24:10,080 --> 00:24:12,360
Speaker 1: that the data that we were using the right data.

406
00:24:12,440 --> 00:24:15,639
Speaker 1: But when you look down at the at the intercuartile

407
00:24:15,760 --> 00:24:17,960
Speaker 1: ranges as we as we picked them out, So in

408
00:24:17,960 --> 00:24:22,119
Speaker 1: other words, sort of the the concentration of bonds for

409
00:24:22,160 --> 00:24:23,800
Speaker 1: the most part in the middle that it was a

410
00:24:23,960 --> 00:24:28,080
Speaker 1: very very narrow band at the end of September. Then

411
00:24:28,119 --> 00:24:30,520
Speaker 1: when you got to the end of the first quarter,

412
00:24:32,000 --> 00:24:36,040
Speaker 1: there were pricing differences that went not quite to a

413
00:24:36,040 --> 00:24:39,119
Speaker 1: full percentage point, but just under that. And as you said,

414
00:24:39,200 --> 00:24:43,840
Speaker 1: that's that's pretty remarkable. Um. You know, the reasons for

415
00:24:43,920 --> 00:24:46,560
Speaker 1: that are kind of all over the map a little

416
00:24:46,600 --> 00:24:48,639
Speaker 1: bit in terms of um, you know, some of this

417
00:24:48,800 --> 00:24:50,600
Speaker 1: was covered pretty widely in the press in terms of

418
00:24:50,600 --> 00:24:54,119
Speaker 1: off the run securities and what have you. UM, But

419
00:24:55,280 --> 00:24:57,280
Speaker 1: the bottom line I think is that it really it

420
00:24:57,320 --> 00:25:00,480
Speaker 1: really made a strong case that it was important that

421
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Speaker 1: that UM that the FED stepped in when they did

422
00:25:04,040 --> 00:25:06,320
Speaker 1: and made the decision that did, because you can only imagine,

423
00:25:06,880 --> 00:25:10,720
Speaker 1: you know, we saw much wider differences for other sectors. UM.

424
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Speaker 1: You can only imagine how much worse it would have

425
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Speaker 1: been and would have potentially gotten if they hadn't gotten.

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Speaker 1: And I'm sorry much it where you're gonna add something, No,

427
00:25:18,160 --> 00:25:20,239
Speaker 1: no, no no, no no, because the fact that I was

428
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Speaker 1: just leading up to the same timp but you said

429
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Speaker 1: it already. I mean, the Thud was really worried about

430
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Speaker 1: what was happening, even in the you know, the treasuries

431
00:25:31,119 --> 00:25:35,159
Speaker 1: are supposed to be the gold standard trading much and

432
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Speaker 1: I don't trade bonds ourselves, but you know, we've definitely

433
00:25:37,560 --> 00:25:41,880
Speaker 1: heard observations that there were certain bonds at certain times

434
00:25:41,880 --> 00:25:46,480
Speaker 1: of the day during that period where people were seeing

435
00:25:47,040 --> 00:25:51,720
Speaker 1: UM spreads that were unheard of from anything they had

436
00:25:51,760 --> 00:25:54,080
Speaker 1: seen before. And as much as said that was that

437
00:25:54,200 --> 00:25:57,639
Speaker 1: was you know, again, however you want to frame it,

438
00:25:57,680 --> 00:25:59,800
Speaker 1: I mean, I think we were all very fortunate that

439
00:25:59,880 --> 00:26:03,800
Speaker 1: the that was was awakened at the switch when that happened,

440
00:26:04,640 --> 00:26:07,359
Speaker 1: because as bad as that is for the treasuring market.

441
00:26:07,400 --> 00:26:10,520
Speaker 1: The implications down the way from that are just huge.

442
00:26:11,520 --> 00:26:13,920
Speaker 1: I think hopefully the average person on the street that

443
00:26:14,000 --> 00:26:18,200
Speaker 1: doesn't read, you know, the financial papers, probably didn't even

444
00:26:18,280 --> 00:26:20,480
Speaker 1: notice it. But if it had gotten to that point,

445
00:26:20,480 --> 00:26:22,480
Speaker 1: we really would have been in a real best trip.

446
00:26:23,640 --> 00:26:27,720
Speaker 1: H Well, one other thing that maybe should have mentioned

447
00:26:27,760 --> 00:26:30,919
Speaker 1: that It just occurred to me recently that you know,

448
00:26:31,080 --> 00:26:36,280
Speaker 1: I've given what we are seeing with these prices, what

449
00:26:36,400 --> 00:26:41,240
Speaker 1: is the row of quantitative approaches and fixed income? That's

450
00:26:41,320 --> 00:26:44,840
Speaker 1: kind of began to worry me a little bit. If

451
00:26:44,840 --> 00:26:49,919
Speaker 1: you don't really know what the prices of something, how

452
00:26:50,040 --> 00:26:53,920
Speaker 1: you're trying to arbitract some differences between these mombs. So

453
00:26:55,000 --> 00:26:59,360
Speaker 1: I'm sure that people who do this have thought about it,

454
00:26:59,440 --> 00:27:03,959
Speaker 1: but I haven't, and I don't know how they are

455
00:27:04,000 --> 00:27:06,320
Speaker 1: dealing with it. But that does seem to I mean,

456
00:27:06,320 --> 00:27:08,280
Speaker 1: it is an interesting question. I mean, when you talk

457
00:27:08,400 --> 00:27:13,800
Speaker 1: to sort of quants in the traditional equity space, you

458
00:27:13,840 --> 00:27:16,639
Speaker 1: get the impressure. They spend a lot of time on

459
00:27:17,320 --> 00:27:21,199
Speaker 1: data quality, cleaning the data, making sure that they have

460
00:27:21,280 --> 00:27:23,920
Speaker 1: access to really high you know that the data is good.

461
00:27:24,000 --> 00:27:26,880
Speaker 1: So when we when thinking about poorting some of these

462
00:27:26,920 --> 00:27:29,600
Speaker 1: ideas to the bond space, if you can't even agree

463
00:27:29,760 --> 00:27:34,119
Speaker 1: on what historical bond pricing data is, it does seem

464
00:27:34,160 --> 00:27:36,520
Speaker 1: harder to imagine that some of these strategies would be

465
00:27:36,520 --> 00:27:42,400
Speaker 1: as effective. Yeah, and and you don't see I don't

466
00:27:42,440 --> 00:27:45,720
Speaker 1: hear that much about those right in the market. So

467
00:27:46,520 --> 00:27:49,280
Speaker 1: I wonder if that's part of the reason. I don't know.

468
00:27:50,200 --> 00:27:53,080
Speaker 1: I think that's one of the ultimate reasons why. You know,

469
00:27:53,119 --> 00:27:56,919
Speaker 1: the conventional wisdom is that there is more more to

470
00:27:57,000 --> 00:28:00,719
Speaker 1: do in the fixed income space for active management um

471
00:28:00,840 --> 00:28:03,560
Speaker 1: then perhaps on the equity side, because there is so

472
00:28:03,640 --> 00:28:06,680
Speaker 1: much structural inefficiency. And one thing we haven't talked about

473
00:28:06,760 --> 00:28:10,200
Speaker 1: is the fact that you're literally talking about millions of bonds,

474
00:28:10,880 --> 00:28:14,240
Speaker 1: and not only are there several million bonds out there

475
00:28:14,280 --> 00:28:17,520
Speaker 1: at this moment, but a month from now, those bonds

476
00:28:17,560 --> 00:28:19,440
Speaker 1: will be different. And over the course of a year,

477
00:28:19,760 --> 00:28:22,600
Speaker 1: you know that that inventory, if you will turn over

478
00:28:22,600 --> 00:28:25,880
Speaker 1: because bonds are constantly maturing and their new bonds constantly

479
00:28:25,880 --> 00:28:30,920
Speaker 1: coming out. The universe of US domestic stocks is reasonably static,

480
00:28:30,960 --> 00:28:32,840
Speaker 1: and that statics probably not the right word, but the

481
00:28:32,920 --> 00:28:35,159
Speaker 1: number is a manageable number most of the time. You know,

482
00:28:35,160 --> 00:28:37,840
Speaker 1: we're talking about several thousand Once you get out into

483
00:28:37,880 --> 00:28:41,560
Speaker 1: the millions. You've got to do a lot to keep

484
00:28:41,600 --> 00:28:44,080
Speaker 1: that data clean and too, and to even something as

485
00:28:44,080 --> 00:28:46,320
Speaker 1: simple as getting a price as as you said, So

486
00:28:46,800 --> 00:28:49,680
Speaker 1: it is a it is a big, big lift for

487
00:28:49,760 --> 00:28:52,440
Speaker 1: a lot of firms and they spend a tremendous amount

488
00:28:52,440 --> 00:28:54,880
Speaker 1: of money and time on it. Yeah, the barriers to

489
00:28:55,200 --> 00:28:57,680
Speaker 1: entry are very high in the extent income. It's not

490
00:28:57,800 --> 00:29:00,880
Speaker 1: like if you want to open, uh, you know, an

491
00:29:00,920 --> 00:29:03,720
Speaker 1: equity account, um, you still have to do all the

492
00:29:03,920 --> 00:29:08,120
Speaker 1: kind of compliance and whatever stuff. But but other than that,

493
00:29:09,560 --> 00:29:13,680
Speaker 1: you can just you know, do your research and a

494
00:29:13,720 --> 00:29:17,600
Speaker 1: constructive portfolio with you can just walk off the street

495
00:29:17,680 --> 00:29:20,800
Speaker 1: and then start a bunch of that that Really there

496
00:29:20,880 --> 00:29:23,880
Speaker 1: is no room, there is no room for small players here.

497
00:29:24,080 --> 00:29:27,880
Speaker 1: I mean the outlays of you know that you have

498
00:29:28,000 --> 00:29:32,680
Speaker 1: to spend on on data and analytics are just just enormous,

499
00:29:33,600 --> 00:29:36,200
Speaker 1: which kind of makes you wonder. It makes you wonder

500
00:29:37,000 --> 00:29:39,720
Speaker 1: what is what the future of this of this whole

501
00:29:39,800 --> 00:29:56,040
Speaker 1: market is going to look like. M Magic. You touched

502
00:29:56,040 --> 00:29:59,840
Speaker 1: on the idea of what the solutions could be too

503
00:30:00,080 --> 00:30:03,760
Speaker 1: these bond pricing issues, And for as long as I've

504
00:30:03,920 --> 00:30:07,680
Speaker 1: covered bonds, especially in the corporate space, there's been talk

505
00:30:07,760 --> 00:30:12,160
Speaker 1: about doing more electronic bond trading, UM, maybe moving it

506
00:30:12,240 --> 00:30:16,440
Speaker 1: to something that resembles an exchange and something that might

507
00:30:16,520 --> 00:30:21,400
Speaker 1: have more transparent pricing. But what are the prospects of

508
00:30:21,440 --> 00:30:25,080
Speaker 1: that actually happening, because again, like I feel like the

509
00:30:25,120 --> 00:30:27,280
Speaker 1: industry has been talking about it for years and years

510
00:30:27,320 --> 00:30:31,120
Speaker 1: and years and it just never really seems to UM.

511
00:30:31,160 --> 00:30:34,440
Speaker 1: I mean, there's been progress, but it certainly isn't anywhere

512
00:30:34,440 --> 00:30:37,440
Speaker 1: near the level of something like stocks. Well. I mean one,

513
00:30:37,560 --> 00:30:41,160
Speaker 1: I'll let Eric pick it up later. But but one

514
00:30:41,200 --> 00:30:45,360
Speaker 1: thing that you know, whatever platform you you can think of,

515
00:30:46,600 --> 00:30:49,600
Speaker 1: will not address as the fact that you know, some

516
00:30:49,680 --> 00:30:53,880
Speaker 1: of these guys just not trade a sign how the

517
00:30:54,000 --> 00:30:56,760
Speaker 1: US sign a price to something that last traded three

518
00:30:56,800 --> 00:30:59,560
Speaker 1: weeks ago. So that that was our finding. I think

519
00:30:59,560 --> 00:31:04,080
Speaker 1: that's about half of mombs, half of corporate bombs well

520
00:31:04,200 --> 00:31:06,560
Speaker 1: and through at least a three week period when they

521
00:31:06,560 --> 00:31:09,600
Speaker 1: were not traded. Yeah, I think the issue is really

522
00:31:09,640 --> 00:31:13,200
Speaker 1: that it's always going to be a part of the market. UM.

523
00:31:13,280 --> 00:31:16,440
Speaker 1: The there are a couple issues there. One is this

524
00:31:16,600 --> 00:31:19,680
Speaker 1: issue a sort of critical mass, so you know, firms

525
00:31:19,720 --> 00:31:24,400
Speaker 1: have definitely talked about and tried to take more of it.

526
00:31:24,640 --> 00:31:31,040
Speaker 1: Electronic and that works better in places where there's going

527
00:31:31,080 --> 00:31:33,160
Speaker 1: to be a lot of trading and a lot of

528
00:31:33,760 --> 00:31:37,760
Speaker 1: supply and demand meeting. It's meeting halfway in the same spaces, right,

529
00:31:38,080 --> 00:31:42,959
Speaker 1: And that's why there are some electronic trading platforms um

530
00:31:43,120 --> 00:31:46,080
Speaker 1: that do some of the work. You know there there are,

531
00:31:46,120 --> 00:31:48,520
Speaker 1: There is a lot of electronic trading in the treasury market.

532
00:31:48,800 --> 00:31:51,720
Speaker 1: There even is quite a bit in the higher, higher

533
00:31:51,800 --> 00:31:56,400
Speaker 1: quality corporate market. But that that is that works best

534
00:31:57,000 --> 00:32:02,240
Speaker 1: when you're dealing with the high volume, high deal size bonds.

535
00:32:03,120 --> 00:32:07,040
Speaker 1: The further down the ladder you go, the more um

536
00:32:07,040 --> 00:32:10,960
Speaker 1: fragmented it gets, the less trading there is. Then it's

537
00:32:11,080 --> 00:32:13,440
Speaker 1: a bigger lift to try and get everybody together. And

538
00:32:13,800 --> 00:32:16,040
Speaker 1: the fact of the matter is is that for for

539
00:32:16,080 --> 00:32:19,120
Speaker 1: anybody who's actively involved in the industry, whether that's the

540
00:32:19,880 --> 00:32:24,760
Speaker 1: investment banks and dealers or even the large active managers,

541
00:32:24,760 --> 00:32:29,960
Speaker 1: to some degree, there's an incentive too have some inefficiency

542
00:32:30,000 --> 00:32:33,000
Speaker 1: in the trading, especially when it comes to the dealers,

543
00:32:33,040 --> 00:32:36,200
Speaker 1: because they do make a lot more money on these

544
00:32:36,240 --> 00:32:40,720
Speaker 1: structural inefficiencies in fixed income than they're able to in equities.

545
00:32:41,360 --> 00:32:46,360
Speaker 1: It's inevitable that when there is inefficiency that you can

546
00:32:46,520 --> 00:32:49,360
Speaker 1: ring out with technology. Somebody will eventually get there and

547
00:32:49,400 --> 00:32:52,720
Speaker 1: be able to do it. It will take more time, um,

548
00:32:52,760 --> 00:32:55,440
Speaker 1: you know, because it requires that sort of critical mass.

549
00:32:55,480 --> 00:32:57,680
Speaker 1: You have to be able to bring enough buyers and

550
00:32:57,680 --> 00:33:00,800
Speaker 1: sellers together. Um. And when you don't have a single

551
00:33:01,000 --> 00:33:04,520
Speaker 1: point of exchange, that that's more difficult. But what we

552
00:33:04,600 --> 00:33:07,200
Speaker 1: said earlier about the nature of the bond market, the

553
00:33:07,240 --> 00:33:10,880
Speaker 1: fact that it is so fragmented and splintered, and there

554
00:33:10,880 --> 00:33:13,800
Speaker 1: are you know, even even a single I mean, look

555
00:33:13,800 --> 00:33:16,480
Speaker 1: at it this way. A single large company, a very

556
00:33:16,600 --> 00:33:21,080
Speaker 1: very large mega cap company will still have one stock right,

557
00:33:21,200 --> 00:33:24,600
Speaker 1: one share, common equity, maybe a couple of maybe they've

558
00:33:24,600 --> 00:33:26,920
Speaker 1: got some prefers, what have you. But fundamentally, when you

559
00:33:27,000 --> 00:33:30,880
Speaker 1: trade you know G E, you're trading G. They made.

560
00:33:30,920 --> 00:33:34,840
Speaker 1: The same company may have literally hundreds of bonds, and

561
00:33:35,320 --> 00:33:38,840
Speaker 1: the differences among them may have Sometimes it may be

562
00:33:38,920 --> 00:33:41,600
Speaker 1: as simple as just the maturity. But once you spread

563
00:33:41,600 --> 00:33:44,360
Speaker 1: that out, you've got different coupons, different maturities, and very

564
00:33:44,440 --> 00:33:47,560
Speaker 1: large companies with subsidiaries and so forth, may issue bonds

565
00:33:47,560 --> 00:33:50,760
Speaker 1: at every different level, so the underlying credit qualities slightly

566
00:33:50,800 --> 00:33:52,959
Speaker 1: different because they have legal differences in one of them

567
00:33:53,000 --> 00:33:57,680
Speaker 1: as well. Trying to standardize and commoditize those Um there

568
00:33:57,720 --> 00:33:59,880
Speaker 1: there are certainly party of these parties that benefit from that,

569
00:34:00,000 --> 00:34:04,000
Speaker 1: including the issuers themselves would But as long as you've

570
00:34:04,040 --> 00:34:07,959
Speaker 1: got that much differentiation, you're always going to have a

571
00:34:08,040 --> 00:34:10,200
Speaker 1: huge swath of the market that isn't going to trade

572
00:34:10,640 --> 00:34:13,239
Speaker 1: quite that often. I do think that in some of

573
00:34:13,239 --> 00:34:14,840
Speaker 1: it is a matter of time and some of it

574
00:34:14,920 --> 00:34:17,080
Speaker 1: is a matter of sort of the socialization of the market,

575
00:34:17,080 --> 00:34:20,400
Speaker 1: people sort of getting on the same page. But no

576
00:34:20,440 --> 00:34:22,719
Speaker 1: matter how far down the road you go in terms

577
00:34:22,760 --> 00:34:27,560
Speaker 1: of making it electronic, UM, you're still gonna have inefficiency

578
00:34:27,760 --> 00:34:30,239
Speaker 1: people trying. You know, the bottom line is traders still

579
00:34:30,239 --> 00:34:34,160
Speaker 1: get on the phone and haggle over prices for bonds.

580
00:34:34,640 --> 00:34:37,799
Speaker 1: That's always going to happen to some degree, the less

581
00:34:37,840 --> 00:34:41,239
Speaker 1: standardized and the smaller the bond is. So one other

582
00:34:41,320 --> 00:34:45,399
Speaker 1: thing to add to to this, Uh, what we are

583
00:34:45,480 --> 00:34:51,040
Speaker 1: hearing is that pricing agencies, pricing services now apparently look

584
00:34:51,080 --> 00:34:56,320
Speaker 1: at at e t F prices because whoever is creating

585
00:34:56,400 --> 00:35:00,160
Speaker 1: the E t F units, um, they are implicit like

586
00:35:01,200 --> 00:35:04,719
Speaker 1: putting some price on these on these things, whether they

587
00:35:04,719 --> 00:35:07,400
Speaker 1: have been traded or not. So that might be a

588
00:35:07,480 --> 00:35:11,480
Speaker 1: potentially interesting having you to to get around that problem.

589
00:35:11,480 --> 00:35:14,960
Speaker 1: Although it's it's clearly not perfect, but but it tells

590
00:35:15,000 --> 00:35:19,000
Speaker 1: you something. It's kind of crazy when the like liquid

591
00:35:19,239 --> 00:35:22,160
Speaker 1: wrapper that you put around the stuff that doesn't trade

592
00:35:22,239 --> 00:35:25,799
Speaker 1: very much becomes the reference point for pricing because it

593
00:35:25,840 --> 00:35:30,040
Speaker 1: doesn't trade much. It's weird. Yeah, I think that that's definitely,

594
00:35:30,440 --> 00:35:33,880
Speaker 1: definitely an important, interesting thing that's that the market is

595
00:35:33,920 --> 00:35:37,600
Speaker 1: starting to absorb and learn about. I would point out though,

596
00:35:37,680 --> 00:35:41,000
Speaker 1: that you're still dealing with a subset of the market.

597
00:35:41,120 --> 00:35:44,279
Speaker 1: Usually when you have a corporate bond e t F

598
00:35:44,400 --> 00:35:47,680
Speaker 1: that has a hundred bonds in it, that will certainly

599
00:35:47,719 --> 00:35:51,319
Speaker 1: affect the liquidity of those one bonds and bonds that

600
00:35:51,360 --> 00:35:54,399
Speaker 1: are similar in nature to it UM, but you wind

601
00:35:54,480 --> 00:35:58,279
Speaker 1: up getting concentration liquidity in those in that area as well,

602
00:35:58,360 --> 00:36:01,319
Speaker 1: So that kind of things. Certainly there's no question that

603
00:36:01,320 --> 00:36:05,680
Speaker 1: that should have an effect of creating better efficiency in

604
00:36:05,760 --> 00:36:08,800
Speaker 1: parts of the market where those et f s live UM,

605
00:36:08,840 --> 00:36:11,879
Speaker 1: But to the degree that they have that bonds are

606
00:36:11,920 --> 00:36:15,480
Speaker 1: not concentrated inside those et f s, you're still going

607
00:36:15,520 --> 00:36:18,160
Speaker 1: to be dealing quite a bit with with this issue.

608
00:36:18,480 --> 00:36:21,080
Speaker 1: Look that it's still an analogy, it's not doesn't fit entirely.

609
00:36:21,120 --> 00:36:23,600
Speaker 1: But you know, when we talk about companies being a

610
00:36:23,640 --> 00:36:25,200
Speaker 1: part of our not being a part of the SMP

611
00:36:25,280 --> 00:36:27,920
Speaker 1: five hundred, it makes a difference. If you're not in

612
00:36:28,000 --> 00:36:31,000
Speaker 1: that s your the demand for your stock is not

613
00:36:31,040 --> 00:36:33,520
Speaker 1: going to be the same. So it is kind of

614
00:36:33,560 --> 00:36:38,160
Speaker 1: a somewhat paradoxical situation where you know, fixed income is

615
00:36:38,160 --> 00:36:42,560
Speaker 1: supposed to be this safe and kind of boring asset,

616
00:36:42,600 --> 00:36:46,279
Speaker 1: but we don't really to some extent now what these

617
00:36:46,320 --> 00:36:51,279
Speaker 1: prices are, at least much less clearly than than we

618
00:36:51,360 --> 00:36:55,520
Speaker 1: do four equities. That to me that was a little paradoxical,

619
00:36:56,360 --> 00:36:59,120
Speaker 1: and that sends fixed income is a little closer to

620
00:36:59,200 --> 00:37:02,240
Speaker 1: like private equa to you or something of that nature.

621
00:37:02,440 --> 00:37:07,759
Speaker 1: Not maybe to the same degree, but nature, I think

622
00:37:08,200 --> 00:37:11,880
Speaker 1: it's closer in terms of pricing. I love the idea

623
00:37:11,960 --> 00:37:15,320
Speaker 1: that we think of bonds is really boring, as you said,

624
00:37:15,440 --> 00:37:19,040
Speaker 1: but like below the surface, maybe you know someone an

625
00:37:19,040 --> 00:37:22,799
Speaker 1: asset manager and a pricing service provider are having like

626
00:37:22,880 --> 00:37:26,360
Speaker 1: this raging debate about how much the bond is actually worth,

627
00:37:27,000 --> 00:37:29,200
Speaker 1: But we don't get to see that most of the time.

628
00:37:29,840 --> 00:37:32,879
Speaker 1: You know, Marchick mentioned earlier about the fact that such

629
00:37:32,920 --> 00:37:37,520
Speaker 1: a huge proportion of municipal bonds that we observed were

630
00:37:37,560 --> 00:37:40,720
Speaker 1: only being held in the funds of a single firm each.

631
00:37:41,280 --> 00:37:44,000
Speaker 1: That's that's what's particularly interesting when you said about below

632
00:37:44,080 --> 00:37:46,920
Speaker 1: the surface. You know, that's where that kind of argument

633
00:37:46,920 --> 00:37:48,960
Speaker 1: may really come in when a manager may be the

634
00:37:49,080 --> 00:37:55,600
Speaker 1: only large investor holding that bond, and that that means

635
00:37:55,640 --> 00:37:59,360
Speaker 1: that the pricing service itself isn't necessarily seeing in anybody

636
00:37:59,360 --> 00:38:02,840
Speaker 1: else's port olio either. Um, They're gonna sign a price

637
00:38:02,840 --> 00:38:07,480
Speaker 1: based on some formula, some matrix or or artificial intelligence.

638
00:38:07,480 --> 00:38:11,320
Speaker 1: And that's a case where the manager may know something

639
00:38:11,360 --> 00:38:13,480
Speaker 1: about the you know, it's if it's a few million

640
00:38:13,520 --> 00:38:16,279
Speaker 1: dollar bond of a small, you know, nursing home in

641
00:38:16,320 --> 00:38:19,960
Speaker 1: West Texas, that's where that argument may come. But it's

642
00:38:20,120 --> 00:38:21,920
Speaker 1: as you said, it's all it's all under the surface,

643
00:38:21,960 --> 00:38:24,080
Speaker 1: and we'll never see anything about that. So there was

644
00:38:24,120 --> 00:38:30,520
Speaker 1: more though bonds all right, Well, Um, Matcha and Eric.

645
00:38:30,600 --> 00:38:33,719
Speaker 1: That was that was really interesting, um, and really good

646
00:38:33,719 --> 00:38:38,200
Speaker 1: fun to dive beneath the surface of an otherwise boring

647
00:38:38,320 --> 00:38:40,880
Speaker 1: fixed income market. So thank you so much for coming on.

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00:38:41,080 --> 00:38:43,920
Speaker 1: Really appreciate it. Thank you, it's our pleasure. Thanks. That

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00:38:44,000 --> 00:39:03,359
Speaker 1: was great, So Joe, I actually feel kind of bad

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00:39:03,400 --> 00:39:06,560
Speaker 1: for calling the fixed income market boring because I don't

651
00:39:06,560 --> 00:39:08,680
Speaker 1: think it is. But I do think that there is

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00:39:08,719 --> 00:39:11,200
Speaker 1: this big portion of it in terms of the market

653
00:39:11,239 --> 00:39:15,280
Speaker 1: structure that doesn't get as much attention as it should

654
00:39:15,520 --> 00:39:18,680
Speaker 1: in my mind, and the pricing of a lot of

655
00:39:18,680 --> 00:39:21,040
Speaker 1: bonds is one of them. No, I think it's super

656
00:39:21,040 --> 00:39:23,799
Speaker 1: one of those things. Interesting. My big takeaway is that

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00:39:23,920 --> 00:39:26,719
Speaker 1: I feel like if I were going to start some

658
00:39:26,800 --> 00:39:29,200
Speaker 1: sort of like asset manager, or if I were going

659
00:39:29,239 --> 00:39:31,879
Speaker 1: to get into trading or something like that, I feel

660
00:39:31,920 --> 00:39:34,600
Speaker 1: like I would definitely go into the bond space, just

661
00:39:34,680 --> 00:39:37,560
Speaker 1: because you know, listening to that after all, you know,

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00:39:37,600 --> 00:39:39,680
Speaker 1: it still feels like it's come up in some of

663
00:39:39,680 --> 00:39:43,640
Speaker 1: our conversations. There are so many I guess inefficiencies or

664
00:39:43,840 --> 00:39:46,600
Speaker 1: sources of friction might be a better way to characterize

665
00:39:46,600 --> 00:39:50,520
Speaker 1: it in the space, whereas with equities there are very few,

666
00:39:51,280 --> 00:39:53,680
Speaker 1: And as such, I suspect that there are you know,

667
00:39:54,160 --> 00:39:58,359
Speaker 1: risk premium out there yet still to be harvested by

668
00:39:58,400 --> 00:40:01,720
Speaker 1: the enterprising bond manager the more they understand this stuff.

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00:40:02,480 --> 00:40:04,600
Speaker 1: I was worried for a second when when you talked

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00:40:04,600 --> 00:40:06,600
Speaker 1: about starting something that you were going to start like

671
00:40:06,680 --> 00:40:11,680
Speaker 1: the team the electronic bond trading platform. Um, but no,

672
00:40:11,920 --> 00:40:16,200
Speaker 1: in a different direction. Okay, I take advantage, take advantage

673
00:40:16,200 --> 00:40:23,640
Speaker 1: of all all the fragmented bond trading platforms to find inefficiencies. Yes, Um.

674
00:40:23,680 --> 00:40:25,880
Speaker 1: The other thing, I mean, there's a lot to unpack

675
00:40:25,960 --> 00:40:30,680
Speaker 1: in that discussion. Um. The description of the treasury pricing

676
00:40:30,760 --> 00:40:34,560
Speaker 1: discrepancies is still really remarkable to me, um, and I

677
00:40:34,560 --> 00:40:37,080
Speaker 1: would love to hear more about that. But the other

678
00:40:37,120 --> 00:40:38,840
Speaker 1: thing that stuck out was this idea of e t

679
00:40:39,160 --> 00:40:42,759
Speaker 1: s kind of becoming um the reference price for the

680
00:40:42,800 --> 00:40:46,759
Speaker 1: bonds they're actually wrapped around. UM. And I've heard that

681
00:40:46,880 --> 00:40:51,800
Speaker 1: before from people in the market, and I can understand why,

682
00:40:52,000 --> 00:40:55,879
Speaker 1: but it just seems so circular to me and sort

683
00:40:55,920 --> 00:40:59,680
Speaker 1: of like intuitively odd when when that came up, like

684
00:40:59,719 --> 00:41:02,600
Speaker 1: I literally got in my head that image of the

685
00:41:02,640 --> 00:41:07,280
Speaker 1: snake eating its tail. So say it's exactly like It's like, okay,

686
00:41:07,280 --> 00:41:10,160
Speaker 1: so it doesn't sound right. It sounds problematic, Like I

687
00:41:10,160 --> 00:41:13,080
Speaker 1: don't know how it would become a problem, but it

688
00:41:13,120 --> 00:41:16,880
Speaker 1: doesn't sound great if the instrument designed to hold the

689
00:41:16,920 --> 00:41:21,880
Speaker 1: bonds can't be priced easily because the bonds are a

690
00:41:21,960 --> 00:41:24,080
Speaker 1: liquid and so you end up pricing the bonds based

691
00:41:24,080 --> 00:41:27,359
Speaker 1: on where the et F trade. It does not sound great,

692
00:41:27,400 --> 00:41:29,400
Speaker 1: but maybe it's fine. I don't know. We'll have to

693
00:41:29,400 --> 00:41:31,160
Speaker 1: wait to a crisis and then will say, oh, yes,

694
00:41:31,239 --> 00:41:34,560
Speaker 1: that was a big deal. Well, I mean, to some extent,

695
00:41:34,600 --> 00:41:37,840
Speaker 1: we we kind of had, um the credit crisis in

696
00:41:38,840 --> 00:41:41,239
Speaker 1: and the e t f s performed reasonably well. But

697
00:41:41,360 --> 00:41:45,000
Speaker 1: you could imagine a scenario where um, because the e

698
00:41:45,080 --> 00:41:47,239
Speaker 1: t f s are sort of influencing the underlying and

699
00:41:47,320 --> 00:41:51,280
Speaker 1: vice versa, maybe you get a cascade effect of some sort.

700
00:41:51,480 --> 00:41:55,839
Speaker 1: But anyway, um, your your image of the snake eating

701
00:41:55,880 --> 00:41:58,720
Speaker 1: its own tail is it's gonna stick with me. Okay,

702
00:41:58,840 --> 00:42:01,279
Speaker 1: should we leave it there? Let's leave it there? All right?

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Speaker 1: This has been another episode of the All Thoughts podcast.

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00:42:04,280 --> 00:42:07,120
Speaker 1: I'm Tracy Alloway. You can follow me on Twitter at

705
00:42:07,160 --> 00:42:10,080
Speaker 1: Tracy Alloway and I'm Joe wi Isn't though. You could

706
00:42:10,080 --> 00:42:13,480
Speaker 1: follow me on Twitter at the Stalwart. Follow our producer

707
00:42:13,560 --> 00:42:17,520
Speaker 1: Laura Carlson. She's at Laura M. Carlson. Follow the Bloomberg

708
00:42:17,560 --> 00:42:21,480
Speaker 1: head of podcast Francesca Levi at Francesca Today, and check

709
00:42:21,520 --> 00:42:24,440
Speaker 1: out all of our podcasts at Bloomberg under the handle

710
00:42:24,760 --> 00:42:26,600
Speaker 1: at podcasts. Thanks for listening,