Gamified Crypto Trading Can Bring Promise of Prediction Markets to Masses

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In Brief
  • Using real money is lucrative, but the barriers for end-users remain significant.

  • Public prediction markets have taken on a cyclical hype cycle.

  • A truly simplified model gives prediction markets the capacity to become mainstream.

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Typically every two years markets get attention as the media looks to them for insights in United States election cycles, after which volume drops precipitously and mention of their prices vanish from the mainstream press.



As someone who has worked with prediction markets for past 15 years, deploying them for government agencies and some of the largest corporations in the world, I’ve looked on with amusement as interest in external, public prediction markets have taken on a cyclical hype cycle.

But starting five years ago, a new interest emerged in the crypto space, independent from any election cycle.



While founders claimed noble intentions of new governance models and decentralized input in to decision making, many were simply excited about shirking US gambling and securities law, and finally having access to highly liquid, global prediction markets that did not have the same limitations as centralized, regulated markets like PredictIt, and its predecessor, InTrade.

Building an effective prediction market 

Starting with Augur and followed by Gnosis, it seemed every week someone was launching a market as a use case for their token. Unfortunately, after a lot of hype, none of those markets gained much traction, and most projects have already died.

Now, a new generation of entrants are trying their luck, and a few old hands soldier on with v2’s. Poly.market, for example, has claimed they have “solved” prediction markets, and just like the prediction markets of yore, saw increased volume with the 2020 presidential election. 

While I’d love for all of these efforts to succeed, I’m concerned they will, for the foreseeable future — over three to five years — remain a highly niche interest. It has not been proven that a general-topic prediction market can gain significant traction, and who is to say crypto markets will be any different?

Using real money is lucrative, but the barriers for end-users remain significant: the hassle of funding a wallet, understanding the market mechanism and payout scheme, finding a topic of interest, ensuring you’re not breaking federal, state, or local law by participating, among others.

Building an effective prediction market is extremely difficult, and even if these issues are solved for, there is little evidence real money markets outperform other non-market mechanisms like opinion polls used by the Good Judgment Open, or even play money markets at Metaculus.

So we’re left watching all these prediction market efforts and wondering: are they fighting the right fight?

Taking new approaches to trading

Meanwhile, in the world of crypto trading, there are a small number of platforms who are trying to take a new approach to trading by abstracting the trading experience using simple, lucrative, game mechanics, opening the door to non-traders, much the same way eTrade, Ameritrade, and others brought casual stock trading to the consumer 25 years ago through a simplified web-based experience.

I bring this up because the market for trading currency, commodities, or equities is proven and massive, which is the main problem every prediction market platform is trying to solve. It’s the classic chicken or egg problem.

And that’s what’s so fascinating, and potentially lucrative. If a tool like Hxro, a gamified crypto trading platform, is successful at creating a lucrative product that can attract a large, global pool of users (see Hxro’s TixWix market), are they a backdoor to the kinds of information markets the existing prediction markets are so desperately trying to get off the ground? 

I recently tried a beta, play money version of TixWix, where you make predictions on whether BTC or ETH will hit a certain price within a given time frame. I was struck by the simplicity of the application — and how addictive it was, staring at the second by second changes in BTC price, as I tried to will it to hit the price I had predicted.

I contrasted this to prediction markets I’ve designed over the years, where no matter how much you abstract the market mechanism, you’re still leaving the user with a complex task that is a high cognitive load: decide what my belief is or what I think the crowd’s belief is, then decide the strength and confidence in my belief, then decide how much money I want to spend to reflect that belief. 

Making it “fun”

A truly simplified model gives prediction markets the capacity to become mainstream. What prevents simply changing the question being asked from “Will BTC hit X by Y time period” to “Will the Bears score at least 24 points by halftime?,” “Will confirmed Covid-19 cases reach 1M by X date?,” “Will AAPL hit $X/share by X date?,” or “Will Justin Bieber’s new single hit 100M views on Youtube?”

Like a prediction market, people will be expressing their beliefs and quantifying their judgments, just in a different way. 

Business orthodoxy says find a large addressable market and make something they want. The population of casual traders around the globe — not institutional — is in the hundreds of millions.

The population of gamers around the world is undoubtedly equally massive. It’s not surprising then that someone is simply going to a time-tested product development playbook by trying to marry the two and making trading “fun.”

Perhaps at the end of the day, it won’t be decentralization, new governance models, and oracles that finally bring the promise of information markets to widespread fruition, it will be a game.

Disclaimer

All the information contained on our website is published in good faith and for general information purposes only. Any action the reader takes upon the information found on our website is strictly at their own risk.
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Adam is the CEO of Cultivate Labs, a company that leverages prediction markets to help business leaders make informed decisions.

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