By no means am I an expert in compute markets, but was inspired to develop a take by both Brett and
@0xfishylosopher
Compute keeps getting scored against the commodity formation checklist and keeps failing the same two boxes, standardized delivery and time plus location pricing. Fair enough as history.
Grain, oil and electricity all needed those things because their markets terminated in a dated futures contract, and a dated contract has to bridge into the physical world somehow.
But new markets stopped terminating there. Perps collapsed the term structure into a funding rate and swapped the delivery bridge for an oracle print.
Hyperliquid became the deepest novel derivatives venue of the cycle on underlyings it never delivers.
AX clears over a billion a month in perps on traditional assets and already lists GPU-hour contracts. The catch is that the perp stuffs the whole thing into the benchmark. A funding rate needs an anchor, and for compute the anchor is the entire fight.
Compute varies by SKU, location, tenor and counterparty. No index can carry all four, so every index picks what to keep and drops the rest.
The three racing to list made three different cuts: on-demand rental rates, printed transactions only, energy normalized. One of these is the LIBOR to SOFR argument, real prints over posted quotes, being made at the birth of a benchmark instead of after a scandal.
Whatever an index drops has to go somewhere, and it goes onto dealer balance sheets. Which is why this market is forming dealer first, exchange second. The cleared contract ends up as the hedge leg for the OTC book, and price discovery moves into the spread between indices. Oil did this with WTI-Brent, gas did it with JKM-TTF. When no benchmark is complete, the basis between imperfect ones carries the information. That still leaves the part neither a funding rate nor a basis trade can touch: jumps.
An export control ruling, a Rubin slip, an interconnection queue decision, a hyperscaler capex cut. The whole surface moves at once and resolves as an event, not drift.
The instrument for that slice is a binary, and the first compute price markets settling on printed transaction data went live in May on
@Kalshi.
For a dealer warehousing SKU basis that’s the right shape, you lay off the timing and keep the size. Perp for the level, index menu for the shape, dealers for the residual, binaries for the jumps. All four layers are live today.
Historical path-dependencies may not be a precise source of truth here.
US Compute Futures As Hedges
Compute futures face the argument that if a future doesn’t track the exact costs hedgers incur, it will carry too much basis risk to form a viable market. This fundamentally misrepresents how hedges actually function in many major US markets.
A hedge does not need to be perfect in order to be useful, let alone transformative, to its underlying commodity market. To be viable as a multi-billion dollar market, a hedging instrument needs to remove enough risk at scale to be worth its initial cost. If the correlation between a hedging instrument and the portfolio is ρ and the optimal hedge ratio is used, the fraction of variance eliminated by the hedge is ρ². A correlation of only 0.7 cuts variance in half.
Cross-hedges built on loose relationships predominate in the real US economy. Airlines hedge jet fuel with crude. Bond desks hedge rate risk in credit with treasuries. Long-short equity portfolios hedge market beta with S&P 500 futures. At my former firms Jane Street and Citadel Securities, every trading desk was required to hedge portfolio factors with related instruments intraday and overnight to isolate alpha.
Commodity markets are typically heterogeneous. Compute is not a unique underlying in this respect. An “H100 hour” could represent many different goods: SXM or PCIe, spot or reserved, hyperscaler or neocloud, US or Asia. Weigh this “problem” against the “solution” that compute buyers and sellers have today: nothing. Asset-backed loans on GPUs carry 40-50% haircuts because lenders can’t transfer the associated risks. The institutions financing the >$1T datacenter-linked debt sector regularly transact in other heterogeneous commodity markets.
The success of US compute futures/options markets primarily depends on CFTC-regulated exchanges’ agility and competency at collaborating with index providers native to chip configurations, neocloud procurement, and timeseries interpolation on a continuous basis. Designing a futures contract that minimizes basis risk and maximizes liquidity formation is an antecedent requirement. Fulfilling the US government mandate to “accelerate the maturation of a healthy financial market for compute” is the main goal.
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