A simple average of GPU prices is useless because 'two H100s' can have different CPUs, RAM, and locations. A valid index requires ingesting thousands of daily prices and normalizing them against a base case, using a model that identifies key price-driving factors. This is crucial for creating a reliable hedging instrument.

The potential for a futures market in any asset, from onions to AI compute, depends on two factors. The product must be homogenous enough to standardize into a contract, and its price must be volatile enough to create demand for hedging from both producers and consumers.

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.

According to BlackRock's CEO, AI compute is poised to become a new asset class, similar to oil or corn. Due to its scarcity, standardization, and price volatility, it's likely that futures markets will emerge, allowing companies to trade and hedge compute resources.

While futures contracts for GPU compute will allow companies to hedge costs, they also introduce systemic financial risks into the AI ecosystem. The inability to predict who holds the ultimate risk and the potential for counterparty default could create new, complex vulnerabilities, mirroring challenges seen in the maturation of other financial markets.

The head of AI at Hudson River Trading highlights a practical barrier to creating a financial market for compute. For serious training, the minimum "lot size" is thousands of GPUs, not a small, fungible unit. This makes it difficult to standardize a contract and create liquidity, unlike commodities with smaller, interchangeable units.

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.