feat: HFT infrastructure — tick backtest runner, VPIN-gated A-S maker, WQI predictor, queue-aware fills

- backtests/tick_runner.py: TickBacktestRunner replays stored Parquet L2/trade events
  through sim/engine.py with queue position modeling, producing PnL breakdowns,
  equity curves, VPIN curves, and QuantVerdict significance reports
- VPINGatedASMaker: VPIN-toxicity-gated A-S market maker with inventory skew
  and dynamic spread widening; blocks quoting when VPIN >= alarm threshold
- sim/engine.py: Added SimConfig.from_fee_tier() factory — constructs sim
  config from Hyperliquid fee tier (VIP + staking)
- sim/fills.py: Added QueueAwareFillModel — realistic queue-priority fill
  simulation replacing random fills in paper trading
- strategies/wqi_predictor.py: WQI z-score directional strategy with
  adverse selection gating, timeout exit, stop-loss, and take-profit
- cli.py: Added 'tick', 'markout' analysis, and 'discover' signal-discovery
  commands for end-to-end tick-level HFT research pipeline

301 tests passing (23 new).

sim/engine.py

@@ -60,10 +60,31 @@ class SimConfig:
     scenario: ScenarioConfig = field(default_factory=ScenarioConfig)
 
     # Simulation behavior
-    cancel_after_ms: float = 5000.0     # cancel and re-quote every N ms
-    quote_refresh_ms: float = 2000.0    # refresh quotes every N ms
+    cancel_after_ms: float = 5000.0
+    quote_refresh_ms: float = 2000.0
     seed: int | None = None
 
+    @classmethod
+    def from_fee_tier(
+        cls,
+        vip_tier: int = 0,
+        staking_tier: str = "none",
+        maker_rebate_tier: int = 0,
+        **kwargs,
+    ) -> "SimConfig":
+        from config.fee_tiers import get_perp_fees, PERPS_TIERS, STAKING_TIERS
+
+        maker_fee = get_perp_fees(vip_tier, staking_tier, "maker", maker_rebate_tier)
+        taker_fee = get_perp_fees(vip_tier, staking_tier, "taker", maker_rebate_tier)
+        tier_name = PERPS_TIERS[vip_tier]["name"]
+        staking_name = STAKING_TIERS.get(staking_tier, STAKING_TIERS["none"])["name"]
+
+        return cls(
+            maker_fee_pct=maker_fee,
+            taker_fee_pct=taker_fee,
+            **kwargs,
+        )
+
 
 class SimulationEngine:
     """Event-driven market-making simulator.