jgrusewski 1fb2decb79 feat(ml-backtesting): resting orders + stops + OCO + audit ring (C11)
Picks up the deferred work from C5/C7 trim notes. Adds:

  cuda/lob_state.cuh — LimitSlot (32 B) + StopSlot (32 B) + Orders
    (limits[32] + stops[16] = 1536 B/backtest). u64-aligned with
    explicit _pad[6] on both slot structs so the Rust mirrors
    (LimitSlotFlat / StopSlotFlat) bytemuck::Pod-derive without
    panics about implicit padding.

  cuda/resting_orders.cu — three kernels:
    resting_orders_step (runs per event after book_update):
      1. In-flight → resting promotion at arrival_ts_ns. Queue position
         initialised pessimistically (full level depth ahead) per spec §9.
      2. Queue decay against same-side trade_signed_vol at level: ahead-
         of-us first then us; partial-fill emits OrderEvent + pos update.
      3. Marketability check: book moved through our price → cross at
         the just-arrived book (slippage-aware fill walks levels).
         IOC cancels remainder; FOK does too (partial-fill not allowed).
      4. Stop trigger detection: best ask up for buy-stop, best bid
         down for sell-stop. StopMarket walks book; StopLimit converts
         to a new LimitSlot (overflow → submission_overflow++).
      5. OCO mutual exclusion: oco_pair byte (0..31 = limit, 32..47 =
         stop) — when one leg fills/triggers, the paired slot is freed.
    seed_limit_slot / seed_stop_slot — host-side single-slot seeders
    for fixture testing + as a v1 entry point until the decision
    kernel learns to emit resting orders. Both set an overflow_flag
    if the target slot is already in use (gen_counter bumped on
    successful seed for SlotTag freshness).

  src/sim.rs — wires three new methods:
    seed_limit_order(b, slot, side, kind, active_state, oco_pair,
                     price, size, queue_position_init, arrival_ts_ns)
    seed_stop_order(b, slot, side, kind, active_state, oco_pair,
                    trigger_price, limit_price, size, arrival_ts_ns)
    step_resting_orders(current_ts_ns, trade_signed_vol)
      → launches resting_orders_step kernel + chains step_pnl_track
        so any fill that closes a position emits a TradeRecord.
    Plus read_limit_slot / read_stop_slot / read_audit_records for
    fixture inspection.

  Audit-ring buffers (deferred from C2 originally) now allocated:
    audit_d (n × 256 × 24 B) + audit_head_d (n × u32). Both
    resting_orders.cu and the decision kernel's WriteOrder path
    populate it via the inlined pack_slot_tag + emit_audit helpers.

  Four new GPU fixtures:
    limit_rest_marketable_fill — resting buy at 5500 with book at
      ask 5500 fills immediately on step_resting (3 lots, vwap=5500).
    stop_trigger — buy 4 lots @ 5500, seed sell-stop at trigger=5495,
      book moves so bid=5494.50: stop triggers, walks book, position
      closes flat, TradeRecord emitted, stop slot active=0.
    oco_one_cancels_other — pair {buy@5495, sell@5505} with oco_pair
      cross-linked: book moves so bid=5505.50, sell leg fills (pos=-2),
      buy leg auto-cancelled. Both slots end active=0.
    submission_overflow — host loop fills all 32 limit slots, then 33rd
      seed_limit_order call must return Err (slot 0 already in use).

All 10 GPU fixtures green on RTX 3050 (6 original + 4 new). Ring 2
fuzz at N ∈ {1, 16, 256} still green. 33 lib unit tests still green.

The decision kernel (C7) and submit_market_immediate (C5) paths
are unchanged — they continue to use the "immediate fill" route.
A follow-up commit can teach the decision kernel to emit resting
limits via submit_limit_alloc (already defined in resting_orders.cu).

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-18 09:15:24 +02:00

Foxhunt

Production HFT trading system in Rust.

Architecture

The workspace contains 32 crates organized as follows:

Core Libraries (16)

Crate Purpose
trading_engine Order processing, FIX 4.4, IB TWS, SIMD, RDTSC timing
risk VaR, Kelly, circuit breakers, kill switches, compliance
risk-data Risk data types and shared structures
trading-data Trading data types
ml DQN Rainbow, PPO, TFT, Mamba2, ensemble inference
ml-data ML data types and feature definitions
data Market data ingestion and storage
backtesting Replay engine, strategy tester
adaptive-strategy Ensemble execution, microstructure analysis
common Shared types, resilience, error handling
storage S3 and local model storage
model_loader Model serialization and loading
market-data Market data feed handlers
database PostgreSQL access layer (SQLx)
config Configuration management
tli CLI commands and tooling

Services (8)

Service Purpose
backtesting_service gRPC backtesting service
broker_gateway_service FIX routing, broker connectivity
trading_service Core trading operations
ml_training_service Model training orchestration
data_acquisition_service Market data acquisition
trading_agent_service Autonomous trading agents
api_gateway gRPC API gateway with auth
web-gateway Axum REST + WebSocket gateway

Frontend

web-dashboard/ -- React 19 + TypeScript + Vite + TradingView charts.

Building

# Check compilation (no PostgreSQL required)
SQLX_OFFLINE=true cargo check --workspace

# Run tests for a specific crate
SQLX_OFFLINE=true cargo test -p <crate> --lib

# Clippy
SQLX_OFFLINE=true cargo clippy --workspace

ML Models

Four production model architectures on Candle v0.9.1 with CUDA:

  • DQN Rainbow -- Deep Q-Network with prioritized replay, dueling heads, noisy nets
  • PPO -- Proximal Policy Optimization with GAE and LSTM policies
  • TFT -- Temporal Fusion Transformer for multi-horizon forecasting
  • Mamba2 -- State space model for sequence prediction

Each model has a standalone trainer and a UnifiedTrainable adapter for the hyperopt pipeline.

Infrastructure

  • Git: Gitea at git.fxhnt.ai (Tailscale-only), Scaleway DEV1-S
  • Observability: OpenTelemetry OTLP (env OTEL_EXPORTER_OTLP_ENDPOINT)
  • Database: PostgreSQL with SQLx offline mode for CI

License

Proprietary. All rights reserved.

Description
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