Hedging computing power like hedging crude oil? The world's first AI computing futures contract is about to emerge.

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Startup company Silicon Data, in partnership with CME Group, is seeking to turn GPU computing power into a tradable standardized commodity, creating the world's first AI computing power futures market.

Wallstreetcn reports that on May 12, CME and Silicon Data launched computing power futures, aiming to provide AI developers and financial institutions with tools to hedge against fluctuations in computing power prices. The product will be priced based on a GPU benchmark index compiled by Silicon Data and is currently awaiting regulatory approval.

Within days of Silicon Data and CME Group announcing their partnership, asset management companies such as ProShares and Rex Shares submitted ETF applications linked to the proposed contracts, including leveraged and inverse products.

Silicon Data's founder and CEO Carmen Li predicts that as AI energy consumption eventually surpasses all other uses combined, the computing power futures market "will surpass" the oil futures market in scale. Whether this vision can be realized depends primarily on the attitude of regulatory agencies.

The U.S. Commodity Futures Trading Commission (CFTC) will strictly scrutinize core issues such as the standardization of computing power, contract specifications, and the construction of benchmark prices. Seoyoung Kim, a finance professor at Santa Clara University, notes:

The CFTC will want to clearly understand what the product actually is.

A computing power version of the jet fuel logic

The idea stems from an intuitive analogy: AI companies' dependence on computing power is much like airlines' dependence on jet fuel.

Currently, most companies do not own high-end GPUs required to run AI systems, but instead rent them on demand from cloud service providers and emerging "neocloud" platforms.

With surging demand for AI infrastructure, the cost of renting computing power is fluctuating more sharply, making it harder for companies to forecast expenses effectively. Seoyoung Kim, finance professor at Santa Clara University, said:

We are currently in a period of high uncertainty. Many companies don't know how much computing power they will need next year, suppliers don't know how many GPUs to order, and even manufacturers like Nvidia aren't sure how much to produce.

It is in this context that Silicon Data hopes to use futures contracts to hedge and manage computing power cost risks, just as airlines hedge fuel costs and farmers hedge agricultural prices.

As with all futures markets, computing power contracts will attract not only enterprise users seeking to lock in costs, but also speculators—traders who have opinions on computing power price trends but do not themselves need GPUs.

Supporters argue that speculators play an important role in enhancing market liquidity and improving price discovery, while critics worry that speculation may exaggerate price swings and detach prices from actual supply and demand fundamentals.

Silicon Data’s founder and CEO Carmen Li is open-minded about this:

Speculators are a vital part of the ecosystem. You need natural hedgers, market makers, and speculators. They have their market views and want to express them, and that's perfectly reasonable.

Benchmark Index: Standardization is the key challenge

The prerequisite for the futures market's operation is a credible, unified benchmark price.

Silicon Data has built a GPU price index system that tracks the hourly rental prices of specific chips from different service providers, aiming to replicate the West Texas Intermediate (WTI) crude oil's benchmark status in the energy derivatives market.

However, standardizing computing power is far more complex than oil. According to Silicon Data, there are more than 50 different configurations of just the Nvidia H100 chip alone, and prices vary significantly depending on processor, memory, network bandwidth, utilization rate, and data center location.

Carmen Li says:

We normalize the prices that enter the platform each day to a standard H100 base configuration. This is a very complex normalization step that needs to happen even before the index calculation itself.

Seoyoung Kim points out that standardization is a common challenge faced by all futures markets. Corn futures contracts specify deliverable grades; the computing power market likewise must precisely define the traded subject.

The U.S. Commodity Futures Trading Commission (CFTC) will comprehensively review contract specifications, settlement procedures, and the methodology for building benchmark indexes—crucial thresholds for the contract's eventual launch.

Silicon Data's benchmark data is already being included in important company documents. SpaceX has cited the company's GPU rental price data in its IPO prospectus, lending credibility to the data’s standing in the industry.

Risk Disclosure and DisclaimerThe market is risky, investment requires caution. This article does not constitute personal investment advice and has not taken into account the specific investment objectives, financial situation, or needs of individual users. Users should consider whether any opinions, views, or conclusions in this article are suitable for their particular circumstances. Investing based on this article is at your own risk. ```