Cboe Is Bringing Prediction Markets to Company Earnings
Cboe is expanding further into prediction markets, with plans for exchange-traded contracts that could allow traders to predict specific company results such as revenue, earnings and individual business KPIs.
I was recently at a Cboe presentation to professional investors where the exchange outlined how it is developing binary contracts based on company earnings data.
Rather than trading whether a share price will rise or fall after results, traders could take a position on a much more specific question: will a company report a particular financial metric above or below a set level?
The Cboe explained:
“The question is far more precise.”
One example given was whether Meta’s revenue would exceed a specified figure.
Cboe also highlighted the potential for contracts based on company-specific measures such as Amazon AWS revenue, Tesla Model Y sales and Apple iPhone sales.
How would Cboe’s prediction markets work?
The structure is deliberately simple.
A trader would effectively answer yes or no to a particular outcome. If correct, the contract pays $1; if not, it pays nothing.
The Cboe described the concept as a:
“Very simple, basically yes, no outcome.”
Importantly, the proposed company contracts would settle using figures from the company’s official earnings release.
That removes some of the ambiguity that can exist with prediction markets where a third party has to determine whether an event has actually occurred.
Prediction markets meet traditional financial markets
Cboe already offers S&P 500 prediction contracts based on XSP, its Mini-SPX Index.
These provide a binary outcome based on whether the index reaches a specified level and include zero-days-to-expiry contracts.
Cboe’s next step is potentially more interesting because it applies prediction markets directly to company fundamentals.
Instead of asking whether Apple shares will rise following results, for example, a trader could potentially take a direct position on the number of iPhones Apple sells.
Likewise, an investor who thinks Amazon’s cloud business is performing better than expected could express that view through an AWS revenue contract rather than buying Amazon shares or options.
Why Cboe’s approach is different
One of the biggest questions surrounding prediction markets is how they fit within existing financial and gambling regulation.
Cboe is approaching the sector through traditional financial-market infrastructure.
Speaking about its existing product, the presenter emphasised:
“It is traded on a regulated exchange. It is cleared by a regulated clearing house.”
The contracts also have clearly defined settlement criteria rather than relying on subjective outcomes.
Cboe said the new company KPI contracts were still being finalised from a regulatory perspective at the time of the presentation, describing their arrival as “imminent”.
If they launch as planned, they could represent an important development in the rapidly growing prediction-market sector.
Prediction markets have traditionally concentrated on outcomes such as elections, economic events and sporting results.
Cboe is effectively applying the same idea to one of Wall Street’s oldest activities: predicting company earnings.
Richard is the founder of the Good Money Guide (formerly Good Broker Guide), one of the original investment comparison sites established in 2015. With a career spanning two decades as a broker, he brings extensive expertise and knowledge to the financial landscape.
Having worked as a broker at Investors Intelligence and a multi-asset derivatives broker at MF Global (Man Financial), Richard has acquired substantial experience in the industry. His career began as a private client stockbroker at Walker Crips and Phillip Securities (now King and Shaxson), following internships on the NYMEX oil trading floor in New York and London IPE in 2001 and 2000.
Richard’s contributions and expertise have been recognized by respected publications such as The Sunday Times, BusinessInsider, Yahoo Finance, BusinessNews.org.uk, Master Investor, Wealth Briefing, iNews, and The FT, among many others.
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