So you want to see a meme squeeze:
Please remember I'm a 25 year old girl, and most of what I'm going to talk about with regards to volatility and options is wrong. That disclaimer aside, the popular topic again is meme stock rallies. What is a meme stock rally? 1/x
A meme stock rally is essentially a dislocation that occurs in one or a group of related assets, usually thematically related (the semantic web I discussed many moons ago) that rallies for a short period of time. These tend to start on social media, and one of the foundational 2/
aspects is simply it being funny. We can debate that ad nauseaum, but despite common belief, this isn't really a new phenomenon, and there is ample evidence that supports these price dislocations occurring in 2020 and well before (the 2018 weed bubble, for example). There are two
major causative factors here: realized volatility, and leverage. As the wonderful @choffstein has written about prior, those two concepts are related. What's interesting is the use of weaponized leverage here with convexity, bringing us 2021's buzzword, "gamma squeeze"
Leverage is interesting because, as I blog about in crypto as well, it's one of those special cases where you can exactly know the action of your counterparties, versus the general guesswork of normal trading. When the margin requirement hits, position gets liquidated in crypto
which, in aggregate, can greatly move the coin price. This is because you see a liquidation *cascade* - the action of one liquidation triggers another and another and another like dominoes, until everyone is rekt. We see it pretty similarly in equities due to options. In the most
abstract way, you can view a long option position (let's face it, most of the meme stock OI is going to be sold by MMs/bought by the market) as a leveraged bet with fixed downside (the premium). This is nice, and acts kind of like our leverage in crypto. The more interesting part
isn't the delta (essentially our leverage), but the action of two greeks here - vanna and gamma. Mainstream financial news in general focuses on the gamma aspect, and undeniably that's a significant force. The cycle goes roughly:
1) Ape buys call
2) MM buys shares to hedge (delta)
3) Other ape buys call
4) MM2 has to buy shares, moving price, causing MM1 to buy shares
Ad infinitum
This is important, but we'll get back to it anyway.
There's three key postulates here which we kind of handwave, but are important in seeing the activity of gamma squeezes.
The first and foremost is the float size. The reason gamma squeezes occur is not just because ape buy call, but because of market depth -- more specifically
how thicc our orderbook is. The reason gamma squeezes or w/e occur is because buying shares to hedge moves the price, causing delta of calls to go up, causing more shares to be bought. The thinner our book, the more buying or selling moves our price. This is why you largely see
low float stocks moving, exacerbated by locked institutional float and/or short interest. It's very hard to gamma squeeze an apple, perhaps easier to squeeze a movie theater. However, we can't use volume as a proxy here for our orderbook thiccness - AMC for example, moved 700mm
shares recently. What you *really* want to know is how 'illiquid' it is, which is a more nebulous concept. If you look for example at the covid crash, SPY traded around 1 billion shares, but in the same time price moved a whole lot. On a normal day, SPY might move ~70mm shares
but move an inch or stay flat. Those are clearly not the same when it comes to squeezing our memes, since we care about price moving and that juicy premium. It turns out finance nerds think about this a lot, and come up with weird ways to measure this: Kyle's, Amihud's lambda, et
But anyway, so we've established the thickness of the orderbook matters, and that's why you tend to see shitcos squeeze the squoze. But let's go back to the tasty options and leverage here. One of the underappreciated aspects of meme squeezes is the volatility. I'm going to
mostly gloss over gamma here, except to talk about laddering and tenor if I don't get bored beforehand. But essentially, one of the key drivers of the meme squeeze is realized volatility - the volatility of the underlying - EXPLODING. We saw this with GME, with AMC, etc.
You see IV explode as MMs catch up, or since they all have PTSD by now, you see it pre-explode. This does a funky thing to our options. At the extrema, 300, 500, 1000 vol -- delta is effectively meaningless because *any* price can feasibly be reached. An option contract way OTM
is gonna have a ton more delta than usual thanks to the volatility and chaos, and as @danielrock once told me re: GME, basically every single contract becomes 50 delta. This means due to vol MMs have to overhedge substantially, and of course beta correlation hedging goes out the
fucking window (in general you can hedge like-pairs trading, like KO vs PEP, even for options hedging, but how do you do that in insanity? you can't). So the options market ends up 'weighing' much more, and each call you buy ends up moving the price even more. But it gets better
in the first and second meme squeezes, you also saw a ton of toxic order flow. This is the funny part of being an MM. You make a lot of money by picking up pennies, but the downside is you can fall victim to adverse selection - informed traders eat your lunch and make you pay
. We could see this stupidly clearly in January, by the action of the bid-ask spread, especially in the options (but also in the underlying at points) of GME. What happens when MMs get f*'d? They leave. By conventional estimations, top of book MMs make up about 75% of quotes
, but this of course varies in time and by ticker. When they leave, liquidity dries up fast. Remember we talked about that? Liquidity and volatility have a funny relationship. Low liquidity increases volatility. Which increases implied volatility, which increases our vanna.
So now we're getting some factors here. This time around, MMs are way more crafty, and you can see this in the much tighter bid-ask spreads especially in the options. No more free lunch and paper thin order book. Big boys are playing now. But I hope this helps you hunt for the
next meme stock. Fin.

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More from @LilyWrites4

9 Nov
Okay, so I want to talk about some vol f**kery in the meme stocks, and how to play for fun and profit. That said, not investment advice and in the interest of not upsetting compliance, I'll leave off the actual stock names too.
So lately, things have been odd.
1/x
There's this large company that we all know about that rallied like 50% in a month and pissed off a lot of people. This came at the same time as a larger sector trend rally, so it wasn't too unexpected. CEO might've merked it though.
But anyway, lots of people tried shorting.
In general, shorting these things is a bad idea directly, because of course everyone is buying puts thinking they're righteously clever, and of course the puts tend to be overpriced. In {insert company}'s case, calls were also generally broken, but I digress. So how do I short?
Read 18 tweets
1 Oct
Hi, it's been a minute since I made a thread (I deleted a prior one two weeks ago). This thread will be about natural gas and the United Kingdom, mostly since I have a research post about it coming out probably soon. I am not a natural gas trader unless you count FCG.
I do not claim complete accuracy, and you're more than welcome to correct nicely if there's any misinformation, or get blocked otherwise. Anyhow --
1/n
As I posted yesterday, something weird is going on with natural gas in the United Kingdom. Natural gas prices are going up worldwide from a combination of factors: industrial output returning after COVID-19, mismatched reserves to demand needs, climate factors in a few places 2/
Read 26 tweets
16 Jul
So, a brief thread since I haven't done one in a while about volatility. Unlike all my other threads, this will probably be wrong or something, I'll wait until someone who does vol chimes in or go ask like, Benn Eifert. Volatility in short, is a function of variance and time.
Or in even simpler terms, we have some variable we're looking at - usually price, or more formally spot price. We're looking at how it evolves over time. The wider the distribution of spot prices that occur in a given time range, the more volatility we say is occurring.
This is usually expressed as a function of the spot price itself, but depends on the context. In general the way stock prices move is naturally expressed as a % of the given stock price - we say stocks went 1% down today, vs let's say $3 down. This holds empirically too.
Read 24 tweets
30 May
I don't know who needs to hear this today, but if you have two time series that both increase over time, they will especially visually show spurious correlation. This should be intuitive. Imagine I was looking at number of CS graduate students versus the number of arcades open.
So I fit a model to both, because that makes sense. In this example it shouldn't really matter if I take the totals of each, because we can obviously surmise both the total and rate of CS graduate students is increasing over time. We can't obviously say the same about arcades
without some data to back us up, but we can guess it probably is also increasing at a rate related to urbanization and normal population increase (arcades per capita, essentially). Here's what our graph looks like. Image
Read 10 tweets

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