EXPERIMENT / RESEARCH NOTES

Can an LLM Design a Crypto Factor Strategy in One Shot?

I asked four language models to independently design a cross-sectional strategy for crypto perpetual futures. Each received the same prompt and one response, with no follow-up or parameter search. I translated the answers into frozen, auditable Event strategies and tested them on the same history with identical costs.

The question is not who writes the most convincing strategy memo. It is whether a one-shot specification survives point-in-time data, trading costs, funding, missing observations, execution timing, and path-dependent risk rules.

A fair one-shot contract

Evaluation interval (UTC, end exclusive; plus terminal liquidation)
→
Initial equity
100,000 USDT
Friction per traded notional
5 bp taker fee + 2 bp slippage
  • Same causal universe and point-in-time data.
  • Completed observations only; scheduled fills no earlier than the next minute.
  • One response per model; no clarification, follow-up, or parameter search.
  • Ambiguities resolved mechanically before accessing results, retained as model defects.
  • Each run has an immutable identity tied to source, dataset, and response hashes.

What the models proposed

ChatGPT 6 Astra Ultra

Buffered relative momentum

Daily momentum skips the most recent day and normalizes by volatility. Balanced long/short selection uses entry and retention buffers to reduce replacement; the Event implementation handles stale prices and exposure drift.

Grok 4.7 XHigh

Residual momentum & carry

A daily blend of market-residual momentum and funding carry, with buffered long/short selection and a minute-level exposure enforcer. Its proposed exposure conflicted with the common contract and was mechanically overridden.

Kimi K3 Max

Carry, momentum & reversal

An intraday blend of recent funding carry, medium-horizon momentum and short-term reversal. A portfolio drawdown threshold triggers lower risk.

Claude Fable 5.1 Max

Trailing funding carry reversal

An hourly strategy using trailing funding, inverse-volatility weights and rank holding bands. Cooldowns, drift controls and rapid exits respond to sharp contract moves relative to the market.

Results under the frozen rule

Ranking is preserved: positive total return first, then after-cost Sharpe, Calmar, lower drawdown, and lower turnover. Kimi ranks ahead of Claude under this rule despite its larger loss. A positive Sharpe does not make Grok profitable.

Results under the frozen rule·llm-cs-202509-202608-v1
RankOwner-supplied model labelTotal returnSharpeMax drawdownTurnoverTrades
1ChatGPT 6 Astra Ultra+42.32%1.04-24.67%196.1×24,058
2Grok 4.7 XHigh-3.91%0.16-43.88%270.0×32,200
3Kimi K3 Max-47.06%-1.55-53.15%535.5×53,600
4Claude Fable 5.1 Max-38.69%-1.76-49.03%538.5×115,847

Display precision follows the supplied comparison: percentages and Sharpe to two decimals, turnover to one decimal. Exact source values are retained in the JSON.

The path matters

Daily ending equity in USDT, shared axes for all strategiesDaily ending equity as supplied, with the terminal liquidation point included. Line styles and labels distinguish models without relying on color. ChatGPT 6 Astra Ultra: 142318.68875386892 USDT; Grok 4.7 XHigh: 96088.09532322202 USDT; Kimi K3 Max: 52944.25200357327 USDT; Claude Fable 5.1 Max: 61307.97882318065 USDT50420.71100000181366.122025-09-012026-09-01
  • ChatGPT 6 Astra Ultra
  • Grok 4.7 XHigh
  • Kimi K3 Max
  • Claude Fable 5.1 Max
Daily ending equity as supplied, with the terminal liquidation point included. Line styles and labels distinguish models without relying on color.
Inspect exact daily equity values
Daily ending equity in USDT, shared axes for all strategies
Date (UTC)ChatGPT 6 Astra UltraGrok 4.7 XHighKimi K3 MaxClaude Fable 5.1 Max
2025-09-0199304.41343293886100907.4343465361299209.0906232149498904.07702127169
2025-09-0299199.4301717764898898.6957249066298648.1217249265297930.99586999131
2025-09-03100699.4296701650998419.5326288432102647.3952555272398727.96495722294
2025-09-04101405.0879230650599541.63751955635102147.3603715930498370.16814848065
2025-09-05101224.89030399268100469.89570417494105287.1262346904798415.7890819142
2025-09-06102708.5686797945299489.1332235838106146.9992117123297931.56073192251
2025-09-07100644.3285976744892559.88282160525103461.1945356614396777.40422254088
2025-09-0897999.861605740283056.45899659286103467.901932124394686.12465557683
2025-09-0999415.4417697209483478.3843272908102184.3639922370293904.44333730404
2025-09-1092164.3929194243176823.8073703099489551.1814374903893014.66960587975
2025-09-1191529.1734064031977477.0941147675888707.665638701893566.76600474086
2025-09-1292232.9543454012665639.123990871581645.8127649396692875.8528791554
2025-09-1392342.9671464343768089.1141407789880805.2324240545992499.97770101004
2025-09-1493674.4031571085269342.3479488212582345.9344040872793553.17231509426
2025-09-1593611.4916931193971082.6538617545483066.9476527710495057.12942186752
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2026-08-27143043.8489090209598226.8375539236154716.3518008387260670.992174798244
2026-08-28141815.7557168718292636.4381087956652670.8773190296160933.808157167325
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2026-09-01142318.6887538689296088.0953232220252944.2520035732761307.97882318065

Monthly consistency

Monthly consistency
MonthChatGPT 6 Astra UltraGrok 4.7 XHighKimi K3 MaxClaude Fable 5.1 Max
2025-09-0.63%-14.31%-15.36%+1.70%
2025-10+15.82%+3.88%+2.35%-3.44%
2025-11-10.02%+1.69%-4.10%-3.97%
2025-12+7.56%+7.75%+3.02%-9.53%
2026-01-1.81%+26.14%+9.84%+4.86%
2026-02+8.76%+0.31%+0.44%-9.22%
2026-03+5.80%-1.62%-9.84%+3.92%
2026-04+12.67%+14.17%-8.88%-15.60%
2026-05+0.27%-2.29%-12.77%-15.19%
2026-06+14.96%-11.88%-20.53%+2.22%
2026-07-4.41%-18.44%-5.25%-3.02%
2026-08-8.84%-1.20%+3.95%+2.45%
Positive full months7/126/125/125/12

Terminal liquidation period — excluded from full-month consistency (2026-09): ChatGPT 6 Astra Ultra: -0.08%Grok 4.7 XHigh: -0.08%Kimi K3 Max: -0.04%Claude Fable 5.1 Max: -0.08%

What I learned

A plausible factor story is not enough

Most proposals lost money after costs. Clock consistency, turnover control, missing-data behavior and implementable risk rules mattered alongside factor choice.

Funding was a first-order return source

Every strategy received positive funding cashflows. The winning result was not pure price momentum. Grok also received substantial funding, but adverse price returns and costs absorbed that advantage.

Turnover separated the strategies

Repeated replacement consumed capital through fees and slippage. Read the observed cashflows below alongside cumulative turnover, rather than treating trading frequency as a reporting footnote.

Specification quality is part of model quality

Contradictory clocks, incomplete fallbacks and infeasible constraints were resolved by the narrowest deterministic interpretation. No model benefited from a second attempt.

Observed cashflows (USDT), not a reconstructed return attribution
ModelFunding receivedFees paidSlippage paid
ChatGPT 6 Astra Ultra46,716.7012,273.724,909.49
Grok 4.7 XHigh100,113.6814,532.975,813.19
Kimi K3 Max64,994.5220,980.828,392.33
Claude Fable 5.1 Max81,641.7121,065.728,426.29

Audit & limitations

This benchmark covers owner-selected model labels, one prompt, one historical period, and public Binance USD-M perpetual-futures data. It does not test live fills, liquidation tiers, order-book queueing or strategy discovery across repeated prompts. Complete historical exchange-status snapshots are not available for every timestamp; eligibility inferred from observed bars, history boundaries and trailing liquidity retains this limitation. Model and effort names are supplied by the experiment owner, not claims about current product availability. BFBT is independent and has no Binance affiliation. Historical backtest evidence only; not investment advice.

Benchmark
llm-cs-202509-202608-v1
Frozen source commit
2b1ca8f6826866fcf70e1cc39fefae4c8a668c7f
DatasetSnapshot SHA-256
a49846e623dee5ef16cebe28a48a12e384c07582237a782eeef311208ab75e96
Run identities
  • ChatGPT 6 Astra Ultra
    evt-a01175782a0fa6997144d0da
  • Grok 4.7 XHigh
    evt-c7bdf2892da257893f46be6c
  • Kimi K3 Max
    evt-498d8f170a3ee9272dbbb66c
  • Claude Fable 5.1 Max
    evt-ed4f9aeb18febee2690b12d4

Read the evidence

Start with the unified comparison. Full Event reports provide equity paths, trades, rankings, instructions and risk events; they open only when requested.

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