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6 new modules with 46 new tests (230 total): #21 HLP Vault Monitor (live/monitors/hlp_vault.py): Tracks Hyperliquid's native protocol market maker at address 0xfefefe... Queries clearinghouseState + metaAndAssetCtxs. - Delta exposure per asset (notional + PnL) - Overextension detection (notional exceeds M threshold) - Rebalancing signals: fade_short when HLP too short, fade_long when HLP too long (front-run forced rebalancing) - Toxicity score: HLP losing money = absorbing informed flow - Historical delta tracking #29 Hawkes Processes (microstructure/hawkes.py): Multivariate Hawkes calibrator for limit order book dynamics. - MLE calibration via SGD gradient descent on log-likelihood - Branching ratio enforcement (alpha/beta < 0.99 for stationarity) - Intensity computation λ_i(t) with cross-excitation - Activity forecasting (expected event count in horizon) - Synthetic event generator (Ogata thinning) - Pure functions: hawkes_intensity, hawkes_log_likelihood, generate_hawkes_events #23 Funding Whipsaw Trader (live/strategies/funding_whipsaw.py): Premium index decay trading in final 60s of funding epoch. - Detects deterministic convergence of premium→0 at settlement - Time-scaled position sizing (larger closer to settlement) - Auto-close after funding epoch completes - Confidence scoring based on premium magnitude #32 Term Structure Monitor (live/monitors/term_structure.py): Perp/quarterly/bi-quarterly futures basis curve trading. - Quarterly-perp basis with z-score anomaly detection - BiQ-quarterly curve steepness monitoring - Fair quarterly price via interest rate parity + funding carry - Calendar spread signals: buy_basis, sell_basis, curve_steepener, curve_flattener #24 Liquidation Waterfall (live/monitors/liq_waterfall.py): Cross-margin liquidation order prediction. - Margin ratio tracking (equity / maintenance margin) - Danger/critical level classification - Asset liquidation priority: maintenance / book_liquidity ratio (least liquid asset relative to margin = dumped first) - Strategy output: widen_spreads on target, tighten on rest #31 Spoof Detector (microstructure/spoof_detector.py): Adversarial ML-style spoofing pattern recognition. - Rule 1: Large order far from mid, cancelled immediately - Rule 2: Cancel right before trade approaches price level - Rule 3: Oversized order with no fill within short lifetime - Spoof probability (rolling window ratio) - Cancel-to-fill ratio monitoring