Can Wall Street algo traders win at the NFT game?

For now, the best-known non-fungible token (NFT) investors are folks like Pranksy, Cozomo de’ Medici and Vincent Van Dough. These pseudonymous collectors have amassed troves of digital art so valuable that they can move prices simply through their endorsement.

But a new kind of heavyweight investor is emerging on NFT marketplaces like OpenSea — one very much aware of the influence of big-name collectors: algorithmic traders. 

Crypto trading heavyweight GSR, which moves more than $4 billion in crypto per day, caused a splash earlier in January when it unveiled plans to start using software to trade the largest, most sophisticated NFT sets. The former Goldman Sachs executives of GSR did not, however, come up with the idea. 

There is evidence that automated ‘bots’ have been operating on OpenSea for at least six months, if not longer. Indeed, some operators in the NFT space openly bill themselves as quantitative traders. 

But what does algorithmic trading mean in the context of NFTs? And in the new and relatively slow-moving marketplaces built for these assets, how do the quants find an edge? 

Macro and micro signals 

Skillet Capital is one example of a small quant shop that has discovered a lucrative method of flipping NFTs. 

Co-founders Jordan Heffler and Sean Parsons, who studied together at Penn State University, began with $15,000 of their own money and in a short time have grown that pot to over $4 million, according to Heffler. His associates have backgrounds in data science, machine learning and computer science.

“We started by qualitatively investing in what we thought to be undervalued projects and have since transitioned to high-frequency algorithmic trading strategies,” says Heffler. 

Those strategies include arbitrage plays across different NFT marketplaces. Skillet scans these venues, hunting for variance in the minimum purchase point (the “floor price” in crypto parlance) of certain sets, with the goal of pocketing the spread. 

The outfit’s algorithms also try to identify situations in which NFT owners have mispriced assets, either by listing them below their floor price or too cheaply given the item’s characteristics. Another tactic is to create “minting bots” that can seize on bargains during periods of high volume and volatility in the market. 

“We are scraping real-time as well as historically-looking data that allows us to make informed decisions,” says Heffler. He would not expand further on Skillet’s strategies. 

Then there’s GSR itself, which has more than eight years of trading cryptocurrencies under its belt. 

In developing new algorithms for the NFT space, GSR, too, will pay close attention to the floor prices of certain tokens, according to co-founder and president Rich Rosenblum. But GSR will also home in on the wallet activity of famed collectors. 

“Much of the activity is dominated by a relatively small group, both in terms of minting and trading,” says Rosenblum. “This makes wallet tracking even more important than it is for trading of tokens, especially when the top wallets tend to have similar trading patterns.”  

The former Goldman Sachs managing director divides the factors that feed into NFT trading strategies into “macro” and “micro” camps. 

Macro factors include the performance of an entire NFT collection; the wider NFT market; and indeed the broader crypto market (after all, most NFTs are paid for in ether or some other cryptocurrency). Micro factors, which Rosenblum says are harder to fathom, relate to the specific NFT and the marketplace and blockchain it trades on, he says. 

The distinction may help explain why GSR is so interested in dealing in larger, more sophisticated NFT collections — of the kind produced by Art Blocks, the generative art platform. There are simply more signals of the “micro” variety for algorithms to feast on. 

The good doctor 

One enigma that GSR may look to for inspiration is the pseudonymous DrBurry. 

The good doctor is, according to collector Cozomo de’ Medici, “the most notorious” of the trading bots. 

Their profile picture on OpenSea is an android cartoon of Michael Burry, the hedge fund manager, portrayed by Christian Bale in the film The Big Short, who predicted the subprime mortgage crisis. A caption DrBurry's profile page reads, “Everything I do in investment is just very different.” 

Whoever is behind the account did not respond to The Block’s messages.

DrBurry has been similarly quiet on OpenSea of late, based on transaction records. But just three months ago, the account was making hundreds of simultaneous bids — of tens of thousands of dollars at a time — for items from collections including Cool Cats and Mutant Ape Yacht Club. 

It’s not clear why such frenzied activity died down, but a clue may lie in the doctor’s Twitter activity. They retweeted a post about “bid bots” being good for the market on December 7 — a response elicited by another tweet about OpenSea enforcing a new rule that means outstanding bids on the platform cannot exceed one hundred times a buyer’s available balance. 

A person with knowledge of the matter says that OpenSea has indeed placed different limits on bidding behavior that it considers abusive or spammy, although it’s not clear when these limits were enforced. The rules mean that once a buyer's bid has been accepted, all their other bids will be canceled unless they have enough funds in their wallet to cover the cost of those additional bids.

There is history here. The Defiant and others reported on suspicious activity surrounding OpenSea auctions in August 2021. The basic idea was that bots had been bidding below floor prices, then canceling accepted bids before the trade could be executed — with the aim of ultimately nabbing the piece for a lower price.

It’s hard to say definitively whether this tactic formed part of DrBurry’s approach, but it certainly seems to be one that has already found some success. 

DrBurry also seems to have fared well. A tweet posted in October last year by Shahzeb Z, a NFT data analyst, suggests the doctor had snagged 98 items from the famed Bored Ape Yacht Club collection for a “dirt-cheap” average price of 0.35 ether. Today, the minimum price of an ape is 82 ether (or around $260,000). 

Less fungible, less liquid

For all the hype around algo trading in NFT markets, though, not everyone thinks it works. Perhaps unsurprisingly, some of the big-name collectors are among the doubters. 

“NFTs are quite illiquid and individual,” says Pranksy. “I would say it's very hard to algo trade them.” 

Cozomo de’ Medici agrees: “I don’t believe it’s possible ser. Not enough liquidity.”

Of course, one of the very things that algo traders and market makers promise — indeed, their go-to counter in the face of criticism — is that they will bring liquidity to the sector. That remains to be seen, but it seems self-evident that with hundreds of thousands of new NFTs spawned every day, individual traders will not be able to sustain the market alone. 

But for Maxime Boonen, founder of the crypto market maker B2C2 and an avid collector of Rembrandts and Picassos, NFT markets are simply not suited to algo trading. 

“On the technical side, making markets in NFTs shouldn’t be different than it is for illiquid altcoins. But there is no reason for a single piece of art to have frequent buyers and sellers,” he says. “Paintings don't change hands every day. So the less fungible the asset, the less a liquid market can exist.” 

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