CME Group signage above the former Chicago Board of Trade (CBOT) trading pit in Chicago, Illinois, USA, on Thursday, November 13, 2025.
Christopher Dilts | Bloomberg | Getty Images
A new semiconductor futures market will allow traders to hedge their investments in artificial intelligence by betting on the increasingly expensive prices of computing power.
Contracts on CME Group’s new “compute futures market” will be based on Silicon Data graphics processing unit (GPU) price indices, the companies said in a statement released Tuesday announcing the joint venture, which is pending regulatory review.
The new market will allow investors to set a price for computing capacity based on a GPU benchmark, which can be used to hedge against increasing GPU rental prices and other operating costs in the vast and multifaceted AI expansion.
“GPU markets … have historically lacked standardized reference pricing,” Carmen Li, managing director of Silicon Data, said in the press release. “The launch of Compute Futures is an important step in providing AI developers, cloud providers and investors with more reliable tools for valuation, assurance and long-term planning.”
Futures markets have traditionally been associated with basic commodities such as food, metals and petroleum products, but they have also emerged for assembled components in rapidly developing segments of advanced industrial sectors.
During the broadband explosion of the late 1990s, Enron’s broadband services division aimed to sell unused capacity in its fiber optic cable network before the company failed spectacularly.
Silicon Data sells clients access to special price indexes, similar to the Consumer Price Index or Personal Consumption Expenditure Price Index, with the exception of semiconductors. Its products include a standardized GPU price index, a RAM index, and GPU rental price forecasts.
Wall Street doesn’t expect demand for GPUs or more traditional central processing units (CPUs) to slow down any time soon.
“Agent AI requires entirely new racks of CPU servers sitting and running alongside GPU infrastructure to drive the work of all those agents,” Morgan Stanley analyst Shawn Kim wrote in a report Monday.
“The AI system of the future will look like a distributed system consisting of GPU racks for dense model computation… [and] “Agent CPU racks for orchestration, data processing and tool execution,” Kim said.
Memory chip prices jumped in the first quarter as AI drove demand for CPUs. Hyperscalers increased capital spending across the board while executives expressed concerns about a storage shortage driving up input costs.
Memory chip makers are expecting huge profit margins this year and next as valuations have skyrocketed.
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