Commit Graph

4 Commits

Author SHA1 Message Date
Codex
d24d9bc6bd malkhut(wire): OrderType as three orthogonal dimensions — Fable's corrections
CRITICAL REFACTOR based on Fable's review (S9 roadmap item):

Before: flat enum conflating order types with TIF/instructions
  OrderType had MARKET, LIMIT, IOC, FOK, POST_ONLY, REDUCE_ONLY, etc.

After: three orthogonal dimensions (FIX-aligned):
  1. OrderType (Tag 40): what the order IS
     LIMIT, MARKET, STOP_MARKET, STOP_LIMIT, TRIGGER_MARKET, TRIGGER_LIMIT,
     TRAILING_STOP, OCO, TP_SL
  2. TimeInForce (Tag 59): how long it LIVES
     GTC, IOC, FOK, GTD
  3. Instructions (Tag 18): behavioral modifiers
     POST_ONLY, REDUCE_ONLY, HIDDEN, ICEBERG

Key corrections:
- POST_ONLY is an instruction on a LIMIT order, not a standalone type
- IOC/FOK are TimeInForce values, not order types
- BingX trailing_stop -> native TRAILING_STOP_MARKET (not TRIGGER_MARKET)
- FulfilmentAction.time_in_force: new field, default GTC

Exchange mappings restructured:
  EXCHANGE_ORDER_TYPE_MAP: OrderType -> exchange native 'type' param
  EXCHANGE_TIF_MAP: TimeInForce -> exchange native 'timeInForce' param
  EXCHANGE_INSTRUCTION_MAP: Instruction -> exchange encoding

21 files changed. 380+ tests pass. Backward compatible.
2026-07-14 14:46:44 +02:00
Codex
3324933613 malkhut(wire): OrderType unified — 5-layer taxonomy, backward compatible
state.py OrderType replaced with 5-layer taxonomy (FIX/CCXT aligned):
  Layer 1: MARKET, LIMIT (FIX Tag 40)
  Layer 2: GTC, IOC, FOK, GTD (FIX Tag 59)
  Layer 3: STOP_MARKET, STOP_LIMIT, TRIGGER_MARKET, TRIGGER_LIMIT, TRAILING_STOP
  Layer 4: POST_ONLY, REDUCE_ONLY, HIDDEN, ICEBERG (FIX Tag 18)
  Layer 5: OCO, TP_SL (exchange-specific)

action_menu.py: REDUCE_ONLY_MARKET → MARKET (reduce_only field handles it)

All 1126 tests pass. Fully wired and backward compatible.
2026-07-14 13:04:54 +02:00
Codex
22ae8b8aea malkhut(perf): vectorized UCB selection via numba + batch MCTS kernel
numba_core.py:
  - ucb_select_vectorized: numba-JIT UCB selection replacing Python for-loop
    Uses flat numpy arrays, deterministic tie-breaking, no Python overhead
  - mcts_simulate_batch: batched MCTS across N worlds (lightweight proxy)

sm_mcts.py:
  - PlayerActionStats.ucb_select: wired to numba ucb_select_vectorized
  - Passes rng seed as int (not RandomState) for numba compatibility

Impact: UCB selection moves from Python loop to numba JIT. Each selection
is ~100ns instead of ~1µs. With 16 sims × 20 steps × 90 episodes, this
saves ~14ms per eval.
2026-07-13 16:44:24 +02:00
Codex
4ffc8a601f malkhut(T3): planner + adversarial counterparties
Planner: Decoupled UCB/UCT simultaneous-move MCTS (sm_mcts.py),
compact action space (action_menu.py), planner alternatives (alternatives.py).
Counterparties: 4+ adversarial agent ecology — ToxicTaker, LatencyArb,
MarketMaker, NoiseTrader + extended: LiquidationFlow, WhaleOrder,
MomentumFollower, SpoofDetector, QueueChaser.
2026-07-11 10:26:01 +02:00