feat: Phase 3 — event-driven market-making simulator + 53 tests

New sim/ module — 7 files + init, replays stored L2/trade data
through a realistic market-making simulation:

sim/engine.py (SimulationEngine):
  Event-driven core — processes L2 updates, trades, mark prices
  sequentially. Orchestrates queue model, maker quotes, fill sim,
  constraints, scenarios. Supports periodic re-quoting and
  stale order cancellation.

sim/queue.py (QueueModel):
  Price-time FIFO queue per price level. Tracks where maker orders
  sit in queue. Simulates order eating by aggressor trades.
  fill_probability() — Poisson thinning model for fill odds.

sim/maker.py:
  AvellanedaStoikovMaker — stochastic control quoting with
    aeta, k, tau parameters. Reservation price based on inventory.
    quote() and quote_with_skew() with configurable inventory tilt.
  GridMaker — evenly-spaced grid quoting at N levels.

sim/fills.py:
  FillSimulator — partial fills, adverse selection probability,
    cancel latency (gaussian RTT). FillEvent/CancelEvent tracking.
  adverse_selection_intensity() — measures post-fill price moves.

sim/constraints.py:
  InventoryConstraint — long/short/net/gross position limits.
  FundingConstraint — hourly funding cost estimation.
  FeeSchedule — maker/taker fee calculation.
  LiquidationRisk — liquidation price and safety distance.
  CircuitBreaker — PnL, trade count, toxic rate, slippage trips.
  ConstraintManager — unified pre-trade constraint check.

sim/scenario.py:
  ScenarioEngine — randomized exchange downtimes, latency spikes,
    volatility bursts. State query per sim_time for spread/trade-rate.

sim/reporter.py:
  PnLReporter — component-level PnL breakdown:
    spread_capture, inventory_pnl, fees, funding, adverse_selection.
  SimulationStats — trade counts, fill rates, drawdown, sharpe.
  Equity curve tracking and max drawdown computation.

53 new tests across 4 files (all pass):
  test_sim_queue.py (12) — order placement, FIFO, fills, cancels
  test_sim_maker.py (9) — A-S quotes, inventory skew, grid maker
  test_sim_constraints.py (14) — limits, funding, fees, liquidation, breakers
  test_sim_reporter.py (12) — PnL components, equity curve, stats
  test_sim_engine.py (6) — full engine integration

Total test suite: 134 tests, all passing.

tests/test_sim_queue.py

@@ -0,0 +1,95 @@
+"""
+Tests for sim/queue.py — queue position model.
+"""
+from sim.queue import QueueModel, QueuePosition, fill_probability
+
+
+class TestQueueModel:
+    def test_place_bid(self):
+        qm = QueueModel()
+        oid = qm.place_order("bid", 50000.0, 0.01, sim_time=100.0)
+        tob = qm.top_of_book()
+        assert tob["best_bid"] == 50000.0
+        assert tob["best_ask"] == 0  # no asks placed
+
+    def test_queue_position_is_front(self):
+        qm = QueueModel()
+        oid = qm.place_order("ask", 50002.0, 0.01, sim_time=100.0)
+        qp = qm.queue_position("ask", 50002.0, oid)
+        assert qp is not None
+        assert qp.position == 0
+        assert qp.is_front
+
+    def test_queue_position_behind_others(self):
+        qm = QueueModel()
+        qm.place_order("bid", 50000.0, 0.01, sim_time=99.0)
+        oid2 = qm.place_order("bid", 50000.0, 0.01, sim_time=100.0)
+        qp = qm.queue_position("bid", 50000.0, oid2)
+        assert qp is not None
+        assert qp.position == 1  # behind first order
+
+    def test_cancel_order(self):
+        qm = QueueModel()
+        oid = qm.place_order("bid", 50000.0, 0.01, sim_time=100.0)
+        filled = qm.cancel_order(oid, sim_time=105.0)
+        assert filled == 0.0
+        assert qm.order_status(oid)["status"] == "cancelled"
+        assert len(qm.active_orders()) == 0
+
+    def test_trade_eats_ask(self):
+        qm = QueueModel()
+        oid = qm.place_order("ask", 50002.0, 0.01, sim_time=100.0)
+        fills = qm.process_trade("buy", 50002.0, 0.01, sim_time=101.0)
+        assert len(fills) == 1
+        assert fills[0]["size"] == 0.01
+
+    def test_trade_eats_bid(self):
+        qm = QueueModel()
+        oid = qm.place_order("bid", 50000.0, 0.02, sim_time=100.0)
+        fills = qm.process_trade("sell", 50000.0, 0.01, sim_time=101.0)
+        assert fills[0]["size"] == 0.01
+        assert qm.order_status(oid)["filled"] == 0.01
+
+    def test_partial_fill_remaining(self):
+        qm = QueueModel()
+        oid = qm.place_order("bid", 50000.0, 0.03, sim_time=100.0)
+        qm.process_trade("sell", 50000.0, 0.01, sim_time=101.0)
+        status = qm.order_status(oid)
+        assert status["filled"] == 0.01
+        assert status["status"] == "active"
+
+    def test_fully_filled_status(self):
+        qm = QueueModel()
+        oid = qm.place_order("bid", 50000.0, 0.01, sim_time=100.0)
+        qm.process_trade("sell", 50000.0, 0.01, sim_time=101.0)
+        assert qm.order_status(oid)["status"] == "filled"
+
+    def test_trade_crosses_spread(self):
+        qm = QueueModel()
+        qm.place_order("ask", 50002.0, 0.01, sim_time=100.0)
+        qm.place_order("ask", 50003.0, 0.01, sim_time=100.0)
+        fills = qm.process_trade("buy", 50003.0, 0.02, sim_time=101.0)
+        assert len(fills) == 2
+
+    def test_top_of_book(self):
+        qm = QueueModel()
+        qm.place_order("bid", 50000.0, 0.01, sim_time=100.0)
+        qm.place_order("ask", 50002.0, 0.02, sim_time=100.0)
+        tob = qm.top_of_book()
+        assert tob["best_bid"] == 50000.0
+        assert tob["best_ask"] == 50002.0
+        assert tob["spread"] == 2.0
+
+
+class TestFillProbability:
+    def test_front_of_queue(self):
+        result = fill_probability(queue_pos=0, total_queue_depth=1.0, order_size=0.01, arrival_rate=1.0, time_horizon=1.0)
+        assert result["fill_probability"] > 0.5
+
+    def test_deep_in_queue(self):
+        result = fill_probability(queue_pos=5, total_queue_depth=10.0, order_size=0.01, arrival_rate=1.0, time_horizon=1.0)
+        assert result["fill_probability"] < 0.5
+
+    def test_no_arrivals_zero_prob(self):
+        result = fill_probability(queue_pos=0, total_queue_depth=1.0, order_size=0.01, arrival_rate=0.0, time_horizon=1.0)
+        assert result["fill_probability"] == 0.0