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Don Wilson rejects the idea that futures simply let firms borrow more against the same risk. He says every contract needs a rational buyer, and heavy hedging by compute sellers should push forward prices lower, forcing investors to buy them only if they expect a return.
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Don Wilson says a neocloud selling to less creditworthy customers faces a higher cost of capital. Once GPU futures exist, it can buy chips, sell a strip of futures, and still sell on-demand or short contracts with collateral. He calls this a giant basis trade that markets should reward with cheaper funding.
Goldman Sachs and JPMorgan are exploring the creation of futures contracts based on the hourly rental cost of a GPU. This move would transform scarce computing power into a tradable commodity, similar to oil or corn, allowing companies to hedge against price volatility. It marks a significant step in the financialization of the AI industry's core resource.
Previous attempts at tech futures like DRAM failed because prices only moved in one predictable direction: down. In contrast, the market for GPU compute will experience cycles of high demand and excess supply. This two-way volatility creates genuine hedging needs, making a futures market viable and necessary.
Don Wilson says the trillion-dollar question is what a B200 will be worth four or five years out. H100 on-demand prices fell for months, then rose after Anthropic's new model boosted inference demand, while token prices moved differently. That volatility is why he argues forward contracts are badly needed.
Don Wilson says chip and configuration differences can be handled by correlated benchmark contracts and basis trading. He expects futures on token output eventually, letting operators hedge the margin between renting GPUs and selling open-source model tokens, analogous to oil's crack spread. DRW calls it the crunch spread.
The massive global investment required for AI will drive demand for GPUs so high that the annual market spend will exceed that of crude oil. This scale necessitates a dedicated futures market to allow participants, especially new cloud providers, to hedge price risk and lower their cost of capital.
The economic roles in the emerging compute futures market directly parallel the oil market. Compute providers ('NeoClouds') are like oil producers (Shell), needing to hedge revenue volatility. AI companies and other users are like airlines, needing to hedge cost volatility. This classic structure is essential for building a liquid, functional derivatives market.
Despite narratives of prices only going up or down, the normalized daily price movement of A100 and H100 chips is 20-30%. This is considered a healthy volatility range for a commodity, creating a genuine need for hedging instruments. If prices were stable, there would be no risk to manage and thus no functional futures market.
Instead of speculating on abstract market valuations, a practical way to assess the 'AI bubble' is at the asset level. For a GPU, one can analyze its forward contracts to project future cash flows. If the discounted value of this cash flow exceeds the purchase price, the investment is sound, regardless of broader market sentiment.
The CME is creating futures contracts based on H100 and B200 GPU rental price indices. This marks the financialization of compute, allowing providers to hedge revenue and enterprises to lock in future costs, with a long-term vision for physical delivery of compute capacity.
