If you were wondering how much SoftBank made buying calls on US tech stocks over the summer, the answer is around $4 billion, apparently. The gains are unrealized as of now.

SoftBank’s aggressive buying program entailed spending some $4 billion on upside premium, with Masayoshi Son taking on notional exposure of around $30 billion in the process, sources told FT, which unmasked the “Nasdaq Whale” on Friday and followed up with additional details around 48 hours later.

One columnist remarked that investors have long debated “whether Son is a true visionary” or more of a gunslinger. Over the weekend, former institutional equity derivatives trader Kevin Muir likened Son to a “riverboat gambler” as it relates to this trade.

Read more: Whale Tales And Riverboat Gamblers: The Story Of 2020’s Summer Tech Bonanza

Those characterizations were echoed by at least one source with direct knowledge of the positions who spoke to FT for a piece published Sunday. “It’s just a levered punt on the market”, the person said, adding that “the whole strategy is just momentum buying”.

That’s correct, but the trades themselves, alongside the by-now-familiar, multi-month theme of small, speculative buying in short-dated paper, together created an interesting risk management environment for the Street.

The dynamics associated with the SoftBank trade(s) are different from those engendered by retail option activity, but in both cases, the proverbial “tail” has most assuredly been “wagging the dog”, as dealers’ hedging needs end up amplifying upside moves in the underlying, impacting the index and/or driving up implied vol.

Again, the specific ramifications for dealers from the flows associated with the two types of gamblers (a couple of whales and tens of thousands of home gamers) are distinct, but in both cases, you get forced adjustments as the underlying continues to surge and the upside premium buying persists.

As discussed extensively in the “Whale Tales” piece linked above, it’s not possible to delineate precisely what’s attributable to the knock-on effects of opaque institutional flows and what’s down to what Nomura’s Charlie McElligott described as “the larger theme of ‘Robinhood-esque’ speculative buying in short-dated deep OTM calls”.

Macro Risk Advisors’ Dean Curnutt dubbed the latter “The Mighty Call Trading Legion” (the acronym is “LTCM” in reverse) and it’s been the subject of a series of Bloomberg articles which together suggest that retail traders may have done more to create the self-feeding loop at play in tech than SoftBank or any other large, institutional flows.

Bloomberg’s Katherine Greifeld, Vildana Hajric, and Sarah Ponczek have spilled gallons of digital ink on this subject over the past week or so, including a pair of posts out over the weekend.

“What is emerging as a parallel factor in the market’s often-uncanny buoyancy is the presence of giant options positions in many of the same stocks [stuck-at-home individuals] favor”, Ponczek wrote Saturday, adding that soaring call open interest is visible in “virtually all the stocks that have led the rally”.

The overarching point in all of this is that no matter how granular (or not) you want to get when it comes to parsing which flows mattered more, and how the hedging of those flows served to accentuate directional moves and/or create the “stocks up, vol up” character of the late-summer rally, separating the tech surge from the options mania is now all but impossible.

And, as some readers pointed out over the weekend, to the extent retail traders were driving this earlier in the summer only for larger players to jump in last month, it means that a Reddit experiment wherein home gamers collectively tried to harness the power of gamma flows, actually escaped from the lab.

Bloomberg’s Greifeld and Hajric said as much explicitly in a piece out Sunday. “The strategy celebrated in the Reddit forum r/wallstreetbets is at least fairly simple — spend some money on bullish calls on shares you own in hopes of forcing the sellers to purchase the same stock as a hedge [then] an ensuing feedback loop drives everything higher”, they wrote, on the way to musing that “now, by happenstance or design, something like this appears to be happening on a grand scale in US technology shares, dialing up a blistering rally and possibly worsening last week’s decline”.

On that narrative, the notoriously clueless masses — your stereotypical retail “bagholders” — spent months working on a Frankenstein blueprint in the Reddit basement.

After shocking this monstrosity to life with their own call buying, the creature made its way up the steps, out of the lab, and to the front door of the castle. When institutions decided to employ the same strategy, the castle door was thrown open. As tech continued to rally, the short gamma feedback loop kicked in. Frankenstein then ran down the hill, into the village.

He’s still loose.


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14 thoughts on “Frankenstein

  1. Can anyone help me understand this: do (and how do) dealers set the premium for an option? If dealers perceive risk to themselves from options transactions, can they simply jack up premiums to compensate?

      1. While the Black-Scholes model was the first to try to help determine “efficient” intrinsic values for options, before its publication the market was very different, but instructive. While a finance doctoral student in the late 1960s I shared an office with a brilliant 19 year-old PhD student who was an expert in options. In those days options had no organized market, no exchange trading. Options were transacted through facilitating broker-dealers who literally put buyers and sellers together on the telephone where give-and-take auctions would take place until the parties agreed to a price. My classmate would start getting calls when the NYSE market opened and stocks started to trade, something that would last until the Pacific Coast Exchange closed. Some broker would call him and say something like, I’ve got a guy who wants a put for 600 shares of IBM to expire on such and such a date. Will you write it? How much do you want for the put? My friend would make a few calculations and say I’ll write the put for $xxx. The broker would say something like, I’ll get back to you. Fifteen minutes later the broker calls back with an acceptance or a counter-offer. If the deal gets done, money changes hands, the transaction is recorded and funds held in the proper account. That’s how premiums used to be set. They were whatever the market needed to clear the transaction. This classmate was very good at this, btw. He essentially started at zero in high school and when I graduated he was nearly done with school and had a mid- six figure net worth and a PhD. His dissertation was the first comprehensive study of the options market. Now the market is ordered and bid/ask prices are open for all to see. The market is centralized, transactions take place on exchanges and deliveries and exercises controlled by regulations. Still the market sets the price.

    1. Options pricing is just like any other pricing. The premium goes up when few are willing to sell options and many want to buy them. Sure, Black-Scholes and other models serve as guidelines, but ultimately the price is set by buyers and sellers. Search for “volatility smile curve” to learn more.

      Yes, what you say is true. When the volatility of the underlying is high, you’ll see liquidity dry up in the puts and calls because the options sellers don’t want to get burnt. Lower volatility tends to drive the risk premium up: only those who really want the insurance are willing to chase the widening spread.

  2. “SoftBank’s aggressive buying program entailed spending some $4 billion on upside premium, with Masayoshi Son taking on notional exposure of around $30 billion in the process.”

    I’m a little confused by this in the reporting, as I believe it has also been reported that the buying was in deep OTM options. Right now, for example, AAPL is trading 120ish, and for the same leverage as described above the option purchased would be $16. An option costing $16 for AAPL, for say Oct 23, 7 weeks out, would be at about the 100 strike, or $10 in the money.

    1. The reason I bring this up is it seems to me that Softbanks buying, if the description of the program in the reporting is correct, was not likely in deep OTM options. A ratio of 7.5-1 premium suggests in the money options, or modestly out of the money options, depending on the volatility of the underlying. Perhaps the Softbank buying was in options relatively close to the price of the underlying, and its effect was amplified by retail buying deep OTM options.

      If so, retail once again was the beneficiary of what larger buyers were doing. At least until Thursday.

      1. Exposure equals spot price times delta (value change of the derivative for every dollar change of the underlying). Options close to the money have a delta of around 0.5.

        October 23 AAPL 140 calls have a delta of 0.25 and a cost of about $4. With spot at $120, the leverage is $120 * 0.25 / $4 = 7.5 to 1.

        This agrees with the reporting.

    2. It would be silly for SB to buy options with two-three month expiration date.
      S130 calls for June 2021 cost exactly 16.
      And one-two month ago $130 was way OTM.

  3. I’m interested in game planning the unwind. This does not seem like a viable long term strategy and is merely playing on current market psychology (markets can’t go down because of Uncle Jerome).

    I would expect a black swan would be the catalyst. Then a lot of forced selling. SB and Robinhooders take a bath. But what is the risk? Are we talking about hitting down side circuit breakers for multiple days in a row? What’s the amplitude of the downside.

  4. A Greek that springs to mind is Lamda, defined as the ratio of leverage the option will provide as the price of the underlying asset changes by one percent. The sensitivity increases with price and volatility. So as price goes up at the same time that volatility is increasing, the delta leverage explodes forcing those short to rebalance and buy more an more stock. The Reddit strategy is real. I still wonder if the Whale rebalanced, although it seems to be the case that this did not happen according to most reports.

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