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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. Wisn't all Joe? We

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Speaker 1: have been watching the VIX, haven't we? We have? Um,

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Speaker 1: I mean it's been We've had a lot of episodes

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Speaker 1: this year for pretty obvious reasons, looking at the VICS,

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Speaker 1: exploring volatility, what signal is embedded in it, what it

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Speaker 1: tells you, what it doesn't. But people love hearing about

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Speaker 1: the VIX, so people, I'm always up to talk about it.

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Speaker 1: You know, as I said that sentence, I kind of

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Speaker 1: realized what a week intro it was, and I need

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Speaker 1: to work put more thought into how I start these things.

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Speaker 1: But yes, it's fine, it's fine. We talk a lot

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Speaker 1: about volatility. We talk a lot about the market structure

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Speaker 1: of aol utility, but lately we've been talking about volatility

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Speaker 1: more in the short term, in the sense that we

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Speaker 1: have this really big potential tail risk on the horizon

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Speaker 1: in the form of the U S elections. And if

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Speaker 1: you look at the VIX, even though it's relatively low,

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Speaker 1: if you look at the actual term structure or the

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Speaker 1: curve of the VIX, you can see it's quite well

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Speaker 1: it's not as elevated as it was a few weeks

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Speaker 1: or months ago, but it's still elevated, um, compared to

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Speaker 1: normal right around the time of the elections and for

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Speaker 1: a few weeks after that. So that's a bunch of

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Speaker 1: people pricing in the risk of something unexpected happening in

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Speaker 1: the U S elections. Yeah. Absolutely, I mean this has

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Speaker 1: been building for a while. I shouldn't note we are

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Speaker 1: recording this Tuesday, October twenty, so we're literally two weeks

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Speaker 1: away from November third election day, although by the time

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Speaker 1: you hear this, I think, based on when we expect

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Speaker 1: release it, it's going to be about a week. Yeah,

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Speaker 1: you're absolute lutely correct. Which is that for several weeks

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Speaker 1: or months now, um, the volatility term structure has been

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Speaker 1: super bit up, not just at the beginning of November,

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Speaker 1: but for a long period as the risk of a

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Speaker 1: long drawn out count is a possibility. Some of that

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Speaker 1: has come in a little bit less concerns about that

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Speaker 1: as some of the polls have widened between the two.

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Speaker 1: I mean, I guess there's always sort of going to

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Speaker 1: be some expected volatility to round election. But the clear

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Speaker 1: thing is because of so much going on and all

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Speaker 1: the uncertainty and economic situation. There is a lot of

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Speaker 1: anxiety and uncertainty about the election and its ramifications. Yeah,

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Speaker 1: it kind of for me. It brings to mind three questions. So,

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Speaker 1: number one, our markets pricing in the results of the

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Speaker 1: US election correctly? So are they you know, are the

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Speaker 1: polls right this time versus what we saw in And Secondly,

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Speaker 1: are investors We've discussed this before with Chris Sidile most recently,

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Speaker 1: but our investors so well hedge now around the election

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Speaker 1: that it's going to be really tough to actually spark

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Speaker 1: a volatility event or Third, are we mistaking that's volatility

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Speaker 1: premium um? And is it in fact market complacency? Should

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Speaker 1: investors be more worried? So those are all sort of

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Speaker 1: interconnected questions, but we're going to be discussing them with

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Speaker 1: an All Thoughts favorite on this episode. I think this

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Speaker 1: is going to be his third appearance on All Thoughts.

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Speaker 1: It's Josh Younger, head of US Interest Rate Derivative Strategy

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Speaker 1: over at JP Morgan Chase, and he's been writing quite

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Speaker 1: a lot about this three episodes. Is that when you

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Speaker 1: get the odd that's sorry, you get the sweatshirt. Josh

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Speaker 1: will send that over to you after this episode. Welcome

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Speaker 1: to the show again. Yeah, thanks, it's great to be back.

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Speaker 1: So I guess just to begin, could you maybe laid

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Speaker 1: the scene for us in terms of what we're seeing

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Speaker 1: in market positioning on volatility. We spoke a little bit

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Speaker 1: about how at one point it looks like markets were

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Speaker 1: building in quite a big risk premium around the elections

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Speaker 1: and beyond it. Uh you are? You wrote about this

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Speaker 1: that it looks like investors were bracing possibly for a

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Speaker 1: contested election. But we've seen that risk premium come down recently.

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Speaker 1: What does that say about where the market actually is positioned?

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Speaker 1: So maybe it's best to start by getting a sense

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Speaker 1: of how we actually extract these numbers, because it's it's

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Speaker 1: sort of easy to say, well, the markets pricing x,

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Speaker 1: y or z for the election, but but ultimately we

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Speaker 1: need to get this from some traded instrument and the

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Speaker 1: price of that instrument. And with options markets, the price

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Speaker 1: of the option is proportional to or related to the

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Speaker 1: potential for large moves, So that insurance is worth more

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Speaker 1: if the likelihood of a large move is greater, and

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Speaker 1: so you have to pay up for that insurance, and

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Speaker 1: vice versa. Think the like ahotive of largeness is lesser.

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Speaker 1: And so what we do is we take options that

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Speaker 1: expire after the election, and we compare the price of

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Speaker 1: those options, adjusting for the extra time value of them,

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Speaker 1: to the price of options that expire before the election,

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Speaker 1: and from that you can get a sense of how

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Speaker 1: much additional risk premium there is simply because of the

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Speaker 1: fact the election falls in that window. And it's tough

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Speaker 1: to do this with a lot of precision in most

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Speaker 1: asset classes. So you're mentioning the VIX and those vixed

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Speaker 1: futures are typically calendar months, so it's it's rather hard

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Speaker 1: to isolate the election date itself. Although options do trade

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Speaker 1: at that level of precision. It's usually best done, especially

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Speaker 1: if you're going to compare different asset classes these like

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Speaker 1: benchmark type structure. So one month options on UH rates

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Speaker 1: and equities and foreign exchange and commodities and different equity

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Speaker 1: indices and so forth, and you can compare that to say,

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Speaker 1: three months options on the same and we did that

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Speaker 1: back in late August early September, and you can pull

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Speaker 1: out of that the risk premium and say UH isolated

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Speaker 1: to just election day. That's an assumption you can make

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Speaker 1: and you say how much extra risk is there on

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Speaker 1: election day relative to some background level of volatility, because

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Speaker 1: obviously if markets are are bald already, then volatility risk

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Speaker 1: is gonna be more expensive. And so when we did

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Speaker 1: that exercise, we got something like seven to eight times

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Speaker 1: the typical daily move priced for election day across really

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Speaker 1: a broad range of asset classes. That's not just the

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Speaker 1: US equities, the VIX, the sp that was interest rates,

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Speaker 1: the US dollar interest rates, it was foreign currencies to

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Speaker 1: some extent, especially dollar C N Y exchange rates. So

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Speaker 1: that makes sense, that's a gio political element of the election.

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Speaker 1: You can see it in gold, you could see it

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Speaker 1: in oil, you can see it in credit markets, you

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Speaker 1: can basically everywhere that options traded. You could see something

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Speaker 1: between six and eight times the typical daily move price

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Speaker 1: for election day. And that's again subject to the assumption

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Speaker 1: that it's all isolated to that particular day. No, that's

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Speaker 1: not a great assumption because seven eight times a big number, right,

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Speaker 1: So what we could equivalently say is, well, not only

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Speaker 1: is election date pricing a lot of all risk, but

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Speaker 1: that risk is spread out and and persists past the

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Speaker 1: election itself. That's mathematically consistent. So we interpreted that not

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Speaker 1: to say the markets expect basis point moving interest rates

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Speaker 1: or movement equities on election day, but that the market

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Speaker 1: was assuming a persistent, elevated volatility environment for for weeks

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Speaker 1: and potentially a month thereafter. And so that just increased

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Speaker 1: the value of of those options. Now now that since

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Speaker 1: come down um and and now that's more like three

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Speaker 1: or four times. Go back over the past twenty five years,

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Speaker 1: and why not further It's because we really didn't have

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Speaker 1: much of an options market earlier than years ago, so

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Speaker 1: you really have a small sample there. But and many

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Speaker 1: of those elections weren't that close, especially in the late nineties.

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Speaker 1: But if we go back over that period, we can say, look,

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Speaker 1: typical event risk premium is two to three times the

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Speaker 1: background level of volatility, and we were looking at seven

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Speaker 1: to eight and that's coming down to three or four,

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Speaker 1: but it's still multiples of what you would expect for

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Speaker 1: for a typical election cycle. That was great recent episodes.

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Speaker 1: I feel like I've been asking really remedial questions about volatility.

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Speaker 1: With our recent guest, I asked why vix curves, futures

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Speaker 1: curve slope upward. I'm not going to ask about that now.

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Speaker 1: I'm going to ask it even stupider question though, when

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Speaker 1: I pull up a quote of the VIX and I

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Speaker 1: see right now it's for people who are curious about that.

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Speaker 1: What is that number actually represent? So that's a break

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Speaker 1: even annualized move. So if you were to buy a

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Speaker 1: one year option at it, imply volatility of the equity

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Speaker 1: index would have to move for you to make zero

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Speaker 1: dollars relative to the insurance costs up front. So um,

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Speaker 1: you can change the time frame of that. Obviously, if

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Speaker 1: if you're paying for a three month option, you'd have

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Speaker 1: to have less of a break even because there's less

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Speaker 1: time value. The idea of an option is you have, uh,

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Speaker 1: the intrinsic value of the thing, which is how much

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Speaker 1: the strike price differs from the current price of the assets.

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Speaker 1: So if I bought a call on the smp AT's trading,

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Speaker 1: that means I can buy something worth It's worth hundred dollars, right,

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Speaker 1: And and then the question is if that option expires

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Speaker 1: in six months to a year, If I have protection

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Speaker 1: for a year, that's worth more than protection for six months, um,

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Speaker 1: and so uh, that price is just going to be

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Speaker 1: higher because of that time value. But what we want

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Speaker 1: to do is put everything on equal footing apples to apples,

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Speaker 1: and so we say, what is the break even change

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Speaker 1: over the expiry of this option? UM to UH to

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Speaker 1: get sort of a break a neutral PANO, a neutral payoff.

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Speaker 1: That's where I'm agnostic to eying the option or not.

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Speaker 1: That was great. I think Joe just managed to sneak

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Speaker 1: in the actual question why is the VIX curve upward sloping?

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Speaker 1: And you very nicely answered, so thank you for that.

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Speaker 1: I have a slightly different question, which is you talked

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Speaker 1: about how you've been studying the risk premium across a

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Speaker 1: bunch of different asset classes, and I think you found

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Speaker 1: that it looked like it was bigger or higher in

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Speaker 1: the interest rates market than, for instance, in the stock market.

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Speaker 1: Why do you think that's happening. Why do you think

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Speaker 1: some asset classes or some markets appear to be pricing

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Speaker 1: in higher levels of expected volatility? So I think some

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Speaker 1: of it makes a lot of intuitive sense. So if

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Speaker 1: we if we think about dollar c N Y so

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Speaker 1: Chinese currency exchange rates, UM, I think it's fair to

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Speaker 1: say that a Trump presidency versus Biden presidency could lead

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Speaker 1: to very different outcomes there, and so the binary event

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Speaker 1: has a lot of potential impact on on pricing, and

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Speaker 1: so you'd expect the insurance value of options that protect

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Speaker 1: you against changes in that price to be very high.

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Speaker 1: So that's that's pretty intuitive. Interest rates is a little

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Speaker 1: counterintuitive only in that if we think of interest rates

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Speaker 1: is driven by two things. One is monetary policy and

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Speaker 1: the other is fiscal policy. So on the monetary policy side,

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Speaker 1: how does the FED move short term rates to react

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Speaker 1: to economic conditions? What is their framework, who's in charge? Um?

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Speaker 1: That that is important for even long term interest rates,

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Speaker 1: because if I'm thinking about buying a tenure bond, I

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Speaker 1: could equivalently just roll three months bonds for ten years.

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Speaker 1: So there's an expectations element of this that tenure yield

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Speaker 1: should be roughly equal to the average expected short term

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Speaker 1: yield over the next ten years. And so whoever's in

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Speaker 1: charge of the Fed and how they make decisions affects

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Speaker 1: what that short term rate is going to do. Um.

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Speaker 1: The second is on the fiscal side, which is that

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Speaker 1: tenure bond is not a rolling basket of three months bonds,

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Speaker 1: it's a tenure instrument. Um. The government needs to borrow

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Speaker 1: money across a range of tenors, sometimes for longer, sometimes

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Speaker 1: for shorter, and so the amount they need to borrow

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Speaker 1: um and the way that they choose to do so,

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Speaker 1: like the different maturities they focus on. All that tells

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Speaker 1: you what the level of longer term interest rates is

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Speaker 1: going to do relative to this expectation. So this is

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Speaker 1: often called term premium, right It's it's the premium that

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Speaker 1: is assigned as something that locks you into position for

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Speaker 1: ten years, and or the format in which that risk comes,

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Speaker 1: which is a treasury bond versus U corporate bond versus

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Speaker 1: versus a rolling basket of short term securities, etcetera. So

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Speaker 1: you know that fiscal outlook is not that different. Frankly,

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Speaker 1: across the two candidates. The Committee for Responsible Budget has

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Speaker 1: estimates for both campaign platforms, and I think over the

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Speaker 1: next ten years or so, they have the stock of

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Speaker 1: US debt for Biden at of GDP and for Trump

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Speaker 1: at a hundred twenty five percent of GDP. So it's

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Speaker 1: a very similar fiscal outlook, and that's consistent. The format

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Speaker 1: of that dead increase maybe is different. In one case

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Speaker 1: it's more spending and in the other it's more tax related.

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Speaker 1: But tax expenditures and fiscal expenditures are fundamentally deficit spending anyways,

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Speaker 1: and so like, the outlook isn't that different. And then

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Speaker 1: if we turn to the monetary policy side, I think

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Speaker 1: it's fair to say both candidates preferred devish outlook. And

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Speaker 1: Pal's term doesn't expire until so there's some time there

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Speaker 1: and and so, and the Fed just completed a review

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Speaker 1: of how they make decisions, and they're unlikely to do

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Speaker 1: a wholesale review over the short term, and so like,

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Speaker 1: the outlook isn't that different for interest rates across the

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Speaker 1: two candidates. I think the reason why you you get

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Speaker 1: that knee jerk pricing of event risk is, on the

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Speaker 1: one hand, everyone remembers and there was quite a bit

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Speaker 1: of volatility in interest rates, and by many measures, the

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Speaker 1: reaction of the interst rate market was much more chaotic

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Speaker 1: to the unexpected outcome than equities and effects and other

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Speaker 1: asset classes. So a lot of that post election volatility

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Speaker 1: in six was really concentrated in interest rates. And there's

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Speaker 1: a lot of muscle memory there. Yeah, I remember that.

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Speaker 1: So like stocks, you know, mostly went up pret Trump,

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Speaker 1: they they then continued going up during most of Trump's

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Speaker 1: tenure obviously, but that the tenure moved, the long end

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Speaker 1: of the curve really moved violently after probably people thought

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Speaker 1: maybe Trump would deliver some sort of growth jold due

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Speaker 1: to taxes or spending that would cause rate hike. I

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Speaker 1: remember that day November eight, November nine, pretty some of

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Speaker 1: the biggest moves ever. And so you think that sort

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Speaker 1: of that the memory of that sort of loom looms

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Speaker 1: large in terms of a potential rights turning point. Yeah.

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Speaker 1: And I think one of the funny experiences from that time.

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Speaker 1: We have a model that we trained. It's a machine

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Speaker 1: learning model that looks at different market signals um and

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Speaker 1: and tries to come up with a view on treasuries

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Speaker 1: for a week. So it'says longer short, should I do

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Speaker 1: ten percent? Size size, and it uses it in put.

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Speaker 1: I think we have things going into it, but it's

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Speaker 1: all stuff you can see. It's economic data, it's pricing,

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Speaker 1: it's the yield curve, it's ball levels, it's the depth

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Speaker 1: of the market and different different permutations of that. UM.

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Speaker 1: It doesn't know there's an election. And what I thought

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Speaker 1: was really interesting about that model is that it quote

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Speaker 1: unquote got the election right, meaning it was max short

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Speaker 1: the rates market in the lead up to the to

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Speaker 1: the election date itself. And so if it doesn't know

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Speaker 1: there's an election, it doesn't know what the polls are.

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Speaker 1: It's not like it knew something that Nate Silver didn't.

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Speaker 1: It was basically just saying, like, I look at this

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Speaker 1: set of market data and economic data, and I'm of

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Speaker 1: the opinion, as this agnostic model, that this is a

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Speaker 1: rising rate environment. Economic growth is accelerating, inflation is firming,

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Speaker 1: and rates should be higher, um. And the question is

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Speaker 1: then why were they so low? And and I think

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Speaker 1: you can argue, I mean, it's not a particularly robust argument,

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Speaker 1: but you could say, you know, the narrative that that

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Speaker 1: makes that reasonable is to say the election risk, the

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Speaker 1: binary election risk, independent of what its impact, the impact

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Speaker 1: of either outcome would have been on markets, just the

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Speaker 1: fact of this big event coming up kind of held

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Speaker 1: the market back from pricing in what was otherwise like

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Speaker 1: a very supportive background. Um. And then once the election passes,

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Speaker 1: you just knee jerk price in six months of economic

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Speaker 1: developments over a week or two. And so if that's

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Speaker 1: the case this time around, even if this these these

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Speaker 1: deficit outlooks which are very similar are the same. It

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Speaker 1: could also be the case this time that the event

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Speaker 1: and uncertainties around the event, and even if it seems

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Speaker 1: reasonably high probability of one outcome or nother, everyone's saying,

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Speaker 1: you know, you never know, and polls could be wrong

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Speaker 1: and so forth, And we might talk about that in

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Speaker 1: the episode. But just the fact of this one day

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Speaker 1: that matters and we don't really know what's going to

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Speaker 1: happen can hold things back, and then in the wake

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Speaker 1: of it, potentially independent of what the outcome is, you

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Speaker 1: could frontload all of this repricing very quickly, and that's

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Speaker 1: a very volatile environment. Well, so why don't we talk

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Speaker 1: about that point? Because we have the risk premium built

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Speaker 1: into various markets. So you could argue that in many ways,

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Speaker 1: investors are quite well positioned for something actually happening in November.

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Speaker 1: But on the other hand, you could argue perhaps that

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Speaker 1: the polls are wrong or there's still a chance of

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Speaker 1: something completely unexpected happening, and in that sense they might

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Speaker 1: even be considered complacent despite that higher risk premium. So

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Speaker 1: what's your take on that particular argument. So I think

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Speaker 1: there's not a ton of trading that generates these price

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Speaker 1: changes so the stock of equity positions, the stock of

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Speaker 1: rates positions is just enormous, and a lot of those

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Speaker 1: just have to get rebalanced when there's a big change.

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Speaker 1: So you can get these self reinforcing spirals simply because

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Speaker 1: like changes in the environment, especially among You know, we

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Speaker 1: often think intuitively in terms of retail investing, but you

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Speaker 1: know that the most important transfers of risks happen with

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Speaker 1: with institutions. They're just much larger and they have very

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Speaker 1: different incentives. Um. So, if we think about an insurance company,

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Speaker 1: for example, if rates are rising, they need to shed

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Speaker 1: duration mechanically because of the way that there risks are evolving.

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Speaker 1: So they're they're pro cyclical with the market, and they're

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Speaker 1: just very large in size billions and billions and billions

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Speaker 1: of dollars, and so they're less well hedged just because

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Speaker 1: their their risks are much more complex. On the equity side,

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Speaker 1: you know a lot of exotic type products can generate

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Speaker 1: convexity as well, and those, you know, you can hedge that.

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Speaker 1: But um, the the risks embedded in exotic instruments like

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Speaker 1: these structured notes and other things are very on linear.

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Speaker 1: In many cases, there are sort of binary type risk

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Speaker 1: and other things that it's just hard to keep up frankly. UM.

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Speaker 1: And and so even if you have decent hedged positions

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Speaker 1: out there, I think, on the one hand, and this

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Speaker 1: is more a rates thing than an equace thing, like

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Speaker 1: if the if the environment is changing, that's going to

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Speaker 1: blow through all of these all of these protections, because

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Speaker 1: it's impossible if you're fully hedged. You know, I'm making

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Speaker 1: any money, right, so, so nobody's nobody's ever fully hedged.

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Speaker 1: Otherwise it's you might as well just not be participating

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Speaker 1: in investing. UM. And so those residuals can get very big,

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Speaker 1: very quickly. UM. So I guess a a sort of

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Speaker 1: long winded way to answer the question, which is, I

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Speaker 1: think it's sort of functionally impossible for everyone to be

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Speaker 1: fully hedged. And the event of a sufficiently large macro shock,

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Speaker 1: which again doesn't need to be anything other than the

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Speaker 1: passing of the event itself, which in some sense was

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Speaker 1: the case in two thousand sixteen, UM, you can you

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Speaker 1: can generate these these spirals that that keep out the

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Speaker 1: volatility ellow at it for a long time. UM. It's

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Speaker 1: important to say that the presidential elections are rarely that thing,

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Speaker 1: so is very much the aberration. Usually you get a

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Speaker 1: couple of decently large moves in the lead up and

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Speaker 1: in the aftermath of the election invent itself. But even

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Speaker 1: in two thousand, when we didn't really know the result

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Speaker 1: for weeks, like, the volatility was modestly elevated, but it

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Speaker 1: really wasn't anything like um. And and then if you

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Speaker 1: go back further, you know, in the eighties these weren't

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Speaker 1: really particularly contested elections. Even in the nineties they were

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Speaker 1: pretty solid results. And so now we're talking about the seventies,

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Speaker 1: and I think at that point the utility of the

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Speaker 1: of the analogy kind of drops off quite a bit.

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Speaker 1: Talk to us about the hedging needs of investors this year,

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Speaker 1: because it's been a really weird year. So, I mean,

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Speaker 1: you have some investors that are probably sitting on fantastic

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Speaker 1: gains that they never would have expected to reap in

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Speaker 1: a year in which we have this terrible economic outcome

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Speaker 1: and a pandemic and so forth. So that's maybe some

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Speaker 1: inclination to lock in those gains. We've also had a

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Speaker 1: lot of people missed this ralliant somewhere or another, either

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Speaker 1: because they were just under invested throughout the whole thing,

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Speaker 1: or maybe just overly hedge throughout this whole time due

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Speaker 1: to fears about some second wave or second shoe about

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Speaker 1: to drop. So as people look towards the election, how

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Speaker 1: has what we've seen building up to it influenced their

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Speaker 1: desire to hedge against various outcomes? So so I think

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Speaker 1: there's two really interesting behavioral elements to this. The first is,

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Speaker 1: if you're sitting on very significant gains, you're very highly

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Speaker 1: incentivized not to lose them. And so if if we're

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Speaker 1: trying to figure out why options markets would price so

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Speaker 1: much excess risk around this particular election, On the one hand,

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Speaker 1: there's just the memory of sixteen, but that's not a

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Speaker 1: great argument because that's just saying, you know, I don't

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Speaker 1: want this to happen to me again. But more importantly,

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Speaker 1: I think we were talking about time value before, Like

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Speaker 1: the election is not that far and so the actual

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Speaker 1: dollars you need to put up to protect yourself is

386
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Speaker 1: not that many, and so the price of that option

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Speaker 1: can adjust significantly on relatively small dollar amounts of trading.

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Speaker 1: And so if you're sitting on significant gains, is a

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Speaker 1: hedge funder or individual or asset manager anybody. UM, you

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Speaker 1: know that insurance cost is relatively low, so you might

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Speaker 1: as well buy it. Um And and the the converse

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Speaker 1: is true too, which is why would you sell insurance

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Speaker 1: premium and a relatively small dollar amount when you look

394
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Speaker 1: insane if you get it wrong, It's just like, that's

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Speaker 1: a really bad look for selling those options. Like, no

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Speaker 1: one wants to have that conversation with their boss. Why

397
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Speaker 1: did you sell a bunch of puts on the SMP

398
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Speaker 1: like two weeks before the election? Right? So, so like

399
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Speaker 1: if you have a bias towards buyers of this risk,

400
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Speaker 1: they don't have to put up a ton of concrete

401
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Speaker 1: dollars to get it. And the incentives are very highly

402
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Speaker 1: skewed in favor of protecting gains. You're going to get

403
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Speaker 1: very expensive options optically, And this is where that adjustment.

404
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Speaker 1: If I if the price of a one year option

405
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Speaker 1: was at levels that the price of a two week

406
00:23:25,880 --> 00:23:28,160
Speaker 1: option we're trading, it would be a very expensive instrument.

407
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Speaker 1: But realistically we're talking about a handful of days of

408
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Speaker 1: protection and that just comes relatively inexpensive. So who's actually

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Speaker 1: selling volatility protection this year? Then? I mean, again, it's

410
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Speaker 1: been such an unusual year, and we've seen a lot

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Speaker 1: of options trades exploding in popularity. Who are the big

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Speaker 1: sellers of protection at the moment, So in many cases

413
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Speaker 1: it's the dealers themselves that meaning they don't have the

414
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Speaker 1: other side in full UM. There is a uh there.

415
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Speaker 1: There is a pretty large and relatively persistent systematic program

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Speaker 1: UM that's employed by a range of investors. But basically

417
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Speaker 1: the ideas options tend to trade relatively rich, and so

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Speaker 1: it's a good sort of risk addusted return to keep

419
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Speaker 1: selling them. So harvesting that risk premium over time will

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Speaker 1: be a good returns relative to the volatility of that

421
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Speaker 1: position volatiling in this case, meaning the returns on that

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Speaker 1: strategy of selling options UM that that's been around for

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Speaker 1: years and years and years, twenty years really UM as

424
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Speaker 1: of the two thousand five vintage like that was really

425
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Speaker 1: a consequence of at least in rates markets. Fannie and

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Speaker 1: Freddie were very large UM. They had a trillion dollars

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Speaker 1: in their retain portfolio of mortgage backed securities, and their

428
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Speaker 1: business model was to buy mortgage backed securities, hedge the

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Speaker 1: duration risk with swaps, and then buy back options that

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Speaker 1: replicate the borrowers option to prepay their their mortgage, and

431
00:25:00,119 --> 00:25:03,359
Speaker 1: they were harvesting that what people call it the mortgageness

432
00:25:03,400 --> 00:25:05,080
Speaker 1: of the mortgage. But you can build a model that

433
00:25:05,119 --> 00:25:07,480
Speaker 1: tries to use all the rate risk you can to

434
00:25:07,480 --> 00:25:10,800
Speaker 1: replicate the risks embedded in a mortgage instrument, and whatever

435
00:25:10,880 --> 00:25:12,600
Speaker 1: is left over is the thing that Fannie and Freddie

436
00:25:12,600 --> 00:25:14,719
Speaker 1: wanted to earn. And they had forty turns of leverage,

437
00:25:14,760 --> 00:25:18,360
Speaker 1: so point two times forty is is a pretty good

438
00:25:18,359 --> 00:25:21,720
Speaker 1: return basically UM. And so what that meant was they're

439
00:25:21,720 --> 00:25:24,399
Speaker 1: willing to buy options at a relatively expensive level, and

440
00:25:24,400 --> 00:25:27,840
Speaker 1: whoever was selling them those options was participating to some

441
00:25:27,920 --> 00:25:31,600
Speaker 1: extent in this in this transformation and earning a bit

442
00:25:31,640 --> 00:25:34,200
Speaker 1: of a transaction cost associated with the Fattie and Freddie

443
00:25:34,200 --> 00:25:37,520
Speaker 1: and Fanny programs. UM. That hasn't been the case in

444
00:25:37,520 --> 00:25:41,399
Speaker 1: a very long time. And yet it's been relatively profitable

445
00:25:41,440 --> 00:25:44,720
Speaker 1: to just keep selling options every day, agnostic to the environment.

446
00:25:44,800 --> 00:25:47,680
Speaker 1: So there have been these programs that have built up

447
00:25:48,160 --> 00:25:50,919
Speaker 1: to continue this trade even even as Fanny and Freddie

448
00:25:51,200 --> 00:25:54,600
Speaker 1: have shrunk, and they've been really active at least since

449
00:25:55,760 --> 00:25:59,520
Speaker 1: and and grown and shrunk and over time. But with

450
00:25:59,600 --> 00:26:03,679
Speaker 1: the with the very brief exception of March and April

451
00:26:03,840 --> 00:26:08,320
Speaker 1: this year, they've been pretty persistent through periods of volatility,

452
00:26:08,359 --> 00:26:10,679
Speaker 1: which which is supposed to be what what you do

453
00:26:10,720 --> 00:26:12,480
Speaker 1: with a strategy like that. If you are in a

454
00:26:12,560 --> 00:26:15,719
Speaker 1: systematic strategy, you're not supposed to sit there and say, well,

455
00:26:15,720 --> 00:26:17,920
Speaker 1: it doesn't feel right today, so I'm not going to

456
00:26:18,080 --> 00:26:20,639
Speaker 1: do it. Um. And so I mean I think in

457
00:26:20,640 --> 00:26:22,400
Speaker 1: March it was pretty easy to say it doesn't feel

458
00:26:22,480 --> 00:26:26,119
Speaker 1: right today. Um, when you have the largest discrepancies in

459
00:26:26,160 --> 00:26:30,800
Speaker 1: pricing and and moves in in basically history. Um. And

460
00:26:31,040 --> 00:26:33,760
Speaker 1: we talked about that back in in April. So maybe

461
00:26:33,760 --> 00:26:36,440
Speaker 1: that's the exception, But um, you're really supposed to keep

462
00:26:36,480 --> 00:26:38,760
Speaker 1: doing this through periods of stress, in fact, periods of

463
00:26:38,760 --> 00:26:40,639
Speaker 1: stress or when you earn most of your money and

464
00:26:40,640 --> 00:26:43,719
Speaker 1: a strategy like that, And and it's likely that that

465
00:26:43,800 --> 00:26:49,119
Speaker 1: kind of activity has persisted today. Why hasn't the premium

466
00:26:49,160 --> 00:26:52,200
Speaker 1: on options selling going away? I mean, if it's been

467
00:26:52,240 --> 00:26:57,520
Speaker 1: profitable for twenty years, if people seem to systematically overpay

468
00:26:57,560 --> 00:27:01,880
Speaker 1: for protection, um, why isn't that, just like everything else,

469
00:27:01,960 --> 00:27:03,840
Speaker 1: like sort of crowded out to the point where there's

470
00:27:03,840 --> 00:27:06,520
Speaker 1: no money left in it? Yeah? There should be alpha

471
00:27:06,560 --> 00:27:09,359
Speaker 1: decay and stuff like that. Uh, it's it's one of

472
00:27:09,400 --> 00:27:13,119
Speaker 1: those sort of great mysteries of of interest rate derivative markets,

473
00:27:13,200 --> 00:27:16,520
Speaker 1: and and some people have attributed this to central bank

474
00:27:16,720 --> 00:27:22,600
Speaker 1: activity and and just repression of volatility across various asset classes,

475
00:27:22,680 --> 00:27:26,160
Speaker 1: especially interest rates. So basically the idea of being you're

476
00:27:26,240 --> 00:27:28,320
Speaker 1: you're not fighting the FED by selling options, you're going

477
00:27:28,320 --> 00:27:32,439
Speaker 1: with the FED in doing so, and the presumption that

478
00:27:32,480 --> 00:27:36,800
Speaker 1: the FED will backstop any significant period of volatility with

479
00:27:36,920 --> 00:27:41,119
Speaker 1: purchases that dampen it UM. I don't particularly like that

480
00:27:41,200 --> 00:27:44,240
Speaker 1: narrative just because it's a very strong assumption and and

481
00:27:44,600 --> 00:27:46,919
Speaker 1: we don't really there's there's no reason to believe that

482
00:27:47,080 --> 00:27:50,280
Speaker 1: specifically what's going on day to day. Um. There's also

483
00:27:50,359 --> 00:27:54,320
Speaker 1: this presumption that options are pricing in much higher risk

484
00:27:54,400 --> 00:27:56,879
Speaker 1: of jumps. So when we think of an options price,

485
00:27:57,119 --> 00:28:01,840
Speaker 1: the models that people typically build, they assume some probability

486
00:28:01,880 --> 00:28:04,240
Speaker 1: that will be these discontinuous jumps in the middle of

487
00:28:04,280 --> 00:28:07,639
Speaker 1: the day. And in October was a great example of that,

488
00:28:07,680 --> 00:28:10,840
Speaker 1: where tenure yields drop thirty basis points in ten minutes

489
00:28:10,840 --> 00:28:13,800
Speaker 1: and then came right back. And when you start pricing

490
00:28:13,800 --> 00:28:18,000
Speaker 1: in significant jump risk into the options, it bleeds through

491
00:28:18,080 --> 00:28:21,679
Speaker 1: to other sort of prices associate with them, so it

492
00:28:21,680 --> 00:28:24,440
Speaker 1: makes all options richer. If you think there's some chance

493
00:28:24,520 --> 00:28:26,680
Speaker 1: of these kinds of jumps, and what would generate a

494
00:28:26,760 --> 00:28:29,240
Speaker 1: jump an election result to generate a jump that happened

495
00:28:29,240 --> 00:28:32,240
Speaker 1: in twenty sixteen, You can have the Brexit outcome. Things

496
00:28:32,280 --> 00:28:35,960
Speaker 1: like that. You could have developments overnight with the Chinese

497
00:28:36,000 --> 00:28:39,200
Speaker 1: Yuandi val and implications for for rates, markets and e

498
00:28:39,360 --> 00:28:42,320
Speaker 1: M and so forth. So maybe that could generate some riches.

499
00:28:42,440 --> 00:28:45,200
Speaker 1: But that's me kind of grasping at straws. Frankly, I

500
00:28:45,200 --> 00:28:48,600
Speaker 1: think the usual response has been, UM, I don't know,

501
00:28:48,640 --> 00:28:51,600
Speaker 1: but it keeps working, so which is not a great

502
00:28:51,640 --> 00:28:54,120
Speaker 1: reason to keep doing it, but it is a reason

503
00:28:54,160 --> 00:28:56,280
Speaker 1: to keep doing it. And it's been ten years now,

504
00:28:56,760 --> 00:29:00,760
Speaker 1: ten fifteen years, and it's been a persistent, uh, you know,

505
00:29:00,840 --> 00:29:05,400
Speaker 1: reasonably good return type strategy. UM. I wanted to go

506
00:29:05,440 --> 00:29:11,280
Speaker 1: back to some of your older research, so I gosh,

507
00:29:11,320 --> 00:29:13,400
Speaker 1: I guess it was just last year, but it feels

508
00:29:13,440 --> 00:29:16,600
Speaker 1: like ages ago. You created this thing called the vole

509
00:29:16,760 --> 00:29:21,360
Speaker 1: Fefe index, which basically had well you can explain it,

510
00:29:21,400 --> 00:29:25,920
Speaker 1: but attempted to quantify the impact of Donald Trump's tweeting

511
00:29:26,280 --> 00:29:30,000
Speaker 1: on the rates market, and I know you've been revisiting

512
00:29:30,280 --> 00:29:33,240
Speaker 1: that index every once in a while over the past

513
00:29:33,520 --> 00:29:37,440
Speaker 1: year or so. I guess my question is how much

514
00:29:37,560 --> 00:29:43,520
Speaker 1: does the rates volatility regime change if Biden wins the

515
00:29:43,560 --> 00:29:48,880
Speaker 1: election and you get a more traditional president, let's say,

516
00:29:48,960 --> 00:29:52,600
Speaker 1: one who's less active on social media, for instance, Does

517
00:29:52,640 --> 00:29:55,360
Speaker 1: it change everything for the rates market? Do you have

518
00:29:55,440 --> 00:30:00,760
Speaker 1: to discontinue vol fefe? Probably? So this was work that

519
00:30:00,840 --> 00:30:03,080
Speaker 1: a colleague of my men your sale did and he

520
00:30:03,120 --> 00:30:04,800
Speaker 1: came up with the name. So I shouldn't take credit

521
00:30:05,000 --> 00:30:09,800
Speaker 1: for that, um. And basically the idea was it it

522
00:30:09,840 --> 00:30:12,480
Speaker 1: had felt this way to a lot of people, that

523
00:30:12,480 --> 00:30:16,400
Speaker 1: that the president's tweets had an impact on markets um

524
00:30:16,520 --> 00:30:19,560
Speaker 1: and when they veered towards certain topics, they had a

525
00:30:19,560 --> 00:30:21,960
Speaker 1: greater impact on markets. And at the time, this was

526
00:30:22,080 --> 00:30:24,280
Speaker 1: the height of the trade war. And so you get

527
00:30:24,320 --> 00:30:27,200
Speaker 1: these pronouncements over Twitter about the progress of talks, and

528
00:30:27,400 --> 00:30:31,080
Speaker 1: I remember people being very focused on parsoning words and

529
00:30:31,360 --> 00:30:33,479
Speaker 1: the likelihood of a deal or not a deal, or

530
00:30:33,560 --> 00:30:35,680
Speaker 1: with tears go up or not go up? And and

531
00:30:35,840 --> 00:30:38,520
Speaker 1: and basically the idea was, let's try to put some

532
00:30:38,640 --> 00:30:42,440
Speaker 1: numbers around this. And the reason why this works in

533
00:30:42,480 --> 00:30:45,560
Speaker 1: the first places is for two elements, the first being political,

534
00:30:45,600 --> 00:30:49,280
Speaker 1: which is um, policy announcements were made over Twitter, which

535
00:30:49,320 --> 00:30:52,280
Speaker 1: is a sharp departure. Obama had a Twitter account, but

536
00:30:52,280 --> 00:30:55,000
Speaker 1: that he didn't announce new policies on it, at least

537
00:30:55,720 --> 00:31:00,480
Speaker 1: not initially UM. And just the policy process changed in

538
00:31:00,520 --> 00:31:03,800
Speaker 1: Twitter was a good or was it was a preferred

539
00:31:04,400 --> 00:31:06,400
Speaker 1: vehicle for making those announcements, and so we had to

540
00:31:06,440 --> 00:31:08,960
Speaker 1: pay attention whether we like it or not. UM. The

541
00:31:09,000 --> 00:31:11,600
Speaker 1: second is it's more of a technical thing, but it

542
00:31:11,640 --> 00:31:15,440
Speaker 1: turns out this is a very good problem for machine learning.

543
00:31:15,480 --> 00:31:19,400
Speaker 1: And the reason and natural language processing because UM, the

544
00:31:19,520 --> 00:31:23,640
Speaker 1: data we use it was something like tweets, which is

545
00:31:23,640 --> 00:31:27,800
Speaker 1: not a massive database, but the language that Trump uses

546
00:31:27,880 --> 00:31:32,280
Speaker 1: is pretty consistent and frankly doesn't use that many words. UM.

547
00:31:32,400 --> 00:31:35,920
Speaker 1: And so if you want to try to to digitize

548
00:31:35,960 --> 00:31:40,000
Speaker 1: that in a way that can be analyzed systematically, it's

549
00:31:40,080 --> 00:31:42,440
Speaker 1: it's a good it's a good toy problem for it.

550
00:31:42,440 --> 00:31:44,640
Speaker 1: It's something you can do in a desktop. It doesn't

551
00:31:44,640 --> 00:31:46,920
Speaker 1: take up cherabytes of memory. This is not like trying

552
00:31:46,920 --> 00:31:49,040
Speaker 1: to teach a car how to self drive. This is

553
00:31:49,080 --> 00:31:54,760
Speaker 1: like a very concrete question does this tweet effect market? Um?

554
00:31:54,840 --> 00:31:57,280
Speaker 1: So we can we can very clearly like tag tweets

555
00:31:57,280 --> 00:31:59,080
Speaker 1: as having moved or not moved markets. We don't have

556
00:31:59,120 --> 00:32:01,440
Speaker 1: to try to figure out what sentiment is. Usually when

557
00:32:01,440 --> 00:32:04,760
Speaker 1: we talk about natural language processing, we're talking about like

558
00:32:04,800 --> 00:32:07,520
Speaker 1: good or bad? Is this a good or bad statement? Here,

559
00:32:07,520 --> 00:32:09,360
Speaker 1: we're just saying to the market move. So it's it's

560
00:32:09,360 --> 00:32:14,400
Speaker 1: easy to build a database of of tweets and impact. UM.

561
00:32:14,440 --> 00:32:16,880
Speaker 1: We don't have to think about that much variation in

562
00:32:16,880 --> 00:32:20,560
Speaker 1: the language because it's uses pretty clear, it's pretty consistent,

563
00:32:20,760 --> 00:32:23,120
Speaker 1: not a ton of words, So it's it's something you

564
00:32:23,160 --> 00:32:27,560
Speaker 1: can analyze pretty straightforwardly. UM. And our goal was to

565
00:32:27,600 --> 00:32:29,080
Speaker 1: come up with it. It was more of a detection

566
00:32:29,120 --> 00:32:31,840
Speaker 1: than a forecast. I've I've often got the question like

567
00:32:32,560 --> 00:32:36,040
Speaker 1: does this tweet move markets? Or is this tweet more

568
00:32:36,080 --> 00:32:38,280
Speaker 1: or less likely to move markets than that tweet? And

569
00:32:38,360 --> 00:32:41,480
Speaker 1: I think that the idea here was less to get

570
00:32:41,520 --> 00:32:45,280
Speaker 1: a forecast for any particular Twitter announcement, but to say,

571
00:32:45,760 --> 00:32:49,680
Speaker 1: what's the background of noise that this creates, Like to

572
00:32:49,760 --> 00:32:54,040
Speaker 1: what extent does the accumulated uncertainty with the potential for

573
00:32:54,120 --> 00:32:58,160
Speaker 1: tweeting in general? And especially on particular topics. Does that

574
00:32:58,680 --> 00:33:04,080
Speaker 1: lead to elevated levels of implied volatility? Meaning protection from

575
00:33:04,080 --> 00:33:07,680
Speaker 1: options is more expensive because any minute now the president

576
00:33:07,680 --> 00:33:10,760
Speaker 1: can tweet about the Chinese Strait negotiations. UM. And so

577
00:33:11,400 --> 00:33:13,560
Speaker 1: what we do is we we took this database of tweets.

578
00:33:13,560 --> 00:33:16,160
Speaker 1: We we tried to identify the words that occurred more

579
00:33:16,160 --> 00:33:18,560
Speaker 1: frequently in those that moved the market, and then we

580
00:33:18,680 --> 00:33:21,840
Speaker 1: built a random forest model that tried to account not

581
00:33:21,920 --> 00:33:25,000
Speaker 1: only for the relatives sort of value of each of

582
00:33:25,000 --> 00:33:29,280
Speaker 1: those words and categories in generating market moves, but also

583
00:33:29,320 --> 00:33:33,280
Speaker 1: the interactions between them. So if us if good appeared

584
00:33:33,280 --> 00:33:35,080
Speaker 1: with the word China that had a different meaning than

585
00:33:35,120 --> 00:33:37,680
Speaker 1: have good appeared with with a different word, and and

586
00:33:37,760 --> 00:33:40,960
Speaker 1: so the classic NLP problem. And so what we found

587
00:33:41,000 --> 00:33:44,920
Speaker 1: was when we generated this index UM, it had statistical

588
00:33:44,960 --> 00:33:47,800
Speaker 1: significance in modeling volatility. And what does that mean. It

589
00:33:47,840 --> 00:33:50,480
Speaker 1: means that if we're trying to explain the drivers of

590
00:33:50,520 --> 00:33:55,000
Speaker 1: interest rate volatility and we incorporate this index into that

591
00:33:55,200 --> 00:34:00,720
Speaker 1: statistical explanation, it plays a significant role. So UM, to

592
00:34:01,240 --> 00:34:02,800
Speaker 1: directly answer your question, if if we move to a

593
00:34:02,840 --> 00:34:06,400
Speaker 1: Biden presidency, I don't know what his twitter Twitter habits

594
00:34:06,440 --> 00:34:09,160
Speaker 1: will be I think it's fair to say they would

595
00:34:09,160 --> 00:34:11,400
Speaker 1: be different. Maybe I should hedge a little bit and

596
00:34:11,440 --> 00:34:13,000
Speaker 1: say we'd have to wait and see and try to

597
00:34:13,040 --> 00:34:15,799
Speaker 1: generate enough data to build a model. But looking at

598
00:34:15,800 --> 00:34:18,239
Speaker 1: the at Joe Biden twitter feed versus the at real

599
00:34:18,320 --> 00:34:20,279
Speaker 1: Donald Trump twitter feed, I think it's fair to say

600
00:34:20,760 --> 00:34:26,120
Speaker 1: his look sort of more vetted and um less and

601
00:34:26,200 --> 00:34:28,960
Speaker 1: much more consistent with policies that have been previously announced.

602
00:34:29,200 --> 00:34:32,759
Speaker 1: And so the utility of watching Joe Biden's Twitter feed

603
00:34:32,800 --> 00:34:36,440
Speaker 1: is probably less in a Biden presidency than than that

604
00:34:36,520 --> 00:34:40,239
Speaker 1: of watching Trump's and the Trump presidency. So, um, I

605
00:34:40,280 --> 00:34:42,319
Speaker 1: don't know if we have to mothball it, because who

606
00:34:42,320 --> 00:34:46,359
Speaker 1: knows whether that framework is useful in the future, But

607
00:34:46,800 --> 00:34:50,080
Speaker 1: at a minimum, it means the background level of uncertainty

608
00:34:50,200 --> 00:34:55,360
Speaker 1: comes down because you're transitioning back to a policy process

609
00:34:55,440 --> 00:35:00,319
Speaker 1: where new ideas are vetted internally leaked out in some

610
00:35:00,440 --> 00:35:06,600
Speaker 1: fashion through appearances in the Sunday shows or through articles newspapers,

611
00:35:06,680 --> 00:35:09,840
Speaker 1: and you're going back to a more traditional policy policy

612
00:35:10,400 --> 00:35:15,040
Speaker 1: generating process that doesn't really rely on on Twitter as much. Um. God,

613
00:35:15,080 --> 00:35:17,920
Speaker 1: I can't even I can't even imagine what that world

614
00:35:17,920 --> 00:35:20,520
Speaker 1: could be like, it's it's almost it's so it's like

615
00:35:20,560 --> 00:35:23,040
Speaker 1: I have this vague memory that things used to operate

616
00:35:23,120 --> 00:35:26,120
Speaker 1: like that. I want to ask you another question about

617
00:35:26,320 --> 00:35:31,239
Speaker 1: the current regime, and again not necessarily relating to the

618
00:35:31,280 --> 00:35:35,080
Speaker 1: imminent election, but one of the things on the right

619
00:35:35,160 --> 00:35:38,680
Speaker 1: side that's really sort of characterized the past several months

620
00:35:39,239 --> 00:35:43,719
Speaker 1: is essentially just the fact that the FED has indicated

621
00:35:43,880 --> 00:35:48,360
Speaker 1: very strongly that the bar to a future the first

622
00:35:48,440 --> 00:35:51,080
Speaker 1: rate hike or a future rate hike is probably higher

623
00:35:51,120 --> 00:35:55,000
Speaker 1: than it's ever been before, very ambitious goals with hitting

624
00:35:55,000 --> 00:35:59,560
Speaker 1: its inflation target, full employment, far more forward guidance than

625
00:35:59,600 --> 00:36:02,200
Speaker 1: we ever got during past recoveries or anything like that.

626
00:36:02,239 --> 00:36:05,640
Speaker 1: And as such, even through this huge stock market rally

627
00:36:05,640 --> 00:36:08,839
Speaker 1: from the end of March through now, basically we've seen

628
00:36:08,880 --> 00:36:11,759
Speaker 1: almost no upward move in rates, and I'm curious, like,

629
00:36:12,080 --> 00:36:15,399
Speaker 1: how does that change the game from your perspective, from

630
00:36:15,400 --> 00:36:18,080
Speaker 1: a rates volutility of perspective, The fact that we have

631
00:36:18,239 --> 00:36:22,320
Speaker 1: so much aggressive forward guided so little uh so, a

632
00:36:22,440 --> 00:36:24,520
Speaker 1: little left to the imagination in terms of what the

633
00:36:24,560 --> 00:36:26,800
Speaker 1: FED is going to do. Yeah, so forward guidance is

634
00:36:26,880 --> 00:36:30,600
Speaker 1: very effective at suppressing volatility, when when we didn't experiment recently,

635
00:36:31,239 --> 00:36:34,239
Speaker 1: we took options that the experty was a year out,

636
00:36:34,280 --> 00:36:36,319
Speaker 1: two years out, three years out, five years out, ten

637
00:36:36,400 --> 00:36:39,239
Speaker 1: years out, and we said, you know, these options are

638
00:36:39,280 --> 00:36:42,240
Speaker 1: related to one of two things really, one the pricing

639
00:36:42,239 --> 00:36:47,480
Speaker 1: of them, one the policy outlook. So that's forward guidance. UM.

640
00:36:47,719 --> 00:36:50,440
Speaker 1: I think we used something like the months until the

641
00:36:50,480 --> 00:36:55,040
Speaker 1: next hype per hYP per the FEDS pronouncements, and we

642
00:36:55,080 --> 00:36:57,319
Speaker 1: have a series for that. We can go back and

643
00:36:57,320 --> 00:36:58,799
Speaker 1: just say when did they think they were gonna hike?

644
00:36:58,840 --> 00:37:00,600
Speaker 1: And they had forward guidance into any ten and they

645
00:37:00,600 --> 00:37:05,200
Speaker 1: had forward guns in twenty twelve and they forward guidance again. Um.

646
00:37:06,080 --> 00:37:09,520
Speaker 1: The second part was proxying these exotics flows that that

647
00:37:09,640 --> 00:37:12,360
Speaker 1: tend to drive very long dated options volatility. So this

648
00:37:12,440 --> 00:37:14,799
Speaker 1: comes back to the Taiwanese life insurance companies, which will

649
00:37:14,800 --> 00:37:17,959
Speaker 1: probably talk about at some point we could get bred

650
00:37:18,000 --> 00:37:19,960
Speaker 1: on here, bred sets around here, and we can never

651
00:37:20,000 --> 00:37:24,360
Speaker 1: get enough exactly. Uh. And so what we found was

652
00:37:24,600 --> 00:37:26,800
Speaker 1: if you go out two or three years in expiry,

653
00:37:26,840 --> 00:37:28,200
Speaker 1: so if you want protection for the next two or

654
00:37:28,239 --> 00:37:31,000
Speaker 1: three years, the price of that protection is mostly related

655
00:37:31,040 --> 00:37:34,480
Speaker 1: to this forward guide. So as the forward guidance becomes stronger,

656
00:37:34,520 --> 00:37:37,040
Speaker 1: and further out, the price of that protection comes down

657
00:37:37,080 --> 00:37:39,920
Speaker 1: because in a sense, the FIT is subsidizing it with

658
00:37:40,040 --> 00:37:43,920
Speaker 1: their with their policy. Then when you get further out

659
00:37:43,960 --> 00:37:45,879
Speaker 1: than that, you start getting into this world of well,

660
00:37:45,880 --> 00:37:48,760
Speaker 1: who really trades tenure options on thirty year rates, and

661
00:37:48,880 --> 00:37:53,400
Speaker 1: then you're really talking about much different not really informed

662
00:37:53,400 --> 00:37:57,000
Speaker 1: by likely that as informed by likely realized volatility over

663
00:37:57,040 --> 00:38:00,200
Speaker 1: the next ten years. You're informed by the vale. You

664
00:38:00,239 --> 00:38:02,719
Speaker 1: have that ten years of protection to a very specific

665
00:38:02,760 --> 00:38:07,040
Speaker 1: and relatively idiosyncratic subset. So so you know, to answer

666
00:38:07,080 --> 00:38:10,320
Speaker 1: your question like, it suppresses volatility at least out um

667
00:38:10,480 --> 00:38:15,000
Speaker 1: ways in the term structure UM. And yeah, I think

668
00:38:15,040 --> 00:38:17,680
Speaker 1: the FED has made it very clear that that that's

669
00:38:17,719 --> 00:38:20,520
Speaker 1: their plans, So you know they're they're not purchasing assets

670
00:38:21,200 --> 00:38:24,160
Speaker 1: to tap yields out of three to five years. That

671
00:38:24,239 --> 00:38:26,920
Speaker 1: was something that was sort of floated or speculated at

672
00:38:26,960 --> 00:38:29,720
Speaker 1: times a firm of a form of yield curve control,

673
00:38:29,800 --> 00:38:32,799
Speaker 1: but one that's very tied to reinforcing forward guidance as

674
00:38:32,840 --> 00:38:35,240
Speaker 1: opposed to say, what the Bank of Japan is doing. UM.

675
00:38:35,280 --> 00:38:38,600
Speaker 1: But I think the FED has plenty of credibility in

676
00:38:38,640 --> 00:38:42,800
Speaker 1: this department UM. Their their communications are very clear um,

677
00:38:42,880 --> 00:38:46,680
Speaker 1: and you know it just has not generally paid to

678
00:38:46,800 --> 00:39:01,440
Speaker 1: fight these things. So the feed is suppressing volatility. Plus

679
00:39:01,640 --> 00:39:05,200
Speaker 1: for various reasons that you've already described, you have the

680
00:39:05,239 --> 00:39:10,520
Speaker 1: price of near term volatility protection that's quite reasonable and

681
00:39:10,640 --> 00:39:13,279
Speaker 1: cheap at the moment. So I guess my question is,

682
00:39:13,360 --> 00:39:18,000
Speaker 1: if come November we have the election and everything goes

683
00:39:18,719 --> 00:39:21,640
Speaker 1: sort of not according to plan, but everything goes as

684
00:39:21,680 --> 00:39:27,600
Speaker 1: expected and indicated by the polls currently, how quickly does

685
00:39:27,719 --> 00:39:31,840
Speaker 1: the risk premium that's currently built into markets go away

686
00:39:32,200 --> 00:39:36,200
Speaker 1: if at all? Well, it depends a bit on the Senate.

687
00:39:36,200 --> 00:39:38,719
Speaker 1: So we talked about the presidency a lot, but that

688
00:39:40,400 --> 00:39:44,520
Speaker 1: GDP target for for the stock of government debt that

689
00:39:44,600 --> 00:39:47,920
Speaker 1: depends on Biden actually being able to do things, and

690
00:39:48,280 --> 00:39:49,800
Speaker 1: in order to do things, he needs to have the

691
00:39:49,840 --> 00:39:52,240
Speaker 1: support of both houses of Congress because the vast majority

692
00:39:52,280 --> 00:39:56,040
Speaker 1: of fiscal policy is going to be an Act of Congress. So, um,

693
00:39:56,200 --> 00:39:59,000
Speaker 1: the the outcome of the Senate is key there. If

694
00:39:59,000 --> 00:40:02,080
Speaker 1: you have a democratic leap, which I think betting markets

695
00:40:02,080 --> 00:40:07,239
Speaker 1: haven't what or fifty and these quantitative election models like

696
00:40:07,960 --> 00:40:12,160
Speaker 1: have that closer to seventy. So if you have that

697
00:40:12,239 --> 00:40:15,280
Speaker 1: kind of outcome, then there's potential for a real shift

698
00:40:15,280 --> 00:40:19,000
Speaker 1: in policy um, and that could generate volatility just simply

699
00:40:19,040 --> 00:40:20,879
Speaker 1: for the reasons we were talking about earlier. Now now

700
00:40:20,920 --> 00:40:22,920
Speaker 1: there's now we know what's going to happen, and so

701
00:40:22,960 --> 00:40:25,640
Speaker 1: we're going to reprice the market significantly, and I don't

702
00:40:25,640 --> 00:40:31,160
Speaker 1: think options markets anticipate necessarily that, meaning an extended period

703
00:40:31,160 --> 00:40:35,160
Speaker 1: of repricing of interest rates UM. A lot of that

704
00:40:35,280 --> 00:40:39,360
Speaker 1: election risk has really become more concentrated around the event itself.

705
00:40:39,480 --> 00:40:42,960
Speaker 1: If you have a split power situation, you know, I

706
00:40:43,000 --> 00:40:46,480
Speaker 1: think it's it's quite suppressive of volatility only because it's

707
00:40:46,600 --> 00:40:51,000
Speaker 1: unclear what beyond the current status quo could possibly happen.

708
00:40:51,440 --> 00:40:53,680
Speaker 1: You know that the one caveat to that being if

709
00:40:53,719 --> 00:40:58,600
Speaker 1: literally nothing can get done, then there's a macroeconomic consequence

710
00:40:58,640 --> 00:41:01,920
Speaker 1: to that, which is in the absence of support from

711
00:41:01,920 --> 00:41:05,080
Speaker 1: the federal government, like what is what what is you

712
00:41:05,120 --> 00:41:07,600
Speaker 1: canotic growth? What is GDP do? What is what does

713
00:41:07,600 --> 00:41:10,640
Speaker 1: employment do? Etcetera, And so like that's kind of the

714
00:41:10,880 --> 00:41:14,640
Speaker 1: caveat there um. But you know, I think what's what's

715
00:41:14,680 --> 00:41:17,120
Speaker 1: really interesting about this is it comes back to the

716
00:41:17,160 --> 00:41:19,799
Speaker 1: FED again, which is, let's say there's a democratic suite

717
00:41:20,320 --> 00:41:25,440
Speaker 1: and the Biden campaign platform is is implemented. So this

718
00:41:25,520 --> 00:41:28,880
Speaker 1: brings up broader questions of fiscal dominance, meaning what is

719
00:41:28,880 --> 00:41:31,520
Speaker 1: the role of the FED in an environment where the

720
00:41:31,560 --> 00:41:36,000
Speaker 1: dead is expanding that quickly? And the question that I

721
00:41:36,040 --> 00:41:39,160
Speaker 1: think the market is grappling with is on the one hand,

722
00:41:39,239 --> 00:41:41,799
Speaker 1: the FED is clearly not tied their purchase program to

723
00:41:42,840 --> 00:41:46,360
Speaker 1: fiscal policy, and nor should they, right, independence is important,

724
00:41:47,080 --> 00:41:51,200
Speaker 1: But they've also be very firmly committed themselves to to

725
00:41:51,280 --> 00:41:53,960
Speaker 1: market functioning. And this is a lot what was going

726
00:41:54,000 --> 00:41:56,280
Speaker 1: on in March that the centrality of the treasury market

727
00:41:56,360 --> 00:41:59,560
Speaker 1: not just as an investment, but in just the flow

728
00:41:59,560 --> 00:42:03,080
Speaker 1: of money throughout the financial system and as a provider

729
00:42:03,120 --> 00:42:05,960
Speaker 1: a provider of liquidity to the banking system, and like it,

730
00:42:06,080 --> 00:42:09,000
Speaker 1: it serves a much more important purpose than simply a

731
00:42:09,080 --> 00:42:13,719
Speaker 1: risk free investment. Um. So, if market functioning is part

732
00:42:13,800 --> 00:42:15,880
Speaker 1: of the mandate and part of the reaction function for

733
00:42:15,920 --> 00:42:21,320
Speaker 1: their purchase program, then at some point wider deficits could

734
00:42:21,320 --> 00:42:24,400
Speaker 1: in principle generate market functioning issues, at which point the

735
00:42:24,400 --> 00:42:27,200
Speaker 1: FED has to step in. So like in the absence

736
00:42:27,239 --> 00:42:30,480
Speaker 1: of a change to the regulatory framework that generates these risks,

737
00:42:31,320 --> 00:42:34,040
Speaker 1: are we setting ourselves up for fiscal dominance de facto

738
00:42:34,719 --> 00:42:36,840
Speaker 1: just because of this relationship. And it's not on a

739
00:42:36,920 --> 00:42:39,160
Speaker 1: short term basis, not on a day by day basis.

740
00:42:39,200 --> 00:42:41,799
Speaker 1: But if we look out into the future and we

741
00:42:41,840 --> 00:42:45,680
Speaker 1: say that the ability of dealers to intermediate the sale

742
00:42:45,680 --> 00:42:48,640
Speaker 1: of treasuries and the purchase of treasuries is fixed in size,

743
00:42:48,640 --> 00:42:52,600
Speaker 1: are relatively fixed, but the stock of treasuries is going

744
00:42:52,680 --> 00:42:56,960
Speaker 1: up substantially, then at some point the FED has to

745
00:42:57,000 --> 00:43:01,239
Speaker 1: provide an outlet for that, and so that that at

746
00:43:01,280 --> 00:43:03,720
Speaker 1: some point will rise to some version of fiscal dominance,

747
00:43:03,760 --> 00:43:07,040
Speaker 1: even though it's not UM, not explicitly that. And so

748
00:43:07,160 --> 00:43:09,880
Speaker 1: if you're thinking about volatility like that, that is suppressive

749
00:43:09,880 --> 00:43:13,120
Speaker 1: of volatility. Right If there's a if there's a backstop

750
00:43:13,320 --> 00:43:16,600
Speaker 1: on what yields can do UM, and there's ultimately a

751
00:43:16,680 --> 00:43:20,720
Speaker 1: FED backstop in the market, then the potential for large

752
00:43:20,840 --> 00:43:25,279
Speaker 1: changes is very is very much mitigated. You know, I

753
00:43:25,320 --> 00:43:29,840
Speaker 1: wanna go back to something you're saying about UM looking

754
00:43:29,840 --> 00:43:32,840
Speaker 1: at the polls and the five thirty eight models in

755
00:43:32,880 --> 00:43:35,160
Speaker 1: the betting markets, and of course I read a lot

756
00:43:35,160 --> 00:43:39,120
Speaker 1: of cell side research where the strategists, uh, you know,

757
00:43:39,160 --> 00:43:41,480
Speaker 1: talk about d C and those charts are often in there.

758
00:43:41,719 --> 00:43:44,720
Speaker 1: How much is that really being inputed in real time

759
00:43:44,880 --> 00:43:48,000
Speaker 1: into models these days from clients that you deal with,

760
00:43:48,040 --> 00:43:51,800
Speaker 1: where they have sort of ongoing updates of these models

761
00:43:51,840 --> 00:43:54,840
Speaker 1: that then automatic, you know, take in all this stuff,

762
00:43:54,840 --> 00:43:57,479
Speaker 1: the betting markets and so forth, UH and then spit

763
00:43:57,480 --> 00:43:59,320
Speaker 1: out some results in terms of how they want to

764
00:43:59,360 --> 00:44:01,840
Speaker 1: trade that. I don't get the sense that it's directly

765
00:44:01,880 --> 00:44:05,280
Speaker 1: incorporated that often. I would say the more likely candidate

766
00:44:05,320 --> 00:44:08,560
Speaker 1: for that is UH is prediction markets. And maybe that's

767
00:44:08,560 --> 00:44:12,439
Speaker 1: just our biases as an investment types, where we say, look,

768
00:44:12,440 --> 00:44:16,480
Speaker 1: if there's money behind this, if there's a transactional, transactionally

769
00:44:16,560 --> 00:44:20,680
Speaker 1: based measure, I have a preference for it. Typically those

770
00:44:20,719 --> 00:44:24,080
Speaker 1: two things have gone together to some extent. I think

771
00:44:24,080 --> 00:44:28,439
Speaker 1: there's less of that now. And predicted has what chance

772
00:44:28,520 --> 00:44:31,759
Speaker 1: of Biden victory? And these quantitative election models, And I'm

773
00:44:31,800 --> 00:44:33,960
Speaker 1: saying that because I want to include like the economists

774
00:44:34,000 --> 00:44:37,480
Speaker 1: and Sam Waiting stuff and and five thirty eight stuff,

775
00:44:37,480 --> 00:44:41,000
Speaker 1: all of them kind of converge around something. And that's frankly,

776
00:44:41,000 --> 00:44:43,200
Speaker 1: because there's only so many ways to do this and

777
00:44:43,239 --> 00:44:45,680
Speaker 1: we all have the same input data, Like that's a

778
00:44:45,800 --> 00:44:50,160
Speaker 1: pretty significant discrepancy and I think that raises this this

779
00:44:50,239 --> 00:44:53,200
Speaker 1: issue that was alluded to earlier of polling errors, because

780
00:44:53,239 --> 00:44:57,279
Speaker 1: ultimately these models don't assume polls are right, but they

781
00:44:57,360 --> 00:45:00,120
Speaker 1: assume that they are as wrong as they've been the

782
00:45:00,160 --> 00:45:04,399
Speaker 1: past on average um. And so I think the memory

783
00:45:04,440 --> 00:45:09,080
Speaker 1: of again is relatively fresh, and which is a little

784
00:45:09,080 --> 00:45:13,360
Speaker 1: ironic in the sense that was basically a one sigma

785
00:45:13,360 --> 00:45:17,160
Speaker 1: polling air. It really wasn't that outsize relative to history.

786
00:45:17,200 --> 00:45:20,160
Speaker 1: And and if you get a one signa polling air

787
00:45:20,200 --> 00:45:22,000
Speaker 1: and just the right way in the context of the

788
00:45:22,040 --> 00:45:24,799
Speaker 1: electoral college, you can get a very unexpected outcome. But

789
00:45:25,120 --> 00:45:27,319
Speaker 1: I don't think it's fair to say the polls were

790
00:45:27,360 --> 00:45:32,960
Speaker 1: quote unquote wrong in so you know that that degree

791
00:45:32,960 --> 00:45:36,960
Speaker 1: of wrongness is incorporated into number. What you're saying, you're

792
00:45:37,000 --> 00:45:39,840
Speaker 1: you're seeing is markets in general, and that's reflected in

793
00:45:39,880 --> 00:45:43,560
Speaker 1: option premiums, and then these prediction markets, which admittedly have

794
00:45:43,680 --> 00:45:47,879
Speaker 1: very small transaction volumes, but they feel more financing um

795
00:45:47,960 --> 00:45:53,279
Speaker 1: than that then say pure model estimate, so you know

796
00:45:53,320 --> 00:45:56,879
Speaker 1: that those are more traded together. I think that over

797
00:45:57,080 --> 00:46:00,360
Speaker 1: over time. But you know, I don't think these models

798
00:46:00,360 --> 00:46:03,640
Speaker 1: are really incorporated rigorously into any investment process. I think

799
00:46:03,719 --> 00:46:06,719
Speaker 1: they're there's just not enough time to do that. You

800
00:46:06,760 --> 00:46:10,160
Speaker 1: don't have good data over long periods, and so what

801
00:46:10,239 --> 00:46:13,280
Speaker 1: you end up doing is kind of handicapping, and you

802
00:46:13,280 --> 00:46:15,400
Speaker 1: you make one of these grids, which is like the

803
00:46:15,480 --> 00:46:18,000
Speaker 1: least quantitative exercise in the world, where you say, like

804
00:46:18,640 --> 00:46:22,440
Speaker 1: house Senate control and the y axis and presidential control

805
00:46:22,440 --> 00:46:23,960
Speaker 1: into the X axis, and like, what is it due

806
00:46:23,960 --> 00:46:25,839
Speaker 1: to yields and what's the probability of each and and

807
00:46:25,840 --> 00:46:28,759
Speaker 1: that's how I come up with some target. I mean,

808
00:46:28,760 --> 00:46:31,640
Speaker 1: that's kind of all you can really do UM. And

809
00:46:31,680 --> 00:46:34,480
Speaker 1: it's not like we can choose not to participate in

810
00:46:34,480 --> 00:46:37,000
Speaker 1: the selection from a market's perspective. It's that you have

811
00:46:37,080 --> 00:46:40,160
Speaker 1: to have a view because it matters UM. But it's

812
00:46:40,200 --> 00:46:42,320
Speaker 1: it's hard to do it in a very rigorous way.

813
00:46:42,920 --> 00:46:45,440
Speaker 1: You know. The one thing I like to highlight also

814
00:46:45,920 --> 00:46:48,080
Speaker 1: and others have as well, is that this uncertainty cuts

815
00:46:48,080 --> 00:46:51,200
Speaker 1: both ways. So I think intuitively, when we talk about

816
00:46:51,200 --> 00:46:54,360
Speaker 1: pulling errors, we're talking about Trump winning even when his

817
00:46:54,480 --> 00:46:57,319
Speaker 1: probabilities are relatively low. But you know, a lot of

818
00:46:57,320 --> 00:47:01,239
Speaker 1: these models have a ten plus percent Biden's sweep and

819
00:47:01,719 --> 00:47:05,680
Speaker 1: landslide as more likely than a Trump win. So like

820
00:47:05,719 --> 00:47:10,640
Speaker 1: that generally speaking, error is symmetric, or at least reasonably symmetric.

821
00:47:10,800 --> 00:47:13,480
Speaker 1: So I think there's less attention to the market on

822
00:47:13,520 --> 00:47:17,839
Speaker 1: that potential outcome because a Biden victory by ten plus

823
00:47:17,880 --> 00:47:21,520
Speaker 1: percentage points is a mandate that has implications for policy

824
00:47:21,960 --> 00:47:25,040
Speaker 1: that a two percentage point win would not. So it's

825
00:47:25,040 --> 00:47:29,600
Speaker 1: definitely worth thinking about those scenarios. Do you think that

826
00:47:29,920 --> 00:47:33,360
Speaker 1: the fact that, um, you know, when you talk to clients,

827
00:47:33,520 --> 00:47:37,640
Speaker 1: do you feel like that is um underappreciated, that fact

828
00:47:37,680 --> 00:47:40,399
Speaker 1: that everyone has sort of the twenty six mental model

829
00:47:40,440 --> 00:47:43,480
Speaker 1: in their head where you take Biden's lead and then

830
00:47:43,480 --> 00:47:46,080
Speaker 1: you chop a few points off of it because reasons,

831
00:47:46,360 --> 00:47:48,920
Speaker 1: and then you get maybe this close raise, and by

832
00:47:48,960 --> 00:47:53,399
Speaker 1: and large people aren't thinking about that alternative form of error. Yeah,

833
00:47:54,440 --> 00:47:58,480
Speaker 1: never comes up as an example. So like the I

834
00:47:58,960 --> 00:48:02,960
Speaker 1: think the potential were a very significant Biden win, that

835
00:48:02,960 --> 00:48:05,360
Speaker 1: that brings with it this kind of mandate, and that

836
00:48:05,480 --> 00:48:07,520
Speaker 1: brings into the fold all kinds of other policies that

837
00:48:07,560 --> 00:48:12,200
Speaker 1: were really not in the base case of of the campaign. Um,

838
00:48:12,239 --> 00:48:15,040
Speaker 1: you know, that starts to look a little different, And

839
00:48:15,680 --> 00:48:19,439
Speaker 1: I just don't hear about that very often. That's interesting, Yeah,

840
00:48:19,480 --> 00:48:21,279
Speaker 1: And it's more it's much more along the lines of

841
00:48:21,320 --> 00:48:23,919
Speaker 1: what you're describing, which is like Biden is probably gonna

842
00:48:23,920 --> 00:48:26,640
Speaker 1: win per the polls, But what if we're wrong for

843
00:48:26,640 --> 00:48:29,359
Speaker 1: reasons I'm specified, and so I need to handicap this.

844
00:48:30,000 --> 00:48:35,160
Speaker 1: So mycent turns into from a betting markets perspective and

845
00:48:35,160 --> 00:48:38,400
Speaker 1: and maybe from an investment side perspective, I buy some

846
00:48:38,400 --> 00:48:41,480
Speaker 1: protection on top of that because maybe I'm wrong twice

847
00:48:41,680 --> 00:48:44,480
Speaker 1: and so and so that's why the options get rich, right,

848
00:48:44,840 --> 00:48:47,480
Speaker 1: and that that's why they increasing costs, because that insurance

849
00:48:47,520 --> 00:48:52,680
Speaker 1: is protection against being wrong in that one. Okay, so

850
00:48:52,800 --> 00:48:55,160
Speaker 1: we're going to leave it there for now, but Josh

851
00:48:55,200 --> 00:48:57,839
Speaker 1: will have to have you on after the elections for

852
00:48:57,920 --> 00:49:01,799
Speaker 1: your fourth All Thoughts appearance will make that happen to

853
00:49:01,880 --> 00:49:04,920
Speaker 1: discuss what what may or may not have actually changed

854
00:49:04,960 --> 00:49:08,640
Speaker 1: in the volatility regime. Yah, sounds good to me, looking

855
00:49:08,640 --> 00:49:31,160
Speaker 1: forward to it. Thanks John, Thanks very much, so, Joe.

856
00:49:31,239 --> 00:49:34,120
Speaker 1: It's it's always great to talk to Josh. I think

857
00:49:34,160 --> 00:49:39,520
Speaker 1: he's really good at elaborating on these quite complex topics

858
00:49:39,800 --> 00:49:42,640
Speaker 1: and really you can kind of throw anything at him.

859
00:49:42,680 --> 00:49:45,400
Speaker 1: But the points he was saying about who's actually selling

860
00:49:45,560 --> 00:49:49,200
Speaker 1: volatility at the moment and how it's being priced, and

861
00:49:49,320 --> 00:49:52,200
Speaker 1: why you might want to buy volatility protection just two

862
00:49:52,239 --> 00:49:54,960
Speaker 1: weeks out ahead of the election, or why you might

863
00:49:55,080 --> 00:49:58,879
Speaker 1: avoid selling it. I thought that was really interesting. We're

864
00:49:59,040 --> 00:50:02,600
Speaker 1: very lucky. I feel we've had a richest, a richness

865
00:50:02,760 --> 00:50:06,960
Speaker 1: of people who are just extremely clear about explaining this stuff.

866
00:50:07,120 --> 00:50:10,040
Speaker 1: Recently talked to Chris ben Ifford, who we've had on

867
00:50:10,080 --> 00:50:12,960
Speaker 1: a few times, and Josh just like so clear the

868
00:50:13,000 --> 00:50:16,040
Speaker 1: way he sort of describes the contours of this market.

869
00:50:16,280 --> 00:50:20,319
Speaker 1: I really appreciate that conversation. Yeah. Absolutely, And also the

870
00:50:20,360 --> 00:50:24,680
Speaker 1: point about how no matter what happens in the elections

871
00:50:24,800 --> 00:50:28,640
Speaker 1: and sort of no matter whether it's a huge surprise

872
00:50:28,719 --> 00:50:31,719
Speaker 1: relative to the current polls or not, there is going

873
00:50:31,800 --> 00:50:36,600
Speaker 1: to be a need for investors to reposition. I thought

874
00:50:36,640 --> 00:50:40,080
Speaker 1: that was a really important thing to mention as well. Yeah,

875
00:50:40,200 --> 00:50:43,040
Speaker 1: like the idea that an event doesn't even have to

876
00:50:43,080 --> 00:50:45,880
Speaker 1: be a big event, It just has to pass and

877
00:50:45,920 --> 00:50:49,280
Speaker 1: then suddenly a new regime, a new a new regime

878
00:50:49,320 --> 00:50:52,799
Speaker 1: can emerge, even if nothing really happened that fundamentally changed

879
00:50:52,840 --> 00:50:56,000
Speaker 1: the outlook, just because in the lead up to that

880
00:50:56,440 --> 00:51:00,040
Speaker 1: expected event there was so much sort of um, I

881
00:51:00,040 --> 00:51:02,839
Speaker 1: don't know the word I'm looking for, but hesitant, hesitancy

882
00:51:02,920 --> 00:51:07,799
Speaker 1: perhaps to make any big moves. Yeah, you know, so

883
00:51:07,840 --> 00:51:10,799
Speaker 1: if that was interesting, is like there's like this sort

884
00:51:10,800 --> 00:51:17,520
Speaker 1: of like highly quantitative flair or sort of characterization of

885
00:51:17,640 --> 00:51:20,320
Speaker 1: all of this stuff. But when you talk to Josh,

886
00:51:20,440 --> 00:51:23,120
Speaker 1: like so much of what he describes, uh, in the

887
00:51:23,160 --> 00:51:26,400
Speaker 1: market is sort of just like heuristics and sort of

888
00:51:26,440 --> 00:51:30,440
Speaker 1: people making normal judgments that don't seem that Matthew, it's like,

889
00:51:30,680 --> 00:51:32,520
Speaker 1: do you really want to be the one that's sold

890
00:51:32,600 --> 00:51:37,400
Speaker 1: puts two weeks before the election when everyone remember, do

891
00:51:37,440 --> 00:51:42,480
Speaker 1: you really Okay, you take this expectation, But was like this,

892
00:51:42,600 --> 00:51:45,640
Speaker 1: so maybe it'll be a little closer, Like a lot

893
00:51:45,680 --> 00:51:49,120
Speaker 1: of things that don't seem like that quantitative or rigorous

894
00:51:49,120 --> 00:51:52,480
Speaker 1: at all, and more just like gut feels about how

895
00:51:52,520 --> 00:51:55,480
Speaker 1: you're supposed to play this. So it's interesting that you know,

896
00:51:55,560 --> 00:51:59,520
Speaker 1: here it's like options, derivatives, hedging, volatility curves. You think

897
00:51:59,520 --> 00:52:01,920
Speaker 1: it was this very sort of like mathematical approach, but

898
00:52:01,960 --> 00:52:04,000
Speaker 1: a lot of it is sort of just you know,

899
00:52:04,120 --> 00:52:07,480
Speaker 1: just people going out their gut. Yeah. Well, also the

900
00:52:07,560 --> 00:52:12,200
Speaker 1: example of the systematic vole sellers who are supposed to

901
00:52:12,239 --> 00:52:14,800
Speaker 1: be doing that on a quantitative basis that doesn't change.

902
00:52:14,800 --> 00:52:17,800
Speaker 1: But then back in March, they sort of collectively thought, well,

903
00:52:18,160 --> 00:52:21,000
Speaker 1: wait a second, it's crazy out there, maybe we should

904
00:52:21,040 --> 00:52:26,320
Speaker 1: stop doing this. Whoops, even though it would have been profitable. Yeah, exactly.

905
00:52:27,080 --> 00:52:30,720
Speaker 1: Shall we leave it there? Yeah, let's leave it there. Okay.

906
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Speaker 1: This has been another episode of the All Thoughts Podcast.

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00:52:33,760 --> 00:52:36,319
Speaker 1: I'm Tracy Alloway. You can follow me on Twitter at

908
00:52:36,360 --> 00:52:40,000
Speaker 1: Tracy Alloway, and I'm Joe Wisenthal. You can follow me

909
00:52:40,400 --> 00:52:44,080
Speaker 1: at The Stalwart. Follow our producer Laura Carlson. She's at

910
00:52:44,239 --> 00:52:48,040
Speaker 1: Laura M. Carlson. Follow the Bloomberg head of podcast, Francesca

911
00:52:48,120 --> 00:52:51,759
Speaker 1: Levy at Francesca Today, and check out all of our

912
00:52:51,800 --> 00:52:55,960
Speaker 1: podcasts at Bloomberg under the handle add Podcasts. Thanks for

913
00:52:56,000 --> 00:53:14,120
Speaker 1: listening to