Michael Green, CFA, Portfolio Manager, Chief Strategist, Simplify Asset Management

[00:00:01] Hello, this is Dean Curnutt and welcome to the Alpha Exchange, where we explore topics in financial markets associated with managing risk, generating return, and the deployment of capital in the alternative investment industry.

[00:00:19] A major theme of Alpha Exchange podcast over the years has been the impact that financial products that live and breathe within the markets have on asset clearing prices.

[00:00:28] Events like the crash of 87, the GFC, the 2018 XIV event, or the unwind of short variance exposure in March of 2020 come to mind as examples.

[00:00:40] More recently, the substantial growth of leveraged ETF products has gotten a lot of attention as a potentially amplifying factor with respect to underlying asset volatility.

[00:00:50] With this in mind, it was a pleasure to welcome Mike Green, a partner and chief strategist at Simplify Asset Management, back to the Alpha Exchange.

[00:00:58] Our conversation drills down on leveraged products written on MSTR, the Bitcoin buying company.

[00:01:05] Mike first describes how a leveraged product's rebalancing requirement resembles a short straddle, buying when the underlying rises and selling when it falls.

[00:01:15] He next makes the case that the two times leveraged long products, MSTU and MSTX, are unique in that they are large in size and written on an underlying asset that is extremely volatile.

[00:01:26] This creates the potential for vol amplifying feedback loops that result from the extremely large daily rehedging.

[00:01:34] Mike believes the leverage complex has contributed to the large premium of MSTR to the value of its Bitcoin holdings.

[00:01:41] We talk as well about the cost being borne by the ETFs who have been forced to utilize the options market as the swap providers have reportedly limited the amount of leverage they are willing to provide.

[00:01:52] I hope you enjoy this episode of the Alpha Exchange, my conversation with Mike Green.

[00:01:59] My guest today on the Alpha Exchange is Mike Green.

[00:02:02] He is a partner and the chief strategist at Simplify Asset Management, a firm that's doing some very interesting stuff in the derivatives landscape with respect to ETFs.

[00:02:14] Mike, it's great to have you back on the Alpha Exchange.

[00:02:16] Dean, it's great to be here.

[00:02:17] I'm looking forward to the conversation.

[00:02:19] It's very timely.

[00:02:20] There is a lot of discussion in the marketplace around leveraged ETFs and the way in which they may create some feedback loops.

[00:02:30] And then specifically, everybody's favorite stock to look at these days, MSTR and the leveraged products built on top of that.

[00:02:37] So that's going to be our focus.

[00:02:39] I figured as we get the conversation going, it just would be good to start from a really high level.

[00:02:46] You and I have talked a lot about endogeneity in markets, right?

[00:02:51] That the risks in the market sometimes come from the market, from the products that get innovated and built at different points in time.

[00:03:00] And so I figured maybe we'd start all the way back to really, in some ways, the first derivatives blow up we saw, which was the crash of 87.

[00:03:09] And you've studied it a lot.

[00:03:10] I've studied it a lot.

[00:03:12] Why don't we start there just to kind of get warmed up?

[00:03:15] Because there is some similarities with how these things behave with regard to portfolio insurance.

[00:03:21] So give us kind of the high level of when you think about the impact of products on prices involved.

[00:03:30] How do you incorporate things like the experience of the 87 crash?

[00:03:35] So I did a very deep study on Paul Tudor Jones' work around portfolio insurance in 1987.

[00:03:41] And part of what's so interesting about that is that there are two kind of stories, right?

[00:03:45] One is the PBS special Trader, which if you ever get to watch, is a fantastic snapshot in time.

[00:03:51] But it basically goes through this idea that he is modeling on the basis of the similarity between the 1929 stock market and the 1987 S&P 500 and how this is going to predict a crash.

[00:04:06] That is kind of the headline story behind some of it.

[00:04:10] But the much bigger story, and this is actually contained in his writings to his investors if you go back and review his letters to his limited partners in the 1987 time period.

[00:04:19] What he was really talking about was the reliance that the market suddenly had developed around these products and how these products were consuming an extraordinary amount of the liquidity of the underlying at any point in time.

[00:04:32] And so effectively, he was saying portfolio insurance is not dissimilar to the subsidized flood insurance along the Mississippi or any other river along the coast of Florida that encourage people to make investments that they otherwise would not make.

[00:04:49] Right.

[00:04:50] So you get into this process because you are convinced that there is a way to protect yourself or get out that allows you to take additional risk.

[00:04:59] And that process can actually create exactly what you're describing, the endogenous feedback loop that then amps up the risk and the exposure within the market.

[00:05:08] What Paul identified was very similar to some of the stuff we'll talk about going forward, which was those products themselves had in turn become so large that if you actually started a process of reversal, you tried to actually exit or execute the insurance policy, that it itself would create a feedback loop that would then force the market lower and lower and lower.

[00:05:31] Specifically, specifically in portfolio insurance, the underlying strategy was effectively we're going to do the equivalent of delta hedge your portfolio by selling futures against it.

[00:05:43] As the market falls further, you have to sell more and more futures in order to reflect that the insurance is becoming a bigger and bigger portion of your portfolio.

[00:05:53] And there comes a point at which you try to execute the next sale and it's so large it overwhelms the market.

[00:06:00] And one of the key untold stories of the crash of 1987 is one that came out when I was speaking to Mark Rubenstein in early 2009.

[00:06:11] I was reviewing some of the trades that I was looking at that point.

[00:06:14] I happened to have developed a relationship with Mark Rubenstein, who was one of the partners at Leland O'Brien Rubenstein, the largest of the portfolio insurance firms.

[00:06:22] Mark was a finance professor whose ideas around delta hedging actually underpinned what's called the Cox Rubenstein model of options, the binomial pricing trees.

[00:06:34] And what Mark told me was that when it got to that point, the next sale was going to be so large, his trader actually came to him and said, Mark, if we execute this trade, we will send the market to zero.

[00:06:47] And Mark took the fiduciary responsibility and said, no, right, we're not going to do the trade.

[00:06:53] We will take the loss rather than send the market to zero.

[00:06:57] I think that's a really critical insight on two fronts, right?

[00:07:00] One is we were still existing in a world there where there was a human check.

[00:07:05] Do we do this trade?

[00:07:06] We have to execute this trade.

[00:07:08] Now it's largely embedded in algorithms.

[00:07:10] And so one of the things that you always have to think about is what would have happened if that human intervention hadn't existed?

[00:07:17] So that's one of the things that hits me every time I think about these components.

[00:07:21] I also knew Professor Rubenstein.

[00:07:24] He actually was on the board of a company I had founded in 2000.

[00:07:27] And we didn't get super far, but I got to know him well.

[00:07:31] And I just always found it quite fascinating that the Leland O'Brien Rubenstein part of this and just the take up of corporate America on this product was so substantial.

[00:07:44] That, you know, in some ways, if you just looked at the sponsorship of the product and the delta hedging requirements, again, you were going to have to get subcatalyst.

[00:07:55] I think the VIX got to 150 on the crash of 87, but it was 40 plus the week before.

[00:08:01] This thing didn't truly come out of nowhere.

[00:08:03] Obviously, it accelerated.

[00:08:04] But it's just a fascinating and in a lot of ways, the first example, at least in the stock market, of the market just overwhelming itself.

[00:08:14] And of course, there are many other examples.

[00:08:17] After that, you and I have shared an interest in a study and kind of played some part of analyzing the XIV meltdown in 2018.

[00:08:26] And then around 2017, you could have done some pretty similar analysis and realized that, boy, these guys are going to exhaust the liquidity available in VIX futures pretty quickly with a shock that in some ways was difficult to imagine because 2017 was so low vol.

[00:08:46] But it really wasn't all that big a shock.

[00:08:48] No, and even more recently, we actually just saw the unwind of the dispersion trade around August 5th, in which a lot of people have misassociated August 5th with the Japanese yen.

[00:09:00] I would argue that was just the dispersion trade where people are selling volatility on the index and buying volatility on single stocks.

[00:09:07] The easy articulation of it is the market cannot go up unless NVIDIA goes up.

[00:09:11] Therefore, I'm better off buying increased exposure to call options on those individual names and selling that exposure to the S&P.

[00:09:21] When the actual unwind occurred, the implied volatility to unwind that, I have to buy back my exposure to the S&P while selling it on single stocks.

[00:09:30] And we saw those relationships flip.

[00:09:32] And I think you and I talked about it at the time.

[00:09:35] You saw the number, quote unquote, implied correlation briefly went to 240%, right?

[00:09:40] Now, anyone listening to this type of broadcast would know that correlations actually can't go beyond 100%.

[00:09:48] But that implied pricing is telling you how out of whack things got.

[00:09:53] Yeah.

[00:09:53] What a dislocation that was.

[00:09:55] Let's talk about that briefly.

[00:09:56] It kind of came and went.

[00:09:58] I was just looking at one month implied vol in the S&P.

[00:10:02] Last three years, it's in the kind of first percentile.

[00:10:06] Now, look, it's early December.

[00:10:08] You've got Christmas.

[00:10:09] You've got New Year's.

[00:10:11] So it's a holiday period.

[00:10:13] It definitely gets quiet towards the end of the year.

[00:10:15] So not a huge surprise, but quite a difference from that August 5th disruption.

[00:10:21] What's the big picture?

[00:10:23] What should we take away from that asymmetry in terms of the VIX clearing at a price and then suddenly it gapping out to such an extent?

[00:10:32] Well, I think that there's a couple of things that I would take away from it.

[00:10:36] One is March 2020 is recent enough in history that I would argue that things like the dispersion trade and the short volatility complex, as large as they have gotten, are very different than the types of risks that were being taken going into either 2018 or certainly March 2020, which saw a number of firms just taken out of that kind of uncapped variance exposure.

[00:11:02] The second thing that is important to remember about volatility is that volatility actually is a disappearing event.

[00:11:09] So a VIX contract is a contract for 30 days of implied volatility on the S&P 500.

[00:11:16] As you introduce things like one-day options, etc., you're seeing more and more concentration of actual hedging risks tied to the individual event.

[00:11:26] So if I know Jerome Powell is speaking on Tuesday, I will hedge Jerome Powell on Tuesday through a one-day VIX option that can be constructed through the existence of the S&P single-day option components.

[00:11:40] That means there's much less pressure on that VIX complex.

[00:11:44] There's much less need for it, which was why it was kind of concentrated in this dispersion trade, which had taken on interesting characteristics, single stock versus index.

[00:11:54] And once it was unwound in its relatively smaller size, it was gone.

[00:11:59] I mean, the risk is gone.

[00:12:00] And so there were losses that were taken.

[00:12:02] There were desks that were damaged.

[00:12:04] But it really wasn't a systemic event in the same way that, say, even a 2018-type event would have been, certainly not in 1987.

[00:12:12] So we're going to talk about leveraged ETFs and specifically some of the single stock products that are new and potentially have the spillover effect.

[00:12:24] At least that could happen.

[00:12:26] But let's just step back again.

[00:12:29] I'd love to get your sense from an asset class standpoint where you see products or trading strategies that can be amplifying, that are price-pro-cyclical.

[00:12:43] It could be around the world.

[00:12:45] It could be across the asset classes.

[00:12:47] And it doesn't have to be right now.

[00:12:49] But just what are some other examples that you've keyed in on that you found both interesting but also critical to pay attention to?

[00:12:57] So I am, as you noted at the start, involved with a firm in the ETF space that offers derivative-enhanced strategies.

[00:13:05] Most of our tools are designed to complement portfolios as compared to magnify single exposures.

[00:13:11] But we certainly have investments that we've created along these lines in large liquid markets like Treasuries or TrueYours,

[00:13:19] where we're effectively trying to offer a similar type of exposure by raising the realized volatility of those products to things that look more like equities.

[00:13:30] So I don't necessarily think that the entire class of levered ETFs is necessarily wrong.

[00:13:38] When you start thinking about products like a single-stock ETF that is offering leverage,

[00:13:45] there's a couple of things that I think are important to consider, one of which is just the scale versus the scale of the underlying.

[00:13:51] And so if I think about a 2x levered NVIDIA ETF, while I may bemoan the idea that individuals are paying premium fees in order to access leverage

[00:14:02] that would otherwise be unavailable to them as an individual because their credit is not great

[00:14:08] or because they can't get options contracts approved within their portfolios, I think that's increasingly rare,

[00:14:13] or they can't access margin in their accounts at reasonable borrowing costs,

[00:14:18] I'm not going to wholesale criticize that type of dynamic.

[00:14:21] An NVIDIA ETF that's running $4 or $5 billion relative to the market cap of NVIDIA at $3 plus trillion

[00:14:28] is not that big of a deal. But when you start talking about some of the smaller, more volatile stuff,

[00:14:34] and in particular, we've hopped on to talk about things like microstrategy,

[00:14:38] you're talking about ETFs now that are, give or take $5 billion in assets

[00:14:43] and represent close to 50% of the trading volume that we're actually seeing in the underlying.

[00:14:49] Those are exactly the types of characteristics that we saw with the S&P futures in 1987,

[00:14:54] tied to portfolio insurance, where Paul Tudor Jones estimated that between 50% and 60% of the volume

[00:15:01] in the S&P futures was potentially being consumed by these products. I had the same analysis where

[00:15:08] you were looking at roughly 60% of the daily volume in the UX, the VIX futures, was tied to the

[00:15:15] VIX ETF complex. When you get to those sorts of scales with these levered derivative products,

[00:15:23] it changes the character of both the product and the underlying in a very dangerous way.

[00:15:30] Yeah. And it's an interesting one to sort of go back and think about that XIV event,

[00:15:35] because I think ultimately it really just was the size. Now, look, there were a couple of things

[00:15:40] happening. I want to say the event was Feb 5th. So in and around Feb 3rd, that was the Friday,

[00:15:47] rates were going up. You had kind of an initial move higher involved. But if you just sort of scaled

[00:15:54] that product set maybe down to a third of its size, I don't know, you just got to wonder out loud if

[00:15:59] these things would have self-destructed nearly to that extent. They might've actually been able

[00:16:04] to hang on. It really just becomes a keyhole effect from that perspective. Let's just talk about the way

[00:16:10] in which a leveraged ETF resembles an option, just in terms of the way it rebalances. We know this

[00:16:19] kind of quirky thing where both the leveraged and the inverse go the same way. It's just hard to get

[00:16:26] your arms around, but once you throw it in the spreadsheet, you'll see it. And then let's just

[00:16:31] run with the leverage side. If the underlying goes up, the leverage buys. If the underlying goes down,

[00:16:37] the leverage sells, well, that reminds me of a short vol position. How do you think about these

[00:16:42] things with regard to their option-like characteristics? How would you frame that out?

[00:16:46] Well, I think you actually just described it almost perfectly, right? This is effectively

[00:16:51] delta hedging to maintain yourself in a near at-the-money position, right? Where you're going

[00:16:55] to have a symmetrical response in both directions. If you don't do that constant re-hedging and

[00:17:02] repositioning, then you'll actually find that the product loses leverage as it gets larger,

[00:17:07] or loses in the opposite direction, loses leverage as it falls. Those are undesirable

[00:17:13] characteristics if you're trying to create a product that is on a daily basis delivering 2X

[00:17:18] anything, or 3X or 4X, et cetera. Again, I think one of the key things, like I've had a number of

[00:17:25] conversations with people, there are 3X versions of the S&P. And while I may not think that they are

[00:17:32] always the greatest products for people to be chasing and using, the simple reality is, again,

[00:17:37] you are a small fraction of the total transaction activity that's occurring in the underlying S&P

[00:17:43] index. And you're also talking about a 3X levered version of something that is, you ever take 12 to

[00:17:50] 16 vol in normal conditions. That you can actually manage pretty well, right? Large liquidity, tons

[00:17:56] that you can do. You can delta hedge with impunity. You're not really going to affect the underlying.

[00:18:01] But once again, once you get to that size that you're delta hedging is actually a critical input

[00:18:07] to the price behavior of the underlying, then you have the potential for feedback loops.

[00:18:13] Let's just run with that. And maybe let's just zero in on MicroStrategy, MSTR, and then the products

[00:18:20] that are built around it. So the two inverses are kind of irrelevant now. They trade a ton of volume,

[00:18:25] but it's obviously very low stock prices. MSTX and then MSTU, they sum up to 4.5 billion.

[00:18:34] And you've got this just really interesting story here where you've got an underlying underlying asset,

[00:18:40] Bitcoin, which has got a tremendous story to it, especially post the Trump win. The success

[00:18:47] is self-evident. The distribution of returns is really right-tailed. Very interesting. I was looking

[00:18:56] at the number of 5% up moves in Bitcoin since 2017. I think there's 216 of those and the 5% down moves are

[00:19:07] something like 193. You just don't get that for an equity asset, right? That's a really interesting

[00:19:12] and forceful characteristic of up shocks. And then you got MSTR and then the salesperson

[00:19:20] called Michael Saylor, who's just a tremendous salesperson. And the results there are really

[00:19:26] self-evident. And then you throw these two products on top of it. So that's the setup.

[00:19:31] You've done a lot of work on this. You mentioned the interaction with volume. If you can put some

[00:19:37] numbers to it in terms of what had you start to look at this? And then when did you really start

[00:19:42] to dive into the way in which the products were interacting with the underlying?

[00:19:47] Well, I think that there's a couple of interesting components that you hit on. First of all,

[00:19:51] micro strategy is a derivative of Bitcoin, where ultimately the vast majority of the value that's

[00:19:56] contained within micro strategy represents their treasury holdings of Bitcoin. And like a closed

[00:20:03] end fund, they can trade at a premium or a discount to those holdings. Now, a lot of market participants

[00:20:10] will say, well, Apple trades at a huge premium to the value of their assets. Therefore, the same thing

[00:20:15] should be true for micro strategy or could be true for micro strategy. Unfortunately, that's really

[00:20:21] not true, right? Because what you're describing with Apple is the excess returns that are generated

[00:20:27] by the operations associated with those assets. So Apple earns extraordinary and stable, extraordinary

[00:20:34] profits associated with the investments that it's made in the past. And those investments themselves,

[00:20:40] right, the headquarters or a factory somewhere actually don't really have any value outside of

[00:20:46] their existence within Apple. Very immaterial value, at least relative to what they contribute

[00:20:51] to Apple's operations. Micro strategy is the exact opposite, where Bitcoin is going to deliver its

[00:20:58] return profile regardless of what Michael Saylor does. He can actually influence it. I think that's

[00:21:03] one of the interesting features that's going on through his buying activity, but he's not doing anything

[00:21:09] any different except for the scale of his operations from a retail individual going out and buying Bitcoin.

[00:21:15] The levered component, and so what really captured my attention to this, is if

[00:21:20] micro strategy is trading at roughly two and a half times to even three times a premium to its underlying

[00:21:27] operating asset or this financial asset, I'm sorry, Bitcoin, then a levered variant is actually going

[00:21:35] to trade at even higher multiples. And so if you stop and think about what a 2x leverage means,

[00:21:42] that means that all of a sudden you're going to have something that's now trading at

[00:21:44] 5x the value of its underlying. So I'll be totally honest with you, that's what first caught my

[00:21:50] attention. I was surprised to discover how rapidly these had grown, how much impact that they had on

[00:21:58] the premium that micro strategy itself was trading at. So micro strategy was actually trading fairly tight

[00:22:04] to its underlying Bitcoin holdings until the introduction of these levered products.

[00:22:09] These levered products, the capital flowing into them because it is 2x levered has twice as much

[00:22:17] impact in terms of the underlying. And because the underlying itself is relatively illiquid given the

[00:22:25] relatively small size of micro strategy and its trading activity, it caused this huge premium to emerge.

[00:22:31] So my analysis was that the levered ETFs contributed to the extreme overvaluation of micro strategy relative

[00:22:39] to its holdings. And then the levered vehicles actually just double up that exposure itself,

[00:22:44] right? So you're buying something when you buy these at a huge premium to its underlying.

[00:22:49] That was the initial impetus for me trying to understand it. And then as you dig in,

[00:22:54] you discover the volume characteristics. You discover that the underlying holdings,

[00:23:00] instead of accessing leverage through a total return swap, where you're effectively just borrowing

[00:23:05] money from an investment bank in order to obtain that leverage, they were forced to begin using option contracts.

[00:23:15] And the purchases of the options at the scale that they were purchasing them was in turn forcing implied volatility

[00:23:22] dramatically higher. That premium implied volatility can be reverse engineered effectively into a cost of financing.

[00:23:29] And once you realize that the cost of financing is somewhere in the neighborhood of 5% to 10% per month,

[00:23:36] a levered product becomes extraordinarily dubious in its construction.

[00:23:41] Yeah, there's a bunch of things there. And maybe I'll start with the options portfolio. You and I have talked about this

[00:23:47] and got me super interested in just, again, taking it at face value. So who knows?

[00:23:53] Perhaps these are reported with a wrong multiplier. Maybe some of these are spreads. Maybe there's some

[00:24:00] OTC puts that they've sold against it. There could be any number of things. But on the MHD page on Bloomberg,

[00:24:08] these are official filings taken at face value. These are extremely large trades in a very high

[00:24:16] price stock with an incredibly high implied volatility. And the Greeks are just kind of in your face.

[00:24:24] I'm looking at three or four different line items, just one line of the portfolio. And I'm looking at $400,000

[00:24:32] of short data vega on an asset that has experienced basically 100 balls up, and then it's probably given

[00:24:40] back 40 of them. So lots of vega and an insanely high volleyball asset, which I think as you've alluded

[00:24:48] to, they may be a big part of, right? Well, they have to be. I mean, that's part of what we know.

[00:24:54] We can look at the outstanding option contracts and the size of these exposures, and they are by far

[00:24:58] the largest players. Exactly. Yeah. It's super interesting to look at. And so two questions.

[00:25:05] So you made this point. I just love for you to explore this more,

[00:25:08] that the levered ETFs may be a big part of juicing MSTR. And I get it. I get the statement,

[00:25:16] but I'd love just for you to flesh it out a little bit further as to how we should think about

[00:25:22] potentially that feedback loop. Yeah. So this overlaps with other areas of research I do,

[00:25:28] primarily the impact of flows into markets. And my work is built on the work of others who

[00:25:35] candidly have done far more in this space with far more diligence than I have, in particular guys like

[00:25:40] JP Bouchaud or some academics like Valentin Haddad or Xavier Gbeil and Ralph Coagian at Harvard and

[00:25:46] Chicago, respectively. What we're finding is that the historical theory or frameworks that we would

[00:25:53] have operated under an efficient market hypothesis, where price is largely a derivative of information,

[00:26:00] is just an increasingly flawed model, that there's a component of what's called market impact,

[00:26:06] where a transaction or flow causes a change in the price of the underlying. The efficient market

[00:26:12] hypothesis estimate of the impact of a dollar into a security is somewhere in the neighborhood of one

[00:26:18] penny because every buyer has a seller. And therefore, it should theoretically not have that much of

[00:26:23] an impact. What we're finding is that those numbers are off by several orders of magnitude.

[00:26:28] So the aggregate market impact is somewhere in the neighborhood of $8 worth of market cap that's

[00:26:35] created for a dollar into the market. On a single stock phenomenon, interestingly enough,

[00:26:40] it's tied to the volume and volatility. And in the case of a company like MicroStrategy,

[00:26:45] my estimate is that a dollar in creates something like $14 of market cap. And therefore,

[00:26:51] a 2x leveraged dollar in creates $28 of market cap. And those numbers actually seem to fit the price

[00:26:57] behavior we've seen in MicroStrategy quite well. So in terms of the premium of MSTR to its Bitcoin

[00:27:04] holdings, that premium seems to have a delta with it that's related to the stock itself. And certainly,

[00:27:11] that appears to be part of Michael Saylor's pretty compelling, at least as you listen to him,

[00:27:18] is the ideas that he's putting out there that you want to get long this flywheel. I'm not saying I'm a

[00:27:23] buyer. I'm just saying he speaks in a compelling fashion. Have you looked at sort of the behavior

[00:27:27] of that spread, the premium and the delta of the premium relative to the change in the price of MSTR?

[00:27:36] You're effectively saying the higher the price of MSTR, the more that delta or that premium increases

[00:27:43] as it goes higher.

[00:27:45] I think observationally, that's what's happened, at least recently. And I think that's part of his

[00:27:50] sales pitch is if you can get in, I'm going to continue to work on this Bitcoin yield, and we're

[00:27:57] going to increasingly be valued at a price that's a multiple of what we own in Bitcoin. We're going to

[00:28:05] own more Bitcoin, but MSTR as a function of that is going to actually outperform what it buys.

[00:28:11] Yeah. So this concept of a Bitcoin yield that Saylor talks about is unfortunately not one that I find

[00:28:20] any empirical support for. What he's effectively saying is my share price is higher than the value

[00:28:27] of the underlying financial assets. Therefore, when I issue shares, I can buy more of the underlying

[00:28:34] asset. And that creates an accretion process that's no different than an M&A activity in which you buy a

[00:28:41] company trading at a lower multiple and therefore see earnings accretion. The problem with that analysis

[00:28:46] is just the agency component. What you're actually doing is you are outsourcing to Michael Saylor the

[00:28:52] ability to sell those shares when if you own MicroStrategy, you could simply sell your MicroStrategy

[00:28:57] and buy two and a half to three times as many Bitcoin as you currently hold. So your yield internally

[00:29:03] would be 250% while he's celebrating a 40% yield. Unfortunately, as you said, he is an extraordinary

[00:29:11] salesperson and he's created a narrative that people want to buy into. And again, ironically,

[00:29:18] when they decide to buy into it, well, if you're accessing it through MicroStrategy, why not 2x that

[00:29:23] exposure through MicroStrategy levered ETFs? Right. And so the second part of that, I guess what I would say is

[00:29:30] it's to me seems that there's a vulnerability to this premium on the way down. And I'm recalling

[00:29:38] the Grayscale Trust, right? The Grayscale Trust traded at a big premium to its holdings. And then

[00:29:43] on the way down, it traded at a huge discount to its holdings. So there seemed to be very much a delta

[00:29:50] of the premium that was positive in terms of the directionality of the underlying.

[00:29:55] With regard to MSTR, this is just asking you to speculate a little bit here, but I'd love to

[00:30:02] listen to you on this. Do you think that MSTR is buying outside of its signaling effect,

[00:30:07] which I think we're both agreeing, extraordinary mediator, just speaking with so much confidence

[00:30:15] about this, it's just hard not to think he's not convincing a lot of people. And when you got the

[00:30:21] underlying asset doing what it's doing, it really becomes a wind at your sales with regard to being

[00:30:27] a compelling speaker. Do you believe outside of the signaling effect that MSTR's commitment to

[00:30:34] buying more and more Bitcoin hauls, is that a driver of the price as well? Or is Bitcoin market

[00:30:40] cap big enough to absorb that buying pressure? I don't think there's any question that his activity

[00:30:47] is actually contributing to the upward momentum on Bitcoin. One of the most interesting things that

[00:30:53] has happened over the last year has been the growth of things like the Bitcoin ETFs,

[00:30:59] in which we have readily available information on the flows. And so this has actually been a really

[00:31:05] interesting opportunity, if you're paying close attention to this, to begin to derive components

[00:31:10] of what drives Bitcoin higher. Now, this will come through as a, I think the technical term is no

[00:31:15] shit Sherlock, observation that what causes anything to go up is more buying than sell.

[00:31:21] That is at odds with the information theories of markets. And you referred to the signaling component

[00:31:29] to it that historically would have actually represented the majority of how people would have thought about

[00:31:33] this. But with the availability of information on these ETFs, we can actually track the dollars and

[00:31:40] how that's impacting Bitcoin itself, the net dollars that are coming in. And so over the course of the

[00:31:47] past year, we've actually seen an extraordinary increase in the explanatory power that can be derived

[00:31:53] from tracking flows on ETFs into Bitcoin. Now, MicroStrategy is no different. If they're going to spend

[00:32:00] $40 billion buying Bitcoin, that will push Bitcoin prices higher. The question again, just boils down

[00:32:08] to, are you better off participating in Bitcoin or are you better off participating in the dilutive

[00:32:14] component of owning something that is trading at two and a half to three times the value of those

[00:32:19] underlying Bitcoin? Right. And just back to the levered products built on top of this,

[00:32:24] one of the things you see in every one of these prospectuses is a raft of disclaimers.

[00:32:31] I'm remembering that one of the earlier ones, the TBICs, I think this goes back to 2016 or so,

[00:32:37] but boy, they had some incredible statements in there. I think one of them was the long-term

[00:32:42] expected value of this security is zero. And of course it had no problem accumulating

[00:32:48] a couple of billion dollars of assets anyway, but they typically are including some table that maps

[00:32:55] the performance of the underlying, twice that performance in terms of a daily move,

[00:33:00] and then a vol profile. And of course, what we see is at very low vols, these things,

[00:33:06] yeah, they do an okay job tracking the 2X, but when you get to the higher vols,

[00:33:12] things really don't look good. How should people think about not just the liquidity profile of

[00:33:18] an asset that needs to do a lot, but just the variance drag from the very high vols?

[00:33:25] So a lot of people are very familiar with this concept of volatility drag. And just the simple math

[00:33:32] is if I have an asset that is continuously rebalanced into a 2X levered version or a levered version of

[00:33:40] something. If on day one, I'm up 10% and day two, I'm down 10%, the arithmetic average of those two is

[00:33:47] zero. Theoretically, I'm supposed to be totally flat, but the reality is I've gone to 1.1 and then

[00:33:53] 0.9 times that I'm down 1%. That's the geometric volatility drag. That only plays through if the

[00:34:01] direction is neutral, right? So if I go sideways, I zero arithmetic return, then I will experience that

[00:34:08] volatility drag. But if I go two consecutive days of up 10% each, then I will actually benefit from the

[00:34:16] leverage that I've associated with this. And so this is actually a critical component, right?

[00:34:20] Leverage itself is not necessarily the problem. The unique thing about the VIX ETFs was that the

[00:34:29] expected value of the VIX as a truly mean reverting series is always zero. The expected value of the

[00:34:36] VIX futures, which is actually a series that typically is in contango, meaning the forward futures

[00:34:44] are higher than the spot futures, is a negative expected return. So adding leverage to a negative

[00:34:52] expected return will cause prices to fall on a continuous basis. Something like TVIX, which is

[00:34:58] that 2x levered variant of the VIX itself, has an expected value of zero in relatively short order.

[00:35:06] And we've seen this through the continuous stock splits of these products, etc. It also explains why a

[00:35:12] product that was inverse to that had a very high positive expected return on a daily basis,

[00:35:21] basis, but also had a unique profile in which a unexpected, quote unquote, unexpected event

[00:35:29] could cause the underlying to change to a price level that would cause the liquidation of the product.

[00:35:35] That was really the key insight around the collapse of XIV, was that the level of VIX had fallen to the

[00:35:45] point that a doubling was not implausible at all. And anytime you have a doubling, a product that is

[00:35:52] 1x levered is going to go to zero. Anytime you have a 50% increase, a 2x levered is going to go to zero.

[00:36:00] And in the specific case of XIV and related products like SVXY, there was a force majeure clause built in

[00:36:07] because these were not actually exchange traded funds, they were exchange traded notes in which the

[00:36:11] underwriter wanted to protect themselves against the risk of losing and being responsible for more

[00:36:18] than 100% of the value of the funds that were out there. They had force majeure clauses at 85%.

[00:36:25] And so the analysis I did around XIV was that we had gotten to the point where the sensitivity of

[00:36:31] the VIX to the S&P was such that a mere 4% one day decline could drive this product to zero.

[00:36:40] A 4% down day is not particularly uncommon. In the case of the micro strategy products,

[00:36:45] you're now talking about a stock that is embedding an implied volatility somewhere in the 120, 130% range.

[00:36:55] That's telling you that an expected day is going to be around 10%. A 40% decline shouldn't be that

[00:37:04] shocking, right? That's roughly a three or four standard deviation event, which happens with

[00:37:08] disturbing regularity in markets. Now, do I actually think that that is going to be the cause of this

[00:37:13] as compared to the volatility drag that we talked about earlier? I lean towards the volatility drag

[00:37:18] components of it, but I don't dismiss the possibility of a single day event.

[00:37:22] It's interesting as you talk about SVXY versus XIV and those stipulations, crazy stuff happens near

[00:37:31] the bankruptcy cliff. And there are decisions that need to be made in a very chaotic fashion.

[00:37:38] So if we're sort of thinking about Bitcoin gets whacked, MSTR gets whacked, and then these levered

[00:37:43] products suffer as well. So a couple of things. One is if MSTU truly owns options, well, obviously they

[00:37:52] have options plus, but the option is the automatic stopout, right? In other words, in some ways,

[00:37:58] if they only own options, they could just walk away. They don't have to do anything. Obviously,

[00:38:02] it's not going to be a great result. But I think what you're referring to on February 5th was these

[00:38:08] guys had to make a decision. We've got to stop this now because we could lose more money than we have.

[00:38:14] It's a levered product. And so I was just thinking about this, that, okay, so MSTU has bought a

[00:38:21] truckload of options from the street. It's Jane and Susquehanna and so forth. So these guys are short

[00:38:26] the gamma. So they also have to, in some ways, delta hedge. And they know they can't, right? So the

[00:38:34] solution set to that is to raise the implied volatility to the point, again, that cost of

[00:38:38] financing equivalent to the point that the actual gamma of these options is quite low, which is why

[00:38:44] the products have begun to significantly underperform their theoretical. That's a great point. Well,

[00:38:49] you've made a couple of points here. And so I wanted to see if I could get you to put your thinking cap

[00:38:53] on. So what do we know about the dangers of these products? Well, first and foremost, sometimes the

[00:38:59] products just get too big and they impose themselves on an underlying asset that just doesn't have the

[00:39:05] liquidity capacity to provide it. That's one. Two, you've talked about vol. So when these products

[00:39:13] are on an asset that's especially volatile, that can be a big issue. And then lastly, as you talked

[00:39:19] about the VIX and the Contango and a negative expected return asset, that's especially troublesome as

[00:39:26] well. So if we're to flip these things around and just try to think about under what conditions

[00:39:32] these types of products can be successful, can you kind of talk out loud about if there is a product

[00:39:39] innovation that can be done here and it can be useful for the end user? What does that look like?

[00:39:45] So I think that there's a couple of examples of that. And again, I just want to be very clear that

[00:39:49] I don't think anything is immune from the challenges that we were discussing, right? So I'm not in any way

[00:39:53] implicitly endorsing any one product. And again, I also want to be very explicit, but I don't necessarily

[00:39:58] think that leverage is a bad thing. If I'm levering my exposure to a high expected return product as

[00:40:05] is being articulated by Saylor in relation to Bitcoin, that isn't necessarily a bad decision.

[00:40:12] If I borrow it at four or even 10% to buy something that has an expected return of 100% a year,

[00:40:20] that could actually work out really, really well.

[00:40:23] The challenge in this situation, again, comes back to you have a product, MicroStrategy,

[00:40:30] that derives its value from Bitcoin. Because it is trading at a 250 cent premium to Bitcoin,

[00:40:38] over any reasonable period, you actually would have to expect that the expected return to MicroStrategy,

[00:40:45] and this is part of what lots of commentators have highlighted on MicroStrategy,

[00:40:50] the expected value of that is actually negative unless Bitcoin itself is able to deliver such an

[00:40:56] extraordinarily positive return. Ironically, Saylor, by selling his own shares to generate cash to buy

[00:41:04] Bitcoin, is contributing to the normalization of that spread. Now, his selling activity can be

[00:41:10] overwhelmed by other participants, for example, levered ETFs. But it is still a negative expected

[00:41:18] return asset to which you have now attached leverage. And the costs of that leverage,

[00:41:24] as we've talked about in the option contract, is so extraordinarily high that under almost every

[00:41:30] circumstance, you have to expect these products to return significantly negative. As people begin to

[00:41:37] experience that, that in turn then reverses this whole process. And instead of simply decaying,

[00:41:45] you could actually see outflows, you could actually see outflows in these products.

[00:41:51] But then suddenly means you are actively selling the options on MicroStrategy, potentially compressing,

[00:41:58] creating supply of these options that compresses that implied volatility, crystallizes that vega

[00:42:04] exposure, that loss that you are highlighting, not just in a theta form, but in an actual compression of

[00:42:09] vega. And increases the flow of funds that are basically trying to sell MicroStrategy. So forces

[00:42:16] the prices lower and lower and lower, even as the assets and these levered products begin to

[00:42:22] deteriorate in terms of their importance. That in turn leads to a compression of that premium.

[00:42:28] And a lot of people ultimately saying, wow, that was a really stupid idea. We shouldn't have done it.

[00:42:32] It's just a question of how violently that process occurs in terms of whether it becomes a really

[00:42:37] notable event like an XIV or Volmageddon, or whether it simply becomes a, wow, that was a really bad idea

[00:42:43] like a ARC in 2021.

[00:42:47] Well, as you've talked about just the ecosystem of products here, it's hard to get away from the launch

[00:42:54] of not just IBIT and its brethren. Let's just use that as the representative, the spy, so to speak,

[00:43:02] of the Bitcoin world. And then the options recently. And boy, what a start for the options. I'm looking

[00:43:09] at the January montage. There's 82,000 of the Jan 54 call open. There's 85,000 of the put. I mean,

[00:43:19] there's just a real nice thick series of contracts open. Liquidity, a dime wide,

[00:43:27] rate posted liquidity. That's a dime wide is a vol wide. This is incredibly promising

[00:43:32] with respect to trading. And so what I wanted to ask you was, as you sort of think about

[00:43:38] simplifier, just putting on your financial engineering hat, when you have a vol surface,

[00:43:44] that's this fertile, especially at an early stage, it's got some great characteristics to it.

[00:43:49] It tilts up to the call. It's high in terms of implied vol. Where do you see products being built,

[00:43:56] risk managed products that embed options on IBIT?

[00:44:00] Well, I think you actually are hitting on a couple of really key points, right? Which is a number of

[00:44:06] events have occurred over the last month and a half, including the listing of the 2x levered

[00:44:11] micro strategies and the options on those themselves, the introduction of options on products

[00:44:17] like IBIT that expose people or give people the ability to trade these products with more leverage.

[00:44:22] In other words, there's been an incredible injection of leverage into the system in very short order.

[00:44:27] That creates both opportunities and risks, as I think most people would immediately divine.

[00:44:32] There are opportunities suddenly around products like IBIT and the options that are created there for

[00:44:39] all harvesting strategies, so income enhancement type strategies. There certainly are opportunities

[00:44:44] that are created to leverage those positions. And candidly, as you think about those types of

[00:44:50] exposures, again, it becomes this question of what sort of premium do I want to pay relative to the

[00:44:55] underlying exposure? There's really no reason to try to gain that leverage through a micro strategy

[00:45:01] or even more extreme through a levered variant of micro strategy that's using very expensive options.

[00:45:07] When you can accomplish the same underlying phenomenon on the Bitcoin itself.

[00:45:13] So I think we will see products that multiply into this universe.

[00:45:18] You can disagree with the fundamentals behind Bitcoin as I do, but that has absolutely nothing to do with

[00:45:25] the underlying dynamics that we're referring to, which is these tradable products and there's a realized

[00:45:30] and implied component to the volatility. And I would be very surprised, given the sponsorship of BlackRock

[00:45:36] and others, if at least for the foreseeable future, that liquidity is not maintained and profitable

[00:45:42] products can be constructed around these types of dynamics.

[00:45:46] Yeah, it's super interesting. I'm not as close to this as I once was, but QIS is certainly all the rage

[00:45:52] on the street. You know, they're creating all kinds of risk premium products. There's just every bit of flavor

[00:46:00] on these things, as you can imagine. And I'm just as I sort of think about Bitcoin, I just immediately say,

[00:46:07] OK, well, there's probably some VRP product, vol risk premium product that could be cooked up here.

[00:46:13] Yep. And so actually Simplify offers products that allow you to do that. It's ironic. You mentioned QIS,

[00:46:19] right, quantitative investment strategies. One component of which tends to be short vol,

[00:46:25] volatility risk premium harvesting, generating the return associated with that spread between

[00:46:30] implied and realized. We actually do have an ETF with a ticker QIS that embeds these types of

[00:46:37] strategies to deliver a very stable return profile. But in order to do that, part of what you want to

[00:46:45] do is use a diverse basket or series of strategies that are uncorrelated with each other and in some

[00:46:54] ways cancel each other out so that you generate that stable return profile. The return profile associated

[00:46:59] with short volatility, as you and I have discussed that infinitum, is in itself extremely negatively

[00:47:06] skewed, right? It's very much a Taleb's Turkey type framework where you march upwards, march upwards,

[00:47:11] march upwards, and then all of a sudden the day before Thanksgiving, you discover that your life

[00:47:15] is far shorter than you thought it was going to be. By mixing together strategies, again,

[00:47:20] some of which are negatively correlated with each other, but all that have a positive expected return

[00:47:25] in terms of underlying frameworks, you can change that profile in a way that has been more rewarding

[00:47:31] to investors over time.

[00:47:33] So I think just with Leverage ETF products and specifically MSTR, I think the main message

[00:47:39] I'm hearing, and please feel free to correct me or to add, is there's nothing wrong with Leverage.

[00:47:46] There are some characteristics of daily resetting Leverage products that folks need to be careful on.

[00:47:54] And we also need to be very careful when the product itself imposes itself on the underlying in a way that

[00:48:02] sort of creates alternative risks, one of which is the swap counterparties saying no loss and the ETF

[00:48:09] provider having to go into the options market.

[00:48:12] Yeah. I mean, I think you said that part probably far better than I could have.

[00:48:15] I would add a couple of components to that. One, again, I have no issues with Leverage,

[00:48:21] but Leverage applied to products that are by definition overvalued, right?

[00:48:25] So MicroStrategy versus its underlying exposure suggests that your expected return,

[00:48:32] like the VIX is actually negative over time.

[00:48:35] Leverage in that framework becomes a negative.

[00:48:38] In this case, because you're already buying into a product that is priced at such a huge premium,

[00:48:43] that becomes very quantifiable and fairly obvious in that framework of trading at 5x versus its underlying.

[00:48:51] It's hard to argue that your expected return for Bitcoin over the next year is 500%.

[00:48:57] And even if you did think that, it would be hard to argue that the product that you want to gain access to

[00:49:03] is one that is already trading at 5x that price.

[00:49:06] The second component is this issue of scale, which you referred to both explicitly and implicitly.

[00:49:13] There are some interesting comments that have been made by those associated with these levered ETFs

[00:49:18] that the scale of leverage that was available to them from their prime brokers

[00:49:22] was in the neighborhood of 50 to $100 million.

[00:49:26] These products, as I said, have now grown to $4 billion.

[00:49:30] And as a result, the scale at which they are operating relative to the banks,

[00:49:35] who would actually be doing almost the exact same trading,

[00:49:38] the banks are saying, this is far too risky for us to do.

[00:49:42] And so when you encounter a situation in which the underlying prime brokers,

[00:49:46] who have far better trading systems than any of the rest of us,

[00:49:50] are saying, this is way too much risk for us to wear,

[00:49:53] you should be somewhat thoughtful about whether you want to wear that risk.

[00:49:57] Yeah, I mean, you step back and there's just so much mechanistic trading in markets.

[00:50:01] And I think the lesson that markets try to teach us, but folks just don't seem to want to listen,

[00:50:07] is there's just not an infinite supply or an infinite capacity to accommodate what folks want to do.

[00:50:14] It's not a video game. There actually are limits.

[00:50:18] Well, I just wanted to close out, give you two minutes to just share

[00:50:20] what's on your mind in terms of research for 2025.

[00:50:24] I know Passive is a big ongoing project for you.

[00:50:28] What else is top of your research agenda with regard to whether it's trying to think through things,

[00:50:37] challenging conventional thinking, product development?

[00:50:40] If you can, share some of what your research goals are for next year.

[00:50:45] Sure. So you highlighted the work I'm doing around Passive.

[00:50:49] Part of what's so interesting there is the extraordinary growth of academic literature

[00:50:55] and empirical evidence for the influence of passive strategies

[00:50:59] and what would be described in physics terms as the forcing that is created

[00:51:04] by the government favoring passive strategies

[00:51:08] in the form of both 401k, qualified default investment alternatives,

[00:51:14] and to a certain degree in terms of liability protection for institutions

[00:51:20] or others who choose to access market exposure through low-cost indexing.

[00:51:24] That's created a framework in which you can think about the cost of choosing active management

[00:51:30] or deciding to make active investment decisions

[00:51:33] as distinct from the active decision to decide to buy an index fund

[00:51:38] as there is a liability cost that is laid on top of that

[00:51:42] that would favor the growth of passive vehicles

[00:51:45] and increase the exposures that I'm concerned about,

[00:51:47] the increased inelasticity that is showing up in markets,

[00:51:51] the extreme changes in price, both on a single security basis and on an index level,

[00:51:56] I think we're increasingly aware of the potential impact

[00:52:01] of the growth of these passive strategies.

[00:52:03] I think there's a couple of other things that are going on

[00:52:06] that are worth paying attention to.

[00:52:08] One area I'm spending a lot of time and research on right now

[00:52:11] is actually around the rates market.

[00:52:13] There's a lot of focus, particularly in the United States,

[00:52:15] about the potential for inflation to return

[00:52:19] and resistance to believing that bonds represent value,

[00:52:25] in part because of that fear of inflation.

[00:52:27] Now, ironically, that inflation is not embedded in markets like inflation swaps,

[00:52:32] where you could very easily seek that protection,

[00:52:34] but the narrative exists around it nonetheless.

[00:52:38] What I would suggest is actually the most interesting thing that's happening

[00:52:41] right now in rates markets is the correlation between all Western bond markets,

[00:52:48] including Japan,

[00:52:50] and how everybody is basically behaving the same.

[00:52:54] The correlation between bond prices and bond yields

[00:52:57] on a global basis in the West has exploded,

[00:53:01] which makes me really question whether this is actually about the deficit

[00:53:05] and supply components in the United States,

[00:53:09] as is often articulated.

[00:53:11] What I think is much more interesting is that there is,

[00:53:15] in the aftermath of the U.S. decision to sanction Russia

[00:53:18] and basically take their U.S. Treasury bonds,

[00:53:22] there has been a resistance to accumulating U.S. Treasury bonds

[00:53:28] or Western bonds.

[00:53:29] The fear of those types of sanctions

[00:53:31] has grown amongst many of the countries that run large trade surpluses,

[00:53:36] China being the obvious one.

[00:53:38] And that means that their trade surpluses that they generate,

[00:53:42] in the case of China, somewhere around a trillion dollars,

[00:53:44] are no longer being recycled into Western bonds.

[00:53:47] What's interesting about that is nobody has asked,

[00:53:49] well, then where are they going?

[00:53:51] And a lot of my work is increasingly suggesting

[00:53:54] that those funds are actually being reinvested back

[00:53:57] into the private markets,

[00:53:59] contributing to the compression of credit spreads, etc.

[00:54:02] I don't know this at this point,

[00:54:04] but I'm a little shocked at how little research has actually been done

[00:54:07] around where are those trade surpluses from China

[00:54:10] and other countries, Saudi Arabia might be another example,

[00:54:14] where are they actually ending up?

[00:54:16] And I think the resolution of that

[00:54:18] is going to be an interesting question for 2025.

[00:54:21] Awesome.

[00:54:21] All of the money, as they say.

[00:54:24] It is a lot of money.

[00:54:25] Yeah.

[00:54:26] Well, Mike, I'm really glad we had a chance to do this.

[00:54:28] I always enjoyed the conversations.

[00:54:30] And this is very topical stuff.

[00:54:32] So your analysis is going to be welcomed

[00:54:34] for the listener base of the Alpha Exchange.

[00:54:37] Thanks so much, man.

[00:54:37] Thank you for having me.

[00:54:39] You've been listening to the Alpha Exchange.

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[00:54:48] As we aim to utilize these conversations

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[00:55:00] at alphaexchangepodcast.com.

[00:55:03] Thanks again, and catch you next time.

[00:55:05] Bye.

[00:55:05] Bye.