Can we disrupt Wall Street by remaking it? And can we remake it... out of Legos?
Consider this: two people who detest one another until their friends tell them they are the objects of the other’s love. Projecting amorous images of themselves through each other’s eyes, they realize they may love each other as well (if not simply this falsified idea of themselves). Soon they are a couple. We find ourselves in late 1598, in the plot of Shakespeare’s Much Ado About Nothing, which, like many Shakespeare comedies, might be subtitled The Joke is Real. People simply need to hear false stories about themselves in order to enact them—to turn fantasy into reality.
Now, consider that we’ve moved to 2014: your faintly blazed roommate, Jeff, is telling you how there are these two digital goods that all his guys are exchanging, and one is this coin for buying stuff on the darkweb, and the other is this enigmatic Shiba Inu that’s like the Mona Lisa of Dogs, but since they’re both actually just bits that don’t mean anything, maybe the bits could be programmed to be each other? Jeff finds this ontological conundrum extremely funny. If money is only real because we believe it’s real, then dude, how good would it be if we decided dogecoin were as real as any of the other social abstractions—money, political status, jokes—that orient our sense of self? Or rather: if mistaking money as real is what made it real, what better joke could there be than mistaking a joke as money?
In his haze, Jeff has unwittingly hit upon an incredible proposition: online, everything can become a currency. Neither digital bits nor money is “real” in a material sense, though that commonality is what allows them to be increasingly interchangeable as any digital good or service can be tokenized and exchanged. Both digital bits and money abstract our material world into informational data, but this data can be so powerful that it reorients and eventually replaces our relationship with material reality as well. Once we believe they’re real, they are.
As it turns out, the leap from 1598 to 2014 is not so far. Indeed, one favorite gambit in romantic comedies is the “bet”: Freddie Prinze Jr. takes a bet to date the nerdy girl, but in enacting the bet, the joke becomes real. In a way, Freddie Prinze Jr. is why I actually think Bitcoin’s success was fairly probable. A degenerate gambler in 2010 might have realized that a small bet on Bitcoin eventually becoming money would pay off tremendously if true, no matter the low odds. For that matter, the gambler would have had exactly one way of making that bet, by buying Bitcoin, thereby lending it legitimacy as money, raising the odds of the bet, and bringing more gamblers in. It was, perhaps, a fiction doomed to be real.
In any case, this is the first type of user-generated finance: user-generated legitimacy. User-generated legitimacy can turn anything into money with the firm insight that money always was, after all, a collective delusion.
On the internet, in other words, we decide what’s real.
It is now 2021, and we have indeed reached a vertiginous peak of user-generated content. Reader, it is this:
Over the past few weeks, I’ve tried to argue that user-generated content thrives best as user-aggregated content—that is, when consumers become creators by recontextualizing other users’ work as foundations for their own. Viral examples of this fan-fiction remixing include memes, subtweets, TikTok videos, and maybe most excitingly, Roblox. But note the benefits to the platforms. TikTok, Twitter, and Roblox are all metaverses in their way because they democratize the tools for developing their own platform and hand these over to users to build off each other’s work. Each user’s creation is another’s building block, and so the universe expands virally through users redeploying each other’s work in as lo-fi and relatable a way as possible.
In crypto, there’s a simpler term for this process: a hard fork. A group of users redeploy a pre-fab source code with a few tweaks of their own that change the function and purpose of the project; Ethereum, for example, has been hard-forked as both Ethereum Classic as well as the Binance Smart Chain. Hard forks, like memes or the TikTok video above, are a kind of parodic type of fan fiction in which one user’s project becomes another’s building block for very different aims.
Sure, you might say that there’s a major difference between user-generated content and user-generated finance here: UGC lets users expand a universe by building inside of it whereas UGF produces separate universes altogether. In fact, UGC also has its hard forks of favorite chains (witness the alternate storylines spun off from the TikTok chain above), just as UGF has its own legions of developers building off each other’s code to expand an underlying ecosystem.
But perhaps the bigger difference is that centralized media is not in competition with UGC whereas centralized finance is increasingly at odds with UGF. Netflix and Disney will continue commanding the capital, expertise, and labor-time to produce spectacles that awe with their artifice, precisely because they’re nothing we could see in our home lives; UGC will hopefully continue to pilfer these spectacles’ codes and cliches for videos like the one above. It is harder to imagine how legacy banks with their top-down structures and outdated office politics will continue to compete with the organic, rhizomatic growth of DeFi ecosystems. All else aside, democratizing creation accelerates creation; user-generated universes can grow much faster than their corporate counterparts.
Nevertheless, UGF, like UGC, is still figuring out how to monetize creators for their work within established ecosystems. Paradoxically, the fact that token prices go up when projects are good arguably makes it harder for users to be paid directly for their labor in UGF than UGC. It is one of a few reasons I’m personally excited by Radix, which not only will allow interoperability between different chains, but enable developers to receive rewards whenever another developer expands on their work and sells it. If it works, developers will be massively incentivized to create components that other devs can use with their own projects, not only accelerating development for individual projects but generating a large, open-source library of components for any project to build on—while proportionately compensating each party for their work.
So this is the second type of user-generated finance: user-aggregated finance, in which each developer’s creation is the next one’s canvas and even tool.
An honest question: could we crowdfund a museum? Masterworks lets us invest in pieces of individual artworks, but what if instead, we bought tokens in a gallery (online or physical), used the proceeds to hire curators and rent space and purchase works from emerging artists, and then got free admission as token-holders and some dividends from entrance fees and resales? Meanwhile, the tokens could be resold on DeFi marketplaces for different tiers of a subscription service: 5 tokens lets you enter, 50 tokens gives you an annual pass, 1000 tokens lets you join the curators’ council and attend bobo fundraisers at their inevitable roof-bar, etc. The economic logic is that of most museums with one key difference—any visitor becomes a patron, and any patron becomes a stakeholder. If the model doesn’t exactly solve the problems of casino capitalism (Basel-edition, much chic), it at least seems preferable to investing in art privately as a clueless individual and keeping works locked up from public view.
What about crowdfunding mortgages? As of this week, it’s being done.
And finally, what about crowdsourcing crowdfunding itself? One way to think about user-generated finance, of course, is as a kind of early-2010s crowdfunding, a la Kickstarter or Patreon, in which retail masses came together to give Bitcoin, altcoins, and shitcoins value (they were just ahead of the curve in earning financial value in return). So it’s no surprise that the strategies guiding retail investments would be crowdsourced as well. In this, they are just continuing to decentralize the position of traditional banks by decentralizing their investment strategies as well.
Except that the investment strategies appear to be very different from those used by legacy banks. Check out crypto Twitter—check out the popular accounts of Kaleo and Crypto Dog and Altcoin Psycho—and you find no discussion of finance-class models like Discounted Cash Flows or beta or WACC. You will instead tend to find one of two complementary strategies: Diamond-hands HODLing (let it compound for decades) and, more popular, Technical Analysis of candlestick charts (trade now). This latter graphing, with its immediately-legible visuals and intraday strategies, undoubtedly rewards traders with the adrenaline rush of impulsive game-playing far better than baroque DCF models ever could—as with most successful social media, Technical Analysis tends to take only a moment to understand and act on, even as it seems to contain proprietary wisdom that might have taken decades to reach.
What’s most fascinating about this open source chart-analysis, though, is less its short-term advice than its long-term implications: what if Twitter trading actually does offer better models than the Goldman and Morgan Stanley DCFs? After all, there are two reasons a DCF model would have made sense historically, and it’s not clear that either really holds in a retail market. First, DCF would have given a read on how much cash an owner of an organization would make through the organization’s life—a crucial metric for major stakeholders and a fairly meaningless one for retail investors who don’t expect for their investments to give them any cash flows beyond the occasional dividend. When retail runs the house, DCF starts to feel like a dress code for unruly markets, a suit-and-tie decorum that maintains order by doing things the way they were always done. This leads to the second reason for DCF’s success: like any financial strategy, it will work as long as everyone agrees it will work. And while this may be the bubble speaking, it’s not quite clear how well DCF works these days, either at modeling cash flows long-term or as an investment strategy.
After all, look at some of the most successful money managers of the best decade—those cabalistic hedge funders with their country club business models and proprietary methods that seem, on the surface, so opposed to recent retail moves. Even so, each could be seen as poking the gods of DCF. Perhaps no firm that offers such an indictment of traditional Wall Street Finance as Renaissance Technologies, probably the most successful hedge fund in the world, which refuses to hire anyone with a finance background and evidently makes algorithmic trades by finding correlations with unrelated data sets. It is not clear that they use DCF at all. Similarly, we might consider Ray Dalio’s Bridgewater, which largely focuses on macro development within government policy rather than microeconomic trends within firms (DCF plays a minor role in its research), or Ark Invest, which models cash flows by thinking qualitatively about the ways a company will pivot its model to embrace future trends. For that matter, Ark also open-sources its reports—a brilliant performative move that can influence retail investors in turn and increase the probability of its bets.
What is Crypto and Finance Twitter, then, if not a lo-fi, relatable version of Renaissance, Bridgewater, and Ark strategies broken down into a few colorful lines that let us get the gist of the bigger picture?
This, then, is the third type of user-generated finance: decentralized finance, disintermediating legacy financial institutions by putting their tools into the hands of the retail crowds.
This piece is intended as a kind of hard fork of last month’s User-Generated Finance—taking the same premise, running in a different direction from the type of UGF discussed there (synthetic equity). Special thanks to James Wang for inspiring this piece.