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whalehunter-strategy

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Updated 10-16 08:46

About this skill

🐋 WHALEHUNTERHEDGE v2.0 — Smart-Money-vs-Crowd Divergence (long/short)

Position with the smartest money, against the crowd. WhaleHunterHedge measures what the cohort with the largest lifetime realized gains is actually doing — net long or net short, per asset, and whether they're adding — and fires when the smart money diverges hard from the crowd. The signal it's built to catch:

This week the most profitable wallets on Hyperliquid went heavily short while the crowd piled into longs — and the winners added to that short every single day. That's the setup: smart money net-short + adding, crowd net-long → short it with them.

Sleeve What it positions Direction Wallet
long assets the smart cohort is net-long + adding LONG only one
short assets the smart cohort is net-short + adding SHORT only one

Two wallets, fully independent — so the book can hold conflicting positions on the same asset (smart money net-long ETH while net-short HYPE → long sleeve holds ETH, short sleeve holds HYPE, no netting). Funding default 50/50 — no built-in directional bias.

Why cohort divergence is the edge

A single whale's trade is noise. The weight of the entire >$1M-realized cohort is signal — it's the closest thing Hyperliquid has to a "commitment of the smartest traders." When that cohort is lopsided on an asset and growing the position day over day, while the crowd (the $10k–$100k wallets that are net buyers of every rally) is on the other side, you have a positioning divergence — the most durable read in the market. You're not chasing one bet; you're standing where the people who've actually made money are standing, and fading the people who haven't. Because it's a positioning signal (not a momentum one), a wide DSL fits: you hold while the smart cohort holds.

The engine — four steps, all from Senpi Discover

  1. Cohorts by lifetime realized gains. The ALL-TIME realized-PnL ranking, paged by offset, bucketed by $: smart = ≥ smartMinRealizedUsd ($1M), crowd = crowdMinRealizedUsd..crowdMaxRealizedUsd ($10k–$100k). Paging matters: the ranking is realized-descending, so the smart cohort sits at the top but the crowd lives thousands of ranks deeper — a single top-N pull catches only a weak tail of the crowd (the inverted "crowd ≪ smart" symptom). The walk pages down (cohortMaxPages) until the crowd is representatively sampled or the ranking drops below the crowd floor, capping each cohort (cohortSampleCap) to bound per-tick load. Membership cached daily.
  2. Net positioning per cohort, per asset. discovery_get_trader_state across each cohort → sum signed notional per coin → bias = net / gross in [-1,+1] (+1 = all long, -1 = all short), plus member counts.
  3. The "adding daily" trend. A daily cohort ledger snapshots the smart cohort's net per coin; today's net minus the earliest snapshot in the window = growth. The smart cohort must be growing its position in the signal direction (requireGrowing).
  4. The divergence strike. For this sleeve's direction: the smart cohort is net-directional past biasThreshold (default 0.50) and growing, scored higher when the bias is strong (≥0.7), when it's adding, and when the crowd diverges (net-opposite by ≥crowdDivergenceMin). Score ≥ cohortMinScore emits.

~1-day warmup: the growth gate needs ≥2 daily ledger snapshots, so a fresh deploy emits no divergence strikes on day 1 — it's building the baseline. This is by design.

Mirror + ride + surface

  • Size to YOUR budget, score-scaled — margin = equity × marginPct, scaled up +25% per point above the score floor, capped at maxMarginPct. No hardcoded $.
  • Leverage capped — conviction shows in size, not leverage (clamp to maxLeverage then venue max).
  • Surfaces the insight — every tick the producer emits a human-readable insight line per top divergence ("HYPE: smart -0.85 vs crowd +0.65, Δ-$2.1M → SHORT"), so the agent can report what the smart money is doing, not just trade it.
  • Wide DSL — wide disaster stop, weak_peak OFF, time-cuts OFF, Phase 2 does nothing until a big run. Ride the divergence. Planned invalidation exit: close when the smart cohort flips or unwinds (the mirror of the entry).

Deploy — two wallets

WHALEHUNTER_LEG=long   WHALEHUNTER_LONG_WALLET=<wallet A>
WHALEHUNTER_LEG=short  WHALEHUNTER_SHORT_WALLET=<wallet B>

Fund 50/50 for a balanced smart-money long/short book. Requires a USER-scoped SENPI_AUTH_TOKEN — the discovery_* tools need a valid user id (no user scope → the smart cohort comes back empty and the producer reports "cohort too small").

Fleet-standard rules (enforced)

  • Max leverage 5x (clamp + venue). Score-scaled margin (no hardcoded $); per-position cap maxMarginPct; up to maxSlots (6) per sleeve.
  • Drawdown halt 25%, baseline-seed guard, per-asset cooldown. daily_loss_limit_pct disabled on multi-wallet funds (perpDay base reads ~$0 → $0 limit; DSL + drawdown_halt protect).
  • Mandatory DSL; entries + exits FEE_OPTIMIZED_LIMIT with taker fallback (a confirmed divergence must fill).
  • Sizes off max(main, xyz) account value — never the sum (cross-margin).
  • Signature-adaptive daemon launch; per-(leg,wallet) lock; daily-cached cohorts + daily ledger.

Hard rule — user-conversation sessions are READ-ONLY

A Claude session conversing with a user MUST NOT call create_position, close_position, edit_position, ratchet_stop_*, cancel_order, or any strategy_close* tool against WhaleHunter's wallets. Entries are emitted only by the producer daemons; exits are owned only by the runtime DSL.

Versions

  • v2.0 (current) — the cohort-divergence engine. Pivots from per-whale copying to measuring the NET positioning of the >$1M-realized cohort vs the $10k–$100k crowd, per asset, with an "adding daily" growth gate and a crowd-divergence booster — and surfacing it as a readable insight. Positions WITH the smart money against the crowd. The v1.x per-whale conviction copier is retained behind enableIndividualCopy (OFF by default).
  • v1.2 — activity tune + near-miss observability for the per-whale copier (convictionPct 0.25→0.18, poolSize 30→50) after it sat 0 trades in 3 days (patient whales rarely open a ≥25%-of-book new position — the rarity that v2.0's cohort approach sidesteps).
  • v1.1 — tiered sizing across four consistency×style tiers (tagWeights).
  • v1.0 — patient-whale conviction copier (ELITE+PATIENT, conviction gate, wide-DSL ride).