Collected Thoughts on the GameStop/WSB Imbroglio
Buy the rumor, sell the news
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Introduction
People have been asking me for my thoughts on l’affaire GameStop, and I’ve offered them in a disaggregated and disjointed manner. Here is my attempt to collect them all and synthesize them into a coherent narrative. A fair warning: I’m not on any particular side here. In any fight between apes, shit gets flung everywhere. Intrigued? Read on.
David vs Goliath
There is a facile temptation here, which is to conclude that social media-mediated stock market manipulation is evidence of the David vs Goliath narrative. Glenn Reynolds, law professor and, more famously, Instapundit, argued as much in the New York Post:
This display of spontaneous group power by a bunch of previous unknowns has frightened the Really Smart People(TM) and led to reactions that will make things worse, not better. Some discount brokers started displaying warnings and limiting trades. Discord, a popular online chat service used by the r/wallstreetbets group, shut down the group’s service, offering the usual contemporary excuse that the group was engaged in hate “hate speech” and “spreading disinformation.” Uh-huh.
The David v Goliath narrative is, of course, an allusion to the mythological story of the diminutive David slaying the giant Goliath. In this telling, the retail traders are David and Goliath is the various hedge funds which got caught in a short squeeze.
But this narrative is not too compelling because it misapprehends the algorithms on both sides of this trade. The retail traders who bid up GameStop’s stock are merely humans caught in the middle of increasingly sophisticated algorithms.
The Silicon Angle
The correct way to view this event is through the lens of algorithms:
This requires a bit of unpacking, but Vladimir’s point is basically:
High frequency trading firms (HFTs) buy retail order flow from the likes of Robinhood & Schwab and use that data for their trading algorithms.
Social media companies’ algorithms are trained to prominently feature content which triggers an emotional reaction in people, and that trigger induces some of those people to enter the GameStop fray.
Thus, people (retail traders) are caught between increasingly powerful algorithms. If you extrapolate this line of thinking over the next five to ten years, you will (1) have more of these situations and (2) expect them to be even more volatile.
While the David v Goliath explanation has some kind of attractive narrative simplicity, it ignores what I think is the real issue here, which is that people are getting caught between dueling algorithms, and, critically, don’t understand the game they’re playing. They’re not strategic actors, but, rather, in Vladimir’s construct, mere pawns.
Feedback Loops
Yet another way to understand what happened with GameStop is the notion of feedback loops, as explained by Morgan Housel:
Find a feedback loop and you will find people who underestimate how crazy prices can get, how famous a person can become, how hard it can be to change people’s minds, how irreparable a reputation can be, and how tiny events can compound into something huge.
They take small trends and turn them into big trends with unforeseen momentum. And they happen in ever field.
…
The reddit campaign to push [GameStop’s] stock up started two months ago. At first shares rose a little. That caught people’s attention, those people bought, which pushed prices up more, which caught more people’s attention—on and on—until this week when virtually every investor in America is paying attention to GameStop because it’s risen so high, and it’s rising high because every investor in American is paying attention to it.
And, of course, the aforementioned algorithms both seek out these feedback loops and encourage them.
What’s New is Old
Another interpretation which is also wrong is the claim that this event is somehow indicative of a new, retail-driven era in the markets. Back in February, 2020, Byrne Hobart wrote, of Jonathan Lebed:
One of the best winning streaks in financial history belongs to an independent prop trader named Jonathan Lebed, who made roughly 10,000% from late 1996 to early 2000. Lebed was an agile trader with great timing, especially in small- and micro-cap stocks. He was also, in 2000, fifteen years old.
Lebed’s strategy is very well-documented, because the SEC made him stop; he’d buy stocks, tout them on Yahoo Finance message boards, and sell. What you think of this approach depends on what you’ve read about it. The Michael Lewis article is a good start, arguing that Lebed’s behavior was, in substance, identical to what analysts and amateurs do every day: everyone touts stocks they want to go up, and by induction many of the most energetic touts have serious skin in the game.
Hobart goes on to connect Lebed’s Yahoo Finance-mediated market manipulations to WallStBets, the Reddit subreddit that famously called for retail traders to bid up GameStop’s stock. The point here is that retail traders have been influencing the markets, in sometimes surprising ways, for a quarter century.
The Professionals Don’t Understand the Crowd
Finally, perhaps the most troubling aspect of this whole situation is that a lot of the institutional traders and investors evince little understanding of social media, or the extent to which social media-induced crowds can affect the markets. For large cap stocks, it’s very hard to conceive of a social media-induced short squeeze, simply due to those stocks’ deep liquidity. But for a small-cap, thinly traded stock like GameStop: it doesn’t take that much capital to bid the price up and squeeze the shorts.
Conclusion
Casting this in terms of David v Goliath gives humans too much credit and algorithms not enough. It’s a seductive narrative for those who dislike authority and centralization, but it’s simply wrong. The human actors certainly did slay a hedge fund or two but they did so with neither tactical nor strategic intent. They merely acted as pawns on a chess set mediated by two sets of complex algorithms. And that’s the real story: our world is quickly moving toward one in which almost all commercial transactions are mediated by algorithms. And those who are positioned to understand those algorithms (or at least approach understanding) will prosper. The rest of us need to watch out.