7994d4d1b7
Documents the SP5 implementation (110 ISV slots, 8 layer-A producer kernels, 1 atomic Layer B consumer migration). Closes plan task #295 partial — the 8th pearl (pearl_sp5_close_out) and full close-out commit are DEFERRED until the 50-epoch 3-seed × 3-fold L40S validation (#289) completes. 7 new memory pearls landed: pearl_per_branch_c51_atom_span — Pearl 1 pearl_per_branch_loss_budget — Pearl 2 pearl_per_branch_noisy_sigma — Pearl 3 pearl_per_group_adam_hyperparams — Pearl 4 pearl_per_branch_iqn_tau_schedule — Pearl 5 pearl_kelly_cap_signal_driven_floors — Pearl 6 (cross-fold-persistent) pearl_trail_stop_signal_driven — Pearl 8 Audit doc append covers Pearl 6's cross-fold carve-out, Pearl 4's ε-only fall-back path, and the smoke-test-ks2wf @5845e4403validation metrics (sharpe 4.5→9.77, label_scale 19-28, trade_count 6468-9432). Refs: SP5 spec at6e6e0fa11
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.