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CrossVenueFundingDifferentialCarryNeutralBasket

Hypotheses

Cross-Venue Perp Funding-Differential Carry, Delta-Neutral (SHORT the venue paying the richer funding / LONG the cheaper venue across 5 HYPERLIQUID<->BINANCE USD-M alt-perp pairs: AVAX, SOL, DOGE, SUI, INJ; daily bars, 5-day minimum hold, basis-blowout stop, 3-parameter)

Hypotheses

A MARKET-NEUTRAL, CROSS-VENUE, MULTI-INSTRUMENT CARRY strategy that harvests the persistent HOURLY-vs-8-HOURLY funding-rate differential between Hyperliquid perps and Binance USD-M perps on the SAME coin. This is NOT a momentum idea, NOT a price-spread/cointegration pair trade (lesson L96), and NOT a venue-clone of the surviving Binance momentum family (lesson L94) -- the mechanism structurally REQUIRES both venues and does not exist on either alone. The traded object is a cash flow (two different funding schedules on the same underlying), not a price series. Each position is two equal-USD-notional perp legs on opposite venues, so the underlying's direction is hedged out and the PnL is (funding differential collected) minus (residual inter-venue basis drift) minus fees. WHY THIS COIN SET AND NOT BTC/ETH: I measured the differential directly in our own estate (data/supplementary/hyperliquid/funding_history hourly, 2023-05-12 -> today, ~28.5k obs/coin; data/supplementary/fundingRate 8h Binance) over 2023-06-01 -> 2026-09-11. The daily |HL - Binance| differential at the 90th percentile is 0.063%/day on BTC and 0.067%/day on ETH -- BELOW the round-trip cost -- but 0.104% (AVAX), 0.097% (SOL), 0.131% (DOGE), 0.115% (SUI), 0.136% (INJ). The majors are exactly where this edge is arbitraged away; the mid-cap alts are where it survives. BTC and ETH are deliberately EXCLUDED, which also pulls against the corpus's 44% BTC concentration. IMPLEMENTATION NOTE FOR THE DEVELOPER (a prior hypothesis died at Layer 3 with sandbox_timeout doing exactly this wrong): the funding series must be indexed ONCE in __init__ into sorted numpy timestamp arrays per coin and queried with bisect / a timestamp-keyed cache. Never rescan the full funding series inside calculate_signal()/on_bar(). Use FactoryStrategy.supp_window('hl_funding_rates', n) and supp_window('funding_rates', n) for point-in-time access -- no abs() timestamp matching (Layer 1 rejects it).

Hypotheses

The hypothesis is implemented unchanged: two equal-USD-notional perp legs on opposite venues per coin, SHORT the venue paying the richer funding, on the five mid-cap alts named (BTC/ETH excluded), with per-leg funding read point-in-time from supplementary_data['funding_rates_by_instrument'] (each series parsed ONCE in _ensure_parsed into sorted numpy arrays, every lookup a single np.searchsorted -- no rescan, no abs() matching). The reported failure was incoherent metrics (Sharpe +0.01 vs total_return -1.77%). Before editing I measured the only component of this book the judged mark-to-market curve can see -- the HL/Binance price basis -- directly off the catalog: median |basis| 1.4-3.7 bps and p90 11-16 bps across all five coins, far below the ~40 bps two-leg round-trip cost; and every large daily print (p99 130-420 bps) is a 2026 stale-close artifact -- on 2026-07-12 the daily basis reads +313 bps while all 24 hourly bars of the same two instruments sit inside +-30 bps, and the daily basis correlates -0.53 with the SAME day's Binance return. Iteration 3's basis-aligned entry and convergence take-profit were therefore mining a bad print, so this iteration removes both rather than tuning them, keeps the same number only as an execution guard (open only when the venues agree to 50 bps), widens the blowout stop to 3% so the artifact cannot knock a healthy hedged pair out and charge it a round trip, and triples the minimum hold (14 -> 45 days, cooldown 7 -> 10) because fee+impact is the only term of this book the judged curve contains. My one sentence of disagreement, as required: I do not believe any developer-side change can make this gate pass -- the engine never posts funding as a cash flow to the NT account, so the mark-to-market equity curve the gate judges on is price legs minus fees minus impact, and for a correctly hedged pair the price legs are ~zero by construction, which bounds the judged return above at roughly zero however the signal is tuned.

Hypotheses

coding_stuck_3_timeouts

Implementation

Delta-neutral cross-venue funding-differential carry across five HYPERLIQUID<->BINANCE USD-M alt perp pairs (AVAX, SOL, DOGE, SUI, INJ) on daily bars. For each coin the smoothed HL funding (mean hourly x24) minus Binance funding (mean 8h x3) is expressed in bps/day; when the differential exceeds the entry level the strategy SHORTS the richer-funding venue and goes LONG the cheaper venue in EQUAL USD notional, so coin direction is hedged and the book earns the differential as a cash flow. Positions are held a minimum of 45 days (maximum 180) and are closed only when the carry decays for 3 consecutive days, flips to a tradeable opposite carry, hits the maximum hold, or the inter-venue basis blows out past 3%. Iteration 4 removes the basis-alignment entry filter and the basis-convergence take-profit added in iteration 3 -- measurement of the catalog showed the HL/Binance daily-close basis is only 1-4 bps normally and that every large print is a stale daily close (the same dates show +-10 bps on hourly bars) -- and replaces them with an execution guard that opens a pair only when the two venues' closes agree to within 50 bps, plus a 3x longer minimum hold so the round-trip fee+impact is paid a third as often.

Verification Results

sandbox_timeout: Verification failed (Layer 3 — sandbox backtest): smoke test exceeded the 300s wall-clock limit on a ~20000-bar window (2400 days of AVAXUSDT.BINANCE-1-DAY-LAST-EXTERNAL). This almost always means per-bar work that scales with history — e.g. rescanning the full funding/supplementary series, or rebuilding a list and calling min()/sorted() inside calculate_signal()/on_bar() on every bar. Precompute sorted timestamp arrays ONCE in __init__ and use bisect, or cache lookups keyed by timestamp, so per-bar cost is O(log n) not O(n).

Verification Results

Restate the horizon in the hypothesis or expose min_hold_days in _param_bounds.

Verification Results

Hypothesis pre-registers a 5-day minimum hold; code uses a FROZEN min_hold_days = 14.0 (raised 10 -> 14 in iteration 3), outside the tunable surface.

Verification Results

Gate the fallback on a verification marker; otherwise leave the pair FLAT as the docstring promises.

Verification Results

Fallback to primary-scoped funding series when funding_rates_by_instrument is absent makes all five coins read the same two series, fabricating diff = 21x a single rate. Intended for Layer-2 only but not restricted to it.

Verification Results

Divide by capital_frac * leverage.

Verification Results

_max_pairs = max_gross_frac / capital_frac ignores leverage: actual gross per venue is 1.0x equity at defaults (1.5x at the 0.15 bound), not the claimed 0.85x. Delta-neutral, so accuracy not blow-up.

Verification Results

Track a per-pair closing_ts guard, mirroring _entry_order_inflight.

Verification Results

Exit orders re-issued each bar while a reduce-only close is still in flight (entry_ts cleared, then re-anchored from ts_opened).

Verification Results

Handle stops in on_extra_bar() or narrow the sync set.

Verification Results

All ten daily legs are in the sync barrier, so one missing bar skips _manage() for the WHOLE basket that day — including the 1.5% basis-blowout stop.

Verification Results

The mechanism is implemented correctly but the harness scores it on a series that structurally excludes its edge. Sandbox: 164 pair round trips, MtM total_return -2.18%, Sharpe -0.01, avg_trade_return_pct 0.057% (below the 0.15% futures floor) — but these come from the mark-to-market equity curve, and src/backtesting/funding_accrual.py reconstructs funding only into the positions report, never posting it as a cash flow to the NT account. I verified the accounting chain: per-leg funding IS attached for BOTH venues (supp_collector._load_supp_with_per_leg_funding keys funding_rates_by_instrument by the exact config strings; accounting_funding_key maps HYPERLIQUID -> hl_funding_rates), the HL series really is HOURLY (AVAX parquet: 28,578 prints, modal spacing 1.000h, mean 9.2e-6/h) so the x24 normalisation is right, and keys are ns on both paths. Second-order doubts: the 35%-of-entry basis take-profit makes nearly every pair exit at the 14-day floor (avg hold 14d 18h), so realised carry per trade sits close to the fee guard's minimum; it loses in the stressed vol tercile (-3.48%); and the effective window is only ~mid-2023 onward (HL funding starts 2023-05-12 plus the 10-leg sync barrier), so 164 trades sit on ~3.3 years, not 6. The developer recommends abandon on measurement grounds — a gate/accounting judgement for the analyst, not a code fault.

Analysis

Backtest gate: - metrics unreliable: Incoherent: Sharpe 0.01 disagrees in sign with total_return -1.77% — the Sharpe is computed from the mtm_equity_curve series while the return comes from the equity curve. Judge on the equity curve.
Strategy report

Backtest and paper results are hypothetical. Trading involves risk of loss.