L1SectorBasketCrossSectionalMomentumLongShort

L1 Sector Basket Cross-Sectional Momentum Long-Short (Weekly)

A DOLLAR-NEUTRAL CROSS-SECTIONAL MOMENTUM strategy on a basket of 5 major Layer-1 perpetual futures (BTC, ETH, SOL, BNB, ADA — all with 5+ years of Binance USD-M data). On each weekly close, rank the 5 instruments by their trailing 4-week return. LONG the top-2 performers and SHORT the bottom-2 performers, equal-weighted on each side, dollar-neutral. The middle-ranked instrument is excluded. Rebalance weekly. RATIONALE driven by the now-DECISIVE session finding: after 17+ strategy attempts spanning 6+ supp-data hypotheses, 11+ alt-perp trend-followers, AND 1 cross-asset pair (ETH/BTC OOS Sharpe -4.86), THREE entire mechanism classes have been falsified in the current crypto regime. The analyst's only remaining genuinely-untested categories are: (1) sub-daily intraday, (2) cross-venue arbitrage, (3) SECTOR-BASKET strategies, (4) wait 3-6 months. This proposal targets the SECTOR-BASKET category — a structurally different mechanism class than any prior attempt this session. CROSS-SECTIONAL MOMENTUM IS THE MOST ACADEMICALLY DOCUMENTED MOMENTUM ANOMALY: Jegadeesh-Titman (1993), Carhart (1997), Asness-Moskowitz-Pedersen (2013) — it persists across equity, FX, commodity, and bond markets over many decades. Crucially, it differs from TIME-SERIES momentum (which is what failed across all 11 alt-perp trend-followers this session): cross-sectional momentum captures the persistence of RELATIVE STRENGTH between assets in a peer group, not the persistence of an asset's own price direction. This means it can work in any market regime (bull, bear, or chop) as long as some assets are outperforming others — which is always true. DESIGN ELEMENTS that ELIMINATE every session failure mode: (a) Dollar-neutral by construction (no beta-to-crypto), (b) RELATIVE-strength NOT direction-following (no time-series trend dependency), (c) ZERO supplementary data, (d) 5-instrument basket (not single-pair, immune to ETH/BTC-style cointegration drift), (e) WEEKLY rebalancing (low trade frequency, ~52 rebalances/year per side × 4 legs = ~200 trades/year — fee-friendly), (f) MAXIMALLY SIMPLE — only 2 parameters (ranking lookback weeks, basket top/bottom k). DIFFERENTIATION FROM PIPELINE: 4 pair strategies (each 2-asset) covered; this is a 4-leg basket with cross-sectional ranking — fundamentally different math.

Implements the SECTOR-BASKET cross-sectional momentum hypothesis (Jegadeesh-Titman 1993 relative strength), a distinct mechanism class from time-series trend-following: it ranks assets by RELATIVE performance within the peer group rather than following any single asset's own direction, and is dollar-neutral by construction (no crypto-beta). Design maps directly to the brief: (a) 5-instrument liquid L1 basket with 5+ years of Binance USD-M data; (b) weekly rebalance = low trade frequency (~4 legs x ~52 = ~200 trades/yr, fee-friendly); (c) zero supplementary data, pure OHLCV weekly closes; (d) simple 4-week ranking lookback and top/bottom-k=2. The multi-leg long/short book cannot be expressed through the base template's single-primary should_enter/should_exit, so those hooks are neutralized and all trading runs through a converge-to-target reconcile: each instrument gets a signed target notional (long +12% / short -12% / 0 for the excluded mid) and a single delta market order moves its net position to that target, guarded against stacking by a working-orders check. This reuses an accounting pattern hardened against a prior over-sizing artifact (fill-lag stacking that inflated gross ~8x). Verified locally: Layer 1 static passes with zero issues, Layer 2 passes all 6 synthetic scenarios with a real bar-varying signal, and a direct unit test confirms the ranking selects the correct winners/losers, each leg sizes to exactly 12% ($12k on $100k equity), total gross is capped at $48k (48%), the book is dollar-neutral (2 long / 2 short), and repeated reconciles are idempotent (no accumulation).

Pre-optimization review: the netting implementation is clean this time (avg_position_pct 14.1% ≈ the 12% per-leg design, max_drawdown 32.6%, benchmark_meaningful=false correctly set), so this is not an artifact-dominated blowup — but the strategy has no current edge. The decisive, non-artifact fact is that this dollar-neutral factor is NEGATIVE in four consecutive years (2022 -8.1%, 2023 -7.7%, 2024 -8.8%, 2025 -6.7%); the entire +33% total return comes from 2021 (+38.8%), the old regime. The headline is a near-zero Sharpe (0.153), profit_factor 1.026, and NEGATIVE information ratio (-0.72), with returns carried by a handful of outlier weeks (return_kurtosis 124). A dollar-neutral relative-strength factor is supposed to be regime-independent, so four straight negative years is edge decay/absence, not a tuning problem. Optimization tunes only two parameters (lookback_weeks, n_side); a different formation window will not flip four consecutive negative years positive — it will re-fit the 2021 regime and, consistent with every cross-sectional sibling this session, fail the post-optimization deflated-Sharpe/holdout gates. Spending 2 hours optimizing is not warranted. (Secondary note for the record: the kurtosis-124 weekly outliers — e.g. +25.4% on 2024-01-15, implying a ~100% winner-vs-loser basket spread in one week — warrant a quick netting-artifact check, but the abandon verdict does not depend on them; even at face value the strategy loses in every recent year.)

Dollar-neutral weekly cross-sectional momentum on a 5-instrument L1 basket (BTC/ETH/SOL/BNB/ADA, Binance USD-M perps, 1-week bars). Each week ranks the 5 by trailing 4-week return, goes long the top-2 relative-strength winners and short the bottom-2 losers (equal 12% notional per leg, ~48% gross, dollar-neutral), excludes the middle. Pure OHLCV, leverage 1.0. Trading is done by a NETTING-safe converge-to-target reconcile that submits one delta order per instrument toward its signed 12% target, with a working-order guard so gross never exceeds ~48%.

Netting fix works: avg_position_pct 14.1% (≈12% per-leg design), max_drawdown 32.6% — sane for a dollar-neutral book, no gross-overlap blowup

Clean, well-grounded mechanism (Jegadeesh-Titman cross-sectional momentum), OHLCV-only, market-neutral (benchmark_meaningful=false, beta 0.02), 343 trades

Genuinely distinct mechanism class (sector-basket relative strength) vs the session's prior single-asset/pair attempts

No current edge: NEGATIVE in four consecutive years (2022 -8.1%, 2023 -7.7%, 2024 -8.8%, 2025 -6.7%); entire +33% total return comes from 2021 (+38.8%) alone

Near-zero risk-adjusted return carried by outliers: Sharpe 0.153, profit_factor 1.026, information_ratio -0.72, return_kurtosis 124 (a few big weeks dominate)

Rolling Sharpe negative across 2022-2025 — the relative-strength signal reversed/chopped among these majors post-2021

Only 2 tunable parameters; a different lookback will re-fit the 2021 regime, not reverse four negative years — consistent with this session's cross-sectional siblings failing post-optimization deflation

Secondary: kurtosis 124 weekly outliers (e.g. +25.4% on 2024-01-15) may include residual netting artifacts inflating an already-losing result

Pitched as a structurally novel sector-basket mechanism after prior single-asset and pair attempts failed, this weekly cross-sectional momentum book ranked five L1 perps and traded winners-long/losers-short, dollar-neutral. The implementation was correct this time — sane sizing, 32.6% drawdown, market-neutral beta of 0.02 — but the results exposed no current edge: a 0.153 Sharpe, 1.026 profit factor, negative information ratio, and a +33% total return sourced almost entirely from 2021 while every year from 2022 through 2025 lost money. The analyst read four consecutive negative years as regime decay in a factor that should be regime-independent, and with only a lookback and basket-size to tune, abandoned it at pre-optimization review rather than re-fitting the dead 2021 regime. Optimization, post-optimization analysis, and risk review were never reached.

A dollar-neutral relative-strength factor that is supposed to be regime-independent but loses in every recent year has no live edge; concentration of all profit in a single early year plus extreme kurtosis signals outlier-carried decay that parameter tuning cannot reverse.

The analyst abandoned it at the pre-optimization review, judging the four straight negative years to be edge decay/absence rather than a tuning problem — with only two tunable parameters, re-optimizing would merely re-fit the 2021 regime, so no later stages were reached.

A dollar-neutral weekly cross-sectional momentum strategy on a 5-instrument L1 perp basket (BTC, ETH, SOL, BNB, ADA) that ranked each by trailing 4-week return and went long the top-2, short the bottom-2, equal-weighted, to capture relative-strength persistence rather than time-series trend.

Over 343 trades since 2019 the netting implementation was clean (avg position 14.1%, max drawdown 32.6%, beta 0.02) but the edge was near-zero: Sharpe 0.153, profit factor 1.026, information ratio -0.72, with the entire +33% total return coming from 2021 (+38.8%) and negative returns in four consecutive years (2022 -8.1%, 2023 -7.7%, 2024 -8.8%, 2025 -6.7%); return kurtosis was 124.