How do large delta hedging flows of market makers tie in with Central Bank quantitative easing? How do ETF rebalancing’s and structured note issuer movements shift markets? We sit down with options guru Hari Krishnan talk through his new book: Market Tremors – Quantifying Structural Risks in Modern Financial Markets.
Hari’s first book, The Second Leg Down, talked about what investors can do when they’re in trouble and how to structure actual options trades to keep bleed under control and maximize protection. This time, he’s zooming out and asking how to know when there might be trouble lurking. How we can quantify and identify events like Volmageddon (Feb 2018), the Swiss Franc depeg (Jan 2015), Game Stop run up (2021), and more. In a world where we often get bogged down considering how specific items like this gamma, or that Fed decision, or how large ETFs flows will impact markets, Hari masterfully weaves all those ‘agents’ together to consider how we apply a real world risk to these agents shifting the distributions we rely on to size investment positions. Enjoy the episode.
Find the full episode links for The Derivative below:
Check out the complete Transcript from this weeks podcast below:
Why Whales Tails Whip Up Market Tremors with Hari Krishnan
Jeff Malec 02:33
Hi, everyone, we’re recording on Tuesday, September 28, here with markets down about a 2% on the day. So what a better time to hear the soothing, calm voice of one of the best in the ball space. here with us today to dig into some of the research and reasoning behind his new book, market tremors, quantifying structural risks in modern financial markets. We have none other than Hari Krishna in the book includes very nice acknowledgement for yours truly. So thanks for putting me in print there. I really appreciate it.
Hari Krishnan 03:07
Well deserved. Very well deserved.
Jeff Malec 03:09
That’s my first known acknowledgement. Maybe there’s one I don’t know about out there. But it’s my first known one. So I appreciate it. And how are you? Where are you at home?
Hari Krishnan 03:20
I’m sitting at home. Yeah, at some random room. I’m in Duxbury, Massachusetts. So don’t track me down. But I’m here.
Jeff Malec 03:27
Don’t track you down. And we’ve had you on the pod before talking through your background and how you got into the world of options in the hedge funds. So mostly going to skip over that. But if you could just give us a quick lowdown on kind of what you do in the day out in the options world for clients.
Hari Krishnan 03:47
Well, I nowadays I focus on long volatility strategies. So I do tail risk hedging, adaptive hedging for people who are bearish and just basically stuff that profits from disorder, downside moves and risky assets and general uncertainty in the market. So what I do is kind of like an add on to what people already know.
Jeff Malec 04:10
And what does it mean by adaptive hedging of if they just tactical hedging?
Hari Krishnan 04:16
adaptive hedging to me is finding the best hedge given the market, the state of the market now, if the price of insurance is high, I don’t want to buy the most expensive stuff. I want to find other ways to hedge that don’t involve buying the most expensive stuff. So I’m trying to figure out ways to protect without overpaying for protection. Oh,
Jeff Malec 04:37
And does that bleed into everything you might go long gold or something or just across the ball surface.
Hari Krishnan 04:45
Currently for the separately managed accounts I run. It’s purely equity based, but I do have some advisory business too, which runs the gamut. So yeah, it could include gold, it could include credit anything really,
Jeff Malec 05:01
which has been a tough month for that we’re just looking through some data of right? All the proxies have sold off alongside everything this month. Bond sound gold down, S&P is down, nowhere to hide except natural gas.
Hari Krishnan 05:16
You know our speech Chaffetz volatility is the final frontier. It’s the last chance saloon. Yeah, the last chance to live. said it in the wrong accident. Yes, yes.
Jeff Malec 05:36
Okay, and so on to the book market tremors. I was joking with you on Twitter that you needed to incorporate the tremors movie into the cover, which had a little earthquake cision.
Hari Krishnan 05:49
I hear you on that one. There, all these copyright infringement things under the table. So you have to pick an image that’s compliance. So you get these things I look very at a time, most of them are pretty boring. And so the editor and I got together, one of them and she said, Well, why don’t you make the lettering a bit? jaggedy? She did. Okay, that’s kind of tremor, like so let’s go with that. Yeah.
Jeff Malec 06:19
The How does? How is that whole process before we dig into the meat? how you’ve written the book, your other book? second leg down? I can’t remember. Did you have one prior to that?
Hari Krishnan 06:30
No, no, I got I believe that two bouts of insanity in this career. And those two. second leg down was written in 2017. It came out. And this one came out recently.
Jeff Malec 06:44
So has that whole process work with the editor getting it done? So labor of love? I’m sure.
Hari Krishnan 06:51
Yes, I mean, for me, the big thing was to build a grat. So I try and be a brand, I try and do it as well as I can keep the quality high. But effectively, you can’t be known in this industry for 20 different things. Because you want to focus on the stuff where you can add the highest value and for me was macro slash volatility. And I knew the macro was a tough space, given all of the central bank interventions and interest rates, and currencies, and so on. So volatility outright, seemed like a good place to play. And yet, lots of people didn’t know about it, I would say even four or five years ago, people didn’t consider it an asset class per se. They just thought it was kind of something that occurred on the side of buying options. And I felt there was an important areas focused on and the two areas for me were, what do you do when you’re in trouble? And how do you identify dangerous situations? So the first book was dealing with bad situations? The second book is how do you smell of grass? Even if volatility is low? So that’s what the book is about.
Jeff Malec 08:06
Yeah, you stole my, you stole my thunder there, I was gonna say, without saying anything having to do with math or distributions of why you wrote it, and what the overall theme is. So that’s, that’s that. Sorry about that. No worries. And I’ll dive in my next thing. So I really liked one of my favorite parts is you really dig into the fact that market returns aren’t normally distributed, which has been covered far and wide by Nassim Taleb and elsewhere. And even though you point out, they appear to be a great deal that time appear to be normally distributed, but then you say they’re not just that they aren’t. But actually dig into really what’s going on is that the distribution shifts something or more properly, maybe someone is kind of shifting that distribution and creating the fatter tails or whatnot. So a lot of times, to me, things I read, it’s kind of just throws it out there, like the markets aren’t normally distributed. You need some other thing, but you, to me, it was different in that you’re looking at it more as a shifting distribution, instead of just black or white binary of it’s not normal. It’s this other thing.
Hari Krishnan 09:15
Yeah, there are lots of things that have happened post 2009, post GFC. We had the mean stock explosion with GameStop. So on, we had the volume again in 2018. We had a flash crash in 2010, all sorts of things we’ve had over the years. And many people would say they’re black swans, I’d say they aren’t. They aren’t black swans, because basically what’s happened is, there’s been some out of the market, the London whale, who is in the market, making money highly levered with very strict risk controls, never enters the market unless something big enough happens. In which case, that agents that player, that whale is forced into the market either to rebalance, or to liquidate. And when that happens, when that happens, the old distribution changes. The whole thesis of the book is that even if you think that the distribution of historical returns is okay, if a few players get big enough, and they have to react to a random shock of normal size of moderate size, they’ll be forced into the market, they’ll have to sell typically, and when they sell, the impact of that selling, will cause returns to be much bigger on the downside, especially than they otherwise would have been. So it’s basically taking a view on how the network behaves versus the distribution. And that sounds fancy, I don’t want it to be too fancy. Let me tell you what is fancy. It’s saying, oh, let’s build a model of the entire financial. Let’s look at every transaction that goes through. Let’s look at every buy in every cell. Every settle trade. And so when I build a model of the economy, that’s tough to do, that we talk about that book. On the other hand, the distribution, you know, the classical approach, which is everything is normal, or at least everything that happened in the past is a good proxy for what will happen in the future. That’s also inadequate. So we tried to fuse those two together in a way that people could actually calculate things, calculate real risk numbers, in the presence of whales.
Jeff Malec 11:35
Maybe we should rename the book, there’s London whales everywhere.
Hari Krishnan 11:40
If I had a better marketing sense, I worked out so
Jeff Malec 11:44
I’m brand new, can you say in there that random returns? And I’d like this part to have the it’s not just that the distribution shifts? It’s like the rules of the game change? The talk a little bit more about that of like, how, how do you view that as it doesn’t really matter if there’s right, because I could say, oh, there’s a spike, just now we have a little wider tail over there, you’re saying the rules of the game can totally change and not just ship the distribution, but kind of what the distribution
Hari Krishnan 12:12
is looking at? Yeah, I mean, the simplest cases, let’s say that there were a mega player, a whale, who had huge position and a stop loss 5% below the current price. If the market gets anywhere down, then other people are going to know, there are going to be other agents who I won’t name that, you know, in what’s called the high frequency space or the market making space, who are incentivized to push prices down through that stop loss level, causing the sale, which will precipitate a price move even much further down. So you know, the distribution adapts to, well, big agents that adapt to what’s going on in the markets. And if there’s small round of sharks, they can turn into big ones, purely based on leverage and positioning. It’s a bit of a roundabout reply. But basically, the distribution is affected by a feedback loop between biggest agents who either have to rebalance or have to liquidate, given a sufficiently large move and the original distribution
Jeff Malec 13:23
then I I was reading it and coming back to Ben hunt, which said a great post and he’s been on the podcast he says the markets a bonfire, not a clockwork machine, right? So if it was a clockwork machine, and we could model the whole thing, and we’d know Okay, when this takes this way, this is everything that happened, the gears move, but it’s a bonfire, it’s hard to model a bonfire, right? Um,
Hari Krishnan 13:46
yeah, I mean, the George Soros had this idea of reflexivity, which a lot of people know about. Sure. It’s familiar to many people on the show, we watched the show, but you know, a lot of us believed it. And we knew it. We knew that positioning was a huge factor in markets and cascading sales was a huge factor. But being able to model it and come up with some real numbers was the golden book.
Jeff Malec 14:11
Did stars write that before? Or after he busted the Bank of England? Right? Because that was the mother of all that was probably you should have put it in the book. That was the first kind of asymmetric, huge, huge whale, huge player having to do something.
Hari Krishnan 14:26
Yeah, it’s probably too challenging to do that. I didn’t. Great. Yeah, would have been a great case study. Hard to model.
Jeff Malec 14:39
Okay, so let’s get into how you started to think about this, how you merge those two worlds that normally distributed and the modeling a bonfire super hard to model?
Hari Krishnan 14:51
Yeah, that’s a great question. I mean, what’s been going on over the past decade has become big, Central. Banks, definitely passive investment vehicles like ETFs, definitely
Jeff Malec 15:07
Hari Krishnan 15:09
massively automated market makers who intercepts 90%, or more of all trades that go through the Marketplace hugely. So you’ve got dealers or options market bankers, you’ve got central banks, you’ve got ETFs, ETFs, you’ve got structured products and systematic strategies, those are the whales in the marketplace, they drive a huge percentage of all the volumes that go through. And you know, even if I stick a trade into the market, it gets snapped up very quickly, I almost can feel the machine on the other side of the trade picks it up more quickly than it ever did. Assuming that the market is stable, but just bails out or doesn’t offer any liquidity when things are getting out. So if I want to do a trade now, I can get it off super quickly. In most market conditions, but then the quotes disappear if things get out. And what that means to me even not knowing anything, even if I didn’t know anything about what’s going on, is that the market making community is no longer a community that’s dedicated to providing quotes with size behind them. But rather a community that is incentivized to do so if there is an edge in providing those quotes. So there’s a highly competitive marketplace, with quotes provided with narrow spreads with ease of execution until things get ugly, in which case, all of that disappears. So we have a more we, we basically get data fills most of the time and the median case, and no fills if things are really bad, depending on our position. But yes, did
Jeff Malec 16:58
you see I think it was floating around Twitter yesterday, that was like a market maker PSA video of like, we help pensioners and retirees and provide stability to the economy.
Hari Krishnan 17:10
Yeah, no, I hear that I hear them. And that and they’re not entirely wrong, I have a good buddy east. Back in the day, I used to type my trades into Bloomberg chat. So he would pick them up and he was sitting in London, and he would execute them. And he would work hard, he can be a tick, or half a tick on average for 90% of all trades, but the remaining 10% would go wildly against him. And he’d be scrambling for his life, and I wouldn’t be filled. And I’d be sitting there pulling my hair out for the ends of the and that’s kind of the way that you get treated nowadays, you get media and the media in case you get tons of liquidity. I mean, maybe not in huge size, but you get good fills on decent size. But in the cases where you really need liquidity and the markets against you. The incentive based structure doesn’t really go.
Jeff Malec 18:05
Right. How is it right? It was never a government utility? Like it’s always been an incentive based structure, right? How is it? How’s it different than 10, 20-30 years ago?
Hari Krishnan 18:16
Well, I’m not the expert on this. But in my opinion, nowadays, anyone can be a market maker if they trade sufficient volume. So market making is by definition a based on how much you do, instead of whether you are you have bought the seats on the exchange and you wear the jacket and this and that now anyone can do it, if they have sufficient technology, they do enough size. So it’s much more based on how much edge is perceived to be in supply liquidity, instead of being the sort of the central the sort of the centerpiece for transacting.
Jeff Malec 18:59
Right in the old days was like your job is basically to provide this market. And you can earn a little spread on doing that, versus the philosophy seems like it’s changed to my job is just to come in and make as much money as possible, providing a spread, right semantics, but very important in this case.
Hari Krishnan 19:17
Well, the other thing is that the spreads were much wider back in the day. Yeah, even going from 16th to nickels was a big change in terms of the amount of profit that designated market makers could extract from trading. And now it’s so narrow in so many markets that it’s more as that it’s almost as though they’re running more hedge fund type ideas than just providing liquidity and collecting spreads. So the tiger spread is better on average, on average, perhaps the worst at the extreme.
Jeff Malec 19:53
And you have the other problem that there it’s been a winner take all market right like so the biggest players Do what I think you said before 90% of all the market making, which if some crisis, some liquidity crunch there, they don’t get a influx of capital, their risk controls kick in, right? They’re just not going to play the game anymore.
Hari Krishnan 20:16
Yeah, you know that consolidation is really important, because you might know more about this than I do. But imagine that one of these guys will not, I will not name them. They’re not many that could be catastrophic to market function at this point. Yeah, well, it’s been
Jeff Malec 20:31
in the news, right of the everyone saying can get Griffin lad in front of Congress without the GameStop stuff? And he did they did stop providing liquidity or, you know, a market in that stock. He said they didn’t. So we’ll leave that for the legal scholars to sort out. But there’s definitely something there, right? If that’s a prime example of like, Okay, what what’s going on with the, and that’s the case study in the book of game suffering?
Hari Krishnan 20:56
It sure is, but I won’t go any further on that point.
Jeff Malec 20:59
You got to buy the book.
Hari Krishnan 21:02
Well, I was gonna stand on naming names, that’s the thing. Okay.
Jeff Malec 21:06
I’ll name no problem. And so I want to push back on this, or First I want to say, mean field theory. So is that that’s the basis for all this, of how you brought,
Hari Krishnan 21:18
it’s a jazzy phrase. I mean, basically, mean, field theory says this, imagine that you were in a room, and you wanted to this is a simple case, this is a book, you want to measure the temperature at some location in room temperature really is a function of how much the molecules in the room are buzzing. So the more kinetic energy they have, the higher the temperature will be. But it’s a pointless or hopeless exercise to try and take every single molecule in your room. And measure those collisions and those movements. That’s just a hopelessly high dimensional problem, it’s completely intractable. So the right thing to do is to just think of temperatures and macro level quantity. And if you have it easier on one side of the room, if it were winter, she doesn’t, but that heater would generate some excitation of molecules, and that he would sort of diffuse through the room. And there’s an equation for that. And so basically, you replace every single particle interaction, or pairs of particle interactions with just a distribution. The distribution says, on average at a given point in time, at a given point in space, this the temperature. And that’s the way classical financings, start with Markowitz and before you get distributions of price returns, so what you do is you take time, slice it up into pieces, you assume every piece was generated by the same machine, whether it’s God or just the market machine that generates all these returns, you count, you collect them, and then you build a histogram. And that is the distribution of returns you can expect in the future. Um, it’s a good model to an extent, but it’s been modified in various ways people have said, well, normal distributions are good, so they’re fatter tails, fine, you can parameterize in different ways, you could look at correlations in different ways. But that doesn’t really address the problem in modern markets, which is this. In modern markets, what we’re seeing is periods of very low realized volatility, persist for ages. And then suddenly, there are all these volatility spikes, spikes out of nowhere from a low level. So one case study that we did, it’s very simple is that there have been more 10 point or greater spikes in the VIX. over a five day period, when the VIX started out low, let’s say below 20, than ever before, there were no such events from 2000 to 2000. So that makes sense by 10 points or more in, say, 2008. But it did it from a handle of 30. Now from the handle of 15. So you get all of these spikes, these bouts of volatility from nowhere. And these are all positioning or leverage based risks that just don’t show up in the price action. And you now have a world where everyone wants to use malls, and I hate to point the finger at CTAs because I’m a CTA fan. But there is a some kind of change in the CTA industry, maybe 1015 plus years to get where people start saying, Well, if we have a position that’s becoming more volatile, but it’s inside, look at it, so that we have a constant volatility budget to say, we’ll just let it run, which was the way it used to be. It isn’t today. You then get scaling according to one divided by volatility or one divided by Barron’s whatever the case may be. So CTAs trend followers is scaling their position. inversely to volatility to realize volatility, and then you have all these other players were big in the marketplace, you have volatility control funds. So these funds, say, I’m going to buy the S&P and I will hold cash. And I will mix my S&P cash allocation, so that I can hit some volatility target, say 10%. So if S&P ball goes out, they have to sell their position simply to hit that target. And then you have other funds like risk parity funds, you have various strategies that target volatility, instead of trying to extract alpha from volatility. And given all of this emphasis on targeting risk, instead of managing risk, we have a situation where many players use leverage and have the same sorts of positions. And if everyone is the same risk model, the markets would be doomed one day out of the blue, an event would happen that would force everyone to get out at the same time, because their vol limits would be hit. And the market, whatever market this might be, let’s say the S&P 500 would go to zero. Add this notion that everyone should be doing the same thing on the risk side is really one of the core problems in this business where if big enough players are using the same model, or using a model, it’s very rigid. And everyone knows what that model is. That’s a recipe for challenges. But what is might be perceived as terrorist, but it’s just liquidation in response to a risk limit being yet. And yeah, that’s
Jeff Malec 26:45
- That’s a good mental model of like, if everyone has a 3% stop to exit their whole portfolio. Yeah, the market goes to zero the minute you hit 3%, right, then everyone wants
Hari Krishnan 26:55
selling. Yeah, everyone’s selling it. Good hearts law is something I don’t know very well, but it’s relevant here. Which is that when a metric becomes a target, yeah, there’s a problem.
Jeff Malec 27:07
It fails to be a metric anymore. What?
Hari Krishnan 27:10
Actually is it? Actually, per sages? crisis? Yeah. Right.
Jeff Malec 27:16
And to me, and we’ve talked about this on the pod with a few different guests like it’s, it’s a much different risk environment, right? It’s much stricter, like, in the old days, you could have these blow ups happen inside a bank and whomever didn’t know that this was going on. Nowadays, it’s one strike and you’re out and the risk departments calling you at 345, right? Like, they’re on your stuff, saying, Hey, you got to reduce exposure by the clothes. So in many ways, it’s kind of like, maybe it’s worked. Maybe it is working, like the market keeps going up. But in other ways, yeah, it’s much stricter, and when there’s going to be a severe downturn, all those risk controls are going to kick in. But to me is, it’s not the same model. Like they’re all using XYZ risk platform calm, right? But you’re saying that it mentally all the same model of we need to protect against, you know, extreme risk. And here’s how we’re going to do it. We’re going to put var on it, we’re going to put stops whatever the case might be.
Hari Krishnan 28:14
Yeah, exactly. I mean, I, I used to know a guy and he, this is probably 15 years ago, and he he knew how to keep prime brokers at bay when he got a margin call. So he would get a margin call every single day because he was very thinly funded. And he would say, go to his prime broker and say, Well, are you sure I have a margin call? Show me. And so the guy would send back risk numbers. And it might be some standard risk system that would spit out the numbers, you’d say, okay, but who calculated this? Now, the guy would say, Oh, he was my quants. Our Junior is the quants. And that he would figure out who was the senior guy and the senior guy would invariably be out of town, Paris or wherever. And so he could get five days of margin relief through this sort of process. prime brokerage is no longer that context, right? If you get a margin call, you have to tidy up the cash pretty quickly, nowadays, and it’s much more rigidly defined. And having a good handle on where those limits are going to be set. is very important, even if you’re not hitting those limits, even if you’re well below them. Because, you know, those are the pressure points and mark. And that kind of brings us back to another point in the book, which is a discussion about technical analysis, you know, things like the Iron Cross, the Hindenburg cross and so on. Things like if the 50 day moving average for the S&P drops below the 200 day moving average. Why should anyone care? Well, people should care because if other people are doing that, pressure points in the market where selling may occur so if you can trade around those sorts of positions you may have an edge and that’s a major theme which is understanding how other people are positioned and making sure you’re not having to liquidate at exactly the same time or even worse a bit earlier perhaps a bit later as well.
Jeff Malec 30:23
There was an old trend following program you could buy just off the shelf called aberration I think it anytime it had a signal and platinum or palladium maybe and we would trade this for clients way back when so anytime it had a signal in palladium it’d be up huge overnight because some desk had the system as well you could buy it off the shelf right so it knew in the morning there was going to be you know maybe it was only 500 lots or something from across the world who had purchased this system but in a thin market like palladium that was enough so you get these five 6% overnight spikes you know when it was supposed to be the order comes in on the next morning?
Hari Krishnan 31:04
Jeff Malec 31:06
Yeah. One of the case studies in the book is volume again as a call febby team Yeah, we’ve done a bunch of research on that you did a bunch of research in the book so let’s dig in if we can a little bit that’s kind of a perfect case study of was fairly easy to identify these players looking backwards even more so these agents whales as you can so yeah dig in what you found on vol again and why it’s important how it fits in.
Hari Krishnan 31:42
Okay, well I’m in the chapter in the in the bog is pretty terse, but let me say give me give you the highlights anyway. Um, around 2008 or 2009. A lot of people wanted volatility protection. And so they want us to be long the VIX, and couldn’t get along the VIX because it’s hard to replicate. It’s a complex formula, based on the price of a variant swap. drives the VIX, so, there were a VIX futures by that time by 2009. So there were various contracts. There were various contracts traded, and the VIX, which was the flagship, VIX exchange traded knows where ETN was born in 2009, in the wake of the GFC. And basically what it would do is it would buy the front month VIX futures at second month, and then reweighed the combination, so it always had 30 days to maturity in the blood. That was great, because it gave you at least indirect exposure to the VIX. Problem with the VIX is though is that on average, the futures curve is very steep. Meaning that if markets are calm, investors want to buy protection further outs. So the front month futures tend to trade at a huge discount to the subsequent months in the backlog and so on. So if you try and buy and roll that contract, you’re always getting dinged, because you’re buying high and selling low. So there’s a net carry, which is negative, which is about historically about four or 5% 5%. Let’s say 5% a month is a massive hurdle to overcome. And so the VX X was decaying like crazy as soon as market stabilizes. Now over time, people thought, Well, why don’t we turn that on its head, trade the inverse fix, which is basically shorting the front month or the front two months, and then buying them back and then basically profiting from the role where you benefit from the front month, decaying very rapidly to the spot fix. And you don’t lose as much by the back month, which is dedicated slowly to the front of the trees, whatever, that’s a technical thing. Yeah. And that became super popular and there were people who had quit their jobs at you know, well, yeah, target. I shot the targets I’m not gonna
Jeff Malec 34:17
that was, it was the famous guy who was like in the paper like this guy made 82% turn. I
Hari Krishnan 34:23
remember Jerry Hayworth talking about this. And so I looked it up. And it was true that many years ago. And at some point, we got to late 2017, which was a very quiet year, and the inverse VIX ETFs were growing and growing and growing. There was the SPX why the XIV and they grew so much that if the flow desks that supported them, remember these are notes, not funds, so they’re hedged instead of replicated. If they had been hedged properly, these inverse VIX ETFs would have counted would have accounts For 30% of the open interest across all VIX futures contracts, so they have become the behemoths in the room. Now the trouble with these ETS and ETFs that use leverage or inverse products is that they have to rebalance according to a schedule and they’re highly incentivized to rebalance at the club’s why, because they want to track anything. They didn’t want to be just trading in the market and then be subject to a big move near the close increases their tracking here, the goal of these products is low tracking error and low fees. And they used to use this where they probably still do, they used to use traded settlement as a secondary order book to transact so they could try and get close to nav. Everyone knew on the day that the VIX the vol mageddon occurred, which I think was February the fifth or sixth of 2018. That they would have to trade in Mega size and that the market, the futures market could not support those trades. And even if they had tried to again the S&P futures indirectly, that would have had mega impact to a massive impact. So one could almost predict how much they’d have to try to replicate. And using various arguments that are presented in the book that are pretty tactical, they’re somewhat speculative, but I think a pretty good one could estimate what the follow through would be. So when the VIX had closed on the previous Friday, at 15, spots six or something, and was already at around 2022, whatever. You could guess quite easily we could estimate the VIX futures had to pop to 30 as a function of the impact of forced rebalancing, the mega agent, or whale, which in this case was the ETF. And these sorts of cases are great, because I’ve never made myself many friends in the ETF space, but I’m not massively anti ETF for EGP person is more than I thought they were very good. They were really good laboratory lab for testing the theories about positioning risk, because these are agents, especially the levered products, that tell you exactly what they’re going to do in the prospectus, generally, so they have to do what they say they’re going to do. So everyone knows they’re coming. Yeah, and these are sort of the extreme cases of the positioning risk problems that we tried to deal with.
Jeff Malec 37:40
And I’ll throw out we had Mike green on the pod before who was on stage with Chris Cole, another vault Pro, at a conference at EQ derivatives or some conference ball conference, basically, calling this out and arguing with the, with the ETF creator, I can’t remember his name. But there was this public discussion of the how this was a possibility and how it would spike. So it wasn’t just like, if you were paying enough attention to the perspectives like people were actually out there talking about it. And then my greens told us on the pod he structured to train for Peter teal, they bought, I don’t know, fives or 10s of millions of deep out of the money puts in the, in that one product. And then once it appears to its low, it went out of business, and he made a lot of money. I didn’t ask if that was in the, in the infamous Now Peter teal $5 billion. Ira. We’ll have to we’ll have to ask.
Hari Krishnan 38:37
Well, migraine is a friend of mine, so I’m not going there. But yeah, I mean, that was a fairly predictable case. given what we know today. People didn’t know as much back then. I mean, people were less aware of 2017, let’s say about the potential risks of exchange traded products, and they didn’t even know about leveraged products. And one of the trading books that I ran from 2012 to 16, was a book that effectively shorted badly designed ETFs. So the simplest case is imagine that if you found the levered ETF, levered ETF has to rebalance every day to maintain constant leverage. So if the reference index before leverage is mean reversion, they’re buying and selling at the wrong time every single day. So that thing is going to underperform a constant borrow two times levered for investment in the index. So stuff like that was easy to do. And you know, the way that ETFs and ETNs work and I don’t criticize the business, but the business model is, let’s throw anything against the wall and see if it sticks. No, it’s not a let’s do what we believe in. It’s, let’s see what people will buy. Let’s paper it up carefully. Let’s design it. as best we can not being invested money managers ourselves and run with the stuff that wins. So they’re playing a big options game as well, but it doesn’t necessarily benefit the average guy or girl.
Jeff Malec 40:14
I think the right to Schwab’s and of the world have gotten a little more careful of allowing the customers to trade the levered products and basically pointing out like, hey, these are for trading. It’s not for investing, right? If I’m bullish natural gas, I shouldn’t buy the natural gas 3x bull ETF because it’s going to have a rebalancing issue. So I think the industry’s gotten better at that. But I’ll put, I’ll definitely agree that it’s like Oreos these days, right? If I’m in the grocery store, and they have like, pistachio Oreos, and orange Halloween Oreos, and Star Wars, it’s like any time any type of Oreo you can get. It’s just shelf space. And if something takes off, they’re going to write don’t mass produce those like crazy. So the Sami investment banking model, yeah, we’re gonna put it right. It’s almost like a venture capital deal, right? of like, Hey, we’re gonna launch all these companies. one’s gonna be a huge winner eventually. And so be it if we had 10 losers doesn’t really matter. And they don’t have to be losers, performance wise, but just losers. It didn’t get enough investor interest, right? Yeah. Next, he go into the kind of all bundle at the Gecs, Squeeze metrics, Gem Karsan, Lily, all the gamma people out there. Right.
Hari Krishnan 41:38
So let me practice and jam. Yeah.
Jeff Malec 41:41
Yeah. So that’s become the, like, hottest kind of topic for me in terms of like agents and big players and market makers, right. So yeah, inform your thinking or you were already working on this how to how did that work?
Hari Krishnan 41:55
Well, I worked for marquee making for a couple of years back around 2000. And I knew that I knew Blair Hall. Blair Hall is a an acquaintance friendly acquaintance of mine. So I knew that one of the great innovations in that space was just taking on positions and managing to macro edge them on the back side, you know, that was what that business was, instead of saying, I need to be flat at the end of the day. It was more I need to be hedged. So it was kind of a second generation approach to making markets. And so I was interested in that. And then this notion that everyone that institutions like to buy puts and sell, of course, was well known to me, I knew these color structures big, and they had been big for a long time. And it’s understandable why institutions want to do that they’re worried about losing their jobs by boats. And they need income in a zero interest rate world. So they sell calls to monetize the premium in that. So assuming that the market makers had the opposite position, they were then the dominant agents. Now, these are not dominant agents in the sense that they have billions of dollars of capital, they can be fairly thinly capitalized, that they intercept, the majority of trades that go through the market, increasingly so. So on the assumption that they had this position, where they were short puts, and long calls, I had the reverse position of the large institutions that were looking to color, their positions, their equity index positions, lots of interesting things could be thought, and I love the stuff that squeeze metrics guys do and Jasmine, Lily, Lily, and so on. But I use it more as an indicator of potential pressure points in the market, than as an indicator direction. Even if you look at the squeeze metrics research, it doesn’t really give you direction, it more says that. In areas where there’s high open interest in puts, if the market goes down there expects a lot of oscillation. It might go down a lot, go up a lot. It’s gonna wiggle around hugely in that so and so what the book tried to say was, um, a lot of things that were considered to be a fundamental origin, like in the initial phases that the COVID crisis in February and March 2020. You saw this move in, say the S&P a little overly focused on the S&P but but where you see this jaggedy down move in the index. A lot of people said, oh, there were varying opinions about how serious it would be, what the response would be, and so on. But you could explain it legitimately just based on Hajin from the options market. So whenever the options market makers are short puts in sides, and there’s a small round of shock to the downside, they have to sell buy, sell If there’s another round of shock to the upside they have to buy. So they’re aggressively selling and buying in response to random noise that’s going through the market. And I think that’s a pretty compelling case for positioning risk, overwhelming fundamental information in terms of market movements. And that’s a big theme nowadays, the whole mind green passive argument is an argument against fundamentals dominating pricing in this modern market, it’s more an argument that flows go into passive if there’s a relationship between performance and flows, then passive bias, there’s no latitude there. And so you get these self reinforcing feedback moves, get this distortion of the historical distribution that’s based on positioning or based on this market structure. It’s not based on a view. So little is based on a view now that you know, the very notion of fundamental value or equilibrium, which I find pretty bizarre notion to begin with, is out the window.
Jeff Malec 46:13
Right? And so not like those passive flows are coming in, and the portfolio manager of spy is like, looks a bit Toppy to me here, I’m gonna, I’m gonna put that billion on the side for a month.
Hari Krishnan 46:24
Exactly, exactly. For emails and put it in there.
Jeff Malec 46:27
Or even Cathy wood now or in Ark and all those right? It’s just here’s the stats we’re targeting. And it’s, it’s going into those stocks. And so back to the game is that as you’re writing the book, as it’s coming through, like this GameStop stuff is exploding.
Hari Krishnan 46:44
late in the game for me when no pun intended when the GameStop thing happened. Yeah, so I kind of just mentioned it, the others were saying you really need to analyze it, but I throw my hands up by that. But I was aware that downside risk could be exacerbated by market making options market making activity, I didn’t predict To be fair, the upside, melt ups, you know, the meltdowns that occurred in AMC, and GameStop, and so on. But they’re perfectly logical in the context of this model, where, you know, retail used to be pretty small. And perhaps it still is pretty small in terms of individual retail investments. But one of the big things about options is you can get a ton of implied leverage. If I buy an option at BARC Santee that’s 100% out of the money, and the market starts growing out there, suddenly, I can make 100 times 500 times what I paid. So my tiny investment by 50,000 a month, not tiny, but my 10 or 50,000, or $100,000 investment can become a $10 million notional position pretty quickly. At that point, it’s significant. And so that implied leverage the anyone can get by buying low Delta options or short times and maturity options is significant in terms of distorting the market structure that we use. And that’s a big thing. That’s a big thing nowadays, and it’s hard to trade against. Yes, it’s very, very hard for short sellers.
Jeff Malec 48:25
Right? Well, that the next edition would have a whole chapter right of that retails kind of become a new agent right there. Because they’re not, it used to be each one was doing their own thing. And I think with social media with these message boards, and we’ve kind of read, if they’re all pushing, they figured out if we all push together and use social media to push, we’re an agent, and we can spike this thing up and get, you know, get them to cover. So it seems to me to
Hari Krishnan 48:50
write a book about being Stokes chat. I’m not ready yet. On this one, but yeah,
Jeff Malec 48:55
but it seems to fit perfectly with the theory, right? Like Yeah, they’d be they become in mass, no, not one of them. But in mass, they become an agent. Which kind of got me thinking to have your, your theory of everything’s networked. Right? Have we become more so with social media and with globalization, right, that’s, it’s even become more interconnected. And agents can drive, you know, you had the graphs of all the nodes, right? They’ve not only have they become more connected, but some of them have gotten bigger, which will filter down and, you know, shake the spider web, so to speak.
Hari Krishnan 49:31
Yeah. Which begs the question, what’s the endgame of this for me? And what’s the endgame for the viewer? Or the audience of this? the endgame for me is, we are actively building models of what mega agents are doing, how they act, how they could impact markets, and so on. And we’re trying to trade around. So we’re trying to find value around pressure points in the market. Created by waves. Okay, that’s The technical thing, it lends itself to hedging because if you think that there’s a, I’ll give you the original example, I gave it in this discussion where there’s a well who has to sell at 95, the markets trading at 100. So I know that if the market gets down to 97, it’s going to blow through 96 is going to blow through. So maybe I buy the nice seats, but maybe I do something else. But I’m trading around where the whale is going to have to rebalance. that’s point number one. Point number two is more for the viewer, which is this and hedge funds have made this mistake to AI, there are some very talented people in the hedge fund space, I remember Everest capital tried to fund a lot of their positions by financing in euros versus swissy when there was a pack, and they got blown out doing that. And that was not a function of their investment function of being overconfident in a low volatility, yielding trade positively yielding trade that blew up against. And so my number one takeaway for the readership is do not scale positions as one over volatility, especially when volatility is low. yourself taken out one day, if you do that, and you don’t have regard for position risk. So don’t do that. Do less than you think you should in low volatility regimes, and maybe be a little bit more active when of all spikes, because then you know, that the genie has been unleashed and volatility is actually expressing true risks. In this environment, I think the right approach and the you know, whoever watches this is free to correct me is to do a little bit less, maybe not today, but in general, less than you think you should. Because if you try and gear up to the maximum level possible, what’s your target level, you’re going to be exposed if something happens, and other people will as well. And so there’ll be this vicious feedback loop, where you’re one of the sellers. So some of the easy takeaways don’t scale as one of the volatility scale in a way that’s a little bit different from what these programmatic strategies do, because otherwise, there’ll be defects in this, you won’t make enough relative to the risk in the trade to to justify what you do, do something a little bit out of the ordinary. From a risk management standpoint. I’m not saying don’t do something that’s not defensible, but don’t follow the crowd in terms of managing positions.
Jeff Malec 52:41
So with exhibit one, a and the trial of that theory be bonds, right, like super low vol, and they’re gonna have a flight to safety and all right, everything everyone loves about bonds. But maybe that’s a perfect example of like, there’s some hidden words there. We just can’t see yet. And they seem to be more likely to pop out sooner than later.
Hari Krishnan 53:05
Absolutely. That’s a great, great case. Yeah. Where you count on the Yeah, exactly. Bonvoy has been pretty low. You cannot scale positions, according to bondholders equity. Well, because, you know, what you see nowadays is that equity vol is actually quite elevated relative to volatility in other markets, fixed in fixed income and currency volatility, it’s pretty low. It’s artificially low for good reasons, which I won’t go into now. But equity volatility is still not that low. So to do relative sizing on that basis, it’s dangerous. Yes. Yeah.
Jeff Malec 53:47
Even if it’s relative, even if it’s just I’m looking at my, you know, treasuries, and I think it’s totally safe and totally low vol standing on its own.
Hari Krishnan 53:57
Jeff Malec 53:59
consider elsewhere. Come back for a minute, just of how you’re quantifying this, are you coming up with a single number? Does it inform each market differently? Is it all connected? touch on some of that if you could,
Hari Krishnan 54:19
okay, well, I’m trying to do something a little bit more concrete than what the Charlie metallic, what’s the world do? I think he’s very good at Nomura and various other people too, which is to come up with various models and positioning risks at risk and to figure out where what structures what strategies are growing disproportionately and not necessarily following them. But realizing what could happen if they have to rebalance or liquidate and to use that as a basis for hedging because, you know, you can have a lot of views and I’ve gone on the air on various stations. Not as good as yours, but I’ve been on various stations. And I’ve said well, how solid is the fact? Is it a hard put on credit? Is it a hard put on credit plus equities? Which is a bit of a speculative leap? Was or is it no plus? Now if you do believe that there is effect, but whatever’s been going on with the governor has recently, then you really want to protect against an air pocket move down in risky assets, sort of like a 10% down move in two weeks week or whatever.
Jeff Malec 55:33
And they have everything but beyond that covered,
Hari Krishnan 55:37
because they have everything beyond Well, yes, exactly. Yeah. Although if it is downturn, you really get to risk your career where your wealth won’t go down much further. That’s another question. So really, has you hedging against those sorts of position, or liquidation risks is a good way to play the market, because you understand that on the basis of liquidations, or overzealous positioning or margin changes in margin selling, so you can cover that even if you think the fact was so though, and
Jeff Malec 56:14
you mentioned, we’re great minds think alike. Cuz I was saying like one of the right, Charlie gallican, that you mentioned. No more. Yeah, I was out with the CTA position, I sometimes take offense as being deep in the CTA world of like, hold on, I’m behind the scenes seeing actual positions. And that’s not totally what’s going on, or they’ve exited. So sometimes I’m a little pushing back on that, which you touched on in the book, a little bit of like, we don’t necessarily need to know everything about these positions. But if we have the general idea, correct. Right. You have any thoughts on that?
Hari Krishnan 56:52
I do have a friend Mark Malek conquest. Yeah, I’ve known him for years. And I don’t want to misrepresent what he says. But he used to have this idea that he could replicate the returns of any CTA or any CTA text that you gave him by mixing and matching the asset allocation or the weight assigned to shorter longer term trend signals in any given system, or in his system. So you know that he can take a return stream, and say, if I focus more on short term signals that say, more on rates, or equities, I can more or less match the return stream of a given fund now, generating alpha over and above that is irrelevant. It’s more a function of knowing what they’re doing. And so using a system that you have in house, as an inference tool, to guess how people are positioned is pretty powerful. You don’t need to trade that system. Yeah, you just need to use it as a risk indicator. 100% accurate, right? Yeah, it could be 80% 70%. If you get the gist, or the just a picture is probably just too progressive. Just Yeah.
Jeff Malec 58:09
And Mark’s old partner Nagel, who’s been on the pod and he went into a he can replicate almost any hedge fund, just with short VIX and S&P exposure, right? I’ve just basically just levered one way or the other of, of those kind of tools. So that’s super interesting to have like, and you see that okay, it doesn’t really matter what names they own. At some edge case it does because if just one name sells off, never exit, but right if there’s one big move down and all these names are getting liquidated, and it’s kind of the same thing.
Hari Krishnan 58:41
Absolutely. I fear that discretionary macro is largely a function of one or two decisions made over the period over a 10 year period. So let’s say that you work long or short fix that just before a crisis, you decided to turn the dial down. And you got out of it. Yes, ashcan career. Yeah. And yeah. quest and conquest have kind of cottoned on to those concepts. Yeah, definitely.
Jeff Malec 59:12
And I want to just ask, like, I’ve spoken to many quants managers of the year who kind of say and maybe they’re all fashion or we can get into it like this none of this matters right I can see it on the price stream that’s the ultimate tell of where positioning is and everything of where prices are at the end of the day and remember even at the end of the minute or whatever but write that in you there’s these people price tells all I don’t need to know all this information what do you say to that I’m not putting forth their argument all that well but you put it
Hari Krishnan 59:43
forth pretty well. I’d say how to do size and position if you set the size them as one over ball. You’re in that game anyway. That’s basically what I’m telling you downsize it’s one
Jeff Malec 59:55
game anyway like your risk.
Hari Krishnan 59:57
And you can say the price is the only thing that matters. You We’re making an allocation across segments. So if you have Nat gas is one position. And euro dollars is another position. Obviously you’re sizing the Euro dollars bigger in terms of notional exposure than you are in the NAT gas. How are you doing that? are you basing it on realized volatility? If you are, and there’s positioning risk in one or both. You’re still making some implicit assumptions that are not encoded in price. They’re encoded in maybe in the volatility of price or distribution, but not in the price direction. So Well, yeah, I don’t know,
Jeff Malec 1:00:39
you could argue that it’s it really embedded in the price, right? Like it doesn’t, not as many contracts are bought, because there’s positioning risks. So I dial down my, my exposure, and then it doesn’t drive the price up high enough or something.
Hari Krishnan 1:00:53
Great, great debate, we can have that one. Let’s say that I ran a trend follower with one thing. I’m going to look at the 10 day 100 day moving. Today, the 10 day moving average is higher than the 100 day. But it’s been a rocky road. It’s been super choppy. If I know take volatility into account, I’m going to be potentially under over allocating to that position. If I don’t take positioning risk, perhaps isn’t expressed in terms of the jaggedness of the path into account. I may have a different allocation than you would if you didn’t take. I hope that’s clear. Yes, basically, that sizing seems to be based on realized volatility. And signaled seems to be based on just some combination of fairly crude indicators that may take some path dependence into account. But don’t take positioning risk into account directly.
Jeff Malec 1:01:57
And by positioning risk, we mean that there’s
Hari Krishnan 1:01:59
everyone else is doing the same trade. Yeah, I am more elaborate than I am. So they’re gonna have to bail out sooner.
Jeff Malec 1:02:08
Would you argue some of this not taking positioning risk into account is some of the CTA struggles over the last 10 years? Maybe they, you know, so systematic focus that they’ve forgotten that there’s other players in the game. I guess, basically, we’re saying you can’t just play the game. You got to play the players at the table, right?
Hari Krishnan 1:02:28
Yeah, I mean, any CTA that many CTAs, I don’t want to speak for all of them, because I’m not universal on this, but they’re probably made a lot of money being long fixed income. And so they have been playing the positioning risk game to their benefit for many years, which is central banks have allowed that fixed income game to work? Well, yeah, whether it’s with keeping the short rate suppressed, or kiwi, which keeps longer bonds, it gives support to longer bonds. So an IOU grandfather would not take this into account. But if the if things should change. And I could go into lots of speculations about that. If the central bank should be less active in this, then there could be some very ugly surprises in store for people who are simply basing their allocation on trend with a scaling rule that’s based on one divided by realized volatility. Right. That’s why we focus so much on the ball is a really a really a structural hatch.
Jeff Malec 1:03:40
And then what so if I’m doing that model, I’m saying coal, natural gas volatility is what I’m going to use dollar terms. I have $10,000 per contract. I have a million dollars. I’m risking 10 pips. So I’m going to be one contract. Somebody, check me if my math was wrong on that. But right, you get the point of like, I have a VA number, I get a signal. I’m doing one contract based on that phone number. You’re saying that’s dangerous, right? Because that’s just based on some abbreviated look back period, a ball. But then how do I fix it? So do I extend the look back period? Do I just add some random numbers? You’re saying now, you need to quantify what that
Hari Krishnan 1:04:22
you can quantify, quantify? Yeah, otherwise do 50% of that. Yeah, no, nothing better to do. And of course, the book doesn’t cover every case. Positioning risk is hard to quantify. In every case, just don’t do too much. If you think you’re dealing with a pegged currency or an artificially depressed asset. Don’t go hog wild, do less, just less.
Jeff Malec 1:04:48
And do you have any ones that you can share it that are staring everybody in the face or that people are talking about such as the Swiss peg or the short VIX, ETFs or the British Pound Back in the day,
Hari Krishnan 1:05:01
well, this isn’t my idea. But I’d like to present it which is the Asian currencies are, have been unusually correlated recently. In other words, the cross Asian currency volatility, especially excluding the rupee, but other ones that have been extremely stable. Now that could suggest political influence, I’m not going to go into that, or geopolitical forces. But it also could suggest to investors that they, these are safe currency pairs, I will be more cautious. Now because there is an edge in getting the higher yielding currency, visibly the lower yielding one and we’re trading against the mega country, all I would say is that don’t expect that to be persistent in the future without potential with the left hand with that. So there are things like that where there’s political compression, or geopolitical compression in exchange rates, or geopolitical coordination of interest rates, where one could see real blow up. So I didn’t want to be the guy, the zillionth guy who comes out and says, oh, yields are too low, they blow up here, everywhere else. That’s a hard trade. It’s a hard trade for two reasons. One, because there’s tremendous political incentive to keep yields low. Also, because there’s roll down, you know, even if the tenure has a very low yield, if the five year has a much lower yield, in percentage terms, you’re fighting against the time.
Jeff Malec 1:06:46
Hari Krishnan 1:06:50
Still, I would be very cautious about these three and been wrong for 20 years, but
I don’t blame him. Yeah, I’m not gonna fall into that trap. I’m not the conduit who’s gonna come out and say, Oh, it’s all gonna blow up next month. But I’m just saying there are a lot of structural risks to downscale according to Markowitz, or risk budgeting.
Jeff Malec 1:07:08
And it seems to me my brain just rolls with all these possibilities, right, like Michael burry, and the credit default swaps, right? Like are the mortgage backed loans, right, a similar thing, there’s these huge agents playing this game. If it just trickles down a little bit, it’s going to kick off this cascade where all those have to default. So, right? There’s a million examples like that. But a lot of the examples are people played that on offense, you’re, you’re kind of saying just consider them if you find them, why not play them on offense, but especially be concerned about Fred, and a lot of people a lot of money trying to play that short housing, right? it because it persisted for a long time, so would have been wise to be aware of that risk.
Hari Krishnan 1:07:54
And we’re in a very weird period in the markets where the standard strategy over the years for me was, sell the, or sell insurance against the risk of a moderate down move, and massively buy insurance against the risk of a mega move. But people have cottoned on to that. So they are bidding up the tails quite a bit. I think that seems that ladder, very salaries have been responsible for that. But conceptually, that’s the right way to play. If things are gonna break, they’re gonna break very badly. So currency pegs are a great case study for this sort of question is, as a money manager, can you manage them? So if I self near nearby insurance, and massively over by far away insurance, saying that if the currency peg breaks, it’s gonna break big time. And it breaks somewhere? And I’m sitting at my desk on a given day where I have a rule in my system? What do I do that because if nothing happens there, I could actually lose money on a hedge. So betting on the extreme Taliban is requires a lot of skill.
Jeff Malec 1:09:01
Yeah. But it’s also just it’s back to Nagel, and we’ll put a link to that by right just be positive skew, right? Like that kind of takes away any of these outlier move risks. Right? If you just have kind of a bent towards I’m going to capture these asymmetric moves instead of sell those asymmetric moves.
Hari Krishnan 1:09:22
Exactly. Michael has a meditation. Yes, yeah. Get into it. With a name like mine, I think I could probably read mine out for a little bit more but more power to him.
Jeff Malec 1:09:41
You mentioned before but like main takeaway you want you want people to get out of the book.
Hari Krishnan 1:09:49
The main takeaway is that the major drivers of market movements nowadays are leverage and positioning risk. Those are the twin heralds at risk if you don’t have a handle on that You need to be worried about the way you put the way you put your money into the market, because those things can rear their ugly heads. And the fact that there are more episodes of large spikes in risk from nowhere should make people cautious. Now, that doesn’t mean they shouldn’t be in the market. In the markets pretty good idea, I think migraine is set a lot of things about the impact of passive flows on the drift, the S&P medium returns have gone up. But long plus hedge or long plus a genuine diversifier is a good way to play. You don’t need to do it through tail hedges, you can do it in other ways. But diversification is not working well not, in my opinion work as well as it has over the years. And the reason is that we live in a flow based marketplace. And anyone who doesn’t understand that is vulnerable to getting everything go down in size. At the same time, maybe it will bounce back, maybe the Fed will step in, if you’re in that position, if you’re in that seat. You might not feel too good about your position at time. And so there’s a old saying that every endowment has a 50 year horizon. guys sitting in the seat 50 year horizon. Well, not a three year horizon,
Jeff Malec 1:11:22
apparently last year, they do because they’re all posting 30 4050 60% returns. Right? But that’s that’s the craziest thing. So a lot of people are they are way too clever by half, I’ll say, right? Like, is this too smart? for his own good of like, when all the winners are my question, right? I’m like, hey, wash, you put up a 56% saying, Who cares? Maybe the flow is why they are all in on equities. You know, I’m not gonna discount how smart they are. But maybe they’re saying, Yeah, all these macro agents are pushing things to the moon. And we’re going to be fully invested and take advantage of that.
Hari Krishnan 1:11:59
Well, there’s a world of average returns, and there’s a world of compound returns. And maybe the ultimate, the final frontier, is diversification between the world of average returns in the world of returns. So I work for a firm that does a lot of machine learning. We always look at average returns in the ML stuff. Why? Because average returns are not susceptible to leverage. alterations, if you have a positive average return, there is some level of leverage that will make that a good strategy if it’s sufficiently positive. But hedging is the world of compounded returns, the world where you can have a negative drift strategy that saves your you know, saves you scared when things get really ugly, and also allows you to compound more aggressively using the hedge as a way to access capital when you need. And I think, you know, I haven’t given this speech before, but it just kind of, I think it is a good one, which is the diversifying between the world of average returns and the world of compounded returns is the ultimate form of diversification. And that’s really what one needs to be focused on. Yeah, 36%, whatever I want, guess what they did? Baby 56% of it is unlisted assets like that they had marked themselves. Who knows? Yeah, more power to them. But if it is, a all that stuff has liquidity risk, and pay. They’re all focused on hepatic recipients, perhaps as much as they should be. Now. I agree that you do need to follow the flows, though I don’t resent anyone saying, look, all this money’s flowing, it’s passive. All this passive is flowing into large caps. The large caps are accelerating. Fine. There’s no reason not to follow that. But that cycle can reverse pretty viciously.
Jeff Malec 1:14:03
And explain real quick what you mean just by average returns versus compound return? I think what you mean the average returns,
Hari Krishnan 1:14:13
let’s say that I had a strategy that made 1% if I was right, I lost 0.9% client was wrong. Every day. There was a there was a coin flip. That’s a winner. Right? That’s a winning strategy because my average is 10 basis points and um, you know, on that trade was point five times 10 basis points, but anyway, but if I gear that thing up, if I do it, five to 110 to one, I’m going from 1%, up on up days to minus 0.9% on down days. I’m going from that to 10% up days and 9% Down days, that’s a losing strategy. Because the down days require a bigger return to dig out of that hole. So the world of looking at the median outcomes is the world of average returns over whatever horizon you trade. So the world of compounding returns, you need to find an edge over in the average return world. And that’s what works. Get our product our lab in mediocracy. Ah, yeah, it doesn’t cover the towels to tell us how to be covered elsewhere. But that’s the only way to do model building. But it’s not the way to think about managing the structural risk in your portfolio. I’m always open to questions. So you know, if you want to pop something on Twitter or anything else,
Jeff Malec 1:15:50
yeah, you’re sort of new to Twitter when you come on board last year? Yeah. 2020 and 2020. Right
Hari Krishnan 1:15:56
in time. 2021. So yes, it’s been less than a year. Yeah.
Jeff Malec 1:16:03
It’s been a good fall. So follow him on Twitter. Where do they get the book? How do they get the book?
Hari Krishnan 1:16:08
The best deal is on Springer has a 25% discount for all books until September the 30th. Time shorts.
Jeff Malec 1:16:18
Awesome. We’ll go everyone read the book, file hiring, you won’t regret it. dition some of the best knowledge out there in the ball space.
Hari Krishnan 1:16:27
And just one final comment for me is the acknowledgments to you. And Taylor and Jason was heartfelt because you guys have really been thought leaders in space. Thank you guys.
Jeff Malec 1:16:40
Appreciate it. Yeah. With some other good company to be in there.
I think so. Yeah.
Jeff Malec 1:16:48
Well, Hari. Thanks so much. We’ll see you whenever you get out of your house. I don’t know. We got to get out that way and visit each other one of these days.
Hari Krishnan 1:17:08
Always welcome. Thank you, Jeff.
Jeff Malec 1:17:15
All right, thanks so much.